Variable-Length Computerized Adaptive Testing: Adaptation of the A-Stratified Strategy in Item Selection with Content Balancing

ERIC Educational Resources Information Center

Huo, Yan

2009-01-01

Variable-length computerized adaptive testing (CAT) can provide examinees with tailored test lengths. With the fixed standard error of measurement ("SEM") termination rule, variable-length CAT can achieve predetermined measurement precision by using relatively shorter tests compared to fixed-length CAT. To explore the application of…

A novel variable selection approach that iteratively optimizes variable space using weighted binary matrix sampling.

PubMed

Deng, Bai-chuan; Yun, Yong-huan; Liang, Yi-zeng; Yi, Lun-zhao

2014-10-07

In this study, a new optimization algorithm called the Variable Iterative Space Shrinkage Approach (VISSA) that is based on the idea of model population analysis (MPA) is proposed for variable selection. Unlike most of the existing optimization methods for variable selection, VISSA statistically evaluates the performance of variable space in each step of optimization. Weighted binary matrix sampling (WBMS) is proposed to generate sub-models that span the variable subspace. Two rules are highlighted during the optimization procedure. First, the variable space shrinks in each step. Second, the new variable space outperforms the previous one. The second rule, which is rarely satisfied in most of the existing methods, is the core of the VISSA strategy. Compared with some promising variable selection methods such as competitive adaptive reweighted sampling (CARS), Monte Carlo uninformative variable elimination (MCUVE) and iteratively retaining informative variables (IRIV), VISSA showed better prediction ability for the calibration of NIR data. In addition, VISSA is user-friendly; only a few insensitive parameters are needed, and the program terminates automatically without any additional conditions. The Matlab codes for implementing VISSA are freely available on the website: https://sourceforge.net/projects/multivariateanalysis/files/VISSA/.

[Dietary intervention programs in the workplace: an effective prevention strategy].

PubMed

Barbato, D Lettieri; Sancini, A; Caciari, T; Rosati, M V; Tomei, G; Tomei, F

2010-01-01

The main purpose of our meta-analysis was to investigate the effect of workplace dietary intervention on several variables. We made a systematic literature search by selecting articles published up to September 2009. Only 18 studies were deemed suitable for inclusion criteria considered in our meta-analysis. Among the dietary variables there was significant difference between the two groups after the administration of nutritional intervention programs. A significant improvement was also observed between the anthropometric and metabolic variables. No significant change was instead documented in relation to functional variables (systolic and diastolic pressure). Workplace dietary intervention, improving nutritional, anthropometrical and metabolic variables, can be identified as effective prevention strategy toward chronic diseases.

Life-history strategies associated with local population variability confer regional stability.

PubMed

Pribil, Stanislav; Houlahan, Jeff E

2003-07-07

A widely held ecological tenet is that, at the local scale, populations of K-selected species (i.e. low fecundity, long lifespan and large body size) will be less variable than populations of r-selected species (i.e. high fecundity, short lifespan and small body size). We examined the relationship between long-term population trends and life-history attributes for 185 bird species in the Czech Republic and found that, at regional spatial scales and over moderate temporal scales (100-120 years), K-selected bird species were more likely to show both large increases and decreases in population size than r-selected species. We conclude that life-history attributes commonly associated with variable populations at the local scale, confer stability at the regional scale.

A review of covariate selection for non-experimental comparative effectiveness research.

PubMed

Sauer, Brian C; Brookhart, M Alan; Roy, Jason; VanderWeele, Tyler

2013-11-01

This paper addresses strategies for selecting variables for adjustment in non-experimental comparative effectiveness research and uses causal graphs to illustrate the causal network that relates treatment to outcome. Variables in the causal network take on multiple structural forms. Adjustment for a common cause pathway between treatment and outcome can remove confounding, whereas adjustment for other structural types may increase bias. For this reason, variable selection would ideally be based on an understanding of the causal network; however, the true causal network is rarely known. Therefore, we describe more practical variable selection approaches based on background knowledge when the causal structure is only partially known. These approaches include adjustment for all observed pretreatment variables thought to have some connection to the outcome, all known risk factors for the outcome, and all direct causes of the treatment or the outcome. Empirical approaches, such as forward and backward selection and automatic high-dimensional proxy adjustment, are also discussed. As there is a continuum between knowing and not knowing the causal, structural relations of variables, we recommend addressing variable selection in a practical way that involves a combination of background knowledge and empirical selection and that uses high-dimensional approaches. This empirical approach can be used to select from a set of a priori variables based on the researcher's knowledge to be included in the final analysis or to identify additional variables for consideration. This more limited use of empirically derived variables may reduce confounding while simultaneously reducing the risk of including variables that may increase bias. Copyright © 2013 John Wiley & Sons, Ltd.

A Review of Covariate Selection for Nonexperimental Comparative Effectiveness Research

PubMed Central

Sauer, Brian C.; Brookhart, Alan; Roy, Jason; Vanderweele, Tyler

2014-01-01

This paper addresses strategies for selecting variables for adjustment in non-experimental comparative effectiveness research (CER), and uses causal graphs to illustrate the causal network that relates treatment to outcome. Variables in the causal network take on multiple structural forms. Adjustment for on a common cause pathway between treatment and outcome can remove confounding, while adjustment for other structural types may increase bias. For this reason variable selection would ideally be based on an understanding of the causal network; however, the true causal network is rarely know. Therefore, we describe more practical variable selection approaches based on background knowledge when the causal structure is only partially known. These approaches include adjustment for all observed pretreatment variables thought to have some connection to the outcome, all known risk factors for the outcome, and all direct causes of the treatment or the outcome. Empirical approaches, such as forward and backward selection and automatic high-dimensional proxy adjustment, are also discussed. As there is a continuum between knowing and not knowing the causal, structural relations of variables, we recommend addressing variable selection in a practical way that involves a combination of background knowledge and empirical selection and that uses the high-dimensional approaches. This empirical approach can be used to select from a set of a priori variables based on the researcher’s knowledge to be included in the final analysis or to identify additional variables for consideration. This more limited use of empirically-derived variables may reduce confounding while simultaneously reducing the risk of including variables that may increase bias. PMID:24006330

Molecular Classification Substitutes for the Prognostic Variables Stage, Age, and MYCN Status in Neuroblastoma Risk Assessment.

PubMed

Rosswog, Carolina; Schmidt, Rene; Oberthuer, André; Juraeva, Dilafruz; Brors, Benedikt; Engesser, Anne; Kahlert, Yvonne; Volland, Ruth; Bartenhagen, Christoph; Simon, Thorsten; Berthold, Frank; Hero, Barbara; Faldum, Andreas; Fischer, Matthias

2017-12-01

Current risk stratification systems for neuroblastoma patients consider clinical, histopathological, and genetic variables, and additional prognostic markers have been proposed in recent years. We here sought to select highly informative covariates in a multistep strategy based on consecutive Cox regression models, resulting in a risk score that integrates hazard ratios of prognostic variables. A cohort of 695 neuroblastoma patients was divided into a discovery set (n=75) for multigene predictor generation, a training set (n=411) for risk score development, and a validation set (n=209). Relevant prognostic variables were identified by stepwise multivariable L1-penalized least absolute shrinkage and selection operator (LASSO) Cox regression, followed by backward selection in multivariable Cox regression, and then integrated into a novel risk score. The variables stage, age, MYCN status, and two multigene predictors, NB-th24 and NB-th44, were selected as independent prognostic markers by LASSO Cox regression analysis. Following backward selection, only the multigene predictors were retained in the final model. Integration of these classifiers in a risk scoring system distinguished three patient subgroups that differed substantially in their outcome. The scoring system discriminated patients with diverging outcome in the validation cohort (5-year event-free survival, 84.9±3.4 vs 63.6±14.5 vs 31.0±5.4; P<.001), and its prognostic value was validated by multivariable analysis. We here propose a translational strategy for developing risk assessment systems based on hazard ratios of relevant prognostic variables. Our final neuroblastoma risk score comprised two multigene predictors only, supporting the notion that molecular properties of the tumor cells strongly impact clinical courses of neuroblastoma patients. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

[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.

Active Traffic Management: Comprehension, Legibility, Distance, and Motorist Behavior In Response to Selected Variable Speed Limit and Lane Control Signing

DOT National Transportation Integrated Search

2016-06-01

Active traffic management (ATM) incorporates a collection of strategies allowing the dynamic management of recurrent and nonrecurrent congestion based on prevailing traffic conditions. These strategies help to increase peak capacity, smooth traffic f...

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.

An Assessment Protocol for Selective Mutism: Analogue Assessment Using Parents as Facilitators.

ERIC Educational Resources Information Center

Schill, Melissa T.; And Others

1996-01-01

Assesses protocol for conducting a functional analysis of maintaining variables for children with selective mutism. A parent was trained in and later applied various behavior strategies designed to increase speech in an eight-year-old girl with selective mutism. Parent and child ratings of treatment were positive. Presents implications for future…

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.

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.

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.

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.

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.

Variable Demographic Rates in an Invasive Plant Species: Differences Among Populations and Management Implications

USDA-ARS?s Scientific Manuscript database

Population managers are frequently faced with the challenge of selecting the most effective management strategy from a set of available strategies. In the case of classical weed biological control, this requires predicting a priori which of a group of candidate biocontrol agent species has the great...

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…

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.

Therapists' causal attributions of clients' problems and selection of intervention strategies.

PubMed

Royce, W S; Muehlke, C V

1991-04-01

Therapists' choices of intervention strategies are influenced by many factors, including judgments about the bases of clients' problems. To assess the relationships between such causal attributions and the selection of intervention strategies, 196 counselors, psychologists, and social workers responded to the written transcript of a client's interview by answering two questionnaires, a 1982 scale (Causal Dimension Scale by Russell) which measured causal attribution of the client's problem, and another which measured preference for emotional, rational, and active intervention strategies in dealing with the client, based on the 1979 E-R-A taxonomy of Frey and Raming. A significant relationship was found between the two sets of variables, with internal attributions linked to rational intervention strategies and stable attributions linked to active strategies. The results support Halleck's 1978 hypothesis that theories of psychotherapy tie interventions to etiological considerations.

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.

The Use of Variable Q1 Isolation Windows Improves Selectivity in LC-SWATH-MS Acquisition.

PubMed

Zhang, Ying; Bilbao, Aivett; Bruderer, Tobias; Luban, Jeremy; Strambio-De-Castillia, Caterina; Lisacek, Frédérique; Hopfgartner, Gérard; Varesio, Emmanuel

2015-10-02

As tryptic peptides and metabolites are not equally distributed along the mass range, the probability of cross fragment ion interference is higher in certain windows when fixed Q1 SWATH windows are applied. We evaluated the benefits of utilizing variable Q1 SWATH windows with regards to selectivity improvement. Variable windows based on equalizing the distribution of either the precursor ion population (PIP) or the total ion current (TIC) within each window were generated by an in-house software, swathTUNER. These two variable Q1 SWATH window strategies outperformed, with respect to quantification and identification, the basic approach using a fixed window width (FIX) for proteomic profiling of human monocyte-derived dendritic cells (MDDCs). Thus, 13.8 and 8.4% additional peptide precursors, which resulted in 13.1 and 10.0% more proteins, were confidently identified by SWATH using the strategy PIP and TIC, respectively, in the MDDC proteomic sample. On the basis of the spectral library purity score, some improvement warranted by variable Q1 windows was also observed, albeit to a lesser extent, in the metabolomic profiling of human urine. We show that the novel concept of "scheduled SWATH" proposed here, which incorporates (i) variable isolation windows and (ii) precursor retention time segmentation further improves both peptide and metabolite identifications.

Enhancing PC Cluster-Based Parallel Branch-and-Bound Algorithms for the Graph Coloring Problem

NASA Astrophysics Data System (ADS)

Taoka, Satoshi; Takafuji, Daisuke; Watanabe, Toshimasa

A branch-and-bound algorithm (BB for short) is the most general technique to deal with various combinatorial optimization problems. Even if it is used, computation time is likely to increase exponentially. So we consider its parallelization to reduce it. It has been reported that the computation time of a parallel BB heavily depends upon node-variable selection strategies. And, in case of a parallel BB, it is also necessary to prevent increase in communication time. So, it is important to pay attention to how many and what kind of nodes are to be transferred (called sending-node selection strategy). In this paper, for the graph coloring problem, we propose some sending-node selection strategies for a parallel BB algorithm by adopting MPI for parallelization and experimentally evaluate how these strategies affect computation time of a parallel BB on a PC cluster network.

Ecophysiological and phenological strategies in seasonally-dry ecosystems: an ecohydrological approach

NASA Astrophysics Data System (ADS)

Vico, Giulia; Manzoni, Stefano; Thompson, Sally; Molini, Annalisa; Porporato, Amilcare

2015-04-01

Seasonally-dry climates are particularly challenging for vegetation, as they are characterized by prolonged dry periods and often marked inter-annual variability. During the dry season plants face predictable physiological stress due to lack of water, whereas the inter-annual variability in rainfall timing and amounts requires plants to develop flexible adaptation strategies. The variety of strategies observed across seasonally-dry (Mediterranean and tropical) ecosystems is indeed wide - ranging from near-isohydric species that adjust stomatal conductance to avoid drought, to anisohydric species that maintain gas exchange during the dry season. A suite of phenological strategies are hypothesized to be associated to ecophysiological strategies. Here we synthetize current knowledge on ecophysiological and phenological adaptations through a comprehensive ecohydrological model linking a soil water balance to a vegetation carbon balance. Climatic regimes are found to select for different phenological strategies that maximize the long-term plant carbon uptake. Inter-annual variability of the duration of the wet season allows coexistence of different drought-deciduous strategies. In contrast, short dry seasons or access to groundwater favour evergreen species. Climatic changes causing more intermittent rainfall and/or shorter wet seasons are predicted to favour drought-deciduous species with opportunistic water use.

Impact of strong selection for the PrP major gene on genetic variability of four French sheep breeds (Open Access publication)

PubMed Central

Palhiere, Isabelle; Brochard, Mickaël; Moazami-Goudarzi, Katayoun; Laloë, Denis; Amigues, Yves; Bed'hom, Bertrand; Neuts, Étienne; Leymarie, Cyril; Pantano, Thais; Cribiu, Edmond Paul; Bibé, Bernard; Verrier, Étienne

2008-01-01

Effective selection on the PrP gene has been implemented since October 2001 in all French sheep breeds. After four years, the ARR "resistant" allele frequency increased by about 35% in young males. The aim of this study was to evaluate the impact of this strong selection on genetic variability. It is focussed on four French sheep breeds and based on the comparison of two groups of 94 animals within each breed: the first group of animals was born before the selection began, and the second, 3–4 years later. Genetic variability was assessed using genealogical and molecular data (29 microsatellite markers). The expected loss of genetic variability on the PrP gene was confirmed. Moreover, among the five markers located in the PrP region, only the three closest ones were affected. The evolution of the number of alleles, heterozygote deficiency within population, expected heterozygosity and the Reynolds distances agreed with the criteria from pedigree and pointed out that neutral genetic variability was not much affected. This trend depended on breed, i.e. on their initial states (population size, PrP frequencies) and on the selection strategies for improving scrapie resistance while carrying out selection for production traits. PMID:18990357

A meta-analysis of research on science teacher education practices associated with inquiry strategy

NASA Astrophysics Data System (ADS)

Sweitzer, Gary L.; Anderson, Ronald D.

A meta-analysis was conducted of studies of teacher education having as measured outcomes one or more variables associated with inquiry teaching. Inquiry addresses those teacher behaviors that facilitate student acquisition of concepts and processes through strategies such as problem solving, uses of evidence, logical and analytical reasoning, clarification of values, and decision making. Studies which contained sufficient data for the calculation of an effect size were coded for 114 variables. These variables were divided into the following six major categories: study information and design characteristics, teacher and teacher trainee characteristics, student characteristics, treatment description, outcome description, and effect size calculation. A total of 68 studies resulting in 177 effect size calculations were coded. Mean effect sizes broken across selected variables were calculated.

Variable beam dose rate and DMLC IMRT to moving body anatomy

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

Papiez, Lech; Abolfath, Ramin M.

2008-11-15

Derivation of formulas relating leaf speeds and beam dose rates for delivering planned intensity profiles to static and moving targets in dynamic multileaf collimator (DMLC) intensity modulated radiation therapy (IMRT) is presented. The analysis of equations determining algorithms for DMLC IMRT delivery under a variable beam dose rate reveals a multitude of possible delivery strategies for a given intensity map and for any given target motion patterns. From among all equivalent delivery strategies for DMLC IMRT treatments specific subclasses of strategies can be selected to provide deliveries that are particularly suitable for clinical applications providing existing delivery devices are used.more » Special attention is devoted to the subclass of beam dose rate variable DMLC delivery strategies to moving body anatomy that generalize existing techniques of such deliveries in Varian DMLC irradiation methodology to static body anatomy. Few examples of deliveries from this subclass of DMLC IMRT irradiations are investigated to illustrate the principle and show practical benefits of proposed techniques.« less

Towards a rational strategy for monitoring of microbiological quality of ambient waters

PubMed Central

Poma, Hugo Ramiro; Cacciabue, Dolores Gutiérrez; Garcé, Beatriz; Gonzo, Elio Emilio; Rajal, Verónica Beatriz

2012-01-01

Water is one of the main sources of human exposure to microbiological hazards. Although legislation establishes regulatory standards in terms of fecal indicator bacteria to assess the microbiological quality of water, these do not necessarily predict the presence of pathogens such as parasites and viruses. Better surveillance and management strategies are needed to assess the risk of pathogens waterborne transmission. We established a baseline dataset to characterize river water quality, identify changes over time, and design a rational monitoring strategy. Data from a year-long monthly monitoring campaign of the polluted Arenales River (Argentina), were analyzed to statistically correlate physicochemical and microbiological variables, the seasonal and longitudinal variation of the water quality and determine the similarity between study sites. The measured variables (sixteen) reflected the deterioration in the river quality through the city. Different viruses and parasites found did not correlate with the concentration of total and thermotolerant coliforms. There was significant seasonal variation for temperature, turbidity, conductivity, dissolved oxygen, enterococci, and norovirus. Strong correlations between some variables were found; we selected eight variables (dissolved oxygen, conductivity, turbidity, total and thermotolerant coliforms, Enterococcus, and adenovirus and Microsporidium as viral and parasitological indicators, respectively) for future monitoring. There was similarity between the monitoring locations, which were grouped into four clusters validated by cophenetic correlation and supported by discriminant analysis. This allowed us to reduce the number of sites, from eleven down to five. Sixty seven percent of the total variance and the correlation structure between variables was explained using five principal components. All these analyses led to a new long-term systematic monitoring scheme A rational monitoring strategy based on the selection of the most suitable monitoring points and of the most significant variables to measure, will result in optimal use of the limited resources available to adequately protect public and environmental health. PMID:22771467

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.

"The Knowledge of" Counselors in Balqa Governorate: Behavior Modification Strategies in Light of Some of the Variables

ERIC Educational Resources Information Center

Al-basel, D-Nagham Mohammad Abu

2013-01-01

The present study aimed to identify the extent of knowledge of counselor behavior modification strategies. The current study sample consisted of (80) mentor and guide, were selected randomly from among all workers enrolled in regular public schools in the Balqa governorate represented the community study for the academic year 2012-2013. The study…

Variable Selection Strategies for Small-area Estimation Using FIA Plots and Remotely Sensed Data

Treesearch

Andrew Lister; Rachel Riemann; James Westfall; Mike Hoppus

2005-01-01

The USDA Forest Service's Forest Inventory and Analysis (FIA) unit maintains a network of tens of thousands of georeferenced forest inventory plots distributed across the United States. Data collected on these plots include direct measurements of tree diameter and height and other variables. We present a technique by which FIA plot data and coregistered...

Use of data mining techniques to classify soil CO2 emission induced by crop management in sugarcane field.

PubMed

Farhate, Camila Viana Vieira; Souza, Zigomar Menezes de; Oliveira, Stanley Robson de Medeiros; Tavares, Rose Luiza Moraes; Carvalho, João Luís Nunes

2018-01-01

Soil CO2 emissions are regarded as one of the largest flows of the global carbon cycle and small changes in their magnitude can have a large effect on the CO2 concentration in the atmosphere. Thus, a better understanding of this attribute would enable the identification of promoters and the development of strategies to mitigate the risks of climate change. Therefore, our study aimed at using data mining techniques to predict the soil CO2 emission induced by crop management in sugarcane areas in Brazil. To do so, we used different variable selection methods (correlation, chi-square, wrapper) and classification (Decision tree, Bayesian models, neural networks, support vector machine, bagging with logistic regression), and finally we tested the efficiency of different approaches through the Receiver Operating Characteristic (ROC) curve. The original dataset consisted of 19 variables (18 independent variables and one dependent (or response) variable). The association between cover crop and minimum tillage are effective strategies to promote the mitigation of soil CO2 emissions, in which the average CO2 emissions are 63 kg ha-1 day-1. The variables soil moisture, soil temperature (Ts), rainfall, pH, and organic carbon were most frequently selected for soil CO2 emission classification using different methods for attribute selection. According to the results of the ROC curve, the best approaches for soil CO2 emission classification were the following: (I)-the Multilayer Perceptron classifier with attribute selection through the wrapper method, that presented rate of false positive of 13,50%, true positive of 94,20% area under the curve (AUC) of 89,90% (II)-the Bagging classifier with logistic regression with attribute selection through the Chi-square method, that presented rate of false positive of 13,50%, true positive of 94,20% AUC of 89,90%. However, the (I) approach stands out in relation to (II) for its higher positive class accuracy (high CO2 emission) and lower computational cost.

Use of data mining techniques to classify soil CO2 emission induced by crop management in sugarcane field

PubMed Central

de Souza, Zigomar Menezes; Oliveira, Stanley Robson de Medeiros; Tavares, Rose Luiza Moraes; Carvalho, João Luís Nunes

2018-01-01

Soil CO2 emissions are regarded as one of the largest flows of the global carbon cycle and small changes in their magnitude can have a large effect on the CO2 concentration in the atmosphere. Thus, a better understanding of this attribute would enable the identification of promoters and the development of strategies to mitigate the risks of climate change. Therefore, our study aimed at using data mining techniques to predict the soil CO2 emission induced by crop management in sugarcane areas in Brazil. To do so, we used different variable selection methods (correlation, chi-square, wrapper) and classification (Decision tree, Bayesian models, neural networks, support vector machine, bagging with logistic regression), and finally we tested the efficiency of different approaches through the Receiver Operating Characteristic (ROC) curve. The original dataset consisted of 19 variables (18 independent variables and one dependent (or response) variable). The association between cover crop and minimum tillage are effective strategies to promote the mitigation of soil CO2 emissions, in which the average CO2 emissions are 63 kg ha-1 day-1. The variables soil moisture, soil temperature (Ts), rainfall, pH, and organic carbon were most frequently selected for soil CO2 emission classification using different methods for attribute selection. According to the results of the ROC curve, the best approaches for soil CO2 emission classification were the following: (I)–the Multilayer Perceptron classifier with attribute selection through the wrapper method, that presented rate of false positive of 13,50%, true positive of 94,20% area under the curve (AUC) of 89,90% (II)–the Bagging classifier with logistic regression with attribute selection through the Chi-square method, that presented rate of false positive of 13,50%, true positive of 94,20% AUC of 89,90%. However, the (I) approach stands out in relation to (II) for its higher positive class accuracy (high CO2 emission) and lower computational cost. PMID:29513765

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.

Applicability of ISO 16697 Data to Spacecraft Fire Fighting Strategies

NASA Technical Reports Server (NTRS)

Hirsch, David B.; Beeson, Harold D.

2012-01-01

Presentation Agenda: (1) Selected variables affecting oxygen consumption during spacecraft fires, (2) General overview of ISO 16697, (3) Estimated amounts of material consumed during combustion in typical ISS enclosures, (4) Discussion on potential applications.

GWASinlps: Nonlocal prior based iterative SNP selection tool for genome-wide association studies.

PubMed

Sanyal, Nilotpal; Lo, Min-Tzu; Kauppi, Karolina; Djurovic, Srdjan; Andreassen, Ole A; Johnson, Valen E; Chen, Chi-Hua

2018-06-19

Multiple marker analysis of the genome-wide association study (GWAS) data has gained ample attention in recent years. However, because of the ultra high-dimensionality of GWAS data, such analysis is challenging. Frequently used penalized regression methods often lead to large number of false positives, whereas Bayesian methods are computationally very expensive. Motivated to ameliorate these issues simultaneously, we consider the novel approach of using nonlocal priors in an iterative variable selection framework. We develop a variable selection method, named, iterative nonlocal prior based selection for GWAS, or GWASinlps, that combines, in an iterative variable selection framework, the computational efficiency of the screen-and-select approach based on some association learning and the parsimonious uncertainty quantification provided by the use of nonlocal priors. The hallmark of our method is the introduction of 'structured screen-and-select' strategy, that considers hierarchical screening, which is not only based on response-predictor associations, but also based on response-response associations, and concatenates variable selection within that hierarchy. Extensive simulation studies with SNPs having realistic linkage disequilibrium structures demonstrate the advantages of our computationally efficient method compared to several frequentist and Bayesian variable selection methods, in terms of true positive rate, false discovery rate, mean squared error, and effect size estimation error. Further, we provide empirical power analysis useful for study design. Finally, a real GWAS data application was considered with human height as phenotype. An R-package for implementing the GWASinlps method is available at https://cran.r-project.org/web/packages/GWASinlps/index.html. Supplementary data are available at Bioinformatics online.

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…

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.

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.

Evaluation of delivered dose for a clinical daily adaptive plan selection strategy for bladder cancer radiotherapy.

PubMed

Lutkenhaus, Lotte J; Visser, Jorrit; de Jong, Rianne; Hulshof, Maarten C C M; Bel, Arjan

2015-07-01

To account for variable bladder size during bladder cancer radiotherapy, a daily plan selection strategy was implemented. The aim of this study was to calculate the actually delivered dose using an adaptive strategy, compared to a non-adaptive approach. Ten patients were treated to the bladder and lymph nodes with an adaptive full bladder strategy. Interpolated delineations of bladder and tumor on a full and empty bladder CT scan resulted in five PTVs for which VMAT plans were created. Daily cone beam CT (CBCT) scans were used for plan selection. Bowel, rectum and target volumes were delineated on these CBCTs, and delivered dose for these was calculated using both the adaptive plan, and a non-adaptive plan. Target coverage for lymph nodes improved using an adaptive strategy. The full bladder strategy spared the healthy part of the bladder from a high dose. Average bowel cavity V30Gy and V40Gy significantly reduced with 60 and 69ml, respectively (p<0.01). Other parameters for bowel and rectum remained unchanged. Daily plan selection compared to a non-adaptive strategy yielded similar bladder coverage and improved coverage for lymph nodes, with a significant reduction in bowel cavity V30Gy and V40Gy only, while other sparing was limited. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

The Effects of Paternal Teaching Strategies, Childcare Involvement, and Select Father-Child Variables on the Academic Performance of Mexican-American Children.

ERIC Educational Resources Information Center

Strand, David A.

Fifty-nine Mexican-American families, each with a child between age 5 and 9, participated in a study to determine whether paternal proximal behaviors related to child ability and achievement. Proximal behaviors studied were: (1) teaching strategies; (2) language in literacy related activities; (3) involvement level in childcare; and (4) select…

Techniques for detecting effects of urban and rural land-use practices on stream-water chemistry in selected watersheds in Texas, Minnesota,and Illinois

USGS Publications Warehouse

Walker, J.F.

1993-01-01

Selected statistical techniques were applied to three urban watersheds in Texas and Minnesota and three rural watersheds in Illinois. For the urban watersheds, single- and paired-site data-collection strategies were considered. The paired-site strategy was much more effective than the singlesite strategy for detecting changes. Analysis of storm load regression residuals demonstrated the potential utility of regressions for variability reduction. For the rural watersheds, none of the selected techniques were effective at identifying changes, primarily due to a small degree of management-practice implementation, potential errors introduced through the estimation of storm load, and small sample sizes. A Monte Carlo sensitivity analysis was used to determine the percent change in water chemistry that could be detected for each watershed. In most instances, the use of regressions improved the ability to detect changes.

Genic Variability and Strategies of Adaptation in Animals

PubMed Central

Selander, Robert K.; Kaufman, Donald W.

1973-01-01

Levels of genic heterozygosity, as measured by surveys of allozymic variation, are much lower in populations of large, mobile animals (most vertebrates) than in those of small, relatively immobile animals (most invertebrates). This difference is not consistent with theories relating variability to population size (species number) or dispersal ability (gene flow), but it is predicted by Levins' theory of adaptive strategies in relation to environmental uncertainty (“grain”). Mobility and degree of homeostatic control apparently are important factors influencing levels of genic heterozygosity in natural populations. The results argue indirectly that at least a major proportion of allozymic variation is maintained by natural selection. PMID:4515944

REGULATION OF GEOGRAPHIC VARIABILITY IN HAPLOID:DIPLOD RATIOS OF BIPHASIC SEAWEED LIFE CYCLES(1).

PubMed

da Silva Vieira, Vasco Manuel Nobre de Carvalho; Santos, Rui Orlando Pimenta

2012-08-01

The relative abundance of haploid and diploid individuals (H:D) in isomorphic marine algal biphasic cycles varies spatially, but only if vital rates of haploid and diploid phases vary differently with environmental conditions (i.e. conditional differentiation between phases). Vital rates of isomorphic phases in particular environments may be determined by subtle morphological or physiological differences. Herein, we test numerically how geographic variability in H:D is regulated by conditional differentiation between isomorphic life phases and the type of life strategy of populations (i.e. life cycles dominated by reproduction, survival or growth). Simulation conditions were selected using available data on H:D spatial variability in seaweeds. Conditional differentiation between ploidy phases had a small effect on the H:D variability for species with life strategies that invest either in fertility or in growth. Conversely, species with life strategies that invest mainly in survival, exhibited high variability in H:D through a conditional differentiation in stasis (the probability of staying in the same size class), breakage (the probability of changing to a smaller size class) or growth (the probability of changing to a bigger size class). These results were consistent with observed geographic variability in H:D of natural marine algae populations. © 2012 Phycological Society of America.

Cost-effectiveness of different strategies for selecting and treating individuals at increased risk of osteoporosis or osteopenia: a systematic review.

PubMed

Müller, Dirk; Pulm, Jannis; Gandjour, Afschin

2012-01-01

To compare cost-effectiveness modeling analyses of strategies to prevent osteoporotic and osteopenic fractures either based on fixed thresholds using bone mineral density or based on variable thresholds including bone mineral density and clinical risk factors. A systematic review was performed by using the MEDLINE database and reference lists from previous reviews. On the basis of predefined inclusion/exclusion criteria, we identified relevant studies published since January 2006. Articles included for the review were assessed for their methodological quality and results. The literature search resulted in 24 analyses, 14 of them using a fixed-threshold approach and 10 using a variable-threshold approach. On average, 70% of the criteria for methodological quality were fulfilled, but almost half of the analyses did not include medication adherence in the base case. The results of variable-threshold strategies were more homogeneous and showed more favorable incremental cost-effectiveness ratios compared with those based on a fixed threshold with bone mineral density. For analyses with fixed thresholds, incremental cost-effectiveness ratios varied from €80,000 per quality-adjusted life-year in women aged 55 years to cost saving in women aged 80 years. For analyses with variable thresholds, the range was €47,000 to cost savings. Risk assessment using variable thresholds appears to be more cost-effective than selecting high-risk individuals by fixed thresholds. Although the overall quality of the studies was fairly good, future economic analyses should further improve their methods, particularly in terms of including more fracture types, incorporating medication adherence, and including or discussing unrelated costs during added life-years. Copyright © 2012 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Race, genetics, and human reproductive strategies.

PubMed

Rushton, J P

1996-02-01

The international literature on racial differences is reviewed, novel data are reported, and a distinct pattern is found. People of east Asian ancestry and people of African ancestry average at opposite ends of a continuum, with people of European ancestry averaging intermediately, albeit with much variability within each major race. The racial matrix emerges from measures taken of reproductive behavior, sex hormones, twinning rate, speed of physical maturation, personality, family stability, brain size, intelligence, law abidingness, and social organization. An evolutionary theory of human reproduction is proposed, familiar to biologists as the r-K scale of reproductive strategies. At one end of this scale are r-strategies, which emphasize high reproductive rates; at the other end are K-strategies, which emphasize high levels of parental investment. This scale is generally used to compare the life histories of widely disparate species, but here it is used to describe the immensely smaller variations among human races. It is hypothesized that, again on average, Mongoloid people are more K-selected than Caucasoids, who are more K-selected than Negroids. The r-K scale of reproductive strategies is also mapped on to human evolution. Genetic distances indicate that Africans emerged from the ancestral hominid line about 200,000 years ago, with an African/non-African split about 110,000 years ago, and a Caucasoid/Mongoloid split about 41,000 years ago. Such an ordering fits with and explains how and why the variables cluster.

Predicting punching acceleration from selected strength and power variables in elite karate athletes: a multiple regression analysis.

PubMed

Loturco, Irineu; Artioli, Guilherme Giannini; Kobal, Ronaldo; Gil, Saulo; Franchini, Emerson

2014-07-01

This study investigated the relationship between punching acceleration and selected strength and power variables in 19 professional karate athletes from the Brazilian National Team (9 men and 10 women; age, 23 ± 3 years; height, 1.71 ± 0.09 m; and body mass [BM], 67.34 ± 13.44 kg). Punching acceleration was assessed under 4 different conditions in a randomized order: (a) fixed distance aiming to attain maximum speed (FS), (b) fixed distance aiming to attain maximum impact (FI), (c) self-selected distance aiming to attain maximum speed, and (d) self-selected distance aiming to attain maximum impact. The selected strength and power variables were as follows: maximal dynamic strength in bench press and squat-machine, squat and countermovement jump height, mean propulsive power in bench throw and jump squat, and mean propulsive velocity in jump squat with 40% of BM. Upper- and lower-body power and maximal dynamic strength variables were positively correlated to punch acceleration in all conditions. Multiple regression analysis also revealed predictive variables: relative mean propulsive power in squat jump (W·kg-1), and maximal dynamic strength 1 repetition maximum in both bench press and squat-machine exercises. An impact-oriented instruction and a self-selected distance to start the movement seem to be crucial to reach the highest acceleration during punching execution. This investigation, while demonstrating strong correlations between punching acceleration and strength-power variables, also provides important information for coaches, especially for designing better training strategies to improve punching speed.

Not accounting for interindividual variability can mask habitat selection patterns: a case study on black bears.

PubMed

Lesmerises, Rémi; St-Laurent, Martin-Hugues

2017-11-01

Habitat selection studies conducted at the population scale commonly aim to describe general patterns that could improve our understanding of the limiting factors in species-habitat relationships. Researchers often consider interindividual variation in selection patterns to control for its effects and avoid pseudoreplication by using mixed-effect models that include individuals as random factors. Here, we highlight common pitfalls and possible misinterpretations of this strategy by describing habitat selection of 21 black bears Ursus americanus. We used Bayesian mixed-effect models and compared results obtained when using random intercept (i.e., population level) versus calculating individual coefficients for each independent variable (i.e., individual level). We then related interindividual variability to individual characteristics (i.e., age, sex, reproductive status, body condition) in a multivariate analysis. The assumption of comparable behavior among individuals was verified only in 40% of the cases in our seasonal best models. Indeed, we found strong and opposite responses among sampled bears and individual coefficients were linked to individual characteristics. For some covariates, contrasted responses canceled each other out at the population level. In other cases, interindividual variability was concealed by the composition of our sample, with the majority of the bears (e.g., old individuals and bears in good physical condition) driving the population response (e.g., selection of young forest cuts). Our results stress the need to consider interindividual variability to avoid misinterpretation and uninformative results, especially for a flexible and opportunistic species. This study helps to identify some ecological drivers of interindividual variability in bear habitat selection patterns.

Age and Gender Differences in Emotion Regulation Strategies: Autobiographical Memory, Rumination, Problem Solving and Distraction.

PubMed

Ricarte Trives, Jorge Javier; Navarro Bravo, Beatriz; Latorre Postigo, José Miguel; Ros Segura, Laura; Watkins, Ed

2016-07-18

Our study tested the hypothesis that older adults and men use more adaptive emotion regulatory strategies but fewer negative emotion regulatory strategies than younger adults and women. In addition, we tested the hypothesis that rumination acts as a mediator variable for the effect of age and gender on depression scores. Differences in rumination, problem solving, distraction, autobiographical recall and depression were assessed in a group of young adults (18-29 years) compared to a group of older adults (50-76 years). The older group used more problem solving and distraction strategies when in a depressed state than their younger counterparts (ps .06). Ordinary least squares regression analyses with bootstrapping showed that rumination mediated the association between age, gender and depression scores. These results suggest that older adults and men select more adaptive strategies to regulate emotions than young adults and women with rumination acting as a significant mediator variable in the association between age, gender, and depression.

Microbiome Selection Could Spur Next-Generation Plant Breeding Strategies.

PubMed

Gopal, Murali; Gupta, Alka

2016-01-01

" No plant is an island too …" Plants, though sessile, have developed a unique strategy to counter biotic and abiotic stresses by symbiotically co-evolving with microorganisms and tapping into their genome for this purpose. Soil is the bank of microbial diversity from which a plant selectively sources its microbiome to suit its needs. Besides soil, seeds, which carry the genetic blueprint of plants during trans-generational propagation, are home to diverse microbiota that acts as the principal source of microbial inoculum in crop cultivation. Overall, a plant is ensconced both on the outside and inside with a diverse assemblage of microbiota. Together, the plant genome and the genes of the microbiota that the plant harbors in different plant tissues, i.e., the 'plant microbiome,' form the holobiome which is now considered as unit of selection: 'the holobiont.' The 'plant microbiome' not only helps plants to remain fit but also offers critical genetic variability, hitherto, not employed in the breeding strategy by plant breeders, who traditionally have exploited the genetic variability of the host for developing high yielding or disease tolerant or drought resistant varieties. This fresh knowledge of the microbiome, particularly of the rhizosphere, offering genetic variability to plants, opens up new horizons for breeding that could usher in cultivation of next-generation crops depending less on inorganic inputs, resistant to insect pest and diseases and resilient to climatic perturbations. We surmise, from ever increasing evidences, that plants and their microbial symbionts need to be co-propagated as life-long partners in future strategies for plant breeding. In this perspective, we propose bottom-up approach to co-propagate the co-evolved, the plant along with the target microbiome, through - (i) reciprocal soil transplantation method, or (ii) artificial ecosystem selection method of synthetic microbiome inocula, or (iii) by exploration of microRNA transfer method - for realizing this next-generation plant breeding approach. Our aim, thus, is to bring closer the information accrued through the advanced nucleotide sequencing and bioinformatics in conjunction with conventional culture-dependent isolation method for practical application in plant breeding and overall agriculture.

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.

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.

JCDSA: a joint covariate detection tool for survival analysis on tumor expression profiles.

PubMed

Wu, Yiming; Liu, Yanan; Wang, Yueming; Shi, Yan; Zhao, Xudong

2018-05-29

Survival analysis on tumor expression profiles has always been a key issue for subsequent biological experimental validation. It is crucial how to select features which closely correspond to survival time. Furthermore, it is important how to select features which best discriminate between low-risk and high-risk group of patients. Common features derived from the two aspects may provide variable candidates for prognosis of cancer. Based on the provided two-step feature selection strategy, we develop a joint covariate detection tool for survival analysis on tumor expression profiles. Significant features, which are not only consistent with survival time but also associated with the categories of patients with different survival risks, are chosen. Using the miRNA expression data (Level 3) of 548 patients with glioblastoma multiforme (GBM) as an example, miRNA candidates for prognosis of cancer are selected. The reliability of selected miRNAs using this tool is demonstrated by 100 simulations. Furthermore, It is discovered that significant covariates are not directly composed of individually significant variables. Joint covariate detection provides a viewpoint for selecting variables which are not individually but jointly significant. Besides, it helps to select features which are not only consistent with survival time but also associated with prognosis risk. The software is available at http://bio-nefu.com/resource/jcdsa .

LPTA versus Tradeoff: Analysis of Contract Source Selection Strategies and Performance Outcomes

DTIC Science & Technology

2016-06-15

methodologies contracting professionals employ to acquire what the DOD needs. Contracting professionals may use lowest price technically acceptable...17 1. 2. Lowest Price Technically Acceptable...Acquisition Streamlining Act Government Accountability Office highest technically rated offeror independent variable lowest price technically

The evolution of flowering strategies in US weedy rice

USDA-ARS?s Scientific Manuscript database

Local adaptation in plants often involves changes in flowering time in response to day length and temperature differences. Many crop varieties have been selected for uniformity in flowering time. In contrast, variable flowering may be important for increased competitiveness in weed species invading ...

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...

Male reproductive strategy and decreased longevity.

PubMed

Vinogradov, A E

1998-06-01

An explanation of the inter-gender difference in longevity consistent with the 'disposable soma' theory of ageing is proposed. It is based on the concept of r-K selection as applied to the inter-gender situation. The concept predicts that the gender with a higher potential reproductive rate (males) should invest relatively less in somatic maintenance, which in its turn should result in a lower longevity according to the 'disposable soma' theory of ageing. In females, which are interpreted as K-selected organisms, the reproductive strategy strongly depends on steady, secure constitution designed for oocyte/embryo bearing and is therefore closely related to somatic maintenance, whereas in (r-selected) males it has a greater behavioural component--risky, variable, with a greater potential productive success at the expense of somatic maintenance. The higher metabolic and growth rates, a higher premature mortality and a longer period of sexual competence of males also find explanation as a complex of r-selected traits.

Strategies of marine dinoflagellate survival and some rules of assembly

NASA Astrophysics Data System (ADS)

Smayda, Theodore J.; Reynolds, Colin S.

2003-03-01

Dinoflagellate ecology is based on multiple adaptive strategies and species having diverse habitat preferences. Nine types of mixing-irradiance-nutrient habitats selecting for specific marine dinoflagellate life-form types are recognised, with five rules of assembly proposed to govern bloom-species selection and community organisation within these habitats. Assembly is moulded around an abiotic template of light energy, nutrient supply and physical mixing in permutative combinations. Species selected will have one of three basic ( C-, S-, R-) strategies: colonist species ( C-) which predominate in chemically disturbed habitats; nutrient stress tolerant species ( S-), and species ( R-) tolerant of shear/stress forces in physically disturbed water masses. This organisational plan of three major habitat variables and three major adaptive strategies is termed the 3-3 plan. The bloom behaviour and habitat specialisation of dinoflagellates and diatoms are compared. Dinoflagellates behave as annual species, bloom soloists, are ecophysiologically diverse, and habitat specialists whose blooms tend to be monospecific. Diatoms behave as perennial species, guild members, are habitat cosmopolites, have a relatively uniform bloom strategy based on species-rich pools and exhibit limited habitat specialisation. Dinoflagellate bloom-species selection follows a taxonomic hierarchical pathway which progresses from phylogenetic to generic to species selection, and in that sequence. Each hierarchical taxonomic level has its own adaptive requirements subject to rules of assembly. Dinoflagellates would appear to be well suited to exploit marine habitats and to be competitive with other phylogenetic groups, yet fail to do so.

Top down and bottom up selection drives variations in frequency and form of a visual signal.

PubMed

Yeh, Chien-Wei; Blamires, Sean J; Liao, Chen-Pan; Tso, I-Min

2015-03-30

The frequency and form of visual signals can be shaped by selection from predators, prey or both. When a signal simultaneously attracts predators and prey selection may favour a strategy that minimizes risks while attracting prey. Accordingly, varying the frequency and form of the silken decorations added to their web may be a way that Argiope spiders minimize predation while attracting prey. Nonetheless, the role of extraneous factors renders the influences of top down and bottom up selection on decoration frequency and form variation difficult to discern. Here we used dummy spiders and decorations to simulate four possible strategies that the spider Argiope aemula may choose and measured the prey and predator attraction consequences for each in the field. The strategy of decorating at a high frequency with a variable form attracted the most prey, while that of decorating at a high frequency with a fixed form attracted the most predators. These results suggest that mitigating the cost of attracting predators while maintaining prey attraction drives the use of variation in decoration form by many Argiope spp. when decorating frequently. Our study highlights the importance of considering top-down and bottom up selection pressure when devising evolutionary ecology experiments.

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.

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.

Risky business for a juvenile marine predator? Testing the influence of foraging strategies on size and growth rate under natural conditions

PubMed Central

DiBattista, Joseph D.; Moore, Jonathan W.; Ward, Eric J.; Fisk, Aaron T.; Kessel, Steven; Guttridge, Tristan L.; Feldheim, Kevin A.; Franks, Bryan R.; Gruber, Samuel H.; Weideli, Ornella C.; Chapman, Demian D.

2017-01-01

Mechanisms driving selection of body size and growth rate in wild marine vertebrates are poorly understood, thus limiting knowledge of their fitness costs at ecological, physiological and genetic scales. Here, we indirectly tested whether selection for size-related traits of juvenile sharks that inhabit a nursery hosting two dichotomous habitats, protected mangroves (low predation risk) and exposed seagrass beds (high predation risk), is influenced by their foraging behaviour. Juvenile sharks displayed a continuum of foraging strategies between mangrove and seagrass areas, with some individuals preferentially feeding in one habitat over another. Foraging habitat was correlated with growth rate, whereby slower growing, smaller individuals fed predominantly in sheltered mangroves, whereas larger, faster growing animals fed over exposed seagrass. Concomitantly, tracked juveniles undertook variable movement behaviours across both the low and high predation risk habitat. These data provide supporting evidence for the hypothesis that directional selection favouring smaller size and slower growth rate, both heritable traits in this shark population, may be driven by variability in foraging behaviour and predation risk. Such evolutionary pathways may be critical to adaptation within predator-driven marine ecosystems. PMID:28381626

Risky business for a juvenile marine predator? Testing the influence of foraging strategies on size and growth rate under natural conditions.

PubMed

Hussey, Nigel E; DiBattista, Joseph D; Moore, Jonathan W; Ward, Eric J; Fisk, Aaron T; Kessel, Steven; Guttridge, Tristan L; Feldheim, Kevin A; Franks, Bryan R; Gruber, Samuel H; Weideli, Ornella C; Chapman, Demian D

2017-04-12

Mechanisms driving selection of body size and growth rate in wild marine vertebrates are poorly understood, thus limiting knowledge of their fitness costs at ecological, physiological and genetic scales. Here, we indirectly tested whether selection for size-related traits of juvenile sharks that inhabit a nursery hosting two dichotomous habitats, protected mangroves (low predation risk) and exposed seagrass beds (high predation risk), is influenced by their foraging behaviour. Juvenile sharks displayed a continuum of foraging strategies between mangrove and seagrass areas, with some individuals preferentially feeding in one habitat over another. Foraging habitat was correlated with growth rate, whereby slower growing, smaller individuals fed predominantly in sheltered mangroves, whereas larger, faster growing animals fed over exposed seagrass. Concomitantly, tracked juveniles undertook variable movement behaviours across both the low and high predation risk habitat. These data provide supporting evidence for the hypothesis that directional selection favouring smaller size and slower growth rate, both heritable traits in this shark population, may be driven by variability in foraging behaviour and predation risk. Such evolutionary pathways may be critical to adaptation within predator-driven marine ecosystems. © 2017 The Author(s).

Best practice strategies to safeguard drug prescribing and drug administration: an anthology of expert views and opinions.

PubMed

Seidling, Hanna M; Stützle, Marion; Hoppe-Tichy, Torsten; Allenet, Benoît; Bedouch, Pierrick; Bonnabry, Pascal; Coleman, Jamie J; Fernandez-Llimos, Fernando; Lovis, Christian; Rei, Maria Jose; Störzinger, Dominic; Taylor, Lenka A; Pontefract, Sarah K; van den Bemt, Patricia M L A; van der Sijs, Heleen; Haefeli, Walter E

2016-04-01

While evidence on implementation of medication safety strategies is increasing, reasons for selecting and relinquishing distinct strategies and details on implementation are typically not shared in published literature. We aimed to collect and structure expert information resulting from implementing medication safety strategies to provide advice for decision-makers. Medication safety experts with clinical expertise from thirteen hospitals throughout twelve European and North American countries shared their experience in workshop meetings, on-site-visits and remote structured interviews. We performed an expert-based, in-depth assessment of implementation of best-practice strategies to improve drug prescribing and drug administration. Workflow, variability and recommended medication safety strategies in drug prescribing and drug administration processes. According to the experts, institutions chose strategies that targeted process steps known to be particularly error-prone in the respective setting. Often, the selection was channeled by local constraints such as the e-health equipment and critically modulated by national context factors. In our study, the experts favored electronic prescribing with clinical decision support and medication reconciliation as most promising interventions. They agreed that self-assessment and introduction of medication safety boards were crucial to satisfy the setting-specific differences and foster successful implementation. While general evidence for implementation of strategies to improve medication safety exists, successful selection and adaptation of a distinct strategy requires a thorough knowledge of the institute-specific constraints and an ongoing monitoring and adjustment of the implemented measures.

Phage diabody repertoires for selection of large numbers of bispecific antibody fragments.

PubMed

McGuinness, B T; Walter, G; FitzGerald, K; Schuler, P; Mahoney, W; Duncan, A R; Hoogenboom, H R

1996-09-01

Methods for the generation of large numbers of different bispecific antibodies are presented. Cloning strategies are detailed to create repertoires of bispecific diabody molecules with variability on one or both of the antigen binding sites. This diabody format, when combined with the power of phage display technology, allows the generation and analysis of thousands of different bispecific molecules. Selection for binding presumably also selects for more stable diabodies. Phage diabody libraries enable screening or selection of the best combination bispecific molecule with regards to affinity of binding, epitope recognition and pairing before manufacture of the best candidate.

Identifying the control structure of multijoint coordination during pistol shooting.

PubMed

Scholz, J P; Schöner, G; Latash, M L

2000-12-01

The question of degrees of freedom in the control of multijoint movement is posed as the problem of discovering how the motor control system constrains the many possible combinations of joint postures to stabilize task-dependent essential variables. Success at a task can be achieved, in principle, by always adopting a particular joint combination. In contrast, we propose a more selective control strategy: variations of the joint configuration that leave the values of essential task variables unchanged are predicted to be less controlled (i.e., stabilized to a lesser degree) than joint configuration changes that shift the values of the task variables. Our experimental task involved shooting with a laser pistol at a target under four conditions. The seven joint angles of the arm were obtained from the recorded positions of markers on the limb segments. The joint configurations observed at each point in normalized time were analyzed with respect to trial-to-trial variability. Different hypotheses about relevant task variables were used to define sets of joint configurations ("uncontrolled manifolds" or UCMs) that, if realized, would leave essential task variables unchanged. The variability of joint configurations was decomposed into components lying parallel to those sets and components lying in their complement. The orientation of the gun's barrel relative to a vector pointing from the gun to the target was the task variable most successful at showing a difference between the two components of joint variability. This variable determines success at the task. Throughout the movement, not only while the gun was pointing at the target, fluctuations of joint configuration that affected this variable were much reduced compared with fluctuations that did not affect this variable. The UCM principle applied to relative gun orientation thus captures the structure of the motor control system across different parts of joint configuration space as the movement evolves in time. This suggests a specific control strategy in which changes of joint configuration that are irrelevant to success at the task are selectively released from control. By contrast, constraints representing an invariant spatial position of the gun or of the arm's center of mass structured joint configuration variability in the early and mid-portion of the movement trajectory, but not at the time of shooting. This specific control strategy is not trivial, because a target can be hit successfully also by controlling irrelevant directions in joint space equally to relevant ones. The results indicate that the method can be successfully used to determine the structure of coordination in joint space that underlies the control of the essential variables for a given task.

Representativeness-based sampling network design for the State of Alaska

Treesearch

Forrest M. Hoffman; Jitendra Kumar; Richard T. Mills; William W. Hargrove

2013-01-01

Resource and logistical constraints limit the frequency and extent of environmental observations, particularly in the Arctic, necessitating the development of a systematic sampling strategy to maximize coverage and objectively represent environmental variability at desired scales. A quantitative methodology for stratifying sampling domains, informing site selection,...

Predicting Conflict Management Based on Organizational Commitment and Selected Demographic Variables

ERIC Educational Resources Information Center

Balay, Refik

2007-01-01

The purpose of this study is to investigate the relationship between different levels of organizational commitment (compliance, identification, internalization) of teachers and their different conflict management strategies (compromising, problem solving, forcing, yielding, avoiding). Based on a questionnaire survey of 418 teachers, this study…

The no-show patient in the model family practice unit.

PubMed

Dervin, J V; Stone, D L; Beck, C H

1978-12-01

Appointment breaking by patients causes problems for the physician's office. Patients who neither keep nor cancel their appointments are often referred to as "no shows." Twenty variables were identified as potential predictors of no-show behavior. These predictors were applied to 291 Family Practice Center patients during a one-month study in April 1977. A discriminant function and multiple regression procedure were utilized ascertain the predictability of the selected variables. Predictive accuracy of the variables was 67.4 percent compared to the presently utilized constant predictor technique, which is 73 percent accurate. Modification of appointment schedules based upon utilization of the variables studies as predictors of show/no-show behavior does not appear to be an effective strategy in the Family Practice Center of the Community Hospital of Sonoma County, Santa Rosa, due to the high proportion of patients who do, in fact, show. In clinics with lower show rates, the technique may prove to be an effective strategy.

Neural Architecture of Selective Stopping Strategies: Distinct Brain Activity Patterns Are Associated with Attentional Capture But Not with Outright Stopping.

PubMed

Sebastian, Alexandra; Rössler, Kora; Wibral, Michael; Mobascher, Arian; Lieb, Klaus; Jung, Patrick; Tüscher, Oliver

2017-10-04

In stimulus-selective stop-signal tasks, the salient stop signal needs attentional processing before genuine response inhibition is completed. Differential prefrontal involvement in attentional capture and response inhibition has been linked to the right inferior frontal junction (IFJ) and ventrolateral prefrontal cortex (VLPFC), respectively. Recently, it has been suggested that stimulus-selective stopping may be accomplished by the following different strategies: individuals may selectively inhibit their response only upon detecting a stop signal (independent discriminate then stop strategy) or unselectively whenever detecting a stop or attentional capture signal (stop then discriminate strategy). Alternatively, the discrimination process of the critical signal (stop vs attentional capture signal) may interact with the go process (dependent discriminate then stop strategy). Those different strategies might differentially involve attention- and stopping-related processes that might be implemented by divergent neural networks. This should lead to divergent activation patterns and, if disregarded, interfere with analyses in neuroimaging studies. To clarify this crucial issue, we studied 87 human participants of both sexes during a stimulus-selective stop-signal task and performed strategy-dependent functional magnetic resonance imaging analyses. We found that, regardless of the strategy applied, outright stopping displayed indistinguishable brain activation patterns. However, during attentional capture different strategies resulted in divergent neural activation patterns with variable activation of right IFJ and bilateral VLPFC. In conclusion, the neural network involved in outright stopping is ubiquitous and independent of strategy, while different strategies impact on attention-related processes and underlying neural network usage. Strategic differences should therefore be taken into account particularly when studying attention-related processes in stimulus-selective stopping. SIGNIFICANCE STATEMENT Dissociating inhibition from attention has been a major challenge for the cognitive neuroscience of executive functions. Selective stopping tasks have been instrumental in addressing this question. However, recent theoretical, cognitive and behavioral research suggests that different strategies are applied in successful execution of the task. The underlying strategy-dependent neural networks might differ substantially. Here, we show evidence that, regardless of the strategy used, the neural network involved in outright stopping is ubiquitous. However, significant differences can only be found in the attention-related processes underlying those different strategies. Thus, when studying attentional processing of salient stop signals, strategic differences should be considered. In contrast, the neural networks implementing outright stopping seem less or not at all affected by strategic differences. Copyright © 2017 the authors 0270-6474/17/379786-10$15.00/0.

Measurement of volatile organic chemicals at selected sites in California

NASA Technical Reports Server (NTRS)

Singh, Hanwant B.; Salas, L.; Viezee, W.; Sitton, B.; Ferek, R.

1992-01-01

Urban air concentrations of 24 selected volatile organic chemicals that may be potentially hazardous to human health and environment were measured during field experiments conducted at two California locations, at Houston, and at Denver. Chemicals measured included chlorofluorocarbons, halomethanes, haloethanes, halopropanes, chloroethylenes, and aromatic hydrocarbons. With emphasis on California sites, data from these studies are analyzed and interpreted with respect to variabilities in ambient air concentrations, diurnal changes, relation to prevailing meteorology, sources and trends. Except in a few instances, mean concentrations are typically between 0 and 5 ppb. Significant variabilities in atmospheric concentrations associated with intense sources and adverse meteorological conditions are shown to exist. In addition to short-term variability, there is evidence of systematic diurnal and seasonal trends. In some instances it is possible to detect declining trends resulting from the effectiveness of control strategies.

Gas engine heat pump cycle analysis. Volume 1: Model description and generic analysis

NASA Astrophysics Data System (ADS)

Fischer, R. D.

1986-10-01

The task has prepared performance and cost information to assist in evaluating the selection of high voltage alternating current components, values for component design variables, and system configurations and operating strategy. A steady-state computer model for performance simulation of engine-driven and electrically driven heat pumps was prepared and effectively used for parametric and seasonal performance analyses. Parametric analysis showed the effect of variables associated with design of recuperators, brine coils, domestic hot water heat exchanger, compressor size, engine efficiency, insulation on exhaust and brine piping. Seasonal performance data were prepared for residential and commercial units in six cities with system configurations closely related to existing or contemplated hardware of the five GRI engine contractors. Similar data were prepared for an advanced variable-speed electric unit for comparison purposes. The effect of domestic hot water production on operating costs was determined. Four fan-operating strategies and two brine loop configurations were explored.

Evaluation of Selected Recycling Curricula: Educating the Green Citizen.

ERIC Educational Resources Information Center

Boerschig, Sally; De Young, Raymond

1993-01-01

Solid waste curricula from various programs around the country were reviewed using eight variables identified as predictors of conservation behavior. Scores demonstrated that solid waste curricula focus mainly on knowledge and include, to a lesser extent, attitude change and action strategies. Lists the 14 programs evaluated in the study. (MDH)

Marketing the Community College Starts with Understanding Students' Perspectives.

ERIC Educational Resources Information Center

Absher, Keith; Crawford, Gerald

1996-01-01

Examines variables taken into account by community college students in choosing a college, arguing that increased competition for students means that colleges must employ marketing strategies. Discusses the use of the selection factors as market segmentation tools. Identifies five principal market segments based on student classifications of…

Gender Differences in Field-Dependence and Educational Style.

ERIC Educational Resources Information Center

Fritz, Robert L.

1994-01-01

Secondary marketing students (n=144) completed the Group Embedded Figures Test and Educational Style Preference Inventory. Gender differences were found in information processing strategies and on 12 of 19 conative variables representing the way moods and emotions act as filters to produce selective attention. These differences could be most…

Approaches to Data Analysis in Longitudinal Field Investigations of Educational Programs.

ERIC Educational Resources Information Center

Jovick, Thomas D.

The federally funded longitudinal field study called Management Implications of Team Teaching (MITT) required a search for an appropriate strategy for analyzing through-time relationships among selected variables. The MITT project used questionnaires and interviews to collect data concerning the work, governance, attitudes, and orientation of…

Cider fermentation process monitoring by Vis-NIR sensor system and chemometrics.

PubMed

Villar, Alberto; Vadillo, Julen; Santos, Jose I; Gorritxategi, Eneko; Mabe, Jon; Arnaiz, Aitor; Fernández, Luis A

2017-04-15

Optimization of a multivariate calibration process has been undertaken for a Visible-Near Infrared (400-1100nm) sensor system, applied in the monitoring of the fermentation process of the cider produced in the Basque Country (Spain). The main parameters that were monitored included alcoholic proof, l-lactic acid content, glucose+fructose and acetic acid content. The multivariate calibration was carried out using a combination of different variable selection techniques and the most suitable pre-processing strategies were selected based on the spectra characteristics obtained by the sensor system. The variable selection techniques studied in this work include Martens Uncertainty test, interval Partial Least Square Regression (iPLS) and Genetic Algorithm (GA). This procedure arises from the need to improve the calibration models prediction ability for cider monitoring. Copyright © 2016 Elsevier Ltd. All rights reserved.

Advanced reliability methods for structural evaluation

NASA Technical Reports Server (NTRS)

Wirsching, P. H.; Wu, Y.-T.

1985-01-01

Fast probability integration (FPI) methods, which can yield approximate solutions to such general structural reliability problems as the computation of the probabilities of complicated functions of random variables, are known to require one-tenth the computer time of Monte Carlo methods for a probability level of 0.001; lower probabilities yield even more dramatic differences. A strategy is presented in which a computer routine is run k times with selected perturbed values of the variables to obtain k solutions for a response variable Y. An approximating polynomial is fit to the k 'data' sets, and FPI methods are employed for this explicit form.

[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.

Auditory Speech Perception Tests in Relation to the Coding Strategy in Cochlear Implant.

PubMed

Bazon, Aline Cristine; Mantello, Erika Barioni; Gonçales, Alina Sanches; Isaac, Myriam de Lima; Hyppolito, Miguel Angelo; Reis, Ana Cláudia Mirândola Barbosa

2016-07-01

The objective of the evaluation of auditory perception of cochlear implant users is to determine how the acoustic signal is processed, leading to the recognition and understanding of sound. To investigate the differences in the process of auditory speech perception in individuals with postlingual hearing loss wearing a cochlear implant, using two different speech coding strategies, and to analyze speech perception and handicap perception in relation to the strategy used. This study is prospective cross-sectional cohort study of a descriptive character. We selected ten cochlear implant users that were characterized by hearing threshold by the application of speech perception tests and of the Hearing Handicap Inventory for Adults. There was no significant difference when comparing the variables subject age, age at acquisition of hearing loss, etiology, time of hearing deprivation, time of cochlear implant use and mean hearing threshold with the cochlear implant with the shift in speech coding strategy. There was no relationship between lack of handicap perception and improvement in speech perception in both speech coding strategies used. There was no significant difference between the strategies evaluated and no relation was observed between them and the variables studied.

[Modulator effect of socio-emotional variables on training in elaboration strategies in Compulsory Secondary Education (CSE): paraphrase and applications].

PubMed

Martín-Antón, Luis Jorge; Carbonero Martín, Miguel Angel; Román Sánchez, José María

2012-02-01

The purpose of this work is to verify the modulation of motivation, self-concept, and causal attributions in the efficacy of a training program of strategies to elaborate information in the stage of Compulsory Secondary Education (CSE). We selected 328 students from CSE, 179 from second grade and 149 from fourth grade, and three measurement moments: pretest, posttest, and follow-up. The results indicate greater use of learning strategies by students with higher intrinsic motivation, in contrast to students with higher extrinsic motivation, who use learning strategies less frequently. With regard to self-concept, the results differ as a function of the course. In second grade, we found modulation of the variable Academic self-concept, whereas in fourth grade, such modulation is produced by General self-concept and Private self-concept. In general, there is a tendency towards more enduring significant improvements in students with medium and high self-concept, especially in their perception of the use of strategies or in complex tasks that involve relating the contents to be learned with experiences from their daily life. However, students with low self-concept significantly improve strategies associated with learning how to perform specific tasks.

Ancestrality and evolution of trait syndromes in finches (Fringillidae).

PubMed

Ponge, Jean-François; Zuccon, Dario; Elias, Marianne; Pavoine, Sandrine; Henry, Pierre-Yves; Théry, Marc; Guilbert, Éric

2017-12-01

Species traits have been hypothesized by one of us (Ponge, 2013) to evolve in a correlated manner as species colonize stable, undisturbed habitats, shifting from "ancestral" to "derived" strategies. We predicted that generalism, r-selection, sexual monomorphism, and migration/gregariousness are the ancestral states (collectively called strategy A) and evolved correlatively toward specialism, K-selection, sexual dimorphism, and residence/territoriality as habitat stabilized (collectively called B strategy). We analyzed the correlated evolution of four syndromes, summarizing the covariation between 53 traits, respectively, involved in ecological specialization, r-K gradient, sexual selection, and dispersal/social behaviors in 81 species representative of Fringillidae, a bird family with available natural history information and that shows variability for all these traits. The ancestrality of strategy A was supported for three of the four syndromes, the ancestrality of generalism having a weaker support, except for the core group Carduelinae (69 species). It appeared that two different B-strategies evolved from the ancestral state A, both associated with highly predictable environments: one in poorly seasonal environments, called B1, with species living permanently in lowland tropics, with "slow pace of life" and weak sexual dimorphism, and one in highly seasonal environments, called B2, with species breeding out-of-the-tropics, migratory, with a "fast pace of life" and high sexual dimorphism.

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).

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).

Predictors of science success: The impact of motivation and learning strategies on college chemistry performance

NASA Astrophysics Data System (ADS)

Obrentz, Shari B.

As the number of college students studying science continues to grow, it is important to identify variables that predict their success. The literature indicates that motivation and learning strategy use facilitate science success. Research findings show these variables can change throughout a semester and differ by performance level, gender and ethnicity. However, significant predictors of performance vary by research study and by group. The current study looks beyond the traditional predictors of grade point averages, SAT scores and completion of advanced placement (AP) chemistry to consider a comprehensive set of variables not previously investigated within the same study. Research questions address the predictive ability of motivation constructs and learning strategies for success in introductory college chemistry, how these variables change throughout a semester, and how they differ by performance level, gender and ethnicity. Participants were 413 introductory college chemistry students at a highly selective university in the southeast. Participants completed the Chemistry Motivation Questionnaire (CMQ) and Learning Strategies section of the Motivated Strategies for Learning Questionnaire (MSLQ) three times during the semester. Self-efficacy, effort regulation, assessment anxiety and previous achievement were significant predictors of chemistry course success. Levels of motivation changed with significant decreases in self-efficacy and increases in personal relevance and assessment anxiety. Learning strategy use changed with significant increases in elaboration, critical thinking, metacognitive self-regulation skills and peer learning, and significant decreases in time and study management and effort regulation. High course performers reported the highest levels of motivation and learning strategy use. Females reported lower intrinsic motivation, personal relevance, self-efficacy and critical thinking, and higher assessment anxiety, rehearsal and organization. Self-efficacy predicted performance for males and females, while self-determination, help-seeking and time and study environment also predicted female success. Few differences in these variables were found between ethnicity groups. Self-efficacy positively predicted performance for Asians and Whites, and metacognitive self-regulation skills negatively predicted success for Other students. The results have implications for college science instructors who are encouraged to collect and utilize data on students' motivation and learning strategy use, promote both in science classes, and design interventions for specific students who need more support.

The effect of pacing strategy on physiological, kinetic and performance variables during simulated rowing ergometer.

PubMed

Dimakopoulou, Eleni; Zacharogiannis, Elias; Chairopoulou, Chrysoula; Kaloupsis, Socratis; Platanou, Theodoros

2017-02-21

This study compared the effects of self selected (SSP), negative (NPS) and even (EPS) pacing strategy on performance time, kinetic and physiological variables in overall 2km rowing and in first and second 1km. Fifteen male rowers (15.37 ± 1.34 yrs) realized four tests: an incremental test on a rowing ergometer to determine their VO2peak and three experimental 2 km rowing race, where first 1km was manipulated. From SSP a negative pacing strategy, 4% slower than the mean velocity of SSP, and an even pacing strategy (EPS) with mean velocity of SSP, were developed. High stroke rate and better performance time was observed in SSP. Fstr and Fpeak decreased, whereas performance time increased, in SSP and EPS from first to second 1km.Unlike, performance time, stroke rate and Pst in NPS presented better values (p=0.001) with the exception of decreased stroke length (p=0.03). There was an increase in physiological responses in all pacing strategies from first to second 1km (p=0.001). Performance time, stroke rate and Fstr were better in SSP and EPS compared to NPS in first 1km (p=0.001). VE, VE/VO2, VCO2 were better in SSP and EPS compared to NPS (p=0.001) in both first and second 1km. Stroke length was smaller in SSP compared to NPS and EPS in second 1km (p=0.001). Self selected pacing (parabolic-shaped profile) allowed rowers to cover the 2 km distance in higher stroke rate and in shorter performance time compared to negative and even pacing strategies presenting same physiological responses.

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.

Top down and bottom up selection drives variations in frequency and form of a visual signal

PubMed Central

Yeh, Chien-Wei; Blamires, Sean J.; Liao, Chen-Pan; Tso, I.-Min

2015-01-01

The frequency and form of visual signals can be shaped by selection from predators, prey or both. When a signal simultaneously attracts predators and prey, selection may favour a strategy that minimizes risks while attracting prey. Accordingly, varying the frequency and form of the silken decorations added to their web may be a way that Argiope spiders minimize predation while attracting prey. Nonetheless, the role of extraneous factors renders the influences of top down and bottom up selection on decoration frequency and form variation difficult to discern. Here we used dummy spiders and decorations to simulate four possible strategies that the spider Argiope aemula may choose and measured the prey and predator attraction consequences for each in the field. The strategy of decorating at a high frequency with a variable form attracted the most prey, while that of decorating at a high frequency with a fixed form attracted the most predators. These results suggest that mitigating the cost of attracting predators while maintaining prey attraction drives the use of variation in decoration form by many Argiope spp. when decorating frequently. Our study highlights the importance of considering top-down and bottom up selection pressure when devising evolutionary ecology experiments. PMID:25828030

[Costly drugs: analysis and proposals for the Mercosur countries].

PubMed

Marín, Gustavo H; Polach, María Andrea

2011-08-01

Determine how the Mercosur countries access, regulate, and finance costly drugs and propose joint selection and financing strategies at the subregional level. Qualitative design, using content analyses of primary and secondary sources, document reviews, interviews, focus groups, and case studies. The variables selected included: selection criteria, access, financing, and regulations in the various countries. Costly drugs were divided into those that do not alter the natural course of the disease and those with demonstrated efficacy, using the defined daily dose to compare the costs of classical treatments and those involving costly drugs. The Mercosur countries generally lack formal strategies for dealing with the demand for costly drugs, and governments and insurers wind up financing them by court order. The case studies show that there are costly drugs whose efficacy has not been established but that nonetheless generate demand. The fragmentation of procurement, international commitments with regard to intellectual property, and low negotiating power exponentially increase the price of costly drugs, putting health system finances in jeopardy. Costly drugs must be regulated and rationally selected so that only those that substantively benefit people are accepted. To finance the drugs so selected, common country strategies are needed that include such options as flexible in trade agreements, the creation of national resource funds, or joint procurement by countries to enhance their negotiating power.

Evolution of dispersal in spatially and temporally variable environments: The importance of life cycles.

PubMed

Massol, François; Débarre, Florence

2015-07-01

Spatiotemporal variability of the environment is bound to affect the evolution of dispersal, and yet model predictions strongly differ on this particular effect. Recent studies on the evolution of local adaptation have shown that the life cycle chosen to model the selective effects of spatiotemporal variability of the environment is a critical factor determining evolutionary outcomes. Here, we investigate the effect of the order of events in the life cycle on the evolution of unconditional dispersal in a spatially heterogeneous, temporally varying landscape. Our results show that the occurrence of intermediate singular strategies and disruptive selection are conditioned by the temporal autocorrelation of the environment and by the life cycle. Life cycles with dispersal of adults versus dispersal of juveniles, local versus global density regulation, give radically different evolutionary outcomes that include selection for total philopatry, evolutionary bistability, selection for intermediate stable states, and evolutionary branching points. Our results highlight the importance of accounting for life-cycle specifics when predicting the effects of the environment on evolutionarily selected trait values, such as dispersal, as well as the need to check the robustness of model conclusions against modifications of the life cycle. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

Sampling in health geography: reconciling geographical objectives and probabilistic methods. An example of a health survey in Vientiane (Lao PDR)

PubMed Central

Vallée, Julie; Souris, Marc; Fournet, Florence; Bochaton, Audrey; Mobillion, Virginie; Peyronnie, Karine; Salem, Gérard

2007-01-01

Background Geographical objectives and probabilistic methods are difficult to reconcile in a unique health survey. Probabilistic methods focus on individuals to provide estimates of a variable's prevalence with a certain precision, while geographical approaches emphasise the selection of specific areas to study interactions between spatial characteristics and health outcomes. A sample selected from a small number of specific areas creates statistical challenges: the observations are not independent at the local level, and this results in poor statistical validity at the global level. Therefore, it is difficult to construct a sample that is appropriate for both geographical and probability methods. Methods We used a two-stage selection procedure with a first non-random stage of selection of clusters. Instead of randomly selecting clusters, we deliberately chose a group of clusters, which as a whole would contain all the variation in health measures in the population. As there was no health information available before the survey, we selected a priori determinants that can influence the spatial homogeneity of the health characteristics. This method yields a distribution of variables in the sample that closely resembles that in the overall population, something that cannot be guaranteed with randomly-selected clusters, especially if the number of selected clusters is small. In this way, we were able to survey specific areas while minimising design effects and maximising statistical precision. Application We applied this strategy in a health survey carried out in Vientiane, Lao People's Democratic Republic. We selected well-known health determinants with unequal spatial distribution within the city: nationality and literacy. We deliberately selected a combination of clusters whose distribution of nationality and literacy is similar to the distribution in the general population. Conclusion This paper describes the conceptual reasoning behind the construction of the survey sample and shows that it can be advantageous to choose clusters using reasoned hypotheses, based on both probability and geographical approaches, in contrast to a conventional, random cluster selection strategy. PMID:17543100

Sampling in health geography: reconciling geographical objectives and probabilistic methods. An example of a health survey in Vientiane (Lao PDR).

PubMed

Vallée, Julie; Souris, Marc; Fournet, Florence; Bochaton, Audrey; Mobillion, Virginie; Peyronnie, Karine; Salem, Gérard

2007-06-01

Geographical objectives and probabilistic methods are difficult to reconcile in a unique health survey. Probabilistic methods focus on individuals to provide estimates of a variable's prevalence with a certain precision, while geographical approaches emphasise the selection of specific areas to study interactions between spatial characteristics and health outcomes. A sample selected from a small number of specific areas creates statistical challenges: the observations are not independent at the local level, and this results in poor statistical validity at the global level. Therefore, it is difficult to construct a sample that is appropriate for both geographical and probability methods. We used a two-stage selection procedure with a first non-random stage of selection of clusters. Instead of randomly selecting clusters, we deliberately chose a group of clusters, which as a whole would contain all the variation in health measures in the population. As there was no health information available before the survey, we selected a priori determinants that can influence the spatial homogeneity of the health characteristics. This method yields a distribution of variables in the sample that closely resembles that in the overall population, something that cannot be guaranteed with randomly-selected clusters, especially if the number of selected clusters is small. In this way, we were able to survey specific areas while minimising design effects and maximising statistical precision. We applied this strategy in a health survey carried out in Vientiane, Lao People's Democratic Republic. We selected well-known health determinants with unequal spatial distribution within the city: nationality and literacy. We deliberately selected a combination of clusters whose distribution of nationality and literacy is similar to the distribution in the general population. This paper describes the conceptual reasoning behind the construction of the survey sample and shows that it can be advantageous to choose clusters using reasoned hypotheses, based on both probability and geographical approaches, in contrast to a conventional, random cluster selection strategy.

Differential Analysis of Selected Prompts and Neurological Variables in Motor Assessment of Moderately Mentally Retarded Children.

ERIC Educational Resources Information Center

Ilmer, Steven; Drews, Judith

1980-01-01

The relative effectiveness of multisensory-, physical-, modeling-, and verbal-prompting assessment strategies upon the gross motor performance of 40 moderately retarded children (ages 5 to 15 years) was investigated, taking into account the impact of the Ss' levels of reflexive maturation and orthopedic functioning. (Author/DLS)

Parents' Perspectives on Coping with Duchenne Muscular Dystrophy and Concomitant Specific Learning Disabilities

ERIC Educational Resources Information Center

Webb, Carol L.

2005-01-01

This study addresses parental perspectives and coping strategies related to Duchenne muscular dystrophy and specific learning disabilities. Data were collected through individual semi-structured in-depth interviews with fifteen sets of parents. Participants were selected based on variables such as age of children, number of children with both…

Variable regions in Flavobacterium psychrophilum strains identified by comparative genomics: application to selective breeding for cold water disease resistance

USDA-ARS?s Scientific Manuscript database

Bacterial cold water disease is one of the most frequent causes of elevated loss in juvenile salmonids, and the development of effective control strategies is a high priority to aquaculturists, management agencies, and conservationists. Since 2005, rainbow trout (Oncorhynchus mykiss) have been bred ...

EMI-Sensor Data to Identify Areas of Manure Accumulation on a Feedlot Surface

USDA-ARS?s Scientific Manuscript database

A study was initiated to test the validity of using electromagnetic induction (EMI) survey data, a prediction-based sampling strategy and ordinary linear regression modeling to predict spatially variable feedlot surface manure accumulation. A 30 m × 60 m feedlot pen with a central mound was selecte...

Strength and Power Qualities Are Highly Associated With Punching Impact in Elite Amateur Boxers.

PubMed

Loturco, Irineu; Nakamura, Fabio Y; Artioli, Guilherme G; Kobal, Ronaldo; Kitamura, Katia; Cal Abad, Cesar C; Cruz, Igor F; Romano, Felipe; Pereira, Lucas A; Franchini, Emerson

2016-01-01

This study investigated the relationship between punching impact and selected strength and power variables in 15 amateur boxers from the Brazilian National Team (9 men and 6 women). Punching impact was assessed in the following conditions: 3 jabs starting from the standardized position, 3 crosses starting from the standardized position, 3 jabs starting from a self-selected position, and 3 crosses starting from a self-selected position. For punching tests, a force platform (1.02 × 0.76 m) covered by a body shield was mounted on the wall at a height of 1 m, perpendicular to the floor. The selected strength and power variables were vertical jump height (in squat jump and countermovement jump), mean propulsive power in the jump squat, bench press (BP), and bench throw, maximum isometric force in squat and BP, and rate of force development in the squat and BP. Sex and position main effects were observed, with higher impact for males compared with females (p ≤ 0.05) and the self-selected distance resulting in higher impact in the jab technique compared with the fixed distance (p ≤ 0.05). Finally, the correlations between strength/power variables and punching impact indices ranged between 0.67 and 0.85. Because of the strong associations between punching impact and strength/power variables (e.g., lower limb muscle power), this study provides important information for coaches to specifically design better training strategies to improve punching impact.

A novel porous framework as variable chemo-sensor: from response of specific carcinogenic alkyl-aromatic to selective detection of explosive nitro-aromatics.

PubMed

Chen, Qihui

2018-06-07

Selective probing one molecule from one class similar molecules is highly challenging due to their similar chemical and physical properties. Here, a novel metal-organic framework FJI-H15 with flexible porous cages has been designed and synthesized, which can specifically recognize ethyl-benzene with ultrahigh enhancement efficiency from series of alkyl-aromatics, in which an unusual size-dependent interaction has been found and proved. While it also can selectively detect phenolic-nitroaromatics among series of nitro-aromatics based on energy transferring and electrostatic interaction. Such unusual specificity and variable mechanisms responding to different type molecules has not been reported, which will provide a new strategy for developing more effective chemo-sensor based on MOFs for probing small structural differences in molecules. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Consistent model identification of varying coefficient quantile regression with BIC tuning parameter selection

PubMed Central

Zheng, Qi; Peng, Limin

2016-01-01

Quantile regression provides a flexible platform for evaluating covariate effects on different segments of the conditional distribution of response. As the effects of covariates may change with quantile level, contemporaneously examining a spectrum of quantiles is expected to have a better capacity to identify variables with either partial or full effects on the response distribution, as compared to focusing on a single quantile. Under this motivation, we study a general adaptively weighted LASSO penalization strategy in the quantile regression setting, where a continuum of quantile index is considered and coefficients are allowed to vary with quantile index. We establish the oracle properties of the resulting estimator of coefficient function. Furthermore, we formally investigate a BIC-type uniform tuning parameter selector and show that it can ensure consistent model selection. Our numerical studies confirm the theoretical findings and illustrate an application of the new variable selection procedure. PMID:28008212

Growth gains from selective breeding in a spruce hybrid zone do not compromise local adaptation to climate.

PubMed

MacLachlan, Ian R; Yeaman, Sam; Aitken, Sally N

2018-02-01

Hybrid zones contain extensive standing genetic variation that facilitates rapid responses to selection. The Picea glauca  ×  Picea engelmannii hybrid zone in western Canada is the focus of tree breeding programs that annually produce ~90 million reforestation seedlings. Understanding the direct and indirect effects of selective breeding on adaptive variation is necessary to implement assisted gene flow (AGF) polices in Alberta and British Columbia that match these seedlings with future climates. We decomposed relationships among hybrid ancestry, adaptive traits, and climate to understand the implications of selective breeding for climate adaptations and AGF strategies. The effects of selection on associations among hybrid index estimated from ~6,500 SNPs, adaptive traits, and provenance climates were assessed for ~2,400 common garden seedlings. Hybrid index differences between natural and selected seedlings within breeding zones were small in Alberta (average +2%), but larger and more variable in BC (average -7%, range -24% to +1%), slightly favoring P. glauca ancestry. The average height growth gain of selected seedlings over natural seedlings within breeding zones was 36% (range 12%-86%). Clines in growth with temperature-related variables were strong, but differed little between selected and natural populations. Seedling hybrid index and growth trait associations with evapotranspiration-related climate variables were stronger in selected than in natural seedlings, indicating possible preadaptation to drier future climates. Associations among cold hardiness, hybrid ancestry, and cold-related climate variables dominated signals of local adaptation and were preserved in breeding populations. Strong hybrid ancestry-phenotype-climate associations suggest that AGF will be necessary to match interior spruce breeding populations with shifting future climates. The absence of antagonistic selection responses among traits and maintenance of cold adaptation in selected seedlings suggests breeding populations can be safely redeployed using AGF prescriptions similar to those of natural populations.

Workplace victimization: aggression from the target's perspective.

PubMed

Aquino, Karl; Thau, Stefan

2009-01-01

This article reviews research on workplace victimization, which we define as acts of aggression perpetrated by one or more members of an organization that cause psychological, emotional, or physical harm to their intended target. We compare several types of victimizing behaviors that have been introduced into the organizational psychology literature to illustrate differences and similarities among them. We then review studies looking at who is likely to become a victim of aggression. Predictors include personality, demographic, behavioral, structural, and organizational variables. We also review research on coping strategies for victimization, which include problem-focused and emotion-focused strategies. We conclude with a summary of challenges for victimization research. These include addressing the proliferation of constructs and terms into the literature, attempting to clarify inconclusive findings, and using theory to guide the selection of study variables.

[Selective attention and schizophrenia before the administration of neuroleptics].

PubMed

Lussier, I; Stip, E

1999-01-01

In recent years, the presence of attention deficits has been recognized as a key feature of schizophrenia. Past studies reveal that selective attention, or the ability to select relevant information while ignoring simultaneously irrelevant information, is disturbed in schizophrenic patients. According to Treisman feature-integration theory of selective attention, visual search for conjunctive targets (e.g., shape and color) requires controlled processes, that necessitate attention and operate in a serial manner. Reaction times (RTs) are therefore function of the number of stimuli in the display. When subjects are asked to detect the presence or absence of a target in an array of a variable number of stimuli, different performance patterns are expected for positive (present target) and negative trials (absent target). For positive trials, a self-terminating search is triggered, that is, the search is ended when the target is encountered. For negative trials, an exhaustive search strategy is displayed, where each stimulus is examined before the search can end; the RT slope pattern is thus double that of the positive trials. To assess the integrity of these processes, thirteen drug naive schizophrenic patients were compared to twenty normal control subjects. Neuroleptic naive patients were chosen as subjects to avoid the potential influence of medication and chronicity-related factors on performance. The subjects had to specify as fast as possible the presence or absence of the target in an array of a variable number of stimuli presented in a circular display, and comprising or not the target. Results showed that the patients can use self-terminating search strategies as well as normal control subjects. However, their ability to trigger exhaustive search strategies is impaired. Not only were patients slower than controls, but their pattern of RT results was different. These results argue in favor of an early impairment in selective attention capacities in schizophrenia, which appears before the introduction of neuroleptics. The attention performance was also shown to present some association to clinical symptoms.

A computational approach to compare regression modelling strategies in prediction research.

PubMed

Pajouheshnia, Romin; Pestman, Wiebe R; Teerenstra, Steven; Groenwold, Rolf H H

2016-08-25

It is often unclear which approach to fit, assess and adjust a model will yield the most accurate prediction model. We present an extension of an approach for comparing modelling strategies in linear regression to the setting of logistic regression and demonstrate its application in clinical prediction research. A framework for comparing logistic regression modelling strategies by their likelihoods was formulated using a wrapper approach. Five different strategies for modelling, including simple shrinkage methods, were compared in four empirical data sets to illustrate the concept of a priori strategy comparison. Simulations were performed in both randomly generated data and empirical data to investigate the influence of data characteristics on strategy performance. We applied the comparison framework in a case study setting. Optimal strategies were selected based on the results of a priori comparisons in a clinical data set and the performance of models built according to each strategy was assessed using the Brier score and calibration plots. The performance of modelling strategies was highly dependent on the characteristics of the development data in both linear and logistic regression settings. A priori comparisons in four empirical data sets found that no strategy consistently outperformed the others. The percentage of times that a model adjustment strategy outperformed a logistic model ranged from 3.9 to 94.9 %, depending on the strategy and data set. However, in our case study setting the a priori selection of optimal methods did not result in detectable improvement in model performance when assessed in an external data set. The performance of prediction modelling strategies is a data-dependent process and can be highly variable between data sets within the same clinical domain. A priori strategy comparison can be used to determine an optimal logistic regression modelling strategy for a given data set before selecting a final modelling approach.

Primordial and primary prevention programs for cardiovascular diseases: from risk assessment through risk communication to risk reduction. A review of the literature

PubMed Central

Lancarotte, Inês; Nobre, Moacyr Roberto

2016-01-01

The aim of this study was to identify and reflect on the methods employed by studies focusing on intervention programs for the primordial and primary prevention of cardiovascular diseases. The PubMed, EMBASE, SciVerse Hub-Scopus, and Cochrane Library electronic databases were searched using the terms ‘effectiveness AND primary prevention AND risk factors AND cardiovascular diseases’ for systematic reviews, meta-analyses, randomized clinical trials, and controlled clinical trials in the English language. A descriptive analysis of the employed strategies, theories, frameworks, applied activities, and measurement of the variables was conducted. Nineteen primary studies were analyzed. Heterogeneity was observed in the outcome evaluations, not only in the selected domains but also in the indicators used to measure the variables. There was also a predominance of repeated cross-sectional survey design, differences in community settings, and variability related to the randomization unit when randomization was implemented as part of the sample selection criteria; furthermore, particularities related to measures, limitations, and confounding factors were observed. The employed strategies, including their advantages and limitations, and the employed theories and frameworks are discussed, and risk communication, as the key element of the interventions, is emphasized. A methodological process of selecting and presenting the information to be communicated is recommended, and a systematic theoretical perspective to guide the communication of information is advised. The risk assessment concept, its essential elements, and the relevant role of risk perception are highlighted. It is fundamental for communication that statements targeting other people’s understanding be prepared using systematic data. PMID:27982169

Recent developments in clopidogrel pharmacology and their relation to clinical outcomes.

PubMed

Gurbel, Paul A; Antonino, Mark J; Tantry, Udaya S

2009-08-01

Oral antiplatelet therapy with clopidogrel and aspirin is an important and widely prescribed strategy to prevent ischemic events in patients with cardiovascular diseases. However, the occurrence of thrombotic events including stent thrombosis is still high (> 10%). Current practice guidelines are mainly based on large-scale trials focusing on clinical endpoints and 'one size fits all' strategies of treating all patients with the same clopidogrel doses. Pharmacodynamic studies have demonstrated that the latter strategy is associated with wide response variability where a substantial percentage of patients show nonresponsivenes. Translational research studies have established the relation between clopidogrel nonresponsivenes or high on-treatment platelet reactivity to adverse clinical events, thereby establishing clopidogrel nonresponsivenes as an important emerging clinical entity. Clopidogrel response variability is primarily a pharmacokinetic phenomenon associated with insufficient active metabolite generation that is secondary to i) limited intestinal absorption affected by an ABCB1 gene polymorphism; ii) functional variability in P450 isoenzyme activity; and iii) a genetic polymorphism of CYP450 isoenzymes. Personalized antiplatelet treatment with higher clopidogrel doses in selected patients or with newer more potent P2Y(12) receptor blockers based on individual platelet function measurement can overcome some of the limitations of current clopidogrel treatment.

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.

Multisampling suprathreshold perimetry: a comparison with conventional suprathreshold and full-threshold strategies by computer simulation.

PubMed

Artes, Paul H; Henson, David B; Harper, Robert; McLeod, David

2003-06-01

To compare a multisampling suprathreshold strategy with conventional suprathreshold and full-threshold strategies in detecting localized visual field defects and in quantifying the area of loss. Probability theory was applied to examine various suprathreshold pass criteria (i.e., the number of stimuli that have to be seen for a test location to be classified as normal). A suprathreshold strategy that requires three seen or three missed stimuli per test location (multisampling suprathreshold) was selected for further investigation. Simulation was used to determine how the multisampling suprathreshold, conventional suprathreshold, and full-threshold strategies detect localized field loss. To determine the systematic error and variability in estimates of loss area, artificial fields were generated with clustered defects (0-25 field locations with 8- and 16-dB loss) and, for each condition, the number of test locations classified as defective (suprathreshold strategies) and with pattern deviation probability less than 5% (full-threshold strategy), was derived from 1000 simulated test results. The full-threshold and multisampling suprathreshold strategies had similar sensitivity to field loss. Both detected defects earlier than the conventional suprathreshold strategy. The pattern deviation probability analyses of full-threshold results underestimated the area of field loss. The conventional suprathreshold perimetry also underestimated the defect area. With multisampling suprathreshold perimetry, the estimates of defect area were less variable and exhibited lower systematic error. Multisampling suprathreshold paradigms may be a powerful alternative to other strategies of visual field testing. Clinical trials are needed to verify these findings.

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.

Navigating a Mobile Robot Across Terrain Using Fuzzy Logic

NASA Technical Reports Server (NTRS)

Seraji, Homayoun; Howard, Ayanna; Bon, Bruce

2003-01-01

A strategy for autonomous navigation of a robotic vehicle across hazardous terrain involves the use of a measure of traversability of terrain within a fuzzy-logic conceptual framework. This navigation strategy requires no a priori information about the environment. Fuzzy logic was selected as a basic element of this strategy because it provides a formal methodology for representing and implementing a human driver s heuristic knowledge and operational experience. Within a fuzzy-logic framework, the attributes of human reasoning and decision- making can be formulated by simple IF (antecedent), THEN (consequent) rules coupled with easily understandable and natural linguistic representations. The linguistic values in the rule antecedents convey the imprecision associated with measurements taken by sensors onboard a mobile robot, while the linguistic values in the rule consequents represent the vagueness inherent in the reasoning processes to generate the control actions. The operational strategies of the human expert driver can be transferred, via fuzzy logic, to a robot-navigation strategy in the form of a set of simple conditional statements composed of linguistic variables. These linguistic variables are defined by fuzzy sets in accordance with user-defined membership functions. The main advantages of a fuzzy navigation strategy lie in the ability to extract heuristic rules from human experience and to obviate the need for an analytical model of the robot navigation process.

Multi-objective Extremum Seeking Control for Enhancement of Wind Turbine Power Capture with Load Reduction

NASA Astrophysics Data System (ADS)

Xiao, Yan; Li, Yaoyu; Rotea, Mario A.

2016-09-01

The primary objective in below rated wind speed (Region 2) is to maximize the turbine's energy capture. Due to uncertainty, variability of turbine characteristics and lack of inexpensive but precise wind measurements, model-free control strategies that do not use wind measurements such as Extremum Seeking Control (ESC) have received significant attention. Based on a dither-demodulation scheme, ESC can maximize the wind power capture in real time despite uncertainty, variabilities and lack of accurate wind measurements. The existing work on ESC based wind turbine control focuses on power capture only. In this paper, a multi-objective extremum seeking control strategy is proposed to achieve nearly optimum wind energy capture while decreasing structural fatigue loads. The performance index of the ESC combines the rotor power and penalty terms of the standard deviations of selected fatigue load variables. Simulation studies of the proposed multi-objective ESC demonstrate that the damage-equivalent loads of tower and/or blade loads can be reduced with slight compromise in energy capture.

Predicting short-term positive affect in individuals with social anxiety disorder: The role of selected personality traits and emotion regulation strategies.

PubMed

Weisman, Jaclyn S; Rodebaugh, Thomas L; Lim, Michelle H; Fernandez, Katya C

2015-08-01

Recently, research has provided support for a moderate, inverse relationship between social anxiety and dispositional positive affect. However, the dynamics of this relationship remain poorly understood. The present study evaluates whether certain personality traits and emotion regulation variables predict short-term positive affect for individuals with social anxiety disorder and healthy controls. Positive affect as measured by two self-report instruments was assessed before and after two tasks in which the participant conversed with either a friend or a romantic partner. Tests of models examining the hypothesized prospective predictors revealed that the paths did not differ significantly across diagnostic group and both groups showed the hypothesized patterns of endorsement for the emotion regulation variables. Further, a variable reflecting difficulty redirecting oneself when distressed prospectively predicted one measure of positive affect. Additional research is needed to explore further the role of emotion regulation strategies on positive emotions for individuals higher in social anxiety. Copyright © 2015 Elsevier Ltd. All rights reserved.

Evidence-based mapping of design heterogeneity prior to meta-analysis: a systematic review and evidence synthesis.

PubMed

Althuis, Michelle D; Weed, Douglas L; Frankenfeld, Cara L

2014-07-23

Assessment of design heterogeneity conducted prior to meta-analysis is infrequently reported; it is often presented post hoc to explain statistical heterogeneity. However, design heterogeneity determines the mix of included studies and how they are analyzed in a meta-analysis, which in turn can importantly influence the results. The goal of this work is to introduce ways to improve the assessment and reporting of design heterogeneity prior to statistical summarization of epidemiologic studies. In this paper, we use an assessment of sugar-sweetened beverages (SSB) and type 2 diabetes (T2D) as an example to show how a technique called 'evidence mapping' can be used to organize studies and evaluate design heterogeneity prior to meta-analysis.. Employing a systematic and reproducible approach, we evaluated the following elements across 11 selected cohort studies: variation in definitions of SSB, T2D, and co-variables, design features and population characteristics associated with specific definitions of SSB, and diversity in modeling strategies. Evidence mapping strategies effectively organized complex data and clearly depicted design heterogeneity. For example, across 11 studies of SSB and T2D, 7 measured diet only once (with 7 to 16 years of disease follow-up), 5 included primarily low SSB consumers, and 3 defined the study variable (SSB) as consumption of either sugar or artificially-sweetened beverages. This exercise also identified diversity in analysis strategies, such as adjustment for 11 to 17 co-variables and a large degree of fluctuation in SSB-T2D risk estimates depending on variables selected for multivariable models (2 to 95% change in the risk estimate from the age-adjusted model). Meta-analysis seeks to understand heterogeneity in addition to computing a summary risk estimate. This strategy effectively documents design heterogeneity, thus improving the practice of meta-analysis by aiding in: 1) protocol and analysis planning, 2) transparent reporting of differences in study designs, and 3) interpretation of pooled estimates. We recommend expanding the practice of meta-analysis reporting to include a table that summarizes design heterogeneity. This would provide readers with more evidence to interpret the summary risk estimates.

Evidence-based mapping of design heterogeneity prior to meta-analysis: a systematic review and evidence synthesis

PubMed Central

2014-01-01

Background Assessment of design heterogeneity conducted prior to meta-analysis is infrequently reported; it is often presented post hoc to explain statistical heterogeneity. However, design heterogeneity determines the mix of included studies and how they are analyzed in a meta-analysis, which in turn can importantly influence the results. The goal of this work is to introduce ways to improve the assessment and reporting of design heterogeneity prior to statistical summarization of epidemiologic studies. Methods In this paper, we use an assessment of sugar-sweetened beverages (SSB) and type 2 diabetes (T2D) as an example to show how a technique called ‘evidence mapping’ can be used to organize studies and evaluate design heterogeneity prior to meta-analysis.. Employing a systematic and reproducible approach, we evaluated the following elements across 11 selected cohort studies: variation in definitions of SSB, T2D, and co-variables, design features and population characteristics associated with specific definitions of SSB, and diversity in modeling strategies. Results Evidence mapping strategies effectively organized complex data and clearly depicted design heterogeneity. For example, across 11 studies of SSB and T2D, 7 measured diet only once (with 7 to 16 years of disease follow-up), 5 included primarily low SSB consumers, and 3 defined the study variable (SSB) as consumption of either sugar or artificially-sweetened beverages. This exercise also identified diversity in analysis strategies, such as adjustment for 11 to 17 co-variables and a large degree of fluctuation in SSB-T2D risk estimates depending on variables selected for multivariable models (2 to 95% change in the risk estimate from the age-adjusted model). Conclusions Meta-analysis seeks to understand heterogeneity in addition to computing a summary risk estimate. This strategy effectively documents design heterogeneity, thus improving the practice of meta-analysis by aiding in: 1) protocol and analysis planning, 2) transparent reporting of differences in study designs, and 3) interpretation of pooled estimates. We recommend expanding the practice of meta-analysis reporting to include a table that summarizes design heterogeneity. This would provide readers with more evidence to interpret the summary risk estimates. PMID:25055879

[Cardiac rhythm variability as an index of vegetative heart regulation in a situation of psychoemotional tension].

PubMed

Revina, N E

2006-01-01

Differentiated role of segmental and suprasegmental levels of cardiac rhythm variability regulation in dynamics of motivational human conflict was studied for the first time. The author used an original method allowing simultaneous analysis of psychological and physiological parameters of human activity. The study demonstrates that will and anxiety, as components of motivational activity spectrum, form the "energetic" basis of voluntary-constructive and involuntary-affective behavioral strategies, selectively uniting various levels of suprasegmental and segmental control of human heart functioning in a conflict situation.

The Infant Motor Profile: A Standardized and Qualitative Method to Assess Motor Behaviour in Infancy

ERIC Educational Resources Information Center

Heineman, Kirsten R.; Bos, Arend F.; Hadders-Algra, Mijna

2008-01-01

A reliable and valid instrument to assess neuromotor condition in infancy is a prerequisite for early detection of developmental motor disorders. We developed a video-based assessment of motor behaviour, the Infant Motor Profile (IMP), to evaluate motor abilities, movement variability, ability to select motor strategies, movement symmetry, and…

Gender, College Major Selections, Classifications within Majors, and Its Relationship with Locus of Control: An Empirical Evidence for Counseling Educators

ERIC Educational Resources Information Center

Jemi-Alade, Tunji

2008-01-01

To help counselors develop strategies to enhance students' social, personal, and psychological well-being, this research provides an understanding of how students perceive their environment. Specifically examining graduate and undergraduate students, the researcher was concerned with ascertaining the effect of the college-major variable (Business…

Use of ENSO forecasts to select nitrogen fertilizer application strategies for winter

USDA-ARS?s Scientific Manuscript database

El Niño Southern Oscillation (ENSO) has a strong impact on winter crops in Alabama (AL). Wheat is basically grown during winter as cash crop and sometimes also as fodder or grain crop in AL. Thus, it is very necessary to understand the impact of variability in climate factors due to the different ph...

A Robust Decision-Making Technique for Water Management under Decadal Scale Climate Variability

NASA Astrophysics Data System (ADS)

Callihan, L.; Zagona, E. A.; Rajagopalan, B.

2013-12-01

Robust decision making, a flexible and dynamic approach to managing water resources in light of deep uncertainties associated with climate variability at inter-annual to decadal time scales, is an analytical framework that detects when a system is in or approaching a vulnerable state. It provides decision makers the opportunity to implement strategies that both address the vulnerabilities and perform well over a wide range of plausible future scenarios. A strategy that performs acceptably over a wide range of possible future states is not likely to be optimal with respect to the actual future state. The degree of success--the ability to avoid vulnerable states and operate efficiently--thus depends on the skill in projecting future states and the ability to select the most efficient strategies to address vulnerabilities. This research develops a robust decision making framework that incorporates new methods of decadal scale projections with selection of efficient strategies. Previous approaches to water resources planning under inter-annual climate variability combining skillful seasonal flow forecasts with climatology for subsequent years are not skillful for medium term (i.e. decadal scale) projections as decision makers are not able to plan adequately to avoid vulnerabilities. We address this need by integrating skillful decadal scale streamflow projections into the robust decision making framework and making the probability distribution of this projection available to the decision making logic. The range of possible future hydrologic scenarios can be defined using a variety of nonparametric methods. Once defined, an ensemble projection of decadal flow scenarios are generated from a wavelet-based spectral K-nearest-neighbor resampling approach using historical and paleo-reconstructed data. This method has been shown to generate skillful medium term projections with a rich variety of natural variability. The current state of the system in combination with the probability distribution of the projected flow ensembles enables the selection of appropriate decision options. This process is repeated for each year of the planning horizon--resulting in system outcomes that can be evaluated on their performance and resiliency. The research utilizes the RiverSMART suite of software modeling and analysis tools developed under the Bureau of Reclamation's WaterSMART initiative and built around the RiverWare modeling environment. A case study is developed for the Gunnison and Upper Colorado River Basins. The ability to mitigate vulnerability using the framework is gauged by system performance indicators that measure the ability of the system to meet various water demands (i.e. agriculture, environmental flows, hydropower etc.). Options and strategies for addressing vulnerabilities include measures such as conservation, reallocation and adjustments to operational policy. In addition to being able to mitigate vulnerabilities, options and strategies are evaluated based on benefits, costs and reliability. Flow ensembles are also simulated to incorporate mean and variance from climate change projections for the planning horizon and the above robust decision-making framework is applied to evaluate its performance under changing climate.

Economic evaluation of genomic selection in small ruminants: a sheep meat breeding program.

PubMed

Shumbusho, F; Raoul, J; Astruc, J M; Palhiere, I; Lemarié, S; Fugeray-Scarbel, A; Elsen, J M

2016-06-01

Recent genomic evaluation studies using real data and predicting genetic gain by modeling breeding programs have reported moderate expected benefits from the replacement of classic selection schemes by genomic selection (GS) in small ruminants. The objectives of this study were to compare the cost, monetary genetic gain and economic efficiency of classic selection and GS schemes in the meat sheep industry. Deterministic methods were used to model selection based on multi-trait indices from a sheep meat breeding program. Decisional variables related to male selection candidates and progeny testing were optimized to maximize the annual monetary genetic gain (AMGG), that is, a weighted sum of meat and maternal traits annual genetic gains. For GS, a reference population of 2000 individuals was assumed and genomic information was available for evaluation of male candidates only. In the classic selection scheme, males breeding values were estimated from own and offspring phenotypes. In GS, different scenarios were considered, differing by the information used to select males (genomic only, genomic+own performance, genomic+offspring phenotypes). The results showed that all GS scenarios were associated with higher total variable costs than classic selection (if the cost of genotyping was 123 euros/animal). In terms of AMGG and economic returns, GS scenarios were found to be superior to classic selection only if genomic information was combined with their own meat phenotypes (GS-Pheno) or with their progeny test information. The predicted economic efficiency, defined as returns (proportional to number of expressions of AMGG in the nucleus and commercial flocks) minus total variable costs, showed that the best GS scenario (GS-Pheno) was up to 15% more efficient than classic selection. For all selection scenarios, optimization increased the overall AMGG, returns and economic efficiency. As a conclusion, our study shows that some forms of GS strategies are more advantageous than classic selection, provided that GS is already initiated (i.e. the initial reference population is available). Optimizing decisional variables of the classic selection scheme could be of greater benefit than including genomic information in optimized designs.

SOC Strategies and Organizational Citizenship Behaviors toward the Benefits of Co-workers: A Multi-Source Study.

PubMed

Müller, Andreas; Weigl, Matthias

2017-01-01

Background: Individuals' behavioral strategies like selection, optimization, and compensation (SOC) contribute to efficient use of available resources. In the work context, previous studies revealed positive associations between employees' SOC use and favorable individual outcomes, like engagement and job performance. However, the social implications of self-directed behaviors like SOC that are favorable for the employee but may imply consequences for coworkers have not been investigated yet in an interpersonal work context. Objective: This study aimed to assess associations between employees' use of SOC behaviors at work and their organizational citizenship behaviors (OCB) toward the benefits of co-workers rated by their peers at work. We further sought to identify age-specific associations between SOC use and OCB. Design and Method: A cross-sectional design combining multi-source data was applied in primary school teachers (age range: 23-58 years) who frequently teach in dyads. N = 114 dyads were finally included. Teachers reported on their SOC strategies at work. Their peer colleagues evaluated teachers' OCB. Control variables were gender, workload, working hours, and perceived proximity of relationship between the dyads. Results: We observed a positive effect of loss-based selection behaviors on peer-rated OCB. Moreover, there was a significant two-way interaction effect between the use of compensation strategies and age on OCB, such that there was a positive association for older employees and a negative association for younger employees. There were no significant main and age-related interaction effects of elective selection, optimization, and of overall SOC strategies on OCB. Conclusion: Our study suggests that high use of loss-based selection and high use of compensation strategies in older employees is positively related with OCB as perceived by their colleagues. However, high use of compensation strategies in younger employees is perceived negatively related with OCB. Our findings contribute to a better understanding of the age-differentiated interpersonal effects of successful aging strategies in terms of SOC in organizations.

SOC Strategies and Organizational Citizenship Behaviors toward the Benefits of Co-workers: A Multi-Source Study

PubMed Central

Müller, Andreas; Weigl, Matthias

2017-01-01

Background: Individuals’ behavioral strategies like selection, optimization, and compensation (SOC) contribute to efficient use of available resources. In the work context, previous studies revealed positive associations between employees’ SOC use and favorable individual outcomes, like engagement and job performance. However, the social implications of self-directed behaviors like SOC that are favorable for the employee but may imply consequences for coworkers have not been investigated yet in an interpersonal work context. Objective: This study aimed to assess associations between employees’ use of SOC behaviors at work and their organizational citizenship behaviors (OCB) toward the benefits of co-workers rated by their peers at work. We further sought to identify age-specific associations between SOC use and OCB. Design and Method: A cross-sectional design combining multi-source data was applied in primary school teachers (age range: 23–58 years) who frequently teach in dyads. N = 114 dyads were finally included. Teachers reported on their SOC strategies at work. Their peer colleagues evaluated teachers’ OCB. Control variables were gender, workload, working hours, and perceived proximity of relationship between the dyads. Results: We observed a positive effect of loss-based selection behaviors on peer-rated OCB. Moreover, there was a significant two-way interaction effect between the use of compensation strategies and age on OCB, such that there was a positive association for older employees and a negative association for younger employees. There were no significant main and age-related interaction effects of elective selection, optimization, and of overall SOC strategies on OCB. Conclusion: Our study suggests that high use of loss-based selection and high use of compensation strategies in older employees is positively related with OCB as perceived by their colleagues. However, high use of compensation strategies in younger employees is perceived negatively related with OCB. Our findings contribute to a better understanding of the age-differentiated interpersonal effects of successful aging strategies in terms of SOC in organizations. PMID:29085315

Purposeful Variable Selection and Stratification to Impute Missing FAST Data in Trauma Research

PubMed Central

Fuchs, Paul A.; del Junco, Deborah J.; Fox, Erin E.; Holcomb, John B.; Rahbar, Mohammad H.; Wade, Charles A.; Alarcon, Louis H.; Brasel, Karen J.; Bulger, Eileen M.; Cohen, Mitchell J.; Myers, John G.; Muskat, Peter; Phelan, Herb A.; Schreiber, Martin A.; Cotton, Bryan A.

2013-01-01

Background The Focused Assessment with Sonography for Trauma (FAST) exam is an important variable in many retrospective trauma studies. The purpose of this study was to devise an imputation method to overcome missing data for the FAST exam. Due to variability in patients’ injuries and trauma care, these data are unlikely to be missing completely at random (MCAR), raising concern for validity when analyses exclude patients with missing values. Methods Imputation was conducted under a less restrictive, more plausible missing at random (MAR) assumption. Patients with missing FAST exams had available data on alternate, clinically relevant elements that were strongly associated with FAST results in complete cases, especially when considered jointly. Subjects with missing data (32.7%) were divided into eight mutually exclusive groups based on selected variables that both described the injury and were associated with missing FAST values. Additional variables were selected within each group to classify missing FAST values as positive or negative, and correct FAST exam classification based on these variables was determined for patients with non-missing FAST values. Results Severe head/neck injury (odds ratio, OR=2.04), severe extremity injury (OR=4.03), severe abdominal injury (OR=1.94), no injury (OR=1.94), other abdominal injury (OR=0.47), other head/neck injury (OR=0.57) and other extremity injury (OR=0.45) groups had significant ORs for missing data; the other group odds ratio was not significant (OR=0.84). All 407 missing FAST values were imputed, with 109 classified as positive. Correct classification of non-missing FAST results using the alternate variables was 87.2%. Conclusions Purposeful imputation for missing FAST exams based on interactions among selected variables assessed by simple stratification may be a useful adjunct to sensitivity analysis in the evaluation of imputation strategies under different missing data mechanisms. This approach has the potential for widespread application in clinical and translational research and validation is warranted. Level of Evidence Level II Prognostic or Epidemiological PMID:23778515

A review of selection-based tests of abiotic surrogates for species representation.

PubMed

Beier, Paul; Sutcliffe, Patricia; Hjort, Jan; Faith, Daniel P; Pressey, Robert L; Albuquerque, Fabio

2015-06-01

Because conservation planners typically lack data on where species occur, environmental surrogates--including geophysical settings and climate types--have been used to prioritize sites within a planning area. We reviewed 622 evaluations of the effectiveness of abiotic surrogates in representing species in 19 study areas. Sites selected using abiotic surrogates represented more species than an equal number of randomly selected sites in 43% of tests (55% for plants) and on average improved on random selection of sites by about 8% (21% for plants). Environmental diversity (ED) (42% median improvement on random selection) and biotically informed clusters showed promising results and merit additional testing. We suggest 4 ways to improve performance of abiotic surrogates. First, analysts should consider a broad spectrum of candidate variables to define surrogates, including rarely used variables related to geographic separation, distance from coast, hydrology, and within-site abiotic diversity. Second, abiotic surrogates should be defined at fine thematic resolution. Third, sites (the landscape units prioritized within a planning area) should be small enough to ensure that surrogates reflect species' environments and to produce prioritizations that match the spatial resolution of conservation decisions. Fourth, if species inventories are available for some planning units, planners should define surrogates based on the abiotic variables that most influence species turnover in the planning area. Although species inventories increase the cost of using abiotic surrogates, a modest number of inventories could provide the data needed to select variables and evaluate surrogates. Additional tests of nonclimate abiotic surrogates are needed to evaluate the utility of conserving nature's stage as a strategy for conservation planning in the face of climate change. © 2015 Society for Conservation Biology.

Message Variability and Heterogeneity: A Core Challenge for Communication Research

PubMed Central

Slater, Michael D.; Peter, Jochen; Valkenberg, Patti

2015-01-01

Messages are central to human social experience, and pose key conceptual and methodological challenges in the study of communication. In response to these challenges, we outline a systematic approach to conceptualizing, operationalizing, and analyzing messages. At the conceptual level, we distinguish between two core aspects of messages: message variability (the defined and operationalized features of messages) and message heterogeneity (the undefined and unmeasured features of messages), and suggest preferred approaches to defining message variables. At the operational level, we identify message sampling, selection, and research design strategies responsive to issues of message variability and heterogeneity in experimental and survey research. At the analytical level, we highlight effective techniques to deal with message variability and heterogeneity. We conclude with seven recommendations to increase rigor in the study of communication through appropriately addressing the challenges presented by messages. PMID:26681816

Firstline treatment for chronic phase chronic myeloid leukemia patients should be based on a holistic approach.

PubMed

Breccia, Massimo; Alimena, Giuliana

2015-02-01

New selective and more potent drugs for the cure of chronic phase chronic myeloid leukemia patients are now available: physicians in some countries must decide the best option, selecting one of the drugs available. What the main prognostic factors are in order to make this selection remains a matter of discussion. Introducing a 'holistic approach' for the first time in chronic myeloid leukemia, as practiced in other diseases, and looking at the patient in a complete picture, considering several variables, such as comorbidities, age, concomitant drugs, lifestyle and patient expectations, may be of help to understand, patient by patient, the best therapeutic strategy.

Evolution in plant populations as a driver of ecological changes in arthropod communities

PubMed Central

Johnson, Marc T.J.; Vellend, Mark; Stinchcombe, John R.

2009-01-01

Heritable variation in traits can have wide-ranging impacts on species interactions, but the effects that ongoing evolution has on the temporal ecological dynamics of communities are not well understood. Here, we identify three conditions that, if experimentally satisfied, support the hypothesis that evolution by natural selection can drive ecological changes in communities. These conditions are: (i) a focal population exhibits genetic variation in a trait(s), (ii) there is measurable directional selection on the trait(s), and (iii) the trait(s) under selection affects variation in a community variable(s). When these conditions are met, we expect evolution by natural selection to cause ecological changes in the community. We tested these conditions in a field experiment examining the interactions between a native plant (Oenothera biennis) and its associated arthropod community (more than 90 spp.). Oenothera biennis exhibited genetic variation in several plant traits and there was directional selection on plant biomass, life-history strategy (annual versus biennial reproduction) and herbivore resistance. Genetically based variation in biomass and life-history strategy consistently affected the abundance of common arthropod species, total arthropod abundance and arthropod species richness. Using two modelling approaches, we show that evolution by natural selection in large O. biennis populations is predicted to cause changes in the abundance of individual arthropod species, increases in the total abundance of arthropods and a decline in the number of arthropod species. In small O. biennis populations, genetic drift is predicted to swamp out the effects of selection, making the evolution of plant populations unpredictable. In short, evolution by natural selection can play an important role in affecting the dynamics of communities, but these effects depend on several ecological factors. The framework presented here is general and can be applied to other systems to examine the community-level effects of ongoing evolution. PMID:19414473

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.

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.

Turning science on robust cattle into improved genetic selection decisions.

PubMed

Amer, P R

2012-04-01

More robust cattle have the potential to increase farm profitability, improve animal welfare, reduce the contribution of ruminant livestock to greenhouse gas emissions and decrease the risk of food shortages in the face of increased variability in the farm environment. Breeding is a powerful tool for changing the robustness of cattle; however, insufficient recording of breeding goal traits and selection of animals at younger ages tend to favour genetic change in productivity traits relative to robustness traits. This paper has extended a previously proposed theory of artificial evolution to demonstrate, using deterministic simulation, how choice of breeding scheme design can be used as a tool to manipulate the direction of genetic progress, whereas the breeding goal remains focussed on the factors motivating individual farm decision makers. Particular focus was placed on the transition from progeny testing or mass selection to genomic selection breeding strategies. Transition to genomic selection from a breeding strategy where candidates are selected before records from progeny being available was shown to be highly likely to favour genetic progress in robustness traits relative to productivity traits. This was shown even with modest numbers of animals available for training and when heritability for robustness traits was only slightly lower than that for productivity traits. When transitioning from progeny testing to a genomic selection strategy without progeny testing, it was shown that there is a significant risk that robustness traits could become less influential in selection relative to productivity traits. Augmentations of training populations using genotyped cows and support for industry-wide improvements in phenotypic recording of robustness traits were put forward as investment opportunities for stakeholders wishing to facilitate the application of science on robust cattle into improved genetic selection schemes.

Project To Design a Marketing Plan for Promoting Educators' Awareness of and Access to ERIC Products. Proposed Marketing Plan.

ERIC Educational Resources Information Center

Contemporary Associates, Inc., Washington, DC.

The proposed strategy, which is designed to maximize the effectiveness and minimize the costs of marketing the Information Analysis Products (IAPs) produced by the 16 ERIC Clearinghouses, is based on a study of the concept of centralized versus decentralized ordering of selected ERIC products. The experiment measured four variables--postage,…

How to evade a coevolving brood parasite: egg discrimination versus egg variability as host defences.

PubMed

Spottiswoode, Claire N; Stevens, Martin

2011-12-07

Arms races between avian brood parasites and their hosts often result in parasitic mimicry of host eggs, to evade rejection. Once egg mimicry has evolved, host defences could escalate in two ways: (i) hosts could improve their level of egg discrimination; and (ii) negative frequency-dependent selection could generate increased variation in egg appearance (polymorphism) among individuals. Proficiency in one defence might reduce selection on the other, while a combination of the two should enable successful rejection of parasitic eggs. We compared three highly variable host species of the Afrotropical cuckoo finch Anomalospiza imberbis, using egg rejection experiments and modelling of avian colour and pattern vision. We show that each differed in their level of polymorphism, in the visual cues they used to reject foreign eggs, and in their degree of discrimination. The most polymorphic host had the crudest discrimination, whereas the least polymorphic was most discriminating. The third species, not currently parasitized, was intermediate for both defences. A model simulating parasitic laying and host rejection behaviour based on the field experiments showed that the two host strategies result in approximately the same fitness advantage to hosts. Thus, neither strategy is superior, but rather they reflect alternative potential evolutionary trajectories.

The Role of Body Size in Mate Selection among African American Young Adults

PubMed Central

Simons, Leslie G.; Simons, Ronald L.

2016-01-01

A profusion of studies have demonstrated that body size is a major factor in mate selection for both men and women. The particular role played by weight, however, has been subject to some debate, particularly with respect to the types of body sizes deemed most attractive, and scholars have questioned the degree to which body size preferences are constant across groups. In this paper, we drew from two perspectives on this issue, Sexual Strategies Theory and what we termed the cultural variability perspective, and used survey data to examine how body size was associated with both casual dating and serious romantic relationships. We used a United States sample of 386 African American adolescents and young adults between ages 16 and 21, living in the Midwest and Southeast, and who were enrolled in either high school or college. Results showed that overweight women were more likely to report casually dating than women in the thinnest weight category. Body size was not related to dating status among men. Among women, the results suggest stronger support for the cultural variability argument than for Sexual Strategies Theory. Potential explanations for these findings are discussed. PMID:26973377

Male reproductive strategy explains spatiotemporal segregation in brown bears

PubMed Central

Steyaert, Sam MJG; Kindberg, Jonas; Swenson, Jon E; Zedrosser, Andreas

2013-01-01

1. Spatiotemporal segregation is often explained by the risk for offspring predation or by differences in physiology, predation risk vulnerability or competitive abilities related to size dimorphism. 2. Most large carnivores are size dimorphic and offspring predation is often intraspecific and related to nonparental infanticide (NPI). NPI can be a foraging strategy, a strategy to reduce competition, or a male reproductive strategy. Spatiotemporal segregation is widespread among large carnivores, but its nature remains poorly understood. 3. We evaluated three hypotheses to explain spatiotemporal segregation in the brown bear, a size-dimorphic large carnivore in which NPI is common; the ‘NPI – foraging/competition hypothesis', i.e. NPI as a foraging strategy or a strategy to reduce competition, the ‘NPI – sexual selection hypothesis’, i.e. infanticide as a male reproductive strategy and the ‘body size hypothesis’, i.e. body-size-related differences in physiology, predation risk vulnerability or competitive ability causes spatiotemporal segregation. To test these hypotheses, we quantified spatiotemporal segregation among adult males, lone adult females and females with cubs-of-the-year, based on GPS-relocation data (2006–2010) and resource selection functions in a Scandinavian population. 4. We found that spatiotemporal segregation was strongest between females with cubs-of-the-year and adult males during the mating season. During the mating season, females with cubs-of-the-year selected their resources, in contrast to adult males, in less rugged landscapes in relative close proximity to certain human-related variables, and in more open habitat types. After the mating season, females with cubs-of-the-year markedly shifted their resource selection towards a pattern more similar to that of their conspecifics. No strong spatiotemporal segregation was apparent between females with cubs-of-the-year and conspecifics during the mating and the postmating season. 5. The ‘NPI – sexual selection hypothesis’ best explained spatiotemporal segregation in our study system. We suggest that females with cubs-of-the-year alter their resource selection to avoid infanticidal males. In species exhibiting NPI as a male reproductive strategy, female avoidance of infanticidal males is probably more common than observed or reported, and may come with a fitness cost if females trade safety for optimal resources. PMID:23461483

ASTRAL-R score predicts non-recanalisation after intravenous thrombolysis in acute ischaemic stroke.

PubMed

Vanacker, Peter; Heldner, Mirjam R; Seiffge, David; Mueller, Hubertus; Eskandari, Ashraf; Traenka, Christopher; Ntaios, George; Mosimann, Pascal J; Sztajzel, Roman; Mendes Pereira, Vitor; Cras, Patrick; Engelter, Stefan; Lyrer, Philippe; Fischer, Urs; Lambrou, Dimitris; Arnold, Marcel; Michel, Patrik

2015-05-01

Intravenous thrombolysis (IVT) as treatment in acute ischaemic strokes may be insufficient to achieve recanalisation in certain patients. Predicting probability of non-recanalisation after IVT may have the potential to influence patient selection to more aggressive management strategies. We aimed at deriving and internally validating a predictive score for post-thrombolytic non-recanalisation, using clinical and radiological variables. In thrombolysis registries from four Swiss academic stroke centres (Lausanne, Bern, Basel and Geneva), patients were selected with large arterial occlusion on acute imaging and with repeated arterial assessment at 24 hours. Based on a logistic regression analysis, an integer-based score for each covariate of the fitted multivariate model was generated. Performance of integer-based predictive model was assessed by bootstrapping available data and cross validation (delete-d method). In 599 thrombolysed strokes, five variables were identified as independent predictors of absence of recanalisation: Acute glucose > 7 mmol/l (A), significant extracranial vessel STenosis (ST), decreased Range of visual fields (R), large Arterial occlusion (A) and decreased Level of consciousness (L). All variables were weighted 1, except for (L) which obtained 2 points based on β-coefficients on the logistic scale. ASTRAL-R scores 0, 3 and 6 corresponded to non-recanalisation probabilities of 18, 44 and 74 % respectively. Predictive ability showed AUC of 0.66 (95 %CI, 0.61-0.70) when using bootstrap and 0.66 (0.63-0.68) when using delete-d cross validation. In conclusion, the 5-item ASTRAL-R score moderately predicts non-recanalisation at 24 hours in thrombolysed ischaemic strokes. If its performance can be confirmed by external validation and its clinical usefulness can be proven, the score may influence patient selection for more aggressive revascularisation strategies in routine clinical practice.

FT-MIR and NIR spectral data fusion: a synergetic strategy for the geographical traceability of Panax notoginseng.

PubMed

Li, Yun; Zhang, Jin-Yu; Wang, Yuan-Zhong

2018-01-01

Three data fusion strategies (low-llevel, mid-llevel, and high-llevel) combined with a multivariate classification algorithm (random forest, RF) were applied to authenticate the geographical origins of Panax notoginseng collected from five regions of Yunnan province in China. In low-level fusion, the original data from two spectra (Fourier transform mid-IR spectrum and near-IR spectrum) were directly concatenated into a new matrix, which then was applied for the classification. Mid-level fusion was the strategy that inputted variables extracted from the spectral data into an RF classification model. The extracted variables were processed by iterate variable selection of the RF model and principal component analysis. The use of high-level fusion combined the decision making of each spectroscopic technique and resulted in an ensemble decision. The results showed that the mid-level and high-level data fusion take advantage of the information synergy from two spectroscopic techniques and had better classification performance than that of independent decision making. High-level data fusion is the most effective strategy since the classification results are better than those of the other fusion strategies: accuracy rates ranged between 93% and 96% for the low-level data fusion, between 95% and 98% for the mid-level data fusion, and between 98% and 100% for the high-level data fusion. In conclusion, the high-level data fusion strategy for Fourier transform mid-IR and near-IR spectra can be used as a reliable tool for correct geographical identification of P. notoginseng. Graphical abstract The analytical steps of Fourier transform mid-IR and near-IR spectral data fusion for the geographical traceability of Panax notoginseng.

Cognitive Strategies and Physical Activity in Older Adults: A Discriminant Analysis

PubMed Central

Ferrand, Claude; Audiffren, Michel

2018-01-01

Background Although a number of studies have examined sociodemographic, psychosocial, and environmental determinants of the level of physical activity (PA) for older people, little attention has been paid to the predictive power of cognitive strategies for independently living older adults. However, cognitive strategies have recently been considered to be critical in the management of day-to-day living. Methods Data were collected from 243 men and women aged 55 years and older living in France using face-to-face interviews between 2011 and 2013. Results A stepwise discriminant analysis selected five predictor variables (age, perceived health status, barriers' self-efficacy, internal memory, and attentional control strategies) of the level of PA. The function showed that the rate of correct prediction was 73% for the level of PA. The calculated discriminant function based on the five predictor variables is useful for detecting individuals at high risk of lapses once engaged in regular PA. Conclusions This study highlighted the need to consider cognitive functions as a determinant of the level of PA and, more specifically, those cognitive functions related to executive functions (internal memory and attentional control), to facilitate the maintenance of regular PA. These results are discussed in relation to successful aging. PMID:29850247

Cognitive Strategies and Physical Activity in Older Adults: A Discriminant Analysis.

PubMed

André, Nathalie; Ferrand, Claude; Albinet, Cédric; Audiffren, Michel

2018-01-01

Although a number of studies have examined sociodemographic, psychosocial, and environmental determinants of the level of physical activity (PA) for older people, little attention has been paid to the predictive power of cognitive strategies for independently living older adults. However, cognitive strategies have recently been considered to be critical in the management of day-to-day living. Data were collected from 243 men and women aged 55 years and older living in France using face-to-face interviews between 2011 and 2013. A stepwise discriminant analysis selected five predictor variables (age, perceived health status, barriers' self-efficacy, internal memory, and attentional control strategies) of the level of PA. The function showed that the rate of correct prediction was 73% for the level of PA. The calculated discriminant function based on the five predictor variables is useful for detecting individuals at high risk of lapses once engaged in regular PA. This study highlighted the need to consider cognitive functions as a determinant of the level of PA and, more specifically, those cognitive functions related to executive functions (internal memory and attentional control), to facilitate the maintenance of regular PA. These results are discussed in relation to successful aging.

The evolution of parental cooperation in birds.

PubMed

Remeš, Vladimír; Freckleton, Robert P; Tökölyi, Jácint; Liker, András; Székely, Tamás

2015-11-03

Parental care is one of the most variable social behaviors and it is an excellent model system to understand cooperation between unrelated individuals. Three major hypotheses have been proposed to explain the extent of parental cooperation: sexual selection, social environment, and environmental harshness. Using the most comprehensive dataset on parental care that includes 659 bird species from 113 families covering both uniparental and biparental taxa, we show that the degree of parental cooperation is associated with both sexual selection and social environment. Consistent with recent theoretical models parental cooperation decreases with the intensity of sexual selection and with skewed adult sex ratios. These effects are additive and robust to the influence of life-history variables. However, parental cooperation is unrelated to environmental factors (measured at the scale of whole species ranges) as indicated by a lack of consistent relationship with ambient temperature, rainfall or their fluctuations within and between years. These results highlight the significance of social effects for parental cooperation and suggest that several parental strategies may coexist in a given set of ambient environment.

Natural sequence variants of yeast environmental sensors confer cell-to-cell expression variability

PubMed Central

Fehrmann, Steffen; Bottin-Duplus, Hélène; Leonidou, Andri; Mollereau, Esther; Barthelaix, Audrey; Wei, Wu; Steinmetz, Lars M; Yvert, Gaël

2013-01-01

Living systems may have evolved probabilistic bet hedging strategies that generate cell-to-cell phenotypic diversity in anticipation of environmental catastrophes, as opposed to adaptation via a deterministic response to environmental changes. Evolution of bet hedging assumes that genotypes segregating in natural populations modulate the level of intraclonal diversity, which so far has largely remained hypothetical. Using a fluorescent Pmet17-GFP reporter, we mapped four genetic loci conferring to a wild yeast strain an elevated cell-to-cell variability in the expression of MET17, a gene regulated by the methionine pathway. A frameshift mutation in the Erc1p transmembrane transporter, probably resulting from a release of laboratory strains from negative selection, reduced Pmet17-GFP expression variability. At a second locus, cis-regulatory polymorphisms increased mean expression of the Mup1p methionine permease, causing increased expression variability in trans. These results demonstrate that an expression quantitative trait locus (eQTL) can simultaneously have a deterministic effect in cis and a probabilistic effect in trans. Our observations indicate that the evolution of transmembrane transporter genes can tune intraclonal variation and may therefore be implicated in both reactive and anticipatory strategies of adaptation. PMID:24104478

Effects of age on long-term outcomes after a routine invasive or selective invasive strategy in patients presenting with non-ST segment elevation acute coronary syndromes: a collaborative analysis of individual data from the FRISC II - ICTUS - RITA-3 (FIR) trials.

PubMed

Damman, Peter; Clayton, Tim; Wallentin, Lars; Lagerqvist, Bo; Fox, Keith A A; Hirsch, Alexander; Windhausen, Fons; Swahn, Eva; Pocock, Stuart J; Tijssen, Jan G P; de Winter, Robbert J

2012-02-01

To perform a patient-pooled analysis of a routine invasive versus a selective invasive strategy in elderly patients with non-ST segment elevation acute coronary syndrome. A meta-analysis was performed of patient-pooled data from the FRISC II-ICTUS-RITA-3 (FIR) studies. (Un)adjusted HRs were calculated by Cox regression, with adjustments for variables associated with age and outcomes. The main outcome was 5-year cardiovascular death or myocardial infarction (MI) following routine invasive versus selective invasive management. Regarding the 5-year composite of cardiovascular death or MI, the routine invasive strategy was associated with a lower hazard in patients aged 65-74 years (HR 0.72, 95% CI 0.58 to 0.90) and those aged ≥75 years (HR 0.71, 95% CI 0.55 to 0.91), but not in those aged <65 years (HR 1.11, 95% CI 0.90 to 1.38), p=0.001 for interaction between treatment strategy and age. The interaction was driven by an excess of early MIs in patients <65 years of age; there was no heterogeneity between age groups concerning cardiovascular death. The benefits were smaller for women than for men (p=0.009 for interaction). After adjustment for other clinical risk factors the HRs remained similar. The current analysis of the FIR dataset shows that the long-term benefit of the routine invasive strategy over the selective invasive strategy is attenuated in younger patients aged <65 years and in women by the increased risk of early events which seem to have no consequences for long-term cardiovascular mortality. No other clinical risk factors were able to identify patients with differential responses to a routine invasive strategy. Trial registration http://www.controlled-trials.com/ISRCTN82153174 (ICTUS), http://www.controlled-trials.com/ISRCTN07752711 (RITA-3).

Exploratory Spectroscopy of Magnetic Cataclysmic Variables Candidates and Other Variable Objects

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

Oliveira, A. S.; Palhares, M. S.; Rodrigues, C. V.

2017-04-01

The increasing number of synoptic surveys made by small robotic telescopes, such as the photometric Catalina Real-Time Transient Survey (CRTS), provides a unique opportunity to discover variable sources and improves the statistical samples of such classes of objects. Our goal is the discovery of magnetic Cataclysmic Variables (mCVs). These are rare objects that probe interesting accretion scenarios controlled by the white-dwarf magnetic field. In particular, improved statistics of mCVs would help to address open questions on their formation and evolution. We performed an optical spectroscopy survey to search for signatures of magnetic accretion in 45 variable objects selected mostly from themore » CRTS. In this sample, we found 32 CVs, 22 being mCV candidates, 13 of which were previously unreported as such. If the proposed classifications are confirmed, it would represent an increase of 4% in the number of known polars and 12% in the number of known IPs. A fraction of our initial sample was classified as extragalactic sources or other types of variable stars by the inspection of the identification spectra. Despite the inherent complexity in identifying a source as an mCV, variability-based selection, followed by spectroscopic snapshot observations, has proved to be an efficient strategy for their discoveries, being a relatively inexpensive approach in terms of telescope time.« less

A soft computing based approach using modified selection strategy for feature reduction of medical systems.

PubMed

Zuhtuogullari, Kursat; Allahverdi, Novruz; Arikan, Nihat

2013-01-01

The systems consisting high input spaces require high processing times and memory usage. Most of the attribute selection algorithms have the problems of input dimensions limits and information storage problems. These problems are eliminated by means of developed feature reduction software using new modified selection mechanism with middle region solution candidates adding. The hybrid system software is constructed for reducing the input attributes of the systems with large number of input variables. The designed software also supports the roulette wheel selection mechanism. Linear order crossover is used as the recombination operator. In the genetic algorithm based soft computing methods, locking to the local solutions is also a problem which is eliminated by using developed software. Faster and effective results are obtained in the test procedures. Twelve input variables of the urological system have been reduced to the reducts (reduced input attributes) with seven, six, and five elements. It can be seen from the obtained results that the developed software with modified selection has the advantages in the fields of memory allocation, execution time, classification accuracy, sensitivity, and specificity values when compared with the other reduction algorithms by using the urological test data.

A Soft Computing Based Approach Using Modified Selection Strategy for Feature Reduction of Medical Systems

PubMed Central

Zuhtuogullari, Kursat; Allahverdi, Novruz; Arikan, Nihat

2013-01-01

The systems consisting high input spaces require high processing times and memory usage. Most of the attribute selection algorithms have the problems of input dimensions limits and information storage problems. These problems are eliminated by means of developed feature reduction software using new modified selection mechanism with middle region solution candidates adding. The hybrid system software is constructed for reducing the input attributes of the systems with large number of input variables. The designed software also supports the roulette wheel selection mechanism. Linear order crossover is used as the recombination operator. In the genetic algorithm based soft computing methods, locking to the local solutions is also a problem which is eliminated by using developed software. Faster and effective results are obtained in the test procedures. Twelve input variables of the urological system have been reduced to the reducts (reduced input attributes) with seven, six, and five elements. It can be seen from the obtained results that the developed software with modified selection has the advantages in the fields of memory allocation, execution time, classification accuracy, sensitivity, and specificity values when compared with the other reduction algorithms by using the urological test data. PMID:23573172

Dynamic habitat selection by two wading bird species with divergent foraging strategies in a seasonally fluctuating wetland

USGS Publications Warehouse

Beerens, James M.; Gawlik, Dale E.; Herring, Garth; Cook, Mark I.

2011-01-01

Seasonal and annual variation in food availability during the breeding season plays an influential role in the population dynamics of many avian species. In highly dynamic ecosystems like wetlands, finding and exploiting food resources requires a flexible behavioral response that may produce different population trends that vary with a species' foraging strategy. We quantified dynamic foraging-habitat selection by breeding and radiotagged White Ibises (Eudocimus albus) and Great Egrets (Ardea alba) in the Florida Everglades, where fluctuation in food resources is pronounced because of seasonal drying and flooding. The White Ibis is a tactile “searcher” species in population decline that specializes on highly concentrated prey, whereas the Great Egret, in a growing population, is a visual “exploiter” species that requires lower prey concentrations. In a year with high food availability, resource-selection functions for both species included variables that changed over multiannual time scales and were associated with increased prey production. In a year with low food availability, resource-selection functions included short-term variables that concentrated prey (e.g., water recession rates and reversals in drying pattern), which suggests an adaptive response to poor foraging conditions. In both years, the White Ibis was more restricted in its use of habitats than the Great Egret. Real-time species—habitat suitability models were developed to monitor and assess the daily availability and quality of spatially explicit habitat resources for both species. The models, evaluated through hindcasting using independent observations, demonstrated that habitat use of the more specialized White Ibis was more accurately predicted than that of the more generalist Great Egret.

Intervention strategies for spatial orientation disorders in dementia: a selective review.

PubMed

Caffò, Alessandro O; Hoogeveen, Frans; Groenendaal, Mari; Perilli, Anna Viviana; Picucci, Luciana; Lancioni, Giulio E; Bosco, Andrea

2014-06-01

This article provides a brief overview of the intervention strategies aimed at reducing spatial orientation disorders in elderly people with dementia. Eight experimental studies using spatial cues, assistive technology programs, reality orientation training, errorless learning technique, and backward chaining programs are described. They can be classified into two main approaches: restorative and compensatory, depending on whether they rely or not on residual learning ability, respectively. A review of the efficacy of these intervention strategies is proposed. Results suggest that both compensatory and restorative approaches may be valuable in enhancing correct way-finding behavior, with various degrees of effectiveness. Some issues concerning (a) variability in participants' characteristics and experimental designs and (b) practicality of intervention strategies do not permit to draw a definite conclusion. Future research should be aimed at a direct comparison between these two strategies, and should incorporate an extensive neuropsychological assessment of spatial domain.

Application of multivariable statistical techniques in plant-wide WWTP control strategies analysis.

PubMed

Flores, X; Comas, J; Roda, I R; Jiménez, L; Gernaey, K V

2007-01-01

The main objective of this paper is to present the application of selected multivariable statistical techniques in plant-wide wastewater treatment plant (WWTP) control strategies analysis. In this study, cluster analysis (CA), principal component analysis/factor analysis (PCA/FA) and discriminant analysis (DA) are applied to the evaluation matrix data set obtained by simulation of several control strategies applied to the plant-wide IWA Benchmark Simulation Model No 2 (BSM2). These techniques allow i) to determine natural groups or clusters of control strategies with a similar behaviour, ii) to find and interpret hidden, complex and casual relation features in the data set and iii) to identify important discriminant variables within the groups found by the cluster analysis. This study illustrates the usefulness of multivariable statistical techniques for both analysis and interpretation of the complex multicriteria data sets and allows an improved use of information for effective evaluation of control strategies.

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.

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.

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 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.

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.

Predictors for Physical Activity in Adolescent Girls Using Statistical Shrinkage Techniques for Hierarchical Longitudinal Mixed Effects Models

PubMed Central

Grant, Edward M.; Young, Deborah Rohm; Wu, Tong Tong

2015-01-01

We examined associations among longitudinal, multilevel variables and girls’ physical activity to determine the important predictors for physical activity change at different adolescent ages. The Trial of Activity for Adolescent Girls 2 study (Maryland) contributed participants from 8th (2009) to 11th grade (2011) (n=561). Questionnaires were used to obtain demographic, and psychosocial information (individual- and social-level variables); height, weight, and triceps skinfold to assess body composition; interviews and surveys for school-level data; and self-report for neighborhood-level variables. Moderate to vigorous physical activity minutes were assessed from accelerometers. A doubly regularized linear mixed effects model was used for the longitudinal multilevel data to identify the most important covariates for physical activity. Three fixed effects at the individual level and one random effect at the school level were chosen from an initial total of 66 variables, consisting of 47 fixed effects and 19 random effects variables, in additional to the time effect. Self-management strategies, perceived barriers, and social support from friends were the three selected fixed effects, and whether intramural or interscholastic programs were offered in middle school was the selected random effect. Psychosocial factors and friend support, plus a school’s physical activity environment, affect adolescent girl’s moderate to vigorous physical activity longitudinally. PMID:25928064

Data-driven process decomposition and robust online distributed modelling for large-scale processes

NASA Astrophysics Data System (ADS)

Shu, Zhang; Lijuan, Li; Lijuan, Yao; Shipin, Yang; Tao, Zou

2018-02-01

With the increasing attention of networked control, system decomposition and distributed models show significant importance in the implementation of model-based control strategy. In this paper, a data-driven system decomposition and online distributed subsystem modelling algorithm was proposed for large-scale chemical processes. The key controlled variables are first partitioned by affinity propagation clustering algorithm into several clusters. Each cluster can be regarded as a subsystem. Then the inputs of each subsystem are selected by offline canonical correlation analysis between all process variables and its controlled variables. Process decomposition is then realised after the screening of input and output variables. When the system decomposition is finished, the online subsystem modelling can be carried out by recursively block-wise renewing the samples. The proposed algorithm was applied in the Tennessee Eastman process and the validity was verified.

Maternal source of variability in the embryo development of an annual killifish.

PubMed

Polačik, M; Smith, C; Reichard, M

2017-04-01

Organisms inhabiting unpredictable environments often evolve diversified reproductive bet-hedging strategies, expressed as production of multiple offspring phenotypes, thereby avoiding complete reproductive failure. To cope with unpredictable rainfall, African annual killifish from temporary savannah pools lay drought-resistant eggs that vary widely in the duration of embryo development. We examined the sources of variability in the duration of individual embryo development, egg production and fertilization rate in Nothobranchius furzeri. Using a quantitative genetics approach (North Carolina type II design), we found support for maternal effects rather than polyandrous mating as the primary source of the variability in the duration of embryo development. The number of previously laid eggs appeared to serve as an internal physiological cue initiating a shift from rapid-to-slow embryo developmental mode. In annual killifish, extensive phenotypic variability in progeny traits is adaptive, as the conditions experienced by parents have limited relevance to the offspring generation. In contrast to genetic control, with high phenotypic expression and heritability, maternal control of traits under natural selection prevents standing genetic diversity from potentially detrimental effects of selection in fluctuating environments. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European Society For Evolutionary Biology.

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.

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.

Hydrologic filtering of fish life history strategies across the United States: implications for stream flow alteration

DOE PAGES

McManamay, Ryan A.; Frimpong, Emmanuel A.

2015-01-01

Lotic fish have developed life history strategies adapted to the natural variation in stream flow regimes. The natural timing, duration, and magnitude of flow events has contributed to the diversity, production, and composition of fish assemblages over time. Studies evaluating the role of hydrology in structuring fish assemblages have been more common at the local or regional scale with very few studies conducted at the continental scale. Furthermore, quantitative linkages between natural hydrologic patterns and fish assemblages are rarely used to make predictions of ecological consequences of hydrologic alterations. We ask two questions: (1) what is the relative role ofmore » hydrology in structuring fish assemblages at large scales? and (2) can relationships between fish assemblages and natural hydrology be utilized to predict fish assemblage responses to hydrologic disturbance? We developed models to relate fish life histories and reproductive strategies to landscape and hydrologic variables separately and then combined. Models were then used to predict the ecological consequences of altered hydrology due to dam regulation. Although hydrology plays a considerable role in structuring fish assemblages, the performance of models using only hydrologic variables was lower than that of models constructed using landscape variables. Isolating the relative importance of hydrology in structuring fish assemblages at the continental scale is difficult since hydrology is interrelated to many landscape factors. By applying models to dam-regulated hydrologic data, we observed some consistent predicted responses in fish life history strategies and modes of reproduction. In agreement with existing literature, equilibrium strategists are predicted to increase following dam regulation, whereas opportunistic and periodic species are predicted to decrease. In addition, dam regulation favors the selection of reproductive strategies with extended spawning seasons and preference for stable conditions.« less

Hydrologic filtering of fish life history strategies across the United States: implications for stream flow alteration

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

McManamay, Ryan A.; Frimpong, Emmanuel A.

Lotic fish have developed life history strategies adapted to the natural variation in stream flow regimes. The natural timing, duration, and magnitude of flow events has contributed to the diversity, production, and composition of fish assemblages over time. Studies evaluating the role of hydrology in structuring fish assemblages have been more common at the local or regional scale with very few studies conducted at the continental scale. Furthermore, quantitative linkages between natural hydrologic patterns and fish assemblages are rarely used to make predictions of ecological consequences of hydrologic alterations. We ask two questions: (1) what is the relative role ofmore » hydrology in structuring fish assemblages at large scales? and (2) can relationships between fish assemblages and natural hydrology be utilized to predict fish assemblage responses to hydrologic disturbance? We developed models to relate fish life histories and reproductive strategies to landscape and hydrologic variables separately and then combined. Models were then used to predict the ecological consequences of altered hydrology due to dam regulation. Although hydrology plays a considerable role in structuring fish assemblages, the performance of models using only hydrologic variables was lower than that of models constructed using landscape variables. Isolating the relative importance of hydrology in structuring fish assemblages at the continental scale is difficult since hydrology is interrelated to many landscape factors. By applying models to dam-regulated hydrologic data, we observed some consistent predicted responses in fish life history strategies and modes of reproduction. In agreement with existing literature, equilibrium strategists are predicted to increase following dam regulation, whereas opportunistic and periodic species are predicted to decrease. In addition, dam regulation favors the selection of reproductive strategies with extended spawning seasons and preference for stable conditions.« less

Cognitive strategies regulate fictive, but not reward prediction error signals in a sequential investment task.

PubMed

Gu, Xiaosi; Kirk, Ulrich; Lohrenz, Terry M; Montague, P Read

2014-08-01

Computational models of reward processing suggest that foregone or fictive outcomes serve as important information sources for learning and augment those generated by experienced rewards (e.g. reward prediction errors). An outstanding question is how these learning signals interact with top-down cognitive influences, such as cognitive reappraisal strategies. Using a sequential investment task and functional magnetic resonance imaging, we show that the reappraisal strategy selectively attenuates the influence of fictive, but not reward prediction error signals on investment behavior; such behavioral effect is accompanied by changes in neural activity and connectivity in the anterior insular cortex, a brain region thought to integrate subjective feelings with high-order cognition. Furthermore, individuals differ in the extent to which their behaviors are driven by fictive errors versus reward prediction errors, and the reappraisal strategy interacts with such individual differences; a finding also accompanied by distinct underlying neural mechanisms. These findings suggest that the variable interaction of cognitive strategies with two important classes of computational learning signals (fictive, reward prediction error) represent one contributing substrate for the variable capacity of individuals to control their behavior based on foregone rewards. These findings also expose important possibilities for understanding the lack of control in addiction based on possibly foregone rewarding outcomes. Copyright © 2013 The Authors. Human Brain Mapping Published by Wiley Periodicals, Inc.

[Rapid assessment of critical quality attributes of Chinese materia medica (II): strategy of NIR assignment].

PubMed

Pei, Yan-Ling; Wu, Zhi-Sheng; Shi, Xin-Yuan; Zhou, Lu-Wei; Qiao, Yan-Jiang

2014-09-01

The present paper firstly reviewed the research progress and main methods of NIR spectral assignment coupled with our research results. Principal component analysis was focused on characteristic signal extraction to reflect spectral differences. Partial least squares method was concerned with variable selection to discover characteristic absorption band. Two-dimensional correlation spectroscopy was mainly adopted for spectral assignment. Autocorrelation peaks were obtained from spectral changes, which were disturbed by external factors, such as concentration, temperature and pressure. Density functional theory was used to calculate energy from substance structure to establish the relationship between molecular energy and spectra change. Based on the above reviewed method, taking a NIR spectral assignment of chlorogenic acid as example, a reliable spectral assignment for critical quality attributes of Chinese materia medica (CMM) was established using deuterium technology and spectral variable selection. The result demonstrated the assignment consistency according to spectral features of different concentrations of chlorogenic acid and variable selection region of online NIR model in extract process. Although spectral assignment was initial using an active pharmaceutical ingredient, it is meaningful to look forward to the futurity of the complex components in CMM. Therefore, it provided methodology for NIR spectral assignment of critical quality attributes in CMM.

Effects of Three Sets of Instructional Strategies and Three Demographic Variables on the Food and Nutrition Test Performance of Some Jamaican Tenth-Graders

ERIC Educational Resources Information Center

Kelly, Dennis; Soyibo, Kola

2005-01-01

This study was designed to find out if students taught food and nutrition concepts using the lecture method and practical work would perform significantly better than their counterparts taught with the lecture and teacher demonstrations and the lecture method only. The sample comprised 114 Jamaican 10th-graders (56 boys, 58 girls) selected from…

Genomic analysis and selected molecular pathways in rare cancers

NASA Astrophysics Data System (ADS)

Liu, Stephen V.; Lenkiewicz, Elizabeth; Evers, Lisa; Holley, Tara; Kiefer, Jeffrey; Ruiz, Christian; Glatz, Katharina; Bubendorf, Lukas; Demeure, Michael J.; Eng, Cathy; Ramanathan, Ramesh K.; Von Hoff, Daniel D.; Barrett, Michael T.

2012-12-01

It is widely accepted that many cancers arise as a result of an acquired genomic instability and the subsequent evolution of tumor cells with variable patterns of selected and background aberrations. The presence and behaviors of distinct neoplastic cell populations within a patient's tumor may underlie multiple clinical phenotypes in cancers. A goal of many current cancer genome studies is the identification of recurring selected driver events that can be advanced for the development of personalized therapies. Unfortunately, in the majority of rare tumors, this type of analysis can be particularly challenging. Large series of specimens for analysis are simply not available, allowing recurring patterns to remain hidden. In this paper, we highlight the use of DNA content-based flow sorting to identify and isolate DNA-diploid and DNA-aneuploid populations from tumor biopsies as a strategy to comprehensively study the genomic composition and behaviors of individual cancers in a series of rare solid tumors: intrahepatic cholangiocarcinoma, anal carcinoma, adrenal leiomyosarcoma, and pancreatic neuroendocrine tumors. We propose that the identification of highly selected genomic events in distinct tumor populations within each tumor can identify candidate driver events that can facilitate the development of novel, personalized treatment strategies for patients with cancer.

Genomic analysis and selected molecular pathways in rare cancers.

PubMed

Liu, Stephen V; Lenkiewicz, Elizabeth; Evers, Lisa; Holley, Tara; Kiefer, Jeffrey; Ruiz, Christian; Glatz, Katharina; Bubendorf, Lukas; Demeure, Michael J; Eng, Cathy; Ramanathan, Ramesh K; Von Hoff, Daniel D; Barrett, Michael T

2012-12-01

It is widely accepted that many cancers arise as a result of an acquired genomic instability and the subsequent evolution of tumor cells with variable patterns of selected and background aberrations. The presence and behaviors of distinct neoplastic cell populations within a patient's tumor may underlie multiple clinical phenotypes in cancers. A goal of many current cancer genome studies is the identification of recurring selected driver events that can be advanced for the development of personalized therapies. Unfortunately, in the majority of rare tumors, this type of analysis can be particularly challenging. Large series of specimens for analysis are simply not available, allowing recurring patterns to remain hidden. In this paper, we highlight the use of DNA content-based flow sorting to identify and isolate DNA-diploid and DNA-aneuploid populations from tumor biopsies as a strategy to comprehensively study the genomic composition and behaviors of individual cancers in a series of rare solid tumors: intrahepatic cholangiocarcinoma, anal carcinoma, adrenal leiomyosarcoma, and pancreatic neuroendocrine tumors. We propose that the identification of highly selected genomic events in distinct tumor populations within each tumor can identify candidate driver events that can facilitate the development of novel, personalized treatment strategies for patients with cancer.

Pacing in Swimming: A Systematic Review.

PubMed

McGibbon, Katie E; Pyne, D B; Shephard, M E; Thompson, K G

2018-03-20

Pacing strategy, or how energy is distributed during exercise, can substantially impact athletic performance and is considered crucial for optimal performance in many sports. This is particularly true in swimming given the highly resistive properties of water and low mechanical efficiency of the swimming action. The aim of this systematic review was to determine the pacing strategies utilised by competitive swimmers in competition and their reproducibility, and to examine the impact of different pacing strategies on kinematic, metabolic and performance variables. This will provide valuable and practical information to coaches and sports science practitioners. The databases Web of Science, Scopus, SPORTDiscus and PubMed were searched for published articles up to 1 August 2017. A total of 23 studies examining pool-based swimming competitions or experimental trials in English-language and peer-reviewed journals were included in this review. In short- and middle-distance swimming events maintenance of swimming velocity is critical, whereas in long-distance events a low lap-to-lap variability and the ability to produce an end spurt in the final lap(s) are key. The most effective strategy in the individual medley (IM) is to conserve energy during the butterfly leg to optimise performance in subsequent legs. The pacing profiles of senior swimmers remain relatively stable irrespective of opponents, competition stage or type, and performance time. Implementing event-specific pacing strategies should benefit the performance of competitive swimmers. Given differences between swimmers, there is a need for greater individualisation when considering pacing strategy selection across distances and strokes.

A simulation/optimization study to assess seawater intrusion management strategies for the Gaza Strip coastal aquifer (Palestine)

NASA Astrophysics Data System (ADS)

Dentoni, Marta; Deidda, Roberto; Paniconi, Claudio; Qahman, Khalid; Lecca, Giuditta

2015-03-01

Seawater intrusion is one of the major threats to freshwater resources in coastal areas, often exacerbated by groundwater overexploitation. Mitigation measures are needed to properly manage aquifers, and to restore groundwater quality. This study integrates three computational tools into a unified framework to investigate seawater intrusion in coastal areas and to assess strategies for managing groundwater resources under natural and human-induced stresses. The three components are a three-dimensional hydrogeological model for density-dependent variably saturated flow and miscible salt transport, an automatic calibration procedure that uses state variable outputs from the model to estimate selected model parameters, and an optimization module that couples a genetic algorithm with the simulation model. The computational system is used to rank alternative strategies for mitigation of seawater intrusion, taking into account conflicting objectives and problem constraints. It is applied to the Gaza Strip (Palestine) coastal aquifer to identify a feasible groundwater management strategy for the period 2011-2020. The optimized solution is able to: (1) keep overall future abstraction from municipal groundwater wells close to the user-defined maximum level, (2) increase the average groundwater heads, and (3) lower both the total mass of salt extracted and the extent of the areas affected by seawater intrusion.

Comprehensive Modeling and Analysis of Rotorcraft Variable Speed Propulsion System With Coupled Engine/Transmission/Rotor Dynamics

NASA Technical Reports Server (NTRS)

DeSmidt, Hans A.; Smith, Edward C.; Bill, Robert C.; Wang, Kon-Well

2013-01-01

This project develops comprehensive modeling and simulation tools for analysis of variable rotor speed helicopter propulsion system dynamics. The Comprehensive Variable-Speed Rotorcraft Propulsion Modeling (CVSRPM) tool developed in this research is used to investigate coupled rotor/engine/fuel control/gearbox/shaft/clutch/flight control system dynamic interactions for several variable rotor speed mission scenarios. In this investigation, a prototypical two-speed Dual-Clutch Transmission (DCT) is proposed and designed to achieve 50 percent rotor speed variation. The comprehensive modeling tool developed in this study is utilized to analyze the two-speed shift response of both a conventional single rotor helicopter and a tiltrotor drive system. In the tiltrotor system, both a Parallel Shift Control (PSC) strategy and a Sequential Shift Control (SSC) strategy for constant and variable forward speed mission profiles are analyzed. Under the PSC strategy, selecting clutch shift-rate results in a design tradeoff between transient engine surge margins and clutch frictional power dissipation. In the case of SSC, clutch power dissipation is drastically reduced in exchange for the necessity to disengage one engine at a time which requires a multi-DCT drive system topology. In addition to comprehensive simulations, several sections are dedicated to detailed analysis of driveline subsystem components under variable speed operation. In particular an aeroelastic simulation of a stiff in-plane rotor using nonlinear quasi-steady blade element theory was conducted to investigate variable speed rotor dynamics. It was found that 2/rev and 4/rev flap and lag vibrations were significant during resonance crossings with 4/rev lagwise loads being directly transferred into drive-system torque disturbances. To capture the clutch engagement dynamics, a nonlinear stick-slip clutch torque model is developed. Also, a transient gas-turbine engine model based on first principles mean-line compressor and turbine approximations is developed. Finally an analysis of high frequency gear dynamics including the effect of tooth mesh stiffness variation under variable speed operation is conducted including experimental validation. Through exploring the interactions between the various subsystems, this investigation provides important insights into the continuing development of variable-speed rotorcraft propulsion systems.

Variable speed generator application on the MOD-5A 7.3 mW wind turbine generator

NASA Technical Reports Server (NTRS)

Barton, Robert S.

1995-01-01

This paper describes the application of a Scherbiustat type variable speed subsystem in the MOD-5A Wind Turbine Generator. As designed by General Electric Company, Advanced Energy Programs Department, under contract DEN3-153 with NASA Lewis Research Center and DOE, the MOD-5A utilizes the subsystem for both starting assistance in a motoring mode and generation in a controlled airgap torque mode. Reactive power control is also provided. The Scherbiustat type arrangement of a wound rotor machine with a cycloconverter in the rotor circuit was selected after an evaluation of variable speed technologies that followed a system evaluation of drivetrain cost and risk. The paper describes the evaluation factors considered, the results of the evaluations and summarizes operating strategy and performance simulations.

Quality of search strategies reported in systematic reviews published in stereotactic radiosurgery.

PubMed

Faggion, Clovis M; Wu, Yun-Chun; Tu, Yu-Kang; Wasiak, Jason

2016-06-01

Systematic reviews require comprehensive literature search strategies to avoid publication bias. This study aimed to assess and evaluate the reporting quality of search strategies within systematic reviews published in the field of stereotactic radiosurgery (SRS). Three electronic databases (Ovid MEDLINE(®), Ovid EMBASE(®) and the Cochrane Library) were searched to identify systematic reviews addressing SRS interventions, with the last search performed in October 2014. Manual searches of the reference lists of included systematic reviews were conducted. The search strategies of the included systematic reviews were assessed using a standardized nine-question form based on the Cochrane Collaboration guidelines and Assessment of Multiple Systematic Reviews checklist. Multiple linear regression analyses were performed to identify the important predictors of search quality. A total of 85 systematic reviews were included. The median quality score of search strategies was 2 (interquartile range = 2). Whilst 89% of systematic reviews reported the use of search terms, only 14% of systematic reviews reported searching the grey literature. Multiple linear regression analyses identified publication year (continuous variable), meta-analysis performance and journal impact factor (continuous variable) as predictors of higher mean quality scores. This study identified the urgent need to improve the quality of search strategies within systematic reviews published in the field of SRS. This study is the first to address how authors performed searches to select clinical studies for inclusion in their systematic reviews. Comprehensive and well-implemented search strategies are pivotal to reduce the chance of publication bias and consequently generate more reliable systematic review findings.

Predicting Bobsled Pushing Ability from Various Combine Testing Events.

PubMed

Tomasevicz, Curtis L; Ransone, Jack W; Bach, Christopher W

2018-03-12

The requisite combination of speed, power, and strength necessary for a bobsled push athlete coupled with the difficulty in directly measuring pushing ability makes selecting effective push crews challenging. Current practices by USA Bobsled and Skeleton (USABS) utilize field combine testing to assess and identify specifically selected performance variables in an attempt to best predict push performance abilities. Combine data consisting of 11 physical performance variables were collected from 75 subjects across two winter Olympic qualification years (2009 and 2013). These variables were sprints of 15-, 30-, and 60 m, a flying 30 m sprint, a standing broad jump, a shot toss, squat, power clean, body mass, and dry-land brake and side bobsled pushes. Discriminant Analysis (DA) in addition to Principle Component Analysis (PCA) was used to investigate two cases (Case 1: Olympians vs. non-Olympians; Case 2: National Team vs. non-National Team). Using these 11 variables, DA led to a classification rule that proved capable of identifying Olympians from non-Olympians and National Team members from non-National Team members with 9.33% and 14.67% misclassification rates, respectively. The PCA was used to find similar test variables within the combine that provided redundant or useless data. After eliminating the unnecessary variables, DA on the new combinations showed that 8 (Case 1) and 20 (Case 2) other combinations with fewer performance variables yielded misclassification rates as low as 6.67% and 13.33% respectively. Utilizing fewer performance variables can allow governing bodies in many other sports to create more appropriate combine testing that maximize accuracy, while minimizing irrelevant and redundant strategies.

Genetic parameters and path analysis in cowpea genotypes grown in the Cerrado/Pantanal ecotone.

PubMed

Lopes, K V; Teodoro, P E; Silva, F A; Silva, M T; Fernandes, R L; Rodrigues, T C; Faria, T C; Corrêa, A M

2017-05-18

Estimating genetic parameters in plant breeding allows us to know the population potential for selecting and designing strategies that can maximize the achievement of superior genotypes. The objective of this study was to evaluate the genetic potential of a population of 20 cowpea genotypes by estimating genetic parameters and path analysis among the traits to guide the selection strategies. The trial was conducted in randomized block design with four replications. Its morphophysiological components, components of green grain production and dry grain yield were estimated from genetic use and correlations between the traits. Phenotypic correlations were deployed through path analysis into direct and indirect effects of morphophysiological traits and yield components on dry grain yield. There were significant differences (P < 0.01) between the genotypes for most the traits, indicating the presence of genetic variability in the population and the possibility of practicing selection. The population presents the potential for future genetic breeding studies and is highly promising for the selection of traits dry grain yield, the number of grains per pod, and hundred grains mass. A number of grains per green pod is the main determinant trait of dry grain yield that is also influenced by the cultivar cycle and that the selection for the dry grain yield can be made indirectly by selecting the green pod mass and green pod length.

Optimizing selection of training and auxiliary data for operational land cover classification for the LCMAP initiative

NASA Astrophysics Data System (ADS)

Zhu, Zhe; Gallant, Alisa L.; Woodcock, Curtis E.; Pengra, Bruce; Olofsson, Pontus; Loveland, Thomas R.; Jin, Suming; Dahal, Devendra; Yang, Limin; Auch, Roger F.

2016-12-01

The U.S. Geological Survey's Land Change Monitoring, Assessment, and Projection (LCMAP) initiative is a new end-to-end capability to continuously track and characterize changes in land cover, use, and condition to better support research and applications relevant to resource management and environmental change. Among the LCMAP product suite are annual land cover maps that will be available to the public. This paper describes an approach to optimize the selection of training and auxiliary data for deriving the thematic land cover maps based on all available clear observations from Landsats 4-8. Training data were selected from map products of the U.S. Geological Survey's Land Cover Trends project. The Random Forest classifier was applied for different classification scenarios based on the Continuous Change Detection and Classification (CCDC) algorithm. We found that extracting training data proportionally to the occurrence of land cover classes was superior to an equal distribution of training data per class, and suggest using a total of 20,000 training pixels to classify an area about the size of a Landsat scene. The problem of unbalanced training data was alleviated by extracting a minimum of 600 training pixels and a maximum of 8000 training pixels per class. We additionally explored removing outliers contained within the training data based on their spectral and spatial criteria, but observed no significant improvement in classification results. We also tested the importance of different types of auxiliary data that were available for the conterminous United States, including: (a) five variables used by the National Land Cover Database, (b) three variables from the cloud screening "Function of mask" (Fmask) statistics, and (c) two variables from the change detection results of CCDC. We found that auxiliary variables such as a Digital Elevation Model and its derivatives (aspect, position index, and slope), potential wetland index, water probability, snow probability, and cloud probability improved the accuracy of land cover classification. Compared to the original strategy of the CCDC algorithm (500 pixels per class), the use of the optimal strategy improved the classification accuracies substantially (15-percentage point increase in overall accuracy and 4-percentage point increase in minimum accuracy).

Design and Application of Drought Indexes in Highly Regulated Mediterranean Water Systems

NASA Astrophysics Data System (ADS)

Castelletti, A.; Zaniolo, M.; Giuliani, M.

2017-12-01

Costs of drought are progressively increasing due to the undergoing alteration of hydro-meteorological regimes induced by climate change. Although drought management is largely studied in the literature, most of the traditional drought indexes fail in detecting critical events in highly regulated systems, which generally rely on ad-hoc formulations and cannot be generalized to different context. In this study, we contribute a novel framework for the design of a basin-customized drought index. This index represents a surrogate of the state of the basin and is computed by combining the available information about the water available in the system to reproduce a representative target variable for the drought condition of the basin (e.g., water deficit). To select the relevant variables and combinatione thereof, we use an advanced feature extraction algorithm called Wrapper for Quasi Equally Informative Subset Selection (W-QEISS). W-QEISS relies on a multi-objective evolutionary algorithm to find Pareto-efficient subsets of variables by maximizing the wrapper accuracy, minimizing the number of selected variables, and optimizing relevance and redundancy of the subset. The accuracy objective is evaluated trough the calibration of an extreme learning machine of the water deficit for each candidate subset of variables, with the index selected from the resulting solutions identifying a suitable compromise between accuracy, cardinality, relevance, and redundancy. The approach is tested on Lake Como, Italy, a regulated lake mainly operated for irrigation supply. In the absence of an institutional drought monitoring system, we constructed the combined index using all the hydrological variables from the existing monitoring system as well as common drought indicators at multiple time aggregations. The soil moisture deficit in the root zone computed by a distributed-parameter water balance model of the agricultural districts is used as target variable. Numerical results show that our combined drought index succesfully reproduces the deficit. The index represents a valuable information for supporting appropriate drought management strategies, including the possibility of directly informing the lake operations about the drought conditions and improve the overall reliability of the irrigation supply system.

Analysis of Decentralized Variable Structure Control for Collective Search by Mobile Robots

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

Feddema, J.; Goldsmith, S.; Robinett, R.

1998-11-04

This paper presents an analysis of a decentralized coordination strategy for organizing and controlling a team of mobile robots performing collective search. The alpha-beta coordination strategy is a family of collective search algorithms that allow teams of communicating robots to implicitly coordinate their search activities through a division of labor based on self-selected roIes. In an alpha-beta team. alpha agents are motivated to improve their status by exploring new regions of the search space. Beta a~ents are conservative, and reiy on the alpha agents to provide advanced information on favorable regions of the search space. An agent selects its currentmore » role dynamically based on its current status value relative to the current status values of the other team members. Status is determined by some function of the agent's sensor readings, and is generally a measurement of source intensity at the agent's current location. Variations on the decision rules determining alpha and beta behavior produce different versions of the algorithm that lead to different global properties. The alpha-beta strategy is based on a simple finite-state machine that implements a form of Variable Structure Control (VSC). The VSC system changes the dynamics of the collective system by abruptly switching at defined states to alternative control laws . In VSC, Lyapunov's direct method is often used to design control surfaces which guide the system to a given goal. We introduce the alpha-beta aIgorithm and present an analysis of the equilibrium point and the global stability of the alpha-beta algorithm based on Lyapunov's method.« less

Analysis of decentralized variable structure control for collective search by mobile robots

NASA Astrophysics Data System (ADS)

Goldsmith, Steven Y.; Feddema, John T.; Robinett, Rush D., III

1998-10-01

This paper presents an analysis of a decentralized coordination strategy for organizing and controlling a team of mobile robots performing collective search. The alpha- beta coordination strategy is a family of collective search algorithms that allow teams of communicating robots to implicitly coordinate their search activities through a division of labor based on self-selected roles. In an alpha- beta team, alpha agents are motivated to improve their status by exploring new regions of the search space. Beta agents are conservative, and rely on the alpha agents to provide advanced information on favorable regions of the search space. An agent selects its current role dynamically based on its current status value relative to the current status values of the other team members. Status is determined by some function of the agent's sensor readings, and is generally a measurement of source intensity at the agent's current location. Variations on the decision rules determining alpha and beta behavior produce different versions of the algorithm that lead to different global properties. The alpha-beta strategy is based on a simple finite-state machine that implements a form of Variable Structure Control (VSC). The VSC system changes the dynamics of the collective system by abruptly switching at defined states to alternative control laws. In VSC, Lyapunov's direct method is often used to design control surfaces which guide the system to a given goal. We introduce the alpha- beta algorithm and present an analysis of the equilibrium point and the global stability of the alpha-beta algorithm based on Lyapunov's method.

Reactibodies generated by kinetic selection couple chemical reactivity with favorable protein dynamics

PubMed Central

Smirnov, Ivan; Carletti, Eugénie; Kurkova, Inna; Nachon, Florian; Nicolet, Yvain; Mitkevich, Vladimir A.; Débat, Hélène; Avalle, Bérangère; Belogurov, Alexey A.; Kuznetsov, Nikita; Reshetnyak, Andrey; Masson, Patrick; Tonevitsky, Alexander G.; Ponomarenko, Natalia; Makarov, Alexander A.; Friboulet, Alain; Tramontano, Alfonso; Gabibov, Alexander

2011-01-01

Igs offer a versatile template for combinatorial and rational design approaches to the de novo creation of catalytically active proteins. We have used a covalent capture selection strategy to identify biocatalysts from within a human semisynthetic antibody variable fragment library that uses a nucleophilic mechanism. Specific phosphonylation at a single tyrosine within the variable light-chain framework was confirmed in a recombinant IgG construct. High-resolution crystallographic structures of unmodified and phosphonylated Fabs display a 15-Å-deep two-chamber cavity at the interface of variable light (VL) and variable heavy (VH) fragments having a nucleophilic tyrosine at the base of the site. The depth and structure of the pocket are atypical of antibodies in general but can be compared qualitatively with the catalytic site of cholinesterases. A structurally disordered heavy chain complementary determining region 3 loop, constituting a wall of the cleft, is stabilized after covalent modification by hydrogen bonding to the phosphonate tropinol moiety. These features and presteady state kinetics analysis indicate that an induced fit mechanism operates in this reaction. Mutations of residues located in this stabilized loop do not interfere with direct contacts to the organophosphate ligand but can interrogate second shell interactions, because the H3 loop has a conformation adjusted for binding. Kinetic and thermodynamic parameters along with computational docking support the active site model, including plasticity and simple catalytic components. Although relatively uncomplicated, this catalytic machinery displays both stereo- and chemical selectivity. The organophosphate pesticide paraoxon is hydrolyzed by covalent catalysis with rate-limiting dephosphorylation. This reactibody is, therefore, a kinetically selected protein template that has enzyme-like catalytic attributes. PMID:21896761

Portfolios with fuzzy returns: Selection strategies based on semi-infinite programming

NASA Astrophysics Data System (ADS)

Vercher, Enriqueta

2008-08-01

This paper provides new models for portfolio selection in which the returns on securities are considered fuzzy numbers rather than random variables. The investor's problem is to find the portfolio that minimizes the risk of achieving a return that is not less than the return of a riskless asset. The corresponding optimal portfolio is derived using semi-infinite programming in a soft framework. The return on each asset and their membership functions are described using historical data. The investment risk is approximated by mean intervals which evaluate the downside risk for a given fuzzy portfolio. This approach is illustrated with a numerical example.

Heteroresistance at the single-cell level: adapting to antibiotic stress through a population-based strategy and growth-controlled interphenotypic coordination.

PubMed

Wang, Xiaorong; Kang, Yu; Luo, Chunxiong; Zhao, Tong; Liu, Lin; Jiang, Xiangdan; Fu, Rongrong; An, Shuchang; Chen, Jichao; Jiang, Ning; Ren, Lufeng; Wang, Qi; Baillie, J Kenneth; Gao, Zhancheng; Yu, Jun

2014-02-11

Heteroresistance refers to phenotypic heterogeneity of microbial clonal populations under antibiotic stress, and it has been thought to be an allocation of a subset of "resistant" cells for surviving in higher concentrations of antibiotic. The assumption fits the so-called bet-hedging strategy, where a bacterial population "hedges" its "bet" on different phenotypes to be selected by unpredicted environment stresses. To test this hypothesis, we constructed a heteroresistance model by introducing a blaCTX-M-14 gene (coding for a cephalosporin hydrolase) into a sensitive Escherichia coli strain. We confirmed heteroresistance in this clone and that a subset of the cells expressed more hydrolase and formed more colonies in the presence of ceftriaxone (exhibited stronger "resistance"). However, subsequent single-cell-level investigation by using a microfluidic device showed that a subset of cells with a distinguishable phenotype of slowed growth and intensified hydrolase expression emerged, and they were not positively selected but increased their proportion in the population with ascending antibiotic concentrations. Therefore, heteroresistance--the gradually decreased colony-forming capability in the presence of antibiotic--was a result of a decreased growth rate rather than of selection for resistant cells. Using a mock strain without the resistance gene, we further demonstrated the existence of two nested growth-centric feedback loops that control the expression of the hydrolase and maximize population growth in various antibiotic concentrations. In conclusion, phenotypic heterogeneity is a population-based strategy beneficial for bacterial survival and propagation through task allocation and interphenotypic collaboration, and the growth rate provides a critical control for the expression of stress-related genes and an essential mechanism in responding to environmental stresses. Heteroresistance is essentially phenotypic heterogeneity, where a population-based strategy is thought to be at work, being assumed to be variable cell-to-cell resistance to be selected under antibiotic stress. Exact mechanisms of heteroresistance and its roles in adaptation to antibiotic stress have yet to be fully understood at the molecular and single-cell levels. In our study, we have not been able to detect any apparent subset of "resistant" cells selected by antibiotics; on the contrary, cell populations differentiate into phenotypic subsets with variable growth statuses and hydrolase expression. The growth rate appears to be sensitive to stress intensity and plays a key role in controlling hydrolase expression at both the bulk population and single-cell levels. We have shown here, for the first time, that phenotypic heterogeneity can be beneficial to a growing bacterial population through task allocation and interphenotypic collaboration other than partitioning cells into different categories of selective advantage.

Efficient identification of context dependent subgroups of risk from genome wide association studies

PubMed Central

Dyson, Greg; Sing, Charles F.

2014-01-01

We have developed a modified Patient Rule-Induction Method (PRIM) as an alternative strategy for analyzing representative samples of non-experimental human data to estimate and test the role of genomic variations as predictors of disease risk in etiologically heterogeneous sub-samples. A computational limit of the proposed strategy is encountered when the number of genomic variations (predictor variables) under study is large (> 500) because permutations are used to generate a null distribution to test the significance of a term (defined by values of particular variables) that characterizes a sub-sample of individuals through the peeling and pasting processes. As an alternative, in this paper we introduce a theoretical strategy that facilitates the quick calculation of Type I and Type II errors in the evaluation of terms in the peeling and pasting processes carried out in the execution of a PRIM analysis that are underestimated and non-existent, respectively, when a permutation-based hypothesis test is employed. The resultant savings in computational time makes possible the consideration of larger numbers of genomic variations (an example genome wide association study is given) in the selection of statistically significant terms in the formulation of PRIM prediction models. PMID:24570412

A comprehensive strategy in the development of a cyclodextrin-modified microemulsion electrokinetic chromatographic method for the assay of diclofenac and its impurities: Mixture-process variable experiments and quality by design.

PubMed

Orlandini, S; Pasquini, B; Caprini, C; Del Bubba, M; Squarcialupi, L; Colotta, V; Furlanetto, S

2016-09-30

A comprehensive strategy involving the use of mixture-process variable (MPV) approach and Quality by Design principles has been applied in the development of a capillary electrophoresis method for the simultaneous determination of the anti-inflammatory drug diclofenac and its five related substances. The selected operative mode consisted in microemulsion electrokinetic chromatography with the addition of methyl-β-cyclodextrin. The critical process parameters included both the mixture components (MCs) of the microemulsion and the process variables (PVs). The MPV approach allowed the simultaneous investigation of the effects of MCs and PVs on the critical resolution between diclofenac and its 2-deschloro-2-bromo analogue and on analysis time. MPV experiments were used both in the screening phase and in the Response Surface Methodology, making it possible to draw MCs and PVs contour plots and to find important interactions between MCs and PVs. Robustness testing was carried out by MPV experiments and validation was performed following International Conference on Harmonisation guidelines. The method was applied to a real sample of diclofenac gastro-resistant tablets. Copyright © 2016 Elsevier B.V. All rights reserved.

Effects of two classification strategies on a Benthic Community Index for streams in the Northern Lakes and Forests Ecoregion

USGS Publications Warehouse

Butcher, Jason T.; Stewart, Paul M.; Simon, Thomas P.

2003-01-01

Ninety-four sites were used to analyze the effects of two different classification strategies on the Benthic Community Index (BCI). The first, a priori classification, reflected the wetland status of the streams; the second, a posteriori classification, used a bio-environmental analysis to select classification variables. Both classifications were examined by measuring classification strength and testing differences in metric values with respect to group membership. The a priori (wetland) classification strength (83.3%) was greater than the a posteriori (bio-environmental) classification strength (76.8%). Both classifications found one metric that had significant differences between groups. The original index was modified to reflect the wetland classification by re-calibrating the scoring criteria for percent Crustacea and Mollusca. A proposed refinement to the original Benthic Community Index is suggested. This study shows the importance of using hypothesis-driven classifications, as well as exploratory statistical analysis, to evaluate alternative ways to reveal environmental variability in biological assessment tools.

Comparison of statistical tests for association between rare variants and binary traits.

PubMed

Bacanu, Silviu-Alin; Nelson, Matthew R; Whittaker, John C

2012-01-01

Genome-wide association studies have found thousands of common genetic variants associated with a wide variety of diseases and other complex traits. However, a large portion of the predicted genetic contribution to many traits remains unknown. One plausible explanation is that some of the missing variation is due to the effects of rare variants. Nonetheless, the statistical analysis of rare variants is challenging. A commonly used method is to contrast, within the same region (gene), the frequency of minor alleles at rare variants between cases and controls. However, this strategy is most useful under the assumption that the tested variants have similar effects. We previously proposed a method that can accommodate heterogeneous effects in the analysis of quantitative traits. Here we extend this method to include binary traits that can accommodate covariates. We use simulations for a variety of causal and covariate impact scenarios to compare the performance of the proposed method to standard logistic regression, C-alpha, SKAT, and EREC. We found that i) logistic regression methods perform well when the heterogeneity of the effects is not extreme and ii) SKAT and EREC have good performance under all tested scenarios but they can be computationally intensive. Consequently, it would be more computationally desirable to use a two-step strategy by (i) selecting promising genes by faster methods and ii) analyzing selected genes using SKAT/EREC. To select promising genes one can use (1) regression methods when effect heterogeneity is assumed to be low and the covariates explain a non-negligible part of trait variability, (2) C-alpha when heterogeneity is assumed to be large and covariates explain a small fraction of trait's variability and (3) the proposed trend and heterogeneity test when the heterogeneity is assumed to be non-trivial and the covariates explain a large fraction of trait variability.

Hibernal habitat selection by Wood Frogs (Lithobates sylvaticus) in a northern New England montane landscape

USGS Publications Warehouse

Groff, Luke A.; Calhoun, Aram J.K.; Loftin, Cynthia S.

2016-01-01

Poikilothermic species, such as amphibians, endure harsh winter conditions via freeze-tolerance or freeze-avoidance strategies. Freeze-tolerance requires a suite of complex, physiological mechanisms (e.g., cryoprotectant synthesis); however, behavioral strategies (e.g., hibernal habitat selection) may be used to regulate hibernaculum temperatures and promote overwintering survival. We investigated the hibernal ecology of the freeze-tolerant Wood Frog (Lithobates sylvaticus) in north-central Maine. Our objectives were to characterize the species hibernaculum microclimate (temperature, relative humidity), evaluate hibernal habitat selection, and describe the spatial arrangement of breeding, post-breeding, and hibernal habitats. We monitored 15 frogs during two winters (2011/12: N = 10; 2012/13: N = 5), measured hibernal habitat features at micro (2 m) and macro (10 m) spatial scales, and recorded microclimate hourly in three strata (hibernaculum, leaf litter, ambient air). We compared these data to that of 57 random locations with logistic regression models, Akaike Information Criterion, and Kolmogorov–Smirnov tests. Hibernaculum microclimate was significantly different and less variable than leaf litter, ambient air, and random location microclimate. Model averaging indicated that canopy cover (−), leaf litter depth (+), and number of logs and stumps (+; microhabitat only) were important predictors of Wood Frog hibernal habitat. These habitat features likely act to insulate hibernating frogs from extreme and variable air temperatures. For example, decreased canopy cover facilitates increased snowpack depth and earlier snowpack accumulation and melt. Altered winter temperature and precipitation patterns attributable to climate change may reduce snowpack insulation, facilitate greater temperature variation in the underlying hibernacula, and potentially compromise Wood Frog winter survival.

The variability of software scoring of the CDMAM phantom associated with a limited number of images

NASA Astrophysics Data System (ADS)

Yang, Chang-Ying J.; Van Metter, Richard

2007-03-01

Software scoring approaches provide an attractive alternative to human evaluation of CDMAM images from digital mammography systems, particularly for annual quality control testing as recommended by the European Protocol for the Quality Control of the Physical and Technical Aspects of Mammography Screening (EPQCM). Methods for correlating CDCOM-based results with human observer performance have been proposed. A common feature of all methods is the use of a small number (at most eight) of CDMAM images to evaluate the system. This study focuses on the potential variability in the estimated system performance that is associated with these methods. Sets of 36 CDMAM images were acquired under carefully controlled conditions from three different digital mammography systems. The threshold visibility thickness (TVT) for each disk diameter was determined using previously reported post-analysis methods from the CDCOM scorings for a randomly selected group of eight images for one measurement trial. This random selection process was repeated 3000 times to estimate the variability in the resulting TVT values for each disk diameter. The results from using different post-analysis methods, different random selection strategies and different digital systems were compared. Additional variability of the 0.1 mm disk diameter was explored by comparing the results from two different image data sets acquired under the same conditions from the same system. The magnitude and the type of error estimated for experimental data was explained through modeling. The modeled results also suggest a limitation in the current phantom design for the 0.1 mm diameter disks. Through modeling, it was also found that, because of the binomial statistic nature of the CDMAM test, the true variability of the test could be underestimated by the commonly used method of random re-sampling.

Ecological and personal predictors of science achievement in an urban center

NASA Astrophysics Data System (ADS)

Guidubaldi, John Michael

This study sought to examine selected personal and environmental factors that predict urban students' achievement test scores on the science subject area of the Ohio standardized test. Variables examined were in the general categories of teacher/classroom, student, and parent/home. It assumed that these clusters might add independent variance to a best predictor model, and that discovering relative strength of different predictors might lead to better selection of intervention strategies to improve student performance. This study was conducted in an urban school district and was comprised of teachers and students enrolled in ninth grade science in three of this district's high schools. Consenting teachers (9), students (196), and parents (196) received written surveys with questions designed to examine the predictive power of each variable cluster. Regression analyses were used to determine which factors best correlate with student scores and classroom science grades. Selected factors were then compiled into a best predictive model, predicting success on standardized science tests. Students t tests of gender and racial subgroups confirmed that there were racial differences in OPT scores, and both gender and racial differences in science grades. Additional examinations were therefore conducted for all 12 variables to determine whether gender and race had an impact on the strength of individual variable predictions and on the final best predictor model. Of the 15 original OPT and cluster variable hypotheses, eight showed significant positive relationships that occurred in the expected direction. However, when more broadly based end-of-the-year science class grade was used as a criterion, 13 of the 15 hypotheses showed significant relationships in the expected direction. With both criteria, significant gender and racial differences were observed in the strength of individual predictors and in the composition of best predictor models.

Regionalisation of parameters of a large-scale water quality model in Lithuania using PAIC-SWAT

NASA Astrophysics Data System (ADS)

Zarrineh, Nina; van Griensven, Ann; Sennikovs, Juris; Bekere, Liga; Plunge, Svajunas

2015-04-01

To comply with the EU Water Framework Directive, all water bodies need to achieve good ecological status. To reach these goals, the Environmental Protection Agency (AAA) has to elaborate river basin districts management plans and programmes of measures for all catchments in Lithuania. For this purpose, a Soil and Water Assessment Tool (SWAT) model was set up for all Lithuanian catchments using the most recent version of SWAT2012 rev627 implemented and imbedded in a Python workflow by the Center of Processes Analysis and Research (PAIC). The model was calibrated and evaluated using all monitoring data of river discharge, nitrogen and phosphorous concentrations and load. A regionalisation strategy has been set up by identifying 13 hydrological regions according to the runoff formation and hydrological conditions. In each region, a representative catchment was selected and calibrated using a combination of manual and automated calibration techniques. After final parameterization and fulfilling of calibrating and validating evaluation criteria, the same parameters sets have been extrapolated to other catchments within the same hydrological region. Multi variable cal/val strategy was implemented for the following variables: river flow and in-stream NO3, Total Nitrogen, PO4 and Total Phosphorous concentrations. The criteria used for calibration, validation and extrapolation are: Nash-Sutcliffe Efficiency (NSE) for flow and R-squared for water quality variables and PBIAS (percentage bias) for all variables. For the hydrological calibration, NSE values greater than 0.5 should be achieved, while for validation and extrapolation the threshold is respectively 0.4 and 0.3. PBIAS errors have to be less than 20% for calibration and for validation and extrapolation less than 25% and 30%, respectively. In water quality calibration, R-squared should be achieved to 0.5 for calibration and for validation and extrapolation to 0.4 and 0.3 respectively for nitrogen variables. Besides PBIAS error should be less than 40% for calibration, and less than 70% for validation and extrapolation for all mentioned water quality variables. For the flow calibration, daily discharge data for 62 stations were provided for the period 1997-2012. For more than 500 stations, water quality data was provided and 135 data-rich stations was pre-processed in a database containing all observations from 1997-2012. Finally by implementing this regionalisation strategy, the model could satisfactorily predict the selected variables so that in the hydrological part more than 90% of stations fulfilled the criteria and in the water quality part more than 95% of stations fulfilled the criteria. Keywords: Water Quality Modelling, Regionalisation, Parameterization, Nitrogen and Phosphorus Prediction, Calibration, PAIC-SWAT.

Probabilistic Analysis of Solid Oxide Fuel Cell Based Hybrid Gas Turbine System

NASA Technical Reports Server (NTRS)

Gorla, Rama S. R.; Pai, Shantaram S.; Rusick, Jeffrey J.

2003-01-01

The emergence of fuel cell systems and hybrid fuel cell systems requires the evolution of analysis strategies for evaluating thermodynamic performance. A gas turbine thermodynamic cycle integrated with a fuel cell was computationally simulated and probabilistically evaluated in view of the several uncertainties in the thermodynamic performance parameters. Cumulative distribution functions and sensitivity factors were computed for the overall thermal efficiency and net specific power output due to the uncertainties in the thermodynamic random variables. These results can be used to quickly identify the most critical design variables in order to optimize the design and make it cost effective. The analysis leads to the selection of criteria for gas turbine performance.

Does a microprocessor-controlled prosthetic knee affect stair ascent strategies in persons with transfemoral amputation?

PubMed

Aldridge Whitehead, Jennifer M; Wolf, Erik J; Scoville, Charles R; Wilken, Jason M

2014-10-01

Stair ascent can be difficult for individuals with transfemoral amputation because of the loss of knee function. Most individuals with transfemoral amputation use either a step-to-step (nonreciprocal, advancing one stair at a time) or skip-step strategy (nonreciprocal, advancing two stairs at a time), rather than a step-over-step (reciprocal) strategy, because step-to-step and skip-step allow the leading intact limb to do the majority of work. A new microprocessor-controlled knee (Ottobock X2(®)) uses flexion/extension resistance to allow step-over-step stair ascent. We compared self-selected stair ascent strategies between conventional and X2(®) prosthetic knees, examined between-limb differences, and differentiated stair ascent mechanics between X2(®) users and individuals without amputation. We also determined which factors are associated with differences in knee position during initial contact and swing within X2(®) users. Fourteen individuals with transfemoral amputation participated in stair ascent sessions while using conventional and X2(®) knees. Ten individuals without amputation also completed a stair ascent session. Lower-extremity stair ascent joint angles, moment, and powers and ground reaction forces were calculated using inverse dynamics during self-selected strategy and cadence and controlled cadence using a step-over-step strategy. One individual with amputation self-selected a step-over-step strategy while using a conventional knee, while 10 individuals self-selected a step-over-step strategy while using X2(®) knees. Individuals with amputation used greater prosthetic knee flexion during initial contact (32.5°, p = 0.003) and swing (68.2°, p = 0.001) with higher intersubject variability while using X2(®) knees compared to conventional knees (initial contact: 1.6°, swing: 6.2°). The increased prosthetic knee flexion while using X2(®) knees normalized knee kinematics to individuals without amputation during swing (88.4°, p = 0.179) but not during initial contact (65.7°, p = 0.002). Prosthetic knee flexion during initial contact and swing were positively correlated with prosthetic limb hip power during pull-up (r = 0.641, p = 0.046) and push-up/early swing (r = 0.993, p < 0.001), respectively. Participants with transfemoral amputation were more likely to self-select a step-over-step strategy similar to individuals without amputation while using X2(®) knees than conventional prostheses. Additionally, the increased prosthetic knee flexion used with X2(®) knees placed large power demands on the hip during pull-up and push-up/early swing. A modified strategy that uses less knee flexion can be used to allow step-over-step ascent in individuals with less hip strength.

The use of a genetic algorithm-based search strategy in geostatistics: application to a set of anisotropic piezometric head data

NASA Astrophysics Data System (ADS)

Abedini, M. J.; Nasseri, M.; Burn, D. H.

2012-04-01

In any geostatistical study, an important consideration is the choice of an appropriate, repeatable, and objective search strategy that controls the nearby samples to be included in the location-specific estimation procedure. Almost all geostatistical software available in the market puts the onus on the user to supply search strategy parameters in a heuristic manner. These parameters are solely controlled by geographical coordinates that are defined for the entire area under study, and the user has no guidance as to how to choose these parameters. The main thesis of the current study is that the selection of search strategy parameters has to be driven by data—both the spatial coordinates and the sample values—and cannot be chosen beforehand. For this purpose, a genetic-algorithm-based ordinary kriging with moving neighborhood technique is proposed. The search capability of a genetic algorithm is exploited to search the feature space for appropriate, either local or global, search strategy parameters. Radius of circle/sphere and/or radii of standard or rotated ellipse/ellipsoid are considered as the decision variables to be optimized by GA. The superiority of GA-based ordinary kriging is demonstrated through application to the Wolfcamp Aquifer piezometric head data. Assessment of numerical results showed that definition of search strategy parameters based on both geographical coordinates and sample values improves cross-validation statistics when compared with that based on geographical coordinates alone. In the case of a variable search neighborhood for each estimation point, optimization of local search strategy parameters for an elliptical support domain—the orientation of which is dictated by anisotropic axes—via GA was able to capture the dynamics of piezometric head in west Texas/New Mexico in an efficient way.

Mini-review: Strategies for Variation and Evolution of Bacterial Antigens

PubMed Central

Foley, Janet

2015-01-01

Across the eubacteria, antigenic variation has emerged as a strategy to evade host immunity. However, phenotypic variation in some of these antigens also allows the bacteria to exploit variable host niches as well. The specific mechanisms are not shared-derived characters although there is considerable convergent evolution and numerous commonalities reflecting considerations of natural selection and biochemical restraints. Unlike in viruses, mechanisms of antigenic variation in most bacteria involve larger DNA movement such as gene conversion or DNA rearrangement, although some antigens vary due to point mutations or modified transcriptional regulation. The convergent evolution that promotes antigenic variation integrates various evolutionary forces: these include mutations underlying variant production; drift which could remove alleles especially early in infection or during life history phases in arthropod vectors (when the bacterial population size goes through a bottleneck); selection not only for any particular variant but also for the mechanism for the production of variants (i.e., selection for mutability); and overcoming negative selection against variant production. This review highlights the complexities of drivers of antigenic variation, in particular extending evaluation beyond the commonly cited theory of immune evasion. A deeper understanding of the diversity of purpose and mechanisms of antigenic variation in bacteria will contribute to greater insight into bacterial pathogenesis, ecology and coevolution with hosts. PMID:26288700

QbD for pediatric oral lyophilisates development: risk assessment followed by screening and optimization.

PubMed

Casian, Tibor; Iurian, Sonia; Bogdan, Catalina; Rus, Lucia; Moldovan, Mirela; Tomuta, Ioan

2017-12-01

This study proposed the development of oral lyophilisates with respect to pediatric medicine development guidelines, by applying risk management strategies and DoE as an integrated QbD approach. Product critical quality attributes were overviewed by generating Ishikawa diagrams for risk assessment purposes, considering process, formulation and methodology related parameters. Failure Mode Effect Analysis was applied to highlight critical formulation and process parameters with an increased probability of occurrence and with a high impact on the product performance. To investigate the effect of qualitative and quantitative formulation variables D-optimal designs were used for screening and optimization purposes. Process parameters related to suspension preparation and lyophilization were classified as significant factors, and were controlled by implementing risk mitigation strategies. Both quantitative and qualitative formulation variables introduced in the experimental design influenced the product's disintegration time, mechanical resistance and dissolution properties selected as CQAs. The optimum formulation selected through Design Space presented ultra-fast disintegration time (5 seconds), a good dissolution rate (above 90%) combined with a high mechanical resistance (above 600 g load). Combining FMEA and DoE allowed the science based development of a product with respect to the defined quality target profile by providing better insights on the relevant parameters throughout development process. The utility of risk management tools in pharmaceutical development was demonstrated.

Use and Selection of Sleeping Sites by Proboscis Monkeys, Nasalislarvatus, along the Kinabatangan River, Sabah, Malaysia.

PubMed

Thiry, Valentine; Stark, Danica J; Goossens, Benoît; Slachmuylder, Jean-Louis; Vercauteren Drubbel, Régine; Vercauteren, Martine

2016-01-01

The choice of a sleeping site is crucial for primates and may influence their survival. In this study, we investigated several tree characteristics influencing the sleeping site selection by proboscis monkeys (Nasalis larvatus) along Kinabatangan River, in Sabah, Malaysia. We identified 81 sleeping trees used by one-male and all-male social groups from November 2011 to January 2012. We recorded 15 variables for each tree. Within sleeping sites, sleeping trees were taller, had a larger trunk, with larger and higher first branches than surrounding trees. The crown contained more mature leaves, ripe and unripe fruits but had vines less often than surrounding trees. In addition, in this study, we also focused on a larger scale, considering sleeping and non-sleeping sites. Multivariate analyses highlighted a combination of 6 variables that revealed the significance of sleeping trees as well as surrounding trees in the selection process. During our boat surveys, we observed that adult females and young individuals stayed higher in the canopy than adult males. This pattern may be driven by their increased vulnerability to predation. Finally, we suggest that the selection of particular sleeping tree features (i.e. tall, high first branch) by proboscis monkeys is mostly influenced by antipredation strategies. © 2016 S. Karger AG, Basel.

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

An automatic multi-atlas prostate segmentation in MRI using a multiscale representation and a label fusion strategy

NASA Astrophysics Data System (ADS)

Álvarez, Charlens; Martínez, Fabio; Romero, Eduardo

2015-01-01

The pelvic magnetic Resonance images (MRI) are used in Prostate cancer radiotherapy (RT), a process which is part of the radiation planning. Modern protocols require a manual delineation, a tedious and variable activity that may take about 20 minutes per patient, even for trained experts. That considerable time is an important work ow burden in most radiological services. Automatic or semi-automatic methods might improve the efficiency by decreasing the measure times while conserving the required accuracy. This work presents a fully automatic atlas- based segmentation strategy that selects the more similar templates for a new MRI using a robust multi-scale SURF analysis. Then a new segmentation is achieved by a linear combination of the selected templates, which are previously non-rigidly registered towards the new image. The proposed method shows reliable segmentations, obtaining an average DICE Coefficient of 79%, when comparing with the expert manual segmentation, under a leave-one-out scheme with the training database.

Relationships among student attitudes, motivation, learning styles, learning strategies, patterns of learning, and achievement: A formative evaluation of distance education via Web-based courses

NASA Astrophysics Data System (ADS)

Shih, Ching-Chun

The World Wide Web (WWW) is the latest in a long line of educational technologies, and the list of courses on it is growing daily. Formative evaluations would help educators enhance teaching and learning in Web-based courses. This study analyzed the relationships between student achievement and the following variables: attitudes, motivation, learning strategies, patterns of learning, learning styles, and selected demographics. It was a population study that included 99 students taking two non-major introductory biology courses offered over the WWW by Iowa State University in the fall of 1997. Seventy-four (75%) students completed a learning style test, an on-line questionnaire, and received a grade by the end of the semester. The learning style test was the Group Embedded Figures Test (GEFT), which classified students as either field-dependent or field-independent. The on-line questionnaire consisted of four scales (attitude, motivation, learning strategies, and patterns of learning), whose pilot-test reliabilities ranged from .71 to .91. The selected demographic variables were gender, class level, previous experience in subject area, hours per week studying and working, computer access, and types of students as off-campus, on-campus, or adult students. Over two-thirds of the students taking the Web-based courses were field-independent learners; however, there were no significant differences (.05 level) in achievement by learning style. Also, different backgrounds of students with different learning styles learned equally well in Web-based courses. The students enjoyed the convenience and self-controlled learning pace and were motivated by competition and high expectations in Web-based learning. They used most the learning strategies of finding important ideas from lectures and memorizing key words of important concepts and least the learning strategy of making charts or tables to organize the material. They seemed more interested in checking their grades than in communicating with the class and instructors via e-mail, discussion netforum or chat netforum. Motivation and learning strategies were the two significant factors that explained more than one-third of student achievement measured by class grade. Educators should assist students in mastering different motivational and learning strategies to help them become self-regulated learners.

Identification of Urinary Polyphenol Metabolite Patterns Associated with Polyphenol-Rich Food Intake in Adults from Four European Countries.

PubMed

Noh, Hwayoung; Freisling, Heinz; Assi, Nada; Zamora-Ros, Raul; Achaintre, David; Affret, Aurélie; Mancini, Francesca; Boutron-Ruault, Marie-Christine; Flögel, Anna; Boeing, Heiner; Kühn, Tilman; Schübel, Ruth; Trichopoulou, Antonia; Naska, Androniki; Kritikou, Maria; Palli, Domenico; Pala, Valeria; Tumino, Rosario; Ricceri, Fulvio; Santucci de Magistris, Maria; Cross, Amanda; Slimani, Nadia; Scalbert, Augustin; Ferrari, Pietro

2017-07-25

We identified urinary polyphenol metabolite patterns by a novel algorithm that combines dimension reduction and variable selection methods to explain polyphenol-rich food intake, and compared their respective performance with that of single biomarkers in the European Prospective Investigation into Cancer and Nutrition (EPIC) study. The study included 475 adults from four European countries (Germany, France, Italy, and Greece). Dietary intakes were assessed with 24-h dietary recalls (24-HDR) and dietary questionnaires (DQ). Thirty-four polyphenols were measured by ultra-performance liquid chromatography-electrospray ionization-tandem mass spectrometry (UPLC-ESI-MS-MS) in 24-h urine. Reduced rank regression-based variable importance in projection (RRR-VIP) and least absolute shrinkage and selection operator (LASSO) methods were used to select polyphenol metabolites. Reduced rank regression (RRR) was then used to identify patterns in these metabolites, maximizing the explained variability in intake of pre-selected polyphenol-rich foods. The performance of RRR models was evaluated using internal cross-validation to control for over-optimistic findings from over-fitting. High performance was observed for explaining recent intake (24-HDR) of red wine ( r = 0.65; AUC = 89.1%), coffee ( r = 0.51; AUC = 89.1%), and olives ( r = 0.35; AUC = 82.2%). These metabolite patterns performed better or equally well compared to single polyphenol biomarkers. Neither metabolite patterns nor single biomarkers performed well in explaining habitual intake (as reported in the DQ) of polyphenol-rich foods. This proposed strategy of biomarker pattern identification has the potential of expanding the currently still limited list of available dietary intake biomarkers.

The incorporation of activities to control dengue by community health agents

PubMed Central

Cazola, Luiza Helena de Oliveira; Tamaki, Edson Mamoru; Pontes, Elenir Rose Jardim Cury; de Andrade, Sonia Maria Oliveira

2014-01-01

OBJECTIVE To evaluate the performance of Community Health Agents when dengue control activities were added to their tasks. METHODS Performance was measured comparing the evolution of selected indicators from the Brazilian National Dengue Control Program and the Family Health Strategy for 2002 to 2008 in the municipality of Sao Gabriel do Oeste, MS, Central Western Brazil, with those of Rio Verde de Mato Grosso, neighboring municipality with demographic, socioeconomic and health services similarities. Data were collected from municipal databases of the Information System for Yellow Fever and Dengue and the Information System for Primary Healthcare of the Mato Grosso do Sul State Health Office. The variables selected for the family health strategy activities were: monthly home visits, pregnant women whose antenatal care began in the first trimester, children under one with up-to-date vaccinations and hypertensive patients. Those selected for the Brazilian National Dengue Control Program were: properties inspected with Aedes aegypti and properties not inspected. RESULTS The two municipalities maintained a similar trend in dengue control indicators in the period studied. With regard to the Family Health Strategy, in 2002 Sao Gabriel do Oeste was better off in three of the four indicators studied, however, this situation was reversed at the end of the period when the county was overtaken by Rio Verde de Mato Grosso in three of the four indicators analyzed, including, the monthly average community health worker visits per registered family, the main activity of a Family Health Strategy agent. CONCLUSIONS: Incorporating the National Dengue Control Program into the Family Health Strategy is viable and developed without prejudice to dengue control activities, however, the same did not occur with the activities of family health in Sao Gabriel do Oeste. The additional workload of the community health workers is the most likely hypothesis for the declining performance of these agents in the Family Health Strategy activities. PMID:24789644

Establishing an efficient way to utilize the drought resistance germplasm population in wheat.

PubMed

Wang, Jiancheng; Guan, Yajing; Wang, Yang; Zhu, Liwei; Wang, Qitian; Hu, Qijuan; Hu, Jin

2013-01-01

Drought resistance breeding provides a hopeful way to improve yield and quality of wheat in arid and semiarid regions. Constructing core collection is an efficient way to evaluate and utilize drought-resistant germplasm resources in wheat. In the present research, 1,683 wheat varieties were divided into five germplasm groups (high resistant, HR; resistant, R; moderate resistant, MR; susceptible, S; and high susceptible, HS). The least distance stepwise sampling (LDSS) method was adopted to select core accessions. Six commonly used genetic distances (Euclidean distance, Euclid; Standardized Euclidean distance, Seuclid; Mahalanobis distance, Mahal; Manhattan distance, Manhat; Cosine distance, Cosine; and Correlation distance, Correlation) were used to assess genetic distances among accessions. Unweighted pair-group average (UPGMA) method was used to perform hierarchical cluster analysis. Coincidence rate of range (CR) and variable rate of coefficient of variation (VR) were adopted to evaluate the representativeness of the core collection. A method for selecting the ideal constructing strategy was suggested in the present research. A wheat core collection for the drought resistance breeding programs was constructed by the strategy selected in the present research. The principal component analysis showed that the genetic diversity was well preserved in that core collection.

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.

On the relationship between ecosystem-scale hyperspectral reflectance and CO2 exchange in European mountain grasslands

NASA Astrophysics Data System (ADS)

Balzarolo, M.; Vescovo, L.; Hammerle, A.; Gianelle, D.; Papale, D.; Tomelleri, E.; Wohlfahrt, G.

2015-05-01

In this paper we explore the skill of hyperspectral reflectance measurements and vegetation indices (VIs) derived from these in estimating carbon dioxide (CO2) fluxes of grasslands. Hyperspectral reflectance data, CO2 fluxes and biophysical parameters were measured at three grassland sites located in European mountain regions using standardized protocols. The relationships between CO2 fluxes, ecophysiological variables, traditional VIs and VIs derived using all two-band combinations of wavelengths available from the whole hyperspectral data space were analysed. We found that VIs derived from hyperspectral data generally explained a large fraction of the variability in the investigated dependent variables but differed in their ability to estimate midday and daily average CO2 fluxes and various derived ecophysiological parameters. Relationships between VIs and CO2 fluxes and ecophysiological parameters were site-specific, likely due to differences in soils, vegetation parameters and environmental conditions. Chlorophyll and water-content-related VIs explained the largest fraction of variability in most of the dependent variables. Band selection based on a combination of a genetic algorithm with random forests (GA-rF) confirmed that it is difficult to select a universal band region suitable across the investigated ecosystems. Our findings have major implications for upscaling terrestrial CO2 fluxes to larger regions and for remote- and proximal-sensing sampling and analysis strategies and call for more cross-site synthesis studies linking ground-based spectral reflectance with ecosystem-scale CO2 fluxes.

A particle swarm optimization variant with an inner variable learning strategy.

PubMed

Wu, Guohua; Pedrycz, Witold; Ma, Manhao; Qiu, Dishan; Li, Haifeng; Liu, Jin

2014-01-01

Although Particle Swarm Optimization (PSO) has demonstrated competitive performance in solving global optimization problems, it exhibits some limitations when dealing with optimization problems with high dimensionality and complex landscape. In this paper, we integrate some problem-oriented knowledge into the design of a certain PSO variant. The resulting novel PSO algorithm with an inner variable learning strategy (PSO-IVL) is particularly efficient for optimizing functions with symmetric variables. Symmetric variables of the optimized function have to satisfy a certain quantitative relation. Based on this knowledge, the inner variable learning (IVL) strategy helps the particle to inspect the relation among its inner variables, determine the exemplar variable for all other variables, and then make each variable learn from the exemplar variable in terms of their quantitative relations. In addition, we design a new trap detection and jumping out strategy to help particles escape from local optima. The trap detection operation is employed at the level of individual particles whereas the trap jumping out strategy is adaptive in its nature. Experimental simulations completed for some representative optimization functions demonstrate the excellent performance of PSO-IVL. The effectiveness of the PSO-IVL stresses a usefulness of augmenting evolutionary algorithms by problem-oriented domain knowledge.

The role of personal self-regulation and regulatory teaching to predict motivational-affective variables, achievement, and satisfaction: a structural model

PubMed Central

De la Fuente, Jesus; Zapata, Lucía; Martínez-Vicente, Jose M.; Sander, Paul; Cardelle-Elawar, María

2014-01-01

The present investigation examines how personal self-regulation (presage variable) and regulatory teaching (process variable of teaching) relate to learning approaches, strategies for coping with stress, and self-regulated learning (process variables of learning) and, finally, how they relate to performance and satisfaction with the learning process (product variables). The objective was to clarify the associative and predictive relations between these variables, as contextualized in two different models that use the presage-process-product paradigm (the Biggs and DEDEPRO models). A total of 1101 university students participated in the study. The design was cross-sectional and retrospective with attributional (or selection) variables, using correlations and structural analysis. The results provide consistent and significant empirical evidence for the relationships hypothesized, incorporating variables that are part of and influence the teaching–learning process in Higher Education. Findings confirm the importance of interactive relationships within the teaching–learning process, where personal self-regulation is assumed to take place in connection with regulatory teaching. Variables that are involved in the relationships validated here reinforce the idea that both personal factors and teaching and learning factors should be taken into consideration when dealing with a formal teaching–learning context at university. PMID:25964764

The Effects of Selected Instructional Variables on the Acquisition of Cognitive Learning Strategies

DTIC Science & Technology

1980-08-01

Free Recall Scores in Exneriment I.......................11 Table 4. Source Table for Analysis of Variance on the Paired- A-sociate Task in Experiment I...analysis of the free recall data, the scores of two students in the traditional instructions group had to be eliminated due to a faulty slide projector...For the analysis of the 8 paired-associate data, the score of one student in the combined instructions qroup and the score of one student in the

Exploratory Spectroscopy of Magnetic Cataclysmic Variables Candidates and Other Variable Objects

NASA Astrophysics Data System (ADS)

Oliveira, A. S.; Rodrigues, C. V.; Cieslinski, D.; Jablonski, F. J.; Silva, K. M. G.; Almeida, L. A.; Rodríguez-Ardila, A.; Palhares, M. S.

2017-04-01

The increasing number of synoptic surveys made by small robotic telescopes, such as the photometric Catalina Real-Time Transient Survey (CRTS), provides a unique opportunity to discover variable sources and improves the statistical samples of such classes of objects. Our goal is the discovery of magnetic Cataclysmic Variables (mCVs). These are rare objects that probe interesting accretion scenarios controlled by the white-dwarf magnetic field. In particular, improved statistics of mCVs would help to address open questions on their formation and evolution. We performed an optical spectroscopy survey to search for signatures of magnetic accretion in 45 variable objects selected mostly from the CRTS. In this sample, we found 32 CVs, 22 being mCV candidates, 13 of which were previously unreported as such. If the proposed classifications are confirmed, it would represent an increase of 4% in the number of known polars and 12% in the number of known IPs. A fraction of our initial sample was classified as extragalactic sources or other types of variable stars by the inspection of the identification spectra. Despite the inherent complexity in identifying a source as an mCV, variability-based selection, followed by spectroscopic snapshot observations, has proved to be an efficient strategy for their discoveries, being a relatively inexpensive approach in terms of telescope time. Based on observations obtained at the Observatório do Pico dos Dias/LNA, and at the Southern Astrophysical Research (SOAR) telescope, which is a joint project of the Ministério da Ciência, Tecnologia, e Inovação (MCTI) da República Federativa do Brasil, the U.S. National Optical Astronomy Observatory (NOAO), the University of North Carolina at Chapel Hill (UNC), and Michigan State University (MSU).

A conceptual approach to the development of motivational strategies.

PubMed

Wong, J; Wong, S; Mensah, L L

1983-03-01

Teachers in both general and professional education are well aware of the importance of motivation as the basis of effective teaching. Heidgerken maintains that a major problem that faces nursing educators is to select the right type of motivation and to know how to effect motivation. The authors propose a conceptual model for developing strategies to deal with motivational problems. This model is an application of Vroom's value/expectancy theory and Rotter's social learning theory, and is based on the premise that nursing faculty are in strategic positions to enhance student motivation for learning by manipulating variables that are believed to influence motivation. These suggested strategies include: enhancing student's need value by rewarding them with rewards that they value the most; increasing student's perceptions of a strong link between performance and rewards; providing students with consistent and clear role perceptions; improving student satisfaction towards learning.

Integrating health and safety in the workplace: how closely aligning health and safety strategies can yield measurable benefits.

PubMed

Loeppke, Ronald R; Hohn, Todd; Baase, Catherine; Bunn, William B; Burton, Wayne N; Eisenberg, Barry S; Ennis, Trish; Fabius, Raymond; Hawkins, R Jack; Hudson, T Warner; Hymel, Pamela A; Konicki, Doris; Larson, Paul; McLellan, Robert K; Roberts, Mark A; Usrey, Cary; Wallace, Joseph A; Yarborough, Charles M; Siuba, Justina

2015-05-01

To better understand how integrating health and safety strategies in the workplace has evolved and establish a replicable, scalable framework for advancing the concept with a system of health and safety metrics, modeled after the Dow Jones Sustainability Index. Seven leading national and international programs aimed at creating a culture of health and safety in the workplace were compared and contrasted. A list of forty variables was selected, making it clear there is a wide variety of approaches to integration of health and safety in the workplace. Depending on how well developed the culture of health and safety is within a company, there are unique routes to operationalize and institutionalize the integration of health and safety strategies to achieve measurable benefits to enhance the overall health and well-being of workers, their families, and the community.

Which Are the Determinants of Online Students' Efficiency in Higher Education?

NASA Astrophysics Data System (ADS)

Castillo-Merino, David; Serradell-Lopez, Enric; González-González, Inés

International literature shows that the positive effect on students performance from the adoption of innovations in the technology of teaching and learning do not affect all teaching methods and learning styles equally, as it depends on university strategy and policy towards Information and Communication Technologies (ICT) adoption, students abilities, technology uses in the educational process by teachers and students, or the selection of a methodology that matches with digital uses. This paper provides empirical answers to these questions with data from online students at the Open University of Catalonia (UOC). An empirical model based on structural equations has been defined to explain complex relationships between variables. Our results show that motivation is the main variable affecting online students' performance. It appears as a latent variable influenced by students' perception of efficiency, a driver for indirect positive and significant effect on students' performance from students' ability in ICT uses.

Automated storm water sampling on small watersheds

USGS Publications Warehouse

Harmel, R.D.; King, K.W.; Slade, R.M.

2003-01-01

Few guidelines are currently available to assist in designing appropriate automated storm water sampling strategies for small watersheds. Therefore, guidance is needed to develop strategies that achieve an appropriate balance between accurate characterization of storm water quality and loads and limitations of budget, equipment, and personnel. In this article, we explore the important sampling strategy components (minimum flow threshold, sampling interval, and discrete versus composite sampling) and project-specific considerations (sampling goal, sampling and analysis resources, and watershed characteristics) based on personal experiences and pertinent field and analytical studies. These components and considerations are important in achieving the balance between sampling goals and limitations because they determine how and when samples are taken and the potential sampling error. Several general recommendations are made, including: setting low minimum flow thresholds, using flow-interval or variable time-interval sampling, and using composite sampling to limit the number of samples collected. Guidelines are presented to aid in selection of an appropriate sampling strategy based on user's project-specific considerations. Our experiences suggest these recommendations should allow implementation of a successful sampling strategy for most small watershed sampling projects with common sampling goals.

Landslide susceptibility mapping in three selected target zones in Afghanistan

NASA Astrophysics Data System (ADS)

Schwanghart, Wolfgang; Seegers, Joe; Zeilinger, Gerold

2015-04-01

In May 2014, a large and mobile landslide destroyed the village Ab Barek, a village in Badakshan Province, Afghanistan. The landslide caused several hundred fatalities and once again demonstrated the vulnerability of Afghanistan's population to extreme natural events following more than 30 years of civil war and violent conflict. Increasing the capacity of Afghanistan's population by strengthening the disaster preparedness and management of responsible government authorities and institutions is thus a major component of international cooperation and development strategies. Afghanistan is characterized by high relief and widely varying rock types that largely determine the spatial distribution as well as emplacement modes of mass movements. The major aim of our study is to characterize this variability by conducting a landslide susceptibility analysis in three selected target zones: Greater Kabul Area, Badakhshan Province and Takhar Province. We expand on an existing landslide database by mapping landforms diagnostic for landslides (e.g. head scarps, normal faults and tension cracks), and historical landslide scars and landslide deposits by visual interpretation of high-resolution satellite imagery. We conduct magnitude frequency analysis within subregional physiogeographic classes based on geological maps, climatological and topographic data to identify regional parameters influencing landslide magnitude and frequency. In addition, we prepare a landslide susceptibility map for each area using the Weight-of-Evidence model. Preliminary results show that the three selected target zones vastly differ in modes of landsliding. Low magnitude but frequent rockfall events are a major hazard in the Greater Kabul Area threatening buildings and infrastructure encroaching steep terrain in the city's outskirts. Mass movements in loess covered areas of Badakshan are characterized by medium to large magnitudes. This spatial variability of characteristic landslide magnitudes and modes of emplacement necessitates different strategies to assess, mitigate, and prepare for landslides in the three different target zones.

Designing basin-customized combined drought indices via feature extraction

NASA Astrophysics Data System (ADS)

Zaniolo, Marta; Giuliani, Matteo; Castelletti, Andrea

2017-04-01

The socio-economic costs of drought are progressively increasing worldwide due to the undergoing alteration of hydro-meteorological regimes induced by climate change. Although drought management is largely studied in the literature, most of the traditional drought indexes fail in detecting critical events in highly regulated systems, which generally rely on ad-hoc formulations and cannot be generalized to different context. In this study, we contribute a novel framework for the design of a basin-customized drought index. This index represents a surrogate of the state of the basin and is computed by combining the available information about the water available in the system to reproduce a representative target variable for the drought condition of the basin (e.g., water deficit). To select the relevant variables and how to combine them, we use an advanced feature extraction algorithm called Wrapper for Quasi Equally Informative Subset Selection (W-QEISS). The W-QEISS algorithm relies on a multi-objective evolutionary algorithm to find Pareto-efficient subsets of variables by maximizing the wrapper accuracy, minimizing the number of selected variables (cardinality) and optimizing relevance and redundancy of the subset. The accuracy objective is evaluated trough the calibration of a pre-defined model (i.e., an extreme learning machine) of the water deficit for each candidate subset of variables, with the index selected from the resulting solutions identifying a suitable compromise between accuracy, cardinality, relevance, and redundancy. The proposed methodology is tested in the case study of Lake Como in northern Italy, a regulated lake mainly operated for irrigation supply to four downstream agricultural districts. In the absence of an institutional drought monitoring system, we constructed the combined index using all the hydrological variables from the existing monitoring system as well as the most common drought indicators at multiple time aggregations. The soil moisture deficit in the root zone computed by a distributed-parameter water balance model of the agricultural districts is used as target variable. Numerical results show that our framework succeeds in constructing a combined drought index that reproduces the soil moisture deficit. Moreover, this index represents a valuable information for supporting appropriate drought management strategies, including the possibility of directly informing the lake operations about the drought conditions and improve the overall reliability of the irrigation supply system.

Bioaccessibility and bioavailability of phenolic compounds in bread: a review.

PubMed

Angelino, Donato; Cossu, Marta; Marti, Alessandra; Zanoletti, Miriam; Chiavaroli, Laura; Brighenti, Furio; Del Rio, Daniele; Martini, Daniela

2017-07-19

Cereal-based products, like breads, are a vehicle for bioactive compounds, including polyphenols. The health effects of polyphenols like phenolic acids (PAs) are dependent on their bioaccessibility and bioavailability. The present review summarizes the current understanding of potential strategies to improve phenolic bioaccessibility and bioavailability and the main findings of in vitro and in vivo studies investigating these strategies applied to breads, including the use of raw ingredients with greater phenolic content and different pre-processing technologies, such as fermentation and enzymatic treatment of ingredients. There is considerable variability between in vitro studies, mainly resulting from the use of different methodologies, highlighting the need for standardization. Of the few in vivo bioavailability studies identified, acute, single-dose studies demonstrate that modifications to selected raw materials and bioprocessing of bran could increase the bioavailability, but not necessarily the net content, of bread phenolics. The two medium-term identified dietary interventions also demonstrated greater phenolic content, resulting from the modification of the raw materials used. Overall, the findings suggest that several strategies can be used to develop new bread products with greater phenolic bioaccessibility and bioavailability. However, due to the large variability and the few studies available, further investigations are required to determine better the usefulness of these innovative processes.

Analysis of low flows and selected methods for estimating low-flow characteristics at partial-record and ungaged stream sites in western Washington

USGS Publications Warehouse

Curran, Christopher A.; Eng, Ken; Konrad, Christopher P.

2012-01-01

Regional low-flow regression models for estimating Q7,10 at ungaged stream sites are developed from the records of daily discharge at 65 continuous gaging stations (including 22 discontinued gaging stations) for the purpose of evaluating explanatory variables. By incorporating the base-flow recession time constant τ as an explanatory variable in the regression model, the root-mean square error for estimating Q7,10 at ungaged sites can be lowered to 72 percent (for known values of τ), which is 42 percent less than if only basin area and mean annual precipitation are used as explanatory variables. If partial-record sites are included in the regression data set, τ must be estimated from pairs of discharge measurements made during continuous periods of declining low flows. Eight measurement pairs are optimal for estimating τ at partial-record sites, and result in a lowering of the root-mean square error by 25 percent. A low-flow survey strategy that includes paired measurements at partial-record sites requires additional effort and planning beyond a standard strategy, but could be used to enhance regional estimates of τ and potentially reduce the error of regional regression models for estimating low-flow characteristics at ungaged sites.

Optimal speech motor control and token-to-token variability: a Bayesian modeling approach.

PubMed

Patri, Jean-François; Diard, Julien; Perrier, Pascal

2015-12-01

The remarkable capacity of the speech motor system to adapt to various speech conditions is due to an excess of degrees of freedom, which enables producing similar acoustical properties with different sets of control strategies. To explain how the central nervous system selects one of the possible strategies, a common approach, in line with optimal motor control theories, is to model speech motor planning as the solution of an optimality problem based on cost functions. Despite the success of this approach, one of its drawbacks is the intrinsic contradiction between the concept of optimality and the observed experimental intra-speaker token-to-token variability. The present paper proposes an alternative approach by formulating feedforward optimal control in a probabilistic Bayesian modeling framework. This is illustrated by controlling a biomechanical model of the vocal tract for speech production and by comparing it with an existing optimal control model (GEPPETO). The essential elements of this optimal control model are presented first. From them the Bayesian model is constructed in a progressive way. Performance of the Bayesian model is evaluated based on computer simulations and compared to the optimal control model. This approach is shown to be appropriate for solving the speech planning problem while accounting for variability in a principled way.

Exact tests using two correlated binomial variables in contemporary cancer clinical trials.

PubMed

Yu, Jihnhee; Kepner, James L; Iyer, Renuka

2009-12-01

New therapy strategies for the treatment of cancer are rapidly emerging because of recent technology advances in genetics and molecular biology. Although newer targeted therapies can improve survival without measurable changes in tumor size, clinical trial conduct has remained nearly unchanged. When potentially efficacious therapies are tested, current clinical trial design and analysis methods may not be suitable for detecting therapeutic effects. We propose an exact method with respect to testing cytostatic cancer treatment using correlated bivariate binomial random variables to simultaneously assess two primary outcomes. The method is easy to implement. It does not increase the sample size over that of the univariate exact test and in most cases reduces the sample size required. Sample size calculations are provided for selected designs.

Genome-wide association studies on HIV susceptibility, pathogenesis and pharmacogenomics

PubMed Central

2012-01-01

Susceptibility to HIV-1 and the clinical course after infection show a substantial heterogeneity between individuals. Part of this variability can be attributed to host genetic variation. Initial candidate gene studies have revealed interesting host factors that influence HIV infection, replication and pathogenesis. Recently, genome-wide association studies (GWAS) were utilized for unbiased searches at a genome-wide level to discover novel genetic factors and pathways involved in HIV-1 infection. This review gives an overview of findings from the GWAS performed on HIV infection, within different cohorts, with variable patient and phenotype selection. Furthermore, novel techniques and strategies in research that might contribute to the complete understanding of virus-host interactions and its role on the pathogenesis of HIV infection are discussed. PMID:22920050

Older adults' exercise behavior: roles of selected constructs of social-cognitive theory.

PubMed

Umstattd, M Renée; Hallam, Jeffrey

2007-04-01

Exercise is consistently related to physical and psychological health benefits in older adults. Bandura's social-cognitive theory (SCT) is one theoretical perspective on understanding and predicting exercise behavior. Thus, the authors examined whether three SCT variables-self-efficacy, self-regulation, and outcome-expectancy value-predicted older adults' (N = 98) exercise behavior. Bivariate analyses revealed that regular exercise was associated with being male, White, and married; having higher income, education, and self-efficacy; using self-regulation skills; and having favorable outcome-expectancy values (p < .05). In a simultaneous multivariate model, however, self-regulation (p = .0097) was the only variable independently associated with regular exercise. Thus, exercise interventions targeting older adults should include components aimed at increasing the use of self-regulation strategies.

Life history theory predicts fish assemblage response to hydrologic regimes.

PubMed

Mims, Meryl C; Olden, Julian D

2012-01-01

The hydrologic regime is regarded as the primary driver of freshwater ecosystems, structuring the physical habitat template, providing connectivity, framing biotic interactions, and ultimately selecting for specific life histories of aquatic organisms. In the present study, we tested ecological theory predicting directional relationships between major dimensions of the flow regime and life history composition of fish assemblages in perennial free-flowing rivers throughout the continental United States. Using long-term discharge records and fish trait and survey data for 109 stream locations, we found that 11 out of 18 relationships (61%) tested between the three life history strategies (opportunistic, periodic, and equilibrium) and six hydrologic metrics (two each describing flow variability, predictability, and seasonality) were statistically significant (P < or = 0.05) according to quantile regression. Our results largely support a priori hypotheses of relationships between specific flow indices and relative prevalence of fish life history strategies, with 82% of all significant relationships observed supporting predictions from life history theory. Specifically, we found that (1) opportunistic strategists were positively related to measures of flow variability and negatively related to predictability and seasonality, (2) periodic strategists were positively related to high flow seasonality and negatively related to variability, and (3) the equilibrium strategists were negatively related to flow variability and positively related to predictability. Our study provides important empirical evidence illustrating the value of using life history theory to understand both the patterns and processes by which fish assemblage structure is shaped by adaptation to natural regimes of variability, predictability, and seasonality of critical flow events over broad biogeographic scales.

Locomotor-respiratory coupling patterns and oxygen consumption during walking above and below preferred stride frequency.

PubMed

O'Halloran, Joseph; Hamill, Joseph; McDermott, William J; Remelius, Jebb G; Van Emmerik, Richard E A

2012-03-01

Locomotor respiratory coupling patterns in humans have been assessed on the basis of the interaction between different physiological and motor subsystems; these interactions have implications for movement economy. A complex and dynamical systems framework may provide more insight than entrainment into the variability and adaptability of these rhythms and their coupling. The purpose of this study was to investigate the relationship between steady state locomotor-respiratory coordination dynamics and oxygen consumption [Formula: see text] of the movement by varying walking stride frequency from preferred. Twelve male participants walked on a treadmill at a self-selected speed. Stride frequency was varied from -20 to +20% of preferred stride frequency (PSF) while respiratory airflow, gas exchange variables, and stride kinematics were recorded. Discrete relative phase and return map techniques were used to evaluate the strength, stability, and variability of both frequency and phase couplings. Analysis of [Formula: see text] during steady-state walking showed a U-shaped response (P = 0.002) with a minimum at PSF and PSF - 10%. Locomotor-respiratory frequency coupling strength was not greater (P = 0.375) at PSF than any other stride frequency condition. The dominant coupling across all conditions was 2:1 with greater occurrences at the lower stride frequencies. Variability in coupling was the greatest during PSF, indicating an exploration of coupling strategies to search for the coupling frequency strategy with the least oxygen consumption. Contrary to the belief that increased strength of frequency coupling would decrease oxygen consumption; these results conclude that it is the increased variability of frequency coupling that results in lower oxygen consumption.

Volume-based response evaluation with consensual lesion selection: a pilot study by using cloud solutions and comparison to RECIST 1.1.

PubMed

Oubel, Estanislao; Bonnard, Eric; Sueoka-Aragane, Naoko; Kobayashi, Naomi; Charbonnier, Colette; Yamamichi, Junta; Mizobe, Hideaki; Kimura, Shinya

2015-02-01

Lesion volume is considered as a promising alternative to Response Evaluation Criteria in Solid Tumors (RECIST) to make tumor measurements more accurate and consistent, which would enable an earlier detection of temporal changes. In this article, we report the results of a pilot study aiming at evaluating the effects of a consensual lesion selection on volume-based response (VBR) assessments. Eleven patients with lung computed tomography scans acquired at three time points were selected from Reference Image Database to Evaluate Response to therapy in lung cancer (RIDER) and proprietary databases. Images were analyzed according to RECIST 1.1 and VBR criteria by three readers working in different geographic locations. Cloud solutions were used to connect readers and carry out a consensus process on the selection of lesions used for computing response. Because there are not currently accepted thresholds for computing VBR, we have applied a set of thresholds based on measurement variability (-35% and +55%). The benefit of this consensus was measured in terms of multiobserver agreement by using Fleiss kappa (κfleiss) and corresponding standard errors (SE). VBR after consensual selection of target lesions allowed to obtain κfleiss = 0.85 (SE = 0.091), which increases up to 0.95 (SE = 0.092), if an extra consensus on new lesions is added. As a reference, the agreement when applying RECIST without consensus was κfleiss = 0.72 (SE = 0.088). These differences were found to be statistically significant according to a z-test. An agreement on the selection of lesions allows reducing the inter-reader variability when computing VBR. Cloud solutions showed to be an interesting and feasible strategy for standardizing response evaluations, reducing variability, and increasing consistency of results in multicenter clinical trials. Copyright © 2015 AUR. Published by Elsevier Inc. All rights reserved.

A study of culturally syntonic variables in the bilingual/bicultural science classroom

NASA Astrophysics Data System (ADS)

Barba, Robertta H.

The purpose of this study was to conduct a needs assessment of bilingual/bicultural elementary science classrooms in order to determine if the current instructional environment addresses the educational needs of Hispanic/Latino children. This study examined 57 randomly selected elementary bilingual/bicultural science classrooms in a large metropolitan area of the southwestern United States in terms of culturally syntonic variables (i.e., culture-of-origin beliefs and/or practices that impact the teaching/learning process). Findings from this study indicate that Hispanic/Latino children are receiving science instruction: (a) with culturally asyntonic printed materials, teaching strategies, and supplementary materials, (b) in classrooms that do not use the child's native language, familia learning groups, peer tutoring, or manipulative materials, and (c) with oral and verbal instruction that lack culturally syntonic role models, examples, analogies, and elaborations. Findings from this study imply that changes are needed in pre-service and in-service teacher training, in science textbook formats, and in the scope and focus of elementary school bilingual/bicultural science curriculum and instructional strategies.

Multivariate probability distribution for sewer system vulnerability assessment under data-limited conditions.

PubMed

Del Giudice, G; Padulano, R; Siciliano, D

2016-01-01

The lack of geometrical and hydraulic information about sewer networks often excludes the adoption of in-deep modeling tools to obtain prioritization strategies for funds management. The present paper describes a novel statistical procedure for defining the prioritization scheme for preventive maintenance strategies based on a small sample of failure data collected by the Sewer Office of the Municipality of Naples (IT). Novelty issues involve, among others, considering sewer parameters as continuous statistical variables and accounting for their interdependences. After a statistical analysis of maintenance interventions, the most important available factors affecting the process are selected and their mutual correlations identified. Then, after a Box-Cox transformation of the original variables, a methodology is provided for the evaluation of a vulnerability map of the sewer network by adopting a joint multivariate normal distribution with different parameter sets. The goodness-of-fit is eventually tested for each distribution by means of a multivariate plotting position. The developed methodology is expected to assist municipal engineers in identifying critical sewers, prioritizing sewer inspections in order to fulfill rehabilitation requirements.

Recent advancements in GRACE mascon regularization and uncertainty assessment

NASA Astrophysics Data System (ADS)

Loomis, B. D.; Luthcke, S. B.

2017-12-01

The latest release of the NASA Goddard Space Flight Center (GSFC) global time-variable gravity mascon product applies a new regularization strategy along with new methods for estimating noise and leakage uncertainties. The critical design component of mascon estimation is the construction of the applied regularization matrices, and different strategies exist between the different centers that produce mascon solutions. The new approach from GSFC directly applies the pre-fit Level 1B inter-satellite range-acceleration residuals in the design of time-dependent regularization matrices, which are recomputed at each step of our iterative solution method. We summarize this new approach, demonstrating the simultaneous increase in recovered time-variable gravity signal and reduction in the post-fit inter-satellite residual magnitudes, until solution convergence occurs. We also present our new approach for estimating mascon noise uncertainties, which are calibrated to the post-fit inter-satellite residuals. Lastly, we present a new technique for end users to quickly estimate the signal leakage errors for any selected grouping of mascons, and we test the viability of this leakage assessment procedure on the mascon solutions produced by other processing centers.

Selection Pressure in CD8+ T-cell Epitopes in the pol Gene of HIV-1 Infected Individuals in Colombia. A Bioinformatic Approach

PubMed Central

Acevedo-Sáenz, Liliana; Ochoa, Rodrigo; Rugeles, Maria Teresa; Olaya-García, Patricia; Velilla-Hernández, Paula Andrea; Diaz, Francisco J.

2015-01-01

One of the main characteristics of the human immunodeficiency virus is its genetic variability and rapid adaptation to changing environmental conditions. This variability, resulting from the lack of proofreading activity of the viral reverse transcriptase, generates mutations that could be fixed either by random genetic drift or by positive selection. Among the forces driving positive selection are antiretroviral therapy and CD8+ T-cells, the most important immune mechanism involved in viral control. Here, we describe mutations induced by these selective forces acting on the pol gene of HIV in a group of infected individuals. We used Maximum Likelihood analyses of the ratio of non-synonymous to synonymous mutations per site (dN/dS) to study the extent of positive selection in the protease and the reverse transcriptase, using 614 viral sequences from Colombian patients. We also performed computational approaches, docking and algorithmic analyses, to assess whether the positively selected mutations affected binding to the HLA molecules. We found 19 positively-selected codons in drug resistance-associated sites and 22 located within CD8+ T-cell epitopes. A high percentage of mutations in these epitopes has not been previously reported. According to the docking analyses only one of those mutations affected HLA binding. However, algorithmic methods predicted a decrease in the affinity for the HLA molecule in seven mutated peptides. The bioinformatics strategies described here are useful to identify putative positively selected mutations associated with immune escape but should be complemented with an experimental approach to define the impact of these mutations on the functional profile of the CD8+ T-cells. PMID:25803098

Bayesian variable selection for post-analytic interrogation of susceptibility loci.

PubMed

Chen, Siying; Nunez, Sara; Reilly, Muredach P; Foulkes, Andrea S

2017-06-01

Understanding the complex interplay among protein coding genes and regulatory elements requires rigorous interrogation with analytic tools designed for discerning the relative contributions of overlapping genomic regions. To this aim, we offer a novel application of Bayesian variable selection (BVS) for classifying genomic class level associations using existing large meta-analysis summary level resources. This approach is applied using the expectation maximization variable selection (EMVS) algorithm to typed and imputed SNPs across 502 protein coding genes (PCGs) and 220 long intergenic non-coding RNAs (lncRNAs) that overlap 45 known loci for coronary artery disease (CAD) using publicly available Global Lipids Gentics Consortium (GLGC) (Teslovich et al., 2010; Willer et al., 2013) meta-analysis summary statistics for low-density lipoprotein cholesterol (LDL-C). The analysis reveals 33 PCGs and three lncRNAs across 11 loci with >50% posterior probabilities for inclusion in an additive model of association. The findings are consistent with previous reports, while providing some new insight into the architecture of LDL-cholesterol to be investigated further. As genomic taxonomies continue to evolve, additional classes such as enhancer elements and splicing regions, can easily be layered into the proposed analysis framework. Moreover, application of this approach to alternative publicly available meta-analysis resources, or more generally as a post-analytic strategy to further interrogate regions that are identified through single point analysis, is straightforward. All coding examples are implemented in R version 3.2.1 and provided as supplemental material. © 2016, The International Biometric Society.

Dose Rationalization of Pembrolizumab and Nivolumab Using Pharmacokinetic Modeling and Simulation and Cost Analysis.

PubMed

Ogungbenro, Kayode; Patel, Alkesh; Duncombe, Robert; Nuttall, Richard; Clark, James; Lorigan, Paul

2018-04-01

Pembrolizumab and nivolumab are highly selective anti-programmed cell death 1 (PD-1) antibodies approved for the treatment of advanced malignancies. Variable exposure and significant wastage have been associated with body size dosing of monoclonal antibodies (mAbs). The following dosing strategies were evaluated using simulations: body weight, dose banding, fixed dose, and pharmacokinetic (PK)-based methods. The relative cost to body weight dosing for band, fixed 150 mg and 200 mg, and PK-derived strategies were -15%, -25%, + 7%, and -16% for pembrolizumab and -8%, -6%, and -10% for band, fixed, and PK-derived strategies for nivolumab, respectively. Relative to mg/kg doses, the median exposures were -1.0%, -4.6%, + 27.1%, and +3.0% for band, fixed 150 mg, fixed 200 mg, and PK-derived strategies, respectively, for pembrolizumab and -3.1%, + 1.9%, and +1.4% for band, fixed 240 mg, and PK-derived strategies, respectively, for nivolumab. Significant wastage can be reduced by alternative dosing strategies without compromising exposure and efficacy. © 2017 American Society for Clinical Pharmacology and Therapeutics.

Evaluating the performance of different predictor strategies in regression-based downscaling with a focus on glacierized mountain environments

NASA Astrophysics Data System (ADS)

Hofer, Marlis; Nemec, Johanna

2016-04-01

This study presents first steps towards verifying the hypothesis that uncertainty in global and regional glacier mass simulations can be reduced considerably by reducing the uncertainty in the high-resolution atmospheric input data. To this aim, we systematically explore the potential of different predictor strategies for improving the performance of regression-based downscaling approaches. The investigated local-scale target variables are precipitation, air temperature, wind speed, relative humidity and global radiation, all at a daily time scale. Observations of these target variables are assessed from three sites in geo-environmentally and climatologically very distinct settings, all within highly complex topography and in the close proximity to mountain glaciers: (1) the Vernagtbach station in the Northern European Alps (VERNAGT), (2) the Artesonraju measuring site in the tropical South American Andes (ARTESON), and (3) the Brewster measuring site in the Southern Alps of New Zealand (BREWSTER). As the large-scale predictors, ERA interim reanalysis data are used. In the applied downscaling model training and evaluation procedures, particular emphasis is put on appropriately accounting for the pitfalls of limited and/or patchy observation records that are usually the only (if at all) available data from the glacierized mountain sites. Generalized linear models and beta regression are investigated as alternatives to ordinary least squares regression for the non-Gaussian target variables. By analyzing results for the three different sites, five predictands and for different times of the year, we look for systematic improvements in the downscaling models' skill specifically obtained by (i) using predictor data at the optimum scale rather than the minimum scale of the reanalysis data, (ii) identifying the optimum predictor allocation in the vertical, and (iii) considering multiple (variable, level and/or grid point) predictor options combined with state-of-art empirical feature selection tools. First results show that in particular for air temperature, those downscaling models based on direct predictor selection show comparative skill like those models based on multiple predictors. For all other target variables, however, multiple predictor approaches can considerably outperform those models based on single predictors. Including multiple variable types emerges as the most promising predictor option (in particular for wind speed at all sites), even if the same predictor set is used across the different cases.

SSL: A Theory of How People Learn to Select Strategies

ERIC Educational Resources Information Center

Rieskamp, Jorg; Otto, Philipp E.

2006-01-01

The assumption that people possess a repertoire of strategies to solve the inference problems they face has been raised repeatedly. However, a computational model specifying how people select strategies from their repertoire is still lacking. The proposed strategy selection learning (SSL) theory predicts a strategy selection process on the basis…

Behavioral biomarkers of aging: illustration of a multivariate approach for detecting age-related behavioral changes.

PubMed

Markowska, A L; Breckler, S J

1999-12-01

The goal of the current project is to develop a multivariate statistical strategy for the formation of behavioral indices of performance and, further, to apply this strategy to establish the relationship between age and important characteristics of performance. The strategy was to begin with a large set of measures that span a broad range of behaviors. The behavioral effects of the following variables were examined: Age (4, 12, 24, and 30 months), genotype [Fischer 344 and a hybrid (F1) of Fischer 344 and Brown Norway (F344xBN)], gender (Fischer 344 males and Fischer 344 females), long-term diet (ad lib diet or dietary restriction beginning at 4 months of age), and short-term diet (ad lib diet or dietary restriction during testing). The behavioral measures were grouped into conceptually related indicators. The indicators within a set were submitted to a principal component analysis to help identify the summary indices of performance, which were formed with the assumption that these component scores would offer more reliable and valid measures of relevant aspects of behavioral performance than would individual measures taken alone. In summary, this approach has made a number of important contributions. It has provided sensitive and selective measures of performance that indicated contributions of all variables: psychological process, age, genotype, gender, long-term and short-term diet and has increased the sensitivity of behavioral measures to age-related behavioral impairment. It has also improved task-manageability by decreasing the number of meaningful variables without losing important information, consequently providing a simplification of the pattern of changes.

Differential approach to strategies of segmental stabilisation in postural control.

PubMed

Isableu, Brice; Ohlmann, Théophile; Crémieux, Jacques; Amblard, Bernard

2003-05-01

The present paper attempts to clarify the between-subjects variability exhibited in both segmental stabilisation strategies and their subordinated or associated sensory contribution. Previous data have emphasised close relationships between the interindividual variability in both the visual control of posture and the spatial visual perception. In this study, we focused on the possible relationships that might link perceptual visual field dependence-independence and the visual contribution to segmental stabilisation strategies. Visual field dependent (FD) and field independent (FI) subjects were selected on the basis of their extreme score in a static rod and frame test where an estimation of the subjective vertical was required. In the postural test, the subjects stood in the sharpened Romberg position in darkness or under normal or stroboscopic illumination, in front of either a vertical or a tilted frame. Strategies of segmental stabilisation of the head, shoulders and hip in the roll plane were analysed by means of their anchoring index (AI). Our hypothesis was that FD subjects might use mainly visual cues for calibrating not only their spatial perception but also their strategies of segmental stabilisation. In the case of visual cue disturbances, a greater visual dependency to the strategies of segmental stabilisation in FD subjects should be validated by observing more systematic "en bloc" functioning (i.e. negative AI) between two adjacent segments. The main results are the following: 1. Strategies of segmental stabilisation differed between both groups and differences were amplified with the deprivation of either total vision and/or static visual cues. 2. In the absence of total vision and/or static visual cues, FD subjects have shown an increased efficiency of the hip stabilisation in space strategy and an "en bloc" operation of the shoulder-hip unit (whole trunk). The last "en bloc" operation was extended to the whole head-trunk unit in darkness, associated with a hip stabilisation in space. 3. The FI subjects have adopted neither a strategy of segmental stabilisation in space nor on the underlying segment, whatever the body segment considered and the visual condition. Thus, in this group, head, shoulder and hip moved independently from each other during stance control, roughly without taking into account the visual condition. The results, emphasising a differential weighting of sensory input involved in both perceptual and postural control, are discussed in terms of the differential choice and/or ability to select the adequate frame of reference common to both cognitive and motor spatial activities. We assumed that a motor-somesthetics "neglect" or a lack of mastering of these inputs/outputs rather than a mere visual dependence in FD subjects would generate these interindividual differences in both spatial perception and postural balance. This proprioceptive "neglect" is assumed to lead FD subjects to sensory reweighting, whereas proprioceptive dominance would lead FI subjects to a greater ability in selecting the adequate frame of reference in the case of intersensory disturbances. Finally, this study also provides evidence for a new interpretation of the visual field dependence-independence dimension in both spatial perception and postural control.

Efficient Variable Selection Method for Exposure Variables on Binary Data

NASA Astrophysics Data System (ADS)

Ohno, Manabu; Tarumi, Tomoyuki

In this paper, we propose a new variable selection method for "robust" exposure variables. We define "robust" as property that the same variable can select among original data and perturbed data. There are few studies of effective for the selection method. The problem that selects exposure variables is almost the same as a problem that extracts correlation rules without robustness. [Brin 97] is suggested that correlation rules are possible to extract efficiently using chi-squared statistic of contingency table having monotone property on binary data. But the chi-squared value does not have monotone property, so it's is easy to judge the method to be not independent with an increase in the dimension though the variable set is completely independent, and the method is not usable in variable selection for robust exposure variables. We assume anti-monotone property for independent variables to select robust independent variables and use the apriori algorithm for it. The apriori algorithm is one of the algorithms which find association rules from the market basket data. The algorithm use anti-monotone property on the support which is defined by association rules. But independent property does not completely have anti-monotone property on the AIC of independent probability model, but the tendency to have anti-monotone property is strong. Therefore, selected variables with anti-monotone property on the AIC have robustness. Our method judges whether a certain variable is exposure variable for the independent variable using previous comparison of the AIC. Our numerical experiments show that our method can select robust exposure variables efficiently and precisely.

Using Temporal Modulation Sensitivity to Select Stimulation Sites for Processor MAPs in Cochlear Implant Listeners

PubMed Central

Garadat, Soha N.; Zwolan, Teresa A.; Pfingst, Bryan E.

2013-01-01

Previous studies in our laboratory showed that temporal acuity as assessed by modulation detection thresholds (MDTs) varied across activation sites and that this site-to-site variability was subject specific. Using two 10-channel MAPs, the previous experiments showed that processor MAPs that had better across-site mean (ASM) MDTs yielded better speech recognition than MAPs with poorer ASM MDTs tested in the same subject. The current study extends our earlier work on developing more optimal fitting strategies to test the feasibility of using a site-selection approach in the clinical domain. This study examined the hypothesis that revising the clinical speech processor MAP for cochlear implant (CI) recipients by turning off selected sites that have poorer temporal acuity and reallocating frequencies to the remaining electrodes would lead to improved speech recognition. Twelve CI recipients participated in the experiments. We found that site selection procedure based on MDTs in the presence of a masker resulted in improved performance on consonant recognition and recognition of sentences in noise. In contrast, vowel recognition was poorer with the experimental MAP than with the clinical MAP, possibly due to reduced spectral resolution when sites were removed from the experimental MAP. Overall, these results suggest a promising path for improving recipient outcomes using personalized processor-fitting strategies based on a psychophysical measure of temporal acuity. PMID:23881208

[Modelling the effect of local climatic variability on dengue transmission in Medellin (Colombia) by means of time series analysis].

PubMed

Rúa-Uribe, Guillermo L; Suárez-Acosta, Carolina; Chauca, José; Ventosilla, Palmira; Almanza, Rita

2013-09-01

Dengue fever is a major impact on public health vector-borne disease, and its transmission is influenced by entomological, sociocultural and economic factors. Additionally, climate variability plays an important role in the transmission dynamics. A large scientific consensus has indicated that the strong association between climatic variables and disease could be used to develop models to explain the incidence of the disease. To develop a model that provides a better understanding of dengue transmission dynamics in Medellin and predicts increases in the incidence of the disease. The incidence of dengue fever was used as dependent variable, and weekly climatic factors (maximum, mean and minimum temperature, relative humidity and precipitation) as independent variables. Expert Modeler was used to develop a model to better explain the behavior of the disease. Climatic variables with significant association to the dependent variable were selected through ARIMA models. The model explains 34% of observed variability. Precipitation was the climatic variable showing statistically significant association with the incidence of dengue fever, but with a 20 weeks delay. In Medellin, the transmission of dengue fever was influenced by climate variability, especially precipitation. The strong association dengue fever/precipitation allowed the construction of a model to help understand dengue transmission dynamics. This information will be useful to develop appropriate and timely strategies for dengue control.

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.

Toward a formalization of the process to select IMIA Yearbook best papers.

PubMed

Lamy, J-B; Séroussi, B; Griffon, N; Kerdelhué, G; Jaulent, M-C; Bouaud, J

2015-01-01

Each year, the International Medical Informatics Association Yearbook recognizes significant scientific papers, labelled as "best papers", published the previous year in the subfields of biomedical informatics that correspond to the different section topics of the journal. For each section, about fifteen pre-selected "candidate" best papers are externally peer-reviewed to select the actual best papers. Although based on the available literature, little is known about the pre-selection process. To move toward an explicit formalization of the candidate best papers selection process to reduce variability in the literature search across sections and over years. A methodological framework is proposed to build for each section topic specific queries tailored to PubMed and Web of Science citation databases. The two sets of returned papers are merged and reviewed by two independent section editors and citations are tagged as "discarded", "pending", and "kept". A protocolized consolidation step is then jointly conducted to resolve conflicts. A bibliographic software tool, BibReview, was developed to support the whole process. The proposed search strategy was fully applied to the Decision Support section of the 2013 edition of the Yearbook. For this section, 1124 references were returned (689 PubMed-specific, 254 WoS-specific, 181 common to both databases) among which the 15 candidate best papers were selected. The search strategy for determining candidate best papers for an IMIA Yearbook's section is now explicitly specified and allows for reproducibility. However, some aspects of the whole process remain reviewer-dependent, mostly because there is no characterization of a "best paper".

MRJP microsatellite markers in Africanized Apis mellifera colonies selected on the basis of royal jelly production.

PubMed

Parpinelli, R S; Ruvolo-Takasusuki, M C C; Toledo, V A A

2014-08-28

It is important to select the best honeybees that produce royal jelly to identify important molecular markers, such as major royal jelly proteins (MRJPs), and hence contribute to the development of new breeding strategies to improve the production of this substance. Therefore, this study focused on evaluating the genetic variability of mrjp3, mrjp5, and mrjp8 and associated allele maintenance during the process of selective reproduction in Africanized Apis mellifera individuals, which were chosen based on royal jelly production. The three loci analyzed were polymorphic, and produced a total of 16 alleles, with 4 new alleles, which were identified at mrjp5. The effective number of alleles at mrjp3 was 3.81. The observed average heterozygosity was 0.4905, indicating a high degree of genetic variability at these loci. The elevated FIS values for mrjp3, mrjp5, and mrjp8 (0.4188, 0.1077, and 0.2847, respectively) indicate an excess of homozygotes. The selection of Africanized A. mellifera queens for royal jelly production has maintained the mrjp3 C, D, and E alleles; although, the C allele occurred at a low frequency. The heterozygosity and FIS values show that the genetic variability of the queens is decreasing at the analyzed loci, generating an excess of homozygotes. However, the large numbers of drones that fertilize the queens make it difficult to develop homozygotes at mrjp3. Mating through instrumental insemination using the drones of known genotypes is required to increase the efficiency of Africanized A. mellifera-breeding programs, and to improve the quality and efficiency of commercial royal jelly apiaries.

The Role of Individual Differences and Situational Variables in the Use of Workplace Sexual Identity Management Strategies.

PubMed

Reed, Louren; Leuty, Melanie E

2016-07-01

Examination of individual difference variables have been largely ignored within research on the use of workplace sexual identity management strategies. The current study examined personality traits (extraversion, openness, and neuroticism), facets of sexual identity development (identity confusion, internalized heterosexism), and situational variables (e.g., perceptions of workplace climate and heterosexism) in explaining the use of management strategies, as well as possible interactions between individual and situational factors. Perceptions of the workplace climate toward lesbian and gay individuals significantly related to the use each of the management strategies, and Internalized Heterosexism was found to significantly predict the use of the Explicitly Out strategy. Most interactions between individual difference and situational variables were not supported, with the exception of an interaction between workplace heterosexism and internalized homophobia in explaining the use of the Explicitly Out strategy.

Analysis of host response to bacterial infection using error model based gene expression microarray experiments

PubMed Central

Stekel, Dov J.; Sarti, Donatella; Trevino, Victor; Zhang, Lihong; Salmon, Mike; Buckley, Chris D.; Stevens, Mark; Pallen, Mark J.; Penn, Charles; Falciani, Francesco

2005-01-01

A key step in the analysis of microarray data is the selection of genes that are differentially expressed. Ideally, such experiments should be properly replicated in order to infer both technical and biological variability, and the data should be subjected to rigorous hypothesis tests to identify the differentially expressed genes. However, in microarray experiments involving the analysis of very large numbers of biological samples, replication is not always practical. Therefore, there is a need for a method to select differentially expressed genes in a rational way from insufficiently replicated data. In this paper, we describe a simple method that uses bootstrapping to generate an error model from a replicated pilot study that can be used to identify differentially expressed genes in subsequent large-scale studies on the same platform, but in which there may be no replicated arrays. The method builds a stratified error model that includes array-to-array variability, feature-to-feature variability and the dependence of error on signal intensity. We apply this model to the characterization of the host response in a model of bacterial infection of human intestinal epithelial cells. We demonstrate the effectiveness of error model based microarray experiments and propose this as a general strategy for a microarray-based screening of large collections of biological samples. PMID:15800204

Variability in colonization of arbuscular mycorrhizal fungi and its effect on mycorrhizal dependency of improved and unimproved soybean cultivars.

PubMed

Salloum, M S; Guzzo, M C; Velazquez, M S; Sagadin, M B; Luna, C M

2016-12-01

Breeding selection of germplasm under fertilized conditions may reduce the frequency of genes that promote mycorrhizal associations. This study was developed to compare variability in mycorrhizal colonization and its effect on mycorrhizal dependency (MD) in improved soybean genotypes (I-1 and I-2) with differential tolerance to drought stress, and in unimproved soybean genotypes (UI-3 and UI-4). As inoculum, a mixed native arbuscular mycorrhizal fungi (AMF) was isolated from soybean roots, showing spores mostly of the species Funneliformis mosseae. At 20 days, unimproved genotypes followed by I-2, showed an increase in arbuscule formation, but not in I-1. At 40 days, mycorrhizal plants showed an increase in nodulation, this effect being more evident in unimproved genotypes. Mycorrhizal dependency, evaluated as growth and biochemical parameters from oxidative stress was increased in unimproved and I-2 since 20 days, whereas in I-1, MD increased at 40 days. We cannot distinguish significant differences in AMF colonization and MD between unimproved and I-2. However, variability among improved genotypes was observed. Our results suggest that selection for improved soybean genotypes with good and rapid AMF colonization, particularly high arbuscule/hyphae ratio could be a useful strategy for the development of genotypes that optimize AMF contribution to cropping systems.

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.

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

Strategies for minimizing sample size for use in airborne LiDAR-based forest inventory

USGS Publications Warehouse

Junttila, Virpi; Finley, Andrew O.; Bradford, John B.; Kauranne, Tuomo

2013-01-01

Recently airborne Light Detection And Ranging (LiDAR) has emerged as a highly accurate remote sensing modality to be used in operational scale forest inventories. Inventories conducted with the help of LiDAR are most often model-based, i.e. they use variables derived from LiDAR point clouds as the predictive variables that are to be calibrated using field plots. The measurement of the necessary field plots is a time-consuming and statistically sensitive process. Because of this, current practice often presumes hundreds of plots to be collected. But since these plots are only used to calibrate regression models, it should be possible to minimize the number of plots needed by carefully selecting the plots to be measured. In the current study, we compare several systematic and random methods for calibration plot selection, with the specific aim that they be used in LiDAR based regression models for forest parameters, especially above-ground biomass. The primary criteria compared are based on both spatial representativity as well as on their coverage of the variability of the forest features measured. In the former case, it is important also to take into account spatial auto-correlation between the plots. The results indicate that choosing the plots in a way that ensures ample coverage of both spatial and feature space variability improves the performance of the corresponding models, and that adequate coverage of the variability in the feature space is the most important condition that should be met by the set of plots collected.

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

PubMed

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

2010-06-01

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

Age trends of genetic parameters, early selection and family by site interactions for growth traits in Larix kaempferi open-pollinated families.

PubMed

Diao, Shu; Hou, Yimei; Xie, Yunhui; Sun, Xiaomei

2016-07-07

Japanese larch (Larix kaempferi) as a successful exotic species has become one of the most important economic and ecological conifers in China. In order to broaden the genetic resource of Larix kaempferi, an effort was made in 1996 to introduce 128 families from seven seed orchards in Japan, with which to establish two progeny trials in climatically different environments. The experiment was aimed to determine the strategy of early selection, particularly important for long-rotated Japanese larch, and the optimal breeding program for specific environments. Growth trajectories revealed different growth performances of stem height (HGT) and diameter at breast height (DBH) in two different environments, Hubei and Liaoning. In both sites, there were marked variabilities in HGT, DBH and volume (VOL) among families at each year. The trends of individual and family heritability and age-age correlations were found to follow a certain dynamic pattern. Based on these trends, the optimum selection age was determined at four years for HGT and five years for DBH in Hubei and Liaoning. Genetic gains for VOL were 34.4 and 6.04 % in Hubei and Liaoning respectively when selection ratio was 10 % at age 16. Type-B correlations were less than 0.67 and rank correlations of breeding value were less than 0.4 for HGT, DBH and VOL between the two sites, revealing that there exist pronounced family-by-site interactions for the growth traits of Larix kaempferi. Early selection for Larix kaempferi is an effective strategy to overcome its long rotation age. In early selection, dual growth trait selection is more effective than single one. Regionalization deployment should be considered in Larix. kaempferi breeding program based on different environmental factors.

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.

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

Cognitive Niches: An Ecological Model of Strategy Selection

ERIC Educational Resources Information Center

Marewski, Julian N.; Schooler, Lael J.

2011-01-01

How do people select among different strategies to accomplish a given task? Across disciplines, the strategy selection problem represents a major challenge. We propose a quantitative model that predicts how selection emerges through the interplay among strategies, cognitive capacities, and the environment. This interplay carves out for each…

'Who is the ideal candidate?': decisions and issues relating to visual neuroprosthesis development, patient testing and neuroplasticity

NASA Astrophysics Data System (ADS)

Merabet, Lotfi B.; Rizzo, Joseph F., III; Pascual-Leone, Alvaro; Fernandez, Eduardo

2007-03-01

Appropriate delivery of electrical stimulation to intact visual structures can evoke patterned sensations of light in individuals who have been blind for many years. This pivotal finding has lent credibility to the concept of restoring functional vision by artificial means. As numerous groups worldwide pursue human clinical testing with visual prosthetic devices, it is becoming increasingly clear that there remains a considerable gap between the challenges of prosthetic device development and the rehabilitative strategies needed to implement this new technology in patients. An important area of future work will be the development of appropriate pre- and post-implantation measures of performance and establishing candidate selection criteria in order to quantify technical advances, guide future device design and optimize therapeutic success. We propose that the selection of an 'ideal' candidate should also be considered within the context of the variable neuroplastic changes that follow vision loss. Specifically, an understanding of the adaptive and compensatory changes that occur within the brain could assist in guiding the development of post-implantation rehabilitative strategies and optimize behavioral outcomes.

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.

POTENTIAL EFFECTS OF WHOLE-BODY VIBRATION EXERCISES ON BLOOD FLOW KINETICS OF DIFFERENT POPULATIONS: A SYSTEMATIC REVIEW WITH A SUITABLE APPROACH.

PubMed

Sá-Caputo, Danúbia; Paineiras-Domingos, Laisa; Carvalho-Lima, Rafaelle; Dias-Costa, Glenda; de Paiva, Patrícia de Castro; de Azeredo, Claudia Figueiredo; Carmo, Roberto Carlos Resende; Dionello, Carla F; Moreira-Marconi, Eloá; Frederico, Éric Heleno F F; Sousa-Gonçalves, Cintia Renata; Morel, Danielle S; Paiva, Dulciane N; Avelar, Núbia C P; Lacerda, Ana C; Magalhães, Carlos E V; Castro, Leonardo S; Presta, Giuseppe A; de Paoli, Severo; Sañudo, Borja; Bernardo-Filho, Mario

2017-01-01

The ability to control skin blood flow decreases with advancing age and some clinical disorders, as in diabetes and in rheumatologic diseases. Feasible clinical strategies such as whole-body vibration exercise (WBVE) are being used without a clear understanding of its effects. The aim of the present study is to review the effects of the WBVE on blood flow kinetics and its feasibility in different populations. The level of evidence (LE) of selected papers in PubMed and/or PEDRo databases was determined. We selected randomized, controlled trials in English to be evaluated. Six studies had LE II, one had LE III-2 and one III-3 according to the NHMRC. A great variability among the protocols was observed but also in the assessment devices; therefore, more research about this topic is warranted. Despite the limitations, it is can be concluded that the use of WBVE has proven to be a safe and useful strategy to improve blood flow. However, more studies with greater methodological quality are needed to clearly define the more suitable protocols.

Preventing the return of fear using reconsolidation updating and methylene blue is differentially dependent on extinction learning

PubMed Central

Auchter, Allison M.; Shumake, Jason; Gonzalez-Lima, Francisco; Monfils, Marie H.

2017-01-01

Many factors account for how well individuals extinguish conditioned fears, such as genetic variability, learning capacity and conditions under which extinction training is administered. We predicted that memory-based interventions would be more effective to reduce the reinstatement of fear in subjects genetically predisposed to display more extinction learning. We tested this hypothesis in rats genetically selected for differences in fear extinction using two strategies: (1) attenuation of fear memory using post-retrieval extinction training, and (2) pharmacological enhancement of the extinction memory after extinction training by low-dose USP methylene blue (MB). Subjects selectively bred for divergent extinction phenotypes were fear conditioned to a tone stimulus and administered either standard extinction training or retrieval + extinction. Following extinction, subjects received injections of saline or MB. Both reconsolidation updating and MB administration showed beneficial effects in preventing fear reinstatement, but differed in the groups they targeted. Reconsolidation updating showed an overall effect in reducing fear reinstatement, whereas pharmacological memory enhancement using MB was an effective strategy, but only for individuals who were responsive to extinction. PMID:28397861

A catalog of galaxy morphology and photometric redshift

NASA Astrophysics Data System (ADS)

Paul, Nicholas; Shamir, Lior

2018-01-01

Morphology carries important information about the physical characteristics of a galaxy. Here we used machine learning to produce a catalog of ~3,000,000 SDSS galaxies classified by their broad morphology into spiral and elliptical galaxies. Comparison of the catalog to Galaxy Zooshows that the catalog contains a subset of 1.7*10^6 galaxies classified with the same level of consistency as the debiased “superclean” sub-sample. In addition to the morphology, we also computed the photometric redshifts of the galaxies. Several pattern recognition algorithms and variable selection strategies were tested, and the best accuracy of mean absolute error of ~0.0062 was achieved by using random forest with a combination of manually and automatically selected variables. The catalog shows that for redshift lower than 0.085 galaxies that visually look spiral become more prevalent as the redshift gets higher. For redshift greater than 0.085 galaxies thatvisually look elliptical become more prevalent. The catalog as well as the source code used to produce it is publicly available athttps://figshare.com/articles/Morphology_and_photometric_redshift_catalog/4833593 .

Evolutionary algorithm for vehicle driving cycle generation.

PubMed

Perhinschi, Mario G; Marlowe, Christopher; Tamayo, Sergio; Tu, Jun; Wayne, W Scott

2011-09-01

Modeling transit bus emissions and fuel economy requires a large amount of experimental data over wide ranges of operational conditions. Chassis dynamometer tests are typically performed using representative driving cycles defined based on vehicle instantaneous speed as sequences of "microtrips", which are intervals between consecutive vehicle stops. Overall significant parameters of the driving cycle, such as average speed, stops per mile, kinetic intensity, and others, are used as independent variables in the modeling process. Performing tests at all the necessary combinations of parameters is expensive and time consuming. In this paper, a methodology is proposed for building driving cycles at prescribed independent variable values using experimental data through the concatenation of "microtrips" isolated from a limited number of standard chassis dynamometer test cycles. The selection of the adequate "microtrips" is achieved through a customized evolutionary algorithm. The genetic representation uses microtrip definitions as genes. Specific mutation, crossover, and karyotype alteration operators have been defined. The Roulette-Wheel selection technique with elitist strategy drives the optimization process, which consists of minimizing the errors to desired overall cycle parameters. This utility is part of the Integrated Bus Information System developed at West Virginia University.

Association between age factors and strategies for promoting participation in gastric and colorectal cancer screenings.

PubMed

Hamashima, Chisato; Sano, Hiroshi

2018-03-27

Despite the long history of cancer screening in Japan, the participation rates in gastric and colorectal cancer screenings have not increased. Strategies for improving the participation rates have been proposed, but differences in their effects among different age groups remain unclear. The Japanese government conducted a national survey in all municipalities in Japan in 2010 to investigate whether the implementation of promotion strategies increased participation in cancer screening. We investigated the association between age factors and strategies for promoting participation in cancer screening based on this national survey. Multiple regression analysis with generalized linear model was performed using the participation rates in gastric and colorectal cancer screenings as dependent variables, and the following strategies for promoting participation as independent variables: 1) personal invitation letters, 2) household invitation letters, 3) home visits by community nurses, 4) screenings in medical offices, and 5) free cancer screening programs. One thousand six hundred thirty nine municipalities for gastric cancer screening and 1666 municipalities for colorectal cancer screening were selected for the analysis. In gastric and colorectal cancer screenings, the participation rates of individuals aged 60-69 years was higher than those of other age groups. Personal and household invitation letters were effective promotion strategies for all age groups, which encouraged even older people to participate in gastric and colorectal cancer screenings. Screening in medical offices and free screenings were not effective in all age groups. Home visits were effective, but their adoption was limited to small municipalities. To clarify whether promotion strategies can increase the participation rate in cancer screening among different age groups, 5 strategies were assessed on the basis of a national survey. Although personal and household invitation letters were effective strategies for promoting participation in cancer screening for all age groups, these strategies equally encouraged older people to participate in gastric and colorectal cancer screenings. If resource for sending invitation letters are limited, priority should be given to individuals who are in their 50s and 60s for gastric and colorectal cancer screening.

Predictors of Outcomes in Autism Early Intervention: Why Don’t We Know More?

PubMed Central

Vivanti, Giacomo; Prior, Margot; Williams, Katrina; Dissanayake, Cheryl

2014-01-01

Response to early intervention programs in autism is variable. However, the factors associated with positive versus poor treatment outcomes remain unknown. Hence the issue of which intervention/s should be chosen for an individual child remains a common dilemma. We argue that lack of knowledge on “what works for whom and why” in autism reflects a number of issues in current approaches to outcomes research, and we provide recommendations to address these limitations. These include: a theory-driven selection of putative predictors; the inclusion of proximal measures that are directly relevant to the learning mechanisms demanded by the specific educational strategies; the consideration of family characteristics. Moreover, all data on associations between predictor and outcome variables should be reported in treatment studies. PMID:24999470

Food security and climate change: on the potential to adapt global crop production by active selection to rising atmospheric carbon dioxide

PubMed Central

Ziska, Lewis H.; Bunce, James A.; Shimono, Hiroyuki; Gealy, David R.; Baker, Jeffrey T.; Newton, Paul C. D.; Reynolds, Matthew P.; Jagadish, Krishna S. V.; Zhu, Chunwu; Howden, Mark; Wilson, Lloyd T.

2012-01-01

Agricultural production is under increasing pressure by global anthropogenic changes, including rising population, diversion of cereals to biofuels, increased protein demands and climatic extremes. Because of the immediate and dynamic nature of these changes, adaptation measures are urgently needed to ensure both the stability and continued increase of the global food supply. Although potential adaption options often consider regional or sectoral variations of existing risk management (e.g. earlier planting dates, choice of crop), there may be a global-centric strategy for increasing productivity. In spite of the recognition that atmospheric carbon dioxide (CO2) is an essential plant resource that has increased globally by approximately 25 per cent since 1959, efforts to increase the biological conversion of atmospheric CO2 to stimulate seed yield through crop selection is not generally recognized as an effective adaptation measure. In this review, we challenge that viewpoint through an assessment of existing studies on CO2 and intraspecific variability to illustrate the potential biological basis for differential plant response among crop lines and demonstrate that while technical hurdles remain, active selection and breeding for CO2 responsiveness among cereal varieties may provide one of the simplest and direct strategies for increasing global yields and maintaining food security with anthropogenic change. PMID:22874755

Food security and climate change: on the potential to adapt global crop production by active selection to rising atmospheric carbon dioxide.

PubMed

Ziska, Lewis H; Bunce, James A; Shimono, Hiroyuki; Gealy, David R; Baker, Jeffrey T; Newton, Paul C D; Reynolds, Matthew P; Jagadish, Krishna S V; Zhu, Chunwu; Howden, Mark; Wilson, Lloyd T

2012-10-22

Agricultural production is under increasing pressure by global anthropogenic changes, including rising population, diversion of cereals to biofuels, increased protein demands and climatic extremes. Because of the immediate and dynamic nature of these changes, adaptation measures are urgently needed to ensure both the stability and continued increase of the global food supply. Although potential adaption options often consider regional or sectoral variations of existing risk management (e.g. earlier planting dates, choice of crop), there may be a global-centric strategy for increasing productivity. In spite of the recognition that atmospheric carbon dioxide (CO(2)) is an essential plant resource that has increased globally by approximately 25 per cent since 1959, efforts to increase the biological conversion of atmospheric CO(2) to stimulate seed yield through crop selection is not generally recognized as an effective adaptation measure. In this review, we challenge that viewpoint through an assessment of existing studies on CO(2) and intraspecific variability to illustrate the potential biological basis for differential plant response among crop lines and demonstrate that while technical hurdles remain, active selection and breeding for CO(2) responsiveness among cereal varieties may provide one of the simplest and direct strategies for increasing global yields and maintaining food security with anthropogenic change.

Selection of Representative Models for Decision Analysis Under Uncertainty

NASA Astrophysics Data System (ADS)

Meira, Luis A. A.; Coelho, Guilherme P.; Santos, Antonio Alberto S.; Schiozer, Denis J.

2016-03-01

The decision-making process in oil fields includes a step of risk analysis associated with the uncertainties present in the variables of the problem. Such uncertainties lead to hundreds, even thousands, of possible scenarios that are supposed to be analyzed so an effective production strategy can be selected. Given this high number of scenarios, a technique to reduce this set to a smaller, feasible subset of representative scenarios is imperative. The selected scenarios must be representative of the original set and also free of optimistic and pessimistic bias. This paper is devoted to propose an assisted methodology to identify representative models in oil fields. To do so, first a mathematical function was developed to model the representativeness of a subset of models with respect to the full set that characterizes the problem. Then, an optimization tool was implemented to identify the representative models of any problem, considering not only the cross-plots of the main output variables, but also the risk curves and the probability distribution of the attribute-levels of the problem. The proposed technique was applied to two benchmark cases and the results, evaluated by experts in the field, indicate that the obtained solutions are richer than those identified by previously adopted manual approaches. The program bytecode is available under request.

Non-targeted 1H NMR fingerprinting and multivariate statistical analyses for the characterisation of the geographical origin of Italian sweet cherries.

PubMed

Longobardi, F; Ventrella, A; Bianco, A; Catucci, L; Cafagna, I; Gallo, V; Mastrorilli, P; Agostiano, A

2013-12-01

In this study, non-targeted (1)H NMR fingerprinting was used in combination with multivariate statistical techniques for the classification of Italian sweet cherries based on their different geographical origins (Emilia Romagna and Puglia). As classification techniques, Soft Independent Modelling of Class Analogy (SIMCA), Partial Least Squares Discriminant Analysis (PLS-DA), and Linear Discriminant Analysis (LDA) were carried out and the results were compared. For LDA, before performing a refined selection of the number/combination of variables, two different strategies for a preliminary reduction of the variable number were tested. The best average recognition and CV prediction abilities (both 100.0%) were obtained for all the LDA models, although PLS-DA also showed remarkable performances (94.6%). All the statistical models were validated by observing the prediction abilities with respect to an external set of cherry samples. The best result (94.9%) was obtained with LDA by performing a best subset selection procedure on a set of 30 principal components previously selected by a stepwise decorrelation. The metabolites that mostly contributed to the classification performances of such LDA model, were found to be malate, glucose, fructose, glutamine and succinate. Copyright © 2013 Elsevier Ltd. All rights reserved.

A Highly Efficient Design Strategy for Regression with Outcome Pooling

PubMed Central

Mitchell, Emily M.; Lyles, Robert H.; Manatunga, Amita K.; Perkins, Neil J.; Schisterman, Enrique F.

2014-01-01

The potential for research involving biospecimens can be hindered by the prohibitive cost of performing laboratory assays on individual samples. To mitigate this cost, strategies such as randomly selecting a portion of specimens for analysis or randomly pooling specimens prior to performing laboratory assays may be employed. These techniques, while effective in reducing cost, are often accompanied by a considerable loss of statistical efficiency. We propose a novel pooling strategy based on the k-means clustering algorithm to reduce laboratory costs while maintaining a high level of statistical efficiency when predictor variables are measured on all subjects, but the outcome of interest is assessed in pools. We perform simulations motivated by the BioCycle study to compare this k-means pooling strategy with current pooling and selection techniques under simple and multiple linear regression models. While all of the methods considered produce unbiased estimates and confidence intervals with appropriate coverage, pooling under k-means clustering provides the most precise estimates, closely approximating results from the full data and losing minimal precision as the total number of pools decreases. The benefits of k-means clustering evident in the simulation study are then applied to an analysis of the BioCycle dataset. In conclusion, when the number of lab tests is limited by budget, pooling specimens based on k-means clustering prior to performing lab assays can be an effective way to save money with minimal information loss in a regression setting. PMID:25220822

The evaluation of complex interventions in palliative care: an exploration of the potential of case study research strategies.

PubMed

Walshe, Catherine

2011-12-01

Complex, incrementally changing, context dependent and variable palliative care services are difficult to evaluate. Case study research strategies may have potential to contribute to evaluating such complex interventions, and to develop this field of evaluation research. This paper explores definitions of case study (as a unit of study, a process, and a product) and examines the features of case study research strategies which are thought to confer benefits for the evaluation of complex interventions in palliative care settings. Ten features of case study that are thought to be beneficial in evaluating complex interventions in palliative care are discussed, drawing from exemplars of research in this field. Important features are related to a longitudinal approach, triangulation, purposive instance selection, comprehensive approach, multiple data sources, flexibility, concurrent data collection and analysis, search for proving-disproving evidence, pattern matching techniques and an engaging narrative. The limitations of case study approaches are discussed including the potential for subjectivity and their complex, time consuming and potentially expensive nature. Case study research strategies have great potential in evaluating complex interventions in palliative care settings. Three key features need to be exploited to develop this field: case selection, longitudinal designs, and the use of rival hypotheses. In particular, case study should be used in situations where there is interplay and interdependency between the intervention and its context, such that it is difficult to define or find relevant comparisons.

A highly efficient design strategy for regression with outcome pooling.

PubMed

Mitchell, Emily M; Lyles, Robert H; Manatunga, Amita K; Perkins, Neil J; Schisterman, Enrique F

2014-12-10

The potential for research involving biospecimens can be hindered by the prohibitive cost of performing laboratory assays on individual samples. To mitigate this cost, strategies such as randomly selecting a portion of specimens for analysis or randomly pooling specimens prior to performing laboratory assays may be employed. These techniques, while effective in reducing cost, are often accompanied by a considerable loss of statistical efficiency. We propose a novel pooling strategy based on the k-means clustering algorithm to reduce laboratory costs while maintaining a high level of statistical efficiency when predictor variables are measured on all subjects, but the outcome of interest is assessed in pools. We perform simulations motivated by the BioCycle study to compare this k-means pooling strategy with current pooling and selection techniques under simple and multiple linear regression models. While all of the methods considered produce unbiased estimates and confidence intervals with appropriate coverage, pooling under k-means clustering provides the most precise estimates, closely approximating results from the full data and losing minimal precision as the total number of pools decreases. The benefits of k-means clustering evident in the simulation study are then applied to an analysis of the BioCycle dataset. In conclusion, when the number of lab tests is limited by budget, pooling specimens based on k-means clustering prior to performing lab assays can be an effective way to save money with minimal information loss in a regression setting. Copyright © 2014 John Wiley & Sons, Ltd.

A systematic review on the composting of green waste: Feedstock quality and optimization strategies.

PubMed

Reyes-Torres, M; Oviedo-Ocaña, E R; Dominguez, I; Komilis, D; Sánchez, A

2018-04-27

Green waste (GW) is an important fraction of municipal solid waste (MSW). The composting of lignocellulosic GW is challenging due to its low decomposition rate. Recently, an increasing number of studies that include strategies to optimize GW composting appeared in the literature. This literature review focuses on the physicochemical quality of GW and on the effect of strategies used to improve the process and product quality. A systematic search was carried out, using keywords, and 447 papers published between 2002 and 2018 were identified. After a screening process, 41 papers addressing feedstock quality and 32 papers on optimization strategies were selected to be reviewed and analyzed in detail. The GW composition is highly variable due to the diversity of the source materials, the type of vegetation, and climatic conditions. This variability limits a strict categorization of the GW physicochemical characteristics. However, this research established that the predominant features of GW are a C/N ratio higher than 25, a deficit in important nutrients, namely nitrogen (0.5-1.5% db), phosphorous (0.1-0.2% db) and potassium (0.4-0.8% db) and a high content of recalcitrant organic compounds (e.g. lignin). The promising strategies to improve composting of GW were: i) GW particle size reduction (e.g. shredding and separation of GW fractions); ii) addition of energy amendments (e.g. non-refined sugar, phosphate rock, food waste, volatile ashes), bulking materials (e.g. biocarbon, wood chips), or microbial inoculum (e.g. fungal consortia); and iii) variations in operating parameters (aeration, temperature, and two-phase composting). These alternatives have successfully led to the reduction of process length and have managed to transform recalcitrant substances to a high-quality end-product. Copyright © 2018 Elsevier Ltd. All rights reserved.

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.

Improving automatic peptide mass fingerprint protein identification by combining many peak sets.

PubMed

Rögnvaldsson, Thorsteinn; Häkkinen, Jari; Lindberg, Claes; Marko-Varga, György; Potthast, Frank; Samuelsson, Jim

2004-08-05

An automated peak picking strategy is presented where several peak sets with different signal-to-noise levels are combined to form a more reliable statement on the protein identity. The strategy is compared against both manual peak picking and industry standard automated peak picking on a set of mass spectra obtained after tryptic in gel digestion of 2D-gel samples from human fetal fibroblasts. The set of spectra contain samples ranging from strong to weak spectra, and the proposed multiple-scale method is shown to be much better on weak spectra than the industry standard method and a human operator, and equal in performance to these on strong and medium strong spectra. It is also demonstrated that peak sets selected by a human operator display a considerable variability and that it is impossible to speak of a single "true" peak set for a given spectrum. The described multiple-scale strategy both avoids time-consuming parameter tuning and exceeds the human operator in protein identification efficiency. The strategy therefore promises reliable automated user-independent protein identification using peptide mass fingerprints.

Dynamics of melanoma tumor therapy with vesicular stomatitis virus: explaining the variability in outcomes using mathematical modeling.

PubMed

Rommelfanger, D M; Offord, C P; Dev, J; Bajzer, Z; Vile, R G; Dingli, D

2012-05-01

Tumor selective, replication competent viruses are being tested for cancer gene therapy. This approach introduces a new therapeutic paradigm due to potential replication of the therapeutic agent and induction of a tumor-specific immune response. However, the experimental outcomes are quite variable, even when studies utilize highly inbred strains of mice and the same cell line and virus. Recognizing that virotherapy is an exercise in population dynamics, we utilize mathematical modeling to understand the variable outcomes observed when B16ova malignant melanoma tumors are treated with vesicular stomatitis virus in syngeneic, fully immunocompetent mice. We show how variability in the initial tumor size and the actual amount of virus delivered to the tumor have critical roles on the outcome of therapy. Virotherapy works best when tumors are small, and a robust innate immune response can lead to superior tumor control. Strategies that reduce tumor burden without suppressing the immune response and methods that maximize the amount of virus delivered to the tumor should optimize tumor control in this model system.

Identification of solid state fermentation degree with FT-NIR spectroscopy: Comparison of wavelength variable selection methods of CARS and SCARS.

PubMed

Jiang, Hui; Zhang, Hang; Chen, Quansheng; Mei, Congli; Liu, Guohai

2015-01-01

The use of wavelength variable selection before partial least squares discriminant analysis (PLS-DA) for qualitative identification of solid state fermentation degree by FT-NIR spectroscopy technique was investigated in this study. Two wavelength variable selection methods including competitive adaptive reweighted sampling (CARS) and stability competitive adaptive reweighted sampling (SCARS) were employed to select the important wavelengths. PLS-DA was applied to calibrate identified model using selected wavelength variables by CARS and SCARS for identification of solid state fermentation degree. Experimental results showed that the number of selected wavelength variables by CARS and SCARS were 58 and 47, respectively, from the 1557 original wavelength variables. Compared with the results of full-spectrum PLS-DA, the two wavelength variable selection methods both could enhance the performance of identified models. Meanwhile, compared with CARS-PLS-DA model, the SCARS-PLS-DA model achieved better results with the identification rate of 91.43% in the validation process. The overall results sufficiently demonstrate the PLS-DA model constructed using selected wavelength variables by a proper wavelength variable method can be more accurate identification of solid state fermentation degree. Copyright © 2015 Elsevier B.V. All rights reserved.

Identification of solid state fermentation degree with FT-NIR spectroscopy: Comparison of wavelength variable selection methods of CARS and SCARS

NASA Astrophysics Data System (ADS)

Jiang, Hui; Zhang, Hang; Chen, Quansheng; Mei, Congli; Liu, Guohai

2015-10-01

The use of wavelength variable selection before partial least squares discriminant analysis (PLS-DA) for qualitative identification of solid state fermentation degree by FT-NIR spectroscopy technique was investigated in this study. Two wavelength variable selection methods including competitive adaptive reweighted sampling (CARS) and stability competitive adaptive reweighted sampling (SCARS) were employed to select the important wavelengths. PLS-DA was applied to calibrate identified model using selected wavelength variables by CARS and SCARS for identification of solid state fermentation degree. Experimental results showed that the number of selected wavelength variables by CARS and SCARS were 58 and 47, respectively, from the 1557 original wavelength variables. Compared with the results of full-spectrum PLS-DA, the two wavelength variable selection methods both could enhance the performance of identified models. Meanwhile, compared with CARS-PLS-DA model, the SCARS-PLS-DA model achieved better results with the identification rate of 91.43% in the validation process. The overall results sufficiently demonstrate the PLS-DA model constructed using selected wavelength variables by a proper wavelength variable method can be more accurate identification of solid state fermentation degree.

Flex Fuel Optimized SI and HCCI Engine

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

Zhu, Guoming; Schock, Harold; Yang, Xiaojian

The central objective of the proposed work is to demonstrate an HCCI (homogeneous charge compression ignition) capable SI (spark ignited) engine that is capable of fast and smooth mode transition between SI and HCCI combustion modes. The model-based control technique was used to develop and validate the proposed control strategy for the fast and smooth combustion mode transition based upon the developed control-oriented engine; and an HCCI capable SI engine was designed and constructed using production ready two-step valve-train with electrical variable valve timing actuating system. Finally, smooth combustion mode transition was demonstrated on a metal engine within eight enginemore » cycles. The Chrysler turbocharged 2.0L I4 direct injection engine was selected as the base engine for the project and the engine was modified to fit the two-step valve with electrical variable valve timing actuating system. To develop the model-based control strategy for stable HCCI combustion and smooth combustion mode transition between SI and HCCI combustion, a control-oriented real-time engine model was developed and implemented into the MSU HIL (hardware-in-the-loop) simulation environment. The developed model was used to study the engine actuating system requirement for the smooth and fast combustion mode transition and to develop the proposed mode transition control strategy. Finally, a single cylinder optical engine was designed and fabricated for studying the HCCI combustion characteristics. Optical engine combustion tests were conducted in both SI and HCCI combustion modes and the test results were used to calibrate the developed control-oriented engine model. Intensive GT-Power simulations were conducted to determine the optimal valve lift (high and low) and the cam phasing range. Delphi was selected to be the supplier for the two-step valve-train and Denso to be the electrical variable valve timing system supplier. A test bench was constructed to develop control strategies for the electrical variable valve timing (VVT) actuating system and satisfactory electrical VVT responses were obtained. Target engine control system was designed and fabricated at MSU for both single-cylinder optical and multi-cylinder metal engines. Finally, the developed control-oriented engine model was successfully implemented into the HIL simulation environment. The Chrysler 2.0L I4 DI engine was modified to fit the two-step vale with electrical variable valve timing actuating system. A used prototype engine was used as the base engine and the cylinder head was modified for the two-step valve with electrical VVT actuating system. Engine validation tests indicated that cylinder #3 has very high blow-by and it cannot be reduced with new pistons and rings. Due to the time constraint, it was decided to convert the four-cylinder engine into a single cylinder engine by blocking both intake and exhaust ports of the unused cylinders. The model-based combustion mode transition control algorithm was developed in the MSU HIL simulation environment and the Simulink based control strategy was implemented into the target engine controller. With both single-cylinder metal engine and control strategy ready, stable HCCI combustion was achived with COV of 2.1% Motoring tests were conducted to validate the actuator transient operations including valve lift, electrical variable valve timing, electronic throttle, multiple spark and injection controls. After the actuator operations were confirmed, 15-cycle smooth combustion mode transition from SI to HCCI combustion was achieved; and fast 8-cycle smooth combustion mode transition followed. With a fast electrical variable valve timing actuator, the number of engine cycles required for mode transition can be reduced down to five. It was also found that the combustion mode transition is sensitive to the charge air and engine coolant temperatures and regulating the corresponding temperatures to the target levels during the combustion mode transition is the key for a smooth combustion mode transition. As a summary, the proposed combustion mode transition strategy using the hybrid combustion mode that starts with the SI combustion and ends with the HCCI combustion was experimentally validated on a metal engine. The proposed model-based control approach made it possible to complete the SI-HCCI combustion mode transition within eight engine cycles utilizing the well controlled hybrid combustion mode. Without intensive control-oriented engine modeling and HIL simulation study of using the hybrid combustion mode during the mode transition, it would be impossible to validate the proposed combustion mode transition strategy in a very short period.« less

Managing uncertainty: information and insurance under the risk of starvation.

PubMed Central

Dall, Sasha R X; Johnstone, Rufus A

2002-01-01

In an uncertain world, animals face both unexpected opportunities and danger. Such outcomes can select for two potential strategies: collecting information to reduce uncertainty, or insuring against it. We investigate the relative value of information and insurance (energy reserves) under starvation risk by offering model foragers a choice between constant and varying food sources over finite foraging bouts. We show that sampling the variable option (choosing it when it is not expected to be good) should decline both with lower reserves and late in foraging bouts; in order to be able to reap the reduction in uncertainty associated with exploiting a variable resource effectively, foragers must be able to afford and compensate for an initial increase in the risk of an energetic shortfall associated with choosing the option when it is bad. Consequently, expected exploitation of the varying option increases as it becomes less variable, and when the overall risk of energetic shortfall is reduced. In addition, little activity on the variable alternative is expected until reserves are built up early in a foraging bout. This indicates that gathering information is a luxury while insurance is a necessity, at least when foraging on stochastic and variable food under the risk of starvation. PMID:12495509

Quantifying Variability of Avian Colours: Are Signalling Traits More Variable?

PubMed Central

Delhey, Kaspar; Peters, Anne

2008-01-01

Background Increased variability in sexually selected ornaments, a key assumption of evolutionary theory, is thought to be maintained through condition-dependence. Condition-dependent handicap models of sexual selection predict that (a) sexually selected traits show amplified variability compared to equivalent non-sexually selected traits, and since males are usually the sexually selected sex, that (b) males are more variable than females, and (c) sexually dimorphic traits more variable than monomorphic ones. So far these predictions have only been tested for metric traits. Surprisingly, they have not been examined for bright coloration, one of the most prominent sexual traits. This omission stems from computational difficulties: different types of colours are quantified on different scales precluding the use of coefficients of variation. Methodology/Principal Findings Based on physiological models of avian colour vision we develop an index to quantify the degree of discriminable colour variation as it can be perceived by conspecifics. A comparison of variability in ornamental and non-ornamental colours in six bird species confirmed (a) that those coloured patches that are sexually selected or act as indicators of quality show increased chromatic variability. However, we found no support for (b) that males generally show higher levels of variability than females, or (c) that sexual dichromatism per se is associated with increased variability. Conclusions/Significance We show that it is currently possible to realistically estimate variability of animal colours as perceived by them, something difficult to achieve with other traits. Increased variability of known sexually-selected/quality-indicating colours in the studied species, provides support to the predictions borne from sexual selection theory but the lack of increased overall variability in males or dimorphic colours in general indicates that sexual differences might not always be shaped by similar selective forces. PMID:18301766

Comparison of machine-learning algorithms to build a predictive model for detecting undiagnosed diabetes - ELSA-Brasil: accuracy study.

PubMed

Olivera, André Rodrigues; Roesler, Valter; Iochpe, Cirano; Schmidt, Maria Inês; Vigo, Álvaro; Barreto, Sandhi Maria; Duncan, Bruce Bartholow

2017-01-01

Type 2 diabetes is a chronic disease associated with a wide range of serious health complications that have a major impact on overall health. The aims here were to develop and validate predictive models for detecting undiagnosed diabetes using data from the Longitudinal Study of Adult Health (ELSA-Brasil) and to compare the performance of different machine-learning algorithms in this task. Comparison of machine-learning algorithms to develop predictive models using data from ELSA-Brasil. After selecting a subset of 27 candidate variables from the literature, models were built and validated in four sequential steps: (i) parameter tuning with tenfold cross-validation, repeated three times; (ii) automatic variable selection using forward selection, a wrapper strategy with four different machine-learning algorithms and tenfold cross-validation (repeated three times), to evaluate each subset of variables; (iii) error estimation of model parameters with tenfold cross-validation, repeated ten times; and (iv) generalization testing on an independent dataset. The models were created with the following machine-learning algorithms: logistic regression, artificial neural network, naïve Bayes, K-nearest neighbor and random forest. The best models were created using artificial neural networks and logistic regression. -These achieved mean areas under the curve of, respectively, 75.24% and 74.98% in the error estimation step and 74.17% and 74.41% in the generalization testing step. Most of the predictive models produced similar results, and demonstrated the feasibility of identifying individuals with highest probability of having undiagnosed diabetes, through easily-obtained clinical data.

Dynamic Contrast-Enhanced MRI in Head-and-Neck Cancer: The Impact of Region of Interest Selection on the Intra- and Interpatient Variability of Pharmacokinetic Parameters

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

Craciunescu, Oana I., E-mail: oana.craciunescu@duke.edu; Yoo, David S.; Cleland, Esi

2012-03-01

Purpose: Dynamic contrast-enhanced (DCE) MRI-extracted parameters measure tumor microvascular physiology and are usually calculated from an intratumor region of interest (ROI). Optimal ROI delineation is not established. The valid clinical use of DCE-MRI requires that the variation for any given parameter measured within a tumor be less than that observed between tumors in different patients. This work evaluates the impact of tumor ROI selection on the assessment of intra- and interpatient variability. Method and Materials: Head and neck cancer patients received initial targeted therapy (TT) treatment with erlotinib and/or bevacizumab, followed by radiotherapy and concurrent cisplatin with synchronous TT. DCE-MRImore » data from Baseline and the end of the TT regimen (Lead-In) were analyzed to generate the vascular transfer function (K{sup trans}), the extracellular volume fraction (v{sub e}), and the initial area under the concentration time curve (iAUC{sub 1min}). Four ROI sampling strategies were used: whole tumor or lymph node (Whole), the slice containing the most enhancing voxels (SliceMax), three slices centered in SliceMax (Partial), and the 5% most enhancing contiguous voxels within SliceMax (95Max). The average coefficient of variation (aCV) was calculated to establish intrapatient variability among ROI sets and interpatient variability for each ROI type. The average ratio between each intrapatient CV and the interpatient CV was calculated (aRCV). Results: Baseline primary/nodes aRCVs for different ROIs not including 95Max were, for all three MR parameters, in the range of 0.14-0.24, with Lead-In values between 0.09 and 0.2, meaning a low intrapatient vs. interpatient variation. For 95Max, intrapatient CVs approximated interpatient CVs, meaning similar data dispersion and higher aRCVs (0.6-1.27 for baseline) and 0.54-0.95 for Lead-In. Conclusion: Distinction between different patient's primary tumors and/or nodes cannot be made using 95Max ROIs. The other three strategies are viable and equivalent for using DCE-MRI to measure head and neck cancer physiology.« less

Support for Food and Beverage Worksite Wellness Strategies and Sugar-Sweetened Beverage Intake Among Employed U.S. Adults.

PubMed

Lee-Kwan, Seung Hee; Pan, Liping; Kimmons, Joel; Foltz, Jennifer; Park, Sohyun

2017-03-01

Sugar-sweetened beverage (SSB) consumption is high among U.S. adults and is associated with obesity. Given that more than 100 million Americans consume food or beverages at work daily, the worksite may be a venue for interventions to reduce SSB consumption. However, the level of support for these interventions is unknown. We examined associations between workday SSB intake and employees' support for worksite wellness strategies (WWSs). We conducted a cross-sectional study using data from Web-based annual surveys that gather information on health-related attitudes and behaviors. Study setting was the United States. A total of 1924 employed adults (≥18 years) selected using probability-based sampling. The self-reported independent variable was workday SSB intake (0, <1 or ≥1 times per day), and dependent variables were employees' support (yes/no) for the following WWSs: (1) accessible free water, (2) affordable healthy food/drink, (3) available healthy options, and (4) less available SSB. Multivariable logistic regression was used to control for sociodemographic variables, employee size, and availability of cafeteria/vending machine. About half of employees supported accessible free water (54%), affordable healthy food/drink (49%), and available healthy options (46%), but only 28% supported less available SSB. Compared with non-SSB consumers, daily SSB consumers were significantly less supportive of accessible free water (adjusted odds ratio, .67; p < .05) or less available SSB (odds ratio, .49; p < .05). Almost half of employees supported increasing healthy options within worksites, although daily workday SSB consumers were less supportive of certain strategies. Lack of support could be a potential barrier to the successful implementation of certain worksite interventions.

HMO marketing and selection bias: are TEFRA HMOs skimming?

PubMed

Lichtenstein, R; Thomas, J W; Watkins, B; Puto, C; Lepkowski, J; Adams-Watson, J; Simone, B; Vest, D

1992-04-01

The research evidence indicates that health maintenance organizations (HMOs) participating in the Tax Equity and Fiscal Responsibility Act of 1982 (TEFRA) At-Risk Program tend to experience favorable selection. Although favorable selection might result from patient decisions, a common conjecture is that it can be induced by HMOs through their marketing activities. The purpose of this study is to examine the relationship between HMO marketing strategies and selection bias in TEFRA At-Risk HMOs. A purposive sample of 22 HMOs that were actively marketing their TEFRA programs was selected and data on organizational characteristics, market area characteristics, and HMO marketing decisions were collected. To measure selection bias in these HMOs, the functional health status of approximately 300 enrollees in each HMO was compared to that of 300 non-enrolling beneficiaries in the same area. Three dependent variables, reflecting selection bias at the mean, the low health tail, and the high health tail of the health status distribution were created. Weighted least squares regressions were then used to identify relationships between marketing elements and selection bias. Subject to the statistical limitations of the study, our conclusion is that it is doubtful that HMO marketing decisions are responsible for the prevalence of favorable selection in HMO enrollment. It also appears unlikely that HMOs were differentially targeting healthy and unhealthy segments of the Medicare market.

The Variables of Composition: Process and Product in a Business Setting. Studies in Writing & Rhetoric Series.

ERIC Educational Resources Information Center

Broadhead, Glenn J.; Freed, Richard C.

Describing the variables of composition, offering researchers a methodology with which to investigate how the variables interact in specific writing strategies, and suggesting how teachers might make use of the variables of revision to help students learn successful writing strategies appropriate to a business setting, this book reports a research…

Advances, challenges, and directions in shrimp disease control: the guidelines from an ecological perspective.

PubMed

Xiong, Jinbo; Dai, Wenfang; Li, Chenghua

2016-08-01

High-density aquaculture has led to increasing occurrences of diseases in shrimp. Thus, it is imperative to establish effective and quantitative strategies for preventing and predicting these diseases. Water quality indices and investigations of specific pathogen abundance provide only a qualitative evaluation of the risk of shrimp disease and can be inaccurate. To address these shortcomings, we introduced intestinal indicative assemblages as independent variables with which to quantitatively predict incidences of shrimp disease. Given the ignorance regarding the niches differences in the shrimp intestine throughout its developmental stages, the use of probiotics in aquaculture has had limited success. Therefore, we propose the exploration of effective probiotic bacteria from shrimp intestinal flora and the establishment of therapeutic strategies dependent on shrimp age. Following ecological selection principles, we hypothesize that the larval stage provides the best opportunity to establish a desired gut microbiota through preemptive colonization of the treated rearing water with known probiotics. To employ this strategy, however, substantial barriers must be overcome.

Motion makes sense: an adaptive motor-sensory strategy underlies the perception of object location in rats.

PubMed

Saraf-Sinik, Inbar; Assa, Eldad; Ahissar, Ehud

2015-06-10

Tactile perception is obtained by coordinated motor-sensory processes. We studied the processes underlying the perception of object location in freely moving rats. We trained rats to identify the relative location of two vertical poles placed in front of them and measured at high resolution the motor and sensory variables (19 and 2 variables, respectively) associated with this whiskers-based perceptual process. We found that the rats developed stereotypic head and whisker movements to solve this task, in a manner that can be described by several distinct behavioral phases. During two of these phases, the rats' whiskers coded object position by first temporal and then angular coding schemes. We then introduced wind (in two opposite directions) and remeasured their perceptual performance and motor-sensory variables. Our rats continued to perceive object location in a consistent manner under wind perturbations while maintaining all behavioral phases and relatively constant sensory coding. Constant sensory coding was achieved by keeping one group of motor variables (the "controlled variables") constant, despite the perturbing wind, at the cost of strongly modulating another group of motor variables (the "modulated variables"). The controlled variables included coding-relevant variables, such as head azimuth and whisker velocity. These results indicate that consistent perception of location in the rat is obtained actively, via a selective control of perception-relevant motor variables. Copyright © 2015 the authors 0270-6474/15/358777-13$15.00/0.

The nature of instructional effects in color constancy.

PubMed

Radonjić, Ana; Brainard, David H

2016-06-01

The instructions subjects receive can have a large effect on experimentally measured color constancy, but the nature of these effects and how their existence should inform our understanding of color perception remains unclear. We used a factorial design to measure how instructional effects on constancy vary with experimental task and stimulus set. In each of 2 experiments, we employed both a classic adjustment-based asymmetric matching task and a novel color selection task. Four groups of naive subjects were instructed to make adjustments/selections based on (a) color (neutral instructions); (b) the light reaching the eye (physical spectrum instructions); (c) the actual surface reflectance of an object (objective reflectance instructions); or (d) the apparent surface reflectance of an object (apparent reflectance instructions). Across the 2 experiments we varied the naturalness of the stimuli. We find clear interactions between instructions, task, and stimuli. With simplified stimuli (Experiment 1), instructional effects were large and the data revealed 2 instruction-dependent patterns. In 1 (neutral and physical spectrum instructions) constancy was low, intersubject variability was also low, and adjustment-based and selection-based constancy were in agreement. In the other (reflectance instructions) constancy was high, intersubject variability was large, adjustment-based constancy deviated from selection-based constancy and for some subjects selection-based constancy increased across sessions. Similar patterns held for naturalistic stimuli (Experiment 2), although instructional effects were smaller. We interpret these 2 patterns as signatures of distinct task strategies-1 is perceptual, with judgments based primarily on the perceptual representation of color; the other involves explicit instruction-driven reasoning. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Female reproductive strategies, paternity and community structure in wild West African chimpanzees.

PubMed

Gagneux; Boesch; Woodruff

1999-01-01

Although the variability and complexity of chimpanzee behaviour frustrates generalization, it is widely believed that social evolution in this species occurs in the context of the recognizable social group or community. We used a combination of field observations and noninvasive genotyping to study the genetic structure of a habituated community of 55 wild chimpanzees, Pan troglodytes verus, in the Taï Forest, Côte d'Ivoire. Pedigree relationships in that community show that female mate choice strategies are more variable than previously supposed and that the observed social groups are not the exclusive reproductive units. Genetic evidence based on nuclear microsatellite markers and behavioural obser-vations reveal that females in the Taï forest actively seek mating partners outside their social unit; noncommunity males accounted for half the paternities over 5 years. This female mating strategy increases male gene flow between communities despite male philopatry, and negates the predicted higher relatedness among community males. Kin selection seems unlikely to explain the frequent cooperation and sharing observed among group males in this population. Similarly, inbreeding avoidance is probably not the sole cause of permanent adolescent female dispersal as a combination of extragroup mating and avoidance of incest with home group males would allow females to avoid inbreeding without the hazards associated with immigration into a new community. Extragroup mating as part of chimpanzee females' reproductive strategy may allow them to choose from a wider variety and number of males, without losing the resources and support provided by their male social group partners. Copyright 1999 The Association for the Study of Animal Behaviour.

Corticosteroids and Other Anti-Inflammatory Strategies in Pediatric Heart Surgery: A National Survey of Practice.

PubMed

Fudulu, Daniel P; Schadenberg, Alvin; Gibbison, Ben; Jenkins, Ian; Lightman, Stafford; Angelini, Gianni D; Stoica, Serban

2018-05-01

The role of steroids to mitigate the deleterious effects of pediatric cardiopulmonary bypass (CPB) remains a matter of debate; therefore, we aimed to assess preferences in administering corticosteroids (CSs) and the use of other anti-inflammatory strategies in pediatric cardiac surgery. A 19-question survey was distributed to consultants in pediatric cardiac anesthesia from 12 centers across the United Kingdom and Ireland. Of the 37 respondents (37/60, 62%), 24 (65%) use CSs, while 13 (35%) do not use steroids at all. We found variability within 5 (41%) of the 12 centers. Seven consultants (7/24, 29%) administer CSs in every case, while 17 administer CSs in selected cases only (17/24, 71%). There was variability in the dose of steroid administration. Almost all consultants (23/24, 96%) administer a single dose at induction, and one administers a two-dose regimen (1/24, 4%). There was variability in CS indications. Most consultants (24/37, 66%) use modified ultrafiltration at the conclusion of CPB. Fifteen consultants (15/32, 47%) report the use of aprotinin, while only 3 use heparin-coated circuits (3/24, 9%). We found wide variability in practice in the administration of CSs for pediatric cardiac surgery, both within and between units. While most anesthetists administer CSs in at least some cases, there is no consensus on the type of steroid, the dose, and at which patient groups this should be directed. Modified ultrafiltration is still used by most of the centers. Almost half of consultants use aprotinin, while heparin-coated circuits are infrequently used.

Optimization of formulation variables of benzocaine liposomes using experimental design.

PubMed

Mura, Paola; Capasso, Gaetano; Maestrelli, Francesca; Furlanetto, Sandra

2008-01-01

This study aimed to optimize, by means of an experimental design multivariate strategy, a liposomal formulation for topical delivery of the local anaesthetic agent benzocaine. The formulation variables for the vesicle lipid phase uses potassium glycyrrhizinate (KG) as an alternative to cholesterol and the addition of a cationic (stearylamine) or anionic (dicethylphosphate) surfactant (qualitative factors); the percents of ethanol and the total volume of the hydration phase (quantitative factors) were the variables for the hydrophilic phase. The combined influence of these factors on the considered responses (encapsulation efficiency (EE%) and percent drug permeated at 180 min (P%)) was evaluated by means of a D-optimal design strategy. Graphic analysis of the effects indicated that maximization of the selected responses requested opposite levels of the considered factors: For example, KG and stearylamine were better for increasing EE%, and cholesterol and dicethylphosphate for increasing P%. In the second step, the Doehlert design, applied for the response-surface study of the quantitative factors, pointed out a negative interaction between percent ethanol and volume of the hydration phase and allowed prediction of the best formulation for maximizing drug permeation rate. Experimental P% data of the optimized formulation were inside the confidence interval (P < 0.05) calculated around the predicted value of the response. This proved the suitability of the proposed approach for optimizing the composition of liposomal formulations and predicting the effects of formulation variables on the considered experimental response. Moreover, the optimized formulation enabled a significant improvement (P < 0.05) of the drug anaesthetic effect with respect to the starting reference liposomal formulation, thus demonstrating its actually better therapeutic effectiveness.

Sampling Strategies for Evaluating the Rate of Adventitious Transgene Presence in Non-Genetically Modified Crop Fields.

PubMed

Makowski, David; Bancal, Rémi; Bensadoun, Arnaud; Monod, Hervé; Messéan, Antoine

2017-09-01

According to E.U. regulations, the maximum allowable rate of adventitious transgene presence in non-genetically modified (GM) crops is 0.9%. We compared four sampling methods for the detection of transgenic material in agricultural non-GM maize fields: random sampling, stratified sampling, random sampling + ratio reweighting, random sampling + regression reweighting. Random sampling involves simply sampling maize grains from different locations selected at random from the field concerned. The stratified and reweighting sampling methods make use of an auxiliary variable corresponding to the output of a gene-flow model (a zero-inflated Poisson model) simulating cross-pollination as a function of wind speed, wind direction, and distance to the closest GM maize field. With the stratified sampling method, an auxiliary variable is used to define several strata with contrasting transgene presence rates, and grains are then sampled at random from each stratum. With the two methods involving reweighting, grains are first sampled at random from various locations within the field, and the observations are then reweighted according to the auxiliary variable. Data collected from three maize fields were used to compare the four sampling methods, and the results were used to determine the extent to which transgene presence rate estimation was improved by the use of stratified and reweighting sampling methods. We found that transgene rate estimates were more accurate and that substantially smaller samples could be used with sampling strategies based on an auxiliary variable derived from a gene-flow model. © 2017 Society for Risk Analysis.

Diversity in livestock resources in pastoral systems in Africa.

PubMed

Kaufmann, B A; Lelea, M A; Hulsebusch, C G

2016-11-01

Pastoral systems are important producers and repositories of livestock diversity. Pastoralists use variability in their livestock resources to manage high levels of environmental variability in economically advantageous ways. In pastoral systems, human-animal-environment interactions are the basis of production and the key to higher productivity and efficiency. In other words, pastoralists manage a production system that exploits variability and keeps production costs low. When differentiating, characterising and evaluating pastoral breeds, this context-specific, functional dimension of diversity in livestock resources needs to be considered. The interaction of animals with their environment is determined not only by morphological and physiological traits but also by experience and socially learned behaviour. This high proportion of non-genetic components determining the performance of livestock means that current models for analysing livestock diversity and performance, which are based on genetic inheritance, have limited ability to describe pastoral performance. There is a need for methodological innovations to evaluate pastoral breeds and animals, since comparisons based on performance 'under optimal conditions' are irrelevant within this production system. Such innovations must acknowledge that livestock or breed performance is governed by complex human-animal-environment interactions, and varies through time and space due to the mobile and seasonal nature of the pastoral system. Pastoralists' breeding concepts and selection strategies seem to be geared towards improving their animals' capability to exploit variability, by - among other things - enhancing within-breed diversity. In-depth studies of these concepts and strategies could contribute considerably towards developing methodological innovations for the characterisation and evaluation of pastoral livestock resources.

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.

Resolving the Conflict Between Associative Overdominance and Background Selection

PubMed Central

Zhao, Lei; Charlesworth, Brian

2016-01-01

In small populations, genetic linkage between a polymorphic neutral locus and loci subject to selection, either against partially recessive mutations or in favor of heterozygotes, may result in an apparent selective advantage to heterozygotes at the neutral locus (associative overdominance) and a retardation of the rate of loss of variability by genetic drift at this locus. In large populations, selection against deleterious mutations has previously been shown to reduce variability at linked neutral loci (background selection). We describe analytical, numerical, and simulation studies that shed light on the conditions under which retardation vs. acceleration of loss of variability occurs at a neutral locus linked to a locus under selection. We consider a finite, randomly mating population initiated from an infinite population in equilibrium at a locus under selection. With mutation and selection, retardation occurs only when S, the product of twice the effective population size and the selection coefficient, is of order 1. With S >> 1, background selection always causes an acceleration of loss of variability. Apparent heterozygote advantage at the neutral locus is, however, always observed when mutations are partially recessive, even if there is an accelerated rate of loss of variability. With heterozygote advantage at the selected locus, loss of variability is nearly always retarded. The results shed light on experiments on the loss of variability at marker loci in laboratory populations and on the results of computer simulations of the effects of multiple selected loci on neutral variability. PMID:27182952

Functional molecular markers (EST-SSR) in the full-sib reciprocal recurrent selection program of maize (Zea mays L.).

PubMed

Galvão, K S C; Ramos, H C C; Santos, P H A D; Entringer, G C; Vettorazzi, J C F; Pereira, M G

2015-07-03

This study aimed to improve grain yield in the full-sib reciprocal recurrent selection program of maize from the North Fluminense State University. In the current phase of the program, the goal is to maintain, or even increase, the genetic variability within and among populations, in order to increase heterosis of the 13th cycle of reciprocal recurrent selection. Microsatellite expressed sequence tags (EST-SSRs) were used as a tool to assist the maximization step of genetic variability, targeting the functional genome. Eighty S1 progenies of the 13th recur-rent selection cycle, 40 from each population (CIMMYT and Piranão), were analyzed using 20 EST-SSR loci. Genetic diversity, observed heterozygosity, information content of polymorphism, and inbreeding co-efficient were estimated. Subsequently, analysis of genetic dissimilarity, molecular variance, and a graphical dispersion of genotypes were conducted. The number of alleles in the CIMMYT population ranged from 1 to 6, while in the Piranão population the range was from 2 to 8, with a mean of 3.65 and 4.35, respectively. As evidenced by the number of alleles, the Shannon index showed greater diversity for the Piranão population (1.04) in relation to the CIMMYT population (0.89). The genic SSR markers were effective in clustering genotypes into their respective populations before selection and an increase in the variation between populations after selection was observed. The results indicate that the study populations have expressive genetic diversity, which cor-responds to the functional genome, indicating that this strategy may contribute to genetic gain, especially in association with the grain yield of future hybrids.

Streamlined method for parallel identification of single domain antibodies to membrane receptors on whole cells

PubMed Central

Rossotti, Martín; Tabares, Sofía; Alfaya, Lucía; Leizagoyen, Carmen; Moron, Gabriel; González-Sapienza, Gualberto

2015-01-01

BACKGROUND Owing to their minimal size, high production yield, versatility and robustness, the recombinant variable domain (nanobody) of camelid single chain antibodies are valued affinity reagents for research, diagnostic, and therapeutic applications. While their preparation against purified antigens is straightforward, the generation of nanobodies to difficult targets such as multi-pass or complex membrane cell receptors remains challenging. Here we devised a platform for high throughput identification of nanobodies to cell receptor based on the use of a biotin handle. METHODS Using a biotin-acceptor peptide tag, the in vivo biotinylation of nanobodies in 96 well culture blocks was optimized allowing their parallel analysis by flow cytometry and ELISA, and their direct used for pull-down/MS target identification. RESULTS The potential of this strategy was demonstrated by the selection and characterization of panels of nanobodies to Mac-1 (CD11b/CD18), MHC II and the mouse Ly-5 leukocyte common antigen (CD45) receptors, from a VHH library obtained from a llama immunized with mouse bone marrow derived dendritic cells. By on and off switching of the addition of biotin, the method also allowed the epitope binning of the selected Nbs directly on cells. CONCLUSIONS This strategy streamline the selection of potent nanobodies to complex antigens, and the selected nanobodies constitute ready-to-use biotinylated reagents. GENERAL SIGNIFICANCE This method will accelerate the discovery of nanobodies to cell membrane receptors which comprise the largest group of drug and analytical targets. PMID:25819371

Patient selection, echocardiographic screening and treatment strategies for interventional tricuspid repair using the edge-to-edge repair technique.

PubMed

Hausleiter, Jörg; Braun, Daniel; Orban, Mathias; Latib, Azeem; Lurz, Philipp; Boekstegers, Peter; von Bardeleben, Ralph Stephan; Kowalski, Marek; Hahn, Rebecca T; Maisano, Francesco; Hagl, Christian; Massberg, Steffen; Nabauer, Michael

2018-04-24

Severe tricuspid regurgitation (TR) has long been neglected despite its well known association with mortality. While surgical mortality rates remain high in isolated tricuspid valve surgery, interventional TR repair is rapidly evolving as an alternative to cardiac surgery in selected patients at high surgical risk. Currently, interventional edge-to-edge repair is the most frequently applied technique for TR repair even though the device has not been developed for this particular indication. Due to the inherent differences in tricuspid and mitral valve anatomy and pathology, percutaneous repair of the tricuspid valve is challenging due to a variety of factors including the complexity and variability of tricuspid valve anatomy, echocardiographic visibility of the valve leaflets, and device steering to the tricuspid valve. Furthermore, it remains to be clarified which patients are suitable for a percutaneous tricuspid repair and which features predict a successful procedure. On the basis of the available experience, we describe criteria for patient selection including morphological valve features, a standardized process for echocardiographic screening, and a strategy for clip placement. These criteria will help to achieve standardization of valve assessment and the procedural approach, and to further develop interventional tricuspid valve repair using either currently available devices or dedicated tricuspid edge-to-edge repair devices in the future. In summary, this manuscript will provide guidance for patient selection and echocardiographic screening when considering edge-to-edge repair for severe TR.

Critical evaluation of monitoring strategy for the multi-residue determination of 90 chiral and achiral micropollutants in effluent wastewater.

PubMed

Petrie, Bruce; Proctor, Kathryn; Youdan, Jane; Barden, Ruth; Kasprzyk-Hordern, Barbara

2017-02-01

It is essential to monitor the release of organic micropollutants from wastewater treatment plants (WWTPs) for developing environmental risk assessment and assessing compliance with legislative regulation. In this study the impact of sampling strategy on the quantitative determination of micropollutants in effluent wastewater was investigated. An extended list of 90 chiral and achiral micropollutants representing a broad range of biological and physico-chemical properties were studied simultaneously for the first time. During composite sample collection micropollutants can degrade resulting in the under-estimation of concentration. Cooling collected sub-samples to 4°C stabilised ≥81 of 90 micropollutants to acceptable levels (±20% of the initial concentration) in the studied effluents. However, achieving stability for all micropollutants will require an integrated approach to sample collection (i.e., multi-bottle sampling with more than one stabilisation method applied). Full-scale monitoring of effluent revealed time-paced composites attained similar information to volume-paced composites (influent wastewater requires a sampling mode responsive to flow variation). The option of monitoring effluent using time-paced composite samplers is advantageous as not all WWTPs have flow controlled samplers or suitable sites for deploying portable flow meters. There has been little research to date on the impact of monitoring strategy on the determination of chiral micropollutants at the enantiomeric level. Variability in wastewater flow results in a dynamic hydraulic retention time within the WWTP (and upstream sewerage system). Despite chiral micropollutants being susceptible to stereo-selective degradation, no diurnal variability in their enantiomeric distribution was observed. However, unused medication can be directly disposed into the sewer network creating short-term (e.g., daily) changes to their enantiomeric distribution. As enantio-specific toxicity is observed in the environment, similar resolution of enantio-selective analysis to more routinely applied achiral methods is needed throughout the monitoring period for accurate risk assessment. Copyright © 2016 British Geological Survey, NERC. Published by Elsevier B.V. All rights reserved.

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.

[Dating violence and associations with depression and risk behaviors: female students in Morelos, Mexico].

PubMed

Rivera-Rivera, Leonor; Allen, Betania; Rodríguez-Ortega, Graciela; Chávez-Ayala, Rubén; Lazcano-Ponce, Eduardo

2006-01-01

Determine the prevalence of dating violence and its association with depression and various risk behaviors in a sample of female students from the state of Morelos. This is a baseline cohort study of a sample of 13 293 students from 12 to 24 years of age who attended public schools in the state of Morelos during the 1998-1999 school year. The participants were selected from a random sample of 260 junior high schools, 92 high schools and one university. For the purpose of this analysis, a total of 4 587 female students who had a previous dating relationship were selected. To control for possible confounding variables, multiple logistic regression analysis was used. The total prevalence of dating violence in females who attended public schools in Morelos was 28%. The following variables were associated with dating violence: depression (OR = 1.92; 95% CI 1.61-2.28); tobacco smoking (OR = 1.31; 95% CI 1.06-1.60); alcohol abuse (OR = 1.30, 95% CI 1.12-1.51); poor academic performance (low grades) (OR = 1.25; 95% CI 1.03-1.52); a history of sexual relations (OR = 1.52; 95% CI 1.26-1.82). The results of this study clearly indicate that women experience partner violence beginning with dating during adolescence. Health and education professionals need to establish intervention strategies to prevent or treat dating violence among female students. Such strategies should take into account the association between depression and violence, as well as other related risk behaviors.

Mathematics Boot Camps: A Strategy for Helping Students to Bypass Remedial Courses

NASA Astrophysics Data System (ADS)

Hamilton, Marilyn A. L.

Many community colleges struggle to find the best strategy to help incoming at-risk students prepare for the placement test. The purpose of this quantitative quasi-experimental study, was to answer the question as to which of 2 programs, a 2-week, face-to-face mathematics refresher program, Math Boost-Up, or an online-only program, might increase the ACCUPLACER posttest scores of incoming community college students. The study used archival data for 136 students who self-selected to either participate in the Math Boost-Up program (the experiment group), or in the online-only program (the comparison group). Knowles's theory of adult learning, andragogy, served as the theoretical framework. Spearman, Kruskal-Wallis, Mann-Whitney, and chi-square tests were used to measure the effect of 4 moderator variables (age, high school GPA, number of minutes spent in MyFoundationsLab, and number of days spent in face-to-face sessions) on the pre- and posttest scores of students in each group. The results indicated that students in the Math Boost-Up program experienced statistically significant gains in arithmetic and elementary algebra than did those students in the online-only program. The results also indicated that the 4 moderator variables affected gains in posttest scores. Additionally, the results disproved the andragogical premise that students would be self-directed and would self-select to participate in the intervention. A recommendation was that participation in the face-to-face refresher program should be mandatory. The study contributes to social change by providing evidence that short-term refresher programs could increase the scores of students on placement tests.

Influence of Passive Stiffness of Hamstrings on Postural Stability

PubMed Central

Kuszewski, Michał; Gnat, Rafał; Sobota, Grzegorz; Myśliwiec, Andrzej

2015-01-01

The aim of the study was to explore whether passive stiffness of the hamstrings influences the strategy of maintaining postural stability. A sample of 50 subjects was selected; the final analyses were based on data of 41 individuals (33 men, 8 women) aged 21 to 29 (mean = 23.3, SD = 1.1) years. A quasi- experimental ex post facto design with repeated measures was used. Categories of independent variables were obtained directly prior to the measurement of the dependent variables. In stage one of the study, passive knee extension was measured in the supine position to assess hamstring stiffness. In stage two, the magnitude of postural sway in antero-posterior direction was measured, while varying the body position on a stabilometric platform, both with and without visual control. The margin of safety was used as a measure of postural control. The magnitude of the margin of safety increased significantly between the open-eye and closed-eye trials. However, although we registered a visible tendency for a larger increase of the margin of safety associated with lower levels of passive hamstrings stiffness, no significant differences were found. Therefore, this study demonstrated that hamstring stiffness did not influence the strategy used to maintain postural stability. PMID:25964809

Influence of passive stiffness of hamstrings on postural stability.

PubMed

Kuszewski, Michał; Gnat, Rafał; Sobota, Grzegorz; Myśliwiec, Andrzej

2015-03-29

The aim of the study was to explore whether passive stiffness of the hamstrings influences the strategy of maintaining postural stability. A sample of 50 subjects was selected; the final analyses were based on data of 41 individuals (33 men, 8 women) aged 21 to 29 (mean = 23.3, SD = 1.1) years. A quasi- experimental ex post facto design with repeated measures was used. Categories of independent variables were obtained directly prior to the measurement of the dependent variables. In stage one of the study, passive knee extension was measured in the supine position to assess hamstring stiffness. In stage two, the magnitude of postural sway in antero-posterior direction was measured, while varying the body position on a stabilometric platform, both with and without visual control. The margin of safety was used as a measure of postural control. The magnitude of the margin of safety increased significantly between the open-eye and closed-eye trials. However, although we registered a visible tendency for a larger increase of the margin of safety associated with lower levels of passive hamstrings stiffness, no significant differences were found. Therefore, this study demonstrated that hamstring stiffness did not influence the strategy used to maintain postural stability.

The relationship among young adult college students' depression, anxiety, stress, demographics, life satisfaction, and coping styles.

PubMed

Mahmoud, Jihan Saber Raja; Staten, Ruth; Hall, Lynne A; Lennie, Terry A

2012-03-01

Recent research indicates that young adult college students experience increased levels of depression, anxiety, and stress. It is less clear what strategies college health care providers might use to assist students in decreasing these mental health concerns. In this paper, we examine the relative importance of coping style, life satisfaction, and selected demographics in predicting undergraduates' depression, anxiety, and stress. A total of 508 full-time undergraduate students aged 18-24 years completed the study measures and a short demographics information questionnaire. Coping strategies and life satisfaction were assessed using the Brief COPE Inventory and an adapted version of the Brief Students' Multidimensional Life Satisfaction Scale. Depression, anxiety, and stress were measured using the Depression Anxiety and Stress Scale-21 (DASS-21). Multiple regression analyses were used to examine the relative influence of each of the independent variables on depression, anxiety, and stress. Maladaptive coping was the main predictor of depression, anxiety, and stress. Adaptive coping was not a significant predictor of any of the three outcome variables. Reducing maladaptive coping behaviors may have the most positive impact on reducing depression, anxiety, and stress in this population.

What Effects Do Didactic Interventions Have on Students' Attitudes Towards Science? A Meta-Analysis

NASA Astrophysics Data System (ADS)

Aguilera, David; Perales-Palacios, F. Javier

2018-03-01

Improving the attitudes of students towards science is one of the main challenges facing the teaching of the subject. The main objective of this study is to analyze the effect of students' attitudes towards science through different didactic interventions. The bibliographic search was carried out via the Web of Science database, specifically in the Education and Educational Research category, obtaining a population of 374 articles published between 2006 and 2016. We included studies with pre-experimental or quasi-experimental design that used pretest and posttest phases. Following the application of the inclusion criteria, 24 articles were selected with which a random effects meta-analysis was adopted, obtaining an average effect size of 0.54. Three moderating variables were analyzed, with a significant correlation between the type of teaching strategy and the effect of the attitude towards Science (Q = 23.17; df = 8; p < .01; R 2 = 0.05). The educational implications are mainly due to the importance of the teaching/learning strategy used in science education in the development of positive attitudes towards the subject, and the need to increase the number of Didactic Interventions that contemplate students' attitudes towards science as a study variable is also advocated.

Mammalian cell culture monitoring using in situ spectroscopy: Is your method really optimised?

PubMed

André, Silvère; Lagresle, Sylvain; Hannas, Zahia; Calvosa, Éric; Duponchel, Ludovic

2017-03-01

In recent years, as a result of the process analytical technology initiative of the US Food and Drug Administration, many different works have been carried out on direct and in situ monitoring of critical parameters for mammalian cell cultures by Raman spectroscopy and multivariate regression techniques. However, despite interesting results, it cannot be said that the proposed monitoring strategies, which will reduce errors of the regression models and thus confidence limits of the predictions, are really optimized. Hence, the aim of this article is to optimize some critical steps of spectroscopic acquisition and data treatment in order to reach a higher level of accuracy and robustness of bioprocess monitoring. In this way, we propose first an original strategy to assess the most suited Raman acquisition time for the processes involved. In a second part, we demonstrate the importance of the interbatch variability on the accuracy of the predictive models with a particular focus on the optical probes adjustment. Finally, we propose a methodology for the optimization of the spectral variables selection in order to decrease prediction errors of multivariate regressions. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 33:308-316, 2017. © 2017 American Institute of Chemical Engineers.

Neural Underpinnings of Decision Strategy Selection: A Review and a Theoretical Model.

PubMed

Wichary, Szymon; Smolen, Tomasz

2016-01-01

In multi-attribute choice, decision makers use decision strategies to arrive at the final choice. What are the neural mechanisms underlying decision strategy selection? The first goal of this paper is to provide a literature review on the neural underpinnings and cognitive models of decision strategy selection and thus set the stage for a neurocognitive model of this process. The second goal is to outline such a unifying, mechanistic model that can explain the impact of noncognitive factors (e.g., affect, stress) on strategy selection. To this end, we review the evidence for the factors influencing strategy selection, the neural basis of strategy use and the cognitive models of this process. We also present the Bottom-Up Model of Strategy Selection (BUMSS). The model assumes that the use of the rational Weighted Additive strategy and the boundedly rational heuristic Take The Best can be explained by one unifying, neurophysiologically plausible mechanism, based on the interaction of the frontoparietal network, orbitofrontal cortex, anterior cingulate cortex and the brainstem nucleus locus coeruleus. According to BUMSS, there are three processes that form the bottom-up mechanism of decision strategy selection and lead to the final choice: (1) cue weight computation, (2) gain modulation, and (3) weighted additive evaluation of alternatives. We discuss how these processes might be implemented in the brain, and how this knowledge allows us to formulate novel predictions linking strategy use and neural signals.

The Effects of Training, Modality, and Redundancy on the Development of a Historical Inquiry Strategy in a Multimedia Learning Environment

ERIC Educational Resources Information Center

McNeill, Andrea L.; Doolittle, Peter E.; Hicks, David

2009-01-01

The purpose of this study was to assess the effects of training, modality, and redundancy on the participants' ability to apply and recall a historical inquiry strategy. An experimental research design was utilized with presentation mode as the independent variable and strategy application and strategy recall as the dependent variables. The…

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

Linear Relationship between Resilience, Learning Approaches, and Coping Strategies to Predict Achievement in Undergraduate Students

PubMed Central

de la Fuente, Jesús; Fernández-Cabezas, María; Cambil, Matilde; Vera, Manuel M.; González-Torres, Maria Carmen; Artuch-Garde, Raquel

2017-01-01

The aim of the present research was to analyze the linear relationship between resilience (meta-motivational variable), learning approaches (meta-cognitive variables), strategies for coping with academic stress (meta-emotional variable) and academic achievement, necessary in the context of university academic stress. A total of 656 students from a southern university in Spain completed different questionnaires: a resiliency scale, a coping strategies scale, and a study process questionnaire. Correlations and structural modeling were used for data analyses. There was a positive and significant linear association showing a relationship of association and prediction of resilience to the deep learning approach, and problem-centered coping strategies. In a complementary way, these variables positively and significantly predicted the academic achievement of university students. These results enabled a linear relationship of association and consistent and differential prediction to be established among the variables studied. Implications for future research are set out. PMID:28713298

To pair or not to pair: Sources of social variability with white-faced saki monkeys (Pithecia pithecia) as a case study.

PubMed

Thompson, Cynthia L

2016-05-01

Intraspecific variability in social systems is gaining increased recognition in primatology. Many primate species display variability in pair-living social organizations through incorporating extra adults into the group. While numerous models exist to explain primate pair-living, our tools to assess how and why variation in this trait occurs are currently limited. Here I outline an approach which: (i) utilizes conceptual models to identify the selective forces driving pair-living; (ii) outlines novel possible causes for variability in social organization; and (iii) conducts a holistic species-level analysis of social behavior to determine the factors contributing to variation in pair-living. A case study on white-faced sakis (Pithecia pithecia) is used to exemplify this approach. This species lives in either male-female pairs or groups incorporating "extra" adult males and/or females. Various conceptual models of pair-living suggest that high same-sex aggression toward extra-group individuals is a key component of the white-faced saki social system. Variable pair-living in white-faced sakis likely represents alternative strategies to achieve competency in this competition, in which animals experience conflicting selection pressures between achieving successful group defense and maintaining sole reproductive access to mates. Additionally, independent decisions by individuals may generate social variation by preventing other animals from adopting a social organization that maximizes fitness. White-faced saki inter-individual relationships and demographic patterns also lend conciliatory support to this conclusion. By utilizing both model-level and species-level approaches, with a consideration for potential sources of variation, researchers can gain insight into the factors generating variation in pair-living social organizations. © 2014 The Authors. American Journal of Primatology published by Wiley Periodicals, Inc.

Local search to improve coordinate-based task mapping

DOE PAGES

Balzuweit, Evan; Bunde, David P.; Leung, Vitus J.; ...

2015-10-31

We present a local search strategy to improve the coordinate-based mapping of a parallel job’s tasks to the MPI ranks of its parallel allocation in order to reduce network congestion and the job’s communication time. The goal is to reduce the number of network hops between communicating pairs of ranks. Our target is applications with a nearest-neighbor stencil communication pattern running on mesh systems with non-contiguous processor allocation, such as Cray XE and XK Systems. Utilizing the miniGhost mini-app, which models the shock physics application CTH, we demonstrate that our strategy reduces application running time while also reducing the runtimemore » variability. Furthermore, we further show that mapping quality can vary based on the selected allocation algorithm, even between allocation algorithms of similar apparent quality.« less

On scheduling task systems with variable service times

NASA Astrophysics Data System (ADS)

Maset, Richard G.; Banawan, Sayed A.

1993-08-01

Several strategies have been proposed for developing optimal and near-optimal schedules for task systems (jobs consisting of multiple tasks that can be executed in parallel). Most such strategies, however, implicitly assume deterministic task service times. We show that these strategies are much less effective when service times are highly variable. We then evaluate two strategies—one adaptive, one static—that have been proposed for retaining high performance despite such variability. Both strategies are extensions of critical path scheduling, which has been found to be efficient at producing near-optimal schedules. We found the adaptive approach to be quite effective.

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

Does Sex Trade with Violence among Genotypes in Drosophila melanogaster?

PubMed Central

Cabral, Larry G.; Foley, Brad R.; Nuzhdin, Sergey V.

2008-01-01

The evolutionary forces shaping the ability to win competitive interactions, such as aggressive encounters, are still poorly understood. Given a fitness advantage for competitive success, variance in aggressive and sexual display traits should be depleted, but a great deal of variation in these traits is consistently found. While life history tradeoffs have been commonly cited as a mechanism for the maintenance of variation, the variability of competing strategies of conspecifics may mean there is no single optimum strategy. We measured the genetically determined outcomes of aggressive interactions, and the resulting effects on mating success, in a panel of diverse inbred lines representing both natural variation and artificially selected genotypes. Males of one genotype which consistently lost territorial encounters with other genotypes were nonetheless successful against males that were artificially selected for supernormal aggression and dominated all other lines. Intransitive patterns of territorial success could maintain variation in aggressive strategies if there is a preference for territorial males. Territorial success was not always associated with male mating success however and females preferred ‘winners’ among some male genotypes, and ‘losers’ among other male genotypes. This suggests that studying behaviour from the perspective of population means may provide limited evolutionary and genetic insight. Overall patterns of competitive success among males and mating transactions between the sexes are consistent with mechanisms proposed for the maintenance of genetic variation due to nonlinear outcomes of competitive interactions. PMID:18414669

Does sex trade with violence among genotypes in Drosophila melanogaster?

PubMed

Cabral, Larry G; Foley, Brad R; Nuzhdin, Sergey V

2008-04-16

The evolutionary forces shaping the ability to win competitive interactions, such as aggressive encounters, are still poorly understood. Given a fitness advantage for competitive success, variance in aggressive and sexual display traits should be depleted, but a great deal of variation in these traits is consistently found. While life history tradeoffs have been commonly cited as a mechanism for the maintenance of variation, the variability of competing strategies of conspecifics may mean there is no single optimum strategy. We measured the genetically determined outcomes of aggressive interactions, and the resulting effects on mating success, in a panel of diverse inbred lines representing both natural variation and artificially selected genotypes. Males of one genotype which consistently lost territorial encounters with other genotypes were nonetheless successful against males that were artificially selected for supernormal aggression and dominated all other lines. Intransitive patterns of territorial success could maintain variation in aggressive strategies if there is a preference for territorial males. Territorial success was not always associated with male mating success however and females preferred 'winners' among some male genotypes, and 'losers' among other male genotypes. This suggests that studying behaviour from the perspective of population means may provide limited evolutionary and genetic insight. Overall patterns of competitive success among males and mating transactions between the sexes are consistent with mechanisms proposed for the maintenance of genetic variation due to nonlinear outcomes of competitive interactions.

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

[Subjective memory complaints, perceived stress and coping strategies in young adults].

PubMed

Molina-Rodriguez, Sergio; Pellicer-Porcar, Olga; Mirete-Fructuoso, Marcos; Martinez-Amoros, Estefanía

2016-04-16

Subjective memory complaints are becoming more and more frequent among young adults. There are currently no studies in the literature that analyse the relation among memory complaints, perceived stress and coping strategies as a whole in young adults. To determine the contribution made by perceived stress and different coping strategies on subjective memory complaints in healthy young adults. The sample consisted of 299 university students, of whom 71.6% were women, with a mean age of 22.54 ± 4.73 years. The variable 'memory complaints' was measured with the memory failures questionnaire; the variable 'perceived stress' was measured with the perceived stress scale, and the variables referring to coping strategies were measured using the coping strategies inventory. The variables that made a higher contribution to the variance of the memory complaints are, first, perceived stress and positive problem-focused coping strategies, and, second, negative coping strategies focused on the emotion and on the problem. The positive emotion-focused coping strategies do not make any contribution. Again we find evidence of the influence of stress on memory processes. The use of positive problem-focused coping strategies, such as cognitive restructuring and problem-solving, can be beneficial to lessen the presence of memory complaints. Further research on this matter is warranted.

Development of a simple binary response questionnaire to identify airflow obstruction in a smoking population in Argentina.

PubMed

Bergna, Miguel A; García, Gabriel R; Alchapar, Ramon; Altieri, Hector; Casas, Juan C Figueroa; Larrateguy, Luis; Nannini, Luis J; Pascansky, Daniel; Grabre, Pedro; Zabert, Gustavo; Miravitlles, Marc

2015-06-01

The CODE questionnaire (COPD detection questionnaire), a simple, binary response scale (yes/no), screening questionnaire, was developed for the identification of patients with chronic obstructive pulmonary disease (COPD). We conducted a survey of 468 subjects with a smoking history in 10 public hospitals in Argentina. Patients with a previous diagnosis of COPD, asthma and other respiratory illness were excluded. Items that measured conceptual domains in terms of characteristics of symptoms, smoking history and demographics data were considered. 96 (20.5%) subjects had a diagnosis of COPD according to the 2010 Global Initiative for Chronic Obstructive Lung Disease strategy document. The variables selected for the final questionnaire were based on univariate and multivariate analyses and clinical criteria. Finally, we selected the presence or absence of six variables (age ≥50 years, smoking history ≥30 pack-years, male sex, chronic cough, chronic phlegm and dyspnoea). Of patients without any of these six variables (0 points), none had COPD. The ability of the CODE questionnaire to discriminate between subjects with and without COPD was good (the area under the receiver operating characteristic curve was 0.75). Higher scores were associated with a greater probability of COPD. The CODE questionnaire is a brief, accurate questionnaire that can identify smoking individuals likely to have COPD. Copyright ©ERS 2015.

Strategies for soil-based precision agriculture in cotton

NASA Astrophysics Data System (ADS)

Neely, Haly L.; Morgan, Cristine L. S.; Stanislav, Scott; Rouze, Gregory; Shi, Yeyin; Thomasson, J. Alex; Valasek, John; Olsenholler, Jeff

2016-05-01

The goal of precision agriculture is to increase crop yield while maximizing the use efficiency of farm resources. In this application, UAV-based systems are presenting agricultural researchers with an opportunity to study crop response to environmental and management factors in real-time without disturbing the crop. The spatial variability soil properties, which drive crop yield and quality, cannot be changed and thus keen agronomic choices with soil variability in mind have the potential to increase profits. Additionally, measuring crop stress over time and in response to management and environmental conditions may enable agronomists and plant breeders to make more informed decisions about variety selection than the traditional end-of-season yield and quality measurements. In a previous study, seed-cotton yield was measured over 4 years and compared with soil variability as mapped by a proximal soil sensor. It was found that soil properties had a significant effect on seed-cotton yield and the effect was not consistent across years due to different precipitation conditions. However, when seed-cotton yield was compared to the normalized difference vegetation index (NDVI), as measured using a multispectral camera from a UAV, predictions improved. Further improvement was seen when soil-only pixels were removed from the analysis. On-going studies are using UAV-based data to uncover the thresholds for stress and yield potential. Long-term goals of this research include detecting stress before yield is reduced and selecting better adapted varieties.

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

PubMed

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

2017-01-01

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

Lack of strategy holding: a new pattern of learning deficit in cortical dementias.

PubMed

Benedet, María J; Lauro-Grotto, Rosapia; Giotti, Chiara

2009-09-01

The aim of this study was to demonstrate, by means of systematic research and qualitative data analysis, the presence, among a group of patients with fronto-temporal lobar degeneration of a subgroup that, at variance with the standard pattern, is able to devise and implement learning strategies, but appear impaired at carrying them on from a trial to the next. In order to provide evidence of the existence of a group of patients showing this type of learning disability, that we refer to as lack of strategy holding, we performed a stepwise hierarchical cluster analysis of a set of variables whose scores were selected from the subject's performance at the Test de Aprendizaje Verbal España-Complutense. Results substantiate the segregation of three groups of subjects characterized by the following patterns of performance: normal elderly individuals, who show a quite preserved ability to discover a semantic strategy along the learning trials and to carry it from a trial to the next, patients presenting with a deficit in implementing semantic learning strategies and possibly use of serial and/or phonological strategies to perform the task, and to patients who, although able to generate and implement appropriate learning strategies, appear unable to carry them over the learning trials. The presence of this new pattern raises a few questions that seem worth trying to address.

How Students Circumvent Problem-Solving Strategies that Require Greater Cognitive Complexity.

ERIC Educational Resources Information Center

Niaz, Mansoor

1996-01-01

Analyzes the great diversity in problem-solving strategies used by students in solving a chemistry problem and discusses the relationship between these variables and different cognitive variables. Concludes that students try to circumvent certain problem-solving strategies by adapting flexible and stylistic innovations that render the cognitive…

Variable Selection through Correlation Sifting

NASA Astrophysics Data System (ADS)

Huang, Jim C.; Jojic, Nebojsa

Many applications of computational biology require a variable selection procedure to sift through a large number of input variables and select some smaller number that influence a target variable of interest. For example, in virology, only some small number of viral protein fragments influence the nature of the immune response during viral infection. Due to the large number of variables to be considered, a brute-force search for the subset of variables is in general intractable. To approximate this, methods based on ℓ1-regularized linear regression have been proposed and have been found to be particularly successful. It is well understood however that such methods fail to choose the correct subset of variables if these are highly correlated with other "decoy" variables. We present a method for sifting through sets of highly correlated variables which leads to higher accuracy in selecting the correct variables. The main innovation is a filtering step that reduces correlations among variables to be selected, making the ℓ1-regularization effective for datasets on which many methods for variable selection fail. The filtering step changes both the values of the predictor variables and output values by projections onto components obtained through a computationally-inexpensive principal components analysis. In this paper we demonstrate the usefulness of our method on synthetic datasets and on novel applications in virology. These include HIV viral load analysis based on patients' HIV sequences and immune types, as well as the analysis of seasonal variation in influenza death rates based on the regions of the influenza genome that undergo diversifying selection in the previous season.

Neural Underpinnings of Decision Strategy Selection: A Review and a Theoretical Model

PubMed Central

Wichary, Szymon; Smolen, Tomasz

2016-01-01

In multi-attribute choice, decision makers use decision strategies to arrive at the final choice. What are the neural mechanisms underlying decision strategy selection? The first goal of this paper is to provide a literature review on the neural underpinnings and cognitive models of decision strategy selection and thus set the stage for a neurocognitive model of this process. The second goal is to outline such a unifying, mechanistic model that can explain the impact of noncognitive factors (e.g., affect, stress) on strategy selection. To this end, we review the evidence for the factors influencing strategy selection, the neural basis of strategy use and the cognitive models of this process. We also present the Bottom-Up Model of Strategy Selection (BUMSS). The model assumes that the use of the rational Weighted Additive strategy and the boundedly rational heuristic Take The Best can be explained by one unifying, neurophysiologically plausible mechanism, based on the interaction of the frontoparietal network, orbitofrontal cortex, anterior cingulate cortex and the brainstem nucleus locus coeruleus. According to BUMSS, there are three processes that form the bottom-up mechanism of decision strategy selection and lead to the final choice: (1) cue weight computation, (2) gain modulation, and (3) weighted additive evaluation of alternatives. We discuss how these processes might be implemented in the brain, and how this knowledge allows us to formulate novel predictions linking strategy use and neural signals. PMID:27877103

Cognitive niches: an ecological model of strategy selection.

PubMed

Marewski, Julian N; Schooler, Lael J

2011-07-01

How do people select among different strategies to accomplish a given task? Across disciplines, the strategy selection problem represents a major challenge. We propose a quantitative model that predicts how selection emerges through the interplay among strategies, cognitive capacities, and the environment. This interplay carves out for each strategy a cognitive niche, that is, a limited number of situations in which the strategy can be applied, simplifying strategy selection. To illustrate our proposal, we consider selection in the context of 2 theories: the simple heuristics framework and the ACT-R (adaptive control of thought-rational) architecture of cognition. From the heuristics framework, we adopt the thesis that people make decisions by selecting from a repertoire of simple decision strategies that exploit regularities in the environment and draw on cognitive capacities, such as memory and time perception. ACT-R provides a quantitative theory of how these capacities adapt to the environment. In 14 simulations and 10 experiments, we consider the choice between strategies that operate on the accessibility of memories and those that depend on elaborate knowledge about the world. Based on Internet statistics, our model quantitatively predicts people's familiarity with and knowledge of real-world objects, the distributional characteristics of the associated speed of memory retrieval, and the cognitive niches of classic decision strategies, including those of the fluency, recognition, integration, lexicographic, and sequential-sampling heuristics. In doing so, the model specifies when people will be able to apply different strategies and how accurate, fast, and effortless people's decisions will be.

Patterns of drought tolerance in major European temperate forest trees: climatic drivers and levels of variability.

PubMed

Zang, Christian; Hartl-Meier, Claudia; Dittmar, Christoph; Rothe, Andreas; Menzel, Annette

2014-12-01

The future performance of native tree species under climate change conditions is frequently discussed, since increasingly severe and more frequent drought events are expected to become a major risk for forest ecosystems. To improve our understanding of the drought tolerance of the three common European temperate forest tree species Norway spruce, silver fir and common beech, we tested the influence of climate and tree-specific traits on the inter and intrasite variability in drought responses of these species. Basal area increment data from a large tree-ring network in Southern Germany and Alpine Austria along a climatic cline from warm-dry to cool-wet conditions were used to calculate indices of tolerance to drought events and their variability at the level of individual trees and populations. General patterns of tolerance indicated a high vulnerability of Norway spruce in comparison to fir and beech and a strong influence of bioclimatic conditions on drought response for all species. On the level of individual trees, low-growth rates prior to drought events, high competitive status and low age favored resilience in growth response to drought. Consequently, drought events led to heterogeneous and variable response patterns in forests stands. These findings may support the idea of deliberately using spontaneous selection and adaption effects as a passive strategy of forest management under climate change conditions, especially a strong directional selection for more tolerant individuals when frequency and intensity of summer droughts will increase in the course of global climate change. © 2014 John Wiley & Sons Ltd.

Effectiveness of planned teaching program on knowledge regarding Alzheimer's disease among the family members of elderly in a selected urban community at Mangalore

PubMed Central

Rodrigues, Lavina; Mathias, Thereza

2016-01-01

Background: Alzheimer's disease is one of the debilitating chronic diseases among older persons. It is an irreversible condition that leads to progressive deterioration of cognitive, intellectual, physical, and psychosocial functions. The study was aimed to assess the knowledge of the family members of elderly regarding Alzheimer's disease in a selected urban community at Mangalore. Materials and Methods: A preexperimental research design of one group pretest and posttest with an evaluative approach was adopted for the study. A total of 50 family members of elderly who met the inclusion criteria were selected through purposive sampling technique. The researcher developed a planned teaching program on Alzheimer's disease, and structured knowledge questionnaire on Alzheimer's disease was used to collect the data. Results: Descriptive and inferential statistics was used to analyze the data. Analysis revealed that the mean posttest knowledge (20.78 ± 3.31) was higher than mean pretest knowledge scores (12.90 ± 2.43). Significance of difference between pretest and posttest was statistically tested using paired “t” test and it was found very highly significant (t = 40.85, P < 0.05). Majority of the variables showed no significant association between pretest and posttest knowledge score and with demographic variables. Conclusion: The findings revealed that the planned teaching program is an effective strategy for improving the knowledge of the subjects. PMID:26985104

Effectiveness of planned teaching program on knowledge regarding Alzheimer's disease among the family members of elderly in a selected urban community at Mangalore.

PubMed

Rodrigues, Lavina; Mathias, Thereza

2016-01-01

Alzheimer's disease is one of the debilitating chronic diseases among older persons. It is an irreversible condition that leads to progressive deterioration of cognitive, intellectual, physical, and psychosocial functions. The study was aimed to assess the knowledge of the family members of elderly regarding Alzheimer's disease in a selected urban community at Mangalore. A preexperimental research design of one group pretest and posttest with an evaluative approach was adopted for the study. A total of 50 family members of elderly who met the inclusion criteria were selected through purposive sampling technique. The researcher developed a planned teaching program on Alzheimer's disease, and structured knowledge questionnaire on Alzheimer's disease was used to collect the data. Descriptive and inferential statistics was used to analyze the data. Analysis revealed that the mean posttest knowledge (20.78 ± 3.31) was higher than mean pretest knowledge scores (12.90 ± 2.43). Significance of difference between pretest and posttest was statistically tested using paired "t" test and it was found very highly significant (t = 40.85, P < 0.05). Majority of the variables showed no significant association between pretest and posttest knowledge score and with demographic variables. The findings revealed that the planned teaching program is an effective strategy for improving the knowledge of the subjects.

Genetic variability and evolutionary dynamics of viruses of the family Closteroviridae

PubMed Central

Rubio, Luis; Guerri, José; Moreno, Pedro

2013-01-01

RNA viruses have a great potential for genetic variation, rapid evolution and adaptation. Characterization of the genetic variation of viral populations provides relevant information on the processes involved in virus evolution and epidemiology and it is crucial for designing reliable diagnostic tools and developing efficient and durable disease control strategies. Here we performed an updated analysis of sequences available in Genbank and reviewed present knowledge on the genetic variability and evolutionary processes of viruses of the family Closteroviridae. Several factors have shaped the genetic structure and diversity of closteroviruses. (I) A strong negative selection seems to be responsible for the high genetic stability in space and time for some viruses. (2) Long distance migration, probably by human transport of infected propagative plant material, have caused that genetically similar virus isolates are found in distant geographical regions. (3) Recombination between divergent sequence variants have generated new genotypes and plays an important role for the evolution of some viruses of the family Closteroviridae. (4) Interaction between virus strains or between different viruses in mixed infections may alter accumulation of certain strains. (5) Host change or virus transmission by insect vectors induced changes in the viral population structure due to positive selection of sequence variants with higher fitness for host-virus or vector-virus interaction (adaptation) or by genetic drift due to random selection of sequence variants during the population bottleneck associated to the transmission process. PMID:23805130

Developing a weighting strategy to include mobile phone numbers into an ongoing population health survey using an overlapping dual-frame design with limited benchmark information

PubMed Central

2014-01-01

Background In 2012 mobile phone numbers were included into the ongoing New South Wales Population Health Survey (NSWPHS) using an overlapping dual-frame design. Previously in the NSWPHS the sample was selected using random digit dialing (RDD) of landline phone numbers. The survey was undertaken using computer assisted telephone interviewing (CATI). The weighting strategy needed to be significantly expanded to manage the differing probabilities of selection by frame, including that of children of mobile-only phone users, and to adjust for the increased chance of selection of dual-phone users. This paper describes the development of the final weighting strategy to properly combine the data from two overlapping sample frames accounting for the fact that population benchmarks for the different sampling frames were not available at the state or regional level. Methods Estimates of the number of phone numbers for the landline and mobile phone frames used to calculate the differing probabilities of selection by frame, for New South Wales (NSW) and by stratum, were obtained by apportioning Australian estimates as none were available for NSW. The weighting strategy was then developed by calculating person selection probabilities, selection weights, applying a constant composite factor to the dual-phone users sample weights, and benchmarking to the latest NSW population by age group, sex and stratum. Results Data from the NSWPHS for the first quarter of 2012 was used to test the weighting strategy. This consisted of data on 3395 respondents with 2171 (64%) from the landline frame and 1224 (36%) from the mobile frame. However, in order to calculate the weights, data needed to be available for all core weighting variables and so 3378 respondents, 2933 adults and 445 children, had sufficient data to be included. Average person weights were 3.3 times higher for the mobile-only respondents, 1.3 times higher for the landline-only respondents and 1.7 times higher for dual-phone users in the mobile frame compared to the dual-phone users in the landline frame. The overall weight effect for the first quarter of 2012 was 1.93 and the coefficient of variation of the weights was 0.96. The weight effects for 2012 were similar to, and in many cases less than, the effects found in the corresponding quarter of the 2011 NSWPHS when only a landline based sample was used. Conclusions The inclusion of mobile phone numbers, through an overlapping dual-frame design, improved the coverage of the survey and an appropriate weighing procedure is feasible, although it added substantially to the complexity of the weighting strategy. Access to accurate Australian, State and Territory estimates of the number of landline and mobile phone numbers and type of phone use by at least age group and sex would greatly assist in the weighting of dual-frame surveys in Australia. PMID:25189826

Developing a weighting strategy to include mobile phone numbers into an ongoing population health survey using an overlapping dual-frame design with limited benchmark information.

PubMed

Barr, Margo L; Ferguson, Raymond A; Hughes, Phil J; Steel, David G

2014-09-04

In 2012 mobile phone numbers were included into the ongoing New South Wales Population Health Survey (NSWPHS) using an overlapping dual-frame design. Previously in the NSWPHS the sample was selected using random digit dialing (RDD) of landline phone numbers. The survey was undertaken using computer assisted telephone interviewing (CATI). The weighting strategy needed to be significantly expanded to manage the differing probabilities of selection by frame, including that of children of mobile-only phone users, and to adjust for the increased chance of selection of dual-phone users. This paper describes the development of the final weighting strategy to properly combine the data from two overlapping sample frames accounting for the fact that population benchmarks for the different sampling frames were not available at the state or regional level. Estimates of the number of phone numbers for the landline and mobile phone frames used to calculate the differing probabilities of selection by frame, for New South Wales (NSW) and by stratum, were obtained by apportioning Australian estimates as none were available for NSW. The weighting strategy was then developed by calculating person selection probabilities, selection weights, applying a constant composite factor to the dual-phone users sample weights, and benchmarking to the latest NSW population by age group, sex and stratum. Data from the NSWPHS for the first quarter of 2012 was used to test the weighting strategy. This consisted of data on 3395 respondents with 2171 (64%) from the landline frame and 1224 (36%) from the mobile frame. However, in order to calculate the weights, data needed to be available for all core weighting variables and so 3378 respondents, 2933 adults and 445 children, had sufficient data to be included. Average person weights were 3.3 times higher for the mobile-only respondents, 1.3 times higher for the landline-only respondents and 1.7 times higher for dual-phone users in the mobile frame compared to the dual-phone users in the landline frame. The overall weight effect for the first quarter of 2012 was 1.93 and the coefficient of variation of the weights was 0.96. The weight effects for 2012 were similar to, and in many cases less than, the effects found in the corresponding quarter of the 2011 NSWPHS when only a landline based sample was used. The inclusion of mobile phone numbers, through an overlapping dual-frame design, improved the coverage of the survey and an appropriate weighing procedure is feasible, although it added substantially to the complexity of the weighting strategy. Access to accurate Australian, State and Territory estimates of the number of landline and mobile phone numbers and type of phone use by at least age group and sex would greatly assist in the weighting of dual-frame surveys in Australia.

Predicting cognitive function from clinical measures of physical function and health status in older adults.

PubMed

Bolandzadeh, Niousha; Kording, Konrad; Salowitz, Nicole; Davis, Jennifer C; Hsu, Liang; Chan, Alison; Sharma, Devika; Blohm, Gunnar; Liu-Ambrose, Teresa

2015-01-01

Current research suggests that the neuropathology of dementia-including brain changes leading to memory impairment and cognitive decline-is evident years before the onset of this disease. Older adults with cognitive decline have reduced functional independence and quality of life, and are at greater risk for developing dementia. Therefore, identifying biomarkers that can be easily assessed within the clinical setting and predict cognitive decline is important. Early recognition of cognitive decline could promote timely implementation of preventive strategies. We included 89 community-dwelling adults aged 70 years and older in our study, and collected 32 measures of physical function, health status and cognitive function at baseline. We utilized an L1-L2 regularized regression model (elastic net) to identify which of the 32 baseline measures were strongly predictive of cognitive function after one year. We built three linear regression models: 1) based on baseline cognitive function, 2) based on variables consistently selected in every cross-validation loop, and 3) a full model based on all the 32 variables. Each of these models was carefully tested with nested cross-validation. Our model with the six variables consistently selected in every cross-validation loop had a mean squared prediction error of 7.47. This number was smaller than that of the full model (115.33) and the model with baseline cognitive function (7.98). Our model explained 47% of the variance in cognitive function after one year. We built a parsimonious model based on a selected set of six physical function and health status measures strongly predictive of cognitive function after one year. In addition to reducing the complexity of the model without changing the model significantly, our model with the top variables improved the mean prediction error and R-squared. These six physical function and health status measures can be easily implemented in a clinical setting.

Effects of EFL Individual Learner Variables on Foreign Language Reading Anxiety and Metacognitive Reading Strategy Use.

PubMed

Lien, Hsin-Yi

2016-08-01

Past research has shown an association between foreign language reading anxiety and reading strategy. However, individual variables tend to affect foreign language anxiety and strategy use. The present study examined a hypothesized model that specified direct and indirect effects among English and foreign languages readers' distinct variables, including academic level; self-perceived English level; and satisfaction with reading proficiency, reading anxiety, and metacognitive awareness of reading strategies. A total of 523 volunteer Taiwanese college students provided 372 valid responses to a written questionnaire (281 women and 91 men; M age = 19.7 years, SD = 1.1) containing the translated versions of Foreign Language Reading Anxiety Scale, Survey of Reading Strategies Inventory, and self-assessment background questionnaire. The results showed that self-evaluation of reading proficiency did not correlate with academic level and readers' perceptions. Satisfaction had a direct effect on foreign language reading anxiety but not on metacognitive awareness of reading strategies. Results of path analysis demonstrated that the perception learners who had their own reading proficiency predicted their foreign language reading anxiety and was a mediating variable for metacognitive reading strategy use. © The Author(s) 2016.

Mate choice for major histocompatibility complex genetic divergence as a bet-hedging strategy in the Atlantic salmon (Salmo salar).

PubMed

Evans, Melissa L; Dionne, Mélanie; Miller, Kristina M; Bernatchez, Louis

2012-01-22

Major histocompatibility complex (MHC)-dependent mating preferences have been observed across vertebrate taxa and these preferences are expected to promote offspring disease resistance and ultimately, viability. However, little empirical evidence linking MHC-dependent mate choice and fitness is available, particularly in wild populations. Here, we explore the adaptive potential of previously observed patterns of MHC-dependent mate choice in a wild population of Atlantic salmon (Salmo salar) in Québec, Canada, by examining the relationship between MHC genetic variation and adult reproductive success and offspring survival over 3 years of study. While Atlantic salmon choose their mates in order to increase MHC diversity in offspring, adult reproductive success was in fact maximized between pairs exhibiting an intermediate level of MHC dissimilarity. Moreover, patterns of offspring survival between years 0+ and 1+, and 1+ and 2+ and population genetic structure at the MHC locus relative to microsatellite loci indicate that strong temporal variation in selection is likely to be operating on the MHC. We interpret MHC-dependent mate choice for diversity as a likely bet-hedging strategy that maximizes parental fitness in the face of temporally variable and unpredictable natural selection pressures.

POTENTIAL EFFECTS OF WHOLE-BODY VIBRATION EXERCISES ON BLOOD FLOW KINETICS OF DIFFERENT POPULATIONS: A SYSTEMATIC REVIEW WITH A SUITABLE APPROACH

PubMed Central

Sá-Caputo, Danúbia; Paineiras-Domingos, Laisa; Carvalho-Lima, Rafaelle; Dias-Costa, Glenda; de Paiva, Patrícia de Castro; de Azeredo, Claudia Figueiredo; Carmo, Roberto Carlos Resende; Dionello, Carla F.; Moreira-Marconi, Eloá; Frederico, Éric Heleno F.F.; Sousa-Gonçalves, Cintia Renata; Morel, Danielle S.; Paiva, Dulciane N.; Avelar, Núbia C.P.; Lacerda, Ana C.; Magalhães, Carlos E.V.; Castro, Leonardo S.; Presta, Giuseppe A.; de Paoli, Severo; Sañudo, Borja; Bernardo-Filho, Mario

2017-01-01

Background: The ability to control skin blood flow decreases with advancing age and some clinical disorders, as in diabetes and in rheumatologic diseases. Feasible clinical strategies such as whole-body vibration exercise (WBVE) are being used without a clear understanding of its effects. The aim of the present study is to review the effects of the WBVE on blood flow kinetics and its feasibility in different populations. Material and Methods: The level of evidence (LE) of selected papers in PubMed and/or PEDRo databases was determined. We selected randomized, controlled trials in English to be evaluated. Results: Six studies had LE II, one had LE III-2 and one III-3 according to the NHMRC. A great variability among the protocols was observed but also in the assessment devices; therefore, more research about this topic is warranted. Conclusion: Despite the limitations, it is can be concluded that the use of WBVE has proven to be a safe and useful strategy to improve blood flow. However, more studies with greater methodological quality are needed to clearly define the more suitable protocols. PMID:28740943

Lifestyle of patients with diabetes mellitus type 1: a systematic review.

PubMed

Sales-Peres, Silvia Helena de Carvalho; Guedes, Maria de Fatima Santos; Sá, Letícia Marques; Negrato, Carlos Antonio; Lauris, José Roberto Pereira

2016-04-01

The aim of this review was to verify data concerning the relationship between the existent lifestyle and glycemic control in patients with Diabetes Mellitus Type 1 (DM1). The methods applied included the literature search strategy, selection of studies by means of inclusion and exclusion strategies, according to the characteristics of the studies. The search was conducted in the Lilacs, Medline, PubMed, Cochrame, SciELO and IBECS databases between in the period between 2005 and 2014. The articles selected were studies in humans, investing lifestyle, physical activities and glycemic levels. Of the 1798 studies initially identified, 11 met the eligibility criteria. Among the studies analyzed, 1 cohort; 1 longitudinal prospective, 1 case control and 8 transversal studies that approached the proposed theme were related. Regular physical activity was the variable that presented greatest relationship with the improvement in glycemic levels. Healthy active life, balanced diet, physical activities and education in diabetes improved the glycemic control of the DM1 patient. The results allowed the authors to conclude that a lifestyle based on physical activities interfered directly in the health of patients with DM1, in addition to contributing the glycemic control.

Mate choice for major histocompatibility complex genetic divergence as a bet-hedging strategy in the Atlantic salmon (Salmo salar)

PubMed Central

Evans, Melissa L.; Dionne, Mélanie; Miller, Kristina M.; Bernatchez, Louis

2012-01-01

Major histocompatibility complex (MHC)-dependent mating preferences have been observed across vertebrate taxa and these preferences are expected to promote offspring disease resistance and ultimately, viability. However, little empirical evidence linking MHC-dependent mate choice and fitness is available, particularly in wild populations. Here, we explore the adaptive potential of previously observed patterns of MHC-dependent mate choice in a wild population of Atlantic salmon (Salmo salar) in Québec, Canada, by examining the relationship between MHC genetic variation and adult reproductive success and offspring survival over 3 years of study. While Atlantic salmon choose their mates in order to increase MHC diversity in offspring, adult reproductive success was in fact maximized between pairs exhibiting an intermediate level of MHC dissimilarity. Moreover, patterns of offspring survival between years 0+ and 1+, and 1+ and 2+ and population genetic structure at the MHC locus relative to microsatellite loci indicate that strong temporal variation in selection is likely to be operating on the MHC. We interpret MHC-dependent mate choice for diversity as a likely bet-hedging strategy that maximizes parental fitness in the face of temporally variable and unpredictable natural selection pressures. PMID:21697172

Targeting Stereotyped B Cell Receptors from Chronic Lymphocytic Leukemia Patients with Synthetic Antigen Surrogates.

PubMed

Sarkar, Mohosin; Liu, Yun; Qi, Junpeng; Peng, Haiyong; Morimoto, Jumpei; Rader, Christoph; Chiorazzi, Nicholas; Kodadek, Thomas

2016-04-01

Chronic lymphocytic leukemia (CLL) is a disease in which a single B-cell clone proliferates relentlessly in peripheral lymphoid organs, bone marrow, and blood. DNA sequencing experiments have shown that about 30% of CLL patients have stereotyped antigen-specific B-cell receptors (BCRs) with a high level of sequence homology in the variable domains of the heavy and light chains. These include many of the most aggressive cases that haveIGHV-unmutated BCRs whose sequences have not diverged significantly from the germ line. This suggests a personalized therapy strategy in which a toxin or immune effector function is delivered selectively to the pathogenic B-cells but not to healthy B-cells. To execute this strategy, serum-stable, drug-like compounds able to target the antigen-binding sites of most or all patients in a stereotyped subset are required. We demonstrate here the feasibility of this approach with the discovery of selective, high affinity ligands for CLL BCRs of the aggressive, stereotyped subset 7P that cross-react with the BCRs of several CLL patients in subset 7p, but not with BCRs from patients outside this subset. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Gait impairment precedes clinical symptoms in spinocerebellar ataxia type 6.

PubMed

Rochester, Lynn; Galna, Brook; Lord, Sue; Mhiripiri, Dadirayi; Eglon, Gail; Chinnery, Patrick F

2014-02-01

Spinocerebellar ataxia type 6 (SCA6) is an inherited ataxia with no established treatment. Gait ataxia is a prominent feature causing substantial disability. Understanding the evolution of the gait disturbance is a key step in developing treatment strategies. We studied 9 gait variables in 24 SCA6 (6 presymptomatic; 18 symptomatic) and 24 controls and correlated gait with clinical severity (presymptomatic and symptomatic). Discrete gait characteristics precede symptoms in SCA6 with significantly increased variability of step width and step time, whereas a more global gait deficit was evident in symptomatic individuals. Gait characteristics discriminated between presymptomatic and symptomatic individuals and were selectively associated with disease severity. This is the largest study to include a detailed characterization of gait in SCA6, including presymptomatic subjects, allowing changes across the disease spectrum to be compared. Selective gait disturbance is already present in SCA6 before clinical symptoms appear and gait characteristics are also sensitive to disease progression. Early gait disturbance likely reflects primary pathology distinct from secondary changes. These findings open the opportunity for early evaluation and sensitive measures of therapeutic efficacy using instrumented gait analysis which may have broader relevance for all degenerative ataxias. © 2013 Movement Disorder Society.

The role of fecundity and reproductive effort in defining life-history strategies of North American freshwater mussels.

PubMed

Haag, Wendell R

2013-08-01

Selection is expected to optimize reproductive investment resulting in characteristic trade-offs among traits such as brood size, offspring size, somatic maintenance, and lifespan; relative patterns of energy allocation to these functions are important in defining life-history strategies. Freshwater mussels are a diverse and imperiled component of aquatic ecosystems, but little is known about their life-history strategies, particularly patterns of fecundity and reproductive effort. Because mussels have an unusual life cycle in which larvae (glochidia) are obligate parasites on fishes, differences in host relationships are expected to influence patterns of reproductive output among species. I investigated fecundity and reproductive effort (RE) and their relationships to other life-history traits for a taxonomically broad cross section of North American mussel diversity. Annual fecundity of North American mussel species spans nearly four orders of magnitude, ranging from < 2000 to 10 million, but most species have considerably lower fecundity than previous generalizations, which portrayed the group as having uniformly high fecundity (e.g. > 200000). Estimates of RE also were highly variable, ranging among species from 0.06 to 25.4%. Median fecundity and RE differed among phylogenetic groups, but patterns for these two traits differed in several ways. For example, the tribe Anodontini had relatively low median fecundity but had the highest RE of any group. Within and among species, body size was a strong predictor of fecundity and explained a high percentage of variation in fecundity among species. Fecundity showed little relationship to other life-history traits including glochidial size, lifespan, brooding strategies, or host strategies. The only apparent trade-off evident among these traits was the extraordinarily high fecundity of Leptodea, Margaritifera, and Truncilla, which may come at a cost of greatly reduced glochidial size; there was no relationship between fecundity and glochidial size for the remaining 61 species in the dataset. In contrast to fecundity, RE showed evidence of a strong trade-off with lifespan, which was negatively related to RE. The raw number of glochidia produced may be determined primarily by physical and energetic constraints rather than selection for optimal output based on differences in host strategies or other traits. By integrating traits such as body size, glochidial size, and fecundity, RE appears more useful in defining mussel life-history strategies. Combined with trade-offs between other traits such as growth, lifespan, and age at maturity, differences in RE among species depict a broad continuum of divergent strategies ranging from strongly r-selected species (e.g. tribe Anodontini and some Lampsilini) to K-selected species (e.g. tribes Pleurobemini and Quadrulini; family Margaritiferidae). Future studies of reproductive effort in an environmental and life-history context will be useful for understanding the explosive radiation of this group of animals in North America and will aid in the development of effective conservation strategies. Published 2013. This article is a U.S. Government work and is in the public domain in the USA.

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.

Individualized Nonadaptive and Online-Adaptive Intensity-Modulated Radiotherapy Treatment Strategies for Cervical Cancer Patients Based on Pretreatment Acquired Variable Bladder Filling Computed Tomography Scans

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

Bondar, M.L., E-mail: m.bondar@erasmusmc.nl; Hoogeman, M.S.; Mens, J.W.

2012-08-01

Purpose: To design and evaluate individualized nonadaptive and online-adaptive strategies based on a pretreatment established motion model for the highly deformable target volume in cervical cancer patients. Methods and Materials: For 14 patients, nine to ten variable bladder filling computed tomography (CT) scans were acquired at pretreatment and after 40 Gy. Individualized model-based internal target volumes (mbITVs) accounting for the cervix and uterus motion due to bladder volume changes were generated by using a motion-model constructed from two pretreatment CT scans (full and empty bladder). Two individualized strategies were designed: a nonadaptive strategy, using an mbITV accounting for the full-rangemore » of bladder volume changes throughout the treatment; and an online-adaptive strategy, using mbITVs of bladder volume subranges to construct a library of plans. The latter adapts the treatment online by selecting the plan-of-the-day from the library based on the measured bladder volume. The individualized strategies were evaluated by the seven to eight CT scans not used for mbITVs construction, and compared with a population-based approach. Geometric uniform margins around planning cervix-uterus and mbITVs were determined to ensure adequate coverage. For each strategy, the percentage of the cervix-uterus, bladder, and rectum volumes inside the planning target volume (PTV), and the clinical target volume (CTV)-to-PTV volume (volume difference between PTV and CTV) were calculated. Results: The margin for the population-based approach was 38 mm and for the individualized strategies was 7 to 10 mm. Compared with the population-based approach, the individualized nonadaptive strategy decreased the CTV-to-PTV volume by 48% {+-} 6% and the percentage of bladder and rectum inside the PTV by 5% to 45% and 26% to 74% (p < 0.001), respectively. Replacing the individualized nonadaptive strategy by an online-adaptive, two-plan library further decreased the percentage of bladder and rectum inside the PTV (0% to 10% and -1% to 9%; p < 0.004) and the CTV-to-PTV volume (4-96 ml). Conclusions: Compared with population-based margins, an individualized PTV results in better organ-at-risk sparing. Online-adaptive radiotherapy further improves organ-at-risk sparing.« less

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…

Sorting cells of the microalga Chlorococcum littorale with increased triacylglycerol productivity.

PubMed

Cabanelas, Iago Teles Dominguez; van der Zwart, Mathijs; Kleinegris, Dorinde M M; Wijffels, René H; Barbosa, Maria J

2016-01-01

Despite extensive research in the last decades, microalgae are still only economically feasible for high valued markets. Strain improvement is a strategy to increase productivities, hence reducing costs. In this work, we focus on microalgae selection: taking advantage of the natural biological variability of species to select variations based on desired characteristics. We focused on triacylglycerol (TAG), which have applications ranging from biodiesel to high-value omega-3 fatty-acids. Hence, we demonstrated a strategy to sort microalgae cells with increased TAG productivity. 1. We successfully identified sub-populations of cells with increased TAG productivity using Fluorescence assisted cell sorting (FACS). 2. We sequentially sorted cells after repeated cycles of N-starvation, resulting in five sorted populations (S1-S5). 3. The comparison between sorted and original populations showed that S5 had the highest TAG productivity [0.34 against 0.18 g l(-1) day(-1) (original), continuous light]. 4. Original and S5 were compared in lab-scale reactors under simulated summer conditions confirming the increased TAG productivity of S5 (0.4 against 0.2 g l(-1) day(-1)). Biomass composition analyses showed that S5 produced more biomass under N-starvation because of an increase only in TAG content and, flow cytometry showed that our selection removed cells with lower efficiency in producing TAGs. All combined, our results present a successful strategy to improve the TAG productivity of Chlorococcum littorale, without resourcing to genetic manipulation or random mutagenesis. Additionally, the improved TAG productivity of S5 was confirmed under simulated summer conditions, highlighting the industrial potential of S5 for microalgal TAG production.

Selecting predictors for discriminant analysis of species performance: an example from an amphibious softwater plant.

PubMed

Vanderhaeghe, F; Smolders, A J P; Roelofs, J G M; Hoffmann, M

2012-03-01

Selecting an appropriate variable subset in linear multivariate methods is an important methodological issue for ecologists. Interest often exists in obtaining general predictive capacity or in finding causal inferences from predictor variables. Because of a lack of solid knowledge on a studied phenomenon, scientists explore predictor variables in order to find the most meaningful (i.e. discriminating) ones. As an example, we modelled the response of the amphibious softwater plant Eleocharis multicaulis using canonical discriminant function analysis. We asked how variables can be selected through comparison of several methods: univariate Pearson chi-square screening, principal components analysis (PCA) and step-wise analysis, as well as combinations of some methods. We expected PCA to perform best. The selected methods were evaluated through fit and stability of the resulting discriminant functions and through correlations between these functions and the predictor variables. The chi-square subset, at P < 0.05, followed by a step-wise sub-selection, gave the best results. In contrast to expectations, PCA performed poorly, as so did step-wise analysis. The different chi-square subset methods all yielded ecologically meaningful variables, while probable noise variables were also selected by PCA and step-wise analysis. We advise against the simple use of PCA or step-wise discriminant analysis to obtain an ecologically meaningful variable subset; the former because it does not take into account the response variable, the latter because noise variables are likely to be selected. We suggest that univariate screening techniques are a worthwhile alternative for variable selection in ecology. © 2011 German Botanical Society and The Royal Botanical Society of the Netherlands.

Determination of patellofemoral pain sub-groups and development of a method for predicting treatment outcome using running gait kinematics.

PubMed

Watari, Ricky; Kobsar, Dylan; Phinyomark, Angkoon; Osis, Sean; Ferber, Reed

2016-10-01

Not all patients with patellofemoral pain exhibit successful outcomes following exercise therapy. Thus, the ability to identify patellofemoral pain subgroups related to treatment response is important for the development of optimal therapeutic strategies to improve rehabilitation outcomes. The purpose of this study was to use baseline running gait kinematic and clinical outcome variables to classify patellofemoral pain patients on treatment response retrospectively. Forty-one individuals with patellofemoral pain that underwent a 6-week exercise intervention program were sub-grouped as treatment Responders (n=28) and Non-responders (n=13) based on self-reported measures of pain and function. Baseline three-dimensional running kinematics, and self-reported measures underwent a linear discriminant analysis of the principal components of the variables to retrospectively classify participants based on treatment response. The significance of the discriminant function was verified with a Wilk's lambda test (α=0.05). The model selected 2 gait principal components and had a 78.1% classification accuracy. Overall, Non-responders exhibited greater ankle dorsiflexion, knee abduction and hip flexion during the swing phase and greater ankle inversion during the stance phase, compared to Responders. This is the first study to investigate an objective method to use baseline kinematic and self-report outcome variables to classify on patellofemoral pain treatment outcome. This study represents a significant first step towards a method to help clinicians make evidence-informed decisions regarding optimal treatment strategies for patients with patellofemoral pain. Copyright © 2016 Elsevier Ltd. All rights reserved.

Combinatorial selection of molecular conformations and supramolecular synthons in quercetin cocrystal landscapes: a route to ternary solids

PubMed Central

Dubey, Ritesh; Desiraju, Gautam R.

2015-01-01

The crystallization of 28 binary and ternary cocrystals of quercetin with dibasic coformers is analyzed in terms of a combinatorial selection from a solution of preferred molecular conformations and supramolecular synthons. The crystal structures are characterized by distinctive O—H⋯N and O—H⋯O based synthons and are classified as nonporous, porous and helical. Variability in molecular conformation and synthon structure led to an increase in the energetic and structural space around the crystallization event. This space is the crystal structure landscape of the compound and is explored by fine-tuning the experimental conditions of crystallization. In the landscape context, we develop a strategy for the isolation of ternary cocrystals with the use of auxiliary template molecules to reduce the molecular and supramolecular ‘confusion’ that is inherent in a molecule like quercetin. The absence of concomitant polymorphism in this study highlights the selectivity in conformation and synthon choice from the virtual combinatorial library in solution. PMID:26175900

Drinking Water Quality Criterion - Based site Selection of Aquifer Storage and Recovery Scheme in Chou-Shui River Alluvial Fan

NASA Astrophysics Data System (ADS)

Huang, H. E.; Liang, C. P.; Jang, C. S.; Chen, J. S.

2015-12-01

Land subsidence due to groundwater exploitation is an urgent environmental problem in Choushui river alluvial fan in Taiwan. Aquifer storage and recovery (ASR), where excess surface water is injected into subsurface aquifers for later recovery, is one promising strategy for managing surplus water and may overcome water shortages. The performance of an ASR scheme is generally evaluated in terms of recovery efficiency, which is defined as percentage of water injected in to a system in an ASR site that fulfills the targeted water quality criterion. Site selection of an ASR scheme typically faces great challenges, due to the spatial variability of groundwater quality and hydrogeological condition. This study proposes a novel method for the ASR site selection based on drinking quality criterion. Simplified groundwater flow and contaminant transport model spatial distributions of the recovery efficiency with the help of the groundwater quality, hydrological condition, ASR operation. The results of this study may provide government administrator for establishing reliable ASR scheme.

Variable Neighborhood Search Heuristics for Selecting a Subset of Variables in Principal Component Analysis

ERIC Educational Resources Information Center

Brusco, Michael J.; Singh, Renu; Steinley, Douglas

2009-01-01

The selection of a subset of variables from a pool of candidates is an important problem in several areas of multivariate statistics. Within the context of principal component analysis (PCA), a number of authors have argued that subset selection is crucial for identifying those variables that are required for correct interpretation of the…

Inter-individual variability and pattern recognition of surface electromyography in front crawl swimming.

PubMed

Martens, Jonas; Daly, Daniel; Deschamps, Kevin; Staes, Filip; Fernandes, Ricardo J

2016-12-01

Variability of electromyographic (EMG) recordings is a complex phenomenon rarely examined in swimming. Our purposes were to investigate inter-individual variability in muscle activation patterns during front crawl swimming and assess if there were clusters of sub patterns present. Bilateral muscle activity of rectus abdominis (RA) and deltoideus medialis (DM) was recorded using wireless surface EMG in 15 adult male competitive swimmers. The amplitude of the median EMG trial of six upper arm movement cycles was used for the inter-individual variability assessment, quantified with the coefficient of variation, coefficient of quartile variation, the variance ratio and mean deviation. Key features were selected based on qualitative and quantitative classification strategies to enter in a k-means cluster analysis to examine the presence of strong sub patterns. Such strong sub patterns were found when clustering in two, three and four clusters. Inter-individual variability in a group of highly skilled swimmers was higher compared to other cyclic movements which is in contrast to what has been reported in the previous 50years of EMG research in swimming. This leads to the conclusion that coaches should be careful in using overall reference EMG information to enhance the individual swimming technique of their athletes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Statistical synthesis of contextual knowledge to increase the effectiveness of theory-based behaviour change interventions.

PubMed

Hanbury, Andria; Thompson, Carl; Mannion, Russell

2011-07-01

Tailored implementation strategies targeting health professionals' adoption of evidence-based recommendations are currently being developed. Research has focused on how to select an appropriate theoretical base, how to use that theoretical base to explore the local context, and how to translate theoretical constructs associated with the key factors found to influence innovation adoption into feasible and tailored implementation strategies. The reasons why an intervention is thought not to have worked are often cited as being: inappropriate choice of theoretical base; unsystematic development of the implementation strategies; and a poor evidence base to guide the process. One area of implementation research that is commonly overlooked is how to synthesize the data collected in a local context in order to identify what factors to target with the implementation strategies. This is suggested to be a critical process in the development of a theory-based intervention. The potential of multilevel modelling techniques to synthesize data collected at different hierarchical levels, for example, individual attitudes and team level variables, is discussed. Future research is needed to explore further the potential of multilevel modelling for synthesizing contextual data in implementation studies, as well as techniques for synthesizing qualitative and quantitative data.

Risky choice with heuristics: reply to Birnbaum (2008), Johnson, Schulte-Mecklenbeck, and Willemsen (2008), and Rieger and Wang (2008).

PubMed

Brandstätter, Eduard; Gigerenzer, Gerd; Hertwig, Ralph

2008-01-01

E. Brandstätter, G. Gigerenzer, and R. Hertwig (2006) showed that the priority heuristic matches or outperforms modifications of expected utility theory in predicting choice in 4 diverse problem sets. M. H. Birnbaum (2008) argued that sets exist in which the opposite is true. The authors agree--but stress that all choice strategies have regions of good and bad performance. The accuracy of various strategies systematically depends on choice difficulty, which the authors consider a triggering variable underlying strategy selection. Agreeing with E. J. Johnson, M. Schulte-Mecklenbeck, and M. C. Willemsen (2008) that process (not "as-if") models need to be formulated, the authors show how quantitative predictions can be derived and test them. Finally, they demonstrate that many of Birnbaum's and M. O. Rieger and M. Wang's (2008) case studies championing their preferred models involved biased tests in which the priority heuristic predicted data, whereas the parameterized models were fitted to the same data. The authors propose an adaptive toolbox approach of risky choice, according to which people first seek a no-conflict solution before resorting to conflict-resolving strategies such as the priority heuristic. (c) 2008 APA, all rights reserved

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

Vulnerability and Tradeoffs of Dairy Farmers to the Impacts of Climate Variability and Change in India

NASA Astrophysics Data System (ADS)

Radhakrishnan, A.; Gupta, J.; R, D.

2016-12-01

In recent years climate variability has threatened the sustainability of dairy animals and dairy farming in India. The study aims at assessing the vulnerability and tradeoffs of Dairy Based Livelihoods to Climate Variability and Change in the Western Ghat ecosystem and for this purpose; data were aggregated to an overall Livelihood Vulnerability Index (LVI) to Climate Change underlying the principles of IPCC, using 28 indicators and trade-off between vulnerability and milk production was calculated. Data were collected through Participatory Rural Appraisal and personal interviews from 360 randomly selected dairy farmers of three states of Western Ghat region, complemented by thirty years of gridded weather data and livestock data. The index score of dairy based livelihoods of many regions were negative. Lanja taluka of Maharashtra has highest level of vulnerability with overall LVI value -4.17 with 48% farmers falling in highly vulnerable category. There is also significant tradeoff between milk production and components of LVI. Thus our research will provide an important basis for policy makers to develop appropriate adaptation strategies for alarming situation and decision making for farmers to minimize the risk of dairy sector to climate variability.

Model selection bias and Freedman's paradox

USGS Publications Warehouse

Lukacs, P.M.; Burnham, K.P.; Anderson, D.R.

2010-01-01

In situations where limited knowledge of a system exists and the ratio of data points to variables is small, variable selection methods can often be misleading. Freedman (Am Stat 37:152-155, 1983) demonstrated how common it is to select completely unrelated variables as highly "significant" when the number of data points is similar in magnitude to the number of variables. A new type of model averaging estimator based on model selection with Akaike's AIC is used with linear regression to investigate the problems of likely inclusion of spurious effects and model selection bias, the bias introduced while using the data to select a single seemingly "best" model from a (often large) set of models employing many predictor variables. The new model averaging estimator helps reduce these problems and provides confidence interval coverage at the nominal level while traditional stepwise selection has poor inferential properties. ?? The Institute of Statistical Mathematics, Tokyo 2009.

Family Caregivers of Liver Transplant Recipients: Coping Strategies Associated With Different Levels of Post-traumatic Growth.

PubMed

Pérez-San-Gregorio, M Á; Martín-Rodríguez, A; Borda-Mas, M; Avargues-Navarro, M L; Pérez-Bernal, J; Gómez-Bravo, M Á

2018-03-01

Analyze the influence of 2 variables (post-traumatic growth and time since liver transplantation) on coping strategies used by the transplant recipient's family members. In all, 218 family members who were their main caregivers of liver transplant recipients were selected. They were evaluated using the Posttraumatic Growth Inventory and the Brief COPE. A 3 × 3 factorial analysis of variance was used to analyze the influence that post-traumatic growth level (low, medium, and high) and time since transplantation (≤3.5 years, >3.5 to ≤9 years, and >9 years) exerted on caregiver coping strategies. No interactive effects between the two factors in the study were found. The only significant main effect was the influence of the post-traumatic growth factor on the following variables: instrumental support (P = .007), emotional support (P = .005), self-distraction (P = .006), positive reframing (P = .000), acceptance (P = .013), and religion (P = <.001). According to the most relevant effect sizes, low post-traumatic growth compared with medium growth was associated with less use of self-distraction (P = .006, d = -0.52, medium effect size), positive reframing (P = .001, d = -0.62, medium effect size), and religion (P = .000, d = -0.66, medium effect size), and in comparison with high growth, it was associated with less use of positive reframing (P = .002, d = -0.56, medium effect size) and religion (P = .000, d = 0.87, large effect size). Regardless of the time elapsed since the stressful life event (liver transplantation), family members with low post-traumatic growth usually use fewer coping strategies involving a positive, transcendent vision to deal with transplantation. Copyright © 2017 Elsevier Inc. All rights reserved.

Postcopulatory sexual selection influences baculum evolution in primates and carnivores.

PubMed

Brindle, Matilda; Opie, Christopher

2016-12-14

The extreme morphological variability of the baculum across mammals is thought to be the result of sexual selection (particularly, high levels of postcopulatory selection). However, the evolutionary trajectory of the mammalian baculum is little studied and evidence for the adaptive function of the baculum has so far been elusive. Here, we use Markov chain Monte Carlo methods implemented in a Bayesian phylogenetic framework to reconstruct baculum evolution across the mammalian class and investigate the rate of baculum length evolution within the primate order. We then test the effects of testes mass (postcopulatory sexual selection), polygamy, seasonal breeding and intromission duration on the baculum in primates and carnivores. The ancestral mammal did not have a baculum, but both ancestral primates and carnivores did. No relationship was found between testes mass and baculum length in either primates or carnivores. Intromission duration correlated with baculum presence over the course of primate evolution, and prolonged intromission predicts significantly longer bacula in extant primates and carnivores. Both polygamous and seasonal breeding systems predict significantly longer bacula in primates. These results suggest the baculum plays an important role in facilitating reproductive strategies in populations with high levels of postcopulatory sexual selection. © 2016 The Authors.

Postcopulatory sexual selection influences baculum evolution in primates and carnivores

PubMed Central

Brindle, Matilda

2016-01-01

The extreme morphological variability of the baculum across mammals is thought to be the result of sexual selection (particularly, high levels of postcopulatory selection). However, the evolutionary trajectory of the mammalian baculum is little studied and evidence for the adaptive function of the baculum has so far been elusive. Here, we use Markov chain Monte Carlo methods implemented in a Bayesian phylogenetic framework to reconstruct baculum evolution across the mammalian class and investigate the rate of baculum length evolution within the primate order. We then test the effects of testes mass (postcopulatory sexual selection), polygamy, seasonal breeding and intromission duration on the baculum in primates and carnivores. The ancestral mammal did not have a baculum, but both ancestral primates and carnivores did. No relationship was found between testes mass and baculum length in either primates or carnivores. Intromission duration correlated with baculum presence over the course of primate evolution, and prolonged intromission predicts significantly longer bacula in extant primates and carnivores. Both polygamous and seasonal breeding systems predict significantly longer bacula in primates. These results suggest the baculum plays an important role in facilitating reproductive strategies in populations with high levels of postcopulatory sexual selection. PMID:27974519

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.

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.

An Investigation of Individual Variability in Brain Activity During Episodic Encoding and Retrieval

DTIC Science & Technology

2008-12-01

variability in mnemonic strategy use is, at least in part, related to the extensive variability observed in brain activity patterns. While a number of...1 AN INVESTIGATION OF INDIVIDUAL VARIABILITY IN BRAIN ACTIVITY DURING EPISODIC ENCODING AND RETRIEVAL C.L. Donovan*, and M.B. Miller Department of...strategy measures for predicting differences in brain activity patterns during a learning and memory task and to compare their predictive value to other

Lateral trunk lean and medializing the knee as gait strategies for knee osteoarthritis.

PubMed

Gerbrands, T A; Pisters, M F; Theeven, P J R; Verschueren, S; Vanwanseele, B

2017-01-01

To determine (1) if Medial Thrust or Trunk Lean reduces the knee adduction moment (EKAM) the most during gait in patients with medial knee osteoarthritis, (2) if the best overall strategy is the most effective for each patient and (3) if these strategies affect ankle and hip kinetics. Thirty patients with symptomatic medial knee osteoarthritis underwent 3-dimensional gait analysis. Participants received verbal instructions on two gait strategies (Trunk Lean and Medial Thrust) in randomized order after comfortable walking was recorded. The peaks and impulse of the EKAM and strategy-specific kinematic and kinetic variables were calculated for all conditions. Early stance EKAM peak was significantly reduced during Medial Thrust (-29%). During Trunk Lean, early and late stance EKAM peak and EKAM impulse reduced significantly (38%, 21% and -25%, respectively). In 79% of the subjects, the Trunk Lean condition was significantly more effective in reducing EKAM peak than Medial Thrust. Peak ankle dorsi and plantar flexion, knee flexion and hip extension and adduction moments were not significantly increased. Medial Thrust and Trunk Lean reduced the EKAM during gait in patients with knee osteoarthritis. Individual selection of the most effective gait modification strategy seems vital to optimally reduce dynamic knee loading during gait. No detrimental effects on external ankle and hip moments or knee flexion moments were found for these conditions. Copyright © 2016 Elsevier B.V. All rights reserved.

Individual differences in spatial relation processing: effects of strategy, ability, and gender

PubMed Central

van der Ham, Ineke J. M.; Borst, Gregoire

2011-01-01

Numerous studies have focused on the distinction between categorical and coordinate spatial relations. Categorical relations are propositional and abstract, and often related to a left hemisphere advantage. Coordinate relations specify the metric information of the relative locations of objects, and can be linked to right hemisphere processing. Yet, not all studies have reported such a clear double dissociation; in particular the categorical left hemisphere advantage is not always reported. In the current study we investigated whether verbal and spatial strategies, verbal and spatial cognitive abilities, and gender could account for the discrepancies observed in hemispheric lateralization of spatial relations. Seventy-five participants performed two visual half field, match-to-sample tasks (Van der Ham et al., 2007; 2009) to study the lateralization of categorical and coordinate relation processing. For each participant we determined the strategy they used in each of the two tasks. Consistent with previous findings, we found an overall categorical left hemisphere advantage and coordinate right hemisphere advantage. The lateralization pattern was affected selectively by the degree to which participants used a spatial strategy and by none of the other variables (i.e., verbal strategy, cognitive abilities, and gender). Critically, the categorical left hemisphere advantage was observed only for participants that relied strongly on a spatial strategy. This result is another piece of evidence that categorical spatial relation processing relies on spatial and not verbal processes. PMID:21353361

Language Learning Strategies, Course Grades, and Age in EFL Secondary School Learners

ERIC Educational Resources Information Center

Tragant, Elsa; Victori, Mia

2012-01-01

In studies dealing with language learning strategies in the school context, the variables of proficiency and age are often difficult to isolate since students accumulate more hours of foreign language instruction as they move up from grade to grade. This study aimed to deal with these two variables independently by analysing learning strategy use…

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.

A GPU-Based Implementation of the Firefly Algorithm for Variable Selection in Multivariate Calibration Problems

PubMed Central

de Paula, Lauro C. M.; Soares, Anderson S.; de Lima, Telma W.; Delbem, Alexandre C. B.; Coelho, Clarimar J.; Filho, Arlindo R. G.

2014-01-01

Several variable selection algorithms in multivariate calibration can be accelerated using Graphics Processing Units (GPU). Among these algorithms, the Firefly Algorithm (FA) is a recent proposed metaheuristic that may be used for variable selection. This paper presents a GPU-based FA (FA-MLR) with multiobjective formulation for variable selection in multivariate calibration problems and compares it with some traditional sequential algorithms in the literature. The advantage of the proposed implementation is demonstrated in an example involving a relatively large number of variables. The results showed that the FA-MLR, in comparison with the traditional algorithms is a more suitable choice and a relevant contribution for the variable selection problem. Additionally, the results also demonstrated that the FA-MLR performed in a GPU can be five times faster than its sequential implementation. PMID:25493625

A GPU-Based Implementation of the Firefly Algorithm for Variable Selection in Multivariate Calibration Problems.

PubMed

de Paula, Lauro C M; Soares, Anderson S; de Lima, Telma W; Delbem, Alexandre C B; Coelho, Clarimar J; Filho, Arlindo R G

2014-01-01

Several variable selection algorithms in multivariate calibration can be accelerated using Graphics Processing Units (GPU). Among these algorithms, the Firefly Algorithm (FA) is a recent proposed metaheuristic that may be used for variable selection. This paper presents a GPU-based FA (FA-MLR) with multiobjective formulation for variable selection in multivariate calibration problems and compares it with some traditional sequential algorithms in the literature. The advantage of the proposed implementation is demonstrated in an example involving a relatively large number of variables. The results showed that the FA-MLR, in comparison with the traditional algorithms is a more suitable choice and a relevant contribution for the variable selection problem. Additionally, the results also demonstrated that the FA-MLR performed in a GPU can be five times faster than its sequential implementation.

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.

Sex differences in a landmark environmental re-orientation task only during the learning phase.

PubMed

Piccardi, Laura; Bianchini, Filippo; Iasevoli, Luigi; Giannone, Gianluca; Guariglia, Cecilia

2011-10-10

Sex differences are consistently reported in human navigation. Indeed, to orient themselves during navigation women are more likely to use landmark-based strategies and men Euclidean-based strategies. The difference could be due to selective social pressure, which fosters greater spatial ability in men, or biological factors. And the great variability of the results reported in the literature could be due to the experimental setting more than real differences in ability. In this study, navigational behaviour was assessed by means of a place-learning task in which a modified version of the Morris water maze for humans was used to evaluate sex differences. In using landmarks, sex differences emerged only during the learning phase. Although the men were faster than the women in locating the target position, the differences between the sexes disappeared in delayed recall. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

From Physics Model to Results: An Optimizing Framework for Cross-Architecture Code Generation

DOE PAGES

Blazewicz, Marek; Hinder, Ian; Koppelman, David M.; ...

2013-01-01

Starting from a high-level problem description in terms of partial differential equations using abstract tensor notation, the Chemora framework discretizes, optimizes, and generates complete high performance codes for a wide range of compute architectures. Chemora extends the capabilities of Cactus, facilitating the usage of large-scale CPU/GPU systems in an efficient manner for complex applications, without low-level code tuning. Chemora achieves parallelism through MPI and multi-threading, combining OpenMP and CUDA. Optimizations include high-level code transformations, efficient loop traversal strategies, dynamically selected data and instruction cache usage strategies, and JIT compilation of GPU code tailored to the problem characteristics. The discretization ismore » based on higher-order finite differences on multi-block domains. Chemora's capabilities are demonstrated by simulations of black hole collisions. This problem provides an acid test of the framework, as the Einstein equations contain hundreds of variables and thousands of terms.« less

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.

Systematic design for trait introgression projects.

PubMed

Cameron, John N; Han, Ye; Wang, Lizhi; Beavis, William D

2017-10-01

Using an Operations Research approach, we demonstrate design of optimal trait introgression projects with respect to competing objectives. We demonstrate an innovative approach for designing Trait Introgression (TI) projects based on optimization principles from Operations Research. If the designs of TI projects are based on clear and measurable objectives, they can be translated into mathematical models with decision variables and constraints that can be translated into Pareto optimality plots associated with any arbitrary selection strategy. The Pareto plots can be used to make rational decisions concerning the trade-offs between maximizing the probability of success while minimizing costs and time. The systematic rigor associated with a cost, time and probability of success (CTP) framework is well suited to designing TI projects that require dynamic decision making. The CTP framework also revealed that previously identified 'best' strategies can be improved to be at least twice as effective without increasing time or expenses.

Selection Practices of Group Leaders: A National Survey.

ERIC Educational Resources Information Center

Riva, Maria T.; Lippert, Laurel; Tackett, M. Jan

2000-01-01

Study surveys the selection practices of group leaders. Explores methods of selection, variables used to make selection decisions, and the types of selection errors that leaders have experienced. Results suggest that group leaders use clinical judgment to make selection decisions and endorse using some specific variables in selection. (Contains 22…

A system dynamics approach to analyze laboratory test errors.

PubMed

Guo, Shijing; Roudsari, Abdul; Garcez, Artur d'Avila

2015-01-01

Although many researches have been carried out to analyze laboratory test errors during the last decade, it still lacks a systemic view of study, especially to trace errors during test process and evaluate potential interventions. This study implements system dynamics modeling into laboratory errors to trace the laboratory error flows and to simulate the system behaviors while changing internal variable values. The change of the variables may reflect a change in demand or a proposed intervention. A review of literature on laboratory test errors was given and provided as the main data source for the system dynamics model. Three "what if" scenarios were selected for testing the model. System behaviors were observed and compared under different scenarios over a period of time. The results suggest system dynamics modeling has potential effectiveness of helping to understand laboratory errors, observe model behaviours, and provide a risk-free simulation experiments for possible strategies.

Research on the effects of geometrical and material uncertainties on the band gap of the undulated beam

NASA Astrophysics Data System (ADS)

Li, Yi; Xu, Yanlong

2017-09-01

Considering uncertain geometrical and material parameters, the lower and upper bounds of the band gap of an undulated beam with periodically arched shape are studied by the Monte Carlo Simulation (MCS) and interval analysis based on the Taylor series. Given the random variations of the overall uncertain variables, scatter plots from the MCS are used to analyze the qualitative sensitivities of the band gap respect to these uncertainties. We find that the influence of uncertainty of the geometrical parameter on the band gap of the undulated beam is stronger than that of the material parameter. And this conclusion is also proved by the interval analysis based on the Taylor series. Our methodology can give a strategy to reduce the errors between the design and practical values of the band gaps by improving the accuracy of the specially selected uncertain design variables of the periodical structures.

Stress appraisal, coping, and work engagement among police recruits: an exploratory study.

PubMed

Kaiseler, Mariana; Queirós, Cristina; Passos, Fernando; Sousa, Pedro

2014-04-01

This study investigated the influence of stress appraisal and coping on work engagement levels (Absorption, Vigour, and Dedication) of police recruits. Participants were 387 men, ages 20 to 33 yr. (M = 24.1, SD = 2.4), in their last month of academy training before becoming police officers. Partially in support of predictions, work engagement was associated with Stressor control perceived, but not Stress intensity experienced over a self-selected stressor. Although the three dimensions of work engagement were explained by Stressor control and coping, Absorption was the dimension better explained by these variables. Police recruits reporting higher Absorption, Vigour, and Dedication reported using more Active coping and less Behavioural disengagement. Results showed that stress appraisal and coping are important variables influencing work engagement among police recruits. Findings suggested that future applied interventions fostering work engagement among police recruits should reinforce perceptions of control over a stressor as well as Active coping strategies.

Quality Assurance in the Presence of Variability

NASA Astrophysics Data System (ADS)

Lauenroth, Kim; Metzger, Andreas; Pohl, Klaus

Software Product Line Engineering (SPLE) is a reuse-driven development paradigm that has been applied successfully in information system engineering and other domains. Quality assurance of the reusable artifacts of the product line (e.g. requirements, design, and code artifacts) is essential for successful product line engineering. As those artifacts are reused in several products, a defect in a reusable artifact can affect several products of the product line. A central challenge for quality assurance in product line engineering is how to consider product line variability. Since the reusable artifacts contain variability, quality assurance techniques from single-system engineering cannot directly be applied to those artifacts. Therefore, different strategies and techniques have been developed for quality assurance in the presence of variability. In this chapter, we describe those strategies and discuss in more detail one of those strategies, the so called comprehensive strategy. The comprehensive strategy aims at checking the quality of all possible products of the product line and thus offers the highest benefits, since it is able to uncover defects in all possible products of the product line. However, the central challenge for applying the comprehensive strategy is the complexity that results from the product line variability and the large number of potential products of a product line. In this chapter, we present one concrete technique that we have developed to implement the comprehensive strategy that addresses this challenge. The technique is based on model checking technology and allows for a comprehensive verification of domain artifacts against temporal logic properties.

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.

New bandwidth selection criterion for Kernel PCA: approach to dimensionality reduction and classification problems.

PubMed

Thomas, Minta; De Brabanter, Kris; De Moor, Bart

2014-05-10

DNA microarrays are potentially powerful technology for improving diagnostic classification, treatment selection, and prognostic assessment. The use of this technology to predict cancer outcome has a history of almost a decade. Disease class predictors can be designed for known disease cases and provide diagnostic confirmation or clarify abnormal cases. The main input to this class predictors are high dimensional data with many variables and few observations. Dimensionality reduction of these features set significantly speeds up the prediction task. Feature selection and feature transformation methods are well known preprocessing steps in the field of bioinformatics. Several prediction tools are available based on these techniques. Studies show that a well tuned Kernel PCA (KPCA) is an efficient preprocessing step for dimensionality reduction, but the available bandwidth selection method for KPCA was computationally expensive. In this paper, we propose a new data-driven bandwidth selection criterion for KPCA, which is related to least squares cross-validation for kernel density estimation. We propose a new prediction model with a well tuned KPCA and Least Squares Support Vector Machine (LS-SVM). We estimate the accuracy of the newly proposed model based on 9 case studies. Then, we compare its performances (in terms of test set Area Under the ROC Curve (AUC) and computational time) with other well known techniques such as whole data set + LS-SVM, PCA + LS-SVM, t-test + LS-SVM, Prediction Analysis of Microarrays (PAM) and Least Absolute Shrinkage and Selection Operator (Lasso). Finally, we assess the performance of the proposed strategy with an existing KPCA parameter tuning algorithm by means of two additional case studies. We propose, evaluate, and compare several mathematical/statistical techniques, which apply feature transformation/selection for subsequent classification, and consider its application in medical diagnostics. Both feature selection and feature transformation perform well on classification tasks. Due to the dynamic selection property of feature selection, it is hard to define significant features for the classifier, which predicts classes of future samples. Moreover, the proposed strategy enjoys a distinctive advantage with its relatively lesser time complexity.

Unbiased split variable selection for random survival forests using maximally selected rank statistics.

PubMed

Wright, Marvin N; Dankowski, Theresa; Ziegler, Andreas

2017-04-15

The most popular approach for analyzing survival data is the Cox regression model. The Cox model may, however, be misspecified, and its proportionality assumption may not always be fulfilled. An alternative approach for survival prediction is random forests for survival outcomes. The standard split criterion for random survival forests is the log-rank test statistic, which favors splitting variables with many possible split points. Conditional inference forests avoid this split variable selection bias. However, linear rank statistics are utilized by default in conditional inference forests to select the optimal splitting variable, which cannot detect non-linear effects in the independent variables. An alternative is to use maximally selected rank statistics for the split point selection. As in conditional inference forests, splitting variables are compared on the p-value scale. However, instead of the conditional Monte-Carlo approach used in conditional inference forests, p-value approximations are employed. We describe several p-value approximations and the implementation of the proposed random forest approach. A simulation study demonstrates that unbiased split variable selection is possible. However, there is a trade-off between unbiased split variable selection and runtime. In benchmark studies of prediction performance on simulated and real datasets, the new method performs better than random survival forests if informative dichotomous variables are combined with uninformative variables with more categories and better than conditional inference forests if non-linear covariate effects are included. In a runtime comparison, the method proves to be computationally faster than both alternatives, if a simple p-value approximation is used. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

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.

Pedagogical approaches, contextual variables, and the development of student self-efficacy in undergraduate physics courses

NASA Astrophysics Data System (ADS)

Fencl, Heidi S.; Scheel, Karen R.

2004-09-01

Self-efficacy, or a person's situation-specific belief that s/he can succeed in a given task, has been successful in a variety of educational studies for predicting behaviors such as perseverance and success (grades), and for understanding which behaviors are attempted or avoided. The focus of this study was to examine if classroom factors such as teaching strategies and classroom climate contribute to students' physics self-efficacy. 121 undergraduates in first semester, calculus-based introductory physics courses completed surveys assessing course experiences, self-efficacy and other outcome variables, and demographic information. Students in sections including a mix of teaching strategies did significantly better than students in the traditional section on outcome variables including self-efficacy. When individual strategies were examined, the strongest relationships were found between cooperative learning strategies and all sources of self-efficacy, and between climate variables and all sources of efficacy.

A Systematic Review of the Effect of Cognitive Strategies on Strength Performance.

PubMed

Tod, David; Edwards, Christian; McGuigan, Mike; Lovell, Geoff

2015-11-01

Researchers have tested the beliefs of sportspeople and sports medicine specialists that cognitive strategies influence strength performance. Few investigators have synthesised the literature. The specific objectives were to review evidence regarding (a) the cognitive strategy-strength performance relationship; (b) participant skill level as a moderator; and (c) cognitive, motivational, biomechanical/physiological, and emotional mediators. Studies were sourced via electronic databases, reference lists of retrieved articles, and manual searches of relevant journals. Studies had to be randomised or counterbalanced experiments with a control group or condition, repeated measures, and a quality control score above 0.5 (out of 1). Cognitive strategies included goal setting, imagery, self-talk, preparatory arousal, and free choice. Dependent variables included maximal strength, local muscular endurance, or muscular power. Globally, cognitive strategies were reliability associated with increased strength performance (results ranged from 61 to 65 %). Results were mixed when examining the effects of specific strategies on particular dependent variables, although no intervention had an overall negative influence. Indeterminate relationships emerged regarding hypothesised mediators (except cognitive variables) and participant skill level as a moderator. Although cognitive strategies influence strength performance, there are knowledge gaps regarding specific types of strength, especially muscular power. Cognitive variables, such as concentration, show promise as possible mediators.

CORRELATION PURSUIT: FORWARD STEPWISE VARIABLE SELECTION FOR INDEX MODELS

PubMed Central

Zhong, Wenxuan; Zhang, Tingting; Zhu, Yu; Liu, Jun S.

2012-01-01

In this article, a stepwise procedure, correlation pursuit (COP), is developed for variable selection under the sufficient dimension reduction framework, in which the response variable Y is influenced by the predictors X1, X2, …, Xp through an unknown function of a few linear combinations of them. Unlike linear stepwise regression, COP does not impose a special form of relationship (such as linear) between the response variable and the predictor variables. The COP procedure selects variables that attain the maximum correlation between the transformed response and the linear combination of the variables. Various asymptotic properties of the COP procedure are established, and in particular, its variable selection performance under diverging number of predictors and sample size has been investigated. The excellent empirical performance of the COP procedure in comparison with existing methods are demonstrated by both extensive simulation studies and a real example in functional genomics. PMID:23243388

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.

Input variable selection and calibration data selection for storm water quality regression models.

PubMed

Sun, Siao; Bertrand-Krajewski, Jean-Luc

2013-01-01

Storm water quality models are useful tools in storm water management. Interest has been growing in analyzing existing data for developing models for urban storm water quality evaluations. It is important to select appropriate model inputs when many candidate explanatory variables are available. Model calibration and verification are essential steps in any storm water quality modeling. This study investigates input variable selection and calibration data selection in storm water quality regression models. The two selection problems are mutually interacted. A procedure is developed in order to fulfil the two selection tasks in order. The procedure firstly selects model input variables using a cross validation method. An appropriate number of variables are identified as model inputs to ensure that a model is neither overfitted nor underfitted. Based on the model input selection results, calibration data selection is studied. Uncertainty of model performances due to calibration data selection is investigated with a random selection method. An approach using the cluster method is applied in order to enhance model calibration practice based on the principle of selecting representative data for calibration. The comparison between results from the cluster selection method and random selection shows that the former can significantly improve performances of calibrated models. It is found that the information content in calibration data is important in addition to the size of calibration data.

Group Variable Selection Via Convex Log-Exp-Sum Penalty with Application to a Breast Cancer Survivor Study

PubMed Central

Geng, Zhigeng; Wang, Sijian; Yu, Menggang; Monahan, Patrick O.; Champion, Victoria; Wahba, Grace

2017-01-01

Summary In many scientific and engineering applications, covariates are naturally grouped. When the group structures are available among covariates, people are usually interested in identifying both important groups and important variables within the selected groups. Among existing successful group variable selection methods, some methods fail to conduct the within group selection. Some methods are able to conduct both group and within group selection, but the corresponding objective functions are non-convex. Such a non-convexity may require extra numerical effort. In this article, we propose a novel Log-Exp-Sum(LES) penalty for group variable selection. The LES penalty is strictly convex. It can identify important groups as well as select important variables within the group. We develop an efficient group-level coordinate descent algorithm to fit the model. We also derive non-asymptotic error bounds and asymptotic group selection consistency for our method in the high-dimensional setting where the number of covariates can be much larger than the sample size. Numerical results demonstrate the good performance of our method in both variable selection and prediction. We applied the proposed method to an American Cancer Society breast cancer survivor dataset. The findings are clinically meaningful and may help design intervention programs to improve the qualify of life for breast cancer survivors. PMID:25257196

Choosing a Surgeon: An Exploratory Study of Factors Influencing Selection of a Gender Affirmation Surgeon.

PubMed

Ettner, Randi; Ettner, Frederic; White, Tonya

2016-01-01

Purpose: Selecting a healthcare provider is often a complicated process. Many factors appear to govern the decision as to how to select the provider in the patient-provider relationship. While the possibility of changing primary care physicians or specialists exists, decisions regarding surgeons are immutable once surgery has been performed. This study is an attempt to assess the importance attached to various factors involved in selecting a surgeon to perform gender affirmation surgery (GAS). It was hypothesized that owing to the intimate nature of the surgery, the expense typically involved, the emotional meaning attached to the surgery, and other variables, decisions regarding choice of surgeon for this procedure would involve factors other than those that inform more typical healthcare provider selection or surgeon selection for other plastic/reconstructive procedures. Methods: Questionnaires were distributed to individuals who had undergone GAS and individuals who had undergone elective plastic surgery to assess decision-making. Results: The results generally confirm previous findings regarding how patients select providers. Conclusion: Choosing a surgeon to perform gender-affirming surgery is a challenging process, but patients are quite rational in their decision-making. Unlike prior studies, we did not find a preference for gender-concordant surgeons, even though the surgery involves the genital area. Providing strategies and resources for surgical selection can improve patient satisfaction.

Movement Variability Increases With Shoulder Pain When Compensatory Strategies of the Upper Body Are Constrained.

PubMed

López-Pascual, Juan; Page, Álvaro; Serra-Añó, Pilar

2017-10-13

This cross-sectional study analyzed the influence of chronic shoulder pain (CSP) on movement variability/kinematics during humeral elevation, with the trunk and elbow motions constrained to avoid compensatory strategies. For this purpose, 37 volunteers with CSP as the injured group (IG) and 58 participants with asymptomatic shoulders as the control group (CG) participated in the study. Maximum humeral elevation (Emax), maximum angular velocity (Velmax), variability of the maximum angle (CVEmax), functional variability (Func_var), and approximate entropy (ApEn) were calculated from the kinematic data. Patients' pain was measured on the visual analogue scale (VAS). Compared with the CG, the IG presented lower Emax and Velmax and higher variability (i.e., CVEmax, Func_var, and ApEn). Moderate correlations were achieved for the VAS score and the kinematic variables Emax, Velmax and variability of curve analysis, Func_varm, and ApEn. No significant correlation was found for CVEmax. In conclusion, CSP results in a decrease of angle and velocity and an increased shoulder movement variability when the neuromuscular system cannot use compensatory strategies to avoid painful positions.

Comparing demographic, health status and psychosocial strategies of audience segmentation to promote physical activity.

PubMed

Boslaugh, Sarah E; Kreuter, Matthew W; Nicholson, Robert A; Naleid, Kimberly

2005-08-01

The goal of audience segmentation is to identify population subgroups that are homogeneous with respect to certain variables associated with a given outcome or behavior. When such groups are identified and understood, targeted intervention strategies can be developed to address their unique characteristics and needs. This study compares the results of audience segmentation for physical activity that is based on either demographic, health status or psychosocial variables alone, or a combination of all three types of variables. Participants were 1090 African-American and White adults from two public health centers in St Louis, MO. Using a classification-tree algorithm to form homogeneous groups, analyses showed that more segments with greater variability in physical activity were created using psychosocial versus health status or demographic variables and that a combination of the three outperformed any individual set of variables. Simple segmentation strategies such as those relying on demographic variables alone provided little improvement over no segmentation at all. Audience segmentation appears to yield more homogeneous subgroups when psychosocial and health status factors are combined with demographic variables.

Interventions to prevent overweight in children.

PubMed

Müller, M J; Danielzik, S; Landsberg, B; Pust, S

2006-07-01

There are only few controlled studies on prevention of overweight in children and adolescence. These studies differ with respect to strategy, setting, duration, focus, variables of outcome and statistical power. Universal and school-based interventions show some improvement of health knowledge and health-related behaviours but they have only minor or no effects on nutritional status. However they reduce the incidence of overweight. The effects seem to be more pronounced in girls than in boys. Children of middle and high class as well as children with intact families benefit better from intervention than children with low socioeconomic status. Selected prevention in overweight children was most successful when children were treated together with their parents. However there are social barriers limiting the success. Simple interventions in a single area are unlikely to work on their own. The development of effective preventive interventions likely require strategies that affect multiple settings simultaneously. At present there is no concerted action but many strategies are followed in isolation. There is need for national campaigns and action plans on childhood overweight and obesity. It is tempting to speculate that this will also increase the effects of isolated approaches.

Strategic planning in Brazilian protected areas: Uses and adjustments.

PubMed

Barreto, Cristiane Gomes; Drummond, José Augusto L

2017-09-15

Management plans for protected areas commonly use strategic planning tools in their drafting. It is proposed that the adequate use of the instruments of planning and management of protected areas can improve their strategic competitiveness, providing greater financial and administrative independence, enabling them to be economically sustainable organizations. This study evaluated the application of concepts and strategy formulation, strategy principles and competitiveness, organizational diagnosis, strategic maps, scenarios, and other strategic planning instruments used for conservation management in Brazil. 25 management plans of 25 different protected areas were selected and studied, with special attention to the indicators used in each plan. Results indicate that there is a high suitability for the application of SP tools to the universe of protected areas, although management plans did not take full advantage of these tools. We also found that the broader use of these tools did not guarantee greater managerial effectiveness. We suggest that other governance variables beyond planning strategies must be improved, to ensure a better performance of protected areas. Copyright © 2017 Elsevier Ltd. All rights reserved.

Children's Acquisition and Use of the Control-of-Variables Strategy: Effects of Explicit and Implicit Instructional Guidance

ERIC Educational Resources Information Center

Lazonder, Ard W.; Egberink, Angelique

2014-01-01

Direct instruction is a proven effective method to strengthen children's ability to design unconfounded experiments using the control-of-variables strategy (CVS). Recent research suggests that task segmentation can also promote children's use of this strategy. The present study investigated this assumption by comparing the relative…

Variation of surface ozone in Campo Grande, Brazil: meteorological effect analysis and prediction.

PubMed

Pires, J C M; Souza, A; Pavão, H G; Martins, F G

2014-09-01

The effect of meteorological variables on surface ozone (O3) concentrations was analysed based on temporal variation of linear correlation and artificial neural network (ANN) models defined by genetic algorithms (GAs). ANN models were also used to predict the daily average concentration of this air pollutant in Campo Grande, Brazil. Three methodologies were applied using GAs, two of them considering threshold models. In these models, the variables selected to define different regimes were daily average O3 concentration, relative humidity and solar radiation. The threshold model that considers two O3 regimes was the one that correctly describes the effect of important meteorological variables in O3 behaviour, presenting also a good predictive performance. Solar radiation, relative humidity and rainfall were considered significant for both O3 regimes; however, wind speed (dispersion effect) was only significant for high concentrations. According to this model, high O3 concentrations corresponded to high solar radiation, low relative humidity and wind speed. This model showed to be a powerful tool to interpret the O3 behaviour, being useful to define policy strategies for human health protection regarding air pollution.

Weather conditions drive dynamic habitat selection in a generalist predator.

PubMed

Sunde, Peter; Thorup, Kasper; Jacobsen, Lars B; Rahbek, Carsten

2014-01-01

Despite the dynamic nature of habitat selection, temporal variation as arising from factors such as weather are rarely quantified in species-habitat relationships. We analysed habitat use and selection (use/availability) of foraging, radio-tagged little owls (Athene noctua), a nocturnal, year-round resident generalist predator, to see how this varied as a function of weather, season and availability. Use of the two most frequently used land cover types, gardens/buildings and cultivated fields varied more than 3-fold as a simple function of season and weather through linear effects of wind and quadratic effects of temperature. Even when controlling for the temporal context, both land cover types were used more evenly than predicted from variation in availability (functional response in habitat selection). Use of two other land cover categories (pastures and moist areas) increased linearly with temperature and was proportional to their availability. The study shows that habitat selection by generalist foragers may be highly dependent on temporal variables such as weather, probably because such foragers switch between weather dependent feeding opportunities offered by different land cover types. An opportunistic foraging strategy in a landscape with erratically appearing feeding opportunities in different land cover types, may possibly also explain decreasing selection of the two most frequently used land cover types with increasing availability.

Integrated QTL detection for key breeding traits in multiple peach progenies.

PubMed

Hernández Mora, José R; Micheletti, Diego; Bink, Marco; Van de Weg, Eric; Cantín, Celia; Nazzicari, Nelson; Caprera, Andrea; Dettori, Maria Teresa; Micali, Sabrina; Banchi, Elisa; Campoy, José Antonio; Dirlewanger, Elisabeth; Lambert, Patrick; Pascal, Thierry; Troggio, Michela; Bassi, Daniele; Rossini, Laura; Verde, Ignazio; Quilot-Turion, Bénédicte; Laurens, François; Arús, Pere; Aranzana, Maria José

2017-06-06

Peach (Prunus persica (L.) Batsch) is a major temperate fruit crop with an intense breeding activity. Breeding is facilitated by knowledge of the inheritance of the key traits that are often of a quantitative nature. QTLs have traditionally been studied using the phenotype of a single progeny (usually a full-sib progeny) and the correlation with a set of markers covering its genome. This approach has allowed the identification of various genes and QTLs but is limited by the small numbers of individuals used and by the narrow transect of the variability analyzed. In this article we propose the use of a multi-progeny mapping strategy that used pedigree information and Bayesian approaches that supports a more precise and complete survey of the available genetic variability. Seven key agronomic characters (data from 1 to 3 years) were analyzed in 18 progenies from crosses between occidental commercial genotypes and various exotic lines including accessions of other Prunus species. A total of 1467 plants from these progenies were genotyped with a 9 k SNP array. Forty-seven QTLs were identified, 22 coinciding with major genes and QTLs that have been consistently found in the same populations when studied individually and 25 were new. A substantial part of the QTLs observed (47%) would not have been detected in crosses between only commercial materials, showing the high value of exotic lines as a source of novel alleles for the commercial gene pool. Our strategy also provided estimations on the narrow sense heritability of each character, and the estimation of the QTL genotypes of each parent for the different QTLs and their breeding value. The integrated strategy used provides a broader and more accurate picture of the variability available for peach breeding with the identification of many new QTLs, information on the sources of the alleles of interest and the breeding values of the potential donors of such valuable alleles. These results are first-hand information for breeders and a step forward towards the implementation of DNA-informed strategies to facilitate selection of new cultivars with improved productivity and quality.

An Optimization Model For Strategy Decision Support to Select Kind of CPO’s Ship

NASA Astrophysics Data System (ADS)

Suaibah Nst, Siti; Nababan, Esther; Mawengkang, Herman

2018-01-01

The selection of marine transport for the distribution of crude palm oil (CPO) is one of strategy that can be considered in reducing cost of transport. The cost of CPO’s transport from one area to CPO’s factory located at the port of destination may affect the level of CPO’s prices and the number of demands. In order to maintain the availability of CPO a strategy is required to minimize the cost of transporting. In this study, the strategy used to select kind of charter ships as barge or chemical tanker. This study aims to determine an optimization model for strategy decision support in selecting kind of CPO’s ship by minimizing costs of transport. The select of ship was done randomly, so that two-stage stochastic programming model was used to select the kind of ship. Model can help decision makers to select either barge or chemical tanker to distribute CPO.

Therapeutic Misconception in Psychiatry Research: A Systematic Review.

PubMed

Thong, Ivan Sk; Foo, Meng Yee; Sum, Min Yi; Capps, Benjamin; Lee, Tih-Shih; Ho, Calvin; Sim, Kang

2016-02-29

Therapeutic misconception (TM) denotes the phenomenon in which research subjects conflate research purpose, protocols and procedures with clinical treatment. We examined the prevalence, contributory factors, clinical associations, impact, and collated solutions on TM within psychiatric research, and made suggestions going ahead. Literature search for relevant empirical research papers was conducted until February 2015. Eighty-eight reports were extracted, of which 31 were selected, summarised into different headings for discussion of implications and collated solutions of TM. We found variable and high rates of TM (ranging from 12.5% to 86%) in some psychiatry research populations. Contributory factors to TM included perceived medical roles of researchers, media, research setting and subject factors. Greater TM in affective, neurodevelopmental and psychotic spectrum conditions were associated with demographic variables (such as lower education, increased age), clinical factors (such as poor insight, cognitive deficits, increased symptoms, poorer self-rated quality of health), and social functioning (such as decreased independence). Inattention to TM may lead to frustration, negative impression and abandonment of participation in psychiatry research. Strategies such as the employment of a neutral educator during the informed consent process and education modules may be effective in addressing TM. Further research is warranted to examine the different TM facets, specific clinical correlates and more effective management strategies.

What should I do next? Using shared representations to solve interaction problems.

PubMed

Pezzulo, Giovanni; Dindo, Haris

2011-06-01

Studies on how "the social mind" works reveal that cognitive agents engaged in joint actions actively estimate and influence another's cognitive variables and form shared representations with them. (How) do shared representations enhance coordination? In this paper, we provide a probabilistic model of joint action that emphasizes how shared representations help solving interaction problems. We focus on two aspects of the model. First, we discuss how shared representations permit to coordinate at the level of cognitive variables (beliefs, intentions, and actions) and determine a coherent unfolding of action execution and predictive processes in the brains of two agents. Second, we discuss the importance of signaling actions as part of a strategy for sharing representations and the active guidance of another's actions toward the achievement of a joint goal. Furthermore, we present data from a human-computer experiment (the Tower Game) in which two agents (human and computer) have to build together a tower made of colored blocks, but only the human knows the constellation of the tower to be built (e.g., red-blue-red-blue-…). We report evidence that humans use signaling strategies that take another's uncertainty into consideration, and that in turn our model is able to use humans' actions as cues to "align" its representations and to select complementary actions.

On the selection of significant variables in a model for the deteriorating process of facades

NASA Astrophysics Data System (ADS)

Serrat, C.; Gibert, V.; Casas, J. R.; Rapinski, J.

2017-10-01

In previous works the authors of this paper have introduced a predictive system that uses survival analysis techniques for the study of time-to-failure in the facades of a building stock. The approach is population based, in order to obtain information on the evolution of the stock across time, and to help the manager in the decision making process on global maintenance strategies. For the decision making it is crutial to determine those covariates -like materials, morphology and characteristics of the facade, orientation or environmental conditions- that play a significative role in the progression of different failures. The proposed platform also incorporates an open source GIS plugin that includes survival and test moduli that allow the investigator to model the time until a lesion taking into account the variables collected during the inspection process. The aim of this paper is double: a) to shortly introduce the predictive system, as well as the inspection and the analysis methodologies and b) to introduce and illustrate the modeling strategy for the deteriorating process of an urban front. The illustration will be focused on the city of L’Hospitalet de Llobregat (Barcelona, Spain) in which more than 14,000 facades have been inspected and analyzed.

Isolation of a pH-Sensitive IgNAR Variable Domain from a Yeast-Displayed, Histidine-Doped Master Library.

PubMed

Könning, Doreen; Zielonka, Stefan; Sellmann, Carolin; Schröter, Christian; Grzeschik, Julius; Becker, Stefan; Kolmar, Harald

2016-04-01

In recent years, engineering of pH-sensitivity into antibodies as well as antibody-derived fragments has become more and more attractive for biomedical and biotechnological applications. Herein, we report the isolation of the first pH-sensitive IgNAR variable domain (vNAR), which was isolated from a yeast-displayed, semi-synthetic master library. This strategy enables the direct identification of pH-dependent binders from a histidine-enriched CDR3 library. Displayed vNAR variants contained two histidine substitutions on average at random positions in their 12-residue CDR3 loop. Upon screening of seven rounds against the proof-of-concept target EpCAM (selection for binding at pH 7.4 and decreased binding at pH 6.0), a single clone was obtained that showed specific and pH-dependent binding as characterized by yeast surface display and biolayer interferometry. Potential applications for such pH-dependent vNAR domains include their employment in tailored affinity chromatography, enabling mild elution protocols. Moreover, utilizing a master library for the isolation of pH-sensitive vNAR variants may be a generic strategy to obtain binding entities with prescribed characteristics for applications in biotechnology, diagnostics, and therapy.

An evaluation of unsupervised and supervised learning algorithms for clustering landscape types in the United States

USGS Publications Warehouse

Wendel, Jochen; Buttenfield, Barbara P.; Stanislawski, Larry V.

2016-01-01

Knowledge of landscape type can inform cartographic generalization of hydrographic features, because landscape characteristics provide an important geographic context that affects variation in channel geometry, flow pattern, and network configuration. Landscape types are characterized by expansive spatial gradients, lacking abrupt changes between adjacent classes; and as having a limited number of outliers that might confound classification. The US Geological Survey (USGS) is exploring methods to automate generalization of features in the National Hydrography Data set (NHD), to associate specific sequences of processing operations and parameters with specific landscape characteristics, thus obviating manual selection of a unique processing strategy for every NHD watershed unit. A chronology of methods to delineate physiographic regions for the United States is described, including a recent maximum likelihood classification based on seven input variables. This research compares unsupervised and supervised algorithms applied to these seven input variables, to evaluate and possibly refine the recent classification. Evaluation metrics for unsupervised methods include the Davies–Bouldin index, the Silhouette index, and the Dunn index as well as quantization and topographic error metrics. Cross validation and misclassification rate analysis are used to evaluate supervised classification methods. The paper reports the comparative analysis and its impact on the selection of landscape regions. The compared solutions show problems in areas of high landscape diversity. There is some indication that additional input variables, additional classes, or more sophisticated methods can refine the existing classification.

Prevalence of photoprotection and its associated factors in risk group for skin cancer in Teresina, Piauí*

PubMed Central

Cardoso, Fernanda Ayres de Morais e Silva; Mesquita, Gerardo Vasconcelos; Campelo, Viriato; Martins, Maria do Carmo de Carvalho e; Almeida, Camila Aparecida Pinheiro Landim; Rabelo, Regina Silva; Rocha, Amanda Eugênia Almeida; dos Santos, Jadson Lener Oliveira

2017-01-01

Background The incidence of skin cancer has increased worldwide, particularly melanoma rates, which had a mean development of 2.6 % a year in the last 10 years. The agreement on the relation between long-term or chronic exposure to the sun and the emergence of these neoplasias has made several workers who perform activities exposed to solar radiation to form a risk group for the development of skin cancer, community health agents included. OBJECTIVES To analyze the prevalence of sunscreen-use-related factors to skin cancer in a labor risk group. METHODOLOGY Cross-sectional study with community health agents selected through simple random sampling. After collecting data using semi-structured interviews, a descriptive analysis was performed for the qualitative variables, bivariate analysis was employed for checking the association between sunscreen use and sociodemographic, occupational and knowledge about skin variables, and multivariate analysis was conducted to check independent variables associated to sunscreen use. A 5% significance level was used. Results Of 261 health gents selected, 243 were able to participate in the study. The prevalence rate of sunscreen use was 34.2% (95% CI: 28.2-40.2). Factors associated with sunscreen use were female sex, advanced age, use of sunscreen in situations when the skin got burnt, knowledge of the negative effects of the sun on the skin and skin cancer history. Conclusions The prevalence found reveals that there is a need for implementing educational strategies in health services regarding photoprotection. PMID:28538880

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…

Identification and association of relationships between selected personal and environmental factors and formal components of temperament and strategies of coping with stress in asthmatic patients.

PubMed

Panek, Michał; Pietras, Tadeusz; Witusik, Andrzej; Wieteska, Łukasz; Małachowska, Beata; Mokros, Łukasz; Fendler, Wojciech; Szemraj, Janusz; Kuna, Piotr

2015-10-01

Background: Personal and environmental factors might have an impact on strategies of coping with stress and temperamental traits according to the Regulative Theory of Temperament in asthmatic patients. They can modify the clinical picture, the course of a disease and effectiveness of treatment. Personal variables are key factors in determining formal characteristic of behavior and effective management method in asthmatic patients. Aim of study: The aim of the study was to identify selected personal and environmental factors, as well as factors inducing attacks and asthma exacerbations or maintaining them in a complex of personal traits of patients. Methods: Two hundred and eighty one participants were included in the study. Of this number 122 subjects were healthy volunteers and 159 were asthmatic patients. In all the subjects the authors applied the Formal Characteristic of Behaviour – FCZ-KT – Temperament Inventory, Coping Inventory for Stressful Situations (CISS), Beck Depression Inventory, State-Trait Anxiety Inventory and Borg Rating of Perceived Exertion (RPE) Scale. Genotyping of polymorphic forms of NR3C1 gene was conducted with PCR-RFLP and PCR-HRM methods. Expression of TGFβ1 gene was measured with the use of qRT-PCR. Results: The authors confirmed a significant influence of personal and environmental factors, such as: age, height, body weight, sex, asthma exacerbations, drugs administered by patients, allergy and psychopathological variables on strategies of coping with stress by asthmatic patients (Task-Oriented Coping, Emotion-Oriented Coping, Avoidance-Oriented Coping, distraction seeking, social diversion). Temperamental traits (Briskness, Perseverance, Sensory Sensitivity, Emotional Reactivity, Endurance, Activity) depend on age, sex, body weight, genetic predispositions and they are modified by asthma exacerbations, allergy, drugs administered by patients, depression and anxiety (state and trait). The authors confirmed a correlation between Tth111I polymorphic form of NR3C1 gene and perseverance (p= 0.0450). It was noted that an increase in the TGFβ1 expression level led to a decrease in the patients' emotional reactivity (p= 0.0212). Conclusions: Strategies of coping with stress and temperamental traits according to the Regulative Theory of Temperament in asthmatic patients are determined by personal and environmental factors.

Assessing risk based on uncertain avalanche activity patterns

NASA Astrophysics Data System (ADS)

Zeidler, Antonia; Fromm, Reinhard

2015-04-01

Avalanches may affect critical infrastructure and may cause great economic losses. The planning horizon of infrastructures, e.g. hydropower generation facilities, reaches well into the future. Based on the results of previous studies on the effect of changing meteorological parameters (precipitation, temperature) and the effect on avalanche activity we assume that there will be a change of the risk pattern in future. The decision makers need to understand what the future might bring to best formulate their mitigation strategies. Therefore, we explore a commercial risk software to calculate risk for the coming years that might help in decision processes. The software @risk, is known to many larger companies, and therefore we explore its capabilities to include avalanche risk simulations in order to guarantee a comparability of different risks. In a first step, we develop a model for a hydropower generation facility that reflects the problem of changing avalanche activity patterns in future by selecting relevant input parameters and assigning likely probability distributions. The uncertain input variables include the probability of avalanches affecting an object, the vulnerability of an object, the expected costs for repairing the object and the expected cost due to interruption. The crux is to find the distribution that best represents the input variables under changing meteorological conditions. Our focus is on including the uncertain probability of avalanches based on the analysis of past avalanche data and expert knowledge. In order to explore different likely outcomes we base the analysis on three different climate scenarios (likely, worst case, baseline). For some variables, it is possible to fit a distribution to historical data, whereas in cases where the past dataset is insufficient or not available the software allows to select from over 30 different distribution types. The Monte Carlo simulation uses the probability distribution of uncertain variables using all valid combinations of the values of input variables to simulate all possible outcomes. In our case the output is the expected risk (Euro/year) for each object (e.g. water intake) considered and the entire hydropower generation system. The output is again a distribution that is interpreted by the decision makers as the final strategy depends on the needs and requirements of the end-user, which may be driven by personal preferences. In this presentation, we will show a way on how we used the uncertain information on avalanche activity in future to subsequently use it in a commercial risk software and therefore bringing the knowledge of natural hazard experts to decision makers.

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

PubMed

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

2017-07-01

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

Robust check loss-based variable selection of high-dimensional single-index varying-coefficient model

NASA Astrophysics Data System (ADS)

Song, Yunquan; Lin, Lu; Jian, Ling

2016-07-01

Single-index varying-coefficient model is an important mathematical modeling method to model nonlinear phenomena in science and engineering. In this paper, we develop a variable selection method for high-dimensional single-index varying-coefficient models using a shrinkage idea. The proposed procedure can simultaneously select significant nonparametric components and parametric components. Under defined regularity conditions, with appropriate selection of tuning parameters, the consistency of the variable selection procedure and the oracle property of the estimators are established. Moreover, due to the robustness of the check loss function to outliers in the finite samples, our proposed variable selection method is more robust than the ones based on the least squares criterion. Finally, the method is illustrated with numerical simulations.

Flying with the winds: differential migration strategies in relation to winds in moth and songbirds.

PubMed

Åkesson, Susanne

2016-01-01

The gamma Y moth selects to migrate in stronger winds compared to songbirds, enabling fast transport to distant breeding sites, but a lower precision in orientation as the moth allows itself to be drifted by the winds. Photo: Ian Woiwod. In Focus: Chapman, J.R., Nilsson, C., Lim, K.S., Bäckman, J., Reynolds, D.R. & Alerstam, T. (2015) Adaptive strategies in nocturnally migrating insects and songbirds: contrasting responses to winds. Journal of Animal Ecology, In press Insects and songbirds regularly migrate long distances across continents and seas. During these nocturnal migrations, they are exposed to a fluid medium, the air, in which they transport themselves by flight at similar speeds as the winds may carry them. It is crucial for an animal to select the most favourable flight conditions relative to winds to minimize the distance flown on a given amount of fuel and to avoid hazardous situations. Chapman et al. (2015a) showed contrasting strategies in how moths initiate migration predominantly under tailwind conditions, allowing themselves to drift to a larger extent and gain ground speed as compared to nocturnal songbird migrants. The songbirds use more variable flight strategies in relation to winds, where they sometimes allow themselves to drift, and at other occasions compensate for wind drift. This study shows how insects and birds have differentially adapted to migration in relation to winds, which is strongly dependent on their own flight capability, with higher flexibility enabling fine-tuned responses to keep a time programme and reach a goal in songbirds compared to in insects. © 2015 The Author. Journal of Animal Ecology © 2015 British Ecological Society.

Coping Behavior of International Late Adolescent Students in Selected Australian Educational Institutions

PubMed Central

Shahrill, Masitah; Mundia, Lawrence

2014-01-01

Using the Adolescent Coping Scale, ACS (Frydenberg & Lewis, 1993) we surveyed 45 randomly selected foreign adolescents in Australian schools. The coping strategies used most by the participants were: focus on solving the problem; seeking relaxing diversions; focusing on the positive; seeking social support; worry; seeking to belong; investing in close friends; wishful thinking; and keep to self (Table 4). With regard to coping styles, the most widely used was the productive coping followed by non-productive coping while the least used style was reference to others (Table 4). In terms of both genders the four coping strategies used most often were: work hard to achieve; seeking relaxing diversions; focus on solving the problem; and focus on the positive (Table 5). The most noticeable gender difference was the use of the physical recreation coping strategy in which male students engaged more (Fig 1). The usage of four coping strategies (solving problem; work hard; focus on positive; and social support) was higher for students who have been away from family more than once as compared to those who have been away once only while the usage of seeking relaxing diversions was higher for the first timers (Table 6). No significant differences were obtained on the sample’s performance on the ACS subscales by gender (Table 7), frequency of leaving own country (Table 8), country of origin (Table 9), and length of stay in Australia (Table 11). However, foundation students scored significantly higher on the reference to others variable than their secondary school peers (Table 10). We recommended counseling for students with high support needs and further large-scale mixed-methods research to gain additional insights. PMID:24373267

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

[Application of characteristic NIR variables selection in portable detection of soluble solids content of apple by near infrared spectroscopy].

PubMed

Fan, Shu-Xiang; Huang, Wen-Qian; Li, Jiang-Bo; Guo, Zhi-Ming; Zhaq, Chun-Jiang

2014-10-01

In order to detect the soluble solids content(SSC)of apple conveniently and rapidly, a ring fiber probe and a portable spectrometer were applied to obtain the spectroscopy of apple. Different wavelength variable selection methods, including unin- formative variable elimination (UVE), competitive adaptive reweighted sampling (CARS) and genetic algorithm (GA) were pro- posed to select effective wavelength variables of the NIR spectroscopy of the SSC in apple based on PLS. The back interval LS- SVM (BiLS-SVM) and GA were used to select effective wavelength variables based on LS-SVM. Selected wavelength variables and full wavelength range were set as input variables of PLS model and LS-SVM model, respectively. The results indicated that PLS model built using GA-CARS on 50 characteristic variables selected from full-spectrum which had 1512 wavelengths achieved the optimal performance. The correlation coefficient (Rp) and root mean square error of prediction (RMSEP) for prediction sets were 0.962, 0.403°Brix respectively for SSC. The proposed method of GA-CARS could effectively simplify the portable detection model of SSC in apple based on near infrared spectroscopy and enhance the predictive precision. The study can provide a reference for the development of portable apple soluble solids content spectrometer.

Assessing the accuracy and stability of variable selection ...

EPA Pesticide Factsheets

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

An Improved Search Approach for Solving Non-Convex Mixed-Integer Non Linear Programming Problems

NASA Astrophysics Data System (ADS)

Sitopu, Joni Wilson; Mawengkang, Herman; Syafitri Lubis, Riri

2018-01-01

The nonlinear mathematical programming problem addressed in this paper has a structure characterized by a subset of variables restricted to assume discrete values, which are linear and separable from the continuous variables. The strategy of releasing nonbasic variables from their bounds, combined with the “active constraint” method, has been developed. This strategy is used to force the appropriate non-integer basic variables to move to their neighbourhood integer points. Successful implementation of these algorithms was achieved on various test problems.

Predictors of public support for nutrition-focused policy, systems and environmental change strategies in Los Angeles County, 2013

PubMed Central

Robles, Brenda; Kuo, Tony

2017-01-01

Background Since 2010, federal and local agencies have invested broadly in a variety of nutrition-focused policy, systems and environmental change (PSE) initiatives in Los Angeles County (LAC). To date, little is known about whether the public supports such efforts. We address this gap in the literature by examining predictors of support for a variety of PSEs. Methods Voters residing in LAC (n=1007) were randomly selected to participate in a cross-sectional telephone survey commissioned by the LAC Department of Public Health. The survey asked questions about attitudes towards the obesity epidemic, nutrition knowledge and behaviours, public opinions about changing business practices/government policies related to nutrition, and sociodemographics. A factor analysis informed outcome variable selection (ie, type of PSEs). Multivariable regression analyses were performed to examine predictors of public support. Predictors in the regression models included (primary regressor) community economic hardship; (control variables) political affiliation, sex, age, race and income; and (independent variables) perceptions about obesity, perceived health and weight status, frequency reading nutrition labels, ease of finding healthy and unhealthy foods, and food consumption behaviours (ie, fruit and vegetables, non-diet soda, fast-food and sit-down restaurant meals). Results 3 types of PSE outcome variables were identified: promotional/incentivising, limiting/restrictive and business practices. Community economic hardship was not found to be a significant predictor of public support for any of the 3 PSE types. However, Republican party affiliation, being female and perceiving obesity as a serious health problem were. Conclusions These findings have implications for public health practice and community planning in local health jurisdictions. PMID:28087545

Predictors of public support for nutrition-focused policy, systems and environmental change strategies in Los Angeles County, 2013.

PubMed

Robles, Brenda; Kuo, Tony

2017-01-13

Since 2010, federal and local agencies have invested broadly in a variety of nutrition-focused policy, systems and environmental change (PSE) initiatives in Los Angeles County (LAC). To date, little is known about whether the public supports such efforts. We address this gap in the literature by examining predictors of support for a variety of PSEs. Voters residing in LAC (n=1007) were randomly selected to participate in a cross-sectional telephone survey commissioned by the LAC Department of Public Health. The survey asked questions about attitudes towards the obesity epidemic, nutrition knowledge and behaviours, public opinions about changing business practices/government policies related to nutrition, and sociodemographics. A factor analysis informed outcome variable selection (ie, type of PSEs). Multivariable regression analyses were performed to examine predictors of public support. Predictors in the regression models included (primary regressor) community economic hardship; (control variables) political affiliation, sex, age, race and income; and (independent variables) perceptions about obesity, perceived health and weight status, frequency reading nutrition labels, ease of finding healthy and unhealthy foods, and food consumption behaviours (ie, fruit and vegetables, non-diet soda, fast-food and sit-down restaurant meals). 3 types of PSE outcome variables were identified: promotional/incentivising, limiting/restrictive and business practices. Community economic hardship was not found to be a significant predictor of public support for any of the 3 PSE types. However, Republican party affiliation, being female and perceiving obesity as a serious health problem were. These findings have implications for public health practice and community planning in local health jurisdictions. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Immunogenicity of variable regions of hepatitis C virus proteins: selection and modification of peptide epitopes to assess hepatitis C virus genotypes by ELISA.

PubMed

Rodríguez-López, M; Riezu-Boj, J I; Ruiz, M; Berasain, C; Civeira, M P; Prieto, J; Borrás-Cuesta, F

1999-03-01

The immunogenicity of variable regions of hepatitis C virus (HCV) proteins was studied by ELISA by using 543 synthetic peptides from 120 variable regions and 90 sera from HCV-infected patients. Some regions from certain genotypes were less immunogenic, or even non-immunogenic, compared with their equivalents in other genotypes. However, the mean recognition of all peptides from genotypes 1a, 1b and 3 by sera infected with genotypes 1a, 1b and 3, respectively, showed no significant differences, suggesting a similar overall immunogenicity of variable regions from these genotypes. Proteins NS4a, NS4b and NS5a were found to be the most immunogenic. Recognition of individual peptides by the sera of infected patients showed that the humoral response against HCV is patient-dependent. The work shows that 15-mer peptides may encompass several B-cell epitopes. These epitopes may lie in slightly different positions in different genotypes. Thirty-one percent of the 543 peptides were recognized by some of the 35 healthy donors. This may be a reflection of the large number of antigens to which they had been exposed, but it may also reflect a strategy of HCV to respond to immune pressure. After selection and modification, a set of 40 peptides was used to assess genotypes 1a, 1b, 1, 2 and 3 in the sera of HCV-infected patients, with sensitivities of 34.1, 48.5, 68.8, 58.3 and 48.9% and specificities of 100, 99.1, 97.1, 99.5 and 99%, respectively. The overall sensitivity and specificity for the assessment of genotypes 1, 2 and 3 were 64 and 98%, respectively.

Genetic gain and economic values of selection strategies including semen traits in three- and four-way crossbreeding systems for swine production.

PubMed

González-Peña, D; Knox, R V; MacNeil, M D; Rodriguez-Zas, S L

2015-03-01

Four semen traits: volume (VOL), concentration (CON), progressive motility of spermatozoa (MOT), and abnormal spermatozoa (ABN) provide complementary information on boar fertility. Assessment of the impact of selection for semen traits is hindered by limited information on economic parameters. Objectives of this study were to estimate economic values for semen traits and to evaluate the genetic gain when these traits are incorporated into traditional selection strategies in a 3-tier system of swine production. Three-way (maternal nucleus lines A and B and paternal nucleus line C) and 4-way (additional paternal nucleus line D) crossbreeding schemes were compared. A novel population structure that accommodated selection for semen traits was developed. Three selection strategies were simulated. Selection Strategy I (baseline) encompassed selection for maternal traits: number of pigs born alive (NBA), litter birth weight (LBW), adjusted 21-d litter weight (A21), and number of pigs at 21 d (N21); and paternal traits: number of days to 113.5 kg (D113), backfat (BF), ADG, feed efficiency (FE), and carcass lean % (LEAN). Selection Strategy II included Strategy I and the number of usable semen doses per collection (DOSES), a function of the 4 semen traits. Selection Strategy III included Strategy I and the 4 semen traits individually. The estimated economic values of VOL, CON, MOT, ABN, and DOSES for 7 to 1 collections/wk ranged from $0.21 to $1.44/mL, $0.12 to $0.83/10 spermatozoa/mm, $0.61 to $12.66/%, -$0.53 to -$10.88/%, and $2.01 to $41.43/%, respectively. The decrease in the relative economic values of semen traits and DOSES with higher number of collections per wk was sharper between 1 and 2.33 collections/wk than between 2.33 and 7 collections/wk. The higher economic value of MOT and ABN relative to VOL and CON could be linked to the genetic variances and covariances of these traits. Average genetic gains for the maternal traits were comparable across strategies. Genetic gains for paternal traits, excluding semen traits, were greater in selection Strategy I than Strategies III and II. Genetic gains for paternal and maternal traits were greater in the 4- and 3-way schemes, respectively. The selection strategy including the 4 semen traits is recommended because this approach enables genetic gains for these traits without compromising the genetic gains for maternal traits and with minimal losses in genetic gains for paternal traits.

Optimal strategies for observation of active galactic nuclei variability with Imaging Atmospheric Cherenkov Telescopes

NASA Astrophysics Data System (ADS)

Giomi, Matteo; Gerard, Lucie; Maier, Gernot

2016-07-01

Variable emission is one of the defining characteristic of active galactic nuclei (AGN). While providing precious information on the nature and physics of the sources, variability is often challenging to observe with time- and field-of-view-limited astronomical observatories such as Imaging Atmospheric Cherenkov Telescopes (IACTs). In this work, we address two questions relevant for the observation of sources characterized by AGN-like variability: what is the most time-efficient way to detect such sources, and what is the observational bias that can be introduced by the choice of the observing strategy when conducting blind surveys of the sky. Different observing strategies are evaluated using simulated light curves and realistic instrument response functions of the Cherenkov Telescope Array (CTA), a future gamma-ray observatory. We show that strategies that makes use of very small observing windows, spread over large periods of time, allows for a faster detection of the source, and are less influenced by the variability properties of the sources, as compared to strategies that concentrate the observing time in a small number of large observing windows. Although derived using CTA as an example, our conclusions are conceptually valid for any IACTs facility, and in general, to all observatories with small field of view and limited duty cycle.

Variable Memory Strategy Use in Children's Adaptive Intratask Learning Behavior: Developmental Changes and Working Memory Influences in Free Recall

ERIC Educational Resources Information Center

Lehmann, Martin; Hasselhorn, Marcus

2007-01-01

Variability in strategy use within single trials in free recall was analyzed longitudinally from second to fourth grades (ages 8-10 years). To control for practice effects another sample of fourth graders was included (age 10 years). Video analyses revealed that children employed different strategies when preparing for free recall. A gradual shift…

Spatial Statistical and Modeling Strategy for Inventorying and Monitoring Ecosystem Resources at Multiple Scales and Resolution Levels

Treesearch

Robin M. Reich; C. Aguirre-Bravo; M.S. Williams

2006-01-01

A statistical strategy for spatial estimation and modeling of natural and environmental resource variables and indicators is presented. This strategy is part of an inventory and monitoring pilot study that is being carried out in the Mexican states of Jalisco and Colima. Fine spatial resolution estimates of key variables and indicators are outputs that will allow the...

Analysis of Students' Online Information Searching Strategies, Exposure to Internet Information Pollution and Cognitive Absorption Levels Based on Various Variables

ERIC Educational Resources Information Center

Kurt, Adile Askim; Emiroglu, Bülent Gürsel

2018-01-01

The objective of the present study was to examine students' online information searching strategies, their cognitive absorption levels and the information pollution levels on the Internet based on different variables and to determine the correlation between these variables. The study was designed with the survey model, the study group included 198…

Learning the Control of Variables Strategy in Higher and Lower Achieving Classrooms: Contributions of Explicit Instruction and Experimentation

ERIC Educational Resources Information Center

Lorch, Robert F., Jr.; Lorch, Elizabeth P.; Calderhead, William J.; Dunlap, Emily E.; Hodell, Emily C.; Freer, Benjamin Dunham

2010-01-01

Students (n = 797) from 36 4th-grade classrooms were taught the control of variables strategy for designing experiments. In the instruct condition, classes were taught in an interactive lecture format. In the manipulate condition, students worked in groups to design and run experiments to determine the effects of four variables. In the both…

WWC Review of the Report "Learning the Control of Variables Strategy in Higher and Lower Achieving Classrooms: Contributions of Explicit Instruction and Experimentation"

ERIC Educational Resources Information Center

What Works Clearinghouse, 2012

2012-01-01

The study reviewed in this paper examined three separate methods for teaching the "control of variables strategy" ("CVS"), a procedure for conducting a science experiment so that only one variable is tested and all others are held constant, or "controlled." The study analyzed data from a randomized controlled trial of…

Punishment induced behavioural and neurophysiological variability reveals dopamine-dependent selection of kinematic movement parameters

PubMed Central

Galea, Joseph M.; Ruge, Diane; Buijink, Arthur; Bestmann, Sven; Rothwell, John C.

2013-01-01

Action selection describes the high-level process which selects between competing movements. In animals, behavioural variability is critical for the motor exploration required to select the action which optimizes reward and minimizes cost/punishment, and is guided by dopamine (DA). The aim of this study was to test in humans whether low-level movement parameters are affected by punishment and reward in ways similar to high-level action selection. Moreover, we addressed the proposed dependence of behavioural and neurophysiological variability on DA, and whether this may underpin the exploration of kinematic parameters. Participants performed an out-and-back index finger movement and were instructed that monetary reward and punishment were based on its maximal acceleration (MA). In fact, the feedback was not contingent on the participant’s behaviour but pre-determined. Blocks highly-biased towards punishment were associated with increased MA variability relative to blocks with either reward or without feedback. This increase in behavioural variability was positively correlated with neurophysiological variability, as measured by changes in cortico-spinal excitability with transcranial magnetic stimulation over the primary motor cortex. Following the administration of a DA-antagonist, the variability associated with punishment diminished and the correlation between behavioural and neurophysiological variability no longer existed. Similar changes in variability were not observed when participants executed a pre-determined MA, nor did DA influence resting neurophysiological variability. Thus, under conditions of punishment, DA-dependent processes influence the selection of low-level movement parameters. We propose that the enhanced behavioural variability reflects the exploration of kinematic parameters for less punishing, or conversely more rewarding, outcomes. PMID:23447607

Assessment of Sample Preparation Bias in Mass Spectrometry-Based Proteomics.

PubMed

Klont, Frank; Bras, Linda; Wolters, Justina C; Ongay, Sara; Bischoff, Rainer; Halmos, Gyorgy B; Horvatovich, Péter

2018-04-17

For mass spectrometry-based proteomics, the selected sample preparation strategy is a key determinant for information that will be obtained. However, the corresponding selection is often not based on a fit-for-purpose evaluation. Here we report a comparison of in-gel (IGD), in-solution (ISD), on-filter (OFD), and on-pellet digestion (OPD) workflows on the basis of targeted (QconCAT-multiple reaction monitoring (MRM) method for mitochondrial proteins) and discovery proteomics (data-dependent acquisition, DDA) analyses using three different human head and neck tissues (i.e., nasal polyps, parotid gland, and palatine tonsils). Our study reveals differences between the sample preparation methods, for example, with respect to protein and peptide losses, quantification variability, protocol-induced methionine oxidation, and asparagine/glutamine deamidation as well as identification of cysteine-containing peptides. However, none of the methods performed best for all types of tissues, which argues against the existence of a universal sample preparation method for proteome analysis.

The Challenge of Electrochemical Ammonia Synthesis: A New Perspective on the Role of Nitrogen Scaling Relations.

PubMed

Montoya, Joseph H; Tsai, Charlie; Vojvodic, Aleksandra; Nørskov, Jens K

2015-07-08

The electrochemical production of NH3 under ambient conditions represents an attractive prospect for sustainable agriculture, but electrocatalysts that selectively reduce N2 to NH3 remain elusive. In this work, we present insights from DFT calculations that describe limitations on the low-temperature electrocatalytic production of NH3 from N2 . In particular, we highlight the linear scaling relations of the adsorption energies of intermediates that can be used to model the overpotential requirements in this process. By using a two-variable description of the theoretical overpotential, we identify fundamental limitations on N2 reduction analogous to those present in processes such as oxygen evolution. Using these trends, we propose new strategies for catalyst design that may help guide the search for an electrocatalyst that can achieve selective N2 reduction. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A New Variable Weighting and Selection Procedure for K-Means Cluster Analysis

ERIC Educational Resources Information Center

Steinley, Douglas; Brusco, Michael J.

2008-01-01

A variance-to-range ratio variable weighting procedure is proposed. We show how this weighting method is theoretically grounded in the inherent variability found in data exhibiting cluster structure. In addition, a variable selection procedure is proposed to operate in conjunction with the variable weighting technique. The performances of these…

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

PubMed Central

Brunyé, Tad T.; Collier, Zachary A.; Cantelon, Julie; Holmes, Amanda; Wood, Matthew D.; Linkov, Igor; Taylor, Holly A.

2015-01-01

Previous research has demonstrated that route planners use several reliable strategies for selecting between alternate routes. Strategies include selecting straight rather than winding routes leaving an origin, selecting generally south- rather than north-going routes, and selecting routes that avoid traversal of complex topography. The contribution of this paper is characterizing the relative influence and potential interactions of these strategies. We also examine whether individual differences would predict any strategy reliance. Results showed evidence for independent and additive influences of all three strategies, with a strong influence of topography and initial segment straightness, and relatively weak influence of cardinal direction. Additively, routes were also disproportionately selected when they traversed relatively flat regions, had relatively straight initial segments, and went generally south rather than north. Two individual differences, extraversion and sense of direction, predicted the extent of some effects. Under real-world conditions navigators indeed consider a route’s initial straightness, cardinal direction, and topography, but these cues differ in relative influence and vary in their application across individuals. PMID:25992685

A survey of variable selection methods in two Chinese epidemiology journals

PubMed Central

2010-01-01

Background Although much has been written on developing better procedures for variable selection, there is little research on how it is practiced in actual studies. This review surveys the variable selection methods reported in two high-ranking Chinese epidemiology journals. Methods Articles published in 2004, 2006, and 2008 in the Chinese Journal of Epidemiology and the Chinese Journal of Preventive Medicine were reviewed. Five categories of methods were identified whereby variables were selected using: A - bivariate analyses; B - multivariable analysis; e.g. stepwise or individual significance testing of model coefficients; C - first bivariate analyses, followed by multivariable analysis; D - bivariate analyses or multivariable analysis; and E - other criteria like prior knowledge or personal judgment. Results Among the 287 articles that reported using variable selection methods, 6%, 26%, 30%, 21%, and 17% were in categories A through E, respectively. One hundred sixty-three studies selected variables using bivariate analyses, 80% (130/163) via multiple significance testing at the 5% alpha-level. Of the 219 multivariable analyses, 97 (44%) used stepwise procedures, 89 (41%) tested individual regression coefficients, but 33 (15%) did not mention how variables were selected. Sixty percent (58/97) of the stepwise routines also did not specify the algorithm and/or significance levels. Conclusions The variable selection methods reported in the two journals were limited in variety, and details were often missing. Many studies still relied on problematic techniques like stepwise procedures and/or multiple testing of bivariate associations at the 0.05 alpha-level. These deficiencies should be rectified to safeguard the scientific validity of articles published in Chinese epidemiology journals. PMID:20920252

Methodological development for selection of significant predictors explaining fatal road accidents.

PubMed

Dadashova, Bahar; Arenas-Ramírez, Blanca; Mira-McWilliams, José; Aparicio-Izquierdo, Francisco

2016-05-01

Identification of the most relevant factors for explaining road accident occurrence is an important issue in road safety research, particularly for future decision-making processes in transport policy. However model selection for this particular purpose is still an ongoing research. In this paper we propose a methodological development for model selection which addresses both explanatory variable and adequate model selection issues. A variable selection procedure, TIM (two-input model) method is carried out by combining neural network design and statistical approaches. The error structure of the fitted model is assumed to follow an autoregressive process. All models are estimated using Markov Chain Monte Carlo method where the model parameters are assigned non-informative prior distributions. The final model is built using the results of the variable selection. For the application of the proposed methodology the number of fatal accidents in Spain during 2000-2011 was used. This indicator has experienced the maximum reduction internationally during the indicated years thus making it an interesting time series from a road safety policy perspective. Hence the identification of the variables that have affected this reduction is of particular interest for future decision making. The results of the variable selection process show that the selected variables are main subjects of road safety policy measures. Published by Elsevier Ltd.

Rehabilitative intervention during and after pediatric hematopoietic stem cell transplantation: An analysis of the existing literature.

PubMed

Rossi, Francesca; Coppo, Monica; Zucchetti, Giulia; Bazzano, Daniela; Ricci, Federica; Vassallo, Elena; Nesi, Francesca; Fagioli, Franca

2016-11-01

Hematopoietic stem cell transplantation is a therapeutic strategy for several oncohematological diseases. It increases survival rates but leads to a high incidence of related effects. The objective of this paper was to examine the existing literature on physical exercise interventions among pediatric HSCT recipients to explore the most often utilized rehabilitative assessment and treatment tools. Studies published from 2002 to April 1, 2015 were selected: 10 studies were included. A previous literary review has shown that rehabilitation programs have a positive impact on quality of life. Our analysis identified some significant outcome variables and shared intervention areas. © 2016 Wiley Periodicals, Inc.

Post-Polio Syndrome and the Late Effects of Poliomyelitis: Part 2. Treatment, Management and Prognosis.

PubMed

Lo, Julian K; Robinson, Lawrence R

2018-05-12

Post-Polio Syndrome (PPS) is characterized by new muscle weakness and/or muscle fatigability that occurs many years following the initial poliomyelitis illness. An individualized approach to rehabilitation management is critical. Interventions may include rehabilitation management strategies, adaptive equipment, orthotic equipment, gait/mobility aids and a variety of therapeutic exercises. The progression of muscle weakness in PPS is typically slow and gradual; however, there is also variability in both the natural history of weakness and functional prognosis. Further research is required to determine the effectiveness of selected medical treatment. This article is protected by copyright. All rights reserved. © 2018 Wiley Periodicals, Inc.

Novel metals and metal complexes as platforms for cancer therapy.

PubMed

Frezza, Michael; Hindo, Sarmad; Chen, Di; Davenport, Andrew; Schmitt, Sara; Tomco, Dajena; Dou, Q Ping

2010-06-01

Metals are essential cellular components selected by nature to function in several indispensable biochemical processes for living organisms. Metals are endowed with unique characteristics that include redox activity, variable coordination modes, and reactivity towards organic substrates. Due to their reactivity, metals are tightly regulated under normal conditions and aberrant metal ion concentrations are associated with various pathological disorders, including cancer. For these reasons, coordination complexes, either as drugs or prodrugs, become very attractive probes as potential anticancer agents. The use of metals and their salts for medicinal purposes, from iatrochemistry to modern day, has been present throughout human history. The discovery of cisplatin, cis-[Pt(II) (NH(3))(2)Cl(2)], was a defining moment which triggered the interest in platinum(II)- and other metal-containing complexes as potential novel anticancer drugs. Other interests in this field address concerns for uptake, toxicity, and resistance to metallodrugs. This review article highlights selected metals that have gained considerable interest in both the development and the treatment of cancer. For example, copper is enriched in various human cancer tissues and is a co-factor essential for tumor angiogenesis processes. However the use of copper-binding ligands to target tumor copper could provide a novel strategy for cancer selective treatment. The use of nonessential metals as probes to target molecular pathways as anticancer agents is also emphasized. Finally, based on the interface between molecular biology and bioinorganic chemistry the design of coordination complexes for cancer treatment is reviewed and design strategies and mechanisms of action are discussed.

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.

Path analysis of the energy density of wood in eucalyptus clones.

PubMed

Couto, A M; Teodoro, P E; Trugilho, P F

2017-03-16

Path analysis has been used for establishing selection criteria in genetic breeding programs for several crops. However, it has not been used in eucalyptus breeding programs yet. In the present study, we aimed to identify the wood technology traits that could be used as the criteria for direct and indirect selection of eucalyptus genotypes with high energy density of wood. Twenty-four eucalyptus clones were evaluated in a completely randomized design with five replications. The following traits were assessed: basic wood density, total extractives, lignin content, ash content, nitrogen content, carbon content, hydrogen content, sulfur content, oxygen content, higher calorific power, holocellulose, and energy density. After verifying the variability of all evaluated traits among the clones, a two-dimensional correlation network was used to determine the phenotypic patterns among them. The obtained coefficient of determination (0.94) presented a higher magnitude in relation to the effect of the residual variable, and it served as an excellent model for explaining the genetic effects related to the variations observed in the energy density of wood in all eucalyptus clones. However, for future studies, we recommend evaluating other traits, especially the morphological traits, because of the greater ease in their measurement. Selecting clones with high basic density is the most promising strategy for eucalyptus breeding programs that aim to increase the energy density of wood because of its high heritability and magnitude of the cause-and-effect relationship with this trait.

Chemometric classification of casework arson samples based on gasoline content.

PubMed

Sinkov, Nikolai A; Sandercock, P Mark L; Harynuk, James J

2014-02-01

Detection and identification of ignitable liquids (ILs) in arson debris is a critical part of arson investigations. The challenge of this task is due to the complex and unpredictable chemical nature of arson debris, which also contains pyrolysis products from the fire. ILs, most commonly gasoline, are complex chemical mixtures containing hundreds of compounds that will be consumed or otherwise weathered by the fire to varying extents depending on factors such as temperature, air flow, the surface on which IL was placed, etc. While methods such as ASTM E-1618 are effective, data interpretation can be a costly bottleneck in the analytical process for some laboratories. In this study, we address this issue through the application of chemometric tools. Prior to the application of chemometric tools such as PLS-DA and SIMCA, issues of chromatographic alignment and variable selection need to be addressed. Here we use an alignment strategy based on a ladder consisting of perdeuterated n-alkanes. Variable selection and model optimization was automated using a hybrid backward elimination (BE) and forward selection (FS) approach guided by the cluster resolution (CR) metric. In this work, we demonstrate the automated construction, optimization, and application of chemometric tools to casework arson data. The resulting PLS-DA and SIMCA classification models, trained with 165 training set samples, have provided classification of 55 validation set samples based on gasoline content with 100% specificity and sensitivity. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Selection of nest-site habitat by interior least terns in relation to sandbar construction

USGS Publications Warehouse

Sherfy, M.H.; Stucker, J.H.; Buhl, D.A.

2012-01-01

Federally endangered interior least terns (Sternula antillarum) nest on bare or sparsely vegetated sandbars on midcontinent river systems. Loss of nesting habitat has been implicated as a cause of population declines, and managing these habitats is a major initiative in population recovery. One such initiative involves construction of mid-channel sandbars on the Missouri River, where natural sandbar habitat has declined in quantity and quality since the late 1990s. We evaluated nest-site habitat selection by least terns on constructed and natural sandbars by comparing vegetation, substrate, and debris variables at nest sites (na =a 798) and random points (na =a 1,113) in bare or sparsely vegetated habitats. Our logistic regression models revealed that a broader suite of habitat features was important in nest-site selection on constructed than on natural sandbars. Odds ratios for habitat variables indicated that avoidance of habitat features was the dominant nest-site selection process on both sandbar types, with nesting terns being attracted to nest-site habitat features (gravel and debris) and avoiding vegetation only on constructed sandbars, and avoiding silt and leaf litter on both sandbar types. Despite the seemingly uniform nature of these habitats, our results suggest that a complex suite of habitat features influences nest-site choice by least terns. However, nest-site selection in this social, colonially nesting species may be influenced by other factors, including spatial arrangement of bare sand habitat, proximity to other least terns, and prior habitat occupancy by piping plovers (Charadrius melodus). We found that nest-site selection was sensitive to subtle variation in habitat features, suggesting that rigor in maintaining habitat condition will be necessary in managing sandbars for the benefit of least terns. Further, management strategies that reduce habitat features that are avoided by least terns may be the most beneficial to nesting least terns. ?? 2011 The Wildlife Society.

Selection of nest-site habitat by interior least terns in relation to sandbar construction

USGS Publications Warehouse

Sherfy, Mark H.; Stucker, Jennifer H.; Buhl, Deborah A.

2012-01-01

Federally endangered interior least terns (Sternula antillarum) nest on bare or sparsely vegetated sandbars on midcontinent river systems. Loss of nesting habitat has been implicated as a cause of population declines, and managing these habitats is a major initiative in population recovery. One such initiative involves construction of mid-channel sandbars on the Missouri River, where natural sandbar habitat has declined in quantity and quality since the late 1990s. We evaluated nest-site habitat selection by least terns on constructed and natural sandbars by comparing vegetation, substrate, and debris variables at nest sites (n = 798) and random points (n = 1,113) in bare or sparsely vegetated habitats. Our logistic regression models revealed that a broader suite of habitat features was important in nest-site selection on constructed than on natural sandbars. Odds ratios for habitat variables indicated that avoidance of habitat features was the dominant nest-site selection process on both sandbar types, with nesting terns being attracted to nest-site habitat features (gravel and debris) and avoiding vegetation only on constructed sandbars, and avoiding silt and leaf litter on both sandbar types. Despite the seemingly uniform nature of these habitats, our results suggest that a complex suite of habitat features influences nest-site choice by least terns. However, nest-site selection in this social, colonially nesting species may be influenced by other factors, including spatial arrangement of bare sand habitat, proximity to other least terns, and prior habitat occupancy by piping plovers (Charadrius melodus). We found that nest-site selection was sensitive to subtle variation in habitat features, suggesting that rigor in maintaining habitat condition will be necessary in managing sandbars for the benefit of least terns. Further, management strategies that reduce habitat features that are avoided by least terns may be the most beneficial to nesting least terns.

An analysis of the relationship of seven selected variables to State Board Test Pool Examination performance of the University of Tennessee, Knoxville, College of Nursing.

PubMed

Sharp, T G

1984-02-01

The study was designed to determine whether any one of seven selected variables or a combination of the variables is predictive of performance on the State Board Test Pool Examination. The selected variables studied were: high school grade point average (HSGPA), The University of Tennessee, Knoxville, College of Nursing grade point average (GPA), and American College Test Assessment (ACT) standard scores (English, ENG; mathematics, MA; social studies, SS; natural sciences, NSC; composite, COMP). Data utilized were from graduates of the baccalaureate program of The University of Tennessee, Knoxville, College of Nursing from 1974 through 1979. The sample of 322 was selected from a total population of 572. The Statistical Analysis System (SAS) was designed to accomplish analysis of the predictive relationship of each of the seven selected variables to State Board Test Pool Examination performance (result of pass or fail), a stepwise discriminant analysis was designed for determining the predictive relationship of the strongest combination of the independent variables to overall State Board Test Pool Examination performance (result of pass or fail), and stepwise multiple regression analysis was designed to determine the strongest predictive combination of selected variables for each of the five subexams of the State Board Test Pool Examination. The selected variables were each found to be predictive of SBTPE performance (result of pass or fail). The strongest combination for predicting SBTPE performance (result of pass or fail) was found to be GPA, MA, and NSC.

Flexible stocking strategies for adapting to climatic variability

USDA-ARS?s Scientific Manuscript database

As a result of precipitation-induced variability on forage production, ranchers have difficulty matching animal demand with forage availability in their operations. Flexible stocking strategies could more effectively use extra forage in highly productive years and limit risk of overgrazing during dr...

Proactive vs. reactive car driving: EEG evidence for different driving strategies of older drivers

PubMed Central

Wascher, Edmund; Getzmann, Stephan

2018-01-01

Aging is associated with a large heterogeneity in the extent of age-related changes in sensory, motor, and cognitive functions. All these functions can influence the performance in complex tasks like car driving. The present study aims to identify potential differences in underlying cognitive processes that may explain inter-individual variability in driving performance. Younger and older participants performed a one-hour monotonous driving task in a driving simulator under varying crosswind conditions, while behavioral and electrophysiological data were recorded. Overall, younger and older drivers showed comparable driving performance (lane keeping). However, there was a large difference in driving lane variability within the older group. Dividing the older group in two subgroups with low vs. high driving lane variability revealed differences between the two groups in electrophysiological correlates of mental workload, consumption of mental resources, and activation and sustaining of attention: Older drivers with high driving lane variability showed higher frontal Alpha and Theta activity than older drivers with low driving lane variability and—with increasing crosswind—a more pronounced decrease in Beta activity. These results suggest differences in driving strategies of older and younger drivers, with the older drivers using either a rather proactive and alert driving strategy (indicated by low driving lane variability and lower Alpha and Beta activity), or a rather reactive strategy (indicated by high driving lane variability and higher Alpha activity). PMID:29352314

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.

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

PubMed

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

2017-01-01

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

A non-linear data mining parameter selection algorithm for continuous variables

PubMed Central

Razavi, Marianne; Brady, Sean

2017-01-01

In this article, we propose a new data mining algorithm, by which one can both capture the non-linearity in data and also find the best subset model. To produce an enhanced subset of the original variables, a preferred selection method should have the potential of adding a supplementary level of regression analysis that would capture complex relationships in the data via mathematical transformation of the predictors and exploration of synergistic effects of combined variables. The method that we present here has the potential to produce an optimal subset of variables, rendering the overall process of model selection more efficient. This algorithm introduces interpretable parameters by transforming the original inputs and also a faithful fit to the data. The core objective of this paper is to introduce a new estimation technique for the classical least square regression framework. This new automatic variable transformation and model selection method could offer an optimal and stable model that minimizes the mean square error and variability, while combining all possible subset selection methodology with the inclusion variable transformations and interactions. Moreover, this method controls multicollinearity, leading to an optimal set of explanatory variables. PMID:29131829

[Two-and-a-half year follow-up study of strategy factors in successful learning to predict academic achievements in medical education].

PubMed

Lee, Soon Ok; Lee, Sang Yeoup; Baek, Sunyong; Woo, Jae Seok; Im, Sun Ju; Yune, So Jung; Lee, Sun Hee; Kam, Beesung

2015-06-01

We performed a two-and-a-half year follow-up study of strategy factors in successful learning to predict academic achievements in medical education. Strategy factors in successful learning were identified using a content analysis of open-ended responses from 30 medical students who were ranked in the top 10 of their class. Core words were selected among their responses in each category and the frequency of the words were counted. Then, a factors survey was conducted among year 2 students, before the second semester. Finally, we performed an analysis to assess the association between the factors score and academic achievement for the same students 2.5 years later. The core words were "planning and execution," "daily reviews" in the study schedule category; "focusing in class" and "taking notes" among class-related category; and "lecture notes," "previous exams or papers," and "textbooks" in the primary self-learning resources category. There were associations between the factors scores for study planning and execution, focusing in class, and taking notes and academic achievement, representing the second year second semester credit score, third year written exam scores and fourth year written and skill exam scores. Study planning was only one independent variable to predict fourth year summative written exam scores. In a two-and-a-half year follow-up study, associations were founded between academic achievement and the factors scores for study planning and execution, focusing in class, and taking notes. Study planning as only one independent variable is useful for predicting fourth year summative written exam score.

Documenting Differences between Early Stone Age Flake Production Systems: An Experimental Model and Archaeological Verification.

PubMed

Presnyakova, Darya; Archer, Will; Braun, David R; Flear, Wesley

2015-01-01

This study investigates morphological differences between flakes produced via "core and flake" technologies and those resulting from bifacial shaping strategies. We investigate systematic variation between two technological groups of flakes using experimentally produced assemblages, and then apply the experimental model to the Cutting 10 Mid -Pleistocene archaeological collection from Elandsfontein, South Africa. We argue that a specific set of independent variables--and their interactions--including external platform angle, platform depth, measures of thickness variance and flake curvature should distinguish between these two technological groups. The role of these variables in technological group separation was further investigated using the Generalized Linear Model as well as Linear Discriminant Analysis. The Discriminant model was used to classify archaeological flakes from the Cutting 10 locality in terms of their probability of association, within either experimentally developed technological group. The results indicate that the selected independent variables play a central role in separating core and flake from bifacial technologies. Thickness evenness and curvature had the greatest effect sizes in both the Generalized Linear and Discriminant models. Interestingly the interaction between thickness evenness and platform depth was significant and played an important role in influencing technological group membership. The identified interaction emphasizes the complexity in attempting to distinguish flake production strategies based on flake morphological attributes. The results of the discriminant function analysis demonstrate that the majority of flakes at the Cutting 10 locality were not associated with the production of the numerous Large Cutting Tools found at the site, which corresponds with previous suggestions regarding technological behaviors reflected in this assemblage.

Functional traits and plasticity in response to light in seedlings of four Iberian forest tree species.

PubMed

Sánchez-Gómez, David; Valladares, Fernando; Zavala, Miguel A

2006-11-01

We investigated the differential roles of physiological and morphological features on seedling survivorship along an experimental irradiance gradient in four dominant species of cool temperate-Mediterranean forests (Quercus robur L., Quercus pyrenaica Willd., Pinus sylvestris L. and Pinus pinaster Ait.). The lowest photochemical efficiency (F(v)/F(m) in dark-adapted leaves) was reached in deep shade (1% of full sunlight) in all species except Q. robur, which had the lowest photochemical efficiency in both deep shade and 100% of full sunlight. Species differed significantly in their survival in 1% of full sunlight but exhibited similar survivorship in 6, 20 and 100% of full sunlight. Shade-tolerant oaks had lower leaf area ratios, shoot to root ratios, foliage allocation ratios and higher rates of allocation to structural biomass (stem plus thick roots) than shade-intolerant pines. Overall phenotypic plasticity for each species, estimated as the difference between the minimum and the maximum mean values of the ecophysiological variables studied at the various irradiances divided by the maximum mean value of those variables, was inversely correlated with shade tolerance. Observed morphology, allocation and plasticity conformed to a conservative resource-use strategy, although observed differences in specific leaf area, which was higher in shade-tolerant species, supported a carbon gain maximization strategy. Lack of a congruent suite of traits underlying shade tolerance in the studied species provides evidence of adaptation to multiple selective forces. Although the study was based on only four species, the importance of ecophysiological variables as determinants of interspecific differences in survival in limiting light was demonstrated.

Current dosing of low-molecular-weight heparins does not reflect licensed product labels: an international survey

PubMed Central

Barras, Michael A; Kirkpatrick, Carl M J; Green, Bruce

2010-01-01

AIMS Low-molecular-weight heparins (LMWHs) are used globally to treat thromboembolic diseases; however, there is much debate on how to prescribe effectively for patients who have renal impairment and/or obesity. We aimed to investigate the strategies used to dose-individualize LMWH therapy. METHODS We conducted an online survey of selected hospitals in Australia, New Zealand (NZ), United Kingdom (UK) and the United States (US). Outcome measures included: the percentage of hospitals which recommended that LMWHs were prescribed according to the product label (PL), the percentage of hospitals that dose-individualized LMWHs outside the PL based on renal function, body weight and anti-Xa activity and a summary of methods used to dose-individualize therapy. RESULTS A total of 257 surveys were suitable for analysis: 84 (33%) from Australia, 79 (31%) from the UK, 73 (28%) from the US and 21 (8%) from NZ. Formal dosing protocols were used in 207 (81%) hospitals, of which 198 (96%) did not adhere to the PL. Of these 198 hospitals, 175 (87%) preferred to dose-individualize based on renal function, 128 (62%) on body weight and 48 (23%) by monitoring anti-Xa activity. All three of these variables were used in 29 (14%) hospitals, 98 (47%) used two variables and 71 (34%) used only one variable. CONCLUSIONS Dose-individualization strategies for LMWHs, which contravene the PL, were present in 96% of surveyed hospitals. Common individualization methods included dose-capping, use of lean body size descriptors to calculate renal function and the starting dose, followed by post dose anti-Xa monitoring. PMID:20573088

Current dosing of low-molecular-weight heparins does not reflect licensed product labels: an international survey.

PubMed

Barras, Michael A; Kirkpatrick, Carl M J; Green, Bruce

2010-05-01

Low-molecular-weight heparins (LMWHs) are used globally to treat thromboembolic diseases; however, there is much debate on how to prescribe effectively for patients who have renal impairment and/or obesity. We aimed to investigate the strategies used to dose-individualize LMWH therapy. We conducted an online survey of selected hospitals in Australia, New Zealand (NZ), United Kingdom (UK) and the United States (US). Outcome measures included: the percentage of hospitals which recommended that LMWHs were prescribed according to the product label (PL), the percentage of hospitals that dose-individualized LMWHs outside the PL based on renal function, body weight and anti-Xa activity and a summary of methods used to dose-individualize therapy. A total of 257 surveys were suitable for analysis: 84 (33%) from Australia, 79 (31%) from the UK, 73 (28%) from the US and 21 (8%) from NZ. Formal dosing protocols were used in 207 (81%) hospitals, of which 198 (96%) did not adhere to the PL. Of these 198 hospitals, 175 (87%) preferred to dose-individualize based on renal function, 128 (62%) on body weight and 48 (23%) by monitoring anti-Xa activity. All three of these variables were used in 29 (14%) hospitals, 98 (47%) used two variables and 71 (34%) used only one variable. Dose-individualization strategies for LMWHs, which contravene the PL, were present in 96% of surveyed hospitals. Common individualization methods included dose-capping, use of lean body size descriptors to calculate renal function and the starting dose, followed by post dose anti-Xa monitoring.

Effects of local and widespread muscle fatigue on movement timing.

PubMed

Cowley, Jeffrey C; Dingwell, Jonathan B; Gates, Deanna H

2014-12-01

Repetitive movements can cause muscle fatigue, leading to motor reorganization, performance deficits, and/or possible injury. The effects of fatigue may depend on the type of fatigue task employed, however. The purpose of this study was to determine how local fatigue of a specific muscle group versus widespread fatigue of various muscle groups affected the control of movement timing. Twenty healthy subjects performed an upper extremity low-load work task similar to sawing for 5 continuous minutes both before and after completing a protocol that either fatigued all the muscles used in the task (widespread fatigue) or a protocol that selectively fatigued the primary muscles used to execute the pushing stroke of the sawing task (localized fatigue). Subjects were instructed to time their movements with a metronome. Timing error, movement distance, and speed were calculated for each movement. Data were then analyzed using a goal-equivalent manifold approach to quantify changes in goal-relevant and non-goal-relevant variability. We applied detrended fluctuation analysis to each time series to quantify changes in fluctuation dynamics that reflected changes in the control strategies used. After localized fatigue, subjects made shorter, slower movements and exerted greater control over non-goal-relevant variability. After widespread fatigue, subjects exerted less control over non-goal-relevant variability and did not change movement patterns. Thus, localized and widespread muscle fatigue affected movement differently. Local fatigue may reduce the available motor solutions and therefore cause greater movement reorganization than widespread muscle fatigue. Subjects altered their control strategies but continued to achieve the timing goal after both fatigue tasks.

The Genetic Diversity, Haplotype Analysis, and Phylogenetic Relationship of Aedes albopictus (Diptera: Culicidae) Based on the Cytochrome Oxidase 1 Marker: A Malaysian Scenario.

PubMed

Ismail, Nurul-Ain; Adilah-Amrannudin, Nurul; Hamsidi, Mayamin; Ismail, Rodziah; Dom, Nazri Che; Ahmad, Abu Hassan; Mastuki, Mohd Fahmi; Camalxaman, Siti Nazrina

2017-11-07

The global expansion of Ae. albopictus from its native range in Southeast Asia has been implicated in the recent emergence of dengue endemicity in Malaysia. Genetic variability studies of Ae. albopictus are currently lacking in the Malaysian setting, yet are crucial to enhancing the existing vector control strategies. The study was conducted to establish the genetic variability of maternally inherited mitochondrial DNA encoding for cytochrome oxidase subunit 1 (CO1) gene in Ae. albopictus. Twelve localities were selected in the Subang Jaya district based on temporal indices utilizing 120 mosquito samples. Genetic polymorphism and phylogenetic analysis were conducted to unveil the genetic variability and geographic origins of Ae. albopictus. The haplotype network was mapped to determine the genealogical relationship of sequences among groups of population in the Asian region. Comparison of Malaysian CO1 sequences with sequences derived from five Asian countries revealed genetically distinct Ae. albopictus populations. Phylogenetic analysis revealed that all sequences from other Asian countries descended from the same genetic lineage as the Malaysian sequences. Noteworthy, our study highlights the discovery of 20 novel haplotypes within the Malaysian population which to date had not been reported. These findings could help determine the genetic variation of this invasive species, which in turn could possibly improve the current dengue vector surveillance strategies, locally and regionally. © The Authors 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Age-Related Changes in Children's Executive Functions and Strategy Selection: A Study in Computational Estimation

ERIC Educational Resources Information Center

Lemaire, Patrick; Lecacheur, Mireille

2011-01-01

Third, fifth, and seventh graders selected the best strategy (rounding up or rounding down) for estimating answers to two-digit addition problems. Executive function measures were collected for each individual. Data showed that (a) children's skill at both strategy selection and execution improved with age and (b) increased efficiency in executive…

A cost-effectiveness analysis of two different antimicrobial stewardship programs.

PubMed

Okumura, Lucas Miyake; Riveros, Bruno Salgado; Gomes-da-Silva, Monica Maria; Veroneze, Izelandia

2016-01-01

There is a lack of formal economic analysis to assess the efficiency of antimicrobial stewardship programs. Herein, we conducted a cost-effectiveness study to assess two different strategies of Antimicrobial Stewardship Programs. A 30-day Markov model was developed to analyze how cost-effective was a Bundled Antimicrobial Stewardship implemented in a university hospital in Brazil. Clinical data derived from a historical cohort that compared two different strategies of antimicrobial stewardship programs and had 30-day mortality as main outcome. Selected costs included: workload, cost of defined daily doses, length of stay, laboratory and imaging resources used to diagnose infections. Data were analyzed by deterministic and probabilistic sensitivity analysis to assess model's robustness, tornado diagram and Cost-Effectiveness Acceptability Curve. Bundled Strategy was more expensive (Cost difference US$ 2119.70), however, it was more efficient (US$ 27,549.15 vs 29,011.46). Deterministic and probabilistic sensitivity analysis suggested that critical variables did not alter final Incremental Cost-Effectiveness Ratio. Bundled Strategy had higher probabilities of being cost-effective, which was endorsed by cost-effectiveness acceptability curve. As health systems claim for efficient technologies, this study conclude that Bundled Antimicrobial Stewardship Program was more cost-effective, which means that stewardship strategies with such characteristics would be of special interest in a societal and clinical perspective. Copyright © 2016 Elsevier Editora Ltda. All rights reserved.

The effects of task difficulty on visual search strategy in virtual 3D displays.

PubMed

Pomplun, Marc; Garaas, Tyler W; Carrasco, Marisa

2013-08-28

Analyzing the factors that determine our choice of visual search strategy may shed light on visual behavior in everyday situations. Previous results suggest that increasing task difficulty leads to more systematic search paths. Here we analyze observers' eye movements in an "easy" conjunction search task and a "difficult" shape search task to study visual search strategies in stereoscopic search displays with virtual depth induced by binocular disparity. Standard eye-movement variables, such as fixation duration and initial saccade latency, as well as new measures proposed here, such as saccadic step size, relative saccadic selectivity, and x-y target distance, revealed systematic effects on search dynamics in the horizontal-vertical plane throughout the search process. We found that in the "easy" task, observers start with the processing of display items in the display center immediately after stimulus onset and subsequently move their gaze outwards, guided by extrafoveally perceived stimulus color. In contrast, the "difficult" task induced an initial gaze shift to the upper-left display corner, followed by a systematic left-right and top-down search process. The only consistent depth effect was a trend of initial saccades in the easy task with smallest displays to the items closest to the observer. The results demonstrate the utility of eye-movement analysis for understanding search strategies and provide a first step toward studying search strategies in actual 3D scenarios.

The development of strategy use in elementary school children: working memory and individual differences.

PubMed

Imbo, Ineke; Vandierendonck, André

2007-04-01

The current study tested the development of working memory involvement in children's arithmetic strategy selection and strategy efficiency. To this end, an experiment in which the dual-task method and the choice/no-choice method were combined was administered to 10- to 12-year-olds. Working memory was needed in retrieval, transformation, and counting strategies, but the ratio between available working memory resources and arithmetic task demands changed across development. More frequent retrieval use, more efficient memory retrieval, and more efficient counting processes reduced the working memory requirements. Strategy efficiency and strategy selection were also modified by individual differences such as processing speed, arithmetic skill, gender, and math anxiety. Short-term memory capacity, in contrast, was not related to children's strategy selection or strategy efficiency.

Water governance: learning by developing adaptive capacity to incorporate climate variability and change.

PubMed

Kashyap, A

2004-01-01

There is increasing evidence that global climate variability and change is affecting the quality and availability of water supplies. Integrated water resources development, use, and management strategies, represent an effective approach to achieve sustainable development of water resources in a changing environment with competing demands. It is also a key to achieving the Millennium Development Goals. It is critical that integrated water management strategies must incorporate the impacts of climate variability and change to reduce vulnerability of the poor, strengthen sustainable livelihoods and support national sustainable development. UNDP's strategy focuses on developing adaptation in the water governance sector as an entry point within the framework of poverty reduction and national sustainable development. This strategy aims to strengthen the capacity of governments and civil society organizations to have access to early warning systems, ability to assess the impact of climate variability and change on integrated water resources management, and developing adaptation intervention through hands-on learning by undertaking pilot activities.

When does a strategy intervention overcome a failure of inhibition? Evidence from two left frontal brain tumour cases.

PubMed

Robinson, Gail A; Walker, David G; Biggs, Vivien; Shallice, Tim

2016-06-01

Initiation and inhibition of responses are crucial for appropriate behaviour across different settings. Initiation and inhibition difficulties are well documented following frontal damage, although task differences have limited our understanding. The Hayling Sentence Completion Test was designed to assess verbal initiation and inhibition within the same task. This study investigates the ability of two patients with left frontal tumours (KI: high grade glioma; PM: meningioma) to use a strategy to overcome profound suppression failures on the Hayling Test. KI and PM completed the Hayling Test and two experimental tasks. The Selection Investigation assessed verbal initiation on a sentence completion task that varied selection demands (high/low). The Suppression and Strategy Investigation assessed ability to implement four strategies aimed to override a suppression failure and facilitate production of an unconnected word. On the Hayling Test, KI and PM initiated responses to complete high constraint sentences, in contrast to impaired suppression. KI benefitted minimally from strategies to overcome suppression failure although one strategy (object naming) was partially successful. KI's errors revealed fast suppression errors, in contrast to slow no responses, and selection ability was also impaired for verbal initiation. PM, however, implemented each strategy 100% to overcome a suppression failure and had no difficulty completing sentences meaningfully, regardless of selection demands. This first investigation of strategy implementation to overcome profound suppression impairments provides insights into verbal initiation, inhibition, selection and strategy mechanisms, which has implications for neurorehabilitation. Specifically, both patients had profound inhibition deficits but KI also presented with a selection deficit and was unable to implement a strategy. By contrast, PM's selection ability was intact but she was unable to generate, rather than implement, a strategy. We suggest that KI has both fast, uncontrolled semantic output and response inhibition difficulty, whereas PM's difficulty is underpinned by motivational factors. Copyright © 2016 Elsevier Ltd. All rights reserved.

Evaluation of variable selection methods for random forests and omics data sets.

PubMed

Degenhardt, Frauke; Seifert, Stephan; Szymczak, Silke

2017-10-16

Machine learning methods and in particular random forests are promising approaches for prediction based on high dimensional omics data sets. They provide variable importance measures to rank predictors according to their predictive power. If building a prediction model is the main goal of a study, often a minimal set of variables with good prediction performance is selected. However, if the objective is the identification of involved variables to find active networks and pathways, approaches that aim to select all relevant variables should be preferred. We evaluated several variable selection procedures based on simulated data as well as publicly available experimental methylation and gene expression data. Our comparison included the Boruta algorithm, the Vita method, recurrent relative variable importance, a permutation approach and its parametric variant (Altmann) as well as recursive feature elimination (RFE). In our simulation studies, Boruta was the most powerful approach, followed closely by the Vita method. Both approaches demonstrated similar stability in variable selection, while Vita was the most robust approach under a pure null model without any predictor variables related to the outcome. In the analysis of the different experimental data sets, Vita demonstrated slightly better stability in variable selection and was less computationally intensive than Boruta.In conclusion, we recommend the Boruta and Vita approaches for the analysis of high-dimensional data sets. Vita is considerably faster than Boruta and thus more suitable for large data sets, but only Boruta can also be applied in low-dimensional settings. © The Author 2017. Published by Oxford University Press.

Comparisons of Selected Student and Teacher Variables in All-Girls and Coeducational Physical Education Environments

ERIC Educational Resources Information Center

Derry, Julie A.; Phillips, D. Allen

2004-01-01

The purpose of this study was to investigate selected student and teacher variables and compare the differences between these variables for female students and female teachers in coeducation and single-sex physical education classes. Eighteen female teachers and intact classes were selected; 9 teachers from coeducation and 9 teachers from…

Petroleomics by electrospray ionization FT-ICR mass spectrometry coupled to partial least squares with variable selection methods: prediction of the total acid number of crude oils.

PubMed

Terra, Luciana A; Filgueiras, Paulo R; Tose, Lílian V; Romão, Wanderson; de Souza, Douglas D; de Castro, Eustáquio V R; de Oliveira, Mirela S L; Dias, Júlio C M; Poppi, Ronei J

2014-10-07

Negative-ion mode electrospray ionization, ESI(-), with Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) was coupled to a Partial Least Squares (PLS) regression and variable selection methods to estimate the total acid number (TAN) of Brazilian crude oil samples. Generally, ESI(-)-FT-ICR mass spectra present a power of resolution of ca. 500,000 and a mass accuracy less than 1 ppm, producing a data matrix containing over 5700 variables per sample. These variables correspond to heteroatom-containing species detected as deprotonated molecules, [M - H](-) ions, which are identified primarily as naphthenic acids, phenols and carbazole analog species. The TAN values for all samples ranged from 0.06 to 3.61 mg of KOH g(-1). To facilitate the spectral interpretation, three methods of variable selection were studied: variable importance in the projection (VIP), interval partial least squares (iPLS) and elimination of uninformative variables (UVE). The UVE method seems to be more appropriate for selecting important variables, reducing the dimension of the variables to 183 and producing a root mean square error of prediction of 0.32 mg of KOH g(-1). By reducing the size of the data, it was possible to relate the selected variables with their corresponding molecular formulas, thus identifying the main chemical species responsible for the TAN values.

Two-phase strategy of neural control for planar reaching movements: I. XY coordination variability and its relation to end-point variability.

PubMed

Rand, Miya K; Shimansky, Yury P

2013-03-01

A quantitative model of optimal transport-aperture coordination (TAC) during reach-to-grasp movements has been developed in our previous studies. The utilization of that model for data analysis allowed, for the first time, to examine the phase dependence of the precision demand specified by the CNS for neurocomputational information processing during an ongoing movement. It was shown that the CNS utilizes a two-phase strategy for movement control. That strategy consists of reducing the precision demand for neural computations during the initial phase, which decreases the cost of information processing at the expense of lower extent of control optimality. To successfully grasp the target object, the CNS increases precision demand during the final phase, resulting in higher extent of control optimality. In the present study, we generalized the model of optimal TAC to a model of optimal coordination between X and Y components of point-to-point planar movements (XYC). We investigated whether the CNS uses the two-phase control strategy for controlling those movements, and how the strategy parameters depend on the prescribed movement speed, movement amplitude and the size of the target area. The results indeed revealed a substantial similarity between the CNS's regulation of TAC and XYC. First, the variability of XYC within individual trials was minimal, meaning that execution noise during the movement was insignificant. Second, the inter-trial variability of XYC was considerable during the majority of the movement time, meaning that the precision demand for information processing was lowered, which is characteristic for the initial phase. That variability significantly decreased, indicating higher extent of control optimality, during the shorter final movement phase. The final phase was the longest (shortest) under the most (least) challenging combination of speed and accuracy requirements, fully consistent with the concept of the two-phase control strategy. This paper further discussed the relationship between motor variability and XYC variability.

A Selective Overview of Variable Selection in High Dimensional Feature Space

PubMed Central

Fan, Jianqing

2010-01-01

High dimensional statistical problems arise from diverse fields of scientific research and technological development. Variable selection plays a pivotal role in contemporary statistical learning and scientific discoveries. The traditional idea of best subset selection methods, which can be regarded as a specific form of penalized likelihood, is computationally too expensive for many modern statistical applications. Other forms of penalized likelihood methods have been successfully developed over the last decade to cope with high dimensionality. They have been widely applied for simultaneously selecting important variables and estimating their effects in high dimensional statistical inference. In this article, we present a brief account of the recent developments of theory, methods, and implementations for high dimensional variable selection. What limits of the dimensionality such methods can handle, what the role of penalty functions is, and what the statistical properties are rapidly drive the advances of the field. The properties of non-concave penalized likelihood and its roles in high dimensional statistical modeling are emphasized. We also review some recent advances in ultra-high dimensional variable selection, with emphasis on independence screening and two-scale methods. PMID:21572976

The application of improved NeuroEvolution of Augmenting Topologies neural network in Marcellus Shale lithofacies prediction

NASA Astrophysics Data System (ADS)

Wang, Guochang; Cheng, Guojian; Carr, Timothy R.

2013-04-01

The organic-rich Marcellus Shale was deposited in a foreland basin during Middle Devonian. In terms of mineral composition and organic matter richness, we define seven mudrock lithofacies: three organic-rich lithofacies and four organic-poor lithofacies. The 3D lithofacies model is very helpful to determine geologic and engineering sweet spots, and consequently useful for designing horizontal well trajectories and stimulation strategies. The NeuroEvolution of Augmenting Topologies (NEAT) is relatively new idea in the design of neural networks, and shed light on classification (i.e., Marcellus Shale lithofacies prediction). We have successfully enhanced the capability and efficiency of NEAT in three aspects. First, we introduced two new attributes of node gene, the node location and recurrent connection (RCC), to increase the calculation efficiency. Second, we evolved the population size from an initial small value to big, instead of using the constant value, which saves time and computer memory, especially for complex learning tasks. Third, in multiclass pattern recognition problems, we combined feature selection of input variables and modular neural network to automatically select input variables and optimize network topology for each binary classifier. These improvements were tested and verified by true if an odd number of its arguments are true and false otherwise (XOR) experiments, and were powerful for classification.

Carbon metabolism influenced for promoters and temperature used in the heterologous protein production using Pichia pastoris yeast.

PubMed

Zepeda, Andrea B; Pessoa, Adalberto; Farías, Jorge G

2018-05-19

Nowadays, it is necessary to search for different high-scale production strategies to produce recombinant proteins of economic interest. Only a few microorganisms are industrially relevant for recombinant protein production: methylotrophic yeasts are known to use methanol efficiently as the sole carbon and energy source. Pichia pastoris is a methylotrophic yeast characterized as being an economical, fast and effective system for heterologous protein expression. Many factors can affect both the product and the production, including the promoter, carbon source, pH, production volume, temperature, and many others; but to control all of them most of the time is difficult and this depends on the initial selection of each variable. Therefore, this review focuses on the selection of the best promoter in the recombination process, considering different inductors, and the temperature as a culture medium variable in methylotrophic Pichia pastoris yeast. The goal is to understand the effects associated with different factors that influence its cell metabolism and to reach the construction of an expression system that fulfills the requirements of the yeast, presenting an optimal growth and development in batch, fed-batch or continuous cultures, and at the same time improve its yield in heterologous protein production. Copyright © 2018 Sociedade Brasileira de Microbiologia. Published by Elsevier Editora Ltda. All rights reserved.

Selecting Species Traits for Biomonitoring Applications in light of Phylogenetic Relationships among Lotic Insects

NASA Astrophysics Data System (ADS)

Poff, N.; Vieira, N. K.; Simmons, M. P.; Olden, J. D.; Kondratieff, B. C.; Finn, D. S.

2005-05-01

The use of species traits as indicators of environmental disturbance is being considered for biomonitoring programs globally. As such, methods to select relevant and informative traits for inclusion in biometrics need to be developed. In this research, we identified 20 traits of aquatic insects within six trait groups: morphology, mobility, life-history strategy, thermal tolerance, feeding guild and ecology (e.g., habitat preference). We constructed phylogenetic trees for 1) all lotic insect species of North America and 2) all Ephemeroptera, Plecoptera and Trichoptera species based on morphology- and molecular-based analyses and classifications. We then measured variability (i.e., plasticity) of the 20 traits and six trait groups across the two phylogenetic trees. Traits with higher degrees of plasticity indicated traits that were less phylogenetically constrained, and were considered informative for biomonitoring purposes. Thermal tolerance, rheophily, body size at maturity and feeding guild showed the highest plasticity across both phylogenetic trees. Two mobility traits, occurrence in drift and adult dispersal distance, showed moderate plasticity. By contrast, adult exiting ability, degree of attachment, adult lifespan and body shape showed low variability and were thus less informative. Plastic species traits that are less phylogenetically constrained may be most useful in detecting community change along environmental gradients.

Parameters in selective laser melting for processing metallic powders

NASA Astrophysics Data System (ADS)

Kurzynowski, Tomasz; Chlebus, Edward; Kuźnicka, Bogumiła; Reiner, Jacek

2012-03-01

The paper presents results of studies on Selective Laser Melting. SLM is an additive manufacturing technology which may be used to process almost all metallic materials in the form of powder. Types of energy emission sources, mainly fiber lasers and/or Nd:YAG laser with similar characteristics and the wavelength of 1,06 - 1,08 microns, are provided primarily for processing metallic powder materials with high absorption of laser radiation. The paper presents results of selected variable parameters (laser power, scanning time, scanning strategy) and fixed parameters such as the protective atmosphere (argon, nitrogen, helium), temperature, type and shape of the powder material. The thematic scope is very broad, so the work was focused on optimizing the process of selective laser micrometallurgy for producing fully dense parts. The density is closely linked with other two conditions: discontinuity of the microstructure (microcracks) and stability (repeatability) of the process. Materials used for the research were stainless steel 316L (AISI), tool steel H13 (AISI), and titanium alloy Ti6Al7Nb (ISO 5832-11). Studies were performed with a scanning electron microscope, a light microscopes, a confocal microscope and a μCT scanner.

Modeling the Effects of Augmentation Strategies on the Control of Dengue Fever With an Impulsive Differential Equation.

PubMed

Zhang, Xianghong; Tang, Sanyi; Cheke, Robert A; Zhu, Huaiping

2016-10-01

Dengue fever has rapidly become the world's most common vector-borne viral disease. Use of endosymbiotic Wolbachia is an innovative technology to prevent vector mosquitoes from reproducing and so break the cycle of dengue transmission. However, strategies such as population eradication and replacement will only succeed if appropriate augmentations with Wolbachia-infected mosquitoes that take account of a variety of factors are carried out. Here, we describe the spread of Wolbachia in mosquito populations using an impulsive differential system with four state variables, incorporating the effects of cytoplasmic incompatibility and the augmentation of Wolbachia-infected mosquitoes with different sex ratios. We then evaluated (a) how each parameter value contributes to the success of population replacement; (b) how different release quantities of infected mosquitoes with different sex ratios affect the success of population suppression or replacement; and (c) how the success of these two strategies can be realized to block the transmission of dengue fever. Analysis of the system's stability, bifurcations and sensitivity reveals the existence of forward and backward bifurcations, multiple attractors and the contribution of each parameter to the success of the strategies. The results indicate that the initial density of mosquitoes, the quantities of mosquitoes released in augmentations and their sex ratios have impacts on whether or not the strategies of population suppression or replacement can be achieved. Therefore, successful strategies rely on selecting suitable strains of Wolbachia and carefully designing the mosquito augmentation program.

Identification of spectral regions for the quantification of red wine tannins with fourier transform mid-infrared spectroscopy.

PubMed

Jensen, Jacob S; Egebo, Max; Meyer, Anne S

2008-05-28

Accomplishment of fast tannin measurements is receiving increased interest as tannins are important for the mouthfeel and color properties of red wines. Fourier transform mid-infrared spectroscopy allows fast measurement of different wine components, but quantification of tannins is difficult due to interferences from spectral responses of other wine components. Four different variable selection tools were investigated for the identification of the most important spectral regions which would allow quantification of tannins from the spectra using partial least-squares regression. The study included the development of a new variable selection tool, iterative backward elimination of changeable size intervals PLS. The spectral regions identified by the different variable selection methods were not identical, but all included two regions (1485-1425 and 1060-995 cm(-1)), which therefore were concluded to be particularly important for tannin quantification. The spectral regions identified from the variable selection methods were used to develop calibration models. All four variable selection methods identified regions that allowed an improved quantitative prediction of tannins (RMSEP = 69-79 mg of CE/L; r = 0.93-0.94) as compared to a calibration model developed using all variables (RMSEP = 115 mg of CE/L; r = 0.87). Only minor differences in the performance of the variable selection methods were observed.

Developing cluster strategy of apples dodol SMEs by integration K-means clustering and analytical hierarchy process method

NASA Astrophysics Data System (ADS)

Mustaniroh, S. A.; Effendi, U.; Silalahi, R. L. R.; Sari, T.; Ala, M.

2018-03-01

The purposes of this research were to determine the grouping of apples dodol small and medium enterprises (SMEs) in Batu City and to determine an appropriate development strategy for each cluster. The methods used for clustering SMEs was k-means. The Analytical Hierarchy Process (AHP) approach was then applied to determine the development strategy priority for each cluster. The variables used in grouping include production capacity per month, length of operation, investment value, average sales revenue per month, amount of SMEs assets, and the number of workers. Several factors were considered in AHP include industry cluster, government, as well as related and supporting industries. Data was collected using the methods of questionaire and interviews. SMEs respondents were selected among SMEs appels dodol in Batu City using purposive sampling. The result showed that two clusters were formed from five apples dodol SMEs. The 1stcluster of apples dodol SMEs, classified as small enterprises, included SME A, SME C, and SME D. The 2ndcluster of SMEs apples dodol, classified as medium enterprises, consisted of SME B and SME E. The AHP results indicated that the priority development strategy for the 1stcluster of apples dodol SMEs was improving quality and the product standardisation, while for the 2nd cluster was increasing the marketing access.

Interpersonal conflict strategies and their impact on positive symptom remission in persons aged 55 and older with schizophrenia spectrum disorders.

PubMed

Cohen, Carl I; Solanki, Dishal; Sodhi, Dimple

2013-01-01

Although interpersonal interactions are thought to affect psychopathology in schizophrenia, there is a paucity of data about how older adults with schizophrenia manage interpersonal conflicts. This paper examines interpersonal conflict strategies and their impact on positive symptom remission in older adults with schizophrenia spectrum disorders. The schizophrenia group consisted of 198 persons aged 55 years and over living in the community who developed schizophrenia before age 45. A community comparison group (n = 113) was recruited using randomly selected block-groups. Straus' Conflict Tactics Scale (CTS) was used to assess the ways that respondents handled interpersonal conflicts. Seven conflict management subscales were created based on a principal component analysis with equamax rotation of items from the CTS. The order of the frequency of the tactics that was used was similar for both the schizophrenia and community groups. Calm and Pray tactics were the most commonly used, and the Violent and Aggressive tactics were rarely utilized. In two separate logistic regression analysis, after controlling for confounding variables, positive symptom remission was found to be associated significantly with both the Calm and Pray subscales. The findings suggest that older persons with schizophrenia approximate normal distribution patterns of conflict management strategies and the most commonly used strategies are associated with positive symptom remission.

FT-Raman and NIR spectroscopy data fusion strategy for multivariate qualitative analysis of food fraud.

PubMed

Márquez, Cristina; López, M Isabel; Ruisánchez, Itziar; Callao, M Pilar

2016-12-01

Two data fusion strategies (high- and mid-level) combined with a multivariate classification approach (Soft Independent Modelling of Class Analogy, SIMCA) have been applied to take advantage of the synergistic effect of the information obtained from two spectroscopic techniques: FT-Raman and NIR. Mid-level data fusion consists of merging some of the previous selected variables from the spectra obtained from each spectroscopic technique and then applying the classification technique. High-level data fusion combines the SIMCA classification results obtained individually from each spectroscopic technique. Of the possible ways to make the necessary combinations, we decided to use fuzzy aggregation connective operators. As a case study, we considered the possible adulteration of hazelnut paste with almond. Using the two-class SIMCA approach, class 1 consisted of unadulterated hazelnut samples and class 2 of samples adulterated with almond. Models performance was also studied with samples adulterated with chickpea. The results show that data fusion is an effective strategy since the performance parameters are better than the individual ones: sensitivity and specificity values between 75% and 100% for the individual techniques and between 96-100% and 88-100% for the mid- and high-level data fusion strategies, respectively. Copyright © 2016 Elsevier B.V. All rights reserved.

Modulating RNA Alignment Using Directional Dynamic Kinks: Application in Determining an Atomic-Resolution Ensemble for a Hairpin using NMR Residual Dipolar Couplings.

PubMed

Salmon, Loïc; Giambaşu, George M; Nikolova, Evgenia N; Petzold, Katja; Bhattacharya, Akash; Case, David A; Al-Hashimi, Hashim M

2015-10-14

Approaches that combine experimental data and computational molecular dynamics (MD) to determine atomic resolution ensembles of biomolecules require the measurement of abundant experimental data. NMR residual dipolar couplings (RDCs) carry rich dynamics information, however, difficulties in modulating overall alignment of nucleic acids have limited the ability to fully extract this information. We present a strategy for modulating RNA alignment that is based on introducing variable dynamic kinks in terminal helices. With this strategy, we measured seven sets of RDCs in a cUUCGg apical loop and used this rich data set to test the accuracy of an 0.8 μs MD simulation computed using the Amber ff10 force field as well as to determine an atomic resolution ensemble. The MD-generated ensemble quantitatively reproduces the measured RDCs, but selection of a sub-ensemble was required to satisfy the RDCs within error. The largest discrepancies between the RDC-selected and MD-generated ensembles are observed for the most flexible loop residues and backbone angles connecting the loop to the helix, with the RDC-selected ensemble resulting in more uniform dynamics. Comparison of the RDC-selected ensemble with NMR spin relaxation data suggests that the dynamics occurs on the ps-ns time scales as verified by measurements of R(1ρ) relaxation-dispersion data. The RDC-satisfying ensemble samples many conformations adopted by the hairpin in crystal structures indicating that intrinsic plasticity may play important roles in conformational adaptation. The approach presented here can be applied to test nucleic acid force fields and to characterize dynamics in diverse RNA motifs at atomic resolution.

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.

From chemotaxis to the cognitive map: The function of olfaction

PubMed Central

Jacobs, Lucia F.

2012-01-01

A paradox of vertebrate brain evolution is the unexplained variability in the size of the olfactory bulb (OB), in contrast to other brain regions, which scale predictably with brain size. Such variability appears to be the result of selection for olfactory function, yet there is no obvious concordance that would predict the causal relationship between OB size and behavior. This discordance may derive from assuming the primary function of olfaction is odorant discrimination and acuity. If instead the primary function of olfaction is navigation, i.e., predicting odorant distributions in time and space, variability in absolute OB size could be ascribed and explained by variability in navigational demand. This olfactory spatial hypothesis offers a single functional explanation to account for patterns of olfactory system scaling in vertebrates, the primacy of olfaction in spatial navigation, even in visual specialists, and proposes an evolutionary scenario to account for the convergence in olfactory structure and function across protostomes and deuterostomes. In addition, the unique percepts of olfaction may organize odorant information in a parallel map structure. This could have served as a scaffold for the evolution of the parallel map structure of the mammalian hippocampus, and possibly the arthropod mushroom body, and offers an explanation for similar flexible spatial navigation strategies in arthropods and vertebrates. PMID:22723365

Psychological and biographical differences between secondary school teachers experiencing high and low levels of burnout.

PubMed

Pierce, C M; Molloy, G N

1990-02-01

A total of 750 teachers from 16 government and non-government schools from areas of contrasted socio-economic status (SES) responded to a questionnaire designed to investigate associations between selected aspects of burnout among teachers working in secondary schools in Victoria, Australia. By comparing high and low burnout groups on biographic, psychological and work pattern variables, differences between teachers experiencing high and low levels of burnout were identified. Multiple regression analyses assessed the relative importance of these variables in accounting for the variance in each of the three burnout subscales. School type was related to perceptions of stress and burnout. Higher levels of burnout were associated with poorer physical health, higher rates of absenteeism, lower self-confidence and more frequent use of regressive coping strategies. Teachers classified as experiencing high levels of burnout attributed most of the stress in their lives to teaching and reported low levels of career commitment and satisfaction. Further, teachers who recorded high levels of burnout were characterised by lower levels of the personality disposition of hardiness, lower levels of social support, higher levels of role stress and more custodial pupil control ideologies than their low-burnout counterparts. Psychological variables were found to be more significant predictors of burnout than biographical variables.

Nonpolluting automobiles

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

Hoolboom, G.J.; Szabados, B.

The advantages/disadvantages of energy storage devices, which can provide nonpolluting automobile systems are discussed. Four types of storage devices are identified: electrochemical (batteries); hydrogen; electromechanical (flywheels); and molten salt heat storage. A high-speed flywheel with a small permanent magnet motor/generator has more advantages than any of the other systems and might become a real competitor to the internal combustion engine. A flywheel/motor/generator system for automobiles now becomes practical, because of the technological advances in materials, bearings and solid state control circuits. The motor of choice is the squirrel cage induction motor, specially designed for automobile applications. The preferred controller formore » the induction motor is a forced commutated cycloconverter, which transforms a variable voltage/variable frequency source into a controlled variable-voltage/variable-frequency supply. A modulation strategy of the cycloconverter elements is selected to maintain a unity input displacement factor (power factor) under all conditions of loads voltages and frequencies. The system is similar to that of the existing automobile, if only one motor is used: master controller-controller-motor-gears (fixed)-differential-wheels. In the case of two motors, the mechanical differential is replaced by an electric one: master controller-controller-motor-gears (fixed)-wheel. A four-wheel drive vehicle is obtained when four motors with their own controllers are used. 24 refs.« less

Socio-cognitive profiles for visual learning in young and older adults

PubMed Central

Christian, Julie; Goldstone, Aimee; Kuai, Shu-Guang; Chin, Wynne; Abrams, Dominic; Kourtzi, Zoe

2015-01-01

It is common wisdom that practice makes perfect; but why do some adults learn better than others? Here, we investigate individuals’ cognitive and social profiles to test which variables account for variability in learning ability across the lifespan. In particular, we focused on visual learning using tasks that test the ability to inhibit distractors and select task-relevant features. We tested the ability of young and older adults to improve through training in the discrimination of visual global forms embedded in a cluttered background. Further, we used a battery of cognitive tasks and psycho-social measures to examine which of these variables predict training-induced improvement in perceptual tasks and may account for individual variability in learning ability. Using partial least squares regression modeling, we show that visual learning is influenced by cognitive (i.e., cognitive inhibition, attention) and social (strategic and deep learning) factors rather than an individual’s age alone. Further, our results show that independent of age, strong learners rely on cognitive factors such as attention, while weaker learners use more general cognitive strategies. Our findings suggest an important role for higher-cognitive circuits involving executive functions that contribute to our ability to improve in perceptual tasks after training across the lifespan. PMID:26113820

Collective feature selection to identify crucial epistatic variants.

PubMed

Verma, Shefali S; Lucas, Anastasia; Zhang, Xinyuan; Veturi, Yogasudha; Dudek, Scott; Li, Binglan; Li, Ruowang; Urbanowicz, Ryan; Moore, Jason H; Kim, Dokyoon; Ritchie, Marylyn D

2018-01-01

Machine learning methods have gained popularity and practicality in identifying linear and non-linear effects of variants associated with complex disease/traits. Detection of epistatic interactions still remains a challenge due to the large number of features and relatively small sample size as input, thus leading to the so-called "short fat data" problem. The efficiency of machine learning methods can be increased by limiting the number of input features. Thus, it is very important to perform variable selection before searching for epistasis. Many methods have been evaluated and proposed to perform feature selection, but no single method works best in all scenarios. We demonstrate this by conducting two separate simulation analyses to evaluate the proposed collective feature selection approach. Through our simulation study we propose a collective feature selection approach to select features that are in the "union" of the best performing methods. We explored various parametric, non-parametric, and data mining approaches to perform feature selection. We choose our top performing methods to select the union of the resulting variables based on a user-defined percentage of variants selected from each method to take to downstream analysis. Our simulation analysis shows that non-parametric data mining approaches, such as MDR, may work best under one simulation criteria for the high effect size (penetrance) datasets, while non-parametric methods designed for feature selection, such as Ranger and Gradient boosting, work best under other simulation criteria. Thus, using a collective approach proves to be more beneficial for selecting variables with epistatic effects also in low effect size datasets and different genetic architectures. Following this, we applied our proposed collective feature selection approach to select the top 1% of variables to identify potential interacting variables associated with Body Mass Index (BMI) in ~ 44,000 samples obtained from Geisinger's MyCode Community Health Initiative (on behalf of DiscovEHR collaboration). In this study, we were able to show that selecting variables using a collective feature selection approach could help in selecting true positive epistatic variables more frequently than applying any single method for feature selection via simulation studies. We were able to demonstrate the effectiveness of collective feature selection along with a comparison of many methods in our simulation analysis. We also applied our method to identify non-linear networks associated with obesity.

Evolutionary and ecological consequences of multiscale variation in pollen receipt for seed production.

PubMed

Schreiber, Sebastian J; Rosenheim, Jay A; Williams, Neal W; Harder, Lawrence D

2015-01-01

Variation in resource availability can select for traits that reduce the negative impacts of this variability on mean fitness. Such selection may be particularly potent for seed production in flowering plants, as they often experience variation in pollen receipt among individuals and among flowers within individuals. Using analytically tractable models, we examine the optimal allocations for producing ovules, attracting pollen, and maturing seeds in deterministic and stochastic pollen environments. In deterministic environments, the optimal strategy attracts sufficient pollen to fertilize every ovule and mature every zygote into a seed. Stochastic environments select for allocations proportional to the risk of seed production being limited by zygotes or seed maturation. When producing an ovule is cheap and maturing a seed is expensive, among-plant variation selects for attracting more pollen at the expense of producing fewer ovules and having fewer resources for seed maturation. Despite this increased allocation, such populations are likely to be pollen limited. In contrast, within-plant variation generally selects for an overproduction of ovules and, to a lesser extent, pollen attraction. Such populations are likely to be resource limited and exhibit low seed-to-ovule ratios. These results highlight the importance of multiscale variation in the evolution and ecology of resource allocations.

No difference in variability of unique hue selections and binary hue selections.

PubMed

Bosten, J M; Lawrance-Owen, A J

2014-04-01

If unique hues have special status in phenomenological experience as perceptually pure, it seems reasonable to assume that they are represented more precisely by the visual system than are other colors. Following the method of Malkoc et al. (J. Opt. Soc. Am. A22, 2154 [2005]), we gathered unique and binary hue selections from 50 subjects. For these subjects we repeated the measurements in two separate sessions, allowing us to measure test-retest reliabilities (0.52≤ρ≤0.78; p≪0.01). We quantified the within-individual variability for selections of each hue. Adjusting for the differences in variability intrinsic to different regions of chromaticity space, we compared the within-individual variability for unique hues to that for binary hues. Surprisingly, we found that selections of unique hues did not show consistently lower variability than selections of binary hues. We repeated hue measurements in a single session for an independent sample of 58 subjects, using a different relative scaling of the cardinal axes of MacLeod-Boynton chromaticity space. Again, we found no consistent difference in adjusted within-individual variability for selections of unique and binary hues. Our finding does not depend on the particular scaling chosen for the Y axis of MacLeod-Boynton chromaticity space.

Using variable rate models to identify genes under selection in sequence pairs: their validity and limitations for EST sequences.

PubMed

Church, Sheri A; Livingstone, Kevin; Lai, Zhao; Kozik, Alexander; Knapp, Steven J; Michelmore, Richard W; Rieseberg, Loren H

2007-02-01

Using likelihood-based variable selection models, we determined if positive selection was acting on 523 EST sequence pairs from two lineages of sunflower and lettuce. Variable rate models are generally not used for comparisons of sequence pairs due to the limited information and the inaccuracy of estimates of specific substitution rates. However, previous studies have shown that the likelihood ratio test (LRT) is reliable for detecting positive selection, even with low numbers of sequences. These analyses identified 56 genes that show a signature of selection, of which 75% were not identified by simpler models that average selection across codons. Subsequent mapping studies in sunflower show four of five of the positively selected genes identified by these methods mapped to domestication QTLs. We discuss the validity and limitations of using variable rate models for comparisons of sequence pairs, as well as the limitations of using ESTs for identification of positively selected genes.

Variable screening via quantile partial correlation

PubMed Central

Ma, Shujie; Tsai, Chih-Ling

2016-01-01

In quantile linear regression with ultra-high dimensional data, we propose an algorithm for screening all candidate variables and subsequently selecting relevant predictors. Specifically, we first employ quantile partial correlation for screening, and then we apply the extended Bayesian information criterion (EBIC) for best subset selection. Our proposed method can successfully select predictors when the variables are highly correlated, and it can also identify variables that make a contribution to the conditional quantiles but are marginally uncorrelated or weakly correlated with the response. Theoretical results show that the proposed algorithm can yield the sure screening set. By controlling the false selection rate, model selection consistency can be achieved theoretically. In practice, we proposed using EBIC for best subset selection so that the resulting model is screening consistent. Simulation studies demonstrate that the proposed algorithm performs well, and an empirical example is presented. PMID:28943683