Causality

Science.gov (United States)

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.

Causal events enter awareness faster than non-causal events

Directory of Open Access Journals (Sweden)

Pieter Moors

2017-01-01

Full Text Available 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.

Theories of Causality

Science.gov (United States)

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.

A general, multivariate definition of causal effects in epidemiology.

Science.gov (United States)

Flanders, W Dana; Klein, Mitchel

2015-07-01

Population causal effects are often defined as contrasts of average individual-level counterfactual outcomes, comparing different exposure levels. Common examples include causal risk difference and risk ratios. These and most other examples emphasize effects on disease onset, a reflection of the usual epidemiological interest in disease occurrence. Exposure effects on other health characteristics, such as prevalence or conditional risk of a particular disability, can be important as well, but contrasts involving these other measures may often be dismissed as non-causal. For example, an observed prevalence ratio might often viewed as an estimator of a causal incidence ratio and hence subject to bias. In this manuscript, we provide and evaluate a definition of causal effects that generalizes those previously available. A key part of the generalization is that contrasts used in the definition can involve multivariate, counterfactual outcomes, rather than only univariate outcomes. An important consequence of our generalization is that, using it, one can properly define causal effects based on a wide variety of additional measures. Examples include causal prevalence ratios and differences and causal conditional risk ratios and differences. We illustrate how these additional measures can be useful, natural, easily estimated, and of public health importance. Furthermore, we discuss conditions for valid estimation of each type of causal effect, and how improper interpretation or inferences for the wrong target population can be sources of bias.

Causal boundary for stably causal space-times

International Nuclear Information System (INIS)

Racz, I.

1987-12-01

The usual boundary constructions for space-times often yield an unsatisfactory boundary set. This problem is reviewed and a new solution is proposed. An explicit identification rule is given on the set of the ideal points of the space-time. This construction leads to a satisfactory boundary point set structure for stably causal space-times. The topological properties of the resulting causal boundary construction are examined. For the stably causal space-times each causal curve has a unique endpoint on the boundary set according to the extended Alexandrov topology. The extension of the space-time through the boundary is discussed. To describe the singularities the defined boundary sets have to be separated into two disjoint sets. (D.Gy.) 8 refs

Causal universe

CERN Document Server

Ellis, George FR; Pabjan, Tadeusz

2013-01-01

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

Causal relationship: a new tool for the causal characterization of Lorentzian manifolds

International Nuclear Information System (INIS)

Garcia-Parrado, Alfonso; Senovilla, Jose M M

2003-01-01

We define and study a new kind of relation between two diffeomorphic Lorentzian manifolds called a causal relation, which is any diffeomorphism characterized by mapping every causal vector of the first manifold onto a causal vector of the second. We perform a thorough study of the mathematical properties of causal relations and prove in particular that two given Lorentzian manifolds (say V and W) may be causally related only in one direction (say from V to W, but not from W to V). This leads us to the concept of causally equivalent (or isocausal in short) Lorentzian manifolds as those mutually causally related and to a definition of causal structure over a differentiable manifold as the equivalence class formed by isocausal Lorentzian metrics upon it. Isocausality is a more general concept than the conformal relationship, because we prove the remarkable result that a conformal relation φ is characterized by the fact of being a causal relation of the particular kind in which both φ and φ -1 are causal relations. Isocausal Lorentzian manifolds are mutually causally compatible, they share some important causal properties, and there are one-to-one correspondences, which are sometimes non-trivial, between several classes of their respective future (and past) objects. A more important feature is that they satisfy the same standard causality constraints. We also introduce a partial order for the equivalence classes of isocausal Lorentzian manifolds providing a classification of all the causal structures that a given fixed manifold can have. By introducing the concept of causal extension we put forward a new definition of causal boundary for Lorentzian manifolds based on the concept of isocausality, and thereby we generalize the traditional Penrose constructions of conformal infinity, diagrams and embeddings. In particular, the concept of causal diagram is given. Many explicit clarifying examples are presented throughout the paper

A Causal Model of Faculty Turnover Intentions.

Science.gov (United States)

Smart, John C.

1990-01-01

A causal model assesses the relative influence of individual attributes, institutional characteristics, contextual-work environment variables, and multiple measures of job satisfaction on faculty intentions to leave their current institutions. Factors considered include tenure status, age, institutional status, governance style, organizational…

A Bayesian Theory of Sequential Causal Learning and Abstract Transfer.

Science.gov (United States)

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

2016-03-01

Two key research issues in the field of causal learning are how people acquire causal knowledge when observing data that are presented sequentially, and the level of abstraction at which learning takes place. Does sequential causal learning solely involve the acquisition of specific cause-effect links, or do learners also acquire knowledge about abstract causal constraints? Recent empirical studies have revealed that experience with one set of causal cues can dramatically alter subsequent learning and performance with entirely different cues, suggesting that learning involves abstract transfer, and such transfer effects involve sequential presentation of distinct sets of causal cues. It has been demonstrated that pre-training (or even post-training) can modulate classic causal learning phenomena such as forward and backward blocking. To account for these effects, we propose a Bayesian theory of sequential causal learning. The theory assumes that humans are able to consider and use several alternative causal generative models, each instantiating a different causal integration rule. Model selection is used to decide which integration rule to use in a given learning environment in order to infer causal knowledge from sequential data. Detailed computer simulations demonstrate that humans rely on the abstract characteristics of outcome variables (e.g., binary vs. continuous) to select a causal integration rule, which in turn alters causal learning in a variety of blocking and overshadowing paradigms. When the nature of the outcome variable is ambiguous, humans select the model that yields the best fit with the recent environment, and then apply it to subsequent learning tasks. Based on sequential patterns of cue-outcome co-occurrence, the theory can account for a range of phenomena in sequential causal learning, including various blocking effects, primacy effects in some experimental conditions, and apparently abstract transfer of causal knowledge. Copyright © 2015

Dynamics and causalities of atmospheric and oceanic data identified by complex networks and Granger causality analysis

Science.gov (United States)

Charakopoulos, A. K.; Katsouli, G. A.; Karakasidis, T. E.

2018-04-01

Understanding the underlying processes and extracting detailed characteristics of spatiotemporal dynamics of ocean and atmosphere as well as their interaction is of significant interest and has not been well thoroughly established. The purpose of this study was to examine the performance of two main additional methodologies for the identification of spatiotemporal underlying dynamic characteristics and patterns among atmospheric and oceanic variables from Seawatch buoys from Aegean and Ionian Sea, provided by the Hellenic Center for Marine Research (HCMR). The first approach involves the estimation of cross correlation analysis in an attempt to investigate time-lagged relationships, and further in order to identify the direction of interactions between the variables we performed the Granger causality method. According to the second approach the time series are converted into complex networks and then the main topological network properties such as degree distribution, average path length, diameter, modularity and clustering coefficient are evaluated. Our results show that the proposed analysis of complex network analysis of time series can lead to the extraction of hidden spatiotemporal characteristics. Also our findings indicate high level of positive and negative correlations and causalities among variables, both from the same buoy and also between buoys from different stations, which cannot be determined from the use of simple statistical measures.

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

International Nuclear Information System (INIS)

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 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.

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.

Causality in Science

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.

A theory of causal learning in children: causal maps and Bayes nets.

Science.gov (United States)

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

2004-01-01

The authors outline a cognitive and computational account of causal learning in children. They propose that children use specialized cognitive systems that allow them to recover an accurate "causal map" of the world: an abstract, coherent, learned representation of the causal relations among events. This kind of knowledge can be perspicuously understood in terms of the formalism of directed graphical causal models, or Bayes nets. Children's causal learning and inference may involve computations similar to those for learning causal Bayes nets and for predicting with them. Experimental results suggest that 2- to 4-year-old children construct new causal maps and that their learning is consistent with the Bayes net formalism.

Causal reasoning and models of cognitive tasks for naval nuclear power plant operators; Raisonnement causal et modelisation de l`activite cognitive d`operateurs de chaufferie nucleaire navale

Energy Technology Data Exchange (ETDEWEB)

Salazar-Ferrer, P

1995-06-01

In complex industrial process control, causal reasoning appears as a major component in operators` cognitive tasks. It is tightly linked to diagnosis, prediction of normal and failure states, and explanation. This work provides a detailed review of literature in causal reasoning. A synthesis is proposed as a model of causal reasoning in process control. This model integrates distinct approaches in Cognitive Science: especially qualitative physics, Bayesian networks, knowledge-based systems, and cognitive psychology. Our model defines a framework for the analysis of causal human errors in simulated naval nuclear power plant fault management. Through the methodological framework of critical incident analysis we define a classification of errors and difficulties linked to causal reasoning. This classification is based on shallow characteristics of causal reasoning. As an origin of these errors, more elementary component activities in causal reasoning are identified. The applications cover the field of functional specification for man-machine interfaces, operators support systems design as well as nuclear safety. In addition of this study, we integrate the model of causal reasoning in a model of cognitive task in process control. (authors). 106 refs., 49 figs., 8 tabs.

Non-invasive clinical parameters for the prediction of urodynamic bladder outlet obstruction: analysis using causal Bayesian networks.

Directory of Open Access Journals (Sweden)

Myong Kim

Full Text Available To identify non-invasive clinical parameters to predict urodynamic bladder outlet obstruction (BOO in patients with benign prostatic hyperplasia (BPH using causal Bayesian networks (CBN.From October 2004 to August 2013, 1,381 eligible BPH patients with complete data were selected for analysis. The following clinical variables were considered: age, total prostate volume (TPV, transition zone volume (TZV, prostate specific antigen (PSA, maximum flow rate (Qmax, and post-void residual volume (PVR on uroflowmetry, and International Prostate Symptom Score (IPSS. Among these variables, the independent predictors of BOO were selected using the CBN model. The predictive performance of the CBN model using the selected variables was verified through a logistic regression (LR model with the same dataset.Mean age, TPV, and IPSS were 6.2 (±7.3, SD years, 48.5 (±25.9 ml, and 17.9 (±7.9, respectively. The mean BOO index was 35.1 (±25.2 and 477 patients (34.5% had urodynamic BOO (BOO index ≥40. By using the CBN model, we identified TPV, Qmax, and PVR as independent predictors of BOO. With these three variables, the BOO prediction accuracy was 73.5%. The LR model showed a similar accuracy (77.0%. However, the area under the receiver operating characteristic curve of the CBN model was statistically smaller than that of the LR model (0.772 vs. 0.798, p = 0.020.Our study demonstrated that TPV, Qmax, and PVR are independent predictors of urodynamic BOO.

Causal reasoning in physics

CERN Document Server

Frisch, Mathias

2014-01-01

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

A theory of causal learning in children: Causal maps and Bayes nets

OpenAIRE

Gopnik, A; Glymour, C; Sobel, D M; Schulz, L E; Kushnir, T; Danks, D

2004-01-01

The authors outline a cognitive and computational account of causal learning in children. They propose that children use specialized cognitive systems that allow them to recover an accurate "causal map" of the world: an abstract, coherent, learned representation of the causal relations among events. This kind of knowledge can be perspicuously understood in terms of the formalism of directed graphical causal models, or Bayes nets. Children's causal learning and inference may involve computatio...

How do practising clinicians and students apply newly learned causal information about mental disorders?

Science.gov (United States)

de Kwaadsteniet, Leontien; Kim, Nancy S; Yopchick, Jennelle E

2013-02-01

New causal theories explaining the aetiology of psychiatric disorders continuously appear in the literature. How might such new information directly impact clinical practice, to the degree that clinicians are aware of it and accept it? We investigated whether expert clinical psychologists and students use new causal information about psychiatric disorders according to rationalist norms in their diagnostic reasoning. Specifically, philosophical and Bayesian analyses suggest that it is rational to draw stronger inferences about the presence of a disorder when a client's presenting symptoms are from disparate locations in a causal theory of the disorder than when they are from proximal locations. In a controlled experiment, we presented experienced clinical psychologists and students with recently published causal theories for different disorders; specifically, these theories proposed how the symptoms of each disorder stem from a root cause. Participants viewed hypothetical clients with presenting proximal or diverse symptoms, and indicated either the likelihood that the client has the disorder, or what additional information they would seek out to help inform a diagnostic decision. Clinicians and students alike showed a strong preference for diverse evidence, over proximal evidence, in making diagnostic judgments and in seeking additional information. They did not show this preference in the control condition, in which they gave their own opinions prior to learning the causal information. These findings suggest that experienced clinical psychologists and students are likely to use newly learned causal knowledge in a normative, rational way in diagnostic reasoning. © 2011 Blackwell Publishing Ltd.

Clinical characteristics and management of children with ...

African Journals Online (AJOL)

reflux (VUR), including the clinical characteristics and management. Summary background data The association ... different clinical characteristics compared with the other two groups of patients with high-grade VUR. .... way ANOVA test; while qualitative data were analyzed using Chi square. The difference was considered.

[Clinical characteristics of short tear film breakup time (BUT) -type dry eye].

Science.gov (United States)

Yamamoto, Yuji; Yokoi, Norihiko; Higashihara, Hisayo; Inagaki, Kayoko; Sonomura, Yukiko; Komuro, Aoi; Kinoshita, Shigeru

2012-12-01

To evaluate the clinical characteristics and management of short tear film breakup time (BUT) -type dry eye. Clinical background and post-treatment changes of symptoms in 77 patients with short BUT -type dry eye were investigated. Treatment consisted of artificial-tear eye-drop instillation and, if necessary, the addition of a low-density-level steroid, hyaluronic acid, a low-density-level cyclopentolate prepared by ourselves and punctal plugs inserted into the upper and lower lacrimal puncta. There were three times more women than men among the patients, and the peak age of occurrence was in the twenties in the men and in the sixties in the women. Our findings show that visual display terminal (VDT) work, contact lens (CL) wear, and changes in the sex hormones may initiate subjective symptoms. Some patients had simultaneous conjunctivochalasis, allergic conjunctivitis, and meibomian gland dysfunction. Nineteen patients (24.7%) were effectively treated with eye-drop instillation alone. Thirty-seven patients (48.1%) required punctal-plug insertion, which was completely effective in only 8 of them (21.6%). Mainly young men and menopausal women contract short BUT -type dry eye. Changes in sex hormones, VDT work and CL wear may be causal, and the disease cannot be controlled by eyedrop and punctal-plug treatment alone.

Repeated causal decision making.

Science.gov (United States)

Hagmayer, York; Meder, Björn

2013-01-01

Many of our decisions refer to actions that have a causal impact on the external environment. Such actions may not only allow for the mere learning of expected values or utilities but also for acquiring knowledge about the causal structure of our world. We used a repeated decision-making paradigm to examine what kind of knowledge people acquire in such situations and how they use their knowledge to adapt to changes in the decision context. Our studies show that decision makers' behavior is strongly contingent on their causal beliefs and that people exploit their causal knowledge to assess the consequences of changes in the decision problem. A high consistency between hypotheses about causal structure, causally expected values, and actual choices was observed. The experiments show that (a) existing causal hypotheses guide the interpretation of decision feedback, (b) consequences of decisions are used to revise existing causal beliefs, and (c) decision makers use the experienced feedback to induce a causal model of the choice situation even when they have no initial causal hypotheses, which (d) enables them to adapt their choices to changes of the decision problem. (PsycINFO Database Record (c) 2013 APA, all rights reserved).

Mapping causal functional contributions derived from the clinical assessment of brain damage after stroke

Directory of Open Access Journals (Sweden)

Melissa Zavaglia

2015-01-01

Full Text Available Lesion analysis reveals causal contributions of brain regions to mental functions, aiding the understanding of normal brain function as well as rehabilitation of brain-damaged patients. We applied a novel lesion inference technique based on game theory, Multi-perturbation Shapley value Analysis (MSA, to a large clinical lesion dataset. We used MSA to analyze the lesion patterns of 148 acute stroke patients together with their neurological deficits, as assessed by the National Institutes of Health Stroke Scale (NIHSS. The results revealed regional functional contributions to essential behavioral and cognitive functions as reflected in the NIHSS, particularly by subcortical structures. There were also side specific differences of functional contributions between the right and left hemispheric brain regions which may reflect the dominance of the left hemispheric syndrome aphasia in the NIHSS. Comparison of MSA to established lesion inference methods demonstrated the feasibility of the approach for analyzing clinical data and indicated its capability for objectively inferring functional contributions from multiple injured, potentially interacting sites, at the cost of having to predict the outcome of unknown lesion configurations. The analysis of regional functional contributions to neurological symptoms measured by the NIHSS contributes to the interpretation of this widely used standardized stroke scale in clinical practice as well as clinical trials and provides a first approximation of a ‘map of stroke’.

Mapping causal functional contributions derived from the clinical assessment of brain damage after stroke.

Science.gov (United States)

Zavaglia, Melissa; Forkert, Nils D; Cheng, Bastian; Gerloff, Christian; Thomalla, Götz; Hilgetag, Claus C

2015-01-01

Lesion analysis reveals causal contributions of brain regions to mental functions, aiding the understanding of normal brain function as well as rehabilitation of brain-damaged patients. We applied a novel lesion inference technique based on game theory, Multi-perturbation Shapley value Analysis (MSA), to a large clinical lesion dataset. We used MSA to analyze the lesion patterns of 148 acute stroke patients together with their neurological deficits, as assessed by the National Institutes of Health Stroke Scale (NIHSS). The results revealed regional functional contributions to essential behavioral and cognitive functions as reflected in the NIHSS, particularly by subcortical structures. There were also side specific differences of functional contributions between the right and left hemispheric brain regions which may reflect the dominance of the left hemispheric syndrome aphasia in the NIHSS. Comparison of MSA to established lesion inference methods demonstrated the feasibility of the approach for analyzing clinical data and indicated its capability for objectively inferring functional contributions from multiple injured, potentially interacting sites, at the cost of having to predict the outcome of unknown lesion configurations. The analysis of regional functional contributions to neurological symptoms measured by the NIHSS contributes to the interpretation of this widely used standardized stroke scale in clinical practice as well as clinical trials and provides a first approximation of a 'map of stroke'.

Mapping causal functional contributions derived from the clinical assessment of brain damage after stroke

Science.gov (United States)

Zavaglia, Melissa; Forkert, Nils D.; Cheng, Bastian; Gerloff, Christian; Thomalla, Götz; Hilgetag, Claus C.

2015-01-01

Lesion analysis reveals causal contributions of brain regions to mental functions, aiding the understanding of normal brain function as well as rehabilitation of brain-damaged patients. We applied a novel lesion inference technique based on game theory, Multi-perturbation Shapley value Analysis (MSA), to a large clinical lesion dataset. We used MSA to analyze the lesion patterns of 148 acute stroke patients together with their neurological deficits, as assessed by the National Institutes of Health Stroke Scale (NIHSS). The results revealed regional functional contributions to essential behavioral and cognitive functions as reflected in the NIHSS, particularly by subcortical structures. There were also side specific differences of functional contributions between the right and left hemispheric brain regions which may reflect the dominance of the left hemispheric syndrome aphasia in the NIHSS. Comparison of MSA to established lesion inference methods demonstrated the feasibility of the approach for analyzing clinical data and indicated its capability for objectively inferring functional contributions from multiple injured, potentially interacting sites, at the cost of having to predict the outcome of unknown lesion configurations. The analysis of regional functional contributions to neurological symptoms measured by the NIHSS contributes to the interpretation of this widely used standardized stroke scale in clinical practice as well as clinical trials and provides a first approximation of a ‘map of stroke’. PMID:26448908

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

CERN Document Server

Neelamkavil, Raphael

2014-01-01

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

Statistical causal inferences and their applications in public health research

CERN Document Server

Wu, Pan; Chen, Ding-Geng

2016-01-01

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

Causal Analysis for Performance Modeling of Computer Programs

Directory of Open Access Journals (Sweden)

Jan Lemeire

2007-01-01

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

Non-Causal Computation

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.

Causality re-established.

Science.gov (United States)

D'Ariano, Giacomo Mauro

2018-07-13

Causality has never gained the status of a 'law' or 'principle' in physics. Some recent literature has even popularized the false idea that causality is a notion that should be banned from theory. Such misconception relies on an alleged universality of the reversibility of the laws of physics, based either on the determinism of classical theory, or on the multiverse interpretation of quantum theory, in both cases motivated by mere interpretational requirements for realism of the theory. Here, I will show that a properly defined unambiguous notion of causality is a theorem of quantum theory, which is also a falsifiable proposition of the theory. Such a notion of causality appeared in the literature within the framework of operational probabilistic theories. It is a genuinely theoretical notion, corresponding to establishing a definite partial order among events, in the same way as we do by using the future causal cone on Minkowski space. The notion of causality is logically completely independent of the misidentified concept of 'determinism', and, being a consequence of quantum theory, is ubiquitous in physics. In addition, as classical theory can be regarded as a restriction of quantum theory, causality holds also in the classical case, although the determinism of the theory trivializes it. I then conclude by arguing that causality naturally establishes an arrow of time. This implies that the scenario of the 'block Universe' and the connected 'past hypothesis' are incompatible with causality, and thus with quantum theory: they are both doomed to remain mere interpretations and, as such, are not falsifiable, similar to the hypothesis of 'super-determinism'.This article is part of a discussion meeting issue 'Foundations of quantum mechanics and their impact on contemporary society'. © 2018 The Author(s).

Further properties of causal relationship: causal structure stability, new criteria for isocausality and counterexamples

International Nuclear Information System (INIS)

Garcia-Parrado, Alfonso; Sanchez, Miguel

2005-01-01

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 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

Characteristics of student preparedness for clinical learning: clinical educator perspectives using the Delphi approach

Directory of Open Access Journals (Sweden)

Chipchase Lucinda S

2012-11-01

Full Text Available Abstract Background During clinical placements, clinical educators facilitate student learning. Previous research has defined the skills, attitudes and practices that pertain to an ideal clinical educator. However, less attention has been paid to the role of student readiness in terms of foundational knowledge and attitudes at the commencement of practice education. Therefore, the aim of this study was to ascertain clinical educators’ views on the characteristics that they perceive demonstrate that a student is well prepared for clinical learning. Methods A two round on-line Delphi study was conducted. The first questionnaire was emailed to a total of 636 expert clinical educators from the disciplines of occupational therapy, physiotherapy and speech pathology. Expert clinical educators were asked to describe the key characteristics that indicate a student is prepared for a clinical placement and ready to learn. Open-ended responses received from the first round were subject to a thematic analysis and resulted in six themes with 62 characteristics. In the second round, participants were asked to rate each characteristic on a 7 point Likert Scale. Results A total of 258 (40.56% responded to the first round of the Delphi survey while 161 clinical educators completed the second (62.40% retention rate. Consensus was reached on 57 characteristics (six themes using a cut off of greater than 70% positive respondents and an interquartile deviation IQD of equal or less than 1. Conclusions This study identified 57 characteristics (six themes perceived by clinical educators as indicators of a student who is prepared and ready for clinical learning. A list of characteristics relating to behaviours has been compiled and could be provided to students to aid their preparation for clinical learning and to universities to incorporate within curricula. In addition, the list provides a platform for discussions by professional bodies about the role of placement

The fuzzy cube and causal efficacy: representation of concomitant mechanisms in stroke.

Science.gov (United States)

Jobe, Thomas H.; Helgason, Cathy M.

1998-04-01

Twentieth century medical science has embraced nineteenth century Boolean probability theory based upon two-valued Aristotelian logic. With the later addition of bit-based, von Neumann structured computational architectures, an epistemology based on randomness has led to a bivalent epidemiological methodology that dominates medical decision making. In contrast, fuzzy logic, based on twentieth century multi-valued logic, and computational structures that are content addressed and adaptively modified, has advanced a new scientific paradigm for the twenty-first century. Diseases such as stroke involve multiple concomitant causal factors that are difficult to represent using conventional statistical methods. We tested which paradigm best represented this complex multi-causal clinical phenomenon-stroke. We show that the fuzzy logic paradigm better represented clinical complexity in cerebrovascular disease than current probability theory based methodology. We believe this finding is generalizable to all of clinical science since multiple concomitant causal factors are involved in nearly all known pathological processes.

A quantum causal discovery algorithm

Science.gov (United States)

Giarmatzi, Christina; Costa, Fabio

2018-03-01

Finding a causal model for a set of classical variables is now a well-established task—but what about the quantum equivalent? Even the notion of a quantum causal model is controversial. Here, we present a causal discovery algorithm for quantum systems. The input to the algorithm is a process matrix describing correlations between quantum events. Its output consists of different levels of information about the underlying causal model. Our algorithm determines whether the process is causally ordered by grouping the events into causally ordered non-signaling sets. It detects if all relevant common causes are included in the process, which we label Markovian, or alternatively if some causal relations are mediated through some external memory. For a Markovian process, it outputs a causal model, namely the causal relations and the corresponding mechanisms, represented as quantum states and channels. Our algorithm opens the route to more general quantum causal discovery methods.

Epidemiological causality.

Science.gov (United States)

Morabia, Alfredo

2005-01-01

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

Obesity and infection: reciprocal causality.

Science.gov (United States)

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

2015-01-01

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

Discrete causal theory emergent spacetime and the causal metric hypothesis

CERN Document Server

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.

Causal Analysis After Haavelmo

Science.gov (United States)

Heckman, James; Pinto, Rodrigo

2014-01-01

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

Causal reasoning and models of cognitive tasks for naval nuclear power plant operators

International Nuclear Information System (INIS)

Salazar-Ferrer, P.

1995-06-01

In complex industrial process control, causal reasoning appears as a major component in operators' cognitive tasks. It is tightly linked to diagnosis, prediction of normal and failure states, and explanation. This work provides a detailed review of literature in causal reasoning. A synthesis is proposed as a model of causal reasoning in process control. This model integrates distinct approaches in Cognitive Science: especially qualitative physics, Bayesian networks, knowledge-based systems, and cognitive psychology. Our model defines a framework for the analysis of causal human errors in simulated naval nuclear power plant fault management. Through the methodological framework of critical incident analysis we define a classification of errors and difficulties linked to causal reasoning. This classification is based on shallow characteristics of causal reasoning. As an origin of these errors, more elementary component activities in causal reasoning are identified. The applications cover the field of functional specification for man-machine interfaces, operators support systems design as well as nuclear safety. In addition of this study, we integrate the model of causal reasoning in a model of cognitive task in process control. (authors). 106 refs., 49 figs., 8 tabs

Intelligent diagnosis of jaundice with dynamic uncertain causality graph model*

Science.gov (United States)

Hao, Shao-rui; Geng, Shi-chao; Fan, Lin-xiao; Chen, Jia-jia; Zhang, Qin; Li, Lan-juan

2017-01-01

Jaundice is a common and complex clinical symptom potentially occurring in hepatology, general surgery, pediatrics, infectious diseases, gynecology, and obstetrics, and it is fairly difficult to distinguish the cause of jaundice in clinical practice, especially for general practitioners in less developed regions. With collaboration between physicians and artificial intelligence engineers, a comprehensive knowledge base relevant to jaundice was created based on demographic information, symptoms, physical signs, laboratory tests, imaging diagnosis, medical histories, and risk factors. Then a diagnostic modeling and reasoning system using the dynamic uncertain causality graph was proposed. A modularized modeling scheme was presented to reduce the complexity of model construction, providing multiple perspectives and arbitrary granularity for disease causality representations. A “chaining” inference algorithm and weighted logic operation mechanism were employed to guarantee the exactness and efficiency of diagnostic reasoning under situations of incomplete and uncertain information. Moreover, the causal interactions among diseases and symptoms intuitively demonstrated the reasoning process in a graphical manner. Verification was performed using 203 randomly pooled clinical cases, and the accuracy was 99.01% and 84.73%, respectively, with or without laboratory tests in the model. The solutions were more explicable and convincing than common methods such as Bayesian Networks, further increasing the objectivity of clinical decision-making. The promising results indicated that our model could be potentially used in intelligent diagnosis and help decrease public health expenditure. PMID:28471111

Intelligent diagnosis of jaundice with dynamic uncertain causality graph model.

Science.gov (United States)

Hao, Shao-Rui; Geng, Shi-Chao; Fan, Lin-Xiao; Chen, Jia-Jia; Zhang, Qin; Li, Lan-Juan

2017-05-01

Jaundice is a common and complex clinical symptom potentially occurring in hepatology, general surgery, pediatrics, infectious diseases, gynecology, and obstetrics, and it is fairly difficult to distinguish the cause of jaundice in clinical practice, especially for general practitioners in less developed regions. With collaboration between physicians and artificial intelligence engineers, a comprehensive knowledge base relevant to jaundice was created based on demographic information, symptoms, physical signs, laboratory tests, imaging diagnosis, medical histories, and risk factors. Then a diagnostic modeling and reasoning system using the dynamic uncertain causality graph was proposed. A modularized modeling scheme was presented to reduce the complexity of model construction, providing multiple perspectives and arbitrary granularity for disease causality representations. A "chaining" inference algorithm and weighted logic operation mechanism were employed to guarantee the exactness and efficiency of diagnostic reasoning under situations of incomplete and uncertain information. Moreover, the causal interactions among diseases and symptoms intuitively demonstrated the reasoning process in a graphical manner. Verification was performed using 203 randomly pooled clinical cases, and the accuracy was 99.01% and 84.73%, respectively, with or without laboratory tests in the model. The solutions were more explicable and convincing than common methods such as Bayesian Networks, further increasing the objectivity of clinical decision-making. The promising results indicated that our model could be potentially used in intelligent diagnosis and help decrease public health expenditure.

Causality and hyperbolicity of Lovelock theories

International Nuclear Information System (INIS)

Reall, Harvey S; Tanahashi, Norihiro; Way, Benson

2014-01-01

In Lovelock theories, gravity can travel faster or slower than light. The causal structure is determined by the characteristic hypersurfaces. We generalize a recent result of Izumi to prove that any Killing horizon is a characteristic hypersurface for all gravitational degrees of freedom of a Lovelock theory. Hence gravitational signals cannot escape from the region inside such a horizon. We investigate the hyperbolicity of Lovelock theories by determining the characteristic hypersurfaces for various backgrounds. First we consider Ricci flat type N spacetimes. We show that characteristic hypersurfaces are generically all non-null and that Lovelock theories are hyperbolic in any such spacetime. Next we consider static, maximally symmetric black hole solutions of Lovelock theories. Again, characteristic surfaces are generically non-null. For some small black holes, hyperbolicity is violated near the horizon. This implies that the stability of such black holes is not a well-posed problem. (paper)

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

Science.gov (United States)

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

2004-01-01

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

The Netherlands XTC Toxicity (NeXT) study: objectives and methods of a study investigating causality, course, and clinical relevance.

Science.gov (United States)

De Win, Maartje M L; Jager, Gerry; Vervaeke, Hylke K E; Schilt, Thelma; Reneman, Liesbeth; Booij, Jan; Verhulst, Frank C; Den Heeten, Gerard J; Ramsey, Nick F; Korf, Dirk J; Van den Brink, Wim

2005-01-01

This paper describes the objectives and methods of The Netherlands XTC Toxicity (NeXT) study focussing on the causality, course, and clinical relevance of ecstasy neurotoxicity. Previous studies suggest that ecstasy (3,4 methylene-dioxymethamphetamine, MDMA, XTC) is toxic toward brain serotonin axons, but most of these studies have serious methodological limitations. The current study is a combination of different approaches with three substudies: (1) a crosssectional substudy among heavy ecstasy users and controls with variation in drug use, which will provide information about potential neurotoxic consequences of ecstasy in relation to other drugs; (2) a prospective cohort substudy in ecstasy-naive subjects with high risk for future ecstasy use, which will provide information on the causality and short-term course of ecstasy use and potential neurotoxicity, and (3) a retrospective cohort substudy in lifetime ecstasy users and matched controls of an existing epidemiological sample that will provide information on long-term course and outcome of ecstasy use in the general population. Neurotoxicity is studied using (a) different imaging techniques (beta-CIT SPECT, 1H-MR spectroscopy, diffusion tensor imaging, perfusion weighted imaging and functional magnetic resonance imaging), and (b) neuropsychological and psychiatric assessments of memory, depression, and personality. The combined results will lead to conclusions that can be used in prevention messages, clinical decision making, and the development of an (inter)national ecstasy policy.

Basic clinical characteristics and hospital outcomes of acute ...

African Journals Online (AJOL)

Basic clinical characteristics and hospital outcomes of acute coronary syndrome patients - Sudan. A.M. Taha, H.O. Mirghani. Abstract. Background: There are Variation in the presentation of the acute coronary syndrome between countries. The present study aimed to investigate the basic clinical characteristics and ...

Intracranial Infections: Clinical and Imaging Characteristics

Energy Technology Data Exchange (ETDEWEB)

Foerster, B.R.; Thurnher, M.M.; Malani, P.N.; Petrou, M.; Carets-Zumelzu, F.; Sundgren, P.C. [Dept. of Radiology, and Divisions of Infectious Diseases and G eriatric Medicine, Dept. of Internal Medicine, Univ. of Michigan Medical Center, Ann Arbor, MI (United States)

2007-10-15

The radiologist plays a crucial role in identifying and narrowing the differential diagnosis of intracranial infections. A thorough understanding of the intracranial compartment anatomy and characteristic imaging findings of specific pathogens, as well incorporation of the clinical information, is essential to establish correct diagnosis. Specific types of infections have certain propensities for different anatomical regions within the brain. In addition, the imaging findings must be placed in the context of the clinical setting, particularly in immunocompromised and human immunodeficiency virus (HIV)-positive patients. This paper describes and depicts infections within the different compartments of the brain. Pathology-proven infectious cases are presented in both immunocompetent and immunocompromised patients, with a discussion of the characteristic findings of each pathogen. Magnetic resonance spectroscopy (MRS) characteristics for several infections are also discussed.

SYSTEMATIC\tUSE\tOF CAUSALITY ASSESSMENT IN AEFI SURVEILLANCE: A 2013-2016 PILOT STUDY IN PUGLIA

Directory of Open Access Journals (Sweden)

Pasquale Stefanizzi

2017-10-01

Full Text Available Causality assessment is an algorithm proposed by WHO to identify a causal relationship between vaccines and adverse events following immunization (AEFIs, mostly for serious adverse events. It can be considered consistent, inconsistent, indeterminate or unclassifiable. This study describes AEFIs reported in Puglia from 2013 to 2016 and analyzes the differences between the causality assessments performed on AEFI case-report information and the causality assessments performed after the examination of clinical documentation. 292 AEFI were reported: 191 (65.4% non serious, 59 (20.2% serious and 42 (14.4% undefined. Causality assessment performed on the AEFI case-report information classified 59.2% (n=29/49 of serious AEFIs as consistent while assessment performed after clinical review only classified 30.6% (n=15/49 of serious AEFI as consistent (X2=65.0; p=0,000. In the first approach, inconsistent serious AEFIs were 18.6% (n=11/49 and then became 45.8% (n=27/49 after examination of clinical documentation. Indeterminate serious AEFIs were 6.8% (n=4 at first, and then 3.4% (n=2. Unclassifiables did not change.

Testing causality in the association between regular exercise and symptoms of anxiety and depression.

NARCIS (Netherlands)

de Moor, M.H.M.; Boomsma, D.I.; Stubbe, J.H.; Willemsen, G.; de Geus, E.J.C.

2008-01-01

Context: In the population at large, regular exercise is associated with reduced anxious and depressive symptoms. Results of experimental studies in clinical populations suggest a causal effect of exercise on anxiety and depression, but it is unclear whether such a causal effect also drives the

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.

Causality and complexity: the myth of objectivity in science.

Science.gov (United States)

Mikulecky, Donald C

2007-10-01

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

Agency, time and causality

Directory of Open Access Journals (Sweden)

Thomas eWidlok

2014-11-01

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

Causal boundary for strongly causal spacetimes: Pt. 1

International Nuclear Information System (INIS)

Szabados, L.B.

1989-01-01

In a previous paper an analysis of the general structure of the causal boundary constructions and a new explicit identification rule, built up from elementary TIP-TIF gluings, were presented. In the present paper we complete our identification by incorporating TIP-TIP and TIF-TIF gluings as well. An asymptotic causality condition is found which, for physically important cases, ensures the uniqueness of the endpoints of the non-spacelike curves in the completed spacetime. (author)

Structural Equations and Causal Explanations: Some Challenges for Causal SEM

Science.gov (United States)

Markus, Keith A.

2010-01-01

One common application of structural equation modeling (SEM) involves expressing and empirically investigating causal explanations. Nonetheless, several aspects of causal explanation that have an impact on behavioral science methodology remain poorly understood. It remains unclear whether applications of SEM should attempt to provide complete…

Financial networks based on Granger causality: A case study

Science.gov (United States)

Papana, Angeliki; Kyrtsou, Catherine; Kugiumtzis, Dimitris; Diks, Cees

2017-09-01

Connectivity analysis is performed on a long financial record of 21 international stock indices employing a linear and a nonlinear causality measure, the conditional Granger causality index (CGCI) and the partial mutual information on mixed embedding (PMIME), respectively. Both measures aim to specify the direction of the interrelationships among the international stock indexes and portray the links of the resulting networks, by the presence of direct couplings between variables exploiting all available information. However, their differences are assessed due to the presence of nonlinearity. The weighted networks formed with respect to the causality measures are transformed to binary ones using a significance test. The financial networks are formed on sliding windows in order to examine the network characteristics and trace changes in the connectivity structure. Subsequently, two statistical network quantities are calculated; the average degree and the average shortest path length. The empirical findings reveal interesting time-varying properties of the constructed network, which are clearly dependent on the nature of the financial cycle.

Causality discovery technology

Science.gov (United States)

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.

Regge behavior saves string theory from causality violations

DEFF Research Database (Denmark)

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

2015-01-01

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

Reasoning with Causal Cycles

Science.gov (United States)

Rehder, Bob

2017-01-01

This article assesses how people reason with categories whose features are related in causal cycles. Whereas models based on causal graphical models (CGMs) have enjoyed success modeling category-based judgments as well as a number of other cognitive phenomena, CGMs are only able to represent causal structures that are acyclic. A number of new…

Structure and Strength in Causal Induction

Science.gov (United States)

Griffiths, Thomas L.; Tenenbaum, Joshua B.

2005-01-01

We present a framework for the rational analysis of elemental causal induction--learning about the existence of a relationship between a single cause and effect--based upon causal graphical models. This framework makes precise the distinction between causal structure and causal strength: the difference between asking whether a causal relationship…

Regression to Causality : Regression-style presentation influences causal attribution

DEFF Research Database (Denmark)

Bordacconi, Mats Joe; Larsen, Martin Vinæs

2014-01-01

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...... 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...... more likely. Our experiment drew on a sample of 235 university students from three different social science degree programs (political science, sociology and economics), all of whom had received substantial training in statistics. The subjects were asked to compare and evaluate the validity...

A framework for estimating causal effects in latent class analysis: is there a causal link between early sex and subsequent profiles of delinquency?

Science.gov (United States)

Butera, Nicole M; Lanza, Stephanie T; Coffman, Donna L

2014-06-01

Prevention scientists use latent class analysis (LCA) with increasing frequency to characterize complex behavior patterns and profiles of risk. Often, the most important research questions in these studies involve establishing characteristics that predict membership in the latent classes, thus describing the composition of the subgroups and suggesting possible points of intervention. More recently, prevention scientists have begun to adopt modern methods for drawing causal inference from observational data because of the bias that can be introduced by confounders. This same issue of confounding exists in any analysis of observational data, including prediction of latent class membership. This study demonstrates a straightforward approach to causal inference in LCA that builds on propensity score methods. We demonstrate this approach by examining the causal effect of early sex on subsequent delinquency latent classes using data from 1,890 adolescents in 11th and 12th grade from wave I of the National Longitudinal Study of Adolescent Health. Prior to the statistical adjustment for potential confounders, early sex was significantly associated with delinquency latent class membership for both genders (p = 0.02). However, the propensity score adjusted analysis indicated no evidence for a causal effect of early sex on delinquency class membership (p = 0.76) for either gender. Sample R and SAS code is included in an Appendix in the ESM so that prevention scientists may adopt this approach to causal inference in LCA in their own work.

Causality in Europeanization Research

DEFF Research Database (Denmark)

Lynggaard, Kennet

2012-01-01

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......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......, 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...

Causal attributions in Brazilian children's reasoning about health and illness

Directory of Open Access Journals (Sweden)

Boruchovitch Evely

2000-01-01

Full Text Available INTRODUCTION: At a time when a great number of diseases can be prevented by changing one's habits and life style, investigations have focused on understanding what adults and children believe to be desirable health practices and uncovering the factors associated with successful adherence to such practices. For these, causal attributions for health and illness were investigated among 96 Brazilian elementary school students. METHODS: Ninety six subjects, aged 6 to 14, were interviewed individually and their causal attributions were assessed through 14 true-false items (e.g. people stay well [healthy] because they are lucky. The relationship between the children's causal attributions and demographic characteristics were also examined. RESULTS: Overall, the results were consistent with previous researches. "Taking care of oneself" was considered the most important cause of good health. "Viruses and germs" and "lack of self-care" were the most selected causes of illness. Analyses revealed significant relationship between subjects' causal attribution and their age, school grade level, socioeconomic status and gender. CONCLUSIONS: The study findings suggest that there may be more cross-cultural similarities than differences in children's causal attributions for health and illness. Finding ways to help individuals engage in appropriate preventive-maintenance health practices without developing an exaggerated notion that the individuals can control their own health and illness is a challenge which remains to be addressed by further research.

Viscous causal cosmologies

International Nuclear Information System (INIS)

Novello, M.; Salim, J.M.; Torres, J.; Oliveira, H.P. de

1989-01-01

A set of spatially homogeneous and isotropic cosmological geometries generated by a class of non-perfect is investigated fluids. The irreversibility if this system is studied in the context of causal thermodynamics which provides a useful mechanism to conform to the non-violation of the causal principle. (author) [pt

Dynamics of Quantum Causal Structures

Science.gov (United States)

Castro-Ruiz, Esteban; Giacomini, Flaminia; Brukner, Časlav

2018-01-01

It was recently suggested that causal structures are both dynamical, because of general relativity, and indefinite, because of quantum theory. The process matrix formalism furnishes a framework for quantum mechanics on indefinite causal structures, where the order between operations of local laboratories is not definite (e.g., one cannot say whether operation in laboratory A occurs before or after operation in laboratory B ). Here, we develop a framework for "dynamics of causal structures," i.e., for transformations of process matrices into process matrices. We show that, under continuous and reversible transformations, the causal order between operations is always preserved. However, the causal order between a subset of operations can be changed under continuous yet nonreversible transformations. An explicit example is that of the quantum switch, where a party in the past affects the causal order of operations of future parties, leading to a transition from a channel from A to B , via superposition of causal orders, to a channel from B to A . We generalize our framework to construct a hierarchy of quantum maps based on transformations of process matrices and transformations thereof.

Causal inference based on counterfactuals

Directory of Open Access Journals (Sweden)

Höfler M

2005-09-01

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

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...

Entropy for theories with indefinite causal structure

International Nuclear Information System (INIS)

Markes, Sonia; Hardy, Lucien

2011-01-01

Any theory with definite causal structure has a defined past and future, be it defined by light cones or an absolute time scale. Entropy is a concept that has traditionally been reliant on a definite notion of causality. However, without a definite notion of causality, the concept of entropy is not all lost. Indefinite causal structure results from combining probabilistic predictions and dynamical space-time. The causaloid framework lays the mathematical groundwork to be able to treat indefinite causal structure. In this paper, we build on the causaloid mathematics and define a causally-unbiased entropy for an indefinite causal structure. In defining a causally-unbiased entropy, there comes about an emergent idea of causality in the form of a measure of causal connectedness, termed the Q factor.

Does Subjective Left-Right Position Have a Causal Effect on Support for Redistribution?

DEFF Research Database (Denmark)

Jæger, Mads Meier

characteristics as instruments for left-right position, can be used to estimate the causal effect of left-right position on support for redistribution. I analyze data on Sweden, Germany, and Norway from the two first waves of the European Social Survey and find first that left-right position is endogenous...... to support for redistribution, and second consistent with theory, that a causal effect of left-right position on support for redistribution exists which is stronger than previously shown....

Dynamics of Quantum Causal Structures

Directory of Open Access Journals (Sweden)

Esteban Castro-Ruiz

2018-03-01

Full Text Available It was recently suggested that causal structures are both dynamical, because of general relativity, and indefinite, because of quantum theory. The process matrix formalism furnishes a framework for quantum mechanics on indefinite causal structures, where the order between operations of local laboratories is not definite (e.g., one cannot say whether operation in laboratory A occurs before or after operation in laboratory B. Here, we develop a framework for “dynamics of causal structures,” i.e., for transformations of process matrices into process matrices. We show that, under continuous and reversible transformations, the causal order between operations is always preserved. However, the causal order between a subset of operations can be changed under continuous yet nonreversible transformations. An explicit example is that of the quantum switch, where a party in the past affects the causal order of operations of future parties, leading to a transition from a channel from A to B, via superposition of causal orders, to a channel from B to A. We generalize our framework to construct a hierarchy of quantum maps based on transformations of process matrices and transformations thereof.

Causal inference in public health.

Science.gov (United States)

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.

Putting a cap on causality violations in causal dynamical triangulations

International Nuclear Information System (INIS)

Ambjoern, Jan; Loll, Renate; Westra, Willem; Zohren, Stefan

2007-01-01

The formalism of causal dynamical triangulations (CDT) provides us with a non-perturbatively defined model of quantum gravity, where the sum over histories includes only causal space-time histories. Path integrals of CDT and their continuum limits have been studied in two, three and four dimensions. Here we investigate a generalization of the two-dimensional CDT model, where the causality constraint is partially lifted by introducing branching points with a weight g s , and demonstrate that the system can be solved analytically in the genus-zero sector. The solution is analytic in a neighborhood around weight g s = 0 and cannot be analytically continued to g s = ∞, where the branching is entirely geometric and where one would formally recover standard Euclidean two-dimensional quantum gravity defined via dynamical triangulations or Liouville theory

Causality Statistical Perspectives and Applications

CERN Document Server

Berzuini, Carlo; Bernardinell, Luisa

2012-01-01

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

A frequency domain subspace algorithm for mixed causal, anti-causal LTI systems

NARCIS (Netherlands)

Fraanje, Rufus; Verhaegen, Michel; Verdult, Vincent; Pintelon, Rik

2003-01-01

The paper extends the subspacc identification method to estimate state-space models from frequency response function (FRF) samples, proposed by McKelvey et al. (1996) for mixed causal/anti-causal systems, and shows that other frequency domain subspace algorithms can be extended similarly. The method

Albinism: classification, clinical characteristics, and recent findings.

Science.gov (United States)

Summers, C Gail

2009-06-01

To describe the clinical characteristics and recent findings in the heterogeneous group of inherited disorders of melanin biosynthesis grouped as "albinism." The current classification of albinism, and the cutaneous, ocular, and central nervous system characteristics are presented. Recent clinical findings are summarized. Albinism is now classified based on genes known to be responsible for albinism. Foveal hypoplasia is invariably present and individuals with albinism often have delayed visual development, reduced vision, nystagmus, a positive angle kappa, strabismus, iris transillumination, and absent or reduced melanin pigment in the fundi. A visual-evoked potential can document the excessive retinostriate decussation seen in albinism. Grating acuity can be used to document delayed visual development in preverbal children. Glasses are often needed to improve visual acuity and binocular alignment. Albinism is caused by several different genes. Heterogeneity in clinical phenotype indicates that expressivity is variable.

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.

Causal inference in nonlinear systems: Granger causality versus time-delayed mutual information

Science.gov (United States)

Li, Songting; Xiao, Yanyang; Zhou, Douglas; Cai, David

2018-05-01

The Granger causality (GC) analysis has been extensively applied to infer causal interactions in dynamical systems arising from economy and finance, physics, bioinformatics, neuroscience, social science, and many other fields. In the presence of potential nonlinearity in these systems, the validity of the GC analysis in general is questionable. To illustrate this, here we first construct minimal nonlinear systems and show that the GC analysis fails to infer causal relations in these systems—it gives rise to all types of incorrect causal directions. In contrast, we show that the time-delayed mutual information (TDMI) analysis is able to successfully identify the direction of interactions underlying these nonlinear systems. We then apply both methods to neuroscience data collected from experiments and demonstrate that the TDMI analysis but not the GC analysis can identify the direction of interactions among neuronal signals. Our work exemplifies inference hazards in the GC analysis in nonlinear systems and suggests that the TDMI analysis can be an appropriate tool in such a case.

Paradoxical Behavior of Granger Causality

Science.gov (United States)

Witt, Annette; Battaglia, Demian; Gail, Alexander

2013-03-01

Granger causality is a standard tool for the description of directed interaction of network components and is popular in many scientific fields including econometrics, neuroscience and climate science. For time series that can be modeled as bivariate auto-regressive processes we analytically derive an expression for spectrally decomposed Granger Causality (SDGC) and show that this quantity depends only on two out of four groups of model parameters. Then we present examples of such processes whose SDGC expose paradoxical behavior in the sense that causality is high for frequency ranges with low spectral power. For avoiding misinterpretations of Granger causality analysis we propose to complement it by partial spectral analysis. Our findings are illustrated by an example from brain electrophysiology. Finally, we draw implications for the conventional definition of Granger causality. Bernstein Center for Computational Neuroscience Goettingen

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.

Causal symmetric spaces

CERN Document Server

Olafsson, Gestur; Helgason, Sigurdur

1996-01-01

This book is intended to introduce researchers and graduate students to the concepts of causal symmetric spaces. To date, results of recent studies considered standard by specialists have not been widely published. This book seeks to bring this information to students and researchers in geometry and analysis on causal symmetric spaces.Includes the newest results in harmonic analysis including Spherical functions on ordered symmetric space and the holmorphic discrete series and Hardy spaces on compactly casual symmetric spacesDeals with the infinitesimal situation, coverings of symmetric spaces, classification of causal symmetric pairs and invariant cone fieldsPresents basic geometric properties of semi-simple symmetric spacesIncludes appendices on Lie algebras and Lie groups, Bounded symmetric domains (Cayley transforms), Antiholomorphic Involutions on Bounded Domains and Para-Hermitian Symmetric Spaces

Predicting Causal Relationships from Biological Data: Applying Automated Causal Discovery on Mass Cytometry Data of Human Immune Cells

KAUST Repository

Triantafillou, Sofia; Lagani, Vincenzo; Heinze-Deml, Christina; Schmidt, Angelika; Tegner, Jesper; Tsamardinos, Ioannis

2017-01-01

Learning the causal relationships that define a molecular system allows us to predict how the system will respond to different interventions. Distinguishing causality from mere association typically requires randomized experiments. Methods for automated  causal discovery from limited experiments exist, but have so far rarely been tested in systems biology applications. In this work, we apply state-of-the art causal discovery methods on a large collection of public mass cytometry data sets, measuring intra-cellular signaling proteins of the human immune system and their response to several perturbations. We show how different experimental conditions can be used to facilitate causal discovery, and apply two fundamental methods that produce context-specific causal predictions. Causal predictions were reproducible across independent data sets from two different studies, but often disagree with the KEGG pathway databases. Within this context, we discuss the caveats we need to overcome for automated causal discovery to become a part of the routine data analysis in systems biology.

Predicting Causal Relationships from Biological Data: Applying Automated Causal Discovery on Mass Cytometry Data of Human Immune Cells

KAUST Repository

Triantafillou, Sofia

2017-09-29

Learning the causal relationships that define a molecular system allows us to predict how the system will respond to different interventions. Distinguishing causality from mere association typically requires randomized experiments. Methods for automated  causal discovery from limited experiments exist, but have so far rarely been tested in systems biology applications. In this work, we apply state-of-the art causal discovery methods on a large collection of public mass cytometry data sets, measuring intra-cellular signaling proteins of the human immune system and their response to several perturbations. We show how different experimental conditions can be used to facilitate causal discovery, and apply two fundamental methods that produce context-specific causal predictions. Causal predictions were reproducible across independent data sets from two different studies, but often disagree with the KEGG pathway databases. Within this context, we discuss the caveats we need to overcome for automated causal discovery to become a part of the routine data analysis in systems biology.

Inferring causation from cross-sectional data: Examination of the causal relationship between hyperactivity-impulsivity and novelty seeking

Directory of Open Access Journals (Sweden)

Alexis Caroline Wood

2011-03-01

Full Text Available Previous research suggests an association between hyperactivity-impulsivity – one of the two behavioural dimensions that form attention deficit hyperactivity disorder – and the temperament characteristic of novelty seeking. We aimed to examine etiological links underlying the co-occurrence between these behaviours using a general population sample of 668 twin pairs, ages 7-10, for whom we obtained parent ratings in middle childhood; and pilot longitudinal data on 76 children. Structural equation modelling confirmed a shared genetic etiology (genetic correlation, rD=.81; 95% confidence intervals [CI]= .34-1.00 and showed that much (64% of the covariation can be accounted for by shared genetic effects. In addition, causal paths were modelled between the two behaviours; 12% of the variance in novelty seeking at age 7 was accounted for by hyperactive-impulsive behaviors at the same age. The causal effects model fits with the current characterization of hyperactive-impulsive behaviors reflecting a heightened need for stimulation. This has important implications for the management of hyperactive-impulsive behaviors in clinical settings.

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

Science.gov (United States)

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

2012-09-01

Construction project features (CPFs) are organisational, physical and operational attributes that characterise construction projects. Although previous studies have examined the accident causal influence of CPFs, the multi-causal attribute of this causal phenomenon still remain elusive and thus requires further investigation. Aiming to shed light on this facet of the accident causal phenomenon of CPFs, this study examines relevant literature and crystallises the attained insight of the multi-causal attribute by a graphical model which is subsequently operationalised by a derived mathematical risk expression that offers a systematic approach for evaluating the potential of CPFs to cause harm and consequently their health and safety (H&S) risk implications. The graphical model and the risk expression put forth by the study thus advance current understanding of the accident causal phenomenon of CPFs and they present an opportunity for project participants to manage the H&S risk associated with CPFs from the early stages of project procurement. Copyright © 2011 Elsevier Ltd. All rights reserved.

Quasi-experiments to establish causal effects of HIV care and treatment and to improve the cascade of care

Science.gov (United States)

Bor, Jacob; Geldsetzer, Pascal; Venkataramani, Atheendar; Bärnighausen, Till

2015-01-01

Purpose of review Randomized, population-representative trials of clinical interventions are rare. Quasi-experiments have been used successfully to generate causal evidence on the cascade of HIV care in a broad range of real-world settings. Recent findings Quasi-experiments exploit exogenous, or quasi-random, variation occurring naturally in the world or because of an administrative rule or policy change to estimate causal effects. Well designed quasi-experiments have greater internal validity than typical observational research designs. At the same time, quasi-experiments may also have potential for greater external validity than experiments and can be implemented when randomized clinical trials are infeasible or unethical. Quasi-experimental studies have established the causal effects of HIV testing and initiation of antiretroviral therapy on health, economic outcomes and sexual behaviors, as well as indirect effects on other community members. Recent quasi-experiments have evaluated specific interventions to improve patient performance in the cascade of care, providing causal evidence to optimize clinical management of HIV. Summary Quasi-experiments have generated important data on the real-world impacts of HIV testing and treatment and on interventions to improve the cascade of care. With the growth in large-scale clinical and administrative data, quasi-experiments enable rigorous evaluation of policies implemented in real-world settings. PMID:26371463

Quasi-experiments to establish causal effects of HIV care and treatment and to improve the cascade of care.

Science.gov (United States)

Bor, Jacob; Geldsetzer, Pascal; Venkataramani, Atheendar; Bärnighausen, Till

2015-11-01

Randomized, population-representative trials of clinical interventions are rare. Quasi-experiments have been used successfully to generate causal evidence on the cascade of HIV care in a broad range of real-world settings. Quasi-experiments exploit exogenous, or quasi-random, variation occurring naturally in the world or because of an administrative rule or policy change to estimate causal effects. Well designed quasi-experiments have greater internal validity than typical observational research designs. At the same time, quasi-experiments may also have potential for greater external validity than experiments and can be implemented when randomized clinical trials are infeasible or unethical. Quasi-experimental studies have established the causal effects of HIV testing and initiation of antiretroviral therapy on health, economic outcomes and sexual behaviors, as well as indirect effects on other community members. Recent quasi-experiments have evaluated specific interventions to improve patient performance in the cascade of care, providing causal evidence to optimize clinical management of HIV. Quasi-experiments have generated important data on the real-world impacts of HIV testing and treatment and on interventions to improve the cascade of care. With the growth in large-scale clinical and administrative data, quasi-experiments enable rigorous evaluation of policies implemented in real-world settings.

Principal stratification in causal inference.

Science.gov (United States)

Frangakis, Constantine E; Rubin, Donald B

2002-03-01

Many scientific problems require that treatment comparisons be adjusted for posttreatment variables, but the estimands underlying standard methods are not causal effects. To address this deficiency, we propose a general framework for comparing treatments adjusting for posttreatment variables that yields principal effects based on principal stratification. Principal stratification with respect to a posttreatment variable is a cross-classification of subjects defined by the joint potential values of that posttreatment variable tinder each of the treatments being compared. Principal effects are causal effects within a principal stratum. The key property of principal strata is that they are not affected by treatment assignment and therefore can be used just as any pretreatment covariate. such as age category. As a result, the central property of our principal effects is that they are always causal effects and do not suffer from the complications of standard posttreatment-adjusted estimands. We discuss briefly that such principal causal effects are the link between three recent applications with adjustment for posttreatment variables: (i) treatment noncompliance, (ii) missing outcomes (dropout) following treatment noncompliance. and (iii) censoring by death. We then attack the problem of surrogate or biomarker endpoints, where we show, using principal causal effects, that all current definitions of surrogacy, even when perfectly true, do not generally have the desired interpretation as causal effects of treatment on outcome. We go on to forrmulate estimands based on principal stratification and principal causal effects and show their superiority.

Causal Set Generator and Action Computer

OpenAIRE

Cunningham, William; Krioukov, Dmitri

2017-01-01

The causal set approach to quantum gravity has gained traction over the past three decades, but numerical experiments involving causal sets have been limited to relatively small scales. The software suite presented here provides a new framework for the generation and study of causal sets. Its efficiency surpasses previous implementations by several orders of magnitude. We highlight several important features of the code, including the compact data structures, the $O(N^2)$ causal set generatio...

Clinical Significance and Characteristic Clinical Differences of Cytolytic Vaginosis in Recurrent Vulvovaginitis.

Science.gov (United States)

Yang, Shuhua; Zhang, Yuexiang; Liu, Ying; Wang, Jianhong; Chen, Shuqin; Li, Shuxia

2017-01-01

The study aimed to evaluate whether cytolytic vaginosis (CV) has important clinical implications for recurrent vulvovaginitis and to identify clinical differences between CV and vulvovaginal candidosis (VVC). Medical histories, physical examinations and laboratory findings were used to diagnose and assess the prevalence rates of various vulvovaginal infections among 536 women with recurrent vulvovaginitis. Chi-square and Fisher exact tests were used to compare age, menstrual cycle phase at episode onset, symptoms/signs of infection and discharge characteristics between CV and VVC with single infection. Among the 484 women with a single-infection recurrent vulvovaginitis, the prevalence of CV (n = 143; 26.7%) was second only to VVC (n = 196; 36.6%). CV symptoms occurred predominantly during the ovulatory and luteal phases. Meanwhile, VVC episodes were not concentrated premenstrually, but rather occurred throughout the menstrual cycle. Significant differences were found in the vaginal pH, discharge characteristics and frequency of inflammatory symptoms between the 2 groups. CV is clinically important, because it is a common cause of recurrent vulvovaginitis. To distinguish CV from VVC, gynecologists should consider the patient's medical history, physical and laboratory findings, vaginal pH and vaginal discharge characteristics. © 2016 S. Karger AG, Basel.

Model selection approach suggests causal association between 25-hydroxyvitamin D and colorectal cancer.

Directory of Open Access Journals (Sweden)

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.

Spectral dimension in causal set quantum gravity

International Nuclear Information System (INIS)

Eichhorn, Astrid; Mizera, Sebastian

2014-01-01

We evaluate the spectral dimension in causal set quantum gravity by simulating random walks on causal sets. In contrast to other approaches to quantum gravity, we find an increasing spectral dimension at small scales. This observation can be connected to the nonlocality of causal set theory that is deeply rooted in its fundamentally Lorentzian nature. Based on its large-scale behaviour, we conjecture that the spectral dimension can serve as a tool to distinguish causal sets that approximate manifolds from those that do not. As a new tool to probe quantum spacetime in different quantum gravity approaches, we introduce a novel dimensional estimator, the causal spectral dimension, based on the meeting probability of two random walkers, which respect the causal structure of the quantum spacetime. We discuss a causal-set example, where the spectral dimension and the causal spectral dimension differ, due to the existence of a preferred foliation. (paper)

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

International Nuclear Information System (INIS)

Kandemir Kocaaslan, Ozge

2013-01-01

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

A Causal Theory of Mnemonic Confabulation

Directory of Open Access Journals (Sweden)

Sven Bernecker

2017-07-01

Full Text Available This paper attempts to answer the question of what defines mnemonic confabulation vis-à-vis genuine memory. The two extant accounts of mnemonic confabulation as “false memory” and as ill-grounded memory are shown to be problematic, for they cannot account for the possibility of veridical confabulation, ill-grounded memory, and well-grounded confabulation. This paper argues that the defining characteristic of mnemonic confabulation is that it lacks the appropriate causal history. In the confabulation case, there is no proper counterfactual dependence of the state of seeming to remember on the corresponding past representation.

Causal models in epidemiology: past inheritance and genetic future

Directory of Open Access Journals (Sweden)

Kriebel David

2006-07-01

Full Text Available Abstract The eruption of genetic research presents a tremendous opportunity to epidemiologists to improve our ability to identify causes of ill health. Epidemiologists have enthusiastically embraced the new tools of genomics and proteomics to investigate gene-environment interactions. We argue that neither the full import nor limitations of such studies can be appreciated without clarifying underlying theoretical models of interaction, etiologic fraction, and the fundamental concept of causality. We therefore explore different models of causality in the epidemiology of disease arising out of genes, environments, and the interplay between environments and genes. We begin from Rothman's "pie" model of necessary and sufficient causes, and then discuss newer approaches, which provide additional insights into multifactorial causal processes. These include directed acyclic graphs and structural equation models. Caution is urged in the application of two essential and closely related concepts found in many studies: interaction (effect modification and the etiologic or attributable fraction. We review these concepts and present four important limitations. 1. Interaction is a fundamental characteristic of any causal process involving a series of probabilistic steps, and not a second-order phenomenon identified after first accounting for "main effects". 2. Standard methods of assessing interaction do not adequately consider the life course, and the temporal dynamics through which an individual's sufficient cause is completed. Different individuals may be at different stages of development along the path to disease, but this is not usually measurable. Thus, for example, acquired susceptibility in children can be an important source of variation. 3. A distinction must be made between individual-based and population-level models. Most epidemiologic discussions of causality fail to make this distinction. 4. At the population level, there is additional

Characteristics of effective clinical guidelines for general practice.

NARCIS (Netherlands)

Burgers, J.S.; Grol, R.P.T.M.; Zaat, J.O.M.; Spies, T.H.; Bij, A.K. van der; Mokkink, H.G.A.

2003-01-01

BACKGROUND: The use of clinical guidelines in general practice is often limited. Research on barriers to guideline adherence usually focuses on attitudinal factors. Factors linked to the guideline itself are much less studied. AIM: To identify characteristics of effective clinical guidelines for

¿CONFIEREN PODERES CAUSALES LOS UNIVERSALES TRASCENDENTES?

Directory of Open Access Journals (Sweden)

José Tomás Alvarado Marambio

2013-11-01

Full Text Available This work discusses the so-called ‘Eleatic’ argument against the existence of transcendent universals, i. e. universals which does not require instantiation for its existence. The Eleatic Principle states that everything produces a difference in the causal powers of something. As transcendent universals seem not to produce such a difference, transcendent universals seem not to exist. The argument depends crucially on the justification and the interpretation of the Eleatic Principle. It is argued, first, that it is not very clear that the principle is justified, and, second, that there are several alternatives for its interpretation, in relation with the different theories one can endorse about modality or causality. Anti-realist theories of modality or causality are not very appropriate for the understanding of what should be a ‘causal power’. Neither does a realist theory of causality conjoined with a combinatorial theory of possible worlds. A ‘causal power’ seems to be better understood in connection with a realist –non-reductionist– theory of causality and a causal theory of modality. Taken in this way the Eleatic Principle, nonetheless, it is argued that transcendent universals do ‘produce’ a difference in causal powers, for every causal connection requires such universals for its existence.

Racionalidad científica, causalidad y metaanálisis de ensayos clínicos Scientific rationality, causality and metaanalyses of clinical trials

Directory of Open Access Journals (Sweden)

Luz María De-Regil

2008-12-01

Full Text Available En el campo de la salud las revisiones sistemáticas y el metaanálisis (MA han cobrado auge, ya que permiten congregar estudios de características similares y generar indicadores que describan el riesgo o el beneficio de intervenciones clínicas asociadas a la presencia de un problema de salud. Para interpretar el MA y darle su justa dimensión, es necesario tomar en cuenta la racionalidad del marco teórico que lo sustenta, sus criterios metodológicos y la posible relación causal entre exposición y evento, además del contextualizar la información. Actualmente, un gran reto constituye el análisis y la síntesis de la mayor cantidad de información para tomar decisiones de manera rápida y asertiva Este artículo hace un breve recorrido por la racionalidad científica y su aplicación en la teoría causal en el marco de la epidemiología, para sentar los cimientos que permitan evaluar la pertinencia y validez de las decisiones que se tomen con base en estos análisis.Currently, the challenge is to analyze and synthesize as much information as possible in order to make quick, correct decisions. Systematic reviews and meta-analysis have quickly arisen in the health field because they allow researchers to congregate studies of similar characteristics to generate estimators that describe the risk or benefit of practices related to health problems. To understand and attach the appropriate importance to meta-analyses, it is necessary to consider the rationale of the theoretical framework, the methodological criteria, and the possible causal relationship between exposure and outcome, besides contextualizing the information. This paper briefly explores scientific rationality and its application in causal theory within an epidemiological framework, to set the basis that allows decision-makers and health professionals to evaluate the appropriateness and validity of conclusions derived from this type of analyses.

Re-thinking local causality

NARCIS (Netherlands)

Friederich, Simon

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

mediation: R package for causal mediation analysis

OpenAIRE

Tingley, Dustin; Yamamoto, Teppei; Hirose, Kentaro; Keele, Luke; Imai, Kosuke

2012-01-01

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 su...

Physician and patient characteristics associated with clinical inertia in blood pressure control.

Science.gov (United States)

Harle, Christopher A; Harman, Jeffrey S; Yang, Shuo

2013-11-01

Clinical inertia, the failure to adjust antihypertensive medications during patient visits with uncontrolled hypertension, is thought to be a common problem. This retrospective study used 5 years of electronic medical records from a multispecialty group practice to examine the association between physician and patient characteristics and clinical inertia. Hierarchical linear models (HLMs) were used to examine (1) differences in physician and patient characteristics among patients with and without clinical inertia, and (2) the association between clinical inertia and future uncontrolled hypertension. Overall, 66% of patients experienced clinical inertia. Clinical inertia was associated with one physician characteristic, patient volume (odds ratio [OR]=0.998). However, clinical inertia was associated with multiple patient characteristics, including patient age (OR=1.021), commercial insurance (OR=0.804), and obesity (OR=1.805). Finally, patients with clinical inertia had 2.9 times the odds of uncontrolled hypertension at their final visit in the study period. These findings may aid the design of interventions to reduce clinical inertia. ©2013 Wiley Periodicals, Inc.

Causal knowledge and the development of inductive reasoning.

Science.gov (United States)

Bright, Aimée K; Feeney, Aidan

2014-06-01

We explored the development of sensitivity to causal relations in children's inductive reasoning. Children (5-, 8-, and 12-year-olds) and adults were given trials in which they decided whether a property known to be possessed by members of one category was also possessed by members of (a) a taxonomically related category or (b) a causally related category. The direction of the causal link was either predictive (prey→predator) or diagnostic (predator→prey), and the property that participants reasoned about established either a taxonomic or causal context. There was a causal asymmetry effect across all age groups, with more causal choices when the causal link was predictive than when it was diagnostic. Furthermore, context-sensitive causal reasoning showed a curvilinear development, with causal choices being most frequent for 8-year-olds regardless of context. Causal inductions decreased thereafter because 12-year-olds and adults made more taxonomic choices when reasoning in the taxonomic context. These findings suggest that simple causal relations may often be the default knowledge structure in young children's inductive reasoning, that sensitivity to causal direction is present early on, and that children over-generalize their causal knowledge when reasoning. Copyright © 2013 Elsevier Inc. All rights reserved.

Causal Diagrams for Empirical Research

OpenAIRE

Pearl, Judea

1994-01-01

The primary aim of this paper is to show how graphical models can be used as a mathematical language for integrating statistical and subject-matter information. In particular, the paper develops a principled, nonparametric framework for causal inference, in which diagrams are queried to determine if the assumptions available are sufficient for identifiying causal effects from non-experimental data. If so the diagrams can be queried to produce mathematical expressions for causal effects in ter...

The selective power of causality on memory errors.

Science.gov (United States)

Marsh, Jessecae K; Kulkofsky, Sarah

2015-01-01

We tested the influence of causal links on the production of memory errors in a misinformation paradigm. Participants studied a set of statements about a person, which were presented as either individual statements or pairs of causally linked statements. Participants were then provided with causally plausible and causally implausible misinformation. We hypothesised that studying information connected with causal links would promote representing information in a more abstract manner. As such, we predicted that causal information would not provide an overall protection against memory errors, but rather would preferentially help in the rejection of misinformation that was causally implausible, given the learned causal links. In two experiments, we measured whether the causal linkage of information would be generally protective against all memory errors or only selectively protective against certain types of memory errors. Causal links helped participants reject implausible memory lures, but did not protect against plausible lures. Our results suggest that causal information may promote an abstract storage of information that helps prevent only specific types of memory errors.

Rate-Agnostic (Causal) Structure Learning.

Science.gov (United States)

Plis, Sergey; Danks, David; Freeman, Cynthia; Calhoun, Vince

2015-12-01

Causal structure learning from time series data is a major scientific challenge. Extant algorithms assume that measurements occur sufficiently quickly; more precisely, they assume approximately equal system and measurement timescales. In many domains, however, measurements occur at a significantly slower rate than the underlying system changes, but the size of the timescale mismatch is often unknown. This paper develops three causal structure learning algorithms, each of which discovers all dynamic causal graphs that explain the observed measurement data, perhaps given undersampling. That is, these algorithms all learn causal structure in a "rate-agnostic" manner: they do not assume any particular relation between the measurement and system timescales. We apply these algorithms to data from simulations to gain insight into the challenge of undersampling.

Causal Factors for The Adoption Innovation Teacher’s Tv for Teachersand Educational Personnel

Directory of Open Access Journals (Sweden)

Thanadol Phuseerit

2016-12-01

aire for the experts to examine the causal factors for the adoption innovation teacher’s TV for teachers and education personnel model by focus groups, 4 questionnaire to confirm the causal factors to an innovation teacher’s TV model for teachers and educational personnel Committee of the teacher’s TV, 5 the causal factor for the adoption innovation teacher’s TV for teachers and education personnel model, 6 evaluation form of the causal factor for the adoption of the innovation teacher’s TV for teachers and education personnel model from the specialists. The research results were: 1 The causal factors for the adoption innovation teacher’s TV for Teachers and educational personnel Model. Elements and factors are as follows: 1.1 Elements of the causes and factors of innovation teacher’s TV. Teachers and educational personnel The Review of literature and semi-structured questionnaire, interviewing Collecting quality data from in-depth interviews with a total 9 causal as fallow: (1 Characteristics of innovation, included: relative Advantage, Compatibility, Complexity, Trial ability, Observable (2 Communication Channels, included: interpersonal communication, the media as press, radio, television, communication specialized media (3 Innovation-Decision Process, included: Knowledge, Persuasion, Decision, Implementation, Confirmation (4 Economy and Social System, include: compensation and benefits. Social interaction, (5 Attitude, included: understanding the emotions, behavior (6 Motivation, included: Intrinsic motivation. External motivation (7 Support of Administrator, include: support for innovation, the budget support and materials, Academic support (8 Change agent, included: knowledge and ability, Skill-oriented capabilities Ability attitude (9 Opinion Leaders, included: access to others easily, Creative and 1element of the Adoption of the Innovation: TTV, included: the perceived ease of use, and Perceived benefits. The model’s validity of the consistency

Causality and analyticity in optics

International Nuclear Information System (INIS)

Nussenzveig, H.M.

In order to provide an overall picture of the broad range of optical phenomena that are directly linked with the concepts of causality and analyticity, the following topics are briefly reviewed, emphasizing recent developments: 1) Derivation of dispersion relations for the optical constants of general linear media from causality. Application to the theory of natural optical activity. 2) Derivation of sum rules for the optical constants from causality and from the short-time response function (asymptotic high-frequency behavior). Average spectral behavior of optical media. Applications. 3) Role of spectral conditions. Analytic properties of coherence functions in quantum optics. Reconstruction theorem.4) Phase retrieval problems. 5) Inverse scattering problems. 6) Solution of nonlinear evolution equations in optics by inverse scattering methods. Application to self-induced transparency. Causality in nonlinear wave propagation. 7) Analytic continuation in frequency and angular momentum. Complex singularities. Resonances and natural-mode expansions. Regge poles. 8) Wigner's causal inequality. Time delay. Spatial displacements in total reflection. 9) Analyticity in diffraction theory. Complex angular momentum theory of Mie scattering. Diffraction as a barrier tunnelling effect. Complex trajectories in optics. (Author) [pt

clinical characteristics of cataract patients with pseudoexfoliation

African Journals Online (AJOL)

User

the clinical characteristics of pseudoexfoliation syndrome among cataract patients examined at ... CONCLUSION: A significant number of patients with PEX had poor zonular integrity and high IOP ... Poor zonular integrity may give rise to.

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.

Causal asymmetry across cultures: Assigning causal roles in symmetric physical settings

Directory of Open Access Journals (Sweden)

Andrea eBender

2011-09-01

Full Text Available In the cognitive sciences, causal cognition in the physical domain has featured as a core research topic, but the impact of culture has been rarely ever explored. One case in point for a topic on which this neglect is pronounced is the pervasive tendency of people to consider one of two (equally important entities as more important for bringing about an effect. In order to scrutinize how robust such tendencies are across cultures, we asked German and Tongan participants to assign prime causality in nine symmetric settings. For most settings, strong asymmetries in both cultures were found, but not always in the same direction, depending on the task content. This indicates that causal asymmetries, while indeed being a robust phenomenon across cultures, are also subject to culture-specific concepts. Moreover, the asymmetries were found to be modulated by figure-ground relations, but not by marking agency.

Entanglement, non-Markovianity, and causal non-separability

Science.gov (United States)

Milz, Simon; Pollock, Felix A.; Le, Thao P.; Chiribella, Giulio; Modi, Kavan

2018-03-01

Quantum mechanics, in principle, allows for processes with indefinite causal order. However, most of these causal anomalies have not yet been detected experimentally. We show that every such process can be simulated experimentally by means of non-Markovian dynamics with a measurement on additional degrees of freedom. In detail, we provide an explicit construction to implement arbitrary a causal processes. Furthermore, we give necessary and sufficient conditions for open system dynamics with measurement to yield processes that respect causality locally, and find that tripartite entanglement and nonlocal unitary transformations are crucial requirements for the simulation of causally indefinite processes. These results show a direct connection between three counter-intuitive concepts: entanglement, non-Markovianity, and causal non-separability.

Particulate air pollution and increased mortality: Biological plausibility for causal relationship

International Nuclear Information System (INIS)

Henderson, R.F.

1995-01-01

Recently, a number of epidemiological studies have concluded that ambient particulate exposure is associated with increased mortality and morbidity at PM concentrations well below those previously thought to affect human health. These studies have been conducted in several different geographical locations and have involved a range of populations. While the consistency of the findings and the presence of an apparent concentration response relationship provide a strong argument for causality, epidemiological studies can only conclude this based upon inference from statistical associations. The biological plausibility of a causal relationship between low concentrations of PM and daily mortality and morbidity rates is neither intuitively obvious nor expected based on past experimental studies on the toxicity of inhaled particles. Chronic toxicity from inhaled, poorly soluble particles has been observed based on the slow accumulation of large lung burdens of particles, not on small daily fluctuations in PM levels. Acute toxicity from inhaled particles is associated mainly with acidic particles and is observed at much higher concentrations than those observed in the epidemiology studies reporting an association between PM concentrations and morbidity/mortality. To approach the difficult problem of determining if the association between PM concentrations and daily morbidity and mortality is biologically plausible and causal, one must consider (1) the chemical and physical characteristics of the particles in the inhaled atmospheres, (2) the characteristics of the morbidity/mortality observed and the people who are affected, and (3) potential mechanisms that might link the two

Clinical and radiological characteristics of adult black Zimbabweans ...

African Journals Online (AJOL)

Clinical and radiological characteristics of adult black Zimbabweans with low back pain attending a specialist neurosurgery clinic. ... A past medical history of trauma, no significant illness in the past, smoking cigarettes, and drinking alcohol was observed in 25%, 38%, 23%, and 44% of the records respectively. The common ...

Amodal causal capture in the tunnel effect.

Science.gov (United States)

Bae, Gi Yeul; Flombaum, Jonathan I

2011-01-01

In addition to identifying individual objects in the world, the visual system must also characterize the relationships between objects, for instance when objects occlude one another or cause one another to move. Here we explored the relationship between perceived causality and occlusion. Can one perceive causality in an occluded location? In several experiments, observers judged whether a centrally presented event involved a single object passing behind an occluder, or one object causally launching another (out of view and behind the occluder). With no additional context, the centrally presented event was typically judged as a non-causal pass, even when the occluding and disoccluding objects were different colors--an illusion known as the 'tunnel effect' that results from spatiotemporal continuity. However, when a synchronized context event involved an unambiguous causal launch, participants perceived a causal launch behind the occluder. This percept of an occluded causal interaction could also be driven by grouping and synchrony cues in the absence of any explicitly causal interaction. These results reinforce the hypothesis that causality is an aspect of perception. It is among the interpretations of the world that are independently available to vision when resolving ambiguity, and that the visual system can 'fill in' amodally.

Space-time as a causal set

International Nuclear Information System (INIS)

Bombelli, L.; Lee, J.; Meyer, D.; Sorkin, R.D.

1987-01-01

We propose that space-time at the smallest scales is in reality a causal set: a locally finite set of elements endowed with a partial order corresponding to the macroscopic relation that defines past and future. We explore how a Lorentzian manifold can approximate a causal set, noting in particular that the thereby defined effective dimensionality of a given causal set can vary with length scale. Finally, we speculate briefly on the quantum dynamics of causal sets, indicating why an appropriate choice of action can reproduce general relativity in the classical limit

Representing Personal Determinants in Causal Structures.

Science.gov (United States)

Bandura, Albert

1984-01-01

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

[Causal analysis approaches in epidemiology].

Science.gov (United States)

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

2014-02-01

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

Lipoprotein(a) and ischemic heart disease-A causal association? A review

DEFF Research Database (Denmark)

Kamstrup, P.R.

2010-01-01

association of LPA copy number variants, influencing levels of lipoprotein(a), with risk of IHD. In conclusion, results from epidemiologic, in vitro, animal, and genetic epidemiologic studies support a causal association of lipoprotein(a) with risk of IHD, while results from randomized clinical trials...

Repeated Causal Decision Making

Science.gov (United States)

Hagmayer, York; Meder, Bjorn

2013-01-01

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

Causality in Classical Electrodynamics

Science.gov (United States)

Savage, Craig

2012-01-01

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

Genetic characteristics of Japanese clinical Listeria monocytogenes isolates.

Directory of Open Access Journals (Sweden)

Satoko Miya

Full Text Available Listeria monocytogenes causes foodborne illnesses through consumption of ready-to-eat foods. Although 135-201annual listeriosis cases have been estimated in Japan, the details regarding the clinical isolates such as infection source, virulence level, and other genetic characteristics, are not known. In order to uncover the trends of listeriosis in Japan and use the knowledge for prevention measures to be taken, the genetic characteristics of the past human clinical isolates needs to be elucidated. For this purpose, multilocus tandem-repeat sequence analysis (MLTSA and multi-virulence-locus sequence typing (MVLST were used in this study. The clinical isolates showed a variety of genetically distant genotypes, indicating they were from sporadic cases. However, the MVLST profiles of 7 clinical isolates were identical to those of epidemic clone (EC I isolates, which have caused several serious outbreaks in other countries, suggesting the possibility that they have strong virulence potential and originated from a single outbreak. Moreover, 6 Japanese food isolates shared their genotypes with ECI isolates, indicating that there may be risks for listeriosis outbreak in Japan. This is the first investigational study on genetic characteristics of Japanese listeriosis isolates. The listeriosis cases happened in the past are presumably sporadic, but it is still possible that some isolates with strong virulence potential have caused listeriosis outbreaks, and future listeriosis risks also exist.

Kant on causal laws and powers.

Science.gov (United States)

Henschen, Tobias

2014-12-01

The aim of the paper is threefold. Its first aim is to defend Eric Watkins's claim that for Kant, a cause is not an event but a causal power: a power that is borne by a substance, and that, when active, brings about its effect, i.e. a change of the states of another substance, by generating a continuous flow of intermediate states of that substance. The second aim of the paper is to argue against Watkins that the Kantian concept of causal power is not the pre-critical concept of real ground but the category of causality, and that Kant holds with Hume that causal laws cannot be inferred non-inductively (that he accordingly has no intention to show in the Second analogy or elsewhere that events fall under causal laws). The third aim of the paper is to compare the Kantian position on causality with central tenets of contemporary powers ontology: it argues that unlike the variants endorsed by contemporary powers theorists, the Kantian variants of these tenets are resistant to objections that neo-Humeans raise to these tenets.

Acute appendicitis following blunt abdominal trauma. Coincidence or causality?

Directory of Open Access Journals (Sweden)

Sergio Iván Latorre

2017-01-01

Full Text Available Acute appendicitis is a common disease in clinical practice; some well-defined causes include luminal obstruction by fecoliths, lymphoid hyperplasia, foreign bodies and intestinal parasites. Closed abdominal trauma has been associated as an etiological factor, although, their causal relationship is still unclear. This paper presents the case of a patient with appendicitis after a closed abdominal trauma.

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

Science.gov (United States)

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

2016-01-01

Reverse-engineering of causal pathways that implicate diseases and vital cellular functions is a fundamental problem in biomedicine. Discovery of the local causal pathway of a target variable (that consists of its direct causes and direct effects) is essential for effective intervention and can facilitate accurate diagnosis and prognosis. Recent research has provided several active learning methods that can leverage passively observed high-throughput data to draft causal pathways and then refine the inferred relations with a limited number of experiments. The current study provides a comprehensive evaluation of the performance of active learning methods for local causal pathway discovery in real biological data. Specifically, 54 active learning methods/variants from 3 families of algorithms were applied for local causal pathways reconstruction of gene regulation for 5 transcription factors in S. cerevisiae. Four aspects of the methods’ performance were assessed, including adjacency discovery quality, edge orientation accuracy, complete pathway discovery quality, and experimental cost. The results of this study show that some methods provide significant performance benefits over others and therefore should be routinely used for local causal pathway discovery tasks. This study also demonstrates the feasibility of local causal pathway reconstruction in real biological systems with significant quality and low experimental cost. PMID:26939894

Investigating Driver Fatigue versus Alertness Using the Granger Causality Network

Directory of Open Access Journals (Sweden)

Wanzeng Kong

2015-08-01

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

Characteristics desired in clinical data warehouse for biomedical research.

Science.gov (United States)

Shin, Soo-Yong; Kim, Woo Sung; Lee, Jae-Ho

2014-04-01

Due to the unique characteristics of clinical data, clinical data warehouses (CDWs) have not been successful so far. Specifically, the use of CDWs for biomedical research has been relatively unsuccessful thus far. The characteristics necessary for the successful implementation and operation of a CDW for biomedical research have not clearly defined yet. THREE EXAMPLES OF CDWS WERE REVIEWED: a multipurpose CDW in a hospital, a CDW for independent multi-institutional research, and a CDW for research use in an institution. After reviewing the three CDW examples, we propose some key characteristics needed in a CDW for biomedical research. A CDW for research should include an honest broker system and an Institutional Review Board approval interface to comply with governmental regulations. It should also include a simple query interface, an anonymized data review tool, and a data extraction tool. Also, it should be a biomedical research platform for data repository use as well as data analysis. The proposed characteristics desired in a CDW may have limited transfer value to organizations in other countries. However, these analysis results are still valid in Korea, and we have developed clinical research data warehouse based on these desiderata.

Clinical characteristics of subacute radiation sickness

International Nuclear Information System (INIS)

Jiang Benrong; Ye Genyao; Huang Shimin

1991-01-01

The clinical characteristics, diagnosis and differential diagnosis of subacute radiation sickness are analysed and discussed in this paper on the basis of clinical data from cases in a 137 Cs source accident in Mudanjiang and of a review of the literature. We consider that the subacute radiation sickness is a whole body disease caused by comparatively large dose of continuous or intermittent external irradiation in several weeks or months. it must be differentiated from acute radiation sickness, chronic radiation sickness, idiopathic aplastic anemia and other hematological diseases, such as paroxysmal nocturnal hemoglobinuria, acute leukemia and myelodysplastic syndrome

Repair of Partly Misspecified Causal Diagrams.

Science.gov (United States)

Oates, Chris J; Kasza, Jessica; Simpson, Julie A; Forbes, Andrew B

2017-07-01

Errors in causal diagrams elicited from experts can lead to the omission of important confounding variables from adjustment sets and render causal inferences invalid. In this report, a novel method is presented that repairs a misspecified causal diagram through the addition of edges. These edges are determined using a data-driven approach designed to provide improved statistical efficiency relative to de novo structure learning methods. Our main assumption is that the expert is "directionally informed," meaning that "false" edges provided by the expert would not create cycles if added to the "true" causal diagram. The overall procedure is cast as a preprocessing technique that is agnostic to subsequent causal inferences. Results based on simulated data and data derived from an observational cohort illustrate the potential for data-assisted elicitation in epidemiologic applications. See video abstract at, http://links.lww.com/EDE/B208.

Nursing Students’ Perceptions on Characteristics of an Effective Clinical Instructor

Directory of Open Access Journals (Sweden)

Joan E. Niederriter PhD, MSN, CMSRN, RN-BC

2017-01-01

Full Text Available Purpose To identify characteristics and teaching techniques of effective clinical instructors that can be utilized or implemented to improve the student nurse clinical experience. Background The clinical instructor is an integral part of a quality clinical experience. They help students transfer didactic information to the practice setting. The clinical nursing experience is a vital component in the developmental process of the nursing student. Research has been done on this subject, but gaps remain. The need for a more in-depth understanding of students’ perceptions of the characteristics and teaching techniques that best aid their comprehension and learning will help instructors to maximize student learning experiences in the practice setting. Method This qualitative research study utilized the phenomenological research method. Three open-ended questions were posed to 14 nursing students to identify the characteristics and teaching techniques they believed comprised an effective clinical instructor. Individual interviews were conducted and transcribed interviews were reviewed to identify common themes. Three faculty members provided member checking to prevent bias by reviewing the transcribed interviews for common themes. Findings Participants identified four main themes which include a trusting relationship, experience or knowledge, coach, and role model. The students found that they gained more knowledge, developed more critical thinking, and felt more confident with instructors who utilized characteristics and techniques from these four areas. Conclusion Clinical instructors play an important role in preparing the student nurse in becoming a competent nurse in the practice setting. This information can be used to provide a foundation in creating an educational opportunity to inform nurse educators in the ways to become a more effective clinical instructor.

The influence of causal attribution of parents on developing the child enuresis

Directory of Open Access Journals (Sweden)

Jerković Ivan

2003-01-01

Full Text Available Causal attributions are affirmed as a cognitive element able to explain emotional and motivational aspects of behaviour of some categories of adult psychiatric patients, primarily depressive ones. Theoretical and practical success of cognitive ideas in explaining the origination of depressive disorders, and in the monitoring of depressive patient treatment has led to further development of theory, but also to the attempt to apply the learning about causal attributions to various problems. Characteristic attempts are those that the problems of child abuse, children’s depression, upbringing problems, school failure, hyperactivity, enuresis, and long-term effects of different child treatment, too, are analysed from the point of view of causal attributions. By assessing parent causal attributions regarding child night urination, we wanted to establish to what extent specific attributions for child behaviour differentiate the parents of children having this problem from those parents whose children have established control. Parents were assessed in terms of four dimensions of causal attributions for child’s problem. Those are the dimensions of globality, counter-lability, internality, and the stability of the cause of child’s problem. The analysis of parent causal attributions show that mothers and fathers in both assessed groups similarly experience the cause of enuretic problems of their children. Enuresis is seen as caused by specific, internal, and instable causes. Such a system of dimensions could correspond to the belief that the main etiological factor of the enuresis is maturing. For more reliable verification of this attitude, longitudinal strategy in research is necessary, especially to comprehend whether parental attributions have been developed as an effect of persistent enuresis, or whether the enuresis is developed as an effect of parental attributions.

Functional equations with causal operators

CERN Document Server

Corduneanu, C

2003-01-01

Functional equations encompass most of the equations used in applied science and engineering: ordinary differential equations, integral equations of the Volterra type, equations with delayed argument, and integro-differential equations of the Volterra type. The basic theory of functional equations includes functional differential equations with causal operators. Functional Equations with Causal Operators explains the connection between equations with causal operators and the classical types of functional equations encountered by mathematicians and engineers. It details the fundamentals of linear equations and stability theory and provides several applications and examples.

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 inference in economics and marketing.

Science.gov (United States)

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.

Clinical characteristics and outcomes of septic bursitis.

Science.gov (United States)

Lieber, Sarah B; Fowler, Mary Louise; Zhu, Clara; Moore, Andrew; Shmerling, Robert H; Paz, Ziv

2017-12-01

Limited data guide practice in evaluation and treatment of septic bursitis. We aimed to characterize clinical characteristics, microbiology, and outcomes of patients with septic bursitis stratified by bursal involvement, presence of trauma, and management type. We conducted a retrospective cohort study of adult patients admitted to a single center from 1998 to 2015 with culture-proven olecranon and patellar septic bursitis. Baseline characteristics, clinical features, microbial profiles, operative interventions, hospitalization lengths, and 60-day readmission rates were determined. Patients were stratified by bursitis site, presence or absence of trauma, and operative or non-operative management. Of 44 cases of septic bursitis, patients with olecranon and patellar bursitis were similar with respect to age, male predominance, and frequency of bursal trauma; patients managed operatively were younger (p = 0.05). Clinical features at presentation and comorbidities were similar despite bursitis site, history of trauma, or management. The most common organism isolated from bursal fluid was Staphylococcus aureus. Patients managed operatively were discharged to rehabilitation less frequently (p = 0.04). This study of septic bursitis is among the largest reported. We were unable to identify presenting clinical features that differentiated patients treated surgically from those treated conservatively. There was no clear relationship between preceding trauma or bursitis site and clinical course, management, or outcomes. Patients with bursitis treated surgically were younger. Additional study is needed to identify patients who would benefit from early surgical intervention for septic bursitis.

Interactions of information transfer along separable causal paths

Science.gov (United States)

Jiang, Peishi; Kumar, Praveen

2018-04-01

Complex systems arise as a result of interdependences between multiple variables, whose causal interactions can be visualized in a time-series graph. Transfer entropy and information partitioning approaches have been used to characterize such dependences. However, these approaches capture net information transfer occurring through a multitude of pathways involved in the interaction and as a result mask our ability to discern the causal interaction within a subgraph of interest through specific pathways. We build on recent developments of momentary information transfer along causal paths proposed by Runge [Phys. Rev. E 92, 062829 (2015), 10.1103/PhysRevE.92.062829] to develop a framework for quantifying information partitioning along separable causal paths. Momentary information transfer along causal paths captures the amount of information transfer between any two variables lagged at two specific points in time. Our approach expands this concept to characterize the causal interaction in terms of synergistic, unique, and redundant information transfer through separable causal paths. Through a graphical model, we analyze the impact of the separable and nonseparable causal paths and the causality structure embedded in the graph as well as the noise effect on information partitioning by using synthetic data generated from two coupled logistic equation models. Our approach can provide a valuable reference for an autonomous information partitioning along separable causal paths which form a causal subgraph influencing a target.

Does Causality Matter More Now? Increase in the Proportion of Causal Language in English Texts.

Science.gov (United States)

Iliev, Rumen; Axelrod, Robert

2016-05-01

The vast majority of the work on culture and cognition has focused on cross-cultural comparisons, largely ignoring the dynamic aspects of culture. In this article, we provide a diachronic analysis of causal cognition over time. We hypothesized that the increased role of education, science, and technology in Western societies should be accompanied by greater attention to causal connections. To test this hypothesis, we compared word frequencies in English texts from different time periods and found an increase in the use of causal language of about 40% over the past two centuries. The observed increase was not attributable to general language effects or to changing semantics of causal words. We also found that there was a consistent difference between the 19th and the 20th centuries, and that the increase happened mainly in the 20th century. © The Author(s) 2016.

Severe hypertriglyceridemia. Clinical characteristics and therapeutic management.

Science.gov (United States)

Masson, Walter; Rossi, Emiliano; Siniawski, Daniel; Damonte, Juan; Halsband, Ana; Barolo, Ramiro; Scaramal, Miguel

2018-05-19

The therapeutic management of severe hypertriglyceridaemia represents a clinical challenge. The objectives of this study were 1) to identify the clinical characteristics of patients with severe hypertriglyceridaemia, and 2) to analyse the treatment established by the physicians in each case. A cross-sectional study was carried out using the computerised medical records of all patients>18 years of age with a blood triglyceride level≥1,000mg/dL between 1 January 2011 and 31 December 2016. Clinical and laboratory variables were collected. The behaviour of the physicians in the 6 months after the lipid finding was analysed. A total of 420 patients were included (mean age 49.1±11.4 years, males 78.8%). The median of triglycerides was 1,329mg/dL (interquartile range 1,174-1,658). No secondary causes were found in 34.1% of the patients. The most frequent secondary causes were obesity (38.6%) and diabetes (28.1%). Physical activity was recommended and a nutritionist was referred to in 49.1% and 44.2% of the patients, respectively. Secondary causes were identified and attempts were made to correct them in 40.7% of cases. The most indicated pharmacological treatments were fenofibrate 200mg/day (26.5%) and gemfibrozil 900mg/day (19.3%). Few patients received the indication of omega 3 fatty acids or niacin. This study showed, for the first time in our country, the characteristics of a population with severe hypertriglyceridaemia. The therapeutic measures instituted by the physicians were insufficient. Knowing the characteristics in this particular clinical scenario could improve the current approach of these patients. Copyright © 2018 Sociedad Española de Arteriosclerosis. Publicado por Elsevier España, S.L.U. All rights reserved.

Causality, spin, and equal-time commutators

International Nuclear Information System (INIS)

Abdel-Rahman, A.M.

1975-01-01

We study the causality constraints on the structure of the Lorentz-antisymmetric component of the commutator of two conserved isovector currents between fermion states of equal momenta. We discuss the sum rules that follow from causality and scaling, using the recently introduced refined infinite-momentum technique. The complete set of sum rules is found to include the spin-dependent fixed-mass sum rules obtained from light-cone commutators. The causality and scaling restrictions on the structure of the electromagnetic equal-time commutators are discussed, and it is found, in particular, that causality requires the spin-dependent part of the matrix element for the time-space electromagnetic equal-time commutator to vanish identically. It is also shown, in comparison with the electromagnetic case, that the corresponding matrix element for the time-space isovector current equal-time commutator is required, by causality, to have isospin-antisymmetric tensor and scalar operator Schwinger terms

Causal inference, probability theory, and graphical insights.

Science.gov (United States)

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. Published 2013. This article is a US Government work and is in the public domain in the USA.

Prevalence and Clinical Characteristics of Headaches among ...

African Journals Online (AJOL)

2018-01-24

Jan 24, 2018 ... headache on students' daily physical activity, whether they have seen a doctor on ... Table 3: Comparison of some clinical characteristics by headache .... the prevalence was 3.4% in women and 1.5% in men. The findings of ...

Contours of a causal feedback mechanism between adaptive personality and psychosocial function in patients with personality disorders: a secondary analysis from a randomized clinical trial.

Science.gov (United States)

Klungsøyr, Ole; Antonsen, Bjørnar; Wilberg, Theresa

2017-06-05

Patients with personality disorders commonly exhibit impairment in psychosocial function that persists over time even with diagnostic remission. Further causal knowledge may help to identify and assess factors with a potential to alleviate this impairment. Psychosocial function is associated with personality functioning which describes personality disorder severity in DSM-5 (section III) and which can reportedly be improved by therapy. The reciprocal association between personality functioning and psychosocial function was assessed, in 113 patients with different personality disorders, in a secondary longitudinal analysis of data from a randomized clinical trial, over six years. Personality functioning was represented by three domains of the Severity Indices of Personality Problems: Relational Capacity, Identity Integration, and Self-control. Psychosocial function was measured by Global Assessment of Functioning. The marginal structural model was used for estimation of causal effects of the three personality functioning domains on psychosocial function, and vice versa. The attractiveness of this model lies in the ability to assess an effect of a time - varying exposure on an outcome, while adjusting for time - varying confounding. Strong causal effects were found. A hypothetical intervention to increase Relational Capacity by one standard deviation, both at one and two time-points prior to assessment of psychosocial function, would increase psychosocial function by 3.5 standard deviations (95% CI: 2.0, 4.96). Significant effects of Identity Integration and Self-control on psychosocial function, and from psychosocial function on all three domains of personality functioning, although weaker, were also found. This study indicates that persistent impairment in psychosocial function can be addressed through a causal pathway of personality functioning, with interventions of at least 18 months duration.

Causality as a Rigorous Notion and Quantitative Causality Analysis with Time Series

Science.gov (United States)

Liang, X. S.

2017-12-01

Given two time series, can one faithfully tell, in a rigorous and quantitative way, the cause and effect between them? Here we show that this important and challenging question (one of the major challenges in the science of big data), which is of interest in a wide variety of disciplines, has a positive answer. Particularly, for linear systems, the maximal likelihood estimator of the causality from a series X2 to another series X1, written T2→1, turns out to be concise in form: T2→1 = [C11 C12 C2,d1 — C112 C1,d1] / [C112 C22 — C11C122] where Cij (i,j=1,2) is the sample covariance between Xi and Xj, and Ci,dj the covariance between Xi and ΔXj/Δt, the difference approximation of dXj/dt using the Euler forward scheme. An immediate corollary is that causation implies correlation, but not vice versa, resolving the long-standing debate over causation versus correlation. The above formula has been validated with touchstone series purportedly generated with one-way causality that evades the classical approaches such as Granger causality test and transfer entropy analysis. It has also been applied successfully to the investigation of many real problems. Through a simple analysis with the stock series of IBM and GE, an unusually strong one-way causality is identified from the former to the latter in their early era, revealing to us an old story, which has almost faded into oblivion, about "Seven Dwarfs" competing with a "Giant" for the computer market. Another example presented here regards the cause-effect relation between the two climate modes, El Niño and Indian Ocean Dipole (IOD). In general, these modes are mutually causal, but the causality is asymmetric. To El Niño, the information flowing from IOD manifests itself as a propagation of uncertainty from the Indian Ocean. In the third example, an unambiguous one-way causality is found between CO2 and the global mean temperature anomaly. While it is confirmed that CO2 indeed drives the recent global warming

K-causality and degenerate spacetimes

Science.gov (United States)

Dowker, H. F.; Garcia, R. S.; Surya, S.

2000-11-01

The causal relation K+ was introduced by Sorkin and Woolgar to extend the standard causal analysis of C2 spacetimes to those that are only C0. Most of their results also hold true in the case of metrics with degeneracies which are C0 but vanish at isolated points. In this paper we seek to examine K+ explicitly in the case of topology-changing `Morse histories' which contain degeneracies. We first demonstrate some interesting features of this relation in globally Lorentzian spacetimes. In particular, we show that K+ is robust and the Hawking and Sachs characterization of causal continuity translates into a natural condition in terms of K+. We then examine K+ in topology-changing Morse spacetimes with the degenerate points excised and then for the Morse histories in which the degenerate points are reinstated. We find further characterizations of causal continuity in these cases.

Causal inference in econometrics

CERN Document Server

Kreinovich, Vladik; Sriboonchitta, Songsak

2016-01-01

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

Causal localizations in relativistic quantum mechanics

Science.gov (United States)

Castrigiano, Domenico P. L.; Leiseifer, Andreas D.

2015-07-01

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.

Bayesian networks improve causal environmental ...

Science.gov (United States)

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

Hierarchical organisation of causal graphs

International Nuclear Information System (INIS)

Dziopa, P.

1993-01-01

This paper deals with the design of a supervision system using a hierarchy of models formed by graphs, in which the variables are the nodes and the causal relations between the variables of the arcs. To obtain a representation of the variables evolutions which contains only the relevant features of their real evolutions, the causal relations are completed with qualitative transfer functions (QTFs) which produce roughly the behaviour of the classical transfer functions. Major improvements have been made in the building of the hierarchical organization. First, the basic variables of the uppermost level and the causal relations between them are chosen. The next graph is built by adding intermediary variables to the upper graph. When the undermost graph has been built, the transfer functions parameters corresponding to its causal relations are identified. The second task consists in the upwelling of the information from the undermost graph to the uppermost one. A fusion procedure of the causal relations has been designed to compute the QFTs relevant for each level. This procedure aims to reduce the number of parameters needed to represent an evolution at a high level of abstraction. These techniques have been applied to the hierarchical modelling of nuclear process. (authors). 8 refs., 12 figs

Dynamics and causality constraints

International Nuclear Information System (INIS)

Sousa, Manoelito M. de

2001-04-01

The physical meaning and the geometrical interpretation of causality implementation in classical field theories are discussed. Causality in field theory are kinematical constraints dynamically implemented via solutions of the field equation, but in a limit of zero-distance from the field sources part of these constraints carries a dynamical content that explains old problems of classical electrodynamics away with deep implications to the nature of physicals interactions. (author)

Resting-state brain networks revealed by granger causal connectivity in frogs.

Science.gov (United States)

Xue, Fei; Fang, Guangzhan; Yue, Xizi; Zhao, Ermi; Brauth, Steven E; Tang, Yezhong

2016-10-15

Resting-state networks (RSNs) refer to the spontaneous brain activity generated under resting conditions, which maintain the dynamic connectivity of functional brain networks for automatic perception or higher order cognitive functions. Here, Granger causal connectivity analysis (GCCA) was used to explore brain RSNs in the music frog (Babina daunchina) during different behavioral activity phases. The results reveal that a causal network in the frog brain can be identified during the resting state which reflects both brain lateralization and sexual dimorphism. Specifically (1) ascending causal connections from the left mesencephalon to both sides of the telencephalon are significantly higher than those from the right mesencephalon, while the right telencephalon gives rise to the strongest efferent projections among all brain regions; (2) causal connections from the left mesencephalon in females are significantly higher than those in males and (3) these connections are similar during both the high and low behavioral activity phases in this species although almost all electroencephalograph (EEG) spectral bands showed higher power in the high activity phase for all nodes. The functional features of this network match important characteristics of auditory perception in this species. Thus we propose that this causal network maintains auditory perception during the resting state for unexpected auditory inputs as resting-state networks do in other species. These results are also consistent with the idea that females are more sensitive to auditory stimuli than males during the reproductive season. In addition, these results imply that even when not behaviorally active, the frogs remain vigilant for detecting external stimuli. Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.

Causal uncertainty, claimed and behavioural self-handicapping.

Science.gov (United States)

Thompson, Ted; Hepburn, Jonathan

2003-06-01

Causal uncertainty beliefs involve doubts about the causes of events, and arise as a consequence of non-contingent evaluative feedback: feedback that leaves the individual uncertain about the causes of his or her achievement outcomes. Individuals high in causal uncertainty are frequently unable to confidently attribute their achievement outcomes, experience anxiety in achievement situations and as a consequence are likely to engage in self-handicapping behaviour. Accordingly, we sought to establish links between trait causal uncertainty, claimed and behavioural self-handicapping. Participants were N=72 undergraduate students divided equally between high and low causally uncertain groups. We used a 2 (causal uncertainty status: high, low) x 3 (performance feedback condition: success, non-contingent success, non-contingent failure) between-subjects factorial design to examine the effects of causal uncertainty on achievement behaviour. Following performance feedback, participants completed 20 single-solution anagrams and 12 remote associate tasks serving as performance measures, and 16 unicursal tasks to assess practice effort. Participants also completed measures of claimed handicaps, state anxiety and attributions. Relative to low causally uncertain participants, high causally uncertain participants claimed more handicaps prior to performance on the anagrams and remote associates, reported higher anxiety, attributed their failure to internal, stable factors, and reduced practice effort on the unicursal tasks, evident in fewer unicursal tasks solved. These findings confirm links between trait causal uncertainty and claimed and behavioural self-handicapping, highlighting the need for educators to facilitate means by which students can achieve surety in the manner in which they attribute the causes of their achievement outcomes.

Causal knowledge and reasoning in decision making

NARCIS (Netherlands)

Hagmayer, Y.; Witteman, C.L.M.

2017-01-01

Normative causal decision theories argue that people should use their causal knowledge in decision making. Based on these ideas, we argue that causal knowledge and reasoning may support and thereby potentially improve decision making based on expected outcomes, narratives, and even cues. We will

Expert Causal Reasoning and Explanation.

Science.gov (United States)

Kuipers, Benjamin

The relationship between cognitive psychologists and researchers in artificial intelligence carries substantial benefits for both. An ongoing investigation in causal reasoning in medical problem solving systems illustrates this interaction. This paper traces a dialectic of sorts in which three different types of causal resaoning for medical…

Detangling complex relationships in forensic data: principles and use of causal networks and their application to clinical forensic science.

Science.gov (United States)

Lefèvre, Thomas; Lepresle, Aude; Chariot, Patrick

2015-09-01

The search for complex, nonlinear relationships and causality in data is hindered by the availability of techniques in many domains, including forensic science. Linear multivariable techniques are useful but present some shortcomings. In the past decade, Bayesian approaches have been introduced in forensic science. To date, authors have mainly focused on providing an alternative to classical techniques for quantifying effects and dealing with uncertainty. Causal networks, including Bayesian networks, can help detangle complex relationships in data. A Bayesian network estimates the joint probability distribution of data and graphically displays dependencies between variables and the circulation of information between these variables. In this study, we illustrate the interest in utilizing Bayesian networks for dealing with complex data through an application in clinical forensic science. Evaluating the functional impairment of assault survivors is a complex task for which few determinants are known. As routinely estimated in France, the duration of this impairment can be quantified by days of 'Total Incapacity to Work' ('Incapacité totale de travail,' ITT). In this study, we used a Bayesian network approach to identify the injury type, victim category and time to evaluation as the main determinants of the 'Total Incapacity to Work' (TIW). We computed the conditional probabilities associated with the TIW node and its parents. We compared this approach with a multivariable analysis, and the results of both techniques were converging. Thus, Bayesian networks should be considered a reliable means to detangle complex relationships in data.

Paracetamol in therapeutic dosages and acute liver injury: causality assessment in a prospective case series

Directory of Open Access Journals (Sweden)

Castellote José

2011-07-01

Full Text Available Abstract Background Acute liver injury (ALI induced by paracetamol overdose is a well known cause of emergency hospital admission and death. However, there is debate regarding the risk of ALI after therapeutic dosages of the drug. The aim is to describe the characteristics of patients admitted to hospital with jaundice who had previous exposure to therapeutic doses of paracetamol. An assessment of the causality role of paracetamol was performed in each case. Methods Based on the evaluation of prospectively gathered cases of ALI with detailed clinical information, thirty-two cases of ALI in non-alcoholic patients exposed to therapeutic doses of paracetamol were identified. Two authors assessed all drug exposures by using the CIOMS/RUCAM scale. Each case was classified into one of five categories based on the causality score for paracetamol. Results In four cases the role of paracetamol was judged to be unrelated, in two unlikely, and these were excluded from evaluation. In seven of the remaining 26 cases, the RUCAM score associated with paracetamol was higher than that associated with other concomitant medications. The estimated incidence of ALI related to the use of paracetamol in therapeutic dosages was 0.4 per million inhabitants older than 15 years of age and per year (99%CI, 0.2-0.8 and of 10 per million paracetamol users-year (95% CI 4.3-19.4. Conclusions Our results indicate that paracetamol in therapeutic dosages may be considered in the causality assessment in non-alcoholic patients with liver injury, even if the estimated incidence of ALI related to paracetamol appears to be low.

Non-Gaussian Methods for Causal Structure Learning.

Science.gov (United States)

Shimizu, Shohei

2018-05-22

Causal structure learning is one of the most exciting new topics in the fields of machine learning and statistics. In many empirical sciences including prevention science, the causal mechanisms underlying various phenomena need to be studied. Nevertheless, in many cases, classical methods for causal structure learning are not capable of estimating the causal structure of variables. This is because it explicitly or implicitly assumes Gaussianity of data and typically utilizes only the covariance structure. In many applications, however, non-Gaussian data are often obtained, which means that more information may be contained in the data distribution than the covariance matrix is capable of containing. Thus, many new methods have recently been proposed for using the non-Gaussian structure of data and inferring the causal structure of variables. This paper introduces prevention scientists to such causal structure learning methods, particularly those based on the linear, non-Gaussian, acyclic model known as LiNGAM. These non-Gaussian data analysis tools can fully estimate the underlying causal structures of variables under assumptions even in the presence of unobserved common causes. This feature is in contrast to other approaches. A simulated example is also provided.

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

OpenAIRE

Hagmayer, York; Engelmann, Neele

2014-01-01

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

The process and organizational characteristics of memory clinics in Israel in 2007.

Science.gov (United States)

Werner, Perla; Goldstein, Dovrat; Heinik, Jeremia

2009-01-01

We previously described the characteristics and activities of 25 memory clinics in Israel in 1998 using a mail survey. Questionnaires assessing the administrative structure of the clinics, patient characteristics, processes and methods used, and outcomes of the assessment were mailed again in 2007 to 35 memory clinics. Overall, the general operating characteristics of the clinics in 2007 were found to be similar to those reported in the previous survey conducted in 1998. The assessment process in 2007 was shorter than in 1998 (mean time=1.92 and 3.12 h, respectively), although both surveys were based on an interdisciplinary team, including a physician, a nurse and a social worker. However, in 2007 the teams were more wide-ranging. A wider variety of instruments were reported in the more recent survey. Most of the clinics in both surveys reported that family members were involved at all stages of the assessment. Medication treatment was the main outcome reported by the clinics in both surveys. There has been a development in the process and organizational characteristics of memory clinics in Israel over the years, probably as a consequence of the development of knowledge in the area of cognitive deterioration.

Covariation in Natural Causal Induction.

Science.gov (United States)

Cheng, Patricia W.; Novick, Laura R.

1991-01-01

Biases and models usually offered by cognitive and social psychology and by philosophy to explain causal induction are evaluated with respect to focal sets (contextually determined sets of events over which covariation is computed). A probabilistic contrast model is proposed as underlying covariation computation in natural causal induction. (SLD)

Exploring Individual Differences in Preschoolers' Causal Stance

Science.gov (United States)

Alvarez, Aubry; Booth, Amy E.

2016-01-01

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

Clinical Characteristics of Patients with Intradialytic Hypertension.

Science.gov (United States)

Eftimovska-Otovic, Natasa; Grozdanovski, Risto; Taneva, Borjanka; Stojceva-Taneva, Olivera

2015-01-01

Intradialytic hypertension with a prevalence of 15% among hemodialysis patients is with unknown pathophysiology, demographic, laboratoiy and clinical characteristic of patients, and it's influence on longtenn clinical effects (cardiovascular morbidity and mortality, rate of hospitalization). The aim of the study is to present the clinical, laboratoiy and demographic characteristics of patients with intradialytic hypertension in our dialysis center. Out of 110 hemodialysis patients, 17 patients (15,45%) had intradialytic hypertension - started at a systolic pressure greater than 140 nun Hg or had an increase in systolic pressure more than 10 mm Hg during the session, and 17 patients were nonnotensive or had a drop in blood pressure dining the dialysis. HD were performed 3 times per week with a duration of 4-5 hours, on machines with controlled ultrafiltration and high flux syntetic membrane (polyetersulfon) sterilized with gamma rays. A dialysate with standard electrolytes content was used (Na(+) 138 mmol/L, K(+) 2,0 mmol/L, Ca(++) 1,5 mmol/L, Mg (+)1,0 mmol/L, CH(3)COO(-) 3,0 mmol/L, Cl -110 mmol/1, HCO(3)(-) 35 mmol/L). We analysed the following demographic and clinical characteristics: gender, age, BMI, dialysis vintage, vascular acces, cardiovascular comorbidity (cardiomyopathy, ischemic cardiac disease, peripheral artery disease, heart valve disease), number and type of antihypertensive drugs, weekly dose of erythropoesis - stimulating agent, standard monthly, three and six months laboratoiy analyzes, and sp Kt/V and PCR. Statistical analysis was performed using the statistical software SPSS 17.0. hi both groups men were predominant (IDH group 88.23%, control group 64.07%). The IDH group was older (59.00 ± 7.64 versus 49.00 ± 13.91, p = 0.314) and with lower BMI (p = 0.246) compared to the control group. The DDH patients had significantly lower serum sodium and higher sodium gradient (135.75 ± 2.03 versus 137.33 ± 1.97, p = 0.042; 2.25 ± 1.98 versus 0.66 �

Behavioural Pattern of Causality Parameter of Autoregressive ...

African Journals Online (AJOL)

In this paper, a causal form of Autoregressive Moving Average process, ARMA (p, q) of various orders and behaviour of the causality parameter of ARMA model is investigated. It is deduced that the behaviour of causality parameter ψi depends on positive and negative values of autoregressive parameter φ and moving ...

Tachyons and causal paradoxes

International Nuclear Information System (INIS)

Maund, J.B.

1979-01-01

Although the existence of tachyons is not ruled out by special relativity, it appears that causal paradoxes will arise if there are tachyons. The usual solutions to these paradoxes employ some form of the reinterpretation principle. In this paper it is argued first that, the principle is incoherent, second, that even if it is not, some causal paradoxes remain, and third, the most plausible ''solution,'' which appeals to boundary conditions of the universe, will conflict with special relativity

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

Directory of Open Access Journals (Sweden)

York eHagmayer

2014-11-01

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

Using k-dependence causal forest to mine the most significant dependency relationships among clinical variables for thyroid disease diagnosis.

Directory of Open Access Journals (Sweden)

LiMin Wang

Full Text Available Numerous data mining models have been proposed to construct computer-aided medical expert systems. Bayesian network classifiers (BNCs are more distinct and understandable than other models. To graphically describe the dependency relationships among clinical variables for thyroid disease diagnosis and ensure the rationality of the diagnosis results, the proposed k-dependence causal forest (KCF model generates a series of submodels in the framework of maximum spanning tree (MST and demonstrates stronger dependence representation. Friedman test on 12 UCI datasets shows that KCF has classification accuracy advantage over the other state-of-the-art BNCs, such as Naive Bayes, tree augmented Naive Bayes, and k-dependence Bayesian classifier. Our extensive experimental comparison on 4 medical datasets also proves the feasibility and effectiveness of KCF in terms of sensitivity and specificity.

Linear causal modeling with structural equations

CERN Document Server

Mulaik, Stanley A

2009-01-01

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

Identity, causality, and pronoun ambiguity.

Science.gov (United States)

Sagi, Eyal; Rips, Lance J

2014-10-01

This article looks at the way people determine the antecedent of a pronoun in sentence pairs, such as: Albert invited Ron to dinner. He spent hours cleaning the house. The experiment reported here is motivated by the idea that such judgments depend on reasoning about identity (e.g., the identity of the he who cleaned the house). Because the identity of an individual over time depends on the causal-historical path connecting the stages of the individual, the correct antecedent will also depend on causal connections. The experiment varied how likely it is that the event of the first sentence (e.g., the invitation) would cause the event of the second (the house cleaning) for each of the two individuals (the likelihood that if Albert invited Ron to dinner, this would cause Albert to clean the house, versus cause Ron to clean the house). Decisions about the antecedent followed causal likelihood. A mathematical model of causal identity accounted for most of the key aspects of the data from the individual sentence pairs. Copyright © 2014 Cognitive Science Society, Inc.

Clinical and Socio-Demographic Characteristic of Children who ...

African Journals Online (AJOL)

Clinical and Socio-Demographic Characteristic of Children who receive Emergency Blood Transfusion in Orlu, Imo State Nigeria. ... Malaria was the commonest case of severe anaemia requiring urgent blood transfusion either singly (52.8%) ...

A Causal Theory of Modality

Directory of Open Access Journals (Sweden)

José Tomás Alvarado

2009-08-01

Full Text Available This work presents a causal conception of metaphysical modality in which a state of affairs is metaphysically possible if and only if it can be caused (in the past, the present or the future by current entities. The conception is contrasted with what is called the “combinatorial” conception of modality, in which everything can co-exist with anything else. This work explains how the notion of ‘causality’ should be construed in the causal theory, what difference exists between modalities thus defined from nomological modality, how accessibility relations between possible worlds should be interpreted, and what is the relation between the causal conception and the necessity of origin.

Causal reasoning with mental models

Science.gov (United States)

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

2014-01-01

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

Causal reasoning with mental models.

Science.gov (United States)

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

2014-01-01

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

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.

Foundational perspectives on causality in large-scale brain networks

Science.gov (United States)

Mannino, Michael; Bressler, Steven L.

2015-12-01

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

Clinical characteristics and outcomes of familial and idiopathic ...

African Journals Online (AJOL)

Clinical characteristics and outcomes of familial and idiopathic dilated cardiomyopathy in Cape Town: A comparative study of 120 cases followed up over 14 years. NBA Ntusi, M Badri, F Gumedze, A Wonkam, BM Mayosi ...

Heterogeneous Causal Effects and Sample Selection Bias

DEFF Research Database (Denmark)

Breen, Richard; Choi, Seongsoo; Holm, Anders

2015-01-01

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

The influence of farmer demographic characteristics on environmental behaviour: a review.

Science.gov (United States)

Burton, Rob J F

2014-03-15

Many agricultural studies have observed a relationship between farmer demographic characteristics and environmental behaviours. These relationships are frequently employed in the construction of models, the identification of farmer types, or as part of more descriptive analyses aimed at understanding farmers' environmental behaviour. However, they have also often been found to be inconsistent or contradictory. Although a considerable body of literature has built up around the subject area, research has a tendency to focus on factors such as the direction, strength and consistency of the relationship - leaving the issue of causality largely to speculation. This review addresses this gap by reviewing literature on 4 key demographic variables: age, experience, education, and gender for hypothesised causal links. Overall the review indicates that the issue of causality is a complex one. Inconsistent relationships can be attributed to the presence of multiple causal pathways, the role of scheme factors in determining which pathway is important, inadequately specified measurements of demographic characteristics, and the treatment of non-linear causalities as linear. In addition, all demographic characteristics were perceived to be influenced (to varying extents) by cultural-historical patterns leading to cohort effects or socialised differences in the relationship with environmental behaviour. The paper concludes that more work is required on the issue of causality. Copyright © 2013 Elsevier Ltd. All rights reserved.

Comorbid Depressive Disorders in Anxiety-Disordered Youth: Demographic, Clinical, and Family Characteristics

Science.gov (United States)

O'Neil, Kelly A.; Podell, Jennifer L.; Benjamin, Courtney L.; Kendall, Philip C.

2010-01-01

Research indicates that depression and anxiety are highly comorbid in youth. Little is known, however, about the clinical and family characteristics of youth with principal anxiety disorders and comorbid depressive diagnoses. The present study examined the demographic, clinical, and family characteristics of 200 anxiety-disordered children and…

Entanglement entropy in causal set theory

Science.gov (United States)

Sorkin, Rafael D.; Yazdi, Yasaman K.

2018-04-01

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. Formulating a notion of entanglement entropy in a causal set is not straightforward because the type of canonical hypersurface-data on which its definition typically relies is not available. Instead, we appeal to the more global expression given in Sorkin (2012 (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 (its ‘Wightman function’ W(x, x') ). Carrying this formula over to the causal set, one obtains an entropy which is both finite and of a Lorentz invariant nature. We evaluate this global entropy-expression numerically for certain regions (primarily order-intervals or ‘causal diamonds’) within causal sets of 1  +  1 dimensions. For the causal-set counterpart of the entanglement entropy, we obtain, in the first instance, a result that follows a (spacetime) volume law instead of the expected (spatial) area law. We find, however, that one obtains an area law if one truncates the commutator function (‘Pauli–Jordan operator’) and the Wightman function by projecting out the eigenmodes of the Pauli–Jordan operator whose eigenvalues are too close to zero according to a geometrical criterion which we describe more fully below. In connection with these results and the questions they raise, we also study the ‘entropy of coarse-graining’ generated by thinning out the causal set, and we compare it with what one obtains by similarly thinning out a chain of harmonic oscillators, finding the same, ‘universal’ behaviour in both cases.

Preschoolers prefer to learn causal information

Directory of Open Access Journals (Sweden)

Aubry eAlvarez

2015-02-01

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

Understanding how pain education causes changes in pain and disability: protocol for a causal mediation analysis of the PREVENT trial.

Science.gov (United States)

Lee, Hopin; Moseley, G Lorimer; Hübscher, Markus; Kamper, Steven J; Traeger, Adrian C; Skinner, Ian W; McAuley, James H

2015-07-01

Pain education is a complex intervention developed to help clinicians manage low back pain. Although complex interventions are usually evaluated by their effects on outcomes, such as pain or disability, most do not directly target these outcomes; instead, they target intermediate factors that are presumed to be associated with the outcomes. The mechanisms underlying treatment effects, or the effect of an intervention on an intermediate factor and its subsequent effect on outcome, are rarely investigated in clinical trials. This leaves a gap in the evidence for understanding how treatments exert their effects on outcomes. Mediation analysis provides a method for identifying and quantifying the mechanisms that underlie interventions. To determine whether the effect of pain education on pain and disability is mediated by changes in self-efficacy, catastrophisation and back pain beliefs. Causal mediation analysis of the PREVENT randomised controlled trial. Two hundred and two participants with acute low back pain from primary care clinics in the Sydney metropolitan area. Participants will be randomised to receive either 'pain education' (intervention group) or 'sham education' (control group). All outcome measures (including patient characteristics), primary outcome measures (pain and disability), and putative mediating variables (self-efficacy, catastrophisation and back pain beliefs) will be measured prior to randomisation. Putative mediators and primary outcome measures will be measured 1 week after the intervention, and primary outcome measures will be measured 3 months after the onset of low back pain. Causal mediation analysis under the potential outcomes framework will be used to test single and multiple mediator models. A sensitivity analysis will be conducted to evaluate the robustness of the estimated mediation effects on the influence of violating sequential ignorability--a critical assumption for causal inference. Mediation analysis of clinical trials can

Anxiety among Adolescents : Measurement, Clinical Characteristics, and Influences of Parenting and Genetics

OpenAIRE

Olofsdotter, Susanne

2017-01-01

Anxiety is the most commonly reported mental health problem among adolescents. Still, many adolescents in need of treatment are not detected and the clinical characteristics and etiological pathways of adolescent anxiety are under-researched topics. This thesis examined the clinical utility of the Swedish versions of the Spence Children’s Anxiety Scale (SCAS) and the clinical characteristics of multiple anxiety disorders among psychiatrically referred adolescents, and the influence of parenti...

Mathematical implications of Einstein-Weyl causality

International Nuclear Information System (INIS)

Borchers, H.J.; Sen, R.N.

2006-01-01

The present work is the first systematic attempt at answering the following fundamental question: what mathematical structures does Einstein-Weyl causality impose on a point-set that has no other previous structure defined on it? The authors propose an axiomatization of Einstein-Weyl causality (inspired by physics), and investigate the topological and uniform structures that it implies. Their final result is that a causal space is densely embedded in one that is locally a differentiable manifold. The mathematical level required of the reader is that of the graduate student in mathematical physics. (orig.)

Causality violation, gravitational shockwaves and UV completion

Energy Technology Data Exchange (ETDEWEB)

Hollowood, Timothy J.; Shore, Graham M. [Department of Physics, Swansea University,Swansea, SA2 8PP (United Kingdom)

2016-03-18

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 how the resulting causality problems emerge and are resolved in a two-shockwave time machine scenario. The implications of our results for ultra-high (Planck) energy scattering, in which graviton exchange is modelled by the shockwave background, are highlighted.

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.

The clinical characteristics of the radiation pneumonia

International Nuclear Information System (INIS)

Zhang Fuzheng; Wang Mingzhi; Chen Jianjiang; Wang Zhongxiang; Mao Yongjie

2000-01-01

Objective: To analyse the clinical characteristics of the radiation pneumonia, sum the experience and the basis of the radiation pneumonia for its prevention and treatment. Method: Twenty three cases with radiation pneumonia from 1991 to 1998 were retrospectively analysed. Its clinical manifestation, chest X-ray, thoracic CT and blood routine were evaluated. Result: The acute manifestation was fever, cough, dyspnea, and the chronic manifestation was cough and insufficiency of pulmonary function. Conclusion: The prevention of radiation pneumonia is more important, high dose cortical steroids and antibiotics were prescribed during the acute stage and the chronic radiation pneumonia is irreversible

Quasi-Experimental Designs for Causal Inference

Science.gov (United States)

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…

Gravity and matter in causal set theory

International Nuclear Information System (INIS)

Sverdlov, Roman; Bombelli, Luca

2009-01-01

The goal of this paper is to propose an approach to the formulation of dynamics for causal sets and coupled matter fields. We start from the continuum version of the action for a Klein-Gordon field coupled to gravity, and rewrite it first using quantities that have a direct correspondent in the case of a causal set, namely volumes, causal relations and timelike lengths, as variables to describe the geometry. In this step, the local Lagrangian density L(f;x) for a set of fields f is recast into a quasilocal expression L 0 (f;p,q) that depends on pairs of causally related points pprq and is a function of the values of f in the Alexandrov set defined by those points, and whose limit as p and q approach a common point x is L(f;x). We then describe how to discretize L 0 (f;p,q) and use it to define a causal-set-based action.

Bayesian methods for meta-analysis of causal relationships estimated using genetic instrumental variables

DEFF Research Database (Denmark)

Burgess, Stephen; Thompson, Simon G; Thompson, Grahame

2010-01-01

Genetic markers can be used as instrumental variables, in an analogous way to randomization in a clinical trial, to estimate the causal relationship between a phenotype and an outcome variable. Our purpose is to extend the existing methods for such Mendelian randomization studies to the context o...

Causal theory in (2+1)-dimensional Qed

International Nuclear Information System (INIS)

Scharf, G.; Wreszinski, W.F.

1994-01-01

The program of constructing the S-matrix by means of causality in quantum field theory goes back to Stueckelberg and Bogoliubov. Epstein and Glaser proposed an axiomatic construct where ultraviolet divergences do not appear, leading directly to the renormalized perturbation series. They have shown that in the causal theory the UV problem is a consequence of incorrect distribution splitting. This paper studies the causal theory in (2+1)D Qed

Sydenham's chorea: clinical and evolutive characteristics

OpenAIRE

Terreri, Maria Teresa Ramos Ascensão [UNIFESP; Roja, Suzana Campos [UNIFESP; Len, Claudio Arnaldo [UNIFESP; Faustino, Patricia Corte [UNIFESP; Roberto, Adriana Madureira [UNIFESP; Hilário, Maria Odete Esteves [UNIFESP

2002-01-01

CONTEXT: During the last 12 years we have observed an increase in the frequency of Sydenham's chorea in our country. We have observed that some of our patients have presented recurrence of the chorea despite regular treatment with benzathine penicillin. OBJECTIVE: The aim of our study was to evaluate clinical and evolutive characteristics of Sydenham's chorea in a group of patients followed in our Pediatric Rheumatology Unit. TYPE OF STUDY: Retrospective study. SETTING: Section of Pediatric R...

How multiple causes combine: independence constraints on causal inference.

Science.gov (United States)

Liljeholm, Mimi

2015-01-01

According to the causal power view, two core constraints-that causes occur independently (i.e., no confounding) and influence their effects independently-serve as boundary conditions for causal induction. This study investigated how violations of these constraints modulate uncertainty about the existence and strength of a causal relationship. Participants were presented with pairs of candidate causes that were either confounded or not, and that either interacted or exerted their influences independently. Consistent with the causal power view, uncertainty about the existence and strength of causal relationships was greater when causes were confounded or interacted than when unconfounded and acting independently. An elemental Bayesian causal model captured differences in uncertainty due to confounding but not those due to an interaction. Implications of distinct sources of uncertainty for the selection of contingency information and causal generalization are discussed.

The mistake of the causal relationship

Directory of Open Access Journals (Sweden)

О. Д. Комаров

2015-03-01

Full Text Available The article deals with issues of the mistake of the causal relationship. The modern criminal law science approaches to the content of the mistake of the causal relationship and its significance to the qualification of the crime are described. It is proved that in cases of dolus generalis different mental attitude of the guilty person to two separate acts of his conduct exist. Consequently, in mentioned above cases mistake of the causal relationship does not have place. The rules of qualification of the crimes commited with the mistake of causation and in cases of dolus generalis are proposed .

Causal transfer function analysis to describe closed loop interactions between cardiovascular and cardiorespiratory variability signals.

Science.gov (United States)

Faes, L; Porta, A; Cucino, R; Cerutti, S; Antolini, R; Nollo, G

2004-06-01

Although the concept of transfer function is intrinsically related to an input-output relationship, the traditional and widely used estimation method merges both feedback and feedforward interactions between the two analyzed signals. This limitation may endanger the reliability of transfer function analysis in biological systems characterized by closed loop interactions. In this study, a method for estimating the transfer function between closed loop interacting signals was proposed and validated in the field of cardiovascular and cardiorespiratory variability. The two analyzed signals x and y were described by a bivariate autoregressive model, and the causal transfer function from x to y was estimated after imposing causality by setting to zero the model coefficients representative of the reverse effects from y to x. The method was tested in simulations reproducing linear open and closed loop interactions, showing a better adherence of the causal transfer function to the theoretical curves with respect to the traditional approach in presence of non-negligible reverse effects. It was then applied in ten healthy young subjects to characterize the transfer functions from respiration to heart period (RR interval) and to systolic arterial pressure (SAP), and from SAP to RR interval. In the first two cases, the causal and non-causal transfer function estimates were comparable, indicating that respiration, acting as exogenous signal, sets an open loop relationship upon SAP and RR interval. On the contrary, causal and traditional transfer functions from SAP to RR were significantly different, suggesting the presence of a considerable influence on the opposite causal direction. Thus, the proposed causal approach seems to be appropriate for the estimation of parameters, like the gain and the phase lag from SAP to RR interval, which have a large clinical and physiological relevance.

Morphological and Molecular Identification of the Causal Agent of Anthracnose Disease of Avocado in Kenya.

Science.gov (United States)

Kimaru, S K; Monda, E; Cheruiyot, R C; Mbaka, J; Alakonya, A

2018-01-01

Anthracnose disease of avocado contributes to a huge loss of avocado fruits due to postharvest rot in Kenya. The causal agent of this disease has not been clear but presumed to be Colletotrichum gloeosporioides as reported in other regions where avocado is grown. The fungus mainly infects fruits causing symptoms such as small blackish spots, "pepper spots," and black spots with raised margin which coalesce as infection progresses. Due to economic losses associated with the disease and emerging information of other species of fungi as causal agents of the disease, this study was aimed at identifying causal agent(s) of the disease. A total of 80 fungal isolates were collected from diseased avocado fruits in Murang'a County, the main avocado growing region in Kenya. Forty-six isolates were morphologically identified as Colletotrichum spp. based on their cultural characteristics, mainly whitish, greyish, and creamish colour and cottony/velvety mycelia on the top side of the culture and greyish cream with concentric zonation on the reverse side. Their spores were straight with rounded end and nonseptate. Thirty-four isolates were identified as Pestalotiopsis spp. based on their cultural characteristics: whitish grey mycelium with black fruiting structure on the upper side and greyish black one on the lower side and septate spores with 3-4 septa and 2 or 3 appendages at one end. Further molecular studies using ITS indicated Colletotrichum gloeosporioides , Colletotrichum boninense , and Pestalotiopsis microspora as the causal agents of anthracnose disease in avocado. However, with this being the first report, there is a need to conduct further studies to establish whether there is coinfection or any interaction thereof.

Morphological and Molecular Identification of the Causal Agent of Anthracnose Disease of Avocado in Kenya

Directory of Open Access Journals (Sweden)

S. K. Kimaru

2018-01-01

Full Text Available Anthracnose disease of avocado contributes to a huge loss of avocado fruits due to postharvest rot in Kenya. The causal agent of this disease has not been clear but presumed to be Colletotrichum gloeosporioides as reported in other regions where avocado is grown. The fungus mainly infects fruits causing symptoms such as small blackish spots, “pepper spots,” and black spots with raised margin which coalesce as infection progresses. Due to economic losses associated with the disease and emerging information of other species of fungi as causal agents of the disease, this study was aimed at identifying causal agent(s of the disease. A total of 80 fungal isolates were collected from diseased avocado fruits in Murang’a County, the main avocado growing region in Kenya. Forty-six isolates were morphologically identified as Colletotrichum spp. based on their cultural characteristics, mainly whitish, greyish, and creamish colour and cottony/velvety mycelia on the top side of the culture and greyish cream with concentric zonation on the reverse side. Their spores were straight with rounded end and nonseptate. Thirty-four isolates were identified as Pestalotiopsis spp. based on their cultural characteristics: whitish grey mycelium with black fruiting structure on the upper side and greyish black one on the lower side and septate spores with 3-4 septa and 2 or 3 appendages at one end. Further molecular studies using ITS indicated Colletotrichum gloeosporioides, Colletotrichum boninense, and Pestalotiopsis microspora as the causal agents of anthracnose disease in avocado. However, with this being the first report, there is a need to conduct further studies to establish whether there is coinfection or any interaction thereof.

Causal independence between energy consumption and economic growth in Liberia: Evidence from a non-parametric bootstrapped causality test

International Nuclear Information System (INIS)

Wesseh, Presley K.; Zoumara, Babette

2012-01-01

This contribution investigates causal interdependence between energy consumption and economic growth in Liberia and proposes application of a bootstrap methodology. To better reflect causality, employment is incorporated as additional variable. The study demonstrates evidence of distinct bidirectional Granger causality between energy consumption and economic growth. Additionally, the results show that employment in Liberia Granger causes economic growth and apply irrespective of the short-run or long-run. Evidence from a Monte Carlo experiment reveals that the asymptotic Granger causality test suffers size distortion problem for Liberian data, suggesting that the bootstrap technique employed in this study is more appropriate. Given the empirical results, implications are that energy expansion policies like energy subsidy or low energy tariff for instance, would be necessary to cope with demand exerted as a result of economic growth in Liberia. Furthermore, Liberia might have the performance of its employment generation on the economy partly determined by adequate energy. Therefore, it seems fully justified that a quick shift towards energy production based on clean energy sources may significantly slow down economic growth in Liberia. Hence, the government’s target to implement a long-term strategy to make Liberia a carbon neutral country, and eventually less carbon dependent by 2050 is understandable. - Highlights: ► Causality between energy consumption and economic growth in Liberia investigated. ► There is bidirectional causality between energy consumption and economic growth. ► Energy expansion policies are necessary to cope with demand from economic growth. ► Asymptotic Granger causality test suffers size distortion problem for Liberian data. ► The bootstrap methodology employed in our study is more appropriate.

On minimizers of causal variational principles

International Nuclear Information System (INIS)

Schiefeneder, Daniela

2011-01-01

Causal variational principles are a class of nonlinear minimization problems which arise in a formulation of relativistic quantum theory referred to as the fermionic projector approach. This thesis is devoted to a numerical and analytic study of the minimizers of a general class of causal variational principles. We begin with a numerical investigation of variational principles for the fermionic projector in discrete space-time. It is shown that for sufficiently many space-time points, the minimizing fermionic projector induces non-trivial causal relations on the space-time points. We then generalize the setting by introducing a class of causal variational principles for measures on a compact manifold. In our main result we prove under general assumptions that the support of a minimizing measure is either completely timelike, or it is singular in the sense that its interior is empty. In the examples of the circle, the sphere and certain flag manifolds, the general results are supplemented by a more detailed analysis of the minimizers. (orig.)

Consciousness and the "Causal Paradox"

OpenAIRE

Velmans, Max

1996-01-01

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

Clinical characteristics of keratosis obturans and external auditory canal cholesteatoma.

Science.gov (United States)

Park, So Young; Jung, Young Hoon; Oh, Jeong-Hoon

2015-02-01

Keratosis obturans (KO) and external auditory canal cholesteatoma (EACC) have been considered separate entities. While the disorders are distinct, they share many overlapping characteristics, making a correct diagnosis difficult. In the present study, we compared their clinical characteristics and radiological features to clarify the diagnostic criteria. Retrospective case series. Academic medical center. The clinical data of 23 cases of EACC and KO were retrospectively reviewed. The following clinical characteristics were compared between the 2 groups: sex, age, onset of symptoms, follow-up period, audiometric results, and imaging findings on temporal bone computed tomography including bilaterality, location, and the presence of extension to adjacent tissue. The mean age of the EACC group was significantly older than that of the KO group. All of the cases of EACC occurred unilaterally, and bilateral occurrences of KO were observed in 4 of 9 cases. All of the lesions in the KO group were circumferential, and no lesion in the EACC group invaded the superior canal wall. No significant differences in symptoms, such as acute otalgia, otorrhea, and hearing loss, were noted between the 2 groups. The incidence of conductive hearing impairment more than 10 dB was higher in the KO group than in the EACC group. Thus, KO and EACC are 2 distinct disease entities that share common features in clinical characteristics except for predominant age and bilaterality. Conservative treatment with meticulous cleaning of the lesion was successful in most cases with a long-term follow-up. © American Academy of Otolaryngology—Head and Neck Surgery Foundation 2014.

Identification and functional characterization of HIV-associated neurocognitive disorders with large-scale Granger causality analysis on resting-state functional MRI

Science.gov (United States)

Chockanathan, Udaysankar; DSouza, Adora M.; Abidin, Anas Z.; Schifitto, Giovanni; Wismüller, Axel

2018-02-01

Resting-state functional MRI (rs-fMRI), coupled with advanced multivariate time-series analysis methods such as Granger causality, is a promising tool for the development of novel functional connectivity biomarkers of neurologic and psychiatric disease. Recently large-scale Granger causality (lsGC) has been proposed as an alternative to conventional Granger causality (cGC) that extends the scope of robust Granger causal analyses to high-dimensional systems such as the human brain. In this study, lsGC and cGC were comparatively evaluated on their ability to capture neurologic damage associated with HIV-associated neurocognitive disorders (HAND). Functional brain network models were constructed from rs-fMRI data collected from a cohort of HIV+ and HIV- subjects. Graph theoretic properties of the resulting networks were then used to train a support vector machine (SVM) model to predict clinically relevant parameters, such as HIV status and neuropsychometric (NP) scores. For the HIV+/- classification task, lsGC, which yielded a peak area under the receiver operating characteristic curve (AUC) of 0.83, significantly outperformed cGC, which yielded a peak AUC of 0.61, at all parameter settings tested. For the NP score regression task, lsGC, with a minimum mean squared error (MSE) of 0.75, significantly outperformed cGC, with a minimum MSE of 0.84 (p < 0.001, one-tailed paired t-test). These results show that, at optimal parameter settings, lsGC is better able to capture functional brain connectivity correlates of HAND than cGC. However, given the substantial variation in the performance of the two methods at different parameter settings, particularly for the regression task, improved parameter selection criteria are necessary and constitute an area for future research.

Causal inference in biology networks with integrated belief propagation.

Science.gov (United States)

Chang, Rui; Karr, Jonathan R; Schadt, Eric E

2015-01-01

Inferring causal relationships among molecular and higher order phenotypes is a critical step in elucidating the complexity of living systems. Here we propose a novel method for inferring causality that is no longer constrained by the conditional dependency arguments that limit the ability of statistical causal inference methods to resolve causal relationships within sets of graphical models that are Markov equivalent. Our method utilizes Bayesian belief propagation to infer the responses of perturbation events on molecular traits given a hypothesized graph structure. A distance measure between the inferred response distribution and the observed data is defined to assess the 'fitness' of the hypothesized causal relationships. To test our algorithm, we infer causal relationships within equivalence classes of gene networks in which the form of the functional interactions that are possible are assumed to be nonlinear, given synthetic microarray and RNA sequencing data. We also apply our method to infer causality in real metabolic network with v-structure and feedback loop. We show that our method can recapitulate the causal structure and recover the feedback loop only from steady-state data which conventional method cannot.

Quasi-experiments to establish causal effects of HIV care and treatment and to improve the cascade of care

OpenAIRE

Bor, Jacob; Geldsetzer, Pascal; Venkataramani, Atheendar; B?rnighausen, Till

2015-01-01

Purpose of review Randomized, population-representative trials of clinical interventions are rare. Quasi-experiments have been used successfully to generate causal evidence on the cascade of HIV care in a broad range of real-world settings. Recent findings Quasi-experiments exploit exogenous, or quasi-random, variation occurring naturally in the world or because of an administrative rule or policy change to estimate causal effects. Well designed quasi-experiments have greater internal validit...

Quantifying the improvement in sepsis diagnosis, documentation, and coding: the marginal causal effect of year of hospitalization on sepsis diagnosis.

Science.gov (United States)

Jafarzadeh, S Reza; Thomas, Benjamin S; Marschall, Jonas; Fraser, Victoria J; Gill, Jeff; Warren, David K

2016-01-01

To quantify the coinciding improvement in the clinical diagnosis of sepsis, its documentation in the electronic health records, and subsequent medical coding of sepsis for billing purposes in recent years. We examined 98,267 hospitalizations in 66,208 patients who met systemic inflammatory response syndrome criteria at a tertiary care center from 2008 to 2012. We used g-computation to estimate the causal effect of the year of hospitalization on receiving an International Classification of Diseases, Ninth Revision, Clinical Modification discharge diagnosis code for sepsis by estimating changes in the probability of getting diagnosed and coded for sepsis during the study period. When adjusted for demographics, Charlson-Deyo comorbidity index, blood culture frequency per hospitalization, and intensive care unit admission, the causal risk difference for receiving a discharge code for sepsis per 100 hospitalizations with systemic inflammatory response syndrome, had the hospitalization occurred in 2012, was estimated to be 3.9% (95% confidence interval [CI], 3.8%-4.0%), 3.4% (95% CI, 3.3%-3.5%), 2.2% (95% CI, 2.1%-2.3%), and 0.9% (95% CI, 0.8%-1.1%) from 2008 to 2011, respectively. Patients with similar characteristics and risk factors had a higher of probability of getting diagnosed, documented, and coded for sepsis in 2012 than in previous years, which contributed to an apparent increase in sepsis incidence. Copyright © 2016 Elsevier Inc. All rights reserved.

Information causality from an entropic and a probabilistic perspective

International Nuclear Information System (INIS)

Al-Safi, Sabri W.; Short, Anthony J.

2011-01-01

The information causality principle is a generalization of the no-signaling principle which implies some of the known restrictions on quantum correlations. But despite its clear physical motivation, information causality is formulated in terms of a rather specialized game and figure of merit. We explore different perspectives on information causality, discussing the probability of success as the figure of merit, a relation between information causality and the nonlocal ''inner-product game,'' and the derivation of a quadratic bound for these games. We then examine an entropic formulation of information causality with which one can obtain the same results, arguably in a simpler fashion.

Causal Mediation Analysis: Warning! Assumptions Ahead

Science.gov (United States)

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…

How to Be Causal: Time, Spacetime and Spectra

Science.gov (United States)

Kinsler, Paul

2011-01-01

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

On the road toward formal reasoning: reasoning with factual causal and contrary-to-fact causal premises during early adolescence.

Science.gov (United States)

Markovits, Henry

2014-12-01

Understanding the development of conditional (if-then) reasoning is critical for theoretical and educational reasons. Here we examined the hypothesis that there is a developmental transition between reasoning with true and contrary-to-fact (CF) causal conditionals. A total of 535 students between 11 and 14 years of age received priming conditions designed to encourage use of either a true or CF alternatives generation strategy and reasoning problems with true causal and CF causal premises (with counterbalanced order). Results show that priming had no effect on reasoning with true causal premises. By contrast, priming with CF alternatives significantly improved logical reasoning with CF premises. Analysis of the effect of order showed that reasoning with CF premises reduced logical responding among younger students but had no effect among older students. Results support the idea that there is a transition in the reasoning processes in this age range associated with the nature of the alternatives generation process required for logical reasoning with true and CF causal conditionals. Copyright © 2014 Elsevier Inc. All rights reserved.

BOLD Granger causality reflects vascular anatomy.

Directory of Open Access Journals (Sweden)

J Taylor Webb

Full Text Available A number of studies have tried to exploit subtle phase differences in BOLD time series to resolve the order of sequential activation of brain regions, or more generally the ability of signal in one region to predict subsequent signal in another region. More recently, such lag-based measures have been applied to investigate directed functional connectivity, although this application has been controversial. We attempted to use large publicly available datasets (FCON 1000, ADHD 200, Human Connectome Project to determine whether consistent spatial patterns of Granger Causality are observed in typical fMRI data. For BOLD datasets from 1,240 typically developing subjects ages 7-40, we measured Granger causality between time series for every pair of 7,266 spherical ROIs covering the gray matter and 264 seed ROIs at hubs of the brain's functional network architecture. Granger causality estimates were strongly reproducible for connections in a test and replication sample (n=620 subjects for each group, as well as in data from a single subject scanned repeatedly, both during resting and passive video viewing. The same effect was even stronger in high temporal resolution fMRI data from the Human Connectome Project, and was observed independently in data collected during performance of 7 task paradigms. The spatial distribution of Granger causality reflected vascular anatomy with a progression from Granger causality sources, in Circle of Willis arterial inflow distributions, to sinks, near large venous vascular structures such as dural venous sinuses and at the periphery of the brain. Attempts to resolve BOLD phase differences with Granger causality should consider the possibility of reproducible vascular confounds, a problem that is independent of the known regional variability of the hemodynamic response.

The causal structure of utility conditionals.

Science.gov (United States)

Bonnefon, Jean-François; Sloman, Steven A

2013-01-01

The psychology of reasoning is increasingly considering agents' values and preferences, achieving greater integration with judgment and decision making, social cognition, and moral reasoning. Some of this research investigates utility conditionals, ''if p then q'' statements where the realization of p or q or both is valued by some agents. Various approaches to utility conditionals share the assumption that reasoners make inferences from utility conditionals based on the comparison between the utility of p and the expected utility of q. This article introduces a new parameter in this analysis, the underlying causal structure of the conditional. Four experiments showed that causal structure moderated utility-informed conditional reasoning. These inferences were strongly invited when the underlying structure of the conditional was causal, and significantly less so when the underlying structure of the conditional was diagnostic. This asymmetry was only observed for conditionals in which the utility of q was clear, and disappeared when the utility of q was unclear. Thus, an adequate account of utility-informed inferences conditional reasoning requires three components: utility, probability, and causal structure. Copyright © 2012 Cognitive Science Society, Inc.

Entanglement, holography and causal diamonds

Science.gov (United States)

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

2016-08-01

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

Entanglement, holography and causal diamonds

Energy Technology Data Exchange (ETDEWEB)

Boer, Jan de [Institute of Physics, Universiteit van Amsterdam,Science Park 904, 1090 GL Amsterdam (Netherlands); Haehl, Felix M. [Centre for Particle Theory & Department of Mathematical Sciences, Durham University,South Road, Durham DH1 3LE (United Kingdom); Heller, Michal P.; Myers, Robert C. [Perimeter Institute for Theoretical Physics,31 Caroline Street North, Waterloo, Ontario N2L 2Y5 (Canada)

2016-08-29

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 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.

The clinical characteristics of twenty-eight idiopathic pulmonary fibrosis cases

International Nuclear Information System (INIS)

Yu Yong; Shi Minhua; Hu Huacheng

2007-01-01

Objective: To summarize the clinical characteristics of idiopathic pulmonary fibrosis (IPF). Methods: The clinical characteristics of twenty-eight cases diagnosed as IPF between 1991 and 2006 were studied retrospectively. Results: Most IPF patients had an insidious onset of progressive dyspnea and non-productive cough. Inspiratory crackles and finger clubbing were also noted in most patients. The most impressive appearance of their radiography was peripheral reticular and nodular opacities, distributed largely at the lung bases. Pulmonary function test showed restrictive impairment and impaired oxygen diffusion. The arterial blood gas analysis revealed type I respiratory failure. One IPF case was complicated with lung cancer. The symptoms of fifteen cases(71.4%) were relieved under the therapy with glucocorticoid. Seven patients died as yet in our group and the middle duration was 24 months. Conclusions: The diagnosis of IPF relies mostly on the clinical characteristics, radiography, pulmonary function test, blood gas analysis and exclusion of other ILD. Atypical cases need lung biopsy to do further the diagnosis. Therapy with glucocorticoid may be effective in some cases. Prognosis in IPF cases complicated with lung cancer is poor. (authors)

Detectability of Granger causality for subsampled continuous-time neurophysiological processes.

Science.gov (United States)

Barnett, Lionel; Seth, Anil K

2017-01-01

Granger causality is well established within the neurosciences for inference of directed functional connectivity from neurophysiological data. These data usually consist of time series which subsample a continuous-time biophysiological process. While it is well known that subsampling can lead to imputation of spurious causal connections where none exist, less is known about the effects of subsampling on the ability to reliably detect causal connections which do exist. We present a theoretical analysis of the effects of subsampling on Granger-causal inference. Neurophysiological processes typically feature signal propagation delays on multiple time scales; accordingly, we base our analysis on a distributed-lag, continuous-time stochastic model, and consider Granger causality in continuous time at finite prediction horizons. Via exact analytical solutions, we identify relationships among sampling frequency, underlying causal time scales and detectability of causalities. We reveal complex interactions between the time scale(s) of neural signal propagation and sampling frequency. We demonstrate that detectability decays exponentially as the sample time interval increases beyond causal delay times, identify detectability "black spots" and "sweet spots", and show that downsampling may potentially improve detectability. We also demonstrate that the invariance of Granger causality under causal, invertible filtering fails at finite prediction horizons, with particular implications for inference of Granger causality from fMRI data. Our analysis emphasises that sampling rates for causal analysis of neurophysiological time series should be informed by domain-specific time scales, and that state-space modelling should be preferred to purely autoregressive modelling. On the basis of a very general model that captures the structure of neurophysiological processes, we are able to help identify confounds, and offer practical insights, for successful detection of causal connectivity

Analyzing clinical and electrophysiological characteristics of Paroxysmal Dyskinesia

Directory of Open Access Journals (Sweden)

Jue-qian Zhou

2011-01-01

Full Text Available The classification, clinical and electrophysiological characteristics, treatment outcome and pathogenesis of paroxysmal dyskinesia were summarized and analyzed. Paroxysmal dyskinesia was classified into three types. Different types had different incentives in clinical practice. Patients were mostly male adolescents, and the attacks, which were in various forms, manifested as dysmyotonia of choreoathetosis, body torsion and facemaking; no disturbance of consciousness during attacks. Electroencephalogram and other examinations showed no specific abnormalities during both the attacks and interictal period. Paroxysmal dyskinesia was an independent disease and different from epilepsy.

Dual Causality and the Autonomy of Biology.

Science.gov (United States)

Bock, Walter J

2017-03-01

Ernst Mayr's concept of dual causality in biology with the two forms of causes (proximate and ultimate) continues to provide an essential foundation for the philosophy of biology. They are equivalent to functional (=proximate) and evolutionary (=ultimate) causes with both required for full biological explanations. The natural sciences can be classified into nomological, historical nomological and historical dual causality, the last including only biology. Because evolutionary causality is unique to biology and must be included for all complete biological explanations, biology is autonomous from the physical sciences.

Can chance cause cancer? A causal consideration.

Science.gov (United States)

Stensrud, Mats Julius; Strohmaier, Susanne; Valberg, Morten; Aalen, Odd Olai

2017-04-01

The role of randomness, environment and genetics in cancer development is debated. We approach the discussion by using the potential outcomes framework for causal inference. By briefly considering the underlying assumptions, we suggest that the antagonising views arise due to estimation of substantially different causal effects. These effects may be hard to interpret, and the results cannot be immediately compared. Indeed, it is not clear whether it is possible to define a causal effect of chance at all. Copyright © 2017 Elsevier Ltd. All rights reserved.

Clinical and Biochemical Characteristics of Children with Juvenile Idiopathic Arthritis

International Nuclear Information System (INIS)

Ahmed, S.; Ali, S. R.; Ishaque, S.

2014-01-01

Objective: To determine the clinical and biochemical characteristics of children with Juvenile Idiopathic Arthritis (JIA) at a tertiary care centre in Karachi, Pakistan. Study Design: A descriptive study. Place and Duration of Study: Paediatric Rheumatology Clinic of The Aga Khan University Hospital (AKUH), Karachi, from January 2008 to December 2011. Methodology: Clinical and laboratory profile and outcome of children less than 15 years of age attending the Paediatric Rheumatology Clinic of the Aga Khan University, Karachi with the diagnosis of Juvenile Idiopathic Arthritis according to International League against Rheumatism were studied. These children were classified into different types of JIA; their clinical and laboratory characteristics, response to therapy and outcome was evaluated. Results: Sixty eight patients satisfying the criteria of International League against Rheumatism (ILAR) for Juvenile Idiopathic Arthritis were enrolled during the study period of four consecutive years, their age ranged from 9 months to 15 years. Mean age at onset was 6.45 +- 4.03 years while mean age at diagnosis was 7.60 +- 3.93 years. Polyarticular was the most predominant subtype with 37 (54%) patients, out of these, 9 (24%) were rheumatoid factor positive. An almost equal gender predisposition was observed. Fever and arthritis were the most common presenting symptoms, with only 2 patients presenting with uveitis. Conclusion: The clinico-biochemical characteristics of JIA at the study centre showed a pattern distinct with early onset of disease, high frequency of polyarticular type and a higher rheumatoid factor (QRA) and ANA positivity in girls. (author)

Determining Directional Dependency in Causal Associations

Science.gov (United States)

Pornprasertmanit, Sunthud; Little, Todd D.

2012-01-01

Directional dependency is a method to determine the likely causal direction of effect between two variables. This article aims to critique and improve upon the use of directional dependency as a technique to infer causal associations. We comment on several issues raised by von Eye and DeShon (2012), including: encouraging the use of the signs of…

Using published data in Mendelian randomization: a blueprint for efficient identification of causal risk factors.

Science.gov (United States)

Burgess, Stephen; Scott, Robert A; Timpson, Nicholas J; Davey Smith, George; Thompson, Simon G

2015-07-01

Finding individual-level data for adequately-powered Mendelian randomization analyses may be problematic. As publicly-available summarized data on genetic associations with disease outcomes from large consortia are becoming more abundant, use of published data is an attractive analysis strategy for obtaining precise estimates of the causal effects of risk factors on outcomes. We detail the necessary steps for conducting Mendelian randomization investigations using published data, and present novel statistical methods for combining data on the associations of multiple (correlated or uncorrelated) genetic variants with the risk factor and outcome into a single causal effect estimate. A two-sample analysis strategy may be employed, in which evidence on the gene-risk factor and gene-outcome associations are taken from different data sources. These approaches allow the efficient identification of risk factors that are suitable targets for clinical intervention from published data, although the ability to assess the assumptions necessary for causal inference is diminished. Methods and guidance are illustrated using the example of the causal effect of serum calcium levels on fasting glucose concentrations. The estimated causal effect of a 1 standard deviation (0.13 mmol/L) increase in calcium levels on fasting glucose (mM) using a single lead variant from the CASR gene region is 0.044 (95 % credible interval -0.002, 0.100). In contrast, using our method to account for the correlation between variants, the corresponding estimate using 17 genetic variants is 0.022 (95 % credible interval 0.009, 0.035), a more clearly positive causal effect.

Semmelweis's methodology from the modern stand-point: intervention studies and causal ontology.

Science.gov (United States)

Persson, Johannes

2009-09-01

Semmelweis's work predates the discovery of the power of randomization in medicine by almost a century. Although Semmelweis would not have consciously used a randomized controlled trial (RCT), some features of his material-the allocation of patients to the first and second clinics-did involve what was in fact a randomization, though this was not realised at the time. This article begins by explaining why Semmelweis's methodology, nevertheless, did not amount to the use of a RCT. It then shows why it is descriptively and normatively interesting to compare what he did with the modern approach using RCTs. The argumentation centres on causal inferences and the contrast between Semmelweis's causal concept and that deployed by many advocates of RCTs. It is argued that Semmelweis's approach has implications for matters of explanation and medical practice.

Causal strength induction from time series data.

Science.gov (United States)

Soo, Kevin W; Rottman, Benjamin M

2018-04-01

One challenge when inferring the strength of cause-effect relations from time series data is that the cause and/or effect can exhibit temporal trends. If temporal trends are not accounted for, a learner could infer that a causal relation exists when it does not, or even infer that there is a positive causal relation when the relation is negative, or vice versa. We propose that learners use a simple heuristic to control for temporal trends-that they focus not on the states of the cause and effect at a given instant, but on how the cause and effect change from one observation to the next, which we call transitions. Six experiments were conducted to understand how people infer causal strength from time series data. We found that participants indeed use transitions in addition to states, which helps them to reach more accurate causal judgments (Experiments 1A and 1B). Participants use transitions more when the stimuli are presented in a naturalistic visual format than a numerical format (Experiment 2), and the effect of transitions is not driven by primacy or recency effects (Experiment 3). Finally, we found that participants primarily use the direction in which variables change rather than the magnitude of the change for estimating causal strength (Experiments 4 and 5). Collectively, these studies provide evidence that people often use a simple yet effective heuristic for inferring causal strength from time series data. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

The Relevance of Causal Social Construction

Directory of Open Access Journals (Sweden)

Marques Teresa

2017-02-01

Full Text Available Social constructionist claims are surprising and interesting when they entail that presumably natural kinds are in fact socially constructed. The claims are interesting because of their theoretical and political importance. Authors like Díaz-León argue that constitutive social construction is more relevant for achieving social justice than causal social construction. This paper challenges this claim. Assuming there are socially salient groups that are discriminated against, the paper presents a dilemma: if there were no constitutively constructed social kinds, the causes of the discrimination of existing social groups would have to be addressed, and understanding causal social construction would be relevant to achieve social justice. On the other hand, not all possible constitutively socially constructed kinds are actual social kinds. If an existing social group is constitutively constructed as a social kind K, the fact that it actually exists as a K has social causes. Again, causal social construction is relevant. The paper argues that (i for any actual social kind X, if X is constitutively socially constructed as K, then it is also causally socially constructed; and (ii causal social construction is at least as relevant as constitutive social construction for concerns of social justice. For illustration, I draw upon two phenomena that are presumed to contribute towards the discrimination of women: (i the poor performance effects of stereotype threat, and (ii the silencing effects of gendered language use.

Selecting appropriate cases when tracing causal mechanisms

DEFF Research Database (Denmark)

Beach, Derek; Pedersen, Rasmus Brun

2016-01-01

The last decade has witnessed resurgence in the interest in studying the causal mechanisms linking causes and outcomes in the social sciences. This article explores the overlooked implications for case selection when tracing mechanisms using in-depth case studies. Our argument is that existing case...... selection guidelines are appropriate for research aimed at making cross-case claims about causal relationships, where case selection is primarily used to control for other causes. However, existing guidelines are not in alignment with case-based research that aims to trace mechanisms, where the goal...... is to unpack the causal mechanism between X and Y, enabling causal inferences to be made because empirical evidence is provided for how the mechanism actually operated in a particular case. The in-depth, within-case tracing of how mechanisms operate in particular cases produces what can be termed mechanistic...

Explaining quantum correlations through evolution of causal models

Science.gov (United States)

Harper, Robin; Chapman, Robert J.; Ferrie, Christopher; Granade, Christopher; Kueng, Richard; Naoumenko, Daniel; Flammia, Steven T.; Peruzzo, Alberto

2017-04-01

We propose a framework for the systematic and quantitative generalization of Bell's theorem using causal networks. We first consider the multiobjective optimization problem of matching observed data while minimizing the causal effect of nonlocal variables and prove an inequality for the optimal region that both strengthens and generalizes Bell's theorem. To solve the optimization problem (rather than simply bound it), we develop a genetic algorithm treating as individuals causal networks. By applying our algorithm to a photonic Bell experiment, we demonstrate the trade-off between the quantitative relaxation of one or more local causality assumptions and the ability of data to match quantum correlations.

Tachyon kinematics and causality: a systematic thorough analysis of the tachyon causal paradoxes

International Nuclear Information System (INIS)

Recami, E.

1987-01-01

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

Glaucoma and clinical characteristics in Vietnamese Americans.

Science.gov (United States)

Peng, Pai-Huei; Manivanh, Richard; Nguyen, Ngoc; Weinreb, Robert N; Lin, Shan C

2011-08-01

To assess the proportions of glaucoma types and clinical characteristics in Vietnamese Americans in a single-center, retrospective study. Medical charts of Vietnamese-American patients who visited a single private practice in Northern California from 1998-2007 were reviewed. The main outcome measures included the distribution and characteristics of glaucoma types, and clinical parameters associated with the presence of various glaucomas. Data from 2247 patients aged 18-98 years were reviewed. Glaucoma was determined for 305 patients (13.6%). Among this group, 54.8% had primary open-angle glaucoma (POAG), 26.9% had primary angle-closure glaucoma (PACG), 13.4% had mixed mechanism glaucoma (MMG), and 4.9% had secondary glaucoma. In the MMG group (41 patients), 27 patients who initially had open angles developed narrow angles and underwent laser peripheral iridotomy (LPI) with a mean follow up of 6.4 years from the time of iridotomy. The other 13 patients had glaucoma progression with open angles after LPI. One POAG patient had neovascular glaucoma due to retinal vein occlusion several years later. Compared to the PACG group, the MMG group had significantly lower baseline intraocular pressure (25.0 vs. 20.2 mmHg, p = 0.007) but with no difference in biometry. POAG is the major type of glaucoma in this clinic-based Vietnamese population. However, Vietnamese appear to have a relatively higher proportion of PACG than Caucasians and those of African descent. It is recommended that gonioscopy be part of the regular eye check-up for adult Vietnamese patients.

A significant causal association between C-reactive protein levels and schizophrenia

OpenAIRE

Inoshita, Masatoshi; Numata, Shusuke; Tajima, Atsushi; Kinoshita, Makoto; Umehara, Hidehiro; Nakataki, Masahito; Ikeda, Masashi; Maruyama, Souichiro; Yamamori, Hidenaga; Kanazawa, Tetsufumi; Shimodera, Shinji; Hashimoto, Ryota; Imoto, Issei; Yoneda, Hiroshi; Iwata, Nakao

2016-01-01

Many observational studies have shown elevated blood CRP levels in schizophrenia compared with controls, and one population-based prospective study has reported that elevated plasma CRP levels were associated with late- and very-late-onset schizophrenia. Furthermore, several clinical studies have reported the efficacy of anti-inflammatory drugs on the symptoms in patients with schizophrenia. However, whether elevated CRP levels are causally related to schizophrenia is not still established be...

Moving towards causality in attention-deficit hyperactivity disorder: overview of neural and genetic mechanisms

Science.gov (United States)

Gallo, Eduardo F; Posner, Jonathan

2016-01-01

Attention-deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterised by developmentally inappropriate levels of inattention and hyperactivity or impulsivity. The heterogeneity of its clinical manifestations and the differential responses to treatment and varied prognoses have long suggested myriad underlying causes. Over the past decade, clinical and basic research efforts have uncovered many behavioural and neurobiological alterations associated with ADHD, from genes to higher order neural networks. Here, we review the neurobiology of ADHD by focusing on neural circuits implicated in the disorder and discuss how abnormalities in circuitry relate to symptom presentation and treatment. We summarise the literature on genetic variants that are potentially related to the development of ADHD, and how these, in turn, might affect circuit function and relevant behaviours. Whether these underlying neurobiological factors are causally related to symptom presentation remains unresolved. Therefore, we assess efforts aimed at disentangling issues of causality, and showcase the shifting research landscape towards endophenotype refinement in clinical and preclinical settings. Furthermore, we review approaches being developed to understand the neurobiological underpinnings of this complex disorder including the use of animal models, neuromodulation, and pharmaco-imaging studies. PMID:27183902

Causal learning and inference as a rational process: the new synthesis.

Science.gov (United States)

Holyoak, Keith J; Cheng, Patricia W

2011-01-01

Over the past decade, an active line of research within the field of human causal learning and inference has converged on a general representational framework: causal models integrated with bayesian probabilistic inference. We describe this new synthesis, which views causal learning and inference as a fundamentally rational process, and review a sample of the empirical findings that support the causal framework over associative alternatives. Causal events, like all events in the distal world as opposed to our proximal perceptual input, are inherently unobservable. A central assumption of the causal approach is that humans (and potentially nonhuman animals) have been designed in such a way as to infer the most invariant causal relations for achieving their goals based on observed events. In contrast, the associative approach assumes that learners only acquire associations among important observed events, omitting the representation of the distal relations. By incorporating bayesian inference over distributions of causal strength and causal structures, along with noisy-logical (i.e., causal) functions for integrating the influences of multiple causes on a single effect, human judgments about causal strength and structure can be predicted accurately for relatively simple causal structures. Dynamic models of learning based on the causal framework can explain patterns of acquisition observed with serial presentation of contingency data and are consistent with available neuroimaging data. The approach has been extended to a diverse range of inductive tasks, including category-based and analogical inferences.

Beliefs about causes of major depression: Clinical and treatment correlates among African Americans in an urban community.

Science.gov (United States)

Murphy, Eleanor; Hankerson, Sidney

2018-04-01

Major depression is increasingly viewed in the United States public as a medical disorder with biological and psychosocial causes. Yet little is known about how causal attributions about depression vary among low-income racial minorities. This study examined beliefs about causes of depression and their demographic, clinical and treatment correlates in a lower income African American sample. Volunteers (N = 110) aged 24-79 years, who participated in a family study of depression, completed a 45-item questionnaire on their beliefs about the causes of depression. We used multidimensional scaling (MDS) to cluster items into causal domains and multivariate regression analyses to test associations of causal domains with demographic and clinical characteristics and treatments received. Three causal domains, conceptualized as Eastern culture/supernatural (ECS), Western culture/natural/psychosocial (WCN-P), and /neurobiological (WCN-N) attributions, were derived from MDS clusters. WCN-P was most commonly endorsed (50%-91%) and ECS least endorsed as causes of depression (10-44%). This pattern held across gender, age, educational levels, and diagnostic category. WCN-N items were moderately endorsed, with some distinction between genetic causes and other biological causes. WCN-N was positively associated with medication as opposed to other forms of treatment (B = 1.17; p = .049). Among low-income African Americans, beliefs about causes of depression are varied but broadly consistent explanatory models that include a combination of psychosocial causes with genetic/biological contributions. For certain individuals, supernatural and natural causal attributions may coexist without dissonance. Causal attributions may be associated with types of treatment accepted and have implications for treatment compliance and adherence. © 2017 Wiley Periodicals, Inc.

New Insights into Signed Path Coefficient Granger Causality Analysis.

Science.gov (United States)

Zhang, Jian; Li, Chong; Jiang, Tianzi

2016-01-01

Granger causality analysis, as a time series analysis technique derived from econometrics, has been applied in an ever-increasing number of publications in the field of neuroscience, including fMRI, EEG/MEG, and fNIRS. The present study mainly focuses on the validity of "signed path coefficient Granger causality," a Granger-causality-derived analysis method that has been adopted by many fMRI researches in the last few years. This method generally estimates the causality effect among the time series by an order-1 autoregression, and defines a positive or negative coefficient as an "excitatory" or "inhibitory" influence. In the current work we conducted a series of computations from resting-state fMRI data and simulation experiments to illustrate the signed path coefficient method was flawed and untenable, due to the fact that the autoregressive coefficients were not always consistent with the real causal relationships and this would inevitablely lead to erroneous conclusions. Overall our findings suggested that the applicability of this kind of causality analysis was rather limited, hence researchers should be more cautious in applying the signed path coefficient Granger causality to fMRI data to avoid misinterpretation.

Clinical characteristics of patients with ischemic stroke following the 2016 Kumamoto earthquake.

Science.gov (United States)

Inatomi, Yuichiro; Nakajima, Makoto; Yonehara, Toshiro; Ando, Yukio

2017-12-01

To investigate the clinical characteristics of patients with ischemic stroke following the 2016 Kumamoto earthquake. We retrospectively studied patients with ischemic stroke admitted to our hospital for 12weeks following the earthquake. We compared the clinical backgrounds and characteristics of the patients: before (the same period from the previous 3years) and after the earthquake; and the early (first 2weeks) and late (subsequent 10weeks) phases. A total of 194 patients with ischemic stroke were admitted to our hospital after the earthquake; 496 (165.3/year) patients were admitted before the earthquake. No differences between the two groups were noted for the clinical backgrounds, characteristics, or biomarkers. Past history of sleeping in a shelter or small vehicle was found in 13% and 28% of patients, respectively. Sleeping in a shelter (27% vs. 10%, p=0.013) was found more frequently in patients during the early phase than during the late phase after the earthquake. Admission of patients with ischemic stroke increased after the earthquake; however no differences between before and after the earthquake were noted for their clinical characteristics. To prevent ischemic stroke following earthquakes, mental stress and physical status of evacuees must be assessed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Granger Causality Testing with Intensive Longitudinal Data.

Science.gov (United States)

Molenaar, Peter C M

2018-06-01

The availability of intensive longitudinal data obtained by means of ambulatory assessment opens up new prospects for prevention research in that it allows the derivation of subject-specific dynamic networks of interacting variables by means of vector autoregressive (VAR) modeling. The dynamic networks thus obtained can be subjected to Granger causality testing in order to identify causal relations among the observed time-dependent variables. VARs have two equivalent representations: standard and structural. Results obtained with Granger causality testing depend upon which representation is chosen, yet no criteria exist on which this important choice can be based. A new equivalent representation is introduced called hybrid VARs with which the best representation can be chosen in a data-driven way. Partial directed coherence, a frequency-domain statistic for Granger causality testing, is shown to perform optimally when based on hybrid VARs. An application to real data is provided.

Causality Between Urban Concentration and Environmental Quality

Directory of Open Access Journals (Sweden)

Amin Pujiati

2015-08-01

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

Partial Granger causality--eliminating exogenous inputs and latent variables.

Science.gov (United States)

Guo, Shuixia; Seth, Anil K; Kendrick, Keith M; Zhou, Cong; Feng, Jianfeng

2008-07-15

Attempts to identify causal interactions in multivariable biological time series (e.g., gene data, protein data, physiological data) can be undermined by the confounding influence of environmental (exogenous) inputs. Compounding this problem, we are commonly only able to record a subset of all related variables in a system. These recorded variables are likely to be influenced by unrecorded (latent) variables. To address this problem, we introduce a novel variant of a widely used statistical measure of causality--Granger causality--that is inspired by the definition of partial correlation. Our 'partial Granger causality' measure is extensively tested with toy models, both linear and nonlinear, and is applied to experimental data: in vivo multielectrode array (MEA) local field potentials (LFPs) recorded from the inferotemporal cortex of sheep. Our results demonstrate that partial Granger causality can reveal the underlying interactions among elements in a network in the presence of exogenous inputs and latent variables in many cases where the existing conditional Granger causality fails.

Inductive reasoning about causally transmitted properties.

Science.gov (United States)

Shafto, Patrick; Kemp, Charles; Bonawitz, Elizabeth Baraff; Coley, John D; Tenenbaum, Joshua B

2008-11-01

Different intuitive theories constrain and guide inferences in different contexts. Formalizing simple intuitive theories as probabilistic processes operating over structured representations, we present a new computational model of category-based induction about causally transmitted properties. A first experiment demonstrates undergraduates' context-sensitive use of taxonomic and food web knowledge to guide reasoning about causal transmission and shows good qualitative agreement between model predictions and human inferences. A second experiment demonstrates strong quantitative and qualitative fits to inferences about a more complex artificial food web. A third experiment investigates human reasoning about complex novel food webs where species have known taxonomic relations. Results demonstrate a double-dissociation between the predictions of our causal model and a related taxonomic model [Kemp, C., & Tenenbaum, J. B. (2003). Learning domain structures. In Proceedings of the 25th annual conference of the cognitive science society]: the causal model predicts human inferences about diseases but not genes, while the taxonomic model predicts human inferences about genes but not diseases. We contrast our framework with previous models of category-based induction and previous formal instantiations of intuitive theories, and outline challenges in developing a complete model of context-sensitive reasoning.

Neural correlates of continuous causal word generation.

Science.gov (United States)

Wende, Kim C; Straube, Benjamin; Stratmann, Mirjam; Sommer, Jens; Kircher, Tilo; Nagels, Arne

2012-09-01

Causality provides a natural structure for organizing our experience and language. Causal reasoning during speech production is a distinct aspect of verbal communication, whose related brain processes are yet unknown. The aim of the current study was to investigate the neural mechanisms underlying the continuous generation of cause-and-effect coherences during overt word production. During fMRI data acquisition participants performed three verbal fluency tasks on identical cue words: A novel causal verbal fluency task (CVF), requiring the production of multiple reasons to a given cue word (e.g. reasons for heat are fire, sun etc.), a semantic (free association, FA, e.g. associations with heat are sweat, shower etc.) and a phonological control task (phonological verbal fluency, PVF, e.g. rhymes with heat are meat, wheat etc.). We found that, in contrast to PVF, both CVF and FA activated a left lateralized network encompassing inferior frontal, inferior parietal and angular regions, with further bilateral activation in middle and inferior as well as superior temporal gyri and the cerebellum. For CVF contrasted against FA, we found greater bold responses only in the left middle frontal cortex. Large overlaps in the neural activations during free association and causal verbal fluency indicate that the access to causal relationships between verbal concepts is at least partly based on the semantic neural network. The selective activation in the left middle frontal cortex for causal verbal fluency suggests that distinct neural processes related to cause-and-effect-relations are associated with the recruitment of middle frontal brain areas. Copyright © 2012 Elsevier Inc. All rights reserved.

Testing causal relationships between wholesale electricity prices and primary energy prices

International Nuclear Information System (INIS)

Nakajima, Tadahiro; Hamori, Shigeyuki

2013-01-01

We apply the lag-augmented vector autoregression technique to test the Granger-causal relationships among wholesale electricity prices, natural gas prices, and crude oil prices. In addition, by adopting a cross-correlation function approach, we test not only the causality in mean but also the causality in variance between the variables. The results of tests using both techniques show that gas prices Granger-cause electricity prices in mean. We find no Granger-causality in variance among these variables. -- Highlights: •We test the Granger-causality among wholesale electricity and primary energy prices. •We test not only the causality in mean but also the causality in variance. •The results show that gas prices Granger-cause electricity prices in mean. •We find no Granger-causality in variance among these variables

Significance of functional disease-causal/susceptible variants identified by whole-genome analyses for the understanding of human diseases.

Science.gov (United States)

Hitomi, Yuki; Tokunaga, Katsushi

2017-01-01

Human genome variation may cause differences in traits and disease risks. Disease-causal/susceptible genes and variants for both common and rare diseases can be detected by comprehensive whole-genome analyses, such as whole-genome sequencing (WGS), using next-generation sequencing (NGS) technology and genome-wide association studies (GWAS). Here, in addition to the application of an NGS as a whole-genome analysis method, we summarize approaches for the identification of functional disease-causal/susceptible variants from abundant genetic variants in the human genome and methods for evaluating their functional effects in human diseases, using an NGS and in silico and in vitro functional analyses. We also discuss the clinical applications of the functional disease causal/susceptible variants to personalized medicine.

"Cutaneous rabbit" hops toward a light: Unimodal and cross-modal causality on the skin

Directory of Open Access Journals (Sweden)

Tomohisa eAsai

2012-10-01

Full Text Available Our somatosensory system deals with not only spatial but also temporal imprecision, resulting in characteristic spatiotemporal illusions. Repeated rapid stimulation at the wrist, then near the elbow, can create the illusion of touch at intervening locations along the arm (as if a rabbit is hopping along the arm. This is known as the cutaneous rabbit effect (CRE. Previous studies have suggested that the CRE involves not only an intrinsic somatotopic representation but also the representation of an extended body schema that includes causality or animacy perception upon the skin. On the other hand, unlike other multi-modal causality couplings, it is possible that the CRE is not affected by concurrent auditory temporal information. The present study examined the effect of a simple visual flash on the CRE, which has both temporal and spatial information. Here, stronger cross-modal causality or correspondence could be provided. We presented three successive tactile stimuli on the inside of a participant’s left arm. Stimuli were presented on the wrist, elbow, and midway between the two. Results from our five experimental manipulations suggest that a one-shot flash enhances or attenuates the CRE depending on its congruency with cutaneous rabbit saltation. Our results reflect that 1 our brain interprets successive stimuli on the skin as motion in terms of time and space (unimodal causality and that 2 the concurrent signals from other modalities provide clues for creating unified representations of this external motion (multi-modal causality as to the extent that spatiotemporal synchronicity among modalities is provided.available information from other modalities should also provide a key clue as to the extent that spatiotemporal synchronicity among modalities is provided.

World oil and agricultural commodity prices: Evidence from nonlinear causality

International Nuclear Information System (INIS)

Nazlioglu, Saban

2011-01-01

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

Sydenham's chorea: clinical and evolutive characteristics

Directory of Open Access Journals (Sweden)

Maria Teresa Ramos Ascensão Terreri

2002-01-01

Full Text Available CONTEXT: During the last 12 years we have observed an increase in the frequency of Sydenham's chorea in our country. We have observed that some of our patients have presented recurrence of the chorea despite regular treatment with benzathine penicillin. OBJECTIVE: The aim of our study was to evaluate clinical and evolutive characteristics of Sydenham's chorea in a group of patients followed in our Pediatric Rheumatology Unit. TYPE OF STUDY: Retrospective study. SETTING: Section of Pediatric Rheumatology - Discipline of Allergy, Clinical Immunology and Rheumatology - Department of Pediatrics - UNIFESP - EPM. PARTICIPANTS: Two hundred and ninety patients with rheumatic fever followed between 1986 and 1999. METHODS: We reviewed the records of 290 patients with rheumatic fever followed between 1986 and 1999. All patients were diagnosed according to the revised Jones criteria (1992. We included 86 patients that presented Sydenham's chorea as one of the major criteria (one or more attacks and evaluated their clinical and evolutive characteristics as well the treatment. RESULTS: Fifty-five patients were girls and 31 were boys. The mean age at onset was 9.7 years and mean follow-up period was 3.6 years. The 86 Sydenham's chorea patients presented 110 attacks of chorea. We observed isolated chorea in 35% of the patients, and 25 (29% presented one or more recurrences. We included only 17 of the 25 patients for further analysis, with a total of 22 recurrences of which 14 were attacks of chorea, because it was not possible to precisely detect the interval between attacks in the other patients. The approximate interval between the attacks ranged from 4 to 96 months. In 71% of the patients there was no failure in the secondary prophylaxis with benzathine penicillin, which was performed every 3 weeks. CONCLUSION: Despite the regular use of secondary benzathine penicillin prophylaxis, children with rheumatic fever have a high risk of Sydenham's chorea

UMA TEORÍA CAUSAL PARA LOS CASOS FREGE

Directory of Open Access Journals (Sweden)

ABEL WAJNERMAN PAZ

2015-06-01

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

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...

Quantum theory and local causality

CERN Document Server

Hofer-Szabó, Gábor

2018-01-01

This book summarizes the results of research the authors have pursued in the past years on the problem of implementing Bell's notion of local causality in local physical theories and relating it to other important concepts and principles in the foundations of physics such as the Common Cause Principle, Bell's inequalities, the EPR (Einstein-Podolsky-Rosen) scenario, and various other locality and causality concepts. The book is intended for philosophers of science with an interest in the formal background of sciences, philosophers of physics and physicists working in foundation of physics.

Quantum causality conceptual issues in the causal theory of quantum mechanics

CERN Document Server

Riggs, Peter J; French, Steven RD

2009-01-01

This is a treatise devoted to the foundations of quantum physics and the role that causality plays in the microscopic world governed by the laws of quantum mechanics. The book is controversial and will engender some lively debate on the various issues raised.

A Causal Model of Faculty Research Productivity.

Science.gov (United States)

Bean, John P.

A causal model of faculty research productivity was developed through a survey of the literature. Models of organizational behavior, organizational effectiveness, and motivation were synthesized into a causal model of productivity. Two general types of variables were assumed to affect individual research productivity: institutional variables and…

Causal inheritance in plane wave quotients

International Nuclear Information System (INIS)

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

2003-01-01

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

Testing the causal theory of reference.

Science.gov (United States)

Domaneschi, Filippo; Vignolo, Massimiliano; Di Paola, Simona

2017-04-01

Theories of reference are a crucial research topic in analytic philosophy. Since the publication of Kripke's Naming and Necessity, most philosophers have endorsed the causal/historical theory of reference. The goal of this paper is twofold: (i) to discuss a method for testing experimentally the causal theory of reference for proper names by investigating linguistic usage and (ii) to present the results from two experiments conducted with that method. Data collected in our experiments confirm the causal theory of reference for people proper names and for geographical proper names. A secondary but interesting result is that the semantic domain affects reference assignment: while with people proper names speakers tend to assign the semantic reference, with geographical proper names they are prompted to assign the speaker's reference. Copyright © 2016 Elsevier B.V. All rights reserved.

Causal inheritance in plane wave quotients

Science.gov (United States)

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

2004-01-01

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

[Antibibiotic resistance by nosocomial infections' causal agents].

Science.gov (United States)

Salazar-Holguín, Héctor Daniel; Cisneros-Robledo, María Elena

2016-01-01

The antibibiotic resistance by nosocomial infections (NI) causal agents constitutes a seriously global problematic that involves the Mexican Institute of Social Security's Regional General Hospital 1 in Chihuahua, Mexico; although with special features that required to be specified and evaluated, in order to concrete an effective therapy. Observational, descriptive and prospective study; by means of active vigilance all along 2014 in order to detect the nosocomial infections, for epidemiologic study, culture and antibiogram to identify its causal agents and antibiotics resistance and sensitivity. Among 13527 hospital discharges, 1079 displayed NI (8 %), standed out: the related on vascular lines, of surgical site, pneumonia and urinal track; they added up two thirds of the total. We carried out culture and antibiogram about 300 of them (27.8 %); identifying 31 bacterian species, mainly seven of those (77.9 %): Escherichia coli, Staphylococcus aureus and epidermidis, Pseudomonas aeruginosa, Acinetobacter baumannii, Klebsiella pneumoniae and Enterobacter cloacae; showing multiresistance to 34 tested antibiotics, except in seven with low or without resistance at all: vancomycin, teicoplanin, linezolid, quinupristin-dalfopristin, piperacilin-tazobactam, amikacin and carbapenems. When we contrasted those results with the recommendations in the clinical practice guides, it aroused several contradictions; so they must be taken with reserves and has to be tested in each hospital, by means of cultures and antibiograms in practically every case of nosocomial infection.

Causal mediation analysis with multiple causally non-ordered mediators.

Science.gov (United States)

Taguri, Masataka; Featherstone, John; Cheng, Jing

2018-01-01

In many health studies, researchers are interested in estimating the treatment effects on the outcome around and through an intermediate variable. Such causal mediation analyses aim to understand the mechanisms that explain the treatment effect. Although multiple mediators are often involved in real studies, most of the literature considered mediation analyses with one mediator at a time. In this article, we consider mediation analyses when there are causally non-ordered multiple mediators. Even if the mediators do not affect each other, the sum of two indirect effects through the two mediators considered separately may diverge from the joint natural indirect effect when there are additive interactions between the effects of the two mediators on the outcome. Therefore, we derive an equation for the joint natural indirect effect based on the individual mediation effects and their interactive effect, which helps us understand how the mediation effect works through the two mediators and relative contributions of the mediators and their interaction. We also discuss an extension for three mediators. The proposed method is illustrated using data from a randomized trial on the prevention of dental caries.

Mind and Meaning: Piaget and Vygotsky on Causal Explanation.

Science.gov (United States)

Beilin, Harry

1996-01-01

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

Beyond Markov: Accounting for independence violations in causal reasoning.

Science.gov (United States)

Rehder, Bob

2018-06-01

Although many theories of causal cognition are based on causal graphical models, a key property of such models-the independence relations stipulated by the Markov condition-is routinely violated by human reasoners. This article presents three new accounts of those independence violations, accounts that share the assumption that people's understanding of the correlational structure of data generated from a causal graph differs from that stipulated by causal graphical model framework. To distinguish these models, experiments assessed how people reason with causal graphs that are larger than those tested in previous studies. A traditional common cause network (Y 1 ←X→Y 2 ) was extended so that the effects themselves had effects (Z 1 ←Y 1 ←X→Y 2 →Z 2 ). A traditional common effect network (Y 1 →X←Y 2 ) was extended so that the causes themselves had causes (Z 1 →Y 1 →X←Y 2 ←Z 2 ). Subjects' inferences were most consistent with the beta-Q model in which consistent states of the world-those in which variables are either mostly all present or mostly all absent-are viewed as more probable than stipulated by the causal graphical model framework. Substantial variability in subjects' inferences was also observed, with the result that substantial minorities of subjects were best fit by one of the other models (the dual prototype or a leaky gate models). The discrepancy between normative and human causal cognition stipulated by these models is foundational in the sense that they locate the error not in people's causal reasoning but rather in their causal representations. As a result, they are applicable to any cognitive theory grounded in causal graphical models, including theories of analogy, learning, explanation, categorization, decision-making, and counterfactual reasoning. Preliminary evidence that independence violations indeed generalize to other judgment types is presented. Copyright © 2018 Elsevier Inc. All rights reserved.

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

International Nuclear Information System (INIS)

Solarin, Sakiru Adebola; Shahbaz, Muhammad

2013-01-01

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

Simplifying Causal Complexity: How Interactions between Modes of Causal Induction and Information Availability Lead to Heuristic-Driven Reasoning

Science.gov (United States)

Grotzer, Tina A.; Tutwiler, M. Shane

2014-01-01

This article considers a set of well-researched default assumptions that people make in reasoning about complex causality and argues that, in part, they result from the forms of causal induction that we engage in and the type of information available in complex environments. It considers how information often falls outside our attentional frame…

Causal Relationship between Construction Production and GDP in Turkey

Directory of Open Access Journals (Sweden)

Hakkı Kutay Bolkol

2015-12-01

Full Text Available This study empirically investigates the causal relationship between construction production and GDP for Turkey during 2005Q1-2013Q4 period. Because it is found that, there is no cointegration which means there is no long run relationship between variables, VAR Granger Causality Method is used to test the causality in short run. The findings reveal that, the causality runs from GDP to Building Production and Building Production to Non-Building Production (i.e. bidirectional relationship. Findings of this paper suggest that, because there is no long run relationship between Construction Production (Building and Non-Building and GDP and also in short run the causality runs from GDP to Construction Production, the growth strategy based on mainly Construction Sector growth is not a good idea for Turkey.

Causal Relationship between Construction Production and GDP in Turkey

Directory of Open Access Journals (Sweden)

Hakkı Kutay Bolkol

2015-09-01

Full Text Available This study empirically investigates the causal relationship between construction production and GDP for Turkey during 2005Q1-2013Q4 period. Because it is found that, there is no cointegration which means there is no long run relationship between variables, VAR Granger Causality Method is used to test the causality in short run. The findings reveal that, the causality runs from GDP to Building Production and Building Production to Non-Building Production (i.e. bidirectional relationship. Findings of this paper suggest that, because there is no long run relationship between Construction Production (Building and Non-Building and GDP and also in short run the causality runs from GDP to Construction Production, the growth strategy based on mainly Construction Sector growth is not a good idea for Turkey.

Causality in demand

DEFF Research Database (Denmark)

Nielsen, Max; Jensen, Frank; Setälä, Jari

2011-01-01

to fish demand. On the German market for farmed trout and substitutes, it is found that supply sources, i.e. aquaculture and fishery, are not the only determinant of causality. Storing, tightness of management and aggregation level of integrated markets might also be important. The methodological...

The causal relationship between Foreign Direct Investment (FDI ...

African Journals Online (AJOL)

The causal relationship between Foreign Direct Investment (FDI) and the ... of selected west African countries: Panel ARDL/Granger Causality Analysis. ... among this developing countries and an important revelation for policy implication.

MODY in Siberia – molecular genetics and clinical characteristics

Directory of Open Access Journals (Sweden)

Alla Konstantinovna Ovsyannikova

2017-05-01

Full Text Available The diagnosis of maturity onset diabetes of the young (MODY has high clinical significance in young patients (no absolute need for exogenous insulin; normoglycaemia in most patients achieved by dieting or taking oral hypoglycaemic agents and their relatives (high probability of first-degree relatives being carriers of mutations, which requires a thorough collection of family history and determination of the parameters of carbohydrate metabolism. Aim. This study aimed was to determine the clinical characteristics of different subtypes of MODY in a Siberian region. Materials and Methods. We performed an examination, biochemical and hormonal blood tests, ultrasound and molecular genetic testing of 20 patients with a clinical diagnosis of MODY. Results. Four subtypes of MODY were verified: MODY2 in 11 patients, MODY3 in two, MODY8 in one and MODY12 in two. Eleven patients (69% exhibited no clinical manifestations of carbohydrate metabolism disorders, and one patient showed weight loss during early stage of the disease. Comorbidities included dyslipidemia, thyroid gland disorders and arterial hypertension. One patient (6% exhibited diabetic nephropathy; two (13%, diabetic retinopathy and three (19%, peripheral neuropathy of lower legs. All patients achieved the target carbohydrate metabolism; the level of C-peptide was within the reference range. Conclusion. Four different subtypes of MODY (2, 3, 8, 12 were diagnosed in the present study, which differed in their clinical characteristics, presence of complications and treatment strategies. Our knowledge of monogenic forms of diabetes is expanding with the development in molecular genetics, but several aspects related to them require further study.

Sensitivity Analysis and Bounding of Causal Effects with Alternative Identifying Assumptions

Science.gov (United States)

Jo, Booil; Vinokur, Amiram D.

2011-01-01

When identification of causal effects relies on untestable assumptions regarding nonidentified parameters, sensitivity of causal effect estimates is often questioned. For proper interpretation of causal effect estimates in this situation, deriving bounds on causal parameters or exploring the sensitivity of estimates to scientifically plausible…

Causal quantum theory and the collapse locality loophole

International Nuclear Information System (INIS)

Kent, Adrian

2005-01-01

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

Causal inference in survival analysis using pseudo-observations.

Science.gov (United States)

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

2017-07-30

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

Causal Bayes Model of Mathematical Competence in Kindergarten

Directory of Open Access Journals (Sweden)

Božidar Tepeš

2016-06-01

Full Text Available In this paper authors define mathematical competences in the kindergarten. The basic objective was to measure the mathematical competences or mathematical knowledge, skills and abilities in mathematical education. Mathematical competences were grouped in the following areas: Arithmetic and Geometry. Statistical set consisted of 59 children, 65 to 85 months of age, from the Kindergarten Milan Sachs from Zagreb. The authors describe 13 variables for measuring mathematical competences. Five measuring variables were described for the geometry, and eight measuring variables for the arithmetic. Measuring variables are tasks which children solved with the evaluated results. By measuring mathematical competences the authors make causal Bayes model using free software Tetrad 5.2.1-3. Software makes many causal Bayes models and authors as experts chose the model of the mathematical competences in the kindergarten. Causal Bayes model describes five levels for mathematical competences. At the end of the modeling authors use Bayes estimator. In the results, authors describe by causal Bayes model of mathematical competences, causal effect mathematical competences or how intervention on some competences cause other competences. Authors measure mathematical competences with their expectation as random variables. When expectation of competences was greater, competences improved. Mathematical competences can be improved with intervention on causal competences. Levels of mathematical competences and the result of intervention on mathematical competences can help mathematical teachers.

Demographic, clinical and radiological characteristics of seronegative spondyloarthritis Egyptian patients: A rheumatology clinic experience in Mansoura

Directory of Open Access Journals (Sweden)

Adel Abdelsalam

2017-04-01

Conclusion: The demographic, clinical and radiological characteristics of Egyptian SpA patients are comparable to those from other countries except for the lower prevalence of extra-articular manifestations.

A General Approach to Causal Mediation Analysis

Science.gov (United States)

Imai, Kosuke; Keele, Luke; Tingley, Dustin

2010-01-01

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

Causal knowledge and the development of inductive reasoning

OpenAIRE

Bright, Aimée K.; Feeney, Aidan

2014-01-01

We explored the development of sensitivity to causal relations in children’s inductive reasoning. Children (5-, 8-, and 12-year-olds) and adults were given trials in which they decided whether a property known to be possessed by members of one category was also possessed by members of (a) a taxonomically related category or (b) a causally related category. The direction of the causal link was either predictive (prey → predator) or diagnostic (predator → prey), and the property that participan...

Normalizing the causality between time series

Science.gov (United States)

Liang, X. San

2015-08-01

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

Inference of boundaries in causal sets

Science.gov (United States)

Cunningham, William J.

2018-05-01

We investigate the extrinsic geometry of causal sets in (1+1) -dimensional Minkowski spacetime. The properties of boundaries in an embedding space can be used not only to measure observables, but also to supplement the discrete action in the partition function via discretized Gibbons–Hawking–York boundary terms. We define several ways to represent a causal set using overlapping subsets, which then allows us to distinguish between null and non-null bounding hypersurfaces in an embedding space. We discuss algorithms to differentiate between different types of regions, consider when these distinctions are possible, and then apply the algorithms to several spacetime regions. Numerical results indicate the volumes of timelike boundaries can be measured to within 0.5% accuracy for flat boundaries and within 10% accuracy for highly curved boundaries for medium-sized causal sets with N  =  214 spacetime elements.

Spatial hypersurfaces in causal set cosmology

International Nuclear Information System (INIS)

Major, Seth A; Rideout, David; Surya, Sumati

2006-01-01

Within the causal set approach to quantum gravity, a discrete analogue of a spacelike region is a set of unrelated elements, or an antichain. In the continuum approximation of the theory, a moment-of-time hypersurface is well represented by an inextendible antichain. We construct a richer structure corresponding to a thickening of this antichain containing non-trivial geometric and topological information. We find that covariant observables can be associated with such thickened antichains and transitions between them, in classical sequential growth models of causal sets. This construction highlights the difference between the covariant measure on causal set cosmology and the standard sum-over-histories approach: the measure is assigned to completed histories rather than to histories on a restricted spacetime region. The resulting re-phrasing of the sum-over-histories may be fruitful in other approaches to quantum gravity

Subacute Sclerosing Panencephalitis: Clinical and Demographic Characteristics

International Nuclear Information System (INIS)

Rafique, A.; Amjad, N.; Chand, P.; Ahmed, K.; Ibrahim, S.; Zaidi, S. S. Z.; Rana, M. S.

2014-01-01

Objective: To determine the clinical and demographic characteristics of children diagnosed with Subacute sclerosing panencephalitis (SSPE). Study Design: Case series. Place and Duration of Study: The Aga Khan University Hospital, Karachi, from January 2000 to June 2012. Methodology: A retrospective analysis was done, regarding medical charts of 43 children under the age of 16 years with a discharge diagnosis of SSPE. Demographic and clinical characteristics were recorded. Results were expressed as percentages. Results: Most of the 43 patients were male (72%). The average age at presentation was 8.7 years with average duration of symptoms being 100.6 days. History of measles was present in 17 patients (39.5%). All children had seizures at presentation and 65% had cognitive impairment. Most patients required poly therapy for control of seizures. Sodium valproate was the most commonly used anti-epileptic agent; Isoprinosine was tried in 22 (51%) patients. CSF for antimeasles antibodies was positive in approximately 86% of the 40 (93%) children. EEG showed burst suppression pattern in 36 (83.7%) cases. Forty-two patients (97.6%) were discharged home in a vegetative state. Conclusion: SSPE is progressive neurodegenerative disorder. It can be prevented by timely immunization against measles. Measles antibody in the CSF is diagnostic for SSPE and is helpful in early diagnosis. Most patients experience a gradual but progressive decline in motor and cognitive functions. (author)

Analogy in causal inference: rethinking Austin Bradford Hill's neglected consideration.

Science.gov (United States)

Weed, Douglas L

2018-05-01

The purpose of this article was to rethink and resurrect Austin Bradford Hill's "criterion" of analogy as an important consideration in causal inference. In epidemiology today, analogy is either completely ignored (e.g., in many textbooks), or equated with biologic plausibility or coherence, or aligned with the scientist's imagination. None of these examples, however, captures Hill's description of analogy. His words suggest that there may be something gained by contrasting two bodies of evidence, one from an established causal relationship, the other not. Coupled with developments in the methods of systematic assessments of evidence-including but not limited to meta-analysis-analogy can be restructured as a key component in causal inference. This new approach will require that a collection-a library-of known cases of causal inference (i.e., bodies of evidence involving established causal relationships) be developed. This library would likely include causal assessments by organizations such as the International Agency for Research on Cancer, the National Toxicology Program, and the United States Environmental Protection Agency. In addition, a process for describing key features of a causal relationship would need to be developed along with what will be considered paradigm cases of causation. Finally, it will be important to develop ways to objectively compare a "new" body of evidence with the relevant paradigm case of causation. Analogy, along with all other existing methods and causal considerations, may improve our ability to identify causal relationships. Copyright © 2018 Elsevier Inc. All rights reserved.

Multichannel Signal Enhancement using Non-Causal, Time-Domain Filters

DEFF Research Database (Denmark)

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

2013-01-01

In the vast amount of time-domain filtering methods for speech enhancement, the filters are designed to be causal. Recently, however, it was shown that the noise reduction and signal distortion capabilities of such single-channel filters can be improved by allowing the filters to be non-causal. W......In the vast amount of time-domain filtering methods for speech enhancement, the filters are designed to be causal. Recently, however, it was shown that the noise reduction and signal distortion capabilities of such single-channel filters can be improved by allowing the filters to be non......-causal, multichannel filters for enhancement based on an orthogonal decomposition is proposed. The evaluation shows that there is a potential gain in noise reduction and signal distortion by introducing non-causality. Moreover, experiments on real-life speech show that we can improve the perceptual quality....

Elements of Causal Inference: Foundations and Learning Algorithms

DEFF Research Database (Denmark)

Peters, Jonas Martin; Janzing, Dominik; Schölkopf, Bernhard

A concise and self-contained introduction to causal inference, increasingly important in data science and machine learning......A concise and self-contained introduction to causal inference, increasingly important in data science and machine learning...

Counterfactual overdetermination vs. the causal exclusion problem.

Science.gov (United States)

Sparber, Georg

2005-01-01

This paper aims to show that a counterfactual approach to causation is not sufficient to provide a solution to the causal exclusion problem in the form of systematic overdetermination. Taking into account the truthmakers of causal counterfactuals provides a strong argument in favour of the identity of causes in situations of translevel, causation.

Non-Bayesian Inference: Causal Structure Trumps Correlation

Science.gov (United States)

Bes, Benedicte; Sloman, Steven; Lucas, Christopher G.; Raufaste, Eric

2012-01-01

The study tests the hypothesis that conditional probability judgments can be influenced by causal links between the target event and the evidence even when the statistical relations among variables are held constant. Three experiments varied the causal structure relating three variables and found that (a) the target event was perceived as more…

Aquagenic Pruritus in Polycythemia Vera: Clinical Characteristics

Directory of Open Access Journals (Sweden)

Edyta Lelonek

2018-02-01

Full Text Available Aquagenic pruritus is one of the main clinical features of polycythemia vera. The aim of this study was to analyse the clinical characteristics of aquagenic pruritus. The study group comprised 102 patients with molecularly confirmed polycythemia vera. Demographic data, data on disease history, polycythemia vera status and treatment modalities were collected. Moreover, various clinical features of aquagenic pruritus (including intensity, localization, quality, descriptors and the most common factors responsible for its aggravation or alleviation were examined. Aquagenic pruritus was observed in 41.2% of individuals, mean duration 6.6 ± 8.6 years, and its onset was noticed in the majority of patients (52.4% before the diagnosis of polycythemia vera. The mean intensity of aquagenic pruritus was 4.8 ± 1.9 points (visual analogue scale. One-third of patients with aquagenic pruritus avoided any contact with water. Antipruritic treatment was received only by 3 patients. Aquagenic pruritus seems to be an important, but frequently neglected, symptom in patients with polycythemia vera.

CLINICAL AND LABORATORY CHARACTERISTICS OF THE INFECTION CAUSED BY ENTEROVIRUS-71

Directory of Open Access Journals (Sweden)

E. N. Simovanyan

2014-01-01

Full Text Available Adverse course of enterovirus-71 infection (EVI-71 in children, frequent development of the nervous system pathology determine the need for early disease diagnosis. The study included 139 children aged 6 months to 13 years. Modern EVI-71 features is a frequent defeat of children aged from 3 to 7 years, attending organized groups, the priority development of combined moderate severity forms without nervous system pathology. EVI-71 is characterized by cyclical course, appearance in the first two disease days fever, murrain-like, catarrhal, lymphoproliferative syndromes, conjunctivitis, headaches. The second stage of the disease (3— 6 days in 37.9% children accompanied by attaching of meningitis and meningoencephalitis symptoms (common cerebral, meningeal and encephalic syndromes, changes in cerebrospinal fluid. In the EVI-71 diagnosis must be observed epidemiological history, clinical and laboratory parameters, detection of enterovirus-71 and its RNA from feces, oropharyngeal mucus and cerebrospinal fluid. Patients with EVI-71 need for combined treatment, including causal agents and pathogenetic therapy. 

A retrospective review of trends and clinical characteristics of ...

African Journals Online (AJOL)

Objective: Epidemiological studies indicate that methamphetamine (MA) abuse poses a major challenge to health in the Western Cape. The objectives of this study were to retrospectively assess the trends, clinical characteristics and treatment demand of MArelated admissions to a psychiatric ward in this region. Method: ...

Alcoholics and the emergency ward. Part I. Clinical characteristics.

Science.gov (United States)

Fialkov, M J

1977-10-01

A study of White and Black (Black, Cape Coloured and Asiatic) male alcoholics who attended the psychiatric emergency service unit at Groote Schuur Hospital, Cape Town, is presented. The psychosocial and clinical characteristics are described and compared. In addition, the associated physical and psychiatric morbidity is tabulated.

Causal Relations and Feature Similarity in Children's Inductive Reasoning

Science.gov (United States)

Hayes, Brett K.; Thompson, Susan P.

2007-01-01

Four experiments examined the development of property induction on the basis of causal relations. In the first 2 studies, 5-year-olds, 8-year-olds, and adults were presented with triads in which a target instance was equally similar to 2 inductive bases but shared a causal antecedent feature with 1 of them. All 3 age groups used causal relations…

Causality and correlations between BSE and NYSE indexes: A Janus faced relationship

Science.gov (United States)

Neeraj; Panigrahi, Prasanta K.

2017-09-01

We study the multi-scale temporal correlations and causality connections between the New York Stock Exchange (NYSE) and Bombay Stock Exchange (BSE) monthly average closing price indexes for a period of 300 months, encompassing the time period of the liberalisation of the Indian economy and its gradual global exposure. In multi-scale analysis; clearly identifiable 1, 2 and 3 year non-stationary periodic modulations in NYSE and BSE have been observed, with NYSE commensurating changes in BSE at 3 years scale. Interestingly, at one year time scale, the two exchanges are phase locked only during the turbulent times, while at the scale of three year, in-phase nature is observed for a much longer time frame. The two year time period, having characteristics of both one and three year variations, acts as the transition regime. The normalised NYSE's stock value is found to Granger cause those of BSE, with a time lag of 9 months. Surprisingly, observed Granger causality of high frequency variations reveals BSE behaviour getting reflected in the NYSE index fluctuations, after a smaller time lag. This Janus faced relationship, shows that smaller stock exchanges may provide a natural setting for simulating market fluctuations of much bigger exchanges. This possibly arises due to the fact that high frequency fluctuations form an universal part of the financial time series, and are expected to exhibit similar characteristics in open market economies.

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

NARCIS (Netherlands)

Sanders, T.J.M.|info:eu-repo/dai/nl/075243911; Spooren, W.P.M.S.

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

Campbell's and Rubin's Perspectives on Causal Inference

Science.gov (United States)

West, Stephen G.; Thoemmes, Felix

2010-01-01

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

Pituitary gigantism: Causes and clinical characteristics.

Science.gov (United States)

Rostomyan, Liliya; Daly, Adrian F; Beckers, Albert

2015-12-01

Acromegaly and pituitary gigantism are very rare conditions resulting from excessive secretion of growth hormone (GH), usually by a pituitary adenoma. Pituitary gigantism occurs when GH excess overlaps with the period of rapid linear growth during childhood and adolescence. Until recently, its etiology and clinical characteristics have been poorly understood. Genetic and genomic causes have been identified in recent years that explain about half of cases of pituitary gigantism. We describe these recent discoveries and focus on some important settings in which gigantism can occur, including familial isolated pituitary adenomas (FIPA) and the newly described X-linked acrogigantism (X-LAG) syndrome. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Clinical characteristics of chronic kidney disease of non-traditional causes in women of agricultural communities in El Salvador.

Science.gov (United States)

Herrera Valdés, Raúl; Orantes, Carlos M; Almaguer López, Miguel; López Marín, Laura; Arévalo, Pedro Alfonso; Smith González, Magaly J; Morales, Fabrizio E; Bacallao, Raymed; Bayarre, Héctor D; Vela Parada, Xavier F

2015-01-01

A chronic kidney disease of non-traditional causes (CKDu) has emerged in Central America and elsewhere, predominantly affecting male farmworkers. In El Salvador (2009), it was the second cause of death in men > 18 years old. Causality has not been determined. Most available research focused on men and there is scarce data on women. Describe the clinical and histopathologic characteristics of CKDu in women of agricultural communities in El Salvador. A descriptive study was carried out in 10 women with CKDu stages 2, 3a, and 3b. Researchers studied demographics, clinical examination; hematological and biochemical analyses, urine sediment, renal injury markers, and assessed renal, cardiac, and peripheral arteries, liver, pancreas, and lung anatomy and functions. Kidney biopsy was performed in all. Data was collected on the Lime Survey platform and exported to SPSS 19.0. Patient distribution by stages: 2 (70%), 3a (10%), 3b (20%). Occupation: agricultural 7; non-agricultural 3. agrochemical exposure 100%; farmworkers 70%; incidental malaria 50%, NSAIDs use 40%; hypertension 40%. nocturia 50%; dysuria 50%; arthralgia 70%; asthenia 50%; cramps 30%, profuse sweating 20%. Renal markers: albumin creatinine ratio (ACR) > 300 mg/g 90%; β microglobulin and neutrophil gelatinase- associated lipocalin (NGAL) presence in 40%. Kidney function: hypermagnesuria 100%; hyperphosphaturia 50%, hypercalciuria 40%; hypernatriuria 30%; hyponatremia 60%, hypocalcemia 50%. Doppler: tibial artery damage 40%. Neurological: reflex abnormalities 30%; Babinski and myoclonus 20%. Neurosensorial hypoacusis 70%. Histopathology: damage restricted mostly to the tubulo-interstitium, urine was essentially bland. CKDu in women is a chronic tubulointerstitial nephropathy with varied extrarenal symptoms.

Increasing fMRI sampling rate improves Granger causality estimates.

Directory of Open Access Journals (Sweden)

Fa-Hsuan Lin

Full Text Available Estimation of causal interactions between brain areas is necessary for elucidating large-scale functional brain networks underlying behavior and cognition. Granger causality analysis of time series data can quantitatively estimate directional information flow between brain regions. Here, we show that such estimates are significantly improved when the temporal sampling rate of functional magnetic resonance imaging (fMRI is increased 20-fold. Specifically, healthy volunteers performed a simple visuomotor task during blood oxygenation level dependent (BOLD contrast based whole-head inverse imaging (InI. Granger causality analysis based on raw InI BOLD data sampled at 100-ms resolution detected the expected causal relations, whereas when the data were downsampled to the temporal resolution of 2 s typically used in echo-planar fMRI, the causality could not be detected. An additional control analysis, in which we SINC interpolated additional data points to the downsampled time series at 0.1-s intervals, confirmed that the improvements achieved with the real InI data were not explainable by the increased time-series length alone. We therefore conclude that the high-temporal resolution of InI improves the Granger causality connectivity analysis of the human brain.

Prevalence, demographics and clinical characteristics of multiple sclerosis in Qatar.

Science.gov (United States)

Deleu, Dirk; Mir, Danial; Al Tabouki, Ahmed; Mesraoua, Rim; Mesraoua, Boulenouar; Akhtar, Naveed; Al Hail, Hassan; D'souza, Atlantic; Melikyan, Gayane; Imam, Yahia Z B; Osman, Yasir; Elalamy, Osama; Sokrab, Tageldin; Kamran, Sadaat; Ruiz Miyares, Francisco; Ibrahim, Faiza

2013-05-01

No published epidemiologic data on multiple sclerosis (MS) in Qatar exist. Our objectives were to determine the prevalence, demographics and clinical characteristics of MS in the Middle Eastern country of Qatar. We analyzed data for Qatari MS patients fulfilling the McDonald diagnostic criteria. A total of 154 patients fulfilled the inclusion criteria. On 31 April 2010, the crude prevalence of MS in Qatar was 64.57 per 100,000 inhabitants (95% CI: 58.31-70.37). The female-to-male ratio was 1.33:1. A positive family history was found in 10.4% of included MS patients. We conclude that Qatar is now a medium-to-high risk area for MS, with some important differences in clinical characteristics as compared to other countries in the region.

Inference of Boundaries in Causal Sets

OpenAIRE

Cunningham, William

2017-01-01

We investigate the extrinsic geometry of causal sets in $(1+1)$-dimensional Minkowski spacetime. The properties of boundaries in an embedding space can be used not only to measure observables, but also to supplement the discrete action in the partition function via discretized Gibbons-Hawking-York boundary terms. We define several ways to represent a causal set using overlapping subsets, which then allows us to distinguish between null and non-null bounding hypersurfaces in an embedding space...

Causal Relationship Between Relative Price Variability and Inflation in Turkey:

Directory of Open Access Journals (Sweden)

Nebiye Yamak

2016-09-01

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

The prevalence and clinical characteristics of punding in Parkinson's disease.

Science.gov (United States)

Spencer, Ashley H; Rickards, Hugh; Fasano, Alfonso; Cavanna, Andrea E

2011-03-01

Punding (the display of stereotyped, repetitive behaviors) is a relatively recently discovered feature of Parkinson's disease (PD). Little is known about the prevalence and clinical characteristics of punding in PD. In this review, four large scientific databases were comprehensively searched for literature in relation to punding prevalence and clinical correlates in the context of PD. Prevalence was found to vary greatly (between 0.34 to 14%), although there were large disparities in study populations, assessment methods, and criteria. We observed an association between punding, dopaminergic medications, and impulse control disorder. Other characteristics, which may be more common among punders, include a higher severity of dyskinesia, younger age of disease onset, longer disease duration, and male gender. More research in large clinical datasets is required in many areas before conclusions are drawn. The pathophysiology behind the punding phenomenon is also poorly understood at present, rendering it difficult to develop targeted therapy. The current mainstay of treatment is the reduction in the dose of dopaminergic medications, the evidence for other suggested therapies being purely empirical.

Causality and prediction: differences and points of contact

Directory of Open Access Journals (Sweden)

Luis Carlos Silva Ayçaguer, PhD

2014-09-01

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

Cortical hierarchies perform Bayesian causal inference in multisensory perception.

Directory of Open Access Journals (Sweden)

Tim Rohe

2015-02-01

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

PSA testing without clinical indication for prostate cancer in relation to socio-demographic and clinical characteristics in the Danish Diet, Cancer and Health Study

DEFF Research Database (Denmark)

Karlsen, Randi V; Larsen, Signe B; Christensen, Jane

2013-01-01

Background. Social differences in prostate cancer (PC) incidence and mortality might be related to testing for prostate-specific antigen (PSA). Although routine PSA screening is not recommended in Denmark, testing without clinical indication increased during the past decade. We evaluated...... associations between socio-demographic or clinical characteristics and PSA testing without clinical indication. Material and methods. In the Danish Diet, Cancer and Health Cohort, we identified 1051 men with PC diagnosed in 1993-2008. Diagnostic and clinical characteristics were obtained from medical records......, and socio-demographic information was retrieved from administrative registers. We used general logistic regression analysis to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for associations between socio-demographic or clinical characteristics and PSA testing without clinical indication. Cox...

[Clinical characteristics and preimplantation genetic diagnosis for male Robertsonian translocations].

Science.gov (United States)

Huang, Jin; Lian, Ying; Qiao, Jie; Liu, Ping

2012-08-18

To explore the clinical characteristics and the preimplantation genetic diagnosis (PGD) for male Robertsonian translocations. From Jan 2005 to Oct 2011, 96 PGD cycles of 80 male Robertsonian translocations were performed at the Center of Reproductive Medicine of Peking University Third Hospital, Beijing. All the couples were involved in assisted reproductive therapy because of oligozoospermia or repeated abortions. Pregnancy results and clinical characteristics were analyzed in this study. Of all the 80 Robertsonian translocation couples, 62 (77.50%, 62/80) couples suffered from primary infertility due to severe oligoospermia and 8 (10%, 8/80) couples suffered from secondary infertility due to oligoospermia. Moreover, 10 (12.50%, 10/80) couples had recurrent spontaneous abortion. Of all the 80 male Robertsonian translocations, 50 were (13; 14) translocations and 15 (14; 21) translocations. The study showed that 79 PGD cycles had the balanced embryos to transfer and 25 cycles resulted in clinical pregnancies. The clinical pregnancy rate per transfer cycle was 31.65% (25 of 79). Now, 18 couples had 21 viable infants and 3 were ongoing pregnant. Oligozoospermia is the main factor for the infertility of the male Robertsonian translocations. Artificial reproductive techniques can solve their reproductive problems. Moreover, PGD will decrease the risk of recurrent spontaneous abortion and the malformations.

Causal explanations of distress and general practitioners' assessments of common mental disorder among punjabi and English attendees.

Science.gov (United States)

Bhui, Kamaldeep; Bhugra, Dinesh; Goldberg, David

2002-01-01

The literature on the primary care assessment of mental distress among Indian subcontinent origin patients suggests frequent presentations to general practitioner, but rarely for recognisable psychiatric disorders. This study investigates whether cultural variations in patients' causal explanatory models account for cultural variations in the assessment of non-psychotic mental disorders in primary care. In a two-phase survey, 272 Punjabi and 269 English subjects were screened. The second phase was completed by 209 and 180 subjects, respectively. Causal explanatory models were elicited as explanations of two vignette scenarios. One of these emphasised a somatic presentation and the other anxiety symptoms. Psychiatric disorder was assessed by GPs on a Likert scale and by a psychiatrist on the Clinical Interview Schedule. Punjabis more commonly expressed medical/somatic and religious beliefs. General practitioners were more likely to assess any subject giving psychological explanations to vignette A and English subjects giving religious explanations to vignette B as having a significant psychiatric disorder. Where medical/somatic explanations of distress were most prevalent in response to the somatic vignette, psychological, religious and work explanations were less prevalent among Punjabis but not among English subjects. Causal explanations did not fully explain cultural differences in assessments. General practitioners' assessments and causal explanations are related and influenced by culture, but causal explanations do not fully explain cultural differences in assessments.

Cutaneous Papillomaviruses and Non-melanoma Skin Cancer: Causal Agents or Innocent Bystanders?

Science.gov (United States)

Hasche, Daniel; Vinzón, Sabrina E; Rösl, Frank

2018-01-01

There is still controversy in the scientific field about whether certain types of cutaneous human papillomaviruses (HPVs) are causally involved in the development of non-melanoma skin cancer (NMSC). Deciphering the etiological role of cutaneous HPVs requires - besides tissue culture systems - appropriate preclinical models to match the obtained results with clinical data from affected patients. Clear scientific evidence about the etiology and underlying mechanisms involved in NMSC development is fundamental to provide reasonable arguments for public health institutions to classify at least certain cutaneous HPVs as group 1 carcinogens. This in turn would have implications on fundraising institutions and health care decision makers to force - similarly as for anogenital cancer - the implementation of a broad vaccination program against "high-risk" cutaneous HPVs to prevent NMSC as the most frequent cancer worldwide. Precise knowledge of the multi-step progression from normal cells to cancer is a prerequisite to understand the functional and clinical impact of cofactors that affect the individual outcome and the personalized treatment of a disease. This overview summarizes not only recent arguments that favor the acceptance of a viral etiology in NMSC development but also reflects aspects of causality in medicine, the use of empirically meaningful model systems and strategies for prevention.

Cutaneous Papillomaviruses and Non-melanoma Skin Cancer: Causal Agents or Innocent Bystanders?

Directory of Open Access Journals (Sweden)

Daniel Hasche

2018-05-01

Full Text Available There is still controversy in the scientific field about whether certain types of cutaneous human papillomaviruses (HPVs are causally involved in the development of non-melanoma skin cancer (NMSC. Deciphering the etiological role of cutaneous HPVs requires – besides tissue culture systems – appropriate preclinical models to match the obtained results with clinical data from affected patients. Clear scientific evidence about the etiology and underlying mechanisms involved in NMSC development is fundamental to provide reasonable arguments for public health institutions to classify at least certain cutaneous HPVs as group 1 carcinogens. This in turn would have implications on fundraising institutions and health care decision makers to force – similarly as for anogenital cancer – the implementation of a broad vaccination program against “high-risk” cutaneous HPVs to prevent NMSC as the most frequent cancer worldwide. Precise knowledge of the multi-step progression from normal cells to cancer is a prerequisite to understand the functional and clinical impact of cofactors that affect the individual outcome and the personalized treatment of a disease. This overview summarizes not only recent arguments that favor the acceptance of a viral etiology in NMSC development but also reflects aspects of causality in medicine, the use of empirically meaningful model systems and strategies for prevention.

Whose statistical reasoning is facilitated by a causal structure intervention?

Science.gov (United States)

McNair, Simon; Feeney, Aidan

2015-02-01

People often struggle when making Bayesian probabilistic estimates on the basis of competing sources of statistical evidence. Recently, Krynski and Tenenbaum (Journal of Experimental Psychology: General, 136, 430-450, 2007) proposed that a causal Bayesian framework accounts for peoples' errors in Bayesian reasoning and showed that, by clarifying the causal relations among the pieces of evidence, judgments on a classic statistical reasoning problem could be significantly improved. We aimed to understand whose statistical reasoning is facilitated by the causal structure intervention. In Experiment 1, although we observed causal facilitation effects overall, the effect was confined to participants high in numeracy. We did not find an overall facilitation effect in Experiment 2 but did replicate the earlier interaction between numerical ability and the presence or absence of causal content. This effect held when we controlled for general cognitive ability and thinking disposition. Our results suggest that clarifying causal structure facilitates Bayesian judgments, but only for participants with sufficient understanding of basic concepts in probability and statistics.

Modeling of causality with metamaterials

International Nuclear Information System (INIS)

Smolyaninov, Igor I

2013-01-01

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. (paper)

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

Directory of Open Access Journals (Sweden)

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

Electricity consumption-real GDP causality nexus: Evidence from a bootstrapped causality test for 30 OECD countries

International Nuclear Information System (INIS)

Narayan, Paresh Kumar; Prasad, Arti

2008-01-01

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

Restless legs syndrome in Parkinson's disease: clinical characteristics and biochemical correlations

Directory of Open Access Journals (Sweden)

Tiago Machado Guerreiro

2010-12-01

Full Text Available Restless legs syndrome (RLS is a neurological disorder that responds to dopaminergic drugs, indicating a common pathophysiology with Parkinson's disease (PD. The prevalence of RLS was estimated in a group of PD patients and its clinical and biochemical characteristics were analysed. Forty-eight patients with PD were evaluated into two groups, with and without RLS. Clinical characteristics assessed in both groups were age, gender, duration of PD, Hoehn and Yahr, and Schwab and England scales. Laboratory variables such as hemoglobin, s-iron, s-ferritin and creatinine were obtained. The prevalence of RLS was 18.75%. No significant differences regarding clinical variables and biochemical parameters were observed. The high prevalence of RLS found in PD patients suggests the concept of a common etiological link and it seems that secondary causes did not play a central role in the pathophysiology of RLS in this group of parkinsonian patients.

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

DEFF Research Database (Denmark)

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

2012-01-01

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

Characteristics of clinical trials that require participants to be fluent in English.

Science.gov (United States)

Egleston, Brian L; Pedraza, Omar; Wong, Yu-Ning; Dunbrack, Roland L; Griffin, Candace L; Ross, Eric A; Beck, J Robert

2015-12-01

Diverse samples in clinical trials can make findings more generalizable. We sought to characterize the prevalence of clinical trials in the United States that required English fluency for participants to enroll in the trial. We randomly chose over 10,000 clinical trial protocols registered with ClinicalTrials.gov and examined the inclusion and exclusion criteria of the trials. We compared the relationship of clinical trial characteristics with English fluency inclusion requirements. We merged the ClinicalTrials.gov data with US Census and American Community Survey data to investigate the association of English-language restrictions with ZIP-code-level demographic characteristics of participating institutions. We used Chi-squared tests, t-tests, and logistic regression models for analyses. English fluency requirements have been increasing over time, from 1.7% of trials having such requirements before 2000 to 9.0% after 2010 (p English fluency requirements (1.8%), while behavioral trials had high rates (28.4%). Trials opening in the Northeast of the United States had the highest regional English requirement rates (10.7%), while trials opening in more than one region had the lowest (3.3%, pEnglish fluency requirements (odds ratio=0.92 for each 10% increase in proportion of Hispanics, 95% confidence interval=0.86-0.98, p=0.013). Trials opening in ZIP codes with more residents self-identifying as Black/African American (odds ratio=1.87, 95% confidence interval=1.36-2.58, pEnglish fluency requirements. ZIP codes with higher poverty rates had trials with more English-language restrictions (odds ratio=1.06 for a 10% poverty rate increase, 95% confidence interval=1.001-1.11, p=0.045). There was a statistically significant interaction between year and intervention type, such that the increase in English fluency requirements was more common for some interventions than for others. The proportion of clinical trials registered with ClinicalTrials.gov that have English fluency

Causal Effect Inference with Deep Latent-Variable Models

NARCIS (Netherlands)

Louizos, C; Shalit, U.; Mooij, J.; Sontag, D.; Zemel, R.; Welling, M.

2017-01-01

Learning individual-level causal effects from observational data, such as inferring the most effective medication for a specific patient, is a problem of growing importance for policy makers. The most important aspect of inferring causal effects from observational data is the handling of

Causal inference in survival analysis using pseudo-observations

DEFF Research Database (Denmark)

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

2017-01-01

Causal inference for non-censored response variables, such as binary or quantitative outcomes, is often based on either (1) direct standardization ('G-formula') or (2) inverse probability of treatment assignment weights ('propensity score'). To do causal inference in survival analysis, one needs ...

Causal Indicators Can Help to Interpret Factors

Science.gov (United States)

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)…

QED representation for the net of causal loops

Science.gov (United States)

Ciolli, Fabio; Ruzzi, Giuseppe; Vasselli, Ezio

2015-06-01

The present work tackles the existence of local gauge symmetries in the setting of Algebraic Quantum Field Theory (AQFT). The net of causal loops, previously introduced by the authors, is a model independent construction of a covariant net of local C*-algebras on any 4-dimensional globally hyperbolic space-time, aimed to capture structural properties of any reasonable quantum gauge theory. Representations of this net can be described by causal and covariant connection systems, and local gauge transformations arise as maps between equivalent connection systems. The present paper completes these abstract results, realizing QED as a representation of the net of causal loops in Minkowski space-time. More precisely, we map the quantum electromagnetic field Fμν, not free in general, into a representation of the net of causal loops and show that the corresponding connection system and the local gauge transformations find a counterpart in terms of Fμν.

Causal learning is collaborative: Examining explanation and exploration in social contexts.

Science.gov (United States)

Legare, Cristine H; Sobel, David M; Callanan, Maureen

2017-10-01

Causal learning in childhood is a dynamic and collaborative process of explanation and exploration within complex physical and social environments. Understanding how children learn causal knowledge requires examining how they update beliefs about the world given novel information and studying the processes by which children learn in collaboration with caregivers, educators, and peers. The objective of this article is to review evidence for how children learn causal knowledge by explaining and exploring in collaboration with others. We review three examples of causal learning in social contexts, which elucidate how interaction with others influences causal learning. First, we consider children's explanation-seeking behaviors in the form of "why" questions. Second, we examine parents' elaboration of meaning about causal relations. Finally, we consider parents' interactive styles with children during free play, which constrains how children explore. We propose that the best way to understand children's causal learning in social context is to combine results from laboratory and natural interactive informal learning environments.

Comparing the Cognitive Process of Circular Causality in Two Patients with Strokes through Qualitative Analysis.

Science.gov (United States)

Derakhshanrad, Seyed Alireza; Piven, Emily; Ghoochani, Bahareh Zeynalzadeh

2017-10-01

Walter J. Freeman pioneered the neurodynamic model of brain activity when he described the brain dynamics for cognitive information transfer as the process of circular causality at intention, meaning, and perception (IMP) levels. This view contributed substantially to establishment of the Intention, Meaning, and Perception Model of Neuro-occupation in occupational therapy. As described by the model, IMP levels are three components of the brain dynamics system, with nonlinear connections that enable cognitive function to be processed in a circular causality fashion, known as Cognitive Process of Circular Causality (CPCC). Although considerable research has been devoted to study the brain dynamics by sophisticated computerized imaging techniques, less attention has been paid to study it through investigating the adaptation process of thoughts and behaviors. To explore how CPCC manifested thinking and behavioral patterns, a qualitative case study was conducted on two matched female participants with strokes, who were of comparable ages, affected sides, and other characteristics, except for their resilience and motivational behaviors. CPCC was compared by matrix analysis between two participants, using content analysis with pre-determined categories. Different patterns of thinking and behavior may have happened, due to disparate regulation of CPCC between two participants.

Human Papilloma Viruses and Breast Cancer - Assessment of Causality.

Science.gov (United States)

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

2016-01-01

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

Causality and Free Will

Czech Academy of Sciences Publication Activity Database

Hvorecký, Juraj

2012-01-01

Roč. 19, Supp.2 (2012), s. 64-69 ISSN 1335-0668 R&D Projects: GA ČR(CZ) GAP401/12/0833 Institutional support: RVO:67985955 Keywords : conciousness * free will * determinism * causality Subject RIV: AA - Philosophy ; Religion

The causal effect of family income on child health in the U.K.

Science.gov (United States)

Kuehnle, Daniel

2014-07-01

Recent studies examining the effect of family income on child health have been unable to account for the endogeneity of income. Using data from a British cohort study, we address this gap by exploiting exogenous variation in local labour market characteristics to instrument for family income. We estimate the causal effect of family income on different measures of child health and explore the role of potential transmission mechanisms. We find that income has a very small but significant causal effect on subjective child health and no significant effect on chronic health conditions, apart from respiratory illnesses. Using the panel structure, we show that the timing of income does not matter for young children. Moreover, our results provide further evidence that parental health does not drive a spurious relationship between family income and child health. Our study implies that financial transfers are unlikely to deliver substantial improvements in child health. Copyright © 2014 Elsevier B.V. All rights reserved.

Using large-scale Granger causality to study changes in brain network properties in the Clinically Isolated Syndrome (CIS) stage of multiple sclerosis

Science.gov (United States)

Abidin, Anas Z.; Chockanathan, Udaysankar; DSouza, Adora M.; Inglese, Matilde; Wismüller, Axel

2017-03-01

Clinically Isolated Syndrome (CIS) is often considered to be the first neurological episode associated with Multiple sclerosis (MS). At an early stage the inflammatory demyelination occurring in the CNS can manifest as a change in neuronal metabolism, with multiple asymptomatic white matter lesions detected in clinical MRI. Such damage may induce topological changes of brain networks, which can be captured by advanced functional MRI (fMRI) analysis techniques. We test this hypothesis by capturing the effective relationships of 90 brain regions, defined in the Automated Anatomic Labeling (AAL) atlas, using a large-scale Granger Causality (lsGC) framework. The resulting networks are then characterized using graph-theoretic measures that quantify various network topology properties at a global as well as at a local level. We study for differences in these properties in network graphs obtained for 18 subjects (10 male and 8 female, 9 with CIS and 9 healthy controls). Global network properties captured trending differences with modularity and clustering coefficient (pdifferences in some regions of the inferior frontal and parietal lobe. We conclude that multivariate analysis of fMRI time-series can reveal interesting information about changes occurring in the brain in early stages of MS.

Causality and skies: is non-refocussing necessary?

International Nuclear Information System (INIS)

Bautista, A; Ibort, A; Lafuente, J

2015-01-01

The causal structure of a strongly causal, null pseudo-convex, space-time M is completely characterized in terms of a partial order on its space of skies defined by means of a class of non-negative Legendrian isotopies called sky isotopies. It is also shown that such partial order is determined by the class of future causal celestial curves, that is, curves in the space of light rays which are tangent to skies and such that they determine non-negative sky isotopies. It will also be proved that the space of skies Σ equipped with Low’s (or reconstructive) topology is homeomorphic and diffeomorphic to M under the only additional assumption that M separates skies, that is, that different events determine different skies. The sky-separating property of M is sharp and the previous result provides an answer to the question about the class of space-times whose causal structure, topological and differentiable structure can be reconstructed from their spaces of light rays and skies. These results can be understood as a Malament–Hawking-like theorem stated in terms of the partial order defined on the space of skies. (paper)

A quantum probability model of causal reasoning

Directory of Open Access Journals (Sweden)

Jennifer S Trueblood

2012-05-01

Full Text Available People can often outperform statistical methods and machine learning algorithms in situations that involve making inferences about the relationship between causes and effects. While people are remarkably good at causal reasoning in many situations, there are several instances where they deviate from expected responses. This paper examines three situations where judgments related to causal inference problems produce unexpected results and describes a quantum inference model based on the axiomatic principles of quantum probability theory that can explain these effects. Two of the three phenomena arise from the comparison of predictive judgments (i.e., the conditional probability of an effect given a cause with diagnostic judgments (i.e., the conditional probability of a cause given an effect. The third phenomenon is a new finding examining order effects in predictive causal judgments. The quantum inference model uses the notion of incompatibility among different causes to account for all three phenomena. Psychologically, the model assumes that individuals adopt different points of view when thinking about different causes. The model provides good fits to the data and offers a coherent account for all three causal reasoning effects thus proving to be a viable new candidate for modeling human judgment.

Scalar field Green functions on causal sets

International Nuclear Information System (INIS)

Nomaan Ahmed, S; Surya, Sumati; Dowker, Fay

2017-01-01

We examine the validity and scope of Johnston’s models for scalar field retarded Green functions on causal sets in 2 and 4 dimensions. As in the continuum, the massive Green function can be obtained from the massless one, and hence the key task in causal set theory is to first identify the massless Green function. We propose that the 2d model provides a Green function for the massive scalar field on causal sets approximated by any topologically trivial 2-dimensional spacetime. We explicitly demonstrate that this is indeed the case in a Riemann normal neighbourhood. In 4d the model can again be used to provide a Green function for the massive scalar field in a Riemann normal neighbourhood which we compare to Bunch and Parker’s continuum Green function. We find that the same prescription can also be used for de Sitter spacetime and the conformally flat patch of anti-de Sitter spacetime. Our analysis then allows us to suggest a generalisation of Johnston’s model for the Green function for a causal set approximated by 3-dimensional flat spacetime. (paper)

Norms and customs: causally important or causally impotent?

Science.gov (United States)

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.

Hip fracture in the elderly: a re-analysis of the EPIDOS study with causal Bayesian networks.

Science.gov (United States)

Caillet, Pascal; Klemm, Sarah; Ducher, Michel; Aussem, Alexandre; Schott, Anne-Marie

2015-01-01

Hip fractures commonly result in permanent disability, institutionalization or death in elderly. Existing hip-fracture predicting tools are underused in clinical practice, partly due to their lack of intuitive interpretation. By use of a graphical layer, Bayesian network models could increase the attractiveness of fracture prediction tools. Our aim was to study the potential contribution of a causal Bayesian network in this clinical setting. A logistic regression was performed as a standard control approach to check the robustness of the causal Bayesian network approach. EPIDOS is a multicenter study, conducted in an ambulatory care setting in five French cities between 1992 and 1996 and updated in 2010. The study included 7598 women aged 75 years or older, in which fractures were assessed quarterly during 4 years. A causal Bayesian network and a logistic regression were performed on EPIDOS data to describe major variables involved in hip fractures occurrences. Both models had similar association estimations and predictive performances. They detected gait speed and mineral bone density as variables the most involved in the fracture process. The causal Bayesian network showed that gait speed and bone mineral density were directly connected to fracture and seem to mediate the influence of all the other variables included in our model. The logistic regression approach detected multiple interactions involving psychotropic drug use, age and bone mineral density. Both approaches retrieved similar variables as predictors of hip fractures. However, Bayesian network highlighted the whole web of relation between the variables involved in the analysis, suggesting a possible mechanism leading to hip fracture. According to the latter results, intervention focusing concomitantly on gait speed and bone mineral density may be necessary for an optimal prevention of hip fracture occurrence in elderly people.

BioCause: Annotating and analysing causality in the biomedical domain.

Science.gov (United States)

Mihăilă, Claudiu; Ohta, Tomoko; Pyysalo, Sampo; Ananiadou, Sophia

2013-01-16

Biomedical corpora annotated with event-level information represent an important resource for domain-specific information extraction (IE) systems. However, bio-event annotation alone cannot cater for all the needs of biologists. Unlike work on relation and event extraction, most of which focusses on specific events and named entities, we aim to build a comprehensive resource, covering all statements of causal association present in discourse. Causality lies at the heart of biomedical knowledge, such as diagnosis, pathology or systems biology, and, thus, automatic causality recognition can greatly reduce the human workload by suggesting possible causal connections and aiding in the curation of pathway models. A biomedical text corpus annotated with such relations is, hence, crucial for developing and evaluating biomedical text mining. We have defined an annotation scheme for enriching biomedical domain corpora with causality relations. This schema has subsequently been used to annotate 851 causal relations to form BioCause, a collection of 19 open-access full-text biomedical journal articles belonging to the subdomain of infectious diseases. These documents have been pre-annotated with named entity and event information in the context of previous shared tasks. We report an inter-annotator agreement rate of over 60% for triggers and of over 80% for arguments using an exact match constraint. These increase significantly using a relaxed match setting. Moreover, we analyse and describe the causality relations in BioCause from various points of view. This information can then be leveraged for the training of automatic causality detection systems. Augmenting named entity and event annotations with information about causal discourse relations could benefit the development of more sophisticated IE systems. These will further influence the development of multiple tasks, such as enabling textual inference to detect entailments, discovering new facts and providing new

Theories of conduct disorder: a causal modelling analysis

NARCIS (Netherlands)

Krol, N.P.C.M.; Morton, J.; Bruyn, E.E.J. De

2004-01-01

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

Violation of causality in f(T) gravity

Energy Technology Data Exchange (ETDEWEB)

Otalora, G. [Pontificia Universidad Catolica de Valparaiso, Instituto de Fisica, Valparaiso (Chile); Reboucas, M.J. [Centro Brasileiro de Pesquisas Fisicas, Rio de Janeiro, RJ (Brazil)

2017-11-15

In the standard formulation, the f(T) field equations are not invariant under local Lorentz transformations, and thus the theory does not inherit the causal structure of special relativity. Actually, even locally violation of causality can occur in this formulation of f(T) gravity. A locally Lorentz covariant f(T) gravity theory has been devised recently, and this local causality problem seems to have been overcome. The non-locality question, however, is left open. If gravitation is to be described by this covariant f(T) gravity theory there are a number of issues that ought to be examined in its context, including the question as to whether its field equations allow homogeneous Goedel-type solutions, which necessarily leads to violation of causality on non-local scale. Here, to look into the potentialities and difficulties of the covariant f(T) theories, we examine whether they admit Goedel-type solutions. We take a combination of a perfect fluid with electromagnetic plus a scalar field as source, and determine a general Goedel-type solution, which contains special solutions in which the essential parameter of Goedel-type geometries, m{sup 2}, defines any class of homogeneous Goedel-type geometries. We show that solutions of the trigonometric and linear classes (m{sup 2} < 0 and m = 0) are permitted only for the combined matter sources with an electromagnetic field matter component. We extended to the context of covariant f(T) gravity a theorem which ensures that any perfect-fluid homogeneous Goedel-type solution defines the same set of Goedel tetrads h{sub A}{sup μ} up to a Lorentz transformation. We also showed that the single massless scalar field generates Goedel-type solution with no closed time-like curves. Even though the covariant f(T) gravity restores Lorentz covariance of the field equations and the local validity of the causality principle, the bare existence of the Goedel-type solutions makes apparent that the covariant formulation of f(T) gravity

The balanced survivor average causal effect.

Science.gov (United States)

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

2013-05-07

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

[Clinical characteristics of patients with juvenile localized scleroderma].

Science.gov (United States)

Sun, Qiu-Ning; Du, Wei; Hu, Bin; Liu, Pai; Yuan, Xie

2009-02-01

To investigate the clinical characteristics of juvenile localized scleroderma (JLS). The clinical data of 100 outpatients with JLS who were admitted to PUMC Hospital from 2000 to 2008 were retrospectively analyzed. Of a total of 100 cases, 51 (51%) were confirmed as linear scleroderma, 26 (26%) as plaque morphea, 26 (26%) as deep morphea, 12 (12%) as generalized morphea, and 15 (15%) as a mixed subtype. Nine patients (9%) had family histories of rheumatic or autoimmune diseases, while 16 (16%) might be triggered by unknown factors. Totally 84 patients underwent antinuclear antibody tests and 38 patients (45.2%) had positive results. Linear scleroderma are the most frequent subtype of JLS. Localized scleroderma may be associated with some autoimmune-related causes.

Evaluation of near-miss and adverse events in radiation oncology using a comprehensive causal factor taxonomy.

Science.gov (United States)

Spraker, Matthew B; Fain, Robert; Gopan, Olga; Zeng, Jing; Nyflot, Matthew; Jordan, Loucille; Kane, Gabrielle; Ford, Eric

Incident learning systems (ILSs) are a popular strategy for improving safety in radiation oncology (RO) clinics, but few reports focus on the causes of errors in RO. The goal of this study was to test a causal factor taxonomy developed in 2012 by the American Association of Physicists in Medicine and adopted for use in the RO: Incident Learning System (RO-ILS). Three hundred event reports were randomly selected from an institutional ILS database and Safety in Radiation Oncology (SAFRON), an international ILS. The reports were split into 3 groups of 100 events each: low-risk institutional, high-risk institutional, and SAFRON. Three raters retrospectively analyzed each event for contributing factors using the American Association of Physicists in Medicine taxonomy. No events were described by a single causal factor (median, 7). The causal factor taxonomy was found to be applicable for all events, but 4 causal factors were not described in the taxonomy: linear accelerator failure (n = 3), hardware/equipment failure (n = 2), failure to follow through with a quality improvement intervention (n = 1), and workflow documentation was misleading (n = 1). The most common causal factor categories contributing to events were similar in all event types. The most common specific causal factor to contribute to events was a "slip causing physical error." Poor human factors engineering was the only causal factor found to contribute more frequently to high-risk institutional versus low-risk institutional events. The taxonomy in the study was found to be applicable for all events and may be useful in root cause analyses and future studies. Communication and human behaviors were the most common errors affecting all types of events. Poor human factors engineering was found to specifically contribute to high-risk more than low-risk institutional events, and may represent a strategy for reducing errors in all types of events. Copyright © 2017 American Society for Radiation Oncology

Claudin-Low Breast Cancer; Clinical & Pathological Characteristics.

Directory of Open Access Journals (Sweden)

Kay Dias

Full Text Available Claudin-low breast cancer is a molecular type of breast cancer originally identified by gene expression profiling and reportedly associated with poor survival. Claudin-low tumors have been recognised to preferentially display a triple-negative phenotype, however only a minority of triple-negative breast cancers are claudin-low. We sought to identify an immunohistochemical profile for claudin-low tumors that could facilitate their identification in formalin fixed paraffin embedded tumor material. First, an in silico collection of ~1600 human breast cancer expression profiles was assembled and all claudin-low tumors identified. Second, genes differentially expressed between claudin-low tumors and all other molecular subtypes of breast cancer were identified. Third, a number of these top differentially expressed genes were tested using immunohistochemistry for expression in a diverse panel of breast cancer cell lines to determine their specificity for claudin-low tumors. Finally, the immunohistochemical panel found to be most characteristic of claudin-low tumors was examined in a cohort of 942 formalin fixed paraffin embedded human breast cancers with >10 years clinical follow-up to evaluate the clinico-pathologic and survival characteristics of this tumor subtype. Using this approach we determined that claudin-low breast cancer is typically negative for ER, PR, HER2, claudin 3, claudin 4, claudin 7 and E-cadherin. Claudin-low tumors identified with this immunohistochemical panel, were associated with young age of onset, higher tumor grade, larger tumor size, extensive lymphocytic infiltrate and a circumscribed tumor margin. Patients with claudin-low tumors had a worse overall survival when compared to patients with luminal A type breast cancer. Interestingly, claudin-low tumors were associated with a low local recurrence rate following breast conserving therapy. In conclusion, a limited panel of antibodies can facilitate the identification of

The Bradford Hill considerations on causality: a counterfactual perspective

Directory of Open Access Journals (Sweden)

Höfler Michael

2005-11-01

Full Text Available Abstract Bradford Hill's considerations published in 1965 had an enormous influence on attempts to separate causal from non-causal explanations of observed associations. These considerations were often applied as a checklist of criteria, although they were by no means intended to be used in this way by Hill himself. Hill, however, avoided defining explicitly what he meant by "causal effect". This paper provides a fresh point of view on Hill's considerations from the perspective of counterfactual causality. I argue that counterfactual arguments strongly contribute to the question of when to apply the Hill considerations. Some of the considerations, however, involve many counterfactuals in a broader causal system, and their heuristic value decreases as the complexity of a system increases; the danger of misapplying them can be high. The impacts of these insights for study design and data analysis are discussed. The key analysis tool to assess the applicability of Hill's considerations is multiple bias modelling (Bayesian methods and Monte Carlo sensitivity analysis; these methods should be used much more frequently.

Temporal and Statistical Information in Causal Structure Learning

Science.gov (United States)

McCormack, Teresa; Frosch, Caren; Patrick, Fiona; Lagnado, David

2015-01-01

Three experiments examined children's and adults' abilities to use statistical and temporal information to distinguish between common cause and causal chain structures. In Experiment 1, participants were provided with conditional probability information and/or temporal information and asked to infer the causal structure of a 3-variable mechanical…

Ends, Principles, and Causal Explanation in Educational Justice

Science.gov (United States)

Dum, Jenn

2017-01-01

Many principles characterize educational justice in terms of the relationship between educational inputs, outputs and distributive standards. Such principles depend upon the "causal pathway view" of education. It is implicit in this view that the causally effective aspects of education can be understood as separate from the normative…

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

Science.gov (United States)

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

2012-08-05

We argue for a theoretical link between the development of an extended period of immaturity in human evolution and the emergence of powerful and wide-ranging causal learning mechanisms, specifically the use of causal models and Bayesian learning. We suggest that exploratory childhood learning, childhood play in particular, and causal cognition are closely connected. We report an empirical study demonstrating one such connection--a link between pretend play and counterfactual causal reasoning. Preschool children given new information about a causal system made very similar inferences both when they considered counterfactuals about the system and when they engaged in pretend play about it. Counterfactual cognition and causally coherent pretence were also significantly correlated even when age, general cognitive development and executive function were controlled for. These findings link a distinctive human form of childhood play and an equally distinctive human form of causal inference. We speculate that, during human evolution, computations that were initially reserved for solving particularly important ecological problems came to be used much more widely and extensively during the long period of protected immaturity.

Causal interpretation of stochastic differential equations

DEFF Research Database (Denmark)

Sokol, Alexander; Hansen, Niels Richard

2014-01-01

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

Characteristics of adults with anxiety or depression treated at an internet clinic: comparison with a national survey and an outpatient clinic.

Science.gov (United States)

Titov, Nickolai; Andrews, Gavin; Kemp, Alice; Robinson, Emma

2010-05-28

There is concern that people seeking treatment over the Internet for anxiety or depressive disorders may not resemble the general population or have less severe disorders than patients attending outpatient clinics or cases identified in community surveys. Thus the response to treatment in Internet based trials might not generalize. We reviewed the characteristics of applicants to an Australian Internet-based treatment clinic for anxiety and depression, and compared this sample with people from a national epidemiological survey and a sample of patients at a specialist outpatient anxiety and depression clinic. Participants included 774 volunteers to an Internet clinic, 454 patients at a specialist anxiety disorders outpatient clinic, and 627 cases identified in a national epidemiological survey. Main measures included demographic characteristics, and severity of symptoms as measured by the Kessler 10-Item scale (K-10), the 12-item World Health Organisation Disability Assessment Schedule second edition (WHODAS-II), the Penn State Worry Questionnaire (PSWQ), the Body Sensations Questionnaire (BSQ), the Automatic Cognitions Questionnaire (ACQ), the Social Interaction Anxiety Scale (SIAS) and the Social Phobia Scale (SPS). The severity of symptoms of participants attending the two clinics was similar, and both clinic samples were more severe than cases in the epidemiological survey. The Internet clinic and national samples were older and comprised more females than those attending the outpatient clinic. The Internet clinic sample were more likely to be married than the other samples. The Internet clinic and outpatient clinic samples had higher levels of educational qualifications than the national sample, but employment status was similar across groups. The Internet clinic sample have disorders as severe as those attending an outpatient clinic, but with demographic characteristics more consistent with the national sample. These data indicate that the benefits of Internet

Characteristics of adults with anxiety or depression treated at an internet clinic: comparison with a national survey and an outpatient clinic.

Directory of Open Access Journals (Sweden)

Nickolai Titov

2010-05-01

Full Text Available There is concern that people seeking treatment over the Internet for anxiety or depressive disorders may not resemble the general population or have less severe disorders than patients attending outpatient clinics or cases identified in community surveys. Thus the response to treatment in Internet based trials might not generalize.We reviewed the characteristics of applicants to an Australian Internet-based treatment clinic for anxiety and depression, and compared this sample with people from a national epidemiological survey and a sample of patients at a specialist outpatient anxiety and depression clinic. Participants included 774 volunteers to an Internet clinic, 454 patients at a specialist anxiety disorders outpatient clinic, and 627 cases identified in a national epidemiological survey. Main measures included demographic characteristics, and severity of symptoms as measured by the Kessler 10-Item scale (K-10, the 12-item World Health Organisation Disability Assessment Schedule second edition (WHODAS-II, the Penn State Worry Questionnaire (PSWQ, the Body Sensations Questionnaire (BSQ, the Automatic Cognitions Questionnaire (ACQ, the Social Interaction Anxiety Scale (SIAS and the Social Phobia Scale (SPS.The severity of symptoms of participants attending the two clinics was similar, and both clinic samples were more severe than cases in the epidemiological survey. The Internet clinic and national samples were older and comprised more females than those attending the outpatient clinic. The Internet clinic sample were more likely to be married than the other samples. The Internet clinic and outpatient clinic samples had higher levels of educational qualifications than the national sample, but employment status was similar across groups.The Internet clinic sample have disorders as severe as those attending an outpatient clinic, but with demographic characteristics more consistent with the national sample. These data indicate that the benefits

Occupational safety management: the role of causal attribution.

Science.gov (United States)

Gyekye, Seth Ayim

2010-12-01

The paper addresses the causal attribution theory, an old and well-established theme in social psychology which denotes the everyday, commonsense explanations that people use to explain events and the world around them. The attribution paradigm is considered one of the most appropriate analytical tools for exploratory and descriptive studies in social psychology and organizational literature. It affords the possibility of describing accident processes as objectively as possible and with as much detail as possible. Causal explanations are vital to the formal analysis of workplace hazards and accidents, as they determine how organizations act to prevent accident recurrence. Accordingly, they are regarded as fundamental and prerequisite elements for safety management policies. The paper focuses primarily on the role of causal attributions in occupational and industrial accident analyses and implementation of safety interventions. It thus serves as a review of the contribution of attribution theory to occupational and industrial accidents. It comprises six sections. The first section presents an introduction to the classic attribution theories, and the second an account of the various ways in which the attribution paradigm has been applied in organizational settings. The third and fourth sections review the literature on causal attributions and demographic and organizational variables respectively. The sources of attributional biases in social psychology and how they manifest and are identified in the causal explanations for industrial and occupational accidents are treated in the fifth section. Finally, conclusion and recommendations are presented. The recommendations are particularly important for the reduction of workplace accidents and associated costs. The paper touches on the need for unbiased causal analyses, belief in the preventability of accidents, and the imperative role of management in occupational safety management.

Clinical Characteristics of Dry Eye Patients With Chronic Pain Syndromes

NARCIS (Netherlands)

Vehof, Jelle; Smitt-Kamminga, Nicole Sillevis; Kozareva, Diana; Nibourg, Simone A.; Hammond, Christopher J.

PURPOSE: To investigate clinical characteristics of dry eye disease (DED) patients with a chronic pain syndrome. DESIGN: Cross-sectional. study. METHODS: Four hundred twenty-five patients of a tertiary care DED patient cohort in the Netherlands were included. Chronic pain syndromes irritable bowel

THE CAUSAL ANALYSIS / DIAGNOSIS DECISION ...

Science.gov (United States)

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

Spatial-Temporal Synchrophasor Data Characterization and Analytics in Smart Grid Fault Detection, Identification, and Impact Causal Analysis

Energy Technology Data Exchange (ETDEWEB)

Jiang, Huaiguang; Dai, Xiaoxiao; Gao, David Wenzhong; Zhang, Jun Jason; Zhang, Yingchen; Muljadi, Eduard

2016-09-01

An approach of big data characterization for smart grids (SGs) and its applications in fault detection, identification, and causal impact analysis is proposed in this paper, which aims to provide substantial data volume reduction while keeping comprehensive information from synchrophasor measurements in spatial and temporal domains. Especially, based on secondary voltage control (SVC) and local SG observation algorithm, a two-layer dynamic optimal synchrophasor measurement devices selection algorithm (OSMDSA) is proposed to determine SVC zones, their corresponding pilot buses, and the optimal synchrophasor measurement devices. Combining the two-layer dynamic OSMDSA and matching pursuit decomposition, the synchrophasor data is completely characterized in the spatial-temporal domain. To demonstrate the effectiveness of the proposed characterization approach, SG situational awareness is investigated based on hidden Markov model based fault detection and identification using the spatial-temporal characteristics generated from the reduced data. To identify the major impact buses, the weighted Granger causality for SGs is proposed to investigate the causal relationship of buses during system disturbance. The IEEE 39-bus system and IEEE 118-bus system are employed to validate and evaluate the proposed approach.

Untangling the causal relationship between tax burden distribution and economic growth in 23 OECD countries: Fresh evidence from linear and non-linear Granger causality

Directory of Open Access Journals (Sweden)

Sami Saafi

2017-12-01

Full Text Available The aim of the paper is to investigate the linear and nonlinear causality between a set of alternative tax burden ratios and economic growth in 23 OECD countries. To that end, the linear causality approach of Toda– Yamamoto (1995 and the nonparametric causality method of Kyrtsou and Labys (2006 are applied to annual data spanning from 1970 to 2014. Results obtained from the nonlinear causality test tend to reject the neutrality hypothesis for the tax structure–growth relationship in 19 of the 23 OECD countries. In the majority of the countries under investigation, the evidence is in line with the growth hypothesis where causality running from economic growth to tax burden ratios was detected in Australia, Denmark, Finland, Japan, New Zealand, and Norway. The opposite causality running from tax structure to economic growth was found in Germany, Netherlands, Portugal, and Sweden. In contrast, the neutrality hypothesis was supported in Austria, Italy, Luxembourg, and the USA, whereas the feedback hypothesis was supported in Turkey and the UK. Additional robustness checks show that when the signs of variations are taken into account, there is an asymmetric causality running from positive tax burden shocks to positive per capita GDP shocks for Belgium, France, and Turkey. Overall, our findings suggest that policy implications of the tax structure-economic growth relationships should be interpreted with caution, taking into account the test-dependent and country-specific results.

Causal Learning in Gambling Disorder: Beyond the Illusion of Control.

Science.gov (United States)

Perales, José C; Navas, Juan F; Ruiz de Lara, Cristian M; Maldonado, Antonio; Catena, Andrés

2017-06-01

Causal learning is the ability to progressively incorporate raw information about dependencies between events, or between one's behavior and its outcomes, into beliefs of the causal structure of the world. In spite of the fact that some cognitive biases in gambling disorder can be described as alterations of causal learning involving gambling-relevant cues, behaviors, and outcomes, general causal learning mechanisms in gamblers have not been systematically investigated. In the present study, we compared gambling disorder patients against controls in an instrumental causal learning task. Evidence of illusion of control, namely, overestimation of the relationship between one's behavior and an uncorrelated outcome, showed up only in gamblers with strong current symptoms. Interestingly, this effect was part of a more complex pattern, in which gambling disorder patients manifested a poorer ability to discriminate between null and positive contingencies. Additionally, anomalies were related to gambling severity and current gambling disorder symptoms. Gambling-related biases, as measured by a standard psychometric tool, correlated with performance in the causal learning task, but not in the expected direction. Indeed, performance of gamblers with stronger biases tended to resemble the one of controls, which could imply that anomalies of causal learning processes play a role in gambling disorder, but do not seem to underlie gambling-specific biases, at least in a simple, direct way.

The discourse of causal explanations in school science

Science.gov (United States)

Slater, Tammy Jayne Anne

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

Nonparametric Identification of Causal Effects under Temporal Dependence

Science.gov (United States)

Dafoe, Allan

2018-01-01

Social scientists routinely address temporal dependence by adopting a simple technical fix. However, the correct identification strategy for a causal effect depends on causal assumptions. These need to be explicated and justified; almost no studies do so. This article addresses this shortcoming by offering a precise general statement of the…

Clinical judgement and the medical profession

Science.gov (United States)

Kienle, Gunver S; Kiene, Helmut

2011-01-01

Objectives Clinical judgment is a central element of the medical profession, essential for the performance of the doctor, and potentially generating information also for other clinicians and for scientists and health care managers. The recently renewed interest in clinical judgement is primarily engaged with its role in communication, diagnosis and decision making. Beyond this issue, the present article highlights the interrelations between clinical judgement, therapy assessment and medical professionalism. Methods Literature review and theory development. Results The article presents different methodological approaches to causality assessment in clinical studies and in clinical judgement, and offers criteria for clinical single case causality. The article outlines models of medical professionalism such as technical rationality and practice epistemology, and characterizes features of professional expertise such as tacit knowledge, reflection in action, and gestalt cognition. Conclusions Consequences of a methodological and logistical advancement of clinical judgment are discussed, both in regard to medical progress and to the renewel of the cognitive basis of the medical profession. PMID:20973873

On Storks and Babies: Correlation, Causality and Field Experiments

Directory of Open Access Journals (Sweden)

Lambrecht Anja

2016-11-01

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

Implications of causality for quantum biology - I: topology change

Science.gov (United States)

Scofield, D. F.; Collins, T. C.

2018-06-01

A framework for describing the causal, topology changing, evolution of interacting biomolecules is developed. The quantum dynamical manifold equations (QDMEs) derived from this framework can be related to the causality restrictions implied by a finite speed of light and to Planck's constant to set a transition frequency scale. The QDMEs imply conserved stress-energy, angular-momentum and Noether currents. The functional whose extremisation leads to this result provides a causal, time-dependent, non-equilibrium generalisation of the Hohenberg-Kohn theorem. The system of dynamical equations derived from this functional and the currents J derived from the QDMEs are shown to be causal and consistent with the first and second laws of thermodynamics. This has the potential of allowing living systems to be quantum mechanically distinguished from non-living ones.

Descriptive features and causal attributions of headache in an Australian community.

Science.gov (United States)

Fernandez, E; Sheffield, J

1996-04-01

The reported characteristics and causes of headache differ across individuals and between groups. Such differences are of interest from an epidemiological point of view. This study set out to identify the main descriptive features and causal attributions of headache within an Australian urban community. A sample of 261 subjects reporting headache volunteered to participate in the survey. Subjects completed a self-report questionnaire for assessing demographic variables, headache parameters (intensity, duration, etc), headache medication habits, and perceived causes of one's headache (as in the UK headache survey by Blau, 1990). Results revealed that the typical headache sufferer was a middle-aged employed individual. Migraine versus tension headache were equivalent in number, and on the average, subjects experienced moderate intensity, day-long headaches that recurred about nine times per month. With regard to causal attributions, the prevalence of headaches due to mental stress was higher than that due to any other single stimulus (eg, noise, exercise), and alcohol was the most frequent dietary cause of headache. These findings are generally consistent with those from previous surveys, although some interesting departures emerge which may be accounted for by demographic differences in the populations studied.

On the Temporal Causal Relationship Between Macroeconomic Variables

Directory of Open Access Journals (Sweden)

Srinivasan Palamalai

2014-02-01

Full Text Available The present study examines the dynamic interactions among macroeconomic variables such as real output, prices, money supply, interest rate (IR, and exchange rate (EXR in India during the pre-economic crisis and economic crisis periods, using the autoregressive distributed lag (ARDL bounds test for cointegration, Johansen and Juselius multivariate cointegration test, Granger causality/Block exogeneity Wald test based on Vector Error Correction Model, variance decomposition analysis and impulse response functions. The empirical results reveal a stronger long-run bilateral relationship between real output, price level, IR, and EXR during the pre-crisis sample period. Moreover, the empirical results confirm a unidirectional short-run causality running from price level to EXR, IR to price level, and real output to money supply during the pre-crisis period. Also, it is evident from the test results that there exist short-run bidirectional relationships running between real output and EXR, price level and IR, and IR and EXR in the pre-crisis era, respectively. Most importantly, long-run bidirectional causality is found between real output, EXR, and IR during the economic crisis period. And the study results indicate short-run bidirectional causality between money supply and EXR, IR and price level, and IR and output in India during the crisis era. Also, a short-run unidirectional causality runs from prices to real output in the crisis period.

Schizophrenia-like symptoms in narcolepsy type 1: shared and distinctive clinical characteristics.

Science.gov (United States)

Plazzi, Giuseppe; Fabbri, Chiara; Pizza, Fabio; Serretti, Alessandro

2015-01-01

The occurrence of psychotic symptoms in narcolepsy type 1 (NT1) has been reported as responsible for delayed diagnosis due to the misdiagnosis of schizophrenia. This study aimed to identify shared and distinctive clinical characteristics between NT1 and schizophrenia, with the focus on psychotic symptoms. A total of 28 NT1 and 21 schizophrenia patients were included. Hallucination characteristics and PANSS (Positive and Negative Syndrome Scale), HRSD (Hamilton Rating Scale for Depression), DES (Dissociative Experiences Scale), and STAI (State-Trait Anxiety Inventory) scores were collected. Symptom overlap was investigated by χ(2), Fisher's or t tests and multiple logistic regression models. Hallucinations and illusions frequently occurred in both diseases. Unimodal hallucinations were more common in schizophrenia (p = 6.30e-07) and multimodal hallucinations in NT1, but no clear difference was identified in their sensory modality. Hypnagogic/hypnopompic hallucinations were typical of NT1 (p = 5.22e-07), and 25% of NT1 patients exhibited some degree of insight deficit. Hypnagogic/hypnopompic hallucinations, unimodal hallucinations and PANSS score were the most distinctive clinical characteristics. Clinical overlap was found in the dissociative and anxiety domains, while higher depressive scores were observed in schizophrenia. The overlap between NT1 and schizophrenia should be further investigated under a clinical and pathogenetic point of view to improve diagnostic and therapeutic approaches. © 2015 S. Karger AG, Basel.

Sex differences in clinical characteristics and outcomes after myocardial infarction

DEFF Research Database (Denmark)

Lam, Carolyn S P; McEntegart, Margaret; Claggett, Brian

2015-01-01

BACKGROUND: We examined the association of sex with clinical characteristics and outcomes in patients following myocardial infarction (MI) in the Valsartan in Acute Myocardial Infarction Trial (VALIANT). METHODS AND RESULTS: A total of 4570 women and 10 133 men with heart failure (HF), left...

Explaining through causal mechanisms

NARCIS (Netherlands)

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

They Work Together to Roar: Kindergartners' Understanding of an Interactive Causal Task

Science.gov (United States)

Solis, S. Lynneth; Grotzer, Tina A.

2016-01-01

The aim of this study was to investigate kindergartners' exploration of interactive causality during their play with a pair of toy sound blocks. Interactive causality refers to a type of causal pattern in which two entities interact to produce a causal force, as in particle attraction and symbiotic relationships. Despite being prevalent in nature,…

An Information Processing Approach to Children's Causal Reasoning.

Science.gov (United States)

Siegler, Robert S.

This paper questions evidence for the thesis that causal reasoning of older children is more logical than that of younger ones, and describes two experiments which attempted to determine (1) whether there are true developmental differences in causal reasoning, and (2) what explanations for developmental differences can be supported. In the first…

Weighting-Based Sensitivity Analysis in Causal Mediation Studies

Science.gov (United States)

Hong, Guanglei; Qin, Xu; Yang, Fan

2018-01-01

Through a sensitivity analysis, the analyst attempts to determine whether a conclusion of causal inference could be easily reversed by a plausible violation of an identification assumption. Analytic conclusions that are harder to alter by such a violation are expected to add a higher value to scientific knowledge about causality. This article…

Causality analysis in business performance measurement system using system dynamics methodology

Science.gov (United States)

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

2014-07-01

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

Information–theoretic implications of quantum causal structures

DEFF Research Database (Denmark)

Chaves, Rafael; Majenz, Christian; Gross, David

2015-01-01

. However, no systematic method is known for treating such problems in a way that generalizes to quantum systems. Here, we describe a general algorithm for computing information–theoretic constraints on the correlations that can arise from a given causal structure, where we allow for quantum systems as well...... as classical random variables. The general technique is applied to two relevant cases: first, we show that the principle of information causality appears naturally in our framework and go on to generalize and strengthen it. Second, we derive bounds on the correlations that can occur in a networked architecture......It is a relatively new insight of classical statistics that empirical data can contain information about causation rather than mere correlation. First algorithms have been proposed that are capable of testing whether a presumed causal relationship is compatible with an observed distribution...

Comparison of a noncausal with a causal relativistic wave-packet evolution

International Nuclear Information System (INIS)

Castro, A.N. de; Jabs, A.

1991-01-01

In order to study causality violation in more detail we contrast the Klein-Gordon wave packet of Rosenstein und Usher with the Dirac wave packet of Bakke and Wergeland. Both packets are initially localized with exponentially bounded tails but just outside the condition of the general Hegerfeldt theorem for causality violation. It turns out that the wave packet of Bakke and Wergeland exhibits all the features investigated by Rosenstein and Usher, except that it never violates relativistic causality. Thus none of those features, in particular the back- and forerunners emerging from the light cone, can be held responsible for causality violation, and the Ruijsenaars integral is not necessarily a measure of the amount of causality violation. (orig.)

Children and adolescents referred for treatment of anxiety disorders: differences in clinical characteristics.

Science.gov (United States)

Waite, Polly; Creswell, Cathy

2014-01-01

Reports of the clinical characteristics of children and adolescents with anxiety disorders are typically based on community populations or from clinical samples with exclusion criterion applied. Little is known about the clinical characteristics of children and adolescents routinely referred for treatment for anxiety disorders. Furthermore, children and adolescents are typically treated as one homogeneous group although they may differ in ways that are clinically meaningful. A consecutive series of children (n=100, aged 6-12 years) and adolescents (n=100, aged 13-18 years), referred to a routine clinical service, were assessed for anxiety and comorbid disorders, school refusal and parental symptoms of psychopathology. Children with a primary anxiety disorder were significantly more likely to be diagnosed with separation anxiety disorder than adolescents. Adolescents with a primary anxiety disorder had significantly higher self and clinician rated anxiety symptoms and had more frequent primary diagnoses of social anxiety disorder, diagnoses and symptoms of mood disorders, and irregular school attendance. Childhood and adolescence were considered categorically as distinct, developmental periods; in reality changes would be unlikely to occur in such a discrete manner. The finding that children and adolescents with anxiety disorders have distinct clinical characteristics has clear implications for treatment. Simply adapting treatments designed for children to make the materials more 'adolescent-friendly' is unlikely to sufficiently meet the needs of adolescents. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

[Kleptomania: clinical characteristics and treatment].

Science.gov (United States)

Grant, Jon E; Odlaug, Brian L

2008-05-01

Kleptomania, a disabling impulse control disorder, is characterized by the repetitive and uncontrollable theft of items that are of little use to the afflicted person. Despite its relatively long history, kleptomania remains poorly understood to the general public, clinicians, and sufferers. This article reviews the literature for what is known about the clinical characteristics, family history, neurobiology, and treatment options for individuals with kleptomania. Kleptomania generally has its onset in late adolescence or early adulthood and appears to be more common among women. Lifetime psychiatric comorbidity is frequent, mainly with other impulse control (20-46%), substance use (23-50%) and mood disorders (45-100%). Individuals with kleptomania suffer significant impairment in their ability to function socially and occupationally. Kleptomania may respond to cognitive behavioral therapy and various pharmacotherapies (lithium, anti-epileptics, and opioid antagonists). Kleptomania is a disabling disorder that results in intense shame, as well as legal, social, family, and occupational problems. Large scale treatment studies are needed.

Granger Causality and Transfer Entropy Are Equivalent for Gaussian Variables

Science.gov (United States)

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

2009-12-01

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

Efficient nonparametric estimation of causal mediation effects

OpenAIRE

Chan, K. C. G.; Imai, K.; Yam, S. C. P.; Zhang, Z.

2016-01-01

An essential goal of program evaluation and scientific research is the investigation of causal mechanisms. Over the past several decades, causal mediation analysis has been used in medical and social sciences to decompose the treatment effect into the natural direct and indirect effects. However, all of the existing mediation analysis methods rely on parametric modeling assumptions in one way or another, typically requiring researchers to specify multiple regression models involving the treat...

The Continuum Limit of Causal Fermion Systems

OpenAIRE

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...

On causal nonrelativistic classical electrodynamics

International Nuclear Information System (INIS)

Goedecke, G.H.

1984-01-01

The differential-difference (DD) motion equations of the causal nonrelativistic classical electrodynamics developed by the author in 1975 are shown to possess only nonrunaway, causal solutions with no discontinuities in particle velocity or position. As an example, the DD equation solution for the problem of an electromagnetic shock incident on an initially stationary charged particle is contrasted with the standard Abraham-Lorentz equation solution. The general Cauchy problem for these DD motion equations is discussed. In general, in order to uniquely determine a solution, the initial data must be more detailed than the standard Cauchy data of initial position and velocity. Conditions are given under which the standard Cauchy data will determine the DD equation solutions to sufficient practical accuracy

Clinical characteristics of Helicobacter pylori-negative drug-negative peptic ulcer bleeding.

Science.gov (United States)

Chung, Woo Chul; Jeon, Eun Jung; Kim, Dae Bum; Sung, Hea Jung; Kim, Yeon-Ji; Lim, Eun Sun; Kim, Min-Ah; Oh, Jung Hwan

2015-07-28

To investigate the clinical characteristics and outcomes of idiopathic Helicobacter pylori (H. pylori)-negative and drug-negative] peptic ulcer bleeding (PUB). A consecutive series of patients who experienced PUB between 2006 and 2012 was retrospectively analyzed. A total of 232 patients were enrolled in this study. The patients were divided into four groups according to the etiologies of PUB: idiopathic, H. pylori-associated, drug-induced and combined (H. pylori-associated and drug-induced) types. We compared the clinical characteristics and outcomes between the groups. When the silver stain or rapid urease tests were H. pylori-negative, we obtained an additional biopsy specimen by endoscopic re-examination and performed an H. pylori antibody test 6-8 wk after the initial endoscopic examination. For a diagnosis of idiopathic PUB, a negative result of an H. pylori antibody test was confirmed. In all cases, re-bleeding was confirmed by endoscopic examination. For the risk assessment, the Blatchford and the Rockall scores were calculated for all patients. For PUB, the frequency of H. pylori infection was 59.5% (138/232), whereas the frequency of idiopathic cases was 8.6% (20/232). When idiopathic PUB was compared to H. pylori-associated PUB, the idiopathic PUB group showed a higher rate of re-bleeding after initial hemostasis during the hospital stay (30% vs 7.4%, P = 0.02). When idiopathic PUB was compared to drug-induced PUB, the patients in the idiopathic PUB group showed a higher rate of re-bleeding after initial hemostasis upon admission (30% vs 2.7%, P ulcer (77% vs 49%, P < 0.01). However, the Blatchford and the Rockall scores were not significantly different between the two groups. Among the patients who experienced drug-induced PUB, no significant differences were found with respect to clinical characteristics, irrespective of H. pylori infection. Idiopathic PUB has unique clinical characteristics such as re-bleeding after initial hemostasis upon admission

Neuro-ophthalmic and clinical characteristics of brain tumours in a ...

African Journals Online (AJOL)

Background: Anecdotally, increasing number of patients are seen at Korle Bu Teaching Hospital (KBTH) with brain tumour. Neuro-ophthalmic symptoms and signs may help in timely diagnosis and intervention. Objective: To evaluate the neuro-ophthalmic and clinical characteristics of brain tumour in patients presenting at a ...

Corporate Governance and Financial Performance Nexus: Any Bidirectional Causality?

Directory of Open Access Journals (Sweden)

Alley Ibrahim S.

2016-06-01

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

Clinical characteristics of patients seizure following the 2016 Kumamoto earthquake.

Science.gov (United States)

Inatomi, Yuichiro; Nakajima, Makoto; Yonehara, Toshiro; Ando, Yukio

2017-06-01

To investigate the clinical characteristics of patients with seizure following the 2016 Kumamoto earthquake. We retrospectively studied patients with seizure admitted to our hospital for 12weeks following the earthquake. We compared the clinical backgrounds and characteristics of the patients: before (the same period from the previous 3years) and after the earthquake; and the early (first 2weeks) and late (subsequent 10weeks) phases. A total of 60 patients with seizure were admitted to the emergency room after the earthquake, and 175 (58.3/year) patients were admitted before the earthquake. Of them, 35 patients with seizure were hospitalized in the Department of Neurology after the earthquake, and 96 (32/year) patients were hospitalized before the earthquake. In patients after the earthquake, males and non-cerebrovascular diseases as an epileptogenic disease were seen more frequently than before the earthquake. During the early phase after the earthquake, female, first-attack, and non-focal-type patients were seen more frequently than during the late phase after the earthquake. These characteristics of patients with seizure during the early phase after the earthquake suggest that many patients had non-epileptic seizures. To prevent seizures following earthquakes, mental stress and physical status of evacuees must be assessed. Copyright © 2017. Published by Elsevier Ltd.

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

Directory of Open Access Journals (Sweden)

Adriatik Hoxha

2010-09-01

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

Contrasting cue-density effects in causal and prediction judgments.

Science.gov (United States)

Vadillo, Miguel A; Musca, Serban C; Blanco, Fernando; Matute, Helena

2011-02-01

Many theories of contingency learning assume (either explicitly or implicitly) that predicting whether an outcome will occur should be easier than making a causal judgment. Previous research suggests that outcome predictions would depart from normative standards less often than causal judgments, which is consistent with the idea that the latter are based on more numerous and complex processes. However, only indirect evidence exists for this view. The experiment presented here specifically addresses this issue by allowing for a fair comparison of causal judgments and outcome predictions, both collected at the same stage with identical rating scales. Cue density, a parameter known to affect judgments, is manipulated in a contingency learning paradigm. The results show that, if anything, the cue-density bias is stronger in outcome predictions than in causal judgments. These results contradict key assumptions of many influential theories of contingency learning.

The relationship of individual characteristics, perceived worksite support and perceived creativity to clinical nurses' innovative outcome.

Science.gov (United States)

Tsai, Hsiu-Min; Liou, Shwu-Ru; Hsiao, Ya-Chu; Cheng, Ching-Yu

2013-09-01

To understand the relationship of individual characteristics, perceived worksite support and perceived personal creativity to clinical nurses' innovative outcome (receiving the Nursing Innovation Award). Since the idea of applying creativity and innovation to clinical nursing practice and management was first advocated in the Nursing Administration Quarterly in 1982, the topic of nursing innovation has gained worldwide attention. To increase the prevalence of nursing innovation, it is important to identify and understand the related factors that influence nurses' innovative outcome. This study used a cross-sectional descriptive survey design. A self-administered questionnaire was completed by 32 award winners and 506 nonawarded clinical nurses in Taiwan. The level of creativity perceived by all participants was moderate-to-high. Individual characteristics (r = 0·61) and worksite support (r = 0·27) were both correlated with perceived creativity. Individual characteristics and worksite support showed some correlation as well (r = 0·21). Individual characteristics and worksite support could predict perceived creativity after controlling for demographic variables, but only individual characteristics had an effect on innovative outcome. Perceived creativity did not have mediation effects either between individual characteristics and innovative outcome or between worksite support and innovative outcome. Clinical nurses' individual characteristics had a direct relationship to innovative outcome, whereas neither worksite support nor creativity was correlated with innovative outcome. Although worksite support did not show effects on innovative outcome, it was related to both perceived creativity and individual characteristics. As suggested by other scholars, there might be other related factors between creativity and innovative outcome. Although worksite support did not have effect on clinical nurses' innovative outcome, it was related to individual characteristics

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

Science.gov (United States)

Caro, Daniel H.

2015-01-01

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

The connexion of duality and causal properties for generalized free fields

International Nuclear Information System (INIS)

Garber, W.D.

1975-01-01

It is shown that the time-slice axiom and the diamond property are equivalent for the generalized free field. If, in addition, there is a mass gap, duality is equivalent to either causality requirement. It is further shown that the local rings associated with certain space-time regions are factors in the case of causal generalized free fields with mass gap. Necessary and sufficient conditions for causality and duality and some examples for causal and acausal generalized free fields are also given. (orig.) [de

Clinical and genetic characteristics of Chinese hereditary nonpolyposis colorectal cancer families

OpenAIRE

Wang, Xu-Lin; Yuan, Ying; Zhang, Su-Zhan; Cai, Shan-Rong; Huang, Yan-Qin; Jiang, Qiang; Zheng, Shu

2006-01-01

AIM: To analyze the clinical characteristics of Chinese hereditary nonpolyposis colorectal cancer (HNPCC) families and to screen the germline mutations of human mismatch repair genes hMLH1 and hMSH2 in the probands.

Causal pathways between substance use disorders and personality pathology

NARCIS (Netherlands)

Verheul, R.; van den Brink, W.

2005-01-01

A high co-occurrence between personality and substance use disorders suggests causal relationships between these conditions. Most empirical evidence strongly supports causal pathways in which (pathological) personality traits contribute to the development of a substance use disorder (i.e., primary

Clinical Relevance of Discourse Characteristics after Right Hemisphere Brain Damage

Science.gov (United States)

Blake, Margaret Lehman

2006-01-01

Purpose: Discourse characteristics of adults with right hemisphere brain damage are similar to those reported for healthy older adults, prompting the question of whether changes are due to neurological lesions or normal aging processes. The clinical relevance of potential differences across groups was examined through ratings by speech-language…

Bulk viscous cosmology with causal transport theory

International Nuclear Information System (INIS)

Piattella, Oliver F.; Fabris, Júlio C.; Zimdahl, Winfried

2011-01-01

We consider cosmological scenarios originating from a single imperfect fluid with bulk viscosity and apply Eckart's and both the full and the truncated Müller-Israel-Stewart's theories as descriptions of the non-equilibrium processes. Our principal objective is to investigate if the dynamical properties of Dark Matter and Dark Energy can be described by a single viscous fluid and how such description changes when a causal theory (Müller-Israel-Stewart's, both in its full and truncated forms) is taken into account instead of Eckart's non-causal one. To this purpose, we find numerical solutions for the gravitational potential and compare its behaviour with the corresponding ΛCDM case. Eckart's and the full causal theory seem to be disfavoured, whereas the truncated theory leads to results similar to those of the ΛCDM model for a bulk viscous speed in the interval 10 −11 || cb 2 ∼ −8

Zoonotic bacterial meningitis in adults: clinical characteristics, etiology, treatment and outcome

NARCIS (Netherlands)

van Samkar, A.

2016-01-01

In this thesis, we describe the clinical characteristics, etiology, treatment and outcome of zoonotic bacterial meningitis. Each chapter describes meningitis patients infected by a specific zoonotic pathogen, such as Streptococcus equi, Streptococcuis suis, Capnocytophaga canimorsus, Campylobacter

Carbon monoxide poisoning in Beirut, Lebanon: Patient′s characteristics and exposure sources

Directory of Open Access Journals (Sweden)

Mazen J El Sayed

2014-01-01

Full Text Available Background: Carbon monoxide (CO poisoning is a preventable disease. Patients present with nonspecific symptoms post CO exposure. Causal factors are well described in developed countries, but less in developing countries. Objectives: This study examined the characteristics of patients with CO poisoning treated at a tertiary care center in Beirut, Lebanon, and their association with the CO poisoning source. Materials and Methods: A retrospective chart review of all patients who presented to the Emergency Department (ED of the American University of Beirut Medical Center (AUBMC over 4-year period and for whom a carboxyhemoglobin (CO-Hb level was available. Patients with CO poisoning diagnosis were included in the study. Patients′ characteristics and their association with CO poisoning source were described. Results: Twenty-seven patients were treated for CO poisoning during the study period, 55% of whom were males. Headache was the most common presenting symptom (51.9%. Burning charcoal indoors was the most common causal factor (44.4%, whereas fire-related smoke was another causal factor. The median arterial CO-Hb level on presentation for all cases was 12.0% (interquartile range (IQR 7.3-20.2. All patients received normobaric oxygen therapy. No complications were documented in the ED. All patients were discharged from the ED with a median ED length of stay of 255 min (IQR 210-270. Young females were more likely to present with CO poisoning from burning charcoal indoors than from another cause. Conclusion: CO poisoning in Beirut, Lebanon is mainly due to charcoal burning grills used indoors and to fire-related smoke. A clinically significant association was present between gender and CO poisoning source. An opportunity for prevention is present in terms of education and increased awareness regarding CO emission sources.

In a distinguishing spacetime the horismos relation generates the causal relation

International Nuclear Information System (INIS)

Minguzzi, E

2009-01-01

It is proved that in a distinguishing spacetime the horismos relation E + = J + /I + generates the causal relation J + . In other words two causally related events are joined by a chain of horismotically related events, or again, the causal relation is the smallest transitive relation containing the horismos relation. The result is sharp in the sense that the distinction cannot be weakened to future or past distinction. Finally, it is proved that a spacetime in which the horismos relation generates the causal relation is necessarily non-total imprisoning.

Financial networks based on Granger causality: A case study

NARCIS (Netherlands)

Papana, A.; Kyrtsou, C.; Kugiumtzis, D.; Diks, C.

Connectivity analysis is performed on a long financial record of 21 international stock indices employing a linear and a nonlinear causality measure, the conditional Granger causality index (CGCI) and the partial mutual information on mixed embedding (PMIME), respectively. Both measures aim to

Clinical and microbiologic characteristics of tcdA-negative variant clostridium difficile infections

Directory of Open Access Journals (Sweden)

Kim Jieun

2012-05-01

Full Text Available Abstract Background The tcdA-negative variant (A-B+ of Clostridium difficile is prevalent in East Asian countries. However, the risk factors and clinical characteristics of A-B+C. difficile infections (CDI are not clearly documented. The objective of this study was to investigate these characteristics. Methods From September 2008 through January 2010, the clinical characteristics, medication history and treatment outcomes of CDI patients were recorded prospectively. Toxin characterization and antibiotic susceptibility tests were performed on stool isolates of C. difficile. Results During the study period, we identified 22 cases of CDI caused by tcdA-negative tcdB-positive (A-B+ strains and 105 cases caused by tcdA-positive tcdB-positive (A+B+ strains. There was no significant difference in disease severity or clinical characteristics between the two groups. Previous use of clindamycin and young age were identified as significant risk factors for the acquisition of A-B+ CDI (OR = 4.738, 95% CI 1.48–15.157, p = 0.009 and OR = 0.966, 95% CI 0.935–0.998, p = 0.038, respectively in logistic regression. Rates of resistance to clindamycin were 100% and 69.6% in the A-B+ and A+B+ isolates, respectively (p = 0.006, and the ermB gene was identified in 17 of 21 A-B+ isolates (81%. Resistance to moxifloxacin was also more frequent in the A-B+ than in the A+B+ isolates (95.2% vs. 63.7%, p = 0.004. Conclusions The clinical course of A-B+ CDI is not different from that of A+B+ CDI. Clindamycin use is a significant risk factor for the acquisition of tcdA-negative variant strains.

Early-Onset Bipolar Disorder: Characteristics and Outcomes in the Clinic.

Science.gov (United States)

Connor, Daniel F; Ford, Julian D; Pearson, Geraldine S; Scranton, Victoria L; Dusad, Asha

2017-12-01

To assess patient characteristics and clinician-rated outcomes for children diagnosed with early-onset bipolar disorder in comparison to a depressive disorders cohort from a single clinic site. To assess predictors of bipolar treatment response. Medical records from 714 consecutive pediatric patients evaluated and treated at an academic tertiary child and adolescent psychiatry clinic between 2006 and 2012 were reviewed. Charts of bipolar children (n = 49) and children with depressive disorders (n = 58) meeting study inclusion/exclusion criteria were compared on variables assessing clinical characteristics, treatments, and outcomes. Outcomes were assessed by using pre- and post-Clinical Global Impressions (CGI)-Severity and Children's Global Assessment Scale (CGAS) scores, and a CGI-Improvement score ≤2 at final visit determined responder status. Bipolar outcome predictors were assessed by using multiple linear regression. Clinic prevalence rates were 6.9% for early-onset bipolar disorder and 1.5% for very early-onset bipolar disorder. High rates of comorbid diagnoses, symptom severity, parental stress, and child high-risk behaviors were found in both groups. The bipolar cohort had higher rates of aggression and higher lifetime systems of care utilization. The final CGI and CGAS outcomes for unipolar depression patients differed statistically significantly from those for the bipolar cohort, reflecting better clinical status and more improvement at outcome for the depression patients. Both parent-reported Child Behavior Checklist total T-score at clinic admission and the number of lifetime systems-of-care for the child were significantly and inversely associated with improvement for the bipolar cohort. Early-onset bipolar disorder is a complex and heterogeneous psychiatric disorder. Evidence-based treatment should emphasize psychopharmacology with adjunctive family and individual psychotherapy. Strategies to improve engagement in treatment may be especially

Causality between income and emission. A country group-specific econometric analysis

International Nuclear Information System (INIS)

Coondoo, Dipankor; Dinda, Soumyananda

2002-01-01

Empirical studies of the Environmental Kuznets Curve (EKC) examine the presence or otherwise of an inverted U-shaped relationship between the level of pollution and the level of income. Customarily, in the diagram of EKC the level of income is shown on the horizontal axis and that of pollution on the vertical axis. Thus, it is presumed that the relationship between income and pollution is one of unidirectional causality with income causing environmental changes and not vice versa. The validity of this presumption is now being questioned. It is being asserted that the nature and direction of causality may vary from one country to the other. In this paper, we present the results of a study of income-CO 2 emission causality based on a Granger causality test to cross-country panel data on per capita income and the corresponding per capita CO 2 emission data. Briefly, our results indicate three different types of causality relationship holding for different country groups. For the developed country groups of North America and Western Europe (and also for Eastern Europe) the causality is found to run from emission to income. For the country groups of Central and South America, Oceania and Japan causality from income to emission is obtained. Finally, for the country groups of Asia and Africa the causality is found to be bi-directional. The regression equations estimated as part of the Granger causality test further suggest that for the country groups of North America and Western Europe the growth rate of emission has become stationary around a zero mean, and a shock in the growth rate of emission tends to generate a corresponding shock in the growth rate of income. In contrast, for the country groups of Central and South America, Oceania and Japan a shock in the income growth rate is likely to result in a corresponding shock in the growth rate of emission. Finally, causality being bi-directional for the country groups of Asia and Africa, the income and the emission growth

Causality between income and emission. A country group-specific econometric analysis

Energy Technology Data Exchange (ETDEWEB)

Coondoo, Dipankor [Economic Research Unit, Indian Statistical Institute, 203 B.T. Road, 35 Kolkata (India); Dinda, Soumyananda [S.R. Fatepuria College, Beldanga, West Bengal, Murshidabad (India)

2002-03-01

Empirical studies of the Environmental Kuznets Curve (EKC) examine the presence or otherwise of an inverted U-shaped relationship between the level of pollution and the level of income. Customarily, in the diagram of EKC the level of income is shown on the horizontal axis and that of pollution on the vertical axis. Thus, it is presumed that the relationship between income and pollution is one of unidirectional causality with income causing environmental changes and not vice versa. The validity of this presumption is now being questioned. It is being asserted that the nature and direction of causality may vary from one country to the other. In this paper, we present the results of a study of income-CO{sub 2} emission causality based on a Granger causality test to cross-country panel data on per capita income and the corresponding per capita CO{sub 2} emission data. Briefly, our results indicate three different types of causality relationship holding for different country groups. For the developed country groups of North America and Western Europe (and also for Eastern Europe) the causality is found to run from emission to income. For the country groups of Central and South America, Oceania and Japan causality from income to emission is obtained. Finally, for the country groups of Asia and Africa the causality is found to be bi-directional. The regression equations estimated as part of the Granger causality test further suggest that for the country groups of North America and Western Europe the growth rate of emission has become stationary around a zero mean, and a shock in the growth rate of emission tends to generate a corresponding shock in the growth rate of income. In contrast, for the country groups of Central and South America, Oceania and Japan a shock in the income growth rate is likely to result in a corresponding shock in the growth rate of emission. Finally, causality being bi-directional for the country groups of Asia and Africa, the income and the

Bayesian detection of causal rare variants under posterior consistency.

KAUST Repository

Liang, Faming

2013-07-26

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

Bayesian detection of causal rare variants under posterior consistency.

Directory of Open Access Journals (Sweden)

Faming Liang

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

Bayesian detection of causal rare variants under posterior consistency.

KAUST Repository

Liang, Faming; Xiong, Momiao

2013-01-01

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

Substance Abuse and Clinical Counseling Students' Characteristics and Career Goals

Science.gov (United States)

Goodwin, Lloyd R., Jr.; Sias, Shari M.

2007-01-01

Students from a master's program in Substance Abuse and Clinical Counseling (SACC) at a midsize southeastern university were surveyed to determine personal characteristics and career goals. Sixty-two of the 68 students currently enrolled in the program volunteered to anonymously complete the questionnaire. The typical profile of the SACC student…

Characteristics of Placebo Responders in Pediatric Clinical Trials of Attention-Deficit/Hyperactivity Disorder

Science.gov (United States)

Newcorn, Jeffrey H.; Sutton, Virginia K.; Zhang, Shuyu; Wilens, Timothy; Kratochvil, Christopher; Emslie, Graham J.; D'Souza, Deborah N.; Schuh, Leslie M.; Allen, Albert J.

2009-01-01

Objective: Understanding placebo response is a prerequisite to improving clinical trial methodology. Data from placebo-controlled trials of atomoxetine in the treatment of children and adolescents with attention-deficit/hyperactivity disorder (ADHD) were analyzed to identify demographic and clinical characteristics that might predict placebo…

What is the nature of causality in the brain? - Inherently probabilistic. Comment on "Foundational perspectives on causality in large-scale brain networks" by M. Mannino and S.L. Bressler

Science.gov (United States)

Dhamala, Mukesh

2015-12-01

Understanding cause-and-effect (causal) relations from observations concerns all sciences including neuroscience. Appropriately defining causality and its nature, though, has been a topic of active discussion for philosophers and scientists for centuries. Although brain research, particularly functional neuroimaging research, is now moving rapidly beyond identification of brain regional activations towards uncovering causal relations between regions, the nature of causality has not be been thoroughly described and resolved. In the current review article [1], Mannino and Bressler take us on a beautiful journey into the history of the work on causality and make a well-reasoned argument that the causality in the brain is inherently probabilistic. This notion is consistent with brain anatomy and functions, and is also inclusive of deterministic cases of inputs leading to outputs in the brain.

perception of indonesian nursing students regaring caring behavior and teaching characteristics of their clinical nursing instructors

Directory of Open Access Journals (Sweden)

madiha mukhtar

2016-11-01

Full Text Available Student’s learning and performance reflects the professional attitude, behavior, ethics and standards of their instructors. The aim of this study is to analyse the perception of Indonesian Nursing students regarding caring behavior and teaching characteristics of their CNIs. In this exploratory cross-sectional study, 149 Professional Nursing students from Regular program (Baccalaureate and Post diploma BSN and 15 Clinical Nursing Instructors were recruited from nursing faculty of public university located in Surabaya Indonesia. Data were collected by questionnaire and FGD was conducted to explore detailed information. In descriptive analysis: 6 % students perceived the caring behavior of their clinical instructors as low, 52.3% responds it as enough and 41.6 % considered it good. Teaching characteristics of CNI; 2.7% low, 26.8 as enough and 70.5 % good as perceived by their students. Data collected from students was analysed by using logistic regression test. Professional commitment with (P-value .038, motivation (P-value .010 and clinical placement environment (P-value .002 in main category (significance value is < 0.05 shows influence on perception of Indonesian nursing students regarding caring behaviour and teaching characteristics of their CNIs. In focused group discussion students’ recommended to increase the number of visits in clinical area and emphasises on bed side clinical demonstration. It can be concluded that students’ characteristics does have influence on their perception regarding caring behavior and clinical setting environment influence their perception regarding teaching characteristics of their CNIs.

Autoinflammatory diseases in adults. Clinical characteristics and prognostic implications.

Science.gov (United States)

González García, A; Patier de la Peña, J L; Ortego Centeno, N

2017-03-01

Autoinflammatory diseases are clinical conditions with inflammatory manifestations that present in a periodic or persistent manner and are caused by acquired or hereditary disorders of the innate immune response. In general, these diseases are more common in childhood, but cases have been reported in adults and are therefore important for all specialists. There are few references on these diseases in adults due to their low prevalence and underdiagnosis. The aim of this study is to review the scientific literature on these disorders to systematise their clinical, prognostic and treatment response characteristics in adults. Copyright © 2016 Elsevier España, S.L.U. and Sociedad Española de Medicina Interna (SEMI). All rights reserved.

Structure induction in diagnostic causal reasoning.

Science.gov (United States)

Meder, Björn; Mayrhofer, Ralf; Waldmann, Michael R

2014-07-01

Our research examines the normative and descriptive adequacy of alternative computational models of diagnostic reasoning from single effects to single causes. Many theories of diagnostic reasoning are based on the normative assumption that inferences from an effect to its cause should reflect solely the empirically observed conditional probability of cause given effect. We argue against this assumption, as it neglects alternative causal structures that may have generated the sample data. Our structure induction model of diagnostic reasoning takes into account the uncertainty regarding the underlying causal structure. A key prediction of the model is that diagnostic judgments should not only reflect the empirical probability of cause given effect but should also depend on the reasoner's beliefs about the existence and strength of the link between cause and effect. We confirmed this prediction in 2 studies and showed that our theory better accounts for human judgments than alternative theories of diagnostic reasoning. Overall, our findings support the view that in diagnostic reasoning people go "beyond the information given" and use the available data to make inferences on the (unobserved) causal rather than on the (observed) data level. (c) 2014 APA, all rights reserved.

Concepts in causality: chemically induced human urinary bladder cancer

International Nuclear Information System (INIS)

Lower, G.M. Jr.

1982-01-01

A significant portion of the incidence of human urinary bladder cancer can be attributed to occupational and cultural (tobacco smoking) situations associated with exposures to various arylamines, many of which represent established human carcinogens. A brief historical overview of research in bladder cancer causality indicates that the identification of causal agents and causal mechanism has been approached and rests upon information gathered at the organismal (geographical/historical), cellular, and molecular levels of biologic organization. This viewpoint speaks of a natural evolution within the biomedical sciences; a natural evolution from descriptive approaches to mechanistic approaches; and a natural evolution from more or less independent discipline-oriented approaches to hierarchically organized multidisciplinary approaches. Available information relevant to bladder cancer causality can be readily integrated into general conceptual frameworks to yield a hierarchial view of the natural history of urinary bladder cancer, a view consistent with contemporary natural systems and information theory and perhaps relevant also to other chemically induced epithelial cancers. Such frameworks are useful in appreciating the spatial and temporal boundaries and interrelationships in causality and the conceptual interrelationships within the biomedical sciences. Recent approaches in molecular epidemiology and the assessment of relative individual susceptibility to bladder cancer indicate that such frameworks are useful in forming hypotheses

Empathic concern and professional characteristics associated with clinical empathy in French general practitioners.

Science.gov (United States)

Lelorain, Sophie; Sultan, Serge; Zenasni, Franck; Catu-Pinault, Annie; Jaury, Philippe; Boujut, Emilie; Rigal, Laurent

2013-03-01

Clinical empathy, i.e. the ability of physicians to adopt patient perspective, is an essential component of care, which depends in part on empathic concern, i.e. compassionate emotions felt for others. However, too much empathic concern can be challenging for physicians. Aim of this study was to examine physician practice characteristics that could explain clinical empathy beyond empathic concern. We were also interested in testing whether professional reflective activities, such as Balint group attendance or clinical supervision, might make clinical empathy less dependent on empathic concern. A total of 295 French general practitioners (response rate of 37%) completed self-reported questionnaires on empathic concern and clinical empathy, using the Toronto empathy questionnaire (TEQ) and the Jefferson scale of physician empathy (JSPE), respectively. We also recorded information on their professional practice: professional experience, duration of consultations, and participation in Balint groups or being a clinical supervisor. Hierarchical regression analyses were carried out with clinical empathy as dependent variable. Empathic concern was an important component of clinical empathy variance. The physician practice characteristics 'consultation length' and 'being a Balint attendee or a supervisor,' but not 'clinical experience' made a significant and unique contribution to clinical empathy beyond that of empathic concern. Participating to one reflective activity (either Balint group attendance or clinical supervision) made clinical empathy less dependent on empathic concern. Working conditions such as having enough consultation time and having the opportunity to attend a professional reflective activity support the maintenance of clinical empathy without the burden of too much empathic concern.

Characteristics of people attending psychiatric clinics in inner Sydney homeless hostels.

Science.gov (United States)

Nielssen, Olav B; Stone, William; Jones, Naidene M; Challis, Sarah; Nielssen, Amelia; Elliott, Gordon; Burns, Nicholas; Rogoz, Astrid; Cooper, Lucy E; Large, Matthew M

2018-03-05

To describe the characteristics of people attending mental health clinics at shelters for the homeless in inner city Sydney. Retrospective review of medical records of homeless hostel clinic attenders. Mental health clinics located in three inner city homeless hostels. Consecutive series of clinic attenders, 21 July 2008 - 31 December 2016. Demographic characteristics; social, medical and mental health histories of homeless people. 2388 individual patients were seen at the clinics during the 8.5-year study period. Their mean age was 42 years (standard deviation, 13 years), 93% were men, and 56% were receiving disability support pensions. 59% of attenders had been homeless for more than a year, and 34% of all attenders reported sleeping in the open. The most common diagnoses were substance use disorder (66%), psychotic illness (51%), acquired brain injury (14%), and intellectual disability (5%). Most patients had more than one diagnosis. Early life and recent trauma was reported by 42% of patients. Pathways to homelessness included release from prison (28% of the homeless), discharge from a psychiatric hospital (21%), loss of public housing tenancy (21%), and inability to pay rent because of problem gambling. The high rates of substance use and mental disorder among homeless people in inner Sydney confirms the need for increased access to treatment for these conditions in this setting. Homelessness among those with mental illness might be reduced by developing alternative housing models, and supporting people with multiple problems to retain tenancy.

Clinical characteristics of the asthma-COPD overlap syndrome--a systematic review

DEFF Research Database (Denmark)

Nielsen, Mia; Bårnes, Camilla Boslev; Ulrik, Charlotte Suppli

2015-01-01

BACKGROUND AND OBJECTIVE: In recent years, the so-called asthma-chronic obstructive pulmonary disease (COPD) overlap syndrome (ACOS) has received much attention, not least because elderly individuals may present characteristics suggesting a diagnosis of both asthma and COPD. At present, ACOS...... is described clinically as persistent airflow limitation combined with features of both asthma and COPD. The aim of this paper is, therefore, to review the currently available literature focusing on symptoms and clinical characteristics of patients regarded as having ACOS. METHODS: Based on the preferred......% predicted and FEV1/FVC ratio in spite of lower mean life-time tobacco exposure. Furthermore, studies have revealed that ACOS patients seem to have not only more frequent but also more severe exacerbations. Comorbidity, not least diabetes, has also been reported in a few studies, with a higher prevalence...

Clinical microbiology in the intensive care unit: Strategic and operational characteristics

Directory of Open Access Journals (Sweden)

Bhattacharya S

2010-01-01

Full Text Available Infection is a major cause of morbidity and mortality among patients admitted in intensive care units (ICUs. The application of the principles and the practice of Clinical Microbiology for ICU patients can significantly improve clinical outcome. The present article is aimed at summarising the strategic and operational characteristics of this unique field where medical microbiology attempts to venture into the domain of direct clinical care of critically ill patients. The close and strategic partnership between clinical microbiologists and intensive care specialists, which is essential for this model of patient care have been emphasized. The article includes discussions on a variety of common clinical-microbiological problems faced in the ICUs such as ventilator-associated pneumonia, blood stream infections, skin and soft tissue infection, UTI, infection control, besides antibiotic management.

Moment problems and the causal set approach to quantum gravity

International Nuclear Information System (INIS)

Ash, Avner; McDonald, Patrick

2003-01-01

We study a collection of discrete Markov chains related to the causal set approach to modeling discrete theories of quantum gravity. The transition probabilities of these chains satisfy a general covariance principle, a causality principle, and a renormalizability condition. The corresponding dynamics are completely determined by a sequence of non-negative real coupling constants. Using techniques related to the classical moment problem, we give a complete description of any such sequence of coupling constants. We prove a representation theorem: every discrete theory of quantum gravity arising from causal set dynamics satisfying covariance, causality, and renormalizability corresponds to a unique probability distribution function on the non-negative real numbers, with the coupling constants defining the theory given by the moments of the distribution

Drawing causal inferences using propensity scores: a practical guide for community psychologists.

Science.gov (United States)

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

2013-12-01

Confounding present in observational data impede community psychologists' ability to draw causal inferences. This paper describes propensity score methods as a conceptually straightforward approach to drawing causal inferences from observational data. A step-by-step demonstration of three propensity score methods-weighting, matching, and subclassification-is presented in the context of an empirical examination of the causal effect of preschool experiences (Head Start vs. parental care) on reading development in kindergarten. Although the unadjusted population estimate indicated that children with parental care had substantially higher reading scores than children who attended Head Start, all propensity score adjustments reduce the size of this overall causal effect by more than half. The causal effect was also defined and estimated among children who attended Head Start. Results provide no evidence for improved reading if those children had instead received parental care. We carefully define different causal effects and discuss their respective policy implications, summarize advantages and limitations of each propensity score method, and provide SAS and R syntax so that community psychologists may conduct causal inference in their own research.

Causal Modelling in Evaluation Research.

Science.gov (United States)

Winteler, Adolf

1983-01-01

A study applied path analysis methods, using new techniques of causal analysis, to the problem of predicting the achievement, dropout rate, and satisfaction of university students. Besides providing explanations, the technique indicates possible remedial measures. (MSE)

Characterization of clinical-imaging characteristics of the binswanger's disease

International Nuclear Information System (INIS)

Rodriguez Mutuberria, Livan; Serra Valdes, Yusimi

2002-01-01

A review was made to go deep into the understanding of vascular dementias that behave as the second cause of dementia in practice. Binswanger's disease is one of the most important among them. Its detection has progressively increased with the continual improvement of the radiological diagnostic tools that allow to identify the ischemic damage of the hemispherical cerebral white matter and the presence of lacunar infarctions. It is a disease of chronic course and inexorably progressive that is characterized by the association of subcortical cognitive dysfunction, evidence of cerebrovascular disease, Parkinsonian rigidity and vesicle dysfunction with a characteristic imaging picture. The clinical picture and the main imaging characteristics are explained in this paper and the pathogens of the disease is briefly described

Optimal relaxed causal sampler using sampled-date system theory

NARCIS (Netherlands)

Shekhawat, Hanumant; Meinsma, Gjerrit

This paper studies the design of an optimal relaxed causal sampler using sampled data system theory. A lifted frequency domain approach is used to obtain the existence conditions and the optimal sampler. A state space formulation of the results is also provided. The resulting optimal relaxed causal

Clinical characteristics differentiating bacteriologically positive pulmonary tuberculosis patients from negative ones in Mongolia.

Science.gov (United States)

Toyota, M; Yasuda, N; Koda, S; Ohara, H; Enkhbat, S; Tsogt, G

1998-06-01

The objective of this study is to clarify clinical characteristics which differentiate bacteriologically positive pulmonary tuberculosis patients from negative ones in Mongolia. The subjects include 338 patients aged 16 years and older who had undergone bacteriological examinations. Of them, 107 patients (31.7%) were confirmed bacteriologically. The proportion of bacteriological positive results increased significantly among patients who had cavities in the roentgenographic examination, cough at diagnosis and the family history of tuberculosis. Addressing these clinical characteristics will contribute to raising not only the sensitivity of the sputum examination, but also the specificity of the roentgenographic examination in the diagnostic process of tuberculosis.

Causal assessment of surrogacy in a meta-analysis of colorectal cancer trials

Science.gov (United States)

Li, Yun; Taylor, Jeremy M.G.; Elliott, Michael R.; Sargent, Daniel J.

2011-01-01

When the true end points (T) are difficult or costly to measure, surrogate markers (S) are often collected in clinical trials to help predict the effect of the treatment (Z). There is great interest in understanding the relationship among S, T, and Z. A principal stratification (PS) framework has been proposed by Frangakis and Rubin (2002) to study their causal associations. In this paper, we extend the framework to a multiple trial setting and propose a Bayesian hierarchical PS model to assess surrogacy. We apply the method to data from a large collection of colon cancer trials in which S and T are binary. We obtain the trial-specific causal measures among S, T, and Z, as well as their overall population-level counterparts that are invariant across trials. The method allows for information sharing across trials and reduces the nonidentifiability problem. We examine the frequentist properties of our model estimates and the impact of the monotonicity assumption using simulations. We also illustrate the challenges in evaluating surrogacy in the counterfactual framework that result from nonidentifiability. PMID:21252079

Causality and symmetry in cosmology and the conformal group

International Nuclear Information System (INIS)

Segal, I.E.

1977-01-01

A new theoretic postulate in fundamental physics is considered which is called the chronometric principle because it deals primarily with the nature of time, or its dual or conjugate, energy. Conformality is equivalent to causality. Thus, the group of all local causality-preserving transformations in the vicinity of a point of Minkowski space is, as a local Lie group, identical with the conformal group. The same statement made globally on Minkowski space is: The set of all vector fields on Minkowski space which generate smooth local causality-preserving transformations is identical with the set of all conformal vector fields. The main validation for the chronometric principle is in cosmology or ultramacroscopic physics. Therefore this principle is illustrated along the lines of the red shift. This principle in combination with quantum field theory leads to a convergent and causal description of particle production in which nonlinearities are supplanted by more sophisticated and comprehensive actions for the fundamental symmetry groups. 11 references

The causality between energy consumption and economic growth in Turkey

International Nuclear Information System (INIS)

Erdal, Guelistan; Erdal, Hilmi; Esenguen, Kemal

2008-01-01

This paper applies the causality test to examine the causal relationship between primary energy consumption (EC) and real Gross National Product (GNP) for Turkey during 1970-2006. We employ unit root tests, the augmented Dickey-Fuller (ADF) and the Philips-Perron (PP), Johansen cointegration test, and Pair-wise Granger causality test to examine relation between EC and GNP. Our empirical results indicate that the two series are found to be non-stationary. However, first differences of these series lead to stationarity. Further, the results indicate that EC and GNP are cointegrated and there is bidirectional causality running from EC to GNP and vice versa. This means that an increase in EC directly affects economic growth and that economic growth also stimulates further EC. This bidirectional causality relationship between EC and GNP determined for Turkey at 1970-2006 period is in accordance with the ones in literature reported for similar countries. Consequently, we conclude that energy is a limiting factor to economic growth in Turkey and, hence, shocks to energy supply will have a negative impact on economic growth

On the entanglement entropy of quantum fields in causal sets

Science.gov (United States)

Belenchia, Alessio; Benincasa, Dionigi M. T.; Letizia, Marco; Liberati, Stefano

2018-04-01

In order to understand the detailed mechanism by which a fundamental discreteness can provide a finite entanglement entropy, we consider the entanglement entropy of two classes of free massless scalar fields on causal sets that are well approximated by causal diamonds in Minkowski spacetime of dimensions 2, 3 and 4. The first class is defined from discretised versions of the continuum retarded Green functions, while the second uses the causal set’s retarded nonlocal d’Alembertians parametrised by a length scale l k . In both cases we provide numerical evidence that the area law is recovered when the double-cutoff prescription proposed in Sorkin and Yazdi (2016 Entanglement entropy in causal set theory (arXiv:1611.10281)) is imposed. We discuss in detail the need for this double cutoff by studying the effect of two cutoffs on the quantum field and, in particular, on the entanglement entropy, in isolation. In so doing, we get a novel interpretation for why these two cutoff are necessary, and the different roles they play in making the entanglement entropy on causal sets finite.

Microdosimetric Characteristics of the Clinical Proton Beams at the JINR Phasotron, Dubna

CERN Document Server

Vlcek, B; Spurny, F

2002-01-01

The contribution of the high LET particles to dosimetric and microdosimetric characteristics of 150 and 205 MeV clinical proton beams was experimentally studied using track etched detectors. Secondary heavy charged particles produced from nuclear interactions and degraded protons at the Bragg peak region are particles with high LET. The method of the LET spectra measurement with track etched detectors allows one to determine the contribution of high LET particles to dosimetric characteristics of clinical proton beams: absorbed dose, equivalent dose and the value of the Relative Biological Effectiveness (RBE). Track detectors were irradiated in the various depth of clinical proton beams with the primary energies of 150 and 205 MeV. The LET spectra between 10 and 700 keV/m were measured by means of CR-39 track etched detectors and the automatic optical image analyzer LUCIA-II. The relative contribution of the high LET particles to absorbed dose increases from several per cent at the beam entrance to several ten...

The characteristics of a good clinical teacher as perceived by resident physicians in Japan: a qualitative study.

Science.gov (United States)

Kikukawa, Makoto; Nabeta, Hiromi; Ono, Maiko; Emura, Sei; Oda, Yasutomo; Koizumi, Shunzo; Sakemi, Takanobu

2013-07-25

It is not known whether the characteristics of a good clinical teacher as perceived by resident physicians are the same in Western countries as in non-Western countries including Japan. The objective of this study was to identify the characteristics of a good clinical teacher as perceived by resident physicians in Japan, a non-Western country, and to compare the results with those obtained in Western countries. Data for this qualitative research were collected using semi-structured focus group interviews. Focus group transcripts were independently analyzed and coded by three authors. Residents were recruited by maximum variation sampling until thematic saturation was achieved. Twenty-three residents participated in five focus group interviews regarding the perceived characteristics of a good clinical teacher in Japan. The 197 descriptions of characteristics that were identified were grouped into 30 themes. The most commonly identified theme was "provided sufficient support", followed by "presented residents with chances to think", "provided feedback", and "provided specific indications of areas needing improvement". Using Sutkin's main categories (teacher, physician, and human characteristics), 24 of the 30 themes were categorized as teacher characteristics, 6 as physician characteristics, and none as human characteristics. "Medical knowledge" of teachers was not identified as a concern of residents, and "clinical competence of teachers" was not emphasized, whereas these were the two most commonly recorded themes in Sutkin's study. Our results suggest that Japanese and Western resident physicians place emphasis on different characteristics of their teachers. We speculate that such perceptions are influenced by educational systems, educational settings, and culture. Globalization of medical education is important, but it is also important to consider differences in educational systems, local settings, and culture when evaluating clinical teachers.

Network and system diagrams revisited: Satisfying CEA requirements for causality analysis

International Nuclear Information System (INIS)

Perdicoulis, Anastassios; Piper, Jake

2008-01-01

Published guidelines for Cumulative Effects Assessment (CEA) have called for the identification of cause-and-effect relationships, or causality, challenging researchers to identify methods that can possibly meet CEA's specific requirements. Together with an outline of these requirements from CEA key literature, the various definitions of cumulative effects point to the direction of a method for causality analysis that is visually-oriented and qualitative. This article consequently revisits network and system diagrams, resolves their reported shortcomings, and extends their capabilities with causal loop diagramming methodology. The application of the resulting composite causality analysis method to three Environmental Impact Assessment (EIA) case studies appears to satisfy the specific requirements of CEA regarding causality. Three 'moments' are envisaged for the use of the proposed method: during the scoping stage, during the assessment process, and during the stakeholder participation process

Clinical characteristics of rotavirus diarrhea in hospitalized Romanian infants.

Science.gov (United States)

Lesanu, Gabriela; Becheanu, Cristina Adriana; Vlad, Raluca Maria; Pacurar, Daniela; Tincu, Iulia Florentina; Smadeanu, Roxana Elena

2013-01-01

Clinical characteristics of rotavirus enteritis were evaluated by comparison with acute diarrhea of other etiologies. We reviewed the medical records of children (aged 0-12 months) admitted with acute diarrhea in our hospital between January and December 2011. Of the 839 patients, 49.3% had rotavirus diarrhea. The incidence of severe disease was significantly higher for rotavirus diarrhea (65.2%, P < 0.01) than for other types of diarrheal disease.

Clinical Characteristics and Outcomes of Patients With Cellulitis Requiring Intensive Care

NARCIS (Netherlands)

Cranendonk, Duncan R.; van Vught, Lonneke A.; Wiewel, Maryse A.; Cremer, Olaf L.; Horn, Janneke; Bonten, Marc J.; Schultz, Marcus J.; van der Poll, Tom; Wiersinga, W. Joost

2017-01-01

Cellulitis is a commonly occurring skin and soft tissue infection and one of the most frequently seen dermatological diseases in the intensive care unit (ICU). However, clinical characteristics of patients with cellulitis requiring intensive care treatment are poorly defined. Necrotizing fasciitis

Clinical Characteristics and Outcomes of Patients With Cellulitis Requiring Intensive Care

NARCIS (Netherlands)

Cranendonk, Duncan R; van Vught, Lonneke A; Wiewel, Maryse A; Cremer, Olaf L; Horn, Janneke; Bonten, Marc J; Schultz, Marcus J; van der Poll, Tom; Wiersinga, W Joost

Importance: Cellulitis is a commonly occurring skin and soft tissue infection and one of the most frequently seen dermatological diseases in the intensive care unit (ICU). However, clinical characteristics of patients with cellulitis requiring intensive care treatment are poorly defined. Necrotizing

Human Papilloma Viruses and Breast Cancer – Assessment of Causality

Science.gov (United States)

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

2016-01-01

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

Investigating causality in the association between 25(OH)D and schizophrenia.

Science.gov (United States)

Taylor, Amy E; Burgess, Stephen; Ware, Jennifer J; Gage, Suzanne H; Richards, J Brent; Davey Smith, George; Munafò, Marcus R

2016-05-24

Vitamin D deficiency is associated with increased risk of schizophrenia. However, it is not known whether this association is causal or what the direction of causality is. We performed two sample bidirectional Mendelian randomization analysis using single nucleotide polymorphisms (SNPs) robustly associated with serum 25(OH)D to investigate the causal effect of 25(OH)D on risk of schizophrenia, and SNPs robustly associated with schizophrenia to investigate the causal effect of schizophrenia on 25(OH)D. We used summary data from genome-wide association studies and meta-analyses of schizophrenia and 25(OH)D to obtain betas and standard errors for the SNP-exposure and SNP-outcome associations. These were combined using inverse variance weighted fixed effects meta-analyses. In 34,241 schizophrenia cases and 45,604 controls, there was no clear evidence for a causal effect of 25(OH)D on schizophrenia risk. The odds ratio for schizophrenia per 10% increase in 25(OH)D conferred by the four 25(OH)D increasing SNPs was 0.992 (95% CI: 0.969 to 1.015). In up to 16,125 individuals with measured serum 25(OH)D, there was no clear evidence that genetic risk for schizophrenia causally lowers serum 25(OH)D. These findings suggest that associations between schizophrenia and serum 25(OH)D may not be causal. Therefore, vitamin D supplementation may not prevent schizophrenia.

Clinical Characteristics for 348 Patients with Adrenal Incidentaloma

Directory of Open Access Journals (Sweden)

Jongho Kim

2013-03-01

Full Text Available BackgroundAdrenal incidentaloma is an adrenal neoplasm frequently encountered in clinical practice for which detection rates have recently increased. We describe here the clinical characteristics of adrenal incidentalomas.MethodsA retrospective study was performed examining the age, sex, location, size, function, and the histological findings for 348 patients with an adrenal mass discovered incidentally on computed tomography (CT undertaken for health examination or nonadrenal disease from August 2005 to May 2012.ResultsPatients consisted of 156 males (44.8% and 192 females (55.2%, aged between 20 and 86. Adrenal masses were most commonly found in patients in their sixth decade (32.5%. Regarding the location of the masses, 62.0% were found in the left adrenal gland, 30.2% were found in the right, and 7.8% were found bilaterally. Of all of the masses analyzed, 87.1% were 1 to 4 cm in size, and an adenoma-like appearance was the most common finding (75.3% seen on CT scans. Hormonal analysis showed that 82.2% of the masses were nonfunctioning, 6.0% were diagnosed as subclinical Cushing's syndrome, 4.6% were aldosterone-producing adenomas, and 7.2% were pheochromocytomas. Adrenalectomy was performed in a total of 69 patients having adenoma (50.7%, pheochromocytoma (24.6%, and carcinoma (4.3%.ConclusionThe characteristics of benign, malignant, nonfunctional, and functional adrenal masses that were incidentally found at our hospital were similar to those presented in other studies.

Disease causality extraction based on lexical semantics and document-clause frequency from biomedical literature.

Science.gov (United States)

Lee, Dong-Gi; Shin, Hyunjung

2017-05-18

Recently, research on human disease network has succeeded and has become an aid in figuring out the relationship between various diseases. In most disease networks, however, the relationship between diseases has been simply represented as an association. This representation results in the difficulty of identifying prior diseases and their influence on posterior diseases. In this paper, we propose a causal disease network that implements disease causality through text mining on biomedical literature. To identify the causality between diseases, the proposed method includes two schemes: the first is the lexicon-based causality term strength, which provides the causal strength on a variety of causality terms based on lexicon analysis. The second is the frequency-based causality strength, which determines the direction and strength of causality based on document and clause frequencies in the literature. We applied the proposed method to 6,617,833 PubMed literature, and chose 195 diseases to construct a causal disease network. From all possible pairs of disease nodes in the network, 1011 causal pairs of 149 diseases were extracted. The resulting network was compared with that of a previous study. In terms of both coverage and quality, the proposed method showed outperforming results; it determined 2.7 times more causalities and showed higher correlation with associated diseases than the existing method. This research has novelty in which the proposed method circumvents the limitations of time and cost in applying all possible causalities in biological experiments and it is a more advanced text mining technique by defining the concepts of causality term strength.

Causal structure of analogue spacetimes

International Nuclear Information System (INIS)

Barcelo, Carlos; Liberati, Stefano; Sonego, Sebastiano; Visser, Matt

2004-01-01

The so-called 'analogue models of general relativity' provide a number of specific physical systems, well outside the traditional realm of general relativity, that nevertheless are well-described by the differential geometry of curved spacetime. Specifically, the propagation of perturbations in these condensed matter systems is described by 'effective metrics' that carry with them notions of 'causal structure' as determined by an exchange of quasi-particles. These quasi-particle-induced causal structures serve as specific examples of what can be done in the presence of a Lorentzian metric without having recourse to the Einstein equations of general relativity. (After all, the underlying analogue model is governed by its own specific physics, not necessarily by the Einstein equations.) In this paper we take a careful look at what can be said about the causal structure of analogue spacetimes, focusing on those containing quasi-particle horizons, both with a view to seeing what is different from standard general relativity, and what the similarities might be. For definiteness, and because the physics is particularly simple to understand, we will phrase much of the discussion in terms of acoustic disturbances in moving fluids, where the underlying physics is ordinary fluid mechanics, governed by the equations of traditional hydrodynamics, and the relevant quasi-particles are the phonons. It must however be emphasized that this choice of example is only for the sake of pedagogical simplicity and that our considerations apply generically to wide classes of analogue spacetimes

Causal Attributions about Disease-Onset and Relapse in Patients with Systemic Vasculitis

Science.gov (United States)

Grayson, Peter C.; Amudala, Naomi A.; McAlear, Carol A.; Leduc, Renée L.; Shereff, Denise; Richesson, Rachel; Fraenkel, Liana; Merkel, Peter A.

2014-01-01

Objectives Patients vary in their beliefs related to the cause of serious illness. The impact of these beliefs among patients with systemic vasculitis is not known. This study aimed to describe causal attributions about disease-onset and relapse in systemic vasculitis and to examine whether causal beliefs a) differ by type of vasculitis; and b) are associated with negative health outcomes. Methods Patients with vasculitis were recruited to complete an online questionnaire. Categories of causal beliefs were assessed with the Revised Illness Perception Questionnaire (IPQ-R). Differences in beliefs about disease-onset versus relapse were compared across different forms of vasculitis. Causal beliefs were assessed in association with several health outcomes including fatigue, functional impairments, and personal understanding of the condition. Results 692 patients representing 9 forms of vasculitis completed the questionnaire. The majority (90%) of patients had beliefs about the cause of their illness. Causal attributions were highly variable, but altered immunity and stress were the most commonly agreed upon causal beliefs. Frequencies of causal beliefs were strikingly similar across different forms of vasculitis, with few notable exceptions primarily in Behçet’s disease. Beliefs differed about causes of disease-onset versus relapse. Specific beliefs about disease-onset and relapse were weakly associated with fatigue, functional impairments, and understanding of the condition. Conclusion Patient beliefs related to the cause of systemic vasculitis are highly variable. Patterns of causal beliefs are associated with important negative health outcomes. Clinicians who care for patients with vasculitis should be mindful of these associations and consider asking about patients’ causal beliefs. PMID:24634202

Multifactorial causal model of brain (dis)organization and therapeutic intervention: Application to Alzheimer's disease.

Science.gov (United States)

Iturria-Medina, Yasser; Carbonell, Félix M; Sotero, Roberto C; Chouinard-Decorte, Francois; Evans, Alan C

2017-05-15

Generative models focused on multifactorial causal mechanisms in brain disorders are scarce and generally based on limited data. Despite the biological importance of the multiple interacting processes, their effects remain poorly characterized from an integrative analytic perspective. Here, we propose a spatiotemporal multifactorial causal model (MCM) of brain (dis)organization and therapeutic intervention that accounts for local causal interactions, effects propagation via physical brain networks, cognitive alterations, and identification of optimum therapeutic interventions. In this article, we focus on describing the model and applying it at the population-based level for studying late onset Alzheimer's disease (LOAD). By interrelating six different neuroimaging modalities and cognitive measurements, this model accurately predicts spatiotemporal alterations in brain amyloid-β (Aβ) burden, glucose metabolism, vascular flow, resting state functional activity, structural properties, and cognitive integrity. The results suggest that a vascular dysregulation may be the most-likely initial pathologic event leading to LOAD. Nevertheless, they also suggest that LOAD it is not caused by a unique dominant biological factor (e.g. vascular or Aβ) but by the complex interplay among multiple relevant direct interactions. Furthermore, using theoretical control analysis of the identified population-based multifactorial causal network, we show the crucial advantage of using combinatorial over single-target treatments, explain why one-target Aβ based therapies might fail to improve clinical outcomes, and propose an efficiency ranking of possible LOAD interventions. Although still requiring further validation at the individual level, this work presents the first analytic framework for dynamic multifactorial brain (dis)organization that may explain both the pathologic evolution of progressive neurological disorders and operationalize the influence of multiple interventional

Quantum mechanics, relativity and causality

International Nuclear Information System (INIS)

Tati, Takao.

1975-07-01

In quantum mechanics, the state is prepared by a measurement on a space-like surface sigma. What is that determines the surface sigma on which the measurement prepares the state It is considered either a mechanism proper to the measuring process (apparatus) or a universal property of space-time. In the former case, problems arise, concerning causality or conservation of probability due to that the velocity of reduction of wave-packet is considered to exceed the light velocity. The theory of finite degree of freedom proposed previously belongs to the latter case. In this theory, the surface sigma is restricted to the hyper-plane perpendicular to a universal time-like vector governing causal relations. We propose an experiment to discriminate between the above-mentioned two cases and to test the existence of the universal time-like vector. (auth.)

CAUSALITY RELATIONSHIP BETWEEN GDP AND ENERGY CONSUMPTION IN GEORGIA, AZERBAIJAN AND ARMENIA

Directory of Open Access Journals (Sweden)

Huseyin Kalyoncu

2013-01-01

Full Text Available This research aims to investigate the relationship between energy consumption and economic growth in Georgia, Azerbaijan and Armenia during the period of 1995–2009. The Engle-Granger cointegration and Granger causality tests are used in order to analyse the causal relationship between energy consumption and economic growth. It is crucial to see the directions of causality between two variables for the policy makers. For Georgia and Azerbaijan it is found that these two variables are not cointegrated. In case of Armenia these two variables are cointegrated. Accordingly, causality analysis is conducted for Armenia. The research outcomes reveal that there is unidirectional causality from per capita GDP to per capita energy consumption for Armenia.

Clinical and Laboratory Characteristics of Leishmaniasis in Armenia

Directory of Open Access Journals (Sweden)

A.L. Kazinian

2014-11-01

Full Text Available This work presents the clinical and laboratory characteristics of visceral leishmaniasis according to the data from Clinical hospital of infectious diseases «Nork» in Yerevan for 2013. It is shown that Armenia is a country endemic for visceral leishmaniasis. Most patients (81 % were males. About half of the patients were young children (up to 2 years. It was found that the majority of patients had acute onset of the disease with fever up to 40 °C, severe symptoms of intoxication and single hemorrhages on the skin. Enlargement of the liver and spleen was noted in all patients. The enlargement of the spleen was more pronounced, and it reached the level of the pelvis. One of the cardinal symptoms of visceral leishmaniasis — anemia — developed in all patients admitted to the hospital, and a significant change in the hemogram was observed in young children.

P3-10: Crossmodal Perceptual Grouping Modulates Subjective Causality between Action and Outcome

Directory of Open Access Journals (Sweden)

Takahiro Kawabe

2012-10-01

Full Text Available Agents have to determine which external events their action has causally produced. A sensation of causal relation between action and outcome is called subjective causality. Subjective causality has been linked to the comparator model. This model assumes that the brain compares an internal prediction for action outcome with an actual sensory outcome, distinguishing between self and externally produced outcomes depending on spatiotemporal congruency. However, recent studies have expressed some doubt about the idea that subjective causality arises depending solely on the spatiotemporal congruency, suggesting instead that other perceptual/cognitive factors play a critical role in determining subjective causality. We hypothesized that crossmodal grouping between action and outcome contributed to subjective causality. Crossmodal temporal grouping is an essential factor for crossmodal simultaneity judgments with ungrouped crossmodal signals likely to be judged as non-simultaneous. We predicted that subjective causality would decrease when an agent's action was not temporally grouped with action outcome. In the experiment, observers were asked to press a key in order to trigger a display change with some temporal delay. To disrupt temporal grouping between action and outcome, a task-irrelevant visual flash or tone was sometimes presented synchronously with the button press and/or the display change. Subjective causality was decreased when the flash or the tone was coincided with the button press. This demonstrates that perceptual grouping has a key role in determination of subjective causality, a result that is not accounted for by the standard comparator model.

Thinking Fast and Slow about Causality: Response to Palinkas

Science.gov (United States)

Marsh, Jeanne C.

2014-01-01

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

The causal pie model: an epidemiological method applied to evolutionary biology and ecology.

Science.gov (United States)

Wensink, Maarten; Westendorp, Rudi G J; Baudisch, Annette

2014-05-01

A general concept for thinking about causality facilitates swift comprehension of results, and the vocabulary that belongs to the concept is instrumental in cross-disciplinary communication. The causal pie model has fulfilled this role in epidemiology and could be of similar value in evolutionary biology and ecology. In the causal pie model, outcomes result from sufficient causes. Each sufficient cause is made up of a "causal pie" of "component causes". Several different causal pies may exist for the same outcome. If and only if all component causes of a sufficient cause are present, that is, a causal pie is complete, does the outcome occur. The effect of a component cause hence depends on the presence of the other component causes that constitute some causal pie. Because all component causes are equally and fully causative for the outcome, the sum of causes for some outcome exceeds 100%. The causal pie model provides a way of thinking that maps into a number of recurrent themes in evolutionary biology and ecology: It charts when component causes have an effect and are subject to natural selection, and how component causes affect selection on other component causes; which partitions of outcomes with respect to causes are feasible and useful; and how to view the composition of a(n apparently homogeneous) population. The diversity of specific results that is directly understood from the causal pie model is a test for both the validity and the applicability of the model. The causal pie model provides a common language in which results across disciplines can be communicated and serves as a template along which future causal analyses can be made.

Inferring causal molecular networks: empirical assessment through a community-based effort.

Science.gov (United States)

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.

Inferring causality from noisy time series data

DEFF Research Database (Denmark)

Mønster, Dan; Fusaroli, Riccardo; Tylén, Kristian

2016-01-01

Convergent Cross-Mapping (CCM) has shown high potential to perform causal inference in the absence of models. We assess the strengths and weaknesses of the method by varying coupling strength and noise levels in coupled logistic maps. We find that CCM fails to infer accurate coupling strength...... and even causality direction in synchronized time-series and in the presence of intermediate coupling. We find that the presence of noise deterministically reduces the level of cross-mapping fidelity, while the convergence rate exhibits higher levels of robustness. Finally, we propose that controlled noise...

A new spin on causality constraints

Energy Technology Data Exchange (ETDEWEB)

Hartman, Thomas; Jain, Sachin; Kundu, Sandipan [Department of Physics, Cornell University, Ithaca, New York (United States)

2016-10-26

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

The Hankel transform of causal distributions

Directory of Open Access Journals (Sweden)

Manuel A. Aguirre T.

2012-03-01

Full Text Available In this note we evaluate the unidimensional distributional Hankel transform of \\dfrac{x^{\\alpha-1}_{+}}{\\Gamma^{\\alpha}},\\dfrac{x^{\\alpha-1}_{-}}{\\Gamma^{\\alpha}},dfrac{|x|^{\\alpha-1}}{\\Gamma^{\\frac{\\alpha}{2}}},dfrac{|x|^{\\alpha-1}sgn(x}{\\Gamma^{\\frac{\\alpha +1}{2}}} and (x± i0^{\\alpha-1} and then we extend the formulae to certain kinds of n-dimensional distributions calles "causal" and "anti-causal" distributions. We evaluate the distributional Handel transform of \\dfrac{(m^2+P^{\\alpha -1}_{-}}{\\Gamma^{(\\alpha} }, \\dfrac{|m^2+P|^{\\alpha -1}_{-}}{\\Gamma^{(\\frac{\\alpha}{2}}}, \\dfrac{|m^2+P|^{\\alpha -1}sgn(m^2+P}{\\Gamma (\\frac{\\alpha +1}{2 }} and (m^2+P±i0^{\\alpha-1}

Boundary causality versus hyperbolicity for spherical black holes in Gauss–Bonnet gravity

International Nuclear Information System (INIS)

Andrade, Tomás; Cáceres, Elena; Keeler, Cynthia

2017-01-01

We explore the constraints boundary causality places on the allowable Gauss–Bonnet gravitational couplings in asymptotically AdS spaces, specifically considering spherical black hole solutions. We additionally consider the hyperbolicity properties of these solutions, positing that hyperbolicity-violating solutions are sick solutions whose causality properties provide no information about the theory they reside in. For both signs of the Gauss–Bonnet coupling, spherical black holes violate boundary causality at smaller absolute values of the coupling than planar black holes do. For negative coupling, as we tune the Gauss–Bonnet coupling away from zero, both spherical and planar black holes violate hyperbolicity before they violate boundary causality. For positive coupling, the only hyperbolicity-respecting spherical black holes which violate boundary causality do not do so appreciably far from the planar bound. Consequently, eliminating hyperbolicity-violating solutions means the bound on Gauss–Bonnet couplings from the boundary causality of spherical black holes is no tighter than that from planar black holes. (paper)

Cause and Event: Supporting Causal Claims through Logistic Models

Science.gov (United States)

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

2011-01-01

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

Demographic characteristics and clinical predictors of patients discharged from university hospital-affiliated pain clinic due to breach in narcotic use contract.

Science.gov (United States)

Chakrabortty, Shushovan; Gupta, Deepak; Rustom, David; Berry, Hussein; Rai, Ajit

2014-01-01

The current retrospective study was completed with the aim to identify demographic characteristics and clinical predictors (if any) of the patients discharged from our pain clinic due to breach in narcotic use contract (BNUC). Retrospective patient charts' review and data audit. University hospital-affiliated pain clinic in the United States. All patient charts in our pain clinic for a 2-year period (2011-2012). The patients with BNUC were delineated from the patients who had not been discharged from our pain clinic. Pain characteristics, pain management, and substance abuse status were compared in each patient with BNUC between the time of admission and the time of discharge. The patients with BNUC discharges showed significant variability for the discharging factors among the pain physicians within a single pain clinic model with this variability being dependent on their years of experience and their proactive interventional pain management. The patients with BNUC in our pain clinic setting were primarily middle-aged, obese, unmarried males with nondocumented stable occupational history who were receiving only noninterventional pain management. Substance abuse, doctor shopping, and potential diversion were the top three documented reasons for BNUC discharges. In 2011-2012, our pain clinic discharged 1-in-16 patients due to breach in narcotic use contract.

Confounding effects of phase delays on causality estimation.

Directory of Open Access Journals (Sweden)

Vasily A Vakorin

Full Text Available Linear and non-linear techniques for inferring causal relations between the brain signals representing the underlying neuronal systems have become a powerful tool to extract the connectivity patterns in the brain. Typically these tools employ the idea of Granger causality, which is ultimately based on the temporal precedence between the signals. At the same time, phase synchronization between coupled neural ensembles is considered a mechanism implemented in the brain to integrate relevant neuronal ensembles to perform a cognitive or perceptual task. Phase synchronization can be studied by analyzing the effects of phase-locking between the brain signals. However, we should expect that there is no one-to-one mapping between the observed phase lag and the time precedence as specified by physically interacting systems. Specifically, phase lag observed between two signals may interfere with inferring causal relations. This could be of critical importance for the coupled non-linear oscillating systems, with possible time delays in coupling, when classical linear cross-spectrum strategies for solving phase ambiguity are not efficient. To demonstrate this, we used a prototypical model of coupled non-linear systems, and compared three typical pipelines of inferring Granger causality, as established in the literature. Specifically, we compared the performance of the spectral and information-theoretic Granger pipelines as well as standard Granger causality in their relations to the observed phase differences for frequencies at which the signals become synchronized to each other. We found that an information-theoretic approach, which takes into account different time lags between the past of one signal and the future of another signal, was the most robust to phase effects.

Association between neurovascular contact and clinical characteristics in classical trigeminal neuralgia

DEFF Research Database (Denmark)

Maarbjerg, Stine; Wolfram, Frauke; Gozalov, Aydin

2015-01-01

and severe NVC. METHODS: Clinical characteristics were prospectively collected from consecutive TN patients using semi-structured interviews in a cross-sectional study design. We evaluated 3.0 Tesla MRI blinded to the symptomatic side. RESULTS: We included 135 TN patients. Severe NVC was more prevalent...

Detecting switching and intermittent causalities in time series

Science.gov (United States)

Zanin, Massimiliano; Papo, David

2017-04-01

During the last decade, complex network representations have emerged as a powerful instrument for describing the cross-talk between different brain regions both at rest and as subjects are carrying out cognitive tasks, in healthy brains and neurological pathologies. The transient nature of such cross-talk has nevertheless by and large been neglected, mainly due to the inherent limitations of some metrics, e.g., causality ones, which require a long time series in order to yield statistically significant results. Here, we present a methodology to account for intermittent causal coupling in neural activity, based on the identification of non-overlapping windows within the original time series in which the causality is strongest. The result is a less coarse-grained assessment of the time-varying properties of brain interactions, which can be used to create a high temporal resolution time-varying network. We apply the proposed methodology to the analysis of the brain activity of control subjects and alcoholic patients performing an image recognition task. Our results show that short-lived, intermittent, local-scale causality is better at discriminating both groups than global network metrics. These results highlight the importance of the transient nature of brain activity, at least under some pathological conditions.

The Causal Relationship between Health and Education Expenditures in Malaysia

Directory of Open Access Journals (Sweden)

Chor Foon TANG

2011-08-01

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

Clinical characteristics and causes of visual impairment in a low vision clinic in northern Jordan.

Science.gov (United States)

Bakkar, May M; Alzghoul, Eman A; Haddad, Mera F

2018-01-01

The aim of the study was to identify causes of visual impairment among patients attending a low vision clinic in the north of Jordan and to study the relevant demographic characteristics of these patients. The retrospective study was conducted through a review of clinical records of 135 patients who attended a low vision clinic in Irbid. Clinical characteristics of the patients were collected, including age, gender, primary cause of low vision, best corrected visual acuity, and current prescribed low vision aids. Descriptive statistics analysis using numbers and percentages were calculated to summarize categorical and nominal data. A total of 135 patients (61 [45.2%] females and 74 [54.8%] males) were recruited in the study. Mean age ± standard deviation for the study population was 24.53 ± 16.245 years; age range was 5-90 years. Of the study population, 26 patients (19.3%) had mild visual impairment, 61 patients (45.2%) had moderate visual impairment, 27 patients (20.0%) had severe visual impairment, and 21 patients (15.6%) were blind. The leading causes of visual impairment across all age groups were albinism (31.9%) and retinitis pigmentosa (RP) (18.5%). Albinism also accounted for the leading cause of visual impairment among the pediatric age group (0-15 years) while albinism, RP, and keratoconus were the primary causes of visual impairment for older patients. A total of 59 patients (43.7%) were given low vision aids either for near or distance. The only prescribed low vision aids for distances were telescopes. For near, spectacle-type low vision aid was the most commonly prescribed low vision aids. Low vision services in Jordan are still very limited. A national strategy programme to increase awareness of low vision services should be implemented, and health care policies should be enforced to cover low vision aids through the national medical insurance.

"What is this genetics, anyway?" Understandings of genetics, illness causality and inheritance among British Pakistani users of genetic services.

Science.gov (United States)

Shaw, Alison; Hurst, Jane A

2008-08-01

Misconceptions about basic genetic concepts and inheritance patterns may be widespread in the general population. This paper investigates understandings of genetics, illness causality and inheritance among British Pakistanis referred to a UK genetics clinic. During participant observation of genetics clinic consultations and semi-structured interviews in Urdu or English in respondents' homes, we identified an array of environmental, behavioral and spiritual understandings of the causes of medical and intellectual problems. Misconceptions about the location of genetic information in the body and of genetic mechanisms of inheritance were common, reflected the range of everyday theories observed for White British patients and included the belief that a child receives more genetic material from the father than the mother. Despite some participants' conversational use of genetic terminology, some patients had assimilated genetic information in ways that conflict with genetic theory with potentially serious clinical consequences. Additionally, skepticism of genetic theories of illness reflected a rejection of a dominant discourse of genetic risk that stigmatizes cousin marriages. Patients referred to genetics clinics may not easily surrender their lay or personal theories about the causes of their own or their child's condition and their understandings of genetic risk. Genetic counselors may need to identify, work with and at times challenge patients' understandings of illness causality and inheritance.

Work characteristics and psychological well-being. Testing normal reversed and reciprocal relationships within the 4-wave smash study

NARCIS (Netherlands)

Taris, T.W.; Kompier, M.A.J.; Houtman, I.L.D.; Bongers, P.M.

2004-01-01

This longitudinal study examined the causal relationships between job demands, job control and supervisor support on the one hand and mental health on the other. Whereas we assumed that work characteristics affect mental health, we also examined reversed causal relationships (mental health

Work characteristics and psychological well-being. Testing normal, reversed and reciprocal relationships within the 4-wave SMASH study

NARCIS (Netherlands)

de Lange, A.H.; Taris, T.W.; Kompier, M.A.J.; Houtman, I.L.D.; Bongers, P.M.

2004-01-01

This longitudinal study examined the causal relationships between job demands, job control and supervisor support on the one hand and mental health on the other. Whereas we assumed that work characteristics affect mental health, we also examined reversed causal relationships (mental health

Measures of Coupling between Neural Populations Based on Granger Causality Principle.

Science.gov (United States)