Dynamic causal modelling revisited.
Friston, K J; Preller, Katrin H; Mathys, Chris; Cagnan, Hayriye; Heinzle, Jakob; Razi, Adeel; Zeidman, Peter
2017-02-17
This paper revisits the dynamic causal modelling of fMRI timeseries by replacing the usual (Taylor) approximation to neuronal dynamics with a neural mass model of the canonical microcircuit. This provides a generative or dynamic causal model of laminar specific responses that can generate haemodynamic and electrophysiological measurements. In principle, this allows the fusion of haemodynamic and (event related or induced) electrophysiological responses. Furthermore, it enables Bayesian model comparison of competing hypotheses about physiologically plausible synaptic effects; for example, does attentional modulation act on superficial or deep pyramidal cells - or both? In this technical note, we describe the resulting dynamic causal model and provide an illustrative application to the attention to visual motion dataset used in previous papers. Our focus here is on how to answer long-standing questions in fMRI; for example, do haemodynamic responses reflect extrinsic (afferent) input from distant cortical regions, or do they reflect intrinsic (recurrent) neuronal activity? To what extent do inhibitory interneurons contribute to neurovascular coupling? What is the relationship between haemodynamic responses and the frequency of induced neuronal activity? This paper does not pretend to answer these questions; rather it shows how they can be addressed using neural mass models of fMRI timeseries. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.
Revisiting Causality in Markov Chains
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,...
Causality in the Semantics of Esterel: Revisited
Mousavi, MohammadReza
2010-01-01
We re-examine the challenges concerning causality in the semantics of Esterel and show that they pertain to the known issues in the semantics of Structured Operational Semantics with negative premises. We show that the solutions offered for the semantics of SOS also provide answers to the semantic challenges of Esterel and that they satisfy the intuitive requirements set by the language designers.
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.
The metagenomic approach and causality in virology
Castrignano, Silvana Beres; Nagasse-Sugahara, Teresa Keico
2015-01-01
Nowadays, the metagenomic approach has been a very important tool in the discovery of new viruses in environmental and biological samples. Here we discuss how these discoveries may help to elucidate the etiology of diseases and the criteria necessary to establish a causal association between a virus and a disease. PMID:25902566
Finite quantum electrodynamics the causal approach
Scharf, Günter
2014-01-01
In this classic text for advanced undergraduates and graduate students of physics, author Günter Scharf carefully analyzes the role of causality in quantum electrodynamics. His approach offers full proofs and detailed calculations of scattering processes in a mathematically rigorous manner. This third edition contains Scharf's revisions and corrections plus a brief new Epilogue on gauge invariance of quantum electrodynamics to all orders. The book begins with Dirac's theory, followed by the quantum theory of free fields and causal perturbation theory, a powerful method that avoids ultraviolet divergences and solves the infrared problem by means of the adiabatic limit. Successive chapters explore properties of the S-matrix — such as renormalizability, gauge invariance, and unitarity — the renormalization group, and interactive fields. Additional topics include electromagnetic couplings and the extension of the methods to non-abelian gauge theories. Each chapter is supplemented with problems, and four appe...
Pearl, Judea
2000-03-01
Written by one of the pre-eminent researchers in the field, this book provides a comprehensive exposition of modern analysis of causation. It shows how causality has grown from a nebulous concept into a mathematical theory with significant applications in the fields of statistics, artificial intelligence, philosophy, cognitive science, and the health and social sciences. Pearl presents a unified account of the probabilistic, manipulative, counterfactual and structural approaches to causation, and devises simple mathematical tools for analyzing the relationships between causal connections, statistical associations, actions and observations. The book will open the way for including causal analysis in the standard curriculum of statistics, artifical intelligence, business, epidemiology, social science and economics. Students in these areas will find natural models, simple identification procedures, and precise mathematical definitions of causal concepts that traditional texts have tended to evade or make unduly complicated. This book will be of interest to professionals and students in a wide variety of fields. Anyone who wishes to elucidate meaningful relationships from data, predict effects of actions and policies, assess explanations of reported events, or form theories of causal understanding and causal speech will find this book stimulating and invaluable.
The stochastic system approach to causality with a view toward lifecourse epidemiology
Commenges, Daniel
2012-01-01
The approach of causality based on physical laws and systems is revisited. The issue of "levels", the relevance to epidemiology and the definition of effects are particularly developed. Moreover it is argued that this approach that we call the stochastic system approach is particularly well fitted to study lifecourse epidemiology. A hierarchy of factors is described that could be modeled using a suitable multivariate stochastic process. To illustrate this approach, a conceptual model for coronary heart disease mixing continuous and discrete state-space processes is proposed.
Guessing Revisited: A Large Deviations Approach
Hanawal, Manjesh Kumar
2010-01-01
The problem of guessing a random string is revisited. A close relation between guessing and compression is first established. Then it is shown that if the sequence of distributions of the information spectrum satisfies the large deviation property with a certain rate function, then the limiting guessing exponent exists and is a scalar multiple of the Legendre-Fenchel dual of the rate function. Other sufficient conditions related to certain continuity properties of the information spectrum are briefly discussed. This approach highlights the importance of the information spectrum in determining the limiting guessing exponent. All known prior results are then re-derived as example applications of our unifying approach.
Carbon Emissions and Economic Growth: Alternative Approaches to Causality Testing
Energy Technology Data Exchange (ETDEWEB)
Rehdanz, Katrin (Christian-Albrechts Univ., Kiel (Germany)); Maddison, David J. (Univ. of Birmingham, Dept. of Economics, Birmingham (United Kingdom))
2008-07-01
Numerous papers have examined data on energy and GDP for evidence of Granger causality. More recently this technique has been extended to looking at the relationship between carbon emissions and GDP per capita. These analyses frequently reach differing conclusions concerning the existence and direction of Granger causality. This paper compares the standard fixed-dynamic-effects approach to a heterogenous panel approach testing for evidence of a causal relationship between GDP per capita and carbon emissions per capita allowing for heterogeneity. Overall there is strong evidence for the existence of a bidirectional causal relationship between GDP per capita and CO{sub 2} emissions per capita
Antonakis, J.
2015-01-01
Making correct causal claims is important for research and practice. This article explains what causality is, and how it can be established via experimental design. Because experiments are infeasible in many applied settings, researchers often use "observational" methods to estimate causal models. In these situations, it is likely that model estimates are compromised by endogeneity. The article discusses the conditions that engender endogeneity and methods that can eliminate it.
'Mendelian randomization': an approach for exploring causal relations in epidemiology.
Gupta, V; Walia, G K; Sachdeva, M P
2017-04-01
To assess the current status of Mendelian randomization (MR) approach in effectively influencing the observational epidemiology for examining causal relationships. Narrative review on studies related to principle, strengths, limitations, and achievements of MR approach. Observational epidemiological studies have repeatedly produced several beneficiary associations which were discarded when tested by standard randomized controlled trials (RCTs). The technique which is more feasible, highly similar to RCTs, and has the potential to establish a causal relationship between modifiable exposures and disease outcomes is known as MR. The technique uses genetic variants related to modifiable traits/exposures as instruments for detecting causal and directional associations with outcomes. In the last decade, the approach of MR has methodologically developed and progressed to a stage of high acceptance among the epidemiologists and is gradually expanding the landscape of causal relationships in non-communicable chronic diseases. Copyright © 2016 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.
New Approaches to Establish Genetic Causality
McNally, Elizabeth M.; George, Alfred L.
2015-01-01
Cardiovascular medicine has evolved rapidly in the era of genomics with many diseases having primary genetic origins becoming the subject of intense investigation. The resulting avalanche of information on the molecular causes of these disorders has prompted a revolution in our understanding of disease mechanisms and provided new avenues for diagnoses. At the heart of this revolution is the need to correctly classify genetic variants discovered during the course of research or reported from clinical genetic testing. This review will address current concepts related to establishing the cause and effect relationship between genomic variants and heart diseases. A survey of general approaches used for functional annotation of variants will also be presented. PMID:25864169
Causal Information Approach to Partial Conditioning in Multivariate Data Sets
Directory of Open Access Journals (Sweden)
D. Marinazzo
2012-01-01
Full Text Available When evaluating causal influence from one time series to another in a multivariate data set it is necessary to take into account the conditioning effect of the other variables. In the presence of many variables and possibly of a reduced number of samples, full conditioning can lead to computational and numerical problems. In this paper, we address the problem of partial conditioning to a limited subset of variables, in the framework of information theory. The proposed approach is tested on simulated data sets and on an example of intracranial EEG recording from an epileptic subject. We show that, in many instances, conditioning on a small number of variables, chosen as the most informative ones for the driver node, leads to results very close to those obtained with a fully multivariate analysis and even better in the presence of a small number of samples. This is particularly relevant when the pattern of causalities is sparse.
A systematic approach to multifactorial cardiovascular disease: causal analysis.
Schwartz, Stephen M; Schwartz, Hillel T; Horvath, Steven; Schadt, Eric; Lee, Su-In
2012-12-01
The combination of systems biology and large data sets offers new approaches to the study of cardiovascular diseases. These new approaches are especially important for the common cardiovascular diseases that have long been described as multifactorial. This promise is undermined by biologists' skepticism of the spider web-like network diagrams required to analyze these large data sets. Although these spider webs resemble composites of the familiar biochemical pathway diagrams, the complexity of the webs is overwhelming. As a result, biologists collaborate with data analysts whose mathematical methods seem much like those of experts using Ouija boards. To make matters worse, it is not evident how to design experiments when the network implies that many molecules must be part of the disease process. Our goal is to remove some of this mystery and suggest a simple experimental approach to the design of experiments appropriate for such analysis. We will attempt to explain how combinations of data sets that include all possible variables, graphical diagrams, complementation of different data sets, and Bayesian analyses now make it possible to determine the causes of multifactorial cardiovascular disease. We will describe this approach using the term causal analysis. Finally, we will describe how causal analysis is already being used to decipher the interactions among cytokines as causes of cardiovascular disease.
Energy Technology Data Exchange (ETDEWEB)
Chiou-Wei, Song Zan [Department of Managerial Economics, Nan-Hua University, Chia-Yi (China); Chen, Ching-Fu [Department of Transportation and Communication Management Science, National Cheng Kung University, 1, Ta-Hsueh Road, Tainan, 701 (China); Zhu, Zhen [Department of Economics, College of Business, University of Central Oklahoma, Edmon, OK, 43034 (United States)
2008-11-15
The relationship between energy consumption and economic growth is considered as an imperative issue in energy economics. Previous studies have ignored the nonlinear behavior which could be caused by structural breaks. In this study, both linear and nonlinear Granger causality tests are applied to examine the causal relationship between energy consumption and economic growth for a sample of Asian newly industrialized countries as well as the U.S. This study finds evidence supporting a neutrality hypothesis for the United States, Thailand, and South Korea. However, empirical evidence on Philippines and Singapore reveals a unidirectional causality running from economic growth to energy consumption while energy consumption may have affected economic growth for Taiwan, Hong Kong, Malaysia and Indonesia. Policy implications are also discussed. (author)
Energy-income causality in OECD countries revisited: The key role of capital stock
Energy Technology Data Exchange (ETDEWEB)
Lee, Chien-Chiang [Department of Applied Economics, National Chung Hsing University, Taichung (China); Chang, Chun-Ping [Department of Business Administration, Shih Chien University Kaohsiung Campus, Kaohsiung (China); Chen, Pei-Fen [Department of International Business, National Chi Nan University, Taiwan, Nantou (China)
2008-09-15
This paper applies a recent advance in panel analysis to estimate the panel cointegration and panel vector error correction models for a set of 22 OECD countries using annual data covering the period 1960-2001. We investigate the relationship between energy consumption and income using an aggregate production function and controlling for the capital stock, as well as by exploring the dynamic directions of the causality among these three variables. We firstly obtain solid and convincing evidence of a fairly strong long-run equilibrium relationship among them. Secondly, it is found that the capital stock is much more productive than energy consumption. Third, it is observed that neglecting the impact of the capital stock on income tends to overestimate the effect of energy consumption. Finally, the panel causality test shows bi-directional causal linkages exist among energy consumption, the capital stock and economic growth. Overall, the findings reveal that the capital stock plays a critical role in realizing the dynamic relationship between energy and income. (author)
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.
A developmental approach to learning causal models for cyber security
Mugan, Jonathan
2013-05-01
To keep pace with our adversaries, we must expand the scope of machine learning and reasoning to address the breadth of possible attacks. One approach is to employ an algorithm to learn a set of causal models that describes the entire cyber network and each host end node. Such a learning algorithm would run continuously on the system and monitor activity in real time. With a set of causal models, the algorithm could anticipate novel attacks, take actions to thwart them, and predict the second-order effects flood of information, and the algorithm would have to determine which streams of that flood were relevant in which situations. This paper will present the results of efforts toward the application of a developmental learning algorithm to the problem of cyber security. The algorithm is modeled on the principles of human developmental learning and is designed to allow an agent to learn about the computer system in which it resides through active exploration. Children are flexible learners who acquire knowledge by actively exploring their environment and making predictions about what they will find,1, 2 and our algorithm is inspired by the work of the developmental psychologist Jean Piaget.3 Piaget described how children construct knowledge in stages and learn new concepts on top of those they already know. Developmental learning allows our algorithm to focus on subsets of the environment that are most helpful for learning given its current knowledge. In experiments, the algorithm was able to learn the conditions for file exfiltration and use that knowledge to protect sensitive files.
Causality between Regional Stock Markets: A Frequency Domain Approach
National Research Council Canada - National Science Library
Nikola Gradojevic; Eldin Dobardzic
2013-01-01
...), 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...
Crisis Typologies Revisited: An Interdisciplinary Approach
Directory of Open Access Journals (Sweden)
Albena Björck
2016-09-01
Full Text Available For effective crisis management and communication, a decision maker has to understand the causes and nature of a crisis and how it influences stakeholder perceptions. Identifying an organization’s vulnerabilities is essential for crisis prevention but practitioners often lack the ability to define crisis scenarios, especially the worst-case ones. A crisis typology is a structured approach to analyze crisis situations and to introduce measures for crisis prevention and containment. This paper aims to review recent literature on crisis classifications and to discuss their application. Because a single typology cannot capture the complexity and the interdisciplinary nature of a crisis, four relevant typologies from different disciplines are compared. Their combined application in an interdisciplinary framework is suggested. The paper discusses the need for typologies that reflect the cultural and contextual dimensions. Conclusions concerning the limitations and directions for further research are drawn.
Classical stochastic approach to cosmology revisited
Indian Academy of Sciences (India)
Moncy V John; C Sivakumar; K Babu Joseph
2003-01-01
The classical stochastic model of cosmology recently developed by us is reconsidered. In that approach the parameter deﬁned by the equation of state = wρ was taken to be ﬂuctuating with mean zero and we compared the theoretical probability distribution function (PDF) for the Hubble parameter with observational data corresponding to a universe with matter and vacuum energy. Even though qualitative agreement between the two was obtained, an attempt is herein made to introduce a more realistic assumption for the mean ofwand use it for the calculations. In the present theory the mean values of both and are taken to be nonzero. The theoretical and observational PDFs are compared for different epochs and values of the Hubble parameter. The corresponding values of the diffusion constant obtained are approximately constant. We use the scatter in the observed redshift-magnitude data of Type Ia supernova to place limits on the stochastic variation in expansion rate and consequently, on the stochastic variation of the equation of state.
Dark matter perturbations and viscosity: a causal approach
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.
A Bayesian approach to estimating causal vaccine effects on binary post-infection outcomes.
Zhou, Jincheng; Chu, Haitao; Hudgens, Michael G; Halloran, M Elizabeth
2016-01-15
To estimate causal effects of vaccine on post-infection outcomes, Hudgens and Halloran (2006) defined a post-infection causal vaccine efficacy estimand VEI based on the principal stratification framework. They also derived closed forms for the maximum likelihood estimators of the causal estimand under some assumptions. Extending their research, we propose a Bayesian approach to estimating the causal vaccine effects on binary post-infection outcomes. The identifiability of the causal vaccine effect VEI is discussed under different assumptions on selection bias. The performance of the proposed Bayesian method is compared with the maximum likelihood method through simulation studies and two case studies - a clinical trial of a rotavirus vaccine candidate and a field study of pertussis vaccination. For both case studies, the Bayesian approach provided similar inference as the frequentist analysis. However, simulation studies with small sample sizes suggest that the Bayesian approach provides smaller bias and shorter confidence interval length.
What kind of causal modelling approach does personality research need?
Borsboom, D.; van der Sluis, S.; Noordhof, A.; Wichers, M.; Geschwind, N.; Aggen, S.H.; Kendler, K.S.; Cramer, A.O.J.
2012-01-01
Lee (2012) proposes that personality research should utilise recent theories of causality. Although we agree that such theories are important, we also note that their empirical application has not been very successful to date. The reason may be that psychological systems are frequently characterised
Renormalization group approach to causal bulk viscous cosmological models
Energy Technology Data Exchange (ETDEWEB)
Belinchon, J A [Grupo Inter-Universitario de Analisis Dimensional, Dept. Fisica ETS Arquitectura UPM, Av. Juan de Herrera 4, Madrid (Spain); Harko, T [Department of Physics, University of Hong Kong, Pokfulam Road, Hong Kong (China); Mak, M K [Department of Physics, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong (China)
2002-06-07
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.
Measuring causality by taking the directional symbolic mutual information approach
Institute of Scientific and Technical Information of China (English)
Chen Gui; Xie Lei; Chu Jian
2013-01-01
We propose a novel measure to assess causality through the comparison of symbolic mutual information between the future of one random quantity and the past of the other.This provides a new perspective that is different from the conventional conceptions.Based on this point of view,a new causality index is derived that uses the definition of directional symbolic mutual information.This measure presents properties that are different from the time delayed mutual information since the symbolization captures the dynamic features of the analyzed time series.In addition to characterizing the direction and the amplitude of the information flow,it can also detect coupling delays.This method has the property of robustness,conceptual simplicity,and fast computational speed.
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.
Scientific realism in particle physics a causal approach
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.
Heckman, James J.
2008-01-01
This paper presents the econometric approach to causal modeling. It is motivated by policy problems. New causal parameters are defined and identified to address specific policy problems. Economists embrace a scientific approach to causality and model the preferences and choices of agents to infer subjective (agent) evaluations as well as objective outcomes. Anticipated and realized subjective and objective outcomes are distinguished. Models for simultaneous causality are developed. The paper ...
Locality and causality revisited
Kent, A
2002-01-01
Bell gave the now standard definition of a local hidden variable theory and showed that such theories cannot reproduce the predictions of quantum mechanics without violating his ``free will'' criterion: experimenters' measurement choices can be assumed to be uncorrelated with properties of the measured system prior to measurement. An alternative is considered here: a probabilistic theory of hidden variables underlying quantum mechanics could be statistically local, in the sense that it supplies global configuration probabilities which are defined by expressions involving only local terms. This allows Bell correlations without relying on {\\it either} a conspiracy theory in which prior common causes correlate the system state with experimenters' choices {\\it or} a reverse causation principle in which experimenters' choices affect the earlier system states. In particular, there is no violation of the free will criterion. It gives a different perspective on Bell correlations, in which the puzzle is not that appar...
Directory of Open Access Journals (Sweden)
Lin Hung-Pin
2014-01-01
Full Text Available The purpose of this paper is to investigate the short-run and long-run causality between renewable energy (RE consumption and economic growth (EG in nine OECD countries from the period between 1982 and 2011. To examine the linkage, this paper uses the autoregressive distributed lag (ARDL bounds testing approach of cointegration test and vector error-correction models to test the causal relationship between variables. The co-integration and causal relationships are found in five countries—United States of America (USA, Japan, Germany, Italy, and United Kingdom (UK. The overall results indicate that (1 a short-run unidirectional causality runs from EG to RE in Italy and UK; (2 long-run unidirectional causalities run from RE to EG for Germany, Italy, and UK; (3 a long-run unidirectional causality runs from EG to RE in USA, and Japan; (4 both long-run and strong unidirectional causalities run from RE to EG for Germany and UK; and (5 Finally, both long-run and strong unidirectional causalities run from EG to RE in only USA. Further evidence reveals that policies for renewable energy conservation may have no impact on economic growth in France, Denmark, Portugal, and Spain.
Hung-Pin, Lin
2014-01-01
The purpose of this paper is to investigate the short-run and long-run causality between renewable energy (RE) consumption and economic growth (EG) in nine OECD countries from the period between 1982 and 2011. To examine the linkage, this paper uses the autoregressive distributed lag (ARDL) bounds testing approach of cointegration test and vector error-correction models to test the causal relationship between variables. The co-integration and causal relationships are found in five countries-United States of America (USA), Japan, Germany, Italy, and United Kingdom (UK). The overall results indicate that (1) a short-run unidirectional causality runs from EG to RE in Italy and UK; (2) long-run unidirectional causalities run from RE to EG for Germany, Italy, and UK; (3) a long-run unidirectional causality runs from EG to RE in USA, and Japan; (4) both long-run and strong unidirectional causalities run from RE to EG for Germany and UK; and (5) Finally, both long-run and strong unidirectional causalities run from EG to RE in only USA. Further evidence reveals that policies for renewable energy conservation may have no impact on economic growth in France, Denmark, Portugal, and Spain.
An Adaptive and Hybrid Approach for Revisiting the Visibility Pipeline
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Ícaro Lins Leitão da Cunha
2016-04-01
Full Text Available We revisit the visibility problem, which is traditionally known in Computer Graphics and Vision fields as the process of computing a (potentially visible set of primitives in the computational model of a scene. We propose a hybrid solution that uses a dry structure (in the sense of data reduction, a triangulation of the type J1a, to accelerate the task of searching for visible primitives. We came up with a solution that is useful for real-time, on-line, interactive applications as 3D visualization. In such applications the main goal is to load the minimum amount of primitives from the scene during the rendering stage, as possible. For this purpose, our algorithm executes the culling by using a hybrid paradigm based on viewing-frustum, back-face culling and occlusion models. Results have shown substantial improvement over these traditional approaches if applied separately. This novel approach can be used in devices with no dedicated processors or with low processing power, as cell phones or embedded displays, or to visualize data through the Internet, as in virtual museums applications.
Do trend extraction approaches affect causality detection in climate change studies?
Huang, Xu; Hassani, Hossein; Ghodsi, Mansi; Mukherjee, Zinnia; Gupta, Rangan
2017-03-01
Various scientific studies have investigated the causal link between solar activity (SS) and the earth's temperature (GT). Results from literature indicate that both the detected structural breaks and existing trend have significant effects on the causality detection outcomes. In this paper, we make a contribution to this literature by evaluating and comparing seven trend extraction methods covering various aspects of trend extraction studies to date. In addition, we extend previous work by using Convergent Cross Mapping (CCM) - an advanced non-parametric causality detection technique to provide evidence on the effect of existing trend in global temperature on the causality detection outcome. This paper illustrates the use of a method to find the most reliable trend extraction approach for data preprocessing, as well as provides detailed analyses of the causality detection of each component by this approach to achieve a better understanding of the causal link between SS and GT. Furthermore, the corresponding CCM results indicate increasing significance of causal effect from SS to GT since 1880 to recent years, which provide solid evidences that may contribute on explaining the escalating global tendency of warming up recent decades.
Monteiro, Wuelton Marcelo; Alexandre, Márcia Araújo; Siqueira, André; Melo, Gisely; Romero, Gustavo Adolfo Sierra; d'Ávila, Efrem; Benzecry, Silvana Gomes; Leite, Heitor Pons; Lacerda, Marcus Vinícius Guimarães
2016-01-01
The benign characteristics formerly attributed to Plasmodium vivax infections have recently changed owing to the increasing number of reports of severe vivax malaria resulting in a broad spectrum of clinical complications, probably including undernutrition. Causal inference is a complex process, and arriving at a tentative inference of the causal or non-causal nature of an association is a subjective process limited by the existing evidence. Applying classical epidemiology principles, such as the Bradford Hill criteria, may help foster an understanding of causality and lead to appropriate interventions being proposed that may improve quality of life and decrease morbidity in neglected populations. Here, we examined these criteria in the context of the available data suggesting that vivax malaria may substantially contribute to childhood malnutrition. We found the data supported a role for P. vivax in the etiology of undernutrition in endemic areas. Thus, the application of modern causal inference tools, in future studies, may be useful in determining causation.
Directory of Open Access Journals (Sweden)
Wuelton Marcelo Monteiro
2016-06-01
Full Text Available Abstract: The benign characteristics formerly attributed to Plasmodium vivax infections have recently changed owing to the increasing number of reports of severe vivax malaria resulting in a broad spectrum of clinical complications, probably including undernutrition. Causal inference is a complex process, and arriving at a tentative inference of the causal or non-causal nature of an association is a subjective process limited by the existing evidence. Applying classical epidemiology principles, such as the Bradford Hill criteria, may help foster an understanding of causality and lead to appropriate interventions being proposed that may improve quality of life and decrease morbidity in neglected populations. Here, we examined these criteria in the context of the available data suggesting that vivax malaria may substantially contribute to childhood malnutrition. We found the data supported a role for P. vivax in the etiology of undernutrition in endemic areas. Thus, the application of modern causal inference tools, in future studies, may be useful in determining causation.
Energy Technology Data Exchange (ETDEWEB)
Shahbaz, Muhammad [COMSATS Institute of Information Technology, Lahore (Pakistan); Tang, Chor Foon, E-mail: tcfoon@yahoo.com [Department of Economics, Faculty of Economics and Administration, University of Malaya, 50603 Kuala Lumpur (Malaysia); Shahbaz Shabbir, Muhammad [University of Illinois at Urbana-Champaign, Champaign (United States)
2011-06-15
The aim of this paper is to re-examine the relationship between electricity consumption, economic growth, and employment in Portugal using the cointegration and Granger causality frameworks. This study covers the sample period from 1971 to 2009. We examine the presence of a long-run equilibrium relationship using the bounds testing approach to cointegration within the Unrestricted Error-Correction Model (UECM). Moreover, we examine the direction of causality between electricity consumption, economic growth, and employment in Portugal using the Granger causality test within the Vector Error-Correction Model (VECM). As a summary of the empirical findings, we find that electricity consumption, economic growth, and employment in Portugal are cointegrated and there is bi-directional Granger causality between the three variables in the long-run. With the exception of the Granger causality between electricity consumption and economic growth, the rest of the variables are also bi-directional Granger causality in the short-run. Furthermore, we find that there is unidirectional Granger causality running from economic growth to electricity consumption, but no evidence of reversal causality. - Highlights: > We re-examine the relationship between electricity consumption, economic growth, and employment in Portugal. > The electricity consumption and economic growth is causing each other in the long-run. > In the short-run, economic growth Granger-cause electricity consumption, but no evidence of reversal causality. > Energy conservation policy will deteriorate the process of economic growth in the long-run. > Portugal should increase investment on R and D to design new energy savings technology.
Richards, P.
2011-01-01
Many accounts of cultural factors in armed conflicts are dependent on circumstantial details. Alternative quantitative approaches suffer from confusion of correlation and cause. This paper describes and exemplifies a third approach to the analysis of cultural factors in war—causal process tracing.
Richards, P.
2011-01-01
Many accounts of cultural factors in armed conflicts are dependent on circumstantial details. Alternative quantitative approaches suffer from confusion of correlation and cause. This paper describes and exemplifies a third approach to the analysis of cultural factors in war—causal process tracing. S
Directory of Open Access Journals (Sweden)
Tian Ge
2009-11-01
Full Text Available Two main approaches in exploring causal relationships in biological systems using time-series data are the application of Dynamic Causal model (DCM and Granger Causal model (GCM. These have been extensively applied to brain imaging data and are also readily applicable to a wide range of temporal changes involving genes, proteins or metabolic pathways. However, these two approaches have always been considered to be radically different from each other and therefore used independently. Here we present a novel approach which is an extension of Granger Causal model and also shares the features of the bilinear approximation of Dynamic Causal model. We have first tested the efficacy of the extended GCM by applying it extensively in toy models in both time and frequency domains and then applied it to local field potential recording data collected from in vivo multi-electrode array experiments. We demonstrate face discrimination learning-induced changes in inter- and intra-hemispheric connectivity and in the hemispheric predominance of theta and gamma frequency oscillations in sheep inferotemporal cortex. The results provide the first evidence for connectivity changes between and within left and right inferotemporal cortexes as a result of face recognition learning.
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Lina Zgaga
Full Text Available Vitamin D deficiency has been associated with increased risk of colorectal cancer (CRC, but causal relationship has not yet been confirmed. We investigate the direction of causation between vitamin D and CRC by extending the conventional approaches to allow pleiotropic relationships and by explicitly modelling unmeasured confounders.Plasma 25-hydroxyvitamin D (25-OHD, genetic variants associated with 25-OHD and CRC, and other relevant information was available for 2645 individuals (1057 CRC cases and 1588 controls and included in the model. We investigate whether 25-OHD is likely to be causally associated with CRC, or vice versa, by selecting the best modelling hypothesis according to Bayesian predictive scores. We examine consistency for a range of prior assumptions.Model comparison showed preference for the causal association between low 25-OHD and CRC over the reverse causal hypothesis. This was confirmed for posterior mean deviances obtained for both models (11.5 natural log units in favour of the causal model, and also for deviance information criteria (DIC computed for a range of prior distributions. Overall, models ignoring hidden confounding or pleiotropy had significantly poorer DIC scores.Results suggest causal association between 25-OHD and colorectal cancer, and support the need for randomised clinical trials for further confirmations.
Mendelian Randomization as an Approach to Assess Causality Using Observational Data.
Sekula, Peggy; Del Greco M, Fabiola; Pattaro, Cristian; Köttgen, Anna
2016-11-01
Mendelian randomization refers to an analytic approach to assess the causality of an observed association between a modifiable exposure or risk factor and a clinically relevant outcome. It presents a valuable tool, especially when randomized controlled trials to examine causality are not feasible and observational studies provide biased associations because of confounding or reverse causality. These issues are addressed by using genetic variants as instrumental variables for the tested exposure: the alleles of this exposure-associated genetic variant are randomly allocated and not subject to reverse causation. This, together with the wide availability of published genetic associations to screen for suitable genetic instrumental variables make Mendelian randomization a time- and cost-efficient approach and contribute to its increasing popularity for assessing and screening for potentially causal associations. An observed association between the genetic instrumental variable and the outcome supports the hypothesis that the exposure in question is causally related to the outcome. This review provides an overview of the Mendelian randomization method, addresses assumptions and implications, and includes illustrative examples. We also discuss special issues in nephrology, such as inverse risk factor associations in advanced disease, and outline opportunities to design Mendelian randomization studies around kidney function and disease. Copyright © 2016 by the American Society of Nephrology.
Shadish, William R.
2010-01-01
This article compares Donald Campbell's and Donald Rubin's work on causal inference in field settings on issues of epistemology, theories of cause and effect, methodology, statistics, generalization, and terminology. The two approaches are quite different but compatible, differing mostly in matters of bandwidth versus fidelity. Campbell's work…
Shadish, William R.
2010-01-01
This article compares Donald Campbell's and Donald Rubin's work on causal inference in field settings on issues of epistemology, theories of cause and effect, methodology, statistics, generalization, and terminology. The two approaches are quite different but compatible, differing mostly in matters of bandwidth versus fidelity. Campbell's work…
Gul, Sehrish; Zou, Xiang; Hassan, Che Hashim; Azam, Muhammad; Zaman, Khalid
2015-12-01
This study investigates the relationship between energy consumption and carbon dioxide emission in the causal framework, as the direction of causality remains has a significant policy implication for developed and developing countries. The study employed maximum entropy bootstrap (Meboot) approach to examine the causal nexus between energy consumption and carbon dioxide emission using bivariate as well as multivariate framework for Malaysia, over a period of 1975-2013. This is a unified approach without requiring the use of conventional techniques based on asymptotical theory such as testing for possible unit root and cointegration. In addition, it can be applied in the presence of non-stationary of any type including structural breaks without any type of data transformation to achieve stationary. Thus, it provides more reliable and robust inferences which are insensitive to time span as well as lag length used. The empirical results show that there is a unidirectional causality running from energy consumption to carbon emission both in the bivariate model and multivariate framework, while controlling for broad money supply and population density. The results indicate that Malaysia is an energy-dependent country and hence energy is stimulus to carbon emissions.
Institute of Scientific and Technical Information of China (English)
吕思琪
2013-01-01
This paper intends to analyze the six types of English imperative sentences proposed by Chen (1984) from a perspective of causal-chain windowing. It comes to the conclusions that Talmy’s causal-chain windowing approach as well as the cognitive underpinnings of causal windowing and gapping is proved to be applicable in English imperative structures, and that generally speaking, the final portion of an imperative sentence is always windowed while the intermediate portions gapped.
Lannoy, N; Abinet, I; Bosmans, A; Lambert, C; Vermylen, C; Hermans, C
2012-05-01
Haemophilia A (HA) is caused by widespread mutations in the factor VIII gene. The high spontaneous mutation rate of this gene means that roughly 40% of HA mutations are private. This study aimed to describe the approaches used to confirm private disease-causing mutations in a cohort of Belgian HA patients. We studied 148 unrelated HA families for the presence of intron 22 and intron 1 inversion by Southern blotting and polymerase chain reaction (PCR). Multiplex ligation-dependent probe amplification (MLPA) assay was used to detect large genomic rearrangements. Detection of point mutations was performed by DNA sequencing. Predicting the causal impact of new non-synonymous changes was studied by two general strategies: (i) molecular approaches such as family cosegregation, evaluation of the implicated codon based on phylogenic separated species and absence of the mutation in the general Belgian population, and (ii) bioinformatics approaches to analyse the potential functional consequences of missense mutations. Among the 148 HA patients, in addition to common intron 22 and intron 1 inversions as well as large deletions or duplications, 67 different point mutations were identified, of which 42 had been reported in the HAMSTeRS database, and 25 were novel including 10 null variants for which RNA analyses confirmed the causal effect of mutations located in a splice site consensus and 15 missense mutations whose causality was demonstrated by molecular approaches and bioinformatics. This article reports several strategies to evaluate the deleterious consequences of unreported F8 substitutions in a large cohort of HA patients.
Moura, Lidia Mvr; Westover, M Brandon; Kwasnik, David; Cole, Andrew J; Hsu, John
2017-01-01
The elderly population faces an increasing number of cases of chronic neurological conditions, such as epilepsy and Alzheimer's disease. Because the elderly with epilepsy are commonly excluded from randomized controlled clinical trials, there are few rigorous studies to guide clinical practice. When the elderly are eligible for trials, they either rarely participate or frequently have poor adherence to therapy, thus limiting both generalizability and validity. In contrast, large observational data sets are increasingly available, but are susceptible to bias when using common analytic approaches. Recent developments in causal inference-analytic approaches also introduce the possibility of emulating randomized controlled trials to yield valid estimates. We provide a practical example of the application of the principles of causal inference to a large observational data set of patients with epilepsy. This review also provides a framework for comparative-effectiveness research in chronic neurological conditions.
Merlo, Juan; Ohlsson, Henrik; Chaix, Basile; Lichtenstein, Paul; Kawachi, Ichiro; Subramanian, S V
2013-01-01
Neighborhood socioeconomic disadvantage is associated to increased individual risk of ischemic heart disease (IHD). However, the value of this association for causal inference is uncertain. Moreover, neighborhoods are often defined by available administrative boundaries without evaluating in which degree these boundaries embrace a relevant socio-geographical context that condition individual differences in IHD risk. Therefore, we performed an analysis of variance, and also compared the associations obtained by conventional multilevel analyses and by quasi-experimental family-based design that provides stronger evidence for causal inference. Linking the Swedish Multi-Generation Register to several other national registers, we analyzed 184,931 families embracing 415,540 full brothers 45-64 years old in 2004, and residing in 8408 small-area market statistics (SAMS) considered as "neighborhoods" in our study. We investigated the association between low neighborhood income (categorized in groups by deciles) and IHD risk in the next four years. We distinguished between family mean and intrafamilial-centered low neighborhood income, which allowed us to investigate both unrelated individuals from different families and full brothers within families. We applied multilevel logistic regression techniques to obtain odds ratios (OR), variance partition coefficients (VPC) and 95% credible intervals (CI). In unrelated individuals a decile unit increase of low neighborhood income increased individual IHD risk (OR = 1.04, 95% CI: 1.03-1.07). In the intrafamilial analysis this association was reduced (OR = 1.02, 95% CI: 1.02-1.04). Low neighborhood income seems associated with IHD risk in middle-aged men. However, despite the family-based design, we cannot exclude residual confounding by genetic and non-shared environmental factors. Besides, the low neighborhood level VPC = 1.5% suggest that the SAMS are a rather inappropriate construct of the socio-geographic context that
RNS derivation of N-point disk amplitudes from the revisited S-matrix approach
Energy Technology Data Exchange (ETDEWEB)
Barreiro, Luiz Antonio, E-mail: luiz.a.barreiro@gmail.com [Departamento de Física, UNESP, Rio Claro, São Paulo (Brazil); Instituto de Matemática e Computação, Universidade Federal de Itajubá, Itajubá, Minas Gerais (Brazil); Medina, Ricardo, E-mail: rmedina50@gmail.com [Instituto de Matemática e Computação, Universidade Federal de Itajubá, Itajubá, Minas Gerais (Brazil)
2014-09-15
Recently, in [7] we proposed a revisited S-matrix approach to efficiently find the bosonic terms of the open superstring low energy effective lagrangian (OSLEEL). This approach allows to compute the α{sup ′N} terms of the OSLEEL using open superstring n-point amplitudes in which n is considerably lower than (N+2) (which is the order of the required amplitude to obtain those α{sup ′N} terms by means of the conventional S-matrix approach). In this work we use our revisited S-matrix approach to examine the structure of the scattering amplitudes, arriving at a closed form for them. This is a RNS derivation of the formula first found by Mafra, Schlotterer and Stieberger [21], using the pure spinor formalism. We have succeeded doing this for the 5, 6 and 7-point amplitudes. In order to achieve these results we have done a careful analysis of the kinematical structure of the amplitudes, finding as a by-product a purely kinematical derivation of the BCJ relations (for N=4,5,6 and 7). Also, following the spirit of the revisited S-matrix approach, we have found the α{sup ′} expansions for these amplitudes up to α{sup ′6} order in some cases, by only using the well known open superstring 4-point amplitude, cyclic symmetry and tree level unitarity: we have not needed to compute any numerical series or any integral involving polylogarithms, at any moment.
RNS derivation of N-point disk amplitudes from the revisited S-matrix approach
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Luiz Antonio Barreiro
2014-09-01
Full Text Available Recently, in [7] we proposed a revisited S-matrix approach to efficiently find the bosonic terms of the open superstring low energy effective lagrangian (OSLEEL. This approach allows to compute the α′N terms of the OSLEEL using open superstring n-point amplitudes in which n is considerably lower than (N+2 (which is the order of the required amplitude to obtain those α′N terms by means of the conventional S-matrix approach. In this work we use our revisited S-matrix approach to examine the structure of the scattering amplitudes, arriving at a closed form for them. This is a RNS derivation of the formula first found by Mafra, Schlotterer and Stieberger [21], using the pure spinor formalism. We have succeeded doing this for the 5, 6 and 7-point amplitudes. In order to achieve these results we have done a careful analysis of the kinematical structure of the amplitudes, finding as a by-product a purely kinematical derivation of the BCJ relations (for N=4,5,6 and 7. Also, following the spirit of the revisited S-matrix approach, we have found the α′ expansions for these amplitudes up to α′6 order in some cases, by only using the well known open superstring 4-point amplitude, cyclic symmetry and tree level unitarity: we have not needed to compute any numerical series or any integral involving polylogarithms, at any moment.
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Moura LMVR
2016-12-01
Full Text Available Lidia MVR Moura,1,2 M Brandon Westover,1,2 David Kwasnik,1 Andrew J Cole,1,2 John Hsu3–5 1Massachusetts General Hospital, Department of Neurology, Epilepsy Service, Boston, MA, USA; 2Harvard Medical School, Boston, MA, USA; 3Massachusetts General Hospital, Mongan Institute, Boston, MA, USA; 4Harvard Medical School, Department of Medicine, Boston, MA, USA; 5Harvard Medical School, Department of Health Care Policy, Boston, MA, USA Abstract: The elderly population faces an increasing number of cases of chronic neurological conditions, such as epilepsy and Alzheimer’s disease. Because the elderly with epilepsy are commonly excluded from randomized controlled clinical trials, there are few rigorous studies to guide clinical practice. When the elderly are eligible for trials, they either rarely participate or frequently have poor adherence to therapy, thus limiting both generalizability and validity. In contrast, large observational data sets are increasingly available, but are susceptible to bias when using common analytic approaches. Recent developments in causal inference-analytic approaches also introduce the possibility of emulating randomized controlled trials to yield valid estimates. We provide a practical example of the application of the principles of causal inference to a large observational data set of patients with epilepsy. This review also provides a framework for comparative-effectiveness research in chronic neurological conditions. Keywords: epilepsy, epidemiology, neurostatistics, causal inference
Cognitive Structure of Climate Information System Actors:Using Causal Mapping Approach
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Maryam Sharifzadeh
2012-01-01
Full Text Available Promoting sustainability, productivity, efficiency, and development of agricultural sector are the functions of utilization of appropriate information in terms of agricultural climate information system (ACIS. In this regard, the main question is that, to what extent does the ACIS lead to or provide the necessary context for agricultural development? This research aimed to employ causal mapping approach to investigate cognitive structure of human actors in a climate information system. This explorative qualitative research used case study methodology. This paper is an examination and reflection upon analysis of qualitative data reports, with particular attention to the process of interactively elicited causal maps based on focus group interviews. An exploratory coding approach was used to identify concepts that emerged from the interview transcripts. The relevant knowledge is gathered through the tacit understandings of climate information producers (2 groups, extensionists (6 groups, and users (7 groups in Fars province to reach to the point of redundancy. Investigating causal maps revealed that, actors perceived climate information system challenges as economic, information processing, socio-political, organizational, and technical challenges. The study provided some suggestions to reach to a responsive short term and sustainable long term climate information system in Fars province.
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Guo Shuixia
2010-06-01
Full Text Available Abstract Background Reverse-engineering approaches such as Bayesian network inference, ordinary differential equations (ODEs and information theory are widely applied to deriving causal relationships among different elements such as genes, proteins, metabolites, neurons, brain areas and so on, based upon multi-dimensional spatial and temporal data. There are several well-established reverse-engineering approaches to explore causal relationships in a dynamic network, such as ordinary differential equations (ODE, Bayesian networks, information theory and Granger Causality. Results Here we focused on Granger causality both in the time and frequency domain and in local and global networks, and applied our approach to experimental data (genes and proteins. For a small gene network, Granger causality outperformed all the other three approaches mentioned above. A global protein network of 812 proteins was reconstructed, using a novel approach. The obtained results fitted well with known experimental findings and predicted many experimentally testable results. In addition to interactions in the time domain, interactions in the frequency domain were also recovered. Conclusions The results on the proteomic data and gene data confirm that Granger causality is a simple and accurate approach to recover the network structure. Our approach is general and can be easily applied to other types of temporal data.
Energy Technology Data Exchange (ETDEWEB)
Wolde-Rufael, Yemane
2010-01-15
This paper attempts to examine the dynamic relationship between economic growth, nuclear energy consumption, labor and capital for India for the period 1969-2006. Applying the bounds test approach to cointegration developed by we find that there was a short- and a long-run relationship between nuclear energy consumption and economic growth. Using four long-run estimators we also found that nuclear energy consumption has a positive and a statistically significant impact on India's economic growth. Further, applying the approach to Granger causality and the variance decomposition approach developed by, we found a positive and a significant uni-directional causality running from nuclear energy consumption to economic growth without feedback. This implies that economic growth in India is dependent on nuclear energy consumption where a decrease in nuclear energy consumption may lead to a decrease in real income. For a fast growing energy-dependent economy this may have far-reaching implications for economic growth. India's economic growth can be frustrated if energy conservation measures are undertaken without due regard to the negative impact they have on economic growth. (author)
Combining FDI and AI approaches within causal-model-based diagnosis.
Gentil, Sylviane; Montmain, Jacky; Combastel, Christophe
2004-10-01
This paper presents a model-based diagnostic method designed in the context of process supervision. It has been inspired by both artificial intelligence and control theory. AI contributes tools for qualitative modeling, including causal modeling, whose aim is to split a complex process into elementary submodels. Control theory, within the framework of fault detection and isolation (FDI), provides numerical models for generating and testing residuals, and for taking into account inaccuracies in the model, unknown disturbances and noise. Consistency-based reasoning provides a logical foundation for diagnostic reasoning and clarifies fundamental assumptions, such as single fault and exoneration. The diagnostic method presented in the paper benefits from the advantages of all these approaches. Causal modeling enables the method to focus on sufficient relations for fault isolation, which avoids combinatorial explosion. Moreover, it allows the model to be modified easily without changing any aspect of the diagnostic algorithm. The numerical submodels that are used to detect inconsistency benefit from the precise quantitative analysis of the FDI approach. The FDI models are studied in order to link this method with DX component-oriented reasoning. The recursive on-line use of this algorithm is explained and the concept of local exoneration is introduced.
An Isometric Dynamics for a Causal Set Approach to Discrete Quantum Gravity
Gudder, Stan
2014-01-01
We consider a covariant causal set approach to discrete quantum gravity. We first review the microscopic picture of this approach. In this picture a universe grows one element at a time and its geometry is determined by a sequence of integers called the shell sequence. We next present the macroscopic picture which is described by a sequential growth process. We introduce a model in which the dynamics is governed by a quantum transition amplitude. The amplitude satisfies a stochastic and unitary condition and the resulting dynamics becomes isometric. We show that the dynamics preserves stochastic states. By "doubling down" on the dynamics we obtain a unitary group representation and a natural energy operator. These unitary operators are employed to define canonical position and momentum operators.
Emergence of Four Dimensions in the Causal Set Approach to Discrete Quantum Gravity
Gudder, Stan
2015-01-01
One could begin a study like the present one by simply postulating that our universe is four-dimensional. There are ample reasons for doing this. Experience, observation and experiment all point to the fact that we inhabit a four-dimensional universe. Another approach would be to show that four-dimensions arise naturally from a reasonable model of the universe or multiverse. After reviewing the causal set approach to discrete quantum gravity in Section~1, we shall discuss the emergence of four-dimensions in Section~2. We shall see that certain patterns of four arise that suggest the introduction of a 4-dimensional discrete manifold. In the later sections we shall discuss some consequences of this introduced framework. In particular, we will show that quantum amplitudes can be employed to describe a multiverse dynamics. Moreover, a natural unitary operator together with energy, position and momentum operators will be introduced and their properties studied.
DEFF Research Database (Denmark)
Kogelman, Lisette; Zhernakova, Daria V.; Westra, Harm-Jan
2015-01-01
BACKGROUND: Obesity is a multi-factorial health problem in which genetic factors play an important role. Limited results have been obtained in single-gene studies using either genomic or transcriptomic data. RNA sequencing technology has shown its potential in gaining accurate knowledge about...... the transcriptome, and may reveal novel genes affecting complex diseases. Integration of genomic and transcriptomic variation (expression quantitative trait loci [eQTL] mapping) has identified causal variants that affect complex diseases. We integrated transcriptomic data from adipose tissue and genomic data from...... a porcine model to investigate the mechanisms involved in obesity using a systems genetics approach. METHODS: Using a selective gene expression profiling approach, we selected 36 animals based on a previously created genomic Obesity Index for RNA sequencing of subcutaneous adipose tissue. Differential...
RNS derivation of N-point disk amplitudes from the revisited S-matrix approach
Barreiro, Luiz Antonio
2014-01-01
In the past year, in arXiv:1208.6066 we proposed a revisited S-matrix approach to efficiently find the bosonic terms of the open superstring low energy effective lagrangian (OSLEEL). This approach allows to compute the ${\\alpha'}^N$ terms of the OSLEEL using open superstring $n$-point amplitudes in which $n$ is very much lower than $(N+2)$ (which is the order of the required amplitude to obtain those ${\\alpha'}^N$ terms by means of the conventional S-matrix approach). In this work we use our revisited S-matrix approach to examine the structure of the scattering amplitudes, arriving at a closed form for them. This is a RNS derivation of the formula first found by Mafra, Schlotterer and Stieberger in arXiv:1106.2645, using the Pure Spinor formalism. We have succeeded doing this for the 5, 6 and 7-point amplitudes. In order to achieve these results we have done a careful analysis of the kinematical structure of the amplitudes, finding as a by-product a purely kinematical derivation of the BCJ relations (for N=4,...
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Saghir Pervaiz Ghauri
2017-02-01
Full Text Available The objective of this research paper is to examine the relationship between relative price variability and inflation by using consumer price index (CPI of Pakistan. The outcomes of the research further divided into food and non-food groups too. The monthly data of CPI was taken from the Pakistan Bureau of Statistics, from August 2001 to July 2011 (with 2000-01 base for 92 composite commodities with 12 sub-groups. We employed the Granger causality testing approach for the evaluation of any possible influence of one indicator to another. In this scenario, it is viable to state that there is a presence of causality and bidirectional feedback between the variables or the two variables are independent. The major issue is to identify a suitable statistical method that enables us to analyze the association among the variables. The findings of this study demonstrated that there is a probable relationship between inflation (DPt and both un-weighted measures of price variability (VPt and SPt for the whole items that have been considered for the analysis. Apart from that, this association also exists between food and non-food categories of CPI basket.
DEFF Research Database (Denmark)
Husemoen, L. L. N.; Skaaby, T.; Martinussen, Torben
2014-01-01
Background/Objectives: The aim was to examine the causal effect of vitamin D on serum adiponectin using a multiple instrument Mendelian randomization approach. Subjects/Methods: Serum 25-hydroxy vitamin D (25(OH)D) and serum total or high molecular weight (HMW) adiponectin were measured in two...... Danish population-based studies: the Inter99 study (6405 adults, 30-60 years) conducted in 1999-2001, and the MONICA10 study (2656 adults, 41-71 years) conducted in 1993-1994. Results: In the Inter99 study, serum 25(OH)D was positively associated with total adiponectin (the effect estimate in % per...... doubling of 25(OH)D was 4.78, 95% CI: 1.96, 7.68, Padiponectin per doubling of 25(OH)D. In the MONICA10...
Inflation and Dirac in the Causal Set Approach to Discrete Quantum Gravity
Gudder, Stan
2015-01-01
In this approach to discrete quantum gravity the basic structural element is a covariant causal set ($c$-causet). The geometry of a $c$-causet is described by a shell-sequence that determines the discrete gravity of a universe. In this growth model, universes evolve in discrete time by adding new vertices to their generating $c$-causet. We first describe an inflationary period that is common to all universes. After this very brief cycle, the model enters a multiverse period in which the system diverges in various ways forming paths of $c$-causets. At the beginning of the multiverse period, the structure of a four-dimensional discrete manifold emerges and quantum mechanics enters the picture. A natural Hilbert space is defined and a discrete, free Dirac operator is introduced. We determine the eigenvalues and eigenvectors of this operator. Finally, we propose values for coupling constants that determine multiverse probabilities. These probabilities predict the dominance of pulsating universes.
System identification based approach to dynamic weighing revisited
Niedźwiecki, Maciej; Meller, Michał; Pietrzak, Przemysław
2016-12-01
Dynamic weighing, i.e., weighing of objects in motion, without stopping them on the weighing platform, allows one to increase the rate of operation of automatic weighing systems, used in industrial production processes, without compromising their accuracy. Since the classical identification-based approach to dynamic weighing, based on the second-order mass-spring-damper model of the weighing system, does not yield satisfactory results when applied to conveyor belt type checkweighers, several extensions of this technique are examined. Experiments confirm that when appropriately modified the identification-based approach becomes a reliable tool for dynamic mass measurement in checkweighers.
Revisiting Cyberbullying in Schools Using the Quality Circle Approach
Paul, Simone; Smith, Peter K.; Blumberg, Herbert H.
2012-01-01
An earlier study reported the use of Quality Circles (QC) in a UK school in the context of understanding and reducing bullying and cyberbullying. Here, we report further work in the same school setting. The QC approach allows explorative analysis of problems in school settings, whereby students embark on a problem-solving exercise over a period of…
Revisiting Cyberbullying in Schools Using the Quality Circle Approach
Paul, Simone; Smith, Peter K.; Blumberg, Herbert H.
2012-01-01
An earlier study reported the use of Quality Circles (QC) in a UK school in the context of understanding and reducing bullying and cyberbullying. Here, we report further work in the same school setting. The QC approach allows explorative analysis of problems in school settings, whereby students embark on a problem-solving exercise over a period of…
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.
The control outcome calibration approach for causal inference with unobserved confounding.
Tchetgen Tchetgen, Eric
2014-03-01
Unobserved confounding can seldom be ruled out with certainty in nonexperimental studies. Negative controls are sometimes used in epidemiologic practice to detect the presence of unobserved confounding. An outcome is said to be a valid negative control variable to the extent that it is influenced by unobserved confounders of the exposure effects on the outcome in view, although not directly influenced by the exposure. Thus, a negative control outcome found to be empirically associated with the exposure after adjustment for observed confounders indicates that unobserved confounding may be present. In this paper, we go beyond the use of control outcomes to detect possible unobserved confounding and propose to use control outcomes in a simple but formal counterfactual-based approach to correct causal effect estimates for bias due to unobserved confounding. The proposed control outcome calibration approach is developed in the context of a continuous or binary outcome, and the control outcome and the exposure can be discrete or continuous. A sensitivity analysis technique is also developed, which can be used to assess the degree to which a violation of the main identifying assumption of the control outcome calibration approach might impact inference about the effect of the exposure on the outcome in view.
The two capacitor problem revisited: simple harmonic oscillator model approach
Lee, Keeyung
2012-01-01
The well-known two-capacitor problem, in which exactly half the stored energy disappears when a charged capacitor is connected to an identical capacitor is discussed based on the mechanical harmonic oscillator model approach. In the mechanical harmonic oscillator model, it is shown first that \\emph {exactly half} the work done by a constant applied force is dissipated irrespective of the form of dissipation mechanism when the system comes to a new equilibrium after a constant force is abruptly applied. This model is then applied to the energy loss mechanism in the capacitor charging problem or the two-capacitor problem. This approach allows a simple explanation of the energy dissipation mechanism in these problems and shows that the dissipated energy should always be \\emph {exactly half} the supplied energy whether that is caused by the Joule heat or by the radiation. This paper which provides a simple treatment of the energy dissipation mechanism in the two-capacitor problem is suitable for all undergraduate...
Hume, Mill, Hill, and the sui generis epidemiologic approach to causal inference.
Morabia, Alfredo
2013-11-15
The epidemiologic approach to causal inference (i.e., Hill's viewpoints) consists of evaluating potential causes from the following 2, noncumulative angles: 1) established results from comparative, observational, or experimental epidemiologic studies; and 2) reviews of nonepidemiologic evidence. It does not involve statements of statistical significance. The philosophical roots of Hill's viewpoints are unknown. Superficially, they seem to descend from the ideas of Hume and Mill. Hill's viewpoints, however, use a different kind of evidence and have different purposes than do Hume's rules or Mill's system of logic. In a nutshell, Hume ignores comparative evidence central to Hill's viewpoints. Mill's logic disqualifies as invalid nonexperimental evidence, which forms the bulk of epidemiologic findings reviewed from Hill's viewpoints. The approaches by Hume and Mill cannot corroborate successful implementations of Hill's viewpoints. Besides Hume and Mill, the epidemiologic literature is clueless about a plausible, pre-1965 philosophical origin of Hill's viewpoints. Thus, Hill's viewpoints may be philosophically novel, sui generis, still waiting to be validated and justified.
Directory of Open Access Journals (Sweden)
Irina A. Mironenko
2009-01-01
Full Text Available Russian psychology has brought into the world science at least two great ideas: the conditioned reflex (Pavlov and the zone of proximal development (Vygotsky. These concepts were formulated before “iron curtain” fell. Since then Russian science dropped out from the view of western colleagues for decades. Now it is challenged to re-join international mainstream. Are we in a position to contribute?A key concept for Russian psychology is personality impact on psycho-physiological functions and causal approach to self-determination. The concept of selfdetermination appeared in Western theories in 1980-es and since then it has been developed in the context of teleological humanitarian approach. In Russian science the concept of self-determination dates back to 1934, when it was defined by Rubinstein as “sub’ekt”. Self-determination of ontogenesis of psycho physiological functions resulting from confluence of ontogenesis and social development was explicated by Russian scientists whose theoretical reasoning and empirical results are compared to Western counterparts.
Evaluation of Methyl-Binding Domain Based Enrichment Approaches Revisited.
Directory of Open Access Journals (Sweden)
Karolina A Aberg
Full Text Available Methyl-binding domain (MBD enrichment followed by deep sequencing (MBD-seq, is a robust and cost efficient approach for methylome-wide association studies (MWAS. MBD-seq has been demonstrated to be capable of identifying differentially methylated regions, detecting previously reported robust associations and producing findings that replicate with other technologies such as targeted pyrosequencing of bisulfite converted DNA. There are several kits commercially available that can be used for MBD enrichment. Our previous work has involved MethylMiner (Life Technologies, Foster City, CA, USA that we chose after careful investigation of its properties. However, in a recent evaluation of five commercially available MBD-enrichment kits the performance of the MethylMiner was deemed poor. Given our positive experience with MethylMiner, we were surprised by this report. In an attempt to reproduce these findings we here have performed a direct comparison of MethylMiner with MethylCap (Diagenode Inc, Denville, NJ, USA, the best performing kit in that study. We find that both MethylMiner and MethylCap are two well performing MBD-enrichment kits. However, MethylMiner shows somewhat better enrichment efficiency and lower levels of background "noise". In addition, for the purpose of MWAS where we want to investigate the majority of CpGs, we find MethylMiner to be superior as it allows tailoring the enrichment to the regions where most CpGs are located. Using targeted bisulfite sequencing we confirmed that sites where methylation was detected by either MethylMiner or by MethylCap indeed were methylated.
Kogelman, Lisette J A; Zhernakova, Daria V; Westra, Harm-Jan; Cirera, Susanna; Fredholm, Merete; Franke, Lude; Kadarmideen, Haja N
2015-10-20
Obesity is a multi-factorial health problem in which genetic factors play an important role. Limited results have been obtained in single-gene studies using either genomic or transcriptomic data. RNA sequencing technology has shown its potential in gaining accurate knowledge about the transcriptome, and may reveal novel genes affecting complex diseases. Integration of genomic and transcriptomic variation (expression quantitative trait loci [eQTL] mapping) has identified causal variants that affect complex diseases. We integrated transcriptomic data from adipose tissue and genomic data from a porcine model to investigate the mechanisms involved in obesity using a systems genetics approach. Using a selective gene expression profiling approach, we selected 36 animals based on a previously created genomic Obesity Index for RNA sequencing of subcutaneous adipose tissue. Differential expression analysis was performed using the Obesity Index as a continuous variable in a linear model. eQTL mapping was then performed to integrate 60 K porcine SNP chip data with the RNA sequencing data. Results were restricted based on genome-wide significant single nucleotide polymorphisms, detected differentially expressed genes, and previously detected co-expressed gene modules. Further data integration was performed by detecting co-expression patterns among eQTLs and integration with protein data. Differential expression analysis of RNA sequencing data revealed 458 differentially expressed genes. The eQTL mapping resulted in 987 cis-eQTLs and 73 trans-eQTLs (false discovery rate genes and disease-associated single nucleotide polymorphisms to detect obesity-related genes and pathways. Building a co-expression network using eQTLs resulted in the detection of a module strongly associated with lipid pathways. Furthermore, we detected several obesity candidate genes, for example, ENPP1, CTSL, and ABHD12B. To our knowledge, this is the first study to perform an integrated genomics and
The Epstein–Glaser causal approach to the light-front QED{sub 4}. II: Vacuum polarization tensor
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Bufalo, R., E-mail: rodrigo.bufalo@helsinki.fi [Department of Physics, University of Helsinki, P.O. Box 64, FI-00014 Helsinki (Finland); Instituto de Física Teórica (IFT/UNESP), UNESP - São Paulo State University, Rua Dr. Bento Teobaldo Ferraz 271, Bloco II Barra Funda, CEP 01140-070 São Paulo, SP (Brazil); Pimentel, B.M., E-mail: pimentel@ift.unesp.br [Instituto de Física Teórica (IFT/UNESP), UNESP - São Paulo State University, Rua Dr. Bento Teobaldo Ferraz 271, Bloco II Barra Funda, CEP 01140-070 São Paulo, SP (Brazil); Soto, D.E., E-mail: danielsb@ift.unesp.br [Instituto de Física Teórica (IFT/UNESP), UNESP - São Paulo State University, Rua Dr. Bento Teobaldo Ferraz 271, Bloco II Barra Funda, CEP 01140-070 São Paulo, SP (Brazil)
2014-12-15
In this work we show how to construct the one-loop vacuum polarization for light-front QED{sub 4} in the framework of the perturbative causal theory. Usually, in the canonical approach, it is considered for the fermionic propagator the so-called instantaneous term, but it is known in the literature that this term is controversial because it can be omitted by computational reasons; for instance, by compensation or vanishing by dimensional regularization. In this work we propose a solution to this paradox. First, in the Epstein–Glaser causal theory, it is shown that the fermionic propagator does not have instantaneous term, and with this propagator we calculate the one-loop vacuum polarization, from this calculation it follows the same result as those obtained by the standard approach, but without reclaiming any extra assumptions. Moreover, since the perturbative causal theory is defined in the distributional framework, we can also show the reason behind our obtaining the same result whether we consider or not the instantaneous fermionic propagator term. - Highlights: • We develop the Epstein–Glaser causal approach for light-front field theory. • We evaluate in detail the vacuum polarization at one-loop for the light-front QED. • We discuss the subtle issues of the Instantaneous part of the fermionic propagator in the light-front. • We evaluate the vacuum polarization at one-loop for the light-front QED with the Instantaneous fermionic part.
Ortega, Pedro A
2011-01-01
Discovering causal relationships is a hard task, often hindered by the need for intervention, and often requiring large amounts of data to resolve statistical uncertainty. However, humans quickly arrive at useful causal relationships. One possible reason is that humans use strong prior knowledge; and rather than encoding hard causal relationships, they encode beliefs over causal structures, allowing for sound generalization from the observations they obtain from directly acting in the world. In this work we propose a Bayesian approach to causal induction which allows modeling beliefs over multiple causal hypotheses and predicting the behavior of the world under causal interventions. We then illustrate how this method extracts causal information from data containing interventions and observations.
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.
A new approach for agroecosystems monitoring using high-revisit multitemporal satellite data series
Diez, M.; Moclán, C.; Romo, A.; Pirondini, F.
2014-10-01
With increasing population pressure throughout the world and the need for increased agricultural production there is a definite need for improved management of the world's agricultural resources. Comprehensive, reliable and timely information on agricultural resources is necessary for the implementation of effective management decisions. In that sense, the demand for high-quality and high-frequency geo-information for monitoring of agriculture and its associated ecosystems has been growing in the recent decades. Satellite image data enable direct observation of large areas at frequent intervals and therefore allow unprecedented mapping and monitoring of crops evolution. Furthermore, real time analysis can assist in making timely management decisions that affect the outcome of the crops. The DEIMOS-1 satellite, owned and operated by ELECNOR DEIMOS IMAGING (Spain), provides 22m, 3-band imagery with a very wide (620-km) swath, and has been specifically designed to produce high-frequency revisit on very large areas. This capability has been proved through the contracts awarded to Airbus Defence and Space every year since 2011, where DEIMOS-1 has provided the USDA with the bulk of the imagery used to monitor the crop season in the Lower 48, in cooperation with its twin satellite DMCii's UK-DMC2. Furthermore, high density agricultural areas have been targeted with increased frequency and analyzed in near real time to monitor tightly the evolution. In this paper we present the results obtained from a campaign carried out in 2013 with DEIMOS-1 and UK-DMC2 satellites. These campaigns provided a high-frequency revisit of target areas, with one image every two days on average: almost a ten-fold frequency improvement with respect to Landsat-8. The results clearly show the effectiveness of a high-frequency monitoring approach with high resolution images with respect to classic strategies where results are more exposed to weather conditions.
Chee-Yin, Yip; Hock-Eam, Lim
2014-12-01
This paper examines using housing supply as proxy to house prices, the causal relationship on house prices among 8 states in Malaysia by applying the Engle-Granger cointegration test and Granger causality test approach. The target states are Perak, Selangor, Penang, Federal Territory of Kuala Lumpur (WPKL or Kuala Lumpur), Kedah, Negeri Sembilan, Sabah and Sarawak. The primary aim of this study is to estimate how long (in months) house prices in Perak lag behind that of Selangor, Penang and WPKL. We classify the 8 states into two categories - developed and developing states. We use Engle-Granger cointegration test and Granger causality test to examine the long run and short run equilibrium relationship among the two categories.. It is found that the causal relationship is bidirectional in Perak and Sabah, Perak and Selangor while it is unidirectional for Perak and Sarawak, Perak and Penang, Perak and WPKL. The speed of deviation adjustment is about 273%, suggesting that the pricing dynamic of Perak has a 32- month or 2 3/4- year lag behind that of WPKL, Selangor and Penang. Such information will be useful to investors, house buyers and speculators.
Directory of Open Access Journals (Sweden)
Rohin Anhal
2013-10-01
Full Text Available The aim of this paper is to examine the direction of causality between real GDP on the one hand and final energy and coal consumption on the other in India, for the period from 1970 to 2011. The methodology adopted is the non-parametric bootstrap procedure, which is used to construct the critical values for the hypothesis of causality. The results of the bootstrap tests show that for total energy consumption, there exists no causal relationship in either direction with GDP of India. However, if coal consumption is considered, we find evidence in support of unidirectional causality running from coal consumption to GDP. This clearly has important implications for the Indian economy. The most important implication is that curbing coal consumption in order to reduce carbon emissions would in turn have a limiting effect on economic growth. Our analysis contributes to the literature in three distinct ways. First, this is the first paper to use the bootstrap method to examine the growth-energy connection for the Indian economy. Second, we analyze data for the time period 1970 to 2011, thereby utilizing recently available data that has not been used by others. Finally, in contrast to the recently done studies, we adopt a disaggregated approach for the analysis of the growth-energy nexus by considering not only aggregate energy consumption, but coal consumption as well.
Directory of Open Access Journals (Sweden)
Blossfeld, Hans-Peter
2001-01-01
Full Text Available FrenchOne of the most important advances brought about by life course and eventhistory studies is the use of parallel or independent processes as explaining history factors intransition rate models. The purpose of this paper is to demonstrate a causal approach to the study ofinterrelated family events. Various types of interdependent processes are described first, followed bytwo event history perspectives: the "system" and "causal" approaches. The authors assert that thecausal approach is more appropriate from an analytical point of view as it provides a straightforwardsolution to simultaneity, cause-effect lags, and temporal shapes of effects. Based on comparativecross-national applications in West and East Germany, Canada, Latvia and the Netherlands, wedemonstrate the usefulness of the causal approach by analyzing two highly interdependent famlyprocesses: entry into marriage (for individuals who are in a consensual union as the dependentprocess and first pregnancy/childbirth as the explaining one. Both statistical and theorteticalexplanations are explored emphasizing the need for conceptual reasoning.FrenchL’utilisation des processus interdépendants ou parallèles en tant que facteursexplicatifs dans des modèles des transitions aux quotients instantanés est une descontributions les plus importantes de l’analyse des biographies. Le but de cetarticle est d’appliquer une approche causale à l’analyse des événements familiauxinterdépendants. L’étude présente une typologie de processus parallèles et deuxperspectives de l’analyse des biographies: les approches ‘systémique’ et‘causale’. Les auteurs soutiennent que l’approche causale est plus appropriée dupoint de vue d’analyse. Elle offre une solution valable aux problèmes desimultanéité, les problèmes de décalage dans les intervalles entre la cause etl’effet, et, enfin, les problèmes des courbes temporelles modelées par les effets.L’utilité de cette
Directory of Open Access Journals (Sweden)
Hazuki Ishida
2013-01-01
Full Text Available This paper explores whether Japanese economy can continue to grow without extensive dependence on fossil fuels. The paper conducts time series analysis using a multivariate model of fossil fuels, non-fossil energy, labor, stock and GDP to investigate the relationship between fossil fuel consumption and economic growth in Japan. The results of cointegration tests indicate long-run relationships among the variables. Using a vector error-correction model, the study reveals bidirectional causality between fossil fuels and GDP. The results also show that there is no causal relationship between non-fossil energy and GDP. The results of cointegration analysis, Granger causality tests, and variance decomposition analysis imply that non-fossil energy may not necessarily be able to play the role of fossil fuels. Japan cannot seem to realize both continuous economic growth and the departure from dependence on fossil fuels. Hence, growth-oriented macroeconomic policies should be re-examined.
A new approach in classical electrodynamics to protect principle of causality
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Biswaranjan Dikshit
2014-03-01
Full Text Available In classical electrodynamics, electromagnetic effects are calculated from solution of wave equation formed by combination of four Maxwell’s equations. However, along with retarded solution, this wave equation admits advanced solution in which case the effect happens before the cause. So, to preserve causality in natural events, the retarded solution is intentionally chosen and the advance part is just ignored. But, an equation or method cannot be called fundamental if it admits a wrong result (that violates principle of causality in addition to the correct result. Since it is the Maxwell’s form of equations that gives birth to this acausal advanced potential, we rewrite these equations in a different form using the recent theory of reaction at a distance (Biswaranjan Dikshit, Physics essays, 24(1, 4-9, 2011 so that the process of calculation does not generate any advanced effects. Thus, the long-standing causality problem in electrodynamics is solved.
A Bayesian network approach for causal inferences in pesticide risk assessment and management
Pesticide risk assessment and management must balance societal benefits and ecosystem protection, based on quantified risks and the strength of the causal linkages between uses of the pesticide and socioeconomic and ecological endpoints of concern. A Bayesian network (BN) is a gr...
Energy Technology Data Exchange (ETDEWEB)
Ciarreta, A. [Department of Economic Analysis II, University of the Basque Country (UPV/EHU), Avda, Lehendakari Aguirre, 83, 48015 Bilbao (Spain); Zarraga, A. [Department of Applied Economics III, University of the Basque Country (UPV/EHU), Avda, Lehendakari Aguirre, 83, 48015 Bilbao (Spain)
2010-07-15
This paper applies recent panel methodology to investigate the long-run and causal relationship between electricity consumption and real GDP for a set of 12 European countries using annual data for the period 1970-2007. The sample countries have moved faster than other neighboring countries towards the creation of a single electricity market over the past 30 years. Energy prices are also included in the study due to their important role in affecting the above variables, thus avoiding the problem of omitted variable bias. Tests for panel unit roots, cointegration in heterogeneous panels and panel causality are employed in a trivariate VECM estimated by system GMM. The results show evidence of a long-run equilibrium relationship between the three series and a negative short-run and strong causality from electricity consumption to GDP. As expected, there is bidirectional causality between energy prices and GDP and weaker evidence between electricity consumption and energy prices. These results support the policies implemented towards the creation of a common European electricity market. (author)
Energy Technology Data Exchange (ETDEWEB)
Ciarreta, A., E-mail: aitor.ciarreta@ehu.e [Department of Economic Analysis II, University of the Basque Country (UPV/EHU), Avda, Lehendakari Aguirre, 83, 48015 Bilbao (Spain); Zarraga, A., E-mail: ainhoa.zarraga@ehu.e [Department of Applied Economics III, University of the Basque Country (UPV/EHU), Avda, Lehendakari Aguirre, 83, 48015 Bilbao (Spain)
2010-07-15
This paper applies recent panel methodology to investigate the long-run and causal relationship between electricity consumption and real GDP for a set of 12 European countries using annual data for the period 1970-2007. The sample countries have moved faster than other neighboring countries towards the creation of a single electricity market over the past 30 years. Energy prices are also included in the study due to their important role in affecting the above variables, thus avoiding the problem of omitted variable bias. Tests for panel unit roots, cointegration in heterogeneous panels and panel causality are employed in a trivariate VECM estimated by system GMM. The results show evidence of a long-run equilibrium relationship between the three series and a negative short-run and strong causality from electricity consumption to GDP. As expected, there is bidirectional causality between energy prices and GDP and weaker evidence between electricity consumption and energy prices. These results support the policies implemented towards the creation of a common European electricity market.
Vinod Mishra; Ingrid Nielsen; Russell Smyth; Alex Newman
2014-01-01
This paper uses a novel identification strategy proposed by Lewbel (2012, J. Bus. Econ. Stat.) to illustrate how causation between job satisfaction and life satisfaction can be established with cross-sectional data. In addition to examining the relationship between composite job satisfaction and life satisfaction, we consider the relationship between life satisfaction and different facets of job satisfaction. We find evidence of bidirectional causality between job satisfaction and life satisf...
On the notion of causality in medicine: addressing Austin Bradford Hill and John L. Mackie
Directory of Open Access Journals (Sweden)
Luís Fernando S. C. de Araújo
2014-03-01
Full Text Available Almost 50 years ago appeared the seminal article by Austin Bradford Hill where he presented parameters for inferring causes from statistical associations, which became known as Hill’s causal criteria. This was a milestone for the renewal of the idea of cause in medicine. Our article revisits his contribution in light of the ideas from the Australian philosopher John L. Mackie, whose important works on causality reached an audience distinct from Hill’s. We suggest that both the British epidemiologist and the Australian philosopher share the purpose of articulating probabilistic determinism and multi-causality, the first with a predominantly probabilistic model and the second with an analytical approach. This article explores the possible consequences of addressing these authors jointly in regard to causal inferences in medicine, especially in respect to mental disorders.
Asumadu-Sarkodie, Samuel; Owusu, Phebe Asantewaa
2017-01-01
Achieving a long-term food security and preventing hunger include a better nutrition through sustainable systems of production, distribution, and consumption. Nonetheless, the quest for an alternative to increasing global food supply to meet the growing demand has led to the use of poor agricultural practices that promote climate change. Given the contribution of the agricultural ecosystem towards greenhouse gas (GHG) emissions, this study investigated the causal nexus between carbon dioxide emissions and agricultural ecosystem by employing a data spanning from 1961 to 2012. Evidence from long-run elasticity shows that a 1 % increase in the area of rice paddy harvested will increase carbon dioxide emissions by 1.49 %, a 1 % increase in biomass-burned crop residues will increase carbon dioxide emissions by 1.00 %, a 1 % increase in cereal production will increase carbon dioxide emissions by 1.38 %, and a 1 % increase in agricultural machinery will decrease carbon dioxide emissions by 0.09 % in the long run. There was a bidirectional causality between carbon dioxide emissions, cereal production, and biomass-burned crop residues. The Granger causality shows that the agricultural ecosystem in Ghana is sensitive to climate change vulnerability.
Causality between stock price and GDP in Turkey: An ARDL Bounds Testing Approach
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Turgut Tursoy
2016-12-01
Full Text Available The study investigates the dynamic relationship between stock prices and GDP in Turkey using quarterly data from 1989Q2-2014Q2. The study investigated the interrelationship between the variables via auto regressive distributive lag (ARDL framework and ECM to analyse the existence of a long-run equilibrium relationship between gross domestic product and stock prices. The results provide strong evidence that both the stock prices and GDP are strongly cointegrated in the long-run. The empirical estimation indicated a significantly positive relationship between GDP and stock prices. The robustness of the ARDL model was confirmed by using Johansen and Juselius’s cointegration test (1990. The Granger causality test results indicate a long-run bidirectional causality between stock prices and GDP, and also a uni-directional causality from GDP to stock prices in the short-run. Both the stock prices and the economic growth are directly linked with each other. The reliability and validity of our estimations are confirmed by the diagnostics and the CUSUM test.
Revisiting radiative decays of $1^{+-}$ heavy quarkonia in the covariant light-front approach
Shi, Yan-Liang
2016-01-01
We revisit the calculation of the width for the radiative decay of a $1^{+-}$ heavy $Q \\bar Q$ meson via the channel $1^{+-} \\to 0^{-+} +\\gamma$ in the covariant light-front quark model. We carry out the reduction of the light-front amplitude in the non-relativistic limit, explicitly computing the leading and next-to-leading order relativistic corrections. This shows the consistency of the light-front approach with the non-relativistic formula for this electric dipole transition. Furthermore, the theoretical uncertainty in the predicted width is studied as a function of the inputs for the heavy quark mass and wavefunction structure parameter. We analyze the specific decays $h_{c}(1P) \\to \\eta_{c}(1S) + \\gamma$ and $h_{b}(1P) \\to \\eta_{b}(1S) + \\gamma$. We compare our results with experimental data and with other theoretical predictions from calculations based on non-relativistic models and their extensions to include relativistic effects, finding reasonable agreement.
Revisiting radiative decays of 1{sup +-} heavy quarkonia in the covariant light-front approach
Energy Technology Data Exchange (ETDEWEB)
Shi, Yan-Liang [Stony Brook University, C. N. Yang Institute for Theoretical Physics, Stony Brook, NY (United States)
2017-04-15
We revisit the calculation of the width for the radiative decay of a 1{sup +-} heavy Q anti Q meson via the channel 1{sup +-} → 0{sup -+}+γ in the covariant light-front quark model. We carry out the reduction of the light-front amplitude in the non-relativistic limit, explicitly computing the leading and next-to-leading order relativistic corrections. This shows the consistency of the light-front approach with the non-relativistic formula for this electric dipole transition. Furthermore, the theoretical uncertainty in the predicted width is studied as a function of the inputs for the heavy-quark mass and wave function structure parameter. We analyze the specific decays h{sub c}(1P) → η{sub c}(1S) + γ and h{sub b}(1P) → η{sub b}(1S) + γ. We compare our results with experimental data and with other theoretical predictions from calculations based on non-relativistic models and their extensions to include relativistic effects, finding reasonable agreement. (orig.)
Post-Tanner stages of droplet spreading: the energy balance approach revisited
Energy Technology Data Exchange (ETDEWEB)
Mechkov, S; Oshanin, G [Laboratoire de Physique Theorique de la Matiere Condensee, Universite Pierre et Marie Curie, 4 place Jussieu, 75252 Paris Cedex 5 (France); Cazabat, A M, E-mail: mechkov@lptmc.jussieu.f, E-mail: anne-marie.cazabat@lps.ens.f, E-mail: oshanin@lptmc.jussieu.f [Laboratoire de Physique Statistique, Ecole Normale Superieure, 75252 Paris Cedex 5 (France)
2009-11-18
The spreading of a circular liquid drop on a solid substrate can be described in terms of the time evolution of its base radius R(t). In complete wetting, the quasistationary regime (far away from initial and final transients) typically obeys the so-called Tanner law, with Rapproxt{sup alpha}{sub T}, alpha{sub T} = 1/10. Late-time spreading may differ significantly from the Tanner law: in some cases the drop does not thin down to a molecular film and instead reaches an equilibrium pancake-like shape; in other situations, as revealed by recent experiments with spontaneously spreading nematic crystals, the growth of the base radius accelerates after the Tanner stage. Here we demonstrate that these two seemingly conflicting trends can be reconciled within a suitably revisited energy balance approach, by taking into account the line tension contribution to the driving force of spreading: a positive line tension is responsible for the formation of pancake-like structures, whereas a negative line tension tends to lengthen the contact line and induces an accelerated spreading (a transition to a faster power law for R(t) than in the Tanner stage).
Post-Tanner stages of droplet spreading: the energy balance approach revisited.
Mechkov, S; Cazabat, A M; Oshanin, G
2009-11-18
The spreading of a circular liquid drop on a solid substrate can be described in terms of the time evolution of its base radius R(t). In complete wetting, the quasistationary regime (far away from initial and final transients) typically obeys the so-called Tanner law, with R∼t(α(T)), α(T) = 1/10. Late-time spreading may differ significantly from the Tanner law: in some cases the drop does not thin down to a molecular film and instead reaches an equilibrium pancake-like shape; in other situations, as revealed by recent experiments with spontaneously spreading nematic crystals, the growth of the base radius accelerates after the Tanner stage. Here we demonstrate that these two seemingly conflicting trends can be reconciled within a suitably revisited energy balance approach, by taking into account the line tension contribution to the driving force of spreading: a positive line tension is responsible for the formation of pancake-like structures, whereas a negative line tension tends to lengthen the contact line and induces an accelerated spreading (a transition to a faster power law for R(t) than in the Tanner stage).
Shen, Siu-Tsen; Prior, Stephen D.; Chen, Kuen-Meau
2010-01-01
With a quarter of the world’s population now having access to the internet, the area of web efficiency and optimal use is of growing importance to all users. The function of revisitation, where a user wants to return to a website that they have visited in the recent past becomes more important. Current static and textual approaches developed within the latest versions of mainstream web browsers leave much to be desired. This paper suggests a new approach via the use of organic visual and cont...
A Causal, Data-driven Approach to Modeling the Kepler Data
Wang, Dun; Hogg, David W.; Foreman-Mackey, Daniel; Schölkopf, Bernhard
2016-09-01
Astronomical observations are affected by several kinds of noise, each with its own causal source; there is photon noise, stochastic source variability, and residuals coming from imperfect calibration of the detector or telescope. The precision of NASA Kepler photometry for exoplanet science—the most precise photometric measurements of stars ever made—appears to be limited by unknown or untracked variations in spacecraft pointing and temperature, and unmodeled stellar variability. Here, we present the causal pixel model (CPM) for Kepler data, a data-driven model intended to capture variability but preserve transit signals. The CPM works at the pixel level so that it can capture very fine-grained information about the variation of the spacecraft. The CPM models the systematic effects in the time series of a pixel using the pixels of many other stars and the assumption that any shared signal in these causally disconnected light curves is caused by instrumental effects. In addition, we use the target star’s future and past (autoregression). By appropriately separating, for each data point, the data into training and test sets, we ensure that information about any transit will be perfectly isolated from the model. The method has four tuning parameters—the number of predictor stars or pixels, the autoregressive window size, and two L2-regularization amplitudes for model components, which we set by cross-validation. We determine values for tuning parameters that works well for most of the stars and apply the method to a corresponding set of target stars. We find that CPM can consistently produce low-noise light curves. In this paper, we demonstrate that pixel-level de-trending is possible while retaining transit signals, and we think that methods like CPM are generally applicable and might be useful for K2, TESS, etc., where the data are not clean postage stamps like Kepler.
Credible Granger-Causality Inference with Modest Sample Lengths: A Cross-Sample Validation Approach
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Richard A. Ashley
2014-03-01
Full Text Available Credible Granger-causality analysis appears to require post-sample inference, as it is well-known that in-sample fit can be a poor guide to actual forecasting effectiveness. However, post-sample model testing requires an often-consequential a priori partitioning of the data into an “in-sample” period – purportedly utilized only for model specification/estimation – and a “post-sample” period, purportedly utilized (only at the end of the analysis for model validation/testing purposes. This partitioning is usually infeasible, however, with samples of modest length – e.g., T ≤ 150 – as is common in both quarterly data sets and/or in monthly data sets where institutional arrangements vary over time, simply because there is in such cases insufficient data available to credibly accomplish both purposes separately. A cross-sample validation (CSV testing procedure is proposed below which both eliminates the aforementioned a priori partitioning and which also substantially ameliorates this power versus credibility predicament – preserving most of the power of in-sample testing (by utilizing all of the sample data in the test, while also retaining most of the credibility of post-sample testing (by always basing model forecasts on data not utilized in estimating that particular model’s coefficients. Simulations show that the price paid, in terms of power relative to the in-sample Granger-causality F test, is manageable. An illustrative application is given, to a re-analysis of the Engel andWest [1] study of the causal relationship between macroeconomic fundamentals and the exchange rate; several of their conclusions are changed by our analysis.
Causality and contagion in peripheral EMU public debt markets: a dynamic approach
Gomez-Puig, Marta; Sosvilla Rivero, Simón Javier
2016-01-01
Nuestra investigación tiene como objetivo analizar las relaciones causales en el comportamiento de la deuda pública emitida por países miembros periféricos de la Unión Económica y Monetaria (UEM), con especial énfasis en los recientes episodios de crisis desatados en los mercados de deuda soberana de la zona euro desde 2009. Con este objetivo, empleamos una base de datos de la frecuencia diaria de los rendimientos de los bonos gubernamentales a 10 años emitidos por cinco países de la UEM (Gre...
Cortês, Marina
2013-01-01
We propose an approach to quantum theory based on the energetic causal sets, introduced in Cort\\^{e}s and Smolin (2013). Fundamental processes are causal sets whose events carry momentum and energy, which are transmitted along causal links and conserved at each event. Fundamentally there are amplitudes for such causal processes, but no space-time. An embedding of the causal processes in an emergent space-time arises only at the semiclassical level. Hence, fundamentally there are no commutation relations, no uncertainty principle and, indeed, no hbar. All that remains of quantum theory is the relationship between the absolute value squared of complex amplitudes and probabilities. Consequently, we find that neither locality, nor non locality, are primary concepts, only causality exists at the fundamental level.
Blaisdell, A.P.; Beckers, T.
2009-01-01
The article discusses various reports published within the issue, including one on psychological approaches to causal discovery in humans, one on the representational and reasoning capacities that underlie causal cognition in rats and one on the generality of knowledge of Great Ape.
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Grauls D.
2006-12-01
Full Text Available Abnormal fluid pressure regimes are commonly encountered at depth in most sedimentary basins. Relationships between effective vertical stress and porosity have been applied, since 1970 to the Gulf Coast area, to assess the magnitude of overpressures. Positive results have been obtained from seismic and basin-modeling techniques in sand-shale, vertical-stress-dominated tertiary basins, whenever compaction disequilibrium conditions apply. However, overpressures resulting from other and/or additional causes (tectonic stress, hydrocarbon generation, thermal stress, fault-related transfer, hydrofracturing. . . cannot be quantitatively assessed using this approach. A hydromechanical approach is then proposed in addition to conventional methods. At any depth, the upper bound fluid pressure is controlled by in situ conditions related to hydrofracturing or fault reactivation. Fluid-driven fracturing implies an episodically open system, under a close to zerominimum effective stress regime. Sound knowledge of present-day tectonic stress regimes allows a direct estimation of minimum stress evolution. A quantitative fluid pressure assessment at depth is therefore possible, as in undrained or/and compartmented geological systems, pressure regimes, whatever their origin, tend to rapidly reach a value close to the minimum principal stress. Therefore, overpressure assessment will be improved, as this methodology can be applied to various geological settings and situations where present-day overpressures originated from other causal mechanisms, very often combined. However, pressure trends in transition zones are more difficult to assess correctly. Additional research on cap rocks and fault seals is therefore required to improve their predictability. In addition to overpressure assessment, the minimum principal stress concept allows a better understanding of petroleum system, as fault-related hydrocarbon dynamic transfers, hydrofractured domains and cap
Dave, P.; Bhushan, M.; Venkataraman, C.
2016-12-01
Indian subcontinent, in particular, the Indo-gangetic plain (IGP) has witnessed large temperature anomalies (Ratnam et al., 2016) along with high emission of absorbing aerosols (AA) (Gazala, et al., 2005). The anomalous high temperature observed over this region may bear a relationship with high AA emissions. Different studies have been conducted to understand AA and temperature relationships (Turco et al., 1983; Hansen et al., 1997, 2005; Seinfeld 2008; Ramanathan et al. 2010b; Ban-Weiss et al., 2012). It was found that when the AA was injected in the lower- mid troposphere the surface air temperature increases while injection of AA at higher troposphere-lower stratosphere surface temperature decreases. These studies used simulation based results to establish link between AA and temperature (Hansen et al., 1997, 2005; Ban-Weiss et al., 2012). The current work focuses on identifying the causal influence of AA on temperature using observational and re-analysis data over Indian subcontinent using cross correlation (CCs) and Granger causality (GC) (Granger, 1969). Aerosol index (AI) from TOMS-OMI was used as index for AA while ERA-interim reanalysis data was used for temperature at varying altitude. Period of study was March-April-May-June (MAMJ) for years 1979-2015. CCs were calculated for all the atmospheric layers. In each layer nearby and distant pixels (>500 kms) with high CCs were identified using clustering technique. It was found that that AI and Temperature shows statistically significant cross-correlations for co-located and distant pixels and more prominently over IGP. The CCs fades away with higher altitudes. CCs analysis was followed by GC analysis to identify the lag over which AI can influence the Temperature. GC also supported the findings of CCs analysis. It is an early attempt to link persisting large temperature anomalies with absorbing aerosols and may help in identifying the role of absorbing aerosol in causing heat waves.
K-causality coincides with stable causality
Minguzzi, E
2008-01-01
It is proven that K-causality coincides with stable causality, and that in a K-causal spacetime the relation K^+ coincides with the Seifert's relation. As a consequence the causal relation "the spacetime is strongly causal and the closure of the causal relation is transitive" stays between stable causality and causal continuity.
Directory of Open Access Journals (Sweden)
Richard Shoemaker
2014-04-01
Full Text Available Establishing causality has been a problem throughout history of philosophy of science. This paper discusses the philosophy of causal inference along the different school of thoughts and methods: Rationalism, Empiricism, Inductive method, Hypothetical deductive method with pros and cons. The article it starting from the Problem of Hume, also close to the positions of Russell, Carnap, Popper and Kuhn to better understand the modern interpretation and implications of causal inference in epidemiological research.
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.
Performing Causal Configurations in e-Tourism: a Fuzzy-Set Approach
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Hugues Seraphin
2016-07-01
Full Text Available Search engines are constantly endeavouring to integrate social media mentions in the website ranking process. Search Engine Optimization (SEO principles can be used to impact website ranking, considering various social media channels� capability to drive traffic. Both practitioners and researchers has focused on the impact of social media on SEO, but paid little attention to the influences of social media interactions on organic search results. This study explores the causal configurations between social mention variables (strength, sentiment, passion, reach and the rankings of nine websites dedicated to hotel booking (according to organic search results. The social mention variables embedded into the conceptual model were provided by the real-time social media search and analysis tool (www.socialmention.com, while the rankings websites dedicated to hotel booking were determined after a targeted search on Google. The study employs fuzzy-set qualitative comparative analysis (fsQCA and the results reveal that social mention variables has complex links with the rankings of the hotel booking websites included into the sample, according to Quine-McCluskey algorithm solution. The findings extend the body of knowledge related to the impact of social media mentions on
The Epstein-Glaser causal approach to the Light-Front QED$_{4}$. I: Free theory
Bufalo, R; Soto, D E
2014-01-01
In this work we present the study of light-front field theories in the realm of axiomatic theory. It is known that when one uses the light-cone gauge pathological poles $\\left( k^{+}\\right) ^{-n}$ arises, demanding a prescription to be employed in order to tame these ill-defined poles and to have correct Feynman integrals due to the lack of Wick rotation in such theories. In order to shed a new light on this long standing problem we present here a discussion based on the use rigorous mathematical machinery of distributions combined with physical concepts, such as causality, to show how to deal with these singular propagators in a general fashion without making use of any prescription. The first step of our development will consist in showing how analytic representation for propagators arises by requiring general physical properties in the framework of Wightman's formalism. From that we shall determine the equal-time (anti)commutation relations in the light-front form for the scalar, fermionic fields and for t...
Causal and causally separable processes
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
Causality and the speed of sound
Ellis, G; MacCallum, M; Callum, Malcolm Mac; Ellis, George; Maartens, Roy
2007-01-01
A usual causal requirement on a viable theory of matter is that the speed of sound be at most the speed of light. In view of various recent papers querying this limit, the question is revisited here. We point to various issues confronting theories that violate the usual constraint.
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...
A meta-frontier approach for causal inference in productivity analysis
DEFF Research Database (Denmark)
Henningsen, Arne; Mpeta, Daniel F.; Adem, Anwar S.
use the approach of Bravo-Ureta, Greene and Solís (2012) to estimate two separate production frontiers (one for contract farmers and one for non-contract farmers) that account for potential biases due to self-selection on both observed and unobserved variables. Then, we follow Rao, Brümmer and Qaim...... by the contractor’s provision of (additional) extension service and seeds of high-yielding varieties to the contract farmers....
Ishanu Chattopadhyay
2014-01-01
While correlation measures are used to discern statistical relationships between observed variables in almost all branches of data-driven scientific inquiry, what we are really interested in is the existence of causal dependence. Designing an efficient causality test, that may be carried out in the absence of restrictive pre-suppositions on the underlying dynamical structure of the data at hand, is non-trivial. Nevertheless, ability to computationally infer statistical prima facie evidence of...
A meta-frontier approach for causal inference in productivity analysis
DEFF Research Database (Denmark)
Henningsen, Arne; Mpeta, Daniel F.; Adem, Anwar S.
(2012) and create a meta-frontier in order to estimate the effects of participation on the farms’ meta-technology ratio, their group technical efficiency, and their meta-technology technical efficiency. The empirical analysis uses a cross-sectional data set from sunflower farmers in Tanzania, where some...... impact on efficiency and productivity is mostly overlooked. This study addresses this salient gap by combining the approaches suggested by BravoUreta, Greene, and Solís (Empirical Economics 43:55–72, 2012) and Rao, Brümmer, and Qaim (American Journal of Agricultural Economics 94:891–912, 2012). We first...... use the approach of Bravo-Ureta, Greene and Solís (2012) to estimate two separate production frontiers (one for contract farmers and one for non-contract farmers) that account for potential biases due to self-selection on both observed and unobserved variables. Then, we follow Rao, Brümmer and Qaim...
Correlation Measure Equivalence in Dynamic Causal Structures
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...
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Xiaoyan Miao
Full Text Available BACKGROUND: Evidences from normal subjects suggest that the default-mode network (DMN has posterior cingulate cortex (PCC, medial prefrontal cortex (MPFC and inferior parietal cortex (IPC as its hubs; meanwhile, these DMN nodes are often found to be abnormally recruited in Alzheimer's disease (AD patients. The issues on how these hubs interact to each other, with the rest nodes of the DMN and the altered pattern of hubs with respect to AD, are still on going discussion for eventual final clarification. PRINCIPAL FINDINGS: To address these issues, we investigated the causal influences between any pair of nodes within the DMN using Granger causality analysis and graph-theoretic methods on resting-state fMRI data of 12 young subjects, 16 old normal controls and 15 AD patients respectively. We found that: (1 PCC/MPFC/IPC, especially the PCC, showed the widest and distinctive causal effects on the DMN dynamics in young group; (2 the pattern of DMN hubs was abnormal in AD patients compared to old control: MPFC and IPC had obvious causal interaction disruption with other nodes; the PCC showed outstanding performance for it was the only region having causal relation with all other nodes significantly; (3 the altered relation between hubs and other DMN nodes held potential as a noninvasive biomarker of AD. CONCLUSIONS: Our study, to the best of our knowledge, is the first to support the hub configuration of the DMN from the perspective of causal relationship, and reveal abnormal pattern of the DMN hubs in AD. Findings from young subjects provide additional evidence for the role of PCC/MPFC/IPC acting as hubs in the DMN. Compared to old control, MPFC and IPC lost their roles as hubs owing to the obvious causal interaction disruption, and PCC was preserved as the only hub showing significant causal relations with all other nodes.
Causal inference in public health.
Glass, Thomas A; Goodman, Steven N; Hernán, Miguel A; Samet, Jonathan M
2013-01-01
Causal inference has a central role in public health; the determination that an association is causal indicates the possibility for intervention. We review and comment on the long-used guidelines for interpreting evidence as supporting a causal association and contrast them with the potential outcomes framework that encourages thinking in terms of causes that are interventions. We argue that in public health this framework is more suitable, providing an estimate of an action's consequences rather than the less precise notion of a risk factor's causal effect. A variety of modern statistical methods adopt this approach. When an intervention cannot be specified, causal relations can still exist, but how to intervene to change the outcome will be unclear. In application, the often-complex structure of causal processes needs to be acknowledged and appropriate data collected to study them. These newer approaches need to be brought to bear on the increasingly complex public health challenges of our globalized world.
Granger causality for circular variables
Energy Technology Data Exchange (ETDEWEB)
Angelini, Leonardo; Pellicoro, Mario [Istituto Nazionale di Fisica Nucleare, Sezione di Bari (Italy); Dipartimento di Fisica, University of Bari (Italy); Stramaglia, Sebastiano, E-mail: sebastiano.stramaglia@ba.infn.i [Istituto Nazionale di Fisica Nucleare, Sezione di Bari (Italy); Dipartimento di Fisica, University of Bari (Italy)
2009-06-29
In this Letter we discuss the use of Granger causality to the analyze systems of coupled circular variables, by modifying a recently proposed method for multivariate analysis of causality. We show the application of the proposed approach on several Kuramoto systems, in particular one living on networks built by preferential attachment and a model for the transition from deeply to lightly anaesthetized states. Granger causalities describe the flow of information among variables.
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.
Ting, Hiram; Thurasamy, Ramayah
2016-01-01
Notwithstanding the rise of trendy coffee café, little is done to investigate revisit intention towards the café in the context of developing markets. In particular, there is a lack of study which provides theoretical and practical explanation to the perceptions and behaviours of infrequent customers. Hence, the study aims to look into the subject matter by using the theory of reasoned action and social exchange theory as the underpinning basis. The framework proposed by Pine and Gilmore (Strat Leadersh 28:18-23, 2000), which asserts the importance of product quality, service quality and experience quality in a progressive manner, is used to decompose perceived value in the model so as to determine their effects on intention to revisit the café. Given the importance to gain practical insights into revisit intention of infrequent customers, pragmatism stance is assumed. Explanatory sequential mixed-method design is thus adopted whereby qualitative approach is used to confirm and complement quantitative findings. Self-administered questionnaire-based survey is first administered before personal interview is carried out at various cafés. Partial least squares structural equation modelling and content analysis are appropriated successively. In the quantitative findings, although product quality, service quality and experience quality are found to have positive effect on perceived value and revisit intention towards trendy coffee café, experience quality is found to have the greater effect than the others among the infrequent customers. The qualitative findings not only confirm their importance, but most importantly explain the favourable impressions they have at trendy coffee café based on their last in-store experience. While product and service quality might not necessary stimulate them to revisit trendy coffee café, experience quality driven by purposes of visit would likely affect their intention to revisit. As retaining customers is of utmost importance to
Causal inference based on counterfactuals
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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.
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 mode...
Mans, U.
2014-01-01
This article introduces a new perspective on city connectivity in order to analyze non-hub cities and their position in the world economy. The author revisits the different approaches discussed in the Global Commodity Chains (GCC), Global Production Networks (GPN) and World City Network (WCN) discou
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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.
Chu, X.; Wu, C.; Qiu, J.
2016-01-01
In this article, we re-examine the causality between the stock returns and investor sentiment in China. The number of net added accounts is used as a proxy for investor sentiment. To mimic the different investment horizons of market participants, we use the wavelet method to decompose stock returns
A New Life-Span Approach to Conscientiousness and Health: Combining the Pieces of the Causal Puzzle
Friedman, Howard S.; Kern, Margaret L.; Hampson, Sarah E.; Duckworth, Angela Lee
2014-01-01
Conscientiousness has been shown to predict healthy behaviors, healthy social relationships, and physical health and longevity. The causal links, however, are complex and not well elaborated. Many extant studies have used comparable measures for conscientiousness, and a systematic endeavor to build cross-study analyses for conscientiousness and…
Directory of Open Access Journals (Sweden)
Børge G Nordestgaard
Full Text Available Adiposity, assessed as elevated body mass index (BMI, is associated with increased risk of ischemic heart disease (IHD; however, whether this is causal is unknown. We tested the hypothesis that positive observational associations between BMI and IHD are causal.In 75,627 individuals taken from two population-based and one case-control study in Copenhagen, we measured BMI, ascertained 11,056 IHD events, and genotyped FTO(rs9939609, MC4R(rs17782313, and TMEM18(rs6548238. Using genotypes as a combined allele score in instrumental variable analyses, the causal odds ratio (OR between BMI and IHD was estimated and compared with observational estimates. The allele score-BMI and the allele score-IHD associations used to estimate the causal OR were also calculated individually. In observational analyses the OR for IHD was 1.26 (95% CI 1.19-1.34 for every 4 kg/m(2 increase in BMI. A one-unit allele score increase associated with a 0.28 kg/m(2 (95 CI% 0.20-0.36 increase in BMI and an OR for IHD of 1.03 (95% CI 1.01-1.05 (corresponding to an average 1.68 kg/m(2 BMI increase and 18% increase in the odds of IHD for those carrying all six BMI increasing alleles. In instrumental variable analysis using the same allele score the causal IHD OR for a 4 kg/m(2 increase in BMI was 1.52 (95% CI 1.12-2.05.For every 4 kg/m(2 increase in BMI, observational estimates suggested a 26% increase in odds for IHD while causal estimates suggested a 52% increase. These data add evidence to support a causal link between increased BMI and IHD risk, though the mechanism may ultimately be through intermediate factors like hypertension, dyslipidemia, and type 2 diabetes. This work has important policy implications for public health, given the continuous nature of the BMI-IHD association and the modifiable nature of BMI. This analysis demonstrates the value of observational studies and their ability to provide unbiased results through inclusion of genetic data avoiding confounding
Energy Technology Data Exchange (ETDEWEB)
Bruno, J.; Duro, L.; Jordana, S.; Cera, E. [QuantiSci, Barcelona (Spain)
1996-02-01
Solubility limits constitute a critical parameter for the determination of the mobility of radionuclides in the near field and the geosphere, and consequently for the performance assessment of nuclear waste repositories. Mounting evidence from natural system studies indicate that trace elements, and consequently radionuclides, are associated to the dynamic cycling of major geochemical components. We have recently developed a thermodynamic approach to take into consideration the co-precipitation and co-dissolution processes that mainly control this linkage. The approach has been tested in various natural system studies with encouraging results. The Pocos de Caldas natural analogue was one of the sites where a full testing of our predictive geochemical modelling capabilities were done during the analogue project. We have revisited the Pocos de Caldas data and expanded the trace element solubility calculations by considering the documented trace metal/major ion interactions. This has been done by using the co-precipitation/co-dissolution approach. The outcome is as follows: A satisfactory modelling of the behaviour of U, Zn and REEs is achieved by assuming co-precipitation with ferrihydrite. Strontium concentrations are apparently controlled by its co-dissolution from Sr-rich fluorites. From the performance assessment point of view, the present work indicates that calculated solubility limits using the co-precipitation approach are in close agreement with the actual trace element concentrations. Furthermore, the calculated radionuclide concentrations are 2-4 orders of magnitude lower than conservative solubility limits calculated by assuming equilibrium with individual trace element phases. 34 refs, 18 figs, 13 tabs.
Jennings, Wesley G; Park, MiRang; Richards, Tara N; Tomsich, Elizabeth; Gover, Angela; Powers, Ráchael A
2014-12-01
Child maltreatment is one of the most commonly examined risk factors for violence in dating relationships. Often referred to as the intergenerational transmission of violence or cycle of violence, a fair amount of research suggests that experiencing abuse during childhood significantly increases the likelihood of involvement in violent relationships later, but these conclusions are primarily based on correlational research designs. Furthermore, the majority of research linking childhood maltreatment and dating violence has focused on samples of young people from the United States. Considering these limitations, the current study uses a rigorous, propensity score matching approach to estimate the causal effect of experiencing child physical abuse on adult dating violence among a large sample of South Korean emerging adults. Results indicate that the link between child physical abuse and adult dating violence is spurious rather than causal. Study limitations and implications are discussed.
Decomposing Granger Causality over the Spectrum
A. Lemmens (Aurélie); C. Croux (Christophe); M.G. Dekimpe (Marnik)
2004-01-01
textabstractWe develop a bivariate spectral Granger-causality test that can be applied at each individual frequency of the spectrum. The spectral approach to Granger causality has the distinct advantage that it allows to disentangle (potentially) di®erent Granger- causality relationships over di®ere
Revisiting the European sovereign bonds with a permutation-information-theory approach
Fernández Bariviera, Aurelio; Zunino, Luciano; Guercio, María Belén; Martinez, Lisana B.; Rosso, Osvaldo A.
2013-12-01
In this paper we study the evolution of the informational efficiency in its weak form for seventeen European sovereign bonds time series. We aim to assess the impact of two specific economic situations in the hypothetical random behavior of these time series: the establishment of a common currency and a wide and deep financial crisis. In order to evaluate the informational efficiency we use permutation quantifiers derived from information theory. Specifically, time series are ranked according to two metrics that measure the intrinsic structure of their correlations: permutation entropy and permutation statistical complexity. These measures provide the rectangular coordinates of the complexity-entropy causality plane; the planar location of the time series in this representation space reveals the degree of informational efficiency. According to our results, the currency union contributed to homogenize the stochastic characteristics of the time series and produced synchronization in the random behavior of them. Additionally, the 2008 financial crisis uncovered differences within the apparently homogeneous European sovereign markets and revealed country-specific characteristics that were partially hidden during the monetary union heyday.
Bogolubov, Nikolaj N; Taneri, Ufuk
2008-01-01
The main fundamental principles characterizing the vacuum field structure are formulated, the modeling of the related vacuum medium and point charged particle dynamics by means of devised field theoretic tools is analyzed. The Maxwell electrodynamic theory is revisited and newly derived from the suggested vacuum field structure principles, the classical special relativity theory relationship between the energy and the corresponding point particle mass is revisited and newly obtained. The Lorentz force expression with respect to arbitrary non-inertial reference frames is revisited and discussed in detail, some new interpretations of relations between the special relativity theory and quantum mechanics are presented. The famous quantum-mechanical Schr\\"{o}dinger type equation for a relativistic point particle in the external potential field within the quasiclassical approximation as the Plank constant $\\hbar \\to 0$ is obtained.
Temporal causality between house prices and output in the U.S.: a bootstrap rolling-window approach
CSIR Research Space (South Africa)
Nyakabawo, W
2015-07-01
Full Text Available and recessions in the U.S, as well as different market booms and busts, creating substantial volatility, that may provide different outcomes from other less-volatile periods (Iacoviello and Neri, 2010). We test the stability of the short- and long... Granger non- causality tests for a series of rolling-window sub-sample estimations. The subprime mortgage lending fiasco and the financial crisis sparked a price bubble and collapse in the housing market and the subsequent Great Recession. Many...
Discrete causal theory emergent spacetime and the causal metric hypothesis
Dribus, Benjamin F
2017-01-01
This book evaluates and suggests potentially critical improvements to causal set theory, one of the best-motivated approaches to the outstanding problems of fundamental physics. Spacetime structure is of central importance to physics beyond general relativity and the standard model. The causal metric hypothesis treats causal relations as the basis of this structure. The book develops the consequences of this hypothesis under the assumption of a fundamental scale, with smooth spacetime geometry viewed as emergent. This approach resembles causal set theory, but differs in important ways; for example, the relative viewpoint, emphasizing relations between pairs of events, and relationships between pairs of histories, is central. The book culminates in a dynamical law for quantum spacetime, derived via generalized path summation.
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Gaurav Singh Tomar
2013-01-01
Full Text Available The supraclavicular approach was first put into clinical practice in 1965 by Yoffa and is an underused method for gaining central access. It offers several advantages over the conventional infraclavicular approach to the subclavian vein. At the insertion site, the subclavian vein is closer to the skin, and the right-sided approach offers a straighter path into the subclavian vein. Also, this site is often more accessible during CPR and surgical procedures. In patients who are obese, this anatomic area is less distorted and in patient with congestive heart failure and cervical spine instability repositioning is not required.
Attiaoui, Imed; Toumi, Hassen; Ammouri, Bilel; Gargouri, Ilhem
2017-05-01
This research examines the causality (For the remainder of the paper, the notion of causality refers to Granger causality.) links among renewable energy consumption (REC), CO2 emissions (CE), non-renewable energy consumption (NREC), and economic growth (GDP) using an autoregressive distributed lag model based on the pooled mean group estimation (ARDL-PMG) and applying Granger causality tests for a panel consisting of 22 African countries for the period between 1990 and 2011. There is unidirectional and irreversible short-run causality from CE to GDP. The causal direction between CE and REC is unobservable over the short-term. Moreover, we find unidirectional, short-run causality from REC to GDP. When testing per pair of variables, there are short-run bidirectional causalities among REC, CE, and GDP. However, if we add CE to the variables REC and NREC, the causality to GDP is observable, and causality from the pair REC and NREC to economic growth is neutral. Likewise, if we add NREC to the variables GDP and REC, there is causality. There are bidirectional long-run causalities among REC, CE, and GDP, which supports the feedback assumption. Causality from GDP to REC is not strong for the panel. If we test per pair of variables, the strong causality from GDP and CE to REC is neutral. The long-run PMG estimates show that NREC and gross domestic product increase CE, whereas REC decreases CE.
Causal Effect Estimation Methods
2014-01-01
Relationship between two popular modeling frameworks of causal inference from observational data, namely, causal graphical model and potential outcome causal model is discussed. How some popular causal effect estimators found in applications of the potential outcome causal model, such as inverse probability of treatment weighted estimator and doubly robust estimator can be obtained by using the causal graphical model is shown. We confine to the simple case of binary outcome and treatment vari...
Spectral Geometry and Causality
Kopf, T
1996-01-01
For a physical interpretation of a theory of quantum gravity, it is necessary to recover classical spacetime, at least approximately. However, quantum gravity may eventually provide classical spacetimes by giving spectral data similar to those appearing in noncommutative geometry, rather than by giving directly a spacetime manifold. It is shown that a globally hyperbolic Lorentzian manifold can be given by spectral data. A new phenomenon in the context of spectral geometry is observed: causal relationships. The employment of the causal relationships of spectral data is shown to lead to a highly efficient description of Lorentzian manifolds, indicating the possible usefulness of this approach. Connections to free quantum field theory are discussed for both motivation and physical interpretation. It is conjectured that the necessary spectral data can be generically obtained from an effective field theory having the fundamental structures of generalized quantum mechanics: a decoherence functional and a choice of...
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Miljana Valdec
2015-03-01
Full Text Available This paper contributes to the literature by using propensity score matching to test for causal effects of starting to export on firm performance in Croatian manufacturing firm-level data. The results confirm that exporters have characteristics superior to those of non-exporters. In the main sample specification there is pervasive evidence of self-selection into export markets, meaning that firms are successful years before they become exporters. Using multiple firm performance indicators, panel and cross section data models together with various sample specifications there is scant evidence on learning-by-exporting which holds true only in a few cases. On the other hand, higher sales growth is found to be a more conclusive distinguishing characteristic of new exporters. As in similar studies, we find that a part of the results depends on the number of export starters in the estimation sample.
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Jeannette Koschmann
2015-05-01
Full Text Available A strategy is presented that allows a causal analysis of co-expressed genes, which may be subject to common regulatory influences. A state-of-the-art promoter analysis for potential transcription factor (TF binding sites in combination with a knowledge-based analysis of the upstream pathway that control the activity of these TFs is shown to lead to hypothetical master regulators. This strategy was implemented as a workflow in a comprehensive bioinformatic software platform. We applied this workflow to gene sets that were identified by a novel triclustering algorithm in naphthalene-induced gene expression signatures of murine liver and lung tissue. As a result, tissue-specific master regulators were identified that are known to be linked with tumorigenic and apoptotic processes. To our knowledge, this is the first time that genes of expression triclusters were used to identify upstream regulators.
Thomas, R
2006-07-01
The problem of disentangling complex dynamic systems is addressed, especially with a view to identifying those variables that take part in the essential qualitative behaviour of systems. The author presents a series of reflections about the methods of formalisation together with the principles that govern the global operation of systems. In particular, a section on circuits, nuclei, and circular causality and a rather detailed description of the analytic use of the generalised asynchronous logical description, together with a brief description of its synthetic use (OreverseO logic). Some basic rules are recalled, such as the fact that a positive circuit is a necessary condition of multistationarity. Also, the interest of considering as a model, rather than a well-defined set of differential equations, a variety of systems that differ from each other only by the values of constant terms is emphasised. All these systems have a common Jacobian matrix and for all of them phase space has exactly the same structure. It means that all can be partitioned in the same way as regards the signs of the eigenvalues and thus as regards the precise nature of any steady states that might be present. Which steady states are actually present, depends on the values of terms of order zero in the ordinary differential equations (ODEs), and it is easy to find for which values of these terms a given point in phase space is steady. Models can be synthesised first at the level of the circuits involved in the Jacobian matrix (that determines which types and numbers of steady states are consistent with the model), then only at the level of terms of order zero in the ODE's (that determines which of the steady states actually exist), hence the title 'Circular casuality'.
Holland in Iceland Revisited: An Emic Approach to Evaluating U.S. Vocational Interest Models
Einarsdottir, Sif; Rounds, James; Su, Rong
2010-01-01
An emic approach was used to test the structural validity and applicability of Holland's (1997) RIASEC (Realistic, Investigative, Artistic, Social, Enterprising, Conventional) model in Iceland. Archival data from the development of the Icelandic Interest Inventory (Einarsdottir & Rounds, 2007) were used in the present investigation. The data…
Cumming, Brett
2012-01-01
The three concepts Approach, Design and Procedure as proposed in Rodgers' Framework are considered particularly effective as a framework in second language teaching with the specific aim of developing communication as well as for better understanding methodology in the use of communicative language use.
Revisiting the Whole-School Approach to Bullying: Really Looking at the Whole School
Richard, Jacques F.; Schneider, Barry H.; Mallet, Pascal
2012-01-01
The whole-school approach to bullying prevention is predicated on the assumption that bullying is a systemic problem, and, by implication, that intervention must be directed at the entire school context rather than just at individual bullies and victims. Unfortunately, recent meta-analyses that have looked at various bullying programs from many…
Holland in Iceland Revisited: An Emic Approach to Evaluating U.S. Vocational Interest Models
Einarsdottir, Sif; Rounds, James; Su, Rong
2010-01-01
An emic approach was used to test the structural validity and applicability of Holland's (1997) RIASEC (Realistic, Investigative, Artistic, Social, Enterprising, Conventional) model in Iceland. Archival data from the development of the Icelandic Interest Inventory (Einarsdottir & Rounds, 2007) were used in the present investigation. The data…
The Two-Capacitor Problem Revisited: A Mechanical Harmonic Oscillator Model Approach
Lee, Keeyung
2009-01-01
The well-known two-capacitor problem, in which exactly half the stored energy disappears when a charged capacitor is connected to an identical capacitor, is discussed based on the mechanical harmonic oscillator model approach. In the mechanical harmonic oscillator model, it is shown first that "exactly half" the work done by a constant applied…
An Alternative Paradigm for Evidence-Based Medicine: Revisiting Lawrence Weed, MD’s Systems Approach
Shukor, Ali Rafik
2017-01-01
Lawrence Weed, MD, is renowned for being the father of the Problem-Oriented Medical Record (POMR), the medical care standard for collecting, managing, and contextualizing patient data in medical records. What have been consistently overlooked are his teachings on knowledge coupling, which refers to matching patient data with associated medical knowledge. Together, the POMR standard and knowledge coupling are meant to form the basis of a systems approach that enables individualized evidence-based decision making within the context of multimorbidity and patient complexity. The POMR and knowledge coupling tools operationalize a problem-oriented model that reflects a sophisticated general systems theoretical approach to knowledge. This paradigm transcends reductionist approaches to knowledge by depicting how the meaning of specific entities (eg, disease constructs) and their associated probabilities can only be understood within their respective spatiotemporal and biopsychosocial relational contexts. Rigorous POMRs therefore require knowledge inputs from a network of interconnections among specific entities, which Dr Weed enabled through development of the Knowledge Net standard. The Knowledge Net’s relational structure determines the applicability of knowledge within specific patient contexts. To enable the linkage of unique combinations of data in individual patient POMRs with existing medical knowledge structured in Knowledge Nets, Dr Weed developed the Knowledge Coupling standard. Dr Weed’s standards for record keeping and knowledge coupling form the basis of a combinatorial approach to evidence-based medicine that fulfills Stange’s call for a science of connectedness. Ensuing individualized processes of care become the dynamo powering a learning health care system that enables a co-construction of health premised on empowerment and intelligent human decision making, rather than promoting the artificial intelligence of tools. If the value of Engel
Revisiting the $B^{0} \\to \\pi^{0}\\pi^{0} $ decays in the perturbative QCD approach
Li, Yun-Feng
2016-01-01
We recalculate the branching ratio and CP asymmetry for $\\bar{B}^{0} (B^{0})\\to \\pi^{0}\\pi^{0}$ decays in the Perturbative QCD approach. In this approach, we consider all the possible diagrams including non-factorizable contributions and annihilation contributions, and identity principle is also taken into account. We obtain the branching ratio of $B^{0}\\to\\pi^{0}\\pi^{0}$ is about $1.2\\times10^{-6}$. Our result is in agreement with the latest measured branching ratio of $B^{0}\\to\\pi^{0}\\pi^{0}$ by the Belle and HFAG Collaborations. We also predict large direct CP asymmetry and mixing CP asymmetry in $B^{0}\\to\\pi^{0}\\pi^{0}$ decays, which can be tested by the running LHC-b experiments.
Revisiting support optimization at the Driskos tunnel using a quantitative risk approach
Directory of Open Access Journals (Sweden)
J. Connor Langford
2016-04-01
Full Text Available With the scale and cost of geotechnical engineering projects increasing rapidly over the past few decades, there is a clear need for the careful consideration of calculated risks in design. While risk is typically dealt with subjectively through the use of conservative design parameters, with the advent of reliability-based methods, this no longer needs to be the case. Instead, a quantitative risk approach can be considered that incorporates uncertainty in ground conditions directly into the design process to determine the variable ground response and support loads. This allows for the optimization of support on the basis of both worker safety and economic risk. This paper presents the application of such an approach to review the design of the initial lining system along a section of the Driskos twin tunnels as part of the Egnatia Odos highway in northern Greece. Along this section of tunnel, weak rock masses were encountered as well as high in situ stress conditions, which led to excessive deformations and failure of the as built temporary support. Monitoring data were used to validate the rock mass parameters selected in this area and a risk approach was used to determine, in hindsight, the most appropriate support category with respect to the cost of installation and expected cost of failure. Different construction sequences were also considered in the context of both convenience and risk cost.
Baas, Matthijs; Nijstad, Bernard A; Boot, Nathalie C; De Dreu, Carsten K W
2016-06-01
Although many believe that creativity associates with a vulnerability to psychopathology, research findings are inconsistent. Here we address this possible linkage between risk of psychopathology and creativity in nonclinical samples. We propose that propensity for specific psychopathologies can be linked to basic motivational approach and avoidance systems, and that approach and avoidance motivation differentially influences creativity. Based on this reasoning, we predict that propensity for approach-based psychopathologies (e.g., positive schizotypy and risk of bipolar disorder) associates with increased creativity, whereas propensity for avoidance-based psychopathologies (e.g., anxiety, negative schizotypy, and depressive mood) associates with reduced creativity. Previous meta-analyses resonate with this proposition and showed small positive relations between positive schizotypy and creativity and small negative relations between negative schizotypy and creativity and between anxiety and creativity. To this we add new meta-analytic findings showing that risk of bipolar disorder (e.g., hypomania, mania) positively associates with creativity (k = 28, r = .224), whereas depressive mood negatively associates (albeit weakly) with creativity (k = 39, r = -.064). Our theoretical framework, along with the meta-analytic results, indicates when and why specific psychopathologies, and their inclinations, associate with increased or, instead, reduced creativity. (PsycINFO Database Record
A revisitation of the phenomenological approach with applications to radar target decomposition
Huynen, J. R.
1982-05-01
This report highlights some results of a phenomenological approach to radar targets, with applications. The approach grew out of the common sense realization that only those target data are acceptable for discrimination and identification purposes which can be shown to relate in a physically meaningful way to basic target structure. Only then can data, often gathered at great expense, obtained for one type of system, be expected to be useful productively for a new system and hence improve efficiency and cost factors. Although these comments are almost self-evident and common sensical in nature, examples are given to show how this systematic approach has an important effect on the mathematical and practical development toward target identification (inverse) problems. The effect of antenna and target orientation angle on corrupting target information is stressed, in contrast to common practice to allow single H or V polarization data to be accepted as meaningful. The report summarizes the general target decomposition theorems, proved by the author in 1970. It shows that a single-coherent object is electromagnetically irreducible (it cannot be broken down mathematically as the incoherent sum of the smaller parts without violating physical principles). All this opens up new vistas for optimal signal processing schemes which extend the present predominantly scalar case to include vector scattering problems. It is hoped that by these efforts improved reliability with reduced costs for target discrimination and identification purposes can be achieved.
Wolff, Phillip; Barbey, Aron K.
2015-01-01
Causal composition allows people to generate new causal relations by combining existing causal knowledge. We introduce a new computational model of such reasoning, the force theory, which holds that people compose causal relations by simulating the processes that join forces in the world, and compare this theory with the mental model theory (Khemlani et al., 2014) and the causal model theory (Sloman et al., 2009), which explain causal composition on the basis of mental models and structural equations, respectively. In one experiment, the force theory was uniquely able to account for people's ability to compose causal relationships from complex animations of real-world events. In three additional experiments, the force theory did as well as or better than the other two theories in explaining the causal compositions people generated from linguistically presented causal relations. Implications for causal learning and the hierarchical structure of causal knowledge are discussed. PMID:25653611
Causally nonseparable processes admitting a causal model
Feix, Adrien; Araújo, Mateus; Brukner, Časlav
2016-08-01
A recent framework of quantum theory with no global causal order predicts the existence of ‘causally nonseparable’ processes. Some of these processes produce correlations incompatible with any causal order (they violate so-called ‘causal inequalities’ analogous to Bell inequalities) while others do not (they admit a ‘causal model’ analogous to a local model). Here we show for the first time that bipartite causally nonseparable processes with a causal model exist, and give evidence that they have no clear physical interpretation. We also provide an algorithm to generate processes of this kind and show that they have nonzero measure in the set of all processes. We demonstrate the existence of processes which stop violating causal inequalities but are still causally nonseparable when mixed with a certain amount of ‘white noise’. This is reminiscent of the behavior of Werner states in the context of entanglement and nonlocality. Finally, we provide numerical evidence for the existence of causally nonseparable processes which have a causal model even when extended with an entangled state shared among the parties.
Revisiting the cape cod bacteria injection experiment using a stochastic modeling approach
Maxwell, R.M.; Welty, C.; Harvey, R.W.
2007-01-01
Bromide and resting-cell bacteria tracer tests conducted in a sandy aquifer at the U.S. Geological Survey Cape Cod site in 1987 were reinterpreted using a three-dimensional stochastic approach. Bacteria transport was coupled to colloid filtration theory through functional dependence of local-scale colloid transport parameters upon hydraulic conductivity and seepage velocity in a stochastic advection - dispersion/attachment - detachment model. Geostatistical information on the hydraulic conductivity (K) field that was unavailable at the time of the original test was utilized as input. Using geostatistical parameters, a groundwater flow and particle-tracking model of conservative solute transport was calibrated to the bromide-tracer breakthrough data. An optimization routine was employed over 100 realizations to adjust the mean and variance ofthe natural-logarithm of hydraulic conductivity (InK) field to achieve best fit of a simulated, average bromide breakthrough curve. A stochastic particle-tracking model for the bacteria was run without adjustments to the local-scale colloid transport parameters. Good predictions of mean bacteria breakthrough were achieved using several approaches for modeling components of the system. Simulations incorporating the recent Tufenkji and Elimelech (Environ. Sci. Technol. 2004, 38, 529-536) correlation equation for estimating single collector efficiency were compared to those using the older Rajagopalan and Tien (AIChE J. 1976, 22, 523-533) model. Both appeared to work equally well at predicting mean bacteria breakthrough using a constant mean bacteria diameter for this set of field conditions. Simulations using a distribution of bacterial cell diameters available from original field notes yielded a slight improvement in the model and data agreement compared to simulations using an average bacterial diameter. The stochastic approach based on estimates of local-scale parameters for the bacteria-transport process reasonably captured
THE NOTION OF AUTHENTICITY REVISITED A SEARCH FOR URBAN HERITAGE CONSERVATION APPROACH
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Widjaja Martokusumo
2016-01-01
Full Text Available During the last five decades urban heritage conservation has evolved significantly as an urban design discipline which is nec-essary for dealing with older urban areas that were once reduced to being the locus of monuments worthy of architectural conservation. Recent international experiences highlight conflicting interests in term of intention and focus, between archaeologist, who focus on monument restoration, and urban designers, who emphasize the need of conserving the spirit of the past. Nonetheless, a new understand-ing about urban heritage was materialized from the latest urban conservation praxis involving archaeologists, urban planners, urban de-signers and architects. The new insight about urban heritage has brought new approaches to urban conservation during recent decades. The latest of these approaches aim at the creation of enjoyable urban experiences that have a historical identity, rather at the simple re-tention of authentic urban history. In fact, urban heritage conservation is not simply a matter of preserving and creating harmonious constellation between historic fabrics and new infill developments, but rather a continuing project in shaping the environment. Based on several observations, this paper discusses that historic fabrics contribute considerably in place making, in enriching the quality of a place and offer opportunities for cultural appreciation. Thus, creating a sense of place is more than to the exact restoration of urban details. It also argues the importance of the making of interesting and liveable urban quarters that guarantee social, cultural and environmental sustainability.
Court, Deborah
1999-01-01
Revisits and reviews Imre Lakatos' ideas on "Falsification and the Methodology of Scientific Research Programmes." Suggests that Lakatos' framework offers an insightful way of looking at the relationship between theory and research that is relevant not only for evaluating research programs in theoretical physics, but in the social…
Revisiting the Cape Cod Bacteria Injection Experiment Using a Stochastic Modeling Approach
Energy Technology Data Exchange (ETDEWEB)
Maxwell, R M; Welty, C; Harvey, R W
2006-11-22
Bromide and resting-cell bacteria tracer tests carried out in a sand and gravel aquifer at the USGS Cape Cod site in 1987 were reinterpreted using a three-dimensional stochastic approach and Lagrangian particle tracking numerical methods. Bacteria transport was strongly coupled to colloid filtration through functional dependence of local-scale colloid transport parameters on hydraulic conductivity and seepage velocity in a stochastic advection-dispersion/attachment-detachment model. Information on geostatistical characterization of the hydraulic conductivity (K) field from a nearby plot was utilized as input that was unavailable when the original analysis was carried out. A finite difference model for groundwater flow and a particle-tracking model of conservative solute transport was calibrated to the bromide-tracer breakthrough data using the aforementioned geostatistical parameters. An optimization routine was utilized to adjust the mean and variance of the lnK field over 100 realizations such that a best fit of a simulated, average bromide breakthrough curve is achieved. Once the optimal bromide fit was accomplished (based on adjusting the lnK statistical parameters in unconditional simulations), a stochastic particle-tracking model for the bacteria was run without adjustments to the local-scale colloid transport parameters. Good predictions of the mean bacteria breakthrough data were achieved using several approaches for modeling components of the system. Simulations incorporating the recent Tufenkji and Elimelech [1] equation for estimating single collector efficiency were compared to those using the Rajagopalan and Tien [2] model. Both appeared to work equally well at predicting mean bacteria breakthrough using a constant mean bacteria diameter for this set of field conditions, with the Rajagopalan and Tien model yielding approximately a 30% lower peak concentration and less tailing than the Tufenkji and Elimelech formulation. Simulations using a distribution
Ordoñez, Paulina; Gallego, David; Ribera, Pedro; Peña-Ortiz, Cristina; Garcia-Herrera, Ricardo; Vega, Inmaculada; Gómez, Francisco de Paula
2016-04-01
The Indian Summer Monsoon onset is one of the meteorological events most anticipated in the world. Due to its relevance for the population, the India Meteorological Department has dated the onset over the southern tip of the Indian Peninsula (Kerala) since 1901. The traditional method to date the onset was based in the judgment of skilled meteorologist and because of this, the method was considered subjective and not adequate for the study of long-term changes in the onset. A new method for determining the monsoon onset based solely on objective criteria has been in use since 2006. Unfortunately, the new method relies -among other variables- on OLR measurements. This requirement impedes the construction of an objective onset series before the satellite era. An alternative approach to establish the onset by objective methods is the use of the wind field. During the last decade, some works have demonstrated that the changes in the wind direction in some areas of the Indian Ocean can be used to determine the monsoon onset rather precisely. However, this method requires precise wind observations over a large oceanic area which has limited the periods covered for such kind of indices to those of the reanalysis products. In this work we present a new approach to track the Indian monsoon onset based solely on historical wind direction measurements taken onboard ships. Our new series provides an objective record of the onset since the last decade of the 19th century and perhaps more importantly, it can incorporate any new historical wind record not yet known in order to extend the series length. The new series captures quite precisely the rapid precipitation increase associated to the monsoon onset, correlates well with previous approaches and it is robust against anomalous (bogus) onsets. Although no significant trends in the onset date were detected, a tendency to later than average onsets during the 1900-1925 and 1970-1990 periods and earlier than average onsets between
Directory of Open Access Journals (Sweden)
Arup Kumar Baksi
2012-08-01
Full Text Available Information technology induced communications (ICTs have revolutionized the operational aspects of service sector and have triggered a perceptual shift in service quality as rapid dis-intermediation has changed the access-mode of services on part of the consumers. ICT-enabled services further stimulated the perception of automated service quality with renewed dimensions and there subsequent significance to influence the behavioural outcomes of the consumers. Customer Relationship Management (CRM has emerged as an offshoot to technological breakthrough as it ensured service-encapsulation by integrating people, process and technology. This paper attempts to explore the relationship between automated service quality and its behavioural consequences in a relatively novel business-philosophy – CRM. The study has been conducted on the largest public sector bank of India - State bank of India (SBI at Kolkata which has successfully completed its decade-long operational automation in the year 2008. The study used structural equation modeling (SEM to justify the proposed model construct and causal loop diagramming (CLD to depict the negative and positive linkages between the variables.
MultiPaths Revisited - A novel approach using OpenFlow-enabled devices
Al-Shabibi, Ali; Martin, Brian
2011-06-11
This thesis presents novel approaches enhancing the performance of computer networks using multipaths. Our enhancements take the form of congestion-aware routing protocols. We present three protocols called MultiRoute, Step-Route, and finally PathRoute. Each of these protocols leverage both local and remote congestion statistics and build different representations (or views) of the network congestion by using an innovative representation of congestion for router-router links. These congestion statistics are then distributed via an aggregation protocol to other routers in the network. For many years, multipath routing protocols have only been used in simple situations, such as Link Aggregation and/or networks where paths of equal cost (and therefore equal delay) exist. But, paths of unequal costs are often discarded to the benefit of shortest path only routing because it is known that paths of unequal length present different delays and therefore cause out of order packets which cause catastrophic network per...
Revisiting the Twist-3 Distribution Amplitudes of K Meson Within the QCD Background Field Approach
Institute of Scientific and Technical Information of China (English)
钟涛; 吴兴刚; 韩华勇; 廖其力; 付海斌; 方祯云
2012-01-01
In the present paper, we investigate the kaon twist-3 distribution amplitudes （DAs）Cp within the QCD background field approach. The SUf （3）-breaking effects are studied in detail under a systematical way, especiaJ1y the sum rules for the moments of are obtained by keeping all the mass terms in the s-quark propagator consistently. After adding all the uncertainties in quadrature, the first two Gegenbauler moments of are a GeV. A detailed discussion on the properties tion parameters moments shows that the higher-order s-quark mass terms can indeed provide sizable contributions. Fhrthermore, based on the newly obtained moments, a model for the kaon twist-3 wavefunction with a better end-point behavior is constructed, which shall be useful for perturbative QCD calculations. As a byproduct, we make a discussion on the properties of the pion twist-3 DAs.
Defining Jazz Revisited: Taking a social constructionist approach to the characterisation of jazz
DEFF Research Database (Denmark)
Høyer, Ole Izard
2017-01-01
This article reconsiders the definition of jazz as a case study in relation to how a musical genre is constituted through narratives of culture and identity in musical culture. Rethinking the definition of jazz as a way of characterisation through a social constructionist approach, this article...... will provide a discussion of the academic literature of jazz and how jazz has been characterised throughout history in an American context. The discussion presented is divided into three sections. First, a short outline of the term ‘jazz’ and its origin. Second, providing a historiography of how literature has...... defined jazz through time with a thematization on different aspects of the nature of jazz and genre. Here jazz culture is discussed in relation to American cultural heritage, setting the focus on the relationship between multiple discourses of jazz through history. Finally, this article discusses...
Pogue, Brian W.; Elliott, Jonathan T.; Kanick, Stephen C.; Davis, Scott C.; Samkoe, Kimberley S.; Maytin, Edward V.; Pereira, Stephen P.; Hasan, Tayyaba
2016-04-01
Photodynamic therapy (PDT) can be a highly complex treatment, with many parameters influencing treatment efficacy. The extent to which dosimetry is used to monitor and standardize treatment delivery varies widely, ranging from measurement of a single surrogate marker to comprehensive approaches that aim to measure or estimate as many relevant parameters as possible. Today, most clinical PDT treatments are still administered with little more than application of a prescribed drug dose and timed light delivery, and thus the role of patient-specific dosimetry has not reached widespread clinical adoption. This disconnect is at least partly due to the inherent conflict between the need to measure and understand multiple parameters in vivo in order to optimize treatment, and the need for expedience in the clinic and in the regulatory and commercialization process. Thus, a methodical approach to selecting primary dosimetry metrics is required at each stage of translation of a treatment procedure, moving from complex measurements to understand PDT mechanisms in pre-clinical and early phase I trials, towards the identification and application of essential dose-limiting and/or surrogate measurements in phase II/III trials. If successful, identifying the essential and/or reliable surrogate dosimetry measurements should help facilitate increased adoption of clinical PDT. In this paper, examples of essential dosimetry points and surrogate dosimetry tools that may be implemented in phase II/III trials are discussed. For example, the treatment efficacy as limited by light penetration in interstitial PDT may be predicted by the amount of contrast uptake in CT, and so this could be utilized as a surrogate dosimetry measurement to prescribe light doses based upon pre-treatment contrast. Success of clinical ALA-based skin lesion treatment is predicted almost uniquely by the explicit or implicit measurements of photosensitizer and photobleaching, yet the individualization of treatment
Pogue, Brian W; Elliott, Jonathan T; Kanick, Stephen C; Davis, Scott C; Samkoe, Kimberley S; Maytin, Edward V; Pereira, Stephen P; Hasan, Tayyaba
2016-04-01
Photodynamic therapy (PDT) can be a highly complex treatment, with many parameters influencing treatment efficacy. The extent to which dosimetry is used to monitor and standardize treatment delivery varies widely, ranging from measurement of a single surrogate marker to comprehensive approaches that aim to measure or estimate as many relevant parameters as possible. Today, most clinical PDT treatments are still administered with little more than application of a prescribed drug dose and timed light delivery, and thus the role of patient-specific dosimetry has not reached widespread clinical adoption. This disconnect is at least partly due to the inherent conflict between the need to measure and understand multiple parameters in vivo in order to optimize treatment, and the need for expedience in the clinic and in the regulatory and commercialization process. Thus, a methodical approach to selecting primary dosimetry metrics is required at each stage of translation of a treatment procedure, moving from complex measurements to understand PDT mechanisms in pre-clinical and early phase I trials, towards the identification and application of essential dose-limiting and/or surrogate measurements in phase II/III trials. If successful, identifying the essential and/or reliable surrogate dosimetry measurements should help facilitate increased adoption of clinical PDT. In this paper, examples of essential dosimetry points and surrogate dosimetry tools that may be implemented in phase II/III trials are discussed. For example, the treatment efficacy as limited by light penetration in interstitial PDT may be predicted by the amount of contrast uptake in CT, and so this could be utilized as a surrogate dosimetry measurement to prescribe light doses based upon pre-treatment contrast. Success of clinical ALA-based skin lesion treatment is predicted almost uniquely by the explicit or implicit measurements of photosensitizer and photobleaching, yet the individualization of treatment
An alternative approach to analyze Ipsative data. Revisiting Experiential Learning Theory
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Joan Manuel eBatista-Foguet
2015-11-01
Full Text Available The ritualistic use of statistical models regardless of the type of data actually available is a common practice across disciplines. Statistical models involve a series of assumptions whose existence is often neglected altogether, thus making the mentioned common practice even more pervasive. This paper illustrates the consequences of this ritualistic practice within Kolb’s Experiential Learning Theory (ELT operationalized through its Learning Style Inventory (KLSI. We show how using a well-known methodology in other disciplines -compositional data analysis (CODA- KLSI data can be properly analyzed. In addition, a third dimension of the KLSI is unveiled providing room for future research. This third dimension describes an individual’s relative preference for learning by prehension rather than by transformation. Using a sample of European MBA students, we relate this dimension with another self-assessment instrument, the Philosophical Orientation Questionnaire (POQ, and with an observer-assessed instrument, the Emotional and Social Inventory (ESCI-U. Both show plausible statistical relationships. An intellectual operating philosophy is linked to a preference for prehension, whereas a pragmatic operating philosophy is linked to transformation. Self-management and social awareness competencies are linked to a learning preference for transforming knowledge, whereas relationship management and cognitive competencies are more related to approaching learning by prehension.
An Alternative Approach to Analyze Ipsative Data. Revisiting Experiential Learning Theory.
Batista-Foguet, Joan M; Ferrer-Rosell, Berta; Serlavós, Ricard; Coenders, Germà; Boyatzis, Richard E
2015-01-01
The ritualistic use of statistical models regardless of the type of data actually available is a common practice across disciplines which we dare to call type zero error. Statistical models involve a series of assumptions whose existence is often neglected altogether, this is specially the case with ipsative data. This paper illustrates the consequences of this ritualistic practice within Kolb's Experiential Learning Theory (ELT) operationalized through its Learning Style Inventory (KLSI). We show how using a well-known methodology in other disciplines-compositional data analysis (CODA) and log ratio transformations-KLSI data can be properly analyzed. In addition, the method has theoretical implications: a third dimension of the KLSI is unveiled providing room for future research. This third dimension describes an individual's relative preference for learning by prehension rather than by transformation. Using a sample of international MBA students, we relate this dimension with another self-assessment instrument, the Philosophical Orientation Questionnaire (POQ), and with an observer-assessed instrument, the Emotional and Social Competency Inventory (ESCI-U). Both show plausible statistical relationships. An intellectual operating philosophy (IOP) is linked to a preference for prehension, whereas a pragmatic operating philosophy (POP) is linked to transformation. Self-management and social awareness competencies are linked to a learning preference for transforming knowledge, whereas relationship management and cognitive competencies are more related to approaching learning by prehension.
Campbell's and Rubin's Perspectives on Causal Inference
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…
Campbell's and Rubin's Perspectives on Causal Inference
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…
Friston, K J; Harrison, L; Penny, W
2003-08-01
In this paper we present an approach to the identification of nonlinear input-state-output systems. By using a bilinear approximation to the dynamics of interactions among states, the parameters of the implicit causal model reduce to three sets. These comprise (1) parameters that mediate the influence of extrinsic inputs on the states, (2) parameters that mediate intrinsic coupling among the states, and (3) [bilinear] parameters that allow the inputs to modulate that coupling. Identification proceeds in a Bayesian framework given known, deterministic inputs and the observed responses of the system. We developed this approach for the analysis of effective connectivity using experimentally designed inputs and fMRI responses. In this context, the coupling parameters correspond to effective connectivity and the bilinear parameters reflect the changes in connectivity induced by inputs. The ensuing framework allows one to characterise fMRI experiments, conceptually, as an experimental manipulation of integration among brain regions (by contextual or trial-free inputs, like time or attentional set) that is revealed using evoked responses (to perturbations or trial-bound inputs, like stimuli). As with previous analyses of effective connectivity, the focus is on experimentally induced changes in coupling (cf., psychophysiologic interactions). However, unlike previous approaches in neuroimaging, the causal model ascribes responses to designed deterministic inputs, as opposed to treating inputs as unknown and stochastic.
An introduction to causal inference.
Pearl, Judea
2010-02-26
This paper summarizes recent advances in causal inference and underscores the paradigmatic shifts that must be undertaken in moving from traditional statistical analysis to causal analysis of multivariate data. Special emphasis is placed on the assumptions that underlie all causal inferences, the languages used in formulating those assumptions, the conditional nature of all causal and counterfactual claims, and the methods that have been developed for the assessment of such claims. These advances are illustrated using a general theory of causation based on the Structural Causal Model (SCM) described in Pearl (2000a), which subsumes and unifies other approaches to causation, and provides a coherent mathematical foundation for the analysis of causes and counterfactuals. In particular, the paper surveys the development of mathematical tools for inferring (from a combination of data and assumptions) answers to three types of causal queries: those about (1) the effects of potential interventions, (2) probabilities of counterfactuals, and (3) direct and indirect effects (also known as "mediation"). Finally, the paper defines the formal and conceptual relationships between the structural and potential-outcome frameworks and presents tools for a symbiotic analysis that uses the strong features of both. The tools are demonstrated in the analyses of mediation, causes of effects, and probabilities of causation.
González-Ramos, Daniel; Gorter de Vries, Arthur R; Grijseels, Sietske S; van Berkum, Margo C; Swinnen, Steve; van den Broek, Marcel; Nevoigt, Elke; Daran, Jean-Marc G; Pronk, Jack T; van Maris, Antonius J A
2016-01-01
Acetic acid, released during hydrolysis of lignocellulosic feedstocks for second generation bioethanol production, inhibits yeast growth and alcoholic fermentation. Yeast biomass generated in a propagation step that precedes ethanol production should therefore express a high and constitutive level of acetic acid tolerance before introduction into lignocellulosic hydrolysates. However, earlier laboratory evolution strategies for increasing acetic acid tolerance of Saccharomyces cerevisiae, based on prolonged cultivation in the presence of acetic acid, selected for inducible rather than constitutive tolerance to this inhibitor. Preadaptation in the presence of acetic acid was shown to strongly increase the fraction of yeast cells that could initiate growth in the presence of this inhibitor. Serial microaerobic batch cultivation, with alternating transfers to fresh medium with and without acetic acid, yielded evolved S. cerevisiae cultures with constitutive acetic acid tolerance. Single-cell lines isolated from five such evolution experiments after 50-55 transfers were selected for further study. An additional constitutively acetic acid tolerant mutant was selected after UV-mutagenesis. All six mutants showed an increased fraction of growing cells upon a transfer from a non-stressed condition to a medium containing acetic acid. Whole-genome sequencing identified six genes that contained (different) mutations in multiple acetic acid-tolerant mutants. Haploid segregation studies and expression of the mutant alleles in the unevolved ancestor strain identified causal mutations for the acquired acetic acid tolerance in four genes (ASG1, ADH3, SKS1 and GIS4). Effects of the mutations in ASG1, ADH3 and SKS1 on acetic acid tolerance were additive. A novel laboratory evolution strategy based on alternating cultivation cycles in the presence and absence of acetic acid conferred a selective advantage to constitutively acetic acid-tolerant mutants and may be applicable for
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.
Jones, Robert
2010-03-01
There are a wide range of views on causality. To some (e.g. Karl Popper) causality is superfluous. Bertrand Russell said ``In advanced science the word cause never occurs. Causality is a relic of a bygone age.'' At the other extreme Rafael Sorkin and L. Bombelli suggest that space and time do not exist but are only an approximation to a reality that is simply a discrete ordered set, a ``causal set.'' For them causality IS reality. Others, like Judea Pearl and Nancy Cartwright are seaking to build a complex fundamental theory of causality (Causality, Cambridge Univ. Press, 2000) Or perhaps a theory of causality is simply the theory of functions. This is more or less my take on causality.
Directory of Open Access Journals (Sweden)
Cristina Puente Águeda
2011-10-01
Full Text Available Causality is a fundamental notion in every field of science. Since the times of Aristotle, causal relationships have been a matter of study as a way to generate knowledge and provide for explanations. In this paper I review the notion of causality through different scientific areas such as physics, biology, engineering, etc. In the scientific area, causality is usually seen as a precise relation: the same cause provokes always the same effect. But in the everyday world, the links between cause and effect are frequently imprecise or imperfect in nature. Fuzzy logic offers an adequate framework for dealing with imperfect causality, so a few notions of fuzzy causality are introduced.
2005-05-01
environment (i.e., culture , class, family, educational 2 Chapter 23 Intelligence Revisited opportunities, gender) shapes our intellect, and there are no...connectivity is going to be rather problematic, to say the least. A single nano-bot cruising this Disneyland of synaptic wonderment is certainly... cultures ). Embodiment – A sense of being anchored to our physical bodies. Agency – A sense of free will, wherein we are in charge of our own
Liang, Ling L.; Fulmer, Gavin W.; Majerich, David M.; Clevenstine, Richard; Howanski, Raymond
2012-01-01
The purpose of this study is to examine the effects of a model-based introductory physics curriculum on conceptual learning in a Physics First (PF) Initiative. This is the first comparative study in physics education that applies the Rasch modeling approach to examine the effects of a model-based curriculum program combined with PF in the United…
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.
La Bastide-Van Gemert, Sacha; Seggers, Jorien; Haadsma, Maaike L.; Heineman, Maas Jan; Middelburg, Karin J.; Roseboom, Tessa J.; Schendelaar, Pamela; Hadders-Algra, Mijna; Van den Heuvel, Edwin R.
STUDY QUESTION: What causal relationships underlie the associations between ovarian stimulation, the IVF procedure, parental-, fertility- and child characteristics, and blood pressure (BP) and anthropometrics of 4-year-old IVF children? SUMMARY ANSWER: Causal models compatible with the data suggest
An Introduction to Causal Inference
2009-11-02
legitimize causal inference, has removed causation from its natural habitat, and distorted its face beyond recognition. This exclusivist attitude is...In contrast, when the mediation problem is approached from an exclusivist potential-outcome viewpoint, void of the structural guidance of Eq. (28
Cosmic Acceleration from Causal Backreaction with Recursive Nonlinearities
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...
On Causality in Dynamical Systems
Harnack, Daniel
2016-01-01
Identification of causal links is fundamental for the analysis of complex systems. In dynamical systems, however, nonlinear interactions may hamper separability of subsystems which poses a challenge for attempts to determine the directions and strengths of their mutual influences. We found that asymmetric causal influences between parts of a dynamical system lead to characteristic distortions in the mappings between the attractor manifolds reconstructed from respective local observables. These distortions can be measured in a model-free, data-driven manner. This approach extends basic intuitions about cause-effect relations to deterministic dynamical systems and suggests a mathematically well defined explanation of results obtained from previous methods based on state space reconstruction.
Janardhan, Sujatha
2012-01-01
We present a short review of geometric and algebraic approach to causal cones and describe cone preserving transformations and their relationship with causal structure related to special and general theory of relativity. We describe Lie groups, especially matrix Lie groups, homogeneous and symmetric spaces and causal cones and certain implications of these concepts in special and general theory of relativity related to causal structure and topology of space-time. We compare and contrast the results on causal relations with those in the literature for general space-times and compare these relations with K-causal maps. We also describe causal orientations and their implications for space-time topology and discuss some more topologies on space-time which arise as an application of domain theory.
Relativistic causality and clockless circuits
Matherat, Philippe; 10.1145/2043643.2043650
2011-01-01
Time plays a crucial role in the performance of computing systems. The accurate modelling of logical devices, and of their physical implementations, requires an appropriate representation of time and of all properties that depend on this notion. The need for a proper model, particularly acute in the design of clockless delay-insensitive (DI) circuits, leads one to reconsider the classical descriptions of time and of the resulting order and causal relations satisfied by logical operations. This questioning meets the criticisms of classical spacetime formulated by Einstein when founding relativity theory and is answered by relativistic conceptions of time and causality. Applying this approach to clockless circuits and considering the trace formalism, we rewrite Udding's rules which characterize communications between DI components. We exhibit their intrinsic relation with relativistic causality. For that purpose, we introduce relativistic generalizations of traces, called R-traces, which provide a pertinent des...
Causality for nonlocal phenomena
Eckstein, Michał
2015-01-01
Drawing from the theory of optimal transport we propose a rigorous notion of a causal relation for Borel probability measures on a given spacetime. To prepare the ground, we explore the borderland between causality, topology and measure theory. We provide various characterisations of the proposed causal relation, which turn out to be equivalent if the underlying spacetime has a sufficiently robust causal structure. We also present the notion of the 'Lorentz-Wasserstein distance' and study its basic properties. Finally, we discuss how various results on causality in quantum theory, aggregated around Hegerfeldt's theorem, fit into our framework.
2010-01-01
Pennebaker hat doch zurückgeblickt. In weiteren fünfundsechzig Minuten zeigt er mit 65 REVISITED neue und ergänzende Facetten von Bob Dylan auf seiner 1965er Tournee durch England aus bisher unveröffentlichtem und digital aufgearbeitetem Material. Couchman (2002, 94) betont, dass Dylan über vierzig Jahre nach DON‘T LOOK BACK (1965) noch immer nichts von seiner enigmatischen Ausstrahlung verloren habe. Das gleiche gilt auch für den Film und für seine Ergänzung.
Phenomenology of Causal Dynamical Triangulations
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.
Usami, Satoshi; Hayes, Timothy; McArdle, John J
2015-01-01
The present paper focuses on the relationship between latent change score (LCS) and autoregressive cross-lagged (ARCL) factor models in longitudinal designs. These models originated from different theoretical traditions for different analytic purposes, yet they share similar mathematical forms. In this paper, we elucidate the mathematical relationship between these models and show that the LCS model is reduced to the ARCL model when fixed effects are assumed in the slope factor scores. Additionally, we provide an applied example using height and weight data from a gerontological study. Throughout the example, we emphasize caution in choosing which model (ARCL or LCS) to apply due to the risk of obtaining misleading results concerning the presence and direction of causal precedence between two variables. We suggest approaching model specification not only by comparing estimates and fit indices between the LCS and ARCL models (as well as other models) but also by giving appropriate weight to substantive and theoretical considerations, such as assessing the justifiability of the assumption of random effects in the slope factor scores.
Saladié, Òscar; Santos-Lacueva, Raquel
2016-02-01
One of the main objectives of municipal waste management policies is to improve separate collection, both quantitatively and qualitatively. Several factors influence people behavior to recycling and, consequently, they play an important role to achieve the goals proposed in the management policies. People can improve separate collection rates because of a wide range of causes with different weight. Here, we have determined the uplift in probability to improve separate collection of municipal waste created by the awareness campaigns among 806 undergraduate students at Universitat Rovira i Virgili (Catalonia) by means of the Causal Chain Approach, a probabilistic method. A 73.2% state having improved separate collection in recent years and the most of them (75.4%) remember some awareness campaign. The results show the uplift in probability to improve separate collection attributable to the awareness campaigns is 17.9%. They should be taken into account by policy makers in charge of municipal waste management. Nevertheless, it must be assumed an awareness campaign will never be sufficient to achieve the objectives defined in municipal waste management programmes.
Ghasemi, Mahdieh; Mahloojifar, Ali
2013-01-01
Parkinson's disease (PD) is a progressive neurological disorder characterized by tremor, rigidity, and slowness of movements. Particular changes related to various pathological attacks in PD could result in causal interactions of the brain network from resting state functional magnetic resonance imaging (rs-fMRI) data. In this paper, we aimed to disclose the network structure of the directed influences over the brain using multivariate Granger causality analysis and graph theory in patients w...
2015-01-01
Uncovering causal relationships in data is a major objective of data analytics. Causal relationships are normally discovered with designed experiments, e.g. randomised controlled trials, which, however are expensive or infeasible to be conducted in many cases. Causal relationships can also be found using some well designed observational studies, but they require domain experts' knowledge and the process is normally time consuming. Hence there is a need for scalable and automated methods for c...
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.
Coal consumption and economic growth revisited
Energy Technology Data Exchange (ETDEWEB)
Wolde-Rufael, Yemane [135 Carnwath Road, London SW6 3HR (United Kingdom)
2010-01-15
This paper revisits the causal relationship between coal consumption and real GDP for six major coal consuming countries for the period 1965-2005 within a vector autoregressive (VAR) framework by including capital and labour as additional variables. Applying a modified version of the Granger causality test due to Toda and Yamamoto [Toda HY, Yamamoto T. Statistical inference in vector autoregressions with possibly integrated process. J Econom 1995;66:225-50], we found a unidirectional causality running from coal consumption to economic growth in India and Japan while the opposite causality running from economic growth to coal consumption was found in China and South Korea. In contrast there was a bi-directional causality running between economic growth and coal consumption in South Africa and the United States. Variance decomposition analysis seems to confirm our Granger causality results. The policy implication is that measures adopted to mitigate the adverse effects of coal consumption may be taken without harming economic growth in China and South Korea. In contrast, for the remaining four countries conservation measures can harm economic growth. (author)
A Brief Introduction to Temporality and Causality
Karimi, Kamran
2010-01-01
Causality is a non-obvious concept that is often considered to be related to temporality. In this paper we present a number of past and present approaches to the definition of temporality and causality from philosophical, physical, and computational points of view. We note that time is an important ingredient in many relationships and phenomena. The topic is then divided into the two main areas of temporal discovery, which is concerned with finding relations that are stretched over time, and causal discovery, where a claim is made as to the causal influence of certain events on others. We present a number of computational tools used for attempting to automatically discover temporal and causal relations in data.
Causal Behaviour on Carter spacetime
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...
Granger causality for state-space models.
Barnett, Lionel; Seth, Anil K
2015-04-01
Granger causality has long been a prominent method for inferring causal interactions between stochastic variables for a broad range of complex physical systems. However, it has been recognized that a moving average (MA) component in the data presents a serious confound to Granger causal analysis, as routinely performed via autoregressive (AR) modeling. We solve this problem by demonstrating that Granger causality may be calculated simply and efficiently from the parameters of a state-space (SS) model. Since SS models are equivalent to autoregressive moving average models, Granger causality estimated in this fashion is not degraded by the presence of a MA component. This is of particular significance when the data has been filtered, downsampled, observed with noise, or is a subprocess of a higher dimensional process, since all of these operations-commonplace in application domains as diverse as climate science, econometrics, and the neurosciences-induce a MA component. We show how Granger causality, conditional and unconditional, in both time and frequency domains, may be calculated directly from SS model parameters via solution of a discrete algebraic Riccati equation. Numerical simulations demonstrate that Granger causality estimators thus derived have greater statistical power and smaller bias than AR estimators. We also discuss how the SS approach facilitates relaxation of the assumptions of linearity, stationarity, and homoscedasticity underlying current AR methods, thus opening up potentially significant new areas of research in Granger causal analysis.
Causality in Classical Electrodynamics
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…
Causality and Lifshitz Holography
Energy Technology Data Exchange (ETDEWEB)
Koroteev, Peter [Department of Physics and Astronomy, University of Minnesota, 116 Church Street S.E., Minneapolis, MN 55455 (United States)
2011-07-15
We study signal propagation in theories with Lifshitz scaling using the gravity dual and show that backgrounds with z<1 are incompatible with causality of the strongly coupled theory. We argue that causality violations in z<1 theories show up in boundary correlation functions as superluminal modes.
Klein's double discontinuity revisited
DEFF Research Database (Denmark)
Winsløw, Carl; Grønbæk, Niels
2014-01-01
mathematics courses which are mandatory to become a high school teacher of mathematics. To what extent does the “advanced” experience enable them to approach the high school calculus in a deeper and more autonomous way ? To what extent can “capstone” courses support such an approach ? How could it be hindered......Much effort and research has been invested into understanding and bridging the ‘gaps’ which many students experience in terms of contents and expectations as they begin university studies with a heavy component of mathematics, typically in the form of calculus courses. We have several studies...... of bridging measures, success rates and many other aspects of these “entrance transition” problems. In this paper, we consider the inverse transition, experienced by university students as they revisit core parts of high school mathematics (in particular, calculus) after completing the undergraduate...
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...
Widlok, Thomas
2014-01-01
Cognitive Scientists interested in causal cognition increasingly search for evidence from non-Western Educational Industrial Rich Democratic people but find only very few cross-cultural studies that specifically target causal cognition. This article suggests how information about causality can be retrieved from ethnographic monographs, specifically from ethnographies that discuss agency and concepts of time. Many apparent cultural differences with regard to causal cognition dissolve when cultural extensions of agency and personhood to non-humans are taken into account. At the same time considerable variability remains when we include notions of time, linearity and sequence. The article focuses on ethnographic case studies from Africa but provides a more general perspective on the role of ethnography in research on the diversity and universality of causal cognition.
Directory of Open Access Journals (Sweden)
Ämin Baumeler
2017-07-01
Full Text Available Computation models such as circuits describe sequences of computation steps that are carried out one after the other. In other words, algorithm design is traditionally subject to the restriction imposed by a fixed causal order. We address a novel computing paradigm beyond quantum computing, replacing this assumption by mere logical consistency: We study non-causal circuits, where a fixed time structure within a gate is locally assumed whilst the global causal structure between the gates is dropped. We present examples of logically consistent non-causal circuits outperforming all causal ones; they imply that suppressing loops entirely is more restrictive than just avoiding the contradictions they can give rise to. That fact is already known for correlations as well as for communication, and we here extend it to computation.
DEFF Research Database (Denmark)
Nielsen, Max; Jensen, Frank; Setälä, Jari;
2011-01-01
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...... 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...... 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...
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.
DEFF Research Database (Denmark)
Bordacconi, Mats Joe; Larsen, Martin Vinæs
2014-01-01
Humans are fundamentally primed for making causal attributions based on correlations. This implies that researchers must be careful to present their results in a manner that inhibits unwarranted causal attribution. In this paper, we present the results of an experiment that suggests regression...... models – one of the primary vehicles for analyzing statistical results in political science – encourage causal interpretation. Specifically, we demonstrate that presenting observational results in a regression model, rather than as a simple comparison of means, makes causal interpretation of the results...... of equivalent results presented as either regression models or as a test of two sample means. Our experiment shows that the subjects who were presented with results as estimates from a regression model were more inclined to interpret these results causally. Our experiment implies that scholars using regression...
Causal inference in obesity research.
Franks, P W; Atabaki-Pasdar, N
2017-03-01
Obesity is a risk factor for a plethora of severe morbidities and premature death. Most supporting evidence comes from observational studies that are prone to chance, bias and confounding. Even data on the protective effects of weight loss from randomized controlled trials will be susceptible to confounding and bias if treatment assignment cannot be masked, which is usually the case with lifestyle and surgical interventions. Thus, whilst obesity is widely considered the major modifiable risk factor for many chronic diseases, its causes and consequences are often difficult to determine. Addressing this is important, as the prevention and treatment of any disease requires that interventions focus on causal risk factors. Disease prediction, although not dependent on knowing the causes, is nevertheless enhanced by such knowledge. Here, we provide an overview of some of the barriers to causal inference in obesity research and discuss analytical approaches, such as Mendelian randomization, that can help to overcome these obstacles. In a systematic review of the literature in this field, we found: (i) probable causal relationships between adiposity and bone health/disease, cancers (colorectal, lung and kidney cancers), cardiometabolic traits (blood pressure, fasting insulin, inflammatory markers and lipids), uric acid concentrations, coronary heart disease and venous thrombosis (in the presence of pulmonary embolism), (ii) possible causal relationships between adiposity and gray matter volume, depression and common mental disorders, oesophageal cancer, macroalbuminuria, end-stage renal disease, diabetic kidney disease, nuclear cataract and gall stone disease, and (iii) no evidence for causal relationships between adiposity and Alzheimer's disease, pancreatic cancer, venous thrombosis (in the absence of pulmonary embolism), liver function and periodontitis.
Exploratory Causal Analysis in Bivariate Time Series Data
McCracken, James M.
Many scientific disciplines rely on observational data of systems for which it is difficult (or impossible) to implement controlled experiments and data analysis techniques are required for identifying causal information and relationships directly from observational data. This need has lead to the development of many different time series causality approaches and tools including transfer entropy, convergent cross-mapping (CCM), and Granger causality statistics. In this thesis, the existing time series causality method of CCM is extended by introducing a new method called pairwise asymmetric inference (PAI). It is found that CCM may provide counter-intuitive causal inferences for simple dynamics with strong intuitive notions of causality, and the CCM causal inference can be a function of physical parameters that are seemingly unrelated to the existence of a driving relationship in the system. For example, a CCM causal inference might alternate between ''voltage drives current'' and ''current drives voltage'' as the frequency of the voltage signal is changed in a series circuit with a single resistor and inductor. PAI is introduced to address both of these limitations. Many of the current approaches in the times series causality literature are not computationally straightforward to apply, do not follow directly from assumptions of probabilistic causality, depend on assumed models for the time series generating process, or rely on embedding procedures. A new approach, called causal leaning, is introduced in this work to avoid these issues. The leaning is found to provide causal inferences that agree with intuition for both simple systems and more complicated empirical examples, including space weather data sets. The leaning may provide a clearer interpretation of the results than those from existing time series causality tools. A practicing analyst can explore the literature to find many proposals for identifying drivers and causal connections in times series data
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...... underlying studies that use these “causal-temporal” concepts. The chapter shows visually how causality and temporality are linked to one another in varying ways depending on the particular pattern of change. The chapter provides new tools for describing and understanding change in historical- institutional...
Energy Technology Data Exchange (ETDEWEB)
Tipler, F.J.
1977-08-01
Causally symmetric spacetimes are spacetimes with J/sup +/(S) isometric to J/sup -/(S) for some set S. We discuss certain properties of these spacetimes, showing for example that, if S is a maximal Cauchy surface with matter everywhere on S, then the spacetime has singularities in both J/sup +/(S) and J/sup -/(S). We also consider totally vicious spacetimes, a class of causally symmetric spacetimes for which I/sup +/(p) =I/sup -/(p) = M for any point p in M. Two different notions of stability in general relativity are discussed, using various types of causally symmetric spacetimes as starting points for perturbations.
Carbon Emissions and Economic Growth: Causality Testing in Heterogenous Panels
Energy Technology Data Exchange (ETDEWEB)
David Maddison; Katrin Rehdanz [Department of Economics, University of Birmingham, Birmingham (United Kingdom)
2008-09-30
Numerous papers have examined data on energy and GDP for evidence of Granger causality. Using time series techniques these analyses not infrequently reach differing conclusions concerning the existence and direction of Granger causality. This paper presents a heterogenous panel approach to Granger causality testing. This technique is used to examine a panel of data for evidence of a causal relationship between GDP and carbon emissions per capita allowing for heterogeneity in short run dynamics and even the long run cointegrating vector. This technique is compared to the standard fixed dynamic effects approach to pooling individual error correction models. In one important case the heterogenous panel test for Granger causality reaches conclusions quite different to those from conventional tests of Granger causality. Except for Asia there is strong evidence for the existence of a bidirectional causal relationship between GDP per capita and CO{sub 2} emissions per capita.
Chiodi, Filippo; Claudin, Philippe
2012-01-01
The river bar instability is revisited, using a hydrodynamical model based on Reynolds averaged Navier-Stokes equations. The results are contrasted with the standard analysis based on shallow water Saint-Venant equations. We first show that the stability of both transverse modes (ripples) and of small wavelength inclined modes (bars) predicted by the Saint-Venant approach are artefacts of this hydrodynamical approximation. When using a more reliable hydrodynamical model, the dispersion relation does not present any maximum of the growth rate when the sediment transport is assumed to be locally saturated. The analysis therefore reveals the fundamental importance of the relaxation of sediment transport towards equilibrium as it it is responsible for the stabilisation of small wavelength modes. This dynamical mechanism is characterised by the saturation number, defined as the ratio of the saturation length to the water depth Lsat/H. This dimensionless number controls the transition from ripples (transverse patte...
Revisiting the Lambert's Problem
Izzo, Dario
2014-01-01
The orbital boundary value problem, also known as Lambert Problem, is revisited. Building upon Lancaster and Blanchard approach, new relations are revealed and a new variable representing all problem classes, under L-similarity, is used to express the time of flight equation. In the new variable, the time of flight curves have two oblique asymptotes and they mostly appear to be conveniently approximated by piecewise continuous lines. We use and invert such a simple approximation to provide an efficient initial guess to an Householder iterative method that is then able to converge, for the single revoltuion case, in only two iterations. The resulting algorithm is compared to Gooding's procedure revealing to be numerically as accurate, while having a smaller computational complexity.
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.
Remembered Experiences and Revisit Intentions
DEFF Research Database (Denmark)
Barnes, Stuart; Mattsson, Jan; Sørensen, Flemming
2016-01-01
Tourism is an experience-intensive sector in which customers seek and pay for experiences above everything else. Remembering past tourism experiences is also crucial for an understanding of the present, including the predicted behaviours of visitors to tourist destinations. We adopt a longitudinal...... approach to memory data collection from psychological science, which has the potential to contribute to our understanding of tourist behaviour. In this study, we examine the impact of remembered tourist experiences in a safari park. In particular, using matched survey data collected longitudinally and PLS...... path modelling, we examine the impact of positive affect tourist experiences on the development of revisit intentions. We find that longer-term remembered experiences have the strongest impact on revisit intentions, more so than predicted or immediate memory after an event. We also find that remembered...
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.
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...
The Temporal Logic of Causal Structures
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...
Identifiability of Causal Graphs using Functional Models
Peters, Jonas; Janzing, Dominik; Schoelkopf, Bernhard
2012-01-01
This work addresses the following question: Under what assumptions on the data generating process can one infer the causal graph from the joint distribution? The approach taken by conditional independence-based causal discovery methods is based on two assumptions: the Markov condition and faithfulness. It has been shown that under these assumptions the causal graph can be identified up to Markov equivalence (some arrows remain undirected) using methods like the PC algorithm. In this work we propose an alternative by defining Identifiable Functional Model Classes (IFMOCs). As our main theorem we prove that if the data generating process belongs to an IFMOC, one can identify the complete causal graph. To the best of our knowledge this is the first identifiability result of this kind that is not limited to linear functional relationships. We discuss how the IFMOC assumption and the Markov and faithfulness assumptions relate to each other and explain why we believe that the IFMOC assumption can be tested more eas...
Causality discovery technology
Chen, M.; Ertl, T.; Jirotka, M.; Trefethen, A.; Schmidt, A.; Coecke, B.; Bañares-Alcántara, R.
2012-11-01
Causality is the fabric of our dynamic world. We all make frequent attempts to reason causation relationships of everyday events (e.g., what was the cause of my headache, or what has upset Alice?). We attempt to manage causality all the time through planning and scheduling. The greatest scientific discoveries are usually about causality (e.g., Newton found the cause for an apple to fall, and Darwin discovered natural selection). Meanwhile, we continue to seek a comprehensive understanding about the causes of numerous complex phenomena, such as social divisions, economic crisis, global warming, home-grown terrorism, etc. Humans analyse and reason causality based on observation, experimentation and acquired a priori knowledge. Today's technologies enable us to make observations and carry out experiments in an unprecedented scale that has created data mountains everywhere. Whereas there are exciting opportunities to discover new causation relationships, there are also unparalleled challenges to benefit from such data mountains. In this article, we present a case for developing a new piece of ICT, called Causality Discovery Technology. We reason about the necessity, feasibility and potential impact of such a technology.
Biased causal inseparable game
Bhattacharya, Some Sankar
2015-01-01
Here we study the \\emph{causal inseparable} game introduced in [\\href{http://www.nature.com/ncomms/journal/v3/n10/full/ncomms2076.html}{Nat. Commun. {\\bf3}, 1092 (2012)}], but it's biased version. Two separated parties, Alice and Bob, generate biased bits (say input bit) in their respective local laboratories. Bob generates another biased bit (say decision bit) which determines their goal: whether Alice has to guess Bob's bit or vice-verse. Under the assumption that events are ordered with respect to some global causal relation, we show that the success probability of this biased causal game is upper bounded, giving rise to \\emph{biased causal inequality} (BCI). In the \\emph{process matrix} formalism, which is locally in agreement with quantum physics but assume no global causal order, we show that there exist \\emph{inseparable} process matrices that violate the BCI for arbitrary bias in the decision bit. In such scenario we also derive the maximal violation of the BCI under local operations involving tracele...
2012-01-01
The causal assumptions, the study design and the data are the elements required for scientific inference in empirical research. The research is adequately communicated only if all of these elements and their relations are described precisely. Causal models with design describe the study design and the missing data mechanism together with the causal structure and allow the direct application of causal calculus in the estimation of the causal effects. The flow of the study is visualized by orde...
Institute of Scientific and Technical Information of China (English)
闫海; 彭晨
2012-01-01
Causality is one of the elements of civil liability securities misrepresentation. Chinese judicial interpretation of civil liability of securities misrepresentation not only learn from successful experience of the U.S. legislative and judicial, but also should introduce theoretical framework of bifurcated approach to causality. Transaction causation is a causal relationship between securities transactions by investors and misrepresentation, and it should be taken to identify trust presumption. If investors trade on their own to recover damages,they also prove loss causation that a causal relationship between trading losses of investors and misrepresentation. Identification of loss causation can take a direct consequence and make shifting of burden of evidence, as well as other factors such as systematic risk securities to be excluded.%因果关系是证券虚假陈述民事责任的构成要件之一。我国司法解释不仅借鉴美国虚假陈述民事责任立法与司法中较为成功的经验，还应当引入因果关系两分法的理论架构。证券虚假陈述民事责任中的交易因果关系是指投资者的证券交易行为与虚假陈述之间存在因果关系，认定交易因果关系应当采取信赖推定的方法。投资者如果就自己的交易损失予以追偿，在认定交易因果关系的基础上，还必须证明交易损失与虚假陈述行为之间存在因果关系，即损失因果关系。损失因果关系的认定可以采取直接后果并进行举证倒置，以及对证券市场系统风险等其他因素予以排除。
Causal inference in econometrics
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.
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...
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.
Complementarity, causality, and explanation
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
The Future of Engineering Education--Revisited
Wankat, Phillip C.; Bullard, Lisa G.
2016-01-01
This paper revisits the landmark CEE series, "The Future of Engineering Education," published in 2000 (available free in the CEE archives on the internet) to examine the predictions made in the original paper as well as the tools and approaches documented. Most of the advice offered in the original series remains current. Despite new…
Ghasemi, Mahdieh; Mahloojifar, Ali
2013-04-01
Parkinson's disease (PD) is a progressive neurological disorder characterized by tremor, rigidity, and slowness of movements. Particular changes related to various pathological attacks in PD could result in causal interactions of the brain network from resting state functional magnetic resonance imaging (rs-fMRI) data. In this paper, we aimed to disclose the network structure of the directed influences over the brain using multivariate Granger causality analysis and graph theory in patients with PD as compared with control group. rs-fMRI at rest from 10 PD patients and 10 controls were analyzed. Topological properties of the networks showed that information flow in PD is smaller than that in healthy individuals. We found that there is a balanced local network in healthy control group, including positive pair-wise cross connections between caudate and cerebellum and reciprocal connections between motor cortex and caudate in the left and right hemispheres. The results showed that this local network is disrupted in PD due to disturbance of the interactions in the motor networks. These findings suggested alteration of the functional organization of the brain in the resting state that affects the information transmission from and to other brain regions related to both primary dysfunctions and higher-level cognition impairments in PD. Furthermore, we showed that regions with high degree values could be detected as betweenness centrality nodes. Our results demonstrate that properties of small-world connectivity could also recognize and quantify the characteristics of directed influence brain networks in PD.
The Causality between Government Revenue and Government Expenditure in Iran
Elyasi, Yousef; Rahimi, Mohammad
2012-01-01
The causal relationship between government revenue and government expenditure is an important subject in public economics especially to the control of budget deficit. The purpose of this study is to investigate the relationship between government revenue and government expenditure in Iran by applying the bounds testing approach to cointegration. The results of the causality test show that there is a bidirectional causal relationship between government expenditure and revenues in both long run...
Woebken, Dagmar; Burow, Luke C.; Behnam, Faris; Mayali, Xavier; Schintlmeister, Arno; Fleming, Erich D; Prufert-Bebout, Leslie; Singer, Steven W.; Cortés, Alejandro López; Hoehler, Tori M; Pett-Ridge, Jennifer; Spormann, Alfred M.; Wagner, Michael; Weber, Peter K.; Bebout, Brad M
2014-01-01
Photosynthetic microbial mats are complex, stratified ecosystems in which high rates of primary production create a demand for nitrogen, met partially by N2 fixation. Dinitrogenase reductase (nifH) genes and transcripts from Cyanobacteria and heterotrophic bacteria (for example, Deltaproteobacteria) were detected in these mats, yet their contribution to N2 fixation is poorly understood. We used a combined approach of manipulation experiments with inhibitors, nifH sequencing and single-cell is...
Understanding Causal Coherence Relations
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
Causal Responsibility and Counterfactuals
Lagnado, David A.; Gerstenberg, Tobias; Zultan, Ro'i
2013-01-01
How do people attribute responsibility in situations where the contributions of multiple agents combine to produce a joint outcome? The prevalence of over-determination in such cases makes this a difficult problem for counterfactual theories of causal responsibility. In this article, we explore a general framework for assigning responsibility in…
Causality: Physics and Philosophy
Chatterjee, Atanu
2013-01-01
Nature is a complex causal network exhibiting diverse forms and species. These forms or rather systems are physically open, structurally complex and naturally adaptive. They interact with the surrounding media by operating a positive-feedback loop through which, they adapt, organize and self-organize themselves in response to the ever-changing…
Explaining through causal mechanisms
Biesbroek, Robbert; Dupuis, Johann; Wellstead, Adam
2017-01-01
This paper synthesizes and builds on recent critiques of the resilience literature; namely that the field has largely been unsuccessful in capturing the complexity of governance processes, in particular cause–effects relationships. We demonstrate that absence of a causal model is reflected in the
Directory of Open Access Journals (Sweden)
O I Aganson
2011-09-01
Full Text Available The purpose of the article is to define how home debates on international issues influence a state's foreign policy. This task was undertaken on the pattern of Britain's policy in the Balkans in the late 19th/early 20th century. The author examines the role played by the radicals (left-wing liberals in formulating Britain's approaches to the Eastern question. It is stated that the interaction between the Foreign Office and the radicals rendered British policy in the Balkans more flexible.
Orban, Chris
2012-01-01
In setting up initial conditions for cosmological N-body simulations there are, fundamentally, two choices: either maximizing the correspondence of the initial density field to the assumed fourier-space clustering or, instead, matching to the real-space clustering. As a stringent test of both approaches, I perform ensembles of simulations using power law models and exploit the self-similarity of these initial conditions to quantify the accuracy of the results. Originally proposed by Pen 1997 and implemented by Sirko 2005, I show that the real-space motivated approach, which allows the DC mode to vary, performs well in exhibiting the expected self-similar behavior in the mean xi(r) and P(k) and in both methods this behavior extends below the scale of the initial mean interparticle spacing. I also test the real-space method with simulations of a simplified, powerlaw model for baryon acoustic oscillations, again with success, and mindful of the need to generate mock catalogs using simulations I show extensive po...
Salzer, Yael; de Hollander, Gilles; Forstmann, Birte U
2017-02-24
The Simon task is one of the most prominent interference tasks and has been extensively studied in experimental psychology and cognitive neuroscience. Despite years of research, the underlying mechanism driving the phenomenon and its temporal dynamics are still disputed. Within the framework of the review, we adopt a model-based cognitive neuroscience approach. We first go over key findings in the literature of the Simon task, discuss competing qualitative cognitive theories and the difficulty of testing them empirically. We then introduce sequential sampling models, a particular class of mathematical cognitive process models. Finally, we argue that the brain architecture accountable for the processing of spatial ('where') and non-spatial ('what') information, could constrain these models. We conclude that there is a clear need to bridge neural and behavioral measures, and that mathematical cognitive models may facilitate the construction of this bridge and work towards revealing the underlying mechanisms of the Simon effect.
Causal diagrams for physical models
Kinsler, Paul
2015-01-01
I present a scheme of drawing causal diagrams based on physically motivated mathematical models expressed in terms of temporal differential equations. They provide a means of better understanding the processes and causal relationships contained within such systems.
Kondratyuk, S
2000-01-01
Pion-loop corrections for Compton scattering are calculated in a novel approach based on the use of dispersion relations in a formalism obeying unitarity. The basic framework is presented, including an application to Compton scattering. In the approach the effects of the non-pole contribution arising from pion dressing are expressed in terms of (half-off-shell) form factors and the nucleon self-energy. These quantities are constructed through the application of dispersion integrals to the pole contribution of loop diagrams, the same as those included in the calculation of the amplitudes through a K-matrix formalism. The prescription of minimal substitution is used to restore gauge invariance. The resulting relativistic-covariant model combines constraints from unitarity, causality, and crossing symmetry.
Ting, Hiram; Thurasamy, Ramayah
2016-01-01
Notwithstanding the rise of trendy coffee café, little is done to investigate revisit intention towards the café in the context of developing markets. In particular, there is a lack of study which provides theoretical and practical explanation to the perceptions and behaviours of infrequent customers. Hence, the study aims to look into the subject matter by using the theory of reasoned action and social exchange theory as the underpinning basis. The framework proposed by Pine and Gilmore (Str...
Information causality and noisy computations
Energy Technology Data Exchange (ETDEWEB)
Hsu, Li-Yi [Department of Physics, Chung Yuan Christian University, Chung-li 32023, Taiwan (China); Yu, I-Ching; Lin, Feng-Li [Department of Physics, National Taiwan Normal University, Taipei 116, Taiwan (China)
2011-10-15
We reformulate the information causality in a more general framework by adopting the results of signal propagation and computation in a noisy circuit. In our framework, the information causality leads to a broad class of Tsirelson inequalities. This fact allows us to subject information causality to experimental scrutiny. A no-go theorem for reliable nonlocal computation is also derived. Information causality prevents any physical circuit from performing reliable computations.
Granger causality and transfer entropy are equivalent for Gaussian variables.
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.
Granger causality and transfer entropy are equivalent for Gaussian variables
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.
Furstenberg, Gilberte; English, Kathryn
2016-01-01
Two of the original authors of "Giving a Virtual Voice to the Silent Language of Culture: The Cultura Project", published in "Language Learning & Technology" in 2001, look back on the origin of the Cultura project, its goals, and the approach and materials used. Their commentary then focuses on the features and the…
Furstenberg, Gilberte; English, Kathryn
2016-01-01
Two of the original authors of "Giving a Virtual Voice to the Silent Language of Culture: The Cultura Project", published in "Language Learning & Technology" in 2001, look back on the origin of the Cultura project, its goals, and the approach and materials used. Their commentary then focuses on the features and the…
Dimensional reduction in causal set gravity
Carlip, S
2015-01-01
Results from a number of different approaches to quantum gravity suggest that the effective dimension of spacetime may drop to $d=2$ at small scales. I show that two different dimensional estimators in causal set theory display the same behavior, and argue that a third, the spectral dimension, may exhibit a related phenomenon of "asymptotic silence."
Pitalúa-García, Damián
2012-01-01
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 combin...
What determines health: a causal analysis using county level data.
Rettenmaier, Andrew J; Wang, Zijun
2013-10-01
This article revisits the long-standing issue of the determinants of health outcomes. We make two contributions to the literature. First, we use a large and comprehensive US county level health data set that has only recently become available. This data set includes five measures of health outcomes and 24 health risk factors in the categories of health behaviors, clinical care, social and economic factors, and physical environment. Second, to distinguish causality from correlation, we implement an emerging data-driven method to study the causal factors of health outcomes. Among all included potential health risk factors, we identify adult smoking, obesity, motor vehicle crash death rate, the percent of children in poverty, and violent crime rate to be major causal factors of premature mortality. Adult smoking, preventable hospital stays, college or higher education, employment, children in poverty, and adequacy of social support determine health-related quality of life. Finally, the Chlamydia rate, community safety, and liquor store density are three important factors causally related to low birth weight. Policy implications of these findings are discussed.
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...
Institute of Scientific and Technical Information of China (English)
周玉华
2012-01-01
内在化的研究路径借用心灵哲学的方法,以近乎反思的模式探求翻译活动的内在过程与其特征。＂因果＂与＂功能＂是研究中的核心要素,其中＂因果＂是译者主体性发挥的途径,＂功能＂指通过社会赋予方式对＂因果＂施加的限制。两者的结合形成了译者主体性发挥的作用链条：＂功能＂——译者——意向（＂因＂）——翻译行为（＂果＂）。%Internalized approach in translation studies aims at uncovering the internal process of translation practice. Within the process, "causality" and "function" are the two core factors, the former demonstrating the translator' s subjective role and the latter manifesting the restrictions that social institution exerts on causality. Working together, they reveal the way in which translator' s subjective role is performed: ty(cause)--tanslation behavior(result)".
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.
Causality in physiological signals.
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
DEFF Research Database (Denmark)
Hansen, Morten Balle; Lindholst, Andrej Christian
2016-01-01
Purpose: The purpose of this introduction article to the IJPSM special issue on marketization is to clarify the conceptual foundations of marketization as a phenomenon within the public sector and to gauge current marketization trends on the basis of the seven articles in the special issue. Design....../methodology/approach: Conceptual clarification and cross-cutting review of seven articles analysing marketization in six countries in three policy areas at the level of local government. Findings: Four ideal-type models are deduced: Quasi-markets, involving both provider competition and free choice for users; Classic contracting...... out; Benchmarking and yardstick competition; and Public-Private collaboration. On the basis of the review of the seven articles, it is found that all elements in all marketization models are firmly embedded but also under dynamic change within public service delivery systems. The review also...
Quantum information causality.
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.
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.
Johnston, Steven
2010-01-01
Causal set theory provides a model of discrete spacetime in which spacetime events are represented by elements of a causal set---a locally finite, partially ordered set in which the partial order represents the causal relationships between events. The work presented here describes a model for matter on a causal set, specifically a theory of quantum scalar fields on a causal set spacetime background. The work starts with a discrete path integral model for particles on a causal set. Here quantum mechanical amplitudes are assigned to trajectories within the causal set. By summing these over all trajectories between two spacetime events we obtain a causal set particle propagator. With a suitable choice of amplitudes this is shown to agree (in an appropriate sense) with the retarded propagator for the Klein-Gordon equation in Minkowski spacetime. This causal set propagator is then used to define a causal set analogue of the Pauli-Jordan function that appears in continuum quantum field theories. A quantum scalar fi...
Causality and Micro-Causality in Curved Spacetime
Hollowood, Timothy J.; Shore, Graham M.
2007-01-01
We consider how causality and micro-causality are realised in QED in curved spacetime. The photon propagator is found to exhibit novel non-analytic behaviour due to vacuum polarization, which invalidates the Kramers-Kronig dispersion relation and calls into question the validity of micro-causality in curved spacetime. This non-analyticity is ultimately related to the generic focusing nature of congruences of geodesics in curved spacetime, as implied by the null energy condition, and the exist...
Causal events enter awareness faster than non-causal events
Wagemans, Johan; de-Wit, Lee
2017-01-01
Philosophers have long argued that causality cannot be directly observed but requires a conscious inference (Hume, 1967). Albert Michotte however developed numerous visual phenomena in which people seemed to perceive causality akin to primary visual properties like colour or motion (Michotte, 1946). Michotte claimed that the perception of causality did not require a conscious, deliberate inference but, working over 70 years ago, he did not have access to the experimental methods to test this claim. Here we employ Continuous Flash Suppression (CFS)—an interocular suppression technique to render stimuli invisible (Tsuchiya & Koch, 2005)—to test whether causal events enter awareness faster than non-causal events. We presented observers with ‘causal’ and ‘non-causal’ events, and found consistent evidence that participants become aware of causal events more rapidly than non-causal events. Our results suggest that, whilst causality must be inferred from sensory evidence, this inference might be computed at low levels of perceptual processing, and does not depend on a deliberative conscious evaluation of the stimulus. This work therefore supports Michotte’s contention that, like colour or motion, causality is an immediate property of our perception of the world. PMID:28149698
Experimental test of nonlocal causality.
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.
Experimental test of nonlocal causality
Ringbauer, Martin; Giarmatzi, Christina; Chaves, Rafael; Costa, Fabio; White, Andrew G.; Fedrizzi, Alessandro
2016-01-01
Explaining observations in terms of causes and effects is central to empirical science. However, correlations between entangled quantum particles seem to defy such an explanation. This implies that some of the fundamental assumptions of causal explanations have to give way. We consider a relaxation of one of these assumptions, Bell’s local causality, by allowing outcome dependence: a direct causal influence between the outcomes of measurements of remote parties. We use interventional data from a photonic experiment to bound the strength of this causal influence in a two-party Bell scenario, and observational data from a Bell-type inequality test for the considered models. Our results demonstrate the incompatibility of quantum mechanics with a broad class of nonlocal causal models, which includes Bell-local models as a special case. Recovering a classical causal picture of quantum correlations thus requires an even more radical modification of our classical notion of cause and effect. PMID:27532045
Causal evolution of wave packets
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.
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.
Mondrzak, Viviane Sprinz; Duarte, Aldo Luiz; Lewkowicz, Alice Becker; Kauffmann, Anna Luiza; Iankilevich, Eneida; Brodacz, Gisha; Soares, Gustavo P; Pellanda, Luiz Ernesto
2007-04-01
Based on the studies and discussions of the Epistemology Study Group of the Porto Alegre Psychoanalytical Society, the authors aim to connect the notions of psychical determinism with the concept of trauma and temporality, from a perspective of the mind as a complex system. Following consideration of the concept of psychical determinism, they attempt to expand the discussion on causality. They propose that trauma be situated in the body of contemporary psychoanalysis, where emotional experience is favoured over factual events, leading to the need to rethink the concept of trauma and its usefulness. In the same way, in the light of recent developments, the authors revisit the Freudian etiologic equation, with a proposal that an i, for imaginary factor, be included, corresponding to an element of complexity. The question of temporality, connected with trauma and the therapeutic action of psychoanalysis, is approached within a vision of irreversible time, characteristic of complex systems, far-from-equilibrium-which is how the authors understand psychical functioning.
Causality Statistical Perspectives and Applications
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
Spine revisited: Principles and parlance redefined
Directory of Open Access Journals (Sweden)
Kothari M
2005-01-01
Full Text Available A revised appreciation of the evolution and the nature of bone in general and of vertebrae in particular, allows revisiting the human spine to usher in some new principles and more rational parlance, that embody spine′s phylogeny, ontogeny, anatomy and physiology. Such an approach accords primacy to spine′s soft-tissues, and relegates to its bones a secondary place.
Revisiting Cementoblastoma with a Rare Case Presentation.
Subramani, Vijayanirmala; Narasimhan, Malathi; Ramalingam, Suganya; Anandan, Soumya; Ranganathan, Subhashini
2017-01-01
Cementoblastoma is a rare benign odontogenic neoplasm which is characterized by the proliferation of cellular cementum. Diagnosis of cementoblastoma is challenging because of its protracted clinical, radiographic features, and bland histological appearance; most often cementoblastoma is often confused with other cementum and bone originated lesions. The aim of this article is to overview/revisit, approach the diagnosis of cementoblastoma, and also present a unique radiographic appearance of a cementoblastoma lesion associated with an impacted tooth.
Revisiting Cementoblastoma with a Rare Case Presentation
Directory of Open Access Journals (Sweden)
Vijayanirmala Subramani
2017-01-01
Full Text Available Cementoblastoma is a rare benign odontogenic neoplasm which is characterized by the proliferation of cellular cementum. Diagnosis of cementoblastoma is challenging because of its protracted clinical, radiographic features, and bland histological appearance; most often cementoblastoma is often confused with other cementum and bone originated lesions. The aim of this article is to overview/revisit, approach the diagnosis of cementoblastoma, and also present a unique radiographic appearance of a cementoblastoma lesion associated with an impacted tooth.
Structural Equations and Causal Explanations: Some Challenges for Causal SEM
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…
The Cradle of Causal Reasoning: Newborns' Preference for Physical Causality
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…
The Cradle of Causal Reasoning: Newborns' Preference for Physical Causality
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…
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.
Inferring deterministic causal relations
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.
Implementing causality in the spin foam quantum geometry
Livine, E R; Livine, Etera R.; Oriti, Daniele
2003-01-01
We analyse the classical and quantum geometry of the Barrett-Crane spin foam model for four dimensional quantum gravity, explaining why it has to be considering as a covariant realization of the projector operator onto physical quantum gravity states. We discuss how causality requirements can be consistently implemented in this framework, and construct causal transiton amplitudes between quantum gravity states, i.e. realising in the spin foam context the Feynman propagator between states. The resulting causal spin foam model can be seen as a path integral quantization of Lorentzian first order Regge calculus, and represents a link between several approaches to quantum gravity as canonical loop quantum gravity, sum-over-histories formulations, dynamical triangulations and causal sets. In particular, we show how the resulting model can be rephrased within the framework of quantum causal sets (or histories).
Causality in non-commutative quantum field theories
Energy Technology Data Exchange (ETDEWEB)
Haque, Asrarul; Joglekar, Satish D [Department of Physics, I.I.T. Kanpur, Kanpur 208 016 (India)], E-mail: ahaque@iitk.ac.in, E-mail: sdj@iitk.ac.in
2008-05-30
We study causality in noncommutative quantum field theory with a space-space noncommutativity. We employ the S operator approach of Bogoliubov-Shirkov (BS). We generalize the BS criterion of causality to the noncommutative theory. The criterion to test causality leads to a nonzero difference between the T* product and the T product as a condition of causality violation for a spacelike separation. We discuss two examples; one in a scalar theory and another in the Yukawa theory. In particular, in the context of a noncommutative Yukawa theory, with the interaction Lagrangian {psi}-bar(x)*{psi}(x)*{phi}(x), is observed to be causality violating even in the case of space-space noncommutativity for which {theta}{sup 0i} = 0.
World oil and agricultural commodity prices: Evidence from nonlinear causality
Energy Technology Data Exchange (ETDEWEB)
Nazlioglu, Saban, E-mail: snazlioglu@pau.edu.t [Department of Econometrics, Pamukkale University, Denizli (Turkey)
2011-05-15
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: {yields} This study determines the price transmission mechanisms between the world oil and three key agricultural commodity prices (corn, soybeans, and wheat). {yields} The linear and nonlinear cointegration and causality methods are carried out. {yields} The linear causality analysis supports evidence on the neutrality hypothesis. {yields} The nonlinear causality analysis shows that there is a persistent unidirectional causality from the oil prices to the corn and to the soybeans prices.
Multiple Access Channels with States Causally Known at Transmitters
Li, Min; Yener, Aylin
2010-01-01
The state-dependent multiple access channel (MAC) is considered where the state sequences are known causally to the encoders. First, a MAC with two independent states each known causally to one encoder is revisited, and a new achievable scheme inspired by the recently proposed noisy network coding is presented. This scheme is shown to achieve a rate region that is potentially larger than that provided by recent work for the same model. Next, capacity results are presented for a class of channels that include modulo-additive state-dependent MACs. It is shown that the proposed scheme can be easily extended to an arbitrary number of users. Next, a similar scheme is proposed for a MAC with common state known causally to all encoders. The corresponding achievable rate region is shown to reduce to the one given in the previous work as a special case for two users. Finally, output feedback is introduced in the model at hand with independent states and an example is provided to show the advantage of feedback in enlar...
Yoon, Ju Young; Brown, Roger L
2014-01-01
Cross-lagged panel analysis (CLPA) is a method of examining one-way or reciprocal causal inference between longitudinally changing variables. It has been used in the social sciences for many years, but not much in nursing research. This article introduces the conceptual and statistical background of CLPA and provides an exemplar of CLPA that examines the reciprocal causal relationship between depression and cognitive function over time in older adults. The 2-year cross-lagged effects of depressive symptoms (T1) on cognitive function (T2) and cognitive function (T1) on depressive symptoms (T2) were significant, which demonstrated a reciprocal causal relationship between cognitive function and depressive mood over time. Although CLPA is a methodologically strong approach to examine the reciprocal causal inferences over time, it is necessary to consider potential sources of spuriousness to lead to false causal relationship and a reasonable time frame to detect the change of the variables.
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
Expert Causal Reasoning and Explanation.
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…
Causal Inference and Developmental Psychology
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…
Griffiths, Thomas L.; Tenenbaum, Joshua B.
2009-01-01
Inducing causal relationships from observations is a classic problem in scientific inference, statistics, and machine learning. It is also a central part of human learning, and a task that people perform remarkably well given its notorious difficulties. People can learn causal structure in various settings, from diverse forms of data: observations…
Causal Attributions of Shy Subjects.
Teglasi, Hedwig; Hoffman, Mary Ann
1982-01-01
Causal attributions of shy students (N=36) were compared with those of a comparison group of students (N=36) in ten situations. Significant differences between the two groups emerged when explaining outcomes of situations considered to be problematic for shy individuals. Causal attributions may reflect realistic and situation-specific…
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
Causal Inference and Developmental Psychology
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…
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.
On causality of extreme events
Directory of Open Access Journals (Sweden)
Massimiliano Zanin
2016-06-01
Full Text Available Multiple metrics have been developed to detect causality relations between data describing the elements constituting complex systems, all of them considering their evolution through time. Here we propose a metric able to detect causality within static data sets, by analysing how extreme events in one element correspond to the appearance of extreme events in a second one. The metric is able to detect non-linear causalities; to analyse both cross-sectional and longitudinal data sets; and to discriminate between real causalities and correlations caused by confounding factors. We validate the metric through synthetic data, dynamical and chaotic systems, and data representing the human brain activity in a cognitive task. We further show how the proposed metric is able to outperform classical causality metrics, provided non-linear relationships are present and large enough data sets are available.
On causality of extreme events
2016-01-01
Multiple metrics have been developed to detect causality relations between data describing the elements constituting complex systems, all of them considering their evolution through time. Here we propose a metric able to detect causality within static data sets, by analysing how extreme events in one element correspond to the appearance of extreme events in a second one. The metric is able to detect non-linear causalities; to analyse both cross-sectional and longitudinal data sets; and to discriminate between real causalities and correlations caused by confounding factors. We validate the metric through synthetic data, dynamical and chaotic systems, and data representing the human brain activity in a cognitive task. We further show how the proposed metric is able to outperform classical causality metrics, provided non-linear relationships are present and large enough data sets are available. PMID:27330866
Revisiting Okun's Relationship
Dixon, R.; Lim, G.C.; van Ours, Jan
2016-01-01
Our paper revisits Okun's relationship between observed unemployment rates and output gaps. We include in the relationship the effect of labour market institutions as well as age and gender effects. Our empirical analysis is based on 20 OECD countries over the period 1985-2013. We find that the
A Hydrostatic Paradox Revisited
Ganci, Salvatore
2012-01-01
This paper revisits a well-known hydrostatic paradox, observed when turning upside down a glass partially filled with water and covered with a sheet of light material. The phenomenon is studied in its most general form by including the mass of the cover. A historical survey of this experiment shows that a common misunderstanding of the phenomenon…
Bingolbali, Erhan; Monaghan, John
2008-01-01
Concept image and concept definition is an important construct in mathematics education. Its use, however, has been limited to cognitive studies. This article revisits concept image in the context of research on undergraduate students' understanding of the derivative which regards the context of learning as paramount. The literature, mainly on…
Revisiting the Okun relationship
Dixon, R. (Robert); Lim, G.C.; J.C. van Ours (Jan)
2017-01-01
textabstractOur article revisits the Okun relationship between observed unemployment rates and output gaps. We include in the relationship the effect of labour market institutions as well as age and gender effects. Our empirical analysis is based on 20 OECD countries over the period 1985–2013. We
DEFF Research Database (Denmark)
Cornean, Horia; Nenciu, Gheorghe
2009-01-01
This paper is the second in a series revisiting the (effect of) Faraday rotation. We formulate and prove the thermodynamic limit for the transverse electric conductivity of Bloch electrons, as well as for the Verdet constant. The main mathematical tool is a regularized magnetic and geometric...
A Hydrostatic Paradox Revisited
Ganci, Salvatore
2012-01-01
This paper revisits a well-known hydrostatic paradox, observed when turning upside down a glass partially filled with water and covered with a sheet of light material. The phenomenon is studied in its most general form by including the mass of the cover. A historical survey of this experiment shows that a common misunderstanding of the phenomenon…
CausalTrail: Testing hypothesis using causal Bayesian networks.
Stöckel, Daniel; Schmidt, Florian; Trampert, Patrick; Lenhof, Hans-Peter
2015-01-01
Summary Causal Bayesian Networks are a special class of Bayesian networks in which the hierarchy directly encodes the causal relationships between the variables. This allows to compute the effect of interventions, which are external changes to the system, caused by e.g. gene knockouts or an administered drug. Whereas numerous packages for constructing causal Bayesian networks are available, hardly any program targeted at downstream analysis exists. In this paper we present CausalTrail, a tool for performing reasoning on causal Bayesian networks using the do-calculus. CausalTrail's features include multiple data import methods, a flexible query language for formulating hypotheses, as well as an intuitive graphical user interface. The program is able to account for missing data and thus can be readily applied in multi-omics settings where it is common that not all measurements are performed for all samples. Availability and Implementation CausalTrail is implemented in C++ using the Boost and Qt5 libraries. It can be obtained from https://github.com/dstoeckel/causaltrail.
Granger causality vs. dynamic Bayesian network inference: a comparative study
Directory of Open Access Journals (Sweden)
Feng Jianfeng
2009-04-01
Full Text Available Abstract Background In computational biology, one often faces the problem of deriving the causal relationship among different elements such as genes, proteins, metabolites, neurons and so on, based upon multi-dimensional temporal data. Currently, there are two common approaches used to explore the network structure among elements. One is the Granger causality approach, and the other is the dynamic Bayesian network inference approach. Both have at least a few thousand publications reported in the literature. A key issue is to choose which approach is used to tackle the data, in particular when they give rise to contradictory results. Results In this paper, we provide an answer by focusing on a systematic and computationally intensive comparison between the two approaches on both synthesized and experimental data. For synthesized data, a critical point of the data length is found: the dynamic Bayesian network outperforms the Granger causality approach when the data length is short, and vice versa. We then test our results in experimental data of short length which is a common scenario in current biological experiments: it is again confirmed that the dynamic Bayesian network works better. Conclusion When the data size is short, the dynamic Bayesian network inference performs better than the Granger causality approach; otherwise the Granger causality approach is better.
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.
Orthopaedic service lines-revisited.
Patterson, Cheryl
2008-01-01
This article revisits the application of orthopaedic service lines from early introduction and growth of this organizational approach in the 1980s, through the 1990s, and into the current decade. The author has experienced and worked in various service-line structures through these three decades, as well as the preservice-line era of 1970s orthopaedics. Past lessons learned during earlier phases and then current trends and analysis by industry experts are summarized briefly, with indication given of the future for service lines. Variation versus consistency of certain elements in service-line definitions and in operational models is discussed. Main components of service-line structures and typical processes are described briefly, along with a more detailed section on the service-line director/manager role. Current knowledge contained here will help guide the reader to more "out-of-the-box" thinking toward comprehensive orthopaedic centers of excellence.
Forest, Valérie; Vergnon, Jean-Michel; Pourchez, Jérémie
2017-09-18
Although necessary, in vitro and in vivo studies are not fully successful at predicting nanomaterials toxicity. We propose to associate such assays to the biological monitoring of nanoparticles in clinical samples to get more relevant data on the chemical and physical nature and dose of nanoparticles found in humans. The concept is to establish the load of nanoparticles in biological samples of patients. Then, by comparing samples from different patient groups, nanoparticles of interest could be identified and a potential link between a given nanoparticle type and toxicity could be suggested. It must be confirmed by investigating the biological effects induced by these nanoparticles using in vitro or in vivo models (mechanistic or dose-response studies). This translational approach from the bedside to the bench and vice versa could allow a better understanding of the nanoparticle effects and mechanisms of toxicity that can contribute, at least in part, to a disease.
Energy Technology Data Exchange (ETDEWEB)
Steinberg, Aephraim M. [Institute for Experimental Physics, University of Vienna, Vienna (Austria)
2003-12-01
Experiment confirms that information cannot be transmitted faster than the speed of light. Ever since Einstein stated that nothing can travel faster than light, physicists have delighted in finding exceptions. One after another, observations of such 'superluminal' propagation have been made. However, while some image or pattern- such as the motion of a spotlight projected on a distant wall - might have appeared to travel faster than light, it seemed that there was no way to use the superluminal effect to transmit energy or information. In recent years, the superluminal propagation of light pulses through certain media has led to renewed controversy. In 1995, for example, Guenther Nimtz of the University of Cologne encoded Mozart's 40th Symphony on a microwave beam, which he claimed to have transmitted at a speed faster than light. Others maintain that such a violation of Einstein's speed limit would wreak havoc on our most fundamental ideas about causality, allowing an effect to precede its cause. Relativity teaches us that sending a signal faster than light would be equivalent to sending it backwards in time. (U.K.)
History, causality, and sexology.
Money, John
2003-08-01
In 1896, Krafft-Ebing published Psychopathia Sexualis. Popularly defined as hereditary weakness or taintedness in the family pedigree, degeneracy was called upon as a causal explanation for perversions of the sexual instinct. Although Krafft-Ebing accepted Karl Ulrichs proposal that homosexuality could be innate and probably located in the brain, he paid little attention to neuropathological sexology. Alfred Binet challenged Krafft-Ebing's orthodoxy by explaining fetishism in terms of associative learning, to which Krafft-Ebing's response was that only those with a hereditary taint would be vulnerable. Thus did the venerable nature-nurture antithesis maintain its rhetoric, even to the present day. Krafft-Ebing died too soon to meet the Freudian challenge of endopsychic determinism, and too soon also to encounter the idea of a developmental multivariate outcome of what I have termed the lovemap. Like other brain maps, for example the languagemap, the lovemap requires an intact human brain in which to develop. The personalized content of the lovemap has access to the brain by way of the special senses.
Causal Selection and Counterfactual Reasoning
Directory of Open Access Journals (Sweden)
William Jiménez-Leal
2013-01-01
Full Text Available El trabajo defiende la posición según la cual el pensamiento contrafactual depende de nuestra representación causal del mundo y, en este sentido, argumenta que existe una estrecha relación entre el razonamiento causal y el contrafactual. Se lleva a cabo una crítica a la teoría de la disociación de juicios de Mandel (Mandel, 2003b, que defiende la independencia funcional entre el proceso de selección causal y el razonamiento contrafactual en el contexto de la selección causal. En los experimentos realizados se manipularon algunos elementos de la semántica de la tarea con el fin de ilustrar aquellos casos en los que no se da la disociación entre el razonamiento causal y el contrafactual. En el Experimento 1, el nivel de descripción del evento objetivo se manipuló en una tarea de generación de listas y evaluación. El Experimento 2 replicó los hallazgos del Experimento 1 utilizando un sistema de codificación alternativo, mientras que el Experimento 3 realizó lo mismo utilizando un formato de respuesta alternativo. Los resultados de los experimentos apoyan la concepción del entendimiento causal propuesta por los modelos mentales causales.
A causal dispositional account of fitness.
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.
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...
Classical planning and causal implicatures
DEFF Research Database (Denmark)
Blackburn, Patrick Rowan; Benotti, Luciana
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...... 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...
Causal binary mask estimation for speech enhancement using sparsity constraints
DEFF Research Database (Denmark)
Kressner, Abigail Anne; Anderson, David V.; Rozell, Christopher J.
2013-01-01
While most single-channel noise reduction algorithms fail to improve speech intelligibility, the ideal binary mask (IBM) has demonstrated substantial intelligibility improvements for both normal- and impaired-hearing listeners. However, this approach exploits oracle knowledge of the target and in...... algorithm from the signal processing literature. However, the algorithm employs a non-causal estimator. The present work introduces an improved de-noising algorithm that uses more realistic frame-based (causal) computations to estimate a binary mask....
Testing for Causality in Variance Usinf Multivariate GARCH Models
Christian M. Hafner; Herwartz, Helmut
2008-01-01
Tests of causality in variance in multiple time series have been proposed recently, based on residuals of estimated univariate models. Although such tests are applied frequently, little is known about their power properties. In this paper we show that a convenient alternative to residual based testing is to specify a multivariate volatility model, such as multivariate GARCH (or BEKK), and construct a Wald test on noncausality in variance. We compare both approaches to testing causality in var...
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.
Frequency Dependent Attenuation Revisited
Richard, Kowar; Xavier, Bonnefond
2009-01-01
The work is inspired by thermo-and photoacoustic imaging, where recent efforts are devoted to take into account attenuation and varying wave speed parameters. In this paper we study causal equations describing propagation of attenuated pressure waves. We review standard models like frequency power laws and and the thermo-viscous equation. The lack of causality of standard models in the parameter range relevant for photoacoustic imaging requires to derive novel equations. The main ingredients for deriving causal equations are the Kramers-Kronig relation and the mathematical concept of linear system theory. The theoretical results of this work are underpined by numerical experiments.
McConnachie, Alex; Haig, Caroline; Sinclair, Lesley; Bauld, Linda; Tappin, David M
2017-07-20
The Cessation in Pregnancy Incentives Trial (CPIT), which offered financial incentives for smoking cessation during pregnancy showed a clinically and statistically significant improvement in cessation. However, infant birth weight was not seen to be affected. This study re-examines birth weight using an intuitive and a complier average causal effects (CACE) method to uncover important information missed by intention-to-treat analysis. CPIT offered financial incentives up to £400 to pregnant smokers to quit. With incentives, 68 women (23.1%) were confirmed non-smokers at primary outcome, compared to 25 (8.7%) without incentives, a difference of 14.3% (Fisher test, p birth weight gain with incentives is attributable only to potential quitters. We compared an intuitive approach to a CACE analysis. Mean birth weight of potential quitters in the incentives intervention group (who therefore quit) was 3338 g compared with potential quitters in the control group (who did not quit) 3193 g. The difference attributable to incentives, was 3338 - 3193 = 145 g (95% CI -617, +803). The mean difference in birth weight between the intervention and control groups was 21 g, and the difference in the proportion who managed to quit was 14.3%. Since the intervention consisted of the offer of incentives to quit smoking, the intervention was received by all women in the intervention group. However, "compliance" was successfully quitting with incentives, and the CACE analysis yielded an identical result, causal birth weight increase 21 g ÷ 0.143 = 145 g. Policy makers have great difficulty giving pregnant women money to stop smoking. This study indicates that a small clinically insignificant improvement in average birth weight is likely to hide an important clinically significant increase in infants born to pregnant smokers who want to stop but cannot achieve smoking cessation without the addition of financial voucher incentives. ISRCTN Registry, ISRCTN87508788
Moresi, Louis
2015-04-01
Dynamic Topography Revisited Dynamic topography is usually considered to be one of the trinity of contributing causes to the Earth's non-hydrostatic topography along with the long-term elastic strength of the lithosphere and isostatic responses to density anomalies within the lithosphere. Dynamic topography, thought of this way, is what is left over when other sources of support have been eliminated. An alternate and explicit definition of dynamic topography is that deflection of the surface which is attributable to creeping viscous flow. The problem with the first definition of dynamic topography is 1) that the lithosphere is almost certainly a visco-elastic / brittle layer with no absolute boundary between flowing and static regions, and 2) the lithosphere is, a thermal / compositional boundary layer in which some buoyancy is attributable to immutable, intrinsic density variations and some is due to thermal anomalies which are coupled to the flow. In each case, it is difficult to draw a sharp line between each contribution to the overall topography. The second definition of dynamic topography does seem cleaner / more precise but it suffers from the problem that it is not measurable in practice. On the other hand, this approach has resulted in a rich literature concerning the analysis of large scale geoid and topography and the relation to buoyancy and mechanical properties of the Earth [e.g. refs 1,2,3] In convection models with viscous, elastic, brittle rheology and compositional buoyancy, however, it is possible to examine how the surface topography (and geoid) are supported and how different ways of interpreting the "observable" fields introduce different biases. This is what we will do. References (a.k.a. homework) [1] Hager, B. H., R. W. Clayton, M. A. Richards, R. P. Comer, and A. M. Dziewonski (1985), Lower mantle heterogeneity, dynamic topography and the geoid, Nature, 313(6003), 541-545, doi:10.1038/313541a0. [2] Parsons, B., and S. Daly (1983), The
On causality of extreme events
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.
Causal categories: relativistically interacting processes
Coecke, Bob
2011-01-01
A symmetric monoidal category naturally arises as the mathematical structure that organizes physical systems, processes, and composition thereof, both sequentially and in parallel. This structure admits a purely graphical calculus. This paper is concerned with the encoding of a fixed causal structure within a symmetric monoidal category: causal dependencies will correspond to topological connectedness in the graphical language. We show that correlations, either classical or quantum, force terminality of the tensor unit. We also show that well-definedness of the concept of a global state forces the monoidal product to be only partially defined, which in turn results in a relativistic covariance theorem. Except for these assumptions, at no stage do we assume anything more than purely compositional symmetric-monoidal categorical structure. We cast these two structural results in terms of a mathematical entity, which we call a `causal category'. We provide methods of constructing causal categories, and we study t...
Fluctuations in Relativistic Causal Hydrodynamics
Kumar, Avdhesh; Mishra, Ananta P
2013-01-01
The formalism to calculate the hydrodynamics fluctuation using the quasi-stationary fluctuation theory of Onsager to the relativistic Navier-Stokes hydrodynamics is already known. In this work we calculate hydrodynamic fluctuations in relativistic causal theory of Muller, Israel and Stewart and other related causal hydrodynamic theories. We show that expressions for the Onsager coefficients and the correlation functions have form similar to the ones obtained by using Navier-Stokes equation. However, temporal evolution of the correlation functions obtained using MIS and the other causal theories can be significantly different than the correlation functions obtained using the Navier-Stokes equation. Finally, as an illustrative example, we explicitly plot the correlation functions obtained using the causal-hydrodynamics theories and compare them with correlation functions obtained by earlier authors using the expanding boost-invariant (Bjorken) flows.
Boundary Terms for Causal Sets
Buck, Michel; Jubb, Ian; Surya, Sumati
2015-01-01
We propose a family of boundary terms for the action of a causal set with a spacelike boundary. We show that in the continuum limit one recovers the Gibbons-Hawking-York boundary term in the mean. We also calculate the continuum limit of the mean causal set action for an Alexandrov interval in flat spacetime. We find that it is equal to the volume of the codimension-2 intersection of the two light-cone boundaries of the interval.
Causality constraints on TMD PDF
Efremov, A V
2013-01-01
In this short note, we discuss constraints on the transverse momentum dependent factorization formulae coming from the causality properties for the hadronic tensor. We show that the range of definition of the TMD PDFs in the transverse coordinate plane is wider that it is allowed by the causality. It indicates the presents of the large compensating corrections for the TMD PDF factorization theorem and/or overestimation of the transverse component dependence of TMD PDF.
Directory of Open Access Journals (Sweden)
Luiz G. Ferreira
2011-09-01
Full Text Available The very old and successful density-functional technique of half-occupation is revisited [J. C. Slater, Adv. Quant. Chem. 6, 1 (1972]. We use it together with the modern exchange-correlation approximations to calculate atomic ionization energies and band gaps in semiconductors [L. G. Ferreira et al., Phys. Rev. B 78, 125116 (2008]. Here we enlarge the results of the previous paper, add to its understandability, and show when the technique might fail. Even in this latter circumstance, the calculated band gaps are far better than those of simple LDA or GGA. As before, the difference between the Kohn-Sham ground state one-particle eigenvalues and the half-occupation eigenvalues is simply interpreted as the self-energy (not self-interaction of the particle excitation. In both cases, that of atomic ionization energies and semiconductor band gaps, the technique is proven to be very worthy, because not only the results can be very precise but the calculations are fast and very simple.
Rocha, Alexandre B.; de Moura, Carlos E. V.
2011-12-01
Potential energy curves for inner-shell states of nitrogen and carbon dioxide molecules are calculated by inner-shell complete active space self-consistent field (CASSCF) method, which is a protocol, recently proposed, to obtain specifically converged inner-shell states at multiconfigurational level. This is possible since the collapse of the wave function to a low-lying state is avoided by a sequence of constrained optimization in the orbital mixing step. The problem of localization of K-shell states is revisited by calculating their energies at CASSCF level based on both localized and delocalized orbitals. The localized basis presents the best results at this level of calculation. Transition energies are also calculated by perturbation theory, by taking the above mentioned MCSCF function as zeroth order wave function. Values for transition energy are in fairly good agreement with experimental ones. Bond dissociation energies for N2 are considerably high, which means that these states are strongly bound. Potential curves along ground state normal modes of CO2 indicate the occurrence of Renner-Teller effect in inner-shell states.
Vorselaars, Bart
2015-03-21
Liquid free energies are computed by integration along a path from a reference system of known free energy, using a strong localization potential. A particular choice of localization pathway is introduced, convenient for use in molecular dynamics codes, and which achieves accurate results without the need to include the identity-swap or relocation Monte Carlo moves used in previous studies. Moreover, an adaptive timestep is introduced to attain the reference system. Furthermore, a center-of-mass correction that is different from previous studies and phase-independent is incorporated. The resulting scheme allows computation of both solid and liquid free energies with only minor differences in simulation protocol. This is used to re-visit solid-liquid equilibrium in a system of short semi-flexible Lennard-Jones chain molecules. The computed melting curve is demonstrated to be consistent with direct co-existence simulations and computed hysteresis loops, provided that an entropic term arising from unsampled solid states is included.
Gibson, C H
1999-01-01
A theory of fossil turbulence presented in the 11th Liege Colloquium on Marine turbulence is "revisited" in the 29th Liege Colloquium "Marine Turbulence Revisited". The Gibson (1980) theory applied universal similarity theories of turbulence and turbulent mixing to the vertical evolution of an isolated patch of turbulence in a stratified fluid as it is constrained and fossilized by buoyancy forces. Towed oceanic microstructure measurements of Schedvin (1979) confirmed the predicted universal constants. Universal constants, spectra, hydrodynamic phase diagrams (HPDs) and other predictions of the theory have been reconfirmed by a wide variety of field and laboratory observations. Fossil turbulence theory has many applications; for example, in marine biology, laboratory and field measurements suggest phytoplankton species with different swimming abilities adjust their growth strategies differently by pattern recognition of several days of turbulence-fossil-turbulence dissipation and persistence times above thres...
Boubtane, Ekrame; Rault, C; Coulibaly, Dramane
2013-01-01
This paper examines the causality relationship between immigration, unemployment and economic growth of the host country. We employ the panel Granger causality testing approach of Konya (2006) that is based on SUR systems and Wald tests with country specific bootstrap critical values. This approach allows to test for Granger-causality on each individual panel member separately by taking into account the contemporaneous correlation across countries. Using annual data over the 1980-2005 period ...
Deterministic Graphical Games Revisited
DEFF Research Database (Denmark)
Andersson, Daniel; Hansen, Kristoffer Arnsfelt; Miltersen, Peter Bro
2008-01-01
We revisit the deterministic graphical games of Washburn. A deterministic graphical game can be described as a simple stochastic game (a notion due to Anne Condon), except that we allow arbitrary real payoffs but disallow moves of chance. We study the complexity of solving deterministic graphical...... games and obtain an almost-linear time comparison-based algorithm for computing an equilibrium of such a game. The existence of a linear time comparison-based algorithm remains an open problem....
Reverse cholesterol transport revisited
Institute of Scientific and Technical Information of China (English)
Astrid; E; van; der; Velde
2010-01-01
Reverse cholesterol transport was originally described as the high-density lipoprotein-mediated cholesterol flux from the periphery via the hepatobiliary tract to the intestinal lumen, leading to fecal excretion. Since the introduction of reverse cholesterol transport in the 1970s, this pathway has been intensively investigated. In this topic highlight, the classical reverse cholesterol transport concepts are discussed and the subject reverse cholesterol transport is revisited.
Directory of Open Access Journals (Sweden)
Pellegrino Edmund D
2001-04-01
Full Text Available Abstract A decade ago, we reviewed the field of clinical ethics; assessed its progress in research, education, and ethics committees and consultation; and made predictions about the future of the field. In this article, we revisit clinical ethics to examine our earlier observations, highlight key developments, and discuss remaining challenges for clinical ethics, including the need to develop a global perspective on clinical ethics problems.
Revisiting modern portfolio theory
Tenani, Paulo
2016-01-01
This paper revisits Modern Portfolio Theory and derives eleven properties of Efficient Allocations and Portfolios in the presence of leverage. With different degrees of leverage, an Efficient Portfolio is a linear combination of two portfolios that lie in different efficient frontiers - which allows for an attractive reinterpretation of the Separation Theorem. In particular a change in the investor risk-return preferences will leave the allocation between the Minimum Risk and Risk Portfolios ...
Bayesian Discovery of Linear Acyclic Causal Models
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...
Analyzing multiple spike trains with nonparametric Granger causality.
Nedungadi, Aatira G; Rangarajan, Govindan; Jain, Neeraj; Ding, Mingzhou
2009-08-01
Simultaneous recordings of spike trains from multiple single neurons are becoming commonplace. Understanding the interaction patterns among these spike trains remains a key research area. A question of interest is the evaluation of information flow between neurons through the analysis of whether one spike train exerts causal influence on another. For continuous-valued time series data, Granger causality has proven an effective method for this purpose. However, the basis for Granger causality estimation is autoregressive data modeling, which is not directly applicable to spike trains. Various filtering options distort the properties of spike trains as point processes. Here we propose a new nonparametric approach to estimate Granger causality directly from the Fourier transforms of spike train data. We validate the method on synthetic spike trains generated by model networks of neurons with known connectivity patterns and then apply it to neurons simultaneously recorded from the thalamus and the primary somatosensory cortex of a squirrel monkey undergoing tactile stimulation.
Trivial Lagrangians in the Causal Approach
Grigore, Dan-Radu
2015-01-01
We prove the non-uniqueness theorem for the chronological products of a gauge model. We use a cohomological language where the cochains are chronological products, gauge invariance means a cocycle restriction and coboundaries are expressions producing zero sandwiched between physical states. Suppose that we have gauge invariance up to order n of the perturbation theory and we modify the first-order chronological products by a coboundary (a trivial Lagrangian). Then the chronological products up to order n get modified by a coboundary also.
Assesment of mucoadhesion using small deformation rheology revisited
DEFF Research Database (Denmark)
Harloff-Helleberg, Stine; Vissing, Karina Juul; Nielsen, Hanne Mørck
2017-01-01
This work revisits the commonly used approach to assess mucoadhesion in drug delivery by small deformation rheology. The results show that biosimilar mucus serves as a more predictive mucus model system when compared to mucin suspensions. Data is fitted including error propagation, different from...
Educational Administration and the Management of Knowledge: 1980 Revisited
Bates, Richard
2013-01-01
This paper revisits the thesis of a 1980 paper that suggested a new approach to educational administration based upon the New Sociology of Education. In particular it updates answers to the six key questions asked by that paper: what counts as knowledge; how is what counts as knowledge organised; how is what counts as knowledge transmitted; how is…
Educational Administration and the Management of Knowledge: 1980 Revisited
Bates, Richard
2013-01-01
This paper revisits the thesis of a 1980 paper that suggested a new approach to educational administration based upon the New Sociology of Education. In particular it updates answers to the six key questions asked by that paper: what counts as knowledge; how is what counts as knowledge organised; how is what counts as knowledge transmitted; how is…
Causality and Tense - two temporal structure builders
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,
Causal Stability Conditions for General Relativistic Spacetimes
Howard, E M
2016-01-01
A brief overview of some open questions in general relativity with important consequences for causality theory is presented, aiming to a better understanding of the causal structure of the spacetime. Special attention is accorded to the problem of fundamental causal stability conditions. Several questions are raised and some of the potential consequences of recent results regarding the causality problem in general relativity are presented. A key question is whether causality violating regions are locally allowed. The new concept of almost stable causality is introduced; meanwhile, related conditions and criteria for the stability and almost stability of the causal structure are discussed.
Bech, Per; Tanghøj, Per; Cialdella, Philippe; Andersen, Henning Friis; Pedersen, Anders Gersel
2004-09-01
In continuation of a previous psychometric analysis of dose-response data for citalopram in depression, the corresponding study data for escitalopram is of interest, since escitalopram is the active enantiomer of citalopram and because citalopram was used as the active control. Revisiting those corresponding data, the psychometric properties of the Montgomery-Asberg Depression Scale (MADRS) and the Hamilton Depression Scale (HAMD) were investigated by focusing on the unidimensional HAMD6 and MADRS6. Effect sizes were calculated and compared for two dosages of escitalopram (10 mg and 20 mg daily) and between each of these two dosages and 40 mg citalopram daily. The results showed that the three depression scales MADRS6, MADRS10 and HAMD6 were psychometrically acceptable (coefficient of homogeneity of 0.40 or higher). In the severely depressed patients (MADRS10> or =30) a rather clear dose-response relationship for escitalopram was seen on all three scales after 6 and 8 wk of therapy. Thus, the effect size for 10 mg escitalopram ranged from 0.28 to 0.38 while the effect sizes for 20 mg escitalopram ranged from 0.57 to 0.77. This difference was statistically significant (pescitalopram and 40 mg citalopram was seen after 8 wk of therapy for MADRS10 (effect size 0.71 vs. 0.37). An item analysis identified 'suicidal thoughts' to be the most discriminating item in this respect. These results for the severely depressed patients were confirmed by the patients self-reported quality of life evaluation. When all included patients were analysed, however, no clear dose-response relationship was seen. In conclusion, a dose-response relationship for escitalopram was seen in the severely depressed patients on all outcome scales after 6 and 8 wk of treatment. After 8 wk of treatment 20 mg escitalopram was superior to 40 mg citalopram, but not after 2 wk of treatment.
Causal and Topological Aspects in Special and General Theory of Relativity
Saraykar, R V
2014-01-01
In this article we present a review of a geometric and algebraic approach to causal cones and describe cone preserving transformations and their relationship with the causal structure related to special and general relativity. We describe Lie groups, especially matrix Lie groups, homogeneous and symmetric spaces and causal cones and certain implications of these concepts in special and general relativity, related to causal structure and topology of space-time. We compare and contrast the results on causal relations with those in the literature for general space-times and compare these relations with K-causal maps. We also describe causal orientations and their implications for space-time topology and discuss some more topologies on space-time which arise as an application of domain theory. For the sake of completeness, we reproduce proofs of certain theorems which we proved in our earlier work.
Human causal discovery from observational data.
1996-01-01
Utilizing Bayesian belief networks as a model of causality, we examined medical students' ability to discover causal relationships from observational data. Nine sets of patient cases were generated from relatively simple causal belief networks by stochastic simulation. Twenty participants examined the data sets and attempted to discover the underlying causal relationships. Performance was poor in general, except at discovering the absence of a causal relationship. This work supports the poten...
The Geometry of Small Causal Cones
Jubb, Ian
2016-01-01
We derive a formula for the spacetime volume of a small causal cone. We use this formula within the context of causal set theory to construct causal set expressions for certain geometric quantities relating to a spacetime with a spacelike hypersurface. We also consider a scalar field on the causal set, and obtain causal set expressions relating to its normal derivatives with respect to the hypersurface.
Causality and complexity: the myth of objectivity in science.
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
On causality, unitarity and perturbative expansions
Energy Technology Data Exchange (ETDEWEB)
Danilkin, Igor; Gasparyan, Ashot; Lutz, Matthias [GSI, Planck Str. 1, 64291 Darmstadt (Germany)
2011-07-01
We present a pedagogical case study how to combine micro-causality and unitarity based on a perturbative approach. The method we advocate constructs an analytic extrapolation of partial-wave scattering amplitudes that is constrained by the unitarity condition. Suitably constructed conformal mappings help to arrive at a systematic approximation of the scattering amplitude. The technique is illustrated at hand of a Yukawa interaction. The typical case of a superposition of strong short-range and weak long-range forces is investigated.
On causality, unitarity and perturbative expansions
Energy Technology Data Exchange (ETDEWEB)
Danilkin, I.V.; Gasparyan, A.M. [GSI Helmholtzzentrum fuer Schwerionenforschung GmbH, Planck Str. 1, 64291 Darmstadt (Germany); Institute for Theoretical and Experimental Physics, 117259, B. Cheremushkinskaya 25, Moscow (Russian Federation); Lutz, M.F.M., E-mail: m.lutz@gsi.d [GSI Helmholtzzentrum fuer Schwerionenforschung GmbH, Planck Str. 1, 64291 Darmstadt (Germany)
2011-02-28
We present a pedagogical case study how to combine micro-causality and unitarity based on a perturbative approach. The method we advocate constructs an analytic extrapolation of partial-wave scattering amplitudes that is constrained by the unitarity condition. Suitably constructed conformal mappings help to arrive at a systematic approximation of the scattering amplitude in a quantum-field theoretical context. The technique is illustrated at hand of a Yukawa interaction. The typical case of a superposition of strong short-range and weak long-range forces is investigated.
Causality and Primordial Tensor Modes
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...
Causal analysis of academic performance.
Rao, D C; Morton, N E; Elston, R C; Yee, S
1977-03-01
Maximum likelihood methods are presented to test for the relations between causes and effects in linear path diagrams, without assuming that estimates of causes are free of error. Causal analysis is illustrated by published data of the Equal Educational Opportunity Survey, which show that American schools do not significantly modify socioeconomic differences in academic performance and that little of the observed racial difference in academic performance is causal. For two races differing by 15 IQ points, the differential if social class were randomized would be only about 3 points. The principle is stressed that a racial effect in a causal system may be environmental and that its etiology can be studied only by analysis of family resemblance in hybrid populations.
Causal reasoning with mental models.
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.
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.
Statistics, Causality and Bell's theorem
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...
Gravitation, Causality, and Quantum Consistency
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 ...
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.
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.
Cohomology with causally restricted supports
Khavkine, Igor
2014-01-01
De Rham cohomology with spacelike compact and timelike compact supports has recently been noticed to be of importance for understanding the structure of classical and quantum field theories on curved spacetimes. We compute these cohomology groups for globally hyperbolic spacetimes in terms of their standard de Rham cohomologies. The calculation exploits the fact that the de Rham-d'Alambert wave operator can be extended to a chain map that is homotopic to zero and that its causal Green function fits into a convenient exact sequence. This method extends also to the Calabi (or Killing-Riemann-Bianchi) complex and possibly other differential complexes. We also discuss generalized causal structures and functoriality.
Kolmogorov Complexity, Causality And Spin
Shayda, Dara O
2012-01-01
A novel topological and computational method for 'motion' is described. Motion is constrained by inequalities in terms of Kolmogorov Complexity. Causality is obtained as the output of a high-pass filter, passing through only high values of Kolmogorov Complexity. Motion under the electromagnetic field described with immediate relationship with Subscript[G, 2] Holonomy group and its corresponding dense free 2-subgroup. Similar to Causality, Spin emerges as an immediate and inevitable consequence of high values of Kolmogorov Complexity. Consequently, the physical laws are nothing but a low-pass filter for small values of Kolmogorov Complexity.
Information thermodynamics on causal networks.
Ito, Sosuke; Sagawa, Takahiro
2013-11-01
We study nonequilibrium thermodynamics of complex information flows induced by interactions between multiple fluctuating systems. Characterizing nonequilibrium dynamics by causal networks (i.e., Bayesian networks), we obtain novel generalizations of the second law of thermodynamics and the fluctuation theorem, which include an informational quantity characterized by the topology of the causal network. Our result implies that the entropy production in a single system in the presence of multiple other systems is bounded by the information flow between these systems. We demonstrate our general result by a simple model of biochemical adaptation.
Local Causality, Probability and Explanation
Healey, Richard A
2016-01-01
In papers published in the 25 years following his famous 1964 proof John Bell refined and reformulated his views on locality and causality. Although his formulations of local causality were in terms of probability, he had little to say about that notion. But assumptions about probability are implicit in his arguments and conclusions. Probability does not conform to these assumptions when quantum mechanics is applied to account for the particular correlations Bell argues are locally inexplicable. This account involves no superluminal action and there is even a sense in which it is local, but it is in tension with the requirement that the direct causes and effects of events are nearby.
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......, eventually rejecting the null hypothesis, even when the series are independent of each other. Moreover, controlling for these deterministic elements (in the auxiliary regressions of the test) does not preclude the possibility of drawing erroneous inferences. Granger-causality tests should not be used under...
Causality and micro-causality in curved spacetime
Energy Technology Data Exchange (ETDEWEB)
Hollowood, Timothy J. [Department of Physics, University of Wales Swansea, Swansea, SA2 8PP (United Kingdom)], E-mail: t.hollowood@swansea.ac.uk; Shore, Graham M. [Department of Physics, University of Wales Swansea, Swansea, SA2 8PP (United Kingdom)], E-mail: g.m.shore@swansea.ac.uk
2007-10-25
We consider how causality and micro-causality are realised in QED in curved spacetime. The photon propagator is found to exhibit novel non-analytic behaviour due to vacuum polarization, which invalidates the Kramers-Kronig dispersion relation and calls into question the validity of micro-causality in curved spacetime. This non-analyticity is ultimately related to the generic focusing nature of congruences of geodesics in curved spacetime, as implied by the null energy condition, and the existence of conjugate points. These results arise from a calculation of the complete non-perturbative frequency dependence of the vacuum polarization tensor in QED, using novel world-line path integral methods together with the Penrose plane-wave limit of spacetime in the neighbourhood of a null geodesic. The refractive index of curved spacetime is shown to exhibit superluminal phase velocities, dispersion, absorption (due to {gamma}{yields}e{sup +}e{sup -}) and bi-refringence, but we demonstrate that the wavefront velocity (the high-frequency limit of the phase velocity) is indeed c, thereby guaranteeing that causality itself is respected.
Institute of Scientific and Technical Information of China (English)
孙伟; 邵国青; 刘茂军; 武昱孜; 张旭; 华利忠
2013-01-01
利用顶点赋权反馈图分析法分析江苏某猪场沼气系统工程的效益,并建立猪场排泄物无污染的仿真学模型.根据2011年江苏某猪场与年猪粪尿和沼气效益有关的顶点赋权反馈图对其中的权值进行量化,采用量化结果和农户液化气消耗情况及耕地面积,建立猪场排泄物无污染的仿真学模型.结果表明:2011年该系统中含有3条正反馈环(沼气能源效益正反馈环、施肥面积正反馈环和沼渣效益正反馈环)及2条负反馈环(沼气浪费负反馈环和沼肥浪费负反馈环).建立了两套排泄物无污染的仿真学模型的调整方案:一是在平均存栏量(1728头)不变的情况下与168户农户建立输气管道,供农户使用;二是按比例扩大规模至3721头,并建立与周边所有361户农户的输气管道,进一步健全沼液灌溉渠,扩大沼液灌溉面积.%The benefit using biogas engineering system in a pig farm in Jiangsu Province was analyzed with vertex weighted causal loop diagram analysis approach after and a simulation model was established to solve the problem of pollution.According to the vertex weighted causal loop diagram analysis related to annual pig feces and biogas benefit of a pig farm in Jiangsu Province in 2011,the weightings related to the diagram were calculated.Using the results of weightings,the agricultural acreage and the liquefied gas consumption,the simulation model was established.The results showed that there were three positive feedback loops including the biogas benefit,fertilized area and benefit of biogas residues,and two negative feedback loops which were biogas waste and biogas manure waste in the system in 2011.The adjustment schemes of two simulation models were established to solve the problem of pollution:one was to build gas pipeline with 168 households if the amount of livestock (1728) was not changed,the other one was to build gas pipeline with 361 households if the amount of livestock increased
Revisiting Fermat's Factorization for the RSA Modulus
Gupta, Sounak
2009-01-01
We revisit Fermat's factorization method for a positive integer $n$ that is a product of two primes $p$ and $q$. Such an integer is used as the modulus for both encryption and decryption operations of an RSA cryptosystem. The security of RSA relies on the hardness of factoring this modulus. As a consequence of our analysis, two variants of Fermat's approach emerge. We also present a comparison between the two methods' effective regions. Though our study does not yield a new state-of-the-art algorithm for integer factorization, we believe that it reveals some interesting observations that are open for further analysis.
Revisiting and Renegotiating Wars
DEFF Research Database (Denmark)
Gade, Solveig
2014-01-01
Anri Sala’s film 1395 Days Without Red (2011) provides a kind of reenactment of an accidental day during the 1992-95 siege of Sarajevo. Shot in today’s Sarajevo, the film revisits and embodies some of the widely circulated images of the siege, such as inhabitants sprinting across so-called Sniper...... Alley in order to avoid the bullets of the Bosnian Serbian snipers positioned around the city. Based on a close reading of Sala’s work, this article will scrutinize how subjectivating techniques of power, during times of war, affectively work to create boundaries between those excluded from and those...
Osano, Bob
2016-01-01
In this article we revisit the significance of the often debated structural similarity between the equations of electromagnetism and fluid dynamics. Although the matching of the two sets of equations has successfully been done for non-dissipative forms of the equations, little has been done for cases where the dissipative terms are non-negligible. We consider the consequence of non-negligible viscosity and diffusivity, and how the fine-tuning of these parameters could allow fluid dynamics to be used to indirectly study certain properties of magnetic fields.
Hassani, Hossein; Huang, Xu; Gupta, Rangan; Ghodsi, Mansi
2016-10-01
In a recent paper, Gupta et al., (2015), analyzed whether sunspot numbers cause global temperatures based on monthly data covering the period 1880:1-2013:9. The authors find that standard time domain Granger causality test fails to reject the null hypothesis that sunspot numbers do not cause global temperatures for both full and sub-samples, namely 1880:1-1936:2, 1936:3-1986:11 and 1986:12-2013:9 (identified based on tests of structural breaks). However, frequency domain causality test detects predictability for the full-sample at short (2-2.6 months) cycle lengths, but not the sub-samples. But since, full-sample causality cannot be relied upon due to structural breaks, Gupta et al., (2015) conclude that the evidence of causality running from sunspot numbers to global temperatures is weak and inconclusive. Given the importance of the issue of global warming, our current paper aims to revisit this issue of whether sunspot numbers cause global temperatures, using the same data set and sub-samples used by Gupta et al., (2015), based on an nonparametric Singular Spectrum Analysis (SSA)-based causality test. Based on this test, we however, show that sunspot numbers have predictive ability for global temperatures for the three sub-samples, over and above the full-sample. Thus, generally speaking, our non-parametric SSA-based causality test outperformed both time domain and frequency domain causality tests and highlighted that sunspot numbers have always been important in predicting global temperatures.
Causal Categories: Relativistically Interacting Processes
Coecke, Bob; Lal, Raymond
2013-04-01
A symmetric monoidal category naturally arises as the mathematical structure that organizes physical systems, processes, and composition thereof, both sequentially and in parallel. This structure admits a purely graphical calculus. This paper is concerned with the encoding of a fixed causal structure within a symmetric monoidal category: causal dependencies will correspond to topological connectedness in the graphical language. We show that correlations, either classical or quantum, force terminality of the tensor unit. We also show that well-definedness of the concept of a global state forces the monoidal product to be only partially defined, which in turn results in a relativistic covariance theorem. Except for these assumptions, at no stage do we assume anything more than purely compositional symmetric-monoidal categorical structure. We cast these two structural results in terms of a mathematical entity, which we call a causal category. We provide methods of constructing causal categories, and we study the consequences of these methods for the general framework of categorical quantum mechanics.
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.
Causal feedbacks in climate change
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
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...
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...
Learning a Theory of Causality
Goodman, Noah D.; Ullman, Tomer D.; Tenenbaum, Joshua B.
2011-01-01
The very early appearance of abstract knowledge is often taken as evidence for innateness. We explore the relative learning speeds of abstract and specific knowledge within a Bayesian framework and the role for innate structure. We focus on knowledge about causality, seen as a domain-general intuitive theory, and ask whether this knowledge can be…
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".
The argumentative impact of causal relations
DEFF Research Database (Denmark)
Nielsen, Anne Ellerup
1996-01-01
such as causality, explanation and justification. In certain types of discourse, causal relations also imply an intentional element. This paper describes the way in which the semantic and pragmatic functions of causal markers can be accounted for in terms of linguistic and rhetorical theories of argumentation.......The semantic relations between and within utterances are marked by the use of connectors and adverbials. One type of semantic relations is causal relations expressed by causal markers such as because, therefore, so, for, etc. Some of these markers cover different types of causal relations...
Institute of Scientific and Technical Information of China (English)
魏岳嵩; 杜翠真
2014-01-01
确定变量间的因果关系是时间序列分析的重要内容。传统的图模型因果推断算法有着明显的局限性，要求模型是线性的且噪声项服从Gauss分布。本文利用图模型方法辨识非线性结构向量自回归模型变量间的因果关系，给出了一种基于互信息和条件互信息的非线性结构向量自回归因果图模型结构的非参数辨识方法。数值模拟结果验证了方法的有效性。%It is important to detect and clarify the cause-effect relationships among variables in time series analysis. Traditional graphical models causality inference methods have a salient limitation that the model must be linear and with Gaussian noise. In this paper, we apply the graphical models to infer the causal relationships a-mong variables of nonlinear structural vector autoregressive models. We propose a nonparametric method which employs both the mutual information and condi-tional mutual information to identify the causal structure of nonlinear structural vector autoregressive causal graph model. Numerical simulations demonstrate the effectiveness of the method.
Entanglement, holography and causal diamonds
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.
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.
Flux Analysis in Process Models via Causality
Kahramanoğullari, Ozan
2010-01-01
We present an approach for flux analysis in process algebra models of biological systems. We perceive flux as the flow of resources in stochastic simulations. We resort to an established correspondence between event structures, a broadly recognised model of concurrency, and state transitions of process models, seen as Petri nets. We show that we can this way extract the causal resource dependencies in simulations between individual state transitions as partial orders of events. We propose transformations on the partial orders that provide means for further analysis, and introduce a software tool, which implements these ideas. By means of an example of a published model of the Rho GTP-binding proteins, we argue that this approach can provide the substitute for flux analysis techniques on ordinary differential equation models within the stochastic setting of process algebras.
The Importance of Qualitative Research for Causal Explanation in Education
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,…
Explanation in causal inference methods for mediation and interaction
VanderWeele, Tyler
2015-01-01
A comprehensive examination of methods for mediation and interaction, VanderWeele's book is the first to approach this topic from the perspective of causal inference. Numerous software tools are provided, and the text is both accessible and easy to read, with examples drawn from diverse fields. The result is an essential reference for anyone conducting empirical research in the biomedical or social sciences.
The Importance of Qualitative Research for Causal Explanation in Education
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,…
Diagnosability Analysis Considering Causal Interpretations for Differential Constraints
2012-01-01
This paper is focused on structural approaches to study diagnosability properties given a system model taking into account, both simultaneously or separately, integral and differential causal interpretations for differential constraints. We develop a model characterization and corresponding algorithms, for studying system diagnosability using a structural decomposition that avoids generating the full set of system analytical redundancy relations. Simultaneous application of integral and diffe...
Observational studies and the difficult quest for causality
DEFF Research Database (Denmark)
Lipsitch, Marc; Jha, Ayan; Simonsen, Lone
2017-01-01
be answered once the vaccine is in use, from observational studies. However, such studies are inherently at risk for bias. Using a causal framework and illustrating with examples, we review newer approaches to detecting and avoiding confounding and selection bias in three major classes of observational study...
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.
Oriti, D
2004-01-01
We discuss the notion of causality in Quantum Gravity in the context of sum-over-histories approaches, in the absence therefore of any background time parameter. In the spin foam formulation of Quantum Gravity, we identify the appropriate causal structure in the orientation of the spin foam 2-complex and the data that characterize it; we construct a generalised version of spin foam models introducing an extra variable with the interpretation of proper time and show that different ranges of integration for this proper time give two separate classes of spin foam models: one corresponds to the spin foam models currently studied, that are independent of the underlying orientation/causal structure and are therefore interpreted as a-causal transition amplitudes; the second corresponds to a general definition of causal or orientation dependent spin foam models, interpreted as causal transition amplitudes or as the Quantum Gravity analogue of the Feynman propagator of field theory, implying a notion of ''timeless ord...
Designing Effective Supports for Causal Reasoning
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…
Representing Personal Determinants in Causal Structures.
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.…
Designing Effective Supports for Causal Reasoning
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…
Exploring Individual Differences in Preschoolers' Causal Stance
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…
Causal inference in economics and marketing.
Varian, Hal R
2016-07-05
This is an elementary introduction to causal inference in economics written for readers familiar with machine learning methods. The critical step in any causal analysis is estimating the counterfactual-a prediction of what would have happened in the absence of the treatment. The powerful techniques used in machine learning may be useful for developing better estimates of the counterfactual, potentially improving causal inference.
Expectations and Interpretations during Causal Learning
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…
Velocity requirements for causality violation
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...
Painless causality in defect calculations
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...
Confounding Equivalence in Causal Inference
Pearl, Judea
2012-01-01
The paper provides a simple test for deciding, from a given causal diagram, whether two sets of variables have the same bias-reducing potential under adjustment. The test re- quires that one of the following two condi- tions holds: either (1) both sets are admis- sible (i.e., satisfy the back-door criterion) or (2) the Markov boundaries surrounding the manipulated variable(s) are identical in both sets. Applications to covariate selection and model testing are discussed.
Causality and primordial tensor modes
Energy Technology Data Exchange (ETDEWEB)
Baumann, Daniel; Zaldarriaga, Matias, E-mail: dbaumann@physics.harvard.edu, E-mail: mzaldarriaga@cfa.harvard.edu [Department of Physics, Harvard University, 17 Oxford Street, Cambridge, MA 02138, U.S.A. and Center for Astrophysics, Harvard University, 60 Garden Street, Cambridge, MA 02138 (United States)
2009-06-01
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. θ ∼> 2°. 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 B-tilde -modes' for the analysis. We compute the real space B-tilde -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 scale of inflation. Wrongly associating tensor modes from causal seeds with inflation would imply an incorrect inference of the energy scale of inflation. We find that the superhorizon B-tilde -mode signal is above cosmic variance for the angular range 2° < θ < 4° and is therefore in principle detectable. In practice, the signal will be challenging to measure since it requires accurately resolving the recombination peak of the B-mode power spectrum. However, a future CMB satellite (CMBPol), with noise level Δ{sub P} ≅ 1μK-arcmin and sufficient resolution to efficiently correct for lensing-induced B-modes, should be able to detect the signal at more than 3σ if the tensor-to-scalar ratio isn't smaller than r ≅ 0.01.
When two become one: the limits of causality analysis of brain dynamics.
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.
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.
Emergent Geometry from Entropy and Causality
Engelhardt, Netta
generalizations are discussed, both at the classical and perturbatively quantum limits. In particular, several No Go Theorems are proven, indicative of a conclusion that supplementary approaches or information may be necessary to recover the full spacetime geometry. Part II of this thesis involves the relation between geometry and causality, the property that information cannot travel faster than light. Requiring this of any quantum field theory results in constraints on string theory setups that are dual to quantum field theories via the AdS/CFT correspondence. At the level of perturbative quantum gravity, it is shown that causality in the field theory constraints the causal structure in the bulk. At the level of nonperturbative quantum string theory, we find that constraints on causal signals restrict the possible ways in which curvature singularities can be resolved in string theory. Finally, a new program of research is proposed for the construction of bulk geometry from the divergences of correlation functions in the dual field theory. This divergence structure is linked to the causal structure of the bulk and of the field theory.
Modeling of causality with metamaterials
Smolyaninov, Igor I.
2013-02-01
Hyperbolic metamaterials may be used to model a 2 + 1-dimensional Minkowski space-time in which the role of time is played by one of the spatial coordinates. When a metamaterial is built and illuminated with a coherent extraordinary laser beam, the stationary pattern of light propagation inside the metamaterial may be treated as a collection of particle world lines, which represents a complete ‘history’ of this 2 + 1-dimensional space-time. While this model may be used to build interesting space-time analogs, such as metamaterial ‘black holes’ and a metamaterial ‘big bang’, it lacks causality: since light inside the metamaterial may propagate back and forth along the ‘timelike’ spatial coordinate, events in the ‘future’ may affect events in the ‘past’. Here we demonstrate that a more sophisticated metamaterial model may fix this deficiency via breaking the mirror and temporal (PT) symmetries of the original model and producing one-way propagation along the ‘timelike’ spatial coordinate. The resulting 2 + 1-dimensional Minkowski space-time appears to be causal. This scenario may be considered as a metamaterial model of the Wheeler-Feynman absorber theory of causality.
Entanglement, Holography and Causal Diamonds
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...
Reframing in dentistry: Revisited
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Sivakumar Nuvvula
2013-01-01
Full Text Available The successful practice of dentistry involves a good combination of technical skills and soft skills. Soft skills or communication skills are not taught extensively in dental schools and it can be challenging to learn and at times in treating dental patients. Guiding the child′s behavior in the dental operatory is one of the preliminary steps to be taken by the pediatric dentist and one who can successfully modify the behavior can definitely pave the way for a life time comprehensive oral care. This article is an attempt to revisit a simple behavior guidance technique, reframing and explain the possible psychological perspectives behind it for better use in the clinical practice.
Deterministic Graphical Games Revisited
DEFF Research Database (Denmark)
Andersson, Klas Olof Daniel; Hansen, Kristoffer Arnsfelt; Miltersen, Peter Bro
2012-01-01
Starting from Zermelo’s classical formal treatment of chess, we trace through history the analysis of two-player win/lose/draw games with perfect information and potentially infinite play. Such chess-like games have appeared in many different research communities, and methods for solving them......, such as retrograde analysis, have been rediscovered independently. We then revisit Washburn’s deterministic graphical games (DGGs), a natural generalization of chess-like games to arbitrary zero-sum payoffs. We study the complexity of solving DGGs and obtain an almost-linear time comparison-based algorithm...... for finding optimal strategies in such games. The existence of a linear time comparison-based algorithm remains an open problem....
DEFF Research Database (Denmark)
Ditlevsen, Ove Dalager
2004-01-01
The derivation of the life quality index (LQI) is revisited for a revision. This revision takes into account the unpaid but necessary work time needed to stay alive in clean and healthy conditions to be fit for effective wealth producing work and to enjoyable free time. Dimension analysis...... consistency problems with the standard power function expression of the LQI are pointed out. It is emphasized that the combination coefficient in the convex differential combination between the relative differential of the gross domestic product per capita and the relative differential of the expected life...... at birth should not vary between countries. Finally the distributional assumptions are relaxed as compared to the assumptions made in an earlier work by the author. These assumptions concern the calculation of the life expectancy change due to the removal of an accident source. Moreover a simple public...
Lorentz violation naturalness revisited
Belenchia, Alessio; Liberati, Stefano
2016-01-01
We revisit here the naturalness problem of Lorentz invariance violations on a simple toy model of a scalar field coupled to a fermion field via a Yukawa interaction. We first review some well-known results concerning the low-energy percolation of Lorentz violation from high energies, presenting some details of the analysis not explicitly discussed in the literature and discussing some previously unnoticed subtleties. We then show how a separation between the scale of validity of the effective field theory and that one of Lorentz invariance violations can hinder this low-energy percolation. While such protection mechanism was previously considered in the literature, we provide here a simple illustration of how it works and of its general features. Finally, we consider a case in which dissipation is present, showing that the dissipative behaviour does not percolate generically to lower mass dimension operators albeit dispersion does. Moreover, we show that a scale separation can protect from unsuppressed low-en...
Firewall Configuration Errors Revisited
Wool, Avishai
2009-01-01
The first quantitative evaluation of the quality of corporate firewall configurations appeared in 2004, based on Check Point FireWall-1 rule-sets. In general that survey indicated that corporate firewalls were often enforcing poorly written rule-sets, containing many mistakes. The goal of this work is to revisit the first survey. The current study is much larger. Moreover, for the first time, the study includes configurations from two major vendors. The study also introduce a novel "Firewall Complexity" (FC) measure, that applies to both types of firewalls. The findings of the current study indeed validate the 2004 study's main observations: firewalls are (still) poorly configured, and a rule-set's complexity is (still) positively correlated with the number of detected risk items. Thus we can conclude that, for well-configured firewalls, ``small is (still) beautiful''. However, unlike the 2004 study, we see no significant indication that later software versions have fewer errors (for both vendors).
Deterministic Graphical Games Revisited
DEFF Research Database (Denmark)
Andersson, Klas Olof Daniel; Hansen, Kristoffer Arnsfelt; Miltersen, Peter Bro
2012-01-01
Starting from Zermelo’s classical formal treatment of chess, we trace through history the analysis of two-player win/lose/draw games with perfect information and potentially infinite play. Such chess-like games have appeared in many different research communities, and methods for solving them......, such as retrograde analysis, have been rediscovered independently. We then revisit Washburn’s deterministic graphical games (DGGs), a natural generalization of chess-like games to arbitrary zero-sum payoffs. We study the complexity of solving DGGs and obtain an almost-linear time comparison-based algorithm...... for finding optimal strategies in such games. The existence of a linear time comparison-based algorithm remains an open problem....
DEFF Research Database (Denmark)
Grønbæk, Kaj; Whitehead, Jim; De Bra, Paul
2002-01-01
It has been 15 years since the original presentation by Frank Halasz at Hypertext'87 on seven issues for the next generation of hypertext systems. These issues are: Search and Query Composites Virtual Structures Computation in/over hypertext network Versioning Collaborative Work Extensibility...... and Tailorability Since that time, these issues have formed the nucleus of multiple research agendas within the Hypertext community. Befitting this direction-setting role, the issues have been revisited several times, by Halasz in his 1991 Hypertext keynote talk, and by Randy Trigg in his 1996 Hypertext keynote...... five years later. Additionally, over the intervening 15 years, many research systems have addressed the original seven issues, and new research avenues have opened up. The goal of this panel is to begin the process of developing a new set of seven issues for the next generation of hypertext system...
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.
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.
Emergence of Space-Time from Topologically Homogeneous Causal Networks
D'Ariano, Giacomo Mauro
2011-01-01
In this paper we study the emergence of Minkowski space-time from a causal network. Differently from previous approaches, we require the network to be topologically homogeneous, so that the metric is derived from pure event-counting. Emergence from events has an operational motivation in requiring that every physical quantity---including space-time---be defined through precise measurement procedures. Topological homogeneity is a requirement for having space-time metric emergent from the pure topology of causal connections, whereas physically corresponds to the universality of the physical law. We analyze in detail the case of 1+1 dimension. Coordinate systems are established via an Einsteinian protocol, and lead to a digital version of the Lorentz transformations. In a computational analogy, the foliation construction can also be regarded as the synchronization with a global clock of the calls to independent subroutines (corresponding to the causally independent events) in a parallel distributed computation, ...
Structural equation modeling: building and evaluating causal models: Chapter 8
Grace, James B.; Scheiner, Samuel M.; Schoolmaster, Donald R.
2015-01-01
Scientists frequently wish to study hypotheses about causal relationships, rather than just statistical associations. This chapter addresses the question of how scientists might approach this ambitious task. Here we describe structural equation modeling (SEM), a general modeling framework for the study of causal hypotheses. Our goals are to (a) concisely describe the methodology, (b) illustrate its utility for investigating ecological systems, and (c) provide guidance for its application. Throughout our presentation, we rely on a study of the effects of human activities on wetland ecosystems to make our description of methodology more tangible. We begin by presenting the fundamental principles of SEM, including both its distinguishing characteristics and the requirements for modeling hypotheses about causal networks. We then illustrate SEM procedures and offer guidelines for conducting SEM analyses. Our focus in this presentation is on basic modeling objectives and core techniques. Pointers to additional modeling options are also given.
A Causal Model for Fluctuating Sugar Levels in Diabetes Patients
Directory of Open Access Journals (Sweden)
Kinzang Chhogyal
2012-09-01
Full Text Available Background Causal models of physiological systems can be immensely useful in medicine as they may be used for both diagnostic and therapeutic reasoning. Aims In this paper we investigate how an agent may use the theory of belief change to rectify simple causal models of changing blood sugar levels in diabetes patients. Method We employ the semantic approach to belief change together with a popular measure of distance called Dalal distance between different state descriptions in order to implement a simple application that simulates the effectiveness of the proposed method in helping an agent rectify a simple causal model. Results Our simulation results show that distance-based belief change can help in improving the agent’s causal knowledge. However, under the current implementation there is no guarantee that the agent will learn the complete model and the agent may at times get stuck in local optima. Conclusion Distance-based belief change can help in refining simple causal models such as the example in this paper. Future work will include larger state-action spaces, better distance measures and strategies for choosing actions.
Illusions of causality at the heart of pseudoscience.
Matute, Helena; Yarritu, Ion; Vadillo, Miguel A
2011-08-01
Pseudoscience, superstitions, and quackery are serious problems that threaten public health and in which many variables are involved. Psychology, however, has much to say about them, as it is the illusory perceptions of causality of so many people that needs to be understood. The proposal we put forward is that these illusions arise from the normal functioning of the cognitive system when trying to associate causes and effects. Thus, we propose to apply basic research and theories on causal learning to reduce the impact of pseudoscience. We review the literature on the illusion of control and the causal learning traditions, and then present an experiment as an illustration of how this approach can provide fruitful ideas to reduce pseudoscientific thinking. The experiment first illustrates the development of a quackery illusion through the testimony of fictitious patients who report feeling better. Two different predictions arising from the integration of the causal learning and illusion of control domains are then proven effective in reducing this illusion. One is showing the testimony of people who feel better without having followed the treatment. The other is asking participants to think in causal terms rather than in terms of effectiveness. ©2010 The British Psychological Society.
The Causal Relationship between Health and Education Expenditures in Malaysia
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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.
Energy Technology Data Exchange (ETDEWEB)
Narayan, Paresh Kumar [Department of Accounting, Finance and Economics, Griffith University, Gold Coast (Australia); Prasad, Arti [School of Economics, University of the South Pacific, Suva (Fiji)
2008-02-15
The goal of this paper is to examine any causal effects between electricity consumption and real GDP for 30 OECD countries. We use a bootstrapped causality testing approach and unravel evidence in favour of electricity consumption causing real GDP in Australia, Iceland, Italy, the Slovak Republic, the Czech Republic, Korea, Portugal, and the UK. The implication is that electricity conservation policies will negatively impact real GDP in these countries. However, for the rest of the 22 countries our findings suggest that electricity conversation policies will not affect real GDP. (author)
Causality in Psychiatry: A Hybrid Symptom Network Construct Model
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Gerald eYoung
2015-11-01
Full Text Available Causality or etiology in psychiatry is marked by standard biomedical, reductionistic models (symptoms reflect the construct involved that inform approaches to nosology, or classification, such as in the DSM-5 (Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition; American Psychiatric Association, 2013. However, network approaches to symptom interaction (i.e., symptoms are formative of the construct; e.g., McNally, Robinaugh, Wu, Wang, Deserno, & Borsboom, 2014, for PTSD (posttraumatic stress disorder are being developed that speak to bottom-up processes in mental disorder, in contrast to the typical top-down psychological construct approach. The present article presents a hybrid top-down, bottom-up model of the relationship between symptoms and mental disorder, viewing symptom expression and their causal complex as a reciprocally dynamic system with multiple levels, from lower-order symptoms in interaction to higher-order constructs affecting them. The hybrid model hinges on good understanding of systems theory in which it is embedded, so that the article reviews in depth nonlinear dynamical systems theory (NLDST. The article applies the concept of emergent circular causality (Young, 2011 to symptom development, as well. Conclusions consider that symptoms vary over several dimensions, including: subjectivity; objectivity; conscious motivation effort; and unconscious influences, and the degree to which individual (e.g., meaning and universal (e.g., causal processes are involved. The opposition between science and skepticism is a complex one that the article addresses in final comments.
Causality in Psychiatry: A Hybrid Symptom Network Construct Model
Young, Gerald
2015-01-01
Causality or etiology in psychiatry is marked by standard biomedical, reductionistic models (symptoms reflect the construct involved) that inform approaches to nosology, or classification, such as in the DSM-5 [Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition; (1)]. However, network approaches to symptom interaction [i.e., symptoms are formative of the construct; e.g., (2), for posttraumatic stress disorder (PTSD)] are being developed that speak to bottom-up processes in mental disorder, in contrast to the typical top-down psychological construct approach. The present article presents a hybrid top-down, bottom-up model of the relationship between symptoms and mental disorder, viewing symptom expression and their causal complex as a reciprocally dynamic system with multiple levels, from lower-order symptoms in interaction to higher-order constructs affecting them. The hybrid model hinges on good understanding of systems theory in which it is embedded, so that the article reviews in depth non-linear dynamical systems theory (NLDST). The article applies the concept of emergent circular causality (3) to symptom development, as well. Conclusions consider that symptoms vary over several dimensions, including: subjectivity; objectivity; conscious motivation effort; and unconscious influences, and the degree to which individual (e.g., meaning) and universal (e.g., causal) processes are involved. The opposition between science and skepticism is a complex one that the article addresses in final comments. PMID:26635639
Experimental verification of an indefinite causal order
Rubino, Giulia; Rozema, Lee A.; Feix, Adrien; Araújo, Mateus; Zeuner, Jonas M.; Procopio, Lorenzo M.; Brukner, Časlav; Walther, Philip
2017-01-01
Investigating the role of causal order in quantum mechanics has recently revealed that the causal relations of events may not be a priori well defined in quantum theory. Although this has triggered a growing interest on the theoretical side, creating processes without a causal order is an experimental task. We report the first decisive demonstration of a process with an indefinite causal order. To do this, we quantify how incompatible our setup is with a definite causal order by measuring a “causal witness.” This mathematical object incorporates a series of measurements that are designed to yield a certain outcome only if the process under examination is not consistent with any well-defined causal order. In our experiment, we perform a measurement in a superposition of causal orders—without destroying the coherence—to acquire information both inside and outside of a “causally nonordered process.” Using this information, we experimentally determine a causal witness, demonstrating by almost 7 SDs that the experimentally implemented process does not have a definite causal order.
Norms and customs: causally important or causally impotent?
Jones, Todd
2010-01-01
In this article, I argue that norms and customs, despite frequently being described as being causes of behavior in the social sciences and ordinary conversation, cannot really cause behavior. Terms like "norms" and the like seem to refer to philosophically disreputable disjunctive properties. More problematically, even if they do not, or even if there can be disjunctive properties after all, I argue that norms and customs still cannot cause behavior. The social sciences would be better off without referring to properties like norms and customs as if they could be causal.
Inferring causal molecular networks: empirical assessment through a community-based effort.
Hill, Steven M; Heiser, Laura M; Cokelaer, Thomas; Unger, Michael; Nesser, Nicole K; Carlin, Daniel E; Zhang, Yang; Sokolov, Artem; Paull, Evan O; Wong, Chris K; Graim, Kiley; Bivol, Adrian; Wang, Haizhou; Zhu, Fan; Afsari, Bahman; Danilova, Ludmila V; Favorov, Alexander V; Lee, Wai Shing; Taylor, Dane; Hu, Chenyue W; Long, Byron L; Noren, David P; Bisberg, Alexander J; Mills, Gordon B; Gray, Joe W; Kellen, Michael; Norman, Thea; Friend, Stephen; Qutub, Amina A; Fertig, Elana J; Guan, Yuanfang; Song, Mingzhou; Stuart, Joshua M; Spellman, Paul T; Koeppl, Heinz; Stolovitzky, Gustavo; Saez-Rodriguez, Julio; Mukherjee, Sach
2016-04-01
It remains unclear whether causal, rather than merely correlational, relationships in molecular networks can be inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge, which focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective, and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess inferred molecular networks in a causal sense.
Equity Theory Ratios as Causal Schemas
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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.
Quantum Causality, Stochastics, Trajectories and Information
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...
A new recipe for causal completions
Marolf, D; Marolf, Donald; Ross, Simon F.
2003-01-01
We discuss the asymptotic structure of spacetimes, presenting a new construction of ideal points at infinity and introducing useful topologies on the completed space. Our construction is based on structures introduced by Geroch, Kronheimer, and Penrose and has much in common with the modifications introduced by Budic and Sachs as well as those introduced by Szabados. However, these earlier constructions defined ideal points as equivalence classes of certain past and future sets, effectively defining the completed space as a quotient. Our approach is fundamentally different as it identifies ideal points directly as appropriate pairs consisting of a (perhaps empty) future set and a (perhaps empty) past set. These future and past sets are just the future and past of the ideal point within the original spacetime. This provides our construction with useful causal properties and leads to more satisfactory results in a number of examples. We are also able to endow the completion with a topology. In fact, we introduc...
Relativistic non-equilibrium thermodynamics revisited
García-Colin, L S
2006-01-01
Relativistic irreversible thermodynamics is reformulated following the conventional approach proposed by Meixner in the non-relativistic case. Clear separation between mechanical and non-mechanical energy fluxes is made. The resulting equations for the entropy production and the local internal energy have the same structure as the non-relativistic ones. Assuming linear constitutive laws, it is shown that consistency is obtained both with the laws of thermodynamics and causality.
Primordial Magnetic Fields and Causality
Durrer, R; Durrer, Ruth; Caprini, Chiara
2003-01-01
In this letter we discuss the implications of causality on a primordial magnetic field. We show that the residual field on large scales is much stronger suppressed than usually assumed and that a helical component is even suppressed even more than the parity even part. We show that due to this strong suppression, even maximal primordial fields generated at the electroweak phase transition can just marginally seed the fields in galaxies and clusters, but they cannot leave any detectable imprint on the cosmic microwave background.
Random number generators and causality
Energy Technology Data Exchange (ETDEWEB)
Larrondo, H.A. [Facultad de Ingenieria, Universidad Nacional de Mar del Plata, Juan B. Justo 4302, 7600 Mar del Plata (Argentina)]. E-mail: larrondo@fi.mdp.edu.ar; Martin, M.T. [Instituto de Fisica (IFLP), Facultad de Ciencias Exactas, Universidad Nacional de La Plata and Argentina' s National Council (CONICET), C.C. 727, 1900 La Plata (Argentina)]. E-mail: mtmartin@venus.unlp.edu.ar; Gonzalez, C.M. [Facultad de Ingenieria, Universidad Nacional de Mar del Plata, Juan B. Justo 4302, 7600 Mar del Plata (Argentina)]. E-mail: cmgonzal@fi.mdp.edu.ar; Plastino, A. [Instituto de Fisica (IFLP), Facultad de Ciencias Exactas, Universidad Nacional de La Plata and Argentina' s National Council (CONICET), C.C. 727, 1900 La Plata (Argentina)]. E-mail: plastino@venus.unlp.edu.ar; Rosso, O.A. [Chaos and Biology Group, Instituto de Calculo, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Pabellon II, Ciudad Universitaria, 1428 Ciudad de Buenos Aires (Argentina)]. E-mail: oarosso@fibertel.com.ar
2006-04-03
We advance a prescription to randomize physical or algorithmic Random Number Generators (RNG's) that do not pass Marsaglia's DIEHARD test suite and discuss a special physical quantifier, based on an intensive statistical complexity measure, that is able to adequately assess the improvements produced thereby. Eight RNG's are evaluated and the associated results are compared to those obtained by recourse to Marsaglia's DIEHARD test suite. Our quantifier, which is evaluated using causality arguments, can forecast whether a given RNG will pass the above mentioned test.
Random number generators and causality
Larrondo, H. A.; Martín, M. T.; González, C. M.; Plastino, A.; Rosso, O. A.
2006-04-01
We advance a prescription to randomize physical or algorithmic Random Number Generators (RNG's) that do not pass Marsaglia's DIEHARD test suite and discuss a special physical quantifier, based on an intensive statistical complexity measure, that is able to adequately assess the improvements produced thereby. Eight RNG's are evaluated and the associated results are compared to those obtained by recourse to Marsaglia's DIEHARD test suite. Our quantifier, which is evaluated using causality arguments, can forecast whether a given RNG will pass the above mentioned test.
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.
Algorithms of causal inference for the analysis of effective connectivity among brain regions.
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.
Ligature-induced peri-implantitis in minipigs revisited
Stübinger, Stefan; Bucher, Ramon; Kronen, Peter W; Schlottig, Falko; von Rechenberg, Brigitte
2016-01-01
Aim: The ligature-induced defect model still remains the model of first choice to experimentally investigate the cause, effect and treatment approaches of periimplantitis. It was the aim of the present in-vivo trail to revisit the ligature-induced peri-implantitis minipig model regarding its current scientific value and ethical justification in implant research. Materials and methods: Six minipigs were used for the analysis of peri-implant hard and soft tissue structures. Animals were rand...
The discourse of causal explanations in school science
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
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.
Independence and dependence in human causal reasoning.
Rehder, Bob
2014-07-01
Causal graphical models (CGMs) are a popular formalism used to model human causal reasoning and learning. The key property of CGMs is the causal Markov condition, which stipulates patterns of independence and dependence among causally related variables. Five experiments found that while adult's causal inferences exhibited aspects of veridical causal reasoning, they also exhibited a small but tenacious tendency to violate the Markov condition. They also failed to exhibit robust discounting in which the presence of one cause as an explanation of an effect makes the presence of another less likely. Instead, subjects often reasoned "associatively," that is, assumed that the presence of one variable implied the presence of other, causally related variables, even those that were (according to the Markov condition) conditionally independent. This tendency was unaffected by manipulations (e.g., response deadlines) known to influence fast and intuitive reasoning processes, suggesting that an associative response to a causal reasoning question is sometimes the product of careful and deliberate thinking. That about 60% of the erroneous associative inferences were made by about a quarter of the subjects suggests the presence of substantial individual differences in this tendency. There was also evidence that inferences were influenced by subjects' assumptions about factors that disable causal relations and their use of a conjunctive reasoning strategy. Theories that strive to provide high fidelity accounts of human causal reasoning will need to relax the independence constraints imposed by CGMs.
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.
How prescriptive norms influence causal inferences.
Samland, Jana; Waldmann, Michael R
2016-11-01
Recent experimental findings suggest that prescriptive norms influence causal inferences. The cognitive mechanism underlying this finding is still under debate. We compare three competing theories: The culpable control model of blame argues that reasoners tend to exaggerate the causal influence of norm-violating agents, which should lead to relatively higher causal strength estimates for these agents. By contrast, the counterfactual reasoning account of causal selection assumes that norms do not alter the representation of the causal model, but rather later causal selection stages. According to this view, reasoners tend to preferentially consider counterfactual states of abnormal rather than normal factors, which leads to the choice of the abnormal factor in a causal selection task. A third view, the accountability hypothesis, claims that the effects of prescriptive norms are generated by the ambiguity of the causal test question. Asking whether an agent is a cause can be understood as a request to assess her causal contribution but also her moral accountability. According to this theory norm effects on causal selection are mediated by accountability judgments that are not only sensitive to the abnormality of behavior but also to mitigating factors, such as intentionality and knowledge of norms. Five experiments are presented that favor the accountability account over the two alternative theories.
An Algorithmic Information Calculus for Causal Discovery and Reprogramming Systems
Zenil, Hector
2017-09-08
We introduce a conceptual framework and an interventional calculus to steer and manipulate systems based on their intrinsic algorithmic probability using the universal principles of the theory of computability and algorithmic information. By applying sequences of controlled interventions to systems and networks, we estimate how changes in their algorithmic information content are reflected in positive/negative shifts towards and away from randomness. The strong connection between approximations to algorithmic complexity (the size of the shortest generating mechanism) and causality induces a sequence of perturbations ranking the network elements by the steering capabilities that each of them is capable of. This new dimension unmasks a separation between causal and non-causal components providing a suite of powerful parameter-free algorithms of wide applicability ranging from optimal dimension reduction, maximal randomness analysis and system control. We introduce methods for reprogramming systems that do not require the full knowledge or access to the system\\'s actual kinetic equations or any probability distributions. A causal interventional analysis of synthetic and regulatory biological networks reveals how the algorithmic reprogramming qualitatively reshapes the system\\'s dynamic landscape. For example, during cellular differentiation we find a decrease in the number of elements corresponding to a transition away from randomness and a combination of the system\\'s intrinsic properties and its intrinsic capabilities to be algorithmically reprogrammed can reconstruct an epigenetic landscape. The interventional calculus is broadly applicable to predictive causal inference of systems such as networks and of relevance to a variety of machine and causal learning techniques driving model-based approaches to better understanding and manipulate complex systems.
Modeling of causality with metamaterials
Smolyaninov, Igor I
2012-01-01
Hyperbolic metamaterials may be used to model a 2+1 dimensional Minkowski spacetime in which the role of time is played by one of the spatial coordinates. When a metamaterial is built and illuminated with a coherent extraordinary laser beam, the stationary pattern of light propagation inside the metamaterial may be treated as a collection of particle world lines, which represents a complete history of this 2+1 dimensional spacetime. While this model may be used to build interesting spacetime analogs, such as metamaterial black holes and big bang, it lacks causality: since light inside the metamaterial may propagate back and force along the timelike spatial coordinate, events in the future may affect events in the past. Here we demonstrate that a more sophisticated metamaterial model may fix this deficiency via breaking the mirror and temporal (PT) symmetries of the original model and producing one-way propagation along the timelike spatial coordinate. Resulting 2+1 Minkowski spacetime appears to be causal. Th...
Causal viscous cosmology without singularities
Laciana, Carlos E
2016-01-01
An isotropic and homogeneous cosmological model with a source of dark energy is studied. That source is simulated with a viscous relativistic fluid with minimal causal correction. In this model the restrictions on the parameters coming from the following conditions are analized: a) energy density without singularities along time, b) scale factor increasing with time, c) universe accelerated at present time, d) state equation for dark energy with "w" bounded and close to -1. It is found that those conditions are satified for the following two cases. i) When the transport coefficient ({\\tau}_{{\\Pi}}), associated to the causal correction, is negative, with the aditional restriction {\\zeta}|{\\tau}_{{\\Pi}}|>2/3, where {\\zeta} is the relativistic bulk viscosity coefficient. The state equation is in the "phantom" energy sector. ii) For {\\tau}_{{\\Pi}} positive, in the "k-essence" sector. It is performed an exact calculation for the case where the equation of state is constant, finding that option (ii) is favored in r...
Directory of Open Access Journals (Sweden)
Sabine eDelannoy
2016-01-01
Full Text Available Current methods for screening Enterohemorrhagic Escherichia coli (EHEC O157 and non-O157 in beef enrichments typically rely on the molecular detection of stx, eae, and serogroup-specific wzx or wzy gene fragments. As these genetic markers can also be found in some non-EHEC strains, a number of ‘false positive’ results are obtained. Here, we explore the suitability of five novel molecular markers, espK, espV, ureD, Z2098, and CRISPRO26:H11 as candidates for a more accurate screening of EHEC strains of greater clinical significance in industrialized countries. Of the 1,739 beef enrichments tested, 180 were positive for both stx and eae genes. Ninety (50% of these tested negative for espK, espV, ureD, and Z2098, but twelve out of these negative samples were positive for the CRISPRO26:H11 gene marker specific for a newly emerging virulent EHEC O26:H11 French clone. We show that screening for stx, eae, espK, and espV, in association with the CRISPRO26:H11 marker is a better approach to narrow down the EHEC screening step in beef enrichments. The number of potentially positive samples was reduced by 48.88% by means of this alternative strategy compared to the European and American reference methods, thus substantially improving the discriminatory power of EHEC screening systems. This approach is in line with the EFSA (European Food Safety Authority opinion on pathogenic STEC published in 2013.
Furman, Katherine
2017-04-04
In this paper, I utilise the tools of analytic philosophy to amalgamate mono-causal and multi-causal theories of disease. My aim is to better integrate viral and socio-economic explanations of AIDS in particular, and to consider how the perceived divide between mono-causal and multi-causal theories played a role in the tragedy of AIDS denialism in South Africa in the early 2000s. Currently, there is conceptual ambiguity surrounding the relationship between mono-causal and multi-causal theories in biomedicine and epidemiology. Mono-causal theories focus on single, typically microbial, sources of illness and are most concerned with infectious diseases. By contrast, multi-causal theories allow for multiple factors to underpin a disease's aetiology, including socio-economic and behavioural factors, and they usually focus on chronic non-communicable diseases. However, if these theories are taken to be strictly distinct, this prevents the inclusion of both microbial and socio-economic factors in a single explanation of any particular disease. This strict distinction became a problem when trying to explain the disproportionate prevalence of AIDS in southern Africa and ultimately contributed to the tragedy of AIDS denialism in South Africa. In tandem with viewing how the perceived divide between multi-causal and mono-causal theories underpinned AIDS denialism, I examine Thabo Mbeki's specific role, while acknowledging that AIDS is being deprioritised on a broader international level. Overall, I will demonstrate that any long-term plan to eliminate AIDS will require viral and socio-economic factors to be considered simultaneously and that such a theoretical approach requires a clearer understanding of the underlying concepts of disease aetiology.
Spin foam models as energetic causal sets
Cortês, Marina
2014-01-01
Energetic causal sets are causal sets endowed by a flow of energy-momentum between causally related events. These incorporate a novel mechanism for the emergence of space-time from causal relations. Here we construct a spin foam model which is also an energetic causal set model. This model is closely related to the model introduced by Wieland, and this construction makes use of results used there. What makes a spin foam model also an energetic causal set is Wieland's identification of new momenta, conserved at events (or four-simplices), whose norms are not mass, but the volume of tetrahedra. This realizes the torsion constraints, which are missing in previous spin foam models, and are needed to relate the connection dynamics to those of the metric, as in general relativity. This identification makes it possible to apply the new mechanism for the emergence of space-time to a spin foam model.
Lorentz violation naturalness revisited
Energy Technology Data Exchange (ETDEWEB)
Belenchia, Alessio; Gambassi, Andrea; Liberati, Stefano [SISSA - International School for Advanced Studies, via Bonomea 265, 34136 Trieste (Italy); INFN, Sezione di Trieste, via Valerio 2, 34127 Trieste (Italy)
2016-06-08
We revisit here the naturalness problem of Lorentz invariance violations on a simple toy model of a scalar field coupled to a fermion field via a Yukawa interaction. We first review some well-known results concerning the low-energy percolation of Lorentz violation from high energies, presenting some details of the analysis not explicitly discussed in the literature and discussing some previously unnoticed subtleties. We then show how a separation between the scale of validity of the effective field theory and that one of Lorentz invariance violations can hinder this low-energy percolation. While such protection mechanism was previously considered in the literature, we provide here a simple illustration of how it works and of its general features. Finally, we consider a case in which dissipation is present, showing that the dissipative behaviour does not percolate generically to lower mass dimension operators albeit dispersion does. Moreover, we show that a scale separation can protect from unsuppressed low-energy percolation also in this case.
Revisiting energy efficiency fundamentals
Energy Technology Data Exchange (ETDEWEB)
Perez-Lombard, L.; Velazquez, D. [Grupo de Termotecnia, Escuela Superior de Ingenieros, Universidad de Sevilla, Camino de los Descubrimientos s/n, 41092 Seville (Spain); Ortiz, J. [Building Research Establishment (BRE), Garston, Watford, WD25 9XX (United Kingdom)
2013-05-15
Energy efficiency is a central target for energy policy and a keystone to mitigate climate change and to achieve a sustainable development. Although great efforts have been carried out during the last four decades to investigate the issue, focusing into measuring energy efficiency, understanding its trends and impacts on energy consumption and to design effective energy efficiency policies, many energy efficiency-related concepts, some methodological problems for the construction of energy efficiency indicators (EEI) and even some of the energy efficiency potential gains are often ignored or misunderstood, causing no little confusion and controversy not only for laymen but even for specialists. This paper aims to revisit, analyse and discuss some efficiency fundamental topics that could improve understanding and critical judgement of efficiency stakeholders and that could help in avoiding unfounded judgements and misleading statements. Firstly, we address the problem of measuring energy efficiency both in qualitative and quantitative terms. Secondly, main methodological problems standing in the way of the construction of EEI are discussed, and a sequence of actions is proposed to tackle them in an ordered fashion. Finally, two key topics are discussed in detail: the links between energy efficiency and energy savings, and the border between energy efficiency improvement and renewable sources promotion.
Linear causal modeling with structural equations
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
Causal inference in economics and marketing
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
Identifying Causal Effects with Computer Algebra
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.
Causality effects on accelerating light pulses
National Research Council Canada - National Science Library
Kaminer, Ido; Lumer, Yaakov; Segev, Mordechai; Christodoulides, Demetrios N
2011-01-01
.... We explore the effects of causality, and find that, whereas decelerating pulses can asymptotically reach zero group velocity, pulses that accelerate towards infinite group velocity inevitably break...
Scalar Curvature of a Causal Set
Benincasa, Dionigi M. T.; Dowker, Fay
2010-05-01
A one parameter family of retarded linear operators on scalar fields on causal sets is introduced. When the causal set is well approximated by 4 dimensional Minkowski spacetime, the operators are Lorentz invariant but nonlocal, are parametrized by the scale of the nonlocality, and approximate the continuum scalar D’Alembertian □ when acting on fields that vary slowly on the nonlocality scale. The same operators can be applied to scalar fields on causal sets which are well approximated by curved spacetimes in which case they approximate □-(1)/(2)R where R is the Ricci scalar curvature. This can used to define an approximately local action functional for causal sets.
Benjamin Franklin and Mesmerism, revisited.
McConkey, Kevin M; Perry, Campbell
2002-10-01
The authors revisit and update their previous historiographical note (McConkey & Perry, 1985) on Benjamin Franklin's involvement with and investigation of animal magnetism or mesmerism. They incorporate more recent literature and offer additional comment about Franklin's role in and views about mesmerism. Franklin had a higher degree of personal involvement with and a more detailed opinion of mesmerism than has been previously appreciated.
Leadership and Management Theories Revisited
DEFF Research Database (Denmark)
Madsen, Mona Toft
2001-01-01
The goal of the paper is to revisit and analyze key contributions to the understanding of leadership and management. As a part of the discussion a role perspective that allows for additional and/or integrated leader dimensions, including a change-centered, will be outlined. Seemingly, a major...
A remote coal deposit revisited
DEFF Research Database (Denmark)
Bojesen-Kofoed, Jørgen A.; Kalkreuth, Wolfgang; Petersen, Henrik I.
2012-01-01
In 1908, members of the “Danmark Expedition” discovered a coal deposit in a very remote area in western Germania Land, close to the margin of the inland ice in northeast Greenland. The deposit was, however, neither sampled nor described, and was revisited in 2009 for the first time since its disc...
Revisiting Inter-Genre Similarity
DEFF Research Database (Denmark)
Sturm, Bob L.; Gouyon, Fabien
2013-01-01
We revisit the idea of ``inter-genre similarity'' (IGS) for machine learning in general, and music genre recognition in particular. We show analytically that the probability of error for IGS is higher than naive Bayes classification with zero-one loss (NB). We show empirically that IGS does...
ORAL GLUCOSE TOLERANCE TEST REVISITED
African Journals Online (AJOL)
Determinant for the usefulness or otherwise of oral glucose tolerance test for the diagnosis ... personnel, poverty and poor economic management, 8'9 that are known to .... Symptoms of diabetes plus casual plasma glucose ... WHO 2-hr plasma glucose criteria of 1l.1mmol/L .... Diagnostic criteria and performance revisited.
Vincent, Grégoire; Sabatier, Daniel; Rutishauser, Ervan
2014-06-01
Airborne laser scanning provides continuous coverage mapping of forest canopy height and thereby is a powerful tool to scale-up above-ground biomass (AGB) estimates from stand to landscape. A critical first step is the selection of the plot variables which can be related to light detection and ranging (LiDAR) statistics. A universal approach was previously proposed which combines local and regional estimates of basal area (BA) and wood density with LiDAR-derived canopy height to map carbon at a regional scale (Asner et al. in Oecologia 168:1147-1160, 2012). Here we explore the contribution of stem diameter distribution, specific wood density and height-diameter (H-D) allometry to forest stand AGB and propose an alternative model. By applying the new model to a large tropical forest data set we show that an appropriate choice of input variables is essential to minimize prediction error of stand AGB which will propagate at larger scale. Stem number (N) and average stem cross-sectional area should be used instead of BA when scaling from tree to plot. Stand quadratic mean diameter above the census threshold diameter size should be preferred over stand mean diameter as it reduces the prediction error of stand AGB by a factor of ten. Wood density should be weighted by stem volume per species instead of BA. LiDAR-derived statistics should prove useful for estimating local H-D allometries as well as mapping N and the mean quadratic diameter above 10 cm at the landscape level. Prior stratification into forest types is likely to improve both estimation procedures significantly and is considered the foremost current challenge.
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.
The Species Problem in Myxomycetes Revisited.
Walker, Laura M; Stephenson, Steven L
2016-08-01
Species identification in the myxomycetes (plasmodial slime molds or myxogastrids) poses particular challenges to researchers as a result of their morphological plasticity and frequent alteration between sexual and asexual life strategies. Traditionally, myxomycete morphology has been used as the primary method of species delimitation. However, with the increasing availability of genetic information, traditional myxomycete taxonomy is being increasingly challenged, and new hypotheses continue to emerge. Due to conflicts that sometimes occur between traditional and more modern species concepts that are based largely on molecular data, there is a pressing need to revisit the discussion surrounding the species concept used for myxomycetes. Biological diversity is being increasingly studied with molecular methods and data accumulates at ever-faster rates, making resolution of this matter urgent. In this review, currently used and potentially useful species concepts (biological, morphological, phylogenetic and ecological) are reviewed, and an integrated approach to resolve the myxomycete species problem is discussed. Copyright © 2016 Elsevier GmbH. All rights reserved.
Causal compensated perturbations in cosmology
Energy Technology Data Exchange (ETDEWEB)
Veeraraghavan, S.; Stebbins, A. (Harvard-Smithsonian Center for Astrophysics, Cambridge, MA (USA) California Univ., Berkeley (USA) Canadian Institute for Theoretical Astrophysics, Toronto (Canada))
1990-12-01
A theoretical framework is developed to calculate linear perturbations in the gravitational and matter fields which arise causally in response to the presence of stiff matter sources in a FRW cosmology. It is shown that, in order to satisfy energy and momentum conservation, the gravitational fields of the source must be compensated by perturbations in the matter and gravitational fields, and the role of such compensation in containing the initial inhomogeneities in their subsequent evolution is discussed. A complete formal solution is derived in terms of Green functions for the perturbations produced by an arbitrary source in a flat universe containing cold dark matter. Approximate Green function solutions are derived for the late-time density perturbations and late-time gravitational waves in a universe containing a radiation fluid. A cosmological energy-momentum pseudotensor is defined to clarify the nature of energy and momentum conservation in the expanding universe. 55 refs.
Comparison theorems for causal diamonds
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...
The continuum limit of causal fermion systems from Planck scale structures to macroscopic physics
Finster, Felix
2016-01-01
This monograph introduces the basic concepts of the theory of causal fermion systems, a recent approach to the description of fundamental physics. The theory yields quantum mechanics, general relativity and quantum field theory as limiting cases and is therefore a candidate for a unified physical theory. From the mathematical perspective, causal fermion systems provide a general framework for describing and analyzing non-smooth geometries and "quantum geometries". The dynamics is described by a novel variational principle, called the causal action principle. In addition to the basics, the book provides all the necessary mathematical background and explains how the causal action principle gives rise to the interactions of the standard model plus gravity on the level of second-quantized fermionic fields coupled to classical bosonic fields. The focus is on getting a mathematically sound connection between causal fermion systems and physical systems in Minkowski space. The book is intended for graduate students e...
The frequency domain causality analysis between energy consumption and income in the United States
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Aviral Kumar Tiwari
2014-03-01
Full Text Available We investigated Granger-causality in the frequency domain between primary energy consumption/electricity consumption and GDP for the US by employing approach of Lemmens et al. (2008 and covering the period of January, 1973 to December, 2008. We found that causal and reverse causal relations between primary energy consumption and GDP and electricity consumption and GDP vary across frequencies. Our unique contribution in the existing literature lies in decomposing the causality on the basis of time horizons and demonstrating bidirectional the short-run, the medium-run and the long-run causality between GDP and primary energy consumption/electricity consumption and thus providing evidence for the feedback hypothesis. These results have important implications for the US for planning of the short, the medium and the long run energy and economic growth related policies.
Learning causal networks with latent variables from multivariate information in genomic data.
Verny, Louis; Sella, Nadir; Affeldt, Séverine; Singh, Param Priya; Isambert, Hervé
2017-10-02
Learning causal networks from large-scale genomic data remains challenging in absence of time series or controlled perturbation experiments. We report an information- theoretic method which learns a large class of causal or non-causal graphical models from purely observational data, while including the effects of unobserved latent variables, commonly found in many genomic datasets. Starting from a complete graph, the method iteratively removes dispensable edges, by uncovering significant information contributions from indirect paths, and assesses edge-specific confidences from randomization of available data. The remaining edges are then oriented based on the signature of causality in observational data. The approach and associated algorithm, miic, outperform earlier methods on a broad range of benchmark networks. Causal network reconstructions are presented at different biological size and time scales, from gene regulation in single cells to whole genome duplication in tumor development as well as long term evolution of vertebrates. Miic is publicly available at https://github.com/miicTeam/MIIC.
The significance test controversy revisited the fiducial Bayesian alternative
Lecoutre, Bruno
2014-01-01
The purpose of this book is not only to revisit the “significance test controversy,”but also to provide a conceptually sounder alternative. As such, it presents a Bayesian framework for a new approach to analyzing and interpreting experimental data. It also prepares students and researchers for reporting on experimental results. Normative aspects: The main views of statistical tests are revisited and the philosophies of Fisher, Neyman-Pearson and Jeffrey are discussed in detail. Descriptive aspects: The misuses of Null Hypothesis Significance Tests are reconsidered in light of Jeffreys’ Bayesian conceptions concerning the role of statistical inference in experimental investigations. Prescriptive aspects: The current effect size and confidence interval reporting practices are presented and seriously questioned. Methodological aspects are carefully discussed and fiducial Bayesian methods are proposed as a more suitable alternative for reporting on experimental results. In closing, basic routine procedures...
Computation of Probabilities in Causal Models of History of Science
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Osvaldo Pessoa Jr.
2006-12-01
Full Text Available : The aim of this paper is to investigate the ascription of probabilities in a causal model of an episode in the history of science. The aim of such a quantitative approach is to allow the implementation of the causal model in a computer, to run simulations. As an example, we look at the beginning of the science of magnetism, “explaining” — in a probabilistic way, in terms of a single causal model — why the field advanced in China but not in Europe (the difference is due to different prior probabilities of certain cultural manifestations. Given the number of years between the occurrences of two causally connected advances X and Y, one proposes a criterion for stipulating the value pY=X of the conditional probability of an advance Y occurring, given X. Next, one must assume a specific form for the cumulative probability function pY=X(t, which we take to be the time integral of an exponential distribution function, as is done in physics of radioactive decay. Rules for calculating the cumulative functions for more than two events are mentioned, involving composition, disjunction and conjunction of causes. We also consider the problems involved in supposing that the appearance of events in time follows an exponential distribution, which are a consequence of the fact that a composition of causes does not follow an exponential distribution, but a “hypoexponential” one. We suggest that a gamma distribution function might more adequately represent the appearance of advances.
Causal efficacy and the normative notion of sustainability science
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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.
Energy Technology Data Exchange (ETDEWEB)
Garcia-Parrado, Alfonso [Departamento de Fisica Teorica, Universidad del Pais Vasco, Apartado 644, 48080 Bilbao (Spain); Sanchez, Miguel [Departamento de Geometria y Topologia, Facultad de Ciencias, Universidad de Granada, Avenida Fuentenueva s/n, 18071 Granada (Spain)
2005-11-07
Recently (Garcia-Parrado and Senovilla 2003 Class. Quantum Grav. 20 625-64) the concept of causal mapping between spacetimes, essentially equivalent in this context to the chronological map defined in abstract chronological spaces, and the related notion of causal structure, have been introduced as new tools to study causality in Lorentzian geometry. In the present paper, these tools are further developed in several directions such as (i) causal mappings-and, thus, abstract chronological ones-do not preserve two levels of the standard hierarchy of causality conditions (however, they preserve the remaining levels as shown in the above reference), (ii) even though global hyperbolicity is a stable property (in the set of all time-oriented Lorentzian metrics on a fixed manifold), the causal structure of a globally hyperbolic spacetime can be unstable against perturbations; in fact, we show that the causal structures of Minkowski and Einstein static spacetimes remain stable, whereas that of de Sitter becomes unstable, (iii) general criteria allow us to discriminate different causal structures in some general spacetimes (e.g. globally hyperbolic, stationary standard); in particular, there are infinitely many different globally hyperbolic causal structures (and thus, different conformal ones) on R{sup 2} (iv) plane waves with the same number of positive eigenvalues in the frequency matrix share the same causal structure and, thus, they have equal causal extensions and causal boundaries.
The Power of Causal Beliefs and Conflicting Evidence on Causal Judgments and Decision Making
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…
Causal analysis of time series from hydrological systems
Selle, Benny; Aufgebauer, Britta; Knorr, Klaus-Holger
2017-04-01
It is often difficult to infer cause and effect in hydrological systems for which time series of system inputs, outputs and state variables are observed. A recently published technique called Convergent Cross Mapping could be a promising tool to detect causality between time series. A response variable Y may be causally related to a forcing variable X, if the so called cross mapping of X using Y improves with the amount of data included. The idea is that a response variable contains information on the history of its driving variable whereas the reverse may not be true. We propose an alternative approach based on similar ideas using neural networks. Our approach is firstly compared to Convergent Cross Mapping using a synthetic time series of precipitation and streamflow generated by a rainfall runoff model. Secondly, measured concentrations of dissolved organic carbon and dissolved iron from a mountainous stream in Germany, that were previously hypothesised to be casually linked, are tested.
Burns, J. A.; Sharma, I.
2000-10-01
Motivated by the recent detection of complex rotational states for several asteroids and comets, as well as by the ongoing and planned spacecraft missions to such bodies, which should allow their rotational states to be accurately determined, we revisit the problem of the nutational damping of small solar system bodies. The nutational damping of asteroids has been approximately analyzed by Prendergast (1958), Burns and Safronov (1973), and Efroimsky and Lazarian (2000). Many other similar dynamical studies concern planetary wobble decay (e.g., Peale 1973; Yoder and Ward 1979), interstellar dust grain alignment (e.g., Purcell 1979; Lazarian and Efroimsky 1999) and damping of Earth's Chandler wobble (Lambeck 1980). Recall that rotational energy loss for an isolated body aligns the body's angular momentum vector with its axis of maximum inertia. Assuming anelastic dissipation, simple dimensional analysis determines a functional form of the damping timescale, on which all the above authors agree. However, the numerical coefficients of published results are claimed to differ by orders of magnitude. Differences have been ascribed to absent physics, to solutions that fail to satisfy boundary conditions perfectly, and to unphysical choices for the Q parameter. The true reasons for the discrepancy are unclear since, despite contrary claims, the full 3D problem (nutational damping of an anelastic ellipsoid) is analytically intractable so far. To move the debate forward, we compare the solution of a related 2D problem to the expressions found previously, and we present results from a finite element model. On this basis, we feel that previous rates for the decay of asteroidal tumbling (Harris 1994), derived from Burns and Safronov (1973), are likely to be accurate, at least to a factor of a few. Funded by NASA.
Context and time in causal learning: contingency and mood dependent effects.
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Rachel M Msetfi
Full Text Available Defining cues for instrumental causality are the temporal, spatial and contingency relationships between actions and their effects. In this study, we carried out a series of causal learning experiments that systematically manipulated time and context in positive and negative contingency conditions. In addition, we tested participants categorized as non-dysphoric and mildly dysphoric because depressed mood has been shown to affect the processing of all these causal cues. Findings showed that causal judgements made by non-dysphoric participants were contextualized at baseline and were affected by the temporal spacing of actions and effects only with generative, but not preventative, contingency relationships. Participants categorized as dysphoric made less contextualized causal ratings at baseline but were more sensitive than others to temporal manipulations across the contingencies. These effects were consistent with depression affecting causal learning through the effects of slowed time experience on accrued exposure to the context in which causal events took place. Taken together, these findings are consistent with associative approaches to causal judgement.
Causality principle in reconstruction of sparse NMR spectra
Mayzel, Maxim; Orekhov, Vladislav Yu
2014-01-01
Rapid development of sparse sampling methodology offers dramatic increase in power and efficiency of magnetic resonance techniques in medicine, chemistry, molecular structural biology, and other fields. We show that harnessing causality of the sparsely detected NMR signal is a general approach for a major improvement of the spectra quality. The work gives a theoretical framework of the method and demonstrates notable improvement of the spectra reconstructed with two state-of-the-art signal processing algorithms, compressed sensing and SIFT.
Altered cortical causality after remifentanil administration in healthy volunteers
DEFF Research Database (Denmark)
Khodayari-Rostamabad, Ahmad; Graversen, Carina; Olesen, Soren S;
2014-01-01
being reproducible between the two baseline recordings, several PSI features were altered by remifentanil administration in comparison to placebo. Furthermore, several of the PSI features altered by remifentanil were correlated to changes in both CRT and pain scores. The results indicate...... that remifentanil administration influence the information flow between several brain areas. Hence, the EEG causality approach offers the potential to assist in deciphering the cortical effects of remifentanil administration....
Testing for causality in variance using multivariate GARCH models
Hafner, Christian; Herwartz, H.
2004-01-01
textabstractTests of causality in variance in multiple time series have been proposed recently, based on residuals of estimated univariate models. Although such tests are applied frequently little is known about their power properties. In this paper we show that a convenient alternative to residual based testing is to specify a multivariate volatility model, such as multivariate GARCH (or BEKK), and construct a Wald test on noncausality in variance. We compare both approaches to testing causa...
The transfer matrix in four-dimensional Causal Dynamical Triangulations
Görlich, Andrzej
2013-01-01
Causal Dynamical Triangulations is a background independent approach to quantum gravity. In this paper we introduce a phenomenological transfer matrix model, where at each time step a reduced set of quantum states is used. The states are solely characterized by the discretized spatial volume. Using Monte Carlo simulations we determine the effective transfer matrix elements and extract the effective action for the scale factor. In this framework no degrees of freedom are frozen, however, the obtained action agrees with the minisuperspace model.
Causal Mediation Analysis: Warning! Assumptions Ahead
Keele, Luke
2015-01-01
In policy evaluations, interest may focus on why a particular treatment works. One tool for understanding why treatments work is causal mediation analysis. In this essay, I focus on the assumptions needed to estimate mediation effects. I show that there is no "gold standard" method for the identification of causal mediation effects. In…
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...
Causal Moderation Analysis Using Propensity Score Methods
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…
Essays on Causal Inference for Public Policy
Zajonc, Tristan
2012-01-01
Effective policymaking requires understanding the causal effects of competing proposals. Relevant causal quantities include proposals' expected effect on different groups of recipients, the impact of policies over time, the potential trade-offs between competing objectives, and, ultimately, the optimal policy. This dissertation studies causal…
"Comments on Slavin": Synthesizing Causal Inferences
Briggs, Derek C.
2008-01-01
When causal inferences are to be synthesized across multiple studies, efforts to establish the magnitude of a causal effect should be balanced by an effort to evaluate the generalizability of the effect. The evaluation of generalizability depends on two factors that are given little attention in current syntheses: construct validity and external…
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....
Quasi-Experimental Designs for Causal Inference
Kim, Yongnam; Steiner, Peter
2016-01-01
When randomized experiments are infeasible, quasi-experimental designs can be exploited to evaluate causal treatment effects. The strongest quasi-experimental designs for causal inference are regression discontinuity designs, instrumental variable designs, matching and propensity score designs, and comparative interrupted time series designs. This…
The causal order on the ambient boundary
Antoniadis, Ignatios; Papadopoulos, Kyriakos
2016-01-01
We analyse the causal structure of the ambient boundary, the conformal infinity of the ambient (Poincar\\'e) metric. Using topological tools we show that the only causal relation compatible with the global topology of the boundary spacetime is the horismos order. This has important consequences for the notion of time in the conformal geometry of the ambient boundary.
Causal Indicators Can Help to Interpret Factors
Bentler, Peter M.
2016-01-01
The latent factor in a causal indicator model is no more than the latent factor of the factor part of the model. However, if the causal indicator variables are well-understood and help to improve the prediction of individuals' factor scores, they can help to interpret the meaning of the latent factor. Aguirre-Urreta, Rönkkö, and Marakas (2016)…
On the spectral formulation of Granger causality.
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.
Towards Spectral Geometry for Causal Sets
Yazdi, Yasaman K
2016-01-01
We show that the Feynman propagator (or the d'Alembertian) of a causal set contains the complete information about the causal set. Intuitively, this is because the Feynman propagator, being a correlator that decays with distance, provides a measure for the invariant distance between pairs of events. Further, we show that even the spectra alone (of the self-adjoint and anti-self-adjoint parts) of the propagator(s) and d'Alembertian already carry large amounts of geometric information about their causal set. This geometric information is basis independent and also gauge invariant in the sense that it is relabeling invariant (which is analogue to diffeomorphism invariance). We provide numerical evidence that the associated spectral distance between causal sets can serve as a measure for the geometric similarity between causal sets.
Causality, Bell's theorem, and Ontic Definiteness
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...
Quantum-coherent mixtures of causal relations
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.
A Causal Alternative to Feynman's Propagator
Koksma, Jurjen F
2010-01-01
The Feynman propagator used in the conventional in-out formalism in quantum field theory is not a causal propagator as wave packets are propagated virtually instantaneously outside the causal region of the initial state. We formulate a causal in-out formalism in quantum field theory by making use of the Wheeler propagator, the time ordered commutator propagator, which is manifestly causal. Only free scalar field theories and their first quantization are considered. We identify the real Klein Gordon field itself as the wave function of a neutral spinless relativistic particle. Furthermore, we derive a probability density for our relativistic wave packet using the inner product between states that live on a suitably defined Hilbert space of real quantum fields. We show that the time evolution of our probability density is governed by the Wheeler propagator, such that it behaves causally too.
Quantum-coherent mixtures of causal relations
MacLean, Jean-Philippe W.; Ried, Katja; Spekkens, Robert W.; Resch, Kevin J.
2017-01-01
Understanding the causal influences that hold among 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 a coherent mixture of these two possibilities. We realize this 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 effect, whereby two independent causes can become correlated on observation of their common effect. The interplay of causality and quantum theory lies at the heart of challenging foundational puzzles, including Bell's theorem and the search for quantum gravity. PMID:28485394
Causality Violation, Gravitational Shockwaves and UV Completion
Hollowood, Timothy J
2015-01-01
The effective actions describing the low-energy dynamics of QFTs involving gravity generically exhibit causality violations. These may take the form of superluminal propagation or Shapiro time advances and allow the construction of "time machines", i.e. spacetimes admitting closed non-spacelike curves. Here, we discuss critically whether such causality violations may be used as a criterion to identify unphysical effective actions or whether, and how, causality problems may be resolved by embedding the action in a fundamental, UV complete QFT. We study in detail the case of photon scattering in an Aichelburg-Sexl gravitational shockwave background and calculate the phase shifts in QED for all energies, demonstrating their smooth interpolation from the causality-violating effective action values at low-energy to their manifestly causal high-energy limits. At low energies, these phase shifts may be interpreted as backwards-in-time coordinate jumps as the photon encounters the shock wavefront, and we illustrate h...
A Multivariate Granger Causality Concept towards Full Brain Functional Connectivity.
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.
A Multivariate Granger Causality Concept towards Full Brain Functional Connectivity.
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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.
Causal ubiquity in quantum physics a superluminal and local-causal physical ontology
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
Social Life Cycle Assessment Revisited
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Ruqun Wu
2014-07-01
Full Text Available To promote the development of Social Life Cycle Assessment (SLCA, we conducted a comprehensive review of recently developed frameworks, methods, and characterization models for impact assessment for future method developers and SLCA practitioners. Two previous reviews served as our foundations for this review. We updated the review by including a comprehensive list of recently-developed SLCA frameworks, methods and characterization models. While a brief discussion from goal, data, and indicator perspectives is provided in Sections 2 to 4 for different frameworks/methods, the focus of this review is Section 5 where discussion on characterization models for impact assessment of different methods is provided. The characterization models are categorized into two types following the UNEP/SETAC guidelines: type I models without impact pathways and type II models with impact pathways. Different from methods incorporating type I/II characterization models, another LCA modeling approach, Life Cycle Attribute Assessment (LCAA, is also discussed in this review. We concluded that methods incorporating either type I or type II models have limitations. For type I models, the challenge lies in the systematic identification of relevant stakeholders and materiality issues; while for type II models, identification of impact pathways that most closely and accurately represent the real-world causal relationships is the key. LCAA may avoid these problems, but the ultimate questions differ from those asked by the methods using type I and II models.
Combining Research Approaches: The Anvil Writers Revisited.
Sanders, Keith P.; Morris, Daniel N.
1990-01-01
Conjoins Q methodology with the interviewing techniques of the oral historian in a study of eight surviving contributors to "The Anvil," a midwestern proletarian magazine of the 1920s and 1930s. Finds four factors, labeled as the patron, the revolutionary artist, the Jack Conroy factor, and the humanist. Discusses the limitations and advantages of…
Causal systems categories: differences in novice and expert categorization of causal phenomena.
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.
Enceladus' tidal dissipation revisited
Tobie, Gabriel; Behounkova, Marie; Choblet, Gael; Cadek, Ondrej; Soucek, Ondrej
2016-10-01
A series of chemical and physical evidence indicates that the intense activity at Enceladus' South Pole is related to a subsurface salty water reservoir underneath the tectonically active ice shell. The detection of a significant libration implies that this water reservoir is global and that the average ice shell thickness is about 20-25km (Thomas et al. 2016). The interpretation of gravity and topography data further predicts large variations in ice shell thickness, resulting in a shell potentially thinner than 5 km in the South Polar Terrain (SPT) (Cadek et al. 2016). Such an ice shell structure requires a very strong heat source in the interior, with a focusing mechanism at the SPT. Thermal diffusion through the ice shell implies that at least 25-30 GW is lost into space by passive diffusion, implying a very efficient dissipation mechanism in Enceladus' interior to maintain such an ocean/ice configuration thermally stable.In order to determine in which conditions such a large dissipation power may be generated, we model the tidal response of Enceladus including variable ice shell thickness. For the rock core, we consider a wide range of rheological parameters representative of water-saturated porous rock materials. We demonstrate that the thinning toward the South Pole leads to a strong increase in heat production in the ice shell, with a optimal thickness obtained between 1.5 and 3 km, depending on the assumed ice viscosity. Our results imply that the heat production in the ice shell within the SPT may be sufficient to counterbalance the heat loss by diffusion and to power eruption activity. However, outside the SPT, a strong dissipation in the porous core is required to counterbalance the diffusive heat loss. We show that about 20 GW can be generated in the core, for an effective viscosity of 1012 Pa.s, which is comparable to the effective viscosity estimated in water-saturated glacial tills on Earth. We will discuss the implications of this revisited tidal
Spread of entanglement and causality
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...
Spread of entanglement and causality
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.
Normalizability analysis of the generalized quantum electrodynamics from the causal point of view
Bufalo, R; 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 implication of the gauge invariance onto the model and obtain the respective Ward-Takahashi-Fradkin identities.
Directory of Open Access Journals (Sweden)
David Matesanz
2015-01-01
Full Text Available This paper revisits the issue of the influence of macro-economic announcements over the exchange rates volatility, but from a different perspective as it is the usual in the econometric literature. By quantifying the impact of world-wide macroeconomic information published in the economic calendar in several recent years we were able to construct long events’ time series with the objective to test whether they influence exchange rate volatilities in several currencies. In order to do that, Granger causality test was employed by using a computational approach. Our results show that announcements from U.S.A are, by far, the most important influence over the three spot forex quotes, Euro/Dollar, Euro/Yen and Dollar/Yen. The method proposed here opens the door to address several open questions until now.
The role of causal maps in intellectual capital measurement and management
DEFF Research Database (Denmark)
Montemari, Marco; Nielsen, Christian
2013-01-01
of the lag and the persistence of the effects of managerial actions. In addition, it can signal when and how to refine and update the causal map. The combination of these factors supports the dynamic measurement and management of intellectual capital. Research limitations/implications – The paper presented......Purpose – The purpose of this paper is to investigate the measurement and the management of the dynamic aspects of intellectual capital through the use of causal mapping. Design/methodology/approach – The study details the methods utilized in a single in-depth case study of a network-based business...... the causal mapping approach into practice. Practical implications – The paper highlights the need to build causal maps to enhance the measurement and management of intellectual capital, which is dynamic of nature. As a consequence, this tool can be useful for companies to monitor their intangibles...
Causal inference, probability theory, and graphical insights.
Baker, Stuart G
2013-11-10
Causal inference from observational studies is a fundamental topic in biostatistics. The causal graph literature typically views probability theory as insufficient to express causal concepts in observational studies. In contrast, the view here is that probability theory is a desirable and sufficient basis for many topics in causal inference for the following two reasons. First, probability theory is generally more flexible than causal graphs: Besides explaining such causal graph topics as M-bias (adjusting for a collider) and bias amplification and attenuation (when adjusting for instrumental variable), probability theory is also the foundation of the paired availability design for historical controls, which does not fit into a causal graph framework. Second, probability theory is the basis for insightful graphical displays including the BK-Plot for understanding Simpson's paradox with a binary confounder, the BK2-Plot for understanding bias amplification and attenuation in the presence of an unobserved binary confounder, and the PAD-Plot for understanding the principal stratification component of the paired availability design.
A Simple Test for Causality in Volatility
Directory of Open Access Journals (Sweden)
Chia-Lin Chang
2017-03-01
Full Text Available An early development in testing for causality (technically, Granger non-causality in the conditional variance (or volatility associated with financial returns was the portmanteau statistic for non-causality in the variance of Cheng and Ng (1996. A subsequent development was the Lagrange Multiplier (LM test of non-causality in the conditional variance by Hafner and Herwartz (2006, who provided simulation results to show that their LM test was more powerful than the portmanteau statistic for sample sizes of 1000 and 4000 observations. While the LM test for causality proposed by Hafner and Herwartz (2006 is an interesting and useful development, it is nonetheless arbitrary. In particular, the specification on which the LM test is based does not rely on an underlying stochastic process, so the alternative hypothesis is also arbitrary, which can affect the power of the test. The purpose of the paper is to derive a simple test for causality in volatility that provides regularity conditions arising from the underlying stochastic process, namely a random coefficient autoregressive process, and a test for which the (quasi- maximum likelihood estimates have valid asymptotic properties under the null hypothesis of non-causality. The simple test is intuitively appealing as it is based on an underlying stochastic process, is sympathetic to Granger’s (1969, 1988 notion of time series predictability, is easy to implement, and has a regularity condition that is not available in the LM test.
Entanglement Entropy in Causal Set Theory
Sorkin, Rafael D
2016-01-01
Entanglement entropy is now widely accepted as having deep connections with quantum gravity. It is therefore desirable to understand it in the context of causal sets, especially since they provide in a natural manner the UV cutoff needed to render entanglement entropy finite. Defining entropy in a causal set is not straightforward because the type of canonical hypersurface-data on which definitions of entanglement typically rely is not available in a causal set. Instead, we will appeal to a more global expression given in arXiv:1205.2953 which, for a gaussian scalar field, expresses the entropy of a spacetime region in terms of the field's correlation function within that region. Carrying this formula over to the causal set, one obtains an entanglement entropy which is both finite and of a Lorentz invariant nature. Herein we evaluate this entropy for causal sets of 1+1 dimensions, and specifically for order-intervals ("causal diamonds") within the causal set, finding in the first instance an entropy that obey...
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.
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.
Diagnosis and causal explanation in psychiatry.
Maung, Hane Htut
2016-12-01
In clinical medicine, a diagnosis can offer an explanation of a patient's symptoms by specifying the pathology that is causing them. Diagnoses in psychiatry are also sometimes presented in clinical texts as if they pick out pathological processes that cause sets of symptoms. However, current evidence suggests the possibility that many diagnostic categories in psychiatry are highly causally heterogeneous. For example, major depressive disorder may not be associated with a single type of underlying pathological process, but with a range of different causal pathways, each involving complex interactions of various biological, psychological, and social factors. This paper explores the implications of causal heterogeneity for whether psychiatric diagnoses can be said to serve causal explanatory roles in clinical practice. I argue that while they may fall short of picking out a specific cause of the patient's symptoms, they can nonetheless supply different sorts of clinically relevant causal information. In particular, I suggest that some psychiatric diagnoses provide negative information that rules out certain causes, some provide approximate or disjunctive information about the range of possible causal processes, and some provide causal information about the relations between the symptoms themselves.
The Damped String Problem Revisited
Gesztesy, Fritz
2010-01-01
We revisit the damped string equation on a compact interval with a variety of boundary conditions and derive an infinite sequence of trace formulas associated with it, employing methods familiar from supersymmetric quantum mechanics. We also derive completeness and Riesz basis results (with parentheses) for the associated root functions under less smoothness assumptions on the coefficients than usual, using operator theoretic methods (rather than detailed eigenvalue and root function asymptotics) only.
Zuber, Jean-Bernard
2016-01-01
In this note, I revisit integrals over $\\SU(N)$ of the form $ \\int DU\\, U_{i_1j_1}\\cdots U_{i_pj_p}\\Ud_{k_1l_1}\\cdots \\Ud_{k_nl_n}$. While the case $p=n$ is well known, it seems that explicit expressions for $p=n+N$ had not appeared in the literature. Similarities and differences, in particular in the large $N$ limit, between the two cases are discussed
Computer-Aided Experiment Planning toward Causal Discovery in Neuroscience.
Matiasz, Nicholas J; Wood, Justin; Wang, Wei; Silva, Alcino J; Hsu, William
2017-01-01
Computers help neuroscientists to analyze experimental results by automating the application of statistics; however, computer-aided experiment planning is far less common, due to a lack of similar quantitative formalisms for systematically assessing evidence and uncertainty. While ontologies and other Semantic Web resources help neuroscientists to assimilate required domain knowledge, experiment planning requires not only ontological but also epistemological (e.g., methodological) information regarding how knowledge was obtained. Here, we outline how epistemological principles and graphical representations of causality can be used to formalize experiment planning toward causal discovery. We outline two complementary approaches to experiment planning: one that quantifies evidence per the principles of convergence and consistency, and another that quantifies uncertainty using logical representations of constraints on causal structure. These approaches operationalize experiment planning as the search for an experiment that either maximizes evidence or minimizes uncertainty. Despite work in laboratory automation, humans must still plan experiments and will likely continue to do so for some time. There is thus a great need for experiment-planning frameworks that are not only amenable to machine computation but also useful as aids in human reasoning.