A Comparison of Three Polytomous Item Response Theory Models in the Context of Testlet Scoring.
ERIC Educational Resources Information Center
Cook, Karon F.; Dodd, Barbara G.; Fitzpatrick, Steven J.
1999-01-01
The partial-credit model, the generalized partial-credit model, and the graded-response model were compared in the context of testlet scoring using Scholastic Assessment Tests results (n=2,548) and a simulated data set. Results favor the partial-credit model in this context; considerations for model selection in other contexts are discussed. (SLD)
A Context Maintenance and Retrieval Model of Organizational Processes in Free Recall
ERIC Educational Resources Information Center
Polyn, Sean M.; Norman, Kenneth A.; Kahana, Michael J.
2009-01-01
The authors present the context maintenance and retrieval (CMR) model of memory search, a generalized version of the temporal context model of M. W. Howard and M. J. Kahana (2002a), which proposes that memory search is driven by an internally maintained context representation composed of stimulus-related and source-related features. In the CMR…
González, Felisa; Quinn, Jennifer J; Fanselow, Michael S
2003-01-01
Rats were conditioned across 2 consecutive days where a single unsignaled footshock was presented in the presence of specific contextual cues. Rats were tested with contexts that had additional stimulus components either added or subtracted. Using freezing as a measure of conditioning, removal but not addition of a cue from the training context produced significant generalization decrement. The results are discussed in relation to the R. A. Rescorla and A. R. Wagner (1972), J. M. Pearce (1994), and A. R. Wagner and S. E. Brandon (2001) accounts of generalization. Although the present data are most consistent with elemental models such as Rescorla and Wagner, a slight modification of the Wagner-Brandon replaced-elements model that can account for differences in the pattern of generalization obtained with contexts and discrete conditional stimuli is proposed.
Towards Increased Relevance: Context-Adapted Models of the Learning Organization
ERIC Educational Resources Information Center
Örtenblad, Anders
2015-01-01
Purpose: The purposes of this paper are to take a closer look at the relevance of the idea of the learning organization for organizations in different generalized organizational contexts; to open up for the existence of multiple, context-adapted models of the learning organization; and to suggest a number of such models.…
NASA Technical Reports Server (NTRS)
Phillips, K.
1976-01-01
A mathematical model for job scheduling in a specified context is presented. The model uses both linear programming and combinatorial methods. While designed with a view toward optimization of scheduling of facility and plant operations at the Deep Space Communications Complex, the context is sufficiently general to be widely applicable. The general scheduling problem including options for scheduling objectives is discussed and fundamental parameters identified. Mathematical algorithms for partitioning problems germane to scheduling are presented.
Compositional clustering in task structure learning
Frank, Michael J.
2018-01-01
Humans are remarkably adept at generalizing knowledge between experiences in a way that can be difficult for computers. Often, this entails generalizing constituent pieces of experiences that do not fully overlap, but nonetheless share useful similarities with, previously acquired knowledge. However, it is often unclear how knowledge gained in one context should generalize to another. Previous computational models and data suggest that rather than learning about each individual context, humans build latent abstract structures and learn to link these structures to arbitrary contexts, facilitating generalization. In these models, task structures that are more popular across contexts are more likely to be revisited in new contexts. However, these models can only re-use policies as a whole and are unable to transfer knowledge about the transition structure of the environment even if only the goal has changed (or vice-versa). This contrasts with ecological settings, where some aspects of task structure, such as the transition function, will be shared between context separately from other aspects, such as the reward function. Here, we develop a novel non-parametric Bayesian agent that forms independent latent clusters for transition and reward functions, affording separable transfer of their constituent parts across contexts. We show that the relative performance of this agent compared to an agent that jointly clusters reward and transition functions depends environmental task statistics: the mutual information between transition and reward functions and the stochasticity of the observations. We formalize our analysis through an information theoretic account of the priors, and propose a meta learning agent that dynamically arbitrates between strategies across task domains to optimize a statistical tradeoff. PMID:29672581
Deep Belief Networks Learn Context Dependent Behavior
Raudies, Florian; Zilli, Eric A.; Hasselmo, Michael E.
2014-01-01
With the goal of understanding behavioral mechanisms of generalization, we analyzed the ability of neural networks to generalize across context. We modeled a behavioral task where the correct responses to a set of specific sensory stimuli varied systematically across different contexts. The correct response depended on the stimulus (A,B,C,D) and context quadrant (1,2,3,4). The possible 16 stimulus-context combinations were associated with one of two responses (X,Y), one of which was correct for half of the combinations. The correct responses varied symmetrically across contexts. This allowed responses to previously unseen stimuli (probe stimuli) to be generalized from stimuli that had been presented previously. By testing the simulation on two or more stimuli that the network had never seen in a particular context, we could test whether the correct response on the novel stimuli could be generated based on knowledge of the correct responses in other contexts. We tested this generalization capability with a Deep Belief Network (DBN), Multi-Layer Perceptron (MLP) network, and the combination of a DBN with a linear perceptron (LP). Overall, the combination of the DBN and LP had the highest success rate for generalization. PMID:24671178
The Effectiveness of CBL Model to Improve Analytical Thinking Skills the Students of Sport Science
ERIC Educational Resources Information Center
Sudibyo, Elok; Jatmiko, Budi; Widodo, Wahono
2016-01-01
Sport science undergraduate education, one of which purposes is to produce an analyst in sport. However, generally analytical thinking skills of sport science's students is still relatively very low in the context of sport. This study aimed to describe the effectiveness of Physics Learning Model in Sport Context, Context Based Learning (CBL)…
Context management platform for tourism applications.
Buján, David; Martín, David; Torices, Ortzi; López-de-Ipiña, Diego; Lamsfus, Carlos; Abaitua, Joseba; Alzua-Sorzabal, Aurkene
2013-06-24
The notion of context has been widely studied and there are several authors that have proposed different definitions of context. However, context has not been widely studied in the framework of human mobility and the notion of context has been imported directly from other computing fields without specifically addressing the tourism domain requirements. In order to store and manage context information a context data model and a context management platform are needed. Ontologies have been widely used in context modelling, but many of them are designed to be applied in general ubiquitous computing environments, do not contain specific concepts related to the tourism domain or some approaches do not contain enough concepts to represent context information related to the visitor on the move. That is why we propose a new approach to provide a better solution to model context data in tourism environments, adding more value to our solution reusing data about tourist resources from an Open Data repository and publishing it as Linked Data. We also propose the architecture for a context information management platform based on this context data model.
Context Management Platform for Tourism Applications
Buján, David; Martín, David; Torices, Ortzi; López-de-Ipiña, Diego; Lamsfus, Carlos; Abaitua, Joseba; Alzua-Sorzabal, Aurkene
2013-01-01
The notion of context has been widely studied and there are several authors that have proposed different definitions of context. However, context has not been widely studied in the framework of human mobility and the notion of context has been imported directly from other computing fields without specifically addressing the tourism domain requirements. In order to store and manage context information a context data model and a context management platform are needed. Ontologies have been widely used in context modelling, but many of them are designed to be applied in general ubiquitous computing environments, do not contain specific concepts related to the tourism domain or some approaches do not contain enough concepts to represent context information related to the visitor on the move. That is why we propose a new approach to provide a better solution to model context data in tourism environments, adding more value to our solution reusing data about tourist resources from an Open Data repository and publishing it as Linked Data. We also propose the architecture for a context information management platform based on this context data model. PMID:23797739
On the effects of alternative optima in context-specific metabolic model predictions
Nikoloski, Zoran
2017-01-01
The integration of experimental data into genome-scale metabolic models can greatly improve flux predictions. This is achieved by restricting predictions to a more realistic context-specific domain, like a particular cell or tissue type. Several computational approaches to integrate data have been proposed—generally obtaining context-specific (sub)models or flux distributions. However, these approaches may lead to a multitude of equally valid but potentially different models or flux distributions, due to possible alternative optima in the underlying optimization problems. Although this issue introduces ambiguity in context-specific predictions, it has not been generally recognized, especially in the case of model reconstructions. In this study, we analyze the impact of alternative optima in four state-of-the-art context-specific data integration approaches, providing both flux distributions and/or metabolic models. To this end, we present three computational methods and apply them to two particular case studies: leaf-specific predictions from the integration of gene expression data in a metabolic model of Arabidopsis thaliana, and liver-specific reconstructions derived from a human model with various experimental data sources. The application of these methods allows us to obtain the following results: (i) we sample the space of alternative flux distributions in the leaf- and the liver-specific case and quantify the ambiguity of the predictions. In addition, we show how the inclusion of ℓ1-regularization during data integration reduces the ambiguity in both cases. (ii) We generate sets of alternative leaf- and liver-specific models that are optimal to each one of the evaluated model reconstruction approaches. We demonstrate that alternative models of the same context contain a marked fraction of disparate reactions. Further, we show that a careful balance between model sparsity and metabolic functionality helps in reducing the discrepancies between alternative models. Finally, our findings indicate that alternative optima must be taken into account for rendering the context-specific metabolic model predictions less ambiguous. PMID:28557990
On the effects of alternative optima in context-specific metabolic model predictions.
Robaina-Estévez, Semidán; Nikoloski, Zoran
2017-05-01
The integration of experimental data into genome-scale metabolic models can greatly improve flux predictions. This is achieved by restricting predictions to a more realistic context-specific domain, like a particular cell or tissue type. Several computational approaches to integrate data have been proposed-generally obtaining context-specific (sub)models or flux distributions. However, these approaches may lead to a multitude of equally valid but potentially different models or flux distributions, due to possible alternative optima in the underlying optimization problems. Although this issue introduces ambiguity in context-specific predictions, it has not been generally recognized, especially in the case of model reconstructions. In this study, we analyze the impact of alternative optima in four state-of-the-art context-specific data integration approaches, providing both flux distributions and/or metabolic models. To this end, we present three computational methods and apply them to two particular case studies: leaf-specific predictions from the integration of gene expression data in a metabolic model of Arabidopsis thaliana, and liver-specific reconstructions derived from a human model with various experimental data sources. The application of these methods allows us to obtain the following results: (i) we sample the space of alternative flux distributions in the leaf- and the liver-specific case and quantify the ambiguity of the predictions. In addition, we show how the inclusion of ℓ1-regularization during data integration reduces the ambiguity in both cases. (ii) We generate sets of alternative leaf- and liver-specific models that are optimal to each one of the evaluated model reconstruction approaches. We demonstrate that alternative models of the same context contain a marked fraction of disparate reactions. Further, we show that a careful balance between model sparsity and metabolic functionality helps in reducing the discrepancies between alternative models. Finally, our findings indicate that alternative optima must be taken into account for rendering the context-specific metabolic model predictions less ambiguous.
Willoughby, Jessica Fitts; Myrick, Jessica Gall
2016-06-01
Research indicates that when people seek health information, they typically look for information about a specific symptom, preventive measure, disease, or treatment. It is unclear, however, whether general or disease-specific theoretical models best predict how people search for health information. We surveyed undergraduates (N = 963) at a large public southeastern university to examine health information seeking in two incongruent health contexts (sexual health and cancer) to test whether a general model would hold for specific topics that differed in their immediate personal relevance for the target population. We found that the planned risk information seeking model was statistically a good fit for the data. Yet multiple predicted paths were not supported in either data set. Certain variables, such as attitudes, norms, and affect, appear to be strong predictors of intentions to seek information across health contexts. Implications for theory building, research methodology, and applied work in health-related risk information seeking are discussed.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Loubenets, Elena R.
We prove the existence for each Hilbert space of the two new quasi hidden variable (qHV) models, statistically noncontextual and context-invariant, reproducing all the von Neumann joint probabilities via non-negative values of real-valued measures and all the quantum product expectations—via the qHV (classical-like) average of the product of the corresponding random variables. In a context-invariant model, a quantum observable X can be represented by a variety of random variables satisfying the functional condition required in quantum foundations but each of these random variables equivalently models X under all joint von Neumann measurements, regardless of their contexts. The proved existence ofmore » this model negates the general opinion that, in terms of random variables, the Hilbert space description of all the joint von Neumann measurements for dimH≥3 can be reproduced only contextually. The existence of a statistically noncontextual qHV model, in particular, implies that every N-partite quantum state admits a local quasi hidden variable model introduced in Loubenets [J. Math. Phys. 53, 022201 (2012)]. The new results of the present paper point also to the generality of the quasi-classical probability model proposed in Loubenets [J. Phys. A: Math. Theor. 45, 185306 (2012)].« less
NASA Astrophysics Data System (ADS)
Jara, A. J.; Bocchi, Y.; Fernandez, D.; Molina, G.; Gomez, A.
2017-09-01
Smart Cities requires the support of context-aware and enriched semantic descriptions to support a scalable and cross-domain development of smart applications. For example, nowadays general purpose sensors such as crowd monitoring (counting people in an area), environmental information (pollution, air quality, temperature, humidity, noise) etc. can be used in multiple solutions with different objectives. For that reason, a data model that offers advanced capabilities for the description of context is required. This paper presents an overview of the available technologies for this purpose and how it is being addressed by the Open and Agile Smart Cities principles and FIWARE platform through the data models defined by the ETSI ISG Context Information Management (ETSI CIM).
Soft context clustering for F0 modeling in HMM-based speech synthesis
NASA Astrophysics Data System (ADS)
Khorram, Soheil; Sameti, Hossein; King, Simon
2015-12-01
This paper proposes the use of a new binary decision tree, which we call a soft decision tree, to improve generalization performance compared to the conventional `hard' decision tree method that is used to cluster context-dependent model parameters in statistical parametric speech synthesis. We apply the method to improve the modeling of fundamental frequency, which is an important factor in synthesizing natural-sounding high-quality speech. Conventionally, hard decision tree-clustered hidden Markov models (HMMs) are used, in which each model parameter is assigned to a single leaf node. However, this `divide-and-conquer' approach leads to data sparsity, with the consequence that it suffers from poor generalization, meaning that it is unable to accurately predict parameters for models of unseen contexts: the hard decision tree is a weak function approximator. To alleviate this, we propose the soft decision tree, which is a binary decision tree with soft decisions at the internal nodes. In this soft clustering method, internal nodes select both their children with certain membership degrees; therefore, each node can be viewed as a fuzzy set with a context-dependent membership function. The soft decision tree improves model generalization and provides a superior function approximator because it is able to assign each context to several overlapped leaves. In order to use such a soft decision tree to predict the parameters of the HMM output probability distribution, we derive the smoothest (maximum entropy) distribution which captures all partial first-order moments and a global second-order moment of the training samples. Employing such a soft decision tree architecture with maximum entropy distributions, a novel speech synthesis system is trained using maximum likelihood (ML) parameter re-estimation and synthesis is achieved via maximum output probability parameter generation. In addition, a soft decision tree construction algorithm optimizing a log-likelihood measure is developed. Both subjective and objective evaluations were conducted and indicate a considerable improvement over the conventional method.
Does the context of reinforcement affect resistance to change?
Nevin, J A; Grace, R C
1999-04-01
Eight pigeons were trained on multiple schedules of reinforcement where pairs of components alternated in blocks on different keys to define 2 local contexts. On 1 key, components arranged 160 and 40 reinforcers/hr; on the other, components arranged 40 and 10 reinforcers/hr. Response rates in the 40/hr component were higher in the latter pair. Within pairs, resistance to prefeeding and resistance to extinction were generally greater in the richer component. The two 40/hr components did not differ in resistance to prefeeding, but the 40/hr component that alternated with 10/hr was more resistant to extinction. This discrepancy was interpreted by an algebraic model relating response strength to component reinforcer rate, including generalization decrement. According to this model, strength is independent of context, consistent with research on schedule preference.
ERIC Educational Resources Information Center
Kavgaoglu, Derya; Alci, Bülent
2016-01-01
The goal of this research which was carried out in reputable dedicated call centres within the Turkish telecommunication sector aims is to evaluate competence-based curriculums designed by means of internal funding through Stufflebeam's context, input, process, product (CIPP) model. In the research, a general scanning pattern in the scope of…
Ingram, James N; Howard, Ian S; Flanagan, J Randall; Wolpert, Daniel M
2011-09-01
Motor learning has been extensively studied using dynamic (force-field) perturbations. These induce movement errors that result in adaptive changes to the motor commands. Several state-space models have been developed to explain how trial-by-trial errors drive the progressive adaptation observed in such studies. These models have been applied to adaptation involving novel dynamics, which typically occurs over tens to hundreds of trials, and which appears to be mediated by a dual-rate adaptation process. In contrast, when manipulating objects with familiar dynamics, subjects adapt rapidly within a few trials. Here, we apply state-space models to familiar dynamics, asking whether adaptation is mediated by a single-rate or dual-rate process. Previously, we reported a task in which subjects rotate an object with known dynamics. By presenting the object at different visual orientations, adaptation was shown to be context-specific, with limited generalization to novel orientations. Here we show that a multiple-context state-space model, with a generalization function tuned to visual object orientation, can reproduce the time-course of adaptation and de-adaptation as well as the observed context-dependent behavior. In contrast to the dual-rate process associated with novel dynamics, we show that a single-rate process mediates adaptation to familiar object dynamics. The model predicts that during exposure to the object across multiple orientations, there will be a degree of independence for adaptation and de-adaptation within each context, and that the states associated with all contexts will slowly de-adapt during exposure in one particular context. We confirm these predictions in two new experiments. Results of the current study thus highlight similarities and differences in the processes engaged during exposure to novel versus familiar dynamics. In both cases, adaptation is mediated by multiple context-specific representations. In the case of familiar object dynamics, however, the representations can be engaged based on visual context, and are updated by a single-rate process.
Topological and Orthomodular Modeling of Context in Behavioral Science
NASA Astrophysics Data System (ADS)
Narens, Louis
2017-02-01
Two non-boolean methods are discussed for modeling context in behavioral data and theory. The first is based on intuitionistic logic, which is similar to classical logic except that not every event has a complement. Its probability theory is also similar to classical probability theory except that the definition of probability function needs to be generalized to unions of events instead of applying only to unions of disjoint events. The generalization is needed, because intuitionistic event spaces may not contain enough disjoint events for the classical definition to be effective. The second method develops a version of quantum logic for its underlying probability theory. It differs from Hilbert space logic used in quantum mechanics as a foundation for quantum probability theory in variety of ways. John von Neumann and others have commented about the lack of a relative frequency approach and a rational foundation for this probability theory. This article argues that its version of quantum probability theory does not have such issues. The method based on intuitionistic logic is useful for modeling cognitive interpretations that vary with context, for example, the mood of the decision maker, the context produced by the influence of other items in a choice experiment, etc. The method based on this article's quantum logic is useful for modeling probabilities across contexts, for example, how probabilities of events from different experiments are related.
A Measurable Model of the Creative Process in the Context of a Learning Process
ERIC Educational Resources Information Center
Ma, Min; Van Oystaeyen, Fred
2016-01-01
The authors' aim was to arrive at a measurable model of the creative process by putting creativity in the context of a learning process. The authors aimed to provide a rather detailed description of how creative thinking fits in a general description of the learning process without trying to go into an analysis of a biological description of the…
Dohnke, Birte; Steinhilber, Amina; Fuchs, Tanja
2015-01-01
To investigate the prototype-willingness model (PWM) for eating behaviour in general and in the peer context in order to gain further evidence on the PWM and social-reactive processes in adolescents' eating behaviour. A longitudinal study was conducted. PWM variables for unhealthy and healthy eating were assessed at baseline in 356 adolescents (mean age 12.61 years). Eating behaviour was measured four weeks after baseline by two indicators: general eating pattern index (self-report) and consumption of unhealthy and healthy snacks in the peer context (behavioural observation). For both, structural equation models were conducted introducing PWM variables for either unhealthy or healthy eating. The PWM was mainly confirmed for the eating pattern index; intention, willingness and prototype perception had direct effects. Differences between unhealthy and healthy eating were found. Moreover, the PWM contributed to the prediction of healthy, but not unhealthy, snack consumption over and above current hunger; willingness had a direct effect. The PWM can be applied to predict and understand adolescents' eating behaviour. Social-reactive processes, namely willingness and prototype perception, are behavioural determinants that should be considered in theory and as novel targets in health promotion interventions.
Evolution Equations of C(3)I: Cannonical Forms and Their Properties.
1983-10-01
paper are all generalized Lotka - Volterra equations for two-species systems. In spite of these restric- tions, their interpretation in the C31 context...most general properties of that model exposed the fact that, unlike the earlier counter-C3 model, a four-species model is environmentally unstable...Coupled two-species evolution equations are of the general form a -F (X, Y. U) + V Y - -F (X, Y, + V(y y Fx and Fy are attrition functions. They depend
Zamboni, B D; Crawford, I; Williams, P G
2000-12-01
The current study explored the relationship between communication and assertiveness in general and sexual contexts and examined each construct's differential ability to predict reported condom use among college students. The results suggest that the constructs are positively related to each other, but general communication does not predict sexual assertiveness. Although sexual assertiveness is a better predictor of condom use than general assertiveness, general communication, and sexual communication, it needs to be considered within the context of other variables (e.g., normative beliefs regarding condom use). HIV prevention programs and models of health behavior should incorporate individual characteristics such as sexual assertiveness. The results of this study suggest that sexual assertiveness, social norm perceptions of condom use, self-efficacy for HIV prevention, and condom attitudes are among the critical variables that should be examined in an integrated model of sexual health behavior.
Incorporating spatial context into statistical classification of multidimensional image data
NASA Technical Reports Server (NTRS)
Bauer, M. E. (Principal Investigator); Tilton, J. C.; Swain, P. H.
1981-01-01
Compound decision theory is employed to develop a general statistical model for classifying image data using spatial context. The classification algorithm developed from this model exploits the tendency of certain ground-cover classes to occur more frequently in some spatial contexts than in others. A key input to this contextural classifier is a quantitative characterization of this tendency: the context function. Several methods for estimating the context function are explored, and two complementary methods are recommended. The contextural classifier is shown to produce substantial improvements in classification accuracy compared to the accuracy produced by a non-contextural uniform-priors maximum likelihood classifier when these methods of estimating the context function are used. An approximate algorithm, which cuts computational requirements by over one-half, is presented. The search for an optimal implementation is furthered by an exploration of the relative merits of using spectral classes or information classes for classification and/or context function estimation.
Mathematical Modeling Approaches in Plant Metabolomics.
Fürtauer, Lisa; Weiszmann, Jakob; Weckwerth, Wolfram; Nägele, Thomas
2018-01-01
The experimental analysis of a plant metabolome typically results in a comprehensive and multidimensional data set. To interpret metabolomics data in the context of biochemical regulation and environmental fluctuation, various approaches of mathematical modeling have been developed and have proven useful. In this chapter, a general introduction to mathematical modeling is presented and discussed in context of plant metabolism. A particular focus is laid on the suitability of mathematical approaches to functionally integrate plant metabolomics data in a metabolic network and combine it with other biochemical or physiological parameters.
Challenging the Context: Perception, Polity, and Power.
ERIC Educational Resources Information Center
Hartfield, Ronne
1994-01-01
"Contextual areas" employ models, replicas, artwork, art materials, tools, interpretive panels, and interactive computer installations to help visitors explore the historical and cultural context of 6 of 12 works of art at the "Art Inside Out" exhibition in the Kraft General Foods Education Center of the Art Institute of Chicago. (MDH)
Variable context Markov chains for HIV protease cleavage site prediction.
Oğul, Hasan
2009-06-01
Deciphering the knowledge of HIV protease specificity and developing computational tools for detecting its cleavage sites in protein polypeptide chain are very desirable for designing efficient and specific chemical inhibitors to prevent acquired immunodeficiency syndrome. In this study, we developed a generative model based on a generalization of variable order Markov chains (VOMC) for peptide sequences and adapted the model for prediction of their cleavability by certain proteases. The new method, called variable context Markov chains (VCMC), attempts to identify the context equivalence based on the evolutionary similarities between individual amino acids. It was applied for HIV-1 protease cleavage site prediction problem and shown to outperform existing methods in terms of prediction accuracy on a common dataset. In general, the method is a promising tool for prediction of cleavage sites of all proteases and encouraged to be used for any kind of peptide classification problem as well.
p-brane actions and higher Roytenberg brackets
NASA Astrophysics Data System (ADS)
Jurčo, Branislav; Schupp, Peter; Vysoký, Jan
2013-02-01
Motivated by the quest to understand the analog of non-geometric flux compactification in the context of M-theory, we study higher dimensional analogs of generalized Poisson sigma models and corresponding dual string and p-brane models. We find that higher generalizations of the algebraic structures due to Dorfman, Roytenberg and Courant play an important role and establish their relation to Nambu-Poisson structures.
Theme-Based Tests: Teaching in Context
ERIC Educational Resources Information Center
Anderson, Gretchen L.; Heck, Marsha L.
2005-01-01
Theme-based tests provide an assessment tool that instructs as well as provides a single general context for a broad set of biochemical concepts. A single story line connects the questions on the tests and models applications of scientific principles and biochemical knowledge in an extended scenario. Theme-based tests are based on a set of…
Do perceived context pictures automatically activate their phonological code?
Jescheniak, Jörg D; Oppermann, Frank; Hantsch, Ansgar; Wagner, Valentin; Mädebach, Andreas; Schriefers, Herbert
2009-01-01
Morsella and Miozzo (Morsella, E., & Miozzo, M. (2002). Evidence for a cascade model of lexical access in speech production. Journal of Experimental Psychology: Learning, Memory, and Cognition, 28, 555-563) have reported that the to-be-ignored context pictures become phonologically activated when participants name a target picture, and took this finding as support for cascaded models of lexical retrieval in speech production. In a replication and extension of their experiment in German, we failed to obtain priming effects from context pictures phonologically related to a to-be-named target picture. By contrast, corresponding context words (i.e., the names of the respective pictures) and the same context pictures, when used in an identity condition, did reliably facilitate the naming process. This pattern calls into question the generality of the claim advanced by Morsella and Miozzo that perceptual processing of pictures in the context of a naming task automatically leads to the activation of corresponding lexical-phonological codes.
DOE Office of Scientific and Technical Information (OSTI.GOV)
McManamay, Ryan A
2014-01-01
Despite the ubiquitous existence of dams within riverscapes, much of our knowledge about dams and their environmental effects remains context-specific. Hydrology, more than any other environmental variable, has been studied in great detail with regard to dam regulation. While much progress has been made in generalizing the hydrologic effects of regulation by large dams, many aspects of hydrology show site-specific fidelity to dam operations, small dams (including diversions), and regional hydrologic regimes. A statistical modeling framework is presented to quantify and generalize hydrologic responses to varying degrees of dam regulation. Specifically, the objectives were to 1) compare the effects ofmore » local versus cumulative dam regulation, 2) determine the importance of different regional hydrologic regimes in influencing hydrologic responses to dams, and 3) evaluate how different regulation contexts lead to error in predicting hydrologic responses to dams. Overall, model performance was poor in quantifying the magnitude of hydrologic responses, but performance was sufficient in classifying hydrologic responses as negative or positive. Responses of some hydrologic indices to dam regulation were highly dependent upon hydrologic class membership and the purpose of the dam. The opposing coefficients between local and cumulative-dam predictors suggested that hydrologic responses to cumulative dam regulation are complex, and predicting the hydrology downstream of individual dams, as opposed to multiple dams, may be more easy accomplished using statistical approaches. Results also suggested that particular contexts, including multipurpose dams, high cumulative regulation by multiple dams, diversions, close proximity to dams, and certain hydrologic classes are all sources of increased error when predicting hydrologic responses to dams. Statistical models, such as the ones presented herein, show promise in their ability to model the effects of dam regulation effects at large spatial scales as to generalize the directionality of hydrologic responses.« less
Galilean generalized Robertson-Walker spacetimes: A new family of Galilean geometrical models
NASA Astrophysics Data System (ADS)
de la Fuente, Daniel; Rubio, Rafael M.
2018-02-01
We introduce a new family of Galilean spacetimes, the Galilean generalized Robertson-Walker spacetimes. This new family is relevant in the context of a generalized Newton-Cartan theory. We study its geometrical structure and analyse the completeness of its inextensible free falling observers. This sort of spacetimes constitutes the local geometric model of a much wider family of spacetimes admitting certain conformal symmetry. Moreover, we find some sufficient geometric conditions which guarantee a global splitting of a Galilean spacetime as a Galilean generalized Robertson-Walker spacetime.
On the Relation between the Linear Factor Model and the Latent Profile Model
ERIC Educational Resources Information Center
Halpin, Peter F.; Dolan, Conor V.; Grasman, Raoul P. P. P.; De Boeck, Paul
2011-01-01
The relationship between linear factor models and latent profile models is addressed within the context of maximum likelihood estimation based on the joint distribution of the manifest variables. Although the two models are well known to imply equivalent covariance decompositions, in general they do not yield equivalent estimates of the…
Pelloux, Yann; Hoots, Jennifer K; Cifani, Carlo; Adhikary, Sweta; Martin, Jennifer; Minier-Toribio, Angelica; Bossert, Jennifer M; Shaham, Yavin
2018-03-01
We recently developed a rat model of context-induced relapse to alcohol seeking after punishment-imposed abstinence to mimic relapse after self-imposed abstinence due to adverse consequences of drug use. Here, we determined the model's generality to cocaine and have begun to explore brain mechanisms of context-induced relapse to cocaine seeking after punishment-imposed abstinence, using the activity marker Fos. In exp. 1, we trained rats to self-administer cocaine (0.75 mg/kg/infusion, 6 hours/day, 12 days) in context A. Next, we transferred them to context B where for the paired group, but not unpaired group, 50 percent of cocaine-reinforced lever presses caused aversive footshock. We then tested the rats for cocaine seeking under extinction conditions in contexts A and B. We also retested them for relapse after retraining in context A and repunishment in context B. In exp. 2, we used Fos immunoreactivity to determine relapse-associated neuronal activation in brain regions of rats exposed to context A, context B or neither context. Results showed the selective shock-induced suppression of cocaine self-administration and context-induced relapse after punishment-imposed abstinence in rats exposed to paired, but not unpaired, footshock. Additionally, context-induced relapse was associated with selective activation of dorsal and ventral medial prefrontal cortex, anterior insula, dorsal striatum, basolateral amygdala, paraventricular nucleus of the thalamus, lateral habenula, substantia nigra, ventral subiculum, and dorsal raphe, but not nucleus accumbens, central amygdala, lateral hypothalamus, ventral tegmental area and other brain regions. Together, context-induced relapse after punishment-imposed abstinence generalizes to rats with a history of cocaine self-administration and is associated with selective activation of cortical and subcortical regions. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.
Nonlinear evolution of coarse-grained quantum systems with generalized purity constraints
NASA Astrophysics Data System (ADS)
Burić, Nikola
2010-12-01
Constrained quantum dynamics is used to propose a nonlinear dynamical equation for pure states of a generalized coarse-grained system. The relevant constraint is given either by the generalized purity or by the generalized invariant fluctuation, and the coarse-grained pure states correspond to the generalized coherent, i.e. generalized nonentangled states. Open system model of the coarse-graining is discussed. It is shown that in this model and in the weak coupling limit the constrained dynamical equations coincide with an equation for pointer states, based on Hilbert-Schmidt distance, that was previously suggested in the context of the decoherence theory.
Two statistical approaches, weighted regression on time, discharge, and season and generalized additive models, have recently been used to evaluate water quality trends in estuaries. Both models have been used in similar contexts despite differences in statistical foundations and...
ERIC Educational Resources Information Center
Bain, Kinsey; Rodriguez, Jon-Marc G.; Towns, Marcy H.
2018-01-01
Zero-order systems provide an interesting opportunity for students to think about the underlying mechanism behind the physical phenomena being modeled. The work reported here is part of a larger study that seeks to characterize how students integrate chemistry and mathematics in the context of chemical kinetics. Thirty-six general chemistry…
Behavioral mechanisms of context fear generalization in mice
Huckleberry, Kylie A.; Ferguson, Laura B.
2016-01-01
There is growing interest in generalization of learned contextual fear, driven in part by the hypothesis that mood and anxiety disorders stem from impaired hippocampal mechanisms of fear generalization and discrimination. However, there has been relatively little investigation of the behavioral and procedural mechanisms that might control generalization of contextual fear. We assessed the relative contribution of different contextual features to context fear generalization and characterized how two common conditioning protocols—foreground (uncued) and background (cued) contextual fear conditioning—affected context fear generalization. In one experiment, mice were fear conditioned in context A, and then tested for contextual fear both in A and in an alternate context created by changing a subset of A's elements. The results suggest that floor configuration and odor are more salient features than chamber shape. A second experiment compared context fear generalization in background and foreground context conditioning. Although foreground conditioning produced more context fear than background conditioning, the two procedures produced equal amounts of generalized fear. Finally, results indicated that the order of context tests (original first versus alternate first) significantly modulates context fear generalization, perhaps because the original and alternate contexts are differentially sensitive to extinction. Overall, results demonstrate that context fear generalization is sensitive to procedural variations and likely reflects the operation of multiple interacting psychological and neural mechanisms. PMID:27918275
Keiser, Ashley A; Turnbull, Lacie M; Darian, Mara A; Feldman, Dana E; Song, Iris; Tronson, Natalie C
2017-01-01
Anxiety disorders are commonly associated with increased generalization of fear from a stress- or trauma-associated environment to a neutral context or environment. Differences in context-associated memory in males and females may contribute to increased susceptibility to anxiety disorders in women. Here we examined sex differences in context fear generalization and its neural correlates. We observed stronger context fear conditioning and more generalization of fear to a similar context in females than males. In addition, context preexposure increased fear conditioning in males and decreased generalization in females. Accordingly, males showed stronger cFos activity in dorsal hippocampus during memory retrieval and context generalization, whereas females showed preferential recruitment of basal amygdala. Together, these findings are consistent with previous research showing that hippocampal activity correlates with reduced context fear generalization. Differential competition between hippocampus and amygdala-dependent processes may thus contribute to sex differences in retrieval of context fear and greater generalization of fear-associated memory. PMID:27577601
Rivas, Elena; Lang, Raymond; Eddy, Sean R
2012-02-01
The standard approach for single-sequence RNA secondary structure prediction uses a nearest-neighbor thermodynamic model with several thousand experimentally determined energy parameters. An attractive alternative is to use statistical approaches with parameters estimated from growing databases of structural RNAs. Good results have been reported for discriminative statistical methods using complex nearest-neighbor models, including CONTRAfold, Simfold, and ContextFold. Little work has been reported on generative probabilistic models (stochastic context-free grammars [SCFGs]) of comparable complexity, although probabilistic models are generally easier to train and to use. To explore a range of probabilistic models of increasing complexity, and to directly compare probabilistic, thermodynamic, and discriminative approaches, we created TORNADO, a computational tool that can parse a wide spectrum of RNA grammar architectures (including the standard nearest-neighbor model and more) using a generalized super-grammar that can be parameterized with probabilities, energies, or arbitrary scores. By using TORNADO, we find that probabilistic nearest-neighbor models perform comparably to (but not significantly better than) discriminative methods. We find that complex statistical models are prone to overfitting RNA structure and that evaluations should use structurally nonhomologous training and test data sets. Overfitting has affected at least one published method (ContextFold). The most important barrier to improving statistical approaches for RNA secondary structure prediction is the lack of diversity of well-curated single-sequence RNA secondary structures in current RNA databases.
Rivas, Elena; Lang, Raymond; Eddy, Sean R.
2012-01-01
The standard approach for single-sequence RNA secondary structure prediction uses a nearest-neighbor thermodynamic model with several thousand experimentally determined energy parameters. An attractive alternative is to use statistical approaches with parameters estimated from growing databases of structural RNAs. Good results have been reported for discriminative statistical methods using complex nearest-neighbor models, including CONTRAfold, Simfold, and ContextFold. Little work has been reported on generative probabilistic models (stochastic context-free grammars [SCFGs]) of comparable complexity, although probabilistic models are generally easier to train and to use. To explore a range of probabilistic models of increasing complexity, and to directly compare probabilistic, thermodynamic, and discriminative approaches, we created TORNADO, a computational tool that can parse a wide spectrum of RNA grammar architectures (including the standard nearest-neighbor model and more) using a generalized super-grammar that can be parameterized with probabilities, energies, or arbitrary scores. By using TORNADO, we find that probabilistic nearest-neighbor models perform comparably to (but not significantly better than) discriminative methods. We find that complex statistical models are prone to overfitting RNA structure and that evaluations should use structurally nonhomologous training and test data sets. Overfitting has affected at least one published method (ContextFold). The most important barrier to improving statistical approaches for RNA secondary structure prediction is the lack of diversity of well-curated single-sequence RNA secondary structures in current RNA databases. PMID:22194308
Context Modeler for Wavelet Compression of Spectral Hyperspectral Images
NASA Technical Reports Server (NTRS)
Kiely, Aaron; Xie, Hua; Klimesh, matthew; Aranki, Nazeeh
2010-01-01
A context-modeling sub-algorithm has been developed as part of an algorithm that effects three-dimensional (3D) wavelet-based compression of hyperspectral image data. The context-modeling subalgorithm, hereafter denoted the context modeler, provides estimates of probability distributions of wavelet-transformed data being encoded. These estimates are utilized by an entropy coding subalgorithm that is another major component of the compression algorithm. The estimates make it possible to compress the image data more effectively than would otherwise be possible. The following background discussion is prerequisite to a meaningful summary of the context modeler. This discussion is presented relative to ICER-3D, which is the name attached to a particular compression algorithm and the software that implements it. The ICER-3D software is summarized briefly in the preceding article, ICER-3D Hyperspectral Image Compression Software (NPO-43238). Some aspects of this algorithm were previously described, in a slightly more general context than the ICER-3D software, in "Improving 3D Wavelet-Based Compression of Hyperspectral Images" (NPO-41381), NASA Tech Briefs, Vol. 33, No. 3 (March 2009), page 7a. In turn, ICER-3D is a product of generalization of ICER, another previously reported algorithm and computer program that can perform both lossless and lossy wavelet-based compression and decompression of gray-scale-image data. In ICER-3D, hyperspectral image data are decomposed using a 3D discrete wavelet transform (DWT). Following wavelet decomposition, mean values are subtracted from spatial planes of spatially low-pass subbands prior to encoding. The resulting data are converted to sign-magnitude form and compressed. In ICER-3D, compression is progressive, in that compressed information is ordered so that as more of the compressed data stream is received, successive reconstructions of the hyperspectral image data are of successively higher overall fidelity.
Learning general phonological rules from distributional information: a computational model.
Calamaro, Shira; Jarosz, Gaja
2015-04-01
Phonological rules create alternations in the phonetic realizations of related words. These rules must be learned by infants in order to identify the phonological inventory, the morphological structure, and the lexicon of a language. Recent work proposes a computational model for the learning of one kind of phonological alternation, allophony (Peperkamp, Le Calvez, Nadal, & Dupoux, 2006). This paper extends the model to account for learning of a broader set of phonological alternations and the formalization of these alternations as general rules. In Experiment 1, we apply the original model to new data in Dutch and demonstrate its limitations in learning nonallophonic rules. In Experiment 2, we extend the model to allow it to learn general rules for alternations that apply to a class of segments. In Experiment 3, the model is further extended to allow for generalization by context; we argue that this generalization must be constrained by linguistic principles. Copyright © 2014 Cognitive Science Society, Inc.
The Strategies of Modeling in Biology Education
ERIC Educational Resources Information Center
Svoboda, Julia; Passmore, Cynthia
2013-01-01
Modeling, like inquiry more generally, is not a single method, but rather a complex suite of strategies. Philosophers of biology, citing the diverse aims, interests, and disciplinary cultures of biologists, argue that modeling is best understood in the context of its epistemic aims and cognitive payoffs. In the science education literature,…
Fear and Loving in Las Vegas: Evolution, Emotion, and Persuasion.
Griskevicius, Vladas; Goldstein, Noah J; Mortensen, Chad R; Sundie, Jill M; Cialdini, Robert B; Kenrick, Douglas T
2009-06-01
How do arousal-inducing contexts, such as frightening or romantic television programs, influence the effectiveness of basic persuasion heuristics? Different predictions are made by three theoretical models: A general arousal model predicts that arousal should increase effectiveness of heuristics; an affective valence model predicts that effectiveness should depend on whether the context elicits positive or negative affect; an evolutionary model predicts that persuasiveness should depend on both the specific emotion that is elicited and the content of the particular heuristic. Three experiments examined how fear-inducing versus romantic contexts influenced the effectiveness of two widely used heuristics-social proof (e.g., "most popular") and scarcity (e.g., "limited edition"). Results supported predictions from an evolutionary model, showing that fear can lead scarcity appeals to be counter-persuasive, and that romantic desire can lead social proof appeals to be counter-persuasive. The findings highlight how an evolutionary theoretical approach can lead to novel theoretical and practical marketing insights.
Medial Temporal Lobe Contributions to Cued Retrieval of Items and Contexts
Hannula, Deborah E.; Libby, Laura A.; Yonelinas, Andrew P.; Ranganath, Charan
2013-01-01
Several models have proposed that different regions of the medial temporal lobes contribute to different aspects of episodic memory. For instance, according to one view, the perirhinal cortex represents specific items, parahippocampal cortex represents information regarding the context in which these items were encountered, and the hippocampus represents item-context bindings. Here, we used event-related functional magnetic resonance imaging (fMRI) to test a specific prediction of this model – namely, that successful retrieval of items from context cues will elicit perirhinal recruitment and that successful retrieval of contexts from item cues will elicit parahippocampal cortex recruitment. Retrieval of the bound representation in either case was expected to elicit hippocampal engagement. To test these predictions, we had participants study several item-context pairs (i.e., pictures of objects and scenes, respectively), and then had them attempt to recall items from associated context cues and contexts from associated item cues during a scanned retrieval session. Results based on both univariate and multivariate analyses confirmed a role for hippocampus in content-general relational memory retrieval, and a role for parahippocampal cortex in successful retrieval of contexts from item cues. However, we also found that activity differences in perirhinal cortex were correlated with successful cued recall for both items and contexts. These findings provide partial support for the above predictions and are discussed with respect to several models of medial temporal lobe function. PMID:23466350
Teaching Popular Culture in a Second Language University Context
ERIC Educational Resources Information Center
Pierson-Smith, Anne; Chik, Alice; Miller, Lindsay
2014-01-01
This article examines an established course on Popular Culture which is framed within the general educational model in an English-medium university. The article is organized into three parts: the underlining educational rationale for general educational courses, the course description, and the students' perspectives of their learning experience.…
Using MHD Models for Context for Multispacecraft Missions
NASA Astrophysics Data System (ADS)
Reiff, P. H.; Sazykin, S. Y.; Webster, J.; Daou, A.; Welling, D. T.; Giles, B. L.; Pollock, C.
2016-12-01
The use of global MHD models such as BATS-R-US to provide context to data from widely spaced multispacecraft mission platforms is gaining in popularity and in effectiveness. Examples are shown, primarily from the Magnetospheric Multiscale Mission (MMS) program compared to BATS-R-US. We present several examples of large-scale magnetospheric configuration changes such as tail dipolarization events and reconfigurations after a sector boundary crossing which are made much more easily understood by placing the spacecraft in the model fields. In general, the models can reproduce the large-scale changes observed by the various spacecraft but sometimes miss small-scale or rapid time changes.
Dawson, Colin; Gerken, Louann
2011-09-01
While many constraints on learning must be relatively experience-independent, past experience provides a rich source of guidance for subsequent learning. Discovering structure in some domain can inform a learner's future hypotheses about that domain. If a general property accounts for particular sub-patterns, a rational learner should not stipulate separate explanations for each detail without additional evidence, as the general structure has "explained away" the original evidence. In a grammar-learning experiment using tone sequences, manipulating learners' prior exposure to a tone environment affects their sensitivity to the grammar-defining feature, in this case consecutive repeated tones. Grammar-learning performance is worse if context melodies are "smooth" -- when small intervals occur more than large ones -- as Smoothness is a general property accounting for a high rate of repetition. We present an idealized Bayesian model as a "best case" benchmark for learning repetition grammars. When context melodies are Smooth, the model places greater weight on the small-interval constraint, and does not learn the repetition rule as well as when context melodies are not Smooth, paralleling the human learners. These findings support an account of abstract grammar-induction in which learners rationally assess the statistical evidence for underlying structure based on a generative model of the environment. Copyright © 2010 Elsevier B.V. All rights reserved.
Horizon fluffs: In the context of generalized minimal massive gravity
NASA Astrophysics Data System (ADS)
Setare, Mohammad Reza; Adami, Hamed
2018-02-01
We consider a metric which describes Bañados geometries and show that the considered metric is a solution of the generalized minimal massive gravity (GMMG) model. We consider the Killing vector field which preserves the form of the considered metric. Using the off-shell quasi-local approach we obtain the asymptotic conserved charges of the given solution. Similar to the Einstein gravity in the presence of negative cosmological constant, for the GMMG model, we also show that the algebra among the asymptotic conserved charges is isomorphic to two copies of the Virasoro algebra. Eventually, we find a relation between the algebra of the near-horizon and the asymptotic conserved charges. This relation shows that the main part of the horizon fluffs proposed by Afshar et al., Sheikh-Jabbari and Yavartanoo appear for generic black holes in the class of Bañados geometries in the context of the GMMG model.
Denault, Anne-Sophie; Guay, Frédéric
2017-01-01
Participation in extracurricular activities is a promising avenue for enhancing students' school motivation. Using self-determination theory (Deci & Ryan, 2000), the goal of this study was to test a serial multiple mediator model. In this model, students' perceptions of autonomy support from their extracurricular activity leader predicted their activity-based intrinsic and identified regulations. In turn, these regulations predicted their school-based intrinsic and identified regulations during the same school year. Finally, these regulations predicted their school-based intrinsic and identified regulations one year later. A total of 276 youths (54% girls) from disadvantaged neighborhoods were surveyed over two waves of data collection. The proposed mediation model was supported for both types of regulation. These results highlight the generalization effects of motivation from the extracurricular activity context to the school context. Copyright © 2016 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.
Conceptualising GP teachers' knowledge: a pedagogical content knowledge perspective.
Cantillon, Peter; de Grave, Willem
2012-05-01
Most teacher development initiatives focus on enhancing knowledge of teaching (pedagogy), whilst largely ignoring other important features of teacher knowledge such as subject matter knowledge and awareness of the learning context. Furthermore, teachers' ability to learn from faculty development interventions is limited by their existing (often implicit) pedagogical knowledge and beliefs. Pedagogical content knowledge (PCK) represents a model of teacher knowledge incorporating what they know about subject matter, pedagogy and context. PCK can be used to explore teachers' prior knowledge and to structure faculty development programmes so that they take account of a broader range of teachers' knowledge. We set out to examine the application of a PCK model in a general practice education setting. This study is part of a larger study that employed a mixed method approach (concept mapping, phenomenological interviews and video-stimulated recall) to explore features of GP teachers' subject matter knowledge, pedagogical knowledge and knowledge of the learning environment in the context of a general practice tutorial. This paper presents data on GP teachers' pedagogical and context knowledge. There was considerable overlap between different GP teachers' knowledge and beliefs about learners and the clinical learning environment (i.e. knowledge of context). The teachers' beliefs about learners were largely based on assumptions derived from their own student experiences. There were stark differences, however, between teachers in terms of pedagogical knowledge, particularly in terms of their teaching orientations (i.e. transmission or facilitation orientation) and this was manifest in their teaching behaviours. PCK represents a useful model for conceptualising clinical teacher prior knowledge in three domains, namely subject matter, learning context and pedagogy. It can and should be used as a simple guiding framework by faculty developers to inform the design and delivery of their faculty development programmes.
NASA Astrophysics Data System (ADS)
Krishna, Anirudh; Spekkens, Robert W.; Wolfe, Elie
2017-12-01
When a measurement is compatible with each of two other measurements that are incompatible with one another, these define distinct contexts for the given measurement. The Kochen-Specker theorem rules out models of quantum theory that satisfy a particular assumption of context-independence: that sharp measurements are assigned outcomes both deterministically and independently of their context. This notion of noncontextuality is not suited to a direct experimental test because realistic measurements always have some degree of unsharpness due to noise. However, a generalized notion of noncontextuality has been proposed that is applicable to any experimental procedure, including unsharp measurements, but also preparations as well, and for which a quantum no-go result still holds. According to this notion, the model need only specify a probability distribution over the outcomes of a measurement in a context-independent way, rather than specifying a particular outcome. It also implies novel constraints of context-independence for the representation of preparations. In this article, we describe a general technique for translating proofs of the Kochen-Specker theorem into inequality constraints on realistic experimental statistics, the violation of which witnesses the impossibility of a noncontextual model. We focus on algebraic state-independent proofs, using the Peres-Mermin square as our illustrative example. Our technique yields the necessary and sufficient conditions for a particular set of correlations (between the preparations and the measurements) to admit a noncontextual model. The inequalities thus derived are demonstrably robust to noise. We specify how experimental data must be processed in order to achieve a test of these inequalities. We also provide a criticism of prior proposals for experimental tests of noncontextuality based on the Peres-Mermin square.
ERIC Educational Resources Information Center
Ginovart, Marta
2014-01-01
The general aim is to promote the use of individual-based models (biological agent-based models) in teaching and learning contexts in life sciences and to make their progressive incorporation into academic curricula easier, complementing other existing modelling strategies more frequently used in the classroom. Modelling activities for the study…
Teaching Communication Skills in Science: Tracing Teacher Change
ERIC Educational Resources Information Center
Spektor-Levy, Ornit; Eylon, Bat-Sheva; Scherz, Zahava
2008-01-01
This paper describes a general model for skills instruction and its implementation through the program "Scientific Communication" for acquiring learning skills. The model is characterized by modularity, explicit instruction, spiral integration into contents, practice in various contexts, and implementation in performance tasks. It requires…
Fiscal Neutrality and Local Choice in Public Education.
ERIC Educational Resources Information Center
Weber, William L.
1991-01-01
Extends Feldstein's notion of wealth neutrality to embrace fiscal neutrality, using a representative consumer context. Employs an "ideal" demand system to model school district expenditures in a general equilibrium framework. Rejects constant price and income elasticity demand models. Supports the fiscally neutral elasticity model…
Multilevel Evaluation Alignment: An Explication of a Four-Step Model
ERIC Educational Resources Information Center
Yang, Huilan; Shen, Jianping; Cao, Honggao; Warfield, Charles
2004-01-01
Using the evaluation work on the W.K. Kellogg Foundation's Unleashing Resources Initiative as an example, in this article we explicate a general four-step model appropriate for multilevel evaluation alignment. We review the relevant literature, argue for the need for evaluation alignment in a multilevel context, explain the four-step model,…
Exponential inflation with F (R ) gravity
NASA Astrophysics Data System (ADS)
Oikonomou, V. K.
2018-03-01
In this paper, we shall consider an exponential inflationary model in the context of vacuum F (R ) gravity. By using well-known reconstruction techniques, we shall investigate which F (R ) gravity can realize the exponential inflation scenario at leading order in terms of the scalar curvature, and we shall calculate the slow-roll indices and the corresponding observational indices, in the context of slow-roll inflation. We also provide some general formulas of the slow-roll and the corresponding observational indices in terms of the e -foldings number. In addition, for the calculation of the slow-roll and of the observational indices, we shall consider quite general formulas, for which it is not necessary for the assumption that all the slow-roll indices are much smaller than unity to hold true. Finally, we investigate the phenomenological viability of the model by comparing it with the latest Planck and BICEP2/Keck-Array observational data. As we demonstrate, the model is compatible with the current observational data for a wide range of the free parameters of the model.
Toward a general psychological model of tension and suspense
Lehne, Moritz; Koelsch, Stefan
2015-01-01
Tension and suspense are powerful emotional experiences that occur in a wide variety of contexts (e.g., in music, film, literature, and everyday life). The omnipresence of tension and suspense suggests that they build on very basic cognitive and affective mechanisms. However, the psychological underpinnings of tension experiences remain largely unexplained, and tension and suspense are rarely discussed from a general, domain-independent perspective. In this paper, we argue that tension experiences in different contexts (e.g., musical tension or suspense in a movie) build on the same underlying psychological processes. We discuss key components of tension experiences and propose a domain-independent model of tension and suspense. According to this model, tension experiences originate from states of conflict, instability, dissonance, or uncertainty that trigger predictive processes directed at future events of emotional significance. We also discuss possible neural mechanisms underlying tension and suspense. The model provides a theoretical framework that can inform future empirical research on tension phenomena. PMID:25717309
Toward a general psychological model of tension and suspense.
Lehne, Moritz; Koelsch, Stefan
2015-01-01
Tension and suspense are powerful emotional experiences that occur in a wide variety of contexts (e.g., in music, film, literature, and everyday life). The omnipresence of tension and suspense suggests that they build on very basic cognitive and affective mechanisms. However, the psychological underpinnings of tension experiences remain largely unexplained, and tension and suspense are rarely discussed from a general, domain-independent perspective. In this paper, we argue that tension experiences in different contexts (e.g., musical tension or suspense in a movie) build on the same underlying psychological processes. We discuss key components of tension experiences and propose a domain-independent model of tension and suspense. According to this model, tension experiences originate from states of conflict, instability, dissonance, or uncertainty that trigger predictive processes directed at future events of emotional significance. We also discuss possible neural mechanisms underlying tension and suspense. The model provides a theoretical framework that can inform future empirical research on tension phenomena.
Multivariate Longitudinal Analysis with Bivariate Correlation Test.
Adjakossa, Eric Houngla; Sadissou, Ibrahim; Hounkonnou, Mahouton Norbert; Nuel, Gregory
2016-01-01
In the context of multivariate multilevel data analysis, this paper focuses on the multivariate linear mixed-effects model, including all the correlations between the random effects when the dimensional residual terms are assumed uncorrelated. Using the EM algorithm, we suggest more general expressions of the model's parameters estimators. These estimators can be used in the framework of the multivariate longitudinal data analysis as well as in the more general context of the analysis of multivariate multilevel data. By using a likelihood ratio test, we test the significance of the correlations between the random effects of two dependent variables of the model, in order to investigate whether or not it is useful to model these dependent variables jointly. Simulation studies are done to assess both the parameter recovery performance of the EM estimators and the power of the test. Using two empirical data sets which are of longitudinal multivariate type and multivariate multilevel type, respectively, the usefulness of the test is illustrated.
Challenges for Cloud Modeling in the Context of Aerosol–Cloud–Precipitation Interactions
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lebo, Zachary J.; Shipway, Ben J.; Fan, Jiwen
The International Cloud Modeling Workshop (CMW) has been a longstanding tradition in the cloud microphysics modeling community and is typically held the week prior to the International Conference on Clouds and Precipitation (ICCP). For the Ninth CMW, more than 40 participants from 10 countries convened at the Met Office in Exeter, United Kingdom. The workshop included 4 detailed case studies (described in more detail below) rooted in recent field campaigns. The overarching objective of these cases was to utilize new observations to better understand inter-model differences and model deficiencies, explore new modeling techniques, and gain physical insight into the behaviormore » of clouds. As was the case at the Eighth CMW, there was a general theme of understanding the role of aerosol impacts in the context of cloud-precipitation interactions. However, an additional objective was the focal point of several cases at the most recent workshop: microphysical-dynamical interactions. Many of the cases focused less on idealized small-domain simulations (as was the general focus of previous workshops) and more on large-scale nested configurations examining effects at various scales.« less
Sauer, James D; Drummond, Aaron; Nova, Natalie
2015-09-01
The potential influence of video game violence on real-world aggression has generated considerable public and scientific interest. Some previous research suggests that playing violent video games can increase postgame aggression. The generalized aggression model (GAM) attributes this to the generalized activation of aggressive schemata. However, it is unclear whether game mechanics that contextualize and encourage or inhibit in-game violence moderate this relationship. Thus, we examined the effects of reward structures and narrative context in a violent video game on in-game and postgame aggression. Contrary to GAM-based predictions, our manipulations differentially affected in-game and postgame aggression. Reward structures selectively affected in-game aggression, whereas narrative context selectively affected postgame aggression. Players who enacted in-game violence through a heroic character exhibited less postgame aggression than players who enacted comparable levels of in-game violence through an antiheroic character. Effects were not attributable to self-activation or character-identification mechanisms, but were consistent with social-cognitive context effects on the interpretation of behavior. These results contradict the GAM's assertion that violent video games affect aggression through a generalized activation mechanism. From an applied perspective, consumer choices may be aided by considering not just game content, but the context in which content is portrayed. (c) 2015 APA, all rights reserved).
Evaluating dedicated and intrinsic models of temporal encoding by varying context
Spencer, Rebecca M.C.; Karmarkar, Uma; Ivry, Richard B.
2009-01-01
Two general classes of models have been proposed to account for how people process temporal information in the milliseconds range. Dedicated models entail a mechanism in which time is explicitly encoded; examples include clock–counter models and functional delay lines. Intrinsic models, such as state-dependent networks (SDN), represent time as an emergent property of the dynamics of neural processing. An important property of SDN is that the encoding of duration is context dependent since the representation of an interval will vary as a function of the initial state of the network. Consistent with this assumption, duration discrimination thresholds for auditory intervals spanning 100 ms are elevated when an irrelevant tone is presented at varying times prior to the onset of the test interval. We revisit this effect in two experiments, considering attentional issues that may also produce such context effects. The disruptive effect of a variable context was eliminated or attenuated when the intervals between the irrelevant tone and test interval were made dissimilar or the duration of the test interval was increased to 300 ms. These results indicate how attentional processes can influence the perception of brief intervals, as well as point to important constraints for SDN models. PMID:19487188
Medial temporal lobe contributions to cued retrieval of items and contexts.
Hannula, Deborah E; Libby, Laura A; Yonelinas, Andrew P; Ranganath, Charan
2013-10-01
Several models have proposed that different regions of the medial temporal lobes contribute to different aspects of episodic memory. For instance, according to one view, the perirhinal cortex represents specific items, parahippocampal cortex represents information regarding the context in which these items were encountered, and the hippocampus represents item-context bindings. Here, we used event-related functional magnetic resonance imaging (fMRI) to test a specific prediction of this model-namely, that successful retrieval of items from context cues will elicit perirhinal recruitment and that successful retrieval of contexts from item cues will elicit parahippocampal cortex recruitment. Retrieval of the bound representation in either case was expected to elicit hippocampal engagement. To test these predictions, we had participants study several item-context pairs (i.e., pictures of objects and scenes, respectively), and then had them attempt to recall items from associated context cues and contexts from associated item cues during a scanned retrieval session. Results based on both univariate and multivariate analyses confirmed a role for hippocampus in content-general relational memory retrieval, and a role for parahippocampal cortex in successful retrieval of contexts from item cues. However, we also found that activity differences in perirhinal cortex were correlated with successful cued recall for both items and contexts. These findings provide partial support for the above predictions and are discussed with respect to several models of medial temporal lobe function. Copyright © 2013 Elsevier Ltd. All rights reserved.
Fisher's geometrical model emerges as a property of complex integrated phenotypic networks.
Martin, Guillaume
2014-05-01
Models relating phenotype space to fitness (phenotype-fitness landscapes) have seen important developments recently. They can roughly be divided into mechanistic models (e.g., metabolic networks) and more heuristic models like Fisher's geometrical model. Each has its own drawbacks, but both yield testable predictions on how the context (genomic background or environment) affects the distribution of mutation effects on fitness and thus adaptation. Both have received some empirical validation. This article aims at bridging the gap between these approaches. A derivation of the Fisher model "from first principles" is proposed, where the basic assumptions emerge from a more general model, inspired by mechanistic networks. I start from a general phenotypic network relating unspecified phenotypic traits and fitness. A limited set of qualitative assumptions is then imposed, mostly corresponding to known features of phenotypic networks: a large set of traits is pleiotropically affected by mutations and determines a much smaller set of traits under optimizing selection. Otherwise, the model remains fairly general regarding the phenotypic processes involved or the distribution of mutation effects affecting the network. A statistical treatment and a local approximation close to a fitness optimum yield a landscape that is effectively the isotropic Fisher model or its extension with a single dominant phenotypic direction. The fit of the resulting alternative distributions is illustrated in an empirical data set. These results bear implications on the validity of Fisher's model's assumptions and on which features of mutation fitness effects may vary (or not) across genomic or environmental contexts.
No need for dark matter in galaxy clusters within Galileon theory
NASA Astrophysics Data System (ADS)
Salzano, Vincenzo; Mota, David F.; Dabrowski, Mariusz P.; Capozziello, Salvatore
2016-10-01
Modified gravity theories with a screening mechanism have acquired much interest recently in the quest for a viable alternative to General Relativity on cosmological scales, given their intrinsic property of being able to pass Solar System scale tests and, at the same time, to possibly drive universe acceleration on much larger scales. Here, we explore the possibility that the same screening mechanism, or its breaking at a certain astrophysical scale, might be responsible of those gravitational effects which, in the context of general relativity, are generally attributed to Dark Matter. We consider a recently proposed extension of covariant Galileon models in the so-called ``beyond Horndeski'' scenario, where a breaking of the Vainshtein mechanism is possible and, thus, some peculiar observational signatures should be detectable and make it distinguishable from general relativity. We apply this model to a sample of clusters of galaxies observed under the CLASH survey, using both new data from gravitational lensing events and archival data from X-ray intra-cluster hot gas observations. In particular, we use the latter to model the gas density, and then use it as the only ingredient in the matter clusters' budget to calculate the expected lensing convergence map. Results show that, in the context of this extended Galileon, the assumption of having only gas and no Dark Matter at all in the clusters is able to match observations. We also obtain narrow and very interesting bounds on the parameters which characterize this model. In particular, we find that, at least for one of them, the general relativity limit is excluded at 2σ confidence level, thus making this model clearly statistically different and competitive with respect to general relativity.
The Economics of Timber Supply: An Analytical Synthesis of Modeling Approaches
David N. Wear; Peter J. Parks
1994-01-01
The joint supply of timber and other services from forest environments plays a central role in most forest land debates. This paper defines a general conceptual model of timber supply that provides the context for discussing both individual harvest choice and aggregate supply models. While the structure and breadth of these models has developed considerably over the...
Krasne, Franklin B.
2017-01-01
Dentate gyrus (DG) is widely thought to provide a teaching signal that enables hippocampal encoding of memories, but its role during retrieval is poorly understood. Some data and models suggest that DG plays no role in retrieval; others encourage the opposite conclusion. To resolve this controversy, we evaluated the effects of optogenetic inhibition of dorsal DG during context fear conditioning, recall, generalization, and extinction in male mice. We found that (1) inhibition during training impaired context fear acquisition; (2) inhibition during recall did not impair fear expression in the training context, unless mice had to distinguish between similar feared and neutral contexts; (3) inhibition increased generalization of fear to an unfamiliar context that was similar to a feared one and impaired fear expression in the conditioned context when it was similar to a neutral one; and (4) inhibition impaired fear extinction. These effects, as well as several seemingly contradictory published findings, could be reproduced by BACON (Bayesian Context Fear Algorithm), a physiologically realistic hippocampal model positing that acquisition and retrieval both involve coordinated activity in DG and CA3. Our findings thus suggest that DG contributes to retrieval and extinction, as well as to the initial establishment of context fear. SIGNIFICANCE STATEMENT Despite abundant evidence that the hippocampal dentate gyrus (DG) plays a critical role in memory, it remains unclear whether the role of DG relates to memory acquisition or retrieval. Using contextual fear conditioning and optogenetic inhibition, we show that DG contributes to both of these processes. Using computational simulations, we identify specific mechanisms through which the suppression of DG affects memory performance. Finally, we show that DG contributes to fear extinction learning, a process in which learned fear is attenuated through exposures to a fearful context in the absence of threat. Our data resolve a long-standing question about the role of DG in memory and provide insight into how disorders affecting DG, including aging, stress, and depression, influence cognitive processes. PMID:28546308
A neuronal network model for context-dependence of pitch change perception.
Huang, Chengcheng; Englitz, Bernhard; Shamma, Shihab; Rinzel, John
2015-01-01
Many natural stimuli have perceptual ambiguities that can be cognitively resolved by the surrounding context. In audition, preceding context can bias the perception of speech and non-speech stimuli. Here, we develop a neuronal network model that can account for how context affects the perception of pitch change between a pair of successive complex tones. We focus especially on an ambiguous comparison-listeners experience opposite percepts (either ascending or descending) for an ambiguous tone pair depending on the spectral location of preceding context tones. We developed a recurrent, firing-rate network model, which detects frequency-change-direction of successively played stimuli and successfully accounts for the context-dependent perception demonstrated in behavioral experiments. The model consists of two tonotopically organized, excitatory populations, E up and E down, that respond preferentially to ascending or descending stimuli in pitch, respectively. These preferences are generated by an inhibitory population that provides inhibition asymmetric in frequency to the two populations; context dependence arises from slow facilitation of inhibition. We show that contextual influence depends on the spectral distribution of preceding tones and the tuning width of inhibitory neurons. Further, we demonstrate, using phase-space analysis, how the facilitated inhibition from previous stimuli and the waning inhibition from the just-preceding tone shape the competition between the E up and E down populations. In sum, our model accounts for contextual influences on the pitch change perception of an ambiguous tone pair by introducing a novel decoding strategy based on direction-selective units. The model's network architecture and slow facilitating inhibition emerge as predictions of neuronal mechanisms for these perceptual dynamics. Since the model structure does not depend on the specific stimuli, we show that it generalizes to other contextual effects and stimulus types.
SDG Fermion-Pair Algebraic SO(12) and Sp(10) Models and Their Boson Realizations
NASA Astrophysics Data System (ADS)
Navratil, P.; Geyer, H. B.; Dobes, J.; Dobaczewski, J.
1995-11-01
It is shown how the boson mapping formalism may be applied as a useful many-body tool to solve a fermion problem. This is done in the context of generalized Ginocchio models for which we introduce S-, D-, and G-pairs of fermions and subsequently construct the sdg-boson realizations of the generalized Dyson type. The constructed SO(12) and Sp(10) fermion models are solved beyond the explicit symmetry limits. Phase transitions to rotational structures are obtained also in situations where there is no underlying SU(3) symmetry.
Pothos, Emmanuel M; Bailey, Todd M
2009-07-01
Naïve observers typically perceive some groupings for a set of stimuli as more intuitive than others. The problem of predicting category intuitiveness has been historically considered the remit of models of unsupervised categorization. In contrast, this article develops a measure of category intuitiveness from one of the most widely supported models of supervised categorization, the generalized context model (GCM). Considering different category assignments for a set of instances, the authors asked how well the GCM can predict the classification of each instance on the basis of all the other instances. The category assignment that results in the smallest prediction error is interpreted as the most intuitive for the GCM-the authors refer to this way of applying the GCM as "unsupervised GCM." The authors systematically compared predictions of category intuitiveness from the unsupervised GCM and two models of unsupervised categorization: the simplicity model and the rational model. The unsupervised GCM compared favorably with the simplicity model and the rational model. This success of the unsupervised GCM illustrates that the distinction between supervised and unsupervised categorization may need to be reconsidered. However, no model emerged as clearly superior, indicating that there is more work to be done in understanding and modeling category intuitiveness.
Alternative Models of Entrance Exams and Access to Higher Education: The Case of the Czech Republic
ERIC Educational Resources Information Center
Konecny, Tomas; Basl, Josef; Myslivecek, Jan; Simonova, Natalie
2012-01-01
The study compares the potential effects of a university admission exam model based on program-specific knowledge and an alternative model relying on general study aptitude (GSA) in the context of a strongly stratified educational system with considerable excess of demand over supply of university education. Using results of the "Sonda…
Intelligent systems in the context of surrounding environment.
Wakeling, J; Bak, P
2001-11-01
We investigate the behavioral patterns of a population of agents, each controlled by a simple biologically motivated neural network model, when they are set in competition against each other in the minority model of Challet and Zhang. We explore the effects of changing agent characteristics, demonstrating that crowding behavior takes place among agents of similar memory, and show how this allows unique "rogue" agents with higher memory values to take advantage of a majority population. We also show that agents' analytic capability is largely determined by the size of the intermediary layer of neurons. In the context of these results, we discuss the general nature of natural and artificial intelligence systems, and suggest intelligence only exists in the context of the surrounding environment (embodiment).
The three principles of action: a Pavlovian-instrumental transfer hypothesis
Cartoni, Emilio; Puglisi-Allegra, Stefano; Baldassarre, Gianluca
2013-01-01
Pavlovian conditioned stimuli can influence instrumental responding, an effect called Pavlovian-instrumental transfer (PIT). During the last decade, PIT has been subdivided into two types: specific PIT and general PIT, each having its own neural substrates. Specific PIT happens when a conditioned stimulus (CS) associated with a reward enhances an instrumental response directed to the same reward. Under general PIT, instead, the CS enhances a response directed to a different reward. While important progress has been made into identifying the neural substrates, the function of specific and general PIT and how they interact with instrumental responses are still not clear. In the experimental paradigm that distinguishes specific and general PIT an effect of PIT inhibition has also been observed and is waiting for an explanation. Here we propose an hypothesis that links these three PIT effects (specific PIT, general PIT and PIT inhibition) to three aspects of action evaluation. These three aspects, which we call “principles of action”, are: context, efficacy, and utility. In goal-directed behavior, an agent has to evaluate if the context is suitable to accomplish the goal, the efficacy of his action in getting the goal, and the utility of the goal itself: we suggest that each of the three PIT effects is related to one of these aspects of action evaluation. In particular, we link specific PIT with the estimation of efficacy, general PIT with the evaluation of utility, and PIT inhibition with the adequacy of context. We also provide a latent cause Bayesian computational model that exemplifies this hypothesis. This hypothesis and the model provide a new framework and new predictions to advance knowledge about PIT functioning and its role in animal adaptation. PMID:24312025
A Storytelling Learning Model for Legal Education
ERIC Educational Resources Information Center
Capuano, Nicola; De Maio, Carmen; Gaeta, Angelo; Mangione, Giuseppina Rita; Salerno, Saverio; Fratesi, Eleonora
2014-01-01
The purpose of this paper is to describe a learning model based on "Storytelling" and its application in the context of legal education helping build challenging training resources that explain, to common citizens with little or no background about legal topics, concepts related to "Legal Mediation" in general and in specific…
Lumped mass formulations for modeling flexible body systems
NASA Technical Reports Server (NTRS)
Rampalli, Rajiv
1989-01-01
The efforts of Mechanical Dynamics, Inc. in obtaining a general formulation for flexible bodies in a multibody setting are discussed. The efforts being supported by MDI, both in house and externally are summarized. The feasibility of using lumped mass approaches to modeling flexibility in a multibody dynamics context is examined. The kinematics and kinetics for a simple system consisting of two rigid bodies connected together by an elastic beam are developed in detail. Accuracy, efficiency and ease of use using this approach are some of the issues that are then looked at. The formulation is then generalized to a superelement containing several nodes and connecting several bodies. Superelement kinematics and kinetics equations are developed. The feasibility and effectiveness of the method is illustrated by the use of some examples illustrating phenomena common in the context of spacecraft motions.
Fear and Loving in Las Vegas: Evolution, Emotion, and Persuasion
Griskevicius, Vladas; Goldstein, Noah J.; Mortensen, Chad R.; Sundie, Jill M.; Cialdini, Robert B.; Kenrick, Douglas T.
2009-01-01
How do arousal-inducing contexts, such as frightening or romantic television programs, influence the effectiveness of basic persuasion heuristics? Different predictions are made by three theoretical models: A general arousal model predicts that arousal should increase effectiveness of heuristics; an affective valence model predicts that effectiveness should depend on whether the context elicits positive or negative affect; an evolutionary model predicts that persuasiveness should depend on both the specific emotion that is elicited and the content of the particular heuristic. Three experiments examined how fear-inducing versus romantic contexts influenced the effectiveness of two widely used heuristics—social proof (e.g., “most popular”) and scarcity (e.g., “limited edition”). Results supported predictions from an evolutionary model, showing that fear can lead scarcity appeals to be counter-persuasive, and that romantic desire can lead social proof appeals to be counter-persuasive. The findings highlight how an evolutionary theoretical approach can lead to novel theoretical and practical marketing insights. PMID:19727416
ERIC Educational Resources Information Center
Gladman, Justin; Perkins, David
2013-01-01
Context and Objective: Australian rural general practitioners (GPs) require public health knowledge. This study explored the suitability of teaching complex public health issues related to Aboriginal health by way of a hybrid problem-based learning (PBL) model within an intensive training retreat for GP registrars, when numerous trainees have no…
General and Culturally Specific Factors Influencing Black and White Rape Survivors' Self-Esteem
ERIC Educational Resources Information Center
Neville, Helen A.; Heppner, Mary J.; Oh, Euna; Spanierman, Lisa B.; Clark, Mary
2004-01-01
Grounded in a culturally inclusive ecological model of sexual assault recovery framework, the influence of personal (e.g., prior victimization), rape context (e.g., degree of injury during last assault), and postrape response factors (e.g., general and cultural attributions, rape related coping) on self-esteem of Black and White college women, who…
Fee, Michale S.
2012-01-01
In its simplest formulation, reinforcement learning is based on the idea that if an action taken in a particular context is followed by a favorable outcome, then, in the same context, the tendency to produce that action should be strengthened, or reinforced. While reinforcement learning forms the basis of many current theories of basal ganglia (BG) function, these models do not incorporate distinct computational roles for signals that convey context, and those that convey what action an animal takes. Recent experiments in the songbird suggest that vocal-related BG circuitry receives two functionally distinct excitatory inputs. One input is from a cortical region that carries context information about the current “time” in the motor sequence. The other is an efference copy of motor commands from a separate cortical brain region that generates vocal variability during learning. Based on these findings, I propose here a general model of vertebrate BG function that combines context information with a distinct motor efference copy signal. The signals are integrated by a learning rule in which efference copy inputs gate the potentiation of context inputs (but not efference copy inputs) onto medium spiny neurons in response to a rewarded action. The hypothesis is described in terms of a circuit that implements the learning of visually guided saccades. The model makes testable predictions about the anatomical and functional properties of hypothesized context and efference copy inputs to the striatum from both thalamic and cortical sources. PMID:22754501
Fee, Michale S
2012-01-01
In its simplest formulation, reinforcement learning is based on the idea that if an action taken in a particular context is followed by a favorable outcome, then, in the same context, the tendency to produce that action should be strengthened, or reinforced. While reinforcement learning forms the basis of many current theories of basal ganglia (BG) function, these models do not incorporate distinct computational roles for signals that convey context, and those that convey what action an animal takes. Recent experiments in the songbird suggest that vocal-related BG circuitry receives two functionally distinct excitatory inputs. One input is from a cortical region that carries context information about the current "time" in the motor sequence. The other is an efference copy of motor commands from a separate cortical brain region that generates vocal variability during learning. Based on these findings, I propose here a general model of vertebrate BG function that combines context information with a distinct motor efference copy signal. The signals are integrated by a learning rule in which efference copy inputs gate the potentiation of context inputs (but not efference copy inputs) onto medium spiny neurons in response to a rewarded action. The hypothesis is described in terms of a circuit that implements the learning of visually guided saccades. The model makes testable predictions about the anatomical and functional properties of hypothesized context and efference copy inputs to the striatum from both thalamic and cortical sources.
Statistical Methods for Generalized Linear Models with Covariates Subject to Detection Limits.
Bernhardt, Paul W; Wang, Huixia J; Zhang, Daowen
2015-05-01
Censored observations are a common occurrence in biomedical data sets. Although a large amount of research has been devoted to estimation and inference for data with censored responses, very little research has focused on proper statistical procedures when predictors are censored. In this paper, we consider statistical methods for dealing with multiple predictors subject to detection limits within the context of generalized linear models. We investigate and adapt several conventional methods and develop a new multiple imputation approach for analyzing data sets with predictors censored due to detection limits. We establish the consistency and asymptotic normality of the proposed multiple imputation estimator and suggest a computationally simple and consistent variance estimator. We also demonstrate that the conditional mean imputation method often leads to inconsistent estimates in generalized linear models, while several other methods are either computationally intensive or lead to parameter estimates that are biased or more variable compared to the proposed multiple imputation estimator. In an extensive simulation study, we assess the bias and variability of different approaches within the context of a logistic regression model and compare variance estimation methods for the proposed multiple imputation estimator. Lastly, we apply several methods to analyze the data set from a recently-conducted GenIMS study.
Exploring the experience of children with disabilities at school settings in Vietnam context.
Tran, Kham V
2014-01-01
The initial findings from 230 questionnaires' survey and 36 interviews, in which informants are CWD, children with non-disabilities (CWND), parents of CWD, and teachers in school settings, are stated as: (a) the general understanding of disability is based on medical model and individual model rather than social model, such understandings contribute great impacts to the CWD's experiences in their daily life in general and in school contexts in particular; (b) the most important difficulties which CWD experience at school are those of learning facilities, the empathy from their student peers and barriers in the physical environment; (c) the ways which CWD try to deal with such difficulties are mostly 'do-by-themselves' or try to adapt themselves rather than asking for supports actively. Based on these findings, recommendations for having further activities to change social awareness of disabilities, specific support structures for CWD and school staff are stated in order to promote the social inclusion of CWD in schools.
Multivariate Longitudinal Analysis with Bivariate Correlation Test
Adjakossa, Eric Houngla; Sadissou, Ibrahim; Hounkonnou, Mahouton Norbert; Nuel, Gregory
2016-01-01
In the context of multivariate multilevel data analysis, this paper focuses on the multivariate linear mixed-effects model, including all the correlations between the random effects when the dimensional residual terms are assumed uncorrelated. Using the EM algorithm, we suggest more general expressions of the model’s parameters estimators. These estimators can be used in the framework of the multivariate longitudinal data analysis as well as in the more general context of the analysis of multivariate multilevel data. By using a likelihood ratio test, we test the significance of the correlations between the random effects of two dependent variables of the model, in order to investigate whether or not it is useful to model these dependent variables jointly. Simulation studies are done to assess both the parameter recovery performance of the EM estimators and the power of the test. Using two empirical data sets which are of longitudinal multivariate type and multivariate multilevel type, respectively, the usefulness of the test is illustrated. PMID:27537692
Nikoloulopoulos, Aristidis K
2017-10-01
A bivariate copula mixed model has been recently proposed to synthesize diagnostic test accuracy studies and it has been shown that it is superior to the standard generalized linear mixed model in this context. Here, we call trivariate vine copulas to extend the bivariate meta-analysis of diagnostic test accuracy studies by accounting for disease prevalence. Our vine copula mixed model includes the trivariate generalized linear mixed model as a special case and can also operate on the original scale of sensitivity, specificity, and disease prevalence. Our general methodology is illustrated by re-analyzing the data of two published meta-analyses. Our study suggests that there can be an improvement on trivariate generalized linear mixed model in fit to data and makes the argument for moving to vine copula random effects models especially because of their richness, including reflection asymmetric tail dependence, and computational feasibility despite their three dimensionality.
A Virtual Environment for Resilient Infrastructure Modeling and Design
2015-09-01
Security CI Critical Infrastructure CID Center for Infrastructure Defense CSV Comma Separated Value DAD Defender-Attacker-Defender DHS Department...responses to disruptive events (e.g., cascading failure behavior) in a context- rich , controlled environment for exercises, education, and training...The general attacker-defender (AD) and defender-attacker-defender ( DAD ) models for CI are defined in Brown et al. (2006). These models help
McLaren, Donald G.; Ries, Michele L.; Xu, Guofan; Johnson, Sterling C.
2012-01-01
Functional MRI (fMRI) allows one to study task-related regional responses and task-dependent connectivity analysis using psychophysiological interaction (PPI) methods. The latter affords the additional opportunity to understand how brain regions interact in a task-dependent manner. The current implementation of PPI in Statistical Parametric Mapping (SPM8) is configured primarily to assess connectivity differences between two task conditions, when in practice fMRI tasks frequently employ more than two conditions. Here we evaluate how a generalized form of context-dependent PPI (gPPI; http://www.nitrc.org/projects/gppi), which is configured to automatically accommodate more than two task conditions in the same PPI model by spanning the entire experimental space, compares to the standard implementation in SPM8. These comparisons are made using both simulations and an empirical dataset. In the simulated dataset, we compare the interaction beta estimates to their expected values and model fit using the Akaike Information Criterion (AIC). We found that interaction beta estimates in gPPI were robust to different simulated data models, were not different from the expected beta value, and had better model fits than when using standard PPI (sPPI) methods. In the empirical dataset, we compare the model fit of the gPPI approach to sPPI. We found that the gPPI approach improved model fit compared to sPPI. There were several regions that became non-significant with gPPI. These regions all showed significantly better model fits with gPPI. Also, there were several regions where task-dependent connectivity was only detected using gPPI methods, also with improved model fit. Regions that were detected with all methods had more similar model fits. These results suggest that gPPI may have greater sensitivity and specificity than standard implementation in SPM. This notion is tempered slightly as there is no gold standard; however, data simulations with a known outcome support our conclusions about gPPI. In sum, the generalized form of context-dependent PPI approach has increased flexibility of statistical modeling, and potentially improves model fit, specificity to true negative findings, and sensitivity to true positive findings. PMID:22484411
DOE Office of Scientific and Technical Information (OSTI.GOV)
Salzano, Vincenzo; Da̧browski, Mariusz P.; Mota, David F.
Modified gravity theories with a screening mechanism have acquired much interest recently in the quest for a viable alternative to General Relativity on cosmological scales, given their intrinsic property of being able to pass Solar System scale tests and, at the same time, to possibly drive universe acceleration on much larger scales. Here, we explore the possibility that the same screening mechanism, or its breaking at a certain astrophysical scale, might be responsible of those gravitational effects which, in the context of general relativity, are generally attributed to Dark Matter. We consider a recently proposed extension of covariant Galileon modelsmore » in the so-called ''beyond Horndeski'' scenario, where a breaking of the Vainshtein mechanism is possible and, thus, some peculiar observational signatures should be detectable and make it distinguishable from general relativity. We apply this model to a sample of clusters of galaxies observed under the CLASH survey, using both new data from gravitational lensing events and archival data from X-ray intra-cluster hot gas observations. In particular, we use the latter to model the gas density, and then use it as the only ingredient in the matter clusters' budget to calculate the expected lensing convergence map. Results show that, in the context of this extended Galileon, the assumption of having only gas and no Dark Matter at all in the clusters is able to match observations. We also obtain narrow and very interesting bounds on the parameters which characterize this model. In particular, we find that, at least for one of them, the general relativity limit is excluded at 2σ confidence level, thus making this model clearly statistically different and competitive with respect to general relativity.« less
A General Multivariate Latent Growth Model with Applications to Student Achievement
ERIC Educational Resources Information Center
Bianconcini, Silvia; Cagnone, Silvia
2012-01-01
The evaluation of the formative process in the University system has been assuming an ever increasing importance in the European countries. Within this context, the analysis of student performance and capabilities plays a fundamental role. In this work, the authors propose a multivariate latent growth model for studying the performances of a…
Approximation Methods for Inverse Problems Governed by Nonlinear Parabolic Systems
1999-12-17
We present a rigorous theoretical framework for approximation of nonlinear parabolic systems with delays in the context of inverse least squares...numerical results demonstrating the convergence are given for a model of dioxin uptake and elimination in a distributed liver model that is a special case of the general theoretical framework .
What Is Coded into Memory in the Absence of Outcome Feedback?
ERIC Educational Resources Information Center
Henriksson, Maria P.; Elwin, Ebba; Juslin, Peter
2010-01-01
Although people often have to learn from environments with scarce and highly selective outcome feedback, the question of how nonfeedback trials are represented in memory and affect later performance has received little attention in models of learning and decision making. In this article, the authors use the generalized context model (Nosofsky,…
A Holistic Approach to the Social Studies.
ERIC Educational Resources Information Center
Davidson, Bonnie
The document explains the need for holistic social studies teaching methods, proposes a holistic model for use in a fourth grade social studies class, and places the model within the general context of social studies education. A holistic method is defined as a way of teaching which is cognitively and affectively integrated with individual…
Fear Control an Danger Control: A Test of the Extended Parallel Process Model (EPPM).
ERIC Educational Resources Information Center
Witte, Kim
1994-01-01
Explores cognitive and emotional mechanisms underlying success and failure of fear appeals in context of AIDS prevention. Offers general support for Extended Parallel Process Model. Suggests that cognitions lead to fear appeal success (attitude, intention, or behavior changes) via danger control processes, whereas the emotion fear leads to fear…
Battling the War for Talent: An Application in a Military Context
ERIC Educational Resources Information Center
Schreurs, Bert H. J.; Syed, Fariya
2011-01-01
Purpose: The purpose of this paper is to introduce a comprehensive new recruitment model that brings together research findings in the different areas of recruitment. This model may serve as a general framework for further recruitment research, and is intended to support Human Resource managers in developing their recruitment policy. To highlight…
The Generalized Problematic Internet Use Scale 2: Validation and test of the model to Facebook use.
Assunção, Raquel S; Matos, Paula Mena
2017-01-01
The main goals of the present study were to test the psychometric properties of a Portuguese version of the GPIUS2 (Generalized Problematic Internet Use Scale 2, Caplan, 2010), and to test whether the cognitive-behavioral model proposed by Caplan (2010) replicated in the context of Facebook use. We used a sample of 761 Portuguese adolescents (53.7% boys, 46.3% girls, mean age = 15.8). Our results showed that the data presented an adequate fit to the original model using confirmatory factor analysis. The scale presented also good internal consistency and adequate construct validity. The cognitive-behavioral model was also applicable to the Facebook context, presenting good fit. Consistently with previous findings we found that preference for online social interaction and the use of Facebook to mood regulation purposes, predicted positively and significantly the deficient self-regulation in Facebook use, which in turn was a significant predictor of the negative outcomes associated with this use. Copyright © 2016 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.
NASA Technical Reports Server (NTRS)
Sheridan, Thomas B.; Raju, G. Jagganath; Buzan, Forrest T.; Yared, Wael; Park, Jong
1989-01-01
Projects recently completed or in progress at MIT Man-Machine Systems Laboratory are summarized. (1) A 2-part impedance network model of a single degree of freedom remote manipulation system is presented in which a human operator at the master port interacts with a task object at the slave port in a remote location is presented. (2) The extension of the predictor concept to include force feedback and dynamic modeling of the manipulator and the environment is addressed. (3) A system was constructed to infer intent from the operator's commands and the teleoperation context, and generalize this information to interpret future commands. (4) A command language system is being designed that is robust, easy to learn, and has more natural man-machine communication. A general telerobot problem selected as an important command language context is finding a collision-free path for a robot.
Cho, Sun-Joo; Goodwin, Amanda P
2016-04-01
When word learning is supported by instruction in experimental studies for adolescents, word knowledge outcomes tend to be collected from complex data structure, such as multiple aspects of word knowledge, multilevel reader data, multilevel item data, longitudinal design, and multiple groups. This study illustrates how generalized linear mixed models can be used to measure and explain word learning for data having such complexity. Results from this application provide deeper understanding of word knowledge than could be attained from simpler models and show that word knowledge is multidimensional and depends on word characteristics and instructional contexts.
Van Hoomissen, Jacqueline; Kunrath, Julie; Dentlinger, Renee; Lafrenz, Andrew; Krause, Mark; Azar, Afaf
2011-09-12
Despite the evidence that exercise improves cognitive behavior in animal models, little is known about these beneficial effects in animal models of pathology. We examined the effects of activity wheel (AW) running on contextual fear conditioning (CFC) and locomotor/exploratory behavior in the olfactory bulbectomy (OBX) model of depression, which is characterized by hyperactivity and changes in cognitive function. Twenty-four hours after the conditioning session of the CFC protocol, the animals were tested for the conditioned response in a conditioned and a novel context to test for the effects of both AW and OBX on CFC, but also the context specificity of the effect. OBX reduced overall AW running behavior throughout the experiment, but increased locomotor/exploratory behavior during CFC, thus demonstrating a context-dependent effect. OBX animals, however, displayed normal CFC behavior that was context-specific, indicating that aversively conditioned memory is preserved in this model. AW running increased freezing behavior during the testing session of the CFC protocol in the control animals but only in the conditioned context, supporting the hypothesis that AW running improves cognitive function in a context-specific manner that does not generalize to an animal model of pathology. Blood corticosterone levels were increased in all animals at the conclusion of the testing sessions, but levels were higher in AW compared to sedentary groups indicating an effect of exercise on neuroendocrine function. Given the differential results of AW running on behavior and neuroendocrine function after OBX, further exploration of the beneficial effects of exercise in animal models of neuropathology is warranted. Copyright © 2011 Elsevier B.V. All rights reserved.
Two models of minimalist, incremental syntactic analysis.
Stabler, Edward P
2013-07-01
Minimalist grammars (MGs) and multiple context-free grammars (MCFGs) are weakly equivalent in the sense that they define the same languages, a large mildly context-sensitive class that properly includes context-free languages. But in addition, for each MG, there is an MCFG which is strongly equivalent in the sense that it defines the same language with isomorphic derivations. However, the structure-building rules of MGs but not MCFGs are defined in a way that generalizes across categories. Consequently, MGs can be exponentially more succinct than their MCFG equivalents, and this difference shows in parsing models too. An incremental, top-down beam parser for MGs is defined here, sound and complete for all MGs, and hence also capable of parsing all MCFG languages. But since the parser represents its grammar transparently, the relative succinctness of MGs is again evident. Although the determinants of MG structure are narrowly and discretely defined, probabilistic influences from a much broader domain can influence even the earliest analytic steps, allowing frequency and context effects to come early and from almost anywhere, as expected in incremental models. Copyright © 2013 Cognitive Science Society, Inc.
NASA Astrophysics Data System (ADS)
Lührs, Nikolas; Jager, Nicolas W.; Challies, Edward; Newig, Jens
2018-02-01
Public participation is potentially useful to improve public environmental decision-making and management processes. In corporate management, the Vroom-Yetton-Jago normative decision-making model has served as a tool to help managers choose appropriate degrees of subordinate participation for effective decision-making given varying decision-making contexts. But does the model recommend participatory mechanisms that would actually benefit environmental management? This study empirically tests the improved Vroom-Jago version of the model in the public environmental decision-making context. To this end, the key variables of the Vroom-Jago model are operationalized and adapted to a public environmental governance context. The model is tested using data from a meta-analysis of 241 published cases of public environmental decision-making, yielding three main sets of findings: (1) The Vroom-Jago model proves limited in its applicability to public environmental governance due to limited variance in its recommendations. We show that adjustments to key model equations make it more likely to produce meaningful recommendations. (2) We find that in most of the studied cases, public environmental managers (implicitly) employ levels of participation close to those that would have been recommended by the model. (3) An ANOVA revealed that such cases, which conform to model recommendations, generally perform better on stakeholder acceptance and environmental standards of outputs than those that diverge from the model. Public environmental management thus benefits from carefully selected and context-sensitive modes of participation.
Lührs, Nikolas; Jager, Nicolas W; Challies, Edward; Newig, Jens
2018-02-01
Public participation is potentially useful to improve public environmental decision-making and management processes. In corporate management, the Vroom-Yetton-Jago normative decision-making model has served as a tool to help managers choose appropriate degrees of subordinate participation for effective decision-making given varying decision-making contexts. But does the model recommend participatory mechanisms that would actually benefit environmental management? This study empirically tests the improved Vroom-Jago version of the model in the public environmental decision-making context. To this end, the key variables of the Vroom-Jago model are operationalized and adapted to a public environmental governance context. The model is tested using data from a meta-analysis of 241 published cases of public environmental decision-making, yielding three main sets of findings: (1) The Vroom-Jago model proves limited in its applicability to public environmental governance due to limited variance in its recommendations. We show that adjustments to key model equations make it more likely to produce meaningful recommendations. (2) We find that in most of the studied cases, public environmental managers (implicitly) employ levels of participation close to those that would have been recommended by the model. (3) An ANOVA revealed that such cases, which conform to model recommendations, generally perform better on stakeholder acceptance and environmental standards of outputs than those that diverge from the model. Public environmental management thus benefits from carefully selected and context-sensitive modes of participation.
Generality and specificity in the effects of musical expertise on perception and cognition.
Carey, Daniel; Rosen, Stuart; Krishnan, Saloni; Pearce, Marcus T; Shepherd, Alex; Aydelott, Jennifer; Dick, Frederic
2015-04-01
Performing musicians invest thousands of hours becoming experts in a range of perceptual, attentional, and cognitive skills. The duration and intensity of musicians' training - far greater than that of most educational or rehabilitation programs - provides a useful model to test the extent to which skills acquired in one particular context (music) generalize to different domains. Here, we asked whether the instrument-specific and more instrument-general skills acquired during professional violinists' and pianists' training would generalize to superior performance on a wide range of analogous (largely non-musical) skills, when compared to closely matched non-musicians. Violinists and pianists outperformed non-musicians on fine-grained auditory psychophysical measures, but surprisingly did not differ from each other, despite the different demands of their instruments. Musician groups did differ on a tuning system perception task: violinists showed clearest biases towards the tuning system specific to their instrument, suggesting that long-term experience leads to selective perceptual benefits given a training-relevant context. However, we found only weak evidence of group differences in non-musical skills, with musicians differing marginally in one measure of sustained auditory attention, but not significantly on auditory scene analysis or multi-modal sequencing measures. Further, regression analyses showed that this sustained auditory attention metric predicted more variance in one auditory psychophysical measure than did musical expertise. Our findings suggest that specific musical expertise may yield distinct perceptual outcomes within contexts close to the area of training. Generalization of expertise to relevant cognitive domains may be less clear, particularly where the task context is non-musical. Copyright © 2014 Elsevier B.V. All rights reserved.
NASA Technical Reports Server (NTRS)
Lin, Shian-Jiann; Chao, Winston C.; Sud, Y. C.; Walker, G. K.
1994-01-01
A generalized form of the second-order van Leer transport scheme is derived. Several constraints to the implied subgrid linear distribution are discussed. A very simple positive-definite scheme can be derived directly from the generalized form. A monotonic version of the scheme is applied to the Goddard Laboratory for Atmospheres (GLA) general circulation model (GCM) for the moisture transport calculations, replacing the original fourth-order center-differencing scheme. Comparisons with the original scheme are made in idealized tests as well as in a summer climate simulation using the full GLA GCM. A distinct advantage of the monotonic transport scheme is its ability to transport sharp gradients without producing spurious oscillations and unphysical negative mixing ratio. Within the context of low-resolution climate simulations, the aforementioned characteristics are demonstrated to be very beneficial in regions where cumulus convection is active. The model-produced precipitation pattern using the new transport scheme is more coherently organized both in time and in space, and correlates better with observations. The side effect of the filling algorithm used in conjunction with the original scheme is also discussed, in the context of idealized tests. The major weakness of the proposed transport scheme with a local monotonic constraint is its substantial implicit diffusion at low resolution. Alternative constraints are discussed to counter this problem.
ERIC Educational Resources Information Center
Andreatta, Marta; Neueder, Dorothea; Glotzbach-Schoon, Evelyn; Mühlberger, Andreas; Pauli, Paul
2017-01-01
Animal studies suggest that time delay between acquisition and retrieval of contextual anxiety increases generalization. Moreover, such generalization is prevented by preexposure to the context (CTX), presumably due to an improved representation of such context. We investigated whether preexposure and time-passing modulate generalization of…
Rodríguez-Abellán, J
1999-02-01
In this article we present a review of the aetiology and treatment of self-injury and self-stimulation in infantile autism and in generalized development disorders. We summarize 20 years of study and investigation in the treatment of these serious behaviour disorders, in a pioneer institution in Spain: the centre for rehabilitation 'El Cau' in Castellon. We describe the most frequent behaviour disorders, with particular reference to self-injury and self-stimulatory behaviour. Models explaining the aetiology and treatment are described in a brief general review of the subject, and we consider explicative models which integrate different treatments (in family and institutional contexts) by means of family therapy, psychoeducational models and social support networks.
American option pricing in Gauss-Markov interest rate models
NASA Astrophysics Data System (ADS)
Galluccio, Stefano
1999-07-01
In the context of Gaussian non-homogeneous interest-rate models, we study the problem of American bond option pricing. In particular, we show how to efficiently compute the exercise boundary in these models in order to decompose the price as a sum of a European option and an American premium. Generalizations to coupon-bearing bonds and jump-diffusion processes for the interest rates are also discussed.
Distributed Cognition (DCOG): Foundations for a Computational Associative Memory Model
2006-08-01
retrieved through context and attention . Instead of looking up an old exemplar in memory, we simulate it by activating the same (or almost the same) set of...association, regardless of current activation. We restrict our attention here to immediate links; although the algorithm can be generalized to include...recognition. A shift in attention may, by creating a new context, trigger the recognition of a concept. A detailed example of the use of attention in
Bernier, Brian E; Lacagnina, Anthony F; Ayoub, Adam; Shue, Francis; Zemelman, Boris V; Krasne, Franklin B; Drew, Michael R
2017-06-28
Dentate gyrus (DG) is widely thought to provide a teaching signal that enables hippocampal encoding of memories, but its role during retrieval is poorly understood. Some data and models suggest that DG plays no role in retrieval; others encourage the opposite conclusion. To resolve this controversy, we evaluated the effects of optogenetic inhibition of dorsal DG during context fear conditioning, recall, generalization, and extinction in male mice. We found that (1) inhibition during training impaired context fear acquisition; (2) inhibition during recall did not impair fear expression in the training context, unless mice had to distinguish between similar feared and neutral contexts; (3) inhibition increased generalization of fear to an unfamiliar context that was similar to a feared one and impaired fear expression in the conditioned context when it was similar to a neutral one; and (4) inhibition impaired fear extinction. These effects, as well as several seemingly contradictory published findings, could be reproduced by BACON (Bayesian Context Fear Algorithm), a physiologically realistic hippocampal model positing that acquisition and retrieval both involve coordinated activity in DG and CA3. Our findings thus suggest that DG contributes to retrieval and extinction, as well as to the initial establishment of context fear. SIGNIFICANCE STATEMENT Despite abundant evidence that the hippocampal dentate gyrus (DG) plays a critical role in memory, it remains unclear whether the role of DG relates to memory acquisition or retrieval. Using contextual fear conditioning and optogenetic inhibition, we show that DG contributes to both of these processes. Using computational simulations, we identify specific mechanisms through which the suppression of DG affects memory performance. Finally, we show that DG contributes to fear extinction learning, a process in which learned fear is attenuated through exposures to a fearful context in the absence of threat. Our data resolve a long-standing question about the role of DG in memory and provide insight into how disorders affecting DG, including aging, stress, and depression, influence cognitive processes. Copyright © 2017 the authors 0270-6474/17/376359-13$15.00/0.
A Cybernetic Approach to the Modeling of Agent Communities
NASA Technical Reports Server (NTRS)
Truszkowski, Walt; Karlin, Jay
2000-01-01
In an earlier paper [1] examples of agent technology in a NASA context were presented. Both groundbased and space-based applications were addressed. This paper continues the discussion of one aspect of the Goddard Space Flight Center's continuing efforts to develop a community of agents that can support both ground-based and space-based systems autonomy. The paper focuses on an approach to agent-community modeling based on the theory of viable systems developed by Stafford Beer. It gives the status of an initial attempt to capture some of the agent-community behaviors in a viable system context. This paper is expository in nature and focuses on a discussion of the modeling of some of the underlying concepts and infrastructure that will serve as the basis of more detailed investigative work into the behavior of agent communities. The paper is organized as follows. First, a general introduction to agent community requirements is presented. Secondly, a brief introduction to the cybernetic concept of a viable system is given. This concept forms the foundation of the modeling approach. Then the concept of an agent community is modeled in the cybernetic context.
Moments of inertia of relativistic magnetized stars
NASA Astrophysics Data System (ADS)
Konno, K.
2001-06-01
We consider principal moments of inertia of axisymmetric, magnetically deformed stars in the context of general relativity. The general expression for the moment of inertia with respect to the symmetric axis is obtained. The numerical estimates are derived for several polytropic stellar models. We find that the values of the principal moments of inertia are modified by a factor of 2 at most from Newtonian estimates.
CMB constraints on β-exponential inflationary models
NASA Astrophysics Data System (ADS)
Santos, M. A.; Benetti, M.; Alcaniz, J. S.; Brito, F. A.; Silva, R.
2018-03-01
We analyze a class of generalized inflationary models proposed in ref. [1], known as β-exponential inflation. We show that this kind of potential can arise in the context of brane cosmology, where the field describing the size of the extra-dimension is interpreted as the inflaton. We discuss the observational viability of this class of model in light of the latest Cosmic Microwave Background (CMB) data from the Planck Collaboration through a Bayesian analysis, and impose tight constraints on the model parameters. We find that the CMB data alone prefer weakly the minimal standard model (ΛCDM) over the β-exponential inflation. However, when current local measurements of the Hubble parameter, H0, are considered, the β-inflation model is moderately preferred over the ΛCDM cosmology, making the study of this class of inflationary models interesting in the context of the current H0 tension.
ERIC Educational Resources Information Center
Nunez, Anne-Marie; Kim, Dongbin
2012-01-01
Latinos' college enrollment rates, particularly in four-year institutions, have not kept pace with their population growth in the United States. Using three-level hierarchical generalized linear modeling, this study analyzes data from the Educational Longitudinal Study (ELS) to examine the influence of high school and state contexts, in addition…
ERIC Educational Resources Information Center
Agustian, Hendra Y.
2016-01-01
The Indonesian model of inclusive society "masyarakat madani" is arguably based on a one-view perspective of Islamic intellectuals. Although it was intended to embrace the whole of society in general, its implications might not reach and permeate the entire society. The unique features of Indonesian society have, to a certain degree,…
How previous experience shapes perception in different sensory modalities
Snyder, Joel S.; Schwiedrzik, Caspar M.; Vitela, A. Davi; Melloni, Lucia
2015-01-01
What has transpired immediately before has a strong influence on how sensory stimuli are processed and perceived. In particular, temporal context can have contrastive effects, repelling perception away from the interpretation of the context stimulus, and attractive effects (TCEs), whereby perception repeats upon successive presentations of the same stimulus. For decades, scientists have documented contrastive and attractive temporal context effects mostly with simple visual stimuli. But both types of effects also occur in other modalities, e.g., audition and touch, and for stimuli of varying complexity, raising the possibility that context effects reflect general computational principles of sensory systems. Neuroimaging shows that contrastive and attractive context effects arise from neural processes in different areas of the cerebral cortex, suggesting two separate operations with distinct functional roles. Bayesian models can provide a functional account of both context effects, whereby prior experience adjusts sensory systems to optimize perception of future stimuli. PMID:26582982
General perceptual contributions to lexical tone normalization.
Huang, Jingyuan; Holt, Lori L
2009-06-01
Within tone languages that use pitch variations to contrast meaning, large variability exists in the pitches produced by different speakers. Context-dependent perception may help to resolve this perceptual challenge. However, whether speakers rely on context in contour tone perception is unclear; previous studies have produced inconsistent results. The present study aimed to provide an unambiguous test of the effect of context on contour lexical tone perception and to explore its underlying mechanisms. In three experiments, Mandarin listeners' perception of Mandarin first and second (high-level and mid-rising) tones was investigated with preceding speech and non-speech contexts. Results indicate that the mean fundamental frequency (f0) of a preceding sentence affects perception of contour lexical tones and the effect is contrastive. Following a sentence with a higher-frequency mean f0, the following syllable is more likely to be perceived as a lower frequency lexical tone and vice versa. Moreover, non-speech precursors modeling the mean spectrum of f0 also elicit this effect, suggesting general perceptual processing rather than articulatory-based or speaker-identity-driven mechanisms.
Stasiewicz, Paul R.; Brandon, Thomas H.; Bradizza, Clara M.
2013-01-01
Pavlovian conditioning models have led to cue-exposure treatments for drug abuse. However, conditioned responding to drug stimuli can return (be renewed) following treatment. Animal research and a previous study of social drinkers indicated that extinction is highly context dependent but that renewal could be reduced by the inclusion of a cue from the extinction context. This study extends this research to a clinical sample. Alcohol-dependent outpatients (N = 143) completed an extinction trial to reduce craving and salivation responses to alcohol cues. They were then randomized to renewal tests in either the same context as extinction, a different context, the different context containing an extinction cue, or the different context with cue plus a manipulation to increase the salience of the cue. Contrary to predictions, the different context did not produce the expected renewal effect. Although the generalization of extinction effects beyond the cue-exposure context is a positive clinical finding, it is inconsistent with basic research findings on the context dependence of extinction. Possible explanations for this inconsistency are discussed. PMID:17563145
Stasiewicz, Paul R; Brandon, Thomas H; Bradizza, Clara M
2007-06-01
Pavlovian conditioning models have led to cue-exposure treatments for drug abuse. However, conditioned responding to drug stimuli can return (be renewed) following treatment. Animal research and a previous study of social drinkers indicated that extinction is highly context dependent but that renewal could be reduced by the inclusion of a cue from the extinction context. This study extends this research to a clinical sample. Alcohol-dependent outpatients (N = 143) completed an extinction trial to reduce craving and salivation responses to alcohol cues. They were then randomized to renewal tests in either the same context as extinction, a different context, the different context containing an extinction cue, or the different context with cue plus a manipulation to increase the salience of the cue. Contrary to predictions, the different context did not produce the expected renewal effect. Although the generalization of extinction effects beyond the cue-exposure context is a positive clinical finding, it is inconsistent with basic research findings on the context dependence of extinction. Possible explanations for this inconsistency are discussed.
Hobbs, Brian P.; Sargent, Daniel J.; Carlin, Bradley P.
2014-01-01
Assessing between-study variability in the context of conventional random-effects meta-analysis is notoriously difficult when incorporating data from only a small number of historical studies. In order to borrow strength, historical and current data are often assumed to be fully homogeneous, but this can have drastic consequences for power and Type I error if the historical information is biased. In this paper, we propose empirical and fully Bayesian modifications of the commensurate prior model (Hobbs et al., 2011) extending Pocock (1976), and evaluate their frequentist and Bayesian properties for incorporating patient-level historical data using general and generalized linear mixed regression models. Our proposed commensurate prior models lead to preposterior admissible estimators that facilitate alternative bias-variance trade-offs than those offered by pre-existing methodologies for incorporating historical data from a small number of historical studies. We also provide a sample analysis of a colon cancer trial comparing time-to-disease progression using a Weibull regression model. PMID:24795786
Adapting chronic care models for diabetes care delivery in low-and-middle-income countries: A review
Ku, Grace Marie V; Kegels, Guy
2015-01-01
A contextual review of models for chronic care was done to develop a context-adapted chronic care model-based service delivery model for chronic conditions including diabetes. The Philippines was used as the setting of a low-to-middle-income country. A context-based narrative review of existing models for chronic care was conducted. A situational analysis was done at the grassroots level, involving the leaders and members of the community, the patients, the local health system and the healthcare providers. A second analysis making use of certain organizational theories was done to explore on improving feasibility and acceptability of organizing care for chronic conditions. The analyses indicated that care for chronic conditions may be introduced, considering the needs of people with diabetes in particular and the community in general as recipients of care, and the issues and factors that may affect the healthcare workers and the health system as providers of this care. The context-adapted chronic care model-based service delivery model was constructed accordingly. Key features are: incorporation of chronic care in the health system’s services; assimilation of chronic care delivery with the other responsibilities of the healthcare workers but with redistribution of certain tasks; and ensuring that the recipients of care experience the whole spectrum of basic chronic care that includes education and promotion in the general population, risk identification, screening, counseling including self-care development, and clinical management of the chronic condition and any co-morbidities, regardless of level of control of the condition. This way, low-to-middle income countries can introduce and improve care for chronic conditions without entailing much additional demand on their limited resources. PMID:25987954
Qualitative model-based diagnosis using possibility theory
NASA Technical Reports Server (NTRS)
Joslyn, Cliff
1994-01-01
The potential for the use of possibility in the qualitative model-based diagnosis of spacecraft systems is described. The first sections of the paper briefly introduce the Model-Based Diagnostic (MBD) approach to spacecraft fault diagnosis; Qualitative Modeling (QM) methodologies; and the concepts of possibilistic modeling in the context of Generalized Information Theory (GIT). Then the necessary conditions for the applicability of possibilistic methods to qualitative MBD, and a number of potential directions for such an application, are described.
2000-04-01
natural systems (King 1993). Population modelers have used certain difference equations, sometimes called the Lotka - Volterra system of equations...environment 28 Step 5 - Simulate the hydraulic and/or water quality field 29 Step 6 - Generate biota response data for decision support 29 Step 7...Quality and Contaminant Modeling Branch (WQCMB), and Mr. R. Andrew Goodwin, contract student, WQCMB, under the general supervision of Dr. Mark S. Dortch
NASA Technical Reports Server (NTRS)
Bertsimas, Dimitris; Odoni, Amedeo
1997-01-01
This document presents a critical review of the principal existing optimization models that have been applied to Air Traffic Flow Management (TFM). Emphasis will be placed on two problems, the Generalized Tactical Flow Management Problem (GTFMP) and the Ground Holding Problem (GHP), as well as on some of their variations. To perform this task, we have carried out an extensive literature review that has covered more than 40 references, most of them very recent. Based on the review of this emerging field our objectives were to: (i) identify the best available models; (ii) describe typical contexts for applications of the models; (iii) provide illustrative model formulations; and (iv) identify the methodologies that can be used to solve the models. We shall begin our presentation below by providing a brief context for the models that we are reviewing. In Section 3 we shall offer a taxonomy and identify four classes of models for review. In Sections 4, 5, and 6 we shall then review, respectively, models for the Single-Airport Ground Holding Problem, the Generalized Tactical FM P and the Multi-Airport Ground Holding Problem (for the definition of these problems see Section 3 below). In each section, we identify the best available models and discuss briefly their computational performance and applications, if any, to date. Section 7 summarizes our conclusions about the state of the art.
NASA Astrophysics Data System (ADS)
Drechsel, Barbara; Carstensen, Claus; Prenzel, Manfred
2011-01-01
This paper focuses interest in science as one of the attitudinal aspects of scientific literacy. Large-scale data from the Programme for International Student Assessment (PISA) 2006 are analysed in order to describe student interest more precisely. So far the analyses have provided a general indicator of interest, aggregated over all contexts and contents in the science test. With its innovative approach PISA embeds interest items within the cognitive test unit and its contents and contexts. The main difference from conventional interest measures is that in most questionnaires, a relatively small number of interest items cover broad fields of contents and contexts. The science units represent a number of systematically differentiated scientific contexts and contents. The units' stimulus texts allow for concrete descriptions of relevant content aspects, applications, and contexts. In the analyses, multidimensional item response models are applied in order to disentangle student interest. The results indicate that multidimensional models fit the data. A two-dimensional model separating interest into two different knowledge of science dimensions described in the PISA science framework is further analysed with respect to gender, performance differences, and country. The findings give a comprehensive description of students' interest in science. The paper deals with methodological problems and describes requirements of the test construction for further assessments. The results are discussed with regard to their significance for science education.
Interference in the classical probabilistic model and its representation in complex Hilbert space
NASA Astrophysics Data System (ADS)
Khrennikov, Andrei Yu.
2005-10-01
The notion of a context (complex of physical conditions, that is to say: specification of the measurement setup) is basic in this paper.We show that the main structures of quantum theory (interference of probabilities, Born's rule, complex probabilistic amplitudes, Hilbert state space, representation of observables by operators) are present already in a latent form in the classical Kolmogorov probability model. However, this model should be considered as a calculus of contextual probabilities. In our approach it is forbidden to consider abstract context independent probabilities: “first context and only then probability”. We construct the representation of the general contextual probabilistic dynamics in the complex Hilbert space. Thus dynamics of the wave function (in particular, Schrödinger's dynamics) can be considered as Hilbert space projections of a realistic dynamics in a “prespace”. The basic condition for representing of the prespace-dynamics is the law of statistical conservation of energy-conservation of probabilities. In general the Hilbert space projection of the “prespace” dynamics can be nonlinear and even irreversible (but it is always unitary). Methods developed in this paper can be applied not only to quantum mechanics, but also to classical statistical mechanics. The main quantum-like structures (e.g., interference of probabilities) might be found in some models of classical statistical mechanics. Quantum-like probabilistic behavior can be demonstrated by biological systems. In particular, it was recently found in some psychological experiments.
Predicting Pilot Error in Nextgen: Pilot Performance Modeling and Validation Efforts
NASA Technical Reports Server (NTRS)
Wickens, Christopher; Sebok, Angelia; Gore, Brian; Hooey, Becky
2012-01-01
We review 25 articles presenting 5 general classes of computational models to predict pilot error. This more targeted review is placed within the context of the broader review of computational models of pilot cognition and performance, including such aspects as models of situation awareness or pilot-automation interaction. Particular emphasis is placed on the degree of validation of such models against empirical pilot data, and the relevance of the modeling and validation efforts to Next Gen technology and procedures.
Variable selection for marginal longitudinal generalized linear models.
Cantoni, Eva; Flemming, Joanna Mills; Ronchetti, Elvezio
2005-06-01
Variable selection is an essential part of any statistical analysis and yet has been somewhat neglected in the context of longitudinal data analysis. In this article, we propose a generalized version of Mallows's C(p) (GC(p)) suitable for use with both parametric and nonparametric models. GC(p) provides an estimate of a measure of model's adequacy for prediction. We examine its performance with popular marginal longitudinal models (fitted using GEE) and contrast results with what is typically done in practice: variable selection based on Wald-type or score-type tests. An application to real data further demonstrates the merits of our approach while at the same time emphasizing some important robust features inherent to GC(p).
A Compositional Relevance Model for Adaptive Information Retrieval
NASA Technical Reports Server (NTRS)
Mathe, Nathalie; Chen, James; Lu, Henry, Jr. (Technical Monitor)
1994-01-01
There is a growing need for rapid and effective access to information in large electronic documentation systems. Access can be facilitated if information relevant in the current problem solving context can be automatically supplied to the user. This includes information relevant to particular user profiles, tasks being performed, and problems being solved. However most of this knowledge on contextual relevance is not found within the contents of documents, and current hypermedia tools do not provide any easy mechanism to let users add this knowledge to their documents. We propose a compositional relevance network to automatically acquire the context in which previous information was found relevant. The model records information on the relevance of references based on user feedback for specific queries and contexts. It also generalizes such information to derive relevant references for similar queries and contexts. This model lets users filter information by context of relevance, build personalized views of documents over time, and share their views with other users. It also applies to any type of multimedia information. Compared to other approaches, it is less costly and doesn't require any a priori statistical computation, nor an extended training period. It is currently being implemented into the Computer Integrated Documentation system which enables integration of various technical documents in a hypertext framework.
Sumter, Takita Felder; Owens, Patrick M
2011-01-01
The need for a revised curriculum within the life sciences has been well-established. One strategy to improve student preparation in the life sciences is to redesign introductory courses like biology, chemistry, and physics so that they better reflect their disciplinary interdependence. We describe a medically relevant, context-based approach to teaching second semester general chemistry that demonstrates the interdisciplinary nature of biology and chemistry. Our innovative method provides a model in which disciplinary barriers are diminished early in the undergraduate science curriculum. The course is divided into three principle educational modules: 1) Fundamentals of General Chemistry, 2) Medical Approaches to Inflammation, and 3) Neuroscience as a connector of chemistry, biology, and psychology. We accurately anticipated that this modified approach to teaching general chemistry would enhance student interest in chemistry and bridge the perceived gaps between biology and chemistry. The course serves as a template for context-based, interdisciplinary teaching that lays the foundation needed to train 21st century scientists. Copyright © 2010 Wiley Periodicals, Inc.
Sumter, Takita Felder; Owens, Patrick M.
2012-01-01
The need for a revised curriculum within the life sciences has been well-established. One strategy to improve student preparation in the life sciences is to redesign introductory courses like biology, chemistry, and physics so that they better reflect their disciplinary interdependence. We describe a medically relevant, context-based approach to teaching second semester general chemistry that demonstrates the interdisciplinary nature of biology and chemistry. Our innovative method provides a model in which disciplinary barriers are diminished early in the undergraduate science curriculum. The course is divided into three principle educational modules: 1) Fundamentals of General Chemistry, 2) Medical Approaches to Inflammation, and 3) Neuroscience as a connector of chemistry, biology, and psychology. We accurately anticipated that this modified approach to teaching general chemistry would enhance student interest in chemistry and bridge the perceived gaps between biology and chemistry. The course serves as a template for context-based, interdisciplinary teaching that lays the foundation needed to train 21st century scientists. PMID:21445902
The mechanism for migration in Poland.
Rykiel, Z
1988-01-01
The author reviews neoclassical theories and models of migration. The mobility theory, which concerns the impact of local labor markets on migration, is discussed in the Polish context. A general model of the regional labor market and a multicausal model are developed to explain the patterns of internal migration. The period of a managed economy (1949-1980) is contrasted with the period since the implementation of a new economic system in 1983.
Cullen, Patrick K; Gilman, T Lee; Winiecki, Patrick; Riccio, David C; Jasnow, Aaron M
2015-10-01
Memories for context become less specific with time resulting in animals generalizing fear from training contexts to novel contexts. Though much attention has been given to the neural structures that underlie the long-term consolidation of a context fear memory, very little is known about the mechanisms responsible for the increase in fear generalization that occurs as the memory ages. Here, we examine the neural pattern of activation underlying the expression of a generalized context fear memory in male C57BL/6J mice. Animals were context fear conditioned and tested for fear in either the training context or a novel context at recent and remote time points. Animals were sacrificed and fluorescent in situ hybridization was performed to assay neural activation. Our results demonstrate activity of the prelimbic, infralimbic, and anterior cingulate (ACC) cortices as well as the ventral hippocampus (vHPC) underlie expression of a generalized fear memory. To verify the involvement of the ACC and vHPC in the expression of a generalized fear memory, animals were context fear conditioned and infused with 4% lidocaine into the ACC, dHPC, or vHPC prior to retrieval to temporarily inactivate these structures. The results demonstrate that activity of the ACC and vHPC is required for the expression of a generalized fear memory, as inactivation of these regions returned the memory to a contextually precise form. Current theories of time-dependent generalization of contextual memories do not predict involvement of the vHPC. Our data suggest a novel role of this region in generalized memory, which should be incorporated into current theories of time-dependent memory generalization. We also show that the dorsal hippocampus plays a prolonged role in contextually precise memories. Our findings suggest a possible interaction between the ACC and vHPC controls the expression of fear generalization. Copyright © 2015 Elsevier Inc. All rights reserved.
Removing but not adding elements of a context affects generalization of instrumental responses.
Bernal-Gamboa, Rodolfo; Nieto, Javier; Uengoer, Metin
2018-01-05
Three experiments with rats investigated whether adding or removing elements of a context affects generalization of instrumental behavior. Each of the experiments used a free operant procedure. In Experiments 1 and 2, rats were trained to press a lever for food in a distinctive context. Then, transfer of lever pressing was tested in a context created either by adding an element to the context of initial acquisition or by removing one of the acquisition context's elements. In Experiment 3, a similar generalization test was conducted after rats received acquisition and extinction within the same context. For Experiments 1 and 2, we observed that removing elements from the acquisition context disrupted acquisition performance, whereas the addition of elements to the context did not. Experiment 3 revealed that removing elements from but not adding elements to the original context improved extinction performance. Our results are consistent with an elemental view of context representation.
ERIC Educational Resources Information Center
Petrin, Robert A.
2011-01-01
As indicated in papers 2 and 3 of this symposium and in published research from Project REAL, there is clear evidence that the SEALS model has a general positive impact on the school context during the early adolescent years. The purpose of this study was to identify key process factors that support gains to academic outcomes in general, but…
Chihab, Jamila; Franke, Hildegard; McNicoll, Ian; Darlison, Matthew W
2017-01-01
We present the first public openEHR archetypes and templates for physiotherapy, and the context of multidisciplinary academic-industry partnership that has enabled their production by a team led by a clinically trained student on the UCL health informatics MSc programme.
Free Fall Misconceptions: Results of a Graph Based Pre-Test of Sophomore Civil Engineering Students
ERIC Educational Resources Information Center
Montecinos, Alicia M.
2014-01-01
A partially unusual behaviour was found among 14 sophomore students of civil engineering who took a pre test for a free fall laboratory session, in the context of a general mechanics course. An analysis contemplating mathematics models and physics models consistency was made. In all cases, the students presented evidence favoring a correct free…
Gagne's Differentiated Model of Giftedness and Talent in Australian Education
ERIC Educational Resources Information Center
Merrotsy, Peter
2017-01-01
It is commonly stated that in Australia Gagne's Differentiated Model of Giftedness and Talent is generally referred to, applied, used, or adopted in most contexts related to the education and support of gifted and talented children and youth. To examine the extent to which this claim is true, an analysis was conducted of policy and related…
A Study on the Models for Corporate Social Responsibility of Small and Medium Enterprises
NASA Astrophysics Data System (ADS)
Ma, Jun
The role of small and medium enterprises (SMEs) in corporate social responsibility (CSR) has attracted increasing attention and interest in recent years. The purpose of this study is to build some relevant models of CSR which are the foundations of empirical study later. The paper begins by an overview of the CSR literature in the context of seven step model for CSR and differences between corporate and small businesses. Noting the general lack of theoretical framework in the literature, the paper then presents relevant theoretical models of CSR that could be useful in conducting further research on CSR and SMEs. The study is qualitative in nature, capitalizing on a comparative research design to highlight differences in CSR orientations between SMEs and MNCs. The research is presented and implications are drawn regarding the peculiar relational attributes of SMEs in the context of CSR generally, and developing countries more specifically, and how this inclination can be further nurtured and leveraged. Further research can seek to highlight how to leverage this natural affinity to CSR among SMEs detected in this study in pursuit of more systematic engagement and more benefits.
Phantom energy mediates a long-range repulsive force.
Amendola, Luca
2004-10-29
Scalar field models with nonstandard kinetic terms have been proposed in the context of k inflation, of Born-Infeld Lagrangians, of phantom energy and, more in general, of low-energy string theory. In general, scalar fields are expected to couple to matter inducing a new interaction. In this Letter I derive the cosmological perturbation equations and the Yukawa correction to gravity for such general models. I find three interesting results: first, when the field behaves as phantom energy (equation of state less than -1), then the coupling strength is negative, inducing a long-range repulsive force; second, the dark-energy field might cluster on astrophysical scales; third, applying the formalism to a Brans-Dicke theory with a general kinetic term it is shown that its Newtonian effects depend on a single parameter that generalizes the Brans-Dicke constant.
Long short-term memory for speaker generalization in supervised speech separation
Chen, Jitong; Wang, DeLiang
2017-01-01
Speech separation can be formulated as learning to estimate a time-frequency mask from acoustic features extracted from noisy speech. For supervised speech separation, generalization to unseen noises and unseen speakers is a critical issue. Although deep neural networks (DNNs) have been successful in noise-independent speech separation, DNNs are limited in modeling a large number of speakers. To improve speaker generalization, a separation model based on long short-term memory (LSTM) is proposed, which naturally accounts for temporal dynamics of speech. Systematic evaluation shows that the proposed model substantially outperforms a DNN-based model on unseen speakers and unseen noises in terms of objective speech intelligibility. Analyzing LSTM internal representations reveals that LSTM captures long-term speech contexts. It is also found that the LSTM model is more advantageous for low-latency speech separation and it, without future frames, performs better than the DNN model with future frames. The proposed model represents an effective approach for speaker- and noise-independent speech separation. PMID:28679261
Aspects géométriques et intégrables des modèles de matrices aléatoires
NASA Astrophysics Data System (ADS)
Marchal, Olivier
2010-12-01
This thesis deals with the geometric and integrable aspects associated with random matrix models. Its purpose is to provide various applications of random matrix theory, from algebraic geometry to partial differential equations of integrable systems. The variety of these applications shows why matrix models are important from a mathematical point of view. First, the thesis will focus on the study of the merging of two intervals of the eigenvalues density near a singular point. Specifically, we will show why this special limit gives universal equations from the Painlevé II hierarchy of integrable systems theory. Then, following the approach of (bi) orthogonal polynomials introduced by Mehta to compute partition functions, we will find Riemann-Hilbert and isomonodromic problems connected to matrix models, making the link with the theory of Jimbo, Miwa and Ueno. In particular, we will describe how the hermitian two-matrix models provide a degenerate case of Jimbo-Miwa-Ueno's theory that we will generalize in this context. Furthermore, the loop equations method, with its central notions of spectral curve and topological expansion, will lead to the symplectic invariants of algebraic geometry recently proposed by Eynard and Orantin. This last point will be generalized to the case of non-hermitian matrix models (arbitrary beta) paving the way to "quantum algebraic geometry" and to the generalization of symplectic invariants to "quantum curves". Finally, this set up will be applied to combinatorics in the context of topological string theory, with the explicit computation of an hermitian random matrix model enumerating the Gromov-Witten invariants of a toric Calabi-Yau threefold.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Seyedhosseini, Mojtaba; Kumar, Ritwik; Jurrus, Elizabeth R.
2011-10-01
Automated neural circuit reconstruction through electron microscopy (EM) images is a challenging problem. In this paper, we present a novel method that exploits multi-scale contextual information together with Radon-like features (RLF) to learn a series of discriminative models. The main idea is to build a framework which is capable of extracting information about cell membranes from a large contextual area of an EM image in a computationally efficient way. Toward this goal, we extract RLF that can be computed efficiently from the input image and generate a scale-space representation of the context images that are obtained at the output ofmore » each discriminative model in the series. Compared to a single-scale model, the use of a multi-scale representation of the context image gives the subsequent classifiers access to a larger contextual area in an effective way. Our strategy is general and independent of the classifier and has the potential to be used in any context based framework. We demonstrate that our method outperforms the state-of-the-art algorithms in detection of neuron membranes in EM images.« less
AI Techniques in a Context-Aware Ubiquitous Environment
NASA Astrophysics Data System (ADS)
Coppola, Paolo; Mea, Vincenzo Della; di Gaspero, Luca; Lomuscio, Raffaella; Mischis, Danny; Mizzaro, Stefano; Nazzi, Elena; Scagnetto, Ivan; Vassena, Luca
Nowadays, the mobile computing paradigm and the widespread diffusion of mobile devices are quickly changing and replacing many common assumptions about software architectures and interaction/communication models. The environment, in particular, or more generally, the so-called user context is claiming a central role in everyday’s use of cellular phones, PDAs, etc. This is due to the huge amount of data “suggested” by the surrounding environment that can be helpful in many common tasks. For instance, the current context can help a search engine to refine the set of results in a useful way, providing the user with a more suitable and exploitable information. Moreover, we can take full advantage of this new data source by “pushing” active contents towards mobile devices, empowering the latter with new features (e.g., applications) that can allow the user to fruitfully interact with the current context. Following this vision, mobile devices become dynamic self-adapting tools, according to the user needs and the possibilities offered by the environment. The present work proposes MoBe: an approach for providing a basic infrastructure for pervasive context-aware applications on mobile devices, in which AI techniques (namely a principled combination of rule-based systems, Bayesian networks and ontologies) are applied to context inference. The aim is to devise a general inferential framework to make easier the development of context-aware applications by integrating the information coming from physical and logical sensors (e.g., position, agenda) and reasoning about this information in order to infer new and more abstract contexts.
MacNab, Ying C
2016-08-01
This paper concerns with multivariate conditional autoregressive models defined by linear combination of independent or correlated underlying spatial processes. Known as linear models of coregionalization, the method offers a systematic and unified approach for formulating multivariate extensions to a broad range of univariate conditional autoregressive models. The resulting multivariate spatial models represent classes of coregionalized multivariate conditional autoregressive models that enable flexible modelling of multivariate spatial interactions, yielding coregionalization models with symmetric or asymmetric cross-covariances of different spatial variation and smoothness. In the context of multivariate disease mapping, for example, they facilitate borrowing strength both over space and cross variables, allowing for more flexible multivariate spatial smoothing. Specifically, we present a broadened coregionalization framework to include order-dependent, order-free, and order-robust multivariate models; a new class of order-free coregionalized multivariate conditional autoregressives is introduced. We tackle computational challenges and present solutions that are integral for Bayesian analysis of these models. We also discuss two ways of computing deviance information criterion for comparison among competing hierarchical models with or without unidentifiable prior parameters. The models and related methodology are developed in the broad context of modelling multivariate data on spatial lattice and illustrated in the context of multivariate disease mapping. The coregionalization framework and related methods also present a general approach for building spatially structured cross-covariance functions for multivariate geostatistics. © The Author(s) 2016.
Discrete Circuits Support Generalized versus Context-Specific Vocal Learning in the Songbird.
Tian, Lucas Y; Brainard, Michael S
2017-12-06
Motor skills depend on the reuse of individual gestures in multiple sequential contexts (e.g., a single phoneme in different words). Yet optimal performance requires that a given gesture be modified appropriately depending on the sequence in which it occurs. To investigate the neural architecture underlying such context-dependent modifications, we studied Bengalese finch song, which, like speech, consists of variable sequences of "syllables." We found that when birds are instructed to modify a syllable in one sequential context, learning generalizes across contexts; however, if unique instruction is provided in different contexts, learning is specific for each context. Using localized inactivation of a cortical-basal ganglia circuit specialized for song, we show that this balance between generalization and specificity reflects a hierarchical organization of neural substrates. Primary motor circuitry encodes a core syllable representation that contributes to generalization, while top-down input from cortical-basal ganglia circuitry biases this representation to enable context-specific learning. Copyright © 2017 Elsevier Inc. All rights reserved.
A social ecological assessment of physical activity among urban adolescents.
Yan, Alice Fang; Voorhees, Carolyn C; Beck, Kenneth H; Wang, Min Qi
2014-05-01
To examine the physical, social and temporal contexts of physical activity, as well as sex variations of the associations among 314 urban adolescents. Three-day physical activity recall measured contextual information of physical activities. Logistic regressions and generalized estimating equation models examined associations among physical activity types and contexts, and sex differences. Active transportation was the most common physical activity. Home/neighborhood and school were the most common physical activity locations. School was the main location for organized physical activity. Boys spent more time on recreational physical activity, regardless of the social context, compared to girls. The average physical activity level was significantly lower for girls than for boys after school. Physical activity promotion interventions need to target physical activity environments and social contexts in a sex-specific manner.
Land-surface influences on weather and climate
NASA Technical Reports Server (NTRS)
Baer, F.; Mintz, Y.
1984-01-01
Land-surface influences on weather and climate are reviewed. The interrelationship of vegetation, evapotranspiration, atmospheric circulation, and climate is discussed. Global precipitation, soil moisture, the seasonal water cycle, heat transfer, and atmospheric temperature are among the parameters considered in the context of a general biosphere model.
Grunwald, Heidi E; Lockwood, Brian; Harris, Philip W; Mennis, Jeremy
2010-09-01
This study examined the effects of neighborhood context on juvenile recidivism to determine if neighborhoods influence the likelihood of reoffending. Although a large body of literature exists regarding the impact of environmental factors on delinquency, very little is known about the effects of these factors on juvenile recidivism. The sample analyzed includes 7,061 delinquent male juveniles committed to community-based programs in Philadelphia, of which 74% are Black, 13% Hispanic, and 11% White. Since sample youths were nested in neighborhoods, a hierarchical generalized linear model was employed to predict recidivism across three general categories of recidivism offenses: drug, violent, and property. Results indicate that predictors vary across the types of offenses and that drug offending differs from property and violent offending. Neighborhood-level factors were found to influence drug offense recidivism, but were not significant predictors of violent offenses, property offenses, or an aggregated recidivism measure, despite contrary expectations. Implications stemming from the finding that neighborhood context influences only juvenile drug recidivism are discussed.
Executable Architecture Research at Old Dominion University
NASA Technical Reports Server (NTRS)
Tolk, Andreas; Shuman, Edwin A.; Garcia, Johnny J.
2011-01-01
Executable Architectures allow the evaluation of system architectures not only regarding their static, but also their dynamic behavior. However, the systems engineering community do not agree on a common formal specification of executable architectures. To close this gap and identify necessary elements of an executable architecture, a modeling language, and a modeling formalism is topic of ongoing PhD research. In addition, systems are generally defined and applied in an operational context to provide capabilities and enable missions. To maximize the benefits of executable architectures, a second PhD effort introduces the idea of creating an executable context in addition to the executable architecture. The results move the validation of architectures from the current information domain into the knowledge domain and improve the reliability of such validation efforts. The paper presents research and results of both doctoral research efforts and puts them into a common context of state-of-the-art of systems engineering methods supporting more agility.
Neisewander, J L; Peartree, N A; Pentkowski, N S
2012-11-01
Social factors are important determinants of drug dependence and relapse. We reviewed pre-clinical literature examining the role of social experiences from early life through the development of drug dependence and relapse, emphasizing two aspects of these experiences: (1) whether the social interaction is appetitive or aversive and (2) whether the social interaction occurs within or outside of the drug-taking context. The models reviewed include neonatal care, isolation, social defeat, chronic subordination, and prosocial interactions. We review results from these models in regard to effects on self-administration and conditioned place preference established with alcohol, psychostimulants, and opiates. We suggest that in general, when the interactions occur outside of the drug-taking context, prosocial interactions are protective against drug abuse-related behaviors, whereas social stressors facilitate these behaviors. By contrast, positive or negative social interactions occurring within the drug-taking context may interact with other risk factors to enhance or inhibit these behaviors. Despite differences in the nature and complexity of human social behavior compared to other species, the evolving animal literature provides useful models for understanding social influences on drug abuse-related behavior that will allow for research on the behavioral and biological mechanisms involved. The models have contributed to understanding social influences on initiation and maintenance of drug use, but more research is needed to understand social influences on drug relapse.
Tsiatis, Anastasios A.; Davidian, Marie; Cao, Weihua
2010-01-01
Summary A routine challenge is that of making inference on parameters in a statistical model of interest from longitudinal data subject to drop out, which are a special case of the more general setting of monotonely coarsened data. Considerable recent attention has focused on doubly robust estimators, which in this context involve positing models for both the missingness (more generally, coarsening) mechanism and aspects of the distribution of the full data, that have the appealing property of yielding consistent inferences if only one of these models is correctly specified. Doubly robust estimators have been criticized for potentially disastrous performance when both of these models are even only mildly misspecified. We propose a doubly robust estimator applicable in general monotone coarsening problems that achieves comparable or improved performance relative to existing doubly robust methods, which we demonstrate via simulation studies and by application to data from an AIDS clinical trial. PMID:20731640
The Semantic Environment: Heuristics for a Cross-Context Human-Information Interaction Model
NASA Astrophysics Data System (ADS)
Resmini, Andrea; Rosati, Luca
This chapter introduces a multidisciplinary holistic approach for the general design of successful bridge experiences as a cross-context human-information interaction model. Nowadays it is common to interact through a number of different domains in order to communicate successfully, complete a task, or elicit a desired response: Users visit a reseller’s web site to find a specific item, book it, then drive to the closest store to complete their purchase. As such, one of the crucial challenges user experience design will face in the near future is how to structure and provide bridge experiences seamlessly spanning multiple communication channels or media formats for a specific purpose.
Theory of Self- vs. Externally-Regulated LearningTM: Fundamentals, Evidence, and Applicability.
de la Fuente-Arias, Jesús
2017-01-01
The Theory of Self- vs. Externally-Regulated Learning TM has integrated the variables of SRL theory, the DEDEPRO model, and the 3P model. This new Theory has proposed: (a) in general, the importance of the cyclical model of individual self-regulation (SR) and of external regulation stemming from the context (ER), as two different and complementary variables, both in combination and in interaction; (b) specifically, in the teaching-learning context, the relevance of different types of combinations between levels of self-regulation (SR) and of external regulation (ER) in the prediction of self-regulated learning (SRL), and of cognitive-emotional achievement. This review analyzes the assumptions, conceptual elements, empirical evidence, benefits and limitations of SRL vs. ERL Theory . Finally, professional fields of application and future lines of research are suggested.
NASA Astrophysics Data System (ADS)
Nemoto, Takahiro; Jack, Robert L.; Lecomte, Vivien
2017-03-01
We analyze large deviations of the time-averaged activity in the one-dimensional Fredrickson-Andersen model, both numerically and analytically. The model exhibits a dynamical phase transition, which appears as a singularity in the large deviation function. We analyze the finite-size scaling of this phase transition numerically, by generalizing an existing cloning algorithm to include a multicanonical feedback control: this significantly improves the computational efficiency. Motivated by these numerical results, we formulate an effective theory for the model in the vicinity of the phase transition, which accounts quantitatively for the observed behavior. We discuss potential applications of the numerical method and the effective theory in a range of more general contexts.
Learning Setting-Generalized Activity Models for Smart Spaces
Cook, Diane J.
2011-01-01
The data mining and pervasive computing technologies found in smart homes offer unprecedented opportunities for providing context-aware services, including health monitoring and assistance to individuals experiencing difficulties living independently at home. In order to provide these services, smart environment algorithms need to recognize and track activities that people normally perform as part of their daily routines. However, activity recognition has typically involved gathering and labeling large amounts of data in each setting to learn a model for activities in that setting. We hypothesize that generalized models can be learned for common activities that span multiple environment settings and resident types. We describe our approach to learning these models and demonstrate the approach using eleven CASAS datasets collected in seven environments. PMID:21461133
Translational Animal Models of Atopic Dermatitis for Preclinical Studies
Martel, Britta C.; Lovato, Paola; Bäumer, Wolfgang; Olivry, Thierry
2017-01-01
There is a medical need to develop new treatments for patients suffering from atopic dermatitis (AD). To improve the discovery and testing of novel treatments, relevant animal models for AD are needed. Generally, these animal models mimic different aspects of the pathophysiology of human AD, such as skin barrier defects and Th2 immune bias with additional Th1 and Th22, and in some populations Th17, activation. However, the pathomechanistic characterization and pharmacological validation of these animal models are generally incomplete. In this paper, we review animal models of AD in the context of preclinical use and their possible translation to the human disease. Most of these models use mice, but we will also critically evaluate dog models of AD, as increasing information on disease mechanism show their likely relevance for the human disease. PMID:28955179
Assessing the Spatial Scale Effect of Anthropogenic Factors on Species Distribution
Mangiacotti, Marco; Scali, Stefano; Sacchi, Roberto; Bassu, Lara; Nulchis, Valeria; Corti, Claudia
2013-01-01
Patch context is a way to describe the effect that the surroundings exert on a landscape patch. Despite anthropogenic context alteration may affect species distributions by reducing the accessibility to suitable patches, species distribution modelling have rarely accounted for its effects explicitly. We propose a general framework to statistically detect the occurrence and the extent of such a factor, by combining presence-only data, spatial distribution models and information-theoretic model selection procedures. After having established the spatial resolution of the analysis on the basis of the species characteristics, a measure of anthropogenic alteration that can be quantified at increasing distance from each patch has to be defined. Then the distribution of the species is modelled under competing hypotheses: H0, assumes that the distribution is uninfluenced by the anthropogenic variables; H1, assumes the effect of alteration at the species scale (resolution); and H2, H3 … Hn add the effect of context alteration at increasing radii. Models are compared using the Akaike Information Criterion to establish the best hypothesis, and consequently the occurrence (if any) and the spatial scale of the anthropogenic effect. As a study case we analysed the distribution data of two insular lizards (one endemic and one naturalised) using four alternative hypotheses: no alteration (H0), alteration at the species scale (H1), alteration at two context scales (H2 and H3). H2 and H3 performed better than H0 and H1, highlighting the importance of context alteration. H2 performed better than H3, setting the spatial scale of the context at 1 km. The two species respond differently to context alteration, the introduced lizard being more tolerant than the endemic one. The proposed approach supplies reliably and interpretable results, uses easily available data on species distribution, and allows the assessing of the spatial scale at which human disturbance produces the heaviest effects. PMID:23825669
Thermomechanical Characterization and Modeling of Superelastic Shape Memory Alloy Beams and Frames
NASA Astrophysics Data System (ADS)
Watkins, Ryan
Of existing applications, the majority of shape memory alloy (SMA) devices consist of beam (orthodontic wire, eye glasses frames, catheter guide wires) and framed structures (cardiovascular stents, vena cava filters). Although uniaxial tension data is often sufficient to model basic beam behavior (which has been the main focus of the research community), the tension-compression asymmetry and complex phase transformation behavior of SMAs suggests more information is necessary to properly model higher complexity states of loading. In this work, SMA beams are experimentally characterized under general loading conditions (including tension, compression, pure bending, and buckling); furthermore, a model is developed with respect to general beam deformation based on the relevant phenomena observed in the experimental characterization. Stress induced phase transformation within superelastic SMA beams is shown to depend on not only the loading mode, but also kinematic constraints imposed by beam geometry (such as beam cross-section and length). In the cases of tension and pure bending, the structural behavior is unstable and corresponds to phase transformation localization and propagation. This unstable behavior is the result of a local level up--down--up stress/strain response in tension, which is measured here using a novel composite-based experimental technique. In addition to unstable phase transformation, intriguing post-buckling straightening is observed in short SMA columns during monotonic loading (termed unbuckling here). Based on this phenomenological understanding of SMA beam behavior, a trilinear based material law is developed in the context of a Shanley column model and is found to capture many of the relevant features of column buckling, including the experimentally observed unbuckling behavior. Due to the success of this model, it is generalized within the context of beam theory and, in conjunction with Bloch wave stability analysis, is used to model and design SMA honeycombs.
NASA Astrophysics Data System (ADS)
Pecháček, T.; Goosmann, R. W.; Karas, V.; Czerny, B.; Dovčiak, M.
2013-08-01
Context. We study some general properties of accretion disc variability in the context of stationary random processes. In particular, we are interested in mathematical constraints that can be imposed on the functional form of the Fourier power-spectrum density (PSD) that exhibits a multiply broken shape and several local maxima. Aims: We develop a methodology for determining the regions of the model parameter space that can in principle reproduce a PSD shape with a given number and position of local peaks and breaks of the PSD slope. Given the vast space of possible parameters, it is an important requirement that the method is fast in estimating the PSD shape for a given parameter set of the model. Methods: We generated and discuss the theoretical PSD profiles of a shot-noise-type random process with exponentially decaying flares. Then we determined conditions under which one, two, or more breaks or local maxima occur in the PSD. We calculated positions of these features and determined the changing slope of the model PSD. Furthermore, we considered the influence of the modulation by the orbital motion for a variability pattern assumed to result from an orbiting-spot model. Results: We suggest that our general methodology can be useful for describing non-monotonic PSD profiles (such as the trend seen, on different scales, in exemplary cases of the high-mass X-ray binary Cygnus X-1 and the narrow-line Seyfert galaxy Ark 564). We adopt a model where these power spectra are reproduced as a superposition of several Lorentzians with varying amplitudes in the X-ray-band light curve. Our general approach can help in constraining the model parameters and in determining which parts of the parameter space are accessible under various circumstances.
Affect in the "Communicative" Classroom: A Model.
ERIC Educational Resources Information Center
Acton, William
Recent research on affective variables and classroom second language learning suggests that: (1) affective variables are context-sensitive in at least two ways; (2) attitudes are contagious, and the general attitude of students can be influenced from various directions; (3) research in pragmatics, discourse analysis, and communicative functions…
ERIC Educational Resources Information Center
Sherritt, Caroline A.
Defining literacy is a compelling challenge to educators. They generally use three models: instrumental, functional, and empowerment. The latter two approaches, which were increasingly evident in the 1980s, identify literacy by the social functions required in a given context or by the qualities needed for illiterate people to take control of…
78 FR 58160 - Certification Process for State Capital Counsel System
Federal Register 2010, 2011, 2012, 2013, 2014
2013-09-23
... make such independent assessments in the context of making certification decisions under chapter 154... decisions concerning the objectives of representation,'' ABA Model Rule 1.2(a), making it difficult to... certification procedures. The Attorney General determined that chapter 154 gave him greater discretion in making...
The Friendly Giant Meets the Fantastic Hulk: Violence in Childrens' TV
ERIC Educational Resources Information Center
Sobol, Ken
1976-01-01
Notes that one of the greatest dangers for Canadian television in general is to take American psychological reality as a model for Canadian reality, and to try to build programs around it, instead of around programs that are indigenous to Canadian context. (Author/AM)
Neueder, Dorothea; Glotzbach-Schoon, Evelyn; Mühlberger, Andreas
2017-01-01
Animal studies suggest that time delay between acquisition and retrieval of contextual anxiety increases generalization. Moreover, such generalization is prevented by preexposure to the context (CTX), presumably due to an improved representation of such context. We investigated whether preexposure and time-passing modulate generalization of contextual anxiety, in humans. On Day 1, 42 participants (preexposure group) explored two virtual offices, while 41 participants (no-preexposure group) explored a virtual stadium. On Day 2 (24 h later), all participants learned to associate one office (CTX+) with unpredictable unconditioned stimuli (USs), and another office (CTX−) with safety. On Day 3, either 24 h (recent test) or 2 wk (remote test) later, participants revisited CTX− and CTX+ without USs, as well as a generalization context (G-CTX). Results revealed successfully conditioned anxiety and anxiety generalization for ratings (G-CTX was as aversive as CTX+ was), while safety generalization was found for startle responses (G-CTX elicited startle attenuation as CTX− did). Time between learning and testing enhanced generalization as reflected by comparable startle responses to all three offices in the remote test. Contextual preexposure facilitated extinction of explicit conditioned anxiety assessed with ratings. These results suggest that memory trace of a context degrades with passage of time in humans like in animals and, consequently, anxiety generalization enhances. After context preexposure, high cognitive processes seem to be crucially involved in facilitating extinction (or safety) learning. PMID:27980075
Altered neural encoding of prediction errors in assault-related posttraumatic stress disorder.
Ross, Marisa C; Lenow, Jennifer K; Kilts, Clinton D; Cisler, Josh M
2018-05-12
Posttraumatic stress disorder (PTSD) is widely associated with deficits in extinguishing learned fear responses, which relies on mechanisms of reinforcement learning (e.g., updating expectations based on prediction errors). However, the degree to which PTSD is associated with impairments in general reinforcement learning (i.e., outside of the context of fear stimuli) remains poorly understood. Here, we investigate brain and behavioral differences in general reinforcement learning between adult women with and without a current diagnosis of PTSD. 29 adult females (15 PTSD with exposure to assaultive violence, 14 controls) underwent a neutral reinforcement-learning task (i.e., two arm bandit task) during fMRI. We modeled participant behavior using different adaptations of the Rescorla-Wagner (RW) model and used Independent Component Analysis to identify timecourses for large-scale a priori brain networks. We found that an anticorrelated and risk sensitive RW model best fit participant behavior, with no differences in computational parameters between groups. Women in the PTSD group demonstrated significantly less neural encoding of prediction errors in both a ventral striatum/mPFC and anterior insula network compared to healthy controls. Weakened encoding of prediction errors in the ventral striatum/mPFC and anterior insula during a general reinforcement learning task, outside of the context of fear stimuli, suggests the possibility of a broader conceptualization of learning differences in PTSD than currently proposed in current neurocircuitry models of PTSD. Copyright © 2018 Elsevier Ltd. All rights reserved.
Alternative probability theories for cognitive psychology.
Narens, Louis
2014-01-01
Various proposals for generalizing event spaces for probability functions have been put forth in the mathematical, scientific, and philosophic literatures. In cognitive psychology such generalizations are used for explaining puzzling results in decision theory and for modeling the influence of context effects. This commentary discusses proposals for generalizing probability theory to event spaces that are not necessarily boolean algebras. Two prominent examples are quantum probability theory, which is based on the set of closed subspaces of a Hilbert space, and topological probability theory, which is based on the set of open sets of a topology. Both have been applied to a variety of cognitive situations. This commentary focuses on how event space properties can influence probability concepts and impact cognitive modeling. Copyright © 2013 Cognitive Science Society, Inc.
From statistical proofs of the Kochen-Specker theorem to noise-robust noncontextuality inequalities
NASA Astrophysics Data System (ADS)
Kunjwal, Ravi; Spekkens, Robert W.
2018-05-01
The Kochen-Specker theorem rules out models of quantum theory wherein projective measurements are assigned outcomes deterministically and independently of context. This notion of noncontextuality is not applicable to experimental measurements because these are never free of noise and thus never truly projective. For nonprojective measurements, therefore, one must drop the requirement that an outcome be assigned deterministically in the model and merely require that it be assigned a distribution over outcomes in a manner that is context-independent. By demanding context independence in the representation of preparations as well, one obtains a generalized principle of noncontextuality that also supports a quantum no-go theorem. Several recent works have shown how to derive inequalities on experimental data which, if violated, demonstrate the impossibility of finding a generalized-noncontextual model of this data. That is, these inequalities do not presume quantum theory and, in particular, they make sense without requiring an operational analog of the quantum notion of projectiveness. We here describe a technique for deriving such inequalities starting from arbitrary proofs of the Kochen-Specker theorem. It extends significantly previous techniques that worked only for logical proofs, which are based on sets of projective measurements that fail to admit of any deterministic noncontextual assignment, to the case of statistical proofs, which are based on sets of projective measurements that d o admit of some deterministic noncontextual assignments, but not enough to explain the quantum statistics.
Neural correlates of context-independent and context-dependent self-knowledge.
Martial, Charlotte; Stawarczyk, David; D'Argembeau, Arnaud
2018-05-25
The self-concept consists of both a general (context-independent) self-representation and a set of context-dependent selves that represent personal attributes in particular contexts (e.g., as a student, as a daughter). To date, however, neuroimaging studies have focused on general self-representations, such that little is known about the neural correlates of context-dependent self-knowledge. The present study aimed at investigating this issue by examining the neural correlates of both kinds of self-knowledge. Participants judged the extent to which trait adjectives described their own personality or the personality of a close friend, either in a specific context (i.e., as a student) or in general. We found that both kinds of self-judgments were associated with common activation in the medial prefrontal cortex (MPFC), as compared to judgments about others. Interestingly, however, there were also notable differences between self-judgments, with context-independent judgments being associated with higher activity in the MPFC, whereas context-dependent judgments were associated with greater activation in posterior brain regions (i.e., the posterior cingulate/retrosplenial cortex). These findings show that context-independent and context-dependent self-referential judgments recruit both common and distinct brain regions, thereby supporting the view that the self-concept is a multi-dimensional knowledge structure that includes a general self-representation and a set of context-specific selves. Copyright © 2018 Elsevier Inc. All rights reserved.
An evaluation of generalization of mands during functional communication training.
Falcomata, Terry S; Wacker, David P; Ringdahl, Joel E; Vinquist, Kelly; Dutt, Anuradha
2013-01-01
The primary purpose of this study was to evaluate the generalization of mands during functional communication training (FCT) and sign language training across functional contexts (i.e., positive reinforcement, negative reinforcement). A secondary purpose was to evaluate a training procedure based on stimulus control to teach manual signs. During the treatment evaluation, we implemented sign language training in 1 functional context (e.g., positive reinforcement by attention) while continuing the functional analysis conditions in 2 other contexts (e.g., positive reinforcement by tangible item; negative reinforcement by escape). During the generalization evaluation, we tested for the generalization of trained mands across functional contexts (i.e., positive reinforcement; negative reinforcement) by implementing extinction in the 2 nontarget contexts. The results suggested that the stimulus control training procedure effectively taught manual signs and treated destructive behavior. Specific patterns of generalization of trained mands and destructive behavior also were observed. © Society for the Experimental Analysis of Behavior.
Model-independent constraints on dark matter annihilation in dwarf spheroidal galaxies
NASA Astrophysics Data System (ADS)
Boddy, Kimberly K.; Kumar, Jason; Marfatia, Danny; Sandick, Pearl
2018-05-01
We present a general, model-independent formalism for determining bounds on the production of photons in dwarf spheroidal galaxies via dark matter annihilation, applicable to any set of assumptions about dark matter particle physics or astrophysics. As an illustration, we analyze gamma-ray data from the Fermi Large Area Telescope to constrain a variety of nonstandard dark matter models, several of which have not previously been studied in the context of dwarf galaxy searches.
Strategy Generalization across Orientation Tasks: Testing a Computational Cognitive Model
2008-07-01
arranged in groups ( clusters ). The space, itself, was divided into four quadrants, which had 1, 2, 3, and 4 objects, respectively. The arrangement of... clusters , of objects play an important role in the model’s performance, by providing some context for narrowing the search for the target to a portion of the...model uses a hierarchical approach to accomplish this. First, the model identifies a group or cluster of objects that contains the target. The number of
NASA Astrophysics Data System (ADS)
Simonton, Dean Keith
2010-06-01
Campbell (1960) proposed that creative thought should be conceived as a blind-variation and selective-retention process (BVSR). This article reviews the developments that have taken place in the half century that has elapsed since his proposal, with special focus on the use of combinatorial models as formal representations of the general theory. After defining the key concepts of blind variants, creative thought, and disciplinary context, the combinatorial models are specified in terms of individual domain samples, variable field size, ideational combination, and disciplinary communication. Empirical implications are then derived with respect to individual, domain, and field systems. These abstract combinatorial models are next provided substantive reinforcement with respect to findings concerning the cognitive processes, personality traits, developmental factors, and social contexts that contribute to creativity. The review concludes with some suggestions regarding future efforts to explicate creativity according to BVSR theory.
A Common Mechanism Underlying Food Choice and Social Decisions.
Krajbich, Ian; Hare, Todd; Bartling, Björn; Morishima, Yosuke; Fehr, Ernst
2015-10-01
People make numerous decisions every day including perceptual decisions such as walking through a crowd, decisions over primary rewards such as what to eat, and social decisions that require balancing own and others' benefits. The unifying principles behind choices in various domains are, however, still not well understood. Mathematical models that describe choice behavior in specific contexts have provided important insights into the computations that may underlie decision making in the brain. However, a critical and largely unanswered question is whether these models generalize from one choice context to another. Here we show that a model adapted from the perceptual decision-making domain and estimated on choices over food rewards accurately predicts choices and reaction times in four independent sets of subjects making social decisions. The robustness of the model across domains provides behavioral evidence for a common decision-making process in perceptual, primary reward, and social decision making.
A Common Mechanism Underlying Food Choice and Social Decisions
Krajbich, Ian; Hare, Todd; Bartling, Björn; Morishima, Yosuke; Fehr, Ernst
2015-01-01
People make numerous decisions every day including perceptual decisions such as walking through a crowd, decisions over primary rewards such as what to eat, and social decisions that require balancing own and others’ benefits. The unifying principles behind choices in various domains are, however, still not well understood. Mathematical models that describe choice behavior in specific contexts have provided important insights into the computations that may underlie decision making in the brain. However, a critical and largely unanswered question is whether these models generalize from one choice context to another. Here we show that a model adapted from the perceptual decision-making domain and estimated on choices over food rewards accurately predicts choices and reaction times in four independent sets of subjects making social decisions. The robustness of the model across domains provides behavioral evidence for a common decision-making process in perceptual, primary reward, and social decision making. PMID:26460812
2013-01-01
Background Organizational context is recognized as an important influence on the successful implementation of research by healthcare professionals. However, there is relatively little empirical evidence to support this widely held view. Methods The objective of this study was to identify dimensions of organizational context and individual (nurse) characteristics that influence pediatric nurses’ self-reported use of research. Data on research use, individual, and contextual variables were collected from registered nurses (N = 735) working on 32 medical, surgical and critical care units in eight Canadian pediatric hospitals using an online survey. We used Generalized Estimating Equation modeling to account for the correlated structure of the data and to identify which contextual dimensions and individual characteristics predict two kinds of self-reported research use: instrumental (direct) and conceptual (indirect). Results Significant predictors of instrumental research use included: at the individual level; belief suspension-implement, research use in the past, and at the hospital unit (context) level; culture, and the proportion on nurses possessing a baccalaureate degree or higher. Significant predictors of conceptual research use included: at the individual nurse level; belief suspension-implement, problem solving ability, use of research in the past, and at the hospital unit (context) level; leadership, culture, evaluation, formal interactions, informal interactions, organizational slack-space, and unit specialty. Conclusions Hospitals, by focusing attention on modifiable elements of unit context may positively influence nurses’ reported use of research. This influence of context may extend to the adoption of best practices in general and other innovative or quality interventions. PMID:24034149
Kohlmayer, Florian; Prasser, Fabian; Kuhn, Klaus A
2015-12-01
With the ARX data anonymization tool structured biomedical data can be de-identified using syntactic privacy models, such as k-anonymity. Data is transformed with two methods: (a) generalization of attribute values, followed by (b) suppression of data records. The former method results in data that is well suited for analyses by epidemiologists, while the latter method significantly reduces loss of information. Our tool uses an optimal anonymization algorithm that maximizes output utility according to a given measure. To achieve scalability, existing optimal anonymization algorithms exclude parts of the search space by predicting the outcome of data transformations regarding privacy and utility without explicitly applying them to the input dataset. These optimizations cannot be used if data is transformed with generalization and suppression. As optimal data utility and scalability are important for anonymizing biomedical data, we had to develop a novel method. In this article, we first confirm experimentally that combining generalization with suppression significantly increases data utility. Next, we proof that, within this coding model, the outcome of data transformations regarding privacy and utility cannot be predicted. As a consequence, existing algorithms fail to deliver optimal data utility. We confirm this finding experimentally. The limitation of previous work can be overcome at the cost of increased computational complexity. However, scalability is important for anonymizing data with user feedback. Consequently, we identify properties of datasets that may be predicted in our context and propose a novel and efficient algorithm. Finally, we evaluate our solution with multiple datasets and privacy models. This work presents the first thorough investigation of which properties of datasets can be predicted when data is anonymized with generalization and suppression. Our novel approach adopts existing optimization strategies to our context and combines different search methods. The experiments show that our method is able to efficiently solve a broad spectrum of anonymization problems. Our work shows that implementing syntactic privacy models is challenging and that existing algorithms are not well suited for anonymizing data with transformation models which are more complex than generalization alone. As such models have been recommended for use in the biomedical domain, our results are of general relevance for de-identifying structured biomedical data. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.
Interaction Analysis in MANOVA.
ERIC Educational Resources Information Center
Betz, M. Austin
Simultaneous test procedures (STPS for short) in the context of the unrestricted full rank general linear multivariate model for population cell means are introduced and utilized to analyze interactions in factorial designs. By appropriate choice of an implying hypothesis, it is shown how to test overall main effects, interactions, simple main,…
Business/School Partnerships: A Path to Effective School Restructuring.
ERIC Educational Resources Information Center
Rigden, Diana W.
General guidelines for companies interested in supporting school-based restructuring are offered in this booklet. Following a brief review of the nature and types of partnerships, chapter 2 examines partnerships within the context of school restructuring outcomes and identifies some essential components for developing a reform-model partnership.…
Beyond Modularisation: The Need of a Socio-Neuro-Constructionist Model of Autism
ERIC Educational Resources Information Center
López, Beatriz
2015-01-01
Autism is a "developmental" disorder defined by "social and communication" impairments. Current theoretical approaches and research studies however conceptualise autism as both static and independent from the social context in which it develops. Two lines of research stand out from this general trend. First, research from the…
Query Expansion and Query Translation as Logical Inference.
ERIC Educational Resources Information Center
Nie, Jian-Yun
2003-01-01
Examines query expansion during query translation in cross language information retrieval and develops a general framework for inferential information retrieval in two particular contexts: using fuzzy logic and probability theory. Obtains evaluation formulas that are shown to strongly correspond to those used in other information retrieval models.…
Group Dynamic Processes in Email Groups
ERIC Educational Resources Information Center
Alpay, Esat
2005-01-01
Discussion is given on the relevance of group dynamic processes in promoting decision-making in email discussion groups. General theories on social facilitation and social loafing are considered in the context of email groups, as well as the applicability of psychodynamic and interaction-based models. It is argued that such theories may indeed…
The Importance of Culture for Developmental Science
ERIC Educational Resources Information Center
Keller, Heidi
2012-01-01
In this essay, it is argued that a general understanding of human development needs a unified framework based on evolutionary theorizing and cross-cultural and cultural anthropological approaches. An eco-social model of development has been proposed that defines cultural milieus as adaptations to specific socio-demographic contexts. Ontogenetic…
Commentary on "Idiographic Filters for Psychological Constructs"
ERIC Educational Resources Information Center
Molenaar, Peter C. M.
2009-01-01
Definitions of measurement equivalence in terms of invariance can be specified at a very general formal level. Presently, however, only the operationalization of measurement equivalence in terms of factor models is at stake. In this article, the author discusses the proposed alternative definition in terms of idiographic filters in the context of…
ERIC Educational Resources Information Center
O'Meara, KerryAnn; Jaeger, Audrey J.
2016-01-01
This article considers the historical and current national context for integrating community engagement into graduate education. While it might be argued that most graduate education contributes generally to society by advancing knowledge, we are referring here to community engagement that involves some reciprocal interaction between graduate…
Symmetry remnants in the face of competing interactions in nuclei
DOE Office of Scientific and Technical Information (OSTI.GOV)
Leviatan, A., E-mail: ami@phys.huji.ac.il; Macek, M., E-mail: michal.macek@yale.edu
2015-10-15
Detailed description of nuclei necessitates model Hamiltonians which break most dynamical symmetries. Nevertheless, generalized notions of partial and quasi dynamical symmetries may still be applicable to selected subsets of states, amidst a complicated environment of other states. We examine such scenarios in the context of nuclear shape-phase transitions.
Creation operator for spinons in one dimension
DOE Office of Scientific and Technical Information (OSTI.GOV)
Talstra, J.C.; Strong, S.P.
1997-09-01
We propose a definition for a creation operator for the spinon, the fractional statistics elementary excitation of the Haldane-Shastry model, and give numerical and analytical evidence that our operator creates a single spinon with nearly unit amplitude in the Heisenberg model with inverse squared exchange. We then discuss how the operator is useful in more general contexts such as studying the underlying spinons of other spin-chain models, like the XXX and XY model, and of the one-dimensional Hubbard model. {copyright} {ital 1997} {ital The American Physical Society}
DOE Office of Scientific and Technical Information (OSTI.GOV)
Aad G.; Abbott B.; Abdallah J.
2012-04-20
A search for diphoton events with large missing transverse momentum has been performed using 1.07 fb{sup -1} of proton-proton collision data at {radical}s = 7 TeV recorded with the ATLAS detector. No excess of events was observed above the Standard Model prediction and 95% Confidence Level (CL) upper limits are set on the production cross section for new physics. The limits depend on each model parameter space and vary as follows: {sigma} < (22-129) fb in the context of a generalized model of gauge-mediated supersymmetry breaking (GGM) with a bino-like lightest neutralino, {sigma} < (27-91) fb in the context ofmore » a minimal model of gauge-mediated supersymmetry breaking (SPS8), and {sigma} < (15-27) fb in the context of a specific model with one universal extra dimension (UED). A 95% CL lower limit of 805 GeV, for bino masses above 50 GeV, is set on the GGM gluino mass. Lower limits of 145 TeV and 1.23 TeV are set on the SPS8 breaking scale {Lambda} and on the UED compactification scale 1/R, respectively. These limits provide the most stringent tests of these models to date.« less
Mishra, Sharmistha; Boily, Marie-Claude; Schwartz, Sheree; Beyrer, Chris; Blanchard, James F; Moses, Stephen; Castor, Delivette; Phaswana-Mafuya, Nancy; Vickerman, Peter; Drame, Fatou; Alary, Michel; Baral, Stefan D
2016-08-01
In the context of generalized human immunodeficiency virus (HIV) epidemics, there has been limited recent investment in HIV surveillance and prevention programming for key populations including female sex workers. Often implicit in the decision to limit investment in these epidemic settings are assumptions including that commercial sex is not significant to the sustained transmission of HIV, and HIV interventions designed to reach "all segments of society" will reach female sex workers and clients. Emerging empiric and model-based evidence is challenging these assumptions. This article highlights the frameworks and estimates used to characterize the role of sex work in HIV epidemics as well as the relevant empiric data landscape on sex work in generalized HIV epidemics and their strengths and limitations. Traditional approaches to estimate the contribution of sex work to HIV epidemics do not capture the potential for upstream and downstream sexual and vertical HIV transmission. Emerging approaches such as the transmission population attributable fraction from dynamic mathematical models can address this gap. To move forward, the HIV scientific community must begin by replacing assumptions about the epidemiology of generalized HIV epidemics with data and more appropriate methods of estimating the contribution of unprotected sex in the context of sex work. Copyright © 2016 Elsevier Inc. All rights reserved.
Mental models as indicators of scientific thinking
NASA Astrophysics Data System (ADS)
Derosa, Donald Anthony
One goal of science education reform is student attainment of scientific literacy. Therefore, it is imperative for science educators to identify its salient elements. A dimension of scientific literacy that warrants careful consideration is scientific thinking and effective ways to foster scientific thinking among students. This study examined the use of mental models as evidence of scientific thinking in the context of two instructional approaches, transmissional and constructivist. Types of mental models, frequency of explanative information, and scores on problem solving transfer questions were measured and compared among subjects in each instructional context. Methods. Subjects consisted of sophomore biology students enrolled in general biology courses at three public high schools. The Group Assessment of Logical Thinking instrument was used to identify two equivalent groups with an N of 65. Each group was taught the molecular basis of sickle cell anemia and the principles of hemoglobin gel electrophoresis using one of the two instructional approaches at their schools during five instructional periods over the course of one week. Laboratory equipment and materials were provided by Boston University School of Medicine's MobileLab program. Following the instructional periods, each subject was asked to think aloud while responding to four problem solving transfer questions. Each response was audiotaped and videotaped. The interviews were transcribed and coded to identify types of mental models and explanative information. Subjects' answers to the problem solving transfer questions were scored using a rubric. Results. Students taught in a constructivist context tended to use more complete mental models than students taught in a transmissional context. Fifty-two percent of constructivist subjects and forty-four percent of transmissional subjects demonstrated evidence of relevant mental models. Overall fifty-two percent of the subjects expressed naive mental models with respect to content. There was no significant difference in the frequency of explanative information expressed by either group. Both groups scored poorly on the problem solving transfer problems. The average score for the constructivist group was 30% and the average score for the transmissional group was 34%. A significant correlation was found between the frequency of explanative information and scores on the problem-solving transfer questions, r = 0.766. Conclusion. The subjects exhibited difficulty in formulating and applying mental models to effectively answer problem solving transfer questions regardless of the context in which the subjects were taught. The results call into question the extent to which students have been taught to use mental models and more generally, the extent to which their prior academic experience has encouraged them to develop an awareness of scientific thinking skills. Implications of the study suggest further consideration of mental modeling in science education reform and the deliberate integration of an awareness of scientific thinking skills in the development of science curricula.
Traditional Payment Models in Radiology: Historical Context for Ongoing Reform.
Silva, Ezequiel; McGinty, Geraldine B; Hughes, Danny R; Duszak, Richard
2016-10-01
The passage of the Medicare Access and CHIP Reauthorization Act (MACRA) replaces the sustainable growth rate with a payment system based on quality and alternative payment model participation. The general structure of payment under MACRA is included in the statute, but the rules and regulations defining its implementation are yet to be formalized. It is imperative that the radiology profession inform policymakers on their role in health care under MACRA. This will require a detailed understanding of prior legislative and nonlegislative actions that helped shape MACRA. To that end, the authors provide a detailed historical context for payment reform, focusing on the payment quality initiatives and alternative payment model demonstrations that helped provide the foundation of future MACRA-driven payment reform. Copyright © 2016 American College of Radiology. Published by Elsevier Inc. All rights reserved.
Theory of Self- vs. Externally-Regulated LearningTM: Fundamentals, Evidence, and Applicability
de la Fuente-Arias, Jesús
2017-01-01
The Theory of Self- vs. Externally-Regulated LearningTM has integrated the variables of SRL theory, the DEDEPRO model, and the 3P model. This new Theory has proposed: (a) in general, the importance of the cyclical model of individual self-regulation (SR) and of external regulation stemming from the context (ER), as two different and complementary variables, both in combination and in interaction; (b) specifically, in the teaching-learning context, the relevance of different types of combinations between levels of self-regulation (SR) and of external regulation (ER) in the prediction of self-regulated learning (SRL), and of cognitive-emotional achievement. This review analyzes the assumptions, conceptual elements, empirical evidence, benefits and limitations of SRL vs. ERL Theory. Finally, professional fields of application and future lines of research are suggested. PMID:29033872
Selecting cockpit functions for speech I/O technology
NASA Technical Reports Server (NTRS)
Simpson, C. A.
1985-01-01
A general methodology for the initial selection of functions for speech generation and speech recognition technology is discussed. The SCR (Stimulus/Central-Processing/Response) compatibility model of Wickens et al. (1983) is examined, and its application is demonstrated for a particular cockpit display problem. Some limits of the applicability of that model are illustrated in the context of predicting overall pilot-aircraft system performance. A program of system performance measurement is recommended for the evaluation of candidate systems. It is suggested that no one measure of system performance can necessarily be depended upon to the exclusion of others. Systems response time, system accuracy, and pilot ratings are all important measures. Finally, these measures must be collected in the context of the total flight task environment.
A radio-frequency sheath model for complex waveforms
NASA Astrophysics Data System (ADS)
Turner, M. M.; Chabert, P.
2014-04-01
Plasma sheaths driven by radio-frequency voltages occur in contexts ranging from plasma processing to magnetically confined fusion experiments. An analytical understanding of such sheaths is therefore important, both intrinsically and as an element in more elaborate theoretical structures. Radio-frequency sheaths are commonly excited by highly anharmonic waveforms, but no analytical model exists for this general case. We present a mathematically simple sheath model that is in good agreement with earlier models for single frequency excitation, yet can be solved for arbitrary excitation waveforms. As examples, we discuss dual-frequency and pulse-like waveforms. The model employs the ansatz that the time-averaged electron density is a constant fraction of the ion density. In the cases we discuss, the error introduced by this approximation is small, and in general it can be quantified through an internal consistency condition of the model. This simple and accurate model is likely to have wide application.
Metrics for Business Process Models
NASA Astrophysics Data System (ADS)
Mendling, Jan
Up until now, there has been little research on why people introduce errors in real-world business process models. In a more general context, Simon [404] points to the limitations of cognitive capabilities and concludes that humans act rationally only to a certain extent. Concerning modeling errors, this argument would imply that human modelers lose track of the interrelations of large and complex models due to their limited cognitive capabilities and introduce errors that they would not insert in a small model. A recent study by Mendling et al. [275] explores in how far certain complexity metrics of business process models have the potential to serve as error determinants. The authors conclude that complexity indeed appears to have an impact on error probability. Before we can test such a hypothesis in a more general setting, we have to establish an understanding of how we can define determinants that drive error probability and how we can measure them.
Finding the target sites of RNA-binding proteins
Li, Xiao; Kazan, Hilal; Lipshitz, Howard D; Morris, Quaid D
2014-01-01
RNA–protein interactions differ from DNA–protein interactions because of the central role of RNA secondary structure. Some RNA-binding domains (RBDs) recognize their target sites mainly by their shape and geometry and others are sequence-specific but are sensitive to secondary structure context. A number of small- and large-scale experimental approaches have been developed to measure RNAs associated in vitro and in vivo with RNA-binding proteins (RBPs). Generalizing outside of the experimental conditions tested by these assays requires computational motif finding. Often RBP motif finding is done by adapting DNA motif finding methods; but modeling secondary structure context leads to better recovery of RBP-binding preferences. Genome-wide assessment of mRNA secondary structure has recently become possible, but these data must be combined with computational predictions of secondary structure before they add value in predicting in vivo binding. There are two main approaches to incorporating structural information into motif models: supplementing primary sequence motif models with preferred secondary structure contexts (e.g., MEMERIS and RNAcontext) and directly modeling secondary structure recognized by the RBP using stochastic context-free grammars (e.g., CMfinder and RNApromo). The former better reconstruct known binding preferences for sequence-specific RBPs but are not suitable for modeling RBPs that recognize shape and geometry of RNAs. Future work in RBP motif finding should incorporate interactions between multiple RBDs and multiple RBPs in binding to RNA. WIREs RNA 2014, 5:111–130. doi: 10.1002/wrna.1201 PMID:24217996
Neisewander, J.L.; Peartree, N.A.; Pentkowski, N.S.
2014-01-01
Rationale Social factors are important determinants of drug dependence and relapse. Objectives We reviewed preclinical literature examining the role of social experiences from early life through the development of drug dependence and relapse, emphasizing two aspects of these experiences: 1) whether the social interaction is appetitive or aversive and 2) whether the social interaction occurs within or outside of the drug-taking context. Methods The models reviewed include neonatal care, isolation, social defeat, chronic subordination, and prosocial interactions. We review results from these models in regard to effects on self-administration and conditioned place preference established with alcohol, psychostimulants, and opiates. Results We suggest that in general, when the interactions occur outside of the drug-taking context, prosocial interactions are protective against drug abuse-related behaviors whereas social stressors facilitate these behaviors. By contrast, positive or negative social interactions occurring within the drug-taking context may interact with other risk factors to enhance or inhibit these behaviors. Conclusions Despite differences in the nature and complexity of human social behavior compared to other species, the evolving animal literature provides useful models for understanding social influences on drug abuse-related behavior that will allow for research on the behavioral and biological mechanisms involved. The models have contributed to understanding social influences on initiation and maintenance of drug use, but more research is needed to understand social influences on drug relapse. PMID:22955569
NASA Technical Reports Server (NTRS)
Brinberg, Herbert R.; Pinelli, Thomas E.
1993-01-01
This paper discusses the various approaches to measuring the value of information, first defining the meanings of information, economics of information, and value. It concludes that no general model of measuring the value of information is possible and that the usual approaches, such as cost/benefit equations, have very limited applications. It also concludes that in specific contexts with given goals for newly developed products and services or newly acquired information, there is a basis for its objective valuation. The axioms and inputs for such a model are described and directions for further verification and analysis are proposed.
Grau-Moya, Jordi; Ortega, Pedro A.; Braun, Daniel A.
2016-01-01
A number of recent studies have investigated differences in human choice behavior depending on task framing, especially comparing economic decision-making to choice behavior in equivalent sensorimotor tasks. Here we test whether decision-making under ambiguity exhibits effects of task framing in motor vs. non-motor context. In a first experiment, we designed an experience-based urn task with varying degrees of ambiguity and an equivalent motor task where subjects chose between hitting partially occluded targets. In a second experiment, we controlled for the different stimulus design in the two tasks by introducing an urn task with bar stimuli matching those in the motor task. We found ambiguity attitudes to be mainly influenced by stimulus design. In particular, we found that the same subjects tended to be ambiguity-preferring when choosing between ambiguous bar stimuli, but ambiguity-avoiding when choosing between ambiguous urn sample stimuli. In contrast, subjects’ choice pattern was not affected by changing from a target hitting task to a non-motor context when keeping the stimulus design unchanged. In both tasks subjects’ choice behavior was continuously modulated by the degree of ambiguity. We show that this modulation of behavior can be explained by an information-theoretic model of ambiguity that generalizes Bayes-optimal decision-making by combining Bayesian inference with robust decision-making under model uncertainty. Our results demonstrate the benefits of information-theoretic models of decision-making under varying degrees of ambiguity for a given context, but also demonstrate the sensitivity of ambiguity attitudes across contexts that theoretical models struggle to explain. PMID:27124723
Grau-Moya, Jordi; Ortega, Pedro A; Braun, Daniel A
2016-01-01
A number of recent studies have investigated differences in human choice behavior depending on task framing, especially comparing economic decision-making to choice behavior in equivalent sensorimotor tasks. Here we test whether decision-making under ambiguity exhibits effects of task framing in motor vs. non-motor context. In a first experiment, we designed an experience-based urn task with varying degrees of ambiguity and an equivalent motor task where subjects chose between hitting partially occluded targets. In a second experiment, we controlled for the different stimulus design in the two tasks by introducing an urn task with bar stimuli matching those in the motor task. We found ambiguity attitudes to be mainly influenced by stimulus design. In particular, we found that the same subjects tended to be ambiguity-preferring when choosing between ambiguous bar stimuli, but ambiguity-avoiding when choosing between ambiguous urn sample stimuli. In contrast, subjects' choice pattern was not affected by changing from a target hitting task to a non-motor context when keeping the stimulus design unchanged. In both tasks subjects' choice behavior was continuously modulated by the degree of ambiguity. We show that this modulation of behavior can be explained by an information-theoretic model of ambiguity that generalizes Bayes-optimal decision-making by combining Bayesian inference with robust decision-making under model uncertainty. Our results demonstrate the benefits of information-theoretic models of decision-making under varying degrees of ambiguity for a given context, but also demonstrate the sensitivity of ambiguity attitudes across contexts that theoretical models struggle to explain.
NASA Astrophysics Data System (ADS)
von Secker, Clare Elaine
The study of students at risk is a major topic of science education policy and discussion. Much research has focused on describing conditions and problems associated with the statistical risk of low science achievement among individuals who are members of groups characterized by problems such as poverty and social disadvantage. But outcomes attributed to these factors do not explain the nature and extent of mechanisms that account for differences in performance among individuals at risk. There is ample theoretical and empirical evidence that demographic differences should be conceptualized as social contexts, or collections of variables, that alter the psychological significance and social demands of life events, and affect subsequent relationships between risk and resilience. The hierarchical linear growth models used in this dissertation provide greater specification of the role of social context and the protective effects of attitude, expectations, parenting practices, peer influences, and learning opportunities on science achievement. While the individual influences of these protective factors on science achievement were small, their cumulative effect was substantial. Meta-analysis conducted on the effects associated with psychological and environmental processes that mediate risk mechanisms in sixteen social contexts revealed twenty-two significant differences between groups of students. Positive attitudes, high expectations, and more intense science course-taking had positive effects on achievement of all students, although these factors were not equally protective in all social contexts. In general, effects associated with authoritative parenting and peer influences were negative, regardless of social context. An evaluation comparing the performance and stability of hierarchical linear growth models with traditional repeated measures models is included as well.
The l z ( p ) * Person-Fit Statistic in an Unfolding Model Context.
Tendeiro, Jorge N
2017-01-01
Although person-fit analysis has a long-standing tradition within item response theory, it has been applied in combination with dominance response models almost exclusively. In this article, a popular log likelihood-based parametric person-fit statistic under the framework of the generalized graded unfolding model is used. Results from a simulation study indicate that the person-fit statistic performed relatively well in detecting midpoint response style patterns and not so well in detecting extreme response style patterns.
Ocampo, Cesar
2004-05-01
The modeling, design, and optimization of finite burn maneuvers for a generalized trajectory design and optimization system is presented. A generalized trajectory design and optimization system is a system that uses a single unified framework that facilitates the modeling and optimization of complex spacecraft trajectories that may operate in complex gravitational force fields, use multiple propulsion systems, and involve multiple spacecraft. The modeling and optimization issues associated with the use of controlled engine burn maneuvers of finite thrust magnitude and duration are presented in the context of designing and optimizing a wide class of finite thrust trajectories. Optimal control theory is used examine the optimization of these maneuvers in arbitrary force fields that are generally position, velocity, mass, and are time dependent. The associated numerical methods used to obtain these solutions involve either, the solution to a system of nonlinear equations, an explicit parameter optimization method, or a hybrid parameter optimization that combines certain aspects of both. The theoretical and numerical methods presented here have been implemented in copernicus, a prototype trajectory design and optimization system under development at the University of Texas at Austin.
Contraction Options and Optimal Multiple-Stopping in Spectrally Negative Lévy Models
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yamazaki, Kazutoshi, E-mail: kyamazak@kansai-u.ac.jp
This paper studies the optimal multiple-stopping problem arising in the context of the timing option to withdraw from a project in stages. The profits are driven by a general spectrally negative Lévy process. This allows the model to incorporate sudden declines of the project values, generalizing greatly the classical geometric Brownian motion model. We solve the one-stage case as well as the extension to the multiple-stage case. The optimal stopping times are of threshold-type and the value function admits an expression in terms of the scale function. A series of numerical experiments are conducted to verify the optimality and tomore » evaluate the efficiency of the algorithm.« less
Transfer of associative grouping to novel perceptual contexts in infancy
Kangas, Ashley; Zieber, Nicole; Hayden, Angela; Quinn, Paul C.; Bhatt, Ramesh S.
2012-01-01
Learning can be highly adaptive if associations learned in one context are generalized to novel contexts. We examined the development of such generalization in infancy in the context of grouping. In Experiment 1, 3- to 4-month-olds and 6- to 7-month-olds were habituated to shapes grouped via the organizational principle of common region and were tested with familiar and novel pairs as determined by the principle of proximity. Older infants generalized from common region to proximity, but younger infants did not. Younger infants failed to generalize when the task was easier (Experiment 2), and their failure was not due to inability to group via proximity (Experiment 3). However, in Experiment 4, even younger infants generalized grouping on the basis of connectedness to proximity. Thus, the ability to transfer learned associations of shapes to novel contexts is evident early in life, although it continues to undergo quantitative change during infancy. Moreover, the operation of this generalization mechanism may be induced by means of bootstrapping onto functional organizational principles, which is consistent with a developmental framework in which core processes scaffold learning. PMID:21826551
Transfer of associative grouping to novel perceptual contexts in infancy.
Kangas, Ashley; Zieber, Nicole; Hayden, Angela; Quinn, Paul C; Bhatt, Ramesh S
2011-11-01
Learning can be highly adaptive if associations learned in one context are generalized to novel contexts. We examined the development of such generalization in infancy in the context of grouping. In Experiment 1, 3- to 4-month-olds and 6- to 7-month-olds were habituated to shapes grouped via the organizational principle of common region and were tested with familiar and novel pairs as determined by the principle of proximity. Older infants generalized from common region to proximity, but younger infants did not. Younger infants failed to generalize when the task was easier (Experiment 2), and their failure was not due to inability to group via proximity (Experiment 3). However, in Experiment 4, even younger infants generalized grouping on the basis of connectedness to proximity. Thus, the ability to transfer learned associations of shapes to novel contexts is evident early in life, although it continues to undergo quantitative change during infancy. Moreover, the operation of this generalization mechanism may be induced by means of bootstrapping onto functional organizational principles, which is consistent with a developmental framework in which core processes scaffold learning.
Nursing knowledge: hints from the placebo effect.
Zanotti, Renzo; Chiffi, Daniele
2017-07-01
Nursing knowledge stems from a dynamic interplay between population-based scientific knowledge (the general) and specific clinical cases (the particular). We compared the 'cascade model of knowledge translation', also known as 'classical biomedical model' in clinical practice (in which knowledge gained at population level may be applied directly to a specific clinical context), with an emergentist model of knowledge translation. The structure and dynamics of nursing knowledge are outlined, adopting the distinction between epistemic and non-epistemic values. Then, a (moderately) emergentist approach to nursing knowledge is proposed, based on the assumption of a two-way flow from the general to the particular and vice versa. The case of the 'placebo effect' is analysed as an example of emergentist knowledge. The placebo effect is usually considered difficult to be explained within the classical biomedical model, and we underscore its importance in shaping nursing knowledge. In fact, nurses are primarily responsible for administering placebo in the clinical setting and have an essential role in promoting the placebo effect and reducing the nocebo effect. The beliefs responsible for the placebo effect are as follows: (1) interactive, because they depend on the relationship between patients and health care professionals; (2) situated, because they occur in a given clinical context related to certain rituals; and (3) grounded on higher order beliefs concerning what an individual thinks about the beliefs of others. It is essential to know the clinical context and to understand other people's beliefs to make sense of the placebo effect. The placebo effect only works when the (higher order) beliefs of doctors, nurses and patients interact in a given setting. Finally, we argue for a close relationship between placebo effect and nursing knowledge. © 2016 John Wiley & Sons Ltd.
Macellini, S.; Maranesi, M.; Bonini, L.; Simone, L.; Rozzi, S.; Ferrari, P. F.; Fogassi, L.
2012-01-01
Macaques can efficiently use several tools, but their capacity to discriminate the relevant physical features of a tool and the social factors contributing to their acquisition are still poorly explored. In a series of studies, we investigated macaques' ability to generalize the use of a stick as a tool to new objects having different physical features (study 1), or to new contexts, requiring them to adapt the previously learned motor strategy (study 2). We then assessed whether the observation of a skilled model might facilitate tool-use learning by naive observer monkeys (study 3). Results of study 1 and study 2 showed that monkeys trained to use a tool generalize this ability to tools of different shape and length, and learn to adapt their motor strategy to a new task. Study 3 demonstrated that observing a skilled model increases the observers' manipulations of a stick, thus facilitating the individual discovery of the relevant properties of this object as a tool. These findings support the view that in macaques, the motor system can be modified through tool use and that it has a limited capacity to adjust the learnt motor skills to a new context. Social factors, although important to facilitate the interaction with tools, are not crucial for tool-use learning. PMID:22106424
Development of a landscape integrity model framework to support regional conservation planning.
Walston, Leroy J; Hartmann, Heidi M
2018-01-01
Land managers increasingly rely upon landscape assessments to understand the status of natural resources and identify conservation priorities. Many of these landscape planning efforts rely on geospatial models that characterize the ecological integrity of the landscape. These general models utilize measures of habitat disturbance and human activity to map indices of ecological integrity. We built upon these modeling frameworks by developing a Landscape Integrity Index (LII) model using geospatial datasets of the human footprint, as well as incorporation of other indicators of ecological integrity such as biodiversity and vegetation departure. Our LII model serves as a general indicator of ecological integrity in a regional context of human activity, biodiversity, and change in habitat composition. We also discuss the application of the LII framework in two related coarse-filter landscape conservation approaches to expand the size and connectedness of protected areas as regional mitigation for anticipated land-use changes.
Development of a landscape integrity model framework to support regional conservation planning
Hartmann, Heidi M.
2018-01-01
Land managers increasingly rely upon landscape assessments to understand the status of natural resources and identify conservation priorities. Many of these landscape planning efforts rely on geospatial models that characterize the ecological integrity of the landscape. These general models utilize measures of habitat disturbance and human activity to map indices of ecological integrity. We built upon these modeling frameworks by developing a Landscape Integrity Index (LII) model using geospatial datasets of the human footprint, as well as incorporation of other indicators of ecological integrity such as biodiversity and vegetation departure. Our LII model serves as a general indicator of ecological integrity in a regional context of human activity, biodiversity, and change in habitat composition. We also discuss the application of the LII framework in two related coarse-filter landscape conservation approaches to expand the size and connectedness of protected areas as regional mitigation for anticipated land-use changes. PMID:29614093
Item Selection and Ability Estimation Procedures for a Mixed-Format Adaptive Test
ERIC Educational Resources Information Center
Ho, Tsung-Han; Dodd, Barbara G.
2012-01-01
In this study we compared five item selection procedures using three ability estimation methods in the context of a mixed-format adaptive test based on the generalized partial credit model. The item selection procedures used were maximum posterior weighted information, maximum expected information, maximum posterior weighted Kullback-Leibler…
Estimation of risks to children from exposure to airborne pollutants is often complicated by the lack of reliable epidemiological data specific to this age group. As a result, risks are generally estimated from extrapolations based on data obtained in other human age groups (e.g....
Tests of Measurement Invariance without Subgroups: A Generalization of Classical Methods
ERIC Educational Resources Information Center
Merkle, Edgar C.; Zeileis, Achim
2013-01-01
The issue of measurement invariance commonly arises in factor-analytic contexts, with methods for assessment including likelihood ratio tests, Lagrange multiplier tests, and Wald tests. These tests all require advance definition of the number of groups, group membership, and offending model parameters. In this paper, we study tests of measurement…
Crossing Cultural and Gender Borders to Change the Way We Use Discourse in the Classroom
ERIC Educational Resources Information Center
Lloyd, Keith
2013-01-01
Though many teachers have adopted collaborative models for teaching writing and literature, much of classroom discussion, in small or large groups, is driven by the assumption that arguing ideas is a competitive exercise. Generally, essays written in this context are "counter-positional" and "agonistic," supporting points by…
Auditing the Numeracy Demands of the Australian Curriculum
ERIC Educational Resources Information Center
Goos, Merrilyn; Dole, Shelley; Geiger, Vince
2012-01-01
Numeracy is a general capability to be developed in all learning areas of the Australian Curriculum. We evaluated the numeracy demands of the F-10 curriculum, using a model of numeracy that incorporates mathematical knowledge, dispositions, tools, contexts, and a critical orientation to the use of mathematics. Findings of the history curriculum…
Assessing the Chances of Success: Naive Statistics versus Kind Experience
ERIC Educational Resources Information Center
Hogarth, Robin M.; Mukherjee, Kanchan; Soyer, Emre
2013-01-01
Additive integration of information is ubiquitous in judgment and has been shown to be effective even when multiplicative rules of probability theory are prescribed. We explore the generality of these findings in the context of estimating probabilities of success in contests. We first define a normative model of these probabilities that takes…
A Comparison of Imputation Methods for Bayesian Factor Analysis Models
ERIC Educational Resources Information Center
Merkle, Edgar C.
2011-01-01
Imputation methods are popular for the handling of missing data in psychology. The methods generally consist of predicting missing data based on observed data, yielding a complete data set that is amiable to standard statistical analyses. In the context of Bayesian factor analysis, this article compares imputation under an unrestricted…
ERIC Educational Resources Information Center
Casey, Catherine
2011-01-01
"Economy, Work and Education: Critical Connections" addresses effects of neoliberal capitalism in particular regard to work and education. The book elaborates key aspects and problems of generalized policy models of knowledge-based economies and learning societies in contexts of liberalized firm action, accelerated competitiveness and labor market…
Exploring the Visuospatial Challenge of Learning about Day and Night and the Sun's Path
ERIC Educational Resources Information Center
Heywood, David; Parker, Joan; Rowlands, Mark
2013-01-01
The role of visualization and model-based reasoning has become increasingly significant in science education across a range of contexts. It is generally recognized that supporting learning in developing causal explanations for observed astronomical events presents considerable pedagogic challenge. Understanding the Sun's apparent movement…
Perceptions of Financial Aid: Black Students at a Predominantly White Institution
ERIC Educational Resources Information Center
Tichavakunda, Antar A.
2017-01-01
This study provides qualitative context for statistics concerning Black college students and financial aid. Using the financial nexus model as a framework, this research draws upon interviews with 29 Black juniors and seniors at a selective, -private, and predominantly White university. The data suggest that students -generally exhibited high…
ERIC Educational Resources Information Center
Pai, Pei-Yu; Tsai, Hsien-Tung
2011-01-01
Extant studies generally recognise that virtual community building is an effective marketing programme for forging deep and enduring affective bonds with consumers. This study extends previous research by proposing and testing a model that investigates key mediating processes (via trust, satisfaction and identification) that underlie the…
Contracts, Choice, and Customer Service: Marketization and Public Engagement in Education
ERIC Educational Resources Information Center
Cucchiara, Maia Bloomfield; Gold, Eva; Simon, Elaine
2011-01-01
Background/Context: Market models of school reform are having a major impact on school districts across the country. While scholars have examined many aspects of this process, we know far less about the general effects of marketization on public participation in education and local education politics. Purpose/Objective/Research Question/Focus of…
Solving Discipline Problems: Strategies for Classroom Teachers.
ERIC Educational Resources Information Center
Wolfgang, Charles H.; Glickman, Carl D.
This book provides classroom teachers with a variety of discipline models, techniques, methods, and constructs designed to enable them to move beyond a singular approach in handling classroom behavior problems. The book first discusses the Teacher Behavior Continuum (TBC) which shows the teacher the context of his or her own general behavior with…
The dual reading of general conditionals: The influence of abstract versus concrete contexts.
Wang, Moyun; Yao, Xinyun
2018-04-01
A current main issue on conditionals is whether the meaning of general conditionals (e.g., If a card is red, then it is round) is deterministic (exceptionless) or probabilistic (exception-tolerating). In order to resolve the issue, two experiments examined the influence of conditional contexts (with vs. without frequency information of truth table cases) on the reading of general conditionals. Experiment 1 examined the direct reading of general conditionals in the possibility judgment task. Experiment 2 examined the indirect reading of general conditionals in the truth judgment task. It was found that both the direct and indirect reading of general conditionals exhibited the duality: the predominant deterministic semantic reading of conditionals without frequency information, and the predominant probabilistic pragmatic reading of conditionals with frequency information. The context of general conditionals determined the predominant reading of general conditionals. There were obvious individual differences in reading general conditionals with frequency information. The meaning of general conditionals is relative, depending on conditional contexts. The reading of general conditionals is flexible and complex so that no simple deterministic and probabilistic accounts are able to explain it. The present findings are beyond the extant deterministic and probabilistic accounts of conditionals.
Using Speculative Execution to Automatically Hide I/O Latency
2001-12-07
sion of the Lempel - Ziv algorithm and the Finite multi-order context models (FMOC) that originated from prediction-by-partial-match data compressors...allowed the cancellation of a single hint at a time.) 2.2.4 Predicting future data needs In order to take advantage of any of the algorithms described...modelling techniques generally used for data compression to perform probabilistic prediction of an application’s next page fault (or, in an object-oriented
The Decision Module Working Paper
1973-12-01
and goal change has received very little attention In the litera- ture on the analysis of choice situations. It has generally been the case that the...Decision Making: Approach and Prototype" (197:0, done In context of the Mesarovlc - Pestel World Model Projet’ The Issues dealing with «-he cho ce...Nelson, Winder, and Schuette (1973) on evolutionary economic growth models. The discussion of the two components of the decision module that follows
Terkamo-Moisio, Anja; Kvist, Tarja; Laitila, Teuvo; Kangasniemi, Mari; Ryynänen, Olli-Pekka; Pietilä, Anna-Maija
2017-08-01
The debate about euthanasia is ongoing in several countries including Finland. However, there is a lack of information on current attitudes toward euthanasia among general Finnish public. The traditional model for predicting individuals' attitudes to euthanasia is based on their age, gender, educational level, and religiosity. However, a new evaluation of religiosity is needed due to the limited operationalization of this factor in previous studies. This study explores the connections between the factors of the traditional model and the attitudes toward euthanasia among the general public in the Finnish context. The Finnish public's attitudes toward euthanasia have become remarkably more positive over the last decade. Further research is needed on the factors that predict euthanasia attitudes. We suggest two different explanatory models for consideration: one that emphasizes the value of individual autonomy and another that approaches euthanasia from the perspective of fears of death or the process of dying.
South Palomares, Jennifer K; Sutherland, Clare A M; Young, Andrew W
2017-12-17
Given the frequency of relationships nowadays initiated online, where impressions from face photographs may influence relationship initiation, it is important to understand how facial first impressions might be used in such contexts. We therefore examined the applicability of a leading model of verbally expressed partner preferences to impressions derived from real face images and investigated how the factor structure of first impressions based on potential partner preference-related traits might relate to a more general model of facial first impressions. Participants rated 1,000 everyday face photographs on 12 traits selected to represent (Fletcher, et al. 1999, Journal of Personality and Social Psychology, 76, 72) verbal model of partner preferences. Facial trait judgements showed an underlying structure that largely paralleled the tripartite structure of Fletcher et al.'s verbal preference model, regardless of either face gender or participant gender. Furthermore, there was close correspondence between the verbal partner preference model and a more general tripartite model of facial first impressions derived from a different literature (Sutherland et al., 2013, Cognition, 127, 105), suggesting an underlying correspondence between verbal conceptual models of romantic preferences and more general models of facial first impressions. © 2017 The British Psychological Society.
Extended generalized geometry and a DBI-type effective action for branes ending on branes
NASA Astrophysics Data System (ADS)
Jurčo, Branislav; Schupp, Peter; Vysoký, Jan
2014-08-01
Starting from the Nambu-Goto bosonic membrane action, we develop a geometric description suitable for p-brane backgrounds. With tools of generalized geometry we derive the pertinent generalization of the string open-closed relations to the p-brane case. Nambu-Poisson structures are used in this context to generalize the concept of semi-classical noncommutativity of D-branes governed by a Poisson tensor. We find a natural description of the correspondence of recently proposed commutative and noncommutative versions of an effective action for p-branes ending on a p '-brane. We calculate the power series expansion of the action in background independent gauge. Leading terms in the double scaling limit are given by a generalization of a (semi-classical) matrix model.
Mohr, Philip; Golley, Sinéad
2016-01-25
This study examined community responses to use of genetically modified (GM) content in food in the context of responses to familiar food additives by testing an empirically and theoretically derived model of the predictors of responses to both GM content and food integrity issues generally. A nationwide sample of 849 adults, selected at random from the Australian Electoral Roll, responded to a postal Food and Health Survey. Structural equation modelling analyses confirmed that ratings of general concern about food integrity (related to the presence of preservatives and other additives) strongly predicted negativity towards GM content. Concern about food integrity was, in turn, predicted by environmental concern and health engagement. In addition, both concern about food integrity generally and responses to GM content specifically were weakly predicted by attitudes to benefits of science and an intuitive (i.e., emotionally-based) reasoning style. Data from a follow-up survey conducted under the same conditions (N=1184) revealed that ratings of concern were significantly lower for use of genetic engineering in food than for four other common food integrity issues examined. Whereas the question of community responses to GM is often treated as a special issue, these findings support the conclusion that responses to the concept of GM content in food in Australia are substantially a specific instance of a general sensitivity towards the integrity of the food supply. They indicate that the origins of responses to GM content may be largely indistinguishable from those of general responses to preservatives and other common food additives. Copyright © 2015 Elsevier B.V. All rights reserved.
Goldman, S R; Hasselbring, T S
1997-01-01
In this article we consider issues relevant to the future of mathematics instruction and achievement for students with learning disabilities. The starting point for envisioning the future is the changing standards for mathematics learning and basic mathematical literacy. We argue that the shift from behaviorist learning theories to constructivist and social constructivist theories (see Rivera, this series) provides an opportunity to develop and implement a hybrid model of mathematics instruction. The hybrid model we propose embeds, or situates, important skill learning in meaningful contexts. We discuss some examples of instructional approaches to complex mathematical problem solving that make use of meaningful contexts. Evaluation data on these approaches have yielded positive and encouraging results for students with learning disabilities as well as general education students. Finally, we discuss various ways in which technology is important for realizing hybrid instructional models in mathematics.
Reconceptualizing Native Women's Health: An “Indigenist” Stress-Coping Model
Walters, Karina L.; Simoni, Jane M.
2002-01-01
This commentary presents an “indigenist” model of Native women's health, a stress-coping paradigm that situates Native women's health within the larger context of their status as a colonized people. The model is grounded in empirical evidence that traumas such as the “soul wound” of historical and contemporary discrimination among Native women influence health and mental health outcomes. The preliminary model also incorporates cultural resilience, including as moderators identity, enculturation, spiritual coping, and traditional healing practices. Current epidemiological data on Native women's general health and mental health are reconsidered within the framework of this model. PMID:11919043
Generalized formulation of the interactions between soft spheres
NASA Astrophysics Data System (ADS)
Alonso-Marroquín, F.; McNamara, S.
2014-10-01
The goal of this paper is to identify the most general formulation that consistently links the different degrees of freedom in a contact between spherical soft particles. These contact laws have two parts: a set of "generalized contact velocities" that characterize the relative motion of the two particles, and a set of "generalized contact forces" that characterize the interparticle forces. One well known constraint on contact models is that the contact velocities must be objective. This requirement fixes the number of linearly independent contact velocities. We also present a previously unnoticed (in this context) constraint, namely, that the velocities and forces must be related in such a way that the stiffness matrix is symmetric. This constraint also places restrictions on the coupling between the contact forces. Within our generalized contact model, we discuss the expression for rolling velocity that need to be used in the calculation of rolling resistance, and the risk or producing perpetual mobile when other expressions of rolling velocity are using instead.
Zhang, Wei; Wu, Yan Yan
2017-03-01
Analyzing the 2011-2013 China Health and Retirement Longitudinal Study with 14,507 respondents from 393 neighborhoods, and applying generalized linear mixed-effects model, this study examines how individual-level education and neighborhood-socioeconomic contexts affect health through social engagement. Findings reveal that measures of social engagement-social activity and productive activity-are significantly related to self-rated health and partially mediate the effects of individual-level education. Neighborhood-socioeconomic contexts have independent effects on self-rated health beyond individual socio-demographics, and social activity mediates the effects of neighborhood recreational facilities. This study is among the first to simultaneously explore the health effects of individual and neighborhood-level socioeconomic conditions. Copyright © 2017 Elsevier Ltd. All rights reserved.
NASA Technical Reports Server (NTRS)
Brinberg, Herbert R.; Pinelli, Thomas E.
1993-01-01
This paper discusses the various approaches to measuring the value of information, first defining the meanings of information, economics of information, and value. It concludes that no general model of measuring the value of information is possible and that the usual approaches, such as cost/benefit equations, have very limited applications. It also concludes that in specific contexts with given goals for newly developed products and services or newly acquired information there is a basis for its objective valuation. The axioms and inputs for such a model are described and directions for further verification and analysis are proposed.
Radiation bounce from the Lee-Wick construction?
DOE Office of Scientific and Technical Information (OSTI.GOV)
Karouby, Johanna; Brandenberger, Robert
2010-09-15
It was recently realized that matter modeled by the scalar field sector of the Lee-Wick standard model yields, in the context of a homogeneous and isotropic cosmological background, a bouncing cosmology. However, bouncing cosmologies induced by pressureless matter are in general unstable to the addition of relativistic matter (i.e. radiation). Here we study the possibility of obtaining a bouncing cosmology if we add not only radiation, but also its Lee-Wick partner, to the matter sector. We find that, in general, no bounce occurs. The only way to obtain a bounce is to choose initial conditions with very special phases ofmore » the radiation field and its Lee-Wick partner.« less
Developing an Iranian ELT Context-Specific Grit Instrument.
Ebadi, Saman; Weisi, Hiwa; Khaksar, Zahra
2018-03-06
Grit as an interesting and significant topic in psychology has been associated with better study habits and higher grades through perseverance and passion for long term goals. The only available measurement instrument of grit (Duckworth et al. in J Personal Soc Psychol 92:1087-1101, 2007) is general both in terms of its subject matter and context. Thus, this study aims to develop and validate an English as a foreign language (EFL) grit instrument whose items are specific to EFL context to obtain a more detailed view of its components for Iranian EFL learners, and to tap on other grit related factors in the EFL context. A four component model of EFL grit was developed through reviewing the existing literature and exploring EFL experts' perspectives. This tentative theoretical model of EFL grit encompasses overarching construct of effort including the following main components: Trying hard to learn English (THLE) having interest in learning English (ILE) practicing a lot in order to learn English (PLE) and having goal for learning English (HGLE). The model was then cross checked against the results of the interviews, and evolved into a scenario-based, 5 point Likert-scale EFL grit instrument. It was later operationalized by an instrument consisting of 26 items, i.e. 6 items for each component plus 2 items for themes 1 and 3. The piloting and testing of the tentative model through exploratory and confirmatory data analyses on a sample of 306 EFL learners indicated the reliability of 0.833 and an acceptable validity. The findings called for a more meaningful interpretation of the concept of grit in relation to Iranian EFL context and offered new insights for higher education administrators considering student academic performance.
2017-01-01
Studies of animal personality attempt to uncover underlying or “latent” personality traits that explain broad patterns of behaviour, often by applying latent variable statistical models (e.g., factor analysis) to multivariate data sets. Two integral, but infrequently confirmed, assumptions of latent variable models in animal personality are: i) behavioural variables are independent (i.e., uncorrelated) conditional on the latent personality traits they reflect (local independence), and ii) personality traits are associated with behavioural variables in the same way across individuals or groups of individuals (measurement invariance). We tested these assumptions using observations of aggression in four age classes (4–10 months, 10 months–3 years, 3–6 years, over 6 years) of male and female shelter dogs (N = 4,743) in 11 different contexts. A structural equation model supported the hypothesis of two positively correlated personality traits underlying aggression across contexts: aggressiveness towards people and aggressiveness towards dogs (comparative fit index: 0.96; Tucker-Lewis index: 0.95; root mean square error of approximation: 0.03). Aggression across contexts was moderately repeatable (towards people: intraclass correlation coefficient (ICC) = 0.479; towards dogs: ICC = 0.303). However, certain contexts related to aggressiveness towards people (but not dogs) shared significant residual relationships unaccounted for by latent levels of aggressiveness. Furthermore, aggressiveness towards people and dogs in different contexts interacted with sex and age. Thus, sex and age differences in displays of aggression were not simple functions of underlying aggressiveness. Our results illustrate that the robustness of traits in latent variable models must be critically assessed before making conclusions about the effects of, or factors influencing, animal personality. Our findings are of concern because inaccurate “aggressive personality” trait attributions can be costly to dogs, recipients of aggression and society in general. PMID:28854267
Goold, Conor; Newberry, Ruth C
2017-01-01
Studies of animal personality attempt to uncover underlying or "latent" personality traits that explain broad patterns of behaviour, often by applying latent variable statistical models (e.g., factor analysis) to multivariate data sets. Two integral, but infrequently confirmed, assumptions of latent variable models in animal personality are: i) behavioural variables are independent (i.e., uncorrelated) conditional on the latent personality traits they reflect (local independence), and ii) personality traits are associated with behavioural variables in the same way across individuals or groups of individuals (measurement invariance). We tested these assumptions using observations of aggression in four age classes (4-10 months, 10 months-3 years, 3-6 years, over 6 years) of male and female shelter dogs (N = 4,743) in 11 different contexts. A structural equation model supported the hypothesis of two positively correlated personality traits underlying aggression across contexts: aggressiveness towards people and aggressiveness towards dogs (comparative fit index: 0.96; Tucker-Lewis index: 0.95; root mean square error of approximation: 0.03). Aggression across contexts was moderately repeatable (towards people: intraclass correlation coefficient (ICC) = 0.479; towards dogs: ICC = 0.303). However, certain contexts related to aggressiveness towards people (but not dogs) shared significant residual relationships unaccounted for by latent levels of aggressiveness. Furthermore, aggressiveness towards people and dogs in different contexts interacted with sex and age. Thus, sex and age differences in displays of aggression were not simple functions of underlying aggressiveness. Our results illustrate that the robustness of traits in latent variable models must be critically assessed before making conclusions about the effects of, or factors influencing, animal personality. Our findings are of concern because inaccurate "aggressive personality" trait attributions can be costly to dogs, recipients of aggression and society in general.
Sandberg, Chaleece; Kiran, Swathi
2014-01-01
Developing language treatments that not only improve trained items but also promote generalization to untrained items is a major focus in aphasia research. This study is a replication and extension of previous work that found that training abstract words in a particular context-category promotes generalization to concrete words but not vice versa (Kiran, Sandberg, & Abbott, 2009). Twelve persons with aphasia (5 female) with varying types and degrees of severity participated in a generative naming treatment based on the complexity account of treatment efficacy (CATE; Thompson, Shapiro, Kiran, & Sobecks, 2003). All participants were trained to generate abstract words in a particular context-category by analyzing the semantic features of the target words. Two other context-categories were used as controls. Ten of the twelve participants improved on the trained abstract words in the trained context-category. Eight of the ten participants who responded to treatment also generalized to concrete words in the same context-category. These results suggest that this treatment is both efficacious and efficient. We discuss possible mechanisms of training and generalization effects. PMID:24805853
Generalized Nonlinear Yule Models
NASA Astrophysics Data System (ADS)
Lansky, Petr; Polito, Federico; Sacerdote, Laura
2016-11-01
With the aim of considering models related to random graphs growth exhibiting persistent memory, we propose a fractional nonlinear modification of the classical Yule model often studied in the context of macroevolution. Here the model is analyzed and interpreted in the framework of the development of networks such as the World Wide Web. Nonlinearity is introduced by replacing the linear birth process governing the growth of the in-links of each specific webpage with a fractional nonlinear birth process with completely general birth rates. Among the main results we derive the explicit distribution of the number of in-links of a webpage chosen uniformly at random recognizing the contribution to the asymptotics and the finite time correction. The mean value of the latter distribution is also calculated explicitly in the most general case. Furthermore, in order to show the usefulness of our results, we particularize them in the case of specific birth rates giving rise to a saturating behaviour, a property that is often observed in nature. The further specialization to the non-fractional case allows us to extend the Yule model accounting for a nonlinear growth.
Maximum Likelihood Shift Estimation Using High Resolution Polarimetric SAR Clutter Model
NASA Astrophysics Data System (ADS)
Harant, Olivier; Bombrun, Lionel; Vasile, Gabriel; Ferro-Famil, Laurent; Gay, Michel
2011-03-01
This paper deals with a Maximum Likelihood (ML) shift estimation method in the context of High Resolution (HR) Polarimetric SAR (PolSAR) clutter. Texture modeling is exposed and the generalized ML texture tracking method is extended to the merging of various sensors. Some results on displacement estimation on the Argentiere glacier in the Mont Blanc massif using dual-pol TerraSAR-X (TSX) and quad-pol RADARSAT-2 (RS2) sensors are finally discussed.
Verification of Autonomous Systems for Space Applications
NASA Technical Reports Server (NTRS)
Brat, G.; Denney, E.; Giannakopoulou, D.; Frank, J.; Jonsson, A.
2006-01-01
Autonomous software, especially if it is based on model, can play an important role in future space applications. For example, it can help streamline ground operations, or, assist in autonomous rendezvous and docking operations, or even, help recover from problems (e.g., planners can be used to explore the space of recovery actions for a power subsystem and implement a solution without (or with minimal) human intervention). In general, the exploration capabilities of model-based systems give them great flexibility. Unfortunately, it also makes them unpredictable to our human eyes, both in terms of their execution and their verification. The traditional verification techniques are inadequate for these systems since they are mostly based on testing, which implies a very limited exploration of their behavioral space. In our work, we explore how advanced V&V techniques, such as static analysis, model checking, and compositional verification, can be used to gain trust in model-based systems. We also describe how synthesis can be used in the context of system reconfiguration and in the context of verification.
ERIC Educational Resources Information Center
Holcombe, Wendy; Plunkett, Margaret
2016-01-01
National statistics indicate the ongoing challenge of catering for the unique needs of students with Autism Spectrum Disorder (ASD) within the context of inclusive education. Higher rates of difficulty and poorer outcomes are experienced by this cohort when compared to both the general population and others within the disability sector. The…
ERIC Educational Resources Information Center
Kim, Jiseon
2010-01-01
Classification testing has been widely used to make categorical decisions by determining whether an examinee has a certain degree of ability required by established standards. As computer technologies have developed, classification testing has become more computerized. Several approaches have been proposed and investigated in the context of…
Screen Design Principles of Computer-Aided Instructional Software for Elementary School Students
ERIC Educational Resources Information Center
Berrin, Atiker; Turan, Bülent Onur
2017-01-01
This study aims to present primary school students' views about current educational software interfaces, and to propose principles for educational software screens. The study was carried out with a general screening model. Sample group of the study consisted of sixth grade students in Sehit Ögretmen Hasan Akan Elementary School. In this context,…
ERIC Educational Resources Information Center
Huh, Seonmin
2016-01-01
This article explores the general patterns of interactions between the teacher and students during the different instructional steps when the teacher attempted to incorporate both conventional skill-based reading and critical literacy in an English as a foreign language (EFL) literacy class in a Korean university. There has been a paucity of EFL…
ERIC Educational Resources Information Center
Pierce, Clayton
2015-01-01
This paper attempts to answer this question: what should ecoliteracy mean in a biocapitalist society? The author situates his analysis of this question within the general context of the neoliberal reconstruction of education in the US. Specifically, focus is given to the shared model of governmentality GE food industries and education policies…
A Case Study of Co-Teaching in an Inclusive Secondary High-Stakes World History I Classroom
ERIC Educational Resources Information Center
van Hover, Stephanie; Hicks, David; Sayeski, Kristin
2012-01-01
In order to provide increasing support for students with disabilities in inclusive classrooms in high-stakes testing contexts, some schools have implemented co-teaching models. This qualitative case study explores how 1 special education teacher (Anna) and 1 general education history teacher (John) make sense of working together in an inclusive…
General Education Development (GED) Recipients' Life Course Experiences: Humanizing the Findings
ERIC Educational Resources Information Center
Hartigan, Lacey A.
2017-01-01
This study examines a range of GED recipients' life course contexts and experiences and their relationship with long-term outcomes. Using descriptive comparisons, bivariate tests, and propensity-score matched regression models to analyze data from rounds 1-15 of the National Longitudinal Survey of Youth, 1997, analyses aim to examine: (1)…
Argumentation in Science Education: A Model-based Framework
NASA Astrophysics Data System (ADS)
Böttcher, Florian; Meisert, Anke
2011-02-01
The goal of this article is threefold: First, the theoretical background for a model-based framework of argumentation to describe and evaluate argumentative processes in science education is presented. Based on the general model-based perspective in cognitive science and the philosophy of science, it is proposed to understand arguments as reasons for the appropriateness of a theoretical model which explains a certain phenomenon. Argumentation is considered to be the process of the critical evaluation of such a model if necessary in relation to alternative models. Secondly, some methodological details are exemplified for the use of a model-based analysis in the concrete classroom context. Third, the application of the approach in comparison with other analytical models will be presented to demonstrate the explicatory power and depth of the model-based perspective. Primarily, the framework of Toulmin to structurally analyse arguments is contrasted with the approach presented here. It will be demonstrated how common methodological and theoretical problems in the context of Toulmin's framework can be overcome through a model-based perspective. Additionally, a second more complex argumentative sequence will also be analysed according to the invented analytical scheme to give a broader impression of its potential in practical use.
Huppert, Theodore J
2016-01-01
Functional near-infrared spectroscopy (fNIRS) is a noninvasive neuroimaging technique that uses low levels of light to measure changes in cerebral blood oxygenation levels. In the majority of NIRS functional brain studies, analysis of this data is based on a statistical comparison of hemodynamic levels between a baseline and task or between multiple task conditions by means of a linear regression model: the so-called general linear model. Although these methods are similar to their implementation in other fields, particularly for functional magnetic resonance imaging, the specific application of these methods in fNIRS research differs in several key ways related to the sources of noise and artifacts unique to fNIRS. In this brief communication, we discuss the application of linear regression models in fNIRS and the modifications needed to generalize these models in order to deal with structured (colored) noise due to systemic physiology and noise heteroscedasticity due to motion artifacts. The objective of this work is to present an overview of these noise properties in the context of the linear model as it applies to fNIRS data. This work is aimed at explaining these mathematical issues to the general fNIRS experimental researcher but is not intended to be a complete mathematical treatment of these concepts.
No effect of glucose administration in a novel contextual fear generalization protocol in rats
Luyten, L; Schroyens, N; Luyck, K; Fanselow, M S; Beckers, T
2016-01-01
The excessive transfer of fear acquired for one particular context to similar situations has been implicated in the development and maintenance of anxiety disorders, such as post-traumatic stress disorder. Recent evidence suggests that glucose ingestion improves the retention of context conditioning. It has been speculated that glucose might exert that effect by ameliorating hippocampal functioning, and may hold promise as a therapeutic add-on in traumatized patients because improved retention of contextual fear could help to restrict its generalization. However, direct data regarding the effect of glucose on contextual generalization are lacking. Here, we introduce a new behavioral protocol to study such contextual fear generalization in rats. In adult Wistar rats, our procedure yields a gradient of generalization, with progressively less freezing when going from the original training context, over a perceptually similar generalization context, to a markedly dissimilar context. Moreover, we find a flattening of the gradient when the training-test interval is prolonged with 1 week. We next examine the effect of systemic glucose administration on contextual generalization with this novel procedure. Our data do not sustain generalization-reducing effects of glucose and question its applicability in traumatic situations. In summary, we have developed a replicable contextual generalization procedure for rats and demonstrate how it is a valuable tool to examine the neurobiological correlates and test pharmacological interventions pertaining to an important mechanism in the etiology of pathological anxiety. PMID:27676444
Role of Prefrontal Cortex in Learning and Generalizing Hierarchical Rules in 8-Month-Old Infants.
Werchan, Denise M; Collins, Anne G E; Frank, Michael J; Amso, Dima
2016-10-05
Recent research indicates that adults and infants spontaneously create and generalize hierarchical rule sets during incidental learning. Computational models and empirical data suggest that, in adults, this process is supported by circuits linking prefrontal cortex (PFC) with striatum and their modulation by dopamine, but the neural circuits supporting this form of learning in infants are largely unknown. We used near-infrared spectroscopy to record PFC activity in 8-month-old human infants during a simple audiovisual hierarchical-rule-learning task. Behavioral results confirmed that infants adopted hierarchical rule sets to learn and generalize spoken object-label mappings across different speaker contexts. Infants had increased activity over right dorsal lateral PFC when rule sets switched from one trial to the next, a neural marker related to updating rule sets into working memory in the adult literature. Infants' eye blink rate, a possible physiological correlate of striatal dopamine activity, also increased when rule sets switched from one trial to the next. Moreover, the increase in right dorsolateral PFC activity in conjunction with eye blink rate also predicted infants' generalization ability, providing exploratory evidence for frontostriatal involvement during learning. These findings provide evidence that PFC is involved in rudimentary hierarchical rule learning in 8-month-old infants, an ability that was previously thought to emerge later in life in concert with PFC maturation. Hierarchical rule learning is a powerful learning mechanism that allows rules to be selected in a context-appropriate fashion and transferred or reused in novel contexts. Data from computational models and adults suggests that this learning mechanism is supported by dopamine-innervated interactions between prefrontal cortex (PFC) and striatum. Here, we provide evidence that PFC also supports hierarchical rule learning during infancy, challenging the current dogma that PFC is an underdeveloped brain system until adolescence. These results add new insights into the neurobiological mechanisms available to support learning and generalization in very early postnatal life, providing evidence that PFC and the frontostriatal circuitry are involved in organizing learning and behavior earlier in life than previously known. Copyright © 2016 the authors 0270-6474/16/3610314-09$15.00/0.
Role of Prefrontal Cortex in Learning and Generalizing Hierarchical Rules in 8-Month-Old Infants
Werchan, Denise M.; Collins, Anne G.E.; Frank, Michael J.
2016-01-01
Recent research indicates that adults and infants spontaneously create and generalize hierarchical rule sets during incidental learning. Computational models and empirical data suggest that, in adults, this process is supported by circuits linking prefrontal cortex (PFC) with striatum and their modulation by dopamine, but the neural circuits supporting this form of learning in infants are largely unknown. We used near-infrared spectroscopy to record PFC activity in 8-month-old human infants during a simple audiovisual hierarchical-rule-learning task. Behavioral results confirmed that infants adopted hierarchical rule sets to learn and generalize spoken object–label mappings across different speaker contexts. Infants had increased activity over right dorsal lateral PFC when rule sets switched from one trial to the next, a neural marker related to updating rule sets into working memory in the adult literature. Infants' eye blink rate, a possible physiological correlate of striatal dopamine activity, also increased when rule sets switched from one trial to the next. Moreover, the increase in right dorsolateral PFC activity in conjunction with eye blink rate also predicted infants' generalization ability, providing exploratory evidence for frontostriatal involvement during learning. These findings provide evidence that PFC is involved in rudimentary hierarchical rule learning in 8-month-old infants, an ability that was previously thought to emerge later in life in concert with PFC maturation. SIGNIFICANCE STATEMENT Hierarchical rule learning is a powerful learning mechanism that allows rules to be selected in a context-appropriate fashion and transferred or reused in novel contexts. Data from computational models and adults suggests that this learning mechanism is supported by dopamine-innervated interactions between prefrontal cortex (PFC) and striatum. Here, we provide evidence that PFC also supports hierarchical rule learning during infancy, challenging the current dogma that PFC is an underdeveloped brain system until adolescence. These results add new insights into the neurobiological mechanisms available to support learning and generalization in very early postnatal life, providing evidence that PFC and the frontostriatal circuitry are involved in organizing learning and behavior earlier in life than previously known. PMID:27707968
Generalized probabilistic scale space for image restoration.
Wong, Alexander; Mishra, Akshaya K
2010-10-01
A novel generalized sampling-based probabilistic scale space theory is proposed for image restoration. We explore extending the definition of scale space to better account for both noise and observation models, which is important for producing accurately restored images. A new class of scale-space realizations based on sampling and probability theory is introduced to realize this extended definition in the context of image restoration. Experimental results using 2-D images show that generalized sampling-based probabilistic scale-space theory can be used to produce more accurate restored images when compared with state-of-the-art scale-space formulations, particularly under situations characterized by low signal-to-noise ratios and image degradation.
Specialized Knowledge Representation and the Parameterization of Context.
Faber, Pamela; León-Araúz, Pilar
2016-01-01
Though instrumental in numerous disciplines, context has no universally accepted definition. In specialized knowledge resources it is timely and necessary to parameterize context with a view to more effectively facilitating knowledge representation, understanding, and acquisition, the main aims of terminological knowledge bases. This entails distinguishing different types of context as well as how they interact with each other. This is not a simple objective to achieve despite the fact that specialized discourse does not have as many contextual variables as those in general language (i.e., figurative meaning, irony, etc.). Even in specialized text, context is an extremely complex concept. In fact, contextual information can be specified in terms of scope or according to the type of information conveyed. It can be a textual excerpt or a whole document; a pragmatic convention or a whole culture; a concrete situation or a prototypical scenario. Although these versions of context are useful for the users of terminological resources, such resources rarely support context modeling. In this paper, we propose a taxonomy of context primarily based on scope (local and global) and further divided into syntactic, semantic, and pragmatic facets. These facets cover the specification of different types of terminological information, such as predicate-argument structure, collocations, semantic relations, term variants, grammatical and lexical cohesion, communicative situations, subject fields, and cultures.
Specialized Knowledge Representation and the Parameterization of Context
Faber, Pamela
2016-01-01
Though instrumental in numerous disciplines, context has no universally accepted definition. In specialized knowledge resources it is timely and necessary to parameterize context with a view to more effectively facilitating knowledge representation, understanding, and acquisition, the main aims of terminological knowledge bases. This entails distinguishing different types of context as well as how they interact with each other. This is not a simple objective to achieve despite the fact that specialized discourse does not have as many contextual variables as those in general language (i.e., figurative meaning, irony, etc.). Even in specialized text, context is an extremely complex concept. In fact, contextual information can be specified in terms of scope or according to the type of information conveyed. It can be a textual excerpt or a whole document; a pragmatic convention or a whole culture; a concrete situation or a prototypical scenario. Although these versions of context are useful for the users of terminological resources, such resources rarely support context modeling. In this paper, we propose a taxonomy of context primarily based on scope (local and global) and further divided into syntactic, semantic, and pragmatic facets. These facets cover the specification of different types of terminological information, such as predicate-argument structure, collocations, semantic relations, term variants, grammatical and lexical cohesion, communicative situations, subject fields, and cultures. PMID:26941674
Aggregate and individual replication probability within an explicit model of the research process.
Miller, Jeff; Schwarz, Wolf
2011-09-01
We study a model of the research process in which the true effect size, the replication jitter due to changes in experimental procedure, and the statistical error of effect size measurement are all normally distributed random variables. Within this model, we analyze the probability of successfully replicating an initial experimental result by obtaining either a statistically significant result in the same direction or any effect in that direction. We analyze both the probability of successfully replicating a particular experimental effect (i.e., the individual replication probability) and the average probability of successful replication across different studies within some research context (i.e., the aggregate replication probability), and we identify the conditions under which the latter can be approximated using the formulas of Killeen (2005a, 2007). We show how both of these probabilities depend on parameters of the research context that would rarely be known in practice. In addition, we show that the statistical uncertainty associated with the size of an initial observed effect would often prevent accurate estimation of the desired individual replication probability even if these research context parameters were known exactly. We conclude that accurate estimates of replication probability are generally unattainable.
Optical-model abrasion cross sections for high-energy heavy ions
NASA Technical Reports Server (NTRS)
Townsend, L. W.
1981-01-01
Within the context of eikonal scattering theory, a generalized optical model potential approximation to the nucleus-nucleus multiple scattering series is used in an abrasion-ablation collision model to predict abrasion cross sections for relativistic projectile heavy ions. Unlike the optical limit of Glauber theory, which cannot be used for very light nuclei, the abrasion formalism is valid for any projectile target combination at any incident kinetic energy for which eikonal scattering theory can be utilized. Results are compared with experimental results and predictions from Glauber theory.
Incorporating interfacial phenomena in solidification models
NASA Technical Reports Server (NTRS)
Beckermann, Christoph; Wang, Chao Yang
1994-01-01
A general methodology is available for the incorporation of microscopic interfacial phenomena in macroscopic solidification models that include diffusion and convection. The method is derived from a formal averaging procedure and a multiphase approach, and relies on the presence of interfacial integrals in the macroscopic transport equations. In a wider engineering context, these techniques are not new, but their application in the analysis and modeling of solidification processes has largely been overlooked. This article describes the techniques and demonstrates their utility in two examples in which microscopic interfacial phenomena are of great importance.
Solli, Hans Magnus; Barbosa da Silva, António; Egeland, Jens
2015-01-01
To investigate whether adding descriptions of the health factors "ability," "environment" and "intentions/goals" to the officially sanctioned biomedical disability model (BDM) would improve assessments of work ability for social security purposes. The study was based on a theoretical design consisting of textual analysis and interpretation. Two further work ability models were defined: the mixed health model (MHM), which describes health factors without assessing a person's abilities in context, and the ability-based health model (AHM), which assesses abilities in a concrete context of environment and intention. Eighty-six social security certificates, written by psychiatrists and psychology specialists in a Norwegian hospital-based mental health clinic, were analysed in relation to the three work ability/disability models. In certificates based on the BDM, a general pattern was found of "gradual work training". The MHM added health factors, but without linking them together in a concrete way. With the AHM, work ability was assessed in terms of a concrete unified evaluation of the claimant's abilities, environments and intentions/goals. Applying the AHM in work ability assessments, in comparison with the BDM and the MHM, is useful because this foregrounds claimants' abilities in a context of concrete goals and work-related opportunities, as a unity. Implications for Rehabilitation A concept of health should include ability, environment and intentions/goals as components. When all three of these components are described in concrete terms in a work ability assessment, an integrated picture of the individual's abilities in the context of his/her particular intentions/goals and work opportunities comes to the fore. This kind of assessment makes it possible to meet the individual's needs for individual follow-up in a work environment.
Generalized contexts and consistent histories in quantum mechanics
NASA Astrophysics Data System (ADS)
Losada, Marcelo; Laura, Roberto
2014-05-01
We analyze a restriction of the theory of consistent histories by imposing that a valid description of a physical system must include quantum histories which satisfy the consistency conditions for all states. We prove that these conditions are equivalent to imposing the compatibility conditions of our formalism of generalized contexts. Moreover, we show that the theory of consistent histories with the consistency conditions for all states and the formalism of generalized context are equally useful representing expressions which involve properties at different times.
Towards improving software security by using simulation to inform requirements and conceptual design
Nutaro, James J.; Allgood, Glenn O.; Kuruganti, Teja
2015-06-17
We illustrate the use of modeling and simulation early in the system life-cycle to improve security and reduce costs. The models that we develop for this illustration are inspired by problems in reliability analysis and supervisory control, for which similar models are used to quantify failure probabilities and rates. In the context of security, we propose that models of this general type can be used to understand trades between risk and cost while writing system requirements and during conceptual design, and thereby significantly reduce the need for expensive security corrections after a system enters operation
Differences in perceptual learning transfer as a function of training task.
Green, C Shawn; Kattner, Florian; Siegel, Max H; Kersten, Daniel; Schrater, Paul R
2015-01-01
A growing body of research--including results from behavioral psychology, human structural and functional imaging, single-cell recordings in nonhuman primates, and computational modeling--suggests that perceptual learning effects are best understood as a change in the ability of higher-level integration or association areas to read out sensory information in the service of particular decisions. Work in this vein has argued that, depending on the training experience, the "rules" for this read-out can either be applicable to new contexts (thus engendering learning generalization) or can apply only to the exact training context (thus resulting in learning specificity). Here we contrast learning tasks designed to promote either stimulus-specific or stimulus-general rules. Specifically, we compare learning transfer across visual orientation following training on three different tasks: an orientation categorization task (which permits an orientation-specific learning solution), an orientation estimation task (which requires an orientation-general learning solution), and an orientation categorization task in which the relevant category boundary shifts on every trial (which lies somewhere between the two tasks above). While the simple orientation-categorization training task resulted in orientation-specific learning, the estimation and moving categorization tasks resulted in significant orientation learning generalization. The general framework tested here--that task specificity or generality can be predicted via an examination of the optimal learning solution--may be useful in building future training paradigms with certain desired outcomes.
On the formalization of multi-scale and multi-science processes for integrative biology
Díaz-Zuccarini, Vanessa; Pichardo-Almarza, César
2011-01-01
The aim of this work is to introduce the general concept of ‘Bond Graph’ (BG) techniques applied in the context of multi-physics and multi-scale processes. BG modelling has a natural place in these developments. BGs are inherently coherent as the relationships defined between the ‘elements’ of the graph are strictly defined by causality rules and power (energy) conservation. BGs clearly show how power flows between components of the systems they represent. The ‘effort’ and ‘flow’ variables enable bidirectional information flow in the BG model. When the power level of a system is low, BGs degenerate into signal flow graphs in which information is mainly one-dimensional and power is minimal, i.e. they find a natural limitation when dealing with populations of individuals or purely kinetic models, as the concept of energy conservation in these systems is no longer relevant. The aim of this work is twofold: on the one hand, we will introduce the general concept of BG techniques applied in the context of multi-science and multi-scale models and, on the other hand, we will highlight some of the most promising features in the BG methodology by comparing with examples developed using well-established modelling techniques/software that could suggest developments or refinements to the current state-of-the-art tools, by providing a consistent framework from a structural and energetic point of view. PMID:22670211
1. General context view of Express Building, looking northwest with ...
1. General context view of Express Building, looking northwest with railroad tracks in foreground - American Railway Express Company Freight Building, 1060 Northeast Division Street, Bend, Deschutes County, OR
Vigo, Ronaldo; Doan, Karina-Mikayla C; Doan, Charles A; Pinegar, Shannon
2018-02-01
The logic operators (e.g., "and," "or," "if, then") play a fundamental role in concept formation, syntactic construction, semantic expression, and deductive reasoning. In spite of this very general and basic role, there are relatively few studies in the literature that focus on their conceptual nature. In the current investigation, we examine, for the first time, the learning difficulty experienced by observers in classifying members belonging to these primitive "modal concepts" instantiated with sets of acoustic and visual stimuli. We report results from two categorization experiments that suggest the acquisition of acoustic and visual modal concepts is achieved by the same general cognitive mechanism. Additionally, we attempt to account for these results with two models of concept learning difficulty: the generalized invariance structure theory model (Vigo in Cognition 129(1):138-162, 2013, Mathematical principles of human conceptual behavior, Routledge, New York, 2014) and the generalized context model (Nosofsky in J Exp Psychol Learn Mem Cogn 10(1):104-114, 1984, J Exp Psychol 115(1):39-57, 1986).
Generalized role for the cerebellum in encoding internal models: evidence from semantic processing.
Moberget, Torgeir; Gullesen, Eva Hilland; Andersson, Stein; Ivry, Richard B; Endestad, Tor
2014-02-19
The striking homogeneity of cerebellar microanatomy is strongly suggestive of a corresponding uniformity of function. Consequently, theoretical models of the cerebellum's role in motor control should offer important clues regarding cerebellar contributions to cognition. One such influential theory holds that the cerebellum encodes internal models, neural representations of the context-specific dynamic properties of an object, to facilitate predictive control when manipulating the object. The present study examined whether this theoretical construct can shed light on the contribution of the cerebellum to language processing. We reasoned that the cerebellum might perform a similar coordinative function when the context provided by the initial part of a sentence can be highly predictive of the end of the sentence. Using functional MRI in humans we tested two predictions derived from this hypothesis, building on previous neuroimaging studies of internal models in motor control. First, focal cerebellar activation-reflecting the operation of acquired internal models-should be enhanced when the linguistic context leads terminal words to be predictable. Second, more widespread activation should be observed when such predictions are violated, reflecting the processing of error signals that can be used to update internal models. Both predictions were confirmed, with predictability and prediction violations associated with increased blood oxygenation level-dependent signal in the posterior cerebellum (Crus I/II). Our results provide further evidence for cerebellar involvement in predictive language processing and suggest that the notion of cerebellar internal models may be extended to the language domain.
Operational method of solution of linear non-integer ordinary and partial differential equations.
Zhukovsky, K V
2016-01-01
We propose operational method with recourse to generalized forms of orthogonal polynomials for solution of a variety of differential equations of mathematical physics. Operational definitions of generalized families of orthogonal polynomials are used in this context. Integral transforms and the operational exponent together with some special functions are also employed in the solutions. The examples of solution of physical problems, related to such problems as the heat propagation in various models, evolutional processes, Black-Scholes-like equations etc. are demonstrated by the operational technique.
Constraints on deviations from ΛCDM within Horndeski gravity
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bellini, Emilio; Cuesta, Antonio J.; Jimenez, Raul
2016-02-01
Recent anomalies found in cosmological datasets such as the low multipoles of the Cosmic Microwave Background or the low redshift amplitude and growth of clustering measured by e.g., abundance of galaxy clusters and redshift space distortions in galaxy surveys, have motivated explorations of models beyond standard ΛCDM. Of particular interest are models where general relativity (GR) is modified on large cosmological scales. Here we consider deviations from ΛCDM+GR within the context of Horndeski gravity, which is the most general theory of gravity with second derivatives in the equations of motion. We adopt a parametrization in which the four additional Horndeskimore » functions of time α{sub i}(t) are proportional to the cosmological density of dark energy Ω{sub DE}(t). Constraints on this extended parameter space using a suite of state-of-the art cosmological observations are presented for the first time. Although the theory is able to accommodate the low multipoles of the Cosmic Microwave Background and the low amplitude of fluctuations from redshift space distortions, we find no significant tension with ΛCDM+GR when performing a global fit to recent cosmological data and thus there is no evidence against ΛCDM+GR from an analysis of the value of the Bayesian evidence ratio of the modified gravity models with respect to ΛCDM, despite introducing extra parameters. The posterior distribution of these extra parameters that we derive return strong constraints on any possible deviations from ΛCDM+GR in the context of Horndeski gravity. We illustrate how our results can be applied to a more general frameworks of modified gravity models.« less
Rodwell, John; Munro, Louise
2013-11-01
To present a novel approach to nurse stress by exploring the demand-control-support model with organisational justice through the lens of relational regulation theory. Nursing is often stressful due to high demands and dissatisfaction with pay, which impacts the mental well-being and productivity of nurses. A cross-sectional design. A validated questionnaire was sent to the work addresses of all nursing and midwifery staff in a medium-sized general acute hospital in Australia. A total of 190 nurses and midwives returned completed questionnaires for the analyses. The multiple regression analyses demonstrated that the model applies to the prototypical context of a general acute hospital and that job control, supervisor support and outside work support improve the job satisfaction and mental health of nurses. Most importantly, supervisor support was found to buffer the impact of excessive work demands. Fairness of procedures, distribution of resources and the quality and consistency of information are also beneficial. Relational regulation theory is applied to these findings as a novel way to conceptualise the mechanisms of support and fairness in nursing. The importance of nurses' well-being and job satisfaction is a priority for improving clinical outcomes. Practically, this means nurse managers should be encouraging nurses in the pursuit of diverse relational activities both at work and outside work. © 2013 John Wiley & Sons Ltd.
Decomposability and scalability in space-based observatory scheduling
NASA Technical Reports Server (NTRS)
Muscettola, Nicola; Smith, Stephen F.
1992-01-01
In this paper, we discuss issues of problem and model decomposition within the HSTS scheduling framework. HSTS was developed and originally applied in the context of the Hubble Space Telescope (HST) scheduling problem, motivated by the limitations of the current solution and, more generally, the insufficiency of classical planning and scheduling approaches in this problem context. We first summarize the salient architectural characteristics of HSTS and their relationship to previous scheduling and AI planning research. Then, we describe some key problem decomposition techniques supported by HSTS and underlying our integrated planning and scheduling approach, and we discuss the leverage they provide in solving space-based observatory scheduling problems.
A model for indexing medical documents combining statistical and symbolic knowledge.
Avillach, Paul; Joubert, Michel; Fieschi, Marius
2007-10-11
To develop and evaluate an information processing method based on terminologies, in order to index medical documents in any given documentary context. We designed a model using both symbolic general knowledge extracted from the Unified Medical Language System (UMLS) and statistical knowledge extracted from a domain of application. Using statistical knowledge allowed us to contextualize the general knowledge for every particular situation. For each document studied, the extracted terms are ranked to highlight the most significant ones. The model was tested on a set of 17,079 French standardized discharge summaries (SDSs). The most important ICD-10 term of each SDS was ranked 1st or 2nd by the method in nearly 90% of the cases. The use of several terminologies leads to more precise indexing. The improvement achieved in the models implementation performances as a result of using semantic relationships is encouraging.
Bounded rationality alters the dynamics of paediatric immunization acceptance.
Oraby, Tamer; Bauch, Chris T
2015-06-02
Interactions between disease dynamics and vaccinating behavior have been explored in many coupled behavior-disease models. Cognitive effects such as risk perception, framing, and subjective probabilities of adverse events can be important determinants of the vaccinating behaviour, and represent departures from the pure "rational" decision model that are often described as "bounded rationality". However, the impact of such cognitive effects in the context of paediatric infectious disease vaccines has received relatively little attention. Here, we develop a disease-behavior model that accounts for bounded rationality through prospect theory. We analyze the model and compare its predictions to a reduced model that lacks bounded rationality. We find that, in general, introducing bounded rationality increases the dynamical richness of the model and makes it harder to eliminate a paediatric infectious disease. In contrast, in other cases, a low cost, highly efficacious vaccine can be refused, even when the rational decision model predicts acceptance. Injunctive social norms can prevent vaccine refusal, if vaccine acceptance is sufficiently high in the beginning of the vaccination campaign. Cognitive processes can have major impacts on the predictions of behaviour-disease models, and further study of such processes in the context of vaccination is thus warranted.
Bounded rationality alters the dynamics of paediatric immunization acceptance
Oraby, Tamer; Bauch, Chris T.
2015-01-01
Interactions between disease dynamics and vaccinating behavior have been explored in many coupled behavior-disease models. Cognitive effects such as risk perception, framing, and subjective probabilities of adverse events can be important determinants of the vaccinating behaviour, and represent departures from the pure “rational” decision model that are often described as “bounded rationality”. However, the impact of such cognitive effects in the context of paediatric infectious disease vaccines has received relatively little attention. Here, we develop a disease-behavior model that accounts for bounded rationality through prospect theory. We analyze the model and compare its predictions to a reduced model that lacks bounded rationality. We find that, in general, introducing bounded rationality increases the dynamical richness of the model and makes it harder to eliminate a paediatric infectious disease. In contrast, in other cases, a low cost, highly efficacious vaccine can be refused, even when the rational decision model predicts acceptance. Injunctive social norms can prevent vaccine refusal, if vaccine acceptance is sufficiently high in the beginning of the vaccination campaign. Cognitive processes can have major impacts on the predictions of behaviour-disease models, and further study of such processes in the context of vaccination is thus warranted. PMID:26035413
NASA Astrophysics Data System (ADS)
Efstratiou, P.
2013-09-01
This presentation will be based on my, undergraduate, thesis at Aristotle University of Thessoliniki with the same subject, supervised by Professor Demetrios Papadopoulos. I will first present the general mathematical formulation of the Chern-Simons (CS) modified gravity, which is split in a dynamical and a non-dynamical context, and the different physical theories which suggest this modification. Then proceed by examing the possibility that the CS theory shares solutions with General Relativity in both contexts. In the non-dynamical context I will present a new, undocumented solution as well as all the other possible solutions found to date. I will conclude by arguing that General Relativity and CS Theory share any solutions in the dynamical context.
Low-fidelity bench models for basic surgical skills training during undergraduate medical education.
Denadai, Rafael; Saad-Hossne, Rogério; Todelo, Andréia Padilha; Kirylko, Larissa; Souto, Luís Ricardo Martinhão
2014-01-01
It is remarkable the reduction in the number of medical students choosing general surgery as a career. In this context, new possibilities in the field of surgical education should be developed to combat this lack of interest. In this study, a program of surgical training based on learning with models of low-fidelity bench is designed as a complementary alternative to the various methodologies in the teaching of basic surgical skills during medical education, and to develop personal interests in career choice.
Skin mechanical properties and modeling: A review.
Joodaki, Hamed; Panzer, Matthew B
2018-04-01
The mechanical properties of the skin are important for various applications. Numerous tests have been conducted to characterize the mechanical behavior of this tissue, and this article presents a review on different experimental methods used. A discussion on the general mechanical behavior of the skin, including nonlinearity, viscoelasticity, anisotropy, loading history dependency, failure properties, and aging effects, is presented. Finally, commonly used constitutive models for simulating the mechanical response of skin are discussed in the context of representing the empirically observed behavior.
A scheme for parameterizing ice cloud water content in general circulation models
NASA Technical Reports Server (NTRS)
Heymsfield, Andrew J.; Donner, Leo J.
1989-01-01
A method for specifying ice water content in GCMs is developed, based on theory and in-cloud measurements. A theoretical development of the conceptual precipitation model is given and the aircraft flights used to characterize the ice mass distribution in deep ice clouds is discussed. Ice water content values derived from the theoretical parameterization are compared with the measured values. The results demonstrate that a simple parameterization for atmospheric ice content can account for ice contents observed in several synoptic contexts.
Two approaches to forecast Ebola synthetic epidemics.
Champredon, David; Li, Michael; Bolker, Benjamin M; Dushoff, Jonathan
2018-03-01
We use two modelling approaches to forecast synthetic Ebola epidemics in the context of the RAPIDD Ebola Forecasting Challenge. The first approach is a standard stochastic compartmental model that aims to forecast incidence, hospitalization and deaths among both the general population and health care workers. The second is a model based on the renewal equation with latent variables that forecasts incidence in the whole population only. We describe fitting and forecasting procedures for each model and discuss their advantages and drawbacks. We did not find that one model was consistently better in forecasting than the other. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Ortega-Rodríguez, M.; Solís-Sánchez, H.; López-Barquero, V.; Matamoros-Alvarado, B.; Venegas-Li, A.
2014-06-01
We propose a simple toy model to explain the 2:3:6 quasi-periodic oscillation (QPO) structure in GRS 1915+105 and, more generally, the 2:3 QPO structure in XTE J1550-564, GRO J1655-40 and H1743-322. The model exploits the onset of subharmonics in the context of discoseismology. We suggest that the observed frequencies may be the consequence of a resonance between a fundamental g mode and an unobservable p wave. The results include the prediction that, as better data become available, a QPO with a frequency of twice the higher twin frequency and a large quality factor will be observed in twin peak sources, as it might already have been observed in the especially active GRS 1915+105.
The (Mathematical) Modeling Process in Biosciences.
Torres, Nestor V; Santos, Guido
2015-01-01
In this communication, we introduce a general framework and discussion on the role of models and the modeling process in the field of biosciences. The objective is to sum up the common procedures during the formalization and analysis of a biological problem from the perspective of Systems Biology, which approaches the study of biological systems as a whole. We begin by presenting the definitions of (biological) system and model. Particular attention is given to the meaning of mathematical model within the context of biology. Then, we present the process of modeling and analysis of biological systems. Three stages are described in detail: conceptualization of the biological system into a model, mathematical formalization of the previous conceptual model and optimization and system management derived from the analysis of the mathematical model. All along this work the main features and shortcomings of the process are analyzed and a set of rules that could help in the task of modeling any biological system are presented. Special regard is given to the formative requirements and the interdisciplinary nature of this approach. We conclude with some general considerations on the challenges that modeling is posing to current biology.
Sex Differences in the Generalization of Fear as a Function of Retention Intervals
ERIC Educational Resources Information Center
Lynch, Joseph, III; Cullen, Patrick K.; Jasnow, Aaron M.; Riccio, David C.
2013-01-01
In previous studies using male rodents, context change disrupted a fear response at a short, but not a long, retention interval. Here, we examined the effects of context changes on fear responses as a function of time in male and female rats. Males displayed context discrimination at all intervals, whereas females exhibited generalization by 5 d.…
Observations and Modeling of the Transient General Circulation of the North Pacific Basin
NASA Technical Reports Server (NTRS)
McWilliams, James C.
2000-01-01
Because of recent progress in satellite altimetry and numerical modeling and the accumulation and archiving of long records of hydrographic and meteorological variables, it is becoming feasible to describe and understand the transient general circulation of the ocean (i.e., variations with spatial scales larger than a few hundred kilometers and time scales of seasonal and longer-beyond the mesoscale). We have carried out various studies in investigation of the transient general circulation of the Pacific Ocean from a coordinated analysis of satellite altimeter data, historical hydrographic gauge data, scatterometer wind observations, reanalyzed operational wind fields, and a variety of ocean circulation models. Broadly stated, our goal was to achieve a phenomenological catalogue of different possible types of large-scale, low-frequency variability, as a context for understanding the observational record. The approach is to identify the simplest possible model from which particular observed phenomena can be isolated and understood dynamically and then to determine how well these dynamical processes are represented in more complex Oceanic General Circulation Models (OGCMs). Research results have been obtained on Rossby wave propagation and transformation, oceanic intrinsic low-frequency variability, effects of surface gravity waves, pacific data analyses, OGCM formulation and developments, and OGCM simulations of forced variability.
Open source and open content: A framework for global collaboration in social-ecological research
Charles Schweik; Tom Evans; J. Morgan Grove
2005-01-01
This paper discusses opportunities for alternative collaborative approaches for social-ecological research in general and, in this context, for modeling land-use/land-cover change. In this field, the rate of progress in academic research is steady but perhaps not as rapid or efficient as might be possible with alternative organizational frameworks. The convergence of...
ERIC Educational Resources Information Center
Haezendonck, Elvira; Willems, Kim; Hillemann, Jenny
2017-01-01
Universities, and higher education institutions in general, are ever more influenced by output-driven performance indicators and models that originally stem from the profit-organisational context. As a result, universities are increasingly considering management tools that support them in the (decision) process for attaining their strategic goals.…
ERIC Educational Resources Information Center
Gregory, Eve; Ruby, Mahera; Kenner, Charmian
2010-01-01
Studies on child development in cross-cultural contexts generally contrast child-rearing practices in traditional or non-Western with those of Western societies. Thus, they show how non-Western communities tend to emphasise the importance of interdependence and collectivism between family and group members; Western communities focus rather on the…
ERIC Educational Resources Information Center
Tekleselassie, Abebayehu; Mallery, Coretta; Choi, Jaehwa
2013-01-01
National reports recognize a growing gender gap in postsecondary enrollment as a major challenge impacting the lives of young men, particularly African Americans. Previous gender and race specific research is largely inconclusive. It is, for example, unclear from previous research how persistent the gender gap is across various school contexts,…
ERIC Educational Resources Information Center
Gustafsson, Peter; Jonsson, Gunnar; Enghag, Margareta
2015-01-01
The problem-solving process is investigated for five groups of students when solving context-rich problems in an introductory physics course included in an engineering programme. Through transcripts of their conversation, the paths in the problem-solving process have been traced and related to a general problem-solving model. All groups exhibit…
ERIC Educational Resources Information Center
Harris, Karen R.; Lane, Kathleen Lynne; Driscoll, Steven A.; Graham, Steve; Wilson, Kristen; Sandmel, Karin; Brindle, Mary; Schatschneider, Chris
2012-01-01
This study took place in the context of schools collaborating with a local university to implement an evidence-based, 3-tiered model of prevention and supports targeting academic, behavioral, and social goals. We examined whether Self-Regulated Strategy Development (SRSD) instruction, delivered by grade 2 and 3 general education teachers to all…
General view of building in context showing row of residences ...
General view of building in context showing row of residences on Canfield Avenue, facing northwest. - Albrook Air Force Station, Company Officer's Quarters, East side of Canfield Avenue, Balboa, Former Panama Canal Zone, CZ
General view of building in context showing row of residences ...
General view of building in context showing row of residences adjacent to golf course, facing northeast. - Marine Barracks, Panama Canal, Officers' Quarters, 800' West of Bruja Road, Balboa, Former Panama Canal Zone, CZ
Minnis, Helen; Bryce, Graham; Phin, Louise; Wilson, Phil
2010-10-01
Children in care have higher rates of mental health problems than the general population and placement instability contributes to this. Children are both most vulnerable to the effects of poor quality care and most responsive to treatment in the early weeks and months of life yet, in the UK, permanency decisions are generally not in place until around the age of four. We aimed to understand the components of an innovative system for assessing and intervening with maltreated children and their families developed in New Orleans and to consider how it might be implemented in Glasgow, UK. During and after a visit to New Orleans by a team of Glasgow practitioners, eight key interviews and meetings with New Orleans and Glasgow staff were audio-recorded. Qualitative analysis of verbatim transcripts identified key themes. Themes highlighted shared aspects of the context and attitudes of the two teams, identified gaps in the Glasgow service and steps that would be needed to implement a version of the New Orleans model in Glasgow. Our discussions with the New Orleans team have highlighted concrete steps we can take, in Glasgow, to make better decision-making for vulnerable children a reality.
The Predictive Validity of Savry Ratings for Assessing Youth Offenders in Singapore
Chu, Chi Meng; Goh, Mui Leng; Chong, Dominic
2015-01-01
Empirical support for the usage of the SAVRY has been reported in studies conducted in many Western contexts, but not in a Singaporean context. This study compared the predictive validity of the SAVRY ratings for violent and general recidivism against the Youth Level of Service/Case Management Inventory (YLS/CMI) ratings within the Singaporean context. Using a sample of 165 male young offenders (Mfollow-up = 4.54 years), results showed that the SAVRY Total Score and Summary Risk Rating, as well as YLS/CMI Total Score and Overall Risk Rating, predicted violent and general recidivism. SAVRY Protective Total Score was only significantly predictive of desistance from general recidivism, and did not show incremental predictive validity for violent and general recidivism over the SAVRY Total Score. Overall, the results suggest that the SAVRY is suited (to varying degrees) for assessing the risk of violent and general recidivism in young offenders within the Singaporean context, but might not be better than the YLS/CMI. PMID:27231403
Context-Aware Recommender Systems
NASA Astrophysics Data System (ADS)
Adomavicius, Gediminas; Tuzhilin, Alexander
The importance of contextual information has been recognized by researchers and practitioners in many disciplines, including e-commerce personalization, information retrieval, ubiquitous and mobile computing, data mining, marketing, and management. While a substantial amount of research has already been performed in the area of recommender systems, most existing approaches focus on recommending the most relevant items to users without taking into account any additional contextual information, such as time, location, or the company of other people (e.g., for watching movies or dining out). In this chapter we argue that relevant contextual information does matter in recommender systems and that it is important to take this information into account when providing recommendations. We discuss the general notion of context and how it can be modeled in recommender systems. Furthermore, we introduce three different algorithmic paradigms - contextual prefiltering, post-filtering, and modeling - for incorporating contextual information into the recommendation process, discuss the possibilities of combining several contextaware recommendation techniques into a single unifying approach, and provide a case study of one such combined approach. Finally, we present additional capabilities for context-aware recommenders and discuss important and promising directions for future research.
Yuan, Robin K; Hebert, Jenna C; Thomas, Arthur S; Wann, Ellen G; Muzzio, Isabel A
2015-01-01
Although predator odors are ethologically relevant stimuli for rodents, the molecular pathways and contribution of some brain regions involved in predator odor conditioning remain elusive. Inhibition of histone deacetylases (HDACs) in the dorsal hippocampus has been shown to enhance shock-induced contextual fear learning, but it is unknown if HDACs have differential effects along the dorso-ventral hippocampal axis during predator odor fear learning. We injected MS-275, a class I HDAC inhibitor, bilaterally in the dorsal or ventral hippocampus of mice and found that it had no effects on innate anxiety in either region. We then assessed the effects of MS-275 at different stages of fear learning along the longitudinal hippocampal axis. Animals were injected with MS-275 or vehicle after context pre-exposure (pre-conditioning injections), when a representation of the context is first formed, or after exposure to coyote urine (post-conditioning injections), when the context becomes associated with predator odor. When MS-275 was administered after context pre-exposure, dorsally injected animals showed enhanced fear in the training context but were able to discriminate it from a neutral environment. Conversely, ventrally injected animals did not display enhanced learning in the training context but generalized the fear response to a neutral context. However, when MS-275 was administered after conditioning, there were no differences between the MS-275 and vehicle control groups in either the dorsal or ventral hippocampus. Surprisingly, all groups displayed generalization to a neutral context, suggesting that predator odor exposure followed by a mild stressor such as restraint leads to fear generalization. These results may elucidate distinct functions of the dorsal and ventral hippocampus in predator odor-induced fear conditioning as well as some of the molecular mechanisms underlying fear generalization.
Efficient numerical modeling of the cornea, and applications
NASA Astrophysics Data System (ADS)
Gonzalez, L.; Navarro, Rafael M.; Hdez-Matamoros, J. L.
2004-10-01
Corneal topography has shown to be an essential tool in the ophthalmology clinic both in diagnosis and custom treatments (refractive surgery, keratoplastia), having also a strong potential in optometry. The post processing and analysis of corneal elevation, or local curvature data, is a necessary step to refine the data and also to extract relevant information for the clinician. In this context a parametric cornea model is proposed consisting of a surface described mathematically by two terms: one general ellipsoid corresponding to a regular base surface, expressed by a general quadric term located at an arbitrary position and free orientation in 3D space and a second term, described by a Zernike polynomial expansion, which accounts for irregularities and departures from the basic geometry. The model has been validated obtaining better adjustment of experimental data than other previous models. Among other potential applications, here we present the determination of the optical axis of the cornea by transforming the general quadric to its canonical form. This has permitted us to perform 3D registration of corneal topographical maps to improve the signal-to-noise ratio. Other basic and clinical applications are also explored.
Hoffmann, Falk-Martin; Fazi, Filippo Maria; Williams, Earl G; Fontana, Simone
2017-09-01
In this work an expression for the solution of the Helmholtz equation for wedge spaces is derived. Such propagation spaces represent scenarios for many acoustical problems where a free field assumption is not eligible. The proposed sound field model is derived from the general solution of the wave equation in cylindrical coordinates, using sets of orthonormal basis functions. The latter are modified to satisfy several boundary conditions representing the reflective behaviour of wedge-shaped propagation spaces. This formulation is then used in the context of nearfield acoustical holography (NAH) and to obtain the expression of the Neumann Green function. The model and its suitability for NAH is demonstrated through both numerical simulations and measured data, where the latter was acquired for the specific case of a loudspeaker on a hemi-cylindrical rigid baffle.
NASA Astrophysics Data System (ADS)
Zeng, Jicai; Zha, Yuanyuan; Zhang, Yonggen; Shi, Liangsheng; Zhu, Yan; Yang, Jinzhong
2017-11-01
Multi-scale modeling of the localized groundwater flow problems in a large-scale aquifer has been extensively investigated under the context of cost-benefit controversy. An alternative is to couple the parent and child models with different spatial and temporal scales, which may result in non-trivial sub-model errors in the local areas of interest. Basically, such errors in the child models originate from the deficiency in the coupling methods, as well as from the inadequacy in the spatial and temporal discretizations of the parent and child models. In this study, we investigate the sub-model errors within a generalized one-way coupling scheme given its numerical stability and efficiency, which enables more flexibility in choosing sub-models. To couple the models at different scales, the head solution at parent scale is delivered downward onto the child boundary nodes by means of the spatial and temporal head interpolation approaches. The efficiency of the coupling model is improved either by refining the grid or time step size in the parent and child models, or by carefully locating the sub-model boundary nodes. The temporal truncation errors in the sub-models can be significantly reduced by the adaptive local time-stepping scheme. The generalized one-way coupling scheme is promising to handle the multi-scale groundwater flow problems with complex stresses and heterogeneity.
The importance of source and cue type in time-based everyday prospective memory.
Oates, Joyce M; Peynircioğlu, Zehra F
2014-01-01
We examined the effects of the source of a prospective memory task (provided or generated) and the type of cue (specific or general) triggering that task in everyday settings. Participants were asked to complete both generated and experimenter-provided tasks and to send a text message when each task was completed. The cue/context for the to-be-completed tasks was either a specific time or a general deadline (time-based cue), and the cue/context for the texting task was the completion of the task itself (activity-based cue). Although generated tasks were completed more often, generated cues/contexts were no more effective than provided ones in triggering the intention. Furthermore, generated tasks were completed more often when the cue/context comprised a specific time, whereas provided tasks were completed more often when the cue/context comprised a general deadline. However, texting was unaffected by the source of the cue/context. Finally, emotion modulated the effects. Results are discussed within a process-driven framework.
Mass Function of Galaxy Clusters in Relativistic Inhomogeneous Cosmology
NASA Astrophysics Data System (ADS)
Ostrowski, Jan J.; Buchert, Thomas; Roukema, Boudewijn F.
The current cosmological model (ΛCDM) with the underlying FLRW metric relies on the assumption of local isotropy, hence homogeneity of the Universe. Difficulties arise when one attempts to justify this model as an average description of the Universe from first principles of general relativity, since in general, the Einstein tensor built from the averaged metric is not equal to the averaged stress-energy tensor. In this context, the discrepancy between these quantities is called "cosmological backreaction" and has been the subject of scientific debate among cosmologists and relativists for more than 20 years. Here we present one of the methods to tackle this problem, i.e. averaging the scalar parts of the Einstein equations, together with its application, the cosmological mass function of galaxy clusters.
Error suppression for Hamiltonian quantum computing in Markovian environments
NASA Astrophysics Data System (ADS)
Marvian, Milad; Lidar, Daniel A.
2017-03-01
Hamiltonian quantum computing, such as the adiabatic and holonomic models, can be protected against decoherence using an encoding into stabilizer subspace codes for error detection and the addition of energy penalty terms. This method has been widely studied since it was first introduced by Jordan, Farhi, and Shor (JFS) in the context of adiabatic quantum computing. Here, we extend the original result to general Markovian environments, not necessarily in Lindblad form. We show that the main conclusion of the original JFS study holds under these general circumstances: Assuming a physically reasonable bath model, it is possible to suppress the initial decay out of the encoded ground state with an energy penalty strength that grows only logarithmically in the system size, at a fixed temperature.
Exact general relativistic disks with magnetic fields
NASA Astrophysics Data System (ADS)
Letelier, Patricio S.
1999-11-01
The well-known ``displace, cut, and reflect'' method used to generate cold disks from given solutions of Einstein equations is extended to solutions of Einstein-Maxwell equations. Four exact solutions of the these last equations are used to construct models of hot disks with surface density, azimuthal pressure, and azimuthal current. The solutions are closely related to Kerr, Taub-NUT, Lynden-Bell-Pinault, and to a one-soliton solution. We find that the presence of the magnetic field can change in a nontrivial way the different properties of the disks. In particular, the pure general relativistic instability studied by Bic̆ák, Lynden-Bell, and Katz [Phys. Rev. D 47, 4334 (1993)] can be enhanced or cured by different distributions of currents inside the disk. These currents, outside the disk, generate a variety of axial symmetric magnetic fields. As far as we know these are the first models of hot disks studied in the context of general relativity.
The Power Prior: Theory and Applications
Ibrahim, Joseph G.; Chen, Ming-Hui; Gwon, Yeongjin; Chen, Fang
2015-01-01
The power prior has been widely used in many applications covering a large number of disciplines. The power prior is intended to be an informative prior constructed from historical data. It has been used in clinical trials, genetics, health care, psychology, environmental health, engineering, economics, and business. It has also been applied for a wide variety of models and settings, both in the experimental design and analysis contexts. In this review article, we give an A to Z exposition of the power prior and its applications to date. We review its theoretical properties, variations in its formulation, statistical contexts for which it has been used, applications, and its advantages over other informative priors. We review models for which it has been used, including generalized linear models, survival models, and random effects models. Statistical areas where the power prior has been used include model selection, experimental design, hierarchical modeling, and conjugate priors. Prequentist properties of power priors in posterior inference are established and a simulation study is conducted to further examine the empirical performance of the posterior estimates with power priors. Real data analyses are given illustrating the power prior as well as the use of the power prior in the Bayesian design of clinical trials. PMID:26346180
2. General context view of Express Building, looking northeast, with ...
2. General context view of Express Building, looking northeast, with Division Street in foreground, showing relationship to the Bend Depot - American Railway Express Company Freight Building, 1060 Northeast Division Street, Bend, Deschutes County, OR
General and gay-related racism experienced by Latino gay men.
Ibañez, Gladys E; Van Oss Marin, Barbara; Flores, Stephen A; Millett, Gregorio; Diaz, Rafael M
2009-07-01
Latino gay men report experiences of racial discrimination within and outside the gay community. This study focused on correlates of racism within general and gay contexts. Racism was assessed in a probability sample of 911 Latino gay men recruited from 3 U.S. cities. Factor analysis of the 10-item scale produced 2 factors: (a) General Racism Experiences, and (b) Racism Experiences in Gay Contexts. The scale and each factor showed adequate reliability and validity. Latino gay men with darker skin, more Indian features, more time in the United States, and low self-esteem reported more racism in both general and gay contexts. The authors examine the psychometric properties of a measure that assesses interpersonal racism among Latinos, report correlates of racism within a gay context, and provide an assessment tool for understanding the role of racism in the lives of Latino gay men.
Gao, Meng; Lengersdorf, Daniel; Stüttgen, Maik C; Güntürkün, Onur
2018-05-02
Extinction learning is an essential mechanism that enables constant adaptation to ever-changing environmental conditions. The underlying neural circuit is mostly studied with rodent models using auditory cued fear conditioning. In order to uncover the variant and the invariant neural properties of extinction learning, we adopted pigeons as an animal model in an appetitive sign-tracking paradigm. The animals firstly learned to respond to two conditioned stimuli in two different contexts (CS-1 in context A and CS-2 in context B), before conditioned responses to the stimuli were extinguished in the opposite contexts (CS-1 in context B and CS-2 in context A). Subsequently, responding to both stimuli was tested in both contexts. Prior to extinction training, we locally injected the N-methyl-d-aspartate receptor (NMDAR) antagonist 2-Amino-5-phosphonovaleric acid (APV) in either the amygdala or the (pre)motor arcopallium to investigate their involvement in extinction learning. Our findings suggest that the encoding of extinction memory required the activation of amygdala, as visible by an impairment of extinction acquisition by concurrent inactivation of local NMDARs. In contrast, consolidation and subsequent retrieval of extinction memory recruited the (pre)motor arcopallium. Also, the inactivation of arcopallial NMDARs induced a general motoric slowing during extinction training. Thus, our results reveal a double dissociation between arcopallium and amygdala with respect to acquisition and consolidation of extinction, respectively. Our study therefore provides new insights on the two key components of the avian extinction network and their resemblance to the data obtained from mammals, possibly indicating a shared neural mechanism underlying extinction learning shaped by evolution. Copyright © 2018 Elsevier B.V. All rights reserved.
ERIC Educational Resources Information Center
Ellwanger, Steven J.
2007-01-01
This article enhances our knowledge of general strain theory (GST) by applying it to the context of traffic delinquency. It does so by first describing and confirming the development of a social-psychological measure allowing for a test of GST. Structural regression analysis is subsequently employed to test the theory within this context across a…
ERIC Educational Resources Information Center
Biedenkapp, Joseph C.; Rudy, Jerry W.
2007-01-01
Contextual fear conditioning was maintained over a 15-day retention interval suggesting no forgetting of the conditioning experience. However, a more subtle generalization test revealed that, as the retention interval increased, rats showed enhanced generalized fear to an altered context. Preexposure to the training context prior to conditioning,…
Social Salience Discriminates Learnability of Contextual Cues in an Artificial Language.
Rácz, Péter; Hay, Jennifer B; Pierrehumbert, Janet B
2017-01-01
We investigate the learning of contextual meaning by adults in an artificial language. Contextual meaning here refers to the non-denotative contextual information that speakers attach to a linguistic construction. Through a series of short games, played online, we test how well adults can learn different contextual meanings for a word-formation pattern in an artificial language. We look at whether learning contextual meanings depends on the social salience of the context, whether our players interpret these contexts generally, and whether the learned meaning is generalized to new words. Our results show that adults are capable of learning contextual meaning if the context is socially salient, coherent, and interpretable. Once a contextual meaning is recognized, it is readily generalized to related forms and contexts.
The Effect of Realistic Contexts on Ontological Judgments of Novel Entities
Van Reet, Jennifer; Pinkham, Ashley M.; Lillard, Angeline S.
2014-01-01
Although a great deal of research has focused on ontological judgments in preschoolers, very little has examined ontological judgments in older children. The present study asked 10-year-olds and adults (N = 94) to judge the reality status of known real, known imagined, and novel entities presented in simple and elaborate contexts and to explain their judgments. Although judgments were generally apt, participants were more likely to endorse imagined and novel entities when the entities were presented in elaborate contexts. When asked to explain their reasoning, participants at both ages cited firsthand experience for real entities and general knowledge for imagined entities. For novel entities, participants referred most to indirect experiences when entities were presented in simple contexts and to general knowledge when those entities were presented in elaborate contexts. These results suggest that rich contextual information continues to be an important influence on ontological judgments past the preschool years. PMID:25914442
The Effect of Realistic Contexts on Ontological Judgments of Novel Entities.
Van Reet, Jennifer; Pinkham, Ashley M; Lillard, Angeline S
2015-01-01
Although a great deal of research has focused on ontological judgments in preschoolers, very little has examined ontological judgments in older children. The present study asked 10-year-olds and adults (N = 94) to judge the reality status of known real, known imagined, and novel entities presented in simple and elaborate contexts and to explain their judgments. Although judgments were generally apt, participants were more likely to endorse imagined and novel entities when the entities were presented in elaborate contexts. When asked to explain their reasoning, participants at both ages cited firsthand experience for real entities and general knowledge for imagined entities. For novel entities, participants referred most to indirect experiences when entities were presented in simple contexts and to general knowledge when those entities were presented in elaborate contexts. These results suggest that rich contextual information continues to be an important influence on ontological judgments past the preschool years.
NASA Astrophysics Data System (ADS)
Tang, F. R.; Zhang, Rong; Li, Huichao; Li, C. N.; Liu, Wei; Bai, Long
2018-05-01
The trade-off criterion is used to systemically investigate the performance features of two chemical engine models (the low-dissipation model and the endoreversible model). The optimal efficiencies, the dissipation ratios, and the corresponding ratios of the dissipation rates for two models are analytically determined. Furthermore, the performance properties of two kinds of chemical engines are precisely compared and analyzed, and some interesting physics is revealed. Our investigations show that the certain universal equivalence between two models is within the framework of the linear irreversible thermodynamics, and their differences are rooted in the different physical contexts. Our results can contribute to a precise understanding of the general features of chemical engines.
Sumaedi, Sik; Bakti, I Gede Mahatma Yuda; Rakhmawati, Tri; Astrini, Nidya Judhi; Yarmen, Medi; Widianti, Tri
2015-07-06
This study aims to investigate the simultaneous effect of subjective norm, perceived behavioral control and trust on patient loyalty. The empirical data were collected through survey. The respondents of the survey are 157 patients of a health-care service institution in Bogor, Indonesia. Multiple regressions analysis was performed to test the conceptual model and the proposed hypotheses. The findings showed that subjective norm and trust influence patient loyalty positively. However, this research also found that perceived behavioral control does not influence patient loyalty significantly. The survey was only conducted at one health-care service institution in Bogor, Indonesia. In addition, convenience sampling method was used. These conditions may cause that the research results can not be generalized to the other contexts. Therefore, replication research is needed to test the stability of the findings in the other contexts. Health-care service institutions need to pay attention to trust and subjective norm to establish patient loyalty. This study is believed to be the first to develop and test patient loyalty model that includes subjective norm, perceived behavioral control and trust.
The Gtr-Model a Universal Framework for Quantum-Like Measurements
NASA Astrophysics Data System (ADS)
Aerts, Diederik; Bianchi, Massimiliano Sassoli De
We present a very general geometrico-dynamical description of physical or more abstract entities, called the general tension-reduction (GTR) model, where not only states, but also measurement-interactions can be represented, and the associated outcome probabilities calculated. Underlying the model is the hypothesis that indeterminism manifests as a consequence of unavoidable uctuations in the experimental context, in accordance with the hidden-measurements interpretation of quantum mechanics. When the structure of the state space is Hilbertian, and measurements are of the universal kind, i.e., are the result of an average over all possible ways of selecting an outcome, the GTR-model provides the same predictions of the Born rule, and therefore provides a natural completed version of quantum mechanics. However, when the structure of the state space is non-Hilbertian and/or not all possible ways of selecting an outcome are available to be actualized, the predictions of the model generally differ from the quantum ones, especially when sequential measurements are considered. Some paradigmatic examples will be discussed, taken from physics and human cognition. Particular attention will be given to some known psychological effects, like question order effects and response replicability, which we show are able to generate non-Hilbertian statistics. We also suggest a realistic interpretation of the GTR-model, when applied to human cognition and decision, which we think could become the generally adopted interpretative framework in quantum cognition research.
Leveraging prognostic baseline variables to gain precision in randomized trials
Colantuoni, Elizabeth; Rosenblum, Michael
2015-01-01
We focus on estimating the average treatment effect in a randomized trial. If baseline variables are correlated with the outcome, then appropriately adjusting for these variables can improve precision. An example is the analysis of covariance (ANCOVA) estimator, which applies when the outcome is continuous, the quantity of interest is the difference in mean outcomes comparing treatment versus control, and a linear model with only main effects is used. ANCOVA is guaranteed to be at least as precise as the standard unadjusted estimator, asymptotically, under no parametric model assumptions and also is locally semiparametric efficient. Recently, several estimators have been developed that extend these desirable properties to more general settings that allow any real-valued outcome (e.g., binary or count), contrasts other than the difference in mean outcomes (such as the relative risk), and estimators based on a large class of generalized linear models (including logistic regression). To the best of our knowledge, we give the first simulation study in the context of randomized trials that compares these estimators. Furthermore, our simulations are not based on parametric models; instead, our simulations are based on resampling data from completed randomized trials in stroke and HIV in order to assess estimator performance in realistic scenarios. We provide practical guidance on when these estimators are likely to provide substantial precision gains and describe a quick assessment method that allows clinical investigators to determine whether these estimators could be useful in their specific trial contexts. PMID:25872751
Improving Flood Predictions in Data-Scarce Basins
NASA Astrophysics Data System (ADS)
Vimal, Solomon; Zanardo, Stefano; Rafique, Farhat; Hilberts, Arno
2017-04-01
Flood modeling methodology at Risk Management Solutions Ltd. has evolved over several years with the development of continental scale flood risk models spanning most of Europe, the United States and Japan. Pluvial (rain fed) and fluvial (river fed) flood maps represent the basis for the assessment of regional flood risk. These maps are derived by solving the 1D energy balance equation for river routing and 2D shallow water equation (SWE) for overland flow. The models are run with high performance computing and GPU based solvers as the time taken for simulation is large in such continental scale modeling. These results are validated with data from authorities and business partners, and have been used in the insurance industry for many years. While this methodology has been proven extremely effective in regions where the quality and availability of data are high, its application is very challenging in other regions where data are scarce. This is generally the case for low and middle income countries, where simpler approaches are needed for flood risk modeling and assessment. In this study we explore new methods to make use of modeling results obtained in data-rich contexts to improve predictive ability in data-scarce contexts. As an example, based on our modeled flood maps in data-rich countries, we identify statistical relationships between flood characteristics and topographic and climatic indicators, and test their generalization across physical domains. Moreover, we apply the Height Above Nearest Drainage (HAND)approach to estimate "probable" saturated areas for different return period flood events as functions of basin characteristics. This work falls into the well-established research field of Predictions in Ungauged Basins.
Montgomery, Karienn S; Edwards, George; Levites, Yona; Kumar, Ashok; Myers, Catherine E; Gluck, Mark A; Setlow, Barry; Bizon, Jennifer L
2016-04-01
Elevated β-amyloid and impaired synaptic function in hippocampus are among the earliest manifestations of Alzheimer's disease (AD). Most cognitive assessments employed in both humans and animal models, however, are insensitive to this early disease pathology. One critical aspect of hippocampal function is its role in episodic memory, which involves the binding of temporally coincident sensory information (e.g., sights, smells, and sounds) to create a representation of a specific learning epoch. Flexible associations can be formed among these distinct sensory stimuli that enable the "transfer" of new learning across a wide variety of contexts. The current studies employed a mouse analog of an associative "transfer learning" task that has previously been used to identify risk for prodromal AD in humans. The rodent version of the task assesses the transfer of learning about stimulus features relevant to a food reward across a series of compound discrimination problems. The relevant feature that predicts the food reward is unchanged across problems, but an irrelevant feature (i.e., the context) is altered. Experiment 1 demonstrated that C57BL6/J mice with bilateral ibotenic acid lesions of hippocampus were able to discriminate between two stimuli on par with control mice; however, lesioned mice were unable to transfer or apply this learning to new problem configurations. Experiment 2 used the APPswe PS1 mouse model of amyloidosis to show that robust impairments in transfer learning are evident in mice with subtle β-amyloid-induced synaptic deficits in the hippocampus. Finally, Experiment 3 confirmed that the same transfer learning impairments observed in APPswePS1 mice were also evident in the Tg-SwDI mouse, a second model of amyloidosis. Together, these data show that the ability to generalize learned associations to new contexts is disrupted even in the presence of subtle hippocampal dysfunction and suggest that, across species, this aspect of hippocampal-dependent learning may be useful for early identification of AD-like pathology. © 2015 Wiley Periodicals, Inc.
Montgomery, Karienn S.; Edwards, George; Levites, Yona; Kumar, Ashok; Myers, Catherine E.; Gluck, Mark A.; Setlow, Barry; Bizon, Jennifer L.
2015-01-01
Elevated β-amyloid and impaired synaptic function in hippocampus are among the earliest manifestations of Alzheimer’s disease (AD). Most cognitive assessments employed in both humans and animal models, however, are insensitive to this early disease pathology. One critical aspect of hippocampal function is its role in episodic memory, which involves the binding of temporally coincident sensory information (e.g., sights, smells, and sounds) to create a representation of a specific learning epoch. Flexible associations can be formed among these distinct sensory stimuli that enable the “transfer” of new learning across a wide variety of contexts. The current studies employed a mouse analog of an associative “transfer learning” task that has previously been used to identify risk for prodromal AD in humans. The rodent version of the task assesses the transfer of learning about stimulus features relevant to a food reward across a series of compound discrimination problems. The relevant feature that predicts the food reward is unchanged across problems, but an irrelevant feature (i.e., the context) is altered. Experiment 1 demonstrated that C57BL6/J mice with bilateral ibotenic acid lesions of hippocampus were able to discriminate between two stimuli on par with control mice; however, lesioned mice were unable to transfer or apply this learning to new problem configurations. Experiment 2 used the APPswePS1 mouse model of amyloidosis to show that robust impairments in transfer learning are evident in mice with subtle β amyloid-induced synaptic deficits in the hippocampus. Finally, Experiment 3 confirmed that the same transfer learning impairments observed in APPswePS1 mice were also evident in the Tg-SwDI mouse, a second model of amyloidosis. Together, these data show that the ability to generalize learned associations to new contexts is disrupted even in the presence of subtle hippocampal dysfunction and suggest that, across species, this aspect of hippocampal-dependent learning may be useful for early identification of AD-like pathology. PMID:26418152
NASA Astrophysics Data System (ADS)
Caflisch, Robert G.
1988-09-01
An argument is given that the model of Buda, Florio, and Giaquinta (BFG)[Phys. Rev. B 35, 2021 (1987)] for anisotropic molecules on a square lattice is inappropriate in that context, because it confuses anisotropy of the lattice with the anisotropy of the molecule. The importance of this is made clear by noting the absence (in BFG) of a dilute isotropic phase. Such a phase is unavoidable on very general grounds. Comments are made about an alternative realization of their results and an alternative class of models for anisotropic molecules.
Wave-Optics Analysis of Pupil Imaging
NASA Technical Reports Server (NTRS)
Dean, Bruce H.; Bos, Brent J.
2006-01-01
Pupil imaging performance is analyzed from the perspective of physical optics. A multi-plane diffraction model is constructed by propagating the scalar electromagnetic field, surface by surface, along the optical path comprising the pupil imaging optical system. Modeling results are compared with pupil images collected in the laboratory. The experimental setup, although generic for pupil imaging systems in general, has application to the James Webb Space Telescope (JWST) optical system characterization where the pupil images are used as a constraint to the wavefront sensing and control process. Practical design considerations follow from the diffraction modeling which are discussed in the context of the JWST Observatory.
Fermion masses and mixing in general warped extra dimensional models
NASA Astrophysics Data System (ADS)
Frank, Mariana; Hamzaoui, Cherif; Pourtolami, Nima; Toharia, Manuel
2015-06-01
We analyze fermion masses and mixing in a general warped extra dimensional model, where all the Standard Model (SM) fields, including the Higgs, are allowed to propagate in the bulk. In this context, a slightly broken flavor symmetry imposed universally on all fermion fields, without distinction, can generate the full flavor structure of the SM, including quarks, charged leptons and neutrinos. For quarks and charged leptons, the exponential sensitivity of their wave functions to small flavor breaking effects yield hierarchical masses and mixing as it is usual in warped models with fermions in the bulk. In the neutrino sector, the exponential wave-function factors can be flavor blind and thus insensitive to the small flavor symmetry breaking effects, directly linking their masses and mixing angles to the flavor symmetric structure of the five-dimensional neutrino Yukawa couplings. The Higgs must be localized in the bulk and the model is more successful in generalized warped scenarios where the metric background solution is different than five-dimensional anti-de Sitter (AdS5 ). We study these features in two simple frameworks, flavor complimentarity and flavor democracy, which provide specific predictions and correlations between quarks and leptons, testable as more precise data in the neutrino sector becomes available.
Arantes, Joana
2008-06-01
The present research tested the generality of the "context effect" previously reported in experiments using temporal double bisection tasks [e.g., Arantes, J., Machado, A. Context effects in a temporal discrimination task: Further tests of the Scalar Expectancy Theory and Learning-to-Time models. J. Exp. Anal. Behav., in press]. Pigeons learned two temporal discriminations in which all the stimuli appear successively: 1s (red) vs. 4s (green) and 4s (blue) vs. 16s (yellow). Then, two tests were conducted to compare predictions of two timing models, Scalar Expectancy Theory (SET) and the Learning-to-Time (LeT) model. In one test, two psychometric functions were obtained by presenting pigeons with intermediate signal durations (1-4s and 4-16s). Results were mixed. In the critical test, pigeons were exposed to signals ranging from 1 to 16s and followed by the green or the blue key. Whereas SET predicted that the relative response rate to each of these keys should be independent of the signal duration, LeT predicted that the relative response rate to the green key (compared with the blue key) should increase with the signal duration. Results were consistent with LeT's predictions, showing that the context effect is obtained even when subjects do not need to make a choice between two keys presented simultaneously.
Generalized Optoelectronic Model of Series-Connected Multijunction Solar Cells
Geisz, John F.; Steiner, Myles A.; Garcia, Ivan; ...
2015-10-02
The emission of light from each junction in a series-connected multijunction solar cell, we found, both complicates and elucidates the understanding of its performance under arbitrary conditions. Bringing together many recent advances in this understanding, we present a general 1-D model to describe luminescent coupling that arises from both voltage-driven electroluminescence and voltage-independent photoluminescence in nonideal junctions that include effects such as Sah-Noyce-Shockley (SNS) recombination with n ≠ 2, Auger recombination, shunt resistance, reverse-bias breakdown, series resistance, and significant dark area losses. The individual junction voltages and currents are experimentally determined from measured optical and electrical inputs and outputs ofmore » the device within the context of the model to fit parameters that describe the devices performance under arbitrary input conditions. Furthermore, our techniques to experimentally fit the model are demonstrated for a four-junction inverted metamorphic solar cell, and the predictions of the model are compared with concentrator flash measurements.« less
A dynamic simulation based water resources education tool.
Williams, Alison; Lansey, Kevin; Washburne, James
2009-01-01
Educational tools to assist the public in recognizing impacts of water policy in a realistic context are not generally available. This project developed systems with modeling-based educational decision support simulation tools to satisfy this need. The goal of this model is to teach undergraduate students and the general public about the implications of common water management alternatives so that they can better understand or become involved in water policy and make more knowledgeable personal or community decisions. The model is based on Powersim, a dynamic simulation software package capable of producing web-accessible, intuitive, graphic, user-friendly interfaces. Modules are included to represent residential, agricultural, industrial, and turf uses, as well as non-market values, water quality, reservoir, flow, and climate conditions. Supplementary materials emphasize important concepts and lead learners through the model, culminating in an open-ended water management project. The model is used in a University of Arizona undergraduate class and within the Arizona Master Watershed Stewards Program. Evaluation results demonstrated improved understanding of concepts and system interactions, fulfilling the project's objectives.
Specialists without spirit: limitations of the mechanistic biomedical model.
Hewa, S; Hetherington, R W
1995-06-01
This paper examines the origin and the development of the mechanistic model of the human body and health in terms of Max Weber's theory of rationalization. It is argued that the development of Western scientific medicine is a part of the broad process of rationalization that began in sixteenth century Europe as a result of the Reformation. The development of the mechanistic view of the human body in Western medicine is consistent with the ideas of calculability, predictability, and control-the major tenets of the process of rationalization as described by Weber. In recent years, however, the limitations of the mechanistic model have been the topic of many discussions. George Engel, a leading advocate of general systems theory, is one of the leading proponents of a new medical model which includes the general quality of life, clean environment, and psychological, or spiritual stability of life. The paper concludes with consideration of the potential of Engel's proposed new model in the context of the current state of rationalization in modern industrialized society.
NASA Astrophysics Data System (ADS)
Hütter, Markus; Svendsen, Bob
2017-12-01
The purpose of the current work is the formulation of models for conservative and non-conservative dynamics in solid systems with the help of the General Equation for the Non-Equilibrium Reversible-Irreversible Coupling (GENERIC: e.g., Grmela and Öttinger, Phys. Rev. E 56(6), 6620 (1997); Öttinger and Grmela, Phys. Rev. E 56(6), 6633 (1997)). In this context, the resulting models are inherently spatially strongly non-local (i.e., functional) and non-isothermal in character. They are applicable in particular to the modeling of phase transitions as well as mass and heat transport in multiphase, multicomponent solids. In the last part of the work, the strongly non-local model formulation is reduced to weakly non-local form with the help of generalized gradient approximation of the energy and entropy functionals. On this basis, the current model formulation is shown to be consistent with and reduce to a recent non-isothermal generalization (Gladkov et al., J. Non-Equilib. Thermodyn. 41(2), 131 (2016)) of the well-known phase-field models of Cahn and Hilliard (J. Chem. Phys. 28(2), 258 (1958)) for conservative dynamics and of Allen and Cahn (Acta Metall. 27(6), 1085 (1979)) for non-conservative dynamics. Finally, the current approach is applied to derive a non-isothermal generalization of a phase-field crystal model for binary alloys (see, e.g., Elder et al., Phys. Rev. B 75(6), 064107 (2007)).
Prospective Investigation of the Contrast Avoidance Model of Generalized Anxiety and Worry.
Crouch, Tara A; Lewis, Jamie A; Erickson, Thane M; Newman, Michelle G
2017-07-01
The factors that maintain generalized anxiety disorder (GAD) symptoms and worry over time are not entirely clear. The Contrast Avoidance Model (CAM) postulates that individuals at risk for pathological worry and GAD symptoms uniquely fear emotional shifts from neutral or positive emotions into negative emotional states, and consequently use worry to maintain negative emotion in order to avoid shifts or blunt the effect of negative contrasts. This model has received support in laboratory experiments, but has not been investigated prospectively in the naturalistic context of daily life. The present study tested the CAM in a longitudinal experience sampling study with a subclinical sample. Participants selected to represent a broad range of symptoms (N = 92) completed baseline measures of GAD and depression symptoms, and eight weekly assessments of worry, experiences of negative emotional contrasts during their worst event of the week, and situation-specific negative emotion. Consistent with the CAM, GAD symptoms prospectively predicted higher endorsement of negative contrast experiences as worst events, independent of depression symptoms. Unsurprisingly, higher negative contrasts predicted higher negative emotion. However, both higher baseline GAD symptoms and weekly worry uniquely moderated (reduced) this relationship, providing consistent support for the idea that worry may blunt the emotional effects of contrasts. Depression symptoms did not have the same moderating effect. These findings support the CAM in an ecologically valid context. Copyright © 2016. Published by Elsevier Ltd.
Summary of photovoltaic system performance models
NASA Technical Reports Server (NTRS)
Smith, J. H.; Reiter, L. J.
1984-01-01
A detailed overview of photovoltaics (PV) performance modeling capabilities developed for analyzing PV system and component design and policy issues is provided. A set of 10 performance models are selected which span a representative range of capabilities from generalized first order calculations to highly specialized electrical network simulations. A set of performance modeling topics and characteristics is defined and used to examine some of the major issues associated with photovoltaic performance modeling. Each of the models is described in the context of these topics and characteristics to assess its purpose, approach, and level of detail. The issues are discussed in terms of the range of model capabilities available and summarized in tabular form for quick reference. The models are grouped into categories to illustrate their purposes and perspectives.
Use of 3D models of congenital heart disease as an education tool for cardiac nurses.
Biglino, Giovanni; Capelli, Claudio; Koniordou, Despina; Robertshaw, Di; Leaver, Lindsay-Kay; Schievano, Silvia; Taylor, Andrew M; Wray, Jo
2017-01-01
Nurse education and training are key to providing congenital heart disease (CHD) patients with consistent high standards of care as well as enabling career progression. One approach for improving educational experience is the use of 3D patient-specific models. To gather pilot data to assess the feasibility of using 3D models of CHD during a training course for cardiac nurses; to evaluate the potential of 3D models in this context, from the nurses' perspective; and to identify possible improvements to optimise their use for teaching. A cross-sectional survey. A national training week for cardiac nurses. One hundred cardiac nurses (of which 65 pediatric and 35 adult). Nurses were shown nine CHD models within the context of a specialized course, following a lecture on the process of making the models themselves, starting from medical imaging. Participants were asked about their general learning experience, if models were more/less informative than diagrams/drawings and lesion-specific/generic models, and their overall reaction to the models. Possible differences between adult and pediatric nurses were investigated. Written feedback was subjected to content analysis and quantitative data were analyzed using nonparametric statistics. Generally models were well liked and nurses considered them more informative than diagrams. Nurses found that 3D models helped in the appreciation of overall anatomy (86%), spatial orientation (70%), and anatomical complexity after treatment (66%). There was no statistically significant difference between adult and pediatric nurses' responses. Thematic analysis highlighted the need for further explanation, use of labels and use of colors to highlight the lesion of interest amongst improvements for optimizing 3D models for teaching/training purposes. 3D patient-specific models are useful tools for training adult and pediatric cardiac nurses and are particularly helpful for understanding CHD anatomy after repair. © 2016 Wiley Periodicals, Inc.
GeoFramework: A Modeling Framework for Solid Earth Geophysics
NASA Astrophysics Data System (ADS)
Gurnis, M.; Aivazis, M.; Tromp, J.; Tan, E.; Thoutireddy, P.; Liu, Q.; Choi, E.; Dicaprio, C.; Chen, M.; Simons, M.; Quenette, S.; Appelbe, B.; Aagaard, B.; Williams, C.; Lavier, L.; Moresi, L.; Law, H.
2003-12-01
As data sets in geophysics become larger and of greater relevance to other earth science disciplines, and as earth science becomes more interdisciplinary in general, modeling tools are being driven in new directions. There is now a greater need to link modeling codes to one another, link modeling codes to multiple datasets, and to make modeling software available to non modeling specialists. Coupled with rapid progress in computer hardware (including the computational speed afforded by massively parallel computers), progress in numerical algorithms, and the introduction of software frameworks, these lofty goals of merging software in geophysics are now possible. The GeoFramework project, a collaboration between computer scientists and geoscientists, is a response to these needs and opportunities. GeoFramework is based on and extends Pyre, a Python-based modeling framework, recently developed to link solid (Lagrangian) and fluid (Eulerian) models, as well as mesh generators, visualization packages, and databases, with one another for engineering applications. The utility and generality of Pyre as a general purpose framework in science is now being recognized. Besides its use in engineering and geophysics, it is also being used in particle physics and astronomy. Geology and geophysics impose their own unique requirements on software frameworks which are not generally available in existing frameworks and so there is a need for research in this area. One of the special requirements is the way Lagrangian and Eulerian codes will need to be linked in time and space within a plate tectonics context. GeoFramework has grown beyond its initial goal of linking a limited number of exiting codes together. The following codes are now being reengineered within the context of Pyre: Tecton, 3-D FE Visco-elastic code for lithospheric relaxation; CitComS, a code for spherical mantle convection; SpecFEM3D, a SEM code for global and regional seismic waves; eqsim, a FE code for dynamic earthquake rupture; SNAC, a developing 3-D coded based on the FLAC method for visco-elastoplastic deformation; SNARK, a 3-D FE-PIC method for viscoplastic deformation; and gPLATES an open source paleogeographic/plate tectonics modeling package. We will demonstrate how codes can be linked with themselves, such as a regional and global model of mantle convection and a visco-elastoplastic representation of the crust within viscous mantle flow. Finally, we will describe how http://GeoFramework.org has become a distribution site for a suite of modeling software in geophysics.
Toward a Trust Evaluation Mechanism in the Social Internet of Things.
Truong, Nguyen Binh; Lee, Hyunwoo; Askwith, Bob; Lee, Gyu Myoung
2017-06-09
In the blooming era of the Internet of Things (IoT), trust has been accepted as a vital factor for provisioning secure, reliable, seamless communications and services. However, a large number of challenges still remain unsolved due to the ambiguity of the concept of trust as well as the variety of divergent trust models in different contexts. In this research, we augment the trust concept, the trust definition and provide a general conceptual model in the context of the Social IoT (SIoT) environment by breaking down all attributes influencing trust. Then, we propose a trust evaluation model called REK, comprised of the triad of trust indicators (TIs) Reputation, Experience and Knowledge. The REK model covers multi-dimensional aspects of trust by incorporating heterogeneous information from direct observation (as Knowledge TI), personal experiences (as Experience TI) to global opinions (as Reputation TI). The associated evaluation models for the three TIs are also proposed and provisioned. We then come up with an aggregation mechanism for deriving trust values as the final outcome of the REK evaluation model. We believe this article offers better understandings on trust as well as provides several prospective approaches for the trust evaluation in the SIoT environment.
High School Students' Meta-Modeling Knowledge
NASA Astrophysics Data System (ADS)
Fortus, David; Shwartz, Yael; Rosenfeld, Sherman
2016-12-01
Modeling is a core scientific practice. This study probed the meta-modeling knowledge (MMK) of high school students who study science but had not had any explicit prior exposure to modeling as part of their formal schooling. Our goals were to (A) evaluate the degree to which MMK is dependent on content knowledge and (B) assess whether the upper levels of the modeling learning progression defined by Schwarz et al. (2009) are attainable by Israeli K-12 students. Nine Israeli high school students studying physics, chemistry, biology, or general science were interviewed individually, once using a context related to the science subject that they were learning and once using an unfamiliar context. All the interviewees displayed MMK superior to that of elementary and middle school students, despite the lack of formal instruction on the practice. Their MMK was independent of content area, but their ability to engage in the practice of modeling was content dependent. This study indicates that, given proper support, the upper levels of the learning progression described by Schwarz et al. (2009) may be attainable by K-12 science students. The value of explicitly focusing on MMK as a learning goal in science education is considered.
Toward a Trust Evaluation Mechanism in the Social Internet of Things
Truong, Nguyen Binh; Lee, Hyunwoo; Askwith, Bob; Lee, Gyu Myoung
2017-01-01
In the blooming era of the Internet of Things (IoT), trust has been accepted as a vital factor for provisioning secure, reliable, seamless communications and services. However, a large number of challenges still remain unsolved due to the ambiguity of the concept of trust as well as the variety of divergent trust models in different contexts. In this research, we augment the trust concept, the trust definition and provide a general conceptual model in the context of the Social IoT (SIoT) environment by breaking down all attributes influencing trust. Then, we propose a trust evaluation model called REK, comprised of the triad of trust indicators (TIs) Reputation, Experience and Knowledge. The REK model covers multi-dimensional aspects of trust by incorporating heterogeneous information from direct observation (as Knowledge TI), personal experiences (as Experience TI) to global opinions (as Reputation TI). The associated evaluation models for the three TIs are also proposed and provisioned. We then come up with an aggregation mechanism for deriving trust values as the final outcome of the REK evaluation model. We believe this article offers better understandings on trust as well as provides several prospective approaches for the trust evaluation in the SIoT environment. PMID:28598401
Exploring dust emission responses to land cover change using an ecological land classification
NASA Astrophysics Data System (ADS)
Galloza, Magda S.; Webb, Nicholas P.; Bleiweiss, Max P.; Winters, Craig; Herrick, Jeffrey E.; Ayers, Eldon
2018-06-01
Despite efforts to quantify the impacts of land cover change on wind erosion, assessment uncertainty remains large. We address this uncertainty by evaluating the application of ecological site concepts and state-and-transition models (STMs) for detecting and quantitatively describing the impacts of land cover change on wind erosion. We apply a dust emission model over a rangeland study area in the northern Chihuahuan Desert, New Mexico, USA, and evaluate spatiotemporal patterns of modelled horizontal sediment mass flux and dust emission in the context of ecological sites and their vegetation states; representing a diversity of land cover types. Our results demonstrate how the impacts of land cover change on dust emission can be quantified, compared across land cover classes, and interpreted in the context of an ecological model that encapsulates land management intensity and change. Results also reveal the importance of established weaknesses in the dust model soil characterisation and drag partition scheme, which appeared generally insensitive to the impacts of land cover change. New models that address these weaknesses, coupled with ecological site concepts and field measurements across land cover types, could significantly reduce assessment uncertainties and provide opportunities for identifying land management options.
On domain modelling of the service system with its application to enterprise information systems
NASA Astrophysics Data System (ADS)
Wang, J. W.; Wang, H. F.; Ding, J. L.; Furuta, K.; Kanno, T.; Ip, W. H.; Zhang, W. J.
2016-01-01
Information systems are a kind of service systems and they are throughout every element of a modern industrial and business system, much like blood in our body. Types of information systems are heterogeneous because of extreme uncertainty in changes in modern industrial and business systems. To effectively manage information systems, modelling of the work domain (or domain) of information systems is necessary. In this paper, a domain modelling framework for the service system is proposed and its application to the enterprise information system is outlined. The framework is defined based on application of a general domain modelling tool called function-context-behaviour-principle-state-structure (FCBPSS). The FCBPSS is based on a set of core concepts, namely: function, context, behaviour, principle, state and structure and system decomposition. Different from many other applications of FCBPSS in systems engineering, the FCBPSS is applied to both infrastructure and substance systems, which is novel and effective to modelling of service systems including enterprise information systems. It is to be noted that domain modelling of systems (e.g. enterprise information systems) is a key to integration of heterogeneous systems and to coping with unanticipated situations facing to systems.
Towards a General Theory of Immunity?
Eberl, Gérard; Pradeu, Thomas
2018-04-01
Theories are indispensable to organize immunological data into coherent, explanatory, and predictive frameworks. We propose to combine different models to develop a unifying theory of immunity which situates immunology in the wider context of physiology. We believe that the immune system will be increasingly understood as a central component of a network of partner physiological systems that interconnect to maintain homeostasis. Copyright © 2017 Elsevier Ltd. All rights reserved.
ERIC Educational Resources Information Center
Jacobs, Cecelia; Smiley-Marquez, Carolyna
People generally learn best when information is presented to them in a culturally and socially relevant context or framework. This issue is addressed by the Science of Alcohol Curriculum for American Indians through the use of the Medicine Circle, a model that represents the concepts of wholeness, interconnectedness, and balance in a manner…
On the structure of arithmetic sums of Cantor sets with constant ratios of dissection
NASA Astrophysics Data System (ADS)
Anisca, Razvan; Chlebovec, Christopher
2009-09-01
We investigate conditions which imply that the topological structure of the arithmetic sum of two Cantor sets with constant ratios of dissection at each step is either: a Cantor set, a finite union of closed intervals, or three mixed models (L, R and M-Cantorval). We obtain general results that apply in particular for the case of homogeneous Cantor sets, thus generalizing the results of Mendes and Oliveira. The method used here is new in this context. We also produce results regarding the arithmetic sum of two affine Cantor sets of a special kind.
A Quantum-Like View to a Generalized Two Players Game
NASA Astrophysics Data System (ADS)
Bagarello, F.
2015-10-01
This paper consider the possibility of using some quantum tools in decision making strategies. In particular, we consider here a dynamical open quantum system helping two players, and , to take their decisions in a specific context. We see that, within our approach, the final choices of the players do not depend in general on their initial mental states, but they are driven essentially by the environment which interacts with them. The model proposed here also considers interactions of different nature between the two players, and it is simple enough to allow for an analytical solution of the equations of motion.
NASA Astrophysics Data System (ADS)
Çalik, Muammer; Özsevgeç, Tuncay; Ebenezer, Jazlin; Artun, Hüseyin; Küçük, Zeynel
2014-06-01
The purpose of this study is to examine the effects of `environmental chemistry' elective course via Technology-Embedded Scientific Inquiry (TESI) model on senior science student teachers' (SSSTs) conceptions of environmental chemistry concepts/issues, attitudes toward chemistry, and technological pedagogical content knowledge (TPACK) levels. Within one group pre-test-post-test design, the study was conducted with 117 SSSTs (68 females and 49 males—aged 21-23 years) enrolled in an `environmental chemistry' elective course in the spring semester of 2011-2012 academic-years. Instruments for data collection comprised of Environmental Chemistry Conceptual Understanding Questionnaire, TPACK survey, and Chemistry Attitudes and Experiences Questionnaire. Significant increases in the SSSTs' conceptions of environmental chemistry concepts/issues, attitudes toward chemistry, and TPACK levels are attributed to the SSSTs learning how to use the innovative technologies in the contexts of the `environmental chemistry' elective course and teaching practicum. The study implies that the TESI model may serve a useful purpose in experimental science courses that use the innovative technologies. However, to generalize feasibility of the TESI model, it should be evaluated with SSSTs in diverse learning contexts.
Kukona, Anuenue; Tabor, Whitney
2011-01-01
The visual world paradigm presents listeners with a challenging problem: they must integrate two disparate signals, the spoken language and the visual context, in support of action (e.g., complex movements of the eyes across a scene). We present Impulse Processing, a dynamical systems approach to incremental eye movements in the visual world that suggests a framework for integrating language, vision, and action generally. Our approach assumes that impulses driven by the language and the visual context impinge minutely on a dynamical landscape of attractors corresponding to the potential eye-movement behaviors of the system. We test three unique predictions of our approach in an empirical study in the visual world paradigm, and describe an implementation in an artificial neural network. We discuss the Impulse Processing framework in relation to other models of the visual world paradigm. PMID:21609355
Students’ Algebraic Thinking Process in Context of Point and Line Properties
NASA Astrophysics Data System (ADS)
Nurrahmi, H.; Suryadi, D.; Fatimah, S.
2017-09-01
Learning of schools algebra is limited to symbols and operating procedures, so students are able to work on problems that only require the ability to operate symbols but unable to generalize a pattern as one of part of algebraic thinking. The purpose of this study is to create a didactic design that facilitates students to do algebraic thinking process through the generalization of patterns, especially in the context of the property of point and line. This study used qualitative method and includes Didactical Design Research (DDR). The result is students are able to make factual, contextual, and symbolic generalization. This happen because the generalization arises based on facts on local terms, then the generalization produced an algebraic formula that was described in the context and perspective of each student. After that, the formula uses the algebraic letter symbol from the symbol t hat uses the students’ language. It can be concluded that the design has facilitated students to do algebraic thinking process through the generalization of patterns, especially in the context of property of the point and line. The impact of this study is this design can use as one of material teaching alternative in learning of school algebra.
Classification with spatio-temporal interpixel class dependency contexts
NASA Technical Reports Server (NTRS)
Jeon, Byeungwoo; Landgrebe, David A.
1992-01-01
A contextual classifier which can utilize both spatial and temporal interpixel dependency contexts is investigated. After spatial and temporal neighbors are defined, a general form of maximum a posterior spatiotemporal contextual classifier is derived. This contextual classifier is simplified under several assumptions. Joint prior probabilities of the classes of each pixel and its spatial neighbors are modeled by the Gibbs random field. The classification is performed in a recursive manner to allow a computationally efficient contextual classification. Experimental results with bitemporal TM data show significant improvement of classification accuracy over noncontextual pixelwise classifiers. This spatiotemporal contextual classifier should find use in many applications of remote sensing, especially when the classification accuracy is important.
Real time eye tracking using Kalman extended spatio-temporal context learning
NASA Astrophysics Data System (ADS)
Munir, Farzeen; Minhas, Fayyaz ul Amir Asfar; Jalil, Abdul; Jeon, Moongu
2017-06-01
Real time eye tracking has numerous applications in human computer interaction such as a mouse cursor control in a computer system. It is useful for persons with muscular or motion impairments. However, tracking the movement of the eye is complicated by occlusion due to blinking, head movement, screen glare, rapid eye movements, etc. In this work, we present the algorithmic and construction details of a real time eye tracking system. Our proposed system is an extension of Spatio-Temporal context learning through Kalman Filtering. Spatio-Temporal Context Learning offers state of the art accuracy in general object tracking but its performance suffers due to object occlusion. Addition of the Kalman filter allows the proposed method to model the dynamics of the motion of the eye and provide robust eye tracking in cases of occlusion. We demonstrate the effectiveness of this tracking technique by controlling the computer cursor in real time by eye movements.
Reverdito, Riller S; Carvalho, Humberto M; Galatti, Larissa R; Scaglia, Alcides J; Gonçalves, Carlos E; Paes, Roberto R
2017-06-01
The present study examined extracurricular sport participation variables and developmental context in relationship to perceived self-efficacy among underserved adolescents. Participants ( n = 821, 13.6 ± 1.5 years) completed the Youth Experience in Sport questionnaire and General Self-Efficacy Scale. We used the Human Development Index (HDI) to characterize developmental contexts. Multilevel regression models were used to explore the relative contributions of age, sex, years of participation in extracurricular sport, HDI, and perceived positive experience in sport. Our results highlight that positive experience alone and in interaction with length of participation in the program fostered perceived self-efficacy. Participants from higher HDI contexts remained longer in the program. An implication of our research is that variables linked to positive sport experiences and perceived self-efficacy can be used as markers to evaluate the outcomes and impact of sport participation programs aimed at promoting positive youth development.
Normalization is a general neural mechanism for context-dependent decision making
Louie, Kenway; Khaw, Mel W.; Glimcher, Paul W.
2013-01-01
Understanding the neural code is critical to linking brain and behavior. In sensory systems, divisive normalization seems to be a canonical neural computation, observed in areas ranging from retina to cortex and mediating processes including contrast adaptation, surround suppression, visual attention, and multisensory integration. Recent electrophysiological studies have extended these insights beyond the sensory domain, demonstrating an analogous algorithm for the value signals that guide decision making, but the effects of normalization on choice behavior are unknown. Here, we show that choice models using normalization generate significant (and classically irrational) choice phenomena driven by either the value or number of alternative options. In value-guided choice experiments, both monkey and human choosers show novel context-dependent behavior consistent with normalization. These findings suggest that the neural mechanism of value coding critically influences stochastic choice behavior and provide a generalizable quantitative framework for examining context effects in decision making. PMID:23530203
The place of knowledge and evidence in the context of Australian general practice nursing.
Mills, Jane; Field, John; Cant, Robyn
2009-01-01
The purpose of the study was to ascertain the place of knowledge and evidence in the context of Australian general practice nursing. General practice nursing is a rapidly developing area of specialized nursing in Australia. The provision of primary care services in Australia rests largely with medical general practitioners who employ nurses in a small business model. A statistical research design was used that included a validated instrument: the developing evidence-based practice questionnaire (Gerrish et al. 2007). A total of 1,800 Victorian practice nurses were surveyed with a return of 590 completed questionnaires, equaling a response rate of 33%. Lack of time to access knowledge for practice was a barrier for participants in this study. In-service education and training opportunities were ranked as the number one source of knowledge for general practice nurses. Experiential learning and interactions with clients, peers, medical practitioners, and specialist nurses were also considered very important sources of knowledge. Research journals were ranked much lower than experiential learning and personal interactions. Participants assessed their own skills at sourcing and translating evidence into practice knowledge as low. Younger general practice nurses were more likely than older nurses to assess themselves as competent at using the library and Internet to locate evidence. The predominantly oral culture of nursing needs to be identified and incorporated into methods for disseminating evidence from research findings in order to increase the knowledge base of Australian general practice nurses. Findings from this study will be significant for policy makers and funders of Australian nursing in general practice. The establishment of a career structure for general practice nurses that includes salaried positions for clinical nurse specialists would assist in the translation of evidence into knowledge for utilization at the point of care.
Social Salience Discriminates Learnability of Contextual Cues in an Artificial Language
Rácz, Péter; Hay, Jennifer B.; Pierrehumbert, Janet B.
2017-01-01
We investigate the learning of contextual meaning by adults in an artificial language. Contextual meaning here refers to the non-denotative contextual information that speakers attach to a linguistic construction. Through a series of short games, played online, we test how well adults can learn different contextual meanings for a word-formation pattern in an artificial language. We look at whether learning contextual meanings depends on the social salience of the context, whether our players interpret these contexts generally, and whether the learned meaning is generalized to new words. Our results show that adults are capable of learning contextual meaning if the context is socially salient, coherent, and interpretable. Once a contextual meaning is recognized, it is readily generalized to related forms and contexts. PMID:28194122
Acculturative Stress and Diminishing Family Cohesion Among Recent Latino Immigrants
De La Rosa, Mario; Ibañez, Gladys E.
2012-01-01
This study investigates a theorized link between Latino immigrants’ experience of acculturative stress during their two initial years in the United States (US) and declines in family cohesion from pre- to post-immigration contexts. This retrospective cohort study included 405 adult participants. Baseline assessment occurred during participants’ first 12 months in the US. Follow-up assessment occurred during participants’ second year in the US. General linear mixed models were used to estimate change in family cohesion and sociocultural correlates of this change. Inverse associations were determined between acculturative stress during initial years in the US and declines in family cohesion from pre-immigration to post-immigration contexts. Participants with undocumented immigration status, those with lower education levels, and those without family in the US generally indicated lower family cohesion. Participants who experienced more acculturative stress and those without family in the US evidenced a greater decline in family cohesion. Results are promising in terms of implications for health services for recent Latino immigrants. PMID:22790880
Role of the registered nurse in primary health care: meeting health care needs in the 21st century.
Smolowitz, Janice; Speakman, Elizabeth; Wojnar, Danuta; Whelan, Ellen-Marie; Ulrich, Suzan; Hayes, Carolyn; Wood, Laura
2015-01-01
There is widespread interest in the redesign of primary health care practice models to increase access to quality health care. Registered nurses (RNs) are well positioned to assume direct care and leadership roles based on their understanding of patient, family, and system priorities. This project identified 16 exemplar primary health care practices that used RNs to the full extent of their scope of practice in team-based care. Interviews were conducted with practice representatives. RN activities were performed within three general contexts: episodic and preventive care, chronic disease management, and practice operations. RNs performed nine general functions in these contexts including telephone triage, assessment and documentation of health status, chronic illness case management, hospital transition management, delegated care for episodic illness, health coaching, medication reconciliation, staff supervision, and quality improvement leadership. These functions improved quality and efficiency and decreased cost. Implications for policy, practice, and RN education are considered. Copyright © 2015 Elsevier Inc. All rights reserved.
Transcontextual development of motivation in sport injury prevention among elite athletes.
Chan, Derwin King Chung; Hagger, Martin S
2012-10-01
The present study investigated the transcontextual process of motivation in sport injury prevention. We examined whether general causality orientation, perceived autonomy support from coaches (PAS), self-determined motivation (SD-Mtv), and basic need satisfaction in a sport context predicted SD-Mtv, beliefs, and adherence with respect to sport injury prevention. Elite athletes (N = 533) completed self-report measures of the predictors (Week 1) and the dependent variables (Week 2). Variance-based structural equation modeling supported hypotheses: SD-Mtv in a sport context was significantly predicted by PAS and basic need satisfaction and was positively associated with SD-Mtv for sport injury prevention when controlling for general causality orientation. SD-Mtv for sport injury prevention was a significant predictor of adherence to injury-preventive behaviors and beliefs regarding safety in sport. In conclusion, the transcontextual mechanism of motivation may explain the process by which distal motivational factors in sport direct the formation of proximal motivation, beliefs, and behaviors of sport injury prevention.
Synthetic cognitive development. Where intelligence comes from
NASA Astrophysics Data System (ADS)
Weinbaum (Weaver), D.; Veitas, V.
2017-01-01
The human cognitive system is a remarkable exemplar of a general intelligent system whose competence is not confined to a specific problem domain. Evidently, general cognitive competences are a product of a prolonged and complex process of cognitive development. Therefore, the process of cognitive development is a primary key to understanding the emergence of intelligent behavior. This paper develops the theoretical foundations for a model that generalizes the process of cognitive development. The model aims to provide a realistic scheme for the synthesis of scalable cognitive systems with an open-ended range of capabilities. Major concepts and theories of human cognitive development are introduced and briefly explored, focusing on the enactive approach to cognition and the concept of sense-making. The initial scheme of human cognitive development is then generalized by introducing the philosophy of individuation and the abstract mechanism of transduction. The theory of individuation provides the ground for the necessary paradigmatic shift from cognitive systems as given products to cognitive development as a formative process of self-organization. Next, the conceptual model is specified as a scalable scheme of networks of agents. The mechanisms of individuation are formulated in context-independent information theoretical terms. Finally, the paper discusses two concrete aspects of the generative model - mechanisms of transduction and value modulating systems. These are topics of further research towards an implementable architecture.
Petranka, James W; Kennedy, Caroline A
1999-09-01
With rare exceptions, anuran larvae have traditionally been considered to occupy lower trophic levels in aquatic communities where they function as microphagous suspension feeders. This view is being challenged by studies showing that tadpoles with generalized morphology often function as macrophagous predators. Here, we review the literature concerning macrophagy by tadpoles and provide two additional examples involving generalized tadpoles. In the first, we demonstrate with laboratory and field experiments that wood frog (Rana sylvatica) tadpoles are major predators of macroinvertebrates in ponds. In the second, we show that green frog (R. clamitans) tadpoles can cause catastrophic reproductive failure of the wood frog via egg predation. These results and data from other studies challenge the assumption that generalized tadpoles function as filter-feeding omnivores, and question the general applicability of community organization models which assume that predation risk increases with pond permanence. We suggest that predation risk is greater in temporary ponds than in more permanent ponds for many organisms that are vulnerable to predation by tadpoles. This being so, a conditional model based upon interactions that are species-specific, life-stage-specific, and context-dependent may better explain community organization along hydrological gradients than models which assume that temporary ponds have few or no predators.
Models for small-scale structure on cosmic strings. II. Scaling and its stability
NASA Astrophysics Data System (ADS)
Vieira, J. P. P.; Martins, C. J. A. P.; Shellard, E. P. S.
2016-11-01
We make use of the formalism described in a previous paper [Martins et al., Phys. Rev. D 90, 043518 (2014)] to address general features of wiggly cosmic string evolution. In particular, we highlight the important role played by poorly understood energy loss mechanisms and propose a simple Ansatz which tackles this problem in the context of an extended velocity-dependent one-scale model. We find a general procedure to determine all the scaling solutions admitted by a specific string model and study their stability, enabling a detailed comparison with future numerical simulations. A simpler comparison with previous Goto-Nambu simulations supports earlier evidence that scaling is easier to achieve in the matter era than in the radiation era. In addition, we also find that the requirement that a scaling regime be stable seems to notably constrain the allowed range of energy loss parameters.
Lang, Jonas W B; Bliese, Paul D
2009-03-01
The present research provides new insights into the relationship between general mental ability (GMA) and adaptive performance by applying a discontinuous growth modeling framework to a study of unforeseen change on a complex decision-making task. The proposed framework provides a way to distinguish 2 types of adaptation (transition adaptation and reacquisition adaptation) from 2 common performance components (skill acquisition and basal task performance). Transition adaptation refers to an immediate loss of performance following a change, whereas reacquisition adaptation refers to the ability to relearn a changed task over time. Analyses revealed that GMA was negatively related to transition adaptation and found no evidence for a relationship between GMA and reacquisition adaptation. The results are integrated within the context of adaptability research, and implications of using the described discontinuous growth modeling framework to study adaptability are discussed. (c) 2009 APA, all rights reserved.
A Model for Indexing Medical Documents Combining Statistical and Symbolic Knowledge.
Avillach, Paul; Joubert, Michel; Fieschi, Marius
2007-01-01
OBJECTIVES: To develop and evaluate an information processing method based on terminologies, in order to index medical documents in any given documentary context. METHODS: We designed a model using both symbolic general knowledge extracted from the Unified Medical Language System (UMLS) and statistical knowledge extracted from a domain of application. Using statistical knowledge allowed us to contextualize the general knowledge for every particular situation. For each document studied, the extracted terms are ranked to highlight the most significant ones. The model was tested on a set of 17,079 French standardized discharge summaries (SDSs). RESULTS: The most important ICD-10 term of each SDS was ranked 1st or 2nd by the method in nearly 90% of the cases. CONCLUSIONS: The use of several terminologies leads to more precise indexing. The improvement achieved in the model’s implementation performances as a result of using semantic relationships is encouraging. PMID:18693792
NASA Astrophysics Data System (ADS)
Lachowicz, Mirosław
2016-03-01
The very stimulating paper [6] discusses an approach to perception and learning in a large population of living agents. The approach is based on a generalization of kinetic theory methods in which the interactions between agents are described in terms of game theory. Such an approach was already discussed in Ref. [2-4] (see also references therein) in various contexts. The processes of perception and learning are based on the interactions between agents and therefore the general kinetic theory is a suitable tool for modeling them. However the main question that rises is how the perception and learning processes may be treated in the mathematical modeling. How may we precisely deliver suitable mathematical structures that are able to capture various aspects of perception and learning?
Rajah, M Natasha; Ames, Blaine; D'Esposito, Mark
2008-03-07
Neuroimaging studies have reported increased prefrontal cortex (PFC) activity during temporal context retrieval versus recognition memory. However, it remains unclear if these activations reflect PFC contributions to domain-general executive control processes or domain-specific retrieval processes. To gain a better understanding of the functional roles of these various PFC regions during temporal context retrieval we propose it is necessary to examine PFC activity across tasks from different domains, in which parallel manipulations are included targeting specific cognitive processes. In the current fMRI study, we examined domain-general and domain-specific PFC contributions to temporal context retrieval by increasing stimulus (but maintaining response number) and increasing response number (but maintaining stimulus number) across temporal context memory and ordering control tasks, for faces. The control task required subjects to order faces from youngest to oldest. Our behavioral results indicate that the combination of increased stimulus and response numbers significantly increased task difficulty for temporal context retrieval and ordering tasks. Across domains, increasing stimulus number, while maintaining response numbers, caused greater right lateral premotor cortex (BA 6/8) activity; whereas increasing response number, while maintaining stimulus number, caused greater domain-general left DLPFC (BA 9) and VLPFC (BA 44/45) activity. In addition, we found domain-specific right DLPFC (BA 9) activity only during retrieval events. These results highlight the functional heterogeneity of frontal cortex, and suggest its involvement in temporal context retrieval is related to its role in various cognitive control processes.
Kalénine, Solène; Mirman, Daniel; Middleton, Erica L.; Buxbaum, Laurel J.
2012-01-01
The current research aimed at specifying the activation time course of different types of semantic information during object conceptual processing and the effect of context on this time course. We distinguished between thematic and functional knowledge and the specificity of functional similarity. Two experiments were conducted with healthy older adults using eye tracking in a word-to-picture matching task. The time course of gaze fixations was used to assess activation of distractor objects during the identification of manipulable artifact targets (e.g., broom). Distractors were (a) thematically related (e.g., dustpan), (b) related by a specific function (e.g., vacuum cleaner), or (c) related by a general function (e.g., sponge). Growth curve analyses were used to assess competition effects when target words were presented in isolation (Experiment 1) and embedded in contextual sentences of different generality levels (Experiment 2). In the absence of context, there was earlier and shorter lasting activation of thematically related as compared to functionally related objects. The time course difference was more pronounced for general functions than specific functions. When contexts were provided, functional similarities that were congruent with context generality level increased in salience with earlier activation of those objects. Context had little impact on thematic activation time course. These data demonstrate that processing a single manipulable artifact concept implicitly activates thematic and functional knowledge with different time courses and that context speeds activation of context-congruent functional similarity. PMID:22449134
Adapting an Infectious Diseases Course for “Engaged Citizen” Themes†
Senchina, David S.
2016-01-01
This article describes philosophies and perspectives underpinning scientific citizenship–focused curricular changes implemented into a pre-existing undergraduate infectious diseases course. Impetus for the curricular changes was a novel, campus-wide, multidisciplinary “Engaged Citizen” theme for the general education curriculum. The first half of the article describes the larger contexts from which the curricular changes were borne and the resulting instructional model. The second half of the article shares both student and instructor perspectives on the curricular changes and potential application of the model to other science courses. PMID:27047601
Inflation and acceleration of the universe by nonlinear magnetic monopole fields
NASA Astrophysics Data System (ADS)
Övgün, A.
2017-02-01
Despite impressive phenomenological success, cosmological models are incomplete without an understanding of what happened at the big bang singularity. Maxwell electrodynamics, considered as a source of the classical Einstein field equations, leads to the singular isotropic Friedmann solutions. In the context of Friedmann-Robertson-Walker (FRW) spacetime, we show that singular behavior does not occur for a class of nonlinear generalizations of the electromagnetic theory for strong fields. A new mathematical model is proposed for which the analytical nonsingular extension of FRW solutions is obtained by using the nonlinear magnetic monopole fields.
On classical and quantum dynamics of tachyon-like fields and their cosmological implications
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dimitrijević, Dragoljub D., E-mail: ddrag@pmf.ni.ac.rs; Djordjević, Goran S., E-mail: ddrag@pmf.ni.ac.rs; Milošević, Milan, E-mail: ddrag@pmf.ni.ac.rs
2014-11-24
We consider a class of tachyon-like potentials, motivated by string theory, D-brane dynamics and inflation theory in the context of classical and quantum mechanics. A formalism for describing dynamics of tachyon fields in spatially homogenous and one-dimensional - classical and quantum mechanical limit is proposed. A few models with concrete potentials are considered. Additionally, possibilities for p-adic and adelic generalization of these models are discussed. Classical actions and corresponding quantum propagators, in the Feynman path integral approach, are calculated in a form invariant on a change of the background number fields, i.e. on both archimedean and nonarchimedean spaces. Looking formore » a quantum origin of inflation, relevance of p-adic and adelic generalizations are briefly discussed.« less
Allen, Johnie J; Anderson, Craig A; Bushman, Brad J
2018-02-01
The General Aggression Model (GAM) is a comprehensive, integrative, framework for understanding aggression. It considers the role of social, cognitive, personality, developmental, and biological factors on aggression. Proximate processes of GAM detail how person and situation factors influence cognitions, feelings, and arousal, which in turn affect appraisal and decision processes, which in turn influence aggressive or nonaggressive behavioral outcomes. Each cycle of the proximate processes serves as a learning trial that affects the development and accessibility of aggressive knowledge structures. Distal processes of GAM detail how biological and persistent environmental factors can influence personality through changes in knowledge structures. GAM has been applied to understand aggression in many contexts including media violence effects, domestic violence, intergroup violence, temperature effects, pain effects, and the effects of global climate change. Copyright © 2017 Elsevier Ltd. All rights reserved.
When the job is boring: the role of boredom in organizational contexts.
Guglielmi, Dina; Simbula, Silvia; Mazzetti, Greta; Tabanelli, Maria Carla; Bonfiglioli, Roberta
2013-01-01
The present study investigates the role of boredom within the Job Demands-Resources model. Although empirical evidence suggests that the incidence of boredom at work is widespread, the study of job boredom remains neglected today. Data were collected from 269 mass-retail workers, by means of structured face-to-face interviews. Results of multiple mediation analyses partially supported our hypotheses. Boredom mediates the relationship between transformational leadership, low learning opportunities and general dysphoria, while work engagement mediates the relationship between transformational leadership, low learning opportunities and job satisfaction as well as general dysphoria. Taken together, our results confirm the suitability of conceptualizing boredom within the JD-R model and contribute to the ongoing conceptualization of both the boredom literature and the JD-R literature.
Frikke-Schmidt, Ruth; Tybjærg-Hansen, Anne; Dyson, Greg; Haase, Christiane L; Benn, Marianne; Nordestgaard, Børge G; Sing, Charles F
2015-01-01
Background The aetiology of ischaemic heart disease (IHD) is complex and is influenced by a spectrum of environmental factors and susceptibility genes. Traditional statistical modelling considers such factors to act independently in an additive manner. The Patient Rule-Induction Method (PRIM) is a multi-model building strategy for evaluating risk attributable to context-dependent gene and environmental effects. Methods PRIM was applied to 9073 participants from the prospective Copenhagen City Heart Study (CCHS). Gender-specific cumulative incidences were estimated for subgroups defined by categories of age, smoking, hypertension, diabetes, body mass index, total cholesterol, high-density lipoprotein cholesterol and triglycerides and by 94 single nucleotide variants (SNVs).Cumulative incidences for subgroups were validated using an independently ascertained sample of 58 240 participants from the Copenhagen General Population Study (CGPS). Results In the CCHS the overall cumulative incidences were 0.17 in women and 0.21 in men. PRIM identified six and four mutually exclusive subgroups in women and men, respectively, with cumulative incidences of IHD ranging from 0.02 to 0.34. Cumulative incidences of IHD generated by PRIM in the CCHS were validated in four of the six subgroups of women and two of the four subgroups of men in the CGPS. Conclusions PRIM identified high-risk subgroups characterized by specific contexts of selected values of traditional risk factors and genetic variants. These subgroups were validated in an independently ascertained cohort study. Thus, a multi-model strategy may identify groups of individuals with substantially higher risk of IHD than the overall risk for the general population. PMID:25361584
NASA Astrophysics Data System (ADS)
Anugrah, I. R.; Mudzakir, A.; Sumarna, O.
2017-09-01
Teaching materials used in Indonesia generally just emphasize remembering skill so that the students’ science literacy is low. Innovation is needed to transform traditional teaching materials so that it can stimulate students’ science literacy, one of which is by context-based approach. This study focused on the construction of context-based module for high school using Organic Light-Emitting Diode (OLED) topics. OLED was chosen because it is an up-to-date topic and relevant to real life. This study used Model of Educational Reconstruction (MER) to reconstruct science content structure about OLED through combining scientist’s perspectives with student’s preconceptions and national curriculum. Literature review of OLED includes its definition, components, characteristics and working principle. Student’s preconceptions about OLED are obtained through interviews. The result shows that student’s preconceptions have not been fully similar with the scientist’s perspective. One of the reasons is that some of the related Chemistry concepts are too complicated. Through curriculum analysis, Chemistry about OLED that are appropriate for high school are Bohr’s atomic theory, redox and organic chemistry including polymers and aromatics. The OLED context and its Chemistry concept were developed into context-based module by adapting science literacy-based learning. This module is expected to increase students’ science literacy performance.
Zetsche, Ulrike; Rief, Winfried; Westermann, Stefan; Exner, Cornelia
2015-01-01
The present study examines the interplay between cognitive deficits and emotional context in obsessive-compulsive disorder (OCD) and social phobia (SP). Specifically, this study examines whether the inflexible use of efficient learning strategies in an emotional context underlies impairments in probabilistic classification learning (PCL) in OCD, and whether PCL impairments are specific to OCD. Twenty-three participants with OCD, 30 participants with SP and 30 healthy controls completed a neutral and an OCD-specific PCL task. OCD participants failed to adopt efficient learning strategies and showed fewer beneficial strategy switches than controls only in an OCD-specific context, but not in a neutral context. Additionally, OCD participants did not show any explicit memory impairments. Number of beneficial strategy switches in the OCD-specific task mediated the difference in PCL performance between OCD and control participants. Individuals with SP were impaired in both PCL tasks. In contrast to neuropsychological models postulating general cognitive impairments in OCD, the present findings suggest that it is the interaction between cognition and emotion that is impaired in OCD. Specifically, activated disorder-specific fears may impair the flexible adoption of efficient learning strategies and compromise otherwise unimpaired PCL. Impairments in PCL are not specific to OCD.
Spence, Nicholas D
2016-03-01
Debates surrounding the importance of social context versus individual level processes have a long history in public health. Aboriginal peoples in Canada are very diverse, and the reserve communities in which they reside are complex mixes of various cultural and socioeconomic circumstances. The social forces of these communities are believed to affect health, in addition to individual level determinants, but no large scale work has ever probed their relative effects. One aspect of social context, relative deprivation, as indicated by income inequality, has greatly influenced the social determinants of health landscape. An investigation of relative deprivation in Canada's Aboriginal population has never been conducted. This paper proposes a new model of Aboriginal health, using a multidisciplinary theoretical approach that is multilevel. This study explored the self-rated health of respondents using two levels of determinants, contextual and individual. Data were from the 2001 Aboriginal Peoples Survey. There were 18,890 Registered First Nations (subgroup of Aboriginal peoples) on reserve nested within 134 communities. The model was assessed using a hierarchical generalized linear model. There was no significant variation at the contextual level. Subsequently, a sequential logistic regression analysis was run. With the sole exception culture, demographics, lifestyle factors, formal health services, and social support were significant in explaining self-rated health. The non-significant effect of social context, and by extension relative deprivation, as indicated by income inequality, is noteworthy, and the primary role of individual level processes, including the material conditions, social support, and lifestyle behaviors, on health outcomes is illustrated. It is proposed that social structure is best conceptualized as a dynamic determinant of health inequality and more multilevel theoretical models of Aboriginal health should be developed and tested.
Meeusen, Cecil; Kern, Anna
2016-01-01
The goal of this paper was to investigate the generalizability of prejudice across contexts by analyzing associations between different types of prejudice in a cross-national perspective and by investigating the relation between country-specific contextual factors and target-specific prejudices. Relying on the European Social Survey (2008), results indicated that prejudices were indeed positively associated, confirming the existence of a generalized prejudice component. Next to substantial cross-national differences in associational strength, also within country variance in target-specific associations was observed. This suggested that the motivations for prejudice largely vary according to the intergroup context. Two aspects of the intergroup context - economic conditions and cultural values - showed to be related to generalized and target-specific components of prejudice. Future research on prejudice and context should take an integrative approach that considers both the idea of generalized and specific prejudice simultaneously. Copyright © 2015 Elsevier Inc. All rights reserved.
Morris, Melody K.; Saez-Rodriguez, Julio; Clarke, David C.; Sorger, Peter K.; Lauffenburger, Douglas A.
2011-01-01
Predictive understanding of cell signaling network operation based on general prior knowledge but consistent with empirical data in a specific environmental context is a current challenge in computational biology. Recent work has demonstrated that Boolean logic can be used to create context-specific network models by training proteomic pathway maps to dedicated biochemical data; however, the Boolean formalism is restricted to characterizing protein species as either fully active or inactive. To advance beyond this limitation, we propose a novel form of fuzzy logic sufficiently flexible to model quantitative data but also sufficiently simple to efficiently construct models by training pathway maps on dedicated experimental measurements. Our new approach, termed constrained fuzzy logic (cFL), converts a prior knowledge network (obtained from literature or interactome databases) into a computable model that describes graded values of protein activation across multiple pathways. We train a cFL-converted network to experimental data describing hepatocytic protein activation by inflammatory cytokines and demonstrate the application of the resultant trained models for three important purposes: (a) generating experimentally testable biological hypotheses concerning pathway crosstalk, (b) establishing capability for quantitative prediction of protein activity, and (c) prediction and understanding of the cytokine release phenotypic response. Our methodology systematically and quantitatively trains a protein pathway map summarizing curated literature to context-specific biochemical data. This process generates a computable model yielding successful prediction of new test data and offering biological insight into complex datasets that are difficult to fully analyze by intuition alone. PMID:21408212
The (Mathematical) Modeling Process in Biosciences
Torres, Nestor V.; Santos, Guido
2015-01-01
In this communication, we introduce a general framework and discussion on the role of models and the modeling process in the field of biosciences. The objective is to sum up the common procedures during the formalization and analysis of a biological problem from the perspective of Systems Biology, which approaches the study of biological systems as a whole. We begin by presenting the definitions of (biological) system and model. Particular attention is given to the meaning of mathematical model within the context of biology. Then, we present the process of modeling and analysis of biological systems. Three stages are described in detail: conceptualization of the biological system into a model, mathematical formalization of the previous conceptual model and optimization and system management derived from the analysis of the mathematical model. All along this work the main features and shortcomings of the process are analyzed and a set of rules that could help in the task of modeling any biological system are presented. Special regard is given to the formative requirements and the interdisciplinary nature of this approach. We conclude with some general considerations on the challenges that modeling is posing to current biology. PMID:26734063
Quantitative reactive modeling and verification.
Henzinger, Thomas A
Formal verification aims to improve the quality of software by detecting errors before they do harm. At the basis of formal verification is the logical notion of correctness , which purports to capture whether or not a program behaves as desired. We suggest that the boolean partition of software into correct and incorrect programs falls short of the practical need to assess the behavior of software in a more nuanced fashion against multiple criteria. We therefore propose to introduce quantitative fitness measures for programs, specifically for measuring the function, performance, and robustness of reactive programs such as concurrent processes. This article describes the goals of the ERC Advanced Investigator Project QUAREM. The project aims to build and evaluate a theory of quantitative fitness measures for reactive models. Such a theory must strive to obtain quantitative generalizations of the paradigms that have been success stories in qualitative reactive modeling, such as compositionality, property-preserving abstraction and abstraction refinement, model checking, and synthesis. The theory will be evaluated not only in the context of software and hardware engineering, but also in the context of systems biology. In particular, we will use the quantitative reactive models and fitness measures developed in this project for testing hypotheses about the mechanisms behind data from biological experiments.
Vaidyanathan, Uma; Patrick, Christopher J.; Cuthbert, Bruce N.
2009-01-01
Integrative hierarchical models have sought to account for the extensive comorbidity between various internalizing disorders in terms of broad individual difference factors these disorders share. However, such models have been developed largely on the basis of self-report and diagnostic symptom data. Toward the goal of linking such models to neurobiological systems, we review studies that have employed variants of the affect-modulated startle paradigm to investigate emotional processing in internalizing disorders as well as personality constructs known to be associated with these disorders. Specifically, we focus on four parameters of startle reactivity: fear-potentiated startle, inhibition of startle in the context of pleasant stimuli, context-potentiated startle, and general startle reactivity. On the basis of available data, we argue that these varying effects index differing neurobiological processes related to mood and anxiety disorders that are interpretable from the standpoint of dimensional models of the internalizing spectrum. Further, we contend that these empirical findings can feed back into and help reshape conceptualizations of internalizing disorders in ways that make them more amenable to neurobiological analysis. PMID:19883142
ERIC Educational Resources Information Center
Johnson, Wendy; Deary, Ian J.
2011-01-01
The idea that information processing speed is related to cognitive ability has a long history. Much evidence has been amassed in its support, with respect to both individual differences in general intelligence and developmental trajectories. Two so-called elementary cognitive tasks, reaction time and inspection time, have been used to compile this…
Non-minimal Higgs inflation and frame dependence in cosmology
NASA Astrophysics Data System (ADS)
Steinwachs, Christian F.; Kamenshchik, Alexander Yu.
2013-02-01
We investigate a very general class of cosmological models with scalar fields non-minimally coupled to gravity. A particular representative in this class is given by the non-minimal Higgs inflation model in which the Standard Model Higgs boson and the inflaton are described by one and the same scalar particle. While the predictions of the non-minimal Higgs inflation scenario come numerically remarkably close to the recently discovered mass of the Higgs boson, there remains a conceptual problem in this model that is associated with the choice of the cosmological frame. While the classical theory is independent of this choice, we find by an explicit calculation that already the first quantum corrections induce a frame dependence. We give a geometrical explanation of this frame dependence by embedding it into a more general field theoretical context. From this analysis, some conceptional points in the long lasting cosmological debate: "Jordan frame vs. Einstein frame" become more transparent and in principle can be resolved in a natural way.
Bayesian inference based on stationary Fokker-Planck sampling.
Berrones, Arturo
2010-06-01
A novel formalism for bayesian learning in the context of complex inference models is proposed. The method is based on the use of the stationary Fokker-Planck (SFP) approach to sample from the posterior density. Stationary Fokker-Planck sampling generalizes the Gibbs sampler algorithm for arbitrary and unknown conditional densities. By the SFP procedure, approximate analytical expressions for the conditionals and marginals of the posterior can be constructed. At each stage of SFP, the approximate conditionals are used to define a Gibbs sampling process, which is convergent to the full joint posterior. By the analytical marginals efficient learning methods in the context of artificial neural networks are outlined. Offline and incremental bayesian inference and maximum likelihood estimation from the posterior are performed in classification and regression examples. A comparison of SFP with other Monte Carlo strategies in the general problem of sampling from arbitrary densities is also presented. It is shown that SFP is able to jump large low-probability regions without the need of a careful tuning of any step-size parameter. In fact, the SFP method requires only a small set of meaningful parameters that can be selected following clear, problem-independent guidelines. The computation cost of SFP, measured in terms of loss function evaluations, grows linearly with the given model's dimension.
Demographic noise can reverse the direction of deterministic selection
Constable, George W. A.; Rogers, Tim; McKane, Alan J.; Tarnita, Corina E.
2016-01-01
Deterministic evolutionary theory robustly predicts that populations displaying altruistic behaviors will be driven to extinction by mutant cheats that absorb common benefits but do not themselves contribute. Here we show that when demographic stochasticity is accounted for, selection can in fact act in the reverse direction to that predicted deterministically, instead favoring cooperative behaviors that appreciably increase the carrying capacity of the population. Populations that exist in larger numbers experience a selective advantage by being more stochastically robust to invasions than smaller populations, and this advantage can persist even in the presence of reproductive costs. We investigate this general effect in the specific context of public goods production and find conditions for stochastic selection reversal leading to the success of public good producers. This insight, developed here analytically, is missed by the deterministic analysis as well as by standard game theoretic models that enforce a fixed population size. The effect is found to be amplified by space; in this scenario we find that selection reversal occurs within biologically reasonable parameter regimes for microbial populations. Beyond the public good problem, we formulate a general mathematical framework for models that may exhibit stochastic selection reversal. In this context, we describe a stochastic analog to r−K theory, by which small populations can evolve to higher densities in the absence of disturbance. PMID:27450085
Context in Models of Human-Machine Systems
NASA Technical Reports Server (NTRS)
Callantine, Todd J.; Null, Cynthia H. (Technical Monitor)
1998-01-01
All human-machine systems models represent context. This paper proposes a theory of context through which models may be usefully related and integrated for design. The paper presents examples of context representation in various models, describes an application to developing models for the Crew Activity Tracking System (CATS), and advances context as a foundation for integrated design of complex dynamic systems.
Huberts, W; Donders, W P; Delhaas, T; van de Vosse, F N
2014-12-01
Patient-specific modeling requires model personalization, which can be achieved in an efficient manner by parameter fixing and parameter prioritization. An efficient variance-based method is using generalized polynomial chaos expansion (gPCE), but it has not been applied in the context of model personalization, nor has it ever been compared with standard variance-based methods for models with many parameters. In this work, we apply the gPCE method to a previously reported pulse wave propagation model and compare the conclusions for model personalization with that of a reference analysis performed with Saltelli's efficient Monte Carlo method. We furthermore differentiate two approaches for obtaining the expansion coefficients: one based on spectral projection (gPCE-P) and one based on least squares regression (gPCE-R). It was found that in general the gPCE yields similar conclusions as the reference analysis but at much lower cost, as long as the polynomial metamodel does not contain unnecessary high order terms. Furthermore, the gPCE-R approach generally yielded better results than gPCE-P. The weak performance of the gPCE-P can be attributed to the assessment of the expansion coefficients using the Smolyak algorithm, which might be hampered by the high number of model parameters and/or by possible non-smoothness in the output space. Copyright © 2014 John Wiley & Sons, Ltd.
Parker, Linda A; Kwiatkowska, Magdalena; Mechoulam, Raphael
2006-01-30
Chemotherapy patients report not only acute nausea and vomiting during the treatment itself, but also report anticipatory nausea and vomiting upon re-exposure to the cues associated with the treatment. We present a model of anticipatory nausea based on the emetic reactions of the Suncus murinus (musk shrew). Following three pairings of a novel distinctive contextual cue with the emetic effects of an injection of lithium chloride, the context acquired the potential to elicit conditioned retching in the absence of the toxin. The expression of this conditioned retching reaction was completely suppressed by pretreatment with each of the principal cannabinoids found in marijuana, Delta(9)-tetrahydrocannabinol or cannabidiol, at a dose that did not suppress general activity. On the other hand, pretreatment with a dose of ondansetron (a 5-HT(3) antagonist) that interferes with acute vomiting in this species, did not suppress the expression of conditioned retching during re-exposure to the lithium-paired context. These results support anecdotal claims that marijuana, but not ondansetron, may suppress the expression of anticipatory nausea.
The power prior: theory and applications.
Ibrahim, Joseph G; Chen, Ming-Hui; Gwon, Yeongjin; Chen, Fang
2015-12-10
The power prior has been widely used in many applications covering a large number of disciplines. The power prior is intended to be an informative prior constructed from historical data. It has been used in clinical trials, genetics, health care, psychology, environmental health, engineering, economics, and business. It has also been applied for a wide variety of models and settings, both in the experimental design and analysis contexts. In this review article, we give an A-to-Z exposition of the power prior and its applications to date. We review its theoretical properties, variations in its formulation, statistical contexts for which it has been used, applications, and its advantages over other informative priors. We review models for which it has been used, including generalized linear models, survival models, and random effects models. Statistical areas where the power prior has been used include model selection, experimental design, hierarchical modeling, and conjugate priors. Frequentist properties of power priors in posterior inference are established, and a simulation study is conducted to further examine the empirical performance of the posterior estimates with power priors. Real data analyses are given illustrating the power prior as well as the use of the power prior in the Bayesian design of clinical trials. Copyright © 2015 John Wiley & Sons, Ltd.
Phenomenology of stochastic exponential growth
NASA Astrophysics Data System (ADS)
Pirjol, Dan; Jafarpour, Farshid; Iyer-Biswas, Srividya
2017-06-01
Stochastic exponential growth is observed in a variety of contexts, including molecular autocatalysis, nuclear fission, population growth, inflation of the universe, viral social media posts, and financial markets. Yet literature on modeling the phenomenology of these stochastic dynamics has predominantly focused on one model, geometric Brownian motion (GBM), which can be described as the solution of a Langevin equation with linear drift and linear multiplicative noise. Using recent experimental results on stochastic exponential growth of individual bacterial cell sizes, we motivate the need for a more general class of phenomenological models of stochastic exponential growth, which are consistent with the observation that the mean-rescaled distributions are approximately stationary at long times. We show that this behavior is not consistent with GBM, instead it is consistent with power-law multiplicative noise with positive fractional powers. Therefore, we consider this general class of phenomenological models for stochastic exponential growth, provide analytical solutions, and identify the important dimensionless combination of model parameters, which determines the shape of the mean-rescaled distribution. We also provide a prescription for robustly inferring model parameters from experimentally observed stochastic growth trajectories.
Krans, Julie; Langner, Oliver; Reinecke, Andrea; Pearson, David G
2013-12-01
The present study addressed the role of context information and dual-task interference during the encoding of negative pictures on intrusion development and voluntary recall. Healthy participants were shown negative pictures with or without context information. Pictures were either viewed alone or concurrently with a visuospatial or verbal task. Participants reported their intrusive images of the pictures in a diary. At follow-up, perceptual and contextual memory was tested. Participants in the context group reported more intrusive images and perceptual voluntary memory than participants in the no context group. No effects of the concurrent tasks were found on intrusive image frequency, but perceptual and contextual memory was affected according to the cognitive load of the task. The analogue method cannot be generalized to real-life trauma and the secondary tasks may differ in cognitive load. The findings challenge a dual memory model of PTSD but support an account in which retrieval strategy, rather than encoding processes, accounts for the experience of involuntary versus voluntary recall. Copyright © 2013 Elsevier Ltd. All rights reserved.
ERIC Educational Resources Information Center
Lee, Chun-Yi; Chen, Ming-Jang; Chang, Wen-Long
2014-01-01
The aim of this study is to investigate the effects of solution methods and question prompts on generalization and justification of non-routine problem solving for Grade 9 students. The learning activities are based on the context of the frog jumping game. In addition, related computer tools were used to support generalization and justification of…
Scalar-tensor extension of the ΛCDM model
DOE Office of Scientific and Technical Information (OSTI.GOV)
Algoner, W.C.; Velten, H.E.S.; Zimdahl, W., E-mail: w.algoner@cosmo-ufes.org, E-mail: velten@pq.cnpq.br, E-mail: winfried.zimdahl@pq.cnpq.br
2016-11-01
We construct a cosmological scalar-tensor-theory model in which the Brans-Dicke type scalar Φ enters the effective (Jordan-frame) Hubble rate as a simple modification of the Hubble rate of the ΛCDM model. This allows us to quantify differences between the background dynamics of scalar-tensor theories and general relativity (GR) in a transparent and observationally testable manner in terms of one single parameter. Problems of the mapping of the scalar-field degrees of freedom on an effective fluid description in a GR context are discused. Data from supernovae, the differential age of old galaxies and baryon acoustic oscillations are shown to strongly limitmore » potential deviations from the standard model.« less
The effect of model uncertainty on some optimal routing problems
NASA Technical Reports Server (NTRS)
Mohanty, Bibhu; Cassandras, Christos G.
1991-01-01
The effect of model uncertainties on optimal routing in a system of parallel queues is examined. The uncertainty arises in modeling the service time distribution for the customers (jobs, packets) to be served. For a Poisson arrival process and Bernoulli routing, the optimal mean system delay generally depends on the variance of this distribution. However, as the input traffic load approaches the system capacity the optimal routing assignment and corresponding mean system delay are shown to converge to a variance-invariant point. The implications of these results are examined in the context of gradient-based routing algorithms. An example of a model-independent algorithm using online gradient estimation is also included.
Mediating objects: scientific and public functions of models in nineteenth-century biology.
Ludwig, David
2013-01-01
The aim of this article is to examine the scientific and public functions of two- and three-dimensional models in the context of three episodes from nineteenth-century biology. I argue that these models incorporate both data and theory by presenting theoretical assumptions in the light of concrete data or organizing data through theoretical assumptions. Despite their diverse roles in scientific practice, they all can be characterized as mediators between data and theory. Furthermore, I argue that these different mediating functions often reflect their different audiences that included specialized scientists, students, and the general public. In this sense, models in nineteenth-century biology can be understood as mediators between theory, data, and their diverse audiences.
Understanding the role of emotion in sense-making: a semiotic psychoanalytic oriented perspective.
Salvatore, Sergio; Venuleo, Claudia
2008-03-01
We propose a model of emotion grounded on Ignacio Matte Blanco's theory of the unconscious. According to this conceptualization, emotion is a generalized representation of the social context actors are involved in. We discuss how this model can help to better understand the sensemaking processes. For this purpose we present a hierarchical model of sensemaking based on the distinction between significance--the content of the sign--and sense--the psychological value of the act of producing the sign in the given contingence of the social exchange. According to this model, emotion categorization produces the frame of sense regulating the interpretation of the sense of the signs, therefore creating the psychological value of the sensemaking.
NASA Astrophysics Data System (ADS)
Grabau, Larry J.; Ma, Xin
2017-05-01
Using data from the 2006 Program for International Student Assessment (PISA), we explored nine aspects of science engagement (science self-efficacy, science self-concept, enjoyment of science, general interest in learning science, instrumental motivation for science, future-oriented science motivation, general value of science, personal value of science, and science-related activities) as outcomes and predictors of science achievement. Based on results from multilevel modelling with 4456 students nested within 132 schools, we found that all aspects of science engagement were statistically significantly and positively related to science achievement, and nearly all showed medium or large effect sizes. Each aspect was positively associated with one of the (four) practices (strategies) of science teaching. Focus on applications or models was positively related to the most aspects of science engagement (science self-concept, enjoyment of science, instrumental motivation for science, general value of science, and personal value of science). Hands-on activities were positively related to additional aspects of science engagement (science self-efficacy and general interest in learning science) and also showed a positive relationship with science achievement.
Mola, Ernesto
2013-06-01
Growing evidence supports the inclusion of patient empowerment as a key ingredient of care for patients with chronic conditions. In recent years, several studies based on patient empowerment, have been carried out in different European countries in the context of general practice and primary care to improve management of chronic diseases. These studies have shown good results of the care model, increasing patient and health professionals' satisfaction, adherence to guidelines and to treatment, and improving clinical outcomes. In 2011, the Wonca European Council included as the twelfth characteristic of the European definitions of general practice/family medicine: 'promote patient empowerment'. The aim of this paper is to clarify the meaning of 'patient empowerment' and to explain why family medicine should be considered the most suitable setting to promote it. The inclusion of patient empowerment as one of the essential characteristics of general practice fills a conceptual gap and clearly suggests to the European health care systems a tested model to face chronic diseases: involving and empowering patients in managing their own conditions to improve health and well-being.
1. General oblique view of the context, view to northeast, ...
1. General oblique view of the context, view to northeast, showing vehicle bays at west end and overhead doors at east end - Fort Hood, World War II Temporary Buildings, Company Maintenance Shop & Arms Room, North of Park Avenue at Forty-ninth Street, Killeen, Bell County, TX
Sleddens, Ester F C; Kremers, Stef P J; Stafleu, Annette; Dagnelie, Pieter C; De Vries, Nanne K; Thijs, Carel
2014-08-01
Research on parenting practices has focused on individual behaviors while largely failing to consider the context of their use, i.e., general parenting. We examined the extent to which food parenting practices predict children's dietary behavior (classified as unhealthy: snacking, sugar-sweetened beverage; and healthy: water and fruit intake). Furthermore, we tested the moderating role of general parenting on this relationship. Within the KOALA Birth Cohort Study, in the Netherlands, questionnaire data were collected at 6 and 8 years (N = 1654). Correlations were computed to assess the association between food parenting practices and general parenting (i.e., nurturance, behavioral control, structure, coercive control, and overprotection). Linear regression models were fitted to assess whether food parenting practices predict dietary behavior. Instrumental and emotional feeding, and pressure to eat were found to have associations with undesirable child dietary behavior (increased unhealthy intake/decreased healthy intake), whereas associations were in the desirable direction for covert control, encouragement and restriction. Moderation analyses were performed by evaluating interactions with general parenting. The associations of encouragement and covert control with desirable child dietary behaviors were found to be stronger for children who were reared in a positive parenting context. Future research should assess the influence of contextual parenting factors moderating the relationships between food parenting and child dietary behavior as the basis for the development of more effective family-based interventions. Copyright © 2014 Elsevier Ltd. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yang, Laurence; Yurkovich, James T.; Lloyd, Colton J.
Integrating omics data to refine or make context-specific models is an active field of constraint-based modeling. Proteomics now cover over 95% of the Escherichia coli proteome by mass. Genome-scale models of Metabolism and macromolecular Expression (ME) compute proteome allocation linked to metabolism and fitness. Using proteomics data, we formulated allocation constraints for key proteome sectors in the ME model. The resulting calibrated model effectively computed the “generalist” (wild-type) E. coli proteome and phenotype across diverse growth environments. Across 15 growth conditions, prediction errors for growth rate and metabolic fluxes were 69% and 14% lower, respectively. The sector-constrained ME model thusmore » represents a generalist ME model reflecting both growth rate maximization and “hedging” against uncertain environments and stresses, as indicated by significant enrichment of these sectors for the general stress response sigma factor σS. Finally, the sector constraints represent a general formalism for integrating omics data from any experimental condition into constraint-based ME models. The constraints can be fine-grained (individual proteins) or coarse-grained (functionally-related protein groups) as demonstrated here. Furthermore, this flexible formalism provides an accessible approach for narrowing the gap between the complexity captured by omics data and governing principles of proteome allocation described by systems-level models.« less
2009-01-01
Background There is a general expectation within healthcare that organizations should use evidence-based practice (EBP) as an approach to improving the quality of care. However, challenges exist regarding how to make EBP a reality, particularly at an organizational level and as a routine, sustained aspect of professional practice. Methods A mixed method explanatory case study was conducted to study context; i.e., in terms of the presence or absence of multiple, inter-related contextual elements and associated strategic approaches required for integrated, routine use of EBP ('institutionalization'). The Pettigrew et al. Content, Context, and Process model was used as the theoretical framework. Two sites in the US were purposively sampled to provide contrasting cases: i.e., a 'role model' site, widely recognized as demonstrating capacity to successfully implement and sustain EBP to a greater degree than others; and a 'beginner' site, self-perceived as early in the journey towards institutionalization. Results The two sites were clearly different in terms of their organizational context, level of EBP activity, and degree of institutionalization. For example, the role model site had a pervasive, integrated presence of EBP versus a sporadic, isolated presence in the beginner site. Within the inner context of the role model site, there was also a combination of the Pettigrew and colleagues' receptive elements that, together, appeared to enhance its ability to effectively implement EBP-related change at multiple levels. In contrast, the beginner site, which had been involved for a few years in EBP-related efforts, had primarily non-receptive conditions in several contextual elements and a fairly low overall level of EBP receptivity. The beginner site thus appeared, at the time of data collection, to lack an integrated context to either support or facilitate the institutionalization of EBP. Conclusion Our findings provide evidence of some of the key contextual elements that may require attention if institutionalization of EBP is to be realized. They also suggest the need for an integrated set of receptive contextual elements to achieve EBP institutionalization; and they further support the importance of specific interactions among these elements, including ways in which leadership affects other contextual elements positively or negatively. PMID:19948064
Constraints on a new post-general relativity cosmological parameter
NASA Astrophysics Data System (ADS)
Caldwell, Robert; Cooray, Asantha; Melchiorri, Alessandro
2007-07-01
A new cosmological variable is introduced to characterize the degree of departure from Einstein’s general relativity with a cosmological constant. The new parameter, ϖ, is the cosmological analog of γ, the parametrized post-Newtonian variable which measures the amount of spacetime curvature per unit mass. In the cosmological context, ϖ measures the difference between the Newtonian and longitudinal potentials in response to the same matter sources, as occurs in certain scalar-tensor theories of gravity. Equivalently, ϖ measures the scalar shear fluctuation in a dark-energy component. In the context of a vanilla, cosmological constant-dominated universe, a nonzero ϖ signals a departure from general relativity or a fluctuating cosmological constant. Using a phenomenological model for the time evolution ϖ=ϖ0ρDE/ρM which depends on the ratio of energy density in the cosmological constant to the matter density at each epoch, it is shown that the observed cosmic microwave background temperature anisotropies limit the overall normalization constant to be -0.4<ϖ0<0.1 at the 95% confidence level. Existing measurements of the cross-correlations of the cosmic microwave background with large-scale structure further limit ϖ0>-0.2 at the 95% CL. In the future, integrated Sachs-Wolfe and weak lensing measurements can more tightly constrain ϖ0, providing a valuable clue to the nature of dark energy and the validity of general relativity.
Automated smoother for the numerical decoupling of dynamics models.
Vilela, Marco; Borges, Carlos C H; Vinga, Susana; Vasconcelos, Ana Tereza R; Santos, Helena; Voit, Eberhard O; Almeida, Jonas S
2007-08-21
Structure identification of dynamic models for complex biological systems is the cornerstone of their reverse engineering. Biochemical Systems Theory (BST) offers a particularly convenient solution because its parameters are kinetic-order coefficients which directly identify the topology of the underlying network of processes. We have previously proposed a numerical decoupling procedure that allows the identification of multivariate dynamic models of complex biological processes. While described here within the context of BST, this procedure has a general applicability to signal extraction. Our original implementation relied on artificial neural networks (ANN), which caused slight, undesirable bias during the smoothing of the time courses. As an alternative, we propose here an adaptation of the Whittaker's smoother and demonstrate its role within a robust, fully automated structure identification procedure. In this report we propose a robust, fully automated solution for signal extraction from time series, which is the prerequisite for the efficient reverse engineering of biological systems models. The Whittaker's smoother is reformulated within the context of information theory and extended by the development of adaptive signal segmentation to account for heterogeneous noise structures. The resulting procedure can be used on arbitrary time series with a nonstationary noise process; it is illustrated here with metabolic profiles obtained from in-vivo NMR experiments. The smoothed solution that is free of parametric bias permits differentiation, which is crucial for the numerical decoupling of systems of differential equations. The method is applicable in signal extraction from time series with nonstationary noise structure and can be applied in the numerical decoupling of system of differential equations into algebraic equations, and thus constitutes a rather general tool for the reverse engineering of mechanistic model descriptions from multivariate experimental time series.
The interrogation decision-making model: A general theoretical framework for confessions.
Yang, Yueran; Guyll, Max; Madon, Stephanie
2017-02-01
This article presents a new model of confessions referred to as the interrogation decision-making model . This model provides a theoretical umbrella with which to understand and analyze suspects' decisions to deny or confess guilt in the context of a custodial interrogation. The model draws upon expected utility theory to propose a mathematical account of the psychological mechanisms that not only underlie suspects' decisions to deny or confess guilt at any specific point during an interrogation, but also how confession decisions can change over time. Findings from the extant literature pertaining to confessions are considered to demonstrate how the model offers a comprehensive and integrative framework for organizing a range of effects within a limited set of model parameters. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Complex systems and health behavior change: insights from cognitive science.
Orr, Mark G; Plaut, David C
2014-05-01
To provide proof-of-concept that quantum health behavior can be instantiated as a computational model that is informed by cognitive science, the Theory of Reasoned Action, and quantum health behavior theory. We conducted a synthetic review of the intersection of quantum health behavior change and cognitive science. We conducted simulations, using a computational model of quantum health behavior (a constraint satisfaction artificial neural network) and tested whether the model exhibited quantum-like behavior. The model exhibited clear signs of quantum-like behavior. Quantum health behavior can be conceptualized as constraint satisfaction: a mitigation between current behavioral state and the social contexts in which it operates. We outlined implications for moving forward with computational models of both quantum health behavior and health behavior in general.
The malleability of intertemporal choice
Lempert, Karolina M.; Phelps, Elizabeth A.
2015-01-01
Intertemporal choices are ubiquitous: people often have to choose between outcomes realized at different times. Although it is generally believed that people have stable tendencies toward being impulsive or patient, an emerging body of evidence indicates that intertemporal choice is malleable and can be profoundly influenced by context. How the choice is framed, or the state of the decision-maker at the time of choice, can induce a shift in preference. Framing effects are underpinned by: allocation of attention to choice attributes, reference-dependence and time construal. Incidental affective states and prospection also influence intertemporal choice. We advocate that intertemporal choice models account for these context effects, and encourage the use of this knowledge to nudge people toward making more advantageous choices. PMID:26483153
A general approach for predicting the behavior of the Supreme Court of the United States
Bommarito, Michael J.; Blackman, Josh
2017-01-01
Building on developments in machine learning and prior work in the science of judicial prediction, we construct a model designed to predict the behavior of the Supreme Court of the United States in a generalized, out-of-sample context. To do so, we develop a time-evolving random forest classifier that leverages unique feature engineering to predict more than 240,000 justice votes and 28,000 cases outcomes over nearly two centuries (1816-2015). Using only data available prior to decision, our model outperforms null (baseline) models at both the justice and case level under both parametric and non-parametric tests. Over nearly two centuries, we achieve 70.2% accuracy at the case outcome level and 71.9% at the justice vote level. More recently, over the past century, we outperform an in-sample optimized null model by nearly 5%. Our performance is consistent with, and improves on the general level of prediction demonstrated by prior work; however, our model is distinctive because it can be applied out-of-sample to the entire past and future of the Court, not a single term. Our results represent an important advance for the science of quantitative legal prediction and portend a range of other potential applications. PMID:28403140
The mind over the Web: the quest for the definition of a method for Internet research.
Riva, G
2001-02-01
Psychology is increasingly interested in understanding the characteristics of the Internet and its effects on people, groups and organizations. However, studying the Internet is not a simple task. First, the Internet is a medium that can be experienced in many different ways. Though a computer and keyboard are usually the mediator of our Internet experience, there are different ways in which users can explore the Internet, present themselves, and communicate using it. Second, the Internet is a social and cognitive space. The handling of information is linked to the activation of psychosocial relationships in which cognitions are elaborated. This happens inside a rather special kind of container--Cyberspace--which tends to rarefy the structural and process features of communication. Third, the Internet experience is always situated in a specific context, even when we are chatting alone in a room. In this sense it can only be fully understood through detailed analysis of the social context in which it happens. Starting from a general three-level model of interpersonal interaction in the Web, this paper tries to define a model of data analysis (Complementary Explorative Multilevel Data Analysis--CEMDA) suited to the constraints of Internet research. The main characteristics of the model are: the focus on different frames and objects for each considered unit of research; the mixed use of quantitative and qualitative tools; and the final integration of results in a general framework.
ERIC Educational Resources Information Center
Marsh, Richard L.; Meeks, J. Thadeus; Hicks, Jason L.; Cook, Gabriel I.; Clark-Foos, Arlo
2006-01-01
Context variability can be defined as the number of preexperimental contexts in which a given concept appears. Following M. Steyvers and K. J. Malmberg's (2003) work, the authors have shown that concepts that are experienced in fewer preexperimental contexts generally are better remembered in episodic memory tasks than concepts that are …
Shukla, Shrivridhi; Muchomba, Felix M; McCoyd, Judith L M
2018-06-01
Integrated models of HIV/AIDS service delivery are believed to have advantages over stand-alone models of care from health planners' and providers' perspectives. Integration models differ, yet there is little information about the influence of differing models on workers' beliefs about models' efficacy. Here, we examine the effect of integration of HIV care into the general health system in India. In 2014, India replaced its stand-alone model of HIV service delivery-Community Care Centers (CCCs)-with a purported integrated model that delivers HIV medical services at general hospitals and HIV psychosocial services at nearby Care and Support Centers (CSCs). We examine 15 health workers' perceptions of how change from the earlier stand-alone model to the current model impacted women's care in a district in Uttar Pradesh, India. Results indicate that (1) Women's antiretroviral (ART) adherence and utilization of psychosocial support service for HIV/AIDS suffered when services were not provided at one site; (2) Provision of inpatient care in the CCC model offered women living in poverty personal safety in accessing HIV health services and promoted chances of competent ART usage and repeat service utilization; and (3) Although integration of HIV services with the general health system was perceived to improve patient anonymity and decrease chances of HIV-related stigma and discrimination, resource shortages continued to plague the integrated system while shifting costs of time and money to the patients. Findings suggest that integration efforts need to consider the context of service provision and the gendered nature of access to HIV care.
A continuous-time neural model for sequential action.
Kachergis, George; Wyatte, Dean; O'Reilly, Randall C; de Kleijn, Roy; Hommel, Bernhard
2014-11-05
Action selection, planning and execution are continuous processes that evolve over time, responding to perceptual feedback as well as evolving top-down constraints. Existing models of routine sequential action (e.g. coffee- or pancake-making) generally fall into one of two classes: hierarchical models that include hand-built task representations, or heterarchical models that must learn to represent hierarchy via temporal context, but thus far lack goal-orientedness. We present a biologically motivated model of the latter class that, because it is situated in the Leabra neural architecture, affords an opportunity to include both unsupervised and goal-directed learning mechanisms. Moreover, we embed this neurocomputational model in the theoretical framework of the theory of event coding (TEC), which posits that actions and perceptions share a common representation with bidirectional associations between the two. Thus, in this view, not only does perception select actions (along with task context), but actions are also used to generate perceptions (i.e. intended effects). We propose a neural model that implements TEC to carry out sequential action control in hierarchically structured tasks such as coffee-making. Unlike traditional feedforward discrete-time neural network models, which use static percepts to generate static outputs, our biological model accepts continuous-time inputs and likewise generates non-stationary outputs, making short-timescale dynamic predictions. © 2014 The Author(s) Published by the Royal Society. All rights reserved.
Thomas, Kendra J; Napolitano, Patricia H
2017-12-01
The purpose of this study is to understand the development of Brazilian adolescents' justice perceptions across different contexts of educational privilege. Past research has found that, in adolescence, the belief in a just world (BJW) differentiates between personal and general and declines. However, prior research has not included adolescents from various socioeconomic statuses, samples in Latin America, or focused on the role of the educational context on the developmental trajectory. Participants were 385 adolescents from 3 schools (private, public and military) in Southern Brazil between 9th and 11th grade. Students completed the personal and general BJW survey. Results revealed a significant interaction of school and grade level of adolescents' personal BJW. Contrary to previous research, personal and general BJW was not always lower in higher grades. Among privileged educational contexts, data indicated that personal BJW may even increase, with the decrease notable in the lower resourced school. In contrast, general BJW was relatively consistent across all Brazilian adolescents. Results provide important insight into the role that privilege and education play across adolescents' development of BJW. This research questions the generalizability of previous studies on the development of BJW and indicates that the trajectory may be dependent upon educational and cultural context. © 2016 International Union of Psychological Science.
Context generalization in Drosophila visual learning requires the mushroom bodies
NASA Astrophysics Data System (ADS)
Liu, Li; Wolf, Reinhard; Ernst, Roman; Heisenberg, Martin
1999-08-01
The world is permanently changing. Laboratory experiments on learning and memory normally minimize this feature of reality, keeping all conditions except the conditioned and unconditioned stimuli as constant as possible. In the real world, however, animals need to extract from the universe of sensory signals the actual predictors of salient events by separating them from non-predictive stimuli (context). In principle, this can be achieved ifonly those sensory inputs that resemble the reinforcer in theirtemporal structure are taken as predictors. Here we study visual learning in the fly Drosophila melanogaster, using a flight simulator,, and show that memory retrieval is, indeed, partially context-independent. Moreover, we show that the mushroom bodies, which are required for olfactory but not visual or tactile learning, effectively support context generalization. In visual learning in Drosophila, it appears that a facilitating effect of context cues for memory retrieval is the default state, whereas making recall context-independent requires additional processing.
Thorn, M C; Kelly, M; Rees, J H; Sánchez-Friera, P; Calvez, M
2002-09-01
Bioaccumulation and dosimetric models have been developed that allow the computation of dose rates to a wide variety of plants and animals in the context of the deep geological disposal of solid radioactive wastes. These dose rates can be compared with the threshold dose rates at which significant deleterious effects have been observed in field and laboratory observations. This provides a general indication of whether effects on ecosystems could be observable, but does not quantify the level of those effects. To address this latter issue, two indicator organisms were identified and exposure-response relationships were developed for endpoints of potential interest (mortality in conifers and the induction of skeletal malformations in rodents irradiated in utero). The bioaccumulation, dosimetry and exposure-response models were implemented and used to evaluate the potential significance of radionuclide releases from a proposed deep geological repository for radioactive wastes in France. This evaluation was undertaken in the context of a programme of assessment studies being performed by the Agence nationale pour la gestion des déchets radioactifs (ANDRA).
Software Helps Retrieve Information Relevant to the User
NASA Technical Reports Server (NTRS)
Mathe, Natalie; Chen, James
2003-01-01
The Adaptive Indexing and Retrieval Agent (ARNIE) is a code library, designed to be used by an application program, that assists human users in retrieving desired information in a hypertext setting. Using ARNIE, the program implements a computational model for interactively learning what information each human user considers relevant in context. The model, called a "relevance network," incrementally adapts retrieved information to users individual profiles on the basis of feedback from the users regarding specific queries. The model also generalizes such knowledge for subsequent derivation of relevant references for similar queries and profiles, thereby, assisting users in filtering information by relevance. ARNIE thus enables users to categorize and share information of interest in various contexts. ARNIE encodes the relevance and structure of information in a neural network dynamically configured with a genetic algorithm. ARNIE maintains an internal database, wherein it saves associations, and from which it returns associated items in response to a query. A C++ compiler for a platform on which ARNIE will be utilized is necessary for creating the ARNIE library but is not necessary for the execution of the software.
Bergman, Mindy E; Palmieri, Patrick A; Drasgow, Fritz; Ormerod, Alayne J
2012-01-01
A general model of workplace prejudice acts, their antecedents, and their consequences is proposed and examined in the context of racial/ethnic harassment and discrimination (REHD). Antecedents proposed and tested here include context and climate, whereas consequences proposed and tested here include work, supervisor, and opportunity satisfaction and turnover intentions. The theoretical model is first tested and cross-validated in two ethnically diverse subsamples (approximately 2,000 each). Then, hierarchical multigroup modeling was conducted to determine whether the relationships among REHD, its antecedents, and its outcomes are equivalent across five racial/ethnic groups (N = 1,000 per group) in the U.S. military. This addresses the issue of differential exposure (i.e., varying amounts of stressors across groups) versus differential vulnerability (i.e., discrepant impact of a stressor on outcomes across groups) across racial/ethnic groups. Consistent with expectations, results suggest that although racial/ethnic groups differ in their mean exposure to REHD, the relationships among REHD and its outcomes are the same across race/ethnicity, supporting the differential exposure view. In addition, the results show some differences between antecedents and REHD across race/ethnicity.
Managers as Writers: A Metanalysis of Research in Context.
ERIC Educational Resources Information Center
Smeltzer, Larry R.; Thomas, Gail Fann
1994-01-01
Argues that managers write within a unique context, and, thus, much of what is known about writing in general or professional writing may not apply. Reviews the literature on managerial writing, finding a paucity of research and a heavy emphasis on survey methodology. Offers six general research questions for future research. (SR)
ERIC Educational Resources Information Center
Pintrich, Paul R.
2003-01-01
Develops a motivational science perspective on student motivation in learning and teaching contexts that highlights 3 general themes for motivational research. The 3 themes include the importance of a general scientific approach for research on student motivation, the utility of multidisciplinary perspectives, and the importance of use-inspired…
Developing an ELT Context-Specific Teacher Efficacy Instrument
ERIC Educational Resources Information Center
Akbari, Ramin; Tavassoli, Kobra
2014-01-01
Teacher efficacy is a topic of significance in mainstream education and various instruments have been developed to measure this construct. The available instruments however, are general both in terms of their subject matter and context. To compensate for this generality, the present study aims to develop a new teacher efficacy instrument whose…
Treatment model in children with speech disorders and its therapeutic efficiency.
Barberena, Luciana; Keske-Soares, Márcia; Cervi, Taís; Brandão, Mariane
2014-07-01
Introduction Speech articulation disorders affect the intelligibility of speech. Studies on therapeutic models show the effectiveness of the communication treatment. Objective To analyze the progress achieved by treatment with the ABAB-Withdrawal and Multiple Probes Model in children with different degrees of phonological disorders. Methods The diagnosis of speech articulation disorder was determined by speech and hearing evaluation and complementary tests. The subjects of this research were eight children, with the average age of 5:5. The children were distributed into four groups according to the degrees of the phonological disorders, based on the percentage of correct consonants, as follows: severe, moderate to severe, mild to moderate, and mild. The phonological treatment applied was the ABAB-Withdrawal and Multiple Probes Model. The development of the therapy by generalization was observed through the comparison between the two analyses: contrastive and distinctive features at the moment of evaluation and reevaluation. Results The following types of generalization were found: to the items not used in the treatment (other words), to another position in the word, within a sound class, to other classes of sounds, and to another syllable structure. Conclusion The different types of generalization studied showed the expansion of production and proper use of therapy-trained targets in other contexts or untrained environments. Therefore, the analysis of the generalizations proved to be an important criterion to measure the therapeutic efficacy.
A generalized form of the Bernoulli Trial collision scheme in DSMC: Derivation and evaluation
NASA Astrophysics Data System (ADS)
Roohi, Ehsan; Stefanov, Stefan; Shoja-Sani, Ahmad; Ejraei, Hossein
2018-02-01
The impetus of this research is to present a generalized Bernoulli Trial collision scheme in the context of the direct simulation Monte Carlo (DSMC) method. Previously, a subsequent of several collision schemes have been put forward, which were mathematically based on the Kac stochastic model. These include Bernoulli Trial (BT), Ballot Box (BB), Simplified Bernoulli Trial (SBT) and Intelligent Simplified Bernoulli Trial (ISBT) schemes. The number of considered pairs for a possible collision in the above-mentioned schemes varies between N (l) (N (l) - 1) / 2 in BT, 1 in BB, and (N (l) - 1) in SBT or ISBT, where N (l) is the instantaneous number of particles in the lth cell. Here, we derive a generalized form of the Bernoulli Trial collision scheme (GBT) where the number of selected pairs is any desired value smaller than (N (l) - 1), i.e., Nsel < (N (l) - 1), keeping the same the collision frequency and accuracy of the solution as the original SBT and BT models. We derive two distinct formulas for the GBT scheme, where both formula recover BB and SBT limits if Nsel is set as 1 and N (l) - 1, respectively, and provide accurate solutions for a wide set of test cases. The present generalization further improves the computational efficiency of the BT-based collision models compared to the standard no time counter (NTC) and nearest neighbor (NN) collision models.
Are Earth System model software engineering practices fit for purpose? A case study.
NASA Astrophysics Data System (ADS)
Easterbrook, S. M.; Johns, T. C.
2009-04-01
We present some analysis and conclusions from a case study of the culture and practices of scientists at the Met Office and Hadley Centre working on the development of software for climate and Earth System models using the MetUM infrastructure. The study examined how scientists think about software correctness, prioritize their requirements in making changes, and develop a shared understanding of the resulting models. We conclude that highly customized techniques driven strongly by scientific research goals have evolved for verification and validation of such models. In a formal software engineering context these represents costly, but invaluable, software integration tests with considerable benefits. The software engineering practices seen also exhibit recognisable features of both agile and open source software development projects - self-organisation of teams consistent with a meritocracy rather than top-down organisation, extensive use of informal communication channels, and software developers who are generally also users and science domain experts. We draw some general conclusions on whether these practices work well, and what new software engineering challenges may lie ahead as Earth System models become ever more complex and petascale computing becomes the norm.
ERIC Educational Resources Information Center
Anthony, Seth
2014-01-01
Part I: Students' participation in inquiry-based chemistry laboratory curricula, and, in particular, engagement with key thinking processes in conjunction with these experiences, is linked with success at the difficult task of "transfer"--applying their knowledge in new contexts to solve unfamiliar types of problems. We investigate…
Autocorrelation and Regularization of Query-Based Information Retrieval Scores
2008-02-01
of the most general information retrieval models [ Salton , 1968]. By treating a query as a very short document, documents and queries can be rep... Salton , 1971]. In the context of single link hierarchical clustering, Jardine and van Rijsbergen showed that ranking all k clusters and retrieving a...a document about “dogs”, then the system will always miss this document when a user queries “dog”. Salton recognized that a document’s representation
ERIC Educational Resources Information Center
Stambler, Moses
In explorations of American literature in high school, the tradition of sailormen and the sea is generally not considered independently or distinctly because the sea is not viewed as a separate region of thought. Songs of the whalers and sailors of the sea and the inland waterways are frequently related to the historical and spatial context of…
D-cycloserine enhances generalization of fear extinction in children.
Byrne, Simon P; Rapee, Ronald M; Richardson, Rick; Malhi, Gin S; Jones, Michael; Hudson, Jennifer L
2015-06-01
For exposure therapy to be successful, it is essential that fear extinction learning extends beyond the treatment setting. D-cycloserine (DCS) may facilitate treatment gains by increasing generalization of extinction learning, however, its effects have not been tested in children. We examined whether DCS enhanced generalization of fear extinction learning across different stimuli and contexts among children with specific phobias. The study was a double-blind placebo-controlled randomized controlled trial among dog or spider phobic children aged 6-14. Participants ingested either 50 mg of DCS (n = 18) or placebo (n = 17) before receiving a single prolonged exposure session to their feared stimulus. Return of fear was examined 1 week later to a different stimulus (a different dog or spider), presented in both the original treatment context and an alternate context. Avoidance and fear were measured with Behavior Approach Tests (BATs), where the child was asked to increase proximity to the stimulus while reporting their fear level. There were no differences in BAT performance between groups during the exposure session or when a new stimulus was later presented in the treatment context. However, when the new stimulus was presented in a different context, relative to placebo, the DCS group showed less avoidance (P = .03) and less increase in fear (P = .04) with moderate effect sizes. DCS enabled children to better retain their fear extinction learning. This new learning generalized to different stimuli and contexts. © 2015 Wiley Periodicals, Inc.
Reeder, Patricia A.; Newport, Elissa L.; Aslin, Richard N.
2012-01-01
A fundamental component of language acquisition involves organizing words into grammatical categories. Previous literature has suggested a number of ways in which this categorization task might be accomplished. Here we ask whether the patterning of the words in a corpus of linguistic input (distributional information) is sufficient, along with a small set of learning biases, to extract these underlying structural categories. In a series of experiments, we show that learners can acquire linguistic form-classes, generalizing from instances of the distributional contexts of individual words in the exposure set to the full range of contexts for all the words in the set. Crucially, we explore how several specific distributional variables enable learners to form a category of lexical items and generalize to novel words, yet also allow for exceptions that maintain lexical specificity. We suggest that learners are sensitive to the contexts of individual words, the overlaps among contexts across words, the non-overlap of contexts (or systematic gaps in information), and the size of the exposure set. We also ask how learners determine the category membership of a new word for which there is very sparse contextual information. We find that, when there are strong category cues and robust category learning of other words, adults readily generalize the distributional properties of the learned category to a new word that shares just one context with the other category members. However, as the distributional cues regarding the category become sparser and contain more consistent gaps, learners show more conservatism in generalizing distributional properties to the novel word. Taken together, these results show that learners are highly systematic in their use of the distributional properties of the input corpus, using them in a principled way to determine when to generalize and when to preserve lexical specificity. PMID:23089290
Reeder, Patricia A; Newport, Elissa L; Aslin, Richard N
2013-02-01
A fundamental component of language acquisition involves organizing words into grammatical categories. Previous literature has suggested a number of ways in which this categorization task might be accomplished. Here we ask whether the patterning of the words in a corpus of linguistic input (distributional information) is sufficient, along with a small set of learning biases, to extract these underlying structural categories. In a series of experiments, we show that learners can acquire linguistic form-classes, generalizing from instances of the distributional contexts of individual words in the exposure set to the full range of contexts for all the words in the set. Crucially, we explore how several specific distributional variables enable learners to form a category of lexical items and generalize to novel words, yet also allow for exceptions that maintain lexical specificity. We suggest that learners are sensitive to the contexts of individual words, the overlaps among contexts across words, the non-overlap of contexts (or systematic gaps in information), and the size of the exposure set. We also ask how learners determine the category membership of a new word for which there is very sparse contextual information. We find that, when there are strong category cues and robust category learning of other words, adults readily generalize the distributional properties of the learned category to a new word that shares just one context with the other category members. However, as the distributional cues regarding the category become sparser and contain more consistent gaps, learners show more conservatism in generalizing distributional properties to the novel word. Taken together, these results show that learners are highly systematic in their use of the distributional properties of the input corpus, using them in a principled way to determine when to generalize and when to preserve lexical specificity. Copyright © 2012 Elsevier Inc. All rights reserved.
A Role for the X Chromosome in Sex Differences in Variability in General Intelligence?
Johnson, Wendy; Carothers, Andrew; Deary, Ian J
2009-11-01
There is substantial evidence that males are more variable than females in general intelligence. In recent years, researchers have presented this as a reason that, although there is little, if any, mean sex difference in general intelligence, males tend to be overrepresented at both ends of its overall distribution. Part of the explanation could be the presence of genes on the X chromosome related both to syndromal disorders involving mental retardation and to population variation in general intelligence occurring normally. Genes on the X chromosome appear overrepresented among genes with known involvement in mental retardation, which is consistent with a model we developed of the population distribution of general intelligence as a mixture of two normal distributions. Using this model, we explored the expected ratios of males to females at various points in the distribution and estimated the proportion of variance in general intelligence potentially due to genes on the X chromosome. These estimates provide clues to the extent to which biologically based sex differences could be manifested in the environment as sex differences in displayed intellectual abilities. We discuss these observations in the context of sex differences in specific cognitive abilities and evolutionary theories of sexual selection. © 2009 Association for Psychological Science.
Hierarchical Context Modeling for Video Event Recognition.
Wang, Xiaoyang; Ji, Qiang
2016-10-11
Current video event recognition research remains largely target-centered. For real-world surveillance videos, targetcentered event recognition faces great challenges due to large intra-class target variation, limited image resolution, and poor detection and tracking results. To mitigate these challenges, we introduced a context-augmented video event recognition approach. Specifically, we explicitly capture different types of contexts from three levels including image level, semantic level, and prior level. At the image level, we introduce two types of contextual features including the appearance context features and interaction context features to capture the appearance of context objects and their interactions with the target objects. At the semantic level, we propose a deep model based on deep Boltzmann machine to learn event object representations and their interactions. At the prior level, we utilize two types of prior-level contexts including scene priming and dynamic cueing. Finally, we introduce a hierarchical context model that systematically integrates the contextual information at different levels. Through the hierarchical context model, contexts at different levels jointly contribute to the event recognition. We evaluate the hierarchical context model for event recognition on benchmark surveillance video datasets. Results show that incorporating contexts in each level can improve event recognition performance, and jointly integrating three levels of contexts through our hierarchical model achieves the best performance.
Assessment Research in the Context of Practice.
ERIC Educational Resources Information Center
Tittle, Carol Kehr
Commemorating the work of Anne Cleary, the author considers the need for research on assessment in the practice context, provides an example of research in context, and proposes general areas of development for assessment research in the context of practice. Research has shown that effects of testing programs on practice are often not those that…
Signals from flavor changing scalar currents at the future colliders
DOE Office of Scientific and Technical Information (OSTI.GOV)
Atwood, D.; Reina, L.; Soni, A.
1996-11-22
We present a general phenomenological analysis of a class of Two Higgs Doublet Models with Flavor Changing Neutral Currents arising at the tree level. The existing constraints mainly affect the couplings of the first two generations of quarks, leaving the possibility for non negligible Flavor Changing couplings of the top quark open. The next generation of lepton and hadron colliders will offer the right environment to study the physics of the top quark and to unravel the presence of new physics beyond the Standard Model. In this context we discuss some interesting signals from Flavor Changing Scalar Neutral Currents.
Observations on the T lnR term in the quark-antiquark free energy
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kiskis, J.
1986-06-15
Consider the response of a pure gauge theory at temperature T to an external quark-antiquark pair separated by R. In the confining phase, the leading term in the free energy at large R is sigmaR. A string-model calculation has given T lnR for the next-to-leading term. In this paper, the origin of the T lnR term is considered in a more general context that includes the analog spin model and the lattice gauge theory at strong coupling. The connection with transverse fluctuations is emphasized.
A new generation of intelligent trainable tools for analyzing large scientific image databases
NASA Technical Reports Server (NTRS)
Fayyad, Usama M.; Smyth, Padhraic; Atkinson, David J.
1994-01-01
The focus of this paper is on the detection of natural, as opposed to human-made, objects. The distinction is important because, in the context of image analysis, natural objects tend to possess much greater variability in appearance than human-made objects. Hence, we shall focus primarily on the use of algorithms that 'learn by example' as the basis for image exploration. The 'learn by example' approach is potentially more generally applicable compared to model-based vision methods since domain scientists find it relatively easier to provide examples of what they are searching for versus describing a model.
Finite-deformation phase-field chemomechanics for multiphase, multicomponent solids
NASA Astrophysics Data System (ADS)
Svendsen, Bob; Shanthraj, Pratheek; Raabe, Dierk
2018-03-01
The purpose of this work is the development of a framework for the formulation of geometrically non-linear inelastic chemomechanical models for a mixture of multiple chemical components diffusing among multiple transforming solid phases. The focus here is on general model formulation. No specific model or application is pursued in this work. To this end, basic balance and constitutive relations from non-equilibrium thermodynamics and continuum mixture theory are combined with a phase-field-based description of multicomponent solid phases and their interfaces. Solid phase modeling is based in particular on a chemomechanical free energy and stress relaxation via the evolution of phase-specific concentration fields, order-parameter fields (e.g., related to chemical ordering, structural ordering, or defects), and local internal variables. At the mixture level, differences or contrasts in phase composition and phase local deformation in phase interface regions are treated as mixture internal variables. In this context, various phase interface models are considered. In the equilibrium limit, phase contrasts in composition and local deformation in the phase interface region are determined via bulk energy minimization. On the chemical side, the equilibrium limit of the current model formulation reduces to a multicomponent, multiphase, generalization of existing two-phase binary alloy interface equilibrium conditions (e.g., KKS). On the mechanical side, the equilibrium limit of one interface model considered represents a multiphase generalization of Reuss-Sachs conditions from mechanical homogenization theory. Analogously, other interface models considered represent generalizations of interface equilibrium conditions consistent with laminate and sharp-interface theory. In the last part of the work, selected existing models are formulated within the current framework as special cases and discussed in detail.
NASA Astrophysics Data System (ADS)
Alinea, Allan L.; Kubota, Takahiro
2018-03-01
We perform adiabatic regularization of power spectrum in nonminimally coupled general single-field inflation with varying speed of sound. The subtraction is performed within the framework of earlier study by Urakawa and Starobinsky dealing with the canonical inflation. Inspired by Fakir and Unruh's model on nonminimally coupled chaotic inflation, we find upon imposing near scale-invariant condition, that the subtraction term exponentially decays with the number of e -folds. As in the result for the canonical inflation, the regularized power spectrum tends to the "bare" power spectrum as the Universe expands during (and even after) inflation. This work justifies the use of the "bare" power spectrum in standard calculation in the most general context of slow-roll single-field inflation involving nonminimal coupling and varying speed of sound.
Extreme events and event size fluctuations in biased random walks on networks.
Kishore, Vimal; Santhanam, M S; Amritkar, R E
2012-05-01
Random walk on discrete lattice models is important to understand various types of transport processes. The extreme events, defined as exceedences of the flux of walkers above a prescribed threshold, have been studied recently in the context of complex networks. This was motivated by the occurrence of rare events such as traffic jams, floods, and power blackouts which take place on networks. In this work, we study extreme events in a generalized random walk model in which the walk is preferentially biased by the network topology. The walkers preferentially choose to hop toward the hubs or small degree nodes. In this setting, we show that extremely large fluctuations in event sizes are possible on small degree nodes when the walkers are biased toward the hubs. In particular, we obtain the distribution of event sizes on the network. Further, the probability for the occurrence of extreme events on any node in the network depends on its "generalized strength," a measure of the ability of a node to attract walkers. The generalized strength is a function of the degree of the node and that of its nearest neighbors. We obtain analytical and simulation results for the probability of occurrence of extreme events on the nodes of a network using a generalized random walk model. The result reveals that the nodes with a larger value of generalized strength, on average, display lower probability for the occurrence of extreme events compared to the nodes with lower values of generalized strength.
Recombinative Generalization: An Exploratory Study in Musical Reading
Perez, William Ferreira; de Rose, Julio C
2010-01-01
The present study aimed to extend the findings of recombinative generalization research in alphabetical reading and spelling to the context of musical reading. One participant was taught to respond discriminatively to six two-note sequences, choosing the corresponding notation on the staff in the presence of each sequence. When novel three- and four-note sequences were presented, she selected the corresponding notation. These results suggest the generality of previous research to the context of musical teaching. PMID:22477462
Army Support of Military Cyberspace Operations: Joint Contexts and Global Escalation Implications
2015-01-01
Contexts and Global Escalation Implications 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e...the command under the leadership of Lieu- tenant General Rhett Hernandez as well as its current operations led by Lieutenant General Edward Cardon ...operations led by Lieutenant General Edward Cardon . This includes a brief review of recent efforts to establish Fort Gordon, Georgia as the center of
Fear Generalization and Anxiety: Behavioral and Neural Mechanisms.
Dunsmoor, Joseph E; Paz, Rony
2015-09-01
Fear can be an adaptive emotion that helps defend against potential danger. Classical conditioning models elegantly describe how animals learn which stimuli in the environment signal danger, but understanding how this learning is generalized to other stimuli that resemble aspects of a learned threat remains a challenge. Critically, the overgeneralization of fear to harmless stimuli or situations is a burden to daily life and characteristic of posttraumatic stress disorder and other anxiety disorders. Here, we review emerging evidence on behavioral and neural mechanisms of generalization of emotional learning with the goal of encouraging further research on generalization in anxiety disorders. We begin by placing research on fear generalization in a rich historical context of stimulus generalization dating back to Pavlov, which lays the foundation for theoretical and experimental approaches used today. We then transition to contemporary behavioral and neurobiological research on generalization of emotional learning in humans and nonhuman animals and discuss the factors that promote generalization on the one hand from discrimination on the other hand. Copyright © 2015 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.
Alvaro, M; Bonilla, L L; Carretero, M; Melnik, R V N; Prabhakar, S
2013-08-21
In this paper we develop a kinetic model for the analysis of semiconductor superlattices, accounting for quantum effects. The model consists of a Boltzmann-Poisson type system of equations with simplified Bhatnagar-Gross-Krook collisions, obtained from the general time-dependent Schrödinger-Poisson model using Wigner functions. This system for superlattice transport is supplemented by the quantum mechanical part of the model based on the Ben-Daniel-Duke form of the Schrödinger equation for a cylindrical superlattice of finite radius. The resulting energy spectrum is used to characterize the Fermi-Dirac distribution that appears in the Bhatnagar-Gross-Krook collision, thereby coupling the quantum mechanical and kinetic parts of the model. The kinetic model uses the dispersion relation obtained by the generalized Kronig-Penney method, and allows us to estimate radii of quantum wire superlattices that have the same miniband widths as in experiments. It also allows us to determine more accurately the time-dependent characteristics of superlattices, in particular their current density. Results, for several experimentally grown superlattices, are discussed in the context of self-sustained coherent oscillations of the current density which are important in an increasing range of current and potential applications.
Modeling logistic performance in quantitative microbial risk assessment.
Rijgersberg, Hajo; Tromp, Seth; Jacxsens, Liesbeth; Uyttendaele, Mieke
2010-01-01
In quantitative microbial risk assessment (QMRA), food safety in the food chain is modeled and simulated. In general, prevalences, concentrations, and numbers of microorganisms in media are investigated in the different steps from farm to fork. The underlying rates and conditions (such as storage times, temperatures, gas conditions, and their distributions) are determined. However, the logistic chain with its queues (storages, shelves) and mechanisms for ordering products is usually not taken into account. As a consequence, storage times-mutually dependent in successive steps in the chain-cannot be described adequately. This may have a great impact on the tails of risk distributions. Because food safety risks are generally very small, it is crucial to model the tails of (underlying) distributions as accurately as possible. Logistic performance can be modeled by describing the underlying planning and scheduling mechanisms in discrete-event modeling. This is common practice in operations research, specifically in supply chain management. In this article, we present the application of discrete-event modeling in the context of a QMRA for Listeria monocytogenes in fresh-cut iceberg lettuce. We show the potential value of discrete-event modeling in QMRA by calculating logistic interventions (modifications in the logistic chain) and determining their significance with respect to food safety.
Context-induced relapse after extinction versus punishment: similarities and differences.
Marchant, Nathan J; Campbell, Erin J; Pelloux, Yann; Bossert, Jennifer M; Shaham, Yavin
2018-05-24
Results from clinical studies suggest that drug relapse and craving are often provoked by exposure to drug-associated contexts. Since 2002, this phenomenon has been modeled in laboratory animals using the ABA renewal model. In the classical version of this model, rats with a history of drug self-administration in one context (A) undergo extinction in a different context (B) and reinstate (or relapse to) drug seeking after exposure to the original drug-associated context (A). In a more recent version of the model introduced in 2013, the experimental conditions in context A are identical to those used in the classical model, but drug-reinforced responding in context B is suppressed by probabilistic punishment. The punishment-based ABA renewal model is proposed to resemble abstinence in humans, which is often initiated by the desire to avoid the negative consequences of drug use. The goal of our review is to discuss similarities and differences in mechanisms that play a role in suppression of drug seeking in context B and context-induced relapse to drug seeking in context A in the two models. We first describe psychological mechanisms that mediate extinction and punishment of drug-reinforced responding in context B. We then summarize recent findings on brain mechanisms of context-induced relapse of drug seeking after extinction, or punishment-imposed abstinence. These findings demonstrate both similarities and differences in brain mechanisms underlying relapse in the two variations of the ABA renewal model. We conclude by briefly discussing clinical implications of the preclinical studies.
de la Colina, M A; Pompilio, L; Hauber, M E; Reboreda, J C; Mahler, B
2018-03-01
Obligate avian brood parasites lay their eggs in nests of other host species, which assume all the costs of parental care for the foreign eggs and chicks. The most common defensive response to parasitism is the rejection of foreign eggs by hosts. Different cognitive mechanisms and decision-making rules may guide both egg recognition and rejection behaviors. Classical optimization models generally assume that decisions are based on the absolute properties of the options (i.e., absolute valuation). Increasing evidence shows instead that hosts' rejection decisions also depend on the context in which options are presented (i.e., context-dependent valuation). Here we study whether the chalk-browed mockingbird's (Mimus saturninus) rejection of parasitic shiny cowbird (Molothrus bonariensis) eggs is a fixed behavior or varies with the context of the clutch. We tested three possible context-dependent mechanisms: (1) range effect, (2) habituation to variation, and (3) sensitization to variation. We found that mockingbird rejection of parasitic eggs does not change according to the characteristics of the other eggs in the nest. Thus, rejection decisions may exclusively depend on the objective characteristics of the eggs, meaning that the threshold of acceptance or rejection of a foreign egg is context-independent in this system.
Sierra-Fitzgerald, O; Quevedo-Caicedo, J
The aim of this article is to relate two theories regarding the structure of the human mind. We suggest that the theory of multiple intelligences, a neurocognitive theory of the psychologist Howard Garnerd provides a suitable context for theoretical understanding and validation of the hypothesis of the pathology of superiority, a neuropsychological hypothesis formulated by the neuropsychologists Norman Geschwind and Albert Galaburda. Similarly, we show that, apart from being a context, the first theory enriches the second. We review the essential elements of both theories together with the arguments for them so that the reader may judge for himself. Similarly we review the factors determining intelligence; the association between neuropathology and intellectual dysfunction, general and specific, and the new directions in the understanding of human cognition. We propose to consider the first theory as a fertile ambit and broad methodological framework for investigation in neuropsychology. This simultaneously shows the relevance of including neuropsychological investigation in broader cognitive and neuropsychological theories and models.
NASA Technical Reports Server (NTRS)
Mellstrom, J. A.; Smyth, P.
1991-01-01
The results of applying pattern recognition techniques to diagnose fault conditions in the pointing system of one of the Deep Space network's large antennas, the DSS 13 34-meter structure, are discussed. A previous article described an experiment whereby a neural network technique was used to identify fault classes by using data obtained from a simulation model of the Deep Space Network (DSN) 70-meter antenna system. Described here is the extension of these classification techniques to the analysis of real data from the field. The general architecture and philosophy of an autonomous monitoring paradigm is described and classification results are discussed and analyzed in this context. Key features of this approach include a probabilistic time-varying context model, the effective integration of signal processing and system identification techniques with pattern recognition algorithms, and the ability to calibrate the system given limited amounts of training data. Reported here are recognition accuracies in the 97 to 98 percent range for the particular fault classes included in the experiments.
MicroRNA Targeting Specificity in Mammals: Determinants Beyond Seed Pairing
Grimson, Andrew; Farh, Kyle Kai-How; Johnston, Wendy K.; Garrett-Engele, Philip; Lim, Lee P.; Bartel, David P.
2013-01-01
Summary Mammalian microRNAs (miRNAs) pair to 3'UTRs of mRNAs to direct their posttranscriptional repression. Important for target recognition are ~7-nt sites that match the seed region of the miRNA. However, these seed matches are not always sufficient for repression, indicating that other characteristics help specify targeting. By combining computational and experimental approaches, we uncovered five general features of site context that boost site efficacy: AU-rich nucleotide composition near the site, proximity to sites for co-expressed miRNAs (which leads to cooperative action), proximity to residues pairing to miRNA nucleotides 13–16, and positioning within the 3'UTR at least 15 nt from the stop codon and away from the center of long UTRs. A model combining these context determinants quantitatively predicts site performance both for exogenously added miRNAs and for endogenous miRNA-message interactions. Because it predicts site efficacy without recourse to evolutionary conservation, the model also identifies effective nonconserved sites and siRNA off-targets. PMID:17612493
Sequential bearings-only-tracking initiation with particle filtering method.
Liu, Bin; Hao, Chengpeng
2013-01-01
The tracking initiation problem is examined in the context of autonomous bearings-only-tracking (BOT) of a single appearing/disappearing target in the presence of clutter measurements. In general, this problem suffers from a combinatorial explosion in the number of potential tracks resulted from the uncertainty in the linkage between the target and the measurement (a.k.a the data association problem). In addition, the nonlinear measurements lead to a non-Gaussian posterior probability density function (pdf) in the optimal Bayesian sequential estimation framework. The consequence of this nonlinear/non-Gaussian context is the absence of a closed-form solution. This paper models the linkage uncertainty and the nonlinear/non-Gaussian estimation problem jointly with solid Bayesian formalism. A particle filtering (PF) algorithm is derived for estimating the model's parameters in a sequential manner. Numerical results show that the proposed solution provides a significant benefit over the most commonly used methods, IPDA and IMMPDA. The posterior Cramér-Rao bounds are also involved for performance evaluation.
Do large-scale inhomogeneities explain away dark energy?
NASA Astrophysics Data System (ADS)
Geshnizjani, Ghazal; Chung, Daniel J.; Afshordi, Niayesh
2005-07-01
Recently, new arguments [E. Barausse, S. Matarrese, and A. Riotto, Phys. Rev. D 71, 063537 (2005)., PRVDAQ, 0556-2821, 10.1103/PhysRevD.71.063537][
Rossier, Jérôme; Hansenne, Michel; Baudin, Nicolas; Morizot, Julien
2012-01-01
The aim of this study was to analyze the replicability of Zuckerman's revised Alternative Five-factor model in a French-speaking context by validating the Zuckerman-Kuhlman-Aluja Personality Questionnaire (ZKA-PQ) simultaneously in 4 French-speaking countries. The total sample was made up of 1,497 subjects from Belgium, Canada, France, and Switzerland. The internal consistencies for all countries were generally similar to those found for the normative U.S. and Spanish samples. A factor analysis confirmed that the normative structure replicated well and was stable within this French-speaking context. Moreover, multigroup confirmatory factor analyses have shown that the ZKA-PQ reaches scalar invariance across these 4 countries. Mean scores were slightly different for women and men, with women scoring higher on Neuroticism but lower on Sensation Seeking. Globally, mean score differences across countries were small. Overall, the ZKA-PQ seems an interesting alternative to assess both lower and higher order personality traits for applied or research purposes.
Classes of Split-Plot Response Surface Designs for Equivalent Estimation
NASA Technical Reports Server (NTRS)
Parker, Peter A.; Kowalski, Scott M.; Vining, G. Geoffrey
2006-01-01
When planning an experimental investigation, we are frequently faced with factors that are difficult or time consuming to manipulate, thereby making complete randomization impractical. A split-plot structure differentiates between the experimental units associated with these hard-to-change factors and others that are relatively easy-to-change and provides an efficient strategy that integrates the restrictions imposed by the experimental apparatus. Several industrial and scientific examples are presented to illustrate design considerations encountered in the restricted randomization context. In this paper, we propose classes of split-plot response designs that provide an intuitive and natural extension from the completely randomized context. For these designs, the ordinary least squares estimates of the model are equivalent to the generalized least squares estimates. This property provides best linear unbiased estimators and simplifies model estimation. The design conditions that allow for equivalent estimation are presented enabling design construction strategies to transform completely randomized Box-Behnken, equiradial, and small composite designs into a split-plot structure.
Jones, Michael N.
2017-01-01
A central goal of cognitive neuroscience is to decode human brain activity—that is, to infer mental processes from observed patterns of whole-brain activation. Previous decoding efforts have focused on classifying brain activity into a small set of discrete cognitive states. To attain maximal utility, a decoding framework must be open-ended, systematic, and context-sensitive—that is, capable of interpreting numerous brain states, presented in arbitrary combinations, in light of prior information. Here we take steps towards this objective by introducing a probabilistic decoding framework based on a novel topic model—Generalized Correspondence Latent Dirichlet Allocation—that learns latent topics from a database of over 11,000 published fMRI studies. The model produces highly interpretable, spatially-circumscribed topics that enable flexible decoding of whole-brain images. Importantly, the Bayesian nature of the model allows one to “seed” decoder priors with arbitrary images and text—enabling researchers, for the first time, to generate quantitative, context-sensitive interpretations of whole-brain patterns of brain activity. PMID:29059185
JPKWIC - General key word in context and subject index report generator
NASA Technical Reports Server (NTRS)
Jirka, R.; Kabashima, N.; Kelly, D.; Plesset, M.
1968-01-01
JPKWIC computer program is a general key word in context and subject index report generator specifically developed to help nonprogrammers and nontechnical personnel to use the computer to access files, libraries and mass documentation. This program is designed to produce a KWIC index, a subject index, an edit report, a summary report, and an exclusion list.
2. GENERAL CONTEXT VIEW SHOWING 36004 AT FAR LEFT, LAUNCH ...
2. GENERAL CONTEXT VIEW SHOWING 36004 AT FAR LEFT, LAUNCH PAD A GANTRY AT CENTER, LAUNCH PAD B GANTRY AT RIGHT; THIS VIEW MATCHES FL-8-5-1 TO FORM PANORAMIC SWEEP OF SITE; VIEW TO NORTHEAST. - Cape Canaveral Air Station, Launch Complex 17, East end of Lighthouse Road, Cape Canaveral, Brevard County, FL
Three hybridization models based on local search scheme for job shop scheduling problem
NASA Astrophysics Data System (ADS)
Balbi Fraga, Tatiana
2015-05-01
This work presents three different hybridization models based on the general schema of Local Search Heuristics, named Hybrid Successive Application, Hybrid Neighborhood, and Hybrid Improved Neighborhood. Despite similar approaches might have already been presented in the literature in other contexts, in this work these models are applied to analyzes the solution of the job shop scheduling problem, with the heuristics Taboo Search and Particle Swarm Optimization. Besides, we investigate some aspects that must be considered in order to achieve better solutions than those obtained by the original heuristics. The results demonstrate that the algorithms derived from these three hybrid models are more robust than the original algorithms and able to get better results than those found by the single Taboo Search.
Chaplygin gas inspired scalar fields inflation via well-known potentials
NASA Astrophysics Data System (ADS)
Jawad, Abdul; Butt, Sadaf; Rani, Shamaila
2016-08-01
Brane inflationary universe models in the context of modified Chaplygin gas and generalized cosmic Chaplygin gas are being studied. We develop these models in view of standard scalar and tachyon fields. In both models, the implemented inflationary parameters such as scalar and tensor power spectra, scalar spectral index and tensor to scalar ratio are derived under slow roll approximations. We also use chaotic and exponential potential in high energy limits and discuss the characteristics of inflationary parameters for both potentials. These models are compatible with recent astronomical observations provided by WMAP7{+}9 and Planck data, i.e., ηs=1.027±0.051, 1.009±0.049, 0.096±0.025 and r<0.38, 0.36, 0.11.
Consistent Parameter and Transfer Function Estimation using Context Free Grammars
NASA Astrophysics Data System (ADS)
Klotz, Daniel; Herrnegger, Mathew; Schulz, Karsten
2017-04-01
This contribution presents a method for the inference of transfer functions for rainfall-runoff models. Here, transfer functions are defined as parametrized (functional) relationships between a set of spatial predictors (e.g. elevation, slope or soil texture) and model parameters. They are ultimately used for estimation of consistent, spatially distributed model parameters from a limited amount of lumped global parameters. Additionally, they provide a straightforward method for parameter extrapolation from one set of basins to another and can even be used to derive parameterizations for multi-scale models [see: Samaniego et al., 2010]. Yet, currently an actual knowledge of the transfer functions is often implicitly assumed. As a matter of fact, for most cases these hypothesized transfer functions can rarely be measured and often remain unknown. Therefore, this contribution presents a general method for the concurrent estimation of the structure of transfer functions and their respective (global) parameters. Note, that by consequence an estimation of the distributed parameters of the rainfall-runoff model is also undertaken. The method combines two steps to achieve this. The first generates different possible transfer functions. The second then estimates the respective global transfer function parameters. The structural estimation of the transfer functions is based on the context free grammar concept. Chomsky first introduced context free grammars in linguistics [Chomsky, 1956]. Since then, they have been widely applied in computer science. But, to the knowledge of the authors, they have so far not been used in hydrology. Therefore, the contribution gives an introduction to context free grammars and shows how they can be constructed and used for the structural inference of transfer functions. This is enabled by new methods from evolutionary computation, such as grammatical evolution [O'Neill, 2001], which make it possible to exploit the constructed grammar as a search space for equations. The parametrization of the transfer functions is then achieved through a second optimization routine. The contribution explores different aspects of the described procedure through a set of experiments. These experiments can be divided into three categories: (1) The inference of transfer functions from directly measurable parameters; (2) The estimation of global parameters for given transfer functions from runoff data; and (3) The estimation of sets of completely unknown transfer functions from runoff data. The conducted tests reveal different potentials and limits of the procedure. In concrete it is shown that example (1) and (2) work remarkably well. Example (3) is much more dependent on the setup. In general, it can be said that in that case much more data is needed to derive transfer function estimations, even for simple models and setups. References: - Chomsky, N. (1956): Three Models for the Description of Language. IT IRETr. 2(3), p 113-124 - O'Neil, M. (2001): Grammatical Evolution. IEEE ToEC, Vol.5, No. 4 - Samaniego, L.; Kumar, R.; Attinger, S. (2010): Multiscale parameter regionalization of a grid-based hydrologic model at the mesoscale. WWR, Vol. 46, W05523, doi:10.1029/2008WR007327
Learning abstract visual concepts via probabilistic program induction in a Language of Thought.
Overlan, Matthew C; Jacobs, Robert A; Piantadosi, Steven T
2017-11-01
The ability to learn abstract concepts is a powerful component of human cognition. It has been argued that variable binding is the key element enabling this ability, but the computational aspects of variable binding remain poorly understood. Here, we address this shortcoming by formalizing the Hierarchical Language of Thought (HLOT) model of rule learning. Given a set of data items, the model uses Bayesian inference to infer a probability distribution over stochastic programs that implement variable binding. Because the model makes use of symbolic variables as well as Bayesian inference and programs with stochastic primitives, it combines many of the advantages of both symbolic and statistical approaches to cognitive modeling. To evaluate the model, we conducted an experiment in which human subjects viewed training items and then judged which test items belong to the same concept as the training items. We found that the HLOT model provides a close match to human generalization patterns, significantly outperforming two variants of the Generalized Context Model, one variant based on string similarity and the other based on visual similarity using features from a deep convolutional neural network. Additional results suggest that variable binding happens automatically, implying that binding operations do not add complexity to peoples' hypothesized rules. Overall, this work demonstrates that a cognitive model combining symbolic variables with Bayesian inference and stochastic program primitives provides a new perspective for understanding people's patterns of generalization. Copyright © 2017 Elsevier B.V. All rights reserved.
Stochastic von Bertalanffy models, with applications to fish recruitment.
Lv, Qiming; Pitchford, Jonathan W
2007-02-21
We consider three individual-based models describing growth in stochastic environments. Stochastic differential equations (SDEs) with identical von Bertalanffy deterministic parts are formulated, with a stochastic term which decreases, remains constant, or increases with organism size, respectively. Probability density functions for hitting times are evaluated in the context of fish growth and mortality. Solving the hitting time problem analytically or numerically shows that stochasticity can have a large positive impact on fish recruitment probability. It is also demonstrated that the observed mean growth rate of surviving individuals always exceeds the mean population growth rate, which itself exceeds the growth rate of the equivalent deterministic model. The consequences of these results in more general biological situations are discussed.
Stop-catalyzed baryogenesis beyond the MSSM
DOE Office of Scientific and Technical Information (OSTI.GOV)
Katz, Andrey; Perelstein, Maxim; Ramsey-Musolf, Michael J.
2015-11-19
Nonminimal supersymmetric models that predict a tree-level Higgs mass above the minimal supersymmetric standard model (MSSM) bound are well motivated by naturalness considerations. Indirect constraints on the stop sector parameters of such models are significantly relaxed compared to the MSSM; in particular, both stops can have weak-scale masses. We revisit the stop-catalyzed electroweak baryogenesis (EWB) scenario in this context. We find that the LHC measurements of the Higgs boson production and decay rates already rule out the possibility of stop-catalyzed EWB. Here, we also introduce a gauge-invariant analysis framework that may generalize to other scenarios in which interactions outside themore » gauge sector drive the electroweak phase transition.« less
A Fractional PDE Approach to Turbulent Mixing; Part II: Numerical Simulation
NASA Astrophysics Data System (ADS)
Samiee, Mehdi; Zayernouri, Mohsen
2016-11-01
We propose a generalizing fractional order transport model of advection-diffusion kind with fractional time- and space-derivatives, governing the evolution of passive scalar turbulence. This approach allows one to incorporate the nonlocal and memory effects in the underlying anomalous diffusion i.e., sub-to-standard diffusion to model the trapping of particles inside the eddied, and super-diffusion associated with the sudden jumps of particles from one coherent region to another. For this nonlocal model, we develop a high order numerical (spectral) method in addition to a fast solver, examined in the context of some canonical problems. PhD student, Department of Mechanical Engineering, & Department Computational Mathematics, Science, and Engineering.
ERIC Educational Resources Information Center
Mahaffy, Peter G.; Holme, Thomas A.; Martin-Visscher, Leah; Martin, Brian E.; Versprille, Ashley; Kirchhoff, Mary; McKenzie, Lallie; Town, Marcy
2017-01-01
As one approach to moving beyond transmitting "inert" ideas to chemistry students, we use the term "teaching from rich contexts" to describe implementations of case studies or context-based learning based on systems thinking that provide deep and rich opportunities for learning crosscutting concepts through contexts. This…
A Social Approach to High-Level Context Generation for Supporting Context-Aware M-Learning
ERIC Educational Resources Information Center
Pan, Xu-Wei; Ding, Ling; Zhu, Xi-Yong; Yang, Zhao-Xiang
2017-01-01
In m-learning environments, context-awareness is for wide use where learners' situations are varied, dynamic and unpredictable. We are facing the challenge of requirements of both generality and depth in generating and processing high-level context. In this paper, we present a social approach which exploits social dynamics and social computing for…
Generalized thermoelastic problem of an infinite body with a spherical cavity under dual-phase-lags
NASA Astrophysics Data System (ADS)
Karmakar, R.; Sur, A.; Kanoria, M.
2016-07-01
The aim of the present contribution is the determination of the thermoelastic temperatures, stress, displacement, and strain in an infinite isotropic elastic body with a spherical cavity in the context of the mechanism of the two-temperature generalized thermoelasticity theory (2TT). The two-temperature Lord-Shulman (2TLS) model and two-temperature dual-phase-lag (2TDP) model of thermoelasticity are combined into a unified formulation with unified parameters. The medium is assumed to be initially quiescent. The basic equations are written in the form of a vector matrix differential equation in the Laplace transform domain, which is then solved by the state-space approach. The expressions for the conductive temperature and elongation are obtained at small times. The numerical inversion of the transformed solutions is carried out by using the Fourier-series expansion technique. A comparative study is performed for the thermoelastic stresses, conductive temperature, thermodynamic temperature, displacement, and elongation computed by using the Lord-Shulman and dual-phase-lag models.
Minimal S U ( 3 ) × S U ( 3 ) symmetry breaking patterns
Bai, Yang; Dobrescu, Bogdan A.
2018-03-16
Here, we study the vacua of anmore » $$SU(3)\\times SU(3)$$-symmetric model with a bifundamental scalar. Structures of this type appear in various gauge theories such as the Renormalizable Coloron Model, which is an extension of QCD, or the Trinification extension of the electroweak group. In other contexts, such as chiral symmetry, $$SU(3)\\times SU(3)$$ is a global symmetry. As opposed to more general $$SU(N)\\times SU(N)$$ symmetric models, the $N=3$ case is special due to the presence of a trilinear scalar term in the potential. We find that the most general tree-level potential has only three types of minima: one that preserves the diagonal $SU(3)$ subgroup, one that is $$SU(2)\\times SU(2)\\times U(1)$$ symmetric, and a trivial one where the full symmetry remains unbroken. The phase diagram is complicated, with some regions where there is a unique minimum, and other regions where two minima coexist.« less
NASA Technical Reports Server (NTRS)
Hoff, Claus; Cady, Eric; Chainyk, Mike; Kissil, Andrew; Levine, Marie; Moore, Greg
2011-01-01
The efficient simulation of multidisciplinary thermo-opto-mechanical effects in precision deployable systems has for years been limited by numerical toolsets that do not necessarily share the same finite element basis, level of mesh discretization, data formats, or compute platforms. Cielo, a general purpose integrated modeling tool funded by the Jet Propulsion Laboratory and the Exoplanet Exploration Program, addresses shortcomings in the current state of the art via features that enable the use of a single, common model for thermal, structural and optical aberration analysis, producing results of greater accuracy, without the need for results interpolation or mapping. This paper will highlight some of these advances, and will demonstrate them within the context of detailed external occulter analyses, focusing on in-plane deformations of the petal edges for both steady-state and transient conditions, with subsequent optical performance metrics including intensity distributions at the pupil and image plane.
Minimal S U ( 3 ) × S U ( 3 ) symmetry breaking patterns
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bai, Yang; Dobrescu, Bogdan A.
Here, we study the vacua of anmore » $$SU(3)\\times SU(3)$$-symmetric model with a bifundamental scalar. Structures of this type appear in various gauge theories such as the Renormalizable Coloron Model, which is an extension of QCD, or the Trinification extension of the electroweak group. In other contexts, such as chiral symmetry, $$SU(3)\\times SU(3)$$ is a global symmetry. As opposed to more general $$SU(N)\\times SU(N)$$ symmetric models, the $N=3$ case is special due to the presence of a trilinear scalar term in the potential. We find that the most general tree-level potential has only three types of minima: one that preserves the diagonal $SU(3)$ subgroup, one that is $$SU(2)\\times SU(2)\\times U(1)$$ symmetric, and a trivial one where the full symmetry remains unbroken. The phase diagram is complicated, with some regions where there is a unique minimum, and other regions where two minima coexist.« less
Bayesian model evidence as a model evaluation metric
NASA Astrophysics Data System (ADS)
Guthke, Anneli; Höge, Marvin; Nowak, Wolfgang
2017-04-01
When building environmental systems models, we are typically confronted with the questions of how to choose an appropriate model (i.e., which processes to include or neglect) and how to measure its quality. Various metrics have been proposed that shall guide the modeller towards a most robust and realistic representation of the system under study. Criteria for evaluation often address aspects of accuracy (absence of bias) or of precision (absence of unnecessary variance) and need to be combined in a meaningful way in order to address the inherent bias-variance dilemma. We suggest using Bayesian model evidence (BME) as a model evaluation metric that implicitly performs a tradeoff between bias and variance. BME is typically associated with model weights in the context of Bayesian model averaging (BMA). However, it can also be seen as a model evaluation metric in a single-model context or in model comparison. It combines a measure for goodness of fit with a penalty for unjustifiable complexity. Unjustifiable refers to the fact that the appropriate level of model complexity is limited by the amount of information available for calibration. Derived in a Bayesian context, BME naturally accounts for measurement errors in the calibration data as well as for input and parameter uncertainty. BME is therefore perfectly suitable to assess model quality under uncertainty. We will explain in detail and with schematic illustrations what BME measures, i.e. how complexity is defined in the Bayesian setting and how this complexity is balanced with goodness of fit. We will further discuss how BME compares to other model evaluation metrics that address accuracy and precision such as the predictive logscore or other model selection criteria such as the AIC, BIC or KIC. Although computationally more expensive than other metrics or criteria, BME represents an appealing alternative because it provides a global measure of model quality. Even if not applicable to each and every case, we aim at stimulating discussion about how to judge the quality of hydrological models in the presence of uncertainty in general by dissecting the mechanism behind BME.
Sherrouse, Benson C.; Semmens, Darius J.
2014-01-01
With growing pressures on ecosystem services, social values attributed to them are increasingly important to land management decisions. Social values, defined here as perceived values the public ascribes to ecosystem services, particularly cultural services, are generally not accounted for through economic markets or considered alongside economic and ecological values in ecosystem service assessments. Social-values data can be elicited through public value and preference surveys; however, limitations prevent them from being regularly collected. These limitations led to our three study objectives: (1) demonstrate an approach for applying benefit transfer, a nonmarket-valuation method, to spatially explicit social values; (2) validate the approach; and (3) identify potential improvements. We applied Social Values for Ecosystem Services (SolVES) to survey data for three national forests in Colorado and Wyoming. Social-value maps and models were generated, describing relationships between the maps and various combinations of environmental variables. Models from each forest were used to estimate social-value maps for the other forests via benefit transfer. Model performance was evaluated relative to the locally derived models. Performance varied with the number and type of environmental variables used, as well as differences in the forests' physical and social contexts. Enhanced metadata and better social-context matching could improve model transferability.
Models of user involvement in the mental health context: intentions and implementation challenges.
Storm, Marianne; Edwards, Adrian
2013-09-01
Patient-centered care, shared decision-making, patient participation and the recovery model are models of care which incorporate user involvement and patients' perspectives on their treatment and care. The aims of this paper are to examine these different care models and their association with user involvement in the mental health context and discuss some of the challenges associated with their implementation. The sources used are health policy documents and published literature and research on patient-centered care, shared decision-making, patient participation and recovery. The policy documents advocate that mental health services should be oriented towards patients' or users' needs, participation and involvement. These policies also emphasize recovery and integration of people with mental disorders in the community. However, these collaborative care models have generally been subject to limited empirical research about effectiveness. There are also challenges to implementation of the models in inpatient care. What evidence there is indicates tensions between patients' and providers' perspectives on treatment and care. There are issues related to risk and the person's capacity for user involvement, and concerns about what role patients themselves wish to play in decision-making. Lack of competence and awareness among providers are further issues. Further work on training, evaluation and implementation is needed to ensure that inpatient mental health services are adapting user oriented care models at all levels of services.
Principles of proteome allocation are revealed using proteomic data and genome-scale models
Yang, Laurence; Yurkovich, James T.; Lloyd, Colton J.; Ebrahim, Ali; Saunders, Michael A.; Palsson, Bernhard O.
2016-01-01
Integrating omics data to refine or make context-specific models is an active field of constraint-based modeling. Proteomics now cover over 95% of the Escherichia coli proteome by mass. Genome-scale models of Metabolism and macromolecular Expression (ME) compute proteome allocation linked to metabolism and fitness. Using proteomics data, we formulated allocation constraints for key proteome sectors in the ME model. The resulting calibrated model effectively computed the “generalist” (wild-type) E. coli proteome and phenotype across diverse growth environments. Across 15 growth conditions, prediction errors for growth rate and metabolic fluxes were 69% and 14% lower, respectively. The sector-constrained ME model thus represents a generalist ME model reflecting both growth rate maximization and “hedging” against uncertain environments and stresses, as indicated by significant enrichment of these sectors for the general stress response sigma factor σS. Finally, the sector constraints represent a general formalism for integrating omics data from any experimental condition into constraint-based ME models. The constraints can be fine-grained (individual proteins) or coarse-grained (functionally-related protein groups) as demonstrated here. This flexible formalism provides an accessible approach for narrowing the gap between the complexity captured by omics data and governing principles of proteome allocation described by systems-level models. PMID:27857205
Ebesutani, Chad; Kim, Mirihae; Park, Hee-Hoon
2016-08-01
The present study was the first to examine the applicability of the bifactor structure underlying the Anxiety Sensitivity Index-3 (ASI-3) in an East Asian (South Korean) sample and to determine which factors in the bifactor model were significantly associated with anxiety, depression, and negative affect. Using a sample of 289 South Korean university students, we compared (a) the original 3-factor AS model, (b) a 3-group bifactor AS model, and (c) a 2-group bifactor AS model (with only the physical and social concern group factors present). Results revealed that the 2-group bifactor AS model fit the ASI-3 data the best. Relatedly, although all ASI-3 items loaded on the general AS factor, the Cognitive Concern group factor was not defined in the bifactor model and may therefore need to be omitted in order to accurately model AS when conducting factor analysis and structural equation modeling (SEM) in cross cultural contexts. SEM results also revealed that the general AS factor was the only factor from the 2-group bifactor model that significantly predicted anxiety, depression, and negative affect. Implications and importance of this new bifactor structure of Anxiety Sensitivity in East Asian samples are discussed. Copyright © 2016 Elsevier B.V. All rights reserved.
Principles of proteome allocation are revealed using proteomic data and genome-scale models
Yang, Laurence; Yurkovich, James T.; Lloyd, Colton J.; ...
2016-11-18
Integrating omics data to refine or make context-specific models is an active field of constraint-based modeling. Proteomics now cover over 95% of the Escherichia coli proteome by mass. Genome-scale models of Metabolism and macromolecular Expression (ME) compute proteome allocation linked to metabolism and fitness. Using proteomics data, we formulated allocation constraints for key proteome sectors in the ME model. The resulting calibrated model effectively computed the “generalist” (wild-type) E. coli proteome and phenotype across diverse growth environments. Across 15 growth conditions, prediction errors for growth rate and metabolic fluxes were 69% and 14% lower, respectively. The sector-constrained ME model thusmore » represents a generalist ME model reflecting both growth rate maximization and “hedging” against uncertain environments and stresses, as indicated by significant enrichment of these sectors for the general stress response sigma factor σS. Finally, the sector constraints represent a general formalism for integrating omics data from any experimental condition into constraint-based ME models. The constraints can be fine-grained (individual proteins) or coarse-grained (functionally-related protein groups) as demonstrated here. Furthermore, this flexible formalism provides an accessible approach for narrowing the gap between the complexity captured by omics data and governing principles of proteome allocation described by systems-level models.« less
Boluda-Ruiz, Rubén; García-Zambrana, Antonio; Castillo-Vázquez, Carmen; Castillo-Vázquez, Beatriz
2016-10-03
A novel accurate and useful approximation of the well-known Beckmann distribution is presented here, which is used to model generalized pointing errors in the context of free-space optical (FSO) communication systems. We derive an approximate closed-form probability density function (PDF) for the composite gamma-gamma (GG) atmospheric turbulence with the pointing error model using the proposed approximation of the Beckmann distribution, which is valid for most practical terrestrial FSO links. This approximation takes into account the effect of the beam width, different jitters for the elevation and the horizontal displacement and the simultaneous effect of nonzero boresight errors for each axis at the receiver plane. Additionally, the proposed approximation allows us to delimit two different FSO scenarios. The first of them is when atmospheric turbulence is the dominant effect in relation to generalized pointing errors, and the second one when generalized pointing error is the dominant effect in relation to atmospheric turbulence. The second FSO scenario has not been studied in-depth by the research community. Moreover, the accuracy of the method is measured both visually and quantitatively using curve-fitting metrics. Simulation results are further included to confirm the analytical results.
ERIC Educational Resources Information Center
Bonnafous, Laurence
2014-01-01
This article is drawn from broader qualitative research on innovation in the field of professional adult training within the framework of European pilot projects such as the LEONARDO projects. This research aims at contributing to a general understanding of the phenomenon of innovation, in the context of European calls for projects, as an…
CERN IT Book Fair 2009 - Special talk by Bjarne Stroustrup: "The Design of C++0x"
Stroustrup, Bjarne
2018-05-24
A draft for a revised ISO C++ standard, C++0x, has been produced. The speaker will present the background of C++, its aims, the standards process (with opinions), some of the guiding design principles (with tiny code examples), and two case studies.The case studies are initialization (a general and uniform syntax and semantics for initializers in all contexts) and concurrent support facilities (memory model, threads, locks, futures).
NASA Technical Reports Server (NTRS)
Schenker, Paul S. (Editor)
1990-01-01
Various papers on human and machine strategies in sensor fusion are presented. The general topics addressed include: active vision, measurement and analysis of visual motion, decision models for sensor fusion, implementation of sensor fusion algorithms, applying sensor fusion to image analysis, perceptual modules and their fusion, perceptual organization and object recognition, planning and the integration of high-level knowledge with perception, using prior knowledge and context in sensor fusion.
Procurement, Cost Overruns and Severance. A Study in Commitment and Renegotiation
1984-12-01
projects involve a decentralization of responsibility to a research or a production department. The purpose of this paper is to analyze deci- sion... rationality constraints, which affect the set of possible allocations. Section T uses a two-period version of the general model to study this issue...determines the q function, which in turn affects e.. -^/ This point is made in a somewhat different context hy Williamson who notices that "a king
Ma, Yuanxiao; Ma, Haijing; Chen, Xu; Ran, Guangming; Zhang, Xing
2017-07-01
People tend to respond to rejection and attack with aggression. The present research examined the modulation role of attachment patterns on provoked aggression following punishment and proposed an executive functioning account of attachment patterns' modulating influence based on the General Aggression Model. Attachment style was measured using the Experiences in Close Relationships inventory. Experiments 1a and b and 2 adopted a social rejection task and assessed subsequent unprovoked and provoked aggression with different attachment patterns. Moreover, Experiment 1b and 2 used a Stroop task to examine whether differences in provoked aggression by attachment patterns are due to the amount of executive functioning following social rejection, or after unprovoked punishment, or even before social rejection. Anxiously attached participants displayed significant more provoked aggression than securely and avoidantly attached participants in provoked aggression following unprovoked punishment in Experiments 1 and 2. Meanwhile, subsequent Stroop tests indicated anxiously attached participants experienced more executive functioning depletion after social rejection and unprovoked aggression. The present findings support the General Aggression Model and suggest that provoked aggression is predicted by attachment patterns in the context of social rejection; different provoked aggression may depend on the degree of executive functioning that individuals preserved in aggressive situations. The current study contributes to our understanding of the importance of the role of attachment patterns in modulating aggressive behavior accompanying unfair social encounters. © 2017 Wiley Periodicals, Inc.
Farmers' preferences for water policy reforms: Results from a survey in Alberta
NASA Astrophysics Data System (ADS)
Zhang, W.; Bjornlund, H.; Klein, K.
2012-12-01
Facing increasingly urgent stress on global water scarcity, many reforms have been launched in countries around the world. As the biggest group of natural resource managers, farmers' behaviour is drawing increasingly wide attention. Satisfying new demands for water will depend on farmers' support since, generally, water will need to be transferred from farmers who have historically secure rights. Although water pricing reform is widely considered to lead to water conservation, the uncertainty of its potential impacts hinders the process of reform. This farmer-level empirical research explores farmers' possible responses to introduction of reforms in water pricing. A survey was conducted of about 300 farm households that use water for irrigating crops in Southern Alberta, an area that is facing water shortages and has had to stop issuing new water licences. By using structural equation modelling, the strength and direction of direct and indirect relationships between external, internal and behavioural variables as proposed in general attitude theory have been estimated. Farming as a family engagement, family members' and family unit's characteristics doubtlessly affect farming practice and farm decisions. Farmers' behaviour was explored under the family and farm context. In developing and testing conceptual models that integrate socio-demographic, psychological, farming context and social milieu factors, we may develop a deeper understanding of farmers' behaviour. The findings and recommendations will be beneficial for environmental practitioners and policy makers.
Decolonising medical curricula through diversity education: lessons from students.
Nazar, Mahdi; Kendall, Kathleen; Day, Lawrence; Nazar, Hamde
2015-04-01
The General Medical Council (GMC) expects that medical students graduate with an awareness of how the diversity of the patient population may affect health outcomes and behaviours. However, little guidance has been provided on how to incorporate diversity teaching into medical school curricula. Research highlights the existence of two different models within medical education: cultural competency and cultural humility. The Southampton medical curriculum includes both models in its diversity teaching, but little was known about which model was dominant or about the students' experience. Fifteen semi-structured, in-depth interviews were carried out with medical students at the University of Southampton. Data were analysed thematically using elements of grounded theory and constant comparison. Students identified early examples of diversity teaching consistent with a cultural humility approach. In later years, the limited diversity teaching recognised by students generally adopted a cultural competency approach. Students tended to perceive diversity as something that creates problems for healthcare professionals due to patients' perceived differences. They also reported witnessing a number of questionable practices related to diversity issues that they felt unable to challenge. The dissonance created by differences in the largely lecture based and the clinical environments left students confused and doubting the value of cultural humility in a clinical context. Staff training on diversity issues is required to encourage institutional buy-in and establish consistent educational and clinical environments. By tackling cultural diversity within the context of patient-centred care, cultural humility, the approach students valued most, would become the default model. Reflective practice and the development of a critical consciousness are crucial in the improvement of cultural diversity training and thus should be facilitated and encouraged. Educators can adopt a bidirectional mode of teaching and work with students to decolonise medical curricula and improve medical practice.
Ding, Liya; Martinez, Aleix M
2010-11-01
The appearance-based approach to face detection has seen great advances in the last several years. In this approach, we learn the image statistics describing the texture pattern (appearance) of the object class we want to detect, e.g., the face. However, this approach has had limited success in providing an accurate and detailed description of the internal facial features, i.e., eyes, brows, nose, and mouth. In general, this is due to the limited information carried by the learned statistical model. While the face template is relatively rich in texture, facial features (e.g., eyes, nose, and mouth) do not carry enough discriminative information to tell them apart from all possible background images. We resolve this problem by adding the context information of each facial feature in the design of the statistical model. In the proposed approach, the context information defines the image statistics most correlated with the surroundings of each facial component. This means that when we search for a face or facial feature, we look for those locations which most resemble the feature yet are most dissimilar to its context. This dissimilarity with the context features forces the detector to gravitate toward an accurate estimate of the position of the facial feature. Learning to discriminate between feature and context templates is difficult, however, because the context and the texture of the facial features vary widely under changing expression, pose, and illumination, and may even resemble one another. We address this problem with the use of subclass divisions. We derive two algorithms to automatically divide the training samples of each facial feature into a set of subclasses, each representing a distinct construction of the same facial component (e.g., closed versus open eyes) or its context (e.g., different hairstyles). The first algorithm is based on a discriminant analysis formulation. The second algorithm is an extension of the AdaBoost approach. We provide extensive experimental results using still images and video sequences for a total of 3,930 images. We show that the results are almost as good as those obtained with manual detection.
Prediction of Human Activity by Discovering Temporal Sequence Patterns.
Li, Kang; Fu, Yun
2014-08-01
Early prediction of ongoing human activity has become more valuable in a large variety of time-critical applications. To build an effective representation for prediction, human activities can be characterized by a complex temporal composition of constituent simple actions and interacting objects. Different from early detection on short-duration simple actions, we propose a novel framework for long -duration complex activity prediction by discovering three key aspects of activity: Causality, Context-cue, and Predictability. The major contributions of our work include: (1) a general framework is proposed to systematically address the problem of complex activity prediction by mining temporal sequence patterns; (2) probabilistic suffix tree (PST) is introduced to model causal relationships between constituent actions, where both large and small order Markov dependencies between action units are captured; (3) the context-cue, especially interactive objects information, is modeled through sequential pattern mining (SPM), where a series of action and object co-occurrence are encoded as a complex symbolic sequence; (4) we also present a predictive accumulative function (PAF) to depict the predictability of each kind of activity. The effectiveness of our approach is evaluated on two experimental scenarios with two data sets for each: action-only prediction and context-aware prediction. Our method achieves superior performance for predicting global activity classes and local action units.
Context-Model-Based Instruction in Teaching EFL Writing: A Narrative Inquiry
ERIC Educational Resources Information Center
Lin, Zheng
2016-01-01
This study aims to re-story the provision of the context-model-based instruction in teaching EFL writing, focusing especially on students' development of the context model and learning to guide EFL writing with the context model. The research data have been collected from the audio recordings of the classroom instruction, the teacher-researcher's…
Frankel, Leslie; Fisher, Jennifer O; Power, Thomas G; Chen, Tzu-An; Cross, Matthew B; Hughes, Sheryl O
2015-08-01
Assessing parent affect is important because studies examining the parent-child dyad have shown that parent affect has a profound impact on parent-child interactions and related outcomes. Although some measures that assess general affect during daily lives exist, to date there are only few tools that assess parent affect in the context of feeding. The aim of this study was to develop an instrument to measure parent affect specific to the feeding context and determine its validity and reliability. A brief instrument consisting of 20 items was developed that specifically asks how parents feel during the feeding process. This brief instrument draws on the structure of a well-validated general affect measure. A total of 296 Hispanic and Black Head Start parents of preschoolers completed the Feeding Emotions Scale along with other parent-report measures as part of a larger study designed to better understand feeding interactions during the dinner meal. Confirmatory factor analysis supported a two-factor model with independent subscales of positive affect and negative affect (Cronbach's alphas of 0.85 and 0.84, respectively). Concurrent and convergent construct validity was evaluated by correlating the subscales of the Feeding Emotions Scale with positive emotionality and negative emotionality from the Differential Emotions Scale - a measure of general adult emotions. Concurrent and convergent criterion validity was evaluated by testing mean differences in affect across parent feeding styles using ANOVA. A significant difference was found across maternal weight status for positive feeding affect. The resulting validated measure can be used to assess parent affect in studies of feeding to better understand how interactions during feeding may impact the development of child eating behaviors and possibly weight status. Copyright © 2015 Elsevier Ltd. All rights reserved.
An information theory account of late frontoparietal ERP positivities in cognitive control.
Barceló, Francisco; Cooper, Patrick S
2018-03-01
ERP research on task switching has revealed distinct transient and sustained positive waveforms (latency circa 300-900 ms) while shifting task rules or stimulus-response (S-R) mappings. However, it remains unclear whether such switch-related positivities show similar scalp topography and index context-updating mechanisms akin to those posed for domain-general (i.e., classic P300) positivities in many task domains. To examine this question, ERPs were recorded from 31 young adults (18-30 years) while they were intermittently cued to switch or repeat their perceptual categorization of Gabor gratings varying in color and thickness (switch task), or else they performed two visually identical control tasks (go/no-go and oddball). Our task cueing paradigm examined two temporarily distinct stages of proactive rule updating and reactive rule execution. A simple information theory model helped us gauge cognitive demands under distinct temporal and task contexts in terms of low-level S-R pathways and higher-order rule updating operations. Task demands modulated domain-general (indexed by classic oddball P3) and switch positivities-indexed by both a cue-locked late positive complex and a sustained positivity ensuing task transitions. Topographic scalp analyses confirmed subtle yet significant split-second changes in the configuration of neural sources for both domain-general P3s and switch positivities as a function of both the temporal and task context. These findings partly meet predictions from information estimates, and are compatible with a family of P3-like potentials indexing functionally distinct neural operations within a common frontoparietal "multiple demand" system during the preparation and execution of simple task rules. © 2016 Society for Psychophysiological Research.
Msetfi, Rachel; Jay, Sarah; O'Donnell, Aisling T; Kearns, Michelle; Kinsella, Elaine L; McMahon, Jennifer; Muldoon, Orla T; Naughton, Catherine; Creaven, Ann-Marie
2018-02-01
Few studies have investigated the role of disenfranchisement and denial of agency in women's sexual health. To address this, a cross-sectional study of disenfranchisement, control (general and reproductive control) and health was conducted in Ireland, where abortion is severely restricted. Multiple mediation models ( N = 513 women) indicated that general but not reproductive control mediates the association between disenfranchisement and psychological well-being. Additionally, serial mediation shows disenfranchisement is associated with lower sense of control, which is linked to poorer well-being and risky sexual behaviour. Disenfranchisement arising from socio-political contexts may have important implications for women's sexual health.
Higher-derivative operators and effective field theory for general scalar-tensor theories
NASA Astrophysics Data System (ADS)
Solomon, Adam R.; Trodden, Mark
2018-02-01
We discuss the extent to which it is necessary to include higher-derivative operators in the effective field theory of general scalar-tensor theories. We explore the circumstances under which it is correct to restrict to second-order operators only, and demonstrate this using several different techniques, such as reduction of order and explicit field redefinitions. These methods are applied, in particular, to the much-studied Horndeski theories. The goal is to clarify the application of effective field theory techniques in the context of popular cosmological models, and to explicitly demonstrate how and when higher-derivative operators can be cast into lower-derivative forms suitable for numerical solution techniques.
Studying the Supra-National in Education: GATS, Education and Teacher Union Policies
ERIC Educational Resources Information Center
Fredriksson, Ulf
2004-01-01
This article starts by putting the General Agreement on Trade in Services (GATS) into a general context of privatisation. It is noted that the privatisation process is in many cases complex and not only about full-scale privatisation of schools. The growing trade in education must be seen in this context. GATS is not an agreement which deals with…
Soto, Fabian A; Gershman, Samuel J; Niv, Yael
2014-07-01
How do we apply learning from one situation to a similar, but not identical, situation? The principles governing the extent to which animals and humans generalize what they have learned about certain stimuli to novel compounds containing those stimuli vary depending on a number of factors. Perhaps the best studied among these factors is the type of stimuli used to generate compounds. One prominent hypothesis is that different generalization principles apply depending on whether the stimuli in a compound are similar or dissimilar to each other. However, the results of many experiments cannot be explained by this hypothesis. Here, we propose a rational Bayesian theory of compound generalization that uses the notion of consequential regions, first developed in the context of rational theories of multidimensional generalization, to explain the effects of stimulus factors on compound generalization. The model explains a large number of results from the compound generalization literature, including the influence of stimulus modality and spatial contiguity on the summation effect, the lack of influence of stimulus factors on summation with a recovered inhibitor, the effect of spatial position of stimuli on the blocking effect, the asymmetrical generalization decrement in overshadowing and external inhibition, and the conditions leading to a reliable external inhibition effect. By integrating rational theories of compound and dimensional generalization, our model provides the first comprehensive computational account of the effects of stimulus factors on compound generalization, including spatial and temporal contiguity between components, which have posed long-standing problems for rational theories of associative and causal learning. (c) 2014 APA, all rights reserved.
Soto, Fabian A.; Gershman, Samuel J.; Niv, Yael
2014-01-01
How do we apply learning from one situation to a similar, but not identical, situation? The principles governing the extent to which animals and humans generalize what they have learned about certain stimuli to novel compounds containing those stimuli vary depending on a number of factors. Perhaps the best studied among these factors is the type of stimuli used to generate compounds. One prominent hypothesis is that different generalization principles apply depending on whether the stimuli in a compound are similar or dissimilar to each other. However, the results of many experiments cannot be explained by this hypothesis. Here we propose a rational Bayesian theory of compound generalization that uses the notion of consequential regions, first developed in the context of rational theories of multidimensional generalization, to explain the effects of stimulus factors on compound generalization. The model explains a large number of results from the compound generalization literature, including the influence of stimulus modality and spatial contiguity on the summation effect, the lack of influence of stimulus factors on summation with a recovered inhibitor, the effect of spatial position of stimuli on the blocking effect, the asymmetrical generalization decrement in overshadowing and external inhibition, and the conditions leading to a reliable external inhibition effect. By integrating rational theories of compound and dimensional generalization, our model provides the first comprehensive computational account of the effects of stimulus factors on compound generalization, including spatial and temporal contiguity between components, which have posed longstanding problems for rational theories of associative and causal learning. PMID:25090430
Zhang, Ruixun; Brennan, Thomas J.; Lo, Andrew W.
2014-01-01
Risk aversion is one of the most basic assumptions of economic behavior, but few studies have addressed the question of where risk preferences come from and why they differ from one individual to the next. Here, we propose an evolutionary explanation for the origin of risk aversion. In the context of a simple binary-choice model, we show that risk aversion emerges by natural selection if reproductive risk is systematic (i.e., correlated across individuals in a given generation). In contrast, risk neutrality emerges if reproductive risk is idiosyncratic (i.e., uncorrelated across each given generation). More generally, our framework implies that the degree of risk aversion is determined by the stochastic nature of reproductive rates, and we show that different statistical properties lead to different utility functions. The simplicity and generality of our model suggest that these implications are primitive and cut across species, physiology, and genetic origins. PMID:25453072
Socioemotional deficits associated with obsessive-compulsive symptomatology.
Grisham, Jessica R; Henry, Julie D; Williams, Alishia D; Bailey, Phoebe E
2010-02-28
Increasing emphasis has been placed on the role of socioemotional functioning in models of obsessive-compulsive disorder (OCD). The present study investigated whether OCD symptoms were associated with capacity for theory of mind (ToM) and basic affect recognition. Non-clinical volunteers (N=204) completed self report measures of OCD and general psychopathology, in addition to behavioral measures of ToM and affect recognition. The results indicated that higher OCD symptoms were associated with reduced ToM, as well as reduced accuracy decoding the specific emotion of disgust. Importantly, these relationships could not be attributed to other, more general features of psychopathology. The findings of the current study therefore further our understanding of how the processing and interpretation of social and emotional information is affected in the context of OCD symptomatology, and are discussed in relation to neuropsychological models of OCD. 2009 Elsevier Ireland Ltd. All rights reserved.
Resonant activation of population extinctions
NASA Astrophysics Data System (ADS)
Spalding, Christopher; Doering, Charles R.; Flierl, Glenn R.
2017-10-01
Understanding the mechanisms governing population extinctions is of key importance to many problems in ecology and evolution. Stochastic factors are known to play a central role in extinction, but the interactions between a population's demographic stochasticity and environmental noise remain poorly understood. Here we model environmental forcing as a stochastic fluctuation between two states, one with a higher death rate than the other. We find that, in general, there exists a rate of fluctuations that minimizes the mean time to extinction, a phenomenon previously dubbed "resonant activation." We develop a heuristic description of the phenomenon, together with a criterion for the existence of resonant activation. Specifically, the minimum extinction time arises as a result of the system approaching a scenario wherein the severity of rare events is balanced by the time interval between them. We discuss our findings within the context of more general forms of environmental noise and suggest potential applications to evolutionary models.
Massive parallelization of serial inference algorithms for a complex generalized linear model
Suchard, Marc A.; Simpson, Shawn E.; Zorych, Ivan; Ryan, Patrick; Madigan, David
2014-01-01
Following a series of high-profile drug safety disasters in recent years, many countries are redoubling their efforts to ensure the safety of licensed medical products. Large-scale observational databases such as claims databases or electronic health record systems are attracting particular attention in this regard, but present significant methodological and computational concerns. In this paper we show how high-performance statistical computation, including graphics processing units, relatively inexpensive highly parallel computing devices, can enable complex methods in large databases. We focus on optimization and massive parallelization of cyclic coordinate descent approaches to fit a conditioned generalized linear model involving tens of millions of observations and thousands of predictors in a Bayesian context. We find orders-of-magnitude improvement in overall run-time. Coordinate descent approaches are ubiquitous in high-dimensional statistics and the algorithms we propose open up exciting new methodological possibilities with the potential to significantly improve drug safety. PMID:25328363
Energy and mass balance in the three-phase interstellar medium
NASA Technical Reports Server (NTRS)
Wang, Zhong; Cowie, Lennox L.
1988-01-01
Details of the energy and mass balances are considered in the context of a three-phase interstellar medium. The rates of mass exchange between the different phases are derived based on the pressure variations created by supernova remnant expansions. It is shown that the pressure-confined warm and cold gases have stable temperatures under a variety of interstellar conditions. The three-phase quasi-static configuration is found to be a natural outcome, and both warm and cold phases generally contribute about half of the total mass density to the diffuse interstellar gas. The model is also likely to be self-regulatory in the sense that variations of the input parameters do not strongly alter the general result, which is consistent with most current observations. The consequences of extreme conditions on this model are considered, and the possible implications for interstellar medium in other galaxies are briefly discussed.
Biodiversity and ecosystem stability across scales in metacommunities
Wang, Shaopeng; Loreau, Michel
2016-01-01
Although diversity-stability relationships have been extensively studied in local ecosystems, the global biodiversity crisis calls for an improved understanding of these relationships in a spatial context. Here we use a dynamical model of competitive metacommunities to study the relationships between species diversity and ecosystem variability across scales. We derive analytic relationships under a limiting case; these results are extended to more general cases with numerical simulations. Our model shows that, while alpha diversity decreases local ecosystem variability, beta diversity generally contributes to increasing spatial asynchrony among local ecosystems. Consequently, both alpha and beta diversity provide stabilizing effects for regional ecosystems, through local and spatial insurance effects, respectively. We further show that at the regional scale, the stabilizing effect of biodiversity increases as spatial environmental correlation increases. Our findings have important implications for understanding the interactive effects of global environmental changes (e.g. environmental homogenization) and biodiversity loss on ecosystem sustainability at large scales. PMID:26918536
Zhang, Ruixun; Brennan, Thomas J; Lo, Andrew W
2014-12-16
Risk aversion is one of the most basic assumptions of economic behavior, but few studies have addressed the question of where risk preferences come from and why they differ from one individual to the next. Here, we propose an evolutionary explanation for the origin of risk aversion. In the context of a simple binary-choice model, we show that risk aversion emerges by natural selection if reproductive risk is systematic (i.e., correlated across individuals in a given generation). In contrast, risk neutrality emerges if reproductive risk is idiosyncratic (i.e., uncorrelated across each given generation). More generally, our framework implies that the degree of risk aversion is determined by the stochastic nature of reproductive rates, and we show that different statistical properties lead to different utility functions. The simplicity and generality of our model suggest that these implications are primitive and cut across species, physiology, and genetic origins.
Machine Learning Meta-analysis of Large Metagenomic Datasets: Tools and Biological Insights.
Pasolli, Edoardo; Truong, Duy Tin; Malik, Faizan; Waldron, Levi; Segata, Nicola
2016-07-01
Shotgun metagenomic analysis of the human associated microbiome provides a rich set of microbial features for prediction and biomarker discovery in the context of human diseases and health conditions. However, the use of such high-resolution microbial features presents new challenges, and validated computational tools for learning tasks are lacking. Moreover, classification rules have scarcely been validated in independent studies, posing questions about the generality and generalization of disease-predictive models across cohorts. In this paper, we comprehensively assess approaches to metagenomics-based prediction tasks and for quantitative assessment of the strength of potential microbiome-phenotype associations. We develop a computational framework for prediction tasks using quantitative microbiome profiles, including species-level relative abundances and presence of strain-specific markers. A comprehensive meta-analysis, with particular emphasis on generalization across cohorts, was performed in a collection of 2424 publicly available metagenomic samples from eight large-scale studies. Cross-validation revealed good disease-prediction capabilities, which were in general improved by feature selection and use of strain-specific markers instead of species-level taxonomic abundance. In cross-study analysis, models transferred between studies were in some cases less accurate than models tested by within-study cross-validation. Interestingly, the addition of healthy (control) samples from other studies to training sets improved disease prediction capabilities. Some microbial species (most notably Streptococcus anginosus) seem to characterize general dysbiotic states of the microbiome rather than connections with a specific disease. Our results in modelling features of the "healthy" microbiome can be considered a first step toward defining general microbial dysbiosis. The software framework, microbiome profiles, and metadata for thousands of samples are publicly available at http://segatalab.cibio.unitn.it/tools/metaml.
Westö, Johan; May, Patrick J C
2018-05-02
Receptive field (RF) models are an important tool for deciphering neural responses to sensory stimuli. The two currently popular RF models are multi-filter linear-nonlinear (LN) models and context models. Models are, however, never correct and they rely on assumptions to keep them simple enough to be interpretable. As a consequence, different models describe different stimulus-response mappings, which may or may not be good approximations of real neural behavior. In the current study, we take up two tasks: First, we introduce new ways to estimate context models with realistic nonlinearities, that is, with logistic and exponential functions. Second, we evaluate context models and multi-filter LN models in terms of how well they describe recorded data from complex cells in cat primary visual cortex. Our results, based on single-spike information and correlation coefficients, indicate that context models outperform corresponding multi-filter LN models of equal complexity (measured in terms of number of parameters), with the best increase in performance being achieved by the novel context models. Consequently, our results suggest that the multi-filter LN-model framework is suboptimal for describing the behavior of complex cells: the context-model framework is clearly superior while still providing interpretable quantizations of neural behavior.
Modeling Nonstationary Emotion Dynamics in Dyads using a Time-Varying Vector-Autoregressive Model.
Bringmann, Laura F; Ferrer, Emilio; Hamaker, Ellen L; Borsboom, Denny; Tuerlinckx, Francis
2018-01-01
Emotion dynamics are likely to arise in an interpersonal context. Standard methods to study emotions in interpersonal interaction are limited because stationarity is assumed. This means that the dynamics, for example, time-lagged relations, are invariant across time periods. However, this is generally an unrealistic assumption. Whether caused by an external (e.g., divorce) or an internal (e.g., rumination) event, emotion dynamics are prone to change. The semi-parametric time-varying vector-autoregressive (TV-VAR) model is based on well-studied generalized additive models, implemented in the software R. The TV-VAR can explicitly model changes in temporal dependency without pre-existing knowledge about the nature of change. A simulation study is presented, showing that the TV-VAR model is superior to the standard time-invariant VAR model when the dynamics change over time. The TV-VAR model is applied to empirical data on daily feelings of positive affect (PA) from a single couple. Our analyses indicate reliable changes in the male's emotion dynamics over time, but not in the female's-which were not predicted by her own affect or that of her partner. This application illustrates the usefulness of using a TV-VAR model to detect changes in the dynamics in a system.
Feng, Sally; McGhee, Katie E.; Bell, Alison M.
2017-01-01
Maternal stress can have long-term negative consequences for offspring learning performance. However, it is unknown whether these maternal effects extend to the ability of offspring to apply previously learned information to new situations. In this study, we first demonstrate that juvenile threespine sticklebacks, Gasterosteus aculeatus, are indeed capable of generalizing an association between a colour and a food reward learned in one foraging context to a new foraging context (i.e. they can apply previously learned knowledge to a new situation). Next, we examined whether this ability to generalize was affected by maternal predator stress. We manipulated whether mothers were repeatedly chased by a model predator while yolking eggs (i.e. before spawning) and then assessed the learning performance of their juvenile offspring in groups and pairs using a colour discrimination task that associated a colour with a food reward. We found that maternal predator exposure affected the tendency of offspring to use social cues: offspring of predator-exposed mothers were faster at copying a leader’s behaviour towards the rewarded colour than offspring of unexposed mothers. However, once the colour–reward association had been learned, offspring of predator-exposed and unexposed mothers were equally able to generalize their learned association to a new foraging task. These results suggest that offspring of predator-exposed mothers might be able to overcome learning deficits caused by maternal stress by relying more on social cues. PMID:29046591
Currie, Danielle J; Smith, Carl; Jagals, Paul
2018-03-27
Policy and decision-making processes are routinely challenged by the complex and dynamic nature of environmental health problems. System dynamics modelling has demonstrated considerable value across a number of different fields to help decision-makers understand and predict the dynamic behaviour of complex systems in support the development of effective policy actions. In this scoping review we investigate if, and in what contexts, system dynamics modelling is being used to inform policy or decision-making processes related to environmental health. Four electronic databases and the grey literature were systematically searched to identify studies that intersect the areas environmental health, system dynamics modelling, and decision-making. Studies identified in the initial screening were further screened for their contextual, methodological and application-related relevancy. Studies deemed 'relevant' or 'highly relevant' according to all three criteria were included in this review. Key themes related to the rationale, impact and limitation of using system dynamics in the context of environmental health decision-making and policy were analysed. We identified a limited number of relevant studies (n = 15), two-thirds of which were conducted between 2011 and 2016. The majority of applications occurred in non-health related sectors (n = 9) including transportation, public utilities, water, housing, food, agriculture, and urban and regional planning. Applications were primarily targeted at micro-level (local, community or grassroots) decision-making processes (n = 9), with macro-level (national or international) decision-making to a lesser degree. There was significant heterogeneity in the stated rationales for using system dynamics and the intended impact of the system dynamics model on decision-making processes. A series of user-related, technical and application-related limitations and challenges were identified. None of the reported limitations or challenges appeared unique to the application of system dynamics within the context of environmental health problems, but rather to the use of system dynamics in general. This review reveals that while system dynamics modelling is increasingly being used to inform decision-making related to environmental health, applications are currently limited. Greater application of system dynamics within this context is needed before its benefits and limitations can be fully understood.
The super-Turing computational power of plastic recurrent neural networks.
Cabessa, Jérémie; Siegelmann, Hava T
2014-12-01
We study the computational capabilities of a biologically inspired neural model where the synaptic weights, the connectivity pattern, and the number of neurons can evolve over time rather than stay static. Our study focuses on the mere concept of plasticity of the model so that the nature of the updates is assumed to be not constrained. In this context, we show that the so-called plastic recurrent neural networks (RNNs) are capable of the precise super-Turing computational power--as the static analog neural networks--irrespective of whether their synaptic weights are modeled by rational or real numbers, and moreover, irrespective of whether their patterns of plasticity are restricted to bi-valued updates or expressed by any other more general form of updating. Consequently, the incorporation of only bi-valued plastic capabilities in a basic model of RNNs suffices to break the Turing barrier and achieve the super-Turing level of computation. The consideration of more general mechanisms of architectural plasticity or of real synaptic weights does not further increase the capabilities of the networks. These results support the claim that the general mechanism of plasticity is crucially involved in the computational and dynamical capabilities of biological neural networks. They further show that the super-Turing level of computation reflects in a suitable way the capabilities of brain-like models of computation.
Different Context but Similar Cognitive Structures: Older Adults in Rural Bangladesh.
Sternäng, Ola; Lövdén, Martin; Kabir, Zarina N; Hamadani, Jena D; Wahlin, Åke
2016-06-01
Most research in cognitive aging is based on literate participants from high-income and Western populations. The extent to which findings generalize to low-income and illiterate populations is unknown. The main aim was to examine the structure of between-person differences in cognitive functions among elderly from rural Bangladesh. We used data from the Poverty and Health in Aging (PHA) project in Bangladesh. The participants (n = 452) were in the age range 60-92 years. Structural equation modeling was used to estimate the fit of a five-factor model (episodic recall, episodic recognition, verbal fluency, semantic knowledge, processing speed) and to examine whether the model generalized across age, sex, and literacy. This study demonstrates that an established model of cognition is valid also among older persons from rural Bangladesh. The model demonstrated strong (or scalar) invariance for age, and partial strong invariance for sex and literacy. Semantic knowledge and processing speed showed weak (or metric) sex invariance, and semantic knowledge demonstrated also sensitivity to illiteracy. In general, women performed poorer on all abilities. The structure of individual cognitive differences established in Western populations also fits a population in rural Bangladesh well. This is an important prerequisite for comparisons of cognitive functioning (e.g., declarative memory) across cultures. It is also worth noting that absolute sex differences in cognitive performance among rural elderly in Bangladesh differ from those usually found in Western samples.