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Sample records for causal approaches needed

  1. [Causal analysis approaches in epidemiology].

    PubMed

    Dumas, O; Siroux, V; Le Moual, N; Varraso, R

    2014-02-01

    Epidemiological research is mostly based on observational studies. Whether such studies can provide evidence of causation remains discussed. Several causal analysis methods have been developed in epidemiology. This paper aims at presenting an overview of these methods: graphical models, path analysis and its extensions, and models based on the counterfactual approach, with a special emphasis on marginal structural models. Graphical approaches have been developed to allow synthetic representations of supposed causal relationships in a given problem. They serve as qualitative support in the study of causal relationships. The sufficient-component cause model has been developed to deal with the issue of multicausality raised by the emergence of chronic multifactorial diseases. Directed acyclic graphs are mostly used as a visual tool to identify possible confounding sources in a study. Structural equations models, the main extension of path analysis, combine a system of equations and a path diagram, representing a set of possible causal relationships. They allow quantifying direct and indirect effects in a general model in which several relationships can be tested simultaneously. Dynamic path analysis further takes into account the role of time. The counterfactual approach defines causality by comparing the observed event and the counterfactual event (the event that would have been observed if, contrary to the fact, the subject had received a different exposure than the one he actually received). This theoretical approach has shown limits of traditional methods to address some causality questions. In particular, in longitudinal studies, when there is time-varying confounding, classical methods (regressions) may be biased. Marginal structural models have been developed to address this issue. In conclusion, "causal models", though they were developed partly independently, are based on equivalent logical foundations. A crucial step in the application of these models is the

  2. Perturbative gravity in the causal approach

    NASA Astrophysics Data System (ADS)

    Grigore, D. R.

    2010-01-01

    Quantum theory of the gravitation in the causal approach is studied up to the second order of perturbation theory in the causal approach. We emphasize the use of cohomology methods in this framework. After describing in detail the mathematical structure of the cohomology method we apply it in three different situations: (a) the determination of the most general expression of the interaction Lagrangian; (b) the proof of gauge invariance in the second order of perturbation theory for the pure gravity system—massless and massive; (c) the investigation of the arbitrariness of the second-order chronological products compatible with renormalization principles and gauge invariance (i.e. the renormalization problem in the second order of perturbation theory). In case (a) we investigate pure gravity systems and the interaction of massless gravity with matter (described by scalars and spinors) and massless Yang-Mills fields. We obtain a difference with respect to the classical field theory due to the fact that in quantum field theory one cannot enforce the divergenceless property on the vector potential and this spoils the divergenceless property of the usual energy-momentum tensor. To correct this one needs a supplementary ghost term in the interaction Lagrangian. In all three case, the computations are more simple than by the usual methods.

  3. A copula approach to assessing Granger causality.

    PubMed

    Hu, Meng; Liang, Hualou

    2014-10-15

    In neuroscience, as in many other fields of science and engineering, it is crucial to assess the causal interactions among multivariate time series. Granger causality has been increasingly used to identify causal influence between time series based on multivariate autoregressive models. Such an approach is based on linear regression framework with implicit Gaussian assumption of model noise residuals having constant variance. As a consequence, this measure cannot detect the cause-effect relationship in high-order moments and nonlinear causality. Here, we propose an effective model-free, copula-based Granger causality measure that can be used to reveal nonlinear and high-order moment causality. We first formulate Granger causality as the log-likelihood ratio in terms of conditional distribution, and then derive an efficient estimation procedure using conditional copula. We use resampling techniques to build a baseline null-hypothesis distribution from which statistical significance can be derived. We perform a series of simulations to investigate the performance of our copula-based Granger causality, and compare its performance against other state-of-the-art techniques. Our method is finally applied to neural field potential time series recorded from visual cortex of a monkey while performing a visual illusion task.

  4. The metagenomic approach and causality in virology

    PubMed Central

    Castrignano, Silvana Beres; Nagasse-Sugahara, Teresa Keico

    2015-01-01

    Nowadays, the metagenomic approach has been a very important tool in the discovery of new viruses in environmental and biological samples. Here we discuss how these discoveries may help to elucidate the etiology of diseases and the criteria necessary to establish a causal association between a virus and a disease. PMID:25902566

  5. Causality

    NASA Astrophysics Data System (ADS)

    Pearl, Judea

    2000-03-01

    Written by one of the pre-eminent researchers in the field, this book provides a comprehensive exposition of modern analysis of causation. It shows how causality has grown from a nebulous concept into a mathematical theory with significant applications in the fields of statistics, artificial intelligence, philosophy, cognitive science, and the health and social sciences. Pearl presents a unified account of the probabilistic, manipulative, counterfactual and structural approaches to causation, and devises simple mathematical tools for analyzing the relationships between causal connections, statistical associations, actions and observations. The book will open the way for including causal analysis in the standard curriculum of statistics, artifical intelligence, business, epidemiology, social science and economics. Students in these areas will find natural models, simple identification procedures, and precise mathematical definitions of causal concepts that traditional texts have tended to evade or make unduly complicated. This book will be of interest to professionals and students in a wide variety of fields. Anyone who wishes to elucidate meaningful relationships from data, predict effects of actions and policies, assess explanations of reported events, or form theories of causal understanding and causal speech will find this book stimulating and invaluable.

  6. A General Approach to Causal Mediation Analysis

    ERIC Educational Resources Information Center

    Imai, Kosuke; Keele, Luke; Tingley, Dustin

    2010-01-01

    Traditionally in the social sciences, causal mediation analysis has been formulated, understood, and implemented within the framework of linear structural equation models. We argue and demonstrate that this is problematic for 3 reasons: the lack of a general definition of causal mediation effects independent of a particular statistical model, the…

  7. A psychological approach to learning causal networks.

    PubMed

    Zargoush, Manaf; Alemi, Farrokh; Esposito Vinzi, Vinzenzo; Vang, Jee; Kheirbek, Raya

    2014-06-01

    We examine the role of a common cognitive heuristic in unsupervised learning of Bayesian probability networks from data. Human beings perceive a larger association between causal than diagnostic relationships. This psychological principal can be used to orient the arcs within Bayesian networks by prohibiting the direction that is less predictive. The heuristic increased predictive accuracy by an average of 0.51 % percent, a small amount. It also increased total agreement between different network learning algorithms (Max Spanning Tree, Taboo, EQ, SopLeq, and Taboo Order) by 25 %. Prior to use of the heuristic, the multiple raters Kappa between the algorithms was 0.60 (95 % confidence interval, CI, from 0.53 to 0.67) indicating moderate agreement among the networks learned through different algorithms. After the use of the heuristic, the multiple raters Kappa was 0.85 (95 % CI from 0.78 to 0.92). There was a statistically significant increase in agreement between the five algorithms (alpha < 0.05). These data suggest that the heuristic increased agreement between networks learned through use of different algorithms, without loss of predictive accuracy. Additional research is needed to see if findings persist in other data sets and to explain why a heuristic used by humans could improve construct validity of mathematical algorithms.

  8. New approaches to establish genetic causality.

    PubMed

    McNally, Elizabeth M; George, Alfred L

    2015-10-01

    Cardiovascular medicine has evolved rapidly in the era of genomics with many diseases having primary genetic origins becoming the subject of intense investigation. The resulting avalanche of information on the molecular causes of these disorders has prompted a revolution in our understanding of disease mechanisms and provided new avenues for diagnoses. At the heart of this revolution is the need to correctly classify genetic variants discovered during the course of research or reported from clinical genetic testing. This review will address current concepts related to establishing the cause and effect relationship between genomic variants and heart diseases. A survey of general approaches used for functional annotation of variants will also be presented.

  9. Subjective spacetime derived from a causal histories approach

    NASA Astrophysics Data System (ADS)

    Gunji, Yukio-Pegio; Haruna, Taichi; Uragami, Daisuke; Nishikawa, Asaki

    2009-10-01

    The internal description of spacetime can reveal ambiguity regarding an observer’s perception of the present, where an observer can refer to the present as if he were outside spacetime while actually existing in the present. This ambiguity can be expressed as the compatibility between an element and a set, and is here called a/{a}-compatibility. We describe a causal set as a lattice and a causal history as a quotient lattice, and implement the a/{a}-compatibility in the framework of a causal histories approach. This leads to a perpetual change of a pair of causal set and causal history, and can be used to describe subjective spacetime including the déjà vu experience and/or schizophrenic time.

  10. A Complex Systems Approach to Causal Discovery in Psychiatry.

    PubMed

    Saxe, Glenn N; Statnikov, Alexander; Fenyo, David; Ren, Jiwen; Li, Zhiguo; Prasad, Meera; Wall, Dennis; Bergman, Nora; Briggs, Ernestine C; Aliferis, Constantin

    2016-01-01

    Conventional research methodologies and data analytic approaches in psychiatric research are unable to reliably infer causal relations without experimental designs, or to make inferences about the functional properties of the complex systems in which psychiatric disorders are embedded. This article describes a series of studies to validate a novel hybrid computational approach--the Complex Systems-Causal Network (CS-CN) method-designed to integrate causal discovery within a complex systems framework for psychiatric research. The CS-CN method was first applied to an existing dataset on psychopathology in 163 children hospitalized with injuries (validation study). Next, it was applied to a much larger dataset of traumatized children (replication study). Finally, the CS-CN method was applied in a controlled experiment using a 'gold standard' dataset for causal discovery and compared with other methods for accurately detecting causal variables (resimulation controlled experiment). The CS-CN method successfully detected a causal network of 111 variables and 167 bivariate relations in the initial validation study. This causal network had well-defined adaptive properties and a set of variables was found that disproportionally contributed to these properties. Modeling the removal of these variables resulted in significant loss of adaptive properties. The CS-CN method was successfully applied in the replication study and performed better than traditional statistical methods, and similarly to state-of-the-art causal discovery algorithms in the causal detection experiment. The CS-CN method was validated, replicated, and yielded both novel and previously validated findings related to risk factors and potential treatments of psychiatric disorders. The novel approach yields both fine-grain (micro) and high-level (macro) insights and thus represents a promising approach for complex systems-oriented research in psychiatry.

  11. 'Mendelian randomization': an approach for exploring causal relations in epidemiology.

    PubMed

    Gupta, V; Walia, G K; Sachdeva, M P

    2017-04-01

    To assess the current status of Mendelian randomization (MR) approach in effectively influencing the observational epidemiology for examining causal relationships. Narrative review on studies related to principle, strengths, limitations, and achievements of MR approach. Observational epidemiological studies have repeatedly produced several beneficiary associations which were discarded when tested by standard randomized controlled trials (RCTs). The technique which is more feasible, highly similar to RCTs, and has the potential to establish a causal relationship between modifiable exposures and disease outcomes is known as MR. The technique uses genetic variants related to modifiable traits/exposures as instruments for detecting causal and directional associations with outcomes. In the last decade, the approach of MR has methodologically developed and progressed to a stage of high acceptance among the epidemiologists and is gradually expanding the landscape of causal relationships in non-communicable chronic diseases. Copyright © 2016 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

  12. A Complex Systems Approach to Causal Discovery in Psychiatry

    PubMed Central

    Saxe, Glenn N.; Statnikov, Alexander; Fenyo, David; Ren, Jiwen; Li, Zhiguo; Prasad, Meera; Wall, Dennis; Bergman, Nora; Briggs, Ernestine C.; Aliferis, Constantin

    2016-01-01

    Conventional research methodologies and data analytic approaches in psychiatric research are unable to reliably infer causal relations without experimental designs, or to make inferences about the functional properties of the complex systems in which psychiatric disorders are embedded. This article describes a series of studies to validate a novel hybrid computational approach–the Complex Systems-Causal Network (CS-CN) method–designed to integrate causal discovery within a complex systems framework for psychiatric research. The CS-CN method was first applied to an existing dataset on psychopathology in 163 children hospitalized with injuries (validation study). Next, it was applied to a much larger dataset of traumatized children (replication study). Finally, the CS-CN method was applied in a controlled experiment using a ‘gold standard’ dataset for causal discovery and compared with other methods for accurately detecting causal variables (resimulation controlled experiment). The CS-CN method successfully detected a causal network of 111 variables and 167 bivariate relations in the initial validation study. This causal network had well-defined adaptive properties and a set of variables was found that disproportionally contributed to these properties. Modeling the removal of these variables resulted in significant loss of adaptive properties. The CS-CN method was successfully applied in the replication study and performed better than traditional statistical methods, and similarly to state-of-the-art causal discovery algorithms in the causal detection experiment. The CS-CN method was validated, replicated, and yielded both novel and previously validated findings related to risk factors and potential treatments of psychiatric disorders. The novel approach yields both fine-grain (micro) and high-level (macro) insights and thus represents a promising approach for complex systems-oriented research in psychiatry. PMID:27028297

  13. Assessing a surrogate predictive value: a causal inference approach.

    PubMed

    Alonso, Ariel; Van der Elst, Wim; Meyvisch, Paul

    2017-03-30

    Several methods have been developed for the evaluation of surrogate endpoints within the causal-inference and meta-analytic paradigms. In both paradigms, much effort has been made to assess the capacity of the surrogate to predict the causal treatment effect on the true endpoint. In the present work, the so-called surrogate predictive function (SPF) is introduced for that purpose, using potential outcomes. The relationship between the SPF and the individual causal association, a new metric of surrogacy recently proposed in the literature, is studied in detail. It is shown that the SPF, in conjunction with the individual causal association, can offer an appealing quantification of the surrogate predictive value. However, neither the distribution of the potential outcomes nor the SPF are identifiable from the data. These identifiability issues are tackled using a two-step procedure. In the first step, the region of the parametric space of the distribution of the potential outcomes, compatible with the data at hand, is geometrically characterized. Further, in a second step, a Monte Carlo approach is used to study the behavior of the SPF on the previous region. The method is illustrated using data from a clinical trial involving schizophrenic patients and a newly developed and user friendly R package Surrogate is provided to carry out the validation exercise. Copyright © 2016 John Wiley & Sons, Ltd.

  14. Gauge invariance of quantum gravity in the causal approach

    NASA Astrophysics Data System (ADS)

    Schorn, Ivo

    1997-03-01

    We investigate gauge invariance of perturbative quantum gravity without matter fields in the causal Epstein - Glaser approach. This approach uses free fields only so that all objects of the theory are mathematically well defined. The first-order graviton self-couplings are obtained from the Einstein - Hilbert Lagrangian written in terms of Goldberg variables and expanded to lowest order on the flat Minkowski background metric (linearized Einstein theory). Similar to Yang - Mills theory, gauge invariance to first order requires an additional coupling to fermionic ghost fields. For second-order tree graphs, gauge invariance generates four-graviton normalization terms, which agree exactly with the next order of the expansion of the Einstein - Hilbert Lagrangian. Gauge invariance of the ghost sector is then examined in detail. It is stressed that, despite some formal similarities, the concept of operator gauge invariance used in the causal method is different from the conventional BRS-invariance commonly used in the literature.

  15. Causality and persistence in ecological systems: a nonparametric spectral granger causality approach.

    PubMed

    Detto, Matteo; Molini, Annalisa; Katul, Gabriel; Stoy, Paul; Palmroth, Sari; Baldocchi, Dennis

    2012-04-01

    Abstract Directionality in coupling, defined as the linkage relating causes to their effects at a later time, can be used to explain the core dynamics of ecological systems by untangling direct and feedback relationships between the different components of the systems. Inferring causality from measured ecological variables sampled through time remains a formidable challenge further made difficult by the action of periodic drivers overlapping the natural dynamics of the system. Periodicity in the drivers can often mask the self-sustained oscillations originating from the autonomous dynamics. While linear and direct causal relationships are commonly addressed in the time domain, using the well-established machinery of Granger causality (G-causality), the presence of periodic forcing requires frequency-based statistics (e.g., the Fourier transform), able to distinguish coupling induced by oscillations in external drivers from genuine endogenous interactions. Recent nonparametric spectral extensions of G-causality to the frequency domain pave the way for the scale-by-scale decomposition of causality, which can improve our ability to link oscillatory behaviors of ecological networks to causal mechanisms. The performance of both spectral G-causality and its conditional extension for multivariate systems is explored in quantifying causal interactions within ecological networks. Through two case studies involving synthetic and actual time series, it is demonstrated that conditional G-causality outperforms standard G-causality in identifying causal links and their concomitant timescales.

  16. A time domain frequency-selective multivariate Granger causality approach.

    PubMed

    Leistritz, Lutz; Witte, Herbert

    2016-08-01

    The investigation of effective connectivity is one of the major topics in computational neuroscience to understand the interaction between spatially distributed neuronal units of the brain. Thus, a wide variety of methods has been developed during the last decades to investigate functional and effective connectivity in multivariate systems. Their spectrum ranges from model-based to model-free approaches with a clear separation into time and frequency range methods. We present in this simulation study a novel time domain approach based on Granger's principle of predictability, which allows frequency-selective considerations of directed interactions. It is based on a comparison of prediction errors of multivariate autoregressive models fitted to systematically modified time series. These modifications are based on signal decompositions, which enable a targeted cancellation of specific signal components with specific spectral properties. Depending on the embedded signal decomposition method, a frequency-selective or data-driven signal-adaptive Granger Causality Index may be derived.

  17. A developmental approach to learning causal models for cyber security

    NASA Astrophysics Data System (ADS)

    Mugan, Jonathan

    2013-05-01

    To keep pace with our adversaries, we must expand the scope of machine learning and reasoning to address the breadth of possible attacks. One approach is to employ an algorithm to learn a set of causal models that describes the entire cyber network and each host end node. Such a learning algorithm would run continuously on the system and monitor activity in real time. With a set of causal models, the algorithm could anticipate novel attacks, take actions to thwart them, and predict the second-order effects flood of information, and the algorithm would have to determine which streams of that flood were relevant in which situations. This paper will present the results of efforts toward the application of a developmental learning algorithm to the problem of cyber security. The algorithm is modeled on the principles of human developmental learning and is designed to allow an agent to learn about the computer system in which it resides through active exploration. Children are flexible learners who acquire knowledge by actively exploring their environment and making predictions about what they will find,1, 2 and our algorithm is inspired by the work of the developmental psychologist Jean Piaget.3 Piaget described how children construct knowledge in stages and learn new concepts on top of those they already know. Developmental learning allows our algorithm to focus on subsets of the environment that are most helpful for learning given its current knowledge. In experiments, the algorithm was able to learn the conditions for file exfiltration and use that knowledge to protect sensitive files.

  18. A Quantum Bayes Net Approach to Causal Reasoning

    NASA Astrophysics Data System (ADS)

    Trueblood, Jennifer S.; Mistry, Percy K.; Pothos, Emmanuel M.

    When individuals have little knowledge about a causal system and must make causal inferences based on vague and imperfect information, their judgments often deviate from the normative prescription of classical probability. Previously, many researchers have dealt with violations of normative rules by elaborating causal Bayesian networks through the inclusion of hidden variables. While these models often provide good accounts of data, the addition of hidden variables is often post hoc, included when a Bayes net fails to capture data. Further, Bayes nets with multiple hidden variables are often difficult to test. Rather than elaborating a Bayes net with hidden variables, we generalize the probabilistic rules of these models. The basic idea is that any classic Bayes net can be generalized to a quantum Bayes net by replacing the probabilities in the classic model with probability amplitudes in the quantum model. We discuss several predictions of quantum Bayes nets for human causal reasoning.

  19. Answering the "Why" Question in Evaluation: The Causal-Model Approach.

    ERIC Educational Resources Information Center

    Petrosino, Anthony

    2000-01-01

    Defines causal-model evaluation and uses an example from the crime prevention literature to contrast this approach with traditional evaluations. Discusses benefits and limitations of the approach, as well as other issues. (SLD)

  20. Nanoparticles in the environment: assessment using the causal diagram approach

    PubMed Central

    2012-01-01

    Nanoparticles (NPs) cause concern for health and safety as their impact on the environment and humans is not known. Relatively few studies have investigated the toxicological and environmental effects of exposure to naturally occurring NPs (NNPs) and man-made or engineered NPs (ENPs) that are known to have a wide variety of effects once taken up into an organism. A review of recent knowledge (between 2000-2010) on NP sources, and their behaviour, exposure and effects on the environment and humans was performed. An integrated approach was used to comprise available scientific information within an interdisciplinary logical framework, to identify knowledge gaps and to describe environment and health linkages for NNPs and ENPs. The causal diagram has been developed as a method to handle the complexity of issues on NP safety, from their exposure to the effects on the environment and health. It gives an overview of available scientific information starting with common sources of NPs and their interactions with various environmental processes that may pose threats to both human health and the environment. Effects of NNPs on dust cloud formation and decrease in sunlight intensity were found to be important environmental changes with direct and indirect implication in various human health problems. NNPs and ENPs exposure and their accumulation in biological matrices such as microbiota, plants and humans may result in various adverse effects. The impact of some NPs on human health by ROS generation was found to be one of the major causes to develop various diseases. A proposed cause-effects diagram for NPs is designed considering both NNPs and ENPs. It represents a valuable information package and user-friendly tool for various stakeholders including students, researchers and policy makers, to better understand and communicate on issues related to NPs. PMID:22759495

  1. Dark matter perturbations and viscosity: A causal approach

    NASA Astrophysics Data System (ADS)

    Acquaviva, Giovanni; John, Anslyn; Pénin, Aurélie

    2016-08-01

    The inclusion of dissipative effects in cosmic fluids modifies their clustering properties and could have observable effects on the formation of large-scale structures. We analyze the evolution of density perturbations of cold dark matter endowed with causal bulk viscosity. The perturbative analysis is carried out in the Newtonian approximation and the bulk viscosity is described by the causal Israel-Stewart (IS) theory. In contrast to the noncausal Eckart theory, we obtain a third-order evolution equation for the density contrast that depends on three free parameters. For certain parameter values, the density contrast and growth factor in IS mimic their behavior in Λ CDM when z ≥1 . Interestingly, and contrary to intuition, certain sets of parameters lead to an increase of the clustering.

  2. Statistical approaches for enhancing causal interpretation of the M to Y relation in mediation analysis.

    PubMed

    MacKinnon, David P; Pirlott, Angela G

    2015-02-01

    Statistical mediation methods provide valuable information about underlying mediating psychological processes, but the ability to infer that the mediator variable causes the outcome variable is more complex than widely known. Researchers have recently emphasized how violating assumptions about confounder bias severely limits causal inference of the mediator to dependent variable relation. Our article describes and addresses these limitations by drawing on new statistical developments in causal mediation analysis. We first review the assumptions underlying causal inference and discuss three ways to examine the effects of confounder bias when assumptions are violated. We then describe four approaches to address the influence of confounding variables and enhance causal inference, including comprehensive structural equation models, instrumental variable methods, principal stratification, and inverse probability weighting. Our goal is to further the adoption of statistical methods to enhance causal inference in mediation studies.

  3. Statistical Approaches for Enhancing Causal Interpretation of the M to Y Relation in Mediation Analysis

    PubMed Central

    MacKinnon, David P.; Pirlott, Angela G.

    2016-01-01

    Statistical mediation methods provide valuable information about underlying mediating psychological processes, but the ability to infer that the mediator variable causes the outcome variable is more complex than widely known. Researchers have recently emphasized how violating assumptions about confounder bias severely limits causal inference of the mediator to dependent variable relation. Our article describes and addresses these limitations by drawing on new statistical developments in causal mediation analysis. We first review the assumptions underlying causal inference and discuss three ways to examine the effects of confounder bias when assumptions are violated. We then describe four approaches to address the influence of confounding variables and enhance causal inference, including comprehensive structural equation models, instrumental variable methods, principal stratification, and inverse probability weighting. Our goal is to further the adoption of statistical methods to enhance causal inference in mediation studies. PMID:25063043

  4. A novel approach for identifying causal models of complex diseases from family data.

    PubMed

    Park, Leeyoung; Kim, Ju H

    2015-04-01

    Causal models including genetic factors are important for understanding the presentation mechanisms of complex diseases. Familial aggregation and segregation analyses based on polygenic threshold models have been the primary approach to fitting genetic models to the family data of complex diseases. In the current study, an advanced approach to obtaining appropriate causal models for complex diseases based on the sufficient component cause (SCC) model involving combinations of traditional genetics principles was proposed. The probabilities for the entire population, i.e., normal-normal, normal-disease, and disease-disease, were considered for each model for the appropriate handling of common complex diseases. The causal model in the current study included the genetic effects from single genes involving epistasis, complementary gene interactions, gene-environment interactions, and environmental effects. Bayesian inference using a Markov chain Monte Carlo algorithm (MCMC) was used to assess of the proportions of each component for a given population lifetime incidence. This approach is flexible, allowing both common and rare variants within a gene and across multiple genes. An application to schizophrenia data confirmed the complexity of the causal factors. An analysis of diabetes data demonstrated that environmental factors and gene-environment interactions are the main causal factors for type II diabetes. The proposed method is effective and useful for identifying causal models, which can accelerate the development of efficient strategies for identifying causal factors of complex diseases.

  5. A Longitudinal Study of Hong Kong Chinese University Students' Academic Causal Attributions, Self-Concept, Learning Approaches, and Their Causal Effects on Achievement.

    ERIC Educational Resources Information Center

    Yin, Lai Po

    The longitudinal changes in the causal attributions, academic self-concept, and learning approaches of 549 university students in Hong Kong were studied. Students were enrolled in two different disciplines: language/health studies (n=272) and construction/engineering (n=277). Measurements of causal dimensions, academic self-concept, learning…

  6. Renewable energy consumption and economic growth in nine OECD countries: bounds test approach and causality analysis.

    PubMed

    Hung-Pin, Lin

    2014-01-01

    The purpose of this paper is to investigate the short-run and long-run causality between renewable energy (RE) consumption and economic growth (EG) in nine OECD countries from the period between 1982 and 2011. To examine the linkage, this paper uses the autoregressive distributed lag (ARDL) bounds testing approach of cointegration test and vector error-correction models to test the causal relationship between variables. The co-integration and causal relationships are found in five countries-United States of America (USA), Japan, Germany, Italy, and United Kingdom (UK). The overall results indicate that (1) a short-run unidirectional causality runs from EG to RE in Italy and UK; (2) long-run unidirectional causalities run from RE to EG for Germany, Italy, and UK; (3) a long-run unidirectional causality runs from EG to RE in USA, and Japan; (4) both long-run and strong unidirectional causalities run from RE to EG for Germany and UK; and (5) Finally, both long-run and strong unidirectional causalities run from EG to RE in only USA. Further evidence reveals that policies for renewable energy conservation may have no impact on economic growth in France, Denmark, Portugal, and Spain.

  7. Renewable Energy Consumption and Economic Growth in Nine OECD Countries: Bounds Test Approach and Causality Analysis

    PubMed Central

    Hung-Pin, Lin

    2014-01-01

    The purpose of this paper is to investigate the short-run and long-run causality between renewable energy (RE) consumption and economic growth (EG) in nine OECD countries from the period between 1982 and 2011. To examine the linkage, this paper uses the autoregressive distributed lag (ARDL) bounds testing approach of cointegration test and vector error-correction models to test the causal relationship between variables. The co-integration and causal relationships are found in five countries—United States of America (USA), Japan, Germany, Italy, and United Kingdom (UK). The overall results indicate that (1) a short-run unidirectional causality runs from EG to RE in Italy and UK; (2) long-run unidirectional causalities run from RE to EG for Germany, Italy, and UK; (3) a long-run unidirectional causality runs from EG to RE in USA, and Japan; (4) both long-run and strong unidirectional causalities run from RE to EG for Germany and UK; and (5) Finally, both long-run and strong unidirectional causalities run from EG to RE in only USA. Further evidence reveals that policies for renewable energy conservation may have no impact on economic growth in France, Denmark, Portugal, and Spain. PMID:24558343

  8. Processing of positive-causal and negative-causal coherence relations in primary school children and adults: a test of the cumulative cognitive complexity approach in German.

    PubMed

    Knoepke, Julia; Richter, Tobias; Isberner, Maj-Britt; Naumann, Johannes; Neeb, Yvonne; Weinert, Sabine

    2017-03-01

    Establishing local coherence relations is central to text comprehension. Positive-causal coherence relations link a cause and its consequence, whereas negative-causal coherence relations add a contrastive meaning (negation) to the causal link. According to the cumulative cognitive complexity approach, negative-causal coherence relations are cognitively more complex than positive-causal ones. Therefore, they require greater cognitive effort during text comprehension and are acquired later in language development. The present cross-sectional study tested these predictions for German primary school children from Grades 1 to 4 and adults in reading and listening comprehension. Accuracy data in a semantic verification task support the predictions of the cumulative cognitive complexity approach. Negative-causal coherence relations are cognitively more demanding than positive-causal ones. Moreover, our findings indicate that children's comprehension of negative-causal coherence relations continues to develop throughout the course of primary school. Findings are discussed with respect to the generalizability of the cumulative cognitive complexity approach to German.

  9. Do trend extraction approaches affect causality detection in climate change studies?

    NASA Astrophysics Data System (ADS)

    Huang, Xu; Hassani, Hossein; Ghodsi, Mansi; Mukherjee, Zinnia; Gupta, Rangan

    2017-03-01

    Various scientific studies have investigated the causal link between solar activity (SS) and the earth's temperature (GT). Results from literature indicate that both the detected structural breaks and existing trend have significant effects on the causality detection outcomes. In this paper, we make a contribution to this literature by evaluating and comparing seven trend extraction methods covering various aspects of trend extraction studies to date. In addition, we extend previous work by using Convergent Cross Mapping (CCM) - an advanced non-parametric causality detection technique to provide evidence on the effect of existing trend in global temperature on the causality detection outcome. This paper illustrates the use of a method to find the most reliable trend extraction approach for data preprocessing, as well as provides detailed analyses of the causality detection of each component by this approach to achieve a better understanding of the causal link between SS and GT. Furthermore, the corresponding CCM results indicate increasing significance of causal effect from SS to GT since 1880 to recent years, which provide solid evidences that may contribute on explaining the escalating global tendency of warming up recent decades.

  10. A causal approach to the study of fertility and familism.

    PubMed

    Krishnan, V

    1990-01-01

    This paper tests, within the framework of LISREL, the causal structures of fertility using data from the 1973-74 Growth of Alberta Family Study (GAFS) of women aged 18-44 who are currently married or living common-law. Differential fertility among two groups of women classified by nativity also are examined. The women's background characteristics (e.g., age, religiosity, and education) are viewed as exogenous variables. The endogenous variables are familism and expected family size; familism is designated as an intermediate variable in the model, linking demographic and socioeconomic (including cultural) factors to fertility, The results indicate that familism acts as an important variable explaining fertility, particularly, among foreign-born women. The study confirms and extends earlier research findings that religiosity and education influence couples' fertility, the former positively and the latter negatively.

  11. Population metrics for suicide events: A causal inference approach.

    PubMed

    He, Hua; Lu, Naiji; Stephens, Brady; Xia, Yinglin; Bossarte, Robert M; Kane, Cathleen P; Tang, Wan; Tu, Xin M

    2017-01-01

    Large-scale public health prevention initiatives and interventions are a very important component to current public health strategies. But evaluating effects of such large-scale prevention/intervention faces a lot of challenges due to confounding effects and heterogeneity of study population. In this paper, we will develop metrics to assess the risk for suicide events based on causal inference framework when the study population is heterogeneous. The proposed metrics deal with the confounding effect by first estimating the risk of suicide events within each of the risk levels, number of prior attempts, and then taking a weighted sum of the conditional probabilities. The metrics provide unbiased estimates of the risk of suicide events. Simulation studies and a real data example will be used to demonstrate the proposed metrics.

  12. Causal chain analysis and root causes: the GIWA approach.

    PubMed

    Belausteguigoitia, Juan Carlos

    2004-02-01

    The Global International Waters Assessment (GIWA) was created to help develop a priority setting mechanism for actions in international waters. Apart from assessing the severity of environmental problems in ecosystems, the GIWA's task is to analyze potential policy actions that could solve or mitigate these problems. Given the complex nature of the problems, understanding their root causes is essential to develop effective solutions. The GIWA provides a framework to analyze these causes, which is based on identifying the factors that shape human behavior in relation to the use (direct or indirect) of aquatic resources. Two sets of factors are analyzed. The first one consists of social coordination mechanisms (institutions). Faults in these mechanisms lead to wasteful use of resources. The second consists of factors that do not cause wasteful use of resources per se (poverty, trade, demographic growth, technology), but expose and magnify the faults of the first group of factors. The picture that comes out is that diagnosing simple generic causes, e.g. poverty or trade, without analyzing the case specific ways in which the root causes act and interact to degrade the environment, will likely ignore important links that may put the effectiveness of the recommended policies at risk. A summary of the causal chain analysis for the Colorado River Delta is provided as an example.

  13. Sophisticated Merging Over Random Partitions: A Scalable and Robust Causal Discovery Approach.

    PubMed

    Cai, Ruichu; Zhang, Zhenjie; Hao, Zhifeng; Winslett, Marianne

    2017-08-24

    Scalable causal discovery is an essential technology to a wide spectrum of applications, including biomedical studies and social network evolution analysis. To tackle the difficulty of high dimensionality, a number of solutions are proposed in the literature, generally dividing the original variable domain into smaller subdomains by computation intensive partitioning strategies. These approaches usually suffer significant structural errors when the partitioning strategies fail to recognize true causal edges across the output subdomains. Such a structural error accumulates quickly with the growing depth of recursive partitioning, due to the lack of correction mechanism over causally connected variables when they are wrongly divided into two subdomains, finally jeopardizing the robustness of the integrated results. This paper proposes a completely different strategy to solve the problem, powered by a lightweight random partitioning scheme together with a carefully designed merging algorithm over results from the random partitions. Based on the randomness properties of the partitioning scheme, we design a suite of tricks for the merging algorithm, in order to support propagation-based significance enhancement, maximal acyclic subgraph causal ordering, and order-sensitive redundancy elimination. Theoretical studies as well as empirical evaluations verify the genericity, effectiveness, and scalability of our proposal on both simulated and real-world causal structures when the scheme is used in combination with a variety of causal solvers known effective on smaller domains.

  14. Mendelian Randomization as an Approach to Assess Causality Using Observational Data.

    PubMed

    Sekula, Peggy; Del Greco M, Fabiola; Pattaro, Cristian; Köttgen, Anna

    2016-11-01

    Mendelian randomization refers to an analytic approach to assess the causality of an observed association between a modifiable exposure or risk factor and a clinically relevant outcome. It presents a valuable tool, especially when randomized controlled trials to examine causality are not feasible and observational studies provide biased associations because of confounding or reverse causality. These issues are addressed by using genetic variants as instrumental variables for the tested exposure: the alleles of this exposure-associated genetic variant are randomly allocated and not subject to reverse causation. This, together with the wide availability of published genetic associations to screen for suitable genetic instrumental variables make Mendelian randomization a time- and cost-efficient approach and contribute to its increasing popularity for assessing and screening for potentially causal associations. An observed association between the genetic instrumental variable and the outcome supports the hypothesis that the exposure in question is causally related to the outcome. This review provides an overview of the Mendelian randomization method, addresses assumptions and implications, and includes illustrative examples. We also discuss special issues in nephrology, such as inverse risk factor associations in advanced disease, and outline opportunities to design Mendelian randomization studies around kidney function and disease. Copyright © 2016 by the American Society of Nephrology.

  15. Causal inference in public health.

    PubMed

    Glass, Thomas A; Goodman, Steven N; Hernán, Miguel A; Samet, Jonathan M

    2013-01-01

    Causal inference has a central role in public health; the determination that an association is causal indicates the possibility for intervention. We review and comment on the long-used guidelines for interpreting evidence as supporting a causal association and contrast them with the potential outcomes framework that encourages thinking in terms of causes that are interventions. We argue that in public health this framework is more suitable, providing an estimate of an action's consequences rather than the less precise notion of a risk factor's causal effect. A variety of modern statistical methods adopt this approach. When an intervention cannot be specified, causal relations can still exist, but how to intervene to change the outcome will be unclear. In application, the often-complex structure of causal processes needs to be acknowledged and appropriate data collected to study them. These newer approaches need to be brought to bear on the increasingly complex public health challenges of our globalized world.

  16. Campbell and Rubin: A Primer and Comparison of Their Approaches to Causal Inference in Field Settings

    ERIC Educational Resources Information Center

    Shadish, William R.

    2010-01-01

    This article compares Donald Campbell's and Donald Rubin's work on causal inference in field settings on issues of epistemology, theories of cause and effect, methodology, statistics, generalization, and terminology. The two approaches are quite different but compatible, differing mostly in matters of bandwidth versus fidelity. Campbell's work…

  17. Campbell and Rubin: A Primer and Comparison of Their Approaches to Causal Inference in Field Settings

    ERIC Educational Resources Information Center

    Shadish, William R.

    2010-01-01

    This article compares Donald Campbell's and Donald Rubin's work on causal inference in field settings on issues of epistemology, theories of cause and effect, methodology, statistics, generalization, and terminology. The two approaches are quite different but compatible, differing mostly in matters of bandwidth versus fidelity. Campbell's work…

  18. Spatial-temporal causal modeling: a data centric approach to climate change attribution (Invited)

    NASA Astrophysics Data System (ADS)

    Lozano, A. C.

    2010-12-01

    Attribution of climate change has been predominantly based on simulations using physical climate models. These approaches rely heavily on the employed models and are thus subject to their shortcomings. Given the physical models’ limitations in describing the complex system of climate, we propose an alternative approach to climate change attribution that is data centric in the sense that it relies on actual measurements of climate variables and human and natural forcing factors. We present a novel class of methods to infer causality from spatial-temporal data, as well as a procedure to incorporate extreme value modeling into our methodology in order to address the attribution of extreme climate events. We develop a collection of causal modeling methods using spatio-temporal data that combine graphical modeling techniques with the notion of Granger causality. “Granger causality” is an operational definition of causality from econometrics, which is based on the premise that if a variable causally affects another, then the past values of the former should be helpful in predicting the future values of the latter. In its basic version, our methodology makes use of the spatial relationship between the various data points, but treats each location as being identically distributed and builds a unique causal graph that is common to all locations. A more flexible framework is then proposed that is less restrictive than having a single causal graph common to all locations, while avoiding the brittleness due to data scarcity that might arise if one were to independently learn a different graph for each location. The solution we propose can be viewed as finding a middle ground by partitioning the locations into subsets that share the same causal structures and pooling the observations from all the time series belonging to the same subset in order to learn more robust causal graphs. More precisely, we make use of relationships between locations (e.g. neighboring

  19. Causal nexus between energy consumption and carbon dioxide emission for Malaysia using maximum entropy bootstrap approach.

    PubMed

    Gul, Sehrish; Zou, Xiang; Hassan, Che Hashim; Azam, Muhammad; Zaman, Khalid

    2015-12-01

    This study investigates the relationship between energy consumption and carbon dioxide emission in the causal framework, as the direction of causality remains has a significant policy implication for developed and developing countries. The study employed maximum entropy bootstrap (Meboot) approach to examine the causal nexus between energy consumption and carbon dioxide emission using bivariate as well as multivariate framework for Malaysia, over a period of 1975-2013. This is a unified approach without requiring the use of conventional techniques based on asymptotical theory such as testing for possible unit root and cointegration. In addition, it can be applied in the presence of non-stationary of any type including structural breaks without any type of data transformation to achieve stationary. Thus, it provides more reliable and robust inferences which are insensitive to time span as well as lag length used. The empirical results show that there is a unidirectional causality running from energy consumption to carbon emission both in the bivariate model and multivariate framework, while controlling for broad money supply and population density. The results indicate that Malaysia is an energy-dependent country and hence energy is stimulus to carbon emissions.

  20. The Optimal Treatment Approach to Needs Assessment.

    ERIC Educational Resources Information Center

    Cox, Gary B.; And Others

    1979-01-01

    The Optimal Treatment approach to needs assessment consists of comparing the most desirable set of services for a client with the services actually received. Discrepancies due to unavailable resources are noted and aggregated across clients. Advantages and disadvantages of this and other needs assessment procedures are considered. (Author/RL)

  1. Causal inference as an emerging statistical approach in neurology: an example for epilepsy in the elderly.

    PubMed

    Moura, Lidia Mvr; Westover, M Brandon; Kwasnik, David; Cole, Andrew J; Hsu, John

    2017-01-01

    The elderly population faces an increasing number of cases of chronic neurological conditions, such as epilepsy and Alzheimer's disease. Because the elderly with epilepsy are commonly excluded from randomized controlled clinical trials, there are few rigorous studies to guide clinical practice. When the elderly are eligible for trials, they either rarely participate or frequently have poor adherence to therapy, thus limiting both generalizability and validity. In contrast, large observational data sets are increasingly available, but are susceptible to bias when using common analytic approaches. Recent developments in causal inference-analytic approaches also introduce the possibility of emulating randomized controlled trials to yield valid estimates. We provide a practical example of the application of the principles of causal inference to a large observational data set of patients with epilepsy. This review also provides a framework for comparative-effectiveness research in chronic neurological conditions.

  2. Causal inference as an emerging statistical approach in neurology: an example for epilepsy in the elderly

    PubMed Central

    Moura, Lidia MVR; Westover, M Brandon; Kwasnik, David; Cole, Andrew J; Hsu, John

    2017-01-01

    The elderly population faces an increasing number of cases of chronic neurological conditions, such as epilepsy and Alzheimer’s disease. Because the elderly with epilepsy are commonly excluded from randomized controlled clinical trials, there are few rigorous studies to guide clinical practice. When the elderly are eligible for trials, they either rarely participate or frequently have poor adherence to therapy, thus limiting both generalizability and validity. In contrast, large observational data sets are increasingly available, but are susceptible to bias when using common analytic approaches. Recent developments in causal inference-analytic approaches also introduce the possibility of emulating randomized controlled trials to yield valid estimates. We provide a practical example of the application of the principles of causal inference to a large observational data set of patients with epilepsy. This review also provides a framework for comparative-effectiveness research in chronic neurological conditions. PMID:28115873

  3. The Reactive-Causal Architecture: Introducing an Emotion Model along with Theories of Needs

    NASA Astrophysics Data System (ADS)

    Aydin, Ali Orhan; Orgun, Mehmet Ali

    In the entertainment application area, one of the major aims is to develop believable agents. To achieve this aim, agents should be highly autonomous, situated, flexible, and display affect. The Reactive-Causal Architecture (ReCau) is proposed to simulate these core attributes. In its current form, ReCau cannot explain the effects of emotions on intelligent behaviour. This study aims is to further improve the emotion model of ReCau to explain the effects of emotions on intelligent behaviour. This improvement allows ReCau to be emotional to support the development of believable agents.

  4. Trajectories and causal phase-space approach to relativistic quantum mechanics

    SciTech Connect

    Holland, P.R.; Kyprianidis, A.; Vigier, J.P.

    1987-05-01

    The authors analyze phase-space approaches to relativistic quantum mechanics from the viewpoint of the causal interpretation. In particular, they discuss the canonical phase space associated with stochastic quantization, its relation to Hilbert space, and the Wigner-Moyal formalism. They then consider the nature of Feynman paths, and the problem of nonlocality, and conclude that a perfectly consistent relativistically covariant interpretation of quantum mechanics which retains the notion of particle trajectory is possible.

  5. Causal heterogeneity in attention-deficit/hyperactivity disorder: do we need neuropsychologically impaired subtypes?

    PubMed

    Nigg, Joel T; Willcutt, Erik G; Doyle, Alysa E; Sonuga-Barke, Edmund J S

    2005-06-01

    Before assigning full etiologic validity to a psycopathologic disorder, disease theory suggests that a causal dysfunction in a mechanism within the affect individuals must be identified. Existing theories on attention-deficit/hyperactivity disorder (ADHD) suggest such dysfunctions in cognitive, neuropsychological, or motivational processes in the child. To date, researchers have tested these theories by comparing groups with DSM-defined ADHD to children without ADHD. Using executive functioning as an illustration of an issue that exists across all such theories, this article describes substantial overlaps in the group performance data. Thus only a subgroup may have executive deficits. Noted are other supportive data suggesting multiple pathways to ADHD. The article explores implications and recommends that future theory and research give more consideration to the probability that only a subset of behaviorally defined children will have a deficit in a given neurocognitive mechanism believed to contribute to the disorder. Creation of a provisional set of criteria in DSM-V for defining an "executive deficit type" could stimulate research to validate the first etiologic subtype of ADHD and spur the development of more sophisticated causal models, which in the longer term may give clinicians ways to target and tailor treatments.

  6. Many replications do not causal inferences make: the need for critical replications to test competing explanations of nonrandomized studies.

    PubMed

    Larzelere, Robert E; Cox, Ronald B; Swindle, Taren M

    2015-05-01

    Although direct replications are ideal for randomized studies, areas of psychological science that lack randomized studies should incorporate Rosenbaum's (2001) distinction between trivial and nontrivial replications, relabeled herein as exact and critical replications. If exact replications merely repeat systematic biases, they cannot enhance cumulative progress in psychological science. In contrast, critical replications distinguish between competing explanations by using crucial tests to clarify the underlying causal influences. We illustrate this potential with examples from research on corrective actions by professionals (e.g., psychotherapy, Ritalin) and parents (e.g., spanking, homework assistance), where critical replications are needed to overcome the inherent selection bias due to corrective actions being triggered by children's symptoms. Purported causal effects must first prove to be replicable after plausible confounds such as selection bias are eliminated. Subsequent critical replications can then compare plausible alternative explanations of the average unbiased causal effect and of individual differences in those effects. We conclude that this type of systematic sequencing of critical replications has more potential for making the kinds of discriminations typical of cumulative progress in science than do exact replications alone, especially in areas where randomized studies are unavailable.

  7. Spectral properties of a double-quantum-dot structure: A causal Green's function approach

    NASA Astrophysics Data System (ADS)

    You, J. Q.; Zheng, Hou-Zhi

    1999-09-01

    Spectral properties of a double quantum dot (QD) structure are studied by a causal Green's function (GF) approach. The double QD system is modeled by an Anderson-type Hamiltonian in which both the intra- and interdot Coulomb interactions are taken into account. The GF's are derived by an equation-of-motion method and the real-space renormalization-group technique. The numerical results show that the average occupation number of electrons in the QD exhibits staircase features and the local density of states depends appreciably on the electron occupation of the dot.

  8. Combining FDI and AI approaches within causal-model-based diagnosis.

    PubMed

    Gentil, Sylviane; Montmain, Jacky; Combastel, Christophe

    2004-10-01

    This paper presents a model-based diagnostic method designed in the context of process supervision. It has been inspired by both artificial intelligence and control theory. AI contributes tools for qualitative modeling, including causal modeling, whose aim is to split a complex process into elementary submodels. Control theory, within the framework of fault detection and isolation (FDI), provides numerical models for generating and testing residuals, and for taking into account inaccuracies in the model, unknown disturbances and noise. Consistency-based reasoning provides a logical foundation for diagnostic reasoning and clarifies fundamental assumptions, such as single fault and exoneration. The diagnostic method presented in the paper benefits from the advantages of all these approaches. Causal modeling enables the method to focus on sufficient relations for fault isolation, which avoids combinatorial explosion. Moreover, it allows the model to be modified easily without changing any aspect of the diagnostic algorithm. The numerical submodels that are used to detect inconsistency benefit from the precise quantitative analysis of the FDI approach. The FDI models are studied in order to link this method with DX component-oriented reasoning. The recursive on-line use of this algorithm is explained and the concept of local exoneration is introduced.

  9. Physician Educational Needs in Osteoporosis: An Approach to Needs Assessment.

    ERIC Educational Resources Information Center

    Lockyer, Jocelyn; Hanley, David; Fidler, Herta; Toews, John; Lysholm-Andrews, Elaine

    1998-01-01

    A literature review, focus groups (n=200), and questionnaire responses from 324 family physicians identified their learning needs related to osteoporosis. The three methods identified different learning issues, suggesting the importance of triangulation to ensure currency and relevance in continuing-education needs-assessment. (SK)

  10. Physician Educational Needs in Osteoporosis: An Approach to Needs Assessment.

    ERIC Educational Resources Information Center

    Lockyer, Jocelyn; Hanley, David; Fidler, Herta; Toews, John; Lysholm-Andrews, Elaine

    1998-01-01

    A literature review, focus groups (n=200), and questionnaire responses from 324 family physicians identified their learning needs related to osteoporosis. The three methods identified different learning issues, suggesting the importance of triangulation to ensure currency and relevance in continuing-education needs-assessment. (SK)

  11. The causal model approach to nutritional problems: an effective tool for research and action at the local level.

    PubMed

    Tonglet, R; Mudosa, M; Badashonderana, M; Beghin, I; Hennart, P

    1992-01-01

    Reported are the results of a case study from Kirotshe rural health district, Northern Kivu, Zaire, where a workshop on the causal model approach to nutrition was organized in 1987. The model has since been used in the field for research design, training of health professionals, nutrition intervention, and community development. The rationale behind this approach is reviewed, the experience accumulated from Kirotshe district is described, and the ways in which the causal model contributes to comprehensive health and nutrition care are discussed. The broad range of possible policy implications of this approach underlines its usefulness for future action.

  12. The causal model approach to nutritional problems: an effective tool for research and action at the local level.

    PubMed Central

    Tonglet, R.; Mudosa, M.; Badashonderana, M.; Beghin, I.; Hennart, P.

    1992-01-01

    Reported are the results of a case study from Kirotshe rural health district, Northern Kivu, Zaire, where a workshop on the causal model approach to nutrition was organized in 1987. The model has since been used in the field for research design, training of health professionals, nutrition intervention, and community development. The rationale behind this approach is reviewed, the experience accumulated from Kirotshe district is described, and the ways in which the causal model contributes to comprehensive health and nutrition care are discussed. The broad range of possible policy implications of this approach underlines its usefulness for future action. PMID:1486667

  13. A proxy outcome approach for causal effect in observational studies: a simulation study.

    PubMed

    Liang, Wenbin; Zhao, Yuejen; Lee, Andy H

    2014-01-01

    Known and unknown/unmeasured risk factors are the main sources of confounding effects in observational studies and can lead to false observations of elevated protective or hazardous effects. In this study, we investigate an alternative approach of analysis that is operated on field-specific knowledge rather than pure statistical assumptions. The proposed approach introduces a proxy outcome into the estimation system. A proxy outcome possesses the following characteristics: (i) the exposure of interest is not a cause for the proxy outcome; (ii) causes of the proxy outcome and the study outcome are subsets of a collection of correlated variables. Based on these two conditions, the confounding-effect-driven association between the exposure and proxy outcome can then be measured and used as a proxy estimate for the effects of unknown/unmeasured confounders on the outcome of interest. Performance of this approach is tested by a simulation study, whereby 500 different scenarios are generated, with the causal factors of a proxy outcome and a study outcome being partly overlapped under low-to-moderate correlations. The simulation results demonstrate that the conventional approach only led to a correct conclusion in 21% of the 500 scenarios, as compared to 72.2% for the alternative approach. The proposed method can be applied in observational studies in social science and health research that evaluates the health impact of behaviour and mental health problems.

  14. WWC Review of the Report "Looking beyond Enrollment: The Causal Effect of Need-Based Grants on College Access, Persistence, and Graduation." What Works Clearinghouse Single Study Review

    ERIC Educational Resources Information Center

    What Works Clearinghouse, 2014

    2014-01-01

    The 2013 study, "Looking Beyond Enrollment: The Causal Effect of Need-Based Grants on College Access, Persistence, and Graduation," examined whether eligibility for the Florida Student Access Grant (FSAG), a need-based grant for low-income students in Florida, affects college enrollment, credit accumulation, persistence over time in…

  15. Epidemiological causality.

    PubMed

    Morabia, Alfredo

    2005-01-01

    Epidemiological methods, which combine population thinking and group comparisons, can primarily identify causes of disease in populations. There is therefore a tension between our intuitive notion of a cause, which we want to be deterministic and invariant at the individual level, and the epidemiological notion of causes, which are invariant only at the population level. Epidemiologists have given heretofore a pragmatic solution to this tension. Causal inference in epidemiology consists in checking the logical coherence of a causality statement and determining whether what has been found grossly contradicts what we think we already know: how strong is the association? Is there a dose-response relationship? Does the cause precede the effect? Is the effect biologically plausible? Etc. This approach to causal inference can be traced back to the English philosophers David Hume and John Stuart Mill. On the other hand, the mode of establishing causality, devised by Jakob Henle and Robert Koch, which has been fruitful in bacteriology, requires that in every instance the effect invariably follows the cause (e.g., inoculation of Koch bacillus and tuberculosis). This is incompatible with epidemiological causality which has to deal with probabilistic effects (e.g., smoking and lung cancer), and is therefore invariant only for the population.

  16. The control outcome calibration approach for causal inference with unobserved confounding.

    PubMed

    Tchetgen Tchetgen, Eric

    2014-03-01

    Unobserved confounding can seldom be ruled out with certainty in nonexperimental studies. Negative controls are sometimes used in epidemiologic practice to detect the presence of unobserved confounding. An outcome is said to be a valid negative control variable to the extent that it is influenced by unobserved confounders of the exposure effects on the outcome in view, although not directly influenced by the exposure. Thus, a negative control outcome found to be empirically associated with the exposure after adjustment for observed confounders indicates that unobserved confounding may be present. In this paper, we go beyond the use of control outcomes to detect possible unobserved confounding and propose to use control outcomes in a simple but formal counterfactual-based approach to correct causal effect estimates for bias due to unobserved confounding. The proposed control outcome calibration approach is developed in the context of a continuous or binary outcome, and the control outcome and the exposure can be discrete or continuous. A sensitivity analysis technique is also developed, which can be used to assess the degree to which a violation of the main identifying assumption of the control outcome calibration approach might impact inference about the effect of the exposure on the outcome in view.

  17. A Systematic Approach to Educational Needs Assessment.

    ERIC Educational Resources Information Center

    Florida Univ., Gainesville. Center for Community Needs Assessment.

    The focus of this paper is on the development of a model for assessing community educational needs, referred to as the Needs Assessment Project (NAP). The model's primary purpose is to classify, organize, and assign priority to community needs, so that the educational system can assign these needs to the proper administrative unit for changes to…

  18. A conditional Granger causality model approach for group analysis in functional magnetic resonance imaging.

    PubMed

    Zhou, Zhenyu; Wang, Xunheng; Klahr, Nelson J; Liu, Wei; Arias, Diana; Liu, Hongzhi; von Deneen, Karen M; Wen, Ying; Lu, Zuhong; Xu, Dongrong; Liu, Yijun

    2011-04-01

    Granger causality model (GCM) derived from multivariate vector autoregressive models of data has been employed to identify effective connectivity in the human brain with functional magnetic resonance imaging (fMRI) and to reveal complex temporal and spatial dynamics underlying a variety of cognitive processes. In the most recent fMRI effective connectivity measures, pair-wise GCM has commonly been applied based on single-voxel values or average values from special brain areas at the group level. Although a few novel conditional GCM methods have been proposed to quantify the connections between brain areas, our study is the first to propose a viable standardized approach for group analysis of fMRI data with GCM. To compare the effectiveness of our approach with traditional pair-wise GCM models, we applied a well-established conditional GCM to preselected time series of brain regions resulting from general linear model (GLM) and group spatial kernel independent component analysis of an fMRI data set in the temporal domain. Data sets consisting of one task-related and one resting-state fMRI were used to investigate connections among brain areas with the conditional GCM method. With the GLM-detected brain activation regions in the emotion-related cortex during the block design paradigm, the conditional GCM method was proposed to study the causality of the habituation between the left amygdala and pregenual cingulate cortex during emotion processing. For the resting-state data set, it is possible to calculate not only the effective connectivity between networks but also the heterogeneity within a single network. Our results have further shown a particular interacting pattern of default mode network that can be characterized as both afferent and efferent influences on the medial prefrontal cortex and posterior cingulate cortex. These results suggest that the conditional GCM approach based on a linear multivariate vector autoregressive model can achieve greater accuracy

  19. A conditional Granger causality model approach for group analysis in functional MRI

    PubMed Central

    Zhou, Zhenyu; Wang, Xunheng; Klahr, Nelson J.; Liu, Wei; Arias, Diana; Liu, Hongzhi; von Deneen, Karen M.; Wen, Ying; Lu, Zuhong; Xu, Dongrong; Liu, Yijun

    2011-01-01

    Granger causality model (GCM) derived from multivariate vector autoregressive models of data has been employed for identifying effective connectivity in the human brain with functional MR imaging (fMRI) and to reveal complex temporal and spatial dynamics underlying a variety of cognitive processes. In the most recent fMRI effective connectivity measures, pairwise GCM has commonly been applied based on single voxel values or average values from special brain areas at the group level. Although a few novel conditional GCM methods have been proposed to quantify the connections between brain areas, our study is the first to propose a viable standardized approach for group analysis of an fMRI data with GCM. To compare the effectiveness of our approach with traditional pairwise GCM models, we applied a well-established conditional GCM to pre-selected time series of brain regions resulting from general linear model (GLM) and group spatial kernel independent component analysis (ICA) of an fMRI dataset in the temporal domain. Datasets consisting of one task-related and one resting-state fMRI were used to investigate connections among brain areas with the conditional GCM method. With the GLM detected brain activation regions in the emotion related cortex during the block design paradigm, the conditional GCM method was proposed to study the causality of the habituation between the left amygdala and pregenual cingulate cortex during emotion processing. For the resting-state dataset, it is possible to calculate not only the effective connectivity between networks but also the heterogeneity within a single network. Our results have further shown a particular interacting pattern of default mode network (DMN) that can be characterized as both afferent and efferent influences on the medial prefrontal cortex (mPFC) and posterior cingulate cortex (PCC). These results suggest that the conditional GCM approach based on a linear multivariate vector autoregressive (MVAR) model can achieve

  20. Long-Term Consequences of Early Sexual Initiation on Young Adult Health: A Causal Inference Approach

    ERIC Educational Resources Information Center

    Kugler, Kari C.; Vasilenko, Sara A.; Butera, Nicole M.; Coffman, Donna L.

    2017-01-01

    Although early sexual initiation has been linked to negative outcomes, it is unknown whether these effects are causal. In this study, we use propensity score methods to estimate the causal effect of early sexual initiation on young adult sexual risk behaviors and health outcomes using data from the National Longitudinal Study of Adolescent to…

  1. There aren't plenty more fish in the sea: a causal network approach.

    PubMed

    Nikolic, Milena; Lagnado, David A

    2015-11-01

    The current research investigated how lay representations of the causes of an environmental problem may underlie individuals' reasoning about the issue. Naïve participants completed an experiment that involved two main tasks. The causal diagram task required participants to depict the causal relations between a set of factors related to overfishing and to estimate the strength of these relations. The counterfactual task required participants to judge the effect of counterfactual suppositions based on the diagrammed factors. We explored two major questions: (1) what is the relation between individual causal models and counterfactual judgments? Consistent with previous findings (e.g., Green et al., 1998, Br. J. Soc. Psychology, 37, 415), these judgments were best explained by a combination of the strength of both direct and indirect causal paths. (2) To what extent do people use two-way causal thinking when reasoning about an environmental problem? In contrast to previous research (e.g., White, 2008, Appl. Cogn. Psychology, 22, 559), analyses based on individual causal networks revealed the presence of numerous feedback loops. The studies support the value of analysing individual causal models in contrast to consensual representations. Theoretical and practical implications are discussed in relation to causal reasoning as well as environmental psychology.

  2. Hume, Mill, Hill, and the Sui Generis Epidemiologic Approach to Causal Inference

    PubMed Central

    Morabia, Alfredo

    2013-01-01

    The epidemiologic approach to causal inference (i.e., Hill's viewpoints) consists of evaluating potential causes from the following 2, noncumulative angles: 1) established results from comparative, observational, or experimental epidemiologic studies; and 2) reviews of nonepidemiologic evidence. It does not involve statements of statistical significance. The philosophical roots of Hill's viewpoints are unknown. Superficially, they seem to descend from the ideas of Hume and Mill. Hill's viewpoints, however, use a different kind of evidence and have different purposes than do Hume's rules or Mill's system of logic. In a nutshell, Hume ignores comparative evidence central to Hill's viewpoints. Mill's logic disqualifies as invalid nonexperimental evidence, which forms the bulk of epidemiologic findings reviewed from Hill's viewpoints. The approaches by Hume and Mill cannot corroborate successful implementations of Hill's viewpoints. Besides Hume and Mill, the epidemiologic literature is clueless about a plausible, pre-1965 philosophical origin of Hill's viewpoints. Thus, Hill's viewpoints may be philosophically novel, sui generis, still waiting to be validated and justified. PMID:24071010

  3. Hume, Mill, Hill, and the sui generis epidemiologic approach to causal inference.

    PubMed

    Morabia, Alfredo

    2013-11-15

    The epidemiologic approach to causal inference (i.e., Hill's viewpoints) consists of evaluating potential causes from the following 2, noncumulative angles: 1) established results from comparative, observational, or experimental epidemiologic studies; and 2) reviews of nonepidemiologic evidence. It does not involve statements of statistical significance. The philosophical roots of Hill's viewpoints are unknown. Superficially, they seem to descend from the ideas of Hume and Mill. Hill's viewpoints, however, use a different kind of evidence and have different purposes than do Hume's rules or Mill's system of logic. In a nutshell, Hume ignores comparative evidence central to Hill's viewpoints. Mill's logic disqualifies as invalid nonexperimental evidence, which forms the bulk of epidemiologic findings reviewed from Hill's viewpoints. The approaches by Hume and Mill cannot corroborate successful implementations of Hill's viewpoints. Besides Hume and Mill, the epidemiologic literature is clueless about a plausible, pre-1965 philosophical origin of Hill's viewpoints. Thus, Hill's viewpoints may be philosophically novel, sui generis, still waiting to be validated and justified.

  4. Causal Inference in Public Health

    PubMed Central

    Glass, Thomas A.; Goodman, Steven N.; Hernán, Miguel A.; Samet, Jonathan M.

    2014-01-01

    Causal inference has a central role in public health; the determination that an association is causal indicates the possibility for intervention. We review and comment on the long-used guidelines for interpreting evidence as supporting a causal association and contrast them with the potential outcomes framework that encourages thinking in terms of causes that are interventions. We argue that in public health this framework is more suitable, providing an estimate of an action’s consequences rather than the less precise notion of a risk factor’s causal effect. A variety of modern statistical methods adopt this approach. When an intervention cannot be specified, causal relations can still exist, but how to intervene to change the outcome will be unclear. In application, the often-complex structure of causal processes needs to be acknowledged and appropriate data collected to study them. These newer approaches need to be brought to bear on the increasingly complex public health challenges of our globalized world. PMID:23297653

  5. An integrative systems genetics approach reveals potential causal genes and pathways related to obesity.

    PubMed

    Kogelman, Lisette J A; Zhernakova, Daria V; Westra, Harm-Jan; Cirera, Susanna; Fredholm, Merete; Franke, Lude; Kadarmideen, Haja N

    2015-10-20

    Obesity is a multi-factorial health problem in which genetic factors play an important role. Limited results have been obtained in single-gene studies using either genomic or transcriptomic data. RNA sequencing technology has shown its potential in gaining accurate knowledge about the transcriptome, and may reveal novel genes affecting complex diseases. Integration of genomic and transcriptomic variation (expression quantitative trait loci [eQTL] mapping) has identified causal variants that affect complex diseases. We integrated transcriptomic data from adipose tissue and genomic data from a porcine model to investigate the mechanisms involved in obesity using a systems genetics approach. Using a selective gene expression profiling approach, we selected 36 animals based on a previously created genomic Obesity Index for RNA sequencing of subcutaneous adipose tissue. Differential expression analysis was performed using the Obesity Index as a continuous variable in a linear model. eQTL mapping was then performed to integrate 60 K porcine SNP chip data with the RNA sequencing data. Results were restricted based on genome-wide significant single nucleotide polymorphisms, detected differentially expressed genes, and previously detected co-expressed gene modules. Further data integration was performed by detecting co-expression patterns among eQTLs and integration with protein data. Differential expression analysis of RNA sequencing data revealed 458 differentially expressed genes. The eQTL mapping resulted in 987 cis-eQTLs and 73 trans-eQTLs (false discovery rate < 0.05), of which the cis-eQTLs were associated with metabolic pathways. We reduced the eQTL search space by focusing on differentially expressed and co-expressed genes and disease-associated single nucleotide polymorphisms to detect obesity-related genes and pathways. Building a co-expression network using eQTLs resulted in the detection of a module strongly associated with lipid pathways. Furthermore, we

  6. The Epstein–Glaser causal approach to the light-front QED{sub 4}. II: Vacuum polarization tensor

    SciTech Connect

    Bufalo, R.; Pimentel, B.M.; Soto, D.E.

    2014-12-15

    In this work we show how to construct the one-loop vacuum polarization for light-front QED{sub 4} in the framework of the perturbative causal theory. Usually, in the canonical approach, it is considered for the fermionic propagator the so-called instantaneous term, but it is known in the literature that this term is controversial because it can be omitted by computational reasons; for instance, by compensation or vanishing by dimensional regularization. In this work we propose a solution to this paradox. First, in the Epstein–Glaser causal theory, it is shown that the fermionic propagator does not have instantaneous term, and with this propagator we calculate the one-loop vacuum polarization, from this calculation it follows the same result as those obtained by the standard approach, but without reclaiming any extra assumptions. Moreover, since the perturbative causal theory is defined in the distributional framework, we can also show the reason behind our obtaining the same result whether we consider or not the instantaneous fermionic propagator term. - Highlights: • We develop the Epstein–Glaser causal approach for light-front field theory. • We evaluate in detail the vacuum polarization at one-loop for the light-front QED. • We discuss the subtle issues of the Instantaneous part of the fermionic propagator in the light-front. • We evaluate the vacuum polarization at one-loop for the light-front QED with the Instantaneous fermionic part.

  7. Testing a Landsat-based approach for mapping disturbance causality in U.S. forests

    Treesearch

    Todd A. Schroeder; Karen G. Schleeweis; Gretchen G. Moisen; Chris Toney; Warren B. Cohen; Elizabeth A. Freeman; Zhiqiang Yang; Chengquan Huang

    2017-01-01

    In light of Earth's changing climate and growing human population, there is an urgent need to improve monitoring of natural and anthropogenic disturbanceswhich effect forests' ability to sequester carbon and provide other ecosystem services. In this study, a two-step modeling approach was used to map the type and timing of forest disturbances occurring...

  8. Special Needs Adoption: An Ecological Systems Approach

    ERIC Educational Resources Information Center

    Schweiger, Wendi K.; O'Brien, Marion

    2005-01-01

    Because of changes in legislation and policies regarding child welfare, increasing numbers of older children are being placed for adoption. Many of these children are defined as having "special needs" and include children who are at risk for physical, emotional, or behavioral problems. We use Bronfenbrenner's ecological systems theory as a…

  9. Energy planning for development - needs and approaches

    SciTech Connect

    Mubayi, V

    1981-01-01

    The capability of developing countries to carry out comprehensive national energy planning is examined. The analytical methods or models constructed for analyzing the energy system have to take into account the specific context in which they are built to address issues of interest to development planners. Issues discussed are resource development and technology research, energy equity considerations to all peoples in a nation, the pricing policy, and the balance of payments considerations. The impartance of the availability of adequate skilled personnel and training programs to impart the requisite skill necessary to carry out the planning is discussed. Various surveys were conducted to determine the training needs for energy planners in developing countries. (MCW)

  10. Comprehensive Approach Training Toolkit: Training Needs Analysis

    DTIC Science & Technology

    2013-03-01

    needs and obje ime commitme sires. solutions/operat Associates in i-media teach personnel to nteractions b ing were req d another for rlap between rom...course- Courses seware that o that can be u he materials es. A “traine and teaching n the situatio ate to learnin n, then the to pertise to cu son...Training shou . Takes place in iness focus. re are several re lligence and pro . The workshop nization. There ited. Classroom ctive at teaching be as

  11. The opportune time to invest in residential properties - Engle-Granger cointegration test and Granger causality test approach

    NASA Astrophysics Data System (ADS)

    Chee-Yin, Yip; Hock-Eam, Lim

    2014-12-01

    This paper examines using housing supply as proxy to house prices, the causal relationship on house prices among 8 states in Malaysia by applying the Engle-Granger cointegration test and Granger causality test approach. The target states are Perak, Selangor, Penang, Federal Territory of Kuala Lumpur (WPKL or Kuala Lumpur), Kedah, Negeri Sembilan, Sabah and Sarawak. The primary aim of this study is to estimate how long (in months) house prices in Perak lag behind that of Selangor, Penang and WPKL. We classify the 8 states into two categories - developed and developing states. We use Engle-Granger cointegration test and Granger causality test to examine the long run and short run equilibrium relationship among the two categories.. It is found that the causal relationship is bidirectional in Perak and Sabah, Perak and Selangor while it is unidirectional for Perak and Sarawak, Perak and Penang, Perak and WPKL. The speed of deviation adjustment is about 273%, suggesting that the pricing dynamic of Perak has a 32- month or 2 3/4- year lag behind that of WPKL, Selangor and Penang. Such information will be useful to investors, house buyers and speculators.

  12. Why tackling MRSA needs a comprehensive approach.

    PubMed

    Fairclough, Sarah J

    Methicillin-resistant Staphylococcus aureus (MRSA) causes a fifth of hospital-acquired infections and many other bacteria now show increased resistance to antibacterials. In some parts of the world, community-associated MRSA infections cause a growing number of infections (Fridkin et al, 2005). Attempts to control the spread of MRSA rely on several factors: detecting and isolating infected or colonized patients (cordon sanitaire), rational antibiotic prescribing, hand hygiene and cleanliness. Nurses are key to implementing all of these measures. This article examines the epidemiology of MRSA, as exemplifying an antibiotic-resistant bacterium, and reviews the evidence for the various interventions. A single measure alone is unlikely to eradicate MRSA from either hospitals or the community; indeed, eradicating MRSA is probably impossible. However, a comprehensive approach, including, in particular, good hand hygiene, could reduce the morbidity and mortality arising from MRSA and other hospital-acquired infections.

  13. Noninvasive Electromagnetic Source Imaging and Granger Causality Analysis: An Electrophysiological Connectome (eConnectome) Approach.

    PubMed

    Sohrabpour, Abbas; Ye, Shuai; Worrell, Gregory A; Zhang, Wenbo; He, Bin

    2016-10-11

    Combined source imaging techniques and directional connectivity analysis can provide useful information about the underlying brain networks in a noninvasive fashion. Source imaging techniques have been used successfully to either determine the source of activity or to extract source time-courses for Granger causality analysis, previously. In this work, we utilize source imaging algorithms to both find the network nodes (regions of interest) and then extract the activation time series for further Granger causality analysis. The aim of this work is to find network nodes objectively from noninvasive electromagnetic signals, extract activation timecourses and apply Granger analysis on the extracted series to study brain networks under realistic conditions.

  14. When One Model Casts Doubt on Another: A Levels-of-Analysis Approach to Causal Discounting

    ERIC Educational Resources Information Center

    Khemlani, Sangeet S.; Oppenheimer, Daniel M.

    2011-01-01

    Discounting is a phenomenon in causal reasoning in which the presence of one cause casts doubt on another. We provide a survey of the descriptive and formal models that attempt to explain the discounting process and summarize what current models do not account for and where room for improvement exists. We propose a levels-of-analysis framework…

  15. A Bayesian network approach for causal inferences in pesticide risk assessment and management

    EPA Science Inventory

    Pesticide risk assessment and management must balance societal benefits and ecosystem protection, based on quantified risks and the strength of the causal linkages between uses of the pesticide and socioeconomic and ecological endpoints of concern. A Bayesian network (BN) is a gr...

  16. Grief among Surviving Family Members of Homicide Victims: A Causal Approach.

    ERIC Educational Resources Information Center

    Sprang, M. Virginia; And Others

    1993-01-01

    Proposed causal model to delineate predictors of self-reported grief among surviving family members of homicide victims. Evaluated model using data from survey of members of "Victims of Violence" support groups. Results generally supported model and indicated that correlates of grief differed across gender-specific subgroups in terms of their…

  17. A Bayesian network approach for causal inferences in pesticide risk assessment and management

    EPA Science Inventory

    Pesticide risk assessment and management must balance societal benefits and ecosystem protection, based on quantified risks and the strength of the causal linkages between uses of the pesticide and socioeconomic and ecological endpoints of concern. A Bayesian network (BN) is a gr...

  18. From Felt Need to Actual Need: A Multi-Method Multi-Sample Approach to Needs Assessment

    ERIC Educational Resources Information Center

    Peterson, Tim O.; Peterson, Claudette M.

    2004-01-01

    This study reports on an approach for assessing managerial development needs. The approach uses multi-methods such as qualitative career plots, critical incidents, a skill rating form, and surveys to identify the critical managerial development needs for a target managerial position. In addition, it uses multi-subject groups in an effort to…

  19. Exploratory Causal Analysis in Bivariate Time Series Data

    NASA Astrophysics Data System (ADS)

    McCracken, James M.

    Many scientific disciplines rely on observational data of systems for which it is difficult (or impossible) to implement controlled experiments and data analysis techniques are required for identifying causal information and relationships directly from observational data. This need has lead to the development of many different time series causality approaches and tools including transfer entropy, convergent cross-mapping (CCM), and Granger causality statistics. In this thesis, the existing time series causality method of CCM is extended by introducing a new method called pairwise asymmetric inference (PAI). It is found that CCM may provide counter-intuitive causal inferences for simple dynamics with strong intuitive notions of causality, and the CCM causal inference can be a function of physical parameters that are seemingly unrelated to the existence of a driving relationship in the system. For example, a CCM causal inference might alternate between ''voltage drives current'' and ''current drives voltage'' as the frequency of the voltage signal is changed in a series circuit with a single resistor and inductor. PAI is introduced to address both of these limitations. Many of the current approaches in the times series causality literature are not computationally straightforward to apply, do not follow directly from assumptions of probabilistic causality, depend on assumed models for the time series generating process, or rely on embedding procedures. A new approach, called causal leaning, is introduced in this work to avoid these issues. The leaning is found to provide causal inferences that agree with intuition for both simple systems and more complicated empirical examples, including space weather data sets. The leaning may provide a clearer interpretation of the results than those from existing time series causality tools. A practicing analyst can explore the literature to find many proposals for identifying drivers and causal connections in times series data

  20. Estimation and Inference for the Causal Effect of Receiving Treatment on a Multinomial Outcome: An Alternative Approach

    PubMed Central

    Baker, Stuart G.

    2010-01-01

    SUMMARY Recently Cheng (Biometrics, 2009) proposed a model for the causal effect of receiving treatment when there is all-or-none compliance in one randomization group, with maximum likelihood estimation based on convex programming. We discuss an alternative approach that involves a model for all-or-none compliance in two randomization groups and estimation via a perfect fit or an EM algorithm for count data. We believe this approach is easier to implement, which would facilitate the reproduction of calculations. PMID:20560933

  1. The causal nexus between carbon dioxide emissions and agricultural ecosystem-an econometric approach.

    PubMed

    Asumadu-Sarkodie, Samuel; Owusu, Phebe Asantewaa

    2017-01-01

    Achieving a long-term food security and preventing hunger include a better nutrition through sustainable systems of production, distribution, and consumption. Nonetheless, the quest for an alternative to increasing global food supply to meet the growing demand has led to the use of poor agricultural practices that promote climate change. Given the contribution of the agricultural ecosystem towards greenhouse gas (GHG) emissions, this study investigated the causal nexus between carbon dioxide emissions and agricultural ecosystem by employing a data spanning from 1961 to 2012. Evidence from long-run elasticity shows that a 1 % increase in the area of rice paddy harvested will increase carbon dioxide emissions by 1.49 %, a 1 % increase in biomass-burned crop residues will increase carbon dioxide emissions by 1.00 %, a 1 % increase in cereal production will increase carbon dioxide emissions by 1.38 %, and a 1 % increase in agricultural machinery will decrease carbon dioxide emissions by 0.09 % in the long run. There was a bidirectional causality between carbon dioxide emissions, cereal production, and biomass-burned crop residues. The Granger causality shows that the agricultural ecosystem in Ghana is sensitive to climate change vulnerability.

  2. Causal relationship between malocclusion and oral muscles dysfunction: a model of approach.

    PubMed

    Saccomanno, S; Antonini, G; D'Alatri, L; D'Angelantonio, M; Fiorita, A; Deli, R

    2012-12-01

    Bad habits result in altered functions which with time can cause anomalies of the orofacial morphology. To solve these problems, orthodontic treatment can be supported by myofunctional therapy in order to recover the normal functionality of the oral muscles. The aim of this study is to assess the need to treat patients with neuromuscular disorders, from both the occlusion and the muscles condition approach in order to obtain the balance needed for the stability of treatment. A sample of 23 patients with atypical swallowing was included in this study, some of them presented thumb sucking and oral breathing. After case history collection, in order to make a correct orthodontic and functional diagnosis, correction of anomalies was carried out since they could compromise the success of the therapy (maxillary contraction, oral breathing, and short lingual fraenum). Then a different therapeutic approach was applied on the basis of the specific dental features. Both from the diagnostic and therapeutic point of view, important results were achieved especially through muscle analysis with dynamometer and surface electromyography. Orthodontic therapy, in the presence of bad habits, is not enough to solve orthodontic issues, it must be combined with a myofunctional treatment. The success of the therapy is granted only when patients and their family comply with the treatment and all factors which can prevent success of the therapy are removed.

  3. A Statistical Approach to Fine Mapping for the Identification of Potential Causal Variants Related to Bone Mineral Density.

    PubMed

    Greenbaum, Jonathan; Deng, Hong-Wen

    2017-08-01

    Although genomewide association studies (GWASs) have been able to successfully identify dozens of genetic loci associated with bone mineral density (BMD) and osteoporosis-related traits, very few of these loci have been confirmed to be causal. This is because in a given genetic region there may exist many trait-associated SNPs that are highly correlated. Although this correlation is useful for discovering novel associations, the high degree of linkage disequilibrium that persists throughout the genome presents a major challenge to discern which among these correlated variants has a direct effect on the trait. In this study we apply a recently developed Bayesian fine-mapping method, PAINTOR, to determine the SNPs that have the highest probability of causality for femoral neck (FNK) BMD and lumbar spine (LS) BMD. The advantage of this method is that it allows for the incorporation of information about GWAS summary statistics, linkage disequilibrium, and functional annotations to calculate a posterior probability of causality for SNPs across all loci of interest. We present a list of the top 10 candidate SNPs for each BMD trait to be followed up in future functional validation experiments. The SNPs rs2566752 (WLS) and rs436792 (ZNF621 and CTNNB1) are particularly noteworthy because they have more than 90% probability to be causal for both FNK and LS BMD. Using this statistical fine-mapping approach we expect to gain a better understanding of the genetic determinants contributing to BMD at multiple skeletal sites. © 2017 American Society for Bone and Mineral Research. © 2017 American Society for Bone and Mineral Research.

  4. A Causal, Data-driven Approach to Modeling the Kepler Data

    NASA Astrophysics Data System (ADS)

    Wang, Dun; Hogg, David W.; Foreman-Mackey, Daniel; Schölkopf, Bernhard

    2016-09-01

    Astronomical observations are affected by several kinds of noise, each with its own causal source; there is photon noise, stochastic source variability, and residuals coming from imperfect calibration of the detector or telescope. The precision of NASA Kepler photometry for exoplanet science—the most precise photometric measurements of stars ever made—appears to be limited by unknown or untracked variations in spacecraft pointing and temperature, and unmodeled stellar variability. Here, we present the causal pixel model (CPM) for Kepler data, a data-driven model intended to capture variability but preserve transit signals. The CPM works at the pixel level so that it can capture very fine-grained information about the variation of the spacecraft. The CPM models the systematic effects in the time series of a pixel using the pixels of many other stars and the assumption that any shared signal in these causally disconnected light curves is caused by instrumental effects. In addition, we use the target star’s future and past (autoregression). By appropriately separating, for each data point, the data into training and test sets, we ensure that information about any transit will be perfectly isolated from the model. The method has four tuning parameters—the number of predictor stars or pixels, the autoregressive window size, and two L2-regularization amplitudes for model components, which we set by cross-validation. We determine values for tuning parameters that works well for most of the stars and apply the method to a corresponding set of target stars. We find that CPM can consistently produce low-noise light curves. In this paper, we demonstrate that pixel-level de-trending is possible while retaining transit signals, and we think that methods like CPM are generally applicable and might be useful for K2, TESS, etc., where the data are not clean postage stamps like Kepler.

  5. Door-to-Needle Delays in Minor Stroke: A Causal Inference Approach.

    PubMed

    Rostanski, Sara K; Shahn, Zachary; Elkind, Mitchell S V; Liberman, Ava L; Marshall, Randolph S; Stillman, Joshua I; Williams, Olajide; Willey, Joshua Z

    2017-07-01

    Thrombolysis rates among minor stroke (MS) patients are increasing because of increased recognition of disability in this group and guideline changes regarding treatment indications. We examined the association of delays in door-to-needle (DTN) time with stroke severity. We performed a retrospective analysis of all stroke patients who received intravenous tissue-type plasminogen activator in our emergency department between July 1, 2011, and February 29, 2016. Baseline characteristics and DTN were compared between MS (National Institutes of Health Stroke Scale score ≤5) and nonminor strokes (National Institutes of Health Stroke Scale score >5). We applied causal inference methodology to estimate the magnitude and mechanisms of the causal effect of stroke severity on DTN. Of 315 patients, 133 patients (42.2%) had National Institutes of Health Stroke Scale score ≤5. Median DTN was longer in MS than nonminor strokes (58 versus 53 minutes; P=0.01); fewer MS patients had DTN ≤45 minutes (19.5% versus 32.4%; P=0.01). MS patients were less likely to use emergency medical services (EMS; 62.6% versus 89.6%, P<0.01) and to receive EMS prenotification (43.9% versus 72.4%; P<0.01). Causal analyses estimated MS increased average DTN by 6 minutes, partly through mode of arrival. EMS prenotification decreased average DTN by 10 minutes in MS patients. MS had longer DTN times, an effect partly explained by patterns of EMS prenotification. Interventions to improve EMS recognition of MS may accelerate care. © 2017 American Heart Association, Inc.

  6. Causal Discovery of Dynamic Systems

    ERIC Educational Resources Information Center

    Voortman, Mark

    2010-01-01

    Recently, several philosophical and computational approaches to causality have used an interventionist framework to clarify the concept of causality [Spirtes et al., 2000, Pearl, 2000, Woodward, 2005]. The characteristic feature of the interventionist approach is that causal models are potentially useful in predicting the effects of manipulations.…

  7. Causal Discovery of Dynamic Systems

    ERIC Educational Resources Information Center

    Voortman, Mark

    2010-01-01

    Recently, several philosophical and computational approaches to causality have used an interventionist framework to clarify the concept of causality [Spirtes et al., 2000, Pearl, 2000, Woodward, 2005]. The characteristic feature of the interventionist approach is that causal models are potentially useful in predicting the effects of manipulations.…

  8. Causality and Composite Structure

    SciTech Connect

    Joglekar, Satish D.

    2007-10-03

    In this talk, we discuss the question of whether a composite structure of elementary particles, with a length scale 1/{lambda}, can leave observable effects of non-locality and causality violation at higher energies (but {<=}{lambda}); employing a model-independent approach based on Bogoliubov-Shirkov formulation of causality. We formulate a condition which must be fulfilled for the derived theory to be causal, if the fundamental theory is so; and analyze it to exhibit possibilities which fulfil and which violate the condition. We comment on how causality violating amplitudes can arise.

  9. The need for transparency and reproducibility in documenting values for regulatory decision making and evaluating causality: The example of formaldehyde.

    PubMed

    Van Landingham, Cynthia; Mundt, Kenneth A; Allen, Bruce C; Gentry, P Robinan

    2016-11-01

    Reproducibility and transparency in scientific reporting is paramount to advancing science and providing the foundation required for sound regulation. Recent examples demonstrate that pivotal scientific findings cannot be replicated, due to poor documentation or methodological bias, sparking debate across scientific and regulatory communities. However, there is general agreement that improvements in communicating and documenting research and risk assessment methods are needed. In the case of formaldehyde, the peer-review conducted by a National Academy of Sciences (NAS) Committee questioned the approaches used by the Integrated Risk Information System (IRIS) in developing draft unit risk values. Using the original data from the key study (Beane Freeman et al., 2009) and documentation provided in the draft IRIS profile, we attempted to duplicate the reported inhalation unit risk values and address the NAS Committee's questions regarding application of the appropriate dose-response model. Overall, documentation of the methods lacked sufficient detail to allow for replication of the unit risk estimates, specifically for Hodgkin lymphoma and leukemias, the key systemic endpoints selected by IRIS. The lack of apparent exposure-response relationships for selected endpoints raises the question whether quantitative analyses are appropriate for these endpoints, and if so, how results are to be interpreted.

  10. Non-Abelian Gauge Symmetry in the Causal Epstein-Glaser Approach

    NASA Astrophysics Data System (ADS)

    Hurth, Tobias

    Non-Abelian gauge symmetry in (3 + 1)-dimensional space-time is analyzed in the causal Epstein-Glaser framework. In this formalism, the technical details concerning the well-known UV and IR problem in quantum field theory are separated and reduced to well-defined problems, namely the causal splitting and the adiabatic switching of operator-valued distributions. Non-Abelian gauge invariance in perturbation theory is completely discussed in the well-defined Fock space of free asymptotic fields. The LSZ formalism is not used in this construction. The linear operator condition of asymptotic gauge invariance is sufficient for the unitarity of the S matrix in the physical subspace and the usual Slavnov-Taylor identities. We explicitly derive the most general specific coupling compatible with this condition. By analyzing only tree graphs in the second order of perturbation theory we show that the well-known Yang-Mills couplings with anticommuting ghosts are the only ones which are compatible with asymptotic gauge invariance. The required generalizations for linear gauges are given.

  11. Instrumental variable approaches to identifying the causal effect of educational attainment on dementia risk.

    PubMed

    Nguyen, Thu T; Tchetgen Tchetgen, Eric J; Kawachi, Ichiro; Gilman, Stephen E; Walter, Stefan; Liu, Sze Y; Manly, Jennifer J; Glymour, M Maria

    2016-01-01

    Education is an established correlate of cognitive status in older adulthood, but whether expanding educational opportunities would improve cognitive functioning remains unclear given limitations of prior studies for causal inference. Therefore, we conducted instrumental variable (IV) analyses of the association between education and dementia risk, using for the first time in this area, genetic variants as instruments as well as state-level school policies. IV analyses in the Health and Retirement Study cohort (1998-2010) used two sets of instruments: (1) a genetic risk score constructed from three single-nucleotide polymorphisms (SNPs; n = 7981); and (2) compulsory schooling laws (CSLs) and state school characteristics (term length, student teacher ratios, and expenditures; n = 10,955). Using the genetic risk score as an IV, there was a 1.1% reduction in dementia risk per year of schooling (95% confidence interval, -2.4 to 0.02). Leveraging compulsory schooling laws and state school characteristics as IVs, there was a substantially larger protective effect (-9.5%; 95% confidence interval, -14.8 to -4.2). Analyses evaluating the plausibility of the IV assumptions indicated estimates derived from analyses relying on CSLs provide the best estimates of the causal effect of education. IV analyses suggest education is protective against risk of dementia in older adulthood. Copyright © 2016 Elsevier Inc. All rights reserved.

  12. Instrumental variable approaches to identifying the causal effect of educational attainment on dementia risk

    PubMed Central

    Nguyen, Thu T.; Tchetgen Tchetgen, Eric J.; Kawachi, Ichiro; Gilman, Stephen E.; Walter, Stefan; Liu, Sze Y.; Manly, Jennifer; Glymour, M. Maria

    2015-01-01

    Purpose Education is an established correlate of cognitive status in older adulthood, but whether expanding educational opportunities would improve cognitive functioning remains unclear given limitations of prior studies for causal inference. Therefore, we conducted instrumental variable (IV) analyses of the association between education and dementia risk, using for the first time in this area, genetic variants as instruments as well as state-level school policies. Methods IV analyses in the Health and Retirement Study cohort (1998–2010) used two sets of instruments: 1) a genetic risk score constructed from three single nucleotide polymorphisms (SNPs) (n=8,054); and 2) compulsory schooling laws (CSLs) and state school characteristics (term length, student teacher ratios, and expenditures) (n=13,167). Results Employing the genetic risk score as an IV, there was a 1.1% reduction in dementia risk per year of schooling (95% CI: −2.4, 0.02). Leveraging compulsory schooling laws and state school characteristics as IVs, there was a substantially larger protective effect (−9.5%; 95% CI: −14.8, −4.2). Analyses evaluating the plausibility of the IV assumptions indicated estimates derived from analyses relying on CSLs provide the best estimates of the causal effect of education. Conclusion IV analyses suggest education is protective against risk of dementia in older adulthood. PMID:26633592

  13. The Epstein-Glaser causal approach to the light-front QED4. I: Free theory

    NASA Astrophysics Data System (ADS)

    Bufalo, R.; Pimentel, B. M.; Soto, D. E.

    2014-12-01

    In this work we present the study of light-front field theories in the realm of the axiomatic theory. It is known that when one uses the light-cone gauge pathological poles (k+) - n arises, demanding a prescription to be employed in order to tame these ill-defined poles and to have the correct Feynman integrals due to the lack of Wick rotation in such theories. In order to shed a new light on this long standing problem we present here a discussion based on the use of rigorous mathematical machinery of the distributional theory combined with physical concepts, such as causality, to show how to deal with these singular propagators in a general fashion without making use of any prescription. The first step of our development will consist in showing how the analytic representation for propagators arises by requiring general physical properties within the framework of Wightman's formalism. From that we shall determine the equal-time (anti)commutation relations in the light-front form for the scalar and fermionic fields, as well as for the dynamical components of the electromagnetic field. In conclusion, we introduce the Epstein-Glaser causal method in order to have a mathematical rigorous description of the free propagators of the theory, allowing us to discuss a general treatment for propagators of the type (k+) - n. Afterwards, we show that at given conditions our results reproduce known prescriptions in the literature.

  14. Spatio-temporal interaction between absorbing aerosols and temperature: Correlation and causality based approach

    NASA Astrophysics Data System (ADS)

    Dave, P.; Bhushan, M.; Venkataraman, C.

    2016-12-01

    Indian subcontinent, in particular, the Indo-gangetic plain (IGP) has witnessed large temperature anomalies (Ratnam et al., 2016) along with high emission of absorbing aerosols (AA) (Gazala, et al., 2005). The anomalous high temperature observed over this region may bear a relationship with high AA emissions. Different studies have been conducted to understand AA and temperature relationships (Turco et al., 1983; Hansen et al., 1997, 2005; Seinfeld 2008; Ramanathan et al. 2010b; Ban-Weiss et al., 2012). It was found that when the AA was injected in the lower- mid troposphere the surface air temperature increases while injection of AA at higher troposphere-lower stratosphere surface temperature decreases. These studies used simulation based results to establish link between AA and temperature (Hansen et al., 1997, 2005; Ban-Weiss et al., 2012). The current work focuses on identifying the causal influence of AA on temperature using observational and re-analysis data over Indian subcontinent using cross correlation (CCs) and Granger causality (GC) (Granger, 1969). Aerosol index (AI) from TOMS-OMI was used as index for AA while ERA-interim reanalysis data was used for temperature at varying altitude. Period of study was March-April-May-June (MAMJ) for years 1979-2015. CCs were calculated for all the atmospheric layers. In each layer nearby and distant pixels (>500 kms) with high CCs were identified using clustering technique. It was found that that AI and Temperature shows statistically significant cross-correlations for co-located and distant pixels and more prominently over IGP. The CCs fades away with higher altitudes. CCs analysis was followed by GC analysis to identify the lag over which AI can influence the Temperature. GC also supported the findings of CCs analysis. It is an early attempt to link persisting large temperature anomalies with absorbing aerosols and may help in identifying the role of absorbing aerosol in causing heat waves.

  15. Multisource causal data mining

    NASA Astrophysics Data System (ADS)

    Woodley, Robert; Gosnell, Michael; Shallenberger, Kevin

    2012-06-01

    Analysts are faced with mountains of data, and finding that relevant piece of information is the proverbial needle in a haystack, only with dozens of haystacks. Analysis tools that facilitate identifying causal relationships across multiple data sets are sorely needed. 21st Century Systems, Inc. (21CSi) has initiated research called Causal-View, a causal datamining visualization tool, to address this challenge. Causal-View is built on an agent-enabled framework. Much of the processing that Causal-View will do is in the background. When a user requests information, Data Extraction Agents launch to gather information. This initial search is a raw, Monte Carlo type search designed to gather everything available that may have relevance to an individual, location, associations, and more. This data is then processed by Data- Mining Agents. The Data-Mining Agents are driven by user supplied feature parameters. If the analyst is looking to see if the individual frequents a known haven for insurgents he may request information on his last known locations. Or, if the analyst is trying to see if there is a pattern in the individual's contacts, the mining agent can be instructed with the type and relevance of the information fields to look at. The same data is extracted from the database, but the Data Mining Agents customize the feature set to determine causal relationships the user is interested in. At this point, a Hypothesis Generation and Data Reasoning Agents take over to form conditional hypotheses about the data and pare the data, respectively. The newly formed information is then published to the agent communication backbone of Causal- View to be displayed. Causal-View provides causal analysis tools to fill the gaps in the causal chain. We present here the Causal-View concept, the initial research into data mining tools that assist in forming the causal relationships, and our initial findings.

  16. A new life-span approach to conscientiousness and health: combining the pieces of the causal puzzle.

    PubMed

    Friedman, Howard S; Kern, Margaret L; Hampson, Sarah E; Duckworth, Angela Lee

    2014-05-01

    Conscientiousness has been shown to predict healthy behaviors, healthy social relationships, and physical health and longevity. The causal links, however, are complex and not well elaborated. Many extant studies have used comparable measures for conscientiousness, and a systematic endeavor to build cross-study analyses for conscientiousness and health now seems feasible. Of particular interest are efforts to construct new, more comprehensive causal models by linking findings and combining data from existing studies of different cohorts. Although methodological perils can threaten such integration, such efforts offer an early opportunity to enliven a life course perspective on conscientiousness, to see whether component facets of conscientiousness remain related to each other and to relevant mediators across broad spans of time, and to bolster the findings of the few long-term longitudinal studies of the dynamics of personality and health. A promising approach to testing new models involves pooling data from extant studies as an efficient and heuristic prelude to large-scale testing of interventions.

  17. Introduction to causal diagrams for confounder selection.

    PubMed

    Williamson, Elizabeth J; Aitken, Zoe; Lawrie, Jock; Dharmage, Shyamali C; Burgess, John A; Forbes, Andrew B

    2014-04-01

    In respiratory health research, interest often lies in estimating the effect of an exposure on a health outcome. If randomization of the exposure of interest is not possible, estimating its effect is typically complicated by confounding bias. This can often be dealt with by controlling for the variables causing the confounding, if measured, in the statistical analysis. Common statistical methods used to achieve this include multivariable regression models adjusting for selected confounding variables or stratification on those variables. Therefore, a key question is which measured variables need to be controlled for in order to remove confounding. An approach to confounder-selection based on the use of causal diagrams (often called directed acyclic graphs) is discussed. A causal diagram is a visual representation of the causal relationships believed to exist between the variables of interest, including the exposure, outcome and potential confounding variables. After creating a causal diagram for the research question, an intuitive and easy-to-use set of rules can be applied, based on a foundation of rigorous mathematics, to decide which measured variables must be controlled for in the statistical analysis in order to remove confounding, to the extent that is possible using the available data. This approach is illustrated by constructing a causal diagram for the research question: 'Does personal smoking affect the risk of subsequent asthma?'. Using data taken from the Tasmanian Longitudinal Health Study, the statistical analysis suggested by the causal diagram approach was performed.

  18. CADDIS Volume 1. Stressor Identification: About Causal Assessment

    EPA Pesticide Factsheets

    An introduction to the history of our approach to causal assessment, A chronology of causal history and philosophy, An introduction to causal history and philosophy, References for the Causal Assessment Background section of Stressor Identification

  19. Efficiency characterization of a large neuronal network: A causal information approach

    NASA Astrophysics Data System (ADS)

    Montani, Fernando; Deleglise, Emilia B.; Rosso, Osvaldo A.

    2014-05-01

    When inhibitory neurons constitute about 40% of neurons they could have an important antinociceptive role, as they would easily regulate the level of activity of other neurons. We consider a simple network of cortical spiking neurons with axonal conduction delays and spike timing dependent plasticity, representative of a cortical column or hypercolumn with a large proportion of inhibitory neurons. Each neuron fires following a Hodgkin-Huxley like dynamics and it is interconnected randomly to other neurons. The network dynamics is investigated estimating Bandt and Pompe probability distribution function associated to the interspike intervals and taking different degrees of interconnectivity across neurons. More specifically we take into account the fine temporal “structures” of the complex neuronal signals not just by using the probability distributions associated to the interspike intervals, but instead considering much more subtle measures accounting for their causal information: the Shannon permutation entropy, Fisher permutation information and permutation statistical complexity. This allows us to investigate how the information of the system might saturate to a finite value as the degree of interconnectivity across neurons grows, inferring the emergent dynamical properties of the system.

  20. Causal and causally separable processes

    NASA Astrophysics Data System (ADS)

    Oreshkov, Ognyan; Giarmatzi, Christina

    2016-09-01

    The idea that events are equipped with a partial causal order is central to our understanding of physics in the tested regimes: given two pointlike events A and B, either A is in the causal past of B, B is in the causal past of A, or A and B are space-like separated. Operationally, the meaning of these order relations corresponds to constraints on the possible correlations between experiments performed in the vicinities of the respective events: if A is in the causal past of B, an experimenter at A could signal to an experimenter at B but not the other way around, while if A and B are space-like separated, no signaling is possible in either direction. In the context of a concrete physical theory, the correlations compatible with a given causal configuration may obey further constraints. For instance, space-like correlations in quantum mechanics arise from local measurements on joint quantum states, while time-like correlations are established via quantum channels. Similarly to other variables, however, the causal order of a set of events could be random, and little is understood about the constraints that causality implies in this case. A main difficulty concerns the fact that the order of events can now generally depend on the operations performed at the locations of these events, since, for instance, an operation at A could influence the order in which B and C occur in A’s future. So far, no formal theory of causality compatible with such dynamical causal order has been developed. Apart from being of fundamental interest in the context of inferring causal relations, such a theory is imperative for understanding recent suggestions that the causal order of events in quantum mechanics can be indefinite. Here, we develop such a theory in the general multipartite case. Starting from a background-independent definition of causality, we derive an iteratively formulated canonical decomposition of multipartite causal correlations. For a fixed number of settings and

  1. Olfactory Network Differences in Master Sommeliers: Connectivity Analysis Using Granger Causality and Graph Theoretical Approach.

    PubMed

    Sreenivasan, Karthik; Zhuang, Xiaowei; Banks, Sarah J; Mishra, Virendra; Yang, Zhengshi; Deshpande, Gopikrishna; Cordes, Dietmar

    2017-03-01

    Previous studies investigating the differences in olfactory processing and judgments between trained sommeliers and controls have shown increased activations in brain regions involving higher level cognitive processes in sommeliers. However, there is little information about the influence of expertise on causal connectivity and topological properties of the connectivity networks between these regions. Therefore, the current study focuses on addressing these questions in a functional magnetic resonance imaging (fMRI) study of olfactory perception in Master Sommeliers. fMRI data were acquired from Master Sommeliers and control participants during different olfactory and nonolfactory tasks. Mean time series were extracted from 90 different regions of interest (ROIs; based on Automated Anatomical Labeling atlas). The underlying neuronal variables were extracted using blind hemodynamic deconvolution and then input into a dynamic multivariate autoregressive model to obtain connectivity between every pair of ROIs as a function of time. These connectivity values were then statistically compared to obtain paths that were significantly different between the two groups. The obtained connectivity matrices were further studied using graph theoretical methods. In sommeliers, significantly greater connectivity was observed in connections involving the precuneus, caudate, putamen, and several frontal and temporal regions. The controls showed increased connectivity from the left hippocampus to the frontal regions. Furthermore, the sommeliers exhibited significantly higher small-world topology than the controls. These findings are significant, given that learning about neuroplasticity in adulthood in these regions may then have added clinical importance in diseases such as Alzheimer's and Parkinson's where early neurodegeneration is isolated to regions important in smell.

  2. Hemispheric lateralization in top-down attention during spatial relation processing: a Granger causal model approach.

    PubMed

    Falasca, N W; D'Ascenzo, S; Di Domenico, A; Onofrj, M; Tommasi, L; Laeng, B; Franciotti, R

    2015-04-01

    Magnetoencephalography was recorded during a matching-to-sample plus cueing paradigm, in which participants judged the occurrence of changes in either categorical (CAT) or coordinate (COO) spatial relations. Previously, parietal and frontal lobes were identified as key areas in processing spatial relations and it was shown that each hemisphere was differently involved and modulated by the scope of the attention window (e.g. a large and small cue). In this study, Granger analysis highlighted the patterns of causality among involved brain areas--the direction of information transfer ran from the frontal to the visual cortex in the right hemisphere, whereas it ran in the opposite direction in the left side. Thus, the right frontal area seems to exert top-down influence, supporting the idea that, in this task, top-down signals are selectively related to the right side. Additionally, for CAT change preceded by a small cue, the right frontal gyrus was not involved in the information transfer, indicating a selective specialization of the left hemisphere for this condition. The present findings strengthen the conclusion of the presence of a remarkable hemispheric specialization for spatial relation processing and illustrate the complex interactions between the lateralized parts of the neural network. Moreover, they illustrate how focusing attention over large or small regions of the visual field engages these lateralized networks differently, particularly in the frontal regions of each hemisphere, consistent with the theory that spatial relation judgements require a fronto-parietal network in the left hemisphere for categorical relations and on the right hemisphere for coordinate spatial processing.

  3. Localization of causal locus in the genome of the brown macroalga Ectocarpus: NGS-based mapping and positional cloning approaches.

    PubMed

    Billoud, Bernard; Jouanno, Émilie; Nehr, Zofia; Carton, Baptiste; Rolland, Élodie; Chenivesse, Sabine; Charrier, Bénédicte

    2015-01-01

    Mutagenesis is the only process by which unpredicted biological gene function can be identified. Despite that several macroalgal developmental mutants have been generated, their causal mutation was never identified, because experimental conditions were not gathered at that time. Today, progresses in macroalgal genomics and judicious choices of suitable genetic models make mutated gene identification possible. This article presents a comparative study of two methods aiming at identifying a genetic locus in the brown alga Ectocarpus siliculosus: positional cloning and Next-Generation Sequencing (NGS)-based mapping. Once necessary preliminary experimental tools were gathered, we tested both analyses on an Ectocarpus morphogenetic mutant. We show how a narrower localization results from the combination of the two methods. Advantages and drawbacks of these two approaches as well as potential transfer to other macroalgae are discussed.

  4. Localization of causal locus in the genome of the brown macroalga Ectocarpus: NGS-based mapping and positional cloning approaches

    PubMed Central

    Billoud, Bernard; Jouanno, Émilie; Nehr, Zofia; Carton, Baptiste; Rolland, Élodie; Chenivesse, Sabine; Charrier, Bénédicte

    2015-01-01

    Mutagenesis is the only process by which unpredicted biological gene function can be identified. Despite that several macroalgal developmental mutants have been generated, their causal mutation was never identified, because experimental conditions were not gathered at that time. Today, progresses in macroalgal genomics and judicious choices of suitable genetic models make mutated gene identification possible. This article presents a comparative study of two methods aiming at identifying a genetic locus in the brown alga Ectocarpus siliculosus: positional cloning and Next-Generation Sequencing (NGS)-based mapping. Once necessary preliminary experimental tools were gathered, we tested both analyses on an Ectocarpus morphogenetic mutant. We show how a narrower localization results from the combination of the two methods. Advantages and drawbacks of these two approaches as well as potential transfer to other macroalgae are discussed. PMID:25745426

  5. The Epstein–Glaser causal approach to the light-front QED{sub 4}. I: Free theory

    SciTech Connect

    Bufalo, R. Pimentel, B.M. Soto, D.E.

    2014-12-15

    In this work we present the study of light-front field theories in the realm of the axiomatic theory. It is known that when one uses the light-cone gauge pathological poles (k{sup +}){sup −n} arises, demanding a prescription to be employed in order to tame these ill-defined poles and to have the correct Feynman integrals due to the lack of Wick rotation in such theories. In order to shed a new light on this long standing problem we present here a discussion based on the use of rigorous mathematical machinery of the distributional theory combined with physical concepts, such as causality, to show how to deal with these singular propagators in a general fashion without making use of any prescription. The first step of our development will consist in showing how the analytic representation for propagators arises by requiring general physical properties within the framework of Wightman’s formalism. From that we shall determine the equal-time (anti)commutation relations in the light-front form for the scalar and fermionic fields, as well as for the dynamical components of the electromagnetic field. In conclusion, we introduce the Epstein–Glaser causal method in order to have a mathematical rigorous description of the free propagators of the theory, allowing us to discuss a general treatment for propagators of the type (k{sup +}){sup −n}. Afterwards, we show that at given conditions our results reproduce known prescriptions in the literature. - Highlights: • We develop the analytic representation for propagators in Wightman’s framework. • We make use of the analytic representation to obtain equal-time (anti)commutation relations in the light-front. • We derive the free Feynman propagators for the light-front quantum electrodynamics in the Epstein–Glaser approach. • We determine a general expression for the propagator associated to the light-cone poles (k{sup +}){sup −n} in the causal approach.

  6. Combining GWAS and RNA-Seq Approaches for Detection of the Causal Mutation for Hereditary Junctional Epidermolysis Bullosa in Sheep.

    PubMed

    Suárez-Vega, Aroa; Gutiérrez-Gil, Beatriz; Benavides, Julio; Perez, Valentín; Tosser-Klopp, Gwenola; Klopp, Christophe; Keennel, Stephen J; Arranz, Juan José

    2015-01-01

    In this study, we demonstrate the use of a genome-wide association mapping together with RNA-seq in a reduced number of samples, as an efficient approach to detect the causal mutation for a Mendelian disease. Junctional epidermolysis bullosa is a recessive genodermatosis that manifests with neonatal mechanical fragility of the skin, blistering confined to the lamina lucida of the basement membrane and severe alteration of the hemidesmosomal junctions. In Spanish Churra sheep, junctional epidermolysis bullosa (JEB) has been detected in two commercial flocks. The JEB locus was mapped to Ovis aries chromosome 11 by GWAS and subsequently fine-mapped to an 868-kb homozygous segment using the identical-by-descent method. The ITGB4, which is located within this region, was identified as the best positional and functional candidate gene. The RNA-seq variant analysis enabled us to discover a 4-bp deletion within exon 33 of the ITGB4 gene (c.4412_4415del). The c.4412_4415del mutation causes a frameshift resulting in a premature stop codon at position 1472 of the integrin β4 protein. A functional analysis of this deletion revealed decreased levels of mRNA in JEB skin samples and the absence of integrin β4 labeling in immunohistochemical assays. Genotyping of c.4412_4415del showed perfect concordance with the recessive mode of the disease phenotype. Selection against this causal mutation will now be used to solve the problem of JEB in flocks of Churra sheep. Furthermore, the identification of the ITGB4 mutation means that affected sheep can be used as a large mammal animal model for the human form of epidermolysis bullosa with aplasia cutis. Our approach evidences that RNA-seq offers cost-effective alternative to identify variants in the species in which high resolution exome-sequencing is not straightforward.

  7. Combining GWAS and RNA-Seq Approaches for Detection of the Causal Mutation for Hereditary Junctional Epidermolysis Bullosa in Sheep

    PubMed Central

    Suárez-Vega, Aroa; Gutiérrez-Gil, Beatriz; Benavides, Julio; Perez, Valentín; Tosser-Klopp, Gwenola; Klopp, Christophe; Keennel, Stephen J.; Arranz, Juan José

    2015-01-01

    In this study, we demonstrate the use of a genome-wide association mapping together with RNA-seq in a reduced number of samples, as an efficient approach to detect the causal mutation for a Mendelian disease. Junctional epidermolysis bullosa is a recessive genodermatosis that manifests with neonatal mechanical fragility of the skin, blistering confined to the lamina lucida of the basement membrane and severe alteration of the hemidesmosomal junctions. In Spanish Churra sheep, junctional epidermolysis bullosa (JEB) has been detected in two commercial flocks. The JEB locus was mapped to Ovis aries chromosome 11 by GWAS and subsequently fine-mapped to an 868-kb homozygous segment using the identical-by-descent method. The ITGB4, which is located within this region, was identified as the best positional and functional candidate gene. The RNA-seq variant analysis enabled us to discover a 4-bp deletion within exon 33 of the ITGB4 gene (c.4412_4415del). The c.4412_4415del mutation causes a frameshift resulting in a premature stop codon at position 1472 of the integrin β4 protein. A functional analysis of this deletion revealed decreased levels of mRNA in JEB skin samples and the absence of integrin β4 labeling in immunohistochemical assays. Genotyping of c.4412_4415del showed perfect concordance with the recessive mode of the disease phenotype. Selection against this causal mutation will now be used to solve the problem of JEB in flocks of Churra sheep. Furthermore, the identification of the ITGB4 mutation means that affected sheep can be used as a large mammal animal model for the human form of epidermolysis bullosa with aplasia cutis. Our approach evidences that RNA-seq offers cost-effective alternative to identify variants in the species in which high resolution exome-sequencing is not straightforward. PMID:25955497

  8. Making valid causal inferences from observational data.

    PubMed

    Martin, Wayne

    2014-02-15

    The ability to make strong causal inferences, based on data derived from outside of the laboratory, is largely restricted to data arising from well-designed randomized control trials. Nonetheless, a number of methods have been developed to improve our ability to make valid causal inferences from data arising from observational studies. In this paper, I review concepts of causation as a background to counterfactual causal ideas; the latter ideas are central to much of current causal theory. Confounding greatly constrains causal inferences in all observational studies. Confounding is a biased measure of effect that results when one or more variables, that are both antecedent to the exposure and associated with the outcome, are differentially distributed between the exposed and non-exposed groups. Historically, the most common approach to control confounding has been multivariable modeling; however, the limitations of this approach are discussed. My suggestions for improving causal inferences include asking better questions (relates to counterfactual ideas and "thought" trials); improving study design through the use of forward projection; and using propensity scores to identify potential confounders and enhance exchangeability, prior to seeing the outcome data. If time-dependent confounders are present (as they are in many longitudinal studies), more-advanced methods such as marginal structural models need to be implemented. Tutorials and examples are cited where possible. Copyright © 2013 Elsevier B.V. All rights reserved.

  9. A systematic approach to training: A training needs assessment

    NASA Technical Reports Server (NTRS)

    Manning, Margaret H.

    1989-01-01

    In an effort to determine the gap between the actual performance and the necessary performance of employees for the effective and efficient accomplishment of an organization's mission and goals, an organization-wide Training Needs Assessment must be conducted. The purpose of this work was to conduct a training needs analysis and prepare a NASA Langley Catalog of On-Site Training programs. The work included developing a Training Needs Assessment Survey, implementing the survey, analyzing and researching the training needs, identifying the courses to meet the needs, and preparing and designing an On-Site Training Catalog. This needs analysis attempted to identify performance weaknesses and deficits; seek out and provide opportunities for improved performance; anticipate and avoid future problems; enhance and create new strengths. The end product is a user-friendly catalog of on-site training available. The results include: top-down approach to needs assessment; improved communication with training coordinators; 98 percent return rate of the Training Needs Assessment survey; complete, newly designed, user-friendly catalog; 167 catalog descriptions advertised; 82 new courses advertised; training logo; and request for the training application form.

  10. A Summative Evaluation of RCT Methodology: & An Alternative Approach to Causal Research

    ERIC Educational Resources Information Center

    Scriven, Michael

    2008-01-01

    This review focuses on what the author terms a reconsideration of the working credentials of the randomly controlled trial (RCT) design, and includes a discussion of popularly accepted aspects as well as some new perspectives. The author concludes that there is nothing either Imperative or superior about the need for RCT designs, and that an…

  11. [Needs assessment across social insurance agencies - potential approaches and prospects].

    PubMed

    Beck, L; Giraud, B; Petri, B

    2011-02-01

    To enable self-determination and participation equal with others for persons with disabilities, the social insurance agencies involved in rehabilitation provide benefits for rehabilitation and participation. In order to initiate and perform those benefits individually and purposively, it is necessary to detect and assess a potential need early across social insurance agencies. This requirement was strengthened by the UN Convention on the Rights of Persons with Disabilities. The article outlines the legal background and practical framework conditions for the present assessment duty and refers to examples of existing methods for needs assessment, which in general are still too much aligned to specific benefits. In light of these circumstances, a need for action exists in order to implement legal demands relative to needs assessments across social insurance agencies and to advance approaches already in place. © Georg Thieme Verlag KG Stuttgart · New York.

  12. Taking Emergence Seriously: The Centrality of Circular Causality for Dynamic Systems Approaches to Development

    ERIC Educational Resources Information Center

    Witherington, David C.

    2011-01-01

    The dynamic systems (DS) approach has emerged as an influential and potentially unifying metatheory for developmental science. Its central platform--the argument against design--suggests that structure spontaneously and without prescription emerges through self-organization. In one of the most prominent accounts of DS, Thelen and her colleagues…

  13. Model-based causal closed-loop approach to the estimate of baroreflex sensitivity during propofol anesthesia in patients undergoing coronary artery bypass graft.

    PubMed

    Porta, Alberto; Bari, Vlasta; Bassani, Tito; Marchi, Andrea; Pistuddi, Valeria; Ranucci, Marco

    2013-10-01

    Cardiac baroreflex is a fundamental component of the cardiovascular control. The continuous assessment of baroreflex sensitivity (BRS) from spontaneous heart period (HP) and systolic arterial pressure (SAP) variations during general anesthesia provides relevant information about cardiovascular regulation in physiological conditions. Unfortunately, several difficulties including unknown HP-SAP causal relations, negligible SAP changes, small BRS values, and confounding influences due to mechanical ventilation prevent BRS monitoring from HP and SAP variabilities during general anesthesia. We applied a model-based causal closed-loop approach aiming at BRS assessment during propofol anesthesia in 34 patients undergoing coronary artery bypass graft (CABG) surgery. We found the following: 1) traditional time and frequency domain approaches (i.e., baroreflex sequence, cross-correlation, spectral, and transfer function techniques) exhibited irremediable methodological limitations preventing the assessment of the BRS decrease during propofol anesthesia; 2) Granger causality approach proved that the methodological caveats were linked to the decreased presence of bidirectional closed-loop HP-SAP interactions and to the increased incidence of the HP-SAP uncoupling; 3) our model-based closed-loop approach detected the significant BRS decrease during propofol anesthesia as a likely result of accounting for the influences of mechanical ventilation and causal HP-SAP interactions; and 4) the model-based closed-loop approach found also a diminished gain of the relation from HP to SAP linked to vasodilatation and reduced ventricular contractility during propofol anesthesia. The proposed model-based causal closed-loop approach is more effective than traditional approaches in monitoring cardiovascular control during propofol anesthesia and indicates an overall depression of the HP-SAP closed-loop regulation.

  14. Causality and headache triggers

    PubMed Central

    Turner, Dana P.; Smitherman, Todd A.; Martin, Vincent T.; Penzien, Donald B.; Houle, Timothy T.

    2013-01-01

    Objective The objective of this study was to explore the conditions necessary to assign causal status to headache triggers. Background The term “headache trigger” is commonly used to label any stimulus that is assumed to cause headaches. However, the assumptions required for determining if a given stimulus in fact has a causal-type relationship in eliciting headaches have not been explicated. Methods A synthesis and application of Rubin’s Causal Model is applied to the context of headache causes. From this application the conditions necessary to infer that one event (trigger) causes another (headache) are outlined using basic assumptions and examples from relevant literature. Results Although many conditions must be satisfied for a causal attribution, three basic assumptions are identified for determining causality in headache triggers: 1) constancy of the sufferer; 2) constancy of the trigger effect; and 3) constancy of the trigger presentation. A valid evaluation of a potential trigger’s effect can only be undertaken once these three basic assumptions are satisfied during formal or informal studies of headache triggers. Conclusions Evaluating these assumptions is extremely difficult or infeasible in clinical practice, and satisfying them during natural experimentation is unlikely. Researchers, practitioners, and headache sufferers are encouraged to avoid natural experimentation to determine the causal effects of headache triggers. Instead, formal experimental designs or retrospective diary studies using advanced statistical modeling techniques provide the best approaches to satisfy the required assumptions and inform causal statements about headache triggers. PMID:23534872

  15. Translational research-the need of a new bioethics approach.

    PubMed

    Hostiuc, Sorin; Moldoveanu, Alin; Dascălu, Maria-Iuliana; Unnthorsson, Runar; Jóhannesson, Ómar I; Marcus, Ioan

    2016-01-15

    Translational research tries to apply findings from basic science to enhance human health and well-being. Many phases of the translational research may include non-medical tasks (information technology, engineering, nanotechnology, biochemistry, animal research, economy, sociology, psychology, politics, and so on). Using common bioethics principles to these areas might sometimes be not feasible, or even impossible. However, the whole process must respect some fundamental, moral principles. The purpose of this paper is to argument the need for a different approach to the morality in translational bioethics, and to suggest some directions that might be followed when constructing such a bioethics. We will show that a new approach is needed and present a few ethical issues that are specific to the translational research.

  16. Abnormal causal attribution leads to advantageous economic decision-making: A neuropsychological approach

    PubMed Central

    Koscik, Timothy R.; Tranel, Daniel

    2013-01-01

    People tend to assume that outcomes are caused by dispositional factors, e.g., a person’s constitution or personality, even when the actual cause is due to situational factors, e.g., luck or coincidence. This is known as the ‘correspondence bias.’ This tendency can lead normal, intelligent persons to make suboptimal decisions. Here, we used a neuropsychological approach to investigate the neural basis of the correspondence bias, by studying economic decision-making in patients with damage to the ventromedial prefrontal cortex (vmPFC). Given the role of the vmPFC in social cognition, we predicted that vmPFC is necessary for the normal correspondence bias. In our experiment, consistent with expectations, healthy (N=46) and brain-damaged (N=30) comparison participants displayed the correspondence bias when investing and invested no differently when given dispositional or situational information. By contrast, vmPFC patients (N=17) displayed a lack of correspondence bias and invested more when given dispositional than situational information. The results support the conclusion that vmPFC is critical for normal social inference and the correspondence bias, and our findings help clarify the important (and potentially disadvantageous) role of social inference in economic decision-making. PMID:23574584

  17. Relativistic causality

    NASA Astrophysics Data System (ADS)

    Valente, Giovanni; Owen Weatherall, James

    2014-11-01

    Relativity theory is often taken to include, or to imply, a prohibition on superluminal propagation of causal processes. Yet, what exactly the prohibition on superluminal propagation amounts to and how one should deal with its possible violation have remained open philosophical problems, both in the context of the metaphysics of causation and the foundations of physics. In particular, recent work in philosophy of physics has focused on the causal structure of spacetime in relativity theory and on how this causal structure manifests itself in our most fundamental theories of matter. These topics were the subject of a workshop on "Relativistic Causality in Quantum Field Theory and General Relativity" that we organized (along with John Earman) at the Center for Philosophy of Science in Pittsburgh on April 5-7, 2013. The present Special Issue comprises contributions by speakers in that workshop as well as several other experts exploring different aspects of relativistic causality. We are grateful to the journal for hosting this Special Issue, to the journal's managing editor, Femke Kuiling, for her help and support in putting the issue together, and to the authors and the referees for their excellent work.

  18. Attribution and social cognitive neuroscience: a new approach for the "online-assessment" of causality ascriptions and their emotional consequences.

    PubMed

    Terbeck, Sylvia; Chesterman, Paul; Fischmeister, Florian Ph S; Leodolter, Ulrich; Bauer, Herbert

    2008-08-15

    Attribution theory plays a central role in understanding cognitive processes that have emotional consequences; however, there has been very limited attention to its neural basis. After reviewing classical studies in social psychology in which attribution has been experimentally manipulated we developed a new approach that allows the investigation of state attributions and emotional consequences using neuroscience methodologies. Participants responded to the Erikson Flanker Task, but, in order to maintain the participant's beliefs about the nature of the task and to produce a significant number of error responses, an adaptive algorithm tuned the available time to respond such that, dependent on the subject's current performance, the negative feedback rate was held at chance level. In order to initiate variation in attribution participants were informed that one and the same task was either easy or difficult. As a result of these two different instructions the two groups differed significantly in error attribution only on the locus of causality dimension. Additionally, attributions were found to be stable over a large number of trials, while accuracy and reaction time remained the same. Thus, the new paradigm is particularly suitable for cognitive neuroscience research that evaluates brain behaviour relationships of higher order processes in 'simulated achievement settings'.

  19. Explaining Racial Disparities in Child Asthma Readmission Using a Causal Inference Approach.

    PubMed

    Beck, Andrew F; Huang, Bin; Auger, Katherine A; Ryan, Patrick H; Chen, Chen; Kahn, Robert S

    2016-07-01

    difference between African American and white children with respect to readmission hazard no longer reached the level of significance (hazard ratio, 1.18; 95% CI, 0.87-1.60; Cox P = .30 and log-rank P = .39). A total of 80% of the observed readmission disparity between African American and white children could be explained after statistically balancing available biologic, environmental, disease management, access to care, and socioeconomic and hardship variables across racial groups. Such a comprehensive, well-framed approach to exposures that are associated with morbidity is critical as we attempt to better understand and lessen persistent child asthma disparities.

  20. Explaining Racial Disparities in Child Asthma Readmission Using a Causal Inference Approach

    PubMed Central

    Beck, Andrew F.; Huang, Bin; Auger, Katherine A.; Ryan, Patrick H.; Chen, Chen; Kahn, Robert S.

    2017-01-01

    access variables resulted in 80% of the readmission disparity being explained. The difference between African American and white children with respect to readmission hazard no longer reached the level of significance (hazard ratio, 1.18; 95% CI, 0.87–1.60; Cox P = .30 and log-rank P = .39). CONCLUSIONS AND RELEVANCE A total of 80% of the observed readmission disparity between African American and white children could be explained after statistically balancing available biologic, environmental, disease management, access to care, and socioeconomic and hardship variables across racial groups. Such a comprehensive, well-framed approach to exposures that are associated with morbidity is critical as we attempt to better understand and lessen persistent child asthma disparities. PMID:27182793

  1. Basic needs: New approach to development — But new approach to education?

    NASA Astrophysics Data System (ADS)

    Allen, Dwight W.; Anzalone, Stephen

    1981-09-01

    The article is an examination of what has been called the basic needs approach to development and the implications of adopting such an approach for education. The authors trace briefly the sequence by which the basic needs approach reached the corridors of international development policy. This sequence, together with an analysis of some of the conceptual underpinnings of the basic needs approach, suggest that the approach may be biased toward the experience of the Western industrial nations, and some aspects may be inappropriate for the social realities found in developing countries. The authors take up the question of how education relates to the basic needs philosophy. They look at attempts to fashion a conception of education for basic needs and how such conceptions compare to the prevailing notions of basic education. Finally, the authors identify some key issues where, conceivably, education for basic needs could emerge as distinct from basic education and become consistent with the aspirations of the basic needs approach taken as a whole.

  2. Ecosystem approach to inland fisheries: Research needs and implementation strategies

    USGS Publications Warehouse

    Beard, T.D.; Arlinghaus, R.; Cooke, S.J.; McIntyre, P.B.; De Silva, S.; Bartley, D.; Cowx, I.G.

    2011-01-01

    Inland fisheries are a vital component in the livelihoods and food security of people throughout the world, as well as contributing huge recreational and economic benefits. These valuable assets are jeopardized by lack of research-based understanding of the impacts of fisheries on inland ecosystems, and similarly the impact of human activities associated with inland waters on fisheries and aquatic biodiversity. To explore this topic, an international workshop was organized in order to examine strategies to incorporate fisheries into ecosystem approaches for management of inland waters. To achieve this goal, a new research agenda is needed that focuses on: quantifying the ecosystem services provided by fresh waters; quantifying the economic, social and nutritional benefits of inland fisheries; improving assessments designed to evaluate fisheries exploitation potential; and examining feedbacks between fisheries, ecosystem productivity and aquatic biodiversity. Accomplishing these objectives will require merging natural and social science approaches to address coupled social-ecological system dynamics. ?? 2010 The Royal Society.

  3. Ecosystem approach to inland fisheries: research needs and implementation strategies

    USGS Publications Warehouse

    Beard, T. Douglas; Arlinghaus, Robert; Cooke, Steven J.; McIntyre, Peter B.; De Silva, Sena; Bartley, Devin M.; Cowx, Ian G.

    2011-01-01

    Inland fisheries are a vital component in the livelihoods and food security of people throughout the world, as well as contributing huge recreational and economic benefits. These valuable assets are jeopardized by lack of research-based understanding of the impacts of fisheries on inland ecosystems, and similarly the impact of human activities associated with inland waters on fisheries and aquatic biodiversity. To explore this topic, an international workshop was organized in order to examine strategies to incorporate fisheries into ecosystem approaches for management of inland waters. To achieve this goal, a new research agenda is needed that focuses on: quantifying the ecosystem services provided by fresh waters; quantifying the economic, social and nutritional benefits of inland fisheries; improving assessments designed to evaluate fisheries exploitation potential; and examining feedbacks between fisheries, ecosystem productivity and aquatic biodiversity. Accomplishing these objectives will require merging natural and social science approaches to address coupled social–ecological system dynamics.

  4. Ecosystem approach to inland fisheries: research needs and implementation strategies.

    PubMed

    Beard, T Douglas; Arlinghaus, Robert; Cooke, Steven J; McIntyre, Peter B; De Silva, Sena; Bartley, Devin; Cowx, Ian G

    2011-08-23

    Inland fisheries are a vital component in the livelihoods and food security of people throughout the world, as well as contributing huge recreational and economic benefits. These valuable assets are jeopardized by lack of research-based understanding of the impacts of fisheries on inland ecosystems, and similarly the impact of human activities associated with inland waters on fisheries and aquatic biodiversity. To explore this topic, an international workshop was organized in order to examine strategies to incorporate fisheries into ecosystem approaches for management of inland waters. To achieve this goal, a new research agenda is needed that focuses on: quantifying the ecosystem services provided by fresh waters; quantifying the economic, social and nutritional benefits of inland fisheries; improving assessments designed to evaluate fisheries exploitation potential; and examining feedbacks between fisheries, ecosystem productivity and aquatic biodiversity. Accomplishing these objectives will require merging natural and social science approaches to address coupled social-ecological system dynamics.

  5. Ecosystem approach to inland fisheries: research needs and implementation strategies

    PubMed Central

    Beard, T. Douglas; Arlinghaus, Robert; Cooke, Steven J.; McIntyre, Peter B.; De Silva, Sena; Bartley, Devin; Cowx, Ian G.

    2011-01-01

    Inland fisheries are a vital component in the livelihoods and food security of people throughout the world, as well as contributing huge recreational and economic benefits. These valuable assets are jeopardized by lack of research-based understanding of the impacts of fisheries on inland ecosystems, and similarly the impact of human activities associated with inland waters on fisheries and aquatic biodiversity. To explore this topic, an international workshop was organized in order to examine strategies to incorporate fisheries into ecosystem approaches for management of inland waters. To achieve this goal, a new research agenda is needed that focuses on: quantifying the ecosystem services provided by fresh waters; quantifying the economic, social and nutritional benefits of inland fisheries; improving assessments designed to evaluate fisheries exploitation potential; and examining feedbacks between fisheries, ecosystem productivity and aquatic biodiversity. Accomplishing these objectives will require merging natural and social science approaches to address coupled social–ecological system dynamics. PMID:21325307

  6. Genomic Oncology Education: An Urgent Need, A New Approach

    PubMed Central

    Haspel, Richard L.; Saffitz, Jeffrey E.

    2014-01-01

    Genomic testing has entered oncology practice. With reduced cost and faster turn-around-times, clinical applications for next-generation sequencing-based assays will only continue to increase. As such, there is an urgent need for health professional education to allow implementation of these new diagnostic tools. However, current medical school, residency and fellowship training has had limited success in educating physicians in the fundamentals of single gene testing let alone genomic methods. In this review, we describe the novel approach the pathology community has taken in genomic education and the potential for application to oncology trainees. PMID:24445771

  7. The causal effect of red blood cell folate on genome-wide methylation in cord blood: a Mendelian randomization approach.

    PubMed

    Binder, Alexandra M; Michels, Karin B

    2013-12-04

    Investigation of the biological mechanism by which folate acts to affect fetal development can inform appraisal of expected benefits and risk management. This research is ethically imperative given the ubiquity of folic acid fortified products in the US. Considering that folate is an essential component in the one-carbon metabolism pathway that provides methyl groups for DNA methylation, epigenetic modifications provide a putative molecular mechanism mediating the effect of folic acid supplementation on neonatal and pediatric outcomes. In this study we use a Mendelian Randomization Unnecessary approach to assess the effect of red blood cell (RBC) folate on genome-wide DNA methylation in cord blood. Site-specific CpG methylation within the proximal promoter regions of approximately 14,500 genes was analyzed using the Illumina Infinium Human Methylation27 Bead Chip for 50 infants from the Epigenetic Birth Cohort at Brigham and Women's Hospital in Boston. Using methylenetetrahydrofolate reductase genotype as the instrument, the Mendelian Randomization approach identified 7 CpG loci with a significant (mostly positive) association between RBC folate and methylation level. Among the genes in closest proximity to this significant subset of CpG loci, several enriched biologic processes were involved in nucleic acid transport and metabolic processing. Compared to the standard ordinary least squares regression method, our estimates were demonstrated to be more robust to unmeasured confounding. To the authors' knowledge, this is the largest genome-wide analysis of the effects of folate on methylation pattern, and the first to employ Mendelian Randomization to assess the effects of an exposure on epigenetic modifications. These results can help guide future analyses of the causal effects of periconceptional folate levels on candidate pathways.

  8. Redundant variables and Granger causality

    NASA Astrophysics Data System (ADS)

    Angelini, L.; de Tommaso, M.; Marinazzo, D.; Nitti, L.; Pellicoro, M.; Stramaglia, S.

    2010-03-01

    We discuss the use of multivariate Granger causality in presence of redundant variables: the application of the standard analysis, in this case, leads to under estimation of causalities. Using the un-normalized version of the causality index, we quantitatively develop the notions of redundancy and synergy in the frame of causality and propose two approaches to group redundant variables: (i) for a given target, the remaining variables are grouped so as to maximize the total causality and (ii) the whole set of variables is partitioned to maximize the sum of the causalities between subsets. We show the application to a real neurological experiment, aiming to a deeper understanding of the physiological basis of abnormal neuronal oscillations in the migraine brain. The outcome by our approach reveals the change in the informational pattern due to repetitive transcranial magnetic stimulations.

  9. Is ovarian hyperstimulation associated with higher blood pressure in 4-year-old IVF offspring? Part II: an explorative causal inference approach.

    PubMed

    La Bastide-Van Gemert, Sacha; Seggers, Jorien; Haadsma, Maaike L; Heineman, Maas Jan; Middelburg, Karin J; Roseboom, Tessa J; Schendelaar, Pamela; Hadders-Algra, Mijna; Van den Heuvel, Edwin R

    2014-03-01

    What causal relationships underlie the associations between ovarian stimulation, the IVF procedure, parental-, fertility- and child characteristics, and blood pressure (BP) and anthropometrics of 4-year-old IVF children? Causal models compatible with the data suggest the presence of positive direct effects of controlled ovarian hyperstimulation as applied in IVF (COH-IVF) on systolic blood pressure (SBP) percentiles and subscapular skinfold thickness. Increasing evidence suggests that IVF is associated with higher blood pressure and altered body fat distribution in offspring, but underlying mechanisms describing the causal relationships between the variables are largely unknown. In this assessor-blinded follow-up study, 194 children were assessed. The attrition rate until the 4-year-old assessment was 10%. We measured blood pressure and anthropometrics of 4-year-old singletons born following COH-IVF (n = 63), or born following modified natural cycle IVF (MNC-IVF, n = 52) or born to subfertile couples who conceived naturally (Sub-NC, n = 79). Primary outcome measures were the SBP and diastolic blood pressure (DBP) percentiles. Anthropometrics included triceps and subscapular skinfold thickness. Causal inference search algorithms and structural equation modeling were applied. Explorative analyses suggested a direct effect of COH on SBP percentiles and on subscapular skinfold thickness. This hypothesis needs confirmation with additional, preferably larger, studies. Search algorithms were used as explorative tools to generate hypotheses on the causal mechanisms underlying fertility treatment, blood pressure, anthropometrics and other variables. More studies using larger groups are needed to draw firm conclusions. Our findings are in line with other studies describing adverse effects of IVF on cardiometabolic outcome, but this is the first study suggesting a causal mechanism underlying this association. Perhaps ovarian hyperstimulation negatively influences

  10. [Rare Diseases: chronic diseases that need a new approach].

    PubMed

    Avellaneda, A; Izquierdo, M; Torrent-Farnell, J; Ramón, J R

    2007-01-01

    The concept of Rare Diseases is relatively new. They are those processes "...that can be mortal or to cause a chronic weakening of the patient and who, due to its little prevalence, require combined efforts to treat them. For indicative purposes, a little prevalence is considered when is lesser than 5 cases per 10,000 people in the Community". The existence of these diseases is closely tied with orphan drugs, meaning all drugs, prosthesis, biological agents or dietetic preparations destined to the treatment of a Rare Disease. Besides, it is necessary to add two factors more: 1. The Primary Attention physicians do not feel very motivated in their knowledge and 2. These diseases need a complex sociosanitary attention, habitually more expensive than chronic diseases. By all exposed the Rare Diseases appear like a universe that requires a new sociosanitary approach from the health system.

  11. Designing sustainable work systems: the need for a systems approach.

    PubMed

    Zink, Klaus J

    2014-01-01

    There is a growing discussion concerning sustainability. While this discussion was at first mainly focused on a society level--and sometimes regarding especially environmental problems, one can now see that this topic is of increasing relevance for companies worldwide and even the social dimension of this three pillar approach is gaining more and more importance. This leads to some questions: Is sustainability already a part of human factors thinking or do we have to further develop our discipline? How can we define sustainable work systems? What are the topics we have to consider? Do we need a new systems ergonomics perspective regarding whole value creation chains and a life-cycle perspective concerning products (and work systems)? How can we deal with potential contradictions about social, ecological, and economic goals? Copyright © 2013 Elsevier Ltd and The Ergonomics Society. All rights reserved.

  12. NRC says integrated approach needed to understand, protect environment

    NASA Astrophysics Data System (ADS)

    Kolb, Charles E.; Loehr, Raymond C.; Gopnik, Morgan

    A recent study by the National Research Council (NRC) advocates a more comprehensive and integrated approach to our nation's environmental research and development (R&D) activities. Because we face environmental problems of unprecedented complexity, the study maintains that the traditional practice of studying isolated environmental problems and devising narrowly focused control or remediation strategies to manage them will no longer suffice.In the report, Building a Foundation for Sound Environmental Decisions [National Academy Press, 1997], an NRC committee highlighted the need for developing a deeper scientific understanding of ecosystems, as well as the sociological and economic aspects of human interactions with the environment. To achieve these goals, the committee recommended a core research agenda for the Environmental Protection Agency (EPA) that has three components.

  13. Treatment Needs of Driving While Intoxicated Offenders: The Need for a Multimodal Approach to Treatment.

    PubMed

    Mullen, Jillian; Ryan, Stacy R; Mathias, Charles W; Dougherty, Donald M

    2015-01-01

    This study aimed to characterize and compare the treatment needs of adults with driving while intoxicated (DWI) offenders recruited from a correctional residential treatment facility and the community to provide recommendations for treatment development. A total of 119 adults (59 residential, 60 community) with at least one DWI offense were administered clinical diagnostic interviews to assess substance use disorders and completed a battery of questionnaires assessing demographic characteristics, legal history, psychiatric diagnoses, medical diagnoses, and health care utilization. Almost all (96.6%) DWI offenders met clinical diagnostic criteria for an alcohol use disorder, approximately half of the sample also met diagnostic criteria for comorbid substance use disorders, and a substantial proportion also reported psychiatric and medical comorbidities. However, a high percentage were not receiving treatment for these issues, most likely as a result of having limited access to care, because the majority of participants had no current health insurance (64.45%) or primary care physician (74.0%). The residential sample had more extensive criminal histories compared to the community sample but was generally representative of the community in terms of their clinical characteristics. For instance, the groups did not differ in rates of substance use, psychiatric and medical health diagnoses, or the treatment of such issues, with the exception of alcohol abuse treatment. DWI offenders represent a clinical population with high levels of complex and competing treatment needs that are not currently being met. Our findings demonstrate the need for standardized screening of DWI offenders and call for the development of a multimodal treatment approach in efforts to reduce recidivism.

  14. Polish spaces of causal curves

    NASA Astrophysics Data System (ADS)

    Miller, Tomasz

    2017-06-01

    We propose and study a new approach to the topologization of spaces of (possibly not all) future-directed causal curves in a stably causal spacetime. It relies on parametrizing the curves ;in accordance; with a chosen time function. Thus obtained topological spaces of causal curves are separable and completely metrizable, i.e. Polish. The latter property renders them particularly useful in the optimal transport theory. To illustrate this fact, we explore the notion of a causal time-evolution of measures in globally hyperbolic spacetimes and discuss its physical interpretation.

  15. Causal inference based on counterfactuals

    PubMed Central

    Höfler, M

    2005-01-01

    Background The counterfactual or potential outcome model has become increasingly standard for causal inference in epidemiological and medical studies. Discussion This paper provides an overview on the counterfactual and related approaches. A variety of conceptual as well as practical issues when estimating causal effects are reviewed. These include causal interactions, imperfect experiments, adjustment for confounding, time-varying exposures, competing risks and the probability of causation. It is argued that the counterfactual model of causal effects captures the main aspects of causality in health sciences and relates to many statistical procedures. Summary Counterfactuals are the basis of causal inference in medicine and epidemiology. Nevertheless, the estimation of counterfactual differences pose several difficulties, primarily in observational studies. These problems, however, reflect fundamental barriers only when learning from observations, and this does not invalidate the counterfactual concept. PMID:16159397

  16. Oral allergy syndrome--the need of a multidisciplinary approach.

    PubMed

    Kelava, Nikolina; Lugović-Mihić, Liborija; Duvancić, Tomislav; Romić, Renata; Situm, Mirna

    2014-06-01

    Oral allergy syndrome (OAS) is one of the most common types of food allergy. The syndrome includes itching and swelling of the lips, palate and tongue, usually after consuming fresh fruits and vegetables. The underlying pathogenic mechanism is cross-reactivity between IgE antibodies specific to pollen, and antigens in food, such as fresh fruits, vegetables and nuts that are structurally similar to pollen. Both pollen and food antigens can bind to IgE and trigger type I immune reaction. Diagnosis is primarily based on the patient's history, and confirmed by skin tests, in vitro tests, and oral provocation tests. Differential diagnoses include many diseases (such as burning mouth syndrome, angioedema, hay fever, various other oral diseases, etc.), and for this reason a multidisciplinary approach is necessary, as different specialists need to be involved in the diagnostic procedure. Therapy includes avoiding, or thermal processing of, fruit and vegetables known to trigger a reaction, and antihistamine medications. If a more severe anaphylactic reaction develops, more aggressive therapy is required. The goal of this article is to present OAS, its etiopathogenesis, clinical picture, and symptoms, diagnostic approach and therapy for OAS.

  17. Commentary on Causal Prescriptive Statements

    ERIC Educational Resources Information Center

    Graesser, Arthur C.; Hu, Xiangen

    2011-01-01

    Causal prescriptive statements are valued in the social sciences when there is the goal of helping people through interventions. The articles in this special issue cover different methods for testing causal prescriptive statements. This commentary identifies both virtues and liabilities of these different approaches. We argue that it is extremely…

  18. Commentary on Causal Prescriptive Statements

    ERIC Educational Resources Information Center

    Graesser, Arthur C.; Hu, Xiangen

    2011-01-01

    Causal prescriptive statements are valued in the social sciences when there is the goal of helping people through interventions. The articles in this special issue cover different methods for testing causal prescriptive statements. This commentary identifies both virtues and liabilities of these different approaches. We argue that it is extremely…

  19. Integrated approaches to climate–crop modelling: needs and challenges

    PubMed Central

    A. Betts, Richard

    2005-01-01

    This paper discusses the need for a more integrated approach to modelling changes in climate and crops, and some of the challenges posed by this. While changes in atmospheric composition are expected to exert an increasing radiative forcing of climate change leading to further warming of global mean temperatures and shifts in precipitation patterns, these are not the only climatic processes which may influence crop production. Changes in the physical characteristics of the land cover may also affect climate; these may arise directly from land use activities and may also result from the large-scale responses of crops to seasonal, interannual and decadal changes in the atmospheric state. Climate models used to drive crop models may, therefore, need to consider changes in the land surface, either as imposed boundary conditions or as feedbacks from an interactive climate–vegetation model. Crops may also respond directly to changes in atmospheric composition, such as the concentrations of carbon dioxide (CO2), ozone (O3) and compounds of sulphur and nitrogen, so crop models should consider these processes as well as climate change. Changes in these, and the responses of the crops, may be intimately linked with meteorological processes so crop and climate models should consider synergies between climate and atmospheric chemistry. Some crop responses may occur at scales too small to significantly influence meteorology, so may not need to be included as feedbacks within climate models. However, the volume of data required to drive the appropriate crop models may be very large, especially if short-time-scale variability is important. Implementation of crop models within climate models would minimize the need to transfer large quantities of data between separate modelling systems. It should also be noted that crop responses to climate change may interact with other impacts of climate change, such as hydrological changes. For example, the availability of water for

  20. A New Life-Span Approach to Conscientiousness and Health: Combining the Pieces of the Causal Puzzle

    ERIC Educational Resources Information Center

    Friedman, Howard S.; Kern, Margaret L.; Hampson, Sarah E.; Duckworth, Angela Lee

    2014-01-01

    Conscientiousness has been shown to predict healthy behaviors, healthy social relationships, and physical health and longevity. The causal links, however, are complex and not well elaborated. Many extant studies have used comparable measures for conscientiousness, and a systematic endeavor to build cross-study analyses for conscientiousness and…

  1. The Well-Being of Children Born to Teen Mothers: Multiple Approaches to Assessing the Causal Links. JCPR Working Paper.

    ERIC Educational Resources Information Center

    Levine, Judith A.; Pollack, Harold

    This study used linked maternal-child data from the 1997-1998 National Longitudinal Survey of Youth to explore the wellbeing of children born to teenage mothers. Two econometric techniques explored the causal impact of early childbearing on subsequent child and adolescent outcomes. First, a fixed-effect, cousin-comparison analysis controlled for…

  2. Exploring the relationship between child physical abuse and adult dating violence using a causal inference approach in an emerging adult population in South Korea.

    PubMed

    Jennings, Wesley G; Park, MiRang; Richards, Tara N; Tomsich, Elizabeth; Gover, Angela; Powers, Ráchael A

    2014-12-01

    Child maltreatment is one of the most commonly examined risk factors for violence in dating relationships. Often referred to as the intergenerational transmission of violence or cycle of violence, a fair amount of research suggests that experiencing abuse during childhood significantly increases the likelihood of involvement in violent relationships later, but these conclusions are primarily based on correlational research designs. Furthermore, the majority of research linking childhood maltreatment and dating violence has focused on samples of young people from the United States. Considering these limitations, the current study uses a rigorous, propensity score matching approach to estimate the causal effect of experiencing child physical abuse on adult dating violence among a large sample of South Korean emerging adults. Results indicate that the link between child physical abuse and adult dating violence is spurious rather than causal. Study limitations and implications are discussed.

  3. Nonprofit Hospitals’ Approach to Community Health Needs Assessment

    PubMed Central

    McLeroy, Kenneth R.; Burdine, James N.; Matarrita-Cascante, David

    2015-01-01

    Objectives. We sought a better understanding of how nonprofit hospitals are fulfilling the community health needs assessment (CHNA) provision of the 2010 Patient Protection and Affordable Care Act to conduct CHNAs and develop CHNA and implementation strategies reports. Methods. Through an Internet search of an estimated 179 nonprofit hospitals in Texas conducted between December 1, 2013, and January 5, 2014, we identified and reviewed 95 CHNA and implementation strategies reports. We evaluated and scored reports with specific criteria. We analyzed hospital-related and other report characteristics to understand relationships with report quality. Results. There was wide-ranging diversity in CHNA approaches and report quality. Consultant-led CHNA processes and collaboration with local health departments were associated with higher-quality reports. Conclusions. At the time of this study, the Internal Revenue Service had not yet issued the final regulations for the CHNA requirement. This provides an opportunity to strengthen the CHNA guidance for the final regulations, clarify the purpose of the assessment and planning process and reports, and better align assessment and planning activities through a public health framework. PMID:25602862

  4. Nonprofit hospitals' approach to community health needs assessment.

    PubMed

    Pennel, Cara L; McLeroy, Kenneth R; Burdine, James N; Matarrita-Cascante, David

    2015-03-01

    We sought a better understanding of how nonprofit hospitals are fulfilling the community health needs assessment (CHNA) provision of the 2010 Patient Protection and Affordable Care Act to conduct CHNAs and develop CHNA and implementation strategies reports. Through an Internet search of an estimated 179 nonprofit hospitals in Texas conducted between December 1, 2013, and January 5, 2014, we identified and reviewed 95 CHNA and implementation strategies reports. We evaluated and scored reports with specific criteria. We analyzed hospital-related and other report characteristics to understand relationships with report quality. There was wide-ranging diversity in CHNA approaches and report quality. Consultant-led CHNA processes and collaboration with local health departments were associated with higher-quality reports. At the time of this study, the Internal Revenue Service had not yet issued the final regulations for the CHNA requirement. This provides an opportunity to strengthen the CHNA guidance for the final regulations, clarify the purpose of the assessment and planning process and reports, and better align assessment and planning activities through a public health framework.

  5. Using a Team Approach When Mainstreaming Special Needs Students.

    ERIC Educational Resources Information Center

    Reed, Jack C.

    1987-01-01

    The author defines mainstreaming and discusses how business education teachers and special needs instructors can work as a team on instructional and materials adaptation to meet the special needs of students. (CH)

  6. A Systems Genetics Approach Implicates USF1, FADS3, and Other Causal Candidate Genes for Familial Combined Hyperlipidemia

    PubMed Central

    Plaisier, Christopher L.; Horvath, Steve; Huertas-Vazquez, Adriana; Cruz-Bautista, Ivette; Herrera, Miguel F.; Tusie-Luna, Teresa; Aguilar-Salinas, Carlos; Pajukanta, Päivi

    2009-01-01

    We hypothesized that a common SNP in the 3' untranslated region of the upstream transcription factor 1 (USF1), rs3737787, may affect lipid traits by influencing gene expression levels, and we investigated this possibility utilizing the Mexican population, which has a high predisposition to dyslipidemia. We first associated rs3737787 genotypes in Mexican Familial Combined Hyperlipidemia (FCHL) case/control fat biopsies, with global expression patterns. To identify sets of co-expressed genes co-regulated by similar factors such as transcription factors, genetic variants, or environmental effects, we utilized weighted gene co-expression network analysis (WGCNA). Through WGCNA in the Mexican FCHL fat biopsies we identified two significant Triglyceride (TG)-associated co-expression modules. One of these modules was also associated with FCHL, the other FCHL component traits, and rs3737787 genotypes. This USF1-regulated FCHL-associated (URFA) module was enriched for genes involved in lipid metabolic processes. Using systems genetics procedures we identified 18 causal candidate genes in the URFA module. The FCHL causal candidate gene fatty acid desaturase 3 (FADS3) was associated with TGs in a recent Caucasian genome-wide significant association study and we replicated this association in Mexican FCHL families. Based on a USF1-regulated FCHL-associated co-expression module and SNP rs3737787, we identify a set of causal candidate genes for FCHL-related traits. We then provide evidence from two independent datasets supporting FADS3 as a causal gene for FCHL and elevated TGs in Mexicans. PMID:19750004

  7. Treating to Protect: Current Cardiovascular Treatment Approaches and Remaining Needs

    PubMed Central

    Böhm, Michael; Werner, Christian

    2008-01-01

    Current best practice to reduce cardiovascular disease involves evaluating patients' global cardiovascular risk profiles and devising treatment strategies accordingly. Despite the proven efficacy of this approach, very few physicians are adequately assessing risk, and consequently patients are failing to achieve desired treatment targets. Modifying lifestyle factors, such as diet, exercise, and cessation of smoking, remains one of the simplest and most potent means of reducing risk. Newly emerging evidence suggests that moderate physical activity (such as brisk walking for 30 minutes a day), eg, by raising levels of circulating endothelial progenitor cells, improves endothelial function and enhances vascular repair. However, patients remain remarkably reluctant to lifestyle changes, even in the face of overt, life-threatening disease. Statin treatment reduces cardiovascular morbidity and death in both primary and secondary prevention studies. However, over 90% of adults at high risk for coronary heart disease fail to achieve target low-density lipoprotein cholesterol levels in spite of statin therapy. Similarly, only about 37% of patients with hypertension meet blood pressure targets. Antihypertensive drugs achieve different levels of cardioprotection. Mounting evidence links regimens containing beta-blockers or diuretics with higher incidence of type 2 diabetes. In contrast, angiotensin-converting enzyme inhibitors and angiotensin receptor blockers appear to confer extra protection on target organs on top of blood pressure reduction. The ONTARGET Trial Program is designed to clarify the importance of this effect. Educating patients, raising physicians' awareness, and implementing effective and safe treatment regimens are all necessary steps to bring about the much-needed improvements in cardiac health outcomes. PMID:18449384

  8. Towards an Algebra for Analyzing Causal Relations.

    ERIC Educational Resources Information Center

    Ellett, Frederick S., Jr.; Ericson, David P.

    Correlation-based approaches to causal analysis contain too much irrelevant information that masks and modulates the true nature of causal processes in the world. Both causal modeling and path analysis/structural equations give the wrong answers for certain conceptions of causation, given certain assumptions about the "error" variables.…

  9. The effects of informal carers' characteristics on their information needs: The information needs state approach.

    PubMed

    Alzougool, Basil; Chang, Shanton; Gray, Kathleen

    2017-09-01

    There has been little research that provides a comprehensive account of the nature and aspects of information needs of informal carers. The authors have previously developed and validated a framework that accounts for major underlying states of information need. This paper aims to apply this framework to explore whether there are common demographic and socioeconomic characteristics that affect the information needs states of carers. A questionnaire about the information needs states was completed by 198 carers above 18 years old. We use statistical methods to look for similarities and differences in respondents' information needs states, in terms of the demographic and socioeconomic variables. At least one information needs state varies among carers, in terms of seven demographic and socioeconomic variables: the age of the patient(s) that they are caring for; the condition(s) of the patient(s) that they are caring for; the number of patients that they are caring for; their length of time as a carer; their gender; the country that they live in; and the population of the area that they live in. The findings demonstrate the utility of the information needs state framework. We outline some practical implications of the framework.

  10. Meeting the Needs of LGBTQ Youth: A "Relational Assets" Approach

    ERIC Educational Resources Information Center

    Sadowski, Michael; Chow, Stephen; Scanlon, Constance P.

    2009-01-01

    Drawing primarily on three case studies, this article proposes a framework that those concerned about the welfare of lesbian, gay, bisexual, transgender, queer, and questioning (LGBTQ) youth can consider when developing, evaluating, or arguing for more effective programming: a relational assets approach. The relational assets approach merges the…

  11. Meeting the Needs of LGBTQ Youth: A "Relational Assets" Approach

    ERIC Educational Resources Information Center

    Sadowski, Michael; Chow, Stephen; Scanlon, Constance P.

    2009-01-01

    Drawing primarily on three case studies, this article proposes a framework that those concerned about the welfare of lesbian, gay, bisexual, transgender, queer, and questioning (LGBTQ) youth can consider when developing, evaluating, or arguing for more effective programming: a relational assets approach. The relational assets approach merges the…

  12. The Power of Behavioural Approaches--We Need a Revival

    ERIC Educational Resources Information Center

    Buckley, Sue

    2008-01-01

    Behavioural approaches can be used effectively to teach new skills and to change behaviours that are challenging and not socially adaptive. The behaviour modification approach--now called applied behaviour analysis--is based on the assumption that all behaviours are learned, both the useful ones (new skills) and the ones that are not so useful…

  13. Financial Planning for Information Technology: Conventional Approaches Need Not Apply.

    ERIC Educational Resources Information Center

    Falduto, Ellen F.

    1999-01-01

    Rapid advances in information technology have rendered conventional approaches to planning and budgeting useless, and no single method is universally appropriate. The most successful planning efforts are consistent with the institution's overall plan, and may combine conventional, opportunistic, and entrepreneurial approaches. Chief financial…

  14. Scalar Matter Coupled to Quantum Gravity in the Causal Approach. One-Loop Calculations and Perturbative Gauge Invariance

    NASA Astrophysics Data System (ADS)

    Grillo, Nicola

    2001-02-01

    Quantum gravity coupled to scalar massive matter fields is investigated in the framework of causal perturbation theory using the Epstein-Glaser regularization/renormalization scheme. Detailed one-loop calculations include the matter loop graviton self-energy and the matter self-energy. The condition of perturbative operator gauge invariance to second order implies the usual Slavnov-Ward identities for the graviton two-point connected Green function in the loop graph sector and generates the correct quartic graviton-matter interaction in the tree graph sector. The mass zero case is also discussed.

  15. Culture, needs and nursing: a critical theory approach.

    PubMed

    Holmes, C A; Warelow, P J

    1997-03-01

    This paper will bring the critique of culture, notably that undertaken by the Frankfurt School of Critical Social Science, to bear on the problem of needs, and expose its significance for the practice and discipline of nursing. The paper begins by reviewing ways in which the idea of 'needs' has been depicted in nursing literature, and it is suggested that this depiction is inadequate in fundamental ways. The critique of existing culture is then outlined and the implications for nursing are suggested in terms of the dissolution of hegemonic practices and the development of a concept of need built around the notion of 'praxis'.

  16. An Approach to Meeting Managements Needs for Financial Information

    ERIC Educational Resources Information Center

    Norberg, Douglas; Spilka, Leonard S.

    1973-01-01

    A discussion of the Automated Management Planning and Controls System (AMPACS) that is being designed for public television stations in order to provide much needed timely and complete information upon which management can base its decisions. (Author/HB)

  17. Fourth Generation Warfare: The Need for a Comprehensive Approach

    DTIC Science & Technology

    2008-08-25

    to unity of effort. This ad- hoc structure eventually evolved into its final organizational structure of CORDS that gave the needed unity of effort...war on terrorism. 57 The document also recognizes shortfalls in the organizational structure between the Department of Defense, the Department of...or Geographic Combatant Commands depending on the point of view. Though this organizational structure has worked thus far, it may need adjustments to

  18. A new approach to assessing skill needs of senior managers.

    PubMed

    Griffith, John R; Warden, Gail L; Neighbors, Kamilah; Shim, Beth

    2002-01-01

    Management of health care organizations must improve to meet the well-documented challenges of quality improvement and cost control. Other industries have developed the tools--entry education, mentoring, planned mid-career formal education and experience, and special programs for senior management. The purpose of this paper is to pilot test an alternative method to identify competencies and performance of health care executives. We propose using formal lists of technical, interpersonal, and strategic competencies and specific real events chosen by the respondent to identify and prioritize competencies. Results of a trial with 30 large health care system CEOs and 15 early careerists demonstrate that the method reveals useful depth and detail about managers' educational needs. The results suggest that current thinking about managerial education and learning patterns may be seriously inadequate in several respects. The continued improvement of U.S. health care is a pressing national concern. Quality of care is highly variable and substantially deficient in many institutions (Chassin and Galvin 1998; Committee on Quality of Health Care in America 2001). "Quality improvement should be the essential business strategy for healthcare in the 21st century (Kizer 2001)." Productivity improvements will be essential to balance cost pressures from an aging population and growing technology (Heffler, et al. 2002). Skillful management is necessary to improve quality and productivity. Teams of dozens of caregivers are often required to improve a patient's health. The organizations that provide care have grown larger in response to the greater cost, complexity of operation and finance, and evidence of the success of scale in other industries. While many small professional practices, hospitals, and nursing homes remain, consolidation has created a few dozen provider and intermediary organizations exceeding a billion dollars a year in expenditures. These large health care

  19. Investigating the effect of external trauma through a dynamic system modeling approach for clustering causality in diabetic foot ulcer development.

    PubMed

    Salimi, Parisa; Hamedi, Mohsen; Jamshidi, Nima; Vismeh, Milad

    2017-04-01

    Diabetes and its associated complications are realized as one of the most challenging medical conditions threatening more than 29 million people only in the USA. The forecasts suggest a suffering of more than half a billion worldwide by 2030. Amid all diabetic complications, diabetic foot ulcer (DFU) has attracted much scientific investigations to lead to a better management of this disease. In this paper, a system thinking methodology is adopted to investigate the dynamic nature of the ulceration. The causal loop diagram as a tool is utilized to illustrate the well-researched relations and interrelations between causes of the DFU. The result of clustering causality evaluation suggests a vicious loop that relates external trauma to callus. Consequently a hypothesis is presented which localizes development of foot ulceration considering distribution of normal and shear stress. It specifies that normal and tangential forces, as the main representatives of external trauma, play the most important role in foot ulceration. The evaluation of this hypothesis suggests the significance of the information related to both normal and shear stress for managing DFU. The results also discusses how these two react on different locations on foot such as metatarsal head, heel and hallux. The findings of this study can facilitate tackling the complexity of DFU problem and looking for constructive mitigation measures. Moreover they lead to developing a more promising methodology for managing DFU including better prognosis, designing prosthesis and insoles for DFU and patient caring recommendations. Copyright © 2017 Elsevier Ltd. All rights reserved.

  20. We need theoretical physics approaches to study living systems

    NASA Astrophysics Data System (ADS)

    Blagoev, Krastan B.; Shukla, Kamal; affil="3" >Herbert Levine,

    2013-08-01

    , nor collect data on the kinetics of the many complex reactions. Instead, the focus was on formulating two- or three-component reaction-diffusion equations (e.g. the Oregonator), which could explain such generic features as the existence of rotating spiral waves (and their instability), the transition to chaos, the control of the reaction by light etc. By stressing mechanism instead of meticulous detail, one could understand the system even if there were still components and interactions waiting to be cataloged and quantified. In living systems, this way of thinking is even more crucial. A leading biologist once remarked to one of us that a calculation of in vivo cytoskeletal dynamics that did not take into account the fact that the particular cell in question had more than ten isoforms of actin could not possibly be correct. We need to counter that any calculation which takes into account all these isoforms is overwhelmingly likely to be vastly under-constrained and ultimately not useful. Adding more details can often bring us further from reality. Of course, the challenge for models is then falsification, i.e., finding robust predictions which can be directly tested experimentally. The most severe criticism, to quote Pauli, remains that 'your model is not even wrong.' Is this approach proving successful? In many cases it is too early to tell, but simple models have already proved useful in understanding protein folding, directed cell motility, gene expression variability and even laboratory-scale Darwinian evolution. One could argue as well that the extremely influential Hodgkin-Huxley approach to the action potential in neurons is a vastly oversimplified description and that is why it is tractable and compelling. There are other cases, however, where the model was too simple—the simple Turing instability does not account for Drosophila segment formation [2] and the binary state relaxational dynamics of the Hopfield model may prove incapable of explaining memory

  1. Causality links among renewable energy consumption, CO2 emissions, and economic growth in Africa: evidence from a panel ARDL-PMG approach.

    PubMed

    Attiaoui, Imed; Toumi, Hassen; Ammouri, Bilel; Gargouri, Ilhem

    2017-04-05

    This research examines the causality (For the remainder of the paper, the notion of causality refers to Granger causality.) links among renewable energy consumption (REC), CO2 emissions (CE), non-renewable energy consumption (NREC), and economic growth (GDP) using an autoregressive distributed lag model based on the pooled mean group estimation (ARDL-PMG) and applying Granger causality tests for a panel consisting of 22 African countries for the period between 1990 and 2011. There is unidirectional and irreversible short-run causality from CE to GDP. The causal direction between CE and REC is unobservable over the short-term. Moreover, we find unidirectional, short-run causality from REC to GDP. When testing per pair of variables, there are short-run bidirectional causalities among REC, CE, and GDP. However, if we add CE to the variables REC and NREC, the causality to GDP is observable, and causality from the pair REC and NREC to economic growth is neutral. Likewise, if we add NREC to the variables GDP and REC, there is causality. There are bidirectional long-run causalities among REC, CE, and GDP, which supports the feedback assumption. Causality from GDP to REC is not strong for the panel. If we test per pair of variables, the strong causality from GDP and CE to REC is neutral. The long-run PMG estimates show that NREC and gross domestic product increase CE, whereas REC decreases CE.

  2. Estimating physician requirements for neurology: a needs-based approach.

    PubMed

    Garrison, L P; Bowman, M A; Perrin, E B

    1984-09-01

    Applying the adjusted needs-based model developed by the Graduate Medical Education National Advisory Committee (GMENAC), physician requirements in neurology were estimated for the year 1990. A Delphi panel of physician experts estimated appropriate patterns of treatment for 56 neurologic conditions. Their median estimates implied a need for 14,500 neurologists in 1990, suggesting a shortage relative to the projected supply. An advisory panel of former GMENAC members reviewed those estimates and recommended certain adjustments to ensure internal consistency and compatibility with those for other specialties. Adoption of these adjustments significantly reduces requirements, implying a total need for 8,400 neurologists--a figure in near balance with the projected supply of 8,650. The difference between the Delphi and Advisory Panel estimates reflects divergent views, apparent as well among the Delphi panelists, of the appropriate role of neurologists--consultants versus principal care providers.

  3. A Theoretical Approach to Information Needs Across Different Healthcare Stakeholders

    NASA Astrophysics Data System (ADS)

    Raitoharju, Reetta; Aarnio, Eeva

    Increased access to medical information can lead to information overload among both the employees in the healthcare sector as well as among healthcare consumers. Moreover, medical information can be hard to understand for consumers who have no prerequisites for interpreting and understanding it. Information systems (e.g. electronic patient records) are normally designed to meet the demands of one professional group, for instance those of physicians. Therefore, the same information in the same form is presented to all the users of the systems regardless of the actual need or prerequisites. The purpose of this article is to illustrate the differences in information needs across different stakeholders in healthcare. A literature review was conducted to collect examples of these different information needs. Based on the findings the role of more user specific information systems is discussed.

  4. The Substance Abuse Counseling Needs of Women in the Criminal Justice System: A Needs Assessment Approach

    ERIC Educational Resources Information Center

    Laux, John M.; Dupuy, Paula J.; Moe, Jeffry L.; Cox, Jane A.; Lambert, Eric; Ventura, Lois A.; Williamson, Celia; Benjamin, Barbaranne J.

    2008-01-01

    The authors assessed the substance abuse counseling needs of women in the criminal justice system using interviews (n = 304) and surveys (n = 1,170). On the basis of the results, the authors call for gender-specific treatment as well as family-oriented support for women who are mothers.

  5. The Substance Abuse Counseling Needs of Women in the Criminal Justice System: A Needs Assessment Approach

    ERIC Educational Resources Information Center

    Laux, John M.; Dupuy, Paula J.; Moe, Jeffry L.; Cox, Jane A.; Lambert, Eric; Ventura, Lois A.; Williamson, Celia; Benjamin, Barbaranne J.

    2008-01-01

    The authors assessed the substance abuse counseling needs of women in the criminal justice system using interviews (n = 304) and surveys (n = 1,170). On the basis of the results, the authors call for gender-specific treatment as well as family-oriented support for women who are mothers.

  6. Academic Writing Task Surveys: The Need for a Fresh Approach.

    ERIC Educational Resources Information Center

    Braine, George

    1988-01-01

    A study investigated whether the academic writing task surveys conducted at American universities reflect accurately the need for student academic writing skills. These surveys are used as a basis for designing composition courses for both native English-speakers and students of English as a second language. The study is restricted to surveys in…

  7. Complex vestibular macular anatomical relationships need a synthetic approach

    NASA Technical Reports Server (NTRS)

    Ross, M. D.

    2001-01-01

    Mammalian vestibular maculae are anatomically organized for complex parallel processing of linear acceleration information. Anatomical findings in rat maculae are provided in order to underscore this complexity, which is little understood functionally. This report emphasizes that a synthetic approach is critical to understanding how maculae function and the kind of information they conduct to the brain.

  8. Using a Team Approach to Meet Complex Family Needs

    ERIC Educational Resources Information Center

    Njorge, Wanijiku F. M.

    2011-01-01

    Mental health clinicians who work with families with infants and toddlers often face complex challenges that require collaboration among many professionals and disciplines. A team approach to addressing infant mental health is critical to successful intervention. In this articles, a fractured family dealing with interpersonal violence and maternal…

  9. Complex vestibular macular anatomical relationships need a synthetic approach

    NASA Technical Reports Server (NTRS)

    Ross, M. D.

    2001-01-01

    Mammalian vestibular maculae are anatomically organized for complex parallel processing of linear acceleration information. Anatomical findings in rat maculae are provided in order to underscore this complexity, which is little understood functionally. This report emphasizes that a synthetic approach is critical to understanding how maculae function and the kind of information they conduct to the brain.

  10. Using a Team Approach to Meet Complex Family Needs

    ERIC Educational Resources Information Center

    Njorge, Wanijiku F. M.

    2011-01-01

    Mental health clinicians who work with families with infants and toddlers often face complex challenges that require collaboration among many professionals and disciplines. A team approach to addressing infant mental health is critical to successful intervention. In this articles, a fractured family dealing with interpersonal violence and maternal…

  11. Respiratory sensitization and allergy: Current research approaches and needs

    SciTech Connect

    Boverhof, Darrell R. Billington, Richard; Gollapudi, B. Bhaskar; Hotchkiss, John A.; Krieger, Shannon M.; Poole, Alan; Wiescinski, Connie M.; Woolhiser, Michael R.

    2008-01-01

    There are currently no accepted regulatory models for assessing the potential of a substance to cause respiratory sensitization and allergy. In contrast, a number of models exist for the assessment of contact sensitization and allergic contact dermatitis (ACD). Research indicates that respiratory sensitizers may be identified through contact sensitization assays such as the local lymph node assay, although only a small subset of the compounds that yield positive results in these assays are actually respiratory sensitizers. Due to the increasing health concerns associated with occupational asthma and the impending directives on the regulation of respiratory sensitizers and allergens, an approach which can identify these compounds and distinguish them from contact sensitizers is required. This report discusses some of the important contrasts between respiratory allergy and ACD, and highlights several prominent in vivo, in vitro and in silico approaches that are being applied or could be further developed to identify compounds capable of causing respiratory allergy. Although a number of animal models have been used for researching respiratory sensitization and allergy, protocols and endpoints for these approaches are often inconsistent, costly and difficult to reproduce, thereby limiting meaningful comparisons of data between laboratories and development of a consensus approach. A number of emerging in vitro and in silico models show promise for use in the characterization of contact sensitization potential and should be further explored for their ability to identify and differentiate contact and respiratory sensitizers. Ultimately, the development of a consistent, accurate and cost-effective model will likely incorporate a number of these approaches and will require effective communication, collaboration and consensus among all stakeholders.

  12. Technology Development Roadmaps - a Systematic Approach to Maturing Needed Technologies

    SciTech Connect

    John W. Colllins; Layne Pincock

    2010-07-01

    Abstract. Planning and decision making represent important challenges for all projects. This paper presents the steps needed to assess technical readiness and determine the path forward to mature the technologies required for the Next Generation Nuclear Plant. A Technology Readiness Assessment is used to evaluate the required systems, subsystems, and components (SSC) comprising the desired plant architecture and assess the SSCs against established Technology Readiness Levels (TRLs). A validated TRL baseline is then established for the proposed physical design. Technology Development Roadmaps are generated to define the path forward and focus project research and development and engineering tasks on advancing the technologies to increasing levels of maturity. Tasks include modeling, testing, bench-scale demonstrations, pilot-scale demonstrations, and fully integrated prototype demonstrations. The roadmaps identify precise project objectives and requirements; create a consensus vision of project needs; provide a structured, defensible, decision-based project plan; and, minimize project costs and schedules.

  13. Why health care corruption needs a new approach.

    PubMed

    Radin, Dagmar

    2016-07-01

    While corruption has been at the center of academic studies and on the agenda of international organizations for a couple of decades, in the health care sector corruption has not generated much interest or progress. At the centre of this issue is the lack of an interdisciplinary approach, which is warranted given the complexity of the issue and the lack of cooperation between STET scientifically rigorous academics and policy-makers, leaving room for more cooperation and progress.

  14. Hygiene and health - the need for a holistic approach.

    PubMed

    Exner, M; Hartemann, P; Kistemann, T

    2001-08-01

    The holistic principles of hygiene and public health have contributed substantially to an increase in life expectancy by more than 30 years and in life quality since the beginning of the 20th century. Frank, Pettenkofer, Nightingale, Pasteur, Lister, and Koch have been pioneering protagonists of the holistic approach to hygiene and public health. Socioeconomic development and related factors such as nutrition status and food hygiene, housing conditions, water supply and sewage systems, and education (including motivation for personal hygiene) have obviously been of more importance for life expectancy and life quality than progress in curative medicine, such as availability of microbial diagnosis, vaccination, and antibiotics. Today, new risk factors for infectious diseases arise, even in developed countries. These risk factors arise from emerging pathogens, antibiotic-resistant microorganisms, changing demographic patterns, an increasing amount of ambulatory and home care, socioeconomic and environmental changes, technical environments, worldwide distribution of food, and changing human behavior with a decreased awareness of microbial threats. These new challenges worldwide make a renewal of the holistic approach of hygiene and public health both urgent and necessary. On the basis of historic experience, policies that focus on surveillance and control, diagnosis, and therapy only can be assumed to be both insufficient and inefficient in controlling the new challenges in infectious diseases. Experiences in Germany with a holistic hospital hygiene strategy since 1976 provide encouragement for the promotion of holistic health concepts. Risk assessment, risk management, and risk communication are basic steps of a modern holistic strategy. Hygiene has the potential to act as a moderator of diverging positions of different disciplines within this renewed approach.

  15. Analytical Approaches to Verify Food Integrity: Needs and Challenges.

    PubMed

    Stadler, Richard H; Tran, Lien-Anh; Cavin, Christophe; Zbinden, Pascal; Konings, Erik J M

    2016-09-01

    A brief overview of the main analytical approaches and practices to determine food authenticity is presented, addressing, as well, food supply chain and future requirements to more effectively mitigate food fraud. Food companies are introducing procedures and mechanisms that allow them to identify vulnerabilities in their food supply chain under the umbrella of a food fraud prevention management system. A key step and first line of defense is thorough supply chain mapping and full transparency, assessing the likelihood of fraudsters to penetrate the chain at any point. More vulnerable chains, such as those where ingredients and/or raw materials are purchased through traders or auctions, may require a higher degree of sampling, testing, and surveillance. Access to analytical tools is therefore pivotal, requiring continuous development and possibly sophistication in identifying chemical markers, data acquisition, and modeling. Significant progress in portable technologies is evident already today, for instance, as in the rapid testing now available at the agricultural level. In the near future, consumers may also have the ability to scan products in stores or at home to authenticate labels and food content. For food manufacturers, targeted analytical methods complemented by untargeted approaches are end control measures at the factory gate when the material is delivered. In essence, testing for food adulterants is an integral part of routine QC, ideally tailored to the risks in the individual markets and/or geographies or supply chains. The development of analytical methods is a first step in verifying the compliance and authenticity of food materials. A next, more challenging step is the successful establishment of global consensus reference methods as exemplified by the AOAC Stakeholder Panel on Infant Formula and Adult Nutritionals initiative, which can serve as an approach that could also be applied to methods for contaminants and adulterants in food. The food

  16. The Need for Integrated Approaches in Metabolic Engineering

    DOE PAGES

    Lechner, Anna; Brunk, Elizabeth; Keasling, Jay D.

    2016-08-15

    Highlights include state-of-the-art procedures for heterologous small-molecule biosynthesis, the associated bottlenecks, and new strategies that have the potential to accelerate future accomplishments in metabolic engineering. A combination of different approaches over multiple time and size scales must be considered for successful pathway engineering in a heterologous host. We have classified these optimization procedures based on the “system” that is being manipulated: transcriptome, translatome, proteome, or reactome. Here, by bridging multiple disciplines, including molecular biology, biochemistry, biophysics, and computational sciences, we can create an integral framework for the discovery and implementation of novel biosynthetic production routes.

  17. Sickle cell anaemia: The need for new approaches in management.

    PubMed

    Ghosh, Kanjaksha

    2015-01-01

    Sickle cell anaemia is an important genetic disorder in India and is associated with considerable morbidity and mortality. Over 100 000 people are affected by this disorder and 10%-40% of the 85 million tribal population carries this gene. Conventional management and therapy with hydroxyurea provides symptomatic relief. A search for an anti-sickling agent has so far proved unsuccessful. However, improving upon existing compounds; looking for newer products using modern tools of bioinformatics, monoclonal antibody and aptamer technology; and evaluating medicines from ethno-pharmacology are promising approaches in managing this disease.

  18. Causal reasoning with forces

    PubMed Central

    Wolff, Phillip; Barbey, Aron K.

    2015-01-01

    Causal composition allows people to generate new causal relations by combining existing causal knowledge. We introduce a new computational model of such reasoning, the force theory, which holds that people compose causal relations by simulating the processes that join forces in the world, and compare this theory with the mental model theory (Khemlani et al., 2014) and the causal model theory (Sloman et al., 2009), which explain causal composition on the basis of mental models and structural equations, respectively. In one experiment, the force theory was uniquely able to account for people's ability to compose causal relationships from complex animations of real-world events. In three additional experiments, the force theory did as well as or better than the other two theories in explaining the causal compositions people generated from linguistically presented causal relations. Implications for causal learning and the hierarchical structure of causal knowledge are discussed. PMID:25653611

  19. Expectations and Interpretations During Causal Learning

    PubMed Central

    Luhmann, Christian C.; Ahn, Woo-kyoung

    2012-01-01

    In existing models of causal induction, 4 types of covariation information (i.e., presence/absence of an event followed by presence/absence of another event) always exert identical influences on causal strength judgments (e.g., joint presence of events always suggests a generative causal relationship). In contrast, we suggest that, due to expectations developed during causal learning, learners give varied interpretations to covariation information as it is encountered and that these interpretations influence the resulting causal beliefs. In Experiments 1A–1C, participants’ interpretations of observations during a causal learning task were dynamic, expectation based, and, furthermore, strongly tied to subsequent causal judgments. Experiment 2 demonstrated that adding trials of joint absence or joint presence of events, whose roles have been traditionally interpreted as increasing causal strengths, could result in decreased overall causal judgments and that adding trials where one event occurs in the absence of another, whose roles have been traditionally interpreted as decreasing causal strengths, could result in increased overall causal judgments. We discuss implications for traditional models of causal learning and how a more top-down approach (e.g., Bayesian) would be more compatible with the current findings. PMID:21534705

  20. Analyzing Information Flow in Brain Networks with Nonparametric Granger Causality

    PubMed Central

    Dhamala, Mukeshwar; Rangarajan, Govindan; Ding, Mingzhou

    2009-01-01

    Multielectrode neurophysiological recording and high-resolution neuroimaging generate multivariate data that are the basis for understanding the patterns of neural interactions. How to extract directions of information flow in brain networks from these data remains a key challenge. Research over the last few years has identified Granger causality as a statistically principled technique to furnish this capability. The estimation of Granger causality currently requires autoregressive modeling of neural data. Here, we propose a nonparametric approach based on widely used Fourier and wavelet transforms to estimate Granger causality, eliminating the need of explicit autoregressive data modeling. We demonstrate the effectiveness of this approach by applying it to synthetic data generated by network models with known connectivity and to local field potentials recorded from monkeys performing a sensorimotor task. PMID:18394927

  1. Analyzing information flow in brain networks with nonparametric Granger causality.

    PubMed

    Dhamala, Mukeshwar; Rangarajan, Govindan; Ding, Mingzhou

    2008-06-01

    Multielectrode neurophysiological recording and high-resolution neuroimaging generate multivariate data that are the basis for understanding the patterns of neural interactions. How to extract directions of information flow in brain networks from these data remains a key challenge. Research over the last few years has identified Granger causality as a statistically principled technique to furnish this capability. The estimation of Granger causality currently requires autoregressive modeling of neural data. Here, we propose a nonparametric approach based on widely used Fourier and wavelet transforms to estimate both pairwise and conditional measures of Granger causality, eliminating the need of explicit autoregressive data modeling. We demonstrate the effectiveness of this approach by applying it to synthetic data generated by network models with known connectivity and to local field potentials recorded from monkeys performing a sensorimotor task.

  2. Workforce Development: A Survey of Industry Needs and Training Approaches

    SciTech Connect

    Ventre, Jerry; Weissman, Jane

    2009-04-01

    This paper presents information and data collected during 2008 on PV workforce needs by the Interstate Renewable Energy Council for the U.S. Department of Energy. The data was collected from licensed contractors, PV practitioners, educators and expert instructors at training sessions, and at focus group and advisory committee meetings. Respondents were primarily from three states: Florida, New York and California. Other states were represented, but to a lesser extent. For data collection, a 12-item questionnaire was developed that addressed key workforce development issues from the perspectives of both the PV industry and training institutions. A total of 63 responses were collected, although not every respondent answered every question. Industry representatives slightly outnumbered the educators, although the difference in responses was not significant.

  3. Surgical approach to retrosternal goitre: do we still need sternotomy?

    PubMed

    Rugiu, M G; Piemonte, M

    2009-12-01

    Retrosternal goitre is defined as a goitre with a portion of its mass > or = 50% located in the mediastinum. Surgical removal is the treatment of choice and, in most cases, the goitre can be removed via a cervical approach. Aim of this retrospective study was to analyse personal experience in the surgical management of retrosternal goitres, defining, in particular, the features requiring sternotomy. Over a 5-year period (2004-2008), 986 patients underwent thyroidectomy in the ENT Department of the University Hospital of Udine, Italy; in 53 patients, 37 females, 16 males (mean age: 64 years, range: 35-85), thyroidectomy was performed for a retrosternal goitre, which extended, at computed tomography at least 3 cm below the cervico-thoracic isthmus. Retrosternal goitres were removed via a cervical approach in 49 patients; a sternotomy was necessary in 4 patients (7.5%), due to an ectopic intra-thoracic thyroid in one patient, and a very large thyroid reaching the main bronchial bifurcation in the other 3 (mean weight of goitres: 883 g, range: 520-1600). Histo-pathological studies revealed a benign lesion in 50 patients and a carcinoma in 2 (3.7%). The incidence of transient and permanent hypoparathyroidism was 13% and 3.7%, respectively. Transient recurrent laryngeal nerve palsy occurred in one patient (1.8%), post-operative bleeding in 3 patients (5.6%) and respiratory complications, requiring a tracheotomy in one case, in 2 patients (3.7%). Surgical removal of a retrosternal goitre is a challenging procedure; it can be performed safely, in most cases, via a cervical approach, with a complication rate slightly higher than the average rate for cervical goitre thyroidectomy, especially concerning hypoparathyroidism and post-operative bleeding. The most significant criteria for selecting patients requiring sternotomy are computed tomography features, in particular the presence of an ectopic goitre, the thyroid gland volume and the extent of the goitre to or below the

  4. Causal pathways linking Farm to School to childhood obesity prevention.

    PubMed

    Joshi, Anupama; Ratcliffe, Michelle M

    2012-08-01

    Farm to School programs are rapidly gaining attention as a potential strategy for preventing childhood obesity; however, the causal linkages between Farm to School activities and health outcomes are not well documented. To capitalize on the increased interest in and momentum for Farm to School, researchers and practitioners need to move from developing and implementing evidence informed programs and policies to ones that are evidence-based. The purpose of this article is to outline a framework for facilitating an evidence base for Farm to School programs and policies through a systematic and coordinated approach. Employing the concepts of causal pathways, the authors introduce a proposed framework for organizing and systematically testing out multiple hypotheses (or potential causal links) for how, why, and under what conditions Farm to School Inputs and Activities may result in what Outputs, Effects, and Impacts. Using the causal pathways framework may help develop and test competing hypotheses, identify multicausality, strength, and interactions of causes, and discern the difference between catalysts and causes. In this article, we introduce causal pathways, present menus of potential independent and dependent variables from which to create and test causal pathways linking Farm to School interventions and their role in preventing childhood obesity, discuss their applicability to Farm to School research and practice, and outline proposed next steps for developing a coordinated research framework for Farm to School programs.

  5. Causal Responsibility and Counterfactuals

    PubMed Central

    Lagnado, David A; Gerstenberg, Tobias; Zultan, Ro'i

    2013-01-01

    How do people attribute responsibility in situations where the contributions of multiple agents combine to produce a joint outcome? The prevalence of over-determination in such cases makes this a difficult problem for counterfactual theories of causal responsibility. In this article, we explore a general framework for assigning responsibility in multiple agent contexts. We draw on the structural model account of actual causation (e.g., Halpern & Pearl, 2005) and its extension to responsibility judgments (Chockler & Halpern, 2004). We review the main theoretical and empirical issues that arise from this literature and propose a novel model of intuitive judgments of responsibility. This model is a function of both pivotality (whether an agent made a difference to the outcome) and criticality (how important the agent is perceived to be for the outcome, before any actions are taken). The model explains empirical results from previous studies and is supported by a new experiment that manipulates both pivotality and criticality. We also discuss possible extensions of this model to deal with a broader range of causal situations. Overall, our approach emphasizes the close interrelations between causality, counterfactuals, and responsibility attributions. PMID:23855451

  6. Causal responsibility and counterfactuals.

    PubMed

    Lagnado, David A; Gerstenberg, Tobias; Zultan, Ro'i

    2013-08-01

    How do people attribute responsibility in situations where the contributions of multiple agents combine to produce a joint outcome? The prevalence of over-determination in such cases makes this a difficult problem for counterfactual theories of causal responsibility. In this article, we explore a general framework for assigning responsibility in multiple agent contexts. We draw on the structural model account of actual causation (e.g., Halpern & Pearl, 2005) and its extension to responsibility judgments (Chockler & Halpern, 2004). We review the main theoretical and empirical issues that arise from this literature and propose a novel model of intuitive judgments of responsibility. This model is a function of both pivotality (whether an agent made a difference to the outcome) and criticality (how important the agent is perceived to be for the outcome, before any actions are taken). The model explains empirical results from previous studies and is supported by a new experiment that manipulates both pivotality and criticality. We also discuss possible extensions of this model to deal with a broader range of causal situations. Overall, our approach emphasizes the close interrelations between causality, counterfactuals, and responsibility attributions. Copyright © 2013 Cognitive Science Society, Inc.

  7. Novel approaches are needed to develop tomorrow's antibacterial therapies.

    PubMed

    Spellberg, Brad; Bartlett, John; Wunderink, Rich; Gilbert, David N

    2015-01-15

    Society faces a crisis of rising antibiotic resistance even as the pipeline of new antibiotics has been drying up. Antibiotics are a public trust; every individual's use of antibiotics affects their efficacy for everyone else. As such, responses to the antibiotic crisis must take a societal perspective. The market failure of antibiotics is due to a combination of scientific challenges to discovering and developing new antibiotics, unfavorable economics, and a hostile regulatory environment. Scientific solutions include changing the way we screen for new antibiotics. More transformationally, developing new treatments that seek to disarm pathogens without killing them, or that modulate the host inflammatory response to infection, will reduce selective pressure and hence minimize resistance emergence. Economic transformation will require new business models to support antibiotic development. Finally, regulatory reform is needed so that clinical development programs are feasible, rigorous, and clinically relevant. Pulmonary and critical care specialists can have tremendous impact on the continued availability of effective antibiotics. Encouraging use of molecular diagnostic tests to allow pathogen-targeted, narrow-spectrum antibiotic therapy, using short rather than unnecessarily long course therapy, reducing inappropriate antibiotic use for probable viral infections, and reducing infection rates will help preserve the antibiotics we have for future generations.

  8. Effect of Age on Complexity and Causality of the Cardiovascular Control: Comparison between Model-Based and Model-Free Approaches

    PubMed Central

    Porta, Alberto; Faes, Luca; Bari, Vlasta; Marchi, Andrea; Bassani, Tito; Nollo, Giandomenico; Perseguini, Natália Maria; Milan, Juliana; Minatel, Vinícius; Borghi-Silva, Audrey; Takahashi, Anielle C. M.; Catai, Aparecida M.

    2014-01-01

    The proposed approach evaluates complexity of the cardiovascular control and causality among cardiovascular regulatory mechanisms from spontaneous variability of heart period (HP), systolic arterial pressure (SAP) and respiration (RESP). It relies on construction of a multivariate embedding space, optimization of the embedding dimension and a procedure allowing the selection of the components most suitable to form the multivariate embedding space. Moreover, it allows the comparison between linear model-based (MB) and nonlinear model-free (MF) techniques and between MF approaches exploiting local predictability (LP) and conditional entropy (CE). The framework was applied to study age-related modifications of complexity and causality in healthy humans in supine resting (REST) and during standing (STAND). We found that: 1) MF approaches are more efficient than the MB method when nonlinear components are present, while the reverse situation holds in presence of high dimensional embedding spaces; 2) the CE method is the least powerful in detecting age-related trends; 3) the association of HP complexity on age suggests an impairment of cardiac regulation and response to STAND; 4) the relation of SAP complexity on age indicates a gradual increase of sympathetic activity and a reduced responsiveness of vasomotor control to STAND; 5) the association from SAP to HP on age during STAND reveals a progressive inefficiency of baroreflex; 6) the reduced connection from HP to SAP with age might be linked to the progressive exploitation of Frank-Starling mechanism at REST and to the progressive increase of peripheral resistances during STAND; 7) at REST the diminished association from RESP to HP with age suggests a vagal withdrawal and a gradual uncoupling between respiratory activity and heart; 8) the weakened connection from RESP to SAP with age might be related to the progressive increase of left ventricular thickness and vascular stiffness and to the gradual decrease of

  9. Sociotechnical approaches to workplace safety: Research needs and opportunities

    PubMed Central

    Robertson, Michelle M.; Hettinger, Lawrence J.; Waterson, Patrick E.; Ian Noy, Y.; Dainoff, Marvin J.; Leveson, Nancy G.; Carayon, Pascale; Courtney, Theodore K.

    2015-01-01

    The sociotechnical systems perspective offers intriguing and potentially valuable insights into problems associated with workplace safety. While formal sociotechnical systems thinking originated in the 1950s, its application to the analysis and design of sustainable, safe working environments has not been fully developed. To that end, a Hopkinton Conference was organised to review and summarise the state of knowledge in the area and to identify research priorities. A group of 26 international experts produced collaborative articles for this special issue of Ergonomics, and each focused on examining a key conceptual, methodological and/or theoretical issue associated with sociotechnical systems and safety. In this concluding paper, we describe the major conference themes and recommendations. These are organised into six topic areas: (1) Concepts, definitions and frameworks, (2) defining research methodologies, (3) modelling and simulation, (4) communications and decision-making, (5) sociotechnical attributes of safe and unsafe systems and (6) potential future research directions for sociotechnical systems research. Practitioner Summary: Sociotechnical complexity, a characteristic of many contemporary work environments, presents potential safety risks that traditional approaches to workplace safety may not adequately address. In this paper, we summarise the investigations of a group of international researchers into questions associated with the application of sociotechnical systems thinking to improve worker safety. PMID:25728246

  10. Sociotechnical approaches to workplace safety: Research needs and opportunities.

    PubMed

    Robertson, Michelle M; Hettinger, Lawrence J; Waterson, Patrick E; Noy, Y Ian; Dainoff, Marvin J; Leveson, Nancy G; Carayon, Pascale; Courtney, Theodore K

    2015-01-01

    The sociotechnical systems perspective offers intriguing and potentially valuable insights into problems associated with workplace safety. While formal sociotechnical systems thinking originated in the 1950s, its application to the analysis and design of sustainable, safe working environments has not been fully developed. To that end, a Hopkinton Conference was organised to review and summarise the state of knowledge in the area and to identify research priorities. A group of 26 international experts produced collaborative articles for this special issue of Ergonomics, and each focused on examining a key conceptual, methodological and/or theoretical issue associated with sociotechnical systems and safety. In this concluding paper, we describe the major conference themes and recommendations. These are organised into six topic areas: (1) Concepts, definitions and frameworks, (2) defining research methodologies, (3) modelling and simulation, (4) communications and decision-making, (5) sociotechnical attributes of safe and unsafe systems and (6) potential future research directions for sociotechnical systems research. Sociotechnical complexity, a characteristic of many contemporary work environments, presents potential safety risks that traditional approaches to workplace safety may not adequately address. In this paper, we summarise the investigations of a group of international researchers into questions associated with the application of sociotechnical systems thinking to improve worker safety.

  11. Characterising powder flow properties - the need for a multivariate approach

    NASA Astrophysics Data System (ADS)

    Freeman, Tim; Brockbank, Katrina; Sabathier, Jerome

    2017-06-01

    Despite their widespread and well-established use, powders are challenging materials to work with, as evidenced by the common problems encountered during storage and processing, as well as in the quality and consistency of final products. The diverse range of unit operations used to handle and manipulate powders subject them to extremes of stress and flow regimes; from the high stress, static conditions present in hoppers to the dispersed, dynamic state of a fluidised bed dryer. It is therefore possible for a powder to behave a certain way in a given unit operation, but entirely differently in another. Many existing powder testing techniques don't deliver the required information as the test conditions do not represent the conditions in the process. Modern powder rheometers generate process relevant data by accurately measuring dynamic flow, bulk and shear properties. This approach enables a powder's response to aeration, consolidation, forced flow and changes in flow rate to be reliably quantified thereby simulating the conditions which a powder will be subjected to in process. This paper provides an introduction to powder rheology, including a comparison with traditional techniques, and uses case studies to demonstrate how powder rheology can be applied to optimise production processes and enhance product quality

  12. Distinguishing causal interactions in neural populations.

    PubMed

    Seth, Anil K; Edelman, Gerald M

    2007-04-01

    We describe a theoretical network analysis that can distinguish statistically causal interactions in population neural activity leading to a specific output. We introduce the concept of a causal core to refer to the set of neuronal interactions that are causally significant for the output, as assessed by Granger causality. Because our approach requires extensive knowledge of neuronal connectivity and dynamics, an illustrative example is provided by analysis of Darwin X, a brain-based device that allows precise recording of the activity of neuronal units during behavior. In Darwin X, a simulated neuronal model of the hippocampus and surrounding cortical areas supports learning of a spatial navigation task in a real environment. Analysis of Darwin X reveals that large repertoires of neuronal interactions contain comparatively small causal cores and that these causal cores become smaller during learning, a finding that may reflect the selection of specific causal pathways from diverse neuronal repertoires.

  13. Bayesian networks improve causal environmental ...

    EPA Pesticide Factsheets

    Rule-based weight of evidence approaches to ecological risk assessment may not account for uncertainties and generally lack probabilistic integration of lines of evidence. Bayesian networks allow causal inferences to be made from evidence by including causal knowledge about the problem, using this knowledge with probabilistic calculus to combine multiple lines of evidence, and minimizing biases in predicting or diagnosing causal relationships. Too often, sources of uncertainty in conventional weight of evidence approaches are ignored that can be accounted for with Bayesian networks. Specifying and propagating uncertainties improve the ability of models to incorporate strength of the evidence in the risk management phase of an assessment. Probabilistic inference from a Bayesian network allows evaluation of changes in uncertainty for variables from the evidence. The network structure and probabilistic framework of a Bayesian approach provide advantages over qualitative approaches in weight of evidence for capturing the impacts of multiple sources of quantifiable uncertainty on predictions of ecological risk. Bayesian networks can facilitate the development of evidence-based policy under conditions of uncertainty by incorporating analytical inaccuracies or the implications of imperfect information, structuring and communicating causal issues through qualitative directed graph formulations, and quantitatively comparing the causal power of multiple stressors on value

  14. Campbell's and Rubin's Perspectives on Causal Inference

    ERIC Educational Resources Information Center

    West, Stephen G.; Thoemmes, Felix

    2010-01-01

    Donald Campbell's approach to causal inference (D. T. Campbell, 1957; W. R. Shadish, T. D. Cook, & D. T. Campbell, 2002) is widely used in psychology and education, whereas Donald Rubin's causal model (P. W. Holland, 1986; D. B. Rubin, 1974, 2005) is widely used in economics, statistics, medicine, and public health. Campbell's approach focuses on…

  15. Campbell's and Rubin's Perspectives on Causal Inference

    ERIC Educational Resources Information Center

    West, Stephen G.; Thoemmes, Felix

    2010-01-01

    Donald Campbell's approach to causal inference (D. T. Campbell, 1957; W. R. Shadish, T. D. Cook, & D. T. Campbell, 2002) is widely used in psychology and education, whereas Donald Rubin's causal model (P. W. Holland, 1986; D. B. Rubin, 1974, 2005) is widely used in economics, statistics, medicine, and public health. Campbell's approach focuses on…

  16. Causal thinking and causal language in epidemiology: it's in the details

    PubMed Central

    Lipton, Robert; Ødegaard, Terje

    2005-01-01

    Although epidemiology is necessarily involved with elucidating causal processes, we argue that there is little practical need, having described an epidemiological result, to then explicitly label it as causal (or not). Doing so is a convention which obscures the valuable core work of epidemiology as an important constituent of public health practice. We discuss another approach which emphasizes the public health "use value" of research findings in regard to prediction and intervention independent from explicit metaphysical causal claims. Examples are drawn from smoking and lung cancer, with particular focus on the original 1964 Surgeon General's report on smoking and the new version released in 2004. The intent is to help the epidemiologist focus on the pertinent implications of research, which, from a public health point of view, in large part entails the ability to predict and to intervene. Further discussion will center on the importance of differentiating between technical/practical uses of causal language, as might be used in structural equations or marginal structural modeling, and more foundational notions of cause. We show that statistical/epidemiological results, such as "smoking two packs a day increases risk of lung cancer by 10 times" are in themselves a kind of causal argument that are not in need of additional support from relatively ambiguous language such as "smoking causes lung cancer." We will show that the confusion stemming from the use of this latter statement is more than mere semantics. Our goal is to allow researchers to feel more confident in the power of their research to tell a convincing story without resorting to metaphysical/unsupportable notions of cause. PMID:16053522

  17. An introduction to causal inference.

    PubMed

    Pearl, Judea

    2010-02-26

    This paper summarizes recent advances in causal inference and underscores the paradigmatic shifts that must be undertaken in moving from traditional statistical analysis to causal analysis of multivariate data. Special emphasis is placed on the assumptions that underlie all causal inferences, the languages used in formulating those assumptions, the conditional nature of all causal and counterfactual claims, and the methods that have been developed for the assessment of such claims. These advances are illustrated using a general theory of causation based on the Structural Causal Model (SCM) described in Pearl (2000a), which subsumes and unifies other approaches to causation, and provides a coherent mathematical foundation for the analysis of causes and counterfactuals. In particular, the paper surveys the development of mathematical tools for inferring (from a combination of data and assumptions) answers to three types of causal queries: those about (1) the effects of potential interventions, (2) probabilities of counterfactuals, and (3) direct and indirect effects (also known as "mediation"). Finally, the paper defines the formal and conceptual relationships between the structural and potential-outcome frameworks and presents tools for a symbiotic analysis that uses the strong features of both. The tools are demonstrated in the analyses of mediation, causes of effects, and probabilities of causation.

  18. A new laboratory evolution approach to select for constitutive acetic acid tolerance in Saccharomyces cerevisiae and identification of causal mutations.

    PubMed

    González-Ramos, Daniel; Gorter de Vries, Arthur R; Grijseels, Sietske S; van Berkum, Margo C; Swinnen, Steve; van den Broek, Marcel; Nevoigt, Elke; Daran, Jean-Marc G; Pronk, Jack T; van Maris, Antonius J A

    2016-01-01

    Acetic acid, released during hydrolysis of lignocellulosic feedstocks for second generation bioethanol production, inhibits yeast growth and alcoholic fermentation. Yeast biomass generated in a propagation step that precedes ethanol production should therefore express a high and constitutive level of acetic acid tolerance before introduction into lignocellulosic hydrolysates. However, earlier laboratory evolution strategies for increasing acetic acid tolerance of Saccharomyces cerevisiae, based on prolonged cultivation in the presence of acetic acid, selected for inducible rather than constitutive tolerance to this inhibitor. Preadaptation in the presence of acetic acid was shown to strongly increase the fraction of yeast cells that could initiate growth in the presence of this inhibitor. Serial microaerobic batch cultivation, with alternating transfers to fresh medium with and without acetic acid, yielded evolved S. cerevisiae cultures with constitutive acetic acid tolerance. Single-cell lines isolated from five such evolution experiments after 50-55 transfers were selected for further study. An additional constitutively acetic acid tolerant mutant was selected after UV-mutagenesis. All six mutants showed an increased fraction of growing cells upon a transfer from a non-stressed condition to a medium containing acetic acid. Whole-genome sequencing identified six genes that contained (different) mutations in multiple acetic acid-tolerant mutants. Haploid segregation studies and expression of the mutant alleles in the unevolved ancestor strain identified causal mutations for the acquired acetic acid tolerance in four genes (ASG1, ADH3, SKS1 and GIS4). Effects of the mutations in ASG1, ADH3 and SKS1 on acetic acid tolerance were additive. A novel laboratory evolution strategy based on alternating cultivation cycles in the presence and absence of acetic acid conferred a selective advantage to constitutively acetic acid-tolerant mutants and may be applicable for

  19. Implications of a needs-based approach to estimating psychiatric workforce requirements.

    PubMed

    Faulkner, Larry R

    2003-01-01

    The author reviews a needs-based approach to estimating psychiatric workforce requirements that entails five determinations: (1) number of people with mental health problems, (2) number of people needing mental health treatment, (3) number of people needing psychiatric treatment, (4) amount of psychiatric time required to meet patient needs, and (5) amount of time psychiatrists have available to provide direct patient care. Questions, issues, and strategies raised by the needs-based approach are outlined. The author suggests that only a coordinated, carefully orchestrated effort among national psychiatric organizations will ensure that the future psychiatric workforce is adequate to meet the needs of the mentally ill.

  20. Independence and dependence in human causal reasoning.

    PubMed

    Rehder, Bob

    2014-07-01

    Causal graphical models (CGMs) are a popular formalism used to model human causal reasoning and learning. The key property of CGMs is the causal Markov condition, which stipulates patterns of independence and dependence among causally related variables. Five experiments found that while adult's causal inferences exhibited aspects of veridical causal reasoning, they also exhibited a small but tenacious tendency to violate the Markov condition. They also failed to exhibit robust discounting in which the presence of one cause as an explanation of an effect makes the presence of another less likely. Instead, subjects often reasoned "associatively," that is, assumed that the presence of one variable implied the presence of other, causally related variables, even those that were (according to the Markov condition) conditionally independent. This tendency was unaffected by manipulations (e.g., response deadlines) known to influence fast and intuitive reasoning processes, suggesting that an associative response to a causal reasoning question is sometimes the product of careful and deliberate thinking. That about 60% of the erroneous associative inferences were made by about a quarter of the subjects suggests the presence of substantial individual differences in this tendency. There was also evidence that inferences were influenced by subjects' assumptions about factors that disable causal relations and their use of a conjunctive reasoning strategy. Theories that strive to provide high fidelity accounts of human causal reasoning will need to relax the independence constraints imposed by CGMs.

  1. Causal models and learning from data: integrating causal modeling and statistical estimation.

    PubMed

    Petersen, Maya L; van der Laan, Mark J

    2014-05-01

    The practice of epidemiology requires asking causal questions. Formal frameworks for causal inference developed over the past decades have the potential to improve the rigor of this process. However, the appropriate role for formal causal thinking in applied epidemiology remains a matter of debate. We argue that a formal causal framework can help in designing a statistical analysis that comes as close as possible to answering the motivating causal question, while making clear what assumptions are required to endow the resulting estimates with a causal interpretation. A systematic approach for the integration of causal modeling with statistical estimation is presented. We highlight some common points of confusion that occur when causal modeling techniques are applied in practice and provide a broad overview on the types of questions that a causal framework can help to address. Our aims are to argue for the utility of formal causal thinking, to clarify what causal models can and cannot do, and to provide an accessible introduction to the flexible and powerful tools provided by causal models.

  2. What Works Clearinghouse Quick Review: "Looking Beyond Enrollment: The Causal Effect of Need-Based Grants on College Access, Persistence, and Graduation"

    ERIC Educational Resources Information Center

    What Works Clearinghouse, 2013

    2013-01-01

    This study examined whether eligibility for the Florida Student Access Grant, a need-based grant for low-income students in Florida, affects college enrollment, credit accumulation, persistence over time in college, and, eventually, graduation. The sample for this study included seniors in Florida public high schools in 1999-2000 who submitted a…

  3. Looking beyond Enrollment: The Causal Effect of Need-Based Grants on College Access, Persistence, and Graduation. An NCPR Working Paper

    ERIC Educational Resources Information Center

    Castleman, Benjamin L.; Long, Bridget Terry

    2013-01-01

    Gaps in average college success among students of differing backgrounds have persisted in the United States for decades. One of the primary ways governments have attempted to ameliorate such gaps is by providing need-based grants, but little evidence exists on the impacts of such aid on longer term outcomes such as college persistence and degree…

  4. Looking beyond Enrollment: The Causal Effect of Need-Based Grants on College Access, Persistence, and Graduation. NBER Working Paper No. 19306

    ERIC Educational Resources Information Center

    Castleman, Benjamin L.; Long, Bridget Terry

    2013-01-01

    Gaps in average college success among students of differing backgrounds have persisted in the United States for decades. One of the primary ways governments have attempted to ameliorate such gaps is by providing need-based grants, but little evidence exists on the impacts of such aid on longer-term outcomes such as college persistence and degree…

  5. Looking beyond Enrollment: The Causal Effect of Need-Based Grants on College Access, Persistence, and Graduation. NBER Working Paper No. 19306

    ERIC Educational Resources Information Center

    Castleman, Benjamin L.; Long, Bridget Terry

    2013-01-01

    Gaps in average college success among students of differing backgrounds have persisted in the United States for decades. One of the primary ways governments have attempted to ameliorate such gaps is by providing need-based grants, but little evidence exists on the impacts of such aid on longer-term outcomes such as college persistence and degree…

  6. Causal Mediation Analysis: Warning! Assumptions Ahead

    ERIC Educational Resources Information Center

    Keele, Luke

    2015-01-01

    In policy evaluations, interest may focus on why a particular treatment works. One tool for understanding why treatments work is causal mediation analysis. In this essay, I focus on the assumptions needed to estimate mediation effects. I show that there is no "gold standard" method for the identification of causal mediation effects. In…

  7. Causal Mediation Analysis: Warning! Assumptions Ahead

    ERIC Educational Resources Information Center

    Keele, Luke

    2015-01-01

    In policy evaluations, interest may focus on why a particular treatment works. One tool for understanding why treatments work is causal mediation analysis. In this essay, I focus on the assumptions needed to estimate mediation effects. I show that there is no "gold standard" method for the identification of causal mediation effects. In…

  8. The Effects of a Model-Based Physics Curriculum Program with a Physics First Approach: a Causal-Comparative Study

    NASA Astrophysics Data System (ADS)

    Liang, Ling L.; Fulmer, Gavin W.; Majerich, David M.; Clevenstine, Richard; Howanski, Raymond

    2012-02-01

    The purpose of this study is to examine the effects of a model-based introductory physics curriculum on conceptual learning in a Physics First (PF) Initiative. This is the first comparative study in physics education that applies the Rasch modeling approach to examine the effects of a model-based curriculum program combined with PF in the United States. Five teachers and 301 students (in grades 9 through 12) in two mid-Atlantic high schools participated in the study. The students' conceptual learning was measured by the Force Concept Inventory (FCI). It was found that the ninth-graders enrolled in the model-based program in a PF initiative achieved substantially greater conceptual understanding of the physics content than those 11th-/12th-graders enrolled in the conventional non-modeling, non-PF program (Honors strand). For the 11th-/12th-graders enrolled in the non-PF, non-honors strands, the modeling classes also outperformed the conventional non-modeling classes. The instructional activity reports by students indicated that the model-based approach was generally implemented in modeling classrooms. A closer examination of the field notes and the classroom observation profiles revealed that the greatest inconsistencies in model-based teaching practices observed were related to classroom interactions or discourse. Implications and recommendations for future studies are also discussed.

  9. Algorithm to assess causality after individual adverse events following immunizations.

    PubMed

    Halsey, Neal A; Edwards, Kathryn M; Dekker, Cornelia L; Klein, Nicola P; Baxter, Roger; Larussa, Philip; Marchant, Colin; Slade, Barbara; Vellozzi, Claudia

    2012-08-24

    Assessing individual reports of adverse events following immunizations (AEFI) can be challenging. Most published reviews are based on expert opinions, but the methods and logic used to arrive at these opinions are neither well described nor understood by many health care providers and scientists. We developed a standardized algorithm to assist in collecting and interpreting data, and to help assess causality after individual AEFI. Key questions that should be asked during the assessment of AEFI include: Is the diagnosis of the AEFI correct? Does clinical or laboratory evidence exist that supports possible causes for the AEFI other than the vaccine in the affected individual? Is there a known causal association between the AEFI and the vaccine? Is there strong evidence against a causal association? Is there a specific laboratory test implicating the vaccine in the pathogenesis? An algorithm can assist with addressing these questions in a standardized, transparent manner which can be tracked and reassessed if additional information becomes available. Examples in this document illustrate the process of using the algorithm to determine causality. As new epidemiologic and clinical data become available, the algorithm and guidelines will need to be modified. Feedback from users of the algorithm will be invaluable in this process. We hope that this algorithm approach can assist with educational efforts to improve the collection of key information on AEFI and provide a platform for teaching about causality assessment. Copyright © 2012 Elsevier Ltd. All rights reserved.

  10. Illusions of causality at the heart of pseudoscience.

    PubMed

    Matute, Helena; Yarritu, Ion; Vadillo, Miguel A

    2011-08-01

    Pseudoscience, superstitions, and quackery are serious problems that threaten public health and in which many variables are involved. Psychology, however, has much to say about them, as it is the illusory perceptions of causality of so many people that needs to be understood. The proposal we put forward is that these illusions arise from the normal functioning of the cognitive system when trying to associate causes and effects. Thus, we propose to apply basic research and theories on causal learning to reduce the impact of pseudoscience. We review the literature on the illusion of control and the causal learning traditions, and then present an experiment as an illustration of how this approach can provide fruitful ideas to reduce pseudoscientific thinking. The experiment first illustrates the development of a quackery illusion through the testimony of fictitious patients who report feeling better. Two different predictions arising from the integration of the causal learning and illusion of control domains are then proven effective in reducing this illusion. One is showing the testimony of people who feel better without having followed the treatment. The other is asking participants to think in causal terms rather than in terms of effectiveness. ©2010 The British Psychological Society.

  11. Model Averaging for Improving Inference from Causal Diagrams.

    PubMed

    Hamra, Ghassan B; Kaufman, Jay S; Vahratian, Anjel

    2015-08-11

    Model selection is an integral, yet contentious, component of epidemiologic research. Unfortunately, there remains no consensus on how to identify a single, best model among multiple candidate models. Researchers may be prone to selecting the model that best supports their a priori, preferred result; a phenomenon referred to as "wish bias". Directed acyclic graphs (DAGs), based on background causal and substantive knowledge, are a useful tool for specifying a subset of adjustment variables to obtain a causal effect estimate. In many cases, however, a DAG will support multiple, sufficient or minimally-sufficient adjustment sets. Even though all of these may theoretically produce unbiased effect estimates they may, in practice, yield somewhat distinct values, and the need to select between these models once again makes the research enterprise vulnerable to wish bias. In this work, we suggest combining adjustment sets with model averaging techniques to obtain causal estimates based on multiple, theoretically-unbiased models. We use three techniques for averaging the results among multiple candidate models: information criteria weighting, inverse variance weighting, and bootstrapping. We illustrate these approaches with an example from the Pregnancy, Infection, and Nutrition (PIN) study. We show that each averaging technique returns similar, model averaged causal estimates. An a priori strategy of model averaging provides a means of integrating uncertainty in selection among candidate, causal models, while also avoiding the temptation to report the most attractive estimate from a suite of equally valid alternatives.

  12. Developing Causal Understanding with Causal Maps: The Impact of Total Links, Temporal Flow, and Lateral Position of Outcome Nodes

    ERIC Educational Resources Information Center

    Jeong, Allan; Lee, Woon Jee

    2012-01-01

    This study examined some of the methodological approaches used by students to construct causal maps in order to determine which approaches help students understand the underlying causes and causal mechanisms in a complex system. This study tested the relationship between causal understanding (ratio of root causes correctly/incorrectly identified,…

  13. Developing Causal Understanding with Causal Maps: The Impact of Total Links, Temporal Flow, and Lateral Position of Outcome Nodes

    ERIC Educational Resources Information Center

    Jeong, Allan; Lee, Woon Jee

    2012-01-01

    This study examined some of the methodological approaches used by students to construct causal maps in order to determine which approaches help students understand the underlying causes and causal mechanisms in a complex system. This study tested the relationship between causal understanding (ratio of root causes correctly/incorrectly identified,…

  14. Invited Commentary: Causal Inference Across Space and Time-Quixotic Quest, Worthy Goal, or Both?

    PubMed

    Edwards, Jessie K; Lesko, Catherine R; Keil, Alexander P

    2017-07-15

    The g-formula and agent-based models (ABMs) are 2 approaches used to estimate causal effects. In the current issue of the Journal, Murray et al. (Am J Epidemiol. 2017;186(2):131-142) compare the performance of the g-formula and ABMs to estimate causal effects in 3 target populations. In their thoughtful paper, the authors outline several reasons that a causal effect estimated using an ABM may be biased when parameterized from at least 1 source external to the target population. The authors have addressed an important issue in epidemiology: Often causal effect estimates are needed to inform public health decisions in settings without complete data. Because public health decisions are urgent, epidemiologists are frequently called upon to estimate a causal effect from existing data in a separate population rather than perform new data collection activities. The assumptions needed to transport causal effects to a specific target population must be carefully stated and assessed, just as one would explicitly state and analyze the assumptions required to draw internally valid causal inference in a specific study sample. Considering external validity in important target populations increases the impact of epidemiologic studies. © The Author(s) 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  15. Nonlinear connectivity by Granger causality.

    PubMed

    Marinazzo, Daniele; Liao, Wei; Chen, Huafu; Stramaglia, Sebastiano

    2011-09-15

    The communication among neuronal populations, reflected by transient synchronous activity, is the mechanism underlying the information processing in the brain. Although it is widely assumed that the interactions among those populations (i.e. functional connectivity) are highly nonlinear, the amount of nonlinear information transmission and its functional roles are not clear. The state of the art to understand the communication between brain systems are dynamic causal modeling (DCM) and Granger causality. While DCM models nonlinear couplings, Granger causality, which constitutes a major tool to reveal effective connectivity, and is widely used to analyze EEG/MEG data as well as fMRI signals, is usually applied in its linear version. In order to capture nonlinear interactions between even short and noisy time series, a few approaches have been proposed. We review them and focus on a recently proposed flexible approach has been recently proposed, consisting in the kernel version of Granger causality. We show the application of the proposed approach on EEG signals and fMRI data.

  16. Exploring complex causal pathways between urban renewal, health and health inequality using a theory-driven realist approach.

    PubMed

    Mehdipanah, Roshanak; Manzano, Ana; Borrell, Carme; Malmusi, Davide; Rodriguez-Sanz, Maica; Greenhalgh, Joanne; Muntaner, Carles; Pawson, Ray

    2015-01-01

    Urban populations are growing and to accommodate these numbers, cities are becoming more involved in urban renewal programs to improve the physical, social and economic conditions in different areas. This paper explores some of the complexities surrounding the link between urban renewal, health and health inequalities using a theory-driven approach. We focus on an urban renewal initiative implemented in Barcelona, the Neighbourhoods Law, targeting Barcelona's (Spain) most deprived neighbourhoods. We present evidence from two studies on the health evaluation of the Neighbourhoods Law, while drawing from recent urban renewal literature, to follow a four-step process to develop a program theory. We then use two specific urban renewal interventions, the construction of a large central plaza and the repair of streets and sidewalks, to further examine this link. In order for urban renewal programs to affect health and health inequality, neighbours must use and adapt to the changes produced by the intervention. However, there exist barriers that can result in negative outcomes including factors such as accessibility, safety and security. This paper provides a different perspective to the field that is largely dominated by traditional quantitative studies that are not always able to address the complexities such interventions provide. Furthermore, the framework and discussions serve as a guide for future research, policy development and evaluation. Copyright © 2014 Elsevier Ltd. All rights reserved.

  17. Causal Imprinting in Causal Structure Learning

    PubMed Central

    Taylor, Eric G.; Ahn, Woo-kyoung

    2012-01-01

    Suppose one observes a correlation between two events, B and C, and infers that B causes C. Later one discovers that event A explains away the correlation between B and C. Normatively, one should now dismiss or weaken the belief that B causes C. Nonetheless, participants in the current study who observed a positive contingency between B and C followed by evidence that B and C were independent given A, persisted in believing that B causes C. The authors term this difficulty in revising initially learned causal structures “causal imprinting.” Throughout four experiments, causal imprinting was obtained using multiple dependent measures and control conditions. A Bayesian analysis showed that causal imprinting may be normative under some conditions, but causal imprinting also occurred in the current study when it was clearly non-normative. It is suggested that causal imprinting occurs due to the influence of prior knowledge on how reasoners interpret later evidence. Consistent with this view, when participants first viewed the evidence showing that B and C are independent given A, later evidence with only B and C did not lead to the belief that B causes C. PMID:22859019

  18. Causal imprinting in causal structure learning.

    PubMed

    Taylor, Eric G; Ahn, Woo-Kyoung

    2012-11-01

    Suppose one observes a correlation between two events, B and C, and infers that B causes C. Later one discovers that event A explains away the correlation between B and C. Normatively, one should now dismiss or weaken the belief that B causes C. Nonetheless, participants in the current study who observed a positive contingency between B and C followed by evidence that B and C were independent given A, persisted in believing that B causes C. The authors term this difficulty in revising initially learned causal structures "causal imprinting." Throughout four experiments, causal imprinting was obtained using multiple dependent measures and control conditions. A Bayesian analysis showed that causal imprinting may be normative under some conditions, but causal imprinting also occurred in the current study when it was clearly non-normative. It is suggested that causal imprinting occurs due to the influence of prior knowledge on how reasoners interpret later evidence. Consistent with this view, when participants first viewed the evidence showing that B and C are independent given A, later evidence with only B and C did not lead to the belief that B causes C. Copyright © 2012 Elsevier Inc. All rights reserved.

  19. The role of awareness campaigns in the improvement of separate collection rates of municipal waste among university students: A Causal Chain Approach.

    PubMed

    Saladié, Òscar; Santos-Lacueva, Raquel

    2016-02-01

    One of the main objectives of municipal waste management policies is to improve separate collection, both quantitatively and qualitatively. Several factors influence people behavior to recycling and, consequently, they play an important role to achieve the goals proposed in the management policies. People can improve separate collection rates because of a wide range of causes with different weight. Here, we have determined the uplift in probability to improve separate collection of municipal waste created by the awareness campaigns among 806 undergraduate students at Universitat Rovira i Virgili (Catalonia) by means of the Causal Chain Approach, a probabilistic method. A 73.2% state having improved separate collection in recent years and the most of them (75.4%) remember some awareness campaign. The results show the uplift in probability to improve separate collection attributable to the awareness campaigns is 17.9%. They should be taken into account by policy makers in charge of municipal waste management. Nevertheless, it must be assumed an awareness campaign will never be sufficient to achieve the objectives defined in municipal waste management programmes.

  20. Revealing Cross-Frequency Causal Interactions During a Mental Arithmetic Task Through Symbolic Transfer Entropy: A Novel Vector-Quantization Approach.

    PubMed

    Dimitriadis, Stavros; Sun, Yu; Laskaris, Nikolaos; Thakor, Nitish; Bezerianos, Anastasios

    2016-10-01

    Working memory (WM) is a distributed cognitive process that employs communication between prefrontal cortex and posterior brain regions in the form of cross-frequency coupling between theta ( θ) and high-alpha ( α2) brain waves. A novel method for deriving causal interactions between brain waves of different frequencies is essential for a better understanding of the neural dynamics of such complex cognitive process. Here, we proposed a novel method to estimate transfer entropy ( TE) through a symbolization scheme, which is based on neural-gas algorithm (NG) and encodes a bivariate time series in the form of two symbolic sequences. Given the symbolic sequences, the delay symbolic transfer entropy ( dSTE(NG)) is defined. Our approach is akin to standard symbolic transfer entropy ( STE) that incorporates the ordinal pattern (OP) symbolization technique. We assessed the proposed method in a WM-invoked paradigm that included a mental arithmetic task at various levels of difficulty. Effective interactions between Frontal(θ) ( F(θ) ) and [Formula: see text] ( PO(α2)) brain waves were detected in multichannel EEG recordings from 16 subjects. Compared with conventional methods, our technique was less sensitive to noise and demonstrated improved computational efficiency in quantifying the dominating direction of effective connectivity between brain waves of different spectral content. Moreover, we discovered an efferent F(θ) connectivity pattern and an afferent PO(α2) one, in all the levels of the task. Further statistical analysis revealed an increasing dSTE(NG) strength following the task's difficulty.

  1. [Social use of alcohol among adolescent offenders: a fundamental approach toward human needs].

    PubMed

    D'Andrea, Gustavo; Ventura, Carla Aparecida Arena; da Costa, Moacyr Lobo

    2014-02-01

    This study examined some basic health care approaches toward human needs, with a particular focus on nursing. We aimed to incorporate these approaches into the discussion of the mental health of adolescent offenders who consume alcohol. We discuss specific needs of the delinquent group, critique policies that prioritize coercion of adolescent offenders, and the role that nurses could play in the sphere of juvenile delinquency.

  2. The TEACH Method: An Interactive Approach for Teaching the Needs-Based Theories Of Motivation

    ERIC Educational Resources Information Center

    Moorer, Cleamon, Jr.

    2014-01-01

    This paper describes an interactive approach for explaining and teaching the Needs-Based Theories of Motivation. The acronym TEACH stands for Theory, Example, Application, Collaboration, and Having Discussion. This method can help business students to better understand and distinguish the implications of Maslow's Hierarchy of Needs,…

  3. The TEACH Method: An Interactive Approach for Teaching the Needs-Based Theories Of Motivation

    ERIC Educational Resources Information Center

    Moorer, Cleamon, Jr.

    2014-01-01

    This paper describes an interactive approach for explaining and teaching the Needs-Based Theories of Motivation. The acronym TEACH stands for Theory, Example, Application, Collaboration, and Having Discussion. This method can help business students to better understand and distinguish the implications of Maslow's Hierarchy of Needs,…

  4. Instructionally Differentiated Programming. A Needs-Based Approach for Students with Behavior Disorders.

    ERIC Educational Resources Information Center

    Cessna, K. Kay; And Others

    This monograph offers six papers which present a model to assist in developing instructionally differentiated programming based on individual needs for students with behavioral disorders. The first three chapters focus on underlying philosophies. A paper by Myron Swize titled "Colorado's Needs-Based Approach" stresses that it is more…

  5. Analyzing multiple nonlinear time series with extended Granger causality

    NASA Astrophysics Data System (ADS)

    Chen, Yonghong; Rangarajan, Govindan; Feng, Jianfeng; Ding, Mingzhou

    2004-04-01

    Identifying causal relations among simultaneously acquired signals is an important problem in multivariate time series analysis. For linear stochastic systems Granger proposed a simple procedure called the Granger causality to detect such relations. In this work we consider nonlinear extensions of Granger's idea and refer to the result as extended Granger causality. A simple approach implementing the extended Granger causality is presented and applied to multiple chaotic time series and other types of nonlinear signals. In addition, for situations with three or more time series we propose a conditional extended Granger causality measure that enables us to determine whether the causal relation between two signals is direct or mediated by another process.

  6. Implications of the Changing Conversation about Causality for Evaluators

    ERIC Educational Resources Information Center

    Gates, Emily; Dyson, Lisa

    2017-01-01

    Making causal claims is central to evaluation practice because we want to know the effects of a program, project, or policy. In the past decade, the conversation about establishing causal claims has become prominent (and problematic). In response to this changing conversation about causality, we argue that evaluators need to take up some new ways…

  7. Implications of the Changing Conversation about Causality for Evaluators

    ERIC Educational Resources Information Center

    Gates, Emily; Dyson, Lisa

    2017-01-01

    Making causal claims is central to evaluation practice because we want to know the effects of a program, project, or policy. In the past decade, the conversation about establishing causal claims has become prominent (and problematic). In response to this changing conversation about causality, we argue that evaluators need to take up some new ways…

  8. Causality in thought.

    PubMed

    Sloman, Steven A; Lagnado, David

    2015-01-03

    Causal knowledge plays a crucial role in human thought, but the nature of causal representation and inference remains a puzzle. Can human causal inference be captured by relations of probabilistic dependency, or does it draw on richer forms of representation? This article explores this question by reviewing research in reasoning, decision making, various forms of judgment, and attribution. We endorse causal Bayesian networks as the best normative framework and as a productive guide to theory building. However, it is incomplete as an account of causal thinking. On the basis of a range of experimental work, we identify three hallmarks of causal reasoning-the role of mechanism, narrative, and mental simulation-all of which go beyond mere probabilistic knowledge. We propose that the hallmarks are closely related. Mental simulations are representations over time of mechanisms. When multiple actors are involved, these simulations are aggregated into narratives.

  9. Causal density matrices

    NASA Astrophysics Data System (ADS)

    Engelhardt, Netta; Fischetti, Sebastian

    2017-06-01

    We define a new construct in quantum field theory—the causal density matrix—obtained from the singularity structure of correlators of local operators. This object provides a necessary and sufficient condition for a quantum field theory state to have a holographic semiclassical dual causal geometry. By exploiting the causal density matrix, we find that these dual causal geometries quite generally (even away from AdS /CFT ) exhibit features of quantum error correction. Within AdS /CFT , we argue that the "reduced" causal density matrix is the natural dual to the causal wedge. Our formalism is very well-suited to generalizations of holography beyond AdS /CFT or even gravity/QFT.

  10. Key concepts of demand-driven health care; an approach based on client's needs.

    PubMed

    Rijckmans, M J N; Garretsen, H F L; van de Goor, L A M; Bongers, I M B

    2005-09-01

    In most European countries we are witnessing a shift from supply-driven to demand-driven approaches in health care. According to these approaches, health care should contribute to the fulfillment of health-care-related needs of individuals and, therefore, to their perceived quality of life. The purpose of this study is to develop a conceptual framework for research in this new view of health care. The authors conclude that the 'felt need' should be the foundation of demand-driven care. The second part of the study is based on a widely used behavioral model resulting in a conceptual framework for research, policy and practice. This study makes a start at providing information about fundamental concepts that are at the heart of the demand-driven approach. In order to contribute to quality of life, health care providers should explore the underlying needs while developing services in order to fit the demand-driven approach.

  11. Information Theoretic Causal Coordination

    DTIC Science & Technology

    2013-09-12

    his 1969 paper, Clive Granger , British economist and Nobel laureate, proposed a statistical def- inition of causality between stochastic processes. It...showed that the directed infor- mation, an information theoretic quantity, quantifies Granger causality . We also explored a more pessimistic setup...Final Technical Report Project Title: Information Theoretic Causal Coordination AFOSR Award Number: AF FA9550-10-1-0345 Reporting Period: July 15

  12. Treatment Needs of Driving While Intoxicated Offenders: The Need for a Multi-modal Approach to Treatment

    PubMed Central

    Mullen, Jillian; Ryan, Stacy R.; Mathias, Charles W.; Dougherty, Donald M.

    2015-01-01

    Objective This study aimed to characterize and compare the treatment needs of adults with driving while intoxicated (DWI) offenses recruited from a correctional residential treatment facility and the community to provide recommendations for treatment development. Method A total of 119 adults (59 Residential, 60 Community) with at least one DWI offense were administered clinical diagnostic interviews to assess substance use disorders and completed a battery of questionnaires assessing demographic characteristics, legal history, psychiatric diagnoses, medical diagnoses, and health care utilization. Results Almost all (96.6%) DWI offenders met clinical diagnostic criteria for an alcohol use disorder, approximately half of the sample also met diagnostic criteria for co-morbid substance use disorders and a substantial proportion also reported psychiatric and medical co-morbidities. However, a high percentage were not receiving treatment for these issues, most likely as a result of having limited access to care as the majority of participants had no current health insurance (64.45%) or primary care physician (74.0%). The residential sample had more extensive criminal histories compared to the community sample but was generally representative of the community in terms of their clinical characteristics. For instance, the groups did not differ in rates of substance use, psychiatric and medical health diagnoses or in the treatment of such issues, with the exception of alcohol abuse treatment. Conclusions DWI offenders represent a clinical population with high levels of complex and competing treatment needs which are not currently being met. Our findings demonstrate the need for standardized screening of DWI offenders and call for the development of a multi-modal treatment approach in efforts to reduce recidivism. PMID:25664371

  13. Granger causality revisited.

    PubMed

    Friston, Karl J; Bastos, André M; Oswal, Ashwini; van Wijk, Bernadette; Richter, Craig; Litvak, Vladimir

    2014-11-01

    This technical paper offers a critical re-evaluation of (spectral) Granger causality measures in the analysis of biological timeseries. Using realistic (neural mass) models of coupled neuronal dynamics, we evaluate the robustness of parametric and nonparametric Granger causality. Starting from a broad class of generative (state-space) models of neuronal dynamics, we show how their Volterra kernels prescribe the second-order statistics of their response to random fluctuations; characterised in terms of cross-spectral density, cross-covariance, autoregressive coefficients and directed transfer functions. These quantities in turn specify Granger causality - providing a direct (analytic) link between the parameters of a generative model and the expected Granger causality. We use this link to show that Granger causality measures based upon autoregressive models can become unreliable when the underlying dynamics is dominated by slow (unstable) modes - as quantified by the principal Lyapunov exponent. However, nonparametric measures based on causal spectral factors are robust to dynamical instability. We then demonstrate how both parametric and nonparametric spectral causality measures can become unreliable in the presence of measurement noise. Finally, we show that this problem can be finessed by deriving spectral causality measures from Volterra kernels, estimated using dynamic causal modelling.

  14. Granger causality revisited

    PubMed Central

    Friston, Karl J.; Bastos, André M.; Oswal, Ashwini; van Wijk, Bernadette; Richter, Craig; Litvak, Vladimir

    2014-01-01

    This technical paper offers a critical re-evaluation of (spectral) Granger causality measures in the analysis of biological timeseries. Using realistic (neural mass) models of coupled neuronal dynamics, we evaluate the robustness of parametric and nonparametric Granger causality. Starting from a broad class of generative (state-space) models of neuronal dynamics, we show how their Volterra kernels prescribe the second-order statistics of their response to random fluctuations; characterised in terms of cross-spectral density, cross-covariance, autoregressive coefficients and directed transfer functions. These quantities in turn specify Granger causality — providing a direct (analytic) link between the parameters of a generative model and the expected Granger causality. We use this link to show that Granger causality measures based upon autoregressive models can become unreliable when the underlying dynamics is dominated by slow (unstable) modes — as quantified by the principal Lyapunov exponent. However, nonparametric measures based on causal spectral factors are robust to dynamical instability. We then demonstrate how both parametric and nonparametric spectral causality measures can become unreliable in the presence of measurement noise. Finally, we show that this problem can be finessed by deriving spectral causality measures from Volterra kernels, estimated using dynamic causal modelling. PMID:25003817

  15. Accounting for respiration is necessary to reliably infer Granger causality from cardiovascular variability series.

    PubMed

    Porta, Alberto; Bassani, Tito; Bari, Vlasta; Pinna, Gian D; Maestri, Roberto; Guzzetti, Stefano

    2012-03-01

    This study was designed to demonstrate the need of accounting for respiration (R) when causality between heart period (HP) and systolic arterial pressure (SAP) is under scrutiny. Simulations generated according to a bivariate autoregressive closed-loop model were utilized to assess how causality changes as a function of the model parameters. An exogenous (X) signal was added to the bivariate autoregressive closed-loop model to evaluate the bias on causality induced when the X source was disregarded. Causality was assessed in the time domain according to a predictability improvement approach (i.e., Granger causality). HP and SAP variability series were recorded with R in 19 healthy subjects during spontaneous and controlled breathing at 10, 15, and 20 breaths/min. Simulations proved the importance of accounting for X signals. During spontaneous breathing, assessing causality without taking into consideration R leads to a significantly larger percentage of closed-loop interactions and a smaller fraction of unidirectional causality from HP to SAP. This finding was confirmed during paced breathing and it was independent of the breathing rate. These results suggest that the role of baroreflex cannot be correctly assessed without accounting for R.

  16. Granger causality for state-space models

    NASA Astrophysics Data System (ADS)

    Barnett, Lionel; Seth, Anil K.

    2015-04-01

    Granger causality has long been a prominent method for inferring causal interactions between stochastic variables for a broad range of complex physical systems. However, it has been recognized that a moving average (MA) component in the data presents a serious confound to Granger causal analysis, as routinely performed via autoregressive (AR) modeling. We solve this problem by demonstrating that Granger causality may be calculated simply and efficiently from the parameters of a state-space (SS) model. Since SS models are equivalent to autoregressive moving average models, Granger causality estimated in this fashion is not degraded by the presence of a MA component. This is of particular significance when the data has been filtered, downsampled, observed with noise, or is a subprocess of a higher dimensional process, since all of these operations—commonplace in application domains as diverse as climate science, econometrics, and the neurosciences—induce a MA component. We show how Granger causality, conditional and unconditional, in both time and frequency domains, may be calculated directly from SS model parameters via solution of a discrete algebraic Riccati equation. Numerical simulations demonstrate that Granger causality estimators thus derived have greater statistical power and smaller bias than AR estimators. We also discuss how the SS approach facilitates relaxation of the assumptions of linearity, stationarity, and homoscedasticity underlying current AR methods, thus opening up potentially significant new areas of research in Granger causal analysis.

  17. Granger causality for state-space models.

    PubMed

    Barnett, Lionel; Seth, Anil K

    2015-04-01

    Granger causality has long been a prominent method for inferring causal interactions between stochastic variables for a broad range of complex physical systems. However, it has been recognized that a moving average (MA) component in the data presents a serious confound to Granger causal analysis, as routinely performed via autoregressive (AR) modeling. We solve this problem by demonstrating that Granger causality may be calculated simply and efficiently from the parameters of a state-space (SS) model. Since SS models are equivalent to autoregressive moving average models, Granger causality estimated in this fashion is not degraded by the presence of a MA component. This is of particular significance when the data has been filtered, downsampled, observed with noise, or is a subprocess of a higher dimensional process, since all of these operations-commonplace in application domains as diverse as climate science, econometrics, and the neurosciences-induce a MA component. We show how Granger causality, conditional and unconditional, in both time and frequency domains, may be calculated directly from SS model parameters via solution of a discrete algebraic Riccati equation. Numerical simulations demonstrate that Granger causality estimators thus derived have greater statistical power and smaller bias than AR estimators. We also discuss how the SS approach facilitates relaxation of the assumptions of linearity, stationarity, and homoscedasticity underlying current AR methods, thus opening up potentially significant new areas of research in Granger causal analysis.

  18. Two roads to noncommutative causality

    NASA Astrophysics Data System (ADS)

    Besnard, Fabien

    2015-08-01

    We review the physical motivations and the mathematical results obtained so far in the isocone-based approach to noncommutative causality. We also give a briefer account of the alternative framework of Franco and Eckstein which is based on Lorentzian spectral triples. We compare the two theories on the simple example of the product geometry of the Minkowski plane by the finite noncommutative space with algebra M2(C).

  19. Causal Learning Across Domains

    ERIC Educational Resources Information Center

    Schulz, Laura E.; Gopnik, Alison

    2004-01-01

    Five studies investigated (a) children's ability to use the dependent and independent probabilities of events to make causal inferences and (b) the interaction between such inferences and domain-specific knowledge. In Experiment 1, preschoolers used patterns of dependence and independence to make accurate causal inferences in the domains of…

  20. Repeated Causal Decision Making

    ERIC Educational Resources Information Center

    Hagmayer, York; Meder, Bjorn

    2013-01-01

    Many of our decisions refer to actions that have a causal impact on the external environment. Such actions may not only allow for the mere learning of expected values or utilities but also for acquiring knowledge about the causal structure of our world. We used a repeated decision-making paradigm to examine what kind of knowledge people acquire in…

  1. Causality in Classical Electrodynamics

    ERIC Educational Resources Information Center

    Savage, Craig

    2012-01-01

    Causality in electrodynamics is a subject of some confusion, especially regarding the application of Faraday's law and the Ampere-Maxwell law. This has led to the suggestion that we should not teach students that electric and magnetic fields can cause each other, but rather focus on charges and currents as the causal agents. In this paper I argue…

  2. Causality in Classical Electrodynamics

    ERIC Educational Resources Information Center

    Savage, Craig

    2012-01-01

    Causality in electrodynamics is a subject of some confusion, especially regarding the application of Faraday's law and the Ampere-Maxwell law. This has led to the suggestion that we should not teach students that electric and magnetic fields can cause each other, but rather focus on charges and currents as the causal agents. In this paper I argue…

  3. Postmenopausal women with abdominal obesity choosing a nutritional approach for weight loss: A decisional needs assessment.

    PubMed

    Poirier, Nadine; Légaré, France; Stacey, Dawn; Lemieux, Simone; Bégin, Catherine; Lapointe, Annie; Desroches, Sophie

    2016-12-01

    To identify the decisional needs of postmenopausal women with abdominal obesity choosing between two nutritional approaches for weight loss: a low-fat diet or a diet rich in fruit and vegetables. Our descriptive qualitative study was based on the Ottawa Decision Support Framework. Four focus groups were conducted with postmenopausal women. A thematic content analysis was performed to determine the decisional needs influencing the choice of a low-fat diet or a diet rich in fruit and vegetables. Seventeen postmenopausal women participated in the study (median age 59 years). Most frequently reported decisional needs for each nutritional approach were sufficient levels of nutritional skills and knowledge, consideration of the physiological impacts and the sensory aspect of approaches, food availability, social support, finances and motivation. Partners, friends and daughters were considered as the most important individuals involved in the decision. We identified several decisional needs influencing postmenopausal women when choosing between a low-fat diet and a diet rich in fruit and vegetables. These findings could inform the design of decision support interventions that address the decisional needs of women for making and implementing informed decisions about a nutritional approach for weight loss. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  4. Understanding the subjective experiences and needs of patients as they approach death.

    PubMed

    Sartori, Penny

    When patients are approaching the end of life their spiritual as well as physical needs should be considered. This article considers how nurses can best support patients who are dying and work to ensure they experience a peaceful transition to death. Attending to their spiritual needs is shown to be of utmost importance; the near death and end of life experiences that some patients may have are also taken into consideration.

  5. Agency, time, and causality

    PubMed Central

    Widlok, Thomas

    2014-01-01

    Cognitive Scientists interested in causal cognition increasingly search for evidence from non-Western Educational Industrial Rich Democratic people but find only very few cross-cultural studies that specifically target causal cognition. This article suggests how information about causality can be retrieved from ethnographic monographs, specifically from ethnographies that discuss agency and concepts of time. Many apparent cultural differences with regard to causal cognition dissolve when cultural extensions of agency and personhood to non-humans are taken into account. At the same time considerable variability remains when we include notions of time, linearity and sequence. The article focuses on ethnographic case studies from Africa but provides a more general perspective on the role of ethnography in research on the diversity and universality of causal cognition. PMID:25414683

  6. Agency, time, and causality.

    PubMed

    Widlok, Thomas

    2014-01-01

    Cognitive Scientists interested in causal cognition increasingly search for evidence from non-Western Educational Industrial Rich Democratic people but find only very few cross-cultural studies that specifically target causal cognition. This article suggests how information about causality can be retrieved from ethnographic monographs, specifically from ethnographies that discuss agency and concepts of time. Many apparent cultural differences with regard to causal cognition dissolve when cultural extensions of agency and personhood to non-humans are taken into account. At the same time considerable variability remains when we include notions of time, linearity and sequence. The article focuses on ethnographic case studies from Africa but provides a more general perspective on the role of ethnography in research on the diversity and universality of causal cognition.

  7. Quantum causal graph dynamics

    NASA Astrophysics Data System (ADS)

    Arrighi, Pablo; Martiel, Simon

    2017-07-01

    Consider a graph having quantum systems lying at each node. Suppose that the whole thing evolves in discrete time steps, according to a global, unitary causal operator. By causal we mean that information can only propagate at a bounded speed, with respect to the distance given by the graph. Suppose, moreover, that the graph itself is subject to the evolution, and may be driven to be in a quantum superposition of graphs—in accordance to the superposition principle. We show that these unitary causal operators must decompose as a finite-depth circuit of local unitary gates. This unifies a result on quantum cellular automata with another on reversible causal graph dynamics. Along the way we formalize a notion of causality which is valid in the context of quantum superpositions of time-varying graphs, and has a number of good properties. We discuss some of the implications for quantum gravity.

  8. The Need to Take a Staging Approach to the Biological Mechanisms of PTSD and its Treatment.

    PubMed

    McFarlane, Alexander Cowell; Lawrence-Wood, Eleanor; Van Hooff, Miranda; Malhi, Gin S; Yehuda, Rachel

    2017-02-01

    Despite the substantial body of neurobiological research, no specific drug target has been developed to treat PTSD and there are substantial limitations with the available interventions. We propose that advances are likely to depend on the development of better classification of the heterogeneity of PTSD using a staging approach of disease. A primary rationale for staging is to highlight the probability that distinct therapeutic approaches need to be utilised according to the degree of biological progression of the disorder. Prospective studies, particularly of military populations, provide substantial evidence about the emerging biological abnormalities that precede the full-blown disorder. These need to be targeted with tailored interventions to prevent disease progression. Equally, the neurobiology of chronic unremitting PTSD needs to be differentiated from the acute disorder which emerges across a spectrum of severity, and this range of presentations correspondingly needs to be addressed with differing therapeutic strategies. The staging approach also needs to take account of the range of somatic pathological outcomes that are being identified as a consequence of traumatic stress exposure. PTSD should be conceptualised as a systemic disorder underpinned a range of biological dysregulation, including metabolic and altered immune function, reflected in the increased rates of cardiovascular and autoimmune disease. The effectiveness of novel treatments needs to be judged across their effectiveness in addressing the spectrum of trauma-related pathology.

  9. Student (dis)engagement and need-supportive teaching behavior: a multi-informant and multilevel approach.

    PubMed

    Van den Berghe, Lynn; Tallir, Isabel B; Cardon, Greet; Aelterman, Nathalie; Haerens, Leen

    2015-08-01

    Starting from self-determination theory, we explored whether student engagement/disengagement relates to teachers' need support and whether this relationship is moderated by teachers' causality orientations. A sample of 2004 students situated in 127 classes taught by 33 physical education teachers participated in the study. Both teachers and students reported on students' (dis)engagement, allowing investigation of the proposed relationships both at the student and teacher level. Most of the variance in need support was at the student level, but there was also between-teacher and between-class variance in need support. Engagement related to more need support, but only at the student level. In total, few moderation effects were found. Teachers with a relatively low controlled orientation were more need supportive when perceiving their students as emotionally and behaviorally engaged. By making teachers aware of these dynamics, automatic responses to student engagement can be better thought out. Recommendations for future research are discussed.

  10. Causal inference in obesity research.

    PubMed

    Franks, P W; Atabaki-Pasdar, N

    2017-03-01

    Obesity is a risk factor for a plethora of severe morbidities and premature death. Most supporting evidence comes from observational studies that are prone to chance, bias and confounding. Even data on the protective effects of weight loss from randomized controlled trials will be susceptible to confounding and bias if treatment assignment cannot be masked, which is usually the case with lifestyle and surgical interventions. Thus, whilst obesity is widely considered the major modifiable risk factor for many chronic diseases, its causes and consequences are often difficult to determine. Addressing this is important, as the prevention and treatment of any disease requires that interventions focus on causal risk factors. Disease prediction, although not dependent on knowing the causes, is nevertheless enhanced by such knowledge. Here, we provide an overview of some of the barriers to causal inference in obesity research and discuss analytical approaches, such as Mendelian randomization, that can help to overcome these obstacles. In a systematic review of the literature in this field, we found: (i) probable causal relationships between adiposity and bone health/disease, cancers (colorectal, lung and kidney cancers), cardiometabolic traits (blood pressure, fasting insulin, inflammatory markers and lipids), uric acid concentrations, coronary heart disease and venous thrombosis (in the presence of pulmonary embolism), (ii) possible causal relationships between adiposity and gray matter volume, depression and common mental disorders, oesophageal cancer, macroalbuminuria, end-stage renal disease, diabetic kidney disease, nuclear cataract and gall stone disease, and (iii) no evidence for causal relationships between adiposity and Alzheimer's disease, pancreatic cancer, venous thrombosis (in the absence of pulmonary embolism), liver function and periodontitis. © 2016 The Association for the Publication of the Journal of Internal Medicine.

  11. Psychological trauma and substance abuse: the need for an integrated approach.

    PubMed

    Dass-Brailsford, Priscilla; Myrick, Amie C

    2010-10-01

    There is consensus that an integrated approach which addresses the clinical needs of individuals who have histories of substance abuse and psychological trauma concurrently is an acceptable and preferred approach to treatment. Several integrated models have emerged in recent years. In this paper we first define the concepts of substance abuse and psychological trauma, investigate the relationship between both and proceed to discuss why an integrated approach is most compelling. Finally, we review and critically examine the different integrated models that have been developed in terms of efficacy, effectiveness and empirical evidence. The paper concludes with suggestions on how the field can be improved.

  12. Analysing connectivity with Granger causality and dynamic causal modelling.

    PubMed

    Friston, Karl; Moran, Rosalyn; Seth, Anil K

    2013-04-01

    This review considers state-of-the-art analyses of functional integration in neuronal macrocircuits. We focus on detecting and estimating directed connectivity in neuronal networks using Granger causality (GC) and dynamic causal modelling (DCM). These approaches are considered in the context of functional segregation and integration and--within functional integration--the distinction between functional and effective connectivity. We review recent developments that have enjoyed a rapid uptake in the discovery and quantification of functional brain architectures. GC and DCM have distinct and complementary ambitions that are usefully considered in relation to the detection of functional connectivity and the identification of models of effective connectivity. We highlight the basic ideas upon which they are grounded, provide a comparative evaluation and point to some outstanding issues.

  13. Causality modeling for directed disease network.

    PubMed

    Bang, Sunjoo; Kim, Jae-Hoon; Shin, Hyunjung

    2016-09-01

    Causality between two diseases is valuable information as subsidiary information for medicine which is intended for prevention, diagnostics and treatment. Conventional cohort-centric researches are able to obtain very objective results, however, they demands costly experimental expense and long period of time. Recently, data source to clarify causality has been diversified: available information includes gene, protein, metabolic pathway and clinical information. By taking full advantage of those pieces of diverse information, we may extract causalities between diseases, alternatively to cohort-centric researches. In this article, we propose a new approach to define causality between diseases. In order to find causality, three different networks were constructed step by step. Each step has different data sources and different analytical methods, and the prior step sifts causality information to the next step. In the first step, a network defines association between diseases by utilizing disease-gene relations. And then, potential causalities of disease pairs are defined as a network by using prevalence and comorbidity information from clinical results. Finally, disease causalities are confirmed by a network defined from metabolic pathways. The proposed method is applied to data which is collected from database such as MeSH, OMIM, HuDiNe, KEGG and PubMed. The experimental results indicated that disease causality that we found is 19 times higher than that of random guessing. The resulting pairs of causal-effected diseases are validated on medical literatures. http://www.alphaminers.net shin@ajou.ac.kr Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  14. Causal Networks or Causal Islands? The Representation of Mechanisms and the Transitivity of Causal Judgment

    ERIC Educational Resources Information Center

    Johnson, Samuel G. B.; Ahn, Woo-kyoung

    2015-01-01

    Knowledge of mechanisms is critical for causal reasoning. We contrasted two possible organizations of causal knowledge--an interconnected causal "network," where events are causally connected without any boundaries delineating discrete mechanisms; or a set of disparate mechanisms--causal "islands"--such that events in different…

  15. Causal Networks or Causal Islands? The Representation of Mechanisms and the Transitivity of Causal Judgment

    ERIC Educational Resources Information Center

    Johnson, Samuel G. B.; Ahn, Woo-kyoung

    2015-01-01

    Knowledge of mechanisms is critical for causal reasoning. We contrasted two possible organizations of causal knowledge--an interconnected causal "network," where events are causally connected without any boundaries delineating discrete mechanisms; or a set of disparate mechanisms--causal "islands"--such that events in different…

  16. The Relationship among Student Basic Need Satisfaction, Approaches to Learning, Reporting of Avoidance Strategies and Achievement

    ERIC Educational Resources Information Center

    Betoret, Fernando Domenech; Artiga, Amparo Gomez

    2011-01-01

    Introduction: This study examines the relationship between student basic need satisfaction (autonomy, competence, relatedness and belonging), their reporting of approaches to learning (deep and surface), their reporting of avoidance strategies (avoidance of effort and challenge, avoidance of help seeking and preference to avoid novelty) and…

  17. The Relationship among Student Basic Need Satisfaction, Approaches to Learning, Reporting of Avoidance Strategies and Achievement

    ERIC Educational Resources Information Center

    Betoret, Fernando Domenech; Artiga, Amparo Gomez

    2011-01-01

    Introduction: This study examines the relationship between student basic need satisfaction (autonomy, competence, relatedness and belonging), their reporting of approaches to learning (deep and surface), their reporting of avoidance strategies (avoidance of effort and challenge, avoidance of help seeking and preference to avoid novelty) and…

  18. Career Education for Handicapped Students: A Suggested Approach. Technical Assistance Services: Illinois Special Needs Populations.

    ERIC Educational Resources Information Center

    Miller, Sidney R.; And Others

    This monograph describes a suggested approach to career education for handicapped students that focuses on two aspects of the career development process, career exploration and development of an academic program reflecting vocational needs. Discussed in the section on career exploration are career goals, the teacher-counselor role, individual…

  19. Access and Quality in Nigeria's Higher Education: Need for a Pragmatic Approach for Sustainable Transformation

    ERIC Educational Resources Information Center

    Njoku, Joy N.

    2016-01-01

    Access and quality of higher education are among the major criteria for assessing the product of any institution of higher learning. This paper discusses access and quality in Nigeria's higher education; need for a pragmatic approach for sustainable transformation. It discusses problems of access in the areas of carrying capacity of universities,…

  20. The Need for a Culturally Relevant Approach to Gifted Education: The Case of Cyprus

    ERIC Educational Resources Information Center

    Ieridou, Alexandra N.

    2013-01-01

    This article presents an overview of the status of gifted education in Cyprus and argues for the need for a culturally relevant approach. First, the history of education in Cyprus is briefly reviewed. Then, past unsuccessful efforts to provide education for academically advanced students in the public elementary schools are critically examined.…

  1. The Special Needs of Women: A Plea for an Integrated Approach and Some Programme Proposals.

    ERIC Educational Resources Information Center

    Bharadwaj, Geeta R.; Srivastava, Suman

    The paper examines family planning and nutrition needs as well as education and employment while exploring ideas of how an integrated approach is possible in promoting quality of both the reproductive and productive sphere of women's lives. It is suggested that understanding women's differential role will make it possible for planners, policy…

  2. [The causal relationship].

    PubMed

    Glemain, P

    2000-09-01

    Only the controlled trial method, clinical equivalent to the experimental method, with its successive phases and randomization, is able to confirm a real causal relationship and quantify the risk of error (alpha). However, the study must have sufficient power and randomization must not have resulted in an unbalanced distribution of various parameters likely to influence the result. Other methods, particularly surveys and case studies, only provide presumptions of causality. This review article, illustrated by three examples from the urological literature, is designed to demonstrate the difficulties of establishing a causal relationship when possible biases and confounding factors are taken into account.

  3. Prehospital fluid resuscitation in hypotensive trauma patients: do we need a tailored approach?

    PubMed

    Geeraedts, Leo M G; Pothof, Leonie A H; Caldwell, Erica; de Lange-de Klerk, Elly S M; D'Amours, Scott K

    2015-01-01

    The ideal strategy for prehospital intravenous fluid resuscitation in trauma remains unclear. Fluid resuscitation may reverse shock but aggravate bleeding by raising blood pressure and haemodilution. We examined the effect of prehospital i.v. fluid on the physiologic status and need for blood transfusion in hypotensive trauma patients after their arrival in the emergency department (ED). Retrospective analysis of trauma patients (n=941) with field hypotension presenting to a level 1 trauma centre. Regression models were used to investigate associations between prehospital fluid volumes and shock index and blood transfusion respectively in the emergency department and mortality at 24h. A 1L increase of prehospital i.v. fluid was associated with a 7% decrease of shock index in the emergency department (p<0.001). Volumes of 0.5-1L and 1-2L were associated with reduced likelihood of shock as compared to volumes of 0-0.5L: OR 0.61 (p=0.03) and OR 0.54 (p=0.02), respectively. Volumes of 1-2L were also associated with an increased likelihood of receiving blood transfusion in ED: OR 3.27 (p<0.001). Patients who had received volumes of >2L have a much greater likelihood of receiving blood transfusion in ED: OR 9.92 (p<0.001). Mortality at 24h was not associated with prehospital i.v. fluids. In hypotensive trauma patients, prehospital i.v. fluids were associated with a reduction of likelihood of shock upon arrival in ED. However, volumes of >1L were associated with a markedly increased likelihood of receiving blood transfusion in ED. Therefore, decision making regarding prehospital i.v. fluid resuscitation is critical and may need to be tailored to the individual situation. Further research is needed to clarify whether a causal relationship exists between prehospital i.v. fluid volume and blood transfusion. Also, prospective trials on prehospital i.v. fluid resuscitation strategies in specific patient subgroups (e.g. traumatic brain injury and concomitant haemorrhage) are

  4. Predicting Cell Cycle Regulated Genes by Causal Interactions

    PubMed Central

    Emmert-Streib, Frank; Dehmer, Matthias

    2009-01-01

    The fundamental difference between classic and modern biology is that technological innovations allow to generate high-throughput data to get insights into molecular interactions on a genomic scale. These high-throughput data can be used to infer gene networks, e.g., the transcriptional regulatory or signaling network, representing a blue print of the current dynamical state of the cellular system. However, gene networks do not provide direct answers to biological questions, instead, they need to be analyzed to reveal functional information of molecular working mechanisms. In this paper we propose a new approach to analyze the transcriptional regulatory network of yeast to predict cell cycle regulated genes. The novelty of our approach is that, in contrast to all other approaches aiming to predict cell cycle regulated genes, we do not use time series data but base our analysis on the prior information of causal interactions among genes. The major purpose of the present paper is to predict cell cycle regulated genes in S. cerevisiae. Our analysis is based on the transcriptional regulatory network, representing causal interactions between genes, and a list of known periodic genes. No further data are used. Our approach utilizes the causal membership of genes and the hierarchical organization of the transcriptional regulatory network leading to two groups of periodic genes with a well defined direction of information flow. We predict genes as periodic if they appear on unique shortest paths connecting two periodic genes from different hierarchy levels. Our results demonstrate that a classical problem as the prediction of cell cycle regulated genes can be seen in a new light if the concept of a causal membership of a gene is applied consequently. This also shows that there is a wealth of information buried in the transcriptional regulatory network whose unraveling may require more elaborate concepts than it might seem at first. PMID:19688096

  5. Meeting water needs for sustainable development: an overview of approaches, measures and data sources

    NASA Astrophysics Data System (ADS)

    Lissner, Tabea; Reusser, Dominik E.; Sullivan, Caroline A.; Kropp, Jürgen P.

    2013-04-01

    An essential part of a global transition towards sustainability is the Millennium Development Goals (MDG), providing a blueprint of goals to meet human needs. Water is an essential resource in itself, but also a vital factor of production for food, energy and other industrial products. Access to sufficient water has only recently been recognized as a human right. One central MDG is halving the population without access to safe drinking water and sanitation. To adequately assess the state of development and the potential for a transition towards sustainability, consistent and meaningful measures of water availability and adequate access are thus fundamental. Much work has been done to identify thresholds and definitions to measure water scarcity. This includes some work on defining basic water needs of different sectors. A range of data and approaches has been made available from a variety of sources, but all of these approaches differ in their underlying assumptions, the nature of the data used, and consequently in the final results. We review and compare approaches, methods and data sources on human water use and human water needs. This data review enables identifying levels of consumption in different countries and different sectors. Further comparison is made between actual water needs (based on human and ecological requirements), and recognised levels of water abstraction. The results of our review highlight the differences between different accounts of water use and needs, and reflect the importance of standardised approaches to data definitions and measurements, making studies more comparable across space and time. The comparison of different use and allocation patterns in countries enables levels of water use to be identified which allow for an adequate level of human wellbeing to be maintained within sustainable water abstraction limits. Recommendations are provided of how data can be defined more clearly to make comparisons of water use more meaningful and

  6. Causal networks in EIA

    SciTech Connect

    Perdicoulis, Anastassios . E-mail: tasso@utad.pt; Glasson, John . E-mail: jglasson@brookes.ac.uk

    2006-08-15

    Causal networks have been used in Environmental Impact Assessment (EIA) since its early days, but they appear to have a minimal use in modern practice. This article reviews the typology of causal networks in EIA as well as in other academic and professional fields, verifies their contribution to EIA against the principles and requirements of the process, and discusses alternative scenarios for their future in EIA.

  7. High school teachers' perspectives on effective approaches for teaching biology to students with special needs

    NASA Astrophysics Data System (ADS)

    Kos, Agnieszka

    The demands of national educational reforms require high school biology teachers to provide high quality instruction to students with and without special needs. The reforms, however, do not provide teachers with adequate teaching strategies to meet the needs of all students in the same context. The purpose of this grounded theory study was to understand high school biology teachers' perspectives, practices, and challenges in relation to teaching students with special needs. This approach was used to develop a substantive model for high school biology teachers who are challenged with teaching students with and without special needs. Data were collected via in-depth interviews with 15 high school teachers in a Midwestern school district. The data were analyzed using open coding, axial coding, and selective coding procedures in accordance with the grounded theory approach. Essential model components included skills and training for teachers, classroom management strategies, teaching strategies, and student skills. The emergent substantive theory indicated that that teacher preparation and acquired skills greatly influence the effectiveness of inclusion implementation. Key findings also indicated the importance of using of a variety of instructional strategies and classroom management strategies that address students' special needs and their learning styles. This study contributes to social change by providing a model for teaching students and effectively implementing inclusion in regular science classrooms. Following further study, this model may be used to support teacher professional development and improve teaching practices that in turn may improve science literacy supported by the national educational reforms.

  8. Obesity and infection: reciprocal causality.

    PubMed

    Hainer, V; Zamrazilová, H; Kunešová, M; Bendlová, B; Aldhoon-Hainerová, I

    2015-01-01

    Associations between different infectious agents and obesity have been reported in humans for over thirty years. In many cases, as in nosocomial infections, this relationship reflects the greater susceptibility of obese individuals to infection due to impaired immunity. In such cases, the infection is not related to obesity as a causal factor but represents a complication of obesity. In contrast, several infections have been suggested as potential causal factors in human obesity. However, evidence of a causal linkage to human obesity has only been provided for adenovirus 36 (Adv36). This virus activates lipogenic and proinflammatory pathways in adipose tissue, improves insulin sensitivity, lipid profile and hepatic steatosis. The E4orf1 gene of Adv36 exerts insulin senzitizing effects, but is devoid of its pro-inflammatory modalities. The development of a vaccine to prevent Adv36-induced obesity or the use of E4orf1 as a ligand for novel antidiabetic drugs could open new horizons in the prophylaxis and treatment of obesity and diabetes. More experimental and clinical studies are needed to elucidate the mutual relations between infection and obesity, identify additional infectious agents causing human obesity, as well as define the conditions that predispose obese individuals to specific infections.

  9. A New Approach for Assessing the Needs of Service Members and Their Families

    DTIC Science & Technology

    2011-01-01

    for members and spouses, utilization and satisfaction with the MWR programs and services were significant predictors of satisfaction with different...cohesion, career issues, and satisfaction with Army quality of life. They found that for Soldiers, usage of MWR programs and services had a...review to ensure high standards for research quality and objectivity. A New Approach for Assessing the Needs of Service Members and Their Families

  10. Coping with dating errors in causality estimation

    NASA Astrophysics Data System (ADS)

    Smirnov, D. A.; Marwan, N.; Breitenbach, S. F. M.; Lechleitner, F.; Kurths, J.

    2017-01-01

    We consider the problem of estimating causal influences between observed processes from time series possibly corrupted by errors in the time variable (dating errors) which are typical in palaeoclimatology, planetary science and astrophysics. “Causality ratio” based on the Wiener-Granger causality is proposed and studied for a paradigmatic class of model systems to reveal conditions under which it correctly indicates directionality of unidirectional coupling. It is argued that in the case of a priori known directionality, the causality ratio allows a characterization of dating errors and observational noise. Finally, we apply the developed approach to palaeoclimatic data and quantify the influence of solar activity on tropical Atlantic climate dynamics over the last two millennia. A stronger solar influence in the first millennium A.D. is inferred. The results also suggest a dating error of about 20 years in the solar proxy time series over the same period.

  11. Effective connectivity: Influence, causality and biophysical modeling

    PubMed Central

    Valdes-Sosa, Pedro A.; Roebroeck, Alard; Daunizeau, Jean; Friston, Karl

    2011-01-01

    This is the final paper in a Comments and Controversies series dedicated to “The identification of interacting networks in the brain using fMRI: Model selection, causality and deconvolution”. We argue that discovering effective connectivity depends critically on state-space models with biophysically informed observation and state equations. These models have to be endowed with priors on unknown parameters and afford checks for model Identifiability. We consider the similarities and differences among Dynamic Causal Modeling, Granger Causal Modeling and other approaches. We establish links between past and current statistical causal modeling, in terms of Bayesian dependency graphs and Wiener–Akaike–Granger–Schweder influence measures. We show that some of the challenges faced in this field have promising solutions and speculate on future developments. PMID:21477655

  12. Considerations on causality in pharmacovigilance.

    PubMed

    Edwards, I Ralph

    2012-01-01

    Causality has been a topic of debate by philosophers, scientists, lawyers and for centuries. It is essential to define as precisely as possible all steps in the logical chain of events, since each may strengthen or confound an argument. Almost always there are issues of missing and conflicting data that need to be addressed specifically. In pharmacovigilance, as in many other situations, there is not just one possible causation for an effect but several. Each must be evaluated in the given context for probability. There is also likely to be a causal chain of events to the adverse effect under consideration, and each must be considered. In an individual patient diagnosis the components of patient history, clinical findings and various laboratory test findings are combined to point to the probability of the patho-physiological diagnosis, which in turn is related to possible causes with a strength determined by the constellation of findings. The established Bradford-Hill criteria are valuable in considering all the possible causal factors. Pharmacoepidemiology allows for population incidences of causes for particular effects and therefore provides an a priori probability listing for competing possible causes, or at least of one possible cause against the background of all others in a control group. Since adverse effects of medicines are generally rare, it is not possible to exclude drug causation in an individual by reliance on epidemiological evidence alone, only to argue that the incidence is below a level determined by statistical power, of the study or studies combined. Other areas of society are concerned with the process of causal inference, and this is especially true in legal cases in which judgements are made on possible personal injury by drugs.

  13. On the Brink of Shifting Paradigms, Molecular Systems Engineering Ethics Needs to Take a Proactive Approach.

    PubMed

    Heidari, Raheleh; Elger, Bernice S; Stutzki, Ralf

    2016-01-01

    Molecular Systems Engineering (MSE) is a paradigm shift in both engineering and life sciences. While the field is still in its infancy the perspectives of MSE in revolutionising technology is promising. MSE will offer a wide range of applications in clinical, biotechnological and engineering fields while simultaneously posing serious questions on the ethical and societal aspects of such technology. The moral and societal aspects of MSE need systematic investigation from scientific and social perspectives. In a democratic setting, the societal outcomes of MSE's cutting-edge technology need to be consulted and influenced by society itself. For this purpose MSE needs inclusive public engagement strategies that bring together the public, ethicists, scientists and policy makers for optimum flow of information that maximizes the impact of public engagement. In this report we present an MSE consortium and its ethics framework for establishing a proactive approach in the study of the ethics of MSE technology.

  14. Support for information management in critical care: a new approach to identify needs.

    PubMed Central

    Rosenal, T. W.; Forsythe, D. E.; Musen, M. A.; Seiver, A.

    1995-01-01

    Managing information is necessary to support clinical decision making and action in critical care. By understanding the nature of information management and its relationship to sound clinical practice, we should come to use technology more wisely. We demonstrated that a new approach inspired by ethnographic research methods could identify useful and unexpected findings about clinical information management. In this approach, a clinician experienced in a specific domain (critical care), with advice from a medical anthropologist, made short-term observations of information management in that domain. We identified 8 areas in a critical care Unit in which information management was seriously in need of better support. We also found interesting differences in how these needs were viewed by nurses and physicians. Our interest in this approach was at two levels: 1. Identify and describe representative instances of sub-optimal information management in a critical care Unit. 2. Investigate the effectiveness of such short-term observations by clinicians. Our long-range goal is to explore the use of this approach and the information it reveals to optimize the process of developing and selecting new information support tools, preparing for their introduction, and optimizing clinical outcomes. PMID:8563267

  15. Computer-Aided Experiment Planning toward Causal Discovery in Neuroscience

    PubMed Central

    Matiasz, Nicholas J.; Wood, Justin; Wang, Wei; Silva, Alcino J.; Hsu, William

    2017-01-01

    Computers help neuroscientists to analyze experimental results by automating the application of statistics; however, computer-aided experiment planning is far less common, due to a lack of similar quantitative formalisms for systematically assessing evidence and uncertainty. While ontologies and other Semantic Web resources help neuroscientists to assimilate required domain knowledge, experiment planning requires not only ontological but also epistemological (e.g., methodological) information regarding how knowledge was obtained. Here, we outline how epistemological principles and graphical representations of causality can be used to formalize experiment planning toward causal discovery. We outline two complementary approaches to experiment planning: one that quantifies evidence per the principles of convergence and consistency, and another that quantifies uncertainty using logical representations of constraints on causal structure. These approaches operationalize experiment planning as the search for an experiment that either maximizes evidence or minimizes uncertainty. Despite work in laboratory automation, humans must still plan experiments and will likely continue to do so for some time. There is thus a great need for experiment-planning frameworks that are not only amenable to machine computation but also useful as aids in human reasoning. PMID:28243197

  16. Computer-Aided Experiment Planning toward Causal Discovery in Neuroscience.

    PubMed

    Matiasz, Nicholas J; Wood, Justin; Wang, Wei; Silva, Alcino J; Hsu, William

    2017-01-01

    Computers help neuroscientists to analyze experimental results by automating the application of statistics; however, computer-aided experiment planning is far less common, due to a lack of similar quantitative formalisms for systematically assessing evidence and uncertainty. While ontologies and other Semantic Web resources help neuroscientists to assimilate required domain knowledge, experiment planning requires not only ontological but also epistemological (e.g., methodological) information regarding how knowledge was obtained. Here, we outline how epistemological principles and graphical representations of causality can be used to formalize experiment planning toward causal discovery. We outline two complementary approaches to experiment planning: one that quantifies evidence per the principles of convergence and consistency, and another that quantifies uncertainty using logical representations of constraints on causal structure. These approaches operationalize experiment planning as the search for an experiment that either maximizes evidence or minimizes uncertainty. Despite work in laboratory automation, humans must still plan experiments and will likely continue to do so for some time. There is thus a great need for experiment-planning frameworks that are not only amenable to machine computation but also useful as aids in human reasoning.

  17. Context Specificity in Causal Signaling Networks Revealed by Phosphoprotein Profiling.

    PubMed

    Hill, Steven M; Nesser, Nicole K; Johnson-Camacho, Katie; Jeffress, Mara; Johnson, Aimee; Boniface, Chris; Spencer, Simon E F; Lu, Yiling; Heiser, Laura M; Lawrence, Yancey; Pande, Nupur T; Korkola, James E; Gray, Joe W; Mills, Gordon B; Mukherjee, Sach; Spellman, Paul T

    2017-01-25

    Signaling networks downstream of receptor tyrosine kinases are among the most extensively studied biological networks, but new approaches are needed to elucidate causal relationships between network components and understand how such relationships are influenced by biological context and disease. Here, we investigate the context specificity of signaling networks within a causal conceptual framework using reverse-phase protein array time-course assays and network analysis approaches. We focus on a well-defined set of signaling proteins profiled under inhibition with five kinase inhibitors in 32 contexts: four breast cancer cell lines (MCF7, UACC812, BT20, and BT549) under eight stimulus conditions. The data, spanning multiple pathways and comprising ∼70,000 phosphoprotein and ∼260,000 protein measurements, provide a wealth of testable, context-specific hypotheses, several of which we experimentally validate. Furthermore, the data provide a unique resource for computational methods development, permitting empirical assessment of causal network learning in a complex, mammalian setting. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  18. Causality discovery technology

    NASA Astrophysics Data System (ADS)

    Chen, M.; Ertl, T.; Jirotka, M.; Trefethen, A.; Schmidt, A.; Coecke, B.; Bañares-Alcántara, R.

    2012-11-01

    Causality is the fabric of our dynamic world. We all make frequent attempts to reason causation relationships of everyday events (e.g., what was the cause of my headache, or what has upset Alice?). We attempt to manage causality all the time through planning and scheduling. The greatest scientific discoveries are usually about causality (e.g., Newton found the cause for an apple to fall, and Darwin discovered natural selection). Meanwhile, we continue to seek a comprehensive understanding about the causes of numerous complex phenomena, such as social divisions, economic crisis, global warming, home-grown terrorism, etc. Humans analyse and reason causality based on observation, experimentation and acquired a priori knowledge. Today's technologies enable us to make observations and carry out experiments in an unprecedented scale that has created data mountains everywhere. Whereas there are exciting opportunities to discover new causation relationships, there are also unparalleled challenges to benefit from such data mountains. In this article, we present a case for developing a new piece of ICT, called Causality Discovery Technology. We reason about the necessity, feasibility and potential impact of such a technology.

  19. Causal conditionals and counterfactuals

    PubMed Central

    Frosch, Caren A.; Byrne, Ruth M.J.

    2012-01-01

    Causal counterfactuals e.g., ‘if the ignition key had been turned then the car would have started’ and causal conditionals e.g., ‘if the ignition key was turned then the car started’ are understood by thinking about multiple possibilities of different sorts, as shown in six experiments using converging evidence from three different types of measures. Experiments 1a and 1b showed that conditionals that comprise enabling causes, e.g., ‘if the ignition key was turned then the car started’ primed people to read quickly conjunctions referring to the possibility of the enabler occurring without the outcome, e.g., ‘the ignition key was turned and the car did not start’. Experiments 2a and 2b showed that people paraphrased causal conditionals by using causal or temporal connectives (because, when), whereas they paraphrased causal counterfactuals by using subjunctive constructions (had…would have). Experiments 3a and 3b showed that people made different inferences from counterfactuals presented with enabling conditions compared to none. The implications of the results for alternative theories of conditionals are discussed. PMID:22858874

  20. Health care providers and adolescents' perspectives towards adolescents' health education needs: a need assessment based on comparative approach.

    PubMed

    Shahhosseini, Zohreh; Abedian, Kobra

    2015-02-01

    Health care providers have considerable influence on adolescents' health promotion. Thus, it is important to focus on the views of this group as one of the most reliable sources in the evaluation of teenagers' health needs. The aim of this study was to compare the attitudes of Iranian health care providers and adolescents towards the latter's health education needs. A quantitative cross-sectional survey, including 72 health care providers and 402 female students from 14 high schools in northern Iran, was carried out in 2011. Topics in a self-administrated questionnaire covered the participants' perspectives towards the educational health needs of adolescents in a five-point Likert scale. Findings revealed from health care providers' views indicate that the highest mean score was assigned to "Education about prevention of sexual high risk behavior", which was significantly different from adolescents' perspective (t=8.42, p<0.05). RESULTS showed that health care providers and adolescents both emphasized on the mothers' role as the most reliable source of adolescents' education (t=1.85, p>0.05). Provision of health education programs for adolescents, which are based on integration of health care providers' perspectives and the adolescents' views, are essential in meeting adolescents' educational health needs.

  1. Reference Data Layers for Earth and Environmental Science: History, Frameworks, Science Needs, Approaches, and New Technologies

    NASA Astrophysics Data System (ADS)

    Lenhardt, W. C.

    2015-12-01

    Global Mapping Project, Web-enabled Landsat Data (WELD), International Satellite Land Surface Climatology Project (ISLSCP), hydrology, solid earth dynamics, sedimentary geology, climate modeling, integrated assessments and so on all have needs for or have worked to develop consistently integrated data layers for Earth and environmental science. This paper will present an overview of an abstract notion of data layers of this types, what we are referring to as reference data layers for Earth and environmental science, highlight some historical examples, and delve into new approaches. The concept of reference data layers in this context combines data availability, cyberinfrastructure and data science, as well as domain science drivers. We argue that current advances in cyberinfrastructure such as iPython notebooks and integrated science processing environments such as iPlant's Discovery Environment coupled with vast arrays of new data sources warrant another look at the how to create, maintain, and provide reference data layers. The goal is to provide a context for understanding science needs for reference data layers to conduct their research. In addition, to the topics described above this presentation will also outline some of the challenges to and present some ideas for new approaches to addressing these needs. Promoting the idea of reference data layers is relevant to a number of existing related activities such as EarthCube, RDA, ESIP, the nascent NSF Regional Big Data Innovation Hubs and others.

  2. Taking health needs seriously: against a luck egalitarian approach to justice in health.

    PubMed

    Nielsen, Lasse

    2013-08-01

    In recent works, Shlomi Segall suggests and defends a luck egalitarian approach to justice in health. Concurring with G. A. Cohen's mature position he defends the idea that people should be compensated for "brute luck", i.e. the outcome of actions that it would be unreasonable to expect them to avoid. In his defense of the luck egalitarian approach he seeks to rebut the criticism raised by Norman Daniels that luck egalitarianism is in some way too narrow and in another too wide to uphold justice in health and health care distribution. He points out that a pluralistic outline of luck egalitarianism taking into account the moral requirement of meeting everyone's basic needs can avoid this line of criticism. In this article I argue against the application of such pluralistic luck egalitarianism in matters of health distribution. First of all, Segall has not shown that luck egalitarianism handles well health distributions above a threshold of basic needs. Secondly, his way of avoiding Elizabeth Anderson's abandonment objection is theoretically problematic. Finally, I argue that luck egalitarianism in general fails to acknowledge the moral foundation of health and health care as a basic human entitlement. Thus I conclude that luck egalitarianism fails to take health needs seriously and that it cannot therefore uphold justice in health.

  3. Causal networks or causal islands? The representation of mechanisms and the transitivity of causal judgment

    PubMed Central

    Johnson, Samuel G. B.; Ahn, Woo-kyoung

    2014-01-01

    Knowledge of mechanisms is critical for causal reasoning. We contrasted two possible organizations of causal knowledge—an interconnected causal network, where events are causally connected without any boundaries delineating discrete mechanisms; or a set of disparate mechanisms—causal islands—such that events in different mechanisms are not thought to be related even when they belong to the same causal chain. To distinguish these possibilities, we used causal transitivity—the inference given A causes B and B causes C that A causes C. Specifically, causal chains schematized as one chunk or mechanism in semantic memory (e.g., exercising, becoming thirsty, drinking water) led to transitive causal judgments. On the other hand, chains schematized as multiple chunks (e.g., having sex, becoming pregnant, becoming nauseous) led to intransitive judgments despite strong intermediate links (Experiments 1–3). Normative accounts of causal intransitivity could not explain these intransitive judgments (Experiments 4–5). PMID:25556901

  4. Can Granger causality delineate natural versus anthropogenic drivers of climate change from global-average multivariate time series?

    NASA Astrophysics Data System (ADS)

    Kodra, E. A.; Chatterjee, S.; Ganguly, A. R.

    2009-12-01

    The Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC) notes with a high degree of certainty that global warming can be attributed to anthropogenic emissions. Detection and attribution studies, which attempt to delineate human influences on regional- and decadal-scale climate change or its impacts, use a variety of techniques, including Granger causality. Recently, Granger causality was used as a tool for detection and attribution in climate based on a spatio-temporal data mining approach. However, the degree to which Granger causality may be able to delineate natural versus anthropogenic drivers of change in these situations needs to be thoroughly investigated. As a first step, we use multivariate global-average time series of observations to test the performance of Granger causality. We apply the popular Granger F-tests to Radiative Forcing (RF), which is a transformation of carbon dioxide (CO2), and Global land surface Temperature anomalies (GT). Our preliminary results with observations appear to suggest that RF Granger-causes GT, which seem to become more apparent with more data. However, carefully designed simulations indicate that these results are not reliable and may, in fact, be misleading. On the other hand, the same observation- and simulation-driven methodologies, when applied to the El Niño Southern Oscillation (ENSO) index, clearly show reliable Granger-causality from ENSO to GT. We develop and test several hypotheses to explain why the Granger causality tests between RF and GT are not reliable. We conclude that the form of Granger causality used in this study, and in past studies reported in the literature, is sensitive to data availability, random variability, and especially whether the variables arise from a deterministic or stochastic process. Simulations indicate that Granger causality in this form performs poorly, even in simple linear effect cases, when applied to one deterministic and one stochastic time

  5. Critical review of forensic trace evidence analysis and the need for a new approach.

    PubMed

    Stoney, David A; Stoney, Paul L

    2015-06-01

    The historical development, contributions and limitations of the two traditional approaches to trace evidence analysis are reviewed. The first approach was as generalist practitioner, looking broadly at an assemblage of many different particle types. The second was that of specialist practitioner, with attention focused on one specific particle type. Four factors have significantly impacted the effectiveness of these approaches: (1) increasing technological capabilities, (2) increasing complexity in the character of manufactured materials, (3) changes in forensic laboratory management, and (4) changing scientific and legal expectations. The effectiveness of each approach is assessed within the context of these changes. More recently, new technologies have been applied to some trace evidence problems, intended to address one or more limitations. This has led to a third approach founded on discrete, highly technical methods addressing specific analytical problems. After evaluating the contributions and limitations of this third approach, we consider the different ways that technologies could be developed to address unmet needs in forensic trace evidence analysis. The route toward effective use of new technologies is contrasted with how forensic science laboratories are currently choosing and employing them. The conclusion is that although new technologies are contributing, we are not on a path that will result in their most effective and appropriate use. A new approach is required. Based on an analysis of the contributions of each of the three exisiting approaches, seven characteristics of an effective trace evidence analysis capability were determined: (1) particle traces should be a major problem-solving tool, (2) there should be readily available, straightforward methods to enable their use, (3) all available and potentially useful particle types should be considered, (4) decisions to use them should be made in the context of each case, guided by what they can

  6. Causality assessment for suspected DILI during clinical phases of drug development.

    PubMed

    Regev, Arie; Seeff, Leonard B; Merz, Michael; Ormarsdottir, Sif; Aithal, Guruprasad P; Gallivan, Jim; Watkins, Paul B

    2014-11-01

    Causality assessment is a critical step in establishing the diagnosis of drug induced liver injury (DILI) during drug development. DILI may resemble almost any type of liver disease, and often presents a serious challenge to clinical investigators and drug makers. The diagnosis of DILI is largely based upon a combination of a compatible clinical course, exclusion of all other reasonable causes, resemblance of clinical and pathological features to known features of liver injury due to the drug (i.e., "drug's signature"), and incidence of liver injury among patients treated with the drug compared to placebo or comparator. Causality assessment for suspected DILI is currently performed using either evaluation by physicians with expertise in liver disorders (i.e., expert opinion) or standardized scoring instruments such as the Roussel Uclaf Causality Assessment Method (RUCAM). Both approaches are widely used in the post marketing setting. Causality assessment based on expert opinion is considered superior to standardized instruments such as RUCAM, in the setting of drug development, and is currently the preferred approach during clinical trials. There is a need for a systematic revision of RUCAM that will render it more suitable for the setting of clinical trials and drug development. Careful monitoring and meticulous data collection during clinical trials are essential in all cases with established liver injury to allow for a proper causality assessment. A workshop was convened to discuss best practices for the assessment of drug-induced liver injury (DILI) in clinical trials. This publication is based on the conclusions of this workshop.

  7. Forecasting the global shortage of physicians: an economic- and needs-based approach.

    PubMed

    Scheffler, Richard M; Liu, Jenny X; Kinfu, Yohannes; Dal Poz, Mario R

    2008-07-01

    Global achievements in health may be limited by critical shortages of health-care workers. To help guide workforce policy, we estimate the future demand for, need for and supply of physicians, by WHO region, to determine where likely shortages will occur by 2015, the target date of the Millennium Development Goals. Using World Bank and WHO data on physicians per capita from 1980 to 2001 for 158 countries, we employ two modelling approaches for estimating the future global requirement for physicians. A needs-based model determines the number of physicians per capita required to achieve 80% coverage of live births by a skilled health-care attendant. In contrast, our economic model identifies the number of physicians per capita that are likely to be demanded, given each country's economic growth. These estimates are compared to the future supply of physicians projected by extrapolating the historical rate of increase in physicians per capita for each country. By 2015, the global supply of physicians appears to be in balance with projected economic demand. Because our measure of need reflects the minimum level of workforce density required to provide a basic health service that is met in all but the least developed countries, the needs-based estimates predict a global surplus of physicians. However, on a regional basis, both models predict shortages for many countries in the WHO African Region in 2015, with some countries experiencing a needs-based shortage, a demand-based shortage, or both. The type of policy intervention needed to alleviate projected shortages, such as increasing health-care training or adopting measures to discourage migration, depends on the type of shortage projected.

  8. Causal Discovery from Subsampled Time Series Data by Constraint Optimization

    PubMed Central

    Hyttinen, Antti; Plis, Sergey; Järvisalo, Matti; Eberhardt, Frederick; Danks, David

    2017-01-01

    This paper focuses on causal structure estimation from time series data in which measurements are obtained at a coarser timescale than the causal timescale of the underlying system. Previous work has shown that such subsampling can lead to significant errors about the system’s causal structure if not properly taken into account. In this paper, we first consider the search for the system timescale causal structures that correspond to a given measurement timescale structure. We provide a constraint satisfaction procedure whose computational performance is several orders of magnitude better than previous approaches. We then consider finite-sample data as input, and propose the first constraint optimization approach for recovering the system timescale causal structure. This algorithm optimally recovers from possible conflicts due to statistical errors. More generally, these advances allow for a robust and non-parametric estimation of system timescale causal structures from subsampled time series data. PMID:28203316

  9. Causal Discovery from Subsampled Time Series Data by Constraint Optimization.

    PubMed

    Hyttinen, Antti; Plis, Sergey; Järvisalo, Matti; Eberhardt, Frederick; Danks, David

    2016-08-01

    This paper focuses on causal structure estimation from time series data in which measurements are obtained at a coarser timescale than the causal timescale of the underlying system. Previous work has shown that such subsampling can lead to significant errors about the system's causal structure if not properly taken into account. In this paper, we first consider the search for the system timescale causal structures that correspond to a given measurement timescale structure. We provide a constraint satisfaction procedure whose computational performance is several orders of magnitude better than previous approaches. We then consider finite-sample data as input, and propose the first constraint optimization approach for recovering the system timescale causal structure. This algorithm optimally recovers from possible conflicts due to statistical errors. More generally, these advances allow for a robust and non-parametric estimation of system timescale causal structures from subsampled time series data.

  10. Cooperative learning in 'Special Needs in Dentistry' for undergraduate students using the Jigsaw approach.

    PubMed

    Suárez-Cunqueiro, M M; Gándara-Lorenzo, D; Mariño-Pérez, R; Piñeiro-Abalo, S; Pérez-López, D; Tomás, I

    2016-07-15

    The goals of this study were to (i) describe the use of the Jigsaw approach for the resolution of clinical cases by undergraduate students in the subject 'Special Needs in Dentistry' and (ii) assess the impact of its implementation on academic performance and the students' perception. The Jigsaw approach was applied to the fifth-year in the subject 'Special Needs in Dentistry', as part of the Dentistry degree curriculum of the University of Santiago de Compostela, during the academic years 2012/2013 and 2013/2014. A total of 109 dental students were enrolled in the study, and the final marks of the Jigsaw (n = 55) and the non-Jigsaw groups (n = 54) were compared. Students' perceptions on the Jigsaw technique were assessed using a 13-question questionnaire. Academic performance based on the final examination mark for the Jigsaw and non-Jigsaw groups was 6.45 ± 1.49 and 6.13 ± 1.50, respectively. There were not students in the Jigsaw group who failed to attend the mandatory examination (0% vs. 12.96% in the non-Jigsaw group, P = 0.006). The questionnaire's internal consistency was 0.90. The mean value for all the questionnaire items was 3.80, with the highest response score of 4.35 for the statement 'I have seen the complexity that the resolution of a clinical case can involve'. Based on the students' perceptions, the Jigsaw approach could contribute to a better understanding of the complexity of solving clinical cases in the subject 'Special Needs in Dentistry'. However, further investigations should be conducted to analyse the influence of this technique on students' academic performance in the field of clinical dentistry. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  11. Paediatric burn unit in Portugal: Beds needed using a bed-day approach.

    PubMed

    Santos, João V; Viana, João; Amarante, José; Freitas, Alberto

    2017-03-01

    Despite the high burden of children with burns, there is not a paediatric burn unit (PBU) in Portugal. We aimed to estimate the Portuguese health care providing needs on paediatric burns. We performed a nation-wide retrospective study, between 2009 and 2013, among less than 16 years-old inpatients with burns that met the transfer criteria to a burn unit in Portugal. A bed-day approach was used, targeting an occupancy rate of 70-75%, and possible locations were studied. The primary outcome was the number of beds needed, and secondary outcomes were the overload and revenue for each possible number of beds in a PBU. A total of 1155 children met the transfer criteria to a burn unit, representing a total of 17,371 bed-days. Occupancy rates of 11-bed, 12-bed, 13-bed and 14-bed PBU were, respectively, 79.7%, 75.3%, 71.0% and 66.8%. The 13-bed PBU scenario would represent an overload of 523 bed-days, revenue of more than 5 million Euros and a ratio of 1 PBU bed per 123,409 children. Using a groundbreaking approach, the optimal number of PBU beds needed in Portugal is 13. However, as half of the patients who met burn transfer criteria are not transferred, this bed number might be overestimated if this pattern maintains, despite the underestimation with our method approach. If a PBU is to be created the preferable location is Porto. Cost-effectiveness studies should be performed. Copyright © 2016 Elsevier Ltd and ISBI. All rights reserved.

  12. Disorganization of Equilibrium Directional Interactions in the Brain Motor Network of Parkinson's disease: New Insight of Resting State Analysis Using Granger Causality and Graphical Approach

    PubMed Central

    Ghasemi, Mahdieh; Mahloojifar, Ali

    2013-01-01

    Parkinson's disease (PD) is a progressive neurological disorder characterized by tremor, rigidity, and slowness of movements. Particular changes related to various pathological attacks in PD could result in causal interactions of the brain network from resting state functional magnetic resonance imaging (rs-fMRI) data. In this paper, we aimed to disclose the network structure of the directed influences over the brain using multivariate Granger causality analysis and graph theory in patients with PD as compared with control group. rs-fMRI at rest from 10 PD patients and 10 controls were analyzed. Topological properties of the networks showed that information flow in PD is smaller than that in healthy individuals. We found that there is a balanced local network in healthy control group, including positive pair-wise cross connections between caudate and cerebellum and reciprocal connections between motor cortex and caudate in the left and right hemispheres. The results showed that this local network is disrupted in PD due to disturbance of the interactions in the motor networks. These findings suggested alteration of the functional organization of the brain in the resting state that affects the information transmission from and to other brain regions related to both primary dysfunctions and higher-level cognition impairments in PD. Furthermore, we showed that regions with high degree values could be detected as betweenness centrality nodes. Our results demonstrate that properties of small-world connectivity could also recognize and quantify the characteristics of directed influence brain networks in PD. PMID:24098860

  13. Disorganization of Equilibrium Directional Interactions in the Brain Motor Network of Parkinson's disease: New Insight of Resting State Analysis Using Granger Causality and Graphical Approach.

    PubMed

    Ghasemi, Mahdieh; Mahloojifar, Ali

    2013-04-01

    Parkinson's disease (PD) is a progressive neurological disorder characterized by tremor, rigidity, and slowness of movements. Particular changes related to various pathological attacks in PD could result in causal interactions of the brain network from resting state functional magnetic resonance imaging (rs-fMRI) data. In this paper, we aimed to disclose the network structure of the directed influences over the brain using multivariate Granger causality analysis and graph theory in patients with PD as compared with control group. rs-fMRI at rest from 10 PD patients and 10 controls were analyzed. Topological properties of the networks showed that information flow in PD is smaller than that in healthy individuals. We found that there is a balanced local network in healthy control group, including positive pair-wise cross connections between caudate and cerebellum and reciprocal connections between motor cortex and caudate in the left and right hemispheres. The results showed that this local network is disrupted in PD due to disturbance of the interactions in the motor networks. These findings suggested alteration of the functional organization of the brain in the resting state that affects the information transmission from and to other brain regions related to both primary dysfunctions and higher-level cognition impairments in PD. Furthermore, we showed that regions with high degree values could be detected as betweenness centrality nodes. Our results demonstrate that properties of small-world connectivity could also recognize and quantify the characteristics of directed influence brain networks in PD.

  14. A social impact assessment of the floodwater spreading project on the Gareh-Bygone plain in Iran: A causal comparative approach

    SciTech Connect

    Ahmadvand, Mostafa Karami, Ezatollah

    2009-02-15

    The purpose of this study was to explore the social impacts of the floodwater spreading project (FWSP) on the Gareh-Bygone plain, Iran. The study was in the form of a causal comparative design, and a triangulation technique was used to collect data including the use of survey data, archival data, and a participatory rural appraisal (PRA). The causal comparative method requires a comparison of villages with and without the FWSP. Therefore, a survey was conducted using stratified random sampling to select 202 households in villages with and without FWSP in the plain. Significant differences were found between the respondents in villages with and without FWSP with regard to social impact criteria. In spite of the project had negative impact on perceived wellbeing, social capital, social structure development; it had positive impact on quality of life, rural and agricultural economic conditions, and conservation of community resources. However, no significant difference was found between women and men regarding the SIA of FWSP in Gareh-Bygone plain. Analysis of the archival data and PRA techniques supported the survey results and demonstrated that the project improved environmental criteria and deteriorated social dimensions.

  15. Practical approaches to supporting young women with intellectual disabilities and high support needs with their menstruation.

    PubMed

    Gomez, Miriam Taylor; Carlson, Glenys M; Van Dooren, Kate

    2012-01-01

    Menstrual myths may influence decisions about menstrual and fertility management for women with intellectual disabilities and high support needs. We identify six myths (related to menstruation, menstrual management, communication, sexual feelings, menstrual difficulties, and surgical elimination) and the evidence that dispels these myths. We provide reflexive questions for practitioners to help them critically reflect on their own approaches to menstrual management. We encourage those supporting women with disabilities to consider the reflective questions we have provided and to strive to support informed decision-making about menstruation and the related areas of fertility and sexual feelings.

  16. The need to disentangle key concepts from ecosystem-approach jargon.

    PubMed

    Waylen, K A; Hastings, E J; Banks, E A; Holstead, K L; Irvine, R J; Blackstock, K L

    2014-10-01

    The ecosystem approach--as endorsed by the Convention on Biological Diversity (CDB) in 2000-is a strategy for holistic, sustainable, and equitable natural resource management, to be implemented via the 12 Malawi Principles. These principles describe the need to manage nature in terms of dynamic ecosystems, while fully engaging with local peoples. It is an ambitious concept. Today, the term is common throughout the research and policy literature on environmental management. However, multiple meanings have been attached to the term, resulting in confusion. We reviewed references to the ecosystem approach from 1957 to 2012 and identified 3 primary uses: as an alternative to ecosystem management or ecosystem-based management; in reference to an integrated and equitable approach to resource management as per the CBD; and as a term signifying a focus on understanding and valuing ecosystem services. Although uses of this term and its variants may overlap in meaning, typically, they do not entirely reflect the ethos of the ecosystem approach as defined by the CBD. For example, there is presently an increasing emphasis on ecosystem services, but focusing on these alone does not promote decentralization of management or use of all forms of knowledge, both of which are integral to the CBD's concept. We highlight that the Malawi Principles are at risk of being forgotten. To better understand these principles, more effort to implement them is required. Such efforts should be evaluated, ideally with comparative approaches, before allowing the CBD's concept of holistic and socially engaged management to be abandoned or superseded. It is possible that attempts to implement all 12 principles together will face many challenges, but they may also offer a unique way to promote holistic and equitable governance of natural resources. Therefore, we believe that the CBD's concept of the ecosystem approach demands more attention. © 2014 Society for Conservation Biology.

  17. Need for Orientation, Media Uses and Gratifications, and Media Effects.

    ERIC Educational Resources Information Center

    Weaver, David

    In order to study the influence of need for orientation and media gratifications on media use and media effects in political communication, two previous surveys were studied to compare the causal modeling approach and the contingent conditions approach. In the first study, 339 personal interviews were conducted with registered voters during a…

  18. The need for comprehensive vulnerability approaches to mirror the multiplicity in mountain hazard risk

    NASA Astrophysics Data System (ADS)

    Keiler, Margreth; Fuchs, Sven

    2014-05-01

    The concept of vulnerability is pillared by multiple disciplinary theories underpinning either a technical or a social origin of the concept and resulting in a range of paradigms for vulnerability quantification. By taking a natural scientific approach we argue that a large number of studies have focused either on damage-loss functions for individual mountain hazards or on semi-quantitative indicator-based approaches for multiple hazards (hazard chains). However, efforts to reduce susceptibility to hazards and to create disaster-resilient communities require intersections among these approaches, as well as among theories originating in natural and social sciences, since human activity cannot be seen independently from the environmental setting. Acknowledging different roots of disciplinary paradigms in risk management, issues determining structural, economic, institutional and social vulnerability have to be more comprehensively addressed in the future with respect to mountain hazards in Europe and beyond. It is argued that structural vulnerability as originator results in considerable economic vulnerability, generated by the institutional settings of dealing with natural hazards and shaped by the overall societal framework. If vulnerability and its counterpart, resilience, is analysed and evaluated by using such a comprehensive approach, a better understanding of the vulnerability-influencing parameters could be achieved, taking into account the interdependencies and interactions between the disciplinary foci. As a result, three key issues should be addressed in future research: (1) Vulnerability requires a new perspective on the relationship between society and environment: not as a duality, but more as a mutually constitutive relationship (including methods for assessment). (2) There is a need for concepts of vulnerability that emphasise the dynamics of temporal and spatial scales, particularly with respect to Global Change processes in mountain regions. (3

  19. More discussions for granger causality and new causality measures.

    PubMed

    Hu, Sanqing; Cao, Yu; Zhang, Jianhai; Kong, Wanzeng; Yang, Kun; Zhang, Yanbin; Li, Xun

    2012-02-01

    Granger causality (GC) has been widely applied in economics and neuroscience to reveal causality influence of time series. In our previous paper (Hu et al., in IEEE Trans on Neural Netw, 22(6), pp. 829-844, 2011), we proposed new causalities in time and frequency domains and particularly focused on new causality in frequency domain by pointing out the shortcomings/limitations of GC or Granger-alike causality metrics and the advantages of new causality. In this paper we continue our previous discussions and focus on new causality and GC or Granger-alike causality metrics in time domain. Although one strong motivation was introduced in our previous paper (Hu et al., in IEEE Trans on Neural Netw, 22(6), pp. 829-844, 2011) we here present additional motivation for the proposed new causality metric and restate the previous motivation for completeness. We point out one property of conditional GC in time domain and the shortcomings/limitations of conditional GC which cannot reveal the real strength of the directional causality among three time series. We also show the shortcomings/limitations of directed causality (DC) or normalize DC for multivariate time series and demonstrate it cannot reveal real causality at all. By calculating GC and new causality values for an example we demonstrate the influence of one of the time series on the other is linearly increased as the coupling strength is linearly increased. This fact further supports reasonability of new causality metric. We point out that larger instantaneous correlation does not necessarily mean larger true causality (e.g., GC and new causality), or vice versa. Finally we conduct analysis of statistical test for significance and asymptotic distribution property of new causality metric by illustrative examples.

  20. Evaluating Causal Models.

    ERIC Educational Resources Information Center

    Watt, James H., Jr.

    Pointing out that linear causal models can organize the interrelationships of a large number of variables, this paper contends that such models are particularly useful to mass communication research, which must by necessity deal with complex systems of variables. The paper first outlines briefly the philosophical requirements for establishing a…

  1. Causal Premise Semantics

    ERIC Educational Resources Information Center

    Kaufmann, Stefan

    2013-01-01

    The rise of causality and the attendant graph-theoretic modeling tools in the study of counterfactual reasoning has had resounding effects in many areas of cognitive science, but it has thus far not permeated the mainstream in linguistic theory to a comparable degree. In this study I show that a version of the predominant framework for the formal…

  2. Causal Responsibility and Counterfactuals

    ERIC Educational Resources Information Center

    Lagnado, David A.; Gerstenberg, Tobias; Zultan, Ro'i

    2013-01-01

    How do people attribute responsibility in situations where the contributions of multiple agents combine to produce a joint outcome? The prevalence of over-determination in such cases makes this a difficult problem for counterfactual theories of causal responsibility. In this article, we explore a general framework for assigning responsibility in…

  3. Causality: Physics and Philosophy

    ERIC Educational Resources Information Center

    Chatterjee, Atanu

    2013-01-01

    Nature is a complex causal network exhibiting diverse forms and species. These forms or rather systems are physically open, structurally complex and naturally adaptive. They interact with the surrounding media by operating a positive-feedback loop through which, they adapt, organize and self-organize themselves in response to the ever-changing…

  4. Causal Responsibility and Counterfactuals

    ERIC Educational Resources Information Center

    Lagnado, David A.; Gerstenberg, Tobias; Zultan, Ro'i

    2013-01-01

    How do people attribute responsibility in situations where the contributions of multiple agents combine to produce a joint outcome? The prevalence of over-determination in such cases makes this a difficult problem for counterfactual theories of causal responsibility. In this article, we explore a general framework for assigning responsibility in…

  5. Causal Premise Semantics

    ERIC Educational Resources Information Center

    Kaufmann, Stefan

    2013-01-01

    The rise of causality and the attendant graph-theoretic modeling tools in the study of counterfactual reasoning has had resounding effects in many areas of cognitive science, but it has thus far not permeated the mainstream in linguistic theory to a comparable degree. In this study I show that a version of the predominant framework for the formal…

  6. The development of causal reasoning.

    PubMed

    Kuhn, Deanna

    2012-05-01

    How do inference rules for causal learning themselves change developmentally? A model of the development of causal reasoning must address this question, as well as specify the inference rules. Here, the evidence for developmental changes in processes of causal reasoning is reviewed, with the distinction made between diagnostic causal inference and causal prediction. Also addressed is the paradox of a causal reasoning literature that highlights the competencies of young children and the proneness to error among adults. WIREs Cogn Sci 2012, 3:327-335. doi: 10.1002/wcs.1160 For further resources related to this article, please visit the WIREs website.

  7. Meeting the Late-Career Needs of Faculty Transitioning Through Retirement: One Institution's Approach.

    PubMed

    Cain, Joanna M; Felice, Marianne E; Ockene, Judith K; Milner, Robert J; Congdon, John L; Tosi, Stephen; Thorndyke, Luanne E

    2017-09-26

    Medical school faculty are aging, but few academic health centers are adequately prepared with policies, programs, and resources (PPR) to assist late-career faculty. The authors sought to examine cultural barriers to successful retirement and create alignment between individual and institutional needs and tasks through PPR that embrace the contributions of senior faculty while enabling retirement transitions at the University of Massachusetts Medical School, 2013-2017. Faculty 50 or older were surveyed, programs at other institutions and from the literature (multiple fields) were reviewed, and senior faculty and leaders, including retired faculty, were engaged to develop and implement PPR. Cultural barriers were found to be significant, and a multipronged, multiyear strategy to address these barriers, which sequentially added PPR to support faculty, was put in place. A comprehensive framework of sequenced PPR was developed to address the needs and tasks of late-career transitions within three distinct phases: pre-retirement, retirement, and post-retirement. This sequential introduction approach has led to important outcomes for all three of the retirement phases, including reduction of cultural barriers, a policy that has been useful in assessing viability of proposed phased retirement plans, transparent and realistic discussions about financial issues, and consideration of roles that retired faculty can provide. The authors are tracking the issues mentioned in consultations and efficacy of succession planning, and will be resurveying faculty to further refine their work. This framework approach could serve as a template for other academic health centers to address late-career faculty development.

  8. A True Delphi Approach: Developing a Tailored Curriculum in Response to Local Agriscience Need

    SciTech Connect

    Rubenstein, Eric; Thoron, Andrew; Burleson, Sarah

    2012-02-07

    The Delphi approach is a structured communication technique, developed as a systematic, interactive forecasting method which relies on a panel of experts. In this specific case experts from Industry, Education and Extension fields addressed needs for educational programs in a traditional agriculturally-based community, environmentally conscious practices in order to restore environmental integrity and multi-disciplinary approach to solve sustainability problems facing the agricultural industry. The experts were divided into two main groups, (A) Secondary and (B) Post-secondary, and answered questionnaires in three rounds: • 1st Round – Participants generated a list of knowledge, skills, and competencies followed • 2nd Round – Panelists rated each item • 3rd Round – Panelists were given the opportunity to combine and add additional items As a result, top six items from both groups were not found similar, secondary panelists centralized around employment skills and post-secondary panelists focused on content areas. Implications include a need for content-based curriculum for post-secondary graduates, utilization of true-Delphi technique for future curriculum development research and further examination of students that complete secondary and post-secondary programs in biofuels/sustainable agriculture.

  9. Process-outcome interrelationship and standard setting in medical education: the need for a comprehensive approach.

    PubMed

    Christensen, Leif; Karle, Hans; Nystrup, Jørgen

    2007-09-01

    An outcome-based approach to medical education compared to a process/content orientation is currently being discussed intensively. In this article, the process and outcome interrelationship in medical education is discussed, with specific emphasis on the relation to the definition of standards in basic medical education. Perceptions of outcome have always been an integrated element of curricular planning. The present debate underlines the need for stronger focus on learning objectives and outcome assessment in many medical schools around the world. The need to maintain an integrated approach of process/content and outcome is underlined in this paper. A worry is expressed about the taxonomy of learning in pure outcome-based medical education, in which student assessment can be a major determinant for the learning process, leaving the control of the medical curriculum to medical examiners. Moreover, curricula which favour reductionism by stating everything in terms of instrumental outcomes or competences, do face a risk of lowering quality and do become a prey for political interference. Standards based on outcome alone rise unclarified problems in relationship to licensure requirements of medical doctors. It is argued that the alleged dichotomy between process/content and outcome seems artificial, and that formulation of standards in medical education must follow a comprehensive line in curricular planning.

  10. Swimming hydrodynamics: ten questions and the technical approaches needed to resolve them

    NASA Astrophysics Data System (ADS)

    Lauder, George V.

    2011-07-01

    Recent experimental and computational studies of swimming hydrodynamics have contributed significantly to our understanding of how animals swim, but much remains to be done. Ten questions are presented here as an avenue to discuss some of the arenas in which progress still is needed and as a means of considering the technical approaches to address these questions. 1. What is the three-dimensional structure of propulsive surfaces? 2. How do propulsive surfaces move in three dimensions? 3. What are the hydrodynamic effects of propulsor deformation during locomotion? 4. How are locomotor kinematics and dynamics altered during unsteady conditions? 5. What is the three-dimensional structure of aquatic animal vortex wakes? 6. To what extent are observed propulsor deformations actively controlled? 7. What is the response of the body and fins of moving animals to external perturbations? 8. How can robotic models help us understand locomotor dynamics of organisms? 9. How do propulsive surfaces interact hydrodynamically during natural motions? 10. What new computational approaches are needed to better understand locomotor hydrodynamics? These ten questions point, not exclusively, toward areas in which progress would greatly enhance our understanding of the hydrodynamics of swimming organisms, and in which the application of new technology will allow continued progress toward understanding the interaction between organisms and the aquatic medium in which they live and move.

  11. Drug- and Herb-Induced Liver Injury in Clinical and Translational Hepatology: Causality Assessment Methods, Quo Vadis?

    PubMed Central

    Eickhoff, Axel; Schulze, Johannes

    2013-01-01

    Drug-induced liver injury (DILI) and herb-induced liver injury (HILI) are typical diseases of clinical and translational hepatology. Their diagnosis is complex and requires an experienced clinician to translate basic science into clinical judgment and identify a valid causality algorithm. To prospectively assess causality starting on the day DILI or HILI is suspected, the best approach for physicians is to use the Council for International Organizations of Medical Sciences (CIOMS) scale in its original or preferably its updated version. The CIOMS scale is validated, liver-specific, structured, and quantitative, providing final causality grades based on scores of specific items for individual patients. These items include latency period, decline in liver values after treatment cessation, risk factors, co-medication, alternative diagnoses, hepatotoxicity track record of the suspected product, and unintentional re-exposure. Provided causality is established as probable or highly probable, data of the CIOMS scale with all individual items, a short clinical report, and complete raw data should be transmitted to the regulatory agencies, manufacturers, expert panels, and possibly to the scientific community for further refinement of the causality evaluation in a setting of retrospective expert opinion. Good-quality case data combined with thorough CIOMS-based assessment as a standardized approach should avert subsequent necessity for other complex causality assessment methods that may have inter-rater problems because of poor-quality data. In the future, the CIOMS scale will continue to be the preferred tool to assess causality of DILI and HILI cases and should be used consistently, both prospectively by physicians, and retrospectively for subsequent expert opinion if needed. For comparability and international harmonization, all parties assessing causality in DILI and HILI cases should attempt this standardized approach using the updated CIOMS scale. PMID:26357608

  12. Employee Training Needs and Perceived Value of Training in the Pearl River Delta of China: A Human Capital Development Approach

    ERIC Educational Resources Information Center

    Au, Alan Kai Ming; Altman, Yochanan; Roussel, Josse

    2008-01-01

    Purpose: This paper aims to explore Hong Kong firms' training needs in the Pearl River Delta, a booming region in the fast growing People Republic of China economy, by resorting to a human capital approach. Also, to identify the training policies selected by those firms in order to cater for those needs. Design/methodology/approach: A survey based…

  13. Employee Training Needs and Perceived Value of Training in the Pearl River Delta of China: A Human Capital Development Approach

    ERIC Educational Resources Information Center

    Au, Alan Kai Ming; Altman, Yochanan; Roussel, Josse

    2008-01-01

    Purpose: This paper aims to explore Hong Kong firms' training needs in the Pearl River Delta, a booming region in the fast growing People Republic of China economy, by resorting to a human capital approach. Also, to identify the training policies selected by those firms in order to cater for those needs. Design/methodology/approach: A survey based…

  14. Mental health research in the criminal justice system: The need for common approaches and international perspectives.

    PubMed

    Roesch, R; Ogloff, J R; Eaves, D

    1995-01-01

    There is a need for researchers and policy makers in the area of mental health and law to collaborate and develop common methods of approach to research. Although we have learned a great deal about the prevalence and needs of mentally ill offenders in jails and prisons, there are a number of research questions that remain. If the "second generation" of research is to be fruitful--and useful to policy makers--we need to be sure that the methods we employ are valid and that the findings we obtain are reliable. By collaborating with colleagues in other jurisdictions, we can begin to learn whether some of the existing findings are of a general nature, or dependent upon the system in which they were found. Similarly, while the first-generation research has alerted us to the needs of mentally ill offenders in jails and prisons, second-generation research is needed to help identify factors that may help prevent the "revolving door phenomenon," which results in mentally ill people being volleyed among mental health, criminal justice, and community settings. One area that has received embarrassingly little attention has been the need for considering the relationship between substance abuse and mental disorders. In our own work, we have found an alarmingly high degree of substance abuse among offenders, including mentally ill offenders. We have come to realize the importance of considering the role that substance abuse coupled with other mental disorders may play in the criminal justice system. As a result of this concern, the Surrey Mental Health Project recently hired a full-time drug and alcohol counselor whose job it is to work with inmates with substance abuse disorders while in the jail, and to help arrange continuing treatment resources upon their release. As Wilson et al. (1995) discuss, intensive case management projects may be particularly useful at targeting the unique needs of mentally ill offenders with multiple problems. Much of the research conducted with

  15. A Hybrid Approach to Finding Relevant Social Media Content for Complex Domain Specific Information Needs

    PubMed Central

    Cameron, Delroy; Sheth, Amit P.; Jaykumar, Nishita; Thirunarayan, Krishnaprasad; Anand, Gaurish; Smith, Gary A.

    2015-01-01

    While contemporary semantic search systems offer to improve classical keyword-based search, they are not always adequate for complex domain specific information needs. The domain of prescription drug abuse, for example, requires knowledge of both ontological concepts and “intelligible constructs” not typically modeled in ontologies. These intelligible constructs convey essential information that include notions of intensity, frequency, interval, dosage and sentiments, which could be important to the holistic needs of the information seeker. In this paper, we present a hybrid approach to domain specific information retrieval that integrates ontology-driven query interpretation with synonym-based query expansion and domain specific rules, to facilitate search in social media on prescription drug abuse. Our framework is based on a context-free grammar (CFG) that defines the query language of constructs interpretable by the search system. The grammar provides two levels of semantic interpretation: 1) a top-level CFG that facilitates retrieval of diverse textual patterns, which belong to broad templates and 2) a low-level CFG that enables interpretation of specific expressions belonging to such textual patterns. These low-level expressions occur as concepts from four different categories of data: 1) ontological concepts, 2) concepts in lexicons (such as emotions and sentiments), 3) concepts in lexicons with only partial ontology representation, called lexico-ontology concepts (such as side effects and routes of administration (ROA)), and 4) domain specific expressions (such as date, time, interval, frequency and dosage) derived solely through rules. Our approach is embodied in a novel Semantic Web platform called PREDOSE, which provides search support for complex domain specific information needs in prescription drug abuse epidemiology. When applied to a corpus of over 1 million drug abuse-related web forum posts, our search framework proved effective in retrieving

  16. A Hybrid Approach to Finding Relevant Social Media Content for Complex Domain Specific Information Needs.

    PubMed

    Cameron, Delroy; Sheth, Amit P; Jaykumar, Nishita; Thirunarayan, Krishnaprasad; Anand, Gaurish; Smith, Gary A

    2014-12-01

    While contemporary semantic search systems offer to improve classical keyword-based search, they are not always adequate for complex domain specific information needs. The domain of prescription drug abuse, for example, requires knowledge of both ontological concepts and "intelligible constructs" not typically modeled in ontologies. These intelligible constructs convey essential information that include notions of intensity, frequency, interval, dosage and sentiments, which could be important to the holistic needs of the information seeker. In this paper, we present a hybrid approach to domain specific information retrieval that integrates ontology-driven query interpretation with synonym-based query expansion and domain specific rules, to facilitate search in social media on prescription drug abuse. Our framework is based on a context-free grammar (CFG) that defines the query language of constructs interpretable by the search system. The grammar provides two levels of semantic interpretation: 1) a top-level CFG that facilitates retrieval of diverse textual patterns, which belong to broad templates and 2) a low-level CFG that enables interpretation of specific expressions belonging to such textual patterns. These low-level expressions occur as concepts from four different categories of data: 1) ontological concepts, 2) concepts in lexicons (such as emotions and sentiments), 3) concepts in lexicons with only partial ontology representation, called lexico-ontology concepts (such as side effects and routes of administration (ROA)), and 4) domain specific expressions (such as date, time, interval, frequency and dosage) derived solely through rules. Our approach is embodied in a novel Semantic Web platform called PREDOSE, which provides search support for complex domain specific information needs in prescription drug abuse epidemiology. When applied to a corpus of over 1 million drug abuse-related web forum posts, our search framework proved effective in retrieving

  17. Meeting the Needs for Released Nanomaterials Required for Further Testing-The SUN Approach.

    PubMed

    Nowack, Bernd; Boldrin, Alessio; Caballero, Alejandro; Hansen, Steffen Foss; Gottschalk, Fadri; Heggelund, Laura; Hennig, Michael; Mackevica, Aiga; Maes, Hanna; Navratilova, Jana; Neubauer, Nicole; Peters, Ruud; Rose, Jerome; Schäffer, Andreas; Scifo, Lorette; van Leeuwen, Stefan van; von der Kammer, Frank; Wohlleben, Wendel; Wyrwoll, Anne; Hristozov, Danail

    2016-03-15

    The analysis of the potential risks of engineered nanomaterials (ENM) has so far been almost exclusively focused on the pristine, as-produced particles. However, when considering a life-cycle perspective, it is clear that ENM released from genuine products during manufacturing, use, and disposal is far more relevant. Research on the release of materials from nanoproducts is growing and the next necessary step is to investigate the behavior and effects of these released materials in the environment and on humans. Therefore, sufficient amounts of released materials need to be available for further testing. In addition, ENM-free reference materials are needed since many processes not only release ENM but also nanosized fragments from the ENM-containing matrix that may interfere with further tests. The SUN consortium (Project on "Sustainable Nanotechnologies", EU seventh Framework funding) uses methods to characterize and quantify nanomaterials released from composite samples that are exposed to environmental stressors. Here we describe an approach to provide materials in hundreds of gram quantities mimicking actual released materials from coatings and polymer nanocomposites by producing what is called "fragmented products" (FP). These FP can further be exposed to environmental conditions (e.g., humidity, light) to produce "weathered fragmented products" (WFP) or can be subjected to a further size fractionation to isolate "sieved fragmented products" (SFP) that are representative for inhalation studies. In this perspective we describe the approach, and the used methods to obtain released materials in amounts large enough to be suitable for further fate and (eco)toxicity testing. We present a case study (nanoparticulate organic pigment in polypropylene) to show exemplarily the procedures used to produce the FP. We present some characterization data of the FP and discuss critically the further potential and the usefulness of the approach we developed.

  18. Policy Making in Newborn Screening Needs a Structured and Transparent Approach.

    PubMed

    Jansen, Marleen E; Lister, Karla J; van Kranen, Henk J; Cornel, Martina C

    2017-01-01

    Newborn bloodspot screening (NBS) programs have expanded significantly in the past years and are expected to expand further with the emergence of genetic technologies. Historically, NBS expansion has often occurred following ad hoc consideration of conditions, instead of a structured and transparent approach. In this review, we explore issues pertinent to NBS policy making, through the lens of the policy cycle: (a) agenda setting, (b) policy advice, (c) policy decision, (d) implementation, and (e) evaluation. A literature search was conducted to gather information on the elements specific to NBS and its policy making process. The review highlighted two approaches to nominate a condition: a structured approach through horizon scanning; and an ad hoc process. For assessment of a condition, there was unanimous support for a robust process based on criteria. While the need to assess harms and benefits was a repeated theme in the articles, there is no agreed-upon threshold for benefit in decision-making. Furthermore, the literature was consistent in its recommendation for an overarching, independent, multidisciplinary group providing recommendations to government. An implementation plan focusing on the different levels on which NBS operates and the information needed on each level is essential for successful implementation. Continuously monitoring, and improving a program is vital, particularly following the implementation of screening for a new condition. An advisory committee could advise on implementation, development, review, modification, and cessation of (parts of) NBS. The results highlight that there are a wave of issues facing NBS programs that policy makers must take into account when developing policy processes. What conditions to screen, and the technologies used in NBS, are both up for debate.

  19. Causality and the Interpretation of Epidemiologic Evidence

    PubMed Central

    Kundi, Michael

    2006-01-01

    There is an ongoing debate regarding how and when an agent’s or determinant’s impact can be interpreted as causation with respect to some target disease. The so-called criteria of causation, originating from the seminal work of Sir Austin Bradford Hill and Mervyn Susser, are often schematically applied disregarding the fact that they were meant neither as criteria nor as a checklist for attributing to a hazard the potential of disease causation. Furthermore, there is a tendency to misinterpret the lack of evidence for causation as evidence for lack of a causal relation. There are no criteria in the strict sense for the assessment of evidence concerning an agent’s or determinant’s propensity to cause a disease, nor are there criteria to dismiss the notion of causation. Rather, there is a discursive process of conjecture and refutation. In this commentary, I propose a dialogue approach for the assessment of an agent or determinant. Starting from epidemiologic evidence, four issues need to be addressed: temporal relation, association, environmental equivalence, and population equivalence. If there are no valid counterarguments, a factor is attributed the potential of disease causation. More often than not, there will be insufficient evidence from epidemiologic studies. In these cases, other evidence can be used instead that increases or decreases confidence in a factor being causally related to a disease. Even though every verdict of causation is provisional, action must not be postponed until better evidence is available if our present knowledge appears to demand immediate measures for health protection. PMID:16835045

  20. Causal Status and Coherence in Causal-Based Categorization

    ERIC Educational Resources Information Center

    Rehder, Bob; Kim, ShinWoo

    2010-01-01

    Research has documented two effects of interfeature causal knowledge on classification. A "causal status effect" occurs when features that are causes are more important to category membership than their effects. A "coherence effect" occurs when combinations of features that are consistent with causal laws provide additional…

  1. Causal Status and Coherence in Causal-Based Categorization

    ERIC Educational Resources Information Center

    Rehder, Bob; Kim, ShinWoo

    2010-01-01

    Research has documented two effects of interfeature causal knowledge on classification. A "causal status effect" occurs when features that are causes are more important to category membership than their effects. A "coherence effect" occurs when combinations of features that are consistent with causal laws provide additional…

  2. Biodiversity in the context of ecosystem services: the applied need for systems approaches

    PubMed Central

    Norris, Ken

    2012-01-01

    Recent evidence strongly suggests that biodiversity loss and ecosystem degradation continue. How might a systems approach to ecology help us better understand and address these issues? Systems approaches play a very limited role in the science that underpins traditional biodiversity conservation, but could provide important insights into mechanisms that affect population growth. This potential is illustrated using data from a critically endangered bird population. Although species-specific insights have practical value, the main applied challenge for a systems approach is to help improve our understanding of the role of biodiversity in the context of ecosystem services (ES) and the associated values and benefits people derive from these services. This has profound implications for the way we conceptualize and address ecological problems. Instead of focusing directly on biodiversity, the important response variables become measures of values and benefits, ES or ecosystem processes. We then need to understand the sensitivity of these variables to biodiversity change relative to other abiotic or anthropogenic factors, which includes exploring the role of variability at different levels of biological organization. These issues are discussed using the recent UK National Ecosystems Assessment as a framework. PMID:22144382

  3. Biodiversity in the context of ecosystem services: the applied need for systems approaches.

    PubMed

    Norris, Ken

    2012-01-19

    Recent evidence strongly suggests that biodiversity loss and ecosystem degradation continue. How might a systems approach to ecology help us better understand and address these issues? Systems approaches play a very limited role in the science that underpins traditional biodiversity conservation, but could provide important insights into mechanisms that affect population growth. This potential is illustrated using data from a critically endangered bird population. Although species-specific insights have practical value, the main applied challenge for a systems approach is to help improve our understanding of the role of biodiversity in the context of ecosystem services (ES) and the associated values and benefits people derive from these services. This has profound implications for the way we conceptualize and address ecological problems. Instead of focusing directly on biodiversity, the important response variables become measures of values and benefits, ES or ecosystem processes. We then need to understand the sensitivity of these variables to biodiversity change relative to other abiotic or anthropogenic factors, which includes exploring the role of variability at different levels of biological organization. These issues are discussed using the recent UK National Ecosystems Assessment as a framework.

  4. Conditional Granger causality and partitioned Granger causality: differences and similarities.

    PubMed

    Malekpour, Sheida; Sethares, William A

    2015-12-01

    Neural information modeling and analysis often requires a measurement of the mutual influence among many signals. A common technique is the conditional Granger causality (cGC) which measures the influence of one time series on another time series in the presence of a third. Geweke has translated this condition into the frequency domain and has explored the mathematical relationships between the time and frequency domain expressions. Chen has observed that in practice, the expressions may return (meaningless) negative numbers, and has proposed an alternative which is based on a partitioned matrix scheme, which we call partitioned Granger causality (pGC). There has been some confusion in the literature about the relationship between cGC and pGC; some authors treat them as essentially identical measures, while others have noted that some properties (such as the relationship between the time and frequency domain expressions) do not hold for the pGC. This paper presents a series of matrix equalities that simplify the calculation of the pGC. In this simplified expression, the essential differences and similarities between the cGC and the pGC become clear; in essence, the pGC is dependent on only a subset of the parameters in the model estimation, and the noise residuals (which are uncorrelated in the cGC) need not be uncorrelated in the pGC. The mathematical results are illustrated with a simulation, and the measures are applied to an EEG dataset.

  5. Causal Attributions in Young Children.

    ERIC Educational Resources Information Center

    Friedberg, Robert D.; Dalenberg, Constance J.

    1990-01-01

    Investigated the causal explanations children use to account for common experiences. In the study, 60 preschoolers watched videotaped puppet shows designed to elicit causal attributions. Most children predominantly used internal, unstable, and specific attributions. (CB)

  6. Causal Attributions in Young Children.

    ERIC Educational Resources Information Center

    Friedberg, Robert D.; Dalenberg, Constance J.

    1990-01-01

    Investigated the causal explanations children use to account for common experiences. In the study, 60 preschoolers watched videotaped puppet shows designed to elicit causal attributions. Most children predominantly used internal, unstable, and specific attributions. (CB)

  7. The development of causal categorization.

    PubMed

    Hayes, Brett K; Rehder, Bob

    2012-08-01

    Two experiments examined the impact of causal relations between features on categorization in 5- to 6-year-old children and adults. Participants learned artificial categories containing instances with causally related features and noncausal features. They then selected the most likely category member from a series of novel test pairs. Classification patterns and logistic regression were used to diagnose the presence of independent effects of causal coherence, causal status, and relational centrality. Adult classification was driven primarily by coherence when causal links were deterministic (Experiment 1) but showed additional influences of causal status when links were probabilistic (Experiment 2). Children's classification was based primarily on causal coherence in both cases. There was no effect of relational centrality in either age group. These results suggest that the generative model (Rehder, 2003a) provides a good account of causal categorization in children as well as adults. Copyright © 2012 Cognitive Science Society, Inc.

  8. To Infinity and Beyond: Using a Narrative Approach to Identify Training Needs for Unknown and Dynamic Situations

    ERIC Educational Resources Information Center

    Dachner, Alison M.; Saxton, Brian M.; Noe, Raymond A.; Keeton, Kathryn E.

    2013-01-01

    Training effectiveness depends on conducting a thorough needs assessment. Traditional needs assessment methods are insufficient for today's business environment characterized by rapid pace, risk, and uncertainty. To overcome the deficiencies of traditional needs assessment methods, a narrative-based unstructured interview approach with subject…

  9. To Infinity and Beyond: Using a Narrative Approach to Identify Training Needs for Unknown and Dynamic Situations

    ERIC Educational Resources Information Center

    Dachner, Alison M.; Saxton, Brian M.; Noe, Raymond A.; Keeton, Kathryn E.

    2013-01-01

    Training effectiveness depends on conducting a thorough needs assessment. Traditional needs assessment methods are insufficient for today's business environment characterized by rapid pace, risk, and uncertainty. To overcome the deficiencies of traditional needs assessment methods, a narrative-based unstructured interview approach with subject…

  10. The Challenge of Child Day Care Needs and Improved Federal and State Approaches to Day Care Standard Setting and Enforcement.

    ERIC Educational Resources Information Center

    Costin, Lela B.; And Others

    This paper examines child day care needs and ways that federal and state approaches to day care standard setting and enforcement might be improved. Chapter I documents the magnitude of child day care needs, citing Department of Labor, Census, and other survey statistics on the numbers of children needing day care and the number of day care centers…

  11. Child Care Subsidy Use and Child Development: Potential Causal Mechanisms

    ERIC Educational Resources Information Center

    Hawkinson, Laura E.

    2011-01-01

    Research using an experimental design is needed to provide firm causal evidence on the impacts of child care subsidy use on child development, and on underlying causal mechanisms since subsidies can affect child development only indirectly via changes they cause in children's early experiences. However, before costly experimental research is…

  12. Causal Modeling and Research on Teacher EducaLion.

    ERIC Educational Resources Information Center

    Denton, Jon J.; Mabry, M. Patrick, Jr.

    The technique of causal modeling as applied to theoretical constructs in teacher education is demonstrated. The abstract principles of causality are explained, and are applied to various educational research needs. An example is made using data collected from a sample of 44 secondary level students who participated in a one semester student…

  13. The Role of Functional Form in Causal-Based Categorization

    ERIC Educational Resources Information Center

    Rehder, Bob

    2015-01-01

    Two experiments tested how the "functional form" of the causal relations that link features of categories affects category-based inferences. Whereas "independent causes" can each bring about an effect by themselves, "conjunctive causes" all need to be present for an effect to occur. The causal model view of category…

  14. Theories of Conduct Disorder: A Causal Modelling Analysis

    ERIC Educational Resources Information Center

    Krol, N.; Morton, J.; De Bruyn, E.

    2004-01-01

    Background: If a clinician has to make decisions on diagnosis and treatment, he or she is confronted with a variety of causal theories. In order to compare these theories a neutral terminology and notational system is needed. The Causal Modelling framework involving three levels of description--biological, cognitive and behavioural--has previously…

  15. Granger Causality and Transfer Entropy Are Equivalent for Gaussian Variables

    NASA Astrophysics Data System (ADS)

    Barnett, Lionel; Barrett, Adam B.; Seth, Anil K.

    2009-12-01

    Granger causality is a statistical notion of causal influence based on prediction via vector autoregression. Developed originally in the field of econometrics, it has since found application in a broader arena, particularly in neuroscience. More recently transfer entropy, an information-theoretic measure of time-directed information transfer between jointly dependent processes, has gained traction in a similarly wide field. While it has been recognized that the two concepts must be related, the exact relationship has until now not been formally described. Here we show that for Gaussian variables, Granger causality and transfer entropy are entirely equivalent, thus bridging autoregressive and information-theoretic approaches to data-driven causal inference.

  16. Supporting Early Childhood Preservice Teachers in Their Work with Children and Families with Complex Needs: A Strengths Approach

    ERIC Educational Resources Information Center

    Fenton, Angela; McFarland-Piazza, Laura

    2014-01-01

    This article explores the potential of tailoring the inherent principles of the Strengths Approach (McCashen, 2005) for preparing early childhood educators to work with children and families with complex needs. The term "Strengths Approach" (capitalized) is presented in the article as the name of a specific approach developed by St.…

  17. Supporting Early Childhood Preservice Teachers in Their Work with Children and Families with Complex Needs: A Strengths Approach

    ERIC Educational Resources Information Center

    Fenton, Angela; McFarland-Piazza, Laura

    2014-01-01

    This article explores the potential of tailoring the inherent principles of the Strengths Approach (McCashen, 2005) for preparing early childhood educators to work with children and families with complex needs. The term "Strengths Approach" (capitalized) is presented in the article as the name of a specific approach developed by St.…

  18. THE CHILD'S CONCEPTION OF PHYSICAL CAUSALITY.

    ERIC Educational Resources Information Center

    PIAGET, JEAN

    THE CHILD'S CONCEPTION OF PHYSICAL CAUSALITY WAS INVESTIGATED. THREE METHODS OF INVESTIGATION WERE USED. THE FIRST METHOD WAS PURELY VERBAL, AND CONSISTED OF A SERIES OF QUESTIONS DIRECTED TO CHILDREN, REGARDING SOME NATURAL PHENOMENON. THE SECOND METHOD INVOLVED A HALF-VERBAL, HALF-PRACTICAL APPROACH, WHEREIN A SPECIFIC REFERENCE TO NATURAL…

  19. THE CHILD'S CONCEPTION OF PHYSICAL CAUSALITY.

    ERIC Educational Resources Information Center

    PIAGET, JEAN

    THE CHILD'S CONCEPTION OF PHYSICAL CAUSALITY WAS INVESTIGATED. THREE METHODS OF INVESTIGATION WERE USED. THE FIRST METHOD WAS PURELY VERBAL, AND CONSISTED OF A SERIES OF QUESTIONS DIRECTED TO CHILDREN, REGARDING SOME NATURAL PHENOMENON. THE SECOND METHOD INVOLVED A HALF-VERBAL, HALF-PRACTICAL APPROACH, WHEREIN A SPECIFIC REFERENCE TO NATURAL…

  20. From Granger causality to long-term causality: Application to climatic data

    NASA Astrophysics Data System (ADS)

    Smirnov, Dmitry A.; Mokhov, Igor I.

    2009-07-01

    Quantitative characterization of interaction between processes from time series is often required in different fields of natural science including geophysics and biophysics. Typically, one estimates “short-term” influences, e.g., the widely used Granger causality is defined via one-step-ahead predictions. Such an approach does not reveal how strongly the “long-term” behavior of one process under study is affected by the others. To overcome this problem, we introduce the concept of long-term causality, which extends the concept of Granger causality. The long-term causality is estimated from data via empirical modeling and analysis of model dynamics under different conditions. Apart from mathematical examples, we apply both approaches to find out how strongly the global surface temperature (GST) is affected by variations in carbon dioxide atmospheric content, solar activity, and volcanic activity during the last 150 years. Influences of all the three factors on GST are detected with the Granger causality. However, the long-term causality shows that the rise in GST during the last decades can be explained only if the anthropogenic factor (CO2) is taken into account in a model.

  1. Sleepwalking Into Infertility: The Need for a Public Health Approach Toward Advanced Maternal Age.

    PubMed

    Lemoine, Marie-Eve; Ravitsky, Vardit

    2015-01-01

    In Western countries today, a growing number of women delay motherhood until their late 30s and even 40s, as they invest time in pursuing education and career goals before starting a family. This social trend results from greater gender equality and expanded opportunities for women and is influenced by the availability of contraception and assisted reproductive technologies (ART). However, advanced maternal age is associated with increased health risks, including infertility. While individual medical solutions such as ART and elective egg freezing can promote reproductive autonomy, they entail significant risks and limitations. We thus argue that women should be better informed regarding the risks of advanced maternal age and ART, and that these individual solutions need to be supplemented by a public health approach, including policy measures that provide women with the opportunity to start a family earlier in life without sacrificing personal career goals.

  2. Oncology Education in Medical Schools: Towards an Approach that Reflects Australia's Health Care Needs.

    PubMed

    McRae, Robert J

    2016-12-01

    Cancer has recently overtaken heart disease to become the number 1 cause of mortality both globally and in Australia. As such, adequate oncology education must be an integral component of medical school if students are to achieve learning outcomes that meet the needs of the population. The aim of this review is to evaluate the current state of undergraduate oncology education and identify how Australian medical schools can improve oncology learning outcomes for students and, by derivative, improve healthcare outcomes for Australians with cancer. The review shows that oncology is generally not well represented in medical school curricula, that few medical schools offer mandatory oncology or palliative care rotations, and that junior doctors are exhibiting declining oncology knowledge and skills. To address these issues, Australian medical schools should implement the Oncology Education Committee's Ideal Oncology Curriculum, enact mandatory oncology and palliative care clinical rotations for students, and in doing so, appreciate the importance of students' differing approaches to learning.

  3. In Defense of Causal-Formative Indicators: A Minority Report.

    PubMed

    Bollen, Kenneth A; Diamantopoulos, Adamantios

    2015-09-21

    Causal-formative indicators directly affect their corresponding latent variable. They run counter to the predominant view that indicators depend on latent variables and are thus often controversial. If present, such indicators have serious implications for factor analysis, reliability theory, item response theory, structural equation models, and most measurement approaches that are based on reflective or effect indicators. Psychological Methods has published a number of influential articles on causal and formative indicators as well as launching the first major backlash against them. This article examines 7 common criticisms of these indicators distilled from the literature: (a) A construct measured with "formative" indicators does not exist independently of its indicators; (b) Such indicators are causes rather than measures; (c) They imply multiple dimensions to a construct and this is a liability; (d) They are assumed to be error-free, which is unrealistic; (e) They are inherently subject to interpretational confounding; (f) They fail proportionality constraints; and (g) Their coefficients should be set in advance and not estimated. We summarize each of these criticisms and point out the flaws in the logic and evidence marshaled in their support. The most common problems are not distinguishing between what we call causal-formative and composite-formative indicators, tautological fallacies, and highlighting issues that are common to all indicators, but presenting them as special problems of causal-formative indicators. We conclude that measurement theory needs (a) to incorporate these types of indicators, and (b) to better understand their similarities to and differences from traditional indicators. (PsycINFO Database Record

  4. Dynamic Granger-Geweke causality modeling with application to interictal spike propagation.

    PubMed

    Lin, Fa-Hsuan; Hara, Keiko; Solo, Victor; Vangel, Mark; Belliveau, John W; Stufflebeam, Steven M; Hämäläinen, Matti S

    2009-06-01

    A persistent problem in developing plausible neurophysiological models of perception, cognition, and action is the difficulty of characterizing the interactions between different neural systems. Previous studies have approached this problem by estimating causal influences across brain areas activated during cognitive processing using structural equation modeling (SEM) and, more recently, with Granger-Geweke causality. While SEM is complicated by the need for a priori directional connectivity information, the temporal resolution of dynamic Granger-Geweke estimates is limited because the underlying autoregressive (AR) models assume stationarity over the period of analysis. We have developed a novel optimal method for obtaining data-driven directional causality estimates with high temporal resolution in both time and frequency domains. This is achieved by simultaneously optimizing the length of the analysis window and the chosen AR model order using the SURE criterion. Dynamic Granger-Geweke causality in time and frequency domains is subsequently calculated within a moving analysis window. We tested our algorithm by calculating the Granger-Geweke causality of epileptic spike propagation from the right frontal lobe to the left frontal lobe. The results quantitatively suggested that the epileptic activity at the left frontal lobe was propagated from the right frontal lobe, in agreement with the clinical diagnosis. Our novel computational tool can be used to help elucidate complex directional interactions in the human brain.

  5. Dynamic Granger-Geweke causality modeling with application to interictal spike propagation

    PubMed Central

    Lin, Fa-Hsuan; Hara, Keiko; Solo, Victor; Vangel, Mark; Belliveau, John W.; Stufflebeam, Steven M.; Hamalainen, Matti S.

    2010-01-01

    A persistent problem in developing plausible neurophysiological models of perception, cognition, and action is the difficulty of characterizing the interactions between different neural systems. Previous studies have approached this problem by estimating causal influences across brain areas activated during cognitive processing using Structural Equation Modeling and, more recently, with Granger-Geweke causality. While SEM is complicated by the need for a priori directional connectivity information, the temporal resolution of dynamic Granger-Geweke estimates is limited because the underlying autoregressive (AR) models assume stationarity over the period of analysis. We have developed a novel optimal method for obtaining data-driven directional causality estimates with high temporal resolution in both time and frequency domains. This is achieved by simultaneously optimizing the length of the analysis window and the chosen AR model order using the SURE criterion. Dynamic Granger-Geweke causality in time and frequency domains is subsequently calculated within a moving analysis window. We tested our algorithm by calculating the Granger-Geweke causality of epileptic spike propagation from the right frontal lobe to the left frontal lobe. The results quantitatively suggested the epileptic activity at the left frontal lobe was propagated from the right frontal lobe, in agreement with the clinical diagnosis. Our novel computational tool can be used to help elucidate complex directional interactions in the human brain. PMID:19378280

  6. Interventionist causal models in psychiatry: repositioning the mind-body problem.

    PubMed

    Kendler, K S; Campbell, J

    2009-06-01

    The diversity of research methods applied to psychiatric disorders results in a confusing plethora of causal claims. To help make sense of these claims, the interventionist model (IM) of causality has several attractive features. First, it connects causation with the practical interests of psychiatry, defining causation in terms of 'what would happen under interventions', a question of key interest to those of us whose interest is ultimately in intervening to prevent and treat illness. Second, it distinguishes between predictive-correlative and true causal relationships, an essential issue cutting across many areas in psychiatric research. Third, the IM is non-reductive and agnostic to issues of mind-body problem. Fourth, the IM model cleanly separates issues of causation from questions about the underlying mechanism. Clarifying causal influences can usefully structure the search for underlying mechanisms. Fifth, it provides a sorely needed conceptual rigor to multi-level modeling, thereby avoiding a return to uncritical holistic approaches that 'everything is relevant' to psychiatric illness. Sixth, the IM provides a clear way to judge both the generality and depth of explanations. In conclusion, the IM can provide a single, clear empirical framework for the evaluation of all causal claims of relevance to psychiatry and presents psychiatry with a method of avoiding the sterile metaphysical arguments about mind and brain which have preoccupied our field but yielded little of practical benefit.

  7. Dynamic causal modelling revisited.

    PubMed

    Friston, K J; Preller, Katrin H; Mathys, Chris; Cagnan, Hayriye; Heinzle, Jakob; Razi, Adeel; Zeidman, Peter

    2017-02-17

    This paper revisits the dynamic causal modelling of fMRI timeseries by replacing the usual (Taylor) approximation to neuronal dynamics with a neural mass model of the canonical microcircuit. This provides a generative or dynamic causal model of laminar specific responses that can generate haemodynamic and electrophysiological measurements. In principle, this allows the fusion of haemodynamic and (event related or induced) electrophysiological responses. Furthermore, it enables Bayesian model comparison of competing hypotheses about physiologically plausible synaptic effects; for example, does attentional modulation act on superficial or deep pyramidal cells - or both? In this technical note, we describe the resulting dynamic causal model and provide an illustrative application to the attention to visual motion dataset used in previous papers. Our focus here is on how to answer long-standing questions in fMRI; for example, do haemodynamic responses reflect extrinsic (afferent) input from distant cortical regions, or do they reflect intrinsic (recurrent) neuronal activity? To what extent do inhibitory interneurons contribute to neurovascular coupling? What is the relationship between haemodynamic responses and the frequency of induced neuronal activity? This paper does not pretend to answer these questions; rather it shows how they can be addressed using neural mass models of fMRI timeseries.

  8. Educational needs assessment for psychiatry residents to prevent suicide: a qualitative approach.

    PubMed

    Barekatain, Majid; Aminoroaia, Mahin; Samimi, Seyed Mehdi Ardestani; Rajabi, Fatemeh; Attari, Abbas

    2013-10-01

    Suicide is a commonly encountered and stressful event in professional life of any psychiatrist. Suicide risk assessment is a major gateway to patient treatment and management. It is a core competency requirement in training of psychiatry. The present study designed to assesseducational needsfor suicide prevention in residents of psychiatry in two medical schools in Iran, Isfahan University of Medical Sciences (IUMS) and Shahid Beheshti Medical University (SBUMS) inTehran. This was a qualitative triangulation study, conducted in two steps. The first step was based on a phenomenological approach and the second was based on focus groups. The studied population was the psychiatric residents of IUMS and SBUMS. Purposive sampling was implemented until saturation. Interviews were performed. Colaizzi method was used to analyze the data. In the second step, participants attended a session, in which all final codes of the first step were discussed, and regarding the views, educational priorities and needs were listed. A total of 2047 codes, extracted from 31 interviews, analyzed through Colaizzi method, were categorized in three groups: Educational, facilities and processes, human resources. According to defects of current educational program, we suggest regular reevaluations and revisions of clinical training programs according to current needs.

  9. Assessing the reliability of ecotoxicological studies: An overview of current needs and approaches.

    PubMed

    Moermond, Caroline; Beasley, Amy; Breton, Roger; Junghans, Marion; Laskowski, Ryszard; Solomon, Keith; Zahner, Holly

    2016-11-21

    In general, reliable studies are well designed and well performed, and enough details on study design and performance are reported to assess the study. For hazard and risk assessment in various legal frameworks, many different types of ecotoxicity studies need to be evaluated for reliability. These studies vary in study design, methodology, quality, and level of detail reported (e.g., reviews, peer-reviewed research papers, or industry-sponsored studies documented under Good Laboratory Practice [GLP] guidelines). Regulators have the responsibility to make sound and verifiable decisions and should evaluate each study for reliability in accordance with scientific principles regardless of whether they were conducted in accordance with GLP and/or standardized methods. Thus, a systematic and transparent approach is needed to evaluate studies for reliability. In this paper, 8 different methods for reliability assessment were compared using a number of attributes: categorical versus numerical scoring methods, use of exclusion and critical criteria, weighting of criteria, whether methods are tested with case studies, domain of applicability, bias toward GLP studies, incorporation of standard guidelines in the evaluation method, number of criteria used, type of criteria considered, and availability of guidance material. Finally, some considerations are given on how to choose a suitable method for assessing reliability of ecotoxicity studies. Integr Environ Assess Manag. ©2016 SETAC.

  10. Normalizing the causality between time series

    NASA Astrophysics Data System (ADS)

    Liang, X. San

    2015-08-01

    Recently, a rigorous yet concise formula was derived to evaluate information flow, and hence the causality in a quantitative sense, between time series. To assess the importance of a resulting causality, it needs to be normalized. The normalization is achieved through distinguishing a Lyapunov exponent-like, one-dimensional phase-space stretching rate and a noise-to-signal ratio from the rate of information flow in the balance of the marginal entropy evolution of the flow recipient. It is verified with autoregressive models and applied to a real financial analysis problem. An unusually strong one-way causality is identified from IBM (International Business Machines Corporation) to GE (General Electric Company) in their early era, revealing to us an old story, which has almost faded into oblivion, about "Seven Dwarfs" competing with a giant for the mainframe computer market.

  11. [Clinical research III. The causality studies].

    PubMed

    Talavera, Juan O; Wacher-Rodarte, Niels H; Rivas-Ruiz, Rodolfo

    2011-01-01

    The need to solve a clinical problem leads us to establish a starting point to address (risk, prognosis or treatment studies), all these cases seek to attribute causality. Clinical reasoning described in the book Clinical Epidemiology. The architecture of clinical research, offers a simple guide to understanding this phenomenon. And proposes three basic components: baseline, maneuver and outcome. In this model, different systematic errors (bias) are described, which may be favored by omitting characteristics of the three basic components. Thus, omissions in the baseline characteristics cause an improper assembly of the population and susceptibility bias, omissions in the application or evaluation of the maneuver provoke performance bias, and omissions in the assessment of out-come cause detection bias and transfer bias. Importantly, if this way of thinking facilitates understanding of the causal phenomenon, the appropriateness of the variables to be selected in the studies to which attribute or not causality, require additional arguments for evaluate clinical relevance.

  12. Normalizing the causality between time series.

    PubMed

    Liang, X San

    2015-08-01

    Recently, a rigorous yet concise formula was derived to evaluate information flow, and hence the causality in a quantitative sense, between time series. To assess the importance of a resulting causality, it needs to be normalized. The normalization is achieved through distinguishing a Lyapunov exponent-like, one-dimensional phase-space stretching rate and a noise-to-signal ratio from the rate of information flow in the balance of the marginal entropy evolution of the flow recipient. It is verified with autoregressive models and applied to a real financial analysis problem. An unusually strong one-way causality is identified from IBM (International Business Machines Corporation) to GE (General Electric Company) in their early era, revealing to us an old story, which has almost faded into oblivion, about "Seven Dwarfs" competing with a giant for the mainframe computer market.

  13. Innovative laser based approaches to laryngeal cancer: what an engineer and physicist need to know

    NASA Astrophysics Data System (ADS)

    Burns, James A.

    2008-02-01

    Innovative laser-based approaches to laryngeal cancer include the clinical applications of two new technologies, photoangiolysis using a 532nm wavelength pulsed-KTP laser and fiber-based cutting using a 2μm wavelength thulium laser. Photoangiolysis is well-suited for treatment of minimally invasive glottic cancer and allows maximum preservation of phonatory surfaces needed for optimal voicing. The thulium laser offers an alternative to the carbon dioxide laser as an endolaryngeal cutting tool due to its enhanced hemostatic properties and fiber-based delivery. Clinical examples of pulsed-KTP laser involution of early glottic cancer will be presented in order to highlight the concept of targeting tumor angiogenesis in treating laryngeal cancer. The surgical experience using the thulium laser for complex endoscopic endolaryngeal excisions of large laryngeal cancers is presented to demonstrate the expanded clinical applications of endolaryngeal cutting offered by this laser. The laryngeal tissue effects of various laser power and pulse width (PW) settings, mode of delivery, active cooling to reduce thermal trauma, and wavelength selection have been extensively studied for the KTP and thulium lasers in both ex-vivo and live-perfusing models. The results from these studies, included herein, determine the clinical efficacy and safety of these innovative laser-based approaches to laryngeal cancer.

  14. Atomic and Molecular Data Needs for Radiation Damage Modeling: Multiscale Approach

    NASA Astrophysics Data System (ADS)

    Yakubovich, Alexander V.; Surdutovich, Eugene; Solov'yov, Andrey V.

    2011-05-01

    We present a brief overview of the multiscale approach towards understanding of the processes responsible for the radiation damage caused by energetic ions. This knowledge is very important, because it can be utilized in the ion-beam cancer therapy, which is one of the most advanced modern techniques to cure certain type of cancer. The central element of the multiscale approach is the theoretical evaluation and quantification of the DNA damage within cell environment. To achieve this goal one needs a significant amount of data on various atomic and molecular processes involved into the cascade of events starting with the ion entering and propagation in the biological medium and resulting in the DNA damage. The discussion of the follow up biological processes are beyond the scope of this brief overview. We consider different paths of the DNA damage and focus on the the illustration of the thermo-mechanical effects caused by the propagation of ions through the biological environment and in particular on the possibility of the creation of the shock waves in the vicinity of the ion tracks. We demonstrate that at the initial stages after ion's passage the shock wave is so strong that it can contribute to the DNA damage due to large pressure gradients developed at the distances of a few nanometers from the ionic tracks. This novel mechanism of the DNA damage provides an important contribution to the cumulative biodamage caused by low-energy secondary electrons, holes and free radicals.

  15. Atomic and Molecular Data Needs for Radiation Damage Modeling: Multiscale Approach

    SciTech Connect

    Yakubovich, Alexander V.; Solov'yov, Andrey V.; Surdutovich, Eugene

    2011-05-11

    We present a brief overview of the multiscale approach towards understanding of the processes responsible for the radiation damage caused by energetic ions. This knowledge is very important, because it can be utilized in the ion-beam cancer therapy, which is one of the most advanced modern techniques to cure certain type of cancer. The central element of the multiscale approach is the theoretical evaluation and quantification of the DNA damage within cell environment. To achieve this goal one needs a significant amount of data on various atomic and molecular processes involved into the cascade of events starting with the ion entering and propagation in the biological medium and resulting in the DNA damage. The discussion of the follow up biological processes are beyond the scope of this brief overview. We consider different paths of the DNA damage and focus on the the illustration of the thermo-mechanical effects caused by the propagation of ions through the biological environment and in particular on the possibility of the creation of the shock waves in the vicinity of the ion tracks. We demonstrate that at the initial stages after ion's passage the shock wave is so strong that it can contribute to the DNA damage due to large pressure gradients developed at the distances of a few nanometers from the ionic tracks. This novel mechanism of the DNA damage provides an important contribution to the cumulative biodamage caused by low-energy secondary electrons, holes and free radicals.

  16. Modelling approaches for coastal simulation based on cellular automata: the need and potential.

    PubMed

    Dearing, J A; Richmond, N; Plater, A J; Wolf, J; Prandle, D; Coulthard, T J

    2006-04-15

    The paper summarizes the theoretical and practical needs for cellular automata (CA)-type models in coastal simulation, and describes early steps in the development of a CA-based model for estuarine sedimentation. It describes the key approaches and formulae used for tidal, wave and sediment processes in a prototype integrated cellular model for coastal simulation designed to simulate estuary sedimentary responses during the tidal cycle in the short-term and climate driven changes in sea-level in the long-term. Results of simple model testing for both one-dimensional and two-dimensional models, and a preliminary parameterization for the Blackwater Estuary, UK, are shown. These reveal a good degree of success in using a CA-type model for water and sediment transport as a function of water level and wave height, but tidal current vectors are not effectively simulated in the approach used. The research confirms that a CA-type model for the estuarine sediment system is feasible, with a real prospect for coupling to existing catchment and nearshore beach/cliff models to produce integrated coastal simulators of sediment response to climate, sea-level change and human actions.

  17. From computer-assisted intervention research to clinical impact: The need for a holistic approach.

    PubMed

    Ourselin, Sébastien; Emberton, Mark; Vercauteren, Tom

    2016-10-01

    The early days of the field of medical image computing (MIC) and computer-assisted intervention (CAI), when publishing a strong self-contained methodological algorithm was enough to produce impact, are over. As a community, we now have substantial responsibility to translate our scientific progresses into improved patient care. In the field of computer-assisted interventions, the emphasis is also shifting from the mere use of well-known established imaging modalities and position trackers to the design and combination of innovative sensing, elaborate computational models and fine-grained clinical workflow analysis to create devices with unprecedented capabilities. The barriers to translating such devices in the complex and understandably heavily regulated surgical and interventional environment can seem daunting. Whether we leave the translation task mostly to our industrial partners or welcome, as researchers, an important share of it is up to us. We argue that embracing the complexity of surgical and interventional sciences is mandatory to the evolution of the field. Being able to do so requires large-scale infrastructure and a critical mass of expertise that very few research centres have. In this paper, we emphasise the need for a holistic approach to computer-assisted interventions where clinical, scientific, engineering and regulatory expertise are combined as a means of moving towards clinical impact. To ensure that the breadth of infrastructure and expertise required for translational computer-assisted intervention research does not lead to a situation where the field advances only thanks to a handful of exceptionally large research centres, we also advocate that solutions need to be designed to lower the barriers to entry. Inspired by fields such as particle physics and astronomy, we claim that centralised very large innovation centres with state of the art technology and health technology assessment capabilities backed by core support staff and open

  18. How many general surgeons do you need in rural areas? Three approaches to physician resource planning in southern Manitoba.

    PubMed Central

    Roos, N; Black, C; Wade, J; Decker, K

    1996-01-01

    OBJECTIVE: To assess critically the results of using three different approaches to planning for the number of general surgeons in rural areas. DESIGN: Estimates of the number of general surgeons needed using a ratio approach, a and a population-needs-based approach. SETTING: Rural southern Manitoba. OUTCOME MEASURE: Number of general surgeons needed. RESULTS: The ratio approach supported the recruitment of 7.8 to 14.5 additional general surgeons to rural southern Manitoba. The repatriation approach suggested that the area might support five additional general surgeons, if residents could be persuaded to undergo their surgery closer to home. The population-needs-based approach suggested that the health status of area residents was similar to that of residents of other areas of the province and that they had a higher rate of surgery than residents of other areas; no additional surgeons were apparently needed. CONCLUSIONS: Each method has certain advantages, and none is necessarily useful in isolation. Hence, the most effective approach to planning for general surgeons is likely a combination of all three methods. Other factors that may be important include the type of payment structure and the need for professional groups to monitor variations in rates of surgery. PMID:8752064

  19. The urgent need to change the current medical approach on tobacco cessation in Latin America.

    PubMed

    Ponciano-Rodríguez, Guadalupe

    2010-01-01

    Despite of the accumulation of scientific evidence confirming the health consequences of smoking and the new paradigm of smoking as a disease where nicotine is the drug that modifies the functional and morphological characteristics of the brain in dependent smokers, tobacco smoking continues as an important public health problem in many Latin American countries. In contrast with big advances in the tobacco control area, as an example the Framework Convention on Tobacco Control signed by 168 countries, the role of health professional in the fight against tobacco is still less than ideal. In many Latin American schools of medicine, deficiencies in medical education has led to insecure physicians when they have to motivate their patients to stop smoking or to prevent young people to begin tobacco consumption. If each general practitioner or specialist during their daily medical assistance could talk to their smoker patients about the big benefits of stop smoking and support them to get free of tobacco, we would be winning a battle against smoking. Also if we could achieve generations of young non smoking doctors, who could be a real example for patients, this could also impact the prevalence of smokers. In this article we analyze the neurobiological bases of nicotine addiction, which we think are missing in the medical curriculum and could help doctors to understand tobacco smoking as a disease rather than a risk factor, and discuss the main reasons supporting an urgent change in the medical approach of tobacco cessation in Latin America as well as the need to actualize the medical curriculum in order to give physicians the skills needed to intervene successfully with their smoker patients and to be themselves non smokers.

  20. Identifying children in need of ancillary and enabling services: a population approach.

    PubMed

    Benedict, Ruth E; Farel, Anita M

    2003-12-01

    Children with chronic or disabling conditions use health, education and social services at a higher rate than their healthy peers. Estimates of the number of children in need of these specialized services are widely varied and often depend on categorical definitions that do not account for either the diversity or commonality of their experiences. Developing methods for identifying the population in need of services, particularly children likely to use long-term ancillary (audiology, occupational, physical or speech therapy, or social work) and/or enabling services (special equipment, personal care assistance, respite care, transportation, or environmental modifications), is essential for effective policy and program implementation. This study examines several recent attempts to operationalize definitions of children with chronic conditions using a noncategorical classification approach. Particular emphasis is placed on the subgroup of children identified as having functional limitations. Proposed operational definitions of children with functional limitations are compared using data from the 1994-1995 Disability Supplement to the US National Health Interview Survey. Estimates of the number of children reported to be using ancillary and enabling services are generated and compared across operational definitions of functional limitation as well as by the number, severity, and type (i.e. mobility, self-care, communication/sensory, social cognition/learning ability) of limitation. Depending on the operational definition selected, 9-14% of US community-dwelling children are estimated to have functional limitations. Among children with limitations, 26-30% regularly use ancillary services and 11-14% use enabling services. The strengths, limitations, and potential applications for each operational definition are discussed.

  1. The need for a systematic approach to disaster psychosocial response: a suggested competency framework.

    PubMed

    Cox, Robin S; Danford, Taryn

    2014-04-01

    Competency models attempt to define what makes expert performers "experts." Successful disaster psychosocial planning and the institutionalizing of psychosocial response within emergency management require clearly-defined skill sets. This necessitates anticipating both the short- and long-term psychosocial implications of a disaster or health emergency (ie, pandemic) by developing effective and sustained working relationships among psychosocial providers, programs, and other planning partners. The following article outlines recommended competencies for psychosocial responders to enable communities and organizations to prepare for and effectively manage a disaster response. Competency-based models are founded on observable performance or behavioral indicators, attitudes, traits, or personalities related to effective performance in a specific role or job. After analyzing the literature regarding competency-based frameworks, a proposed competency framework that details 13 competency domains is suggested. Each domain describes a series of competencies and suggests behavioral indicators for each competency and, where relevant, associated training expectations. These domains have been organized under three distinct categories or types of competencies: general competency domains; disaster psychosocial intervention competency domains; and disaster psychosocial program leadership and coordination competency domains. Competencies do not replace job descriptions nor should they be confused with performance assessments. What they can do is update and revise job descriptions; orient existing and new employees to their disaster/emergency roles and responsibilities; target training needs; provide the basis for ongoing self-assessment by agencies and individuals as they evaluate their readiness to respond; and provide a job- or role-relevant basis for performance appraisal dimensions or standards and review discussions. Using a modular approach to psychosocial planning, service

  2. Health status transitions in community-living elderly with complex care needs: a latent class approach

    PubMed Central

    Lafortune, Louise; Béland, François; Bergman, Howard; Ankri, Joël

    2009-01-01

    Background For older persons with complex care needs, accounting for the variability and interdependency in how health dimensions manifest themselves is necessary to understand the dynamic of health status. Our objective is to test the hypothesis that a latent classification can capture this heterogeneity in a population of frail elderly persons living in the community. Based on a person-centered approach, the classification corresponds to substantively meaningful groups of individuals who present with a comparable constellation of health problems. Methods Using data collected for the SIPA project, a system of integrated care for frail older people (n = 1164), we performed latent class analyses to identify homogenous categories of health status (i.e. health profiles) based on 17 indicators of prevalent health problems (chronic conditions; depression; cognition; functional and sensory limitations; instrumental, mobility and personal care disability) Then, we conducted latent transition analyses to study change in profile membership over 2 consecutive periods of 12 and 10 months, respectively. We modeled competing risks for mortality and lost to follow-up as absorbing states to avoid attrition biases. Results We identified four health profiles that distinguish the physical and cognitive dimensions of health and capture severity along the disability dimension. The profiles are stable over time and robust to mortality and lost to follow-up attrition. The differentiated and gender-specific patterns of transition probabilities demonstrate the profiles' sensitivity to change in health status and unmasked the differential relationship of physical and cognitive domains with progression in disability. Conclusion Our approach may prove useful at organization and policy levels where many issues call for classification of individuals into pragmatically meaningful groups. In dealing with attrition biases, our analytical strategy could provide critical information for the

  3. Demystifying Concepts of Epidemic and Causal Association for Public Health Students--A Pedagogical Approach to Promote Critical and Analytical Thinking

    ERIC Educational Resources Information Center

    Patil, Rajan R.

    2011-01-01

    Epidemiology is a difficult but an important subject in public health curriculum. As teachers, we need to be very innovative in teaching the core concepts in epidemiology since it is basically a research oriented subject that calls for enormous application of logic and mathematical skills. Very often, complex epidemiological concepts need to be…

  4. Demystifying Concepts of Epidemic and Causal Association for Public Health Students--A Pedagogical Approach to Promote Critical and Analytical Thinking

    ERIC Educational Resources Information Center

    Patil, Rajan R.

    2011-01-01

    Epidemiology is a difficult but an important subject in public health curriculum. As teachers, we need to be very innovative in teaching the core concepts in epidemiology since it is basically a research oriented subject that calls for enormous application of logic and mathematical skills. Very often, complex epidemiological concepts need to be…

  5. Quantum information causality.

    PubMed

    Pitalúa-García, Damián

    2013-05-24

    How much information can a transmitted physical system fundamentally communicate? We introduce the principle of quantum information causality, which states the maximum amount of quantum information that a quantum system can communicate as a function of its dimension, independently of any previously shared quantum physical resources. We present a new quantum information task, whose success probability is upper bounded by the new principle, and show that an optimal strategy to perform it combines the quantum teleportation and superdense coding protocols with a task that has classical inputs.

  6. Fast causal multicast

    NASA Technical Reports Server (NTRS)

    Birman, Kenneth P.; Schiper, Andre; Stephenson, Pat

    1990-01-01

    A new protocol is presented that efficiently implements a reliable, causally ordered multicast primitive and is easily extended into a totally ordered one. Intended for use in the ISIS toolkit, it offers a way to bypass the most costly aspects of ISIS while benefiting from virtual synchrony. The facility scales with bounded overhead. Measured speedups of more than an order of magnitude were obtained when the protocol was implemented within ISIS. One conclusion is that systems such as ISIS can achieve performance competitive with the best existing multicast facilities - a finding contradicting the widespread concern that fault-tolerance may be unacceptably costly.

  7. Causal Entropic Forces

    NASA Astrophysics Data System (ADS)

    Wissner-Gross, A. D.; Freer, C. E.

    2013-04-01

    Recent advances in fields ranging from cosmology to computer science have hinted at a possible deep connection between intelligence and entropy maximization, but no formal physical relationship between them has yet been established. Here, we explicitly propose a first step toward such a relationship in the form of a causal generalization of entropic forces that we find can cause two defining behaviors of the human “cognitive niche”—tool use and social cooperation—to spontaneously emerge in simple physical systems. Our results suggest a potentially general thermodynamic model of adaptive behavior as a nonequilibrium process in open systems.

  8. Learning a theory of causality.

    PubMed

    Goodman, Noah D; Ullman, Tomer D; Tenenbaum, Joshua B

    2011-01-01

    The very early appearance of abstract knowledge is often taken as evidence for innateness. We explore the relative learning speeds of abstract and specific knowledge within a Bayesian framework and the role for innate structure. We focus on knowledge about causality, seen as a domain-general intuitive theory, and ask whether this knowledge can be learned from co-occurrence of events. We begin by phrasing the causal Bayes nets theory of causality and a range of alternatives in a logical language for relational theories. This allows us to explore simultaneous inductive learning of an abstract theory of causality and a causal model for each of several causal systems. We find that the correct theory of causality can be learned relatively quickly, often becoming available before specific causal theories have been learned--an effect we term the blessing of abstraction. We then explore the effect of providing a variety of auxiliary evidence and find that a collection of simple perceptual input analyzers can help to bootstrap abstract knowledge. Together, these results suggest that the most efficient route to causal knowledge may be to build in not an abstract notion of causality but a powerful inductive learning mechanism and a variety of perceptual supports. While these results are purely computational, they have implications for cognitive development, which we explore in the conclusion.

  9. Frequency decomposition of conditional Granger causality and application to multivariate neural field potential data.

    PubMed

    Chen, Yonghong; Bressler, Steven L; Ding, Mingzhou

    2006-01-30

    It is often useful in multivariate time series analysis to determine statistical causal relations between different time series. Granger causality is a fundamental measure for this purpose. Yet the traditional pairwise approach to Granger causality analysis may not clearly distinguish between direct causal influences from one time series to another and indirect ones acting through a third time series. In order to differentiate direct from indirect Granger causality, a conditional Granger causality measure in the frequency domain is derived based on a partition matrix technique. Simulations and an application to neural field potential time series are demonstrated to validate the method.

  10. Diagnosis and underdiagnosis of comorbidities in psoriasis patients - need for a multidisciplinary approach*

    PubMed Central

    Duarte, Gleison Vieira; de Oliveira, Maria de Fátima S. P.; Follador, Ivonise; Silva, Thadeu Santo; de Carvalho Filho, Edgar Marcelino

    2016-01-01

    BACKGROUND Psoriasis is an immune-mediated disease that manifests predominantly in the skin, although systemic involvement may also occur. Although associated comorbidities have long been recognized and despite several studies indicating psoriasis as an independent risk factor for cardiovascular events, little has been done in general medical practice regardind screening. In the United States, less than 50% of clinicians are aware of these recommendations. OBJECTIVE To identify the prevalence of these comorbidities in 296 patients followed up at a university dermatology clinic. METHODS Systematically investigated comorbidity frequencies were compared with general practitioners' registry frequencies. Clinical features correlated with comorbidities were also investigated. RESULTS High prevalences of systematically investigated comorbidities such as hypertension (30%) and dyslipidemia (26.5%) were documented. Conversely, data from general practitioners' records showed that 33% of dyslipidemia cases were undiagnosed and indicated possible underdiagnosis of some comorbidities. Furthermore, an association was found between: the number of comorbidities and psoriasis duration, age and high body mass index an association was found between the number of comorbidities and psoriasis duration, age, high body mass index, waist circumference or waist-to-hip ratio. (p<0.05). CONCLUSION Disease duration, age and high body mass index, waist circumference or waist-to-hip ratio are possible criteria for choosing which patients should be screened for comorbidities. Underdiagnosis of comorbidities by general practitioners highlights the need for a multidisciplinary approach in psoriasis management. PMID:28099594

  11. [Need to approach the obesity in Asturias. Proposal of nursing actions in primary care].

    PubMed

    Prida-Villa, Eva; Ronzón-Fernández, María Aránzazu; Sandoval-González, Virginia; Maciá-Bobes, Carmen

    2010-01-01

    The number of people suffering from overweight and obesity has grown in Spain in recent years and the number of specialists warning us of an epidemic continues to rise. In 2006, the World Health Organization (WHO) raised the alarm in the European Charter on counteracting obesity. Two years later, a number of scientific societies and health organizations at international level agreed that obesity should be treated as a disease and vigorously approached. Asturias is not the exception; for instance between 2002 and 2008 the prevalence of morbid obesity increased from 0.4% to 5.1% in the community. In view of this data it seems essential to launch specific programmes to reverse this trend. In this work we will propose some measures that can be carried out at the primary care level in the public health service in order to offer quality and individualized care plans both to adult and children. First, the need of an exhaustive questionnaire on diet and physical activity to be included in the program of obesity of the clinical computerized history is suggested. Secondly, the Health Administration should promote specific courses on obesity, before the new obesity program was released. Thirdly, institutional publicising of Clinical Guidelines on obesity based on the scientific evidence is recommended so that health professionals are made aware of the importance of this disease. Copyright © 2010 Elsevier España, S.L. All rights reserved.

  12. International trade in livestock and livestock products: the need for a commodity-based approach.

    PubMed

    Thomson, G R; Tambi, E N; Hargreaves, S K; Leyland, T J; Catley, A P; van 't Klooster, G G M; Penrith, M L

    2004-10-02

    International animal health standards designed to facilitate safe trade in livestock and livestock products are set by the Office International des Epizooties (OIE) under the Sanitary and Phytosanitary Agreement of the World Trade Organization (WTO) and documented in the OIE's Terrestrial Animal Health Code. A core principle of the Code is the need for countries to eradicate important transboundary animal diseases (TADs) to reduce the risk of exporting disease to trading partners. International food safety standards are set by the Codex Alimentarius Commission, administered jointly by the World Health Organization and the Food and Agriculture Organization of the United Nations. The goal of global eradication of most TADs is unachievable for the foreseeable future, other than in the case of rinderpest, and this prevents many countries, especially developing nations, from engaging in international trade under WTO rules. This paper proposes an alternative, commodity-based approach to the formulation of international animal health and food safety standards, based on the fact that different commodities pose very different risks when it comes to the spread of human and animal pathogens. Therefore, the risk mitigation strategies required are equally commodity-dependent. The authors conclude that more focused commodity standards would improve access to international markets for all countries, especially those in the developing world. For this objective to be realised, credible and independent certification is required.

  13. Clinical roundtable monograph: unmet needs in the treatment of chronic lymphocytic leukemia: integrating a targeted approach.

    PubMed

    O'Brien, Susan M; Furman, Richard R; Byrd, John C; Smith, Ashbel

    2014-01-01

    Chronic lymphocytic leukemia (CLL) is the most frequently diagnosed hematologic malignancy in the United States. Although several features can be useful in the diagnosis of CLL, the most important is the immunophenotype.Two staging systems--the Binet system and the Rai classification--are used to assess risk. After diagnosis, the first major therapeutic decision is when to initiate therapy, as a watchful waiting approach is often appropriate for patients with asymptomatic disease. Once a patient has met the criteria for treatment, the choice of therapy is the next major decision. Younger patients (<65 years) often receive more aggressive treatment that typically consists of cytotoxic chemotherapy. There is a great unmet need concerning treatment of older patients with CLL, who often present with more comorbid conditions that can decrease their ability to tolerate particular regimens. The current standard of care for older patients with CLL is rituximab plus chlorambucil. The concept of targeted agents is currently an area of intense interest in CLL. The Bruton’s tyrosine kinase inhibitor ibrutinib is the targeted agent that is furthest along in clinical development. It is associated with an overall survival rate of 83%. Idelalisib targets the phosphatidyl inositol 3-kinase and is under evaluation in pivotal trials. Targeted agents offer much promise in terms of efficacy, toxicity, and oral availability. They will change the management of patients with CLL.

  14. Bioethical dimensions of cultural psychosomatics: the need for an ethical research approach.

    PubMed

    Lolas, Fernando

    2013-01-01

    Contemporary psychosomatics is a research-based technical discipline and its social power depends on how scientific knowledge is obtained and applied in practice, considering cultural contexts. This article presents the view that the dialogical principles on which bioethical discourse is based are more inclusive than professional ethics and philosophical reflection. The distinction is advanced between rule-guided behavior and norm-justifiable acts (substantiation and justification). The practical implications of good practices in the generation of valid, reliable, generalizable and applicable knowledge are emphasized. For practitioners and researchers, the need to reflect on the distinction between patient and research participant can avoid the therapeutic misunderstanding, a form of abuse of the doctor-patient relationship. In addition, in resource-poor settings, the dilemma presented by the know-do gap (inapplicability of research results due to financial or social constraints) is part of the ethics' realm of the profession. Future prospects include a wider use of research results in practice, but avoidance of the know-do gap (the disparity between what is known and what can be done, particularly in settings with limited resources) requires a synthetic and holistic approach to medical ethics, combining moral reflection, theoretical analysis and empirical data.

  15. Translating the patient navigator approach to meet the needs of primary care.

    PubMed

    Ferrante, Jeanne M; Cohen, Deborah J; Crosson, Jesse C

    2010-01-01

    Helping patients navigate the complex and fragmented US health care system and coordinating their care are central to the patient-centered medical home. We evaluated the pilot use of a patient navigator (PN), someone who helps patients use the health care system effectively and efficiently, in primary care practices. This study was a cross-case comparative analysis of 4 community practices that implemented patient navigation. Project meeting notes, PN activity logs and debriefings, physician interviews, and patient/family member interviews were analyzed using a grounded approach. Seventy-five mostly female, elderly patients received navigation services from a social worker. The PN typically helped patients obtain social services and navigate health coverage and complex referrals. Availability of workspace for PN, interaction with practice members, and processes used for selecting and referring patients affected PN collaboration with and integration into practices. Patients found PN services very helpful, and physicians viewed the PN as someone carrying out new tasks that the practice was not previously doing. Patient navigation in community primary care practices is useful for patients who have complex needs. Integrating such services into primary care settings will require new practice and payment models to realize the full potential of integrated patient navigation services in this setting.

  16. Support Needs for Canadian Health Providers Responding to Disaster: New Insights from a Grounded Theory Approach

    PubMed Central

    Fahim, Christine; O'Sullivan, Tracey L.; Lane, Dan

    2015-01-01

    Introduction: An earlier descriptive study exploring the various supports available to Canadian health and social service providers who deployed to the 2010 earthquake disaster in Haiti, indicated that when systems are compromised, professionals are at physical, emotional and mental risk during overseas deployment. While these risks are generally well-identified, there is little literature that explores the effectiveness of the supports in place to mitigate this risk. This study provides evidence to inform policy development regarding future disaster relief, and the effectiveness of supports available to responders assisting with international disaster response. Methods: This study follows Strauss and Corbin’s 1990 structured approach to grounded theory to develop a framework for effective disaster support systems. N=21 interviews with Canadian health and social service providers, who deployed to Haiti in response to the 2010 earthquake, were conducted and analyzed. Resulting data were transcribed, coded and analysed for emergent themes. Results and Discussion: Three themes were identified in the data and were used to develop the evolving theory. The interview data indicate that the experiences of responders are determined based on an interaction between the individual’s ‘lens’ or personal expectations, as well as the supports that an organization is able to provide. Therefore, organizations should consider the following factors: experience, expectations, and supports, to tailor a successful support initiative that caters to the needs of the volunteer workforce. PMID:26203399

  17. The lesson of causal discovery algorithms for quantum correlations: causal explanations of Bell-inequality violations require fine-tuning

    NASA Astrophysics Data System (ADS)

    Wood, Christopher J.; Spekkens, Robert W.

    2015-03-01

    An active area of research in the fields of machine learning and statistics is the development of causal discovery algorithms, the purpose of which is to infer the causal relations that hold among a set of variables from the correlations that these exhibit . We apply some of these algorithms to the correlations that arise for entangled quantum systems. We show that they cannot distinguish correlations that satisfy Bell inequalities from correlations that violate Bell inequalities, and consequently that they cannot do justice to the challenges of explaining certain quantum correlations causally. Nonetheless, by adapting the conceptual tools of causal inference, we can show that any attempt to provide a causal explanation of nonsignalling correlations that violate a Bell inequality must contradict a core principle of these algorithms, namely, that an observed statistical independence between variables should not be explained by fine-tuning of the causal parameters. In particular, we demonstrate the need for such fine-tuning for most of the causal mechanisms that have been proposed to underlie Bell correlations, including superluminal causal influences, superdeterminism (that is, a denial of freedom of choice of settings), and retrocausal influences which do not introduce causal cycles.

  18. Causal events enter awareness faster than non-causal events

    PubMed Central

    Wagemans, Johan; de-Wit, Lee

    2017-01-01

    Philosophers have long argued that causality cannot be directly observed but requires a conscious inference (Hume, 1967). Albert Michotte however developed numerous visual phenomena in which people seemed to perceive causality akin to primary visual properties like colour or motion (Michotte, 1946). Michotte claimed that the perception of causality did not require a conscious, deliberate inference but, working over 70 years ago, he did not have access to the experimental methods to test this claim. Here we employ Continuous Flash Suppression (CFS)—an interocular suppression technique to render stimuli invisible (Tsuchiya & Koch, 2005)—to test whether causal events enter awareness faster than non-causal events. We presented observers with ‘causal’ and ‘non-causal’ events, and found consistent evidence that participants become aware of causal events more rapidly than non-causal events. Our results suggest that, whilst causality must be inferred from sensory evidence, this inference might be computed at low levels of perceptual processing, and does not depend on a deliberative conscious evaluation of the stimulus. This work therefore supports Michotte’s contention that, like colour or motion, causality is an immediate property of our perception of the world. PMID:28149698

  19. Causal attributions of dementia among Korean American immigrants.

    PubMed

    Lee, Sang E; Diwan, Sadhna; Yeo, Gwen

    2010-11-01

    To better understand conceptualizations of dementia, this study explored causal attributions of dementia among 209 Korean Americans, using a self-administered questionnaire in Korean. Findings show that Korean Americans endorsed various causal attributions. Factor analysis yielded 3 dimensions of their attributions including psychological, physical/environmental, and cognitive/social. Bivariate analyses showed that younger age and higher education were related to more physical/environmental attributions, and younger age was related to more cognitive/social attributions. The study provides an understanding of causal attributions of dementia that practitioners need to understand to provide culturally competent practice and highlights a need to customize public education messages by specific ethnic groups.

  20. The Functional-Notional Approach to Second Language Learning and Teaching: Starting with the Learner's Communicative Needs.

    ERIC Educational Resources Information Center

    Trabert, Judith A.

    This paper describes the functional-notional approach to language teaching and learning in terms of the ways it can be used to meet the communicative needs of the potential language learners, particularly adults, who vary in what they want to do in the target language. It contrasts the functional system with conventional approaches, illustrates…

  1. Adjusting for reverse causality in the relationship between obesity and mortality.

    PubMed

    Flanders, W D; Augestad, L B

    2008-08-01

    Reverse causality, in which obesity-induced disease leads to both weight loss and higher mortality, may bias observed associations between body mass index (BMI) and mortality, but the magnitude of that bias is unknown. The authors examined the impact of reverse causality and the exclusion of various diseases on the observed age-specific mortality ratios for BMI by using a state space model and sensitivity analyses. They found that reverse causality may decrease the ratios and induce a J-shaped curve on a graph. The authors further found that the net effect of excluding various diseases becomes a balance of competing forces, some tending to increase observed mortality ratios, where as others, such as selection based on common effects, may decrease them. Instead of studying just the change in observed mortality ratios, which can be misleading, investigators need to consider causal relationships and evaluate the conceptual and theoretical impact of any analytic maneuver. Analyses should be balanced with sensitivity approaches as well as with alternative analytic approaches such as the use of structural models, G-estimation, simulations and ancillary data from animal studies.

  2. On directed information theory and Granger causality graphs.

    PubMed

    Amblard, Pierre-Olivier; Michel, Olivier J J

    2011-02-01

    Directed information theory deals with communication channels with feedback. When applied to networks, a natural extension based on causal conditioning is needed. We show here that measures built from directed information theory in networks can be used to assess Granger causality graphs of stochastic processes. We show that directed information theory includes measures such as the transfer entropy, and that it is the adequate information theoretic framework needed for neuroscience applications, such as connectivity inference problems.

  3. MINIMIZING COGNITIVE ERRORS IN SITE-SPECIFIC CAUSAL ASSESSMENT

    EPA Science Inventory

    Interest in causal investigations in aquatic systems has been a natural outgrowth of the increased use of biological monitoring to characterize the condition of resources. Although biological monitoring approaches are critical tools for detecting whether effects are occurring, t...

  4. MINIMIZING COGNITIVE ERRORS IN SITE-SPECIFIC CAUSAL ASSESSMENT

    EPA Science Inventory

    Interest in causal investigations in aquatic systems has been a natural outgrowth of the increased use of biological monitoring to characterize the condition of resources. Although biological monitoring approaches are critical tools for detecting whether effects are occurring, t...

  5. Experimental test of nonlocal causality

    PubMed Central

    Ringbauer, Martin; Giarmatzi, Christina; Chaves, Rafael; Costa, Fabio; White, Andrew G.; Fedrizzi, Alessandro

    2016-01-01

    Explaining observations in terms of causes and effects is central to empirical science. However, correlations between entangled quantum particles seem to defy such an explanation. This implies that some of the fundamental assumptions of causal explanations have to give way. We consider a relaxation of one of these assumptions, Bell’s local causality, by allowing outcome dependence: a direct causal influence between the outcomes of measurements of remote parties. We use interventional data from a photonic experiment to bound the strength of this causal influence in a two-party Bell scenario, and observational data from a Bell-type inequality test for the considered models. Our results demonstrate the incompatibility of quantum mechanics with a broad class of nonlocal causal models, which includes Bell-local models as a special case. Recovering a classical causal picture of quantum correlations thus requires an even more radical modification of our classical notion of cause and effect. PMID:27532045

  6. Experimental test of nonlocal causality.

    PubMed

    Ringbauer, Martin; Giarmatzi, Christina; Chaves, Rafael; Costa, Fabio; White, Andrew G; Fedrizzi, Alessandro

    2016-08-01

    Explaining observations in terms of causes and effects is central to empirical science. However, correlations between entangled quantum particles seem to defy such an explanation. This implies that some of the fundamental assumptions of causal explanations have to give way. We consider a relaxation of one of these assumptions, Bell's local causality, by allowing outcome dependence: a direct causal influence between the outcomes of measurements of remote parties. We use interventional data from a photonic experiment to bound the strength of this causal influence in a two-party Bell scenario, and observational data from a Bell-type inequality test for the considered models. Our results demonstrate the incompatibility of quantum mechanics with a broad class of nonlocal causal models, which includes Bell-local models as a special case. Recovering a classical causal picture of quantum correlations thus requires an even more radical modification of our classical notion of cause and effect.

  7. Topological Causality in Dynamical Systems

    NASA Astrophysics Data System (ADS)

    Harnack, Daniel; Laminski, Erik; Schünemann, Maik; Pawelzik, Klaus Richard

    2017-09-01

    Determination of causal relations among observables is of fundamental interest in many fields dealing with complex systems. Since nonlinear systems generically behave as wholes, classical notions of causality assuming separability of subsystems often turn out inadequate. Still lacking is a mathematically transparent measure of the magnitude of effective causal influences in cyclic systems. For deterministic systems we found that the expansions of mappings among time-delay state space reconstructions from different observables not only reflect the directed coupling strengths, but also the dependency of effective influences on the system's temporally varying state. Estimation of the expansions from pairs of time series is straightforward and used to define novel causality indices. Mathematical and numerical analysis demonstrate that they reveal the asymmetry of causal influences including their time dependence, as well as provide measures for the effective strengths of causal links in complex systems.

  8. Do we need a voxel-based approach for LiDAR data in geomorphology?

    NASA Astrophysics Data System (ADS)

    Székely, Balázs; Dorninger, Peter; Faber, Robert; Nothegger, Clemens

    2010-05-01

    Generations of geomorphologists have developed a multi-faceted approach to model the Earth's (and planetary) surface and the corresponding processes. This set of models is based on data, more specifically on conspicuously increasing amount of data. Obviously, all geomorphologists wish themselves more accurate and increasingly high resolution data on, or related to the Earth surface. This evolution also means that the studied boundary is not anymore a single surface; instead it is considered mostly a 2.5D object, sometimes a real 3D object. LiDAR technology can cope with this challenge: the data accuracy and resolution requirements can be fulfilled by applying this method. Although it is yet somewhat still expensive, more and more areas will be scanned, and in some regions the topographic point clouds are already multitemporal (causing of course other types of processing and evaluation problems). It is rather obvious that for certain, geomorphologically very interesting areas very dense and severalfold multitemporal LiDAR data will be available in the near future. These data sets will have various differences concerning the data density, accuracy, data acquisition technique (conventional or full-waveform), and perhaps most importantly, concerning the actual state of the surface. Similar to the satellite imagery integration problems, soon we all have to face with the LiDAR data integration problem. What type of surface or surfaces can be derived from this multitude of data sources with acceptable ambiguity? What conclusions can be drawn from these data that were originally acquired for various other purposes using various acquisition concepts? Will it be advantageous for geomorphic use to have a coverage of the surface with 100-200 points/m² density? Clearly, these data are, if they are once collected, still too expensive not to be integrated for further analyses. Consequently, we need a data reduction concept that effectively decreases the computer capacity needed

  9. Negative Emissions Technologies, the Paris Agreement, and the Need for a Human-Rights Based Approach

    NASA Astrophysics Data System (ADS)

    Burns, W. C. G.

    2016-12-01

    The new Paris Agreement under the United Nations Framework Convention on Climate Change contemplates that its prospective Parties will balance emissions and sinks by 2050 as a means to effectuate the goal of holding temperature increases to well below 2°C from pre-industrial levels, as well as the more aspirational goal of holding temperature increases to 1.5°C. Most of the IPCC's AR5 scenarios that achieve these objectives contemplate the large-scale deployment of so-called "negative emissions technologies," with an emphasis on bioenergy and carbon capture and storage (BECCS), and to a lesser degree afforestation. BECCS could assuredly help society avoid passing critical climatic thresholds, or address overshoot scenarios in this century and beyond. However, it could also profound implications for food production, the status of forests, access to lands for livelihoods by vulnerable populations, and the integrity of critical ecosystems. This, in turn could have serious ramifications for human rights of some of the world's most vulnerable populations, including the rights to food, water, livelihoods and the benefits of biodiversity. The Preamble to the Paris Agreement acknowledges the need to take into consideration the potential impact of responses to climate change, providing that "Parties should, when taking action to address climate change, respect, promote and consider their respective obligations on human rights." This presentation will outline how application of a human rights-based approach to assessing such options could help to reconcile the objectives of ameliorating potential climatic impacts while protecting the human rights of potentially affected individuals and groups. This will include the potential role of Human Rights Impacts Assessments and potential configuration of HRIAs at the national and international level. It will also briefly suggest how to operationalize this approach within the Paris Agreement framework, including institutional

  10. Effectively Serving the Needs of Today's Business Student: The Product Life Cycle Approach to Class Organization

    ERIC Educational Resources Information Center

    Eastman, Jacqueline K.; Aviles, Maria; Hanna, Mark

    2012-01-01

    We illustrate a class organization process utilizing the concept of the Product Life Cycle to meet the needs of today's millennial student. In the Introduction stage of a business course, professors need to build structure to encourage commitment. In the Growth stage, professors need to promote the structure through multiple, brief activities that…

  11. Application of Database Approaches to the Study of Earth's Aeolian Environments: Community Needs and Goals

    NASA Astrophysics Data System (ADS)

    Scuderi, Louis A.; Weissmann, Gary S.; Hartley, Adrian J.; Yang, Xiaoping; Lancaster, Nicholas

    2017-08-01

    Aeolian science is faced with significant challenges that impact its ability to benefit from recent advances in information technology. The discipline deals with high-end systems in the form of ground and satellite based sensors, computer modeling and simulation, and wind tunnel experiments. Aeolian scientists also collect field data manually with observational methods that may differ significantly between studies with little agreement on even basic morphometric parameters and terminology. Data produced from these studies, while forming the core of research papers and reports, is rarely available to the community at large. Recent advances are also superimposed on an underlying semantic structure that dates to the 1800's or earlier that is confusing, with ambiguously defined, and at times even contradictory, meanings. The aeolian "world-view" does not always fit within neat increments nor is defined by crisp objects. Instead change is continuous and features are fuzzy. Development of an ontological framework to guide spatiotemporal research is the fundamental starting point for organizing data in aeolian science. This requires a "rethinking" of how we define, collect, process, store and share data along with the development of a community-wide collaborative approach designed to bring the discipline into a data rich future. There is also a pressing need to develop efficient methods to integrate, analyze and manage spatial and temporal data and to promote data produced by aeolian scientists so it is available for preparing diagnostic studies, as input into a range of environmental models, and for advising national and international bodies that drive research agendas. This requires the establishment of working groups within the discipline to deal with content, format, processing pipelines, knowledge discovery tools and database access issues unique to aeolian science.

  12. Bridging cancer biology and the patients' needs with nanotechnology-based approaches.

    PubMed

    Fonseca, Nuno A; Gregório, Ana C; Valério-Fernandes, Angela; Simões, Sérgio; Moreira, João N

    2014-06-01

    Cancer remains as stressful condition and a leading cause of death in the western world. Actual cornerstone treatments of cancer disease rest as an elusive alternative, offering limited efficacy with extensive secondary effects as a result of severe cytotoxic effects in healthy tissues. The advent of nanotechnology brought the promise to revolutionize many fields including oncology, proposing advanced systems for cancer treatment. Drug delivery systems rest among the most successful examples of nanotechnology. Throughout time they have been able to evolve as a function of an increased understanding from cancer biology and the tumor microenvironment. Marketing of Doxil® unleashed a remarkable impulse in the development of drug delivery systems. Since then, several nanocarriers have been introduced, with aspirations to overrule previous technologies, demonstrating increased therapeutic efficacy besides decreased toxicity. Spatial and temporal targeting to cancer cells has been explored, as well as the use of drug combinations co-encapsulated in the same particle as a mean to take advantage of synergistic interactions in vivo. Importantly, targeted delivery of siRNA for gene silencing therapy has made its way to the clinic for a "first in man" trial using lipid-polymeric-based particles. Focusing in state-of-the-art technology, this review will provide an insightful vision on nanotechnology-based strategies for cancer treatment, approaching them from a tumor biology-driven perspective, since their early EPR-based dawn to the ones that have truly the potential to address unmet medical needs in the field of oncology, upon targeting key cell subpopulations from the tumor microenvironment.

  13. The need for multisectoral food chain approaches to reduce trans fat consumption in India.

    PubMed

    Downs, Shauna M; Singh, Archna; Gupta, Vidhu; Lock, Karen; Ghosh-Jerath, Suparna

    2015-07-22

    The World Health Organization (WHO) recommends virtually eliminating trans fat from the global food supply. Although several high-income countries have successfully reduced trans fat levels in foods, low- and middle-income countries such as India face additional challenges to its removal from the food supply. This study provides a systems analysis of the Indian food chain to assess intervention options for reducing trans fat intake in low-income consumers. Data were collected at the manufacturer, retailer and consumer levels. Qualitative interviews were conducted with vanaspati manufacturers (n = 13) and local food vendors (n = 44). Laboratory analyses (n = 39) of street foods/snacks sold by the vendors were also conducted. Trans fat and snack intakes were also examined in low-income consumers in two rural villages (n = 260) and an urban slum (n = 261). Manufacturers of vanaspati described reducing trans fat levels as feasible but identified challenges in using healthier oils. The fat content of sampled oils from street vendors contained high levels of saturated fat (24.7-69.3 % of total fat) and trans fat (0.1-29.9 % of total fat). Households were consuming snacks high in trans fat as part of daily diets (31 % village and 84.3 % of slum households) and 4 % of rural and 13 % of urban households exceeded WHO recommendations for trans fat intakes. A multisectoral food chain approach to reducing trans fat is needed in India and likely in other low- and middle-income countries worldwide. This will require investment in development of competitively priced bakery shortenings and economic incentives for manufacturing foods using healthier oils. Increased production of healthier oils will also be required alongside these investments, which will become increasingly important as more and more countries begin investing in palm oil production.

  14. Massive dose vitamin A programme in India--need for a targeted approach.

    PubMed

    Kapil, Umesh; Sachdev, H P S

    2013-09-01

    The National Prophylaxis Programme against Nutritional Blindness due to vitamin A deficiency (NPPNB due to VAD) was started in 1970 with the specific aim of preventing nutritional blindness due to keratomalacia . The Programme was launched as an urgent remedial measure to combat the unacceptably high magnitude of xerophthalmic blindness in the country seen in the 1950s and 1960s. Clinical VAD has declined drastically during the last 40 years. Also, indicators of child health have shown substantial gains in different States in the country. The prevalence of severe undernutrition has come down significantly. Immunization coverage for measles and other vaccine preventable diseases has improved from 5-7 per cent in early seventies to currently 60-90 per cent, in different States. Similarly, there has been a significant improvement in the overall dietary intake of young children. There has been virtual disappearance of keratomalacia, and a sharp decline in the prevalence of Bitot spots. Prophylactic mega dose administration of vitamin A is primarily advocated because of the claim of 23 per cent reduction in childhood mortality. However, benefits on this scale have been found only in areas with rudimentary health care facilities where clinical deficiency is common, and there is substantial heterogeneity, especially with inclusion of all trials. There is an urgent need for adopting a targeted rather than universal prophylactic mega dose vitamin A supplementation in preschool children. This approach is justified on the basis of currently available evidence documenting a substantial decline in VAD prevalence, substantial heterogeneity and uncertainty about mortality effects in present era with improved health care, and resource constraints with competing priorities.

  15. IITET and shadow TT: an innovative approach to training at the point of need

    NASA Astrophysics Data System (ADS)

    Gross, Andrew; Lopez, Favio; Dirkse, James; Anderson, Darran; Berglie, Stephen; May, Christopher; Harkrider, Susan

    2014-06-01

    The Image Intensification and Thermal Equipment Training (IITET) project is a joint effort between Night Vision and Electronics Sensors Directorate (NVESD) Modeling and Simulation Division (MSD) and the Army Research Institute (ARI) Fort Benning Research Unit. The IITET effort develops a reusable and extensible training architecture that supports the Army Learning Model and trains Manned-Unmanned Teaming (MUM-T) concepts to Shadow Unmanned Aerial Systems (UAS) payload operators. The training challenge of MUM-T during aviation operations is that UAS payload operators traditionally learn few of the scout-reconnaissance skills and coordination appropriate to MUM-T at the schoolhouse. The IITET effort leveraged the simulation experience and capabilities at NVESD and ARI's research to develop a novel payload operator training approach consistent with the Army Learning Model. Based on the training and system requirements, the team researched and identified candidate capabilities in several distinct technology areas. The training capability will support a variety of training missions as well as a full campaign. Data from these missions will be captured in a fully integrated AAR capability, which will provide objective feedback to the user in near-real-time. IITET will be delivered via a combination of browser and video streaming technologies, eliminating the requirement for a client download and reducing user computer system requirements. The result is a novel UAS Payload Operator training capability, nested within an architecture capable of supporting a wide variety of training needs for air and ground tactical platforms and sensors, and potentially several other areas requiring vignette-based serious games training.

  16. Evaluating Criteria for English Learner Reclassification: A Causal-Effects Approach Using a Binding-Score Regression Discontinuity Design with Instrumental Variables

    ERIC Educational Resources Information Center

    Robinson, Joseph P.

    2011-01-01

    When English learners are "reclassified" as fluent English proficient, often their instructional setting changes, including a significant reduction in or elimination of English language development services. Depending on a child's language skills, this instructional change could hinder future development or provide needed opportunities…

  17. The Cradle of Causal Reasoning: Newborns' Preference for Physical Causality

    ERIC Educational Resources Information Center

    Mascalzoni, Elena; Regolin, Lucia; Vallortigara, Giorgio; Simion, Francesca

    2013-01-01

    Perception of mechanical (i.e. physical) causality, in terms of a cause-effect relationship between two motion events, appears to be a powerful mechanism in our daily experience. In spite of a growing interest in the earliest causal representations, the role of experience in the origin of this sensitivity is still a matter of dispute. Here, we…

  18. The Cradle of Causal Reasoning: Newborns' Preference for Physical Causality

    ERIC Educational Resources Information Center

    Mascalzoni, Elena; Regolin, Lucia; Vallortigara, Giorgio; Simion, Francesca

    2013-01-01

    Perception of mechanical (i.e. physical) causality, in terms of a cause-effect relationship between two motion events, appears to be a powerful mechanism in our daily experience. In spite of a growing interest in the earliest causal representations, the role of experience in the origin of this sensitivity is still a matter of dispute. Here, we…

  19. The cradle of causal reasoning: newborns' preference for physical causality.

    PubMed

    Mascalzoni, Elena; Regolin, Lucia; Vallortigara, Giorgio; Simion, Francesca

    2013-05-01

    Perception of mechanical (i.e. physical) causality, in terms of a cause-effect relationship between two motion events, appears to be a powerful mechanism in our daily experience. In spite of a growing interest in the earliest causal representations, the role of experience in the origin of this sensitivity is still a matter of dispute. Here, we asked the question about the innate origin of causal perception, never tested before at birth. Three experiments were carried out to investigate sensitivity at birth to some visual spatiotemporal cues present in a launching event. Newborn babies, only a few hours old, showed that they significantly preferred a physical causality event (i.e. Michotte's Launching effect) when matched to a delay event (i.e. a delayed launching; Experiment 1) or to a non-causal event completely identical to the causal one except for the order of the displacements of the two objects involved which was swapped temporally (Experiment 3). This preference for the launching event, moreover, also depended on the continuity of the trajectory between the objects involved in the event (Experiment 2). These results support the hypothesis that the human system possesses an early available, possibly innate basic mechanism to compute causality, such a mechanism being sensitive to the additive effect of certain well-defined spatiotemporal cues present in the causal event independently of any prior visual experience. © 2013 Blackwell Publishing Ltd.

  20. Structural Equations and Causal Explanations: Some Challenges for Causal SEM

    ERIC Educational Resources Information Center

    Markus, Keith A.

    2010-01-01

    One common application of structural equation modeling (SEM) involves expressing and empirically investigating causal explanations. Nonetheless, several aspects of causal explanation that have an impact on behavioral science methodology remain poorly understood. It remains unclear whether applications of SEM should attempt to provide complete…

  1. Structural Equations and Causal Explanations: Some Challenges for Causal SEM

    ERIC Educational Resources Information Center

    Markus, Keith A.

    2010-01-01

    One common application of structural equation modeling (SEM) involves expressing and empirically investigating causal explanations. Nonetheless, several aspects of causal explanation that have an impact on behavioral science methodology remain poorly understood. It remains unclear whether applications of SEM should attempt to provide complete…

  2. Leveraging ancestry to improve causal variant identification in exome sequencing for monogenic disorders.

    PubMed

    Brown, Robert; Lee, Hane; Eskin, Ascia; Kichaev, Gleb; Lohmueller, Kirk E; Reversade, Bruno; Nelson, Stanley F; Pasaniuc, Bogdan

    2016-01-01

    Recent breakthroughs in exome-sequencing technology have made possible the identification of many causal variants of monogenic disorders. Although extremely powerful when closely related individuals (eg, child and parents) are simultaneously sequenced, sequencing of a single case is often unsuccessful due to the large number of variants that need to be followed up for functional validation. Many approaches filter out common variants above a given frequency threshold (eg, 1%), and then prioritize the remaining variants according to their functional, structural and conservation properties. Here we present methods that leverage the genetic structure across different populations to improve filtering performance while accounting for the finite sample size of the reference panels. We show that leveraging genetic structure reduces the number of variants that need to be followed up by 16% in simulations and by up to 38% in empirical data of 20 exomes from individuals with monogenic disorders for which the causal variants are known.

  3. Mitigating the effects of measurement noise on Granger causality

    SciTech Connect

    Nalatore, Hariharan; Ding Mingzhou; Rangarajan, Govindan

    2007-03-15

    Computing Granger causal relations among bivariate experimentally observed time series has received increasing attention over the past few years. Such causal relations, if correctly estimated, can yield significant insights into the dynamical organization of the system being investigated. Since experimental measurements are inevitably contaminated by noise, it is thus important to understand the effects of such noise on Granger causality estimation. The first goal of this paper is to provide an analytical and numerical analysis of this problem. Specifically, we show that, due to noise contamination (1) spurious causality between two measured variables can arise and (2) true causality can be suppressed. The second goal of the paper is to provide a denoising strategy to mitigate this problem. Specifically, we propose a denoising algorithm based on the combined use of the Kalman filter theory and the expectation-maximization algorithm. Numerical examples are used to demonstrate the effectiveness of the denoising approach.

  4. Spatio-temporal Granger causality: a new framework

    PubMed Central

    Luo, Qiang; Lu, Wenlian; Cheng, Wei; Valdes-Sosa, Pedro A.; Wen, Xiaotong; Ding, Mingzhou; Feng, Jianfeng

    2015-01-01

    That physiological oscillations of various frequencies are present in fMRI signals is the rule, not the exception. Herein, we propose a novel theoretical framework, spatio-temporal Granger causality, which allows us to more reliably and precisely estimate the Granger causality from experimental datasets possessing time-varying properties caused by physiological oscillations. Within this framework, Granger causality is redefined as a global index measuring the directed information flow between two time series with time-varying properties. Both theoretical analyses and numerical examples demonstrate that Granger causality is a monotonically increasing function of the temporal resolution used in the estimation. This is consistent with the general principle of coarse graining, which causes information loss by smoothing out very fine-scale details in time and space. Our results confirm that the Granger causality at the finer spatio-temporal scales considerably outperforms the traditional approach in terms of an improved consistency between two resting-state scans of the same subject. To optimally estimate the Granger causality, the proposed theoretical framework is implemented through a combination of several approaches, such as dividing the optimal time window and estimating the parameters at the fine temporal and spatial scales. Taken together, our approach provides a novel and robust framework for estimating the Granger causality from fMRI, EEG, and other related data. PMID:23643924

  5. Spatio-temporal Granger causality: a new framework.

    PubMed

    Luo, Qiang; Lu, Wenlian; Cheng, Wei; Valdes-Sosa, Pedro A; Wen, Xiaotong; Ding, Mingzhou; Feng, Jianfeng

    2013-10-01

    That physiological oscillations of various frequencies are present in fMRI signals is the rule, not the exception. Herein, we propose a novel theoretical framework, spatio-temporal Granger causality, which allows us to more reliably and precisely estimate the Granger causality from experimental datasets possessing time-varying properties caused by physiological oscillations. Within this framework, Granger causality is redefined as a global index measuring the directed information flow between two time series with time-varying properties. Both theoretical analyses and numerical examples demonstrate that Granger causality is a monotonically increasing function of the temporal resolution used in the estimation. This is consistent with the general principle of coarse graining, which causes information loss by smoothing out very fine-scale details in time and space. Our results confirm that the Granger causality at the finer spatio-temporal scales considerably outperforms the traditional approach in terms of an improved consistency between two resting-state scans of the same subject. To optimally estimate the Granger causality, the proposed theoretical framework is implemented through a combination of several approaches, such as dividing the optimal time window and estimating the parameters at the fine temporal and spatial scales. Taken together, our approach provides a novel and robust framework for estimating the Granger causality from fMRI, EEG, and other related data.

  6. Instrumental variable methods for causal inference.

    PubMed

    Baiocchi, Michael; Cheng, Jing; Small, Dylan S

    2014-06-15

    A goal of many health studies is to determine the causal effect of a treatment or intervention on health outcomes. Often, it is not ethically or practically possible to conduct a perfectly randomized experiment, and instead, an observational study must be used. A major challenge to the validity of observational studies is the possibility of unmeasured confounding (i.e., unmeasured ways in which the treatment and control groups differ before treatment administration, which also affect the outcome). Instrumental variables analysis is a method for controlling for unmeasured confounding. This type of analysis requires the measurement of a valid instrumental variable, which is a variable that (i) is independent of the unmeasured confounding; (ii) affects the treatment; and (iii) affects the outcome only indirectly through its effect on the treatment. This tutorial discusses the types of causal effects that can be estimated by instrumental variables analysis; the assumptions needed for instrumental variables analysis to provide valid estimates of causal effects and sensitivity analysis for those assumptions; methods of estimation of causal effects using instrumental variables; and sources of instrumental variables in health studies. Copyright © 2014 John Wiley & Sons, Ltd.

  7. The Need to Disentangle Key Concepts from Ecosystem-Approach Jargon

    PubMed Central

    WAYLEN, K A; HASTINGS, E J; BANKS, E A; HOLSTEAD, K L; IRVINE, R J; BLACKSTOCK, K L

    2014-01-01

    The ecosystem approach—as endorsed by the Convention on Biological Diversity (CDB) in 2000—is a strategy for holistic, sustainable, and equitable natural resource management, to be implemented via the 12 Malawi Principles. These principles describe the need to manage nature in terms of dynamic ecosystems, while fully engaging with local peoples. It is an ambitious concept. Today, the term is common throughout the research and policy literature on environmental management. However, multiple meanings have been attached to the term, resulting in confusion. We reviewed references to the ecosystem approach from 1957 to 2012 and identified 3 primary uses: as an alternative to ecosystem management or ecosystem-based management; in reference to an integrated and equitable approach to resource management as per the CBD; and as a term signifying a focus on understanding and valuing ecosystem services. Although uses of this term and its variants may overlap in meaning, typically, they do not entirely reflect the ethos of the ecosystem approach as defined by the CBD. For example, there is presently an increasing emphasis on ecosystem services, but focusing on these alone does not promote decentralization of management or use of all forms of knowledge, both of which are integral to the CBD’s concept. We highlight that the Malawi Principles are at risk of being forgotten. To better understand these principles, more effort to implement them is required. Such efforts should be evaluated, ideally with comparative approaches, before allowing the CBD’s concept of holistic and socially engaged management to be abandoned or superseded. It is possible that attempts to implement all 12 principles together will face many challenges, but they may also offer a unique way to promote holistic and equitable governance of natural resources. Therefore, we believe that the CBD’s concept of the ecosystem approach demands more attention. La Necesidad de Desenredar Conceptos Clave del

  8. Pharmacological Approaches for the Management of Persistent Pain in Older Adults: What Nurses Need to Know.

    PubMed

    Guerriero, Fabio; Bolier, Ruth; Van Cleave, Janet H; Reid, M Cary

    2016-12-01

    HOW TO OBTAIN CONTACT HOURS BY READING THIS ARTICLE INSTRUCTIONS 1.4 contact hours will be awarded by Villanova University College of Nursing upon successful completion of this activity. A contact hour is a unit of measurement that denotes 60 minutes of an organized learning activity. This is a learner-based activity. Villanova University College of Nursing does not require submission of your answers to the quiz. A contact hour certificate will be awarded once you register, pay the registration fee, and complete the evaluation form online at http://goo.gl/gMfXaf. To obtain contact hours you must: 1. Read the article, "Pharmacological Approaches for the Management of Persistent Pain in Older Adults: What Nurses Need to Know" found on pages 49-57, carefully noting any tables and other illustrative materials that are included to enhance your knowledge and understanding of the content. Be sure to keep track of the amount of time (number of minutes) you spend reading the article and completing the quiz. 2. Read and answer each question on the quiz. After completing all of the questions, compare your answers to those provided within this issue. If you have incorrect answers, return to the article for further study. 3. Go to the Villanova website listed above to register for contact hour credit. You will be asked to provide your name; contact information; and a VISA, MasterCard, or Discover card number for payment of the $20.00 fee. Once you complete the online evaluation, a certificate will be automatically generated. This activity is valid for continuing education credit until November 30, 2019. CONTACT HOURS This activity is co-provided by Villanova University College of Nursing and SLACK Incorporated. Villanova University College of Nursing is accredited as a provider of continuing nursing education by the American Nurses Credentialing Center's Commission on Accreditation. ACTIVITY OBJECTIVES 1. Describe age-related barriers to pain assessment and key aspects of the

  9. Causal inference in cross-lagged panel analysis: a reciprocal causal relationship between cognitive function and depressive symptoms.

    PubMed

    Yoon, Ju Young; Brown, Roger L

    2014-01-01

    Cross-lagged panel analysis (CLPA) is a method of examining one-way or reciprocal causal inference between longitudinally changing variables. It has been used in the social sciences for many years, but not much in nursing research. This article introduces the conceptual and statistical background of CLPA and provides an exemplar of CLPA that examines the reciprocal causal relationship between depression and cognitive function over time in older adults. The 2-year cross-lagged effects of depressive symptoms (T1) on cognitive function (T2) and cognitive function (T1) on depressive symptoms (T2) were significant, which demonstrated a reciprocal causal relationship between cognitive function and depressive mood over time. Although CLPA is a methodologically strong approach to examine the reciprocal causal inferences over time, it is necessary to consider potential sources of spuriousness to lead to false causal relationship and a reasonable time frame to detect the change of the variables.

  10. Photoemission in strongly correlated crystalline f-electron systems: A need for a new approach

    SciTech Connect

    Arko, A.J.; Joyce, J.J.; Sarrao, J.

    1998-12-01

    The unusual properties of heavy fermion (or heavy electron) materials have sparked an avalanche of research over the last two decades in order to understand the basic phenomena responsible for these properties. Photoelectron spectroscopy (often referred to as PES in the following sections), the most direct measurement of the electronic structure of a material, should in principle be able to shed considerable light on this matter. In general the distinction between a localized and a band-like state is trivially observed in band dispersion. Much of the past work was performed on poly-crystalline samples, scraped in-situ to expose a clean surface for PES. There have since been considerable advances both in the quality of specimens as well as experimental resolution, which raise questions regarding these conclusions. Much of the past work on poly-crystalline samples has been reported in several review articles, most notably Allen et al., and it is not necessary here to review those efforts again, with the exception of subsequent work performed at high resolution. The primary focus of the present review will be on new measurements obtained on single crystals, cleaved or prepared in situ and measured at high resolution, which seem to suggest that agreement with the GS and NCA approximations is less than perfect, and that perhaps the starting models need to be modified, or that even an entirely new approach is called for. Of the promising new models the Periodic Anderson Model is most closely related to the SIM. Indeed, at high temperatures it reverts to the SIM. However, the charge polaron model of Liu (1997) as well as the two-electron band model of Sheng and Cooper (1995) cannot yet be ruled out. Inasmuch as the bulk of the single crystal work was performed by the Los Alamos group, this review will draw heavily on those results. Moreover, since the GS and NCA approximations represent the most comprehensive and widely accepted treatment of heavy fermion PES, it is only

  11. Soil erosion and watershed carbon budget: the need for a multifaceted approach

    NASA Astrophysics Data System (ADS)

    Jacinthe, P.-A.

    2009-04-01

    fluvial reservoir from a net sink to a net source. Therefore, coupling with the hydrologic cycle must be considered when assessing the net contribution of eroded C sedimentation to the global/regional C budget. These results will be discussed with emphasis on the multifaceted approach that is needed to advance this area of research.

  12. Ecological and evolutionary mechanisms for low seed: ovule ratios: need for a pluralistic approach?

    PubMed

    Holland, J Nathaniel; Chamberlain, Scott A

    2007-03-01

    need to adopt a more pluralistic approach to seed : ovule ratios and consider alternative hypotheses, including a greater array of proximate and ultimate causes. Initial results of this study suggest that floral allometry, selection on correlated floral traits, stigma clogging with pollen grains, and style clogging with pollen tubes may provide promising avenues for understanding low seed : ovule ratios.

  13. Causal Inference in Retrospective Studies.

    ERIC Educational Resources Information Center

    Holland, Paul W.; Rubin, Donald B.

    1988-01-01

    The problem of drawing causal inferences from retrospective case-controlled studies is considered. A model for causal inference in prospective studies is applied to retrospective studies. Limitations of case-controlled studies are formulated concerning relevant parameters that can be estimated in such studies. A coffee-drinking/myocardial…

  14. The Development of Causal Categorization

    ERIC Educational Resources Information Center

    Hayes, Brett K.; Rehder, Bob

    2012-01-01

    Two experiments examined the impact of causal relations between features on categorization in 5- to 6-year-old children and adults. Participants learned artificial categories containing instances with causally related features and noncausal features. They then selected the most likely category member from a series of novel test pairs.…

  15. Theory-Based Causal Induction

    ERIC Educational Resources Information Center

    Griffiths, Thomas L.; Tenenbaum, Joshua B.

    2009-01-01

    Inducing causal relationships from observations is a classic problem in scientific inference, statistics, and machine learning. It is also a central part of human learning, and a task that people perform remarkably well given its notorious difficulties. People can learn causal structure in various settings, from diverse forms of data: observations…

  16. Expert Causal Reasoning and Explanation.

    ERIC Educational Resources Information Center

    Kuipers, Benjamin

    The relationship between cognitive psychologists and researchers in artificial intelligence carries substantial benefits for both. An ongoing investigation in causal reasoning in medical problem solving systems illustrates this interaction. This paper traces a dialectic of sorts in which three different types of causal resaoning for medical…

  17. Causal Inference and Developmental Psychology

    ERIC Educational Resources Information Center

    Foster, E. Michael

    2010-01-01

    Causal inference is of central importance to developmental psychology. Many key questions in the field revolve around improving the lives of children and their families. These include identifying risk factors that if manipulated in some way would foster child development. Such a task inherently involves causal inference: One wants to know whether…

  18. Causality in Solving Economic Problems

    ERIC Educational Resources Information Center

    Robinson, A. Emanuel; Sloman, Steven A.; Hagmayer, York; Hertzog, Christopher K.

    2010-01-01

    The role of causal beliefs in people's decisions when faced with economic problems was investigated. Two experiments are reported that vary the causal structure in prisoner's dilemma-like economic situations. We measured willingness to cooperate or defect and collected justifications and think-aloud protocols to examine the strategies that people…

  19. Causal Inference in Retrospective Studies.

    ERIC Educational Resources Information Center

    Holland, Paul W.; Rubin, Donald B.

    1988-01-01

    The problem of drawing causal inferences from retrospective case-controlled studies is considered. A model for causal inference in prospective studies is applied to retrospective studies. Limitations of case-controlled studies are formulated concerning relevant parameters that can be estimated in such studies. A coffee-drinking/myocardial…

  20. Causal Learning with Local Computations

    ERIC Educational Resources Information Center

    Fernbach, Philip M.; Sloman, Steven A.

    2009-01-01

    The authors proposed and tested a psychological theory of causal structure learning based on local computations. Local computations simplify complex learning problems via cues available on individual trials to update a single causal structure hypothesis. Structural inferences from local computations make minimal demands on memory, require…

  1. Causal Inference and Developmental Psychology

    ERIC Educational Resources Information Center

    Foster, E. Michael

    2010-01-01

    Causal inference is of central importance to developmental psychology. Many key questions in the field revolve around improving the lives of children and their families. These include identifying risk factors that if manipulated in some way would foster child development. Such a task inherently involves causal inference: One wants to know whether…

  2. Causal Attributions of Shy Subjects.

    ERIC Educational Resources Information Center

    Teglasi, Hedwig; Hoffman, Mary Ann

    1982-01-01

    Causal attributions of shy students (N=36) were compared with those of a comparison group of students (N=36) in ten situations. Significant differences between the two groups emerged when explaining outcomes of situations considered to be problematic for shy individuals. Causal attributions may reflect realistic and situation-specific…

  3. A basic need theory approach to problematic Internet use and the mediating effect of psychological distress.

    PubMed

    Wong, Ting Yat; Yuen, Kenneth S L; Li, Wang On

    2014-01-01

    The Internet provides an easily accessible way to meet certain needs. Over-reliance on it leads to problematic use, which studies show can be predicted by psychological distress. Self-determination theory proposes that we all have the basic need for autonomy, competency, and relatedness. This has been shown to explain the motivations behind problematic Internet use. This study hypothesizes that individuals who are psychologically disturbed because their basic needs are not being met are more vulnerable to becoming reliant on the Internet when they seek such needs satisfaction from online activities, and tests a model in which basic needs predict problematic Internet use, fully mediated by psychological distress. Problematic Internet use, psychological distress, and basic needs satisfaction were psychometrically measured in a sample of 229 Hong Kong University students and structural equation modeling was used to test the hypothesized model. All indices showed the model has a good fit. Further, statistical testing supported a mediation effect for psychological distress between needs satisfaction and problematic Internet use. The results extend our understanding of the development and prevention of problematic Internet use based on the framework of self-determination theory. Psychological distress could be used as an early predictor, while preventing and treating problematic Internet use should emphasize the fulfillment of unmet needs.

  4. Service Approaches to Young People with Complex Needs Leaving Out-of-Home Care

    ERIC Educational Resources Information Center

    Malvaso, Catia; Delfabbro, Paul; Hackett, Louisa; Mills, Hayley

    2016-01-01

    Although leaving statutory out-of-home care can be a challenging time for many young people, it is recognised that young people who have multiple or complex needs find this transition particularly difficult. This study aims to gain a deeper understanding of the challenges faced by care leavers who have complex needs, as well as to identify some of…

  5. Need Supportive Teaching in Practice: A Narrative Analysis in Schools with Contrasting Educational Approaches

    ERIC Educational Resources Information Center

    Stroet, Kim; Opdenakker, Marie-Christine; Minnaert, Alexander

    2015-01-01

    Research on self-determination theory (SDT) has shown that positive learning outcomes accrue in classrooms that support students' needs for autonomy, competence, and relatedness. Studies on what need supportive teaching entails in practice are, however, scarce. In the present study, we aimed to gain in-depth understanding of typical manifestations…

  6. Service Approaches to Young People with Complex Needs Leaving Out-of-Home Care

    ERIC Educational Resources Information Center

    Malvaso, Catia; Delfabbro, Paul; Hackett, Louisa; Mills, Hayley

    2016-01-01

    Although leaving statutory out-of-home care can be a challenging time for many young people, it is recognised that young people who have multiple or complex needs find this transition particularly difficult. This study aims to gain a deeper understanding of the challenges faced by care leavers who have complex needs, as well as to identify some of…

  7. Need Supportive Teaching in Practice: A Narrative Analysis in Schools with Contrasting Educational Approaches

    ERIC Educational Resources Information Center

    Stroet, Kim; Opdenakker, Marie-Christine; Minnaert, Alexander

    2015-01-01

    Research on self-determination theory (SDT) has shown that positive learning outcomes accrue in classrooms that support students' needs for autonomy, competence, and relatedness. Studies on what need supportive teaching entails in practice are, however, scarce. In the present study, we aimed to gain in-depth understanding of typical manifestations…

  8. Meeting the Needs of All Students: A Universal Design Approach to Computer-Based Testing

    ERIC Educational Resources Information Center

    Russell, Michael; Hoffmann, Thomas; Higgins, Jennifer

    2009-01-01

    Michael Russell, Thomas Hoffmann, and Jennifer Higgins describe how the principles of universal design were applied to the development of an innovative computer-based test delivery system, NimbleTools, to meet the accessibility and accommodation needs of students with a wide range of disabilities and special needs. Noting the movement to…

  9. Teaching Music to Students with Special Needs: A Label-Free Approach

    ERIC Educational Resources Information Center

    Hammel, Alice; Hourigan, Ryan

    2011-01-01

    A practical guide & reference manual, "Teaching Music to Students with Special Needs" addresses special needs in the broadest possible sense to equip teachers with proven, research-based curricular strategies that are grounded in both best practice and current special education law. Chapters address the full range of topics and issues music…

  10. Supervision Strategies and Approaches for Female Parolees: Examining the Link between Unmet Needs and Parolee Outcome

    ERIC Educational Resources Information Center

    Schram, Pamela J.; Koons-Witt, Barbara A.; Williams, Frank P., III; McShane, Marilyn D.

    2006-01-01

    A number of parolees are returning to the community with programming needs that may not have been addressed during their incarceration; these unmet needs may subsequently affect their successful reintegration into the community. Although there is an increasing female parole population, there has been a paucity of research concerning female…

  11. Basic Human Needs: A Development Planning Approach. AID Discussion Paper No. 38.

    ERIC Educational Resources Information Center

    Crosswell, Michael

    The monograph explores basic needs of all human beings and considers various patterns of growth and development toward meeting these needs on a sustainable basis. The purpose of the study is to improve knowledge of analytical studies, research results, and financial assistance policies among personnel of the Agency for International Development…

  12. Teaching Music to Students with Special Needs: A Label-Free Approach

    ERIC Educational Resources Information Center

    Hammel, Alice; Hourigan, Ryan

    2011-01-01

    A practical guide & reference manual, "Teaching Music to Students with Special Needs" addresses special needs in the broadest possible sense to equip teachers with proven, research-based curricular strategies that are grounded in both best practice and current special education law. Chapters address the full range of topics and issues music…

  13. High School Teachers' Perspectives on Effective Approaches for Teaching Biology to Students with Special Needs

    ERIC Educational Resources Information Center

    Kos, Agnieszka

    2010-01-01

    The demands of national educational reforms require high school biology teachers to provide high quality instruction to students with and without special needs. The reforms, however, do not provide teachers with adequate teaching strategies to meet the needs of all students in the same context. The purpose of this grounded theory study was to…

  14. Understanding Social and Emotional Needs as an Approach in Developing a Positive Classroom Environment

    ERIC Educational Resources Information Center

    Ozorio, Kristen

    2014-01-01

    The classroom environment is an important aspect of classroom management that concerns many teachers. Properly engaging students in the classroom can foster a positive environment. This study examines social and emotional needs of students and its implications in developing a positive classroom. How can meeting social and emotional needs of…

  15. Supervision Strategies and Approaches for Female Parolees: Examining the Link between Unmet Needs and Parolee Outcome

    ERIC Educational Resources Information Center

    Schram, Pamela J.; Koons-Witt, Barbara A.; Williams, Frank P., III; McShane, Marilyn D.

    2006-01-01

    A number of parolees are returning to the community with programming needs that may not have been addressed during their incarceration; these unmet needs may subsequently affect their successful reintegration into the community. Although there is an increasing female parole population, there has been a paucity of research concerning female…

  16. Dual Powerpoint Presentation Approach for Students with Special Educational Needs and Note-Takers

    ERIC Educational Resources Information Center

    Naik, Nitin

    2017-01-01

    In higher education, supporting students with special educational needs (SEN) necessitates an understanding of these needs, additional teaching aids and innovative ideas. The teacher must be an integral part of this support process, and this is difficult for the majority of teachers, due to their lack of core understanding of SEN. However,…

  17. Dual Powerpoint Presentation Approach for Students with Special Educational Needs and Note-Takers

    ERIC Educational Resources Information Center

    Naik, Nitin

    2017-01-01

    In higher education, supporting students with special educational needs (SEN) necessitates an understanding of these needs, additional teaching aids and innovative ideas. The teacher must be an integral part of this support process, and this is difficult for the majority of teachers, due to their lack of core understanding of SEN. However,…

  18. Beyond the Dilemma of Difference: The Capability Approach to Disability and Special Educational Needs

    ERIC Educational Resources Information Center

    Terzi, Lorella

    2005-01-01

    In her recent pamphlet "Special Educational Needs: a new look (2005)," Mary Warnock has called for a radical review of special needs education and a substantial reconsideration of the assumptions upon which the current educational framework is based. The latter, she maintains, is hindered by a contradiction between the intention to treat all…

  19. Meeting the Needs of All Students: A Universal Design Approach to Computer-Based Testing

    ERIC Educational Resources Information Center

    Russell, Michael; Hoffmann, Thomas; Higgins, Jennifer

    2009-01-01

    Michael Russell, Thomas Hoffmann, and Jennifer Higgins describe how the principles of universal design were applied to the development of an innovative computer-based test delivery system, NimbleTools, to meet the accessibility and accommodation needs of students with a wide range of disabilities and special needs. Noting the movement to…

  20. A basic need theory approach to problematic Internet use and the mediating effect of psychological distress

    PubMed Central

    Wong, Ting Yat; Yuen, Kenneth S. L.; Li, Wang On

    2015-01-01

    The Internet provides an easily accessible way to meet certain needs. Over-reliance on it leads to problematic use, which studies show can be predicted by psychological distress. Self-determination theory proposes that we all have the basic need for autonomy, competency, and relatedness. This has been shown to explain the motivations behind problematic Internet use. This study hypothesizes that individuals who are psychologically disturbed because their basic needs are not being met are more vulnerable to becoming reliant on the Internet when they seek such needs satisfaction from online activities, and tests a model in which basic needs predict problematic Internet use, fully mediated by psychological distress. Problematic Internet use, psychological distress, and basic needs satisfaction were psychometrically measured in a sample of 229 Hong Kong University students and structural equation modeling was used to test the hypothesized model. All indices showed the model has a good fit. Further, statistical testing supported a mediation effect for psychological distress between needs satisfaction and problematic Internet use. The results extend our understanding of the development and prevention of problematic Internet use based on the framework of self-determination theory. Psychological distress could be used as an early predictor, while preventing and treating problematic Internet use should emphasize the fulfillment of unmet needs. PMID:25642201

  1. On causality of extreme events

    PubMed Central

    2016-01-01

    Multiple metrics have been developed to detect causality relations between data describing the elements constituting complex systems, all of them considering their evolution through time. Here we propose a metric able to detect causality within static data sets, by analysing how extreme events in one element correspond to the appearance of extreme events in a second one. The metric is able to detect non-linear causalities; to analyse both cross-sectional and longitudinal data sets; and to discriminate between real causalities and correlations caused by confounding factors. We validate the metric through synthetic data, dynamical and chaotic systems, and data representing the human brain activity in a cognitive task. We further show how the proposed metric is able to outperform classical causality metrics, provided non-linear relationships are present and large enough data sets are available. PMID:27330866

  2. Paradoxical Behavior of Granger Causality

    NASA Astrophysics Data System (ADS)

    Witt, Annette; Battaglia, Demian; Gail, Alexander

    2013-03-01

    Granger causality is a standard tool for the description of directed interaction of network components and is popular in many scientific fields including econometrics, neuroscience and climate science. For time series that can be modeled as bivariate auto-regressive processes we analytically derive an expression for spectrally decomposed Granger Causality (SDGC) and show that this quantity depends only on two out of four groups of model parameters. Then we present examples of such processes whose SDGC expose paradoxical behavior in the sense that causality is high for frequency ranges with low spectral power. For avoiding misinterpretations of Granger causality analysis we propose to complement it by partial spectral analysis. Our findings are illustrated by an example from brain electrophysiology. Finally, we draw implications for the conventional definition of Granger causality. Bernstein Center for Computational Neuroscience Goettingen

  3. An introduction to causal modeling in clinical trials.

    PubMed

    Bellamy, Scarlett L; Lin, Julia Y; Ten Have, Thomas R

    2007-01-01

    We review and compare two causal modeling approaches that correspond to two major and distinct classes of inference - efficacy and intervention-based inference - in the context of randomized trials with subject noncompliance. We review the definitions of efficacy and intervention-based effects in the clinical trials literature and relate these to two separate and distinct causal modeling approaches: the structural mean modeling (SMM) approach and the principal stratification, instrumental variable approach. The SMM-based efficacy approach focuses on the effect of actually receiving treatment. In contrast, the principal stratification method addresses the effect of treatment assignment within partially unobserved latent subgroups defined by compliance behavior. While these approaches differ in terms of philosophy, model definitions, and estimation, they estimate the same causal effect under certain assumptions, but estimate very different causal effects when those assumptions are relaxed. We illustrate these results using a randomized psychiatry trial where the focus is physician compliance to the designated protocol and the other examines patient compliance to the designated protocol, both from the same trial. The validity of the models under the instrumental variable, SMM and principal stratification approaches depends on modeling assumptions, some of which may not be verifiable from the observed data and potentially less realistic than the no-confounding assumption made by non-causal approaches. This comparison in terms of efficacy versus intervention-based effects in causal modeling parallels the explanatory versus pragmatic approaches in clinical trials research; therefore researchers should weigh carefully when choosing causal modeling methodology based on whether efficacy or intervention-based effects are of interest.

  4. Strengthening the Focus on Business Results: The Need for Systems Approaches in Organizational Behavior Management

    ERIC Educational Resources Information Center

    Hyten, Cloyd

    2009-01-01

    Current Organizational Behavior Management (OBM) research and practice may be characterized as either behavior focused or results focused. These two approaches stem from different origins and have different characteristics. The behavior-focused approach stems from applied behavior analysis (ABA) methods and emphasizes direct observation of and…

  5. A Multi-Faceted Formative Assessment Approach: Better Recognising the Learning Needs of Students

    ERIC Educational Resources Information Center

    Jenkins, James O.

    2010-01-01

    Students are increasingly subject to a series of learning pressures that prevent effective engagement in assessment. Thus, the aim of this study was to create a multi-faceted formative assessment approach that better enabled students to engage in the assessment process. A formative assessment approach, consisting of six key initiatives, is…

  6. A Multi-Faceted Formative Assessment Approach: Better Recognising the Learning Needs of Students

    ERIC Educational Resources Information Center

    Jenkins, James O.

    2010-01-01

    Students are increasingly subject to a series of learning pressures that prevent effective engagement in assessment. Thus, the aim of this study was to create a multi-faceted formative assessment approach that better enabled students to engage in the assessment process. A formative assessment approach, consisting of six key initiatives, is…

  7. A toolkit modeling approach for sustainable forest management planning: achieving balance between science and local needs

    Treesearch

    Brian R. Sturtevant; Andrew Fall; Daniel D. Kneeshaw; Neal P. P. Simon; Michael J. Papaik; Kati Berninger; Frederik Doyon; Don G. Morgan; Christian Messier

    2007-01-01

    To assist forest managers in balancing an increasing diversity of resource objectives, we developed a toolkit modeling approach for sustainable forest management (SFM). The approach inserts a meta-modeling strategy into a collaborative modeling framework grounded in adaptive management philosophy that facilitates participation among stakeholders, decision makers, and...

  8. Strengthening the Focus on Business Results: The Need for Systems Approaches in Organizational Behavior Management

    ERIC Educational Resources Information Center

    Hyten, Cloyd

    2009-01-01

    Current Organizational Behavior Management (OBM) research and practice may be characterized as either behavior focused or results focused. These two approaches stem from different origins and have different characteristics. The behavior-focused approach stems from applied behavior analysis (ABA) methods and emphasizes direct observation of and…

  9. Structure and Strength in Causal Induction

    ERIC Educational Resources Information Center

    Griffiths, Thomas L.; Tenenbaum, Joshua B.

    2005-01-01

    We present a framework for the rational analysis of elemental causal induction--learning about the existence of a relationship between a single cause and effect--based upon causal graphical models. This framework makes precise the distinction between causal structure and causal strength: the difference between asking whether a causal relationship…

  10. Masculinities and young men's sex education needs in Ireland: problematizing client-centred health promotion approaches.

    PubMed

    Hyde, Abbey; Howlett, Etaoine; Drennan, Jonathan; Brady, Dympna

    2005-12-01

    In recent decades, dominant discourses in health promotion have emphasized empowerment, client participation and the notion of people identifying and being facilitated to meet their own health needs. However, there has been little analysis of the concept of 'need' and the possibility, at least, that the fulfillment of some such self-defined needs are not in the interest of social justice and equality. In this article, we present an account of the sex education needs of secondary school pupils from their own perspectives, and problematize the concept of self-identified needs in health education. Twenty-nine focus group interviews were conducted with 226 secondary school pupils in Ireland, and data were subjected to a qualitative analysis. Findings suggested that young men tended to prioritize practical guidance that would provide them with the skills and confidence to take the lead in sexual encounters, and display competence in the act of penetrative sex. We argue that these self-defined sex education needs emanate from a culture of traditional masculinity where, for a male, one's place in the pecking order is derived from one's capacity to conquer, lead and display mastery with regard to sex. In the discussion, we attempt to unpack the notion of clients identifying their own needs and the concept of empowerment as it relates to our data, in the context of gender-based structural inequalities.

  11. Tailoring online information retrieval to user's needs based on a logical semantic approach to natural language processing and UMLS mapping.

    PubMed

    Kossman, Susan; Jones, Josette; Brennan, Patricia Flatley

    2007-10-11

    Depression can derail teenagers' lives and cause serious chronic health problems. Acquiring pertinent knowledge and skills supports care management, but retrieving appropriate information can be difficult. This poster presents a strategy to tailor online information to user attributes using a logical semantic approach to natural language processing (NLP) and mapping propositions to UMLS terms. This approach capitalizes on existing NLM resources and presents a potentially sustainable plan for meeting consumers and providers information needs.

  12. Nonlinear Modeling of Causal Interrelationships in Neuronal Ensembles

    PubMed Central

    Zanos, Theodoros P.; Courellis, Spiros H.; Berger, Theodore W.; Hampson, Robert E.; Deadwyler, Sam A.; Marmarelis, Vasilis Z.

    2009-01-01

    The increasing availability of multiunit recordings gives new urgency to the need for effective analysis of “multidimensional” time-series data that are derived from the recorded activity of neuronal ensembles in the form of multiple sequences of action potentials—treated mathematically as point-processes and computationally as spike-trains. Whether in conditions of spontaneous activity or under conditions of external stimulation, the objective is the identification and quantification of possible causal links among the neurons generating the observed binary signals. A multiple-input/multiple-output (MIMO) modeling methodology is presented that can be used to quantify the neuronal dynamics of causal interrelationships in neuronal ensembles using spike-train data recorded from individual neurons. These causal interrelationships are modeled as transformations of spike-trains recorded from a set of neurons designated as the “inputs” into spike-trains recorded from another set of neurons designated as the “outputs.” The MIMO model is composed of a set of multiinput/single-output (MISO) modules, one for each output. Each module is the cascade of a MISO Volterra model and a threshold operator generating the output spikes. The Laguerre expansion approach is used to estimate the Volterra kernels of each MISO module from the respective input–output data using the least-squares method. The predictive performance of the model is evaluated with the use of the receiver operating characteristic (ROC) curve, from which the optimum threshold is also selected. The Mann–Whitney statistic is used to select the significant inputs for each output by examining the statistical significance of improvements in the predictive accuracy of the model when the respective inputs is included. Illustrative examples are presented for a simulated system and for an actual application using multiunit data recordings from the hippocampus of a behaving rat. PMID:18701382

  13. Towards Effective Elicitation of NIN-AND Tree Causal Models

    NASA Astrophysics Data System (ADS)

    Xiang, Yang; Li, Yu; Zhu, Zoe Jingyu

    To specify a Bayes net (BN), a conditional probability table (CPT), often of an effect conditioned on its n causes, needs assessed for each node. It generally has the complexity exponential on n. Noisy-OR reduces the complexity to linear, but can only represent reinforcing causal interactions. The non-impeding noisy-AND (NIN-AND) tree is the first causal model that explicitly expresses reinforcement, undermining, and their mixture. It has linear complexity, but requires elicitation of a tree topology for types of causal interactions. We study their topology space and develop two novel techniques for more effective elicitation.

  14. Dilemmas of the causality assessment tools in the diagnosis of adverse drug reactions.

    PubMed

    Khan, Lateef M; Al-Harthi, Sameer E; Osman, Abdel-Moneim M; Sattar, Mai A Alim A; Ali, Ahmed S

    2016-07-01

    Basic essence of Pharmacovigilance is prevention of ADRs and its precise diagnosis is crucially a primary step, which still remains a challenge among clinicians. This study is undertaken with the objective to scrutinize and offer a notion of commonly used as well as recently developed methods of causality assessment tools for the diagnosis of adverse drug reactions and discuss their pros and cons. Overall 49 studies were recognized for all assessment methods with five major decisive factors of causality evaluation, all the information regarding reasons allocating causality, the advantages and limitations of the appraisal methods were extracted and scrutinized. From epidemiological information a past prospect is designed and subsequent possibility merged this background information with a clue in the individual case to crop up with an approximation of causation. Expert judgment is typically based on the decisive factor on which algorithms are based, nevertheless in imprecise manner. The probabilistic methods use the similar principle; however connect probabilities to each measure. Such approaches are quite skeptical and liable to generate cloudy causation results. Causation is quite intricate to ascertain than correlation in Pharmacovigilance due to numerous inherent shortcomings in causality assessment tools. We suggest that there is a need to develop a high quality assessment tool which can meticulously establish suitable diagnostic criteria for ADRs with universal acceptance to improvise the fundamental aspect of drug safety and evade the impending ADRs with the motive to convert Pharmacovigilance into a state of art.

  15. Biological Monitoring of Inhaled Nanoparticles in Patients: An Appealing Approach To Study Causal Link between Human Respiratory Pathology and Exposure to Nanoparticles.

    PubMed

    Forest, Valérie; Vergnon, Jean-Michel; Pourchez, Jérémie

    2017-09-18

    Although necessary, in vitro and in vivo studies are not fully successful at predicting nanomaterials toxicity. We propose to associate such assays to the biological monitoring of nanoparticles in clinical samples to get more relevant data on the chemical and physical nature and dose of nanoparticles found in humans. The concept is to establish the load of nanoparticles in biological samples of patients. Then, by comparing samples from different patient groups, nanoparticles of interest could be identified and a potential link between a given nanoparticle type and toxicity could be suggested. It must be confirmed by investigating the biological effects induced by these nanoparticles using in vitro or in vivo models (mechanistic or dose-response studies). This translational approach from the bedside to the bench and vice versa could allow a better understanding of the nanoparticle effects and mechanisms of toxicity that can contribute, at least in part, to a disease.

  16. Causal Rasch models

    PubMed Central

    Stenner, A. Jackson; Fisher, William P.; Stone, Mark H.; Burdick, Donald S.

    2013-01-01

    Rasch's unidimensional models for measurement show how to connect object measures (e.g., reader abilities), measurement mechanisms (e.g., machine-generated cloze reading items), and observational outcomes (e.g., counts correct on reading instruments). Substantive theory shows what interventions or manipulations to the measurement mechanism can be traded off against a change to the object measure to hold the observed outcome constant. A Rasch model integrated with a substantive theory dictates the form and substance of permissible interventions. Rasch analysis, absent construct theory and an associated specification equation, is a black box in which understanding may be more illusory than not. Finally, the quantitative hypothesis can be tested by comparing theory-based trade-off relations with observed trade-off relations. Only quantitative variables (as measured) support such trade-offs. Note that to test the quantitative hypothesis requires more than manipulation of the algebraic equivalencies in the Rasch model or descriptively fitting data to the model. A causal Rasch model involves experimental intervention/manipulation on either reader ability or text complexity or a conjoint intervention on both simultaneously to yield a successful prediction of the resultant observed outcome (count correct). We conjecture that when this type of manipulation is introduced for individual reader text encounters and model predictions are consistent with observations, the quantitative hypothesis is sustained. PMID:23986726

  17. Generalized Causal Mediation Analysis

    PubMed Central

    Albert, Jeffrey M.; Nelson, Suchitra

    2010-01-01

    Summary The goal of mediation analysis is to assess direct and indirect effects of a treatment or exposure on an outcome. More generally, we may be interested in the context of a causal model as characterized by a directed acyclic graph (DAG), where mediation via a specific path from exposure to outcome may involve an arbitrary number of links (or ‘stages’). Methods for estimating mediation (or pathway) effects are available for a continuous outcome and a continuous mediator related via a linear model, while for a categorical outcome or categorical mediator, methods are usually limited to two-stage mediation. We present a method applicable to multiple stages of mediation and mixed variable types using generalized linear models. We define pathway effects using a potential outcomes framework and present a general formula that provides the effect of exposure through any specified pathway. Some pathway effects are nonidentifiable and their estimation requires an assumption regarding the correlation between counterfactuals. We provide a sensitivity analysis to assess of the impact of this assumption. Confidence intervals for pathway effect estimates are obtained via a bootstrap method. The method is applied to a cohort study of dental caries in very low birth weight adolescents. A simulation study demonstrates low bias of pathway effect estimators and close-to-nominal coverage rates of confidence intervals. We also find low sensitivity to the counterfactual correlation in most scenarios. PMID:21306353

  18. History, causality, and sexology.

    PubMed

    Money, John

    2003-08-01

    In 1896, Krafft-Ebing published Psychopathia Sexualis. Popularly defined as hereditary weakness or taintedness in the family pedigree, degeneracy was called upon as a causal explanation for perversions of the sexual instinct. Although Krafft-Ebing accepted Karl Ulrichs proposal that homosexuality could be innate and probably located in the brain, he paid little attention to neuropathological sexology. Alfred Binet challenged Krafft-Ebing's orthodoxy by explaining fetishism in terms of associative learning, to which Krafft-Ebing's response was that only those with a hereditary taint would be vulnerable. Thus did the venerable nature-nurture antithesis maintain its rhetoric, even to the present day. Krafft-Ebing died too soon to meet the Freudian challenge of endopsychic determinism, and too soon also to encounter the idea of a developmental multivariate outcome of what I have termed the lovemap. Like other brain maps, for example the languagemap, the lovemap requires an intact human brain in which to develop. The personalized content of the lovemap has access to the brain by way of the special senses.

  19. Space, time, and causality in the human brain.

    PubMed

    Woods, Adam J; Hamilton, Roy H; Kranjec, Alexander; Minhaus, Preet; Bikson, Marom; Yu, Jonathan; Chatterjee, Anjan

    2014-05-15

    The ability to perceive causality is a central human ability constructed from elemental spatial and temporal information present in the environment. Although the nature of causality has captivated philosophers and scientists since antiquity, the neural correlates of causality remain poorly understood. In the present study, we used functional magnetic resonance imaging (fMRI) to generate hypotheses for candidate brain regions related to component processes important for perceptual causality in the human brain: elemental space perception, elemental time perception, and decision-making (Experiment 1; n=16). We then used transcranial direct current stimulation (tDCS) to test neural hypotheses generated from the fMRI experiment (Experiment 2; n=16). In both experiments, participants judged causality in billiard-ball style launching events; a blue ball approaches and contacts a red ball. Spatial and temporal contributions to causal perception were assessed by parametrically varying the spatial linearity and the temporal delays of the movement of the balls. Experiment 1 demonstrated unique patterns of activation correlated with spatial, temporal, and decision-making components of causality perception. Using tDCS, we then tested hypotheses for the specific roles of the parietal and frontal cortices found in the fMRI experiment. Parietal stimulation only decreased participants' perception of causality based on spatial violations, while frontal stimulation made participants less likely to perceive causality based on violations of space and time. Converging results from fMRI and tDCS indicate that parietal cortices contribute to causal perception because of their specific role in processing spatial relations, while the frontal cortices contribute more generally, consistent with their role in decision-making.

  20. Space, Time, and Causality in the Human Brain

    PubMed Central

    Woods, Adam J.; Hamilton, Roy H.; Kranjec, Alexander; Minhaus, Preet; Bikson, Marom; Yu, Jonathan; Chatterjee, Anjan

    2014-01-01

    The ability to perceive causality is a central human ability constructed from elemental spatial and temporal information present in the environment. Although the nature of causality has captivated philosophers and scientists since antiquity, the neural correlates of causality remain poorly understood. In the present study, we used functional magnetic resonance imaging (fMRI) to generate hypotheses for candidate brain regions related to component processes important for perceptual causality in the human brain: elemental space perception, elemental time perception, and decision-making (Experiment 1; n=16). We then used transcranial direct current stimulation (tDCS) to test neural hypotheses generated from the fMRI experiment (Experiment 2; n=16). In both experiments, participants judged causality in billiard-ball style launching events; a blue ball approaches and contacts a red ball. Spatial and temporal contributions to causal perception were assessed by parametrically varying the spatial linearity and the temporal delays of the movement of the balls. Experiment 1 demonstrated unique patterns of activation correlated with spatial, temporal, and decision-making components of causality perception. Using tDCS, we then tested hypotheses for the specific roles of the parietal and frontal cortices found in the fMRI experiment. Parietal stimulation only decreased participants’ perception of causality based on spatial violations, while frontal stimulation made participants less likely to perceive causality based on violations of space and time. Converging results from fMRI and tDCS indicate that parietal cortices contribute to causal perception because of their specific role in processing spatial relations, while the frontal cortices contribute more generally, consistent with their role in decision-making. PMID:24561228

  1. Causality assessment methods in drug induced liver injury: strengths and weaknesses.

    PubMed

    García-Cortés, Miren; Stephens, Camilla; Lucena, M Isabel; Fernández-Castañer, Alejandra; Andrade, Raúl J

    2011-09-01

    Diagnosis of drug-induced liver injury (DILI) remains a challenge and eagerly awaits the development of reliable hepatotoxicity biomarkers. Several methods have been developed in order to facilitate hepatotoxicity causality assessments. These methods can be divided into three categories: (1) expert judgement, (2) probabilistic approaches, and (3) algorithms or scales. The last category is further divided into general and liver-specific scales. The Council for International Organizations of Medical Sciences (CIOMS) scale, also referred to as the Roussel Uclaf Causality Assessment Method (RUCAM), although cumbersome and difficult to apply by physicians not acquainted with DILI, is used by many expert hepatologists, researchers, and regulatory authorities to assess the probability of suspected causal agents. However, several limitations of this scale have been brought to light, indicating that a number of adjustments are needed. This review is a detailed timely criticism to alert the readers of the limitations and give insight into what would be needed to improve the scale. Instructions on how to approach DILI diagnosis in practice are provided, using CIOMS as an aid to emphasize the topics to be addressed when assessing DILI cases. Amendments of the CIOMS scale in the form of applying authoritative evidence-based criteria, a simplified scoring system and appropriate weighting given to individual parameters based on statistical evaluations with large databases will provide wider applicability in the clinical setting.

  2. Retrieving hydrological connectivity from empirical causality in karst systems

    NASA Astrophysics Data System (ADS)

    Delforge, Damien; Vanclooster, Marnik; Van Camp, Michel; Poulain, Amaël; Watlet, Arnaud; Hallet, Vincent; Kaufmann, Olivier; Francis, Olivier

    2017-04-01

    Because of their complexity, karst systems exhibit nonlinear dynamics. Moreover, if one attempts to model a karst, the hidden behavior complicates the choice of the most suitable model. Therefore, both intense investigation methods and nonlinear data analysis are needed to reveal the underlying hydrological connectivity as a prior for a consistent physically based modelling approach. Convergent Cross Mapping (CCM), a recent method, promises to identify causal relationships between time series belonging to the same dynamical systems. The method is based on phase space reconstruction and is suitable for nonlinear dynamics. As an empirical causation detection method, it could be used to highlight the hidden complexity of a karst system by revealing its inner hydrological and dynamical connectivity. Hence, if one can link causal relationships to physical processes, the method should show great potential to support physically based model structure selection. We present the results of numerical experiments using karst model blocks combined in different structures to generate time series from actual rainfall series. CCM is applied between the time series to investigate if the empirical causation detection is consistent with the hydrological connectivity suggested by the karst model.

  3. Principal stratification in causal inference.

    PubMed

    Frangakis, Constantine E; Rubin, Donald B

    2002-03-01

    Many scientific problems require that treatment comparisons be adjusted for posttreatment variables, but the estimands underlying standard methods are not causal effects. To address this deficiency, we propose a general framework for comparing treatments adjusting for posttreatment variables that yields principal effects based on principal stratification. Principal stratification with respect to a posttreatment variable is a cross-classification of subjects defined by the joint potential values of that posttreatment variable tinder each of the treatments being compared. Principal effects are causal effects within a principal stratum. The key property of principal strata is that they are not affected by treatment assignment and therefore can be used just as any pretreatment covariate. such as age category. As a result, the central property of our principal effects is that they are always causal effects and do not suffer from the complications of standard posttreatment-adjusted estimands. We discuss briefly that such principal causal effects are the link between three recent applications with adjustment for posttreatment variables: (i) treatment noncompliance, (ii) missing outcomes (dropout) following treatment noncompliance. and (iii) censoring by death. We then attack the problem of surrogate or biomarker endpoints, where we show, using principal causal effects, that all current definitions of surrogacy, even when perfectly true, do not generally have the desired interpretation as causal effects of treatment on outcome. We go on to forrmulate estimands based on principal stratification and principal causal effects and show their superiority.

  4. Causal inference and developmental psychology.

    PubMed

    Foster, E Michael

    2010-11-01

    Causal inference is of central importance to developmental psychology. Many key questions in the field revolve around improving the lives of children and their families. These include identifying risk factors that if manipulated in some way would foster child development. Such a task inherently involves causal inference: One wants to know whether the risk factor actually causes outcomes. Random assignment is not possible in many instances, and for that reason, psychologists must rely on observational studies. Such studies identify associations, and causal interpretation of such associations requires additional assumptions. Research in developmental psychology generally has relied on various forms of linear regression, but this methodology has limitations for causal inference. Fortunately, methodological developments in various fields are providing new tools for causal inference-tools that rely on more plausible assumptions. This article describes the limitations of regression for causal inference and describes how new tools might offer better causal inference. This discussion highlights the importance of properly identifying covariates to include (and exclude) from the analysis. This discussion considers the directed acyclic graph for use in accomplishing this task. With the proper covariates having been chosen, many of the available methods rely on the assumption of "ignorability." The article discusses the meaning of ignorability and considers alternatives to this assumption, such as instrumental variables estimation. Finally, the article considers the use of the tools discussed in the context of a specific research question, the effect of family structure on child development.

  5. Medical Student Volunteerism Addresses Patients' Social Needs: A Novel Approach to Patient-Centered Care.

    PubMed

    Onyekere, Chinwe; Ross, Sandra; Namba, Alexa; Ross, Justin C; Mann, Barry D

    2016-01-01

    Healthcare providers must be equipped to recognize and address patients' psychosocial needs to improve overall health outcomes. To give future healthcare providers the tools and training necessary to identify and address psychosocial issues, Lankenau Medical Center in partnership with the Philadelphia College of Osteopathic Medicine designed the Medical Student Advocate (MSA) program. The MSA program places volunteer second-year osteopathic medical students in care coordination teams at Lankenau Medical Associates, a primary care practice serving a diverse patient population in the Philadelphia, PA, region. As active members of the team, MSAs are referred high-risk patients who have resource needs such as food, employment, child care, and transportation. MSAs work collaboratively with patients and the multidisciplinary team to address patients' nonmedical needs. From August 2013 to August 2015, 31 osteopathic medical students volunteered for the MSA program and served 369 patients with 720 identified needs. Faculty and participating medical students report that the MSA program provided an enhanced understanding of the holistic nature of patient care and a comprehensive view of patient needs. The MSA program provides students with a unique educational opportunity that encompasses early exposure to patient interaction, social determinants of health, population health, and interdisciplinary collaboration. Students develop skills to help them build patient relationships, understand the psychosocial factors shaping health outcomes, and engage with other healthcare professionals. This work in the preclinical years provides students with the knowledge to help them perform more effectively in the changing healthcare environment.

  6. Some Reasons for a Need to Change the Approach to Trigonometry Instruction and a Proposal for Change.

    ERIC Educational Resources Information Center

    O'Mahony, Rosalie M.; Jackson, James L.

    Arguing that high attrition rates and low grades in trigonometry classes underscore the need for changes in the approach to trigonometry instruction, these papers suggest an instructional model and present a proposal for its adoption at the College of San Mateo (CSM). The first paper begins with the argument that students' lack of preparation for…

  7. Coherent Teaching and Need-Based Learning in Science: An Approach to Teach Engineering Students in Basic Physics Courses

    ERIC Educational Resources Information Center

    Kurki-Suonio, T.; Hakola, A.

    2007-01-01

    In the present paper, we propose an alternative, based on constructivism, to the conventional way of teaching basic physics courses at the university level. We call this approach "coherent teaching" and the underlying philosophy of teaching science and engineering "need-based learning". We have been applying this philosophy in…

  8. Observations of Social Competence of Children in Need of Special Support Based on Traditional Disability Categories versus a Functional Approach

    ERIC Educational Resources Information Center

    Lillvist, Anne

    2010-01-01

    Background: Traditional disability categories may reveal little of the functional characteristics and social competence of a child. Objective: To compare the social competence of typically developing children, children with established disabilities and undiagnosed children identified by a functional approach to be in need of special support.…

  9. Implementing a Public Health Approach to Addressing Mental Health Needs in a University Setting: Lessons and Challenges

    ERIC Educational Resources Information Center

    Parcover, Jason; Mays, Sally; McCarthy, Amy

    2015-01-01

    The mental health needs of college students are placing increasing demands on counseling center resources, and traditional outreach efforts may be outdated or incomplete. The public health model provides an approach for reaching more students, decreasing stigma, and addressing mental health concerns before they reach crisis levels. Implementing a…

  10. Coherent Teaching and Need-Based Learning in Science: An Approach to Teach Engineering Students in Basic Physics Courses

    ERIC Educational Resources Information Center

    Kurki-Suonio, T.; Hakola, A.

    2007-01-01

    In the present paper, we propose an alternative, based on constructivism, to the conventional way of teaching basic physics courses at the university level. We call this approach "coherent teaching" and the underlying philosophy of teaching science and engineering "need-based learning". We have been applying this philosophy in…

  11. Implementing a Public Health Approach to Addressing Mental Health Needs in a University Setting: Lessons and Challenges

    ERIC Educational Resources Information Center

    Parcover, Jason; Mays, Sally; McCarthy, Amy

    2015-01-01

    The mental health needs of college students are placing increasing demands on counseling center resources, and traditional outreach efforts may be outdated or incomplete. The public health model provides an approach for reaching more students, decreasing stigma, and addressing mental health concerns before they reach crisis levels. Implementing a…

  12. Needs assessment in health research projects: a new approach to project management in iran.

    PubMed

    Peykari, Niloofar; Owlia, Parviz; Malekafzali, Hossein; Ghanei, Mostafa; Babamahmoodi, Abdolreza; Djalalinia, Shirin

    2013-01-01

    The science and technology health plan has defined the outline of health research to the national vision of Iran by 2025. The aim of this study was to focus on the process of needs assessment of health research projects also health research priority setting in Iran. THE PROJECT MANAGEMENT LIFE CYCLE HAS FOUR PHASES: Initiation, Planning, Execution and Closure. Based on abovementioned points we conducted the study. Focusing on the needs assessment led to systematic implementation of needs assessment of health project in all of the medical sciences universities. Parallel with this achieved strategies health research priority setting was followed through specific process from empowerment to implementation. We should adopt with more systematic progressive methods of health project managements for both our national convenience as well as our international health research programs.

  13. Physical causality and brain theories.

    PubMed

    Yates, F E

    1980-05-01

    The history of deterministic theories in physics is reviewed, and four levels of determinism are found: 1) absolute, 2) asymptotic, 3) probabilistic, and 4) absolute indeterminism. Nagel's view that all causal laws are deterministic in the frame of the state descriptions to which they refer is acknowledged, but the inevitability of macroscopic measurement noise may hint that dynamical laws are innately noisy. Quantum mechanical effects are not the noise source. Symmetry and broken symmetry are introduced as physical concepts that can account both for lawfulness, and for the hierarchical nature of the universe. Physical ideas are chosen over those of formal systems with indirect self-reference as the basis of a global theory of brains. By exclusion it is concluded that only a statistical thermodynamics, combined with nonlinear mechanics, has the features needed for theorizing about brains in a physical sense. Quantum mechanics is judged not to be relevant. New statistical thermodynamic theories are briefly described, and their strengths and weaknesses noted. The question, "Why should neuroscience look to physics for its theories?" is raised and answered. Some concrete objectives for a program of theoretical research are stated.

  14. A causal dispositional account of fitness.

    PubMed

    Triviño, Vanessa; Nuño de la Rosa, Laura

    2016-09-01

    The notion of fitness is usually equated to reproductive success. However, this actualist approach presents some difficulties, mainly the explanatory circularity problem, which have lead philosophers of biology to offer alternative definitions in which fitness and reproductive success are distinguished. In this paper, we argue  that none of these alternatives is satisfactory and, inspired by Mumford and Anjum's dispositional theory of causation, we offer a definition of fitness as a causal dispositional property. We argue that, under this framework, the distinctiveness that biologists usually attribute to fitness-namely, the fact that fitness is something different from both the physical traits of an organism and the number of offspring it leaves-can be explained, and the main problems associated with the concept of fitness can be solved. Firstly, we introduce Mumford and Anjum's dispositional theory of causation and present our definition of fitness as a causal disposition. We explain in detail each of the elements involved in our definition, namely: the relationship between fitness and the functional dispositions that compose it, the emergent character of fitness, and the context-sensitivity of fitness. Finally, we explain how fitness and realized fitness, as well as expected and realized fitness are distinguished in our approach to fitness as a causal disposition.

  15. Causal evolution of wave packets

    NASA Astrophysics Data System (ADS)

    Eckstein, Michał; Miller, Tomasz

    2017-03-01

    Drawing from the optimal transport theory adapted to the relativistic setting we formulate the principle of a causal flow of probability and apply it in the wave-packet formalism. We demonstrate that whereas the Dirac Hamiltonian impels a causal evolution of probabilities, even in the presence of interactions, the relativistic-Schrödinger model is acausal. We quantify the causality breakdown in the latter model and argue that, in contrast to the popular viewpoint, it is not related to the localization properties of the states.

  16. Human causal discovery from observational data.

    PubMed Central

    Hashem, A. I.; Cooper, G. F.

    1996-01-01

    Utilizing Bayesian belief networks as a model of causality, we examined medical students' ability to discover causal relationships from observational data. Nine sets of patient cases were generated from relatively simple causal belief networks by stochastic simulation. Twenty participants examined the data sets and attempted to discover the underlying causal relationships. Performance was poor in general, except at discovering the absence of a causal relationship. This work supports the potential for combining human and computer methods for causal discovery. PMID:8947621

  17. Do we need sustainability as a new approach in human factors and ergonomics?

    PubMed

    Zink, Klaus J; Fischer, Klaus

    2013-01-01

    The International Ergonomics Association Technical Committee 'Human Factors and Sustainable Development' was established to contribute to a broad discourse about opportunities and risks resulting from current societal 'mega-trends' and their impacts on the interactions among humans and other elements of a system, e.g. in work systems. This paper focuses on the underlying key issues: how do the sustainability paradigm and human factors/ergonomics interplay and interact, and is sustainability necessary as a new approach for our discipline? Based on a discussion of the sustainability concept, some general principles for designing new and enhancing existent approaches of human factors and ergonomics regarding their orientation towards sustainability are proposed. The increasing profile of sustainability on the international stage presents new opportunities for human factors/ergonomics. Positioning of the sustainability paradigm within human factors/ergonomics is discussed. Approaches to incorporating sustainability in the design of work systems are considered.

  18. Applying Causal Discovery to the Output of Climate Models - What Can We Learn from the Causal Signatures?

    NASA Astrophysics Data System (ADS)

    Ebert-Uphoff, I.; Hammerling, D.; Samarasinghe, S.; Baker, A. H.

    2015-12-01

    The framework of causal discovery provides algorithms that seek to identify potential cause-effect relationships from observational data. The output of such algorithms is a graph structure that indicates the potential causal connections between the observed variables. Originally developed for applications in the social sciences and economics, causal discovery has been used with great success in bioinformatics and, most recently, in climate science, primarily to identify interaction patterns between compound climate variables and to track pathways of interactions between different locations around the globe. Here we apply causal discovery to the output data of climate models to learn so-called causal signatures from the data that indicate interactions between the different atmospheric variables. These causal signatures can act like fingerprints for the underlying dynamics and thus serve a variety of diagnostic purposes. We study the use of the causal signatures for three applications: 1) For climate model software verification we suggest to use causal signatures as a means of detecting statistical differences between model runs, thus identifying potential errors and supplementing the Community Earth System Model Ensemble Consistency Testing (CESM-ECT) tool recently developed at NCAR for CESM verification. 2) In the context of data compression of model runs, we will test how much the causal signatures of the model outputs changes after different compression algorithms have been applied. This may result in additional means to determine which type and amount of compression is acceptable. 3) This is the first study applying causal discovery simultaneously to a large number of different atmospheric variables, and in the process of studying the resulting interaction patterns for the two aforementioned applications, we expect to gain some new insights into their relationships from this approach. We will present first results obtained for Applications 1 and 2 above.

  19. Causal Network Inference Via Group Sparse Regularization

    PubMed Central

    Bolstad, Andrew; Van Veen, Barry D.; Nowak, Robert

    2011-01-01

    This paper addresses the problem of inferring sparse causal networks modeled by multivariate autoregressive (MAR) processes. Conditions are derived under which the Group Lasso (gLasso) procedure consistently estimates sparse network structure. The key condition involves a “false connection score” ψ. In particular, we show that consistent recovery is possible even when the number of observations of the network is far less than the number of parameters describing the network, provided that ψ < 1. The false connection score is also demonstrated to be a useful metric of recovery in nonasymptotic regimes. The conditions suggest a modified gLasso procedure which tends to improve the false connection score and reduce the chances of reversing the direction of causal influence. Computational experiments and a real network based electrocorticogram (ECoG) simulation study demonstrate the effectiveness of the approach. PMID:21918591

  20. Universal antifungal therapy is not needed in persistent febrile neutropenia: a tailored diagnostic and therapeutic approach

    PubMed Central

    Aguilar-Guisado, Manuela; Martín-Peña, Almudena; Espigado, Ildefonso; Ruiz Pérez de Pipaon, Maite; Falantes, José; de la Cruz, Fátima; Cisneros, José M.

    2012-01-01

    Background Giving antifungal therapy exclusively to selected patients with persistent febrile neutropenia may avoid over-treatment without increasing mortality. The aim of this study was to validate an innovative diagnostic and therapeutic approach based on assessing patients’ risk profile and clinical criteria in order to select those patients requiring antifungal therapy. The efficacy of this approach was compared to that of universal empirical antifungal therapy. Design and Methods This was a prospective study which included all consecutive adult hematology patients with neutropenia and fever refractory to 5 days of empirical antibacterial therapy admitted to a teaching hospital in Spain over a 2-year period. A diagnostic and therapeutic approach based on clinical criteria and risk profile was applied in order to select patients for antifungal therapy. The sensitivity, specificity and negative predictive value of this approach and also the overall success rate, according to the same criteria of efficacy described in classical clinical trials, were analyzed. Results Eighty-five episodes were included, 35 of them (41.2%) in patients at high risk of invasive fungal infections. Antifungal therapy was not indicated in 33 episodes (38.8%). The overall incidence of proven and probable invasive fungal infections was 14.1%, all of which occurred in patients who had received empirical antifungal therapy. The 30-day crude mortality rate was 15.3% and the invasive fungal infection-related mortality rate was 2.8% (2/72). The overall success rate following the diagnostic and therapeutic approach was 36.5% compared with 33.9% and 33.7% obtained in the trial by Walsh et al. The sensitivity, specificity and negative predictive value of the study approach were 100%, 52.4% and 100%, respectively. Conclusions Based on the high negative predictive value of this diagnostic and therapeutic approach in persistent febrile neutropenia patients with hematologic malignancies or patients

  1. Universal antifungal therapy is not needed in persistent febrile neutropenia: a tailored diagnostic and therapeutic approach.

    PubMed

    Aguilar-Guisado, Manuela; Martín-Peña, Almudena; Espigado, Ildefonso; Ruiz Pérez de Pipaon, Maite; Falantes, José; de la Cruz, Fátima; Cisneros, José M

    2012-03-01

    Giving antifungal therapy exclusively to selected patients with persistent febrile neutropenia may avoid over-treatment without increasing mortality. The aim of this study was to validate an innovative diagnostic and therapeutic approach based on assessing patients' risk profile and clinical criteria in order to select those patients requiring antifungal therapy. The efficacy of this approach was compared to that of universal empirical antifungal therapy. This was a prospective study which included all consecutive adult hematology patients with neutropenia and fever refractory to 5 days of empirical antibacterial therapy admitted to a teaching hospital in Spain over a 2-year period. A diagnostic and therapeutic approach based on clinical criteria and risk profile was applied in order to select patients for antifungal therapy. The sensitivity, specificity and negative predictive value of this approach and also the overall success rate, according to the same criteria of efficacy described in classical clinical trials, were analyzed. Eighty-five episodes were included, 35 of them (41.2%) in patients at high risk of invasive fungal infections. Antifungal therapy was not indicated in 33 episodes (38.8%). The overall incidence of proven and probable invasive fungal infections was 14.1%, all of which occurred in patients who had received empirical antifungal therapy. The 30-day crude mortality rate was 15.3% and the invasive fungal infection-related mortality rate was 2.8% (2/72). The overall success rate following the diagnostic and therapeutic approach was 36.5% compared with 33.9% and 33.7% obtained in the trial by Walsh et al. The sensitivity, specificity and negative predictive value of the study approach were 100%, 52.4% and 100%, respectively. Based on the high negative predictive value of this diagnostic and therapeutic approach in persistent febrile neutropenia patients with hematologic malignancies or patients who have received a hematopoietic stem cell

  2. Unintended outcomes of health care delivery and the need for a national risk management approach.

    PubMed

    O'Donnell, C

    1999-01-01

    Unlike the situation in occupational health and safety, there is no nationally coordinated approach to risk management to prevent unintended outcomes of health care provision and improve health care quality. There is a related absence of linkages between quality assurance process, other programs aimed at patient injury prevention and professional indemnity insurance systems. This article discusses the Australian health policy direction and argues for a coordinated national health risk management approach developed through contract requirements which include duty of care and information provision, nationally approved standards and codes, professional liability requirements, and supporting health education, research and information technology development.

  3. Time-varying linear and nonlinear parametric model for Granger causality analysis.

    PubMed

    Li, Yang; Wei, Hua-Liang; Billings, Steve A; Liao, Xiao-Feng

    2012-04-01

    Statistical measures such as coherence, mutual information, or correlation are usually applied to evaluate the interactions between two or more signals. However, these methods cannot distinguish directions of flow between two signals. The capability to detect causalities is highly desirable for understanding the cooperative nature of complex systems. The main objective of this work is to present a linear and nonlinear time-varying parametric modeling and identification approach that can be used to detect Granger causality, which may change with time and may not be detected by traditional methods. A numerical example, in which the exact causal influences relationships, is presented to illustrate the performance of the method for time-varying Granger causality detection. The approach is applied to EEG signals to track and detect hidden potential causalities. One advantage of the proposed model, compared with traditional Granger causality, is that the results are easier to interpret and yield additional insights into the transient directed dynamical Granger causality interactions.

  4. Recursive partitioning for heterogeneous causal effects.

    PubMed

    Athey, Susan; Imbens, Guido

    2016-07-05

    In this paper we propose methods for estimating heterogeneity in causal effects in experimental and observational studies and for conducting hypothesis tests about the magnitude of differences in treatment effects across subsets of the population. We provide a data-driven approach to partition the data into subpopulations that differ in the magnitude of their treatment effects. The approach enables the construction of valid confidence intervals for treatment effects, even with many covariates relative to the sample size, and without "sparsity" assumptions. We propose an "honest" approach to estimation, whereby one sample is used to construct the partition and another to estimate treatment effects for each subpopulation. Our approach builds on regression tree methods, modified to optimize for goodness of fit in treatment effects and to account for honest estimation. Our model selection criterion anticipates that bias will be eliminated by honest estimation and also accounts for the effect of making additional splits on the variance of treatment effect estimates within each subpopulation. We address the challenge that the "ground truth" for a causal effect is not observed for any individual unit, so that standard approaches to cross-validation must be modified. Through a simulation study, we show that for our preferred method honest estimation results in nominal coverage for 90% confidence intervals, whereas coverage ranges between 74% and 84% for nonhonest approaches. Honest estimation requires estimating the model with a smaller sample size; the cost in terms of mean squared error of treatment effects for our preferred method ranges between 7-22%.

  5. Serving the Needs of Challenged Students at a Private Shanghai School: An Action Research Approach

    ERIC Educational Resources Information Center

    Liu, Jerry

    2013-01-01

    This action research started in year 2009 at LIU Shanghai, a private school for children with autism spectrum disorder, to serve the needs of challenged students. The purpose of this qualitative study was to identify the strengths and challenges of the program, plus solicit recommendations from the parents and teachers for making improvements. The…

  6. "Trees and Things That Live in Trees": Three Children with Special Needs Experience the Project Approach

    ERIC Educational Resources Information Center

    Griebling, Susan; Elgas, Peg; Konerman, Rachel

    2015-01-01

    The authors report on research conducted during a project investigation undertaken with preschool children, ages 3-5. The report focuses on three children with special needs and the positive outcomes for each child as they engaged in the project Trees and Things That Live in Trees. Two of the children were diagnosed with developmental delays, and…

  7. "But, We Don't Have a Library": Exploring Approaches to Addressing Branch Campuses' Library Needs

    ERIC Educational Resources Information Center

    Hostetler, Kirsten; DeSilva, Michele

    2016-01-01

    Librarians at Central Oregon Community College's Barber Library explored how to best serve the needs of three satellite campuses across a large geographic region. While initially intending to start an embedded librarianship program, a pair of surveys showed the relationships and awareness necessary for the foundation of such a program were…

  8. An Empirical Study on Business English Teaching and Development in China--A Needs Analysis Approach

    ERIC Educational Resources Information Center

    Guiyu, Dai; Yang, Liu

    2016-01-01

    This paper first reviews the developmental history and status quo of Business English Program in China. Then based on the theory of needs analysis, it researches on 226 questionnaires from Business English Program students from Guangdong University of Foreign Studies to investigate the problems encountered and current situation of Business English…

  9. Dual Differentiation: An Approach for Meeting the Curricular Needs of Gifted Students with Learning Disabilities.

    ERIC Educational Resources Information Center

    Baum, Susan M.; Cooper, Carolyn R.; Neu, Terry W.

    2001-01-01

    This article discusses the dual characteristics of gifted learning disabled students and suggests a unique curriculum that integrates both through talent development. Developed through Project HIGH HOPES, this dually differentiated curriculum offers strategies for addressing students' learning problems while fulfilling their need for sophisticated…

  10. Hospital-Based Educators as Internal Consultants: The Need for Effective Approaches to Evaluation.

    ERIC Educational Resources Information Center

    Piantanida, Maria

    A shift in the role function of the hospital-based educator has increased his/her involvement in organizational decision making, including internal consulting. One aspect of the educator's practice now is evaluation. A broader, more flexible concept of evaluation is needed which is applicable to decision making about human resource/organizational…

  11. "But, We Don't Have a Library": Exploring Approaches to Addressing Branch Campuses' Library Needs

    ERIC Educational Resources Information Center

    Hostetler, Kirsten; DeSilva, Michele

    2016-01-01

    Librarians at Central Oregon Community College's Barber Library explored how to best serve the needs of three satellite campuses across a large geographic region. While initially intending to start an embedded librarianship program, a pair of surveys showed the relationships and awareness necessary for the foundation of such a program were…

  12. Who Needs Contingency Approaches and Guidelines in Order to Adapt Vague Management Ideas?

    ERIC Educational Resources Information Center

    Ortenblad, Anders

    2010-01-01

    The purpose of this conceptual paper is to question the assumption that the general idea of the learning organisation needs to be adapted to the specific context before it can be put into practical use. It is suggested that there are lots of ways to use management ideas, other than implementing them in the practice of organisations. It is further…

  13. A Boosting Approach to eContent Development for Learners with Special Needs

    ERIC Educational Resources Information Center

    Gabrielli, Silvia; Mirabella, Valeria; Kimani, Stephen; Catarci, Tiziana

    2006-01-01

    Of late there has been a growing interest and effort toward meeting the requirements of persons with special needs. However, most of the accessibility standards and guidelines that have been proposed have been developed by adopting a domain independent and often "technical" perspective. Such proposals are therefore often not sufficient…

  14. Creativity and the Transformation of Higher Education: The Need for a Black Mountain College Approach

    ERIC Educational Resources Information Center

    Emanuel, Richard C.; Challons-Lipton, Siu

    2013-01-01

    The need for increased creativity in education is currently being proposed in much innovative thinking on higher education as universities are forced to recreate themselves. There are four conditions facing higher education worldwide: alignment, motivation, connection, and direction. Higher education is characterized by a hierarchy of subjects and…

  15. Serving the Needs of Challenged Students at a Private Shanghai School: An Action Research Approach

    ERIC Educational Resources Information Center

    Liu, Jerry

    2013-01-01

    This action research started in year 2009 at LIU Shanghai, a private school for children with autism spectrum disorder, to serve the needs of challenged students. The purpose of this qualitative study was to identify the strengths and challenges of the program, plus solicit recommendations from the parents and teachers for making improvements. The…

  16. Addressing tuberculosis patients' medical and socio-economic needs: a comprehensive programmatic approach.

    PubMed

    Contreras, Carmen C; Millones, Ana K; Santa Cruz, Janeth; Aguilar, Margot; Clendenes, Martin; Toranzo, Miguel; Llaro, Karim; Lecca, Leonid; Becerra, Mercedes C; Yuen, Courtney M

    2017-04-01

    For a cohort of patients with tuberculosis in Carabayllo, Peru, we describe the prevalence of medical comorbidities and socio-economic needs, the efforts required by a comprehensive support programme ('TB Cero') to address them and the success of this programme in linking patients to care. Patients diagnosed with tuberculosis in Carabayllo underwent evaluations for HIV, diabetes, mental health and unmet basic needs. For patients initiating treatment during 14 September, 2015-15 May, 2016, we abstracted data from evaluation forms and a support request system. We calculated the prevalence of medical comorbidities and the need for socio-economic support at the time of tuberculosis diagnosis, as well as the proportion of patients successfully linked to care or support. Of 192 patients, 83 (43%) had at least one medical comorbidity other than tuberculosis. These included eight (4%) patients with HIV, 12 (6%) with diabetes and 62 (32%) deemed at risk for a mental health condition. Of patients who required follow-up for a comorbidity, 100% initiated antiretroviral therapy, 71% attended endocrinology consultations and 66% attended psychology consultations. Of 126 (65%) patients who completed the socio-economic evaluation, 58 (46%) reported already receiving food baskets from the municipality, and 79 (63%) were given additional support, most commonly food vouchers and assistance in accessing health care. Carabayllo tuberculosis patients face many challenges in addition to tuberculosis. A collaborative, comprehensive treatment support programme can achieve high rates of linkage to care for these needs. © 2017 John Wiley & Sons Ltd.

  17. Pediatric Health Fairs: One Approach to the Health Needs of Appalachian Children.

    ERIC Educational Resources Information Center

    Huff, Cynthia O.

    An assessment of the health education needs of children in Tennessee resulted in the initiation of a pediatric health fair by nursing students at Carson-Newman College. The fair was presented to approximately 180 second-grade students in a rural elementary school in East Tennessee. The following activities took place at the exhibits: (1) at the…

  18. A Needs-Based Approach to the Development of a Diagnostic College English Speaking Test

    ERIC Educational Resources Information Center

    Zhao, Zhongbao

    2014-01-01

    This paper investigated the current situation of oral English teaching, learning, and assessment at the tertiary level in China through needs analysis and explored the implications for the development of a diagnostic speaking test. Through random sampling, the researcher administered both a student questionnaire and a teacher questionnaire to over…

  19. A Boosting Approach to eContent Development for Learners with Special Needs

    ERIC Educational Resources Information Center

    Gabrielli, Silvia; Mirabella, Valeria; Kimani, Stephen; Catarci, Tiziana

    2006-01-01

    Of late there has been a growing interest and effort toward meeting the requirements of persons with special needs. However, most of the accessibility standards and guidelines that have been proposed have been developed by adopting a domain independent and often "technical" perspective. Such proposals are therefore often not sufficient…

  20. Exploring Reading Comprehension Needs of Iranian EAP Students of Health Information Management (HIM): A Triangulated Approach

    ERIC Educational Resources Information Center

    Atai, Mahmood Reza; Nazari, Ogholgol

    2011-01-01

    Discipline-based English for Academic Purposes (EAP) reading programs in Iran are designed to fill the gap between the students' general English reading competence and their ability to read authentic discipline-specific texts. This study attempted to assess target and present reading comprehension needs of EAP students of Health Information…