WorldWideScience

Sample records for causality

  1. Causal universe

    CERN Document Server

    Ellis, George FR; Pabjan, Tadeusz

    2013-01-01

    Written by philosophers, cosmologists, and physicists, this collection of essays deals with causality, which is a core issue for both science and philosophy. Readers will learn about different types of causality in complex systems and about new perspectives on this issue based on physical and cosmological considerations. In addition, the book includes essays pertaining to the problem of causality in ancient Greek philosophy, and to the problem of God's relation to the causal structures of nature viewed in the light of contemporary physics and cosmology.

  2. Causal and causally separable processes

    Science.gov (United States)

    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

  3. Causal mapping

    DEFF Research Database (Denmark)

    Rasmussen, Lauge Baungaard

    2006-01-01

    The lecture note explains how to use the causal mapping method as well as the theoretical framework aoosciated to the method......The lecture note explains how to use the causal mapping method as well as the theoretical framework aoosciated to the method...

  4. Epidemiological causality.

    Science.gov (United States)

    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.

  5. Causality Principle

    OpenAIRE

    Chi, Do Minh

    2001-01-01

    We advance a famous principle - causality principle - but under a new view. This principle is a principium automatically leading to most fundamental laws of the nature. It is the inner origin of variation, rules evolutionary processes of things, and the answer of the quest for ultimate theories of the Universe.

  6. Causal reasoning in physics

    CERN Document Server

    Frisch, Mathias

    2014-01-01

    Much has been written on the role of causal notions and causal reasoning in the so-called 'special sciences' and in common sense. But does causal reasoning also play a role in physics? Mathias Frisch argues that, contrary to what influential philosophical arguments purport to show, the answer is yes. Time-asymmetric causal structures are as integral a part of the representational toolkit of physics as a theory's dynamical equations. Frisch develops his argument partly through a critique of anti-causal arguments and partly through a detailed examination of actual examples of causal notions in physics, including causal principles invoked in linear response theory and in representations of radiation phenomena. Offering a new perspective on the nature of scientific theories and causal reasoning, this book will be of interest to professional philosophers, graduate students, and anyone interested in the role of causal thinking in science.

  7. The Equation of Causality

    OpenAIRE

    Chi, Do Minh

    1999-01-01

    We research the natural causality of the Universe. We find that the equation of causality provides very good results on physics. That is our first endeavour and success in describing a quantitative expression of the law of causality. Hence, our theoretical point suggests ideas to build other laws including the law of the Universe's evolution.

  8. Times and Causality

    OpenAIRE

    Davidson, Russell

    2013-01-01

    The understanding of causal chains and mechanisms is an essential part of any scientific activity that aims at better explanation of its subject matter, and better understanding of it. While any account of causality requires that a cause should precede its effect, accounts of causality inphysics are complicated by the fact that the role of time in current theoretical physics has evolved very substantially throughout the twentieth century. In this article, I review the status of time and causa...

  9. How to be causal

    CERN Document Server

    Kinsler, Paul

    2011-01-01

    I explain a simple definition of causality in widespread use, and indicate how it links to the Kramers Kronig relations. The specification of causality in terms of temporal differential eqations then shows us the way to write down dynamical models so that their causal nature in the sense used here should be obvious to all. In particular, I apply this reasoning to Maxwell's equations, which is an instructive example since their casual properties are sometimes debated.

  10. Causality in Classical Electrodynamics

    Science.gov (United States)

    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…

  11. Causality and Composite Structure

    CERN Document Server

    Joglekar, Satish D

    2007-01-01

    We study 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 $\\lesssim \\Lambda$). We formulate a model-independent approach based on Bogoliubov-Shirkov formulation of causality. We analyze the relation between the fundamental theory (of finer constituents) and the derived theory (of composite particles). We assume that the fundamental theory is causal and formulate a condition which must be fulfilled for the derived theory to be causal. We analyze the condition and exhibit possibilities which fulfil and which violate the condition. We make comments on how causality violating amplitudes can arise.

  12. Causality in demand

    DEFF Research Database (Denmark)

    Nielsen, Max; Jensen, Frank; Setälä, Jari;

    2011-01-01

    to fish demand. On the German market for farmed trout and substitutes, it is found that supply sources, i.e. aquaculture and fishery, are not the only determinant of causality. Storing, tightness of management and aggregation level of integrated markets might also be important. The methodological......This article focuses on causality in demand. A methodology where causality is imposed and tested within an empirical co-integrated demand model, not prespecified, is suggested. The methodology allows different causality of different products within the same demand system. The methodology is applied...... implication is that more explicit focus on causality in demand analyses provides improved information. The results suggest that frozen trout forms part of a large European whitefish market, where prices of fresh trout are formed on a relatively separate market. Redfish is a substitute on both markets. The...

  13. Causality in Europeanization Research

    DEFF Research Database (Denmark)

    Lynggaard, Kennet

    2012-01-01

    Discourse analysis as a methodology is perhaps not readily associated with substantive causality claims. At the same time the study of discourses is very much the study of conceptions of causal relations among a set, or sets, of agents. Within Europeanization research we have seen endeavours...... to develop discursive institutional analytical frameworks and something that comes close to the formulation of hypothesis on the effects of European Union (EU) policies and institutions on domestic change. Even if these efforts so far do not necessarily amount to substantive theories or claims of causality......, it suggests that discourse analysis and the study of causality are by no means opposites. The study of Europeanization discourses may even be seen as an essential step in the move towards claims of causality in Europeanization research. This chapter deals with the question of how we may move from the study...

  14. Agency, time and causality

    Directory of Open Access Journals (Sweden)

    Thomas eWidlok

    2014-11-01

    Full Text Available Cognitive Scientists interested in causal cognition increasingly search for evidence from non-WEIRD 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.

  15. Causal Newton Gravity Law

    CERN Document Server

    Zinoviev, Yury M

    2012-01-01

    The equations of the relativistic causal Newton gravity law for the planets of the solar system are studied in the approximation when the Sun rests at the coordinates origin and the planets do not iteract between each other.

  16. Causal spin foams

    CERN Document Server

    Immirzi, Giorgio

    2016-01-01

    I discuss how to impose causality on spin-foam models, separating forward and backward propagation, turning a given triangulation to a 'causal set', and giving asymptotically the exponential of the Regge action, not a cosine. I show the equivalence of the prescriptions which have been proposed to achieve this. Essential to the argument is the closure condition for the 4-simplices, all made of space-like tetrahedra.

  17. Quantum Causal Graph Dynamics

    CERN Document Server

    Arrighi, Pablo

    2016-01-01

    Consider a graph having quantum systems lying at each node. Suppose that the whole thing evolves in discrete time steps, according to a global, unitary causal operator. By causal we mean that information can only propagate at a bounded speed, with respect to the distance given by the graph. Suppose, moreover, that the graph itself is subject to the evolution, and may be driven to be in a quantum superposition of graphs---in accordance to the superposition principle. We show that these unitary causal operators must decompose as a finite-depth circuit of local unitary gates. This unifies a result on Quantum Cellular Automata with another on Reversible Causal Graph Dynamics. Along the way we formalize a notion of causality which is valid in the context of quantum superpositions of time-varying graphs, and has a number of good properties. Keywords: Quantum Lattice Gas Automata, Block-representation, Curtis-Hedlund-Lyndon, No-signalling, Localizability, Quantum Gravity, Quantum Graphity, Causal Dynamical Triangula...

  18. Assimetria causal: um estudo

    Directory of Open Access Journals (Sweden)

    Túlio Aguiar

    2003-12-01

    Full Text Available Neste artigo, examinamos o aspecto assimétrico da relação causal, confrontando-o com o ponto de vista humiano e neo-humiano. Seguindo Hausman e Ehring, favorecemos uma abordagem situacional para a assimetria causal. Nós exploramos a análise do famoso exemplo do mastro (Flagpole, esclarecendo as conexões entre causação e explicação. Nosso diagnóstico geral é que a tradição neo-humiana supõe, equivocadamente, que as relações nômicas, com exceção de pequenos detalhes, exaurem as relações causais.This paper examines the asymmetrical aspect of causal relation, confronting it to Humean and Neo-Humean's view. Following Hausman and Ehring, we favor a situational approach to causal asymmetry. We explore the Hausman's analysis of flagpole's example, clearing the connexions between causation and explanation. Our general diagnosis is that the Neo-humean tradition wrongly supposes that nomic relations, with the exception of minor details, exhaust the causal relations.

  19. Causality and the Doppler Peaks

    OpenAIRE

    Turok, Neil

    1996-01-01

    Could cosmic structure have formed by the action of causal physics within the standard hot big bang, or was a prior period of inflation required? Recently there has been some discussion of whether causal sources could reproduce the pattern of Doppler peaks of the standard scale-invariant adiabatic theory. This paper gives a rigorous definition of causality, and a causal decomposition of a general source. I present an example of a simple causal source which mimics the standard adiabatic theory...

  20. Causal graph dynamics

    CERN Document Server

    Arrighi, Pablo

    2012-01-01

    We generalize the theory of Cellular Automata to arbitrary, time-varying graphs. In other words we formalize, and prove theorems about, the intuitive idea of a labelled graph which evolves in time - but under the natural constraint that information can only ever be transmitted at a bounded speed, with respect to the distance given by the graph. The notion of translation-invariance is also generalized. The definition we provide for these `causal graph dynamics' is simple and axiomatic. The theorems we provide also show that it is robust. For instance, causal graph dynamics are stable under composition and under restriction to radius one. In the finite case some fundamental facts of Cellular Automata theory carry through: causal graph dynamics admit a characterization as continuous functions and they are stable under inversion. The provided examples suggest a wide range of applications of this mathematical object, from complex systems science to theoretical physics. Keywords: Dynamical networks, Boolean network...

  1. Causal inference in econometrics

    CERN Document Server

    Kreinovich, Vladik; Sriboonchitta, Songsak

    2016-01-01

    This book is devoted to the analysis of causal inference which is one of the most difficult tasks in data analysis: when two phenomena are observed to be related, it is often difficult to decide whether one of them causally influences the other one, or whether these two phenomena have a common cause. This analysis is the main focus of this volume. To get a good understanding of the causal inference, it is important to have models of economic phenomena which are as accurate as possible. Because of this need, this volume also contains papers that use non-traditional economic models, such as fuzzy models and models obtained by using neural networks and data mining techniques. It also contains papers that apply different econometric models to analyze real-life economic dependencies.

  2. Complementarity, causality, and explanation

    CERN Document Server

    Losee, John

    2013-01-01

    Prior to the work of Niels Bohr, discussions on the relationship of cause and effect presupposed that successful causal attribution implies explanation. The success of quantum theory challenged this presupposition. In this succinct review of the history of these discussions, John Losee presents the philosophical background of debates over the cause-effect relation. He reviews the positions of Aristotle, René Descartes, Isaac Newton, David Hume, Immanuel Kant, and John Stuart Mill. He shows how nineteenth-century theories in physics and chemistry were informed by a dominant theory of causality

  3. Causal premise semantics.

    Science.gov (United States)

    Kaufmann, Stefan

    2013-08-01

    The rise of causality and the attendant graph-theoretic modeling tools in the study of counterfactual reasoning has had resounding effects in many areas of cognitive science, but it has thus far not permeated the mainstream in linguistic theory to a comparable degree. In this study I show that a version of the predominant framework for the formal semantic analysis of conditionals, Kratzer-style premise semantics, allows for a straightforward implementation of the crucial ideas and insights of Pearl-style causal networks. I spell out the details of such an implementation, focusing especially on the notions of intervention on a network and backtracking interpretations of counterfactuals.

  4. Understanding Causal Coherence Relations

    NARCIS (Netherlands)

    Mulder, G.

    2008-01-01

    The research reported in this dissertation focuses on the cognitive processes and representations involved in understanding causal coherence relations in text. Coherence relations are the meaning relations between the information units in the text, such as Cause-Consequence. These relations can be m

  5. Revisiting Causality in Markov Chains

    OpenAIRE

    Shojaee, Abbas

    2016-01-01

    Identifying causal relationships is a key premise of scientific research. The growth of observational data in different disciplines along with the availability of machine learning methods offers the possibility of using an empirical approach to identifying potential causal relationships, to deepen our understandings of causal behavior and to build theories accordingly. Conventional methods of causality inference from observational data require a considerable length of time series data to capt...

  6. Context, causality, and appreciation.

    Science.gov (United States)

    Ross, Stephanie

    2013-04-01

    I applaud and elaborate on the contextualism at the heart of Bullot & Reber's (B&R's) theory, challenge two aspects of the appreciative structure they posit (the causal reasoning that allegedly underlies the design stance and the segregation of the component stages), suggest that expert and novice appreciators operate differently, and question the degree to which B&R's final theory is open to empirical investigation. PMID:23507111

  7. Causality between time series

    CERN Document Server

    Liang, X San

    2014-01-01

    Given two time series, can one tell, in a rigorous and quantitative way, the cause and effect between them? Based on a recently rigorized physical notion namely information flow, we arrive at a concise formula and give this challenging question, which is of wide concern in different disciplines, a positive answer. Here causality is measured by the time rate of change of information flowing from one series, say, X2, to another, X1. The measure is asymmetric between the two parties and, particularly, if the process underlying X1 does not depend on X2, then the resulting causality from X2 to X1 vanishes. The formula is tight in form, involving only the commonly used statistics, sample covariances. It has been validated with touchstone series purportedly generated with one-way causality. It has also been applied to the investigation of real world problems; an example presented here is the cause-effect relation between two climate modes, El Ni\\~no and Indian Ocean Dipole, which have been linked to the hazards in f...

  8. Tachyon Kinematics and causality

    International Nuclear Information System (INIS)

    The chronological order of the events along a space-like path is not invariant under Lorentz transformations, as wellknown. This led to an early conviction that tachyons would give rise to causal anomalies. A relativistic version of the Stuckelberg-Feynman switching procedure (SWP) has been invoked as the suitable tool to eliminate those anomalies. The application of the SWP does eliminate the motions backwards in time, but interchanges the roles of source and dector. This fact triggered the proposal of a host of causal paradoxes. Till now, however, it has not been recognized that such paradoxes can be sensibly discussed (and completely solved, at least in microphysics) only after having properly developed the tachyon relativistic mechanics. We start by showing how to apply the SWP, both in the case of ordiry Special Relativity, and in the case with tachyons. Then, we carefully exploit the kinematics of the tachyon-exchange between to (ordinary) bodies. Being finally able to tackle the tachyon-causality problem, we successively solve the paradoxes: (i) by Tolman-Regge; (ii) by Pirani; (iii) by Edmonds; (iv) by Bell. At last, we discuss a further, new paradox associated with the transmission of signals by modulated tachyon beams

  9. Revisiting Causality in Markov Chains

    CERN Document Server

    Shojaee, Abbas

    2016-01-01

    Identifying causal relationships is a key premise of scientific research. The growth of observational data in different disciplines along with the availability of machine learning methods offers the possibility of using an empirical approach to identifying potential causal relationships, to deepen our understandings of causal behavior and to build theories accordingly. Conventional methods of causality inference from observational data require a considerable length of time series data to capture cause-effect relationship. We find that potential causal relationships can be inferred from the composition of one step transition rates to and from an event. Also known as Markov chain, one step transition rates are a commonly available resource in different scientific disciplines. Here we introduce a simple, effective and computationally efficient method that we termed 'Causality Inference using Composition of Transitions CICT' to reveal causal structure with high accuracy. We characterize the differences in causes,...

  10. Entropy of Causal Horizons

    CERN Document Server

    Howard, Eric M

    2016-01-01

    We analyze spacetimes with horizons and study the thermodynamic aspects of causal horizons, suggesting that the resemblance between gravitational and thermodynamic systems has a deeper quantum mechanical origin. We find that the observer dependence of such horizons is a direct consequence of associating a temperature and entropy to a spacetime. The geometrical picture of a horizon acting as a one-way membrane for information flow can be accepted as a natural interpretation of assigning a quantum field theory to a spacetime with boundary, ultimately leading to a close connection with thermodynamics.

  11. Quantum information causality.

    Science.gov (United States)

    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. PMID:23745844

  12. Inferring deterministic causal relations

    OpenAIRE

    Daniusis, Povilas; Janzing, Dominik; Mooij, Joris; Zscheischler, Jakob; Steudel, Bastian; Zhang, Kun; Schoelkopf, Bernhard

    2012-01-01

    We consider two variables that are related to each other by an invertible function. While it has previously been shown that the dependence structure of the noise can provide hints to determine which of the two variables is the cause, we presently show that even in the deterministic (noise-free) case, there are asymmetries that can be exploited for causal inference. Our method is based on the idea that if the function and the probability density of the cause are chosen independently, then the ...

  13. Experimental test of nonlocal causality.

    Science.gov (United States)

    Ringbauer, Martin; Giarmatzi, Christina; Chaves, Rafael; Costa, Fabio; White, Andrew G; Fedrizzi, Alessandro

    2016-08-01

    Explaining observations in terms of causes and effects is central to empirical science. However, correlations between entangled quantum particles seem to defy such an explanation. This implies that some of the fundamental assumptions of causal explanations have to give way. We consider a relaxation of one of these assumptions, Bell's local causality, by allowing outcome dependence: a direct causal influence between the outcomes of measurements of remote parties. We use interventional data from a photonic experiment to bound the strength of this causal influence in a two-party Bell scenario, and observational data from a Bell-type inequality test for the considered models. Our results demonstrate the incompatibility of quantum mechanics with a broad class of nonlocal causal models, which includes Bell-local models as a special case. Recovering a classical causal picture of quantum correlations thus requires an even more radical modification of our classical notion of cause and effect.

  14. Causal inference based on counterfactuals

    Directory of Open Access Journals (Sweden)

    Höfler M

    2005-09-01

    Full Text Available Abstract 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.

  15. Experimental test of nonlocal causality.

    Science.gov (United States)

    Ringbauer, Martin; Giarmatzi, Christina; Chaves, Rafael; Costa, Fabio; White, Andrew G; Fedrizzi, Alessandro

    2016-08-01

    Explaining observations in terms of causes and effects is central to empirical science. However, correlations between entangled quantum particles seem to defy such an explanation. This implies that some of the fundamental assumptions of causal explanations have to give way. We consider a relaxation of one of these assumptions, Bell's local causality, by allowing outcome dependence: a direct causal influence between the outcomes of measurements of remote parties. We use interventional data from a photonic experiment to bound the strength of this causal influence in a two-party Bell scenario, and observational data from a Bell-type inequality test for the considered models. Our results demonstrate the incompatibility of quantum mechanics with a broad class of nonlocal causal models, which includes Bell-local models as a special case. Recovering a classical causal picture of quantum correlations thus requires an even more radical modification of our classical notion of cause and effect. PMID:27532045

  16. Experimental test of nonlocal causality

    OpenAIRE

    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 fro...

  17. Causal evolution of wave packets

    CERN Document Server

    Eckstein, Michał

    2016-01-01

    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 system is causal, the relativistic-Schr\\"odinger Hamiltonian impels a superluminal evolution of probabilities. We quantify the causality breakdown in the latter system and argue that, in contrast to the popular viewpoint, it is not related to the localisation properties of the states.

  18. Relativistic hydrodynamics - causality and stability

    OpenAIRE

    Ván, P.; Biró, T. S.

    2007-01-01

    Causality and stability in relativistic dissipative hydrodynamics are important conceptual issues. We argue that causality is not restricted to hyperbolic set of differential equations. E.g. heat conduction equation can be causal considering the physical validity of the theory. Furthermore we propose a new concept of relativistic internal energy that clearly separates the dissipative and non-dissipative effects. We prove that with this choice we remove all known instabilities of the linear re...

  19. Relationship of causal effects in a causal chain and related inference

    Institute of Scientific and Technical Information of China (English)

    GENG; Zhi; HE; Yangbo; WANG; Xueli

    2004-01-01

    This paper discusses the relationship among the total causal effect and local causal effects in a causal chain and identifiability of causal effects. We show a transmission relationship of causal effects in a causal chain. According to the relationship, we give an approach to eliminating confounding bias through controlling for intermediate variables in a causal chain.

  20. Causality Statistical Perspectives and Applications

    CERN Document Server

    Berzuini, Carlo; Bernardinell, Luisa

    2012-01-01

    A state of the art volume on statistical causality Causality: Statistical Perspectives and Applications presents a wide-ranging collection of seminal contributions by renowned experts in the field, providing a thorough treatment of all aspects of statistical causality. It covers the various formalisms in current use, methods for applying them to specific problems, and the special requirements of a range of examples from medicine, biology and economics to political science. This book:Provides a clear account and comparison of formal languages, concepts and models for statistical causality. Addr

  1. Identifiability of causal effect for a simple causal model

    Institute of Scientific and Technical Information of China (English)

    郑忠国; 张艳艳; 童行伟

    2002-01-01

    Counterfactual model is put forward to discuss the causal inference in the directed acyclic graph and its corresponding identifiability is thus studied with the ancillary information based on conditional independence. It is shown that the assumption of ignorability can be expanded to the assumption of replaceability,under which the causal efiects are identifiable.

  2. Structural Equations and Causal Explanations: Some Challenges for Causal SEM

    Science.gov (United States)

    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…

  3. Inferring deterministic causal relations

    CERN Document Server

    Daniusis, Povilas; Mooij, Joris; Zscheischler, Jakob; Steudel, Bastian; Zhang, Kun; Schoelkopf, Bernhard

    2012-01-01

    We consider two variables that are related to each other by an invertible function. While it has previously been shown that the dependence structure of the noise can provide hints to determine which of the two variables is the cause, we presently show that even in the deterministic (noise-free) case, there are asymmetries that can be exploited for causal inference. Our method is based on the idea that if the function and the probability density of the cause are chosen independently, then the distribution of the effect will, in a certain sense, depend on the function. We provide a theoretical analysis of this method, showing that it also works in the low noise regime, and link it to information geometry. We report strong empirical results on various real-world data sets from different domains.

  4. Expert Causal Reasoning and Explanation.

    Science.gov (United States)

    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…

  5. Introduction to causal dynamical triangulations

    DEFF Research Database (Denmark)

    Görlich, Andrzej

    2013-01-01

    The method of causal dynamical triangulations is a non-perturbative and background-independent approach to quantum theory of gravity. In this review we present recent results obtained within the four dimensional model of causal dynamical triangulations. We describe the phase structure of the model...

  6. Re-thinking local causality

    NARCIS (Netherlands)

    Friederich, Simon

    2015-01-01

    There is widespread belief in a tension between quantum theory and special relativity, motivated by the idea that quantum theory violates J. S. Bell's criterion of local causality, which is meant to implement the causal structure of relativistic space-time. This paper argues that if one takes the es

  7. Causal Inference and Developmental Psychology

    Science.gov (United States)

    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…

  8. Neural Correlates of Causal Power Judgments

    Directory of Open Access Journals (Sweden)

    Denise Dellarosa Cummins

    2014-12-01

    Full Text Available Causal inference is a fundamental component of cognition and perception. Probabilistic theories of causal judgment (most notably causal Bayes networks derive causal judgments using metrics that integrate contingency information. But human estimates typically diverge from these normative predictions. This is because human causal power judgments are typically strongly influenced by beliefs concerning underlying causal mechanisms, and because of the way knowledge is retrieved from human memory during the judgment process. Neuroimaging studies indicate that the brain distinguishes causal events from mere covariation, and between perceived and inferred causality. Areas involved in error prediction are also activated, implying automatic activation of possible exception cases during causal decision-making.

  9. The Visual Causality Analyst: An Interactive Interface for Causal Reasoning.

    Science.gov (United States)

    Wang, Jun; Mueller, Klaus

    2016-01-01

    Uncovering the causal relations that exist among variables in multivariate datasets is one of the ultimate goals in data analytics. Causation is related to correlation but correlation does not imply causation. While a number of casual discovery algorithms have been devised that eliminate spurious correlations from a network, there are no guarantees that all of the inferred causations are indeed true. Hence, bringing a domain expert into the casual reasoning loop can be of great benefit in identifying erroneous casual relationships suggested by the discovery algorithm. To address this need we present the Visual Causal Analyst-a novel visual causal reasoning framework that allows users to apply their expertise, verify and edit causal links, and collaborate with the causal discovery algorithm to identify a valid causal network. Its interface consists of both an interactive 2D graph view and a numerical presentation of salient statistical parameters, such as regression coefficients, p-values, and others. Both help users in gaining a good understanding of the landscape of causal structures particularly when the number of variables is large. Our framework is also novel in that it can handle both numerical and categorical variables within one unified model and return plausible results. We demonstrate its use via a set of case studies using multiple practical datasets. PMID:26529703

  10. ["Karoshi" and causal relationships].

    Science.gov (United States)

    Hamajima, N

    1992-08-01

    This paper aims to introduce a measure for use by physicians for stating the degree of probable causal relationship for "Karoshi", ie, a sudden death from cerebrovascular diseases or ischemic heart diseases under occupational stresses, as well as to give a brief description for legal procedures associated with worker's compensation and civil trial in Japan. It is a well-used measure in epidemiology, "attributable risk percent (AR%)", which can be applied to describe the extent of contribution to "Karoshi" of the excess occupational burdens the deceased worker was forced to bear. Although several standards such as average occupational burdens for the worker, average occupational burdens for an ordinary worker, burdens in a nonoccupational life, and a complete rest, might be considered for the AR% estimation, the average occupational burdens for an ordinary worker should normally be utilized as a standard for worker's compensation. The adoption of AR% could be helpful for courts to make a consistent judgement whether "Karoshi" cases are compensatable or not. PMID:1392028

  11. Classical planning and causal implicatures

    DEFF Research Database (Denmark)

    Blackburn, Patrick Rowan; Benotti, Luciana

    to generate clarification requests"; as a result we can model task-oriented dialogue as an interactive process locally structured by negotiation of the underlying task. We give several examples of Frolog-human dialog, discuss the limitations imposed by the classical planning paradigm, and indicate......In this paper we motivate and describe a dialogue manager (called Frolog) which uses classical planning to infer causal implicatures. A causal implicature is a type of Gricean relation implicature, a highly context dependent form of inference. As we shall see, causal implicatures are important...

  12. On causality of extreme events

    CERN Document Server

    Zanin, Massimiliano

    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 both linear and 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.

  13. Causal Structure and Spacetime Singularities

    CERN Document Server

    Stoica, Ovidiu Cristinel

    2015-01-01

    In General Relativity the metric can be recovered from the structure of the lightcones and a measure giving the volume element. Since the causal structure seems to be simpler than the Lorentzian manifold structure, this suggests that it is more fundamental. But there are cases when seemingly healthy causal structure and measure determine a singular metric. Here it is shown that this is not a bug, but a feature, because big-bang and black hole singularities are instances of this situation. But while the metric is special at singularities, being singular, the causal structure and the measure are not special in an explicit way at singularities. Therefore, considering the causal structure more fundamental than the metric provides a more natural framework to deal with spacetime singularities.

  14. Causal reasoning with mental models

    OpenAIRE

    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 e...

  15. Consciousness and the "Causal Paradox"

    OpenAIRE

    Velmans, Max

    1996-01-01

    Viewed from a first-person perspective consciousness appears to be necessary for complex, novel human activity - but viewed from a third-person perspective consciousness appears to play no role in the activity of brains, producing a "causal paradox". To resolve this paradox one needs to distinguish consciousness of processing from consciousness accompanying processing or causing processing. Accounts of consciousness/brain causal interactions switch between first- and third-person perspectives...

  16. Realist Magic : Objects, Ontology, Causality

    OpenAIRE

    Morton, Timothy

    2013-01-01

    Object-oriented ontology offers a startlingly fresh way to think about causality that takes into account developments in physics since 1900. Causality, argues, Object Oriented Ontology (OOO), is aesthetic. In this book, Timothy Morton explores what it means to say that a thing has come into being, that it is persisting, and that it has ended. Drawing from examples in physics, biology, ecology, art, literature and music, Morton demonstrates the counterintuitive yet elegant explanatory power of...

  17. Correlation Measure Equivalence in Dynamic Causal Structures

    CERN Document Server

    Gyongyosi, Laszlo

    2016-01-01

    We prove an equivalence transformation between the correlation measure functions of the causally-unbiased quantum gravity space and the causally-biased standard space. The theory of quantum gravity fuses the dynamic (nonfixed) causal structure of general relativity and the quantum uncertainty of quantum mechanics. In a quantum gravity space, the events are causally nonseparable and all time bias vanishes, which makes it no possible to use the standard causally-biased entropy and the correlation measure functions. Since a corrected causally-unbiased entropy function leads to an undefined, obscure mathematical structure, in our approach the correction is made in the data representation of the causally-unbiased space. We prove that the standard causally-biased entropy function with a data correction can be used to identify correlations in dynamic causal structures. As a corollary, all mathematical properties of the causally-biased correlation measure functions are preserved in the causally-unbiased space. The eq...

  18. Causality, causality, causality: the view of education inputs and outputs from economics

    OpenAIRE

    Lisa Barrow; Cecilia Elena Rouse

    2005-01-01

    Educators and policy makers are increasingly intent on using scientifically-based evidence when making decisions about education policy. Thus, education research today must necessarily be focused on identifying the causal relationships between education inputs and student outcomes. In this paper we discuss methodologies for estimating the causal effect of resources on education outcomes; we also review what we believe to be the best evidence from economics on a few important inputs: spending,...

  19. Causality in physiological signals.

    Science.gov (United States)

    Müller, Andreas; Kraemer, Jan F; Penzel, Thomas; Bonnemeier, Hendrik; Kurths, Jürgen; Wessel, Niels

    2016-05-01

    Health is one of the most important non-material assets and thus also has an enormous influence on material values, since treating and preventing diseases is expensive. The number one cause of death worldwide today originates in cardiovascular diseases. For these reasons the aim of understanding the functions and the interactions of the cardiovascular system is and has been a major research topic throughout various disciplines for more than a hundred years. The purpose of most of today's research is to get as much information as possible with the lowest possible effort and the least discomfort for the subject or patient, e.g. via non-invasive measurements. A family of tools whose importance has been growing during the last years is known under the headline of coupling measures. The rationale for this kind of analysis is to identify the structure of interactions in a system of multiple components. Important information lies for example in the coupling direction, the coupling strength, and occurring time lags. In this work, we will, after a brief general introduction covering the development of cardiovascular time series analysis, introduce, explain and review some of the most important coupling measures and classify them according to their origin and capabilities in the light of physiological analyses. We will begin with classical correlation measures, go via Granger-causality-based tools, entropy-based techniques (e.g. momentary information transfer), nonlinear prediction measures (e.g. mutual prediction) to symbolic dynamics (e.g. symbolic coupling traces). All these methods have contributed important insights into physiological interactions like cardiorespiratory coupling, neuro-cardio-coupling and many more. Furthermore, we will cover tools to detect and analyze synchronization and coordination (e.g. synchrogram and coordigram). As a last point we will address time dependent couplings as identified using a recent approach employing ensembles of time series. The

  20. Uniform infinite and Gibbs causal triangulations

    NARCIS (Netherlands)

    Zohren, Stefan

    2012-01-01

    We discuss uniform infinite causal triangulations (UICT) and Gibbs causal triangulations which are probabilistic models for the causal dynamical triangulations (CDT) approach to quantum gravity. Since there is a bijection between causal triangulations and planar rooted trees we first discuss some as

  1. Causality and Tense - two temporal structure builders

    NARCIS (Netherlands)

    Oversteegen, E.

    2005-01-01

    By force of causes precede effects, causality contributes to the temporal meaning of discourse. In case of semantic causal relations, this contribution is straightforward, but in case of epistemic causal relations, it is not. In order to gain insight into the semantics of epistemic causal relations,

  2. Statistics, Causality and Bell's theorem

    CERN Document Server

    Gill, Richard D

    2012-01-01

    Bell's (1964) theorem is popularly supposed to establish the non-locality of quantum physics as a mathematical-physical theory. Building from this, observed violation of Bell's inequality in experiments such as that of Aspect and coworkers (1982) is popularly supposed to provide empirical proof of non-locality in the real world. This paper reviews recent work on Bell's theorem, linking it to issues in causality as understood by statisticians. The paper starts with a new proof of a strong (finite sample) version of Bell's theorem which relies only on elementary arithmetic and (counting) probability. This proof underscores the fact that Bell's theorem tells us that quantum theory is incompatible with the conjunction of three cherished and formerly uncontroversial physical principles, nicknamed here locality, realism, and freedom. The first, locality, is obviously connected to causality: causal influences need time to propagate spatially. Less obviously, the other two principles, realism and freedom, are also fo...

  3. Introductive remarks on causal inference

    Directory of Open Access Journals (Sweden)

    Silvana A. Romio

    2013-05-01

    Full Text Available One of the more challenging issues in epidemiological research is being able to provide an unbiased estimate of the causal exposure-disease effect, to assess the possible etiological mechanisms and the implication for public health. A major source of bias is confounding, which can spuriously create or mask the causal relationship. In the last ten years, methodological research has been developed to better de_ne the concept of causation in epidemiology and some important achievements have resulted in new statistical models. In this review, we aim to show how a technique the well known by statisticians, i.e. standardization, can be seen as a method to estimate causal e_ects, equivalent under certain conditions to the inverse probability treatment weight procedure.

  4. Causal reasoning with mental models.

    Science.gov (United States)

    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

  5. Causal reasoning with mental models

    Directory of Open Access Journals (Sweden)

    Sangeet eKhemlani

    2014-10-01

    Full Text Available 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.

  6. Gravitation, Causality, and Quantum Consistency

    CERN Document Server

    Hertzberg, Mark P

    2016-01-01

    We examine the role of consistency with causality and quantum mechanics in determining the properties of gravitation. We begin by constructing two different classes of interacting theories of massless spin 2 particles -- gravitons. One involves coupling the graviton with the lowest number of derivatives to matter, the other involves coupling the graviton with higher derivatives to matter, making use of the linearized Riemann tensor. The first class requires an infinite tower of terms for consistency, which is known to lead uniquely to general relativity. The second class only requires a finite number of terms for consistency, which appears as a new class of theories of massless spin 2. We recap the causal consistency of general relativity and show how this fails in the second class for the special case of coupling to photons, exploiting related calculations in the literature. In an upcoming publication [1] this result is generalized to a much broader set of theories. Then, as a causal modification of general ...

  7. Causality and Primordial Tensor Modes

    CERN Document Server

    Baumann, Daniel

    2009-01-01

    We introduce the real space correlation function of $B$-mode polarization of the cosmic microwave background (CMB) as a probe of superhorizon tensor perturbations created by inflation. By causality, any non-inflationary mechanism for gravitational wave production after reheating, like global phase transitions or cosmic strings, must have vanishing correlations for angular separations greater than the angle subtended by the particle horizon at recombination, i.e. $\\theta \\gtrsim 2^\\circ$. Since ordinary $B$-modes are defined non-locally in terms of the Stokes parameters $Q$ and $U$ and therefore don't have to respect causality, special care is taken to define `causal $\\tilde B$-modes' for the analysis. We compute the real space $\\tilde B$-mode correlation function for inflation and discuss its detectability on superhorizon scales where it provides an unambiguous test of inflationary gravitational waves. The correct identification of inflationary tensor modes is crucial since it relates directly to the energy s...

  8. Causal Models for Risk Management

    Directory of Open Access Journals (Sweden)

    Neysis Hernández Díaz

    2013-12-01

    Full Text Available In this work a study about the process of risk management in major schools in the world. The project management tools worldwide highlights the need to redefine risk management processes. From the information obtained it is proposed the use of causal models for risk analysis based on information from the project or company, say risks and the influence thereof on the costs, human capital and project requirements and detect the damages of a number of tasks without tribute to the development of the project. A study on the use of causal models as knowledge representation techniques causal, among which are the Fuzzy Cognitive Maps (DCM and Bayesian networks, with the most favorable MCD technique to use because it allows modeling the risk information witho ut having a knowledge base either itemize.

  9. On the Axioms of Causal Set Theory

    CERN Document Server

    Dribus, Benjamin F

    2013-01-01

    This paper offers suggested improvements to the causal sets program in discrete gravity, which treats spacetime geometry as an emergent manifestation of causal structure at the fundamental scale. This viewpoint, which I refer to as the causal metric hypothesis, is summarized by Rafael Sorkin's phrase, "order plus number equals geometry." Proposed improvements include recognition of a generally nontransitive causal relation more fundamental than the causal order, an improved local picture of causal structure, development and use of relation space methods, and a new background-independent version of the histories approach to quantum theory. Besides causal set theory, \\`a la Bombelli, Lee, Meyer, and Sorkin, this effort draws on Isham's topos-theoretic framework for physics, Sorkin's quantum measure theory, Finkelstein's causal nets, and Grothendieck's structural principles. This approach circumvents undesirable structural features in causal set theory, such as the permeability of maximal antichains, studied by ...

  10. Causality problem in Economic Science

    Directory of Open Access Journals (Sweden)

    JOSÉ LUIS RETOLAZA

    2007-12-01

    Full Text Available The main point of the paper is the problem of the economy to be consider like a science in the most strict term of the concept. In the first step we are going to tackle a presentation about what we understand by science to subsequently present some of the fallacies which have bring certain scepticism about the scientific character of the investigation in economy, to know: 1 The differences between hard and weak sciences -physics and social; 2 The differences between paradigm, —positivist and phenomenological— 3 The differences between physic causalityand historic causality. In the second step we are going to talk about two fundamental problems which are questioned: 1 the confusion between ontology and gnoseology and, 2 the erroneous concept of causality that commonly is used. In the last step of the paper we are going over the recent models of «causal explanation» and we suggest the probabilistic casualty development next with a more elaborated models of causal explanation, like a way to conjugate the scientific severity with the possibility to tackle complex economic realities.

  11. Causal Behaviour on Carter spacetime

    CERN Document Server

    Blanco, Oihane F

    2015-01-01

    In this work we will focus on the causal character of Carter Spacetime (see B. Carter, Causal structure in space-time, Gen. Rel. Grav. 1 4 337-406, 1971). The importance of this spacetime is the following: for the causally best well behaved spacetimes (the globally hyperbolic ones), there are several characterizations or alternative definitions. In some cases, it has been shown that some of the causal properties required in these characterizations can be weakened. But Carter spacetime provides a counterexample for an impossible relaxation in one of them. We studied the possibility of Carter spacetime to be a counterexample for impossible lessening in another characterization, based on the previous results. In particular, we will prove that the time-separation or Lorentzian distance between two chosen points in Carter spacetime is infinite. Although this spacetime turned out not to be the counterexample we were looking for, the found result is interesting per se and provides ideas for alternate approaches to t...

  12. Causal feedbacks in climate change

    NARCIS (Netherlands)

    Nes, van E.H.; Scheffer, M.; Brovkin, V.; Lenton, T.M.; Ye, H.; Deyle, E.; Sugihara, G.

    2015-01-01

    The statistical association between temperature and greenhouse gases over glacial cycles is well documented1, but causality behind this correlation remains difficult to extract directly from the data. A time lag of CO2 behind Antarctic temperature—originally thought to hint at a driving role for tem

  13. Granger Causality and Unit Roots

    DEFF Research Database (Denmark)

    Rodríguez-Caballero, Carlos Vladimir; Ventosa-Santaulària, Daniel

    2014-01-01

    The asymptotic behavior of the Granger-causality test under stochastic nonstationarity is studied. Our results confirm that the inference drawn from the test is not reliable when the series are integrated to the first order. In the presence of deterministic components, the test statistic diverges...

  14. Free Fermions on causal sets

    CERN Document Server

    Noldus, Johan

    2013-01-01

    We construct a Dirac theory on causal sets; a key element in the construction being that the causet must be regarded as emergent in an appropriate sense too. We further notice that mixed norm spaces appear in the construction allowing for negative norm particles and "ghosts".

  15. Entanglement, holography and causal diamonds

    Science.gov (United States)

    de Boer, Jan; Haehl, Felix M.; Heller, Michal P.; Myers, Robert C.

    2016-08-01

    We argue that the degrees of freedom in a d-dimensional CFT can be reorganized in an insightful way by studying observables on the moduli space of causal diamonds (or equivalently, the space of pairs of timelike separated points). This 2 d-dimensional space naturally captures some of the fundamental nonlocality and causal structure inherent in the entanglement of CFT states. For any primary CFT operator, we construct an observable on this space, which is defined by smearing the associated one-point function over causal diamonds. Known examples of such quantities are the entanglement entropy of vacuum excitations and its higher spin generalizations. We show that in holographic CFTs, these observables are given by suitably defined integrals of dual bulk fields over the corresponding Ryu-Takayanagi minimal surfaces. Furthermore, we explain connections to the operator product expansion and the first law of entanglemententropy from this unifying point of view. We demonstrate that for small perturbations of the vacuum, our observables obey linear two-derivative equations of motion on the space of causal diamonds. In two dimensions, the latter is given by a product of two copies of a two-dimensional de Sitter space. For a class of universal states, we show that the entanglement entropy and its spin-three generalization obey nonlinear equations of motion with local interactions on this moduli space, which can be identified with Liouville and Toda equations, respectively. This suggests the possibility of extending the definition of our new observables beyond the linear level more generally and in such a way that they give rise to new dynamically interacting theories on the moduli space of causal diamonds. Various challenges one has to face in order to implement this idea are discussed.

  16. Anticipation of physical causality guides eye movements

    OpenAIRE

    Wende, Kim; Theunissen, Laetitia; Missal, Marcus

    2016-01-01

    Causality is a unique feature of human perception. We present here a behavioral investigation of the influence of physical causality during visual pursuit of object collisions. Pursuit and saccadic eye movements of human subjects were recorded during ocular pursuit of two concurrently launched targets, one that moved according to the laws of Newtonian mechanics (the causal target) and the other one that moved in a physically implausible direction (the non-causal target). We found that anticip...

  17. Estimating causal structure using conditional DAG models

    OpenAIRE

    Oates, Chris J.; Smith, Jim Q.; Mukherjee, Sach

    2014-01-01

    This paper considers inference of causal structure in a class of graphical models called "conditional DAGs". These are directed acyclic graph (DAG) models with two kinds of variables, primary and secondary. The secondary variables are used to aid in estimation of causal relationships between the primary variables. We give causal semantics for this model class and prove that, under certain assumptions, the direction of causal influence is identifiable from the joint observational distribution ...

  18. Designing Effective Supports for Causal Reasoning

    Science.gov (United States)

    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 inferences, and…

  19. Representing Personal Determinants in Causal Structures.

    Science.gov (United States)

    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.…

  20. Exploring Individual Differences in Preschoolers' Causal Stance

    Science.gov (United States)

    Alvarez, Aubry; Booth, Amy E.

    2016-01-01

    Preschoolers, as a group, are highly attuned to causality, and this attunement is known to facilitate memory, learning, and problem solving. However, recent work reveals substantial individual variability in the strength of children's "causal stance," as demonstrated by their curiosity about and preference for new causal information. In…

  1. Expectations and Interpretations during Causal Learning

    Science.gov (United States)

    Luhmann, Christian C.; Ahn, Woo-kyoung

    2011-01-01

    In existing models of causal induction, 4 types of covariation information (i.e., presence/absence of an event followed by presence/absence of another event) always exert identical influences on causal strength judgments (e.g., joint presence of events always suggests a generative causal relationship). In contrast, we suggest that, due to…

  2. Painless causality in defect calculations

    CERN Document Server

    Cheung, C; Cheung, Charlotte; Magueijo, Joao

    1997-01-01

    Topological defects must respect causality, a statement leading to restrictive constraints on the power spectrum of the total cosmological perturbations they induce. Causality constraints have for long been known to require the presence of an under-density in the surrounding matter compensating the defect network on large scales. This so-called compensation can never be neglected and significantly complicates calculations in defect scenarios, eg. computing cosmic microwave background fluctuations. A quick and dirty way to implement the compensation are the so-called compensation fudge factors. Here we derive the complete photon-baryon-CDM backreaction effects in defect scenarios. The fudge factor comes out as an algebraic identity and so we drop the negative qualifier ``fudge''. The compensation scale is computed and physically interpreted. Secondary backreaction effects exist, and neglecting them constitutes the well-defined approximation scheme within which one should consider compensation factor calculatio...

  3. Velocity requirements for causality violation

    CERN Document Server

    Modanese, Giovanni

    2013-01-01

    It is known that the hypothetical existence of superluminal signals would imply the logical possibility of active causal violation: an observer in relative motion with respect to a primary source could in principle emit secondary superluminal signals (triggered by the primary ones) which go back in time and deactivate the primary source before the initial emission. This is a direct consequence of the structure of the Lorentz transformations, sometimes called "Regge-Tolman paradox". It is straightforward to find a formula for the velocity of the moving observer required to produce the causality violation. When applied to some recent claims of slight superluminal propagation, this formula yields a required velocity very close to the speed of light; this raises some doubts about the real physical observability of such violations. We re-compute this velocity requirement introducing a realistic delay between the reception of the primary signal and the emission of the secondary. It turns out that for -any- delay it...

  4. Phenomenology of Causal Dynamical Triangulations

    CERN Document Server

    Mielczarek, Jakub

    2015-01-01

    The four dimensional Causal Dynamical Triangulations (CDT) approach to quantum gravity is already more than ten years old theory with numerous unprecedented predictions such as non-trivial phase structure of gravitational field and dimensional running. Here, we discuss possible empirical consequences of CDT derived based on the two features of the approach mentioned above. A possibility of using both astrophysical and cosmological observations to test CDT is discussed. We show that scenarios which can be ruled out at the empirical level exist.

  5. Velocity Requirements for Causality Violation

    Science.gov (United States)

    Modanese, Giovanni

    We re-examine the "Regge-Tolman paradox" with reference to some recent experimental results. It is straightforward to find a formula for the velocity v of the moving system required to produce causality violation. This formula typically yields a velocity very close to the speed of light (for instance, v/c > 0.97 for X-shaped microwaves), which raises some doubts about the real physical observability of the violations. We then compute the velocity requirement introducing a delay between the reception of the primary signal and the emission of the secondary. It turns out that in principle for any delay it is possible to find moving observers able to produce active causal violation. This is mathematically due to the singularity of the Lorentz transformations for β →1. For a realistic delay due to the propagation of a luminal precursor, we find that causality violations in the reported experiments are still more unlikely (v/c > 0.989), and even in the hypothesis that the superluminal propagation velocity goes to infinity, the velocity requirement is bounded by v/c > 0.62. We also prove that if two oscopic bodies exchange energy and momentum through superluminal signals, then the swap of signal source and target is incompatible with the Lorentz transformations; therefore it is not possible to distinguish between source and target, even with reference to a definite reference frame.

  6. Entanglement, Holography and Causal Diamonds

    CERN Document Server

    de Boer, Jan; Heller, Michal P; Myers, Robert C

    2016-01-01

    We argue that the degrees of freedom in a d-dimensional CFT can be re-organized in an insightful way by studying observables on the moduli space of causal diamonds (or equivalently, the space of pairs of timelike separated points). This 2d-dimensional space naturally captures some of the fundamental nonlocality and causal structure inherent in the entanglement of CFT states. For any primary CFT operator, we construct an observable on this space, which is defined by smearing the associated one-point function over causal diamonds. Known examples of such quantities are the entanglement entropy of vacuum excitations and its higher spin generalizations. We show that in holographic CFTs, these observables are given by suitably defined integrals of dual bulk fields over the corresponding Ryu-Takayanagi minimal surfaces. Furthermore, we explain connections to the operator product expansion and the first law of entanglement entropy from this unifying point of view. We demonstrate that for small perturbations of the va...

  7. Breaking the arrows of causality

    DEFF Research Database (Denmark)

    Valsiner, Jaan

    2014-01-01

    Theoretical models of catalysis have proven to bring with them major breakthroughs in chemistry and biology, from the 1830s onward. It can be argued that the scientific status of chemistry has become established through the move from causal to catalytic models. Likewise, the central explanatory...... role of cyclical models in biology has made it possible to move from the idea of genetic determination to that of epigenetic negotiation as the core of biological theory. In psychology, catalytic thinking has been outside of the realm of accepted scientific schemes, as the axiomatic dependence upon the...

  8. The Impossibility of Causality Testing

    OpenAIRE

    Conway, Roger K.; P. A. V. B. Swamy; Yanagida, John F.; Muehlen, Peter von zur

    1984-01-01

    Causality tests developed by Sims and Granger are fatally flawed for several reasons First, when two variables, X and Y, are uncorrelated, X has no linear predictive value for Y, but X,and Y may be nonlinearly related unless they are statistically Independent, In which case X and Y are not related at all The light-hand side variables In a regression equation are exogenous If they are mean Independent of the disturbance term Mean Independence IS stronger than uncorrelatedness The proofs for de...

  9. Space and time in perceptual causality.

    Science.gov (United States)

    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. PMID:20463866

  10. Space and time in perceptual causality

    Directory of Open Access Journals (Sweden)

    Benjamin Straube

    2010-04-01

    Full Text Available 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.

  11. The Functions of Danish Causal Conjunctions

    Directory of Open Access Journals (Sweden)

    Rita Therkelsen

    2004-01-01

    Full Text Available In the article I propose an analysis of the Danish causal conjunctions fordi, siden and for based on the framework of Danish Functional Grammar. As conjunctions they relate two clauses, and their semantics have in common that it indicates a causal relationship between the clauses. The causal conjunctions are different as far as their distribution is concerned; siden conjoins a subordinate clause and a main clause, for conjoins two main clauses, and fordi is able to do both. Methodologically I have based my analysis on these distributional properties comparing siden and fordi conjoining a subordinate and a main clause, and comparing for and fordi conjoining two main clauses, following the thesis that they would establish a causal relationship between different kinds of content. My main findings are that fordi establishes a causal relationship between the events referred to by the two clauses, and the whole utterance functions as a statement of this causal relationship. Siden presupposes such a general causal relationship between the two events and puts forward the causing event as a reason for assuming or wishing or ordering the caused event, siden thus establishes a causal relationship between an event and a speech act. For equally presupposes a general causal relationship between two events and it establishes a causal relationship between speech acts, and fordi conjoining two main clauses is able to do this too, but in this position it also maintains its event-relating ability, the interpretation depending on contextual factors.

  12. Probabilistic causality and radiogenic cancers

    International Nuclear Information System (INIS)

    A review and scrutiny of the literature on probability and probabilistic causality shows that it is possible under certain assumptions to estimate the probability that a certain type of cancer diagnosed in an individual exposed to radiation prior to diagnosis was caused by this exposure. Diagnosis of this causal relationship like diagnosis of any disease - malignant or not - requires always some subjective judgments by the diagnostician. It is, therefore, illusory to believe that tables based on actuarial data can provide objective estimates of the chance that a cancer diagnosed in an individual is radiogenic. It is argued that such tables can only provide a base from which the diagnostician(s) deviate in one direction or the other according to his (their) individual (consensual) judgment. Acceptance of a physician's diagnostic judgment by patients is commonplace. Similar widespread acceptance of expert judgment by claimants in radiation compensation cases does presently not exist. Judicious use of the present radioepidemiological tables prepared by the Working Group of the National Institutes of Health or of updated future versions of similar tables may improve the situation. 20 references

  13. Linear causal modeling with structural equations

    CERN Document Server

    Mulaik, Stanley A

    2009-01-01

    Emphasizing causation as a functional relationship between variables that describe objects, Linear Causal Modeling with Structural Equations integrates a general philosophical theory of causation with structural equation modeling (SEM) that concerns the special case of linear causal relations. In addition to describing how the functional relation concept may be generalized to treat probabilistic causation, the book reviews historical treatments of causation and explores recent developments in experimental psychology on studies of the perception of causation. It looks at how to perceive causal

  14. The problem of causality in cultivation research

    OpenAIRE

    Rossmann, Constanze; Brosius, Hans-Bernd

    2004-01-01

    This paper offers an up-to-date review of problems in determining causal relationships in cultivation research, and considers the research rationales of various approaches with special reference to causal interpretation. It describes in turn a number of methodologies for addressing the problem and resolving it as far as this is possible. The issue of causal inference arises not only in cultivation research, however, but is basic to all media effects theories and approaches primarily at the ma...

  15. Identifying Causal Effects with Computer Algebra

    CERN Document Server

    García-Puente, Luis David; Sullivant, Seth

    2010-01-01

    The long-standing identification problem for causal effects in graphical models has many partial results but lacks a systematic study. We show how computer algebra can be used to either prove that a causal effect can be identified, generically identified, or show that the effect is not generically identifiable. We report on the results of our computations for linear structural equation models, where we determine precisely which causal effects are generically identifiable for all graphs on three and four vertices.

  16. Causal inference in economics and marketing.

    Science.gov (United States)

    Varian, Hal R

    2016-07-01

    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

  17. Causal inference in economics and marketing

    Science.gov (United States)

    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

  18. Heterogeneous Causal Effects and Sample Selection Bias

    DEFF Research Database (Denmark)

    Breen, Richard; Choi, Seongsoo; Holm, Anders

    2015-01-01

    The role of education in the process of socioeconomic attainment is a topic of long standing interest to sociologists and economists. Recently there has been growing interest not only in estimating the average causal effect of education on outcomes such as earnings, but also in estimating how...... causal effects might vary over individuals or groups. In this paper we point out one of the under-appreciated hazards of seeking to estimate heterogeneous causal effects: conventional selection bias (that is, selection on baseline differences) can easily be mistaken for heterogeneity of causal effects...

  19. Causal ubiquity in quantum physics. A superluminal and local-causal physical ontology

    Energy Technology Data Exchange (ETDEWEB)

    Neelamkavil, Raphael

    2014-07-01

    A fixed highest criterial velocity (of light) in STR (special theory of relativity) is a convention for a layer of physical inquiry. QM (Quantum Mechanics) avoids action-at-a-distance using this concept, but accepts non-causality and action-at-a-distance in EPR (Einstein-Podolsky-Rosen-Paradox) entanglement experiments. Even in such allegedly [non-causal] processes, something exists processually in extension-motion, between the causal and the [non-causal]. If STR theoretically allows real-valued superluminal communication between EPR entangled particles, quantum processes become fully causal. That is, the QM world is sub-luminally, luminally and superluminally local-causal throughout, and the Law of Causality is ubiquitous in the micro-world. Thus, ''probabilistic causality'' is a merely epistemic term.

  20. Comparison theorems for causal diamonds

    CERN Document Server

    Berthiere, Clement; Solodukhin, Sergey N

    2015-01-01

    We formulate certain inequalities for the geometric quantities characterizing causal diamonds in curved and Minkowski spacetimes. These inequalities involve the red-shift 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 centre. As a byproduct of our discussion we re-derive 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 {\\it 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 behaviours 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 nea...

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

    Science.gov (United States)

    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…

  2. Unpacking the causal chain of financial literacy

    OpenAIRE

    Carpena, Fenella; Cole, Shawn; Shapiro, Jeremy; Zia, Bilal

    2011-01-01

    A growing body of literature examines the causal impact of financial literacy on individual, household, and firm level outcomes. This paper unpacks the mechanism of impact by focusing on the first link in the causal chain. Specifically, it studies the experimental impact of financial literacy on three distinct dimensions of financial knowledge. The analysis finds that financial literacy do...

  3. Causal Indicator Models: Identification, Estimation, and Testing

    Science.gov (United States)

    Bollen, Kenneth A.; Davis, Walter R.

    2009-01-01

    We discuss the identification, estimation, and testing of structural equation models that have causal indicators. We first provide 2 rules of identification that are particularly helpful in models with causal indicators--the 2C emitted paths rule and the exogenous X rule. We demonstrate how these rules can help us distinguish identified from…

  4. Causal Moderation Analysis Using Propensity Score Methods

    Science.gov (United States)

    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…

  5. Controlling for causally relevant third variables.

    Science.gov (United States)

    Goodie, Adam S; Williams, Cristina C; Crooks, C L

    2003-10-01

    In 3 experiments, the authors tested the conditions under which 3rd variables are controlled for in making causal judgments. The authors hypothesized that 3rd variables are controlled for when the 3rd variables are themselves perceived as causal. In Experiment 1, the participants predicted test performance after seeing information about wearing a lucky garment, taking a test-preparation course, and staying up late. The course (perceived as more causally relevant) was controlled for more than was the garment (perceived as less causally relevant) in assessing the effectiveness of staying up late. In Experiments 2 and 3, to obviate the many alternative accounts that arise from the realistic cover story of Experiment 1, participants predicted flowers' blooming after the presentation or nonpresentation of liquids. When one liquid was trained as causal, it was controlled for more in judging another liquid than when it was trained as neutral. Overall, stimuli perceived as causal were controlled for more when judging other stimuli. The authors concluded that the effect of perceived causal relevance on causal conditionalizing is real and normatively reasonable. PMID:14672103

  6. On the spectral formulation of Granger causality.

    Science.gov (United States)

    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.

  7. mediation: R Package for Causal Mediation Analysis

    Directory of Open Access Journals (Sweden)

    Dustin Tingley

    2014-09-01

    Full Text Available In this paper, we describe the R package mediation for conducting causal mediation analysis in applied empirical research. In many scientific disciplines, the goal of researchers is not only estimating causal effects of a treatment but also understanding the process in which the treatment causally affects the outcome. Causal mediation analysis is frequently used to assess potential causal mechanisms. The mediation package implements a comprehensive suite of statistical tools for conducting such an analysis. The package is organized into two distinct approaches. Using the model-based approach, researchers can estimate causal mediation effects and conduct sensitivity analysis under the standard research design. Furthermore, the design-based approach provides several analysis tools that are applicable under different experimental designs. This approach requires weaker assumptions than the model-based approach. We also implement a statistical method for dealing with multiple (causally dependent mediators, which are often encountered in practice. Finally, the package also offers a methodology for assessing causal mediation in the presence of treatment noncompliance, a common problem in randomized trials.

  8. Causally pathological spacetimes are physically relevant

    CERN Document Server

    Hubeny, V E; Ross, S F; Hubeny, Veronika E.; Rangamani, Mukund; Ross, Simon F.

    2005-01-01

    We argue that in the context of string theory, the usual restriction to globally hyperbolic spacetimes should be considerably relaxed. We exhibit an example of a spacetime which only satisfies the causal condition, and so is arbitrarily close to admitting closed causal curves, but which has a well-behaved dual description, free of paradoxes.

  9. Structural intervention distance for evaluating causal graphs

    DEFF Research Database (Denmark)

    Peters, Jonas; Bühlmann, Peter

    2015-01-01

    Causal inference relies on the structure of a graph, often a directed acyclic graph (DAG). Different graphs may result in different causal inference statements and different intervention distributions. To quantify such differences, we propose a (pre-)metric between DAGs, the structural interventi...... implementation with software code available on the first author's home page....

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

    Science.gov (United States)

    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…

  11. Causalities of the Taiwan Stock Market

    OpenAIRE

    Juhi-Lian Julian Ting

    2003-01-01

    Volatility, fitting with first order Landau expansion, stationarity, and causality of the Taiwan stock market (TAIEX) are investigated based on daily records. Instead of consensuses that consider stock market index change as a random time series we propose the market change as a dual time series consists of the index and the corresponding volume. Therefore, causalities between these two time series are investigated.

  12. Causal random geometry from stochastic quantization

    DEFF Research Database (Denmark)

    Ambjørn, Jan; Loll, R.; Westra, W.;

    2010-01-01

     in this short note we review a recently found formulation of two-dimensional causal quantum gravity defined through Causal Dynamical Triangulations and stochastic quantization. This procedure enables one to extract the nonperturbative quantum Hamiltonian of the random surface model including the...... the sum over topologies. Interestingly, the generally fictitious stochastic time corresponds to proper time on the geometries...

  13. Causality, Bell's theorem, and Ontic Definiteness

    CERN Document Server

    Henson, Joe

    2011-01-01

    Bell's theorem shows that the reasonable relativistic causal principle known as "local causality" is not compatible with the predictions of quantum mechanics. It is not possible maintain a satisfying causal principle of this type while dropping any of the better-known assumptions of Bell's theorem. However, another assumption of Bell's theorem is the use of classical logic. One part of this assumption is the principle of "ontic definiteness", that is, that it must in principle be possible to assign definite truth values to all propositions treated in the theory. Once the logical setting is clarified somewhat, it can be seen that rejecting this principle does not in any way undermine the type of causal principle used by Bell. Without ontic definiteness, the deterministic causal condition known as Einstein Locality succeeds in banning superluminal influence (including signalling) whilst allowing correlations that violate Bell's inequalities. Objections to altering logic, and the consequences for operational and...

  14. Granger causality in wall-bounded turbulence

    International Nuclear Information System (INIS)

    Granger causality is based on the idea that if a variable helps to predict another one, then they are probably involved in a causality relationship. This technique is based on the identification of a predictive model for causality detection. The aim of this paper is to use Granger causality to study the dynamics and the energy redistribution between scales and components in wall-bounded turbulent flows. In order to apply it on flows, Granger causality is generalized for snapshot-based observations of large size using linear-model identification methods coming from model reduction. Optimized DMD, a variant of the Dynamic Mode Decomposition, is considered for building a linear model based on snapshots. This method is used to link physical events and extract physical mechanisms associated to the bursting process in the logarithmic layer of a turbulent channel flow.

  15. Quantum-coherent mixtures of causal relations

    CERN Document Server

    MacLean, Jean-Philippe W; Spekkens, Robert W; Resch, Kevin J

    2016-01-01

    Understanding the causal influences that hold among the parts of a system is critical both to explaining that system's natural behaviour and to controlling it through targeted interventions. In a quantum world, understanding causal relations is equally important, but the set of possibilities is far richer. The two basic ways in which a pair of time-ordered quantum systems may be causally related are by a cause-effect mechanism or by a common cause acting on both. Here, we show that it is possible to have a coherent mixture of these two possibilities. We realize such a nonclassical causal relation in a quantum optics experiment and derive a set of criteria for witnessing the coherence based on a quantum version of Berkson's paradox. The interplay of causality and quantum theory lies at the heart of challenging foundational puzzles, such as Bell's theorem and the search for quantum gravity, but could also provide a resource for novel quantum technologies.

  16. On the spectral dimension of causal triangulations

    CERN Document Server

    Durhuus, Bergfinnur; Wheater, John F

    2009-01-01

    We introduce an ensemble of infinite causal triangulations, called the uniform infinite causal triangulation, and show that it is equivalent to an ensemble of infinite trees, the uniform infinite planar tree. It is proved that in both cases the Hausdorff dimension almost surely equals 2. The infinite causal triangulations are shown to be almost surely recurrent or, equivalently, their spectral dimension is almost surely less than or equal to 2. We also establish that for certain reduced versions of the infinite causal triangulations the spectral dimension equals 2 both for the ensemble average and almost surely. The triangulation ensemble we consider is equivalent to the causal dynamical triangulation model of two-dimensional quantum gravity and therefore our results apply to that model.

  17. Causal ubiquity in quantum physics a superluminal and local-causal physical ontology

    CERN Document Server

    Neelamkavil, Raphael

    2014-01-01

    A fixed highest criterial velocity (of light) in STR (special theory of relativity) is a convention for a layer of physical inquiry. QM (Quantum Mechanics) avoids action-at-a-distance using this concept, but accepts non-causality and action-at-a-distance in EPR (Einstein-Podolsky-Rosen-Paradox) entanglement experiments. Even in such allegedly non-causal processes, something exists processually in extension-motion, between the causal and the non-causal. If STR theoretically allows real-valued superluminal communication between EPR entangled particles, quantum processes become fully causal. That

  18. Causal systems categories: differences in novice and expert categorization of causal phenomena.

    Science.gov (United States)

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

    2012-07-01

    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 feedback vs. causal chain) and in their content domain (e.g., economics vs. biology). Our hypothesis was that there would be a shift from domain-based sorting to causal sorting with increasing expertise in the relevant domains. This prediction was borne out: the novice groups sorted primarily by domain and the expert group sorted by causal category. These results suggest that science training facilitates insight about causal structures.

  19. Spread of entanglement and causality

    Science.gov (United States)

    Casini, Horacio; Liu, Hong; Mezei, Márk

    2016-07-01

    We investigate causality constraints on the time evolution of entanglement entropy after a global quench in relativistic theories. We first provide a general proof that the so-called tsunami velocity is bounded by the speed of light. We then generalize the free particle streaming model of [1] to general dimensions and to an arbitrary entanglement pattern of the initial state. In more than two spacetime dimensions the spread of entanglement in these models is highly sensitive to the initial entanglement pattern, but we are able to prove an upper bound on the normalized rate of growth of entanglement entropy, and hence the tsunami velocity. The bound is smaller than what one gets for quenches in holographic theories, which highlights the importance of interactions in the spread of entanglement in many-body systems. We propose an interacting model which we believe provides an upper bound on the spread of entanglement for interacting relativistic theories. In two spacetime dimensions with multiple intervals, this model and its variations are able to reproduce intricate results exhibited by holographic theories for a significant part of the parameter space. For higher dimensions, the model bounds the tsunami velocity at the speed of light. Finally, we construct a geometric model for entanglement propagation based on a tensor network construction for global quenches.

  20. Spread of entanglement and causality

    CERN Document Server

    Casini, Horacio; Mezei, Márk

    2015-01-01

    We investigate causality constraints on the time evolution of entanglement entropy after a global quench in relativistic theories. We first provide a general proof that the so-called tsunami velocity is bounded by the speed of light. We then generalize the free particle streaming model of arXiv:cond-mat/0503393 to general dimensions and to an arbitrary entanglement pattern of the initial state. In more than two spacetime dimensions the spread of entanglement in these models is highly sensitive to the initial entanglement pattern, but we are able to prove an upper bound on the normalized rate of growth of entanglement entropy, and hence the tsunami velocity. The bound is smaller than what one gets for quenches in holographic theories, which highlights the importance of interactions in the spread of entanglement in many-body systems. We propose an interacting model which we believe provides an upper bound on the spread of entanglement for interacting relativistic theories. In two spacetime dimensions with multi...

  1. Mining Causality for Explanation Knowledge from Text

    Institute of Scientific and Technical Information of China (English)

    Chaveevan Pechsiri; Asanee Kawtrakul

    2007-01-01

    Mining causality is essential to provide a diagnosis. This research aims at extracting the causality existing within multiple sentences or EDUs (Elementary Discourse Unit). The research emphasizes the use of causality verbs because they make explicit in a certain way the consequent events of a cause, e.g., "Aphids suck the sap from rice leaves. Then leaves will shrink. Later, they will become yellow and dry.". A verb can also be the causal-verb link between cause and effect within EDU(s), e.g., "Aphids suck the sap from rice leaves causing leaves to be shrunk" ("causing" is equivalent to a causal-verb link in Thai). The research confronts two main problems: identifying the interesting causality events from documents and identifying their boundaries. Then, we propose mining on verbs by using two different machine learning techniques, Naive Bayes classifier and Support Vector Machine. The resulted mining rules will be used for the identification and the causality extraction of the multiple EDUs from text. Our multiple EDUs extraction shows 0.88 precision with 0.75 recall from Na'ive Bayes classifier and 0.89 precision with 0.76 recall from Support Vector Machine.

  2. Causal localizations in relativistic quantum mechanics

    International Nuclear Information System (INIS)

    Causal localizations describe the position of quantum systems moving not faster than light. They are constructed for the systems with finite spinor dimension. At the center of interest are the massive relativistic systems. For every positive mass, there is the sequence of Dirac tensor-localizations, which provides a complete set of inequivalent irreducible causal localizations. They obey the principle of special relativity and are fully Poincaré covariant. The boosters are determined by the causal position operator and the other Poincaré generators. The localization with minimal spinor dimension is the Dirac localization. Thus, the Dirac equation is derived here as a mere consequence of the principle of causality. Moreover, the higher tensor-localizations, not known so far, follow from Dirac’s localization by a simple construction. The probability of localization for positive energy states results to be described by causal positive operator valued (PO-) localizations, which are the traces of the causal localizations on the subspaces of positive energy. These causal Poincaré covariant PO-localizations for every irreducible massive relativistic system were, all the more, not known before. They are shown to be separated. Hence, the positive energy systems can be localized within every open region by a suitable preparation as accurately as desired. Finally, the attempt is made to provide an interpretation of the PO-localization operators within the frame of conventional quantum mechanics attributing an important role to the negative energy states

  3. Causal localizations in relativistic quantum mechanics

    Energy Technology Data Exchange (ETDEWEB)

    Castrigiano, Domenico P. L., E-mail: castrig@ma.tum.de; Leiseifer, Andreas D., E-mail: andreas.leiseifer@tum.de [Fakultät für Mathematik, TU München, Boltzmannstraße 3, 85747 Garching (Germany)

    2015-07-15

    Causal localizations describe the position of quantum systems moving not faster than light. They are constructed for the systems with finite spinor dimension. At the center of interest are the massive relativistic systems. For every positive mass, there is the sequence of Dirac tensor-localizations, which provides a complete set of inequivalent irreducible causal localizations. They obey the principle of special relativity and are fully Poincaré covariant. The boosters are determined by the causal position operator and the other Poincaré generators. The localization with minimal spinor dimension is the Dirac localization. Thus, the Dirac equation is derived here as a mere consequence of the principle of causality. Moreover, the higher tensor-localizations, not known so far, follow from Dirac’s localization by a simple construction. The probability of localization for positive energy states results to be described by causal positive operator valued (PO-) localizations, which are the traces of the causal localizations on the subspaces of positive energy. These causal Poincaré covariant PO-localizations for every irreducible massive relativistic system were, all the more, not known before. They are shown to be separated. Hence, the positive energy systems can be localized within every open region by a suitable preparation as accurately as desired. Finally, the attempt is made to provide an interpretation of the PO-localization operators within the frame of conventional quantum mechanics attributing an important role to the negative energy states.

  4. Perception of causality in schizophrenia spectrum disorder.

    Science.gov (United States)

    Tschacher, Wolfgang; Kupper, Zeno

    2006-10-01

    Patients with schizophrenia spectrum disorders often maintain deviating views on cause-effect relationships, especially when positive and disorganization symptoms are manifest. Altered perceived causality is prominent in delusional ideation, in ideas of reference, and in the mentalizing ability (theory of mind [ToM]) of patients. Perceiving causal relationships may be understood either as higher order cognitive reasoning or as low-level information processing. In the present study, perception of causality was investigated as a low-level, preattentional capability similar to gestalt-like perceptual organization. Thirty-one patients (24 men and 7 women with mean age 27.7 years) and the same number of healthy control subjects matched to patients with respect to age and sex were tested. A visual paradigm was used in which 2 identical discs move, from opposite sides of a monitor, steadily toward and then past one another. Their coincidence generates an ambiguous, bistable percept (discs either "stream through" or "bounce off" one another). The bouncing perception, ie, perceived causality, is enhanced when auditory stimuli are presented at the time of coincidence. Psychopathology was measured using the Positive and Negative Syndrome Scale. It was found that positive symptoms were strongly associated with increased perceived causality and disorganization with attenuated perceived causality. Patients in general were not significantly different from controls, but symptom subgroups showed specifically altered perceived causality. Perceived causality as a basic preattentional process may contribute to higher order cognitive alterations and ToM deficiencies. It is suggested that cognitive remediation therapy should address both increased and reduced perception of causality. PMID:16896057

  5. On the origin of Hill's causal criteria.

    Science.gov (United States)

    Morabia, A

    1991-09-01

    The rules to assess causation formulated by the eighteenth century Scottish philosopher David Hume are compared to Sir Austin Bradford Hill's causal criteria. The strength of the analogy between Hume's rules and Hill's causal criteria suggests that, irrespective of whether Hume's work was known to Hill or Hill's predecessors, Hume's thinking expresses a point of view still widely shared by contemporary epidemiologists. The lack of systematic experimental proof to causal inferences in epidemiology may explain the analogy of Hume's and Hill's, as opposed to Popper's, logic.

  6. Causal localizations in relativistic quantum mechanics

    Energy Technology Data Exchange (ETDEWEB)

    Leiseifer, Andreas David

    2014-06-30

    Sufficient and necessary conditions for causal localizations of massive relativistic systems are developed. It is proven that the Dirac- and the Dirac tensor-system are up to unitary equivalence the only irreducible causal localizations with finite spinor dimension which have a massive relativistic extension. A formula for this extension is given. The existence of arbitrarily good localized states of positive energy is shown. In the context of the causality condition a Paley-Wiener theorem for bounded measurable matrix-valued functions is proven.

  7. Causality and momentum conservation from relative locality

    Science.gov (United States)

    Amelino-Camelia, Giovanni; Bianco, Stefano; Brighenti, Francesco; Buonocore, Riccardo Junior

    2015-04-01

    Theories involving curved momentum space, which recently became a topic of interest in the quantum-gravity literature, can, in general, violate many apparently robust aspects of our current description of the laws of physics, including relativistic invariance, locality, causality, and global momentum conservation. Here, we explore some aspects of the pathologies arising in generic theories involving curved momentum space for what concerns causality and momentum conservation. However, we also report results suggesting that when momentum space is maximally symmetric, and the theory is formulated relativistically, most notably including translational invariance with the associated relativity of spacetime locality, momentum is globally conserved and there is no violation of causality.

  8. Causal structures of pp-waves

    CERN Document Server

    Hubeny, V E; Hubeny, Veronika E.; Rangamani, Mukund

    2002-01-01

    We discuss the causal structure of pp-wave spacetimes using the ideal point construction outlined by Geroch, Kronheimer, and Penrose. This generalizes the recent work of Marolf and Ross, who considered similar issues for plane wave spacetimes. We address the question regarding the dimension of the causal boundary for certain specific pp-wave backgrounds. In particular, we demonstrate that the pp-wave spacetime which gives rise to the N = 2 sine-Gordon string world-sheet theory is geodesically complete and has a one-dimensional causal boundary.

  9. The CMB in a Causal Set Universe

    CERN Document Server

    Zuntz, Joe

    2007-01-01

    We discuss Cosmic Microwave Background constraints on the causal set theory of quantum gravity, which has made testable predictions about the nature of dark energy. We flesh out previously discussed heuristic constraints by showing how the power spectrum of causal set dark energy fluctuations can be found from the overlap volumes of past light cones of points in the universe. Using a modified Boltzmann code we put constraints on the single parameter of the theory that are somewhat stronger than previous ones. We conclude that causal set theory cannot explain late-time acceleration without radical alterations to General Relativity.

  10. Intrinsic Universality of Causal Graph Dynamics

    Directory of Open Access Journals (Sweden)

    Simon Martiel

    2013-09-01

    Full Text Available Causal graph dynamics are transformations over graphs that capture two important symmetries of physics, namely causality and homogeneity. They can be equivalently defined as continuous and translation invariant transformations or functions induced by a local rule applied simultaneously on every vertex of the graph. Intrinsic universality is the ability of an instance of a model to simulate every other instance of the model while preserving the structure of the computation at every step of the simulation. In this work we present the construction of a family of intrinsically universal instances of causal graphs dynamics, each instance being able to simulate a subset of instances.

  11. Selecting appropriate cases when tracing causal mechanisms

    DEFF Research Database (Denmark)

    Beach, Derek; Pedersen, Rasmus Brun

    2016-01-01

    , ontological determinism, causal asymmetry and causal homogeneity and the importance of context. We then develop a set of case selection guidelines that are in methodological alignment with these underlying assumptions. Section 4 develops guidelines for research where the mechanism is the primary focus......The last decade has witnessed resurgence in the interest in studying the causal mechanisms linking causes and outcomes in the social sciences. This article explores the overlooked implications for case selection when tracing mechanisms using in-depth case studies. Our argument is that existing case...... selection guidelines are appropriate for research aimed at making cross-case claims about causal relationships, where case selection is primarily used to control for other causes. However, existing guidelines are not in alignment with case-based research that aims to trace mechanisms, where the goal is to...

  12. A Causal Model for Diagnostic Reasoning

    Institute of Scientific and Technical Information of China (English)

    PENG Guoqiang; CHENG Hu

    2000-01-01

    Up to now, there have been many methods for knowledge representation and reasoning in causal networks, but few of them include the research on the coactions of nodes. In practice, ignoring these coactions may influence the accuracy of reasoning and even give rise to incorrect reasoning. In this paper, based on multilayer causal networks, the definitions on coaction nodes are given to construct a new causal network called Coaction Causal Network, which serves to construct a model of neural network for diagnosis followed by fuzzy reasoning, and then the activation rules are given and neural computing methods are used to finish the diagnostic reasoning. These methods are proved in theory and a method of computing the number of solutions for the diagnostic reasoning is given. Finally, the experiments and the conclusions are presented.

  13. The Gravity Dual of Boundary Causality

    CERN Document Server

    Engelhardt, Netta

    2016-01-01

    In gauge/gravity duality, points which are not causally related on the boundary cannot be causally related through the bulk; this is the statement of boundary causality. By the Gao-Wald theorem, the averaged null energy condition in the bulk is sufficient to ensure this property. Here we proceed in the converse direction: we derive a necessary as well as sufficient condition for the preservation of boundary causality under perturbative (quantum or stringy) corrections to the bulk. The condition that we find is a (background-dependent) constraint on the amount by which light cones can "open" over all null bulk geodesics. We show that this constraint is weaker than the averaged null energy condition.

  14. The Temporal Logic of Causal Structures

    CERN Document Server

    Kleinberg, Samantha

    2012-01-01

    Computational analysis of time-course data with an underlying causal structure is needed in a variety of domains, including neural spike trains, stock price movements, and gene expression levels. However, it can be challenging to determine from just the numerical time course data alone what is coordinating the visible processes, to separate the underlying prima facie causes into genuine and spurious causes and to do so with a feasible computational complexity. For this purpose, we have been developing a novel algorithm based on a framework that combines notions of causality in philosophy with algorithmic approaches built on model checking and statistical techniques for multiple hypotheses testing. The causal relationships are described in terms of temporal logic formulae, reframing the inference problem in terms of model checking. The logic used, PCTL, allows description of both the time between cause and effect and the probability of this relationship being observed. We show that equipped with these causal f...

  15. What becomes of a causal set

    CERN Document Server

    Wuthrich, Christian

    2015-01-01

    Unlike the relativity theory it seeks to replace, causal set theory has been interpreted to leave space for a substantive, though perhaps 'localized', form of 'becoming'. The possibility of fundamental becoming is nourished by the fact that the analogue of Stein's theorem from special relativity does not hold in causal set theory. Despite this, we find that in many ways, the debate concerning becoming parallels the well-rehearsed lines it follows in the domain of relativity. We present, however, some new twists and challenges. In particular, we show that a novel and exotic notion of becoming is compatible with causal sets. In contrast to the 'localized' becoming considered compatible with the dynamics of causal set theory by its advocates, our novel kind of becoming, while not answering to the typical A-theoretic demands, is 'global' and objective.

  16. Ten simple rules for dynamic causal modeling.

    NARCIS (Netherlands)

    Stephan, K.E.; Penny, W.D.; Moran, R.J.; Ouden, H.E.M. den; Daunizeau, J.; Friston, K.J.

    2010-01-01

    Dynamic causal modeling (DCM) is a generic Bayesian framework for inferring hidden neuronal states from measurements of brain activity. It provides posterior estimates of neurobiologically interpretable quantities such as the effective strength of synaptic connections among neuronal populations and

  17. Causality Between Urban Concentration and Environmental Quality

    Directory of Open Access Journals (Sweden)

    Amin Pujiati

    2015-08-01

    Full Text Available Population is concentrated in urban areas can cause the external diseconomies on environment if it exceeds the carrying capacity of the space and the urban economy. Otherwise the quality of the environment is getting better, led to the concentration of population in urban areas are increasingly high. This study aims to analyze the relationship of causality between the urban concentration and environmental quality in urban agglomeration areas. The data used in the study of secondary data obtained from the Central Bureau of statistics and the City Government from 2000 to 2013. The analytical method used is the Granger causality and descriptive. Granger causality study results showed no pattern of reciprocal causality, between urban concentration and the quality of the environment, but there unidirectional relationship between the urban concentration and environmental quality. This means that increasing urban concentration led to decreased environmental quality.

  18. Causal Structure and Birefringence in Nonlinear Electrodynamics

    OpenAIRE

    de Melo, C. A. M.; Medeiros, L. G.; Pompeia, P. J.(Instituto de Fomento e Coordenação Industrial, Departamento de Ciência e Tecnologia Aeroespacial, Praça Mal. Eduardo Gomes 50, 12228-901, São José dos Campos, SP , Brazil)

    2014-01-01

    We investigate the causal structure of general nonlinear electrodynamics and determine which Lagrangians generate an effective metric conformal to Minkowski. We also proof that there is only one analytic nonlinear electrodynamics presenting no birefringence.

  19. The Causal Effects of Father Absence

    OpenAIRE

    McLanahan, Sara; TACH, LAURA; Schneider, Daniel

    2013-01-01

    The literature on father absence is frequently criticized for its use of cross-sectional data and methods that fail to take account of possible omitted variable bias and reverse causality. We review studies that have responded to this critique by employing a variety of innovative research designs to identify the causal effect of father absence, including studies using lagged dependent variable models, growth curve models, individual fixed effects models, sibling fixed effects models, natural ...

  20. Locally Causal Dynamical Triangulations in Two Dimensions

    CERN Document Server

    Loll, Renate

    2015-01-01

    We analyze the universal properties of a new two-dimensional quantum gravity model defined in terms of Locally Causal Dynamical Triangulations (LCDT). Measuring the Hausdorff and spectral dimensions of the dynamical geometrical ensemble, we find numerical evidence that the continuum limit of the model lies in a new universality class of two-dimensional quantum gravity theories, inequivalent to both Euclidean and Causal Dynamical Triangulations.

  1. Inter-causal Independence and Heterogeneous Factorization

    OpenAIRE

    Zhang, Nevin Lianwen; Poole, David L

    2013-01-01

    It is well known that conditional independence can be used to factorize a joint probability into a multiplication of conditional probabilities. This paper proposes a constructive definition of inter-causal independence, which can be used to further factorize a conditional probability. An inference algorithm is developed, which makes use of both conditional independence and inter-causal independence to reduce inference complexity in Bayesian networks.

  2. Causal Inference in Urban and Regional Economics

    OpenAIRE

    Nathaniel Baum-Snow; Fernando Ferreira

    2014-01-01

    Recovery of causal relationships in data is an essential part of scholarly inquiry in the social sciences. This chapter discusses strategies that have been successfully used in urban and regional economics for recovering such causal relationships. Essential to any successful empirical inquiry is careful consideration of the sources of variation in the data that identify parameters of interest. Interpretation of such parameters should take into account the potential for their heterogeneity as ...

  3. Causal transmission in reduced-form models

    OpenAIRE

    Vassili Bazinas; Bent Nielsen

    2015-01-01

    We propose a method to explore the causal transmission of a catalyst variable through two endogenous variables of interest. The method is based on the reduced-form system formed from the conditional distribution of the two endogenous variables given the catalyst. The method combines elements from instru- mental variable analysis and Cholesky decomposition of structural vector autoregressions. We give conditions for uniqueness of the causal transmission.

  4. Causales de ausencia de responsabilidad penal

    Directory of Open Access Journals (Sweden)

    Jaime Sandoval Fernández

    2003-01-01

    Full Text Available Este trabajo se ocupa de las causales de ausencia de responsabilidad penal, especialmente de aquellas que tienen efecto en el injusto. Como subtemas se delimita el concepto de responsabilidad penal y su ausencia. Se estudian las principales teorias a cerca de la relación tipicidad-antijuridicidad y su incidencia en el derecho penal colombiano. Por último contiene una propuesta acerca de cómo deberian agruparse las causales del arto 32 C. PlOO.

  5. Associative foundation of causal learning in rats.

    Science.gov (United States)

    Polack, Cody W; McConnell, Bridget L; Miller, Ralph R

    2013-03-01

    Are humans unique in their ability to interpret exogenous events as causes? We addressed this question by observing the behavior of rats for indications of causal learning. Within an operant motor-sensory preconditioning paradigm, associative surgical techniques revealed that rats attempted to control an outcome (i.e., a potential effect) by manipulating a potential exogenous cause (i.e., an intervention). Rats were able to generate an innocuous auditory stimulus. This stimulus was then paired with an aversive stimulus. The animals subsequently avoided potential generation of the predictive cue, but not if the aversive stimulus was subsequently devalued or the predictive cue was extinguished (Exp. 1). In Experiment 2, we demonstrated that the aversive stimulus we used was in fact aversive, that it was subject to devaluation, that the cue-aversive stimulus pairings did make the cue a conditioned stimulus, and that the cue was subject to extinction. In Experiments 3 and 4, we established that the decrease in leverpressing observed in Experiment 1 was goal-directed instrumental behavior rather than purely a product of Pavlovian conditioning. To the extent that interventions suggest causal reasoning, it appears that causal reasoning can be based on associations between contiguous exogenous events. Thus, contiguity appears capable of establishing causal relationships between exogenous events. Our results challenge the widely held view that causal learning is uniquely human, and suggest that causal learning is explicable in an associative framework. PMID:22562460

  6. Linear structures, causal sets and topology

    Science.gov (United States)

    Hudetz, Laurenz

    2015-11-01

    Causal set theory and the theory of linear structures (which has recently been developed by Tim Maudlin as an alternative to standard topology) share some of their main motivations. In view of that, I raise and answer the question how these two theories are related to each other and to standard topology. I show that causal set theory can be embedded into Maudlin's more general framework and I characterise what Maudlin's topological concepts boil down to when applied to discrete linear structures that correspond to causal sets. Moreover, I show that all topological aspects of causal sets that can be described in Maudlin's theory can also be described in the framework of standard topology. Finally, I discuss why these results are relevant for evaluating Maudlin's theory. The value of this theory depends crucially on whether it is true that (a) its conceptual framework is as expressive as that of standard topology when it comes to describing well-known continuous as well as discrete models of spacetime and (b) it is even more expressive or fruitful when it comes to analysing topological aspects of discrete structures that are intended as models of spacetime. On one hand, my theorems support (a). The theory is rich enough to incorporate causal set theory and its definitions of topological notions yield a plausible outcome in the case of causal sets. On the other hand, the results undermine (b). Standard topology, too, has the conceptual resources to capture those topological aspects of causal sets that are analysable within Maudlin's framework. This fact poses a challenge for the proponents of Maudlin's theory to prove it fruitful.

  7. The Cradle of Causal Reasoning: Newborns' Preference for Physical Causality

    Science.gov (United States)

    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…

  8. Causal impressions: predicting when, not just whether.

    Science.gov (United States)

    Young, Michael E; Rogers, Ester T; Beckmann, Joshua S

    2005-03-01

    In 1739, David Hume established the so-called cues to causality--environmental cues that are important to the inference of causality. Although this descriptive account has been corroborated experimentally, it has not been established why these cues are useful, except that they may reflect statistical regularities in the environment. One of the cues to causality, covariation, helps predict whether an effect will occur, but not its time of occurrence. In the present study, evidence is provided that spatial and temporal contiguity improve an observer's ability to predict when an effect will occur, thus complementing the utility of covariation as a predictor of whether an effect will occur. While observing Michotte's (1946/1963) launching effect, participants showed greater accuracy and precision in their predictions of the onset of movement by the launched object when there was spatial and temporal contiguity. Furthermore, when auditory cues that bridged a delayed launch were included, causal ratings and predictability were similarly affected. These results suggest that the everyday inference of causality relies on our ability to predict whether and when an effect will occur.

  9. Preschoolers prefer to learn causal information

    Directory of Open Access Journals (Sweden)

    Aubry eAlvarez

    2015-02-01

    Full Text Available Young children, in general, appear to have a strong drive to explore the environment in ways that reveal its underlying causal structure. But are they really attuned specifically to casual information in this quest for understanding, or do they show equal interest in other types of non-obvious information about the world? To answer this question, we introduced 20 three-year-old children to two puppets who were anxious to tell the child about a set of novel artifacts and animals. One puppet consistently described causal properties of the items while the other puppet consistently described carefully matched non-causal properties of the same items. After a familiarization period in which children learned which type of information to expect from each informant, children were given the opportunity to choose which they wanted to hear describe each of eight pictured test items. On average, children chose to hear from the informant that provided causal descriptions on 72% of the trials. This preference for causal information has important implications for explaining the role of conceptual information in supporting early learning and may suggest means for maximizing interest and motivation in young children.

  10. Causal binding of actions to their effects.

    Science.gov (United States)

    Buehner, Marc J; Humphreys, Gruffydd R

    2009-10-01

    According to widely held views in cognitive science harking back to David Hume, causality cannot be perceived directly, but instead is inferred from patterns of sensory experience, and the quality of these inferences is determined by perceivable quantities such as contingency and contiguity. We report results that suggest a reversal of Hume's conjecture: People's sense of time is warped by the experience of causality. In a stimulus-anticipation task, participants' response behavior reflected a shortened experience of time in the case of target stimuli participants themselves had generated, relative to equidistant, equally predictable stimuli they had not caused. These findings suggest that causality in the mind leads to temporal binding of cause and effect, and extend and generalize beyond earlier claims of intentional binding between action and outcome.

  11. Causal inheritence in plane wave quotients

    Energy Technology Data Exchange (ETDEWEB)

    Hubeny, Veronika E.; Rangamani, Mukund; Ross, Simon F.

    2003-11-24

    We investigate the appearance of closed timelike curves in quotients of plane waves along spacelike isometries. First we formulate a necessary and sufficient condition for a quotient of a general spacetime to preserve stable causality. We explicitly show that the plane waves are stably causal; in passing, we observe that some pp-waves are not even distinguishing. We then consider the classification of all quotients of the maximally supersymmetric ten-dimensional plane wave under a spacelike isometry, and show that the quotient will lead to closed timelike curves iff the isometry involves a translation along the u direction. The appearance of these closed timelike curves is thus connected to the special properties of the light cones in plane wave spacetimes. We show that all other quotients preserve stable causality.

  12. The causal meaning of Hamilton's rule.

    Science.gov (United States)

    Okasha, Samir; Martens, Johannes

    2016-03-01

    Hamilton's original derivation of his rule for the spread of an altruistic gene (rb>c) assumed additivity of costs and benefits. Recently, it has been argued that an exact version of the rule holds under non-additive pay-offs, so long as the cost and benefit terms are suitably defined, as partial regression coefficients. However, critics have questioned both the biological significance and the causal meaning of the resulting rule. This paper examines the causal meaning of the generalized Hamilton's rule in a simple model, by computing the effect of a hypothetical experiment to assess the cost of a social action and comparing it to the partial regression definition. The two do not agree. A possible way of salvaging the causal meaning of Hamilton's rule is explored, by appeal to R. A. Fisher's 'average effect of a gene substitution'. PMID:27069669

  13. Causality, initial conditions and inflationary magnetogenesis

    CERN Document Server

    Tsagas, Christos G

    2016-01-01

    The post-inflationary evolution of inflation-produced magnetic fields, conventional or not, can change dramatically when two fundamental issues are accounted for. The first is causality, which demands that local physical processes can never affect superhorizon perturbations. The second is the nature of the transition from inflation to reheating and then to the radiation era, which determine the initial conditions at the start of these epochs. Technically, the latter issue can be addressed by appealing to Israel's junction conditions. Causality implies that inflationary magnetic fields dot not freeze into the matter until they have re-entered the causal horizon. The nature of cosmological transitions and the associated initial conditions, on the other hand, determine the large-scale magnetic evolution after inflation. Put together, the two can slow down the adiabatic decay of superhorizon-sized magnetic fields throughout their post-inflationary life and thus lead to considerably stronger residual strengths. Th...

  14. Normalizing the causality between time series

    Science.gov (United States)

    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.

  15. A causally connected superluminal Warp Drive spacetime

    CERN Document Server

    Loup, F; Waite, D; Halerewicz, E F; Stabno, M; Kuntzman, M; Sims, R

    2002-01-01

    It will be shown that while horizons do not exist for warp drive spacetimes traveling at subluminal velocities horizons begin to develop when a warp drive spacetime reaches luminal velocities. However it will be shown that the control region of a warp drive ship lie within the portion of the warped region that is still causally connected to the ship even at superluminal velocities, therefore allowing a ship to slow to subluminal velocities. Further it is shown that the warped regions which are causally disconnected from a warp ship have no correlation to the ship velocity.

  16. Causal interpretation of stochastic differential equations

    DEFF Research Database (Denmark)

    Sokol, Alexander; Hansen, Niels Richard

    2014-01-01

    We give a causal interpretation of stochastic differential equations (SDEs) by defining the postintervention SDE resulting from an intervention in an SDE. We show that under Lipschitz conditions, the solution to the postintervention SDE is equal to a uniform limit in probability of postintervention...... structural equation models based on the Euler scheme of the original SDE, thus relating our definition to mainstream causal concepts. We prove that when the driving noise in the SDE is a Lévy process, the postintervention distribution is identifiable from the generator of the SDE....

  17. Inferring causality from noisy time series data

    DEFF Research Database (Denmark)

    Mønster, Dan; Fusaroli, Riccardo; Tylén, Kristian;

    2016-01-01

    Convergent Cross-Mapping (CCM) has shown high potential to perform causal inference in the absence of models. We assess the strengths and weaknesses of the method by varying coupling strength and noise levels in coupled logistic maps. We find that CCM fails to infer accurate coupling strength...... injections in intermediate-to-strongly coupled systems could enable more accurate causal inferences. Given the inherent noisy nature of real-world systems, our findings enable a more accurate evaluation of CCM applicability and advance suggestions on how to overcome its weaknesses....

  18. Introducing Mechanics by Tapping Core Causal Knowledge

    Science.gov (United States)

    Klaassen, Kees; Westra, Axel; Emmett, Katrina; Eijkelhof, Harrie; Lijnse, Piet

    2008-01-01

    This article concerns an outline of an introductory mechanics course. It is based on the argument that various uses of the concept of force (e.g. from Kepler, Newton and everyday life) share an explanatory strategy based on core causal knowledge. The strategy consists of (a) the idea that a force causes a deviation from how an object would move of…

  19. Linear Response Laws and Causality in Electrodynamics

    Science.gov (United States)

    Yuffa, Alex J.; Scales, John A.

    2012-01-01

    Linear response laws and causality (the effect cannot precede the cause) are of fundamental importance in physics. In the context of classical electrodynamics, students often have a difficult time grasping these concepts because the physics is obscured by the intermingling of the time and frequency domains. In this paper, we analyse the linear…

  20. A Causal Construction of Diffusion Processes

    OpenAIRE

    Banek, Tadeusz

    2010-01-01

    A simple nonlinear integral equation for Ito's map is obtained. Although, it does not include stochastic integrals, it does give causal construction of diffusion processes which can be easily implemented by iteration systems. Applications in financial modelling and extension to fBm are discussed.

  1. The metagenomic approach and causality in virology

    Directory of Open Access Journals (Sweden)

    Silvana Beres Castrignano

    2015-01-01

    Full Text Available 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.

  2. Causality and Time in Historical Institutionalism

    DEFF Research Database (Denmark)

    Mahoney, James; Mohamedali, Khairunnisa; Nguyen, Christoph

    2016-01-01

    This chapter explores the dual concern with causality and time in historical institutionalism using a graphical approach. The analysis focuses on three concepts that are central to this field: critical junctures, gradual change, and path dependence. The analysis makes explicit and formal the logic...

  3. Escaping Myopia: Teaching Students about Historical Causality

    Science.gov (United States)

    Waring, Scott M.

    2010-01-01

    There are so many aspects to teaching history that are vital to creating well-rounded historical thinkers, but one of the most fundamental and most overlooked elements is the idea of causality. Far too many students do not understand the idea of causation, that there are multiple reasons for why historical events occurred and transpired in the way…

  4. Exploring Torus Universes in Causal Dynamical Triangulations

    DEFF Research Database (Denmark)

    Budd, Timothy George; Loll, R.

    2013-01-01

    Motivated by the search for new observables in nonperturbative quantum gravity, we consider Causal Dynamical Triangulations (CDT) in 2+1 dimensions with the spatial topology of a torus. This system is of particular interest, because one can study not only the global scale factor, but also global...

  5. Marriage and Anomie: A Causal Argument

    Science.gov (United States)

    Lee, Gary R.

    1974-01-01

    A sample of 394 married couples is employed to test the possibility of an association between marital satisfaction and personal (attitudinal) anomie. The hypothesis is supported. Conclusions are offered relevant to anomie theory, and to utilization of marital and family phenomena as independent variables in causal explanations of nonfamily events.…

  6. Manipulation and the causal Markov condition

    OpenAIRE

    Hausman, Daniel; Woodward, James

    2004-01-01

    This paper explores the relationship between a manipulability conception of causation and the causal Markov condition (CM). We argue that violations of CM also violate widely shared expectations—implicit in the manipulability conception—having to do with the absence of spontaneous correlations. They also violate expectations concerning the connection between independence or dependence relationships in the presence and absence of interventions.

  7. Causality and Teleology in High School Biology.

    Science.gov (United States)

    Tamir, Pinchas

    1985-01-01

    Ability to distinguish between causal (cause-effect) and teleological (means-ends) explanations was measured in 1905 twelfth-grade biology students and found to be dependent on student knowledge. Although the inability to make these distinctions contributes to misconceptions in biology, appropriate instruction can easily remedy the problem. Sample…

  8. Causal and Teleological Explanations in Biology

    Science.gov (United States)

    Yip, Cheng-Wai

    2009-01-01

    A causal explanation in biology focuses on the mechanism by which a biological process is brought about, whereas a teleological explanation considers the end result, in the context of the survival of the organism, as a reason for certain biological processes or structures. There is a tendency among students to offer a teleological explanation…

  9. Causality and analyticity in quantum fields theory

    International Nuclear Information System (INIS)

    This is a presentation of results on the causal and analytical structure of Green functions and on the collision amplitudes in fields theories, for massive particles of one type, with a positive mass and a zero spin value. (A.B.)

  10. Comments: Causal Interpretations of Mediation Effects

    Science.gov (United States)

    Jo, Booil; Stuart, Elizabeth A.

    2012-01-01

    The authors thank Dr. Lindsay Page for providing a nice illustration of the use of the principal stratification framework to define causal effects, and a Bayesian model for effect estimation. They hope that her well-written article will help expose education researchers to these concepts and methods, and move the field of mediation analysis in…

  11. Sequential causal learning in humans and rats

    NARCIS (Netherlands)

    H. Lu; R.R. Rojas; T. Beckers; A. Yuille

    2008-01-01

    Recent experiments (Beckers, De Houwer, Pineño, & Miller, 2005;Beckers, Miller, De Houwer, & Urushihara, 2006) have shown that pretraining with unrelated cues can dramatically influence the performance of humans in a causal learning paradigm and rats in a standard Pavlovian conditioning paradigm. Su

  12. The causal link between energy and output growth: Evidence from Markov switching Granger causality

    International Nuclear Information System (INIS)

    In this paper we empirically investigate the causal link between energy consumption and economic growth employing a Markov switching Granger causality analysis. We carry out our investigation using annual U.S. real GDP, total final energy consumption and total primary energy consumption data which cover the period between 1968 and 2010. We find that there are significant changes in the causal relation between energy consumption and economic growth over the sample period under investigation. Our results show that total final energy consumption and total primary energy consumption have significant predictive content for real economic activity in the U.S. economy. Furthermore, the causality running from energy consumption to output growth seems to be strongly apparent particularly during the periods of economic downturn and energy crisis. We also document that output growth has predictive power in explaining total energy consumption. Furthermore, the power of output growth in predicting total energy consumption is found to diminish after the mid of 1980s. - Highlights: • Total energy consumption has predictive content for real economic activity. • The causality from energy to output growth is apparent in the periods of recession. • The causality from energy to output growth is strong in the periods of energy crisis. • Output growth has predictive power in explaining total energy consumption. • The power of output growth in explaining energy diminishes after the mid of 1980s

  13. Assessing statistical significance in causal graphs

    Directory of Open Access Journals (Sweden)

    Chindelevitch Leonid

    2012-02-01

    Full Text Available Abstract Background Causal graphs are an increasingly popular tool for the analysis of biological datasets. In particular, signed causal graphs--directed graphs whose edges additionally have a sign denoting upregulation or downregulation--can be used to model regulatory networks within a cell. Such models allow prediction of downstream effects of regulation of biological entities; conversely, they also enable inference of causative agents behind observed expression changes. However, due to their complex nature, signed causal graph models present special challenges with respect to assessing statistical significance. In this paper we frame and solve two fundamental computational problems that arise in practice when computing appropriate null distributions for hypothesis testing. Results First, we show how to compute a p-value for agreement between observed and model-predicted classifications of gene transcripts as upregulated, downregulated, or neither. Specifically, how likely are the classifications to agree to the same extent under the null distribution of the observed classification being randomized? This problem, which we call "Ternary Dot Product Distribution" owing to its mathematical form, can be viewed as a generalization of Fisher's exact test to ternary variables. We present two computationally efficient algorithms for computing the Ternary Dot Product Distribution and investigate its combinatorial structure analytically and numerically to establish computational complexity bounds. Second, we develop an algorithm for efficiently performing random sampling of causal graphs. This enables p-value computation under a different, equally important null distribution obtained by randomizing the graph topology but keeping fixed its basic structure: connectedness and the positive and negative in- and out-degrees of each vertex. We provide an algorithm for sampling a graph from this distribution uniformly at random. We also highlight theoretical

  14. Trimmed Granger causality between two groups of time series

    OpenAIRE

    Hung, Ying-Chao; Tseng, Neng-Fang; Balakrishnan, Narayanaswamy

    2014-01-01

    The identification of causal effects between two groups of time series has been an important topic in a wide range of applications such as economics, engineering, medicine, neuroscience, and biology. In this paper, a simplified causal relationship (called trimmed Granger causality) based on the context of Granger causality and vector autoregressive (VAR) model is introduced. The idea is to characterize a subset of “important variables” for both groups of time series so that the underlying cau...

  15. Institutional Investors and Stock Market Development: A Causality Study

    OpenAIRE

    Guler Aras; Alovsat Muslumov

    2008-01-01

    This article examines causality relationships between institutional investors and stock market development based on the panel data compiled from 23 OECD countries for the years 1982 through 2000. In order to test causality relationship, Sims’ causality test based on Granger definition of causality was used in our study. Our empirical results provide evidence that there are statistically significant positive relationship between institutional investors and stock market development. The develop...

  16. Interpretational Confounding or Confounded Interpretations of Causal Indicators?

    Science.gov (United States)

    Bainter, Sierra A.; Bollen, Kenneth A.

    2014-01-01

    In measurement theory, causal indicators are controversial and little understood. Methodological disagreement concerning causal indicators has centered on the question of whether causal indicators are inherently sensitive to interpretational confounding, which occurs when the empirical meaning of a latent construct departs from the meaning…

  17. Rationales in Children's Causal Learning from Others' Actions

    Science.gov (United States)

    Sobel, David M.; Sommerville, Jessica A.

    2009-01-01

    Shown commensurate actions and information by an adult, preschoolers' causal learning was influenced by the pedagogical context in which these actions occurred. Four-year-olds who were provided with a reason for an experimenter's action relevant to learning causal structure showed more accurate causal learning than children exposed to the same…

  18. Mind and Meaning: Piaget and Vygotsky on Causal Explanation.

    Science.gov (United States)

    Beilin, Harry

    1996-01-01

    Piaget's theory has been characterized as descriptive and not explanatory, not qualifying as causal explanation. Piaget was consistent in showing how his theory was both explanatory and causal. Vygotsky also endorsed causal-genetic explanation but, on the basis of knowledge of only Piaget's earliest works, he claimed that Piaget's theory was not…

  19. A Bayesian Theory of Sequential Causal Learning and Abstract Transfer

    Science.gov (United States)

    Lu, Hongjing; Rojas, Randall R.; Beckers, Tom; Yuille, Alan L.

    2016-01-01

    Two key research issues in the field of causal learning are how people acquire causal knowledge when observing data that are presented sequentially, and the level of abstraction at which learning takes place. Does sequential causal learning solely involve the acquisition of specific cause-effect links, or do learners also acquire knowledge about…

  20. How to Be Causal: Time, Spacetime and Spectra

    Science.gov (United States)

    Kinsler, Paul

    2011-01-01

    I explain a simple definition of causality in widespread use, and indicate how it links to the Kramers-Kronig relations. The specification of causality in terms of temporal differential equations then shows us the way to write down dynamical models so that their causal nature "in the sense used here" should be obvious to all. To extend existing…

  1. Causality and Nonlocality as Axioms for Quantum Mechanics

    OpenAIRE

    Popescu, Sandu; Rohrlich, Daniel

    1997-01-01

    Quantum mechanics permits nonlocality - both nonlocal correlations and nonlocal equations of motion - while respecting relativistic causality. Is quantum mechanics the unique theory that reconciles nonlocality and causality? We consider two models, going beyond quantum mechanics, of nonlocality: "superquantum" correlations, and nonlocal "jamming" of correlations. These models are consistent with some definitions of nonlocality and causality.

  2. Normalizing the causality between time series

    CERN Document Server

    Liang, X San

    2015-01-01

    Recently, a rigorous yet concise formula has been derived to evaluate the 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 three types of fundamental mechanisms that govern the marginal entropy change of the flow recipient. A normalized or relative flow measures its importance relative to other mechanisms. In analyzing realistic series, both absolute and relative information flows need to be taken into account, since the normalizers for a pair of reverse flows belong to two different entropy balances; it is quite normal that two identical flows may differ a lot in relative importance in their respective balances. We have reproduced these results with several autoregressive models. We have also shown applications to a climate change problem and a financial analysis problem. For the former, reconfirmed is the role of the Indian Ocean Dipole as ...

  3. Sentencing goals, causal attributions, ideology, and personality.

    Science.gov (United States)

    Carroll, J S; Perkowitz, W T; Lurigio, A J; Weaver, F M

    1987-01-01

    Disparity in sentencing of criminals has been related to a variety of individual difference variables. We propose a framework establishing resonances or coherent patterns among sentencing goals, causal attributions, ideology, and personality. Two studies are described, one with law and criminology students, the other with probation officers. Relations among the different types of variables reveal two resonances among both students and officers. One comprises various conservative and moralistic elements: a tough, punitive stance toward crime; belief in individual causality for crime; high scores on authoritarianism, dogmatism, and internal locus of control; lower moral stage; and political conservatism. The second comprises various liberal elements: rehabilitation, belief in economic and other external determinants of crime, higher moral stage, and belief in the powers and responsibilities of government to correct social problems. Implications of these results are discussed for individual differences in sentencing, attribution theory, and attempts to reduce disparity. PMID:3820064

  4. A New Spin on Causality Constraints

    CERN Document Server

    Hartman, Thomas; Kundu, Sandipan

    2016-01-01

    Causality in a shockwave state is related to the analytic properties of a four-point correlation function. Extending recent results for scalar probes, we show that this constrains the couplings of the stress tensor to light spinning operators in conformal field theory, and interpret these constraints in terms of the interaction with null energy. For spin-1 and spin-2 conserved currents in four dimensions, the resulting inequalities are a subset of the Hofman-Maldacena conditions for positive energy deposition. It is well known that energy conditions in holographic theories are related to causality on the gravity side; our results make a connection on the CFT side, and extend it to non-holographic theories.

  5. Consistence beats causality in recommender systems

    CERN Document Server

    Zhu, Xuzhen; Hu, Zheng; Zhang, Ping; Zhou, Tao

    2015-01-01

    The explosive growth of information challenges people's capability in finding out items fitting to their own interests. Recommender systems provide an efficient solution by automatically push possibly relevant items to users according to their past preferences. Recommendation algorithms usually embody the causality from what having been collected to what should be recommended. In this article, we argue that in many cases, a user's interests are stable, and thus the previous and future preferences are highly consistent. The temporal order of collections then does not necessarily imply a causality relationship. We further propose a consistence-based algorithm that outperforms the state-of-the-art recommendation algorithms in disparate real data sets, including \\textit{Netflix}, \\textit{MovieLens}, \\textit{Amazon} and \\textit{Rate Your Music}.

  6. An insider's guide to quantum causal histories

    CERN Document Server

    Markopoulou, F

    2000-01-01

    A review is given of recent work aimed at constructing a quantum theory of cosmology in which all observables refer to information measurable by observers inside the universe. At the classical level the algebra of observables should be modified to take into account the fact that observers can only give truth values to observables that have to do with their backwards light cone. The resulting algebra is a Heyting rather than a Boolean algebra. The complement is non-trivial and contains information about horizons and topology change. Representation of such observables quantum mechanically requires a many-Hilbert space formalism, in which different observers make measurements in different Hilbert spaces. I describe such a formalism, called "quantum causal histories"; examples include causally evolving spin networks and quantum computers.

  7. Consistence beats causality in recommender systems

    OpenAIRE

    Zhu, Xuzhen; Tian, Hui; Hu, Zheng; Zhang, Ping; Zhou, Tao

    2015-01-01

    The explosive growth of information challenges people's capability in finding out items fitting to their own interests. Recommender systems provide an efficient solution by automatically push possibly relevant items to users according to their past preferences. Recommendation algorithms usually embody the causality from what having been collected to what should be recommended. In this article, we argue that in many cases, a user's interests are stable, and thus the previous and future prefere...

  8. Gauge theory origins of supergravity causal structure

    CERN Document Server

    Kabat, D; Kabat, Daniel; Lifschytz, Gilad

    1999-01-01

    We discuss the gauge theory mechanisms which are responsible for the causal structure of the dual supergravity. For D-brane probes we show that the light cone structure and Killing horizons of supergravity emerge dynamically. They are associated with the appearance of new light degrees of freedom in the gauge theory, which we explicitly identify. This provides a picture of physics at the horizon of a black hole as seen by a D-brane probe.

  9. Imposing causality on a matrix model

    International Nuclear Information System (INIS)

    We introduce a new matrix model that describes Causal Dynamical Triangulations (CDT) in two dimensions. In order to do so, we introduce a new, simpler definition of 2D CDT and show it to be equivalent to the old one. The model makes use of ideas from dually weighted matrix models, combined with multi-matrix models, and can be studied by the method of character expansion.

  10. Isocausal spacetimes may have different causal boundaries

    Energy Technology Data Exchange (ETDEWEB)

    Flores, J L; Herrera, J [Departamento de Algebra, Geometria y Topologia, Facultad de Ciencias, Universidad de Malaga, Campus Teatinos, 29071 Malaga (Spain); Sanchez, M, E-mail: floresj@agt.cie.uma.es, E-mail: jherrera@uma.es, E-mail: sanchezm@ugr.es [Departamento de Geometria y Topologia, Facultad de Ciencias, Universidad de Granada, Avenida Fuentenueva s/n, 18071 Granada (Spain)

    2011-09-07

    We construct an example which shows that two isocausal spacetimes, in the sense introduced recently in GarcIa-Parrado and Senovilla (2003 Class. Quantum Grav. 20 625-64), may have c-boundaries which are not equal (more precisely, not equivalent, as no bijection between the completions can preserve all the binary relations induced by causality). This example also suggests that isocausality can be useful for the understanding and computation of the c-boundary.

  11. A causally connected superluminal Warp Drive spacetime

    OpenAIRE

    Loup, F.; Held, R.; Waite, D; Halerewicz, Jr., E.; Stabno, M.; Kuntzman, M.; Sims, R.

    2002-01-01

    It will be shown that while horizons do not exist for warp drive spacetimes traveling at subluminal velocities horizons begin to develop when a warp drive spacetime reaches luminal velocities. However it will be shown that the control region of a warp drive ship lie within the portion of the warped region that is still causally connected to the ship even at superluminal velocities, therefore allowing a ship to slow to subluminal velocities. Further it is shown that the warped regions which ar...

  12. Relativistic causality and position space renormalization

    CERN Document Server

    Todorov, Ivan

    2016-01-01

    We survey the causal position space renormalization with a special attention to the role of Raymond Stora in the development of the subject. Renormalization is effected by subtracting pole terms in analytically regularized amplitudes. Residues are identified with periods whose relation to recent development in number theory is emphasized. We demonstrate the possibility of integration over internal vertices in the case of a (massless) conformal theory and display the dilation and the conformal anomaly.

  13. Extending Temporal Causal Graph For Diagnosis Problems

    OpenAIRE

    Belouaer, Lamia; Bouzid, Maroua; Mouhoub, Malek

    2009-01-01

    Poster International audience Abductive diagnosis (Brusoni et al. 1998) consists in finding explanations for given observations by using rules of inference based on the causal dependences of the system. Time is important for abductive diagnosis (Hamscher and Davis 1984), (Hamscher, Console, and Kleer 1992). There are few works in litterature handling temporal diagnosis (Kautz 1999). They differ in the expressiveness of the temporal knowledge. We propose a new approach for Temporal Diagn...

  14. Ten simple rules for dynamic causal modeling

    OpenAIRE

    Stephan, K E; Penny, W.D.; Moran, R. J.; den Ouden, H.E.M.; Daunizeau, J.; Friston, K J

    2010-01-01

    Dynamic causal modeling (DCM) is a generic Bayesian framework for inferring hidden neuronal states from measurements of brain activity. It provides posterior estimates of neurobiologically interpretable quantities such as the effective strength of synaptic connections among neuronal populations and their context-dependent modulation. DCM is increasingly used in the analysis of a wide range of neuroimaging and electrophysiological data. Given the relative complexity of DCM, compared to convent...

  15. Bayesian Discovery of Linear Acyclic Causal Models

    CERN Document Server

    Hoyer, Patrik O

    2012-01-01

    Methods for automated discovery of causal relationships from non-interventional data have received much attention recently. A widely used and well understood model family is given by linear acyclic causal models (recursive structural equation models). For Gaussian data both constraint-based methods (Spirtes et al., 1993; Pearl, 2000) (which output a single equivalence class) and Bayesian score-based methods (Geiger and Heckerman, 1994) (which assign relative scores to the equivalence classes) are available. On the contrary, all current methods able to utilize non-Gaussianity in the data (Shimizu et al., 2006; Hoyer et al., 2008) always return only a single graph or a single equivalence class, and so are fundamentally unable to express the degree of certainty attached to that output. In this paper we develop a Bayesian score-based approach able to take advantage of non-Gaussianity when estimating linear acyclic causal models, and we empirically demonstrate that, at least on very modest size networks, its accur...

  16. A causal dispositional account of fitness.

    Science.gov (United States)

    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. PMID:27338570

  17. [Causality in cardiology: concepts in evolution].

    Science.gov (United States)

    Méndez, Gustavo F

    2005-01-01

    This paper describes several concepts about causality from Empedocles, Aristoteles and Galeno, to Koch and Hill and the evolution of these concepts related to cardiovascular diseases. Also defines cause and risk, and the philosophical theories about scientific knowledge: inductive versus refutation analysis. On these basis, the study of cardiovascular disease's causality, especially coronary heart disease, allows us the identification of several risk factors involved in its development. However, even with the presently coronary heart disease risk charts (from Framingham and European studies) the higher probability for the development of a cardiovascular ischemic event is around 40%, establishing an important degree of uncertainty. With the improvement in molecular biology techniques, genetics have attempted to analyse several genetic polymorphisms in search of the origin of coronary heart disease. Unfortunately, less than 10% of these polymorphisms have had a positive correlation with coronary heart disease being of minor risk that those obtained for having the diagnosis of type 2 diabetes mellitus or hypercholesterolemia. On these basis, the requirement of new population research projects in which clinical and genetic risk factors are to be studied for the appropriate understanding of the causality process of cardiovascular diseases must be a worldwide priority.

  18. Causality, initial conditions, and inflationary magnetogenesis

    Science.gov (United States)

    Tsagas, Christos G.

    2016-05-01

    The post-inflationary evolution of inflation-produced magnetic fields, conventional or not, can change dramatically when two fundamental issues are accounted for. The first is causality, which demands that local physical processes can never affect superhorizon perturbations. The second is the nature of the transition from inflation to reheating and then to the radiation era, which determine the initial conditions at the start of these epochs. Causality implies that inflationary magnetic fields do not freeze into the matter until they have re-entered the causal horizon. The nature of the cosmological transitions and the associated initial conditions, on the other hand, determine the large-scale magnetic evolution after inflation. Put together, the two can slow down the adiabatic magnetic decay on superhorizon scales throughout the Universe's post-inflationary evolution and thus lead to considerably stronger residual magnetic fields. This is "good news" for both the conventional and the nonconventional scenarios of cosmic magnetogenesis. Mechanisms operating outside standard electromagnetism, in particular, do not need to enhance their fields too much during inflation in order to produce seeds that can feed the galactic dynamo today. In fact, even conventionally produced inflationary magnetic fields might be able to sustain the dynamo.

  19. A causal dispositional account of fitness.

    Science.gov (United States)

    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. Causal beliefs about depression in different cultural groups – What do cognitive psychological theories of causal learning and reasoning predict?

    OpenAIRE

    York eHagmayer; Neele eEngelmann

    2014-01-01

    Cognitive psychological research focusses on causal learning and reasoning while cognitive anthropological and social science research tend to focus on systems of beliefs. Our aim was to explore how these two types of research can inform each other. Cognitive psychological theories (causal model theory and causal Bayes nets) were used to derive predictions for systems of causal beliefs. These predictions were then applied to lay theories of depression as a specific test case. A systematic...

  1. Causal beliefs about depression in different cultural groups—what do cognitive psychological theories of causal learning and reasoning predict?

    OpenAIRE

    Hagmayer, York; Engelmann, Neele

    2014-01-01

    Cognitive psychological research focuses on causal learning and reasoning while cognitive anthropological and social science research tend to focus on systems of beliefs. Our aim was to explore how these two types of research can inform each other. Cognitive psychological theories (causal model theory and causal Bayes nets) were used to derive predictions for systems of causal beliefs. These predictions were then applied to lay theories of depression as a specific test case. A systematic lite...

  2. The Causality between Human Capital and Economic Growth in Oil Exporting Countries: Panel Cointegration and Causality

    OpenAIRE

    Mehrara, Mohsen

    2013-01-01

    This paper investigates the causal relationship between education and GDP in a panel of 11 selected oil exporting countries by using panel unit root tests and panel cointegration analysis for the period 1970-2010. A three-variable model is formulated with oil exports as the third variable. The results show a strong causality from oil revenues and economic growth to education in the oil exporting countries. Yet, education does not have any significant effects on GDP in short- and long-run. It ...

  3. Causal Loop Analysis of coastal geomorphological systems

    Science.gov (United States)

    Payo, Andres; Hall, Jim W.; French, Jon; Sutherland, James; van Maanen, Barend; Nicholls, Robert J.; Reeve, Dominic E.

    2016-03-01

    As geomorphologists embrace ever more sophisticated theoretical frameworks that shift from simple notions of evolution towards single steady equilibria to recognise the possibility of multiple response pathways and outcomes, morphodynamic modellers are facing the problem of how to keep track of an ever-greater number of system feedbacks. Within coastal geomorphology, capturing these feedbacks is critically important, especially as the focus of activity shifts from reductionist models founded on sediment transport fundamentals to more synthesist ones intended to resolve emergent behaviours at decadal to centennial scales. This paper addresses the challenge of mapping the feedback structure of processes controlling geomorphic system behaviour with reference to illustrative applications of Causal Loop Analysis at two study cases: (1) the erosion-accretion behaviour of graded (mixed) sediment beds, and (2) the local alongshore sediment fluxes of sand-rich shorelines. These case study examples are chosen on account of their central role in the quantitative modelling of geomorphological futures and as they illustrate different types of causation. Causal loop diagrams, a form of directed graph, are used to distil the feedback structure to reveal, in advance of more quantitative modelling, multi-response pathways and multiple outcomes. In the case of graded sediment bed, up to three different outcomes (no response, and two disequilibrium states) can be derived from a simple qualitative stability analysis. For the sand-rich local shoreline behaviour case, two fundamentally different responses of the shoreline (diffusive and anti-diffusive), triggered by small changes of the shoreline cross-shore position, can be inferred purely through analysis of the causal pathways. Explicit depiction of feedback-structure diagrams is beneficial when developing numerical models to explore coastal morphological futures. By explicitly mapping the feedbacks included and neglected within a

  4. On asymmetric causal relationships in Petropolitics

    Directory of Open Access Journals (Sweden)

    Balan Feyza

    2016-01-01

    Full Text Available The aim of this paper is to examine whether the First Law of Petropolitics denominated by Friedman in 2006 is valid for OPEC countries. To do this, this paper analyses the relationship between political risk and oil supply by applying the asymmetric panel causality test suggested by Hatemi-J (2011 to these countries for the period 1984-2014. The results show that the First Law of Petropolitics is valid for Angola, Iraq, Kuwait, Libya, Nigeria, Qatar, Saudi Arabia, and the UAE, given that positive oil supply shocks significantly lead to negative political stability shocks, and negative oil supply shocks significantly lead to positive shocks in political stability.

  5. Rapidity Correlation Structures from Causal Hydrodynamics

    CERN Document Server

    Gavin, Sean; Zin, Christopher

    2016-01-01

    Viscous diffusion can broaden the rapidity dependence of two-particle transverse momentum fluctuations. Surprisingly, measurements at RHIC by the STAR collaboration demonstrate that this broadening is accompanied by the appearance of unanticipated structure in the rapidity distribution of these fluctuations in the most central collisions. Although a first order classical Navier-Stokes theory can roughly explain the rapidity broadening, it cannot explain the additional structure. We propose that the rapidity structure can be explained using the second order causal Israel-Stewart hydrodynamics with stochastic noise.

  6. Bianchi-I cosmology from causal thermodynamics

    CERN Document Server

    Bittencourt, Eduardo; Klippert, Renato

    2016-01-01

    We investigate diagonal Bianchi-I spacetimes in the presence of viscous fluids by using the shear and the anisotropic pressure components as the basic variables, where the viscosity is driven by the (second-order) causal thermodynamics. A few exact solutions are presented, among which we mention the anisotropic versions of de Sitter/anti-de Sitter geometries as well as an asymptotically isotropic spacetime presenting an effective constant cosmic acceleration without any cosmological constant. The qualitative analysis of the solutions for barotropic fluids with linear equations of state suggests that the behaviour is quite general.

  7. Foundational perspectives on causality in large-scale brain networks.

    Science.gov (United States)

    Mannino, Michael; Bressler, Steven L

    2015-12-01

    A profusion of recent work in cognitive neuroscience has been concerned with the endeavor to uncover causal influences in large-scale brain networks. However, despite the fact that many papers give a nod to the important theoretical challenges posed by the concept of causality, this explosion of research has generally not been accompanied by a rigorous conceptual analysis of the nature of causality in the brain. This review provides both a descriptive and prescriptive account of the nature of causality as found within and between large-scale brain networks. In short, it seeks to clarify the concept of causality in large-scale brain networks both philosophically and scientifically. This is accomplished by briefly reviewing the rich philosophical history of work on causality, especially focusing on contributions by David Hume, Immanuel Kant, Bertrand Russell, and Christopher Hitchcock. We go on to discuss the impact that various interpretations of modern physics have had on our understanding of causality. Throughout all this, a central focus is the distinction between theories of deterministic causality (DC), whereby causes uniquely determine their effects, and probabilistic causality (PC), whereby causes change the probability of occurrence of their effects. We argue that, given the topological complexity of its large-scale connectivity, the brain should be considered as a complex system and its causal influences treated as probabilistic in nature. We conclude that PC is well suited for explaining causality in the brain for three reasons: (1) brain causality is often mutual; (2) connectional convergence dictates that only rarely is the activity of one neuronal population uniquely determined by another one; and (3) the causal influences exerted between neuronal populations may not have observable effects. A number of different techniques are currently available to characterize causal influence in the brain. Typically, these techniques quantify the statistical

  8. Foundational perspectives on causality in large-scale brain networks

    Science.gov (United States)

    Mannino, Michael; Bressler, Steven L.

    2015-12-01

    A profusion of recent work in cognitive neuroscience has been concerned with the endeavor to uncover causal influences in large-scale brain networks. However, despite the fact that many papers give a nod to the important theoretical challenges posed by the concept of causality, this explosion of research has generally not been accompanied by a rigorous conceptual analysis of the nature of causality in the brain. This review provides both a descriptive and prescriptive account of the nature of causality as found within and between large-scale brain networks. In short, it seeks to clarify the concept of causality in large-scale brain networks both philosophically and scientifically. This is accomplished by briefly reviewing the rich philosophical history of work on causality, especially focusing on contributions by David Hume, Immanuel Kant, Bertrand Russell, and Christopher Hitchcock. We go on to discuss the impact that various interpretations of modern physics have had on our understanding of causality. Throughout all this, a central focus is the distinction between theories of deterministic causality (DC), whereby causes uniquely determine their effects, and probabilistic causality (PC), whereby causes change the probability of occurrence of their effects. We argue that, given the topological complexity of its large-scale connectivity, the brain should be considered as a complex system and its causal influences treated as probabilistic in nature. We conclude that PC is well suited for explaining causality in the brain for three reasons: (1) brain causality is often mutual; (2) connectional convergence dictates that only rarely is the activity of one neuronal population uniquely determined by another one; and (3) the causal influences exerted between neuronal populations may not have observable effects. A number of different techniques are currently available to characterize causal influence in the brain. Typically, these techniques quantify the statistical

  9. God Does Not Play Dice: Causal Determinism and Preschoolers' Causal Inferences

    Science.gov (United States)

    Schulz, Laura E.; Sommerville, Jessica

    2006-01-01

    Three studies investigated children's belief in causal determinism. If children are determinists, they should infer unobserved causes whenever observed causes appear to act stochastically. In Experiment 1, 4-year-olds saw a stochastic generative cause and inferred the existence of an unobserved inhibitory cause. Children traded off inferences…

  10. Trivariate causality between economic growth, urbanisation and electricity consumption in Angola: Cointegration and causality analysis

    International Nuclear Information System (INIS)

    This paper investigates the causal relationship between economic growth, urbanisation and electricity consumption in the case of Angola, while utilizing the data over the period of 1971–2009. We have applied Lee and Strazicich (2003. The Review of Economics and Statistics 63, 1082–1089; 2004. Working Paper. Department of Economics, Appalachian State University) unit root tests to examine the stationarity properties of the series. Using the Gregory–Hansen structural break cointegration procedure as a complement, we employ the ARDL bounds test to investigate long run relationships. The VECM Granger causality test is subsequently used to examine the direction of causality between economic growth, urbanisation, and electricity consumption. Our results indicate the existence of long run relationships. We further observe evidence in favour of bidirectional causality between electricity consumption and economic growth. The feedback hypothesis is also found between urbanisation and economic growth. Urbanisation and electricity consumption Granger cause each other. We conclude that Angola is energy-dependent country. Consequently, the relevant authorities should boost electricity production as one of the means of achieving sustainable economic development in the long run. - Highlights: • We consider the link between electricity consumption and economic growth in Angola. • Urbanisation is added to turn the research into a trivariate investigation. • Various time series procedures are used. • Results show that increasing electricity will improve economic growth in Angola. • Results show urbanisations reduced economic growth during civil war

  11. Interference between Cues Requires a Causal Scenario: Favorable Evidence for Causal Reasoning Models in Learning Processes

    Science.gov (United States)

    Luque, David; Cobos, Pedro L.; Lopez, Francisco J.

    2008-01-01

    In an interference-between-cues design (IbC), the expression of a learned Cue A-Outcome 1 association has been shown to be impaired if another cue, B, is separately paired with the same outcome in a second learning phase. The present study examined whether IbC could be caused by associative mechanisms independent of causal reasoning processes.…

  12. Causal-Explanatory Pluralism: How Intentions, Functions, and Mechanisms Influence Causal Ascriptions

    Science.gov (United States)

    Lombrozo, Tania

    2010-01-01

    Both philosophers and psychologists have argued for the existence of distinct kinds of explanations, including teleological explanations that cite functions or goals, and mechanistic explanations that cite causal mechanisms. Theories of causation, in contrast, have generally been unitary, with dominant theories focusing either on counterfactual…

  13. Diagnostic reasoning using qualitative causal models

    International Nuclear Information System (INIS)

    The application of expert systems to reasoning problems involving real-time data from plant measurements has been a topic of much research, but few practical systems have been deployed. One obstacle to wider use of expert systems in applications involving real-time data is the lack of adequate knowledge representation methodologies for dynamic processes. Knowledge bases composed mainly of rules have disadvantages when applied to dynamic processes and real-time data. This paper describes a methodology for the development of qualitative causal models that can be used as knowledge bases for reasoning about process dynamic behavior. These models provide a systematic method for knowledge base construction, considerably reducing the engineering effort required. They also offer much better opportunities for verification and validation of the knowledge base, thus increasing the possibility of the application of expert systems to reasoning about mission critical systems. Starting with the Signed Directed Graph (SDG) method that has been successfully applied to describe the behavior of diverse dynamic processes, the paper shows how certain non-physical behaviors that result from abstraction may be eliminated by applying causal constraint to the models. The resulting Extended Signed Directed Graph (ESDG) may then be compiled to produce a model for use in process fault diagnosis. This model based reasoning methodology is used in the MOBIAS system being developed by Duke Power Company under EPRI sponsorship. 15 refs., 4 figs

  14. Emergent Horizons and Causal Structures in Holography

    CERN Document Server

    Banerjee, Avik; Kundu, Sandipan

    2016-01-01

    The open string metric arises kinematically in studying fluctuations of open string degrees of freedom on a D-brane. An observer, living on a probe D-brane, can send signals through the spacetime by using such fluctuations on the probe, that propagate in accordance with a metric which is conformal to the open string metric. Event horizons can emerge in the open string metric when one considers a D-brane with an electric field on its worldvolume. Here, we emphasize the role of and investigate, in details, the causal structure of the resulting open string event horizon and demonstrate, among other things, its close similarities to an usual black hole event horizon in asymptotically AdS-spaces. To that end, we analyze relevant geodesics, Penrose diagrams and various causal holographic observables for a given open string metric. For analytical control, most of our calculations are performed in an asymptotically AdS$_3$-background, however, we argue that the physics is qualitatively the same in higher dimensions. ...

  15. Immunity in arterial hypertension: associations or causalities?

    Science.gov (United States)

    Anders, Hans-Joachim; Baumann, Marcus; Tripepi, Giovanni; Mallamaci, Francesca

    2015-12-01

    Numerous studies describe associations between markers of inflammation and arterial hypertension (aHT), but does that imply causality? Interventional studies that reduce blood pressure reduced also markers of inflammation, but does immunosuppression improve hypertension? Here, we review the available mechanistic data. Aberrant immunity can trigger endothelial dysfunction but is hardly ever the primary cause of aHT. Innate and adaptive immunity get involved once hypertension has caused vascular wall injury as immunity is a modifier of endothelial dysfunction and vascular wall remodelling. As vascular remodelling progresses, immunity-related mechanisms can become significant cofactors for cardiovascular (CV) disease progression; vice versa, suppressing immunity can improve hypertension and CV outcomes. Innate and adaptive immunity both contribute to vascular wall remodelling. Innate immunity is driven by danger signals that activate Toll-like receptors and other pattern-recognition receptors. Adaptive immunity is based on loss of tolerance against vascular autoantigens and includes autoreactive T-cell immunity as well as non-HLA angiotensin II type 1 receptor-activating autoantibodies. Such processes involve numerous other modulators such as regulatory T cells. Together, immunity is not causal for hypertension but rather an important secondary pathomechanism and a potential therapeutic target in hypertension.

  16. Causal mechanisms in airfoil-circulation formation

    Science.gov (United States)

    Zhu, J. Y.; Liu, T. S.; Liu, L. Q.; Zou, S. F.; Wu, J. Z.

    2015-12-01

    In this paper, we trace the dynamic origin, rather than any kinematic interpretations, of lift in two-dimensional flow to the physical root of airfoil circulation. We show that the key causal process is the vorticity creation by tangent pressure gradient at the airfoil surface via no-slip condition, of which the theoretical basis has been given by Lighthill ["Introduction: Boundary layer theory," in Laminar Boundary Layers, edited by L. Rosenhead (Clarendon Press, 1963), pp. 46-113], which we further elaborate. This mechanism can be clearly revealed in terms of vorticity formulation but is hidden in conventional momentum formulation, and hence has long been missing in the history of one's efforts to understand lift. By a careful numerical simulation of the flow around a NACA-0012 airfoil, and using both Eulerian and Lagrangian descriptions, we illustrate the detailed transient process by which the airfoil gains its circulation and demonstrate the dominating role of relevant dynamical causal mechanisms at the boundary. In so doing, we find that the various statements for the establishment of Kutta condition in steady inviscid flow actually correspond to a sequence of events in unsteady viscous flow.

  17. EEG oscillations: From correlation to causality.

    Science.gov (United States)

    Herrmann, Christoph S; Strüber, Daniel; Helfrich, Randolph F; Engel, Andreas K

    2016-05-01

    Already in his first report on the discovery of the human EEG in 1929, Berger showed great interest in further elucidating the functional roles of the alpha and beta waves for normal mental activities. Meanwhile, most cognitive processes have been linked to at least one of the traditional frequency bands in the delta, theta, alpha, beta, and gamma range. Although the existing wealth of high-quality correlative EEG data led many researchers to the conviction that brain oscillations subserve various sensory and cognitive processes, a causal role can only be demonstrated by directly modulating such oscillatory signals. In this review, we highlight several methods to selectively modulate neuronal oscillations, including EEG-neurofeedback, rhythmic sensory stimulation, repetitive transcranial magnetic stimulation (rTMS), and transcranial alternating current stimulation (tACS). In particular, we discuss tACS as the most recent technique to directly modulate oscillatory brain activity. Such studies demonstrating the effectiveness of tACS comprise reports on purely behavioral or purely electrophysiological effects, on combination of behavioral effects with offline EEG measurements or on simultaneous (online) tACS-EEG recordings. Whereas most tACS studies are designed to modulate ongoing rhythmic brain activity at a specific frequency, recent evidence suggests that tACS may also modulate cross-frequency interactions. Taken together, the modulation of neuronal oscillations allows to demonstrate causal links between brain oscillations and cognitive processes and to obtain important insights into human brain function. PMID:25659527

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

    Science.gov (United States)

    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. PMID:26099149

  19. On the causal structure between CO2 and global temperature

    OpenAIRE

    Adolf Stips; Diego Macias; Clare Coughlan; Elisa Garcia-Gorriz; X. San Liang

    2016-01-01

    We use a newly developed technique that is based on the information flow concept to investigate the causal structure between the global radiative forcing and the annual global mean surface temperature anomalies (GMTA) since 1850. Our study unambiguously shows one-way causality between the total Greenhouse Gases and GMTA. Specifically, it is confirmed that the former, especially CO2, are the main causal drivers of the recent warming. A significant but smaller information flow comes from aeroso...

  20. Non-parametric causal inference for bivariate time series

    CERN Document Server

    McCracken, James M

    2015-01-01

    We introduce new quantities for exploratory causal inference between bivariate time series. The quantities, called penchants and leanings, are computationally straightforward to apply, follow directly from assumptions of probabilistic causality, do not depend on any assumed models for the time series generating process, and do not rely on any embedding procedures; these features may provide a clearer interpretation of the results than those from existing time series causality tools. The penchant and leaning are computed based on a structured method for computing probabilities.

  1. Causality, Unintended Consequences and Deducing Shared Causes

    OpenAIRE

    Steven M. Shugan

    2007-01-01

    Despite warnings against inferring causality from observed correlations or statistical dependence, some articles do. Observed correlation is neither necessary nor sufficient to infer causality as defined by the term's everyday usage. For example, a deterministic causal process creates pseudorandom numbers; yet, we observe no correlation between the numbers. Child height correlates with spelling ability because age causes both. Moreover, order is problematic—we hear train whistles before obser...

  2. Dark matter perturbations and viscosity: a causal approach

    OpenAIRE

    Acquaviva, Giovanni; John, Anslyn; Pénin, Aurélie

    2016-01-01

    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 analyse 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 non-causal Eckart theory, we obtain a third order evo...

  3. Linkage intensity learning approach with genetic algorithm for causality diagram

    Institute of Scientific and Technical Information of China (English)

    WANG Cheng-liang; CHEN Juan-juan

    2007-01-01

    The causality diagram theory, which adopts graphical expression of knowledge and direct intensity of causality, overcomes some shortages in belief network and has evolved into a mixed causality diagram methodology for discrete and continuous variable. But to give linkage intensity of causality diagram is difficult, particularly in many working conditions in which sampling data are limited or noisy. The classic learning algorithm is hard to be adopted. We used genetic algorithm to learn linkage intensity from limited data. The simulation results demonstrate that this algorithm is more suitable than the classic algorithm in the condition of sample shortage such as space shuttle's fault diagnoisis.

  4. Granger causality and transfer entropy are equivalent for Gaussian variables.

    Science.gov (United States)

    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.

  5. Granger causality and transfer entropy are equivalent for Gaussian variables

    CERN Document Server

    Barnett, Lionel; Seth, Anil

    2009-01-01

    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. It has always seemed plausible that the two concepts ought to be related. 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.

  6. Causality and stability of cosmic jets

    Science.gov (United States)

    Porth, Oliver; Komissarov, Serguei S.

    2015-09-01

    In stark contrast to their laboratory and terrestrial counterparts, cosmic jets appear to be very stable. They are able to penetrate vast spaces, which exceed by up to a billion times the size of their central engines. We propose that the reason behind this remarkable property is the loss of causal connectivity across these jets, caused by their rapid expansion in response to fast decline of external pressure with the distance from the `jet engine'. In atmospheres with power-law pressure distribution, pext ∝ z-κ, the total loss of causal connectivity occurs, when κ > 2 - the steepness which is expected to be quite common for many astrophysical environments. This conclusion does not seem to depend on the physical nature of jets - it applies both to relativistic and non-relativistic flows, both magnetically dominated and unmagnetized jets. In order to verify it, we have carried out numerical simulations of moderately magnetized and moderately relativistic jets. The results give strong support to our hypothesis and provide with valuable insights. In particular, we find that the z-pinched inner cores of magnetic jets expand slower than their envelopes and become susceptible to instabilities even when the whole jet is stable. This may result in local dissipation and emission without global disintegration of the flow. Cosmic jets may become globally unstable when they enter flat sections of external atmospheres. We propose that the Fanaroff-Riley (FR) morphological division of extragalactic radio sources into two classes is related to this issue. In particular, we argue that the low power FR-I jets become reconfined, causally connected and globally unstable on the scale of galactic X-ray coronas, whereas more powerful FR-II jets reconfine much further out, already on the scale of radio lobes and remain largely intact until they terminate at hotspots. Using this idea, we derived the relationship between the critical jet power and the optical luminosity of the host

  7. Equity Theory Ratios as Causal Schemas.

    Science.gov (United States)

    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

  8. Quantum Causality, Stochastics, Trajectories and Information

    CERN Document Server

    Belavkin, V P

    2002-01-01

    A history of the discovery of quantum mechanics and paradoxes of its interpretation is reconsidered from the modern point of view of quantum stochastics and information. It is argued that in the orthodox quantum mechanics there is no place for quantum phenomenology such as events. The development of quantum measurement theory, initiated by von Neumann, and Bell's conceptual critics of hidden variable theories indicated a possibility for resolution of this crisis. This can be done by divorcing the algebra of the dynamical generators and an extended algebra of the potential (quantum) and the actual (classical) observables. The latter, called beables, form the center of the algebra of all observables, as the only visible (macroscopic) observables must be compatible with any hidden (microscopic) observable. It is shown that within this approach quantum causality can be rehabilitated within an extended quantum mechanics (eventum mechanics) in the form of a superselection rule for compatibility of the consistent hi...

  9. Equity Theory Ratios as Causal Schemas

    Science.gov (United States)

    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.

  10. Causality and local determinism versus quantum nonlocality

    CERN Document Server

    Kupczynski, Marian

    2013-01-01

    The entanglement and the violation of Bell and CHSH inequalities in spin polarization correlation experiments (SPCE) is considered to be one of the biggest mysteries of Nature and is called quantum nonlocality. In this paper we show once again that this conclusion is based on imprecise terminology and on the lack of understanding of probabilistic models used in various proofs of Bell and CHSH theorems. These models are inconsistent with experimental protocols used in SPCE. This is the only reason why Bell and CHSH inequalities are violated. A probabilistic non-signalling description of SPCE, consistent with quantum predictions, is possible and it depends explicitly on the context of each experiment. It is also deterministic in the sense that the outcome is determined by supplementary local parameters describing both a physical signals and measuring instruments. The existence of such description gives additional arguments that quantum theory is emergent from some more detailed theory respecting causality and l...

  11. Causal structure and electrodynamics on Finsler spacetimes

    Science.gov (United States)

    Pfeifer, Christian; Wohlfarth, Mattias N. R.

    2011-08-01

    We present a concise new definition of Finsler spacetimes that generalizes Lorentzian metric manifolds and provides consistent backgrounds for physics. Extending standard mathematical constructions known from Finsler spaces, we show that geometric objects like the Cartan nonlinear connection and its curvature are well defined almost everywhere on Finsler spacetimes, including their null structure. This allows us to describe the complete causal structure in terms of timelike and null curves; these are essential to model physical observers and the propagation of light. We prove that the timelike directions form an open convex cone with a null boundary, as is the case in Lorentzian geometry. Moreover, we develop action integrals for physical field theories on Finsler spacetimes, and tools to deduce the corresponding equations of motion. These are applied to construct a theory of electrodynamics that confirms the claimed propagation of light along Finsler null geodesics.

  12. Causal structure and electrodynamics on Finsler spacetimes

    CERN Document Server

    Pfeifer, Christian

    2011-01-01

    We present a concise new definition of Finsler spacetimes that generalize Lorentzian metric manifolds and provide consistent backgrounds for physics. Extending standard mathematical constructions known from Finsler spaces we show that geometric objects like the Cartan non-linear connection and its curvature are well-defined almost everywhere on Finsler spacetimes, also on their null structure. This allows us to describe the complete causal structure in terms of timelike and null curves; these are essential to model physical observers and the propagation of light. We prove that the timelike directions form an open convex cone with null boundary as is the case in Lorentzian geometry. Moreover, we develop action integrals for physical field theories on Finsler spacetimes, and tools to deduce the corresponding equations of motion. These are applied to construct a theory of electrodynamics that confirms the claimed propagation of light along Finsler null geodesics.

  13. Exploring Torus Universes in Causal Dynamical Triangulations

    CERN Document Server

    Budd, T G

    2013-01-01

    Motivated by the search for new observables in nonperturbative quantum gravity, we consider Causal Dynamical Triangulations (CDT) in 2+1 dimensions with the spatial topology of a torus. This system is of particular interest, because one can study not only the global scale factor, but also global shape variables in the presence of arbitrary quantum fluctuations of the geometry. Our initial investigation focusses on the dynamics of the scale factor and uncovers a qualitatively new behaviour, which leads us to investigate a novel type of boundary conditions for the path integral. Comparing large-scale features of the emergent quantum geometry in numerical simulations with a classical minisuperspace formulation, we find partial agreement. By measuring the correlation matrix of volume fluctuations we succeed in reconstructing the effective action for the scale factor directly from the simulation data. Apart from setting the stage for the analysis of shape dynamics on the torus, the new set-up highlights the role o...

  14. Equity Theory Ratios as Causal Schemas

    Directory of Open Access Journals (Sweden)

    Alexios Arvanitis

    2016-08-01

    Full Text Available 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.

  15. A study in cosmology and causal thermodynamics

    International Nuclear Information System (INIS)

    The especial relativity of thermodynamic theories for reversible and irreversible processes in continuous medium is studied. The formalism referring to equilibrium and non-equilibrium configurations, and theories which includes the presence of gravitational fields are discussed. The nebular model in contraction with dissipative processes identified by heat flux and volumetric viscosity is thermodymically analysed. This model is presented by a plane conformal metric. The temperature, pressure, entropy and entropy production within thermodynamic formalism which adopts the hypothesis of local equilibrium, is calculated. The same analysis is carried out considering a causal thermodynamics, which establishes a local entropy of non-equilibrium. Possible homogeneous and isotropic cosmological models, considering the new phenomenological equation for volumetric viscosity deriving from cause thermodynamics are investigated. The found out models have plane spatial section (K=0) and some ones do not have singularities. The energy conditions are verified and the entropy production for physically reasobable models are calculated. (M.C.K.)

  16. Causality constraints in conformal field theory

    Science.gov (United States)

    Hartman, Thomas; Jain, Sachin; Kundu, Sandipan

    2016-05-01

    Causality places nontrivial constraints on QFT in Lorentzian signature, for example fixing the signs of certain terms in the low energy Lagrangian. In d dimensional conformal field theory, we show how such constraints are encoded in crossing symmetry of Euclidean correlators, and derive analogous constraints directly from the conformal bootstrap (analytically). The bootstrap setup is a Lorentzian four-point function corresponding to propagation through a shockwave. Crossing symmetry fixes the signs of certain log terms that appear in the conformal block expansion, which constrains the interactions of low-lying operators. As an application, we use the bootstrap to rederive the well known sign constraint on the (∂ ϕ)4 coupling in effective field theory, from a dual CFT. We also find constraints on theories with higher spin conserved currents. Our analysis is restricted to scalar correlators, but we argue that similar methods should also impose nontrivial constraints on the interactions of spinning operators.

  17. The balanced survivor average causal effect.

    Science.gov (United States)

    Greene, Tom; Joffe, Marshall; Hu, Bo; Li, Liang; Boucher, Ken

    2013-01-01

    Statistical analysis of longitudinal outcomes is often complicated by the absence of observable values in patients who die prior to their scheduled measurement. In such cases, the longitudinal data are said to be "truncated by death" to emphasize that the longitudinal measurements are not simply missing, but are undefined after death. Recently, the truncation by death problem has been investigated using the framework of principal stratification to define the target estimand as the survivor average causal effect (SACE), which in the context of a two-group randomized clinical trial is the mean difference in the longitudinal outcome between the treatment and control groups for the principal stratum of always-survivors. The SACE is not identified without untestable assumptions. These assumptions have often been formulated in terms of a monotonicity constraint requiring that the treatment does not reduce survival in any patient, in conjunction with assumed values for mean differences in the longitudinal outcome between certain principal strata. In this paper, we introduce an alternative estimand, the balanced-SACE, which is defined as the average causal effect on the longitudinal outcome in a particular subset of the always-survivors that is balanced with respect to the potential survival times under the treatment and control. We propose a simple estimator of the balanced-SACE that compares the longitudinal outcomes between equivalent fractions of the longest surviving patients between the treatment and control groups and does not require a monotonicity assumption. We provide expressions for the large sample bias of the estimator, along with sensitivity analyses and strategies to minimize this bias. We consider statistical inference under a bootstrap resampling procedure. PMID:23658214

  18. Assessing thalamocortical functional connectivity with Granger causality.

    Science.gov (United States)

    Chen, Cheng; Maybhate, Anil; Israel, David; Thakor, Nitish V; Jia, Xiaofeng

    2013-09-01

    Assessment of network connectivity across multiple brain regions is critical to understanding the mechanisms underlying various neurological disorders. Conventional methods for assessing dynamic interactions include cross-correlation and coherence analysis. However, these methods do not reveal the direction of information flow, which is important for studying the highly directional neurological system. Granger causality (GC) analysis can characterize the directional influences between two systems. We tested GC analysis for its capability to capture directional interactions within both simulated and in vivo neural networks. The simulated networks consisted of Hindmarsh-Rose neurons; GC analysis was used to estimate the causal influences between two model networks. Our analysis successfully detected asymmetrical interactions between these networks ( , t -test). Next, we characterized the relationship between the "electrical synaptic strength" in the model networks and interactions estimated by GC analysis. We demonstrated the novel application of GC to monitor interactions between thalamic and cortical neurons following ischemia induced brain injury in a rat model of cardiac arrest (CA). We observed that during the post-CA acute period the GC interactions from the thalamus to the cortex were consistently higher than those from the cortex to the thalamus ( 1.983±0.278 times higher, p = 0.021). In addition, the dynamics of GC interactions between the thalamus and the cortex were frequency dependent. Our study demonstrated the feasibility of GC to monitor the dynamics of thalamocortical interactions after a global nervous system injury such as CA-induced ischemia, and offers preferred alternative applications in characterizing other inter-regional interactions in an injured brain.

  19. Recursive partitioning for heterogeneous causal effects.

    Science.gov (United States)

    Athey, Susan; Imbens, Guido

    2016-07-01

    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

  20. World oil and agricultural commodity prices: Evidence from nonlinear causality

    International Nuclear Information System (INIS)

    The increasing co-movements between the world oil and agricultural commodity prices have renewed interest in determining price transmission from oil prices to those of agricultural commodities. This study extends the literature on the oil-agricultural commodity prices nexus, which particularly concentrates on nonlinear causal relationships between the world oil and three key agricultural commodity prices (corn, soybeans, and wheat). To this end, the linear causality approach of Toda-Yamamoto and the nonparametric causality method of Diks-Panchenko are applied to the weekly data spanning from 1994 to 2010. The linear causality analysis indicates that the oil prices and the agricultural commodity prices do not influence each other, which supports evidence on the neutrality hypothesis. In contrast, the nonlinear causality analysis shows that: (i) there are nonlinear feedbacks between the oil and the agricultural prices, and (ii) there is a persistent unidirectional nonlinear causality running from the oil prices to the corn and to the soybeans prices. The findings from the nonlinear causality analysis therefore provide clues for better understanding the recent dynamics of the agricultural commodity prices and some policy implications for policy makers, farmers, and global investors. This study also suggests the directions for future studies. - Research highlights: → This study determines the price transmission mechanisms between the world oil and three key agricultural commodity prices (corn, soybeans, and wheat). → The linear and nonlinear cointegration and causality methods are carried out. → The linear causality analysis supports evidence on the neutrality hypothesis. → The nonlinear causality analysis shows that there is a persistent unidirectional causality from the oil prices to the corn and to the soybeans prices.

  1. Causal Propagators for the Second Order Wilson Loop

    OpenAIRE

    Pimentel, B. M.; Tomazelli, J. L.

    1996-01-01

    We evaluate the Wilson loop at second order in general non-covariant gauges by means of the causal principal-value prescription for the gauge- dependent poles in the gauge-boson propagator and show that the result agrees with the usual causal prescriptions.

  2. Time Symmetric Quantum Mechanics and Causal Classical Physics

    CERN Document Server

    Bopp, Fritz W

    2016-01-01

    A two boundary quantum mechanics without time ordered causal structure is advocated as consistent theory. The apparent causal structure of usual "near future" macroscopic phenomena is attributed to a cosmological asymmetry and to rules governing the transition between microscopic to macroscopic observations. Our interest is a heuristic understanding of the resulting macroscopic physics.

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

    Science.gov (United States)

    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…

  4. The Feasibility of Using Causal Indicators in Educational Measurement

    Science.gov (United States)

    Wang, Jue; Engelhard, George, Jr.

    2016-01-01

    The authors of the focus article describe an important issue related to the use and interpretation of causal indicators within the context of structural equation modeling (SEM). In the focus article, the authors illustrate with simulated data the effects of omitting a causal indicator. Since SEMs are used extensively in the social and behavioral…

  5. Cause and Event: Supporting Causal Claims through Logistic Models

    Science.gov (United States)

    O'Connell, Ann A.; Gray, DeLeon L.

    2011-01-01

    Efforts to identify and support credible causal claims have received intense interest in the research community, particularly over the past few decades. In this paper, we focus on the use of statistical procedures designed to support causal claims for a treatment or intervention when the response variable of interest is dichotomous. We identify…

  6. Evidence for Deductive Reasoning in Blocking of Causal Judgments

    Science.gov (United States)

    Mitchell, C.J.; Lovibond, P.F.; Condoleon, M.

    2005-01-01

    We have recently demonstrated that pre-training of additivity (the outcome of two causal cues is larger than one causal cue) greatly enhances blocking. This manipulation could work by removing a ceiling effect on the outcome, as proposed by Cheng (1997). Alternatively, it could remove the logical ambiguity associated with blocking under…

  7. The causal boundary and its relations with the conformal boundary

    Energy Technology Data Exchange (ETDEWEB)

    Herrera, J, E-mail: jherrera@agt.cie.uma.e [Departamento de Algebra, GeometrIa y TopologIa, Facultad de Ciencias, Universidad de Malaga, Campus Teatinos, 29071 Malaga (Spain)

    2010-05-01

    Our aim in this note is to present the results (obtained in [2]) which ensure that, under certain regularity conditions, the conformal boundary becomes equal to the causal boundary, not only as a point set, but in a topological and chronological level. In particular, under these conditions the conformal boundary becomes a powerful tool to compute the causal one.

  8. Causal Discourse Analyzer: Improving Automated Feedback on Academic ESL Writing

    Science.gov (United States)

    Chukharev-Hudilainen, Evgeny; Saricaoglu, Aysel

    2016-01-01

    Expressing causal relations plays a central role in academic writing. While it is important that writing instructors assess and provide feedback on learners' causal discourse, it could be a very time-consuming task. In this respect, automated writing evaluation (AWE) tools may be helpful. However, to date, there have been no AWE tools capable of…

  9. From Blickets to Synapses: Inferring Temporal Causal Networks by Observation

    Science.gov (United States)

    Fernando, Chrisantha

    2013-01-01

    How do human infants learn the causal dependencies between events? Evidence suggests that this remarkable feat can be achieved by observation of only a handful of examples. Many computational models have been produced to explain how infants perform causal inference without explicit teaching about statistics or the scientific method. Here, we…

  10. Manifest Variable Granger Causality Models for Developmental Research: A Taxonomy

    Science.gov (United States)

    von Eye, Alexander; Wiedermann, Wolfgang

    2015-01-01

    Granger models are popular when it comes to testing hypotheses that relate series of measures causally to each other. In this article, we propose a taxonomy of Granger causality models. The taxonomy results from crossing the four variables Order of Lag, Type of (Contemporaneous) Effect, Direction of Effect, and Segment of Dependent Series…

  11. Thinking Fast and Slow about Causality: Response to Palinkas

    Science.gov (United States)

    Marsh, Jeanne C.

    2014-01-01

    Larry Palinkas advances the developing science of social work by providing an explanation of how social science research methods, both qualitative and quantitative, can improve our capacity to draw casual inferences. Understanding causal relations and making causal inferences--with the promise of being able to predict and control outcomes--is…

  12. Temporal and Causal Reasoning in Deaf and Hearing Novice Readers

    Science.gov (United States)

    Sullivan, Susan; Oakhill, Jane; Arfé, Barbara; Boureux, Magali

    2014-01-01

    Temporal and causal information in text are crucial in helping the reader form a coherent representation of a narrative. Deaf novice readers are generally poor at processing linguistic markers of causal/temporal information (i.e., connectives), but what is unclear is whether this is indicative of a more general deficit in reasoning about…

  13. Bell's theorem and the causal arrow of time

    Science.gov (United States)

    Argaman, Nathan

    2010-10-01

    Einstein held that the formalism of quantum mechanics involves "spooky actions at a distance." In the 1960s, Bell amplified this by showing that the predictions of quantum mechanics disagree with the results of any locally causal description. It should be appreciated that accepting nonlocal descriptions while retaining causality leads to a clash with relativity. Furthermore, the causal arrow of time by definition contradicts time-reversal symmetry. For these reasons, Wheeler and Feynman, Costa de Beauregard, Cramer, Price, and others have advocated abandoning microscopic causality. In this paper, a simplistic but concrete example of this line of thought is presented, in the form of a retro-causal toy model that is stochastic and provides an appealing description of the quantum correlations discussed by Bell. It is concluded that Einstein's "spooky actions" may occur "in the past" rather than "at a distance," resolving the tension between quantum mechanics and relativity and opening unexplored possibilities for future reformulations of quantum mechanics.

  14. Mitigating the effects of measurement noise on Granger causality

    CERN Document Server

    Nalatore, Hariharan; Ding, Mingzhou

    2007-01-01

    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 (EM) algorithm. Numerical examples are used to demonstrate the effectiveness of the den...

  15. A causal net approach to relativistic quantum mechanics

    Science.gov (United States)

    Bateson, R. D.

    2012-05-01

    In this paper we discuss a causal network approach to describing relativistic quantum mechanics. Each vertex on the causal net represents a possible point event or particle observation. By constructing the simplest causal net based on Reichenbach-like conjunctive forks in proper time we can exactly derive the 1+1 dimension Dirac equation for a relativistic fermion and correctly model quantum mechanical statistics. Symmetries of the net provide various quantum mechanical effects such as quantum uncertainty and wavefunction, phase, spin, negative energy states and the effect of a potential. The causal net can be embedded in 3+1 dimensions and is consistent with the conventional Dirac equation. In the low velocity limit the causal net approximates to the Schrodinger equation and Pauli equation for an electromagnetic field. Extending to different momentum states the net is compatible with the Feynman path integral approach to quantum mechanics that allows calculation of well known quantum phenomena such as diffraction.

  16. Causal Relationship Between Relative Price Variability and Inflation in Turkey:

    Directory of Open Access Journals (Sweden)

    Nebiye Yamak

    2016-09-01

    Full Text Available This study investigates the causal relationship between inflation and relative price variability in Turkey for the period of January 2003-January 2014, by using panel data. In the study, a Granger (1969 non-causality test in heterogeneous panel data models developed by Dumitrescu and Hurlin (2012 is utilized to determine the causal relations between inflation rate relative price variability. The panel data consists of 4123 observations: 133 time observations and 31 cross-section observations. The results of panel causality test indicate that there is a bidirectional causality between inflation rate and relative price variability by not supporting the imperfection information model of Lucas and the menu cost model of Ball and Mankiw.

  17. Statistical causal inferences and their applications in public health research

    CERN Document Server

    Wu, Pan; Chen, Ding-Geng

    2016-01-01

    This book compiles and presents new developments in statistical causal inference. The accompanying data and computer programs are publicly available so readers may replicate the model development and data analysis presented in each chapter. In this way, methodology is taught so that readers may implement it directly. The book brings together experts engaged in causal inference research to present and discuss recent issues in causal inference methodological development. This is also a timely look at causal inference applied to scenarios that range from clinical trials to mediation and public health research more broadly. In an academic setting, this book will serve as a reference and guide to a course in causal inference at the graduate level (Master's or Doctorate). It is particularly relevant for students pursuing degrees in Statistics, Biostatistics and Computational Biology. Researchers and data analysts in public health and biomedical research will also find this book to be an important reference.

  18. Quantum objects as elementary units of causality and locality

    CERN Document Server

    Diel, Hans H

    2016-01-01

    The author's attempt to construct a local causal model of quantum theory (QT) that includes quantum field theory (QFT) resulted in the identification of "quantum objects" as the elementary units of causality and locality. Quantum objects are collections of particles (including single particles) whose collective dynamics and measurement results can only be described by the laws of QT and QFT. Local causal models of quantum objects' internal dynamics are not possible if a locality is understood as a space-point locality. Within quantum objects, state transitions may occur which instantly affect the whole quantum object. The identification of quantum objects as the elementary units of causality and locality has two primary implications for a causal model of quantum objects: (1) quantum objects run autonomously with system-state update frequencies based on their local proper times and with either no or minimal dependency on external parameters. (2) The laws of physics that describe global (but relativistic) inter...

  19. A causal net approach to relativistic quantum mechanics

    International Nuclear Information System (INIS)

    In this paper we discuss a causal network approach to describing relativistic quantum mechanics. Each vertex on the causal net represents a possible point event or particle observation. By constructing the simplest causal net based on Reichenbach-like conjunctive forks in proper time we can exactly derive the 1+1 dimension Dirac equation for a relativistic fermion and correctly model quantum mechanical statistics. Symmetries of the net provide various quantum mechanical effects such as quantum uncertainty and wavefunction, phase, spin, negative energy states and the effect of a potential. The causal net can be embedded in 3+1 dimensions and is consistent with the conventional Dirac equation. In the low velocity limit the causal net approximates to the Schrodinger equation and Pauli equation for an electromagnetic field. Extending to different momentum states the net is compatible with the Feynman path integral approach to quantum mechanics that allows calculation of well known quantum phenomena such as diffraction.

  20. Causal beliefs about depression in different cultural groups-what do cognitive psychological theories of causal learning and reasoning predict?

    Science.gov (United States)

    Hagmayer, York; Engelmann, Neele

    2014-01-01

    Cognitive psychological research focuses on causal learning and reasoning while cognitive anthropological and social science research tend to focus on systems of beliefs. Our aim was to explore how these two types of research can inform each other. Cognitive psychological theories (causal model theory and causal Bayes nets) were used to derive predictions for systems of causal beliefs. These predictions were then applied to lay theories of depression as a specific test case. A systematic literature review on causal beliefs about depression was conducted, including original, quantitative research. Thirty-six studies investigating 13 non-Western and 32 Western cultural groups were analyzed by classifying assumed causes and preferred forms of treatment into common categories. Relations between beliefs and treatment preferences were assessed. Substantial agreement between cultural groups was found with respect to the impact of observable causes. Stress was generally rated as most important. Less agreement resulted for hidden, especially supernatural causes. Causal beliefs were clearly related to treatment preferences in Western groups, while evidence was mostly lacking for non-Western groups. Overall predictions were supported, but there were considerable methodological limitations. Pointers to future research, which may combine studies on causal beliefs with experimental paradigms on causal reasoning, are given.

  1. Causal beliefs about depression in different cultural groups – What do cognitive psychological theories of causal learning and reasoning predict?

    Directory of Open Access Journals (Sweden)

    York eHagmayer

    2014-11-01

    Full Text Available Cognitive psychological research focusses on causal learning and reasoning while cognitive anthropological and social science research tend to focus on systems of beliefs. Our aim was to explore how these two types of research can inform each other. Cognitive psychological theories (causal model theory and causal Bayes nets were used to derive predictions for systems of causal beliefs. These predictions were then applied to lay theories of depression as a specific test case. A systematic literature review on causal beliefs about depression was conducted, including original, quantitative research. Thirty-six studies investigating 13 non-Western and 32 Western cultural groups were analysed by classifying assumed causes and preferred forms of treatment into common categories. Relations between beliefs and treatment preferences were assessed. Substantial agreement between cultural groups was found with respect to the impact of observable causes. Stress was generally rated as most important. Less agreement resulted for hidden, especially supernatural causes. Causal beliefs were clearly related to treatment preferences in Western groups, while evidence was mostly lacking for non-Western groups. Overall predictions were supported, but there were considerable methodological limitations. Pointers to future research, which may combine studies on causal beliefs with experimental paradigms on causal reasoning, are given.

  2. Causal beliefs about depression in different cultural groups-what do cognitive psychological theories of causal learning and reasoning predict?

    Science.gov (United States)

    Hagmayer, York; Engelmann, Neele

    2014-01-01

    Cognitive psychological research focuses on causal learning and reasoning while cognitive anthropological and social science research tend to focus on systems of beliefs. Our aim was to explore how these two types of research can inform each other. Cognitive psychological theories (causal model theory and causal Bayes nets) were used to derive predictions for systems of causal beliefs. These predictions were then applied to lay theories of depression as a specific test case. A systematic literature review on causal beliefs about depression was conducted, including original, quantitative research. Thirty-six studies investigating 13 non-Western and 32 Western cultural groups were analyzed by classifying assumed causes and preferred forms of treatment into common categories. Relations between beliefs and treatment preferences were assessed. Substantial agreement between cultural groups was found with respect to the impact of observable causes. Stress was generally rated as most important. Less agreement resulted for hidden, especially supernatural causes. Causal beliefs were clearly related to treatment preferences in Western groups, while evidence was mostly lacking for non-Western groups. Overall predictions were supported, but there were considerable methodological limitations. Pointers to future research, which may combine studies on causal beliefs with experimental paradigms on causal reasoning, are given. PMID:25505432

  3. Causality and subjectivity in discourse : The meaning and use of causal connectives in spontaneous conversation, chat interactions and written text

    NARCIS (Netherlands)

    Sanders, T.J.M.; Spooren, W.P.M.S.

    2015-01-01

    Many languages of the world have connectives to express causal relations at the discourse level. Often, language users systematically prefer one lexical item (because) over another (even highly similar) one (since) to express a causal relationship. Such choices provide a window on speakers' cognitiv

  4. Causality and subjectivity in discourse: The meaning and use of causal connectives in spontaneous conversation, chat interactions and written text

    NARCIS (Netherlands)

    Sanders, T.J.M.; Spooren, W.P.M.S.

    2015-01-01

    Many languages of the world have connectives to express causal relations at the discourse level. Often, language users systematically prefer one lexical item (because) over another (even highly similar) one (since) to express a causal relationship. Such choices provide a window on speakers’ cognitiv

  5. Simulation of system models containing zero-order causal paths - I. Classification of zero-order causal paths

    NARCIS (Netherlands)

    Dijk, van J.; Breedveld, P.C.

    1991-01-01

    The existence of zero-order causal paths in bond graphs of physical systems implies the set of state equations to be an implicit mixed set of Differential and Algebraic Equations (DAEs). In the block diagram expansion of such a bond graph, this type of causal path corresponds with a zero-order loop.

  6. Causation or only correlation? Application of causal inference graphs for evaluating causality in nano-QSAR models

    Science.gov (United States)

    Sizochenko, Natalia; Gajewicz, Agnieszka; Leszczynski, Jerzy; Puzyn, Tomasz

    2016-03-01

    In this paper, we suggest that causal inference methods could be efficiently used in Quantitative Structure-Activity Relationships (QSAR) modeling as additional validation criteria within quality evaluation of the model. Verification of the relationships between descriptors and toxicity or other activity in the QSAR model has a vital role in understanding the mechanisms of action. The well-known phrase ``correlation does not imply causation'' reflects insight statistically correlated with the endpoint descriptor may not cause the emergence of this endpoint. Hence, paradigmatic shifts must be undertaken when moving from traditional statistical correlation analysis to causal analysis of multivariate data. Methods of causal discovery have been applied for broader physical insight into mechanisms of action and interpretation of the developed nano-QSAR models. Previously developed nano-QSAR models for toxicity of 17 nano-sized metal oxides towards E. coli bacteria have been validated by means of the causality criteria. Using the descriptors confirmed by the causal technique, we have developed new models consistent with the straightforward causal-reasoning account. It was proven that causal inference methods are able to provide a more robust mechanistic interpretation of the developed nano-QSAR models.In this paper, we suggest that causal inference methods could be efficiently used in Quantitative Structure-Activity Relationships (QSAR) modeling as additional validation criteria within quality evaluation of the model. Verification of the relationships between descriptors and toxicity or other activity in the QSAR model has a vital role in understanding the mechanisms of action. The well-known phrase ``correlation does not imply causation'' reflects insight statistically correlated with the endpoint descriptor may not cause the emergence of this endpoint. Hence, paradigmatic shifts must be undertaken when moving from traditional statistical correlation analysis to causal

  7. On Optimum Causal Cognitive Spectrum Reutilization Strategy

    CERN Document Server

    Haghighi, Kasra; Agrell, Erik

    2011-01-01

    In this paper we study opportunistic transmission strategies for cognitive radios (CR) in which causal noisy observation from a primary user(s) (PU) state is available. PU is assumed to be operating in a slotted manner, according to a two-state Markov model. The objective is to maximize utilization ratio (UR), i.e., relative number of the PU-idle slots that are used by CR, subject to interference ratio (IR), i.e., relative number of the PU-active slots that are used by CR, below a certain level. We introduce an a-posteriori LLR-based cognitive transmission strategy and show that this strategy is optimum in the sense of maximizing UR given a certain maximum allowed IR. Two methods for calculating threshold for this strategy in practical situations are presented. One of them performs well in higher SNRs but might have too large IR at low SNRs and low PU activity levels, and the other is proven to never violate the allowed IR at the price of a reduced UR. In addition, an upper-bound for the UR of any CR strategy...

  8. Causal structure and hierarchies of models.

    Science.gov (United States)

    Hoover, Kevin D

    2012-12-01

    Economics prefers complete explanations: general over partial equilibrium, microfoundational over aggregate. Similarly, probabilistic accounts of causation frequently prefer greater detail to less as in typical resolutions of Simpson's paradox. Strategies of causal refinement equally aim to distinguish direct from indirect causes. Yet, there are countervailing practices in economics. Representative-agent models aim to capture economic motivation but not to reduce the level of aggregation. Small structural vector-autoregression and dynamic stochastic general-equilibrium models are practically preferred to larger ones. The distinction between exogenous and endogenous variables suggests partitioning the world into distinct subsystems. The tension in these practices is addressed within a structural account of causation inspired by the work of Herbert Simon's, which defines cause with reference to complete systems adapted to deal with incomplete systems and piecemeal evidence. The focus is on understanding the constraints that a structural account of causation places on the freedom to model complex or lower-order systems as simpler or higher-order systems and on to what degree piecemeal evidence can be incorporated into a structural account.

  9. Body selectivity in occipitotemporal cortex: Causal evidence.

    Science.gov (United States)

    Downing, Paul E; Peelen, Marius V

    2016-03-01

    Perception of others' bodies provides information that is useful for a number of important social-cognitive processes. Evidence from neuroimaging methods has identified focal cortical regions that are highly selective for perceiving bodies and body parts, including the extrastriate body area (EBA) and fusiform body area (FBA). Our understanding of the functional properties of these regions, and their causal contributions to behavior, has benefitted from the study of neuropsychological patients and particularly from investigations using transcranial magnetic stimulation (TMS). We review this evidence, focusing on TMS studies that are revealing of how (and when) activity in EBA contributes to detecting people in natural scenes; to resolving their body shape, movements, actions, individual parts, and identities; and to guiding goal-directed behavior. These findings are considered in reference to a framework for body perception in which the patterns of neural activity in EBA and FBA jointly serve to make explicit the elements of the visual scene that correspond to the body and its parts. These representations are modulated by other sources of information such as prior knowledge, and are shared with wider brain networks involved in many aspects of social cognition. PMID:26044771

  10. Dynamic causal models and autopoietic systems.

    Science.gov (United States)

    David, Olivier

    2007-01-01

    Dynamic Causal Modelling (DCM) and the theory of autopoietic systems are two important conceptual frameworks. In this review, we suggest that they can be combined to answer important questions about self-organising systems like the brain. DCM has been developed recently by the neuroimaging community to explain, using biophysical models, the non-invasive brain imaging data are caused by neural processes. It allows one to ask mechanistic questions about the implementation of cerebral processes. In DCM the parameters of biophysical models are estimated from measured data and the evidence for each model is evaluated. This enables one to test different functional hypotheses (i.e., models) for a given data set. Autopoiesis and related formal theories of biological systems as autonomous machines represent a body of concepts with many successful applications. However, autopoiesis has remained largely theoretical and has not penetrated the empiricism of cognitive neuroscience. In this review, we try to show the connections that exist between DCM and autopoiesis. In particular, we propose a simple modification to standard formulations of DCM that includes autonomous processes. The idea is to exploit the machinery of the system identification of DCMs in neuroimaging to test the face validity of the autopoietic theory applied to neural subsystems. We illustrate the theoretical concepts and their implications for interpreting electroencephalographic signals acquired during amygdala stimulation in an epileptic patient. The results suggest that DCM represents a relevant biophysical approach to brain functional organisation, with a potential that is yet to be fully evaluated. PMID:18575681

  11. Solution to causality paradox upon total reflection

    Institute of Scientific and Technical Information of China (English)

    LIU Xiang-min; CAO Zhuang-qi; ZHU Peng-fei; SHEN Qi-shun

    2006-01-01

    A dispute about the existence of an additional time (named as the Goos-H(a)nchen time) associated with the Goos-H(a)nchen shift in total reflection has recently arisen.At the same time,an inconsistency between the optical ray model and the electromagnetic theory also appears in the optical planar waveguide.By analyzing light propagation in an optical planar waveguide with both the zigzag-ray model and the electromagnetic theory,this paper shows that the Goos-H(a)nchen time really exists,and the total time delay upon total reflection upon an ideal nonabsorbing plasma mirror is the sum of the group-delay time and the Goos-H(a)nchen time.The causality paradox of total reflection of a TM wave upon an ideal nonabsorbing plasma mirror is also solved taking into consideration the negative Goos-H(a)nchen shift.Finally,the expression of the group velocity of the guided mode in optical planar waveguide was obtained,which clearly shows that the time delay upon total reflection is the sum of the group-delay time and the Goos-H(a)nchen time at given any time.

  12. Applying Causal Discovery to the Output of Climate Models - What Can We Learn from the Causal Signatures?

    Science.gov (United States)

    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.

  13. Time reordered: Causal perception guides the interpretation of temporal order.

    Science.gov (United States)

    Bechlivanidis, Christos; Lagnado, David A

    2016-01-01

    We present a novel temporal illusion in which the perceived order of events is dictated by their perceived causal relationship. Participants view a simple Michotte-style launching sequence featuring 3 objects, in which one object starts moving before its presumed cause. Not only did participants re-order the events in a causally consistent way, thus violating the objective temporal order, but they also failed to recognise the clip they had seen, preferring a clip in which temporal and causal order matched. We show that the effect is not due to lack of attention to the presented events and we discuss the problem of determining whether causality affects temporal order at an early perceptual stage or whether it distorts an accurately perceived order during retrieval. Alternatively, we propose a mechanism by which temporal order is neither misperceived nor misremembered but inferred "on-demand" given phenomenal causality and the temporal priority principle, the assumption that causes precede their effects. Finally, we discuss how, contrary to theories of causal perception, impressions of causality can be generated from dynamic sequences with strong spatiotemporal deviations. PMID:26402648

  14. Causality between Prices and Wages: VECM Analysis for EU-27

    Directory of Open Access Journals (Sweden)

    Adriatik Hoxha

    2010-09-01

    Full Text Available The literature on causality as well as the empirical evidence clearly shows that there are two opposing groups of economists, who support different hypotheses with respect to the flow of causality in the price-wage causal relationship. The first group argues that causality runs from wages to prices, whereas the second argues that effect flows from prices to wages. Nonetheless, the literature review suggeststhat there is at least some consensus in that researcher’s conclusions may be contingent on the type of data employed, applied econometric model, or even that relationship may alter with economic cycles. This paper empirically examines theprice-wage causal relationship in EU-27, by using the OLS and VECM analysis, and it also provides robust evidence in support of a bilateral causal relationship between prices and wages, both in long-run as well as in the shortrun.Prior to designing and estimating the econometric model we have performed stationarity tests for the employed price, wage and productivity variables. Additionally, we have also specified the model taking into account the lag order as well as the rank of co-integration for the co-integrated variables. Furthermore, we have also applied respective restrictions on the parameters of estimatedVECM. The evidence resulting from model robustness checks indicates that results are statistically robust. Although far from closing the issue of causality between prices and wages, this paper at least provides some fresh evidence in the case of EU-27.

  15. Spacetime Causal Structure and Dimension from Horismotic Relation

    Directory of Open Access Journals (Sweden)

    O. C. Stoica

    2016-01-01

    Full Text Available A reflexive relation on a set can be a starting point in defining the causal structure of a spacetime in General Relativity and other relativistic theories of gravity. If we identify this relation as the relation between lightlike separated events (the horismos relation, we can construct in a natural way the entire causal structure: causal and chronological relations, causal curves, and a topology. By imposing a simple additional condition, the structure gains a definite number of dimensions. This construction works with both continuous and discrete spacetimes. The dimensionality is obtained also in the discrete case, so this approach can be suited to prove the fundamental conjecture of causal sets. Other simple conditions lead to a differentiable manifold with a conformal structure (the metric up to a scaling factor as in Lorentzian manifolds. This structure provides a simple and general reconstruction of the spacetime in relativistic theories of gravity, which normally requires topological structure, differential structure, and geometric structure (which decomposes in the conformal structure, giving the causal relations and the volume element. Motivations for such a reconstruction come from relativistic theories of gravity, where the conformal structure is important, from the problem of singularities, and from Quantum Gravity, where various discretization methods are pursued, particularly in the causal sets approach.

  16. Causality between Prices and Wages: VECM Analysis for EU-12

    Directory of Open Access Journals (Sweden)

    Adriatik HOXHA

    2010-05-01

    Full Text Available The literature on causality as well as the empirical evidence clearly shows that there are two opposing groups of economists, who support different hypotheses with respect to the flow of causality in the price-wage causal relationship. The first group argues that causality runs from wages to price, whereas the second argue that effect flows from prices to wages. Nonetheless, there is at least some consensus that researchers conclusions may be contingent on the type of data employed, applied econometric model, or even that the relationship may vary through economic cycles. This paper empirically examines the pricewage causal relationship in EMU, by using OLS and VECM analysis, and also it provides robust evidence in support of a bilateral causal relationship between prices and wages, both in long-run as well as in the short-run. Prior to designing and estimating the econometric model we have performed stationarity tests for the employed price, wage and productivity variables. Additionally, we have also specified the model taking into account the lag order as well as the rank of co-integration for the co-integrated variables. Furthermore, we have also applied respective restrictions on the parameters of the estimated VECM and finally model robustness checks indicate that results are statistically robust. Although far from closing the issue of causality between prices and variables, this paper at least provides some fresh evidence for the case of EMU.

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

    Directory of Open Access Journals (Sweden)

    Glenn N Saxe

    Full Text Available 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.

  18. The Importance of Discovery in Children's Causal Learning from Interventions.

    Science.gov (United States)

    Sobel, David M; Sommerville, Jessica A

    2010-01-01

    Four-year-olds were more accurate at learning causal structures from their own actions when they were allowed to act first and then observe an experimenter act, as opposed to observing first and then acting on the environment. Children who discovered the causal efficacy of events (as opposed to confirming the efficacy of events that they observed another discover) were also more accurate than children who only observed the experimenter act on the environment; accuracy in the confirmation and observation conditions was at similar levels. These data suggest that while children learn from acting on the environment, not all self-generated action produces equivalent causal learning.

  19. Kernel canonical-correlation Granger causality for multiple time series

    Science.gov (United States)

    Wu, Guorong; Duan, Xujun; Liao, Wei; Gao, Qing; Chen, Huafu

    2011-04-01

    Canonical-correlation analysis as a multivariate statistical technique has been applied to multivariate Granger causality analysis to infer information flow in complex systems. It shows unique appeal and great superiority over the traditional vector autoregressive method, due to the simplified procedure that detects causal interaction between multiple time series, and the avoidance of potential model estimation problems. However, it is limited to the linear case. Here, we extend the framework of canonical correlation to include the estimation of multivariate nonlinear Granger causality for drawing inference about directed interaction. Its feasibility and effectiveness are verified on simulated data.

  20. Causality and prediction: differences and points of contact

    Directory of Open Access Journals (Sweden)

    Luis Carlos Silva Ayçaguer, PhD

    2014-09-01

    Full Text Available This contribution presents the differences between those variables that might play a causal role in a certain process and those only valuable for predicting the outcome. Some considerations are made about the core intervention of the association and the temporal precedence and biases in both cases, the study of causality and predictive modeling. In that context, several relevant aspects related to the design of the corresponding studies are briefly reviewed and some of the mistakes that are often committed in handling both, causality and prediction, are illustrated.

  1. Stock Market and Economic Growth in Malaysia: Causality Test

    OpenAIRE

    Har Wai Mun; Ee Chun Siong; Tan Chai Thing

    2009-01-01

    Stock market has been associated with economic growth through its role as source for new private capital.  On the other hand, economic growth may be the catalyst for stock market growth. Thus, the purpose of this paper was to explore causal relationships between stock market and the economy using formal tests of causality developed by C. J. Granger and yearly Malaysia data for the period 1977-2006. Results show that stock market Granger-caused economic activity with no reverse causality obser...

  2. Spatial Causality. An application to the Deforestation Process in Bolivia

    Directory of Open Access Journals (Sweden)

    Javier Aliaga

    2011-01-01

    Full Text Available This paper analyses the causes of deforestation for a representative set of Bolivian municipalities. The literature on environmental economics insists on the importance of physical and social factors. We focus on the last group of variables. Our objective is to identify causal mechanisms between these factors of risk and the problem of deforestation. To this end, we present a testing strategy for spatial causality, based on a sequence of Lagrange Multipliers. The results that we obtain for the Bolivian case confirm only partially the traditional view of the problem of deforestation. Indeed, we only find unequivocal signs of causality in relation to the structure of property rights.

  3. An Evaluation of Active Learning Causal Discovery Methods for Reverse-Engineering Local Causal Pathways of Gene Regulation.

    Science.gov (United States)

    Ma, Sisi; Kemmeren, Patrick; Aliferis, Constantin F; Statnikov, Alexander

    2016-01-01

    Reverse-engineering of causal pathways that implicate diseases and vital cellular functions is a fundamental problem in biomedicine. Discovery of the local causal pathway of a target variable (that consists of its direct causes and direct effects) is essential for effective intervention and can facilitate accurate diagnosis and prognosis. Recent research has provided several active learning methods that can leverage passively observed high-throughput data to draft causal pathways and then refine the inferred relations with a limited number of experiments. The current study provides a comprehensive evaluation of the performance of active learning methods for local causal pathway discovery in real biological data. Specifically, 54 active learning methods/variants from 3 families of algorithms were applied for local causal pathways reconstruction of gene regulation for 5 transcription factors in S. cerevisiae. Four aspects of the methods' performance were assessed, including adjacency discovery quality, edge orientation accuracy, complete pathway discovery quality, and experimental cost. The results of this study show that some methods provide significant performance benefits over others and therefore should be routinely used for local causal pathway discovery tasks. This study also demonstrates the feasibility of local causal pathway reconstruction in real biological systems with significant quality and low experimental cost.

  4. Dynamic Interactions in Artificial Environments: Causal and Non-Causal Aspects for the Emergence of Meaning

    Directory of Open Access Journals (Sweden)

    Argyris Arnellos

    2005-02-01

    Full Text Available Initially, the analysis and development of adaptive artificial systems has been based in metaphors taken from philosophical schools as well as the disciplines of biology and cognitive science. So far, the dominant approaches exhibit many advantages in specific domains of application but there all have a certain drawback, which is their inability to produce an artificial system which will be able to internally ground its representations so as to use them to produce newer, more developed ones. The respective frameworks are studied in terms of this inability and it is concluded that the problem is traced in the purely causal treatment, function and creation of the notion of representation, wherever it is used. In the case of purely dynamic systems, where the representations seem not to be very useful, it is proposed that the incorporation of a special non-causal kind of representations would give a framework which seems promising in realizing real adaptation. The relevant architecture is analyzed and discussed mainly in terms of its functionality and its contribution to the integration of pragmatic meaning aspects in an artificial system's interaction.

  5. On Storks and Babies: Correlation, Causality and Field Experiments

    Directory of Open Access Journals (Sweden)

    Lambrecht Anja

    2016-11-01

    Full Text Available The explosion of available data has created much excitement among marketing practitioners about their ability to better understand the impact of marketing investments. Big data allows for detecting patterns and often it seems plausible to interpret them as causal. While it is quite obvious that storks do not bring babies, marketing relationships are usually less clear. Apparent “causalities” often fail to hold up under examination. If marketers want to be sure not to walk into a causality trap, they need to conduct field experiments to detect true causal relationships. In the present digital environment, experiments are easier than ever to execute. However, they need to be prepared and interpreted with great care in order to deliver meaningful and genuinely causal results that help improve marketing decisions.

  6. Environment - Assisted Invariance, Causality, and Probabilities in Quantum Physics

    OpenAIRE

    Zurek, W. H.

    2002-01-01

    I introduce environment - assisted invariance -- a symmetry related to causality that is exhibited by correlated quantum states -- and describe how it can be used to understand the nature of ignorance and, hence, the origin of probabilities in quantum physics.

  7. Learning Why Things Change: The Difference-Based Causality Learner

    CERN Document Server

    Voortman, Mark; Druzdzel, Marek J

    2012-01-01

    In this paper, we present the Difference- Based Causality Learner (DBCL), an algorithm for learning a class of discrete-time dynamic models that represents all causation across time by means of difference equations driving change in a system. We motivate this representation with real-world mechanical systems and prove DBCL's correctness for learning structure from time series data, an endeavour that is complicated by the existence of latent derivatives that have to be detected. We also prove that, under common assumptions for causal discovery, DBCL will identify the presence or absence of feedback loops, making the model more useful for predicting the effects of manipulating variables when the system is in equilibrium. We argue analytically and show empirically the advantages of DBCL over vector autoregression (VAR) and Granger causality models as well as modified forms of Bayesian and constraintbased structure discovery algorithms. Finally, we show that our algorithm can discover causal directions of alpha r...

  8. Holographic entanglement and causal information in coherent states

    International Nuclear Information System (INIS)

    Scalar solitons in global AdS4 are holographically dual to coherent states carrying a non-trivial condensate of a scalar operator. We study the holographic information content of these states, focusing on a particular spatial region, by examining the entanglement entropy and causal holographic information. We show generically that whenever the dimension of the condensed operator is sufficiently low (characterized by the double-trace operator becoming relevant), such coherent states have lower entanglement and causal holographic information than the vacuum state of the system, despite having greater energy. We also use these geometries to illustrate the fact that causal wedges associated with a simply-connected boundary region can have non-trivial topology even in causally trivial spacetimes

  9. Cosmic Acceleration from Causal Backreaction with Recursive Nonlinearities

    CERN Document Server

    Bochner, Brett

    2013-01-01

    We revisit the causal backreaction paradigm, in which the need for Dark Energy is eliminated via the generation of an apparent cosmic acceleration from the causal flow of inhomogeneity information coming in towards each observer from distant structure-forming regions. This second-generation formalism incorporates "recursive nonlinearities": the process by which already-established metric perturbations will then act to slow down all future flows of inhomogeneity information. Here, the long-range effects of causal backreaction are now damped, weakening its impact for models that were previously best-fit cosmologies. Nevertheless, we find that causal backreaction can be recovered as a replacement for Dark Energy via the adoption of larger values for the dimensionless `strength' of the clustering evolution functions being modeled -- a change justified by the hierarchical nature of clustering and virialization in the universe, occurring on multiple cosmic length scales simultaneously. With this, and with one new m...

  10. Causal association rule mining methods based on fuzzy state description

    Institute of Scientific and Technical Information of China (English)

    Liang Kaijian; Liang Quan; Yang Bingru

    2006-01-01

    Aiming at the research that using more new knowledge to develope knowledge system with dynamic accordance, and under the background of using Fuzzy language field and Fuzzy language values structure as description framework, the generalized cell Automation that can synthetically process fuzzy indeterminacy and random indeterminacy and generalized inductive logic causal model is brought forward. On this basis, a kind of the new method that can discover causal association rules is provded. According to the causal information of standard sample space and commonly sample space,through constructing its state (abnormality) relation matrix, causal association rules can be gained by using inductive reasoning mechanism. The estimate of this algorithm complexity is given,and its validity is proved through case.

  11. Management’s causal reasoning on performance and earnings management

    NARCIS (Netherlands)

    Aerts, W.A.A.; Zhang, S.

    2014-01-01

    We investigate the association between the intensity of causal reasoning on performance in a firm’s annual management commentary and its earnings management propensity. Anticipated earnings management concerns are argued to constitute a significant accountability predicament, bringing management to

  12. On the causal structure between CO2 and global temperature.

    Science.gov (United States)

    Stips, Adolf; Macias, Diego; Coughlan, Clare; Garcia-Gorriz, Elisa; Liang, X San

    2016-01-01

    We use a newly developed technique that is based on the information flow concept to investigate the causal structure between the global radiative forcing and the annual global mean surface temperature anomalies (GMTA) since 1850. Our study unambiguously shows one-way causality between the total Greenhouse Gases and GMTA. Specifically, it is confirmed that the former, especially CO2, are the main causal drivers of the recent warming. A significant but smaller information flow comes from aerosol direct and indirect forcing, and on short time periods, volcanic forcings. In contrast the causality contribution from natural forcings (solar irradiance and volcanic forcing) to the long term trend is not significant. The spatial explicit analysis reveals that the anthropogenic forcing fingerprint is significantly regionally varying in both hemispheres. On paleoclimate time scales, however, the cause-effect direction is reversed: temperature changes cause subsequent CO2/CH4 changes. PMID:26900086

  13. Obesity as a causal risk factor for deep venous thrombosis

    DEFF Research Database (Denmark)

    Klovaite, Jolanta; Benn, M; Nordestgaard, B G

    2015-01-01

    OBJECTIVE: To test the hypothesis that obesity is causally associated with deep venous thrombosis (DVT). DESIGN: A Mendelian randomization design. SETTING: The Copenhagen General Population Study and the Copenhagen City Heart Study combined. SUBJECTS: Body mass index (BMI) measurements were...

  14. Replicating the benefits of closed timelike curves without breaking causality

    CERN Document Server

    Yuan, Xiao; Thompson, Jayne; Haw, Jing Yan; Vedral, Vlatko; Ralph, Timothy C; Lam, Ping Koy; Weedbrook, Christian; Gu, Mile

    2014-01-01

    In general relativity, closed timelike curves can break causality with remarkable and unsettling consequences. At the classical level, they induce causal paradoxes disturbing enough to motivate conjectures that explicitly prevent their existence. At the quantum level, resolving such paradoxes induce radical benefits - from cloning unknown quantum states to solving problems intractable to quantum computers. Instinctively, one expects these benefits to vanish if causality is respected. Here we show that in harnessing entanglement, we can efficiently solve NP-complete problems and clone arbitrary quantum states - even when all time-travelling systems are completely isolated from the past. Thus, the many defining benefits of closed timelike curves can still be harnessed, even when causality is preserved. Our results unveil the subtle interplay between entanglement and general relativity, and significantly improve the potential of probing the radical effects that may exist at the interface between relativity and q...

  15. Eventos Quânticos e Reducionismo Causal

    Directory of Open Access Journals (Sweden)

    Osvaldo Pessoa Jr.

    2013-12-01

    Full Text Available This paper is the first step in an investigation of whether microscopic events can be reduced to a mereological composition of elementary events, especially in biological systems. The hypothesis is made that, between events in which quanta are exchanged, there is causal flow, but strictly speaking no events take place. A causal event is characterized by the possibility of an intervention or manipulation. Thus, three types of quantum mechanical events may be found: (1 detection of a quantum of energy; (2 confinement by an apparatus in a Glauber coherent state; (3 null result measurement (without exchange of quanta. The paper explores these three types of elementary causal events, e sets forth as the next step the investigation of the causal events involved in the action of a molecular motor.

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

    Science.gov (United States)

    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

  17. On directed information theory and Granger causality graphs.

    Science.gov (United States)

    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.

  18. The role of causal links in performance measurement models

    OpenAIRE

    Kasperskaya, Yulia; Tayles, Michael

    2013-01-01

    Abstract Purpose: Several well-known managerial accounting performance measurement models rely on causal assumptions. Whilst users of the models express satisfaction and link them with improved organizational performance, academic research, of the realworld applications, shows few reliable statistical associations. This paper provides a discussion on the"problematic" of causality in a performance measurement setting. Design/methodology/approach: This is a conceptual study based on an analysis...

  19. The causal effect of teen motherhood on worklessness

    OpenAIRE

    WALKER, Ian; Zhu, Yu

    2009-01-01

    Teen motherhood continues to be high in the US and the UK relative to most other western European countries. While recent research has clarified how effective policies to reduce teen motherhood might be (Kearney (2009)), there remains little evidence that quantifies the causal effects of teen motherhood on such mothers and their first born children. This paper provides estimates of the causal effect of teen motherhood on worklessness and does so by exploiting the availability of two sources o...

  20. Causality between Electricity Consumption & Economic growth : Empirical Evidence from India

    OpenAIRE

    Gupta, Geetu; Sahu, Naresh Chandra

    2009-01-01

    In this study ,an attempt has been made to investigate causality between electricity consumption and economic growth in India by adopting Granger Engel causality model for 1960-2006 period .Test results shows that electricity consumption has positive effect on economic growth. The paper support for the reforms in power sector and indicates that electricity act as a catalyst in realizing various social and economic goals.

  1. The role of activity in visual impressions of causality.

    Science.gov (United States)

    White, Peter A

    2006-01-01

    Phenomenal causality is an illusion built on an incomplete perception. It is an illusion because we can have visual impressions of causality when no interaction between objects is actually taking place. It is an illusion built on an incomplete perception because causality as we understand it neglects some factors involved in objective descriptions of interactions between objects in terms of the laws of mechanics. So, why don't we perceive object interactions in accordance with the laws of mechanics? I first consider what kinds of things can and cannot be causes perceptually, arguing that active objects can be causes and non-moving objects cannot be. Then, I argue that causal understanding originates with what we have the most direct experience of, our own actions on objects, and extends out from this point of origin to other domains of causality by a form of schema matching the interpretation of stimulus input by matching to abstracted stored representations of experiences. Schema matching raises the possibility of many more kinds of phenomenal causality than have hitherto been considered, and I conclude by suggesting some possibilities.

  2. Causal quantum theory and the collapse locality loophole

    International Nuclear Information System (INIS)

    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 ≅0.1 light seconds

  3. Human Papilloma Viruses and Breast Cancer – Assessment of Causality

    Science.gov (United States)

    Lawson, James Sutherland; Glenn, Wendy K.; Whitaker, Noel James

    2016-01-01

    High risk human papilloma viruses (HPVs) may have a causal role in some breast cancers. Case–control studies, conducted in many different countries, consistently indicate that HPVs are more frequently present in breast cancers as compared to benign breast and normal breast controls (odds ratio 4.02). The assessment of causality of HPVs in breast cancer is difficult because (i) the HPV viral load is extremely low, (ii) HPV infections are common but HPV associated breast cancers are uncommon, and (iii) HPV infections may precede the development of breast and other cancers by years or even decades. Further, HPV oncogenesis can be indirect. Despite these difficulties, the emergence of new evidence has made the assessment of HPV causality, in breast cancer, a practical proposition. With one exception, the evidence meets all the conventional criteria for a causal role of HPVs in breast cancer. The exception is “specificity.” HPVs are ubiquitous, which is the exact opposite of specificity. An additional reservation is that the prevalence of breast cancer is not increased in immunocompromised patients as is the case with respect to HPV-associated cervical cancer. This indicates that HPVs may have an indirect causal influence in breast cancer. Based on the overall evidence, high-risk HPVs may have a causal role in some breast cancers. PMID:27747193

  4. Another(’s perspective on subjectivity in causal connectives: a usage-based analysis of volitional causal relations

    Directory of Open Access Journals (Sweden)

    Ninke Stukker

    2009-06-01

    Full Text Available Dans une hypothèse de catégorisation linguistique, les connecteurs de cause sont pris comme des outils de catégorisation. En effet, des études sur corpus suggèrent que les connecteurs sont fortement spécialisés dans une seule catégorie de causalité spécifique, mais aussi que leur usage n'est pas limité aux catégories de causalité auxquelles ils sont prototypiquement associés. Si nous supposons que le sens des connecteurs causaux peut être adéquatement décrit en référence à des catégories conceptuelles bien définies, comment pouvons-nous expliquer qu’il y ait une variation dans leur usage réel? Nous mettons l'accent sur les relations de cohérence causale volitionnelle, qui constituent le contexte d'usage prototypique du connecteur néerlandais daarom ‘c'est pourquoi’. Un autre moyen d’expression des relations causales volitionnelles est le recours au connecteur dus ‘alors/donc’ qui est prototypiquement utilisé dans les relations de causalité épistémique. Notre hypothèse est que les relations de causalité volitionnelle exprimées par daarom vs dus diffèrent systématiquement en termes de subjectivité. Nous proposons un modèle d'analyse qui contient de multiples opérationnalisation de la notion de subjectivité et une distinction entre différents niveaux de complexité (sous-clause, clause, et discours. Nous constatons que les relations causales volitionnelles en dus contiennent plus souvent des éléments subjectifs que les relations causales volitionnelles en daarom. Nous interprétons cette distribution au sein d'un cadre théorique fondé sur l'usage (usage-based framework, et nous proposons d'analyser les cas volitionnels de dus comme des instanciations non-prototypiques du sens de dus,qui est donc intrinsèquement subjectif et prototypiquement épistémique.Under a linguistic categorization hypothesis causal connectives are taken as categorization devices. Indeed, corpus studies suggest that

  5. General solutions and causality for a Voigt medium

    Energy Technology Data Exchange (ETDEWEB)

    Duren, R.E.; Heestand, R.L. [Exxon Production Co., Houston, TX (United States)

    1995-01-01

    A 1-D wave equation solution for a propagating seismic pulse in a Voigt medium can be obtained by using a separation of variables to find time harmonic particular solutions and then superimposing the particular solutions. This superposition is a time convolution of the boundary condition (or incident pulse) and the medium`s impulse response. Even though causality is not introduced during the solution of the wave equation, the general solution is causal since the boundary condition is causal and the medium`s impulse response can be shown to be causal. The relationship between attenuation and phase velocity as well as their dependence on frequency arise from the form chosen for the particular solutions. The arbitrary constants associated with the particular solutions are determined by the boundary condition, and the initial condition is also dependent on the boundary condition; however, the initial condition is properly determined and does not depend on times after the initial time (thereby satisfying causality). The convolutional nature of the general solution allows it to also be expressed as a time convolution of the boundary conditions`s time derivative and the medium`s step function response. This expression can be viewed as a superposition of step function responses where the step function response is a particular solution to the wave equation obtained using an approach that is similar to one recently developed for propagating electric pulses. This new solution is obtained with the initial and boundary conditions being independently introduced during the solution of the wave equation. There is no frequency dependence in this solution, and the general solution is causal since it is a superposition of causal step function responses.

  6. UMA TEORÍA CAUSAL PARA LOS CASOS FREGE

    Directory of Open Access Journals (Sweden)

    ABEL WAJNERMAN PAZ

    2015-06-01

    Full Text Available Fodor ha argumentado a favor de un par de tesis que pueden caracterizarse como constituyendo un dilema: Por un lado, si adoptamos una teoría funcional para los conceptos explicamos semánticamente los casos Frege pero caemos en el holismo semántico. Por otro lado, si adoptamos una teoría causal/informacional evitamos el holismo pero no explicamos los casos Frege semánticamente. Fodor (por ej, 1994, 1998 y 2008 intenta evitar la segunda parte del dilema argumentando que los casos de Frege pueden tener una explicación sintáctica y no semántica. En este trabajo intentaré ofrecer una salida alternativa al dilema fodoriano. Propondré una explicación semántica de los casos Frege que incorpora tanto elementos de una teoría causal como de una de rol funcional. Afirmaré que el contenido cognitivo o estrecho de un concepto (el tipo de contenido aparentemente exigido por los casos Frege es el conjunto de contenidos causales/informacionales de las representaciones que figuran en su rol funcional. Considero que individuar a las representaciones en los roles por medio de sus contenidos causales permite evitar el holismo (evitando el proceso de ramsificación típicamente empleado para individuar a los roles y que identificar el contenido cognitivo con contenidos causales/informacionales de las representaciones en los roles permite evitar el referencialismo de las propuestas causales (podemos distinguir sentido de referencia en términos causales.

  7. Opening the Black Box and Searching for Smoking Guns: Process Causality in Qualitative Research

    Science.gov (United States)

    Bennett, Elisabeth E.; McWhorter, Rochell R.

    2016-01-01

    Purpose: The purpose of this paper is to explore the role of qualitative research in causality, with particular emphasis on process causality. In one paper, it is not possible to discuss all the issues of causality, but the aim is to provide useful ways of thinking about causality and qualitative research. Specifically, a brief overview of the…

  8. The Shared Causal Pasts and Futures of Cosmological Events

    CERN Document Server

    Friedman, Andrew S; Gallicchio, Jason

    2013-01-01

    We derive criteria for whether two cosmological events can have a shared causal past or a shared causal future, assuming a Friedmann-Lemaitre-Robertson-Walker universe with best-fit \\Lambda CDM cosmological parameters from the Planck satellite. We further derive criteria for whether either cosmic event could have been in past causal contact with our own worldline since the time of the hot "big bang", which we take to be the end of early-universe inflation. We find that pairs of objects such as quasars on opposite sides of the sky with redshifts z >= 3.65 have no shared causal past with each other or with our past worldline. More complicated constraints apply if the objects are at different redshifts from each other or appear at some relative angle less than 180 degrees, as seen from Earth. We present examples of observed quasar pairs that satisfy all, some, or none of the criteria for past causal independence. Given dark energy and the recent accelerated expansion, our observable universe has a finite conform...

  9. Corporate Governance and Financial Performance Nexus: Any Bidirectional Causality?

    Directory of Open Access Journals (Sweden)

    Alley Ibrahim S.

    2016-06-01

    Full Text Available Most studies on corporate governance recognize endogeneity in the nexus between corporate governance and financial performance. Little attention has, however, been paid to the direction of causality between the two phenomena, and hence the Vector Error Correction (VEC model, which allows for endogenous determination of the direction of causality, has not been widely employed. This study fills that gap by estimating the nexus and the direction of causality using the VEC model to analyze panel data on selected listed firms in Nigeria. The results agree with the findings of most previous studies that corporate governance significantly affects financial performance. Board skills, board composition and management skills enhanced financial performance indicators – return on equity (ROE, return on asset (ROA and net profit margin (NPM; in many occasions, significantly. Board size and audit committee size did not, and can actually undermine financial performance. More importantly, financial performance did not significantly affect corporate governance. On the basis of the lag structure of the VEC model, this study affirms unidirectional causality in the nexus, running from corporate governance to financial performance, nullifying the hypothesis of bidirectional causality in the nexus.

  10. Causality between public policies and exports of renewable energy technologies

    International Nuclear Information System (INIS)

    This article investigates the causal relationship between public policies and exports of renewable energy technologies using panel data from 18 countries for the period 1991–2007. A number of panel unit root and cointegration tests are applied. Time series data on public policies and exports are integrated and cointegrated. The dynamic OLS results indicate that in the long run, a 1% increase in government R and D expenditures (RAD) increases exports (EX) by 0.819%. EX and RAD variables respond to deviations from the long-run equilibrium in the previous period. Additionally, the Blundell–Bond system generalized methods of moments (GMM) is employed to conduct a panel causality test in a vector error-correction mechanism (VECM) setting. Evidence of a bidirectional and short-run, and strong causal relationship between EX and the contribution of renewable energy to the total energy supply (CRES) is uncovered. CRES has a negative effect on EX, whereas EX has a positive effect on CRES. We suggest some policy implications based on the results of this study. - Highlights: ► We model VECM to test the Granger causality between the policies and the export. ► Technology-push policy has a positive impact on export in the long-run. ► There are the short-run causal relationships between market-pull policy and export

  11. Extraction of Textual Causal Relationships based on Natural Language Processing

    Directory of Open Access Journals (Sweden)

    Sepideh Jamshidi-Nejad

    2015-11-01

    Full Text Available Natural language processing is a highly important subcategory in the wide area of artificial intelligence. Employing appropriate computational algorithms on sophisticated linguistic operations is the aim of natural language processing to extract and create computational theories from languages. In order to achieve this goal, the knowledge of linguists is needed in addition to computer science. In the field of linguistics, the syntactic and semantic relation of words and phrases and the extraction of causation is very significant which the latter is an information retrieval challenge. Recently, there is an increased attention towards the automatic extraction of causation from textual data sets. Although, previous research extracted the casual relations from uninterrupted data sets by using knowledge-based inference technologies and manual coding. Recently, finding comprehensive approaches for detection and extractions of causal arguments is a research area in the field of natural language processing.In this paper, a three-stepped approach is established through which, the position of words with syntax trees is obtained by extracting causation from causal and non-causal sentences of Web text. The arguments of events were extracted according to the dependency tree of phrases implemented by Python packages. Then potential causal relations were extracted by the extraction of specific nodes of the tree. In the final step, a statistical model is introduced for measuring the potential causal relations. Experimental results and evaluations with Recall, Precision and F-measure metrics show the accuracy and efficiency of the suggested model.

  12. The Causal Relationship between Health and Education Expenditures in Malaysia

    Directory of Open Access Journals (Sweden)

    Chor Foon TANG

    2011-08-01

    Full Text Available A major macroeconomic policy in generating economic growth is to encourage investments on human capital such as health and education. This is because both health and education make significant contribution to increasing productivity of the labour force which ultimately exerts a positive effect on raising output levels. A question that arises is whether investments on health and education have a causal relationship and if so, what is the directional causality? The objective of this study is to examine the causal relationship between health and education expenditures in Malaysia. This study covered annual data from 1970 to 2007. Using Granger causality as well as Toda and Yamamoto MWALD causality approaches, this study suggests that education Granger-causes health expenditure in both the short run and long run. The findings of this study implied that the Malaysian society places preference on education expenditure rather than health. This preference is not unexpected as generally, an educated and knowledgeable society precedes a healthy one. Before a society has attained a relatively higher level of education, it is less aware of the importance of health. Thus, expenditure on education should lead expenditure on health.

  13. Quantifying causal emergence shows that macro can beat micro.

    Science.gov (United States)

    Hoel, Erik P; Albantakis, Larissa; Tononi, Giulio

    2013-12-01

    Causal interactions within complex systems can be analyzed at multiple spatial and temporal scales. For example, the brain can be analyzed at the level of neurons, neuronal groups, and areas, over tens, hundreds, or thousands of milliseconds. It is widely assumed that, once a micro level is fixed, macro levels are fixed too, a relation called supervenience. It is also assumed that, although macro descriptions may be convenient, only the micro level is causally complete, because it includes every detail, thus leaving no room for causation at the macro level. However, this assumption can only be evaluated under a proper measure of causation. Here, we use a measure [effective information (EI)] that depends on both the effectiveness of a system's mechanisms and the size of its state space: EI is higher the more the mechanisms constrain the system's possible past and future states. By measuring EI at micro and macro levels in simple systems whose micro mechanisms are fixed, we show that for certain causal architectures EI can peak at a macro level in space and/or time. This happens when coarse-grained macro mechanisms are more effective (more deterministic and/or less degenerate) than the underlying micro mechanisms, to an extent that overcomes the smaller state space. Thus, although the macro level supervenes upon the micro, it can supersede it causally, leading to genuine causal emergence--the gain in EI when moving from a micro to a macro level of analysis.

  14. A Taxonomy of Causality-Based Biological Properties

    CERN Document Server

    Bodei, Chiara; Chiarugi, Davide; Gori, Roberta; 10.4204/EPTCS.19.8

    2010-01-01

    We formally characterize a set of causality-based properties of metabolic networks. This set of properties aims at making precise several notions on the production of metabolites, which are familiar in the biologists' terminology. From a theoretical point of view, biochemical reactions are abstractly represented as causal implications and the produced metabolites as causal consequences of the implication representing the corresponding reaction. The fact that a reactant is produced is represented by means of the chain of reactions that have made it exist. Such representation abstracts away from quantities, stoichiometric and thermodynamic parameters and constitutes the basis for the characterization of our properties. Moreover, we propose an effective method for verifying our properties based on an abstract model of system dynamics. This consists of a new abstract semantics for the system seen as a concurrent network and expressed using the Chemical Ground Form calculus. We illustrate an application of this fr...

  15. Capturing connectivity and causality in complex industrial processes

    CERN Document Server

    Yang, Fan; Shah, Sirish L; Chen, Tongwen

    2014-01-01

    This brief reviews concepts of inter-relationship in modern industrial processes, biological and social systems. Specifically ideas of connectivity and causality within and between elements of a complex system are treated; these ideas are of great importance in analysing and influencing mechanisms, structural properties and their dynamic behaviour, especially for fault diagnosis and hazard analysis. Fault detection and isolation for industrial processes being concerned with root causes and fault propagation, the brief shows that, process connectivity and causality information can be captured in two ways: ·      from process knowledge: structural modeling based on first-principles structural models can be merged with adjacency/reachability matrices or topology models obtained from process flow-sheets described in standard formats; and ·      from process data: cross-correlation analysis, Granger causality and its extensions, frequency domain methods, information-theoretical methods, and Bayesian ne...

  16. The why of things: causality in science, medicine, and life

    CERN Document Server

    Rabins, Peter V.

    2013-01-01

    Why was there a meltdown at the Fukushima power plant? Why do some people get cancer and not others? Why is global warming happening? Why does one person get depressed in the face of life's vicissitudes while another finds resilience? Questions like these -- questions of causality -- form the basis of modern scientific inquiry, posing profound intellectual and methodological challenges for researchers in the physical, natural, biomedical, and social sciences. In this groundbreaking book, noted psychiatrist and author Peter Rabins offers a conceptual framework for analyzing daunting questions of causality. Navigating a lively intellectual voyage between the shoals of strict reductionism and relativism, Rabins maps a three-facet model of causality and applies it to a variety of questions in science, medicine, economics, and more. Throughout this book, Rabins situates his argument within relevant scientific contexts, such as quantum mechanics, cybernetics, chaos theory, and epigenetics. A renowned communicator o...

  17. Causal Space-Times on a Null Lattice

    CERN Document Server

    Schaden, Martin

    2015-01-01

    I investigate a model of quantum gravity based on the first order Hilbert Palatini action with cosmological constant, discretized on a causal null-lattice with SL(2,C) structure group. The description is coordinate invariant and foliates in a causal and physically transparent manner. Lattice variables and observables are constructed. Conditions for a lattice configuration to describe a triangulated causal manifold are derived and encoded by a topological lattice theory. An equivariant BRST-construction is used to partially localize the SL(2,C) structure group of this model to the compact SU(2) of local spatial rotations. The latter in turn is completely localized using the spinors of this formulation. The integration measure of this completely localized model is derived from the SL(2,C)-invariant integration measure and is expressed in terms of SL(2,C)-invariant variables. An invariant regularization of the lattice integration measure that suppresses configurations with small local four-volumes is proposed. N...

  18. Identifiability, stratification and minimum variance estimation of causal effects.

    Science.gov (United States)

    Tong, Xingwei; Zheng, Zhongguo; Geng, Zhi

    2005-10-15

    The weakest sufficient condition for the identifiability of causal effects is the weakly ignorable treatment assignment, which implies that potential responses are independent of treatment assignment in each fine subpopulation stratified by a covariate. In this paper, we expand the independence that holds in fine subpopulations to the case that the independence may also hold in several coarse subpopulations, each of which consists of several fine subpopulations and may have overlaps with other coarse subpopulations. We first show that the identifiability of causal effects occurs if and only if the coarse subpopulations partition the whole population. We then propose a principle, called minimum variance principle, which says that the estimator possessing the minimum variance is preferred, in dealing with the stratification and the estimation of the causal effects. The simulation results with the detail programming and a practical example demonstrate that it is a feasible and reasonable way to achieve our goals. PMID:16149123

  19. Dark matter perturbations and viscosity: a causal approach

    CERN Document Server

    Acquaviva, Giovanni; Pénin, Aurélie

    2016-01-01

    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 analyse 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 non-causal 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 behaviour in $\\Lambda$CDM when $z \\geq 1$. Interestingly, and contrary to intuition, certain sets of parameters lead to an increase of the clustering.

  20. Causal Patch Complementarity: The Inside Story for Old Black Holes

    CERN Document Server

    Ilgin, Irfan

    2013-01-01

    We carefully analyze the causal patches which belong to observers falling into an old black hole. We show that without a distillation-like process, the AMPS paradox cannot challenge complementarity. That is because the two ingredients for the paradox, the interior region and the early Hawking radiation, cannot be space-like separated and both low-energy within any single causal patch. Either the early quanta have Planckian wavelengths, or the interior region is exponentially smaller than the Schwarzschild size. This means that their appearances in the low-energy theory are strictly time-like separated, which nullifies the problem of double entanglement/purity or quantum cloning. This verifies that the AMPS paradox is either only a paradox in the global description like the original information paradox, or a direct consequence of the assumption that a distillation process is feasible without hidden consequences. We discuss possible relations to cosmological causal patches and the possibility to transfer energy...

  1. Predicting the Cosmological Constant from the CausalEntropic Principle

    Energy Technology Data Exchange (ETDEWEB)

    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.

  2. Predicting the Cosmological Constant from the Causal Entropic Principle

    Energy Technology Data Exchange (ETDEWEB)

    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.

  3. Causal Analysis for Performance Modeling of Computer Programs

    Directory of Open Access Journals (Sweden)

    Jan Lemeire

    2007-01-01

    Full Text Available Causal modeling and the accompanying learning algorithms provide useful extensions for in-depth statistical investigation and automation of performance modeling. We enlarged the scope of existing causal structure learning algorithms by using the form-free information-theoretic concept of mutual information and by introducing the complexity criterion for selecting direct relations among equivalent relations. The underlying probability distribution of experimental data is estimated by kernel density estimation. We then reported on the benefits of a dependency analysis and the decompositional capacities of causal models. Useful qualitative models, providing insight into the role of every performance factor, were inferred from experimental data. This paper reports on the results for a LU decomposition algorithm and on the study of the parameter sensitivity of the Kakadu implementation of the JPEG-2000 standard. Next, the analysis was used to search for generic performance characteristics of the applications.

  4. Informational and Causal Architecture of Discrete-Time Renewal Processes

    Directory of Open Access Journals (Sweden)

    Sarah E. Marzen

    2015-07-01

    Full Text Available Renewal processes are broadly used to model stochastic behavior consisting of isolated events separated by periods of quiescence, whose durations are specified by a given probability law. Here, we identify the minimal sufficient statistic for their prediction (the set of causal states, calculate the historical memory capacity required to store those states (statistical complexity, delineate what information is predictable (excess entropy, and decompose the entropy of a single measurement into that shared with the past, future, or both. The causal state equivalence relation defines a new subclass of renewal processes with a finite number of causal states despite having an unbounded interevent count distribution. We use the resulting formulae to analyze the output of the parametrized Simple Nonunifilar Source, generated by a simple two-state hidden Markov model, but with an infinite-state ϵ-machine presentation. All in all, the results lay the groundwork for analyzing more complex processes with infinite statistical complexity and infinite excess entropy.

  5. On the Capacity of Interference Channel with Causal and Non-causal Generalized Feedback at the Cognitive Transmitter

    CERN Document Server

    Mirmohseni, Mahtab; Aref, Mohammad Reza

    2012-01-01

    In this paper, taking into account the effect of link delays, we investigate the capacity region of the Cognitive Interference Channel (C-IFC), where cognition can be obtained from either causal or non-causal generalized feedback. For this purpose, we introduce the Causal Cognitive Interference Channel With Delay (CC-IFC-WD) in which the cognitive user's transmission can depend on $L$ future received symbols as well as the past ones. We show that the CC-IFC-WD model is equivalent to a classical Causal C-IFC (CC-IFC) with link delays. Moreover, CC-IFC-WD extends both genie-aided and causal cognitive radio channels and bridges the gap between them. First, we derive an outer bound on the capacity region for the arbitrary value of $L$ and specialize this general outer bound to the strong interference case. Then, under strong interference conditions, we tighten the outer bound. To derive the achievable rate regions, we concentrate on three special cases: 1) Classical CC-IFC (L=0), 2) CC-IFC without delay (L=1), an...

  6. Timing and causality in the generation of learned eyelid responses

    Directory of Open Access Journals (Sweden)

    Raudel eSánchez-Campusano

    2011-08-01

    Full Text Available The cerebellum-red nucleus-facial motoneuron (Mn pathway has been reported as being involved in the proper timing of classically conditioned eyelid responses. This special type of associative learning serves as a model of event timing for studying the role of the cerebellum in dynamic motor control. Here, we have re-analyzed the firing activities of cerebellar posterior interpositus (IP neurons and orbicularis oculi (OO Mns in alert behaving cats during classical eyeblink conditioning, using a delay paradigm. The aim was to revisit the hypothesis that the IP neurons can be considered a neuronal phase-modulating device supporting OO Mns firing with an emergent timing mechanism and an explicit correlation code during learned eyelid movements. Optimized experimental and computational tools allowed us to determine the different causal relationships (temporal order and correlation code during and between trials. These intra- and inter-trial timing strategies expanding from sub-second range (millisecond timing to longer-lasting ranges (interval timing expanded the functional domain of cerebellar timing beyond motor control. Interestingly, the results supported the above-mentioned hypothesis. The causal inferences were influenced by the precise motor and premotor spike-timing in the cause-effect interval, and, in addition, the timing of the learned responses depended on cerebellar-Mn network causality. Furthermore, the timing of CRs depended upon the probability of simulated causal conditions in the cause-effect interval and not the mere duration of the inter-stimulus interval. In this work, the close relation between timing and causality was verified. It could thus be concluded that the firing activities of IP neurons may be related more to the proper performance of ongoing CRs (i.e., the proper timing as a consequence of the pertinent causality than to their generation and/or initiation.

  7. How difficult is inference of mammalian causal gene regulatory networks?

    Directory of Open Access Journals (Sweden)

    Djordje Djordjevic

    Full Text Available Gene regulatory networks (GRNs play a central role in systems biology, especially in the study of mammalian organ development. One key question remains largely unanswered: Is it possible to infer mammalian causal GRNs using observable gene co-expression patterns alone? We assembled two mouse GRN datasets (embryonic tooth and heart and matching microarray gene expression profiles to systematically investigate the difficulties of mammalian causal GRN inference. The GRNs were assembled based on > 2,000 pieces of experimental genetic perturbation evidence from manually reading > 150 primary research articles. Each piece of perturbation evidence records the qualitative change of the expression of one gene following knock-down or over-expression of another gene. Our data have thorough annotation of tissue types and embryonic stages, as well as the type of regulation (activation, inhibition and no effect, which uniquely allows us to estimate both sensitivity and specificity of the inference of tissue specific causal GRN edges. Using these unprecedented datasets, we found that gene co-expression does not reliably distinguish true positive from false positive interactions, making inference of GRN in mammalian development very difficult. Nonetheless, if we have expression profiling data from genetic or molecular perturbation experiments, such as gene knock-out or signalling stimulation, it is possible to use the set of differentially expressed genes to recover causal regulatory relationships with good sensitivity and specificity. Our result supports the importance of using perturbation experimental data in causal network reconstruction. Furthermore, we showed that causal gene regulatory relationship can be highly cell type or developmental stage specific, suggesting the importance of employing expression profiles from homogeneous cell populations. This study provides essential datasets and empirical evidence to guide the development of new GRN inference

  8. How difficult is inference of mammalian causal gene regulatory networks?

    Science.gov (United States)

    Djordjevic, Djordje; Yang, Andrian; Zadoorian, Armella; Rungrugeecharoen, Kevin; Ho, Joshua W K

    2014-01-01

    Gene regulatory networks (GRNs) play a central role in systems biology, especially in the study of mammalian organ development. One key question remains largely unanswered: Is it possible to infer mammalian causal GRNs using observable gene co-expression patterns alone? We assembled two mouse GRN datasets (embryonic tooth and heart) and matching microarray gene expression profiles to systematically investigate the difficulties of mammalian causal GRN inference. The GRNs were assembled based on > 2,000 pieces of experimental genetic perturbation evidence from manually reading > 150 primary research articles. Each piece of perturbation evidence records the qualitative change of the expression of one gene following knock-down or over-expression of another gene. Our data have thorough annotation of tissue types and embryonic stages, as well as the type of regulation (activation, inhibition and no effect), which uniquely allows us to estimate both sensitivity and specificity of the inference of tissue specific causal GRN edges. Using these unprecedented datasets, we found that gene co-expression does not reliably distinguish true positive from false positive interactions, making inference of GRN in mammalian development very difficult. Nonetheless, if we have expression profiling data from genetic or molecular perturbation experiments, such as gene knock-out or signalling stimulation, it is possible to use the set of differentially expressed genes to recover causal regulatory relationships with good sensitivity and specificity. Our result supports the importance of using perturbation experimental data in causal network reconstruction. Furthermore, we showed that causal gene regulatory relationship can be highly cell type or developmental stage specific, suggesting the importance of employing expression profiles from homogeneous cell populations. This study provides essential datasets and empirical evidence to guide the development of new GRN inference methods for

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

    Science.gov (United States)

    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.

  10. Bayesian detection of causal rare variants under posterior consistency.

    Directory of Open Access Journals (Sweden)

    Faming Liang

    Full Text Available Identification of causal rare variants that are associated with complex traits poses a central challenge on genome-wide association studies. However, most current research focuses only on testing the global association whether the rare variants in a given genomic region are collectively associated with the trait. Although some recent work, e.g., the Bayesian risk index method, have tried to address this problem, it is unclear whether the causal rare variants can be consistently identified by them in the small-n-large-P situation. We develop a new Bayesian method, the so-called Bayesian Rare Variant Detector (BRVD, to tackle this problem. The new method simultaneously addresses two issues: (i (Global association test Are there any of the variants associated with the disease, and (ii (Causal variant detection Which variants, if any, are driving the association. The BRVD ensures the causal rare variants to be consistently identified in the small-n-large-P situation by imposing some appropriate prior distributions on the model and model specific parameters. The numerical results indicate that the BRVD is more powerful for testing the global association than the existing methods, such as the combined multivariate and collapsing test, weighted sum statistic test, RARECOVER, sequence kernel association test, and Bayesian risk index, and also more powerful for identification of causal rare variants than the Bayesian risk index method. The BRVD has also been successfully applied to the Early-Onset Myocardial Infarction (EOMI Exome Sequence Data. It identified a few causal rare variants that have been verified in the literature.

  11. Bayesian detection of causal rare variants under posterior consistency.

    KAUST Repository

    Liang, Faming

    2013-07-26

    Identification of causal rare variants that are associated with complex traits poses a central challenge on genome-wide association studies. However, most current research focuses only on testing the global association whether the rare variants in a given genomic region are collectively associated with the trait. Although some recent work, e.g., the Bayesian risk index method, have tried to address this problem, it is unclear whether the causal rare variants can be consistently identified by them in the small-n-large-P situation. We develop a new Bayesian method, the so-called Bayesian Rare Variant Detector (BRVD), to tackle this problem. The new method simultaneously addresses two issues: (i) (Global association test) Are there any of the variants associated with the disease, and (ii) (Causal variant detection) Which variants, if any, are driving the association. The BRVD ensures the causal rare variants to be consistently identified in the small-n-large-P situation by imposing some appropriate prior distributions on the model and model specific parameters. The numerical results indicate that the BRVD is more powerful for testing the global association than the existing methods, such as the combined multivariate and collapsing test, weighted sum statistic test, RARECOVER, sequence kernel association test, and Bayesian risk index, and also more powerful for identification of causal rare variants than the Bayesian risk index method. The BRVD has also been successfully applied to the Early-Onset Myocardial Infarction (EOMI) Exome Sequence Data. It identified a few causal rare variants that have been verified in the literature.

  12. The discourse of causal explanations in school science

    Science.gov (United States)

    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

  13. Towards a definition of locality in a manifoldlike causal set

    DEFF Research Database (Denmark)

    Glaser, Lisa; Surya, Sumati

    2013-01-01

    It is a common misconception that spacetime discreteness necessarily implies a violation of local Lorentz invariance. In fact, in the causal set approach to quantum gravity, Lorentz invariance follows from the specific implementation of the discreteness hypothesis. However, this comes at the cost...... of locality. In particular, it is difficult to define a "local" region in a manifoldlike causal set, i.e., one that corresponds to an approximately flat spacetime region. Following up on suggestions from previous work, we bridge this lacuna by proposing a definition of locality based on the abundance of m...

  14. Causal relationship between obesity and vitamin D status

    DEFF Research Database (Denmark)

    Vimaleswaran, Karani S; Berry, Diane J; Lu, Chen;

    2013-01-01

    Obesity is associated with vitamin D deficiency, and both are areas of active public health concern. We explored the causality and direction of the relationship between body mass index (BMI) and 25-hydroxyvitamin D [25(OH)D] using genetic markers as instrumental variables (IVs) in bi-directional ......Obesity is associated with vitamin D deficiency, and both are areas of active public health concern. We explored the causality and direction of the relationship between body mass index (BMI) and 25-hydroxyvitamin D [25(OH)D] using genetic markers as instrumental variables (IVs) in bi...

  15. Temporal sequence in observational studies to establish causality

    Directory of Open Access Journals (Sweden)

    Luis Carlos Silva Ayçaguer, PhD

    2014-05-01

    Full Text Available The article includes a brief summary on the scope of the notions of causality and risk and considers some operational difficulties that arise when dealing with problems associated with them. It underscores the vital importance of timing and its link with the most commonly used observational research designs that address causal relationships. The article describes in detail the need to record the order in which the relevant events occur and how to consider this in the analysis. A detailed example of errors that are usually incurred in and their effect is provided.

  16. Causality and Kramers-Kronig relations for waveguides.

    Science.gov (United States)

    Haakestad, Magnus; Skaar, Johannes

    2005-11-28

    Starting from the condition that optical signals propagate causally, we derive Kramers-Kronig relations for waveguides. For hollow waveguides with perfectly conductive walls, the modes propagate causally and Kramers-Kronig relations between the real and imaginary part of the mode indices exist. For dielectric waveguides, there exists a Kramers-Kronig type relation between the real mode index of a guided mode and the imaginary mode indices associated with the evanescent modes. For weakly guiding waveguides, the Kramers-Kronig relations are particularly simple, as the modal dispersion is determined solely from the profile of the corresponding mode field.

  17. Causality relations for materials with strong artificial optical chirality

    CERN Document Server

    Gorkunov, M V; Ezhov, A A; Artemov, V V; Rogov, O Y

    2014-01-01

    We demonstrate that the fundamental causality principle being applied to strongly chiral artificial materials yields the generalized Kramers-Kronig relations for the observables -- circular dichroism and optical activity. The relations include the Blaschke terms determined by material-specific features - the zeros of transmission amplitude on the complex frequency plane. By the example of subwavelength arrays of chiral holes in silver films we show that the causality relations can be used not only for a precise verification of experimental data but also for resolving the positions of material anomalies and resonances and quantifying the degree of their chiral splitting.

  18. Simulation of system models containing zero-order causal paths - I. Classification of zero-order causal paths

    OpenAIRE

    van Dijk; Breedveld, P.C.

    1991-01-01

    The existence of zero-order causal paths in bond graphs of physical systems implies the set of state equations to be an implicit mixed set of Differential and Algebraic Equations (DAEs). In the block diagram expansion of such a bond graph, this type of causal path corresponds with a zero-order loop. In this paper the numerical solution of the DAEs by methods commonly used for solving stiff systems of Ordinary Differential Equations (ODEs) is discussed. Apart from a description of the numerica...

  19. Causal Indicator Models: Unresolved Issues of Construction and Evaluation

    Science.gov (United States)

    West, Stephen G.; Grimm, Kevin J.

    2014-01-01

    These authors agree with Bainter and Bollen that causal effects represents a useful measurement structure in some applications. The structure of the science of the measurement problem should determine the model; the measurement model should not determine the science. They also applaud Bainter and Bollen's important reminder that the full…

  20. What Is the Latent Variable in Causal Indicator Models?

    Science.gov (United States)

    Howell, Roy D.

    2014-01-01

    Building on the work of Bollen (2007) and Bollen & Bauldry (2011), Bainter and Bollen (this issue) clarifies several points of confusion in the literature regarding causal indicator models. This author would certainly agree that the effect indicator (reflective) measurement model is inappropriate for some indicators (such as the social…

  1. Fertility and Female Employment: Problems of Causal Direction.

    Science.gov (United States)

    Cramer, James C.

    1980-01-01

    Considers multicollinearity in nonrecursive models, misspecification of models, discrepancies between attitudes and behavior, and differences between static and dynamic models as explanations for contradictory information on the causal relationship between fertility and female employment. Finds that initially fertility affects employment but that,…

  2. Geometric Time and Causal Time in Relativistic Lagrangian Mechanics

    CERN Document Server

    Brunet, Olivier

    2016-01-01

    In this article, we argue that two distinct types of time should be taken into account in relativistic physics: a geometric time, which emanates from the structure of spacetime and its metrics, and a causal time, indicating the flow from the past to the future. A particularity of causal times is that its values have no intrinsic meaning, as their evolution alone is meaningful. In the context of relativistic Lagrangian mechanics, causal times corresponds to admissible parameterizations of paths, and we show that in order for a langragian to not depend on any particular causal time (as its values have no intrinsic meaning), it has to be homogeneous in its velocity argument. We illustrate this property with the example of a free particle in a potential. Then, using a geometric Lagrangian (i.e. a parameterization independent Lagrangian which is also manifestly covariant), we introduce the notion of ageodesicity of a path which measures to what extent a path is far from being a geodesic, and show how the notion ca...

  3. The Role of Probability and Intentionality in Preschoolers' Causal Generalizations

    Science.gov (United States)

    Sobel, David M.; Sommerville, Jessica A.; Travers, Lea V.; Blumenthal, Emily J.; Stoddard, Emily

    2009-01-01

    Three experiments examined whether preschoolers recognize that the causal properties of objects generalize to new members of the same set given either deterministic or probabilistic data. Experiment 1 found that 3- and 4-year-olds were able to make such a generalization given deterministic data but were at chance when they observed probabilistic…

  4. Causal efficacy and the normative notion of sustainability science

    Directory of Open Access Journals (Sweden)

    Lin-Shu Wang

    2011-10-01

    Full Text Available Sustainability science requires both a descriptive understanding and a normative approach. Modern science, however, began as purely descriptive knowledge, the core of which is that matter is dynamically inert and without purpose. The British philosopher David Hume concluded that the only type of causation in the material world is “efficient causation,” which supported this purposeless view of a deterministic world “governed” by the causal laws of dynamics. But Hume did not argue against the existence of efficacious causation, only the error of humans projecting the mind’s efficacy to objects. Though dynamically inert, a material object away from equilibrium can be thermodynamically reactive, suggesting the possibility of the object being efficaciously managed for a purpose. Furthermore, quantum physics has replaced classical physics as the fundamental theory of the material world. Its basic equation, the Schrödinger wave-equation, is deterministic but causally inert—it cannot govern, leaving the determinism door unlocked. This causal gap, according to the von Neumann-Stapp quantum measurement/activation theory, necessitates the pragmatic existence in an irreversible universe of the causal efficacy of mental effort and information management. The resulting “bigger” empirical science has room for “descriptive determinism” and “normative action,” both of which are utterly essential in formulating sustainability science as an integral discipline.

  5. Emergence of a 4D World from Causal Quantum Gravity

    CERN Document Server

    Ambjørn, Jan; Loll, R

    2004-01-01

    Causal Dynamical Triangulations in four dimensions provide a background-independent definition of the sum over geometries in nonperturbative quantum gravity, with a positive cosmological constant. We present evidence that a macroscopic four-dimensional world emerges from this theory dynamically.

  6. Temperature has a causal effect on avian timing of reproduction

    NARCIS (Netherlands)

    Visser, M.E.; Holleman, L.J.M.; Caro, S.P.

    2009-01-01

    Many bird species reproduce earlier in years with high spring temperatures, but little is known about the causal effect of temperature. Temperature may have a direct effect on timing of reproduction but the correlation may also be indirect, for instance via food phenology. As climate change has led

  7. Emergence of a 4D world from causal quantum gravity

    OpenAIRE

    Ambjørn, J.; Jurkiewicz, J.(Faculty of Physics, Astronomy and Applied Computer Science, Jagiellonian University, ul. prof. Stanislawa Lojasiewicza 11, Krakow, PL 30-348, Poland); Loll, R

    2006-01-01

    Causal Dynamical Triangulations in four dimensions provide a background- independent definition of the sum over geometries in nonperturbative quantum gravity, with a positive cosmological constant. We present evidence that a macro- scopic four-dimensional world emerges from this theory dynamically.

  8. Intimate Partner Violence and Welfare Participation: A Longitudinal Causal Analysis

    Science.gov (United States)

    Cheng, Tyrone C.

    2013-01-01

    This longitudinal study examined the temporal-ordered causal relationship between intimate partner violence (IPV), five mental disorders (depression, generalized anxiety disorder, social phobia, panic attack, posttraumatic stress disorder [PTSD]), alcohol abuse/dependence, drug abuse/ dependence, treatment seeking (from physician, counselor, and…

  9. Remarks on the correspondence of the relativity and causality principles

    OpenAIRE

    Kholmetskii, Alexander L.

    2002-01-01

    A particular problem about special kind of two light pulses propagation has been considered in cases of inertial motion, constant homogeneous gravitation field and progressive non-inertial motion with constant acceleration. A contradiction between the causality principle and relativity theory has been revealed.

  10. Psychology and evolutionary biology; Causal analysis, evidence, and nomothetic laws

    OpenAIRE

    Van Hezewijk, René

    2008-01-01

    Published as a chapter in Van Hezewijk, R. (2003). Psychology and evolutionary biology; Causal analysis, evidence, and nomothetic laws. In N. Stephenson, L. Radtke, R. Jorna & H. J. Stam (Eds.), Theoretical psychology; Critical contributions (pp. 405-415). Concord, Ontario: Captus Press.

  11. Vaccines and autism: evidence does not support a causal association.

    Science.gov (United States)

    DeStefano, F

    2007-12-01

    A suggested association between certain childhood vaccines and autism has been one of the most contentious vaccine safety controversies in recent years. Despite compelling scientific evidence against a causal association, many parents and parent advocacy groups continue to suspect that vaccines, particularly measles-mumps-rubella (MMR) vaccine and thimerosal-containing vaccines (TCVs), can cause autism.

  12. Music and Spatial Task Performance: A Causal Relationship.

    Science.gov (United States)

    Rauscher, Frances H.; And Others

    This research paper reports on testing the hypothesis that music and spatial task performance are causally related. Two complementary studies are presented that replicate and explore previous findings. One study of college students showed that listening to a Mozart sonata induces subsequent short-term spatial reasoning facilitation and tested the…

  13. Clarity and causality needed in claims about Big Gods.

    Science.gov (United States)

    Watts, Joseph; Bulbulia, Joseph; Gray, Russell D; Atkinson, Quentin D

    2016-01-01

    We welcome Norenzayan et al.'s claim that the prosocial effects of beliefs in supernatural agents extend beyond Big Gods. To date, however, supporting evidence has focused on the Abrahamic Big God, making generalisations difficult. We discuss a recent study that highlights the need for clarity about the causal path by which supernatural beliefs affect the evolution of big societies. PMID:26948745

  14. Effects of Perceived Causality on Perceptions of Persons Who Stutter

    Science.gov (United States)

    Boyle, Michael P.; Blood, Gordon W.; Blood, Ingrid M.

    2009-01-01

    This study examined the effects of the perceived cause of stuttering on perceptions of persons who stutter (PWS) using a 7-item social distance scale, a 25-item adjective pair scale and a 2-item visual analogue scale. Two hundred and four university students rated vignettes which varied on describing a PWS with different causalities for stuttering…

  15. The Special Status of Actions in Causal Reasoning in Rats

    Science.gov (United States)

    Leising, Kenneth J.; Wong, Jared; Waldmann, Michael R.; Blaisdell, Aaron P.

    2008-01-01

    A. P. Blaisdell, K. Sawa, K. J. Leising, and M. R. Waldmann (2006) reported evidence for causal reasoning in rats. After learning through Pavlovian observation that Event A (a light) was a common cause of Events X (an auditory stimulus) and F (food), rats predicted F in the test phase when they observed Event X as a cue but not when they generated…

  16. Political Socialization and Mass Media Use: A Reverse Causality Model.

    Science.gov (United States)

    Tan, Alexis S.

    A reverse causality model treating mass media use for public affairs information as a result rather than as a cause of political behavior was tested utilizing surveys of 190 Mexican-American, 176 black, and 225 white adults. The criterion variable used in each sample was frequency of television and newspaper use for public affairs information. The…

  17. Testing Information Causality for General Quantum Communication Protocols

    CERN Document Server

    Yu, I-Ching

    2015-01-01

    Information causality was proposed as a physical principle to put upper bound on the accessible information gain in a physical bi-partite communication scheme. Intuitively, the information gain cannot be larger than the amount of classical communication to avoid violation of causality. Moreover, it was shown that this bound is consistent with the Tsirelson bound for the binary quantum systems. In this paper, we test the information causality for the more general (non-binary) quantum communication schemes. In order to apply the semi-definite programming method to find the maximal information gain, we only consider the schemes in which the information gain is monotonically related to the Bell-type functions, i.e., the generalization of CHSH functions for Bell inequalities in a binary schemes. We determine these Bell-type functions by using the signal decay theorem. Our results support the proposal of information causality. We also find the maximal information gain by numerical brute-force method for the most ge...

  18. Theory of Mind, Causal Attribution and Paranoia in Asperger Syndrome.

    Science.gov (United States)

    Blackshaw, Alison J.; Kinderman, Peter; Hare, Dougal J.; Hatton, Chris

    2001-01-01

    Twenty-five participants (ages 15-40) with Asperger syndrome scored significantly higher on a measure of paranoia and lower on a measure of theory of mind, compared with a control group. They did not differ in self-concept and causal attributions. A regression analysis highlighted private self-consciousness as the only predictor of paranoia.…

  19. What is causal about individual differences? : A comment on Weinberger

    NARCIS (Netherlands)

    D. Borsboom

    2015-01-01

    Weinberger (2015) claims that if a latent variable is a cause, it must be a within-subject cause. In addition, Weinberger suggests that this fact refutes the conclusion of Borsboom, Mellenbergh, and Van Heerden (2003), who stated that standard psychometric models have a causal interpretation that is

  20. Fostering Deeper Critical Inquiry with Causal Layered Analysis

    Science.gov (United States)

    Haigh, Martin

    2016-01-01

    Causal layered analysis (CLA) is a technique that enables deeper critical inquiry through a structured exploration of four layers of causation. CLA's layers reach down from the surface litany of media understanding, through the layer of systemic causes identified by conventional research, to underpinning worldviews, ideologies and philosophies,…

  1. Altered cortical causality after remifentanil administration in healthy volunteers

    DEFF Research Database (Denmark)

    Khodayari-Rostamabad, Ahmad; Graversen, Carina; Olesen, Soren S;

    2014-01-01

    Alterations in cortical causality information flow induced by remifentanil infusion in healthy volunteers was investigated in a placebo-controlled double-blind cross-over study. For each of the 21 enrolled male subjects, 2.5 minutes of resting electroencephalography (EEG) data were collected befo...

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

    Science.gov (United States)

    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. What can causal networks tell us about metabolic pathways?

    Directory of Open Access Journals (Sweden)

    Rachael Hageman Blair

    Full Text Available Graphical models describe the linear correlation structure of data and have been used to establish causal relationships among phenotypes in genetic mapping populations. Data are typically collected at a single point in time. Biological processes on the other hand are often non-linear and display time varying dynamics. The extent to which graphical models can recapitulate the architecture of an underlying biological processes is not well understood. We consider metabolic networks with known stoichiometry to address the fundamental question: "What can causal networks tell us about metabolic pathways?". Using data from an Arabidopsis Bay[Formula: see text]Sha population and simulated data from dynamic models of pathway motifs, we assess our ability to reconstruct metabolic pathways using graphical models. Our results highlight the necessity of non-genetic residual biological variation for reliable inference. Recovery of the ordering within a pathway is possible, but should not be expected. Causal inference is sensitive to subtle patterns in the correlation structure that may be driven by a variety of factors, which may not emphasize the substrate-product relationship. We illustrate the effects of metabolic pathway architecture, epistasis and stochastic variation on correlation structure and graphical model-derived networks. We conclude that graphical models should be interpreted cautiously, especially if the implied causal relationships are to be used in the design of intervention strategies.

  4. The development of causality in the young child

    Science.gov (United States)

    Campbell, Brian David

    The concepts of action and reaction, force and movement, prediction and reason have been central to scientific thinking since the time of Aristotle. It has been argued that the development of causal thinking is pivotal in the evolution of an individual making predictions and creating explanatory theories for phenomena. It follows that an understanding of the development of causal thinking is central to the understanding of scientific thinking. This work explores the development of causal thinking in the young child. Six Piagetian-type tasks were developed to investigate causal explanations and 101 subjects were independently interviewed. The subjects were from a rural Iowa elementary school. The academic grade of the subjects ranged from kindergarten through third. The three research hypotheses tested yielded the following results: (1) Subjects in this study showed a difference in task performance along academic grade levels on four of the tasks but not on two. The results showed that, as grade level increased for four of the six tasks, performance on those tasks tended to improve. (2) The four tasks analyzed with the Chilton modified Guttman Scalogram Analysis did form a unidimensional scale. Two tasks could not be analyzed. (3) Subjects in the study showed no statistically significant difference between gender and performance on the tasks.

  5. Causality: School Libraries and Student Success (CLASS). White Paper

    Science.gov (United States)

    American Association of School Librarians, 2014

    2014-01-01

    On April 11 and 12, 2014, the American Association of School Librarians (AASL) held "Causality: School Libraries and Student Success" (CLASS), an IMLS-funded national forum. Dr. Thomas Cook, one of the most influential methodologists in education research, and a five member panel of expert scholars and practitioners led 50 established…

  6. A Bayesian Nonparametric Causal Model for Regression Discontinuity Designs

    Science.gov (United States)

    Karabatsos, George; Walker, Stephen G.

    2013-01-01

    The regression discontinuity (RD) design (Thistlewaite & Campbell, 1960; Cook, 2008) provides a framework to identify and estimate causal effects from a non-randomized design. Each subject of a RD design is assigned to the treatment (versus assignment to a non-treatment) whenever her/his observed value of the assignment variable equals or…

  7. The TETRAD Project: Constraint Based Aids to Causal Model Specification.

    Science.gov (United States)

    Scheines, Richard; Spirtes, Peter; Glymour, Clark; Meek, Christopher; Richardson, Thomas

    1998-01-01

    The TETRAD for constraint-based aids to causal model specification project and related work in computer science aims to apply standards of rigor and precision to the problem of using data and background knowledge to make inferences about a model's specifications. Several algorithms that are implemented in the TETRAD II program are presented. (SLD)

  8. Affect and Causal Attribution in Marital Conflicts: An Exploratory Study.

    Science.gov (United States)

    White, David M.

    Recent attempts to predict marital success or failure have explored the explanations couples offer for interpersonal events. To investigate whether positive and negative affect would lead to different causal attributions in a conflict-resolution conversation, 20 married couples were asked to observe a conflict-resolution and a control conversation…

  9. Causal Temperature Profiles in Horizon-free Collapse

    Indian Academy of Sciences (India)

    N. F. Naidu; M. Govender

    2007-12-01

    We investigate the causal temperature profiles in a recent model of a radiating star undergoing dissipative gravitational collapse without the formation of a horizon. It is shown that this simple exact model provides physically reasonable behaviour for the temperature profile within the framework of extended irreversible thermodynamics.

  10. Causal discovery via reproducing kernel Hilbert space embeddings.

    Science.gov (United States)

    Chen, Zhitang; Zhang, Kun; Chan, Laiwan; Schölkopf, Bernhard

    2014-07-01

    Causal discovery via the asymmetry between the cause and the effect has proved to be a promising way to infer the causal direction from observations. The basic idea is to assume that the mechanism generating the cause distribution p(x) and that generating the conditional distribution p(y|x) correspond to two independent natural processes and thus p(x) and p(y|x) fulfill some sort of independence condition. However, in many situations, the independence condition does not hold for the anticausal direction; if we consider p(x, y) as generated via p(y)p(x|y), then there are usually some contrived mutual adjustments between p(y) and p(x|y). This kind of asymmetry can be exploited to identify the causal direction. Based on this postulate, in this letter, we define an uncorrelatedness criterion between p(x) and p(y|x) and, based on this uncorrelatedness, show asymmetry between the cause and the effect in terms that a certain complexity metric on p(x) and p(y|x) is less than the complexity metric on p(y) and p(x|y). We propose a Hilbert space embedding-based method EMD (an abbreviation for EMbeDding) to calculate the complexity metric and show that this method preserves the relative magnitude of the complexity metric. Based on the complexity metric, we propose an efficient kernel-based algorithm for causal discovery. The contribution of this letter is threefold. It allows a general transformation from the cause to the effect involving the noise effect and is applicable to both one-dimensional and high-dimensional data. Furthermore it can be used to infer the causal ordering for multiple variables. Extensive experiments on simulated and real-world data are conducted to show the effectiveness of the proposed method. PMID:24708374

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

    Science.gov (United States)

    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

  12. Goal orientations in sport: a causal model Orientaciones de Meta en el deporte: un modelo causal

    Directory of Open Access Journals (Sweden)

    Francisco P. Holgado

    2010-05-01

    Full Text Available The study is based on research work relating goal orientation in sport with contextual variables and personal variables. The sample was 511 professional athletes. A “causal” model is proposed in which task and goal ego orientations are the dependent variables. A hypothetical model is obtained using structural equations modelling, supporting that: a athletes who find satisfaction experimenting mastery, who perceive a motivational climate that rewards hard work and who believe that success depends on their effort, develop task goal orientation; and b athletes who get satisfaction demonstrating greater capacity than the rest, who live a motivational climate that leads them to be better than the others and that only rewards the best players, and whose main motive for practising sport is to achieve certain social status and popularity, will have an ego goal orientation. Este trabajo parte de las investigaciones que relacionan las orientaciones de meta en el deporte con variables contextuales, como el clima motivacional percibido, y con variables personales, tales como la satisfacción con los resultados deportivos, las creencias relacionadas con los factores implicados en la obtención del éxito y los motivos por lo que se practica deporte. La muestra está compuesta por 511 deportistas profesionales. Se llevan a cabo análisis de regresión múltiple y se propone un modelo causal en el que las variables a predecir son las orientaciones de meta, a la tarea y al ego. Con ecuaciones estructurales se contrasta un modelo hipotético, que presenta un ajuste adecuado, y que defiende que: a el deportista que encuentra la satisfacción experimentando maestría, que percibe un clima motivacional que premia el trabajo duro y que cree que el éxito depende de su esfuerzo, desarrolla una orientación de meta a la tarea: y b que el deportista que obtiene satisfacción demostrando mayor capacidad que los demás, que vive un clima motivacional que le conduce a

  13. Concepts of Causality in Psychopathology: Applications in Clinical Assessment, Clinical Case Formulation and Functional Analysis

    NARCIS (Netherlands)

    Haynes, S.H.; O'Brien, W.H.; Kaholokula, J.K.; Witteman, C.L.M.

    2012-01-01

    This paper discusses and integrates concepts of causality in psychopathology, clinical assessment, clinical case formulation and the functional analysis. We propose that identifying causal variables, relations and mechanisms in psychopathology and clinical assessment can lead to more powerful and e

  14. K-causal structure of space-time in general relativity

    Indian Academy of Sciences (India)

    Sujatha Janardhan; R V Saraykar

    2008-04-01

    Using K-causal relation introduced by Sorkin and Woolgar [1], we generalize results of Garcia-Parrado and Senovilla [2,3] on causal maps. We also introduce causality conditions with respect to K-causality which are analogous to those in classical causality theory and prove their inter-relationships. We introduce a new causality condition following the work of Bombelli and Noldus [4] and show that this condition lies in between global hyperbolicity and causal simplicity. This approach is simpler and more general as compared to traditional causal approach [5,6] and it has been used by Penrose et al [7] in giving a new proof of positivity of mass theorem. 0-space-time structures arise in many mathematical and physical situations like conical singularities, discontinuous matter distributions, phenomena of topology-change in quantum field theory etc.

  15. The Causality Relation Between Consumer Confidence and Stock Prices: Case of Turkey

    OpenAIRE

    Topuz, Yusuf Volkan

    2010-01-01

    In this study, the causality relation between consumer confidence and stock price is discussed. This study is based on the assumption of potential bi-directional casuality which is from stock prices towards consumer confidence as there might also be causality from consumer confidence towards stock prices. To this end, in this study the causality relation between consumer confidence index and ISE-100 index during the terms of 2004:01-2009:01 is examined by using Granger Causality test. One-dir...

  16. Global properties of causal wedges in asymptotically AdS spacetimes

    CERN Document Server

    Hubeny, Veronika E; Tonni, Erik

    2013-01-01

    We examine general features of causal wedges in asymptotically AdS spacetimes and show that in a wide variety of cases they have non-trivial topology. We also prove some general results regarding minimal area surfaces on the causal wedge boundary and thereby derive constraints on the causal holographic information. We go on to demonstrate that certain properties of the causal wedge impact significantly on features of extremal surfaces which are relevant for computation of holographic entanglement entropy.

  17. The power of possibility: causal learning, counterfactual reasoning, and pretend play

    OpenAIRE

    Buchsbaum, Daphna; Bridgers, Sophie; Skolnick Weisberg, Deena; Gopnik, Alison

    2012-01-01

    We argue for a theoretical link between the development of an extended period of immaturity in human evolution and the emergence of powerful and wide-ranging causal learning mechanisms, specifically the use of causal models and Bayesian learning. We suggest that exploratory childhood learning, childhood play in particular, and causal cognition are closely connected. We report an empirical study demonstrating one such connection—a link between pretend play and counterfactual causal reasoning. ...

  18. Change, Self-Organization and the Search for Causality in Educational Research and Practice

    Science.gov (United States)

    Koopmans, Matthijs

    2014-01-01

    Causality is an inextricable part of the educational process, as our understanding of what works in education depends on our ability to make causal attributions. Yet, the research and policy literature in education tends to define causality narrowly as the attribution of educational outcomes to intervention effects in a randomized control trial…

  19. Non-Causal Time-Domain Filters for Single-Channel Noise Reduction

    DEFF Research Database (Denmark)

    Jensen, Jesper Rindom; Benesty, Jacob; Christensen, Mads Græsbøll;

    2012-01-01

    suppression and signal distortion by allowing the filters to be non-causal. Non-causal time-domain filters require knowledge of the future, and are therefore not directly implementable. If the observed signal is processed in blocks, however, the non-causal filters are implementable. In this paper, we propose...

  20. Finding the Cause: Verbal Framing Helps Children Extract Causal Evidence Embedded in a Complex Scene

    Science.gov (United States)

    Butler, Lucas P.; Markman, Ellen M.

    2012-01-01

    In making causal inferences, children must both identify a causal problem and selectively attend to meaningful evidence. Four experiments demonstrate that verbally framing an event ("Which animals make Lion laugh?") helps 4-year-olds extract evidence from a complex scene to make accurate causal inferences. Whereas framing was unnecessary when…

  1. Exploring causal networks of bovine milk fatty acids in a multivariate mixed model context

    DEFF Research Database (Denmark)

    Bouwman, Aniek C; Valente, Bruno D; Janss, Luc L G;

    2014-01-01

    are fitted conditionally on a causal structure among traits, represented by a directed acyclic graph and an Inductive Causation (IC) algorithm can be used to search for causal structures. The aim of this study was to explore the space of causal structures involving bovine milk fatty acids and to select...

  2. Causal Mediation in Educational Research: An Illustration Using International Assessment Data

    Science.gov (United States)

    Caro, Daniel H.

    2015-01-01

    This paper applies the causal mediation framework proposed by Kosuke Imai and colleagues (Imai, Keele, & Tingley, 2010) to educational research by examining the causal mediating role of early literacy activities in parental education influences on reading performance. The paper argues that the study of causal mediation is particularly relevant…

  3. Using Propensity Score Analysis for Making Causal Claims in Research Articles

    Science.gov (United States)

    Bai, Haiyan

    2011-01-01

    The central role of the propensity score analysis (PSA) in observational studies is for causal inference; as such, PSA is often used for making causal claims in research articles. However, there are still some issues for researchers to consider when making claims of causality using PSA results. This summary first briefly reviews PSA, followed by…

  4. Causality and Truth [Cauzalitate şi adevăr

    OpenAIRE

    Dinga Emil

    2014-01-01

    The paper aims to discuss the concept of truth in its relation with causality. More exactly, the relation of causality between… causality and truth recognition is exposed and debated. The three types of truth are presented and examined in the light of the paper purpose, commenting on the consequences of the concordance-truth type, as well as crucial questions in knowledge and praxeology.

  5. Causal Reasoning in Economics: A Selective Exploration of Semantic, Epistemic and Dynamical Aspects

    NARCIS (Netherlands)

    F. Claveau (Francois)

    2012-01-01

    textabstractEconomists reason causally. Like many other scientists, they aim at formulating justified causal claims about their object of study. This thesis contributes to our understanding of how causal reasoning proceeds in economics. By using the research on the causes of unemployment as a case s

  6. Automatic Reasoning about Causal Events in Surveillance Video

    Directory of Open Access Journals (Sweden)

    Reid IanD

    2011-01-01

    Full Text Available We present a new method for explaining causal interactions among people in video. The input to the overall system is video in which people are low/medium resolution. We extract and maintain a set of qualitative descriptions of single-person activity using the low-level vision techniques of spatiotemporal action recognition and gaze-direction approximation. This models the input to the "sensors" of the person agent in the scene and is a general sensing strategy for a person agent in a variety of application domains. The information subsequently available to the reasoning process is deliberately limited to model what an agent would actually be able to sense. The reasoning is therefore not a classical "all-knowing" strategy but uses these "sensed" facts obtained from the agents, combined with generic domain knowledge, to generate causal explanations of interactions. We present results from urban surveillance video.

  7. Who caused it? Interpersonal causal inferences in young children.

    Science.gov (United States)

    Vikan, A; Skevik, H

    1992-01-01

    Three experiments were designed to test 4- and 6-year-old children's causal inferences in interpersonal settings where emotions (glad, angry, and sad) were effect responses. The results showed that emotion and orientation (towards or away from) were central cues, and that sex and age also were used to some extent. Cues related to regularity philosophic notions (e.g. David Hume), such as contiguity in time and space, and time order of cause and effect were little used by comparison. The results raise questions about the basic role attributed to regularity cues both by philosophers and psychologists, and suggest a multiple cue contribution rather than a basic cue generalization approach to causal cognition development.

  8. Renormalization group approach to causal bulk viscous cosmological models

    International Nuclear Information System (INIS)

    The renormalization group method is applied to the study of homogeneous and flat Friedmann-Robertson-Walker type universes, filled with a causal bulk viscous cosmological fluid. The starting point of the study is the consideration of the scaling properties of the gravitational field equations, the causal evolution equation of the bulk viscous pressure and the equations of state. The requirement of scale invariance imposes strong constraints on the temporal evolution of the bulk viscosity coefficient, temperature and relaxation time, thus leading to the possibility of obtaining the bulk viscosity coefficient-energy density dependence. For a cosmological model with bulk viscosity coefficient proportional to the Hubble parameter, we perform the analysis of the renormalization group flow around the scale-invariant fixed point, thereby obtaining the long-time behaviour of the scale factor

  9. Regge behavior saves string theory from causality violations

    DEFF Research Database (Denmark)

    di Vecchia, Paolo; Giuseppe, D'Appollonio; Russo, Rodolfo;

    2015-01-01

    Higher-derivative corrections to the Einstein-Hilbert action are present in bosonic string theory leading to the potential causality violations recently pointed out by Camanho et al. [1]. We analyze in detail this question by considering high-energy string-brane collisions at impact parameters b....... Such violations are instead neatly avoided when the full structure of string theory — and in particular its Regge behavior — is taken into account....... ≤ l s (the string-length parameter) with l s ≫ R p (the characteristic scale of the Dp-brane geometry). If we keep only the contribution of the massless states causality is violated for a set of initial states whose polarization is suitably chosen with respect to the impact parameter vector...

  10. Zika Virus Infection and Microcephaly: Evidence for a Causal Link

    Directory of Open Access Journals (Sweden)

    Jin-Na Wang

    2016-10-01

    Full Text Available Zika virus (ZIKV is a flavivirus related to the Dengue, yellow fever and West Nile viruses. Since the explosive outbreaks of ZIKV in Latin America in 2015, a sudden increase in the number of microcephaly cases has been observed in infants of women who were pregnant when they contracted the virus. The severity of this condition raises grave concerns, and extensive studies on the possible link between ZIKV infection and microcephaly have been conducted. There is substantial evidence suggesting that there is a causal link between ZIKV and microcephaly, however, future studies are warranted to solidify this association. To summarize the most recent evidence on this issue and provide perspectives for future studies, we reviewed the literature to identify existing evidence of the causal link between ZIKV infection and microcephaly within research related to the epidemics, laboratory diagnosis, and possible mechanisms.

  11. Reward-Guided Learning with and without Causal Attribution.

    Science.gov (United States)

    Jocham, Gerhard; Brodersen, Kay H; Constantinescu, Alexandra O; Kahn, Martin C; Ianni, Angela M; Walton, Mark E; Rushworth, Matthew F S; Behrens, Timothy E J

    2016-04-01

    When an organism receives a reward, it is crucial to know which of many candidate actions caused this reward. However, recent work suggests that learning is possible even when this most fundamental assumption is not met. We used novel reward-guided learning paradigms in two fMRI studies to show that humans deploy separable learning mechanisms that operate in parallel. While behavior was dominated by precise contingent learning, it also revealed hallmarks of noncontingent learning strategies. These learning mechanisms were separable behaviorally and neurally. Lateral orbitofrontal cortex supported contingent learning and reflected contingencies between outcomes and their causal choices. Amygdala responses around reward times related to statistical patterns of learning. Time-based heuristic mechanisms were related to activity in sensorimotor corticostriatal circuitry. Our data point to the existence of several learning mechanisms in the human brain, of which only one relies on applying known rules about the causal structure of the task. PMID:26971947

  12. Probing the Cultural Constitution of Causal Cognition - A Research Program.

    Science.gov (United States)

    Bender, Andrea; Beller, Sieghard

    2016-01-01

    To what extent is the way people perceive, represent, and reason about causal relationships dependent on culture? While there have been sporadic attempts to explore this question, a systematic investigation is still lacking. Here, we propose that human causal cognition is not only superficially affected by cultural background, but that it is co-constituted by the cultural nature of the human species. To this end, we take stock of on-going research, with a particular focus on the methodological approaches taken: cross-species comparisons, archeological accounts, developmental studies, cross-cultural, and cross-linguistic experiments, as well as in-depth within-culture analyses of cognitive concepts, processes, and changes over time. We argue that only a combination of these approaches will allow us to integrate different components of cognition, levels of analysis, and points of view-the key requirements for a comprehensive, interdisciplinary research program to advance this field. PMID:26941695

  13. Dark matter perturbations and viscosity: A causal approach

    Science.gov (United States)

    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.

  14. Research designs and making causal inferences from health care studies.

    Science.gov (United States)

    Flannelly, Kevin J; Jankowski, Katherine R B

    2014-01-01

    This article summarizes the major types of research designs used in healthcare research, including experimental, quasi-experimental, and observational studies. Observational studies are divided into survey studies (descriptive and correlational studies), case-studies and analytic studies, the last of which are commonly used in epidemiology: case-control, retrospective cohort, and prospective cohort studies. Similarities and differences among the research designs are described and the relative strength of evidence they provide is discussed. Emphasis is placed on five criteria for drawing causal inferences that are derived from the writings of the philosopher John Stuart Mill, especially his methods or canons. The application of the criteria to experimentation is explained. Particular attention is given to the degree to which different designs meet the five criteria for making causal inferences. Examples of specific studies that have used various designs in chaplaincy research are provided.

  15. Static- and Stationary-complete Spacetimes: Algebraic and Causal Structures

    CERN Document Server

    Harris, Steven G

    2014-01-01

    This is intended as an analysis of the global properties of static and stationary spacetimes with complete (timelike) Killing field, with particular attention to quotients by group actions. This is presented in terms of algebraic structures which are fairly simple for the static case and more involved for the stationary case; the most important tool, the fundamental cocycle, is a cohomological class for static spacetimes but of somewhat looser structure in the stationary case. In particular: (1) A new measurement, similar to the spacetime interval in Minkowski space, is devised for detecting whether two points are causally related in a stationary spacetime; this proves very useful for analysis. (2) All stationary spacetimes are categorized by how they behave with respect to the fundamental cocycle; this enables a complete characterization of global causality properties. (3) It is shown how these tools determine whether global hyperbolicity of a stationary spacetime is inherited by its quotients. (4) Examples ...

  16. Causality between regional stock markets: A frequency domain approach

    Directory of Open Access Journals (Sweden)

    Gradojević Nikola

    2013-01-01

    Full Text Available Using a data set from five regional stock exchanges (Serbia, Croatia, Slovenia, Hungary and Germany, this paper presents a frequency domain analysis of a causal relationship between the returns on the CROBEX, SBITOP, CETOP and DAX indices, and the return on the major Serbian stock exchange index, BELEX 15. We find evidence of a somewhat dominant effect of the CROBEX and CETOP stock indices on the BELEX 15 stock index across a range of frequencies. The results also indicate that the BELEX 15 index and the SBITOP index interact in a bi-directional causal fashion. Finally, the DAX index movements consistently drive the BELEX 15 index returns for cycle lengths between 3 and 11 days without any feedback effect.

  17. Causal explanation, intentionality, and prediction: Evaluating the Criticism of "Deductivism"

    DEFF Research Database (Denmark)

    Koch, Carsten Allan

    2001-01-01

    In a number of influential contributions, Tony Lawson has attacked a view of science that he refers to as deductivism, and criticized economists for implicitly using it in their research. Lawson argues that deductivism is simply the covering-law model, also known as the causal model of scientific...... critisizes the use of universal laws in social science, especially in economics. This view cannot be as easily dismissed as his general criticism of causal explanation. We argue that a number of arguments often used against the existence of (correct) universal laws in the social sciences can be put...... into question. First, it is argued that entities need not be identical, or even remotely alike, to be applicable to the same law. What is necessary is that they have common properties, e.g. mass in physics, and that the law relates to that property (section 6). Second, one might take the so-called model...

  18. Reward-Guided Learning with and without Causal Attribution.

    Science.gov (United States)

    Jocham, Gerhard; Brodersen, Kay H; Constantinescu, Alexandra O; Kahn, Martin C; Ianni, Angela M; Walton, Mark E; Rushworth, Matthew F S; Behrens, Timothy E J

    2016-04-01

    When an organism receives a reward, it is crucial to know which of many candidate actions caused this reward. However, recent work suggests that learning is possible even when this most fundamental assumption is not met. We used novel reward-guided learning paradigms in two fMRI studies to show that humans deploy separable learning mechanisms that operate in parallel. While behavior was dominated by precise contingent learning, it also revealed hallmarks of noncontingent learning strategies. These learning mechanisms were separable behaviorally and neurally. Lateral orbitofrontal cortex supported contingent learning and reflected contingencies between outcomes and their causal choices. Amygdala responses around reward times related to statistical patterns of learning. Time-based heuristic mechanisms were related to activity in sensorimotor corticostriatal circuitry. Our data point to the existence of several learning mechanisms in the human brain, of which only one relies on applying known rules about the causal structure of the task.

  19. Causal Evolutions of Bulk Local Excitations from CFT

    CERN Document Server

    Goto, Kanato; Takayanagi, Tadashi

    2016-01-01

    Bulk localized excited states in an AdS spacetime can be constructed from Ishibashi states with respect to the global conformal symmetry in the dual CFT. We study boundary two point functions of primary operators in the presence of bulk localized excitations in two dimensional CFTs. From two point functions in holographic CFTs, we observe causal propagations of radiations when the mass of dual bulk scalar field is close to the BF bound. This behavior for holographic CFTs is consistent with the locality and causality in classical gravity duals. We also show that this cannot be seen in free fermion CFTs. Moreover, we find that the short distance behavior of two point functions is universal and obeys the relation which generalizes the first law of entanglement entropy.

  20. Regge behavior saves String Theory from causality violations

    CERN Document Server

    D'Appollonio, Giuseppe; Russo, Rodolfo; Veneziano, Gabriele

    2015-01-01

    Higher-derivative corrections to the Einstein-Hilbert action are present in bosonic string theory leading to the potential causality violations recently pointed out by Camanho et al. We analyze in detail this question by considering high-energy string-brane collisions at impact parameters $b \\le l_s$ (the string-length parameter) with $l_s \\gg R_p$ (the characteristic scale of the D$p$-brane geometry). If we keep only the contribution of the massless states causality is violated for a set of initial states whose polarization is suitably chosen with respect to the impact parameter vector. Such violations are instead neatly avoided when the full structure of string theory - and in particular its Regge behavior - is taken into account.

  1. Causal explanation, intentionality, and prediction: Evaluating the Criticism of "Deductivism"

    DEFF Research Database (Denmark)

    Koch, Carsten Allan

    2001-01-01

    In a number of influential contributions, Tony Lawson has attacked a view of science that he refers to as deductivism, and criticized economists for implicitly using it in their research. Lawson argues that deductivism is simply the covering-law model, also known as the causal model of scientific...... critisizes the use of universal laws in social science, especially in economics. This view cannot be as easily dismissed as his general criticism of causal explanation. We argue that a number of arguments often used against the existence of (correct) universal laws in the social sciences can be put into...... question. First, it is argued that entities need not be identical, or even remotely alike, to be applicable to the same law. What is necessary is that they have common properties, e.g. mass in physics, and that the law relates to that property (section 6). Second, one might take the so-called model of...

  2. Causal inference and the data-fusion problem.

    Science.gov (United States)

    Bareinboim, Elias; Pearl, Judea

    2016-07-01

    We review concepts, principles, and tools that unify current approaches to causal analysis and attend to new challenges presented by big data. In particular, we address the problem of data fusion-piecing together multiple datasets collected under heterogeneous conditions (i.e., different populations, regimes, and sampling methods) to obtain valid answers to queries of interest. The availability of multiple heterogeneous datasets presents new opportunities to big data analysts, because the knowledge that can be acquired from combined data would not be possible from any individual source alone. However, the biases that emerge in heterogeneous environments require new analytical tools. Some of these biases, including confounding, sampling selection, and cross-population biases, have been addressed in isolation, largely in restricted parametric models. We here present a general, nonparametric framework for handling these biases and, ultimately, a theoretical solution to the problem of data fusion in causal inference tasks. PMID:27382148

  3. A causal link between prediction errors, dopamine neurons and learning.

    Science.gov (United States)

    Steinberg, Elizabeth E; Keiflin, Ronald; Boivin, Josiah R; Witten, Ilana B; Deisseroth, Karl; Janak, Patricia H

    2013-07-01

    Situations in which rewards are unexpectedly obtained or withheld represent opportunities for new learning. Often, this learning includes identifying cues that predict reward availability. Unexpected rewards strongly activate midbrain dopamine neurons. This phasic signal is proposed to support learning about antecedent cues by signaling discrepancies between actual and expected outcomes, termed a reward prediction error. However, it is unknown whether dopamine neuron prediction error signaling and cue-reward learning are causally linked. To test this hypothesis, we manipulated dopamine neuron activity in rats in two behavioral procedures, associative blocking and extinction, that illustrate the essential function of prediction errors in learning. We observed that optogenetic activation of dopamine neurons concurrent with reward delivery, mimicking a prediction error, was sufficient to cause long-lasting increases in cue-elicited reward-seeking behavior. Our findings establish a causal role for temporally precise dopamine neuron signaling in cue-reward learning, bridging a critical gap between experimental evidence and influential theoretical frameworks.

  4. Domain-specific perceptual causality in children depends on the spatio-temporal configuration, not motion onset

    OpenAIRE

    AnneSchlottmann

    2013-01-01

    Humans, even babies, perceive causality when one shape moves briefly and linearly after another. Motion timing is crucial in this and causal impressions disappear with short delays between motions. However, the role of temporal information is more complex: It is both a cue to causality and a factor that constrains processing. It affects ability to distinguish causality from non-causality, and social from mechanical causality. Here we study both issues with 3- to 7-year-olds and adults who saw...

  5. Causality between Indian Exports, Imports, and Agricultural, Manufacturing GDP.

    OpenAIRE

    László Kónya; Jai Pal Singh

    2007-01-01

    Singh and Kónya (2006) studied the relationship between Indian GDP, exports, and imports from 1950/51 to 2003/2004. A logical further step is to investigate the same issue for two major sectors of the Indian economy: agriculture and manufacturing. In both sectors there is evidence of Granger causality between GDP and total exports, imports. In particular, agricultural GDP causes imports, exports cause agricultural GDP, and any two variables jointly cause the third one. There is also some evid...

  6. The Causal Relationship between Private and Public Investment in Zimbabwe

    OpenAIRE

    Muyambiri, Brian; Chiwira, Oscar; Enowbi Batuo, Michael; Chiranga, Ngonidzashe

    2010-01-01

    The study examines the relationship between private and public investment in Zimbabwe utilizing yearly time series data for the period 1970 to 2007. Emphasis is placed on the direction of causality and the effect of the two types of investment on each other. The paper constructs empirical models for both private and public investment, based on the flexible accelerator theory. Private investment is found to be cointegrated with public investment. A cointergration approach and VEC model are em...

  7. Learning strategies and causal attributions in second language learning

    OpenAIRE

    Sorić, Izabela; Ančić, Jadranka

    2008-01-01

    Although in itself “motivation to learn” is a complex multifaceted construct, according to Dornyei (2001), the picture becomes even more complex when the motivation to learn a foreign/second language is concerned. It seems that a better understanding of the dynamic relationship between learners’ use of language learning strategies and the causal attributions they make for their achievement in language learning is necessary in order to direct and improve learners’ motivation. The present study...

  8. Identifying Causal Marketing Mix Effects Using a Regression Discontinuity Design

    OpenAIRE

    Wesley Hartmann; Harikesh S. Nair; Sridhar Narayanan

    2011-01-01

    We discuss how regression discontinuity designs arise naturally in settings where firms target marketing activity at consumers, and we illustrate how this aspect may be exploited for econometric inference of causal effects of marketing effort. Our main insight is to use commonly observed discontinuities and kinks in the heuristics by which firms target such marketing activity to consumers for nonparametric identification. Such kinks, along with continuity restrictions that are typically satis...

  9. Variational multi-fluid dynamics and causal heat conductivity

    OpenAIRE

    Andersson, N.; Comer, G. L.

    2009-01-01

    We discuss heat conductivity from the point of view of a variational multi-fluid model, treating entropy as a dynamical entity. We demonstrate that a two-fluid model with a massive fluid component and a massless entropy can reproduce a number of key results from extended irreversible thermodynamics. In particular, we show that the entropy entrainment is intimately linked to the thermal relaxation time that is required to make heat propagation in solids causal. We also discuss non-local terms ...

  10. Scientific realism in particle physics a causal approach

    CERN Document Server

    Egg, Matthias

    2014-01-01

    Does particle physics really describe the basic constituents of the material world or is it just a useful tool for deriving empirical predictions? This book proposes a novel answer to that question, emphasizing the importance of causal reasoning for the justification of scientific claims. It thereby responds to general worries about scientific realism as well as to more specific challenges stemming from the interpretation of quantum physics.

  11. Causality between Malaysian Islamic Stock Market and Macroeconomic Variables

    OpenAIRE

    Naseri, Marjan; Masih, Mansur

    2013-01-01

    This paper makes an attempt to analyse the causality between Islamic stock market and three macroeconomic variables in the case of Malaysia. Although there are numerous studies investigating relationship between conventional stock market and macroeconomic fundamentals, there is a certain gap in the literature pertaining to the relationship between Islamic indices and macroeconomic variables which are becoming an interesting area of research due to fast growing force of Islamic finance. Thus, ...

  12. Towards understanding causality between work engagement and psychological capital

    OpenAIRE

    De Waal, Johannes J.; Jaco Pienaar

    2013-01-01

    Orientation: It is of theoretical and practical interest to establish the sequential relationship between work engagement and positive organisational behaviour, as represented by the psychological capital (PsyCap) construct.Research purpose: The main aim of this study was to conceptualise and investigate the causal relationship and temporal order in the relationship between PsyCap and engagement by means of longitudinal data.Motivation for the study: The rationale for establishing the sequenc...

  13. Impact of topology in causal dynamical triangulations quantum gravity

    OpenAIRE

    Ambjorn, Jan; Drogosz, Zbigniew; Gizbert-Studnicki, Jakub; Goerlich, Andrzej; Jurkiewicz, Jerzy; Nemeth, Daniel

    2016-01-01

    We investigate the impact of spatial topology in 3+1 dimensional causal dynamical triangulations (CDT) by performing numerical simulations with toroidal spatial topology instead of the previously used spherical topology. In the case of spherical spatial topology we observed in the so-called phase C an average spatial volume distribution n(t) which after a suitable time redefinition could be identified as the spatial volume distribution of the four-sphere. Imposing toroidal spatial topology we...

  14. On Properties of Update Sequences Based on Causal Rejection

    OpenAIRE

    Eiter, T.; Fink, M; Sabbatini, G; Tompits, H.

    2001-01-01

    We consider an approach to update nonmonotonic knowledge bases represented as extended logic programs under answer set semantics. New information is incorporated into the current knowledge base subject to a causal rejection principle enforcing that, in case of conflicts, more recent rules are preferred and older rules are overridden. Such a rejection principle is also exploited in other approaches to update logic programs, e.g., in dynamic logic programming by Alferes et al. We give a thoroug...

  15. Export and Economic Growth in India: Causal Interpretation

    OpenAIRE

    Pandey, Alok Kumar

    2006-01-01

    The relationship between export and economic growth has been an important issue of discussion among scholars and economist throughout the world. The existence of nexus in between export and economic growth can be examined in several ways like growth rates relating to GDP and export, proportion of export to growth, several policies relating to accelerate economic growth and export etc. The effective way to explore nexus in export and economic growth would be the causal analysis between two var...

  16. Causal effects of paternity leave on children and parents

    OpenAIRE

    Cools, Sara; Jon H. Fiva; Lars J. Kirkebøen

    2011-01-01

    In this paper we use a parental leave reform directed towards fathers to identify the causal effects of paternity leave on children’s and parents’ outcomes. We document that paternity leave causes fathers to become more important for children’s cognitive skills. School performance at age 16 increases for children whose father is relatively higher educated than the mother. We find no evidence that fathers’ earnings and work hours are affected by paternity leave. Contrary to expectation, mother...

  17. Causal effects of parents' education on children's education

    OpenAIRE

    Ermisch, John; Pronzato, Chiara

    2010-01-01

    The paper shows that parents’ education is an important, but hardly exclusive part of the common family background that generates positive correlation between the educational attainments of siblings from the same family. But the correlation between the educational attainments of parents and those of their children overstates considerably the causal effect of parents’ education on the education of their children. Our estimates based on Norwegian twin-mothers indicate that an additional year of...

  18. Causality in 1+1-dimensional Yukawa model-II

    Indian Academy of Sciences (India)

    Asrarul Haque; Satish D Joglekar

    2013-10-01

    The limits → large, $M →$ large with ($g^{3}/M$) = const. of the 1+1-dimensional Yukawa model are discussed. The conclusion of the results on bound states of the Yukawa model in this limit (obtained in arXiv:0908.4510v3 [hep-th]) is taken into account. It is found that model reduces to an effective non-local 3 theory in this limit. Causality violation also is observed in this limit.

  19. The Environmental Kuznets Curve for Green House Gases- Causality structures

    OpenAIRE

    Pancharatnam, Padmaja; Aisabokhae, Ruth A.

    2012-01-01

    The inverted U shaped hypothesis between various indicators of environmental degradation and income per capita otherwise known as the Environmental Kuznets Curve (EKC) has gained immense popularity over the past twenty years. Cross-country panel data methods are generally adopted to study the relationship amongst the variables of interest with a possible drawback being that a certain causality structure is presumed to be true. The Directed Acylical Graph technique reveals the underlying causa...

  20. The transfer matrix in four dimensional causal dynamical triangulations

    OpenAIRE

    Ambjo̸rn, J.; Gizbert-Studnicki, J.(Faculty of Physics, Astronomy and Applied Computer Science, Jagiellonian University, ul. prof. Stanislawa Lojasiewicza 11, Krakow, PL 30-348, Poland); Görlich, A.T.; Jurkiewicz, J.; Loll, R.

    2013-01-01

    The Causal Dynamical Triangulation model of quantum gravity (CDT) is a proposition to evaluate the path integral over space-time geometries using a lattice regularization with a discrete proper time and geometries realized as simplicial manifolds. The model admits a Wick rotation to imaginary time for each space-time configuration. Using computer simulations we determined the phase structure of the model and discovered that it predicts a de Sitter phase with a four-dimensional spherical semi-...

  1. Informational and Causal Architecture of Discrete-Time Renewal Processes

    OpenAIRE

    Marzen, Sarah E.; Crutchfield, James P.

    2015-01-01

    © 2015 by the authors; licensee MDPI, Basel, Switzerland. Renewal processes are broadly used to model stochastic behavior consisting of isolated events separated by periods of quiescence, whose durations are specified by a given probability law. Here, we identify the minimal sufficient statistic for their prediction (the set of causal states), calculate the historical memory capacity required to store those states (statistical complexity), delineate what information is predictable (excess ent...

  2. Darwin, Veblen and the problem of causality in economics.

    Science.gov (United States)

    Hodgson, G M

    2001-01-01

    This article discusses some of the ways in which Darwinism has influenced a small minority of economists. It is argued that Darwinism involves a philosophical as well as a theoretical doctrine. Despite claims to the contrary, the uses of analogies to Darwinian natural selection theory are highly limited in economics. Exceptions include Thorstein Veblen, Richard Nelson, and Sidney Winter. At the philosophical level, one of the key features of Darwinism is its notion of detailed understanding in terms of chains of cause and effect. This issue is discussed in the context of the problem of causality in social theory. At least in Darwinian terms, the prevailing causal dualism--of intentional and mechanical causality--in the social sciences is found wanting. Once again, Veblen was the first economist to understand the implications for economics of Darwinism at this philosophical level. For Veblen, it was related to his notion of 'cumulative causation'. The article concludes with a discussion of the problems and potential of this Veblenian position. PMID:12472063

  3. On the Inference of Functional Circadian Networks Using Granger Causality.

    Science.gov (United States)

    Pourzanjani, Arya; Herzog, Erik D; Petzold, Linda R

    2015-01-01

    Being able to infer one way direct connections in an oscillatory network such as the suprachiastmatic nucleus (SCN) of the mammalian brain using time series data is difficult but crucial to understanding network dynamics. Although techniques have been developed for inferring networks from time series data, there have been no attempts to adapt these techniques to infer directional connections in oscillatory time series, while accurately distinguishing between direct and indirect connections. In this paper an adaptation of Granger Causality is proposed that allows for inference of circadian networks and oscillatory networks in general called Adaptive Frequency Granger Causality (AFGC). Additionally, an extension of this method is proposed to infer networks with large numbers of cells called LASSO AFGC. The method was validated using simulated data from several different networks. For the smaller networks the method was able to identify all one way direct connections without identifying connections that were not present. For larger networks of up to twenty cells the method shows excellent performance in identifying true and false connections; this is quantified by an area-under-the-curve (AUC) 96.88%. We note that this method like other Granger Causality-based methods, is based on the detection of high frequency signals propagating between cell traces. Thus it requires a relatively high sampling rate and a network that can propagate high frequency signals.

  4. Sensitivity analyses for parametric causal mediation effect estimation.

    Science.gov (United States)

    Albert, Jeffrey M; Wang, Wei

    2015-04-01

    Causal mediation analysis uses a potential outcomes framework to estimate the direct effect of an exposure on an outcome and its indirect effect through an intermediate variable (or mediator). Causal interpretations of these effects typically rely on sequential ignorability. Because this assumption is not empirically testable, it is important to conduct sensitivity analyses. Sensitivity analyses so far offered for this situation have either focused on the case where the outcome follows a linear model or involve nonparametric or semiparametric models. We propose alternative approaches that are suitable for responses following generalized linear models. The first approach uses a Gaussian copula model involving latent versions of the mediator and the final outcome. The second approach uses a so-called hybrid causal-observational model that extends the association model for the final outcome, providing a novel sensitivity parameter. These models, while still assuming a randomized exposure, allow for unobserved (as well as observed) mediator-outcome confounders that are not affected by exposure. The methods are applied to data from a study of the effect of mother education on dental caries in adolescence.

  5. Tachyon kinematics and causality: A systematic, thorough analysis

    International Nuclear Information System (INIS)

    The chronological order of the events along a space-like path is not invariant under Lorentz transformations, as wellknown. This led to an early conviction that tachyons would give rise to causal anomalies. A relativistic version of the Stuckelberg-Feynman 'switching procedure' (SWP) has been invoked as the suitable tool to eliminate those anomalies. The application of the 'SWP' does eliminate the motions backwards in time, but interchanges the roles of source and detector. This fact triggered the proposal of a host of causal 'paradoxes'. Till now, however, it has not been recognized that such paradoxes can be sensibly discussed (and completely solved, at least 'in microphysics') only after having properly developed the tachyon relativistic mechanics. It is shown how to apply the 'SWP', both in the case of ordinary Special Relativity, and in the case with tachyons. Then, the kinematics of the tachyon-exchange between two (ordinary) bodies is carrefully exploited. Being finally able to tackle the tachyon-causality problem, the paradoxes are sucessively solved: (i) by Tolman-Regge; (ii) by Pirani; (iii) by Edmonds; (iv) by Bell. At last, a further new paradox associated with the transmission of signals by modulated tachyon beams is discussed. (Author)

  6. Implications about the causality principle in the business income tax

    Directory of Open Access Journals (Sweden)

    Luis Durán Rojo

    2009-06-01

    Full Text Available The following article presents the implications about the practice of the causality principle for the determination of the income set with intention to apply the business income tax.We start considering the fact that this tax can be imposed to acquire goods known as a deductible expense of the practice, but not from those that are going to be part of the compatible cost to expropriate. Then, we make an extensive analysis about the way the Peruvian income tax law has configured the approaches of this principle and the understanding emerged from important jurisprudence cases from the members that solve problems, specially the Tax Court, when adopting a fast principle of expenses without causes.At the same time, this article describes the achievements of the rational and normality cost principles, so important for the evaluation of the performance of the principle of causality.Finally, we present some ideas about the accreditation of the cost facing and its relation to the causality principle.

  7. Investigating Driver Fatigue versus Alertness Using the Granger Causality Network

    Directory of Open Access Journals (Sweden)

    Wanzeng Kong

    2015-08-01

    Full Text Available Driving fatigue has been identified as one of the main factors affecting drivers’ safety. The aim of this study was to analyze drivers’ different mental states, such as alertness and drowsiness, and find out a neurometric indicator able to detect drivers’ fatigue level in terms of brain networks. Twelve young, healthy subjects were recruited to take part in a driver fatigue experiment under different simulated driving conditions. The Electroencephalogram (EEG signals of the subjects were recorded during the whole experiment and analyzed by using Granger-Causality-based brain effective networks. It was that the topology of the brain networks and the brain’s ability to integrate information changed when subjects shifted from the alert to the drowsy stage. In particular, there was a significant difference in terms of strength of Granger causality (GC in the frequency domain and the properties of the brain effective network i.e., causal flow, global efficiency and characteristic path length between such conditions. Also, some changes were more significant over the frontal brain lobes for the alpha frequency band. These findings might be used to detect drivers’ fatigue levels, and as reference work for future studies.

  8. Evaluating diabetes and hypertension disease causality using mouse phenotypes

    Directory of Open Access Journals (Sweden)

    Han Jing-Dong J

    2010-07-01

    Full Text Available Abstract Background Genome-wide association studies (GWAS have found hundreds of single nucleotide polymorphisms (SNPs associated with common diseases. However, it is largely unknown what genes linked with the SNPs actually implicate disease causality. A definitive proof for disease causality can be demonstration of disease-like phenotypes through genetic perturbation of the genes or alleles, which is obviously a daunting task for complex diseases where only mammalian models can be used. Results Here we tapped the rich resource of mouse phenotype data and developed a method to quantify the probability that a gene perturbation causes the phenotypes of a disease. Using type II diabetes (T2D and hypertension (HT as study cases, we found that the genes, when perturbed, having high probability to cause T2D and HT phenotypes tend to be hubs in the interactome networks and are enriched for signaling pathways regulating metabolism but not metabolic pathways, even though the genes in these metabolic pathways are often the most significantly changed in expression levels in these diseases. Conclusions Compared to human genetic disease-based predictions, our mouse phenotype based predictors greatly increased the coverage while keeping a similarly high specificity. The disease phenotype probabilities given by our approach can be used to evaluate the likelihood of disease causality of disease-associated genes and genes surrounding disease-associated SNPs.

  9. On the Inference of Functional Circadian Networks Using Granger Causality

    Science.gov (United States)

    Pourzanjani, Arya; Herzog, Erik D.; Petzold, Linda R.

    2015-01-01

    Being able to infer one way direct connections in an oscillatory network such as the suprachiastmatic nucleus (SCN) of the mammalian brain using time series data is difficult but crucial to understanding network dynamics. Although techniques have been developed for inferring networks from time series data, there have been no attempts to adapt these techniques to infer directional connections in oscillatory time series, while accurately distinguishing between direct and indirect connections. In this paper an adaptation of Granger Causality is proposed that allows for inference of circadian networks and oscillatory networks in general called Adaptive Frequency Granger Causality (AFGC). Additionally, an extension of this method is proposed to infer networks with large numbers of cells called LASSO AFGC. The method was validated using simulated data from several different networks. For the smaller networks the method was able to identify all one way direct connections without identifying connections that were not present. For larger networks of up to twenty cells the method shows excellent performance in identifying true and false connections; this is quantified by an area-under-the-curve (AUC) 96.88%. We note that this method like other Granger Causality-based methods, is based on the detection of high frequency signals propagating between cell traces. Thus it requires a relatively high sampling rate and a network that can propagate high frequency signals. PMID:26413748

  10. Inference and coherence in causal-based artifact categorization.

    Science.gov (United States)

    Puebla, Guillermo; Chaigneau, Sergio E

    2014-01-01

    In four experiments, we tested conditions under which artifact concepts support inference and coherence in causal categorization. In all four experiments, participants categorized scenarios in which we systematically varied information about artifacts' associated design history, physical structure, user intention, user action and functional outcome, and where each property could be specified as intact, compromised or not observed. Consistently across experiments, when participants received complete information (i.e., when all properties were observed), they categorized based on individual properties and did not show evidence of using coherence to categorize. In contrast, when the state of some property was not observed, participants gave evidence of using available information to infer the state of the unobserved property, which increased the value of the available information for categorization. Our data offers answers to longstanding questions regarding artifact categorization, such as whether there are underlying causal models for artifacts, which properties are part of them, whether design history is an artifact's causal essence, and whether physical appearance or functional outcome is the most central artifact property.

  11. On the Identifiability of the Post-Nonlinear Causal Model

    CERN Document Server

    Zhang, Kun

    2012-01-01

    By taking into account the nonlinear effect of the cause, the inner noise effect, and the measurement distortion effect in the observed variables, the post-nonlinear (PNL) causal model has demonstrated its excellent performance in distinguishing the cause from effect. However, its identifiability has not been properly addressed, and how to apply it in the case of more than two variables is also a problem. In this paper, we conduct a systematic investigation on its identifiability in the two-variable case. We show that this model is identifiable in most cases; by enumerating all possible situations in which the model is not identifiable, we provide sufficient conditions for its identifiability. Simulations are given to support the theoretical results. Moreover, in the case of more than two variables, we show that the whole causal structure can be found by applying the PNL causal model to each structure in the Markov equivalent class and testing if the disturbance is independent of the direct causes for each va...

  12. Can the QCD running coupling have a causal analyticity structure?

    CERN Document Server

    Gardi, E; Karliner, M M; Gardi, Einan; Grunberg, Georges; Karliner, Marek

    1998-01-01

    Solving the QCD renormalization group equation at the 2-loop and 3-loop orders we obtain explicit expressions for the coupling as a function of the scale in terms of the Lambert W function. We study the nature of the ``Landau singularities'' in the complex Q^2 plane and show that perturbative freezing can lead, in certain cases, to an analyticity structure that is consistent with causality. We analyze the Analytic Perturbation Theory (APT) approach which is intended to remove the ``Landau singularities'', and show that at 2-loops it is uniquely defined in terms of the Lambert W function, and that, depending on the value of the first two beta function coefficients beta_0 and beta_1, it is either consistent with perturbative freezing (for beta_1 -beta_0^2). The possibility of a causal perturbative coupling is in accordance with the idea that a purely perturbative Banks-Zaks phase with an infrared fixed-point exists in QCD if the number of flavours (N_f) is increased. The causality condition implies that the pe...

  13. A Multivariate Granger Causality Concept towards Full Brain Functional Connectivity.

    Science.gov (United States)

    Schmidt, Christoph; Pester, Britta; Schmid-Hertel, Nicole; Witte, Herbert; Wismüller, Axel; Leistritz, Lutz

    2016-01-01

    Detecting changes of spatially high-resolution functional connectivity patterns in the brain is crucial for improving the fundamental understanding of brain function in both health and disease, yet still poses one of the biggest challenges in computational neuroscience. Currently, classical multivariate Granger Causality analyses of directed interactions between single process components in coupled systems are commonly restricted to spatially low- dimensional data, which requires a pre-selection or aggregation of time series as a preprocessing step. In this paper we propose a new fully multivariate Granger Causality approach with embedded dimension reduction that makes it possible to obtain a representation of functional connectivity for spatially high-dimensional data. The resulting functional connectivity networks may consist of several thousand vertices and thus contain more detailed information compared to connectivity networks obtained from approaches based on particular regions of interest. Our large scale Granger Causality approach is applied to synthetic and resting state fMRI data with a focus on how well network community structure, which represents a functional segmentation of the network, is preserved. It is demonstrated that a number of different community detection algorithms, which utilize a variety of algorithmic strategies and exploit topological features differently, reveal meaningful information on the underlying network module structure.

  14. A Multivariate Granger Causality Concept towards Full Brain Functional Connectivity.

    Directory of Open Access Journals (Sweden)

    Christoph Schmidt

    Full Text Available Detecting changes of spatially high-resolution functional connectivity patterns in the brain is crucial for improving the fundamental understanding of brain function in both health and disease, yet still poses one of the biggest challenges in computational neuroscience. Currently, classical multivariate Granger Causality analyses of directed interactions between single process components in coupled systems are commonly restricted to spatially low- dimensional data, which requires a pre-selection or aggregation of time series as a preprocessing step. In this paper we propose a new fully multivariate Granger Causality approach with embedded dimension reduction that makes it possible to obtain a representation of functional connectivity for spatially high-dimensional data. The resulting functional connectivity networks may consist of several thousand vertices and thus contain more detailed information compared to connectivity networks obtained from approaches based on particular regions of interest. Our large scale Granger Causality approach is applied to synthetic and resting state fMRI data with a focus on how well network community structure, which represents a functional segmentation of the network, is preserved. It is demonstrated that a number of different community detection algorithms, which utilize a variety of algorithmic strategies and exploit topological features differently, reveal meaningful information on the underlying network module structure.

  15. Time and Causation in Discourse: Temporal Proximity, Implicit Causality, and Re-mention Biases.

    Science.gov (United States)

    Dery, Jeruen E; Bittner, Dagmar

    2016-08-01

    Using referential processing in discourse featuring implicit causality verbs as a test case, we demonstrate how a discourse's causal and temporal dimensions interact. We show that referential processing is affected by multiple discourse biases, and that these biases do not have uniform effects. In three discourse continuation experiments, we show that the bias to re-mention a particular referent in discourse involving implicit causality verbs is not only affected by the verb's implicit causality bias, but also by the discourse's temporal structure, which at times, can even override the implicit causality bias. Our results add to the growing number of studies that show how various discourse dimensions interact in discourse processing.

  16. Dental Caries Risk Studies Revisited: Causal Approaches Needed for Future Inquiries

    Directory of Open Access Journals (Sweden)

    Dorthe Holst

    2009-11-01

    Full Text Available Prediction of high-risk individuals and the multi-risk approach are common inquiries in caries risk epidemiology. These studies prepared the ground for future studies; specific hypotheses about causal patterns can now be formulated and tested applying advanced statistical methods designed for causal studies, such as structural equation modeling, path analysis and multilevel modeling. Causal studies should employ measurements, analyses and interpretation of findings, which are in accordance to causal aims. Examples of causal empirical studies from medical and oral research are presented.

  17. Creating a memory of causal relationships an integration of empirical and explanation-based learning methods

    CERN Document Server

    Pazzani, Michael J

    1990-01-01

    This book presents a theory of learning new causal relationships by making use of perceived regularities in the environment, general knowledge of causality, and existing causal knowledge. Integrating ideas from the psychology of causation and machine learning, the author introduces a new learning procedure called theory-driven learning that uses abstract knowledge of causality to guide the induction process. Known as OCCAM, the system uses theory-driven learning when new experiences conform to common patterns of causal relationships, empirical learning to learn from novel experiences,

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

    International Nuclear Information System (INIS)

    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

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

    Energy Technology Data Exchange (ETDEWEB)

    Hofer-Szabó, Gábor, E-mail: szabo.gabor@btk.mta.hu [Research Center for the Humanities, Budapest (Hungary); Vecsernyés, Péter, E-mail: vecsernyes.peter@wigner.mta.hu [Wigner Research Centre for Physics, Budapest (Hungary)

    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.

  20. Learning about causes from people and about people as causes: probabilistic models and social causal reasoning.

    Science.gov (United States)

    Buchsbaum, Daphna; Seiver, Elizabeth; Bridgers, Sophie; Gopnik, Alison

    2012-01-01

    A major challenge children face is uncovering the causal structure of the world around them. Previous research on children's causal inference has demonstrated their ability to learn about causal relationships in the physical environment using probabilistic evidence. However, children must also learn about causal relationships in the social environment, including discovering the causes of other people's behavior, and understanding the causal relationships between others' goal-directed actions and the outcomes of those actions. In this chapter, we argue that social reasoning and causal reasoning are deeply linked, both in the real world and in children's minds. Children use both types of information together and in fact reason about both physical and social causation in fundamentally similar ways. We suggest that children jointly construct and update causal theories about their social and physical environment and that this process is best captured by probabilistic models of cognition. We first present studies showing that adults are able to jointly infer causal structure and human action structure from videos of unsegmented human motion. Next, we describe how children use social information to make inferences about physical causes. We show that the pedagogical nature of a demonstrator influences children's choices of which actions to imitate from within a causal sequence and that this social information interacts with statistical causal evidence. We then discuss how children combine evidence from an informant's testimony and expressed confidence with evidence from their own causal observations to infer the efficacy of different potential causes. We also discuss how children use these same causal observations to make inferences about the knowledge state of the social informant. Finally, we suggest that psychological causation and attribution are part of the same causal system as physical causation. We present evidence that just as children use covariation between

  1. Spatiotemporal causal modeling for the management of Dengue Fever

    Science.gov (United States)

    Yu, Hwa-Lung; Huang, Tailin; Lee, Chieh-Han

    2015-04-01

    Increasing climatic extremes have caused growing concerns about the health effects and disease outbreaks. The association between climate variation and the occurrence of epidemic diseases play an important role on a country's public health systems. Part of the impacts are direct casualties associated with the increasing frequency and intensity of typhoons, the proliferation of disease vectors and the short-term increase of clinic visits on gastro-intestinal discomforts, diarrhea, dermatosis, or psychological trauma. Other impacts come indirectly from the influence of disasters on the ecological and socio-economic systems, including the changes of air/water quality, living environment and employment condition. Previous risk assessment studies on dengue fever focus mostly on climatic and non-climatic factors and their association with vectors' reproducing pattern. The public-health implication may appear simple. Considering the seasonal changes and regional differences, however, the causality of the impacts is full of uncertainties. Without further investigation, the underlying dengue fever risk dynamics may not be assessed accurately. The objective of this study is to develop an epistemic framework for assessing dynamic dengue fever risk across space and time. The proposed framework integrates cross-departmental data, including public-health databases, precipitation data over time and various socio-economic data. We explore public-health issues induced by typhoon through literature review and spatiotemporal analytic techniques on public health databases. From those data, we identify relevant variables and possible causal relationships, and their spatiotemporal patterns derived from our proposed spatiotemporal techniques. Eventually, we create a spatiotemporal causal network and a framework for modeling dynamic dengue fever risk.

  2. Cystatin C Is Not Causally Related to Coronary Artery Disease.

    Directory of Open Access Journals (Sweden)

    Patrik Svensson-Färbom

    Full Text Available Strong and independent associations between plasma concentration of cystatin C and risk of cardiovascular disease (CVD suggests causal involvement of cystatin C.The aim of our study was to assess whether there is a causal relationship between plasma concentration of cystatin C and risk of coronary artery disease (CAD using a Mendelian Randomization approach.We estimated the strength of association of plasma cystatin C on CAD risk and the strength of association of the strongest GWAS derived cystatin C SNP (rs13038305 on plasma cystatin C in the population-based Malmö Diet and Cancer Study (MDC and thereafter the association between rs13038305 and CAD in the MDC (3200 cases of CAD and 24418 controls and CARDIOGRAM (22233 cases of CAD and 64762 controls.Each standard deviation (SD increment of plasma cystatin C was associated with increased risk of CAD (OR = 1.20, 95% CI 1.07-1.34 after full adjustment. Each copy of the major allele of rs13038305 was associated with 0.34 SD higher plasma concentration of cystatin C (P98% to detect a significant relationship between rs13038305 and CAD in MDC and CARDIOGRAM pooled. The odds ratio for CAD (per copy of the major rs13038305 allele was 1.00 (0.94-1.07; P = 0.92 in MDC, 0.99 (0.96-1.03; P = 0.84 in CARDIOGRAM and 1.00 (0.97-1.03; P = 0.83 in MDC and CARDIOGRAM pooled.Genetic elevation of plasma cystatin C is not related to altered risk of CAD, suggesting that there is no causal relationship between plasma cystatin C and CAD. Rather, the association between cystatin C and CAD appears to be due to the association of eGFR and CAD.

  3. Vitamin D and extra-skeletal health: causality or consequence.

    Science.gov (United States)

    Al Nozha, Omar M

    2016-07-01

    Vitamin D deficiency /insufficiency is widely recognized as a global health problem that is likely to be involved in pathogenesis or progression of many acute and chronic health disorders. Its relation to skeletal health has been clearly demonstrated and thoroughly examined. This review aims to highlight the continuous debate about the relation between vitamin D and extra-skeletal health and whether it is a causality or just an association. Overall, the available evidence does not meet the criteria for establishing cause-and-effect relationships because of the limitations of observational studies to corroborate the causality due to many potential confounders. Moreover, the causal relationship couldn't be established in randomized studies or in many meta-analyses. This may reflect the fact that vitamin D level reduction is just a biomarker of ill health. The inflammatory processes involved in the disease occurrence and the functional limitations of the diseases would have a role in reducing serum 25-hydroxy vitamin D "25 (OH) D" level, which would explain why low vitamin D is reported in a wide range of disorders. This may underscore the possibility of harm instead of benefit of vitamin D supplementation when its exact role is not fully established, thus many guidelines and interest groups are still hesitant toward recommending replacement in extra-skeletal disease. Future directions entails the need for a large well-designed randomized control trials (RCTs) to resolve the active debate on the benefits of vitamin D replacement for extra-skeletal disease, and not only that, future studies should establish specific, clinically relevant effects of vitamin D repletion, provide cut-values for optimal serum levels of 25 (OH) D, and appropriate doses for non-skeletal health benefits. PMID:27610068

  4. Thinking anew causality problems for the radiation reaction force

    CERN Document Server

    Souza, Reinaldo de Melo e

    2015-01-01

    In this work, we analyze a Lagrangian formalism recently proposed to approach the issue of the Abraham-Lorentz force. Instead of involving only position and velocity, as usual in Classical Mechanics, this Lagrangian involves the acceleration of the charge. We find the conserved momentum of the charge in the absence of any field and show that it contains an acceleration term. This enables us to re-visit the well-known pre-acceleration problem and show that, contrary to what has been widely believed, it is not related to any violation of causality.

  5. Cellular senescence as the causal nexus of aging

    Directory of Open Access Journals (Sweden)

    Naina eBhatia-Dey

    2016-02-01

    Full Text Available We present cellular senescence as the ultimate driver of the aging process, as a causal nexus that bridges microscopic subcellular damage with the phenotypic, macroscopic effect of aging. It is important to understand how the various types of subcellular damage correlated with the aging process lead to the larger, visible effects of anatomical aging. While it has always been assumed that subcellular damage (cause results in macroscopic aging (effect, the bridging link between the two has been hard to define. Here, we propose that this bridge, which we term the causal nexus, is in fact cellular senescence. The subcellular damage itself does not directly cause the visible signs of aging, but rather, as the damage accumulates and reaches a critical mass, cells cease to proliferate and acquire the deleterious senescence-associated secretory phenotype (SASP which then leads to the macroscopic consequences of tissue breakdown to create the physiologically aged phenotype. Thus senescence is a precondition for anatomical aging, and this explains why aging is a gradual process that remains largely invisible during most of its progression. The subcellular damage includes shortening of telomeres, damage to mitochondria, aneuploidy and DNA double-strand breaks triggered by various genetic, epigenetic, and environmental factors. Damage pathways acting in isolation or in concert converge at the causal nexus of cellular senescence. In each species some types of damage can be more causative than in others and operate at a variable pace; for example, telomere erosion appears to be a primary cause in human cells, whereas activation of tumor suppressor genes is more causative in rodents. Such species-specific mechanisms indicate that despite different initial causes, most of aging is traced to a single convergent causal nexus: senescence. The exception is in some invertebrate species that escape senescence, and in nondividing cells such as neurons, where

  6. On Real-Time and Causal Secure Source Coding

    OpenAIRE

    Kaspi, Yonatan; Merhav, Neri

    2012-01-01

    We investigate two source coding problems with secrecy constraints. In the first problem we consider real--time fully secure transmission of a memoryless source. We show that although classical variable--rate coding is not an option since the lengths of the codewords leak information on the source, the key rate can be as low as the average Huffman codeword length of the source. In the second problem we consider causal source coding with a fidelity criterion and side information at the decoder...

  7. Perceiving individuals and groups: expectancies, dispositional inferences, and causal attributions.

    Science.gov (United States)

    Susskind, J; Maurer, K; Thakkar, V; Hamilton, D L; Sherman, J W

    1999-02-01

    Two experiments investigated differences in forming impressions of individual and group targets. Experiment 1 showed that when forming an impression of an individual, perceivers made more extreme trait judgments, made those judgments more quickly and with greater confidence, and recalled more information than when the impression target was a group. Experiment 2 showed that when participants were forming an impression of an individual, expectancy-inconsistent behaviors spontaneously triggered causal attributions to resolve the inconsistency; this was not the case when the impression target was a group. Results are interpreted as reflecting perceivers' a priori assumptions of unity and coherence in individual versus group targets.

  8. On the conceptual distinction of general causality orientations

    DEFF Research Database (Denmark)

    Olesen, Martin Hammershøj

    This study investigates the conceptual overlap and distinction between individual differences in the Five-Factor Model and Self-determination theory. Participants were 223 adults (age mean=43.74; 60.09% women), who originated in a Danish national probability sample. The participants completed...... electronic questionnaires of dispositional personality traits (NEO-FFI) and general causality orientations (GCOS). Proposed separate latent models and alternative shared latent models of the underlying individual differences constructs had been developed in a previous exploratory study (Olesen, Thomsen...

  9. Applying the Causal Theory of Reference to Intentional Concepts

    DEFF Research Database (Denmark)

    Michael, John Andrew; Macleod, Miles

    2013-01-01

    We argue that many recent philosophical discussions about the reference of everyday concepts of intentional states have implicitly been predicated on descriptive theories of reference. To rectify this, we attempt to demonstrate how a causal theory can be applied to intentional concepts....... Specifically, we argue that some phenomena in early social de- velopment ðe.g., mimicry, gaze following, and emotional contagionÞ can serve as refer- ence fixers that enable children to track others’ intentional states and, thus, to refer to those states. This allows intentional concepts to be anchored...

  10. A Modification of the Halpern-Pearl Definition of Causality

    OpenAIRE

    Halpern, Joseph Y.

    2015-01-01

    The original Halpern-Pearl definition of causality [Halpern and Pearl, 2001] was updated in the journal version of the paper [Halpern and Pearl, 2005] to deal with some problems pointed out by Hopkins and Pearl [2003]. Here the definition is modified yet again, in a way that (a) leads to a simpler definition, (b) handles the problems pointed out by Hopkins and Pearl, and many others, (c) gives reasonable answers (that agree with those of the original and updated definition) in the standard pr...

  11. Einstein causal quantum fields on lattices with discrete Lorentz invariance

    International Nuclear Information System (INIS)

    Results on rigorous construction of quantum fields on the hypercubic lattice Z4 considered as a lattice in the Minkowski space R4 are presented. Two associated fields are constructed: The first one having on the lattice points of Z4 is causal and Poincare invariant in the discrete sense. The second one is an interpolating field over R4 which is pointlike, translationally covariant and spectral in such a manner that the 'real' lattices field is the restriction of the interpolating field to Z4. Furthermore, results on a rigorous perturbation theory of such fields are mentioned

  12. The gut microbiota and obesity: from correlation to causality.

    Science.gov (United States)

    Zhao, Liping

    2013-09-01

    The gut microbiota has been linked with chronic diseases such as obesity in humans. However, the demonstration of causality between constituents of the microbiota and specific diseases remains an important challenge in the field. In this Opinion article, using Koch's postulates as a conceptual framework, I explore the chain of causation from alterations in the gut microbiota, particularly of the endotoxin-producing members, to the development of obesity in both rodents and humans. I then propose a strategy for identifying the causative agents of obesity in the human microbiota through a combination of microbiome-wide association studies, mechanistic analysis of host responses and the reproduction of diseases in gnotobiotic animals.

  13. A new causal interpretation of EPR-B experiment

    Science.gov (United States)

    Gondran, Michel; Gondran, Alexandre

    2012-12-01

    In this paper we study a two-step version of EPR-B experiment, the Bohm version of the Einstein-Podolsky-Rosen experiment. Its theoretical resolution in space and time enables us to refute the classic "impossibility" to decompose a pair of entangled atoms into two distinct states, one for each atom. We propose a new causal interpretation of the EPR-B experiment where each atom has a position and a spin while the singlet wave function verifies the two-body Pauli equation. In conclusion we suggest a physical explanation of non-local influences, compatible with Einstein's point of view on relativity.

  14. Report on data screening and qualitative identification of causal relationships

    OpenAIRE

    Fabio BARTOLINI; Viaggi, Davide; Bryson, Jessica; Silburn, Anastasia L.; Desjeux, Yann; Latruffe, Laure; Kuhlman, Tom; Juvancic,, Luka; Travnikar, Tanja; Berges, Regine; Piorr, Annette; Uthes, Sandra; Zasada, Ingo

    2011-01-01

    In the context of the SPARD project, WP5 has the objectives to: a) prove that the methodology is feasible at different scales of application; b) that the modelling results are reliable for further specification by using and processing data of higher or different quality (more disaggregated, higher spatial resolution, specific properties).This deliverable D5.1 contains the results of the task 5.1 which aims at the qualitative identification of the causal relationship at case study area (CSA) l...

  15. Causal Attributions and Parents' Acceptance of Their Homosexual Sons.

    Science.gov (United States)

    Belsky, Yael; Diamond, Gary M

    2015-01-01

    This Internet-based study examined the association between Israeli parents' attributions regarding the cause of their son's homosexuality and their level of acceptance of their homosexual son. The sample (N = 57) was recruited via Internet Web sites (gay forums and support groups). Findings suggest that more essentialist (versus constructivist) causal attributions were associated with higher levels of parental acceptance. Length of time parents knew of their son's homosexual orientation predicted the degree to which their attributions were essentialist. Implications are discussed.

  16. Interacciones causales del necrosamiento de yemas florales en zarzamora 'Tupy'.

    OpenAIRE

    Argote Hernández, Cajeme Nicolás

    2013-01-01

    Actualmente en México la principal frutilla que se exporta en fresco es la zarzamora ‘Tupy’ (Rubus spp.). El Estado de Michoacán produce más de 90% del total a nivel nacional. Uno de los problemas de producción es el necrosamiento de las yemas florales. No existen reportes documentados sobre el necrosamiento de las yemas en zarzamora. Se diseñó un experimento con zarzamora ´Tupy´ en Los Reyes, Michoacán para diagnosticar las posibles interacciones causales del necrosamiento de yemas. Se pro...

  17. Global and local aspects of causality in quantum mechanics

    Directory of Open Access Journals (Sweden)

    Stoica Cristinel

    2013-09-01

    Full Text Available Quantum mechanics forces us to reconsider certain aspects of classical causality. The ‘central mystery’ of quantum mechanics manifests in different ways, depending on the interpretation. This mystery can be formulated as the possibility of selecting part of the initial conditions of the Universe ‘retroactively’. This talk aims to show that there is a global, timeless, ‘bird’s view’ of the spacetime, which makes this mystery more reasonable. We will review some well-known quantum effects from the perspective of global consistency.

  18. Causality and Intervention in the Spin-Echo Experiments

    Directory of Open Access Journals (Sweden)

    Fernanda Samaniego Bañuelos

    2013-09-01

    Full Text Available In the so-called “Spin-Echo Experiments” the behaviour of a spin’s system seems to violate the second law of thermodynamics. For this reason the “Spin-Echo Experiments” are considered of particular interest for the Foundations of Physics. Interventionists have provided a classical explanation (Blatt, 1959; Ridderbos & Redhead, 1998 and a quantum-based explanation (Hemmo & Shenker, 2005 of these experiments. Here both interventionist explanations are assessed by means of the Manipulability Theory of Causal Explanation (Woodward, 2003. It is argued that interventionism would gain explanatory depth by providing functional relations and predicting relaxation times.

  19. A possible realization of Einstein's causal theory underlying quantum mechanics

    International Nuclear Information System (INIS)

    It is shown that a new microscopic mechanics formulated earlier can be looked upon as a possible causal theory underlying quantum mechanics, which removes Einstein's famous objections against quantum theory. This approach is free from objections raised against Bohm's hidden variable theory and leads to a clear physical picture in terms of familiar concepts, if self interactions are held responsible for deviations from classical behaviour. The new level of physics unfolded by this approach may reveal novel frontiers in high-energy physics. (author)

  20. Causal Attributions and Parents' Acceptance of Their Homosexual Sons.

    Science.gov (United States)

    Belsky, Yael; Diamond, Gary M

    2015-01-01

    This Internet-based study examined the association between Israeli parents' attributions regarding the cause of their son's homosexuality and their level of acceptance of their homosexual son. The sample (N = 57) was recruited via Internet Web sites (gay forums and support groups). Findings suggest that more essentialist (versus constructivist) causal attributions were associated with higher levels of parental acceptance. Length of time parents knew of their son's homosexual orientation predicted the degree to which their attributions were essentialist. Implications are discussed. PMID:26177158

  1. Perceiving individuals and groups: expectancies, dispositional inferences, and causal attributions.

    Science.gov (United States)

    Susskind, J; Maurer, K; Thakkar, V; Hamilton, D L; Sherman, J W

    1999-02-01

    Two experiments investigated differences in forming impressions of individual and group targets. Experiment 1 showed that when forming an impression of an individual, perceivers made more extreme trait judgments, made those judgments more quickly and with greater confidence, and recalled more information than when the impression target was a group. Experiment 2 showed that when participants were forming an impression of an individual, expectancy-inconsistent behaviors spontaneously triggered causal attributions to resolve the inconsistency; this was not the case when the impression target was a group. Results are interpreted as reflecting perceivers' a priori assumptions of unity and coherence in individual versus group targets. PMID:10074704

  2. Causal effects of alcoholism on earnings: estimates from the NLSY.

    Science.gov (United States)

    Jones, Alison Snow; Richmond, David W

    2006-08-01

    Propensity score matching is used to investigate the causal relationship between alcoholism and earnings in a young cohort of males and females drawn from the 1989 and 1994 National Longitudinal Survey of Youth (NLSY) in order to investigate productivity losses attributed to alcoholism and to quantify these effects. Results suggest that there are productivity losses attributable to alcoholism; that they become more pronounced over the life cycle; and that they differ between men and women. Ways in which estimates from propensity score matching may or may not improve on instrumental variables estimates are discussed.

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    Daniel Chicharro

    Full Text Available 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.

  5. Temperature has a causal effect on avian timing of reproduction.

    Science.gov (United States)

    Visser, Marcel E; Holleman, Leonard J M; Caro, Samuel P

    2009-06-22

    Many bird species reproduce earlier in years with high spring temperatures, but little is known about the causal effect of temperature. Temperature may have a direct effect on timing of reproduction but the correlation may also be indirect, for instance via food phenology. As climate change has led to substantial shifts in timing, it is essential to understand this causal relationship to predict future impacts of climate change. We tested the direct effect of temperature on laying dates in great tits (Parus major) using climatized aviaries in a 6-year experiment. We mimicked the temperature patterns from two specific years in which our wild population laid either early ('warm' treatment) or late ('cold' treatment). Laying dates were affected by temperature directly. As the relevant temperature period started three weeks prior to the mean laying date, with a range of just 4 degrees C between the warm and the cold treatments, and as the birds were fed ad libitum, it is likely that temperature acted as a cue rather than lifting an energetic constraint on the onset of egg production. We furthermore show a high correlation between the laying dates of individuals reproducing both in aviaries and in the wild, validating investigations of reproduction of wild birds in captivity. Our results demonstrate that temperature has a direct effect on timing of breeding, an important step towards assessing the implication of climate change on seasonal timing. PMID:19324731

  6. A Tool for Qualitative Causal Reasoning On Complex Systems

    Directory of Open Access Journals (Sweden)

    Tahar Guerram

    2010-11-01

    Full Text Available A cognitive map, also called a mental map, is a representation and reasoning model on causal knowledge. It is a directed, labeled and cyclic graph whose nodes represent causes or effects and whose arcs represent causal relations between these nodes such as "increases", "decreases", "supports", and "disadvantages". A cognitive map represents beliefs (knowledge which we lay out about a given domain of discourse and is useful as a means of decision making support. There are several types of cognitive maps but the most used are fuzzy cognitive maps. This last treat the cases of existence and no nexistence of relations between nodes but does not deal with the case when these relations are indeterminate. Neutrosophic cognitive maps proposed by F. Smarandache make it possible to take into account these indetermination and thus constitute an extension of fuzzy cognitive maps. This article tries to propose a modeling and reasoning tool for complex systems based on neutrosophic cognitive maps. In order to be able to evaluate our work, we applied our tool to a medical case which is the viral infection biological process.

  7. Video Sensor-Based Complex Scene Analysis with Granger Causality

    Directory of Open Access Journals (Sweden)

    Shuang Wu

    2013-10-01

    Full Text Available In this report, we propose a novel framework to explore the activity interactions and temporal dependencies between activities in complex video surveillance scenes. Under our framework, a low-level codebook is generated by an adaptive quantization with respect to the activeness criterion. The Hierarchical Dirichlet Processes (HDP model is then applied to automatically cluster low-level features into atomic activities. Afterwards, the dynamic behaviors of the activities are represented as a multivariate point-process. The pair-wise relationships between activities are explicitly captured by the non-parametric Granger causality analysis, from which the activity interactions and temporal dependencies are discovered. Then, each video clip is labeled by one of the activity interactions. The results of the real-world traffic datasets show that the proposed method can achieve a high quality classification performance. Compared with traditional K-means clustering, a maximum improvement of 19.19% is achieved by using the proposed causal grouping method.

  8. Reichenbach on causality in 1923: Scientific inference, coordination, and confirmation.

    Science.gov (United States)

    Padovani, Flavia

    2015-10-01

    In The Theory of Relativity and A Priori Knowledge (1920b), Reichenbach developed an original account of cognition as coordination of formal structures to empirical ones. One of the most salient features of this account is that it is explicitly not a top-down type of coordination, and in fact it is crucially "directed" by the empirical side. Reichenbach called this feature "the mutuality of coordination" but, in that work, did not elaborate sufficiently on how this is supposed to work. In a paper that he wrote less than two years afterwards (but that he published only in 1932), "The Principle of Causality and the Possibility of its Empirical Confirmation" (1923/1932), he described what seems to be a model for this idea, now within an analysis of causality that results in an account of scientific inference. Recent reassessments of his early proposal do not seem to capture the extent of Reichenbach's original worries. The present paper analyses Reichenbach's early account and suggests a new way to look at his early work. According to it, we perform measurements, individuate parameters, collect and analyse data, by using a "constructive" approach, such as the one with which we formulate and test hypotheses, which paradigmatically requires some simplicity assumptions. Reichenbach's attempt to account for all these aspects in 1923 was obviously limited and naive in many ways, but it shows that, in his view, there were multiple ways in which the idea of "constitution" is embodied in scientific practice. PMID:26386525

  9. Dyslipidemias in the prevention of cardiovascular disease: risks and causality.

    Science.gov (United States)

    Graham, Ian; Cooney, Marie-Therese; Bradley, David; Dudina, Alexandra; Reiner, Zeljko

    2012-12-01

    Atherosclerotic cardiovascular disease is now the major global cause of death, despite reductions in CVD deaths in developed societies. Dyslipidemias are a major contributor, but the mass occurrence of CVD relates to the combined effects of hyperlipidemia, hypertension, and smoking. Total blood cholesterol and LDL-cholesterol relate to CVD risk in an independent and graded manner and fulfill the criteria for causality. Therapeutic reduction of these lipid fractions is associated with improved outcomes. There is good evidence that HDL-cholesterol, triglycerides, and Lp(a) relate to CVD although the evidence for a causal relationship is weaker. The HDL association with CVD is largely independent of other risk factors whereas triglycerides may be more important as signaling a need to look intensively for other measures of risk such as central obesity, hypertension, low HDL-cholesterol, and glucose intolerance. Lp(a) is an inherited risk marker. The benefit of lowering it is uncertain, but it may be that its impact on risk is attenuated if LDL-cholesterol is low.

  10. A Causal Relationship of Occupational Stress among University Employees

    Directory of Open Access Journals (Sweden)

    Chonticha KAEWANUCHIT

    2015-10-01

    Full Text Available Background: Occupational stress is a psychosocial dimension of occupational health concept on social determinants of health, especially, job & environmental condition. Recently, staff network of different government universities of Thailand have called higher education commission, and Ministry of Education, Thailand to resolve the issue of gov-ernment education policy (e.g. wage inequity, poor welfare, law, and job & environment condition that leads to their job insecurity, physical and mental health problems from occupational stress. The aim of this study was to investigate a causal relationship of occupational stress among the academic university employees.Methods: This cross sectional research was conducted in 2014 among 2,000 academic university employees at Thai government universities using stratified random sampling. Independent variables were wage, family support, periods of duty, and job & environmental condition. Dependent variable was stress.Results: Job & environmental condition, as social and environmental factor, and periods of duty as individual factor had direct effect to stress (P< 0.05. Family support, as family factor, and wage, as individual factor had direct effect to stress (P < 0.05. Both family support and wage were the causal endogenous variables.Conclusion: Job & environmental condition and periods of duty were increased so that it associated with occupation-al stress among academic university employees at moderate level.

  11. SIGNOR: a database of causal relationships between biological entities.

    Science.gov (United States)

    Perfetto, Livia; Briganti, Leonardo; Calderone, Alberto; Perpetuini, Andrea Cerquone; Iannuccelli, Marta; Langone, Francesca; Licata, Luana; Marinkovic, Milica; Mattioni, Anna; Pavlidou, Theodora; Peluso, Daniele; Petrilli, Lucia Lisa; Pirrò, Stefano; Posca, Daniela; Santonico, Elena; Silvestri, Alessandra; Spada, Filomena; Castagnoli, Luisa; Cesareni, Gianni

    2016-01-01

    Assembly of large biochemical networks can be achieved by confronting new cell-specific experimental data with an interaction subspace constrained by prior literature evidence. The SIGnaling Network Open Resource, SIGNOR (available on line at http://signor.uniroma2.it), was developed to support such a strategy by providing a scaffold of prior experimental evidence of causal relationships between biological entities. The core of SIGNOR is a collection of approximately 12,000 manually-annotated causal relationships between over 2800 human proteins participating in signal transduction. Other entities annotated in SIGNOR are complexes, chemicals, phenotypes and stimuli. The information captured in SIGNOR can be represented as a signed directed graph illustrating the activation/inactivation relationships between signalling entities. Each entry is associated to the post-translational modifications that cause the activation/inactivation of the target proteins. More than 4900 modified residues causing a change in protein concentration or activity have been curated and linked to the modifying enzymes (about 351 human kinases and 94 phosphatases). Additional modifications such as ubiquitinations, sumoylations, acetylations and their effect on the modified target proteins are also annotated. This wealth of structured information can support experimental approaches based on multi-parametric analysis of cell systems after physiological or pathological perturbations and to assemble large logic models. PMID:26467481

  12. Dimensions of Causal Attributions of Tax Evasion in Portugal

    Directory of Open Access Journals (Sweden)

    José C. Tavares

    2010-01-01

    Full Text Available Un estudio realizado en España (Salgado, 1998 sugirió que las atribuciones de la evasión fiscal tienen dos dimensiones independientes: (a control de la evasión fiscal, y (b las creencias sobre el sistema fiscal. A fin de comprobar si la percepción de las causas de la evasión fiscal son generalizables transculturalmente, este artículo presenta una investigación realizada en Portugal utilizando las mismas atribuciones causales usadas en la investigación española. A una muestra de 497 hombres y mujeres portugueses, de diferentes puestos de trabajo, se les preguntó acerca de sus percepciones causales de la evasión fiscal. Se llevó a cabo un análisis factorial y los resultados mostraron una estructura factorial que reproduce la estructura factorial española. Los coeficientes de congruencia confirmaron la similitud de las dos estructuras. Estos resultados confirmaron que las dos dimensiones pueden explicar la estructura de la percepción de las causas de la evasión fiscal. Se discuten las implicaciones de los resultados y se sugieren investigaciones futuras.

  13. Topological reversibility and causality in feed-forward networks

    Energy Technology Data Exchange (ETDEWEB)

    Corominas-Murtra, Bernat; RodrIguez-Caso, Carlos; Sole, Ricard [ICREA-Complex Systems Lab, Universitat Pompeu Fabra (Parc de Recerca Biomedica de Barcelona), Dr Aiguader 88, 08003 Barcelona (Spain); Goni, JoaquIn, E-mail: bernat.corominas@upf.ed [Functional Neuroimaging Laboratory, Department of Neurosciences, Center for Applied Medical Research, University of Navarra, Pamplona (Spain)

    2010-11-15

    Systems whose organization displays causal asymmetry constraints, from evolutionary trees to river basins or transport networks, can often be described in terms of directed paths on a discrete set of arbitrary units including states in state spaces, feed-forward neural nets, the evolutionary history of a given collection of events or the chart of computational states visited along a complex computation. Such a set of paths defines a feed-forward, acyclic network. A key problem associated with these systems involves characterizing their intrinsic degree of path reversibility: given an end node in the graph, what is the uncertainty of recovering the process backwards until the origin? Here, we propose a novel concept, topological reversibility, which is a measure of the complexity of the net that rigorously weights such uncertainty in path dependency, quantifying the minimum amount of information required to successfully reverse a causal path. Within the proposed framework, we also analytically characterize limit cases for both topologically reversible and maximally entropic structures. The relevance of these measures within the context of evolutionary dynamics is highlighted.

  14. Economic Growth, Foreign Direct Investment and CO2 Emissions in China: A Panel Granger Causality Analysis

    Directory of Open Access Journals (Sweden)

    Hongfeng Peng

    2016-03-01

    Full Text Available Using a sample of province-level panel data, this paper investigates the Granger causality associations among economic growth (GDP, foreign direct investment (FDI and CO2 emissions in China. By applying the bootstrap Granger panel causality approach (Kónya, 2006, we consider both cross-sectional dependence and homogeneity of different regions in China. The empirical results support that the causality direction not only works in a single direction either from GDP to FDI (in Yunnan or from FDI to GDP (in Beijing, Neimenggu, Jilin, Shanxi and Gansu, but it also works in both directions (in Henan. Moreover, we document that GDP is Granger-causing CO2 emissions in Neimenggu, Hubei, Guangxi and Gansu while there is bidirectional causality between these two variables in Shanxi. In the end, we identify the unidirectional causality from FDI to CO2 emissions in Beijing, Henan, Guizhou and Shanxi, and the bidirectional causality between FDI and CO2 emissions in Neimenggu.

  15. Drawing Causal Inferences Using Propensity Scores: A Practical Guide for Community Psychologists

    OpenAIRE

    Lanza, Stephanie T.; Julia E Moore; Butera, Nicole M.

    2013-01-01

    Confounding present in observational data impede community psychologists’ ability to draw causal inferences. This paper describes propensity score methods as a conceptually straightforward approach to drawing causal inferences from observational data. A step-by-step demonstration of three propensity score methods – weighting, matching, and subclassification – is presented in the context of an empirical examination of the causal effect of preschool experiences (Head Start vs. parental care) on...

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

    Science.gov (United States)

    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.

  17. Causality between FDI and Financial Market Development: Evidence from Emerging Markets

    OpenAIRE

    Soumaré, Issouf; TCHANA TCHANA, Fulbert

    2011-01-01

    This paper studies the causal relationship between foreign direct investment (FDI) and financial market development (FMD) using panel data from emerging markets. Most studies of the relationship between FDI and FMD have focused on the role of FMD in the link between FDI and economic growth, with no deep understanding of direct causality between FDI and FMD, especially in emerging markets, where financial markets are in the development stage. We document bidirectional causality between FDI and...

  18. CAUSALITY AND DYNAMICS OF ENERGY CONSUMPTION AND OUTPUT: EVIDENCE FROM NON-OECD ASIAN COUNTRIES

    OpenAIRE

    RUHUL A. SALIM; Shuddhasattwa Rafiq; A. F. M. KAMRUL HASSAN

    2008-01-01

    This article examines the short-run and long-run causal relationship between energy consumption and output in six non-OECD Asian developing countries. Standard time series econometrics is used for this purpose. Based on cointegration and vector error correction modeling, the empirical result shows a bi-directional causality between energy consumption and income in Malaysia, while a unidirectional causality from output to energy consumption in China and Thailand and energy consumption to outpu...

  19. Recommendation for DSM-V: A Proposal for Adding Causal Specifiers to Axis I Diagnoses

    OpenAIRE

    Aboraya, Ahmed

    2010-01-01

    Causal specifiers are certain and possible causes of mental disorders and can be biological, genetic, environmental, developmental, social, psychodynamic, behavioral, cognitive, or personality characteristics. Depending upon the clinical judgment of the degree of certainty, a causal specifier can be a definite etiopathogenesis or a factor contributing to manifestations of mental disorders. The author recommends adding causal specifiers to Axis I diagnoses in the Diagnostic and Statistical Man...

  20. Atypicalities in Perceptual Adaptation in Autism Do Not Extend to Perceptual Causality

    OpenAIRE

    Themelis Karaminis; Marco Turi; Louise Neil; Badcock, Nicholas A.; David Burr; Elizabeth Pellicano

    2015-01-01

    A recent study showed that adaptation to causal events (collisions) in adults caused subsequent events to be less likely perceived as causal. In this study, we examined if a similar negative adaptation effect for perceptual causality occurs in children, both typically developing and with autism. Previous studies have reported diminished adaptation for face identity, facial configuration and gaze direction in children with autism. To test whether diminished adaptive coding exten...

  1. Normalizability analysis of the generalized quantum electrodynamics from the causal point of view

    OpenAIRE

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

    2015-01-01

    The causal perturbation theory is an axiomatic perturbative theory of the S-matrix. This formalism has as its essence the following axioms: causality, Lorentz invariance and asymptotic conditions. Any other property must be showed via the inductive method order-by-order and, of course, it depends on the particular physical model. In this work we shall study the normalizability of the generalized quantum electrodynamics in the framework of the causal approach. Furthermore, we analyse the impli...

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

    Directory of Open Access Journals (Sweden)

    Daniel eChicharro

    2014-07-01

    Full Text Available 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.

  3. A general solution for classical sequential growth dynamics of Causal Sets

    OpenAIRE

    Varadarajan, Madhavan; Rideout, David

    2005-01-01

    A classical precursor to a full quantum dynamics for causal sets has been forumlated in terms of a stochastic sequential growth process in which the elements of the causal set arise in a sort of accretion process. The transition probabilities of the Markov growth process satisfy certain physical requirements of causality and general covariance, and the generic solution with all transition probabilities non-zero has been found. Here we remove the assumption of non-zero probabilities, define a ...

  4. Causality between Foreign Direct Investment and Tourism : Empirical Evidence from India

    OpenAIRE

    Saroja Selvanathan; Selvanathan, E.A.; Brinda Viswanathan

    2009-01-01

    This paper investigates the causal link between foreign direct investment and tourism in India by employing the Granger causality test under a VAR framework. A one-way causality link is found from foreign direct investment to tourism in India. This evidence once again adds to the need for appropriate policies and plans to further expand and develop tourism given that FDI flow into India is expected to be strong in the coming years, bringing along a demand for tourism as well.

  5. Causal biological network database: a comprehensive platform of causal biological network models focused on the pulmonary and vascular systems.

    Science.gov (United States)

    Boué, Stéphanie; Talikka, Marja; Westra, Jurjen Willem; Hayes, William; Di Fabio, Anselmo; Park, Jennifer; Schlage, Walter K; Sewer, Alain; Fields, Brett; Ansari, Sam; Martin, Florian; Veljkovic, Emilija; Kenney, Renee; Peitsch, Manuel C; Hoeng, Julia

    2015-01-01

    With the wealth of publications and data available, powerful and transparent computational approaches are required to represent measured data and scientific knowledge in a computable and searchable format. We developed a set of biological network models, scripted in the Biological Expression Language, that reflect causal signaling pathways across a wide range of biological processes, including cell fate, cell stress, cell proliferation, inflammation, tissue repair and angiogenesis in the pulmonary and cardiovascular context. This comprehensive collection of networks is now freely available to the scientific community in a centralized web-based repository, the Causal Biological Network database, which is composed of over 120 manually curated and well annotated biological network models and can be accessed at http://causalbionet.com. The website accesses a MongoDB, which stores all versions of the networks as JSON objects and allows users to search for genes, proteins, biological processes, small molecules and keywords in the network descriptions to retrieve biological networks of interest. The content of the networks can be visualized and browsed. Nodes and edges can be filtered and all supporting evidence for the edges can be browsed and is linked to the original articles in PubMed. Moreover, networks may be downloaded for further visualization and evaluation. Database URL: http://causalbionet.com

  6. Intolerance of uncertainty, causal uncertainty, causal importance, self-concept clarity and their relations to generalized anxiety disorder.

    Science.gov (United States)

    Kusec, Andrea; Tallon, Kathleen; Koerner, Naomi

    2016-06-01

    Although numerous studies have provided support for the notion that intolerance of uncertainty plays a key role in pathological worry (the hallmark feature of generalized anxiety disorder (GAD)), other uncertainty-related constructs may also have relevance for the understanding of individuals who engage in pathological worry. Three constructs from the social cognition literature, causal uncertainty, causal importance, and self-concept clarity, were examined in the present study to assess the degree to which these explain unique variance in GAD, over and above intolerance of uncertainty. N = 235 participants completed self-report measures of trait worry, GAD symptoms, and uncertainty-relevant constructs. A subgroup was subsequently classified as low in GAD symptoms (n = 69) or high in GAD symptoms (n = 54) based on validated cut scores on measures of trait worry and GAD symptoms. In logistic regressions, only elevated intolerance of uncertainty and lower self-concept clarity emerged as unique correlates of high (vs. low) GAD symptoms. The possible role of self-concept uncertainty in GAD and the utility of integrating social cognition theories and constructs into clinical research on intolerance of uncertainty are discussed. PMID:27113431

  7. Of arrows and flows. Causality, determination, and specificity in the Central Dogma of molecular biology.

    Science.gov (United States)

    Fantini, Bernardino

    2006-01-01

    From its first proposal, the Central Dogma had a graphical form, complete with arrows of different types, and this form quickly became its standard presentation. In different scientific contexts, arrows have different meanings and in this particular case the arrows indicated the flow of information among different macromolecules. A deeper analysis illustrates that the arrows also imply a causal statement, directly connected to the causal role of genetic information. The author suggests a distinction between two different kinds of causal links, defined as 'physical causality' and 'biological determination', both implied in the production of biological specificity. PMID:18351053

  8. Causality analysis in business performance measurement system using system dynamics methodology

    Science.gov (United States)

    Yusof, Zainuridah; Yusoff, Wan Fadzilah Wan; Maarof, Faridah

    2014-07-01

    One of the main components of the Balanced Scorecard (BSC) that differentiates it from any other performance measurement system (PMS) is the Strategy Map with its unidirectional causality feature. Despite its apparent popularity, criticisms on the causality have been rigorously discussed by earlier researchers. In seeking empirical evidence of causality, propositions based on the service profit chain theory were developed and tested using the econometrics analysis, Granger causality test on the 45 data points. However, the insufficiency of well-established causality models was found as only 40% of the causal linkages were supported by the data. Expert knowledge was suggested to be used in the situations of insufficiency of historical data. The Delphi method was selected and conducted in obtaining the consensus of the causality existence among the 15 selected expert persons by utilizing 3 rounds of questionnaires. Study revealed that only 20% of the propositions were not supported. The existences of bidirectional causality which demonstrate significant dynamic environmental complexity through interaction among measures were obtained from both methods. With that, a computer modeling and simulation using System Dynamics (SD) methodology was develop as an experimental platform to identify how policies impacting the business performance in such environments. The reproduction, sensitivity and extreme condition tests were conducted onto developed SD model to ensure their capability in mimic the reality, robustness and validity for causality analysis platform. This study applied a theoretical service management model within the BSC domain to a practical situation using SD methodology where very limited work has been done.

  9. Causality tests between stock market development and economic growth in West African Monetary Union

    Directory of Open Access Journals (Sweden)

    Maman Tachiwou ABOUDOU

    2009-12-01

    Full Text Available This paper examines the causal relationship between stock market development and economic growth for the West African Monetary Union economy over the last decade or so. By applying the techniques of unit–root tests and the long–run Granger noncausality test proposed by Toda and Yamamoto (1995, the causal relationships between the real GDP growth rate and two stock market development proxies are tested. The results are in line with the supply leading hypothesis in the sense that there is strong causal flow from the stock market development to economic growth. A unidirectional causal relationship is also observed between real market capitalization ratio and economic growth.

  10. Is there a causal relation between mathematical creativity and mathematical problem-solving performance?

    Science.gov (United States)

    Tyagi, Tarun Kumar

    2016-04-01

    The relationship between mathematical creativity (MC) and mathematical problem-solving performance (MP) has often been studied but the causal relation between these two constructs has yet to be clearly reported. The main purpose of this study was to define the causal relationship between MC and MP. Data from a representative sample of 480 eighth-grade students were analysed using a cross-lagged panel correlation (CLPC) design. CLPC attempts to rule out plausible alternative explanation of a causal effect. The result suggests that significant predominant causal relationship was found between MC and MP. It indicates that MP was found to be a cause of MC than the converse.

  11. OPEC oil production and market fundamentals: a causality relationship

    International Nuclear Information System (INIS)

    This paper first establishes a statistical measurement for OPEC Member Countries' compliance levels with their respective quotas and then examines the correlations and the casual relationships between compliance levels and oil market fundamentals. The compliance level is measured by the deviation of the production level from the respective quota for OPEC Member Countries, and this is based on the Euclidean distance formula, while oil market fundamentals are represented by OECD oil demand and stock levels, and the OPEC Basket price and oil supply. Monthly data from January 1996 to June 2000 was used and two sub-periods considered, where the first sub-period was characterized by a low level of compliance and the second by a high level. The analytical results of correlations and causality showed different directions of relationships between compliance levels and oil market fundamentals. (author)

  12. Disaster forensics understanding root cause and complex causality

    CERN Document Server

    2016-01-01

    This book aims to uncover the root causes of natural and man-made disasters by going beyond the typical reports and case studies conducted post-disaster. It opens the black box of disasters by presenting ‘forensic analysis approaches’ to disasters, thereby revealing the complex causality that characterizes them and explaining how and why hazards do, or do not, become disasters. This yields ‘systemic’ strategies for managing disasters. Recently the global threat landscape has seen the emergence of high impact, low probability events. Events like Hurricane Katrina, the Great Japan Earthquake and tsunami, Hurricane Sandy, Super Typhoon Haiyan, global terrorist activities have become the new norm. Extreme events challenge our understanding regarding the interdependencies and complexity of the disaster aetiology and are often referred to as Black Swans. Between 2002 and 2011, there were 4130 disasters recorded that resulted from natural hazards around the world. In these, 1,117,527 people perished and a mi...

  13. The pivotal role of causality in local quantum physics

    Energy Technology Data Exchange (ETDEWEB)

    Schroer, Bert [Freie Univ. Berlin (Germany). Inst. fuer Theoretische Physik

    1999-04-01

    In this article an attempt is made to present very recent conceptual and computational developments in QFT as new manifestation of old well established physical principles. The vehicle for converting the quantum-algebraic aspects of local quantum physics into more classical geometric structures is the modular theory of Tomita. As the above named laureate together with his collaborator showed for the first time, in sufficient generality, its use in physics goes through Einstein causality. This line of research recently gained momentum when it was realized that it is not only of great structural and conceptual innovative power (see section 4), but also promises a new computational road into nonperturbative QFT (section 5) which, picturesquely speaking, enters the subject on the extreme opposite (noncommutative) side relative to (Lagrangian) quantization. (author)

  14. Granger causality stock market networks: Temporal proximity and preferential attachment

    Science.gov (United States)

    Výrost, Tomáš; Lyócsa, Štefan; Baumöhl, Eduard

    2015-06-01

    The structure of return spillovers is examined by constructing Granger causality networks using daily closing prices of 20 developed markets from 2nd January 2006 to 31st December 2013. The data is properly aligned to take into account non-synchronous trading effects. The study of the resulting networks of over 94 sub-samples revealed three significant findings. First, after the recent financial crisis the impact of the US stock market has declined. Second, spatial probit models confirmed the role of the temporal proximity between market closing times for return spillovers, i.e. the time distance between national stock markets matters. Third, a preferential attachment between stock markets exists, i.e. the probability of the presence of spillover effects between any given two markets increases with their degree of connectedness to others.

  15. Evolution of a universe filled with a causal viscous fluid

    CERN Document Server

    Chimento, Luis P

    2012-01-01

    The behaviour of solutions to the Einstein equations with a causal viscous fluid source is investigated. In this model we consider a spatially flat Robertson-Walker metric, the bulk viscosity coefficient is related to the energy density as $\\zeta = \\alpha \\rho^{m}$, and the relaxation time is given by $\\zeta/\\rho$. In the case $m = 1/2$ we find the exact solutions and we verify whether they satisfy the energy conditions. Besides, we study analytically the asymptotic stability of several families of solutions for arbitrary $m$. We find that the qualitative asymptotic behaviour in the far future is not altered by relaxation processes, but they change the behaviour in the past, introducing singular instead of deflationary evolutions or making the Universe bounce due to the violation of the energy conditions.

  16. Dynamical symmetries and causality in non-equilibrium phase transitions

    CERN Document Server

    Henkel, Malte

    2015-01-01

    Dynamical symmetries are of considerable importance in elucidating the complex behaviour of strongly interacting systems with many degrees of freedom. Paradigmatic examples are cooperative phenomena as they arise in phase transitions, where conformal invariance has led to enormous progress in equilibrium phase transitions, especially in two dimensions. Non-equilibrium phase transitions can arise in much larger portions of the parameter space than equilibrium phase transitions. The state of the art of recent attempts to generalise conformal invariance to a new generic symmetry, taking into account the different scaling behaviour of space and time, will be reviewed. Particular attention will be given to the causality properties as they follow for co-variant $n$-point functions. These are important for the physical identification of n-point functions as responses or correlators.

  17. Is XMRV a causal virus for prostate cancer?

    Institute of Scientific and Technical Information of China (English)

    Zhen-Zhen Zhang; Bao-Feng Guo; Zhuang Feng; Ling Zhang; Xue-Jian Zhao

    2011-01-01

    @@ The potential association between xenotropic murine leukaemia virus-related gammaretrovirus (XMRV) and prostate cancer (PCa) has been documented since 2006.It is important for furthering our understanding of the biological mechanisms of PCa to ascertain whether this association is causal.To summarize the available information on the epidemiological and laboratory findings of the association,we conducted a literature search of the PubMed electronic database (from March 2006 to February 2011) to identify relevant published studies that examined the association between XMRV and PCa.Although several studies showed the positive association between XMRV and PCa,more recent studies did not support this conclusion.The positive findings might be due to contamination of human samples.Further studies are needed to clarify this association.

  18. Causal Viscous Hydrodynamics for Relativistic Heavy Ion Collisions

    CERN Document Server

    Song, Huichao

    2009-01-01

    The viscosity of the QGP is a presently hotly debated subject. Since its computation from first principles is difficult, it is desirable to try to extract it from experimental data. Viscous hydrodynamics provides a tool that can attack this problem and which may work in regions where ideal hydrodynamics begins to fail. This thesis focuses on viscous hydrodynamics for relativistic heavy ion collisions. We first review the 2nd order viscous equations obtained from different approaches, and then report on the work of the Ohio State University group on setting up the equations for causal viscous hydrodynamics in 2+1 dimensions and solving them numerically for central and noncentral Cu+Cu and Au+Au collisions at RHIC energies and above. We discuss shear and bulk viscous effects on the hydrodynamic evolution of entropy density, temperature, collective flow, and flow anisotropies, and on the hadron multiplicity, single particle spectra and elliptic flow. Viscous entropy production and its influence on the centrality...

  19. Extrinsic curvature in 2-dimensional Causal Dynamical Triangulation

    CERN Document Server

    Glaser, Lisa; Weinfurtner, Silke

    2016-01-01

    Causal Dynamical Triangulations (CDT) is a non-perturbative quantisation of general relativity. Ho\\v{r}ava-Lifshitz gravity on the other hand modifies general relativity to allow for perturbative quan- tisation. Past work has given rise to the speculation that Ho\\v{r}ava-Lifshitz gravity might correspond to the continuum limit of CDT. In this paper we add another piece to this puzzle by applying the CDT quantisation prescription directly to Ho\\v{r}ava-Lifshitz gravity in 2 dimensions. We derive the continuum Hamiltonian and we show that it matches exactly the Hamiltonian one derives from canonically quantising the Ho\\v{r}ava-Lifshitz action. Unlike the standard CDT case, here the intro- duction of a foliated lattice does not impose further restriction on the configuration space and, as a result, lattice quantisation does not leave any imprint on continuum physics as expected.

  20. Causal Dynamical Triangulation of 3D Tensor Model

    CERN Document Server

    Kawabe, Hiroshi

    2016-01-01

    We extend the string field theory of the two dimensional (2D) generalized causal dynamical triangulation (GCDT) with the Ishibashi-Kawai (IK-) type interaction formulated by the matrix model, to the three dimensional (3D) model of the surface field theory. Based on the loop gas model, we construct a tensor model for the discretized surface field and then apply it the stochastic quantization method. In the double scaling limit, the model is characterized by two scaling dimensions $D$ and $D_N$, the power indices of the minimal length as the scaling parameter. The continuum GCDT model with the IK-type interaction is realized with the similar restriction in the $D_N$-$D$ space, to the 2D model. The distinct property in the 3D model is that the quantum effect contains the IK-type interaction only, while the ordinary splitting interaction is excluded.