Efficient estimators for likelihood ratio sensitivity indices of complex stochastic dynamics.

PubMed

Arampatzis, Georgios; Katsoulakis, Markos A; Rey-Bellet, Luc

2016-03-14

We demonstrate that centered likelihood ratio estimators for the sensitivity indices of complex stochastic dynamics are highly efficient with low, constant in time variance and consequently they are suitable for sensitivity analysis in long-time and steady-state regimes. These estimators rely on a new covariance formulation of the likelihood ratio that includes as a submatrix a Fisher information matrix for stochastic dynamics and can also be used for fast screening of insensitive parameters and parameter combinations. The proposed methods are applicable to broad classes of stochastic dynamics such as chemical reaction networks, Langevin-type equations and stochastic models in finance, including systems with a high dimensional parameter space and/or disparate decorrelation times between different observables. Furthermore, they are simple to implement as a standard observable in any existing simulation algorithm without additional modifications.

Efficient estimators for likelihood ratio sensitivity indices of complex stochastic dynamics

NASA Astrophysics Data System (ADS)

Arampatzis, Georgios; Katsoulakis, Markos A.; Rey-Bellet, Luc

2016-03-01

We demonstrate that centered likelihood ratio estimators for the sensitivity indices of complex stochastic dynamics are highly efficient with low, constant in time variance and consequently they are suitable for sensitivity analysis in long-time and steady-state regimes. These estimators rely on a new covariance formulation of the likelihood ratio that includes as a submatrix a Fisher information matrix for stochastic dynamics and can also be used for fast screening of insensitive parameters and parameter combinations. The proposed methods are applicable to broad classes of stochastic dynamics such as chemical reaction networks, Langevin-type equations and stochastic models in finance, including systems with a high dimensional parameter space and/or disparate decorrelation times between different observables. Furthermore, they are simple to implement as a standard observable in any existing simulation algorithm without additional modifications.

Efficient estimators for likelihood ratio sensitivity indices of complex stochastic dynamics

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

Arampatzis, Georgios; Katsoulakis, Markos A.; Rey-Bellet, Luc

2016-03-14

We demonstrate that centered likelihood ratio estimators for the sensitivity indices of complex stochastic dynamics are highly efficient with low, constant in time variance and consequently they are suitable for sensitivity analysis in long-time and steady-state regimes. These estimators rely on a new covariance formulation of the likelihood ratio that includes as a submatrix a Fisher information matrix for stochastic dynamics and can also be used for fast screening of insensitive parameters and parameter combinations. The proposed methods are applicable to broad classes of stochastic dynamics such as chemical reaction networks, Langevin-type equations and stochastic models in finance, including systemsmore » with a high dimensional parameter space and/or disparate decorrelation times between different observables. Furthermore, they are simple to implement as a standard observable in any existing simulation algorithm without additional modifications.« less

Likelihood Methods for Adaptive Filtering and Smoothing. Technical Report #455.

ERIC Educational Resources Information Center

Butler, Ronald W.

The dynamic linear model or Kalman filtering model provides a useful methodology for predicting the past, present, and future states of a dynamic system, such as an object in motion or an economic or social indicator that is changing systematically with time. Recursive likelihood methods for adaptive Kalman filtering and smoothing are developed.…

Maximum Likelihood Dynamic Factor Modeling for Arbitrary "N" and "T" Using SEM

ERIC Educational Resources Information Center

Voelkle, Manuel C.; Oud, Johan H. L.; von Oertzen, Timo; Lindenberger, Ulman

2012-01-01

This article has 3 objectives that build on each other. First, we demonstrate how to obtain maximum likelihood estimates for dynamic factor models (the direct autoregressive factor score model) with arbitrary "T" and "N" by means of structural equation modeling (SEM) and compare the approach to existing methods. Second, we go beyond standard time…

Counseling Pretreatment and the Elaboration Likelihood Model of Attitude Change.

ERIC Educational Resources Information Center

Heesacker, Martin

1986-01-01

Results of the application of the Elaboration Likelihood Model (ELM) to a counseling context revealed that more favorable attitudes toward counseling occurred as subjects' ego involvement increased and as intervention quality improved. Counselor credibility affected the degree to which subjects' attitudes reflected argument quality differences.…

Conflict effects without conflict in anterior cingulate cortex: multiple response effects and context specific representations

PubMed Central

Brown, Joshua W.

2009-01-01

The error likelihood computational model of anterior cingulate cortex (ACC) (Brown & Braver, 2005) has successfully predicted error likelihood effects, risk prediction effects, and how individual differences in conflict and error likelihood effects vary with trait differences in risk aversion. The same computational model now makes a further prediction that apparent conflict effects in ACC may result in part from an increasing number of simultaneously active responses, regardless of whether or not the cued responses are mutually incompatible. In Experiment 1, the model prediction was tested with a modification of the Eriksen flanker task, in which some task conditions require two otherwise mutually incompatible responses to be generated simultaneously. In that case, the two response processes are no longer in conflict with each other. The results showed small but significant medial PFC effects in the incongruent vs. congruent contrast, despite the absence of response conflict, consistent with model predictions. This is the multiple response effect. Nonetheless, actual response conflict led to greater ACC activation, suggesting that conflict effects are specific to particular task contexts. In Experiment 2, results from a change signal task suggested that the context dependence of conflict signals does not depend on error likelihood effects. Instead, inputs to ACC may reflect complex and task specific representations of motor acts, such as bimanual responses. Overall, the results suggest the existence of a richer set of motor signals monitored by medial PFC and are consistent with distinct effects of multiple responses, conflict, and error likelihood in medial PFC. PMID:19375509

Choosing face: The curse of self in profile image selection.

PubMed

White, David; Sutherland, Clare A M; Burton, Amy L

2017-01-01

People draw automatic social inferences from photos of unfamiliar faces and these first impressions are associated with important real-world outcomes. Here we examine the effect of selecting online profile images on first impressions. We model the process of profile image selection by asking participants to indicate the likelihood that images of their own face ("self-selection") and of an unfamiliar face ("other-selection") would be used as profile images on key social networking sites. Across two large Internet-based studies (n = 610), in line with predictions, image selections accentuated favorable social impressions and these impressions were aligned to the social context of the networking sites. However, contrary to predictions based on people's general expertise in self-presentation, other-selected images conferred more favorable impressions than self-selected images. We conclude that people make suboptimal choices when selecting their own profile pictures, such that self-perception places important limits on facial first impressions formed by others. These results underscore the dynamic nature of person perception in real-world contexts.

Variational Bayesian identification and prediction of stochastic nonlinear dynamic causal models.

PubMed

Daunizeau, J; Friston, K J; Kiebel, S J

2009-11-01

In this paper, we describe a general variational Bayesian approach for approximate inference on nonlinear stochastic dynamic models. This scheme extends established approximate inference on hidden-states to cover: (i) nonlinear evolution and observation functions, (ii) unknown parameters and (precision) hyperparameters and (iii) model comparison and prediction under uncertainty. Model identification or inversion entails the estimation of the marginal likelihood or evidence of a model. This difficult integration problem can be finessed by optimising a free-energy bound on the evidence using results from variational calculus. This yields a deterministic update scheme that optimises an approximation to the posterior density on the unknown model variables. We derive such a variational Bayesian scheme in the context of nonlinear stochastic dynamic hierarchical models, for both model identification and time-series prediction. The computational complexity of the scheme is comparable to that of an extended Kalman filter, which is critical when inverting high dimensional models or long time-series. Using Monte-Carlo simulations, we assess the estimation efficiency of this variational Bayesian approach using three stochastic variants of chaotic dynamic systems. We also demonstrate the model comparison capabilities of the method, its self-consistency and its predictive power.

Construction and identification of a D-Vine model applied to the probability distribution of modal parameters in structural dynamics

NASA Astrophysics Data System (ADS)

Dubreuil, S.; Salaün, M.; Rodriguez, E.; Petitjean, F.

2018-01-01

This study investigates the construction and identification of the probability distribution of random modal parameters (natural frequencies and effective parameters) in structural dynamics. As these parameters present various types of dependence structures, the retained approach is based on pair copula construction (PCC). A literature review leads us to choose a D-Vine model for the construction of modal parameters probability distributions. Identification of this model is based on likelihood maximization which makes it sensitive to the dimension of the distribution, namely the number of considered modes in our context. To this respect, a mode selection preprocessing step is proposed. It allows the selection of the relevant random modes for a given transfer function. The second point, addressed in this study, concerns the choice of the D-Vine model. Indeed, D-Vine model is not uniquely defined. Two strategies are proposed and compared. The first one is based on the context of the study whereas the second one is purely based on statistical considerations. Finally, the proposed approaches are numerically studied and compared with respect to their capabilities, first in the identification of the probability distribution of random modal parameters and second in the estimation of the 99 % quantiles of some transfer functions.

Evaluation of Dynamic Coastal Response to Sea-level Rise Modifies Inundation Likelihood

NASA Technical Reports Server (NTRS)

Lentz, Erika E.; Thieler, E. Robert; Plant, Nathaniel G.; Stippa, Sawyer R.; Horton, Radley M.; Gesch, Dean B.

2016-01-01

Sea-level rise (SLR) poses a range of threats to natural and built environments, making assessments of SLR-induced hazards essential for informed decision making. We develop a probabilistic model that evaluates the likelihood that an area will inundate (flood) or dynamically respond (adapt) to SLR. The broad-area applicability of the approach is demonstrated by producing 30x30m resolution predictions for more than 38,000 sq km of diverse coastal landscape in the northeastern United States. Probabilistic SLR projections, coastal elevation and vertical land movement are used to estimate likely future inundation levels. Then, conditioned on future inundation levels and the current land-cover type, we evaluate the likelihood of dynamic response versus inundation. We find that nearly 70% of this coastal landscape has some capacity to respond dynamically to SLR, and we show that inundation models over-predict land likely to submerge. This approach is well suited to guiding coastal resource management decisions that weigh future SLR impacts and uncertainty against ecological targets and economic constraints.

A Comparison of Pseudo-Maximum Likelihood and Asymptotically Distribution-Free Dynamic Factor Analysis Parameter Estimation in Fitting Covariance Structure Models to Block-Toeplitz Matrices Representing Single-Subject Multivariate Time-Series.

ERIC Educational Resources Information Center

Molenaar, Peter C. M.; Nesselroade, John R.

1998-01-01

Pseudo-Maximum Likelihood (p-ML) and Asymptotically Distribution Free (ADF) estimation methods for estimating dynamic factor model parameters within a covariance structure framework were compared through a Monte Carlo simulation. Both methods appear to give consistent model parameter estimates, but only ADF gives standard errors and chi-square…

Accurate Structural Correlations from Maximum Likelihood Superpositions

PubMed Central

Theobald, Douglas L; Wuttke, Deborah S

2008-01-01

The cores of globular proteins are densely packed, resulting in complicated networks of structural interactions. These interactions in turn give rise to dynamic structural correlations over a wide range of time scales. Accurate analysis of these complex correlations is crucial for understanding biomolecular mechanisms and for relating structure to function. Here we report a highly accurate technique for inferring the major modes of structural correlation in macromolecules using likelihood-based statistical analysis of sets of structures. This method is generally applicable to any ensemble of related molecules, including families of nuclear magnetic resonance (NMR) models, different crystal forms of a protein, and structural alignments of homologous proteins, as well as molecular dynamics trajectories. Dominant modes of structural correlation are determined using principal components analysis (PCA) of the maximum likelihood estimate of the correlation matrix. The correlations we identify are inherently independent of the statistical uncertainty and dynamic heterogeneity associated with the structural coordinates. We additionally present an easily interpretable method (“PCA plots”) for displaying these positional correlations by color-coding them onto a macromolecular structure. Maximum likelihood PCA of structural superpositions, and the structural PCA plots that illustrate the results, will facilitate the accurate determination of dynamic structural correlations analyzed in diverse fields of structural biology. PMID:18282091

The risk of developing a work disability across the adulthood years.

PubMed

Rank, Mark R; Hirschl, Thomas A

2014-04-01

Work disability has implications for individual health, national health care expenditures, economic productivity, and the social safety net. Knowledge about population dynamics and risk factors associated with work disability are not delineated by cross-sectional research. In this paper the authors estimate, for the first time, the prospective lifetime risk that a head of household will report a work disability. Using forty years of longitudinal data from the Panel Study of Income Dynamics (PSID), we estimate the lifetime risk of developing a work disability and conduct a logistic regression analysis to examine personal characteristics that increase the likelihood of a self-reported work disability. Life table methods are used to calculate lifetime prevalence, and to compute covariate effects. Between the ages of 25 and 60, over half (54.6%) of U.S. household heads will self-report a work disability, and approximately one quarter (24.1%) will self-report a severe work disability. Persons with income below 150% of the federal poverty level, or lower educational attainment, have an increased likelihood of reporting a work disability. This study finds that more than half of U.S. household heads will self-report a work disability, which is a higher prevalence than in existing cross-sectional estimates. The social context for this finding is that work disability is a major driver of spending on health care services and the social safety net. Copyright © 2014 Elsevier Inc. All rights reserved.

The Extended Language Network: A Meta-Analysis of Neuroimaging Studies on Text Comprehension

PubMed Central

Ferstl, Evelyn C.; Neumann, Jane; Bogler, Carsten; von Cramon, D. Yves

2010-01-01

Language processing in context requires more than merely comprehending words and sentences. Important subprocesses are inferences for bridging successive utterances, the use of background knowledge and discourse context, and pragmatic interpretations. The functional neuroanatomy of these text comprehension processes has only recently been investigated. Although there is evidence for right-hemisphere contributions, reviews have implicated the left lateral prefrontal cortex, left temporal regions beyond Wernicke’s area, and the left dorso-medial prefrontal cortex (dmPFC) for text comprehension. To objectively confirm this extended language network and to evaluate the respective contribution of right hemisphere regions, meta-analyses of 23 neuroimaging studies are reported here. The analyses used replicator dynamics based on activation likelihood estimates. Independent of the baseline, the anterior temporal lobes (aTL) were active bilaterally. In addition, processing of coherent compared with incoherent text engaged the dmPFC and the posterior cingulate cortex. Right hemisphere activations were seen most notably in the analysis of contrasts testing specific subprocesses, such as metaphor comprehension. These results suggest task dependent contributions for the lateral PFC and the right hemisphere. Most importantly, they confirm the role of the aTL and the fronto-medial cortex for language processing in context. PMID:17557297

MXLKID: a maximum likelihood parameter identifier. [In LRLTRAN for CDC 7600

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

Gavel, D.T.

MXLKID (MaXimum LiKelihood IDentifier) is a computer program designed to identify unknown parameters in a nonlinear dynamic system. Using noisy measurement data from the system, the maximum likelihood identifier computes a likelihood function (LF). Identification of system parameters is accomplished by maximizing the LF with respect to the parameters. The main body of this report briefly summarizes the maximum likelihood technique and gives instructions and examples for running the MXLKID program. MXLKID is implemented LRLTRAN on the CDC7600 computer at LLNL. A detailed mathematical description of the algorithm is given in the appendices. 24 figures, 6 tables.

Automatic segmentation of fibroglandular tissue in breast MRI using anatomy-driven three-dimensional spatial context

NASA Astrophysics Data System (ADS)

Wei, Dong; Weinstein, Susan; Hsieh, Meng-Kang; Pantalone, Lauren; Kontos, Despina

2018-03-01

The relative amount of fibroglandular tissue (FGT) in the breast has been shown to be a risk factor for breast cancer. However, automatic segmentation of FGT in breast MRI is challenging due mainly to its wide variation in anatomy (e.g., amount, location and pattern, etc.), and various imaging artifacts especially the prevalent bias-field artifact. Motivated by a previous work demonstrating improved FGT segmentation with 2-D a priori likelihood atlas, we propose a machine learning-based framework using 3-D FGT context. The framework uses features specifically defined with respect to the breast anatomy to capture spatially varying likelihood of FGT, and allows (a) intuitive standardization across breasts of different sizes and shapes, and (b) easy incorporation of additional information helpful to the segmentation (e.g., texture). Extended from the concept of 2-D atlas, our framework not only captures spatial likelihood of FGT in 3-D context, but also broadens its applicability to both sagittal and axial breast MRI rather than being limited to the plane in which the 2-D atlas is constructed. Experimental results showed improved segmentation accuracy over the 2-D atlas method, and demonstrated further improvement by incorporating well-established texture descriptors.

Migration, business formation, and the informal economy in urban Mexico.

PubMed

Sheehan, Connor M; Riosmena, Fernando

2013-07-01

Although the informal economy has grown rapidly in several developing nations, and migration and informality may be related to similar types of credit constraints and market failures, previous research has not systematically attempted to identify if migrant households are more likely to start informal and formal businesses alike and if this association varies across local contexts. We examine the relationship between prior US migration and the creation of both formal and informal businesses in urban Mexico using several criteria to indirectly assess sector location. We use data from 56 communities from the Mexican Migration Project to estimate multilevel survival and nonmultilevel competing risk models predicting the likelihood of informal, formal, and no business formation. The recent return migration of the household head is strongly associated with informal business creation, particularly in economically dynamic areas. On the other hand, migrants are only marginally more likely to start formal businesses in highly economically dynamic sending areas. Published by Elsevier Inc.

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Free energy reconstruction from steered dynamics without post-processing

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

Athenes, Manuel, E-mail: Manuel.Athenes@cea.f; Condensed Matter and Materials Division, Physics and Life Sciences Directorate, LLNL, Livermore, CA 94551; Marinica, Mihai-Cosmin

2010-09-20

Various methods achieving importance sampling in ensembles of nonequilibrium trajectories enable one to estimate free energy differences and, by maximum-likelihood post-processing, to reconstruct free energy landscapes. Here, based on Bayes theorem, we propose a more direct method in which a posterior likelihood function is used both to construct the steered dynamics and to infer the contribution to equilibrium of all the sampled states. The method is implemented with two steering schedules. First, using non-autonomous steering, we calculate the migration barrier of the vacancy in Fe-{alpha}. Second, using an autonomous scheduling related to metadynamics and equivalent to temperature-accelerated molecular dynamics, wemore » accurately reconstruct the two-dimensional free energy landscape of the 38-atom Lennard-Jones cluster as a function of an orientational bond-order parameter and energy, down to the solid-solid structural transition temperature of the cluster and without maximum-likelihood post-processing.« less

Memory for faces: the effect of facial appearance and the context in which the face is encountered.

PubMed

Mattarozzi, Katia; Todorov, Alexander; Codispoti, Maurizio

2015-03-01

We investigated the effects of appearance of emotionally neutral faces and the context in which the faces are encountered on incidental face memory. To approximate real-life situations as closely as possible, faces were embedded in a newspaper article, with a headline that specified an action performed by the person pictured. We found that facial appearance affected memory so that faces perceived as trustworthy or untrustworthy were remembered better than neutral ones. Furthermore, the memory of untrustworthy faces was slightly better than that of trustworthy faces. The emotional context of encoding affected the details of face memory. Faces encountered in a neutral context were more likely to be recognized as only familiar. In contrast, emotionally relevant contexts of encoding, whether pleasant or unpleasant, increased the likelihood of remembering semantic and even episodic details associated with faces. These findings suggest that facial appearance (i.e., perceived trustworthiness) affects face memory. Moreover, the findings support prior evidence that the engagement of emotion processing during memory encoding increases the likelihood that events are not only recognized but also remembered.

Estimation of Dynamic Discrete Choice Models by Maximum Likelihood and the Simulated Method of Moments

PubMed Central

Eisenhauer, Philipp; Heckman, James J.; Mosso, Stefano

2015-01-01

We compare the performance of maximum likelihood (ML) and simulated method of moments (SMM) estimation for dynamic discrete choice models. We construct and estimate a simplified dynamic structural model of education that captures some basic features of educational choices in the United States in the 1980s and early 1990s. We use estimates from our model to simulate a synthetic dataset and assess the ability of ML and SMM to recover the model parameters on this sample. We investigate the performance of alternative tuning parameters for SMM. PMID:26494926

Evaluation of dynamic coastal response to sea-level rise modifies inundation likelihood

USGS Publications Warehouse

Lentz, Erika E.; Thieler, E. Robert; Plant, Nathaniel G.; Stippa, Sawyer R.; Horton, Radley M.; Gesch, Dean B.

2016-01-01

Sea-level rise (SLR) poses a range of threats to natural and built environments1, 2, making assessments of SLR-induced hazards essential for informed decision making3. We develop a probabilistic model that evaluates the likelihood that an area will inundate (flood) or dynamically respond (adapt) to SLR. The broad-area applicability of the approach is demonstrated by producing 30 × 30 m resolution predictions for more than 38,000 km2 of diverse coastal landscape in the northeastern United States. Probabilistic SLR projections, coastal elevation and vertical land movement are used to estimate likely future inundation levels. Then, conditioned on future inundation levels and the current land-cover type, we evaluate the likelihood of dynamic response versus inundation. We find that nearly 70% of this coastal landscape has some capacity to respond dynamically to SLR, and we show that inundation models over-predict land likely to submerge. This approach is well suited to guiding coastal resource management decisions that weigh future SLR impacts and uncertainty against ecological targets and economic constraints.

Future evolution in a backreaction model and the analogous scalar field cosmology

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

Ali, Amna; Majumdar, A.S., E-mail: amnaalig@gmail.com, E-mail: archan@bose.res.in

We investigate the future evolution of the universe using the Buchert framework for averaged backreaction in the context of a two-domain partition of the universe. We show that this approach allows for the possibility of the global acceleration vanishing at a finite future time, provided that none of the subdomains accelerate individually. The model at large scales is analogously described in terms of a homogeneous scalar field emerging with a potential that is fixed and free from phenomenological parametrization. The dynamics of this scalar field is explored in the analogous FLRW cosmology. We use observational data from Type Ia Supernovae,more » Baryon Acoustic Oscillations, and Cosmic Microwave Background to constrain the parameters of the model for a viable cosmology, providing the corresponding likelihood contours.« less

Measurement of the Top Quark Mass by Dynamical Likelihood Method using the Lepton plus Jets Events in 1.96 Tev Proton-Antiproton Collisions

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

Yorita, Kohei

2005-03-01

We have measured the top quark mass with the dynamical likelihood method (DLM) using the CDF II detector at the Fermilab Tevatron. The Tevatron produces top and anti-top pairs in pp collisions at a center of mass energy of 1.96 TeV. The data sample used in this paper was accumulated from March 2002 through August 2003 which corresponds to an integrated luminosity of 162 pb -1.

Rules or consequences? The role of ethical mind-sets in moral dynamics.

PubMed

Cornelissen, Gert; Bashshur, Michael R; Rode, Julian; Le Menestrel, Marc

2013-04-01

Recent research on the dynamics of moral behavior has documented two contrasting phenomena-moral consistency and moral balancing. Moral balancing refers to the phenomenon whereby behaving ethically or unethically decreases the likelihood of engaging in the same type of behavior again later. Moral consistency describes the opposite pattern-engaging in ethical or unethical behavior increases the likelihood of engaging in the same type of behavior later on. The three studies reported here supported the hypothesis that individuals' ethical mind-set (i.e., outcome-based vs. rule-based) moderates the impact of an initial ethical or unethical act on the likelihood of behaving ethically on a subsequent occasion. More specifically, an outcome-based mind-set facilitated moral balancing, and a rule-based mind-set facilitated moral consistency.

"Medicus Interruptus" in the Behaviour of Children in Disadvantaged Contexts in Scotland

ERIC Educational Resources Information Center

Allan, Julie; Harwood, Valerie

2014-01-01

The medicalisation of the behaviour of children is a phenomenon that is attracting growing attention, with particular concern about the increased likelihood of children living in disadvantaged contexts receiving a medical diagnosis, such as attention-deficit hyperactivity disorder, and treatment. This paper reports on a study of professionals…

Cognitive Effort Is Modulated outside of the Explicit Awareness of Conflict Frequency: Evidence from Pupillometry

ERIC Educational Resources Information Center

Diede, Nathaniel T.; Bugg, Julie M.

2017-01-01

Classic theories of cognitive control conceptualized controlled processes as slow, strategic, and willful, with automatic processes being fast and effortless. The context-specific proportion compatibility (CSPC) effect, the reduction in the compatibility effect in a context (e.g., location) associated with a high relative to low likelihood of…

Urban Options for Psychological Restoration: Common Strategies in Everyday Situations.

PubMed

Staats, Henk; Jahncke, Helena; Herzog, Thomas R; Hartig, Terry

2016-01-01

Given the need for knowledge on the restorative potential of urban settings, we sought to estimate the effects of personal and contextual factors on preferences and restoration likelihood assessments for different urban activities-in-environments. We also sought to study the generality of these effects across different countries. We conducted a true experiment with convenience samples of university students in the Netherlands (n = 80), Sweden (n = 100), and the USA (n = 316). In each country, the experiment had a mixed design with activities-in-environments (sitting in a park, sitting in a cafe, walking in a shopping mall, walking along a busy street) manipulated within-subjects and the need for restoration (attentional fatigue, no attentional fatigue) and immediate social context (in company, alone) manipulated between-subjects. The manipulations relied on previously tested scenarios describing everyday situations that participants were instructed to remember and imagine themselves being in. For each imagined situation (activity-in-environment with antecedent fatigue condition and immediate social context), subjects provided two criterion measures: general preference and the likelihood of achieving psychological restoration. The settings received different preference and restoration likelihood ratings as expected, affirming that a busy street, often used in comparisons with natural settings, is not representative of the restorative potential of urban settings. Being with a close friend and attentional fatigue both moderated ratings for specific settings. Findings of additional moderation by country of residence caution against broad generalizations regarding preferences for and the expected restorative effects of different urban settings. Preferences and restoration likelihood ratings for urban activity-environment combinations are subject to multiple personal and contextual determinants, including level of attentional fatigue, being alone versus in company, and broader aspects of the urban context that vary across cities and countries. Claims regarding a lack of restorative quality in urban environments are problematic.

A black box optimization approach to parameter estimation in a model for long/short term variations dynamics of commodity prices

NASA Astrophysics Data System (ADS)

De Santis, Alberto; Dellepiane, Umberto; Lucidi, Stefano

2012-11-01

In this paper we investigate the estimation problem for a model of the commodity prices. This model is a stochastic state space dynamical model and the problem unknowns are the state variables and the system parameters. Data are represented by the commodity spot prices, very seldom time series of Futures contracts are available for free. Both the system joint likelihood function (state variables and parameters) and the system marginal likelihood (the state variables are eliminated) function are addressed.

Appendix 2: Risk-based framework and risk case studies. Risk assessment for forested habitats in northern Wisconsin.

Treesearch

Louis R. Iverson; Stephen N. Matthews; Anantha M. Prasad; Matthew P. Peters; Gary W. Yohe

2012-01-01

We used a risk matrix to assess risk from climate change for multiple forest species by discussing an example that depicts a range of risk for three tree species of northern Wisconsin. Risk is defined here as the product of the likelihood of an event occurring and the consequences or effects of that event. In the context of species habitats, likelihood is related to...

Application of maximum-likelihood estimation in optical coherence tomography for nanometer-class thickness estimation

NASA Astrophysics Data System (ADS)

Huang, Jinxin; Yuan, Qun; Tankam, Patrice; Clarkson, Eric; Kupinski, Matthew; Hindman, Holly B.; Aquavella, James V.; Rolland, Jannick P.

2015-03-01

In biophotonics imaging, one important and quantitative task is layer-thickness estimation. In this study, we investigate the approach of combining optical coherence tomography and a maximum-likelihood (ML) estimator for layer thickness estimation in the context of tear film imaging. The motivation of this study is to extend our understanding of tear film dynamics, which is the prerequisite to advance the management of Dry Eye Disease, through the simultaneous estimation of the thickness of the tear film lipid and aqueous layers. The estimator takes into account the different statistical processes associated with the imaging chain. We theoretically investigated the impact of key system parameters, such as the axial point spread functions (PSF) and various sources of noise on measurement uncertainty. Simulations show that an OCT system with a 1 μm axial PSF (FWHM) allows unbiased estimates down to nanometers with nanometer precision. In implementation, we built a customized Fourier domain OCT system that operates in the 600 to 1000 nm spectral window and achieves 0.93 micron axial PSF in corneal epithelium. We then validated the theoretical framework with physical phantoms made of custom optical coatings, with layer thicknesses from tens of nanometers to microns. Results demonstrate unbiased nanometer-class thickness estimates in three different physical phantoms.

Testing students' e-learning via Facebook through Bayesian structural equation modeling.

PubMed

Salarzadeh Jenatabadi, Hashem; Moghavvemi, Sedigheh; Wan Mohamed Radzi, Che Wan Jasimah Bt; Babashamsi, Parastoo; Arashi, Mohammad

2017-01-01

Learning is an intentional activity, with several factors affecting students' intention to use new learning technology. Researchers have investigated technology acceptance in different contexts by developing various theories/models and testing them by a number of means. Although most theories/models developed have been examined through regression or structural equation modeling, Bayesian analysis offers more accurate data analysis results. To address this gap, the unified theory of acceptance and technology use in the context of e-learning via Facebook are re-examined in this study using Bayesian analysis. The data (S1 Data) were collected from 170 students enrolled in a business statistics course at University of Malaya, Malaysia, and tested with the maximum likelihood and Bayesian approaches. The difference between the two methods' results indicates that performance expectancy and hedonic motivation are the strongest factors influencing the intention to use e-learning via Facebook. The Bayesian estimation model exhibited better data fit than the maximum likelihood estimator model. The results of the Bayesian and maximum likelihood estimator approaches are compared and the reasons for the result discrepancy are deliberated.

Testing students’ e-learning via Facebook through Bayesian structural equation modeling

PubMed Central

Moghavvemi, Sedigheh; Wan Mohamed Radzi, Che Wan Jasimah Bt; Babashamsi, Parastoo; Arashi, Mohammad

2017-01-01

Learning is an intentional activity, with several factors affecting students’ intention to use new learning technology. Researchers have investigated technology acceptance in different contexts by developing various theories/models and testing them by a number of means. Although most theories/models developed have been examined through regression or structural equation modeling, Bayesian analysis offers more accurate data analysis results. To address this gap, the unified theory of acceptance and technology use in the context of e-learning via Facebook are re-examined in this study using Bayesian analysis. The data (S1 Data) were collected from 170 students enrolled in a business statistics course at University of Malaya, Malaysia, and tested with the maximum likelihood and Bayesian approaches. The difference between the two methods’ results indicates that performance expectancy and hedonic motivation are the strongest factors influencing the intention to use e-learning via Facebook. The Bayesian estimation model exhibited better data fit than the maximum likelihood estimator model. The results of the Bayesian and maximum likelihood estimator approaches are compared and the reasons for the result discrepancy are deliberated. PMID:28886019

Influences of Neighborhood Context, Individual History and Parenting Behavior on Recidivism among Juvenile Offenders

ERIC Educational Resources Information Center

Grunwald, Heidi E.; Lockwood, Brian; Harris, Philip W.; Mennis, Jeremy

2010-01-01

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…

Statistical inference for noisy nonlinear ecological dynamic systems.

PubMed

Wood, Simon N

2010-08-26

Chaotic ecological dynamic systems defy conventional statistical analysis. Systems with near-chaotic dynamics are little better. Such systems are almost invariably driven by endogenous dynamic processes plus demographic and environmental process noise, and are only observable with error. Their sensitivity to history means that minute changes in the driving noise realization, or the system parameters, will cause drastic changes in the system trajectory. This sensitivity is inherited and amplified by the joint probability density of the observable data and the process noise, rendering it useless as the basis for obtaining measures of statistical fit. Because the joint density is the basis for the fit measures used by all conventional statistical methods, this is a major theoretical shortcoming. The inability to make well-founded statistical inferences about biological dynamic models in the chaotic and near-chaotic regimes, other than on an ad hoc basis, leaves dynamic theory without the methods of quantitative validation that are essential tools in the rest of biological science. Here I show that this impasse can be resolved in a simple and general manner, using a method that requires only the ability to simulate the observed data on a system from the dynamic model about which inferences are required. The raw data series are reduced to phase-insensitive summary statistics, quantifying local dynamic structure and the distribution of observations. Simulation is used to obtain the mean and the covariance matrix of the statistics, given model parameters, allowing the construction of a 'synthetic likelihood' that assesses model fit. This likelihood can be explored using a straightforward Markov chain Monte Carlo sampler, but one further post-processing step returns pure likelihood-based inference. I apply the method to establish the dynamic nature of the fluctuations in Nicholson's classic blowfly experiments.

International Sexual Partnerships May Be Shaped by Sexual Histories and Socioeconomic Status.

PubMed

Truong, Hong-Ha M; Mehrotra, Megha; Montoya, Orlando; Lama, Javier R; Guanira, Juan V; Casapía, Martín; Veloso, Valdiléa G; Buchbinder, Susan P; Mayer, Kenneth H; Chariyalertsak, Suwat; Schechter, Mauro; Bekker, Linda-Gail; Kallás, Esper G; Grant, Robert M

2017-05-01

Exchange sex and higher education were associated with an increased likelihood of international sexual partnerships (ISPs). Exchange sex and older age were associated with an increased likelihood of condomless sex in ISPs. Educational and socioeconomic factors may create unbalanced power dynamics that influence exchange sex and condomless sex in ISPs.

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.

Laser-Based Slam with Efficient Occupancy Likelihood Map Learning for Dynamic Indoor Scenes

NASA Astrophysics Data System (ADS)

Li, Li; Yao, Jian; Xie, Renping; Tu, Jinge; Feng, Chen

2016-06-01

Location-Based Services (LBS) have attracted growing attention in recent years, especially in indoor environments. The fundamental technique of LBS is the map building for unknown environments, this technique also named as simultaneous localization and mapping (SLAM) in robotic society. In this paper, we propose a novel approach for SLAMin dynamic indoor scenes based on a 2D laser scanner mounted on a mobile Unmanned Ground Vehicle (UGV) with the help of the grid-based occupancy likelihood map. Instead of applying scan matching in two adjacent scans, we propose to match current scan with the occupancy likelihood map learned from all previous scans in multiple scales to avoid the accumulation of matching errors. Due to that the acquisition of the points in a scan is sequential but not simultaneous, there unavoidably exists the scan distortion at different extents. To compensate the scan distortion caused by the motion of the UGV, we propose to integrate a velocity of a laser range finder (LRF) into the scan matching optimization framework. Besides, to reduce the effect of dynamic objects such as walking pedestrians often existed in indoor scenes as much as possible, we propose a new occupancy likelihood map learning strategy by increasing or decreasing the probability of each occupancy grid after each scan matching. Experimental results in several challenged indoor scenes demonstrate that our proposed approach is capable of providing high-precision SLAM results.

Statistical inference approach to structural reconstruction of complex networks from binary time series

NASA Astrophysics Data System (ADS)

Ma, Chuang; Chen, Han-Shuang; Lai, Ying-Cheng; Zhang, Hai-Feng

2018-02-01

Complex networks hosting binary-state dynamics arise in a variety of contexts. In spite of previous works, to fully reconstruct the network structure from observed binary data remains challenging. We articulate a statistical inference based approach to this problem. In particular, exploiting the expectation-maximization (EM) algorithm, we develop a method to ascertain the neighbors of any node in the network based solely on binary data, thereby recovering the full topology of the network. A key ingredient of our method is the maximum-likelihood estimation of the probabilities associated with actual or nonexistent links, and we show that the EM algorithm can distinguish the two kinds of probability values without any ambiguity, insofar as the length of the available binary time series is reasonably long. Our method does not require any a priori knowledge of the detailed dynamical processes, is parameter-free, and is capable of accurate reconstruction even in the presence of noise. We demonstrate the method using combinations of distinct types of binary dynamical processes and network topologies, and provide a physical understanding of the underlying reconstruction mechanism. Our statistical inference based reconstruction method contributes an additional piece to the rapidly expanding "toolbox" of data based reverse engineering of complex networked systems.

Competitiveness and the Process of Co-adaptation in Team Sport Performance.

PubMed

Passos, Pedro; Araújo, Duarte; Davids, Keith

2016-01-01

An evolutionary psycho-biological perspective on competitiveness dynamics is presented, focusing on continuous behavioral co-adaptations to constraints that arise in performance environments. We suggest that an athlete's behavioral dynamics are constrained by circumstances of competing for the availability of resources, which once obtained offer possibilities for performance success. This defines the influence of the athlete-environment relationship on competitiveness. Constraining factors in performance include proximity to target areas in team sports and the number of other competitors in a location. By pushing the athlete beyond existing limits, competitiveness enhances opportunities for co-adaptation, innovation and creativity, which can lead individuals toward different performance solutions to achieve the same performance goal. Underpinned by an ecological dynamics framework we examine whether competitiveness is a crucial feature to succeed in team sports. Our focus is on intra-team competitiveness, concerning the capacity of individuals within a team to become perceptually attuned to affordances in a given performance context which can increase their likelihood of success. This conceptualization implies a re-consideration of the concept of competitiveness, not as an inherited trait or entity to be acquired, but rather theorizing it as a functional performer-environment relationship that needs to be explored, developed, enhanced and maintained in team games training programs.

Statistical inference approach to structural reconstruction of complex networks from binary time series.

PubMed

Ma, Chuang; Chen, Han-Shuang; Lai, Ying-Cheng; Zhang, Hai-Feng

2018-02-01

Complex networks hosting binary-state dynamics arise in a variety of contexts. In spite of previous works, to fully reconstruct the network structure from observed binary data remains challenging. We articulate a statistical inference based approach to this problem. In particular, exploiting the expectation-maximization (EM) algorithm, we develop a method to ascertain the neighbors of any node in the network based solely on binary data, thereby recovering the full topology of the network. A key ingredient of our method is the maximum-likelihood estimation of the probabilities associated with actual or nonexistent links, and we show that the EM algorithm can distinguish the two kinds of probability values without any ambiguity, insofar as the length of the available binary time series is reasonably long. Our method does not require any a priori knowledge of the detailed dynamical processes, is parameter-free, and is capable of accurate reconstruction even in the presence of noise. We demonstrate the method using combinations of distinct types of binary dynamical processes and network topologies, and provide a physical understanding of the underlying reconstruction mechanism. Our statistical inference based reconstruction method contributes an additional piece to the rapidly expanding "toolbox" of data based reverse engineering of complex networked systems.

Competitiveness and the Process of Co-adaptation in Team Sport Performance

PubMed Central

Passos, Pedro; Araújo, Duarte; Davids, Keith

2016-01-01

An evolutionary psycho-biological perspective on competitiveness dynamics is presented, focusing on continuous behavioral co-adaptations to constraints that arise in performance environments. We suggest that an athlete’s behavioral dynamics are constrained by circumstances of competing for the availability of resources, which once obtained offer possibilities for performance success. This defines the influence of the athlete-environment relationship on competitiveness. Constraining factors in performance include proximity to target areas in team sports and the number of other competitors in a location. By pushing the athlete beyond existing limits, competitiveness enhances opportunities for co-adaptation, innovation and creativity, which can lead individuals toward different performance solutions to achieve the same performance goal. Underpinned by an ecological dynamics framework we examine whether competitiveness is a crucial feature to succeed in team sports. Our focus is on intra-team competitiveness, concerning the capacity of individuals within a team to become perceptually attuned to affordances in a given performance context which can increase their likelihood of success. This conceptualization implies a re-consideration of the concept of competitiveness, not as an inherited trait or entity to be acquired, but rather theorizing it as a functional performer-environment relationship that needs to be explored, developed, enhanced and maintained in team games training programs. PMID:27777565

International Sexual Partnerships May Be Shaped by Sexual Histories and Socioeconomic Status

PubMed Central

Truong, Hong-Ha M.; Mehrotra, Megha; Montoya, Orlando; Lama, Javier R.; Guanira, Juan V.; Casapía, Martín; Veloso, Valdiléa G.; Buchbinder, Susan P.; Mayer, Kenneth H.; Chariyalertsak, Suwat; Schechter, Mauro; Bekker, Linda-Gail; Kallás, Esper G.; Grant, Robert M.

2017-01-01

Exchange sex and higher education were associated with an increased likelihood of international sexual partnerships (ISPs). Exchange sex and older age were associated with an increased likelihood of condomless sex in ISPs. Educational and socioeconomic factors may create unbalanced power dynamics that influence exchange sex and condomless sex in ISPs. PMID:28407648

Getting to social action: the Youth Empowerment Strategies (YES!) project.

PubMed

Wilson, Nance; Minkler, Meredith; Dasho, Stefan; Wallerstein, Nina; Martin, Anna C

2008-10-01

This article describes the social action component of the Youth Empowerment Strategies (YES!) project funded by the Centers for Disease Control and Prevention through its community-based prevention research (CBPR) initiative. YES! is designed to promote problem-solving skills, social action, and civic participation among underserved elementary and middle school youth. The after-school program focuses on identifying and building youths' capacities and strengths as a means of ultimately decreasing rates of alcohol, tobacco, and other drug use and other risky behaviors. The article discusses the conceptual models of risk and intervention and factors contributing to successful social action work, including group dynamics, intragroup leadership, facilitator skills, and school-community contexts. Attention is focused on how the nature of the projects themselves played a key role in determining the likelihood of experiencing success. Implications and recommendations for other youth-focused empowerment education projects are discussed, including the effective use of Photovoice in such projects.

Solving the puzzle of collective action through inter-individual differences

PubMed Central

von Rueden, Chris; Gavrilets, Sergey; Glowacki, Luke

2015-01-01

Models of collective action infrequently account for differences across individuals beyond a limited set of strategies, ignoring variation in endowment (e.g. physical condition, wealth, knowledge, personality, support), individual costs of effort, or expected gains from cooperation. However, behavioural research indicates these inter-individual differences can have significant effects on the dynamics of collective action. The papers contributed to this theme issue evaluate how individual differences affect the propensity to cooperate, and how they can catalyse others’ likelihood of cooperation (e.g. via leadership). Many of the papers emphasize the relationship between individual decisions and socio-ecological context, particularly the effect of group size. All together, the papers in this theme issue provide a more complete picture of collective action, by embracing the reality of inter-individual variation and its multiple roles in the success or failure of collective action. PMID:26503677

Seasonal species interactions minimize the impact of species turnover on the likelihood of community persistence.

PubMed

Saavedra, Serguei; Rohr, Rudolf P; Fortuna, Miguel A; Selva, Nuria; Bascompte, Jordi

2016-04-01

Many of the observed species interactions embedded in ecological communities are not permanent, but are characterized by temporal changes that are observed along with abiotic and biotic variations. While work has been done describing and quantifying these changes, little is known about their consequences for species coexistence. Here, we investigate the extent to which changes of species composition impact the likelihood of persistence of the predator-prey community in the highly seasonal Białowieza Primeval Forest (northeast Poland), and the extent to which seasonal changes of species interactions (predator diet) modulate the expected impact. This likelihood is estimated extending recent developments on the study of structural stability in ecological communities. We find that the observed species turnover strongly varies the likelihood of community persistence between summer and winter. Importantly, we demonstrate that the observed seasonal interaction changes minimize the variation in the likelihood of persistence associated with species turnover across the year. We find that these community dynamics can be explained as the coupling of individual species to their environment by minimizing both the variation in persistence conditions and the interaction changes between seasons. Our results provide a homeostatic explanation for seasonal species interactions and suggest that monitoring the association of interactions changes with the level of variation in community dynamics can provide a good indicator of the response of species to environmental pressures.

Maximum-likelihood methods in wavefront sensing: stochastic models and likelihood functions

PubMed Central

Barrett, Harrison H.; Dainty, Christopher; Lara, David

2008-01-01

Maximum-likelihood (ML) estimation in wavefront sensing requires careful attention to all noise sources and all factors that influence the sensor data. We present detailed probability density functions for the output of the image detector in a wavefront sensor, conditional not only on wavefront parameters but also on various nuisance parameters. Practical ways of dealing with nuisance parameters are described, and final expressions for likelihoods and Fisher information matrices are derived. The theory is illustrated by discussing Shack–Hartmann sensors, and computational requirements are discussed. Simulation results show that ML estimation can significantly increase the dynamic range of a Shack–Hartmann sensor with four detectors and that it can reduce the residual wavefront error when compared with traditional methods. PMID:17206255

Do Different Mental Models Influence Cybersecurity Behavior? Evaluations via Statistical Reasoning Performance.

PubMed

Brase, Gary L; Vasserman, Eugene Y; Hsu, William

2017-01-01

Cybersecurity research often describes people as understanding internet security in terms of metaphorical mental models (e.g., disease risk, physical security risk, or criminal behavior risk). However, little research has directly evaluated if this is an accurate or productive framework. To assess this question, two experiments asked participants to respond to a statistical reasoning task framed in one of four different contexts (cybersecurity, plus the above alternative models). Each context was also presented using either percentages or natural frequencies, and these tasks were followed by a behavioral likelihood rating. As in previous research, consistent use of natural frequencies promoted correct Bayesian reasoning. There was little indication, however, that any of the alternative mental models generated consistently better understanding or reasoning over the actual cybersecurity context. There was some evidence that different models had some effects on patterns of responses, including the behavioral likelihood ratings, but these effects were small, as compared to the effect of the numerical format manipulation. This points to a need to improve the content of actual internet security warnings, rather than working to change the models users have of warnings.

Do Different Mental Models Influence Cybersecurity Behavior? Evaluations via Statistical Reasoning Performance

PubMed Central

Brase, Gary L.; Vasserman, Eugene Y.; Hsu, William

2017-01-01

Cybersecurity research often describes people as understanding internet security in terms of metaphorical mental models (e.g., disease risk, physical security risk, or criminal behavior risk). However, little research has directly evaluated if this is an accurate or productive framework. To assess this question, two experiments asked participants to respond to a statistical reasoning task framed in one of four different contexts (cybersecurity, plus the above alternative models). Each context was also presented using either percentages or natural frequencies, and these tasks were followed by a behavioral likelihood rating. As in previous research, consistent use of natural frequencies promoted correct Bayesian reasoning. There was little indication, however, that any of the alternative mental models generated consistently better understanding or reasoning over the actual cybersecurity context. There was some evidence that different models had some effects on patterns of responses, including the behavioral likelihood ratings, but these effects were small, as compared to the effect of the numerical format manipulation. This points to a need to improve the content of actual internet security warnings, rather than working to change the models users have of warnings. PMID:29163304

Urban Options for Psychological Restoration: Common Strategies in Everyday Situations

PubMed Central

Staats, Henk; Jahncke, Helena; Herzog, Thomas R.; Hartig, Terry

2016-01-01

Objectives Given the need for knowledge on the restorative potential of urban settings, we sought to estimate the effects of personal and contextual factors on preferences and restoration likelihood assessments for different urban activities-in-environments. We also sought to study the generality of these effects across different countries. Methods We conducted a true experiment with convenience samples of university students in the Netherlands (n = 80), Sweden (n = 100), and the USA (n = 316). In each country, the experiment had a mixed design with activities-in-environments (sitting in a park, sitting in a cafe, walking in a shopping mall, walking along a busy street) manipulated within-subjects and the need for restoration (attentional fatigue, no attentional fatigue) and immediate social context (in company, alone) manipulated between-subjects. The manipulations relied on previously tested scenarios describing everyday situations that participants were instructed to remember and imagine themselves being in. For each imagined situation (activity-in-environment with antecedent fatigue condition and immediate social context), subjects provided two criterion measures: general preference and the likelihood of achieving psychological restoration. Results The settings received different preference and restoration likelihood ratings as expected, affirming that a busy street, often used in comparisons with natural settings, is not representative of the restorative potential of urban settings. Being with a close friend and attentional fatigue both moderated ratings for specific settings. Findings of additional moderation by country of residence caution against broad generalizations regarding preferences for and the expected restorative effects of different urban settings. Conclusions Preferences and restoration likelihood ratings for urban activity-environment combinations are subject to multiple personal and contextual determinants, including level of attentional fatigue, being alone versus in company, and broader aspects of the urban context that vary across cities and countries. Claims regarding a lack of restorative quality in urban environments are problematic. PMID:26731272

The association of marital relationship and perceived social support with mental health of women in Pakistan

PubMed Central

2013-01-01

Background Marital circumstances have been indicated to be a salient risk factor for disproportionately high prevalence of depression and anxiety among Pakistani women. Although social support is a known buffer of psychological distress, there is no clear evidence as to how different aspects of marital relations interact and associate with depression and anxiety in the lives of Pakistani married women and the role of social supports in the context of their marriage. Methods Two hundred seventy seven married women were recruited from Rawalpindi district of Pakistan using a door knocking approach to psychometrically evaluate five scales for use in the Pakistani context. A confirmatory factor analysis approach was used to investigate the underlying factor structure of Couple satisfaction Index (CSI-4), Locke-Wallace Marital Adjustment Test (LWMAT), Relationship Dynamic Scale (RDS), Multidimensional Scale for Perceived Social Support (MSPSS) and the Hospital Anxiety and Depression Scale (HADS). The interplay of the constructs underlying the three aspects of marital relations, and the role of social support on the mental health of married Pakistani women were examined using the Structural Equation Model. Results The factor structures of MSPSS, CSI-4, LWMAT, RDS and HADS were similar to the findings reported in the developed and developing countries. Perceived higher social support reduces the likelihood of depression and anxiety by enhancing positive relationship as reflected by a low score on the relationship dynamics scale which decreases CMD symptoms. Moreover, perceived higher social support is positively associated with marital adjustment directly and indirectly through relationship dynamics which is associated with the reduced risk of depression through the increased level of reported marital satisfaction. Nuclear family structure, low level of education and higher socio-economic status were significantly associated with increased risk of mental illness among married women. Conclusion Findings of this study support the importance of considering elements of marital relationship: satisfaction, adjustment and negative interactions which can be prioritized to increase the efficiency of marital interventions. It also highlights the role of social support in the context of marital relationships among Pakistani women. Furthermore, the study presents the etiological models of depression and anxiety with reference to the above. PMID:25226599

The association of marital relationship and perceived social support with mental health of women in Pakistan.

PubMed

Qadir, Farah; Khalid, Amna; Haqqani, Sabahat; Zill-e-Huma; Medhin, Girmay

2013-12-09

Marital circumstances have been indicated to be a salient risk factor for disproportionately high prevalence of depression and anxiety among Pakistani women. Although social support is a known buffer of psychological distress, there is no clear evidence as to how different aspects of marital relations interact and associate with depression and anxiety in the lives of Pakistani married women and the role of social supports in the context of their marriage. Two hundred seventy seven married women were recruited from Rawalpindi district of Pakistan using a door knocking approach to psychometrically evaluate five scales for use in the Pakistani context. A confirmatory factor analysis approach was used to investigate the underlying factor structure of Couple satisfaction Index (CSI-4), Locke-Wallace Marital Adjustment Test (LWMAT), Relationship Dynamic Scale (RDS), Multidimensional Scale for Perceived Social Support (MSPSS) and the Hospital Anxiety and Depression Scale (HADS). The interplay of the constructs underlying the three aspects of marital relations, and the role of social support on the mental health of married Pakistani women were examined using the Structural Equation Model. The factor structures of MSPSS, CSI-4, LWMAT, RDS and HADS were similar to the findings reported in the developed and developing countries. Perceived higher social support reduces the likelihood of depression and anxiety by enhancing positive relationship as reflected by a low score on the relationship dynamics scale which decreases CMD symptoms. Moreover, perceived higher social support is positively associated with marital adjustment directly and indirectly through relationship dynamics which is associated with the reduced risk of depression through the increased level of reported marital satisfaction. Nuclear family structure, low level of education and higher socio-economic status were significantly associated with increased risk of mental illness among married women. Findings of this study support the importance of considering elements of marital relationship: satisfaction, adjustment and negative interactions which can be prioritized to increase the efficiency of marital interventions. It also highlights the role of social support in the context of marital relationships among Pakistani women. Furthermore, the study presents the etiological models of depression and anxiety with reference to the above.

An Analysis of Factor Extraction Strategies: A Comparison of the Relative Strengths of Principal Axis, Ordinary Least Squares, and Maximum Likelihood in Research Contexts That Include Both Categorical and Continuous Variables

ERIC Educational Resources Information Center

Coughlin, Kevin B.

2013-01-01

This study is intended to provide researchers with empirically derived guidelines for conducting factor analytic studies in research contexts that include dichotomous and continuous levels of measurement. This study is based on the hypotheses that ordinary least squares (OLS) factor analysis will yield more accurate parameter estimates than…

A Semiparametric Approach for Composite Functional Mapping of Dynamic Quantitative Traits

PubMed Central

Yang, Runqing; Gao, Huijiang; Wang, Xin; Zhang, Ji; Zeng, Zhao-Bang; Wu, Rongling

2007-01-01

Functional mapping has emerged as a powerful tool for mapping quantitative trait loci (QTL) that control developmental patterns of complex dynamic traits. Original functional mapping has been constructed within the context of simple interval mapping, without consideration of separate multiple linked QTL for a dynamic trait. In this article, we present a statistical framework for mapping QTL that affect dynamic traits by capitalizing on the strengths of functional mapping and composite interval mapping. Within this so-called composite functional-mapping framework, functional mapping models the time-dependent genetic effects of a QTL tested within a marker interval using a biologically meaningful parametric function, whereas composite interval mapping models the time-dependent genetic effects of the markers outside the test interval to control the genome background using a flexible nonparametric approach based on Legendre polynomials. Such a semiparametric framework was formulated by a maximum-likelihood model and implemented with the EM algorithm, allowing for the estimation and the test of the mathematical parameters that define the QTL effects and the regression coefficients of the Legendre polynomials that describe the marker effects. Simulation studies were performed to investigate the statistical behavior of composite functional mapping and compare its advantage in separating multiple linked QTL as compared to functional mapping. We used the new mapping approach to analyze a genetic mapping example in rice, leading to the identification of multiple QTL, some of which are linked on the same chromosome, that control the developmental trajectory of leaf age. PMID:17947431

Unified framework to evaluate panmixia and migration direction among multiple sampling locations.

PubMed

Beerli, Peter; Palczewski, Michal

2010-05-01

For many biological investigations, groups of individuals are genetically sampled from several geographic locations. These sampling locations often do not reflect the genetic population structure. We describe a framework using marginal likelihoods to compare and order structured population models, such as testing whether the sampling locations belong to the same randomly mating population or comparing unidirectional and multidirectional gene flow models. In the context of inferences employing Markov chain Monte Carlo methods, the accuracy of the marginal likelihoods depends heavily on the approximation method used to calculate the marginal likelihood. Two methods, modified thermodynamic integration and a stabilized harmonic mean estimator, are compared. With finite Markov chain Monte Carlo run lengths, the harmonic mean estimator may not be consistent. Thermodynamic integration, in contrast, delivers considerably better estimates of the marginal likelihood. The choice of prior distributions does not influence the order and choice of the better models when the marginal likelihood is estimated using thermodynamic integration, whereas with the harmonic mean estimator the influence of the prior is pronounced and the order of the models changes. The approximation of marginal likelihood using thermodynamic integration in MIGRATE allows the evaluation of complex population genetic models, not only of whether sampling locations belong to a single panmictic population, but also of competing complex structured population models.

Density-based empirical likelihood procedures for testing symmetry of data distributions and K-sample comparisons.

PubMed

Vexler, Albert; Tanajian, Hovig; Hutson, Alan D

In practice, parametric likelihood-ratio techniques are powerful statistical tools. In this article, we propose and examine novel and simple distribution-free test statistics that efficiently approximate parametric likelihood ratios to analyze and compare distributions of K groups of observations. Using the density-based empirical likelihood methodology, we develop a Stata package that applies to a test for symmetry of data distributions and compares K -sample distributions. Recognizing that recent statistical software packages do not sufficiently address K -sample nonparametric comparisons of data distributions, we propose a new Stata command, vxdbel, to execute exact density-based empirical likelihood-ratio tests using K samples. To calculate p -values of the proposed tests, we use the following methods: 1) a classical technique based on Monte Carlo p -value evaluations; 2) an interpolation technique based on tabulated critical values; and 3) a new hybrid technique that combines methods 1 and 2. The third, cutting-edge method is shown to be very efficient in the context of exact-test p -value computations. This Bayesian-type method considers tabulated critical values as prior information and Monte Carlo generations of test statistic values as data used to depict the likelihood function. In this case, a nonparametric Bayesian method is proposed to compute critical values of exact tests.

Stochastic control system parameter identifiability

NASA Technical Reports Server (NTRS)

Lee, C. H.; Herget, C. J.

1975-01-01

The parameter identification problem of general discrete time, nonlinear, multiple input/multiple output dynamic systems with Gaussian white distributed measurement errors is considered. The knowledge of the system parameterization was assumed to be known. Concepts of local parameter identifiability and local constrained maximum likelihood parameter identifiability were established. A set of sufficient conditions for the existence of a region of parameter identifiability was derived. A computation procedure employing interval arithmetic was provided for finding the regions of parameter identifiability. If the vector of the true parameters is locally constrained maximum likelihood (CML) identifiable, then with probability one, the vector of true parameters is a unique maximal point of the maximum likelihood function in the region of parameter identifiability and the constrained maximum likelihood estimation sequence will converge to the vector of true parameters.

Maximum likelihood estimation for Cox's regression model under nested case-control sampling.

PubMed

Scheike, Thomas H; Juul, Anders

2004-04-01

Nested case-control sampling is designed to reduce the costs of large cohort studies. It is important to estimate the parameters of interest as efficiently as possible. We present a new maximum likelihood estimator (MLE) for nested case-control sampling in the context of Cox's proportional hazards model. The MLE is computed by the EM-algorithm, which is easy to implement in the proportional hazards setting. Standard errors are estimated by a numerical profile likelihood approach based on EM aided differentiation. The work was motivated by a nested case-control study that hypothesized that insulin-like growth factor I was associated with ischemic heart disease. The study was based on a population of 3784 Danes and 231 cases of ischemic heart disease where controls were matched on age and gender. We illustrate the use of the MLE for these data and show how the maximum likelihood framework can be used to obtain information additional to the relative risk estimates of covariates.

Risk assessment by dynamic representation of vulnerability, exploitation, and impact

NASA Astrophysics Data System (ADS)

Cam, Hasan

2015-05-01

Assessing and quantifying cyber risk accurately in real-time is essential to providing security and mission assurance in any system and network. This paper presents a modeling and dynamic analysis approach to assessing cyber risk of a network in real-time by representing dynamically its vulnerabilities, exploitations, and impact using integrated Bayesian network and Markov models. Given the set of vulnerabilities detected by a vulnerability scanner in a network, this paper addresses how its risk can be assessed by estimating in real-time the exploit likelihood and impact of vulnerability exploitation on the network, based on real-time observations and measurements over the network. The dynamic representation of the network in terms of its vulnerabilities, sensor measurements, and observations is constructed dynamically using the integrated Bayesian network and Markov models. The transition rates of outgoing and incoming links of states in hidden Markov models are used in determining exploit likelihood and impact of attacks, whereas emission rates help quantify the attack states of vulnerabilities. Simulation results show the quantification and evolving risk scores over time for individual and aggregated vulnerabilities of a network.

Prosocial Bystander Behavior in Bullying Dynamics: Assessing the Impact of Social Capital.

PubMed

Evans, Caroline B R; Smokowski, Paul R

2015-12-01

Individuals who observe a bullying event, but are not directly involved as a bully or victim, are referred to as bystanders. Prosocial bystanders are those individuals who actively intervene in bullying dynamics to support the victim and this prosocial behavior often ends the bullying. The current study examines how social capital in the form of social support, community engagement, mental health functioning, and positive school experiences and characteristics is associated with the likelihood of engaging in prosocial bystander behavior in a large sample (N = 5752; 51.03% female) of racially/ethnically diverse rural youth. It was hypothesized that social capital would be associated with an increased likelihood of engaging in prosocial bystander behavior. Following multiple imputation, an ordered logistic regression with robust standard errors was run. The hypothesis was partially supported and results indicated that social capital in the form of friend and teacher support, ethnic identity, religious orientation, and future optimism were significantly associated with an increased likelihood of engaging in prosocial bystander behavior. Contrary to the hypothesis, a decreased rate of self-esteem was significantly associated with an increased likelihood of engaging in prosocial bystander behavior. The findings highlight the importance of positive social relationships and community engagement in increasing prosocial bystander behavior and ultimately decreasing school bullying. Implications were discussed.

Predicting the evolution of complex networks via similarity dynamics

NASA Astrophysics Data System (ADS)

Wu, Tao; Chen, Leiting; Zhong, Linfeng; Xian, Xingping

2017-01-01

Almost all real-world networks are subject to constant evolution, and plenty of them have been investigated empirically to uncover the underlying evolution mechanism. However, the evolution prediction of dynamic networks still remains a challenging problem. The crux of this matter is to estimate the future network links of dynamic networks. This paper studies the evolution prediction of dynamic networks with link prediction paradigm. To estimate the likelihood of the existence of links more accurate, an effective and robust similarity index is presented by exploiting network structure adaptively. Moreover, most of the existing link prediction methods do not make a clear distinction between future links and missing links. In order to predict the future links, the networks are regarded as dynamic systems in this paper, and a similarity updating method, spatial-temporal position drift model, is developed to simulate the evolutionary dynamics of node similarity. Then the updated similarities are used as input information for the future links' likelihood estimation. Extensive experiments on real-world networks suggest that the proposed similarity index performs better than baseline methods and the position drift model performs well for evolution prediction in real-world evolving networks.

Context-specific control and context selection in conflict tasks.

PubMed

Schouppe, Nathalie; Ridderinkhof, K Richard; Verguts, Tom; Notebaert, Wim

2014-02-01

This study investigated whether participants prefer contexts with relatively little cognitive conflict and whether this preference is related to context-specific control. A conflict selection task was administered in which participants had to choose between two categories that contained different levels of conflict. One category was associated with 80% congruent Stroop trials and 20% incongruent Stroop trials, while the other category was associated with only 20% congruent Stroop trials and 80% incongruent Stroop trials. As predicted, participants selected the low-conflict category more frequently, indicating that participants avoid contexts with high-conflict likelihood. Furthermore, we predicted a correlation between this preference for the low-conflict category and the control implementation associated with the categories (i.e., context-specific proportion congruency effect, CSPC effect). Results however did not show such a correlation, thereby failing to support a relationship between context control and context selection. Copyright © 2013 Elsevier B.V. All rights reserved.

The Dark Side of Context: Context Reinstatement Can Distort Memory.

PubMed

Doss, Manoj K; Picart, Jamila K; Gallo, David A

2018-04-01

It is widely assumed that context reinstatement benefits memory, but our experiments revealed that context reinstatement can systematically distort memory. Participants viewed pictures of objects superimposed over scenes, and we later tested their ability to differentiate these old objects from similar new objects. Context reinstatement was manipulated by presenting objects on the reinstated or switched scene at test. Not only did context reinstatement increase correct recognition of old objects, but it also consistently increased incorrect recognition of similar objects as old ones. This false recognition effect was robust, as it was found in several experiments, occurred after both immediate and delayed testing, and persisted with high confidence even after participants were warned to avoid the distorting effects of context. To explain this memory illusion, we propose that context reinstatement increases the likelihood of confusing conceptual and perceptual information, potentially in medial temporal brain regions that integrate this information.

Anticipating cognitive effort: roles of perceived error-likelihood and time demands.

PubMed

Dunn, Timothy L; Inzlicht, Michael; Risko, Evan F

2017-11-13

Why are some actions evaluated as effortful? In the present set of experiments we address this question by examining individuals' perception of effort when faced with a trade-off between two putative cognitive costs: how much time a task takes vs. how error-prone it is. Specifically, we were interested in whether individuals anticipate engaging in a small amount of hard work (i.e., low time requirement, but high error-likelihood) vs. a large amount of easy work (i.e., high time requirement, but low error-likelihood) as being more effortful. In between-subject designs, Experiments 1 through 3 demonstrated that individuals anticipate options that are high in perceived error-likelihood (yet less time consuming) as more effortful than options that are perceived to be more time consuming (yet low in error-likelihood). Further, when asked to evaluate which of the two tasks was (a) more effortful, (b) more error-prone, and (c) more time consuming, effort-based and error-based choices closely tracked one another, but this was not the case for time-based choices. Utilizing a within-subject design, Experiment 4 demonstrated overall similar pattern of judgments as Experiments 1 through 3. However, both judgments of error-likelihood and time demand similarly predicted effort judgments. Results are discussed within the context of extant accounts of cognitive control, with considerations of how error-likelihood and time demands may independently and conjunctively factor into judgments of cognitive effort.

Benefits of biodiverse marine resources to child nutrition in differing developmental contexts in Hispaniola.

PubMed

Temsah, Gheda; Johnson, Kiersten; Evans, Thea; Adams, Diane K

2018-01-01

There is an urgent need for an improved empirical understanding of the relationship among biodiverse marine resources, human health and development outcomes. Coral reefs are often at this intersection for developing nations in the tropics-an ecosystem targeted for biodiversity conservation and one that provides sustenance and livelihoods for many coastal communities. To explore these relationships, we use the comparative development contexts of Haiti and the Dominican Republic on the island of Hispaniola. We combine child nutrition data from the Demographic Health Survey with coastal proximity and coral reef habitat diversity, and condition to empirically test human benefits of marine natural resources in differing development contexts. Our results indicate that coastal children have a reduced likelihood of severe stunting in Haiti but have increased likelihoods of stunting and reduced dietary diversity in the Dominican Republic. These contrasting results are likely due to the differential in developed infrastructure and market access. Our analyses did not demonstrate an association between more diverse and less degraded coral reefs and better childhood nutrition. The results highlight the complexities of modelling interactions between the health of humans and natural systems, and indicate the next steps needed to support integrated development programming.

Benefits of biodiverse marine resources to child nutrition in differing developmental contexts in Hispaniola

PubMed Central

Temsah, Gheda; Johnson, Kiersten; Evans, Thea

2018-01-01

There is an urgent need for an improved empirical understanding of the relationship among biodiverse marine resources, human health and development outcomes. Coral reefs are often at this intersection for developing nations in the tropics—an ecosystem targeted for biodiversity conservation and one that provides sustenance and livelihoods for many coastal communities. To explore these relationships, we use the comparative development contexts of Haiti and the Dominican Republic on the island of Hispaniola. We combine child nutrition data from the Demographic Health Survey with coastal proximity and coral reef habitat diversity, and condition to empirically test human benefits of marine natural resources in differing development contexts. Our results indicate that coastal children have a reduced likelihood of severe stunting in Haiti but have increased likelihoods of stunting and reduced dietary diversity in the Dominican Republic. These contrasting results are likely due to the differential in developed infrastructure and market access. Our analyses did not demonstrate an association between more diverse and less degraded coral reefs and better childhood nutrition. The results highlight the complexities of modelling interactions between the health of humans and natural systems, and indicate the next steps needed to support integrated development programming. PMID:29795591

A preliminary evaluation of the generalized likelihood ratio for detecting and identifying control element failures in a transport aircraft

NASA Technical Reports Server (NTRS)

Bundick, W. T.

1985-01-01

The application of the Generalized Likelihood Ratio technique to the detection and identification of aircraft control element failures has been evaluated in a linear digital simulation of the longitudinal dynamics of a B-737 aircraft. Simulation results show that the technique has potential but that the effects of wind turbulence and Kalman filter model errors are problems which must be overcome.

Dynamic Histogram Analysis To Determine Free Energies and Rates from Biased Simulations.

PubMed

Stelzl, Lukas S; Kells, Adam; Rosta, Edina; Hummer, Gerhard

2017-12-12

We present an algorithm to calculate free energies and rates from molecular simulations on biased potential energy surfaces. As input, it uses the accumulated times spent in each state or bin of a histogram and counts of transitions between them. Optimal unbiased equilibrium free energies for each of the states/bins are then obtained by maximizing the likelihood of a master equation (i.e., first-order kinetic rate model). The resulting free energies also determine the optimal rate coefficients for transitions between the states or bins on the biased potentials. Unbiased rates can be estimated, e.g., by imposing a linear free energy condition in the likelihood maximization. The resulting "dynamic histogram analysis method extended to detailed balance" (DHAMed) builds on the DHAM method. It is also closely related to the transition-based reweighting analysis method (TRAM) and the discrete TRAM (dTRAM). However, in the continuous-time formulation of DHAMed, the detailed balance constraints are more easily accounted for, resulting in compact expressions amenable to efficient numerical treatment. DHAMed produces accurate free energies in cases where the common weighted-histogram analysis method (WHAM) for umbrella sampling fails because of slow dynamics within the windows. Even in the limit of completely uncorrelated data, where WHAM is optimal in the maximum-likelihood sense, DHAMed results are nearly indistinguishable. We illustrate DHAMed with applications to ion channel conduction, RNA duplex formation, α-helix folding, and rate calculations from accelerated molecular dynamics. DHAMed can also be used to construct Markov state models from biased or replica-exchange molecular dynamics simulations. By using binless WHAM formulated as a numerical minimization problem, the bias factors for the individual states can be determined efficiently in a preprocessing step and, if needed, optimized globally afterward.

Competition between learned reward and error outcome predictions in anterior cingulate cortex.

PubMed

Alexander, William H; Brown, Joshua W

2010-02-15

The anterior cingulate cortex (ACC) is implicated in performance monitoring and cognitive control. Non-human primate studies of ACC show prominent reward signals, but these are elusive in human studies, which instead show mainly conflict and error effects. Here we demonstrate distinct appetitive and aversive activity in human ACC. The error likelihood hypothesis suggests that ACC activity increases in proportion to the likelihood of an error, and ACC is also sensitive to the consequence magnitude of the predicted error. Previous work further showed that error likelihood effects reach a ceiling as the potential consequences of an error increase, possibly due to reductions in the average reward. We explored this issue by independently manipulating reward magnitude of task responses and error likelihood while controlling for potential error consequences in an Incentive Change Signal Task. The fMRI results ruled out a modulatory effect of expected reward on error likelihood effects in favor of a competition effect between expected reward and error likelihood. Dynamic causal modeling showed that error likelihood and expected reward signals are intrinsic to the ACC rather than received from elsewhere. These findings agree with interpretations of ACC activity as signaling both perceptions of risk and predicted reward. Copyright 2009 Elsevier Inc. All rights reserved.

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.

Revision of an automated microseismic location algorithm for DAS - 3C geophone hybrid array

NASA Astrophysics Data System (ADS)

Mizuno, T.; LeCalvez, J.; Raymer, D.

2017-12-01

Application of distributed acoustic sensing (DAS) has been studied in several areas in seismology. One of the areas is microseismic reservoir monitoring (e.g., Molteni et al., 2017, First Break). Considering the present limitations of DAS, which include relatively low signal-to-noise ratio (SNR) and no 3C polarization measurements, a DAS - 3C geophone hybrid array is a practical option when using a single monitoring well. Considering the large volume of data from distributed sensing, microseismic event detection and location using a source scanning type algorithm is a reasonable choice, especially for real-time monitoring. The algorithm must handle both strain rate along the borehole axis for DAS and particle velocity for 3C geophones. Only a small quantity of large SNR events will be detected throughout a large aperture encompassing the hybrid array; therefore, the aperture is to be optimized dynamically to eliminate noisy channels for a majority of events. For such hybrid array, coalescence microseismic mapping (CMM) (Drew et al., 2005, SPE) was revised. CMM forms a likelihood function of location of event and its origin time. At each receiver, a time function of event arrival likelihood is inferred using an SNR function, and it is migrated to time and space to determine hypocenter and origin time likelihood. This algorithm was revised to dynamically optimize such a hybrid array by identifying receivers where a microseismic signal is possibly detected and using only those receivers to compute the likelihood function. Currently, peak SNR is used to select receivers. To prevent false results due to small aperture, a minimum aperture threshold is employed. The algorithm refines location likelihood using 3C geophone polarization. We tested this algorithm using a ray-based synthetic dataset. Leaney (2014, PhD thesis, UBC) is used to compute particle velocity at receivers. Strain rate along the borehole axis is computed from particle velocity as DAS microseismic synthetic data. The likelihood function formed by both DAS and geophone behaves as expected with the aperture dynamically selected depending on the SNR of the event. We conclude that this algorithm can be successfully applied for such hybrid arrays to monitor microseismic activity. A study using a recently acquired dataset is planned.

Utilizing Molecular Dynamics ' Multipotent Methodologies to Measure Microscopic Motions of DNA Molecules: A Magniloquent Manuscript On DNA's Means and Mannerisms

NASA Astrophysics Data System (ADS)

Kingsland, Addie

DNA is an amazing molecule which is the basic template for all genetics. It is the primary molecule for storing biological information, and has many applications in nanotechnology. Double-stranded DNA may contain mismatched base pairs beyond the Watson-Crick pairs guanine-cytosine and adenine-thymine. To date, no one has found a physical property of base pair mismatches which describes the behavior of naturally occurring mismatch repair enzymes. Many materials properties of DNA are also unknown, for instance, when pulling DNA in different configurations, different energy differences are observed with no obvious reason why. DNA mismatches also affect their local environment, for instance changing the quantum yield of nearby azobenzene moieties. We utilize molecular dynamics computer simulations to study the structure and dynamics for both matched and mismatched base pairs, within both biological and materials contexts, and in both equilibrium and biased dynamics. We show that mismatched pairs shift further in the plane normal to the DNA strand and are more likely to exhibit non-canonical structures, including the e-motif. Base pair mismatches alter their local environment, affecting the trans- to cis- photoisomerization quantum yield of azobenzene, as well as increasing the likelihood of observing the e-motif. We also show that by using simulated data, we can give new insights on theoretical models to calculate the energetics of pulling DNA strands apart. These results, all relatively inexpensive on modern computer hardware, can help guide the design of DNA-based nanotechnologies, as well as give new insights into the functioning of mismatch repair systems in cancer prevention.

Factors associated with aggressive behavior between residents and staff in nursing homes.

PubMed

Stutte, Karin; Hahn, Sabine; Fierz, Katharina; Zúñiga, Franziska

The aim of this secondary data analysis of the cross-sectional Swiss Nursing Homes Human Resources Project (SHURP) study was to describe the prevalence of residents' verbal, physical and sexual aggression toward care workers in Swiss nursing homes and to explore their association with context and care worker factors. The study's sample incorporated data from 155 randomly selected nursing homes, including 402 units. Among care workers (n = 3919), 66% reported experiencing verbal, 42% physical and 15% sexual aggression. Logistic regression analyses indicated that non-special care units and care workers' higher perception of staffing and resources adequacy and higher age were associated with a decreased likelihood of aggression, whereas emotional exhaustion was associated with an increased likelihood. Our results suggest an association of aggressive resident behavior with modifiable context and care worker factors. Knowledge about this may contribute to a continuous improvement process, enhancing residents' well-being alongside care workers' safety and satisfaction. Copyright © 2017 Elsevier Inc. All rights reserved.

INCORPORATING ROUTINE ACTIVITIES, ACTIVITY SPACES, AND SITUATIONAL DEFINITIONS INTO THE SOCIAL SCHEMATIC THEORY OF CRIME.

PubMed

Simons, Ronald L; Burt, Callie H; Barr, Ashley B; Lei, Man-Kit; Stewart, Eric

2014-11-01

Simons and Burt's (2011) social schematic theory (SST) of crime posits that adverse social factors are associated with offending because they promote a set of social schemas (i.e., a criminogenic knowledge structure) that elevates the probability of situational definitions favorable to crime. This study extends the SST model by incorporating the role of contexts for action. Furthermore, the study advances tests of the SST by incorporating a measure of criminogenic situational definitions to assess whether such definitions mediate the effects of schemas and contexts on crime. Structural equation models using 10 years of panel data from 582 African American youth provided strong support for the expanded theory. The results suggest that childhood and adolescent social adversity fosters a criminogenic knowledge structure as well as selection into criminogenic activity spaces and risky activities, all of which increase the likelihood of offending largely through situational definitions. Additionally, evidence shows that the criminogenic knowledge structure interacts with settings to amplify the likelihood of situational definitions favorable to crime.

Robust analysis of semiparametric renewal process models

PubMed Central

Lin, Feng-Chang; Truong, Young K.; Fine, Jason P.

2013-01-01

Summary A rate model is proposed for a modulated renewal process comprising a single long sequence, where the covariate process may not capture the dependencies in the sequence as in standard intensity models. We consider partial likelihood-based inferences under a semiparametric multiplicative rate model, which has been widely studied in the context of independent and identical data. Under an intensity model, gap times in a single long sequence may be used naively in the partial likelihood with variance estimation utilizing the observed information matrix. Under a rate model, the gap times cannot be treated as independent and studying the partial likelihood is much more challenging. We employ a mixing condition in the application of limit theory for stationary sequences to obtain consistency and asymptotic normality. The estimator's variance is quite complicated owing to the unknown gap times dependence structure. We adapt block bootstrapping and cluster variance estimators to the partial likelihood. Simulation studies and an analysis of a semiparametric extension of a popular model for neural spike train data demonstrate the practical utility of the rate approach in comparison with the intensity approach. PMID:24550568

A comprehensive Network Security Risk Model for process control networks.

PubMed

Henry, Matthew H; Haimes, Yacov Y

2009-02-01

The risk of cyber attacks on process control networks (PCN) is receiving significant attention due to the potentially catastrophic extent to which PCN failures can damage the infrastructures and commodity flows that they support. Risk management addresses the coupled problems of (1) reducing the likelihood that cyber attacks would succeed in disrupting PCN operation and (2) reducing the severity of consequences in the event of PCN failure or manipulation. The Network Security Risk Model (NSRM) developed in this article provides a means of evaluating the efficacy of candidate risk management policies by modeling the baseline risk and assessing expectations of risk after the implementation of candidate measures. Where existing risk models fall short of providing adequate insight into the efficacy of candidate risk management policies due to shortcomings in their structure or formulation, the NSRM provides model structure and an associated modeling methodology that captures the relevant dynamics of cyber attacks on PCN for risk analysis. This article develops the NSRM in detail in the context of an illustrative example.

System impairment compensation in coherent optical communications by using a bio-inspired detector based on artificial neural network and genetic algorithm

NASA Astrophysics Data System (ADS)

Wang, Danshi; Zhang, Min; Li, Ze; Song, Chuang; Fu, Meixia; Li, Jin; Chen, Xue

2017-09-01

A bio-inspired detector based on the artificial neural network (ANN) and genetic algorithm is proposed in the context of a coherent optical transmission system. The ANN is designed to mitigate 16-quadrature amplitude modulation system impairments, including linear impairment: Gaussian white noise, laser phase noise, in-phase/quadrature component imbalance, and nonlinear impairment: nonlinear phase. Without prior information or heuristic assumptions, the ANN, functioning as a machine learning algorithm, can learn and capture the characteristics of impairments from observed data. Numerical simulations were performed, and dispersion-shifted, dispersion-managed, and dispersion-unmanaged fiber links were investigated. The launch power dynamic range and maximum transmission distance for the bio-inspired method were 2.7 dBm and 240 km greater, respectively, than those of the maximum likelihood estimation algorithm. Moreover, the linewidth tolerance of the bio-inspired technique was 170 kHz greater than that of the k-means method, demonstrating its usability for digital signal processing in coherent systems.

Mass media, stigma, and disclosure of HIV test results: multilevel analysis in the Eastern Cape, South Africa.

PubMed

Hutchinson, P L; Mahlalela, X; Yukich, Josh

2007-12-01

In this article, we examine the role of mass media and interpersonal communication in affecting knowledge of HIV/AIDS, reducing stigma, using condoms, and increasing the likelihood of disclosing HIV test results to sexual partners and family members. Data from a 2002 household survey in the Eastern Cape Province of South Africa are used to measure levels of stigma, interpersonal communication, willingness to disclosure HIV test results and condom use. We use a multilevel framework that accounts for the social context in which individuals access information, gauge social norms, and make decisions about the costs and benefits of HIV testing and disclosure. The results provide support for the positive effects of both media exposure and informal social networks on ideational factors, namely changes in knowledge and stigma, which lead to behavior change. Consistent with common models of health communication dynamics, these latter factors dominate decisions regarding disclosure of HIV test results and condom use.

Changing drug users' risk environments: peer health advocates as multi-level community change agents.

PubMed

Weeks, Margaret R; Convey, Mark; Dickson-Gomez, Julia; Li, Jianghong; Radda, Kim; Martinez, Maria; Robles, Eduardo

2009-06-01

Peer delivered, social oriented HIV prevention intervention designs are increasingly popular for addressing broader contexts of health risk beyond a focus on individual factors. Such interventions have the potential to affect multiple social levels of risk and change, including at the individual, network, and community levels, and reflect social ecological principles of interaction across social levels over time. The iterative and feedback dynamic generated by this multi-level effect increases the likelihood for sustained health improvement initiated by those trained to deliver the peer intervention. The Risk Avoidance Partnership (RAP), conducted with heroin and cocaine/crack users in Hartford, Connecticut, exemplified this intervention design and illustrated the multi-level effect on drug users' risk and harm reduction at the individual level, the social network level, and the larger community level. Implications of the RAP program for designing effective prevention programs and for analyzing long-term change to reduce HIV transmission among high-risk groups are discussed from this ecological and multi-level intervention perspective.

Climate change and ocean deoxygenation within intensified surface-driven upwelling circulations.

PubMed

Bakun, Andrew

2017-09-13

Ocean deoxygenation often takes place in proximity to zones of intense upwelling. Associated concerns about amplified ocean deoxygenation arise from an arguable likelihood that coastal upwelling systems in the world's oceans may further intensify as anthropogenic climate change proceeds. Comparative examples discussed include the uniquely intense seasonal Somali Current upwelling, the massive upwelling that occurs quasi-continuously off Namibia and the recently appearing and now annually recurring 'dead zone' off the US State of Oregon. The evident 'transience' in causal dynamics off Oregon is somewhat mirrored in an interannual-scale intermittence in eruptions of anaerobically formed noxious gases off Namibia. A mechanistic scheme draws the three examples towards a common context in which, in addition to the obvious but politically problematic remedy of actually reducing 'greenhouse' gas emissions, the potentially manageable abundance of strongly swimming, finely gill raker-meshed small pelagic fish emerges as a plausible regulating factor.This article is part of the themed issue 'Ocean ventilation and deoxygenation in a warming world'. © 2017 The Author(s).

Social Contagion, Adolescent Sexual Behavior, and Pregnancy: A Nonlinear Dynamic EMOSA Model.

ERIC Educational Resources Information Center

Rodgers, Joseph Lee; Rowe, David C.; Buster, Maury

1998-01-01

Expands an existing nonlinear dynamic epidemic model of onset of social activities (EMOSA), motivated by social contagion theory, to quantify the likelihood of pregnancy for adolescent girls of different sexuality statuses. Compares five sexuality/pregnancy models to explain variance in national prevalence curves. Finds that adolescent girls have…

Comparisons of Four Methods for Estimating a Dynamic Factor Model

ERIC Educational Resources Information Center

Zhang, Zhiyong; Hamaker, Ellen L.; Nesselroade, John R.

2008-01-01

Four methods for estimating a dynamic factor model, the direct autoregressive factor score (DAFS) model, are evaluated and compared. The first method estimates the DAFS model using a Kalman filter algorithm based on its state space model representation. The second one employs the maximum likelihood estimation method based on the construction of a…

Implementing a Bayes Filter in a Neural Circuit: The Case of Unknown Stimulus Dynamics.

PubMed

Sokoloski, Sacha

2017-09-01

In order to interact intelligently with objects in the world, animals must first transform neural population responses into estimates of the dynamic, unknown stimuli that caused them. The Bayesian solution to this problem is known as a Bayes filter, which applies Bayes' rule to combine population responses with the predictions of an internal model. The internal model of the Bayes filter is based on the true stimulus dynamics, and in this note, we present a method for training a theoretical neural circuit to approximately implement a Bayes filter when the stimulus dynamics are unknown. To do this we use the inferential properties of linear probabilistic population codes to compute Bayes' rule and train a neural network to compute approximate predictions by the method of maximum likelihood. In particular, we perform stochastic gradient descent on the negative log-likelihood of the neural network parameters with a novel approximation of the gradient. We demonstrate our methods on a finite-state, a linear, and a nonlinear filtering problem and show how the hidden layer of the neural network develops tuning curves consistent with findings in experimental neuroscience.

An analytic modeling and system identification study of rotor/fuselage dynamics at hover

NASA Technical Reports Server (NTRS)

Hong, Steven W.; Curtiss, H. C., Jr.

1993-01-01

A combination of analytic modeling and system identification methods have been used to develop an improved dynamic model describing the response of articulated rotor helicopters to control inputs. A high-order linearized model of coupled rotor/body dynamics including flap and lag degrees of freedom and inflow dynamics with literal coefficients is compared to flight test data from single rotor helicopters in the near hover trim condition. The identification problem was formulated using the maximum likelihood function in the time domain. The dynamic model with literal coefficients was used to generate the model states, and the model was parametrized in terms of physical constants of the aircraft rather than the stability derivatives resulting in a significant reduction in the number of quantities to be identified. The likelihood function was optimized using the genetic algorithm approach. This method proved highly effective in producing an estimated model from flight test data which included coupled fuselage/rotor dynamics. Using this approach it has been shown that blade flexibility is a significant contributing factor to the discrepancies between theory and experiment shown in previous studies. Addition of flexible modes, properly incorporating the constraint due to the lag dampers, results in excellent agreement between flight test and theory, especially in the high frequency range.

An analytic modeling and system identification study of rotor/fuselage dynamics at hover

NASA Technical Reports Server (NTRS)

Hong, Steven W.; Curtiss, H. C., Jr.

1993-01-01

A combination of analytic modeling and system identification methods have been used to develop an improved dynamic model describing the response of articulated rotor helicopters to control inputs. A high-order linearized model of coupled rotor/body dynamics including flap and lag degrees of freedom and inflow dynamics with literal coefficients is compared to flight test data from single rotor helicopters in the near hover trim condition. The identification problem was formulated using the maximum likelihood function in the time domain. The dynamic model with literal coefficients was used to generate the model states, and the model was parametrized in terms of physical constants of the aircraft rather than the stability derivatives, resulting in a significant reduction in the number of quantities to be identified. The likelihood function was optimized using the genetic algorithm approach. This method proved highly effective in producing an estimated model from flight test data which included coupled fuselage/rotor dynamics. Using this approach it has been shown that blade flexibility is a significant contributing factor to the discrepancies between theory and experiment shown in previous studies. Addition of flexible modes, properly incorporating the constraint due to the lag dampers, results in excellent agreement between flight test and theory, especially in the high frequency range.

Assessing the Role of Context on the Relationship Between Adolescent Marijuana Use and Property Crimes in Mexico.

PubMed

Vilalta, Carlos Javier; Allmang, Skye

2017-01-28

A limited amount of research has been conducted on the association between marijuana use and adolescent crime in developing countries such as Mexico, where crime rates are high and marijuana use is increasing. To examine the association between the frequency of marijuana use and the likelihood of committing of a property crime, and to identify contextual factors explaining individual differences in the likelihood of committing a property crime. The contribution of marijuana use to property crimes was examined based on two nationwide probabilistic surveys of public high school students, using a multilevel mixed effects logistic regression model. Marijuana use significantly increased the odds of committing a property crime. Differences between schools were observed in the random effects of marijuana use, suggesting that the likelihood of committing a property crime was differentially affected by contextual factors. In addition, students who were victims of bullying by peers and who had parents that abused alcohol had higher odds of committing a property crime. Perceived disorder in students' schools and neighborhoods also increased students' odds of reporting that they had committed a property crime. The importance of the effect of school context on the relationship between marijuana use and the commission of a property crime among Mexican public high school students seemed to increase over time. However, these results may also be due to changes in sampling designs over time.

Validation of DNA-based identification software by computation of pedigree likelihood ratios.

PubMed

Slooten, K

2011-08-01

Disaster victim identification (DVI) can be aided by DNA-evidence, by comparing the DNA-profiles of unidentified individuals with those of surviving relatives. The DNA-evidence is used optimally when such a comparison is done by calculating the appropriate likelihood ratios. Though conceptually simple, the calculations can be quite involved, especially with large pedigrees, precise mutation models etc. In this article we describe a series of test cases designed to check if software designed to calculate such likelihood ratios computes them correctly. The cases include both simple and more complicated pedigrees, among which inbred ones. We show how to calculate the likelihood ratio numerically and algebraically, including a general mutation model and possibility of allelic dropout. In Appendix A we show how to derive such algebraic expressions mathematically. We have set up these cases to validate new software, called Bonaparte, which performs pedigree likelihood ratio calculations in a DVI context. Bonaparte has been developed by SNN Nijmegen (The Netherlands) for the Netherlands Forensic Institute (NFI). It is available free of charge for non-commercial purposes (see www.dnadvi.nl for details). Commercial licenses can also be obtained. The software uses Bayesian networks and the junction tree algorithm to perform its calculations. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Ego involvement increases doping likelihood.

PubMed

Ring, Christopher; Kavussanu, Maria

2018-08-01

Achievement goal theory provides a framework to help understand how individuals behave in achievement contexts, such as sport. Evidence concerning the role of motivation in the decision to use banned performance enhancing substances (i.e., doping) is equivocal on this issue. The extant literature shows that dispositional goal orientation has been weakly and inconsistently associated with doping intention and use. It is possible that goal involvement, which describes the situational motivational state, is a stronger determinant of doping intention. Accordingly, the current study used an experimental design to examine the effects of goal involvement, manipulated using direct instructions and reflective writing, on doping likelihood in hypothetical situations in college athletes. The ego-involving goal increased doping likelihood compared to no goal and a task-involving goal. The present findings provide the first evidence that ego involvement can sway the decision to use doping to improve athletic performance.

Integrating in silico prediction methods, molecular docking, and molecular dynamics simulation to predict the impact of ALK missense mutations in structural perspective.

PubMed

Doss, C George Priya; Chakraborty, Chiranjib; Chen, Luonan; Zhu, Hailong

2014-01-01

Over the past decade, advancements in next generation sequencing technology have placed personalized genomic medicine upon horizon. Understanding the likelihood of disease causing mutations in complex diseases as pathogenic or neutral remains as a major task and even impossible in the structural context because of its time consuming and expensive experiments. Among the various diseases causing mutations, single nucleotide polymorphisms (SNPs) play a vital role in defining individual's susceptibility to disease and drug response. Understanding the genotype-phenotype relationship through SNPs is the first and most important step in drug research and development. Detailed understanding of the effect of SNPs on patient drug response is a key factor in the establishment of personalized medicine. In this paper, we represent a computational pipeline in anaplastic lymphoma kinase (ALK) for SNP-centred study by the application of in silico prediction methods, molecular docking, and molecular dynamics simulation approaches. Combination of computational methods provides a way in understanding the impact of deleterious mutations in altering the protein drug targets and eventually leading to variable patient's drug response. We hope this rapid and cost effective pipeline will also serve as a bridge to connect the clinicians and in silico resources in tailoring treatments to the patients' specific genotype.

Nested Sampling for Bayesian Model Comparison in the Context of Salmonella Disease Dynamics

PubMed Central

Dybowski, Richard; McKinley, Trevelyan J.; Mastroeni, Pietro; Restif, Olivier

2013-01-01

Understanding the mechanisms underlying the observed dynamics of complex biological systems requires the statistical assessment and comparison of multiple alternative models. Although this has traditionally been done using maximum likelihood-based methods such as Akaike's Information Criterion (AIC), Bayesian methods have gained in popularity because they provide more informative output in the form of posterior probability distributions. However, comparison between multiple models in a Bayesian framework is made difficult by the computational cost of numerical integration over large parameter spaces. A new, efficient method for the computation of posterior probabilities has recently been proposed and applied to complex problems from the physical sciences. Here we demonstrate how nested sampling can be used for inference and model comparison in biological sciences. We present a reanalysis of data from experimental infection of mice with Salmonella enterica showing the distribution of bacteria in liver cells. In addition to confirming the main finding of the original analysis, which relied on AIC, our approach provides: (a) integration across the parameter space, (b) estimation of the posterior parameter distributions (with visualisations of parameter correlations), and (c) estimation of the posterior predictive distributions for goodness-of-fit assessments of the models. The goodness-of-fit results suggest that alternative mechanistic models and a relaxation of the quasi-stationary assumption should be considered. PMID:24376528

Changing the Sexual Aggression-Supportive Attitudes of Men: A Psychoeducational Intervention.

ERIC Educational Resources Information Center

Gilbert, Barbara J.; And Others

1991-01-01

Assessed psychoeducational intervention designed to change attitudes of men found to be associated with sexual aggression toward women. College men receiving elaboration likelihood model-based intervention showed significantly more attitude change than did control group. One month later, in unrelated naturalistic context, intervention subjects…

Inferring the parameters of a Markov process from snapshots of the steady state

NASA Astrophysics Data System (ADS)

Dettmer, Simon L.; Berg, Johannes

2018-02-01

We seek to infer the parameters of an ergodic Markov process from samples taken independently from the steady state. Our focus is on non-equilibrium processes, where the steady state is not described by the Boltzmann measure, but is generally unknown and hard to compute, which prevents the application of established equilibrium inference methods. We propose a quantity we call propagator likelihood, which takes on the role of the likelihood in equilibrium processes. This propagator likelihood is based on fictitious transitions between those configurations of the system which occur in the samples. The propagator likelihood can be derived by minimising the relative entropy between the empirical distribution and a distribution generated by propagating the empirical distribution forward in time. Maximising the propagator likelihood leads to an efficient reconstruction of the parameters of the underlying model in different systems, both with discrete configurations and with continuous configurations. We apply the method to non-equilibrium models from statistical physics and theoretical biology, including the asymmetric simple exclusion process (ASEP), the kinetic Ising model, and replicator dynamics.

Species survival and scaling laws in hostile and disordered environments

NASA Astrophysics Data System (ADS)

Rocha, Rodrigo P.; Figueiredo, Wagner; Suweis, Samir; Maritan, Amos

2016-10-01

In this work we study the likelihood of survival of single-species in the context of hostile and disordered environments. Population dynamics in this environment, as modeled by the Fisher equation, is characterized by negative average growth rate, except in some random spatially distributed patches that may support life. In particular, we are interested in the phase diagram of the survival probability and in the critical size problem, i.e., the minimum patch size required for surviving in the long-time dynamics. We propose a measure for the critical patch size as being proportional to the participation ratio of the eigenvector corresponding to the largest eigenvalue of the linearized Fisher dynamics. We obtain the (extinction-survival) phase diagram and the probability distribution function (PDF) of the critical patch sizes for two topologies, namely, the one-dimensional system and the fractal Peano basin. We show that both topologies share the same qualitative features, but the fractal topology requires higher spatial fluctuations to guarantee species survival. We perform a finite-size scaling and we obtain the associated scaling exponents. In addition, we show that the PDF of the critical patch sizes has an universal shape for the 1D case in terms of the model parameters (diffusion, growth rate, etc.). In contrast, the diffusion coefficient has a drastic effect on the PDF of the critical patch sizes of the fractal Peano basin, and it does not obey the same scaling law of the 1D case.

Failure dynamics of the global risk network.

PubMed

Szymanski, Boleslaw K; Lin, Xin; Asztalos, Andrea; Sreenivasan, Sameet

2015-06-18

Risks threatening modern societies form an intricately interconnected network that often underlies crisis situations. Yet, little is known about how risk materializations in distinct domains influence each other. Here we present an approach in which expert assessments of likelihoods and influence of risks underlie a quantitative model of the global risk network dynamics. The modeled risks range from environmental to economic and technological, and include difficult to quantify risks, such as geo-political and social. Using the maximum likelihood estimation, we find the optimal model parameters and demonstrate that the model including network effects significantly outperforms the others, uncovering full value of the expert collected data. We analyze the model dynamics and study its resilience and stability. Our findings include such risk properties as contagion potential, persistence, roles in cascades of failures and the identity of risks most detrimental to system stability. The model provides quantitative means for measuring the adverse effects of risk interdependencies and the materialization of risks in the network.

Using Emotion as Information in Future-Oriented Cognition: Individual Differences in the Context of State Negative Affect

PubMed Central

Marroquín, Brett; Boyle, Chloe C.; Nolen-Hoeksema, Susan; Stanton, Annette L.

2016-01-01

Predictions about the future are susceptible to mood-congruent influences of emotional state. However, recent work suggests individuals also differ in the degree to which they incorporate emotion into cognition. This study examined the role of such individual differences in the context of state negative emotion. We examined whether trait tendencies to use negative or positive emotion as information affect individuals' predictions of what will happen in the future (likelihood estimation) and how events will feel (affective forecasting), and whether trait influences depend on emotional state. Participants (N=119) reported on tendencies to use emotion as information (“following feelings”), underwent an emotion induction (negative versus neutral), and made likelihood estimates and affective forecasts for future events. Views of the future were predicted by both emotional state and individual differences in following feelings. Whereas following negative feelings affected most future-oriented cognition across emotional states, following positive feelings specifically buffered individuals' views of the future in the negative emotion condition, and specifically for positive future events, a category of future-event prediction especially important in psychological health. Individual differences may confer predisposition toward optimistic or pessimistic expectations of the future in the context of acute negative emotion, with implications for adaptive and maladaptive functioning. PMID:27041783

Detection of abrupt changes in dynamic systems

NASA Technical Reports Server (NTRS)

Willsky, A. S.

1984-01-01

Some of the basic ideas associated with the detection of abrupt changes in dynamic systems are presented. Multiple filter-based techniques and residual-based method and the multiple model and generalized likelihood ratio methods are considered. Issues such as the effect of unknown onset time on algorithm complexity and structure and robustness to model uncertainty are discussed.

A single-rate context-dependent learning process underlies rapid adaptation to familiar object dynamics.

PubMed

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.

Communication and Persuasion: Factors Influencing a Patient's Behavior.

ERIC Educational Resources Information Center

Logan, Henrietta L.

1991-01-01

Three elements of persuasion (source, message, and audience) are discussed, and a paradigm for persuasion, the Elaboration Likelihood Model, which unifies many existing attitude theories, is described. Selected concepts and research on attitudes and persuasion are also examined as a context for teaching preventive behaviors and strategies in…

Context-Dependent Control over Attentional Capture

ERIC Educational Resources Information Center

Cosman, Joshua D.; Vecera, Shaun P.

2013-01-01

A number of studies have demonstrated that the likelihood of a salient item capturing attention is dependent on the "attentional set" an individual employs in a given situation. The instantiation of an attentional set is often viewed as a strategic, voluntary process, relying on working memory systems that represent immediate task…

A Distributed Leadership Change Process Model for Higher Education

ERIC Educational Resources Information Center

Jones, Sandra; Harvey, Marina

2017-01-01

The higher education sector operates in an increasingly complex global environment that is placing it under considerable stress and resulting in widespread change to the operating context and leadership of higher education institutions. The outcome has been the increased likelihood of conflict between academics and senior leaders, presaging the…

Data Mining and Knowledge Management in Higher Education -Potential Applications.

ERIC Educational Resources Information Center

Luan, Jing

This paper introduces a new decision support tool, data mining, in the context of knowledge management. The most striking features of data mining techniques are clustering and prediction. The clustering aspect of data mining offers comprehensive characteristics analysis of students, while the predicting function estimates the likelihood for a…

Establishing Factor Validity Using Variable Reduction in Confirmatory Factor Analysis.

ERIC Educational Resources Information Center

Hofmann, Rich

1995-01-01

Using a 21-statement attitude-type instrument, an iterative procedure for improving confirmatory model fit is demonstrated within the context of the EQS program of P. M. Bentler and maximum likelihood factor analysis. Each iteration systematically eliminates the poorest fitting statement as identified by a variable fit index. (SLD)

Silence That Can Be Dangerous: A Vignette Study to Assess Healthcare Professionals’ Likelihood of Speaking up about Safety Concerns

PubMed Central

Schwappach, David L. B.; Gehring, Katrin

2014-01-01

Purpose To investigate the likelihood of speaking up about patient safety in oncology and to clarify the effect of clinical and situational context factors on the likelihood of voicing concerns. Patients and Methods 1013 nurses and doctors in oncology rated four clinical vignettes describing coworkers’ errors and rule violations in a self-administered factorial survey (65% response rate). Multiple regression analysis was used to model the likelihood of speaking up as outcome of vignette attributes, responder’s evaluations of the situation and personal characteristics. Results Respondents reported a high likelihood of speaking up about patient safety but the variation between and within types of errors and rule violations was substantial. Staff without managerial function provided significantly higher levels of decision difficulty and discomfort to speak up. Based on the information presented in the vignettes, 74%−96% would speak up towards a supervisor failing to check a prescription, 45%−81% would point a coworker to a missed hand disinfection, 82%−94% would speak up towards nurses who violate a safety rule in medication preparation, and 59%−92% would question a doctor violating a safety rule in lumbar puncture. Several vignette attributes predicted the likelihood of speaking up. Perceived potential harm, anticipated discomfort, and decision difficulty were significant predictors of the likelihood of speaking up. Conclusions Clinicians’ willingness to speak up about patient safety is considerably affected by contextual factors. Physicians and nurses without managerial function report substantial discomfort with speaking up. Oncology departments should provide staff with clear guidance and trainings on when and how to voice safety concerns. PMID:25116338

Structural effect of size on interracial friendship

PubMed Central

Cheng, Siwei; Xie, Yu

2013-01-01

Social contexts exert structural effects on individuals’ social relationships, including interracial friendships. In this study, we posit that, net of group composition, total context size has a distinct effect on interracial friendship. Under the assumptions of (i) maximization of preference in choosing a friend, (ii) multidimensionality of preference, and (iii) preference for same-race friends, we conducted analyses using microsimulation that yielded three main findings. First, increased context size decreases the likelihood of forming an interracial friendship. Second, the size effect increases with the number of preference dimensions. Third, the size effect is diluted by noise, i.e., the random component affecting friendship formation. Analysis of actual friendship data among 4,745 American high school students yielded results consistent with the main conclusion that increased context size promotes racial segregation and discourages interracial friendship. PMID:23589848

Expectation of an upcoming large postural perturbation influences the recovery stepping response and outcome.

PubMed

Pater, Mackenzie L; Rosenblatt, Noah J; Grabiner, Mark D

2015-01-01

Tripping during locomotion, the leading cause of falls in older adults, generally occurs without prior warning and often while performing a secondary task. Prior warning can alter the state of physiological preparedness and beneficially influence the response to the perturbation. Previous studies have examined how altering the initial "preparedness" for an upcoming perturbation can affect kinematic responses following small disturbances that did not require a stepping response to restore dynamic stability. The purpose of this study was to examine how expectation affected fall outcome and recovery response kinematics following a large, treadmill-delivered perturbation simulating a trip and requiring at least one recovery step to avoid a fall. Following the perturbation, 47% of subjects fell when they were not expecting the perturbation whereas 12% fell when they were aware that the perturbation would occur "sometime in the next minute". The between-group differences were accompanied by slower reaction times in the non-expecting group (p < 0.01). Slower reaction times were associated with kinematics that have previously been shown to increase the likelihood of falling following a laboratory-induced trip. The results demonstrate the importance of considering the context under which recovery responses are assessed, and further, gives insight to the context during which task-specific perturbation training is administered. Copyright © 2014 Elsevier B.V. All rights reserved.

The simple rules of social contagion.

PubMed

Hodas, Nathan O; Lerman, Kristina

2014-03-11

It is commonly believed that information spreads between individuals like a pathogen, with each exposure by an informed friend potentially resulting in a naive individual becoming infected. However, empirical studies of social media suggest that individual response to repeated exposure to information is far more complex. As a proxy for intervention experiments, we compare user responses to multiple exposures on two different social media sites, Twitter and Digg. We show that the position of exposing messages on the user-interface strongly affects social contagion. Accounting for this visibility significantly simplifies the dynamics of social contagion. The likelihood an individual will spread information increases monotonically with exposure, while explicit feedback about how many friends have previously spread it increases the likelihood of a response. We provide a framework for unifying information visibility, divided attention, and explicit social feedback to predict the temporal dynamics of user behavior.

The Simple Rules of Social Contagion

NASA Astrophysics Data System (ADS)

Hodas, Nathan O.; Lerman, Kristina

2014-03-01

It is commonly believed that information spreads between individuals like a pathogen, with each exposure by an informed friend potentially resulting in a naive individual becoming infected. However, empirical studies of social media suggest that individual response to repeated exposure to information is far more complex. As a proxy for intervention experiments, we compare user responses to multiple exposures on two different social media sites, Twitter and Digg. We show that the position of exposing messages on the user-interface strongly affects social contagion. Accounting for this visibility significantly simplifies the dynamics of social contagion. The likelihood an individual will spread information increases monotonically with exposure, while explicit feedback about how many friends have previously spread it increases the likelihood of a response. We provide a framework for unifying information visibility, divided attention, and explicit social feedback to predict the temporal dynamics of user behavior.

New quests for better attitudes

NASA Technical Reports Server (NTRS)

Shuster, Malcolm D.

1991-01-01

During the past few years considerable insight was gained into the QUEST algorithm both as a maximum likelihood estimator and as a Kalman filter/smoother for systems devoid of dynamical noise. The new algorithms and software are described and analytical comparisons are made with the more conventional attitude Kalman filter. It is also described how they may be accommodated to noisy dynamical systems.

Weak and Dynamic GNSS Signal Tracking Strategies for Flight Missions in the Space Service Volume

PubMed Central

Jing, Shuai; Zhan, Xingqun; Liu, Baoyu; Chen, Maolin

2016-01-01

Weak-signal and high-dynamics are of two primary concerns of space navigation using GNSS (Global Navigation Satellite System) in the space service volume (SSV). The paper firstly defines a reference assumption third-order phase-locked loop (PLL) as the baseline of an onboard GNSS receiver, and proves the incompetence of this conventional architecture. Then an adaptive four-state Kalman filter (KF)-based algorithm is introduced to realize the optimization of loop noise bandwidth, which can adaptively regulate its filter gain according to the received signal power and line-of-sight (LOS) dynamics. To overcome the matter of losing lock in weak-signal and high-dynamic environments, an open loop tracking strategy aided by an inertial navigation system (INS) is recommended, and the traditional maximum likelihood estimation (MLE) method is modified in a non-coherent way by reconstructing the likelihood cost function. Furthermore, a typical mission with combined orbital maneuvering and non-maneuvering arcs is taken as a destination object to test the two proposed strategies. Finally, the experiment based on computer simulation identifies the effectiveness of an adaptive four-state KF-based strategy under non-maneuvering conditions and the virtue of INS-assisted methods under maneuvering conditions. PMID:27598164

Weak and Dynamic GNSS Signal Tracking Strategies for Flight Missions in the Space Service Volume.

PubMed

Jing, Shuai; Zhan, Xingqun; Liu, Baoyu; Chen, Maolin

2016-09-02

Weak-signal and high-dynamics are of two primary concerns of space navigation using GNSS (Global Navigation Satellite System) in the space service volume (SSV). The paper firstly defines a reference assumption third-order phase-locked loop (PLL) as the baseline of an onboard GNSS receiver, and proves the incompetence of this conventional architecture. Then an adaptive four-state Kalman filter (KF)-based algorithm is introduced to realize the optimization of loop noise bandwidth, which can adaptively regulate its filter gain according to the received signal power and line-of-sight (LOS) dynamics. To overcome the matter of losing lock in weak-signal and high-dynamic environments, an open loop tracking strategy aided by an inertial navigation system (INS) is recommended, and the traditional maximum likelihood estimation (MLE) method is modified in a non-coherent way by reconstructing the likelihood cost function. Furthermore, a typical mission with combined orbital maneuvering and non-maneuvering arcs is taken as a destination object to test the two proposed strategies. Finally, the experiment based on computer simulation identifies the effectiveness of an adaptive four-state KF-based strategy under non-maneuvering conditions and the virtue of INS-assisted methods under maneuvering conditions.

Using a Novel Spatial Tool to Inform Invasive Species Early Detection and Rapid Response Efforts

NASA Astrophysics Data System (ADS)

Davidson, Alisha D.; Fusaro, Abigail J.; Kashian, Donna R.

2015-07-01

Management of invasive species has increasingly emphasized the importance of early detection and rapid response (EDRR) programs in limiting introductions, establishment, and impacts. These programs require an understanding of vector and species spatial dynamics to prioritize monitoring sites and efficiently allocate resources. Yet managers often lack the empirical data necessary to make these decisions. We developed an empirical mapping tool that can facilitate development of EDRR programs through identifying high-risk locations, particularly within the recreational boating vector. We demonstrated the utility of this tool in the Great Lakes watershed. We surveyed boaters to identify trips among water bodies and to quantify behaviors associated with high likelihood of species transfer (e.g., not removing organic materials from boat trailers) during that trip. We mapped water bodies with high-risk inbound and outbound boater movements using ArcGIS. We also tested for differences in high-risk behaviors based on demographic variables to understand risk differences among boater groups. Incorporation of boater behavior led to identification of additional high-risk water bodies compared to using the number of trips alone. Therefore, the number of trips itself may not fully reflect the likelihood of invasion. This tool can be broadly applied in other geographic contexts and with different taxa, and can be adjusted according to varying levels of information concerning the vector or species of interest. The methodology is straightforward and can be followed after a basic introduction to ArcGIS software. The visual nature of the mapping tool will facilitate site prioritization by managers and stakeholders from diverse backgrounds.

Experimental Design for Parameter Estimation of Gene Regulatory Networks

PubMed Central

Timmer, Jens

2012-01-01

Systems biology aims for building quantitative models to address unresolved issues in molecular biology. In order to describe the behavior of biological cells adequately, gene regulatory networks (GRNs) are intensively investigated. As the validity of models built for GRNs depends crucially on the kinetic rates, various methods have been developed to estimate these parameters from experimental data. For this purpose, it is favorable to choose the experimental conditions yielding maximal information. However, existing experimental design principles often rely on unfulfilled mathematical assumptions or become computationally demanding with growing model complexity. To solve this problem, we combined advanced methods for parameter and uncertainty estimation with experimental design considerations. As a showcase, we optimized three simulated GRNs in one of the challenges from the Dialogue for Reverse Engineering Assessment and Methods (DREAM). This article presents our approach, which was awarded the best performing procedure at the DREAM6 Estimation of Model Parameters challenge. For fast and reliable parameter estimation, local deterministic optimization of the likelihood was applied. We analyzed identifiability and precision of the estimates by calculating the profile likelihood. Furthermore, the profiles provided a way to uncover a selection of most informative experiments, from which the optimal one was chosen using additional criteria at every step of the design process. In conclusion, we provide a strategy for optimal experimental design and show its successful application on three highly nonlinear dynamic models. Although presented in the context of the GRNs to be inferred for the DREAM6 challenge, the approach is generic and applicable to most types of quantitative models in systems biology and other disciplines. PMID:22815723

How does the context and design of participatory decision-making processes affect their outcomes? Evidence from sustainable land management in global drylands.

NASA Astrophysics Data System (ADS)

de Vente, Joris; Reed, Mark; Stringer, Lindsay; Valente, Sandra; Newig, Jens

2014-05-01

It is widely accepted that the design of participatory processes in environmental management needs to be adapted to local contexts. Yet, it is not clear which elements of process design are universal, making it difficult to design processes that deliver beneficial outcomes across different contexts. We used empirical evidence to analyse the extent to which context and process design can enable or impede stakeholder participation and facilitate beneficial environmental and social outcomes in a range of decision-making contexts where stakeholders are engaged in environmental management. To explore the role of national-scale context on the outcomes of participatory processes, we interviewed facilitators from a process that was replicated across 13 dryland study sites around the world, which focussed on selecting Sustainable Land Management (SLM) options in close collaboration with stakeholders. To explore the role of process design and local context, we interviewed participants and facilitators in 11 case studies in Spain and Portugal in which different process designs were used. Interview data were analysed using a combination of quantitative and qualitative approaches to characterise relationships between process design, context and process outcomes. The similarity of outcomes across the 13 international study sites suggested that the national socio-cultural context in which a participatory process is conducted has little impact on its outcomes. However, analysis of cases from Spain and Portugal showed that some aspects of local context may affect outcomes. Having said this, factors associated with process design and participant selection played a more significant role in influencing outcomes in both countries. Processes that led to more beneficial outcomes for the environment and/or participants were likely to include: the legitimate representation of stakeholders; professional facilitation including structured methods for eliciting and aggregating information and balancing power dynamics between participants; and the provision of information and decision-making power to all participants. Participatory processes initiated or facilitated by government bodies led to significantly less trust, information gain, learning, and flexible solutions. However, in these processes, decisions were more acceptable to and likely to be implemented by governments and by those who had to apply them on the ground. These findings provide a solid empirical basis for best practice in the design of participatory processes in SLM in a number of contexts internationally, which if followed, increase the likelihood of providing beneficial environmental and social outcomes for those involved.

Event attribution using data assimilation in an intermediate complexity atmospheric model

NASA Astrophysics Data System (ADS)

Metref, Sammy; Hannart, Alexis; Ruiz, Juan; Carrassi, Alberto; Bocquet, Marc; Ghil, Michael

2016-04-01

A new approach, coined DADA (Data Assimilation for Detection and Attribution) has been recently introduced by Hannart et al. 2015, and is potentially useful for near real time, systematic causal attribution of weather and climate-related events The method is purposely designed to allow its operability at meteorological centers by synergizing causal attribution with Data Assimilation (DA) methods usually designed to deal with large nonlinear models. In Hannart et al. 2015, the DADA proposal is illustrated in the context of a low-order nonlinear model (forced three-variable Lorenz model) that is of course not realistic to represent the events considered. As a continuation of this stream of work, we therefore propose an implementation of the DADA approach in a realistic intermediate complexity atmospheric model (ICTP AGCM, nicknamed SPEEDY). The SPEEDY model is based on a spectral dynamical core developed at the Geophysical Fluid Dynamics Laboratory (see Held and Suarez 1994). It is a hydrostatic, r-coordinate, spectral-transform model in the vorticity-divergence form described by Bourke (1974). A synthetic dataset of observations of an extreme precipitation event over Southeastern South America is extracted from a long SPEEDY simulation under present climatic conditions (i.e. factual conditions). Then, following the DADA approach, observations of this event are assimilated twice in the SPEEDY model: first in the factual configuration of the model and second under its counterfactual, pre-industrial configuration. We show that attribution can be performed based on the likelihood ratio as in Hannart et al. 2015, but we further extend this result by showing that the likelihood can be split in space, time and variables in order to help identify the specific physical features of the event that bear the causal signature. References: Hannart A., A. Carrassi, M. Bocquet, M. Ghil, P. Naveau, M. Pulido, J. Ruiz, P. Tandeo (2015) DADA: Data assimilation for the detection and attribution of weather and climate-related events, Climatic Change, (in press). Held I. M. and M. J. Suarez, (1994): A Proposal for the Intercomparison of the Dynamical Cores of Atmospheric General Circulation Models. Bull. Amer. Meteor. Soc., 75, 1825-1830. Bourke W. (1972): A multi-level spectral model. I. Formulation and hemispheric integrations. Mon. Wea. Rev., 102, 687-701.

Fuzzy fractals, chaos, and noise

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

Zardecki, A.

1997-05-01

To distinguish between chaotic and noisy processes, the authors analyze one- and two-dimensional chaotic mappings, supplemented by the additive noise terms. The predictive power of a fuzzy rule-based system allows one to distinguish ergodic and chaotic time series: in an ergodic series the likelihood of finding large numbers is small compared to the likelihood of finding them in a chaotic series. In the case of two dimensions, they consider the fractal fuzzy sets whose {alpha}-cuts are fractals, arising in the context of a quadratic mapping in the extended complex plane. In an example provided by the Julia set, the conceptmore » of Hausdorff dimension enables one to decide in favor of chaotic or noisy evolution.« less

Developmental Assets: Profile of Youth in a Juvenile Justice Facility

ERIC Educational Resources Information Center

Chew, Weslee; Osseck, Jenna; Raygor, Desiree; Eldridge-Houser, Jennifer; Cox, Carol

2010-01-01

Background: Possessing high numbers of developmental assets greatly reduces the likelihood of a young person engaging in health-risk behaviors. Since youth in the juvenile justice system seem to exhibit many high-risk behaviors, the purpose of this study was to assess the presence of external, internal, and social context areas of developmental…

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…

The Accuracy of Self-Efficacy Beliefs in Outdoor Education

ERIC Educational Resources Information Center

Schumann, Scott

2013-01-01

In the present era of outcome assessment and accountability, self-efficacy is a popular outcome measure in outdoor and adventure education. Self-efficacy beliefs are context specific perceptions an individual possesses about a likelihood of success in future tasks and are related to well-being confidence, and persistence. However, recent research…

Assessing Student Achievement in Large-Scale Educational Programs Using Hierarchical Propensity Scores

ERIC Educational Resources Information Center

Vaughan, Angela L.; Lalonde, Trent L.; Jenkins-Guarnieri, Michael A.

2014-01-01

Many researchers assessing the efficacy of educational programs face challenges due to issues with non-randomization and the likelihood of dependence between nested subjects. The purpose of the study was to demonstrate a rigorous research methodology using a hierarchical propensity score matching method that can be utilized in contexts where…

The Context of Creating Space: Assessing the Likelihood of College LGBT Center Presence

ERIC Educational Resources Information Center

Fine, Leigh E.

2012-01-01

LGBT (lesbian, gay, bisexual, and transgender) resource centers are campus spaces dedicated to the success of sexual minority students. However, only a small handful of American colleges and universities have such spaces. Political opportunity and resource mobilization theory can provide a useful framework for understanding what contextual factors…

Planning for Sustainability from the Outset

ERIC Educational Resources Information Center

Bourne, Janet

2016-01-01

What are the elements of professional learning that lead to an increase of the likelihood of new learning and understandings being embedded into teacher practices? This article details some of the strategies the author has successfully employed to establish a context whereby an innovation would be sustained past the time of the Ministry Gifted and…

Risk assessment [Chapter 9

Treesearch

Dennis S. Ojima; Louis R. Iverson; Brent L. Sohngen; James M. Vose; Christopher W. Woodall; Grant M. Domke; David L. Peterson; Jeremy S. Littell; Stephen N. Matthews; Anantha M. Prasad; Matthew P. Peters; Gary W. Yohe; Megan M. Friggens

2014-01-01

What is "risk" in the context of climate change? How can a "risk-based framework" help assess the effects of climate change and develop adaptation priorities? Risk can be described by the likelihood of an impact occurring and the magnitude of the consequences of the impact (Yohe 2010) (Fig. 9.1). High-magnitude impacts are always...

Effect of Performance Feedback on Perceived Knowledge and Likelihood to Pursue Continuing Education

ERIC Educational Resources Information Center

Eberman, Lindsey E.; Tripp, Brady L.

2011-01-01

Context: For practicing health care professionals, waiting for a teachable moment to identify a gap in knowledge could prove critical. Other methods are needed to help health care professionals identify their knowledge gaps. Objective: To assess the effect of performance feedback on Athletic Trainers' (AT) perceived knowledge (PK) and likelihood…

Semiparametric Item Response Functions in the Context of Guessing

ERIC Educational Resources Information Center

Falk, Carl F.; Cai, Li

2016-01-01

We present a logistic function of a monotonic polynomial with a lower asymptote, allowing additional flexibility beyond the three-parameter logistic model. We develop a maximum marginal likelihood-based approach to estimate the item parameters. The new item response model is demonstrated on math assessment data from a state, and a computationally…

Global Convergence of the EM Algorithm for Unconstrained Latent Variable Models with Categorical Indicators

ERIC Educational Resources Information Center

Weissman, Alexander

2013-01-01

Convergence of the expectation-maximization (EM) algorithm to a global optimum of the marginal log likelihood function for unconstrained latent variable models with categorical indicators is presented. The sufficient conditions under which global convergence of the EM algorithm is attainable are provided in an information-theoretic context by…

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…

INCORPORATING ROUTINE ACTIVITIES, ACTIVITY SPACES, AND SITUATIONAL DEFINITIONS INTO THE SOCIAL SCHEMATIC THEORY OF CRIME*

PubMed Central

BARR, ASHLEY B.; LEI, MAN-KIT; STEWART, ERIC

2014-01-01

Simons and Burt’s (2011) social schematic theory (SST) of crime posits that adverse social factors are associated with offending because they promote a set of social schemas (i.e., a criminogenic knowledge structure) that elevates the probability of situational definitions favorable to crime. This study extends the SST model by incorporating the role of contexts for action. Furthermore, the study advances tests of the SST by incorporating a measure of criminogenic situational definitions to assess whether such definitions mediate the effects of schemas and contexts on crime. Structural equation models using 10 years of panel data from 582 African American youth provided strong support for the expanded theory. The results suggest that childhood and adolescent social adversity fosters a criminogenic knowledge structure as well as selection into criminogenic activity spaces and risky activities, all of which increase the likelihood of offending largely through situational definitions. Additionally, evidence shows that the criminogenic knowledge structure interacts with settings to amplify the likelihood of situational definitions favorable to crime. PMID:26392633

Inverse Ising problem in continuous time: A latent variable approach

NASA Astrophysics Data System (ADS)

Donner, Christian; Opper, Manfred

2017-12-01

We consider the inverse Ising problem: the inference of network couplings from observed spin trajectories for a model with continuous time Glauber dynamics. By introducing two sets of auxiliary latent random variables we render the likelihood into a form which allows for simple iterative inference algorithms with analytical updates. The variables are (1) Poisson variables to linearize an exponential term which is typical for point process likelihoods and (2) Pólya-Gamma variables, which make the likelihood quadratic in the coupling parameters. Using the augmented likelihood, we derive an expectation-maximization (EM) algorithm to obtain the maximum likelihood estimate of network parameters. Using a third set of latent variables we extend the EM algorithm to sparse couplings via L1 regularization. Finally, we develop an efficient approximate Bayesian inference algorithm using a variational approach. We demonstrate the performance of our algorithms on data simulated from an Ising model. For data which are simulated from a more biologically plausible network with spiking neurons, we show that the Ising model captures well the low order statistics of the data and how the Ising couplings are related to the underlying synaptic structure of the simulated network.

Contextual control over task-set retrieval.

PubMed

Crump, Matthew J C; Logan, Gordon D

2010-11-01

Contextual cues signaling task likelihood or the likelihood of task repetition are known to modulate the size of switch costs. We follow up on the finding by Leboe, Wong, Crump, and Stobbe (2008) that location cues predictive of the proportion of switch or repeat trials modulate switch costs. Their design employed one cue per task, whereas our experiment employed two cues per task, which allowed separate assessment of modulations to the cue-repetition benefit, a measure of lower level cue-encoding processes, and to the task-alternation cost, a measure of higher level processes representing task-set information. We demonstrate that location information predictive of switch proportion modulates performance at the level of task-set representations. Furthermore, we demonstrate that contextual control occurs even when subjects are unaware of the associations between context and switch likelihood. We discuss the notion that contextual information provides rapid, unconscious control over the extent to which prior task-set representations are retrieved in the service of guiding online performance.

Technical Note: Approximate Bayesian parameterization of a complex tropical forest model

NASA Astrophysics Data System (ADS)

Hartig, F.; Dislich, C.; Wiegand, T.; Huth, A.

2013-08-01

Inverse parameter estimation of process-based models is a long-standing problem in ecology and evolution. A key problem of inverse parameter estimation is to define a metric that quantifies how well model predictions fit to the data. Such a metric can be expressed by general cost or objective functions, but statistical inversion approaches are based on a particular metric, the probability of observing the data given the model, known as the likelihood. Deriving likelihoods for dynamic models requires making assumptions about the probability for observations to deviate from mean model predictions. For technical reasons, these assumptions are usually derived without explicit consideration of the processes in the simulation. Only in recent years have new methods become available that allow generating likelihoods directly from stochastic simulations. Previous applications of these approximate Bayesian methods have concentrated on relatively simple models. Here, we report on the application of a simulation-based likelihood approximation for FORMIND, a parameter-rich individual-based model of tropical forest dynamics. We show that approximate Bayesian inference, based on a parametric likelihood approximation placed in a conventional MCMC, performs well in retrieving known parameter values from virtual field data generated by the forest model. We analyze the results of the parameter estimation, examine the sensitivity towards the choice and aggregation of model outputs and observed data (summary statistics), and show results from using this method to fit the FORMIND model to field data from an Ecuadorian tropical forest. Finally, we discuss differences of this approach to Approximate Bayesian Computing (ABC), another commonly used method to generate simulation-based likelihood approximations. Our results demonstrate that simulation-based inference, which offers considerable conceptual advantages over more traditional methods for inverse parameter estimation, can successfully be applied to process-based models of high complexity. The methodology is particularly suited to heterogeneous and complex data structures and can easily be adjusted to other model types, including most stochastic population and individual-based models. Our study therefore provides a blueprint for a fairly general approach to parameter estimation of stochastic process-based models in ecology and evolution.

A Dynamic Ubiquitous Learning Resource Model with Context and Its Effects on Ubiquitous Learning

ERIC Educational Resources Information Center

Chen, Min; Yu, Sheng Quan; Chiang, Feng Kuang

2017-01-01

Most ubiquitous learning researchers use resource recommendation and retrieving based on context to provide contextualized learning resources, but it is the kind of one-way context matching. Learners always obtain fixed digital learning resources, which present all learning contents in any context. This study proposed a dynamic ubiquitous learning…

On Restructurable Control System Theory

NASA Technical Reports Server (NTRS)

Athans, M.

1983-01-01

The state of stochastic system and control theory as it impacts restructurable control issues is addressed. The multivariable characteristics of the control problem are addressed. The failure detection/identification problem is discussed as a multi-hypothesis testing problem. Control strategy reconfiguration, static multivariable controls, static failure hypothesis testing, dynamic multivariable controls, fault-tolerant control theory, dynamic hypothesis testing, generalized likelihood ratio (GLR) methods, and adaptive control are discussed.

Information-theoretic model selection for optimal prediction of stochastic dynamical systems from data

NASA Astrophysics Data System (ADS)

Darmon, David

2018-03-01

In the absence of mechanistic or phenomenological models of real-world systems, data-driven models become necessary. The discovery of various embedding theorems in the 1980s and 1990s motivated a powerful set of tools for analyzing deterministic dynamical systems via delay-coordinate embeddings of observations of their component states. However, in many branches of science, the condition of operational determinism is not satisfied, and stochastic models must be brought to bear. For such stochastic models, the tool set developed for delay-coordinate embedding is no longer appropriate, and a new toolkit must be developed. We present an information-theoretic criterion, the negative log-predictive likelihood, for selecting the embedding dimension for a predictively optimal data-driven model of a stochastic dynamical system. We develop a nonparametric estimator for the negative log-predictive likelihood and compare its performance to a recently proposed criterion based on active information storage. Finally, we show how the output of the model selection procedure can be used to compare candidate predictors for a stochastic system to an information-theoretic lower bound.

Joint penalized-likelihood reconstruction of time-activity curves and regions-of-interest from projection data in brain PET

NASA Astrophysics Data System (ADS)

Krestyannikov, E.; Tohka, J.; Ruotsalainen, U.

2008-06-01

This paper presents a novel statistical approach for joint estimation of regions-of-interest (ROIs) and the corresponding time-activity curves (TACs) from dynamic positron emission tomography (PET) brain projection data. It is based on optimizing the joint objective function that consists of a data log-likelihood term and two penalty terms reflecting the available a priori information about the human brain anatomy. The developed local optimization strategy iteratively updates both the ROI and TAC parameters and is guaranteed to monotonically increase the objective function. The quantitative evaluation of the algorithm is performed with numerically and Monte Carlo-simulated dynamic PET brain data of the 11C-Raclopride and 18F-FDG tracers. The results demonstrate that the method outperforms the existing sequential ROI quantification approaches in terms of accuracy, and can noticeably reduce the errors in TACs arising due to the finite spatial resolution and ROI delineation.

Gaussian process inference for estimating pharmacokinetic parameters of dynamic contrast-enhanced MR images.

PubMed

Wang, Shijun; Liu, Peter; Turkbey, Baris; Choyke, Peter; Pinto, Peter; Summers, Ronald M

2012-01-01

In this paper, we propose a new pharmacokinetic model for parameter estimation of dynamic contrast-enhanced (DCE) MRI by using Gaussian process inference. Our model is based on the Tofts dual-compartment model for the description of tracer kinetics and the observed time series from DCE-MRI is treated as a Gaussian stochastic process. The parameter estimation is done through a maximum likelihood approach and we propose a variant of the coordinate descent method to solve this likelihood maximization problem. The new model was shown to outperform a baseline method on simulated data. Parametric maps generated on prostate DCE data with the new model also provided better enhancement of tumors, lower intensity on false positives, and better boundary delineation when compared with the baseline method. New statistical parameter maps from the process model were also found to be informative, particularly when paired with the PK parameter maps.

The Simple Rules of Social Contagion

PubMed Central

Hodas, Nathan O.; Lerman, Kristina

2014-01-01

It is commonly believed that information spreads between individuals like a pathogen, with each exposure by an informed friend potentially resulting in a naive individual becoming infected. However, empirical studies of social media suggest that individual response to repeated exposure to information is far more complex. As a proxy for intervention experiments, we compare user responses to multiple exposures on two different social media sites, Twitter and Digg. We show that the position of exposing messages on the user-interface strongly affects social contagion. Accounting for this visibility significantly simplifies the dynamics of social contagion. The likelihood an individual will spread information increases monotonically with exposure, while explicit feedback about how many friends have previously spread it increases the likelihood of a response. We provide a framework for unifying information visibility, divided attention, and explicit social feedback to predict the temporal dynamics of user behavior. PMID:24614301

Socioeconomic Status and the Increased Prevalence of Autism in California

PubMed Central

King, Marissa D.; Bearman, Peter S.

2011-01-01

The prevalence of autism has increased precipitously—roughly 10-fold in the past 40 years—yet no one knows exactly what caused this dramatic rise. Using a large and representative dataset that spans the California birth cohorts from 1992 through 2000, we examine individual and community resources associated with the likelihood of an autism diagnosis over time. This allows us to identify key social factors that have contributed to increased autism prevalence. While individual-level factors, such as birth weight and parental education, have had a fairly constant effect on likelihood of diagnosis over time, we find that community-level resources drive increased prevalence. This study suggests that neighborhoods dynamically interact with the people living in them in different ways at different times to shape health outcomes. By treating neighborhoods as dynamic, we can better understand the changing socioeconomic gradient of autism and the increase in prevalence. PMID:21547238

A conceptual and statistical framework for adaptive radiations with a key role for diversity dependence.

PubMed

Etienne, Rampal S; Haegeman, Bart

2012-10-01

In this article we propose a new framework for studying adaptive radiations in the context of diversity-dependent diversification. Diversity dependence causes diversification to decelerate at the end of an adaptive radiation but also plays a key role in the initial pulse of diversification. In particular, key innovations (which in our definition include novel traits as well as new environments) may cause decoupling of the diversity-dependent dynamics of the innovative clade from the diversity-dependent dynamics of its ancestral clade. We present a likelihood-based inference method to test for decoupling of diversity dependence using molecular phylogenies. The method, which can handle incomplete phylogenies, identifies when the decoupling took place and which diversification parameters are affected. We illustrate our approach by applying it to the molecular phylogeny of the North American clade of the legume tribe Psoraleeae (47 extant species, of which 4 are missing). Two diversification rate shifts were previously identified for this clade; our analysis shows that the first, positive shift can be associated with decoupling of two Pediomelum subgenera from the other Psoraleeae lineages, while we argue that the second, negative shift can be attributed to speciation being protracted. The latter explanation yields nonzero extinction rates, in contrast to previous findings. Our framework offers a new perspective on macroevolution: new environments and novel traits (ecological opportunity) and diversity dependence (ecological limits) cannot be considered separately.

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…

Impact of Deployment on Air Force Nursing Retention: Completion Phase

DTIC Science & Technology

2010-09-24

the stress and burnout issues of military nurses . The consequences of... The impacts of deployment were examined in the context of their roles in mitigating the likelihood of intent to remain in military nursing careers... nurses rated each of the choices according to their perceived importance. The most important choices were length of deployment and deployed job

ArcFuels User Guide and Tutorial: for use with ArcGIS 9

Treesearch

Nicole M. Vaillant; Alan A. Ager; John Anderson; Lauren. Miller

2013-01-01

Fuel management planning can be a complex problem that is assisted by fire behavior modeling and geospatial analyses. Fuel management often is a particularly complicated process in which the benefits and potential impacts of fuel treatments need to be demonstrated in the context of land management goals and public expectations. Fire intensity, likelihood, and effects...

Cumulative Risk Effects in the Bullying of Children and Young People with Autism Spectrum Conditions

ERIC Educational Resources Information Center

Hebron, Judith; Oldfield, Jeremy; Humphrey, Neil

2017-01-01

Students with autism are more likely to be bullied than their typically developing peers. However, several studies have shown that their likelihood of being bullied increases in the context of exposure to certain risk factors (e.g. behaviour difficulties and poor peer relationships). This study explores vulnerability to bullying from a cumulative…

Semi-Parametric Item Response Functions in the Context of Guessing. CRESST Report 844

ERIC Educational Resources Information Center

Falk, Carl F.; Cai, Li

2015-01-01

We present a logistic function of a monotonic polynomial with a lower asymptote, allowing additional flexibility beyond the three-parameter logistic model. We develop a maximum marginal likelihood based approach to estimate the item parameters. The new item response model is demonstrated on math assessment data from a state, and a computationally…

Drop out and "Disconnected" Young Adults: Examining the Impact of Neighborhood and School Contexts

ERIC Educational Resources Information Center

Rendón, Maria G.

2014-01-01

Using data from the National Longitudinal Study of Adolescent Health (Add Health) this study compares if and how neighborhood effects on the likelihood to drop out and be "disconnected" from school and work in young adulthood change when schools are taken into account. As widely documented, I find that neighborhood socioeconomic status…

Imprecise Frequency Descriptors and the Miscomprehension of Prescription Drug Advertising: Public Policy and Regulatory Implications.

ERIC Educational Resources Information Center

Davis, Joel J.

1999-01-01

Explores the communicative effectiveness of imprecise frequency descriptors within the context of consumer prescription drug advertising. Conducts two separate studies using a total sample of 147 adults. Finds that consumers are unable to accurately estimate the relative likelihood of side effect occurrence when a list of side effects are preceded…

School Context Matters: The Impacts of Concentrated Poverty and Racial Segregation on Childhood Obesity

ERIC Educational Resources Information Center

Piontak, Joy Rayanne; Schulman, Michael D.

2016-01-01

Background: Schools are important sites for interventions to prevent childhood obesity. This study examines how variables measuring the socioeconomic and racial composition of schools and counties affect the likelihood of obesity among third to fifth grade children. Methods: Body mass index data were collected from third to fifth grade public…

Inherent Association Between Academic Delay of Gratification, Future Time Perspective, and Self-Regulated Learning

ERIC Educational Resources Information Center

Bembenutty, Hefer; Karabenick, Stuart A.

2004-01-01

We review the association between delay of gratification and future time perspective (FTP), which can be incorporated within the theoretical perspective of self-regulation of learning. We propose that delay of gratification in academic contexts, along with facilitative beliefs about the future, increase the likelihood of completing academic tasks.…

Impulsive-Analytic Disposition in Mathematical Problem Solving: A Survey and a Mathematics Test

ERIC Educational Resources Information Center

Lim, Kien H.; Wagler, Amy

2012-01-01

The Likelihood-to-Act (LtA) survey and a mathematics test were used in this study to assess students' impulsive-analytic disposition in the context of mathematical problem solving. The results obtained from these two instruments were compared to those obtained using two widely-used scales: Need for Cognition (NFC) and Barratt Impulsivity Scale…

From Consideration to Commitment: Factors in Adults' Decisions to Enroll in a Higher Education Degree Program

ERIC Educational Resources Information Center

Stein, David S.; Wanstreet, Constance; Trinko, Lynn A.

2011-01-01

This study identified factors associated with the decision to enroll in a higher education degree program. In the context of predicting enrollment in a workforce development credentialing program, this study identified six variables that are strongly related to the likelihood to enroll: time out of school; possibilities for intellectual, personal,…

Lord's Wald Test for Detecting Dif in Multidimensional Irt Models: A Comparison of Two Estimation Approaches

ERIC Educational Resources Information Center

Lee, Soo; Suh, Youngsuk

2018-01-01

Lord's Wald test for differential item functioning (DIF) has not been studied extensively in the context of the multidimensional item response theory (MIRT) framework. In this article, Lord's Wald test was implemented using two estimation approaches, marginal maximum likelihood estimation and Bayesian Markov chain Monte Carlo estimation, to detect…

Chern-Simons Modified Gravity

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.

A segmentation/clustering model for the analysis of array CGH data.

PubMed

Picard, F; Robin, S; Lebarbier, E; Daudin, J-J

2007-09-01

Microarray-CGH (comparative genomic hybridization) experiments are used to detect and map chromosomal imbalances. A CGH profile can be viewed as a succession of segments that represent homogeneous regions in the genome whose representative sequences share the same relative copy number on average. Segmentation methods constitute a natural framework for the analysis, but they do not provide a biological status for the detected segments. We propose a new model for this segmentation/clustering problem, combining a segmentation model with a mixture model. We present a new hybrid algorithm called dynamic programming-expectation maximization (DP-EM) to estimate the parameters of the model by maximum likelihood. This algorithm combines DP and the EM algorithm. We also propose a model selection heuristic to select the number of clusters and the number of segments. An example of our procedure is presented, based on publicly available data sets. We compare our method to segmentation methods and to hidden Markov models, and we show that the new segmentation/clustering model is a promising alternative that can be applied in the more general context of signal processing.

Advances in risk assessment for climate change adaptation policy.

PubMed

Adger, W Neil; Brown, Iain; Surminski, Swenja

2018-06-13

Climate change risk assessment involves formal analysis of the consequences, likelihoods and responses to the impacts of climate change and the options for addressing these under societal constraints. Conventional approaches to risk assessment are challenged by the significant temporal and spatial dynamics of climate change; by the amplification of risks through societal preferences and values; and through the interaction of multiple risk factors. This paper introduces the theme issue by reviewing the current practice and frontiers of climate change risk assessment, with specific emphasis on the development of adaptation policy that aims to manage those risks. These frontiers include integrated assessments, dealing with climate risks across borders and scales, addressing systemic risks, and innovative co-production methods to prioritize solutions to climate challenges with decision-makers. By reviewing recent developments in the use of large-scale risk assessment for adaptation policy-making, we suggest a forward-looking research agenda to meet ongoing strategic policy requirements in local, national and international contexts.This article is part of the theme issue 'Advances in risk assessment for climate change adaptation policy'. © 2018 The Author(s).

Advances in risk assessment for climate change adaptation policy

NASA Astrophysics Data System (ADS)

Adger, W. Neil; Brown, Iain; Surminski, Swenja

2018-06-01

Climate change risk assessment involves formal analysis of the consequences, likelihoods and responses to the impacts of climate change and the options for addressing these under societal constraints. Conventional approaches to risk assessment are challenged by the significant temporal and spatial dynamics of climate change; by the amplification of risks through societal preferences and values; and through the interaction of multiple risk factors. This paper introduces the theme issue by reviewing the current practice and frontiers of climate change risk assessment, with specific emphasis on the development of adaptation policy that aims to manage those risks. These frontiers include integrated assessments, dealing with climate risks across borders and scales, addressing systemic risks, and innovative co-production methods to prioritize solutions to climate challenges with decision-makers. By reviewing recent developments in the use of large-scale risk assessment for adaptation policy-making, we suggest a forward-looking research agenda to meet ongoing strategic policy requirements in local, national and international contexts. This article is part of the theme issue `Advances in risk assessment for climate change adaptation policy'.

A meta-analysis of education effects on chronic disease: the causal dynamics of the Population Education Transition Curve.

PubMed

Smith, William C; Anderson, Emily; Salinas, Daniel; Horvatek, Renata; Baker, David P

2015-02-01

As the Epidemiological Transition progresses worldwide, chronic diseases account for the majority of deaths in developed countries and a rising proportion in developing countries indicating a new global pattern of mortality and health challenges into the future. Attainment of formal education is widely reported to have a negative gradient with risk factors and onset of chronic disease, yet there has not been a formal assessment of this research. A random-effects meta-analysis finds that across 414 published effects more education significantly reduces the likelihood of chronic disease, except for neoplastic diseases with substantial genetic causes. Some studies, however, report null effects and other research on infectious disease report positive education gradients. Instead of assuming these contradictory results are spurious, it is suggested that they are part of a predictable systemic interaction between multiple mediating effects of education and the Epidemiological Transition stage of the population; and thus represent one case of the Population Education Transition Curve modeling changes in the association between education and health as dependent on population context. Copyright © 2014 Elsevier Ltd. All rights reserved.

Advances in risk assessment for climate change adaptation policy

PubMed Central

Adger, W. Neil; Brown, Iain; Surminski, Swenja

2018-01-01

Climate change risk assessment involves formal analysis of the consequences, likelihoods and responses to the impacts of climate change and the options for addressing these under societal constraints. Conventional approaches to risk assessment are challenged by the significant temporal and spatial dynamics of climate change; by the amplification of risks through societal preferences and values; and through the interaction of multiple risk factors. This paper introduces the theme issue by reviewing the current practice and frontiers of climate change risk assessment, with specific emphasis on the development of adaptation policy that aims to manage those risks. These frontiers include integrated assessments, dealing with climate risks across borders and scales, addressing systemic risks, and innovative co-production methods to prioritize solutions to climate challenges with decision-makers. By reviewing recent developments in the use of large-scale risk assessment for adaptation policy-making, we suggest a forward-looking research agenda to meet ongoing strategic policy requirements in local, national and international contexts. This article is part of the theme issue ‘Advances in risk assessment for climate change adaptation policy’. PMID:29712800

Urban regulatory focus: a new concept linking city size to human behaviour

PubMed Central

2018-01-01

Why do people in big cities behave differently to those living in small cities? To answer this question, in this paper a new concept of urban dynamics is presented that links city size to human behaviour. The concept has its origins in regulatory focus theory. According to the theory, goal-directed behaviour is regulated by two motivational systems, promotion and prevention. Individuals motivated by promotion goals (growth, accomplishment) focus on winning and tend to take risks, whereas those driven by prevention goals (safety, security) focus on not losing and try to avoid risk. Here we elaborate on the existing literature by linking the theory to the urban context. In our conceptualization, cities are powerful regulatory systems, and as such they impinge upon the way people regulate themselves in the urban space. Evidence from signal detection analysis is provided that supports this concept. The experience of a big-city context intensified both promotion-focused behaviour (a risky bias) for promotion-focused participants and prevention-focused behaviour (a conservative bias) for prevention-focused participants. The experience of a small-city context encouraged the opposite behavioural pattern in both cases. These findings suggest that the urban environment can influence the regulatory focus strategies of an individual in a way that cannot simply be explained by their personal regulatory focus. Specifically, the likelihood of one's behaving in a promotion- or prevention-oriented manner is dependent both on one's chronic regulatory focus and also on the urban context in which one lives. Based on this, we maintain that vibrant cities with a large population and a fast pace of life encourage extreme and polarized behaviours, whereas cities with a smaller population and a slower pace of life encourage more moderate and less polarized behavioural responses, which may explain why people in big cities take more risks, do more business, produce and spend more, and even walk faster. PMID:29892353

PlanetPack: A radial-velocity time-series analysis tool facilitating exoplanets detection, characterization, and dynamical simulations

NASA Astrophysics Data System (ADS)

Baluev, Roman V.

2013-08-01

We present PlanetPack, a new software tool that we developed to facilitate and standardize the advanced analysis of radial velocity (RV) data for the goal of exoplanets detection, characterization, and basic dynamical N-body simulations. PlanetPack is a command-line interpreter, that can run either in an interactive mode or in a batch mode of automatic script interpretation. Its major abilities include: (i) advanced RV curve fitting with the proper maximum-likelihood treatment of unknown RV jitter; (ii) user-friendly multi-Keplerian as well as Newtonian N-body RV fits; (iii) use of more efficient maximum-likelihood periodograms that involve the full multi-planet fitting (sometimes called as “residual” or “recursive” periodograms); (iv) easily calculatable parametric 2D likelihood function level contours, reflecting the asymptotic confidence regions; (v) fitting under some useful functional constraints is user-friendly; (vi) basic tasks of short- and long-term planetary dynamical simulation using a fast Everhart-type integrator based on Gauss-Legendre spacings; (vii) fitting the data with red noise (auto-correlated errors); (viii) various analytical and numerical methods for the tasks of determining the statistical significance. It is planned that further functionality may be added to PlanetPack in the future. During the development of this software, a lot of effort was made to improve the calculational speed, especially for CPU-demanding tasks. PlanetPack was written in pure C++ (standard of 1998/2003), and is expected to be compilable and useable on a wide range of platforms.

Sexual harassment of nurses: an occupational hazard?

PubMed

Finnis, S J; Robbins, I

1994-03-01

A questionnaire was administered to qualified and student nurses to assess the prevalence and consequences of sexual harassment. There was a 56% completion rate. Of these 43 (66%) of the registered nurses and nine (35%) of the student nurses reported having experienced sexual harassment. The incidence of harassment for registered nurses in the year prior to the study was 46%. Patients were most likely to be the harasser for both student and registered nurses but there was an increased likelihood that other staff were involved in the harassment of registered nurses with doctors and male nursing staff being the predominant perpetrators. Dimensions of assertiveness and sex role identity did not predict the likelihood of harassment. Results are discussed in the context of attribution theory and gender power relationships.

Dynamic Scheduling for Veterans Health Administration Patients using Geospatial Dynamic Overbooking.

PubMed

Adams, Stephen; Scherer, William T; White, K Preston; Payne, Jason; Hernandez, Oved; Gerber, Mathew S; Whitehead, N Peter

2017-10-12

The Veterans Health Administration (VHA) is plagued by abnormally high no-show and cancellation rates that reduce the productivity and efficiency of its medical outpatient clinics. We address this issue by developing a dynamic scheduling system that utilizes mobile computing via geo-location data to estimate the likelihood of a patient arriving on time for a scheduled appointment. These likelihoods are used to update the clinic's schedule in real time. When a patient's arrival probability falls below a given threshold, the patient's appointment is canceled. This appointment is immediately reassigned to another patient drawn from a pool of patients who are actively seeking an appointment. The replacement patients are prioritized using their arrival probability. Real-world data were not available for this study, so synthetic patient data were generated to test the feasibility of the design. The method for predicting the arrival probability was verified on a real set of taxicab data. This study demonstrates that dynamic scheduling using geo-location data can reduce the number of unused appointments with minimal risk of double booking resulting from incorrect predictions. We acknowledge that there could be privacy concerns with regards to government possession of one's location and offer strategies for alleviating these concerns in our conclusion.

Likelihood-based methods for evaluating principal surrogacy in augmented vaccine trials.

PubMed

Liu, Wei; Zhang, Bo; Zhang, Hui; Zhang, Zhiwei

2017-04-01

There is growing interest in assessing immune biomarkers, which are quick to measure and potentially predictive of long-term efficacy, as surrogate endpoints in randomized, placebo-controlled vaccine trials. This can be done under a principal stratification approach, with principal strata defined using a subject's potential immune responses to vaccine and placebo (the latter may be assumed to be zero). In this context, principal surrogacy refers to the extent to which vaccine efficacy varies across principal strata. Because a placebo recipient's potential immune response to vaccine is unobserved in a standard vaccine trial, augmented vaccine trials have been proposed to produce the information needed to evaluate principal surrogacy. This article reviews existing methods based on an estimated likelihood and a pseudo-score (PS) and proposes two new methods based on a semiparametric likelihood (SL) and a pseudo-likelihood (PL), for analyzing augmented vaccine trials. Unlike the PS method, the SL method does not require a model for missingness, which can be advantageous when immune response data are missing by happenstance. The SL method is shown to be asymptotically efficient, and it performs similarly to the PS and PL methods in simulation experiments. The PL method appears to have a computational advantage over the PS and SL methods.

Procedure for estimating stability and control parameters from flight test data by using maximum likelihood methods employing a real-time digital system

NASA Technical Reports Server (NTRS)

Grove, R. D.; Bowles, R. L.; Mayhew, S. C.

1972-01-01

A maximum likelihood parameter estimation procedure and program were developed for the extraction of the stability and control derivatives of aircraft from flight test data. Nonlinear six-degree-of-freedom equations describing aircraft dynamics were used to derive sensitivity equations for quasilinearization. The maximum likelihood function with quasilinearization was used to derive the parameter change equations, the covariance matrices for the parameters and measurement noise, and the performance index function. The maximum likelihood estimator was mechanized into an iterative estimation procedure utilizing a real time digital computer and graphic display system. This program was developed for 8 measured state variables and 40 parameters. Test cases were conducted with simulated data for validation of the estimation procedure and program. The program was applied to a V/STOL tilt wing aircraft, a military fighter airplane, and a light single engine airplane. The particular nonlinear equations of motion, derivation of the sensitivity equations, addition of accelerations into the algorithm, operational features of the real time digital system, and test cases are described.

Maximum Likelihood Estimation with Emphasis on Aircraft Flight Data

NASA Technical Reports Server (NTRS)

Iliff, K. W.; Maine, R. E.

1985-01-01

Accurate modeling of flexible space structures is an important field that is currently under investigation. Parameter estimation, using methods such as maximum likelihood, is one of the ways that the model can be improved. The maximum likelihood estimator has been used to extract stability and control derivatives from flight data for many years. Most of the literature on aircraft estimation concentrates on new developments and applications, assuming familiarity with basic estimation concepts. Some of these basic concepts are presented. The maximum likelihood estimator and the aircraft equations of motion that the estimator uses are briefly discussed. The basic concepts of minimization and estimation are examined for a simple computed aircraft example. The cost functions that are to be minimized during estimation are defined and discussed. Graphic representations of the cost functions are given to help illustrate the minimization process. Finally, the basic concepts are generalized, and estimation from flight data is discussed. Specific examples of estimation of structural dynamics are included. Some of the major conclusions for the computed example are also developed for the analysis of flight data.

[An evaluation of some of the relationships between thought-action fusion, attributional styles, and depressive and obsessive-compulsive symptoms].

PubMed

Piri, Serap; Kabakçi, Elif

2007-01-01

Thought-action fusion (TAF) is a cognitive bias presumed to underlie the development of obsessional problems. Two domains of TAF have been identified. The first, TAF-moral, is characterized by the belief that having morally unacceptable thoughts is as bad as actually carrying them out. The second, TAF-likelihood, refers to the belief that certain thoughts cause particular events. The event can be related to one's self (likelihood-self) or to someone else (likelihood-others). The other cognitive variable of the study is attributional style. The theory of attributional styles, in terms of the causes of good and bad events, is taken into account especially in the context of depression and has four dimensions: internality-externality, stability-instability, globality-specifity, and importance-unimportance. The first objective of the present study was to investigate the relationships between TAF, and attributional style, and depressive and obsessive-compulsive symptoms. The second objective was to determine the predictors of TAF when the effects of depressive and obsessive-compulsive symptoms are statistically controlled. The sample consisted of 312 students randomly selected from different departments at Hacettepe University. The Thought-Action Fusion Scale (TAFS), Attributional Style Questionnaire (ASQ), Maudsley Obsessive-Compulsive Inventory (MOCI), and Beck Depression Inventory (BDI) were administered to these students. The correlations among all the subtypes of TAF (TAF-moral, likelihood-self, and likelihood-others), and the global attributions for bad events, BDI, and MOCI were significant. In addition, the correlation between TAF-moral and the importance of the attribution for bad events was significant. TAF-likelihood-others and TAF-likelihood-self were predicted by global attributions for bad events and TAF-moral was predicted by the importance of the attributions for bad events. TAF, and attributional styles, and depressive and obsessive-compulsive symptoms may be related to each other. The results also suggest a possible effect of other variables not controlled in this study, both on TAF and the dimensions of attributional styles.

Reactive aggression and peer victimization from pre-kindergarten to first grade: accounting for hyperactivity and teacher-child conflict.

PubMed

Runions, Kevin C

2014-12-01

The role of reactive aggression in the development of peer victimization remains unclear due in part to a failure to account for confounding problems of behavioural undercontrol (e.g., hyperactivity). As well, the school social context has rarely been examined to see whether these risks are mediated by relationships with teachers. This study tests the prospective relations between reactive aggression, hyperactivity, victimization, and teacher-child (T-C) relationship, to determine whether conflict mediates the relationships between externalizing problems and victimization. A sample of 1,114 Australian students were followed from pre-kindergarten through first grade. Cross-lagged path analyses were conducted, with comparison of gender-moderating models and autocorrelation models. Full-information maximum likelihood was deployed to account for missingness. Best fitting models found that the relationship of early externalizing problems to later victimization was mediated by T-C conflict. No evidence of victimization increasing externalizing problems nor gender differences were observed. T-C conflict in kindergarten predicted subsequent increases in victimization, reactive aggression, and hyperactivity. Understanding the processes whereby externalizing problems confer risk of victimization involves understanding the whole social context of classrooms, including relationships with teachers. Finer-grained research is needed to better understand how peer dynamics may be influenced by observation of T-C relationships. Pre-service teacher education needs to ensure a focus on the potential social impact of teacher's relationships with students. © 2014 The British Psychological Society.

The role of multisensory interplay in enabling temporal expectations.

PubMed

Ball, Felix; Michels, Lara E; Thiele, Carsten; Noesselt, Toemme

2018-01-01

Temporal regularities can guide our attention to focus on a particular moment in time and to be especially vigilant just then. Previous research provided evidence for the influence of temporal expectation on perceptual processing in unisensory auditory, visual, and tactile contexts. However, in real life we are often exposed to a complex and continuous stream of multisensory events. Here we tested - in a series of experiments - whether temporal expectations can enhance perception in multisensory contexts and whether this enhancement differs from enhancements in unisensory contexts. Our discrimination paradigm contained near-threshold targets (subject-specific 75% discrimination accuracy) embedded in a sequence of distractors. The likelihood of target occurrence (early or late) was manipulated block-wise. Furthermore, we tested whether spatial and modality-specific target uncertainty (i.e. predictable vs. unpredictable target position or modality) would affect temporal expectation (TE) measured with perceptual sensitivity (d ' ) and response times (RT). In all our experiments, hidden temporal regularities improved performance for expected multisensory targets. Moreover, multisensory performance was unaffected by spatial and modality-specific uncertainty, whereas unisensory TE effects on d ' but not RT were modulated by spatial and modality-specific uncertainty. Additionally, the size of the temporal expectation effect, i.e. the increase in perceptual sensitivity and decrease of RT, scaled linearly with the likelihood of expected targets. Finally, temporal expectation effects were unaffected by varying target position within the stream. Together, our results strongly suggest that participants quickly adapt to novel temporal contexts, that they benefit from multisensory (relative to unisensory) stimulation and that multisensory benefits are maximal if the stimulus-driven uncertainty is highest. We propose that enhanced informational content (i.e. multisensory stimulation) enables the robust extraction of temporal regularities which in turn boost (uni-)sensory representations. Copyright © 2017 Elsevier B.V. All rights reserved.

Coming-out across the life course: implications of age and historical context.

PubMed

Floyd, Frank J; Bakeman, Roger

2006-06-01

Effects of age and the calendar year when individuals first self-identified as gay, lesbian, or bisexual on their sexual orientation identity development were examined in a large community sample (N=767, 47% female, 18-74-years-old). These 2 variables were used to examine the timing and sequencing of 7 coming-out experiences: first awareness of same-sex attraction; first sexual experiences with opposite-sex partners; first sexual experiences with same-sex partners; self-identification as gay, lesbian, or bisexual; disclosure to someone other than a parent; disclosure to mother; and disclosure to father. The significant effects of age revealed that self-identification in adolescence as opposed to adulthood was associated with an overall young coming-out trajectory for all milestone experiences, which occurred in both earlier and recent historical contexts. Adolescents as opposed to adult self-identifiers were also more likely to demonstrate identity-centered sequences in which self-identification preceded same-sex sexual experiences, and fewer of these individuals had any heterosexual experience. Significant historical context effects indicated recent trends toward younger disclosure of orientation to others and to parents, greater likelihood of an identity-centered sequence, and younger ages for first heterosexual but not same-sex, sexual experiences. Among women, there was a recent trend toward greater likelihood of having a bisexual identity milestone. In general, the maturational effects were independent of historical context, with the exception that only adolescent self-identifiers who came out recently disclosed to others and to parents at an average age younger than 18 years. These developmental and historical trends expand on the stage-sequential framework to show how the process of sexual orientation identity development is driven by maturational factors as well as social changes.

Predicting streamflow response to fire-induced landcover change: implications of parameter uncertainty in the MIKE SHE model.

PubMed

McMichael, Christine E; Hope, Allen S

2007-08-01

Fire is a primary agent of landcover transformation in California semi-arid shrubland watersheds, however few studies have examined the impacts of fire and post-fire succession on streamflow dynamics in these basins. While it may seem intuitive that larger fires will have a greater impact on streamflow response than smaller fires in these watersheds, the nature of these relationships has not been determined. The effects of fire size on seasonal and annual streamflow responses were investigated for a medium-sized basin in central California using a modified version of the MIKE SHE model which had been previously calibrated and tested for this watershed using the Generalized Likelihood Uncertainty Estimation methodology. Model simulations were made for two contrasting periods, wet and dry, in order to assess whether fire size effects varied with weather regime. Results indicated that seasonal and annual streamflow response increased nearly linearly with fire size in a given year under both regimes. Annual flow response was generally higher in wetter years for both weather regimes, however a clear trend was confounded by the effect of stand age. These results expand our understanding of the effects of fire size on hydrologic response in chaparral watersheds, but it is important to note that the majority of model predictions were largely indistinguishable from the predictive uncertainty associated with the calibrated model - a key finding that highlights the importance of analyzing hydrologic predictions for altered landcover conditions in the context of model uncertainty. Future work is needed to examine how alternative decisions (e.g., different likelihood measures) may influence GLUE-based MIKE SHE streamflow predictions following different size fires, and how the effect of fire size on streamflow varies with other factors such as fire location.

Social impact evaluation : Some implications of the specific decisional context approach for anticipatory project assessment with special reference to available alternatives and to techniques of evaluating the social impacts of the anticipated effects of such alternatives

NASA Technical Reports Server (NTRS)

Mayo, L. H.

1972-01-01

The implications are explored of the specific decision context approach to anticipatory project assessment. More specifically, it is hypothesized that with respect to any given effect of a proposed project or action (mobility, job opportunities, air pollution, population distribution, etc.) such effect will likely differ in probability and/or magnitude from one decisional context to another; that the social desirability or undesirability of a given effect is a function (will differ with) each specific decisional context; that therefore the social impact of such effect will in all likelihood differ with each specific decisional context; and that the social significance of even the dame social impact of a given effect will vary from one decisional context to another when such social impact interacts with (competes with or reinforces) the social impacts of other effects. It also follows from this analysis that the respective roles of scientific method (demonstrable data) and adversarial system will not only differ with each specific decisional context but with each alternative course of action available to the decisional entity in each specific context.

Friends and Family: A Literature Review on How High School Social Groups Influence Advanced Math and Science Coursetaking

ERIC Educational Resources Information Center

Gottfried, Michael; Owens, Ann; Williams, Darryl; Kim, Hui Yon; Musto, Michela

2017-01-01

In this study, we synthesized the literature on how informal contexts, namely friends and family social groups, shape high school students' likelihood of pursuing advanced math and science coursework. Extending scholarly understandings of STEM education, we turned to the body of literature with three guiding questions: (1) What influence do…

With All My Relations: Counseling American Indians and Alaska Natives within a Familial Context

ERIC Educational Resources Information Center

Harper, Faith G.

2011-01-01

Statistics show that two thirds of American Indians and Alaska Natives (AIs/ANs) live outside of tribal areas, and 50% of those individuals who seek counseling services will not use tribal resources. There is a strong likelihood that counselors will have the opportunity to provide services to AI/AN clients. The review of the academic literature…

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.

Parameter Estimation in Epidemiology: from Simple to Complex Dynamics

NASA Astrophysics Data System (ADS)

Aguiar, Maíra; Ballesteros, Sebastién; Boto, João Pedro; Kooi, Bob W.; Mateus, Luís; Stollenwerk, Nico

2011-09-01

We revisit the parameter estimation framework for population biological dynamical systems, and apply it to calibrate various models in epidemiology with empirical time series, namely influenza and dengue fever. When it comes to more complex models like multi-strain dynamics to describe the virus-host interaction in dengue fever, even most recently developed parameter estimation techniques, like maximum likelihood iterated filtering, come to their computational limits. However, the first results of parameter estimation with data on dengue fever from Thailand indicate a subtle interplay between stochasticity and deterministic skeleton. The deterministic system on its own already displays complex dynamics up to deterministic chaos and coexistence of multiple attractors.

Social inequality in morbidity, framed within the current economic crisis in Spain.

PubMed

Zapata Moya, A R; Buffel, V; Navarro Yáñez, C J; Bracke, P

2015-11-14

Inspired by the 'Fundamental Cause Theory (FCT)' we explore social inequalities in preventable versus relatively less-preventable illnesses in Spain. The focus is on the education-health gradient, as education is one of the most important components of an individual's socioeconomic status (SES). Framed in the context of the recent economic crisis, we investigate the education gradient in depression, diabetes, and myocardial infarction (relatively highly preventable illnesses) and malignant tumors (less preventable), and whether this educational gradient varies across the regional-economic context and changes therein. We use data from three waves of the Spanish National Health Survey (2003-2004, 2006-2007, and 2011-2012), and from the 2009-2010 wave of the European Health Survey in Spain, which results in a repeated cross-sectional design. Logistic multilevel regressions are performed with depression, diabetes, myocardial infarction, and malignant tumors as dependent variables. The multilevel design has three levels (the individual, period-regional, and regional level), which allows us to estimate both longitudinal and cross-sectional macro effects. The regional-economic context and changes therein are assessed using the real GDP growth rate and the low work intensity indicator. Education gradients in more-preventable illness are observed, while this is far less the case in our less-preventable disease group. Regional economic conditions seem to have a direct impact on depression among Spanish men (y-stand. OR = 1.04 [95 % CI: 1.01-1.07]). Diabetes is associated with cross-regional differences in low work intensity among men (y-stand. OR = 1.02 [95 % CI: 1.00-1.05]) and women (y-stand. OR = 1.04 [95 % CI: 1.01-1.06]). Economic contraction increases the likelihood of having diabetes among men (y-stand. OR = 1.04 [95 % CI: 1.01-1.06]), and smaller decreases in the real GDP growth rate are associated with lower likelihood of myocardial infarction among women (y-stand. OR = 0.83 [95 % CI: 0.69-1.00]). Finally, there are interesting associations between the macroeconomic changes across the crisis period and the likelihood of suffering from myocardial infarction among lower educated groups, and the likelihood of having depression and diabetes among less-educated women. Our findings partially support the predictions of the FCT for Spain. The crisis effects on health emerge especially in the case of our more-preventable illnesses and among lower educated groups. Health inequalities in Spain could increase rapidly in the coming years due to the differential effects of recession on socioeconomic groups.

The Frequency of Fitness Peak Shifts Is Increased at Expanding Range Margins Due to Mutation Surfing

PubMed Central

Burton, Olivia J.; Travis, Justin M. J.

2008-01-01

Dynamic species' ranges, those that are either invasive or shifting in response to environmental change, are the focus of much recent interest in ecology, evolution, and genetics. Understanding how range expansions can shape evolutionary trajectories requires the consideration of nonneutral variability and genetic architecture, yet the majority of empirical and theoretical work to date has explored patterns of neutral variability. Here we use forward computer simulations of population growth, dispersal, and mutation to explore how range-shifting dynamics can influence evolution on rugged fitness landscapes. We employ a two-locus model, incorporating sign epistasis, and find that there is an increased likelihood of fitness peak shifts during a period of range expansion. Maladapted valley genotypes can accumulate at an expanding range front through a phenomenon called mutation surfing, which increases the likelihood that a mutation leading to a higher peak will occur. Our results indicate that most peak shifts occur close to the expanding front. We also demonstrate that periods of range shifting are especially important for peak shifting in species with narrow geographic distributions. Our results imply that trajectories on rugged fitness landscapes can be modified substantially when ranges are dynamic. PMID:18505864

Reorganization of interaction networks modulates the persistence of species in late successional stages.

PubMed

Saavedra, Serguei; Cenci, Simone; Del-Val, Ek; Boege, Karina; Rohr, Rudolf P

2017-09-01

Ecological interaction networks constantly reorganize as interspecific interactions change across successional stages and environmental gradients. This reorganization can also be associated with the extent to which species change their preference for types of niches available in their local sites. Despite the pervasiveness of these interaction changes, previous studies have revealed that network reorganizations have a minimal or insignificant effect on global descriptors of network architecture, such as connectance, modularity and nestedness. However, little is known about whether these reorganizations may have an effect on community dynamics and composition. To answer the question above, we study the multi-year dynamics and reorganization of plant-herbivore interaction networks across secondary successional stages of a tropical dry forest. We develop new quantitative tools based on a structural stability approach to estimate the potential impact of network reorganization on species persistence. Then, we investigate whether this impact can explain the likelihood of persistence of herbivore species in the observed communities. We find that resident (early-arriving) herbivore species increase their likelihood of persistence across time and successional stages. Importantly, we demonstrate that, in late successional stages, the reorganization of interactions among resident species has a strong inhibitory effect on the likelihood of persistence of colonizing (late-arriving) herbivores. These findings support earlier predictions suggesting that, in mature communities, changes of species interactions can act as community-control mechanisms (also known as priority effects). Furthermore, our results illustrate that the dynamics and composition of ecological communities cannot be fully understood without attention to their reorganization processes, despite the invariability of global network properties. © 2017 The Authors. Journal of Animal Ecology © 2017 British Ecological Society.

A state space approach for piecewise-linear recurrent neural networks for identifying computational dynamics from neural measurements.

PubMed

Durstewitz, Daniel

2017-06-01

The computational and cognitive properties of neural systems are often thought to be implemented in terms of their (stochastic) network dynamics. Hence, recovering the system dynamics from experimentally observed neuronal time series, like multiple single-unit recordings or neuroimaging data, is an important step toward understanding its computations. Ideally, one would not only seek a (lower-dimensional) state space representation of the dynamics, but would wish to have access to its statistical properties and their generative equations for in-depth analysis. Recurrent neural networks (RNNs) are a computationally powerful and dynamically universal formal framework which has been extensively studied from both the computational and the dynamical systems perspective. Here we develop a semi-analytical maximum-likelihood estimation scheme for piecewise-linear RNNs (PLRNNs) within the statistical framework of state space models, which accounts for noise in both the underlying latent dynamics and the observation process. The Expectation-Maximization algorithm is used to infer the latent state distribution, through a global Laplace approximation, and the PLRNN parameters iteratively. After validating the procedure on toy examples, and using inference through particle filters for comparison, the approach is applied to multiple single-unit recordings from the rodent anterior cingulate cortex (ACC) obtained during performance of a classical working memory task, delayed alternation. Models estimated from kernel-smoothed spike time data were able to capture the essential computational dynamics underlying task performance, including stimulus-selective delay activity. The estimated models were rarely multi-stable, however, but rather were tuned to exhibit slow dynamics in the vicinity of a bifurcation point. In summary, the present work advances a semi-analytical (thus reasonably fast) maximum-likelihood estimation framework for PLRNNs that may enable to recover relevant aspects of the nonlinear dynamics underlying observed neuronal time series, and directly link these to computational properties.

Statistical methods for analysis of radiation effects with tumor and dose location-specific information with application to the WECARE study of asynchronous contralateral breast cancer

PubMed Central

Langholz, Bryan; Thomas, Duncan C.; Stovall, Marilyn; Smith, Susan A.; Boice, John D.; Shore, Roy E.; Bernstein, Leslie; Lynch, Charles F.; Zhang, Xinbo; Bernstein, Jonine L.

2009-01-01

Summary Methods for the analysis of individually matched case-control studies with location-specific radiation dose and tumor location information are described. These include likelihood methods for analyses that just use cases with precise location of tumor information and methods that also include cases with imprecise tumor location information. The theory establishes that each of these likelihood based methods estimates the same radiation rate ratio parameters, within the context of the appropriate model for location and subject level covariate effects. The underlying assumptions are characterized and the potential strengths and limitations of each method are described. The methods are illustrated and compared using the WECARE study of radiation and asynchronous contralateral breast cancer. PMID:18647297

Pippi — Painless parsing, post-processing and plotting of posterior and likelihood samples

NASA Astrophysics Data System (ADS)

Scott, Pat

2012-11-01

Interpreting samples from likelihood or posterior probability density functions is rarely as straightforward as it seems it should be. Producing publication-quality graphics of these distributions is often similarly painful. In this short note I describe pippi, a simple, publicly available package for parsing and post-processing such samples, as well as generating high-quality PDF graphics of the results. Pippi is easily and extensively configurable and customisable, both in its options for parsing and post-processing samples, and in the visual aspects of the figures it produces. I illustrate some of these using an existing supersymmetric global fit, performed in the context of a gamma-ray search for dark matter. Pippi can be downloaded and followed at http://github.com/patscott/pippi.

Identifying Factors That Increase the Likelihood for Alcohol-Induced Blackouts in the Prepartying Context

PubMed Central

LaBrie, Joseph W.; Hummer, Justin; Kenney, Shannon; Lac, Andrew; Pedersen, Eric

2015-01-01

The present study examined risk factors related to “blacking out” (e.g., temporary periods of memory loss during drinking) during preparty drinking events (i.e., pregaming, predrinking). Participants were students from two universities on the West Coast who reported past month prepartying (N = 2,546) in online surveys administered in the fall of 2008. Among these students, 25% (n = 636) reported blacking out during at least one occasion in which they prepartied in the past month. A logistic regression model underscored that Greek student affiliation, family history of alcohol abuse, frequency of prepartying, and both playing drinking games and consuming shots of liquor while prepartying increased the likelihood of blacking out. Limitations and implications for future research and collegiate prevention strategies are discussed. PMID:21222521

Cosmic shear measurement with maximum likelihood and maximum a posteriori inference

NASA Astrophysics Data System (ADS)

Hall, Alex; Taylor, Andy

2017-06-01

We investigate the problem of noise bias in maximum likelihood and maximum a posteriori estimators for cosmic shear. We derive the leading and next-to-leading order biases and compute them in the context of galaxy ellipticity measurements, extending previous work on maximum likelihood inference for weak lensing. We show that a large part of the bias on these point estimators can be removed using information already contained in the likelihood when a galaxy model is specified, without the need for external calibration. We test these bias-corrected estimators on simulated galaxy images similar to those expected from planned space-based weak lensing surveys, with promising results. We find that the introduction of an intrinsic shape prior can help with mitigation of noise bias, such that the maximum a posteriori estimate can be made less biased than the maximum likelihood estimate. Second-order terms offer a check on the convergence of the estimators, but are largely subdominant. We show how biases propagate to shear estimates, demonstrating in our simple set-up that shear biases can be reduced by orders of magnitude and potentially to within the requirements of planned space-based surveys at mild signal-to-noise ratio. We find that second-order terms can exhibit significant cancellations at low signal-to-noise ratio when Gaussian noise is assumed, which has implications for inferring the performance of shear-measurement algorithms from simplified simulations. We discuss the viability of our point estimators as tools for lensing inference, arguing that they allow for the robust measurement of ellipticity and shear.

Dynamics of sustained use and abandonment of clean cooking systems: study protocol for community-based system dynamics modeling.

PubMed

Kumar, Praveen; Chalise, Nishesh; Yadama, Gautam N

2016-04-26

More than 3 billion of the world's population are affected by household air pollution from relying on unprocessed solid fuels for heating and cooking. Household air pollution is harmful to human health, climate, and environment. Sustained uptake and use of cleaner cooking technologies and fuels are proposed as solutions to this problem. In this paper, we present our study protocol aimed at understanding multiple interacting feedback mechanisms involved in the dynamic behavior between social, ecological, and technological systems driving sustained use or abandonment of cleaner cooking technologies among the rural poor in India. This study uses a comparative case study design to understand the dynamics of sustained use or abandonment of cleaner cooking technologies and fuels in four rural communities of Rajasthan, India. The study adopts a community based system dynamics modeling approach. We describe our approach of using community based system dynamics with rural communities to delineate the feedback mechanisms involved in the uptake and sustainment of clean cooking technologies. We develop a reference mode with communities showing the trend over time of use or abandonment of cleaner cooking technologies and fuels in these communities. Subsequently, the study develops a system dynamics model with communities to understand the complex sub-systems driving the behavior in these communities as reflected in the reference mode. We use group model building techniques to facilitate participation of relevant stakeholders in the four communities and elicit a narrative describing the feedback mechanisms underlying sustained adoption or abandonment of cleaner cooking technologies. In understanding the dynamics of feedback mechanisms in the uptake and exclusive use of cleaner cooking systems, we increase the likelihood of dissemination and implementation of efficacious interventions into everyday settings to improve the health and wellbeing of women and children most affected by household air pollution. The challenge is not confined to developing robust technical solutions to reduce household air pollution and exposure to improve respiratory health, and prevent associated diseases. The bigger challenge is to disseminate and implement cleaner cooking technologies and fuels in the context of various social, behavioral, and economic constraints faced by poor households and communities. The Institutional Review Board of Washington University in St. Louis has exempted community based system dynamics modeling from review.

A Framework for Context Sensitive Risk-Based Access Control in Medical Information Systems

PubMed Central

Choi, Donghee; Kim, Dohoon; Park, Seog

2015-01-01

Since the access control environment has changed and the threat of insider information leakage has come to the fore, studies on risk-based access control models that decide access permissions dynamically have been conducted vigorously. Medical information systems should protect sensitive data such as medical information from insider threat and enable dynamic access control depending on the context such as life-threatening emergencies. In this paper, we suggest an approach and framework for context sensitive risk-based access control suitable for medical information systems. This approach categorizes context information, estimating and applying risk through context- and treatment-based permission profiling and specifications by expanding the eXtensible Access Control Markup Language (XACML) to apply risk. The proposed framework supports quick responses to medical situations and prevents unnecessary insider data access through dynamic access authorization decisions in accordance with the severity of the context and treatment. PMID:26075013

Research on dynamic performance design of mobile phone application based on context awareness

NASA Astrophysics Data System (ADS)

Bo, Zhang

2018-05-01

It aims to explore the dynamic performance of different mobile phone applications and the user's cognitive differences, reduce the cognitive burden, and enhance the sense of experience. By analyzing the dynamic design performance in four different interactive contexts, and constructing the framework of information service process in the interactive context perception and the two perception principles of the cognitive consensus between designer and user, and the two kinds of knowledge in accordance with the perception principles. The analysis of the context will help users sense the dynamic performance more intuitively, so that the details of interaction will be performed more vividly and smoothly, thus enhance user's experience in the interactive process. The common perception experience enables designers and users to produce emotional resonance in different interactive contexts, and help them achieve rapid understanding of interactive content and perceive the logic and hierarchy of the content and the structure, therefore the effectiveness of mobile applications will be improved.

Theoretical Analysis of Penalized Maximum-Likelihood Patlak Parametric Image Reconstruction in Dynamic PET for Lesion Detection.

PubMed

Yang, Li; Wang, Guobao; Qi, Jinyi

2016-04-01

Detecting cancerous lesions is a major clinical application of emission tomography. In a previous work, we studied penalized maximum-likelihood (PML) image reconstruction for lesion detection in static PET. Here we extend our theoretical analysis of static PET reconstruction to dynamic PET. We study both the conventional indirect reconstruction and direct reconstruction for Patlak parametric image estimation. In indirect reconstruction, Patlak parametric images are generated by first reconstructing a sequence of dynamic PET images, and then performing Patlak analysis on the time activity curves (TACs) pixel-by-pixel. In direct reconstruction, Patlak parametric images are estimated directly from raw sinogram data by incorporating the Patlak model into the image reconstruction procedure. PML reconstruction is used in both the indirect and direct reconstruction methods. We use a channelized Hotelling observer (CHO) to assess lesion detectability in Patlak parametric images. Simplified expressions for evaluating the lesion detectability have been derived and applied to the selection of the regularization parameter value to maximize detection performance. The proposed method is validated using computer-based Monte Carlo simulations. Good agreements between the theoretical predictions and the Monte Carlo results are observed. Both theoretical predictions and Monte Carlo simulation results show the benefit of the indirect and direct methods under optimized regularization parameters in dynamic PET reconstruction for lesion detection, when compared with the conventional static PET reconstruction.

Activating Basic Category Exemplars in Sentence Contexts: A Dynamical Account

ERIC Educational Resources Information Center

Raczaszek-Leonardi, Joanna; Shapiro, Lewis P.; Tuller, Betty; Kelso, J. A. Scott

2008-01-01

This paper examines the influence of context on the processing of category names embedded in sentences. The investigation focuses on the nature of information available immediately after such a word is heard as well as on the dynamics of adaptation to context. An on-line method (Cross Modal Lexical Priming) was used to trace how this process…

Predicting critical transitions in dynamical systems from time series using nonstationary probability density modeling.

PubMed

Kwasniok, Frank

2013-11-01

A time series analysis method for predicting the probability density of a dynamical system is proposed. A nonstationary parametric model of the probability density is estimated from data within a maximum likelihood framework and then extrapolated to forecast the future probability density and explore the system for critical transitions or tipping points. A full systematic account of parameter uncertainty is taken. The technique is generic, independent of the underlying dynamics of the system. The method is verified on simulated data and then applied to prediction of Arctic sea-ice extent.

The Role of Dysfunctional Myths in a Decision-Making Process under Bounded Rationality: A Complex Dynamical Systems Perspective.

PubMed

Stamovlasis, Dimitrios; Vaiopoulou, Julie

2017-07-01

The present study examines the factors influencing a decision-making process, with specific focus on the role of dysfunctional myths (DM). DM are thoughts or beliefs that are rather irrational, however influential to people's decisions. In this paper a decision-making process regarding the career choice of university students majoring in natural sciences and education (N=496) is examined by analyzing survey data taken via Career Decision Making Difficulties Questionnaire (CDDQ). The difficulty of making the choice and the certainty about one's decision were the state variables, while the independent variables were factors related to the lack of information or knowledge needed, which actually reflect a bounded rationality. Cusp catastrophe analysis, based on both least squares and maximum likelihood procedures, showed that the nonlinear models predicting the two state variables were superior to linear alternatives. Factors related to lack of knowledge about the steps involved in the process of career decision-making, lack of information about the various occupations, lack of information about self and lack of motivation acted as asymmetry, while dysfunctional myths acted as bifurcation factor for both state variables. The catastrophe model, grounded in empirical data, revealed a unique role for DM and a better interpretation within the context of complexity and the notion of bounded rationality. The analysis opens the nonlinear dynamical systems (NDS) perspective in studying decision-making processes. Theoretical and practical implications are discussed.

Coherent Multimodal Sensory Information Allows Switching between Gravitoinertial Contexts

PubMed Central

Barbiero, Marie; Rousseau, Célia; Papaxanthis, Charalambos; White, Olivier

2017-01-01

Whether the central nervous system is capable to switch between contexts critically depends on experimental details. Motor control studies regularly adopt robotic devices to perturb the dynamics of a certain task. Other approaches investigate motor control by altering the gravitoinertial context itself as in parabolic flights and human centrifuges. In contrast to conventional robotic experiments, where only the hand is perturbed, these gravitoinertial or immersive settings coherently plunge participants into new environments. However, radically different they are, perfect adaptation of motor responses are commonly reported. In object manipulation tasks, this translates into a good matching of the grasping force or grip force to the destabilizing load force. One possible bias in these protocols is the predictability of the forthcoming dynamics. Here we test whether the successful switching and adaptation processes observed in immersive environments are a consequence of the fact that participants can predict the perturbation schedule. We used a short arm human centrifuge to decouple the effects of space and time on the dynamics of an object manipulation task by adding an unnatural explicit position-dependent force. We created different dynamical contexts by asking 20 participants to move the object at three different paces. These contextual sessions were interleaved such that we could simulate concurrent learning. We assessed adaptation by measuring how grip force was adjusted to this unnatural load force. We found that the motor system can switch between new unusual dynamical contexts, as reported by surprisingly well-adjusted grip forces, and that this capacity is not a mere consequence of the ability to predict the time course of the upcoming dynamics. We posit that a coherent flow of multimodal sensory information born in a homogeneous milieu allows switching between dynamical contexts. PMID:28553233

Bologna in Context: A Horizontal Perspective on the Dynamics of Governance Sites for a Europe of Knowledge

ERIC Educational Resources Information Center

Gornitzka, Ase

2010-01-01

This article presents a horizontal perspective on the dynamics of governance sites currently active for the European of Knowledge and places the Bologna process in this wider European level context. It introduces two dynamics of change in political organisation: (a) institutional differentiation and specialisation and (b) the interaction between…

To Learn and to Construct Knowledge in the Context of Work with Adult Education: A Portuguese Case Study

ERIC Educational Resources Information Center

Loureiro, Armando; Caria, Telmo H.

2013-01-01

Work contexts are frequently referred to as spaces of learning and production of individual and/or collective knowledge. In such contexts specific dynamics are developed which cause the processes of learning and of knowledge production to have particularities. This paper aims at accounting for some dynamics that are associated with those…

Metadata behind the Interoperability of Wireless Sensor Networks

PubMed Central

Ballari, Daniela; Wachowicz, Monica; Callejo, Miguel Angel Manso

2009-01-01

Wireless Sensor Networks (WSNs) produce changes of status that are frequent, dynamic and unpredictable, and cannot be represented using a linear cause-effect approach. Consequently, a new approach is needed to handle these changes in order to support dynamic interoperability. Our approach is to introduce the notion of context as an explicit representation of changes of a WSN status inferred from metadata elements, which in turn, leads towards a decision-making process about how to maintain dynamic interoperability. This paper describes the developed context model to represent and reason over different WSN status based on four types of contexts, which have been identified as sensing, node, network and organisational contexts. The reasoning has been addressed by developing contextualising and bridges rules. As a result, we were able to demonstrate how contextualising rules have been used to reason on changes of WSN status as a first step towards maintaining dynamic interoperability. PMID:22412330

Metadata behind the Interoperability of Wireless Sensor Networks.

PubMed

Ballari, Daniela; Wachowicz, Monica; Callejo, Miguel Angel Manso

2009-01-01

Wireless Sensor Networks (WSNs) produce changes of status that are frequent, dynamic and unpredictable, and cannot be represented using a linear cause-effect approach. Consequently, a new approach is needed to handle these changes in order to support dynamic interoperability. Our approach is to introduce the notion of context as an explicit representation of changes of a WSN status inferred from metadata elements, which in turn, leads towards a decision-making process about how to maintain dynamic interoperability. This paper describes the developed context model to represent and reason over different WSN status based on four types of contexts, which have been identified as sensing, node, network and organisational contexts. The reasoning has been addressed by developing contextualising and bridges rules. As a result, we were able to demonstrate how contextualising rules have been used to reason on changes of WSN status as a first step towards maintaining dynamic interoperability.

Dynamic access control model for privacy preserving personalized healthcare in cloud environment.

PubMed

Son, Jiseong; Kim, Jeong-Dong; Na, Hong-Seok; Baik, Doo-Kwon

2015-01-01

When sharing and storing healthcare data in a cloud environment, access control is a central issue for preserving data privacy as a patient's personal health data may be accessed without permission from many stakeholders. Specifically, dynamic authorization for the access of data is required because personal health data is stored in cloud storage via wearable devices. Therefore, we propose a dynamic access control model for preserving the privacy of personal healthcare data in a cloud environment. The proposed model considers context information for dynamic access. According to the proposed model, access control can be dynamically determined by changing the context information; this means that even for a subject with the same role in the cloud, access permission is defined differently depending on the context information and access condition. Furthermore, we experiment the ability of the proposed model to provide correct responses by representing a dynamic access decision with real-life personalized healthcare system scenarios.

F-111C Flight Data Reduction and Analysis Procedures

DTIC Science & Technology

1990-12-01

BPHI NO 24 BTHE YES 25 BPSI NO 26 BH YES 27 LVEL NO 28 LBET NO 29 LALP YES 30 LPHI NO 31 LTHE NO 32 LPSI NO 33 LH NO 34 TABLE 2 INPUTS I Ax YES 2 Av NO...03 * 51 IJ Appendix G - A priori Data from Six Degree of Free- dom Flight Dynamic Model The six degree of freedom flight dynamic mathematical model of...Estimated Mathematical mode response - > of aircraft !Gauss- Maximum " Newton --- likelihood 4,computational cost Salgorithm function Maximum

Estimating residual fault hitting rates by recapture sampling

NASA Technical Reports Server (NTRS)

Lee, Larry; Gupta, Rajan

1988-01-01

For the recapture debugging design introduced by Nayak (1988) the problem of estimating the hitting rates of the faults remaining in the system is considered. In the context of a conditional likelihood, moment estimators are derived and are shown to be asymptotically normal and fully efficient. Fixed sample properties of the moment estimators are compared, through simulation, with those of the conditional maximum likelihood estimators. Properties of the conditional model are investigated such as the asymptotic distribution of linear functions of the fault hitting frequencies and a representation of the full data vector in terms of a sequence of independent random vectors. It is assumed that the residual hitting rates follow a log linear rate model and that the testing process is truncated when the gaps between the detection of new errors exceed a fixed amount of time.

Links Between Contexts and Middle to Late Childhood Social-Emotional Development.

PubMed

Duong, Jeffrey; Bradshaw, Catherine P

2017-12-01

Guided by the social-emotional learning (SEL) framework, we studied developmental trajectory patterns of five key competency outcomes spanning middle through late childhood: altruism, empathy, self-efficacy, aggression, and hyperactivity. We then assessed their links to middle childhood home, parental, and community contexts. Data from the Institute of Education Sciences' Social and Character Development Program, which comprised nearly 2,400 elementary school students who were followed from Grades 3 through 5, were analyzed using growth mixture modeling. Three trajectory groups emerged for each outcome, which were linked to childhood contexts. Positive parenting was associated with a lower likelihood of following a negative empathy trajectory among children. Neighborhood intergenerational closure promoted a stable self-efficacy trajectory. Residing in a high-risk community was linked to increasing normative beliefs about aggression. These findings suggest an important role of contexts in influencing childhood social-emotional development in the later elementary school years. © Society for Community Research and Action 2017.

Dodging Dysfunctional Dynamics in Power Exchange

ERIC Educational Resources Information Center

Boyd, David P.

2010-01-01

In today's organizations, the impetus for employee empowerment remains strong. By developing an internal talent base, companies increase the likelihood of comprehensive contributions and also engender loyalty within the ranks. A proclivity for power dispersion is evident among many pundits, with some even decreeing it an ethical mandate. Yet, if…

Time series modeling by a regression approach based on a latent process.

PubMed

Chamroukhi, Faicel; Samé, Allou; Govaert, Gérard; Aknin, Patrice

2009-01-01

Time series are used in many domains including finance, engineering, economics and bioinformatics generally to represent the change of a measurement over time. Modeling techniques may then be used to give a synthetic representation of such data. A new approach for time series modeling is proposed in this paper. It consists of a regression model incorporating a discrete hidden logistic process allowing for activating smoothly or abruptly different polynomial regression models. The model parameters are estimated by the maximum likelihood method performed by a dedicated Expectation Maximization (EM) algorithm. The M step of the EM algorithm uses a multi-class Iterative Reweighted Least-Squares (IRLS) algorithm to estimate the hidden process parameters. To evaluate the proposed approach, an experimental study on simulated data and real world data was performed using two alternative approaches: a heteroskedastic piecewise regression model using a global optimization algorithm based on dynamic programming, and a Hidden Markov Regression Model whose parameters are estimated by the Baum-Welch algorithm. Finally, in the context of the remote monitoring of components of the French railway infrastructure, and more particularly the switch mechanism, the proposed approach has been applied to modeling and classifying time series representing the condition measurements acquired during switch operations.

Mutalisk: a web-based somatic MUTation AnaLyIS toolKit for genomic, transcriptional and epigenomic signatures.

PubMed

Lee, Jongkeun; Lee, Andy Jinseok; Lee, June-Koo; Park, Jongkeun; Kwon, Youngoh; Park, Seongyeol; Chun, Hyonho; Ju, Young Seok; Hong, Dongwan

2018-05-22

Somatic genome mutations occur due to combinations of various intrinsic/extrinsic mutational processes and DNA repair mechanisms. Different molecular processes frequently generate different signatures of somatic mutations in their own favored contexts. As a result, the regional somatic mutation rate is dependent on the local DNA sequence, the DNA replication/RNA transcription dynamics and epigenomic chromatin organization landscape in the genome. Here, we propose an online computational framework, termed Mutalisk, which correlates somatic mutations with various genomic, transcriptional and epigenomic features in order to understand mutational processes that contribute to the generation of the mutations. This user-friendly tool explores the presence of localized hypermutations (kataegis), dissects the spectrum of mutations into the maximum likelihood combination of known mutational signatures and associates the mutation density with numerous regulatory elements in the genome. As a result, global patterns of somatic mutations in any query sample can be efficiently screened, thus enabling a deeper understanding of various mutagenic factors. This tool will facilitate more effective downstream analyses of cancer genome sequences to elucidate the diversity of mutational processes underlying the development and clonal evolution of cancer cells. Mutalisk is freely available at http://mutalisk.org.

Innovation adoption: a review of theories and constructs.

PubMed

Wisdom, Jennifer P; Chor, Ka Ho Brian; Hoagwood, Kimberly E; Horwitz, Sarah M

2014-07-01

Many theoretical frameworks seek to describe the dynamic process of the implementation of innovations. Little is known, however, about factors related to decisions to adopt innovations and how the likelihood of adoption of innovations can be increased. Using a narrative synthesis approach, this paper compared constructs theorized to be related to adoption of innovations proposed in existing theoretical frameworks in order to identify characteristics likely to increase adoption of innovations. The overall goal was to identify elements across adoption frameworks that are potentially modifiable and, thus, might be employed to improve the adoption of evidence-based practices. The review identified 20 theoretical frameworks that could be grouped into two broad categories: theories that mainly address the adoption process (N = 10) and theories that address adoption within the context of implementation, diffusion, dissemination, and/or sustainability (N = 10). Constructs of leadership, operational size and structure, innovation fit with norms and values, and attitudes/motivation toward innovations each are mentioned in at least half of the theories, though there were no consistent definitions of measures for these constructs. A lack of precise definitions and measurement of constructs suggests further work is needed to increase our understanding of adoption of innovations.

A propagator matrix method for the Rayleigh-Taylor instability of multiple layers: a case study on crustal delamination in the early Earth

NASA Astrophysics Data System (ADS)

Mondal, Puskar; Korenaga, Jun

2018-03-01

The dispersion relation of the Rayleigh-Taylor instability, a gravitational instability associated with unstable density stratification, is of profound importance in various geophysical contexts. When more than two layers are involved, a semi-analytical technique based on the biharmonic formulation of Stokes flow has been extensively used to obtain such dispersion relation. However, this technique may become cumbersome when applied to lithospheric dynamics, where a number of layers are necessary to represent the continuous variation of viscosity over many orders of magnitude. Here, we present an alternative and more efficient method based on the propagator matrix formulation of Stokes flow. With this approach, the original instability problem is reduced to a compact eigenvalue equation whose size is solely determined by the number of primary density contrasts. We apply this new technique to the stability of the early crust, and combined with the Monte Carlo sensitivity analysis, we derive an empirical formula to compute the growth rate of the Rayleigh-Taylor instability for this particular geophysical setting. Our analysis indicates that the likelihood of crustal delamination hinges critically on the effective viscosity of eclogite.

Innovation Adoption: A Review of Theories and Constructs

PubMed Central

Chor, Ka Ho Brian; Hoagwood, Kimberly E.; Horwitz, Sarah M.

2013-01-01

Many theoretical frameworks seek to describe the dynamic process of the implementation of innovations. Little is known, however, about factors related to decisions to adopt innovations and how the likelihood of adoption of innovations can be increased. Using a narrative synthesis approach, this paper compared constructs theorized to be related to adoption of innovations proposed in existing theoretical frameworks in order to identify characteristics likely to increase adoption of innovations. The overall goal was to identify elements across adoption frameworks that are potentially modifiable and, thus, might be employed to improve the adoption of evidence-based practices. The review identified 20 theoretical frameworks that could be grouped into two broad categories: theories that mainly address the adoption process (N = 10) and theories that address adoption within the context of implementation, diffusion, dissemination, and/or sustainability (N = 10). Constructs of leadership, operational size and structure, innovation fit with norms and values, and attitudes/motivation toward innovations each are mentioned in at least half of the theories, though there were no consistent definitions of measures for these constructs. A lack of precise definitions and measurement of constructs suggests further work is needed to increase our understanding of adoption of innovations. PMID:23549911

Data and animal management software for large-scale phenotype screening.

PubMed

Ching, Keith A; Cooke, Michael P; Tarantino, Lisa M; Lapp, Hilmar

2006-04-01

The mouse N-ethyl-N-nitrosourea (ENU) mutagenesis program at the Genomics Institute of the Novartis Research Foundation (GNF) uses MouseTRACS to analyze phenotype screens and manage animal husbandry. MouseTRACS is a Web-based laboratory informatics system that electronically records and organizes mouse colony operations, prints cage cards, tracks inventory, manages requests, and reports Institutional Animal Care and Use Committee (IACUC) protocol usage. For efficient phenotype screening, MouseTRACS identifies mutants, visualizes data, and maps mutations. It displays and integrates phenotype and genotype data using likelihood odds ratio (LOD) plots of genetic linkage between genotype and phenotype. More detailed mapping intervals show individual single nucleotide polymorphism (SNP) markers in the context of phenotype. In addition, dynamically generated pedigree diagrams and inventory reports linked to screening results summarize the inheritance pattern and the degree of penetrance. MouseTRACS displays screening data in tables and uses standard charts such as box plots, histograms, scatter plots, and customized charts looking at clustered mice or cross pedigree comparisons. In summary, MouseTRACS enables the efficient screening, analysis, and management of thousands of animals to find mutant mice and identify novel gene functions. MouseTRACS is available under an open source license at http://www.mousetracs.sourceforge.net.

Exploiting social media for Army operations: Syrian crisis use case

NASA Astrophysics Data System (ADS)

Kase, Sue E.; Bowman, Elizabeth K.; Al Amin, Tanvir; Abdelzaher, Tarek

2014-05-01

Millions of people exchange user-generated information through online social media (SM) services. The prevalence of SM use globally and its growing significance to the evolution of events has attracted the attention of the Army and other agencies charged with protecting national security interests. The information exchanged in SM sites and the networks of people who interact with these online communities can provide value to Army intelligence efforts. SM could facilitate the Military Decision Making Process by providing ongoing assessment of military actions from a local citizen perspective. Despite potential value, there are significant technological barriers to leveraging SM. SM collection and analysis are difficult in the dynamic SM environment and deception is a real concern. This paper introduces a credibility analysis approach and prototype fact-finding technology called the "Apollo Fact-finder" that mitigates the problem of inaccurate or falsified SM data. Apollo groups data into sets (or claims), corroborating specific observations, then iteratively assesses both claim and source credibility resulting in a ranking of claims by likelihood of occurrence. These credibility analysis approaches are discussed in the context of a conflict event, the Syrian civil war, and applied to tweets collected in the aftermath of the Syrian chemical weapons crisis.

A new model to predict weak-lensing peak counts. II. Parameter constraint strategies

NASA Astrophysics Data System (ADS)

Lin, Chieh-An; Kilbinger, Martin

2015-11-01

Context. Peak counts have been shown to be an excellent tool for extracting the non-Gaussian part of the weak lensing signal. Recently, we developed a fast stochastic forward model to predict weak-lensing peak counts. Our model is able to reconstruct the underlying distribution of observables for analysis. Aims: In this work, we explore and compare various strategies for constraining a parameter using our model, focusing on the matter density Ωm and the density fluctuation amplitude σ8. Methods: First, we examine the impact from the cosmological dependency of covariances (CDC). Second, we perform the analysis with the copula likelihood, a technique that makes a weaker assumption than does the Gaussian likelihood. Third, direct, non-analytic parameter estimations are applied using the full information of the distribution. Fourth, we obtain constraints with approximate Bayesian computation (ABC), an efficient, robust, and likelihood-free algorithm based on accept-reject sampling. Results: We find that neglecting the CDC effect enlarges parameter contours by 22% and that the covariance-varying copula likelihood is a very good approximation to the true likelihood. The direct techniques work well in spite of noisier contours. Concerning ABC, the iterative process converges quickly to a posterior distribution that is in excellent agreement with results from our other analyses. The time cost for ABC is reduced by two orders of magnitude. Conclusions: The stochastic nature of our weak-lensing peak count model allows us to use various techniques that approach the true underlying probability distribution of observables, without making simplifying assumptions. Our work can be generalized to other observables where forward simulations provide samples of the underlying distribution.

The Impact of Full Time Enrollment in the First Semester on Community College Transfer Rates: New Evidence from Texas with Pre-College Determinants

ERIC Educational Resources Information Center

Park, Toby J.

2015-01-01

Background/Context: Recent developments in state-level policy have begun to require, incentivize, and/or encourage students at community colleges to enroll full time in an effort to increase the likelihood that students will persist and transfer to four-year institution where they will be able to complete their bachelor's degree. Often, these…

Effects of context and individual differences on the processing of taboo words.

PubMed

Christianson, Kiel; Zhou, Peiyun; Palmer, Cassie; Raizen, Adina

2017-07-01

Previous studies suggest that taboo words are special in regards to language processing. Findings from the studies have led to the formation of two theories, global resource theory and binding theory, of taboo word processing. The current study investigates how readers process taboo words embedded in sentences during silent reading. In two experiments, measures collected include eye movement data, accuracy and reaction time measures for recalling probe words within the sentences, and individual differences in likelihood of being offended by taboo words. Although certain aspects of the results support both theories, as the likelihood of a person being offended by a taboo word influenced some measures, neither theory sufficiently predicts or describes the effects observed. The results are interpreted as evidence that processing effects ascribed to taboo words are largely, but not completely, attributable to the context in which they are used and the individual attitudes of the people who hear/read them. The results also demonstrate the importance of investigating taboo words in naturalistic language processing paradigms. A revised theory of taboo word processing is proposed that incorporates both global resource theory and binding theory along with the sociolinguistic factors and individual differences that largely drive the effects observed here. Copyright © 2017 Elsevier B.V. All rights reserved.

Fifty years of progress in speech and speaker recognition

NASA Astrophysics Data System (ADS)

Furui, Sadaoki

2004-10-01

Speech and speaker recognition technology has made very significant progress in the past 50 years. The progress can be summarized by the following changes: (1) from template matching to corpus-base statistical modeling, e.g., HMM and n-grams, (2) from filter bank/spectral resonance to Cepstral features (Cepstrum + DCepstrum + DDCepstrum), (3) from heuristic time-normalization to DTW/DP matching, (4) from gdistanceh-based to likelihood-based methods, (5) from maximum likelihood to discriminative approach, e.g., MCE/GPD and MMI, (6) from isolated word to continuous speech recognition, (7) from small vocabulary to large vocabulary recognition, (8) from context-independent units to context-dependent units for recognition, (9) from clean speech to noisy/telephone speech recognition, (10) from single speaker to speaker-independent/adaptive recognition, (11) from monologue to dialogue/conversation recognition, (12) from read speech to spontaneous speech recognition, (13) from recognition to understanding, (14) from single-modality (audio signal only) to multi-modal (audio/visual) speech recognition, (15) from hardware recognizer to software recognizer, and (16) from no commercial application to many practical commercial applications. Most of these advances have taken place in both the fields of speech recognition and speaker recognition. The majority of technological changes have been directed toward the purpose of increasing robustness of recognition, including many other additional important techniques not noted above.

Is there a hierarchy of social inferences? The likelihood and speed of inferring intentionality, mind, and personality.

PubMed

Malle, Bertram F; Holbrook, Jess

2012-04-01

People interpret behavior by making inferences about agents' intentionality, mind, and personality. Past research studied such inferences 1 at a time; in real life, people make these inferences simultaneously. The present studies therefore examined whether 4 major inferences (intentionality, desire, belief, and personality), elicited simultaneously in response to an observed behavior, might be ordered in a hierarchy of likelihood and speed. To achieve generalizability, the studies included a wide range of stimulus behaviors, presented them verbally and as dynamic videos, and assessed inferences both in a retrieval paradigm (measuring the likelihood and speed of accessing inferences immediately after they were made) and in an online processing paradigm (measuring the speed of forming inferences during behavior observation). Five studies provide evidence for a hierarchy of social inferences-from intentionality and desire to belief to personality-that is stable across verbal and visual presentations and that parallels the order found in developmental and primate research. (c) 2012 APA, all rights reserved.

User's manual for MMLE3, a general FORTRAN program for maximum likelihood parameter estimation

NASA Technical Reports Server (NTRS)

Maine, R. E.; Iliff, K. W.

1980-01-01

A user's manual for the FORTRAN IV computer program MMLE3 is described. It is a maximum likelihood parameter estimation program capable of handling general bilinear dynamic equations of arbitrary order with measurement noise and/or state noise (process noise). The theory and use of the program is described. The basic MMLE3 program is quite general and, therefore, applicable to a wide variety of problems. The basic program can interact with a set of user written problem specific routines to simplify the use of the program on specific systems. A set of user routines for the aircraft stability and control derivative estimation problem is provided with the program.

Predictors of verb-mediated anticipatory eye movements in the visual world.

PubMed

Hintz, Florian; Meyer, Antje S; Huettig, Falk

2017-09-01

Many studies have demonstrated that listeners use information extracted from verbs to guide anticipatory eye movements to objects in the visual context that satisfy the selection restrictions of the verb. An important question is what underlies such verb-mediated anticipatory eye gaze. Based on empirical and theoretical suggestions, we investigated the influence of 5 potential predictors of this behavior: functional associations and general associations between verb and target object, as well as the listeners' production fluency, receptive vocabulary knowledge, and nonverbal intelligence. In 3 eye-tracking experiments, participants looked at sets of 4 objects and listened to sentences where the final word was predictable or not predictable (e.g., "The man peels/draws an apple"). On predictable trials only the target object, but not the distractors, were functionally and associatively related to the verb. In Experiments 1 and 2, objects were presented before the verb was heard. In Experiment 3, participants were given a short preview of the display after the verb was heard. Functional associations and receptive vocabulary were found to be important predictors of verb-mediated anticipatory eye gaze independent of the amount of contextual visual input. General word associations did not and nonverbal intelligence was only a very weak predictor of anticipatory eye movements. Participants' production fluency correlated positively with the likelihood of anticipatory eye movements when participants were given the long but not the short visual display preview. These findings fit best with a pluralistic approach to predictive language processing in which multiple mechanisms, mediating factors, and situational context dynamically interact. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Identification of dynamic systems, theory and formulation

NASA Technical Reports Server (NTRS)

Maine, R. E.; Iliff, K. W.

1985-01-01

The problem of estimating parameters of dynamic systems is addressed in order to present the theoretical basis of system identification and parameter estimation in a manner that is complete and rigorous, yet understandable with minimal prerequisites. Maximum likelihood and related estimators are highlighted. The approach used requires familiarity with calculus, linear algebra, and probability, but does not require knowledge of stochastic processes or functional analysis. The treatment emphasizes unification of the various areas in estimation in dynamic systems is treated as a direct outgrowth of the static system theory. Topics covered include basic concepts and definitions; numerical optimization methods; probability; statistical estimators; estimation in static systems; stochastic processes; state estimation in dynamic systems; output error, filter error, and equation error methods of parameter estimation in dynamic systems, and the accuracy of the estimates.

[Effects of attitude formation, persuasive message, and source expertise on attitude change: an examination based on the Elaboration Likelihood Model and the Attitude Formation Theory].

PubMed

Nakamura, M; Saito, K; Wakabayashi, M

1990-04-01

The purpose of this study was to investigate how attitude change is generated by the recipient's degree of attitude formation, evaluative-emotional elements contained in the persuasive messages, and source expertise as a peripheral cue in the persuasion context. Hypotheses based on the Attitude Formation Theory of Mizuhara (1982) and the Elaboration Likelihood Model of Petty and Cacioppo (1981, 1986) were examined. Eighty undergraduate students served as subjects in the experiment, the first stage of which involving manipulating the degree of attitude formation with respect to nuclear power development. Then, the experimenter presented persuasive messages with varying combinations of evaluative-emotional elements from a source with either high or low expertise on the subject. Results revealed a significant interaction effect on attitude change among attitude formation, persuasive message and the expertise of the message source. That is, high attitude formation subjects resisted evaluative-emotional persuasion from the high expertise source while low attitude formation subjects changed their attitude when exposed to the same persuasive message from a low expertise source. Results exceeded initial predictions based on the Attitude Formation Theory and the Elaboration Likelihood Model.

Normal Theory Two-Stage ML Estimator When Data Are Missing at the Item Level

PubMed Central

Savalei, Victoria; Rhemtulla, Mijke

2017-01-01

In many modeling contexts, the variables in the model are linear composites of the raw items measured for each participant; for instance, regression and path analysis models rely on scale scores, and structural equation models often use parcels as indicators of latent constructs. Currently, no analytic estimation method exists to appropriately handle missing data at the item level. Item-level multiple imputation (MI), however, can handle such missing data straightforwardly. In this article, we develop an analytic approach for dealing with item-level missing data—that is, one that obtains a unique set of parameter estimates directly from the incomplete data set and does not require imputations. The proposed approach is a variant of the two-stage maximum likelihood (TSML) methodology, and it is the analytic equivalent of item-level MI. We compare the new TSML approach to three existing alternatives for handling item-level missing data: scale-level full information maximum likelihood, available-case maximum likelihood, and item-level MI. We find that the TSML approach is the best analytic approach, and its performance is similar to item-level MI. We recommend its implementation in popular software and its further study. PMID:29276371

Normal Theory Two-Stage ML Estimator When Data Are Missing at the Item Level.

PubMed

Savalei, Victoria; Rhemtulla, Mijke

2017-08-01

In many modeling contexts, the variables in the model are linear composites of the raw items measured for each participant; for instance, regression and path analysis models rely on scale scores, and structural equation models often use parcels as indicators of latent constructs. Currently, no analytic estimation method exists to appropriately handle missing data at the item level. Item-level multiple imputation (MI), however, can handle such missing data straightforwardly. In this article, we develop an analytic approach for dealing with item-level missing data-that is, one that obtains a unique set of parameter estimates directly from the incomplete data set and does not require imputations. The proposed approach is a variant of the two-stage maximum likelihood (TSML) methodology, and it is the analytic equivalent of item-level MI. We compare the new TSML approach to three existing alternatives for handling item-level missing data: scale-level full information maximum likelihood, available-case maximum likelihood, and item-level MI. We find that the TSML approach is the best analytic approach, and its performance is similar to item-level MI. We recommend its implementation in popular software and its further study.

Parameter estimation of history-dependent leaky integrate-and-fire neurons using maximum-likelihood methods

PubMed Central

Dong, Yi; Mihalas, Stefan; Russell, Alexander; Etienne-Cummings, Ralph; Niebur, Ernst

2012-01-01

When a neuronal spike train is observed, what can we say about the properties of the neuron that generated it? A natural way to answer this question is to make an assumption about the type of neuron, select an appropriate model for this type, and then to choose the model parameters as those that are most likely to generate the observed spike train. This is the maximum likelihood method. If the neuron obeys simple integrate and fire dynamics, Paninski, Pillow, and Simoncelli (2004) showed that its negative log-likelihood function is convex and that its unique global minimum can thus be found by gradient descent techniques. The global minimum property requires independence of spike time intervals. Lack of history dependence is, however, an important constraint that is not fulfilled in many biological neurons which are known to generate a rich repertoire of spiking behaviors that are incompatible with history independence. Therefore, we expanded the integrate and fire model by including one additional variable, a variable threshold (Mihalas & Niebur, 2009) allowing for history-dependent firing patterns. This neuronal model produces a large number of spiking behaviors while still being linear. Linearity is important as it maintains the distribution of the random variables and still allows for maximum likelihood methods to be used. In this study we show that, although convexity of the negative log-likelihood is not guaranteed for this model, the minimum of the negative log-likelihood function yields a good estimate for the model parameters, in particular if the noise level is treated as a free parameter. Furthermore, we show that a nonlinear function minimization method (r-algorithm with space dilation) frequently reaches the global minimum. PMID:21851282

A Bayesian Alternative for Multi-objective Ecohydrological Model Specification

NASA Astrophysics Data System (ADS)

Tang, Y.; Marshall, L. A.; Sharma, A.; Ajami, H.

2015-12-01

Process-based ecohydrological models combine the study of hydrological, physical, biogeochemical and ecological processes of the catchments, which are usually more complex and parametric than conceptual hydrological models. Thus, appropriate calibration objectives and model uncertainty analysis are essential for ecohydrological modeling. In recent years, Bayesian inference has become one of the most popular tools for quantifying the uncertainties in hydrological modeling with the development of Markov Chain Monte Carlo (MCMC) techniques. Our study aims to develop appropriate prior distributions and likelihood functions that minimize the model uncertainties and bias within a Bayesian ecohydrological framework. In our study, a formal Bayesian approach is implemented in an ecohydrological model which combines a hydrological model (HyMOD) and a dynamic vegetation model (DVM). Simulations focused on one objective likelihood (Streamflow/LAI) and multi-objective likelihoods (Streamflow and LAI) with different weights are compared. Uniform, weakly informative and strongly informative prior distributions are used in different simulations. The Kullback-leibler divergence (KLD) is used to measure the dis(similarity) between different priors and corresponding posterior distributions to examine the parameter sensitivity. Results show that different prior distributions can strongly influence posterior distributions for parameters, especially when the available data is limited or parameters are insensitive to the available data. We demonstrate differences in optimized parameters and uncertainty limits in different cases based on multi-objective likelihoods vs. single objective likelihoods. We also demonstrate the importance of appropriately defining the weights of objectives in multi-objective calibration according to different data types.

A framework to observe and evaluate the sustainability of human-natural systems in a complex dynamic context.

PubMed

Satanarachchi, Niranji; Mino, Takashi

2014-01-01

This paper aims to explore the prominent implications of the process of observing complex dynamics linked to sustainability in human-natural systems and to propose a framework for sustainability evaluation by introducing the concept of sustainability boundaries. Arguing that both observing and evaluating sustainability should engage awareness of complex dynamics from the outset, we try to embody this idea in the framework by two complementary methods, namely, the layer view- and dimensional view-based methods, which support the understanding of a reflexive and iterative sustainability process. The framework enables the observation of complex dynamic sustainability contexts, which we call observation metastructures, and enable us to map the contexts to sustainability boundaries.

Dynamically heterogenous partitions and phylogenetic inference: an evaluation of analytical strategies with cytochrome b and ND6 gene sequences in cranes.

PubMed

Krajewski, C; Fain, M G; Buckley, L; King, D G

1999-11-01

ki ctes over whether molecular sequence data should be partitioned for phylogenetic analysis often confound two types of heterogeneity among partitions. We distinguish historical heterogeneity (i.e., different partitions have different evolutionary relationships) from dynamic heterogeneity (i.e., different partitions show different patterns of sequence evolution) and explore the impact of the latter on phylogenetic accuracy and precision with a two-gene, mitochondrial data set for cranes. The well-established phylogeny of cranes allows us to contrast tree-based estimates of relevant parameter values with estimates based on pairwise comparisons and to ascertain the effects of incorporating different amounts of process information into phylogenetic estimates. We show that codon positions in the cytochrome b and NADH dehydrogenase subunit 6 genes are dynamically heterogenous under both Poisson and invariable-sites + gamma-rates versions of the F84 model and that heterogeneity includes variation in base composition and transition bias as well as substitution rate. Estimates of transition-bias and relative-rate parameters from pairwise sequence comparisons were comparable to those obtained as tree-based maximum likelihood estimates. Neither rate-category nor mixed-model partitioning strategies resulted in a loss of phylogenetic precision relative to unpartitioned analyses. We suggest that weighted-average distances provide a computationally feasible alternative to direct maximum likelihood estimates of phylogeny for mixed-model analyses of large, dynamically heterogenous data sets. Copyright 1999 Academic Press.

Adaptive time-sequential binary sensing for high dynamic range imaging

NASA Astrophysics Data System (ADS)

Hu, Chenhui; Lu, Yue M.

2012-06-01

We present a novel image sensor for high dynamic range imaging. The sensor performs an adaptive one-bit quantization at each pixel, with the pixel output switched from 0 to 1 only if the number of photons reaching that pixel is greater than or equal to a quantization threshold. With an oracle knowledge of the incident light intensity, one can pick an optimal threshold (for that light intensity) and the corresponding Fisher information contained in the output sequence follows closely that of an ideal unquantized sensor over a wide range of intensity values. This observation suggests the potential gains one may achieve by adaptively updating the quantization thresholds. As the main contribution of this work, we propose a time-sequential threshold-updating rule that asymptotically approaches the performance of the oracle scheme. With every threshold mapped to a number of ordered states, the dynamics of the proposed scheme can be modeled as a parametric Markov chain. We show that the frequencies of different thresholds converge to a steady-state distribution that is concentrated around the optimal choice. Moreover, numerical experiments show that the theoretical performance measures (Fisher information and Craḿer-Rao bounds) can be achieved by a maximum likelihood estimator, which is guaranteed to find globally optimal solution due to the concavity of the log-likelihood functions. Compared with conventional image sensors and the strategy that utilizes a constant single-photon threshold considered in previous work, the proposed scheme attains orders of magnitude improvement in terms of sensor dynamic ranges.

Complex Dynamic Systems View on Conceptual Change: How a Picture of Students' Intuitive Conceptions Accrue from Dynamically Robust Task Dependent Learning Outcomes

ERIC Educational Resources Information Center

Koponen, Ismo T.; Kokkonen, Tommi; Nousiainen, Maiji

2017-01-01

We discuss here conceptual change and the formation of robust learning outcomes from the viewpoint of complex dynamic systems (CDS). The CDS view considers students' conceptions as context dependent and multifaceted structures which depend on the context of their application. In the CDS view the conceptual patterns (i.e. intuitive conceptions…

Cross-validation to select Bayesian hierarchical models in phylogenetics.

PubMed

Duchêne, Sebastián; Duchêne, David A; Di Giallonardo, Francesca; Eden, John-Sebastian; Geoghegan, Jemma L; Holt, Kathryn E; Ho, Simon Y W; Holmes, Edward C

2016-05-26

Recent developments in Bayesian phylogenetic models have increased the range of inferences that can be drawn from molecular sequence data. Accordingly, model selection has become an important component of phylogenetic analysis. Methods of model selection generally consider the likelihood of the data under the model in question. In the context of Bayesian phylogenetics, the most common approach involves estimating the marginal likelihood, which is typically done by integrating the likelihood across model parameters, weighted by the prior. Although this method is accurate, it is sensitive to the presence of improper priors. We explored an alternative approach based on cross-validation that is widely used in evolutionary analysis. This involves comparing models according to their predictive performance. We analysed simulated data and a range of viral and bacterial data sets using a cross-validation approach to compare a variety of molecular clock and demographic models. Our results show that cross-validation can be effective in distinguishing between strict- and relaxed-clock models and in identifying demographic models that allow growth in population size over time. In most of our empirical data analyses, the model selected using cross-validation was able to match that selected using marginal-likelihood estimation. The accuracy of cross-validation appears to improve with longer sequence data, particularly when distinguishing between relaxed-clock models. Cross-validation is a useful method for Bayesian phylogenetic model selection. This method can be readily implemented even when considering complex models where selecting an appropriate prior for all parameters may be difficult.

Female sex workers and the social context of workplace violence in Tijuana, Mexico.

PubMed

Katsulis, Yasmina; Lopez, Vera; Durfee, Alesha; Robillard, Alyssa

2010-09-01

Gender-based violence in the workplace impacts the physical and emotional wellbeing of sex workers and may lead to other health problems, such as PTSD and depression, drug abuse, and a greater likelihood of sexually transmitted infections. This study examines the social context of workplace violence and risk avoidance in the context of legal regulations meant to reduce harms associated with the industry. Ethnographic research, including 18 months of extended field observations and interviews with 190 female sex workers, is used to illustrate how sex workers in Tijuana, Mexico, experience and manage workplace violence. Multiple subthemes emerge from this analysis, including deciding where to work, working with a third party, avoiding theft, and dealing with police. These findings support the idea that the risk of violence is part of a larger "hierarchy of risk" that can result in a "tradeoff" of harms.

Evaluation of the patient with an exposure-related disease: the occupational and environmental history.

PubMed

Papali, Alfred; Hines, Stella E

2015-03-01

Although the process of taking an occupational and environmental history has remained largely the same, the context in which it is done has changed dramatically over recent years. This review examines the role of the occupational and environmental history in the context of the changing nature of medical practice and discusses methods for evaluating patients with contemporary exposure-related respiratory illnesses. Surveillance for occupational lung disease using mnemonic devices, screening questions and the use of structured questionnaires can significantly increase the likelihood and accuracy of detection. Electronic health records likewise can be adapted to include the most important elements of the occupational and environmental history. The emergence of new technologies and industries will lead to respiratory diseases in novel occupational and environmental contexts. Using the methods described herein can make detecting these diseases easier and less time-consuming.

A predictive framework for evaluating models of semantic organization in free recall

PubMed Central

Morton, Neal W; Polyn, Sean M.

2016-01-01

Research in free recall has demonstrated that semantic associations reliably influence the organization of search through episodic memory. However, the specific structure of these associations and the mechanisms by which they influence memory search remain unclear. We introduce a likelihood-based model-comparison technique, which embeds a model of semantic structure within the context maintenance and retrieval (CMR) model of human memory search. Within this framework, model variants are evaluated in terms of their ability to predict the specific sequence in which items are recalled. We compare three models of semantic structure, latent semantic analysis (LSA), global vectors (GloVe), and word association spaces (WAS), and find that models using WAS have the greatest predictive power. Furthermore, we find evidence that semantic and temporal organization is driven by distinct item and context cues, rather than a single context cue. This finding provides important constraint for theories of memory search. PMID:28331243

Estimating Phenomenological Parameters in Multi-Assets Markets

NASA Astrophysics Data System (ADS)

Raffaelli, Giacomo; Marsili, Matteo

Financial correlations exhibit a non-trivial dynamic behavior. This is reproduced by a simple phenomenological model of a multi-asset financial market, which takes into account the impact of portfolio investment on price dynamics. This captures the fact that correlations determine the optimal portfolio but are affected by investment based on it. Such a feedback on correlations gives rise to an instability when the volume of investment exceeds a critical value. Close to the critical point the model exhibits dynamical correlations very similar to those observed in real markets. We discuss how the model's parameter can be estimated in real market data with a maximum likelihood principle. This confirms the main conclusion that real markets operate close to a dynamically unstable point.

14 CFR 25.562 - Emergency landing dynamic conditions.

Code of Federal Regulations, 2014 CFR

2014-01-01

...— (1) Proper use is made of seats, safety belts, and shoulder harnesses provided for in the design; and... likelihood of the upper torso restraint system (where installed) moving off the occupant's shoulder, and with... shoulder during the impact. (4) The lap safety belt must remain on the occupant's pelvis during the impact...

14 CFR 25.562 - Emergency landing dynamic conditions.

Code of Federal Regulations, 2013 CFR

2013-01-01

...— (1) Proper use is made of seats, safety belts, and shoulder harnesses provided for in the design; and... likelihood of the upper torso restraint system (where installed) moving off the occupant's shoulder, and with... shoulder during the impact. (4) The lap safety belt must remain on the occupant's pelvis during the impact...

14 CFR 25.562 - Emergency landing dynamic conditions.

Code of Federal Regulations, 2012 CFR

2012-01-01

...— (1) Proper use is made of seats, safety belts, and shoulder harnesses provided for in the design; and... likelihood of the upper torso restraint system (where installed) moving off the occupant's shoulder, and with... shoulder during the impact. (4) The lap safety belt must remain on the occupant's pelvis during the impact...

14 CFR 25.562 - Emergency landing dynamic conditions.

Code of Federal Regulations, 2011 CFR

2011-01-01

...— (1) Proper use is made of seats, safety belts, and shoulder harnesses provided for in the design; and... likelihood of the upper torso restraint system (where installed) moving off the occupant's shoulder, and with... shoulder during the impact. (4) The lap safety belt must remain on the occupant's pelvis during the impact...

Climate Prediction Center - Week 3-4 Outlook

Science.gov Websites

extends from northeast Florida through North Carolina, based on the likelihood for much above-normal soil is forecast. In contrast, soil moisture deficits are anticipated at the start of the period over the anticipated below-normal soil moisture conditions at the start of the Week 3-4 period. Dynamical model

Managing multi-ungulate systems in disturbance-adapted forest ecosystems in North America

Treesearch

Martin Vavra; Robert A. Riggs

2010-01-01

Understanding how interactions among ungulate populations and their environmental dynamics play out across scales of time and space is a principal obstacle to managing ungulates in western North America. Morphological similarity, forage-base homogeneity and increasing animal density each enhance the likelihood of competitive interactions among sympatric populations....

Modeling Dynamic Functional Neuroimaging Data Using Structural Equation Modeling

ERIC Educational Resources Information Center

Price, Larry R.; Laird, Angela R.; Fox, Peter T.; Ingham, Roger J.

2009-01-01

The aims of this study were to present a method for developing a path analytic network model using data acquired from positron emission tomography. Regions of interest within the human brain were identified through quantitative activation likelihood estimation meta-analysis. Using this information, a "true" or population path model was then…

Sediment Resuspension and Transport in Water Distribution ...

EPA Pesticide Factsheets

Journal article This journal article addresses the question of how likely tank sediments are to be resuspended and to drain from the tank, potentially impacting human health. AUsing computational fluid dynamics software, and sediment models from the literature, a variety of normal tank operating conditions are assessed to evaluate the likelihood of tank sediment resuspension.

Variables Associated with Treatment Failure among Adolescent Sex Offenders

ERIC Educational Resources Information Center

Eastman, Brenda J.

2005-01-01

While an adolescent sexual offender's response to treatment is thought to be impacted by both static and dynamic factors, there is no objective method of assessing the likelihood of success or failure in treatment. The assessment of amenability to treatment is generally a subjective process completed by clinicians in the field. Using descriptive…

The role of landscape-dependent disturbance and dispersal in metapopulation persistence.

PubMed

Elkin, Ché M; Possingham, Hugh

2008-10-01

The fundamental processes that influence metapopulation dynamics (extinction and recolonization) will often depend on landscape structure. Disturbances that increase patch extinction rates will frequently be landscape dependent such that they are spatially aggregated and have an increased likelihood of occurring in some areas. Similarly, landscape structure can influence organism movement, producing asymmetric dispersal between patches. Using a stochastic, spatially explicit model, we examine how landscape-dependent correlations between dispersal and disturbance rates influence metapopulation dynamics. Habitat patches that are situated in areas where the likelihood of disturbance is low will experience lower extinction rates and will function as partial refuges. We discovered that the presence of partial refuges increases metapopulation viability and that the value of partial refuges was contingent on whether dispersal was also landscape dependent. Somewhat counterintuitively, metapopulation viability was reduced when individuals had a preponderance to disperse away from refuges and was highest when there was biased dispersal toward refuges. Our work demonstrates that landscape structure needs to be incorporated into metapopulation models when there is either empirical data or ecological rationale for extinction and/or dispersal rates being landscape dependent.

Stage-structured transmission of phocine distemper virus in the Dutch 2002 outbreak

PubMed Central

Klepac, Petra; Pomeroy, Laura W.; Bjørnstad, Ottar N.; Kuiken, Thijs; Osterhaus, Albert D.M.E.; Rijks, Jolianne M.

2009-01-01

Heterogeneities in transmission among hosts can be very important in shaping infectious disease dynamics. In mammals with strong social organization, such heterogeneities are often structured by functional stage: juveniles, subadults and adults. We investigate the importance of such stage-related heterogeneities in shaping the 2002 phocine distemper virus (PDV) outbreak in the Dutch Wadden Sea, when more than 40 per cent of the harbour seals were killed. We do this by comparing the statistical fit of a hierarchy of models with varying transmission complexity: homogeneous versus heterogeneous mixing and density- versus frequency-dependent transmission. We use the stranding data as a proxy for incidence and use Poisson likelihoods to estimate the ‘who acquires infection from whom’ (WAIFW) matrix. Statistically, the model with strong heterogeneous mixing and density-dependent transmission was found to best describe the transmission dynamics. However, patterns of incidence support a model of frequency-dependent transmission among adults and juveniles. Based on the maximum-likelihood WAIFW matrix estimates, we use the next-generation formalism to calculate an R0 between 2 and 2.5 for the Dutch 2002 PDV epidemic. PMID:19364743

Maximum likelihood estimation of between and within variations in energy and protein intakes from infancy to adolescence for the Philippines.

PubMed

Bhargava, A; Bouis, H

1992-02-28

The assessment of subjects' 'usual' intake of nutrients is important in assessing relationships between diet and disease and in identifying malnourished sub-groups of the populations. Estimation of the variation in intakes within subjects over time ('within variation') has importance in epidemiologic research; estimation of the between subject variation in the sample has use in defining the recommended dietary allowances that take into account the inter-individual differences. This paper estimates the between and within variances in the energy and protein intakes of 1189 Filipino children, based on 4 rounds of 24-hour recall data within a dynamic framework by means of maximum likelihood. The main findings are that the proportion of variation due to the within variance is higher for children from poorer households. Also, from the estimates of dynamic regression models for nutrient intakes of children and adults, it appears that school programmes that provide subsidized foods with good sources of protein to the poorest among school attendees will be cost effective.

Thought-action fusion across anxiety disorder diagnoses: Specificity and treatment effects

PubMed Central

Thompson-Hollands, Johanna; Farchione, Todd J.; Barlow, David H.

2013-01-01

Thought-action fusion (TAF) is a cognitive error that has been frequently investigated within the context of obsessive-compulsive disorder (OCD). However, evidence suggests that this error may also be present in disorders other than OCD, indicating that TAF is related to higher-order factors rather than a specific diagnosis. We explored TAF in a sample of patients with mixed diagnoses undergoing treatment with a transdiagnostic CBT protocol. Elevated TAF levels at baseline were not specific to patients with OCD. However, the presence of any generalized anxiety disorder (GAD) diagnosis was unexpectedly the strongest predictor of likelihood TAF. Likelihood TAF, a particular component of TAF, was reduced after transdiagnostic treatment, and this reduction was not affected by the presence of a GAD diagnosis. Results indicate that TAF is responsive to treatment and should be assessed and, perhaps, treated in disorders beyond OCD. PMID:23595095

Thought-action fusion across anxiety disorder diagnoses: specificity and treatment effects.

PubMed

Thompson-Hollands, Johanna; Farchione, Todd J; Barlow, David H

2013-05-01

Thought-action fusion (TAF) is a cognitive error that has been frequently investigated within the context of obsessive-compulsive disorder (OCD). However, evidence suggests that this error may also be present in disorders other than OCD, indicating that TAF is related to higher order factors rather than a specific diagnosis. We explored TAF in a sample of patients with mixed diagnoses undergoing treatment with a transdiagnostic CBT protocol. Elevated TAF levels at baseline were not specific to patients with OCD. However, the presence of any generalized anxiety disorder (GAD) diagnosis was unexpectedly the strongest predictor of likelihood TAF. Likelihood TAF, a particular component of TAF, was reduced after transdiagnostic treatment, and this reduction was not affected by the presence of a GAD diagnosis. Results indicate that TAF is responsive to treatment and should be assessed and, perhaps, treated in disorders beyond OCD.

Likelihood-Based Random-Effect Meta-Analysis of Binary Events.

PubMed

Amatya, Anup; Bhaumik, Dulal K; Normand, Sharon-Lise; Greenhouse, Joel; Kaizar, Eloise; Neelon, Brian; Gibbons, Robert D

2015-01-01

Meta-analysis has been used extensively for evaluation of efficacy and safety of medical interventions. Its advantages and utilities are well known. However, recent studies have raised questions about the accuracy of the commonly used moment-based meta-analytic methods in general and for rare binary outcomes in particular. The issue is further complicated for studies with heterogeneous effect sizes. Likelihood-based mixed-effects modeling provides an alternative to moment-based methods such as inverse-variance weighted fixed- and random-effects estimators. In this article, we compare and contrast different mixed-effect modeling strategies in the context of meta-analysis. Their performance in estimation and testing of overall effect and heterogeneity are evaluated when combining results from studies with a binary outcome. Models that allow heterogeneity in both baseline rate and treatment effect across studies have low type I and type II error rates, and their estimates are the least biased among the models considered.

Singing it for "us": Team passion displayed during national anthems is associated with subsequent success.

PubMed

Slater, Matthew J; Haslam, S Alexander; Steffens, Niklas K

2018-05-01

The present research examined the link between passion displayed by team members during the singing of national anthems at UEFA Euro 2016 and team performance in the tournaments' 51 games. Drawing on social identity theorising, we hypothesised a positive relationship between passion and performance. Consistent with this hypothesis, results showed that teams that sang national anthems with greater passion went on to concede fewer goals. Moreover, results provided evidence that the impact of passion on the likelihood of winning a game depended on the stage of the competition: in the knockout stage (but not the group stage) greater passion was associated with a greater likelihood of victory. Extending recent reviews that highlight the importance of social identity processes in sporting contexts, these results suggest that team members' identity-based expression of passion for the collective can be an important predictor of subsequent performance.

How are important life events disclosed on facebook? Relationships with likelihood of sharing and privacy.

PubMed

Bevan, Jennifer L; Cummings, Megan B; Kubiniec, Ashley; Mogannam, Megan; Price, Madison; Todd, Rachel

2015-01-01

This study examined an aspect of Facebook disclosure that has as yet gone unexplored: whether a user prefers to share information directly, for example, through status updates, or indirectly, via photos with no caption or relationship status changes without context or explanation. The focus was on the sharing of important positive and negative life events related to romantic relationships, health, and work/school in relation to likelihood of sharing this type of information on Facebook and general attitudes toward privacy. An online survey of 599 adult Facebook users found that when positive life events were shared, users preferred to do so indirectly, whereas negative life events were more likely to be disclosed directly. Privacy shared little association with how information was shared. Implications for understanding the finer nuances of how news is shared on Facebook are discussed.

Modeling and Maximum Likelihood Fitting of Gamma-Ray and Radio Light Curves of Millisecond Pulsars Detected with Fermi

NASA Technical Reports Server (NTRS)

Johnson, T. J.; Harding, A. K.; Venter, C.

2012-01-01

Pulsed gamma rays have been detected with the Fermi Large Area Telescope (LAT) from more than 20 millisecond pulsars (MSPs), some of which were discovered in radio observations of bright, unassociated LAT sources. We have fit the radio and gamma-ray light curves of 19 LAT-detected MSPs in the context of geometric, outermagnetospheric emission models assuming the retarded vacuum dipole magnetic field using a Markov chain Monte Carlo maximum likelihood technique. We find that, in many cases, the models are able to reproduce the observed light curves well and provide constraints on the viewing geometries that are in agreement with those from radio polarization measurements. Additionally, for some MSPs we constrain the altitudes of both the gamma-ray and radio emission regions. The best-fit magnetic inclination angles are found to cover a broader range than those of non-recycled gamma-ray pulsars.

Identifying habitats at risk: simple models can reveal complex ecosystem dynamics.

PubMed

Maxwell, Paul S; Pitt, Kylie A; Olds, Andrew D; Rissik, David; Connolly, Rod M

2015-03-01

The relationship between ecological impact and ecosystem structure is often strongly nonlinear, so that small increases in impact levels can cause a disproportionately large response in ecosystem structure. Nonlinear ecosystem responses can be difficult to predict because locally relevant data sets can be difficult or impossible to obtain. Bayesian networks (BN) are an emerging tool that can help managers to define ecosystem relationships using a range of data types from comprehensive quantitative data sets to expert opinion. We show how a simple BN can reveal nonlinear dynamics in seagrass ecosystems using ecological relationships sourced from the literature. We first developed a conceptual diagram by cataloguing the ecological responses of seagrasses to a range of drivers and impacts. We used the conceptual diagram to develop a BN populated with values sourced from published studies. We then applied the BN to show that the amount of initial seagrass biomass has a mitigating effect on the level of impact a meadow can withstand without loss, and that meadow recovery can often require disproportionately large improvements in impact levels. This mitigating effect resulted in the middle ranges of impact levels having a wide likelihood of seagrass presence, a situation known as bistability. Finally, we applied the model in a case study to identify the risk of loss and the likelihood of recovery for the conservation and management of seagrass meadows in Moreton Bay, Queensland, Australia. We used the model to predict the likelihood of bistability in 23 locations in the Bay. The model predicted bistability in seven locations, most of which have experienced seagrass loss at some stage in the past 25 years providing essential information for potential future restoration efforts. Our results demonstrate the capacity of simple, flexible modeling tools to facilitate collation and synthesis of disparate information. This approach can be adopted in the initial stages of conservation programs as a low-cost and relatively straightforward way to provide preliminary assessments of.nonlinear dynamics in ecosystems.

Combining operational models and data into a dynamic vessel risk assessment tool for coastal regions

NASA Astrophysics Data System (ADS)

Fernandes, R.; Braunschweig, F.; Lourenço, F.; Neves, R.

2015-07-01

The technological evolution in terms of computational capacity, data acquisition systems, numerical modelling and operational oceanography is supplying opportunities for designing and building holistic approaches and complex tools for newer and more efficient management (planning, prevention and response) of coastal water pollution risk events. A combined methodology to dynamically estimate time and space variable shoreline risk levels from ships has been developed, integrating numerical metocean forecasts and oil spill simulations with vessel tracking automatic identification systems (AIS). The risk rating combines the likelihood of an oil spill occurring from a vessel navigating in a study area - Portuguese Continental shelf - with the assessed consequences to the shoreline. The spill likelihood is based on dynamic marine weather conditions and statistical information from previous accidents. The shoreline consequences reflect the virtual spilled oil amount reaching shoreline and its environmental and socio-economic vulnerabilities. The oil reaching shoreline is quantified with an oil spill fate and behaviour model running multiple virtual spills from vessels along time. Shoreline risks can be computed in real-time or from previously obtained data. Results show the ability of the proposed methodology to estimate the risk properly sensitive to dynamic metocean conditions and to oil transport behaviour. The integration of meteo-oceanic + oil spill models with coastal vulnerability and AIS data in the quantification of risk enhances the maritime situational awareness and the decision support model, providing a more realistic approach in the assessment of shoreline impacts. The risk assessment from historical data can help finding typical risk patterns, "hot spots" or developing sensitivity analysis to specific conditions, whereas real time risk levels can be used in the prioritization of individual ships, geographical areas, strategic tug positioning and implementation of dynamic risk-based vessel traffic monitoring.

Framework for adaptive multiscale analysis of nonhomogeneous point processes.

PubMed

Helgason, Hannes; Bartroff, Jay; Abry, Patrice

2011-01-01

We develop the methodology for hypothesis testing and model selection in nonhomogeneous Poisson processes, with an eye toward the application of modeling and variability detection in heart beat data. Modeling the process' non-constant rate function using templates of simple basis functions, we develop the generalized likelihood ratio statistic for a given template and a multiple testing scheme to model-select from a family of templates. A dynamic programming algorithm inspired by network flows is used to compute the maximum likelihood template in a multiscale manner. In a numerical example, the proposed procedure is nearly as powerful as the super-optimal procedures that know the true template size and true partition, respectively. Extensions to general history-dependent point processes is discussed.

Orthogonal series generalized likelihood ratio test for failure detection and isolation. [for aircraft control

NASA Technical Reports Server (NTRS)

Hall, Steven R.; Walker, Bruce K.

1990-01-01

A new failure detection and isolation algorithm for linear dynamic systems is presented. This algorithm, the Orthogonal Series Generalized Likelihood Ratio (OSGLR) test, is based on the assumption that the failure modes of interest can be represented by truncated series expansions. This assumption leads to a failure detection algorithm with several desirable properties. Computer simulation results are presented for the detection of the failures of actuators and sensors of a C-130 aircraft. The results show that the OSGLR test generally performs as well as the GLR test in terms of time to detect a failure and is more robust to failure mode uncertainty. However, the OSGLR test is also somewhat more sensitive to modeling errors than the GLR test.

BOREAS TE-18 Landsat TM Maximum Likelihood Classification Image of the NSA

NASA Technical Reports Server (NTRS)

Hall, Forrest G. (Editor); Knapp, David

2000-01-01

The BOREAS TE-18 team focused its efforts on using remotely sensed data to characterize the successional and disturbance dynamics of the boreal forest for use in carbon modeling. The objective of this classification is to provide the BOREAS investigators with a data product that characterizes the land cover of the NSA. A Landsat-5 TM image from 20-Aug-1988 was used to derive this classification. A standard supervised maximum likelihood classification approach was used to produce this classification. The data are provided in a binary image format file. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Activity Archive Center (DAAC).

Supporting Teachers' Management of Middle School Social Dynamics: The Scouting Report Process

ERIC Educational Resources Information Center

Farmer, Thomas W.; Chen, Chin-Chih; Hamm, Jill V.; Moates, Meredith M.; Mehtaji, Meera; Lee, David; Huneke, Michelle R.

2016-01-01

This describes the "scouting report" as an approach that social and behavior intervention specialists can use to help middle-level teachers create social contexts that support productive social roles and relationships of students with disabilities. Building from research on early adolescent social dynamics and context-based interventions…

Westerlund 1: monolithic formation of a starburst cluster

NASA Astrophysics Data System (ADS)

Negueruela, Ignacio; Clark, J. Simon; Ritchie, Ben; Goodwin, Simon

2015-08-01

Westerlund 1 is in all likelihood the most massive young cluster in the Milky Way, with a mass on the order of 105 Msol. We have been observing its massive star population for ten years, measuring radial velocity changes for a substantial fraction of its OB stars and evolved supergiants. The properties of the evolved population are entirely consisting with a single burst of star formation, in excellent agreement with the results of studies based on the lower-mass population.Here we will present two new studies of the cluster: 1) A direct measurement of its average radial velocity and velocity dispersion based on individual measurements for several dozen stars with constant radial velocity and 2) A search for massive stars in its immediate neighbourhood using multi-object spectroscopy.The results of these two studies show that Westerlund 1 is decidedly subvirial and has a systemic radial velocity significantly different from that of nearby gas, which was assumed to provide a dynamical distance by previous authors. Moreover, the dynamical distance is inconsistent with the properties of the high-mass stellar population. In addition, we find that the cluster is completely isolated, with hardly any massive star in its vicinity that could be associated in terms of distance modulus or radial velocity. The cluster halo does not extend much further than five parsec away from the centre. All these properties are very unusual among starburst clusters in the Local Universe, which tend to form in the context of large star-forming regions.Westerlund 1 is thus the best example we have of a starburst cluster formed monolithically.

The geosimulation of West Nile virus propagation: a multi-agent and climate sensitive tool for risk management in public health

PubMed Central

Bouden, Mondher; Moulin, Bernard; Gosselin, Pierre

2008-01-01

Background Since 1999, the expansion of the West Nile virus (WNV) epizooty has led public health authorities to build and operate surveillance systems in North America. These systems are very useful to collect data, but cannot be used to forecast the probable spread of the virus in coming years. Such forecasts, if proven reliable, would permit preventive measures to be put into place at the appropriate level of expected risk and at the appropriate time. It is within this context that the Multi-Agent GeoSimulation approach has been selected to develop a system that simulates the interactions of populations of mosquitoes and birds over space and time in relation to the spread and transmission of WNV. This simulation takes place in a virtual mapping environment representing a large administrative territory (e.g. province, state) and carried out under various climate scenarios in order to simulate the effects of vector control measures such as larviciding at scales of 1/20 000 or smaller. Results After setting some hypotheses, a conceptual model and system architecture were developed to describe the population dynamics and interactions of mosquitoes (genus Culex) and American crows, which were chosen as the main actors in the simulation. Based on a mathematical compartment model used to simulate the population dynamics, an operational prototype was developed for the Southern part of Quebec (Canada). The system allows users to modify the parameters of the model, to select various climate and larviciding scenarios, to visualize on a digital map the progression (on a weekly or daily basis) of the infection in and around the crows' roosts and to generate graphs showing the evolution of the populations. The basic units for visualisation are municipalities. Conclusion In all likelihood this system might be used to support short term decision-making related to WNV vector control measures, including the use of larvicides, according to climatic scenarios. Once fully calibrated in several real-life contexts, this promising approach opens the door to the study and management of other zoonotic diseases such as Lyme disease. PMID:18606008

Return-to-Work Within a Complex and Dynamic Organizational Work Disability System.

PubMed

Jetha, Arif; Pransky, Glenn; Fish, Jon; Hettinger, Lawrence J

2016-09-01

Background Return-to-work (RTW) within a complex organizational system can be associated with suboptimal outcomes. Purpose To apply a sociotechnical systems perspective to investigate complexity in RTW; to utilize system dynamics modeling (SDM) to examine how feedback relationships between individual, psychosocial, and organizational factors make up the work disability system and influence RTW. Methods SDMs were developed within two companies. Thirty stakeholders including senior managers, and frontline supervisors and workers participated in model building sessions. Participants were asked questions that elicited information about the structure of the work disability system and were translated into feedback loops. To parameterize the model, participants were asked to estimate the shape and magnitude of the relationship between key model components. Data from published literature were also accessed to supplement participant estimates. Data were entered into a model created in the software program Vensim. Simulations were conducted to examine how financial incentives and light duty work disability-related policies, utilized by the participating companies, influenced RTW likelihood and preparedness. Results The SDMs were multidimensional, including individual attitudinal characteristics, health factors, and organizational components. Among the causal pathways uncovered, psychosocial components including workplace social support, supervisor and co-worker pressure, and supervisor-frontline worker communication impacted RTW likelihood and preparedness. Interestingly, SDM simulations showed that work disability-related policies in both companies resulted in a diminishing or opposing impact on RTW preparedness and likelihood. Conclusion SDM provides a novel systems view of RTW. Policy and psychosocial component relationships within the system have important implications for RTW, and may contribute to unanticipated outcomes.

The dynamics of latifundia formation.

PubMed

Chaves, Luis Fernando

2013-01-01

Land tenure inequity is a major social problem in developing nations worldwide. In societies, where land is a commodity, inequities in land tenure are associated with gaps in income distribution, poverty and biodiversity loss. A common pattern of land tenure inequities through the history of civilization has been the formation of latifundia [Zhuāngyuán in chinese], i.e., a pattern where land ownership is concentrated by a small fraction of the whole population. Here, we use simple Markov chain models to study the dynamics of latifundia formation in a heterogeneous landscape where land can transition between forest, agriculture and recovering land. We systematically study the likelihood of latifundia formation under the assumption of pre-capitalist trade, where trade is based on the average utility of land parcels belonging to each individual landowner during a discrete time step. By restricting land trade to that under recovery, we found the likelihood of latifundia formation to increase with the size of the system, i.e., the amount of land and individuals in the society. We found that an increase of the transition rate for land use changes, i.e., how quickly land use changes, promotes more equitable patterns of land ownership. Disease introduction in the system, which reduced land profitability for infected individual landowners, promoted the formation of latifundia, with an increased likelihood for latifundia formation when there were heterogeneities in the susceptibility to infection. Finally, our model suggests that land ownership reforms need to guarantee an equitative distribution of land among individuals in a society to avoid the formation of latifundia.

The Dynamics of Latifundia Formation

PubMed Central

Chaves, Luis Fernando

2013-01-01

Land tenure inequity is a major social problem in developing nations worldwide. In societies, where land is a commodity, inequities in land tenure are associated with gaps in income distribution, poverty and biodiversity loss. A common pattern of land tenure inequities through the history of civilization has been the formation of latifundia [Zhuāngyuán in chinese], i.e., a pattern where land ownership is concentrated by a small fraction of the whole population. Here, we use simple Markov chain models to study the dynamics of latifundia formation in a heterogeneous landscape where land can transition between forest, agriculture and recovering land. We systematically study the likelihood of latifundia formation under the assumption of pre-capitalist trade, where trade is based on the average utility of land parcels belonging to each individual landowner during a discrete time step. By restricting land trade to that under recovery, we found the likelihood of latifundia formation to increase with the size of the system, i.e., the amount of land and individuals in the society. We found that an increase of the transition rate for land use changes, i.e., how quickly land use changes, promotes more equitable patterns of land ownership. Disease introduction in the system, which reduced land profitability for infected individual landowners, promoted the formation of latifundia, with an increased likelihood for latifundia formation when there were heterogeneities in the susceptibility to infection. Finally, our model suggests that land ownership reforms need to guarantee an equitative distribution of land among individuals in a society to avoid the formation of latifundia. PMID:24376597

Influence of family and school-level factors on age of sexual initiation.

PubMed

White, Candace N; Warner, Lynn A

2015-02-01

This study examined the association of individual, family, and school-level characteristics with age of sexual initiation (ASI) and focused specifically on school context as a moderator of known predictors of ASI. Data are from Waves I and IV of the National Longitudinal Study of Adolescent Health (N = 10,596). Predictors include grade point average, physical development, attitudes about sex, likelihood of higher education, alcohol use, delinquency, family structure, parents' education level, childhood abuse, maternal approval of sex, parental monitoring, and parent-child relationship quality. School-level predictors are averages of adolescents' attitudes about sex and likelihood of higher education and parents' education. Hierarchical linear models run separately by sex were used to predict ASI. When school-level attitudes about sex are more favorable, both boys and girls report younger ASI, and school mean parental education attainment moderates the influence of individual adolescents' attitudes about sex on ASI. More of the predictors are significant for girls than boys, whereas perception of maternal and peer approval of sexual activity are the most salient predictors of younger ASI for boys. Results highlight the importance of school context for understanding adolescents' motivations for early ASI. Findings support the need for school-wide prevention interventions that engage adolescents, peers, and parents in addressing attitudes about early sex. Copyright © 2015 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Age and the purchase of prescription drug insurance by older adults.

PubMed

Szrek, Helena; Bundorf, M Kate

2011-06-01

The Medicare Part D Prescription Drug Program places an unprecedented degree of choice in the hands of older adults despite concerns over their ability to make effective decisions and desire to have extensive choice in this context. While previous research has compared older adults to younger adults along these dimensions, our study, in contrast, examines how likelihood to delay decision making and preferences for choice differ by age among older age cohorts. Our analysis is based on responses of older adults to a simulation of enrollment in Medicare Part D. We examine how age, numeracy, cognitive reflection, and the interaction between age and performance on these instruments are related to the decision to enroll in a Medicare prescription drug plan and preference for choice in this context. We find that numeracy and cognitive reflection are positively associated with enrollment likelihood and that they are more important determinants of enrollment than age. We also find that greater numeracy is associated with a lower willingness to pay for choice. Hence, our findings raise concern that older adults, and, in particular, those with poorer numerical processing skills, may need extra support in enrolling in the program: they are less likely to enroll than those with stronger numerical processing skills, even though they show greater willingness to pay for choice. (c) 2011 APA, all rights reserved.

Dynamic Financial Constraints: Distinguishing Mechanism Design from Exogenously Incomplete Regimes*

PubMed Central

Karaivanov, Alexander; Townsend, Robert M.

2014-01-01

We formulate and solve a range of dynamic models of constrained credit/insurance that allow for moral hazard and limited commitment. We compare them to full insurance and exogenously incomplete financial regimes (autarky, saving only, borrowing and lending in a single asset). We develop computational methods based on mechanism design, linear programming, and maximum likelihood to estimate, compare, and statistically test these alternative dynamic models with financial/information constraints. Our methods can use both cross-sectional and panel data and allow for measurement error and unobserved heterogeneity. We estimate the models using data on Thai households running small businesses from two separate samples. We find that in the rural sample, the exogenously incomplete saving only and borrowing regimes provide the best fit using data on consumption, business assets, investment, and income. Family and other networks help consumption smoothing there, as in a moral hazard constrained regime. In contrast, in urban areas, we find mechanism design financial/information regimes that are decidedly less constrained, with the moral hazard model fitting best combined business and consumption data. We perform numerous robustness checks in both the Thai data and in Monte Carlo simulations and compare our maximum likelihood criterion with results from other metrics and data not used in the estimation. A prototypical counterfactual policy evaluation exercise using the estimation results is also featured. PMID:25246710

Climate-FVS Version 2: Content, users guide, applications, and behavior

Treesearch

Nicholas L. Crookston

2014-01-01

Climate change in the 21st Century is projected to cause widespread changes in forest ecosystems. Climate-FVS is a modification to the Forest Vegetation Simulator designed to take climate change into account when predicting forest dynamics at decadal to century time scales. Individual tree climate viability scores measure the likelihood that the climate at a given...

Evidence, Expertise, and Ethics: The Making of an Influential in American Social Work

ERIC Educational Resources Information Center

Burnette, Denise

2016-01-01

The extent to which people choose their professions and professions choose their practitioners is not always clear; it is in all likelihood a "simpatico" process. But, growing attention to the study of careers can help elucidate the nexus of personal and professional forces that underpins this complex dynamic. This line of inquiry can…

Reservoir Computing Properties of Neural Dynamics in Prefrontal Cortex

PubMed Central

Procyk, Emmanuel; Dominey, Peter Ford

2016-01-01

Primates display a remarkable ability to adapt to novel situations. Determining what is most pertinent in these situations is not always possible based only on the current sensory inputs, and often also depends on recent inputs and behavioral outputs that contribute to internal states. Thus, one can ask how cortical dynamics generate representations of these complex situations. It has been observed that mixed selectivity in cortical neurons contributes to represent diverse situations defined by a combination of the current stimuli, and that mixed selectivity is readily obtained in randomly connected recurrent networks. In this context, these reservoir networks reproduce the highly recurrent nature of local cortical connectivity. Recombining present and past inputs, random recurrent networks from the reservoir computing framework generate mixed selectivity which provides pre-coded representations of an essentially universal set of contexts. These representations can then be selectively amplified through learning to solve the task at hand. We thus explored their representational power and dynamical properties after training a reservoir to perform a complex cognitive task initially developed for monkeys. The reservoir model inherently displayed a dynamic form of mixed selectivity, key to the representation of the behavioral context over time. The pre-coded representation of context was amplified by training a feedback neuron to explicitly represent this context, thereby reproducing the effect of learning and allowing the model to perform more robustly. This second version of the model demonstrates how a hybrid dynamical regime combining spatio-temporal processing of reservoirs, and input driven attracting dynamics generated by the feedback neuron, can be used to solve a complex cognitive task. We compared reservoir activity to neural activity of dorsal anterior cingulate cortex of monkeys which revealed similar network dynamics. We argue that reservoir computing is a pertinent framework to model local cortical dynamics and their contribution to higher cognitive function. PMID:27286251

High school dropouts: interactions between social context, self-perceptions, school engagement, and student dropout.

PubMed

Fall, Anna-Mária; Roberts, Greg

2012-08-01

Research suggests that contextual, self-system, and school engagement variables influence dropping out from school. However, it is not clear how different types of contextual and self-system variables interact to affect students' engagement or contribute to decisions to dropout from high school. The self-system model of motivational development represents a promising theory for understanding this complex phenomenon. The self-system model acknowledges the interactive and iterative roles of social context, self-perceptions, school engagement, and academic achievement as antecedents to the decision to dropout of school. We analyzed data from the Education Longitudinal Study of 2002-2004 in the context of the self-system model, finding that perception of social context (teacher support and parent support) predicts students' self-perceptions (perception of control and identification with school), which in turn predict students' academic and behavioral engagement, and academic achievement. Further, students' academic and behavioral engagement and achievement in 10th grade were associated with decreased likelihood of dropping out of school in 12th grade. Published by Elsevier Ltd.

High school dropouts: Interactions between social context, self-perceptions, school engagement, and student dropout☆

PubMed Central

Fall, Anna-Mária; Roberts, Greg

2012-01-01

Research suggests that contextual, self-system, and school engagement variables influence dropping out from school. However, it is not clear how different types of contextual and self-system variables interact to affect students’ engagement or contribute to decisions to dropout from high school. The self-system model of motivational development represents a promising theory for understanding this complex phenomenon. The self-system model acknowledges the interactive and iterative roles of social context, self-perceptions, school engagement, and academic achievement as antecedents to the decision to dropout of school. We analyzed data from the Education Longitudinal Study of 2002–2004 in the context of the self-system model, finding that perception of social context (teacher support and parent support) predicts students’ self-perceptions (perception of control and identification with school), which in turn predict students’ academic and behavioral engagement, and academic achievement. Further, students’ academic and behavioral engagement and achievement in 10th grade were associated with decreased likelihood of dropping out of school in 12th grade. PMID:22153483

Hospitals as a 'risk environment': an ethno-epidemiological study of voluntary and involuntary discharge from hospital against medical advice among people who inject drugs.

PubMed

McNeil, Ryan; Small, Will; Wood, Evan; Kerr, Thomas

2014-03-01

People who inject drugs (PWID) experience high levels of HIV/AIDS and hepatitis C (HCV) infection that, together with injection-related complications such as non-fatal overdose and injection-related infections, lead to frequent hospitalizations. However, injection drug-using populations are among those most likely to be discharged from hospital against medical advice, which significantly increases their likelihood of hospital readmission, longer overall hospital stays, and death. In spite of this, little research has been undertaken examining how social-structural forces operating within hospital settings shape the experiences of PWID in receiving care in hospitals and contribute to discharges against medical advice. This ethno-epidemiological study was undertaken in Vancouver, Canada to explore how the social-structural dynamics within hospitals function to produce discharges against medical advice among PWID. In-depth interviews were conducted with thirty PWID recruited from among participants in ongoing observational cohort studies of people who inject drugs who reported that they had been discharged from hospital against medical advice within the previous two years. Data were analyzed thematically, and by drawing on the 'risk environment' framework and concepts of social violence. Our findings illustrate how intersecting social and structural factors led to inadequate pain and withdrawal management, which led to continued drug use in hospital settings. In turn, diverse forms of social control operating to regulate and prevent drug use in hospital settings amplified drug-related risks and increased the likelihood of discharge against medical advice. Given the significant morbidity and health care costs associated with discharge against medical advice among drug-using populations, there is an urgent need to reshape the social-structural contexts of hospital care for PWID by shifting emphasis toward evidence-based pain and drug treatment augmented by harm reduction supports, including supervised drug consumption services. Copyright © 2014 Elsevier Ltd. All rights reserved.

Hospitals as a `risk environment: An ethno-epidemiological study of voluntary and involuntary discharge from hospital against medical advice among people who inject drugs

PubMed Central

McNeil, Ryan; Small, Will; Wood, Evan; Kerr, Thomas

2014-01-01

People who inject drugs (PWID) experience high levels of HIV/AIDS and hepatitis C (HCV) infection that, together with injection-related complications such as non-fatal overdose and injection-related infections, lead to frequent hospitalizations. However, injection drug-using populations are among those most likely to be discharged from hospital against medical advice, which significantly increases their likelihood of hospital readmission, longer overall hospital stays, and death. In spite of this, little research has been undertaken examining how social-structural forces operating within hospital settings shape the experiences of PWID in receiving care in hospitals and contribute to discharges against medical advice. This ethno-epidemiological study was undertaken in Vancouver, Canada to explore how the social-structural dynamics within hospitals function to produce discharges against medical advice among PWID. In-depth interviews were conducted with thirty PWID recruited from among participants in ongoing observational cohort studies of people who inject drugs who reported that they had been discharged from hospital against medical advice within the previous two years. Data were analyzed thematically, and by drawing on the `Risk Environment' framework and concepts of social violence. Our findings illustrate how intersecting social and structural factors led to inadequate pain and withdrawal management, which led to continued drug use in hospital settings. In turn, diverse forms of social control operating to regulate and prevent drug use in hospital settings amplified drug-related risks and increased the likelihood of discharge against medical advice. Given the significant morbidity and health care costs associated with discharge against medical advice among drug-using populations, there is an urgent need to reshape the social-structural contexts of hospital care for PWID by shifting emphasis toward evidence-based pain and drug treatment augmented by harm reduction supports, including supervised drug consumption services. PMID:24508718

Estimating the Effect of Competition on Trait Evolution Using Maximum Likelihood Inference.

PubMed

Drury, Jonathan; Clavel, Julien; Manceau, Marc; Morlon, Hélène

2016-07-01

Many classical ecological and evolutionary theoretical frameworks posit that competition between species is an important selective force. For example, in adaptive radiations, resource competition between evolving lineages plays a role in driving phenotypic diversification and exploration of novel ecological space. Nevertheless, current models of trait evolution fit to phylogenies and comparative data sets are not designed to incorporate the effect of competition. The most advanced models in this direction are diversity-dependent models where evolutionary rates depend on lineage diversity. However, these models still treat changes in traits in one branch as independent of the value of traits on other branches, thus ignoring the effect of species similarity on trait evolution. Here, we consider a model where the evolutionary dynamics of traits involved in interspecific interactions are influenced by species similarity in trait values and where we can specify which lineages are in sympatry. We develop a maximum likelihood based approach to fit this model to combined phylogenetic and phenotypic data. Using simulations, we demonstrate that the approach accurately estimates the simulated parameter values across a broad range of parameter space. Additionally, we develop tools for specifying the biogeographic context in which trait evolution occurs. In order to compare models, we also apply these biogeographic methods to specify which lineages interact sympatrically for two diversity-dependent models. Finally, we fit these various models to morphological data from a classical adaptive radiation (Greater Antillean Anolis lizards). We show that models that account for competition and geography perform better than other models. The matching competition model is an important new tool for studying the influence of interspecific interactions, in particular competition, on phenotypic evolution. More generally, it constitutes a step toward a better integration of interspecific interactions in many ecological and evolutionary processes. © The Author(s) 2016. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Impact of the spread of mass education on married women's experience with domestic violence.

PubMed

Ghimire, Dirgha J; Axinn, William G; Smith-Greenaway, Emily

2015-11-01

This paper investigates the association between mass education and married women's experience with domestic violence in rural Nepal. Previous research on domestic violence in South Asian societies emphasizes patriarchal ideology and the widespread subordinate status of women within their communities and families. The recent spread of mass education is likely to shift these gendered dynamics, thereby lowering women's likelihood of experiencing domestic violence. Using data from 1775 currently married women from the Chitwan Valley Family Study in Nepal, we provide a thorough analysis of how the spread of mass education is associated with domestic violence among married women. The results show that women's childhood access to school, their parents' schooling, their own schooling, and their husbands' schooling are each associated with their lower likelihood of experiencing domestic violence. Indeed, husbands' education has a particularly strong, inverse association with women's likelihood of experiencing domestic violence. These associations suggest that the proliferation of mass education will lead to a marked decline in women's experience with domestic violence in Nepal. Copyright © 2015 Elsevier Inc. All rights reserved.

Impact of the Spread of Mass Education on Married Women’s Experience with Domestic Violence

PubMed Central

Ghimire, Dirgha J.; Axinn, William G.; Smith-Greenaway, Emily

2015-01-01

This paper investigates the association between mass education and married women’s experience with domestic violence in rural Nepal. Previous research on domestic violence in South Asian societies emphasizes patriarchal ideology and the widespread subordinate status of women within their communities and families. The recent spread of mass education is likely to shift these gendered dynamics, thereby lowering women’s likelihood of experiencing domestic violence. Using data from 1,775 currently married women from the Chitwan Valley Family Study in Nepal, we provide a thorough analysis of how the spread of mass education is associated with domestic violence among married women. The results show that women’s childhood access to school, their parents’ schooling, their own schooling, and their husbands’ schooling are each associated with their lower likelihood of experiencing domestic violence. Indeed, husbands’ education has a particularly strong, inverse association with women’s likelihood of experiencing domestic violence. These associations suggest that the proliferation of mass education will lead to a marked decline in women’s experience with domestic violence in Nepal. PMID:26463551

Cyber Foraging for Improving Survivability of Mobile Systems

DTIC Science & Technology

2016-02-10

environments—such as dynamic context, limited computing resources, disconnected- intermittent - limited (DIL) network connectivity, and high levels of stress...environments, such as dynamic context, limited computing resources, disconnected- intermittent -limited (DIL) network connectivity, and high levels of...Table 1: Mapping of Cloudlet Features to Survivability Requirements Threats Intermittent Cloudlet- Enterprise Connectivity Mobility Limited

Dynamics of Western Career Attributes in the Russian Context

ERIC Educational Resources Information Center

Khapova, Svetlana N.; Korotov, Konstantin

2007-01-01

Purpose: The purpose of this article is to raise awareness of the dynamic character of career and its key attributes, and the embeddedness of their definitions and meanings in national social, political and economic contexts. Design/methodology/approach: Features of three recent distinct social, political and economic situations in Russia are used…

Understanding the Influence of Organizational Culture and Group Dynamics on Organizational Change and Learning

ERIC Educational Resources Information Center

Lucas, Colleen; Kline, Theresa

2008-01-01

Purpose: The purpose of this study is to investigate the relationship between organizational culture, group dynamics, and organizational learning in the context of organizational change. Design/methodology/approach: A case study was used to examine cultural and group level factors that potentially influence groups' learning in the context of…

Normalized value coding explains dynamic adaptation in the human valuation process.

PubMed

Khaw, Mel W; Glimcher, Paul W; Louie, Kenway

2017-11-28

The notion of subjective value is central to choice theories in ecology, economics, and psychology, serving as an integrated decision variable by which options are compared. Subjective value is often assumed to be an absolute quantity, determined in a static manner by the properties of an individual option. Recent neurobiological studies, however, have shown that neural value coding dynamically adapts to the statistics of the recent reward environment, introducing an intrinsic temporal context dependence into the neural representation of value. Whether valuation exhibits this kind of dynamic adaptation at the behavioral level is unknown. Here, we show that the valuation process in human subjects adapts to the history of previous values, with current valuations varying inversely with the average value of recently observed items. The dynamics of this adaptive valuation are captured by divisive normalization, linking these temporal context effects to spatial context effects in decision making as well as spatial and temporal context effects in perception. These findings suggest that adaptation is a universal feature of neural information processing and offer a unifying explanation for contextual phenomena in fields ranging from visual psychophysics to economic choice.

Matching mammographic regions in mediolateral oblique and cranio caudal views: a probabilistic approach

NASA Astrophysics Data System (ADS)

Samulski, Maurice; Karssemeijer, Nico

2008-03-01

Most of the current CAD systems detect suspicious mass regions independently in single views. In this paper we present a method to match corresponding regions in mediolateral oblique (MLO) and craniocaudal (CC) mammographic views of the breast. For every possible combination of mass regions in the MLO view and CC view, a number of features are computed, such as the difference in distance of a region to the nipple, a texture similarity measure, the gray scale correlation and the likelihood of malignancy of both regions computed by single-view analysis. In previous research, Linear Discriminant Analysis was used to discriminate between correct and incorrect links. In this paper we investigate if the performance can be improved by employing a statistical method in which four classes are distinguished. These four classes are defined by the combinations of view (MLO/CC) and pathology (TP/FP) labels. We use distance-weighted k-Nearest Neighbor density estimation to estimate the likelihood of a region combination. Next, a correspondence score is calculated as the likelihood that the region combination is a TP-TP link. The method was tested on 412 cases with a malignant lesion visible in at least one of the views. In 82.4% of the cases a correct link could be established between the TP detections in both views. In future work, we will use the framework presented here to develop a context dependent region matching scheme, which takes the number and likelihood of possible alternatives into account. It is expected that more accurate determination of matching probabilities will lead to improved CAD performance.

Cognitive Control Functions of Anterior Cingulate Cortex in Macaque Monkeys Performing a Wisconsin Card Sorting Test Analog

PubMed Central

Kuwabara, Masaru; Mansouri, Farshad A.; Buckley, Mark J.

2014-01-01

Monkeys were trained to select one of three targets by matching in color or matching in shape to a sample. Because the matching rule frequently changed and there were no cues for the currently relevant rule, monkeys had to maintain the relevant rule in working memory to select the correct target. We found that monkeys' error commission was not limited to the period after the rule change and occasionally occurred even after several consecutive correct trials, indicating that the task was cognitively demanding. In trials immediately after such error trials, monkeys' speed of selecting targets was slower. Additionally, in trials following consecutive correct trials, the monkeys' target selections for erroneous responses were slower than those for correct responses. We further found evidence for the involvement of the cortex in the anterior cingulate sulcus (ACCs) in these error-related behavioral modulations. First, ACCs cell activity differed between after-error and after-correct trials. In another group of ACCs cells, the activity differed depending on whether the monkeys were making a correct or erroneous decision in target selection. Second, bilateral ACCs lesions significantly abolished the response slowing both in after-error trials and in error trials. The error likelihood in after-error trials could be inferred by the error feedback in the previous trial, whereas the likelihood of erroneous responses after consecutive correct trials could be monitored only internally. These results suggest that ACCs represent both context-dependent and internally detected error likelihoods and promote modes of response selections in situations that involve these two types of error likelihood. PMID:24872558

Malpractice Burden, Rural Location, and Discontinuation of Obstetric Care: A Study of Obstetric Providers in Michigan

PubMed Central

Xu, Xiao; Siefert, Kristine A.; Jacobson, Peter D.; Lori, Jody R.; Gueorguieva, Iana; Ransom, Scott B.

2011-01-01

Context It has long been a concern that professional liability problems disproportionately affect the delivery of obstetrical services to women living in rural areas. Michigan, a state with a large number of rural communities, is considered to be at risk for a medical liability crisis. Purpose This study examined whether higher malpractice burden on obstetric providers was associated with an increased likelihood of discontinuing obstetric care and whether there were rural-urban differences in the relationship. Methods Data on 500 obstetrician-gynecologists and family physicians who had provided obstetric care at some point in their career (either currently or previously) were obtained from a statewide survey in Michigan. Statistical tests and multivariate regression analyses were performed to examine the interrelationship among malpractice burden, rural location, and discontinuation of obstetric care. Findings After adjusting for other factors that might influence a physician’s decision about whether to stop obstetric care, our results showed no significant impact of malpractice burden on physicians’ likelihood to discontinue obstetric care. Rural-urban location of the practice did not modify the nature of this relationship. However, family physicians in rural Michigan had a nearly four fold higher likelihood of withdrawing obstetric care when compared to urban family physicians. Conclusions The higher likelihood of rural family physicians to discontinue obstetric care should be carefully weighed in future interventions to preserve obstetric care supply. More research is needed to better understand the practice environment of rural family physicians and the reasons for their withdrawal from obstetric care. PMID:19166559

Hybrid approach combining chemometrics and likelihood ratio framework for reporting the evidential value of spectra.

PubMed

Martyna, Agnieszka; Zadora, Grzegorz; Neocleous, Tereza; Michalska, Aleksandra; Dean, Nema

2016-08-10

Many chemometric tools are invaluable and have proven effective in data mining and substantial dimensionality reduction of highly multivariate data. This becomes vital for interpreting various physicochemical data due to rapid development of advanced analytical techniques, delivering much information in a single measurement run. This concerns especially spectra, which are frequently used as the subject of comparative analysis in e.g. forensic sciences. In the presented study the microtraces collected from the scenarios of hit-and-run accidents were analysed. Plastic containers and automotive plastics (e.g. bumpers, headlamp lenses) were subjected to Fourier transform infrared spectrometry and car paints were analysed using Raman spectroscopy. In the forensic context analytical results must be interpreted and reported according to the standards of the interpretation schemes acknowledged in forensic sciences using the likelihood ratio approach. However, for proper construction of LR models for highly multivariate data, such as spectra, chemometric tools must be employed for substantial data compression. Conversion from classical feature representation to distance representation was proposed for revealing hidden data peculiarities and linear discriminant analysis was further applied for minimising the within-sample variability while maximising the between-sample variability. Both techniques enabled substantial reduction of data dimensionality. Univariate and multivariate likelihood ratio models were proposed for such data. It was shown that the combination of chemometric tools and the likelihood ratio approach is capable of solving the comparison problem of highly multivariate and correlated data after proper extraction of the most relevant features and variance information hidden in the data structure. Copyright © 2016 Elsevier B.V. All rights reserved.

The 'warm' side of coldness: Cold promotes interpersonal warmth in negative contexts.

PubMed

Wei, Wenqi; Ma, Jingjing; Wang, Lei

2015-12-01

The concrete experience of physical warmth has been demonstrated to promote interpersonal warmth. This well-documented link, however, tells only half of the story. In the current study, we thus examined whether physical coldness can also increase interpersonal warmth under certain circumstances. We conducted three experiments to demonstrate that the relationship between the experience of physical temperature and interpersonal outcomes is context dependent. Experiment 1 showed that participants touching cold (vs. warm) objects were more willing to forgive a peer's dishonest behaviour. Experiment 2 demonstrated the fully interactive effect of temperature and context on interpersonal warmth: Participants touching cold (vs. warm) objects were less likely to assist an individual who had provided them with good service (positive social context), but more likely to assist an individual who had provided them with poor service (negative social context). Experiment 3 replicated the results of Experiment 2 using the likelihood to complain, a hostility-related indicator, as the dependent variable: In a pleasant queue (positive social context), participants touching cold objects were more likely to complain and those touching warm objects were less likely to complain compared with the control group. This pattern was reversed in an annoying queue (negative social context). © 2015 The Authors. British Journal of Social Psychology published by John Wiley & Sons Ltd on behalf of British Psychological Society.

Multi-atlas segmentation for abdominal organs with Gaussian mixture models

NASA Astrophysics Data System (ADS)

Burke, Ryan P.; Xu, Zhoubing; Lee, Christopher P.; Baucom, Rebeccah B.; Poulose, Benjamin K.; Abramson, Richard G.; Landman, Bennett A.

2015-03-01

Abdominal organ segmentation with clinically acquired computed tomography (CT) is drawing increasing interest in the medical imaging community. Gaussian mixture models (GMM) have been extensively used through medical segmentation, most notably in the brain for cerebrospinal fluid / gray matter / white matter differentiation. Because abdominal CT exhibit strong localized intensity characteristics, GMM have recently been incorporated in multi-stage abdominal segmentation algorithms. In the context of variable abdominal anatomy and rich algorithms, it is difficult to assess the marginal contribution of GMM. Herein, we characterize the efficacy of an a posteriori framework that integrates GMM of organ-wise intensity likelihood with spatial priors from multiple target-specific registered labels. In our study, we first manually labeled 100 CT images. Then, we assigned 40 images to use as training data for constructing target-specific spatial priors and intensity likelihoods. The remaining 60 images were evaluated as test targets for segmenting 12 abdominal organs. The overlap between the true and the automatic segmentations was measured by Dice similarity coefficient (DSC). A median improvement of 145% was achieved by integrating the GMM intensity likelihood against the specific spatial prior. The proposed framework opens the opportunities for abdominal organ segmentation by efficiently using both the spatial and appearance information from the atlases, and creates a benchmark for large-scale automatic abdominal segmentation.

Exploring the impact of walk–bike infrastructure, safety perception, and built-environment on active transportation mode choice: a random parameter model using New York City commuter data

DOE PAGES

Aziz, H. M. Abdul; Nagle, Nicholas N.; Morton, April M.; ...

2017-02-06

Here, this study finds the effects of traffic safety, walk-bike network facilities, and land use attributes on walk and bicycle mode choice decision in the New York City for home-to-work commute. Applying the flexible econometric structure of random parameter models, we capture the heterogeneity in the decision making process and simulate scenarios considering improvement in walk-bike infrastructure such as sidewalk width and length of bike lane. Our results indicate that increasing sidewalk width, total length of bike lane, and proportion of protected bike lane will increase the likelihood of more people taking active transportation mode This suggests that the localmore » authorities and planning agencies to invest more on building and maintaining the infrastructure for pedestrians. Furthermore, improvement in traffic safety by reducing traffic crashes involving pedestrians and bicyclists will increase the likelihood of taking active transportation modes. Our results also show positive correlation between number of non-motorized trips by the other family members and the likelihood to choose active transportation mode. The findings will help to make smart investment decisions in context of building sustainable transportation systems accounting for active transportation.« less

Exploring the impact of walk–bike infrastructure, safety perception, and built-environment on active transportation mode choice: a random parameter model using New York City commuter data

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

Aziz, H. M. Abdul; Nagle, Nicholas N.; Morton, April M.

Here, this study finds the effects of traffic safety, walk-bike network facilities, and land use attributes on walk and bicycle mode choice decision in the New York City for home-to-work commute. Applying the flexible econometric structure of random parameter models, we capture the heterogeneity in the decision making process and simulate scenarios considering improvement in walk-bike infrastructure such as sidewalk width and length of bike lane. Our results indicate that increasing sidewalk width, total length of bike lane, and proportion of protected bike lane will increase the likelihood of more people taking active transportation mode This suggests that the localmore » authorities and planning agencies to invest more on building and maintaining the infrastructure for pedestrians. Furthermore, improvement in traffic safety by reducing traffic crashes involving pedestrians and bicyclists will increase the likelihood of taking active transportation modes. Our results also show positive correlation between number of non-motorized trips by the other family members and the likelihood to choose active transportation mode. The findings will help to make smart investment decisions in context of building sustainable transportation systems accounting for active transportation.« less

Superfast maximum-likelihood reconstruction for quantum tomography

NASA Astrophysics Data System (ADS)

Shang, Jiangwei; Zhang, Zhengyun; Ng, Hui Khoon

2017-06-01

Conventional methods for computing maximum-likelihood estimators (MLE) often converge slowly in practical situations, leading to a search for simplifying methods that rely on additional assumptions for their validity. In this work, we provide a fast and reliable algorithm for maximum-likelihood reconstruction that avoids this slow convergence. Our method utilizes the state-of-the-art convex optimization scheme, an accelerated projected-gradient method, that allows one to accommodate the quantum nature of the problem in a different way than in the standard methods. We demonstrate the power of our approach by comparing its performance with other algorithms for n -qubit state tomography. In particular, an eight-qubit situation that purportedly took weeks of computation time in 2005 can now be completed in under a minute for a single set of data, with far higher accuracy than previously possible. This refutes the common claim that MLE reconstruction is slow and reduces the need for alternative methods that often come with difficult-to-verify assumptions. In fact, recent methods assuming Gaussian statistics or relying on compressed sensing ideas are demonstrably inapplicable for the situation under consideration here. Our algorithm can be applied to general optimization problems over the quantum state space; the philosophy of projected gradients can further be utilized for optimization contexts with general constraints.

Cardiorespiratory dynamics measured from continuous ECG monitoring improves detection of deterioration in acute care patients: A retrospective cohort study

PubMed Central

Clark, Matthew T.; Calland, James Forrest; Enfield, Kyle B.; Voss, John D.; Lake, Douglas E.; Moorman, J. Randall

2017-01-01

Background Charted vital signs and laboratory results represent intermittent samples of a patient’s dynamic physiologic state and have been used to calculate early warning scores to identify patients at risk of clinical deterioration. We hypothesized that the addition of cardiorespiratory dynamics measured from continuous electrocardiography (ECG) monitoring to intermittently sampled data improves the predictive validity of models trained to detect clinical deterioration prior to intensive care unit (ICU) transfer or unanticipated death. Methods and findings We analyzed 63 patient-years of ECG data from 8,105 acute care patient admissions at a tertiary care academic medical center. We developed models to predict deterioration resulting in ICU transfer or unanticipated death within the next 24 hours using either vital signs, laboratory results, or cardiorespiratory dynamics from continuous ECG monitoring and also evaluated models using all available data sources. We calculated the predictive validity (C-statistic), the net reclassification improvement, and the probability of achieving the difference in likelihood ratio χ2 for the additional degrees of freedom. The primary outcome occurred 755 times in 586 admissions (7%). We analyzed 395 clinical deteriorations with continuous ECG data in the 24 hours prior to an event. Using only continuous ECG measures resulted in a C-statistic of 0.65, similar to models using only laboratory results and vital signs (0.63 and 0.69 respectively). Addition of continuous ECG measures to models using conventional measurements improved the C-statistic by 0.01 and 0.07; a model integrating all data sources had a C-statistic of 0.73 with categorical net reclassification improvement of 0.09 for a change of 1 decile in risk. The difference in likelihood ratio χ2 between integrated models with and without cardiorespiratory dynamics was 2158 (p value: <0.001). Conclusions Cardiorespiratory dynamics from continuous ECG monitoring detect clinical deterioration in acute care patients and improve performance of conventional models that use only laboratory results and vital signs. PMID:28771487

Cardiorespiratory dynamics measured from continuous ECG monitoring improves detection of deterioration in acute care patients: A retrospective cohort study.

PubMed

Moss, Travis J; Clark, Matthew T; Calland, James Forrest; Enfield, Kyle B; Voss, John D; Lake, Douglas E; Moorman, J Randall

2017-01-01

Charted vital signs and laboratory results represent intermittent samples of a patient's dynamic physiologic state and have been used to calculate early warning scores to identify patients at risk of clinical deterioration. We hypothesized that the addition of cardiorespiratory dynamics measured from continuous electrocardiography (ECG) monitoring to intermittently sampled data improves the predictive validity of models trained to detect clinical deterioration prior to intensive care unit (ICU) transfer or unanticipated death. We analyzed 63 patient-years of ECG data from 8,105 acute care patient admissions at a tertiary care academic medical center. We developed models to predict deterioration resulting in ICU transfer or unanticipated death within the next 24 hours using either vital signs, laboratory results, or cardiorespiratory dynamics from continuous ECG monitoring and also evaluated models using all available data sources. We calculated the predictive validity (C-statistic), the net reclassification improvement, and the probability of achieving the difference in likelihood ratio χ2 for the additional degrees of freedom. The primary outcome occurred 755 times in 586 admissions (7%). We analyzed 395 clinical deteriorations with continuous ECG data in the 24 hours prior to an event. Using only continuous ECG measures resulted in a C-statistic of 0.65, similar to models using only laboratory results and vital signs (0.63 and 0.69 respectively). Addition of continuous ECG measures to models using conventional measurements improved the C-statistic by 0.01 and 0.07; a model integrating all data sources had a C-statistic of 0.73 with categorical net reclassification improvement of 0.09 for a change of 1 decile in risk. The difference in likelihood ratio χ2 between integrated models with and without cardiorespiratory dynamics was 2158 (p value: <0.001). Cardiorespiratory dynamics from continuous ECG monitoring detect clinical deterioration in acute care patients and improve performance of conventional models that use only laboratory results and vital signs.

Efficient Exploration of the Space of Reconciled Gene Trees

PubMed Central

Szöllősi, Gergely J.; Rosikiewicz, Wojciech; Boussau, Bastien; Tannier, Eric; Daubin, Vincent

2013-01-01

Gene trees record the combination of gene-level events, such as duplication, transfer and loss (DTL), and species-level events, such as speciation and extinction. Gene tree–species tree reconciliation methods model these processes by drawing gene trees into the species tree using a series of gene and species-level events. The reconstruction of gene trees based on sequence alone almost always involves choosing between statistically equivalent or weakly distinguishable relationships that could be much better resolved based on a putative species tree. To exploit this potential for accurate reconstruction of gene trees, the space of reconciled gene trees must be explored according to a joint model of sequence evolution and gene tree–species tree reconciliation. Here we present amalgamated likelihood estimation (ALE), a probabilistic approach to exhaustively explore all reconciled gene trees that can be amalgamated as a combination of clades observed in a sample of gene trees. We implement the ALE approach in the context of a reconciliation model (Szöllősi et al. 2013), which allows for the DTL of genes. We use ALE to efficiently approximate the sum of the joint likelihood over amalgamations and to find the reconciled gene tree that maximizes the joint likelihood among all such trees. We demonstrate using simulations that gene trees reconstructed using the joint likelihood are substantially more accurate than those reconstructed using sequence alone. Using realistic gene tree topologies, branch lengths, and alignment sizes, we demonstrate that ALE produces more accurate gene trees even if the model of sequence evolution is greatly simplified. Finally, examining 1099 gene families from 36 cyanobacterial genomes we find that joint likelihood-based inference results in a striking reduction in apparent phylogenetic discord, with respectively. 24%, 59%, and 46% reductions in the mean numbers of duplications, transfers, and losses per gene family. The open source implementation of ALE is available from https://github.com/ssolo/ALE.git. [amalgamation; gene tree reconciliation; gene tree reconstruction; lateral gene transfer; phylogeny.] PMID:23925510

Assessment of goals and priorities in patients with a chronic condition: a secondary quantitative analysis of determinants across 11 countries.

PubMed

Vermunt, Neeltje P C A; Westert, Gert P; Olde Rikkert, Marcel G M; Faber, Marjan J

2018-03-01

To assess the impact of patient characteristics, patient-professional engagement, communication and context on the probability that healthcare professionals will discuss goals or priorities with older patients. Secondary analysis of cross-sectional data from the 2014 Commonwealth Fund International Health Policy Survey of Older Adults. 11 western countries. Community-dwelling adults, aged 55 or older. Assessment of goals and priorities. The final sample size consisted of 17,222 respondents, 54% of whom reported an assessment of their goals and priorities (AGP) by healthcare professionals. In logistic regression model 1, which was used to analyse the entire population, the determinants found to have moderate to large effects on the likelihood of AGP were information exchange on stress, diet or exercise, or both. Country (living in Sweden) and continuity of care (no regular professional or organisation) had moderate to large negative effects on the likelihood of AGP. In model 2, which focussed on respondents who experienced continuity of care, country and information exchange on stress and lifestyle were the main determinants of AGP, with comparable odds ratios to model 1. Furthermore, a professional asking questions also increased the likelihood of AGP. Continuity of care and information exchange is associated with a higher probability of AGP, while people living in Sweden are less likely to experience these assessments. Further study is required to determine whether increasing information exchange and professionals asking more questions may improve goal setting with older patients. Key points   A patient goal-oriented approach can be beneficial for older patients with chronic conditions or multimorbidity; however, discussing goals with these patients is not a common practice. The likelihood of discussing goals varies by country, occurring most commonly in the USA, and least often in Sweden. Country-level differences in continuity of care and questions asked by a regularly visited professional affect the goal discussion probability. Patient characteristics, including age, have less impact than expected on the likelihood of sharing goals.

Early Lapses in a Cessation Attempt: Lapse Contexts, Cessation Success, and Predictors of Early Lapse

PubMed Central

2013-01-01

Introduction: The great majority of smokers relapse when they make quit attempts. Therefore, understanding the process of relapse may guide the development of more effective smoking cessation or relapse prevention treatments. The goal of this research is to extend our understanding of the context of initial lapses that occur within 8 weeks of quitting by using more comprehensive assessments of context, a contemporary sample, and sophisticated analytic techniques. Methods: Participants from a randomized controlled smoking cessation trial completed baseline assessments of demographics and tobacco dependence, a daily smoking calendar to determine latency to lapse and relapse (7 consecutive days of smoking), and an assessment of initial lapse context (affect, location, activity, interpersonal, smoke exposure, and cigarette availability). Latent class analysis (LCA) was used to analyze the 6 early lapse (within the first 8 weeks; N = 551) context dimensions; logistic regression and Cox regression were used to relate context to cessation outcomes. Results: LCA revealed 5 distinct initial lapse context classes (talking, with friends, angry; social; alone; with spouse, angry; and with smoking spouse) that were differentially related to cessation outcome. The easy availability of cigarettes characterized almost 75% of lapses, but being with friends, drinking, and not being at home were associated with a lower likelihood of progression to relapse. Conclusions: Early lapsing is highly related to ultimate relapse, and lapsing in frequently experienced contexts seemed most strongly linked with progression to full relapse. PMID:23780705

A Single Camera Motion Capture System for Human-Computer Interaction

NASA Astrophysics Data System (ADS)

Okada, Ryuzo; Stenger, Björn

This paper presents a method for markerless human motion capture using a single camera. It uses tree-based filtering to efficiently propagate a probability distribution over poses of a 3D body model. The pose vectors and associated shapes are arranged in a tree, which is constructed by hierarchical pairwise clustering, in order to efficiently evaluate the likelihood in each frame. Anew likelihood function based on silhouette matching is proposed that improves the pose estimation of thinner body parts, i. e. the limbs. The dynamic model takes self-occlusion into account by increasing the variance of occluded body-parts, thus allowing for recovery when the body part reappears. We present two applications of our method that work in real-time on a Cell Broadband Engine™: a computer game and a virtual clothing application.

Enhancing Learners' Emotions in an L2 Context through Emotionalized Dynamic Assessment

ERIC Educational Resources Information Center

Abdolrezapour, Parisa; Tavakoli, Mansoor; Ketabi, Saeed

2013-01-01

The aim of this study was to gain more in-depth understanding of students' emotions in an EFL context by applying dynamic assessment (DA) procedures to the development of learners' emotional intelligence. The study with 50 intermediate learners aged 12-15 used three modalities: a control group, which was taught under institute's normal procedures;…

Family Income Dynamics, Early Childhood Education and Care, and Early Child Behavior Problems in Norway

ERIC Educational Resources Information Center

Zachrisson, Henrik D.; Dearing, Eric

2015-01-01

The sociopolitical context of Norway includes low poverty rates and universal access to subsidized and regulated Early Childhood Education and Care (ECEC). In this context, the association between family income dynamics and changes in early child behavior problems was investigated, as well as whether high-quality ECEC buffers children from the…

The utility of combining RSA indices in depression prediction.

PubMed

Yaroslavsky, Ilya; Rottenberg, Jonathan; Kovacs, Maria

2013-05-01

Depression is associated with protracted despondent mood, blunted emotional reactivity, and dysregulated parasympathetic nervous system (PNS) activity. PNS activity is commonly indexed via cardiac output, using indictors of its level (resting respiratory sinus arrhythmia [RSA]) or fluctuations (RSA reactivity). RSA reactivity can reflect increased or decreased PNS cardiac output (RSA augmentation and RSA withdrawal, respectively). Because a single index of a dynamic physiological system may be inadequate to characterize interindividual differences, we investigated whether the interaction of RSA reactivity and resting RSA is a better predictor of depression. Adult probands with childhood-onset depressive disorder histories (n = 113) and controls with no history of major mental disorders (n = 93) completed a psychophysiology protocol involving assessment of RSA at multiple rest periods and while watching a sad film. When examined independently, resting RSA and RSA reactivity were unrelated to depression, but their interaction predicted latent depression levels and proband status. In the context of high resting RSA, RSA withdrawal from the sad film predicted the lowest levels of depressive symptoms (irrespective of depression histories) and the greatest likelihood of having had no history of major mental disorder (irrespective of current distress). Our findings highlight the utility of combining indices of physiological responses in studying depression; combinations of RSA indices should be given future consideration as reflecting depression endophenotypes. © 2013 American Psychological Association

Infusional β-lactam antibiotics in febrile neutropenia: has the time come?

PubMed

Abbott, Iain J; Roberts, Jason A

2012-12-01

Febrile neutropenia presents a clinical challenge in which timely and appropriate antibiotic exposure is crucial. In the context of altered pharmacokinetics and rising bacterial resistance, standard antibiotic doses are unlikely to be sufficient. This review explores the potential utility of altered dosing approaches of β-lactam antibiotics to optimize treatment in febrile neutropenia. There is a dynamic relationship between the antibiotic, the infecting pathogen, and the host. Great advancements have been made in the understanding of the pharmacokinetic changes in critical illness and the pharmacodynamic relationships of antibiotics in these settings. Antibiotic treatment in febrile neutropenia is becoming increasingly difficult. Patients are of higher acuity, receive more intensive chemotherapy regimens leading to prolonged neutropenia, and are often exposed to multiple antibiotic courses. These patients display significant variability in antibiotic clearances and increases in volume of distribution compared with standard ward-based patients. Rising antibiotic resistance and a lack of new antibiotics in production have prompted alternative dosing strategies based on pharmacokinetic/pharmacodynamic data, such as extended or continuous infusions of β-lactam antibiotics, to maximize the likelihood of treatment success. A definitive study that describes a mortality benefit of such dosing regimens remains elusive and the theoretical advantages require testing in well designed clinical trials.

Estimation in a discrete tail rate family of recapture sampling models

NASA Technical Reports Server (NTRS)

Gupta, Rajan; Lee, Larry D.

1990-01-01

In the context of recapture sampling design for debugging experiments the problem of estimating the error or hitting rate of the faults remaining in a system is considered. Moment estimators are derived for a family of models in which the rate parameters are assumed proportional to the tail probabilities of a discrete distribution on the positive integers. The estimators are shown to be asymptotically normal and fully efficient. Their fixed sample properties are compared, through simulation, with those of the conditional maximum likelihood estimators.

Beware of Imitators: Al-Qa’ida through the Lens of its Confidential Secretary

DTIC Science & Technology

2012-06-04

reader; rather in all likelihood are the result of several factors, including Harun’s lapses in memory ; his having to make notes while evading the...they also earned it an indelible place in the collective memory of Washington’s political and intelligence community. In the mind of the then National...a reflective autobiographical style, e.g., the first part narrates his early life in the context of his native homeland, the Comoros Islands, and

The l z ( p ) * Person-Fit Statistic in an Unfolding Model Context.

PubMed

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.

Ethics and risk management in administrative child and adolescent psychiatry.

PubMed

Sondheimer, Adrian

2010-01-01

This article examines ethics (the philosophic study of "doing the right thing") and risk management (the practice that seeks to manage the likelihood of "doing the wrong thing") and the relationship between them in the context of administrative child and adolescent psychiatry. Issues that affect child and adolescent psychiatrists who manage staff and business units and clinical practitioners who treat and manage individual patients are addressed. Malpractice, budgeting, credentialing, boundaries, assessment, documentation, treatment, research, dangerousness, and confidentiality are among the topics reviewed.

Identification of cascade water tanks using a PWARX model

NASA Astrophysics Data System (ADS)

Mattsson, Per; Zachariah, Dave; Stoica, Petre

2018-06-01

In this paper we consider the identification of a discrete-time nonlinear dynamical model for a cascade water tank process. The proposed method starts with a nominal linear dynamical model of the system, and proceeds to model its prediction errors using a model that is piecewise affine in the data. As data is observed, the nominal model is refined into a piecewise ARX model which can capture a wide range of nonlinearities, such as the saturation in the cascade tanks. The proposed method uses a likelihood-based methodology which adaptively penalizes model complexity and directly leads to a computationally efficient implementation.

Malaria control under unstable dynamics: reactive vs. climate-based strategies.

PubMed

Baeza, Andres; Bouma, Menno J; Dhiman, Ramesh; Pascual, Mercedes

2014-01-01

In areas of the world where malaria prevails under unstable conditions, attacking the adult vector population through insecticide-based Indoor Residual Spraying (IRS) is the most common method for controlling epidemics. Defined in policy guidance, the use of Annual Parasitic Incidence (API) is an important tool for assessing the effectiveness of control and for planning new interventions. To investigate the consequences that a policy based on API in previous seasons might have on the population dynamics of the disease and on control itself in regions of low and seasonal transmission, we formulate a mathematical malaria model that couples epidemiologic and vector dynamics with IRS intervention. This model is parameterized for a low transmission and semi-arid region in northwest India, where epidemics are driven by high rainfall variability. We show that this type of feedback mechanism in control strategies can generate transient cycles in malaria even in the absence of environmental variability, and that this tendency to cycle can in turn limit the effectiveness of control in the presence of such variability. Specifically, for realistic rainfall conditions and over a range of control intensities, the effectiveness of such 'reactive' intervention is compared to that of an alternative strategy based on rainfall and therefore vector variability. Results show that the efficacy of intervention is strongly influenced by rainfall variability and the type of policy implemented. In particular, under an API 'reactive' policy, high vector populations can coincide more frequently with low control coverage, and in so doing generate large unexpected epidemics and decrease the likelihood of elimination. These results highlight the importance of incorporating information on climate variability, rather than previous incidence, in planning IRS interventions in regions of unstable malaria. These findings are discussed in the more general context of elimination and other low transmission regions such as highlands. Copyright © 2013. Published by Elsevier B.V.

Dynamics of a low-density tiger population in Southeast Asia in the context of improved law enforcement.

PubMed

Duangchantrasiri, Somphot; Umponjan, Mayuree; Simcharoen, Saksit; Pattanavibool, Anak; Chaiwattana, Soontorn; Maneerat, Sompoch; Kumar, N Samba; Jathanna, Devcharan; Srivathsa, Arjun; Karanth, K Ullas

2016-06-01

Recovering small populations of threatened species is an important global conservation strategy. Monitoring the anticipated recovery, however, often relies on uncertain abundance indices rather than on rigorous demographic estimates. To counter the severe threat from poaching of wild tigers (Panthera tigris), the Government of Thailand established an intensive patrolling system in 2005 to protect and recover its largest source population in Huai Kha Khaeng Wildlife Sanctuary. Concurrently, we assessed the dynamics of this tiger population over the next 8 years with rigorous photographic capture-recapture methods. From 2006 to 2012, we sampled across 624-1026 km(2) with 137-200 camera traps. Cameras deployed for 21,359 trap days yielded photographic records of 90 distinct individuals. We used closed model Bayesian spatial capture-recapture methods to estimate tiger abundances annually. Abundance estimates were integrated with likelihood-based open model analyses to estimate rates of annual and overall rates of survival, recruitment, and changes in abundance. Estimates of demographic parameters fluctuated widely: annual density ranged from 1.25 to 2.01 tigers/100 km(2) , abundance from 35 to 58 tigers, survival from 79.6% to 95.5%, and annual recruitment from 0 to 25 tigers. The number of distinct individuals photographed demonstrates the value of photographic capture-recapture methods for assessments of population dynamics in rare and elusive species that are identifiable from natural markings. Possibly because of poaching pressure, overall tiger densities at Huai Kha Khaeng were 82-90% lower than in ecologically comparable sites in India. However, intensified patrolling after 2006 appeared to reduce poaching and was correlated with marginal improvement in tiger survival and recruitment. Our results suggest that population recovery of low-density tiger populations may be slower than anticipated by current global strategies aimed at doubling the number of wild tigers in a decade. © 2015 Society for Conservation Biology.

The Role of piRNA-Mediated Epigenetic Silencing in the Population Dynamics of Transposable Elements in Drosophila melanogaster

PubMed Central

Lee, Yuh Chwen G.

2015-01-01

The piwi-interacting RNAs (piRNA) are small RNAs that target selfish transposable elements (TEs) in many animal genomes. Until now, piRNAs’ role in TE population dynamics has only been discussed in the context of their suppression of TE transposition, which alone is not sufficient to account for the skewed frequency spectrum and stable containment of TEs. On the other hand, euchromatic TEs can be epigenetically silenced via piRNA-dependent heterochromatin formation and, similar to the widely known “Position-effect variegation”, heterochromatin induced by TEs can “spread” into nearby genes. We hypothesized that the piRNA-mediated spread of heterochromatin from TEs into adjacent genes has deleterious functional effects and leads to selection against individual TEs. Unlike previously identified deleterious effects of TEs due to the physical disruption of DNA, the functional effect we investigated here is mediated through the epigenetic influences of TEs. We found that the repressive chromatin mark, H3K9me, is elevated in sequences adjacent to euchromatic TEs at multiple developmental stages in Drosophila melanogaster. Furthermore, the heterochromatic states of genes depend not only on the number of and distance from adjacent TEs, but also on the likelihood that their nearest TEs are targeted by piRNAs. These variations in chromatin status probably have functional consequences, causing genes near TEs to have lower expression. Importantly, we found stronger selection against TEs that lead to higher H3K9me enrichment of adjacent genes, demonstrating the pervasive evolutionary consequences of TE-induced epigenetic silencing. Because of the intrinsic biological mechanism of piRNA amplification, spread of TE heterochromatin could result in the theoretically required synergistic deleterious effects of TE insertions for stable containment of TE copy number. The indirect deleterious impact of piRNA-mediated epigenetic silencing of TEs is a previously unexplored, yet important, element for the evolutionary dynamics of TEs. PMID:26042931

A probabilistic model of debris-flow delivery to stream channels, demonstrated for the Coast Range of Oregon, USA

Treesearch

Daniel J. Miller; Kelly M. Burnett

2008-01-01

Debris flows are important geomorphic agents in mountainous terrains that shape channel environments and add a dynamic element to sediment supply and channel disturbance. Identification of channels susceptible to debris-flow inputs of sediment and organic debris, and quantification of the likelihood and magnitude of those inputs, are key tasks for characterizing...

If Men Do More Housework, Do Their Wives Have More Babies?

ERIC Educational Resources Information Center

Craig, Lyn; Siminski, Peter

2011-01-01

We analyze data from the Household, Income and Labour Dynamics in Australia (HILDA) survey waves 1-6, to investigate whether the housework and childcare contributions of coupled Australian men with one child affect the likelihood that their wives will have a second child. We find no evidence that the way housework or childcare is shared has an…

Real-Time Population Health Detector

DTIC Science & Technology

2004-11-01

military and civilian populations. General Dynamics (then Veridian Systems Division), in cooperation with Stanford University, won a competitive DARPA...via the sequence of one-step ahead forecast errors from the Kalman recursions: 1| −−= tttt Hye µ The log-likelihood then follows by treating the... parking in the transient parking structure. Norfolk Area Military Treatment Facility Patient Files GDAIS received historic CHCS data from all

The Influence of Education on Violent Conflict and Peace: Inequality, Opportunity and the Management of Diversity

ERIC Educational Resources Information Center

Brown, Graham K.

2011-01-01

This article examines the ways in which education and educational policy impact upon the likelihood and dynamics of violent conflict. It argues that education is rarely directly implicated in the incidence of violent conflict but identifies three main mechanisms through which education can indirectly accentuate or mitigate the risk of conflict:…

State-Space Modeling of Dynamic Psychological Processes via the Kalman Smoother Algorithm: Rationale, Finite Sample Properties, and Applications

ERIC Educational Resources Information Center

Song, Hairong; Ferrer, Emilio

2009-01-01

This article presents a state-space modeling (SSM) technique for fitting process factor analysis models directly to raw data. The Kalman smoother via the expectation-maximization algorithm to obtain maximum likelihood parameter estimates is used. To examine the finite sample properties of the estimates in SSM when common factors are involved, a…

Volunteerism: Social Network Dynamics and Education

PubMed Central

Ajrouch, Kristine J.; Antonucci, Toni C.; Webster, Noah J.

2016-01-01

Objectives . We examine how changes in social networks influence volunteerism through bridging (diversity) and bonding (spending time) mechanisms. We further investigate whether social network change substitutes or amplifies the effects of education on volunteerism. Methods . Data (n = 543) are drawn from a two-wave survey of Social Relations and Health over the Life Course (SRHLC). Zero-inflated negative binomial regressions were conducted to test competing hypotheses about how changes in social network characteristics alone and in conjunction with education level predict likelihood and frequency of volunteering. Results . Changes in social networks were associated with volunteerism: as the proportion of family members decreased and the average number of network members living within a one-hour drive increased over time, participants reported higher odds of volunteering. The substitution hypothesis was supported: social networks that exhibited more geographic proximity and greater contact frequency over-time compensated for lower levels of education to predict volunteering more hours. Discussion . The dynamic role of social networks and the ways in which they may work through bridging and bonding to influence both likelihood and frequency of volunteering are discussed. The potential benefits of volunteerism in light of longer life expectancies and smaller families are also considered. PMID:25512570

Estimation of Time-Varying Pilot Model Parameters

NASA Technical Reports Server (NTRS)

Zaal, Peter M. T.; Sweet, Barbara T.

2011-01-01

Human control behavior is rarely completely stationary over time due to fatigue or loss of attention. In addition, there are many control tasks for which human operators need to adapt their control strategy to vehicle dynamics that vary in time. In previous studies on the identification of time-varying pilot control behavior wavelets were used to estimate the time-varying frequency response functions. However, the estimation of time-varying pilot model parameters was not considered. Estimating these parameters can be a valuable tool for the quantification of different aspects of human time-varying manual control. This paper presents two methods for the estimation of time-varying pilot model parameters, a two-step method using wavelets and a windowed maximum likelihood estimation method. The methods are evaluated using simulations of a closed-loop control task with time-varying pilot equalization and vehicle dynamics. Simulations are performed with and without remnant. Both methods give accurate results when no pilot remnant is present. The wavelet transform is very sensitive to measurement noise, resulting in inaccurate parameter estimates when considerable pilot remnant is present. Maximum likelihood estimation is less sensitive to pilot remnant, but cannot detect fast changes in pilot control behavior.

Nonparametric modeling of longitudinal covariance structure in functional mapping of quantitative trait loci.

PubMed

Yap, John Stephen; Fan, Jianqing; Wu, Rongling

2009-12-01

Estimation of the covariance structure of longitudinal processes is a fundamental prerequisite for the practical deployment of functional mapping designed to study the genetic regulation and network of quantitative variation in dynamic complex traits. We present a nonparametric approach for estimating the covariance structure of a quantitative trait measured repeatedly at a series of time points. Specifically, we adopt Huang et al.'s (2006, Biometrika 93, 85-98) approach of invoking the modified Cholesky decomposition and converting the problem into modeling a sequence of regressions of responses. A regularized covariance estimator is obtained using a normal penalized likelihood with an L(2) penalty. This approach, embedded within a mixture likelihood framework, leads to enhanced accuracy, precision, and flexibility of functional mapping while preserving its biological relevance. Simulation studies are performed to reveal the statistical properties and advantages of the proposed method. A real example from a mouse genome project is analyzed to illustrate the utilization of the methodology. The new method will provide a useful tool for genome-wide scanning for the existence and distribution of quantitative trait loci underlying a dynamic trait important to agriculture, biology, and health sciences.

“Connectedness to Nature Scale”: Validity and Reliability in the French Context

PubMed Central

Navarro, Oscar; Olivos, Pablo; Fleury-Bahi, Ghozlane

2017-01-01

Connectedness to nature represents the relationship of the self with the natural environment and has been operationalized using different scales. One of the most systematically studied in the Anglo-Saxon context is the Connectedness to Nature Scale (CNS). In an attempt to study the psychometric properties of this instrument in a French-speaking context, three studies (Study 1 n = 204, Study 2 n = 153, and Study 3 n = 322) were carried out in France to provide evidence of the internal consistency of the CNS, as well as its convergent, discriminant, and predictive validity. Moreover, as anticipated, positive correlations between the CNS and the environmental identity and environmental concerns scales were observed. Based on factorial analyses of maximum likelihood and reliability, an improvement in the psychometric properties was identified by eliminating three items. Through confirmatory factor analysis, the factorial structure and the psychometric properties of the CNS French version were confirmed, as well as their significate regression prediction on eudaimonic wellbeing. PMID:29312052

Influences of neighborhood context, individual history and parenting behavior on recidivism among juvenile offenders.

PubMed

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.

"Transformation Tuesday": Temporal context and post valence influence the provision of social support on social media.

PubMed

Vogel, Erin A; Rose, Jason P; Crane, Chantal

2018-01-01

Social network sites (SNSs) such as Facebook have become integral in the development and maintenance of interpersonal relationships. Users of SNSs seek social support and validation, often using posts that illustrate how they have changed over time. The purpose of the present research is to examine how the valence and temporal context of an SNS post affect the likelihood of other users providing social support. Participants viewed hypothetical SNS posts and reported their intentions to provide social support to the users. Results revealed that participants were more likely to provide social support for posts that were positive and included temporal context (i.e., depicted improvement over time; Study 1). Furthermore, this research suggests that visual representations of change over time are needed to elicit social support (Study 2). Results are discussed in terms of their practical implications for SNS users and theoretical implications for the literature on social support and social media.

Social context and sexual intercourse among first-year students at selective colleges and universities in the United States.

PubMed

Uecker, Jeremy E

2015-07-01

Most examinations of sexual behavior ignore social context. Using panel data from the National Longitudinal Study of Freshmen, a panel study of 3924 students at 28 selective colleges and universities, I examine how institutional and peer-group characteristics influence the incidence of sexual intercourse among students during their freshman year. Students who enter college as virgins are more likely to have sexual intercourse on campuses where women comprise a higher proportion of the campus population and on campuses that are more academically rigorous. Students who had sex prior to college are less likely to have sex in college when campuses are more residential. Moreover, having friends who value religion and partying affects the likelihood that a student will have sex irrespective of their prior virginity status. These findings highlight the importance of social context for sexual behavior among college students and in the general population. Copyright © 2015 Elsevier Inc. All rights reserved.

The application of system dynamics modelling to environmental health decision-making and policy - a scoping review.

PubMed

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.

A framework for extracting and representing project knowledge contexts using topic models and dynamic knowledge maps

NASA Astrophysics Data System (ADS)

Xu, Jin; Li, Zheng; Li, Shuliang; Zhang, Yanyan

2015-07-01

There is still a lack of effective paradigms and tools for analysing and discovering the contents and relationships of project knowledge contexts in the field of project management. In this paper, a new framework for extracting and representing project knowledge contexts using topic models and dynamic knowledge maps under big data environments is proposed and developed. The conceptual paradigm, theoretical underpinning, extended topic model, and illustration examples of the ontology model for project knowledge maps are presented, with further research work envisaged.

A note by any other name: Intonation context rapidly changes absolute note judgments.

PubMed

Van Hedger, Stephen C; Heald, Shannon L M; Uddin, Sophia; Nusbaum, Howard C

2018-04-30

Absolute pitch (AP) judgments, by definition, do not require a reference note, and thus might be viewed as context independent. Here, we specifically test whether short-term exposure to particular intonation contexts influences AP categorization on a rapid time scale and whether such context effects can change from moment to moment. In Experiment 1, participants heard duets in which a "lead" instrument always began before a "secondary" instrument. Both instruments independently varied on intonation (flat, in-tune, or sharp). Despite participants being instructed to judge only the intonation of the secondary instrument, we found that participants treated the lead instrument's intonation as "in-tune" and intonation judgments of the secondary instrument were relativized against this standard. In Experiment 2, participants heard a short antecedent context melody (flat, in-tune, or sharp) followed by an isolated target note (flat, in-tune, or sharp). Target note intonation judgments were once again relativized against the context melody's intonation, though only for notes that were experienced in the context or implied by the context key signature. Moreover, maximally contrastive intonation combinations of context and target engendered systematic note misclassifications. For example, a flat melody resulted in a greater likelihood of misclassifying a "sharp F-sharp" as a "G." These results highlight that both intonation and note category judgments among AP possessors are rapidly modified by the listening environment on the order of seconds, arguing against an invariant mental representation of the absolute pitches of notes. Implications for general auditory theories of perception are discussed. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Context and group dynamics in a CBPR-developed HIV prevention intervention

PubMed Central

Dickson-Gomez, Julia; Corbett, A. Michelle; Bodnar, Gloria; Zuniga, Maria Ofelia; Guevara, Carmen Eugenia; Rodriguez, Karla; Navas, Verónica

2016-01-01

This paper will explore in detail the effects of context and group dynamics on the development of a multi-level community-based HIV prevention intervention for crack cocaine users in the San Salvador Metropolitan Area, El Salvador. Community partners included residents from marginal communities, service providers from the historic center of San Salvador and research staff from a non-profit organization. The community contexts from which partners came varied considerably and affected structural group dynamics, i.e. who was identified as community partners, their research and organizational capacity, and their ability to represent their communities, with participants from marginal communities most likely to hold community leadership positions and be residents, and those from the center of San Salvador most likely to work in religious organizations dedicated to HIV prevention or feeding indigent drug users. These differences also affected the intervention priorities of different partners. The context of communities changed over time, particularly levels of violence, and affected group dynamics and the intervention developed. Finally, strategies were needed to elicit input from stakeholders under-represented in the community advisory board, in particular active crack users, in order to check the feasibility of the proposed intervention and revise it as necessary. Because El Salvador is a very different context than that in which most CBPR studies have been conducted, our results reveal important contextual factors and their effects on partnerships not often considered in the literature. PMID:25070835

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.

Supervised multimedia categorization

NASA Astrophysics Data System (ADS)

Aldershoff, Frank; Salden, Alfons H.; Iacob, Sorin M.; Kempen, Masja

2003-01-01

Static multimedia on the Web can already be hardly structured manually. Although unavoidable and necessary, manual annotation of dynamic multimedia becomes even less feasible when multimedia quickly changes in complexity, i.e. in volume, modality, and usage context. The latter context could be set by learning or other purposes of the multimedia material. This multimedia dynamics calls for categorisation systems that index, query and retrieve multimedia objects on the fly in a similar way as a human expert would. We present and demonstrate such a supervised dynamic multimedia object categorisation system. Our categorisation system comes about by continuously gauging it to a group of human experts who annotate raw multimedia for a certain domain ontology given a usage context. Thus effectively our system learns the categorisation behaviour of human experts. By inducing supervised multi-modal content and context-dependent potentials our categorisation system associates field strengths of raw dynamic multimedia object categorisations with those human experts would assign. After a sufficient long period of supervised machine learning we arrive at automated robust and discriminative multimedia categorisation. We demonstrate the usefulness and effectiveness of our multimedia categorisation system in retrieving semantically meaningful soccer-video fragments, in particular by taking advantage of multimodal and domain specific information and knowledge supplied by human experts.

Leveraging Cognitive Context for Object Recognition

DTIC Science & Technology

2014-06-01

learned from large image databases. We build upon this concept by exploring cognitive context, demonstrating how rich dynamic context provided by...context that people rely upon as they perceive the world. Context in ACT-R/E takes the form of associations between related concepts that are learned ...and accuracy of object recognition. Context is most often viewed as a static concept, learned from large image databases. We build upon this concept by

Extreme-Scale Bayesian Inference for Uncertainty Quantification of Complex Simulations

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

Biros, George

Uncertainty quantification (UQ)—that is, quantifying uncertainties in complex mathematical models and their large-scale computational implementations—is widely viewed as one of the outstanding challenges facing the field of CS&E over the coming decade. The EUREKA project set to address the most difficult class of UQ problems: those for which both the underlying PDE model as well as the uncertain parameters are of extreme scale. In the project we worked on these extreme-scale challenges in the following four areas: 1. Scalable parallel algorithms for sampling and characterizing the posterior distribution that exploit the structure of the underlying PDEs and parameter-to-observable map. Thesemore » include structure-exploiting versions of the randomized maximum likelihood method, which aims to overcome the intractability of employing conventional MCMC methods for solving extreme-scale Bayesian inversion problems by appealing to and adapting ideas from large-scale PDE-constrained optimization, which have been very successful at exploring high-dimensional spaces. 2. Scalable parallel algorithms for construction of prior and likelihood functions based on learning methods and non-parametric density estimation. Constructing problem-specific priors remains a critical challenge in Bayesian inference, and more so in high dimensions. Another challenge is construction of likelihood functions that capture unmodeled couplings between observations and parameters. We will create parallel algorithms for non-parametric density estimation using high dimensional N-body methods and combine them with supervised learning techniques for the construction of priors and likelihood functions. 3. Bayesian inadequacy models, which augment physics models with stochastic models that represent their imperfections. The success of the Bayesian inference framework depends on the ability to represent the uncertainty due to imperfections of the mathematical model of the phenomena of interest. This is a central challenge in UQ, especially for large-scale models. We propose to develop the mathematical tools to address these challenges in the context of extreme-scale problems. 4. Parallel scalable algorithms for Bayesian optimal experimental design (OED). Bayesian inversion yields quantified uncertainties in the model parameters, which can be propagated forward through the model to yield uncertainty in outputs of interest. This opens the way for designing new experiments to reduce the uncertainties in the model parameters and model predictions. Such experimental design problems have been intractable for large-scale problems using conventional methods; we will create OED algorithms that exploit the structure of the PDE model and the parameter-to-output map to overcome these challenges. Parallel algorithms for these four problems were created, analyzed, prototyped, implemented, tuned, and scaled up for leading-edge supercomputers, including UT-Austin’s own 10 petaflops Stampede system, ANL’s Mira system, and ORNL’s Titan system. While our focus is on fundamental mathematical/computational methods and algorithms, we will assess our methods on model problems derived from several DOE mission applications, including multiscale mechanics and ice sheet dynamics.« less

A risk-based approach to flood management decisions in a nonstationary world

NASA Astrophysics Data System (ADS)

Rosner, Ana; Vogel, Richard M.; Kirshen, Paul H.

2014-03-01

Traditional approaches to flood management in a nonstationary world begin with a null hypothesis test of "no trend" and its likelihood, with little or no attention given to the likelihood that we might ignore a trend if it really existed. Concluding a trend exists when it does not, or rejecting a trend when it exists are known as type I and type II errors, respectively. Decision-makers are poorly served by statistical and/or decision methods that do not carefully consider both over- and under-preparation errors, respectively. Similarly, little attention is given to how to integrate uncertainty in our ability to detect trends into a flood management decision context. We show how trend hypothesis test results can be combined with an adaptation's infrastructure costs and damages avoided to provide a rational decision approach in a nonstationary world. The criterion of expected regret is shown to be a useful metric that integrates the statistical, economic, and hydrological aspects of the flood management problem in a nonstationary world.

An Informative Interpretation of Decision Theory: The Information Theoretic Basis for Signal-to-Noise Ratio and Log Likelihood Ratio

DOE PAGES

Polcari, J.

2013-08-16

The signal processing concept of signal-to-noise ratio (SNR), in its role as a performance measure, is recast within the more general context of information theory, leading to a series of useful insights. Establishing generalized SNR (GSNR) as a rigorous information theoretic measure inherent in any set of observations significantly strengthens its quantitative performance pedigree while simultaneously providing a specific definition under general conditions. This directly leads to consideration of the log likelihood ratio (LLR): first, as the simplest possible information-preserving transformation (i.e., signal processing algorithm) and subsequently, as an absolute, comparable measure of information for any specific observation exemplar. Furthermore,more » the information accounting methodology that results permits practical use of both GSNR and LLR as diagnostic scalar performance measurements, directly comparable across alternative system/algorithm designs, applicable at any tap point within any processing string, in a form that is also comparable with the inherent performance bounds due to information conservation.« less

Associations between social support network characteristics and receipt of emotional and material support among a sample of male sexual minority youth

PubMed Central

Kapadia, Farzana; Halkitis, Perry; Barton, Staci; Siconolfi, Daniel; Figueroa, Rafael Perez

2014-01-01

Few studies have examined how social support network characteristics are related to perceived receipt of social support among male sexual minority youth. Using egocentric network data collected from a study of male sexual minority youth (n=592), multivariable logistic regression analyses examined distinct associations between individual and social network characteristics with receipt of (1) emotional and (2) material support. In multivariable models, frequent communication and having friends in one’s network yielded a two-fold increase in the likelihood of receiving emotional support whereas frequent communication was associated with an almost three-fold higher likelihood of perceived material support. Finally, greater internalized homophobia and personal experiences of gay-related stigma were inversely associated with perceived receipt of emotional and material support, respectively. Understanding the evolving social context and social interactions of this new generation of male sexual minority youth is warranted in order to understand the broader, contextual factors associated with their overall health and well-being. PMID:25214756

Statistical analyses support power law distributions found in neuronal avalanches.

PubMed

Klaus, Andreas; Yu, Shan; Plenz, Dietmar

2011-01-01

The size distribution of neuronal avalanches in cortical networks has been reported to follow a power law distribution with exponent close to -1.5, which is a reflection of long-range spatial correlations in spontaneous neuronal activity. However, identifying power law scaling in empirical data can be difficult and sometimes controversial. In the present study, we tested the power law hypothesis for neuronal avalanches by using more stringent statistical analyses. In particular, we performed the following steps: (i) analysis of finite-size scaling to identify scale-free dynamics in neuronal avalanches, (ii) model parameter estimation to determine the specific exponent of the power law, and (iii) comparison of the power law to alternative model distributions. Consistent with critical state dynamics, avalanche size distributions exhibited robust scaling behavior in which the maximum avalanche size was limited only by the spatial extent of sampling ("finite size" effect). This scale-free dynamics suggests the power law as a model for the distribution of avalanche sizes. Using both the Kolmogorov-Smirnov statistic and a maximum likelihood approach, we found the slope to be close to -1.5, which is in line with previous reports. Finally, the power law model for neuronal avalanches was compared to the exponential and to various heavy-tail distributions based on the Kolmogorov-Smirnov distance and by using a log-likelihood ratio test. Both the power law distribution without and with exponential cut-off provided significantly better fits to the cluster size distributions in neuronal avalanches than the exponential, the lognormal and the gamma distribution. In summary, our findings strongly support the power law scaling in neuronal avalanches, providing further evidence for critical state dynamics in superficial layers of cortex.

Scale-free dynamics of the synchronization between sleep EEG power bands and the high frequency component of heart rate variability in normal men and patients with sleep apnea-hypopnea syndrome.

PubMed

Dumont, Martine; Jurysta, Fabrice; Lanquart, Jean-Pol; Noseda, André; van de Borne, Philippe; Linkowski, Paul

2007-12-01

To investigate the dynamics of the synchronization between heart rate variability and sleep electroencephalogram power spectra and the effect of sleep apnea-hypopnea syndrome. Heart rate and sleep electroencephalogram signals were recorded in controls and patients with sleep apnea-hypopnea syndrome that were matched for age, gender, sleep parameters, and blood pressure. Spectral analysis was applied to electrocardiogram and electroencephalogram sleep recordings to obtain power values every 20s. Synchronization likelihood was computed between time series of the normalized high frequency spectral component of RR-intervals and all electroencephalographic frequency bands. Detrended fluctuation analysis was applied to the synchronizations in order to qualify their dynamic behaviors. For all sleep bands, the fluctuations of the synchronization between sleep EEG and heart activity appear scale free and the scaling exponent is close to one as for 1/f noise. We could not detect any effect due to sleep apnea-hypopnea syndrome. The synchronizations between the high frequency component of heart rate variability and all sleep power bands exhibited robust fluctuations characterized by self-similar temporal behavior of 1/f noise type. No effects of sleep apnea-hypopnea syndrome were observed in these synchronizations. Sleep apnea-hypopnea syndrome does not affect the interdependence between the high frequency component of heart rate variability and all sleep power bands as measured by synchronization likelihood.

Association between mediterranean diet and non-fatal cardiovascular events, in the context of anxiety and depression disorders: a case/case-control study.

PubMed

Georgousopoulou, Ekavi N; Kastorini, Christina-Maria; Milionis, Haralampos J; Ntziou, Evangelia; Kostapanos, Michael S; Nikolaou, Vassilios; Vemmos, Konstantinos N; Goudevenos, John A; Panagiotakos, Demosthenes B

2014-01-01

The aim of this study was to investigate the effect of the Mediterranean diet on the likelihood of having a non-fatal cardiovascular outcome, taking into account anxiety and depression status. This was a case-control study with individual matching by age and sex. During 2009-2010, 1000 participants were enrolled; 250 were consecutive patients with a first acute coronary syndrome (ACS), 250 were consecutive patients with a first ischemic stroke, and 500 were population-based control subjects, one-for-one matched to the patients by age and sex. Among other characteristics, adherence to the Mediterranean diet was assessed by the MedDietScore, anxiety was assessed with the Spielberger State-Trait Anxiety Inventory form Y-2, while depressive symptomatology was evaluated by the Zung Depression Rating Scale. Higher adherence to the Mediterranean diet was associated with a lower likelihood of ACS and ischemic stroke, even after adjusting for anxiety or depression (ACS: OR=0.92, 95%CI 0.87-0.98 and 0.93, 0.88-0.98, respectively; ischemic stroke: 0.91, 0.84-0.98 and 0.90, 0.83-0.97, respectively). For both ACS and stroke patients, anxiety and depression were associated with a higher likelihood of ACS and stroke. When stratifying for depression or anxiety status, the Mediterranean diet remained a significantly protective factor only for people with low levels of depression and anxiety for ACS, and only for people with low levels of anxiety, as far as stroke was concerned. Anxiety and depression seem to play a mediating role in the protective relationship between adherence to the Mediterranean diet and the likelihood of developing cardiovascular events.

Factors Associated With High-Risk Alcohol Consumption Among LGB Older Adults: The Roles of Gender, Social Support, Perceived Stress, Discrimination, and Stigma.

PubMed

Bryan, Amanda E B; Kim, Hyun-Jun; Fredriksen-Goldsen, Karen I

2017-02-01

Lesbian, gay, and bisexual (LGB) adults have elevated rates of high-risk alcohol consumption compared with heterosexual adults. Although drinking tends to decline with age in the general population, we know little about LGB older adults' drinking. Using 2014 data from Aging with Pride: National Health, Aging, and Sexuality/Gender Study (NHAS), we aimed to identify factors associated with high-risk drinking in LGB older adults. A U.S. sample of 2,351 LGB adults aged 50-98 years completed a survey about personal and social experiences, substance use, and health. Multinomial logistic regression was conducted to identify predictors of past-month high-risk alcohol consumption. Approximately one fifth (20.6%) of LGB older adults reported high-risk drinking, with nonsignificantly different rates between men (22.4%) and women (18.4%). For women, current smoking and greater social support were associated with greater likelihood of high-risk drinking; older age, higher income, recovery from addiction, and greater perceived stress were associated with lower likelihood. For men, higher income, current smoking, and greater day-to-day discrimination were associated with greater likelihood of high-risk drinking; transgender identity and recovery from addiction were associated with lower likelihood. Social contexts and perceived drinking norms may encourage higher levels of alcohol consumption in LGB older women, whereas men's drinking may be linked with discrimination-related stress. Prevention and intervention with this population should take into account gender differences and sexual minority-specific risk factors. With future waves of data, we will be able to examine LGB older adults' drinking trajectories over time. © The Author 2017. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Resilience amongst Australian Aboriginal Youth: An Ecological Analysis of Factors Associated with Psychosocial Functioning in High and Low Family Risk Contexts

PubMed Central

Hopkins, Katrina D.; Zubrick, Stephen R.; Taylor, Catherine L.

2014-01-01

We investigate whether the profile of factors protecting psychosocial functioning of high risk exposed Australian Aboriginal youth are the same as those promoting psychosocial functioning in low risk exposed youth. Data on 1,021 youth aged 12–17 years were drawn from the Western Australian Aboriginal Child Health Survey (WAACHS 2000–2002), a population representative survey of the health and well-being of Aboriginal children, their families and community contexts. A person-centered approach was used to define four groups of youth cross-classified according to level of risk exposure (high/low) and psychosocial functioning (good/poor). Multivariate logistic regression was used to model the influence of individual, family, cultural and community factors on psychosocial outcomes separately for youth in high and low family-risk contexts. Results showed that in high family risk contexts, prosocial friendship and low area-level socioeconomic status uniquely protected psychosocial functioning. However, in low family risk contexts the perception of racism increased the likelihood of poor psychosocial functioning. For youth in both high and low risk contexts, higher self-esteem and self-regulation were associated with good psychosocial functioning although the relationship was non-linear. These findings demonstrate that an empirical resilience framework of analysis can identify potent protective processes operating uniquely in contexts of high risk and is the first to describe distinct profiles of risk, protective and promotive factors within high and low risk exposed Australian Aboriginal youth. PMID:25068434

Sequential interactions-in which one player plays first and another responds-promote cooperation in evolutionary-dynamical simulations of single-shot Prisoner's Dilemma and Snowdrift games.

PubMed

Laird, Robert A

2018-09-07

Cooperation is a central topic in evolutionary biology because (a) it is difficult to reconcile why individuals would act in a way that benefits others if such action is costly to themselves, and (b) it underpins many of the 'major transitions of evolution', making it essential for explaining the origins of successively higher levels of biological organization. Within evolutionary game theory, the Prisoner's Dilemma and Snowdrift games are the main theoretical constructs used to study the evolution of cooperation in dyadic interactions. In single-shot versions of these games, wherein individuals play each other only once, players typically act simultaneously rather than sequentially. Allowing one player to respond to the actions of its co-player-in the absence of any possibility of the responder being rewarded for cooperation or punished for defection, as in simultaneous or sequential iterated games-may seem to invite more incentive for exploitation and retaliation in single-shot games, compared to when interactions occur simultaneously, thereby reducing the likelihood that cooperative strategies can thrive. To the contrary, I use lattice-based, evolutionary-dynamical simulation models of single-shot games to demonstrate that under many conditions, sequential interactions have the potential to enhance unilaterally or mutually cooperative outcomes and increase the average payoff of populations, relative to simultaneous interactions-benefits that are especially prevalent in a spatially explicit context. This surprising result is attributable to the presence of conditional strategies that emerge in sequential games that can't occur in the corresponding simultaneous versions. Copyright © 2018 Elsevier Ltd. All rights reserved.

Exploiting Non-sequence Data in Dynamic Model Learning

DTIC Science & Technology

2013-10-01

For our experiments here and in Section 3.5, we implement the proposed algorithms in MATLAB and use the maximum directed spanning tree solver...embarrassingly parallelizable, whereas PM’s maximum directed spanning tree procedure is harder to parallelize. In this experiment, our MATLAB ...some estimation problems, this approach is able to give unique and consistent estimates while the maximum- likelihood method gets entangled in

SPATIAL AND TEMPORAL DIMENSIONS OF NEIGHBORHOOD EFFECTS ON HIGH SCHOOL GRADUATION.

PubMed

Crowder, Kyle; South, Scott J

2011-01-30

Research into the effects of neighborhood characteristics on children's behavior has burgeoned in recent years, but these studies have generally adopted a limited conceptualization of the spatial and temporal dimensions of neighborhood effects. We use longitudinal data from the Panel Study of Income Dynamics and techniques of spatial data analysis to examine how both the socioeconomic characteristics of extralocal neighborhoods-neighborhoods surrounding the immediate neighborhood of residence-and the duration of exposure to disadvantaged neighborhoods throughout the childhood life course influence the likelihood of graduating from high school. Among blacks and whites, socioeconomic advantage in the immediate neighborhood increases the likelihood of completing high school, but among whites higher levels of socioeconomic advantage in extralocal neighborhoods decrease high school graduation rates. Extralocal neighborhood advantage suppresses the influence of advantage in the immediate neighborhood so that controlling for extralocal conditions provides stronger support for the neighborhood effects hypothesis than has previously been observed. Exposure to advantaged neighborhoods over the childhood life course exerts a stronger effect than point-in-time measures on high school graduation, and racial differences in exposure to advantaged neighbors over the childhood life course help to suppress a net black advantage in the likelihood of completing high school.

SPATIAL AND TEMPORAL DIMENSIONS OF NEIGHBORHOOD EFFECTS ON HIGH SCHOOL GRADUATION

PubMed Central

Crowder, Kyle; South, Scott J.

2010-01-01

Research into the effects of neighborhood characteristics on children’s behavior has burgeoned in recent years, but these studies have generally adopted a limited conceptualization of the spatial and temporal dimensions of neighborhood effects. We use longitudinal data from the Panel Study of Income Dynamics and techniques of spatial data analysis to examine how both the socioeconomic characteristics of extralocal neighborhoods—neighborhoods surrounding the immediate neighborhood of residence—and the duration of exposure to disadvantaged neighborhoods throughout the childhood life course influence the likelihood of graduating from high school. Among blacks and whites, socioeconomic advantage in the immediate neighborhood increases the likelihood of completing high school, but among whites higher levels of socioeconomic advantage in extralocal neighborhoods decrease high school graduation rates. Extralocal neighborhood advantage suppresses the influence of advantage in the immediate neighborhood so that controlling for extralocal conditions provides stronger support for the neighborhood effects hypothesis than has previously been observed. Exposure to advantaged neighborhoods over the childhood life course exerts a stronger effect than point-in-time measures on high school graduation, and racial differences in exposure to advantaged neighbors over the childhood life course help to suppress a net black advantage in the likelihood of completing high school. PMID:21180398

Transfer Entropy as a Log-Likelihood Ratio

NASA Astrophysics Data System (ADS)

Barnett, Lionel; Bossomaier, Terry

2012-09-01

Transfer entropy, an information-theoretic measure of time-directed information transfer between joint processes, has steadily gained popularity in the analysis of complex stochastic dynamics in diverse fields, including the neurosciences, ecology, climatology, and econometrics. We show that for a broad class of predictive models, the log-likelihood ratio test statistic for the null hypothesis of zero transfer entropy is a consistent estimator for the transfer entropy itself. For finite Markov chains, furthermore, no explicit model is required. In the general case, an asymptotic χ2 distribution is established for the transfer entropy estimator. The result generalizes the equivalence in the Gaussian case of transfer entropy and Granger causality, a statistical notion of causal influence based on prediction via vector autoregression, and establishes a fundamental connection between directed information transfer and causality in the Wiener-Granger sense.

Transfer entropy as a log-likelihood ratio.

PubMed

Barnett, Lionel; Bossomaier, Terry

2012-09-28

Transfer entropy, an information-theoretic measure of time-directed information transfer between joint processes, has steadily gained popularity in the analysis of complex stochastic dynamics in diverse fields, including the neurosciences, ecology, climatology, and econometrics. We show that for a broad class of predictive models, the log-likelihood ratio test statistic for the null hypothesis of zero transfer entropy is a consistent estimator for the transfer entropy itself. For finite Markov chains, furthermore, no explicit model is required. In the general case, an asymptotic χ2 distribution is established for the transfer entropy estimator. The result generalizes the equivalence in the Gaussian case of transfer entropy and Granger causality, a statistical notion of causal influence based on prediction via vector autoregression, and establishes a fundamental connection between directed information transfer and causality in the Wiener-Granger sense.

Lightweight genome viewer: portable software for browsing genomics data in its chromosomal context

PubMed Central

Faith, Jeremiah J; Olson, Andrew J; Gardner, Timothy S; Sachidanandam, Ravi

2007-01-01

Background Lightweight genome viewer (lwgv) is a web-based tool for visualization of sequence annotations in their chromosomal context. It performs most of the functions of larger genome browsers, while relying on standard flat-file formats and bypassing the database needs of most visualization tools. Visualization as an aide to discovery requires display of novel data in conjunction with static annotations in their chromosomal context. With database-based systems, displaying dynamic results requires temporary tables that need to be tracked for removal. Results lwgv simplifies the visualization of user-generated results on a local computer. The dynamic results of these analyses are written to transient files, which can import static content from a more permanent file. lwgv is currently used in many different applications, from whole genome browsers to single-gene RNAi design visualization, demonstrating its applicability in a large variety of contexts and scales. Conclusion lwgv provides a lightweight alternative to large genome browsers for visualizing biological annotations and dynamic analyses in their chromosomal context. It is particularly suited for applications ranging from short sequences to medium-sized genomes when the creation and maintenance of a large software and database infrastructure is not necessary or desired. PMID:17877794

Lightweight genome viewer: portable software for browsing genomics data in its chromosomal context.

PubMed

Faith, Jeremiah J; Olson, Andrew J; Gardner, Timothy S; Sachidanandam, Ravi

2007-09-18

Lightweight genome viewer (lwgv) is a web-based tool for visualization of sequence annotations in their chromosomal context. It performs most of the functions of larger genome browsers, while relying on standard flat-file formats and bypassing the database needs of most visualization tools. Visualization as an aide to discovery requires display of novel data in conjunction with static annotations in their chromosomal context. With database-based systems, displaying dynamic results requires temporary tables that need to be tracked for removal. lwgv simplifies the visualization of user-generated results on a local computer. The dynamic results of these analyses are written to transient files, which can import static content from a more permanent file. lwgv is currently used in many different applications, from whole genome browsers to single-gene RNAi design visualization, demonstrating its applicability in a large variety of contexts and scales. lwgv provides a lightweight alternative to large genome browsers for visualizing biological annotations and dynamic analyses in their chromosomal context. It is particularly suited for applications ranging from short sequences to medium-sized genomes when the creation and maintenance of a large software and database infrastructure is not necessary or desired.

Acknowledging the Elephant in the Room: How Stressful Environmental Contexts Shape Relationship Dynamics

PubMed Central

Neff, Lisa A.; Karney, Benjamin R.

2016-01-01

Compared to affluent marriages, lower income marriages develop within a context filled with negative stressors that may prove quite toxic for marital stability. The current paper argues that stressful contexts may undermine marital well-being through two routes. First, external stressors create additional problems within the marriage by diverting time and attention away from activities that promote intimacy between partners. Second, external stress may render spouses ill-equipped to cope with this increase in problems by draining spouses of the energy and resources necessary for responding to marital challenges in a constructive manner. In acknowledging the role of the marital context for relationship dynamics, this model suggests new directions for interventions designed to strengthen the marriages of lower income couples. PMID:27766285

Addressing group dynamics in a brief motivational intervention for college student drinkers.

PubMed

Faris, Alexander S; Brown, Janice M

2003-01-01

Previous research indicates that brief motivational interventions for college student drinkers may be less effective in group settings than individual settings. Social psychological theories about counterproductive group dynamics may partially explain this finding. The present study examined potential problems with group motivational interventions by comparing outcomes from a standard group motivational intervention (SGMI; n = 25), an enhanced group motivational intervention (EGMI; n = 27) designed to suppress counterproductive processes, and a no intervention control (n = 23). SGMI and EGMI participants reported disruptive group dynamics as evidenced by low elaboration likelihood, production blocking, and social loafing, though the level of disturbance was significantly lower for EGMI individuals (p = .001). Despite counteracting group dynamics in the EGMI condition, participants in the two interventions were statistically similar in post-intervention problem recognition and future drinking intentions. The results raise concerns over implementing individually-based interventions in group settings without making necessary adjustments.

Combining operational models and data into a dynamic vessel risk assessment tool for coastal regions

NASA Astrophysics Data System (ADS)

Fernandes, R.; Braunschweig, F.; Lourenço, F.; Neves, R.

2016-02-01

The technological evolution in terms of computational capacity, data acquisition systems, numerical modelling and operational oceanography is supplying opportunities for designing and building holistic approaches and complex tools for newer and more efficient management (planning, prevention and response) of coastal water pollution risk events. A combined methodology to dynamically estimate time and space variable individual vessel accident risk levels and shoreline contamination risk from ships has been developed, integrating numerical metocean forecasts and oil spill simulations with vessel tracking automatic identification systems (AIS). The risk rating combines the likelihood of an oil spill occurring from a vessel navigating in a study area - the Portuguese continental shelf - with the assessed consequences to the shoreline. The spill likelihood is based on dynamic marine weather conditions and statistical information from previous accidents. The shoreline consequences reflect the virtual spilled oil amount reaching shoreline and its environmental and socio-economic vulnerabilities. The oil reaching shoreline is quantified with an oil spill fate and behaviour model running multiple virtual spills from vessels along time, or as an alternative, a correction factor based on vessel distance from coast. Shoreline risks can be computed in real time or from previously obtained data. Results show the ability of the proposed methodology to estimate the risk properly sensitive to dynamic metocean conditions and to oil transport behaviour. The integration of meteo-oceanic + oil spill models with coastal vulnerability and AIS data in the quantification of risk enhances the maritime situational awareness and the decision support model, providing a more realistic approach in the assessment of shoreline impacts. The risk assessment from historical data can help finding typical risk patterns ("hot spots") or developing sensitivity analysis to specific conditions, whereas real-time risk levels can be used in the prioritization of individual ships, geographical areas, strategic tug positioning and implementation of dynamic risk-based vessel traffic monitoring.

Global Contexts for Learning: Exploring the Relationship between Low-Context Online Learning and High-Context Learners

ERIC Educational Resources Information Center

Westbrook, Timothy Paul

2014-01-01

Current research on culture and distance education suggests that cultural variables influence student success online. When online courses are writing-based, they may provide easy information dissemination; however, the low-context medium may restrict the learning experience and class dynamic due to the lack of nonverbal communication. Students who…

Digit ratio (2D : 4D) moderates the impact of sexual cues on men's decisions in ultimatum games

PubMed Central

Van den Bergh, Bram; Dewitte, Siegfried

2006-01-01

Three experimental studies demonstrate that ‘sex-related cues’ impact human decision-making in ultimatum games. In the ultimatum game, two individuals divide a sum of money. The proposer offers a portion of the money to the other player, the responder. If the responder accepts the offer, the money is distributed in agreement with the proposer's offer. If the responder rejects the offer, neither player receives anything. Our studies show that exposure to pictures of sexy women or lingerie increases the likelihood of accepting unfair offers. Digit ratios of responders are reliably associated with their behaviour: males with lower digit ratios are more likely to reject an unfair split in neutral contexts, but more likely to accept unfair offers in sex-related contexts. PMID:16846918

Music-colour synaesthesia: Concept, context and qualia.

PubMed

Curwen, Caroline

2018-05-01

This review provides a commentary on coloured-hearing arising on hearing music: music-colour synaesthesia. Although traditionally explained by the hyperconnectivity theory (Ramachandran & Hubbard, 2001a) and the disinhibited feedback theory (Grossenbacher & Lovelace, 2001) as a purely perceptual phenomenon, the review of eight coloured-hearing neuroimaging studies shows that it may not be assumed that these explanations are directly translatable to music-colour synaesthesia. The concept of 'ideaesthesia' (Nikolić, 2009) and the role of conceptual and semantic inducers challenge the likelihood of a single mechanism underlying the cause of synaesthesia and argue for a move away from a purely sensory to sensory explanation. Finally, music-colour synaesthesia forms a challenge for established philosophical theories and the position of synaesthesia is considered within the larger context of musical qualia. Copyright © 2018 Elsevier Inc. All rights reserved.

GPS Spoofing Attack Characterization and Detection in Smart Grids

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

Blum, Rick S.; Pradhan, Parth; Nagananda, Kyatsandra

The problem of global positioning system (GPS) spoofing attacks on smart grids endowed with phasor measurement units (PMUs) is addressed, taking into account the dynamical behavior of the states of the system. First, it is shown how GPS spoofing introduces a timing synchronization error in the phasor readings recorded by the PMUs and alters the measurement matrix of the dynamical model. Then, a generalized likelihood ratio-based hypotheses testing procedure is devised to detect changes in the measurement matrix when the system is subjected to a spoofing attack. Monte Carlo simulations are performed on the 9-bus, 3-machine test grid to demonstratemore » the implication of the spoofing attack on dynamic state estimation and to analyze the performance of the proposed hypotheses test.« less

Dynamic Selective Exposure during Decision-Making.

PubMed

Phillips, James G; Hoon, Teressa; Landon, Jason

2016-01-01

To understand dynamic changes in the likelihood that people would access and selectively expose themselves to information online, the present study examined the checking of account balances during simulated gambling. Sixteen participants played 120 hands of computer Blackjack for points, at higher or lower levels of risk (different point multipliers), and after each win or loss the computer recorded if participants checked their account balances. There were individual differences in checking rates. Participants who were more likely to check balances exhibited a selectivity of exposure to decision consonant information after a win at low risk. Although it was expected that people would seek to maintain positive mood, data were better explained in terms of Cognitive Dissonance. The effects of Cognitive Dissonance are liable to extend beyond single static decisions into dynamic online environments.

Dynamic analysis of a hepatitis B model with three-age-classes

NASA Astrophysics Data System (ADS)

Zhang, Suxia; Zhou, Yicang

2014-07-01

Based on the fact that the likelihood of becoming chronically infected is dependent on age at primary infection Kane (1995) [2], Edmunds et al. (1993) [3], Medley et al. (2001) [4], and Ganem and Prince (2004) [6], we formulate a hepatitis B transmission model with three age classes. The reproduction number, R0 is defined and the dynamical behavior of the model is analyzed. It is proved that the disease-free equilibrium is globally stable if R0<1, and there exists at least one endemic equilibrium and that the disease is uniformly persistent if R0>1. The unique endemic equilibrium and its global stability is obtained in a special case. Simulations are also conducted to compare the dynamical behavior of the model with and without age classes.

Cardiorespiratory interactions in neural circulatory control in humans.

PubMed

Shamsuzzaman, A S; Somers, V K

2001-06-01

The reflex mechanisms and interactions described in this overview provide some explanation for the range of neural circulatory responses evident during changes in breathing. The effects described represent the integrated responses to activation of several reflex mechanisms, including peripheral and central chemoreflexes, arterial baroreflexes, pulmonary stretch receptors, and ventricular mechanoreceptors. These interactions occur on a dynamic basis and the transfer characteristics of any single interaction are, in all likelihood, also highly dynamic. Nevertheless, it is only by attempting to understand individual reflexes and their modulating influences that a more thorough understanding of the responses to complex phenomena such as hyperventilation, apnea, and obstructive sleep apnea can be better understood.

Assessing Measles Transmission in the United States Following a Large Outbreak in California

PubMed Central

Blumberg, Seth; Worden, Lee; Enanoria, Wayne; Ackley, Sarah; Deiner, Michael; Liu, Fengchen; Gao, Daozhou; Lietman, Thomas; Porco, Travis

2015-01-01

The recent increase in measles cases in California may raise questions regarding the continuing success of measles control. To determine whether the dynamics of measles is qualitatively different in comparison to previous years, we assess whether the 2014-2015 measles outbreak associated with an Anaheim theme park is consistent with subcriticality by calculating maximum-likelihood estimates for the effective reproduction numbe given this year’s outbreak, using the Galton-Watson branching process model. We find that the dynamics after the initial transmission event are consistent with prior transmission, but does not exclude the possibilty that the effective reproduction number has increased. PMID:26052471

Population dynamics of HIV-1 inferred from gene sequences.

PubMed Central

Grassly, N C; Harvey, P H; Holmes, E C

1999-01-01

A method for the estimation of population dynamic history from sequence data is described and used to investigate the past population dynamics of HIV-1 subtypes A and B. Using both gag and env gene alignments the effective population size of each subtype is estimated and found to be surprisingly small. This may be a result of the selective sweep of mutations through the population, or may indicate an important role of genetic drift in the fixation of mutations. The implications of these results for the spread of drug-resistant mutations and transmission dynamics, and also the roles of selection and recombination in shaping HIV-1 genetic diversity, are discussed. A larger estimated effective population size for subtype A may be the result of differences in time of origin, transmission dynamics, and/or population structure. To investigate the importance of population structure a model of population subdivision was fitted to each subtype, although the improvement in likelihood was found to be nonsignificant. PMID:9927440

The theory of reasoned action as parallel constraint satisfaction: towards a dynamic computational model of health behavior.

PubMed

Orr, Mark G; Thrush, Roxanne; Plaut, David C

2013-01-01

The reasoned action approach, although ubiquitous in health behavior theory (e.g., Theory of Reasoned Action/Planned Behavior), does not adequately address two key dynamical aspects of health behavior: learning and the effect of immediate social context (i.e., social influence). To remedy this, we put forth a computational implementation of the Theory of Reasoned Action (TRA) using artificial-neural networks. Our model re-conceptualized behavioral intention as arising from a dynamic constraint satisfaction mechanism among a set of beliefs. In two simulations, we show that constraint satisfaction can simultaneously incorporate the effects of past experience (via learning) with the effects of immediate social context to yield behavioral intention, i.e., intention is dynamically constructed from both an individual's pre-existing belief structure and the beliefs of others in the individual's social context. In a third simulation, we illustrate the predictive ability of the model with respect to empirically derived behavioral intention. As the first known computational model of health behavior, it represents a significant advance in theory towards understanding the dynamics of health behavior. Furthermore, our approach may inform the development of population-level agent-based models of health behavior that aim to incorporate psychological theory into models of population dynamics.

The Theory of Reasoned Action as Parallel Constraint Satisfaction: Towards a Dynamic Computational Model of Health Behavior

PubMed Central

Orr, Mark G.; Thrush, Roxanne; Plaut, David C.

2013-01-01

The reasoned action approach, although ubiquitous in health behavior theory (e.g., Theory of Reasoned Action/Planned Behavior), does not adequately address two key dynamical aspects of health behavior: learning and the effect of immediate social context (i.e., social influence). To remedy this, we put forth a computational implementation of the Theory of Reasoned Action (TRA) using artificial-neural networks. Our model re-conceptualized behavioral intention as arising from a dynamic constraint satisfaction mechanism among a set of beliefs. In two simulations, we show that constraint satisfaction can simultaneously incorporate the effects of past experience (via learning) with the effects of immediate social context to yield behavioral intention, i.e., intention is dynamically constructed from both an individual’s pre-existing belief structure and the beliefs of others in the individual’s social context. In a third simulation, we illustrate the predictive ability of the model with respect to empirically derived behavioral intention. As the first known computational model of health behavior, it represents a significant advance in theory towards understanding the dynamics of health behavior. Furthermore, our approach may inform the development of population-level agent-based models of health behavior that aim to incorporate psychological theory into models of population dynamics. PMID:23671603

Capturing Context-Related Change in Emotional Dynamics via Fixed Moderated Time Series Analysis.

PubMed

Adolf, Janne K; Voelkle, Manuel C; Brose, Annette; Schmiedek, Florian

2017-01-01

Much of recent affect research relies on intensive longitudinal studies to assess daily emotional experiences. The resulting data are analyzed with dynamic models to capture regulatory processes involved in emotional functioning. Daily contexts, however, are commonly ignored. This may not only result in biased parameter estimates and wrong conclusions, but also ignores the opportunity to investigate contextual effects on emotional dynamics. With fixed moderated time series analysis, we present an approach that resolves this problem by estimating context-dependent change in dynamic parameters in single-subject time series models. The approach examines parameter changes of known shape and thus addresses the problem of observed intra-individual heterogeneity (e.g., changes in emotional dynamics due to observed changes in daily stress). In comparison to existing approaches to unobserved heterogeneity, model estimation is facilitated and different forms of change can readily be accommodated. We demonstrate the approach's viability given relatively short time series by means of a simulation study. In addition, we present an empirical application, targeting the joint dynamics of affect and stress and how these co-vary with daily events. We discuss potentials and limitations of the approach and close with an outlook on the broader implications for understanding emotional adaption and development.

A mechanistic pan-cancer pathway model informed by multi-omics data interprets stochastic cell fate responses to drugs and mitogens

PubMed Central

Bouhaddou, Mehdi; Koch, Rick J.; DiStefano, Matthew S.; Tan, Annie L.; Mertz, Alex E.

2018-01-01

Most cancer cells harbor multiple drivers whose epistasis and interactions with expression context clouds drug and drug combination sensitivity prediction. We constructed a mechanistic computational model that is context-tailored by omics data to capture regulation of stochastic proliferation and death by pan-cancer driver pathways. Simulations and experiments explore how the coordinated dynamics of RAF/MEK/ERK and PI-3K/AKT kinase activities in response to synergistic mitogen or drug combinations control cell fate in a specific cellular context. In this MCF10A cell context, simulations suggest that synergistic ERK and AKT inhibitor-induced death is likely mediated by BIM rather than BAD, which is supported by prior experimental studies. AKT dynamics explain S-phase entry synergy between EGF and insulin, but simulations suggest that stochastic ERK, and not AKT, dynamics seem to drive cell-to-cell proliferation variability, which in simulations is predictable from pre-stimulus fluctuations in C-Raf/B-Raf levels. Simulations suggest MEK alteration negligibly influences transformation, consistent with clinical data. Tailoring the model to an alternate cell expression and mutation context, a glioma cell line, allows prediction of increased sensitivity of cell death to AKT inhibition. Our model mechanistically interprets context-specific landscapes between driver pathways and cell fates, providing a framework for designing more rational cancer combination therapy. PMID:29579036

Avoiding failure: tools for successful and sustainable quality-improvement projects.

PubMed

Donnelly, Lane F

2017-06-01

Involvement in successful and sustained quality improvement can be a very rewarding experience. However, it can be very difficult work. Up to 70% of attempted organizational change is not sustained. There are many reasons why quality-improvement projects might not be successful. In this article, the author reviews items associated with an increased or decreased likelihood of success. Such items have been categorized as structural issues, human issues and environmental context. This paper is intended to serve those embarking on quality-improvement projects as a resource to help position them for success.

Diagnosing acute aortic dissection : Both an artery and a science.

PubMed

Ohle, Robert

2018-06-14

Thank you very much for your interest in our paper. We agree that retrospective nature of this study in isolation does not provide proof of a hypothesis. However taken in context of the evidence as quoted in the paper and the new prospective trial by Nazerian et al, we believe it adds to the conversation that classically reported high risk features do in fact change the likelihood of acute aortic dissection. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

CONTEXTUALIZED ASSESSMENT WITH BATTERED WOMEN: STRATEGIC SAFETY PLANNING TO COPE WITH MULTIPLE HARMS

PubMed Central

Lindhorst, Taryn; Nurius, Paula; Macy, Rebecca J.

2007-01-01

Given the prevalence of domestic violence and the likelihood that many victims will not receive services from specialized domestic violence providers, this article provides a framework for contextualized assessment that can be used by generalist practitioners. Drawing from stress and coping theory, the authors discuss the relevance of assessing appraisals and emotional responses within the context of environmental and individual risk and protective factors. Through an illustrative case assessment, the authors describe the contextualized assessment process and its ramifications for strategic safety planning. PMID:18167523

Commentary 2: Sibling Power Dynamics: The Role of Family and Sociocultural Context.

PubMed

Updegraff, Kimberly A

2017-06-01

The balance of power and control is an understudied, yet important, aspect of the sibling relationship that is theorized to shift over the course of development from early childhood to young adulthood. The investigations in this issue offer support for this overall progression, but extend prior research by providing a nuanced understanding of sibling power dynamics using different methodologies, analytic approaches, and study designs. Grounded within an ecological framework, directions for future research are offered to expand our understanding of sibling power dynamics in diverse family and sociocultural contexts. © 2017 Wiley Periodicals, Inc.

Thrilling News Revisited: The Role of Suspense for the Enjoyment of News Stories.

PubMed

Kaspar, Kai; Zimmermann, Daniel; Wilbers, Anne-Kathrin

2016-01-01

Previous research on news perception has been dominated by a cognitively oriented perspective on reception processes, whereas emotions have been widely neglected. Consequently, it has remained open which features of a news story might elicit affective responses and hence modulate news perception, shifting the focus to the emotional potential of the narrative. According to the affective-disposition theory, the experience of suspense is the striving force of immersion in fictional dramas. Thereby, a positive affective disposition toward the protagonist of a story and a high likelihood of a bad ending should increase suspense that, in turn, should positively influence reading appreciation and lingering interest in the story. We investigated whether suspense and its determinants also play such a key role in the context of news stories. Study 1 ( n = 263) successfully replicated results of an earlier study, whereas Studies 2 ( n = 255) and 3 ( n = 599) challenged the generalizability of some effects related to manipulated characteristics of a news story. In contrast, correlational relationships between perceived news characteristics and news evaluation were relatively stable. In particular, participants' liking of the protagonist and the perceived likelihood of a good ending were positively associated with suspense, reading appreciation, and lingering interest. This result indicates a preference for happy endings and contradicts the notion that likely negative outcomes are beneficial for suspense and the enjoyment of news stories, as postulated by the affective-disposition theory in the context of fictional dramas. Moreover, experienced suspense reliably mediated the correlations between, on the one hand, participants' liking of the protagonist and the perceived likelihood of a good ending and, on the other hand, reading appreciation and lingering interest. The news story's personal relevance was less influential than expected. Further, we observed a large absence of interaction effects, indicating that central characteristics of a news story can be independently varied to a large degree. In a nutshell, we may conclude that suspense significantly mediates the correlation between perceived news characteristics and the enjoyment of news stories, whereas manipulations of news characteristics do not necessarily influence the enjoyment of narratives as desired.

Thrilling News Revisited: The Role of Suspense for the Enjoyment of News Stories

PubMed Central

Kaspar, Kai; Zimmermann, Daniel; Wilbers, Anne-Kathrin

2016-01-01

Previous research on news perception has been dominated by a cognitively oriented perspective on reception processes, whereas emotions have been widely neglected. Consequently, it has remained open which features of a news story might elicit affective responses and hence modulate news perception, shifting the focus to the emotional potential of the narrative. According to the affective-disposition theory, the experience of suspense is the striving force of immersion in fictional dramas. Thereby, a positive affective disposition toward the protagonist of a story and a high likelihood of a bad ending should increase suspense that, in turn, should positively influence reading appreciation and lingering interest in the story. We investigated whether suspense and its determinants also play such a key role in the context of news stories. Study 1 (n = 263) successfully replicated results of an earlier study, whereas Studies 2 (n = 255) and 3 (n = 599) challenged the generalizability of some effects related to manipulated characteristics of a news story. In contrast, correlational relationships between perceived news characteristics and news evaluation were relatively stable. In particular, participants' liking of the protagonist and the perceived likelihood of a good ending were positively associated with suspense, reading appreciation, and lingering interest. This result indicates a preference for happy endings and contradicts the notion that likely negative outcomes are beneficial for suspense and the enjoyment of news stories, as postulated by the affective-disposition theory in the context of fictional dramas. Moreover, experienced suspense reliably mediated the correlations between, on the one hand, participants' liking of the protagonist and the perceived likelihood of a good ending and, on the other hand, reading appreciation and lingering interest. The news story's personal relevance was less influential than expected. Further, we observed a large absence of interaction effects, indicating that central characteristics of a news story can be independently varied to a large degree. In a nutshell, we may conclude that suspense significantly mediates the correlation between perceived news characteristics and the enjoyment of news stories, whereas manipulations of news characteristics do not necessarily influence the enjoyment of narratives as desired. PMID:28018260

Important factors in the maximum likelihood analysis of flight test maneuvers

NASA Technical Reports Server (NTRS)

Iliff, K. W.; Maine, R. E.; Montgomery, T. D.

1979-01-01

The information presented is based on the experience in the past 12 years at the NASA Dryden Flight Research Center of estimating stability and control derivatives from over 3500 maneuvers from 32 aircraft. The overall approach to the analysis of dynamic flight test data is outlined. General requirements for data and instrumentation are discussed and several examples of the types of problems that may be encountered are presented.

Scaling up from greenhouse resistance to fitness in the field for a host of an emerging forest disease

PubMed Central

Hayden, Katherine J; Garbelotto, Matteo; Dodd, Richard; Wright, Jessica W

2013-01-01

Forest systems are increasingly threatened by emergent, exotic diseases, yet management strategies for forest trees may be hindered by long generation times and scant background knowledge. We tested whether nursery disease resistance and growth traits have predictive value for the conservation of Notholithocarpus densiflorus, the host most susceptible to sudden oak death. We established three experimental populations to assess nursery growth and resistance to Phytophthora ramorum, and correlations between nursery-derived breeding values with seedling survival in a field disease trial. Estimates of nursery traits’ heritability were low to moderate, with lowest estimates for resistance traits. Within the field trial, survival likelihood was increased in larger seedlings and decreased with the development of disease symptoms. The seed-parent family wide likelihood of survival was likewise correlated with family predictors for size and resistance to disease in 2nd year laboratory assays, though not resistance in 1st year leaf assays. We identified traits and seedling families with increased survivorship in planted tanoaks, and a framework to further identify seed parents favored for restoration. The additive genetic variation and seedling disease dynamics we describe hold promise to refine current disease models and expand the understanding of evolutionary dynamics of emergent infectious diseases in highly susceptible hosts. PMID:24062805

A motor speech assessment for children with severe speech disorders: reliability and validity evidence.

PubMed

Strand, Edythe A; McCauley, Rebecca J; Weigand, Stephen D; Stoeckel, Ruth E; Baas, Becky S

2013-04-01

In this article, the authors report reliability and validity evidence for the Dynamic Evaluation of Motor Speech Skill (DEMSS), a new test that uses dynamic assessment to aid in the differential diagnosis of childhood apraxia of speech (CAS). Participants were 81 children between 36 and 79 months of age who were referred to the Mayo Clinic for diagnosis of speech sound disorders. Children were given the DEMSS and a standard speech and language test battery as part of routine evaluations. Subsequently, intrajudge, interjudge, and test-retest reliability were evaluated for a subset of participants. Construct validity was explored for all 81 participants through the use of agglomerative cluster analysis, sensitivity measures, and likelihood ratios. The mean percentage of agreement for 171 judgments was 89% for test-retest reliability, 89% for intrajudge reliability, and 91% for interjudge reliability. Agglomerative hierarchical cluster analysis showed that total DEMSS scores largely differentiated clusters of children with CAS vs. mild CAS vs. other speech disorders. Positive and negative likelihood ratios and measures of sensitivity and specificity suggested that the DEMSS does not overdiagnose CAS but sometimes fails to identify children with CAS. The value of the DEMSS in differential diagnosis of severe speech impairments was supported on the basis of evidence of reliability and validity.

Inference of the sparse kinetic Ising model using the decimation method

NASA Astrophysics Data System (ADS)

Decelle, Aurélien; Zhang, Pan

2015-05-01

In this paper we study the inference of the kinetic Ising model on sparse graphs by the decimation method. The decimation method, which was first proposed in Decelle and Ricci-Tersenghi [Phys. Rev. Lett. 112, 070603 (2014), 10.1103/PhysRevLett.112.070603] for the static inverse Ising problem, tries to recover the topology of the inferred system by setting the weakest couplings to zero iteratively. During the decimation process the likelihood function is maximized over the remaining couplings. Unlike the ℓ1-optimization-based methods, the decimation method does not use the Laplace distribution as a heuristic choice of prior to select a sparse solution. In our case, the whole process can be done auto-matically without fixing any parameters by hand. We show that in the dynamical inference problem, where the task is to reconstruct the couplings of an Ising model given the data, the decimation process can be applied naturally into a maximum-likelihood optimization algorithm, as opposed to the static case where pseudolikelihood method needs to be adopted. We also use extensive numerical studies to validate the accuracy of our methods in dynamical inference problems. Our results illustrate that, on various topologies and with different distribution of couplings, the decimation method outperforms the widely used ℓ1-optimization-based methods.

Volunteerism: Social Network Dynamics and Education.

PubMed

Ajrouch, Kristine J; Antonucci, Toni C; Webster, Noah J

2016-03-01

. We examine how changes in social networks influence volunteerism through bridging (diversity) and bonding (spending time) mechanisms. We further investigate whether social network change substitutes or amplifies the effects of education on volunteerism. . Data (n = 543) are drawn from a two-wave survey of Social Relations and Health over the Life Course (SRHLC). Zero-inflated negative binomial regressions were conducted to test competing hypotheses about how changes in social network characteristics alone and in conjunction with education level predict likelihood and frequency of volunteering. . Changes in social networks were associated with volunteerism: as the proportion of family members decreased and the average number of network members living within a one-hour drive increased over time, participants reported higher odds of volunteering. The substitution hypothesis was supported: social networks that exhibited more geographic proximity and greater contact frequency over-time compensated for lower levels of education to predict volunteering more hours. . The dynamic role of social networks and the ways in which they may work through bridging and bonding to influence both likelihood and frequency of volunteering are discussed. The potential benefits of volunteerism in light of longer life expectancies and smaller families are also considered. © The Author 2014. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Probabilistic fusion of stereo with color and contrast for bilayer segmentation.

PubMed

Kolmogorov, Vladimir; Criminisi, Antonio; Blake, Andrew; Cross, Geoffrey; Rother, Carsten

2006-09-01

This paper describes models and algorithms for the real-time segmentation of foreground from background layers in stereo video sequences. Automatic separation of layers from color/contrast or from stereo alone is known to be error-prone. Here, color, contrast, and stereo matching information are fused to infer layers accurately and efficiently. The first algorithm, Layered Dynamic Programming (LDP), solves stereo in an extended six-state space that represents both foreground/background layers and occluded regions. The stereo-match likelihood is then fused with a contrast-sensitive color model that is learned on-the-fly and stereo disparities are obtained by dynamic programming. The second algorithm, Layered Graph Cut (LGC), does not directly solve stereo. Instead, the stereo match likelihood is marginalized over disparities to evaluate foreground and background hypotheses and then fused with a contrast-sensitive color model like the one used in LDP. Segmentation is solved efficiently by ternary graph cut. Both algorithms are evaluated with respect to ground truth data and found to have similar performance, substantially better than either stereo or color/ contrast alone. However, their characteristics with respect to computational efficiency are rather different. The algorithms are demonstrated in the application of background substitution and shown to give good quality composite video output.

Technical Note: Approximate Bayesian parameterization of a process-based tropical forest model

NASA Astrophysics Data System (ADS)

Hartig, F.; Dislich, C.; Wiegand, T.; Huth, A.

2014-02-01

Inverse parameter estimation of process-based models is a long-standing problem in many scientific disciplines. A key question for inverse parameter estimation is how to define the metric that quantifies how well model predictions fit to the data. This metric can be expressed by general cost or objective functions, but statistical inversion methods require a particular metric, the probability of observing the data given the model parameters, known as the likelihood. For technical and computational reasons, likelihoods for process-based stochastic models are usually based on general assumptions about variability in the observed data, and not on the stochasticity generated by the model. Only in recent years have new methods become available that allow the generation of likelihoods directly from stochastic simulations. Previous applications of these approximate Bayesian methods have concentrated on relatively simple models. Here, we report on the application of a simulation-based likelihood approximation for FORMIND, a parameter-rich individual-based model of tropical forest dynamics. We show that approximate Bayesian inference, based on a parametric likelihood approximation placed in a conventional Markov chain Monte Carlo (MCMC) sampler, performs well in retrieving known parameter values from virtual inventory data generated by the forest model. We analyze the results of the parameter estimation, examine its sensitivity to the choice and aggregation of model outputs and observed data (summary statistics), and demonstrate the application of this method by fitting the FORMIND model to field data from an Ecuadorian tropical forest. Finally, we discuss how this approach differs from approximate Bayesian computation (ABC), another method commonly used to generate simulation-based likelihood approximations. Our results demonstrate that simulation-based inference, which offers considerable conceptual advantages over more traditional methods for inverse parameter estimation, can be successfully applied to process-based models of high complexity. The methodology is particularly suitable for heterogeneous and complex data structures and can easily be adjusted to other model types, including most stochastic population and individual-based models. Our study therefore provides a blueprint for a fairly general approach to parameter estimation of stochastic process-based models.

Infant discrimination of faces in naturalistic events: actions are more salient than faces.

PubMed

Bahrick, Lorraine E; Newell, Lisa C

2008-07-01

Despite the fact that faces are typically seen in the context of dynamic events, there is little research on infants' perception of moving faces. L. E. Bahrick, L. J. Gogate, and I. Ruiz (2002) demonstrated that 5-month-old infants discriminate and remember repetitive actions but not the faces of the women performing the actions. The present research tested an attentional salience explanation for these findings: that dynamic faces are discriminable to infants, but more salient actions compete for attention. Results demonstrated that 5-month-old infants discriminated faces in the context of actions when they had longer familiarization time (Experiment 1) and following habituation to a single person performing 3 different activities (Experiment 2). Further, 7-month-old infants who have had more experience with social events also discriminated faces in the context of actions. Overall, however, discrimination of actions was more robust and occurred earlier in processing time than discrimination of dynamic faces. These findings support an attentional salience hypothesis and indicate that faces are not special in the context of actions in early infancy.

Post-learning hippocampal dynamics promote preferential retention of rewarding events

PubMed Central

Gruber, Matthias J.; Ritchey, Maureen; Wang, Shao-Fang; Doss, Manoj K.; Ranganath, Charan

2016-01-01

Reward motivation is known to modulate memory encoding, and this effect depends on interactions between the substantia nigra/ ventral tegmental area complex (SN/VTA) and the hippocampus. It is unknown, however, whether these interactions influence offline neural activity in the human brain that is thought to promote memory consolidation. Here, we used functional magnetic resonance imaging (fMRI) to test the effect of reward motivation on post-learning neural dynamics and subsequent memory for objects that were learned in high- or low-reward motivation contexts. We found that post-learning increases in resting-state functional connectivity between the SN/VTA and hippocampus predicted preferential retention of objects that were learned in high-reward contexts. In addition, multivariate pattern classification revealed that hippocampal representations of high-reward contexts were preferentially reactivated during post-learning rest, and the number of hippocampal reactivations was predictive of preferential retention of items learned in high-reward contexts. These findings indicate that reward motivation alters offline post-learning dynamics between the SN/VTA and hippocampus, providing novel evidence for a potential mechanism by which reward could influence memory consolidation. PMID:26875624

A shared neural ensemble links distinct contextual memories encoded close in time

NASA Astrophysics Data System (ADS)

Cai, Denise J.; Aharoni, Daniel; Shuman, Tristan; Shobe, Justin; Biane, Jeremy; Song, Weilin; Wei, Brandon; Veshkini, Michael; La-Vu, Mimi; Lou, Jerry; Flores, Sergio E.; Kim, Isaac; Sano, Yoshitake; Zhou, Miou; Baumgaertel, Karsten; Lavi, Ayal; Kamata, Masakazu; Tuszynski, Mark; Mayford, Mark; Golshani, Peyman; Silva, Alcino J.

2016-06-01

Recent studies suggest that a shared neural ensemble may link distinct memories encoded close in time. According to the memory allocation hypothesis, learning triggers a temporary increase in neuronal excitability that biases the representation of a subsequent memory to the neuronal ensemble encoding the first memory, such that recall of one memory increases the likelihood of recalling the other memory. Here we show in mice that the overlap between the hippocampal CA1 ensembles activated by two distinct contexts acquired within a day is higher than when they are separated by a week. Several findings indicate that this overlap of neuronal ensembles links two contextual memories. First, fear paired with one context is transferred to a neutral context when the two contexts are acquired within a day but not across a week. Second, the first memory strengthens the second memory within a day but not across a week. Older mice, known to have lower CA1 excitability, do not show the overlap between ensembles, the transfer of fear between contexts, or the strengthening of the second memory. Finally, in aged mice, increasing cellular excitability and activating a common ensemble of CA1 neurons during two distinct context exposures rescued the deficit in linking memories. Taken together, these findings demonstrate that contextual memories encoded close in time are linked by directing storage into overlapping ensembles. Alteration of these processes by ageing could affect the temporal structure of memories, thus impairing efficient recall of related information.

Developmental assets: profile of youth in a juvenile justice facility.

PubMed

Chew, Weslee; Osseck, Jenna; Raygor, Desiree; Eldridge-Houser, Jennifer; Cox, Carol

2010-02-01

Possessing high numbers of developmental assets greatly reduces the likelihood of a young person engaging in health-risk behaviors. Since youth in the juvenile justice system seem to exhibit many high-risk behaviors, the purpose of this study was to assess the presence of external, internal, and social context areas of developmental assets in at-risk youth attending a northeast Missouri juvenile justice center. Male and female middle and high school students moved to a residential juvenile justice center voluntarily completed the Developmental Assets Profile (DAP) instrument during a regularly scheduled "intake" session. Most respondents reported lacking risk-protective factors in the internal and social context areas. Respondents noted their lack of community involvement in the social context area and their overinvolvement with negative influences in the internal context area. Specifically in the internal and external context areas, most respondents reported having trouble with substance abuse and not having positive peer or parental support. In the social context area, many noted that they wanted to do well in activities and were encouraged to do well; however, they scored service to others and involvement in religious groups or activities as low. Students who lack protective qualities, especially those who do not feel committed to their community, are more likely to be involved in substance abuse and risky behaviors. School-community partnerships may provide the targeted health protective factors that encourage more community involvement and more positive health behaviors in these youth.

Cognitive effort is modulated outside of the explicit awareness of conflict frequency: Evidence from pupillometry.

PubMed

Diede, Nathaniel T; Bugg, Julie M

2017-05-01

Classic theories of cognitive control conceptualized controlled processes as slow, strategic, and willful, with automatic processes being fast and effortless. The context-specific proportion compatibility (CSPC) effect, the reduction in the compatibility effect in a context (e.g., location) associated with a high relative to low likelihood of conflict, challenged classic theories by demonstrating fast and flexible control that appears to operate outside of conscious awareness. Two theoretical questions yet to be addressed are whether the CSPC effect is accompanied by context-dependent variation in effort, and whether the exertion of effort depends on explicit awareness of context-specific task demands. To address these questions, pupil diameter was measured during a CSPC paradigm. Stimuli were randomly presented in either a mostly compatible location or a mostly incompatible location. Replicating prior research, the CSPC effect was found. The novel finding was that pupil diameter was greater in the mostly incompatible location compared to the mostly compatible location, despite participants' lack of awareness of context-specific task demands. Additionally, this difference occurred regardless of trial type or a preceding switch in location. These patterns support the view that context (location) dictates selection of optimal attentional settings in the CSPC paradigm, and varying levels of effort and performance accompany these settings. Theoretically, these patterns imply that cognitive control may operate fast, flexibly, and outside of awareness, but not effortlessly. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Negative Bystander Behavior in Bullying Dynamics: Assessing the Impact of Social Capital Deprivation and Anti-social Capital.

PubMed

Evans, Caroline B R; Smokowski, Paul R

2017-02-01

Bystanders witness bullying, but are not directly involved as a bully or victim; however, they often engage in negative bystander behavior. This study examines how social capital deprivation and anti-social capital are associated with the likelihood of engaging in negative bystander behavior in a sample (N = 5752) of racially/ethnically diverse rural youth. Data were collected using an online, youth self-report; the current study uses cross sectional data. Following multiple imputation, a binary logistic regression with robust standard errors was run. Results partially supported the hypothesis and indicated that social capital deprivation in the form of peer pressure and verbal victimization and anti-social capital in the form of delinquent friends, bullying perpetration, verbal perpetration, and physical perpetration were significantly associated with an increased likelihood of engaging in negative bystander behavior. Findings highlight the importance of establishing sources of positive social support for disenfranchised youth.

Anatomically-Aided PET Reconstruction Using the Kernel Method

PubMed Central

Hutchcroft, Will; Wang, Guobao; Chen, Kevin T.; Catana, Ciprian; Qi, Jinyi

2016-01-01

This paper extends the kernel method that was proposed previously for dynamic PET reconstruction, to incorporate anatomical side information into the PET reconstruction model. In contrast to existing methods that incorporate anatomical information using a penalized likelihood framework, the proposed method incorporates this information in the simpler maximum likelihood (ML) formulation and is amenable to ordered subsets. The new method also does not require any segmentation of the anatomical image to obtain edge information. We compare the kernel method with the Bowsher method for anatomically-aided PET image reconstruction through a simulated data set. Computer simulations demonstrate that the kernel method offers advantages over the Bowsher method in region of interest (ROI) quantification. Additionally the kernel method is applied to a 3D patient data set. The kernel method results in reduced noise at a matched contrast level compared with the conventional ML expectation maximization (EM) algorithm. PMID:27541810

Anatomically-aided PET reconstruction using the kernel method.

PubMed

Hutchcroft, Will; Wang, Guobao; Chen, Kevin T; Catana, Ciprian; Qi, Jinyi

2016-09-21

This paper extends the kernel method that was proposed previously for dynamic PET reconstruction, to incorporate anatomical side information into the PET reconstruction model. In contrast to existing methods that incorporate anatomical information using a penalized likelihood framework, the proposed method incorporates this information in the simpler maximum likelihood (ML) formulation and is amenable to ordered subsets. The new method also does not require any segmentation of the anatomical image to obtain edge information. We compare the kernel method with the Bowsher method for anatomically-aided PET image reconstruction through a simulated data set. Computer simulations demonstrate that the kernel method offers advantages over the Bowsher method in region of interest quantification. Additionally the kernel method is applied to a 3D patient data set. The kernel method results in reduced noise at a matched contrast level compared with the conventional ML expectation maximization algorithm.

Anatomically-aided PET reconstruction using the kernel method

NASA Astrophysics Data System (ADS)

Hutchcroft, Will; Wang, Guobao; Chen, Kevin T.; Catana, Ciprian; Qi, Jinyi

2016-09-01

This paper extends the kernel method that was proposed previously for dynamic PET reconstruction, to incorporate anatomical side information into the PET reconstruction model. In contrast to existing methods that incorporate anatomical information using a penalized likelihood framework, the proposed method incorporates this information in the simpler maximum likelihood (ML) formulation and is amenable to ordered subsets. The new method also does not require any segmentation of the anatomical image to obtain edge information. We compare the kernel method with the Bowsher method for anatomically-aided PET image reconstruction through a simulated data set. Computer simulations demonstrate that the kernel method offers advantages over the Bowsher method in region of interest quantification. Additionally the kernel method is applied to a 3D patient data set. The kernel method results in reduced noise at a matched contrast level compared with the conventional ML expectation maximization algorithm.

Bayesian framework for the evaluation of fiber evidence in a double murder--a case report.

PubMed

Causin, Valerio; Schiavone, Sergio; Marigo, Antonio; Carresi, Pietro

2004-05-10

Fiber evidence found on a suspect vehicle was the only useful trace to reconstruct the dynamics of the transportation of two corpses. Optical microscopy, UV-Vis microspectrophotometry and infrared analysis were employed to compare fibers recovered in the trunk of a car to those of the blankets composing the wrapping in which the victims had been hidden. A "pseudo-1:1" taping permitted to reconstruct the spatial distribution of the traces and to further strengthen the support to one of the hypotheses. The Likelihood Ratio (LR) was calculated, in order to quantify the support given by forensic evidence to the explanations proposed. A generalization of the Likelihood Ratio equation to cases analogous to this has been derived. Fibers were the only traces that helped in the corroboration of the crime scenario, being absent any DNA, fingerprints and ballistic evidence.

Uncertainty, learning, and the optimal management of wildlife

USGS Publications Warehouse

Williams, B.K.

2001-01-01

Wildlife management is limited by uncontrolled and often unrecognized environmental variation, by limited capabilities to observe and control animal populations, and by a lack of understanding about the biological processes driving population dynamics. In this paper I describe a comprehensive framework for management that includes multiple models and likelihood values to account for structural uncertainty, along with stochastic factors to account for environmental variation, random sampling, and partial controllability. Adaptive optimization is developed in terms of the optimal control of incompletely understood populations, with the expected value of perfect information measuring the potential for improving control through learning. The framework for optimal adaptive control is generalized by including partial observability and non-adaptive, sample-based updating of model likelihoods. Passive adaptive management is derived as a special case of constrained adaptive optimization, representing a potentially efficient suboptimal alternative that nonetheless accounts for structural uncertainty.

Encircling the dark: constraining dark energy via cosmic density in spheres

NASA Astrophysics Data System (ADS)

Codis, S.; Pichon, C.; Bernardeau, F.; Uhlemann, C.; Prunet, S.

2016-08-01

The recently published analytic probability density function for the mildly non-linear cosmic density field within spherical cells is used to build a simple but accurate maximum likelihood estimate for the redshift evolution of the variance of the density, which, as expected, is shown to have smaller relative error than the sample variance. This estimator provides a competitive probe for the equation of state of dark energy, reaching a few per cent accuracy on wp and wa for a Euclid-like survey. The corresponding likelihood function can take into account the configuration of the cells via their relative separations. A code to compute one-cell-density probability density functions for arbitrary initial power spectrum, top-hat smoothing and various spherical-collapse dynamics is made available online, so as to provide straightforward means of testing the effect of alternative dark energy models and initial power spectra on the low-redshift matter distribution.

Immediate early gene activation throughout the brain is associated with dynamic changes in social context.

PubMed

Williamson, Cait M; Klein, Inbal S; Lee, Won; Curley, James P

2018-05-31

Social competence is dependent on successful processing of social context information. The social opportunity paradigm is a methodology in which dynamic shifts in social context are induced through removal of the alpha male in a dominance hierarchy, leading to rapid ascent in the hierarchy of the beta male and of other subordinate males in the social group. In the current study, we use the social opportunity paradigm to determine what brain regions respond to this dynamic change in social context, allowing an individual to recognize the absence of the alpha male and subsequently perform status-appropriate social behaviors. Replicating our previous work, we show that following removal of the alpha male, beta males rapidly ascend the social hierarchy and attain dominant status by increasing aggression towards more subordinate individuals. Analysis of patterns of Fos immunoreactivity throughout the brain indicates that in individuals undergoing social ascent, there is increased activity in regions of the social behavior network, as well as the infralimbic and prelimbic regions of the prefrontal cortex and areas of the hippocampus. Our findings demonstrate that male mice are able to respond to changes in social context and provide insight into the how the brain processes these complex behavioral changes.

Interdependence and dynamics of essential services in an extensive risk context: a case study in Montserrat, West Indies

NASA Astrophysics Data System (ADS)

Sword-Daniels, V. L.; Rossetto, T.; Wilson, T. M.; Sargeant, S.

2015-05-01

The essential services that support urban living are complex and interdependent, and their disruption in disasters directly affects society. Yet there are few empirical studies to inform our understanding of the vulnerabilities and resilience of complex infrastructure systems in disasters. This research takes a systems thinking approach to explore the dynamic behaviour of a network of essential services, in the presence and absence of volcanic ashfall hazards in Montserrat, West Indies. Adopting a case study methodology and qualitative methods to gather empirical data, we centre the study on the healthcare system and its interconnected network of essential services. We identify different types of relationship between sectors and develop a new interdependence classification system for analysis. Relationships are further categorised by hazard conditions, for use in extensive risk contexts. During heightened volcanic activity, relationships between systems transform in both number and type: connections increase across the network by 41%, and adapt to increase cooperation and information sharing. Interconnections add capacities to the network, increasing the resilience of prioritised sectors. This in-depth and context-specific approach provides a new methodology for studying the dynamics of infrastructure interdependence in an extensive risk context, and can be adapted for use in other hazard contexts.

Interdependence and dynamics of essential services in an extensive risk context: a case study in Montserrat, West Indies

NASA Astrophysics Data System (ADS)

Sword-Daniels, V. L.; Rossetto, T.; Wilson, T. M.; Sargeant, S.

2015-02-01

The essential services that support urban living are complex and interdependent, and their disruption in disasters directly affects society. Yet there are few empirical studies to inform our understanding of the vulnerabilities and resilience of complex infrastructure systems in disasters. This research takes a systems thinking approach to explore the dynamic behaviour of a network of essential services, in the presence and absence of volcanic ashfall hazards in Montserrat, West Indies. Adopting a case study methodology and qualitative methods to gather empirical data we centre the study on the healthcare system and its interconnected network of essential services. We identify different types of relationship between sectors and develop a new interdependence classification system for analysis. Relationships are further categorised by hazard condition, for use in extensive risk contexts. During heightened volcanic activity, relationships between systems transform in both number and type: connections increase across the network by 41%, and adapt to increase cooperation and information sharing. Interconnections add capacities to the network, increasing the resilience of prioritised sectors. This in-depth and context-specific approach provides a new methodology for studying the dynamics of infrastructure interdependence in an extensive risk context, and can be adapted for use in other hazard contexts.

The role of gender identity in adolescents' antisocial behavior.

PubMed

Moreira Trillo, Vanesa; Mirón Redondo, Lourdes

2013-01-01

Analysis of the relevance of the variables sex and gender to explain delinquency is a topic of growing interest in Criminology. This study tests a model of juvenile delinquency that integrates gender identity, the association with deviant peers, and a lack of attachment to conventional contexts. We used a sample of 970 adolescents of both sexes, representative of the urban population, between 12 and 18 years, attending public schools in Galicia (Spain). The results of path analysis confirm that: a) weak attachment to conventional contexts, and belonging to a deviant groups are precedents for deviation of adolescents of both sexes; b) these contexts also contribute to the development of gender identity; and c) gender identity affects the likelihood of deviation: femininity tends to reduce this behavior, and masculinity (in particular, negatively valued masculinity) contributes to increase it. These findings support the adequacy of including gender identity in the explanatory models of delinquency. They also suggest the need to reconsider the role of conventional settings in the socialization of masculinity and, therefore, in the genesis of adolescent delinquency of both sexes.

Not all repetition is alike: Different benefits of repetition in amnesia and normal memory

PubMed Central

Verfaellie, Mieke; Rajaram, Suparna; Fossum, Karen; Williams, Lisa

2008-01-01

While it is well known that repetition can enhance memory in amnesia, little is known about which forms of repetition are most beneficial. This study compared the effect on recognition memory of repetition of words in the same semantic context and in varied semantic contexts. To gain insight into the mechanisms by which these forms of repetition affect performance, participants were asked to make Remember/Know judgments during recognition. These judgments were used to make inferences about the contribution of recollection and familiarity to performance. For individuals with intact memory, the two forms of repetition were equally beneficial to overall recognition, and were associated with both enhanced Remember and Know responses. However, varied repetition was associated with a higher likelihood of Remember responses than was fixed repetition. The two forms of repetition also conferred equivalent benefits on overall recognition in amnesia, but in both cases, this enhancement was manifest exclusively in enhanced Know responses. We conclude that the repetition of information, and especially repetition in varied contexts, enhances recollection in individuals with intact memory, but exclusively affects familiarity in patients with severe amnesia. PMID:18419835

Exploring risk factors associated with intimate partner violence in Vietnam: results from a cross-sectional national survey.

PubMed

Jansen, Henrica A F M; Nguyen, Thi Viet Nga; Hoang, Tu Anh

2016-11-01

Empirical evidence documents that some risk factors for intimate partner violence (IPV) are similar across contexts, while others differ considerably. In Vietnam, there was a need to investigate risk factors for IPV to support evidence-based policy and programming. Using the dataset gathered in the 2010 National Study on Domestic Violence against Women, forty variables were explored in logistic regression analysis, including socio-demographic characteristics of women and their husbands, other experiences with violence, husband's behaviours, family support, and context-specific variables such as the sex of their children. Fifteen independent factors remained strongly associated with IPV. Significant risk was associated with husbands' behaviour that supports male power (extra-marital relationships; fighting with other men) and alcohol use. Violence experienced in childhood increased the likelihood of women experiencing and of men perpetrating IPV. Notable was further the association with women's higher financial contribution to the household and lack of association with not having sons. The findings support theories describing how underlying gender and power imbalance are fundamental causes of IPV and indicate the need for context-specific interventions.

Characterization of Vulnerable and Resilient Spanish Adolescents in Their Developmental Contexts

PubMed Central

Moreno, Carmen; García-Moya, Irene; Rivera, Francisco; Ramos, Pilar

2016-01-01

Research on resilience and vulnerability can offer very valuable information for optimizing design and assessment of interventions and policies aimed at fostering adolescent health. This paper used the adversity level associated with family functioning and the positive adaptation level, as measured by means of a global health score, to distinguish four groups within a representative sample of Spanish adolescents aged 13–16 years: maladaptive, resilient, competent and vulnerable. The aforementioned groups were compared in a number of demographic, school context, peer context, lifestyles, psychological and socioeconomic variables, which can facilitate or inhibit positive adaptation in each context. In addition, the degree to which each factor tended to associate with resilience and vulnerability was examined. The majority of the factors operated by increasing the likelihood of good adaptation in resilient adolescents and diminishing it in vulnerable ones. Overall, more similarities than differences were found in the factors contributing to explaining resilience or vulnerability. However, results also revealed some differential aspects: psychological variables showed a larger explicative capacity in vulnerable adolescents, whereas factors related to school and peer contexts, especially the second, showed a stronger association with resilience. In addition, perceived family wealth, satisfaction with friendships and breakfast frequency only made a significant contribution to the explanation of resilience. The current study provides a highly useful characterization of resilience and vulnerability phenomena in adolescence. PMID:27458397

Accuracy of maximum likelihood estimates of a two-state model in single-molecule FRET

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

Gopich, Irina V.

2015-01-21

Photon sequences from single-molecule Förster resonance energy transfer (FRET) experiments can be analyzed using a maximum likelihood method. Parameters of the underlying kinetic model (FRET efficiencies of the states and transition rates between conformational states) are obtained by maximizing the appropriate likelihood function. In addition, the errors (uncertainties) of the extracted parameters can be obtained from the curvature of the likelihood function at the maximum. We study the standard deviations of the parameters of a two-state model obtained from photon sequences with recorded colors and arrival times. The standard deviations can be obtained analytically in a special case when themore » FRET efficiencies of the states are 0 and 1 and in the limiting cases of fast and slow conformational dynamics. These results are compared with the results of numerical simulations. The accuracy and, therefore, the ability to predict model parameters depend on how fast the transition rates are compared to the photon count rate. In the limit of slow transitions, the key parameters that determine the accuracy are the number of transitions between the states and the number of independent photon sequences. In the fast transition limit, the accuracy is determined by the small fraction of photons that are correlated with their neighbors. The relative standard deviation of the relaxation rate has a “chevron” shape as a function of the transition rate in the log-log scale. The location of the minimum of this function dramatically depends on how well the FRET efficiencies of the states are separated.« less

Accuracy of maximum likelihood estimates of a two-state model in single-molecule FRET

PubMed Central

Gopich, Irina V.

2015-01-01

Photon sequences from single-molecule Förster resonance energy transfer (FRET) experiments can be analyzed using a maximum likelihood method. Parameters of the underlying kinetic model (FRET efficiencies of the states and transition rates between conformational states) are obtained by maximizing the appropriate likelihood function. In addition, the errors (uncertainties) of the extracted parameters can be obtained from the curvature of the likelihood function at the maximum. We study the standard deviations of the parameters of a two-state model obtained from photon sequences with recorded colors and arrival times. The standard deviations can be obtained analytically in a special case when the FRET efficiencies of the states are 0 and 1 and in the limiting cases of fast and slow conformational dynamics. These results are compared with the results of numerical simulations. The accuracy and, therefore, the ability to predict model parameters depend on how fast the transition rates are compared to the photon count rate. In the limit of slow transitions, the key parameters that determine the accuracy are the number of transitions between the states and the number of independent photon sequences. In the fast transition limit, the accuracy is determined by the small fraction of photons that are correlated with their neighbors. The relative standard deviation of the relaxation rate has a “chevron” shape as a function of the transition rate in the log-log scale. The location of the minimum of this function dramatically depends on how well the FRET efficiencies of the states are separated. PMID:25612692

Contextual and Developmental Differences in the Neural Architecture of Cognitive Control.

PubMed

Petrican, Raluca; Grady, Cheryl L

2017-08-09

Because both development and context impact functional brain architecture, the neural connectivity signature of a cognitive or affective predisposition may similarly vary across different ages and circumstances. To test this hypothesis, we investigated the effects of age and cognitive versus social-affective context on the stable and time-varying neural architecture of inhibition, the putative core cognitive control component, in a subsample ( N = 359, 22-36 years, 174 men) of the Human Connectome Project. Among younger individuals, a neural signature of superior inhibition emerged in both stable and dynamic connectivity analyses. Dynamically, a context-free signature emerged as stronger segregation of internal cognition (default mode) and environmentally driven control (salience, cingulo-opercular) systems. A dynamic social-affective context-specific signature was observed most clearly in the visual system. Stable connectivity analyses revealed both context-free (greater default mode segregation) and context-specific (greater frontoparietal segregation for higher cognitive load; greater attentional and environmentally driven control system segregation for greater reward value) signatures of inhibition. Superior inhibition in more mature adulthood was typified by reduced segregation in the default network with increasing reward value and increased ventral attention but reduced cingulo-opercular and subcortical system segregation with increasing cognitive load. Failure to evidence this neural profile after the age of 30 predicted poorer life functioning. Our results suggest that distinguishable neural mechanisms underlie individual differences in cognitive control during different young adult stages and across tasks, thereby underscoring the importance of better understanding the interplay among dispositional, developmental, and contextual factors in shaping adaptive versus maladaptive patterns of thought and behavior. SIGNIFICANCE STATEMENT The brain's functional architecture changes across different contexts and life stages. To test whether the neural signature of a trait similarly varies, we investigated cognitive versus social-affective context effects on the stable and time-varying neural architecture of inhibition during a period of neurobehavioral fine-tuning (age 22-36 years). Younger individuals with superior inhibition showed distinguishable context-free and context-specific neural profiles, evidenced in both static and dynamic connectivity analyses. More mature individuals with superior inhibition evidenced only context-specific profiles, revealed in the static connectivity patterns linked to increased reward or cognitive load. Delayed expression of this profile predicted poorer life functioning. Our results underscore the importance of understanding the interplay among dispositional, developmental, and contextual factors in shaping behavior. Copyright © 2017 the authors 0270-6474/17/377711-16$15.00/0.

Recent forest cover changes (2002-2015) in the Southern Carpathians: A case study of the Iezer Mountains, Romania.

PubMed

Mihai, Bogdan; Săvulescu, Ionuț; Rujoiu-Mare, Marina; Nistor, Constantin

2017-12-01

The paper explores the dynamics of the forest cover change in the Iezer Mountains, part of Southern Carpathians, in the context of the forest ownership recovery and deforestation processes, combined with the effects of biotic and abiotic disturbances. The aim of the study is to map and evaluate the typology and the spatial extension of changes in the montane forest cover between 700 and 2462m a.s.l., sampling all the representative Carpathian ecosystems, from the European beech zone up to the spruce-fir zone and the subalpine-alpine pastures. The methodology uses a change detection analysis of satellite imagery with Landsat ETM+/OLI and Sentinel-2 MSI data. The workflow started with a complete calibration of multispectral data from 2002, before the massive forest restitution to private owners, after the Law 247/2005 empowerment, and 2015, the intensification of deforestation process. For the data classification, a Maximum Likelihood supervised classification algorithm was utilized. The forest change map was developed after combining the classifications in a unitary formula using image difference. The principal outcome of the research identifies the type of forest cover change using a quantitative formula. This information can be integrated in the future decision-making strategies for forest stand management and sustainable development. Copyright © 2017 Elsevier B.V. All rights reserved.

Romantic Relationship Experiences from Late Adolescence to Young Adulthood: The Role of Older Siblings in Mexican-Origin Families

PubMed Central

Wheeler, Lorey A.; Killoren, Sarah E.; Whiteman, Shawn D.; Updegraff, Kimberly A.; McHale, Susan M.; Umaña-Taylor, Adriana J.

2016-01-01

Youth's experiences with romantic relationships during adolescence and young adulthood have far reaching implications for future relationships, health, and well-being; yet, although scholars have examined potential peer and parent influences, we know little about the role of siblings in youth's romantic relationships. Accordingly, this study examined the prospective longitudinal links between Mexican-origin older and younger siblings' romantic relationship experiences and variation by sibling structural and relationship characteristics (i.e., sibling age and gender similarity, younger siblings' modeling) and cultural values (i.e., younger siblings' familism values). Data from 246 Mexican-origin families with older (M = 20.65 years; SD = 1.57; 50% female) and younger (M = 17.72 years; SD = .57; 51% female) siblings were used to examine the likelihood of younger siblings' involvement in dating relationships, sexual relations, cohabitation, and engagement/marriage with probit path analyses. Findings revealed older siblings' reports of involvement in a dating relationship, cohabitation, and engagement/marriage predicted younger siblings' relationship experiences over a two-year period. These links were moderated by sibling age spacing, younger siblings' reports of modeling and familism values. Our findings suggest the significance of social learning dynamics as well as relational and cultural contexts in understanding the links between older and younger siblings' romantic relationship experiences among Mexican-origin youth. PMID:26590830

Romantic Relationship Experiences from Late Adolescence to Young Adulthood: The Role of Older Siblings in Mexican-Origin Families.

PubMed

Wheeler, Lorey A; Killoren, Sarah E; Whiteman, Shawn D; Updegraff, Kimberly A; McHale, Susan M; Umaña-Taylor, Adriana J

2016-05-01

Youth's experiences with romantic relationships during adolescence and young adulthood have far reaching implications for future relationships, health, and well-being; yet, although scholars have examined potential peer and parent influences, we know little about the role of siblings in youth's romantic relationships. Accordingly, this study examined the prospective longitudinal links between Mexican-origin older and younger siblings' romantic relationship experiences and variation by sibling structural and relationship characteristics (i.e., sibling age and gender similarity, younger siblings' modeling) and cultural values (i.e., younger siblings' familism values). Data from 246 Mexican-origin families with older (M = 20.65 years; SD = 1.57; 50 % female) and younger (M = 17.72 years; SD = .57; 51 % female) siblings were used to examine the likelihood of younger siblings' involvement in dating relationships, sexual relations, cohabitation, and engagement/marriage with probit path analyses. Findings revealed older siblings' reports of involvement in a dating relationship, cohabitation, and engagement/marriage predicted younger siblings' relationship experiences over a 2-year period. These links were moderated by sibling age spacing, younger siblings' reports of modeling and familism values. Our findings suggest the significance of social learning dynamics as well as relational and cultural contexts in understanding the links between older and younger siblings' romantic relationship experiences among Mexican-origin youth.

Magnetic navigation behavior and the oceanic ecology of young loggerhead sea turtles.

PubMed

Putman, Nathan F; Verley, Philippe; Endres, Courtney S; Lohmann, Kenneth J

2015-04-01

During long-distance migrations, animals navigate using a variety of sensory cues, mechanisms and strategies. Although guidance mechanisms are usually studied under controlled laboratory conditions, such methods seldom allow for navigation behavior to be examined in an environmental context. Similarly, although realistic environmental models are often used to investigate the ecological implications of animal movement, explicit consideration of navigation mechanisms in such models is rare. Here, we used an interdisciplinary approach in which we first conducted lab-based experiments to determine how hatchling loggerhead sea turtles (Caretta caretta) respond to magnetic fields that exist at five widely separated locations along their migratory route, and then studied the consequences of the observed behavior by simulating it within an ocean circulation model. Magnetic fields associated with two geographic regions that pose risks to young turtles (due to cold wintertime temperatures or potential displacement from the migratory route) elicited oriented swimming, whereas fields from three locations where surface currents and temperature pose no such risk did not. Additionally, at locations with fields that elicited oriented swimming, simulations indicate that the observed behavior greatly increases the likelihood of turtles advancing along the migratory pathway. Our findings suggest that the magnetic navigation behavior of sea turtles is intimately tied to their oceanic ecology and is shaped by a complex interplay between ocean circulation and geomagnetic dynamics. © 2015. Published by The Company of Biologists Ltd.

Family process correlates of firearm ownership and firearm storage among families with young children.

PubMed

Martin-Storey, Alexa; Prickett, Kate C; Crosnoe, Robert

2015-01-01

To understand how family relations and dynamics were associated with firearm ownership among US families with 4-year-olds and with firearm storage among those families with firearms, controlling for sociodemographic characteristics of families and states. With representative data from the Early Childhood Longitudinal Study-Birth Cohort (n = 8,100), logistic regression models employed a set of family process variables (e.g., parenting practices, parental stress, maternal depression, and safety behaviors) as (1) predictors of firearm ownership among all families and, (2) as predictors of safe firearm storage among firearm owning families. An estimated 22 % of families with pre-kindergarten age children reported having firearms in their households. Among firearm owning families, 69 % of families kept firearms in a locked cabinet. Comparing families who did and did not report owning firearms, those who did were more likely to report spanking their children. Firearm owning parents who reported higher levels of parenting stress and lower likelihood that their child always wore a helmet when bicycling were also more likely to report unsafe firearm storage practices. Family processes differentiated both firearm owners from non-firearm owners and firearms owners who locked up their firearms from firearm owners who did not. These findings suggest that firearm ownership and firearm safety behaviors likely arise from a more general family context related to child health and safety.

Large scale dynamic systems

NASA Technical Reports Server (NTRS)

Doolin, B. F.

1975-01-01

Classes of large scale dynamic systems were discussed in the context of modern control theory. Specific examples discussed were in the technical fields of aeronautics, water resources and electric power.

A comparison of likelihood ratio tests and Rao's score test for three separable covariance matrix structures.

PubMed

Filipiak, Katarzyna; Klein, Daniel; Roy, Anuradha

2017-01-01

The problem of testing the separability of a covariance matrix against an unstructured variance-covariance matrix is studied in the context of multivariate repeated measures data using Rao's score test (RST). The RST statistic is developed with the first component of the separable structure as a first-order autoregressive (AR(1)) correlation matrix or an unstructured (UN) covariance matrix under the assumption of multivariate normality. It is shown that the distribution of the RST statistic under the null hypothesis of any separability does not depend on the true values of the mean or the unstructured components of the separable structure. A significant advantage of the RST is that it can be performed for small samples, even smaller than the dimension of the data, where the likelihood ratio test (LRT) cannot be used, and it outperforms the standard LRT in a number of contexts. Monte Carlo simulations are then used to study the comparative behavior of the null distribution of the RST statistic, as well as that of the LRT statistic, in terms of sample size considerations, and for the estimation of the empirical percentiles. Our findings are compared with existing results where the first component of the separable structure is a compound symmetry (CS) correlation matrix. It is also shown by simulations that the empirical null distribution of the RST statistic converges faster than the empirical null distribution of the LRT statistic to the limiting χ 2 distribution. The tests are implemented on a real dataset from medical studies. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Late-life and life history predictors of older adults' high-risk alcohol consumption and drinking problems.

PubMed

Moos, Rudolf H; Schutte, Kathleen K; Brennan, Penny L; Moos, Bernice S

2010-04-01

This prospective, longitudinal study focused on late-life and life history predictors of high-risk alcohol consumption and drinking problems during a 20-year interval as adults matured from age 55-65 to 75-85. A sample of older community residents (N=719) who had consumed alcohol in the past year or shortly before was surveyed at baseline and 10 and 20 years later. At each contact point, participants completed an inventory that assessed their alcohol consumption, drinking problems, and personal and life context factors. Participants also provided information about their life history of drinking and help-seeking. Older adults who, at baseline, had more friends who approved of drinking, relied on substances for tension reduction, and had more financial resources were more likely to engage in high-risk alcohol consumption and to incur drinking problems at 10- and 20-year follow-ups. With respect to life history factors, drinking problems by age 50 were associated with a higher likelihood of late-life high-risk alcohol consumption and drinking problems; having tried to cut down on drinking and participation in Alcoholics Anonymous were associated with a lower likelihood of high-risk consumption and problems. Specific late-life and life history factors can identify older adults likely to engage in excessive alcohol consumption 10 and 20 years later. Targeted screening that considers current alcohol consumption and life context, and history of drinking problems and help-seeking, could help identify older adults at higher risk for excessive or problematic drinking. Published by Elsevier Ireland Ltd.

Late-Life and Life History Predictors of Older Adults of High-Risk Alcohol Consumption and Drinking Problems

PubMed Central

Moos, Rudolf H.; Schutte, Kathleen K.; Brennan, Penny L.; Moos, Bernice S.

2009-01-01

Aims This prospective, longitudinal study focused on late-life and life history predictors of high-risk alcohol consumption and drinking problems during a 20-year interval as adults matured from age 55–65 to age 75–85. Design, Setting, Participants A sample of older community residents (N=719) who had consumed alcohol in the past year or shortly before was surveyed at baseline and 10 years and 20 years later. Measurements At each contact point, participants completed an inventory that assessed their alcohol consumption, drinking problems, and personal and life context factors. Participants also provided information about their life history of drinking and help-seeking. Results Older adults who, at baseline, had more friends who approved of drinking, relied on substances for tension reduction, and had more financial resources were more likely to engage in high-risk alcohol consumption and to incur drinking problems at 10-year and 20-year follow-ups. With respect to life history factors, drinking problems by age 50 were associated with a higher likelihood of late-life high-risk alcohol consumption and drinking problems; having tried to cut down on drinking and participation in Alcoholics Anonymous were associated with a lower likelihood of high-risk consumption and problems. Conclusion Specific late-life and life history factors can identify older adults likely to engage in excessive alcohol consumption 10 and 20 years later. Targeted screening that considers current alcohol consumption and life context, and history of drinking problems and help-seeking, could help identify older adults at higher risk for excessive or problematic drinking. PMID:19969428

Proximate Context of HIV-Related Stigma and Women's Use of Skilled Childbirth Services in Uganda.

PubMed

Ng, Courtney K; Tsai, Alexander C

2017-01-01

HIV-related stigma compromises both HIV prevention and treatment and has recently been described as a barrier to utilization of skilled childbirth services in sub-Saharan Africa. This study uses the 2011 Uganda Demographic Health Survey to estimate the associations between HIV-related stigma, measured both at the individual and community level, and use of facility delivery among women. Consistent with theoretical predictions, higher levels of stigma are associated with reduced likelihood of facility delivery. The negative relationship between stigma and facility delivery is especially pronounced when stigma is measured at the community level, highlighting the importance of understanding the proximate context of HIV-related stigma and its potential effects on behavior. Reducing the stigma of HIV will be critical to achieving the twin goals of reducing overall maternal mortality and preventing mother-to-child HIV transmission.

Exposure to Violence, Substance Use, and Neighborhood Context

PubMed Central

Wright, Emily M.; Pinchevsky, Gillian M.

2014-01-01

Adolescent exposure to violence and substance use are both public health problems, but how neighborhood context contributes to these outcomes is unclear. This study uses prospective data from 1,416 adolescents to examine the direct and interacting influences of victimization and neighborhood factors on adolescent substance use. Based on hierarchical Bernoulli regression models that controlled for prior substance use and multiple individual-level factors, exposure to violence significantly increased the likelihood of marijuana use but not alcohol use or binge drinking. There was little evidence that community norms regarding adolescent substance use influenced rates of substance use or moderated the impact of victimization. Community disadvantage did not directly impact substance use, but the relationship between victimization and marijuana use was stronger for those in neighborhoods with greater disadvantage. The results suggest that victimization is particularly likely to affect adolescents’ marijuana use, and that this relationship may be contingent upon neighborhood economic conditions. PMID:25432621

Nonfamily Experience and Receipt of Personal Care in a Rapidly Changing Context

PubMed Central

Yarger, Jennifer; Brauner-Otto, Sarah R.

2013-01-01

Scholars and policy makers have expressed concern that social and economic changes occurring throughout Asia are threatening the well-being of older adults by undercutting their systems of family support. Using a sample of 1,654 men and women aged 45 and older from the Chitwan Valley Family Study in Nepal, we evaluated the relationship between individuals’ nonfamily experiences, such as education, travel, and nonfamily living, and their likelihood of receiving personal care in older adulthood. Overall, we found that among individuals in poor health, those who had received more education, traveled to the capital city, or lived away from their families were less likely to have received personal care in the previous two weeks than adults who had not had these experiences. Our findings provide evidence that although familial connections remain strong in Nepal, experiences in new nonfamily social contexts are tied to lower levels of care receipt. PMID:24999289

Recent advances in symmetric and network dynamics

NASA Astrophysics Data System (ADS)

Golubitsky, Martin; Stewart, Ian

2015-09-01

We summarize some of the main results discovered over the past three decades concerning symmetric dynamical systems and networks of dynamical systems, with a focus on pattern formation. In both of these contexts, extra constraints on the dynamical system are imposed, and the generic phenomena can change. The main areas discussed are time-periodic states, mode interactions, and non-compact symmetry groups such as the Euclidean group. We consider both dynamics and bifurcations. We summarize applications of these ideas to pattern formation in a variety of physical and biological systems, and explain how the methods were motivated by transferring to new contexts René Thom's general viewpoint, one version of which became known as "catastrophe theory." We emphasize the role of symmetry-breaking in the creation of patterns. Topics include equivariant Hopf bifurcation, which gives conditions for a periodic state to bifurcate from an equilibrium, and the H/K theorem, which classifies the pairs of setwise and pointwise symmetries of periodic states in equivariant dynamics. We discuss mode interactions, which organize multiple bifurcations into a single degenerate bifurcation, and systems with non-compact symmetry groups, where new technical issues arise. We transfer many of the ideas to the context of networks of coupled dynamical systems, and interpret synchrony and phase relations in network dynamics as a type of pattern, in which space is discretized into finitely many nodes, while time remains continuous. We also describe a variety of applications including animal locomotion, Couette-Taylor flow, flames, the Belousov-Zhabotinskii reaction, binocular rivalry, and a nonlinear filter based on anomalous growth rates for the amplitude of periodic oscillations in a feed-forward network.

Ubiquitous Geo-Sensing for Context-Aware Analysis: Exploring Relationships between Environmental and Human Dynamics

PubMed Central

Sagl, Günther; Blaschke, Thomas; Beinat, Euro; Resch, Bernd

2012-01-01

Ubiquitous geo-sensing enables context-aware analyses of physical and social phenomena, i.e., analyzing one phenomenon in the context of another. Although such context-aware analysis can potentially enable a more holistic understanding of spatio-temporal processes, it is rarely documented in the scientific literature yet. In this paper we analyzed the collective human behavior in the context of the weather. We therefore explored the complex relationships between these two spatio-temporal phenomena to provide novel insights into the dynamics of urban systems. Aggregated mobile phone data, which served as a proxy for collective human behavior, was linked with the weather data from climate stations in the case study area, the city of Udine, Northern Italy. To identify and characterize potential patterns within the weather-human relationships, we developed a hybrid approach which integrates several spatio-temporal statistical analysis methods. Thereby we show that explanatory factor analysis, when applied to a number of meteorological variables, can be used to differentiate between normal and adverse weather conditions. Further, we measured the strength of the relationship between the ‘global’ adverse weather conditions and the spatially explicit effective variations in user-generated mobile network traffic for three distinct periods using the Maximal Information Coefficient (MIC). The analyses result in three spatially referenced maps of MICs which reveal interesting insights into collective human dynamics in the context of weather, but also initiate several new scientific challenges. PMID:23012571

The Limits of Dialogue among Teachers from Different National Contexts

ERIC Educational Resources Information Center

Shim, Jenna Min

2015-01-01

In this study, the author investigates the dynamics of dialogue among teachers in different national contexts based on their responses to different cultural practices. Employing Pierre Bourdieu's sociological theory of practice and his concept of habitus, the author shows that, as the teachers' responses are not entirely context-specific, they are…

A probabilistic assessment of the likelihood of vegetation drought under varying climate conditions across China.

PubMed

Liu, Zhiyong; Li, Chao; Zhou, Ping; Chen, Xiuzhi

2016-10-07

Climate change significantly impacts the vegetation growth and terrestrial ecosystems. Using satellite remote sensing observations, here we focus on investigating vegetation dynamics and the likelihood of vegetation-related drought under varying climate conditions across China. We first compare temporal trends of Normalized Difference Vegetation Index (NDVI) and climatic variables over China. We find that in fact there is no significant change in vegetation over the cold regions where warming is significant. Then, we propose a joint probability model to estimate the likelihood of vegetation-related drought conditioned on different precipitation/temperature scenarios in growing season across China. To the best of our knowledge, this study is the first to examine the vegetation-related drought risk over China from a perspective based on joint probability. Our results demonstrate risk patterns of vegetation-related drought under both low and high precipitation/temperature conditions. We further identify the variations in vegetation-related drought risk under different climate conditions and the sensitivity of drought risk to climate variability. These findings provide insights for decision makers to evaluate drought risk and vegetation-related develop drought mitigation strategies over China in a warming world. The proposed methodology also has a great potential to be applied for vegetation-related drought risk assessment in other regions worldwide.

Individual differences in boldness influence patterns of social interactions and the transmission of cuticular bacteria among group-mates

PubMed Central

Keiser, Carl N.; Pinter-Wollman, Noa; Augustine, David A.; Ziemba, Michael J.; Hao, Lingran; Lawrence, Jeffrey G.; Pruitt, Jonathan N.

2016-01-01

Despite the importance of host attributes for the likelihood of associated microbial transmission, individual variation is seldom considered in studies of wildlife disease. Here, we test the influence of host phenotypes on social network structure and the likelihood of cuticular bacterial transmission from exposed individuals to susceptible group-mates using female social spiders (Stegodyphus dumicola). Based on the interactions of resting individuals of known behavioural types, we assessed whether individuals assorted according to their behavioural traits. We found that individuals preferentially interacted with individuals of unlike behavioural phenotypes. We next applied a green fluorescent protein-transformed cuticular bacterium, Pantoea sp., to individuals and allowed them to interact with an unexposed colony-mate for 24 h. We found evidence for transmission of bacteria in 55% of cases. The likelihood of transmission was influenced jointly by the behavioural phenotypes of both the exposed and susceptible individuals: transmission was more likely when exposed spiders exhibited higher ‘boldness’ relative to their colony-mate, and when unexposed individuals were in better body condition. Indirect transmission via shared silk took place in only 15% of cases. Thus, bodily contact appears key to transmission in this system. These data represent a fundamental step towards understanding how individual traits influence larger-scale social and epidemiological dynamics. PMID:27097926

Individual differences in boldness influence patterns of social interactions and the transmission of cuticular bacteria among group-mates.

PubMed

Keiser, Carl N; Pinter-Wollman, Noa; Augustine, David A; Ziemba, Michael J; Hao, Lingran; Lawrence, Jeffrey G; Pruitt, Jonathan N

2016-04-27

Despite the importance of host attributes for the likelihood of associated microbial transmission, individual variation is seldom considered in studies of wildlife disease. Here, we test the influence of host phenotypes on social network structure and the likelihood of cuticular bacterial transmission from exposed individuals to susceptible group-mates using female social spiders (Stegodyphus dumicola). Based on the interactions of resting individuals of known behavioural types, we assessed whether individuals assorted according to their behavioural traits. We found that individuals preferentially interacted with individuals of unlike behavioural phenotypes. We next applied a green fluorescent protein-transformed cuticular bacterium,Pantoeasp., to individuals and allowed them to interact with an unexposed colony-mate for 24 h. We found evidence for transmission of bacteria in 55% of cases. The likelihood of transmission was influenced jointly by the behavioural phenotypes of both the exposed and susceptible individuals: transmission was more likely when exposed spiders exhibited higher 'boldness' relative to their colony-mate, and when unexposed individuals were in better body condition. Indirect transmission via shared silk took place in only 15% of cases. Thus, bodily contact appears key to transmission in this system. These data represent a fundamental step towards understanding how individual traits influence larger-scale social and epidemiological dynamics. © 2016 The Author(s).

Inferring epidemiological parameters from phylogenetic information for the HIV-1 epidemic among MSM

NASA Astrophysics Data System (ADS)

Quax, Rick; van de Vijver, David A. M. C.; Frentz, Dineke; Sloot, Peter M. A.

2013-09-01

The HIV-1 epidemic in Europe is primarily sustained by a dynamic topology of sexual interactions among MSM who have individual immune systems and behavior. This epidemiological process shapes the phylogeny of the virus population. Both fields of epidemic modeling and phylogenetics have a long history, however it remains difficult to use phylogenetic data to infer epidemiological parameters such as the structure of the sexual network and the per-act infectiousness. This is because phylogenetic data is necessarily incomplete and ambiguous. Here we show that the cluster-size distribution indeed contains information about epidemiological parameters using detailed numberical experiments. We simulate the HIV epidemic among MSM many times using the Monte Carlo method with all parameter values and their ranges taken from literature. For each simulation and the corresponding set of parameter values we calculate the likelihood of reproducing an observed cluster-size distribution. The result is an estimated likelihood distribution of all parameters from the phylogenetic data, in particular the structure of the sexual network, the per-act infectiousness, and the risk behavior reduction upon diagnosis. These likelihood distributions encode the knowledge provided by the observed cluster-size distrbution, which we quantify using information theory. Our work suggests that the growing body of genetic data of patients can be exploited to understand the underlying epidemiological process.

A probabilistic assessment of the likelihood of vegetation drought under varying climate conditions across China

PubMed Central

Liu, Zhiyong; Li, Chao; Zhou, Ping; Chen, Xiuzhi

2016-01-01

Climate change significantly impacts the vegetation growth and terrestrial ecosystems. Using satellite remote sensing observations, here we focus on investigating vegetation dynamics and the likelihood of vegetation-related drought under varying climate conditions across China. We first compare temporal trends of Normalized Difference Vegetation Index (NDVI) and climatic variables over China. We find that in fact there is no significant change in vegetation over the cold regions where warming is significant. Then, we propose a joint probability model to estimate the likelihood of vegetation-related drought conditioned on different precipitation/temperature scenarios in growing season across China. To the best of our knowledge, this study is the first to examine the vegetation-related drought risk over China from a perspective based on joint probability. Our results demonstrate risk patterns of vegetation-related drought under both low and high precipitation/temperature conditions. We further identify the variations in vegetation-related drought risk under different climate conditions and the sensitivity of drought risk to climate variability. These findings provide insights for decision makers to evaluate drought risk and vegetation-related develop drought mitigation strategies over China in a warming world. The proposed methodology also has a great potential to be applied for vegetation-related drought risk assessment in other regions worldwide. PMID:27713530

Enrollment in prescription drug insurance: the interaction of numeracy and choice set size.

PubMed

Szrek, Helena; Bundorf, M Kate

2014-04-01

To determine how choice set size affects decision quality among individuals of different levels of numeracy choosing prescription drug plans. Members of an Internet-enabled panel age 65 and over were randomly assigned to sets of prescription drug plans varying in size from 2 to 16 plans from which they made a hypothetical choice. They answered questions about enrollment likelihood and the costs and benefits of their choice. The measure of decision quality was enrollment likelihood among those for whom enrollment was beneficial. Enrollment likelihood by numeracy and choice set size was calculated. A model of moderated mediation was analyzed to understand the role of numeracy as a moderator of the relationship between the number of plans and the quality of the enrollment decision and the roles of the costs and benefits in mediating that relationship. More numerate adults made better decisions than less numerate adults when choosing among a small number of alternatives but not when choice sets were larger. Choice set size had little effect on decision making of less numerate adults. Differences in decision making costs between more and less numerate adults helped explain the effect of choice set size on decision quality. Interventions to improve decision making in the context of Medicare Part D may differentially affect lower and higher numeracy adults. The conflicting results on choice overload in the psychology literature may be explained in part by differences amongst individuals in how they respond to choice set size.

Family emergency preparedness plans in severe tornadoes.

PubMed

Cong, Zhen; Liang, Daan; Luo, Jianjun

2014-01-01

Tornadoes, with warnings usually issued just minutes before their touchdowns, pose great threats to properties and people's physical and mental health. Few studies have empirically investigated the association of family emergency preparedness planning and observed protective behaviors in the context of tornadoes. The purpose of this study was to examine predictors for the action of taking shelter at the time of tornadoes. Specifically, this study investigated whether having a family emergency preparedness plan was associated with higher likelihood of taking shelter upon receiving tornado warnings. This study also examined the effects of socioeconomic status and functional limitations on taking such actions. A telephone survey based on random sampling was conducted in 2012 with residents in Tuscaloosa AL and Joplin MO. Each city experienced considerable damages, injuries, and casualties after severe tornadoes (EF-4 and EF-5) in 2011. The working sample included 892 respondents. Analysis was conducted in early 2013. Logistic regression identified emergency preparedness planning as the only shared factor that increased the likelihood of taking shelter in both cities and the only significant factor in Joplin. In Tuscaloosa, being female and white also increased the likelihood of taking shelter. Disability was not found to have an effect. This study provided empirical evidence on the importance of having a family emergency preparedness plan in mitigating the risk of tornadoes. The findings could be applied to other rapid-onset disasters. © 2013 American Journal of Preventive Medicine Published by American Journal of Preventive Medicine All rights reserved.

Self-compassion, pain, and breaking a social contract.

PubMed

Purdie, Fiona; Morley, Stephen

2015-11-01

Self-compassion is the ability to respond to one's failures, shortcomings, and difficulties with kindness and openness rather than criticism. This study, which might be regarded as a proof-of-concept study, aimed to establish whether self-compassion is associated with expected emotional responses and the likelihood of responding with problem solving, support seeking, distraction, avoidance, rumination, or catastrophizing to unpleasant self-relevant events occurring in 3 social contexts. Sixty chronic pain patients were presented with 6 vignettes describing scenes in which the principal actor transgressed a social contract with negative interpersonal consequences. Vignettes represented 2 dimensions: (1) whether pain or a nonpain factor interrupted the fulfillment of the contract and (2) variation in the social setting (work, peer, and family). The Self-Compassion Scale was the covariate in the analysis. Higher levels of self-compassion were associated with significantly lower negative affect and lower reported likelihood of avoidance, catastrophizing, and rumination. Self-compassion did not interact with pain vs nonpain factor. Work-related vignettes were rated as more emotional and more likely to be associated with avoidance, catastrophizing, and rumination and less likelihood of problem solving. The findings suggest that self-compassion warrants further investigation in the chronic pain population both regarding the extent of its influence as a trait and in terms of the potential to enhance chronic pain patients' ability to be self-compassionate, with a view to its therapeutic utility in enhancing psychological well-being and adjustment. Limitations regarding the possible criterion contamination and the generalizability of vignette studies are discussed.

Is Using the Strengths and Difficulties Questionnaire in a Community Sample the Optimal Way to Assess Mental Health Functioning?

PubMed

Vaz, Sharmila; Cordier, Reinie; Boyes, Mark; Parsons, Richard; Joosten, Annette; Ciccarelli, Marina; Falkmer, Marita; Falkmer, Torbjorn

2016-01-01

An important characteristic of a screening tool is its discriminant ability or the measure's accuracy to distinguish between those with and without mental health problems. The current study examined the inter-rater agreement and screening concordance of the parent and teacher versions of SDQ at scale, subscale and item-levels, with the view of identifying the items that have the most informant discrepancies; and determining whether the concordance between parent and teacher reports on some items has the potential to influence decision making. Cross-sectional data from parent and teacher reports of the mental health functioning of a community sample of 299 students with and without disabilities from 75 different primary schools in Perth, Western Australia were analysed. The study found that: a) Intraclass correlations between parent and teacher ratings of children's mental health using the SDQ at person level was fair on individual child level; b) The SDQ only demonstrated clinical utility when there was agreement between teacher and parent reports using the possible or 90% dichotomisation system; and c) Three individual items had positive likelihood ratio scores indicating clinical utility. Of note was the finding that the negative likelihood ratio or likelihood of disregarding the absence of a condition when both parents and teachers rate the item as absent was not significant. Taken together, these findings suggest that the SDQ is not optimised for use in community samples and that further psychometric evaluation of the SDQ in this context is clearly warranted.

Male Sex Workers: Practices, Contexts, and Vulnerabilities for HIV acquisition and transmission

PubMed Central

Baral, Stefan David; Friedman, M. Reuel; Geibel, Scott; Rebe, Kevin; Bozhinov, Borche; Diouf, Daouda; Sabin, Keith; Holland, Claire E.; Chan, Roy; Caceres, Carlos

2015-01-01

Summary Male sex workers (MSW) who sell/exchange sex for money or goods comprise an extremely diverse population across and within countries worldwide. Information characterizing their practices, contexts where they live, and their needs is very limited, as these men are generally included as subsets of larger studies focused on gay men and other men who have sex with men (MSM) or even female sex workers. MSW, regardless of their sexual orientation, mostly offer sex to men, and rarely identify as sex workers, using local or international terms instead. There is growing evidence of a sustained or increasing burden of HIV among some MSW in the context of the slowing global HIV pandemic. There are several synergistic facilitator spotentiating HIV acquisition and transmission among MSW, including biological, behavioural, and structural determinants. The criminalization and intersectional stigmas of same-sex practices, commercial sex, and HIV all increase HIV and STI risk for MSW and decrease their likelihood of accessing essential services. These contexts, taken together with complex sexual networks among MSW, define them as a key population underserved by current HIV prevention, treatment, and care services. Dedicated efforts are needed to make those services available for the sake of both public health and human rights. PMID:25059939

Positive-Themed Suicide Prevention Messages Delivered by Adolescent Peer Leaders: Proximal Impact on Classmates' Coping Attitudes and Perceptions of Adult Support.

PubMed

Petrova, Mariya; Wyman, Peter A; Schmeelk-Cone, Karen; Pisani, Anthony R

2015-12-01

Developing science-based communication guidance and positive-themed messages for suicide prevention are important priorities. Drawing on social learning and elaboration likelihood models, we designed and tested two positive-focused presentations by high school peer leaders delivered in the context of a suicide prevention program (Sources of Strength). Thirty-six classrooms in four schools (N = 706 students) were randomized to (1) peer leader modeling of healthy coping, (2) peer leader modeling plus audience involvement to identify trusted adults, or (3) control condition. Students' attitudes and norms were assessed by immediate post-only assessments. Exposure to either presentation enhanced positive coping attitudes and perceptions of adult support. Students who reported suicide ideation in the past 12 months benefited more than nonsuicidal students. Beyond modeling alone, audience involvement modestly enhanced expectations of adult support, congruent with the elaboration likelihood model. Positive peer modeling is a promising alternative to communications focused on negative consequences and directives and may enhance social-interpersonal factors linked to reduced suicidal behaviors. © 2015 The American Association of Suicidology.

Multilevel modeling of single-case data: A comparison of maximum likelihood and Bayesian estimation.

PubMed

Moeyaert, Mariola; Rindskopf, David; Onghena, Patrick; Van den Noortgate, Wim

2017-12-01

The focus of this article is to describe Bayesian estimation, including construction of prior distributions, and to compare parameter recovery under the Bayesian framework (using weakly informative priors) and the maximum likelihood (ML) framework in the context of multilevel modeling of single-case experimental data. Bayesian estimation results were found similar to ML estimation results in terms of the treatment effect estimates, regardless of the functional form and degree of information included in the prior specification in the Bayesian framework. In terms of the variance component estimates, both the ML and Bayesian estimation procedures result in biased and less precise variance estimates when the number of participants is small (i.e., 3). By increasing the number of participants to 5 or 7, the relative bias is close to 5% and more precise estimates are obtained for all approaches, except for the inverse-Wishart prior using the identity matrix. When a more informative prior was added, more precise estimates for the fixed effects and random effects were obtained, even when only 3 participants were included. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Public risk perceptions and preventive behaviors during the 2009 H1N1 influenza pandemic.

PubMed

Kim, Yushim; Zhong, Wei; Jehn, Megan; Walsh, Lauren

2015-04-01

This study examines the public perception of the 2009 H1N1 influenza risk and its association with flu-related knowledge, social contexts, and preventive behaviors during the second wave of the influenza outbreak in Arizona. Statistical analyses were conducted on survey data, which were collected from a random-digit telephone survey of the general public in Arizona in October 2009. The public perceived different levels of risk regarding the likelihood and their concern about contracting the 2009 H1N1 flu. These measures of risk perception were primarily correlated with people of Hispanic ethnicity, having children in the household, and recent seasonal flu experience in the previous year. The perceived likelihood was not strongly associated with preventive behaviors, whereas the perceived concern was significantly associated with precautionary and preparatory behaviors. The association between perceived concern and precautionary behavior persisted after controlling for demographic characteristics. Pandemic preparedness and response efforts need to incorporate these findings to help develop effective risk communication strategies that properly induce preventive behaviors among the public.

Positive-Themed Suicide Prevention Messages Delivered by Adolescent Peer Leaders: Proximal Impact on Classmates’ Coping Attitudes and Perceptions of Adult Support

PubMed Central

Petrova, Mariya; Wyman, Peter A.; Schmeelk-Cone, Karen; Pisani, Anthony R.

2015-01-01

Developing science-based communication guidance and positive-themed messages for suicide prevention are important priorities. Drawing on social learning and elaboration likelihood models, we designed and tested two positive-focused presentations by high school peer leaders delivered in the context of a suicide prevention program (Sources of Strength). Thirty six classrooms in four schools (N=706 students) were randomized to: (a) peer leader modeling of healthy coping, (b) peer leader modeling plus audience involvement to identify trusted adults, or (c) control condition. Students’ attitudes and norms were assessed by immediate post-only assessments. Exposure to either presentation enhanced positive coping attitudes and perceptions of adult support. Students who reported suicide ideation in the past 12 months benefited more than non-suicidal students. Beyond modeling alone, audience involvement modestly enhanced expectations of adult support, congruent with the elaboration likelihood model. Positive peer modeling is a promising alternative to communications focused on negative consequences and directives and may enhance social-interpersonal factors linked to reduced suicidal behaviors. PMID:25692382

Happy hour drink specials in the Alcohol Purchase Task.

PubMed

Kaplan, Brent A; Reed, Derek D

2018-04-01

There is strong evidence to suggest that happy hour drink specials are associated with undesirable outcomes such as increased amount of drinking, increased likelihood of being highly intoxicated, and increased likelihood of experiencing negative outcomes related to drinking (e.g., getting into fights). Public policy efforts have been made to ban or at least restrict alcohol drink specials. Research in behavioral economics-primarily demand curve analyses-has yielded valuable insights into the role of environmental effects on reinforcer consumption, especially within the context of alcohol reinforcement. The use of the Alcohol Purchase Task (APT), which asks respondents to report how many alcoholic drinks they would be willing to purchase at various prices, has contributed greatly to these efforts. The purpose of the current experiment was to determine whether self-reported consumption of alcohol on an APT changes when participants imagine a hypothetical "happy hour" scenario, akin to drink specials encountered in the real world. Results from the current experiment extend previous literature on APT vignette manipulations and provide implications for efforts to reduce problematic drinking. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Spatial design and strength of spatial signal: Effects on covariance estimation

USGS Publications Warehouse

Irvine, Kathryn M.; Gitelman, Alix I.; Hoeting, Jennifer A.

2007-01-01

In a spatial regression context, scientists are often interested in a physical interpretation of components of the parametric covariance function. For example, spatial covariance parameter estimates in ecological settings have been interpreted to describe spatial heterogeneity or “patchiness” in a landscape that cannot be explained by measured covariates. In this article, we investigate the influence of the strength of spatial dependence on maximum likelihood (ML) and restricted maximum likelihood (REML) estimates of covariance parameters in an exponential-with-nugget model, and we also examine these influences under different sampling designs—specifically, lattice designs and more realistic random and cluster designs—at differing intensities of sampling (n=144 and 361). We find that neither ML nor REML estimates perform well when the range parameter and/or the nugget-to-sill ratio is large—ML tends to underestimate the autocorrelation function and REML produces highly variable estimates of the autocorrelation function. The best estimates of both the covariance parameters and the autocorrelation function come under the cluster sampling design and large sample sizes. As a motivating example, we consider a spatial model for stream sulfate concentration.

The Relationship between Trauma, Arrest, and Incarceration History among Black Americans: Findings from the National Survey of American Life

PubMed Central

Jäggi, Lena J.; Mezuk, Briana; Watkins, Daphne C.; Jackson, James S.

2016-01-01

Prior research indicates an association between exposure to trauma (e.g., being victimized) and perpetration of crime, especially in the context of chronic victimization. This study examines the relationship between trauma exposure, posttraumatic stress disorder (PTSD), and history of arrest and incarceration among a representative sample of black Americans from the National Survey of American Life (N = 5,189). One-third had a history of arrest, and 18 percent had a history of incarceration. Frequency of trauma exposure was associated with involvement with the criminal justice system. Relative to never experiencing trauma, experiencing ≥4 traumas was associated with elevated odds of arrest (odds ratio [OR] = 4.03), being jailed (OR = 5.15), and being imprisoned (OR = 4.41), all p <.01. PTSD was also associated with likelihood of incarceration among those with a history of trauma (OR = 2.18, p <.01). Both trauma exposure and trauma-associated psychopathology are associated with increased likelihood of arrest and incarceration in adulthood among black Americans. PMID:27795871

Evolutionary genetic analyses of MEF2C gene: implications for learning and memory in Homo sapiens.

PubMed

Kalmady, Sunil V; Venkatasubramanian, Ganesan; Arasappa, Rashmi; Rao, Naren P

2013-02-01

MEF2C facilitates context-dependent fear conditioning (CFC) which is a salient aspect of hippocampus-dependent learning and memory. CFC might have played a crucial role in human evolution because of its advantageous influence on survival of species. In this study, we analyzed 23 orthologous mammalian gene sequences of MEF2C gene to examine the evidence for positive selection on this gene in Homo sapiens using Phylogenetic Analysis by Maximum Likelihood (PAML) and HyPhy software. Both PAML Bayes Empirical Bayes (BEB) and HyPhy Fixed Effects Likelihood (FEL) analyses supported significant positive selection on 4 codon sites in H. sapiens. Also, haplotter analysis revealed significant ongoing positive selection on this gene in Central European population. The study findings suggest that adaptive selective pressure on this gene might have influenced human evolution. Further research on this gene might unravel the potential role of this gene in learning and memory as well as its pathogenetic effect in certain hippocampal disorders with evolutionary basis like schizophrenia. Copyright © 2012 Elsevier B.V. All rights reserved.

Indirect detection constraints on s- and t-channel simplified models of dark matter

NASA Astrophysics Data System (ADS)

Carpenter, Linda M.; Colburn, Russell; Goodman, Jessica; Linden, Tim

2016-09-01

Recent Fermi-LAT observations of dwarf spheroidal galaxies in the Milky Way have placed strong limits on the gamma-ray flux from dark matter annihilation. In order to produce the strongest limit on the dark matter annihilation cross section, the observations of each dwarf galaxy have typically been "stacked" in a joint-likelihood analysis, utilizing optical observations to constrain the dark matter density profile in each dwarf. These limits have typically been computed only for singular annihilation final states, such as b b ¯ or τ+τ- . In this paper, we generalize this approach by producing an independent joint-likelihood analysis to set constraints on models where the dark matter particle annihilates to multiple final-state fermions. We interpret these results in the context of the most popular simplified models, including those with s- and t-channel dark matter annihilation through scalar and vector mediators. We present our results as constraints on the minimum dark matter mass and the mediator sector parameters. Additionally, we compare our simplified model results to those of effective field theory contact interactions in the high-mass limit.

Site occupancy models with heterogeneous detection probabilities

USGS Publications Warehouse

Royle, J. Andrew

2006-01-01

Models for estimating the probability of occurrence of a species in the presence of imperfect detection are important in many ecological disciplines. In these ?site occupancy? models, the possibility of heterogeneity in detection probabilities among sites must be considered because variation in abundance (and other factors) among sampled sites induces variation in detection probability (p). In this article, I develop occurrence probability models that allow for heterogeneous detection probabilities by considering several common classes of mixture distributions for p. For any mixing distribution, the likelihood has the general form of a zero-inflated binomial mixture for which inference based upon integrated likelihood is straightforward. A recent paper by Link (2003, Biometrics 59, 1123?1130) demonstrates that in closed population models used for estimating population size, different classes of mixture distributions are indistinguishable from data, yet can produce very different inferences about population size. I demonstrate that this problem can also arise in models for estimating site occupancy in the presence of heterogeneous detection probabilities. The implications of this are discussed in the context of an application to avian survey data and the development of animal monitoring programs.

Statistical Signal Processing and the Motor Cortex

PubMed Central

Brockwell, A.E.; Kass, R.E.; Schwartz, A.B.

2011-01-01

Over the past few decades, developments in technology have significantly improved the ability to measure activity in the brain. This has spurred a great deal of research into brain function and its relation to external stimuli, and has important implications in medicine and other fields. As a result of improved understanding of brain function, it is now possible to build devices that provide direct interfaces between the brain and the external world. We describe some of the current understanding of function of the motor cortex region. We then discuss a typical likelihood-based state-space model and filtering based approach to address the problems associated with building a motor cortical-controlled cursor or robotic prosthetic device. As a variation on previous work using this approach, we introduce the idea of using Markov chain Monte Carlo methods for parameter estimation in this context. By doing this instead of performing maximum likelihood estimation, it is possible to expand the range of possible models that can be explored, at a cost in terms of computational load. We demonstrate results obtained applying this methodology to experimental data gathered from a monkey. PMID:21765538

Comparing the Performance of Improved Classify-Analyze Approaches For Distal Outcomes in Latent Profile Analysis

PubMed Central

Dziak, John J.; Bray, Bethany C.; Zhang, Jieting; Zhang, Minqiang; Lanza, Stephanie T.

2016-01-01

Several approaches are available for estimating the relationship of latent class membership to distal outcomes in latent profile analysis (LPA). A three-step approach is commonly used, but has problems with estimation bias and confidence interval coverage. Proposed improvements include the correction method of Bolck, Croon, and Hagenaars (BCH; 2004), Vermunt’s (2010) maximum likelihood (ML) approach, and the inclusive three-step approach of Bray, Lanza, & Tan (2015). These methods have been studied in the related case of latent class analysis (LCA) with categorical indicators, but not as well studied for LPA with continuous indicators. We investigated the performance of these approaches in LPA with normally distributed indicators, under different conditions of distal outcome distribution, class measurement quality, relative latent class size, and strength of association between latent class and the distal outcome. The modified BCH implemented in Latent GOLD had excellent performance. The maximum likelihood and inclusive approaches were not robust to violations of distributional assumptions. These findings broadly agree with and extend the results presented by Bakk and Vermunt (2016) in the context of LCA with categorical indicators. PMID:28630602

The Episodic Nature of Experience: A Dynamical Systems Analysis.

PubMed

Sreekumar, Vishnu; Dennis, Simon; Doxas, Isidoros

2017-07-01

Context is an important construct in many domains of cognition, including learning, memory, and emotion. We used dynamical systems methods to demonstrate the episodic nature of experience by showing a natural separation between the scales over which within-context and between-context relationships operate. To do this, we represented an individual's emails extending over about 5 years in a high-dimensional semantic space and computed the dimensionalities of the subspaces occupied by these emails. Personal discourse has a two-scaled geometry with smaller within-context dimensionalities than between-context dimensionalities. Prior studies have shown that reading experience (Doxas, Dennis, & Oliver, 2010) and visual experience (Sreekumar, Dennis, Doxas, Zhuang, & Belkin, 2014) have a similar two-scaled structure. Furthermore, the recurrence plot of the emails revealed that experience is predictable and hierarchical, supporting the constructs of some influential theories of memory. The results demonstrate that experience is not scale-free and provide an important target for accounts of how experience shapes cognition. Copyright © 2016 Cognitive Science Society, Inc.

Social energy exchange theory for postpartum depression.

PubMed

Posmontier, Bobbie; Waite, Roberta

2011-01-01

Postpartum depression (PPD), a significant health problem affecting about 19.4% of postpartum women worldwide, may result in long-term cognitive and behavior problems in children, spousal depression, widespread family dysfunction, and chronic and increasingly severe maternal depression. Although current theoretical frameworks provide a rich context for studying PPD,none provides a framework that specifically addresses the dynamic relationship of the inner personal experience with the social and cultural context of PPD. The authors propose the social energy exchange theory for postpartum depression to understand how PPD impedes this dynamic relationship and suggest it as a theoretical framework for the study of interventions that would target intra- and interpersonal disturbance within the social and cultural context.

Task-dependent recurrent dynamics in visual cortex

PubMed Central

Tajima, Satohiro; Koida, Kowa; Tajima, Chihiro I; Suzuki, Hideyuki; Aihara, Kazuyuki; Komatsu, Hidehiko

2017-01-01

The capacity for flexible sensory-action association in animals has been related to context-dependent attractor dynamics outside the sensory cortices. Here, we report a line of evidence that flexibly modulated attractor dynamics during task switching are already present in the higher visual cortex in macaque monkeys. With a nonlinear decoding approach, we can extract the particular aspect of the neural population response that reflects the task-induced emergence of bistable attractor dynamics in a neural population, which could be obscured by standard unsupervised dimensionality reductions such as PCA. The dynamical modulation selectively increases the information relevant to task demands, indicating that such modulation is beneficial for perceptual decisions. A computational model that features nonlinear recurrent interaction among neurons with a task-dependent background input replicates the key properties observed in the experimental data. These results suggest that the context-dependent attractor dynamics involving the sensory cortex can underlie flexible perceptual abilities. DOI: http://dx.doi.org/10.7554/eLife.26868.001 PMID:28737487

20 Years Later: Dynamics of the School-College Partnership

ERIC Educational Resources Information Center

Heimann, Revital

2015-01-01

This descriptive study examined the dynamics of partnership over time between a training school and a college of education. Its purpose was to provide a deeper understanding of the dynamics of collaboration within the context of the partnership between the school and the college. The dynamics of the changes occurring in this collaboration over a…

Towards ultrafast dynamics with split-pulse X-ray photon correlation spectroscopy at free electron laser sources

DOE PAGES

Roseker, W.; Hruszkewycz, S. O.; Lehmkuhler, F.; ...

2018-04-27

One of the important challenges in condensed matter science is to understand ultrafast, atomic-scale fluctuations that dictate dynamic processes in equilibrium and non-equilibrium materials. Here, we report an important step towards reaching that goal by using a state-of-the-art perfect crystal based split-and-delay system, capable of splitting individual X-ray pulses and introducing femtosecond to nanosecond time delays. We show the results of an ultrafast hard X-ray photon correlation spectroscopy experiment at LCLS where split X-ray pulses were used to measure the dynamics of gold nanoparticles suspended in hexane. We show how reliable speckle contrast values can be extracted even from verymore » low intensity free electron laser (FEL) speckle patterns by applying maximum likelihood fitting, thus demonstrating the potential of a split-and-delay approach for dynamics measurements at FEL sources. This will enable the characterization of equilibrium and, importantly also reversible non-equilibrium processes in atomically disordered materials.« less

A Dynamic Navigation Model for Unmanned Aircraft Systems and an Application to Autonomous Front-On Environmental Sensing and Photography Using Low-Cost Sensor Systems.

PubMed

Cooper, Andrew James; Redman, Chelsea Anne; Stoneham, David Mark; Gonzalez, Luis Felipe; Etse, Victor Kwesi

2015-08-28

This paper presents an unmanned aircraft system (UAS) that uses a probabilistic model for autonomous front-on environmental sensing or photography of a target. The system is based on low-cost and readily-available sensor systems in dynamic environments and with the general intent of improving the capabilities of dynamic waypoint-based navigation systems for a low-cost UAS. The behavioural dynamics of target movement for the design of a Kalman filter and Markov model-based prediction algorithm are included. Geometrical concepts and the Haversine formula are applied to the maximum likelihood case in order to make a prediction regarding a future state of a target, thus delivering a new waypoint for autonomous navigation. The results of the application to aerial filming with low-cost UAS are presented, achieving the desired goal of maintained front-on perspective without significant constraint to the route or pace of target movement.

Application of system identification to analytic rotor modeling from simulated and wind tunnel dynamic test data, part 2

NASA Technical Reports Server (NTRS)

Hohenemser, K. H.; Banerjee, D.

1977-01-01

An introduction to aircraft state and parameter identification methods is presented. A simplified form of the maximum likelihood method is selected to extract analytical aeroelastic rotor models from simulated and dynamic wind tunnel test results for accelerated cyclic pitch stirring excitation. The dynamic inflow characteristics for forward flight conditions from the blade flapping responses without direct inflow measurements were examined. The rotor blades are essentially rigid for inplane bending and for torsion within the frequency range of study, but flexible in out-of-plane bending. Reverse flow effects are considered for high rotor advance ratios. Two inflow models are studied; the first is based on an equivalent blade Lock number, the second is based on a time delayed momentum inflow. In addition to the inflow parameters, basic rotor parameters like the blade natural frequency and the actual blade Lock number are identified together with measurement bias values. The effect of the theoretical dynamic inflow on the rotor eigenvalues is evaluated.

Towards ultrafast dynamics with split-pulse X-ray photon correlation spectroscopy at free electron laser sources

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

Roseker, W.; Hruszkewycz, S. O.; Lehmkuhler, F.

One of the important challenges in condensed matter science is to understand ultrafast, atomic-scale fluctuations that dictate dynamic processes in equilibrium and non-equilibrium materials. Here, we report an important step towards reaching that goal by using a state-of-the-art perfect crystal based split-and-delay system, capable of splitting individual X-ray pulses and introducing femtosecond to nanosecond time delays. We show the results of an ultrafast hard X-ray photon correlation spectroscopy experiment at LCLS where split X-ray pulses were used to measure the dynamics of gold nanoparticles suspended in hexane. We show how reliable speckle contrast values can be extracted even from verymore » low intensity free electron laser (FEL) speckle patterns by applying maximum likelihood fitting, thus demonstrating the potential of a split-and-delay approach for dynamics measurements at FEL sources. This will enable the characterization of equilibrium and, importantly also reversible non-equilibrium processes in atomically disordered materials.« less

A Dynamic Navigation Model for Unmanned Aircraft Systems and an Application to Autonomous Front-On Environmental Sensing and Photography Using Low-Cost Sensor Systems

PubMed Central

Cooper, Andrew James; Redman, Chelsea Anne; Stoneham, David Mark; Gonzalez, Luis Felipe; Etse, Victor Kwesi

2015-01-01

This paper presents an unmanned aircraft system (UAS) that uses a probabilistic model for autonomous front-on environmental sensing or photography of a target. The system is based on low-cost and readily-available sensor systems in dynamic environments and with the general intent of improving the capabilities of dynamic waypoint-based navigation systems for a low-cost UAS. The behavioural dynamics of target movement for the design of a Kalman filter and Markov model-based prediction algorithm are included. Geometrical concepts and the Haversine formula are applied to the maximum likelihood case in order to make a prediction regarding a future state of a target, thus delivering a new waypoint for autonomous navigation. The results of the application to aerial filming with low-cost UAS are presented, achieving the desired goal of maintained front-on perspective without significant constraint to the route or pace of target movement. PMID:26343680

Similarity Metrics for Closed Loop Dynamic Systems

NASA Technical Reports Server (NTRS)

Whorton, Mark S.; Yang, Lee C.; Bedrossian, Naz; Hall, Robert A.

2008-01-01

To what extent and in what ways can two closed-loop dynamic systems be said to be "similar?" This question arises in a wide range of dynamic systems modeling and control system design applications. For example, bounds on error models are fundamental to the controller optimization with modern control design methods. Metrics such as the structured singular value are direct measures of the degree to which properties such as stability or performance are maintained in the presence of specified uncertainties or variations in the plant model. Similarly, controls-related areas such as system identification, model reduction, and experimental model validation employ measures of similarity between multiple realizations of a dynamic system. Each area has its tools and approaches, with each tool more or less suited for one application or the other. Similarity in the context of closed-loop model validation via flight test is subtly different from error measures in the typical controls oriented application. Whereas similarity in a robust control context relates to plant variation and the attendant affect on stability and performance, in this context similarity metrics are sought that assess the relevance of a dynamic system test for the purpose of validating the stability and performance of a "similar" dynamic system. Similarity in the context of system identification is much more relevant than are robust control analogies in that errors between one dynamic system (the test article) and another (the nominal "design" model) are sought for the purpose of bounding the validity of a model for control design and analysis. Yet system identification typically involves open-loop plant models which are independent of the control system (with the exception of limited developments in closed-loop system identification which is nonetheless focused on obtaining open-loop plant models from closed-loop data). Moreover the objectives of system identification are not the same as a flight test and hence system identification error metrics are not directly relevant. In applications such as launch vehicles where the open loop plant is unstable it is similarity of the closed-loop system dynamics of a flight test that are relevant.

Using Context-Aware Ubiquitous Learning to Support Students' Understanding of Geometry

ERIC Educational Resources Information Center

Crompton, Helen

2015-01-01

In this study, context-aware ubiquitous learning was used to support 4th grade students as they learn angle concepts. Context-aware ubiquitous learning was provided to students primarily through the use of iPads to access real-world connections and a Dynamic Geometry Environment. Gravemeijer and van Eerde's (2009), design-based research (DBR)…

Full Service Extended Schools and Educational Inequality in Urban Contexts--New Opportunities for Progress?

ERIC Educational Resources Information Center

Raffo, Carlo; Dyson, Alan

2007-01-01

This paper examines the extent to which the UK government's full service extended schools programme has the capacity to ameliorate educational inequality in urban contexts. It starts by examining a variety of explanatory narratives for educational inequality in urban contexts in the UK and suggests that the dynamics of social exclusion created by…

Does This Older Adult With Lower Extremity Pain Have the Clinical Syndrome of Lumbar Spinal Stenosis?

PubMed Central

Suri, Pradeep; Rainville, James; Kalichman, Leonid; Katz, Jeffrey N.

2012-01-01

Context The clinical syndrome of lumbar spinal stenosis (LSS) is a common diagnosis in older adults presenting with lower extremity pain. Objective To systematically review the accuracy of the clinical examination for the diagnosis of the clinical syndrome of LSS. Data Sources MEDLINE, EMBASE, and CINAHL searches of articles published from January 1966 to September 2010. Study Selection Studies were included if they contained adequate data on the accuracy of the history and physical examination for diagnosing the clinical syndrome of LSS, using a reference standard of expert opinion with radiographic or anatomic confirmation. Data Extraction Two authors independently reviewed each study to determine eligibility, extract data, and appraise levels of evidence. Data Synthesis Four studies evaluating 741 patients were identified. Among patients with lower extremity pain, the likelihood of the clinical syndrome of LSS was increased for individuals older than 70 years (likelihood ratio [LR], 2.0; 95% confidence interval [CI], 1.6–2.5), and was decreased for those younger than 60 years (LR, 0.40; 95% CI, 0.29–0.57). The most useful symptoms for increasing the likelihood of the clinical syndrome of LSS were having no pain when seated (LR, 7.4; 95% CI, 1.9–30), improvement of symptoms when bending forward (LR, 6.4; 95% CI, 4.1–9.9), the presence of bilateral buttock or leg pain (LR, 6.3; 95% CI, 3.1–13), and neurogenic claudication (LR, 3.7; 95% CI, 2.9–4.8). Absence of neurogenic claudication (LR, 0.23; 95% CI, 0.17–0.31) decreased the likelihood of the diagnosis. A wide-based gait (LR, 13; 95% CI, 1.9–95) and abnormal Romberg test result (LR, 4.2; 95% CI, 1.4–13) increased the likelihood of the clinical syndrome of LSS. A score of 7 or higher on a diagnostic support tool including history and examination findings increased the likelihood of the clinical syndrome of LSS (LR, 3.3; 95% CI, 2.7–4.0), while a score lower than 7 made the diagnosis much less likely (LR, 0.10; 95% CI, 0.06–0.16). Conclusions The diagnosis of the clinical syndrome of LSS requires the appropriate clinical picture and radiographic findings. Absence of pain when seated and improvement of symptoms when bending forward are the most useful individual findings. Combinations of findings are most useful for identifying patients who are unlikely to have the diagnosis. PMID:21156951

Make the most of your samples: Bayes factor estimators for high-dimensional models of sequence evolution.

PubMed

Baele, Guy; Lemey, Philippe; Vansteelandt, Stijn

2013-03-06

Accurate model comparison requires extensive computation times, especially for parameter-rich models of sequence evolution. In the Bayesian framework, model selection is typically performed through the evaluation of a Bayes factor, the ratio of two marginal likelihoods (one for each model). Recently introduced techniques to estimate (log) marginal likelihoods, such as path sampling and stepping-stone sampling, offer increased accuracy over the traditional harmonic mean estimator at an increased computational cost. Most often, each model's marginal likelihood will be estimated individually, which leads the resulting Bayes factor to suffer from errors associated with each of these independent estimation processes. We here assess the original 'model-switch' path sampling approach for direct Bayes factor estimation in phylogenetics, as well as an extension that uses more samples, to construct a direct path between two competing models, thereby eliminating the need to calculate each model's marginal likelihood independently. Further, we provide a competing Bayes factor estimator using an adaptation of the recently introduced stepping-stone sampling algorithm and set out to determine appropriate settings for accurately calculating such Bayes factors, with context-dependent evolutionary models as an example. While we show that modest efforts are required to roughly identify the increase in model fit, only drastically increased computation times ensure the accuracy needed to detect more subtle details of the evolutionary process. We show that our adaptation of stepping-stone sampling for direct Bayes factor calculation outperforms the original path sampling approach as well as an extension that exploits more samples. Our proposed approach for Bayes factor estimation also has preferable statistical properties over the use of individual marginal likelihood estimates for both models under comparison. Assuming a sigmoid function to determine the path between two competing models, we provide evidence that a single well-chosen sigmoid shape value requires less computational efforts in order to approximate the true value of the (log) Bayes factor compared to the original approach. We show that the (log) Bayes factors calculated using path sampling and stepping-stone sampling differ drastically from those estimated using either of the harmonic mean estimators, supporting earlier claims that the latter systematically overestimate the performance of high-dimensional models, which we show can lead to erroneous conclusions. Based on our results, we argue that highly accurate estimation of differences in model fit for high-dimensional models requires much more computational effort than suggested in recent studies on marginal likelihood estimation.

Make the most of your samples: Bayes factor estimators for high-dimensional models of sequence evolution

PubMed Central

2013-01-01

Background Accurate model comparison requires extensive computation times, especially for parameter-rich models of sequence evolution. In the Bayesian framework, model selection is typically performed through the evaluation of a Bayes factor, the ratio of two marginal likelihoods (one for each model). Recently introduced techniques to estimate (log) marginal likelihoods, such as path sampling and stepping-stone sampling, offer increased accuracy over the traditional harmonic mean estimator at an increased computational cost. Most often, each model’s marginal likelihood will be estimated individually, which leads the resulting Bayes factor to suffer from errors associated with each of these independent estimation processes. Results We here assess the original ‘model-switch’ path sampling approach for direct Bayes factor estimation in phylogenetics, as well as an extension that uses more samples, to construct a direct path between two competing models, thereby eliminating the need to calculate each model’s marginal likelihood independently. Further, we provide a competing Bayes factor estimator using an adaptation of the recently introduced stepping-stone sampling algorithm and set out to determine appropriate settings for accurately calculating such Bayes factors, with context-dependent evolutionary models as an example. While we show that modest efforts are required to roughly identify the increase in model fit, only drastically increased computation times ensure the accuracy needed to detect more subtle details of the evolutionary process. Conclusions We show that our adaptation of stepping-stone sampling for direct Bayes factor calculation outperforms the original path sampling approach as well as an extension that exploits more samples. Our proposed approach for Bayes factor estimation also has preferable statistical properties over the use of individual marginal likelihood estimates for both models under comparison. Assuming a sigmoid function to determine the path between two competing models, we provide evidence that a single well-chosen sigmoid shape value requires less computational efforts in order to approximate the true value of the (log) Bayes factor compared to the original approach. We show that the (log) Bayes factors calculated using path sampling and stepping-stone sampling differ drastically from those estimated using either of the harmonic mean estimators, supporting earlier claims that the latter systematically overestimate the performance of high-dimensional models, which we show can lead to erroneous conclusions. Based on our results, we argue that highly accurate estimation of differences in model fit for high-dimensional models requires much more computational effort than suggested in recent studies on marginal likelihood estimation. PMID:23497171

Constrained Stochastic Extended Redundancy Analysis.

PubMed

DeSarbo, Wayne S; Hwang, Heungsun; Stadler Blank, Ashley; Kappe, Eelco

2015-06-01

We devise a new statistical methodology called constrained stochastic extended redundancy analysis (CSERA) to examine the comparative impact of various conceptual factors, or drivers, as well as the specific predictor variables that contribute to each driver on designated dependent variable(s). The technical details of the proposed methodology, the maximum likelihood estimation algorithm, and model selection heuristics are discussed. A sports marketing consumer psychology application is provided in a Major League Baseball (MLB) context where the effects of six conceptual drivers of game attendance and their defining predictor variables are estimated. Results compare favorably to those obtained using traditional extended redundancy analysis (ERA).

Titan's Elusive Lakes? Properties and Context of Dark Spots in Cassini TA Radar Data

NASA Technical Reports Server (NTRS)

Lorenz, R. D.; Elachi, C.; Stiles, B.; West, R.; Janssen, M.; Lopes, R.; Stofan, E.; Paganelli, F.; Wood, C.; Kirk, R.

2005-01-01

Titan's atmospheric methane abundance suggests the likelihood of a surface reservoir of methane and a surface sink for its photochemical products, which might also be predominantly liquid. Although large expanses of obvious hydrocarbon seas have not been unambiguously observed, a number of rather radar-dark spots up to approximately 30 km across are observed in the Synthetic Aperture Radar (SAR) data acquired during the Cassini TA encounter on October 26th 2004. Here we review the properties and setting of these dark spots to explore whether these may be hydrocarbon lakes.

The concordance index C and the Mann-Whitney parameter Pr(X>Y) with randomly censored data.

PubMed

Koziol, James A; Jia, Zhenyu

2009-06-01

Harrell's c-index or concordance C has been widely used as a measure of separation of two survival distributions. In the absence of censored data, the c-index estimates the Mann-Whitney parameter Pr(X>Y), which has been repeatedly utilized in various statistical contexts. In the presence of randomly censored data, the c-index no longer estimates Pr(X>Y); rather, a parameter that involves the underlying censoring distributions. This is in contrast to Efron's maximum likelihood estimator of the Mann-Whitney parameter, which is recommended in the setting of random censorship.

Local neighborhood transition probability estimation and its use in contextual classification

NASA Technical Reports Server (NTRS)

Chittineni, C. B.

1979-01-01

The problem of incorporating spatial or contextual information into classifications is considered. A simple model that describes the spatial dependencies between the neighboring pixels with a single parameter, Theta, is presented. Expressions are derived for updating the posteriori probabilities of the states of nature of the pattern under consideration using information from the neighboring patterns, both for spatially uniform context and for Markov dependencies in terms of Theta. Techniques for obtaining the optimal value of the parameter Theta as a maximum likelihood estimate from the local neighborhood of the pattern under consideration are developed.

Socio-economic Aspects of Health-Related Behaviors and Their Dynamics: A Case Study for the Netherlands

PubMed Central

Rezayatmand, Reza; Pavlova, Milena; Groot, Wim

2016-01-01

Background: Previous studies have mostly focused on socio-demographic and health-related determinants of health-related behaviors. Although comprehensive health insurance coverage could discourage individual lifestyle improvement due to the ex-ante moral hazard problem, few studies have examined such effects. This study examines the association of a comprehensive set of factors including socio-demographic, health status, health insurance, and perceived change in health insurance coverage with health-related behaviors and their dynamics (ie, changes in behavior). Methods: Using Survey of Health, Aging, and Retirement in Europe (SHARE) data (a European aging survey among 50+ years old) for the Netherlands in 2004 and 2007 (sample size: 1745), binary and multinomial logit models are employed to study health-related behaviors (daily smoking, excessive alcohol use, and physical inactivity in 2004) and their corresponding changes (stopping or starting unhealthy behavior between 2004 and 2007). Results: Our findings show that being older, being female, having higher education and living with a partner increase the likelihood not to be a daily smoker or to stop daily smoking. At the same time, being older (OR = 3.02 [1.31, 6.95]) and being female (OR = 1.77 [1.05, 2.96]) increases the likelihood to be or to become physically inactive. We also find that worse perceived health insurance coverage in 2007 is associated with a lower likelihood (OR = 0.19 [0.06, 0.57]) of stopping excessive alcohol use in that year. However, we do not find a strong association between the type of health insurance and health behavior. Conclusion: Our findings show that all above mentioned factors (ie, socio-demographic and health status factors) are associated with health-related behavior but not in a consistent way across all behaviors. Moreover, the dynamics of each behavior (positive or negative change) is not necessarily determined by the same factors that determine the state of that behavior. We also find that better perceived health insurance coverage is associated with a healthier lifestyle which is not compatible with an ex-ante moral hazard interpretation. Our results provide input to target policies towards elderly individuals in need of lifestyle change. However, further research should be done to identify the causal effect of health insurance on health-related behavior. PMID:27239865

Facial movements strategically camouflage involuntary social signals of face morphology.

PubMed

Gill, Daniel; Garrod, Oliver G B; Jack, Rachael E; Schyns, Philippe G

2014-05-01

Animals use social camouflage as a tool of deceit to increase the likelihood of survival and reproduction. We tested whether humans can also strategically deploy transient facial movements to camouflage the default social traits conveyed by the phenotypic morphology of their faces. We used the responses of 12 observers to create models of the dynamic facial signals of dominance, trustworthiness, and attractiveness. We applied these dynamic models to facial morphologies differing on perceived dominance, trustworthiness, and attractiveness to create a set of dynamic faces; new observers rated each dynamic face according to the three social traits. We found that specific facial movements camouflage the social appearance of a face by modulating the features of phenotypic morphology. A comparison of these facial expressions with those similarly derived for facial emotions showed that social-trait expressions, rather than being simple one-to-one overgeneralizations of emotional expressions, are a distinct set of signals composed of movements from different emotions. Our generative face models represent novel psychophysical laws for social sciences; these laws predict the perception of social traits on the basis of dynamic face identities.

State Space Modeling of Time-Varying Contemporaneous and Lagged Relations in Connectivity Maps

PubMed Central

Molenaar, Peter C. M.; Beltz, Adriene M.; Gates, Kathleen M.; Wilson, Stephen J.

2017-01-01

Most connectivity mapping techniques for neuroimaging data assume stationarity (i.e., network parameters are constant across time), but this assumption does not always hold true. The authors provide a description of a new approach for simultaneously detecting time-varying (or dynamic) contemporaneous and lagged relations in brain connectivity maps. Specifically, they use a novel raw data likelihood estimation technique (involving a second-order extended Kalman filter/smoother embedded in a nonlinear optimizer) to determine the variances of the random walks associated with state space model parameters and their autoregressive components. The authors illustrate their approach with simulated and blood oxygen level-dependent functional magnetic resonance imaging data from 30 daily cigarette smokers performing a verbal working memory task, focusing on seven regions of interest (ROIs). Twelve participants had dynamic directed functional connectivity maps: Eleven had one or more time-varying contemporaneous ROI state loadings, and one had a time-varying autoregressive parameter. Compared to smokers without dynamic maps, smokers with dynamic maps performed the task with greater accuracy. Thus, accurate detection of dynamic brain processes is meaningfully related to behavior in a clinical sample. PMID:26546863

Impact analyses for negative flexural responses (hogging) in railway prestressed concrete sleepers

NASA Astrophysics Data System (ADS)

Kaewunruen, S.; Ishida, T.; Remennikov, AM

2016-09-01

By nature, ballast interacts with railway concrete sleepers in order to provide bearing support to track system. Most train-track dynamic models do not consider the degradation of ballast over time. In fact, the ballast degradation causes differential settlement and impact forces acting on partial and unsupported tracks. Furthermore, localised ballast breakages underneath railseat increase the likelihood of centrebound cracks in concrete sleepers due to the unbalanced support under sleepers. This paper presents a dynamic finite element model of a standard-gauge concrete sleeper in a track system, taking into account the tensionless nature of ballast support. The finite element model was calibrated using static and dynamic responses in the past. In this paper, the effects of centre-bound ballast support on the impact behaviours of sleepers are highlighted. In addition, it is the first to demonstrate the dynamic effects of sleeper length on the dynamic design deficiency in concrete sleepers. The outcome of this study will benefit the rail maintenance criteria of track resurfacing in order to restore ballast profile and appropriate sleeper/ballast interaction.

The Benefit of Being Naïve and Knowing It: The Unfavourable Impact of Perceived Context Familiarity on Learning in Complex Problem Solving Tasks

ERIC Educational Resources Information Center

Beckmann, Jens F.; Goode, Natassia

2014-01-01

Previous research has found that embedding a problem into a familiar context does not necessarily confer an advantage over a novel context in the acquisition of new knowledge about a complex, dynamic system. In fact, it has been shown that a semantically familiar context can be detrimental to knowledge acquisition. This has been described as the…

Modeling the Impact of White-Plague Coral Disease in Climate Change Scenarios

PubMed Central

Loya, Yossi; Stone, Lewi

2015-01-01

Coral reefs are in global decline, with coral diseases increasing both in prevalence and in space, a situation that is expected only to worsen as future thermal stressors increase. Through intense surveillance, we have collected a unique and highly resolved dataset from the coral reef of Eilat (Israel, Red Sea), that documents the spatiotemporal dynamics of a White Plague Disease (WPD) outbreak over the course of a full season. Based on modern statistical methodologies, we develop a novel spatial epidemiological model that uses a maximum-likelihood procedure to fit the data and assess the transmission pattern of WPD. We link the model to sea surface temperature (SST) and test the possible effect of increasing temperatures on disease dynamics. Our results reveal that the likelihood of a susceptible coral to become infected is governed both by SST and by its spatial location relative to nearby infected corals. The model shows that the magnitude of WPD epidemics strongly depends on demographic circumstances; under one extreme, when recruitment is free-space regulated and coral density remains relatively constant, even an increase of only 0.5°C in SST can cause epidemics to double in magnitude. In reality, however, the spatial nature of transmission can effectively protect the community, restricting the magnitude of annual epidemics. This is because the probability of susceptible corals to become infected is negatively associated with coral density. Based on our findings, we expect that infectious diseases having a significant spatial component, such as Red-Sea WPD, will never lead to a complete destruction of the coral community under increased thermal stress. However, this also implies that signs of recovery of local coral communities may be misleading; indicative more of spatial dynamics than true rehabilitation of these communities. In contrast to earlier generic models, our approach captures dynamics of WPD both in space and time, accounting for the highly seasonal nature of annual WPD outbreaks. PMID:26086846

Risk assessment and subsequent nursing interventions in a forensic mental health inpatient setting: Associations and impact on aggressive behaviour.

PubMed

Maguire, Tessa; Daffern, Michael; Bowe, Steven J; McKenna, Brian

2018-03-01

To examine associations between risk of aggression and nursing interventions designed to prevent aggression. There is scarce empirical research exploring the nature and effectiveness of interventions designed to prevent inpatient aggression. Some strategies may be effective when patients are escalating, whereas others may be effective when aggression is imminent. Research examining level of risk for aggression and selection and effectiveness of interventions and impact on aggression is necessary. Archival case file. Data from clinical files of 30 male and 30 female patients across three forensic acute units for the first 60 days of hospitalisation were collected. Risk for imminent aggression as measured by the Dynamic Appraisal of Situational Aggression, documented nursing interventions following each assessment, and acts of aggression within the 24-hours following assessment were collected. Generalised estimating equations were used to investigate whether intervention strategies were associated with reduction in aggression. When a Dynamic Appraisal of Situational Aggression assessment was completed, nurses intervened more frequently compared to days when no Dynamic Appraisal of Situational Aggression assessment was completed. Higher Dynamic Appraisal of Situational Aggression assessments were associated with a greater number of interventions. The percentage of interventions selected for males differed from females; males received more pro re nata medication and observation, and females received more limit setting, one-to-one nursing and reassurance. Pro re nata medication was the most commonly documented intervention (35.9%) in this study. Pro re nata medication, limit setting and reassurance were associated with an increased likelihood of aggression in some risk bands. Structured risk assessment prompts intervention, and higher risk ratings result in more interventions. Patient gender influences the type of interventions. Some interventions are associated with increased aggression, although this depends upon gender and risk level. When structured risk assessments are used, there is greater likelihood of intervention. Intervention should occur early using least restrictive interventions. © 2017 John Wiley & Sons Ltd.

Plant-herbivore interactions mediated by plant toxicity

USGS Publications Warehouse

Feng, Z.; Liu, R.; DeAngelis, D.L.

2008-01-01

We explore the impact of plant toxicity on the dynamics of a plant-herbivore interaction, such as that of a mammalian browser and its plant forage species, by studying a mathematical model that includes a toxin-determined functional response. In this functional response, the traditional Holling Type 2 response is modified to include the negative effect of toxin on herbivore growth, which can overwhelm the positive effect of biomass ingestion at sufficiently high plant toxicant concentrations. Two types of consumption decisions of the herbivore are considered. One of these (Case 1) incorporates the adaptation of the herbivore to control its rate of consumption of plant items when that is likely to lead to levels of toxicity that more than offset the marginal gain to the herbivore of consuming more plant biomass, while the other (Case 2) simply assumes that, although the herbivore's rate of ingestion of plant biomass is negatively affected by increasing ingestion of toxicant relative to the load it can safely deal with, the herbivore is not able to prevent detrimental or even lethal levels of toxicant intake. A primary result of this work is that these differences in behavior lead to dramatically different outcomes, summarized in bifurcation diagrams. In Case 2, a wide variety of dynamics may occur due to the interplay of Holling Type 2 dynamics and the effect of the plant toxicant. These dynamics include the occurrence of bistability, in which both a periodic solution and the herbivore-extinction equilibrium are attractors, as well the possibility of a homoclinic bifurcation. Whether the herbivore goes to extinction in the bistable case depends on initial conditions of herbivore and plant biomasses. For relatively low herbivore resource acquisition rates, the toxicant effect increases the likelihood of 'paradox of enrichment' type limit cycle oscillations, but at higher resource acquisition rates, the toxicant may decrease the likelihood of these cycles. ?? 2007 Elsevier Ltd. All rights reserved.

Race Differences in Cardiac Catheterization: The Role of Social Contextual Variables

PubMed Central

Kressin, Nancy R.

2010-01-01

BACKGROUND Race differences in the receipt of invasive cardiac procedures are well-documented but the etiology remains poorly understood. OBJECTIVE We examined how social contextual variables were related to race differences in the likelihood of receiving cardiac catheterization in a sample of veterans who were recommended to undergo the procedure by a physician. DESIGN Prospective observational cohort study. PARTICIPANTS A subsample from a study examining race disparities in cardiac catheterization of 48 Black/African American and 189 White veterans who were recommended by a physician to undergo cardiac catheterization. MEASURES We assessed social contextual variables (e.g., knowing somebody who had the procedure, being encouraged by family or friends), clinical variables (e.g., hypertension, maximal medical therapy), and if participants received cardiac catheterization at any point during the study. KEY RESULTS Blacks/African Americans were less likely to undergo cardiac catheterization compared to Whites even after controlling for age, education, and clinical variables (OR = 0.31; 95% CI, 0.13, 0.75). After controlling for demographic and clinical variables, three social contextual variables were significantly related to increased likelihood of receiving catheterization: knowing someone who had undergone the procedure (OR = 3.14; 95% CI, 1.70, 8.74), social support (OR = 2.05; 95% CI, 1.17, 2.78), and being encouraged by family to have procedure (OR = 1.45; 95% CI, 1.08, 1.90). After adding the social contextual variables, race was no longer significantly related to the likelihood of receiving catheterization, thus suggesting that social context plays an important role in the relationship between race and cardiac catheterization. CONCLUSIONS Our results suggest that social contextual factors are related to the likelihood of receiving recommended care. In addition, accounting for these relationships attenuated the observed race disparities between Whites and Blacks/African Americans who were recommended to undergo cardiac catheterization by their physicians. PMID:20383600

Missing data methods for dealing with missing items in quality of life questionnaires. A comparison by simulation of personal mean score, full information maximum likelihood, multiple imputation, and hot deck techniques applied to the SF-36 in the French 2003 decennial health survey.

PubMed

Peyre, Hugo; Leplège, Alain; Coste, Joël

2011-03-01

Missing items are common in quality of life (QoL) questionnaires and present a challenge for research in this field. It remains unclear which of the various methods proposed to deal with missing data performs best in this context. We compared personal mean score, full information maximum likelihood, multiple imputation, and hot deck techniques using various realistic simulation scenarios of item missingness in QoL questionnaires constructed within the framework of classical test theory. Samples of 300 and 1,000 subjects were randomly drawn from the 2003 INSEE Decennial Health Survey (of 23,018 subjects representative of the French population and having completed the SF-36) and various patterns of missing data were generated according to three different item non-response rates (3, 6, and 9%) and three types of missing data (Little and Rubin's "missing completely at random," "missing at random," and "missing not at random"). The missing data methods were evaluated in terms of accuracy and precision for the analysis of one descriptive and one association parameter for three different scales of the SF-36. For all item non-response rates and types of missing data, multiple imputation and full information maximum likelihood appeared superior to the personal mean score and especially to hot deck in terms of accuracy and precision; however, the use of personal mean score was associated with insignificant bias (relative bias <2%) in all studied situations. Whereas multiple imputation and full information maximum likelihood are confirmed as reference methods, the personal mean score appears nonetheless appropriate for dealing with items missing from completed SF-36 questionnaires in most situations of routine use. These results can reasonably be extended to other questionnaires constructed according to classical test theory.

Conscious and unconscious context-specific cognitive control

PubMed Central

Schouppe, Nathalie; de Ferrerre, Evelien; Van Opstal, Filip; Braem, Senne; Notebaert, Wim

2014-01-01

A key feature of the human cognitive system is its ability to deal with an ever-changing environment. One prototypical example is the observation that we adjust our information processing depending on the conflict-likelihood of a context (context-specific proportion congruency effect, CSPC, Crump etal., 2006). Recently, empirical studies started to question the role of consciousness in these strategic adaptation processes (for reviews, see Desender and Van den Bussche, 2012; Kunde etal., 2012). However, these studies have not yielded unequivocal results (e.g., Kunde, 2003; Heinemann etal., 2009; Van Gaal etal., 2010a; Desender etal., 2013; Reuss etal., 2014). In the present study, we aim at replicating the experiment of Heinemann etal. (2009) in which the proportion of congruent and incongruent trials between different contexts was varied in a masked priming task. Their results showed a reduction of the congruency effect for the context with more incongruent trials. However, this CSPC effect was only observed when the prime–target conflict was conscious, rather than unconscious, suggesting that context-specific control operates within the boundaries of awareness. Our replication attempt however contrasts these findings. In the first experiment we found no evidence for a CSPC effect in reaction times (RTs), neither in the conscious nor in the unconscious condition. The error rate analysis did show a CSPC effect, albeit not one modulated by consciousness. In the second experiment we found an overall CSPC effect in RTs, independent of consciousness. The error rates did not display a CSPC pattern. These mixed results seem to nuance the findings of Heinemann etal. (2009) and highlight the need for replication studies in psychology research. PMID:24926275

Valuing EQ-5D-5L health states 'in context' using a discrete choice experiment.

PubMed

Cole, Amanda; Shah, Koonal; Mulhern, Brendan; Feng, Yan; Devlin, Nancy

2018-05-01

In health state valuation studies, health states are typically presented as a series of sentences, each describing a health dimension and severity 'level'. Differences in the severity levels can be subtle, and confusion about which is 'worse' can lead to logically inconsistent valuation data. A solution could be to mimic the way patients self-report health, where the ordinal structure of levels is clear. We develop and test the feasibility of presenting EQ-5D-5L health states in the 'context' of the entire EQ-5D-5L descriptive system. An online two-arm discrete choice experiment was conducted in the UK (n = 993). Respondents were randomly allocated to a control (standard presentation) or 'context' arm. Each respondent completed 16 paired comparison tasks and feedback questions about the tasks. Differences across arms were assessed using regression analyses. Presenting health states 'in context' can significantly reduce the selection of logically dominated health states, particularly for labels 'severe' and 'extreme' (χ 2  = 46.02, p < 0.001). Preferences differ significantly between arms (likelihood ratio statistic = 42.00, p < 0.05). Comparing conditional logit modeling results, coefficients are ordered as expected for both arms, but the magnitude of decrements between levels is larger for the context arm. Health state presentation is a key consideration in the design of valuation studies. Presenting health states 'in context' affects valuation data and reduces logical inconsistencies. Our results could have implications for other valuation tasks such as time trade-off, and for the valuation of other preference-based measures.

Does social context matter? An ecological momentary assessment study of marijuana use among college students.

PubMed

Phillips, Kristina T; Phillips, Michael M; Lalonde, Trent L; Prince, Mark A

2018-08-01

Past research has shown that marijuana use occurs commonly in social situations for young adults, though few studies have examined the association between immediate social context and marijuana use patterns and associated problems. The current study examined the impact of demographics, marijuana use and problem use, alcohol use, craving, and social context on the likelihood of using marijuana with others via ecological momentary assessment (EMA). College-student marijuana users (N=56) were recruited and completed a baseline assessment and training on the two-week signal-contingent EMA protocol. Participants were sent text messages three times per day randomly for two weeks. Of the 1131 EMA instances during which participants reported using marijuana, 862 (76.22%) were labeled as being with others. Forty-five participants (80.36%) reported marijuana use with others present during at least half of the times they used marijuana. Findings from a multilevel logistic regression model showed a significant positive association between the probability of using with others and minutes spent using marijuana (b=0.047, p<0.001), social facilitation (b=0.138, p<0.001), and DSM-IV diagnosis (dependence versus no diagnosis, b=1.350, p=0.047). Cannabis dependence, more time using marijuana in the moment, and using for social facilitation purposes were positively associated with using marijuana in the context of being with others. Daily users had more variability in terms of the social context of their use. This study illustrates the complex relationship between social context and marijuana use. Copyright © 2018 Elsevier Ltd. All rights reserved.

The past and future of modeling forest dynamics: from growth and yield curves to forest landscape models

Treesearch

Stephen R. Shifley; Hong S. He; Heike Lischke; Wen J. Wang; Wenchi Jin; Eric J. Gustafson; Jonathan R. Thompson; Frank R. Thompson; William D. Dijak; Jian Yang

2017-01-01

Context. Quantitative models of forest dynamics have followed a progression toward methods with increased detail, complexity, and spatial extent. Objectives. We highlight milestones in the development of forest dynamics models and identify future research and application opportunities. Methods. We reviewed...

Dynamic Geometry as a Context for Exploring Conjectures

ERIC Educational Resources Information Center

Wares, Arsalan

2018-01-01

The purpose of this paper is to provide examples of "non-traditional" proof-related activities that can explored in a dynamic geometry environment by university and high school students of mathematics. These propositions were encountered in the dynamic geometry environment. The author believes that teachers can ask their students to…

Student Errors in Dynamic Mathematical Environments

ERIC Educational Resources Information Center

Brown, Molly; Bossé, Michael J.; Chandler, Kayla

2016-01-01

This study investigates the nature of student errors in the context of problem solving and Dynamic Math Environments. This led to the development of the Problem Solving Action Identification Framework; this framework captures and defines all activities and errors associated with problem solving in a dynamic math environment. Found are three…

Mental models accurately predict emotion transitions.

PubMed

Thornton, Mark A; Tamir, Diana I

2017-06-06

Successful social interactions depend on people's ability to predict others' future actions and emotions. People possess many mechanisms for perceiving others' current emotional states, but how might they use this information to predict others' future states? We hypothesized that people might capitalize on an overlooked aspect of affective experience: current emotions predict future emotions. By attending to regularities in emotion transitions, perceivers might develop accurate mental models of others' emotional dynamics. People could then use these mental models of emotion transitions to predict others' future emotions from currently observable emotions. To test this hypothesis, studies 1-3 used data from three extant experience-sampling datasets to establish the actual rates of emotional transitions. We then collected three parallel datasets in which participants rated the transition likelihoods between the same set of emotions. Participants' ratings of emotion transitions predicted others' experienced transitional likelihoods with high accuracy. Study 4 demonstrated that four conceptual dimensions of mental state representation-valence, social impact, rationality, and human mind-inform participants' mental models. Study 5 used 2 million emotion reports on the Experience Project to replicate both of these findings: again people reported accurate models of emotion transitions, and these models were informed by the same four conceptual dimensions. Importantly, neither these conceptual dimensions nor holistic similarity could fully explain participants' accuracy, suggesting that their mental models contain accurate information about emotion dynamics above and beyond what might be predicted by static emotion knowledge alone.

Fitting of dynamic recurrent neural network models to sensory stimulus-response data.

PubMed

Doruk, R Ozgur; Zhang, Kechen

2018-06-02

We present a theoretical study aiming at model fitting for sensory neurons. Conventional neural network training approaches are not applicable to this problem due to lack of continuous data. Although the stimulus can be considered as a smooth time-dependent variable, the associated response will be a set of neural spike timings (roughly the instants of successive action potential peaks) that have no amplitude information. A recurrent neural network model can be fitted to such a stimulus-response data pair by using the maximum likelihood estimation method where the likelihood function is derived from Poisson statistics of neural spiking. The universal approximation feature of the recurrent dynamical neuron network models allows us to describe excitatory-inhibitory characteristics of an actual sensory neural network with any desired number of neurons. The stimulus data are generated by a phased cosine Fourier series having a fixed amplitude and frequency but a randomly shot phase. Various values of amplitude, stimulus component size, and sample size are applied in order to examine the effect of the stimulus to the identification process. Results are presented in tabular and graphical forms at the end of this text. In addition, to demonstrate the success of this research, a study involving the same model, nominal parameters and stimulus structure, and another study that works on different models are compared to that of this research.

Sequential dynamics in visual short-term memory.

PubMed

Kool, Wouter; Conway, Andrew R A; Turk-Browne, Nicholas B

2014-10-01

Visual short-term memory (VSTM) is thought to help bridge across changes in visual input, and yet many studies of VSTM employ static displays. Here we investigate how VSTM copes with sequential input. In particular, we characterize the temporal dynamics of several different components of VSTM performance, including: storage probability, precision, variability in precision, guessing, and swapping. We used a variant of the continuous-report VSTM task developed for static displays, quantifying the contribution of each component with statistical likelihood estimation, as a function of serial position and set size. In Experiments 1 and 2, storage probability did not vary by serial position for small set sizes, but showed a small primacy effect and a robust recency effect for larger set sizes; precision did not vary by serial position or set size. In Experiment 3, the recency effect was shown to reflect an increased likelihood of swapping out items from earlier serial positions and swapping in later items, rather than an increased rate of guessing for earlier items. Indeed, a model that incorporated responding to non-targets provided a better fit to these data than alternative models that did not allow for swapping or that tried to account for variable precision. These findings suggest that VSTM is updated in a first-in-first-out manner, and they bring VSTM research into closer alignment with classical working memory research that focuses on sequential behavior and interference effects.

Sequential dynamics in visual short-term memory

PubMed Central

Conway, Andrew R. A.; Turk-Browne, Nicholas B.

2014-01-01

Visual short-term memory (VSTM) is thought to help bridge across changes in visual input, and yet many studies of VSTM employ static displays. Here we investigate how VSTM copes with sequential input. In particular, we characterize the temporal dynamics of several different components of VSTM performance, including: storage probability, precision, variability in precision, guessing, and swapping. We used a variant of the continuous-report VSTM task developed for static displays, quantifying the contribution of each component with statistical likelihood estimation, as a function of serial position and set size. In Experiments 1 and 2, storage probability did not vary by serial position for small set sizes, but showed a small primacy effect and a robust recency effect for larger set sizes; precision did not vary by serial position or set size. In Experiment 3, the recency effect was shown to reflect an increased likelihood of swapping out items from earlier serial positions and swapping in later items, rather than an increased rate of guessing for earlier items. Indeed, a model that incorporated responding to non-targets provided a better fit to these data than alternative models that did not allow for swapping or that tried to account for variable precision. These findings suggest that VSTM is updated in a first-in-first-out manner, and they bring VSTM research into closer alignment with classical working memory research that focuses on sequential behavior and interference effects. PMID:25228092

Nonlinear Autoregressive Exogenous modeling of a large anaerobic digester producing biogas from cattle waste.

PubMed

Dhussa, Anil K; Sambi, Surinder S; Kumar, Shashi; Kumar, Sandeep; Kumar, Surendra

2014-10-01

In waste-to-energy plants, there is every likelihood of variations in the quantity and characteristics of the feed. Although intermediate storage tanks are used, but many times these are of inadequate capacity to dampen the variations. In such situations an anaerobic digester treating waste slurry operates under dynamic conditions. In this work a special type of dynamic Artificial Neural Network model, called Nonlinear Autoregressive Exogenous model, is used to model the dynamics of anaerobic digesters by using about one year data collected on the operating digesters. The developed model consists of two hidden layers each having 10 neurons, and uses 18days delay. There are five neurons in input layer and one neuron in output layer for a day. Model predictions of biogas production rate are close to plant performance within ±8% deviation. Copyright © 2014 Elsevier Ltd. All rights reserved.

Femur loading in feet-first fall experiments using an anthropomorphic test device.

PubMed

Thompson, Angela; Bertocci, Gina; Smalley, Craig

2018-03-31

Femur fractures are a common orthopedic injury in young children. Falls account for a large portion of accidental femur fractures in young children, but there is also a high prevalence of femur fractures in child abuse, with falls often provided as false histories. Objective information regarding fracture potential in short distance fall scenarios may aid in assessing whether a child's injuries are the result of abuse or an accidental fall. Knowledge of femur loading is the first step towards understanding likelihood of fracture in a fall. Characterize femur loading during feet-first free falls using a surrogate representing a 12-month-old child. The femur and hip joint of a surrogate representing a 12-month-old were modified to improve biofidelity and measure femur loading; 6-axis load cells were integrated into the proximal and distal femur. Femur modification was based upon CT imaging of cadaveric femurs in children 10-14 months of age. Using the modified 12-month-old surrogate, feet-first free falls from 69 cm and 119 cm heights onto padded carpet and linoleum were conducted to assess fall dynamics and determine femur loading. Femur compression, bending moment, shear and torsional moment were measured for each fall. Fall dynamics differed across fall heights, but did not substantially differ by impact surface type. Significant differences were found in all loading conditions across fall heights, while only compression and bending loads differed between carpet and linoleum surfaces. Maximum compression, bending, torsion and shear occurred in 119 cm falls and were 572 N, 23 N-m, 11 N-m and 281 N, respectively. Fall dynamics play an important role in the biomechanical assessment of falls. Fall height was found to influence both fall dynamics and femur loading, while impact surface affected only compression and bending in feet-first falls; fall dynamics did not differ across carpet and linoleum. Improved pediatric thresholds are necessary to predict likelihood of fracture, but morphologically accurate representation of the lower extremity, along with accurate characterization of loading in falls are a crucial first step. Copyright © 2018 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Access Control for Cooperation Systems Based on Group Situation

NASA Astrophysics Data System (ADS)

Kim, Minsoo; Joshi, James B. D.; Kim, Minkoo

Cooperation systems characterize many emerging environments such as ubiquitous and pervasive systems. Agent based cooperation systems have been proposed in the literature to address challenges of such emerging application environments. A key aspect of such agent based cooperation system is the group situation that changes dynamically and governs the requirements of the cooperation. While individual agent context is important, the overall cooperation behavior is more driven by the group context because of relationships and interactions between agents. Dynamic access control based on group situation is a crucial challenge in such cooperation systems. In this paper we propose a dynamic role based access control model for cooperation systems based on group situation. The model emphasizes capability based agent to role mapping and group situation based permission assignment to allow capturing dynamic access policies that evolve continuously.

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.

Equivalence between Step Selection Functions and Biased Correlated Random Walks for Statistical Inference on Animal Movement.

PubMed

Duchesne, Thierry; Fortin, Daniel; Rivest, Louis-Paul

2015-01-01

Animal movement has a fundamental impact on population and community structure and dynamics. Biased correlated random walks (BCRW) and step selection functions (SSF) are commonly used to study movements. Because no studies have contrasted the parameters and the statistical properties of their estimators for models constructed under these two Lagrangian approaches, it remains unclear whether or not they allow for similar inference. First, we used the Weak Law of Large Numbers to demonstrate that the log-likelihood function for estimating the parameters of BCRW models can be approximated by the log-likelihood of SSFs. Second, we illustrated the link between the two approaches by fitting BCRW with maximum likelihood and with SSF to simulated movement data in virtual environments and to the trajectory of bison (Bison bison L.) trails in natural landscapes. Using simulated and empirical data, we found that the parameters of a BCRW estimated directly from maximum likelihood and by fitting an SSF were remarkably similar. Movement analysis is increasingly used as a tool for understanding the influence of landscape properties on animal distribution. In the rapidly developing field of movement ecology, management and conservation biologists must decide which method they should implement to accurately assess the determinants of animal movement. We showed that BCRW and SSF can provide similar insights into the environmental features influencing animal movements. Both techniques have advantages. BCRW has already been extended to allow for multi-state modeling. Unlike BCRW, however, SSF can be estimated using most statistical packages, it can simultaneously evaluate habitat selection and movement biases, and can easily integrate a large number of movement taxes at multiple scales. SSF thus offers a simple, yet effective, statistical technique to identify movement taxis.

Land Suitability Modeling using a Geographic Socio-Environmental Niche-Based Approach: A Case Study from Northeastern Thailand

PubMed Central

Heumann, Benjamin W.; Walsh, Stephen J.; Verdery, Ashton M.; McDaniel, Phillip M.; Rindfuss, Ronald R.

2012-01-01

Understanding the pattern-process relations of land use/land cover change is an important area of research that provides key insights into human-environment interactions. The suitability or likelihood of occurrence of land use such as agricultural crop types across a human-managed landscape is a central consideration. Recent advances in niche-based, geographic species distribution modeling (SDM) offer a novel approach to understanding land suitability and land use decisions. SDM links species presence-location data with geospatial information and uses machine learning algorithms to develop non-linear and discontinuous species-environment relationships. Here, we apply the MaxEnt (Maximum Entropy) model for land suitability modeling by adapting niche theory to a human-managed landscape. In this article, we use data from an agricultural district in Northeastern Thailand as a case study for examining the relationships between the natural, built, and social environments and the likelihood of crop choice for the commonly grown crops that occur in the Nang Rong District – cassava, heavy rice, and jasmine rice, as well as an emerging crop, fruit trees. Our results indicate that while the natural environment (e.g., elevation and soils) is often the dominant factor in crop likelihood, the likelihood is also influenced by household characteristics, such as household assets and conditions of the neighborhood or built environment. Furthermore, the shape of the land use-environment curves illustrates the non-continuous and non-linear nature of these relationships. This approach demonstrates a novel method of understanding non-linear relationships between land and people. The article concludes with a proposed method for integrating the niche-based rules of land use allocation into a dynamic land use model that can address both allocation and quantity of agricultural crops. PMID:24187378

Dynamical Integration of Language and Behavior in a Recurrent Neural Network for Human-Robot Interaction.

PubMed

Yamada, Tatsuro; Murata, Shingo; Arie, Hiroaki; Ogata, Tetsuya

2016-01-01

To work cooperatively with humans by using language, robots must not only acquire a mapping between language and their behavior but also autonomously utilize the mapping in appropriate contexts of interactive tasks online. To this end, we propose a novel learning method linking language to robot behavior by means of a recurrent neural network. In this method, the network learns from correct examples of the imposed task that are given not as explicitly separated sets of language and behavior but as sequential data constructed from the actual temporal flow of the task. By doing this, the internal dynamics of the network models both language-behavior relationships and the temporal patterns of interaction. Here, "internal dynamics" refers to the time development of the system defined on the fixed-dimensional space of the internal states of the context layer. Thus, in the execution phase, by constantly representing where in the interaction context it is as its current state, the network autonomously switches between recognition and generation phases without any explicit signs and utilizes the acquired mapping in appropriate contexts. To evaluate our method, we conducted an experiment in which a robot generates appropriate behavior responding to a human's linguistic instruction. After learning, the network actually formed the attractor structure representing both language-behavior relationships and the task's temporal pattern in its internal dynamics. In the dynamics, language-behavior mapping was achieved by the branching structure. Repetition of human's instruction and robot's behavioral response was represented as the cyclic structure, and besides, waiting to a subsequent instruction was represented as the fixed-point attractor. Thanks to this structure, the robot was able to interact online with a human concerning the given task by autonomously switching phases.

Model systems for single molecule polymer dynamics

PubMed Central

Latinwo, Folarin

2012-01-01

Double stranded DNA (dsDNA) has long served as a model system for single molecule polymer dynamics. However, dsDNA is a semiflexible polymer, and the structural rigidity of the DNA double helix gives rise to local molecular properties and chain dynamics that differ from flexible chains, including synthetic organic polymers. Recently, we developed single stranded DNA (ssDNA) as a new model system for single molecule studies of flexible polymer chains. In this work, we discuss model polymer systems in the context of “ideal” and “real” chain behavior considering thermal blobs, tension blobs, hydrodynamic drag and force–extension relations. In addition, we present monomer aspect ratio as a key parameter describing chain conformation and dynamics, and we derive dynamical scaling relations in terms of this molecular-level parameter. We show that asymmetric Kuhn segments can suppress monomer–monomer interactions, thereby altering global chain dynamics. Finally, we discuss ssDNA in the context of a new model system for single molecule polymer dynamics. Overall, we anticipate that future single polymer studies of flexible chains will reveal new insight into the dynamic behavior of “real” polymers, which will highlight the importance of molecular individualism and the prevalence of non-linear phenomena. PMID:22956980

Fast integration-based prediction bands for ordinary differential equation models.

PubMed

Hass, Helge; Kreutz, Clemens; Timmer, Jens; Kaschek, Daniel

2016-04-15

To gain a deeper understanding of biological processes and their relevance in disease, mathematical models are built upon experimental data. Uncertainty in the data leads to uncertainties of the model's parameters and in turn to uncertainties of predictions. Mechanistic dynamic models of biochemical networks are frequently based on nonlinear differential equation systems and feature a large number of parameters, sparse observations of the model components and lack of information in the available data. Due to the curse of dimensionality, classical and sampling approaches propagating parameter uncertainties to predictions are hardly feasible and insufficient. However, for experimental design and to discriminate between competing models, prediction and confidence bands are essential. To circumvent the hurdles of the former methods, an approach to calculate a profile likelihood on arbitrary observations for a specific time point has been introduced, which provides accurate confidence and prediction intervals for nonlinear models and is computationally feasible for high-dimensional models. In this article, reliable and smooth point-wise prediction and confidence bands to assess the model's uncertainty on the whole time-course are achieved via explicit integration with elaborate correction mechanisms. The corresponding system of ordinary differential equations is derived and tested on three established models for cellular signalling. An efficiency analysis is performed to illustrate the computational benefit compared with repeated profile likelihood calculations at multiple time points. The integration framework and the examples used in this article are provided with the software package Data2Dynamics, which is based on MATLAB and freely available at http://www.data2dynamics.org helge.hass@fdm.uni-freiburg.de Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Model Based Targeting of IL-6-Induced Inflammatory Responses in Cultured Primary Hepatocytes to Improve Application of the JAK Inhibitor Ruxolitinib

PubMed Central

Sobotta, Svantje; Raue, Andreas; Huang, Xiaoyun; Vanlier, Joep; Jünger, Anja; Bohl, Sebastian; Albrecht, Ute; Hahnel, Maximilian J.; Wolf, Stephanie; Mueller, Nikola S.; D'Alessandro, Lorenza A.; Mueller-Bohl, Stephanie; Boehm, Martin E.; Lucarelli, Philippe; Bonefas, Sandra; Damm, Georg; Seehofer, Daniel; Lehmann, Wolf D.; Rose-John, Stefan; van der Hoeven, Frank; Gretz, Norbert; Theis, Fabian J.; Ehlting, Christian; Bode, Johannes G.; Timmer, Jens; Schilling, Marcel; Klingmüller, Ursula

2017-01-01

IL-6 is a central mediator of the immediate induction of hepatic acute phase proteins (APP) in the liver during infection and after injury, but increased IL-6 activity has been associated with multiple pathological conditions. In hepatocytes, IL-6 activates JAK1-STAT3 signaling that induces the negative feedback regulator SOCS3 and expression of APPs. While different inhibitors of IL-6-induced JAK1-STAT3-signaling have been developed, understanding their precise impact on signaling dynamics requires a systems biology approach. Here we present a mathematical model of IL-6-induced JAK1-STAT3 signaling that quantitatively links physiological IL-6 concentrations to the dynamics of IL-6-induced signal transduction and expression of target genes in hepatocytes. The mathematical model consists of coupled ordinary differential equations (ODE) and the model parameters were estimated by a maximum likelihood approach, whereas identifiability of the dynamic model parameters was ensured by the Profile Likelihood. Using model simulations coupled with experimental validation we could optimize the long-term impact of the JAK-inhibitor Ruxolitinib, a therapeutic compound that is quickly metabolized. Model-predicted doses and timing of treatments helps to improve the reduction of inflammatory APP gene expression in primary mouse hepatocytes close to levels observed during regenerative conditions. The concept of improved efficacy of the inhibitor through multiple treatments at optimized time intervals was confirmed in primary human hepatocytes. Thus, combining quantitative data generation with mathematical modeling suggests that repetitive treatment with Ruxolitinib is required to effectively target excessive inflammatory responses without exceeding doses recommended by the clinical guidelines. PMID:29062282

Perceptual precision of passive body tilt is consistent with statistically optimal cue integration

PubMed Central

Karmali, Faisal; Nicoucar, Keyvan; Merfeld, Daniel M.

2017-01-01

When making perceptual decisions, humans have been shown to optimally integrate independent noisy multisensory information, matching maximum-likelihood (ML) limits. Such ML estimators provide a theoretic limit to perceptual precision (i.e., minimal thresholds). However, how the brain combines two interacting (i.e., not independent) sensory cues remains an open question. To study the precision achieved when combining interacting sensory signals, we measured perceptual roll tilt and roll rotation thresholds between 0 and 5 Hz in six normal human subjects. Primary results show that roll tilt thresholds between 0.2 and 0.5 Hz were significantly lower than predicted by a ML estimator that includes only vestibular contributions that do not interact. In this paper, we show how other cues (e.g., somatosensation) and an internal representation of sensory and body dynamics might independently contribute to the observed performance enhancement. In short, a Kalman filter was combined with an ML estimator to match human performance, whereas the potential contribution of nonvestibular cues was assessed using published bilateral loss patient data. Our results show that a Kalman filter model including previously proven canal-otolith interactions alone (without nonvestibular cues) can explain the observed performance enhancements as can a model that includes nonvestibular contributions. NEW & NOTEWORTHY We found that human whole body self-motion direction-recognition thresholds measured during dynamic roll tilts were significantly lower than those predicted by a conventional maximum-likelihood weighting of the roll angular velocity and quasistatic roll tilt cues. Here, we show that two models can each match this “apparent” better-than-optimal performance: 1) inclusion of a somatosensory contribution and 2) inclusion of a dynamic sensory interaction between canal and otolith cues via a Kalman filter model. PMID:28179477

Model Based Targeting of IL-6-Induced Inflammatory Responses in Cultured Primary Hepatocytes to Improve Application of the JAK Inhibitor Ruxolitinib.

PubMed

Sobotta, Svantje; Raue, Andreas; Huang, Xiaoyun; Vanlier, Joep; Jünger, Anja; Bohl, Sebastian; Albrecht, Ute; Hahnel, Maximilian J; Wolf, Stephanie; Mueller, Nikola S; D'Alessandro, Lorenza A; Mueller-Bohl, Stephanie; Boehm, Martin E; Lucarelli, Philippe; Bonefas, Sandra; Damm, Georg; Seehofer, Daniel; Lehmann, Wolf D; Rose-John, Stefan; van der Hoeven, Frank; Gretz, Norbert; Theis, Fabian J; Ehlting, Christian; Bode, Johannes G; Timmer, Jens; Schilling, Marcel; Klingmüller, Ursula

2017-01-01

IL-6 is a central mediator of the immediate induction of hepatic acute phase proteins (APP) in the liver during infection and after injury, but increased IL-6 activity has been associated with multiple pathological conditions. In hepatocytes, IL-6 activates JAK1-STAT3 signaling that induces the negative feedback regulator SOCS3 and expression of APPs. While different inhibitors of IL-6-induced JAK1-STAT3-signaling have been developed, understanding their precise impact on signaling dynamics requires a systems biology approach. Here we present a mathematical model of IL-6-induced JAK1-STAT3 signaling that quantitatively links physiological IL-6 concentrations to the dynamics of IL-6-induced signal transduction and expression of target genes in hepatocytes. The mathematical model consists of coupled ordinary differential equations (ODE) and the model parameters were estimated by a maximum likelihood approach, whereas identifiability of the dynamic model parameters was ensured by the Profile Likelihood. Using model simulations coupled with experimental validation we could optimize the long-term impact of the JAK-inhibitor Ruxolitinib, a therapeutic compound that is quickly metabolized. Model-predicted doses and timing of treatments helps to improve the reduction of inflammatory APP gene expression in primary mouse hepatocytes close to levels observed during regenerative conditions. The concept of improved efficacy of the inhibitor through multiple treatments at optimized time intervals was confirmed in primary human hepatocytes. Thus, combining quantitative data generation with mathematical modeling suggests that repetitive treatment with Ruxolitinib is required to effectively target excessive inflammatory responses without exceeding doses recommended by the clinical guidelines.

A Systematic Mapping on the Learning Analytics Field and Its Analysis in the Massive Open Online Courses Context

ERIC Educational Resources Information Center

Moissa, Barbara; Gasparini, Isabela; Kemczinski, Avanilde

2015-01-01

Learning Analytics (LA) is a field that aims to optimize learning through the study of dynamical processes occurring in the students' context. It covers the measurement, collection, analysis and reporting of data about students and their contexts. This study aims at surveying existing research on LA to identify approaches, topics, and needs for…

Context recognition and situation assessment in autonomous mobile robots

NASA Astrophysics Data System (ADS)

Yavnai, Arie

1993-05-01

The capability to recognize the operating context and to assess the situation in real-time is needed, if a high functionality autonomous mobile robot has to react properly and effectively to continuously changing situations and events, either external or internal, while the robot is performing its assigned tasks. A new approach and architecture for context recognition and situation assessment module (CORSA) is presented in this paper. CORSA is a multi-level information processing module which consists of adaptive decision and classification algorithms. It performs dynamic mapping from the data space to the context space, and dynamically decides on the context class. Learning mechanism is employed to update the decision variables so as to minimize the probability of misclassification. CORSA is embedded within the Mission Manager module of the intelligent autonomous hyper-controller (IAHC) of the mobile robot. The information regarding operating context, events and situation is then communicated to other modules of the IAHC where it is used to: (a) select the appropriate action strategy; (b) support the processes to arbitration and conflict resolution between reflexive behaviors and reasoning-driven behaviors; (c) predict future events and situations; and (d) determine criteria and priorities for planning, replanning, and decision making.

Game-based versus storyboard-based evaluations of crew support prototypes for long duration missions

NASA Astrophysics Data System (ADS)

Smets, N. J. J. M.; Abbing, M. S.; Neerincx, M. A.; Lindenberg, J.; van Oostendorp, H.

2010-03-01

The Mission Execution Crew Assistant (MECA) is developing a distributed system of electronic partners (ePartners) to support astronauts performing nominal and off- nominal actions in long duration missions. The ePartners' support should adequately deal with the dynamics of the context, operations, team and personal conditions, which will change over time substantially. Such support—with the concerning context effects—should be thoroughly tested in all stages of the development process. A major question is how to address the context effects of in-space operations for evaluations of crew support prototypes. Via game-technology, the prototype can be tested with astronauts or their representatives, immersed in the envisioned, simulated context. We investigated if a game-based evaluation better addresses the context effects by producing a more elaborate, in-depth and realistic user experience than a "classical" storyboard-based evaluation. In the game-based evaluation, the participants showed higher arousal levels where expected, a more intense feeling of spatial presence, better situation awareness, and faster performance where needed. Such an evaluation can be used as an alternative or complement of field or micro-world tests when context dynamics cannot be simulated in these last tests cost-efficiently.

Fifty-sixth Christmas Bird Count. 147. Southern Dorchester County, Md

USGS Publications Warehouse

Johnson, F.A.; Williams, B.K.; Nichols, J.D.; Hines, J.E.; Kendall, W.L.; Smith, G.W.; Caithamer, David F.

1956-01-01

Summary and Recommendations: We suggest that managers are approaching the limits of their ability to improve waterfowl harvest management, primarily because the information needed to make better decisions is being sacrificed by the current approach to setting regulations. We propose an actively adaptive management strategy in which regulatory decisions play a dominant role in reducing uncertainty about population dynamics. The proposed strategy recognizes 'value' in acquiring knowledge only to the extent that it contributes to the objective of optimizing harvests. To implement this strategy, managers will need: (1) a set of regulatory options, with possible constraints on their use; (2) quantifiable harvest management objectives; (3) a set of models that represent an array of meaningful hypotheses about the effects of regulations on populations; and (4) a measure of credibility (or likelihood) for each model, which can be updated regularly using information from waterfowl monitoring programs. Adaptive optimization is an iterative process in which the harvest-management policy converges over time to one that maximizes harvest under the most appropriate model. At each time step, an optimal regulatory decision is identified based on the state of the system and the model likelihoods. In the next time step, predicted population changes from the alternative models are compared with the actual changes provided by the monitoring program, The likelihoods are increased or decreased to the extent that predicted and actual population changes correspond. These updated likelihoods then are used in setting regulations in the next cycle and the process begins again. This iterative process produces the most informative regulations when uncertainty is prevalent and produces maximum sustainable yields as uncertainty is eliminated. We see no major obstacles to implementing this adaptive strategy, although there are a number of practical considerations. First and foremost, managers should assess the 'value' of learning. Only when there is a high degree of uncertainty about the effects of hunting regulations on population dynamics will the merit of our proposed strategy be evident. We suggest that this almost always will be true given our current understanding of the relationship between annual regulations, survival and population growth in waterfowl. Nonetheless, careful consideration should be given to formulating the set of alternative models. There is no value in distinguishing between models which differ in their mathematical formulation or biological realism, but which suggest similar harvest strategies. We suspect that 'mechanistic' models (i.e., those that attempt to capture the essence of biological processes) will make better candidates for model sets than so-called 'phenomenological' models. Assuming that all model sets include a good approximation of reality, learning rates will be dependent on the quality of monitoring programs. Fortunately, a variety of high-quality monitoring plans for many duck and goose populations of North America, when used with our adaptive approach, should provide new knowledge about population dynamics and response to hunting, and, thus, lead to improved management.