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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 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.

  7. 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.

  8. 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.

  9. 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

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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)

  16. 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

  17. 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.

  18. 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.

  19. 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.

  20. 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…

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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…

  6. 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

  7. 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)

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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

  13. 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.

  14. 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.

  15. 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)

  16. 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.

  17. 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.

  18. 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…

  19. 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.

  20. 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

  1. 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…

  2. 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.

  3. 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.

  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. 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

  6. 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

  7. 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.

  8. 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

  9. 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.

  10. 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.

  11. 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)

  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. 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.

  14. 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.

  15. 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

  16. 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...

  17. 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…

  18. 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…

  19. 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

  20. 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.

  1. 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.

  2. 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.…

  3. 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.

  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. 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.

  6. 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.

  7. Causal Analysis After Haavelmo

    PubMed Central

    Heckman, James; Pinto, Rodrigo

    2014-01-01

    Haavelmo's seminal 1943 and 1944 papers are the first rigorous treatment of causality. In them, he distinguished the definition of causal parameters from their identification. He showed that causal parameters are defined using hypothetical models that assign variation to some of the inputs determining outcomes while holding all other inputs fixed. He thus formalized and made operational Marshall's (1890) ceteris paribus analysis. We embed Haavelmo's framework into the recursive framework of Directed Acyclic Graphs (DAGs) used in one influential recent approach to causality (Pearl, 2000) and in the related literature on Bayesian nets (Lauritzen, 1996). We compare the simplicity of an analysis of causality based on Haavelmo's methodology with the complex and nonintuitive approach used in the causal literature of DAGs—the “do-calculus” of Pearl (2009). We discuss the severe limitations of DAGs and in particular of the do-calculus of Pearl in securing identification of economic models. We extend our framework to consider models for simultaneous causality, a central contribution of Haavelmo. In general cases, DAGs cannot be used to analyze models for simultaneous causality, but Haavelmo's approach naturally generalizes to cover them. PMID:25729123

  8. 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.

  9. 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

  10. 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.

  11. 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.

  12. 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.

  13. 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

  14. 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

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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

  20. 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.

  1. 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…

  2. 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

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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

  8. 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'.

  9. 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.

  10. 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.

  11. [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.

  12. 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.

  13. 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

  14. 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

  15. 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…

  16. 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

  17. 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)

  18. 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

  19. 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…

  20. 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…

  1. 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.

  2. 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.…

  3. 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…

  4. 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…

  5. 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

  6. 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)

  7. 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

  8. 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

  9. 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.

  10. 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.

  11. 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…

  12. 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…

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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

  20. 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.

  1. 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.

  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. 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.

  5. 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

  6. 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.

  7. 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

  8. 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.

  9. 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

  10. 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.

  11. 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

  12. 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…

  13. 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

  14. 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.

  15. 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…

  16. 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…

  17. 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…

  18. 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.

  19. 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.

  20. 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…

  1. 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.

  2. 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,…

  3. [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.

  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. 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,…

  6. 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.

  7. 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.

  8. 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

  9. 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

  10. 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.

  11. 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.

  12. 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…

  13. 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.

  14. 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.

  15. 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

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  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 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…

  2. 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).

  3. 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…

  4. 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…

  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. 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.

  8. 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

  9. 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.

  10. 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.

  11. 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…

  12. Predicting cell cycle regulated genes by causal interactions.

    PubMed

    Emmert-Streib, Frank; Dehmer, Matthias

    2009-08-18

    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.

  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. 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.

  16. 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.

  17. 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.

  18. 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

  19. 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.

  20. 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

  1. 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.

  2. 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…

  3. 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

  4. 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.

  5. 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

  6. 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.

  7. 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

  8. 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.

  9. 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

  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. 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.

  12. 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

  13. 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

  14. 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.

  15. 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…

  16. 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

  17. 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

  18. 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.

  19. 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.

  20. 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

  1. 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…

  2. 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…

  3. 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.

  4. 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

  5. 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.

  6. 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.

  7. 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.…

  8. 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.

  9. 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…

  10. 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…

  11. 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…

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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…

  18. 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…

  19. 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.

  20. 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.

  1. 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)

  2. 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.

  3. 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

  4. 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.

  5. 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

  6. 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…

  7. 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.

  8. 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

  9. Investigating the multi-causal and complex nature of the accident causal influence of construction project features.

    PubMed

    Manu, Patrick A; Ankrah, Nii A; Proverbs, David G; Suresh, Subashini

    2012-09-01

    Construction project features (CPFs) are organisational, physical and operational attributes that characterise construction projects. Although previous studies have examined the accident causal influence of CPFs, the multi-causal attribute of this causal phenomenon still remain elusive and thus requires further investigation. Aiming to shed light on this facet of the accident causal phenomenon of CPFs, this study examines relevant literature and crystallises the attained insight of the multi-causal attribute by a graphical model which is subsequently operationalised by a derived mathematical risk expression that offers a systematic approach for evaluating the potential of CPFs to cause harm and consequently their health and safety (H&S) risk implications. The graphical model and the risk expression put forth by the study thus advance current understanding of the accident causal phenomenon of CPFs and they present an opportunity for project participants to manage the H&S risk associated with CPFs from the early stages of project procurement.

  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. 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.

  13. 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

  14. 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

  15. 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.

  16. 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.

  17. 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

  18. 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

  19. 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.

  20. 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.

  1. 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…

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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…

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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...

  13. 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

  14. 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

  15. 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

  16. 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.

  17. 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.

  18. 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.

  19. 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

  20. 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

  1. 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…

  2. 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…

  3. 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…

  4. 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…

  5. 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…

  6. 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,…

  7. 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…

  8. 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.

  9. 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…

  10. 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

  11. 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.

  12. 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.

  13. 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…

  14. 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…

  15. 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.

  16. 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…

  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. 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…

  19. 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.

  20. 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…

  1. 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.…

  2. 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…

  3. 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…

  4. 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…

  5. 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…

  6. 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…

  7. 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…

  8. 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

  9. 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

  10. 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…

  11. 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…

  12. 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…

  13. A Mixed-Methods, Multiprofessional Approach to Needs Assessment for Designing Education

    ERIC Educational Resources Information Center

    Moore, Heidi K.; McKeithen, Tom M.; Holthusen, Amy E.

    2011-01-01

    Like most hospital units, neonatal intensive care units (NICUs) are multidisciplinary and team-based. As a result, providing optimal nutritional care to premature infants involves using the knowledge and skills of several types of professionals. Using traditional needs assessment methodologies to effectively understand the educational needs…

  14. 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…

  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. 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…

  17. 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…

  18. 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…

  19. "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…

  20. "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…

  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. Exploring the Ecological Approach Used by RTLBs in Interventions for Students with Learning and Behaviour Needs

    ERIC Educational Resources Information Center

    Sebestian, Sandiyao

    2013-01-01

    The ecological approach, based on the RTLB Toolkit that guides RTLBs in New Zealand, is one of the seven principles used for interventions for students with learning and behaviour concerns. As a result of a paradigm shift moving from a functional limitations perspective to a more inclusive/ecological perspective in 1999, RTLBs have been trained…

  3. A Theory-Mindedness Approach: Eliminating the Need for a Gap in Baccalaureate Education

    ERIC Educational Resources Information Center

    Miller, Shari E.; Skinner, Jeffrey F.

    2013-01-01

    Social work educators have been grappling for years with the continually challenging notion of the "integration of theory and practice" and the converse concept, the "gap between theory and practice." This article posits the utility of a theory-mindedness approach to learning and practice as an alternative conceptualization…

  4. Towards an Agile Approach to Adapting Dynamic Collaboration Support to Student Needs

    ERIC Educational Resources Information Center

    Adamson, David; Dyke, Gregory; Jang, Hyeju; Rosé, Carolyn Penstein

    2014-01-01

    This paper investigates the use of conversational agents to scaffold on-line collaborative learning discussions through an approach called Academically Productive Talk (APT). In contrast to past work on dynamic support for collaborative learning, where agents were used to elevate conceptual depth by leading students through directed lines of…

  5. Training and Developing an Age Diverse Workforce in SMEs: The Need for a Strategic Approach

    ERIC Educational Resources Information Center

    Beaver, Graham; Hutchings, Kate

    2005-01-01

    Purpose: The purpose of this paper is to examine the importance of strategic human resource development (HRD) in small and medium-sized enterprises (SMEs) with specific reference to key issues around training, development and education as well as an emerging issue of significance, age diversity management. Design/Methodology/Approach: The approach…

  6. Personal paper: medicine in the 1990s needs a team approach.

    PubMed Central

    English, T.

    1997-01-01

    Health care increasingly emphasises the team approach in which doctors, nurses, and other health workers adapt and develop new skills. Before changes of this kind are widely accepted, however, there must be clarity about the training, status, authority, working relationships, career structure, and remuneration of those who undertake responsibilities well beyond their traditional roles. PMID:9066483

  7. 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.

  8. Quantitative Risk reduction estimation Tool For Control Systems, Suggested Approach and Research Needs

    SciTech Connect

    Miles McQueen; Wayne Boyer; Mark Flynn; Sam Alessi

    2006-03-01

    For the past year we have applied a variety of risk assessment technologies to evaluate the risk to critical infrastructure from cyber attacks on control systems. More recently, we identified the need for a stand alone control system risk reduction estimation tool to provide owners and operators of control systems with a more useable, reliable, and credible method for managing the risks from cyber attack. Risk is defined as the probability of a successful attack times the value of the resulting loss, typically measured in lives and dollars. Qualitative and ad hoc techniques for measuring risk do not provide sufficient support for cost benefit analyses associated with cyber security mitigation actions. To address the need for better quantitative risk reduction models we surveyed previous quantitative risk assessment research; evaluated currently available tools; developed new quantitative techniques [17] [18]; implemented a prototype analysis tool to demonstrate how such a tool might be used; used the prototype to test a variety of underlying risk calculational engines (e.g. attack tree, attack graph); and identified technical and research needs. We concluded that significant gaps still exist and difficult research problems remain for quantitatively assessing the risk to control system components and networks, but that a useable quantitative risk reduction estimation tool is not beyond reach.

  9. Adverse drug reactions in neonates and infants: a population-tailored approach is needed

    PubMed Central

    Allegaert, Karel; van den Anker, Johannes N

    2015-01-01

    Drug therapy is a powerful tool to improve outcome, but there is an urgent need to improve pharmacotherapy in neonates through tailored prevention and management of adverse drug reactions (ADRs). At present, infants commonly receive off-label drugs, at dosages extrapolated from those in children or adults. Besides the lack of labelling, inappropriate formulations, (poly)pharmacy, immature organ function and multiple illnesses further raise the risk for ADRs in neonates and infants. Pharmacovigilance to improve the prevention and management of ADRs needs to be tailored to neonates and infants. We illustrate this using prevention strategies for drug prescription and administration errors (e.g. formulation, bedside manipulation, access), detection through laboratory signalling or clinical outlier data (e.g. reference laboratory values, overall high morbidity), assessment through algorithm scoring (e.g. Naranjo or population specific), as well as understanding of the developmental toxicology (e.g. covariates, developmental pharmacology) to avoid re-occurrence and for development of guidelines. Such tailored strategies need collaborative initiatives to combine the knowledge and expertise of different disciplines, but hold promise to become a very effective tool to improve pharmacotherapy and reduce ADRs in infants. PMID:24862557

  10. Enhancing periodontal health through regenerative approaches: a commentary on the need for patient-reported outcomes.

    PubMed

    Inglehart, Marita R

    2015-02-01

    Starting in the 1970s, social scientists have discussed the importance of assessing subjective indicators of well-being and quality of life. Medical researchers followed this line of reasoning since the 1990s, emphasizing the significance of understanding how disease and its treatment affect patients' quality of life. Since the start of the 21(st) century, oral health-related quality of life (OHRQoL) received increasingly more attention. While research concerning the effects of periodontal disease and its surgical and non-surgical treatment on patients' lives has been considered in numerous studies, research including patient-reported outcomes when assessing how periodontal health can be enhanced through regenerative approaches is largely missing. This commentary proposes to consider 1) OHRQoL and 2) patients' treatment satisfaction as patient-reported outcomes in conjunction with objectively measured patient-centered factors, and discusses the value of such an approach.

  11. Use of comparative genomics approaches to characterize interspecies differences in response to environmental chemicals: Challenges, opportunities, and research needs

    SciTech Connect

    Burgess-Herbert, Sarah L.; Euling, Susan Y.

    2013-09-15

    A critical challenge for environmental chemical risk assessment is the characterization and reduction of uncertainties introduced when extrapolating inferences from one species to another. The purpose of this article is to explore the challenges, opportunities, and research needs surrounding the issue of how genomics data and computational and systems level approaches can be applied to inform differences in response to environmental chemical exposure across species. We propose that the data, tools, and evolutionary framework of comparative genomics be adapted to inform interspecies differences in chemical mechanisms of action. We compare and contrast existing approaches, from disciplines as varied as evolutionary biology, systems biology, mathematics, and computer science, that can be used, modified, and combined in new ways to discover and characterize interspecies differences in chemical mechanism of action which, in turn, can be explored for application to risk assessment. We consider how genetic, protein, pathway, and network information can be interrogated from an evolutionary biology perspective to effectively characterize variations in biological processes of toxicological relevance among organisms. We conclude that comparative genomics approaches show promise for characterizing interspecies differences in mechanisms of action, and further, for improving our understanding of the uncertainties inherent in extrapolating inferences across species in both ecological and human health risk assessment. To achieve long-term relevance and consistent use in environmental chemical risk assessment, improved bioinformatics tools, computational methods robust to data gaps, and quantitative approaches for conducting extrapolations across species are critically needed. Specific areas ripe for research to address these needs are recommended.

  12. 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.

  13. Telemedicine licensure in the United States: the need for a cooperative regional approach.

    PubMed

    Cwiek, Mark A; Rafiq, Azhar; Qamar, Aamna; Tobey, Charles; Merrell, Ronald C

    2007-04-01

    The extraordinary successes and refinement of modern telemedicine applications in recent years have been diminished somewhat by the anachronistic licensure laws of the 50 state jurisdictions that limit the practice of medicine to specific state geographic boundaries. This approach is deficient when applied to telemedicine because, with the advent of the Internet and modern technological advances, differences in space and time are rendered nearly meaningless. It is recommended in this paper that the practice of telemedicine be handled differently than the practice of face-to-face medicine, as related to licensure. Although it may be argued persuasively that a national licensure model for telemedicine should be advanced, the political and constitutional hurdles may be too great to overcome. It is therefore recommended that a voluntary, regional geographic approach be instituted by jurisdictions already demonstrating a commonality of interests, such as through the Southern Governors' Association or the Western Governors' Association. The benefits to be derived from this approach would include improving access to healthcare and medical specialists, enhancing the quality and timeliness of care, cutting medical costs by moving information instead of people, securing patients' access to medical records and information, and facilitating commercial export of American telemedicine services.

  14. HIV prevention, structural change and social values: the need for an explicit normative approach

    PubMed Central

    Parkhurst, Justin O

    2012-01-01

    Background The fact that HIV prevention often deals with politicised sexual and drug taking behaviour is well known, but structural HIV prevention interventions in particular can involve alteration of social arrangements over which there may be further contested values at stake. As such, normative frameworks are required to inform HIV prevention decisions and avoid conflicts between social goals. Methods This paper provides a conceptual review and discussion of the normative issues surrounding structural HIV prevention strategies. It applies political and ethical concepts to explore the contested nature of HIV planning and suggests conceptual frameworks to inform future structural HIV responses. Results HIV prevention is an activity that cannot be pursued without making value judgements; it is inherently political. Appeals to health outcomes alone are insufficient when intervention strategies have broader social impacts, or when incidence reduction can be achieved at the expense of other social values such as freedom, equality, or economic growth. This is illustrated by the widespread unacceptability of forced isolation which may be efficacious in preventing spread of infectious agents, but conflicts with other social values. Conclusions While no universal value system exists, the capability approach provides one potential framework to help overcome seeming contradictions or value trade-offs in structural HIV prevention approaches. However, even within the capability approach, valuations must still be made. Making normative values explicit in decision making processes is required to ensure transparency, accountability, and representativeness of the public interest, while ensuring structural HIV prevention efforts align with broader social development goals as well. PMID:22713355

  15. 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.

  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. 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.

  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. 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.

  20. Training UAP to care for special needs students in the classroom: one district's approach.

    PubMed

    Raible, Cathy L

    2012-07-01

    As more children with complex medical needs are entering the school system, it may be appropriate for nurses to delegate some of the routine tasks to paraprofessional staff (Resha, 2010). With proper training, some non-complex daily treatments and many emergency procedures can be performed safely and effectively by UAP. NASN has several position statements directly related to this topic. Before a nurse decides to enlist unlicensed personnel for assistance, it is important to ensure that delegation of treatment is allowed under their school's policies and procedures as well as their state Nurse Practice Acts.

  1. 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

  2. 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.

  3. Ambiguity in the Presentation of Decellularized Tissue Composition: The Need for Standardized Approaches.

    PubMed

    Bruyneel, Arne A N; Carr, Carolyn A

    2016-12-07

    Decellularization offers great potential to the field of tissue engineering, as this method gives rise to scaffold material with the native organ architecture by removing all cellular material and leaving much of the extracellular matrix (ECM) intact. However, many parameters may affect decellularization efficacy and ECM retention and, therefore, decellularization protocols need to be optimized for specific needs. This requires robust methods for comparison of decellularized tissue composition. Various representation methods are used in literature to express tissue composition (DNA, glycosaminoglycans, collagen, other ECM proteins, and growth factors). Here, we present and compare the various methods used and demonstrate that normalization to either dry or wet decellularized weight might be misleading and may overestimate true component retention. Moreover, the magnitude of the confounding effect is likely to be decellularization treatment dependent. As a result, we propose alternative comparison strategies: normalization to whole organ or to a unit of whole initial organ weight. We believe proper assessment of decellularized tissue composition is paramount for the successful comparison of different decellularization protocols and clinical translation.

  4. An approach to vehicle design: In-depth audit to understand the needs of older drivers.

    PubMed

    Karali, Sukru; Mansfield, Neil J; Gyi, Diane E

    2017-01-01

    The population of older people continues to increase around the world, and this trend is expected to continue; the population of older drivers is increasing accordingly. January 2012 figures from the DVLA in the UK stated that there were more than 15 million drivers aged over 60; more than 1 million drivers were aged over 80. There is a need for specific research tools to understand and capture how all users interact with features in the vehicle cabin e.g. controls and tasks, including the specific needs of the increasingly older driving population. This paper describes an in-depth audit that was conducted to understand how design of the vehicle cabin impacts on comfort, posture, usability, health and wellbeing in older drivers. The sample involved 47 drivers (38% female, 62% male). The age distribution was: 50-64 (n = 12), 65-79 (n = 20), and those 80 and over (n = 15). The methodology included tools to capture user experience in the vehicle cabin and functional performance tests relevant to specific driving tasks. It is shown that drivers' physical capabilities reduce with age and that there are associated difficulties in setting up an optimal driving position such that some controls cannot be operated as intended, and many adapt their driving cabins. The cabin set-up process consistently began with setting up the seat and finished with operation of the seat belt.

  5. Cortical hierarchies perform Bayesian causal inference in multisensory perception.

    PubMed

    Rohe, Tim; Noppeney, Uta

    2015-02-01

    To form a veridical percept of the environment, the brain needs to integrate sensory signals from a common source but segregate those from independent sources. Thus, perception inherently relies on solving the "causal inference problem." Behaviorally, humans solve this problem optimally as predicted by Bayesian Causal Inference; yet, the underlying neural mechanisms are unexplored. Combining psychophysics, Bayesian modeling, functional magnetic resonance imaging (fMRI), and multivariate decoding in an audiovisual spatial localization task, we demonstrate that Bayesian Causal Inference is performed by a hierarchy of multisensory processes in the human brain. At the bottom of the hierarchy, in auditory and visual areas, location is represented on the basis that the two signals are generated by independent sources (= segregation). At the next stage, in posterior intraparietal sulcus, location is estimated under the assumption that the two signals are from a common source (= forced fusion). Only at the top of the hierarchy, in anterior intraparietal sulcus, the uncertainty about the causal structure of the world is taken into account and sensory signals are combined as predicted by Bayesian Causal Inference. Characterizing the computational operations of signal interactions reveals the hierarchical nature of multisensory perception in human neocortex. It unravels how the brain accomplishes Bayesian Causal Inference, a statistical computation fundamental for perception and cognition. Our results demonstrate how the brain combines information in the face of uncertainty about the underlying causal structure of the world.

  6. Why We Need Evidence-Based, Community-Wide Approaches for Prevention of Teen Pregnancy.

    PubMed

    Barfield, Wanda D; Warner, Lee; Kappeler, Evelyn

    2017-03-01

    Teen pregnancy and childbearing have declined over the past two decades to historic lows. The most recent declines have occurred during a time of coordinated national efforts focused on teen pregnancy. This article highlights a federal partnership to reduce teen pregnancy through the implementation of innovative, evidence-based approaches in affected communities, with a focus on reaching African-American and Latino/Hispanic youth. This initiative has the potential to transform the design and implementation of future teen pregnancy prevention efforts and provide a model that can be replicated in communities across the nation.

  7. Dhat syndrome: Evolution of concept, current understanding, and need of an integrated approach

    PubMed Central

    Kar, Sujita Kumar; Sarkar, Siddharth

    2015-01-01

    Dhat syndrome has often been construed as a culture-bound sexual neurosis of the Indian subcontinent. Symptoms similar to that of Dhat syndrome has been described in other cultures across different time periods. The present paper looks at the evolution of the concept of Dhat syndrome in India. The review also takes an overview of the current understanding of this syndrome in terms of nosological status as a distinct entity and its “culture-bound” status. The narrative finally attempts to discuss the integrated approach for the treatment of this disorder. PMID:26538854

  8. Discounting and Augmentation in Causal Conditional Reasoning: Causal Models or Shallow Encoding?

    PubMed Central

    Hall, Simon; Ali, Nilufa; Chater, Nick

    2016-01-01

    Recent research comparing mental models theory and causal Bayes nets for their ability to account for discounting and augmentation inferences in causal conditional reasoning had some limitations. One of the experiments used an ordinal scale and multiple items and analysed the data by subjects and items. This procedure can create a variety of problems that can be resolved by using an appropriate cumulative link function mixed models approach in which items are treated as random effects. Experiment 1 replicated this earlier experiment and analysed the results using appropriate data analytic techniques. Although successfully replicating earlier research, the pattern of results could be explained by a much simpler “shallow encoding” hypothesis. Experiment 2 introduced a manipulation to critically test this hypothesis. The results favoured the causal Bayes nets predictions and not shallow encoding and were not consistent with mental models theory. Experiment 1 provided qualified support for the causal Bayes net approach using appropriate statistics because it also replicated the failure to observe one of the predicted main effects. Experiment 2 discounted one plausible explanation for this failure. While within the limited goals that were set for these experiments they were successful, more research is required to account for the pattern of findings using this paradigm. PMID:28030583

  9. 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%.

  10. Multispecialty approach: the need for heart failure disease management for refining cardiac resynchronization therapy.

    PubMed

    Tang, W H Wilson; Boehmer, John; Gras, Daniel

    2012-08-01

    Cardiac resynchronization therapy (CRT) has been proven in clinical trials to be a very effective therapy in appropriate patients. However, although the literature has primarily focused on appropriate implanting techniques and inclusion criteria for CRT devices by electrophysiologists, most patients who receive CRT are managed by their primary care providers with the help of general cardiologists and/or heart failure (HF) specialists. As CRT has been more broadly applied over the past decade, the fragmentation and specialization of care in the current health care system have created challenges in optimizing this otherwise invasive but potentially beneficial intervention in the complex HF patient. Furthermore, cost considerations as well as appropriate follow-up care continue to challenge the optimal application of these devices, particularly when evidence to support multidisciplinary approaches is lacking. The challenge begins with identification of appropriate candidates for CRT, which is an evolving concept due to data emerging from new studies with a wide range of inclusion and exclusion criteria coupled with increasing oversight from providers or even logistical hurdles from patients. Postimplant management practices and procedures are still evolving. The important and so-far unresolved concept of the "nonresponder" to CRT remains largely subjective and is variably defined in the literature, and the lack of understanding of the underlying mechanisms of "nonresponse" continues to challenge long-term management of CRT, even given the recent developments in advanced sensor technologies. Therefore, further investigations into HF disease management with a multispecialty approach, pre-CRT and post-CRT, are warranted.

  11. Structural approaches to health promotion: what do we need to know about policy and environmental change?

    PubMed

    Lieberman, Lisa; Golden, Shelley D; Earp, Jo Anne L

    2013-10-01

    Although the public health literature has increasingly called on practitioners to implement changes to social, environmental, and political structures as a means of improving population health, recent research suggests that articles evaluating organization, community, or policy changes are more limited than those focused on programs with individuals or their social networks. Even when these approaches appear promising, we do not fully understand whether they will benefit all population groups or can be successful in the absence of accompanying individually oriented programs. The role of this broad category of approaches, including both policy and environmental changes, in decreasing health disparities is also unclear, often benefiting some communities more than others. Finally, the political nature of policy and environmental change, including the impact on personal autonomy, raises questions about the appropriate role for public health professionals in advancing specific policies and practices that alter the conditions in which people live. This article addresses these issues and ends with a series of questions about the effectiveness and ethical implementation of what we have termed "structural initiatives."

  12. Temporal Information of Directed Causal Connectivity in Multi-Trial ERP Data using Partial Granger Causality.

    PubMed

    Youssofzadeh, Vahab; Prasad, Girijesh; Naeem, Muhammad; Wong-Lin, KongFatt

    2016-01-01

    Partial Granger causality (PGC) has been applied to analyse causal functional neural connectivity after effectively mitigating confounding influences caused by endogenous latent variables and exogenous environmental inputs. However, it is not known how this connectivity obtained from PGC evolves over time. Furthermore, PGC has yet to be tested on realistic nonlinear neural circuit models and multi-trial event-related potentials (ERPs) data. In this work, we first applied a time-domain PGC technique to evaluate simulated neural circuit models, and demonstrated that the PGC measure is more accurate and robust in detecting connectivity patterns as compared to conditional Granger causality and partial directed coherence, especially when the circuit is intrinsically nonlinear. Moreover, the connectivity in PGC settles faster into a stable and correct configuration over time. After method verification, we applied PGC to reveal the causal connections of ERP trials of a mismatch negativity auditory oddball paradigm. The PGC analysis revealed a significant bilateral but asymmetrical localised activity in the temporal lobe close to the auditory cortex, and causal influences in the frontal, parietal and cingulate cortical areas, consistent with previous studies. Interestingly, the time to reach a stable connectivity configuration (~250–300 ms) coincides with the deviation of ensemble ERPs of oddball from standard tones. Finally, using a sliding time window, we showed higher resolution dynamics of causal connectivity within an ERP trial. In summary, time-domain PGC is promising in deciphering directed functional connectivity in nonlinear and ERP trials accurately, and at a sufficiently early stage. This data-driven approach can reduce computational time, and determine the key architecture for neural circuit modeling.

  13. Prevention of the spread of infection--the need for a family-centred approach to hygiene promotion.

    PubMed

    Bloomfield, S; Exner, M; Fara, G M; Scott, E A

    2008-05-29

    Infectious diseases circulating in the home and community are a continuing and significant burden on the health and prosperity of the European community. They could, however, be significantly reduced by better standards of hygiene. Across Europe, public health is currently structured such that the separate aspects of hygiene in different settings (food hygiene, personal hygiene, handwashing, pandemic flu preparedness, patient empowerment etc.) are dealt with by separate agencies. If efforts to promote hygiene at community level are to be successful in changing behaviour, we need a concerted family-centred approach to ensure that a basic understanding of infectious disease agents and their mechanisms of spread, together with an understanding of a risk-based approach to hygiene, are promoted as part of the school curriculum and as part of public health campaigns. Alongside this, we also need unambiguous communication with the public on issues such as the hygiene hypothesis and environmental issues.

  14. The team approach to home-based primary care: restructuring care to meet individual, program, and system needs.

    PubMed

    Reckrey, Jennifer M; Soriano, Theresa A; Hernandez, Cameron R; DeCherrie, Linda V; Chavez, Silvia; Zhang, Meng; Ornstein, Katherine

    2015-02-01

    Team-based models of care are an important way to meet the complex medical and psychosocial needs of the homebound. As part of a quality improvement project to address individual, program, and system needs, a portion of a large, physician-led academic home-based primary care practice was restructured into a team-based model. With support from an office-based nurse practitioner, a dedicated social worker, and a dedicated administrative assistant, physicians were able to care for a larger number of patients. Hospitalizations, readmissions, and patient satisfaction remained the same while physician panel size increased and physician satisfaction improved. The Team Approach is an innovative way to improve interdisciplinary, team-based care through practice restructuring and serves as an example of how other practices can approach the complex task of caring for the homebound.

  15. The Team Approach to Home-Based Primary Care: Restructuring Care to Meet Patient, Program, and System Needs

    PubMed Central

    Reckrey, Jennifer M.; Soriano, Theresa A.; Hernandez, Cameron R.; DeCherrie, Linda V.; Chavez, Silvia; Zhang, Meng; Ornstein, Katherine

    2016-01-01

    Team-based models of care are an important way to meet the complex medical and psychosocial needs of the homebound. As part of a quality improvement project to address patient, program, and system needs, we restructured a portion of our large, physician-led academic home-based primary care practice into a team-based model. With support from an office-based nurse practitioner, a dedicated social worker, and a dedicated administrative assistant, physicians were able to care for a larger number of patients. Hospitalizations, readmissions, and patient satisfaction remained the same while physician panel size increased and physician satisfaction improved. Our Team Approach is an innovative way to improve interdisciplinary, team-based care though practice restructuring and serves as an example of how other practices can approach the complex task of caring for the homebound. PMID:25645568

  16. Nonlinear parametric model for Granger causality of time series

    NASA Astrophysics Data System (ADS)

    Marinazzo, Daniele; Pellicoro, Mario; Stramaglia, Sebastiano

    2006-06-01

    The notion of Granger causality between two time series examines if the prediction of one series could be improved by incorporating information of the other. In particular, if the prediction error of the first time series is reduced by including measurements from the second time series, then the second time series is said to have a causal influence on the first one. We propose a radial basis function approach to nonlinear Granger causality. The proposed model is not constrained to be additive in variables from the two time series and can approximate any function of these variables, still being suitable to evaluate causality. Usefulness of this measure of causality is shown in two applications. In the first application, a physiological one, we consider time series of heart rate and blood pressure in congestive heart failure patients and patients affected by sepsis: we find that sepsis patients, unlike congestive heart failure patients, show symmetric causal relationships between the two time series. In the second application, we consider the feedback loop in a model of excitatory and inhibitory neurons: we find that in this system causality measures the combined influence of couplings and membrane time constants.

  17. [The care needs of women infected with the human papilloma virus: a comprehensive approach].

    PubMed

    Cestari, Maria Elisa Wotzasek; Merighi, Miriam Aparecida Barbosa; Garanhani, Mara Lúcia; Cardeli, Alexandrina Aparecida Maciel; de Jesus, Maria Cristina Pinto; Lopes, Dolores Ferreira de Melo

    2012-10-01

    This study is founded on the phenomenology of Martin Heidegger, with the objective to understand the care needs of women infected with the human papilloma virus. Participants were fourteen women who had been diagnosed with this infection. The guiding questions were: What is it like to have this diagnosis? Tell me your experience, from when you received your diagnosis until today. What has your health care been like? The questions revealed the theme - seeking care as solitude - which showed the importance of the support of family and friends. The presence of the infection as the cause of marital conflicts and separation was another highlighted aspect. The statements showed that there was a sense of resignation after an unsuccessful attempt to find accurate and clear information in order to make assertive decisions. Health interventions for infected women must overcome the traditional models of care, including interventions for health promotion and prevention, with trained professionals who are sensitive to the subjective dimension.

  18. Management of Hospital Infection Control in Iran: A Need for Implementation of Multidisciplinary Approach

    PubMed Central

    Mamishi, Setareh; Pourakbari, Babak; Teymuri, Mostafa; Babamahmoodi, Abdolreza; Mahmoudi, Shima

    2014-01-01

    Nosocomial, or hospital-acquired, infections are considered the most common complications affecting hospitalized patients. According to results obtained from studies conducted in the Children Medical Center Hospital, a teaching children's hospital and a tertiary care referral unit in Tehran, Iran, improvements in infection control practices in our hospital seem necessary. The aim of this study was to identify risk management and review potential hospital hazards that may pose a threat to the health as well as safety and welfare of patients in an Iranian referral hospital. Barriers to compliance and poor design of facilities, impractical guidelines and policies, lack of a framework for risk management, failure to apply behavioral-change theory, and insufficient obligation and enforcement by infection control personnel highlight the need of management systems in infection control in our hospital. In addition, surveillance and early reporting of infections, evaluation of risk-based interventions, and production of evidence-based guidelines in our country are recommended. PMID:25379367

  19. Care needs of pregnant women with a private health insurance: a comprehensive social phenomenology approach.

    PubMed

    Merighi, Miriam Aparecida Barbosa; Rodrigues, Renata Tavares Franco; Domingos, Selisvane Ribeiro da Fonseca

    2007-01-01

    This study aimed to understand the meanings women who possess health plans hold regarding pregnancy and get to know their care needs in this phase of the vital cycle. It was based on the qualitative research of phenomenological inspiration. The discourses analysis was based on the sociologist and fenomenologist Alfred Schutz's thought. Having health plans and being attended in private institutions were defined as inclusion criteria. The following categories emerged from the discourses: having new responsibilities; experiencing a special situation; experiencing insecurity, anxiety and expectations; feeling limited; trusting the health professional. It was found, through the analysis of categories, that the experience of the pregnant women who participated in the study is similar to those who do not possess health plans. However, in the category "trusting the health professional" it was possible to perceive the importance of possessing health plan, which allows the intersubjectivity between the woman and the health professional.

  20. Risk analysis for U.S. offshore wind farms: the need for an integrated approach.

    PubMed

    Staid, Andrea; Guikema, Seth D

    2015-04-01

    Wind power is becoming an increasingly important part of the global energy portfolio, and there is growing interest in developing offshore wind farms in the United States to better utilize this resource. Wind farms have certain environmental benefits, notably near-zero emissions of greenhouse gases, particulates, and other contaminants of concern. However, there are significant challenges ahead in achieving large-scale integration of wind power in the United States, particularly offshore wind. Environmental impacts from wind farms are a concern, and these are subject to a number of on-going studies focused on risks to the environment. However, once a wind farm is built, the farm itself will face a number of risks from a variety of hazards, and managing these risks is critical to the ultimate achievement of long-term reductions in pollutant emissions from clean energy sources such as wind. No integrated framework currently exists for assessing risks to offshore wind farms in the United States, which poses a challenge for wind farm risk management. In this "Perspective", we provide an overview of the risks faced by an offshore wind farm, argue that an integrated framework is needed, and give a preliminary starting point for such a framework to illustrate what it might look like. This is not a final framework; substantial work remains. Our intention here is to highlight the research need in this area in the hope of spurring additional research about the risks to wind farms to complement the substantial amount of on-going research on the risks from wind farms.

  1. Global warming and environmental contaminants in aquatic organisms: the need of the etho-toxicology approach.

    PubMed

    Manciocco, Arianna; Calamandrei, Gemma; Alleva, Enrico

    2014-04-01

    Environmental contaminants are associated with a wide spectrum of pathological effects. Temperature increase affects ambient distribution and toxicity of these chemicals in the water environment, representing a potentially emerging problem for aquatic species with short-, medium- and long-term repercussions on human health through the food chain. We assessed peer-reviewed literature, including primary studies, review articles and organizational reports available. We focused on studies concerning toxicity of environmental pollutants within a global warming scenario. Existing knowledge on the effects that the increase of water temperature in a contaminated situation has on physiological mechanisms of aquatic organisms is presented. Altogether we consider the potential consequences for the human beings due to fish and shellfish consumption. Finally, we propose an etho-toxicological approach to study the effects of toxicants in conditions of thermal increase, using aquatic organisms as experimental models under laboratory controlled conditions.

  2. People for sale: the need for a multidisciplinary approach towards human trafficking.

    PubMed

    Van Impe, K

    2000-01-01

    The article addresses the question of how to develop appropriate measures to tackle trafficking in women, based on the findings of a study of trafficking between the Philippines and Belgium. It argues that there is no easy or unidimensional solution to human trafficking, since it is influenced by a complex set of factors, often working in combination with one another. It concludes that control measures alone cannot stop the flow of trafficking in women and that a legal approach which relies solely on one type of legislation would be too narrow. An effective strategy must combine and balance punitive measures with protection of human rights, stricter border control and the removal of the root causes of irregular movements. Measures must be agreed and coordinated between origin, transit and receiving countries.

  3. The need for an interdisciplinary approach in forensic sciences: perspectives from a peculiar case of mummification.

    PubMed

    Ventura, Francesco; Portunato, Federica; Pizzorno, Enrico; Mazzone, Silvana; Verde, Alfredo; Rocca, Gabriele

    2013-05-01

    The finding of a mummified body raises many problems, also because of the limits of the medico-legal investigations in case of mummification. Psychological autopsy and behavioral analysis have demonstrated a significant impact in case of equivocal death. The mummified corpse of a woman was found sealed in a wardrobe during the death investigation of a 36-year-old man, later discovered to be the woman's son. The woman's corpse was well preserved and no external injuries were found. Autopsy could not ascertain the cause of death. The state of the premises and the writings on the walls offered an opportunity to investigate the man's psychological profile and to better understand how the events might have taken place. The role of an accurate investigative analysis of the crime scene is a cornerstone of forensic pathology and the case presented underlies the importance of an interdisciplinary approach in forensic sciences.

  4. Short bowel syndrome in adults: the need for an interdisciplinary approach and coordinated care.

    PubMed

    Matarese, Laura E; Jeppesen, Palle B; O'Keefe, Stephen J D

    2014-05-01

    Short bowel syndrome (SBS) is a heterogeneous disorder with broad variation in disease severity arising from different types of intestinal resection. The spectrum of malabsorption ranges from intestinal insufficiency to intestinal failure. Individualized patient strategies involving modifications of dietary macro- and micronutrients, fluid, and pharmacologic options are required to maximize health and quality-of-life outcomes and to minimize complications and SBS-associated mortality. Intestinal rehabilitation (IR) is an established but evolving approach to improving patient outcomes by decreasing long-term dependency on parenteral support (PS) for nutrition and fluid requirements. Specialized IR programs employ team-based interdisciplinary approaches to coordinate individualized patient care and treatment management through centralized facilities. Such facilities are often specialized intestinal care centers (ICCs) established at large medical centers. A multifaceted IR program offers the comprehensive interrelated services required by patients with SBS-associated intestinal failure throughout the course of disease. Components of interdisciplinary IR programs should include medical services offering diagnostics and monitoring, pharmacologic management, and symptom and complication control; nutrition services, including dietary modifications and interventions; and supportive psychosocial and educational services. A model of care centered on the IR concept means that long-term patient management, including decisions on long-term PS, is overseen by a member of the specialized care center. Rational, seamless, and timely communication among the patient's network of home-based and ICC healthcare providers is crucial to the success of any IR program. This paradigm shift to specialized IR programs will likely result in improvements across the patient care continuum.

  5. Setting AIDS priorities: the need for a closer alliance of public health and clinical approaches toward the control of AIDS.

    PubMed Central

    Henry, K

    1988-01-01

    The approach to the acquired immune deficiency syndrome (AIDS) taken by public health departments and clinicians varies. Public health programs often neglect the human side of AIDS while clinicians often overlook public health issues. Current research on AIDS has failed to address many fundamental questions including: the biology of the human immunodeficiency virus (HIV) in semen; whether present antiretroviral therapy has any effect on sexual infectivity; and whether adequate counseling was given to persons in HIV discordant partner studies. These unanswered basic questions highlight how research efforts framed from clinical, basic science, or public health viewpoints may have too narrow a focus. Three suggestions are made: 1) additional studies about the biology of HIV in the genital tract need to be conducted; 2) clinical trials studying drug therapy of HIV infection need to assess effect on HIV in the genital tract; 3) clinicians involved in studies and care of HIV infection need to implement educational strategies minimizing transmission of HIV from their patients. More interaction between public health and clinical approaches toward AIDS is needed. PMID:3407822

  6. Recovery of imperiled species under the Endangered Species Act: The need for a new approach

    USGS Publications Warehouse

    Scott, J.M.; Goble, D.D.; Wiens, J.A.; Wilcove, D.S.; Bean, M.; Male, T.

    2005-01-01

    The recovery (delisting) of a threatened or endangered species is often accompanied by the expectation that conservation management of the species will no longer be necessary. However, the magnitude and pace of human impacts on the environment make it unlikely that substantial progress will be made in delisting many species unless the definition of "recovery" includes some form of active management. Preventing delisted species from again being at risk of extinction may require continuing, species-specific management actions. We characterize such species as "conservation-reliant", and suggest that viewing "recovery" as a continuum of states rather than as a simple "recovered/not recovered" dichotomy may enhance our ability to manage such species within the framework of the Endangered Species Act. With ongoing loss of habitat, disruption of natural disturbance regimes, and the increasing impacts of non-native invasive species, it is probable that the number of conservation-reliant species will increase. We propose the development of "recovery management agreements", with legally and biologically defensible contracts that would provide for continu-ing conservation management following delisting. The use of such formalized agreements will facilitate shared management responsibilities between federal wildlife agencies and other federal agencies, and with state, local, and tribal governments, as well as with private entities that have demonstrated the capability to meet the needs of conservation-reliant species. ?? The Ecological Society of America.

  7. Medication reconciliation and therapy management in dialysis-dependent patients: need for a systematic approach.

    PubMed

    Pai, Amy Barton; Cardone, Katie E; Manley, Harold J; St Peter, Wendy L; Shaffer, Rachel; Somers, Michael; Mehrotra, Rajnish

    2013-11-01

    Patients with ESRD undergoing dialysis have highly complex medication regimens and disproportionately higher total cost of care compared with the general Medicare population. As shown by several studies, dialysis-dependent patients are at especially high risk for medication-related problems. Providing medication reconciliation and therapy management services is critically important to avoid costs associated with medication-related problems, such as adverse drug events and hospitalizations in the ESRD population. The Medicare Modernization Act of 2003 included an unfunded mandate stipulating that medication therapy management be offered to high-risk patients enrolled in Medicare Part D. Medication management services are distinct from the dispensing of medications and involve a complete medication review for all disease states. The dialysis facility is a logical coordination center for medication management services, like medication therapy management, and it is likely the first health care facility that a patient will present to after a care transition. A dedicated and adequately trained clinician, such as a pharmacist, is needed to provide consistent, high-quality medication management services. Medication reconciliation and medication management services that could consistently and systematically identify and resolve medication-related problems would be likely to improve ESRD patient outcomes and reduce total cost of care. Herein, this work provides a review of available evidence and recommendations for optimal delivery of medication management services to ESRD patients in a dialysis facility-centered model.

  8. A vaccine manufacturer's approach to address medical needs related to seasonal and pandemic influenza viruses.

    PubMed

    Baras, Benoit; Bouveret, Nancy; Devaster, Jeanne-Marie; Fries, Louis; Gillard, Paul; Sänger, Roland; Hanon, Emmanuel

    2008-11-01

    Vaccination is considered to be one of the most effective tools to decrease morbidity as well as mortality caused by influenza viruses. For the prevention of seasonal influenza, Fluarix and FluLaval have been marketed since 1987 and 1992, respectively. Both vaccines have consistently been shown to meet or exceed the regulatory criteria for immunogenicity against the three strains H1N1, H3N2 and B, have a good safety profile, and are recommended for vaccinating children and adults of all ages. For the prevention of pandemic influenza, GlaxoSmithKline (GSK) has obtained licensure of a pre-pandemic vaccine, Prepandrix. This split-virus H5N1 adjuvanted with AS03, a proprietary oil-in-water emulsion-based adjuvant system, has demonstrated broad immunity against drifted H5N1 strains and has been shown to be effective in preventing mortality and viral shedding in animal studies. The influenza vaccine portfolio of GSK addresses specific medical needs related to seasonal or pandemic influenza viruses, which remain an important public health threat worldwide.

  9. Primary trauma care experience of army reserve combat medics: is a new approach needed?

    PubMed

    Ben-Abraham, R; Paret, G; Kluger, Y; Shemer, J; Stein, M

    1999-01-01

    Combat medics play a significant role in any fighting unit. In recent years, during times of peace and low-intensity military conflicts, as well as in operations other than war, reserve combat medics have been challenged to treat major casualties in the field. Although this work requires important manual skills, the medics perform basic treatment maneuvers that are not necessarily for saving of lives. A sample survey of reserve combat medics revealed that most (70%) were engaged in medical care for trauma victims during their regular and reserve service. Many (32.5%) were involved in incidents with multiple casualties. These incidents included seriously injured victims, with 39.2% of the medics being involved with air evacuation and 44.4% with fatalities. Not all medics are exposed to major trauma, but for those who are, the numbers of patients per medic is not large. Therefore, the need to educate the medics in cognitive, and more importantly, in manual skills, is obvious. Suggestions for the means to do so are provided.

  10. Clothing damage analysis in alleged sexual assaults--the need for a systematic approach.

    PubMed

    Boland, C A; McDermott, S D; Ryan, J

    2007-04-11

    Clothing damage analysis is an integral part of the examinations carried out in sexual assault type cases. This analysis can be used to corroborate different versions of events and is at its most powerful in elucidating false allegation cases and consent cases. The purpose of this study was to determine to what extent people with varying levels of forensic awareness, experience and training could correctly carry out damage analysis. Two participant groups were asked to take part in this study. Group A ('forensic group') comprised participants at a forensic science conference, and Group B ('student group') comprised students undertaking a degree course in Forensic Science. Each group was given a practical workshop consisting of a lecture outlining common fabric types and general features observed in different damage types. Each participant was subsequently shown 25 pieces of 'damage' and asked to identify both the type of fabric construction (knit or weave) and the type of damage (cut, tear, rip, wear and tear). The ability to identify fabric construction and damage types varied within the two groups studied and across the groups. The forensic group performed better both in fabric and damage assessment than the student group. This paper suggests a systematic approach to clothing damage analysis to maximise the benefits that can be obtained from this area of forensic science and to minimise the subjectivity within the field.

  11. Assessing needs and resources for the home visiting system in Alabama: a mixed methods approach.

    PubMed

    Wingate, Martha S; Fifolt, Matthew; Preskitt, Julie; Mulvihill, Beverly; Pass, Mary Ann; Wallace, Lauren; Sims, Dianne; McKim, Susan

    2014-07-01

    The purpose of this article is to describe the initial assessment for the development of a home visiting (HV) system in a state with no existing system. We outline a mixed methods process where the quantitative component was used to identify the communities that possess "at-risk" profiles, and the qualitative component explored the resources and gaps in existing HV services. We employed a mixed methods approach, using six categories of indicators from quantitative secondary data sources to identify "at-risk" profiles for Alabama's 67 counties. A weighted score for each indicator was calculated and counties were ranked. Surveys and focus groups were conducted to further define resources and gaps of existing HV programs. The composite indicator scores identified 13 counties as having the highest level of risk. Five of these 13 communities had no HV home visitation services. Areas of focus for future HV system development include trust, communication, availability, cost, and timeliness. In this assessment related to the Alabama HV system, we used quantitative data to apply criteria to the indicators being measured and qualitative data to supplement the quantitative findings. We examined resources, gaps, program quality, and capacity of the existing HV programs in order to assist in the future development of the HV system and early childhood system. The methods presented in this paper have potential applications beyond HV programs and systems, including broader examinations of complex systems for service provision to the maternal and child health populations.

  12. Biodiesel exhaust: the need for a systematic approach to health effects research.

    PubMed

    Larcombe, Alexander N; Kicic, Anthony; Mullins, Benjamin J; Knothe, Gerhard

    2015-10-01

    Biodiesel is a generic term for fuel that can be made from virtually any plant or animal oil via transesterification of triglycerides with an alcohol (and usually a catalyst). Biodiesel has received considerable scientific attention in recent years, as it is a renewable resource that is directly able to replace mineral diesel in many engines. Additionally, some countries have mandated a minimum biodiesel content in all diesel fuel sold on environmental grounds. When combusted, biodiesel produces exhaust emissions containing particulate matter, adsorbed chemicals and a range of gases. In many cases, absolute amounts of these pollutants are lower in biodiesel exhaust compared with mineral diesel exhaust, leading to speculation that biodiesel exhaust may be less harmful to health. Additionally, engine performance studies show that the concentrations of these pollutants vary significantly depending on the renewable oil used to make the biodiesel and the ratio of biodiesel to mineral diesel in the fuel mix. Given the strategic and legislative push towards the use of biodiesel in many countries, a concerning possibility is that certain biodiesels may produce exhaust emissions that are more harmful to health than others. This variation suggests that a comprehensive, systematic and comparative approach to assessing the potential for a range of different biodiesel exhausts to affect health is urgently required. Such an assessment could inform biodiesel production priorities, drive research and development into new exhaust treatment technologies, and ultimately minimize the health impacts of biodiesel exhaust exposure.

  13. The emergence of personality in animals: the need for a developmental approach.

    PubMed

    Trillmich, Fritz; Hudson, Robyn

    2011-09-01

    Interest has been growing among behavioral biologists in individual differences in animal behavior of the kind that can be considered to reflect differences in personality. Once considered the exclusive domain of human psychology, biologists have found evidence for personality across a wide range of species, while behavioral ecologist and theoretical biologists recognize the likely evolutionary origins and contribution to fitness of such. However, until recently most work has concentrated on ultimate questions of fitness and thus on adult animals, with little attention given to proximate, developmental origins. This is now changing, as approaches to studying animal personality broaden and methodologies are developed enabling this to be studied across periods of near continuous and often rapid ontogenetic change. Debate continues, however, about the right methodologies to characterize the phenomenon and attempt to do so in a comparable manner across taxa that differ as widely in the expression of "personality" as insects and mammals. This makes it necessary to discuss this field in an interdisciplinary context among psychologists and biologists, and was the rational for a meeting on "The Emergence of Personality in Animals" held in May 2010 at the Center for Interdisciplinary Research (Zentrum für Interdisziplinäre Forschung; ZiF), Bielefeld, Germany. The diversity of topics, viewpoints and organisms covered and the excitement created by the ensuing discussions is reflected in the resulting collection of papers forming this special issue.

  14. Use split-flow approach to speed patients to needed care, eliminate inefficiencies and duplication.

    PubMed

    2013-05-01

    To address time and space challenges in the midst of surging demand, the ED at St. Mary Medical Center in Langhorne, PA, turned to the split-flow model, an evidence-based practice that relies heavily on the queuing theory to improve patient throughput. In less than one year, the approach has enabled administrators to reduce door-to-physician times from an average of 47 minutes to 23.5 minutes, and overall length-of-stay in the ED for discharged patients has been slashed by 21 minutes. Under the split-flow system implemented at St. Mary, an expedited triage/assessment process directs patients to prompt care, pediatric care, acute care, or an expedited treatment area (ETA) where patients will undergo further testing or procedures. This initial assessment typically takes about three minutes. Patients sent to the ETA remain there for no longer than 30 minutes.They may then be moved to a holding area while awaiting test results. Patients are constantly moving in the split-flow model, so it is important to pay close attention to handoffs. Patients will begin the process with one nurse and finish with another.

  15. Relevance of Campylobacter to public health--the need for a One Health approach.

    PubMed

    Gölz, Greta; Rosner, Bettina; Hofreuter, Dirk; Josenhans, Christine; Kreienbrock, Lothar; Löwenstein, Anna; Schielke, Anika; Stark, Klaus; Suerbaum, Sebastian; Wieler, Lothar H; Alter, Thomas

    2014-10-01

    Campylobacter species belong to the most important foodborne bacteria which cause gastroenteritis in humans in both developed and developing countries. With increasing reporting rates, the public awareness towards Campylobacter infections is growing continuously. This strengthens the necessity to establish intervention measures for prevention and control of thermophilic Campylobacter spp. along the food chain, as in particular poultry and poultry meat represent a major source of human infections. An interdisciplinary One Health approach and a combined effort of all stakeholders are necessary to ultimately reduce the burden of campylobacteriosis cases in humans. Numerous studies point out, however, that at present a complete elimination of Campylobacter in the food chain is not feasible. The present aim should therefore be to establish control measures and intervention strategies to minimize the occurrence of Campylobacter spp. in livestock (e.g. poultry flocks) and to reduce the quantitative Campylobacter burden in animals and foods. To this end, a combination of intervention methods at different stages of the food chain appears most promising. That has to be accompanied by targeted consumer advice and education campaigns to raise the awareness towards Campylobacter infections.

  16. IAEA Inspections for Undeclared and Declared Activities: Is a More Robust Approach Needed?

    SciTech Connect

    Mark Schanfein

    2009-07-01

    The United States has long supported a strong international safeguards system and for many years has served as the foremost supplier of technology, equipment, and training to the International Atomic Energy Agency (IAEA). In doing so, it drew in many instances on DOE sponsored R&D and training that was directed towards domestic safeguards and then adapted for IAEA purposes. This was relatively straightforward because of the strong overlap between the development of nuclear material accountancy measures needed for both domestic and international purposes. Two factors have emerged that have made this strong reliance on domestic measures less and less able to be a source of support for the IAEA. One is the shift by the IAEA safeguards system towards detecting undeclared activities. The second is the shift of domestic attention away from nuclear material accountancy and towards physical protection. As a result, a gap in US sponsored R&D and training relevant to international safeguards has developed. The NNSA Next Generation Safeguards Initiative and the DOE NA-22 Safeguards R&D program are intended to help fill this gap and, thereby, permit the U.S. to remain as the pre-eminent supplier of technology for international safeguards purposes. In this context, IAEA challenges have been examined from the perspective of detecting the diversion of nuclear material from declared stocks; detecting undeclared production of nuclear material and activities at locations declared under INFCIRC/153; and detecting undeclared nuclear material and activities elsewhere in a state. Of these, the detection of undeclared nuclear material and activities is, perhaps, the IAEA’s most significant challenge. It is a challenge that even the international community finds difficult to meet because of the scope and the geographic scale of the problem, the technical constraints, the knowledge required, and the significant resources needed to deploy effective systems world-wide (e.g., satellite

  17. Filovirus Research: The Need for an Integrated Approach in Time and Space

    NASA Technical Reports Server (NTRS)

    Pinzon, Jorge E.

    2010-01-01

    The episodic appearance of Ebola virus (EBOV) and Marburg virus (MARV) across central Africa over the last 15 years not only underscores the importance of filoviruses as uniquely virulent agents to both human and wildlife communities but also implies a very complex transmission scenario that must be understood if we are to prevent or mitigate filovirus outbreaks in the future. Efforts of a global network of scientists and healthcare workers have expanded our knowledge of filoviruses to meet the growing threat of Ebola and Marburg hemorrhagic fevers in Africa. In recent decades, several newly emerging diseases have resulted in major threats to both affected communities and global public health. Viruses from wildlife hosts in particular, have exhibited a capability for cross-species transmission (CST), and have caused high-impact diseases in humans Such as Ebola and Marburg hemorrhagic fevers, Nipah and severe acute respiratory syndrome (SAILS). It has been estimated that about 60.3% (Jones et al. 2008) of human infectious diseases are of animal origin (zoonoses) and even some important viral diseases that are traditionally considered of human origin, for example measles and smallpox, may very well have their prehistoric origins in wildlife (Wolfe et al 2007). It maybe logical and prudent therefore, to anticipate that there are other, new filoviruses out there that will cross into humans at some point in time. If we anticipate that these will happen and wish to be prepared for and mitigate this potential, then an understanding of filoviruses as a biologic system in the environment will be essential to that process. We will need to know how the ecological dynamic of CST interacts with a 'new' viruse's evolutionary factors to overcome environmental, demographic and host-specific barriers to transmission and infectivity to humans.

  18. [Need for alternative approaches in the evaluation of new antibacterial antibiotics].

    PubMed

    Trémolières, F; Garraffo, R; Lortholary, O

    2005-08-01

    The golden age of antibacterial antibiotics extend from year 1941 to the 1990s decade. At that time, something like an earth quake occurred: from the thirty molecules or so whose development was being achieved or was already marketed, only three were put on the French market, and faced the greatest difficulties to be prescribed by practicians, because: the knights of good practice want a strict limitation of their use to precise indications; the pharmaceutical companies find that the return on investment is almost impossible; the prescribers are stunned by the inconsistency between the MAs, the advances in science and the health economic authorities advices which claim that these products are not very interesting; the research for new antibiotics is stalling; thus, for the first time in 60 years, an iconoclastic question arises: do we need new antibiotics? However, while the debate is raging, many of us think "yes we do", as it is a duty to anticipate today the consequences of tomorrow's bacterial resistances. This paper presents three types of propositions to optimise the development of future molecules: sharpening of the data concerning preclinical security for a better predicting of both the activity and the toxicity; improvement in performances and organization of clinical trials, which implicates to reconsider some of the present methodological rules; inclusion in the evaluation data of some relevant and new features measuring the anti-bacterial activity while taking into account the present and future bacterial resistances. The development of new concepts to develop new drugs which would be active against tomorrow's bacteria compels us to manage in a new fashion today's systems, which have reached their own limits.

  19. Evaluating a basic-needs strategy and population policies: the BACHUE approach.

    PubMed

    Hopkins, M J; Rodgers, G B; Wery, R

    1976-01-01

    The BACHUE model, a dynamic simulation technique developed within the International Labour Organization's World Employment Program, has been applied to the Philippines. The model simulates behavior and consequences in a number of key areas: fertility, marriage, migration, savings and expenditure, and labor force participation for households and a macro-model for demand, ouput, employment, and income. The design and development of the model are discussed in detail. The model was run for a series of 13 experiments ranging from nationlization of modern sectors, increasing self-employment, movement toward labor-intensive techniques, changes in growth rates of various sectors, and a reduction in fertility by 2% over 1976-1985, an increase over the 1% assumed in the base run. Runs R-2 to R-11 all showed that a change in basic needs is associated with significant declines in fertility, largely because of increasing education and decreasing mortality. Better economic conditions in rural areas also reduced migration. R-13 which examined the effects of a family planning program of moderate size on ultimate fertility, showed that even by year 2000 the effects were small. The population is reduced 5% over the run which assumes negative income tax and government subsidies to poor families but the gain in income per adult is less than 4%. Any real improvement in income as the result of family planning will take 40-50 years to achieve. Economic incentives, on the other hand, have much faster demographic results. The models also show that rural-urban migration is responsive to policy changes. Planners are cautioned that the model is not a picture of the entire range of human behavior but is an adjunct for use in analyzing interaction between policies.

  20. On the concept of Bell’s local causality in local classical and quantum theory

    SciTech Connect

    Hofer-Szabó, Gábor; Vecsernyés, Péter

    2015-03-15

    The aim of this paper is to implement Bell’s notion of local causality into a framework, called local physical theory. This framework, based on the axioms of algebraic field theory, is broad enough to integrate both probabilistic and spatiotemporal concepts and also classical and quantum theories. Bell’s original idea of local causality will arise as the classical case of our definition. Classifying local physical theories by whether they obey local primitive causality, a property rendering the dynamics of the theory causal, we then investigate what is needed for a local physical theory to be locally causal. Finally, comparing local causality with the common cause principles and relating both to the Bell inequalities we find a nice parallelism: Bell inequalities cannot be derived neither from local causality nor from a common cause unless the local physical theory is classical or the common cause is commuting, respectively.

  1. The need for an organized approach for Government Medical Insurance Programs in the Commonwealth of Virginia.

    PubMed

    Edlich, Richard F

    2005-01-01

    The Commonwealth of Virginia has a disorganized approach to enrolling their retired faculty in Medicare Supplement Insurance Programs. An organized approach to establishing Medicare Supplemental Insurance for retired University faculty should include the following administrative changes to correct this potential health-care crisis for retired state faculty members. First, the ombudsman for human resources for the state universities must receive educational programs that prepare the retired faculty members over the age of 65 to select the corporate insurance policy from Anthem Blue Cross/Blue Shield Insurance Company. Included in this educational program should be a review of the Advantage 65 Member Handbook. Second, they must point out to the faculty member that they are receiving a CORPORATE insurance policy rather than an individual insurance policy from Anthem Blue Cross/Blue Shield Insurance Company. They must provide the telephone numbers of the Anthem Blue Cross/Blue Shield offices in Roanoke, Virginia. Concomitantly, they must send the name and address of the faculty member to the Commonwealth of Virginia Department of Human Resource Management. They should inform the faculty member that the Commonwealth of Virginia Department of Human Resource Management will be sending them newsletters that outline any changes in the corporate insurance policy that they coordinate with the Anthem Blue Cross/Blue Shield Insurance Company. The Commonwealth of Virginia Department of Human Resource Management must take on some new responsibilities in their efforts to coordinate health-care coverage of the retired faculty over the age of 65. First, they must have a computer registry of all corporate health-care policies of the individual faculty members to ensure that newsletters are being sent to them. Ideally, this agency should have a computerized system that allows it to send out its newsletter update by email to those retired faculty members who have computers. They should

  2. What is the best approach to tailoring hydrocortisone dose to meet patient needs in 2012?

    PubMed

    Debono, Miguel; Ross, Richard J

    2013-05-01

    Cortisol is an essential stress hormone and replacement with oral hydrocortisone is lifesaving in patients with adrenal insufficiency. Cortisol has a diurnal rhythm regulated by the central body clock and this rhythm is a metabolic signal for peripheral tissue clocks. Loss of cortisol rhythmicity is associated with fatigue, depression and insulin resistance. A general principle in endocrinology is to replace hormones to replicate physiological concentrations; however, the pharmacokinetics of oral immediate-release hydrocortisone make it impossible to fully mimic the cortisol rhythm and patients still have an increased morbidity and mortality despite replacement. Traditionally, physicians have replaced hydrocortisone with a total daily dose based on the diurnal 24-h cortisol production rate with hydrocortisone given twice or thrice daily, with the highest dose first thing in the morning. Monitoring treatment and dose titration has been much debated with some clinicians using cortisol day curves and others relying on clinical symptoms. The main challenge is that there is no established biomarker of cortisol activity. In addressing the clinical question, we have taken the view that an understanding of the cortisol circadian rhythm and hydrocortisone pharmacokinetics is essential when tailoring hydrocortisone dose. Using this approach, we have developed a thrice daily, weight-related, dosing regimen and a pharmacokinetic and clinical method to monitor treatment. Our argument for replicating the cortisol circadian rhythm is based on the observation that disruption of the rhythm is associated with ill health, and the few studies that have compared different treatment regimens. Further studies are required to definitively test the benefits of replacing the cortisol circadian rhythm in patients with adrenal insufficiency.

  3. A holistic approach to chronic pain management that involves all stakeholders: change is needed.

    PubMed

    Kress, Hans-Georg; Aldington, Dominic; Alon, Eli; Coaccioli, Stefano; Collett, Beverly; Coluzzi, Flaminia; Huygen, Frank; Jaksch, Wolfgang; Kalso, Eija; Kocot-Kępska, Magdalena; Mangas, Ana Cristina; Ferri, Cesar Margarit; Mavrocordatos, Philippe; Morlion, Bart; Müller-Schwefe, Gerhard; Nicolaou, Andrew; Hernández, Concepción Pérez; Sichère, Patrick

    2015-01-01

    Chronic pain affects a large proportion of the population, imposing significant individual distress and a considerable burden on society, yet treatment is not always instituted and/or adequate. Comprehensive multidisciplinary management based on the biopsychosocial model of pain has been shown to be clinically effective and cost-efficient, but is not widely available. A literature review of stakeholder groups revealed many reasons for this, including: i) many patients believe healthcare professionals lack relevant knowledge, and consultations are rushed, ii) general practitioners consider that pain management has a low priority and is under-resourced, iii) pain specialists cite non-adherence to evidence-based treatment, sub-optimal prescribing, and chronic pain not being regarded as a disease in its own right, iv) nurses', pharmacists' and physiotherapists' skills are not fully utilized, and v) psychological therapy is employed infrequently and often too late. Many of the issues relating to physicians could be addressed by improving medical training, both at undergraduate and postgraduate levels - for example, by making pain medicine a compulsory core subject of the undergraduate medical curriculum. This would improve physician/patient communication, increase the use of standardized pain assessment tools, and allow more patients to participate in treatment decisions. Patient care would also benefit from improved training for other multidisciplinary team members; for example, nurses could provide counseling and follow-up support, psychologists offer coping skills training, and physiotherapists have a greater role in rehabilitation. Equally important measures include the widespread adoption of a patient-centered approach, chronic pain being recognized as a disease in its own right, and the development of universal guidelines for managing chronic non-cancer pain. Perhaps the greatest barrier to improvement is lack of political will at both national and international

  4. Supporting culturally and linguistically diverse children with speech, language and communication needs: Overarching principles, individual approaches.

    PubMed

    Verdon, Sarah; McLeod, Sharynne; Wong, Sandie

    2015-01-01

    Speech-language pathologists (SLPs) are working with an increasing number of families from culturally and linguistically diverse backgrounds as the world's population continues to become more internationally mobile. The heterogeneity of these diverse populations makes it impossible to identify and document a one size fits all strategy for working with culturally and linguistically diverse families. This paper explores approaches to practice by SLPs identified as specialising in multilingual and multicultural practice in culturally and linguistically diverse contexts from around the world. Data were obtained from ethnographic observation of 14 sites in 5 countries on 4 continents. The sites included hospital settings, university clinics, school-based settings, private practices and Indigenous community-based services. There were 652 individual artefacts collected from the sites which included interview transcripts, photographs, videos, narrative reflections, informal and formal field notes. The data were analysed using Cultural-Historical Activity Theory (Engeström, 1987). From the analysis six overarching Principles of Culturally Competent Practice (PCCP) were identified. These were: (1) identification of culturally appropriate and mutually motivating therapy goals, (2) knowledge of languages and culture, (3) use of culturally appropriate resources, (4) consideration of the cultural, social and political context, (5) consultation with families and communities, and (6) collaboration between professionals. These overarching principles align with the six position statements developed by the International Expert Panel on Multilingual Children's Speech (2012) which aim to enhance the cultural competence of speech pathologists and their practice. The international examples provided in the current study demonstrate the individualised ways that these overarching principles are enacted in a range of different organisational, social, cultural and political contexts

  5. Analyzing multiple spike trains with nonparametric Granger causality.

    PubMed

    Nedungadi, Aatira G; Rangarajan, Govindan; Jain, Neeraj; Ding, Mingzhou

    2009-08-01

    Simultaneous recordings of spike trains from multiple single neurons are becoming commonplace. Understanding the interaction patterns among these spike trains remains a key research area. A question of interest is the evaluation of information flow between neurons through the analysis of whether one spike train exerts causal influence on another. For continuous-valued time series data, Granger causality has proven an effective method for this purpose. However, the basis for Granger causality estimation is autoregressive data modeling, which is not directly applicable to spike trains. Various filtering options distort the properties of spike trains as point processes. Here we propose a new nonparametric approach to estimate Granger causality directly from the Fourier transforms of spike train data. We validate the method on synthetic spike trains generated by model networks of neurons with known connectivity patterns and then apply it to neurons simultaneously recorded from the thalamus and the primary somatosensory cortex of a squirrel monkey undergoing tactile stimulation.

  6. Study on weighting of amount of nursing care using data on index of patient's need for nursing and system approach.

    PubMed

    Uto, Yumiko; Kumamoto, Ichiro

    2005-04-01

    The importance of appropriate staffing of nurses has been emphasized and optimal provision of nursing care has increased in order to improve the quality of nursing service. Since the introduction of the nursing information system in 1987, we have creatively categorized the classification of index of patient's need for nursing to collect ever-objective data on the index of patient's need for nursing and utilized it as an indicator to evaluate the amount of nursing care necessary for patients. We also weighted the index of patient's need for nursing and categorized it into categories A, B, and C based on the accumulated data on the index of patient's need for nursing, and calculated the cost of nursing care by adding the nurse salary data to the weighting. In addition, we developed a system in which measurement of amount of nursing care based on the data on the index of patient's need for nursing and calculation of nursing care cost could be done by utilizing the hospital Data Warehouse (DWH) and adopted a system approach that could contribute to improvement in patient service and make hospital management better.

  7. Estimating the need for palliative radiotherapy for brain metastasis: a benchmarking approach.

    PubMed

    Kong, W; Jarvis, C; Mackillop, W J

    2015-02-01

    Palliative radiotherapy (PRT) is useful in the management of many patients with brain metastases, but the need for this treatment in the general cancer population is unknown. The objective of this study was to estimate the appropriate rate of use of PRT for brain metastases (PRT.Br). Ontario's population-based cancer registry was used to identify patients who died of cancer. Radiotherapy records from all the province's radiotherapy centres were linked to Ontario's cancer registry to identify patients who received PRT.Br in the last 2 years of life. Multivariate analysis was used to identify social and health system-related barriers to the use of PRT.Br and to identify a subpopulation of patients with unimpeded access to PRT.Br. The rate of use of PRT.Br was measured in this benchmark subpopulation. The benchmark rate was standardised to the case mix of the overall cancer population. The study population included 231,397 patients who died of cancer in Ontario between 1998 and 2007. Overall, 13,944 patients received at least one course of PRT.Br in the last 2 years of life (6.0%). Multivariate analysis showed that the use of PRT.Br was strongly associated with: the availability of radiotherapy at the diagnosing hospital; the socioeconomic status of the community where the patient lived; and the distance from his/her home to the nearest radiotherapy centre. The benchmark subpopulation was defined as patients diagnosed in a hospital with radiotherapy facilities on site and who resided in a high income community, within 50 km of the nearest radiotherapy centre. The standardised benchmark rate of PRT.Br was 8.0% (95% confidence interval 7.5%, 8.5%). The overall shortfall between the actual rate and the benchmark was 25%, but varied by primary cancer site: lung, 27.6%; melanoma, 19.4%; breast, 13.9%. The magnitude of the shortfall in the use of PRT.Br varied widely across the province. At least 8.0% of patients who die of cancer require PRT.Br at least once in the last 2

  8. Causal tapestries for psychology and physics.

    PubMed

    Sulis, William H

    2012-04-01

    Archetypal dynamics is a formal approach to the modeling of information flow in complex systems used to study emergence. It is grounded in the Fundamental Triad of realisation (system), interpretation (archetype) and representation (formal model). Tapestries play a fundamental role in the framework of archetypal dynamics as a formal representational system. They represent information flow by means of multi layered, recursive, interlinked graphical structures that express both geometry (form or sign) and logic (semantics). This paper presents a detailed mathematical description of a specific tapestry model, the causal tapestry, selected for use in describing behaving systems such as appear in psychology and physics from the standpoint of Process Theory. Causal tapestries express an explicit Lorentz invariant transient now generated by means of a reality game. Observables are represented by tapestry informons while subjective or hidden components (for example intellectual and emotional processes) are incorporated into the reality game that determines the tapestry dynamics. As a specific example, we formulate a random graphical dynamical system using causal tapestries.

  9. Reliability of the Granger causality inference

    NASA Astrophysics Data System (ADS)

    Zhou, Douglas; Zhang, Yaoyu; Xiao, Yanyang; Cai, David

    2014-04-01

    How to characterize information flows in physical, biological, and social systems remains a major theoretical challenge. Granger causality (GC) analysis has been widely used to investigate information flow through causal interactions. We address one of the central questions in GC analysis, that is, the reliability of the GC evaluation and its implications for the causal structures extracted by this analysis. Our work reveals that the manner in which a continuous dynamical process is projected or coarse-grained to a discrete process has a profound impact on the reliability of the GC inference, and different sampling may potentially yield completely opposite inferences. This inference hazard is present for both linear and nonlinear processes. We emphasize that there is a hazard of reaching incorrect conclusions about network topologies, even including statistical (such as small-world or scale-free) properties of the networks, when GC analysis is blindly applied to infer the network topology. We demonstrate this using a small-world network for which a drastic loss of small-world attributes occurs in the reconstructed network using the standard GC approach. We further show how to resolve the paradox that the GC analysis seemingly becomes less reliable when more information is incorporated using finer and finer sampling. Finally, we present strategies to overcome these inference artifacts in order to obtain a reliable GC result.

  10. John S. Bell's concept of local causality

    NASA Astrophysics Data System (ADS)

    Norsen, Travis

    2011-12-01

    John Stewart Bell's famous theorem is widely regarded as one of the most important developments in the foundations of physics. Yet even as we approach the 50th anniversary of Bell's discovery, its meaning and implications remain controversial. Many workers assert that Bell's theorem refutes the possibility suggested by Einstein, Podolsky, and Rosen (EPR) of supplementing ordinary quantum theory with ``hidden'' variables that might restore determinism and/or some notion of an observer-independent reality. But Bell himself interpreted the theorem very differently--as establishing an ``essential conflict'' between the well-tested empirical predictions of quantum theory and relativistic local causality. Our goal is to make Bell's own views more widely known and to explain Bell's little-known formulation of the concept of relativistic local causality on which his theorem rests. We also show precisely how Bell's formulation of local causality can be used to derive an empirically testable Bell-type inequality and to recapitulate the EPR argument.

  11. John S. Bell's concept of local causality

    NASA Astrophysics Data System (ADS)

    Norsen, Travis

    2011-12-01

    John Stewart Bell's famous theorem is widely regarded as one of the most important developments in the foundations of physics. Yet even as we approach the 50th anniversary of Bell's discovery, its meaning and implications remain controversial. Many workers assert that Bell's theorem refutes the possibility suggested by Einstein, Podolsky, and Rosen (EPR) of supplementing ordinary quantum theory with "hidden" variables that might restore determinism and/or some notion of an observer-independent reality. But Bell himself interpreted the theorem very differently—as establishing an "essential conflict" between the well-tested empirical predictions of quantum theory and relativistic local causality. Our goal is to make Bell's own views more widely known and to explain Bell's little-known formulation of the concept of relativistic local causality on which his theorem rests. We also show precisely how Bell's formulation of local causality can be used to derive an empirically testable Bell-type inequality and to recapitulate the EPR argument.

  12. Limitations of individual causal models, causal graphs, and ignorability assumptions, as illustrated by random confounding and design unfaithfulness.

    PubMed

    Greenland, Sander; Mansournia, Mohammad Ali

    2015-10-01

    We describe how ordinary interpretations of causal models and causal graphs fail to capture important distinctions among ignorable allocation mechanisms for subject selection or allocation. We illustrate these limitations in the case of random confounding and designs that prevent such confounding. In many experimental designs individual treatment allocations are dependent, and explicit population models are needed to show this dependency. In particular, certain designs impose unfaithful covariate-treatment distributions to prevent random confounding, yet ordinary causal graphs cannot discriminate between these unconfounded designs and confounded studies. Causal models for populations are better suited for displaying these phenomena than are individual-level models, because they allow representation of allocation dependencies as well as outcome dependencies across individuals. Nonetheless, even with this extension, ordinary graphical models still fail to capture distinctions between hypothetical superpopulations (sampling distributions) and observed populations (actual distributions), although potential-outcome models can be adapted to show these distinctions and their consequences.

  13. Pollutant fates in fluvial systems: on need of individual approach to each case study

    NASA Astrophysics Data System (ADS)

    Matys Grygar, Tomas; Elznicova, Jitka; Novakova, Tereza

    2015-04-01

    deposition in a channel belt and subsequent secondary pollution via physical mobilisation, most pollution storing in the floodplain in a surprisingly heterogeneous manner - in hotspots with a size comparable to fragments of abandoned channels (from a few to few tens of metres). The hotspots are hence best revealed by well-designed field analysis using portable instruments (gamma spectrometry or XRF). The Litavka is specific because most pollution is in its floodplain in the form of anthropogenic alluvium, a very thick vertical accretion body of "artificial" material added to the river system in the amount exceeding its normal transport capacity. That situation favours secondary pollution by chemical mobilisation of pollutants under low river discharges revealed by geochemical analysis. Our case studies show that simple "rules" such as continuous decay of pollutant concentrations downstream from the pollution source, existence of a continuous blanket of polluted overbank fines in floodplain, simple change of the pollution extent with growing distance from the river channel and as a consequence of extreme floods, or simple recipes such as low-density sampling to trace point pollution sources are too simplistic to be applicable in real polluted fluvial systems. Each river system represents a nearly unique combination of individual geomorphic processes, and each pollution has been specific by the mode how it entered the fluvial system. We will not offer "magic tools" in our contribution. In literature we can find all pieces we need for the jigsaw puzzle - pollutants fates in fluvial systems. The question is why so rarely researchers put them together. We would like to encourage them to do so.

  14. Different Kinds of Causality in Event Cognition

    ERIC Educational Resources Information Center

    Radvansky, Gabriel A.; Tamplin, Andrea K.; Armendarez, Joseph; Thompson, Alexis N.

    2014-01-01

    Narrative memory is better for information that is more causally connected and occurs at event boundaries, such as a causal break. However, it is unclear whether there are common or distinct influences of causality. For the event boundaries that arise as a result of causal breaks, the events that follow may subsequently become more causally…

  15. Can pre-operative computed tomography predict the need for a thoracic approach for removal of retrosternal goitre?

    PubMed

    Qureishi, Ali; Garas, George; Tolley, Neil; Palazzo, Fausto; Athanasiou, Thanos; Zacharakis, Emmanouil

    2013-01-01

    A best evidence topic was written according to a structured protocol. The question addressed was whether in patients with retrosternal goitre the need for a thoracic approach can be predicted using pre-operative CT. A total of 381 papers were identified using the reported search protocol of which 7 represented the best evidence to answer the clinical question. The authors, journal, date, country of publication, patient group studied, study type, relevant outcomes and results are tabulated. The evidence on this subject is poor, none of the studies were randomised, only one used controls (historical) and all studies were retrospective. Despite these limitations, CT represents the gold-standard imaging modality in the pre-operative evaluation of patients with retrosternal goitre. CT is essential to define the extent and position of a retrosternal goitre. The literature suggests that CT is the single most valuable pre-operative investigation predicting whether a sternotomy or lateral thoracotomy will be necessary for removal of the retrosternal goitre. Although pre-operative CT does not have the precision to predict whether a thoracic approach is required in all cases, the presence of certain radiological features such as extension of the goitre below the aortic arch or into the posterior mediastinum, a dumbbell shape and a thoracic component that is wider than the thoracic inlet are all associated with the need for a thoracic approach. In some cases a pre-operative CT will not only determine that a thoracic approach is mandatory but it will also guide the surgeon upon the type of thoracic approach.

  16. Quantum Supersymmetric Models in the Causal Approach

    NASA Astrophysics Data System (ADS)

    Grigore, Dan-Radu

    2007-04-01

    We consider the massless supersymmetric vector multiplet in a purely quantum framework. First order gauge invariance determines uniquely the interaction Lagrangian as in the case of Yang-Mills models. Going to the second order of perturbation theory produces an anomaly which cannot be eliminated. We make the analysis of the model working only with the component fields.

  17. Causality and complexity: the myth of objectivity in science.

    PubMed

    Mikulecky, Donald C

    2007-10-01

    Two distinctly different worldviews dominate today's thinking in science and in the world of ideas outside of science. Using the approach advocated by Robert M. Hutchins, it is possible to see a pattern of interaction between ideas in science and in other spheres such as philosophy, religion, and politics. Instead of compartmentalizing these intellectual activities, it is worthwhile to look for common threads of mutual influence. Robert Rosen has created an approach to scientific epistemology that might seem radical to some. However, it has characteristics that resemble ideas in other fields, in particular in the writings of George Lakoff, Leo Strauss, and George Soros. Historically, the atmosphere at the University of Chicago during Hutchins' presidency gave rise to Rashevsky's relational biology, which Rosen carried forward. Strauss was writing his political philosophy there at the same time. One idea is paramount in all this, and it is Lakoff who gives us the most insight into how the worldviews differ using this idea. The central difference has to do with causality, the fundamental concept that we use to build a worldview. Causal entailment has two distinct forms in Lakoff 's analysis: direct causality and complex causality. Rosen's writings on complexity create a picture of complex causality that is extremely useful in its detail, grounding in the ideas of Aristotle. Strauss asks for a return to the ancients to put philosophy back on track. Lakoff sees the weaknesses in Western philosophy in a similar way, and Rosen provides tools for dealing with the problem. This introduction to the relationships between the thinking of these authors is meant to stimulate further discourse on the role of complex causal entailment in all areas of thought, and how it brings them together in a holistic worldview. The worldview built on complex causality is clearly distinct from that built around simple, direct causality. One important difference is that the impoverished causal

  18. Differentiating SIADH from Cerebral/Renal Salt Wasting: Failure of the Volume Approach and Need for a New Approach to Hyponatremia.

    PubMed

    Maesaka, John K; Imbriano, Louis; Mattana, Joseph; Gallagher, Dympna; Bade, Naveen; Sharif, Sairah

    2014-12-08

    Hyponatremia is the most common electrolyte abnormality. Its diagnostic and therapeutic approaches are in a state of flux. It is evident that hyponatremic patients are symptomatic with a potential for serious consequences at sodium levels that were once considered trivial. The recommendation to treat virtually all hyponatremics exposes the need to resolve the diagnostic and therapeutic dilemma of deciding whether to water restrict a patient with the syndrome of inappropriate antidiuretic hormone secretion (SIADH) or administer salt and water to a renal salt waster. In this review, we briefly discuss the pathophysiology of SIADH and renal salt wasting (RSW), and the difficulty in differentiating SIADH from RSW, and review the origin of the perceived rarity of RSW, as well as the value of determining fractional excretion of urate (FEurate) in differentiating both syndromes, the high prevalence of RSW which highlights the inadequacy of the volume approach to hyponatremia, the importance of changing cerebral salt wasting to RSW, and the proposal to eliminate reset osmostat as a subtype of SIADH, and finally propose a new algorithm to replace the outmoded volume approach by highlighting FEurate. This algorithm eliminates the need to assess the volume status with less reliance on determining urine sodium concentration, plasma renin, aldosterone and atrial/brain natriuretic peptide or the BUN to creatinine ratio.

  19. Differentiating SIADH from Cerebral/Renal Salt Wasting: Failure of the Volume Approach and Need for a New Approach to Hyponatremia

    PubMed Central

    Maesaka, John K.; Imbriano, Louis; Mattana, Joseph; Gallagher, Dympna; Bade, Naveen; Sharif, Sairah

    2014-01-01

    Hyponatremia is the most common electrolyte abnormality. Its diagnostic and therapeutic approaches are in a state of flux. It is evident that hyponatremic patients are symptomatic with a potential for serious consequences at sodium levels that were once considered trivial. The recommendation to treat virtually all hyponatremics exposes the need to resolve the diagnostic and therapeutic dilemma of deciding whether to water restrict a patient with the syndrome of inappropriate antidiuretic hormone secretion (SIADH) or administer salt and water to a renal salt waster. In this review, we briefly discuss the pathophysiology of SIADH and renal salt wasting (RSW), and the difficulty in differentiating SIADH from RSW, and review the origin of the perceived rarity of RSW, as well as the value of determining fractional excretion of urate (FEurate) in differentiating both syndromes, the high prevalence of RSW which highlights the inadequacy of the volume approach to hyponatremia, the importance of changing cerebral salt wasting to RSW, and the proposal to eliminate reset osmostat as a subtype of SIADH, and finally propose a new algorithm to replace the outmoded volume approach by highlighting FEurate. This algorithm eliminates the need to assess the volume status with less reliance on determining urine sodium concentration, plasma renin, aldosterone and atrial/brain natriuretic peptide or the BUN to creatinine ratio. PMID:26237607

  20. On the Causality and K-Causality between Measures

    NASA Astrophysics Data System (ADS)

    Miller, Tomasz

    2017-03-01

    Drawing from our earlier works on the notion of causality for nonlocal phenomena, we propose and study the extension of the Sorkin--Woolgar relation $K^+$ onto the space of Borel probability measures on a given spacetime. We show that it retains its fundamental properties of transitivity and closedness. Furthermore, we list and prove several characterizations of this relation, including the `nonlocal' analogue of the characterization of $K^+$ in terms of time functions. This generalizes and casts new light on our earlier results concerning the causal precedence relation $J^+$ between measures.

  1. Computing and information services at the Jet Propulsion Laboratory - A management approach to a diversity of needs

    NASA Technical Reports Server (NTRS)

    Felberg, F. H.

    1984-01-01

    The Jet Propulsion Laboratory, a research and development organization with about 5,000 employees, presents a complicated set of requirements for an institutional system of computing and informational services. The approach taken by JPL in meeting this challenge is one of controlled flexibility. A central communications network is provided, together with selected computing facilities for common use. At the same time, staff members are given considerable discretion in choosing the mini- and microcomputers that they believe will best serve their needs. Consultation services, computer education, and other support functions are also provided.

  2. Challenging empowerment: AIDS-affected South African children and the need for a multi-level relational approach.

    PubMed

    Ansell, Nicola

    2014-01-01

    Critics of empowerment have highlighted the concept's mutability, focus on individual transformation, one-dimensionality and challenges of operationalisation. Relating these critiques to children's empowerment raises new challenges. Drawing on scholarship on children's subjecthood and exercise of power, alongside empirical research with children affected by AIDS, I argue that empowerment envisaged as individual self-transformation and increased capacity to act independently offers little basis for progressive change. Rather it is essential to adopt a relational approach that recognises the need to transform power relationships at multiple levels. This analysis has implications for our wider understanding of empowerment in the 21st century.

  3. An Integrated Systems Approach is Needed to Ensure the Sustainability of Antibiotic Effectiveness for Both Humans and Animals.

    PubMed

    So, Anthony D; Shah, Tejen A; Roach, Steven; Ling Chee, Yoke; Nachman, Keeve E

    2015-01-01

    The growing demand for animal products and the widespread use of antibiotics in bringing food animals to market have heightened concerns over cross-species transmission of drug resistance. Both the biology and emerging epidemiology strongly support the need for global coordination in stemming the generation and propagation of resistance, and the patchwork of global and country-level regulations still leaves significant gaps. More importantly, discussing such a framework opens the door to taking modular steps towards solving these challenges - for example, beginning among targeted parties rather than all countries, tying accountability to financial and technical support, or taxing antibiotic use in animals to deter low-value usage of these drugs. An international agreement would allow integrating surveillance data collection, monitoring and enforcement, research into antibiotic alternatives and more sustainable approaches to agriculture, technical assistance and capacity building, and financing under the umbrella of a One Health approach.

  4. Comparison Analysis: Granger Causality and New Causality and Their Applications to Motor Imagery.

    PubMed

    Hu, Sanqing; Wang, Hui; Zhang, Jianhai; Kong, Wanzeng; Cao, Yu; Kozma, Robert

    2016-07-01

    In this paper we first point out a fatal drawback that the widely used Granger causality (GC) needs to estimate the autoregressive model, which is equivalent to taking a series of backward recursive operations which are infeasible in many irreversible chemical reaction models. Thus, new causality (NC) proposed by Hu et al. (2011) is theoretically shown to be more sensitive to reveal true causality than GC. We then apply GC and NC to motor imagery (MI) which is an important mental process in cognitive neuroscience and psychology and has received growing attention for a long time. We study causality flow during MI using scalp electroencephalograms from nine subjects in Brain-computer interface competition IV held in 2008. We are interested in three regions: Cz (central area of the cerebral cortex), C3 (left area of the cerebral cortex), and C4 (right area of the cerebral cortex) which are considered to be optimal locations for recognizing MI states in the literature. Our results show that: 1) there is strong directional connectivity from Cz to C3/C4 during left- and right-hand MIs based on GC and NC; 2) during left-hand MI, there is directional connectivity from C4 to C3 based on GC and NC; 3) during right-hand MI, there is strong directional connectivity from C3 to C4 which is much clearly revealed by NC than by GC, i.e., NC largely improves the classification rate; and 4) NC is demonstrated to be much more sensitive to reveal causal influence between different brain regions than GC.

  5. Causal inference in survival analysis using pseudo-observations.

    PubMed

    Andersen, Per K; Syriopoulou, Elisavet; Parner, Erik T

    2017-04-06

    Causal inference for non-censored response variables, such as binary or quantitative outcomes, is often based on either (1) direct standardization ('G-formula') or (2) inverse probability of treatment assignment weights ('propensity score'). To do causal inference in survival analysis, one needs to address right-censoring, and often, special techniques are required for that purpose. We will show how censoring can be dealt with 'once and for all' by means of so-called pseudo-observations when doing causal inference in survival analysis. The pseudo-observations can be used as a replacement of the outcomes without censoring when applying 'standard' causal inference methods, such as (1) or (2) earlier. We study this idea for estimating the average causal effect of a binary treatment on the survival probability, the restricted mean lifetime, and the cumulative incidence in a competing risks situation. The methods will be illustrated in a small simulation study and via a study of patients with acute myeloid leukemia who received either myeloablative or non-myeloablative conditioning before allogeneic hematopoetic cell transplantation. We will estimate the average causal effect of the conditioning regime on outcomes such as the 3-year overall survival probability and the 3-year risk of chronic graft-versus-host disease. Copyright © 2017 John Wiley & Sons, Ltd.

  6. Causal quantum theory and the collapse locality loophole

    SciTech Connect

    Kent, Adrian

    2005-07-15

    Causal quantum theory is an umbrella term for ordinary quantum theory modified by two hypotheses: state vector reduction is a well-defined process, and strict local causality applies. The first of these holds in some versions of Copenhagen quantum theory and need not necessarily imply practically testable deviations from ordinary quantum theory. The second implies that measurement events which are spacelike separated have no nonlocal correlations. To test this prediction, which sharply differs from standard quantum theory, requires a precise definition of state vector reduction. Formally speaking, any precise version of causal quantum theory defines a local hidden variable theory. However, causal quantum theory is most naturally seen as a variant of standard quantum theory. For that reason it seems a more serious rival to standard quantum theory than local hidden variable models relying on the locality or detector efficiency loopholes. Some plausible versions of causal quantum theory are not refuted by any Bell experiments to date, nor is it evident that they are inconsistent with other experiments. They evade refutation via a neglected loophole in Bell experiments--the collapse locality loophole--which exists because of the possible time lag between a particle entering a measurement device and a collapse taking place. Fairly definitive tests of causal versus standard quantum theory could be made by observing entangled particles separated by {approx_equal}0.1 light seconds.

  7. Herbal hepatotoxicity: Challenges and pitfalls of causality assessment methods

    PubMed Central

    Teschke, Rolf; Frenzel, Christian; Schulze, Johannes; Eickhoff, Axel

    2013-01-01

    The diagnosis of herbal hepatotoxicity or herb induced liver injury (HILI) represents a particular clinical and regulatory challenge with major pitfalls for the causality evaluation. At the day HILI is suspected in a patient, physicians should start assessing the quality of the used herbal product, optimizing the clinical data for completeness, and applying the Council for International Organizations of Medical Sciences (CIOMS) scale for initial causality assessment. This scale is structured, quantitative, liver specific, and validated for hepatotoxicity cases. Its items provide individual scores, which together yield causality levels of highly probable, probable, possible, unlikely, and excluded. After completion by additional information including raw data, this scale with all items should be reported to regulatory agencies and manufacturers for further evaluation. The CIOMS scale is preferred as tool for assessing causality in hepatotoxicity cases, compared to numerous other causality assessment methods, which are inferior on various grounds. Among these disputed methods are the Maria and Victorino scale, an insufficiently qualified, shortened version of the CIOMS scale, as well as various liver unspecific methods such as the ad hoc causality approach, the Naranjo scale, the World Health Organization (WHO) method, and the Karch and Lasagna method. An expert panel is required for the Drug Induced Liver Injury Network method, the WHO method, and other approaches based on expert opinion, which provide retrospective analyses with a long delay and thereby prevent a timely assessment of the illness in question by the physician. In conclusion, HILI causality assessment is challenging and is best achieved by the liver specific CIOMS scale, avoiding pitfalls commonly observed with other approaches. PMID:23704820

  8. Identification of marginal causal relationships in gene networks from observational and interventional expression data.

    PubMed

    Monneret, Gilles; Jaffrézic, Florence; Rau, Andrea; Zerjal, Tatiana; Nuel, Grégory

    2017-01-01

    Causal network inference is an important methodological challenge in biology as well as other areas of application. Although several causal network inference methods have been proposed in recent years, they are typically applicable for only a small number of genes, due to the large number of parameters to be estimated and the limited number of biological replicates available. In this work, we consider the specific case of transcriptomic studies made up of both observational and interventional data in which a single gene of biological interest is knocked out. We focus on a marginal causal estimation approach, based on the framework of Gaussian directed acyclic graphs, to infer causal relationships between the knocked-out gene and a large set of other genes. In a simulation study, we found that our proposed method accurately differentiates between downstream causal relationships and those that are upstream or simply associative. It also enables an estimation of the total causal effects between the gene of interest and the remaining genes. Our method performed very similarly to a classical differential analysis for experiments with a relatively large number of biological replicates, but has the advantage of providing a formal causal interpretation. Our proposed marginal causal approach is computationally efficient and may be applied to several thousands of genes simultaneously. In addition, it may help highlight subsets of genes of interest for a more thorough subsequent causal network inference. The method is implemented in an R package called MarginalCausality (available on GitHub).

  9. Identification of marginal causal relationships in gene networks from observational and interventional expression data

    PubMed Central

    Monneret, Gilles; Jaffrézic, Florence; Rau, Andrea; Zerjal, Tatiana; Nuel, Grégory

    2017-01-01

    Causal network inference is an important methodological challenge in biology as well as other areas of application. Although several causal network inference methods have been proposed in recent years, they are typically applicable for only a small number of genes, due to the large number of parameters to be estimated and the limited number of biological replicates available. In this work, we consider the specific case of transcriptomic studies made up of both observational and interventional data in which a single gene of biological interest is knocked out. We focus on a marginal causal estimation approach, based on the framework of Gaussian directed acyclic graphs, to infer causal relationships between the knocked-out gene and a large set of other genes. In a simulation study, we found that our proposed method accurately differentiates between downstream causal relationships and those that are upstream or simply associative. It also enables an estimation of the total causal effects between the gene of interest and the remaining genes. Our method performed very similarly to a classical differential analysis for experiments with a relatively large number of biological replicates, but has the advantage of providing a formal causal interpretation. Our proposed marginal causal approach is computationally efficient and may be applied to several thousands of genes simultaneously. In addition, it may help highlight subsets of genes of interest for a more thorough subsequent causal network inference. The method is implemented in an R package called MarginalCausality (available on GitHub). PMID:28301504

  10. Regulatory causality evaluation methods applied in kava hepatotoxicity: are they appropriate?

    PubMed

    Teschke, Rolf; Wolff, Albrecht

    2011-02-01

    Since 1998 liver injury has been assumed in some patients after the use of kava (Piper methysticum G. Forster) as an anxyolytic herbal extract, but the regulatory causality evaluation of these cases was a matter of international and scientific debate. This review critically analyzes the regulatory issues of causality assessments of patients with primarily suspected kava hepatotoxicity and suggests recommendations for minimizing regulatory risks when assessing causality in these and other related cases. The various regulatory causality approaches were based on liver unspecific assessments such as ad hoc evaluations, the WHO scale using the definitions of the WHO Collaborating Centre for International Drug Monitoring, and the Naranjo scale. Due to their liver unspecificity, however, these causality approaches are not suitable for assessing cases of primarily assumed liver related adverse reactions by drugs and herbs including kava. Major problems emerged trough the combination of regulatory inappropriate causality assessment methods with the poor data quality as presented by the regulatory agency when reassessment was done and the resulting data were heavily criticized worldwide within the scientific community. Conversely, causality of cases with primarily assumed kava hepatotoxicity is best assessed by structured, quantitative and liver specific causality algorithms such as the scale of the CIOMS (Council for International Organizations of Medical Sciences) or the main-test as its update. Future strategies should therefore focus on the implementation of structured, quantitative and liver specific causality assessment methods as regulatory standards to improve regulatory causality assessments for liver injury by drugs and herbs including kava.

  11. Causal reasoning with mental models

    PubMed Central

    Khemlani, Sangeet S.; Barbey, Aron K.; Johnson-Laird, Philip N.

    2014-01-01

    This paper outlines the model-based theory of causal reasoning. It postulates that the core meanings of causal assertions are deterministic and refer to temporally-ordered sets of possibilities: A causes B to occur means that given A, B occurs, whereas A enables B to occur means that given A, it is possible for B to occur. The paper shows how mental models represent such assertions, and how these models underlie deductive, inductive, and abductive reasoning yielding explanations. It reviews evidence both to corroborate the theory and to account for phenomena sometimes taken to be incompatible with it. Finally, it reviews neuroscience evidence indicating that mental models for causal inference are implemented within lateral prefrontal cortex. PMID:25389398

  12. Wormholes, baby universes, and causality

    SciTech Connect

    Visser, M. )

    1990-02-15

    In this paper wormholes defined on a Minkowski signature manifold are considered, both at the classical and quantum levels. It is argued that causality in quantum gravity may best be imposed by restricting the functional integral to include only causal Lorentzian spacetimes. Subject to this assumption, one can put very tight constraints on the quantum behavior of wormholes, their cousins the baby universes, and topology-changing processes in general. Even though topology-changing processes are tightly constrained, this still allows very interesting geometrical (rather than topological) effects. In particular, the laboratory construction of baby universes is {ital not} prohibited provided that the umbilical cord'' is never cut. Methods for relaxing these causality constraints are also discussed.

  13. Causal reasoning with mental models.

    PubMed

    Khemlani, Sangeet S; Barbey, Aron K; Johnson-Laird, Philip N

    2014-01-01

    This paper outlines the model-based theory of causal reasoning. It postulates that the core meanings of causal assertions are deterministic and refer to temporally-ordered sets of possibilities: A causes B to occur means that given A, B occurs, whereas A enables B to occur means that given A, it is possible for B to occur. The paper shows how mental models represent such assertions, and how these models underlie deductive, inductive, and abductive reasoning yielding explanations. It reviews evidence both to corroborate the theory and to account for phenomena sometimes taken to be incompatible with it. Finally, it reviews neuroscience evidence indicating that mental models for causal inference are implemented within lateral prefrontal cortex.

  14. Information thermodynamics on causal networks.

    PubMed

    Ito, Sosuke; Sagawa, Takahiro

    2013-11-01

    We study nonequilibrium thermodynamics of complex information flows induced by interactions between multiple fluctuating systems. Characterizing nonequilibrium dynamics by causal networks (i.e., Bayesian networks), we obtain novel generalizations of the second law of thermodynamics and the fluctuation theorem, which include an informational quantity characterized by the topology of the causal network. Our result implies that the entropy production in a single system in the presence of multiple other systems is bounded by the information flow between these systems. We demonstrate our general result by a simple model of biochemical adaptation.

  15. Assessing dynamic spectral causality by lagged adaptive directed transfer function and instantaneous effect factor.

    PubMed

    Xu, Haojie; Lu, Yunfeng; Zhu, Shanan; He, Bin

    2014-07-01

    It is of significance to assess the dynamic spectral causality among physiological signals. Several practical estimators adapted from spectral Granger causality have been exploited to track dynamic causality based on the framework of time-varying multivariate autoregressive (tvMVAR) models. The nonzero covariance of the model's residuals has been used to describe the instantaneous effect phenomenon in some causality estimators. However, for the situations with Gaussian residuals in some autoregressive models, it is challenging to distinguish the directed instantaneous causality if the sufficient prior information about the "causal ordering" is missing. Here, we propose a new algorithm to assess the time-varying causal ordering of tvMVAR model under the assumption that the signals follow the same acyclic causal ordering for all time lags and to estimate the instantaneous effect factor (IEF) value in order to track the dynamic directed instantaneous connectivity. The time-lagged adaptive directed transfer function (ADTF) is also estimated to assess the lagged causality after removing the instantaneous effect. In this study, we first investigated the performance of the causal-ordering estimation algorithm and the accuracy of IEF value. Then, we presented the results of IEF and time-lagged ADTF method by comparing with the conventional ADTF method through simulations of various propagation models. Statistical analysis results suggest that the new algorithm could accurately estimate the causal ordering and give a good estimation of the IEF values in the Gaussian residual conditions. Meanwhile, the time-lagged ADTF approach is also more accurate in estimating the time-lagged dynamic interactions in a complex nervous system after extracting the instantaneous effect. In addition to the simulation studies, we applied the proposed method to estimate the dynamic spectral causality on real visual evoked potential (VEP) data in a human subject. Its usefulness in time

  16. Assessing Dynamic Spectral Causality by Lagged Adaptive Directed Transfer Function and Instantaneous Effect Factor

    PubMed Central

    Xu, Haojie; Lu, Yunfeng; Zhu, Shanan

    2014-01-01

    It is of significance to assess the dynamic spectral causality among physiological signals. Several practical estimators adapted from spectral Granger causality have been exploited to track dynamic causality based on the framework of time-varying multivariate autoregressive (tvMVAR) models. The non-zero covariance of the model’s residuals has been used to describe the instantaneous effect phenomenon in some causality estimators. However, for the situations with Gaussian residuals in some autoregressive models, it is challenging to distinguish the directed instantaneous causality if the sufficient prior information about the “causal ordering” is missing. Here, we propose a new algorithm to assess the time-varying causal ordering of tvMVAR model under the assumption that the signals follow the same acyclic causal ordering for all time lags and to estimate the instantaneous effect factor (IEF) value in order to track the dynamic directed instantaneous connectivity. The time-lagged adaptive directed transfer function (ADTF) is also estimated to assess the lagged causality after removing the instantaneous effect. In the present study, we firstly investigated the performance of the causal-ordering estimation algorithm and the accuracy of IEF value. Then, we presented the results of IEF and time-lagged ADTF method by comparing with the conventional ADTF method through simulations of various propagation models. Statistical analysis results suggest that the new algorithm could accurately estimate the causal ordering and give a good estimation of the IEF values in the Gaussian residual conditions. Meanwhile, the time-lagged ADTF approach is also more accurate in estimating the time-lagged dynamic interactions in a complex nervous system after extracting the instantaneous effect. In addition to the simulation studies, we applied the proposed method to estimate the dynamic spectral causality on real visual evoked potential (VEP) data in a human subject. Its usefulness in

  17. Recursive partitioning for heterogeneous causal effects

    PubMed Central

    Athey, Susan; Imbens, Guido

    2016-01-01

    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%. PMID:27382149

  18. Preventing low birth weight, child abuse, and school failure: the need for comprehensive, community-wide approaches.

    PubMed

    Chamberlin, R W

    1992-02-01

    Based on numerous examples from this country and abroad, we now have a reasonable idea of how we can reduce substantially the incidence of low-weight births, child abuse, adolescent pregnancy, school failure, and school dropout. The most effective long-term strategy appears to be the development of a comprehensive, coordinated, community-wide approach focused on preventing low- and medium-risk families from becoming high-risk as well as providing intensive services to those who already have reached a high-risk status. The best results can be obtained when all levels of government and the private sector work together. In this partnership, the best outcomes appear to result when the state and federal governments, private corporations, or both provide technical assistance, additional funding as needed, and help in setting program standards, and when the community maintains local control over establishing priorities and implementation strategies. However, to reach these goals and to maintain program support over the long time periods needed to show positive results (4 to 8 years), it is necessary to become skilled in social marketing techniques to turn program need into demand and to develop a strong local and statewide advocacy group to facilitate passage of needed legislation and prevent funding cutbacks. Pediatricians can modify their practices to make them more supportive to families and can work with other community leaders to bring about the changes in attitudes and about the changes in attitudes and funding priorities at the state and community levels that will be necessary to develop more effective preventive programs.

  19. Identifying tree crown delineation shapes and need for remediation on high resolution imagery using an evidence based approach

    NASA Astrophysics Data System (ADS)

    Leckie, Donald G.; Walsworth, Nicholas; Gougeon, François A.

    2016-04-01

    In order to fully realize the benefits of automated individual tree mapping for tree species, health, forest inventory attribution and forest management decision making, the tree delineations should be as good as possible. The concept of identifying poorly delineated tree crowns and suggesting likely types of remediation was investigated. Delineations (isolations or isols) were classified into shape types reflecting whether they were realistic tree shapes and the likely kind of remediation needed. Shape type was classified by an evidence based rules approach using primitives based on isol size, shape indices, morphology, the presence of local maxima, and matches with template models representing trees of different sizes. A test set containing 50,000 isols based on an automated tree delineation of 40 cm multispectral airborne imagery of a diverse temperate-boreal forest site was used. Isolations representing single trees or several trees were the focus, as opposed to cases where a tree is split into several isols. For eight shape classes from regular through to convolute, shape classification accuracy was in the order of 62%; simplifying to six classes accuracy was 83%. Shape type did give an indication of the type of remediation and there were 6% false alarms (i.e., isols classed as needing remediation but did not). Alternately, there were 5% omissions (i.e., isols of regular shape and not earmarked for remediation that did need remediation). The usefulness of the concept of identifying poor delineations in need of remediation was demonstrated and one suite of methods developed and shown to be effective.

  20. Causal Conceptions in Social Explanation and Moral Evaluation: A Historical Tour.

    PubMed

    Alicke, Mark D; Mandel, David R; Hilton, Denis J; Gerstenberg, Tobias; Lagnado, David A

    2015-11-01

    Understanding the causes of human behavior is essential for advancing one's interests and for coordinating social relations. The scientific study of how people arrive at such understandings or explanations has unfolded in four distinguishable epochs in psychology, each characterized by a different metaphor that researchers have used to represent how people think as they attribute causality and blame to other individuals. The first epoch was guided by an "intuitive scientist" metaphor, which emphasized whether observers perceived behavior to be caused by the unique tendencies of the actor or by common reactions to the requirements of the situation. This metaphor was displaced in the second epoch by an "intuitive lawyer" depiction that focused on the need to hold people responsible for their misdeeds. The third epoch was dominated by theories of counterfactual thinking, which conveyed a "person as reconstructor" approach that emphasized the antecedents and consequences of imagining alternatives to events, especially harmful ones. With the current upsurge in moral psychology, the fourth epoch emphasizes the moral-evaluative aspect of causal judgment, reflected in a "person as moralist" metaphor. By tracing the progression from the person-environment distinction in early attribution theories to present concerns with moral judgment, our goal is to clarify how causal constructs have been used, how they relate to one another, and what unique attributional problems each addresses.

  1. Hypothesizing and Refining Causal Models,

    DTIC Science & Technology

    1984-12-01

    the purposes of this research, it was critica ! to be able to represent a sequence of events, in which the learning program would look for causal... tlc sense because tliv imply random behavior. This is an oversimplified, but usc^ul telcological assumption about the nature of dependences in designed

  2. Causal Categories: Relativistically Interacting Processes

    NASA Astrophysics Data System (ADS)

    Coecke, Bob; Lal, Raymond

    2013-04-01

    A symmetric monoidal category naturally arises as the mathematical structure that organizes physical systems, processes, and composition thereof, both sequentially and in parallel. This structure admits a purely graphical calculus. This paper is concerned with the encoding of a fixed causal structure within a symmetric monoidal category: causal dependencies will correspond to topological connectedness in the graphical language. We show that correlations, either classical or quantum, force terminality of the tensor unit. We also show that well-definedness of the concept of a global state forces the monoidal product to be only partially defined, which in turn results in a relativistic covariance theorem. Except for these assumptions, at no stage do we assume anything more than purely compositional symmetric-monoidal categorical structure. We cast these two structural results in terms of a mathematical entity, which we call a causal category. We provide methods of constructing causal categories, and we study the consequences of these methods for the general framework of categorical quantum mechanics.

  3. Identity, causality, and pronoun ambiguity.

    PubMed

    Sagi, Eyal; Rips, Lance J

    2014-10-01

    This article looks at the way people determine the antecedent of a pronoun in sentence pairs, such as: Albert invited Ron to dinner. He spent hours cleaning the house. The experiment reported here is motivated by the idea that such judgments depend on reasoning about identity (e.g., the identity of the he who cleaned the house). Because the identity of an individual over time depends on the causal-historical path connecting the stages of the individual, the correct antecedent will also depend on causal connections. The experiment varied how likely it is that the event of the first sentence (e.g., the invitation) would cause the event of the second (the house cleaning) for each of the two individuals (the likelihood that if Albert invited Ron to dinner, this would cause Albert to clean the house, versus cause Ron to clean the house). Decisions about the antecedent followed causal likelihood. A mathematical model of causal identity accounted for most of the key aspects of the data from the individual sentence pairs.

  4. Need for cognition and desire for control as moderators of extrinsic reward effects: a person x situation approach to the study of intrinsic motivation.

    PubMed

    Thompson, E P; Chaiken, S; Hazlewood, J D

    1993-06-01

    Seventy-four Ss in extrinsic-reward or no-reward conditions completed a brainstorming task and then were left alone with the option to engage in additional versions of this task. If the Need for Cognition (NFC) Scale taps intrinsic motivation for effortful cognition (J. T. Cacioppo & R. E. Petty, 1982), the optional task engagement of high-NFCSs, but not low-NFCSs, should be undermined by extrinsic reward. Results confirmed this hypothesis, but regression analyses showed that NFC scores' moderation of reward effects was due to their covariation with scores on J. M. Burger and H. M. Cooper's (1979) Desire for Control Scale. The data suggest that (a) NFC involves intrinsic motivation for effortful cognitive processing, (b) NFC may predict such processing mainly in contexts with minimal extrinsic incentives for processing, and (c) control motivation may be related causally both to extrinsic undermining effects and to individual differences in NFC.

  5. An Empirical Approach to Ocean Color Data: Reducing Bias and the Need for Post-Launch Radiometric Re-Calibration

    NASA Technical Reports Server (NTRS)

    Gregg, Watson W.; Casey, Nancy W.; O'Reilly, John E.; Esaias, Wayne E.

    2009-01-01

    A new empirical approach is developed for ocean color remote sensing. Called the Empirical Satellite Radiance-In situ Data (ESRID) algorithm, the approach uses relationships between satellite water-leaving radiances and in situ data after full processing, i.e., at Level-3, to improve estimates of surface variables while relaxing requirements on post-launch radiometric re-calibration. The approach is evaluated using SeaWiFS chlorophyll, which is the longest time series of the most widely used ocean color geophysical product. The results suggest that ESRID 1) drastically reduces the bias of ocean chlorophyll, most impressively in coastal regions, 2) modestly improves the uncertainty, and 3) reduces the sensitivity of global annual median chlorophyll to changes in radiometric re-calibration. Simulated calibration errors of 1% or less produce small changes in global median chlorophyll (less than 2.7%). In contrast, the standard NASA algorithm set is highly sensitive to radiometric calibration: similar 1% calibration errors produce changes in global median chlorophyll up to nearly 25%. We show that 0.1% radiometric calibration error (about 1% in water-leaving radiance) is needed to prevent radiometric calibration errors from changing global annual median chlorophyll more than the maximum interannual variability observed in the SeaWiFS 9-year record (+/- 3%), using the standard method. This is much more stringent than the goal for SeaWiFS of 5% uncertainty for water leaving radiance. The results suggest ocean color programs might consider less emphasis of expensive efforts to improve post-launch radiometric re-calibration in favor of increased efforts to characterize in situ observations of ocean surface geophysical products. Although the results here are focused on chlorophyll, in principle the approach described by ESRID can be applied to any surface variable potentially observable by visible remote sensing.

  6. Causal impulse response for circular sources in viscous media

    PubMed Central

    Kelly, James F.; McGough, Robert J.

    2008-01-01

    The causal impulse response of the velocity potential for the Stokes wave equation is derived for calculations of transient velocity potential fields generated by circular pistons in viscous media. The causal Green’s function is numerically verified using the material impulse response function approach. The causal, lossy impulse response for a baffled circular piston is then calculated within the near field and the far field regions using expressions previously derived for the fast near field method. Transient velocity potential fields in viscous media are computed with the causal, lossy impulse response and compared to results obtained with the lossless impulse response. The numerical error in the computed velocity potential field is quantitatively analyzed for a range of viscous relaxation times and piston radii. Results show that the largest errors are generated in locations near the piston face and for large relaxation times, and errors are relatively small otherwise. Unlike previous frequency-domain methods that require numerical inverse Fourier transforms for the evaluation of the lossy impulse response, the present approach calculates the lossy impulse response directly in the time domain. The results indicate that this causal impulse response is ideal for time-domain calculations that simultaneously account for diffraction and quadratic frequency-dependent attenuation in viscous media. PMID:18397018

  7. Formalizing Neurath's ship: Approximate algorithms for online causal learning.

    PubMed

    Bramley, Neil R; Dayan, Peter; Griffiths, Thomas L; Lagnado, David A

    2017-04-01

    Higher-level cognition depends on the ability to learn models of the world. We can characterize this at the computational level as a structure-learning problem with the goal of best identifying the prevailing causal relationships among a set of relata. However, the computational cost of performing exact Bayesian inference over causal models grows rapidly as the number of relata increases. This implies that the cognitive processes underlying causal learning must be substantially approximate. A powerful class of approximations that focuses on the sequential absorption of successive inputs is captured by the Neurath's ship metaphor in philosophy of science, where theory change is cast as a stochastic and gradual process shaped as much by people's limited willingness to abandon their current theory when considering alternatives as by the ground truth they hope to approach. Inspired by this metaphor and by algorithms for approximating Bayesian inference in machine learning, we propose an algorithmic-level model of causal structure learning under which learners represent only a single global hypothesis that they update locally as they gather evidence. We propose a related scheme for understanding how, under these limitations, learners choose informative interventions that manipulate the causal system to help elucidate its workings. We find support for our approach in the analysis of 3 experiments. (PsycINFO Database Record

  8. Monitoring is not enough: on the need for a model-based approach to migratory bird management

    USGS Publications Warehouse

    Nichols, J.D.; Bonney, Rick; Pashley, David N.; Cooper, Robert; Niles, Larry

    2000-01-01

    Informed management requires information about system state and about effects of potential management actions on system state. Population monitoring can provide the needed information about system state, as well as information that can be used to investigate effects of management actions. Three methods for investigating effects of management on bird populations are (1) retrospective analysis, (2) formal experimentation and constrained-design studies, and (3) adaptive management. Retrospective analyses provide weak inferences, regardless of the quality of the monitoring data. The active use of monitoring data in experimental or constrained-design studies or in adaptive management is recommended. Under both approaches, learning occurs via the comparison of estimates from the monitoring program with predictions from competing management models.

  9. Identification of severely incinerated human remains: the need for a cooperative approach between forensic specialities. A case report.

    PubMed

    Bassed, Richard

    2003-10-01

    Positive identification of incinerated human remains can be a perplexing problem, especially when there is no genetic material remaining for DNA analysis. This paper illustrates the importance of a multi-disciplinary approach to the identification of such remains, and explores the processes involved in the various effects of heat upon human bone and teeth, and the implications this has for positive identification. A case study is presented to illustrate the various problems encountered and the importance of discovering comprehensive ante-mortem records of the deceased. It is submitted that forensic odontologists and anthropologists be included in the body recovery process, both to maximise the recovery of evidence, and to ensure that all possible avenues for positive identification are explored, so as to avoid the need to rely upon the less robust method of circumstantial identification.

  10. Causal Agency Theory: Reconceptualizing a Functional Model of Self-Determination

    ERIC Educational Resources Information Center

    Shogren, Karrie A.; Wehmeyer, Michael L.; Palmer, Susan B.; Forber-Pratt, Anjali J.; Little, Todd J.; Lopez, Shane

    2015-01-01

    This paper introduces Causal Agency Theory, an extension of the functional model of self-determination. Causal Agency Theory addresses the need for interventions and assessments pertaining to selfdetermination for all students and incorporates the significant advances in understanding of disability and in the field of positive psychology since the…

  11. Enhancing patient engagement in chronic disease self-management support initiatives in Australia: the need for an integrated approach.

    PubMed

    Jordan, Joanne E; Briggs, Andrew M; Brand, Caroline A; Osborne, Richard H

    2008-11-17

    Although emphasis on the prevention of chronic disease is important, governments in Australia need to balance this with continued assistance to the 77% of Australians reported to have at least one long-term medical condition. Self-management support is provided by health care and community services to enhance patients' ability to care for their chronic conditions in a cooperative framework. In Australia, there is a range of self-management support initiatives that have targeted patients (most notably, chronic disease self-management education programs) and health professionals (financial incentives, education and training). To date, there has been little coordination or integration of these self-management initiatives to enhance the patient-health professional clinical encounter. If self-management support is to work, there is a need to better understand the infrastructure, systems and training that are required to engage the key stakeholders - patients, carers, health professionals, and health care organisations. A coordinated approach is required in implementing these elements within existing and new health service models to enhance uptake and sustainability.

  12. Effect of measurement noise on Granger causality

    NASA Astrophysics Data System (ADS)

    Nalatore, Hariharan; N, Sasikumar; Rangarajan, Govindan

    2014-12-01

    Most of the signals recorded in experiments are inevitably contaminated by measurement noise. Hence, it is important to understand the effect of such noise on estimating causal relations between such signals. A primary tool for estimating causality is Granger causality. Granger causality can be computed by modeling the signal using a bivariate autoregressive (AR) process. In this paper, we greatly extend the previous analysis of the effect of noise by considering a bivariate AR process of general order p . From this analysis, we analytically obtain the dependence of Granger causality on various noise-dependent system parameters. In particular, we show that measurement noise can lead to spurious Granger causality and can suppress true Granger causality. These results are verified numerically. Finally, we show how true causality can be recovered numerically using the Kalman expectation maximization algorithm.

  13. Effect of measurement noise on Granger causality.

    PubMed

    Nalatore, Hariharan; Sasikumar, N; Rangarajan, Govindan

    2014-12-01

    Most of the signals recorded in experiments are inevitably contaminated by measurement noise. Hence, it is important to understand the effect of such noise on estimating causal relations between such signals. A primary tool for estimating causality is Granger causality. Granger causality can be computed by modeling the signal using a bivariate autoregressive (AR) process. In this paper, we greatly extend the previous analysis of the effect of noise by considering a bivariate AR process of general order p. From this analysis, we analytically obtain the dependence of Granger causality on various noise-dependent system parameters. In particular, we show that measurement noise can lead to spurious Granger causality and can suppress true Granger causality. These results are verified numerically. Finally, we show how true causality can be recovered numerically using the Kalman expectation maximization algorithm.

  14. Planning for climate change: The need for mechanistic systems-based approaches to study climate change impacts on diarrheal diseases.

    PubMed

    Mellor, Jonathan E; Levy, Karen; Zimmerman, Julie; Elliott, Mark; Bartram, Jamie; Carlton, Elizabeth; Clasen, Thomas; Dillingham, Rebecca; Eisenberg, Joseph; Guerrant, Richard; Lantagne, Daniele; Mihelcic, James; Nelson, Kara

    2016-04-01

    Increased precipitation and temperature variability as well as extreme events related to climate change are predicted to affect the availability and quality of water globally. Already heavily burdened with diarrheal diseases due to poor access to water, sanitation and hygiene facilities, communities throughout the developing world lack the adaptive capacity to sufficiently respond to the additional adversity caused by climate change. Studies suggest that diarrhea rates are positively correlated with increased temperature, and show a complex relationship with precipitation. Although climate change will likely increase rates of diarrheal diseases on average, there is a poor mechanistic understanding of the underlying disease transmission processes and substantial uncertainty surrounding current estimates. This makes it difficult to recommend appropriate adaptation strategies. We review the relevant climate-related mechanisms behind transmission of diarrheal disease pathogens and argue that systems-based mechanistic approaches incorporating human, engineered and environmental components are urgently needed. We then review successful systems-based approaches used in other environmental health fields and detail one modeling framework to predict climate change impacts on diarrheal diseases and design adaptation strategies.

  15. Planning for climate change: the need for mechanistic systems-based approaches to study climate change impacts on diarrheal diseases

    PubMed Central

    Levy, Karen; Zimmerman, Julie; Elliott, Mark; Bartram, Jamie; Carlton, Elizabeth; Clasen, Thomas; Dillingham, Rebecca; Eisenberg, Joseph; Guerrant, Richard; Lantagne, Daniele; Mihelcic, James; Nelson, Kara

    2016-01-01

    Increased precipitation and temperature variability as well as extreme events related to climate change are predicted to affect the availability and quality of water globally. Already heavily burdened with diarrheal diseases due to poor access to water, sanitation and hygiene facilities, communities throughout the developing world lack the adaptive capacity to sufficiently respond to the additional adversity caused by climate change. Studies suggest that diarrhea rates are positively correlated with increased temperature, and show a complex relationship with precipitation. Although climate change will likely increase rates of diarrheal diseases on average, there is a poor mechanistic understanding of the underlying disease transmission processes and substantial uncertainty surrounding current estimates. This makes it difficult to recommend appropriate adaptation strategies. We review the relevant climate-related mechanisms behind transmission of diarrheal disease pathogens and argue that systems-based mechanistic approaches incorporating human, engineered and environmental components are urgently needed. We then review successful systems-based approaches used in other environmental health fields and detail one modeling framework to predict climate change impacts on diarrheal diseases and design adaptation strategies. PMID:26799810

  16. Causality as individual essence: its bearing on synchronicity.

    PubMed

    Tougas, Cecile T

    2014-06-01

    Causality, time, and number are subjectively lived realities and need to be noticed as such. Fundamental to the wide range of living experience, they are also basic to scientific knowing. In this article I examine causality in relation to an article on synchronicity by Harald Atmanspacher and Wolfgang Fach. My examination is neither scientific nor metaphysical, but rather phenomenological, as it is a clarification of form as individual essence of a thing. This non-material form of an individual thing in the widest sense of the word 'thing' was rejected and so lost during modern seventeenth-century science but, renewed now, can help describe synchronicity. A commentary by William Willeford follows.

  17. Relating Granger causality to long-term causal effects.

    PubMed

    Smirnov, Dmitry A; Mokhov, Igor I

    2015-10-01

    In estimation of causal couplings between observed processes, it is important to characterize coupling roles at various time scales. The widely used Granger causality reflects short-term effects: it shows how strongly perturbations of a current state of one process affect near future states of another process, and it quantifies that via prediction improvement (PI) in autoregressive models. However, it is often more important to evaluate the effects of coupling on long-term statistics, e.g., to find out how strongly the presence of coupling changes the variance of a driven process as compared to an uncoupled case. No general relationships between Granger causality and such long-term effects are known. Here, we pose the problem of relating these two types of coupling characteristics, and we solve it for a class of stochastic systems. Namely, for overdamped linear oscillators, we rigorously derive that the above long-term effect is proportional to the short-term effects, with the proportionality coefficient depending on the prediction interval and relaxation times. We reveal that this coefficient is typically considerably greater than unity so that small normalized PI values may well correspond to quite large long-term effects of coupling. The applicability of the derived relationship to wider classes of systems, its limitations, and its value for further research are discussed. To give a real-world example, we analyze couplings between large-scale climatic processes related to sea surface temperature variations in equatorial Pacific and North Atlantic regions.

  18. Relating Granger causality to long-term causal effects

    NASA Astrophysics Data System (ADS)

    Smirnov, Dmitry A.; Mokhov, Igor I.

    2015-10-01

    In estimation of causal couplings between observed processes, it is important to characterize coupling roles at various time scales. The widely used Granger causality reflects short-term effects: it shows how strongly perturbations of a current state of one process affect near future states of another process, and it quantifies that via prediction improvement (PI) in autoregressive models. However, it is often more important to evaluate the effects of coupling on long-term statistics, e.g., to find out how strongly the presence of coupling changes the variance of a driven process as compared to an uncoupled case. No general relationships between Granger causality and such long-term effects are known. Here, we pose the problem of relating these two types of coupling characteristics, and we solve it for a class of stochastic systems. Namely, for overdamped linear oscillators, we rigorously derive that the above long-term effect is proportional to the short-term effects, with the proportionality coefficient depending on the prediction interval and relaxation times. We reveal that this coefficient is typically considerably greater than unity so that small normalized PI values may well correspond to quite large long-term effects of coupling. The applicability of the derived relationship to wider classes of systems, its limitations, and its value for further research are discussed. To give a real-world example, we analyze couplings between large-scale climatic processes related to sea surface temperature variations in equatorial Pacific and North Atlantic regions.

  19. When two become one: the limits of causality analysis of brain dynamics.

    PubMed

    Chicharro, Daniel; Ledberg, Anders

    2012-01-01

    Biological systems often consist of multiple interacting subsystems, the brain being a prominent example. To understand the functions of such systems it is important to analyze if and how the subsystems interact and to describe the effect of these interactions. In this work we investigate the extent to which the cause-and-effect framework is applicable to such interacting subsystems. We base our work on a standard notion of causal effects and define a new concept called natural causal effect. This new concept takes into account that when studying interactions in biological systems, one is often not interested in the effect of perturbations that alter the dynamics. The interest is instead in how the causal connections participate in the generation of the observed natural dynamics. We identify the constraints on the structure of the causal connections that determine the existence of natural causal effects. In particular, we show that the influence of the causal connections on the natural dynamics of the system often cannot be analyzed in terms of the causal effect of one subsystem on another. Only when the causing subsystem is autonomous with respect to the rest can this interpretation be made. We note that subsystems in the brain are often bidirectionally connected, which means that interactions rarely should be quantified in terms of cause-and-effect. We furthermore introduce a framework for how natural causal effects can be characterized when they exist. Our work also has important consequences for the interpretation of other approaches commonly applied to study causality in the brain. Specifically, we discuss how the notion of natural causal effects can be combined with Granger causality and Dynamic Causal Modeling (DCM). Our results are generic and the concept of natural causal effects is relevant in all areas where the effects of interactions between subsystems are of interest.

  20. Motivated Action Theory: A Formal Theory of Causal Reasoning.

    DTIC Science & Technology

    1991-12-01

    approaches to temporal reasoning, and their shortcomings, in light of this analysis. We propose a new system for causal reasoning, motivated action theory , which...builds upon causation as a crucial preference criterion. Motivated action theory solves the traditional problems of both forward and backward

  1. Achievement in Mother Tongue Literature: Some Strategies of Causal Analysis.

    ERIC Educational Resources Information Center

    Bulcock, Jeffrey W.

    Three stages of linear causal model building procedures (conceptual, main theory, and auxiliary theory) were used to examine the cultural and personality resources of individuals and their school-related skills as determinants of achievement in mother tongue literature. A path analytic approach was used to test a popular model of literature…

  2. The Importance of Qualitative Research for Causal Explanation in Education

    ERIC Educational Resources Information Center

    Maxwell, Joseph A.

    2012-01-01

    The concept of causation has long been controversial in qualitative research, and many qualitative researchers have rejected causal explanation as incompatible with an interpretivist or constructivist approach. This rejection conflates causation with the positivist "theory" of causation, and ignores an alternative understanding of causation,…

  3. Causality vs. Plausibility: Alternative Stances for Inquiry into Human Behavior. Draft.

    ERIC Educational Resources Information Center

    Guba, Egon G.; Lincoln, Yvonna S.

    Arguing that the concept of causality in human experience is archaic, unnecessary, and misleading, particularly in the social/behavioral sciences, a new plausibility approach is proposed for understanding relationships among entities. The epistemological history of causality includes positivist, deductive-nomological, essentialist, activity or…

  4. Regression Discontinuity Design: A Guide for Strengthening Causal Inference in HRD

    ERIC Educational Resources Information Center

    Chambers, Silvana

    2016-01-01

    Purpose: Regression discontinuity (RD) design is a sophisticated quasi-experimental approach used for inferring causal relationships and estimating treatment effects. This paper aims to educate human resource development (HRD) researchers and practitioners on the implementation of RD design as an ethical alternative for making causal claims about…

  5. On the relationship between the causal-inference and meta-analytic paradigms for the validation of surrogate endpoints.

    PubMed

    Alonso, Ariel; Van der Elst, Wim; Molenberghs, Geert; Buyse, Marc; Burzykowski, Tomasz

    2015-03-01

    The increasing cost of drug development has raised the demand for surrogate endpoints when evaluating new drugs in clinical trials. However, over the years, it has become clear that surrogate endpoints need to be statistically evaluated and deemed valid, before they can be used as substitutes of "true" endpoints in clinical studies. Nowadays, two paradigms, based on causal-inference and meta-analysis, dominate the scene. Nonetheless, although the literature emanating from these paradigms is wide, till now the relationship between them has largely been left unexplored. In the present work, we discuss the conceptual framework underlying both approaches and study the relationship between them using theoretical elements and the analysis of a real case study. Furthermore, we show that the meta-analytic approach can be embedded within a causal-inference framework on the one hand and that it can be heuristically justified why surrogate endpoints successfully evaluated using this approach will often be appealing from a causal-inference perspective as well, on the other. A newly developed and user friendly R package Surrogate is provided to carry out the evaluation exercise.

  6. Designing Effective Supports for Causal Reasoning

    ERIC Educational Resources Information Center

    Jonassen, David H.; Ionas, Ioan Gelu

    2008-01-01

    Causal reasoning represents one of the most basic and important cognitive processes that underpin all higher-order activities, such as conceptual understanding and problem solving. Hume called causality the "cement of the universe" [Hume (1739/2000). Causal reasoning is required for making predictions, drawing implications and…

  7. Representing Personal Determinants in Causal Structures.

    ERIC Educational Resources Information Center

    Bandura, Albert

    1984-01-01

    Responds to Staddon's critique of the author's earlier article and addresses issues raised by Staddon's (1984) alternative models of causality. The author argues that it is not the formalizability of causal processes that is the issue but whether cognitive determinants of behavior are reducible to past stimulus inputs in causal structures.…

  8. Constraints on Children's Judgments of Magical Causality

    ERIC Educational Resources Information Center

    Woolley, Jacqueline D.; Browne, Cheryl A.; Boerger, Elizabeth A.

    2006-01-01

    In 3 studies we addressed the operation of constraints on children's causal judgments. Our primary focus was whether children's beliefs about magical causality, specifically wishing, are constrained by features that govern the attribution of ordinary causality. In Experiment 1, children witnessed situations in which a confederate's wish appeared…

  9. Causal inference in economics and marketing.

    PubMed

    Varian, Hal R

    2016-07-05

    This is an elementary introduction to causal inference in economics written for readers familiar with machine learning methods. The critical step in any causal analysis is estimating the counterfactual-a prediction of what would have happened in the absence of the treatment. The powerful techniques used in machine learning may be useful for developing better estimates of the counterfactual, potentially improving causal inference.

  10. Causality Assessment in Pharmacovigilance: Still a Challenge.

    PubMed

    Ralph Edwards, I

    2017-02-28

    Causality in pharmacovigilance is a difficult and time consuming exercise. This paper presents the challenges in determining causation by drug therapy. The first is that causation is complex and needs to be viewed from the context of the patient treated, rather than the drug product. Multiple causal vectors should be considered if we are to tackle the many issues involved in, for example, medication error and the many other factors that lead to bad outcomes from therapy, including failure to recognise known risk factors. The aim of pharmacovigilance is not only a bureaucratic exercise in public health norms, but is mainly concerned with small minorities of statistical outliers-and even individuals-whose experiences from harms may together form messages about causation that will prevent further at-risk patients from exposure, or at least assist with earlier recognition of drug-related harm and better management of such harm. This requires more time, more data, more analysis and more patient and clinical involvement in reporting useful clinical detail. The paradigm shift back towards gathering more case data relating to possible causation can be selective and would not be just retrogressive, nor necessarily too costly. Greater transparency of hypotheses and availability of anonymised case data will enrol more expertise into evaluations and hypothesis testing, and the provision of more complete and useful information should reduce clinical burdens from bad patient outcomes as well as their overall costs to society.

  11. Emergent Geometry from Entropy and Causality

    NASA Astrophysics Data System (ADS)

    Engelhardt, Netta

    generalizations are discussed, both at the classical and perturbatively quantum limits. In particular, several No Go Theorems are proven, indicative of a conclusion that supplementary approaches or information may be necessary to recover the full spacetime geometry. Part II of this thesis involves the relation between geometry and causality, the property that information cannot travel faster than light. Requiring this of any quantum field theory results in constraints on string theory setups that are dual to quantum field theories via the AdS/CFT correspondence. At the level of perturbative quantum gravity, it is shown that causality in the field theory constraints the causal structure in the bulk. At the level of nonperturbative quantum string theory, we find that constraints on causal signals restrict the possible ways in which curvature singularities can be resolved in string theory. Finally, a new program of research is proposed for the construction of bulk geometry from the divergences of correlation functions in the dual field theory. This divergence structure is linked to the causal structure of the bulk and of the field theory.

  12. An Introduction to Causal Inference

    DTIC Science & Technology

    2009-11-02

    or new measurements. These tasks are managed well by standard statistical analysis so long as experimental conditions remain the same. Causal analysis...combines features of the structural equation models (SEM) used in economics and social science (Goldberger, 1973; Duncan, 1975), the potential-outcome...analysis which, by definition, are un- correlated with the regressors. The formers are part of physical reality (e.g., genetic factors, socio- economic

  13. Predicting the Cosmological Constant from the Causal Entropic Principle

    SciTech Connect

    Bousso, Raphael; Bousso, Raphael; Harnik, Roni; Kribs, Graham D.; Perez, Gilad

    2007-05-01

    We compute the expected value of the cosmological constant in our universe from the Causal Entropic Principle. Since observers must obey the laws of thermodynamics and causality, the principle asserts that physical parameters are most likely to be found in the range of values for which the total entropy production within a causally connected region is maximized. Despite the absence of more explicit anthropic criteria, the resulting probability distribution turns out to be in excellent agreement with observation. In particular, we find that dust heated by stars dominates the entropy production, demonstrating the remarkable power of this thermodynamic selection criterion. The alternative approach-weighting by the number of"observers per baryon" -- is less well-defined, requires problematic assumptions about the nature of observers, and yet prefers values larger than present experimental bounds.

  14. Determining causality and consequence of expression quantitative trait loci

    PubMed Central

    Battle, A.J.; Montgomery, S.B.

    2014-01-01

    Expression quantitative trait loci (eQTLs) are currently the most abundant and systematically-surveyed class of functional consequence for genetic variation. Recent genetic studies of gene expression have identified thousands of eQTLs in diverse tissue types for the majority of human genes. Application of this large eQTL catalogue provides an important resource for understanding the molecular basis of common genetic diseases. However, only now has both the availability of individuals with full genomes and corresponding advances in functional genomics provided the opportunity to dissect eQTLs to identify causal regulatory variants. Resolving the properties of such causal regulatory variants is improving understanding of the molecular mechanisms that influence traits and guiding the development of new genome-scale approaches to variant interpretation. In this review, we provide an overview of current computational and experimental methods for identifying causal regulatory variants and predicting their phenotypic consequences. PMID:24770875

  15. Structural equation modeling: building and evaluating causal models: Chapter 8

    USGS Publications Warehouse

    Grace, James B.; Scheiner, Samuel M.; Schoolmaster, Donald R.

    2015-01-01

    Scientists frequently wish to study hypotheses about causal relationships, rather than just statistical associations. This chapter addresses the question of how scientists might approach this ambitious task. Here we describe structural equation modeling (SEM), a general modeling framework for the study of causal hypotheses. Our goals are to (a) concisely describe the methodology, (b) illustrate its utility for investigating ecological systems, and (c) provide guidance for its application. Throughout our presentation, we rely on a study of the effects of human activities on wetland ecosystems to make our description of methodology more tangible. We begin by presenting the fundamental principles of SEM, including both its distinguishing characteristics and the requirements for modeling hypotheses about causal networks. We then illustrate SEM procedures and offer guidelines for conducting SEM analyses. Our focus in this presentation is on basic modeling objectives and core techniques. Pointers to additional modeling options are also given.

  16. Predicting the Cosmological Constant from the CausalEntropic Principle

    SciTech Connect

    Bousso, Raphael; Harnik, Roni; Kribs, Graham D.; Perez, Gilad

    2007-02-20

    We compute the expected value of the cosmological constant in our universe from the Causal Entropic Principle. Since observers must obey the laws of thermodynamics and causality, it asserts that physical parameters are most likely to be found in the range of values for which the total entropy production within a causally connected region is maximized. Despite the absence of more explicit anthropic criteria, the resulting probability distribution turns out to be in excellent agreement with observation. In particular, we find that dust heated by stars dominates the entropy production, demonstrating the remarkable power of this thermodynamic selection criterion. The alternative approach--weighting by the number of ''observers per baryon''--is less well-defined, requires problematic assumptions about the nature of observers, and yet prefers values larger than present experimental bounds.

  17. Statistical analysis of single-trial Granger causality spectra.

    PubMed

    Brovelli, Andrea

    2012-01-01

    Granger causality analysis is becoming central for the analysis of interactions between neural populations and oscillatory networks. However, it is currently unclear whether single-trial estimates of Granger causality spectra can be used reliably to assess directional influence. We addressed this issue by combining single-trial Granger causality spectra with statistical inference based on general linear models. The approach was assessed on synthetic and neurophysiological data. Synthetic bivariate data was generated using two autoregressive processes with unidirectional coupling. We simulated two hypothetical experimental conditions: the first mimicked a constant and unidirectional coupling, whereas the second modelled a linear increase in coupling across trials. The statistical analysis of single-trial Granger causality spectra, based on t-tests and linear regression, successfully recovered the underlying pattern of directional influence. In addition, we characterised the minimum number of trials and coupling strengths required for significant detection of directionality. Finally, we demonstrated the relevance for neurophysiology by analysing two local field potentials (LFPs) simultaneously recorded from the prefrontal and premotor cortices of a macaque monkey performing a conditional visuomotor task. Our results suggest that the combination of single-trial Granger causality spectra and statistical inference provides a valuable tool for the analysis of large-scale cortical networks and brain connectivity.

  18. Modeling of causality with metamaterials

    NASA Astrophysics Data System (ADS)

    Smolyaninov, Igor I.

    2013-02-01

    Hyperbolic metamaterials may be used to model a 2 + 1-dimensional Minkowski space-time in which the role of time is played by one of the spatial coordinates. When a metamaterial is built and illuminated with a coherent extraordinary laser beam, the stationary pattern of light propagation inside the metamaterial may be treated as a collection of particle world lines, which represents a complete ‘history’ of this 2 + 1-dimensional space-time. While this model may be used to build interesting space-time analogs, such as metamaterial ‘black holes’ and a metamaterial ‘big bang’, it lacks causality: since light inside the metamaterial may propagate back and forth along the ‘timelike’ spatial coordinate, events in the ‘future’ may affect events in the ‘past’. Here we demonstrate that a more sophisticated metamaterial model may fix this deficiency via breaking the mirror and temporal (PT) symmetries of the original model and producing one-way propagation along the ‘timelike’ spatial coordinate. The resulting 2 + 1-dimensional Minkowski space-time appears to be causal. This scenario may be considered as a metamaterial model of the Wheeler-Feynman absorber theory of causality.

  19. THE CAUSAL ANALYSIS / DIAGNOSIS DECISION ...

    EPA Pesticide Factsheets

    CADDIS is an on-line decision support system that helps investigators in the regions, states and tribes find, access, organize, use and share information to produce causal evaluations in aquatic systems. It is based on the US EPA's Stressor Identification process which is a formal method for identifying causes of impairments in aquatic systems. CADDIS 2007 increases access to relevant information useful for causal analysis and provides methods and tools that practitioners can use to analyze their own data. The new Candidate Cause section provides overviews of commonly encountered causes of impairments to aquatic systems: metals, sediments, nutrients, flow alteration, temperature, ionic strength, and low dissolved oxygen. CADDIS includes new Conceptual Models that illustrate the relationships from sources to stressors to biological effects. An Interactive Conceptual Model for phosphorus links the diagram with supporting literature citations. The new Analyzing Data section helps practitioners analyze their data sets and interpret and use those results as evidence within the USEPA causal assessment process. Downloadable tools include a graphical user interface statistical package (CADStat), and programs for use with the freeware R statistical package, and a Microsoft Excel template. These tools can be used to quantify associations between causes and biological impairments using innovative methods such as species-sensitivity distributions, biological inferenc

  20. Shades of Grey: The Need for a Multi-disciplinary Approach to Research Investigating Alcohol and Ageing

    PubMed Central

    Wilkinson, Celia; Dare, Julie

    2014-01-01

    This paper calls for an increase in multi-disciplinary research on the issue of alcohol and ageing, to ensure public health interventions reflect the complex and diverse needs of older drinkers. Older people (65+ years) represent a unique segment of the population; compared to adolescents and younger people, they are more likely to have a range of co-morbid conditions and be taking prescribed medication, and are more physiologically vulnerable to the effects of alcohol. This suggests that from a public health perspective, alcohol use by older people is problematic. However, as with younger people, alcohol use is closely associated with socialisation and social engagement. While social engagement is important at all stages of life, it is particularly critical as people age, when many of the formal social roles which provide a catalyst for social integration shift or are lost. Currently, however, there is little evidence of an integrated public health response to the complex issue of alcohol and ageing. That is, what is needed is a concurrent acknowledgement of the health problems that may be associated with contraindicated alcohol use, versus the potential health benefits that can accrue from social drinking. This will require a holistic rather than reductionist approach that integrates biomedical and social science insights to develop a more comprehensive and nuanced understanding of the implications of alcohol use amongst diverse populations of older people. Significance for public health With the rapid ageing of the global population and concerns about recent increases in the consumption of alcohol amongst older people, the issue of alcohol and ageing is becoming an important public health issue. However, there remains little research that adopts a holistic multi-disciplinary perspective. Such research is important and may offer the best way forward in terms of unravelling the complexity of competing risks and benefits associated with low to moderate drinking

  1. Causality in Psychiatry: A Hybrid Symptom Network Construct Model.

    PubMed

    Young, Gerald

    2015-01-01

    Causality or etiology in psychiatry is marked by standard biomedical, reductionistic models (symptoms reflect the construct involved) that inform approaches to nosology, or classification, such as in the DSM-5 [Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition; (1)]. However, network approaches to symptom interaction [i.e., symptoms are formative of the construct; e.g., (2), for posttraumatic stress disorder (PTSD)] are being developed that speak to bottom-up processes in mental disorder, in contrast to the typical top-down psychological construct approach. The present article presents a hybrid top-down, bottom-up model of the relationship between symptoms and mental disorder, viewing symptom expression and their causal complex as a reciprocally dynamic system with multiple levels, from lower-order symptoms in interaction to higher-order constructs affecting them. The hybrid model hinges on good understanding of systems theory in which it is embedded, so that the article reviews in depth non-linear dynamical systems theory (NLDST). The article applies the concept of emergent circular causality (3) to symptom development, as well. Conclusions consider that symptoms vary over several dimensions, including: subjectivity; objectivity; conscious motivation effort; and unconscious influences, and the degree to which individual (e.g., meaning) and universal (e.g., causal) processes are involved. The opposition between science and skepticism is a complex one that the article addresses in final comments.

  2. Experimental verification of an indefinite causal order

    PubMed Central

    Rubino, Giulia; Rozema, Lee A.; Feix, Adrien; Araújo, Mateus; Zeuner, Jonas M.; Procopio, Lorenzo M.; Brukner, Časlav; Walther, Philip

    2017-01-01

    Investigating the role of causal order in quantum mechanics has recently revealed that the causal relations of events may not be a priori well defined in quantum theory. Although this has triggered a growing interest on the theoretical side, creating processes without a causal order is an experimental task. We report the first decisive demonstration of a process with an indefinite causal order. To do this, we quantify how incompatible our setup is with a definite causal order by measuring a “causal witness.” This mathematical object incorporates a series of measurements that are designed to yield a certain outcome only if the process under examination is not consistent with any well-defined causal order. In our experiment, we perform a measurement in a superposition of causal orders—without destroying the coherence—to acquire information both inside and outside of a “causally nonordered process.” Using this information, we experimentally determine a causal witness, demonstrating by almost 7 SDs that the experimentally implemented process does not have a definite causal order. PMID:28378018

  3. Improving Causality Induction with Category Learning

    PubMed Central

    Wang, Zhihong; Shao, Zhiqing

    2014-01-01

    Causal relations are of fundamental importance for human perception and reasoning. According to the nature of causality, causality has explicit and implicit forms. In the case of explicit form, causal-effect relations exist at either clausal or discourse levels. The implicit causal-effect relations heavily rely on empirical analysis and evidence accumulation. This paper proposes a comprehensive causality extraction system (CL-CIS) integrated with the means of category-learning. CL-CIS considers cause-effect relations in both explicit and implicit forms and especially practices the relation between category and causality in computation. In elaborately designed experiments, CL-CIS is evaluated together with general causality analysis system (GCAS) and general causality analysis system with learning (GCAS-L), and it testified to its own capability and performance in construction of cause-effect relations. This paper confirms the expectation that the precision and coverage of causality induction can be remarkably improved by means of causal and category learning. PMID:24883419

  4. An integrated approach is needed for ecosystem based fisheries management: insights from ecosystem-level management strategy evaluation.

    PubMed

    Fulton, Elizabeth A; Smith, Anthony D M; Smith, David C; Johnson, Penelope

    2014-01-01

    An ecosystem approach is widely seen as a desirable goal for fisheries management but there is little consensus on what strategies or measures are needed to achieve it. Management strategy evaluation (MSE) is a tool that has been widely used to develop and test single species fisheries management strategies and is now being extended to support ecosystem based fisheries management (EBFM). We describe the application of MSE to investigate alternative strategies for achieving EBFM goals for a complex multispecies fishery in southeastern Australia. The study was undertaken as part of a stakeholder driven process to review and improve the ecological, economic and social performance of the fishery. An integrated management strategy, involving combinations of measures including quotas, gear controls and spatial management, performed best against a wide range of objectives and this strategy was subsequently adopted in the fishery, leading to marked improvements in performance. Although particular to one fishery, the conclusion that an integrated package of measures outperforms single focus measures we argue is likely to apply widely in fisheries that aim to achieve EBFM goals.

  5. An Integrated Approach Is Needed for Ecosystem Based Fisheries Management: Insights from Ecosystem-Level Management Strategy Evaluation

    PubMed Central

    Fulton, Elizabeth A.; Smith, Anthony D. M.; Smith, David C.; Johnson, Penelope

    2014-01-01

    An ecosystem approach is widely seen as a desirable goal for fisheries management but there is little consensus on what strategies or measures are needed to achieve it. Management strategy evaluation (MSE) is a tool that has been widely used to develop and test single species fisheries management strategies and is now being extended to support ecosystem based fisheries management (EBFM). We describe the application of MSE to investigate alternative strategies for achieving EBFM goals for a complex multispecies fishery in southeastern Australia. The study was undertaken as part of a stakeholder driven process to review and improve the ecological, economic and social performance of the fishery. An integrated management strategy, involving combinations of measures including quotas, gear controls and spatial management, performed best against a wide range of objectives and this strategy was subsequently adopted in the fishery, leading to marked improvements in performance. Although particular to one fishery, the conclusion that an integrated package of measures outperforms single focus measures we argue is likely to apply widely in fisheries that aim to achieve EBFM goals. PMID:24454722

  6. Training and Certification for Domestic Violence Service Providers: The Need for a National Standard Curriculum and Training Approach.

    PubMed

    Stover, Carla Smith; Lent, Kimberly

    2014-04-01

    Domestic violence (DV) continues to constitute an enormous public health problem in the United States. Knowledge and understanding of the complexities involved in DV has grown significantly in recent years revealing a need for providers who have broad training in a variety of legal, safety, developmental, and clinical issues that face families impacted by DV. This paper reviews current approaches to training and the ability of such methods to adequately prepare providers. There are no national standards for providers at any level from DV advocates to batterer interventionists, to clinicians with the required hours of training in most states at an alarmingly low level. Few states require cross training for those working as victim advocates or batterer interventionists. The systems that currently provide segregated and limited training create silos of service that are less effective. A proposed set of standards and training guidelines are proposed for DV advocates, batterer interventionists, and clinicians along with a discussion of the implications of such standards for the field.

  7. A novel approach to quantitating leukemia fusion transcripts by qRT-PCR without the need for standard curves.

    PubMed

    Schumacher, Jonathan A; Scott Reading, N; Szankasi, Philippe; Matynia, Anna P; Kelley, Todd W

    2015-08-01

    Acute myeloid leukemia patients with recurrent cytogenetic abnormalities including inv(16);CBFB-MYH11 and t(15;17);PML-RARA may be assessed by monitoring the levels of the corresponding abnormal fusion transcripts by quantitative reverse transcription-PCR (qRT-PCR). Such testing is important for evaluating the response to therapy and for the detection of early relapse. Existing qRT-PCR methods are well established and in widespread use in clinical laboratories but they are laborious and require the generation of standard curves. Here, we describe a new method to quantitate fusion transcripts in acute myeloid leukemia by qRT-PCR without the need for standard curves. Our approach uses a plasmid calibrator containing both a fusion transcript sequence and a reference gene sequence, representing a perfect normalized copy number (fusion transcript copy number/reference gene transcript copy number; NCN) of 1.0. The NCN of patient specimens can be calculated relative to that of the single plasmid calibrator using experimentally derived PCR efficiency values. We compared the data obtained using the plasmid calibrator method to commercially available assays using standard curves and found that the results obtained by both methods are comparable over a broad range of values with similar sensitivities. Our method has the advantage of simplicity and is therefore lower in cost and may be less subject to errors that may be introduced during the generation of standard curves.

  8. Too Much or Not Enough? An Examination of Special Education Provision and School District Leaders' Perceptions of Current Needs and Common Approaches

    ERIC Educational Resources Information Center

    Cameron, David Lansing

    2016-01-01

    The purpose of this study was to examine the relationship between special education provision in Norway and school district leaders' perspectives regarding (a) the need for special education and (b) the importance and prevalence of integrated and segregated approaches. Findings indicate that the percentage of students perceived as being in need of…

  9. Norms and customs: causally important or causally impotent?

    PubMed

    Jones, Todd

    2010-01-01

    In this article, I argue that norms and customs, despite frequently being described as being causes of behavior in the social sciences and ordinary conversation, cannot really cause behavior. Terms like "norms" and the like seem to refer to philosophically disreputable disjunctive properties. More problematically, even if they do not, or even if there can be disjunctive properties after all, I argue that norms and customs still cannot cause behavior. The social sciences would be better off without referring to properties like norms and customs as if they could be causal.

  10. The causal explanatory functions of medical diagnoses.

    PubMed

    Maung, Hane Htut

    2017-02-01

    Diagnoses in medicine are often taken to serve as explanations of patients' symptoms and signs. This article examines how they do so. I begin by arguing that although some instances of diagnostic explanation can be formulated as covering law arguments, they are explanatory neither in virtue of their argumentative structures nor in virtue of general regularities between diagnoses and clinical presentations. I then consider the theory that medical diagnoses explain symptoms and signs by identifying their actual causes in particular cases. While I take this to be largely correct, I argue that for a diagnosis to function as a satisfactory causal explanation of a patient's symptoms and signs, it also needs to be supplemented by understanding the mechanisms by which the identified cause produces the symptoms and signs. This mechanistic understanding comes not from the diagnosis itself, but rather from the theoretical framework within which the physician operates.

  11. Does partial Granger causality really eliminate the influence of exogenous inputs and latent variables?

    PubMed

    Roelstraete, Bjorn; Rosseel, Yves

    2012-04-30

    Partial Granger causality was introduced by Guo et al. (2008) who showed that it could better eliminate the influence of latent variables and exogenous inputs than conditional G-causality. In the recent literature we can find some reviews and applications of this type of Granger causality (e.g. Smith et al., 2011; Bressler and Seth, 2010; Barrett et al., 2010). These articles apparently do not take into account a serious flaw in the original work on partial G-causality, being the negative F values that were reported and even proven to be plausible. In our opinion, this undermines the credibility of the obtained results and thus the validity of the approach. Our study is aimed to further validate partial G-causality and to find an answer why negative partial Granger causality estimates were reported. Time series were simulated from the same toy model as used in the original paper and partial and conditional causal measures were compared in the presence of confounding variables. Inference was done parametrically and using non-parametric block bootstrapping. We counter the proof that partial Granger F values can be negative, but the main conclusion of the original article remains. In the presence of unknown latent and exogenous influences, it appears that partial G-causality will better eliminate their influence than conditional G-causality, at least when non-parametric inference is used.

  12. Algorithms of causal inference for the analysis of effective connectivity among brain regions

    PubMed Central

    Chicharro, Daniel; Panzeri, Stefano

    2014-01-01

    In recent years, powerful general algorithms of causal inference have been developed. In particular, in the framework of Pearl’s causality, algorithms of inductive causation (IC and IC*) provide a procedure to determine which causal connections among nodes in a network can be inferred from empirical observations even in the presence of latent variables, indicating the limits of what can be learned without active manipulation of the system. These algorithms can in principle become important complements to established techniques such as Granger causality and Dynamic Causal Modeling (DCM) to analyze causal influences (effective connectivity) among brain regions. However, their application to dynamic processes has not been yet examined. Here we study how to apply these algorithms to time-varying signals such as electrophysiological or neuroimaging signals. We propose a new algorithm which combines the basic principles of the previous algorithms with Granger causality to obtain a representation of the causal relations suited to dynamic processes. Furthermore, we use graphical criteria to predict dynamic statistical dependencies between the signals from the causal structure. We show how some problems for causal inference from neural signals (e.g., measurement noise, hemodynamic responses, and time aggregation) can be understood in a general graphical approach. Focusing on the effect of spatial aggregation, we show that when causal inference is performed at a coarser scale than the one at which the neural sources interact, results strongly depend on the degree of integration of the neural sources aggregated in the signals, and thus characterize more the intra-areal properties than the interactions among regions. We finally discuss how the explicit consideration of latent processes contributes to understand Granger causality and DCM as well as to distinguish functional and effective connectivity. PMID:25071541

  13. Lightweight causal and atomic group multicast

    NASA Technical Reports Server (NTRS)

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

    1991-01-01

    The ISIS toolkit is a distributed programming environment based on support for virtually synchronous process groups and group communication. A suite of protocols is presented to support this model. The approach revolves around a multicast primitive, called CBCAST, which implements a fault-tolerant, causally ordered message delivery. This primitive can be used directly or extended into a totally ordered multicast primitive, called ABCAST. It normally delivers messages immediately upon reception, and imposes a space overhead proportional to the size of the groups to which the sender belongs, usually a small number. It is concluded that process groups and group communication can achieve performance and scaling comparable to that of a raw message transport layer. This finding contradicts the widespread concern that this style of distributed computing may be unacceptably costly.

  14. Causal Dynamical Triangulations in Four Dimensions

    NASA Astrophysics Data System (ADS)

    Görlich, Andrzej

    2011-11-01

    Recent results obtained within a non-perturbative approach to quantum gravity based on the method of four-dimensional Causal Dynamical Triangulations are described. The phase diagram of the model consists of three phases. In the physically most interesting phase, the time-translational symmetry is spontaneously broken. Calculations of expectation values required introducing procedures taking into account the inhomogeneity of configurations. It was shown that the dynamically emerged four-dimensional background geometry corresponds to a Euclidean de Sitter space and reveals no fractality at large distances. Measurements of the covariance matrix of scale factor fluctuations allowed to reconstruct the effective action, which remained in agreement with the discrete minisuperspace action. Values of the Hausdorff dimension and spectral dimension of three-dimensional spatial slices suggest their fractal nature, which was confirmed by a direct analysis of triangulation structure. The Monte Carlo algorithm used to obtain presented results is described.

  15. Mediation and causality at the individual level.

    PubMed

    Bergman, Lars R

    2009-09-01

    Within a person-oriented research paradigm the focus is on individuals characterized by patterns of information that are regarded as indivisible wholes. It is then not sufficient to carry out standard variable-oriented mediation analysis. The procedure suggested by von Eye, Mun, and Mair (2009) for pattern-oriented mediation analysis is much better aligned to this person-oriented framework. An important new feature in their approach is that it can detect mediator configurations that prohibit predictor and outcome connections at a pattern level. Two extensions of their procedure are suggested, namely (1) the use of cluster analysis to arrive at the categories and (2) the use of other models for estimating the expected frequencies. It is pointed out that in their context a functional relations perspective might be more relevant than the standard causality perspective.

  16. Equity Theory Ratios as Causal Schemas

    PubMed Central

    Arvanitis, Alexios; Hantzi, Alexandra

    2016-01-01

    Equity theory approaches justice evaluations based on ratios of exchange inputs to exchange outcomes. Situations are evaluated as just if ratios are equal and unjust if unequal. We suggest that equity ratios serve a more fundamental cognitive function than the evaluation of justice. More particularly, we propose that they serve as causal schemas for exchange outcomes, that is, they assist in determining whether certain outcomes are caused by inputs of other people in the context of an exchange process. Equality or inequality of ratios in this sense points to an exchange process. Indeed, Study 1 shows that different exchange situations, such as disproportional or balanced proportional situations, create perceptions of give-and-take on the basis of equity ratios. Study 2 shows that perceptions of justice are based more on communicatively accepted rules of interaction than equity-based evaluations, thereby offering a distinction between an attribution and an evaluation cognitive process for exchange outcomes. PMID:27594846

  17. The discourse of causal explanations in school science

    NASA Astrophysics Data System (ADS)

    Slater, Tammy Jayne Anne

    Researchers and educators working from a systemic functional linguistic perspective have provided a body of work on science discourse which offers an excellent starting point for examining the linguistic aspects of the development of causal discourse in school science, discourse which Derewianka (1995) claimed is critical to success in secondary school. No work has yet described the development of causal language by identifying the linguistic features present in oral discourse or by comparing the causal discourse of native and non-native (ESL) speakers of English. The current research responds to this gap by examining the oral discourse collected from ESL and non-ESL students at the primary and high school grades. Specifically, it asks the following questions: (1) How do the teachers and students in these four contexts develop causal explanations and their relevant taxonomies through classroom interactions? (2) What are the causal discourse features being used by the students in these four contexts to construct oral causal explanations? The findings of the social practice analysis showed that the teachers in the four contexts differed in their approaches to teaching, with the primary school mainstream teacher focusing largely on the hands-on practice , the primary school ESL teacher moving from practice to theory, the high school mainstream teacher moving from theory to practice, and the high school ESL teacher relying primarily on theory. The findings from the quantitative, small corpus approach suggest that the developmental path of cause which has been identified in the writing of experts shows up not only in written texts but also in the oral texts which learners construct. Moreover, this move appears when the discourse of high school ESL and non-ESL students is compared, suggesting a developmental progression in the acquisition of these features by these students. The findings also reveal that the knowledge constructed, as shown by the concept maps created

  18. A hierarchical causal taxonomy of psychopathology across the life span.

    PubMed

    Lahey, Benjamin B; Krueger, Robert F; Rathouz, Paul J; Waldman, Irwin D; Zald, David H

    2017-02-01

    We propose a taxonomy of psychopathology based on patterns of shared causal influences identified in a review of multivariate behavior genetic studies that distinguish genetic and environmental influences that are either common to multiple dimensions of psychopathology or unique to each dimension. At the phenotypic level, first-order dimensions are defined by correlations among symptoms; correlations among first-order dimensions similarly define higher-order domains (e.g., internalizing or externalizing psychopathology). We hypothesize that the robust phenotypic correlations among first-order dimensions reflect a hierarchy of increasingly specific etiologic influences. Some nonspecific etiologic factors increase risk for all first-order dimensions of psychopathology to varying degrees through a general factor of psychopathology. Other nonspecific etiologic factors increase risk only for all first-order dimensions within a more specific higher-order domain. Furthermore, each first-order dimension has its own unique causal influences. Genetic and environmental influences common to family members tend to be nonspecific, whereas environmental influences unique to each individual are more dimension-specific. We posit that these causal influences on psychopathology are moderated by sex and developmental processes. This causal taxonomy also provides a novel framework for understanding the heterogeneity of each first-order dimension: Different persons exhibiting similar symptoms may be influenced by different combinations of etiologic influences from each of the 3 levels of the etiologic hierarchy. Furthermore, we relate the proposed causal taxonomy to transdimensional psychobiological processes, which also impact the heterogeneity of each psychopathology dimension. This causal taxonomy implies the need for changes in strategies for studying the etiology, psychobiology, prevention, and treatment of psychopathology. (PsycINFO Database Record

  19. Inferring connectivity in networked dynamical systems: Challenges using Granger causality

    NASA Astrophysics Data System (ADS)

    Lusch, Bethany; Maia, Pedro D.; Kutz, J. Nathan

    2016-09-01

    Determining the interactions and causal relationships between nodes in an unknown networked dynamical system from measurement data alone is a challenging, contemporary task across the physical, biological, and engineering sciences. Statistical methods, such as the increasingly popular Granger causality, are being broadly applied for data-driven discovery of connectivity in fields from economics to neuroscience. A common version of the algorithm is called pairwise-conditional Granger causality, which we systematically test on data generated from a nonlinear model with known causal network structure. Specifically, we simulate networked systems of Kuramoto oscillators and use the Multivariate Granger Causality Toolbox to discover the underlying coupling structure of the system. We compare the inferred results to the original connectivity for a wide range of parameters such as initial conditions, connection strengths, community structures, and natural frequencies. Our results show a significant systematic disparity between the original and inferred network, unless the true structure is extremely sparse or dense. Specifically, the inferred networks have significant discrepancies in the number of edges and the eigenvalues of the connectivity matrix, demonstrating that they typically generate dynamics which are inconsistent with the ground truth. We provide a detailed account of the dynamics for the Erdős-Rényi network model due to its importance in random graph theory and network science. We conclude that Granger causal methods for inferring network structure are highly suspect and should always be checked against a ground truth model. The results also advocate the need to perform such comparisons with any network inference method since the inferred connectivity results appear to have very little to do with the ground truth system.

  20. Inferring connectivity in networked dynamical systems: Challenges using Granger causality.

    PubMed

    Lusch, Bethany; Maia, Pedro D; Kutz, J Nathan

    2016-09-01

    Determining the interactions and causal relationships between nodes in an unknown networked dynamical system from measurement data alone is a challenging, contemporary task across the physical, biological, and engineering sciences. Statistical methods, such as the increasingly popular Granger causality, are being broadly applied for data-driven discovery of connectivity in fields from economics to neuroscience. A common version of the algorithm is called pairwise-conditional Granger causality, which we systematically test on data generated from a nonlinear model with known causal network structure. Specifically, we simulate networked systems of Kuramoto oscillators and use the Multivariate Granger Causality Toolbox to discover the underlying coupling structure of the system. We compare the inferred results to the original connectivity for a wide range of parameters such as initial conditions, connection strengths, community structures, and natural frequencies. Our results show a significant systematic disparity between the original and inferred network, unless the true structure is extremely sparse or dense. Specifically, the inferred networks have significant discrepancies in the number of edges and the eigenvalues of the connectivity matrix, demonstrating that they typically generate dynamics which are inconsistent with the ground truth. We provide a detailed account of the dynamics for the Erdős-Rényi network model due to its importance in random graph theory and network science. We conclude that Granger causal methods for inferring network structure are highly suspect and should always be checked against a ground truth model. The results also advocate the need to perform such comparisons with any network inference method since the inferred connectivity results appear to have very little to do with the ground truth system.

  1. How prescriptive norms influence causal inferences.

    PubMed

    Samland, Jana; Waldmann, Michael R

    2016-11-01

    Recent experimental findings suggest that prescriptive norms influence causal inferences. The cognitive mechanism underlying this finding is still under debate. We compare three competing theories: The culpable control model of blame argues that reasoners tend to exaggerate the causal influence of norm-violating agents, which should lead to relatively higher causal strength estimates for these agents. By contrast, the counterfactual reasoning account of causal selection assumes that norms do not alter the representation of the causal model, but rather later causal selection stages. According to this view, reasoners tend to preferentially consider counterfactual states of abnormal rather than normal factors, which leads to the choice of the abnormal factor in a causal selection task. A third view, the accountability hypothesis, claims that the effects of prescriptive norms are generated by the ambiguity of the causal test question. Asking whether an agent is a cause can be understood as a request to assess her causal contribution but also her moral accountability. According to this theory norm effects on causal selection are mediated by accountability judgments that are not only sensitive to the abnormality of behavior but also to mitigating factors, such as intentionality and knowledge of norms. Five experiments are presented that favor the accountability account over the two alternative theories.

  2. Space and time in perceptual causality.

    PubMed

    Straube, Benjamin; Chatterjee, Anjan

    2010-01-01

    Inferring causality is a fundamental feature of human cognition that allows us to theorize about and predict future states of the world. Michotte suggested that humans automatically perceive causality based on certain perceptual features of events. However, individual differences in judgments of perceptual causality cast doubt on Michotte's view. To gain insights in the neural basis of individual difference in the perception of causality, our participants judged causal relationships in animations of a blue ball colliding with a red ball (a launching event) while fMRI-data were acquired. Spatial continuity and temporal contiguity were varied parametrically in these stimuli. We did not find consistent brain activation differences between trials judged as caused and those judged as non-caused, making it unlikely that humans have universal instantiation of perceptual causality in the brain. However, participants were slower to respond to and showed greater neural activity for violations of causality, suggesting that humans are biased to expect causal relationships when moving objects appear to interact. Our participants demonstrated considerable individual differences in their sensitivity to spatial and temporal characteristics in perceiving causality. These qualitative differences in sensitivity to time or space in perceiving causality were instantiated in individual differences in activation of the left basal ganglia or right parietal lobe, respectively. Thus, the perception that the movement of one object causes the movement of another is triggered by elemental spatial and temporal sensitivities, which themselves are instantiated in specific distinct neural networks.

  3. Measuring causal perception: connections to representational momentum?

    PubMed

    Choi, Hoon; Scholl, Brian J

    2006-01-01

    In a collision between two objects, we can perceive not only low-level properties, such as color and motion, but also the seemingly high-level property of causality. It has proven difficult, however, to measure causal perception in a quantitatively rigorous way which goes beyond perceptual reports. Here we focus on the possibility of measuring perceived causality using the phenomenon of representational momentum (RM). Recent studies suggest a relationship between causal perception and RM, based on the fact that RM appears to be attenuated for causally 'launched' objects. This is explained by appeal to the visual expectation that a 'launched' object is inert and thus should eventually cease its movement after a collision, without a source of self-propulsion. We first replicated these demonstrations, and then evaluated this alleged connection by exploring RM for different types of displays, including the contrast between causal launching and non-causal 'passing'. These experiments suggest that the RM-attenuation effect is not a pure measure of causal perception, but rather may reflect lower-level spatiotemporal correlates of only some causal displays. We conclude by discussing the strengths and pitfalls of various methods of measuring causal perception.

  4. Targeted Maximum Likelihood Estimation for Causal Inference in Observational Studies.

    PubMed

    Schuler, Megan S; Rose, Sherri

    2017-01-01

    Estimation of causal effects using observational data continues to grow in popularity in the epidemiologic literature. While many applications of causal effect estimation use propensity score methods or G-computation, targeted maximum likelihood estimation (TMLE) is a well-established alternative method with desirable statistical properties. TMLE is a doubly robust maximum-likelihood-based approach that includes a secondary "targeting" step that optimizes the bias-variance tradeoff for the target parameter. Under standard causal assumptions, estimates can be interpreted as causal effects. Because TMLE has not been as widely implemented in epidemiologic research, we aim to provide an accessible presentation of TMLE for applied researchers. We give step-by-step instructions for using TMLE to estimate the average treatment effect in the context of an observational study. We discuss conceptual similarities and differences between TMLE and 2 common estimation approaches (G-computation and inverse probability weighting) and present findings on their relative performance using simulated data. Our simulation study compares methods under parametric regression misspecification; our results highlight TMLE's property of double robustness. Additionally, we discuss best practices for TMLE implementation, particularly the use of ensembled machine learning algorithms. Our simulation study demonstrates all methods using super learning, highlighting that incorporation of machine learning may outperform parametric regression in observational data settings.

  5. Wiener-Granger causality: a well established methodology.

    PubMed

    Bressler, Steven L; Seth, Anil K

    2011-09-15

    For decades, the main ways to study the effect of one part of the nervous system upon another have been either to stimulate or lesion the first part and investigate the outcome in the second. This article describes a fundamentally different approach to identifying causal connectivity in neuroscience: a focus on the predictability of ongoing activity in one part from that in another. This approach was made possible by a new method that comes from the pioneering work of Wiener (1956) and Granger (1969). The Wiener-Granger method, unlike stimulation and ablation, does not require direct intervention in the nervous system. Rather, it relies on the estimation of causal statistical influences between simultaneously recorded neural time series data, either in the absence of identifiable behavioral events or in the context of task performance. Causality in the Wiener-Granger sense is based on the statistical predictability of one time series that derives from knowledge of one or more others. This article defines Wiener-Granger Causality, discusses its merits and limitations in neuroscience, and outlines recent developments in its implementation.

  6. Mono-Causal and Multi-Causal Theories of Disease: How to Think Virally and Socially about the Aetiology of AIDS.

    PubMed

    Furman, Katherine

    2017-04-04

    In this paper, I utilise the tools of analytic philosophy to amalgamate mono-causal and multi-causal theories of disease. My aim is to better integrate viral and socio-economic explanations of AIDS in particular, and to consider how the perceived divide between mono-causal and multi-causal theories played a role in the tragedy of AIDS denialism in South Africa in the early 2000s. Currently, there is conceptual ambiguity surrounding the relationship between mono-causal and multi-causal theories in biomedicine and epidemiology. Mono-causal theories focus on single, typically microbial, sources of illness and are most concerned with infectious diseases. By contrast, multi-causal theories allow for multiple factors to underpin a disease's aetiology, including socio-economic and behavioural factors, and they usually focus on chronic non-communicable diseases. However, if these theories are taken to be strictly distinct, this prevents the inclusion of both microbial and socio-economic factors in a single explanation of any particular disease. This strict distinction became a problem when trying to explain the disproportionate prevalence of AIDS in southern Africa and ultimately contributed to the tragedy of AIDS denialism in South Africa. In tandem with viewing how the perceived divide between multi-causal and mono-causal theories underpinned AIDS denialism, I examine Thabo Mbeki's specific role, while acknowledging that AIDS is being deprioritised on a broader international level. Overall, I will demonstrate that any long-term plan to eliminate AIDS will require viral and socio-economic factors to be considered simultaneously and that such a theoretical approach requires a clearer understanding of the underlying concepts of disease aetiology.

  7. Causal diagrams in systems epidemiology

    PubMed Central

    2012-01-01

    Methods of diagrammatic modelling have been greatly developed in the past two decades. Outside the context of infectious diseases, systematic use of diagrams in epidemiology has been mainly confined to the analysis of a single link: that between a disease outcome and its proximal determinant(s). Transmitted causes ("causes of causes") tend not to be systematically analysed. The infectious disease epidemiology modelling tradition models the human population in its environment, typically with the exposure-health relationship and the determinants of exposure being considered at individual and group/ecological levels, respectively. Some properties of the resulting systems are quite general, and are seen in unrelated contexts such as biochemical pathways. Confining analysis to a single link misses the opportunity to discover such properties. The structure of a causal diagram is derived from knowledge about how the world works, as well as from statistical evidence. A single diagram can be used to characterise a whole research area, not just a single analysis - although this depends on the degree of consistency of the causal relationships between different populations - and can therefore be used to integrate multiple datasets. Additional advantages of system-wide models include: the use of instrumental variables - now emerging as an important technique in epidemiology in the context of mendelian randomisation, but under-used in the exploitation of "natural experiments"; the explicit use of change models, which have advantages with respect to inferring causation; and in the detection and elucidation of feedback. PMID:22429606

  8. Comparison theorems for causal diamonds

    NASA Astrophysics Data System (ADS)

    Berthiere, Clément; Gibbons, Gary; Solodukhin, Sergey N.

    2015-09-01

    We formulate certain inequalities for the geometric quantities characterizing causal diamonds in curved and Minkowski spacetimes. These inequalities involve the redshift factor which, as we show explicitly in the spherically symmetric case, is monotonic in the radial direction, and it takes its maximal value at the center. As a by-product of our discussion we rederive Bishop's inequality without assuming the positivity of the spatial Ricci tensor. We then generalize our considerations to arbitrary, static and not necessarily spherically symmetric, asymptotically flat spacetimes. In the case of spacetimes with a horizon our generalization involves the so-called domain of dependence. The respective volume, expressed in terms of the duration measured by a distant observer compared with the volume of the domain in Minkowski spacetime, exhibits behaviors which differ if d =4 or d >4 . This peculiarity of four dimensions is due to the logarithmic subleading term in the asymptotic expansion of the metric near infinity. In terms of the invariant duration measured by a comoving observer associated with the diamond we establish an inequality which is universal for all d . We suggest some possible applications of our results including comparison theorems for entanglement entropy, causal set theory, and fundamental limits on computation.

  9. How can we cope with the complexity of the environment? A "Learning by modelling" approach using qualitative reasoning for developing causal models and simulations with focus on Sustainable River Catchment Management

    NASA Astrophysics Data System (ADS)

    Poppe, Michaela; Zitek, Andreas; Salles, Paulo; Bredeweg, Bert; Muhar, Susanne

    2010-05-01

    The education system needs strategies to attract future scientists and practitioners. There is an alarming decline in the number of students choosing science subjects. Reasons for this include the perceived complexity and the lack of effective cognitive tools that enable learners to acquire the expertise in a way that fits its qualitative nature. The DynaLearn project utilises a "Learning by modelling" approach to deliver an individualised and engaging cognitive tool for acquiring conceptual knowledge. The modelling approach is based on qualitative reasoning, a research area within artificial intelligence, and allows for capturing and simulating qualitative systems knowledge. Educational activities within the DynaLearn software address topics at different levels of complexity, depending on the educational goals and settings. DynaLearn uses virtual characters in the learning environment as agents for engaging and motivating the students during their modelling exercise. The DynaLearn software represents an interactive learning environment in which learners are in control of their learning activities. The software is able to coach them individually based on their current progress, their knowledge needs and learning goals. Within the project 70 expert models on different environmental issues covering seven core topics (Earth Systems and Resources, The Living World, Human population, Land and Water Use, Energy Resources and Consumption, Pollution, and Global Changes) will be delivered. In the context of the core topic "Land and Water Use" the Institute of Hydrobiology and Aquatic Ecosystem Management has developed a model on Sustainable River Catchment Management. River systems with their catchments have been tremendously altered due to human pressures with serious consequences for the ecological integrity of riverine landscapes. The operation of hydropower plants, the implementation of flood protection measures, the regulation of flow and sediment regime and intensive

  10. Illusions of causality: how they bias our everyday thinking and how they could be reduced

    PubMed Central

    Matute, Helena; Blanco, Fernando; Yarritu, Ion; Díaz-Lago, Marcos; Vadillo, Miguel A.; Barberia, Itxaso

    2015-01-01

    Illusions of causality occur when people develop the belief that there is a causal connection between two events that are actually unrelated. Such illusions have been proposed to underlie pseudoscience and superstitious thinking, sometimes leading to disastrous consequences in relation to critical life areas, such as health, finances, and wellbeing. Like optical illusions, they can occur for anyone under well-known conditions. Scientific thinking is the best possible safeguard against them, but it does not come intuitively and needs to be taught. Teaching how to think scientifically should benefit from better understanding of the illusion of causality. In this article, we review experiments that our group has conducted on the illusion of causality during the last 20 years. We discuss how research on the illusion of causality can contribute to the teaching of scientific thinking and how scientific thinking can reduce illusion. PMID:26191014

  11. Illusions of causality: how they bias our everyday thinking and how they could be reduced.

    PubMed

    Matute, Helena; Blanco, Fernando; Yarritu, Ion; Díaz-Lago, Marcos; Vadillo, Miguel A; Barberia, Itxaso

    2015-01-01

    Illusions of causality occur when people develop the belief that there is a causal connection between two events that are actually unrelated. Such illusions have been proposed to underlie pseudoscience and superstitious thinking, sometimes leading to disastrous consequences in relation to critical life areas, such as health, finances, and wellbeing. Like optical illusions, they can occur for anyone under well-known conditions. Scientific thinking is the best possible safeguard against them, but it does not come intuitively and needs to be taught. Teaching how to think scientifically should benefit from better understanding of the illusion of causality. In this article, we review experiments that our group has conducted on the illusion of causality during the last 20 years. We discuss how research on the illusion of causality can contribute to the teaching of scientific thinking and how scientific thinking can reduce illusion.

  12. Multiple Causality: Consequences for Medical Practice

    PubMed Central

    Nydegger, Corinne N.

    1983-01-01

    When a scientifically trained health professional is called upon to deal with patients holding differing causal views of illness, the resulting lack of communication is frustrating to both. This discussion traces some implications for medical practice of significant cultural differences in two aspects of causal paradigms of illness: (1) terms accepted and (2) dimension or level of causality typically sought. The second is the more pervasive and intractable problem, having distinctive consequences for the role of curer, symptomatology, diagnosis and treatment. PMID:6858133

  13. Causal inference in economics and marketing

    PubMed Central

    Varian, Hal R.

    2016-01-01

    This is an elementary introduction to causal inference in economics written for readers familiar with machine learning methods. The critical step in any causal analysis is estimating the counterfactual—a prediction of what would have happened in the absence of the treatment. The powerful techniques used in machine learning may be useful for developing better estimates of the counterfactual, potentially improving causal inference. PMID:27382144

  14. Untangling Our Web: A Statewide Approach Is Needed to Improve/Judge College Readiness and to Increase College Success

    ERIC Educational Resources Information Center

    Howard-Vital, Michelle Rachel

    2006-01-01

    This paper examines the broad concept of college readiness, the research on advanced placement courses in high schools, and recommends that a statewide effort is needed to increase college readiness, college acclimation, college persistence, and college graduation rates. This effort needs to include a shared vision and the inclusion of multiple…

  15. A Study to Identify the Training Needs of Life Insurance Sales Representatives in Taiwan Using the Delphi Approach

    ERIC Educational Resources Information Center

    Fan, Chiang Ku; Cheng, Chen-Liang

    2006-01-01

    This article reports a study conducted to identify the needs for continuing professional development for life insurance sales representatives and to examine the competencies needed by those sales representatives. A modified Delphi technique was used. Most life insurance companies in the USA implement an education and training plan advocated by the…

  16. Predicting the Number of Public Computer Terminals Needed for an On-Line Catalog: A Queuing Theory Approach.

    ERIC Educational Resources Information Center

    Knox, A. Whitney; Miller, Bruce A.

    1980-01-01

    Describes a method for estimating the number of cathode ray tube terminals needed for public use of an online library catalog. Authors claim method could also be used to estimate needed numbers of microform readers for a computer output microform (COM) catalog. Formulae are included. (Author/JD)

  17. Causality from the Cosmological Perspective in Vedanta and Western Physics.

    NASA Astrophysics Data System (ADS)

    Hawley, Danny Lee

    The relation between Western physics and Indian Vedanta philosophy is investigated through the topic of causality, taken in the sense of explanatory theories of the origin of the universe and the relations among its physical, mental, and spiritual aspects. Both physics and Vedanta have a common goal of explanation by means of a unitary principle. While physics has long been separated from metaphysics, its discoveries indicate that consciousness must be included in a complete explanation. Consciousness is taken as the fundamental basis and source of all phenomena in Vedanta. This work traces the developments of causal explanation in Western physics and Indian philosophy, and considers how these views may relate to each other and how they may together suggest a comprehensive view of reality. Approaches typically applied by historians of religion to the study of creation myths, especially the psychological approach which considers myths from the perspective or cyclical stages of conscious development, are applied to the causal theories of the two cultures. The question of how causal explanations attempt to bridge the gap between cause and effect, unity and multiplicity, absolute and relative, conscious and unconscious, etc., is addressed. Though the investigation begins from the earliest causal explanations, viz., creation myths, emphasis is placed upon Samkara's commentaries of Advaita Vedanta, examined in the original Sanskrit, and upon the convergence of modern field theory, astrophysics, and cosmology, seen from the perspective of a previous doctorate in physics. Consideration is given to the comparison between physics and Vedanta as to goals, methods, and domains, to the question of the incompleteness of physics and the extent to which it nevertheless points beyond itself, to the possibility of a synthetic view and how it might be effected, and to analogies and metaphors through which physics and Vedanta may illuminate each other. An intuitive picture is

  18. Reverse causal reasoning: applying qualitative causal knowledge to the interpretation of high-throughput data

    PubMed Central

    2013-01-01

    Background Gene expression profiling and other genome-scale measurement technologies provide comprehensive information about molecular changes resulting from a chemical or genetic perturbation, or disease state. A critical challenge is the development of methods to interpret these large-scale data sets to identify specific biological mechanisms that can provide experimentally verifiable hypotheses and lead to the understanding of disease and drug action. Results We present a detailed description of Reverse Causal Reasoning (RCR), a reverse engineering methodology to infer mechanistic hypotheses from molecular profiling data. This methodology requires prior knowledge in the form of small networks that causally link a key upstream controller node representing a biological mechanism to downstream measurable quantities. These small directed networks are generated from a knowledge base of literature-curated qualitative biological cause-and-effect relationships expressed as a network. The small mechanism networks are evaluated as hypotheses to explain observed differential measurements. We provide a simple implementation of this methodology, Whistle, specifically geared towards the analysis of gene expression data and using prior knowledge expressed in Biological Expression Language (BEL). We present the Whistle analyses for three transcriptomic data sets using a publically available knowledge base. The mechanisms inferred by Whistle are consistent with the expected biology for each data set. Conclusions Reverse Causal Reasoning yields mechanistic insights to the interpretation of gene expression profiling data that are distinct from and complementary to the results of analyses using ontology or pathway gene sets. This reverse engineering algorithm provides an evidence-driven approach to the development of models of disease, drug action, and drug toxicity. PMID:24266983

  19. Detecting nonlinear causal interactions between dynamical systems by non-uniform embedding of multiple time series.

    PubMed

    Faes, Luca; Nollo, Giandomenico; Erla, Silvia; Papadelis, Christos; Braun, Christoph; Porta, Alberto

    2010-01-01

    This study introduces a new approach for the detection of nonlinear Granger causality between dynamical systems. The approach is based on embedding the multivariate (MV) time series measured from the systems X and Y by means of a sequential, non-uniform procedure, and on using the corrected conditional entropy (CCE) as unpredictability measure. The causal coupling from X to Y is quantified as the relative decrease of CCE measured after allowing the series of X to enter the embedding procedure for the description of Y. The ability of the approach to quantify nonlinear causality is assessed on MV time series measured from simulated dynamical systems with unidirectional coupling (the Rössler-Lorenz deterministic system) and bidirectional coupling (two coupled stochastic systems). The method is then applied to real magnetoencephalographic data measured during a visuo-tactile cognitive experiment, showing values of causal coupling consistent with the hypothesis of a cross-processing of different sensory modalities.

  20. CGene: an R package for implementation of causal genetic analyses

    PubMed Central

    Lipman, Peter J; Lange, Christoph

    2011-01-01

    The excitement over findings from Genome-Wide Association Studies (GWASs) has been tempered by the difficulty in finding the location of the true causal disease susceptibility loci (DSLs), rather than markers that are correlated with the causal variants. In addition, many recent GWASs have studied multiple phenotypes – often highly correlated – making it difficult to understand which associations are causal and which are seemingly causal, induced by phenotypic correlations. In order to identify DSLs, which are required to understand the genetic etiology of the observed associations, statistical methodology has been proposed that distinguishes between a direct effect of a genetic locus on the primary phenotype and an indirect effect induced by the association with the intermediate phenotype that is also correlated with the primary phenotype. However, so far, the application of this important methodology has been challenging, as no user-friendly software implementation exists. The lack of software implementation of this sophisticated methodology has prevented its large-scale use in the genetic community. We have now implemented this statistical approach in a user-friendly and robust R package that has been thoroughly tested. The R package ‘CGene' is available for download at http://cran.r-project.org/. The R code is also available at http://people.hsph.harvard.edu/~plipman. PMID:21731061

  1. Estimating Causal Effects with Ancestral Graph Markov Models

    PubMed Central

    Malinsky, Daniel; Spirtes, Peter

    2017-01-01

    We present an algorithm for estimating bounds on causal effects from observational data which combines graphical model search with simple linear regression. We assume that the underlying system can be represented by a linear structural equation model with no feedback, and we allow for the possibility of latent variables. Under assumptions standard in the causal search literature, we use conditional independence constraints to search for an equivalence class of ancestral graphs. Then, for each model in the equivalence class, we perform the appropriate regression (using causal structure information to determine which covariates to include in the regression) to estimate a set of possible causal effects. Our approach is based on the “IDA” procedure of Maathuis et al. (2009), which assumes that all relevant variables have been measured (i.e., no unmeasured confounders). We generalize their work by relaxing this assumption, which is often violated in applied contexts. We validate the performance of our algorithm on simulated data and demonstrate improved precision over IDA when latent variables are present. PMID:28217244

  2. Multivariate Granger causality analysis of fMRI data.

    PubMed

    Deshpande, Gopikrishna; LaConte, Stephan; James, George Andrew; Peltier, Scott; Hu, Xiaoping

    2009-04-01

    This article describes the combination of multivariate Granger causality analysis, temporal down-sampling of fMRI time series, and graph theoretic concepts for investigating causal brain networks and their dynamics. As a demonstration, this approach was applied to analyze epoch-to-epoch changes in a hand-gripping, muscle fatigue experiment. Causal influences between the activated regions were analyzed by applying the directed transfer function (DTF) analysis of multivariate Granger causality with the integrated epoch response as the input, allowing us to account for the effects of several relevant regions simultaneously. Integrated responses were used in lieu of originally sampled time points to remove the effect of the spatially varying hemodynamic response as a confounding factor; using integrated responses did not affect our ability to capture its slowly varying affects of fatigue. We separately modeled the early, middle, and late periods in the fatigue. We adopted graph theoretic concepts of clustering and eccentricity to facilitate the interpretation of the resultant complex networks. Our results reveal the temporal evolution of the network and demonstrate that motor fatigue leads to a disconnection in the related neural network.

  3. Statistical threshold for nonlinear Granger Causality in motor intention analysis.

    PubMed

    Liu, MengTing; Kuo, Ching-Chang; Chiu, Alan W L

    2011-01-01

    Directed influence between multiple channel signal measurements is important for the understanding of large dynamic systems. This research investigates a method to analyze large, complex multi-variable systems using directional flow measure to extract relevant information related to the functional connectivity between different units in the system. The directional flow measure was completed through nonlinear Granger Causality (GC) which is based on the nonlinear predictive models using radial basis functions (RBF). In order to extract relevant information from the causality map, we propose a threshold method that can be set up through a spatial statistical process where only the top 20% of causality pathways is shown. We applied this approach to a brain computer interface (BCI) application to decode the different intended arm reaching movement (left, right and forward) using 128 surface electroencephalography (EEG) electrodes. We also evaluated the importance of selecting the appropriate radius in the region of interest and found that the directions of causal influence of active brain regions were unique with respect to the intended direction.

  4. A sociodental approach to assessing children's oral health needs: integrating an oral health-related quality of life (OHRQoL) measure into oral health service planning.

    PubMed Central

    Gherunpong, Sudaduang; Sheiham, Aubrey; Tsakos, Georgios

    2006-01-01

    OBJECTIVE: We adopted a sociodental approach to assess the real dental needs of Thai primary school children, and integrated an oral health-related quality of life measure (OHRQoL) into oral health service planning. We then compared the results of this sociodental assessment with standard estimates of a child's oral health needs. METHODS: We developed a new model of sociodental needs assessment and used it to assess the level of impact that various oral health conditions have on the everyday lives of school children. We then carried out a cross-sectional study of all grade-6 children (11-12 years old) in Suphan-buri Province, Thailand. We examined the sample (n = 1034) to assess the children's oral health and then we interviewed each child individually to assess what impact any dental conditions he or she may have on their quality of life. This assessment was done using an OHRQoL indicator, the Child Oral Impacts on Daily Performances index (child-OIDP). We integrated the results obtained using this indicator with those estimates obtained using more traditional, standard clinical methods, in order to generate a clearer picture of exactly which non-progressive dental conditions really needed treatment. These results take into account the impact those conditions have on the overall well-being of children and their ability to function normally and unimpeded. We were then able to prioritize their dental needs according to the severity of disruption caused in their daily lives. FINDINGS: Using standard or "normative" estimates of dental health care needs, the children's need was 98.8%. This level of need decreased signifi cantly to 39.5% when adopting the sociodental approach (P <0.001). Overall, per 100 children with a standard or normative need for dental treatment, only 40 had a sociodental need for treatment when taking into account the impact their condition has on their everyday lives. Children thus identifi ed as requiring treatment were further categorized

  5. A Nonlinear Causality Estimator Based on Non-Parametric Multiplicative Regression

    PubMed Central

    Nicolaou, Nicoletta; Constandinou, Timothy G.

    2016-01-01

    Causal prediction has become a popular tool for neuroscience applications, as it allows the study of relationships between different brain areas during rest, cognitive tasks or brain disorders. We propose a nonparametric approach for the estimation of nonlinear causal prediction for multivariate time series. In the proposed estimator, CNPMR, Autoregressive modeling is replaced by Nonparametric Multiplicative Regression (NPMR). NPMR quantifies interactions between a response variable (effect) and a set of predictor variables (cause); here, we modified NPMR for model prediction. We also demonstrate how a particular measure, the sensitivity Q, could be used to reveal the structure of the underlying causal relationships. We apply CNPMR on artificial data with known ground truth (5 datasets), as well as physiological data (2 datasets). CNPMR correctly identifies both linear and nonlinear causal connections that are present in the artificial data, as well as physiologically relevant connectivity in the real data, and does not seem to be affected by filtering. The Sensitivity measure also provides useful information about the latent connectivity.The proposed estimator addresses many of the limitations of linear Granger causality and other nonlinear causality estimators. CNPMR is compared with pairwise and conditional Granger causality (linear) and Kernel-Granger causality (nonlinear). The proposed estimator can be applied to pairwise or multivariate estimations without any modifications to the main method. Its nonpametric nature, its ability to capture nonlinear relationships and its robustness to filtering make it appealing for a number of applications. PMID:27378901

  6. A Nonlinear Causality Estimator Based on Non-Parametric Multiplicative Regression.

    PubMed

    Nicolaou, Nicoletta; Constandinou, Timothy G

    2016-01-01

    Causal prediction has become a popular tool for neuroscience applications, as it allows the study of relationships between different brain areas during rest, cognitive tasks or brain disorders. We propose a nonparametric approach for the estimation of nonlinear causal prediction for multivariate time series. In the proposed estimator, C NPMR , Autoregressive modeling is replaced by Nonparametric Multiplicative Regression (NPMR). NPMR quantifies interactions between a response variable (effect) and a set of predictor variables (cause); here, we modified NPMR for model prediction. We also demonstrate how a particular measure, the sensitivity Q, could be used to reveal the structure of the underlying causal relationships. We apply C NPMR on artificial data with known ground truth (5 datasets), as well as physiological data (2 datasets). C NPMR correctly identifies both linear and nonlinear causal connections that are present in the artificial data, as well as physiologically relevant connectivity in the real data, and does not seem to be affected by filtering. The Sensitivity measure also provides useful information about the latent connectivity.The proposed estimator addresses many of the limitations of linear Granger causality and other nonlinear causality estimators. C NPMR is compared with pairwise and conditional Granger causality (linear) and Kernel-Granger causality (nonlinear). The proposed estimator can be applied to pairwise or multivariate estimations without any modifications to the main method. Its nonpametric nature, its ability to capture nonlinear relationships and its robustness to filtering make it appealing for a number of applications.

  7. Causal compensated perturbations in cosmology

    NASA Technical Reports Server (NTRS)

    Veeraraghavan, Shoba; Stebbins, Albert

    1990-01-01

    A theoretical framework is developed to calculate linear perturbations in the gravitational and matter fields which arise causally in response to the presence of stiff matter sources in a FRW cosmology. It is shown that, in order to satisfy energy and momentum conservation, the gravitational fields of the source must be compensated by perturbations in the matter and gravitational fields, and the role of such compensation in containing the initial inhomogeneities in their subsequent evolution is discussed. A complete formal solution is derived in terms of Green functions for the perturbations produced by an arbitrary source in a flat universe containing cold dark matter. Approximate Green function solutions are derived for the late-time density perturbations and late-time gravitational waves in a universe containing a radiation fluid. A cosmological energy-momentum pseudotensor is defined to clarify the nature of energy and momentum conservation in the expanding universe.

  8. Causal Systems Categories: Differences in Novice and Expert Categorization of Causal Phenomena

    ERIC Educational Resources Information Center

    Rottman, Benjamin M.; Gentner, Dedre; Goldwater, Micah B.

    2012-01-01

    We investigated the understanding of causal systems categories--categories defined by common causal structure rather than by common domain content--among college students. We asked students who were either novices or experts in the physical sciences to sort descriptions of real-world phenomena that varied in their causal structure (e.g., negative…

  9. A Theory of Causal Learning in Children: Causal Maps and Bayes Nets

    ERIC Educational Resources Information Center

    Gopnik, Alison; Glymour, Clark; Sobel, David M.; Schulz, Laura E.; Kushnir, Tamar; Danks, David

    2004-01-01

    The authors outline a cognitive and computational account of causal learning in children. They propose that children use specialized cognitive systems that allow them to recover an accurate "causal map" of the world: an abstract, coherent, learned representation of the causal relations among events. This kind of knowledge can be perspicuously…

  10. The Power of Causal Beliefs and Conflicting Evidence on Causal Judgments and Decision Making

    ERIC Educational Resources Information Center

    Garcia-Retamero, Rocio; Muller, Stephanie M.; Catena, Andres; Maldonado, Antonio

    2009-01-01

    In two experiments, we investigated the relative impact of causal beliefs and empirical evidence on both decision making and causal judgments, and whether this relative impact could be altered by previous experience. 2. Selected groups of participants in both experiments received pre-training with either causal or neutral cues, or no pre-training…

  11. Perceived causal relations: novel methodology for assessing client attributions about causal associations between variables including symptoms and functional impairment.

    PubMed

    Frewen, Paul A; Allen, Samantha L; Lanius, Ruth A; Neufeld, Richard W J

    2012-12-01

    Researchers have argued that the investigation of causal interrelationships between symptoms may help explain the high comorbidity rate between certain psychiatric disorders. Clients' own attributions concerning the causal interrelationships linking the co-occurrence of their symptoms represent data that may inform their clinical case conceptualization, treatment, and psychological theory regarding the etiology of comorbid disorders. The present study developed and evaluated a novel psychological assessment methodology for measuring Perceived Causal Relations (PCR) and examined its psychometric properties as applied to the question of whether posttraumatic stress and anxiety symptoms represent causal risk factors for depressive symptoms in 225 undergraduates. Participants attributed their symptoms of anxiety and posttraumatic reexperiencing as significant causes of their depressive symptoms. Exploratory analyses identified a listing of symptoms reliably attributed as significant causes of other symptoms and functional impairment, as well as a listing of symptoms reliably attributed as significant effects (outcomes) of other symptoms and functional impairment. The PCR method has promise as an idiographic approach to assessing the causes and consequences of comorbid psychiatric symptoms and associated functional impairment. Research is required to assess the relevance and replicate these findings in distinct psychiatric groups experiencing various symptomatic presentations. Future research may also examine PCR ratings associating other individual differences, for example, between measures of history (e.g., life events), life choices, and personality.

  12. Causal Indicators Can Help to Interpret Factors

    ERIC Educational Resources Information Center

    Bentler, Peter M.

    2016-01-01

    The latent factor in a causal indicator model is no more than the latent factor of the factor part of the model. However, if the causal indicator variables are well-understood and help to improve the prediction of individuals' factor scores, they can help to interpret the meaning of the latent factor. Aguirre-Urreta, Rönkkö, and Marakas (2016)…

  13. Essays on Causal Inference for Public Policy

    ERIC Educational Resources Information Center

    Zajonc, Tristan

    2012-01-01

    Effective policymaking requires understanding the causal effects of competing proposals. Relevant causal quantities include proposals' expected effect on different groups of recipients, the impact of policies over time, the potential trade-offs between competing objectives, and, ultimately, the optimal policy. This dissertation studies causal…

  14. "Comments on Slavin": Synthesizing Causal Inferences

    ERIC Educational Resources Information Center

    Briggs, Derek C.

    2008-01-01

    When causal inferences are to be synthesized across multiple studies, efforts to establish the magnitude of a causal effect should be balanced by an effort to evaluate the generalizability of the effect. The evaluation of generalizability depends on two factors that are given little attention in current syntheses: construct validity and external…

  15. Preschoolers' Understanding of Temporal and Causal Relations.

    ERIC Educational Resources Information Center

    Sharp, Kay Colby

    1982-01-01

    Two experiments investigated psychological factors determining preschoolers' success or failure on a sequence-completion task involving temporal and causal ordering of events. Overall findings demonstrate that while preschoolers do understand temporal/causal relationships, their abilities are dependent on process variables demanded by the task…

  16. Updating during Reading Comprehension: Why Causality Matters

    ERIC Educational Resources Information Center

    Kendeou, Panayiota; Smith, Emily R.; O'Brien, Edward J.

    2013-01-01

    The present set of 7 experiments systematically examined the effectiveness of adding causal explanations to simple refutations in reducing or eliminating the impact of outdated information on subsequent comprehension. The addition of a single causal-explanation sentence to a refutation was sufficient to eliminate any measurable disruption in…

  17. Multivariate Granger causality and generalized variance

    NASA Astrophysics Data System (ADS)

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

    2010-04-01

    Granger causality analysis is a popular method for inference on directed interactions in complex systems of many variables. A shortcoming of the standard framework for Granger causality is that it only allows for examination of interactions between single (univariate) variables within a system, perhaps conditioned on other variables. However, interactions do not necessarily take place between single variables but may occur among groups or “ensembles” of variables. In this study we establish a principled framework for Granger causality in the context of causal interactions among two or more multivariate sets of variables. Building on Geweke’s seminal 1982 work, we offer additional justifications for one particular form of multivariate Granger causality based on the generalized variances of residual errors. Taken together, our results support a comprehensive and theoretically consistent extension of Granger causality to the multivariate case. Treated individually, they highlight several specific advantages of the generalized variance measure, which we illustrate using applications in neuroscience as an example. We further show how the measure can be used to define “partial” Granger causality in the multivariate context and we also motivate reformulations of “causal density” and “Granger autonomy.” Our results are directly applicable to experimental data and promise to reveal new types of functional relations in complex systems, neural and otherwise.

  18. On the spectral formulation of Granger causality.

    PubMed

    Chicharro, D

    2011-12-01

    Spectral measures of causality are used to explore the role of different rhythms in the causal connectivity between brain regions. We study several spectral measures related to Granger causality, comprising the bivariate and conditional Geweke measures, the directed transfer function, and the partial directed coherence. We derive the formulation of dependence and causality in the spectral domain from the more general formulation in the information-theory framework. We argue that the transfer entropy, the most general measure derived from the concept of Granger causality, lacks a spectral representation in terms of only the processes associated with the recorded signals. For all the spectral measures we show how they are related to mutual information rates when explicitly considering the parametric autoregressive representation of the processes. In this way we express the conditional Geweke spectral measure in terms of a multiple coherence involving innovation variables inherent to the autoregressive representation. We also link partial directed coherence with Sims' criterion of causality. Given our results, we discuss the causal interpretation of the spectral measures related to Granger causality and stress the necessity to explicitly consider their specific formulation based on modeling the signals as linear Gaussian stationary autoregressive processes.

  19. Causal Moderation Analysis Using Propensity Score Methods

    ERIC Educational Resources Information Center

    Dong, Nianbo

    2012-01-01

    This paper is based on previous studies in applying propensity score methods to study multiple treatment variables to examine the causal moderator effect. The propensity score methods will be demonstrated in a case study to examine the causal moderator effect, where the moderators are categorical and continuous variables. Moderation analysis is an…

  20. Quasi-Experimental Designs for Causal Inference

    ERIC Educational Resources Information Center

    Kim, Yongnam; Steiner, Peter

    2016-01-01

    When randomized experiments are infeasible, quasi-experimental designs can be exploited to evaluate causal treatment effects. The strongest quasi-experimental designs for causal inference are regression discontinuity designs, instrumental variable designs, matching and propensity score designs, and comparative interrupted time series designs. This…