All-cause mortality of elderly Australian veterans using COX-2 selective or non-selective NSAIDs: a longitudinal study

PubMed Central

Kerr, Stephen J; Rowett, Debra S; Sayer, Geoffrey P; Whicker, Susan D; Saltman, Deborah C; Mant, Andrea

2011-01-01

AIM To determine hazard ratios for all-cause mortality in elderly Australian veterans taking COX-2 selective and non-selective NSAIDs. METHODS Patient cohorts were constructed from claims databases (1997 to 2007) for veterans and dependants with full treatment entitlement irrespective of military service. Patients were grouped by initial exposure: celecoxib, rofecoxib, meloxicam, diclofenac, non-selective NSAID. A reference group was constructed of patients receiving glaucoma/hypothyroid medications and none of the study medications. Univariate and multivariate analyses were performed using Cox proportional hazards regression models. Hazard ratios (HR) and 95% confidence intervals (CI) were estimated for each exposure group against each of the reference group. The final model was adjusted for age, gender and co-prescription as a surrogate for cardiovascular risk. Patients were censored if the gap in supply of study prescription exceeded 30 days or if another study medication was initiated. The outcome measure in all analyses was death. RESULTS Hazard ratios and 95% CIs, adjusted for age, gender and cardiovascular risk, for each group relative to the reference group were: celecoxib 1.39 (1.25, 1.55), diclofenac 1.44 (1.28, 1.62), meloxicam 1.49 (1.25, 1.78), rofecoxib 1.58 (1.39, 1.79), non-selective NSAIDs 1.76 (1.59, 1.94). CONCLUSIONS In this large cohort of Australian veterans exposed to COX-2 selective and non-selective NSAIDs, there was a significant increased mortality risk for those exposed to either COX-2-selective or non-selective NSAIDs relative to those exposed to unrelated (glaucoma/hypothyroid) medications. PMID:21276041

Multilevel selection in a resource-based model

NASA Astrophysics Data System (ADS)

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

2013-07-01

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

Design and Evaluation of Perceptual-based Object Group Selection Techniques

NASA Astrophysics Data System (ADS)

Dehmeshki, Hoda

Selecting groups of objects is a frequent task in graphical user interfaces. It is required prior to many standard operations such as deletion, movement, or modification. Conventional selection techniques are lasso, rectangle selection, and the selection and de-selection of items through the use of modifier keys. These techniques may become time-consuming and error-prone when target objects are densely distributed or when the distances between target objects are large. Perceptual-based selection techniques can considerably improve selection tasks when targets have a perceptual structure, for example when arranged along a line. Current methods to detect such groups use ad hoc grouping algorithms that are not based on results from perception science. Moreover, these techniques do not allow selecting groups with arbitrary arrangements or permit modifying a selection. This dissertation presents two domain-independent perceptual-based systems that address these issues. Based on established group detection models from perception research, the proposed systems detect perceptual groups formed by the Gestalt principles of good continuation and proximity. The new systems provide gesture-based or click-based interaction techniques for selecting groups with curvilinear or arbitrary structures as well as clusters. Moreover, the gesture-based system is adapted for the graph domain to facilitate path selection. This dissertation includes several user studies that show the proposed systems outperform conventional selection techniques when targets form salient perceptual groups and are still competitive when targets are semi-structured.

Covariate Selection for Multilevel Models with Missing Data

PubMed Central

Marino, Miguel; Buxton, Orfeu M.; Li, Yi

2017-01-01

Missing covariate data hampers variable selection in multilevel regression settings. Current variable selection techniques for multiply-imputed data commonly address missingness in the predictors through list-wise deletion and stepwise-selection methods which are problematic. Moreover, most variable selection methods are developed for independent linear regression models and do not accommodate multilevel mixed effects regression models with incomplete covariate data. We develop a novel methodology that is able to perform covariate selection across multiply-imputed data for multilevel random effects models when missing data is present. Specifically, we propose to stack the multiply-imputed data sets from a multiple imputation procedure and to apply a group variable selection procedure through group lasso regularization to assess the overall impact of each predictor on the outcome across the imputed data sets. Simulations confirm the advantageous performance of the proposed method compared with the competing methods. We applied the method to reanalyze the Healthy Directions-Small Business cancer prevention study, which evaluated a behavioral intervention program targeting multiple risk-related behaviors in a working-class, multi-ethnic population. PMID:28239457

Capturing the superorganism: a formal theory of group adaptation.

PubMed

Gardner, A; Grafen, A

2009-04-01

Adaptation is conventionally regarded as occurring at the level of the individual organism. However, in recent years there has been a revival of interest in the possibility for group adaptations and superorganisms. Here, we provide the first formal theory of group adaptation. In particular: (1) we clarify the distinction between group selection and group adaptation, framing the former in terms of gene frequency change and the latter in terms of optimization; (2) we capture the superorganism in the form of a 'group as maximizing agent' analogy that links an optimization program to a model of a group-structured population; (3) we demonstrate that between-group selection can lead to group adaptation, but only in rather special circumstances; (4) we provide formal support for the view that between-group selection is the best definition for 'group selection'; and (5) we reveal that mechanisms of conflict resolution such as policing cannot be regarded as group adaptations.

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.

Multilevel selection analysis of a microbial social trait

PubMed Central

de Vargas Roditi, Laura; Boyle, Kerry E; Xavier, Joao B

2013-01-01

The study of microbial communities often leads to arguments for the evolution of cooperation due to group benefits. However, multilevel selection models caution against the uncritical assumption that group benefits will lead to the evolution of cooperation. We analyze a microbial social trait to precisely define the conditions favoring cooperation. We combine the multilevel partition of the Price equation with a laboratory model system: swarming in Pseudomonas aeruginosa. We parameterize a population dynamics model using competition experiments where we manipulate expression, and therefore the cost-to-benefit ratio of swarming cooperation. Our analysis shows that multilevel selection can favor costly swarming cooperation because it causes population expansion. However, due to high costs and diminishing returns constitutive cooperation can only be favored by natural selection when relatedness is high. Regulated expression of cooperative genes is a more robust strategy because it provides the benefits of swarming expansion without the high cost or the diminishing returns. Our analysis supports the key prediction that strong group selection does not necessarily mean that microbial cooperation will always emerge. PMID:23959025

Models Used to Select Strategic Planning Experts for High Technology Productions

NASA Astrophysics Data System (ADS)

Zakharova, Alexandra A.; Grigorjeva, Antonina A.; Tseplit, Anna P.; Ozgogov, Evgenij V.

2016-04-01

The article deals with the problems and specific aspects in organizing works of experts involved in assessment of companies that manufacture complex high-technology products. A model is presented that is intended for evaluating competences of experts in individual functional areas of expertise. Experts are selected to build a group on the basis of tables used to determine a competence level. An expert selection model based on fuzzy logic is proposed and additional requirements for the expert group composition can be taken into account, with regard to the needed quality and competence related preferences of decision-makers. A Web-based information system model is developed for the interaction between experts and decision-makers when carrying out online examinations.

Linguistic Multi-Attribute Group Decision Making with Risk Preferences and Its Use in Low-Carbon Tourism Destination Selection.

PubMed

Lin, Hui; Wang, Zhou-Jing

2017-09-17

Low-carbon tourism plays an important role in carbon emission reduction and environmental protection. Low-carbon tourism destination selection often involves multiple conflicting and incommensurate attributes or criteria and can be modelled as a multi-attribute decision-making problem. This paper develops a framework to solve multi-attribute group decision-making problems, where attribute evaluation values are provided as linguistic terms and the attribute weight information is incomplete. In order to obtain a group risk preference captured by a linguistic term set with triangular fuzzy semantic information, a nonlinear programming model is established on the basis of individual risk preferences. We first convert individual linguistic-term-based decision matrices to their respective triangular fuzzy decision matrices, which are then aggregated into a group triangular fuzzy decision matrix. Based on this group decision matrix and the incomplete attribute weight information, a linear program is developed to find an optimal attribute weight vector. A detailed procedure is devised for tackling linguistic multi-attribute group decision making problems. A low-carbon tourism destination selection case study is offered to illustrate how to use the developed group decision-making model in practice.

Linguistic Multi-Attribute Group Decision Making with Risk Preferences and Its Use in Low-Carbon Tourism Destination Selection

PubMed Central

Lin, Hui; Wang, Zhou-Jing

2017-01-01

Low-carbon tourism plays an important role in carbon emission reduction and environmental protection. Low-carbon tourism destination selection often involves multiple conflicting and incommensurate attributes or criteria and can be modelled as a multi-attribute decision-making problem. This paper develops a framework to solve multi-attribute group decision-making problems, where attribute evaluation values are provided as linguistic terms and the attribute weight information is incomplete. In order to obtain a group risk preference captured by a linguistic term set with triangular fuzzy semantic information, a nonlinear programming model is established on the basis of individual risk preferences. We first convert individual linguistic-term-based decision matrices to their respective triangular fuzzy decision matrices, which are then aggregated into a group triangular fuzzy decision matrix. Based on this group decision matrix and the incomplete attribute weight information, a linear program is developed to find an optimal attribute weight vector. A detailed procedure is devised for tackling linguistic multi-attribute group decision making problems. A low-carbon tourism destination selection case study is offered to illustrate how to use the developed group decision-making model in practice. PMID:28926985

Interpersonal and group processes in long-term spaceflight crews: perspectives from social and organizational psychology.

PubMed

Dion, Kenneth L

2004-07-01

The issues of interpersonal and group processes in long-term spacecrews from the perspectives of social and organizational psychology are considered here. A contrast between the Amundsen vs. Scott expeditions to the South Pole 90 yrs. ago highlights the importance of personnel selection and attention to interpersonal and group dynamics in expeditions to extreme and dangerous environments, such as long-term spaceflights today. Under the rubric of personnel selection, some further psychological "select-in" and "select-out" criteria are suggested, among them implicit measures of human motivation, intergroup attitudes ("implicit" and "explicit" measures of prejudice, social dominance orientation, and right-wing authoritarianism), attachment styles, and dispositional hardiness. The situational interview and the idea of "selection for teams," drawn from current advances in organizational psychology, are recommended for selecting members for future spacecrews. Under the rubrics of interpersonal and group processes, the social relations model is introduced as a technique for modeling and understanding interdependence among spacecrew members and partialling out variance in behavioral and perceptual data into actor/perceiver, partner/target, and relationship components. Group cohesion as a multidimensional construct is introduced, along with a consideration of the groupthink phenomenon and its controversial link to cohesion. Group composition issues are raised with examples concerning cultural heterogeneity and gender composition. Cultural value dimensions, especially power distance and individual-collectivism, should be taken into account at both societal and psychological levels in long-term space missions. Finally, intergroup processes and language issues in crews are addressed. The recategorization induction from the common ingroup identity model is recommended as a possible intervention for overcoming and inhibiting intergroup biases within spacecrews and between space- and groundcrews.

Concave 1-norm group selection

PubMed Central

Jiang, Dingfeng; Huang, Jian

2015-01-01

Grouping structures arise naturally in many high-dimensional problems. Incorporation of such information can improve model fitting and variable selection. Existing group selection methods, such as the group Lasso, require correct membership. However, in practice it can be difficult to correctly specify group membership of all variables. Thus, it is important to develop group selection methods that are robust against group mis-specification. Also, it is desirable to select groups as well as individual variables in many applications. We propose a class of concave \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}$1$\\end{document}-norm group penalties that is robust to grouping structure and can perform bi-level selection. A coordinate descent algorithm is developed to calculate solutions of the proposed group selection method. Theoretical convergence of the algorithm is proved under certain regularity conditions. Comparison with other methods suggests the proposed method is the most robust approach under membership mis-specification. Simulation studies and real data application indicate that the \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}$1$\\end{document}-norm concave group selection approach achieves better control of false discovery rates. An R package grppenalty implementing the proposed method is available at CRAN. PMID:25417206

A Darwinian approach to the origin of life cycles with group properties.

PubMed

Rashidi, Armin; Shelton, Deborah E; Michod, Richard E

2015-06-01

A selective explanation for the evolution of multicellular organisms from unicellular ones requires knowledge of both selective pressures and factors affecting the response to selection. Understanding the response to selection is particularly challenging in the case of evolutionary transitions in individuality, because these transitions involve a shift in the very units of selection. We develop a conceptual framework in which three fundamental processes (growth, division, and splitting) are the scaffold for unicellular and multicellular life cycles alike. We (i) enumerate the possible ways in which these processes can be linked to create more complex life cycles, (ii) introduce three genes based on growth, division and splitting that, acting in concert, determine the architecture of the life cycles, and finally, (iii) study the evolution of the simplest five life cycles using a heuristic model of coupled ordinary differential equations in which mutations are allowed in the three genes. We demonstrate how changes in the regulation of three fundamental aspects of colonial form (cell size, colony size, and colony cell number) could lead unicellular life cycles to evolve into primitive multicellular life cycles with group properties. One interesting prediction of the model is that selection generally favors cycles with group level properties when intermediate body size is associated with lowest mortality. That is, a universal requirement for the evolution of group cycles in the model is that the size-mortality curve be U-shaped. Furthermore, growth must decelerate with size. Copyright © 2015 Elsevier Inc. All rights reserved.

Weak cation magnetic separation technology and MALDI-TOF-MS in screening serum protein markers in primary type I osteoporosis.

PubMed

Shi, X L; Li, C W; Liang, B C; He, K H; Li, X Y

2015-11-30

We investigated weak cation magnetic separation technology and matrix-assisted laser desorption ionization-time of flight-mass spectrometry (MALDI-TOF-MS) in screening serum protein markers of primary type I osteoporosis. We selected 16 postmenopausal women with osteoporosis and nine postmenopausal women as controls to find a new method for screening biomarkers and establishing a diagnostic model for primary type I osteoporosis. Serum samples were obtained from controls and patients. Serum protein was extracted with the WCX protein chip system; protein fingerprints were examined using MALDI-TOF-MS. The preprocessed and model construction data were handled by the ProteinChip system. The diagnostic models were established using a genetic arithmetic model combined with a support vector machine (SVM). The SVM model with the highest Youden index was selected. Combinations with the highest accuracy in distinguishing different groups of data were selected as potential biomarkers. From the two groups of serum proteins, 123 cumulative MS protein peaks were selected. Significant intensity differences in the protein peaks of 16 postmenopausal women with osteoporosis were screened. The difference in Youden index between the four groups of protein peaks showed that the highest peaks had mass-to-charge ratios of 8909.047, 8690.658, 13745.48, and 15114.52. A diagnosis model was established with these four markers as the candidates, and the model specificity and sensitivity were found to be 100%. Two groups of specimens in the SVM results on the scatterplot were distinguishable. We established a diagnosis model, and provided a new serological method for screening and diagnosis of osteoporosis with high sensitivity and specificity.

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

PubMed

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

2014-05-01

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

Language change in a multiple group society

NASA Astrophysics Data System (ADS)

Pop, Cristina-Maria; Frey, Erwin

2013-08-01

The processes leading to change in languages are manifold. In order to reduce ambiguity in the transmission of information, agreement on a set of conventions for recurring problems is favored. In addition to that, speakers tend to use particular linguistic variants associated with the social groups they identify with. The influence of other groups propagating across the speech community as new variant forms sustains the competition between linguistic variants. With the utterance selection model, an evolutionary description of language change, Baxter [Phys. Rev. EPLEEE81539-375510.1103/PhysRevE.73.046118 73, 046118 (2006)] have provided a mathematical formulation of the interactions inside a group of speakers, exploring the mechanisms that lead to or inhibit the fixation of linguistic variants. In this paper, we take the utterance selection model one step further by describing a speech community consisting of multiple interacting groups. Tuning the interaction strength between groups allows us to gain deeper understanding about the way in which linguistic variants propagate and how their distribution depends on the group partitioning. Both for the group size and the number of groups we find scaling behaviors with two asymptotic regimes. If groups are strongly connected, the dynamics is that of the standard utterance selection model, whereas if their coupling is weak, the magnitude of the latter along with the system size governs the way consensus is reached. Furthermore, we find that a high influence of the interlocutor on a speaker's utterances can act as a counterweight to group segregation.

A model for selecting leadership styles.

PubMed

Perkins, V J

1992-01-01

Occupational therapists lead a variety of groups during their professional activities. Such groups include therapy groups, treatment teams and management meetings. Therefore it is important for each therapist to understand theories of leadership and be able to select the most effective style for him or herself in specific situations. This paper presents a review of leadership theory and research as well as therapeutic groups. It then integrates these areas to assist students and new therapists in identifying a style that is effective for a particular group.

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

PubMed

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

2017-10-01

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

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

PubMed

Akram, Nuzhat A; Farooqi, Shakeel R

2014-01-01

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

Covariate selection with group lasso and doubly robust estimation of causal effects

PubMed Central

Koch, Brandon; Vock, David M.; Wolfson, Julian

2017-01-01

Summary The efficiency of doubly robust estimators of the average causal effect (ACE) of a treatment can be improved by including in the treatment and outcome models only those covariates which are related to both treatment and outcome (i.e., confounders) or related only to the outcome. However, it is often challenging to identify such covariates among the large number that may be measured in a given study. In this paper, we propose GLiDeR (Group Lasso and Doubly Robust Estimation), a novel variable selection technique for identifying confounders and predictors of outcome using an adaptive group lasso approach that simultaneously performs coefficient selection, regularization, and estimation across the treatment and outcome models. The selected variables and corresponding coefficient estimates are used in a standard doubly robust ACE estimator. We provide asymptotic results showing that, for a broad class of data generating mechanisms, GLiDeR yields a consistent estimator of the ACE when either the outcome or treatment model is correctly specified. A comprehensive simulation study shows that GLiDeR is more efficient than doubly robust methods using standard variable selection techniques and has substantial computational advantages over a recently proposed doubly robust Bayesian model averaging method. We illustrate our method by estimating the causal treatment effect of bilateral versus single-lung transplant on forced expiratory volume in one year after transplant using an observational registry. PMID:28636276

Covariate selection with group lasso and doubly robust estimation of causal effects.

PubMed

Koch, Brandon; Vock, David M; Wolfson, Julian

2018-03-01

The efficiency of doubly robust estimators of the average causal effect (ACE) of a treatment can be improved by including in the treatment and outcome models only those covariates which are related to both treatment and outcome (i.e., confounders) or related only to the outcome. However, it is often challenging to identify such covariates among the large number that may be measured in a given study. In this article, we propose GLiDeR (Group Lasso and Doubly Robust Estimation), a novel variable selection technique for identifying confounders and predictors of outcome using an adaptive group lasso approach that simultaneously performs coefficient selection, regularization, and estimation across the treatment and outcome models. The selected variables and corresponding coefficient estimates are used in a standard doubly robust ACE estimator. We provide asymptotic results showing that, for a broad class of data generating mechanisms, GLiDeR yields a consistent estimator of the ACE when either the outcome or treatment model is correctly specified. A comprehensive simulation study shows that GLiDeR is more efficient than doubly robust methods using standard variable selection techniques and has substantial computational advantages over a recently proposed doubly robust Bayesian model averaging method. We illustrate our method by estimating the causal treatment effect of bilateral versus single-lung transplant on forced expiratory volume in one year after transplant using an observational registry. © 2017, The International Biometric Society.

A unified framework for group independent component analysis for multi-subject fMRI data

PubMed Central

Guo, Ying; Pagnoni, Giuseppe

2008-01-01

Independent component analysis (ICA) is becoming increasingly popular for analyzing functional magnetic resonance imaging (fMRI) data. While ICA has been successfully applied to single-subject analysis, the extension of ICA to group inferences is not straightforward and remains an active topic of research. Current group ICA models, such as the GIFT (Calhoun et al., 2001) and tensor PICA (Beckmann and Smith, 2005), make different assumptions about the underlying structure of the group spatio-temporal processes and are thus estimated using algorithms tailored for the assumed structure, potentially leading to diverging results. To our knowledge, there are currently no methods for assessing the validity of different model structures in real fMRI data and selecting the most appropriate one among various choices. In this paper, we propose a unified framework for estimating and comparing group ICA models with varying spatio-temporal structures. We consider a class of group ICA models that can accommodate different group structures and include existing models, such as the GIFT and tensor PICA, as special cases. We propose a maximum likelihood (ML) approach with a modified Expectation-Maximization (EM) algorithm for the estimation of the proposed class of models. Likelihood ratio tests (LRT) are presented to compare between different group ICA models. The LRT can be used to perform model comparison and selection, to assess the goodness-of-fit of a model in a particular data set, and to test group differences in the fMRI signal time courses between subject subgroups. Simulation studies are conducted to evaluate the performance of the proposed method under varying structures of group spatio-temporal processes. We illustrate our group ICA method using data from an fMRI study that investigates changes in neural processing associated with the regular practice of Zen meditation. PMID:18650105

Prediction of Depression in Cancer Patients With Different Classification Criteria, Linear Discriminant Analysis versus Logistic Regression.

PubMed

Shayan, Zahra; Mohammad Gholi Mezerji, Naser; Shayan, Leila; Naseri, Parisa

2015-11-03

Logistic regression (LR) and linear discriminant analysis (LDA) are two popular statistical models for prediction of group membership. Although they are very similar, the LDA makes more assumptions about the data. When categorical and continuous variables used simultaneously, the optimal choice between the two models is questionable. In most studies, classification error (CE) is used to discriminate between subjects in several groups, but this index is not suitable to predict the accuracy of the outcome. The present study compared LR and LDA models using classification indices. This cross-sectional study selected 243 cancer patients. Sample sets of different sizes (n = 50, 100, 150, 200, 220) were randomly selected and the CE, B, and Q classification indices were calculated by the LR and LDA models. CE revealed the a lack of superiority for one model over the other, but the results showed that LR performed better than LDA for the B and Q indices in all situations. No significant effect for sample size on CE was noted for selection of an optimal model. Assessment of the accuracy of prediction of real data indicated that the B and Q indices are appropriate for selection of an optimal model. The results of this study showed that LR performs better in some cases and LDA in others when based on CE. The CE index is not appropriate for classification, although the B and Q indices performed better and offered more efficient criteria for comparison and discrimination between groups.

The effects of a technology-enhanced inquiry instructional model on students' understanding of science in Thailand

NASA Astrophysics Data System (ADS)

Lertwanasiriwan, Chaiwuti

The study examined the effects of a technology-enhanced inquiry instructional model on students' understanding of science in Thailand. A mixed quantitative research design was selected for the research design. A pretest-posttest control-group design was implemented for the experimental research. A causal-comparative design using questionnaire and classroom observation was employed for the non-experimental research. Two sixth-grade classrooms at a medium-sized public school in Bangkok, Thailand were randomly selected for the study - one as the control group and the other as the experimental group. The 34 students in the control group only received the inquiry instructional model, while the 35 students in the experimental group received the technology-enhanced inquiry instructional model. Both groups of students had been taught by the same science teacher for 15 weeks (three periods per week). The results and findings from the study seemed to indicate that both the technology-enhanced inquiry instructional model and the inquiry instructional model significantly improve students' understanding of science. However, it might be claimed that students receiving the technology-enhanced inquiry instructional model gain more than students only receiving the inquiry instructional model. In addition, the technology-enhanced inquiry instructional model seemed to support the assessment during the 5E Model's evaluation stage. Most students appeared to have very good attitudes toward using it in the science classroom suggesting that the technology-enhanced inquiry instructional model motivates students to learn science.

A quantitative genetic model of reciprocal altruism: a condition for kin or group selection to prevail.

PubMed Central

Aoki, K

1983-01-01

A condition is derived for reciprocal altruism to evolve by kin or group selection. It is assumed that many additively acting genes of small effect and the environment determine the probability that an individual is a reciprocal altruist, as opposed to being unconditionally selfish. The particular form of reciprocal altruism considered is TIT FOR TAT, a strategy that involves being altruistic on the first encounter with another individual and doing whatever the other did on the previous encounter in subsequent encounters with the same individual. Encounters are restricted to individuals of the same generation belonging to the same kin or breeding group, but first encounters occur at random within that group. The number of individuals with which an individual interacts is assumed to be the same within any kin or breeding group. There are 1 + i expected encounters between two interacting individuals. On any encounter, it is assumed that an individual who behaves altruistically suffers a cost in personal fitness proportional to c while improving his partner's fitness by the same proportion of b. Then, the condition for kin or group selection to prevail is [Formula: see text] if group size is sufficiently large and the group mean and the within-group genotypic variance of the trait value (i.e., the probability of being a TIT-FOR-TAT strategist) are uncorrelated. Here, C, Vb, and Tb are the population mean, between-group variance, and between-group third central moment of the trait value and r is the correlation between the additive genotypic values of interacting kin or of individuals within the same breeding group. The right-hand side of the above inequality is monotone decreasing in C if we hold Tb/Vb constant, and kin and group selection become superfluous beyond a certain threshold value of C. The effect of finite group size is also considered in a kin-selection model. PMID:6575395

Application of random effects to the study of resource selection by animals

USGS Publications Warehouse

Gillies, C.S.; Hebblewhite, M.; Nielsen, S.E.; Krawchuk, M.A.; Aldridge, Cameron L.; Frair, J.L.; Saher, D.J.; Stevens, C.E.; Jerde, C.L.

2006-01-01

1. Resource selection estimated by logistic regression is used increasingly in studies to identify critical resources for animal populations and to predict species occurrence.2. Most frequently, individual animals are monitored and pooled to estimate population-level effects without regard to group or individual-level variation. Pooling assumes that both observations and their errors are independent, and resource selection is constant given individual variation in resource availability.3. Although researchers have identified ways to minimize autocorrelation, variation between individuals caused by differences in selection or available resources, including functional responses in resource selection, have not been well addressed.4. Here we review random-effects models and their application to resource selection modelling to overcome these common limitations. We present a simple case study of an analysis of resource selection by grizzly bears in the foothills of the Canadian Rocky Mountains with and without random effects.5. Both categorical and continuous variables in the grizzly bear model differed in interpretation, both in statistical significance and coefficient sign, depending on how a random effect was included. We used a simulation approach to clarify the application of random effects under three common situations for telemetry studies: (a) discrepancies in sample sizes among individuals; (b) differences among individuals in selection where availability is constant; and (c) differences in availability with and without a functional response in resource selection.6. We found that random intercepts accounted for unbalanced sample designs, and models with random intercepts and coefficients improved model fit given the variation in selection among individuals and functional responses in selection. Our empirical example and simulations demonstrate how including random effects in resource selection models can aid interpretation and address difficult assumptions limiting their generality. This approach will allow researchers to appropriately estimate marginal (population) and conditional (individual) responses, and account for complex grouping, unbalanced sample designs and autocorrelation.

Application of random effects to the study of resource selection by animals.

PubMed

Gillies, Cameron S; Hebblewhite, Mark; Nielsen, Scott E; Krawchuk, Meg A; Aldridge, Cameron L; Frair, Jacqueline L; Saher, D Joanne; Stevens, Cameron E; Jerde, Christopher L

2006-07-01

1. Resource selection estimated by logistic regression is used increasingly in studies to identify critical resources for animal populations and to predict species occurrence. 2. Most frequently, individual animals are monitored and pooled to estimate population-level effects without regard to group or individual-level variation. Pooling assumes that both observations and their errors are independent, and resource selection is constant given individual variation in resource availability. 3. Although researchers have identified ways to minimize autocorrelation, variation between individuals caused by differences in selection or available resources, including functional responses in resource selection, have not been well addressed. 4. Here we review random-effects models and their application to resource selection modelling to overcome these common limitations. We present a simple case study of an analysis of resource selection by grizzly bears in the foothills of the Canadian Rocky Mountains with and without random effects. 5. Both categorical and continuous variables in the grizzly bear model differed in interpretation, both in statistical significance and coefficient sign, depending on how a random effect was included. We used a simulation approach to clarify the application of random effects under three common situations for telemetry studies: (a) discrepancies in sample sizes among individuals; (b) differences among individuals in selection where availability is constant; and (c) differences in availability with and without a functional response in resource selection. 6. We found that random intercepts accounted for unbalanced sample designs, and models with random intercepts and coefficients improved model fit given the variation in selection among individuals and functional responses in selection. Our empirical example and simulations demonstrate how including random effects in resource selection models can aid interpretation and address difficult assumptions limiting their generality. This approach will allow researchers to appropriately estimate marginal (population) and conditional (individual) responses, and account for complex grouping, unbalanced sample designs and autocorrelation.

Estimation of pyrethroid pesticide intake using regression modeling of food groups based on composite dietary samples

EPA Science Inventory

Population-based estimates of pesticide intake are needed to characterize exposure for particular demographic groups based on their dietary behaviors. Regression modeling performed on measurements of selected pesticides in composited duplicate diet samples allowed (1) estimation ...

Estimation of pyrethroid pesticide intake using regression modeling of food groups based on composite dietary samples..

EPA Science Inventory

Population-based estimates of pesticide intake are needed to characterize exposure for particular demographic groups based on their dietary behaviors. Regression modeling performed on measurements of selected pesticides in composited duplicate diet samples allowed (1) estimation ...

Estimation of pyrethroid pesticide intake using regression modeling of food groups based on composite dietary samples.

EPA Science Inventory

Population-based estimates of pesticide intake are needed to characterize exposure for particular demographic groups based on their dietary behaviors. Regression modeling performed on measurements of selected pesticides in composited duplicate diet samples allowed (1) estimation ...

Two methods for parameter estimation using multiple-trait models and beef cattle field data.

PubMed

Bertrand, J K; Kriese, L A

1990-08-01

Two methods are presented for estimating variances and covariances from beef cattle field data using multiple-trait sire models. Both methods require that the first trait have no missing records and that the contemporary groups for the second trait be subsets of the contemporary groups for the first trait; however, the second trait may have missing records. One method uses pseudo expectations involving quadratics composed of the solutions and the right-hand sides of the mixed model equations. The other method is an extension of Henderson's Simple Method to the multiple trait case. Neither of these methods requires any inversions of large matrices in the computation of the parameters; therefore, both methods can handle very large sets of data. Four simulated data sets were generated to evaluate the methods. In general, both methods estimated genetic correlations and heritabilities that were close to the Restricted Maximum Likelihood estimates and the true data set values, even when selection within contemporary groups was practiced. The estimates of residual correlations by both methods, however, were biased by selection. These two methods can be useful in estimating variances and covariances from multiple-trait models in large populations that have undergone a minimal amount of selection within contemporary groups.

A Multi Criteria Group Decision-Making Model for Teacher Evaluation in Higher Education Based on Cloud Model and Decision Tree

ERIC Educational Resources Information Center

Chang, Ting-Cheng; Wang, Hui

2016-01-01

This paper proposes a cloud multi-criteria group decision-making model for teacher evaluation in higher education which is involving subjectivity, imprecision and fuzziness. First, selecting the appropriate evaluation index depending on the evaluation objectives, indicating a clear structural relationship between the evaluation index and…

Introducing the fit-criteria assessment plot - A visualisation tool to assist class enumeration in group-based trajectory modelling.

PubMed

Klijn, Sven L; Weijenberg, Matty P; Lemmens, Paul; van den Brandt, Piet A; Lima Passos, Valéria

2017-10-01

Background and objective Group-based trajectory modelling is a model-based clustering technique applied for the identification of latent patterns of temporal changes. Despite its manifold applications in clinical and health sciences, potential problems of the model selection procedure are often overlooked. The choice of the number of latent trajectories (class-enumeration), for instance, is to a large degree based on statistical criteria that are not fail-safe. Moreover, the process as a whole is not transparent. To facilitate class enumeration, we introduce a graphical summary display of several fit and model adequacy criteria, the fit-criteria assessment plot. Methods An R-code that accepts universal data input is presented. The programme condenses relevant group-based trajectory modelling output information of model fit indices in automated graphical displays. Examples based on real and simulated data are provided to illustrate, assess and validate fit-criteria assessment plot's utility. Results Fit-criteria assessment plot provides an overview of fit criteria on a single page, placing users in an informed position to make a decision. Fit-criteria assessment plot does not automatically select the most appropriate model but eases the model assessment procedure. Conclusions Fit-criteria assessment plot is an exploratory, visualisation tool that can be employed to assist decisions in the initial and decisive phase of group-based trajectory modelling analysis. Considering group-based trajectory modelling's widespread resonance in medical and epidemiological sciences, a more comprehensive, easily interpretable and transparent display of the iterative process of class enumeration may foster group-based trajectory modelling's adequate use.

Simultaneous grouping pursuit and feature selection over an undirected graph*

PubMed Central

Zhu, Yunzhang; Shen, Xiaotong; Pan, Wei

2013-01-01

Summary In high-dimensional regression, grouping pursuit and feature selection have their own merits while complementing each other in battling the curse of dimensionality. To seek a parsimonious model, we perform simultaneous grouping pursuit and feature selection over an arbitrary undirected graph with each node corresponding to one predictor. When the corresponding nodes are reachable from each other over the graph, regression coefficients can be grouped, whose absolute values are the same or close. This is motivated from gene network analysis, where genes tend to work in groups according to their biological functionalities. Through a nonconvex penalty, we develop a computational strategy and analyze the proposed method. Theoretical analysis indicates that the proposed method reconstructs the oracle estimator, that is, the unbiased least squares estimator given the true grouping, leading to consistent reconstruction of grouping structures and informative features, as well as to optimal parameter estimation. Simulation studies suggest that the method combines the benefit of grouping pursuit with that of feature selection, and compares favorably against its competitors in selection accuracy and predictive performance. An application to eQTL data is used to illustrate the methodology, where a network is incorporated into analysis through an undirected graph. PMID:24098061

State of the Art Methodology for the Design and Analysis of Future Large Scale Evaluations: A Selective Examination.

ERIC Educational Resources Information Center

Burstein, Leigh

Two specific methods of analysis in large-scale evaluations are considered: structural equation modeling and selection modeling/analysis of non-equivalent control group designs. Their utility in large-scale educational program evaluation is discussed. The examination of these methodological developments indicates how people (evaluators,…

The Effects of Selection Strategies for Bivariate Loglinear Smoothing Models on NEAT Equating Functions

ERIC Educational Resources Information Center

Moses, Tim; Holland, Paul W.

2010-01-01

In this study, eight statistical strategies were evaluated for selecting the parameterizations of loglinear models for smoothing the bivariate test score distributions used in nonequivalent groups with anchor test (NEAT) equating. Four of the strategies were based on significance tests of chi-square statistics (Likelihood Ratio, Pearson,…

Is portion size selection associated with expected satiation, perceived healthfulness or expected tastiness? A case study on pizza using a photograph-based computer task.

PubMed

Labbe, D; Rytz, A; Godinot, N; Ferrage, A; Martin, N

2017-01-01

Increasing portion sizes over the last 30 years are considered to be one of the factors underlying overconsumption. Past research on the drivers of portion selection for foods showed that larger portions are selected for foods delivering low expected satiation. However, the respective contribution of expected satiation vs. two other potential drivers of portion size selection, i.e. perceived healthfulness and expected tastiness, has never been explored. In this study, we conjointly explored the role of expected satiation, perceived healthfulness and expected tastiness when selecting portions within a range of six commercial pizzas varying in their toppings and brands. For each product, 63 pizza consumers selected a portion size that would satisfy them for lunch and scored their expected satiation, perceived healthfulness and expected tastiness. As six participants selected an entire pizza as ideal portion independently of topping or brand, their data sets were not considered in the data analyses completed on responses from 57 participants. Hierarchical multiple regression analyses showed that portion size variance was predicted by perceived healthiness and expected tastiness variables. Two sub-groups of participants with different portion size patterns across pizzas were identified through post-hoc exploratory analysis. The explanatory power of the regression model was significantly improved by adding interaction terms between sub-group and expected satiation variables and between sub-group and perceived healthfulness variables to the model. Analysis at a sub-group level showed either positive or negative association between portion size and expected satiation depending on sub-groups. For one group, portion size selection was more health-driven and for the other, more hedonic-driven. These results showed that even when considering a well-liked product category, perceived healthfulness can be an important factor influencing portion size decision. Copyright © 2016 Nestec S.A. Published by Elsevier Ltd.. All rights reserved.

Evolution of Swarming Behavior Is Shaped by How Predators Attack.

PubMed

Olson, Randal S; Knoester, David B; Adami, Christoph

2016-01-01

Animal grouping behaviors have been widely studied due to their implications for understanding social intelligence, collective cognition, and potential applications in engineering, artificial intelligence, and robotics. An important biological aspect of these studies is discerning which selection pressures favor the evolution of grouping behavior. In the past decade, researchers have begun using evolutionary computation to study the evolutionary effects of these selection pressures in predator-prey models. The selfish herd hypothesis states that concentrated groups arise because prey selfishly attempt to place their conspecifics between themselves and the predator, thus causing an endless cycle of movement toward the center of the group. Using an evolutionary model of a predator-prey system, we show that how predators attack is critical to the evolution of the selfish herd. Following this discovery, we show that density-dependent predation provides an abstraction of Hamilton's original formulation of domains of danger. Finally, we verify that density-dependent predation provides a sufficient selective advantage for prey to evolve the selfish herd in response to predation by coevolving predators. Thus, our work corroborates Hamilton's selfish herd hypothesis in a digital evolutionary model, refines the assumptions of the selfish herd hypothesis, and generalizes the domain of danger concept to density-dependent predation.

Prevention of Pulmonary Fibrosis via Trichostatin A (TSA) in Bleomycin Induced Rats.

PubMed

Ye, Qing; Li, Yanqin; Jiang, Handong; Xiong, Jianfei; Xu, Jiabo; Qin, Hui; Liu, Bin

2014-10-20

To investigate the effects of non selective histone deacetylase inhibitors Trichostatin A (TSA)on bleomycin-induced pulmonary fibrosis. To investigate the effects of non selective histone deacetylase inhibitors Trichostatin A ( TSA ) on HDAC2, p-SMAD2, HDAC2 mRNA, SMAD2mRNA in pulmonary fibrosis rats and investigate impossible mechanism. 46 SPF level male SD rats were randomly divided into four groups: ten for normal control group, fourteen for model control group I, twelve for model control group II and ten for treatment group. Rat pulmonary fibrosis was induced by bleomycin(5mg/kg) via single intratracheal perfusion in the two model control groups and treatment group. Normal control mice were instilled with a corresponding volume of 0.9% saline intratracheally. Treatment group was treated by the dilution of TSA 2mg/kg DMSO 60ul and0.9% saline 1.2ml intraperitoneal injection from the next day ,once a day for three days. Model control group II was treated by the dilution of DMSO 60ul and0.9% saline 1.2ml intraperitoneal injection from the next day once a day for three days. Model control group I and normal control group were treated by 0.9% saline 1.2ml intraperitoneal injection from the next day once a day for three days. All the animals were sacrificed on the 21 day after modeling. The pathological changes were observed by hematoxylin and eosin(HE)stain and masson trichrome stain. The expression of HDAC2 mRNA,SMAD2 mRNA were measured by real-time PCR. The protein level of HDAC2 and p-SMAD2 in serum was measured by Western blot. The pulmonary fibrosis in treatment group were significantly alleviated compared to the two model control groups (P<0.05). Real-time PCR showed that the treatment group had lower expression of lung tissue HDAC2 mRNA than the two model control groups and normal control group (P<0.05). The expression of lung tissue SMAD2 mRNA increased in the two model control groups and treatment group (P<0.05),but there were no significant differences among the three groups(P>0.05). Western blot indicated that the protein level of HDAC2 and p-SMAD2 in serum increased in the two model control groups compared with normal control group(P<0.05).But treatment group had lower protein level of HDAC2 (P<0.05) and no significant difference in the protein level of p-SMAD2 compared to the two model control groups (P>0.05). Non selective histone deacetylase inhibitors of Trichostatin A (TSA) can reduce the bleomycin induced pulmonary fibrosis in rats. TSA attenuates pulmonary fibrosis and it can inhibit HDAC2 expression at the gene and protein level. Bleomycin induced fibrosis has the relationship with p-SMAD2 in gene and protein levels, but TSA inhibit bleomycin-induced lung fibrosis effect with no relation with SMAD2 phosphorylation pathways.

Using multilevel models to quantify heterogeneity in resource selection

USGS Publications Warehouse

Wagner, Tyler; Diefenbach, Duane R.; Christensen, Sonja; Norton, Andrew S.

2011-01-01

Models of resource selection are being used increasingly to predict or model the effects of management actions rather than simply quantifying habitat selection. Multilevel, or hierarchical, models are an increasingly popular method to analyze animal resource selection because they impose a relatively weak stochastic constraint to model heterogeneity in habitat use and also account for unequal sample sizes among individuals. However, few studies have used multilevel models to model coefficients as a function of predictors that may influence habitat use at different scales or quantify differences in resource selection among groups. We used an example with white-tailed deer (Odocoileus virginianus) to illustrate how to model resource use as a function of distance to road that varies among deer by road density at the home range scale. We found that deer avoidance of roads decreased as road density increased. Also, we used multilevel models with sika deer (Cervus nippon) and white-tailed deer to examine whether resource selection differed between species. We failed to detect differences in resource use between these two species and showed how information-theoretic and graphical measures can be used to assess how resource use may have differed. Multilevel models can improve our understanding of how resource selection varies among individuals and provides an objective, quantifiable approach to assess differences or changes in resource selection.

Self-organization and natural selection in the evolution of complex despotic societies.

PubMed

Hemelrijk, C K

2002-06-01

Differences between related species are usually explained as separate adaptations produced by individual selection. I discuss in this paper how related species, which differ in many respects, may evolve by a combination of individual selection, self-organization, and group-selection, requiring an evolutionary adaptation of only a single trait. In line with the supposed evolution of despotic species of macaques, we take as a starting point an ancestral species that is egalitarian and mildly aggressive. We suppose it to live in an environment with abundant food and we put the case that, if food becomes scarce and more clumped, natural selection at the level of the individual will favor individuals with a more intense aggression (implying, for instance, biting and fierce fighting). Using an individual-centered model, called DomWorld, I show what happens when the intensity of aggression increases. In DomWorld, group life is represented by artificial individuals that live in a homogeneous world. Individuals are extremely simple: all they do is flock together and, upon meeting one another, they may perform dominance interactions in which the effects of winning and losing are self-reinforcing. When the intensity of aggression in the model is increased, a complex feedback between the hierarchy and spatial structure results; via self-organization, this feedback causes the egalitarian society to change into a despotic one. The many differences between the two types of artificial society closely correspond to those between despotic and egalitarian macaques in the real world. Given that, in the model, the organization changes as a side effect of the change of one single trait proper to an egalitarian society, in the real world a despotic society may also have arisen as a side effect of the mutation of a single trait of an egalitarian species. If groups with different intensities of aggression evolve in this way, they will also have different gradients of hierarchy. When food is scarce, groups with the steepest hierarchy may have the best chance to survive, because at least a small number of individuals in such a group may succeed in producing offspring, whereas in egalitarian societies every individual is at risk of being insufficiently fed to reproduce. Therefore, intrademic group selection (selection within an interbreeding group) may have contributed to the evolution of despotic societies.

Comparison of a polymeric pseudostationary phase in EKC with ODS stationary phase in RP-HPLC.

PubMed

Ni, Xinjiong; Zhang, Min; Xing, Xiaoping; Cao, Yuhua; Cao, Guangqun

2018-01-01

Poly(stearyl methacrylate-co-methacrylic acid) (P(SMA-co-MAA)) was induced as pseudostationary phase (PSP) in electrokinetic chromatography (EKC). The n-octadecyl groups in SMA were the same as that in octadecylsilane (ODS) C18 column. Thus, the present work focused on the comparison of selectivity between polymeric PSP and ODS stationary phase (SP), and the effect of organic modifiers on the selectivity of polymeric PSP and ODS SP. 1-butanol could directly interacted with PSP as a Class I modifier, and improved both of the methylene selectivity and polar group selectivity. When the analysis times were similar, the polymeric PSP exhibited better methylene selectivity and polar group selectivity. Although the hydrophobic groups were similar, the substituted benzenes elution order was different between polymeric PSP and ODS SP. Linear solvation energy relationships (LSER) model analysis found that polymeric PSP and ODS SP exhibited two same key factors in selectivity: hydrophobic interaction and hydrogen bonding acidity. But polymeric PSP exhibited relatively strong n- and π-electrons interaction to the analytes. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

QSPR models for half-wave reduction potential of steroids: a comparative study between feature selection and feature extraction from subsets of or entire set of descriptors.

PubMed

Hemmateenejad, Bahram; Yazdani, Mahdieh

2009-02-16

Steroids are widely distributed in nature and are found in plants, animals, and fungi in abundance. A data set consists of a diverse set of steroids have been used to develop quantitative structure-electrochemistry relationship (QSER) models for their half-wave reduction potential. Modeling was established by means of multiple linear regression (MLR) and principle component regression (PCR) analyses. In MLR analysis, the QSPR models were constructed by first grouping descriptors and then stepwise selection of variables from each group (MLR1) and stepwise selection of predictor variables from the pool of all calculated descriptors (MLR2). Similar procedure was used in PCR analysis so that the principal components (or features) were extracted from different group of descriptors (PCR1) and from entire set of descriptors (PCR2). The resulted models were evaluated using cross-validation, chance correlation, application to prediction reduction potential of some test samples and accessing applicability domain. Both MLR approaches represented accurate results however the QSPR model found by MLR1 was statistically more significant. PCR1 approach produced a model as accurate as MLR approaches whereas less accurate results were obtained by PCR2 approach. In overall, the correlation coefficients of cross-validation and prediction of the QSPR models resulted from MLR1, MLR2 and PCR1 approaches were higher than 90%, which show the high ability of the models to predict reduction potential of the studied steroids.

[Natural selection associated with color vision defects in some population groups of Eurasia].

PubMed

Evsiukov, A N

2014-01-01

Fitness coefficients and other quantitative parameters of selection associated with the generalized color blindness gene CB+ were obtained for three ethnogeographic population groups, including Belarusians from Belarus, ethnic populations of the Volga-Ural region, and ethnic populations of Siberia and the Far East of Russia. All abnormalities encoded by the OPN1LW and OPN1MW loci were treated as deviations from normal color perception. Coefficients were estimated from an approximation of the observed CB+ frequency distributions to the theoretical stationary distribution for the Wright island model. This model takes into account the pressure of migrations, selection, and random genetic drift, while the selection parameters are represented in the form of the distribution parameters. In the populations of Siberia and Far East, directional selection in favor of normal color vision and the corresponding allele CB- was observed. In the Belarusian and ethnic populations of the Volga-Ural region, stabilizing selection was observed. The selection intensity constituted 0.03 in the Belarusian; 0.22 in the ethnic populations of the Volga-Ural region; and 0.24 in ethnic populations of Siberia and Far East.

Advanced colorectal neoplasia risk stratification by penalized logistic regression.

PubMed

Lin, Yunzhi; Yu, Menggang; Wang, Sijian; Chappell, Richard; Imperiale, Thomas F

2016-08-01

Colorectal cancer is the second leading cause of death from cancer in the United States. To facilitate the efficiency of colorectal cancer screening, there is a need to stratify risk for colorectal cancer among the 90% of US residents who are considered "average risk." In this article, we investigate such risk stratification rules for advanced colorectal neoplasia (colorectal cancer and advanced, precancerous polyps). We use a recently completed large cohort study of subjects who underwent a first screening colonoscopy. Logistic regression models have been used in the literature to estimate the risk of advanced colorectal neoplasia based on quantifiable risk factors. However, logistic regression may be prone to overfitting and instability in variable selection. Since most of the risk factors in our study have several categories, it was tempting to collapse these categories into fewer risk groups. We propose a penalized logistic regression method that automatically and simultaneously selects variables, groups categories, and estimates their coefficients by penalizing the [Formula: see text]-norm of both the coefficients and their differences. Hence, it encourages sparsity in the categories, i.e. grouping of the categories, and sparsity in the variables, i.e. variable selection. We apply the penalized logistic regression method to our data. The important variables are selected, with close categories simultaneously grouped, by penalized regression models with and without the interactions terms. The models are validated with 10-fold cross-validation. The receiver operating characteristic curves of the penalized regression models dominate the receiver operating characteristic curve of naive logistic regressions, indicating a superior discriminative performance. © The Author(s) 2013.

Splitting of the weak hypercharge quantum

NASA Astrophysics Data System (ADS)

Nielsen, H. B.; Brene, N.

1991-08-01

The ratio between the weak hypercharge quantum for particles having no coupling to the gauge bosons corresponding to the semi-simple component of the gauge group and the smallest hypercharge quantum for particles that do have such couplings is exceptionally large for the standard model, considering its rank. To compare groups with respect to this property we propose a quantity χ which depends on the rank of the group and the splitting ratio of the hypercharge(s) to be found in the group. The quantity χ has maximal value for the gauge group of the standard model. This suggests that the hypercharge splitting may play an important rôle either in the origin of the gauge symmetry at a fundamental scale or in some kind of selection mechanism at a scale perhaps nearer to the experimental scale. Such a selection mechanism might be what we have called confusion which removes groups with many (so-called generalized) automorphisms. The quantity χ tends to be large for groups with few generalized automorphisms.

Behavioral responses in structured populations pave the way to group optimality.

PubMed

Akçay, Erol; Van Cleve, Jeremy

2012-02-01

An unresolved controversy regarding social behaviors is exemplified when natural selection might lead to behaviors that maximize fitness at the social-group level but are costly at the individual level. Except for the special case of groups of clones, we do not have a general understanding of how and when group-optimal behaviors evolve, especially when the behaviors in question are flexible. To address this question, we develop a general model that integrates behavioral plasticity in social interactions with the action of natural selection in structured populations. We find that group-optimal behaviors can evolve, even without clonal groups, if individuals exhibit appropriate behavioral responses to each other's actions. The evolution of such behavioral responses, in turn, is predicated on the nature of the proximate behavioral mechanisms. We model a particular class of proximate mechanisms, prosocial preferences, and find that such preferences evolve to sustain maximum group benefit under certain levels of relatedness and certain ecological conditions. Thus, our model demonstrates the fundamental interplay between behavioral responses and relatedness in determining the course of social evolution. We also highlight the crucial role of proximate mechanisms such as prosocial preferences in the evolution of behavioral responses and in facilitating evolutionary transitions in individuality.

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

PubMed

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

2015-02-01

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

A decision support system using analytical hierarchy process (AHP) for the optimal environmental reclamation of an open-pit mine

NASA Astrophysics Data System (ADS)

Bascetin, A.

2007-04-01

The selection of an optimal reclamation method is one of the most important factors in open-pit design and production planning. It also affects economic considerations in open-pit design as a function of plan location and depth. Furthermore, the selection is a complex multi-person, multi-criteria decision problem. The group decision-making process can be improved by applying a systematic and logical approach to assess the priorities based on the inputs of several specialists from different functional areas within the mine company. The analytical hierarchy process (AHP) can be very useful in involving several decision makers with different conflicting objectives to arrive at a consensus decision. In this paper, the selection of an optimal reclamation method using an AHP-based model was evaluated for coal production in an open-pit coal mine located at Seyitomer region in Turkey. The use of the proposed model indicates that it can be applied to improve the group decision making in selecting a reclamation method that satisfies optimal specifications. Also, it is found that the decision process is systematic and using the proposed model can reduce the time taken to select a optimal method.

Using Latent Class Analysis to Model Temperament Types.

PubMed

Loken, Eric

2004-10-01

Mixture models are appropriate for data that arise from a set of qualitatively different subpopulations. In this study, latent class analysis was applied to observational data from a laboratory assessment of infant temperament at four months of age. The EM algorithm was used to fit the models, and the Bayesian method of posterior predictive checks was used for model selection. Results show at least three types of infant temperament, with patterns consistent with those identified by previous researchers who classified the infants using a theoretically based system. Multiple imputation of group memberships is proposed as an alternative to assigning subjects to the latent class with maximum posterior probability in order to reflect variance due to uncertainty in the parameter estimation. Latent class membership at four months of age predicted longitudinal outcomes at four years of age. The example illustrates issues relevant to all mixture models, including estimation, multi-modality, model selection, and comparisons based on the latent group indicators.

Properties of hypothesis testing techniques and (Bayesian) model selection for exploration-based and theory-based (order-restricted) hypotheses.

PubMed

Kuiper, Rebecca M; Nederhoff, Tim; Klugkist, Irene

2015-05-01

In this paper, the performance of six types of techniques for comparisons of means is examined. These six emerge from the distinction between the method employed (hypothesis testing, model selection using information criteria, or Bayesian model selection) and the set of hypotheses that is investigated (a classical, exploration-based set of hypotheses containing equality constraints on the means, or a theory-based limited set of hypotheses with equality and/or order restrictions). A simulation study is conducted to examine the performance of these techniques. We demonstrate that, if one has specific, a priori specified hypotheses, confirmation (i.e., investigating theory-based hypotheses) has advantages over exploration (i.e., examining all possible equality-constrained hypotheses). Furthermore, examining reasonable order-restricted hypotheses has more power to detect the true effect/non-null hypothesis than evaluating only equality restrictions. Additionally, when investigating more than one theory-based hypothesis, model selection is preferred over hypothesis testing. Because of the first two results, we further examine the techniques that are able to evaluate order restrictions in a confirmatory fashion by examining their performance when the homogeneity of variance assumption is violated. Results show that the techniques are robust to heterogeneity when the sample sizes are equal. When the sample sizes are unequal, the performance is affected by heterogeneity. The size and direction of the deviations from the baseline, where there is no heterogeneity, depend on the effect size (of the means) and on the trend in the group variances with respect to the ordering of the group sizes. Importantly, the deviations are less pronounced when the group variances and sizes exhibit the same trend (e.g., are both increasing with group number). © 2014 The British Psychological Society.

The effect of a commercial competitive exclusion product on the selection of enrofloxacin resistance in commensal E. coli in broilers.

PubMed

Chantziaras, Ilias; Smet, Annemieke; Filippitzi, Maria Eleni; Damiaans, Bert; Haesebrouck, Freddy; Boyen, Filip; Dewulf, Jeroen

2018-06-07

The effect of a competitive exclusion product (Aviguard ® ) on the selection of fluoroquinolone resistance in poultry was assessed in vivo in the absence or presence of fluoroquinolone treatment. Two experiments using a controlled seeder-sentinel animal model (2seeders:4sentinels per group) with one-day-old chicks were used. For both experiments,as soon as the chicks were hatched, the animals of two groups were administered Aviguard ® and two groups were left untreated. Three days later, all groups were inoculated with an enrofloxacin-susceptible commensal E. coli strain. Five days after hatching, two animals per group were inoculated either with a bacteriologically-fit or a bacteriologically non-fit enrofloxacin-resistant commensal E. coli strain. In experiment 2, all groups were orally treated for three consecutive days (Day 8-10) with enrofloxacin. Throughout the experiments, faecal excretion of all inoculated E. coli strains was determined on days 2-5-8-11-18-23 by selective plating (via spiral plater). Linear mixed models were used to assess the effect of Aviguard ® on the selection of fluoroquinolone resistance. The use of Aviguard® (p<0.01) reduced the excretion of enrofloxacin-resistant E. coli when no enrofloxacin treatment was administered. However, this beneficial effect disappeared (p=0.37) when the animals were treated with enrofloxacin. Similarly, bacterial fitness of the enrofloxacin-resistant E. coli strain used for inoculation had an effect (p<0.01) on the selection of enrofloxacin resistance when no treatment was administered, whereas this effect was no longer present when enrofloxacin was administered (p =0.70). Thus, enrofloxacin treatment cancelled the beneficial effects from administrating Aviguard ® in one-day-old broiler chicks and resulted in a enrofloxacin-resistant flora.

A comparison of three models for determining test fairness.

DOT National Transportation Integrated Search

1979-01-01

There are three prominent models of test fairness in the dichotomous situation: : (a) Thorndike's Constant Ratio model (the ratio of the proportion successful to the proportion selected should be equal for the majority and the minority group); : (b) ...

A model of two-way selection system for human behavior.

PubMed

Zhou, Bin; Qin, Shujia; Han, Xiao-Pu; He, Zhe; Xie, Jia-Rong; Wang, Bing-Hong

2014-01-01

Two-way selection is a common phenomenon in nature and society. It appears in the processes like choosing a mate between men and women, making contracts between job hunters and recruiters, and trading between buyers and sellers. In this paper, we propose a model of two-way selection system, and present its analytical solution for the expectation of successful matching total and the regular pattern that the matching rate trends toward an inverse proportion to either the ratio between the two sides or the ratio of the state total to the smaller group's people number. The proposed model is verified by empirical data of the matchmaking fairs. Results indicate that the model well predicts this typical real-world two-way selection behavior to the bounded error extent, thus it is helpful for understanding the dynamics mechanism of the real-world two-way selection system.

Visual Literacy and the Integration of Parametric Modeling in the Problem-Based Curriculum

ERIC Educational Resources Information Center

Assenmacher, Matthew Benedict

2013-01-01

This quasi-experimental study investigated the application of visual literacy skills in the form of parametric modeling software in relation to traditional forms of sketching. The study included two groups of high school technical design students. The control and experimental groups involved in the study consisted of two randomly selected groups…

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

PubMed

Shields, Walker

2006-12-01

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

The concurrent evolution of cooperation and the population structures that support it.

PubMed

Powers, Simon T; Penn, Alexandra S; Watson, Richard A

2011-06-01

The evolution of cooperation often depends upon population structure, yet nearly all models of cooperation implicitly assume that this structure remains static. This is a simplifying assumption, because most organisms possess genetic traits that affect their population structure to some degree. These traits, such as a group size preference, affect the relatedness of interacting individuals and hence the opportunity for kin or group selection. We argue that models that do not explicitly consider their evolution cannot provide a satisfactory account of the origin of cooperation, because they cannot explain how the prerequisite population structures arise. Here, we consider the concurrent evolution of genetic traits that affect population structure, with those that affect social behavior. We show that not only does population structure drive social evolution, as in previous models, but that the opportunity for cooperation can in turn drive the creation of population structures that support it. This occurs through the generation of linkage disequilibrium between socio-behavioral and population-structuring traits, such that direct kin selection on social behavior creates indirect selection pressure on population structure. We illustrate our argument with a model of the concurrent evolution of group size preference and social behavior. © 2011 The Author(s). Evolution© 2011 The Society for the Study of Evolution.

Decision-making deficits in patients with chronic schizophrenia: Iowa Gambling Task and Prospect Valence Learning model.

PubMed

Kim, Myung-Sun; Kang, Bit-Na; Lim, Jae Young

2016-01-01

Decision-making is the process of forming preferences for possible options, selecting and executing actions, and evaluating the outcome. This study used the Iowa Gambling Task (IGT) and the Prospect Valence Learning (PVL) model to investigate deficits in risk-reward related decision-making in patients with chronic schizophrenia, and to identify decision-making processes that contribute to poor IGT performance in these patients. Thirty-nine patients with schizophrenia and 31 healthy controls participated. Decision-making was measured by total net score, block net scores, and the total number of cards selected from each deck of the IGT. PVL parameters were estimated with the Markov chain Monte Carlo sampling scheme in OpenBugs and BRugs, its interface to R, and the estimated parameters were analyzed with the Mann-Whitney U-test. The schizophrenia group received significantly lower total net scores compared to the control group. In terms of block net scores, an interaction effect of group × block was observed. The block net scores of the schizophrenia group did not differ across the five blocks, whereas those of the control group increased as the blocks progressed. The schizophrenia group obtained significantly lower block net scores in the fourth and fifth blocks of the IGT and selected cards from deck D (advantageous) less frequently than the control group. Additionally, the schizophrenia group had significantly lower values on the utility-shape, loss-aversion, recency, and consistency parameters of the PVL model. These results indicate that patients with schizophrenia experience deficits in decision-making, possibly due to failure in learning the expected value of each deck, and incorporating outcome experiences of previous trials into expectancies about options in the present trial.

Selection and study performance: comparing three admission processes within one medical school.

PubMed

Schripsema, Nienke R; van Trigt, Anke M; Borleffs, Jan C C; Cohen-Schotanus, Janke

2014-12-01

This study was conducted to: (i) analyse whether students admitted to one medical school based on top pre-university grades, a voluntary multifaceted selection process, or lottery, respectively, differed in study performance; (ii) examine whether students who were accepted in the multifaceted selection process outperformed their rejected peers, and (iii) analyse whether participation in the multifaceted selection procedure was related to performance. We examined knowledge test and professionalism scores, study progress and dropout in three cohorts of medical students admitted to the University of Groningen, the Netherlands in 2009, 2010 and 2011 (n = 1055). We divided the lottery-admitted group into, respectively, students who had not participated and students who had been rejected in the multifaceted selection process. We used ancova modelling, logistic regression and Bonferroni post hoc multiple-comparison tests and controlled for gender and cohort. The top pre-university grade group achieved higher knowledge test scores and more Year 1 course credits than all other groups (p < 0.05). This group received the highest possible professionalism score more often than the lottery-admitted group that had not participated in the multifaceted selection process (p < 0.05). The group of students accepted in the multifaceted selection process obtained higher written test scores than the lottery-admitted group that had not participated (p < 0.05) and achieved the highest possible professionalism score more often than both lottery-admitted groups. The lottery-admitted group that had not participated in the multifaceted selection process earned fewer Year 1 and 2 course credits than all other groups (p < 0.05). Dropout rates differed among the groups (p < 0.05), but correction for multiple comparisons rendered all pairwise differences non-significant. A top pre-university grade point average was the best predictor of performance. For so-called non-academic performance, the multifaceted selection process was efficient in identifying applicants with suitable skills. Participation in the multifaceted selection procedure seems to be predictive of higher performance. Further research is needed to assess whether our results are generalisable to other medical schools. © 2014 John Wiley & Sons Ltd.

Resilience of the Eastern Chukchi Sea Food Web to Mortality Based Perturbations and Identification of Ecologically Important Species

NASA Astrophysics Data System (ADS)

Whitehouse, G. A.; Aydin, K.

2016-02-01

Evidence of climate impacts on Arctic marine ecosystems is accumulating and Arctic marine ecosystems face additional pressures that may accompany increasing human activities due to improved access following reductions in sea ice cover. Thus, there is growing demand for information on how Arctic ecosystems may respond to potential disturbance. We explore the response of the eastern Chukchi Sea food web to mortality based perturbations using the dynamic food web modeling framework, Ecopath with Ecosim. We generated thousands of ecosystems by drawing random sets of model parameters from informative prior distributions and only retained those ecosystems that resulted in plausible, numerically stable configurations (no extinctions or population growth without limit). To perturb the systems, we increased mortality rates for selected functional groups then ran the retained models forward 50 years to examine how the biomass of other functional groups responded, and evaluated the resilience of the food web as the time for all functional groups to return to within 10 percent of their starting biomass. Ecologically important species were identified as those species (or functional groups of species) for whom changes in mortality had the greatest effect on the remainder of the food web. We also report on how a selection of ecosystem scale properties were affected by selected perturbations, including mean biomass longevity, the distribution of biomass across trophic levels, and a selection of dimensionless biomass ratios. These perturbations simulate a range of potential impacts that mortality events may have on the food web of the eastern Chukchi Sea, and indicate the directional response of other species and functional groups to these simulated events. This information will be of value to decision makers and resource managers developing guidelines for commercial and industrial development in the eastern Chukchi Sea.

Cost analysis of an integrated care model in the management of acute exacerbations of chronic obstructive pulmonary disease.

PubMed

Bakerly, Nawar Diar; Davies, C; Dyer, M; Dhillon, P

2009-01-01

Home treatment models for acute exacerbations of chronic obstructive pulmonary disease (AECOPD) proved to be a safe alternative to hospitalization. These models have the potential to free up resources; however, in the United Kingdom, it remains unclear to whether they provide cost savings compared with hospital treatment. Over a 12-month period from August 2003, 130 patients were selected for the integrated care group (total admissions with AECOPD = 546). These patients were compared with 95 retrospective controls in the hospital treatment group. Controls were selected from admissions during the previous 12 months (total of 662 admissions) to match the integrated care group in age, sex, and postal code. Resource use data were collected for both groups and compared using National Health Service (NHS) perspective for cost minimization analysis. In the integrated care group (130 patients), 107 (82%) patients received home support with average length of stay 3.3 (SD 3.9) days compared with 10.4 (SD 7.7) in the hospital group (95 patients). Average number of visits per patients in the integrated care group was 3.08 (SD = 0.95; 95% CI = 2.9-3.2). Cost per patient in the integrated care group was pound1653 (95% CI, pound1521-1802) compared with pound2256 (95% CI, pound2126- 2407) in the hospital group. The integrated care group resulted in cost saving of approximately pound600 (P < 0.001) per patient. This integrated care model for the management of patients with AECOPD offered cost savings of pound600 per patient over the conventional hospital treatment model using the new NHS tariff from an acute trust provider perspective.

A cultural accommodation model for cross-cultural psychotherapy: Illustrated with the case of Asian Americans.

PubMed

Leong, Frederick T; Lee, Szu-Hui

2006-01-01

As an extension of F. T. L. Leong's (1996) integrative model, this article presents the cultural accommodation model (CAM), an enhanced theoretical guide to effective cross-cultural clinical practice and research. Whereas F. T. L. Leong's model identifies the importance of integrating the universal, group, and individual dimensions, the CAM takes the next step by providing a theoretical guide to effective psychotherapy with culturally different clients by means of a cultural accommodation process. This model argues for the importance of selecting and applying culture-specific constructs when working with culturally diverse groups. The first step of the CAM is to identify cultural disparities that are often ignored and then accommodate them by using current culturally specific concepts. In this article, several different cultural "gaps" or culture-specific constructs of relevance to Asian Americans with strong scientific foundations are selected and discussed as they pertain to providing effective psychotherapy to this ethnic minority group. Finally, a case study is incorporated to illustrate application of the CAM. (PsycINFO Database Record (c) 2010 APA, all rights reserved).

Selective cleavage of the C(α)-C(β) linkage in lignin model compounds via Baeyer-Villiger oxidation.

PubMed

Patil, Nikhil D; Yao, Soledad G; Meier, Mark S; Mobley, Justin K; Crocker, Mark

2015-03-21

Lignin is an amorphous aromatic polymer derived from plants and is a potential source of fuels and bulk chemicals. Herein, we present a survey of reagents for selective stepwise oxidation of lignin model compounds. Specifically, we have targeted the oxidative cleavage of Cα-Cβ bonds as a means to depolymerize lignin and obtain useful aromatic compounds. In this work, we prepared several lignin model compounds that possess structures, characteristic reactivity, and linkages closely related to the parent lignin polymer. We observed that selective oxidation of benzylic hydroxyl groups, followed by Baeyer-Villiger oxidation of the resulting ketones, successfully cleaves the Cα-Cβ linkage in these model compounds.

Current modeling practice may lead to falsely high benchmark dose estimates.

PubMed

Ringblom, Joakim; Johanson, Gunnar; Öberg, Mattias

2014-07-01

Benchmark dose (BMD) modeling is increasingly used as the preferred approach to define the point-of-departure for health risk assessment of chemicals. As data are inherently variable, there is always a risk to select a model that defines a lower confidence bound of the BMD (BMDL) that, contrary to expected, exceeds the true BMD. The aim of this study was to investigate how often and under what circumstances such anomalies occur under current modeling practice. Continuous data were generated from a realistic dose-effect curve by Monte Carlo simulations using four dose groups and a set of five different dose placement scenarios, group sizes between 5 and 50 animals and coefficients of variations of 5-15%. The BMD calculations were conducted using nested exponential models, as most BMD software use nested approaches. "Non-protective" BMDLs (higher than true BMD) were frequently observed, in some scenarios reaching 80%. The phenomenon was mainly related to the selection of the non-sigmoidal exponential model (Effect=a·e(b)(·dose)). In conclusion, non-sigmoid models should be used with caution as it may underestimate the risk, illustrating that awareness of the model selection process and sound identification of the point-of-departure is vital for health risk assessment. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

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

PubMed

Kim, Hee Seok; Lee, Dong Soo

2017-11-01

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

Recruitment Modeling: An Analysis and an Application to the Study of Male-Female Differences in Intelligence

ERIC Educational Resources Information Center

Hunt, Earl; Madhyastha, Tara

2008-01-01

Studies of group differences in intelligence often invite conclusions about groups in general from studies of group differences in selected populations. The same design is used in the study of group differences in other traits as well. Investigators observe samples from two groups (e.g. men and women) in some accessible population, but seek to…

Genetic hitchhiking can promote the initial spread of strong altruism

PubMed Central

2008-01-01

Background The evolutionary origin of strong altruism (where the altruist pays an absolute cost in terms of fitness) towards non-kin has never been satisfactorily explained since no mechanism (except genetic drift) seems to be able to overcome the fitness disadvantage of the individual who practiced altruism in the first place. Results Here we consider a multilocus, single-generation random group model and demonstrate that with low, but realistic levels of recombination and social heterosis (selecting for allelic diversity within groups) altruism can evolve without invoking kin selection, because sampling effects in the formation of temporary groups and selection for complementary haplotypes generate nonrandom associations between alleles at polymorphic loci. Conclusion By letting altruism get off the ground, selection on other genes favourably interferes with the eventual fate of the altruistic trait due to genetic hitchhiking. PMID:18847475

Selection of Branded Alcoholic Beverages by Underage Drinkers

PubMed Central

Ross, Craig S.; Ostroff, Josh; Naimi, Timothy S.; DeJong, William; Siegel, Michael B.; Jernigan, David H.

2015-01-01

Purpose To identify reasons why youth choose to drink specific brands of alcohol and to determine if these reasons are associated with problem drinking patterns and outcomes. Methods We conducted an Internet survey of 1,031 youth ages 13 to 20 who reported drinking within the past 30 days. Of these, 541 youth who reported having a choice of multiple brands of alcohol the last time they drank stated (yes/no) whether each of 16 different reasons had influenced their choice of a specific brand. We reduced these 16 reasons to three principle components and used Latent Class Modeling to identify five groups of youth with similar reasons for selecting a brand, which we then profiled. Results We grouped respondents into the following brand selection groups: “Brand Ambassadors” who were distinguished from other clusters by selecting a brand because they identified with it (32.5% of respondents), “Tasters” who selected a brand because they expected it to taste good (27.2%), “Bargain Hunters” who selected a brand because it was inexpensive (18.5%), “Copycats” who selected a brand because they’d seen adults drinking it or seen it consumed in movies or other media (10.4%), and “Others” (11.5%). Brand Ambassadors and Copycats reported the largest amount of alcohol consumed and had the greatest prevalence of both heavy episodic drinking and negative alcohol-related health consequences. Conclusions Underage drinkers who cite marketing influences and adult or media modeling of brand choices as their reasons for selecting alcohol brands are likely to drink more and incur adverse consequences from drinking. PMID:25907655

Renormalization Group (RG) in Turbulence: Historical and Comparative Perspective

NASA Technical Reports Server (NTRS)

Zhou, Ye; McComb, W. David; Vahala, George

1997-01-01

The term renormalization and renormalization group are explained by reference to various physical systems. The extension of renormalization group to turbulence is then discussed; first as a comprehensive review and second concentrating on the technical details of a few selected approaches. We conclude with a discussion of the relevance and application of renormalization group to turbulence modelling.

Anchor Selection Strategies for DIF Analysis: Review, Assessment, and New Approaches

ERIC Educational Resources Information Center

Kopf, Julia; Zeileis, Achim; Strobl, Carolin

2015-01-01

Differential item functioning (DIF) indicates the violation of the invariance assumption, for instance, in models based on item response theory (IRT). For item-wise DIF analysis using IRT, a common metric for the item parameters of the groups that are to be compared (e.g., for the reference and the focal group) is necessary. In the Rasch model,…

Characterizations of Social-Based and Self-Based Contexts Associated with Students' Awareness, Evaluation, and Regulation of Their Thinking during Small-Group Mathematical Modeling

ERIC Educational Resources Information Center

Magiera, Marta T.; Zawojewski, Judith S.

2011-01-01

This exploratory study focused on characterizing problem-solving situations associated with spontaneous metacognitive activity. The results came from connected case studies of a group of 3 purposefully selected 9th-grade students working collaboratively on a series of 5 modeling problems. Students' descriptions of their own thinking during…

Construct Validity of Selected Measures of Physical Activity Beliefs and Motives in Fifth and Sixth Grade Boys and Girls

PubMed Central

Saunders, Ruth P.; McIver, Kerry L.; Dowda, Marsha; Pate, Russell R.

2013-01-01

Objective Scales used to measure selected social-cognitive beliefs and motives for physical activity were tested among boys and girls. Methods Covariance modeling was applied to responses obtained from large multi-ethnic samples of students in the fifth and sixth grades. Results Theoretically and statistically sound models were developed, supporting the factorial validity of the scales in all groups. Multi-group longitudinal invariance was confirmed between boys and girls, overweight and normal weight students, and non-Hispanic black and white children. The construct validity of the scales was supported by hypothesized convergent and discriminant relationships within a measurement model that included correlations with physical activity (MET • min/day) measured by an accelerometer. Conclusions Scores from the scales provide valid assessments of selected beliefs and motives that are putative mediators of change in physical activity among boys and girls, as they begin the understudied transition from the fifth grade into middle school, when physical activity naturally declines. PMID:23459310

Construct validity of selected measures of physical activity beliefs and motives in fifth and sixth grade boys and girls.

PubMed

Dishman, Rod K; Saunders, Ruth P; McIver, Kerry L; Dowda, Marsha; Pate, Russell R

2013-06-01

Scales used to measure selected social-cognitive beliefs and motives for physical activity were tested among boys and girls. Covariance modeling was applied to responses obtained from large multi-ethnic samples of students in the fifth and sixth grades. Theoretically and statistically sound models were developed, supporting the factorial validity of the scales in all groups. Multi-group longitudinal invariance was confirmed between boys and girls, overweight and normal weight students, and non-Hispanic black and white children. The construct validity of the scales was supported by hypothesized convergent and discriminant relationships within a measurement model that included correlations with physical activity (MET • min/day) measured by an accelerometer. Scores from the scales provide valid assessments of selected beliefs and motives that are putative mediators of change in physical activity among boys and girls, as they begin the understudied transition from the fifth grade into middle school, when physical activity naturally declines.

In love and war: altruism, norm formation, and two different types of group selection.

PubMed

van Veelen, Matthijs; Hopfensitz, Astrid

2007-12-21

We analyse simulations reported in "The co-evolution of individual behaviors and social institutions" by Bowles et al., 2003 in the Journal of Theoretical Biology 223, 135-147, and begin with distinguishing two types of group selection models. The literature does not provide different names for them, but they are shown to be fundamentally different and have quite different empirical implications. The working of the first one depends on the answer to the question "is the probability that you also are an altruist large enough", while the other needs an affirmative answer to "are our interests enough in line". The first one therefore can also be understood as a kin selection model, while the working of the second can also be described in terms of the direct benefits. The actual simulation model is a combination of the two. It is also a Markov chain, which has important implications for how the output data should be handled.

Generation of the first structure-based pharmacophore model containing a selective "zinc binding group" feature to identify potential glyoxalase-1 inhibitors.

PubMed

Al-Balas, Qosay; Hassan, Mohammad; Al-Oudat, Buthina; Alzoubi, Hassan; Mhaidat, Nizar; Almaaytah, Ammar

2012-11-22

Within this study, a unique 3D structure-based pharmacophore model of the enzyme glyoxalase-1 (Glo-1) has been revealed. Glo-1 is considered a zinc metalloenzyme in which the inhibitor binding with zinc atom at the active site is crucial. To our knowledge, this is the first pharmacophore model that has a selective feature for a "zinc binding group" which has been customized within the structure-based pharmacophore model of Glo-1 to extract ligands that possess functional groups able to bind zinc atom solely from database screening. In addition, an extensive 2D similarity search using three diverse similarity techniques (Tanimoto, Dice, Cosine) has been performed over the commercially available "Zinc Clean Drug-Like Database" that contains around 10 million compounds to help find suitable inhibitors for this enzyme based on known inhibitors from the literature. The resultant hits were mapped over the structure based pharmacophore and the successful hits were further docked using three docking programs with different pose fitting and scoring techniques (GOLD, LibDock, CDOCKER). Nine candidates were suggested to be novel Glo-1 inhibitors containing the "zinc binding group" with the highest consensus scoring from docking.

Genomic selection accuracies within and between environments and small breeding groups in white spruce.

PubMed

Beaulieu, Jean; Doerksen, Trevor K; MacKay, John; Rainville, André; Bousquet, Jean

2014-12-02

Genomic selection (GS) may improve selection response over conventional pedigree-based selection if markers capture more detailed information than pedigrees in recently domesticated tree species and/or make it more cost effective. Genomic prediction accuracies using 1748 trees and 6932 SNPs representative of as many distinct gene loci were determined for growth and wood traits in white spruce, within and between environments and breeding groups (BG), each with an effective size of Ne ≈ 20. Marker subsets were also tested. Model fits and/or cross-validation (CV) prediction accuracies for ridge regression (RR) and the least absolute shrinkage and selection operator models approached those of pedigree-based models. With strong relatedness between CV sets, prediction accuracies for RR within environment and BG were high for wood (r = 0.71-0.79) and moderately high for growth (r = 0.52-0.69) traits, in line with trends in heritabilities. For both classes of traits, these accuracies achieved between 83% and 92% of those obtained with phenotypes and pedigree information. Prediction into untested environments remained moderately high for wood (r ≥ 0.61) but dropped significantly for growth (r ≥ 0.24) traits, emphasizing the need to phenotype in all test environments and model genotype-by-environment interactions for growth traits. Removing relatedness between CV sets sharply decreased prediction accuracies for all traits and subpopulations, falling near zero between BGs with no known shared ancestry. For marker subsets, similar patterns were observed but with lower prediction accuracies. Given the need for high relatedness between CV sets to obtain good prediction accuracies, we recommend to build GS models for prediction within the same breeding population only. Breeding groups could be merged to build genomic prediction models as long as the total effective population size does not exceed 50 individuals in order to obtain high prediction accuracy such as that obtained in the present study. A number of markers limited to a few hundred would not negatively impact prediction accuracies, but these could decrease more rapidly over generations. The most promising short-term approach for genomic selection would likely be the selection of superior individuals within large full-sib families vegetatively propagated to implement multiclonal forestry.

Disentangling incentives effects of insurance coverage from adverse selection in the case of drug expenditure: a finite mixture approach.

PubMed

Munkin, Murat K; Trivedi, Pravin K

2010-09-01

This paper takes a finite mixture approach to model heterogeneity in incentive and selection effects of drug coverage on total drug expenditure among the Medicare elderly US population. Evidence is found that the positive drug expenditures of the elderly population can be decomposed into two groups different in the identified selection effects and interpreted as relatively healthy with lower average expenditures and relatively unhealthy with higher average expenditures, accounting for approximately 25 and 75% of the population, respectively. Adverse selection into drug insurance appears to be strong for the higher expenditure component and weak for the lower expenditure group. Copyright (c) 2010 John Wiley & Sons, Ltd.

Fact Sheet: Documenting Ground-Water Models Selection at Site Contaminated with Radioactive Substance

EPA Pesticide Factsheets

This fact sheet summarizes the report by a joint Interagency Environmental Pathway Modeling Working Group. It was designed to be used by technical staff responsible for identifying and implementing flow and transport models to support cleanup decisions.

Selective attention to philopatric models causes directed social learning in wild vervet monkeys.

PubMed

van de Waal, Erica; Renevey, Nathalie; Favre, Camille Monique; Bshary, Redouan

2010-07-22

Human behaviour is often based on social learning, a mechanism that has been documented also in a variety of other vertebrates. However, social learning as a means of problem-solving may be optimal only under specific conditions, and both theoretical work and laboratory experiments highlight the importance of a potential model's identity. Here we present the results from a social learning experiment on six wild vervet monkey groups, where models were either a dominant female or a dominant male. We presented 'artificial fruit' boxes that had doors on opposite, differently coloured ends for access to food. One option was blocked during the demonstration phase, creating consistent demonstrations of one possible solution. Following demonstrations we found a significantly higher participation rate and same-door manipulation in groups with female models compared to groups with male models. These differences appeared to be owing to selective attention of bystanders to female model behaviour rather than owing to female tolerance. Our results demonstrate the favoured role of dominant females as a source for 'directed' social learning in a species with female philopatry. Our findings imply that migration does not necessarily lead to an exchange of socially acquired information within populations, potentially causing highly localized traditions.

Cost effectiveness of adding clostridial collagenase ointment to selective debridement in individuals with stage IV pressure ulcers.

PubMed

Carter, Marissa J; Gilligan, Adrienne M; Waycaster, Curtis R; Schaum, Kathleen; Fife, Caroline E

2017-03-01

The purpose of this study was to determine the cost effectiveness (from a payer's perspective) of adding clostridial collagenase ointment (CCO) to selective debridement compared with selective debridement alone (non-CCO) in the treatment of stage IV pressure ulcers among patients identified from the US Wound Registry. A 3-state Markov model was developed to determine costs and outcomes between the CCO and non-CCO groups over a 2-year time horizon. Outcome data were derived from a retrospective clinical study and included the proportion of pressure ulcers that were closed (epithelialized) over 2 years and the time to wound closure. Transition probabilities for the Markov states were estimated from the clinical study. In the Markov model, the clinical outcome is presented as ulcer-free weeks, which represents the time the wound is in the epithelialized state. Costs for each 4-week cycle were based on frequencies of clinic visits, debridement, and CCO application rates from the clinical study. The final model outputs were cumulative costs (in US dollars), clinical outcome (ulcer-free weeks), and incremental cost-effectiveness ratio (ICER) at 2 years. Compared with the non-CCO group, the CCO group incurred lower costs ($11,151 vs $17,596) and greater benefits (33.9 vs 16.8 ulcer-free weeks), resulting in an economically dominant ICER of -$375 per ulcer. Thus, for each additional ulcer-free week that can be gained, there is a concurrent cost savings of $375 if CCO treatment is selected. Over a 2-year period, an additional 17.2 ulcer-free weeks can be gained with concurrent cost savings of $6,445 for each patient. In this Markov model based on real-world data from the US Wound Registry, the addition of CCO to selective debridement in the treatment of pressure ulcers was economically dominant over selective debridement alone, resulting in greater benefit to the patient at lower cost.

Pressure to drink but not to smoke: disentangling selection and socialization in adolescent peer networks and peer groups.

PubMed

Kiuru, Noona; Burk, William J; Laursen, Brett; Salmela-Aro, Katariina; Nurmi, Jari-Erik

2010-12-01

This paper examined the relative influence of selection and socialization on alcohol and tobacco use in adolescent peer networks and peer groups. The sample included 1419 Finnish secondary education students (690 males and 729 females, mean age 16 years at the outset) from nine schools. Participants identified three school friends and described their alcohol and tobacco use on two occasions one year apart. Actor-based models simultaneously examined changes in peer network ties and changes in individual behaviors for all participants within each school. Multi-level analyses examined changes in individual behaviors for adolescents entering new peer groups and adolescents in stable peer groups, both of which were embedded within the school-based peer networks. Similar results emerged from both analytic methods: Selection and socialization contributed to similarity of alcohol use, but only selection was a factor in tobacco use. Copyright © 2010 The Association for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

Delay Differential Equation Models of Normal and Diseased Electrocardiograms

NASA Astrophysics Data System (ADS)

Lainscsek, Claudia; Sejnowski, Terrence J.

Time series analysis with nonlinear delay differential equations (DDEs) is a powerful tool since it reveals spectral as well as nonlinear properties of the underlying dynamical system. Here global DDE models are used to analyze electrocardiography recordings (ECGs) in order to capture distinguishing features for different heart conditions such as normal heart beat, congestive heart failure, and atrial fibrillation. To capture distinguishing features of the different data types the number of terms and delays in the model as well as the order of nonlinearity of the DDE model have to be selected. The DDE structure selection is done in a supervised way by selecting the DDE that best separates different data types. We analyzed 24 h of data from 15 young healthy subjects in normal sinus rhythm (NSR) of 15 congestive heart failure (CHF) patients as well as of 15 subjects suffering from atrial fibrillation (AF) selected from the Physionet database. For the analysis presented here we used 5 min non-overlapping data windows on the raw data without any artifact removal. For classification performance we used the Cohen Kappa coefficient computed directly from the confusion matrix. The overall classification performance of the three groups was around 72-99 % on the 5 min windows for the different approaches. For 2 h data windows the classification for all three groups was above 95%.

Selectivity in the Addition Reactions of Organometallic Reagents to Aziridine-2-carboxaldehydes: The Effects of Protecting Groups and Substitution Patterns

PubMed Central

Kulshrestha, Aman; Schomaker, Jennifer M.; Holmes, Daniel; Staples, Richard J.; Jackson, James E.; Borhan, Babak

2014-01-01

Good to excellent stereo-selectivity has been found in the addition reactions of Grignard and organo-zinc reagents to N-protected aziridine-2-carboxaldehydes. Specifically, high syn selectivity was obtained with benzyl-protected cis, tert-butyloxycar-bonyl-protected trans, and tosyl-pro-tected 2,3-disubstituted aziridine-2-car-boxaldehydes. Furthermore, rate and selectivity effects of ring substituents, temperature, solvent, and Lewis acid and base modifiers were studied. The diastereomeric preference of addition is dominated by the substrate aziri-dines’ substitution pattern and especially the electronic character and conformational preferences of the nitrogen protecting groups. To help rationalize the observed stereochemical outcomes, conformational and electronic structural analyses of a series of model systems representing the various substitution patterns have been explored by density functional calculations at the B3LYP/6–31G* level of theory with the SM8 solvation model to account for solvent effects. PMID:21928447

A comparative study of machine learning methods for time-to-event survival data for radiomics risk modelling.

PubMed

Leger, Stefan; Zwanenburg, Alex; Pilz, Karoline; Lohaus, Fabian; Linge, Annett; Zöphel, Klaus; Kotzerke, Jörg; Schreiber, Andreas; Tinhofer, Inge; Budach, Volker; Sak, Ali; Stuschke, Martin; Balermpas, Panagiotis; Rödel, Claus; Ganswindt, Ute; Belka, Claus; Pigorsch, Steffi; Combs, Stephanie E; Mönnich, David; Zips, Daniel; Krause, Mechthild; Baumann, Michael; Troost, Esther G C; Löck, Steffen; Richter, Christian

2017-10-16

Radiomics applies machine learning algorithms to quantitative imaging data to characterise the tumour phenotype and predict clinical outcome. For the development of radiomics risk models, a variety of different algorithms is available and it is not clear which one gives optimal results. Therefore, we assessed the performance of 11 machine learning algorithms combined with 12 feature selection methods by the concordance index (C-Index), to predict loco-regional tumour control (LRC) and overall survival for patients with head and neck squamous cell carcinoma. The considered algorithms are able to deal with continuous time-to-event survival data. Feature selection and model building were performed on a multicentre cohort (213 patients) and validated using an independent cohort (80 patients). We found several combinations of machine learning algorithms and feature selection methods which achieve similar results, e.g. C-Index = 0.71 and BT-COX: C-Index = 0.70 in combination with Spearman feature selection. Using the best performing models, patients were stratified into groups of low and high risk of recurrence. Significant differences in LRC were obtained between both groups on the validation cohort. Based on the presented analysis, we identified a subset of algorithms which should be considered in future radiomics studies to develop stable and clinically relevant predictive models for time-to-event endpoints.

Speciation in rapidly diverging systems: lessons from Lake Malawi.

PubMed

Danley, P D; Kocher, T D

2001-05-01

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

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

PubMed

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

2007-04-01

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

The cultural evolution of emergent group-level traits.

PubMed

Smaldino, Paul E

2014-06-01

Many of the most important properties of human groups - including properties that may give one group an evolutionary advantage over another - are properly defined only at the level of group organization. Yet at present, most work on the evolution of culture has focused solely on the transmission of individual-level traits. I propose a conceptual extension of the theory of cultural evolution, particularly related to the evolutionary competition between cultural groups. The key concept in this extension is the emergent group-level trait. This type of trait is characterized by the structured organization of differentiated individuals and constitutes a unit of selection that is qualitatively different from selection on groups as defined by traditional multilevel selection (MLS) theory. As a corollary, I argue that the traditional focus on cooperation as the defining feature of human societies has missed an essential feature of cooperative groups. Traditional models of cooperation assume that interacting with one cooperator is equivalent to interacting with any other. However, human groups involve differential roles, meaning that receiving aid from one individual is often preferred to receiving aid from another. In this target article, I discuss the emergence and evolution of group-level traits and the implications for the theory of cultural evolution, including ramifications for the evolution of human cooperation, technology, and cultural institutions, and for the equivalency of multilevel selection and inclusive fitness approaches.

Evaluation of a nurse practitioner disease management model for chronic heart failure: a multi-site implementation study.

PubMed

Lowery, Julie; Hopp, Faith; Subramanian, Usha; Wiitala, Wyndy; Welsh, Deborah E; Larkin, Angela; Stemmer, Karen; Zak, Cassandra; Vaitkevicius, Peter

2012-01-01

While disease management appears to be effective in selected, small groups of CHF patients from randomized controlled trials, its effectiveness in a broader CHF patient population is not known. This prospective, quasi-experimental study compared patient outcomes under a nurse practitioner-led disease management model (intervention group) with outcomes under usual care (control group) in both primary and tertiary medical centers. The study included 969 veterans (458 intervention, 511 control) treated for CHF at six VA medical centers. Intervention patients had significantly fewer (p<0.05) CHF and all-cause admissions at one-year follow-up, and lower mortality at both one- and two-year follow-up. These data provide support for the potential effectiveness of the intervention, and suggest that the evidence from RCTs of disease management models for CHF can be translated into clinical practice, even without the benefits of a selected patient population and dedicated resources often found in RCTs. © 2011 Wiley Periodicals, Inc.

Alterations of selected iron management parameters and activity in food-restricted female Wistar rats (animal anorexia models).

PubMed

Wojciak, Rafal W

2014-03-01

The aim of this study was to assess the influence of food-restricted diets (anorexia models) on iron management and activity of rats. 48 rats were divided into 6 groups: 1 control (K) and 5 testing groups (K/2, GI, GII, GIII, GIV). K was fed ad libitum. K/2 received half the portion of the diet of K. The other groups received 100% of the diet eaten by K, but with different models of food restriction: GI-1 day on, 1 day starvation; GII-2 days on, 2 days starvation; GIII-3 days on, 3 days starvation; and GIV-4 days on, 4 days starvation. As a result, all testing groups ate half of the diet consumed by the control group. The concentrations of iron in selected tissues, ferritin, and selected iron management parameters in blood were examined, as well as the animals' activities associated with food craving. The animal anorexia models used in this study had a significant influence on the blood concentrations of hemoglobin (p < 0.01), hematocrit (p < 0.05), RBC (p < 0.05), iron levels in liver (p < 0.05), kidney (p < 0.001), and heart (p < 0.05), the serum ferritin concentration (p < 0.001) and the rats activity (p < 0.001); whereas there was no influence on the other parameters. Generally, the statistically negative effects of starvation models on iron management parameters and activity of animals were observed. However, these effects were dependent on the model of anorexia more than on the quantity of food intake. The negative effect of food deprivation on iron deficiency and rat activities were observed in all groups; however, the strongest effect was noticed in those animals subject to chronic starvation. Acute deprivations caused the reduction of activity in the rats, however, chronic starvation caused an increase in the activity of the first phase of the experiment, followed by a decline in the subsequent phase. It is possible that stress and frustration as well as depression may be caused by insufficient food intake, and as a result, by iron deficiency in a diet similar to human anorexia. However, more animal/human comparison studies are necessary.

A novel computer based expert decision making model for prostate cancer disease management.

PubMed

Richman, Martin B; Forman, Ernest H; Bayazit, Yildirim; Einstein, Douglas B; Resnick, Martin I; Stovsky, Mark D

2005-12-01

We propose a strategic, computer based, prostate cancer decision making model based on the analytic hierarchy process. We developed a model that improves physician-patient joint decision making and enhances the treatment selection process by making this critical decision rational and evidence based. Two groups (patient and physician-expert) completed a clinical study comparing an initial disease management choice with the highest ranked option generated by the computer model. Participants made pairwise comparisons to derive priorities for the objectives and subobjectives related to the disease management decision. The weighted comparisons were then applied to treatment options to yield prioritized rank lists that reflect the likelihood that a given alternative will achieve the participant treatment goal. Aggregate data were evaluated by inconsistency ratio analysis and sensitivity analysis, which assessed the influence of individual objectives and subobjectives on the final rank list of treatment options. Inconsistency ratios less than 0.05 were reliably generated, indicating that judgments made within the model were mathematically rational. The aggregate prioritized list of treatment options was tabulated for the patient and physician groups with similar outcomes for the 2 groups. Analysis of the major defining objectives in the treatment selection decision demonstrated the same rank order for the patient and physician groups with cure, survival and quality of life being more important than controlling cancer, preventing major complications of treatment, preventing blood transfusion complications and limiting treatment cost. Analysis of subobjectives, including quality of life and sexual dysfunction, produced similar priority rankings for the patient and physician groups. Concordance between initial treatment choice and the highest weighted model option differed between the groups with the patient group having 59% concordance and the physician group having only 42% concordance. This study successfully validated the usefulness of a computer based prostate cancer management decision making model to produce individualized, rational, clinically appropriate disease management decisions without physician bias.

Modeling Selection and Extinction Mechanisms of Biological Systems

NASA Astrophysics Data System (ADS)

Amirjanov, Adil

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

Long-Term Prognostic Validity of Talent Selections: Comparing National and Regional Coaches, Laypersons and Novices

PubMed Central

Schorer, Jörg; Rienhoff, Rebecca; Fischer, Lennart; Baker, Joseph

2017-01-01

In most sports, the development of elite athletes is a long-term process of talent identification and support. Typically, talent selection systems administer a multi-faceted strategy including national coach observations and varying physical and psychological tests when deciding who is chosen for talent development. The aim of this exploratory study was to evaluate the prognostic validity of talent selections by varying groups 10 years after they had been conducted. This study used a unique, multi-phased approach. Phase 1 involved players (n = 68) in 2001 completing a battery of general and sport-specific tests of handball ‘talent’ and performance. In Phase 2, national and regional coaches (n = 7) in 2001 who attended training camps identified the most talented players. In Phase 3, current novice and advanced handball players (n = 12 in each group) selected the most talented from short videos of matches played during the talent camp. Analyses compared predictions among all groups with a best model-fit derived from the motor tests. Results revealed little difference between regional and national coaches in the prediction of future performance and little difference in forecasting performance between novices and players. The best model-fit regression by the motor-tests outperformed all predictions. While several limitations are discussed, this study is a useful starting point for future investigations considering athlete selection decisions in talent identification in sport. PMID:28744238

Long-Term Prognostic Validity of Talent Selections: Comparing National and Regional Coaches, Laypersons and Novices.

PubMed

Schorer, Jörg; Rienhoff, Rebecca; Fischer, Lennart; Baker, Joseph

2017-01-01

In most sports, the development of elite athletes is a long-term process of talent identification and support. Typically, talent selection systems administer a multi-faceted strategy including national coach observations and varying physical and psychological tests when deciding who is chosen for talent development. The aim of this exploratory study was to evaluate the prognostic validity of talent selections by varying groups 10 years after they had been conducted. This study used a unique, multi-phased approach. Phase 1 involved players ( n = 68) in 2001 completing a battery of general and sport-specific tests of handball 'talent' and performance. In Phase 2, national and regional coaches ( n = 7) in 2001 who attended training camps identified the most talented players. In Phase 3, current novice and advanced handball players ( n = 12 in each group) selected the most talented from short videos of matches played during the talent camp. Analyses compared predictions among all groups with a best model-fit derived from the motor tests. Results revealed little difference between regional and national coaches in the prediction of future performance and little difference in forecasting performance between novices and players. The best model-fit regression by the motor-tests outperformed all predictions. While several limitations are discussed, this study is a useful starting point for future investigations considering athlete selection decisions in talent identification in sport.

Accurate template-based modeling in CASP12 using the IntFOLD4-TS, ModFOLD6, and ReFOLD methods.

PubMed

McGuffin, Liam J; Shuid, Ahmad N; Kempster, Robert; Maghrabi, Ali H A; Nealon, John O; Salehe, Bajuna R; Atkins, Jennifer D; Roche, Daniel B

2018-03-01

Our aim in CASP12 was to improve our Template-Based Modeling (TBM) methods through better model selection, accuracy self-estimate (ASE) scores and refinement. To meet this aim, we developed two new automated methods, which we used to score, rank, and improve upon the provided server models. Firstly, the ModFOLD6_rank method, for improved global Quality Assessment (QA), model ranking and the detection of local errors. Secondly, the ReFOLD method for fixing errors through iterative QA guided refinement. For our automated predictions we developed the IntFOLD4-TS protocol, which integrates the ModFOLD6_rank method for scoring the multiple-template models that were generated using a number of alternative sequence-structure alignments. Overall, our selection of top models and ASE scores using ModFOLD6_rank was an improvement on our previous approaches. In addition, it was worthwhile attempting to repair the detected errors in the top selected models using ReFOLD, which gave us an overall gain in performance. According to the assessors' formula, the IntFOLD4 server ranked 3rd/5th (average Z-score > 0.0/-2.0) on the server only targets, and our manual predictions (McGuffin group) ranked 1st/2nd (average Z-score > -2.0/0.0) compared to all other groups. © 2017 Wiley Periodicals, Inc.

Report of Economics Work Group A.

ERIC Educational Resources Information Center

Moyer, J.; And Others

1992-01-01

This summary of a seminar meeting on economics issues and the "blindness system" addresses the economics of four service delivery models (charity, medical, public provider, and business models) and points to consider in selecting a model (professional specialization, integration, and client roles). A chart compares service delivery principles…

Fact Sheet: A Technical Guide to Ground-Water Model Selection at Sites Contaminated with Radioactive Substances

EPA Pesticide Factsheets

This fact sheet summarizes the findings of a report drafted by a joint Interagency Environmental Pathway Modeling Working Group. It is to be used by technical staff responsible for implementing flow and transport models to support cleanup decisions.

Testing Group Mean Differences of Latent Variables in Multilevel Data Using Multiple-Group Multilevel CFA and Multilevel MIMIC Modeling.

PubMed

Kim, Eun Sook; Cao, Chunhua

2015-01-01

Considering that group comparisons are common in social science, we examined two latent group mean testing methods when groups of interest were either at the between or within level of multilevel data: multiple-group multilevel confirmatory factor analysis (MG ML CFA) and multilevel multiple-indicators multiple-causes modeling (ML MIMIC). The performance of these methods were investigated through three Monte Carlo studies. In Studies 1 and 2, either factor variances or residual variances were manipulated to be heterogeneous between groups. In Study 3, which focused on within-level multiple-group analysis, six different model specifications were considered depending on how to model the intra-class group correlation (i.e., correlation between random effect factors for groups within cluster). The results of simulations generally supported the adequacy of MG ML CFA and ML MIMIC for multiple-group analysis with multilevel data. The two methods did not show any notable difference in the latent group mean testing across three studies. Finally, a demonstration with real data and guidelines in selecting an appropriate approach to multilevel multiple-group analysis are provided.

A multicriteria decision making model for assessment and selection of an ERP in a logistics context

NASA Astrophysics Data System (ADS)

Pereira, Teresa; Ferreira, Fernanda A.

2017-07-01

The aim of this work is to apply a methodology of decision support based on a multicriteria decision analyses (MCDA) model that allows the assessment and selection of an Enterprise Resource Planning (ERP) in a Portuguese logistics company by Group Decision Maker (GDM). A Decision Support system (DSS) that implements a MCDA - Multicriteria Methodology for the Assessment and Selection of Information Systems / Information Technologies (MMASSI / IT) is used based on its features and facility to change and adapt the model to a given scope. Using this DSS it was obtained the information system that best suited to the decisional context, being this result evaluated through a sensitivity and robustness analysis.

Selection of branded alcoholic beverages by underage drinkers.

PubMed

Ross, Craig S; Ostroff, Joshua; Naimi, Timothy S; DeJong, William; Siegel, Michael B; Jernigan, David H

2015-05-01

The purpose of this study was to identify reasons why youth choose to drink specific brands of alcohol and to determine if these reasons are associated with problem drinking patterns and outcomes. We conducted an Internet survey of 1,031 youth aged 13-20 years who reported drinking within the past 30 days. Of these, 541 youth who reported having a choice of multiple brands of alcohol the last time they drank stated (yes/no) whether each of 16 different reasons had influenced their choice of a specific brand. We reduced these 16 reasons to three principal components and used latent class modeling to identify five groups of youth with similar reasons for selecting a brand, which we then profiled. We grouped respondents into the following brand selection groups: "Brand Ambassadors" who were distinguished from other clusters by selecting a brand because they identified with it (32.5% of respondents), "Tasters" who selected a brand because they expected it to taste good (27.2%), "Bargain Hunters" who selected a brand because it was inexpensive (18.5%), "Copycats" who selected a brand because they had seen adults drinking it or seen it consumed in movies or other media (10.4%), and "Others" (11.5%). Brand ambassadors and copycats reported the largest amount of alcohol consumed and had the greatest prevalence of both heavy episodic drinking and negative alcohol-related health consequences. Underage drinkers who cite marketing influences and adult or media modeling of brand choices as their reasons for selecting alcohol brands are likely to drink more and incur adverse consequences from drinking. Copyright © 2015 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Evolution of synchronization and desynchronization in digital organisms.

PubMed

Knoester, David B; McKinley, Philip K

2011-01-01

We present a study in the evolution of temporal behavior, specifically synchronization and desynchronization, through digital evolution and group selection. In digital evolution, a population of self-replicating computer programs exists in a user-defined computational environment and is subject to instruction-level mutations and natural selection. Group selection links the survival of the individual to the survival of its group, thus encouraging cooperation. Previous approaches to engineering synchronization and desynchronization algorithms have taken inspiration from nature: In the well-known firefly model, the only form of communication between agents is in the form of flash messages among neighbors. Here we demonstrate that populations of digital organisms, provided with a similar mechanism and minimal information about their environment, are capable of evolving algorithms for synchronization and desynchronization, and that the evolved behaviors are robust to message loss. We further describe how the evolved behavior for synchronization mimics that of the well-known Ermentrout model for firefly synchronization in biology. In addition to discovering self-organizing behaviors for distributed computing systems, this result indicates that digital evolution may be used to further our understanding of synchronization in biology.

Updated Prognostic Model for Predicting Overall Survival in First-Line Chemotherapy for Patients With Metastatic Castration-Resistant Prostate Cancer

PubMed Central

Halabi, Susan; Lin, Chen-Yen; Kelly, W. Kevin; Fizazi, Karim S.; Moul, Judd W.; Kaplan, Ellen B.; Morris, Michael J.; Small, Eric J.

2014-01-01

Purpose Prognostic models for overall survival (OS) for patients with metastatic castration-resistant prostate cancer (mCRPC) are dated and do not reflect significant advances in treatment options available for these patients. This work developed and validated an updated prognostic model to predict OS in patients receiving first-line chemotherapy. Methods Data from a phase III trial of 1,050 patients with mCRPC were used (Cancer and Leukemia Group B CALGB-90401 [Alliance]). The data were randomly split into training and testing sets. A separate phase III trial served as an independent validation set. Adaptive least absolute shrinkage and selection operator selected eight factors prognostic for OS. A predictive score was computed from the regression coefficients and used to classify patients into low- and high-risk groups. The model was assessed for its predictive accuracy using the time-dependent area under the curve (tAUC). Results The model included Eastern Cooperative Oncology Group performance status, disease site, lactate dehydrogenase, opioid analgesic use, albumin, hemoglobin, prostate-specific antigen, and alkaline phosphatase. Median OS values in the high- and low-risk groups, respectively, in the testing set were 17 and 30 months (hazard ratio [HR], 2.2; P < .001); in the validation set they were 14 and 26 months (HR, 2.9; P < .001). The tAUCs were 0.73 (95% CI, 0.70 to 0.73) and 0.76 (95% CI, 0.72 to 0.76) in the testing and validation sets, respectively. Conclusion An updated prognostic model for OS in patients with mCRPC receiving first-line chemotherapy was developed and validated on an external set. This model can be used to predict OS, as well as to better select patients to participate in trials on the basis of their prognosis. PMID:24449231

Two-level structural sparsity regularization for identifying lattices and defects in noisy images

DOE PAGES

Li, Xin; Belianinov, Alex; Dyck, Ondrej E.; ...

2018-03-09

Here, this paper presents a regularized regression model with a two-level structural sparsity penalty applied to locate individual atoms in a noisy scanning transmission electron microscopy image (STEM). In crystals, the locations of atoms is symmetric, condensed into a few lattice groups. Therefore, by identifying the underlying lattice in a given image, individual atoms can be accurately located. We propose to formulate the identification of the lattice groups as a sparse group selection problem. Furthermore, real atomic scale images contain defects and vacancies, so atomic identification based solely on a lattice group may result in false positives and false negatives.more » To minimize error, model includes an individual sparsity regularization in addition to the group sparsity for a within-group selection, which results in a regression model with a two-level sparsity regularization. We propose a modification of the group orthogonal matching pursuit (gOMP) algorithm with a thresholding step to solve the atom finding problem. The convergence and statistical analyses of the proposed algorithm are presented. The proposed algorithm is also evaluated through numerical experiments with simulated images. The applicability of the algorithm on determination of atom structures and identification of imaging distortions and atomic defects was demonstrated using three real STEM images. In conclusion, we believe this is an important step toward automatic phase identification and assignment with the advent of genomic databases for materials.« less

Two-level structural sparsity regularization for identifying lattices and defects in noisy images

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

Li, Xin; Belianinov, Alex; Dyck, Ondrej E.

Here, this paper presents a regularized regression model with a two-level structural sparsity penalty applied to locate individual atoms in a noisy scanning transmission electron microscopy image (STEM). In crystals, the locations of atoms is symmetric, condensed into a few lattice groups. Therefore, by identifying the underlying lattice in a given image, individual atoms can be accurately located. We propose to formulate the identification of the lattice groups as a sparse group selection problem. Furthermore, real atomic scale images contain defects and vacancies, so atomic identification based solely on a lattice group may result in false positives and false negatives.more » To minimize error, model includes an individual sparsity regularization in addition to the group sparsity for a within-group selection, which results in a regression model with a two-level sparsity regularization. We propose a modification of the group orthogonal matching pursuit (gOMP) algorithm with a thresholding step to solve the atom finding problem. The convergence and statistical analyses of the proposed algorithm are presented. The proposed algorithm is also evaluated through numerical experiments with simulated images. The applicability of the algorithm on determination of atom structures and identification of imaging distortions and atomic defects was demonstrated using three real STEM images. In conclusion, we believe this is an important step toward automatic phase identification and assignment with the advent of genomic databases for materials.« less

Biological evolution and statistical physics

NASA Astrophysics Data System (ADS)

Drossel, Barbara

2001-03-01

This review is an introduction to theoretical models and mathematical calculations for biological evolution, aimed at physicists. The methods in the field are naturally very similar to those used in statistical physics, although the majority of publications have appeared in biology journals. The review has three parts, which can be read independently. The first part deals with evolution in fitness landscapes and includes Fisher's theorem, adaptive walks, quasispecies models, effects of finite population sizes, and neutral evolution. The second part studies models of coevolution, including evolutionary game theory, kin selection, group selection, sexual selection, speciation, and coevolution of hosts and parasites. The third part discusses models for networks of interacting species and their extinction avalanches. Throughout the review, attention is paid to giving the necessary biological information, and to pointing out the assumptions underlying the models, and their limits of validity.

Studies of benzamide- and thiol-based histone deacetylase inhibitors in models of oxidative-stress-induced neuronal death: identification of some HDAC3-selective inhibitors.

PubMed

Chen, Yufeng; He, Rong; Chen, Yihua; D'Annibale, Melissa A; Langley, Brett; Kozikowski, Alan P

2009-05-01

We compare three structurally different classes of histone deacetylase (HDAC) inhibitors that contain benzamide, hydroxamate, or thiol groups as the zinc binding group (ZBG) for their ability to protect cortical neurons in culture from cell death induced by oxidative stress. This study reveals that none of the benzamide-based HDAC inhibitors (HDACIs) provides any neuroprotection whatsoever, in distinct contrast to HDACIs that contain other ZBGs. Some of the sulfur-containing HDACIs, namely the thiols, thioesters, and disulfides present modest neuroprotective activity but show toxicity at higher concentrations. Taken together, these data demonstrate that the HDAC6-selective mercaptoacetamides that were reported previously provide the best protection in the homocysteic acid model of oxidative stress, thus further supporting their study in animal models of neurodegenerative diseases.

78 FR 79579 - Energy Conservation Program: Alternative Efficiency Determination Methods, Basic Model Definition...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-31

... Working Group agreed on a one- sided 5 percent tolerance when comparing the validation test results to the... one DOE representative. 78 FR 22431. The members of the Working Group were selected to ensure a broad... Issues 1. Pre-Approval The Working Group unanimously recommended that DOE not require pre- approval for...

Selection of proper candidates with resected pathological stage IIIA-N2 non-small cell lung cancer for postoperative radiotherapy

PubMed Central

Hui, Zhouguang; Dai, Honghai; Liang, Jun; Lv, Jima; Zhou, Zongmei; Feng, Qinfu; Xiao, Zefen; Chen, Dongfu; Zhang, Hongxing; Yin, Weibo; Wang, Luhua

2015-01-01

Background To establish a prediction model in selecting fit patients with resected pIIIA-N2 non-small cell lung cancer (NSCLC) for postoperative radiotherapy (PORT), and evaluate the model in clinical practice. Methods Between January 2003 and December 2005, 221 patients with resected pIIIA-N2 NSCLC were retrospectively analyzed. The effect of PORT on overall survival (OS) of patients with different clinicopathological factors was evaluated and the results were used to establish a prediction model to select patients fit for PORT. Results Compared with the control, PORT significantly improved the OS of patients with a smoking index ≤400 (P = 0.033), cN2 (P = 0.003), pT3 (P = 0.014), squamous cell carcinoma (SCC) (P = 0.013), or ≥4 positive nodes (P = 0.025). Patients were divided from zero to all five factors into low, middle, and high PORT index (PORT-I) groups (scored 0–1, 2, and 3–5, respectively). PORT did not improve OS (3-year, P = 0.531), disease free survival (DFS) (P = 0.358), or loco-regional recurrence free survival (LRFS) (P = 0.412) in the low PORT-I group. PORT significantly improved OS (P = 0.033), and tended to improve DFS (P = 0.064), but not LRFS (P = 0.287) in the middle PORT-I group. PORT could significantly improve OS (P = 0.000), DFS (P = 0.000), and LRFS (P = 0.006) in the high PORT-I group. Conclusion The prediction model is valuable in selecting patients with resected pIIIA-N2 NSCLC fit for PORT. PORT is strongly recommended for patients with three or more of the five factors of smoking index ≤400, cN2, pT3, SCC, and ≥4 positive nodes. PMID:26273382

Random genetic drift, natural selection, and noise in human cranial evolution.

PubMed

Roseman, Charles C

2016-08-01

This study assesses the extent to which relationships among groups complicate comparative studies of adaptation in recent human cranial variation and the extent to which departures from neutral additive models of evolution hinder the reconstruction of population relationships among groups using cranial morphology. Using a maximum likelihood evolutionary model fitting approach and a mixed population genomic and cranial data set, I evaluate the relative fits of several widely used models of human cranial evolution. Moreover, I compare the goodness of fit of models of cranial evolution constrained by genomic variation to test hypotheses about population specific departures from neutrality. Models from population genomics are much better fits to cranial variation than are traditional models from comparative human biology. There is not enough evolutionary information in the cranium to reconstruct much of recent human evolution but the influence of population history on cranial variation is strong enough to cause comparative studies of adaptation serious difficulties. Deviations from a model of random genetic drift along a tree-like population history show the importance of environmental effects, gene flow, and/or natural selection on human cranial variation. Moreover, there is a strong signal of the effect of natural selection or an environmental factor on a group of humans from Siberia. The evolution of the human cranium is complex and no one evolutionary process has prevailed at the expense of all others. A holistic unification of phenome, genome, and environmental context, gives us a strong point of purchase on these problems, which is unavailable to any one traditional approach alone. Am J Phys Anthropol 160:582-592, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Selection Index in the Study of Adaptability and Stability in Maize

PubMed Central

Lunezzo de Oliveira, Rogério; Garcia Von Pinho, Renzo; Furtado Ferreira, Daniel; Costa Melo, Wagner Mateus

2014-01-01

This paper proposes an alternative method for evaluating the stability and adaptability of maize hybrids using a genotype-ideotype distance index (GIDI) for selection. Data from seven variables were used, obtained through evaluation of 25 maize hybrids at six sites in southern Brazil. The GIDI was estimated by means of the generalized Mahalanobis distance for each plot of the test. We then proceeded to GGE biplot analysis in order to compare the predictive accuracy of the GGE models and the grouping of environments and to select the best five hybrids. The G × E interaction was significant for both variables assessed. The GGE model with two principal components obtained a predictive accuracy (PRECORR) of 0.8913 for the GIDI and 0.8709 for yield (t ha−1). Two groups of environments were obtained upon analyzing the GIDI, whereas all the environments remained in the same group upon analyzing yield. Coincidence occurred in only two hybrids considering evaluation of the two features. The GIDI assessment provided for selection of hybrids that combine adaptability and stability in most of the variables assessed, making its use more highly recommended than analyzing each variable separately. Not all the higher-yielding hybrids were the best in the other variables assessed. PMID:24696641

Predication of different stages of Alzheimer's disease using neighborhood component analysis and ensemble decision tree.

PubMed

Jin, Mingwu; Deng, Weishu

2018-05-15

There is a spectrum of the progression from healthy control (HC) to mild cognitive impairment (MCI) without conversion to Alzheimer's disease (AD), to MCI with conversion to AD (cMCI), and to AD. This study aims to predict the different disease stages using brain structural information provided by magnetic resonance imaging (MRI) data. The neighborhood component analysis (NCA) is applied to select most powerful features for prediction. The ensemble decision tree classifier is built to predict which group the subject belongs to. The best features and model parameters are determined by cross validation of the training data. Our results show that 16 out of a total of 429 features were selected by NCA using 240 training subjects, including MMSE score and structural measures in memory-related regions. The boosting tree model with NCA features can achieve prediction accuracy of 56.25% on 160 test subjects. Principal component analysis (PCA) and sequential feature selection (SFS) are used for feature selection, while support vector machine (SVM) is used for classification. The boosting tree model with NCA features outperforms all other combinations of feature selection and classification methods. The results suggest that NCA be a better feature selection strategy than PCA and SFS for the data used in this study. Ensemble tree classifier with boosting is more powerful than SVM to predict the subject group. However, more advanced feature selection and classification methods or additional measures besides structural MRI may be needed to improve the prediction performance. Copyright © 2018 Elsevier B.V. All rights reserved.

Comparison of statistical methods for detection of serum lipid biomarkers for mesothelioma and asbestos exposure.

PubMed

Xu, Rengyi; Mesaros, Clementina; Weng, Liwei; Snyder, Nathaniel W; Vachani, Anil; Blair, Ian A; Hwang, Wei-Ting

2017-07-01

We compared three statistical methods in selecting a panel of serum lipid biomarkers for mesothelioma and asbestos exposure. Serum samples from mesothelioma, asbestos-exposed subjects and controls (40 per group) were analyzed. Three variable selection methods were considered: top-ranked predictors from univariate model, stepwise and least absolute shrinkage and selection operator. Crossed-validated area under the receiver operating characteristic curve was used to compare the prediction performance. Lipids with high crossed-validated area under the curve were identified. Lipid with mass-to-charge ratio of 372.31 was selected by all three methods comparing mesothelioma versus control. Lipids with mass-to-charge ratio of 1464.80 and 329.21 were selected by two models for asbestos exposure versus control. Different methods selected a similar set of serum lipids. Combining candidate biomarkers can improve prediction.

Identifying Loci Under Selection Against Gene Flow in Isolation-with-Migration Models

PubMed Central

Sousa, Vitor C.; Carneiro, Miguel; Ferrand, Nuno; Hey, Jody

2013-01-01

When divergence occurs in the presence of gene flow, there can arise an interesting dynamic in which selection against gene flow, at sites associated with population-specific adaptations or genetic incompatibilities, can cause net gene flow to vary across the genome. Loci linked to sites under selection may experience reduced gene flow and may experience genetic bottlenecks by the action of nearby selective sweeps. Data from histories such as these may be poorly fitted by conventional neutral model approaches to demographic inference, which treat all loci as equally subject to forces of genetic drift and gene flow. To allow for demographic inference in the face of such histories, as well as the identification of loci affected by selection, we developed an isolation-with-migration model that explicitly provides for variation among genomic regions in migration rates and/or rates of genetic drift. The method allows for loci to fall into any of multiple groups, each characterized by a different set of parameters, thus relaxing the assumption that all loci share the same demography. By grouping loci, the method can be applied to data with multiple loci and still have tractable dimensionality and statistical power. We studied the performance of the method using simulated data, and we applied the method to study the divergence of two subspecies of European rabbits (Oryctolagus cuniculus). PMID:23457232

Spatial and Feature-Based Attention in a Layered Cortical Microcircuit Model

PubMed Central

Wagatsuma, Nobuhiko; Potjans, Tobias C.; Diesmann, Markus; Sakai, Ko; Fukai, Tomoki

2013-01-01

Directing attention to the spatial location or the distinguishing feature of a visual object modulates neuronal responses in the visual cortex and the stimulus discriminability of subjects. However, the spatial and feature-based modes of attention differently influence visual processing by changing the tuning properties of neurons. Intriguingly, neurons' tuning curves are modulated similarly across different visual areas under both these modes of attention. Here, we explored the mechanism underlying the effects of these two modes of visual attention on the orientation selectivity of visual cortical neurons. To do this, we developed a layered microcircuit model. This model describes multiple orientation-specific microcircuits sharing their receptive fields and consisting of layers 2/3, 4, 5, and 6. These microcircuits represent a functional grouping of cortical neurons and mutually interact via lateral inhibition and excitatory connections between groups with similar selectivity. The individual microcircuits receive bottom-up visual stimuli and top-down attention in different layers. A crucial assumption of the model is that feature-based attention activates orientation-specific microcircuits for the relevant feature selectively, whereas spatial attention activates all microcircuits homogeneously, irrespective of their orientation selectivity. Consequently, our model simultaneously accounts for the multiplicative scaling of neuronal responses in spatial attention and the additive modulations of orientation tuning curves in feature-based attention, which have been observed widely in various visual cortical areas. Simulations of the model predict contrasting differences between excitatory and inhibitory neurons in the two modes of attentional modulations. Furthermore, the model replicates the modulation of the psychophysical discriminability of visual stimuli in the presence of external noise. Our layered model with a biologically suggested laminar structure describes the basic circuit mechanism underlying the attention-mode specific modulations of neuronal responses and visual perception. PMID:24324628

Reconstruction of cartilage with clonal mesenchymal stem cell-acellular dermal matrix in cartilage defect model in nonhuman primates.

PubMed

Ma, Anlun; Jiang, Li; Song, Lijun; Hu, Yanxin; Dun, Hao; Daloze, Pierre; Yu, Yonglin; Jiang, Jianyuan; Zafarullah, Muhammad; Chen, Huifang

2013-07-01

Articular cartilage defects are commonly associated with trauma, inflammation and osteoarthritis. Mesenchymal stem cell (MSC)-based therapy is a promising novel approach for repairing articular cartilage. Direct intra-articular injection of uncommitted MSCs does not regenerate high-quality cartilage. This study explored utilization of a new three-dimensional, selected chondrogenic clonal MSC-loaded monkey acellular dermal matrix (MSC-ADM) scaffold to repair damaged cartilage in an experimental model of knee joint cartilage defect in Cynomolgus monkeys. MSCs were characterized for cell size, cell yield, phenotypes, proliferation and chondrogenic differentiation capacity. Chondrogenic differentiation assays were performed at different MSC passages by sulfated glycosaminoglycans (sGAG), collagen, and fluorescence activated cell sorter (FACS) analysis. Selected chondrogenic clonal MSCs were seeded onto ADM scaffold with the sandwich model and MSC-loaded ADM grafts were analyzed by confocal microscopy and scanning electron microscopy. Cartilage defects were treated with normal saline, clonal MSCs and clonal MSC-ADM grafts, respectively. The clinical parameters, and histological and immunohistochemical examinations were evaluated at weeks 8, 16, 24 post-treatment, respectively. Polyclonal and clonal MSCs could differentiate into the chondrogenic lineage after stimulation with suitable chondrogenic factors. They expressed mesenchymal markers and were negative for hematopoietic markers. Articular cartilage defects were considerably improved and repaired by selected chondrogenic clonal MSC-based treatment, particularly, in MSC-ADM-treated group. The histological scores in MSC-ADM-treated group were consistently higher than those of other groups. Our results suggest that selected chondrogenic clonal MSC-loaded ADM grafts could improve the cartilage lesions in Cynomolgus monkey model, which may be applicable for repairing similar human cartilage defects. Copyright © 2013 Elsevier B.V. All rights reserved.

An evolutionary theory of large-scale human warfare: Group-structured cultural selection.

PubMed

Zefferman, Matthew R; Mathew, Sarah

2015-01-01

When humans wage war, it is not unusual for battlefields to be strewn with dead warriors. These warriors typically were men in their reproductive prime who, had they not died in battle, might have gone on to father more children. Typically, they are also genetically unrelated to one another. We know of no other animal species in which reproductively capable, genetically unrelated individuals risk their lives in this manner. Because the immense private costs borne by individual warriors create benefits that are shared widely by others in their group, warfare is a stark evolutionary puzzle that is difficult to explain. Although several scholars have posited models of the evolution of human warfare, these models do not adequately explain how humans solve the problem of collective action in warfare at the evolutionarily novel scale of hundreds of genetically unrelated individuals. We propose that group-structured cultural selection explains this phenomenon. © 2015 Wiley Periodicals, Inc.

Sparse Group Penalized Integrative Analysis of Multiple Cancer Prognosis Datasets

PubMed Central

Liu, Jin; Huang, Jian; Xie, Yang; Ma, Shuangge

2014-01-01

SUMMARY In cancer research, high-throughput profiling studies have been extensively conducted, searching for markers associated with prognosis. Because of the “large d, small n” characteristic, results generated from the analysis of a single dataset can be unsatisfactory. Recent studies have shown that integrative analysis, which simultaneously analyzes multiple datasets, can be more effective than single-dataset analysis and classic meta-analysis. In most of existing integrative analysis, the homogeneity model has been assumed, which postulates that different datasets share the same set of markers. Several approaches have been designed to reinforce this assumption. In practice, different datasets may differ in terms of patient selection criteria, profiling techniques, and many other aspects. Such differences may make the homogeneity model too restricted. In this study, we assume the heterogeneity model, under which different datasets are allowed to have different sets of markers. With multiple cancer prognosis datasets, we adopt the AFT (accelerated failure time) model to describe survival. This model may have the lowest computational cost among popular semiparametric survival models. For marker selection, we adopt a sparse group MCP (minimax concave penalty) approach. This approach has an intuitive formulation and can be computed using an effective group coordinate descent algorithm. Simulation study shows that it outperforms the existing approaches under both the homogeneity and heterogeneity models. Data analysis further demonstrates the merit of heterogeneity model and proposed approach. PMID:23938111

Ability Estimation and Item Calibration Using the One and Three Parameter Logistic Models: A Comparative Study. Research Report 77-1.

ERIC Educational Resources Information Center

Reckase, Mark D.

Latent trait model calibration procedures were used on data obtained from a group testing program. The one-parameter model of Wright and Panchapakesan and the three-parameter logistic model of Wingersky, Wood, and Lord were selected for comparison. These models and their corresponding estimation procedures were compared, using actual and simulated…

Parochial altruism in humans.

PubMed

Bernhard, Helen; Fischbacher, Urs; Fehr, Ernst

2006-08-24

Social norms and the associated altruistic behaviours are decisive for the evolution of human cooperation and the maintenance of social order, and they affect family life, politics and economic interactions. However, as altruistic norm compliance and norm enforcement often emerge in the context of inter-group conflicts, they are likely to be shaped by parochialism--a preference for favouring the members of one's ethnic, racial or language group. We have conducted punishment experiments, which allow 'impartial' observers to punish norm violators, with indigenous groups in Papua New Guinea. Here we show that these experiments confirm the prediction of parochialism. We found that punishers protect ingroup victims--who suffer from a norm violation--much more than they do outgroup victims, regardless of the norm violator's group affiliation. Norm violators also expect that punishers will be lenient if the latter belong to their social group. As a consequence, norm violations occur more often if the punisher and the norm violator belong to the same group. Our results are puzzling for evolutionary multi-level selection theories based on selective group extinction as well as for theories of individual selection; they also indicate the need to explicitly examine the interactions between individuals stemming from different groups in evolutionary models.

Ecogeography, genetics, and the evolution of human body form.

PubMed

Roseman, Charles C; Auerbach, Benjamin M

2015-01-01

Genetic resemblances among groups are non-randomly distributed in humans. This population structure may influence the correlations between traits and environmental drivers of natural selection thus complicating the interpretation of the fossil record when modern human variation is used as a referential model. In this paper, we examine the effects of population structure and natural selection on postcranial traits that reflect body size and shape with application to the more general issue of how climate - using latitude as a proxy - has influenced hominin morphological variation. We compare models that include terms reflecting population structure, ascertained from globally distributed microsatellite data, and latitude on postcranial phenotypes derived from skeletal dimensions taken from a large global sample of modern humans. We find that models with a population structure term fit better than a model of natural selection along a latitudinal cline in all cases. A model including both latitude and population structure terms is a good fit to distal limb element lengths and bi-iliac breadth, indicating that multiple evolutionary forces shaped these morphologies. In contrast, a model that included only a population structure term best explained femoral head diameter and the crural index. The results demonstrate that population structure is an important part of human postcranial variation, and that clinally distributed natural selection is not sufficient to explain among-group differentiation. The distribution of human body form is strongly influenced by the contingencies of modern human origins, which calls for new ways to approach problems in the evolution of human variation, past and present. Copyright © 2014 Elsevier Ltd. All rights reserved.

Surgical model pig ex vivo for venous dissection teaching in medical schools.

PubMed

Tube, Milton Ignacio Carvalho; Spencer-Netto, Fernando Antonio Campelo; Oliveira, Anderson Igor Pereira de; Holanda, Arthur Cesário de; Barros, Bruno Leão Dos Santos; Rezende, Caio Cezar Gomes; Cavalcanti, João Pedro Guerra; Batista, Marília Apolinário; Campos, Josemberg Marins

2017-02-01

To investigate a method for development of surgical skills in medical students simulating venous dissection in surgical ex vivo pig model. Prospective, analytical, experimental, controlled study with four stages: selection, theoretical teaching, training and assessment. Sample of 312 students was divided into two groups: Group A - 2nd semester students; Group B - students of 8th semester. The groups were divided into five groups of 12 students, trained two hours per week in the semester. They set up four models to three students in each skill station assisted by a monitor. Teaching protocol emergency procedures training were applied to venous dissection, test goal-discursive and OSATS scale. The pre-test confirmed that the methodology has not been previously applied to the students. The averages obtained in the theoretical evaluation reached satisfactory parameters in both groups. The results of applying OSATS scale showed the best performance in group A compared to group B, however, both groups had satisfactory medium. The method was enough to raise a satisfactory level of skill both groups in venous dissection running on surgical swine ex vivo models.

Selection of shuttle payload data processing drivers for the data system new technology study

NASA Technical Reports Server (NTRS)

1976-01-01

An investigation of all payloads in the IBM disciplines and the selection of driver payloads within each discipline are described. The driver payloads were selected on the basis of their data processing requirements. These requirements are measured by a weighting scheme. The total requirements for each discipline are estimated by use of the technology payload model. The driver selection process which was both a payload by payload comparison and a comparison of expected groupings of payloads was examined.

A User’s Guide for the Software Technology Economic Impact Model

DTIC Science & Technology

1991-10-01

Copy 16 oft22 oples U AD-A248 023 \\\\1\\\\\\i\\~\\1\\1\\\\1\\1\\11\\\\\\l~ IDA DOCUMENT D-971 E Tt USER’S GUIDE FOR THE SOFTWARE TECHNOLOGY ECONOMIC IMPACT MODEL I... studied , and they are released by the President of IDA. Group Reports Group Reports record the findings and results of IDA established working groups and...the senior individuals responsible for the project and others as selected by IDA to ensure their high quality and relevance to the problems studied

Evaluating the influence of motor control on selective attention through a stochastic model: the paradigm of motor control dysfunction in cerebellar patient.

PubMed

Veneri, Giacomo; Federico, Antonio; Rufa, Alessandra

2014-01-01

Attention allows us to selectively process the vast amount of information with which we are confronted, prioritizing some aspects of information and ignoring others by focusing on a certain location or aspect of the visual scene. Selective attention is guided by two cognitive mechanisms: saliency of the image (bottom up) and endogenous mechanisms (top down). These two mechanisms interact to direct attention and plan eye movements; then, the movement profile is sent to the motor system, which must constantly update the command needed to produce the desired eye movement. A new approach is described here to study how the eye motor control could influence this selection mechanism in clinical behavior: two groups of patients (SCA2 and late onset cerebellar ataxia LOCA) with well-known problems of motor control were studied; patients performed a cognitively demanding task; the results were compared to a stochastic model based on Monte Carlo simulations and a group of healthy subjects. The analytical procedure evaluated some energy functions for understanding the process. The implemented model suggested that patients performed an optimal visual search, reducing intrinsic noise sources. Our findings theorize a strict correlation between the "optimal motor system" and the "optimal stimulus encoders."

Modeling Public School Partnerships: Merging Corporate and Community Issues.

ERIC Educational Resources Information Center

Clark, Cynthia E.; Brill, Dale A.

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

Modeling Homophily over Time with an Actor-Partner Interdependence Model

ERIC Educational Resources Information Center

Popp, Danielle; Laursen, Brett; Kerr, Margaret; Stattin, Hakan; Burk, William J.

2008-01-01

Selection and socialization have been implicated in friendship homophily, but the relative contributions of each are difficult to measure simultaneously because of the nonindependent nature of the data. To address this problem, the authors applied a multiple-groups longitudinal actor-partner interdependence model (D. A. Kashy & D. A. Kenny,…

Beneficial laggards: multilevel selection, cooperative polymorphism and division of labour in threshold public good games

PubMed Central

2010-01-01

Background The origin and stability of cooperation is a hot topic in social and behavioural sciences. A complicated conundrum exists as defectors have an advantage over cooperators, whenever cooperation is costly so consequently, not cooperating pays off. In addition, the discovery that humans and some animal populations, such as lions, are polymorphic, where cooperators and defectors stably live together -- while defectors are not being punished--, is even more puzzling. Here we offer a novel explanation based on a Threshold Public Good Game (PGG) that includes the interaction of individual and group level selection, where individuals can contribute to multiple collective actions, in our model group hunting and group defense. Results Our results show that there are polymorphic equilibria in Threshold PGGs; that multi-level selection does not select for the most cooperators per group but selects those close to the optimum number of cooperators (in terms of the Threshold PGG). In particular for medium cost values division of labour evolves within the group with regard to the two types of cooperative actions (hunting vs. defense). Moreover we show evidence that spatial population structure promotes cooperation in multiple PGGs. We also demonstrate that these results apply for a wide range of non-linear benefit function types. Conclusions We demonstrate that cooperation can be stable in Threshold PGG, even when the proportion of so called free riders is high in the population. A fundamentally new mechanism is proposed how laggards, individuals that have a high tendency to defect during one specific group action can actually contribute to the fitness of the group, by playing part in an optimal resource allocation in Threshold Public Good Games. In general, our results show that acknowledging a multilevel selection process will open up novel explanations for collective actions. PMID:21044340

Latent Class Analysis of Incomplete Data via an Entropy-Based Criterion

PubMed Central

Larose, Chantal; Harel, Ofer; Kordas, Katarzyna; Dey, Dipak K.

2016-01-01

Latent class analysis is used to group categorical data into classes via a probability model. Model selection criteria then judge how well the model fits the data. When addressing incomplete data, the current methodology restricts the imputation to a single, pre-specified number of classes. We seek to develop an entropy-based model selection criterion that does not restrict the imputation to one number of clusters. Simulations show the new criterion performing well against the current standards of AIC and BIC, while a family studies application demonstrates how the criterion provides more detailed and useful results than AIC and BIC. PMID:27695391

Single embryo transfer by Day 3 time-lapse selection versus Day 5 conventional morphological selection: a randomized, open-label, non-inferiority trial.

PubMed

Yang, Lanlin; Cai, Sufen; Zhang, Shuoping; Kong, Xiangyi; Gu, Yifan; Lu, Changfu; Dai, Jing; Gong, Fei; Lu, Guangxiu; Lin, Ge

2018-05-01

Does single cleavage-stage (Day 3) embryo transfer using a time-lapse (TL) hierarchical classification model achieve comparable ongoing pregnancy rates (OPR) to single blastocyst (Day 5) transfer by conventional morphological (CM) selection? Day 3 single embryo transfer (SET) with a hierarchical classification model had a significantly lower OPR compared with Day 5 SET with CM selection. Cleavage-stage SET is an alternative to blastocyst SET. Time-lapse imaging assists better embryo selection, based on studies of pregnancy outcomes when adding time-lapse imaging to CM selection at the cleavage or blastocyst stage. This single-centre, randomized, open-label, active-controlled, non-inferiority study included 600 women between October 2015 and April 2017. Eligible patients were Chinese females, aged ≤36 years, who were undergoing their first or second fresh IVF cycle using their own oocytes, and who had FSH levels ≤12 IU/mL on Day 3 of the cycle and 10 or more oocytes retrieved. Patients who had underlying uterine conditions, oocyte donation, recurrent pregnancy loss, abnormal oocytes or <6 normally fertilized embryos (2PN) were excluded from the study participation. Patients were randomized 1:1 to either the cleavage-stage SET with a time-lapse hierarchical classification model for selection (D3 + TL) or blastocyst SET with CM selection (D5 + CM). All normally fertilized zygotes were cultured in Primo Vision. The study was conducted at a tertiary IVF centre (CITIC-Xiangya) and OPR was the primary outcome. A total of 600 patients were randomized to the two groups, among which 585 (D3 + TL = 290, D5 + CM = 295) were included in the Modified-intention-to-treat (mITT) population and 517 (D3 + TL = 261, D5 + CM = 256) were included in the PP population. In the per protocol (PP) population, OPR was significantly lower in the D3 group (59.4%, 155/261) than in the D5 group (68.4%, 175/256) (difference: -9.0%, 95% CI: -17.1%, -0.7%, P = 0.03). Analysis in mITT population showed a marginally significant difference in the OPR between the D3 + TL and D5 + CM groups (56.6 versus 64.1%, difference: -7.5%, 95% CI: -15.4%, 0.4%, P = 0.06). The D3 + TL group resulted in a markedly lower implantation rate than the D5 + CM group (64.4 versus 77.0%; P = 0.002) in the PP analysis, however, the early miscarriage rate did not significantly differ between the two groups. The study lacked a direct comparison between time-lapse and CM selections at cleavage-stage SET and was statistically underpowered to detect non-inferiority. The subject's eligibility criteria favouring women with a good prognosis for IVF weakened the generalizability of the results. The OPR from Day 3 cleavage-stage SET using hierarchical classification time-lapse selection was significantly lower compared with that from Day 5 blastocyst SET using conventional morphology, yet it appeared to be clinically acceptable in women underwent IVF. This study is supported by grants from Ferring Pharmaceuticals and the Program for New Century Excellent Talents in University, China. ChiCTR-ICR-15006600. 16 June 2015. 1 October 2015.

Reconstruction of Complex Directional Networks with Group Lasso Nonlinear Conditional Granger Causality.

PubMed

Yang, Guanxue; Wang, Lin; Wang, Xiaofan

2017-06-07

Reconstruction of networks underlying complex systems is one of the most crucial problems in many areas of engineering and science. In this paper, rather than identifying parameters of complex systems governed by pre-defined models or taking some polynomial and rational functions as a prior information for subsequent model selection, we put forward a general framework for nonlinear causal network reconstruction from time-series with limited observations. With obtaining multi-source datasets based on the data-fusion strategy, we propose a novel method to handle nonlinearity and directionality of complex networked systems, namely group lasso nonlinear conditional granger causality. Specially, our method can exploit different sets of radial basis functions to approximate the nonlinear interactions between each pair of nodes and integrate sparsity into grouped variables selection. The performance characteristic of our approach is firstly assessed with two types of simulated datasets from nonlinear vector autoregressive model and nonlinear dynamic models, and then verified based on the benchmark datasets from DREAM3 Challenge4. Effects of data size and noise intensity are also discussed. All of the results demonstrate that the proposed method performs better in terms of higher area under precision-recall curve.

Measurement equivalence of seven selected items of posttraumatic growth between black and white adult survivors of Hurricane Katrina.

PubMed

Rhodes, Alison M; Tran, Thanh V

2013-02-01

This study examined the equivalence or comparability of the measurement properties of seven selected items measuring posttraumatic growth among self-identified Black (n = 270) and White (n = 707) adult survivors of Hurricane Katrina, using data from the Baseline Survey of the Hurricane Katrina Community Advisory Group Study. Internal consistency reliability was equally good for both groups (Cronbach's alphas = .79), as were correlations between individual scale items and their respective overall scale. Confirmatory factor analysis of a congeneric measurement model of seven selected items of posttraumatic growth showed adequate measures of fit for both groups. The results showed only small variation in magnitude of factor loadings and measurement errors between the two samples. Tests of measurement invariance showed mixed results, but overall indicated that factor loading, error variance, and factor variance were similar between the two samples. These seven selected items can be useful for future large-scale surveys of posttraumatic growth.

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

PubMed Central

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

2015-01-01

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

On the evolutionary origins of the egalitarian syndrome

PubMed Central

Gavrilets, Sergey

2012-01-01

The evolutionary emergence of the egalitarian syndrome is one of the most intriguing unsolved puzzles related to the origins of modern humans. Standard explanations and models for cooperation and altruism—reciprocity, kin and group selection, and punishment—are not directly applicable to the emergence of egalitarian behavior in hierarchically organized groups that characterized the social life of our ancestors. Here I study an evolutionary model of group-living individuals competing for resources and reproductive success. In the model, the differences in fighting abilities lead to the emergence of hierarchies where stronger individuals take away resources from weaker individuals and, as a result, have higher reproductive success. First, I show that the logic of within-group competition implies under rather general conditions that each individual benefits if the transfer of the resource from a weaker group member to a stronger one is prevented. This effect is especially strong in small groups. Then I demonstrate that this effect can result in the evolution of a particular, genetically controlled psychology causing individuals to interfere in a bully–victim conflict on the side of the victim. A necessary condition is a high efficiency of coalitions in conflicts against the bullies. The egalitarian drive leads to a dramatic reduction in within-group inequality. Simultaneously it creates the conditions for the emergence of inequity aversion, empathy, compassion, and egalitarian moral values via the internalization of behavioral rules imposed by natural selection. It also promotes widespread cooperation via coalition formation. PMID:22891349

Can scrotal circumference-based selection discard bulls with good productive and reproductive potential?

PubMed Central

Villadiego, Faider Alberto Castaño; Camilo, Breno Soares; León, Victor Gomez; Peixoto, Thiago; Díaz, Edgar; Okano, Denise; Maitan, Paula; Lima, Daniel; Guimarães, Simone Facioni; Siqueira, Jeanne Broch; Pinho, Rogério

2018-01-01

Nonlinear mixed models were used to describe longitudinal scrotal circumference (SC) measurements of Nellore bulls. Models comparisons were based on Akaike’s information criterion, Bayesian information criterion, error sum of squares, adjusted R2 and percentage of convergence. Sequentially, the best model was used to compare the SC growth curve in bulls divergently classified according to SC at 18–21 months of age. For this, bulls were classified into five groups: SC < 28cm; 28cm ≤ SC < 30cm, 30cm ≤ SC < 32cm, 32cm ≤ SC < 34cm and SC ≥ 34cm. Michaelis-Menten model showed the best fit according to the mentioned criteria. In this model, β1 is the asymptotic SC value and β2 represents the time to half-final growth and may be related to sexual precocity. Parameters of the individual estimated growth curves were used to create a new dataset to evaluate the effect of the classification, farms, and year of birth on β1 and β2 parameters. Bulls of the largest SC group presented a larger predicted SC along all analyzed periods; nevertheless, smaller SC group showed predicted SC similar to intermediate SC groups (28cm ≤ SC < 32cm), around 1200 days of age. In this context, bulls classified as improper for reproduction at 18–21 months old can reach a similar condition to those considered as good condition. In terms of classification at 18–21 months, asymptotic SC was similar among groups, farms and years; however, β2 differed among groups indicating that differences in growth curves are related to sexual precocity. In summary, it seems that selection based on SC at too early ages may lead to discard bulls with suitable reproductive potential. PMID:29494597

Computational exploration of zinc binding groups for HDAC inhibition.

PubMed

Chen, Kai; Xu, Liping; Wiest, Olaf

2013-05-17

Histone deacetylases (HDACs) have emerged as important drug targets in epigenetics. The most common HDAC inhibitors use hydroxamic acids as zinc binding groups despite unfavorable pharmacokinetic properties. A two-stage protocol of M05-2X calculations of a library of 48 fragments in a small model active site, followed by QM/MM hybrid calculations of the full enzyme with selected binders, is used to prospectively select potential bidentate zinc binders. The energetics and interaction patterns of several zinc binders not previously used for the inhibition of HDACs are discussed.

The large soybean (Glycine max) WRKY TF family expanded by segmental duplication events and subsequent divergent selection among subgroups.

PubMed

Yin, Guangjun; Xu, Hongliang; Xiao, Shuyang; Qin, Yajuan; Li, Yaxuan; Yan, Yueming; Hu, Yingkao

2013-10-03

WRKY genes encode one of the most abundant groups of transcription factors in higher plants, and its members regulate important biological process such as growth, development, and responses to biotic and abiotic stresses. Although the soybean genome sequence has been published, functional studies on soybean genes still lag behind those of other species. We identified a total of 133 WRKY members in the soybean genome. According to structural features of their encoded proteins and to the phylogenetic tree, the soybean WRKY family could be classified into three groups (groups I, II, and III). A majority of WRKY genes (76.7%; 102 of 133) were segmentally duplicated and 13.5% (18 of 133) of the genes were tandemly duplicated. This pattern was not apparent in Arabidopsis or rice. The transcriptome atlas revealed notable differential expression in either transcript abundance or in expression patterns under normal growth conditions, which indicated wide functional divergence in this family. Furthermore, some critical amino acids were detected using DIVERGE v2.0 in specific comparisons, suggesting that these sites have contributed to functional divergence among groups or subgroups. In addition, site model and branch-site model analyses of positive Darwinian selection (PDS) showed that different selection regimes could have affected the evolution of these groups. Sites with high probabilities of having been under PDS were found in groups I, II c, II e, and III. Together, these results contribute to a detailed understanding of the molecular evolution of the WRKY gene family in soybean. In this work, all the WRKY genes, which were generated mainly through segmental duplication, were identified in the soybean genome. Moreover, differential expression and functional divergence of the duplicated WRKY genes were two major features of this family throughout their evolutionary history. Positive selection analysis revealed that the different groups have different evolutionary rates. Together, these results contribute to a detailed understanding of the molecular evolution of the WRKY gene family in soybean.

ICU-acquired candidemia within selective digestive decontamination studies: a meta-analysis.

PubMed

Hurley, James C

2015-11-01

To estimate the direct and indirect (contextual) effects of the factorized constituents of selective digestive decontamination and selective oropharyngeal decontamination (SDD/SOD), being topical antibiotic (TA) and protocolized antifungal prophylaxis (PAFP), on ICU-acquired candidemia. A broad range of ICU candidemia incidence studies were sourced to serve as points of reference. The candidemia incidence was extracted from component (control and intervention) groups decanted from studies of various designs (concurrent or non-concurrent) and whether investigating SDD/SOD versus non-TA methods of ICU infection prevention. The candidemia incidences were summarized in regression models using generalized estimating equation (GEE) methods. Groups derived from observational studies (no prevention method under study) provided an overarching external benchmark candidemia incidence for calibration. Within studies investigating SDD/SOD, the mean (and 95% confidence interval) candidemia incidence among concurrent component groups (40 control; 2.4%; 1.7-3.2% and 43 intervention groups; 2.4%; 1.6-3.1%), but not non-concurrent control groups (11 groups; 1.6%; 0.1-2.7%), is higher than that of the benchmark candidemia incidence derived from 54 observational groups (1.5%; 1.2-1.9%). The TA constituent within SDD/SOD has significant direct and indirect (contextual) effects in GEE models even after adjusting for the publication year and the group-wide presence of either candidemia risk factors or PAFP use. The TA constituent of SDD/SOD is associated with a contextual effect on candidemia incidence which is similar in magnitude to that of the conventional candidemia risk factors and against which PAFP partially attenuates. This increase is inapparent within individual SDD/SOD studies examined in isolation.

Which family physician should I choose? The analytic hierarchy process approach for ranking of criteria in the selection of a family physician.

PubMed

Kuruoglu, Emel; Guldal, Dilek; Mevsim, Vildan; Gunvar, Tolga

2015-08-05

Choosing the most appropriate family physician (FP) for the individual, plays a fundamental role in primary care. The aim of this study is to determine the selection criteria for the patients in choosing their family doctors and priority ranking of these criteria by using the multi-criteria decision-making method of the Analytic Hierarchy Process (AHP) model. The study was planned and conducted in two phases. In the first phase, factors affecting the patients' decisions were revealed with a qualitative research. In the next phase, the priorities of FP selection criteria were determined by using AHP model. Criteria were compared in pairs. 96 patient were asked to fill the information forms which contains comparison scores in the Family Health Centres. According to the analysis of focus group discussions FP selection criteria were congregated in to five groups: Individual Characteristics, Patient-Doctor relationship, Professional characteristics, the Setting, and Ethical Characteristics. For each of the 96 participants, comparison matrixes were formed based on the scores of their information forms. Of these, models of only 5 (5.2 %) of the participants were consistent, in other words, they have been able to score consistent ranking. The consistency ratios (CR) were found to be smaller than 0.10. Therefore the comparison matrix of this new model, which was formed based on the medians of scores only given by these 5 participants, was consistent (CR = 0.06 < 0.10). According to comparison results; with a 0.467 value-weight, the most important criterion for choosing a family physician is his/her 'Professional characteristics'. Selection criteria for choosing a FP were put in a priority order by using AHP model. These criteria can be used as measures for selecting alternative FPs in further researches.

On the use of published radiobiological parameters and the evaluation of NTCP models regarding lung pneumonitis in clinical breast radiotherapy.

PubMed

Svolos, Patricia; Tsougos, Ioannis; Kyrgias, Georgios; Kappas, Constantine; Theodorou, Kiki

2011-04-01

In this study we sought to evaluate and accent the importance of radiobiological parameter selection and implementation to the normal tissue complication probability (NTCP) models. The relative seriality (RS) and the Lyman-Kutcher-Burman (LKB) models were studied. For each model, a minimum and maximum set of radiobiological parameter sets was selected from the overall published sets applied in literature and a theoretical mean parameter set was computed. In order to investigate the potential model weaknesses in NTCP estimation and to point out the correct use of model parameters, these sets were used as input to the RS and the LKB model, estimating radiation induced complications for a group of 36 breast cancer patients treated with radiotherapy. The clinical endpoint examined was Radiation Pneumonitis. Each model was represented by a certain dose-response range when the selected parameter sets were applied. Comparing the models with their ranges, a large area of coincidence was revealed. If the parameter uncertainties (standard deviation) are included in the models, their area of coincidence might be enlarged, constraining even greater their predictive ability. The selection of the proper radiobiological parameter set for a given clinical endpoint is crucial. Published parameter values are not definite but should be accompanied by uncertainties, and one should be very careful when applying them to the NTCP models. Correct selection and proper implementation of published parameters provides a quite accurate fit of the NTCP models to the considered endpoint.

Lessons learned in deploying software estimation technology and tools

NASA Technical Reports Server (NTRS)

Panlilio-Yap, Nikki; Ho, Danny

1994-01-01

Developing a software product involves estimating various project parameters. This is typically done in the planning stages of the project when there is much uncertainty and very little information. Coming up with accurate estimates of effort, cost, schedule, and reliability is a critical problem faced by all software project managers. The use of estimation models and commercially available tools in conjunction with the best bottom-up estimates of software-development experts enhances the ability of a product development group to derive reasonable estimates of important project parameters. This paper describes the experience of the IBM Software Solutions (SWS) Toronto Laboratory in selecting software estimation models and tools and deploying their use to the laboratory's product development groups. It introduces the SLIM and COSTAR products, the software estimation tools selected for deployment to the product areas, and discusses the rationale for their selection. The paper also describes the mechanisms used for technology injection and tool deployment, and concludes with a discussion of important lessons learned in the technology and tool insertion process.

Selection and Storage of Perceptual Groups Is Constrained by a Discrete Resource in Working Memory

ERIC Educational Resources Information Center

Anderson, David E.; Vogel, Edward K.; Awh, Edward

2013-01-01

Perceptual grouping can lead observers to perceive a multielement scene as a smaller number of hierarchical units. Past work has shown that grouping enables more elements to be stored in visual working memory (WM). Although this may appear to contradict so-called discrete resource models that argue for fixed item limits in WM storage, it is also…

Simulating the Evolution of the Human Family: Cooperative Breeding Increases in Harsh Environments

PubMed Central

Smaldino, Paul E.; Newson, Lesley; Schank, Jeffrey C.; Richerson, Peter J.

2013-01-01

Verbal and mathematical models that consider the costs and benefits of behavioral strategies have been useful in explaining animal behavior and are often used as the basis of evolutionary explanations of human behavior. In most cases, however, these models do not account for the effects that group structure and cultural traditions within a human population have on the costs and benefits of its members' decisions. Nor do they consider the likelihood that cultural as well as genetic traits will be subject to natural selection. In this paper, we present an agent-based model that incorporates some key aspects of human social structure and life history. We investigate the evolution of a population under conditions of different environmental harshness and in which selection can occur at the level of the group as well as the level of the individual. We focus on the evolution of a socially learned characteristic related to individuals' willingness to contribute to raising the offspring of others within their family group. We find that environmental harshness increases the frequency of individuals who make such contributions. However, under the conditions we stipulate, we also find that environmental variability can allow groups to survive with lower frequencies of helpers. The model presented here is inevitably a simplified representation of a human population, but it provides a basis for future modeling work toward evolutionary explanations of human behavior that consider the influence of both genetic and cultural transmission of behavior. PMID:24278318

Simulating the evolution of the human family: cooperative breeding increases in harsh environments.

PubMed

Smaldino, Paul E; Newson, Lesley; Schank, Jeffrey C; Richerson, Peter J

2013-01-01

Verbal and mathematical models that consider the costs and benefits of behavioral strategies have been useful in explaining animal behavior and are often used as the basis of evolutionary explanations of human behavior. In most cases, however, these models do not account for the effects that group structure and cultural traditions within a human population have on the costs and benefits of its members' decisions. Nor do they consider the likelihood that cultural as well as genetic traits will be subject to natural selection. In this paper, we present an agent-based model that incorporates some key aspects of human social structure and life history. We investigate the evolution of a population under conditions of different environmental harshness and in which selection can occur at the level of the group as well as the level of the individual. We focus on the evolution of a socially learned characteristic related to individuals' willingness to contribute to raising the offspring of others within their family group. We find that environmental harshness increases the frequency of individuals who make such contributions. However, under the conditions we stipulate, we also find that environmental variability can allow groups to survive with lower frequencies of helpers. The model presented here is inevitably a simplified representation of a human population, but it provides a basis for future modeling work toward evolutionary explanations of human behavior that consider the influence of both genetic and cultural transmission of behavior.

A cost constraint alone has adverse effects on food selection and nutrient density: an analysis of human diets by linear programming.

PubMed

Darmon, Nicole; Ferguson, Elaine L; Briend, André

2002-12-01

Economic constraints may contribute to the unhealthy food choices observed among low socioeconomic groups in industrialized countries. The objective of the present study was to predict the food choices a rational individual would make to reduce his or her food budget, while retaining a diet as close as possible to the average population diet. Isoenergetic diets were modeled by linear programming. To ensure these diets were consistent with habitual food consumption patterns, departure from the average French diet was minimized and constraints that limited portion size and the amount of energy from food groups were introduced into the models. A cost constraint was introduced and progressively strengthened to assess the effect of cost on the selection of foods by the program. Strengthening the cost constraint reduced the proportion of energy contributed by fruits and vegetables, meat and dairy products and increased the proportion from cereals, sweets and added fats, a pattern similar to that observed among low socioeconomic groups. This decreased the nutritional quality of modeled diets, notably the lowest cost linear programming diets had lower vitamin C and beta-carotene densities than the mean French adult diet (i.e., <25% and 10% of the mean density, respectively). These results indicate that a simple cost constraint can decrease the nutrient densities of diets and influence food selection in ways that reproduce the food intake patterns observed among low socioeconomic groups. They suggest that economic measures will be needed to effectively improve the nutritional quality of diets consumed by these populations.

Theoretical study of chlordecone and surface groups interaction in an activated carbon model under acidic and neutral conditions.

PubMed

Gamboa-Carballo, Juan José; Melchor-Rodríguez, Kenia; Hernández-Valdés, Daniel; Enriquez-Victorero, Carlos; Montero-Alejo, Ana Lilian; Gaspard, Sarra; Jáuregui-Haza, Ulises Javier

2016-04-01

Activated carbons (ACs) are widely used in the purification of drinking water without almost any knowledge about the adsorption mechanisms of the persistent organic pollutants. Chlordecone (CLD, Kepone) is an organochlorinated synthetic compound that has been used mainly as agricultural insecticide. CLD has been identified and listed as a persistent organic pollutant by the Stockholm Convention. The selection of the best suited AC for this type of contaminants is mainly an empirical and costly process. A theoretical study of the influence of AC surface groups (SGs) on CLD adsorption is done in order to help understanding the process. This may provide a first selection criteria for the preparation of AC with suitable surface properties. A model of AC consisting of a seven membered ring graphene sheet (coronene) with a functional group on the edge was used to evaluate the influence of the SGs over the adsorption. Multiple Minima Hypersurface methodology (MMH) coupled with PM7 semiempirical Hamiltonian was employed in order to study the interactions of the chlordecone with SGs (hydroxyl and carboxyl) at acidic and neutral pH and different hydration conditions. Selected structures were re-optimized using CAM-B3LYP to achieve a well-defined electron density to characterize the interactions by the Quantum Theory of Atoms in Molecules approach. The deprotonated form of surface carboxyl and hydroxyl groups of AC models show the strongest interactions, suggesting a chemical adsorption. An increase in carboxylic SGs content is proposed to enhance CLD adsorption onto AC at neutral pH conditions. Copyright © 2016 Elsevier Inc. All rights reserved.

USING PHOTOVOICE WITH YOUTH TO DEVELOP A DRUG PREVENTION PROGRAM IN A RURAL HAWAIIAN COMMUNITY

PubMed Central

Helm, Susana; Lee, Wayde; Hanakahi, Vanda; Gleason, Krissy; McCarthy, Kayne

2015-01-01

Introduction Substance use represents a significant and persistent health disparity among Native Hawaiian youth and communities. A community-university participatory action research project was conducted to develop a Native Hawaiian model of drug prevention. Methods Ten youth participated in eight Photovoice focus groups. Focus group transcripts and the youths’ SHOWED (see, happening, our, why, empower, do) worksheets were analyzed. Results Emergent analyses are described regarding focus group theme identification and the meaning of each theme. Youth-selected exemplary photographs and researcher-selected exemplary quotations are provided. Implications Native Hawaiian drug prevention will be place-based in culturally significant community locations, experiential, and guided by multigenerational teaching and learning. PMID:25768388

Road to better health and integration: a Delphi study on health service models for Hong Kong migrants.

PubMed

Wong, William C W; Ho, Petula S Y; Liang, Jun; Holroyd, Eleanor A; Lam, Cindy L K; Pau, Agnes M Y

2014-12-19

In Hong Kong, migrants arriving from Mainland China often have multiple roles and responsibilities while adapting to new lives in their host destination. This paper explored the factors that contribute to the inequity in health services utilisation experienced by these migrants; and, identified the elements that could constitute an effective health delivery model to address the service gap. Site visits and a focus group discussion (n = 13) were held with both public and private health providers before a number of innovative health delivery models were formulated. They were then circulated among the panel in two further rounds of Delphi survey (n = 11) from March-April 2012 to systematically collect opinions and select the most endorsed health service models to serve this target population. Focus group members perceived that most migrants were unaware of, or even ignored, their own physical and mental health needs, and had low utilisation of healthcare services, because of their pre-occupation with daily chores and hardship as well as differing health values, practices and expectations. They further identified that the structural issues such as the healthcare setting or the operation of current service provisions had failed to meet migrants' health needs. Consequently, four new service models that incorporated professional advice and empowerment, which were identified as the two most important elements, were put forward. Thus, the model of having a nurse with social work training, supported by volunteer groups, was selected as the best option to familiarise and empower patients within the labyrinth of local healthcare services. Implementation of a social empowerment model by way of targeted support and specific health information is recommended. Further evaluation of this model is needed to understand its effectiveness for improving health literacy and health status in this disadvantaged group in the long term.

Testing the Cultural Differences of School Characteristics with Measurement Invariance

ERIC Educational Resources Information Center

Demir, Ergül

2016-01-01

In this study, it was aimed to model the school characteristics in multivariate structure, and according to this model, aimed to test the invariance of this model across five randomly selected countries and economies from PISA 2012 sample. It is thought that significant differences across group in the context of school characteristics have the…

Risk Classification with an Adaptive Naive Bayes Kernel Machine Model.

PubMed

Minnier, Jessica; Yuan, Ming; Liu, Jun S; Cai, Tianxi

2015-04-22

Genetic studies of complex traits have uncovered only a small number of risk markers explaining a small fraction of heritability and adding little improvement to disease risk prediction. Standard single marker methods may lack power in selecting informative markers or estimating effects. Most existing methods also typically do not account for non-linearity. Identifying markers with weak signals and estimating their joint effects among many non-informative markers remains challenging. One potential approach is to group markers based on biological knowledge such as gene structure. If markers in a group tend to have similar effects, proper usage of the group structure could improve power and efficiency in estimation. We propose a two-stage method relating markers to disease risk by taking advantage of known gene-set structures. Imposing a naive bayes kernel machine (KM) model, we estimate gene-set specific risk models that relate each gene-set to the outcome in stage I. The KM framework efficiently models potentially non-linear effects of predictors without requiring explicit specification of functional forms. In stage II, we aggregate information across gene-sets via a regularization procedure. Estimation and computational efficiency is further improved with kernel principle component analysis. Asymptotic results for model estimation and gene set selection are derived and numerical studies suggest that the proposed procedure could outperform existing procedures for constructing genetic risk models.

A framework for establishing predictive relationships between specific bacterial 16S rRNA sequence abundances and biotransformation rates.

PubMed

Helbling, Damian E; Johnson, David R; Lee, Tae Kwon; Scheidegger, Andreas; Fenner, Kathrin

2015-03-01

The rates at which wastewater treatment plant (WWTP) microbial communities biotransform specific substrates can differ by orders of magnitude among WWTP communities. Differences in taxonomic compositions among WWTP communities may predict differences in the rates of some types of biotransformations. In this work, we present a novel framework for establishing predictive relationships between specific bacterial 16S rRNA sequence abundances and biotransformation rates. We selected ten WWTPs with substantial variation in their environmental and operational metrics and measured the in situ ammonia biotransformation rate constants in nine of them. We isolated total RNA from samples from each WWTP and analyzed 16S rRNA sequence reads. We then developed multivariate models between the measured abundances of specific bacterial 16S rRNA sequence reads and the ammonia biotransformation rate constants. We constructed model scenarios that systematically explored the effects of model regularization, model linearity and non-linearity, and aggregation of 16S rRNA sequences into operational taxonomic units (OTUs) as a function of sequence dissimilarity threshold (SDT). A large percentage (greater than 80%) of model scenarios resulted in well-performing and significant models at intermediate SDTs of 0.13-0.14 and 0.26. The 16S rRNA sequences consistently selected into the well-performing and significant models at those SDTs were classified as Nitrosomonas and Nitrospira groups. We then extend the framework by applying it to the biotransformation rate constants of ten micropollutants measured in batch reactors seeded with the ten WWTP communities. We identified phylogenetic groups that were robustly selected into all well-performing and significant models constructed with biotransformation rates of isoproturon, propachlor, ranitidine, and venlafaxine. These phylogenetic groups can be used as predictive biomarkers of WWTP microbial community activity towards these specific micropollutants. This work is an important step towards developing tools to predict biotransformation rates in WWTPs based on taxonomic composition. Copyright © 2014 Elsevier Ltd. All rights reserved.

The Process Model of Group-Based Emotion: Integrating Intergroup Emotion and Emotion Regulation Perspectives.

PubMed

Goldenberg, Amit; Halperin, Eran; van Zomeren, Martijn; Gross, James J

2016-05-01

Scholars interested in emotion regulation have documented the different goals and strategies individuals have for regulating their emotions. However, little attention has been paid to the regulation of group-based emotions, which are based on individuals' self-categorization as a group member and occur in response to situations perceived as relevant for that group. We propose a model for examining group-based emotion regulation that integrates intergroup emotions theory and the process model of emotion regulation. This synergy expands intergroup emotion theory by facilitating further investigation of different goals (i.e., hedonic or instrumental) and strategies (e.g., situation selection and modification strategies) used to regulate group-based emotions. It also expands emotion regulation research by emphasizing the role of self-categorization (e.g., as an individual or a group member) in the emotional process. Finally, we discuss the promise of this theoretical synergy and suggest several directions for future research on group-based emotion regulation. © 2015 by the Society for Personality and Social Psychology, Inc.

Impact of the corrin framework of vitamin B12 on the electrochemical carbon-skeleton rearrangement in comparison to an imine/oxime planar ligand; tuning selectivity in 1,2-migration of a functional group by controlling electrolysis potential.

PubMed

Tahara, Keishiro; Pan, Ling; Yamaguchi, Ryoko; Shimakoshi, Hisashi; Abe, Masaaki; Hisaeda, Yoshio

2017-10-01

Among the coenzyme B 12 -dependent enzymes, methylmalonyl-CoA mutase (MMCM) catalyzes the carbon-skeleton rearrangement reaction between R-methylmalonyl-CoA and succinyl-CoA. Diethyl 2-bromomethyl-2-phenylmalonate, an alkyl bromide substrate having two different migrating groups (phenyl and carboxylic ester groups) on the β-carbon, was applied to the electrolysis mediated by a hydrophobic vitamin B 12 model complex, heptamethyl cobyrinate perchlorate in this study. The electrolysis of the substrate at -1.0V vs. Ag-AgCl by light irradiation afforded the simple reduced product (diethyl 2-methyl-2-phenylmalonate) and the phenyl migrated product (diethyl 2-benzyl-2-phenylmalonate), as well as the electrolysis of the substrate at -1.5V vs. Ag-AgCl in the dark. The electrolysis of the substrate at -2.0V vs. Ag-AgCl afforded the carboxylic ester migrated product (diethyl phenylsuccinate) as the major product. The selectivity for the migrating group was successfully tuned by controlling the electrolysis potential. We clarified that the cathodic chemistry of the Co(III) alkylated heptamethyl cobyrinate is critical for the selectivity of the migrating group through mechanistic investigations and comparisons to the simple vitamin B 12 model complex, an imine/oxime-type cobalt complex. Copyright © 2017 Elsevier Inc. All rights reserved.

Continuous-time discrete-space models for animal movement

USGS Publications Warehouse

Hanks, Ephraim M.; Hooten, Mevin B.; Alldredge, Mat W.

2015-01-01

The processes influencing animal movement and resource selection are complex and varied. Past efforts to model behavioral changes over time used Bayesian statistical models with variable parameter space, such as reversible-jump Markov chain Monte Carlo approaches, which are computationally demanding and inaccessible to many practitioners. We present a continuous-time discrete-space (CTDS) model of animal movement that can be fit using standard generalized linear modeling (GLM) methods. This CTDS approach allows for the joint modeling of location-based as well as directional drivers of movement. Changing behavior over time is modeled using a varying-coefficient framework which maintains the computational simplicity of a GLM approach, and variable selection is accomplished using a group lasso penalty. We apply our approach to a study of two mountain lions (Puma concolor) in Colorado, USA.

Item selection via Bayesian IRT models.

PubMed

Arima, Serena

2015-02-10

With reference to a questionnaire that aimed to assess the quality of life for dysarthric speakers, we investigate the usefulness of a model-based procedure for reducing the number of items. We propose a mixed cumulative logit model, which is known in the psychometrics literature as the graded response model: responses to different items are modelled as a function of individual latent traits and as a function of item characteristics, such as their difficulty and their discrimination power. We jointly model the discrimination and the difficulty parameters by using a k-component mixture of normal distributions. Mixture components correspond to disjoint groups of items. Items that belong to the same groups can be considered equivalent in terms of both difficulty and discrimination power. According to decision criteria, we select a subset of items such that the reduced questionnaire is able to provide the same information that the complete questionnaire provides. The model is estimated by using a Bayesian approach, and the choice of the number of mixture components is justified according to information criteria. We illustrate the proposed approach on the basis of data that are collected for 104 dysarthric patients by local health authorities in Lecce and in Milan. Copyright © 2014 John Wiley & Sons, Ltd.

Different binding mechanisms of neutral and anionic poly-/perfluorinated chemicals to human transthyretin revealed by In silico models.

PubMed

Yang, Xianhai; Lyakurwa, Felichesmi; Xie, Hongbin; Chen, Jingwen; Li, Xuehua; Qiao, Xianliang; Cai, Xiyun

2017-09-01

Chemical forms-dependent binding interactions between phenolic compounds and human transthyretin (hTTR) have been elaborated previously. However, it is not known whether the binding interactions between ionizable halogenated alphatic compounds and hTTR also have the same manner. In this study, poly-/perfluorinated chemicals (PFCs) were selected as model compounds and molecular dynamic simulation was performed to investigate the binding mechanisms between PFCs and hTTR. Results show the binding interactions between the halogenated aliphatic compounds and hTTR are related to the chemical forms. The ionized groups of PFCs can form electrostatic interactions with the -NH + 3 groups of Lys 15 residues in hTTR and form hydrogen bonds with the residues of hTTR. By analyzing the molecular orbital energies of PFCs, we also found that the anionic groups (nucleophile) in PFCs could form electron donor - acceptor interactions with the -NH + 3 groups (electrophile) in Lys 15. The aforementioned orientational interactions make the ionized groups of the PFCs point toward the entry port of the binding site. The roles of fluorine atoms in the binding interactions were also explored. The fluorine atoms can influence the binding interactions via inductive effects. Appropriate molecular descriptors were selected to characterize these interactions, and two quantitative structure-activity relationship models were developed. Copyright © 2017 Elsevier Ltd. All rights reserved.

The Evolution of Different Forms of Sociality: Behavioral Mechanisms and Eco-Evolutionary Feedback

PubMed Central

van der Post, Daniel J.; Verbrugge, Rineke; Hemelrijk, Charlotte K.

2015-01-01

Different forms of sociality have evolved via unique evolutionary trajectories. However, it remains unknown to what extent trajectories of social evolution depend on the specific characteristics of different species. Our approach to studying such trajectories is to use evolutionary case-studies, so that we can investigate how grouping co-evolves with a multitude of individual characteristics. Here we focus on anti-predator vigilance and foraging. We use an individual-based model, where behavioral mechanisms are specified, and costs and benefits are not predefined. We show that evolutionary changes in grouping alter selection pressures on vigilance, and vice versa. This eco-evolutionary feedback generates an evolutionary progression from “leader-follower” societies to “fission-fusion” societies, where cooperative vigilance in groups is maintained via a balance between within- and between-group selection. Group-level selection is generated from an assortment that arises spontaneously when vigilant and non-vigilant foragers have different grouping tendencies. The evolutionary maintenance of small groups, and cooperative vigilance in those groups, is therefore achieved simultaneously. The evolutionary phases, and the transitions between them, depend strongly on behavioral mechanisms. Thus, integrating behavioral mechanisms and eco-evolutionary feedback is critical for understanding what kinds of intermediate stages are involved during the evolution of particular forms of sociality. PMID:25629313

Measurement invariance versus selection invariance: is fair selection possible?

PubMed

Borsboom, Denny; Romeijn, Jan-Willem; Wicherts, Jelte M

2008-06-01

This article shows that measurement invariance (defined in terms of an invariant measurement model in different groups) is generally inconsistent with selection invariance (defined in terms of equal sensitivity and specificity across groups). In particular, when a unidimensional measurement instrument is used and group differences are present in the location but not in the variance of the latent distribution, sensitivity and positive predictive value will be higher in the group at the higher end of the latent dimension, whereas specificity and negative predictive value will be higher in the group at the lower end of the latent dimension. When latent variances are unequal, the differences in these quantities depend on the size of group differences in variances relative to the size of group differences in means. The effect originates as a special case of Simpson's paradox, which arises because the observed score distribution is collapsed into an accept-reject dichotomy. Simulations show the effect can be substantial in realistic situations. It is suggested that the effect may be partly responsible for overprediction in minority groups as typically found in empirical studies on differential academic performance. A methodological solution to the problem is suggested, and social policy implications are discussed. (PsycINFO Database Record (c) 2008 APA, all rights reserved).

The evolution of different forms of sociality: behavioral mechanisms and eco-evolutionary feedback.

PubMed

van der Post, Daniel J; Verbrugge, Rineke; Hemelrijk, Charlotte K

2015-01-01

Different forms of sociality have evolved via unique evolutionary trajectories. However, it remains unknown to what extent trajectories of social evolution depend on the specific characteristics of different species. Our approach to studying such trajectories is to use evolutionary case-studies, so that we can investigate how grouping co-evolves with a multitude of individual characteristics. Here we focus on anti-predator vigilance and foraging. We use an individual-based model, where behavioral mechanisms are specified, and costs and benefits are not predefined. We show that evolutionary changes in grouping alter selection pressures on vigilance, and vice versa. This eco-evolutionary feedback generates an evolutionary progression from "leader-follower" societies to "fission-fusion" societies, where cooperative vigilance in groups is maintained via a balance between within- and between-group selection. Group-level selection is generated from an assortment that arises spontaneously when vigilant and non-vigilant foragers have different grouping tendencies. The evolutionary maintenance of small groups, and cooperative vigilance in those groups, is therefore achieved simultaneously. The evolutionary phases, and the transitions between them, depend strongly on behavioral mechanisms. Thus, integrating behavioral mechanisms and eco-evolutionary feedback is critical for understanding what kinds of intermediate stages are involved during the evolution of particular forms of sociality.

Genome-wide association data classification and SNPs selection using two-stage quality-based Random Forests.

PubMed

Nguyen, Thanh-Tung; Huang, Joshua; Wu, Qingyao; Nguyen, Thuy; Li, Mark

2015-01-01

Single-nucleotide polymorphisms (SNPs) selection and identification are the most important tasks in Genome-wide association data analysis. The problem is difficult because genome-wide association data is very high dimensional and a large portion of SNPs in the data is irrelevant to the disease. Advanced machine learning methods have been successfully used in Genome-wide association studies (GWAS) for identification of genetic variants that have relatively big effects in some common, complex diseases. Among them, the most successful one is Random Forests (RF). Despite of performing well in terms of prediction accuracy in some data sets with moderate size, RF still suffers from working in GWAS for selecting informative SNPs and building accurate prediction models. In this paper, we propose to use a new two-stage quality-based sampling method in random forests, named ts-RF, for SNP subspace selection for GWAS. The method first applies p-value assessment to find a cut-off point that separates informative and irrelevant SNPs in two groups. The informative SNPs group is further divided into two sub-groups: highly informative and weak informative SNPs. When sampling the SNP subspace for building trees for the forest, only those SNPs from the two sub-groups are taken into account. The feature subspaces always contain highly informative SNPs when used to split a node at a tree. This approach enables one to generate more accurate trees with a lower prediction error, meanwhile possibly avoiding overfitting. It allows one to detect interactions of multiple SNPs with the diseases, and to reduce the dimensionality and the amount of Genome-wide association data needed for learning the RF model. Extensive experiments on two genome-wide SNP data sets (Parkinson case-control data comprised of 408,803 SNPs and Alzheimer case-control data comprised of 380,157 SNPs) and 10 gene data sets have demonstrated that the proposed model significantly reduced prediction errors and outperformed most existing the-state-of-the-art random forests. The top 25 SNPs in Parkinson data set were identified by the proposed model including four interesting genes associated with neurological disorders. The presented approach has shown to be effective in selecting informative sub-groups of SNPs potentially associated with diseases that traditional statistical approaches might fail. The new RF works well for the data where the number of case-control objects is much smaller than the number of SNPs, which is a typical problem in gene data and GWAS. Experiment results demonstrated the effectiveness of the proposed RF model that outperformed the state-of-the-art RFs, including Breiman's RF, GRRF and wsRF methods.

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

ERIC Educational Resources Information Center

Xiang, Lin

2011-01-01

This is a collective case study seeking to develop detailed descriptions of how programming an agent-based simulation influences a group of 8th grade students' model-based inquiry (MBI) by examining students' agent-based programmable modeling (ABPM) processes and the learning outcomes. The context of the present study was a biology unit on…

An Expression of Periodic Phenomena of Fashion on Sexual Selection Model with Conformity Genes and Memes

NASA Astrophysics Data System (ADS)

Mutoh, Atsuko; Tokuhara, Shinya; Kanoh, Masayoshi; Oboshi, Tamon; Kato, Shohei; Itoh, Hidenori

It is generally thought that living things have trends in their preferences. The mechanism of occurrence of another trends in successive periods is concerned in their conformity. According to social impact theory, the minority is always exists in the group. There is a possibility that the minority make the transition to the majority by conforming agents. Because of agent's promotion of their conform actions, the majority can make the transition. We proposed an evolutionary model with both genes and memes, and elucidated the interaction between genes and memes on sexual selection. In this paper, we propose an agent model for sexual selection imported the concept of conformity. Using this model we try an environment where male agents and female agents are existed, we find that periodic phenomena of fashion are expressed. And we report the influence of conformity and differentiation on the transition of their preferences.

Relationships Between the External and Internal Training Load in Professional Soccer: What Can We Learn From Machine Learning?

PubMed

Jaspers, Arne; De Beéck, Tim Op; Brink, Michel S; Frencken, Wouter G P; Staes, Filip; Davis, Jesse J; Helsen, Werner F

2018-05-01

Machine learning may contribute to understanding the relationship between the external load and internal load in professional soccer. Therefore, the relationship between external load indicators (ELIs) and the rating of perceived exertion (RPE) was examined using machine learning techniques on a group and individual level. Training data were collected from 38 professional soccer players over 2 seasons. The external load was measured using global positioning system technology and accelerometry. The internal load was obtained using the RPE. Predictive models were constructed using 2 machine learning techniques, artificial neural networks and least absolute shrinkage and selection operator (LASSO) models, and 1 naive baseline method. The predictions were based on a large set of ELIs. Using each technique, 1 group model involving all players and 1 individual model for each player were constructed. These models' performance on predicting the reported RPE values for future training sessions was compared with the naive baseline's performance. Both the artificial neural network and LASSO models outperformed the baseline. In addition, the LASSO model made more accurate predictions for the RPE than did the artificial neural network model. Furthermore, decelerations were identified as important ELIs. Regardless of the applied machine learning technique, the group models resulted in equivalent or better predictions for the reported RPE values than the individual models. Machine learning techniques may have added value in predicting RPE for future sessions to optimize training design and evaluation. These techniques may also be used in conjunction with expert knowledge to select key ELIs for load monitoring.

Parent oriented teacher selection causes language diversity.

PubMed

Cimentepe, Ibrahim; Bingol, Haluk O

2017-09-21

An evolutionary model for emergence of diversity in language is developed. We investigated the effects of two real life observations, namely, people prefer people that they communicate with well, and people interact with people that are physically close to each other. Clearly these groups are relatively small compared to the entire population. We restrict selection of the teachers from such small groups, called imitation sets, around parents. Then the child learns language from a teacher selected within the imitation set of her parent. As a result, there are subcommunities with their own languages developed. Within subcommunity comprehension is found to be high. The number of languages is related to the relative size of imitation set by a power law. Copyright © 2017 Elsevier Ltd. All rights reserved.

Mixture Rasch model for guessing group identification

NASA Astrophysics Data System (ADS)

Siow, Hoo Leong; Mahdi, Rasidah; Siew, Eng Ling

2013-04-01

Several alternative dichotomous Item Response Theory (IRT) models have been introduced to account for guessing effect in multiple-choice assessment. The guessing effect in these models has been considered to be itemrelated. In the most classic case, pseudo-guessing in the three-parameter logistic IRT model is modeled to be the same for all the subjects but may vary across items. This is not realistic because subjects can guess worse or better than the pseudo-guessing. Derivation from the three-parameter logistic IRT model improves the situation by incorporating ability in guessing. However, it does not model non-monotone function. This paper proposes to study guessing from a subject-related aspect which is guessing test-taking behavior. Mixture Rasch model is employed to detect latent groups. A hybrid of mixture Rasch and 3-parameter logistic IRT model is proposed to model the behavior based guessing from the subjects' ways of responding the items. The subjects are assumed to simply choose a response at random. An information criterion is proposed to identify the behavior based guessing group. Results show that the proposed model selection criterion provides a promising method to identify the guessing group modeled by the hybrid model.

Visual search and coordination changes in response to video and point-light demonstrations without KR.

PubMed

Horn, R R; Williams, A M; Scott, M A; Hodges, N J

2005-07-01

The authors examined the observational learning of 24 participants whom they constrained to use the model by removing intrinsic visual knowledge of results (KR). Matched participants assigned to video (VID), point-light (PL), and no-model (CON) groups performed a soccer-chipping task in which vision was occluded at ball contact. Pre- and posttests were interspersed with alternating periods of demonstration and acquisition. The authors assessed delayed retention 2-3 days later. In support of the visual perception perspective, the participants who observed the models showed immediate and enduring changes to more closely imitate the model's relative motion. While observing the demonstration, the PL group participants were more selective in their visual search than were the VID group participants but did not perform more accurately or learn more.

Talent identification and selection in elite youth football: An Australian context.

PubMed

O'Connor, Donna; Larkin, Paul; Mark Williams, A

2016-10-01

We identified the perceptual-cognitive skills and player history variables that differentiate players selected or not selected into an elite youth football (i.e. soccer) programme in Australia. A sample of elite youth male football players (n = 127) completed an adapted participation history questionnaire and video-based assessments of perceptual-cognitive skills. Following data collection, 22 of these players were offered a full-time scholarship for enrolment at an elite player residential programme. Participants selected for the scholarship programme recorded superior performance on the combined perceptual-cognitive skills tests compared to the non-selected group. There were no significant between group differences on the player history variables. Stepwise discriminant function analysis identified four predictor variables that resulted in the best categorization of selected and non-selected players (i.e. recent match-play performance, region, number of other sports participated, combined perceptual-cognitive performance). The effectiveness of the discriminant function is reflected by 93.7% of players being correctly classified, with the four variables accounting for 57.6% of the variance. Our discriminating model for selection may provide a greater understanding of the factors that influence elite youth talent selection and identification.

Estimated costs of postoperative wound infections. A case-control study of marginal hospital and social security costs.

PubMed Central

Poulsen, K. B.; Bremmelgaard, A.; Sørensen, A. I.; Raahave, D.; Petersen, J. V.

1994-01-01

A cohort of 4515 surgical patients in ten selected intervention groups was followed. Three hundred and seventeen developed postoperative wound infections, and 291 of these cases were matched 1:1 to controls by operation, sex and age. In comparison to the controls the cases stayed longer in hospital after the intervention and had more contact after discharge with the social security system. Using data from a national sentinel reference database of the incidence of postoperative wound infections, and using national activity data, we established an empirical cost model based on the estimated marginal costs of hospital resources and social sick pay. It showed that the hospital resources spent on the ten groups, which represent half of the postoperative wound infections in Denmark, amounted to approximately 0.5% of the annual national hospital budget. This stratified model creates a better basis for selecting groups of operations which need priority in terms of preventive measures. PMID:7925666

Best Design for Multidimensional Computerized Adaptive Testing With the Bifactor Model

PubMed Central

Seo, Dong Gi; Weiss, David J.

2015-01-01

Most computerized adaptive tests (CATs) have been studied using the framework of unidimensional item response theory. However, many psychological variables are multidimensional and might benefit from using a multidimensional approach to CATs. This study investigated the accuracy, fidelity, and efficiency of a fully multidimensional CAT algorithm (MCAT) with a bifactor model using simulated data. Four item selection methods in MCAT were examined for three bifactor pattern designs using two multidimensional item response theory models. To compare MCAT item selection and estimation methods, a fixed test length was used. The Ds-optimality item selection improved θ estimates with respect to a general factor, and either D- or A-optimality improved estimates of the group factors in three bifactor pattern designs under two multidimensional item response theory models. The MCAT model without a guessing parameter functioned better than the MCAT model with a guessing parameter. The MAP (maximum a posteriori) estimation method provided more accurate θ estimates than the EAP (expected a posteriori) method under most conditions, and MAP showed lower observed standard errors than EAP under most conditions, except for a general factor condition using Ds-optimality item selection. PMID:29795848

The Effect of College Selection Factors on Persistence: An Examination of Black and Latino Males in the Community College

ERIC Educational Resources Information Center

Wood, J. Luke; Harris, Frank, III

2015-01-01

The purpose of this study was to understand the relationship (if any) between college selection factors and persistence for Black and Latino males in the community college. Using data derived from the Educational Longitudinal Study, backwards stepwise logistic regression models were developed for both groups. Findings are contextualized in light…

Ethnic and Gender Differences in Science Graduation at Selective Colleges with Implications for Admission Policy and College Choice

ERIC Educational Resources Information Center

Smyth, Frederick L.; McArdle, John J.

2004-01-01

Using Bowen and Bok's data from 23 selective colleges, we fit multilevel logit models to test two hypotheses with implications for affirmative action and group differences in attainment of science, math, or engineering (SME) degrees. Hypothesis 1, that differences in precollege academic preparation will explain later SME graduation disparities,…

Documentary Photography: Cognitive Dimensionality of Selected Photographs and Community Perceptions in a Coorientation Model.

ERIC Educational Resources Information Center

Brown, James W.; Foushee, Richard E.

A term project for a journalism course in documentary photography (the proposal for which is cited in ED 177 560) centered on photographically documenting a rural community and measuring its symbolic sociodramas. The focus of the project was to determine how various community groups interpreted a given set of photographs selected to represent a…

Molecular-Orbital Models for the Catayltic Activity and Selectivity of Coordinatively Unsaturated Platinum Surfaces and Complexes.

DTIC Science & Technology

1980-12-31

surfaces. Reactions involving the Pt(O)- triphenylphosphine complexes Pt(PPh 3)n, where n = 2, 3, 4, have been shown to have precise analogues on Pt...12], the triphenylphosphine (PPh 3 ) group is modeled by the simpler but chemically similar phosphine (PH3) group. The appropriate Pt-P bond distances...typically refractory oxides ) are of sufficient magnitude as to suggest significant chemical and electronic modifications of the metal at the metal-support

Large-scale model quality assessment for improving protein tertiary structure prediction.

PubMed

Cao, Renzhi; Bhattacharya, Debswapna; Adhikari, Badri; Li, Jilong; Cheng, Jianlin

2015-06-15

Sampling structural models and ranking them are the two major challenges of protein structure prediction. Traditional protein structure prediction methods generally use one or a few quality assessment (QA) methods to select the best-predicted models, which cannot consistently select relatively better models and rank a large number of models well. Here, we develop a novel large-scale model QA method in conjunction with model clustering to rank and select protein structural models. It unprecedentedly applied 14 model QA methods to generate consensus model rankings, followed by model refinement based on model combination (i.e. averaging). Our experiment demonstrates that the large-scale model QA approach is more consistent and robust in selecting models of better quality than any individual QA method. Our method was blindly tested during the 11th Critical Assessment of Techniques for Protein Structure Prediction (CASP11) as MULTICOM group. It was officially ranked third out of all 143 human and server predictors according to the total scores of the first models predicted for 78 CASP11 protein domains and second according to the total scores of the best of the five models predicted for these domains. MULTICOM's outstanding performance in the extremely competitive 2014 CASP11 experiment proves that our large-scale QA approach together with model clustering is a promising solution to one of the two major problems in protein structure modeling. The web server is available at: http://sysbio.rnet.missouri.edu/multicom_cluster/human/. © The Author 2015. Published by Oxford University Press.

Expanding the Capabilities of the JPL Electronic Nose for an International Space Station Technology Demonstration

NASA Technical Reports Server (NTRS)

Ryan, Margaret A.; Shevade, A. V.; Taylor, C. J.; Homer, M. L.; Jewell, A. D.; Kisor, A.; Manatt, K. S .; Yen, S. P. S.; Blanco, M.; Goddard, W. A., III

2006-01-01

An array-based sensing system based on polymer/carbon composite conductometric sensors is under development at JPL for use as an environmental monitor in the International Space Station. Sulfur dioxide has been added to the analyte set for this phase of development. Using molecular modeling techniques, the interaction energy between SO2 and polymer functional groups has been calculated, and polymers selected as potential SO2 sensors. Experiment has validated the model and two selected polymers have been shown to be promising materials for SO2 detection.

Selecting risk factors: a comparison of discriminant analysis, logistic regression and Cox's regression model using data from the Tromsø Heart Study.

PubMed

Brenn, T; Arnesen, E

1985-01-01

For comparative evaluation, discriminant analysis, logistic regression and Cox's model were used to select risk factors for total and coronary deaths among 6595 men aged 20-49 followed for 9 years. Groups with mortality between 5 and 93 per 1000 were considered. Discriminant analysis selected variable sets only marginally different from the logistic and Cox methods which always selected the same sets. A time-saving option, offered for both the logistic and Cox selection, showed no advantage compared with discriminant analysis. Analysing more than 3800 subjects, the logistic and Cox methods consumed, respectively, 80 and 10 times more computer time than discriminant analysis. When including the same set of variables in non-stepwise analyses, all methods estimated coefficients that in most cases were almost identical. In conclusion, discriminant analysis is advocated for preliminary or stepwise analysis, otherwise Cox's method should be used.

Which population groups should be targeted for cardiovascular prevention? A modelling study based on the Norwegian Hordaland Health Study (HUSK).

PubMed

Brekke, Mette; Rekdal, Magne; Straand, Jørund

2007-06-01

To assess level of cardiovascular risk factors in a non-selected, middle-aged population. To estimate the proportion target for risk intervention according to present guidelines and according to different cut-off levels for two risk algorithms. Population survey, modelling study. The Norwegian Hordaland Health Study (HUSK) 1997-99. A total of 22 289 persons born in 1950-57. Own and relatives' cardiovascular morbidity, antihypertensive and lipid-lowering treatment, smoking, blood pressure, cholesterol. Framingham and Systematic Coronary Risk Evaluation (SCORE) algorithms. The European guidelines on CVD prevention in clinical practice were applied to estimate size of risk groups. Some 9.7% of men and 7.6% of women had CVD, diabetes mellitus, a high level of one specific risk factor, or received lipid-lowering or antihypertensive treatment. Applying a SCORE (60 years) cut-off level at 5% to the rest of the population selected 52.4% of men and 0.8% of women into a primary prevention group, while a cut-off level at 8% included 22.0% and 0.06% respectively. A cut-off level for the Framingham score (60 years) of 20% selected 43.6% of men and 4.7% of women, while a cut-off level of 25% selected 25.6% of men and 1.8% of women. The findings illustrate how choices regarding risk estimation highly affect the size of the target population. Modelling studies are important when preparing guidelines, to address implications for resource allocation and risk of medicalization. The population share to be targeted for primary prevention ought to be estimated, including the impact of various cut-off points for risk algorithms on the size of the risk population.

A mechanistic model for the evolution of multicellularity

NASA Astrophysics Data System (ADS)

Amado, André; Batista, Carlos; Campos, Paulo R. A.

2018-02-01

Through a mechanistic approach we investigate the formation of aggregates of variable sizes, accounting mechanisms of aggregation, dissociation, death and reproduction. In our model, cells can produce two metabolites, but the simultaneous production of both metabolites is costly in terms of fitness. Thus, the formation of larger groups can favor the aggregates to evolve to a configuration where division of labor arises. It is assumed that the states of the cells in a group are those that maximize organismal fitness. In the model it is considered that the groups can grow linearly, forming a chain, or compactly keeping a roughly spherical shape. Starting from a population consisting of single-celled organisms, we observe the formation of groups with variable sizes and usually much larger than two-cell aggregates. Natural selection can favor the formation of large groups, which allows the system to achieve new and larger fitness maxima.

Rational group decision making: A random field Ising model at T = 0

NASA Astrophysics Data System (ADS)

Galam, Serge

1997-02-01

A modified version of a finite random field Ising ferromagnetic model in an external magnetic field at zero temperature is presented to describe group decision making. Fields may have a non-zero average. A postulate of minimum inter-individual conflicts is assumed. Interactions then produce a group polarization along one very choice which is however randomly selected. A small external social pressure is shown to have a drastic effect on the polarization. Individual bias related to personal backgrounds, cultural values and past experiences are introduced via quenched local competing fields. They are shown to be instrumental in generating a larger spectrum of collective new choices beyond initial ones. In particular, compromise is found to results from the existence of individual competing bias. Conflict is shown to weaken group polarization. The model yields new psychosociological insights about consensus and compromise in groups.

Pathologic changes of wound tissue in rats with stage III pressure ulcers treated by transplantation of human amniotic epithelial cells.

PubMed

Zheng, Xilan; Jiang, Zhixia; Zhou, Aiting; Yu, Limei; Quan, Mingtao; Cheng, Huagang

2015-01-01

This study aims to determine the impact of orthotopic transplantation of human amniotic epithelial cells (hAECs) on the pathologic changes of wound tissues in a self-prepared rat stage III pressure ulcer model. Ninety-six SD rats were randomly divided into the model group (group M), hAEC transplantation group (group H), traditional treatment group (group T), and the control group (group C), with 24 rats in each group. The wound healing time was observed in 6 rats from each group, and 6 rats of each group were selected for post-modeling on day(s) (D) 1, 3, and 7 for HE staining to compare the pathological changes. The healing time of group H was significantly shorter than the other three groups. Moreover, pathological observations revealed that group H exhibited significant proliferation of fibrous tissues and vessels in the dermal layer, and the appearance time and degree of skin appendages were significantly greater than that observed in the other three groups. Pathological observations showed that hAEC transplantation could significantly speed up the healing of stage III pressure ulcer.

Galaxies in X-ray Selected Clusters and Groups in Dark Energy Survey Data: Stellar Mass Growth of Bright Central Galaxies Since z~1.2

DOE PAGES

Zhang, Y.; Miller, C.; McKay, T.; ...

2016-01-10

Using the science verification data of the Dark Energy Survey for a new sample of 106 X-ray selected clusters and groups, we study the stellar mass growth of bright central galaxies (BCGs) since redshift z ~ 1.2. Compared with the expectation in a semi-analytical model applied to the Millennium Simulation, the observed BCGs become under-massive/under-luminous with decreasing redshift. We incorporate the uncertainties associated with cluster mass, redshift, and BCG stellar mass measurements into analysis of a redshift-dependent BCG-cluster mass relation.

Selective attention deficits in obsessive-compulsive disorder: the role of metacognitive processes.

PubMed

Koch, Julia; Exner, Cornelia

2015-02-28

While initial studies supported the hypothesis that cognitive characteristics that capture cognitive resources act as underlying mechanisms in memory deficits in obsessive-compulsive disorder (OCD), the influence of those characteristics on selective attention has not been studied, yet. In this study, we examined the influence of cognitive self-consciousness (CSC), rumination and worrying on performance in selective attention in OCD and compared the results to a depressive and a healthy control group. We found that 36 OCD and 36 depressive participants were impaired in selective attention in comparison to 36 healthy controls. In all groups, hierarchical regression analyses demonstrated that age, intelligence and years in school significantly predicted performance in selective attention. But only in OCD, the predictive power of the regression model was improved when CSC, rumination and worrying were implemented as predictor variables. In contrast, in none of the three groups the predictive power improved when indicators of severity of obsessive-compulsive (OC) and depressive symptoms and trait anxiety were introduced as predictor variables. Thus, our results support the assumption that mental characteristics that bind cognitive resources play an important role in the understanding of selective attention deficits in OCD and that this mechanism is especially relevant for OCD. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Genetic evaluation and selection response for growth in meat-type quail through random regression models using B-spline functions and Legendre polynomials.

PubMed

Mota, L F M; Martins, P G M A; Littiere, T O; Abreu, L R A; Silva, M A; Bonafé, C M

2018-04-01

The objective was to estimate (co)variance functions using random regression models (RRM) with Legendre polynomials, B-spline function and multi-trait models aimed at evaluating genetic parameters of growth traits in meat-type quail. A database containing the complete pedigree information of 7000 meat-type quail was utilized. The models included the fixed effects of contemporary group and generation. Direct additive genetic and permanent environmental effects, considered as random, were modeled using B-spline functions considering quadratic and cubic polynomials for each individual segment, and Legendre polynomials for age. Residual variances were grouped in four age classes. Direct additive genetic and permanent environmental effects were modeled using 2 to 4 segments and were modeled by Legendre polynomial with orders of fit ranging from 2 to 4. The model with quadratic B-spline adjustment, using four segments for direct additive genetic and permanent environmental effects, was the most appropriate and parsimonious to describe the covariance structure of the data. The RRM using Legendre polynomials presented an underestimation of the residual variance. Lesser heritability estimates were observed for multi-trait models in comparison with RRM for the evaluated ages. In general, the genetic correlations between measures of BW from hatching to 35 days of age decreased as the range between the evaluated ages increased. Genetic trend for BW was positive and significant along the selection generations. The genetic response to selection for BW in the evaluated ages presented greater values for RRM compared with multi-trait models. In summary, RRM using B-spline functions with four residual variance classes and segments were the best fit for genetic evaluation of growth traits in meat-type quail. In conclusion, RRM should be considered in genetic evaluation of breeding programs.

Progress on geoenvironmental models for selected mineral deposit types, edited by R. R. Seal, II and N. K. Foley

USGS Publications Warehouse

Seal, Robert R.; Foley, Nora K.

2002-01-01

Since the beginning of economic geology as a subdiscipline of the geological sciences, economic geologists have tended to classify mineral deposits on the basis of geological, mineralogical, and geochemical criteria, in efforts to systematize our understanding of mineral deposits as an aid to exploration. These efforts have led to classifications based on commodity, geologic setting (Cox and Singer, 1986), inferred temperatures and pressures of ore formation (Lindgren, 1933), and genetic setting (Park and MacDiarmid, 1975; Jensen and Bateman, 1979). None of these classification schemes is mutually exclusive; instead, there is considerable overlap among all of these classifications. A natural outcome of efforts to classify mineral deposits is the development of “mineral deposit models.” A mineral deposit model is a systematically arranged body of information that describes some or all of the essential characteristics of a selected group of mineral deposits; it presents a concept within which essential attributes may be distinguished and from which extraneous, coincidental features may be recognized and excluded (Barton, 1993). Barton (1993) noted that the grouping of deposits on the basis of common characteristics forms the basis for a classification, but the specification of the characteristics required for belonging to the group is the basis for a model. Models range from purely descriptive to genetic. A genetic model is superior to a descriptive model because it provides a basis to distinguish essential from extraneous attributes, and it has flexibility to accommodate variability in sources, processes, and local controls. In general, a descriptive model is a necessary prerequisite to a genetic model.

[Acceleration of Jingui Shenqi Pill on the testis telomerase activity in mice of Shen-yang deficiency].

PubMed

Xu, Cui-Ping; Zhu, Qing-Jun; Song, Jie; Li, Zhen; Zhang, Dan

2013-02-01

To explore the effects of Jingui Shenqi Pill (JSP) on the testis telomerase activity in mice of Shen-yang deficiency syndrome (SYDS). The SYDS model was prepared in 30 mice by over-fatigue and sexual overstrain. They were randomly divided into the model group and the JSP group, 15 in each group. Another 15 normal male mice were selected as the normal group. Mice in the normal group were fed routinely, with distilled water administered intragastrically at the daily dose of 0.1 mL/10 g. Mice in the model group were also administered intragastrically with distilled water at the daily dose of 0.1 mL/10 g while modeling establishment. Mice in the treatment group were administered intragastrically with JSP suspension at 0.1 mL/10 g (the concentration was 0.241 g/mL). The intervention lasted for 4 weeks. Four weeks later, the testis telomerase activity was detected in the three groups by ELISA. The SYDS model was replicated successfully by over-fatigue and sexual overstrain. JSP could improve the signs of mice of SYDS. Compared with the normal group, the activity of testis telomerase decreased in the model group (P < 0.01). Compared with the model group, the testis telomerase activity markedly increased in the treatment group (P < 0.01). The testis telomerase activity in mice of SYDS caused by over-fatigue and sexual overstrain obviously decreased, when compared with that in mice of the normal group. JSP could recover its activity.

[Discriminant analysis to predict the clinical diagnosis of primary immunodeficiencies: a preliminary report].

PubMed

Murata, Chiharu; Ramírez, Ana Belén; Ramírez, Guadalupe; Cruz, Alonso; Morales, José Luis; Lugo-Reyes, Saul Oswaldo

2015-01-01

The features in a clinical history from a patient with suspected primary immunodeficiency (PID) direct the differential diagnosis through pattern recognition. PIDs are a heterogeneous group of more than 250 congenital diseases with increased susceptibility to infection, inflammation, autoimmunity, allergy and malignancy. Linear discriminant analysis (LDA) is a multivariate supervised classification method to sort objects of study into groups by finding linear combinations of a number of variables. To identify the features that best explain membership of pediatric PID patients to a group of defect or disease. An analytic cross-sectional study was done with a pre-existing database with clinical and laboratory records from 168 patients with PID, followed at the National Institute of Pediatrics during 1991-2012, it was used to build linear discriminant models that would explain membership of each patient to the different group defects and to the most prevalent PIDs in our registry. After a preliminary run only 30 features were included (4 demographic, 10 clinical, 10 laboratory, 6 germs), with which the training models were developed through a stepwise regression algorithm. We compared the automatic feature selection with a selection made by a human expert, and then assessed the diagnostic usefulness of the resulting models (sensitivity, specificity, prediction accuracy and kappa coefficient), with 95% confidence intervals. The models incorporated 6 to 14 features to explain membership of PID patients to the five most abundant defect groups (combined, antibody, well-defined, dysregulation and phagocytosis), and to the four most prevalent PID diseases (X-linked agammaglobulinemia, chronic granulomatous disease, common variable immunodeficiency and ataxiatelangiectasia). In practically all cases of feature selection the machine outperformed the human expert. Diagnosis prediction using the equations created had a global accuracy of 83 to 94%, with sensitivity of 60 to 100%, specificity of 83 to 95% and kappa coefficient of 0.37 to 0.76. In general, the selection of features has clinical plausibility, and the practical advantage of utilizing only clinical attributes, infecting germs and routine lab results (blood cell counts and serum immunoglobulins). The performance of the model as a diagnostic tool was acceptable. The study's main limitations are a limited sample size and a lack of cross validation. This is only the first step in the construction of a machine learning system, with a wider approach that includes a larger database and different methodologies, to assist the clinical diagnosis of primary immunodeficiencies.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Polystyrene nanoparticle exposure induces ion-selective pores in lipid bilayers

PubMed Central

Negoda, Alexander; Kim, Kwang-Jin; Crandall, Edward D.; Worden, Robert M.

2014-01-01

A diverse range of molecular interactions can occur between engineered nanomaterials (ENM) and biomembranes, some of which could lead to toxic outcomes following human exposure to ENM. In this study, we adapted electrophysiology methods to investigate the ability of 20 nm polystyrene nanoparticles (PNP) to induce pores in model bilayer lipid membranes (BLM) that mimic biomembranes. PNP charge was varied using PNP decorated with either positive (amidine) groups or negative (carboxyl) groups, and BLM charge was varied using dioleoyl phospholipids having cationic (ethylphosphocholine), zwitterionic (phosphocholine), or anionic (phosphatidic acid) headgroups. Both positive and negative PNP induced BLM pores for all lipid compositions studied, as evidenced by current spikes and integral conductance. Stable PNP-induced pores exhibited ion selectivity, with the highest selectivity for K+ (PK/PCl ~ 8.3) observed when both the PNP and lipids were negatively charged, and the highest selectivity for Cl− (PK/PCl ~ 0.2) observed when both the PNP and lipids were positively charged. This trend is consistent with the finding that selectivity for an ion in channel proteins is imparted by oppositely charged functional groups within the channel’s filter region. The PK/PCl value was unaffected by the voltage-ramp method, the pore conductance, or the side of the BLM to which the PNP were applied. These results demonstrate for the first time that PNP can induce ion-selective pores in BLM, and that the degree of ion selectivity is influenced synergistically by the charges of both the lipid headgroups and functional groups on the PNP. PMID:23747366

The ties that bind: interorganizational linkages and physician-system alignment.

PubMed

Alexander, J A; Waters, T M; Burns, L R; Shortell, S M; Gillies, R R; Budetti, P P; Zuckerman, H S

2001-07-01

To examine the association between the degree of alignment between physicians and health care systems, and interorganizational linkages between physician groups and health care systems. The study used a cross sectional, comparative analysis using a sample of 1,279 physicians practicing in loosely affiliated arrangements and 1,781 physicians in 61 groups closely affiliated with 14 vertically integrated health systems. Measures of physician alignment were based on multiitem scales validated in previous studies and derived from surveys sent to individual physicians. Measures of interorganizational linkages were specified at the institutional, administrative, and technical core levels of the physician group and were developed from surveys sent to the administrator of each of the 61 physician groups in the sample. Two stage Heckman models with fixed effects adjustments in the second stage were used to correct for sample selection and clustering respectively. After accounting for sample selection, fixed effects, and group and individual controls, physicians in groups with more valued practice service linkages display consistently higher alignment with systems than physicians in groups that have fewer such linkages. Results also suggest that centralized administrative control lowers physician-system alignment for selected measures of alignment. Governance interlocks exhibited only weak associations with alignment. Our findings suggest that alignment generally follows resource exchanges that promote value-added contributions to physicians and physician groups while preserving control and authority within the group.

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

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

Cognitive Difficulties in Struggling Comprehenders and Their Relation to Reading Comprehension: A Comparison of Group Selection and Regression-Based Models

ERIC Educational Resources Information Center

Barnes, Marcia A.; Stuebing, Karla K.; Fletcher, Jack M.; Barth, Amy E.; Francis, David J.

2016-01-01

Difficulties suppressing previously encountered but currently irrelevant information from working memory characterize less skilled comprehenders in studies in which they are matched to skilled comprehenders on word decoding and nonverbal IQ. These "extreme" group designs are associated with several methodological issues. When sample size…

Utilities of gossip across organizational levels : Multilevel selection, free-riders, and teams.

PubMed

Kniffin, Kevin M; Wilson, David Sloan

2005-09-01

Gossip is a subject that has been studied by researchers from an array of disciplines with various foci and methods. We measured the content of language use by members of a competitive sports team across 18 months, integrating qualitative ethnographic methods with quantitative sampling and analysis. We hypothesized that the use of gossip will vary significantly depending on whether it is used for self-serving or group-serving purposes. Our results support a model of gossip derived from multilevel selection theory that expects gossip to serve group-beneficial rules when rewards are partitioned at the group level on a scale that permits mutual monitoring. We integrate our case study with earlier studies of gossip conducted by anthropologists, psychologists, and management researchers.

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

PubMed

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

2008-06-01

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

The pathogen transmission avoidance theory of sexual selection

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

Loehle, C.

1997-08-01

The current theory that sexual selection results from female preference for males with good genes suffers from several problems. An alternative explanation, the pathogen transmission avoidance hypothesis, argues that the primary function of showy traits is to provide a reliable signal of current disease status, so that sick individuals can be avoided during mating. This study shows that a significant risk of pathogen transmission occurs during mating and that showy traits are reliable indicators of current disease status. The origin of female choosiness is argued to lie in a general tendency to avoid sick individuals, even in the absence ofmore » showy traits, which originate as exaggerations of normal traits that are indicative of good health (bright feathers, vigorous movement, large size). Thus, in this new model the origins of both showy traits and female choosiness are not problematic and there is no threshold effect. This model predicts that when the possession of male showy traits does not help to reduce disease in the female, showy traits are unlikely to occur. This case corresponds to thorough exposure of every animal to all group pathogens, on average, in large groups. Such species are shown with a large data set on birds to be less likely to exhibit showy traits. The good-genes model does not make this prediction. The pathogen transmission avoidance model can also lead to the evolution of showy traits even when selection is not effective against a given pathogen (e.g., when there is no heritable variation for resistance), but can result in selection for resistance if such genes are present. Monogamy is argued to reduce selection pressures for showy traits; data show monogamous species to be both less parasitized and less showy. In the context of reduction of pathogen transmission rates in showy populations, selection pressure becomes inversely frequency-dependent, which makes showy traits likely to be self-limiting rather than runaway.« less

Basic Diagnosis and Prediction of Persistent Contrail Occurrence using High-resolution Numerical Weather Analyses/Forecasts and Logistic Regression. Part II: Evaluation of Sample Models

NASA Technical Reports Server (NTRS)

Duda, David P.; Minnis, Patrick

2009-01-01

Previous studies have shown that probabilistic forecasting may be a useful method for predicting persistent contrail formation. A probabilistic forecast to accurately predict contrail formation over the contiguous United States (CONUS) is created by using meteorological data based on hourly meteorological analyses from the Advanced Regional Prediction System (ARPS) and from the Rapid Update Cycle (RUC) as well as GOES water vapor channel measurements, combined with surface and satellite observations of contrails. Two groups of logistic models were created. The first group of models (SURFACE models) is based on surface-based contrail observations supplemented with satellite observations of contrail occurrence. The second group of models (OUTBREAK models) is derived from a selected subgroup of satellite-based observations of widespread persistent contrails. The mean accuracies for both the SURFACE and OUTBREAK models typically exceeded 75 percent when based on the RUC or ARPS analysis data, but decreased when the logistic models were derived from ARPS forecast data.

A Novel Group Decision-Making Method Based on Sensor Data and Fuzzy Information.

PubMed

Bai, Yu-Ting; Zhang, Bai-Hai; Wang, Xiao-Yi; Jin, Xue-Bo; Xu, Ji-Ping; Su, Ting-Li; Wang, Zhao-Yang

2016-10-28

Algal bloom is a typical phenomenon of the eutrophication of rivers and lakes and makes the water dirty and smelly. It is a serious threat to water security and public health. Most scholars studying solutions for this pollution have studied the principles of remediation approaches, but few have studied the decision-making and selection of the approaches. Existing research uses simplex decision-making information which is highly subjective and uses little of the data from water quality sensors. To utilize these data and solve the rational decision-making problem, a novel group decision-making method is proposed using the sensor data with fuzzy evaluation information. Firstly, the optimal similarity aggregation model of group opinions is built based on the modified similarity measurement of Vague values. Secondly, the approaches' ability to improve the water quality indexes is expressed using Vague evaluation methods. Thirdly, the water quality sensor data are analyzed to match the features of the alternative approaches with grey relational degrees. This allows the best remediation approach to be selected to meet the current water status. Finally, the selection model is applied to the remediation of algal bloom in lakes. The results show this method's rationality and feasibility when using different data from different sources.

Chest drainage teaching and training for medical students. Use of a surgical ex vivo pig model.

PubMed

Tube, Milton Ignacio Carvalho; Netto, Fernando Antonio Campelo Spencer; Costa, Elaine; Lafayette, Daniell de Siqueira Araújo; Lima, George Augusto da Fonseca Carvalho Antunes; Menezes, Jamile Isabela Santos de; Aires, Vinicius Gueiros Buenos; Ferraz, Álvaro Antônio Bandeira; Campos, Josemberg Marins; Moraes, Fernando Ribeiro de

2016-05-01

Implement a constructivist approach in thoracic drainage training in surgical ex vivo pig models, to compare the acquisition of homogeneous surgical skills between medical students. Experimental study, prospective, transversal, analytical, controlled, three steps. Selection, training, evaluation. a) students without training in thoracic drainage; b) without exposure to constructivist methodology. 2) EXCLUSION CRITERIA: a) students developed surgical skills; b) a history of allergy. (N = 312). Two groups participated in the study: A and B. Lecture equal for both groups. Differentiated teaching: group A, descriptive and informative method; group B, learning method based on problems. A surgical ex vivo pig model for training the chest drain was created. Were applied pre and post-test, test goal-discursive and OSATS scale. Theoretical averages: Group A = 9.5 ± 0.5; Group B = 8.8 ± 1.1 (p = 0.006). Medium Practices: Group A = 22.8 ± 1.8; Group B = 23.0 ± 2.8 (p <0.001). Through the constructivist methodology implemented in the thoracic drainage training in surgical ex vivo pig models, has proven the acquisition of surgical skills homogeneous compared among medical students.

Archer fish fast hunting maneuver may be guided by directionally selective retinal ganglion cells.

PubMed

Tsvilling, Vadim; Donchin, Opher; Shamir, Maoz; Segev, Ronen

2012-02-01

Archer fish are known for their unique hunting method, where one fish in a group shoots down an insect with a jet of water while all the other fish are observing the prey's motion. To reap its reward, the archer fish must reach the prey before its competitors. This requires fast computation of the direction of motion of the prey, which enables the fish to initiate a turn towards the prey with an accuracy of 99%, at about 100 ms after the prey is shot. We explored the hypothesis that direction-selective retinal ganglion cells may underlie this rapid processing. We quantified the degree of directional selectivity of ganglion cells in the archer fish retina. The cells could be categorized into three groups: sharply (5%), broadly (37%) and non-tuned (58%) directionally selective cells. To relate the electrophysiological data to the behavioral results we studied a computational model and estimated the time required to accumulate sufficient directional information to match the decision accuracy of the fish. The computational model is based on two direction-selective populations that race against each other until one reaches the threshold and drives the decision. We found that this competition model can account for the observed response time at the required accuracy. Thus, our results are consistent with the hypothesis that the fast response behavior of the archer fish relies on retinal identification of movement direction. © 2012 The Authors. European Journal of Neuroscience © 2012 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

STUDENT-TEACHER POPULATION GROWTH MODEL--DYNAMOD II.

ERIC Educational Resources Information Center

ZABROWSKI, EDWARD K.; AND OTHERS

DYNAMOD II IS A COMPUTERIZED MARKOVIAN-TYPE FLOW MODEL DEVELOPED TO PROVIDE ESTIMATES OF THE EDUCATIONAL POPULATION OF STUDENTS AND TEACHERS OVER SELECTED INTERVALS OF TIME. THE POPULATION IS CROSS-CLASSIFIED INTO 108 GROUPS BY SEX, RACE, AGE, AND EDUCATIONAL CATEGORY. THIS NOTE DESCRIBES THE METHODOLOGY USED IN DYNAMOD II, COMPARES DYNAMOD II…

A revision of chiggers of the minuta species-group (Acari: Trombiculidae: Neotrombicula Hirst, 1925) using multivariate morphometrics.

PubMed

Stekolnikov, Alexandr A; Klimov, Pavel B

2010-09-01

We revise chiggers belonging to the minuta-species group (genus Neotrombicula Hirst, 1925) from the Palaearctic using size-free multivariate morphometrics. This approach allowed us to resolve several diagnostic problems. We show that the widely distributed Neotrombicula scrupulosa Kudryashova, 1993 forms three spatially and ecologically isolated groups different from each other in size or shape (morphometric property) only: specimens from the Caucasus are distinct from those from Asia in shape, whereas the Asian specimens from plains and mountains are different from each other in size. We developed a multivariate classification model to separate three closely related species: N. scrupulosa, N. lubrica Kudryashova, 1993 and N. minuta Schluger, 1966. This model is based on five shape variables selected from an initial 17 variables by a best subset analysis using a custom size-correction subroutine. The variable selection procedure slightly improved the predictive power of the model, suggesting that it not only removed redundancy but also reduced 'noise' in the dataset. The overall classification accuracy of this model is 96.2, 96.2 and 95.5%, as estimated by internal validation, external validation and jackknife statistics, respectively. Our analyses resulted in one new synonymy: N. dimidiata Stekolnikov, 1995 is considered to be a synonym of N. lubrica. Both N. scrupulosa and N. lubrica are recorded from new localities. A key to species of the minuta-group incorporating results from our multivariate analyses is presented.

Effective connectivity between superior temporal gyrus and Heschl's gyrus during white noise listening: linear versus non-linear models.

PubMed

Hamid, Ka; Yusoff, An; Rahman, Mza; Mohamad, M; Hamid, Aia

2012-04-01

This fMRI study is about modelling the effective connectivity between Heschl's gyrus (HG) and the superior temporal gyrus (STG) in human primary auditory cortices. MATERIALS #ENTITYSTARTX00026; Ten healthy male participants were required to listen to white noise stimuli during functional magnetic resonance imaging (fMRI) scans. Statistical parametric mapping (SPM) was used to generate individual and group brain activation maps. For input region determination, two intrinsic connectivity models comprising bilateral HG and STG were constructed using dynamic causal modelling (DCM). The models were estimated and inferred using DCM while Bayesian Model Selection (BMS) for group studies was used for model comparison and selection. Based on the winning model, six linear and six non-linear causal models were derived and were again estimated, inferred, and compared to obtain a model that best represents the effective connectivity between HG and the STG, balancing accuracy and complexity. Group results indicated significant asymmetrical activation (p(uncorr) < 0.001) in bilateral HG and STG. Model comparison results showed strong evidence of STG as the input centre. The winning model is preferred by 6 out of 10 participants. The results were supported by BMS results for group studies with the expected posterior probability, r = 0.7830 and exceedance probability, ϕ = 0.9823. One-sample t-tests performed on connection values obtained from the winning model indicated that the valid connections for the winning model are the unidirectional parallel connections from STG to bilateral HG (p < 0.05). Subsequent model comparison between linear and non-linear models using BMS prefers non-linear connection (r = 0.9160, ϕ = 1.000) from which the connectivity between STG and the ipsi- and contralateral HG is gated by the activity in STG itself. We are able to demonstrate that the effective connectivity between HG and STG while listening to white noise for the respective participants can be explained by a non-linear dynamic causal model with the activity in STG influencing the STG-HG connectivity non-linearly.

Evaluation of cancer mortality in a cohort of workers exposed to low-level radiation

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

Lea, C.S.

1995-12-01

The purpose of this dissertation was to re-analyze existing data to explore methodologic approaches that may determine whether excess cancer mortality in the ORNL cohort can be explained by time-related factors not previously considered; grouping of cancer outcomes; selection bias due to choice of method selected to incorporate an empirical induction period; or the type of statistical model chosen.

Tree Biomass Allocation and Its Model Additivity for Casuarina equisetifolia in a Tropical Forest of Hainan Island, China.

PubMed

Xue, Yang; Yang, Zhongyang; Wang, Xiaoyan; Lin, Zhipan; Li, Dunxi; Su, Shaofeng

2016-01-01

Casuarina equisetifolia is commonly planted and used in the construction of coastal shelterbelt protection in Hainan Island. Thus, it is critical to accurately estimate the tree biomass of Casuarina equisetifolia L. for forest managers to evaluate the biomass stock in Hainan. The data for this work consisted of 72 trees, which were divided into three age groups: young forest, middle-aged forest, and mature forest. The proportion of biomass from the trunk significantly increased with age (P<0.05). However, the biomass of the branch and leaf decreased, and the biomass of the root did not change. To test whether the crown radius (CR) can improve biomass estimates of C. equisetifolia, we introduced CR into the biomass models. Here, six models were used to estimate the biomass of each component, including the trunk, the branch, the leaf, and the root. In each group, we selected one model among these six models for each component. The results showed that including the CR greatly improved the model performance and reduced the error, especially for the young and mature forests. In addition, to ensure biomass additivity, the selected equation for each component was fitted as a system of equations using seemingly unrelated regression (SUR). The SUR method not only gave efficient and accurate estimates but also achieved the logical additivity. The results in this study provide a robust estimation of tree biomass components and total biomass over three groups of C. equisetifolia.

Tree Biomass Allocation and Its Model Additivity for Casuarina equisetifolia in a Tropical Forest of Hainan Island, China

PubMed Central

Xue, Yang; Yang, Zhongyang; Wang, Xiaoyan; Lin, Zhipan; Li, Dunxi; Su, Shaofeng

2016-01-01

Casuarina equisetifolia is commonly planted and used in the construction of coastal shelterbelt protection in Hainan Island. Thus, it is critical to accurately estimate the tree biomass of Casuarina equisetifolia L. for forest managers to evaluate the biomass stock in Hainan. The data for this work consisted of 72 trees, which were divided into three age groups: young forest, middle-aged forest, and mature forest. The proportion of biomass from the trunk significantly increased with age (P<0.05). However, the biomass of the branch and leaf decreased, and the biomass of the root did not change. To test whether the crown radius (CR) can improve biomass estimates of C. equisetifolia, we introduced CR into the biomass models. Here, six models were used to estimate the biomass of each component, including the trunk, the branch, the leaf, and the root. In each group, we selected one model among these six models for each component. The results showed that including the CR greatly improved the model performance and reduced the error, especially for the young and mature forests. In addition, to ensure biomass additivity, the selected equation for each component was fitted as a system of equations using seemingly unrelated regression (SUR). The SUR method not only gave efficient and accurate estimates but also achieved the logical additivity. The results in this study provide a robust estimation of tree biomass components and total biomass over three groups of C. equisetifolia. PMID:27002822

Histone deacetylase inhibitors with a primary amide zinc binding group display antitumor activity in xenograft model.

PubMed

Attenni, Barbara; Ontoria, Jesus M; Cruz, Jonathan C; Rowley, Michael; Schultz-Fademrecht, Carsten; Steinkühler, Christian; Jones, Philip

2009-06-01

Histone deacetylase (HDAC) inhibition causes hyperacetylation of histones leading to differentiation, growth arrest and apoptosis of malignant cells, representing a new strategy in cancer therapy. Many of the known HDAC inhibitors (HDACi) that are in clinical trials possess a hydroxamic acid, that is a strong Zn(2+) binding group, thereby inhibiting some of the class I and class II isoforms. Herein we describe the identification of a selective class I HDAC inhibitor bearing a primary carboxamide moiety as zinc binding group. This HDACi displays good antiproliferative activity against multiple cancer cell lines, and demonstrates efficacy in a xenograft model comparable to vorinostat.

Furan-2-ylmethylene thiazolidinediones as novel, potent, and selective inhibitors of phosphoinositide 3-kinase gamma.

PubMed

Pomel, Vincent; Klicic, Jasna; Covini, David; Church, Dennis D; Shaw, Jeffrey P; Roulin, Karen; Burgat-Charvillon, Fabienne; Valognes, Delphine; Camps, Montserrat; Chabert, Christian; Gillieron, Corinne; Françon, Bernard; Perrin, Dominique; Leroy, Didier; Gretener, Denise; Nichols, Anthony; Vitte, Pierre Alain; Carboni, Susanna; Rommel, Christian; Schwarz, Matthias K; Rückle, Thomas

2006-06-29

Class I phosphoinositide 3-kinases (PI3Ks), in particular PI3Kgamma, have become attractive drug targets for inflammatory and autoimmune diseases. Here, we disclose a novel series of furan-2-ylmethylene thiazolidinediones as selective, ATP-competitive PI3Kgamma inhibitors. Structure-based design and X-ray crystallography of complexes formed by inhibitors bound to PI3Kgamma identified key pharmacophore features for potency and selectivity. An acidic NH group on the thiazolidinedione moiety and a hydroxy group on the furan-2-yl-phenyl part of the molecule play crucial roles in binding to PI3K and contribute to class IB PI3K selectivity. Compound 26 (AS-252424), a potent and selective small-molecule PI3Kgamma inhibitor emerging from these efforts, was further profiled in three different cellular PI3K assays and shown to be selective for class IB PI3K-mediated cellular effects. Oral administration of 26 in a mouse model of acute peritonitis led to a significant reduction of leukocyte recruitment.

Re-Examining of Moffitt’s Theory of Delinquency through Agent Based Modeling

PubMed Central

Leaw, Jia Ning; Ang, Rebecca P.; Huan, Vivien S.; Chan, Wei Teng; Cheong, Siew Ann

2015-01-01

Moffitt’s theory of delinquency suggests that at-risk youths can be divided into two groups, the adolescence- limited group and the life-course-persistent group, predetermined at a young age, and social interactions between these two groups become important during the adolescent years. We built an agent-based model based on the microscopic interactions Moffitt described: (i) a maturity gap that dictates (ii) the cost and reward of antisocial behavior, and (iii) agents imitating the antisocial behaviors of others more successful than themselves, to find indeed the two groups emerging in our simulations. Moreover, through an intervention simulation where we moved selected agents from one social network to another, we also found that the social network plays an important role in shaping the life course outcome. PMID:26062022

Assessment of resource selection models to predict occurrence of five juvenile flatfish species (Pleuronectidae) over the continental shelf in the western Gulf of Alaska

NASA Astrophysics Data System (ADS)

Wilson, Matthew T.; Mier, Kathryn L.; Cooper, Dan W.

2016-05-01

According to the nursery size hypothesis, flatfish recruitment is constrained by nursery area. Thus, if resource selection models can be shown to accurately predict the location and geographic extent of flatfish nursery areas, they will become important tools in the management and study of flatfish population dynamics. We demonstrate that some resource selection models derived previously to predict the presence and absence of juvenile flatfishes near shore were applicable to the broader continental shelf. For other age-species groups, derivation of new models for the continental shelf was necessary. Our study was conducted in the western Gulf of Alaska (GoA) during October 2011 on four groups of age-0 juvenile flatfishes: Pacific halibut (Hippoglossus stenolepis), arrowtooth flounder (Atheresthes stomias), northern rock sole (Lepidopsetta polyxystra), and flathead sole (Hippoglossoides elassodon); and three groups of age-1 juvenile flatfishes: northern rock sole, flathead sole, and yellowfin sole (Limanda aspera). Sampling occurred at 33 sites across the continental shelf. Fish were collected using a 3-m beam trawl, and a midwater trawl. Environmental data were collected on sediment composition and water temperature and depth. Many of the age-species groups co-occurred in the Shumagin and Barnabus sea valleys; however, age-0 arrowtooth flounder occurred at more locations than other juveniles, perhaps due to a relatively broad tolerance of environmental conditions and to the utilization of midwater habitat. Thus, the large nursery area of arrowtooth flounder may be one reason why they are currently the most abundant GoA flatfish. In fact, among all species, mean recruitment at age 3 increased with the percent occurrence of age-0 juveniles at the 33 sites, a proxy for relative nursery area, in accordance with the nursery size hypothesis, suggesting that mean recruitment among GoA flatfishes is structured by nursery size.

The large soybean (Glycine max) WRKY TF family expanded by segmental duplication events and subsequent divergent selection among subgroups

PubMed Central

2013-01-01

Background WRKY genes encode one of the most abundant groups of transcription factors in higher plants, and its members regulate important biological process such as growth, development, and responses to biotic and abiotic stresses. Although the soybean genome sequence has been published, functional studies on soybean genes still lag behind those of other species. Results We identified a total of 133 WRKY members in the soybean genome. According to structural features of their encoded proteins and to the phylogenetic tree, the soybean WRKY family could be classified into three groups (groups I, II, and III). A majority of WRKY genes (76.7%; 102 of 133) were segmentally duplicated and 13.5% (18 of 133) of the genes were tandemly duplicated. This pattern was not apparent in Arabidopsis or rice. The transcriptome atlas revealed notable differential expression in either transcript abundance or in expression patterns under normal growth conditions, which indicated wide functional divergence in this family. Furthermore, some critical amino acids were detected using DIVERGE v2.0 in specific comparisons, suggesting that these sites have contributed to functional divergence among groups or subgroups. In addition, site model and branch-site model analyses of positive Darwinian selection (PDS) showed that different selection regimes could have affected the evolution of these groups. Sites with high probabilities of having been under PDS were found in groups I, II c, II e, and III. Together, these results contribute to a detailed understanding of the molecular evolution of the WRKY gene family in soybean. Conclusions In this work, all the WRKY genes, which were generated mainly through segmental duplication, were identified in the soybean genome. Moreover, differential expression and functional divergence of the duplicated WRKY genes were two major features of this family throughout their evolutionary history. Positive selection analysis revealed that the different groups have different evolutionary rates. Together, these results contribute to a detailed understanding of the molecular evolution of the WRKY gene family in soybean. PMID:24088323

Factors affecting the accuracy of genomic selection for growth and wood quality traits in an advanced-breeding population of black spruce (Picea mariana).

PubMed

Lenz, Patrick R N; Beaulieu, Jean; Mansfield, Shawn D; Clément, Sébastien; Desponts, Mireille; Bousquet, Jean

2017-04-28

Genomic selection (GS) uses information from genomic signatures consisting of thousands of genetic markers to predict complex traits. As such, GS represents a promising approach to accelerate tree breeding, which is especially relevant for the genetic improvement of boreal conifers characterized by long breeding cycles. In the present study, we tested GS in an advanced-breeding population of the boreal black spruce (Picea mariana [Mill.] BSP) for growth and wood quality traits, and concurrently examined factors affecting GS model accuracy. The study relied on 734 25-year-old trees belonging to 34 full-sib families derived from 27 parents and that were established on two contrasting sites. Genomic profiles were obtained from 4993 Single Nucleotide Polymorphisms (SNPs) representative of as many gene loci distributed among the 12 linkage groups common to spruce. GS models were obtained for four growth and wood traits. Validation using independent sets of trees showed that GS model accuracy was high, related to trait heritability and equivalent to that of conventional pedigree-based models. In forward selection, gains per unit of time were three times higher with the GS approach than with conventional selection. In addition, models were also accurate across sites, indicating little genotype-by-environment interaction in the area investigated. Using information from half-sibs instead of full-sibs led to a significant reduction in model accuracy, indicating that the inclusion of relatedness in the model contributed to its higher accuracies. About 500 to 1000 markers were sufficient to obtain GS model accuracy almost equivalent to that obtained with all markers, whether they were well spread across the genome or from a single linkage group, further confirming the implication of relatedness and potential long-range linkage disequilibrium (LD) in the high accuracy estimates obtained. Only slightly higher model accuracy was obtained when using marker subsets that were identified to carry large effects, indicating a minor role for short-range LD in this population. This study supports the integration of GS models in advanced-generation tree breeding programs, given that high genomic prediction accuracy was obtained with a relatively small number of markers due to high relatedness and family structure in the population. In boreal spruce breeding programs and similar ones with long breeding cycles, much larger gain per unit of time can be obtained from genomic selection at an early age than by the conventional approach. GS thus appears highly profitable, especially in the context of forward selection in species which are amenable to mass vegetative propagation of selected stock, such as spruces.

Variable selection based cotton bollworm odor spectroscopic detection

NASA Astrophysics Data System (ADS)

Lü, Chengxu; Gai, Shasha; Luo, Min; Zhao, Bo

2016-10-01

Aiming at rapid automatic pest detection based efficient and targeting pesticide application and shooting the trouble of reflectance spectral signal covered and attenuated by the solid plant, the possibility of near infrared spectroscopy (NIRS) detection on cotton bollworm odor is studied. Three cotton bollworm odor samples and 3 blank air gas samples were prepared. Different concentrations of cotton bollworm odor were prepared by mixing the above gas samples, resulting a calibration group of 62 samples and a validation group of 31 samples. Spectral collection system includes light source, optical fiber, sample chamber, spectrometer. Spectra were pretreated by baseline correction, modeled with partial least squares (PLS), and optimized by genetic algorithm (GA) and competitive adaptive reweighted sampling (CARS). Minor counts differences are found among spectra of different cotton bollworm odor concentrations. PLS model of all the variables was built presenting RMSEV of 14 and RV2 of 0.89, its theory basis is insect volatilizes specific odor, including pheromone and allelochemics, which are used for intra-specific and inter-specific communication and could be detected by NIR spectroscopy. 28 sensitive variables are selected by GA, presenting the model performance of RMSEV of 14 and RV2 of 0.90. Comparably, 8 sensitive variables are selected by CARS, presenting the model performance of RMSEV of 13 and RV2 of 0.92. CARS model employs only 1.5% variables presenting smaller error than that of all variable. Odor gas based NIR technique shows the potential for cotton bollworm detection.

Development of an evidence-based decision pathway for vestibular schwannoma treatment options.

PubMed

Linkov, Faina; Valappil, Benita; McAfee, Jacob; Goughnour, Sharon L; Hildrew, Douglas M; McCall, Andrew A; Linkov, Igor; Hirsch, Barry; Snyderman, Carl

To integrate multiple sources of clinical information with patient feedback to build evidence-based decision support model to facilitate treatment selection for patients suffering from vestibular schwannomas (VS). This was a mixed methods study utilizing focus group and survey methodology to solicit feedback on factors important for making treatment decisions among patients. Two 90-minute focus groups were conducted by an experienced facilitator. Previously diagnosed VS patients were recruited by clinical investigators at the University of Pittsburgh Medical Center (UPMC). Classical content analysis was used for focus group data analysis. Providers were recruited from practices within the UPMC system and were surveyed using Delphi methods. This information can provide a basis for multi-criteria decision analysis (MCDA) framework to develop a treatment decision support system for patients with VS. Eight themes were derived from these data (focus group + surveys): doctor/health care system, side effects, effectiveness of treatment, anxiety, mortality, family/other people, quality of life, and post-operative symptoms. These data, as well as feedback from physicians were utilized in building a multi-criteria decision model. The study illustrated steps involved in the development of a decision support model that integrates evidence-based data and patient values to select treatment alternatives. Studies focusing on the actual development of the decision support technology for this group of patients are needed, as decisions are highly multifactorial. Such tools have the potential to improve decision making for complex medical problems with alternate treatment pathways. Copyright © 2016 Elsevier Inc. All rights reserved.

The protective effect of different airway humidification liquids to lung after tracheotomy in traumatic brain injury: The role of pulmonary surfactant protein-A (SP-A).

PubMed

Su, Xinyang; Li, Zefu; Wang, Meilin; Li, Zhenzhu; Wang, Qingbo; Lu, Wenxian; Li, Xiaoli; Zhou, Youfei; Xu, Hongmei

2016-02-10

The purpose of this study was to establish a rat model of a brain injury with tracheotomy and compared the wetting effects of different airway humidification liquids, afterward, the best airway humidification liquid was selected for the clinical trial, thus providing a theoretical basis for selecting a proper airway humidification liquid in a clinical setting. Rats were divided into a sham group, group A (0.9% NaCl), group B (0.45% NaCl), group C (0.9% NaCl+ambroxol) and group D (0.9% NaCl+Pulmicort). An established rat model of traumatic brain injury with tracheotomy was used. Brain tissue samples were taken to determine water content, while lung tissue samples were taken to determine wet/dry weight ratio (W/D), histological changes and expression levels of SP-A mRNA and SP-A protein. 30 patients with brain injury and tracheotomy were selected and divided into two groups based on the airway humidification liquid instilled in the trachea tube, 0.45% NaCl and 0.9% NaCl+ambroxol. Blood was then extracted from the patients to measure the levels of SP-A, interleukin-6 (IL-6), interleukin-8 (IL-8) and tumour necrosis factor-α (TNF-α). The difference between group C and other groups in lung W/D and expression levels of SP-A mRNA and SP-A protein was significant (P<0.05). In comparison, the histological changes showed that the lung tissue damage was smallest in group C compared to the three other groups. Aspect of patients, 0.45% NaCl group and 0.9% NaCl+ambroxol group were significantly different in the levels of SP-A, IL-6, IL-8 and TNF-α (P<0.01). In the present study, 0.9% NaCl+ambroxol promote the synthesis and secretion of pulmonary surfactant, and has anti-inflammatory and antioxidant effects, which inhibit the release of inflammatory factors and cytokines, making it an ideal airway humidification liquid. Copyright © 2015 Elsevier B.V. All rights reserved.

Merging universal and indicated prevention programs: the Fast Track model. Conduct Problems Prevention Research Group.

PubMed

2000-01-01

Fast Track is a multisite, multicomponent preventive intervention for young children at high risk for long-term antisocial behavior. Based on a comprehensive developmental model, this intervention includes a universal-level classroom program plus social-skill training, academic tutoring, parent training, and home visiting to improve competencies and reduce problems in a high-risk group of children selected in kindergarten. The theoretical principles and clinical strategies utilized in the Fast Track Project are described to illustrate the interplay between basic developmental research, the understanding of risk and protective factors, and a research-based model of preventive intervention that integrates universal and indicated models of prevention.

Assessing Local Model Adequacy in Bayesian Hierarchical Models Using the Partitioned Deviance Information Criterion

PubMed Central

Wheeler, David C.; Hickson, DeMarc A.; Waller, Lance A.

2010-01-01

Many diagnostic tools and goodness-of-fit measures, such as the Akaike information criterion (AIC) and the Bayesian deviance information criterion (DIC), are available to evaluate the overall adequacy of linear regression models. In addition, visually assessing adequacy in models has become an essential part of any regression analysis. In this paper, we focus on a spatial consideration of the local DIC measure for model selection and goodness-of-fit evaluation. We use a partitioning of the DIC into the local DIC, leverage, and deviance residuals to assess local model fit and influence for both individual observations and groups of observations in a Bayesian framework. We use visualization of the local DIC and differences in local DIC between models to assist in model selection and to visualize the global and local impacts of adding covariates or model parameters. We demonstrate the utility of the local DIC in assessing model adequacy using HIV prevalence data from pregnant women in the Butare province of Rwanda during 1989-1993 using a range of linear model specifications, from global effects only to spatially varying coefficient models, and a set of covariates related to sexual behavior. Results of applying the diagnostic visualization approach include more refined model selection and greater understanding of the models as applied to the data. PMID:21243121

Path analysis and multi-criteria decision making: an approach for multivariate model selection and analysis in health.

PubMed

Vasconcelos, A G; Almeida, R M; Nobre, F F

2001-08-01

This paper introduces an approach that includes non-quantitative factors for the selection and assessment of multivariate complex models in health. A goodness-of-fit based methodology combined with fuzzy multi-criteria decision-making approach is proposed for model selection. Models were obtained using the Path Analysis (PA) methodology in order to explain the interrelationship between health determinants and the post-neonatal component of infant mortality in 59 municipalities of Brazil in the year 1991. Socioeconomic and demographic factors were used as exogenous variables, and environmental, health service and agglomeration as endogenous variables. Five PA models were developed and accepted by statistical criteria of goodness-of fit. These models were then submitted to a group of experts, seeking to characterize their preferences, according to predefined criteria that tried to evaluate model relevance and plausibility. Fuzzy set techniques were used to rank the alternative models according to the number of times a model was superior to ("dominated") the others. The best-ranked model explained above 90% of the endogenous variables variation, and showed the favorable influences of income and education levels on post-neonatal mortality. It also showed the unfavorable effect on mortality of fast population growth, through precarious dwelling conditions and decreased access to sanitation. It was possible to aggregate expert opinions in model evaluation. The proposed procedure for model selection allowed the inclusion of subjective information in a clear and systematic manner.

Semiparametric Bayesian classification with longitudinal markers

PubMed Central

De la Cruz-Mesía, Rolando; Quintana, Fernando A.; Müller, Peter

2013-01-01

Summary We analyse data from a study involving 173 pregnant women. The data are observed values of the β human chorionic gonadotropin hormone measured during the first 80 days of gestational age, including from one up to six longitudinal responses for each woman. The main objective in this study is to predict normal versus abnormal pregnancy outcomes from data that are available at the early stages of pregnancy. We achieve the desired classification with a semiparametric hierarchical model. Specifically, we consider a Dirichlet process mixture prior for the distribution of the random effects in each group. The unknown random-effects distributions are allowed to vary across groups but are made dependent by using a design vector to select different features of a single underlying random probability measure. The resulting model is an extension of the dependent Dirichlet process model, with an additional probability model for group classification. The model is shown to perform better than an alternative model which is based on independent Dirichlet processes for the groups. Relevant posterior distributions are summarized by using Markov chain Monte Carlo methods. PMID:24368871

Computational screening of functional groups for capture of toxic industrial chemicals in porous materials.

PubMed

Kim, Ki Chul; Fairen-Jimenez, David; Snurr, Randall Q

2017-12-06

A thermodynamic analysis using quantum chemical methods was carried out to identify optimal functional group candidates that can be included in metal-organic frameworks and activated carbons for the selective capture of toxic industrial chemicals (TICs) in humid air. We calculated the binding energies of 14 critical TICs plus water with a series of 10 functional groups attached to a naphthalene ring model. Using vibrational calculations, the free energies of adsorption were calculated in addition to the binding energies. Our results show that, in these systems, the binding energies and free energies follow similar trends. We identified copper(i) carboxylate as the optimal functional group (among those studied) for the selective binding of the majority of the TICs in humid air, and this functional group exhibits especially strong binding for sulfuric acid. Further thermodynamic analysis shows that the presence of water weakens the binding strength of sulfuric acid with the copper carboxylate group. Our calculations predict that functionalization of aromatic rings would be detrimental to selective capture of COCl 2 , CO 2 , and Cl 2 under humid conditions. Finally, we found that forming an ionic complex, H 3 O + HSO 4 - , between H 2 SO 4 and H 2 O via proton transfer is not favorable on copper carboxylate.

Home range overlap as a driver of intelligence in primates.

PubMed

Grueter, Cyril C

2015-04-01

Various socioecological factors have been suggested to influence cognitive capacity in primates, including challenges associated with foraging and dealing with the complexities of social life. Alexander [Alexander, 1989]. Evolution of the human psyche. In: Mellars P, Stringer C, editors. The human revolution: Behavioural and biological perspectives on the origins of modern humans. Princeton: Princeton University Press. p 455-513] proposed an integrative model for the evolution of human cognitive abilities and complex sociality that incorporates competition among coalitions of conspecifics (inter-group conflict) as a major selective pressure. However, one of the premises of this model, i.e., that when confronted with inter-group conflict selection should favor enhanced cognition, has remained empirically untested. Using a comparative approach on species data, I aimed to test the prediction that primate species (n = 104) that face greater inter-group conflict have higher cognitive abilities (indexed by endocranial volume). The degree of inter-group conflict/complexity was approximated via the variable home range overlap among groups. I found a significant relationship between home range overlap and endocranial volume, even after controlling for other predictor variables and covariates such as group size and body mass. I conclude that brain size evolution cannot be attributed exclusively to social factors such as group size, but likely reflects a variety of social and ecological determinants including inter-group conflict which poses cognitive demands on monitoring both the wider social milieu as well as spatial attributes of the habitat. © 2014 Wiley Periodicals, Inc.

Motivation and Engagement in the "Asian Century": A Comparison of Chinese Students in Australia, Hong Kong, and Mainland China

ERIC Educational Resources Information Center

Martin, A. J.; Yu, Kai; Hau, Kit-Tai

2014-01-01

The present study investigated multidimensional motivation and engagement among Chinese middle school students in Australia (N?=?273), Hong Kong (N?=?528), and Mainland China (N?=?2106; randomly selected N?=?528). Findings showed that a multidimensional model of motivation and engagement fit very well for all three groups. Multi-group invariance…

Examples of seismic modelling

NASA Astrophysics Data System (ADS)

Pamyatnykh, A. A.

2008-12-01

Findings of a few recent asteroseismic studies of the main sequence pulsating stars, as per- formed in Wojciech Dziembowski’s group in Warsaw and in Michel Breger’s group in Vienna, are briefly presented and discussed. The selected objects are three hybrid pulsators ν Eridani, 12 Lacertae and γ Pegasi, which show both β Cephei and SPB type modes, and the δ Scuti type star 44 Tauri.

Arguments, contradictions, resistances, and conceptual change in students' understanding of atomic structure

NASA Astrophysics Data System (ADS)

Niaz, Mansoor; Aguilera, Damarys; Maza, Arelys; Liendo, Gustavo

2002-07-01

Most general chemistry courses and textbooks emphasize experimental details and lack a history and philosophy of science perspective. The objective of this study is to facilitate freshman general chemistry students' understanding of atomic structure based on the work of Thomson, Rutherford, and Bohr. It is hypothesized that classroom discussions based on arguments/counterarguments of the heuristic principles, on which these scientists based their atomic models, can facilitate students' conceptual understanding. This study is based on 160 freshman students enrolled in six sections of General Chemistry I (three sections formed part of the experimental group). All three models (Thomson, Rutherford, and Bohr) were presented to the experimental and control group students in the traditional manner, as found in most textbooks. After this, the three sections of the experimental group participated in the discussion of six items with alternative responses. Students were first asked to select a response and then participate in classroom discussions leading to arguments in favor or against the selected response and finally select a new response. Three weeks after having discussed the six items, both the experimental and control groups presented a monthly exam (based on the three models) and after another 3 weeks a semester exam. Results obtained show that given the opportunity to argue and discuss, students' understanding can go beyond the simple regurgitation of experimental details. Performance of the experimental group showed contradictions, resistances, and progressive conceptual change with considerable and consistent improvement in the last item. It is concluded that if we want our students to understand scientific progress and practice, then it is important that we include the experimental details not as a rhetoric of conclusions (Schwab, 1962, The teaching of science as enquiry, Cambridge, MA, Harward University Press; Schwab, 1974, Conflicting conceptions of curriculum, Berkeley, CA, McCutchan) but as heuristic principles (Lakatos, 1970, Criticism and the growth of knowledge, Cambridge, UK, Cambridge University Press, pp. 91-195), which were based on arguments, controversies, and interpretations of the scientists.

Screening for thrombophilia in high-risk situations: a meta-analysis and cost-effectiveness analysis.

PubMed

Wu, Olivia; Robertson, Lindsay; Twaddle, Sara; Lowe, Gordon; Clark, Peter; Walker, Isobel; Brenkel, Ivan; Greaves, Mike; Langhorne, Peter; Regan, Lesley; Greer, Ian

2005-10-01

Laboratory testing for the identification of heritable thrombophilia in high-risk patient groups have become common practice; however, indiscriminate testing of all patients is unjustified. The objective of this study was to evaluate the cost-effectiveness of universal and selective history-based thrombophilia screening relative to no screening, from the perspective of the UK National Health Service, in women prior to prescribing combined oral contraceptives and hormone replacement therapy, women during pregnancy and patients prior to major orthopaedic surgery. A decision analysis model was developed, and data from meta-analysis, the literature and two Delphi studies were incorporated in the model. Incremental cost-effectiveness ratios (ICERs) for screening compared with no screening was calculated for each patient group. Of all the patient groups evaluated, universal screening of women prior to prescribing hormone replacement therapy was the most cost-effective (ICER 6824 pounds). In contrast, universal screening of women prior to prescribing combined oral contraceptives was the least cost-effective strategy (ICER 202,402 pounds). Selective thrombophilia screening based on previous personal and/or family history of venous thromboembolism was more cost-effective than universal screening in all the patient groups evaluated.

Alternative Methods for Handling Attrition

PubMed Central

Foster, E. Michael; Fang, Grace Y.

2009-01-01

Using data from the evaluation of the Fast Track intervention, this article illustrates three methods for handling attrition. Multiple imputation and ignorable maximum likelihood estimation produce estimates that are similar to those based on listwise-deleted data. A panel selection model that allows for selective dropout reveals that highly aggressive boys accumulate in the treatment group over time and produces a larger estimate of treatment effect. In contrast, this model produces a smaller treatment effect for girls. The article's conclusion discusses the strengths and weaknesses of the alternative approaches and outlines ways in which researchers might improve their handling of attrition. PMID:15358906

The evolution of colour polymorphism in British winter-active Lepidoptera in response to search image use by avian predators.

PubMed

Weir, Jamie C

2018-05-10

Phenotypic polymorphism in cryptic species is widespread. This may evolve in response to search image use by predators exerting negative frequency-dependent selection on intraspecific colour morphs, 'apostatic selection'. Evidence exists to indicate search image formation by predators and apostatic selection operating on wild prey populations, though not to demonstrate search image use directly resulting in apostatic selection. The present study attempted to address this deficiency, using British Lepidoptera active in winter as a model system. It has been proposed that the typically polymorphic wing colouration of these species represents an anti-search image adaptation against birds. To test (a) for search image-driven apostatic selection, dimorphic populations of artificial moth-like models were established in woodland at varying relative morph frequencies and exposed to predation by natural populations of birds. In addition, to test (b) whether abundance and degree of polymorphism are correlated across British winter-active moths, as predicted where search image use drives apostatic selection, a series of phylogenetic comparative analyses were conducted. There was a positive relationship between artificial morph frequency and probability of predation, consistent with birds utilizing search images and exerting apostatic selection. Abundance and degree of polymorphism were found to be positively correlated across British Lepidoptera active in winter, though not across all taxonomic groups analysed. This evidence is consistent with polymorphism in this group having evolved in response to search image-driven apostatic selection and supports the viability of this mechanism as a means by which phenotypic and genetic variation may be maintained in natural populations. © 2018 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2018 European Society For Evolutionary Biology.

Discovery and quantitative structure-activity relationship study of lepidopteran HMG-CoA reductase inhibitors as selective insecticides.

PubMed

Zang, Yang-Yang; Li, Yuan-Mei; Yin, Yue; Chen, Shan-Shan; Kai, Zhen-Peng

2017-09-01

In a previous study we have demonstrated that insect 3-hydroxy-3-methylglutaryl-CoA reductase (HMGR) can be a potential selective insecticide target. Three series of inhibitors were designed on the basis of the difference in HMGR structures from Homo sapiens and Manduca sexta, with the aim of discovering potent selective insecticide candidates. An in vitro bioassay showed that gem-difluoromethylenated statin analogues have potent effects on JH biosynthesis of M. sexta and high selectivity between H. sapiens and M. sexta. All series II compounds {1,3,5-trisubstituted [4-tert-butyl 2-(5,5-difluoro-2,2-dimethyl-6-vinyl-4-yl) acetate] pyrazoles} have some effect on JH biosynthesis, whereas most of them are inactive on human HMGR. In particular, the IC 50 value of compound II-12 (37.8 nm) is lower than that of lovastatin (99.5 nm) and similar to that of rosuvastatin (24.2 nm). An in vivo bioassay showed that I-1, I-2, I-3 and II-12 are potential selective insecticides, especially for lepidopteran pest control. A predictable and statistically meaningful CoMFA model of 23 inhibitors (20 as training sets and three as test sets) was obtained with a value of q 2 and r 2 of 0.66 and 0.996 respectively. The final model suggested that a potent insect HMGR inhibitor should contain suitable small and non-electronegative groups in the ring part, and electronegative groups in the side chain. Four analogues were discovered as potent selective lepidopteran HMGR inhibitors, which can specifically be used for lepidopteran pest control. The CoMFA model will be useful for the design of new selective insect HMGR inhibitors that are structurally related to the training set compounds. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Probing the chemical interaction space governed by 4-aminosubstituted benzenesulfonamides and carbonic anhydrase isoforms.

PubMed

Rasti, Behnam; Heravi, Yeganeh Entezari

2018-06-01

Isoform diversity, critical physiological roles and involvement in major diseases/disorders such as glaucoma, epilepsy, Alzheimer's disease, obesity, and cancers have made carbonic anhydrase (CA), one of the most interesting case studies in the field of computer aided drug design. Since applying non-selective inhibitors can result in major side effects, there have been considerable efforts so far to achieve selective inhibitors for different isoforms of CA. Using proteochemometrics approach, the chemical interaction space governed by a group of 4-amino-substituted benzenesulfonamides and human CAs has been explored in the present study. Several validation methods have been utilized to assess the validity, robustness and predictivity power of the proposed proteochemometric model. Our model has offered major structural information that can be applied to design new selective inhibitors for distinct isoforms of CA. To prove the applicability of the proposed model, new compounds have been designed based on the offered discriminative structural features.

Water resources planning for rivers draining into Mobile Bay. Part 2: Non-conservative species transport models

NASA Technical Reports Server (NTRS)

April, G. C.; Liu, H. A.

1975-01-01

Total coliform group bacteria were selected to expand the mathematical modeling capabilities of the hydrodynamic and salinity models to understand their relationship to commercial fishing ventures within bay waters and to gain a clear insight into the effect that rivers draining into the bay have on water quality conditions. Parametric observations revealed that temperature factors and river flow rate have a pronounced effect on the concentration profiles, while wind conditions showed only slight effects. An examination of coliform group loading concentrations at constant river flow rates and temperature shows these loading changes have an appreciable influence on total coliform distribution within Mobile Bay.

Pre-Enrollment Reimbursement Patterns of Medicare Beneficiaries Enrolled in “At-Risk” HMOs

PubMed Central

Eggers, Paul W.; Prihoda, Ronald

1982-01-01

The Health Care Financing Administration (HCFA) has initiated several demonstration projects to encourage HMOs to participate in the Medicare program under a risk mechanism. These demonstrations are designed to test innovative marketing techniques, benefit packages, and reimbursement levels. HCFA's current method for prospective payments to HMOs is based on the Adjusted Average Per Capita Cost (AAPCC). An important issue in prospective reimbursement is the extent to which the AAPCC adequately reflects the risk factors which arise out of the selection process of Medicare beneficiaries into HMOs. This study examines the pre-enrollment reimbursement experience of Medicare beneficiaries who enrolled in the demonstration HMOs to determine whether or not a non-random selection process took place. The three demonstration HMOs included in the study are the Fallon Community Health Plan, the Greater Marshfield Community Health Plan, and the Kaiser-Permanente medical program of Portland, Oregon. The study includes 18,085 aged Medicare beneficiaries who had enrolled in the three plans as of April, 1981. We included comparison groups consisting of a 5 percent random sample of aged Medicare beneficiaries (N = 11,240) living in the same geographic areas as the control groups. The study compares the groups by total Medicare reimbursements for the years 1976 through 1979. Adjustments were made for AAPCC factor differences in the groups (age, sex, institutional status, and welfare status). In two of the HMO areas there was evidence of a selection process among the HMOs enrollees. Enrollees in the Fallon and Kaiser health plans were found to have had 20 percent lower Medicare reimbursements than their respective comparison groups in the four years prior to enrollment. This effect was strongest for inpatient services, but a significant difference also existed for use of physician and outpatient services. In the Marshfield HMO there was no statistically significant difference in pre-enrollment Medicare total reimbursements between the enrollee and comparison groups. However, outpatient and physician reimbursements were significantly higher (22 percent) among the enrollee group. The results of this study suggest that the AAPCC may not be an adequate mechanism for setting prospective reimbursement rates. The Marshfield results further suggest that the type of HMO may have an influence on the selection process among Medicare beneficiaries. If Medicare beneficiaries do not have to change providers to join an HMO, as in an IPA model or a staff model which includes most of the providers in an area, the selection process may be more likely to result in an unbiased risk group. PMID:10309720

Analysis of the Efficacy of an Intervention to Improve Parent-Adolescent Problem Solving

PubMed Central

Semeniuk, Yulia Yuriyivna; Brown, Roger L.; Riesch, Susan K.

2016-01-01

We conducted a two-group longitudinal partially nested randomized controlled trial to examine whether young adolescent youth-parent dyads participating in Mission Possible: Parents and Kids Who Listen, in contrast to a comparison group, would demonstrate improved problem solving skill. The intervention is based on the Circumplex Model and Social Problem Solving Theory. The Circumplex Model posits that families who are balanced, that is characterized by high cohesion and flexibility and open communication, function best. Social Problem Solving Theory informs the process and skills of problem solving. The Conditional Latent Growth Modeling analysis revealed no statistically significant differences in problem solving among the final sample of 127 dyads in the intervention and comparison groups. Analyses of effect sizes indicated large magnitude group effects for selected scales for youth and dyads portraying a potential for efficacy and identifying for whom the intervention may be efficacious if study limitations and lessons learned were addressed. PMID:26936844

Auto Body. Instructional System Development Model for Vermont Area Vocational Centers.

ERIC Educational Resources Information Center

1975

The model curriculum guide was developed to teach auto body repair in secondary schools in Vermont. From a needs assessment of the occupational opportunities in automotive services in the state, a group of selected occupations were analyzed for skill content and translated into the curriculum content. The guide consists of 14 units, each with a…

Fuel treatment effects on modeled landscape level fire behavior in the northern Sierra Nevada

Treesearch

J.J. Moghaddas; B.M. Collins; K. Menning; E.E.Y. Moghaddas; S.L. Stephens

2010-01-01

Across the western United States, decades of fire exclusion combined with past management history have contributed to the current condition of extensive areas of high-density, shade-tolerant coniferous stands that are increasingly prone to high-severity fires. Here, we report the modeled effects of constructed defensible fuel profile zones and group selection...

Remote sensing techniques aid in preattack planning for fire management

Treesearch

Lucy Anne Salazar

1982-01-01

Remote sensing techniques were investigated as an alternative for documenting selected prettack fire planning information. Locations of fuel models, road systems, and water sources were recorded by Landsat satellite imagery and aerial photography for a portion of the Six Rivers National Forest in northwestern California. The two fuel model groups used were from the...

Analysis of High School German Textbooks through Rasch Measurement Model

ERIC Educational Resources Information Center

Batdi, Veli; Elaldi, Senel

2016-01-01

The purpose of the present study is to analyze German teacher trainers' views on high school German textbooks through the Rasch measurement model. A survey research design was employed and study group consisted of a total of 21 teacher trainers, three from each region and selected randomly from provinces which are located in seven regions and…

Model forest landscape change in the Missouri Ozarks under alternative management practices

Treesearch

Stephen R. Shifley; Frank R. Thompson; David R. Larsen; William D. Dijak

2000-01-01

We used a spatially explicit landscape model, LANDIS, to simulate the effects of five management alternatives on a 3216 ha forest landscape in southeast Missouri, USA. We compared management alternatives among two intensities of even-aged management with clearcutting, uneven-aged management with group selection harvest, a mixture of even- and uneven-aged management,...

"i h8 u": The Influence of Normative Beliefs and Hostile Response Selection in Predicting Adolescents' Mobile Phone Aggression--A Pilot Study

ERIC Educational Resources Information Center

Nicol, Annemarie; Fleming, Michele J.

2010-01-01

Mobile phone aggression (MPA) is a relatively new phenomenon. Using newly developed measures, a pilot study was conducted with 348 adolescents ages 13-17 years to determine the incidence of MPA and victimization in this group of adolescents and to test a proposed model in which hostile response selection mediated the relationship between normative…

Risk selection and cost shifting in a prospective physician payment system: evidence from Ontario.

PubMed

Kantarevic, Jasmin; Kralj, Boris

2014-04-01

We study the risk-selection and cost-shifting behavior of physicians in a unique capitation payment model in Ontario, using the incentive to enroll and care for complex and vulnerable patients as a case study. This incentive, which is incremental to the regular capitation payment, ceases after the first year of patient enrollment and may therefore impact on the physician's decision to continue to enroll the patient. Furthermore, because the enrolled patients in Ontario can seek care from any provider, the enrolling physician may shift some treatment costs to other providers. Using longitudinal administrative data and a control group of physicians in the fee-for-service model who were eligible for the same incentive, we find no evidence of either patient 'dumping' or cost shifting. These results highlight the need to re-examine the conventional wisdom about risk selection for physician payment models that significantly deviate from the stylized capitation model. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Random and non-random mating populations: Evolutionary dynamics in meiotic drive.

PubMed

Sarkar, Bijan

2016-01-01

Game theoretic tools are utilized to analyze a one-locus continuous selection model of sex-specific meiotic drive by considering nonequivalence of the viabilities of reciprocal heterozygotes that might be noticed at an imprinted locus. The model draws attention to the role of viability selections of different types to examine the stable nature of polymorphic equilibrium. A bridge between population genetics and evolutionary game theory has been built up by applying the concept of the Fundamental Theorem of Natural Selection. In addition to pointing out the influences of male and female segregation ratios on selection, configuration structure reveals some noted results, e.g., Hardy-Weinberg frequencies hold in replicator dynamics, occurrence of faster evolution at the maximized variance fitness, existence of mixed Evolutionarily Stable Strategy (ESS) in asymmetric games, the tending evolution to follow not only a 1:1 sex ratio but also a 1:1 different alleles ratio at particular gene locus. Through construction of replicator dynamics in the group selection framework, our selection model introduces a redefining bases of game theory to incorporate non-random mating where a mating parameter associated with population structure is dependent on the social structure. Also, the model exposes the fact that the number of polymorphic equilibria will depend on the algebraic expression of population structure. Copyright © 2015 Elsevier Inc. All rights reserved.

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

PubMed

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

2015-04-24

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

Disease-Free Survival after Hepatic Resection in Hepatocellular Carcinoma Patients: A Prediction Approach Using Artificial Neural Network

PubMed Central

Ho, Wen-Hsien; Lee, King-Teh; Chen, Hong-Yaw; Ho, Te-Wei; Chiu, Herng-Chia

2012-01-01

Background A database for hepatocellular carcinoma (HCC) patients who had received hepatic resection was used to develop prediction models for 1-, 3- and 5-year disease-free survival based on a set of clinical parameters for this patient group. Methods The three prediction models included an artificial neural network (ANN) model, a logistic regression (LR) model, and a decision tree (DT) model. Data for 427, 354 and 297 HCC patients with histories of 1-, 3- and 5-year disease-free survival after hepatic resection, respectively, were extracted from the HCC patient database. From each of the three groups, 80% of the cases (342, 283 and 238 cases of 1-, 3- and 5-year disease-free survival, respectively) were selected to provide training data for the prediction models. The remaining 20% of cases in each group (85, 71 and 59 cases in the three respective groups) were assigned to validation groups for performance comparisons of the three models. Area under receiver operating characteristics curve (AUROC) was used as the performance index for evaluating the three models. Conclusions The ANN model outperformed the LR and DT models in terms of prediction accuracy. This study demonstrated the feasibility of using ANNs in medical decision support systems for predicting disease-free survival based on clinical databases in HCC patients who have received hepatic resection. PMID:22235270

32 CFR 1624.3 - Age selection groups.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 32 National Defense 6 2013-07-01 2013-07-01 false Age selection groups. 1624.3 Section 1624.3 National Defense Other Regulations Relating to National Defense SELECTIVE SERVICE SYSTEM INDUCTIONS § 1624.3 Age selection groups. Age selection groups are established as follows: (a) The age 20 selection group for each calendar year consists of...

32 CFR 1624.3 - Age selection groups.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 32 National Defense 6 2014-07-01 2014-07-01 false Age selection groups. 1624.3 Section 1624.3 National Defense Other Regulations Relating to National Defense SELECTIVE SERVICE SYSTEM INDUCTIONS § 1624.3 Age selection groups. Age selection groups are established as follows: (a) The age 20 selection group for each calendar year consists of...

32 CFR 1624.3 - Age selection groups.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 32 National Defense 6 2010-07-01 2010-07-01 false Age selection groups. 1624.3 Section 1624.3 National Defense Other Regulations Relating to National Defense SELECTIVE SERVICE SYSTEM INDUCTIONS § 1624.3 Age selection groups. Age selection groups are established as follows: (a) The age 20 selection group for each calendar year consists of...

32 CFR 1624.3 - Age selection groups.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 32 National Defense 6 2012-07-01 2012-07-01 false Age selection groups. 1624.3 Section 1624.3 National Defense Other Regulations Relating to National Defense SELECTIVE SERVICE SYSTEM INDUCTIONS § 1624.3 Age selection groups. Age selection groups are established as follows: (a) The age 20 selection group for each calendar year consists of...

32 CFR 1624.3 - Age selection groups.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 32 National Defense 6 2011-07-01 2011-07-01 false Age selection groups. 1624.3 Section 1624.3 National Defense Other Regulations Relating to National Defense SELECTIVE SERVICE SYSTEM INDUCTIONS § 1624.3 Age selection groups. Age selection groups are established as follows: (a) The age 20 selection group for each calendar year consists of...

Evaluation and determination of soil remediation schemes using a modified AHP model and its application in a contaminated coking plant.

PubMed

Li, Xingang; Li, Jia; Sui, Hong; He, Lin; Cao, Xingtao; Li, Yonghong

2018-07-05

Soil remediation has been considered as one of the most difficult pollution treatment tasks due to its high complexity in contaminants, geological conditions, usage, urgency, etc. The diversity in remediation technologies further makes quick selection of suitable remediation schemes much tougher even the site investigation has been done. Herein, a sustainable decision support hierarchical model has been developed to select, evaluate and determine preferred soil remediation schemes comprehensively based on modified analytic hierarchy process (MAHP). This MAHP method combines competence model and the Grubbs criteria with the conventional AHP. It not only considers the competence differences among experts in group decision, but also adjusts the big deviation caused by different experts' preference through sample analysis. This conversion allows the final remediation decision more reasonable. In this model, different evaluation criteria, including economic effect, environmental effect and technological effect, are employed to evaluate the integrated performance of remediation schemes followed by a strict computation using above MAHP. To confirm the feasibility of this developed model, it has been tested by a benzene workshop contaminated site in Beijing coking plant. Beyond soil remediation, this MAHP model would also be applied in other fields referring to multi-criteria group decision making. Copyright © 2018 Elsevier B.V. All rights reserved.

OCT despeckling via weighted nuclear norm constrained non-local low-rank representation

NASA Astrophysics Data System (ADS)

Tang, Chang; Zheng, Xiao; Cao, Lijuan

2017-10-01

As a non-invasive imaging modality, optical coherence tomography (OCT) plays an important role in medical sciences. However, OCT images are always corrupted by speckle noise, which can mask image features and pose significant challenges for medical analysis. In this work, we propose an OCT despeckling method by using non-local, low-rank representation with weighted nuclear norm constraint. Unlike previous non-local low-rank representation based OCT despeckling methods, we first generate a guidance image to improve the non-local group patches selection quality, then a low-rank optimization model with a weighted nuclear norm constraint is formulated to process the selected group patches. The corrupted probability of each pixel is also integrated into the model as a weight to regularize the representation error term. Note that each single patch might belong to several groups, hence different estimates of each patch are aggregated to obtain its final despeckled result. Both qualitative and quantitative experimental results on real OCT images show the superior performance of the proposed method compared with other state-of-the-art speckle removal techniques.

Selective efficacy of zoledronic acid on metastasis in a patient-derived orthotopic xenograph (PDOX) nude-mouse model of human pancreatic cancer.

PubMed

Hiroshima, Yukihiko; Maawy, Ali A; Katz, Matthew H G; Fleming, Jason B; Bouvet, Michael; Endo, Itaru; Hoffman, Robert M

2015-03-01

Patient-derived orthotopic xenograft (PDOX) nude-mouse models replicate the behavior of clinical cancer, including metastasis. The objective of the study was to determine the efficacy of zoledronic acid (ZA) on metastasis of a patient-derived orthotopic xenograft (PDOX) nude-mouse model of pancreatic cancer. In the present study, we examined the efficacy of ZA on pancreatic cancer growth and metastasis in a PDOX nude-mouse model. ZA monotherapy did not significantly suppress primary tumor growth. However, the primary tumor weight of gemcitabine (GEM) and combination GEM + ZA-treated mice was significantly decreased compared to the control group (GEM: P = 0.003; GEM + ZA: P = 0.002). The primary tumor weight of GEM + ZA-treated mice was significantly decreased compared to GEM-treated mice (P = 0.016). The metastasis weight decreased in ZA- or GEM-treated mice compared to the control group (ZA: P = 0.009; GEM: P = 0.007. No metastasis was detected in combination GEM + ZA-treated mice compared to the control group (GEM + ZA; P = 0.005). The results of the present study indicate that ZA can selectively target metastasis in a pancreatic cancer PDOX model and that the combination of ZA and GEM should be evaluated clinically in the near future for this highly treatment-resistant disease. © 2014 Wiley Periodicals, Inc.

Area 2: Inexpensive Monitoring and Uncertainty Assessment of CO2 Plume Migration using Injection Data

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

Srinivasan, Sanjay

2014-09-30

In-depth understanding of the long-term fate of CO₂ in the subsurface requires study and analysis of the reservoir formation, the overlaying caprock formation, and adjacent faults. Because there is significant uncertainty in predicting the location and extent of geologic heterogeneity that can impact the future migration of CO₂ in the subsurface, there is a need to develop algorithms that can reliably quantify this uncertainty in plume migration. This project is focused on the development of a model selection algorithm that refines an initial suite of subsurface models representing the prior uncertainty to create a posterior set of subsurface models thatmore » reflect injection performance consistent with that observed. Such posterior models can be used to represent uncertainty in the future migration of the CO₂ plume. Because only injection data is required, the method provides a very inexpensive method to map the migration of the plume and the associated uncertainty in migration paths. The model selection method developed as part of this project mainly consists of assessing the connectivity/dynamic characteristics of a large prior ensemble of models, grouping the models on the basis of their expected dynamic response, selecting the subgroup of models that most closely yield dynamic response closest to the observed dynamic data, and finally quantifying the uncertainty in plume migration using the selected subset of models. The main accomplishment of the project is the development of a software module within the SGEMS earth modeling software package that implements the model selection methodology. This software module was subsequently applied to analyze CO₂ plume migration in two field projects – the In Salah CO₂ Injection project in Algeria and CO₂ injection into the Utsira formation in Norway. These applications of the software revealed that the proxies developed in this project for quickly assessing the dynamic characteristics of the reservoir were highly efficient and yielded accurate grouping of reservoir models. The plume migration paths probabilistically assessed by the method were confirmed by field observations and auxiliary data. The report also documents the application of the software to answer practical questions such as the optimum location of monitoring wells to reliably assess the migration of CO₂ plume, the effect of CO₂-rock interactions on plume migration and the ability to detect the plume under those conditions and the effect of a slow, unresolved leak on the predictions of plume migration.« less

Potential field cellular automata model for pedestrian flow

NASA Astrophysics Data System (ADS)

Zhang, Peng; Jian, Xiao-Xia; Wong, S. C.; Choi, Keechoo

2012-02-01

This paper proposes a cellular automata model of pedestrian flow that defines a cost potential field, which takes into account the costs of travel time and discomfort, for a pedestrian to move to an empty neighboring cell. The formulation is based on a reconstruction of the density distribution and the underlying physics, including the rule for resolving conflicts, which is comparable to that in the floor field cellular automaton model. However, we assume that each pedestrian is familiar with the surroundings, thereby minimizing his or her instantaneous cost. This, in turn, helps reduce the randomness in selecting a target cell, which improves the existing cellular automata modelings, together with the computational efficiency. In the presence of two pedestrian groups, which are distinguished by their destinations, the cost distribution for each group is magnified due to the strong interaction between the two groups. As a typical phenomenon, the formation of lanes in the counter flow is reproduced.

Clonal selection prevents tragedy of the commons when neighbors compete in a rock-paper-scissors game

NASA Astrophysics Data System (ADS)

Juul, Jeppe; Sneppen, Kim; Mathiesen, Joachim

2012-06-01

The rock-paper-scissors game is a model example of the ongoing cyclic turnover typical of many ecosystems, ranging from the terrestrial and aquatic to the microbial. Here we explore the evolution of a rock-paper-scissors system where three species compete for space. The species are allowed to mutate and change the speed by which they invade one another. In the case when all species have similar mutation rates, we observe a perpetual arms race where no single species prevails. When only two species mutate, their aggressions increase indefinitely until the ecosystem collapses and only the nonmutating species survives. Finally we show that when only one species mutates, group selection removes individual predators with the fastest growth rates, causing the growth rate of the species to stabilize. We explain this group selection quantitatively.

Predicting higher selection in elite junior Australian Rules football: The influence of physical performance and anthropometric attributes.

PubMed

Robertson, Sam; Woods, Carl; Gastin, Paul

2015-09-01

To develop a physiological performance and anthropometric attribute model to predict Australian Football League draft selection. Cross-sectional observational. Data was obtained (n=4902) from three Under-18 Australian football competitions between 2010 and 2013. Players were allocated into one of the three groups, based on their highest level of selection in their final year of junior football (Australian Football League Drafted, n=292; National Championship, n=293; State-level club, n=4317). Physiological performance (vertical jumps, agility, speed and running endurance) and anthropometric (body mass and height) data were obtained. Hedge's effect sizes were calculated to assess the influence of selection-level and competition on these physical attributes, with logistic regression models constructed to discriminate Australian Football League Drafted and National Championship players. Rule induction analysis was undertaken to determine a set of rules for discriminating selection-level. Effect size comparisons revealed a range of small to moderate differences between State-level club players and both other groups for all attributes, with trivial to small differences between Australian Football League Drafted and National Championship players noted. Logistic regression models showed multistage fitness test, height and 20 m sprint time as the most important attributes in predicting Draft success. Rule induction analysis showed that players displaying multistage fitness test scores of >14.01 and/or 20 m sprint times of <2.99 s were most likely to be recruited. High levels of performance in aerobic and/or speed tests increase the likelihood of elite junior Australian football players being recruited to the highest level of the sport. Copyright © 2014 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

More robust regional precipitation projection from selected CMIP5 models based on multiple-dimensional metrics

NASA Astrophysics Data System (ADS)

Qian, Y.; Wang, L.; Leung, L. R.; Lin, G.; Lu, J.; Gao, Y.; Zhang, Y.

2017-12-01

Projecting precipitation changes is challenging because of incomplete understanding of the climate system and biases and uncertainty in climate models. In East Asia where summer precipitation is dominantly influenced by the monsoon circulation and the global models from Coupled Model Intercomparison Project Phase 5 (CMIP5), however, give various projection of precipitation change for 21th century. It is critical for community to know which models' projection are more reliable in response to natural and anthropogenic forcings. In this study we defined multiple-dimensional metrics, measuring the model performance in simulating the present-day of large-scale circulation, regional precipitation and relationship between them. The large-scale circulation features examined in this study include the lower tropospheric southwesterly winds, the western North Pacific subtropical high, the South China Sea Subtropical High, and the East Asian westerly jet in the upper troposphere. Each of these circulation features transport moisture to East Asia, enhancing the moist static energy and strengthening the Meiyu moisture front that is the primary mechanism for precipitation generation in eastern China. Based on these metrics, 30 models in CMIP5 ensemble are classified into three groups. Models in the top performing group projected regional precipitation patterns that are more similar to each other than the bottom or middle performing group and consistently projected statistically significant increasing trends in two of the large-scale circulation indices and precipitation. In contrast, models in the bottom or middle performing group projected small drying or no trends in precipitation. We also find the models that only reasonably reproduce the observed precipitation climatology does not guarantee more reliable projection of future precipitation because good simulation skill could be achieved through compensating errors from multiple sources. Herein the potential for more robust projections of precipitation changes at regional scale is demonstrated through the use of discriminating metric to subsample the multi-model ensemble. The results from this study provides insights for how to select models from CMIP ensemble to project regional climate and hydrological cycle changes.

Cannabinoid receptor type 2 (CB2)-selective N-aryl-oxadiazolyl-propionamides: synthesis, radiolabelling, molecular modelling and biological evaluation

PubMed Central

2012-01-01

Background The endocannabinoid system is involved in many physiological and pathological processes. Two receptors (cannabinoid receptor type 1 (CB1) and type 2 (CB2)) are known so far. Many unwanted psychotic side effects of inhibitors of this system can be addressed to the interaction with CB1. While CB1 is one of the most abundant neuroreceptors, CB2 is expressed in the brain only at very low levels. Thus, highly potent and selective compounds for CB2 are desired. N-aryl-((hetero)aromatic)-oxadiazolyl-propionamides represent a promising class of such selective ligands for the human CB2. Here, a library of various derivatives is studied for suitable routes for labelling with 18F. Such 18F-labelled compounds can then be employed as CB2-selective radiotracers for molecular imaging studies employing positron emission tomography (PET). Results By varying the N-arylamide substructure, we explored the binding pocket of the human CB2 receptor and identified 9-ethyl-9H-carbazole amide as the group with optimal size. Radioligand replacement experiments revealed that the modification of the (hetero)aromatic moiety in 3-position of the 1,2,4-oxadiazoles shows only moderate impact on affinity to CB2 but high impact on selectivity towards CB2 with respect to CB1. Further, we could show by autoradiography studies that the most promising compounds bind selectively on CB2 receptors in mouse spleen tissue. Molecular docking studies based on a novel three-dimensional structural model of the human CB2 receptor in its activated form indicate that the compounds bind with the N-arylamide substructure in the binding pocket. 18F labelling at the (hetero)aromatic moiety at the opposite site of the compounds via radiochemistry was carried out. Conclusions The synthesized CB2-selective compounds have high affinity towards CB2 and good selectivity against CB1. The introduction of labelling groups at the (hetero)aromatic moiety shows only moderate impact on CB2 affinity, indicating the introduction of potential labelling groups at this position as a promising approach to develop CB2-selective ligands suitable for molecular imaging with PET. The high affinity for human CB2 and selectivity against human CB1 of the herein presented compounds renders them as suitable candidates for molecular imaging studies. PMID:23067874

SELECT RESEARCH GROUP IN AIR POLLUTION METEOROLOGY

EPA Science Inventory

Six individual investigators, who have conducted different but related meteorological research, present in-depth technical reviews of their work. Prime conclusions are that (1) a scale analysis shows that different models are necessary for meteorological processes on urban, regio...

Collective motion in animal groups from a neurobiological perspective: the adaptive benefits of dynamic sensory loads and selective attention.

PubMed

Lemasson, B H; Anderson, J J; Goodwin, R A

2009-12-21

We explore mechanisms associated with collective animal motion by drawing on the neurobiological bases of sensory information processing and decision-making. The model uses simplified retinal processes to translate neighbor movement patterns into information through spatial signal integration and threshold responses. The structure provides a mechanism by which individuals can vary their sets of influential neighbors, a measure of an individual's sensory load. Sensory loads are correlated with group order and density, and we discuss their adaptive values in an ecological context. The model also provides a mechanism by which group members can identify, and rapidly respond to, novel visual stimuli.

The Origin of Species by Means of Mathematical Modelling.

PubMed

Bessonov, Nikolai; Reinberg, Natalia; Banerjee, Malay; Volpert, Vitaly

2018-04-30

Darwin described biological species as groups of morphologically similar individuals. These groups of individuals can split into several subgroups due to natural selection, resulting in the emergence of new species. Some species can stay stable without the appearance of a new species, some others can disappear or evolve. Some of these evolutionary patterns were described in our previous works independently of each other. In this work we have developed a single model which allows us to reproduce the principal patterns in Darwin's diagram. Some more complex evolutionary patterns are also observed. The relation between Darwin's definition of species, stated above, and Mayr's definition of species (group of individuals that can reproduce) is also discussed.

Status change during adulthood: life-history by-product or kin selection based on reproductive value?

PubMed Central

Combes, S. L.; Altmann, J.

2001-01-01

When dominance status predicts fitness, most adaptive models of dominance relationships among cercopithecine primate females predict lifetime maintenance of status. These models and alternative ones positing rank decline as a non-adaptive by-product have remained largely untested, however, because lifetime status of older adults has been virtually unknown for natural populations. In a 25-year study of adult female savannah baboons (Papio cynocephalus), in each of three social groups, rank losses were common among the 66 females that lived past median adult age. These losses were not accounted for by loss in relative rank from group growth or by loss in absolute rank from reversals in rank between members of different maternal families or between sisters. Rather, females that had mature daughters experienced loss of dominance status to these offspring, a characteristic of all but the top-ranking matriline of each group. Among proposed hypotheses for rank reversals between adults, that of kin selection based on relative reproductive value is most clearly supported by these data. In contrast, observed patterns of rank loss are not consistent with alternative models that postulate that changes during adult lifespan are a product of accumulated risk, physical decline during ageing, or coalitionary support among females within or between matrilines. PMID:11429136

Fast Screening Technology for Drug Emergency Management: Predicting Suspicious SNPs for ADR with Information Theory-based Models.

PubMed

Liang, Zhaohui; Liu, Jun; Huang, Jimmy X; Zeng, Xing

2018-01-01

The genetic polymorphism of Cytochrome P450 (CYP 450) is considered as one of the main causes for adverse drug reactions (ADRs). In order to explore the latent correlations between ADRs and potentially corresponding single-nucleotide polymorphism (SNPs) in CYP450, three algorithms based on information theory are used as the main method to predict the possible relation. The study uses a retrospective case-control study to explore the potential relation of ADRs to specific genomic locations and single-nucleotide polymorphism (SNP). The genomic data collected from 53 healthy volunteers are applied for the analysis, another group of genomic data collected from 30 healthy volunteers excluded from the study are used as the control group. The SNPs respective on five loci of CYP2D6*2,*10,*14 and CYP1A2*1C, *1F are detected by the Applied Biosystem 3130xl. The raw data is processed by ChromasPro to detect the specific alleles on the above loci from each sample. The secondary data are reorganized and processed by R combined with the reports of ADRs from clinical reports. Three information theory based algorithms are implemented for the screening task: JMI, CMIM, and mRMR. If a SNP is selected by more than two algorithms, we are confident to conclude that it is related to the corresponding ADR. The selection results are compared with the control decision tree + LASSO regression model. In the study group where ADRs occur, 10 SNPs are considered relevant to the occurrence of a specific ADR by the combined information theory model. In comparison, only 5 SNPs are considered relevant to a specific ADR by the decision tree + LASSO regression model. In addition, the new method detects more relevant pairs of SNP and ADR which are affected by both SNP and dosage. This implies that the new information theory based model is effective to discover correlations of ADRs and CYP 450 SNPs and is helpful in predicting the potential vulnerable genotype for some ADRs. The newly proposed information theory based model has superiority performance in detecting the relation between SNP and ADR compared to the decision tree + LASSO regression model. The new model is more sensitive to detect ADRs compared to the old method, while the old method is more reliable. Therefore, the selection criteria for selecting algorithms should depend on the pragmatic needs. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Social structure affects mating competition in a damselfish

NASA Astrophysics Data System (ADS)

Wacker, Sebastian; Ness, Miriam Horstad; Östlund-Nilsson, Sara; Amundsen, Trond

2017-12-01

The strength of mating competition and sexual selection varies over space and time in many animals. Such variation is typically driven by ecological and demographic factors, including adult sex ratio and consequent availability of mates. The spatial scale at which demographic factors affect mating competition and sexual selection may vary but is not often investigated. Here, we analyse variation in size and sex ratio of social groups, and how group structure affects mating competition, in the site-attached damselfish Chrysiptera cyanea. Site-attached reef fishes are known to show extensive intraspecific variation in social structure. Previous work has focused on species for which the size and dynamics of social groups are constrained by habitat, whereas species with group structure unconstrained by habitat have received little attention. Chrysiptera cyanea is such a species, with individuals occurring in spatial clusters that varied widely in size and sex ratio. Typically, only one male defended a nest in multi-male groups. Nest-holding males were frequently visited by mate-searching females, with more visits in groups with more females, suggesting that courtship and mating mostly occur within groups and that male mating success depends on the number of females in the group. Male-male aggression was frequent in multi-male groups but absent in single-male groups. These findings demonstrate that groups are distinct social units. In consequence, the dynamics of mating and reproduction are mainly a result of group structure, largely unaffected short term by overall population demography which would be important in open social systems. Future studies of the C. cyanea model system should analyse longer-term dynamics, including how groups are formed, how they vary in relation to density and time of season and how social structure affects sexual selection.

Selective visual scaling of time-scale processes facilitates broadband learning of isometric force frequency tracking.

PubMed

King, Adam C; Newell, Karl M

2015-10-01

The experiment investigated the effect of selectively augmenting faster time scales of visual feedback information on the learning and transfer of continuous isometric force tracking tasks to test the generality of the self-organization of 1/f properties of force output. Three experimental groups tracked an irregular target pattern either under a standard fixed gain condition or with selectively enhancement in the visual feedback display of intermediate (4-8 Hz) or high (8-12 Hz) frequency components of the force output. All groups reduced tracking error over practice, with the error lowest in the intermediate scaling condition followed by the high scaling and fixed gain conditions, respectively. Selective visual scaling induced persistent changes across the frequency spectrum, with the strongest effect in the intermediate scaling condition and positive transfer to novel feedback displays. The findings reveal an interdependence of the timescales in the learning and transfer of isometric force output frequency structures consistent with 1/f process models of the time scales of motor output variability.

Substitution of a single amino acid residue in the aromatic/arginine selectivity filter alters the transport profiles of tonoplast aquaporin homologs.

PubMed

Azad, Abul Kalam; Yoshikawa, Naoki; Ishikawa, Takahiro; Sawa, Yoshihiro; Shibata, Hitoshi

2012-01-01

Aquaporins are integral membrane proteins that facilitate the transport of water and some small solutes across cellular membranes. X-ray crystallography of aquaporins indicates that four amino acids constitute an aromatic/arginine (ar/R) pore constriction known as the selectivity filter. On the basis of these four amino acids, tonoplast aquaporins called tonoplast intrinsic proteins (TIPs) are divided into three groups in Arabidopsis. Herein, we describe the characterization of two group I TIP1s (TgTIP1;1 and TgTIP1;2) from tulip (Tulipa gesneriana). TgTIP1;1 and TgTIP1;2 have a novel isoleucine in loop E (LE2 position) of the ar/R filter; the residue at LE2 is a valine in all group I TIPs from model plants. The homologs showed mercury-sensitive water channel activity in a fast kinetics swelling assay upon heterologous expression in Pichia pastoris. Heterologous expression of both homologs promoted the growth of P. pastoris on ammonium or urea as sole sources of nitrogen and decreased growth and survival in the presence of H(2)O(2). TgTIP1;1- and TgTIP1;2-mediated H(2)O(2) conductance was demonstrated further by a fluorescence assay. Substitutions in the ar/R selectivity filter of TgTIP1;1 showed that mutants that mimicked the ar/R constriction of group I TIPs could conduct the same substrates that were transported by wild-type TgTIP1;1. In contrast, mutants that mimicked group II TIPs showed no evidence of urea or H(2)O(2) conductance. These results suggest that the amino acid residue at LE2 position is critical for the transport selectivity of the TIP homologs and group I TIPs might have a broader spectrum of substrate selectivity than group II TIPs. Copyright © 2011 Elsevier B.V. All rights reserved.

Weak cation exchange magnetic beads coupled with matrix-assisted laser desorption ionization-time of flight-mass spectrometry in screening serum protein markers in osteopenia.

PubMed

He, Wei-Tao; Liang, Bo-Cheng; Shi, Zhen-Yu; Li, Xu-Yun; Li, Chun-Wen; Shi, Xiao-Lin

2016-01-01

The present study aimed at investigating the weak cation magnetic separation technology and matrix-assisted laser desorption ionization-time of flight-mass spectrometry (MALDI-TOF-MS) in screening serum protein markers of osteopenia from ten postmenopausal women and ten postmenopausal women without osteopenia as control group, to find a new method for screening biomarkers and establishing a diagnostic model for primary type I osteoporosis. Serum samples were collected from postmenopausal women with osteopenia and postmenopausal women with normal bone mass. Proteins were extracted from serum samples by weak cation exchange magnetic beads technology, and mass spectra acquisition was done by MALDI-TOF-MS. The visualization and comparison of data sets, statistical peak evaluation, model recognition, and discovery of biomarker candidates were handled by the proteinchip data analysis system software(ZJU-PDAS). The diagnostic models were established using genetic arithmetic based support vector machine (SVM). The SVM result with the highest Youden Index was selected as the model. Combinatorial Peaks having the highest accuracy in distinguishing different samples were selected as potential biomarker. From the two group serum samples, a total of 133 differential features were selected. Ten features with significant intensity differences were screened. In the pair-wise comparisons, processing of MALDI-TOF spectra resulted in the identification of ten differential features between postmenopausal women with osteopenia and postmenopausal women with normal bone mass. The difference of features by Youden index showed that the highest features had a mass to charge ratio of 1699 and 3038 Da. A diagnosis model was established with these two peaks as the candidate marker, and the specificity of the model is 100 %, the sensitivity was 90 % by leave-one-out cross validation test. The two groups of specimens in SVM results on the scatter plot could be clearly distinguished. The peak with m/z 3038 in the SVM model was suggested as Secretin by TagIdent tool. To provide further validation, the secretin levels in serum were analyzed using enzyme-linked immunosorbent assays that is a competitive inhibition enzyme immunoassay technique for the in vitro quantitative measurement of secretin in human serum.

Walking performance and muscle strength in the later stage poststroke: a nonlinear relationship.

PubMed

Carvalho, Cristiane; Sunnerhagen, Katharina S; Willén, Carin

2013-05-01

To evaluate the relation between muscle strength in the lower extremities and walking performance (speed and distance) in subjects in the later stage poststroke and to compare this with normative data. A cross-sectional observational study. University hospital department. Subjects poststroke (n=41; 31 men, 10 women) with a mean age of 59±5.8 years and a time from stroke onset of 52±36 months were evaluated. An urban sample (n=144) of 40- to 79-year-olds (69 men, 75 women) formed the healthy reference group. Not applicable. Muscle strength in the lower extremities was measured with an isokinetic dynamometer and combined into a strength index. Values for the 30-meter walk test for self-selected and maximum speed and the 6-minute walk test were measured. A nonlinear regression model was used. The average strength index was 730±309 in the subjects after stroke compared with 1112±362 in the healthy group. A nonlinear relation between walking performance and muscle strength was evident. The model explained 37% of the variance in self-selected speed in the stroke group and 20% in the healthy group, and 63% and 38%, respectively, in the maximum walking speed. For the 6-minute walk test, the model explained 44% of the variance in the stroke group. Subjects in the later stage poststroke were weaker than the healthy reference group, and their weakness was associated with walking performance. At the same strength index, subjects walked at lower speeds and shorter distances after stroke, indicating that there are multiple impairments that affect walking ability. Treatments focused on increasing muscle strength thus continue to hold promise. Copyright © 2013 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Use of Longitudinal Data in Genetic Studies in the Genome-wide Association Studies Era: Summary of Group 14

PubMed Central

Kerner, Berit; North, Kari E; Fallin, M Daniele

2010-01-01

Participants analyzed actual and simulated longitudinal data from the Framingham Heart Study for various metabolic and cardiovascular traits. The genetic information incorporated into these investigations ranged from selected single-nucleotide polymorphisms to genome-wide association arrays. Genotypes were incorporated using a broad range of methodological approaches including conditional logistic regression, linear mixed models, generalized estimating equations, linear growth curve estimation, growth modeling, growth mixture modeling, population attributable risk fraction based on survival functions under the proportional hazards models, and multivariate adaptive splines for the analysis of longitudinal data. The specific scientific questions addressed by these different approaches also varied, ranging from a more precise definition of the phenotype, bias reduction in control selection, estimation of effect sizes and genotype associated risk, to direct incorporation of genetic data into longitudinal modeling approaches and the exploration of population heterogeneity with regard to longitudinal trajectories. The group reached several overall conclusions: 1) The additional information provided by longitudinal data may be useful in genetic analyses. 2) The precision of the phenotype definition as well as control selection in nested designs may be improved, especially if traits demonstrate a trend over time or have strong age-of-onset effects. 3) Analyzing genetic data stratified for high-risk subgroups defined by a unique development over time could be useful for the detection of rare mutations in common multi-factorial diseases. 4) Estimation of the population impact of genomic risk variants could be more precise. The challenges and computational complexity demanded by genome-wide single-nucleotide polymorphism data were also discussed. PMID:19924713

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2017-01-01

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

Model Informed Pediatric Development Applied to Bilastine: Ontogenic PK Model Development, Dose Selection for First Time in Children and PK Study Design.

PubMed

Vozmediano, Valvanera; Sologuren, Ander; Lukas, John C; Leal, Nerea; Rodriguez, Mónica

2017-12-01

Bilastine is an H 1 antagonist whose pharmacokinetics (PK) and pharmacodynamics (PD) have been resolved in adults with a therapeutic oral dose of 20 mg/day. Bilastine has favorable characteristics for use in pediatrics but the PK/PD and the optimal dose in children had yet to be clinically explored. The purpose is to: (1) Develop an ontogenic predictive model of bilastine PK linked to the PD in adults by integrating current knowledge; (2) Use the model to design a PK study in children; (3) Confirm the selected dose and the study design through the evaluation of model predictability in the first recruited children; (4) Consider for inclusion the group of younger children (< 6 years). A semi-mechanistic approach was applied to predict bilastine PK in children assuming the same PD as described in adults. The model was used to simulate the time evolution of plasma levels and wheal and flare effects after several doses and design an adaptive PK trial in children that was then confirmed using data from the first recruits by comparing observations with model predictions. PK/PD simulations supported the selection of 10 mg/day in 2 to <12 year olds. Results from the first interim analysis confirmed the model predictions and design hence trial continuation. The model successfully predicted bilastine PK in pediatrics and optimally assisted the selection of the dose and sampling scheme for the trial in children. The selected dose was considered suitable for younger children and the forthcoming safety study in children aged 2 to <12 years.

Effects of a Target-Task Problem-Solving Model on Senior Secondary School Students' Performance in Physics

ERIC Educational Resources Information Center

Olaniyan, A. O.; Omosewo, E. O.

2015-01-01

The study investigated the Effects of a Target-Task Problem-Solving Model on Senior Secondary School Students' Performance in Physics. The research design was a quasi-experimental, non-randomized, non-equivalent pretest, post-test using a control group. The study was conducted in two schools purposively selected and involved a total of 120 Senior…

The Trilayer Approach of Teaching Physiology, Pathophysiology, and Pharmacology Concepts in a First-Year Pharmacy Course: The TLAT Model

ERIC Educational Resources Information Center

Islam, Mohammed A.; Sabnis, Gauri; Farris, Fred

2017-01-01

This paper describes the development, implementation, and students' perceptions of a new trilayer approach of teaching (TLAT). The TLAT model involved blending lecture, in-class group activities, and out-of-class assignments on selected content areas and was implemented initially in a first-year integrated pharmacy course. Course contents were…

[COMPARISON OF FEMORAL CONDYLAR TWIST ANGLE IN THREE DIMENSIONAL RECONSTRUCTION DIGITAL MODELS OF KNEE JOINT BASED ON TWO DIMENSIONAL IMAGES OF MRI AND CT].

PubMed

Huang, Zan; Li, Yanlin; Hu, Meng; Li, Jian; You, Zhimin; Wang, Guoliang; He, Chuan

2015-02-01

To study the difference of femoral condylar twist angle (CTA) measurement in three dimensional (3-D) reconstruction digital models of human knee joint based on the two dimensional (2-D) images of MRI and CT so as to provide a reference for selecting the best method of CTA measurement in preoperative design for the femoral prosthesis rotational position. The CTA of 10 human cadaveric knee joint was measured in 3-D digital models based on MRI (group A), in 3-D digital models based on CT (group B), in the cadaveric knee joint with cartilage (group C), and in the cadaveric knee joint without cartilage (group D), respectively. The statistical analysis of the differences was made among the measurements of the CTA. The CTA values measured in 3-D digital models were (6.43 ± 0.53) degrees in group A and (3.31 ± 1.07) degrees in group B, showing significant difference (t = 10.235, P = 0.000). The CTA values measured in the cadaveric knee joint were (5.21 ± 1.28) degrees in group C and (3.33 ± 1.12) degrees in group D, showing significant difference (t = 5.770, P = 0.000). There was significant difference in the CTA values between group B and group C (t = 5.779, P = 0.000), but no significant difference was found between group A and group C (t = 3.219, P = 0.110). The CTA values measured in the 3-D digital models based on MRI are closer to the actual values measured in the knee joint with cartilage, and benefit for preoperative plan.

Paradoxical ventilator associated pneumonia incidences among selective digestive decontamination studies versus other studies of mechanically ventilated patients: benchmarking the evidence base

PubMed Central

2011-01-01

Introduction Selective digestive decontamination (SDD) appears to have a more compelling evidence base than non-antimicrobial methods for the prevention of ventilator associated pneumonia (VAP). However, the striking variability in ventilator associated pneumonia-incidence proportion (VAP-IP) among the SDD studies remains unexplained and a postulated contextual effect remains untested for. Methods Nine reviews were used to source 45 observational (benchmark) groups and 137 component (control and intervention) groups of studies of SDD and studies of three non-antimicrobial methods of VAP prevention. The logit VAP-IP data were summarized by meta-analysis using random effects methods and the associated heterogeneity (tau2) was measured. As group level predictors of logit VAP-IP, the mode of VAP diagnosis, proportion of trauma admissions, the proportion receiving prolonged ventilation and the intervention method under study were examined in meta-regression models containing the benchmark groups together with either the control (models 1 to 3) or intervention (models 4 to 6) groups of the prevention studies. Results The VAP-IP benchmark derived here is 22.1% (95% confidence interval; 95% CI; 19.2 to 25.5; tau2 0.34) whereas the mean VAP-IP of control groups from studies of SDD and of non-antimicrobial methods, is 35.7 (29.7 to 41.8; tau2 0.63) versus 20.4 (17.2 to 24.0; tau2 0.41), respectively (P < 0.001). The disparity between the benchmark groups and the control groups of the SDD studies, which was most apparent for the highest quality studies, could not be explained in the meta-regression models after adjusting for various group level factors. The mean VAP-IP (95% CI) of intervention groups is 16.0 (12.6 to 20.3; tau2 0.59) and 17.1 (14.2 to 20.3; tau2 0.35) for SDD studies versus studies of non-antimicrobial methods, respectively. Conclusions The VAP-IP among the intervention groups within the SDD evidence base is less variable and more similar to the benchmark than among the control groups. These paradoxical observations cannot readily be explained. The interpretation of the SDD evidence base cannot proceed without further consideration of this contextual effect. PMID:21214897

On 3-D inelastic analysis methods for hot section components. Volume 1: Special finite element models

NASA Technical Reports Server (NTRS)

Nakazawa, S.

1988-01-01

This annual status report presents the results of work performed during the fourth year of the 3-D Inelastic Analysis Methods for Hot Section Components program (NASA Contract NAS3-23697). The objective of the program is to produce a series of new computer codes permitting more accurate and efficient 3-D analysis of selected hot section components, i.e., combustor liners, turbine blades and turbine vanes. The computer codes embody a progression of math models and are streamlined to take advantage of geometrical features, loading conditions, and forms of material response that distinguish each group of selected components. Volume 1 of this report discusses the special finite element models developed during the fourth year of the contract.

Protein pharmacophore selection using hydration-site analysis

PubMed Central

Hu, Bingjie; Lill, Markus A.

2012-01-01

Virtual screening using pharmacophore models is an efficient method to identify potential lead compounds for target proteins. Pharmacophore models based on protein structures are advantageous because a priori knowledge of active ligands is not required and the models are not biased by the chemical space of previously identified actives. However, in order to capture most potential interactions between all potentially binding ligands and the protein, the size of the pharmacophore model, i.e. number of pharmacophore elements, is typically quite large and therefore reduces the efficiency of pharmacophore based screening. We have developed a new method to select important pharmacophore elements using hydration-site information. The basic premise is that ligand functional groups that replace water molecules in the apo protein contribute strongly to the overall binding affinity of the ligand, due to the additional free energy gained from releasing the water molecule into the bulk solvent. We computed the free energy of water released from the binding site for each hydration site using thermodynamic analysis of molecular dynamics (MD) simulations. Pharmacophores which are co-localized with hydration sites with estimated favorable contributions to the free energy of binding are selected to generate a reduced pharmacophore model. We constructed reduced pharmacophore models for three protein systems and demonstrated good enrichment quality combined with high efficiency. The reduction in pharmacophore model size reduces the required screening time by a factor of 200–500 compared to using all protein pharmacophore elements. We also describe a training process using a small set of known actives to reliably select the optimal set of criteria for pharmacophore selection for each protein system. PMID:22397751

Selection Bias and Utilization of the Dual Eligibles in Medicare and Medicaid HMOs

PubMed Central

Zhang, Hui; Kane, Robert L; Dowd, Bryan; Feldman, Roger

2008-01-01

Objective To examine the existence of selection bias in the first 3 years of the Minnesota Senior Health Options (MSHO) demonstration and to estimate the MSHO effects on medical services utilization after adjusting for selection bias. Data Sources Monthly dual eligibility data and MSHO encounter data of March 1997–December 2000 and Medicaid encounter data of January 1995–December 2000 from the Minnesota Department of Human Services; Medicare fee-for-service claims data of January 1995–December 2000 from the Centers for Medicare and Medicaid Services. Study Design Quasi-experimental design comparing utilization between MSHO and control groups; multiple econometric and statistical models were estimated with time-invariant and time-varying covariates. Principal Findings Favorable MSHO selection was found in the nursing home (NH) and community populations, but selection bias did not substantially affect the findings. Enrollment in MSHO for more than 1 year reduced inpatient hospital admissions and days, emergency room and physician visits for NH residents, and lowered physician visits for community residents. Conclusions There was favorable selection in the first 3 years of the MSHO program. Enrollment in MSHO reduced several types of utilization for the NH group and physician visits for community enrollees. PMID:18479403

Combined universal and selective prevention for adolescent alcohol use: a cluster randomized controlled trial.

PubMed

Teesson, M; Newton, N C; Slade, T; Carragher, N; Barrett, E L; Champion, K E; Kelly, E V; Nair, N K; Stapinski, L A; Conrod, P J

2017-07-01

No existing models of alcohol prevention concurrently adopt universal and selective approaches. This study aims to evaluate the first combined universal and selective approach to alcohol prevention. A total of 26 Australian schools with 2190 students (mean age: 13.3 years) were randomized to receive: universal prevention (Climate Schools); selective prevention (Preventure); combined prevention (Climate Schools and Preventure; CAP); or health education as usual (control). Primary outcomes were alcohol use, binge drinking and alcohol-related harms at 6, 12 and 24 months. Climate, Preventure and CAP students demonstrated significantly lower growth in their likelihood to drink and binge drink, relative to controls over 24 months. Preventure students displayed significantly lower growth in their likelihood to experience alcohol harms, relative to controls. While adolescents in both the CAP and Climate groups demonstrated slower growth in drinking compared with adolescents in the control group over the 2-year study period, CAP adolescents demonstrated faster growth in drinking compared with Climate adolescents. Findings support universal, selective and combined approaches to alcohol prevention. Particularly novel are the findings of no advantage of the combined approach over universal or selective prevention alone.

[How to fit and interpret multilevel models using SPSS].

PubMed

Pardo, Antonio; Ruiz, Miguel A; San Martín, Rafael

2007-05-01

Hierarchic or multilevel models are used to analyse data when cases belong to known groups and sample units are selected both from the individual level and from the group level. In this work, the multilevel models most commonly discussed in the statistic literature are described, explaining how to fit these models using the SPSS program (any version as of the 11 th ) and how to interpret the outcomes of the analysis. Five particular models are described, fitted, and interpreted: (1) one-way analysis of variance with random effects, (2) regression analysis with means-as-outcomes, (3) one-way analysis of covariance with random effects, (4) regression analysis with random coefficients, and (5) regression analysis with means- and slopes-as-outcomes. All models are explained, trying to make them understandable to researchers in health and behaviour sciences.

Frequency-dependent selection predicts patterns of radiations and biodiversity.

PubMed

Melián, Carlos J; Alonso, David; Vázquez, Diego P; Regetz, James; Allesina, Stefano

2010-08-26

Most empirical studies support a decline in speciation rates through time, although evidence for constant speciation rates also exists. Declining rates have been explained by invoking pre-existing niches, whereas constant rates have been attributed to non-adaptive processes such as sexual selection and mutation. Trends in speciation rate and the processes underlying it remain unclear, representing a critical information gap in understanding patterns of global diversity. Here we show that the temporal trend in the speciation rate can also be explained by frequency-dependent selection. We construct a frequency-dependent and DNA sequence-based model of speciation. We compare our model to empirical diversity patterns observed for cichlid fish and Darwin's finches, two classic systems for which speciation rates and richness data exist. Negative frequency-dependent selection predicts well both the declining speciation rate found in cichlid fish and explains their species richness. For groups like the Darwin's finches, in which speciation rates are constant and diversity is lower, speciation rate is better explained by a model without frequency-dependent selection. Our analysis shows that differences in diversity may be driven by incipient species abundance with frequency-dependent selection. Our results demonstrate that genetic-distance-based speciation and frequency-dependent selection are sufficient to explain the high diversity observed in natural systems and, importantly, predict decay through time in speciation rate in the absence of pre-existing niches.

Effect of Precede-Proceed Model on Preventive Behaviors for Type 2 Diabetes Mellitus in High-Risk Individuals.

PubMed

Moshki, Mahdi; Dehnoalian, Atefeh; Alami, Ali

2017-04-01

This study sought to assess the effect of precede-proceed model on preventive behaviors for type 2 diabetes mellitus (DM) in high-risk individuals. In this semi-experimental study, 164 high-risk individuals for type 2 DM were selected and were randomly divided into two groups of intervention and control ( n = 85). Educational intervention was performed as a single session face-to-face instruction for 1.5 hr for the intervention group participants. Data were collected before (baseline) and immediately and 1 month after the intervention in the two groups. The mean score of predisposing (knowledge) factors ( p = .001), reinforcing factors ( p = .001), and enabling factors ( p = .02) were significantly different at baseline and 1 month after the intervention in the intervention group compared with the control group ( p < .05). A significant improvement occurred in the nutritional habits of high-risk participants in the intervention group at 1 month after the intervention compared with controls ( p = .001). The precede-proceed model can be effective for promoting the preventive behaviors for type 2 DM in high-risk individuals.

Selectionist and Evolutionary Approaches to Brain Function: A Critical Appraisal

PubMed Central

Fernando, Chrisantha; Szathmáry, Eörs; Husbands, Phil

2012-01-01

We consider approaches to brain dynamics and function that have been claimed to be Darwinian. These include Edelman’s theory of neuronal group selection, Changeux’s theory of synaptic selection and selective stabilization of pre-representations, Seung’s Darwinian synapse, Loewenstein’s synaptic melioration, Adam’s selfish synapse, and Calvin’s replicating activity patterns. Except for the last two, the proposed mechanisms are selectionist but not truly Darwinian, because no replicators with information transfer to copies and hereditary variation can be identified in them. All of them fit, however, a generalized selectionist framework conforming to the picture of Price’s covariance formulation, which deliberately was not specific even to selection in biology, and therefore does not imply an algorithmic picture of biological evolution. Bayesian models and reinforcement learning are formally in agreement with selection dynamics. A classification of search algorithms is shown to include Darwinian replicators (evolutionary units with multiplication, heredity, and variability) as the most powerful mechanism for search in a sparsely occupied search space. Examples are given of cases where parallel competitive search with information transfer among the units is more efficient than search without information transfer between units. Finally, we review our recent attempts to construct and analyze simple models of true Darwinian evolutionary units in the brain in terms of connectivity and activity copying of neuronal groups. Although none of the proposed neuronal replicators include miraculous mechanisms, their identification remains a challenge but also a great promise. PMID:22557963

Data on Enacted Curriculum Study: Summary of Findings Experimental Design Study of Effectiveness of DEC Professional Development Model in Urban Middle Schools

ERIC Educational Resources Information Center

Blank, Rolf K.

2004-01-01

The purpose of the three-year CCSSO study was to design, implement, and test the effectiveness of the Data on Enacted Curriculum (DEC) model for improving math and science instruction. The model was tested by measuring its effects with a randomly selected sample of ?treatment? schools at the middle grades level as compared to a control group of…

Evaluation of the 29-km Eta Model. Part I: Objective Verification at Three Selected Stations

NASA Technical Reports Server (NTRS)

Manobianco, John; Nutter, Paul

1998-01-01

A subjective evaluation of the National Centers for Environmental Prediction 29-km (meso-) eta model during the 1996 warm (May-August) and cool (October-January) seasons is described. The overall evaluation assessed the utility of the model for operational weather forecasting by the U.S. Air Force 45th Weather Squadron, National Weather Service (NWS) Spaceflight Meteorology Group (SMG) and NWS Office in Melbourne, FL.

Comparing geological and statistical approaches for element selection in sediment tracing research

NASA Astrophysics Data System (ADS)

Laceby, J. Patrick; McMahon, Joe; Evrard, Olivier; Olley, Jon

2015-04-01

Elevated suspended sediment loads reduce reservoir capacity and significantly increase the cost of operating water treatment infrastructure, making the management of sediment supply to reservoirs of increasingly importance. Sediment fingerprinting techniques can be used to determine the relative contributions of different sources of sediment accumulating in reservoirs. The objective of this research is to compare geological and statistical approaches to element selection for sediment fingerprinting modelling. Time-integrated samplers (n=45) were used to obtain source samples from four major subcatchments flowing into the Baroon Pocket Dam in South East Queensland, Australia. The geochemistry of potential sources were compared to the geochemistry of sediment cores (n=12) sampled in the reservoir. The geochemical approach selected elements for modelling that provided expected, observed and statistical discrimination between sediment sources. Two statistical approaches selected elements for modelling with the Kruskal-Wallis H-test and Discriminatory Function Analysis (DFA). In particular, two different significance levels (0.05 & 0.35) for the DFA were included to investigate the importance of element selection on modelling results. A distribution model determined the relative contributions of different sources to sediment sampled in the Baroon Pocket Dam. Elemental discrimination was expected between one subcatchment (Obi Obi Creek) and the remaining subcatchments (Lexys, Falls and Bridge Creek). Six major elements were expected to provide discrimination. Of these six, only Fe2O3 and SiO2 provided expected, observed and statistical discrimination. Modelling results with this geological approach indicated 36% (+/- 9%) of sediment sampled in the reservoir cores were from mafic-derived sources and 64% (+/- 9%) were from felsic-derived sources. The geological and the first statistical approach (DFA0.05) differed by only 1% (σ 5%) for 5 out of 6 model groupings with only the Lexys Creek modelling results differing significantly (35%). The statistical model with expanded elemental selection (DFA0.35) differed from the geological model by an average of 30% for all 6 models. Elemental selection for sediment fingerprinting therefore has the potential to impact modeling results. Accordingly is important to incorporate both robust geological and statistical approaches when selecting elements for sediment fingerprinting. For the Baroon Pocket Dam, management should focus on reducing the supply of sediments derived from felsic sources in each of the subcatchments.

[Study the rudimentary immunoregulatory mechanisms of Ganoderma Spore oil on immunocompromized mice].

PubMed

Yi, Youjin; Hu, Shun; Xiong, Xingyao; Liu, Dongbo; Zhong, Yingli

2012-09-01

To study the rudimentary immunoregulatory mechanisms of Ganoderma spore oil on immunocompromized mice model. Thrity KM mice were randomly selected and assigned into three groups (ten animals per group): the model control group, Ganoderma Lucidum spores oil group and the normal control group. The model control group and Ganoderma Lucidum spores oil group were injected intraperitoneally with cyclophosphamide at 40 mg x kg(-1) d to generate a immunocompromized mice model. The normal control group were administered with 0.9% NaCl solution 0.1 ml/10 g BW as placebo. All agents were given orally once a day, given for consecutive 30 days, Ganoderma Lucidum spores oil group 150 mg/kg, the others given maize 0.1 ml/10 g BW. The serum TNF-alpha , IFN-gamma content of the mice through ELISA kit and the expression levels of IL-2, IL-10, IL-12, IL-4, IFN-gamma, TNF-alpha mRNA in mouse spleen and thymus were examined by RT-PCR to rudimentary study its immunoregulatory mechanisms. Ganoderma spore oil can significantly increased the content of TNF-alpha and IFN-gamma in the serum and the expression levels of IL-2, IL-10, IL-12, IL-4, IFN-gamma, TNF-alpha mRNA in spleen and thymus, with obvious difference from the model control (P < or = 0.05). Ganoderma spore oil can be able to improve the above cytokine ion expression to immunoregulate the immunocompromized mice.

A grouping method based on grid density and relationship for crowd evacuation simulation

NASA Astrophysics Data System (ADS)

Li, Yan; Liu, Hong; Liu, Guang-peng; Li, Liang; Moore, Philip; Hu, Bin

2017-05-01

Psychological factors affect the movement of people in the competitive or panic mode of evacuation, in which the density of pedestrians is relatively large and the distance among them is small. In this paper, a crowd is divided into groups according to their social relations to simulate the actual movement of crowd evacuation more realistically and increase the attractiveness of the group based on social force model. The force of group attraction is the synthesis of two forces; one is the attraction of the individuals generated by their social relations to gather, and the other is that of the group leader to the individuals within the group to ensure that the individuals follow the leader. The synthetic force determines the trajectory of individuals. The evacuation process is demonstrated using the improved social force model. In the improved social force model, the individuals with close social relations gradually present a closer and coordinated action while following the leader. In this paper, a grouping algorithm is proposed based on grid density and relationship via computer simulation to illustrate the features of the improved social force model. The definition of the parameters involved in the algorithm is given, and the effect of relational value on the grouping is tested. Reasonable numbers of grids and weights are selected. The effectiveness of the algorithm is shown through simulation experiments. A simulation platform is also established using the proposed grouping algorithm and the improved social force model for crowd evacuation simulation.

Is cooperation viable in mobile organisms? Simple Walk Away rule favors the evolution of cooperation in groups

PubMed Central

Aktipis, C. Athena

2011-01-01

The evolution of cooperation through partner choice mechanisms is often thought to involve relatively complex cognitive abilities. Using agent-based simulations I model a simple partner choice rule, the ‘Walk Away’ rule, where individuals stay in groups that provide higher returns (by virtue of having more cooperators), and ‘Walk Away’ from groups providing low returns. Implementing this conditional movement rule in a public goods game leads to a number of interesting findings: 1) cooperators have a selective advantage when thresholds are high, corresponding to low tolerance for defectors, 2) high thresholds lead to high initial rates of movement and low final rates of movement (after selection), and 3) as cooperation is selected, the population undergoes a spatial transition from high migration (and a many small and ephemeral groups) to low migration (and large and stable groups). These results suggest that the very simple ‘Walk Away’ rule of leaving uncooperative groups can favor the evolution of cooperation, and that cooperation can evolve in populations in which individuals are able to move in response to local social conditions. A diverse array of organisms are able to leave degraded physical or social environments. The ubiquitous nature of conditional movement suggests that ‘Walk Away’ dynamics may play an important role in the evolution of social behavior in both cognitively complex and cognitively simple organisms. PMID:21666771

The Effect of Orem's Self-Care Model on Quality of Life in Patients with Migraine: a Randomized Clinical Trial.

PubMed

Mahmoudzadeh Zarandi, Fatemeh; Raiesifar, Afsaneh; Ebadi, Abbas

2016-03-01

Many aspects of the lives of migraineurs are commonly affected by the condition, including occupational affairs, social and family life, responsibilities and ultimately the quality of life. This study was designed to determine the effect of orem's self-care nursing model on quality of life in patients with a migraine. This study was carried out in Tehran, Iran. According to the pre-post design of the randomized clinical trial, 88 patients were selected. After obtaining approval from the ethics committee of the Baqiyatallah Medical Sciences University's Research Deputy; Patients who signed the informed consent aged 20-55 years and without any more disease or disability affecting the quality of life were selected and randomly assigned to a group. Data collection tools were a demographic questionnaire, general health survey short form (SF36), and Orem cognition form and self-care checklist. Self-care model were held as four 30-45 minutes training sessions based on self-care deficit needs for the experimental group. The quality of life scores was measured in two stages, before and three months after intervention then were compared in both groups. Data were analyzed with statistical software SPSS and use of descriptive analysis tests, Chi-square, Mann-Whitney u and Wilcoxon. The final analysis was performed on 43 experimental and 40 controls. No significant difference was detected in the two groups in terms of demographic variables (P>0.05). All dimensions of quality of life including physical functioning, physical role limitation, body pain, general health, vitality, social functioning and emotional role limitation and mental health in the experimental group showed a significant increase after intervention compared to the control group (P<0.05). It was concluded that performing Orem's self-care nursing model improves function and overall quality of life and reduces the high cost of a migraine and migraine-related disability to individuals and society.

[Remuneration distribution - should morbidity-dependent overall remuneration also be distributed after adjustments for morbidity?].

PubMed

Walendzik, A; Trottmann, M; Leonhardt, R; Wasem, J

2013-04-01

In the 2009 reform of the German collective remuneration system for outpatient medical care, on the level of overall remuneration, the morbidity risk was transferred to the health funds fulfilling a long-term demand of physicians. Nevertheless not transferring morbidity adjustment to the levels of physician groups and singular practices can lead to budgets not related to patient needs and to incentives for risk selection for individual doctors. The systematics of the distribution of overall remuneration in the German remuneration system for outpatient care are analysed focusing on the aspect of morbidity adjustment. Using diagnostic and pharmaceutical information of about half a million insured subjects, a risk adjustment model able to predict individual expenditures for outpatient care for different provider groups is presented. This model enables to additively split the individual care burden into several parts attributed to different physician groups. Conditions for the use of the model in the distribution of overall remuneration between physician groups are developed. A simulation of the use of diagnoses-based risk adjustment in standard service volumes then highlights the conditions for a successfull installation of standard service volumes representing a higher degree of risk adjustment. The presented estimation model is generally applicable for the distribution of overall remuneration to different physician groups. The simulation of standard service volumes using diagnosis-based risk adjustment does not provide a more accurate prediction of the expenditures on the level of physician practices than the age-related calculation currently used in the German remuneration system for outpatient medical care. Using elements of morbidity-based risk adjustment the current German collective system for outpatient medical care could be transformed towards a higher degree of distributional justice concerning medical care for patients and more appropriate incentives avoiding risk selection. Limitations of the applicability of risk-adjustment can be especially pointed out when a high share of lump-sum-payments is used for the remuneration of some physician groups. © Georg Thieme Verlag KG Stuttgart · New York.

The evolution of nucleotides

NASA Technical Reports Server (NTRS)

Usher, D. A.; Needels, M. C.

1986-01-01

Examples of chiral selection in nonenzymatic aminoacylation of internal 2-prime hydroxyl groups of oligo- and polynucleotides are discussed as an evidence for the early evolution of bionucleotides. Some factors that could influence the degree of this chiral selection and its direction are discussed. These include the structure of the aminoacyl component, the structure of the nucleoside component, and the reaction conditions. Investigation of the mechanism of this reaction was aided by the use of 3-prime inosine methyl phosphate (as a simplified model for a dinucleoside monophosphate) and proton NMR spectroscopy of t-butoxycarbonyl-alanyl esters of nucleosides as models for the transition state of the aminoacylation reaction itself.

3-D inelastic analysis methods for hot section components. Volume 2: Advanced special functions models

NASA Technical Reports Server (NTRS)

Wilson, R. B.; Banerjee, P. K.

1987-01-01

This Annual Status Report presents the results of work performed during the third year of the 3-D Inelastic Analysis Methods for Hot Sections Components program (NASA Contract NAS3-23697). The objective of the program is to produce a series of computer codes that permit more accurate and efficient three-dimensional analyses of selected hot section components, i.e., combustor liners, turbine blades, and turbine vanes. The computer codes embody a progression of mathematical models and are streamlined to take advantage of geometrical features, loading conditions, and forms of material response that distinguish each group of selected components.

Micro turbine engines for drones propulsion

NASA Astrophysics Data System (ADS)

Dutczak, J.

2016-09-01

Development of micro turbine engines began from attempts of application of that propulsion source by group of enthusiasts of aviation model making. Nowadays, the domain of micro turbojet engines is treated on a par with “full size” aviation constructions. The dynamic development of these engines is caused not only by aviation modellers, but also by use of micro turbojet engines by army to propulsion of contemporary drones, i.e. Unmanned Aerial Vehicles (UAV) or Unmanned Aerial Systems (UAS). On the base of selected examples the state of art in the mentioned group of engines has been presented in the article.

A recurrent neural model for proto-object based contour integration and figure-ground segregation.

PubMed

Hu, Brian; Niebur, Ernst

2017-12-01

Visual processing of objects makes use of both feedforward and feedback streams of information. However, the nature of feedback signals is largely unknown, as is the identity of the neuronal populations in lower visual areas that receive them. Here, we develop a recurrent neural model to address these questions in the context of contour integration and figure-ground segregation. A key feature of our model is the use of grouping neurons whose activity represents tentative objects ("proto-objects") based on the integration of local feature information. Grouping neurons receive input from an organized set of local feature neurons, and project modulatory feedback to those same neurons. Additionally, inhibition at both the local feature level and the object representation level biases the interpretation of the visual scene in agreement with principles from Gestalt psychology. Our model explains several sets of neurophysiological results (Zhou et al. Journal of Neuroscience, 20(17), 6594-6611 2000; Qiu et al. Nature Neuroscience, 10(11), 1492-1499 2007; Chen et al. Neuron, 82(3), 682-694 2014), and makes testable predictions about the influence of neuronal feedback and attentional selection on neural responses across different visual areas. Our model also provides a framework for understanding how object-based attention is able to select both objects and the features associated with them.

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

PubMed

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

2010-06-01

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

Interplanetary type II radio bursts and their association with CMEs and flares

NASA Astrophysics Data System (ADS)

Shanmugaraju, A.; Suresh, K.; Vasanth, V.; Selvarani, G.; Umapathy, S.

2018-06-01

We study the characteristics of the CMEs and their association with the end-frequency of interplanetary (IP)-type-II bursts by analyzing a set of 138 events (IP-type-II bursts-flares-CMEs) observed during the period 1997-2012. The present analysis consider only the type II bursts having starting frequency < 14 MHz to avoid the extension of coronal type IIs. The selected events are classified into three groups depending on the end-frequency of type IIs as follows, (A) Higher, (B) Intermediate and (C) Lower end-frequency. We compare characteristics of CMEs, flares and type II burst for the three selected groups of events and report some of the important differences. The observed height of CMEs is compared with the height of IP type IIs estimated using the electron density models. By applying a density multiplier (m) to this model, the density has been constrained both in the upper corona and in the interplanetary medium, respectively as m= 1 to 10 and m = 1 to 3. This study indicates that there is a correlation between the observed CME height and estimated type II height for groups B and C events whereas this correlation is absent in group A. In all the groups (A, B & C), the different heights of CMEs and type II reveal that the type IIs are not only observed at the nose but also at the flank of the CMEs.

Pharmacodynamic and pharmacokinetic studies and prostatic tissue distribution of fosfomycin tromethamine in bacterial prostatitis or normal rats.

PubMed

Fan, L; Shang, X; Zhu, J; Ma, B; Zhang, Q

2018-05-02

In this study, we assessed the therapeutic effects of fosfomycin tromethamine (FT) in a bacterial prostatitis (BP) rat model. The BP model was induced by Escherichia coli and was demonstrated after 7 days microbiologically and histologically. Then, 25 BP rats selected were randomly divided into five treatment groups: model group, positive group, FT-3 day group, FT-7 day group and FT-14 day group. Ventral lobes of prostate from all animals were removed, and the serum samples were collected at the end of the experiments. Microbiological cultures and histological findings of the prostate samples demonstrated reduced bacterial growth and improved inflammatory responses in FT-treatment groups compared with the model group, indicating that FT against prostatic infection induced by E. coli showed good antibacterial effects. Moreover, plasma pharmacokinetics and prostatic distribution of fosfomycin were studied and compared in BP and normal rats. The concentrations of fosfomycin in samples were analysed by liquid chromatography-tandem mass spectrometry. There were no differences in plasma pharmacokinetic parameters between two groups. But significantly higher penetration of fosfomycin into prostatic tissues was found in BP rats. We therefore suggested that FT had a good therapeutic effect on BP and it might be used in curing masculine reproductive system diseases. © 2018 Blackwell Verlag GmbH.

First-Principles Integrated Adsorption Modeling for Selective Capture of Uranium from Seawater by Polyamidoxime Sorbent Materials

DOE PAGES

Ladshaw, Austin P.; Ivanov, Alexander S.; Das, Sadananda; ...

2018-03-27

Nuclear power is a relatively carbon-free energy source that has the capacity to be utilized today in an effort to stem the tides of global warming. The growing demand for nuclear energy, however, could put significant strain on our uranium ore resources, and the mining activities utilized to extract that ore can leave behind long-term environmental damage. A potential solution to enhance the supply of uranium fuel is to recover uranium from seawater using amidoximated adsorbent fibers. This technology has been studied for decades but is currently plagued by the material’s relatively poor selectivity of uranium over its main competitormore » vanadium. In this work, we investigate the binding schemes between uranium, vanadium, and the amidoxime functional groups on the adsorbent surface. Using quantum chemical methods, binding strengths are approximated for a set of complexation reactions between uranium and vanadium with amidoxime functionalities. Those approximations are then coupled with a comprehensive aqueous adsorption model developed in this work to simulate the adsorption of uranium and vanadium under laboratory conditions. Experimental adsorption studies with uranium and vanadium over a wide pH range are performed, and the data collected are compared against simulation results to validate the model. It was found that coupling ab initio calculations with process level adsorption modeling provides accurate predictions of the adsorption capacity and selectivity of the sorbent materials. Furthermore, this work demonstrates that this multiscale modeling paradigm could be utilized to aid in the selection of superior ligands or ligand compositions for the selective capture of metal ions. Furthermore, this first-principles integrated modeling approach opens the door to the in silico design of next-generation adsorbents with potentially superior efficiency and selectivity for uranium over vanadium in seawater.« less

First-Principles Integrated Adsorption Modeling for Selective Capture of Uranium from Seawater by Polyamidoxime Sorbent Materials

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

Ladshaw, Austin P.; Ivanov, Alexander S.; Das, Sadananda

Nuclear power is a relatively carbon-free energy source that has the capacity to be utilized today in an effort to stem the tides of global warming. The growing demand for nuclear energy, however, could put significant strain on our uranium ore resources, and the mining activities utilized to extract that ore can leave behind long-term environmental damage. A potential solution to enhance the supply of uranium fuel is to recover uranium from seawater using amidoximated adsorbent fibers. This technology has been studied for decades but is currently plagued by the material’s relatively poor selectivity of uranium over its main competitormore » vanadium. In this work, we investigate the binding schemes between uranium, vanadium, and the amidoxime functional groups on the adsorbent surface. Using quantum chemical methods, binding strengths are approximated for a set of complexation reactions between uranium and vanadium with amidoxime functionalities. Those approximations are then coupled with a comprehensive aqueous adsorption model developed in this work to simulate the adsorption of uranium and vanadium under laboratory conditions. Experimental adsorption studies with uranium and vanadium over a wide pH range are performed, and the data collected are compared against simulation results to validate the model. It was found that coupling ab initio calculations with process level adsorption modeling provides accurate predictions of the adsorption capacity and selectivity of the sorbent materials. Furthermore, this work demonstrates that this multiscale modeling paradigm could be utilized to aid in the selection of superior ligands or ligand compositions for the selective capture of metal ions. Furthermore, this first-principles integrated modeling approach opens the door to the in silico design of next-generation adsorbents with potentially superior efficiency and selectivity for uranium over vanadium in seawater.« less

First-Principles Integrated Adsorption Modeling for Selective Capture of Uranium from Seawater by Polyamidoxime Sorbent Materials.

PubMed

Ladshaw, Austin P; Ivanov, Alexander S; Das, Sadananda; Bryantsev, Vyacheslav S; Tsouris, Costas; Yiacoumi, Sotira

2018-04-18

Nuclear power is a relatively carbon-free energy source that has the capacity to be utilized today in an effort to stem the tides of global warming. The growing demand for nuclear energy, however, could put significant strain on our uranium ore resources, and the mining activities utilized to extract that ore can leave behind long-term environmental damage. A potential solution to enhance the supply of uranium fuel is to recover uranium from seawater using amidoximated adsorbent fibers. This technology has been studied for decades but is currently plagued by the material's relatively poor selectivity of uranium over its main competitor vanadium. In this work, we investigate the binding schemes between uranium, vanadium, and the amidoxime functional groups on the adsorbent surface. Using quantum chemical methods, binding strengths are approximated for a set of complexation reactions between uranium and vanadium with amidoxime functionalities. Those approximations are then coupled with a comprehensive aqueous adsorption model developed in this work to simulate the adsorption of uranium and vanadium under laboratory conditions. Experimental adsorption studies with uranium and vanadium over a wide pH range are performed, and the data collected are compared against simulation results to validate the model. It was found that coupling ab initio calculations with process level adsorption modeling provides accurate predictions of the adsorption capacity and selectivity of the sorbent materials. Furthermore, this work demonstrates that this multiscale modeling paradigm could be utilized to aid in the selection of superior ligands or ligand compositions for the selective capture of metal ions. Therefore, this first-principles integrated modeling approach opens the door to the in silico design of next-generation adsorbents with potentially superior efficiency and selectivity for uranium over vanadium in seawater.

What is the difference between comprehensive and selective primary health care? Evidence from a five-year longitudinal realist case study in South Australia.

PubMed

Baum, Fran; Freeman, Toby; Lawless, Angela; Labonte, Ronald; Sanders, David

2017-04-28

Since the WHO's Alma Ata Declaration on Primary Health Care (PHC) there has been debate about the advisability of adopting comprehensive or selective PHC. Proponents of the latter argue that a more selective approach will enable interim gains while proponents of a comprehensive approach argue that it is needed to address the underlying causes of ill health and improve health outcomes sustainably. This research is based on four case studies of government-funded and run PHC services in Adelaide, South Australia. Program logic models were constructed from interviews and workshops. The initial model represented relatively comprehensive service provision in 2010. Subsequent interviews in 2013 permitted the construction of a selective PHC program logic model following a series of restructuring service changes. Comparison of the PHC service program logic models before and after restructuring illustrates the changes to the operating context, underlying mechanisms, service qualities, activities, activity outcomes and anticipated community health outcomes. The PHC services moved from focusing on a range of community, group and individual clinical activities to a focus on the management of people with chronic disease. Under the more comprehensive model, activities were along a continuum of promotive, preventive, rehabilitative and curative. Under the selective model, the focus moved to rehabilitative and curative with very little other activities. The study demonstrates the difference between selective and comprehensive approaches to PHC in a rich country setting and is useful in informing debates on PHC especially in the context of the Sustainable Development Goals. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

A new optical intra-tissue fiber irradiation ALA-PDT in the treatment of acne vulgaris in rabbit model: improved safety and tolerability.

PubMed

Wang, Qian; Jiang, Can; Liu, Wei; Chen, Jin; Lin, Xinyu; Huang, Xiangning; Duan, Xiling

2017-01-01

Photodynamic therapy with topical aminolevulinic acid (ALA-PDT) has been suggested to be effective in treatment of acne vulgaris. However, adverse events occur during and after treatment. To compare the efficacy and tolerability of optical intra-tissue fiber irradiation (OFI) ALA-PDT versus traditional ALA-PDT in treatment of acne vulgaris in rabbit models. Twenty-five rabbits of clean grade were used. Twenty rabbits were randomly selected to establish acne model and the other five were used as control. Rabbits in model group (40 ears) were further divided into four groups (10 ears/group): I, OFI-ALA-PDT with the head of optical fiber inserted into the target lesion (intra-tissue); II, traditional ALA-PDT group; III, OFI group; IV, blank control group without any treatment. Uncomfortable symptoms, adverse events, and effectiveness rates were recorded on post-treatment day 14, 30, and 45. On post-treatment day 14, the effectiveness rate in OFI-ALA-PDT group was obviously higher than that of the other three groups (P<0.05). However, no improved effects were observed in OFI-ALA-PDT group on day 30 and 45. During the period of treatment, the frequencies of uncomfortable symptoms in ALA-PDT group were obviously higher than those in the other three groups (P<0.05). The adverse event rate in OFI-ALA-PDT group was obviously lower than that of the ALA-PDT group (P<0.05). The unblindness of the study and temporary animal models of acne induced may hamper the assessment and monitoring of the results, and future studies are still needed to clarify it further. The OFI-ALA-PDT group (intra-tissue irradiation) showed no improved efficacy on treating rabbit ear acne but had higher safety and better tolerability.

Delay selection by spike-timing-dependent plasticity in recurrent networks of spiking neurons receiving oscillatory inputs.

PubMed

Kerr, Robert R; Burkitt, Anthony N; Thomas, Doreen A; Gilson, Matthieu; Grayden, David B

2013-01-01

Learning rules, such as spike-timing-dependent plasticity (STDP), change the structure of networks of neurons based on the firing activity. A network level understanding of these mechanisms can help infer how the brain learns patterns and processes information. Previous studies have shown that STDP selectively potentiates feed-forward connections that have specific axonal delays, and that this underlies behavioral functions such as sound localization in the auditory brainstem of the barn owl. In this study, we investigate how STDP leads to the selective potentiation of recurrent connections with different axonal and dendritic delays during oscillatory activity. We develop analytical models of learning with additive STDP in recurrent networks driven by oscillatory inputs, and support the results using simulations with leaky integrate-and-fire neurons. Our results show selective potentiation of connections with specific axonal delays, which depended on the input frequency. In addition, we demonstrate how this can lead to a network becoming selective in the amplitude of its oscillatory response to this frequency. We extend this model of axonal delay selection within a single recurrent network in two ways. First, we show the selective potentiation of connections with a range of both axonal and dendritic delays. Second, we show axonal delay selection between multiple groups receiving out-of-phase, oscillatory inputs. We discuss the application of these models to the formation and activation of neuronal ensembles or cell assemblies in the cortex, and also to missing fundamental pitch perception in the auditory brainstem.

Delay Selection by Spike-Timing-Dependent Plasticity in Recurrent Networks of Spiking Neurons Receiving Oscillatory Inputs

PubMed Central

Kerr, Robert R.; Burkitt, Anthony N.; Thomas, Doreen A.; Gilson, Matthieu; Grayden, David B.

2013-01-01

Learning rules, such as spike-timing-dependent plasticity (STDP), change the structure of networks of neurons based on the firing activity. A network level understanding of these mechanisms can help infer how the brain learns patterns and processes information. Previous studies have shown that STDP selectively potentiates feed-forward connections that have specific axonal delays, and that this underlies behavioral functions such as sound localization in the auditory brainstem of the barn owl. In this study, we investigate how STDP leads to the selective potentiation of recurrent connections with different axonal and dendritic delays during oscillatory activity. We develop analytical models of learning with additive STDP in recurrent networks driven by oscillatory inputs, and support the results using simulations with leaky integrate-and-fire neurons. Our results show selective potentiation of connections with specific axonal delays, which depended on the input frequency. In addition, we demonstrate how this can lead to a network becoming selective in the amplitude of its oscillatory response to this frequency. We extend this model of axonal delay selection within a single recurrent network in two ways. First, we show the selective potentiation of connections with a range of both axonal and dendritic delays. Second, we show axonal delay selection between multiple groups receiving out-of-phase, oscillatory inputs. We discuss the application of these models to the formation and activation of neuronal ensembles or cell assemblies in the cortex, and also to missing fundamental pitch perception in the auditory brainstem. PMID:23408878

DFT-based ranking of zinc-binding groups in histone deacetylase inhibitors.

PubMed

Vanommeslaeghe, K; Loverix, S; Geerlings, P; Tourwé, D

2005-11-01

Histone deacetylases (HDACs) have recently attracted considerable interest as targets in the treatment of cell proliferative diseases such as cancer. In the present work, a general framework is proposed for chemical groups that bind into the HDAC catalytic core. Based on this framework, a series of groups was selected for further investigation. A method was developed to rank the HDAC inhibitory potential of these moieties at the B3LYP/6-31G* level, making use of extra diffuse functions and of the PCM solvation model where appropriate. The resulting binding geometries indicate that very stringent constraints should be satisfied in order to have bidental zinc chelation, and even more so to have a strong binding affinity, which makes it difficult to predict the binding mode and affinity of such zinc-binding groups. The chemical hardness and the pK(a) were identified as important criteria for the binding affinity. Also, the hydrophilicity may have a direct influence on the binding affinity. The calculated binding energies were qualitatively validated with experimental results from the literature, and were shown to be meaningful for the purpose of ranking. Additionally, the insights gained from the present work may be useful for increasing the accuracy of QSAR models by providing a rational basis for selecting descriptors.

Protein attributes contribute to halo-stability, bioinformatics approach

PubMed Central

2011-01-01

Halophile proteins can tolerate high salt concentrations. Understanding halophilicity features is the first step toward engineering halostable crops. To this end, we examined protein features contributing to the halo-toleration of halophilic organisms. We compared more than 850 features for halophilic and non-halophilic proteins with various screening, clustering, decision tree, and generalized rule induction models to search for patterns that code for halo-toleration. Up to 251 protein attributes selected by various attribute weighting algorithms as important features contribute to halo-stability; from them 14 attributes selected by 90% of models and the count of hydrogen gained the highest value (1.0) in 70% of attribute weighting models, showing the importance of this attribute in feature selection modeling. The other attributes mostly were the frequencies of di-peptides. No changes were found in the numbers of groups when K-Means and TwoStep clustering modeling were performed on datasets with or without feature selection filtering. Although the depths of induced trees were not high, the accuracies of trees were higher than 94% and the frequency of hydrophobic residues pointed as the most important feature to build trees. The performance evaluation of decision tree models had the same values and the best correctness percentage recorded with the Exhaustive CHAID and CHAID models. We did not find any significant difference in the percent of correctness, performance evaluation, and mean correctness of various decision tree models with or without feature selection. For the first time, we analyzed the performance of different screening, clustering, and decision tree algorithms for discriminating halophilic and non-halophilic proteins and the results showed that amino acid composition can be used to discriminate between halo-tolerant and halo-sensitive proteins. PMID:21592393

On 3-D inelastic analysis methods for hot section components. Volume 1: Special finite element models

NASA Technical Reports Server (NTRS)

Nakazawa, S.

1987-01-01

This Annual Status Report presents the results of work performed during the third year of the 3-D Inelastic Analysis Methods for Hot Section Components program (NASA Contract NAS3-23697). The objective of the program is to produce a series of new computer codes that permit more accurate and efficient three-dimensional analysis of selected hot section components, i.e., combustor liners, turbine blades, and turbine vanes. The computer codes embody a progression of mathematical models and are streamlined to take advantage of geometrical features, loading conditions, and forms of material response that distinguish each group of selected components. This report is presented in two volumes. Volume 1 describes effort performed under Task 4B, Special Finite Element Special Function Models, while Volume 2 concentrates on Task 4C, Advanced Special Functions Models.

Parallel medicinal chemistry approaches to selective HDAC1/HDAC2 inhibitor (SHI-1:2) optimization.

PubMed

Kattar, Solomon D; Surdi, Laura M; Zabierek, Anna; Methot, Joey L; Middleton, Richard E; Hughes, Bethany; Szewczak, Alexander A; Dahlberg, William K; Kral, Astrid M; Ozerova, Nicole; Fleming, Judith C; Wang, Hongmei; Secrist, Paul; Harsch, Andreas; Hamill, Julie E; Cruz, Jonathan C; Kenific, Candia M; Chenard, Melissa; Miller, Thomas A; Berk, Scott C; Tempest, Paul

2009-02-15

The successful application of both solid and solution phase library synthesis, combined with tight integration into the medicinal chemistry effort, resulted in the efficient optimization of a novel structural series of selective HDAC1/HDAC2 inhibitors by the MRL-Boston Parallel Medicinal Chemistry group. An initial lead from a small parallel library was found to be potent and selective in biochemical assays. Advanced compounds were the culmination of iterative library design and possess excellent biochemical and cellular potency, as well as acceptable PK and efficacy in animal models.

Methods of preventing bacterial sepsis and wound complications after liver transplantation.

PubMed

Gurusamy, Kurinchi Selvan; Nagendran, Myura; Davidson, Brian R

2014-03-05

Bacterial sepsis and wound complications after liver transplantation increase mortality, morbidity, or hospital stay and are likely to increase overall transplant costs. All liver transplantation patients receive antibiotic prophylaxis. This is an update of our 2008 Cochrane systematic review on the same topic in which we identified seven randomised clinical trials. To assess the benefits and harms of different methods aimed at preventing bacterial sepsis and wound complications in people undergoing liver transplantation. We searched the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, EMBASE, and Science Citation Index Expanded to February 2013. We included only randomised clinical trials irrespective of language or publication status. We excluded quasi-randomised and other observational studies for assessment of benefits, but not for harms. Two review authors collected the data independently. We calculated the risk ratio (RR) or mean difference (MD) with 95% confidence intervals (CI) using fixed-effect and the random-effects models based on available-case analysis. We identified only seven trials for inclusion, including 614 participants. Only one trial was of low risk of bias risk. Overall, the quality of evidence was very low. There were five comparisons in the seven trials: selective bowel decontamination versus inactive control; selective bowel decontamination versus prebiotics with probiotics; selective bowel decontamination versus prebiotics; prebiotics with probiotics versus prebiotics; and granulocyte-colony stimulating factor (G-CSF) versus control. Four trials compared selective bowel decontamination versus placebo or no treatment. In one trial, participants were randomised to selective bowel decontamination, active lactobacillus with fibres (probiotic with prebiotic), or to inactivated lactobacillus with fibres (prebiotic). In one trial, active lactobacillus with fibres (probiotic with prebiotic) was compared with inactive lactobacillus with fibres (prebiotic). In the remaining trial, different doses of G-CSF and placebo were compared. There was no trial comparing different antibiotic prophylactic regimens in people undergoing liver transplantation. Most trials included adults undergoing elective liver transplantation. There was no significant difference in proportion of people who died or required retransplantation between the intervention and control groups in any of the five comparison groups. MORTALITY There were no differences between 190 participants (three trials); 5/87 (adjusted proportion: 6.2%) in selective bowel decontamination group versus 7/103 (6.8%) in inactive control group; RR 0.91 (95% CI 0.31 to 2.72); 63 participants (one trial); 0/32 (0%) in selective bowel decontamination group versus 0/31 (0%) in prebiotics with probiotics group; RR - not estimable; 64 participants (one trial); 0/32 (0%) in selective bowel decontamination group versus 0/32 (0%) in prebiotics group; RR - not estimable; 129 participants (two trials); 0/64 (0%) in prebiotics with probiotics group versus 0/65 (0%) in prebiotics group; RR - not estimable; and 194 participants (one trial); 22/124 (17.7%) in G-CSF group versus 10/70 (14.3%) in placebo group; RR 1.24 (95% 0.62 to 2.47). RETRANSPLANTATION There were no differences between 132 participants (two trials); 4/58 (adjusted proportion: 6.9%) in selective bowel decontamination group versus 6/74 (8.1%) in inactive control group; RR 0.85 (95% CI 0.26 to 2.85); 63 participants (one trial); 1/32 (3.1%) in selective bowel decontamination group versus 0/31 (0%) in prebiotics with probiotics group; RR 2.91 (0.12 to 68.81); 64 participants (one trial); 1/32 (3.1%) in selective bowel decontamination group versus 0/32 (0%) in prebiotics group; RR 3.00 (95% CI 0.13 to 71.00); 129 participants (two trials); 0/64 (0%) in prebiotics with probiotics group versus 1/65 (1.5%) in prebiotics group; RR 0.33 (95% CI 0.01 to 7.9); and 194 participants (one trial); 10/124 (7.1%) in G-CSF group versus 5/70 (7.1%) in placebo group; RR 1.13 (95% CI 0.4 to 3.17).There was no significant difference in the graft rejections, intensive therapy unit stay, or hospital stay between the intervention and control groups in any of the comparisons. Overall, 193/611 participants (31.6%) developed infective complications. The proportion of people who developed infective complications and the number of infective complication episodes were significantly higher in the selective bowel decontamination group than in the prebiotics with probiotics group (1 study; 63 participants; 15/32 (46.9%) in selective bowel decontamination group versus 4/31 (12.9%) in prebiotics with probiotics group; RR 3.63; 95% CI 1.36 to 9.74 and 23/32 participants (0.72 infective complications per participant) in selective bowel decontamination group versus 4/31 participants (0.13 infective complications per participant) in prebiotics with probiotics group; rate ratio 5.58; 95% CI 1.94 to 16.09). There was no significant difference between the proportion of participants who developed infection and the number of infection episodes between the intervention group and control group in any of the other comparisons.No trials reported quality of life and overall serious adverse events. Currently, there is no clear evidence for any intervention offering significant benefits in the reduction of bacterial infections and wound complications in liver transplantation. Selective bowel decontamination may even increase the rate of infections compared with prebiotics with probiotics. The confidence intervals were wide and further randomised clinical trials of low risk of bias are necessary.

A Mathematical Model to Predict Endothelial Cell Density Following Penetrating Keratoplasty With Selective Dropout From Graft Failure

PubMed Central

Riddlesworth, Tonya D.; Kollman, Craig; Lass, Jonathan H.; Patel, Sanjay V.; Stulting, R. Doyle; Benetz, Beth Ann; Gal, Robin L.; Beck, Roy W.

2014-01-01

Purpose. We constructed several mathematical models that predict endothelial cell density (ECD) for patients after penetrating keratoplasty (PK) for a moderate-risk condition (principally Fuchs' dystrophy or pseudophakic/aphakic corneal edema). Methods. In a subset (n = 591) of Cornea Donor Study participants, postoperative ECD was determined by a central reading center. Various statistical models were considered to estimate the ECD trend longitudinally over 10 years of follow-up. A biexponential model with and without a logarithm transformation was fit using the Gauss-Newton nonlinear least squares algorithm. To account for correlated data, a log-polynomial model was fit using the restricted maximum likelihood method. A sensitivity analysis for the potential bias due to selective dropout was performed using Bayesian analysis techniques. Results. The three models using a logarithm transformation yield similar trends, whereas the model without the transform predicts higher ECD values. The adjustment for selective dropout turns out to be negligible. However, this is possibly due to the relatively low rate of graft failure in this cohort (19% at 10 years). Fuchs' dystrophy and pseudophakic/aphakic corneal edema (PACE) patients had similar ECD decay curves, with the PACE group having slightly higher cell densities by 10 years. Conclusions. Endothelial cell loss after PK can be modeled via a log-polynomial model, which accounts for the correlated data from repeated measures on the same subject. This model is not significantly affected by the selective dropout due to graft failure. Our findings warrant further study on how this may extend to ECD following endothelial keratoplasty. PMID:25425307

Automatic migraine classification via feature selection committee and machine learning techniques over imaging and questionnaire data.

PubMed

Garcia-Chimeno, Yolanda; Garcia-Zapirain, Begonya; Gomez-Beldarrain, Marian; Fernandez-Ruanova, Begonya; Garcia-Monco, Juan Carlos

2017-04-13

Feature selection methods are commonly used to identify subsets of relevant features to facilitate the construction of models for classification, yet little is known about how feature selection methods perform in diffusion tensor images (DTIs). In this study, feature selection and machine learning classification methods were tested for the purpose of automating diagnosis of migraines using both DTIs and questionnaire answers related to emotion and cognition - factors that influence of pain perceptions. We select 52 adult subjects for the study divided into three groups: control group (15), subjects with sporadic migraine (19) and subjects with chronic migraine and medication overuse (18). These subjects underwent magnetic resonance with diffusion tensor to see white matter pathway integrity of the regions of interest involved in pain and emotion. The tests also gather data about pathology. The DTI images and test results were then introduced into feature selection algorithms (Gradient Tree Boosting, L1-based, Random Forest and Univariate) to reduce features of the first dataset and classification algorithms (SVM (Support Vector Machine), Boosting (Adaboost) and Naive Bayes) to perform a classification of migraine group. Moreover we implement a committee method to improve the classification accuracy based on feature selection algorithms. When classifying the migraine group, the greatest improvements in accuracy were made using the proposed committee-based feature selection method. Using this approach, the accuracy of classification into three types improved from 67 to 93% when using the Naive Bayes classifier, from 90 to 95% with the support vector machine classifier, 93 to 94% in boosting. The features that were determined to be most useful for classification included are related with the pain, analgesics and left uncinate brain (connected with the pain and emotions). The proposed feature selection committee method improved the performance of migraine diagnosis classifiers compared to individual feature selection methods, producing a robust system that achieved over 90% accuracy in all classifiers. The results suggest that the proposed methods can be used to support specialists in the classification of migraines in patients undergoing magnetic resonance imaging.

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

King, W.A.; Kubas, G.J.

The present invention provides: a composition of the formula M{sup +x}(Ga(Y){sub 4}{sup {minus}}){sub x} where M is a metal selected from the group consisting of lithium, sodium, potassium, cesium, calcium, strontium, thallium, and silver, x is an integer selected from the group consisting of 1 or 2, each Y is a ligand selected from the group consisting of aryl, alkyl, hydride and halide with the proviso that at least one Y is a ligand selected from the group consisting of aryl, alkyl and halide; a composition of the formula (R){sub x}Q{sup +}Ga(Y){sub 4}{sup {minus}} where Q is selected from themore » group consisting of carbon, nitrogen, sulfur, phosphorus and oxygen, each R is a ligand selected from the group consisting of alkyl, aryl, and hydrogen, x is an integer selected from the group consisting of 3 and 4 depending upon Q, and each Y is a ligand selected from the group consisting of aryl, alkyl, hydride and halide with the proviso that at least one Y is a ligand selected from the group consisting of aryl, alkyl and halide; an ionic polymerization catalyst composition including an active cationic portion and a gallium based weakly coordinating anion; and bridged anion species of the formula M{sup +x}{sub y}[X(GaY{sub 3}){sub z}]{sup {minus}y}{sub x} where M is a metal selected from the group consisting of lithium, sodium, potassium, magnesium, cesium, calcium, strontium, thallium, and silver, x is an integer selected from the group consisting of 1 or 2, X is a bridging group between two gallium atoms, y is an integer selected from the group consisting 1 and 2, z is an integer of at least 2, each Y is a ligand selected from the group consisting of aryl, alkyl, hydride and halide with the proviso that at least one Y is a ligand selected from the group consisting of aryl, alkyl and halide.« less

Gallium based low-interaction anions

DOEpatents

King, Wayne A.; Kubas, Gregory J.

2000-01-01

The present invention provides: a composition of the formula M.sup.+x (Ga(Y).sub.4.sup.-).sub.x where M is a metal selected from the group consisting of lithium, sodium, potassium, cesium, calcium, strontium, thallium, and silver, x is an integer selected from the group consisting of 1 or 2, each Y is a ligand selected from the group consisting of aryl, alkyl, hydride and halide with the proviso that at least one Y is a ligand selected from the group consisting of aryl, alkyl and halide; a composition of the formula (R).sub.x Q.sup.+ Ga(Y).sub.4.sup.- where Q is selected from the group consisting of carbon, nitrogen, sulfur, phosphorus and oxygen, each R is a ligand selected from the group consisting of alkyl, aryl, and hydrogen, x is an integer selected from the group consisting of 3 and 4 depending upon Q, and each Y is a ligand selected from the group consisting of aryl, alkyl, hydride and halide with the proviso that at least one Y is a ligand selected from the group consisting of aryl, alkyl and halide; an ionic polymerization catalyst composition including an active cationic portion and a gallium based weakly coordinating anion; and bridged anion species of the formula M.sup.+x.sub.y [X(Ga(Y.sub.3).sub.z ].sup.-y.sub.x where M is a metal selected from the group consisting of lithium, sodium, potassium, magnesium, cesium, calcium, strontium, thallium, and silver, x is an integer selected from the group consisting of 1 or 2, X is a bridging group between two gallium atoms, y is an integer selected from the group consisting 1 and 2, z is an integer of at least 2, each Y is a ligand selected from the group consisting of aryl, alkyl, hydride and halide with the proviso that at least one Y is a ligand selected from the group consisting of aryl, alkyl and halide.

Modeling and management of water in the Klamath River Basin: overcoming politics and conflicts

USGS Publications Warehouse

Flug, Marshall; Scott, John F.; Abt, Steven R.; Young-Pezeshk, Jayne; Watson, Chester C.

1998-01-01

The network flow model MODSIM, which was designed as a water quantity mass balance model for evaluating and selecting water management alternatives, has been applied to the Klamath River basin. A background of conflicting issues in the basin is presented. The complexity of water quantity model development, while satisfying the many stakeholders and involved special interest groups is discussed, as well as the efforts taken to have the technical model accepted and used, and overcome stakeholder criticism, skepticism, and mistrust of the government.

SLAMMER: Seismic LAndslide Movement Modeled using Earthquake Records

USGS Publications Warehouse

Jibson, Randall W.; Rathje, Ellen M.; Jibson, Matthew W.; Lee, Yong W.

2013-01-01

This program is designed to facilitate conducting sliding-block analysis (also called permanent-deformation analysis) of slopes in order to estimate slope behavior during earthquakes. The program allows selection from among more than 2,100 strong-motion records from 28 earthquakes and allows users to add their own records to the collection. Any number of earthquake records can be selected using a search interface that selects records based on desired properties. Sliding-block analyses, using any combination of rigid-block (Newmark), decoupled, and fully coupled methods, are then conducted on the selected group of records, and results are compiled in both graphical and tabular form. Simplified methods for conducting each type of analysis are also included.

Identification of Atuveciclib (BAY 1143572), the First Highly Selective, Clinical PTEFb/CDK9 Inhibitor for the Treatment of Cancer

PubMed Central

Scholz, Arne; Lienau, Philip; Siemeister, Gerhard; Kosemund, Dirk; Bohlmann, Rolf; Briem, Hans; Terebesi, Ildiko; Meyer, Kirstin; Prelle, Katja; Denner, Karsten; Bömer, Ulf; Schäfer, Martina; Eis, Knut; Valencia, Ray; Ince, Stuart; von Nussbaum, Franz; Mumberg, Dominik; Ziegelbauer, Karl; Klebl, Bert; Choidas, Axel; Nussbaumer, Peter; Baumann, Matthias; Schultz‐Fademrecht, Carsten; Rühter, Gerd; Eickhoff, Jan; Brands, Michael

2017-01-01

Abstract Selective inhibition of exclusively transcription‐regulating PTEFb/CDK9 is a promising new approach in cancer therapy. Starting from lead compound BAY‐958, lead optimization efforts strictly focusing on kinase selectivity, physicochemical and DMPK properties finally led to the identification of the orally available clinical candidate atuveciclib (BAY 1143572). Structurally characterized by an unusual benzyl sulfoximine group, BAY 1143572 exhibited the best overall profile in vitro and in vivo, including high efficacy and good tolerability in xenograft models in mice and rats. BAY 1143572 is the first potent and highly selective PTEFb/CDK9 inhibitor to enter clinical trials for the treatment of cancer. PMID:28961375

[Effect of acupuncture on pattern-visual evoked potential in rats with monocular visual deprivation].

PubMed

Yan, Xing-Ke; Dong, Li-Li; Liu, An-Guo; Wang, Jun-Yan; Ma, Chong-Bing; Zhu, Tian-Tian

2013-08-01

To explore electrophysiology mechanism of acupuncture for treatment and prevention of visual deprivation effect. Eighteen healthy 15-day Evans rats were randomly divided into a normal group, a model group and an acupuncture group, 6 rats in each one. Deprivation amblyopia model was established by monocular eyelid suture in the model group and acupuncture group. Acupuncture was applied at "Jingming" (BL 1), "Chengqi" (ST 1), "Qiuhou" (EX-HN 7) and "Cuanzhu" (BL 2) in the acupuncture group. The bilateral acupoints were selected alternately, one side for a day, and totally 14 days were required. The effect of acupuncture on visual evoked potential in different spatial frequencies was observed. Under three different kinds of spatial frequencies of 2 X 2, 4 X 4 and 8 X 8, compared with normal group, there was obvious visual deprivation effect in the model group where P1 peak latency was delayed (P<0.01) while N1 -P1 amplitude value was decreased (P<0.01). Compared with model group, P1 peak latency was obviously ahead of time (P<0.01) while N1-P1 amplitude value was increased (P<0.01) in the acupuncture group, there was no statistical significance compared with normal group (P>0.05). Under spatial frequency of 4 X 4, N1-P1 amplitude value was maximum in the normal group and acupuncture group. With this spatial frequency the rat's eye had best resolving ability, indicating it could be the best spatial frequency for rat visual system. The visual system has obvious electrophysiology plasticity in sensitive period. Acupuncture treatment could adjust visual deprivation-induced suppression and slow of visual response in order to antagonism deprivation effect.

Computer-aided diagnosis of contrast-enhanced spectral mammography: A feasibility study.

PubMed

Patel, Bhavika K; Ranjbar, Sara; Wu, Teresa; Pockaj, Barbara A; Li, Jing; Zhang, Nan; Lobbes, Mark; Zhang, Bin; Mitchell, J Ross

2018-01-01

To evaluate whether the use of a computer-aided diagnosis-contrast-enhanced spectral mammography (CAD-CESM) tool can further increase the diagnostic performance of CESM compared with that of experienced radiologists. This IRB-approved retrospective study analyzed 50 lesions described on CESM from August 2014 to December 2015. Histopathologic analyses, used as the criterion standard, revealed 24 benign and 26 malignant lesions. An expert breast radiologist manually outlined lesion boundaries on the different views. A set of morphologic and textural features were then extracted from the low-energy and recombined images. Machine-learning algorithms with feature selection were used along with statistical analysis to reduce, select, and combine features. Selected features were then used to construct a predictive model using a support vector machine (SVM) classification method in a leave-one-out-cross-validation approach. The classification performance was compared against the diagnostic predictions of 2 breast radiologists with access to the same CESM cases. Based on the SVM classification, CAD-CESM correctly identified 45 of 50 lesions in the cohort, resulting in an overall accuracy of 90%. The detection rate for the malignant group was 88% (3 false-negative cases) and 92% for the benign group (2 false-positive cases). Compared with the model, radiologist 1 had an overall accuracy of 78% and a detection rate of 92% (2 false-negative cases) for the malignant group and 62% (10 false-positive cases) for the benign group. Radiologist 2 had an overall accuracy of 86% and a detection rate of 100% for the malignant group and 71% (8 false-positive cases) for the benign group. The results of our feasibility study suggest that a CAD-CESM tool can provide complementary information to radiologists, mainly by reducing the number of false-positive findings. Copyright © 2017 Elsevier B.V. All rights reserved.

Further evaluation of quantitative structure--activity relationship models for the prediction of the skin sensitization potency of selected fragrance allergens.

PubMed

Patlewicz, Grace Y; Basketter, David A; Pease, Camilla K Smith; Wilson, Karen; Wright, Zoe M; Roberts, David W; Bernard, Guillaume; Arnau, Elena Giménez; Lepoittevin, Jean-Pierre

2004-02-01

Fragrance substances represent a very diverse group of chemicals; a proportion of them are associated with the ability to cause allergic reactions in the skin. Efforts to find substitute materials are hindered by the need to undertake animal testing for determining both skin sensitization hazard and potency. One strategy to avoid such testing is through an understanding of the relationships between chemical structure and skin sensitization, so-called structure-activity relationships. In recent work, we evaluated 2 groups of fragrance chemicals -- saturated aldehydes and alpha,beta-unsaturated aldehydes. Simple quantitative structure-activity relationship (QSAR) models relating the EC3 values [derived from the local lymph node assay (LLNA)] to physicochemical properties were developed for both sets of aldehydes. In the current study, we evaluated an additional group of carbonyl-containing compounds to test the predictive power of the developed QSARs and to extend their scope. The QSAR models were used to predict EC3 values of 10 newly selected compounds. Local lymph node assay data generated for these compounds demonstrated that the original QSARs were fairly accurate, but still required improvement. Development of these QSAR models has provided us with a better understanding of the potential mechanisms of action for aldehydes, and hence how to avoid or limit allergy. Knowledge generated from this work is being incorporated into new/improved rules for sensitization in the expert toxicity prediction system, deductive estimation of risk from existing knowledge (DEREK).

Target selection and comparison of mission design for space debris removal by DLR's advanced study group

NASA Astrophysics Data System (ADS)

van der Pas, Niels; Lousada, Joao; Terhes, Claudia; Bernabeu, Marc; Bauer, Waldemar

2014-09-01

Space debris is a growing problem. Models show that the Kessler syndrome, the exponential growth of debris due to collisions, has become unavoidable unless an active debris removal program is initiated. The debris population in LEO with inclination between 60° and 95° is considered as the most critical zone. In order to stabilize the debris population in orbit, especially in LEO, 5 to 10 objects will need to be removed every year. The unique circumstances of such a mission could require that several objects are removed with a single launch. This will require a mission to rendezvous with a multitude of objects orbiting on different altitudes, inclinations and planes. Removal models have assumed that the top priority targets will be removed first. However this will lead to a suboptimal mission design and increase the ΔV-budget. Since there is a multitude of targets to choose from, the targets can be selected for an optimal mission design. In order to select a group of targets for a removal mission the orbital parameters and political constraints should also be taken into account. Within this paper a number of the target selection criteria are presented. The possible mission targets and their order of retrieval is dependent on the mission architecture. A comparison between several global mission architectures is given. Under consideration are 3 global missions of which a number of parameters are varied. The first mission launches multiple separate deorbit kits. The second launches a mother craft with deorbit kits. The third launches an orbital tug which pulls the debris in a lower orbit, after which a deorbit kit performs the final deorbit burn. A RoM mass and cost comparison is presented. The research described in this paper has been conducted as part of an active debris removal study by the Advanced Study Group (ASG). The ASG is an interdisciplinary student group working at the DLR, analyzing existing technologies and developing new ideas into preliminary concepts.

A null model for microbial diversification

PubMed Central

Straub, Timothy J.

2017-01-01

Whether prokaryotes (Bacteria and Archaea) are naturally organized into phenotypically and genetically cohesive units comparable to animal or plant species remains contested, frustrating attempts to estimate how many such units there might be, or to identify the ecological roles they play. Analyses of gene sequences in various closely related prokaryotic groups reveal that sequence diversity is typically organized into distinct clusters, and processes such as periodic selection and extensive recombination are understood to be drivers of cluster formation (“speciation”). However, observed patterns are rarely compared with those obtainable with simple null models of diversification under stochastic lineage birth and death and random genetic drift. Via a combination of simulations and analyses of core and phylogenetic marker genes, we show that patterns of diversity for the genera Escherichia, Neisseria, and Borrelia are generally indistinguishable from patterns arising under a null model. We suggest that caution should thus be taken in interpreting observed clustering as a result of selective evolutionary forces. Unknown forces do, however, appear to play a role in Helicobacter pylori, and some individual genes in all groups fail to conform to the null model. Taken together, we recommend the presented birth−death model as a null hypothesis in prokaryotic speciation studies. It is only when the real data are statistically different from the expectations under the null model that some speciation process should be invoked. PMID:28630293

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…

Mathematics Literacy on Problem Based Learning with Indonesian Realistic Mathematics Education Approach Assisted E-Learning Edmodo

NASA Astrophysics Data System (ADS)

Wardono; Waluya, S. B.; Mariani, Scolastika; Candra D, S.

2016-02-01

This study aims to find out that there are differences in mathematical literacy ability in content Change and Relationship class VII Junior High School 19, Semarang by Problem Based Learning (PBL) model with an Indonesian Realistic Mathematics Education (called Pendidikan Matematika Realistik Indonesia or PMRI in Indonesia) approach assisted Elearning Edmodo, PBL with a PMRI approach, and expository; to know whether the group of students with learning PBL models with PMRI approach and assisted E-learning Edmodo can improve mathematics literacy; to know that the quality of learning PBL models with a PMRI approach assisted E-learning Edmodo has a good category; to describe the difficulties of students in working the problems of mathematical literacy ability oriented PISA. This research is a mixed methods study. The population was seventh grade students of Junior High School 19, Semarang Indonesia. Sample selection is done by random sampling so that the selected experimental class 1, class 2 and the control experiment. Data collected by the methods of documentation, tests and interviews. From the results of this study showed average mathematics literacy ability of students in the group PBL models with a PMRI approach assisted E-learning Edmodo better than average mathematics literacy ability of students in the group PBL models with a PMRI approach and better than average mathematics literacy ability of students in the expository models; Mathematics literacy ability in the class using the PBL model with a PMRI approach assisted E-learning Edmodo have increased and the improvement of mathematics literacy ability is higher than the improvement of mathematics literacy ability of class that uses the model of PBL learning with PMRI approach and is higher than the improvement of mathematics literacy ability of class that uses the expository models; The quality of learning using PBL models with a PMRI approach assisted E-learning Edmodo have very good category.

Feature selection through validation and un-censoring of endovascular repair survival data for predicting the risk of re-intervention.

PubMed

Attallah, Omneya; Karthikesalingam, Alan; Holt, Peter J E; Thompson, Matthew M; Sayers, Rob; Bown, Matthew J; Choke, Eddie C; Ma, Xianghong

2017-08-03

Feature selection (FS) process is essential in the medical area as it reduces the effort and time needed for physicians to measure unnecessary features. Choosing useful variables is a difficult task with the presence of censoring which is the unique characteristic in survival analysis. Most survival FS methods depend on Cox's proportional hazard model; however, machine learning techniques (MLT) are preferred but not commonly used due to censoring. Techniques that have been proposed to adopt MLT to perform FS with survival data cannot be used with the high level of censoring. The researcher's previous publications proposed a technique to deal with the high level of censoring. It also used existing FS techniques to reduce dataset dimension. However, in this paper a new FS technique was proposed and combined with feature transformation and the proposed uncensoring approaches to select a reduced set of features and produce a stable predictive model. In this paper, a FS technique based on artificial neural network (ANN) MLT is proposed to deal with highly censored Endovascular Aortic Repair (EVAR). Survival data EVAR datasets were collected during 2004 to 2010 from two vascular centers in order to produce a final stable model. They contain almost 91% of censored patients. The proposed approach used a wrapper FS method with ANN to select a reduced subset of features that predict the risk of EVAR re-intervention after 5 years to patients from two different centers located in the United Kingdom, to allow it to be potentially applied to cross-centers predictions. The proposed model is compared with the two popular FS techniques; Akaike and Bayesian information criteria (AIC, BIC) that are used with Cox's model. The final model outperforms other methods in distinguishing the high and low risk groups; as they both have concordance index and estimated AUC better than the Cox's model based on AIC, BIC, Lasso, and SCAD approaches. These models have p-values lower than 0.05, meaning that patients with different risk groups can be separated significantly and those who would need re-intervention can be correctly predicted. The proposed approach will save time and effort made by physicians to collect unnecessary variables. The final reduced model was able to predict the long-term risk of aortic complications after EVAR. This predictive model can help clinicians decide patients' future observation plan.

Design, synthesis, and biological evaluation of 3,4-dihydroquinolin-2(1H)-one and 1,2,3,4-tetrahydroquinoline-based selective human neuronal nitric oxide synthase (nNOS) inhibitors.

PubMed

Ramnauth, Jailall; Speed, Joanne; Maddaford, Shawn P; Dove, Peter; Annedi, Subhash C; Renton, Paul; Rakhit, Suman; Andrews, John; Silverman, Sarah; Mladenova, Gabriela; Zinghini, Salvatore; Nair, Sheela; Catalano, Concettina; Lee, David K H; De Felice, Milena; Porreca, Frank

2011-08-11

Neuronal nitric oxide synthase (nNOS) inhibitors are effective in preclinical models of many neurological disorders. In this study, two related series of compounds, 3,4-dihydroquinolin-2(1H)-one and 1,2,3,4-tetrahydroquinoline, containing a 6-substituted thiophene amidine group were synthesized and evaluated as inhibitors of human nitric oxide synthase (NOS). A structure-activity relationship (SAR) study led to the identification of a number of potent and selective nNOS inhibitors. Furthermore, a few representative compounds were shown to possess druglike properties, features that are often difficult to achieve when designing nNOS inhibitors. Compound (S)-35, with excellent potency and selectivity for nNOS, was shown to fully reverse thermal hyperalgesia when given to rats at a dose of 30 mg/kg intraperitonieally (ip) in the L5/L6 spinal nerve ligation model of neuropathic pain (Chung model). In addition, this compound reduced tactile hyperesthesia (allodynia) after oral administration (30 mg/kg) in a rat model of dural inflammation relevant to migraine pain.

Comparison of genetic algorithm and imperialist competitive algorithms in predicting bed load transport in clean pipe.

PubMed

Ebtehaj, Isa; Bonakdari, Hossein

2014-01-01

The existence of sediments in wastewater greatly affects the performance of the sewer and wastewater transmission systems. Increased sedimentation in wastewater collection systems causes problems such as reduced transmission capacity and early combined sewer overflow. The article reviews the performance of the genetic algorithm (GA) and imperialist competitive algorithm (ICA) in minimizing the target function (mean square error of observed and predicted Froude number). To study the impact of bed load transport parameters, using four non-dimensional groups, six different models have been presented. Moreover, the roulette wheel selection method is used to select the parents. The ICA with root mean square error (RMSE) = 0.007, mean absolute percentage error (MAPE) = 3.5% show better results than GA (RMSE = 0.007, MAPE = 5.6%) for the selected model. All six models return better results than the GA. Also, the results of these two algorithms were compared with multi-layer perceptron and existing equations.

Protective effects of molecular hydrogen on steroid-induced osteonecrosis in rabbits via reducing oxidative stress and apoptosis.

PubMed

Li, Jia; Ge, Zhaogang; Fan, Lihong; Wang, Kunzheng

2017-02-02

The objective of this study was to investigate the protective effects of molecular hydrogen, a novel and selective antioxidant, on steroid-induced osteonecrosis (ON) in a rabbit model. Sixty rabbits were randomly divided into two groups (model group and hydrogen group). Osteonecrosis was induced according to an established protocol of steroid-induced ON. Rabbits in the hydrogen group were treated with intraperitoneal injections of molecular hydrogen at 10 ml/kg body weight for seven consecutive days. Plasma levels of total cholesterol, triglycerides, soluble thrombomodulin(sTM), glutathione(GSH) and malondialdehyde(MDA) were measured before and after steroid administration. The presence or absence of ON was examined histopathologically. Oxidative injury and vascular injury were assessed in vivo by immunohistochemical staining of 8-hydoxy-2-deoxyguanosine(8-OHdG) and MDA, and ink artery infusion angiography. The terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling (TUNEL) assays were performed to measure apoptosis. The incidence of steroid-induced ON was significantly lower in hydrogen group (28.6%) than that in model group (68.0%). No statistically differences were observed on the levels of total cholesterol and triglycerides. Oxidative injury, vascular injury and apoptosis were attenuated in the hydrogen group compared with those in the model group in vivo. These results suggested that molecular hydrogen prevents steroid-induced osteonecrosis in rabbits by suppressing oxidative injury, vascular injury and apoptosis.

Analysis of the Efficacy of an Intervention to Improve Parent-Adolescent Problem Solving.

PubMed

Semeniuk, Yulia Yuriyivna; Brown, Roger L; Riesch, Susan K

2016-07-01

We conducted a two-group longitudinal partially nested randomized controlled trial to examine whether young adolescent youth-parent dyads participating in Mission Possible: Parents and Kids Who Listen, in contrast to a comparison group, would demonstrate improved problem-solving skill. The intervention is based on the Circumplex Model and Social Problem-Solving Theory. The Circumplex Model posits that families who are balanced, that is characterized by high cohesion and flexibility and open communication, function best. Social Problem-Solving Theory informs the process and skills of problem solving. The Conditional Latent Growth Modeling analysis revealed no statistically significant differences in problem solving among the final sample of 127 dyads in the intervention and comparison groups. Analyses of effect sizes indicated large magnitude group effects for selected scales for youth and dyads portraying a potential for efficacy and identifying for whom the intervention may be efficacious if study limitations and lessons learned were addressed. © The Author(s) 2016.

Will they stay fit and healthy? A three-year follow-up evaluation of a physical activity and health intervention in Polish youth.

PubMed

Bronikowski, Michal; Bronikowska, Malgorzata

2011-11-01

In this paper we evaluate the sustainability of changes of involvement in physical activity. The paper examines the effectiveness of a model aiming at influencing the frequency of leisure time physical activity, physical fitness and body constituency in youth. The baseline of this study was a randomly selected sample of 13 year olds who participated in an intervention programme carried out in three schools in Poznan in 2005-08. From a total of 199 adolescent boys a subsample of 38 individuals from the experimental group and 34 from the control group were followed for 15 months after the interventional programme finished. From 170 girls, a subsample of 33 from the experimental group and 32 girls from the control group were also randomly selected for the follow-up study. Among the variables monitored were: physical fitness, body constituency, and frequency of leisure time physical activity. All the variables were monitored in pre-test, post-test and follow-up examinations. It was established that 15 months after the end of the interventional programme boys and girls from the intervention groups maintained a higher level of leisure time physical activity than their control group peers, and similarly in the case of selected health-related components of physical fitness. No distinctive differences were found in the case of body constituency, though, apart from muscle mass and the sum of skinfolds in girls. The study exposed an increase in leisure time physical activity in time and a positive influence on selected components of health-related variables. The findings confirm the effectiveness of a multi-level intervention programme involving self-determined out-of-school physical activity planning for school-age youths, indicating the importance of personal and social context.

Phylogeny reconstruction in the Caesalpinieae grade (Leguminosae) based on duplicated copies of the sucrose synthase gene and plastid markers.

PubMed

Manzanilla, Vincent; Bruneau, Anne

2012-10-01

The Caesalpinieae grade (Leguminosae) forms a morphologically and ecologically diverse group of mostly tropical tree species with a complex evolutionary history. This grade comprises several distinct lineages, but the exact delimitation of the group relative to subfamily Mimosoideae and other members of subfamily Caesalpinioideae, as well as phylogenetic relationships among the lineages are uncertain. With the aim of better resolving phylogenetic relationships within the Caesalpinieae grade, we investigated the utility of several nuclear markers developed from genomic studies in the Papilionoideae. We cloned and sequenced the low copy nuclear gene sucrose synthase (SUSY) and combined the data with plastid trnL and matK sequences. SUSY has two paralogs in the Caesalpinieae grade and in the Mimosoideae, but occurs as a single copy in all other legumes tested. Bayesian and maximum likelihood phylogenetic analyses suggest the two nuclear markers are congruent with plastid DNA data. The Caesalpinieae grade is divided into four well-supported clades (Cassia, Caesalpinia, Tachigali and Peltophorum clades), a poorly supported clade of Dimorphandra Group genera, and two paraphyletic groups, one with other Dimorphandra Group genera and the other comprising genera previously recognized as the Umtiza clade. A selection analysis of the paralogs, using selection models from PAML, suggests that SUSY genes are subjected to a purifying selection. One of the SUSY paralogs, under slightly stronger positive selection, may be undergoing subfunctionalization. The low copy SUSY gene is useful for phylogeny reconstruction in the Caesalpinieae despite the presence of duplicate copies. This study confirms that the Caesalpinieae grade is an artificial group, and highlights the need for further analyses of lineages at the base of the Mimosoideae. Copyright © 2012 Elsevier Inc. All rights reserved.

Graft selection strategy in adult-to-adult living donor liver transplantation: When both hemiliver grafts meet volumetric criteria.

PubMed

Kurihara, Takeshi; Yoshizumi, Tomoharu; Yoshida, Yoshihiro; Ikegami, Toru; Itoh, Shinji; Harimoto, Norifumi; Ninomiya, Mizuki; Uchiyama, Hideaki; Okabe, Hirohisa; Kimura, Koichi; Kawanaka, Hirofumi; Shirabe, Ken; Maehara, Yoshihiko

2016-07-01

To ensure donor safety in living donor liver transplantation (LDLT), the left and caudate lobe (LL) is the preferred graft choice. However, patient prognosis may still be poor even if graft volume (GV) selection criteria are met. Our aim was to evaluate the effects of right lobe (RL) donation when the LL graft selection criteria are met. Consecutive donors (n = 135) with preoperative LL graft volumetric GV/standard liver volume (SLV) of ≥35% and RL remnant of ≥35% were retrospectively studied. Patients were divided into 2 groups: LL graft and RL graft. Recipient's body surface area (BSA), Model for End-Stage Liver Disease (MELD) score, and the donor's age were higher in the RL group. The donor's BSA and preoperative volumetric GV/SLV of the LL graft were smaller in the RL group. The predicted score (calculated using data for graft size, donor age, MELD score, and the presence of portosystemic shunt, which correlated well with graft function and with 6-month graft survival) of the RL group, was significantly lower if the LL graft were used, but using the actual RL graft improved the score equal to that of the LL group. Six-month and 12-month graft survival rates did not differ between the 2 groups. In patients with a poor prognosis, a larger RL graft improved the predicted score and survival was equal to that of patients who received LL grafts. In conclusion, graft selection by GV, donor age, and recipient MELD score improves outcomes in LDLT. Liver Transplantation 22 914-922 2016 AASLD. © 2016 American Association for the Study of Liver Diseases.

What to do When Scalar Invariance Fails: The Extended Alignment Method for Multi-Group Factor Analysis Comparison of Latent Means Across Many Groups.

PubMed

Marsh, Herbert W; Guo, Jiesi; Parker, Philip D; Nagengast, Benjamin; Asparouhov, Tihomir; Muthén, Bengt; Dicke, Theresa

2017-01-12

Scalar invariance is an unachievable ideal that in practice can only be approximated; often using potentially questionable approaches such as partial invariance based on a stepwise selection of parameter estimates with large modification indices. Study 1 demonstrates an extension of the power and flexibility of the alignment approach for comparing latent factor means in large-scale studies (30 OECD countries, 8 factors, 44 items, N = 249,840), for which scalar invariance is typically not supported in the traditional confirmatory factor analysis approach to measurement invariance (CFA-MI). Importantly, we introduce an alignment-within-CFA (AwC) approach, transforming alignment from a largely exploratory tool into a confirmatory tool, and enabling analyses that previously have not been possible with alignment (testing the invariance of uniquenesses and factor variances/covariances; multiple-group MIMIC models; contrasts on latent means) and structural equation models more generally. Specifically, it also allowed a comparison of gender differences in a 30-country MIMIC AwC (i.e., a SEM with gender as a covariate) and a 60-group AwC CFA (i.e., 30 countries × 2 genders) analysis. Study 2, a simulation study following up issues raised in Study 1, showed that latent means were more accurately estimated with alignment than with the scalar CFA-MI, and particularly with partial invariance scalar models based on the heavily criticized stepwise selection strategy. In summary, alignment augmented by AwC provides applied researchers from diverse disciplines considerable flexibility to address substantively important issues when the traditional CFA-MI scalar model does not fit the data. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

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.

Are groups of galaxies virialized systems?

NASA Technical Reports Server (NTRS)

Diaferio, Antonaldo; Ramella, Massimo; Geller, Margaret J.; Ferrari, Attilio

1993-01-01

Groups are systems of galaxies with crossing times t(cr) much smaller than the Hubble time. Most of them have t(cr) less than 0.1/H0. The usual interpretation is that they are in virial equilibrium. We compare the data of the group catalog selected from the CfA redshift survey extension with different N-body models. We show that the distributions of kinematic and dynamical quantities of the groups in the CfA catalog can be reproduced by a single collapsing group observed along different line of sights. This result shows that (1) projection effects dominate the statistics of these systems, and (2) observed groups of galaxies are probably still in the collapse phase.

The effect of inquiry-flipped classroom model toward students' achievement on chemical reaction rate

NASA Astrophysics Data System (ADS)

Paristiowati, Maria; Fitriani, Ella; Aldi, Nurul Hanifah

2017-08-01

The aim of this research is to find out the effect of Inquiry-Flipped Classroom Models toward Students' Achievement on Chemical Reaction Rate topic. This study was conducted at SMA Negeri 3 Tangerang in Eleventh Graders. The Quasi Experimental Method with Non-equivalent Control Group design was implemented in this study. 72 students as the sample was selected by purposive sampling. Students in experimental group were learned through inquiry-flipped classroom model. Meanwhile, in control group, students were learned through guided inquiry learning model. Based on the data analysis, it can be seen that there is significant difference in the result of the average achievement of the students. The average achievement of the students in inquiry-flipped classroom model was 83,44 and the average achievement of the students in guided inquiry learning model was 74,06. It can be concluded that the students' achievement with inquiry-flipped classroom better than guided inquiry. The difference of students' achievement were significant through t-test which is tobs 3.056 > ttable 1.994 (α = 0.005).

Reducing Schoolchildren With Reactive Aggression Through Child, Parent, and Conjoint Parent-Child Group Interventions: A Longitudinal Outcome Effectiveness Study.

PubMed

Fung, Annis Lai Chu

2017-10-10

This study was the first to evaluate the effectiveness of three different group interventions to reduce children's reactive aggression based on the social information processing (SIP) model. In the first stage of screening, 3,734 children of Grades 4-6 completed the Reactive-Proactive Aggression Questionnaire (RPQ) to assess their reactive and proactive aggression. Respondents with a total score of z ≥ 1 on the RPQ were shortlisted for the second stage of screening by qualitative interview. Interviews with 475 children were conducted to select those who showed reactive aggression featuring a hostile attributional bias. Finally, 126 children (97 males and 29 females) aged 8 to 14 (M = 9.71, SD = 1.23) were selected and randomly assigned to one of the three groups: a child group, a parent group, and a parent-child group. A significant Time × Intervention effect was found for general and reactive aggression. The parent-child group and child group showed a significant drop in general aggression and reactive aggression from posttest to 6-month follow-up, after controlling for baseline scores, sex, and age. However, the parent group showed no treatment effect: reactive aggression scores were significantly higher than those in the child group at 6-month follow-up. This study has provided strong evidence that children with reactive aggression need direct and specific treatment to reconstruct the steps of the SIP involving the selection and interpretation of cues. The intervention could help to prevent severe violent crimes at the later stage of a reactive aggressor. © 2017 Family Process Institute.

A selective cyclooxygenase-2 inhibitor (Etodolac) prevents spontaneous biliary tumorigenesis in a hamster bilioenterostomy model.

PubMed

Kitasato, Amane; Kuroki, Tamotsu; Adachi, Tomohiko; Ono, Shinichiro; Tanaka, Takayuki; Tsuneoka, Noritsugu; Hirabaru, Masataka; Takatsuki, Mitsuhisa; Eguchi, Susumu

2014-01-01

Secondary biliary carcinomas are associated with persistent reflux cholangitis after bilioenterostomy. Cyclooxygenase-2 (COX-2) has been a target for cancer prevention. The aim of this study was to evaluate the chemopreventive efficacy of long-term treatment with a selective COX-2 inhibitor medication during the natural course after bilioenterostomy without chemical induction. Syrian golden hamsters which underwent choledochojejunostomy were randomly divided into two groups: the control group (n = 31), which was fed a normal diet, and the etodolac group (n = 33), which was fed 0.01% etodolac (a selective COX-2 inhibitor) mixed in the meal. The hamsters were killed at the postoperative weeks 20-39, 40-59, 60-79, or 80-100. Biliary neoplasms, cholangitis, proliferating cell nuclear antigen labeling index (PCNA-LI) of the biliary epithelium, and prostaglandin E2 (PGE2) production were evaluated. The occurrence rates of biliary neoplasm were 43.8 and 15.2% in the control and etodolac groups, respectively (p < 0.05). The incidence of biliary neoplasm increased as time progressed in the control group, whereas it remained at a low level throughout the experimental period in the etodolac group. PGE2 products tended to be lower in the etodolac group, and PCNA-LI was significantly lower in the etodolac group (p < 0.01). These results suggest that the medication etodolac suppresses cell proliferation of the biliary epithelium, thereby preventing biliary carcinogenesis. Etodolac is expected to prevent secondary biliary carcinogenesis caused by persistent reflux cholangitis after bilioenterostomy. © 2014 S. Karger AG, Basel.

Evaluation of approaches focused on modelling of organic carbon stocks using the RothC model

NASA Astrophysics Data System (ADS)

Koco, Štefan; Skalský, Rastislav; Makovníková, Jarmila; Tarasovičová, Zuzana; Barančíková, Gabriela

2014-05-01

The aim of current efforts in the European area is the protection of soil organic matter, which is included in all relevant documents related to the protection of soil. The use of modelling of organic carbon stocks for anticipated climate change, respectively for land management can significantly help in short and long-term forecasting of the state of soil organic matter. RothC model can be applied in the time period of several years to centuries and has been tested in long-term experiments within a large range of soil types and climatic conditions in Europe. For the initialization of the RothC model, knowledge about the carbon pool sizes is essential. Pool size characterization can be obtained from equilibrium model runs, but this approach is time consuming and tedious, especially for larger scale simulations. Due to this complexity we search for new possibilities how to simplify and accelerate this process. The paper presents a comparison of two approaches for SOC stocks modelling in the same area. The modelling has been carried out on the basis of unique input of land use, management and soil data for each simulation unit separately. We modeled 1617 simulation units of 1x1 km grid on the territory of agroclimatic region Žitný ostrov in the southwest of Slovakia. The first approach represents the creation of groups of simulation units based on the evaluation of results for simulation unit with similar input values. The groups were created after the testing and validation of modelling results for individual simulation units with results of modelling the average values of inputs for the whole group. Tests of equilibrium model for interval in the range 5 t.ha-1 from initial SOC stock showed minimal differences in results comparing with result for average value of whole interval. Management inputs data from plant residues and farmyard manure for modelling of carbon turnover were also the same for more simulation units. Combining these groups (intervals of initial SOC stock, groups of plant residues inputs, groups of farmyard manure inputs), we created 661 simulation groups. Within the group, for all simulation units we used average values of inputs. Export of input data and modelling has been carried out manually in the graphic environment of RothC 26.3 v2.0 application for each group separately. SOC stocks were modeled for 661 groups of simulation units. For the second possibility we used RothC 26.3 version for DOS. The inputs for modelling were exported using VBA scripts in the environment of MS Access program. Equilibrium modelling for more variations of plant residues inputs was performed. Subsequently we selected the nearest value of total pool size to the real initial SOC stock value. All simulation units (1617) were automatically modeled by means of the predefined Batch File. The comparison of two methods of modelling showed spatial differentiation of results mainly with the increasing time of modelling period. In the time sequence, from initial period we mark the increasing the number of simulation units with differences in SOC stocks according to selected approaches. Observed differences suggest that the results of modelling obtained by inputs generalization should be taken into account with a certain degree of reserve. At large scales simulations it is more appropriate to use the DOS version of RothC 26.3 model which allows automated modelling. This reduces the time needed for model operation, without the necessity to look for the possibilities of minimizing the simulated units. Key words Soil organic carbon stock, modelling, RothC 26.3, agricultural soils, Slovakia Acknowledgements This work was supported by the Slovak Research and Development Agency under the contract No. APVV-0580-10 and APVV-0131-11.

Breakpoint-forced and bound long waves in the nearshore: A model comparison

USGS Publications Warehouse

List, Jeffrey H.; ,

1993-01-01

A finite-difference model is used to compare long wave amplitudes arising from two-group forced generation mechanisms in the nearshore: long waves generated at a time-varying breakpoint and the shallow-water extension of the bound long wave. Plane beach results demonstrate that the strong frequency selection in the outgoing wave predicted by the breakpoint-forcing mechanism may not be observable in field data due to this wave's relatively small size and its predicted phase relation with the bound wave. Over a bar/trough nearshore, it is shown that a strong frequency selection in shoreline amplitudes is not a unique result of the time-varying breakpoint model, but a general result of the interaction between topography and any broad-banded forcing of nearshore long waves.

Features of effective medical knowledge resources to support point of care learning: a focus group study.

PubMed

Cook, David A; Sorensen, Kristi J; Hersh, William; Berger, Richard A; Wilkinson, John M

2013-01-01

Health care professionals access various information sources to quickly answer questions that arise in clinical practice. The features that favorably influence the selection and use of knowledge resources remain unclear. We sought to better understand how clinicians select among the various knowledge resources available to them, and from this to derive a model for an effective knowledge resource. We conducted 11 focus groups at an academic medical center and outlying community sites. We included a purposive sample of 50 primary care and subspecialist internal medicine and family medicine physicians. We transcribed focus group discussions and analyzed these using a constant comparative approach to inductively identify features that influence the selection of knowledge resources. We identified nine features that influence users' selection of knowledge resources, namely efficiency (with sub-features of comprehensiveness, searchability, and brevity), integration with clinical workflow, credibility, user familiarity, capacity to identify a human expert, reflection of local care processes, optimization for the clinical question (e.g., diagnosis, treatment options, drug side effect), currency, and ability to support patient education. No single existing resource exemplifies all of these features. The influential features identified in this study will inform the development of knowledge resources, and could serve as a framework for future research in this field.

Features of Effective Medical Knowledge Resources to Support Point of Care Learning: A Focus Group Study

PubMed Central

Cook, David A.; Sorensen, Kristi J.; Hersh, William; Berger, Richard A.; Wilkinson, John M.

2013-01-01

Objective Health care professionals access various information sources to quickly answer questions that arise in clinical practice. The features that favorably influence the selection and use of knowledge resources remain unclear. We sought to better understand how clinicians select among the various knowledge resources available to them, and from this to derive a model for an effective knowledge resource. Methods We conducted 11 focus groups at an academic medical center and outlying community sites. We included a purposive sample of 50 primary care and subspecialist internal medicine and family medicine physicians. We transcribed focus group discussions and analyzed these using a constant comparative approach to inductively identify features that influence the selection of knowledge resources. Results We identified nine features that influence users' selection of knowledge resources, namely efficiency (with sub-features of comprehensiveness, searchability, and brevity), integration with clinical workflow, credibility, user familiarity, capacity to identify a human expert, reflection of local care processes, optimization for the clinical question (e.g., diagnosis, treatment options, drug side effect), currency, and ability to support patient education. No single existing resource exemplifies all of these features. Conclusion The influential features identified in this study will inform the development of knowledge resources, and could serve as a framework for future research in this field. PMID:24282535

Investigation of the degradation of cresols in the treatments with ozone

EPA Science Inventory

The reaction between ozone and the three cresol isomers was investigated in pure water. Cresols were selected as model substrates representing an important component of humic material. Cresols carry both a hydroxyl and a methyl group, each theoretically increasing the reactivity ...

Modeling intercalated PAH metabolites: Explanation for the stereochemical and shape selectivity of B-DNA for bay-region carcinogens

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

Szentpaly, L.V.; Shamovsky, I.L.

1996-12-31

The equilibrium structures of 22 intercalation complexes of different metabolites of polycyclic aromatic hydrocarbons (PAH) with the dG{sub 2}{lg_bullet}dC{sub 2} dinucleotide are obtained by AMBER and FLEX molecular modeling. The triol carbocations of highly potent carcinogens are stereochemically compatible with the dinucleotide and B-DNA. Their intercalation complexes are found (1) to be stabilized by two hydrogen bonds between DH groups of the triol cation and the N(3) atoms of the adjacent guanine residues, (2) to be {open_quotes}preorganized{close_quotes} for covalent bonding to the N(2) amino group of quanine, (3) to display only minor conformational changes with respect to the uncomplexed dinucleotidemore » in B-DNA. A new explanation for the stereochemical and shape selectivity in the initiation of cancer by PAHa is presented. The molecular mechanics study is sugmented by HF/6-31G{sup I} calculations on the conformations of phenanthrene triol carbocation.« less

Parallel selective pressures drive convergent diversification of phenotypes in pythons and boas.

PubMed

Esquerré, Damien; Scott Keogh, J

2016-07-01

Pythons and boas are globally distributed and distantly related radiations with remarkable phenotypic and ecological diversity. We tested whether pythons, boas and their relatives have evolved convergent phenotypes when they display similar ecology. We collected geometric morphometric data on head shape for 1073 specimens representing over 80% of species. We show that these two groups display strong and widespread convergence when they occupy equivalent ecological niches and that the history of phenotypic evolution strongly matches the history of ecological diversification, suggesting that both processes are strongly coupled. These results are consistent with replicated adaptive radiation in both groups. We argue that strong selective pressures related to habitat-use have driven this convergence. Pythons and boas provide a new model system for the study of macro-evolutionary patterns of morphological and ecological evolution and they do so at a deeper level of divergence and global scale than any well-established adaptive radiation model systems. © 2016 John Wiley & Sons Ltd/CNRS.

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

PubMed

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

2017-07-01

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

Modelling the distributions and spatial coincidence of bluetongue vectors Culicoides imicola and the Culicoides obsoletus group throughout the Iberian peninsula.

PubMed

Calvete, C; Estrada, R; Miranda, M A; Borrás, D; Calvo, J H; Lucientes, J

2008-06-01

Data obtained by a Spanish national surveillance programme in 2005 were used to develop climatic models for predictions of the distribution of the bluetongue virus (BTV) vectors Culicoides imicola Kieffer (Diptera: Ceratopogonidae) and the Culicoides obsoletus group Meigen throughout the Iberian peninsula. Models were generated using logistic regression to predict the probability of species occurrence at an 8-km spatial resolution. Predictor variables included the annual mean values and seasonalities of a remotely sensed normalized difference vegetation index (NDVI), a sun index, interpolated precipitation and temperature. Using an information-theoretic paradigm based on Akaike's criterion, a set of best models accounting for 95% of model selection certainty were selected and used to generate an average predictive model for each vector. The predictive performances (i.e. the discrimination capacity and calibration) of the average models were evaluated by both internal and external validation. External validation was achieved by comparing average model predictions with surveillance programme data obtained in 2004 and 2006. The discriminatory capacity of both models was found to be reasonably high. The estimated areas under the receiver operating characteristic (ROC) curve (AUC) were 0.78 and 0.70 for the C. imicola and C. obsoletus group models, respectively, in external validation, and 0.81 and 0.75, respectively, in internal validation. The predictions of both models were in close agreement with the observed distribution patterns of both vectors. Both models, however, showed a systematic bias in their predicted probability of occurrence: observed occurrence was systematically overestimated for C. imicola and underestimated for the C. obsoletus group. Average models were used to determine the areas of spatial coincidence of the two vectors. Although their spatial distributions were highly complementary, areas of spatial coincidence were identified, mainly in Portugal and in the southwest of peninsular Spain. In a hypothetical scenario in which both Culicoides members had similar vectorial capacity for a BTV strain, these areas should be considered of special epidemiological concern because any epizootic event could be intensified by consecutive vector activity developed for both species during the year; consequently, the probability of BTV spreading to remaining areas occupied by both vectors might also be higher.

Computer-aided solvent selection for multiple scenarios operation of limited-known properties solute

NASA Astrophysics Data System (ADS)

Anantpinijwatna, Amata

2017-12-01

Solvents have been applied for both production and separation of the complex chemical substance such as the pyrrolidine-2-carbonyl chloride (C5H8ClNO). Since the properties of the target substance itself are largely unknown, the selection of the solvent is limited by experiment only. However, the reaction carried out in conventional solvents are either afforded low yields or obtained slow reaction rates. Moreover, the solvents are also highly toxic and environmental unfriendly. Alternative solvents are required to enhance the production and lessen the harmful effect toward both organism and environment. A costly, time-consuming, and laborious experiments are required for acquiring a better solvent suite for production and separation of these complex compounds; whereas, a limited improvement can be obtained. On the other hand, the combination of the state-of-the-art thermodynamic models can provide faster and more robust solutions to this solvent selection problem. In this work, a framework for solvents selection in complex chemical production process is presented. The framework combines a group-contribution thermodynamic model and a segment activity coefficient model for predicting chemical properties and solubilities of the target chemical in newly formulated solvents. A guideline for solvent selection is also included. The potential of the selected solvents is then analysed and verified. The improvement toward the production yield, production rate, and product separation is then discussed.

Variance Component Selection With Applications to Microbiome Taxonomic Data.

PubMed

Zhai, Jing; Kim, Juhyun; Knox, Kenneth S; Twigg, Homer L; Zhou, Hua; Zhou, Jin J

2018-01-01

High-throughput sequencing technology has enabled population-based studies of the role of the human microbiome in disease etiology and exposure response. Microbiome data are summarized as counts or composition of the bacterial taxa at different taxonomic levels. An important problem is to identify the bacterial taxa that are associated with a response. One method is to test the association of specific taxon with phenotypes in a linear mixed effect model, which incorporates phylogenetic information among bacterial communities. Another type of approaches consider all taxa in a joint model and achieves selection via penalization method, which ignores phylogenetic information. In this paper, we consider regression analysis by treating bacterial taxa at different level as multiple random effects. For each taxon, a kernel matrix is calculated based on distance measures in the phylogenetic tree and acts as one variance component in the joint model. Then taxonomic selection is achieved by the lasso (least absolute shrinkage and selection operator) penalty on variance components. Our method integrates biological information into the variable selection problem and greatly improves selection accuracies. Simulation studies demonstrate the superiority of our methods versus existing methods, for example, group-lasso. Finally, we apply our method to a longitudinal microbiome study of Human Immunodeficiency Virus (HIV) infected patients. We implement our method using the high performance computing language Julia. Software and detailed documentation are freely available at https://github.com/JingZhai63/VCselection.

Deprivation, reinforcement and peer support as work motivators: A paradigm for habilitation of older retardates.

PubMed

Cleland, C C; Swartz, J D

1968-04-01

A chronically institutionalized, high-grade retardate group traditionally characterized as possessing poor habilitation prognosis was re-appraised and good prognostic indices were isolated and described, from this appraisal the principles of deprivation, reinforcement and peer support were invoked to develop an habilitation paradigm for this selected high-risk group. Although specifically tailored to retardates, the model may have generalization potential for other handicapped groups. Through this research and placement approach, it appears possible to more validly assess the circumstances that enhance or undermine retardates' motivation to work.

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

PubMed Central

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

2010-01-01

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

A Model of an Integrated Air Defense System (IADS) for the TACOPS program

DTIC Science & Technology

1991-09-01

SUBJECT TERMS (Continue on reverse If necessary and Identify by block number) FIELD GROUP SUB-GROUP Integrated Air Defense System, iADS, TACOPS...needed. Selection criteria for picking a Measurement Of Effectiveness (MOE) are presented. Acceslon For I NTIS CRA&I DTIC TAB 0 Unannouticed 1 ...Justification B y ............................................... Di.,t ibiation Av.iabilily Codes Avai i:.djor Dist A- 1 THESIS DISCLAIMER The reader is cautioned

Identifying taxonomic and functional surrogates for spring biodiversity conservation.

PubMed

Jyväsjärvi, Jussi; Virtanen, Risto; Ilmonen, Jari; Paasivirta, Lauri; Muotka, Timo

2018-02-27

Surrogate approaches are widely used to estimate overall taxonomic diversity for conservation planning. Surrogate taxa are frequently selected based on rarity or charisma, whereas selection through statistical modeling has been applied rarely. We used boosted-regression-tree models (BRT) fitted to biological data from 165 springs to identify bryophyte and invertebrate surrogates for taxonomic and functional diversity of boreal springs. We focused on these 2 groups because they are well known and abundant in most boreal springs. The best indicators of taxonomic versus functional diversity differed. The bryophyte Bryum weigelii and the chironomid larva Paratrichocladius skirwithensis best indicated taxonomic diversity, whereas the isopod Asellus aquaticus and the chironomid Macropelopia spp. were the best surrogates of functional diversity. In a scoring algorithm for priority-site selection, taxonomic surrogates performed only slightly better than random selection for all spring-dwelling taxa, but they were very effective in representing spring specialists, providing a distinct improvement over random solutions. However, the surrogates for taxonomic diversity represented functional diversity poorly and vice versa. When combined with cross-taxon complementarity analyses, surrogate selection based on statistical modeling provides a promising approach for identifying groundwater-dependent ecosystems of special conservation value, a key requirement of the EU Water Framework Directive. © 2018 Society for Conservation Biology.

Habitat selection by postbreeding female diving ducks: Influence of habitat attributes and conspecifics

USGS Publications Warehouse

Austin, Jane E.; O'Neil, Shawn T.; Warren, Jeffrey M.

2017-01-01

Habitat selection studies of postbreeding waterfowl have rarely focused on within-wetland attributes such as water depth, escape cover, and food availability. Flightless waterfowl must balance habitat selection between avoiding predation risks and feeding. Reproductively successful female ducks face the greatest challenges because they begin the definitive prebasic molt at or near the end of brood rearing, when their body condition is at a low point. We assessed the relative importance of habitat attributes and group effects in habitat selection by postbreeding female lesser scaup Aythya affinis on a 2332-ha montane wetland complex during the peak flightless period (August) over seven years. Hypothesis-based habitat attributes included percent open water, open water:emergent edge density, water depth, percent flooded bare substrate, fetch (distance wind can travel unobstructed), group size, and several interactions representing functional responses to interannual variation in water levels. Surveys of uniquely marked females were conducted within randomly ordered survey blocks. We fitted two-part generalized linear mixed-effects models to counts of marked females within survey blocks, which allowed us to relate habitat attributes to relative probability of occurrence and, given the presence of a marked female, abundance of marked individuals. Postbreeding female scaup selected areas with water depths > 40 cm, large open areas, and intermediate edge densities but showed no relation to flooded bare substrate, suggesting their habitat preferences were more influenced by avoiding predation risks and disturbances than in meeting foraging needs. Grouping behavior by postbreeding scaup suggests habitat selection is influenced in part by behavioral components and/or social information, conferring energetic and survival benefits (predation and disturbance risks) but potentially also contributing to competition for food resources. This study demonstrates the importance of incorporating group effects and interannual variability in habitat conditions when investigating habitat selection, particularly for seasons when waterfowl are aggregated.

A Group Decision Framework with Intuitionistic Preference Relations and Its Application to Low Carbon Supplier Selection.

PubMed

Tong, Xiayu; Wang, Zhou-Jing

2016-09-19

This article develops a group decision framework with intuitionistic preference relations. An approach is first devised to rectify an inconsistent intuitionistic preference relation to derive an additive consistent one. A new aggregation operator, the so-called induced intuitionistic ordered weighted averaging (IIOWA) operator, is proposed to aggregate individual intuitionistic fuzzy judgments. By using the mean absolute deviation between the original and rectified intuitionistic preference relations as an order inducing variable, the rectified consistent intuitionistic preference relations are aggregated into a collective preference relation. This treatment is presumably able to assign different weights to different decision-makers' judgments based on the quality of their inputs (in terms of consistency of their original judgments). A solution procedure is then developed for tackling group decision problems with intuitionistic preference relations. A low carbon supplier selection case study is developed to illustrate how to apply the proposed decision model in practice.

A Group Decision Framework with Intuitionistic Preference Relations and Its Application to Low Carbon Supplier Selection

PubMed Central

Tong, Xiayu; Wang, Zhou-Jing

2016-01-01

This article develops a group decision framework with intuitionistic preference relations. An approach is first devised to rectify an inconsistent intuitionistic preference relation to derive an additive consistent one. A new aggregation operator, the so-called induced intuitionistic ordered weighted averaging (IIOWA) operator, is proposed to aggregate individual intuitionistic fuzzy judgments. By using the mean absolute deviation between the original and rectified intuitionistic preference relations as an order inducing variable, the rectified consistent intuitionistic preference relations are aggregated into a collective preference relation. This treatment is presumably able to assign different weights to different decision-makers’ judgments based on the quality of their inputs (in terms of consistency of their original judgments). A solution procedure is then developed for tackling group decision problems with intuitionistic preference relations. A low carbon supplier selection case study is developed to illustrate how to apply the proposed decision model in practice. PMID:27657097

The use of computer-assisted image analysis in the evaluation of the effect of management systems on changes in the color, chemical composition and texture of m. longissimus dorsi in pigs.

PubMed

Zapotoczny, Piotr; Kozera, Wojciech; Karpiesiuk, Krzysztof; Pawłowski, Rodian

2014-08-01

The effect of management systems on selected physical properties and chemical composition of m. longissimus dorsi was studied in pigs. Muscle texture parameters were determined by computer-assisted image analysis, and the color of muscle samples was evaluated using a spectrophotometer. Highly significant correlations were observed between chemical composition and selected texture variables in the analyzed images. Chemical composition was not correlated with color or spectral distribution. Subject to the applied classification methods and groups of variables included in the classification model, the experimental groups were identified correctly in 35-95%. No significant differences in the chemical composition of m. longissimus dorsi were observed between experimental groups. Significant differences were noted in color lightness (L*) and redness (a*). Copyright © 2014 Elsevier Ltd. All rights reserved.

Effects of high-pressure oxygen therapy on brain tissue water content and AQP4 expression in rabbits with cerebral hemorrhage.

PubMed

Wu, Jing; Chen, Jiong; Guo, Hua; Peng, Fang

2014-12-01

To investigate the effects of different atmosphere absolutes (ATA) of high-pressure oxygen (HPO) on brain tissue water content and Aquaporin-4 (AQP4) expression in rabbits with cerebral hemorrhage. 180 New Zealand white rabbits were selected and randomly divided into normal group (n = 30), control group (n = 30) and cerebral hemorrhage group (n = 120), and cerebral hemorrhage group was divided into group A, B, C and D with 30 rabbits in each group. The groups received 1.0, 1.8, 2.0 and 2.2 ATA of HPO treatments, respectively. Ten rabbits in each group were killed at first, third and fifth day to detect the brain tissue water content and change of AQP4 expression. In cerebral hemorrhage group, brain tissue water content and AQP4 expression after model establishment were first increased, then decreased and reached the maximum on third day (p < 0.05). Brain tissue water content and AQP4 expression in control group and cerebral hemorrhage group were significantly higher than normal group at different time points (p < 0.05). In contrast, brain tissue water content and AQP4 expression in group C were significantly lower than in group A, group B, group D and control group (p < 0.05). In control group, AQP4-positive cells significantly increased after model establishment, which reached maximum on third day, and positive cells in group C were significantly less than in group A, group B and group D. We also found that AQP4 expression were positively correlated with brain tissue water content (r = 0.719, p < 0.05) demonstrated by significantly increased AQP4 expression along with increased brain tissue water content. In conclusion, HPO can decrease AQP4 expression in brain tissue of rabbits with cerebral hemorrhage to suppress the progression of brain edema and promote repairing of injured tissue. 2.0 ATA HPO exerts best effects, which provides an experimental basis for ATA selection of HPO in treating cerebral hemorrhage.

Shock Index Correlates with Extravasation on Angiographs of Gastrointestinal Hemorrhage: A Logistics Regression Analysis

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

Nakasone, Yutaka, E-mail: n-yutaka@cd5.so-net.ne.jp; Ikeda, Osamu; Yamashita, Yasuyuki

We applied multivariate analysis to the clinical findings in patients with acute gastrointestinal (GI) hemorrhage and compared the relationship between these findings and angiographic evidence of extravasation. Our study population consisted of 46 patients with acute GI bleeding. They were divided into two groups. In group 1 we retrospectively analyzed 41 angiograms obtained in 29 patients (age range, 25-91 years; average, 71 years). Their clinical findings including the shock index (SI), diastolic blood pressure, hemoglobin, platelet counts, and age, which were quantitatively analyzed. In group 2, consisting of 17 patients (age range, 21-78 years; average, 60 years), we prospectively appliedmore » statistical analysis by a logistics regression model to their clinical findings and then assessed 21 angiograms obtained in these patients to determine whether our model was useful for predicting the presence of angiographic evidence of extravasation. On 18 of 41 (43.9%) angiograms in group 1 there was evidence of extravasation; in 3 patients it was demonstrated only by selective angiography. Factors significantly associated with angiographic visualization of extravasation were the SI and patient age. For differentiation between cases with and cases without angiographic evidence of extravasation, the maximum cutoff point was between 0.51 and 0.0.53. Of the 21 angiograms obtained in group 2, 13 (61.9%) showed evidence of extravasation; in 1 patient it was demonstrated only on selective angiograms. We found that in 90% of the cases, the prospective application of our model correctly predicted the angiographically confirmed presence or absence of extravasation. We conclude that in patients with GI hemorrhage, angiographic visualization of extravasation is associated with the pre-embolization SI. Patients with a high SI value should undergo study to facilitate optimal treatment planning.« less

Selective percutaneous desiccation of the perforators with radiofrequency for strategic transfer of angiosomes in a sequential four-territory cutaneous island flap model.

PubMed

Demirtas, Yener; Ayhan, Suhan; Findikcioglu, Kemal; Yavuzer, Reha; Atabay, Kenan

2007-05-01

Research in prevention of partial flap necrosis has recently concentrated on extending the safe length of a flap by ligating vessels of known territories. To advance this approach one step further, the authors decided to reveal the least invasive surgical strategy for transfer of angiosomes. The study was arranged into three experiments. In the first experiment (n = 17 rabbits), a cutaneous island flap model spanning four adjacent vascular territories was developed. In the second experiment (n = 15 rabbits), the flap model was used to test the possibility of desiccating those vessels supplying the angiosomes to be captured percutaneously with radiofrequency. The delay procedures were performed by means of minimal skin incisions, and the flaps were elevated after a 2-week delay period. In the third experiment, the effectiveness of selective interference of these pedicles was compared to minimize the number of target vessels for successful transfer of angiosomes. The mean surviving area of the new flap model was 63 +/- 2 percent. The mean surviving flap area was 97 +/- 3 percent for the endoscopy equivalent technique and 94 +/- 4 percent for radiofrequency delay. The results were statistically insignificant between these two groups. In experiment 3, comparison of the results yielded a statistically insignificant difference for flap survival area among all four of the groups. An alternative flap model is introduced for future investigation of the vascular delay process. Percutaneous desiccation of the perforators with radiofrequency was found to be a reliable method, and selective desiccation of the perforator(s) was as efficient as destruction of all vascular sources other than the pedicle.

Population Structure, Diversity and Trait Association Analysis in Rice (Oryza sativa L.) Germplasm for Early Seedling Vigor (ESV) Using Trait Linked SSR Markers

PubMed Central

Anandan, Annamalai; Anumalla, Mahender; Pradhan, Sharat Kumar; Ali, Jauhar

2016-01-01

Early seedling vigor (ESV) is the essential trait for direct seeded rice to dominate and smother the weed growth. In this regard, 629 rice genotypes were studied for their morphological and physiological responses in the field under direct seeded aerobic situation on 14th, 28th and 56th days after sowing (DAS). It was determined that the early observations taken on 14th and 28th DAS were reliable estimators to study ESV as compared to56th DAS. Further, 96 were selected from 629 genotypes by principal component (PCA) and discriminate function analyses. The selected genotypes were subjected to decipher the pattern of genetic diversity in terms of both phenotypic and genotypic by using ESV QTL linked simple sequence repeat (SSR) markers. To assess the genetic structure, model and distance based approaches were used. Genotyping of 96 rice lines using 39 polymorphic SSRs produced a total of 128 alleles with the phenotypic information content (PIC) value of 0.24. The model based population structure approach grouped the accession into two distinct populations, whereas unrooted tree grouped the genotypes into three clusters. Both model based and structure based approach had clearly distinguished the early vigor genotypes from non-early vigor genotypes. Association analysis revealed that 16 and 10 SSRs showed significant association with ESV traits by general linear model (GLM) and mixed linear model (MLM) approaches respectively. Marker alleles on chromosome 2 were associated with shoot dry weight on 28 DAS, vigor index on 14 and 28 DAS. Improvement in the rate of seedling growth will be useful for identifying rice genotypes acquiescent to direct seeded conditions through marker-assisted selection. PMID:27031620

Transformation and model choice for RNA-seq co-expression analysis.

PubMed

Rau, Andrea; Maugis-Rabusseau, Cathy

2018-05-01

Although a large number of clustering algorithms have been proposed to identify groups of co-expressed genes from microarray data, the question of if and how such methods may be applied to RNA sequencing (RNA-seq) data remains unaddressed. In this work, we investigate the use of data transformations in conjunction with Gaussian mixture models for RNA-seq co-expression analyses, as well as a penalized model selection criterion to select both an appropriate transformation and number of clusters present in the data. This approach has the advantage of accounting for per-cluster correlation structures among samples, which can be strong in RNA-seq data. In addition, it provides a rigorous statistical framework for parameter estimation, an objective assessment of data transformations and number of clusters and the possibility of performing diagnostic checks on the quality and homogeneity of the identified clusters. We analyze four varied RNA-seq data sets to illustrate the use of transformations and model selection in conjunction with Gaussian mixture models. Finally, we propose a Bioconductor package coseq (co-expression of RNA-seq data) to facilitate implementation and visualization of the recommended RNA-seq co-expression analyses.

Selection of appropriate reference genes for RT-qPCR analysis in a streptozotocin-induced Alzheimer's disease model of cynomolgus monkeys (Macaca fascicularis).

PubMed

Park, Sang-Je; Kim, Young-Hyun; Lee, Youngjeon; Kim, Kyoung-Min; Kim, Heui-Soo; Lee, Sang-Rae; Kim, Sun-Uk; Kim, Sang-Hyun; Kim, Ji-Su; Jeong, Kang-Jin; Lee, Kyoung-Min; Huh, Jae-Won; Chang, Kyu-Tae

2013-01-01

Reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) has been widely used to quantify relative gene expression because of the specificity, sensitivity, and accuracy of this technique. In order to obtain reliable gene expression data from RT-qPCR experiments, it is important to utilize optimal reference genes for the normalization of target gene expression under varied experimental conditions. Previously, we developed and validated a novel icv-STZ cynomolgus monkey model for Alzheimer's disease (AD) research. However, in order to enhance the reliability of this disease model, appropriate reference genes must be selected to allow meaningful analysis of the gene expression levels in the icv-STZ cynomolgus monkey brain. In this study, we assessed the expression stability of 9 candidate reference genes in 2 matched-pair brain samples (5 regions) of control cynomolgus monkeys and those who had received intracerebroventricular injection of streptozotocin (icv-STZ). Three well-known analytical programs geNorm, NormFinder, and BestKeeper were used to choose the suitable reference genes from the total sample group, control group, and icv-STZ group. Combination analysis of the 3 different programs clearly indicated that the ideal reference genes are RPS19 and YWHAZ in the total sample group, GAPDH and RPS19 in the control group, and ACTB and GAPDH in the icv-STZ group. Additionally, we validated the normalization accuracy of the most appropriate reference genes (RPS19 and YWHAZ) by comparison with the least stable gene (TBP) using quantification of the APP and MAPT genes in the total sample group. To the best of our knowledge, this research is the first study to identify and validate the appropriate reference genes in cynomolgus monkey brains. These findings provide useful information for future studies involving the expression of target genes in the cynomolgus monkey.

Empathic skills and theory of mind in female adolescents with conduct disorder.

PubMed

Arango Tobón, Olber E; Olivera-La Rosa, Antonio; Restrepo Tamayo, Viviana; Puerta Lopera, Isabel C

2018-01-01

Most studies on conduct disorder (CD) have focused on male adolescents, disregarding analysis of this psychopathology in women. The purpose of this study was to identify differences in empathy and theory of mind (ToM) in a group of adolescent women with CD and a control group. Thirty-six adolescent women were selected from an initial sample of 239 adolescents (CD group = 18, control group = 18). Empathy and ToM were evaluated through objective instruments. Mean comparisons and multivariate analysis were performed to ascertain differences between cases and controls and to propose a prediction model based on clinical status. Significant differences in empathic abilities and ToM were found between the groups. The model that differentiated both groups was composed of eye-reading ability, perspective taking, and personal distress. These findings are consistent with previous studies. Capacity to take the other's perspective and the recognition of emotions in the face are protective factors against CD in women.

Group III metabotropic glutamate receptors inhibit hyperalgesia in animal models of inflammation and neuropathic pain.

PubMed

Goudet, Cyril; Chapuy, Eric; Alloui, Abdelkrim; Acher, Francine; Pin, Jean-Philippe; Eschalier, Alain

2008-07-01

Glutamate plays a key role in modulation of nociceptive processing. This excitatory amino acid exerts its action through two distinct types of receptors, ionotropic and metabotropic glutamate receptors (mGluRs). Eight mGluRs have been identified and divided in three groups based on their sequence similarity, pharmacology and G-protein coupling. While the role of group I and II mGluRs is now well established, little is known about the part played by group III mGluRs in pain. In this work, we studied comparatively the involvement of spinal group III mGluR in modulation of acute, inflammatory and neuropathic pain. While intrathecal injection of ACPT-I, a selective group III mGluR agonist, failed to induce any change in vocalization thresholds of healthy animals submitted to mechanical or thermal stimuli, it dose-dependently inhibited the nociceptive behavior of rats submitted to the formalin test and the mechanical hyperalgesia associated with different animal models of inflammatory (carrageenan-treated and monoarthritic rats) or neuropathic pain (mononeuropathic and vincristine-treated rats). Similar effects were also observed following intrathecal injection of PHCCC, a positive allosteric modulator of mGlu4. Antihyperalgesia induced by ACPT-I was blocked either by LY341495, a nonselective antagonist of mGluR, by MAP4, a selective group III antagonist. This study provide new evidences supporting the role of spinal group III mGluRs in the modulation of pain perception in different pathological pain states of various etiologies but not in normal conditions. It more particularly highlights the specific involvement of mGlu4 in this process and may be a useful therapeutic approach to chronic pain treatment.

Combining cow and bull reference populations to increase accuracy of genomic prediction and genome-wide association studies.

PubMed

Calus, M P L; de Haas, Y; Veerkamp, R F

2013-10-01

Genomic selection holds the promise to be particularly beneficial for traits that are difficult or expensive to measure, such that access to phenotypes on large daughter groups of bulls is limited. Instead, cow reference populations can be generated, potentially supplemented with existing information from the same or (highly) correlated traits available on bull reference populations. The objective of this study, therefore, was to develop a model to perform genomic predictions and genome-wide association studies based on a combined cow and bull reference data set, with the accuracy of the phenotypes differing between the cow and bull genomic selection reference populations. The developed bivariate Bayesian stochastic search variable selection model allowed for an unbalanced design by imputing residuals in the residual updating scheme for all missing records. The performance of this model is demonstrated on a real data example, where the analyzed trait, being milk fat or protein yield, was either measured only on a cow or a bull reference population, or recorded on both. Our results were that the developed bivariate Bayesian stochastic search variable selection model was able to analyze 2 traits, even though animals had measurements on only 1 of 2 traits. The Bayesian stochastic search variable selection model yielded consistently higher accuracy for fat yield compared with a model without variable selection, both for the univariate and bivariate analyses, whereas the accuracy of both models was very similar for protein yield. The bivariate model identified several additional quantitative trait loci peaks compared with the single-trait models on either trait. In addition, the bivariate models showed a marginal increase in accuracy of genomic predictions for the cow traits (0.01-0.05), although a greater increase in accuracy is expected as the size of the bull population increases. Our results emphasize that the chosen value of priors in Bayesian genomic prediction models are especially important in small data sets. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Selective attention in an insect visual neuron.

PubMed

Wiederman, Steven D; O'Carroll, David C

2013-01-21

Animals need attention to focus on one target amid alternative distracters. Dragonflies, for example, capture flies in swarms comprising prey and conspecifics, a feat that requires neurons to select one moving target from competing alternatives. Diverse evidence, from functional imaging and physiology to psychophysics, highlights the importance of such "competitive selection" in attention for vertebrates. Analogous mechanisms have been proposed in artificial intelligence and even in invertebrates, yet direct neural correlates of attention are scarce from all animal groups. Here, we demonstrate responses from an identified dragonfly visual neuron that perfectly match a model for competitive selection within limits of neuronal variability (r(2) = 0.83). Responses to individual targets moving at different locations within the receptive field differ in both magnitude and time course. However, responses to two simultaneous targets exclusively track those for one target alone rather than any combination of the pair. Irrespective of target size, contrast, or separation, this neuron selects one target from the pair and perfectly preserves the response, regardless of whether the "winner" is the stronger stimulus if presented alone. This neuron is amenable to electrophysiological recordings, providing neuroscientists with a new model system for studying selective attention. Copyright © 2013 Elsevier Ltd. All rights reserved.

Diet Quality and Physical Activity Outcome Improvements Resulting From a Church-Based Diet and Supervised Physical Activity Intervention for Rural, Southern, African American Adults: Delta Body and Soul III.

PubMed

Thomson, Jessica L; Goodman, Melissa H; Tussing-Humphreys, Lisa

2015-09-01

We assessed the effects of a 6-month, church-based, diet and supervised physical activity intervention, conducted between 2011 and 2012, on improving diet quality and increasing physical activity of Southern, African American adults. Using a quasi-experimental design, eight self-selected, eligible churches were assigned to intervention or control. Assessments included dietary, physical activity, anthropometric, and clinical measures. Mixed model regression analysis and McNemar's test were used to determine if within and between group differences were significant. Cohen's d effect sizes for selected outcomes also were computed and compared with an earlier, lower dose intervention. Retention rates were 84% (102/122) for control and 76% (219/287) for intervention participants. Diet quality components, including fruits, vegetables, discretionary calories, and total quality, improved significantly in the intervention group. Strength/flexibility physical activity also increased in the intervention group, while both aerobic and strength/flexibility physical activity significantly decreased in the control group. Effect sizes for selected health outcomes were larger in the current intervention as compared to an earlier, less intense iteration of the study. Results suggest that more frequent education sessions as well as supervised group physical activity may be key components to increasing the efficacy of behavioral lifestyle interventions in rural, Southern, African American adults. © 2015 Society for Public Health Education.

TH-A-9A-01: Active Optical Flow Model: Predicting Voxel-Level Dose Prediction in Spine SBRT

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

Liu, J; Wu, Q.J.; Yin, F

2014-06-15

Purpose: To predict voxel-level dose distribution and enable effective evaluation of cord dose sparing in spine SBRT. Methods: We present an active optical flow model (AOFM) to statistically describe cord dose variations and train a predictive model to represent correlations between AOFM and PTV contours. Thirty clinically accepted spine SBRT plans are evenly divided into training and testing datasets. The development of predictive model consists of 1) collecting a sequence of dose maps including PTV and OAR (spinal cord) as well as a set of associated PTV contours adjacent to OAR from the training dataset, 2) classifying data into fivemore » groups based on PTV's locations relative to OAR, two “Top”s, “Left”, “Right”, and “Bottom”, 3) randomly selecting a dose map as the reference in each group and applying rigid registration and optical flow deformation to match all other maps to the reference, 4) building AOFM by importing optical flow vectors and dose values into the principal component analysis (PCA), 5) applying another PCA to features of PTV and OAR contours to generate an active shape model (ASM), and 6) computing a linear regression model of correlations between AOFM and ASM.When predicting dose distribution of a new case in the testing dataset, the PTV is first assigned to a group based on its contour characteristics. Contour features are then transformed into ASM's principal coordinates of the selected group. Finally, voxel-level dose distribution is determined by mapping from the ASM space to the AOFM space using the predictive model. Results: The DVHs predicted by the AOFM-based model and those in clinical plans are comparable in training and testing datasets. At 2% volume the dose difference between predicted and clinical plans is 4.2±4.4% and 3.3±3.5% in the training and testing datasets, respectively. Conclusion: The AOFM is effective in predicting voxel-level dose distribution for spine SBRT. Partially supported by NIH/NCI under grant #R21CA161389 and a master research grant by Varian Medical System.« less

Status and Future of the Naval R&D Establishment

DTIC Science & Technology

2010-09-01

above or by innovating in business models to create new markets (e.g., iTunes , iPhone App Store). The secret sauce allows Apple to 17...DASN C3I gave them a mixed report card as did ONR and DARPA who stated that they use selected individuals or small groups at the Centers but not...heavily on SSC LANT. However, DASN C3I gave them a mixed report card as did ONR and DARPA who stated that they use selected individuals or small

Accounting for Genotype-by-Environment Interactions and Residual Genetic Variation in Genomic Selection for Water-Soluble Carbohydrate Concentration in Wheat.

PubMed

Ovenden, Ben; Milgate, Andrew; Wade, Len J; Rebetzke, Greg J; Holland, James B

2018-05-31

Abiotic stress tolerance traits are often complex and recalcitrant targets for conventional breeding improvement in many crop species. This study evaluated the potential of genomic selection to predict water-soluble carbohydrate concentration (WSCC), an important drought tolerance trait, in wheat under field conditions. A panel of 358 varieties and breeding lines constrained for maturity was evaluated under rainfed and irrigated treatments across two locations and two years. Whole-genome marker profiles and factor analytic mixed models were used to generate genomic estimated breeding values (GEBVs) for specific environments and environment groups. Additive genetic variance was smaller than residual genetic variance for WSCC, such that genotypic values were dominated by residual genetic effects rather than additive breeding values. As a result, GEBVs were not accurate predictors of genotypic values of the extant lines, but GEBVs should be reliable selection criteria to choose parents for intermating to produce new populations. The accuracy of GEBVs for untested lines was sufficient to increase predicted genetic gain from genomic selection per unit time compared to phenotypic selection if the breeding cycle is reduced by half by the use of GEBVs in off-season generations. Further, genomic prediction accuracy depended on having phenotypic data from environments with strong correlations with target production environments to build prediction models. By combining high-density marker genotypes, stress-managed field evaluations, and mixed models that model simultaneously covariances among genotypes and covariances of complex trait performance between pairs of environments, we were able to train models with good accuracy to facilitate genetic gain from genomic selection. Copyright © 2018 Ovenden et al.

Comparison of the selection of antimicrobial resistance in fecal Escherichia coli during enrofloxacin administration with a local drug delivery system or with intramuscular injections in a swine model

PubMed Central

Béraud, Romain; Huneault, Louis; Bernier, Dave; Beaudry, Francis; Letellier, Ann; del Castillo, Jérôme R.E.

2008-01-01

This study evaluated, for the first time, the selection of antibiotic resistance in fecal Escherichia coli, a potential reservoir of genes of resistance, during the prolonged exposure to fluoroquinolones after the implantation of a local drug delivery system (LDDS) in a swine model. Fourteen pigs were randomly assigned to group IM (5 mg/kg/day of intramuscular enrofloxacin — EFX) or LD (surgical implantation of EFX-polymethyl-methacrylate perifemoral implants). Blood samples were collected daily for determination of plasma EFX and ciprofloxacin (CFX) concentrations. Fecal samples were collected daily to determine the E. coli counts and the susceptibility patterns of its isolates as evaluated by antibiotic disk diffusion tests. In both groups, EFX administration significantly reduced the bacterial counts after 2 days. During recolonization, the bacterial counts remained lower than baseline in group IM but not significantly, and almost reached pre-treatment levels in group LD. Susceptibility to EFX, CFX, and nalidixic acid of recolonizing E. coli in LD pigs slightly decreased but remained within the limit of “susceptible” isolates. In contrast, quinolone susceptibility of recolonizing E. coli in IM pigs dropped dramatically (P < 0.0001). In addition, intramuscular exposure to fluoroquinolones significantly decreased the susceptibility of E. coli to ampicillin and trimethoprim-sulfamethoxazole (P < 0.05). In conclusion, the use of a dosing regimen that minimized the intestinal output of fluoroquinolones also minimized the selection of resistance to several classes of antibiotics. This could represent another advantage of LDDS usage compared to long-lasting systemic administration of fluoroquinolones. PMID:18783019

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

PubMed

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

2017-03-01

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

Evaluating intra- and inter-individual variation in the human placental transcriptome.

PubMed

Hughes, David A; Kircher, Martin; He, Zhisong; Guo, Song; Fairbrother, Genevieve L; Moreno, Carlos S; Khaitovich, Philipp; Stoneking, Mark

2015-03-19

Gene expression variation is a phenotypic trait of particular interest as it represents the initial link between genotype and other phenotypes. Analyzing how such variation apportions among and within groups allows for the evaluation of how genetic and environmental factors influence such traits. It also provides opportunities to identify genes and pathways that may have been influenced by non-neutral processes. Here we use a population genetics framework and next generation sequencing to evaluate how gene expression variation is apportioned among four human groups in a natural biological tissue, the placenta. We estimate that on average, 33.2%, 58.9%, and 7.8% of the placental transcriptome is explained by variation within individuals, among individuals, and among human groups, respectively. Additionally, when technical and biological traits are included in models of gene expression they each account for roughly 2% of total gene expression variation. Notably, the variation that is significantly different among groups is enriched in biological pathways associated with immune response, cell signaling, and metabolism. Many biological traits demonstrate correlated changes in expression in numerous pathways of potential interest to clinicians and evolutionary biologists. Finally, we estimate that the majority of the human placental transcriptome exhibits expression profiles consistent with neutrality; the remainder are consistent with stabilizing selection, directional selection, or diversifying selection. We apportion placental gene expression variation into individual, population, and biological trait factors and identify how each influence the transcriptome. Additionally, we advance methods to associate expression profiles with different forms of selection.

Acute exercise and aerobic fitness influence selective attention during visual search.

PubMed

Bullock, Tom; Giesbrecht, Barry

2014-01-01

Successful goal directed behavior relies on a human attention system that is flexible and able to adapt to different conditions of physiological stress. However, the effects of physical activity on multiple aspects of selective attention and whether these effects are mediated by aerobic capacity, remains unclear. The aim of the present study was to investigate the effects of a prolonged bout of physical activity on visual search performance and perceptual distraction. Two groups of participants completed a hybrid visual search flanker/response competition task in an initial baseline session and then at 17-min intervals over a 2 h 16 min test period. Participants assigned to the exercise group engaged in steady-state aerobic exercise between completing blocks of the visual task, whereas participants assigned to the control group rested in between blocks. The key result was a correlation between individual differences in aerobic capacity and visual search performance, such that those individuals that were more fit performed the search task more quickly. Critically, this relationship only emerged in the exercise group after the physical activity had begun. The relationship was not present in either group at baseline and never emerged in the control group during the test period, suggesting that under these task demands, aerobic capacity may be an important determinant of visual search performance under physical stress. The results enhance current understanding about the relationship between exercise and cognition, and also inform current models of selective attention.

Acute exercise and aerobic fitness influence selective attention during visual search

PubMed Central

Bullock, Tom; Giesbrecht, Barry

2014-01-01

Successful goal directed behavior relies on a human attention system that is flexible and able to adapt to different conditions of physiological stress. However, the effects of physical activity on multiple aspects of selective attention and whether these effects are mediated by aerobic capacity, remains unclear. The aim of the present study was to investigate the effects of a prolonged bout of physical activity on visual search performance and perceptual distraction. Two groups of participants completed a hybrid visual search flanker/response competition task in an initial baseline session and then at 17-min intervals over a 2 h 16 min test period. Participants assigned to the exercise group engaged in steady-state aerobic exercise between completing blocks of the visual task, whereas participants assigned to the control group rested in between blocks. The key result was a correlation between individual differences in aerobic capacity and visual search performance, such that those individuals that were more fit performed the search task more quickly. Critically, this relationship only emerged in the exercise group after the physical activity had begun. The relationship was not present in either group at baseline and never emerged in the control group during the test period, suggesting that under these task demands, aerobic capacity may be an important determinant of visual search performance under physical stress. The results enhance current understanding about the relationship between exercise and cognition, and also inform current models of selective attention. PMID:25426094

Effects of cisatracurium in combination with ventilation on inflammatory factors and immune variations in sepsis rats.

PubMed

He, Tongyun; Tao, Jianmei; Wang, Xinqiang; Wang, Xuena

2018-05-01

The effects of cisatracurium in combination with ventilation on inflammatory factors and immune variations in sepsis rats were investigated. A total of 54 male Sprague-Dawley rats were selected and divided randomly into three groups: Sham group (n=6), model group (n=24) and experiment group (n=24). Rats in the model and experiment groups underwent cecal ligation and puncture (CLP) for establishment of sepsis model. Rats in experiment group additionally received cisatracurium medication in combination with ventilation for treatment. At 6, 12 and 24 h after CLP, the levels of tumor necrosis factor (TNF)-α, interleukin (IL)-1β, IL-6 and procalcitonin (PCT) in serum and the ratio of leukocyte to neutrophil in peripheral blood was also detected. Twenty-four hours later, the expression of high mobility group box 1 (HMGB1) in lung tissues and cluster of differentiation (CD) 4 + and CD8 + in T-lymphocyte subsets were also detected, and the wet/dry (W/D) ratio of lung was measured. Compared with that in model group, the levels of inflammatory factors in the experiment group were significantly decreased, while the indicators in assays of cellular immunity were obviously elevated. Ratio of leukocyte to neutrophil in peripheral blood was significantly decreased after treatment. Cisatracurium in combination with ventilation can alleviate the inflammatory injury to organs in sepsis rats through inhibiting the inflammatory responses and regulating the immune functions, which manifests a new significance in guiding the clinical diagnosis and treatment.

Neuroprotective effects of agmatine in experimental peripheral nerve injury in rats: a prospective randomized and placebo-controlled trial.

PubMed

Sezer, Aykut; Guclu, Bulent; Kazanci, Burak; Cakir, Murteza; Coban, Mustafa Kemal

2014-01-01

The purpose of this study was to demonstrate the activity of agmatine, an inducible nitric oxide synthase (iNOS) inhibitor and selective N-methyl-D-aspartate receptor (NMDAR) antagonist, on reducing tissue damage in distal part of traumatic nerve in an experimental rat peripheral nerve injury model. Sciatic nerves of 30 Sprague Dawley male rats were used. Rats were divided into 5 groups; group 1 (n=6), control group; group 2 (n=6), axonotmesis + placebo group; group 3 (n=6), axonotmesis + 50 mg/kg agmatine treatment group; group 4 (n=6), neurotmesis + placebo group; group 5 (n=6), neurotmesis + 50 mg/kg agmatine treatment group. Axonolysis, axon degeneration, edema, hemorrhage, and inflammation were evaluated in histopathologic examinations of all the groups. When group 2 was compared with group 3 in histopathologic sections, axonolysis was less in group 3 (p=0.007), as was axon degeneration (p=0.022) and edema (p=0.018). When group 4 was compared with group 5, axonolysis was less in group 5 (p=0.009), as was axon degeneration (p=0.006) and edema (p=0.021). This study demonstrated agmatine to have antioxidant and antineurotoxic effects in an experimental rat peripheral nerve injury model.

Infanticide and within-clutch competition select for reproductive synchrony in a cooperative bird.

PubMed

Riehl, Christina

2016-08-01

Reproduction among members of social animal groups is often highly synchronized, but neither the selective advantages nor the proximate causes of synchrony are fully understood. Here I investigate the evolution of hatching synchrony in the Greater Ani (Crotophaga major), a communally nesting bird in which several unrelated females contribute eggs to a large, shared clutch. Hatching synchrony is variable, ranging from complete synchrony to moderate asynchrony, and is determined by the onset of incubation of the communal clutch. Data from a 10-year field study indicate that individual reproductive success is highest in synchronous groups, and that nestlings that hatch in the middle of the hatching sequence are most likely to survive. Nestling mortality is high in asynchronous clutches because early-hatching nestlings are more likely to be killed by adult group members, whereas late-hatching nestlings are more likely to starve due competition with their older nest-mates. Therefore, the timing of hatching appears to be under stabilizing selection from infanticide and resource competition acting in concert. These results provide empirical support for models predicting that synchrony may evolve as an adaptive counter-strategy to infanticide, and they highlight the importance of competition in shaping the timing of reproduction in social groups. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

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

PubMed Central

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

2010-01-01

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

Information Memory Processing and Retrieval: Relationships of the Intellect with the Processing of a Learning and Cognition Task.

ERIC Educational Resources Information Center

Moser, Gene W.

Reported is one of a series of investigations of the Project on an Information Memory Model. This study was done to test an information memory model for identifying the unit of information structure involved in task cognitions by humans. Four groups of 30 randomly selected subjects (ages 7, 9, 11 and 15 years) performed a sorting task of 14…

Dealing with Multiple Solutions in Structural Vector Autoregressive Models.

PubMed

Beltz, Adriene M; Molenaar, Peter C M

2016-01-01

Structural vector autoregressive models (VARs) hold great potential for psychological science, particularly for time series data analysis. They capture the magnitude, direction of influence, and temporal (lagged and contemporaneous) nature of relations among variables. Unified structural equation modeling (uSEM) is an optimal structural VAR instantiation, according to large-scale simulation studies, and it is implemented within an SEM framework. However, little is known about the uniqueness of uSEM results. Thus, the goal of this study was to investigate whether multiple solutions result from uSEM analysis and, if so, to demonstrate ways to select an optimal solution. This was accomplished with two simulated data sets, an empirical data set concerning children's dyadic play, and modifications to the group iterative multiple model estimation (GIMME) program, which implements uSEMs with group- and individual-level relations in a data-driven manner. Results revealed multiple solutions when there were large contemporaneous relations among variables. Results also verified several ways to select the correct solution when the complete solution set was generated, such as the use of cross-validation, maximum standardized residuals, and information criteria. This work has immediate and direct implications for the analysis of time series data and for the inferences drawn from those data concerning human behavior.

An Integrated model for Product Quality Development—A case study on Quality functions deployment and AHP based approach

NASA Astrophysics Data System (ADS)

Maitra, Subrata; Banerjee, Debamalya

2010-10-01

Present article is based on application of the product quality and improvement of design related with the nature of failure of machineries and plant operational problems of an industrial blower fan Company. The project aims at developing the product on the basis of standardized production parameters for selling its products in the market. Special attention is also being paid to the blower fans which have been ordered directly by the customer on the basis of installed capacity of air to be provided by the fan. Application of quality function deployment is primarily a customer oriented approach. Proposed model of QFD integrated with AHP to select and rank the decision criterions on the commercial and technical factors and the measurement of the decision parameters for selection of best product in the compettitive environment. The present AHP-QFD model justifies the selection of a blower fan with the help of the group of experts' opinion by pairwise comparison of the customer's and ergonomy based technical design requirements. The steps invoved in implementation of the QFD—AHP and selection of weighted criterion may be helpful for all similar purpose industries maintaining cost and utility for competitive product.

Multivariate analysis of volatile compounds detected by headspace solid-phase microextraction/gas chromatography: A tool for sensory classification of cork stoppers.

PubMed

Prat, Chantal; Besalú, Emili; Bañeras, Lluís; Anticó, Enriqueta

2011-06-15

The volatile fraction of aqueous cork macerates of tainted and non-tainted agglomerate cork stoppers was analysed by headspace solid-phase microextraction (HS-SPME)/gas chromatography. Twenty compounds containing terpenoids, aliphatic alcohols, lignin-related compounds and others were selected and analysed in individual corks. Cork stoppers were previously classified in six different classes according to sensory descriptions including, 2,4,6-trichloroanisole taint and other frequent, non-characteristic odours found in cork. A multivariate analysis of the chromatographic data of 20 selected chemical compounds using linear discriminant analysis models helped in the differentiation of the a priori made groups. The discriminant model selected five compounds as the best combination. Selected compounds appear in the model in the following order; 2,4,6 TCA, fenchyl alcohol, 1-octen-3-ol, benzyl alcohol and benzothiazole. Unfortunately, not all six a priori differentiated sensory classes were clearly discriminated in the model, probably indicating that no measurable differences exist in the chromatographic data for some categories. The predictive analyses of a refined model in which two sensory classes were fused together resulted in a good classification. Prediction rates of control (non-tainted), TCA, musty-earthy-vegetative, vegetative and chemical descriptions were 100%, 100%, 85%, 67.3% and 100%, respectively, when the modified model was used. The multivariate analysis of chromatographic data will help in the classification of stoppers and provide a perfect complement to sensory analyses. Copyright © 2010 Elsevier Ltd. All rights reserved.

Criterion learning in rule-based categorization: Simulation of neural mechanism and new data

PubMed Central

Helie, Sebastien; Ell, Shawn W.; Filoteo, J. Vincent; Maddox, W. Todd

2015-01-01

In perceptual categorization, rule selection consists of selecting one or several stimulus-dimensions to be used to categorize the stimuli (e.g, categorize lines according to their length). Once a rule has been selected, criterion learning consists of defining how stimuli will be grouped using the selected dimension(s) (e.g., if the selected rule is line length, define ‘long’ and ‘short’). Very little is known about the neuroscience of criterion learning, and most existing computational models do not provide a biological mechanism for this process. In this article, we introduce a new model of rule learning called Heterosynaptic Inhibitory Criterion Learning (HICL). HICL includes a biologically-based explanation of criterion learning, and we use new category-learning data to test key aspects of the model. In HICL, rule selective cells in prefrontal cortex modulate stimulus-response associations using pre-synaptic inhibition. Criterion learning is implemented by a new type of heterosynaptic error-driven Hebbian learning at inhibitory synapses that uses feedback to drive cell activation above/below thresholds representing ionic gating mechanisms. The model is used to account for new human categorization data from two experiments showing that: (1) changing rule criterion on a given dimension is easier if irrelevant dimensions are also changing (Experiment 1), and (2) showing that changing the relevant rule dimension and learning a new criterion is more difficult, but also facilitated by a change in the irrelevant dimension (Experiment 2). We conclude with a discussion of some of HICL’s implications for future research on rule learning. PMID:25682349

Criterion learning in rule-based categorization: simulation of neural mechanism and new data.

PubMed

Helie, Sebastien; Ell, Shawn W; Filoteo, J Vincent; Maddox, W Todd

2015-04-01

In perceptual categorization, rule selection consists of selecting one or several stimulus-dimensions to be used to categorize the stimuli (e.g., categorize lines according to their length). Once a rule has been selected, criterion learning consists of defining how stimuli will be grouped using the selected dimension(s) (e.g., if the selected rule is line length, define 'long' and 'short'). Very little is known about the neuroscience of criterion learning, and most existing computational models do not provide a biological mechanism for this process. In this article, we introduce a new model of rule learning called Heterosynaptic Inhibitory Criterion Learning (HICL). HICL includes a biologically-based explanation of criterion learning, and we use new category-learning data to test key aspects of the model. In HICL, rule selective cells in prefrontal cortex modulate stimulus-response associations using pre-synaptic inhibition. Criterion learning is implemented by a new type of heterosynaptic error-driven Hebbian learning at inhibitory synapses that uses feedback to drive cell activation above/below thresholds representing ionic gating mechanisms. The model is used to account for new human categorization data from two experiments showing that: (1) changing rule criterion on a given dimension is easier if irrelevant dimensions are also changing (Experiment 1), and (2) showing that changing the relevant rule dimension and learning a new criterion is more difficult, but also facilitated by a change in the irrelevant dimension (Experiment 2). We conclude with a discussion of some of HICL's implications for future research on rule learning. Copyright © 2015 Elsevier Inc. All rights reserved.

A new data-driven model for post-transplant antibody dynamics in high risk kidney transplantation.

PubMed

Zhang, Yan; Briggs, David; Lowe, David; Mitchell, Daniel; Daga, Sunil; Krishnan, Nithya; Higgins, Robert; Khovanova, Natasha

2017-02-01

The dynamics of donor specific human leukocyte antigen antibodies during early stage after kidney transplantation are of great clinical interest as these antibodies are considered to be associated with short and long term clinical outcomes. The limited number of antibody time series and their diverse patterns have made the task of modelling difficult. Focusing on one typical post-transplant dynamic pattern with rapid falls and stable settling levels, a novel data-driven model has been developed for the first time. A variational Bayesian inference method has been applied to select the best model and learn its parameters for 39 time series from two groups of graft recipients, i.e. patients with and without acute antibody-mediated rejection (AMR) episodes. Linear and nonlinear dynamic models of different order were attempted to fit the time series, and the third order linear model provided the best description of the common features in both groups. Both deterministic and stochastic parameters are found to be significantly different in the AMR and no-AMR groups showing that the time series in the AMR group have significantly higher frequency of oscillations and faster dissipation rates. This research may potentially lead to better understanding of the immunological mechanisms involved in kidney transplantation. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

The CERAD Neuropsychological Assessment Battery Is Sensitive to Alcohol-Related Cognitive Deficiencies in Elderly Patients: A Retrospective Matched Case-Control Study.

PubMed

Kaufmann, Liane; Huber, Stefan; Mayer, Daniel; Moeller, Korbinian; Marksteiner, Josef

2018-04-01

Adverse effects of heavy drinking on cognition have frequently been reported. In the present study, we systematically examined for the first time whether clinical neuropsychological assessments may be sensitive to alcohol abuse in elderly patients with suspected minor neurocognitive disorder. A total of 144 elderly with and without alcohol abuse (each group n=72; mean age 66.7 years) were selected from a patient pool of n=738 by applying propensity score matching (a statistical method allowing to match participants in experimental and control group by balancing various covariates to reduce selection bias). Accordingly, study groups were almost perfectly matched regarding age, education, gender, and Mini Mental State Examination score. Neuropsychological performance was measured using the CERAD (Consortium to Establish a Registry for Alzheimer's Disease). Classification analyses (i.e., decision tree and boosted trees models) were conducted to examine whether CERAD variables or total score contributed to group classification. Decision tree models disclosed that groups could be reliably classified based on the CERAD variables "Word List Discriminability" (tapping verbal recognition memory, 64% classification accuracy) and "Trail Making Test A" (measuring visuo-motor speed, 59% classification accuracy). Boosted tree analyses further indicated the sensitivity of "Word List Recall" (measuring free verbal recall) for discriminating elderly with versus without a history of alcohol abuse. This indicates that specific CERAD variables seem to be sensitive to alcohol-related cognitive dysfunctions in elderly patients with suspected minor neurocognitive disorder. (JINS, 2018, 24, 360-371).

Selective Thinning of the Perifoveal Inner Retina as an Early Sign of Hydroxychloroquine Retinal Toxicity

PubMed Central

Pasadhika, Sirichai; Fishman, Gerald A; Choi, Dongseok; Shahidi, Mahnaz

2013-01-01

Purpose To evaluate macular thickness profiles using spectral-domain optical coherence tomography (SDOCT) and image segmentation in patients with chronic exposure to hydroxychloroquine. Methods This study included 8 patients with chronic exposure to hydroxychloroquine (Group 1) and 8 controls (Group 2). Group 1 patients had no clinically-evident retinal toxicity. All subjects underwent SDOCT imaging of the macula. An image segmentation technique was used to measure thickness of 6 retinal layers at 200 µm intervals. A mixed-effects model was used for multivariate analysis. Results By measuring total retinal thickness either at the central macular (2800 µm in diameter), the perifoveal region 1200-µm-width ring surrounding the central macula), or the overall macular area (5200 µm in diameter), there were no significant differences in the thickness between Groups 1 and 2. On an image segmentation analysis, selective thinning of the inner plexiform + ganglion cell layers (p=0.021) was observed only in the perifoveal area of the patients in Group 1 compared to that of Group 2 by using the mixed-effects model analysis. Conclusions Our results suggest that chronic exposure to hydroxychloroquine is associated with thinning of the perifoveal inner retinal layers, especially in the ganglion cell and inner plexiform layers, even in the absence of functional or structural clinical changes involving the photoreceptor or retinal pigment epithelial cell layers. This may be a contributing factor as the reason most patients who have early detectable signs of drug toxicity present with paracentral or pericentral scotomas. PMID:20395978

Echo Chambers: Emotional Contagion and Group Polarization on Facebook

NASA Astrophysics Data System (ADS)

Del Vicario, Michela; Vivaldo, Gianna; Bessi, Alessandro; Zollo, Fabiana; Scala, Antonio; Caldarelli, Guido; Quattrociocchi, Walter

2016-12-01

Recent findings showed that users on Facebook tend to select information that adhere to their system of beliefs and to form polarized groups - i.e., echo chambers. Such a tendency dominates information cascades and might affect public debates on social relevant issues. In this work we explore the structural evolution of communities of interest by accounting for users emotions and engagement. Focusing on the Facebook pages reporting on scientific and conspiracy content, we characterize the evolution of the size of the two communities by fitting daily resolution data with three growth models - i.e. the Gompertz model, the Logistic model, and the Log-logistic model. Although all the models appropriately describe the data structure, the Logistic one shows the best fit. Then, we explore the interplay between emotional state and engagement of users in the group dynamics. Our findings show that communities’ emotional behavior is affected by the users’ involvement inside the echo chamber. Indeed, to an higher involvement corresponds a more negative approach. Moreover, we observe that, on average, more active users show a faster shift towards the negativity than less active ones.

Echo Chambers: Emotional Contagion and Group Polarization on Facebook.

PubMed

Del Vicario, Michela; Vivaldo, Gianna; Bessi, Alessandro; Zollo, Fabiana; Scala, Antonio; Caldarelli, Guido; Quattrociocchi, Walter

2016-12-01

Recent findings showed that users on Facebook tend to select information that adhere to their system of beliefs and to form polarized groups - i.e., echo chambers. Such a tendency dominates information cascades and might affect public debates on social relevant issues. In this work we explore the structural evolution of communities of interest by accounting for users emotions and engagement. Focusing on the Facebook pages reporting on scientific and conspiracy content, we characterize the evolution of the size of the two communities by fitting daily resolution data with three growth models - i.e. the Gompertz model, the Logistic model, and the Log-logistic model. Although all the models appropriately describe the data structure, the Logistic one shows the best fit. Then, we explore the interplay between emotional state and engagement of users in the group dynamics. Our findings show that communities' emotional behavior is affected by the users' involvement inside the echo chamber. Indeed, to an higher involvement corresponds a more negative approach. Moreover, we observe that, on average, more active users show a faster shift towards the negativity than less active ones.

Rationality and social behavior.

PubMed

Tullberg, Jan

2003-10-21

This article penetrates the relationship between social behavior and rationality. A critical analysis is made of efforts to classify some behaviors as altruistic, as they simultaneously meet criteria of rationality by not truly being self-destructive. Newcomb's paradox is one attempt to create a hybrid behavior that is both irrational and still meets some criterion of rationality. Such dubious rationality is often seen as a source of altruistic behavior. Group selection is a controversial topic. Sober and Wilson (Unto Others--The Evolution and Psychology of Unselfish Behavior, Harvard University Press, Cambridge, MA, 1998) suggest that a very wide concept of group selection might be used to explain altruism. This concept also includes kin selection and reciprocity, which blurs its focus. The latter mechanisms hardly need further arguments to prove their existence. This article suggests that it is group selection in a strict sense that should be investigated to limit semantic neologism and confusion. In evaluation, the effort to muster a mechanism for altruism out of group selection has not been successful. However, this is not the end to group selection, but rather a good reason to investigate more promising possibilities. There is little reason to burden group selection with the instability of altruism caused by altruistic members of a group having lower fitness than egoistic members. Group selection is much more likely to develop in combination with group egoism. A common project is supported by incitement against free riding, where conformist members joined in solidarity achieve a higher fitness than members pursuing more individualistic options. Group egoism is in no conflict with rationality, and the effects of group selection will be supported rather than threatened by individual selection. Empirical evidence indicates a high level of traits such as conformism and out-group antagonism in line with group egoism. These traits are also likely candidates for behavior favored by group selection since they homogenize the group and link the different individuals closer to one another and a similar fate.

Analysing the Costs of Integrated Care: A Case on Model Selection for Chronic Care Purposes

PubMed Central

Sánchez-Pérez, Inma; Ibern, Pere; Coderch, Jordi; Inoriza, José María

2016-01-01

Background: The objective of this study is to investigate whether the algorithm proposed by Manning and Mullahy, a consolidated health economics procedure, can also be used to estimate individual costs for different groups of healthcare services in the context of integrated care. Methods: A cross-sectional study focused on the population of the Baix Empordà (Catalonia-Spain) for the year 2012 (N = 92,498 individuals). A set of individual cost models as a function of sex, age and morbidity burden were adjusted and individual healthcare costs were calculated using a retrospective full-costing system. The individual morbidity burden was inferred using the Clinical Risk Groups (CRG) patient classification system. Results: Depending on the characteristics of the data, and according to the algorithm criteria, the choice of model was a linear model on the log of costs or a generalized linear model with a log link. We checked for goodness of fit, accuracy, linear structure and heteroscedasticity for the models obtained. Conclusion: The proposed algorithm identified a set of suitable cost models for the distinct groups of services integrated care entails. The individual morbidity burden was found to be indispensable when allocating appropriate resources to targeted individuals. PMID:28316542

Genetic Structure, Linkage Disequilibrium and Signature of Selection in Sorghum: Lessons from Physically Anchored DArT Markers

PubMed Central

Bouchet, Sophie; Pot, David; Deu, Monique; Rami, Jean-François; Billot, Claire; Perrier, Xavier; Rivallan, Ronan; Gardes, Laëtitia; Xia, Ling; Wenzl, Peter; Kilian, Andrzej; Glaszmann, Jean-Christophe

2012-01-01

Population structure, extent of linkage disequilibrium (LD) as well as signatures of selection were investigated in sorghum using a core sample representative of worldwide diversity. A total of 177 accessions were genotyped with 1122 informative physically anchored DArT markers. The properties of DArTs to describe sorghum genetic structure were compared to those of SSRs and of previously published RFLP markers. Model-based (STRUCTURE software) and Neighbor-Joining diversity analyses led to the identification of 6 groups and confirmed previous evolutionary hypotheses. Results were globally consistent between the different marker systems. However, DArTs appeared more robust in terms of data resolution and bayesian group assignment. Whole genome linkage disequilibrium as measured by mean r2 decreased from 0.18 (between 0 to 10 kb) to 0.03 (between 100 kb to 1 Mb), stabilizing at 0.03 after 1 Mb. Effects on LD estimations of sample size and genetic structure were tested using i. random sampling, ii. the Maximum Length SubTree algorithm (MLST), and iii. structure groups. Optimizing population composition by the MLST reduced the biases in small samples and seemed to be an efficient way of selecting samples to make the best use of LD as a genome mapping approach in structured populations. These results also suggested that more than 100,000 markers may be required to perform genome-wide association studies in collections covering worldwide sorghum diversity. Analysis of DArT markers differentiation between the identified genetic groups pointed out outlier loci potentially linked to genes controlling traits of interest, including disease resistance genes for which evidence of selection had already been reported. In addition, evidence of selection near a homologous locus of FAR1 concurred with sorghum phenotypic diversity for sensitivity to photoperiod. PMID:22428056

Liver cirrhosis in selected autoimmune diseases: a nationwide cohort study in Taiwan.

PubMed

Tung, Chien-Hsueh; Lai, Ning-Seng; Lu, Ming-Chi; Lee, Ching-Chih

2016-02-01

The association between autoimmune diseases and liver cirrhosis has rarely been explored in Asian populations, an endemic area of viral hepatitis. The aim of this study was to investigate the comparative risk of liver cirrhosis among a group of selective autoimmune diseases in Taiwanese patients and to identify groups of high risk. This retrospective study was a nationwide, population-based study and used Taiwan's National Health Insurance Research Database. A total of 29,856 patients with definite diagnosis of selected autoimmune diseases (Registry of Taiwan Catastrophic Illness Database, ACR classification) at the starting time point of January 1, 2005, were enrolled in this study. After tracked for a 5-year period, the endpoints were diagnosis of liver cirrhosis (in accordance with International Classification of Diseases, Ninth Revision, Clinical Modification, ICD-9-CM codes 571). The control group was composed of other patients in the same database and consisted of randomly selected 753,495 sex- and age-matched non-autoimmune disease patients. The Cox proportional hazard regression model was used to calculate the risk of liver cirrhosis after adjusting for certain variables such as comorbidity, living area, and socioeconomic status. Among the patients with selected autoimmune diseases, 1987 liver cirrhosis were observed. Patients with psoriasis had a significantly increased risk of liver cirrhosis (HR 1.87, 95 % CI 1.25-2.81) than control group without psoriasis. The risk of liver cirrhosis was significantly lower in patients with rheumatoid arthritis (HR 0.29, 95 % CI 0.19-0.44). There is a gradient of risk of liver cirrhosis among the autoimmune diseases; the specific risks need to be investigated on the basis of hypotheses. Conventional immunosuppressive drug administration should be carefully implemented by regular monitoring of liver condition in order to avoid causing an adverse effect of chronic liver fibrosis.

Genetic structure, linkage disequilibrium and signature of selection in Sorghum: lessons from physically anchored DArT markers.

PubMed

Bouchet, Sophie; Pot, David; Deu, Monique; Rami, Jean-François; Billot, Claire; Perrier, Xavier; Rivallan, Ronan; Gardes, Laëtitia; Xia, Ling; Wenzl, Peter; Kilian, Andrzej; Glaszmann, Jean-Christophe

2012-01-01

Population structure, extent of linkage disequilibrium (LD) as well as signatures of selection were investigated in sorghum using a core sample representative of worldwide diversity. A total of 177 accessions were genotyped with 1122 informative physically anchored DArT markers. The properties of DArTs to describe sorghum genetic structure were compared to those of SSRs and of previously published RFLP markers. Model-based (STRUCTURE software) and Neighbor-Joining diversity analyses led to the identification of 6 groups and confirmed previous evolutionary hypotheses. Results were globally consistent between the different marker systems. However, DArTs appeared more robust in terms of data resolution and bayesian group assignment. Whole genome linkage disequilibrium as measured by mean r(2) decreased from 0.18 (between 0 to 10 kb) to 0.03 (between 100 kb to 1 Mb), stabilizing at 0.03 after 1 Mb. Effects on LD estimations of sample size and genetic structure were tested using i. random sampling, ii. the Maximum Length SubTree algorithm (MLST), and iii. structure groups. Optimizing population composition by the MLST reduced the biases in small samples and seemed to be an efficient way of selecting samples to make the best use of LD as a genome mapping approach in structured populations. These results also suggested that more than 100,000 markers may be required to perform genome-wide association studies in collections covering worldwide sorghum diversity. Analysis of DArT markers differentiation between the identified genetic groups pointed out outlier loci potentially linked to genes controlling traits of interest, including disease resistance genes for which evidence of selection had already been reported. In addition, evidence of selection near a homologous locus of FAR1 concurred with sorghum phenotypic diversity for sensitivity to photoperiod.

Applying a deep learning based CAD scheme to segment and quantify visceral and subcutaneous fat areas from CT images

NASA Astrophysics Data System (ADS)

Wang, Yunzhi; Qiu, Yuchen; Thai, Theresa; Moore, Kathleen; Liu, Hong; Zheng, Bin

2017-03-01

Abdominal obesity is strongly associated with a number of diseases and accurately assessment of subtypes of adipose tissue volume plays a significant role in predicting disease risk, diagnosis and prognosis. The objective of this study is to develop and evaluate a new computer-aided detection (CAD) scheme based on deep learning models to automatically segment subcutaneous fat areas (SFA) and visceral (VFA) fat areas depicting on CT images. A dataset involving CT images from 40 patients were retrospectively collected and equally divided into two independent groups (i.e. training and testing group). The new CAD scheme consisted of two sequential convolutional neural networks (CNNs) namely, Selection-CNN and Segmentation-CNN. Selection-CNN was trained using 2,240 CT slices to automatically select CT slices belonging to abdomen areas and SegmentationCNN was trained using 84,000 fat-pixel patches to classify fat-pixels as belonging to SFA or VFA. Then, data from the testing group was used to evaluate the performance of the optimized CAD scheme. Comparing to manually labelled results, the classification accuracy of CT slices selection generated by Selection-CNN yielded 95.8%, while the accuracy of fat pixel segmentation using Segmentation-CNN yielded 96.8%. Therefore, this study demonstrated the feasibility of using deep learning based CAD scheme to recognize human abdominal section from CT scans and segment SFA and VFA from CT slices with high agreement compared with subjective segmentation results.

Berberine inhibits hepatic gluconeogenesis via the LKB1-AMPK-TORC2 signaling pathway in streptozotocin-induced diabetic rats.

PubMed

Jiang, Shu-Jun; Dong, Hui; Li, Jing-Bin; Xu, Li-Jun; Zou, Xin; Wang, Kai-Fu; Lu, Fu-Er; Yi, Ping

2015-07-07

To investigate the molecular mechanisms of berberine inhibition of hepatic gluconeogenesis in a diabetic rat model. The 40 rats were randomly divided into five groups. One group was selected as the normal group. In the remaining groups (n = 8 each), the rats were fed on a high-fat diet for 1 mo and received intravenous injection of streptozotocin for induction of the diabetic models. Berberine (156 mg/kg per day) (berberine group) or metformin (184 mg/kg per day) (metformin group) was intragastrically administered to the diabetic rats and 5-aminoimidazole-4-carboxamide1-β-D-ribofuranoside (AICAR) (0.5 mg/kg per day) (AICAR group) was subcutaneously injected to the diabetic rats for 12 wk. The remaining eight diabetic rats served as the model group. Fasting plasma glucose and insulin levels as well as lipid profile were tested. The expressions of proteins were examined by western blotting. The nuclear translocation of CREB-regulated transcription co-activator (TORC)2 was observed by immunohistochemical staining. Berberine improved impaired glucose tolerance and decreased plasma hyperlipidemia. Moreover, berberine decreased fasting plasma insulin and homeostasis model assessment of insulin resistance (HOMA-IR). Berberine upregulated protein expression of liver kinase (LK)B1, AMP-activated protein kinase (AMPK) and phosphorylated AMPK (p-AMPK). The level of phophorylated TORC2 (p-TORC2) protein in the cytoplasm was higher in the berberine group than in the model group, and no significant difference in total TORC2 protein level was observed. Immunohistochemical staining revealed that more TORC2 was localized in the cytoplasm of the berberine group than in the model group. Moreover, berberine treatment downregulated protein expression of the key gluconeogenic enzymes (phosphoenolpyruvate carboxykinase and glucose-6-phosphatase) in the liver tissues. Our findings revealed that berberine inhibited hepatic gluconeogenesis via the regulation of the LKB1-AMPK-TORC2 signaling pathway.

Role of Rho-mediated ROCK-Semaphorin3A signaling pathway in the pathogenesis of Parkinson's disease in a mouse model.

PubMed

Qi, Li; Tang, Yong-Gang; Wang, Lin; He, Wei; Pan, Hong-Hua; Nie, Rong-Rong; Can, Yan

2016-11-15

The present study aims to elucidate the role of Rho-mediated ROCK-Semaphorin3A signaling pathway in the pathogenesis of Parkinson's disease (PD) in a mouse model. One-hundred twelve eight-week male C57BL/6 mice were selected. The mouse model of PD was constructed by intraperitoneal injection of MPTP. All mice were divided into four groups (28 mice in each group): Blank group, Model group, Rho knockout (Rho+/-) group and ROCK knockout (ROCK+/-) group. Changes of behavior of the mice were studied through automatic moving test and rotarod test. Immunohistochemistry (IHC) was used to detect the expressions of TH, CD11b and GFAP. High performance liquid chromatograph (HPLC) was performed for detection of dopamine and its metabolic product. The mRNA and protein expressions of Rho, ROCK, Sema3A, PlexinA and NRP-1 were detected using quantitative real-time polymerase chain reaction (qRT-PCR) and Western blotting. Rho and ROCK knockout improved the damage caused by MPTP on the behavior of mice and protected dopaminergic neurons from injury, along with the increases of dopamine and its metabolic product. The mRNA and protein expressions of Rho, ROCK, Sema3A, PlexinA and NRP-1 were increased in PD mice in the Model group compared with those in the Blank group. Compared to the Model group, the mRNA and protein expressions of Rho, ROCK, Sema3A, PlexinA and NRP-1 were reduced in the Rho+/- and ROCK+/- groups. These findings indicate that Rho and ROCK knockout may improve the behavior of mice and prevent MPTP-induced dopaminergic neurons damage by regulating Sema3A, PlexinA and NRP-1 in a mouse model of PD. Copyright © 2016 Elsevier B.V. All rights reserved.

The development and use of a molecular model for soybean maturity groups.

PubMed

Langewisch, Tiffany; Lenis, Julian; Jiang, Guo-Liang; Wang, Dechun; Pantalone, Vince; Bilyeu, Kristin

2017-05-30

Achieving appropriate maturity in a target environment is essential to maximizing crop yield potential. In soybean [Glycine max (L.) Merr.], the time to maturity is largely dependent on developmental response to dark periods. Once the critical photoperiod is reached, flowering is initiated and reproductive development proceeds. Therefore, soybean adaptation has been attributed to genetic changes and natural or artificial selection to optimize plant development in specific, narrow latitudinal ranges. In North America, these regions have been classified into twelve maturity groups (MG), with lower MG being shorter season than higher MG. Growing soybean lines not adapted to a particular environment typically results in poor growth and significant yield reductions. The objective of this study was to develop a molecular model for soybean maturity based on the alleles underlying the major maturity loci: E1, E2, and E3. We determined the allelic variation and diversity of the E maturity genes in a large collection of soybean landraces, North American ancestors, Chinese cultivars, North American cultivars or expired Plant Variety Protection lines, and private-company lines. The E gene status of accessions in the USDA Soybean Germplasm Collection with SoySNP50K Beadchip data was also predicted. We determined the E allelic combinations needed to adapt soybean to different MGs in the United States (US) and discovered a strong signal of selection for E genotypes released in North America, particularly the US and Canada. The E gene maturity model proposed will enable plant breeders to more effectively transfer traits into different MGs and increase the overall efficiency of soybean breeding in the US and Canada. The powerful yet simple selection strategy for increasing soybean breeding efficiency can be used alone or to directly enhance genomic prediction/selection schemes. The results also revealed previously unrecognized aspects of artificial selection in soybean imposed by soybean breeders based on geography that highlights the need for plant breeding that is optimized for specific environments.

Use of 3D models of vascular rings and slings to improve resident education.

PubMed

Jones, Trahern W; Seckeler, Michael D

2017-09-01

Three-dimensional (3D) printing is a manufacturing method by which an object is created in an additive process, and can be used with medical imaging data to generate accurate physical reproductions of organs and tissues for a variety of applications. We hypothesized that using 3D printed models of congenital cardiovascular lesions to supplement an educational lecture would improve learners' scores on a board-style examination. Patients with normal and abnormal aortic arches were selected and anonymized to generate 3D printed models. A cohort of pediatric and combined pediatric/emergency medicine residents were then randomized to intervention and control groups. Each participant was given a subjective survey and an objective board-style pretest. Each group received the same 20-minutes lecture on vascular rings and slings. During the intervention group's lecture, 3D printed physical models of each lesion were distributed for inspection. After each lecture, both groups completed the same subjective survey and objective board-style test to assess their comfort with and postlecture knowledge of vascular rings. There were no differences in the basic demographics of the two groups. After the lectures, both groups' subjective comfort levels increased. Both groups' scores on the objective test improved, but the intervention group scored higher on the posttest. This study demonstrated a measurable gain in knowledge about vascular rings and pulmonary artery slings with the addition of 3D printed models of the defects. Future applications of this teaching modality could extend to other congenital cardiac lesions and different learners. © 2017 Wiley Periodicals, Inc.

Induction of osteoarthritis by injecting monosodium iodoacetate into the patellofemoral joint of an experimental rat model.

PubMed

Takahashi, Ikufumi; Matsuzaki, Taro; Kuroki, Hiroshi; Hoso, Masahiro

2018-01-01

This study aimed to investigate the histopathological changes in the patellofemoral joint using a rat model of osteoarthritis that was induced using monosodium iodoacetate, and to establish a novel model of patellofemoral osteoarthritis in a rat model using histopathological analysis. Sixty male rats were used. Osteoarthritis was induced through a single intra-articular injection of monosodium iodoacetate in both knee joints. Animals were equally divided into two experimental groups based on the monosodium iodoacetate dose: 0.2 mg and 1.0 mg. Histopathological changes in the articular cartilage of the patellofemoral joint and the infrapatellar fat pad were examined at 3 days, 1 week, 2 weeks, 4 weeks, 8 weeks, and 12 weeks after the monosodium iodoacetate injection. In the 1.0-mg group, the representative histopathological findings of osteoarthritis were observed in the articular cartilage of the patellofemoral joint over time. Additionally, the Osteoarthritis Research Society International scores of the patellofemoral joint increased over time. The synovitis scores of the infrapatellar fat pad in both groups were highest at 3 days, and then the values decreased over time. The fibrosis score of the infrapatellar fat pad in the 1.0-mg group increased with time, whereas the fibrosis score in the 0.2-mg group remained low. Representative histopathological findings of osteoarthritis were observed in the articular cartilage of the patellofemoral joint in a rat model of osteoarthritis induced using monosodium iodoacetate. With appropriate selection, this model may be regarded as an ideal patellofemoral osteoarthritis model.

Identification, Characterization, and Utilization of Adult Meniscal Progenitor Cells

DTIC Science & Technology

2017-11-01

approach including row scaling and Ward’s minimum variance method was chosen. This analysis revealed two groups of four samples each. For the selected...articular cartilage in an ovine model. Am J Sports Med. 2008;36(5):841-50. 7. Deshpande BR, Katz JN, Solomon DH, Yelin EH, Hunter DJ, Messier SP, et al...Miosge1,* 1Tissue Regeneration Work Group , Department of Prosthodontics, Medical Faculty, Georg-August-University, 37075 Goettingen, Germany 2Institute of

[Antitumor effect of recombinant T7 phage vaccine expressing xenogenic vascular endothelial growth factor on Lewis lung cancer in mice].

PubMed

Li, Xiao-Hui; Tang, Liang; Liu, Dong; Sun, Hong-Mei; Zhou, Cai-Cun; Tan, Li-Song; Wang, Li-Ping; Zhang, Pei-De; Zhang, Shang-Quan

2006-10-01

Angiogenesis plays an important role in growth and metastasis of tumors. Vascular endothelial growth factor (VEGF) is considered as a fundamental regulator for angiogenesis. This study was to construct a recombinant T7 phage vaccine expressing xenogenic VEGF on the capsid, and test its inhibitory effect on Lewis lung cancer cells in mice. VEGF gene was cloned by reverse transcription-polymerase chain reaction (RT-PCR) from human lung cancer tissues, and inserted into phage using T7 Select10-3b kit to construct T7 Select10-3b_VEGF vaccine. The titer of prepared phage reached 1x10(13) pfu/ml. C57BL/6J mice were randomly divided into 3 groups: T7 Select10-3b_VEGF vaccine group (T7-VEGF), T7 phage (T7) group, normal saline (NS) group (10 mice/group). Each mouse was injected with Freundos adjuvant mixed with 1x10(12) pfu/200 microl T7 Select10-3b_VEGF, or T7, or normal saline once a week for 4 weeks. Lewis lung carcinoma model (LL/2) was established in C57BL/6J mice after 4-week immunization. Tumor growth and mouse's physical status were observed during immunization. Tumor weight and serum level of specific anti-VEGF antibody were measured by enzyme-linked immunosorbent assay (ELISA). Microvessel density (MVD) of tumors was detected by immunohistochemistry 14 days after the inoculation of tumor cells. Tumor weight of T7-VEGF vaccine group,T7 group, and NS group were (0.543+/-0.259)g, (0.982+/-0.359)g, (1.169+/-0.460)g, respectively. Tumor weight of T7-VEGF vaccine group was significantly lower than that of NS group (P<0.01). Serum anti-VEGF antibody level in T7-VEGF vaccine group was 1:1,000. MVD was significantly lower in T7-VEGF vaccine group than in NS group (8.5+/-0.8 vs 18.5+/-1.6, P<0.05). MVD in T7 group was 16.4+/-1.3. Recombinant T7 phage vaccine expressing xenogenic VEGF can break immunologic tolerance against self-VEGF and inhibit the growth of Lewis lung cancer cells.

Genome-wide Selective Sweeps in Natural Bacterial Populations Revealed by Time-series Metagenomics

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

Chan, Leong-Keat; Bendall, Matthew L.; Malfatti, Stephanie

2014-05-12

Multiple evolutionary models have been proposed to explain the formation of genetically and ecologically distinct bacterial groups. Time-series metagenomics enables direct observation of evolutionary processes in natural populations, and if applied over a sufficiently long time frame, this approach could capture events such as gene-specific or genome-wide selective sweeps. Direct observations of either process could help resolve how distinct groups form in natural microbial assemblages. Here, from a three-year metagenomic study of a freshwater lake, we explore changes in single nucleotide polymorphism (SNP) frequencies and patterns of gene gain and loss in populations of Chlorobiaceae and Methylophilaceae. SNP analyses revealedmore » substantial genetic heterogeneity within these populations, although the degree of heterogeneity varied considerably among closely related, co-occurring Methylophilaceae populations. SNP allele frequencies, as well as the relative abundance of certain genes, changed dramatically over time in each population. Interestingly, SNP diversity was purged at nearly every genome position in one of the Chlorobiaceae populations over the course of three years, while at the same time multiple genes either swept through or were swept from this population. These patterns were consistent with a genome-wide selective sweep, a process predicted by the ecotype model? of diversification, but not previously observed in natural populations.« less

Engaging Watershed Stakeholders for Cost-Effective Environmental Management Planning with "Watershed Manager"

ERIC Educational Resources Information Center

Williams, Jeffery R.; Smith, Craig M.; Roe, Josh D.; Leatherman, John C.; Wilson, Robert M.

2012-01-01

"Watershed Manager" is a spreadsheet-based model that is used in extension education programs for learning about and selecting cost-effective watershed management practices to reduce soil, nitrogen, and phosphorus losses from cropland. It can facilitate Watershed Restoration and Protection Strategy (WRAPS) stakeholder groups' development…

Strategies for Retaining Minority Students in Higher Education.

ERIC Educational Resources Information Center

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

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

Selection of basic data for numerical modeling of rock mass stress state at Mirny Mining and Processing Works, Alrosa Group of Companies

NASA Astrophysics Data System (ADS)

Bokiy, IB; Zoteev, OV; Pul, VV; Pul, EK

2018-03-01

The influence of structural features on the strength and elasticity modulus is studied in rock mass in the area of Mirny Mining and Processing Works. The authors make recommendations on the values of physical properties of rocks.

Autonomic Physiological Response Patterns Related to Intelligence

ERIC Educational Resources Information Center

Melis, Cor; van Boxtel, Anton

2007-01-01

We examined autonomic physiological responses induced by six different cognitive ability tasks, varying in complexity, that were selected on the basis of on Guilford's Structure of Intellect model. In a group of 52 participants, task performance was measured together with nine different autonomic response measures and respiration rate. Weighted…

Freshman Learning Communities, College Performance, and Retention. Working Paper 2005-22

ERIC Educational Resources Information Center

Hotchkiss, Julie L.; Moore, Robert E.; Pitts, M. Melinda

2005-01-01

This paper applies a standard treatment effects model to determine that participation in Freshman Learning Communities (FLCs) improves academic performance and retention. Not controlling for individual self-selection into FLC participation leads one to incorrectly conclude that the impact is the same across race and gender groups. Accurately…

Development of a web-based liver cancer prediction model for type II diabetes patients by using an artificial neural network.

PubMed

Rau, Hsiao-Hsien; Hsu, Chien-Yeh; Lin, Yu-An; Atique, Suleman; Fuad, Anis; Wei, Li-Ming; Hsu, Ming-Huei

2016-03-01

Diabetes mellitus is associated with an increased risk of liver cancer, and these two diseases are among the most common and important causes of morbidity and mortality in Taiwan. To use data mining techniques to develop a model for predicting the development of liver cancer within 6 years of diagnosis with type II diabetes. Data were obtained from the National Health Insurance Research Database (NHIRD) of Taiwan, which covers approximately 22 million people. In this study, we selected patients who were newly diagnosed with type II diabetes during the 2000-2003 periods, with no prior cancer diagnosis. We then used encrypted personal ID to perform data linkage with the cancer registry database to identify whether these patients were diagnosed with liver cancer. Finally, we identified 2060 cases and assigned them to a case group (patients diagnosed with liver cancer after diabetes) and a control group (patients with diabetes but no liver cancer). The risk factors were identified from the literature review and physicians' suggestion, then, chi-square test was conducted on each independent variable (or potential risk factor) for a comparison between patients with liver cancer and those without, those found to be significant were selected as the factors. We subsequently performed data training and testing to construct artificial neural network (ANN) and logistic regression (LR) prediction models. The dataset was randomly divided into 2 groups: a training group and a test group. The training group consisted of 1442 cases (70% of the entire dataset), and the prediction model was developed on the basis of the training group. The remaining 30% (618 cases) were assigned to the test group for model validation. The following 10 variables were used to develop the ANN and LR models: sex, age, alcoholic cirrhosis, nonalcoholic cirrhosis, alcoholic hepatitis, viral hepatitis, other types of chronic hepatitis, alcoholic fatty liver disease, other types of fatty liver disease, and hyperlipidemia. The performance of the ANN was superior to that of LR, according to the sensitivity (0.757), specificity (0.755), and the area under the receiver operating characteristic curve (0.873). After developing the optimal prediction model, we base on this model to construct a web-based application system for liver cancer prediction, which can provide support to physicians during consults with diabetes patients. In the original dataset (n=2060), 33% of diabetes patients were diagnosed with liver cancer (n=515). After using 70% of the original data to training the model and other 30% for testing, the sensitivity and specificity of our model were 0.757 and 0.755, respectively; this means that 75.7% of diabetes patients can be predicted correctly to receive a future liver cancer diagnosis, and 75.5% can be predicted correctly to not be diagnosed with liver cancer. These results reveal that this model can be used as effective predictors of liver cancer for diabetes patients, after discussion with physicians; they also agreed that model can assist physicians to advise potential liver cancer patients and also helpful to decrease the future cost incurred upon cancer treatment. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Group II metabotropic glutamate receptor activation attenuates peripheral sensitization in inflammatory states

PubMed Central

Du, Junhui; Zhou, Shengtai; Carlton, Susan M.

2008-01-01

Several lines of evidence indicate that Group II metabotropic glutamate receptor (mGluR) activation can depress sensory transmission. We have reported the expression of Group II mGluRs on unmyelinated axons, many of which were presumed to be nociceptors, in the rat digital nerve (Carlton et al., 2001b). The goals of the present study are to further our understanding of Group II modulation of nociceptor processing in the periphery, documenting behavioral changes using inflammatory models and documenting, for the first time, cutaneous single fiber activity following exposure to a Group II agonist (2R,4R)-4-aminopyrrolidine-2,4-dicarboxylate (APDC) and antagonist LY341495 (LY). The data indicate that peripheral Group II mGluR activation does not depress nociceptive behaviors or nociceptor fiber responses in the non-sensitized state (i.e. following brief nociceptive mechanical or thermal stimulation) but can depress these responses when nociceptors are sensitized by exposure to formalin or inflammatory soup. Group II mGluR agonist-induced inhibition can be blocked by a selective Group II antagonist. Peripheral Group II mGluR-induced inhibition evoked in these studies occurs through activation of local receptors and not through spinal or supraspinal mechanisms. The data indicate that administration of selective Group II agonists may be potent therapeutic agents for prevention of peripheral sensitization and for treatment of inflammatory pain. PMID:18487022

[Effect of hyperforin on learning and memory abilities and Aβ₁₋₄₂, βAPP and BACE1 protein expressions in hippocampus of Alzheimer's disease model mice].

PubMed

Geng, Yan-Na; Wu, Yi-Jun; Zhang, Wen-Xin

2016-08-01

To investigate the effect of the hyperforin (HF) on learning and memory function and Aβ₁₋₄₂, βAPP and BACE1 protein expressions in hippocampus of five-month-old APP/PS1 double transgenic mice, and discuss the underlying mechanism of HF. The five-month-old APP/PS1 double transgenic mice were randomly divided into the model group, rosiglitazone group (12 mg•kg⁻¹•d⁻¹) and HF high dose, middle dose and low dose groups (600, 300 and 150 mg•kg⁻¹•d⁻¹) in each group; in addition, 15C57BL/6J mice with the same months and background were selected as normal group. Drugs were diluted in the same volume before using, and then administrated by ig for 7 months, 1 time a day; the mice in normal group and model group received the same volume of distilled water. The learning and memory ability was tested by Morris water maze; Aβ₁₋₄₂, βAPP and BACE1proteinexpressionlevelswere tested by immunohistochemistry and Western blot. The Morris water maze results showed that as compared with the normal group, the learning and memory ability was significantly impaired in mice of model group (P<0.01); as compared with the model group, the learning and memory ability was improved in mice of rosiglitazone group and HF high, middle and low dose groups(P<0.01 or P<0.05). Immunohistochemistry and western blot results showed thatas compared with the normal group, the Aβ₁₋₄₂, βAPP and BACE1 protein expression levels in hippocampus were significantly increased in mice of model group (P<0.01);as compared with the model group, Aβ₁₋₄₂, βAPP and BACE1 protein expression levels in hippocampus were decreased in mice of rosiglitazone group and HF high, middle and low dose groups (P<0.01 or P<0.05). HF may improve the learning and memory ability of AD model mice via inhibition of βAPP and BACE1 protein expressions, thus reduced the generation of Aβ₁₋₄₂ proteins and amyloid plaque deposits in the brain. Copyright© by the Chinese Pharmaceutical Association.

Surface remineralization potential of casein phosphopeptide-amorphous calcium phosphate on enamel eroded by cola-drinks: An in-situ model study.

PubMed

Grewal, Navneet; Kudupudi, Vinod; Grewal, Sukrit

2013-07-01

The aim of this study was to investigate the remineralization potential of casein phosphopeptide-amorphous calcium phosphate (CPP-ACP) on enamel eroded by cola drinks. A total of 30 healthy subjects were selected from a random sample of 1200 children and divided into two groups of 15 each wherein calcium and phosphorus analyses and scanning electron microscope (SEM) analysis was carried out to investigate the remineralization of enamel surface. A total of 30 non-carious premolar teeth were selected from the human tooth bank (HTB) to prepare the in-situ appliance. Three enamel slabs were prepared from the same. One enamel slab was used to obtain baseline values and the other two were embedded into the upper palatal appliances prepared on the subjects' maxillary working model. The subjects wore the appliance after which 30 ml cola drink exposure was given. After 15 days, the slabs were removed and subjected to respective analysis. Means of all the readings of soluble calcium and phosphorous levels at baseline,post cola-drink exposure and post cpp-acp application were subjected to statistical analysis SPSS11.5 version. Comparison within groups and between groups was carried out using ANOVA and F-values at 1% level of significance. Decrease in calcium solubility of enamel in the CPP-ACP application group as compared to post-cola drink exposure group (P < 0.05) was seen. Distinctive change in surface topography of enamel in the post-CPP-ACP application group as compared to post-cola drink exposure group was observed. CPP-ACP significantly promoted remineralization of enamel eroded by cola drinks as revealed by significant morphological changes seen in SEM magnification and spectrophotometric analyses.

Forming groups of aggressive sows based on a predictive test of aggression does not affect overall sow aggression or welfare.

PubMed

Verdon, Megan; Morrison, R S; Hemsworth, P H

2018-05-01

This experiment examined the effects of group composition on sow aggressive behaviour and welfare. Over 6 time replicates, 360 sows (parity 1-6) were mixed into groups (10 sows per pen, 1.8 m 2 /sow) composed of animals that were predicted to be aggressive (n = 18 pens) or groups composed of animals that were randomly selected (n = 18 pens). Predicted aggressive sows were selected based on a model-pig test that has been shown to be related to the aggressive behaviour of parity 2 sows when subsequently mixed in groups. Measurements were taken on aggression delivered post-mixing, and aggression delivered around feeding, fresh skin injuries and plasma cortisol concentrations at days 2 and 24 post-mixing. Live weight gain, litter size (born alive, total born, stillborn piglets), and farrowing rate were also recorded. Manipulating the group composition based on predicted sow aggressiveness had no effect (P > 0.05) on sow aggression delivered at mixing or around feeding, fresh injuries, cortisol, weight gain from day 2 to day 24, farrowing rate, or litter size. The lack of treatment effects in the present experiment could be attributed to (1) a failure of the model-pig test to predict aggression in older sows in groups, or (2) the dependence of the expression of the aggressive phenotype on factors such as social experience and characteristics (e.g., physical size and aggressive phenotype) of pen mates. This research draws attention to the intrinsic difficulties associated with predicting behaviour across contexts, particularly when the behaviour is highly dependent on interactions with conspecifics, and highlights the social complexities involved in the presentation of a behavioural phenotype. Copyright © 2018 Elsevier B.V. All rights reserved.

Changing Friend Selection in Middle School: A Social Network Analysis of a Randomized Intervention Study Designed to Prevent Adolescent Problem Behavior.

PubMed

DeLay, Dawn; Ha, Thao; Van Ryzin, Mark; Winter, Charlotte; Dishion, Thomas J

2016-04-01

Adolescent friendships that promote problem behavior are often chosen in middle school. The current study examines the unintended impact of a randomized school-based intervention on the selection of friends in middle school, as well as on observations of deviant talk with friends 5 years later. Participants included 998 middle school students (526 boys and 472 girls) recruited at the onset of middle school (age 11-12 years) from three public middle schools participating in the Family Check-up model intervention. The current study focuses only on the effects of the SHAPe curriculum-one level of the Family Check-up model-on friendship choices. Participants nominated friends and completed measures of deviant peer affiliation. Approximately half of the sample (n = 500) was randomly assigned to the intervention, and the other half (n = 498) comprised the control group within each school. The results indicate that the SHAPe curriculum affected friend selection within school 1 but not within schools 2 or 3. The effects of friend selection in school 1 translated into reductions in observed deviancy training 5 years later (age 16-17 years). By coupling longitudinal social network analysis with a randomized intervention study, the current findings provide initial evidence that a randomized public middle school intervention can disrupt the formation of deviant peer groups and diminish levels of adolescent deviance 5 years later.

Interspecific competition underlying mutualistic networks.

PubMed

Maeng, Seong Eun; Lee, Jae Woo; Lee, Deok-Sun

2012-03-09

Multiple classes of interactions may exist affecting one another in a given system. For the mutualistic networks of plants and pollinating animals, it has been known that the degree distribution is broad but often deviates from power-law form more significantly for plants than animals. To illuminate the origin of such asymmetry, we study a model network in which links are assigned under generalized preferential-selection rules between two groups of nodes and find the sensitive dependence of the resulting connectivity pattern on the model parameters. The nonlinearity of preferential selection can come from interspecific interactions among animals and among plants. The model-based analysis of real-world mutualistic networks suggests that a new animal determines its partners not only by their abundance but also under the competition with existing animal species, which leads to the stretched-exponential degree distributions of plants.

Interspecific Competition Underlying Mutualistic Networks

NASA Astrophysics Data System (ADS)

Maeng, Seong Eun; Lee, Jae Woo; Lee, Deok-Sun

2012-03-01

Multiple classes of interactions may exist affecting one another in a given system. For the mutualistic networks of plants and pollinating animals, it has been known that the degree distribution is broad but often deviates from power-law form more significantly for plants than animals. To illuminate the origin of such asymmetry, we study a model network in which links are assigned under generalized preferential-selection rules between two groups of nodes and find the sensitive dependence of the resulting connectivity pattern on the model parameters. The nonlinearity of preferential selection can come from interspecific interactions among animals and among plants. The model-based analysis of real-world mutualistic networks suggests that a new animal determines its partners not only by their abundance but also under the competition with existing animal species, which leads to the stretched-exponential degree distributions of plants.

QMEANclust: estimation of protein model quality by combining a composite scoring function with structural density information.

PubMed

Benkert, Pascal; Schwede, Torsten; Tosatto, Silvio Ce

2009-05-20

The selection of the most accurate protein model from a set of alternatives is a crucial step in protein structure prediction both in template-based and ab initio approaches. Scoring functions have been developed which can either return a quality estimate for a single model or derive a score from the information contained in the ensemble of models for a given sequence. Local structural features occurring more frequently in the ensemble have a greater probability of being correct. Within the context of the CASP experiment, these so called consensus methods have been shown to perform considerably better in selecting good candidate models, but tend to fail if the best models are far from the dominant structural cluster. In this paper we show that model selection can be improved if both approaches are combined by pre-filtering the models used during the calculation of the structural consensus. Our recently published QMEAN composite scoring function has been improved by including an all-atom interaction potential term. The preliminary model ranking based on the new QMEAN score is used to select a subset of reliable models against which the structural consensus score is calculated. This scoring function called QMEANclust achieves a correlation coefficient of predicted quality score and GDT_TS of 0.9 averaged over the 98 CASP7 targets and perform significantly better in selecting good models from the ensemble of server models than any other groups participating in the quality estimation category of CASP7. Both scoring functions are also benchmarked on the MOULDER test set consisting of 20 target proteins each with 300 alternatives models generated by MODELLER. QMEAN outperforms all other tested scoring functions operating on individual models, while the consensus method QMEANclust only works properly on decoy sets containing a certain fraction of near-native conformations. We also present a local version of QMEAN for the per-residue estimation of model quality (QMEANlocal) and compare it to a new local consensus-based approach. Improved model selection is obtained by using a composite scoring function operating on single models in order to enrich higher quality models which are subsequently used to calculate the structural consensus. The performance of consensus-based methods such as QMEANclust highly depends on the composition and quality of the model ensemble to be analysed. Therefore, performance estimates for consensus methods based on large meta-datasets (e.g. CASP) might overrate their applicability in more realistic modelling situations with smaller sets of models based on individual methods.

Tree regeneration following group selection harvesting in southern Indiana

Treesearch

Dale R. Weigel; George R. Parker

1995-01-01

An increased interest in the use of group selection harvesting in the Central Hardwood forests has emphasized the lack of scientific information about species response under this uneven-aged management system. Tree regeneration response following group selection harvesting was studied on thirty-six group selection openings on the Naval Surface Warfare Center, Crane...

Stochastic Frontier Model Approach for Measuring Stock Market Efficiency with Different Distributions

PubMed Central

Hasan, Md. Zobaer; Kamil, Anton Abdulbasah; Mustafa, Adli; Baten, Md. Azizul

2012-01-01

The stock market is considered essential for economic growth and expected to contribute to improved productivity. An efficient pricing mechanism of the stock market can be a driving force for channeling savings into profitable investments and thus facilitating optimal allocation of capital. This study investigated the technical efficiency of selected groups of companies of Bangladesh Stock Market that is the Dhaka Stock Exchange (DSE) market, using the stochastic frontier production function approach. For this, the authors considered the Cobb-Douglas Stochastic frontier in which the technical inefficiency effects are defined by a model with two distributional assumptions. Truncated normal and half-normal distributions were used in the model and both time-variant and time-invariant inefficiency effects were estimated. The results reveal that technical efficiency decreased gradually over the reference period and that truncated normal distribution is preferable to half-normal distribution for technical inefficiency effects. The value of technical efficiency was high for the investment group and low for the bank group, as compared with other groups in the DSE market for both distributions in time- varying environment whereas it was high for the investment group but low for the ceramic group as compared with other groups in the DSE market for both distributions in time-invariant situation. PMID:22629352

Stochastic frontier model approach for measuring stock market efficiency with different distributions.

PubMed

Hasan, Md Zobaer; Kamil, Anton Abdulbasah; Mustafa, Adli; Baten, Md Azizul

2012-01-01

The stock market is considered essential for economic growth and expected to contribute to improved productivity. An efficient pricing mechanism of the stock market can be a driving force for channeling savings into profitable investments and thus facilitating optimal allocation of capital. This study investigated the technical efficiency of selected groups of companies of Bangladesh Stock Market that is the Dhaka Stock Exchange (DSE) market, using the stochastic frontier production function approach. For this, the authors considered the Cobb-Douglas Stochastic frontier in which the technical inefficiency effects are defined by a model with two distributional assumptions. Truncated normal and half-normal distributions were used in the model and both time-variant and time-invariant inefficiency effects were estimated. The results reveal that technical efficiency decreased gradually over the reference period and that truncated normal distribution is preferable to half-normal distribution for technical inefficiency effects. The value of technical efficiency was high for the investment group and low for the bank group, as compared with other groups in the DSE market for both distributions in time-varying environment whereas it was high for the investment group but low for the ceramic group as compared with other groups in the DSE market for both distributions in time-invariant situation.

Improving plant functional groups for dynamic models of biodiversity: at the crossroads between functional and community ecology

PubMed Central

Isabelle, Boulangeat; Pauline, Philippe; Sylvain, Abdulhak; Roland, Douzet; Luc, Garraud; Sébastien, Lavergne; Sandra, Lavorel; Jérémie, Van Es; Pascal, Vittoz; Wilfried, Thuiller

2013-01-01

The pace of on-going climate change calls for reliable plant biodiversity scenarios. Traditional dynamic vegetation models use plant functional types that are summarized to such an extent that they become meaningless for biodiversity scenarios. Hybrid dynamic vegetation models of intermediate complexity (hybrid-DVMs) have recently been developed to address this issue. These models, at the crossroads between phenomenological and process-based models, are able to involve an intermediate number of well-chosen plant functional groups (PFGs). The challenge is to build meaningful PFGs that are representative of plant biodiversity, and consistent with the parameters and processes of hybrid-DVMs. Here, we propose and test a framework based on few selected traits to define a limited number of PFGs, which are both representative of the diversity (functional and taxonomic) of the flora in the Ecrins National Park, and adapted to hybrid-DVMs. This new classification scheme, together with recent advances in vegetation modeling, constitutes a step forward for mechanistic biodiversity modeling. PMID:24403847

Probability Models Based on Soil Properties for Predicting Presence-Absence of Pythium in Soybean Roots.

PubMed

Zitnick-Anderson, Kimberly K; Norland, Jack E; Del Río Mendoza, Luis E; Fortuna, Ann-Marie; Nelson, Berlin D

2017-10-01

Associations between soil properties and Pythium groups on soybean roots were investigated in 83 commercial soybean fields in North Dakota. A data set containing 2877 isolates of Pythium which included 26 known spp. and 1 unknown spp. and 13 soil properties from each field were analyzed. A Pearson correlation analysis was performed with all soil properties to observe any significant correlation between properties. Hierarchical clustering, indicator spp., and multi-response permutation procedures were used to identify groups of Pythium. Logistic regression analysis using stepwise selection was employed to calculate probability models for presence of groups based on soil properties. Three major Pythium groups were identified and three soil properties were associated with these groups. Group 1, characterized by P. ultimum, was associated with zinc levels; as zinc increased, the probability of group 1 being present increased (α = 0.05). Pythium group 2, characterized by Pythium kashmirense and an unknown Pythium sp., was associated with cation exchange capacity (CEC) (α < 0.05); as CEC increased, these spp. increased. Group 3, characterized by Pythium heterothallicum and Pythium irregulare, were associated with CEC and calcium carbonate exchange (CCE); as CCE increased and CEC decreased, these spp. increased (α = 0.05). The regression models may have value in predicting pathogenic Pythium spp. in soybean fields in North Dakota and adjacent states.

Nimesulide, a cyclooxygenase-2 selective inhibitor, suppresses obesity-related non-alcoholic fatty liver disease and hepatic insulin resistance through the regulation of peroxisome proliferator-activated receptor γ

PubMed Central

Tsujimoto, Shunsuke; Kishina, Manabu; Koda, Masahiko; Yamamoto, Yasutaka; Tanaka, Kohei; Harada, Yusuke; Yoshida, Akio; Hisatome, Ichiro

2016-01-01

Cyclooxygenase (COX)-2 selective inhibitors suppress non-alcoholic fatty liver disease (NAFLD); however, the precise mechanism of action remains unknown. The aim of this study was to examine how the COX-2 selective inhibitor nimesulide suppresses NAFLD in a murine model of high-fat diet (HFD)-induced obesity. Mice were fed either a normal chow diet (NC), an HFD, or HFD plus nimesulide (HFD-nime) for 12 weeks. Body weight, hepatic COX-2 mRNA expression and triglyceride accumulation were significantly increased in the HFD group. Triglyceride accumulation was suppressed in the HFD-nime group. The mRNA expression of hepatic peroxisome proliferator-activated receptor γ (PPARγ) and the natural PPARγ agonist 15-deoxy-Δ12,14-prostaglandin J2 (15d-PGJ2) were significantly increased in the HFD group and significantly suppressed in the HFD-nime group. Glucose metabolism was impaired in the HFD group compared with the NC group, and it was significantly improved in the HFD-nime group. In addition, the plasma insulin levels in the HFD group were increased compared with those in the NC group, and were decreased in the HFD-nime group. These results indicate that HFD-induced NAFLD is mediated by the increased hepatic expression of COX-2. We suggest that the production of 15d-PGJ2, which is mediated by COX-2, induces NAFLD and hepatic insulin resistance by activating PPARγ. Furthermore, the mRNA expression of tissue inhibitor of metalloproteinases-1 (TIMP-1), procollagen-1 and monocyte chemoattractant protein-1 (MCP-1), as well as the number of F4/80-positive hepatic (Kupffer) cells, were significantly increased in the HFD group compared with the NC group, and they were reduced by nimesulide. In conclusion, COX-2 may emerge as a molecular target for preventing the development of NAFLD and insulin resistance in diet-related obesity. PMID:27431935

Use of Extended Characteristics of Locomotion and Feeding Behavior for Automated Identification of Lame Dairy Cows

PubMed Central

Beer, Gian; Starke, Alexander; Schuepbach-Regula, Gertraud; Müller, Hendrik; Kohler, Philipp

2016-01-01

This study was carried out to detect differences in locomotion and feeding behavior in lame (group L; n = 41; gait score ≥ 2.5) and non-lame (group C; n = 12; gait score ≤ 2) multiparous Holstein cows in a cross-sectional study design. A model for automatic lameness detection was created, using data from accelerometers attached to the hind limbs and noseband sensors attached to the head. Each cow’s gait was videotaped and scored on a 5-point scale before and after a period of 3 consecutive days of behavioral data recording. The mean value of 3 independent experienced observers was taken as a definite gait score and considered to be the gold standard. For statistical analysis, data from the noseband sensor and one of two accelerometers per cow (randomly selected) of 2 out of 3 randomly selected days was used. For comparison between group L and group C, the T-test, the Aspin-Welch Test and the Wilcoxon Test were used. The sensitivity and specificity for lameness detection was determined with logistic regression and ROC-analysis. Group L compared to group C had significantly lower eating and ruminating time, fewer eating chews, ruminating chews and ruminating boluses, longer lying time and lying bout duration, lower standing time, fewer standing and walking bouts, fewer, slower and shorter strides and a lower walking speed. The model considering the number of standing bouts and walking speed was the best predictor of cows being lame with a sensitivity of 90.2% and specificity of 91.7%. Sensitivity and specificity of the lameness detection model were considered to be very high, even without the use of halter data. It was concluded that under the conditions of the study farm, accelerometer data were suitable for accurately distinguishing between lame and non-lame dairy cows, even in cases of slight lameness with a gait score of 2.5. PMID:27187073

Use of Extended Characteristics of Locomotion and Feeding Behavior for Automated Identification of Lame Dairy Cows.

PubMed

Beer, Gian; Alsaaod, Maher; Starke, Alexander; Schuepbach-Regula, Gertraud; Müller, Hendrik; Kohler, Philipp; Steiner, Adrian

2016-01-01

This study was carried out to detect differences in locomotion and feeding behavior in lame (group L; n = 41; gait score ≥ 2.5) and non-lame (group C; n = 12; gait score ≤ 2) multiparous Holstein cows in a cross-sectional study design. A model for automatic lameness detection was created, using data from accelerometers attached to the hind limbs and noseband sensors attached to the head. Each cow's gait was videotaped and scored on a 5-point scale before and after a period of 3 consecutive days of behavioral data recording. The mean value of 3 independent experienced observers was taken as a definite gait score and considered to be the gold standard. For statistical analysis, data from the noseband sensor and one of two accelerometers per cow (randomly selected) of 2 out of 3 randomly selected days was used. For comparison between group L and group C, the T-test, the Aspin-Welch Test and the Wilcoxon Test were used. The sensitivity and specificity for lameness detection was determined with logistic regression and ROC-analysis. Group L compared to group C had significantly lower eating and ruminating time, fewer eating chews, ruminating chews and ruminating boluses, longer lying time and lying bout duration, lower standing time, fewer standing and walking bouts, fewer, slower and shorter strides and a lower walking speed. The model considering the number of standing bouts and walking speed was the best predictor of cows being lame with a sensitivity of 90.2% and specificity of 91.7%. Sensitivity and specificity of the lameness detection model were considered to be very high, even without the use of halter data. It was concluded that under the conditions of the study farm, accelerometer data were suitable for accurately distinguishing between lame and non-lame dairy cows, even in cases of slight lameness with a gait score of 2.5.

Selectivity and direct visualization of carbon dioxide and sulfur dioxide in a decorated porous host.

PubMed

Yang, Sihai; Sun, Junliang; Ramirez-Cuesta, Anibal J; Callear, Samantha K; David, William I F; Anderson, Daniel P; Newby, Ruth; Blake, Alexander J; Parker, Julia E; Tang, Chiu C; Schröder, Martin

2012-11-01

Understanding the mechanism by which porous solids trap harmful gases such as CO(2) and SO(2) is essential for the design of new materials for their selective removal. Materials functionalized with amine groups dominate this field, largely because of their potential to form carbamates through H(2)N(δ(-))···C(δ(+))O(2) interactions, thereby trapping CO(2) covalently. However, the use of these materials is energy-intensive, with significant environmental impact. Here, we report a non-amine-containing porous solid (NOTT-300) in which hydroxyl groups within pores bind CO(2) and SO(2) selectively. In situ powder X-ray diffraction and inelastic neutron scattering studies, combined with modelling, reveal that hydroxyl groups bind CO(2) and SO(2) through the formation of O=C(S)=O(δ(-))···H(δ(+))-O hydrogen bonds, which are reinforced by weak supramolecular interactions with C-H atoms on the aromatic rings of the framework. This offers the potential for the application of new 'easy-on/easy-off' capture systems for CO(2) and SO(2) that carry fewer economic and environmental penalties.

Selectivity and direct visualization of carbon dioxide and sulfur dioxide in a decorated porous host

NASA Astrophysics Data System (ADS)

Yang, Sihai; Sun, Junliang; Ramirez-Cuesta, Anibal J.; Callear, Samantha K.; David, William I. F.; Anderson, Daniel P.; Newby, Ruth; Blake, Alexander J.; Parker, Julia E.; Tang, Chiu C.; Schröder, Martin

2012-11-01

Understanding the mechanism by which porous solids trap harmful gases such as CO2 and SO2 is essential for the design of new materials for their selective removal. Materials functionalized with amine groups dominate this field, largely because of their potential to form carbamates through H2N(δ-)···C(δ+)O2 interactions, thereby trapping CO2 covalently. However, the use of these materials is energy-intensive, with significant environmental impact. Here, we report a non-amine-containing porous solid (NOTT-300) in which hydroxyl groups within pores bind CO2 and SO2 selectively. In situ powder X-ray diffraction and inelastic neutron scattering studies, combined with modelling, reveal that hydroxyl groups bind CO2 and SO2 through the formation of O=C(S)=O(δ-)···H(δ+)-O hydrogen bonds, which are reinforced by weak supramolecular interactions with C-H atoms on the aromatic rings of the framework. This offers the potential for the application of new ‘easy-on/easy-off’ capture systems for CO2 and SO2 that carry fewer economic and environmental penalties.

[Meta-analysis of laparoscopic and open repair of perforated peptic ulcer].

PubMed

Ding, Jie; Liao, Guo-qing; Zhang, Zhong-min; Pan, Yang; Li, Dong-miao; Wang, Run-hua; Xu, Kai-sheng; Yang, Xiao-fei; Yuan, Ping; Wang, Shao-yong

2011-10-01

To assess the safety and feasibility of laparoscopic and open repair of perforated peptic ulcer. Studies on comparison between laparoscopic repair(LR) and open repair(OR) of perforated peptic ulcer were collected. Data of operating time, blood loss, time to first flatus, postoperative hospital stay, postoperative complications and mortality between LR group and OR group were meta-analyzed using fixed effect model and random effect model. Nineteen studies including 1507 patients were selected for this study,including laparoscopic surgery(n=673) and open surgery(n=834). There were significant differences in blood loss, time to first flatus, postoperative hospital stay, wound infection rate and mortality between LR group and OR group. However, no significant differences existed in operative time, postoperative sepsis, pulmonary infection, abdominal abscess, and suture leakage between the two groups. Laparoscopic repair of perforated peptic ulcer is associated with improved outcomes in terms of less blood loss, quicker recovery, and lower rates of wound infection and mortality. Laparoscopic repair of perforated peptic ulcer is safe and feasible.

[Effects of electroacupuncture at "Yishu" (EX-B 3) on the relative hormones of HPA axis in rats with type-2 diabetes mellitus].

PubMed

Gao, Shana; Li, Rui; Tian, Huan-huan; Pei, En-shi; Cao, Bing-yan; Wu, Yan

2014-11-01

To observe the intervention effects of electroacupuncture at "Yishu" (EX-B 3) on rats with type-2 diabetes mellitus (T2DM), so as to provide experiment references for acupuncture to treat T2DM. Among seventy male Wistar clean-grade rats, 8 rats were randomly selected into a control group; the rest rats were made T2DM model. Fifty-two rats which were successfully made T2DM model, according to randomized block method, were divided into a model group (10 rats), a medication group (10 rats), an electroacupuncture at "Shenshu" (BL 23) group (11 rats), an electroacupuncture at "Pishu" (BL 20) group (10 rats) and an electroacupuncture at "Yishu" (EX-B 3) group (11 rats). Seven days after successful establishment of model, the rats in the model group were fixed in the self-made rat bag without receiving any treatment; the rats in the medication group, according to body mass (10 mL/kg), were treated with intragastric administration of glimepiride; the rats in all the electroacupuncture groups were treated with electroacupuncture at "Shenshu" (BL 23), "Pishu" (BL 20) and "Yishu" (EX-B 3), respectively. The continuous wave was selected with a frequency of 15 Hz and a current intensity of 4 to 6 mA. The treatment was given 20 min per treatment, once a day, 5 treatments per week for continuous 4 weeks. Before the establishment of model and continuous 4 weeks after the intervention, blood samples were collected from rats' caudal vein, and fasting blood glucose (FBG) was measured with FBG device each week. After the last intervention, the rats were killed and hypothalamus, pituitary and adrenal gland were collected. The colorimetric method was applied to measure the contents of triglyceride (TG), cholesterol (TC), high-density lipoprotein (HDL-C) and low-density lipoprotein (LDL-C); radioimmunoassay was used to test the contents of glycated serum protein (GSP), fasting insulin (FINS), corticotropin-releasing hormone (CRH), adrenocorticotropic hormone (ACTH) and cortin (CORT). Four weeks after the intervention, except that the rat's body mass in the normal group continued to increase, body mass in the model group, medication group and each electroacupuncture group were significantly reduced (P<0.01, P<0.05). Compared with the model group, the FBG in the electroacupuncture at "Pishu" (BL 20) group and electroacupuncture at "Yishu" (EX-B 3) group were obviously reduced (P<0.05, P<0.01); FBG in the electroacupuncture at "Yishu" (EX-B 3) group was lower than that in the medication group and electroacupuncture at "Shenshu" (BL 23) group (both P<0.05). The contents of TG, HDL-C and LDL-C in the electroacupuncture at "Yishu" (EX-B 3) group were reduced (P<0.05, P<0.01), the content of TG was significantly lower than that in the medication group and electroacupuncture at "Shenshu" (BL 23) group (both P<0.05), the content of LDL-C was significantly lower than that in electroacupuncture at "Shenshu" (BL 23) group (P<0.05). Insulin sensitivity index (ISI) in the medication group, electroacupuncture at "Pishu" (BL 20) group and electroacupuncture at "Yishu (EX-B 3)" group were evidently increased (P<0.05, P<0.01); ISI in the medication group was lower than that in the electroacupuncture at "Yishu" (EX-B 3) group (P<0.05). The content of CRH in the electroacupuncture at "Yishu" (EX-B 3) group was lower than that in the medication group and electroacupuncture at "Shenshu" (BL 23) group (P<0.05, P<0.01); the content of CORT in the electroacupuncture at "Yishu" (EX-B 3) group was lower than that in the medication group and electroacupuncture at "Pishu" (BL 20) group (both P<0.05). Electroacupuncture at "Yishu" (EX-B 3) could reduce the level of CORT to improve the insulin resistance in rats with T2DM, improve insulin sensitivity index, regulate blood lipid metabolism and relieve the hyperactivity of the HPA axis.

Group sparse multiview patch alignment framework with view consistency for image classification.

PubMed

Gui, Jie; Tao, Dacheng; Sun, Zhenan; Luo, Yong; You, Xinge; Tang, Yuan Yan

2014-07-01

No single feature can satisfactorily characterize the semantic concepts of an image. Multiview learning aims to unify different kinds of features to produce a consensual and efficient representation. This paper redefines part optimization in the patch alignment framework (PAF) and develops a group sparse multiview patch alignment framework (GSM-PAF). The new part optimization considers not only the complementary properties of different views, but also view consistency. In particular, view consistency models the correlations between all possible combinations of any two kinds of view. In contrast to conventional dimensionality reduction algorithms that perform feature extraction and feature selection independently, GSM-PAF enjoys joint feature extraction and feature selection by exploiting l(2,1)-norm on the projection matrix to achieve row sparsity, which leads to the simultaneous selection of relevant features and learning transformation, and thus makes the algorithm more discriminative. Experiments on two real-world image data sets demonstrate the effectiveness of GSM-PAF for image classification.

On selection of primary modes for generation of strong internally resonant second harmonics in plate

NASA Astrophysics Data System (ADS)

Liu, Yang; Chillara, Vamshi Krishna; Lissenden, Cliff J.

2013-09-01

The selection of primary shear-horizontal (SH) and Rayleigh-Lamb (RL) ultrasonic wave modes that generate cumulative second harmonics in homogeneous isotropic plates is analyzed by theoretical modeling. Selection criteria include: internal resonance (synchronism and nonzero power flux), group velocity matching, and excitability/receivability. The power flux, group velocity matching, and excitability are tabulated for the SH and RL internal resonance points. The analysis indicates that SH waves can generate cumulative symmetric RL secondary wave fields. Laboratory experiments on aluminum plates demonstrate that excitation of the SH3 primary mode generates the s4 secondary RL mode and that the secondary wave field amplitude increases linearly with propagation distance. Simple magnetostrictive transducers were used to excite the primary SH wave and to receive the SH and RL wave signals. Reception of these wave modes having orthogonal polarizations was achieved by simply reorienting the electrical coil. The experiment was complicated by the presence of a nonplanar primary wavefront, however finite element simulations were able to clarify the experimental results.

Serial grouping of 2D-image regions with object-based attention in humans.

PubMed

Jeurissen, Danique; Self, Matthew W; Roelfsema, Pieter R

2016-06-13

After an initial stage of local analysis within the retina and early visual pathways, the human visual system creates a structured representation of the visual scene by co-selecting image elements that are part of behaviorally relevant objects. The mechanisms underlying this perceptual organization process are only partially understood. We here investigate the time-course of perceptual grouping of two-dimensional image-regions by measuring the reaction times of human participants and report that it is associated with the gradual spread of object-based attention. Attention spreads fastest over large and homogeneous areas and is slowed down at locations that require small-scale processing. We find that the time-course of the object-based selection process is well explained by a 'growth-cone' model, which selects surface elements in an incremental, scale-dependent manner. We discuss how the visual cortical hierarchy can implement this scale-dependent spread of object-based attention, leveraging the different receptive field sizes in distinct cortical areas.

Aminoacyl transfer from an adenylate anhydride to polyribonucleotides

NASA Technical Reports Server (NTRS)

Weber, A. L.; Lacey, J. C., Jr.

1975-01-01

Imidazole catalysis of phenylalanyl transfer from phenylalanine adenylate to hydroxyl groups of homopolyribonucleotides is studied as a possible chemical model of biochemical aminoacylation of transfer RNA (tRNA). The effect of pH on imidazole-catalyzed transfer of phenylalanyl residues to poly(U) and poly(A) double helix strands, the number of peptide linkages and their lability to base and neutral hydroxylamine, and the nature of adenylate condensation products are investigated. The chemical model entertained exhibits a constraint by not acylating the hydroxyl groups of polyribonucleotides in a double helix. The constraint is consistent with selective biochemical aminoacylation at the tRNA terminus. Interest in imidazole as a model of histidine residue in protoenzymes participating in prebiotic aminoacyl transfer to polyribonucleotides, and in rendering the tRNA a more efficient adaptor, is indicated.

Learning from Past Classification Errors: Exploring Methods for Improving the Performance of a Deep Learning-based Building Extraction Model through Quantitative Analysis of Commission Errors for Optimal Sample Selection

NASA Astrophysics Data System (ADS)

Swan, B.; Laverdiere, M.; Yang, L.

2017-12-01

In the past five years, deep Convolutional Neural Networks (CNN) have been increasingly favored for computer vision applications due to their high accuracy and ability to generalize well in very complex problems; however, details of how they function and in turn how they may be optimized are still imperfectly understood. In particular, their complex and highly nonlinear network architecture, including many hidden layers and self-learned parameters, as well as their mathematical implications, presents open questions about how to effectively select training data. Without knowledge of the exact ways the model processes and transforms its inputs, intuition alone may fail as a guide to selecting highly relevant training samples. Working in the context of improving a CNN-based building extraction model used for the LandScan USA gridded population dataset, we have approached this problem by developing a semi-supervised, highly-scalable approach to select training samples from a dataset of identified commission errors. Due to the large scope this project, tens of thousands of potential samples could be derived from identified commission errors. To efficiently trim those samples down to a manageable and effective set for creating additional training sample, we statistically summarized the spectral characteristics of areas with rates of commission errors at the image tile level and grouped these tiles using affinity propagation. Highly representative members of each commission error cluster were then used to select sites for training sample creation. The model will be incrementally re-trained with the new training data to allow for an assessment of how the addition of different types of samples affects the model performance, such as precision and recall rates. By using quantitative analysis and data clustering techniques to select highly relevant training samples, we hope to improve model performance in a manner that is resource efficient, both in terms of training process and in sample creation.

A preclinical model of binge eating elicited by yo-yo dieting and stressful exposure to food: effect of sibutramine, fluoxetine, topiramate, and midazolam.

PubMed

Cifani, Carlo; Polidori, Carlo; Melotto, Sergio; Ciccocioppo, Roberto; Massi, Maurizio

2009-05-01

Preclinical models are needed to investigate the neurobiology and psychobiology of binge eating and to identify innovative pharmacotherapeutic strategies. A modification of the model based on the combination of cyclic caloric restrictions and acute stress was developed to further increase its face validity and reliability and, for the first time, to assess its predictive value. Four groups of female rats were employed: group 1 was normally fed and not stressed on the test day (25th); group 2 was fed normally but was exposed to an acute stress on day 25; group 3 was exposed to three cycles (4 days 66% of chow intake + 4 days food ad libitum) of yo-yo dieting but not stressed; and group 4 was exposed to cyclic yo-yo dieting and then stressed. All groups were fed highly palatable food (HPF) for 2 h on days 5-6 and 13-14. Acute stress was elicited by exposing rats to HPF, but preventing them from access to it for 15 min. The combination of cyclic food restriction and stressful exposure to food markedly increased HPF intake. Sibutramine and fluoxetine inhibited food intake in all conditions. Topiramate selectively inhibited compulsive HPF intake in rats submitted to caloric restriction and stress. Midazolam increased HPF intake. Pharmacological results suggest that this model, in addition to face validity as an isomorphic model of human binge eating, is endowed with good predictive validity.

[Effect of Acupoint Injection on Eosinophil Counts,Protein and mRNA Expressions of Eotaxin in Nasal Mucosa of Allergic Rhinitis Rats].

PubMed

Zhang, Yuan; Hou, Xun-Rui; Li, Li-Hong; Yang, Meng; Liang, Fei-Hong

2017-04-25

To observe the effect of acupoint injection on eosinophils (EOS) counts and expression of eotaxin in nasal mucosa of allergic rhinitis (AR) rats, so as to reveal its mechanism underlying improving AR. Twenty-four Sprague-Dawley (SD) rats were randomly divided into normal, model and acupoint injection groups ( n =8 in each group). The AR model was established by intraperitoneal injection of ovalbumin sensitization. Bilateral "Yingxiang"(LI 20) and "Yintang"(GV 29) were selected for acupoint injection of the mixture solution of lidocaine, dexamethasone, and transfer factor (0.1 mL/acupoint) on the 1 st , 5 th , 9 th , and 13 th day after AR model established, a total of four times. EOS in the nasal mucosa was counted under light microscope after HE staining. Protein and mRNA expressions of eotaxin in the nasal mucosa were detected by immunohistochemical and RT-PCR methods, respectively. Compared with the normal group, EOS counts, protein and mRNA expressions of eotaxin in the nasal mucosa were significantly higher in the model group ( P <0.05). Compared with the model group, EOS counts, protein and mRNA expressions of eotaxin in the nasal mucosa were significantly lower in the acupoint injection group ( P <0.05). Acupoint injection can reduce the nasal mucosa inflammation by suppressing the protein and mRNA expressions of eotaxin, decreasing the infiltration and gathering of EOS in the nasal mucosa.

Emergence of parochial altruism in well-mixed populations of multiple groups

NASA Astrophysics Data System (ADS)

Gao, Shiping; Wu, Te; Nie, Suli; Wang, Long

2015-10-01

Understanding the evolution of parochial altruism is of great importance. We here institute an analytical model to study the emergence of parochial altruism in group-structured populations. Individuals' strategy is contingent on interacting partners' group property. Only when sharing common tag(s), they play the prisoner's dilemma game; otherwise they play the punishment game. The conditions for the emergence of parochial altruism are specified for weak selection. Emergence of parochial altruism is promoted by assortment as well as by intergroup punishment. Furthermore, the affiliation plays a negative (positive) role in the emergence of parochial altruism for low (high) mutation.

[Effects of Tongluo Xingnao effervescent tablets on blood rheology, iNOS, VEGF and LDH-5 in MID rats].

PubMed

Ren, Xiang-Yi; Hu, Yong; Wei, Jiang-Ping; Fu, Wen-Jun; Xu, Shi-Jun; Wang, Yong-Yan

2016-03-01

The study was to explore effects of Tongluo Xingnao effervescent tablets on the blood rheology, iNOS, VEGF and LDH-5 in multi-infarct dementia(MID) model rats. Establish MID model rats were induced by microthrombosis, from which 50 successful model rats were randomly divided into five groups, such as the model control group, the dihydroergotoxine mesylate tablets(hydergine) group(0.7 mg•kg⁻¹), Tongluo Xingnao effervescent tablets high-dose, medium-dose and low-dose groups(7.56, 3.78, 1.89 g•kg⁻¹). Another ten rats in the sham group were randomly selected as the parallel control group. Each group was orally administered with drugs for 90 days. The learning and memory ability was evaluated with the Morris water maze test, while the whole blood viscosity and the erythrocyte aggregation index derived from abdominal aorta were measured in different shear rates. In addition, the levels of VEGF and iNOS in the serum were determined by ELISA kits. The expression of LDH-5 in hippocampus of rats was measured with immunohistochemistry and image quantitative analysis. The result showed that Tongluo Xingnao effervescent tablets notably decreased the escape latency of MID model rats, increased times of entering into the escape platform and prolonged retention time in medium ring, meanwhile the whole blood viscosity in MID model rats was also notably reduced in four shear rates, i.e. 1, 5, 30, 200 S⁻¹, erythrocyte aggregation index, serum VEGF and iNOS, and average optical density value of LDH-5, with a statistically significant differences compared with the model control group (P<0.05). In conclusion, Tongluo Xingnao effervescent tablets could improve the ability of learning and memory of MID model rats and the blood rheology, reduce the level of iNOS, VEGF and the expression of LDH-5, and then improved the brain energy supply. Copyright© by the Chinese Pharmaceutical Association.

Toward the definition of stereochemical requirements for MT2-selective antagonists and partial agonists by studying 4-phenyl-2-propionamidotetralin derivatives.

PubMed

Bedini, Annalida; Lucarini, Simone; Spadoni, Gilberto; Tarzia, Giorgio; Scaglione, Francesco; Dugnani, Silvana; Pannacci, Marilou; Lucini, Valeria; Carmi, Caterina; Pala, Daniele; Rivara, Silvia; Mor, Marco

2011-12-22

New derivatives of 4-phenyl-2-propionamidotetralin (4-P-PDOT) were prepared and tested on cloned MT1 and MT2 receptors, with the purpose of merging previously reported pharmacophores for nonselective agonists and for MT2-selective antagonists. A 8-methoxy group increases binding affinity of both (±)-cis- and (±)-trans-4-P-PDOT, and it can be bioisosterically replaced by a bromine. Conformational analysis of 8-methoxy-4-P-PDOT by molecular dynamics, supported by NMR data, revealed an energetically favored conformation for the (2S,4S)-cis isomer and a less favorable conformation for the (2R,4S)-trans one, fulfilling the requirements of a pharmacophore model for nonselective melatonin receptor agonists. A new superposition model, including features characteristic of MT2-selective antagonists, suggests that MT1/MT2 agonists and MT2 antagonists can share the same arrangement for their pharmacophoric elements. The model correctly predicted the eutomers of (±)-cis- and (±)-trans-4-P-PDOT. The model was validated by preparing three dihydronaphthalene derivatives, either able or not able to reproduce the putative active conformation of 4-P-PDOT.

Exploring the effect of oxygen-containing functional groups on the water-holding capacity of lignite.

PubMed

Liu, Jie; Jiang, Xiangang; Cao, Yu; Zhang, Chen; Zhao, Guangyao; Zhao, Maoshuang; Feng, Li

2018-05-07

Graphene oxide with different degrees of oxidation was prepared and selected as a model compound of lignite to study quantitatively, using both experiment and theoretical calculation methods, the effect on water-holding capacity of oxygen-containing functional groups. The experimental results showed that graphite can be oxidized, and forms epoxy groups most easily, followed by hydroxyl and carboxyl groups. The prepared graphene oxide forms a membrane-state as a single layer structure, with an irregular surface. The water-holding capacity of lignite increased with the content of oxygen-containing functional groups. The influence on the configuration of water molecule clusters and binding energy of water molecules of different oxygen-containing functional groups was calculated by density functional theory. The calculation results indicated that the configuration of water molecule clusters was totally changed by oxygen-containing functional groups. The order of binding energy produced by oxygen-containing functional groups and water molecules was as follows: carboxyl > edge phenol hydroxyl >epoxy group. Finally, it can be concluded that the potential to form more hydrogen bonds is the key factor influencing the interaction energy between model compounds and water molecules.

Quantitative structure-activity relationship (QSAR) for insecticides: development of predictive in vivo insecticide activity models.

PubMed

Naik, P K; Singh, T; Singh, H

2009-07-01

Quantitative structure-activity relationship (QSAR) analyses were performed independently on data sets belonging to two groups of insecticides, namely the organophosphates and carbamates. Several types of descriptors including topological, spatial, thermodynamic, information content, lead likeness and E-state indices were used to derive quantitative relationships between insecticide activities and structural properties of chemicals. A systematic search approach based on missing value, zero value, simple correlation and multi-collinearity tests as well as the use of a genetic algorithm allowed the optimal selection of the descriptors used to generate the models. The QSAR models developed for both organophosphate and carbamate groups revealed good predictability with r(2) values of 0.949 and 0.838 as well as [image omitted] values of 0.890 and 0.765, respectively. In addition, a linear correlation was observed between the predicted and experimental LD(50) values for the test set data with r(2) of 0.871 and 0.788 for both the organophosphate and carbamate groups, indicating that the prediction accuracy of the QSAR models was acceptable. The models were also tested successfully from external validation criteria. QSAR models developed in this study should help further design of novel potent insecticides.

Predicting mortality over different time horizons: which data elements are needed?

PubMed

Goldstein, Benjamin A; Pencina, Michael J; Montez-Rath, Maria E; Winkelmayer, Wolfgang C

2017-01-01

Electronic health records (EHRs) are a resource for "big data" analytics, containing a variety of data elements. We investigate how different categories of information contribute to prediction of mortality over different time horizons among patients undergoing hemodialysis treatment. We derived prediction models for mortality over 7 time horizons using EHR data on older patients from a national chain of dialysis clinics linked with administrative data using LASSO (least absolute shrinkage and selection operator) regression. We assessed how different categories of information relate to risk assessment and compared discrete models to time-to-event models. The best predictors used all the available data (c-statistic ranged from 0.72-0.76), with stronger models in the near term. While different variable groups showed different utility, exclusion of any particular group did not lead to a meaningfully different risk assessment. Discrete time models performed better than time-to-event models. Different variable groups were predictive over different time horizons, with vital signs most predictive for near-term mortality and demographic and comorbidities more important in long-term mortality. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

A Novel Group-Fused Sparse Partial Correlation Method for Simultaneous Estimation of Functional Networks in Group Comparison Studies.

PubMed

Liang, Xiaoyun; Vaughan, David N; Connelly, Alan; Calamante, Fernando

2018-05-01

The conventional way to estimate functional networks is primarily based on Pearson correlation along with classic Fisher Z test. In general, networks are usually calculated at the individual-level and subsequently aggregated to obtain group-level networks. However, such estimated networks are inevitably affected by the inherent large inter-subject variability. A joint graphical model with Stability Selection (JGMSS) method was recently shown to effectively reduce inter-subject variability, mainly caused by confounding variations, by simultaneously estimating individual-level networks from a group. However, its benefits might be compromised when two groups are being compared, given that JGMSS is blinded to other groups when it is applied to estimate networks from a given group. We propose a novel method for robustly estimating networks from two groups by using group-fused multiple graphical-lasso combined with stability selection, named GMGLASS. Specifically, by simultaneously estimating similar within-group networks and between-group difference, it is possible to address inter-subject variability of estimated individual networks inherently related with existing methods such as Fisher Z test, and issues related to JGMSS ignoring between-group information in group comparisons. To evaluate the performance of GMGLASS in terms of a few key network metrics, as well as to compare with JGMSS and Fisher Z test, they are applied to both simulated and in vivo data. As a method aiming for group comparison studies, our study involves two groups for each case, i.e., normal control and patient groups; for in vivo data, we focus on a group of patients with right mesial temporal lobe epilepsy.

Prognostic model of survival for typical bronchial carcinoid tumours: analysis of 1109 patients on behalf of the European Association of Thoracic Surgeons (ESTS) Neuroendocrine Tumours Working Group.

PubMed

Filosso, Pier Luigi; Guerrera, Francesco; Evangelista, Andrea; Welter, Stefan; Thomas, Pascal; Casado, Paula Moreno; Rendina, Erino Angelo; Venuta, Federico; Ampollini, Luca; Brunelli, Alessandro; Stella, Franco; Nosotti, Mario; Raveglia, Federico; Larocca, Valentina; Rena, Ottavio; Margaritora, Stefano; Ardissone, Francesco; Travis, William D; Sarkaria, Inderpal; Sagan, Dariusz

2015-09-01

Typical carcinoids (TCs) are uncommon, slow-growing neoplasms, usually with high 5-year survival rates. As these are rare tumours, their management is still based on small clinical observations and no international guidelines exist. Based on the European Society of Thoracic Surgeon Neuroendocrine Tumours Working Group (NET-WG) Database, we evaluated factors that may influence TCs mortality. Using the NET-WG database, an analysis on TC survival was performed. Overall survival (OS) was calculated starting from the date of intervention. Predictors of OS were investigated using the Cox model with shared frailty (accounting for the within-centre correlation). Candidate predictors were: gender, age, smoking habit, tumour location, previous malignancy, Eastern Cooperative Oncology Group (ECOG) performance status (PS), pT, pN, TNM stage and tumour vascular invasion. The final model included predictors with P ≤ 0.15 after a backward selection. Missing data in the evaluated predictors were multiple-imputed and combined estimates were obtained from five imputed data sets. For 58 of 1167 TC patients vital status was unavailable and analyses were therefore performed on 1109 patients from 17 institutions worldwide. During a median follow-up of 50 months, 87 patients died, with a 5-year OS rate of 93.7% (95% confidence interval: 91.7-95.3). Backward selection resulted in a prediction model for mortality containing age, gender, previous malignancies, peripheral tumour, TNM stage and ECOG PS. The final model showed a good discrimination ability with a C-statistic equal to 0.836 (bootstrap optimism-corrected 0.806). We presented and validated a promising prognostic model for TC survival, showing good calibration and discrimination ability. Further analyses are needed and could be focused on an external validation of this model. © The Author 2015. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.

Intermediate-term emotional bookkeeping is necessary for long-term reciprocal grooming partner preferences in an agent-based model of macaque groups

PubMed Central

Evers, Ellen; de Vries, Han; Spruijt, Berry M.

2016-01-01

Whether and how primates are able to maintain long-term affiliative relationships is still under debate. Emotional bookkeeping (EB), the partner-specific accumulation of emotional responses to earlier interactions, is a candidate mechanism that does not require high cognitive abilities. EB is difficult to study in real animals, due to the complexity of primate social life. Therefore, we developed an agent-based model based on macaque behavior, the EMO-model, that implements arousal and two emotional dimensions, anxiety-FEAR and satisfaction-LIKE, which regulate social behavior. To implement EB, model individuals assign dynamic LIKE attitudes towards their group members, integrating partner-specific emotional responses to earlier received grooming episodes. Two key parameters in the model were varied to explore their effects on long-term affiliative relationships: (1) the timeframe over which earlier affiliation is accumulated into the LIKE attitudes; and (2) the degree of partner selectivity. EB over short and long timeframes gave rise to low variation in LIKE attitudes, and grooming partner preferences were only maintained over one to two months. Only EB over intermediate-term timeframes resulted in enough variation in LIKE attitudes, which, in combination with high partner selectivity, enables individuals to differentiate between regular and incidental grooming partners. These specific settings resulted in a strong feedback between differentiated LIKE attitudes and the distribution of grooming, giving rise to strongly reciprocated partner preferences that could be maintained for longer periods, occasionally up to one or two years. Moreover, at these settings the individual’s internal, socio-emotional memory of earlier affiliative episodes (LIKE attitudes) corresponded best to observable behavior (grooming partner preferences). In sum, our model suggests that intermediate-term LIKE dynamics and high partner selectivity seem most plausible for primates relying on emotional bookkeeping to maintain their social bonds. PMID:26839737

Intermediate-term emotional bookkeeping is necessary for long-term reciprocal grooming partner preferences in an agent-based model of macaque groups.

PubMed

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

2016-01-01

Whether and how primates are able to maintain long-term affiliative relationships is still under debate. Emotional bookkeeping (EB), the partner-specific accumulation of emotional responses to earlier interactions, is a candidate mechanism that does not require high cognitive abilities. EB is difficult to study in real animals, due to the complexity of primate social life. Therefore, we developed an agent-based model based on macaque behavior, the EMO-model, that implements arousal and two emotional dimensions, anxiety-FEAR and satisfaction-LIKE, which regulate social behavior. To implement EB, model individuals assign dynamic LIKE attitudes towards their group members, integrating partner-specific emotional responses to earlier received grooming episodes. Two key parameters in the model were varied to explore their effects on long-term affiliative relationships: (1) the timeframe over which earlier affiliation is accumulated into the LIKE attitudes; and (2) the degree of partner selectivity. EB over short and long timeframes gave rise to low variation in LIKE attitudes, and grooming partner preferences were only maintained over one to two months. Only EB over intermediate-term timeframes resulted in enough variation in LIKE attitudes, which, in combination with high partner selectivity, enables individuals to differentiate between regular and incidental grooming partners. These specific settings resulted in a strong feedback between differentiated LIKE attitudes and the distribution of grooming, giving rise to strongly reciprocated partner preferences that could be maintained for longer periods, occasionally up to one or two years. Moreover, at these settings the individual's internal, socio-emotional memory of earlier affiliative episodes (LIKE attitudes) corresponded best to observable behavior (grooming partner preferences). In sum, our model suggests that intermediate-term LIKE dynamics and high partner selectivity seem most plausible for primates relying on emotional bookkeeping to maintain their social bonds.

Investigation on Quantitative Structure Activity Relationships of a Series of Inducible Nitric Oxide.

PubMed

Sharma, Mukesh C; Sharma, S

2016-12-01

A series of 2-dihydro-4-quinazolin with potent highly selective inhibitors of inducible nitric oxide synthase activities was subjected to quantitative structure activity relationships (QSAR) analysis. Statistically significant equations with high correlation coefficient (r 2  = 0.8219) were developed. The k-nearest neighbor model has showed good cross-validated correlation coefficient and external validation values of 0.7866 and 0.7133, respectively. The selected electrostatic field descriptors the presence of blue ball around R1 and R4 in the quinazolinamine moiety showed electronegative groups favorable for nitric oxide synthase activity. The QSAR models may lead to the structural requirements of inducible nitric oxide compounds and help in the design of new compounds.

An Interactive Tool For Semi-automated Statistical Prediction Using Earth Observations and Models

NASA Astrophysics Data System (ADS)

Zaitchik, B. F.; Berhane, F.; Tadesse, T.

2015-12-01

We developed a semi-automated statistical prediction tool applicable to concurrent analysis or seasonal prediction of any time series variable in any geographic location. The tool was developed using Shiny, JavaScript, HTML and CSS. A user can extract a predictand by drawing a polygon over a region of interest on the provided user interface (global map). The user can select the Climatic Research Unit (CRU) precipitation or Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) as predictand. They can also upload their own predictand time series. Predictors can be extracted from sea surface temperature, sea level pressure, winds at different pressure levels, air temperature at various pressure levels, and geopotential height at different pressure levels. By default, reanalysis fields are applied as predictors, but the user can also upload their own predictors, including a wide range of compatible satellite-derived datasets. The package generates correlations of the variables selected with the predictand. The user also has the option to generate composites of the variables based on the predictand. Next, the user can extract predictors by drawing polygons over the regions that show strong correlations (composites). Then, the user can select some or all of the statistical prediction models provided. Provided models include Linear Regression models (GLM, SGLM), Tree-based models (bagging, random forest, boosting), Artificial Neural Network, and other non-linear models such as Generalized Additive Model (GAM) and Multivariate Adaptive Regression Splines (MARS). Finally, the user can download the analysis steps they used, such as the region they selected, the time period they specified, the predictand and predictors they chose and preprocessing options they used, and the model results in PDF or HTML format. Key words: Semi-automated prediction, Shiny, R, GLM, ANN, RF, GAM, MARS

Selective aggressiveness in European free-tailed bats ( Tadarida teniotis): influence of familiarity, age and sex

NASA Astrophysics Data System (ADS)

Ancillotto, Leonardo; Russo, Danilo

2014-03-01

Bats are highly social mammals that often form large groups and represent good models to test the role played by individual status in shaping social relationships. Social cohesion relies on the ability of group and individual recognition, which is mediated by a range of sensorial cues. In this study, we selected the European free-tailed bat Tadarida teniotis as a model species to test the effects of familiarity, sex and age on aggressiveness and mutual tolerance. We hypothesize that T. teniotis is able to recognize group members and exhibit selective aggressiveness, and thus we predict fewer aggressive events and more amicable encounters between colony mates than between strangers. As female bats are generally more sociable and perform prolonged parental care to juveniles even after weaning, we hypothesize that sex and age of bats have significant influences on aggressive behaviours and thus predict that females will perform more amicable behaviours than males and that adults of both sexes will be less aggressive towards juveniles. Our results confirm that T. teniotis is able to discriminate between familiar and stranger individuals, showing higher rates of aggressive behaviours towards the latter. Females are more prone to exhibit amicable behaviours, particularly during same-sex interactions, while males show higher level of aggressiveness. Juveniles are subjected to fewer aggressive behaviours by adults of both sexes. Familiarity appears crucial for T. teniotis in determining the degree of aggressiveness during social interactions but the rate of aggressive events is also influenced by intrinsic individual factors such as sex and age.

Reverse audience effects on helping in cooperatively breeding marmoset monkeys.

PubMed

Brügger, R K; Kappeler-Schmalzriedt, T; Burkart, J M

2018-03-01

Cooperatively breeding common marmosets show substantial variation in the amount of help they provide. Pay-to-stay and social prestige models of helping attribute this variation to audience effects, i.e. that individuals help more if group members can witness their interactions with immatures, whereas models of kin selection, group augmentation or those stressing the need to gain parenting experience do not predict any audience effects. We quantified the readiness of adult marmosets to share food in the presence or absence of other group members. Contrary to both predictions, we found a reverse audience effect on food-sharing behaviour: marmosets would systematically share more food with immatures when no audience was present. Thus, helping in common marmosets, at least in related family groups, does not support the pay-to-stay or the social prestige model, and helpers do not take advantage of the opportunity to engage in reputation management. Rather, the results appear to reflect a genuine concern for the immatures' well-being, which seems particularly strong when solely responsible for the immatures. © 2018 The Author(s).

Family ties: the multilevel effects of households and kinship on the networks of individuals.

PubMed

Koster, Jeremy

2018-04-01

Among social mammals, humans uniquely organize themselves into communities of households that are centred around enduring, predominantly monogamous unions of men and women. As a consequence of this social organization, individuals maintain social relationships both within and across households, and potentially there is conflict among household members about which social ties to prioritize or de-emphasize. Extending the logic of structural balance theory, I predict that there will be considerable overlap in the social networks of individual household members, resulting in a pattern of group-level reciprocity. To test this prediction, I advance the Group-Structured Social Relations Model, a generalized linear mixed model that tests for group-level effects in the inter-household social networks of individuals. The empirical data stem from social support interviews conducted in a community of indigenous Nicaraguan horticulturalists, and model results show high group-level reciprocity among households. Although support networks are organized around kinship, covariates that test predictions of kin selection models do not receive strong support, potentially because most kin-directed altruism occurs within households, not between households. In addition, the models show that households with high genetic relatedness in part from children born to adulterous relationships are less likely to assist each other.

A modular approach for item response theory modeling with the R package flirt.

PubMed

Jeon, Minjeong; Rijmen, Frank

2016-06-01

The new R package flirt is introduced for flexible item response theory (IRT) modeling of psychological, educational, and behavior assessment data. flirt integrates a generalized linear and nonlinear mixed modeling framework with graphical model theory. The graphical model framework allows for efficient maximum likelihood estimation. The key feature of flirt is its modular approach to facilitate convenient and flexible model specifications. Researchers can construct customized IRT models by simply selecting various modeling modules, such as parametric forms, number of dimensions, item and person covariates, person groups, link functions, etc. In this paper, we describe major features of flirt and provide examples to illustrate how flirt works in practice.

Synthesis of [.sup.13C] and [.sup.2H] substituted methacrylic acid, [.sup.13C] and [.sup.2H] substituted methyl methacrylate and/or related compounds

DOEpatents

Alvarez, Marc A.; Martinez, Rodolfo A.; Unkefer, Clifford J.

2010-02-16

The present invention is directed to labeled compounds of the formulae ##STR00001## wherein Q is selected from the group consisting of --S(.dbd.O)--, and --S(.dbd.O).sub.2--, Z is selected from the group consisting of 1-naphthyl, substituted 1-naphthyl, 2-naphthyl, substituted 2-naphthyl, and phenyl groups with the structure ##STR00002## wherein R.sub.1, R.sub.2, R.sub.3, R.sub.4 and R.sub.5 are each independently selected from the group consisting of hydrogen, a C.sub.1-C.sub.4 lower alkyl, a halogen, and an amino group selected from the group consisting of NH.sub.2, NHR and NRR' where R and R' are each independently selected from the group consisting of a C.sub.1-C.sub.4 lower alkyl, an aryl, and an alkoxy group, and X is selected from the group consisting of hydrogen, a C.sub.1-C.sub.4 lower alkyl group, and a fully-deuterated C.sub.1-C.sub.4 lower alkyl group.

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.

Modeling the two-locus architecture of divergent pollinator adaptation: how variation in SAD paralogs affects fitness and evolutionary divergence in sexually deceptive orchids.

PubMed

Xu, Shuqing; Schlüter, Philipp M

2015-01-01

Divergent selection by pollinators can bring about strong reproductive isolation via changes at few genes of large effect. This has recently been demonstrated in sexually deceptive orchids, where studies (1) quantified the strength of reproductive isolation in the field; (2) identified genes that appear to be causal for reproductive isolation; and (3) demonstrated selection by analysis of natural variation in gene sequence and expression. In a group of closely related Ophrys orchids, specific floral scent components, namely n-alkenes, are the key floral traits that control specific pollinator attraction by chemical mimicry of insect sex pheromones. The genetic basis of species-specific differences in alkene production mainly lies in two biosynthetic genes encoding stearoyl-acyl carrier protein desaturases (SAD) that are associated with floral scent variation and reproductive isolation between closely related species, and evolve under pollinator-mediated selection. However, the implications of this genetic architecture of key floral traits on the evolutionary processes of pollinator adaptation and speciation in this plant group remain unclear. Here, we expand on these recent findings to model scenarios of adaptive evolutionary change at SAD2 and SAD5, their effects on plant fitness (i.e., offspring number), and the dynamics of speciation. Our model suggests that the two-locus architecture of reproductive isolation allows for rapid sympatric speciation by pollinator shift; however, the likelihood of such pollinator-mediated speciation is asymmetric between the two orchid species O. sphegodes and O. exaltata due to different fitness effects of their predominant SAD2 and SAD5 alleles. Our study not only provides insight into pollinator adaptation and speciation mechanisms of sexually deceptive orchids but also demonstrates the power of applying a modeling approach to the study of pollinator-driven ecological speciation.

Genome-wide selective sweeps and gene-specific sweeps in natural bacterial populations

DOE PAGES

Bendall, Matthew L.; Stevens, Sarah L.R.; Chan, Leong-Keat; ...

2016-01-08

Multiple models describe the formation and evolution of distinct microbial phylogenetic groups. These evolutionary models make different predictions regarding how adaptive alleles spread through populations and how genetic diversity is maintained. Processes predicted by competing evolutionary models, for example, genome-wide selective sweeps vs gene-specific sweeps, could be captured in natural populations using time-series metagenomics if the approach were applied over a sufficiently long time frame. Direct observations of either process would help resolve how distinct microbial groups evolve. Using a 9-year metagenomic study of a freshwater lake (2005–2013), we explore changes in single-nucleotide polymorphism (SNP) frequencies and patterns of genemore » gain and loss in 30 bacterial populations. SNP analyses revealed substantial genetic heterogeneity within these populations, although the degree of heterogeneity varied by >1000-fold among populations. SNP allele frequencies also changed dramatically over time within some populations. Interestingly, nearly all SNP variants were slowly purged over several years from one population of green sulfur bacteria, while at the same time multiple genes either swept through or were lost from this population. Furthermore, these patterns were consistent with a genome-wide selective sweep in progress, a process predicted by the ‘ecotype model’ of speciation but not previously observed in nature. In contrast, other populations contained large, SNP-free genomic regions that appear to have swept independently through the populations prior to the study without purging diversity elsewhere in the genome. Finally, evidence for both genome-wide and gene-specific sweeps suggests that different models of bacterial speciation may apply to different populations coexisting in the same environment.« less

Propulsion and Energetics Panel Working Group 15 on the Uniform Engine Test Programme

DTIC Science & Technology

1990-02-01

earlier test of uniform aerodynamic models in wind tunnels under the auspices of the Fluid Dynamics Panel. A formal proposal was presented to the...this major new effort and members of the engine test community throughout AGARD were selected to serve on Working Group 15 along with PEP...STPA/MO 4 Mr J.R.Bednarsk; 4 Avenue de Ia Porte d’lssy PE-63 75015 Paris Naval Air Propulsion Center PO Box 7176 GERMANY Trenton. New Jersey 08628

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

PubMed

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

2016-06-10

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

The selective kappa-opioid receptor agonist U50,488H attenuates voluntary ethanol intake in the rat.

PubMed

Lindholm, S; Werme, M; Brené, S; Franck, J

2001-05-01

Non-selective opioid receptor antagonists are increasingly used in the treatment of alcohol dependence. The clinical effects are significant but the effect size is rather small and unpleasant side effects may limit the benefits of the compounds. Ligands acting at mu- and/or delta- receptors can alter the voluntary intake of ethanol in various animal models. Therefore, the attenuating effects of selective opioid receptor ligands on ethanol intake may be of clinical interest in the treatment of alcoholism. The objective of this study was to examine the effects of a selective kappa-receptor agonist, U50,488H on voluntary ethanol intake in the rat. We used a restricted access model with a free choice between an ethanol solution (10% v/v) and water. During the 3-days baseline period, the rats received a daily saline injection (1 ml/kg, i.p.) 15 min before the 2 h access to ethanol. The animals had free access to water at all times. The control group received a daily saline injection during the 4-days treatment-period, whereas the treatment groups received a daily dose of U50,488H (2.5, 5.0 or 10 mg/kg per day). Animals treated with U50,488H dose-dependently decreased their ethanol intake. The effect of the highest dose of U50,488H was reduced by pre-treatment with the selective kappa-antagonist nor-binaltorphimine (nor-BNI). These results demonstrate that activation of kappa-opioid receptors can attenuate voluntary ethanol intake in the rat, and the data suggest that the brain dynorphin/kappa-receptor systems may represent a novel target for pharmacotherapy in the treatment of alcohol dependence.

The efficacy and safety of selective leukocytapheresis in the treatment of ulcerative colitis: a meta-analysis.

PubMed

Zhu, Mingming; Xu, Xitao; Nie, Fang; Tong, Jinlu; Xiao, Shudong; Ran, Zhihua

2011-08-01

The use of selective leukocytapheresis for the treatment of ulcerative colitis (UC) has been evaluated in several open and controlled trials, with varying outcomes. A meta-analysis was performed to better assess the efficacy and safety of selective leukocytapheresis as supplemental therapy compared with conventional pharmacotherapy in patients with UC. All randomized trials comparing selective leukocytapheresis supplementation with conventional pharmacotherapy were included from electronic databases and reference lists. A meta-analysis that pooled the outcome effects of leukocytapheresis and pharmacotherapy was performed. A fixed effect model or random effect model was selected depending on the heterogeneity test of the trials. Nine randomized controlled trials met the inclusion criteria contributing a total of 686 participants. Compared with conventional pharmacotherapy, leukocytapheresis supplementation presented a significant benefit in promoting a response rate (OR, 2.88, 95% CI: 1.60-5.18) and remission rate (OR, 2.04; 95% CI, 1.36-3.07) together with significant higher steroid-sparing effects (OR, 10.49; 95% CI, 3.44-31.93) in patients with active moderate-to-severe UC by intention-to-treat analysis. Leukocytapheresis was more effective in maintaining clinical remission for asymptomatic UC patients than conventional therapy (OR, 8.14; 95% CI, 2.22-29.90). The incidence of mild-moderate adverse effects was much less frequent in the leukocytapheresis groups than conventional pharmacotherapy groups (OR, 0.16; 95% CI, 0.04-0.60). Few severe adverse events were observed. Current data indicate that leukocytapheresis supplementation may be more efficacious on improving response and remission rates and tapering corticosteroid dosage with excellent tolerability and safety than conventional pharmacotherapy in patients with UC. In addition, more high-quality randomized controlled trials are required to confirm the higher efficacy of leukocytapheresis in patients with UC.

Sexual Response Models: Toward a More Flexible Pattern of Women's Sexuality.

PubMed

Ferenidou, Fotini; Kirana, Paraskevi-Sofia; Fokas, Konstantinos; Hatzichristou, Dimitrios; Athanasiadis, Loukas

2016-09-01

Recent research suggests that none of the current theoretical models can sufficiently describe women's sexual response, because several factors and situations can influence this. To explore individual variations of a sexual model that describes women's sexual responses and to assess the association of endorsement of that model with sexual dysfunctions and reasons to engage in sexual activity. A sample of 157 randomly selected hospital employees completed self-administered questionnaires. Two models were developed: one merged the Master and Johnson model with the Kaplan model (linear) and the other was the Basson model (circular). Sexual function was evaluated by the Female Sexual Function Index and the Brief Sexual Symptom Checklist for Women. The Reasons for Having Sex Questionnaire was administered to investigate the reasons for which women have sex. Women reported that their current sexual experiences were at times consistent with the linear and circular models (66.9%), only the linear model (27%), only the circular model (5.4%), and neither model (0.7%). When the groups were reconfigured to the group that endorsed more than 5 of 10 sexual experiences, 64.3% of women endorsed the linear model, 20.4% chose the linear and circular models, 14.6% chose the circular model, and 0.7% selected neither. The Female Sexual Function Index, demographic factors, having sex for insecurity reasons, and sexual satisfaction correlated with the endorsement of a sexual response model. When these factors were entered in a stepwise logistic regression analysis, only the Female Sexual Function Index and having sex for insecurity reasons maintained a significant association with the sexual response model. The present study emphasizes the heterogeneity of female sexuality, with most of the sample reporting alternating between the linear and circular models. Sexual dysfunctions and having sex for insecurity reasons were associated with the Basson model. Copyright © 2016 International Society for Sexual Medicine. Published by Elsevier Inc. All rights reserved.

Design and experimentation of an empirical multistructure framework for accurate, sharp and reliable hydrological ensembles

NASA Astrophysics Data System (ADS)

Seiller, G.; Anctil, F.; Roy, R.

2017-09-01

This paper outlines the design and experimentation of an Empirical Multistructure Framework (EMF) for lumped conceptual hydrological modeling. This concept is inspired from modular frameworks, empirical model development, and multimodel applications, and encompasses the overproduce and select paradigm. The EMF concept aims to reduce subjectivity in conceptual hydrological modeling practice and includes model selection in the optimisation steps, reducing initial assumptions on the prior perception of the dominant rainfall-runoff transformation processes. EMF generates thousands of new modeling options from, for now, twelve parent models that share their functional components and parameters. Optimisation resorts to ensemble calibration, ranking and selection of individual child time series based on optimal bias and reliability trade-offs, as well as accuracy and sharpness improvement of the ensemble. Results on 37 snow-dominated Canadian catchments and 20 climatically-diversified American catchments reveal the excellent potential of the EMF in generating new individual model alternatives, with high respective performance values, that may be pooled efficiently into ensembles of seven to sixty constitutive members, with low bias and high accuracy, sharpness, and reliability. A group of 1446 new models is highlighted to offer good potential on other catchments or applications, based on their individual and collective interests. An analysis of the preferred functional components reveals the importance of the production and total flow elements. Overall, results from this research confirm the added value of ensemble and flexible approaches for hydrological applications, especially in uncertain contexts, and open up new modeling possibilities.

Linked population and economic models: some methodological issues in forecasting, analysis, and policy optimization.

PubMed

Madden, M; Batey Pwj

1983-05-01

Some problems associated with demographic-economic forecasting include finding models appropriate for a declining economy with unemployment, using a multiregional approach in an interregional model, finding a way to show differential consumption while endogenizing unemployment, and avoiding unemployment inconsistencies. The solution to these problems involves the construction of an activity-commodity framework, locating it within a group of forecasting models, and indicating possible ratios towards dynamization of the framework. The authors demonstrate the range of impact multipliers that can be derived from the framework and show how these multipliers relate to Leontief input-output multipliers. It is shown that desired population distribution may be obtained by selecting instruments from the economic sphere to produce, through the constraints vector of an activity-commodity framework, targets selected from demographic activities. The next step in this process, empirical exploitation, was carried out by the authors in the United Kingdom, linking an input-output model with a wide selection of demographic and demographic-economic variables. The generally tenuous control which government has over any variables in systems of this type, especially in market economies, makes application in the policy field of the optimization approach a partly conjectural exercise, although the analytic capacity of the approach can provide clear indications of policy directions.

Modelling individual difference in visual categorization.

PubMed

Shen, Jianhong; Palmeri, Thomas J

Recent years has seen growing interest in understanding, characterizing, and explaining individual differences in visual cognition. We focus here on individual differences in visual categorization. Categorization is the fundamental visual ability to group different objects together as the same kind of thing. Research on visual categorization and category learning has been significantly informed by computational modeling, so our review will focus both on how formal models of visual categorization have captured individual differences and how individual difference have informed the development of formal models. We first examine the potential sources of individual differences in leading models of visual categorization, providing a brief review of a range of different models. We then describe several examples of how computational models have captured individual differences in visual categorization. This review also provides a bit of an historical perspective, starting with models that predicted no individual differences, to those that captured group differences, to those that predict true individual differences, and to more recent hierarchical approaches that can simultaneously capture both group and individual differences in visual categorization. Via this selective review, we see how considerations of individual differences can lead to important theoretical insights into how people visually categorize objects in the world around them. We also consider new directions for work examining individual differences in visual categorization.

Modelling individual difference in visual categorization

PubMed Central

Shen, Jianhong; Palmeri, Thomas J.

2016-01-01

Recent years has seen growing interest in understanding, characterizing, and explaining individual differences in visual cognition. We focus here on individual differences in visual categorization. Categorization is the fundamental visual ability to group different objects together as the same kind of thing. Research on visual categorization and category learning has been significantly informed by computational modeling, so our review will focus both on how formal models of visual categorization have captured individual differences and how individual difference have informed the development of formal models. We first examine the potential sources of individual differences in leading models of visual categorization, providing a brief review of a range of different models. We then describe several examples of how computational models have captured individual differences in visual categorization. This review also provides a bit of an historical perspective, starting with models that predicted no individual differences, to those that captured group differences, to those that predict true individual differences, and to more recent hierarchical approaches that can simultaneously capture both group and individual differences in visual categorization. Via this selective review, we see how considerations of individual differences can lead to important theoretical insights into how people visually categorize objects in the world around them. We also consider new directions for work examining individual differences in visual categorization. PMID:28154496

[An Integrative Review of Home Care Service for Pregnant Women, Mothers, Infants, and Toddlers in Vulnerable Group].

PubMed

Kim, Dasom; Lee, Insook

2017-10-01

This study was intended to integrate the evidence of home care service intervention for mothers and children in vulnerable groups through an integrative literature review. We searched the MEDLINE (PubMED), EMBASE, Cochrane Central Register of Controlled Trials, CINAHL, DBpia databases. The quality of the articles was assessed by one doctoral researcher and verified by one professor of community health nursing who had participated in the systematic review of literature. A framework was developed to identify the intervention patterns in the selected papers and categorize various elements. The extracted intervention elements were grouped into potential themes, which were verified by assessors on whether they clearly reflected the interventions in the papers. Among 878 searched papers, we selected 16 papers after excluding literature that does not satisfy the selection criteria and quality evaluation. The intervention elements of 16 selected papers were categorized into six themes. The extracted intervention elements were divided into the themes of Patient-specific/Situation-specific care planning and intervention, Emphasis on self care competency, Intense home visit by developmental milestone, Reinforcing and modeling mother-child attachment, Communication and interaction across the intervention, Linkage with community resource and multidisciplinary approach. As a result of the analysis of proper interventions of home care services for mothers and children in vulnerable groups, it was found that it is necessary to consider indispensable intervention elements that can standardize the quality of home care services, and conduct studies on developing intervention programs based on the elements. © 2017 Korean Society of Nursing Science

Cadmium(II) and lead(II) adsorption onto hetero-atom functional mesoporous silica and activated carbon

NASA Astrophysics Data System (ADS)

Machida, Motoi; Fotoohi, Babak; Amamo, Yoshimasa; Mercier, Louis

2012-07-01

Adsorption of cadmium(II) and lead(II) on amino-, mercapto-functionalized mesoporous silica (HMS) and carboxylic-functionalized activated carbon (AC) were examined. The resultant isotherms fitted the Langmuir model and amino-functionalized HMS exhibited the highest adsorption capacity for both cadmium(II) and lead(II). Adsorption affinities for cadmium(II) were always greater than those for lead(II) in all three adsorbent types, while the difference between the two values was the largest for mercapto-functionalized HMS indicating a selective adsorption of cadmium(II). Influence of equilibrium solution pH on adsorption of cadmium(II), lead(II) and their binary mixtures was also studied. Carboxylic-functionalized AC adsorbed cadmium(II) and lead(II) in a wide pH range than conditions for the mercapto-functionalized HMS. It was concluded that each functional group had its own characteristics and advantages for adsorption of heavy metal ions; amino-groups showed high adsorption capacity, while mercapto-groups had good selectivity toward cadmium(II) adsorption and a wide solution pH in adsorption by carboxylic-groups were established in this study.

Structure based drug design: development of potent and selective factor IXa (FIXa) inhibitors.

PubMed

Wang, Shouming; Beck, Richard; Burd, Andrew; Blench, Toby; Marlin, Frederic; Ayele, Tenagne; Buxton, Stuart; Dagostin, Claudio; Malic, Maja; Joshi, Rina; Barry, John; Sajad, Mohammed; Cheung, Chiming; Shaikh, Shaheda; Chahwala, Suresh; Chander, Chaman; Baumgartner, Christine; Holthoff, Hans-Peter; Murray, Elizabeth; Blackney, Michael; Giddings, Amanda

2010-02-25

On the basis of our understanding on the binding interactions of the benzothiophene template within the FIXa active site by X-ray crystallography and molecular modeling studies, we developed our SAR strategy by targeting the 4-position of the template to access the S1 beta and S2-S4 sites. A number of highly selective and potent factor Xa (FXa) and FIXa inhibitors were identified by simple switch of functional groups with conformational changes toward the S2-S4 sites.

Supercritical fluid chromatography of metoprolol and analogues on aminopropyl and ethylpyridine silica without any additives.

PubMed

Lundgren, Johanna; Salomonsson, John; Gyllenhaal, Olle; Johansson, Erik

2007-06-22

Metoprolol and a number of related amino alcohols and similar analytes have been chromatographed on aminopropyl (APS) and ethylpyridine (EPS) silica columns. The mobile phase was carbon dioxide with methanol as modifier and no amine additive was present. Optimal isocratic conditions for the selectivity were evaluated based on experiments using design of experiments. A central composite circumscribed model for each column was used. Factors were column temperature, back-pressure and % (v/v) of modifier. The responses were retention and selectivity versus metoprolol. The % of modifier mainly controlled the retention on both columns but pressure and temperature could also be important for optimizing the selectivity between the amino alcohols. The compounds could be divided into four and five groups on both columns, with respect to the selectivity. Furthermore, on the aminopropyl silica the analytes were more spread out whereas on the ethylpyridine silica, due to its aromaticity, retention and selectivity were closer. For optimal conditions the column temperature and back-pressure should be high and the modifier concentration low. A comparison of the selectivity using optimized conditions show a few switches of retention order between the two columns. On aminopropyl silica an aldehyde failed to be eluted owing to Schiff-base formation. Peak symmetry and column efficiency were briefly studied for some structurally close analogues. This revealed some activity from the columns that affected analytes that had less protected amino groups, a methyl group instead of isopropyl. The tailing was more marked with the ethylpyridine column even with the more bulky alkyl substituents. Plate number N was a better measure than the asymmetry factor since some analyte peaks broadened without serious deterioration of symmetry compared to homologues.

Cultural group selection follows Darwin's classic syllogism for the operation of selection.

PubMed

Richerson, Peter; Baldini, Ryan; Bell, Adrian V; Demps, Kathryn; Frost, Karl; Hillis, Vicken; Mathew, Sarah; Newton, Emily K; Naar, Nicole; Newson, Lesley; Ross, Cody; Smaldino, Paul E; Waring, Timothy M; Zefferman, Matthew

2016-01-01

The main objective of our target article was to sketch the empirical case for the importance of selection at the level of groups on cultural variation. Such variation is massive in humans, but modest or absent in other species. Group selection processes acting on this variation is a framework for developing explanations of the unusual level of cooperation between non-relatives found in our species. Our case for cultural group selection (CGS) followed Darwin's classic syllogism regarding natural selection: If variation exists at the level of groups, if this variation is heritable, and if it plays a role in the success or failure of competing groups, then selection will operate at the level of groups. We outlined the relevant domains where such evidence can be sought and characterized the main conclusions of work in those domains. Most commentators agree that CGS plays some role in human evolution, although some were considerably more skeptical. Some contributed additional empirical cases. Some raised issues of the scope of CGS explanations versus competing ones.

Games of multicellularity.

PubMed

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

2016-08-21

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

The role of Homer 1a in increasing locomotor activity and non-selective attention, and impairing learning and memory abilities.

PubMed

Yang, Lei; Hong, Qin; Zhang, Min; Liu, Xiao; Pan, Xiao-Qin; Guo, Mei; Fei, Li; Guo, Xi-Rong; Tong, Mei-Ling; Chi, Xia

2013-06-17

The current study aimed to investigate the possible role of Homer 1a in the etiology and pathogenesis of attention deficit hyperactivity disorder (ADHD). We divided 32 rats into four groups. The rats in the RNAi-MPH group were given the lentiviral vector containing Homer 1a-specific miRNA (Homer 1a-RNAi-LV) by intracerebroventricular injection, and 7 days later they were given three daily doses of methylphenidate (MPH) by intragastric gavage. The RNAi-SAL group was given Homer 1a-RNAi-LV and saline later. The NC-MPH group was given the negative control lentiviral vector (NC-LV) and MPH later. The NC-SAL group was given NC-LV and saline later. Rats that were given Homer 1a RNAi exhibited increased locomotor activity and non-selective attention, and impaired learning and memory abilities, which is in line with the behavioral findings of animal models of ADHD. However, MPH ameliorated these abnormal behaviors. All findings indicated that Homer 1a may play an important role in the etiology and pathogenesis of ADHD. Copyright © 2013 Elsevier B.V. All rights reserved.

Modeling the origins of mammalian sociality: moderate evidence for matrilineal signatures in mouse lemur vocalizations.

PubMed

Kessler, Sharon E; Radespiel, Ute; Hasiniaina, Alida I F; Leliveld, Lisette M C; Nash, Leanne T; Zimmermann, Elke

2014-02-20

Maternal kin selection is a driving force in the evolution of mammalian social complexity and it requires that kin are distinctive from nonkin. The transition from the ancestral state of asociality to the derived state of complex social groups is thought to have occurred via solitary foraging, in which individuals forage alone, but, unlike the asocial ancestors, maintain dispersed social networks via scent-marks and vocalizations. We hypothesize that matrilineal signatures in vocalizations were an important part of these networks. We used the solitary foraging gray mouse lemur (Microcebus murinus) as a model for ancestral solitary foragers and tested for matrilineal signatures in their calls, thus investigating whether such signatures are already present in solitary foragers and could have facilitated the kin selection thought to have driven the evolution of increased social complexity in mammals. Because agonism can be very costly, selection for matrilineal signatures in agonistic calls should help reduce agonism between unfamiliar matrilineal kin. We conducted this study on a well-studied population of wild mouse lemurs at Ankarafantsika National Park, Madagascar. We determined pairwise relatedness using seven microsatellite loci, matrilineal relatedness by sequencing the mitrochondrial D-loop, and sleeping group associations using radio-telemetry. We recorded agonistic calls during controlled social encounters and conducted a multi-parametric acoustic analysis to determine the spectral and temporal structure of the agonistic calls. We measured 10 calls for each of 16 females from six different matrilineal kin groups. Calls were assigned to their matriline at a rate significantly higher than chance (pDFA: correct = 47.1%, chance = 26.7%, p = 0.03). There was a statistical trend for a negative correlation between acoustic distance and relatedness (Mantel Test: g = -1.61, Z = 4.61, r = -0.13, p = 0.058). Mouse lemur agonistic calls are moderately distinctive by matriline. Because sleeping groups consisted of close maternal kin, both genetics and social learning may have generated these acoustic signatures. As mouse lemurs are models for solitary foragers, we recommend further studies testing whether the lemurs use these calls to recognize kin. This would enable further modeling of how kin recognition in ancestral species could have shaped the evolution of complex sociality.

The efficiency of a group-specific mandated benefit revisited: the effect of infertility mandates.

PubMed

Lahey, Joanna N

2012-01-01

This paper examines the labor market effects of state health insurance mandates that increase the cost of employing a demographically identifiable group. State mandates requiring that health insurance plans cover infertility treatment raise the relative cost of insuring older women of child-bearing age. Empirically, wages in this group are unaffected, but their total labor input decreases. Workers do not value infertility mandates at cost, and so will not take wage cuts in exchange, leading employers to decrease their demand for this affected and identifiable group. Differences in the empirical effects of mandates found in the literature are explained by a model including variations in the elasticity of demand, moral hazard, ability to identify a group, and adverse selection.

Promotion of cooperation by selective group extinction

NASA Astrophysics Data System (ADS)

Böttcher, Marvin A.; Nagler, Jan

2016-06-01

Multilevel selection is an important organizing principle that crucially underlies evolutionary processes from the emergence of cells to eusociality and the economics of nations. Previous studies on multilevel selection assumed that the effective higher-level selection emerges from lower-level reproduction. This leads to selection among groups, although only individuals reproduce. We introduce selective group extinction, where groups die with a probability inversely proportional to their group fitness. When accounting for this the critical benefit-to-cost ratio is substantially lowered. Because in game theory and evolutionary dynamics the degree of cooperation crucially depends on this ratio above which cooperation emerges, previous studies may have substantially underestimated the establishment and maintenance of cooperation.

An affine projection algorithm using grouping selection of input vectors

NASA Astrophysics Data System (ADS)

Shin, JaeWook; Kong, NamWoong; Park, PooGyeon

2011-10-01

This paper present an affine projection algorithm (APA) using grouping selection of input vectors. To improve the performance of conventional APA, the proposed algorithm adjusts the number of the input vectors using two procedures: grouping procedure and selection procedure. In grouping procedure, the some input vectors that have overlapping information for update is grouped using normalized inner product. Then, few input vectors that have enough information for for coefficient update is selected using steady-state mean square error (MSE) in selection procedure. Finally, the filter coefficients update using selected input vectors. The experimental results show that the proposed algorithm has small steady-state estimation errors comparing with the existing algorithms.

Three-dimensional computer-assisted study model analysis of long-term oral-appliance wear. Part 1: Methodology.

PubMed

Chen, Hui; Lowe, Alan A; de Almeida, Fernanda Riberiro; Wong, Mary; Fleetham, John A; Wang, Bangkang

2008-09-01

The aim of this study was to test a 3-dimensional (3D) computer-assisted dental model analysis system that uses selected landmarks to describe tooth movement during treatment with an oral appliance. Dental casts of 70 patients diagnosed with obstructive sleep apnea and treated with oral appliances for a mean time of 7 years 4 months were evaluated with a 3D digitizer (MicroScribe-3DX, Immersion, San Jose, Calif) compatible with the Rhinoceros modeling program (version 3.0 SR3c, Robert McNeel & Associates, Seattle, Wash). A total of 86 landmarks on each model were digitized, and 156 variables were calculated as either the linear distance between points or the distance from points to reference planes. Four study models for each patient (maxillary baseline, mandibular baseline, maxillary follow-up, and mandibular follow-up) were superimposed on 2 sets of reference points: 3 points on the palatal rugae for maxillary model superimposition, and 3 occlusal contact points for the same set of maxillary and mandibular model superimpositions. The patients were divided into 3 evaluation groups by 5 orthodontists based on the changes between baseline and follow-up study models. Digital dental measurements could be analyzed, including arch width, arch length, curve of Spee, overbite, overjet, and the anteroposterior relationship between the maxillary and mandibular arches. A method error within 0.23 mm in 14 selected variables was found for the 3D system. The statistical differences in the 3 evaluation groups verified the division criteria determined by the orthodontists. The system provides a method to record 3D measurements of study models that permits computer visualization of tooth position and movement from various perspectives.

A Comparative Model of Field Investigations: Aligning School Science Inquiry with the Practices of Contemporary Science

ERIC Educational Resources Information Center

Windschitl, Mark; Dvornich, Karen; Ryken, Amy E.; Tudor, Margaret; Koehler, Gary

2007-01-01

Field investigations are not characterized by randomized and manipulated control group experiments; however, most school science and high-stakes tests recognize only this paradigm of investigation. Scientists in astronomy, genetics, field biology, oceanography, geology, and meteorology routinely select naturally occurring events and conditions and…

Validation Study of Waray Text Readability Instrument

ERIC Educational Resources Information Center

Oyzon, Voltaire Q.; Corrales, Juven B.; Estardo, Wilfredo M., Jr.

2015-01-01

In 2012 the Leyte Normal University developed a computer software--modelled after the Spache Readability Formula (1953) made for English--made to help rank texts that can is used by teachers or research groups on selecting appropriate reading materials to support the DepEd's MTB-MLE program in Region VIII, in the Philippines. However,…

Longitudinal IQ Outcomes of the Mother-Child Home Program, 1967-1973.

ERIC Educational Resources Information Center

Madden, John; And Others

Low-income families participated in several variations of a home-based intervention program which focused on modeling verbal interaction between mother and child around selected toys and books. Long-term results from a quasi-experimental design including 83 variously treated and 55 untreated students indicated that the amount of between group IQ…

Peace Crane Project: An Interdisciplinary Approach.

ERIC Educational Resources Information Center

LeBert, Linda L.; Calais, Jerry; Cuevas, Phyllis; Fruge', Hugh; Gardiner, Judy Carter; Larmon, Marilyn; Rees, Jocelyn

To model collaboration and to "practice what we teach," a group of faculty members at McNeese State University in Louisiana developed a college-wide theme based on the book, "Sadako and the Thousand Paper Cranes." This book was selected because of the importance of seeking and achieving peace in a world that is struggling and,…

Evaluating Expectations about Negative Emotional States of Aggressive Boys Using Bayesian Model Selection

ERIC Educational Resources Information Center

van de Schoot, Rens; Hoijtink, Herbert; Mulder, Joris; Van Aken, Marcel A. G.; Orobio de Castro, Bram; Meeus, Wim; Romeijn, Jan-Willem

2011-01-01

Researchers often have expectations about the research outcomes in regard to inequality constraints between, e.g., group means. Consider the example of researchers who investigated the effects of inducing a negative emotional state in aggressive boys. It was expected that highly aggressive boys would, on average, score higher on aggressive…

John Langstaff: Community Musician and Reveler

ERIC Educational Resources Information Center

Bartolome, Sarah J.; Campbell, Patricia Shehan

2009-01-01

John Langstaff fits within a select group of pathfinders in American music education who have shaped the profession's service to schools and society with special attention to the traditional musical expressions of American folk. His life and works are worthy of study for the contributions he made as a singer who modelled the nuances of traditional…