Quantum-coherent mixtures of causal relations
MacLean, Jean-Philippe W; Spekkens, Robert W; Resch, Kevin J
2016-01-01
Understanding the causal influences that hold among the parts of a system is critical both to explaining that system's natural behaviour and to controlling it through targeted interventions. In a quantum world, understanding causal relations is equally important, but the set of possibilities is far richer. The two basic ways in which a pair of time-ordered quantum systems may be causally related are by a cause-effect mechanism or by a common cause acting on both. Here, we show that it is possible to have a coherent mixture of these two possibilities. We realize such a nonclassical causal relation in a quantum optics experiment and derive a set of criteria for witnessing the coherence based on a quantum version of Berkson's paradox. The interplay of causality and quantum theory lies at the heart of challenging foundational puzzles, such as Bell's theorem and the search for quantum gravity, but could also provide a resource for novel quantum technologies.
Antonakis, J.
2015-01-01
Making correct causal claims is important for research and practice. This article explains what causality is, and how it can be established via experimental design. Because experiments are infeasible in many applied settings, researchers often use "observational" methods to estimate causal models. In these situations, it is likely that model estimates are compromised by endogeneity. The article discusses the conditions that engender endogeneity and methods that can eliminate it.
Systems and methods for removing components of a gas mixture
None
2016-09-06
A system for removing components of a gaseous mixture is provided comprising: a reactor fluid containing vessel having conduits extending therefrom, aqueous fluid within the reactor, the fluid containing a ligand and a metal, and at least one reactive surface within the vessel coupled to a power source. A method for removing a component from a gaseous mixture is provided comprising exposing the gaseous mixture to a fluid containing a ligand and a reactive metal, the exposing chemically binding the component of the gaseous mixture to the ligand. A method of capturing a component of a gaseous mixture is provided comprising: exposing the gaseous mixture to a fluid containing a ligand and a reactive metal, the exposing chemically binding the component of the gaseous mixture to the ligand, altering the oxidation state of the metal, the altering unbinding the component from the ligand, and capturing the component.
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.
Intertrial coherence and causal interaction among independent EEG components.
Zervakis, M; Michalopoulos, K; Iordanidou, V; Sakkalis, V
2011-04-30
Over the past few years there has been an increased interest in studying the underlying neural mechanism of attention and cognitive brain activity. This paper aims towards identifying and analyzing distinct responses in an auditory working memory paradigm, as independent components with variable latency, frequency and phase characteristics. The event-related nature of components (either phase or non-phase-locked) over multiple trials is thoroughly examined through intertrial coherence measures. Furthermore, the functional coupling of independent components is investigated through the concept of partial directed coherence depicted as a directed graph. Using these tools, the paper compares issues of activation, connectivity and directionality in the synchronization maps of two populations, of control and Alzheimer's subjects. The results on real data from an oddball experiment verify and further enhance the findings of previous studies and illustrate the potential of the proposed analysis framework.
Independent components in spectroscopic analysis of complex mixtures
Monakhova, Yulia B; Kraskov, Alexander; Mushtakova, Svetlana P; 10.1016/j.chemolab.2010.05.023
2010-01-01
We applied two methods of "blind" spectral decomposition (MILCA and SNICA) to quantitative and qualitative analysis of UV absorption spectra of several non-trivial mixture types. Both methods use the concept of statistical independence and aim at the reconstruction of minimally dependent components from a linear mixture. We examined mixtures of major ecotoxicants (aromatic and polyaromatic hydrocarbons), amino acids and complex mixtures of vitamins in a veterinary drug. Both MICLA and SNICA were able to recover concentrations and individual spectra with minimal errors comparable with instrumental noise. In most cases their performance was similar to or better than that of other chemometric methods such as MCR-ALS, SIMPLISMA, RADICAL, JADE and FastICA. These results suggest that the ICA methods used in this study are suitable for real life applications.
Hydrogen component fugacities in binary mixtures with methane and propane
Energy Technology Data Exchange (ETDEWEB)
Bruno, T.J.; Ely, J.F.; Hume, G.L.
1986-09-01
The fugacity coefficients of hydrogen in binary mixtures with methane and propane were measured using a physical equilibrium technique. This technique involves the use of an experimental chamber which is divided into two regions by a semipermeable membrane. Hydrogen can penetrate and pass through the membrane, while the other component (in this case, methane or propane) cannot. At equilibrium, pure hydrogen will permeate into one ''compartment'' of the chamber, while the binary mixture occupies the other compartment. Thus, the pressure of pure hydrogen on one side approaches the partial pressure of hydrogen in the mixture on the other side of the membrane. This allows a direct measurement of the hydrogen component fugacity at a given mixture mole fraction. In this study, results are reported for measurements made on the hydrogen+propane binary at 80 degrees C (353 K) and 130 degrees C (403 K) and the hydrogen+methane binary at 80 degrees C (353 K). All measurements were performed with a total mixture pressure of 3.45 MPa. The experimental results are compared with predictions from the Redlich-Kwong, Peng-Robinson, and extended corresponding-states models.
Predicting minimum fluidization velocities of multi-component solid mixtures
Institute of Scientific and Technical Information of China (English)
Mohammad Asif
2013-01-01
Employing well-established mixing rules for mean properties,appropriate expressions are aerivea for predicting minimum fluidization velocities of multi-component solid mixtures in terms of monocomponent values for the velocity and the bed voidage at incipient fluidization.Based on flow regime and the mixing level of constituent species,it is found that these relationships differ significantly from each other,whether related to size-different or density-different mixtures.For mixed beds of size-different mixtures,the effect of volume contraction is accounted for by the mean voidage term,which is absent for segregated beds.Incorporating the volume-change of mixing leads to values of the mixture minimum fluidization velocities even lower than corresponding values for segregated bed,thus conforming to the trend reported in the literature.Size-different mixtures exhibit flow regime dependence irrespective of whether the bed is mixed or segregated.On the other hand,the mixing of constituent species does not affect the minimum fluidization velocity of density-different mixtures,as the difference in the expressions for a segregated and a mixed system is rather inconsequential.Comparison with experimental data available in the literature is made to test the efficacy of the minimum fluidization velocity expressions derived here.
A micropolar mixture theory of multi-component porous media
Institute of Scientific and Technical Information of China (English)
Lu HUANG; Cheng-gang ZHAO
2009-01-01
A mixture theory is developed for multi-component micropolar porous media with a combination of the hybrid mixture theory and the micropolar continuum theory.The system is modeled as multi-component micropolar elastic solids saturated with multicomponent micropolar viscous fluids. Balance equations are given through the mixture theory. Constitutive equations are developed based on the second law of thermodynamics and constitutive assumptions. Taking account of compressibility of solid phases,the volume fraction of fluid as an independent state variable is introduced in the free energy function,and the dynamic compatibility condition is obtained to restrict the change of pressure difference on the solid-fluid interface. The constructed constitutive equations are used to close the field equations. The linear field equations are obtained using a linearization procedure,and the micropolar thermo-hydro-mechanical component transport model is established. This model can be applied to practical problems,such as contaminant,drug,and pesticide transport. When the proposed model is supposed to be porous media,and both fluid and solid are single-component,it will almost agree with Eringen's model.
Efficient speaker verification using Gaussian mixture model component clustering.
Energy Technology Data Exchange (ETDEWEB)
De Leon, Phillip L. (New Mexico State University, Las Cruces, NM); McClanahan, Richard D.
2012-04-01
In speaker verification (SV) systems that employ a support vector machine (SVM) classifier to make decisions on a supervector derived from Gaussian mixture model (GMM) component mean vectors, a significant portion of the computational load is involved in the calculation of the a posteriori probability of the feature vectors of the speaker under test with respect to the individual component densities of the universal background model (UBM). Further, the calculation of the sufficient statistics for the weight, mean, and covariance parameters derived from these same feature vectors also contribute a substantial amount of processing load to the SV system. In this paper, we propose a method that utilizes clusters of GMM-UBM mixture component densities in order to reduce the computational load required. In the adaptation step we score the feature vectors against the clusters and calculate the a posteriori probabilities and update the statistics exclusively for mixture components belonging to appropriate clusters. Each cluster is a grouping of multivariate normal distributions and is modeled by a single multivariate distribution. As such, the set of multivariate normal distributions representing the different clusters also form a GMM. This GMM is referred to as a hash GMM which can be considered to a lower resolution representation of the GMM-UBM. The mapping that associates the components of the hash GMM with components of the original GMM-UBM is referred to as a shortlist. This research investigates various methods of clustering the components of the GMM-UBM and forming hash GMMs. Of five different methods that are presented one method, Gaussian mixture reduction as proposed by Runnall's, easily outperformed the other methods. This method of Gaussian reduction iteratively reduces the size of a GMM by successively merging pairs of component densities. Pairs are selected for merger by using a Kullback-Leibler based metric. Using Runnal's method of reduction, we
Merging Mixture Components for Cell Population Identification in Flow Cytometry
Directory of Open Access Journals (Sweden)
Greg Finak
2009-01-01
Full Text Available We present a framework for the identification of cell subpopulations in flow cytometry data based on merging mixture components using the flowClust methodology. We show that the cluster merging algorithm under our framework improves model fit and provides a better estimate of the number of distinct cell subpopulations than either Gaussian mixture models or flowClust, especially for complicated flow cytometry data distributions. Our framework allows the automated selection of the number of distinct cell subpopulations and we are able to identify cases where the algorithm fails, thus making it suitable for application in a high throughput FCM analysis pipeline. Furthermore, we demonstrate a method for summarizing complex merged cell subpopulations in a simple manner that integrates with the existing flowClust framework and enables downstream data analysis. We demonstrate the performance of our framework on simulated and real FCM data. The software is available in the flowMerge package through the Bioconductor project.
Construction of a 21-Component Layered Mixture Experiment Design
Energy Technology Data Exchange (ETDEWEB)
Piepel, Gregory F.; Cooley, Scott K.; Jones, Bradley
2004-09-22
This paper describes the solution to a unique and challenging mixture experiment design problem involving: (1) 19 and 21 components for two different parts of the design, (2) many single-component and multi-component constraints, (3) augmentation of existing data, (4) a layered design developed in stages, and (5) a no-candidate-point optimal design approach. The problem involved studying the liquidus temperature of spinel crystals as a function of nuclear waste glass composition. The statistical objective was to develop an experimental design by augmenting existing glasses with new nonradioactive and radioactive glasses chosen to cover the designated nonradioactive and radioactive experimental regions. The existing 144 glasses were expressed as 19-component nonradioactive compositions and then augmented with 40 new nonradioactive glasses. These included 8 glasses on the outer layer of the region, 27 glasses on an inner layer, 2 replicate glasses at the centroid, and one replicate each of three existing glasses. Then, the 144 + 40 = 184 glasses were expressed as 21-component radioactive compositions and augmented with 5 radioactive glasses. A D-optimal design algorithm was used to select the new outer layer, inner layer, and radioactive glasses. Several statistical software packages can generate D-optimal experimental designs, but nearly all require a set of candidate points (e.g., vertices) from which to select design points. The large number of components (19 or 21) and many constraints made it impossible to generate the huge number of vertices and other typical candidate points. JMP(R) was used to select design points without candidate points. JMP uses a coordinate-exchange algorithm modified for mixture experiments, which is discussed in the paper.
Schifferstein, H.N.J.
1996-01-01
The Equiratio Mixture Model predicts the psychophysical function for an equiratio mixture type on the basis of the psychophysical functions for the unmixed components. The model reliably estimates the sweetness of mixtures of sugars and sugar-alchohols, but is unable to predict intensity for asparta
Energy Technology Data Exchange (ETDEWEB)
Piepel, Greg F.; Cooley, Scott K.; Vienna, John D.; Crum, Jarrod V.
2015-12-14
This article presents a case study of developing an experimental design for a constrained mixture experiment when the experimental region is defined by single-component constraints (SCCs), linear multiple-component constraints (MCCs), and a nonlinear MCC. Traditional methods and software for designing constrained mixture experiments with SCCs and linear MCCs are not directly applicable because of the nonlinear MCC. A modification of existing methodology to account for the nonlinear MCC was developed and is described in this article. The case study involves a 15-component nuclear waste glass example in which SO3 is one of the components. SO3 has a solubility limit in glass that depends on the composition of the balance of the glass. A goal was to design the experiment so that SO3 would not exceed its predicted solubility limit for any of the experimental glasses. The SO3 solubility limit had previously been modeled by a partial quadratic mixture (PQM) model expressed in the relative proportions of the 14 other components. The PQM model was used to construct a nonlinear MCC in terms of all 15 components. In addition, there were SCCs and linear MCCs. This article discusses the waste glass example and how a layered design was generated to (i) account for the SCCs, linear MCCs, and nonlinear MCC and (ii) meet the goals of the study.
Dong, Chao-Yi; Yoon, Tae-Woong; Bates, Declan G; Cho, Kwang-Hyun
2010-02-01
Feedback circuits are crucial dynamic motifs which occur in many biomolecular regulatory networks. They play a pivotal role in the regulation and control of many important cellular processes such as gene transcription, signal transduction, and metabolism. In this study, we develop a novel computationally efficient method to identify feedback loops embedded in intracellular networks, which uses only time-series experimental data and requires no knowledge of the network structure. In the proposed approach, a non-parametric system identification technique, as well as a spectral factor analysis, is applied to derive a graphical criterion based on non-causal components of the system's impulse response. The appearance of non-causal components in the impulse response sequences arising from stochastic output perturbations is shown to imply the presence of underlying feedback connections within a linear network. In order to extend the approach to nonlinear networks, we linearize the intracellular networks about an equilibrium point, and then choose the magnitude of the output perturbations sufficiently small so that the resulting time-series responses remain close to the chosen equilibrium point. In this way, the impulse response sequences of the linearized system can be used to determine the presence or absence of feedback loops in the corresponding nonlinear network. The proposed method utilizes the time profile data from intracellular perturbation experiments and only requires the perturbability of output nodes. Most importantly, the method does not require any a priori knowledge of the system structure. For these reasons, the proposed approach is very well suited to identifying feedback loops in large-scale biomolecular networks. The effectiveness of the proposed method is illustrated via two examples: a synthetic network model with a negative feedback loop and a nonlinear caspase function model of apoptosis with a positive feedback loop.
Bikulov, R. A.; Kotlyar, L. M.
2014-12-01
For the development and management of the manufacturing processes of axisymmetric articles with compositional structure by centrifugal casting method [1,2,3,4] is necessary to create a generalized mathematical model of the dynamics of component mixture in the molten cast iron during centrifugation. In article. based on the analysis of the dynamics of two-component mixture at sedimentation, a method of successive approximations to determine the distribution of a multicomponent mixture by centrifugation in a parabolic crucible is developed.
Structure of multi-component/multi-Yukawa mixtures
Blum, L.; Arias, M.
2006-09-01
\\begin{equation} \\fl 2 \\pi \\tilde{g}_{ij}(s)=-\\frac{\\rme^{-s \\sigma_{ij}}}{D_{\\tau}(s)} \\left\\{{1\\over s^2}+{1\\over s}Q^{\\prime}_{ij}(\\sigma_{ij})+\\sum_{m=1}^{M}{{ z_m \\tilde{\\cal{X}}}_i^{(m)}{f}_j^{(m)}\\over{s+z_m}}\\right\\}. \\label{eq2} \\end{equation} This function is also easily transformed into S(k) by replacing s\\Rightarrow \\rmi k . For low density situations (dilute colloids) D_{\\tau } (s)\\sim 1+{\\cal {O}(\\rho)} and S(k) is a sum of M Lorentzians. For hard sphere PY mixtures we get the simple (compare Lebowitz 1964 Phys. Rev. 133 A895 and Blum and Stell 1979 J. Chem. Phys. 71 42) \\[ 2 \\pi \\tilde{g}_{ij}(s)=-\\frac{\\rme^{-s \\sigma_{ij}}}{s^2 D_{\\tau}(s)} \\left\\{1+s\\left[(Q^{HS})^{\\prime}_{ij}(\\sigma_{ij})\\right]\\right\\} \\] where Dτ(s) is a scalar function. For polydisperse electrolytes in the MSA a simpler expression is also obtained (compare Blum and Hoye 1977 J. Phys. Chem. 81 1311). An explicit continued fraction solution of the one component multi-Yukawa case is also given.
Energy Technology Data Exchange (ETDEWEB)
Bowers, W.; Nakai, J.; Yagminas, A.; Chu, I.; Moir, D. [Health Canada (Canada)
2004-09-15
The current study was designed to evaluate the neurobehavioral effects of perinatal exposure to a chemical mixture that is based on relative concentrations of persistent organic pollutants found in the blood of Canadian Arctic populations and contains 14 PCB congeners, 12 organochlorine pesticides and methyl mercury. This study compared the effects of the complete mixture with the effects of three major components of the mixture (the PCB component, the organochlorine pesticide component, and the methyl mercury component). By examining a range of neurobehavioural functions over development we also determine if specific neurobehavioural disturbances produced by the mixture can be attributed to components of the mixture and if neurobehavioural effects produced by components of the mixture are altered by concurrent exposure to other components in the mixture. Ninety-two nulliparious female Sprague-Dawley rats served as subjects.
Magnetic ordering of three-component ultracold fermionic mixtures in optical lattices
Sotnikov, Andrii; Hofstetter, Walter
2014-06-01
We study finite-temperature magnetic phases of three-component mixtures of ultracold fermions with repulsive interactions in optical lattices with simple cubic or square geometry by means of dynamical mean-field theory (DMFT). We focus on the case of one particle per site (1/3 band filling) at moderate interaction strength, where we observe a sequence of thermal phase transitions into two- and three-sublattice ordered states by means of the unrestricted real-space generalization of DMFT. From our quantitative analysis we conclude that long-range ordering in three-component mixtures should be observable at comparable temperatures as in two-component mixtures.
Component separation in harmonically trapped boson-fermion mixtures
DEFF Research Database (Denmark)
Nygaard, Nicolai; Mølmer, Klaus
1999-01-01
We present a numerical study of mixed boson-fermion systems at zero temperature in isotropic and anise tropic harmonic traps. We investigate the phenomenon of component separation as a function of the strength ut the interparticle interaction. While solving a Gross-Pitaevskii mean-field equation ...... for the boson distribution in the trap, we utilize two different methods to extract the density profile of the fermion component; a semiclassical Thomas-Fermi approximation and a quantum-mechanical Slater determinant Schrodinger equation....
Kinetic Modeling of Gasoline Surrogate Components and Mixtures under Engine Conditions
Energy Technology Data Exchange (ETDEWEB)
Mehl, M; Pitz, W J; Westbrook, C K; Curran, H J
2010-01-11
Real fuels are complex mixtures of thousands of hydrocarbon compounds including linear and branched paraffins, naphthenes, olefins and aromatics. It is generally agreed that their behavior can be effectively reproduced by simpler fuel surrogates containing a limited number of components. In this work, an improved version of the kinetic model by the authors is used to analyze the combustion behavior of several components relevant to gasoline surrogate formulation. Particular attention is devoted to linear and branched saturated hydrocarbons (PRF mixtures), olefins (1-hexene) and aromatics (toluene). Model predictions for pure components, binary mixtures and multicomponent gasoline surrogates are compared with recent experimental information collected in rapid compression machine, shock tube and jet stirred reactors covering a wide range of conditions pertinent to internal combustion engines (3-50 atm, 650-1200K, stoichiometric fuel/air mixtures). Simulation results are discussed focusing attention on the mixing effects of the fuel components.
Energy Technology Data Exchange (ETDEWEB)
Piepel, G.; Redgate, T. [Pacific Northwest National Lab., Richland, WA (United States). Statistics Group
1997-12-01
Statistical mixture experiment techniques were applied to a waste glass data set to investigate the effects of the glass components on Product Consistency Test (PCT) sodium release (NR) and to develop a model for PCT NR as a function of the component proportions. The mixture experiment techniques indicate that the waste glass system can be reduced from nine to four components for purposes of modeling PCT NR. Empirical mixture models containing four first-order terms and one or two second-order terms fit the data quite well, and can be used to predict the NR of any glass composition in the model domain. The mixture experiment techniques produce a better model in less time than required by another approach.
Directory of Open Access Journals (Sweden)
Frolov Sergey M.
2016-02-01
Full Text Available Causal relations between components of the region foreign trade turnover and indicators, which characterize the economic situation of the region, country and the world, have been studied. 3 groups of indicators, which can have an impact on the region export-import activity, were formed by the degree of the covered influence level: the level of region, country and world. All the selected indicators were tested for causality by Granger test. As a result of the study it has been found that the export of Sumy region is directly affected by the volume of industrial production, inflation rate in Ukraine and the world price for wheat. The export of services is affected by the volume of extended credits, income of the population per person, the world prices for corn and wheat. Causality has also been determined between the import of goods in Sumy region and indicators of extended credits, turnover of retail trade and wholesale trade of enterprises. As regards the import of services, the influence was recorded from the side of the official exchange rate of hryvnia to the US dollar and the price index of industrial producers. The prospect of further research in this direction is expansion of the set of indicators characterizing the economic activity of the region, country and the world. The further research can contribute to building up the export-import potential of the region.
Energy Technology Data Exchange (ETDEWEB)
Piepel, Gregory F.; Cooley, Scott K.; Jones, Bradley
2005-11-01
This paper describes the solution to a unique and challenging mixture experiment design problem involving: 1) 19 and 21 components for two different parts of the design, 2) many single-component and multi-component constraints, 3) augmentation of existing data, 4) a layered design developed in stages, and 5) a no-candidate-point optimal design approach. The problem involved studying the liquidus temperature of spinel crystals as a function of nuclear waste glass composition. The statistical objective was to develop an experimental design by augmenting existing glasses with new nonradioactive and radioactive glasses chosen to cover the designated nonradioactive and radioactive experimental regions. The existing 144 glasses were expressed as 19-component nonradioactive compositions and then augmented with 40 new nonradioactive glasses. These included 8 glasses on the outer layer of the region, 27 glasses on an inner layer, 2 replicate glasses at the centroid, and one replicate each of three existing glasses. Then, the 144 + 40 = 184 glasses were expressed as 21-component radioactive compositions, and augmented with 5 radioactive glasses. A D-optimal design algorithm was used to select the new outer layer, inner layer, and radioactive glasses. Several statistical software packages can generate D-optimal experimental designs, but nearly all of them require a set of candidate points (e.g., vertices) from which to select design points. The large number of components (19 or 21) and many constraints made it impossible to generate the huge number of vertices and other typical candidate points. JMP was used to select design points without candidate points. JMP uses a coordinate-exchange algorithm modified for mixture experiments, which is discussed and illustrated in the paper.
Mixture component effects on the in vitro dermal absorption of pentachlorophenol
Energy Technology Data Exchange (ETDEWEB)
Riviere, J.E.; Qiao, G.; Baynes, R.E.; Brooks, J.D. [Coll. of Veterinary Medicine, North Carolina State Univ., Raleigh, NC (United States); Mumtaz, M. [Agency for Toxic Substances and Disease Registry (ATSDR), Atlanta, GA (United States)
2001-08-01
Interactions between chemicals in a mixture and interactions of mixture components with the skin can significantly alter the rate and extent of percutaneous absorption, as well as the cutaneous disposition of a topically applied chemical. The predictive ability of dermal absorption models, and consequently the dermal risk assessment process, would be greatly improved by the elucidation and characterization of these interactions. Pentachlorophenol (PCP), a compound known to penetrate the skin readily, was used as a marker compound to examine mixture component effects using in vitro porcine skin models. PCP was administered in ethanol or in a 40% ethanol/60% water mixture or a 40% ethanol/60% water mixture containing either the rubefacient methyl nicotinate (MNA) or the surfactant sodium lauryl sulfate (SLS), or both MNA and SLS. Experiments were also conducted with {sup 14}C-labelled 3,3',4,4'-tetrachlorobiphenyl (TCB) and 3,3',4,4',5-pentachlorobiphenyl (PCB). Maximal PCP absorption was 14.12% of the applied dose from the mixture containing SLS, MNA, ethanol and water. However, when PCP was administered in ethanol only, absorption was only 1.12% of the applied dose. There were also qualitative differences among the absorption profiles for the different PCP mixtures. In contrast with the PCP results, absorption of TCB or PCB was negligible in perfused porcine skin, with only 0.14% of the applied TCB dose and 0.05% of the applied PCB dose being maximally absorbed. The low absorption levels for the PCB congeners precluded the identification of mixture component effects. These results suggest that dermal absorption estimates from a single chemical exposure may not reflect absorption seen after exposure as a chemical mixture and that absorption of both TCB and PCB are minimal in this model system. (orig.)
Operation of the multigap resistive plate chamber using a gas mixture free of flammable components
Akindinov, A; Antonioli, P; Arcelli, S; Basile, M; Cara Romeo, G; Cifarelli, Luisa; Cindolo, F; De Caro, A; De Pasquale, S; Di Bartolomeo, A; Fusco-Girard, M; Golovine, V; Guida, M; Hatzifotiadou, D; Kaidalov, A B; Kim, D H; Kim, D W; Kisselev, S M; Laurenti, G; Lee, K; Lee, S C; Lioublev, E; Luvisetto, M L; Margotti, A; Martemyanov, A N; Nania, R; Noferini, F; Otiougova, P; Pesci, A; Pinazza, O; Polozov, P A; Scapparone, E; Scioli, G; Sellitto, S B; Semeria, F; Smirnitsky, A V; Tchoumakov, M M; Usenko, E; Valenti, G; Voloshin, K G; Williams, M C S; Zagreev, B V; Zampolli, C; Zichichi, A
2004-01-01
We have investigated the operation of the multigap resistive plate chamber (MRPC) for the ALICE-TOF system with a gas mixture free of flammable components. Two different gas mixtures, with and without iso-C//4H//1//0 have been used to measure the performance of the MRPC. The efficiency, time resolution, total charge, and the fast to total charge ratio have been found to be comparable.
Energy Technology Data Exchange (ETDEWEB)
Piepel, Gregory F.
2006-05-01
A mixture experiment involves combining two or more components in various proportions and collecting data on one or more responses. A linear mixture model may adequately represent the relationship between a response and mixture component proportions and be useful in screening the mixture components. The Scheffé and Cox parameterizations of the linear mixture model are commonly used for analyzing mixture experiment data. With the Scheffé parameterization, the fitted coefficient for a component is the predicted response at that pure component (i.e., single-component mixture). With the Cox parameterization, the fitted coefficient for a mixture component is the predicted difference in response at that pure component and at a pre-specified reference composition. This paper presents a new component-slope parameterization, in which the fitted coefficient for a mixture component is the predicted slope of the linear response surface along the direction determined by that pure component and at a pre-specified reference composition. The component-slope, Scheffé, and Cox parameterizations of the linear mixture model are compared and their advantages and disadvantages are discussed.
Chen, Zhe; Daehler, Marvin W.
1992-01-01
Kindergartners and second graders heard stories containing an intention to solve a problem and a successful outcome or stories that lacked these components. Second graders showed evidence of transfer of knowledge for stories containing an intentional component. (BC)
Phase Equilibrium Calculations for Multi-Component Polar Fluid Mixtures with tPC-PSAFT
DEFF Research Database (Denmark)
Karakatsani, Eirini; Economou, Ioannis
2007-01-01
The truncated Perturbed-Chain Polar Statistical Associating Fluid Theory (tPC-PSAFT) is applied to a number of different mixtures, including binary, ternary and quaternary mixtures of components that differ substantially in terms of intermolecular interactions and molecular size. In contrast...... to most other SAFT versions, tPC-PSAFT accounts explicitly for polar forces. Three pure-component parameters are required for non-polar and non-associating compounds, two additional parameters characterize the association contribution and one parameter is needed to account for polar interactions...
Phase equilibria in DOPC/DPPC: Conversion from gel to subgel in two component mixtures.
Schmidt, Miranda L; Ziani, Latifa; Boudreau, Michelle; Davis, James H
2009-11-07
Biological membranes contain a mixture of phospholipids with varying degrees of hydrocarbon chain unsaturation. Mixtures of long chain saturated and unsaturated lipids with cholesterol have attracted a lot of attention because of the formation of two coexisting fluid bilayer phases in such systems over a broad range of temperature and composition. Interpretation of the phase behavior of such ternary mixtures must be based on a thorough understanding of the phase behavior of the binary mixtures formed with the same components. This article describes the phase behavior of mixtures of 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC) with 1,2-di-d(31)-palmitoyl-sn-glycero-3-phosphocholine (DPPC) between -20 and 50 degrees C. Particular attention has been paid to the phase coexistence below about 16 degrees C where the subgel phase appears. The changes in the shape of the spectrum (and its spectral moments) during the slow transformation process leads to the conclusion that below 16 degrees C the gel phase is metastable and the gel component of the two-phase mixture slowly transforms to the subgel phase with a slightly different composition. This results in a line of three-phase coexistence near 16 degrees C. Analysis of the transformation of the metastable gel domains into the subgel phase using the nucleation and growth model shows that the subgel domain growth is a two dimensional process.
Transport of a two-component mixture in one-dimensional channels
Borman, VD; Tronin, VN; Tronin, [No Value; Troyan, [No Value
2004-01-01
The transport of a two-component gas mixture in subnanometer channels is investigated theoretically for an arbitrary filling of channels. Special attention is paid to consistent inclusion of density effects, which are associated both with the interaction and with a finite size of particles. The anal
Directory of Open Access Journals (Sweden)
Silva-Aguilar Martín
2011-01-01
Full Text Available Metals are ubiquitous pollutants present as mixtures. In particular, mixture of arsenic-cadmium-lead is among the leading toxic agents detected in the environment. These metals have carcinogenic and cell-transforming potential. In this study, we used a two step cell transformation model, to determine the role of oxidative stress in transformation induced by a mixture of arsenic-cadmium-lead. Oxidative damage and antioxidant response were determined. Metal mixture treatment induces the increase of damage markers and the antioxidant response. Loss of cell viability and increased transforming potential were observed during the promotion phase. This finding correlated significantly with generation of reactive oxygen species. Cotreatment with N-acetyl-cysteine induces effect on the transforming capacity; while a diminution was found in initiation, in promotion phase a total block of the transforming capacity was observed. Our results suggest that oxidative stress generated by metal mixture plays an important role only in promotion phase promoting transforming capacity.
Directory of Open Access Journals (Sweden)
Varun Kumar Ojha
2012-08-01
Full Text Available The article presents performance analysis of a real valued neuro genetic algorithm applied for thedetection of proportion of the gases found in manhole gas mixture. The neural network (NN trained usinggenetic algorithm (GA leads to concept of neuro genetic algorithm, which is used for implementing anintelligent sensory system for the detection of component gases present in manhole gas mixture Usually amanhole gas mixture contains several toxic gases like Hydrogen Sulfide, Ammonia, Methane, CarbonDioxide, Nitrogen Oxide, and Carbon Monoxide. A semiconductor based gas sensor array used for sensingmanhole gas components is an integral part of the proposed intelligent system. It consists of many sensorelements, where each sensor element is responsible for sensing particular gas component. Multiple sensorsof different gases used for detecting gas mixture of multiple gases, results in cross-sensitivity. The crosssensitivity is a major issue and the problem is viewed as pattern recognition problem. The objective of thisarticle is to present performance analysis of the real valued neuro genetic algorithm which is applied formultiple gas detection.
Directory of Open Access Journals (Sweden)
Varun Kumar Ojha
2012-07-01
Full Text Available The article presents performance analysis of a real valued neuro genetic algorithm applied for the detection of proportion of the gases found in manhole gas mixture. The neural network (NN trained using genetic algorithm (GA leads to concept of neuro genetic algorithm, which is used for implementing an intelligent sensory system for the detection of component gases present in manhole gas mixture Usually a manhole gas mixture contains several toxic gases like Hydrogen Sulfide, Ammonia, Methane, Carbon Dioxide, Nitrogen Oxide, and Carbon Monoxide. A semiconductor based gas sensor array used for sensing manhole gas components is an integral part of the proposed intelligent system. It consists of many sensor elements, where each sensor element is responsible for sensing particular gas component. Multiple sensors of different gases used for detecting gas mixture of multiple gases, results in cross-sensitivity. The crosssensitivity is a major issue and the problem is viewed as pattern recognition problem. The objective of this article is to present performance analysis of the real valued neuro genetic algorithm which is applied for multiple gas detection.
Dynamics of Feshbach Molecules in an Ultracold Three-Component Mixture
Khramov, A Y; Jamison, A O; Dowd, W H; Gupta, S
2012-01-01
We present investigations of the formation rate and collisional stability of lithium Feshbach molecules in an ultracold three-component mixture composed of two resonantly interacting fermionic 6-Li spin states and bosonic 174-Yb. We observe long molecule lifetimes (> 100 ms) even in the presence of a large ytterbium bath and extract reaction rate coefficients of the system. We find good collisional stability of the mixture in the unitary regime, opening new possibilities for studies and probes of strongly interacting quantum gases in contact with a bath species.
Mixture gas component concentration analysis based on support vector machine and infrared spectrum
Institute of Scientific and Technical Information of China (English)
Peng Bai; Junhua Liu
2006-01-01
@@ A novel quantitative analysis method of multi-component mixture gas concentration based on support vector machine (SVM) and spectroscopy is proposed. Through transformation of the kernel function, the seriously overlapped and nonlinear spectrum data are transformed in high-dimensional space, but the highdimensional data can be processed in the original space. Some factors, such as kernel function, range of the wavelength, and penalty coefficient, are discussed. This method is applied to the quantitative analysis of natural gas components concentration, and the component concentration maximal deviation is 2.28%.
Optimum Tolerance Design Using Component-Amount and Mixture-Amount Experiments
Energy Technology Data Exchange (ETDEWEB)
Piepel, Gregory F.; Ozler, Cenk; Sehirlioglu, Ali Kemal
2013-08-01
One type of tolerance design problem involves optimizing component and assembly tolerances to minimize the total cost (sum of manufacturing cost and quality loss). Previous literature recommended using traditional response surface (RS) designs and models to solve this type of tolerance design problem. In this article, component-amount (CA) and mixture-amount (MA) approaches are proposed as more appropriate for solving this type of tolerance design problem. The advantages of the CA and MA approaches over the RS approach are discussed. Reasons for choosing between the CA and MA approaches are also discussed. The CA and MA approaches (experimental design, response modeling, and optimization) are illustrated using real examples.
Wang, Xue Z; Yang, Yang; Li, Ruifa; McGuinnes, Catherine; Adamson, Janet; Megson, Ian L; Donaldson, Kenneth
2014-08-01
Structure toxicity relationship analysis was conducted using principal component analysis (PCA) for a panel of nanoparticles that included dry powders of oxides of titanium, zinc, cerium and silicon, dry powders of silvers, suspensions of polystyrene latex beads and dry particles of carbon black, nanotubes and fullerene, as well as diesel exhaust particles. Acute in vitro toxicity was assessed by different measures of cell viability, apoptosis and necrosis, haemolytic effects and the impact on cell morphology, while structural properties were characterised by particle size and size distribution, surface area, morphology, metal content, reactivity, free radical generation and zeta potential. Different acute toxicity measures were processed using PCA that classified the particles and identified four materials with an acute toxicity profile: zinc oxide, polystyrene latex amine, nanotubes and nickel oxide. PCA and contribution plot analysis then focused on identifying the structural properties that could determine the acute cytotoxicity of these four materials. It was found that metal content was an explanatory variable for acute toxicity associated with zinc oxide and nickel oxide, while high aspect ratio appeared the most important feature in nanotubes. Particle charge was considered as a determinant for high toxicity of polystyrene latex amine.
Pratiwi, Destari; Fawcett, J Paul; Gordon, Keith C; Rades, Thomas
2002-11-01
Ranitidine hydrochloride exists as two polymorphs, forms I and II, both of which are used to manufacture commercial tablets. Raman spectroscopy can be used to differentiate the two forms but univariate methods of quantitative analysis of one polymorph as an impurity in the other lack sensitivity. We have applied principal components analysis (PCA) of Raman spectra to binary mixtures of the two polymorphs and to binary mixtures prepared by adding one polymorph to powdered tablets of the other. Based on absorption measurements of seven spectral regions, it was found that >97% of the spectral variation was accounted for by three principal components. Quantitative calibration models generated by multiple linear regression predicted a detection limit and quantitation limit for either forms I or II in mixtures of the two of 0.6 and 1.8%, respectively. This study demonstrates that PCA of Raman spectroscopic data provides a sensitive method for the quantitative analysis of polymorphic impurities of drugs in commercial tablets with a quantitation limit of less than 2%.
Determination of the combustion behavior for pure components and mixtures using a 20-liter sphere
Mashuga, Chad Victor
1999-11-01
also completed. The burning velocities determined compare well to other investigators using this method. The data collected for the methane/ethylene mixture was used to evaluate mixing rules for the flammability limits, maximum combustion pressure, deflagration index, and burning velocity. These rules attempt to predict the behavior of fuel mixtures from pure component data. Le Chatelier's law and averaging both work well for predicting the flammability boundary in the fuel lean region and for mixtures of inerted fuel and air. Both methods underestimate the flammability boundary in the fuel rich region. For a mixture of methane and ethylene, we were unable to identify mixing rules for estimating the maximum combustion pressure and the burning velocity from pure component data. Averaging the deflagration indices for fuel air mixtures did provide a adequate estimation of the mixture behavior. Le Chatelier's method overestimated the maximum deflagration index in air but provided a satisfactory estimation in the extreme fuel lean and rich regions.
Directory of Open Access Journals (Sweden)
Lentka Łukasz
2015-09-01
Full Text Available This paper analyses the effectiveness of determining gas concentrations by using a prototype WO3 resistive gas sensor together with fluctuation enhanced sensing. We have earlier demonstrated that this method can determine the composition of a gas mixture by using only a single sensor. In the present study, we apply Least-Squares Support-Vector-Machine-based (LS-SVM-based nonlinear regression to determine the gas concentration of each constituent in a mixture. We confirmed that the accuracy of the estimated gas concentration could be significantly improved by applying temperature change and ultraviolet irradiation of the WO3 layer. Fluctuation-enhanced sensing allowed us to predict the concentration of both component gases.
Two-component mixture model: Application to palm oil and exchange rate
Phoong, Seuk-Yen; Ismail, Mohd Tahir; Hamzah, Firdaus Mohamad
2014-12-01
Palm oil is a seed crop which is widely adopt for food and non-food products such as cookie, vegetable oil, cosmetics, household products and others. Palm oil is majority growth in Malaysia and Indonesia. However, the demand for palm oil is getting growth and rapidly running out over the years. This phenomenal cause illegal logging of trees and destroy the natural habitat. Hence, the present paper investigates the relationship between exchange rate and palm oil price in Malaysia by using Maximum Likelihood Estimation via Newton-Raphson algorithm to fit a two components mixture model. Besides, this paper proposes a mixture of normal distribution to accommodate with asymmetry characteristics and platykurtic time series data.
Probability theory for number of mixture components resolved by n independent columns.
Davis, Joe M; Blumberg, Leonid M
2005-11-25
A general theory is proposed for the probability of different outcomes of success and failure of component resolution, when complex mixtures are partially separated by n independent columns. Such a separation is called an n-column separation. An outcome of particular interest is component resolution by at least one column. Its probability is identified with the probability of component resolution by a single column, thereby defining the effective saturation of the n-column separation. Several trends are deduced from limiting expressions of the effective saturation. In particular, at low saturation the probability that components cluster together as unresolved peaks decreases exponentially with the number of columns, and the probability that components cluster together on addition of another column decreases by a factor equal to twice the column saturation. The probabilities of component resolution by n-column and two-dimensional separations also are compared. The theory is applied by interpreting three sets of previously reported retention indices of the 209 polychlorinated biphenyls (PCBs), as determined by GC. The origin of column independence is investigated from two perspectives. First, it is suggested that independence exists when the difference between indices of the same compound on two columns is much larger than the interval between indices required for separation. Second, it is suggested that independence exists when the smaller of the two intervals between a compound and its adjacent neighbors is not correlated with its counterpart on another column.
Continuous fractionation of a two-component mixture by zone electrophoresis.
Zalewski, Dawid R; Gardeniers, Han J G E
2009-12-01
Synchronized continuous-flow zone electrophoresis is a recently demonstrated tool for performing electrophoretic fractionation of a complex sample. The method resembles free flow electrophoresis, but unlike in that technique, no mechanical fluid pumping is required. Instead, fast electrokinetic flow switching is used to produce complex stream patterns, which results in lateral separation of components in a separation chamber. Here a solution is presented which allows for simultaneous collection of two fractions in synchronized continuous-flow zone electrophoresis. The method is demonstrated on a model mixture, with subsequent evaluation of the collected fractions purity by MCE. The necessary theoretical background is provided including both steering schemes and calculations of optimum operating points.
DEFF Research Database (Denmark)
Bellotti, Filipe Furlan; Salami Dehkharghani, Amin; Zinner, Nikolaj Thomas
2017-01-01
We investigate one-dimensional harmonically trapped two-component systems for repulsive interaction strengths ranging from the non-interacting to the strongly interacting regime for Fermi-Fermi mixtures. A new and powerful mapping between the interaction strength parameters from a continuous......) and exact diagonalization) and analytically. Since DMRG results do not converge as the interaction strength is increased, analytical solutions are used as a benchmark to identify the point where these calculations become unstable. We use the proposed mapping to set a quantitative limit on the interaction...
Directory of Open Access Journals (Sweden)
Katherine M O'Donnell
Full Text Available Detectability of individual animals is highly variable and nearly always < 1; imperfect detection must be accounted for to reliably estimate population sizes and trends. Hierarchical models can simultaneously estimate abundance and effective detection probability, but there are several different mechanisms that cause variation in detectability. Neglecting temporary emigration can lead to biased population estimates because availability and conditional detection probability are confounded. In this study, we extend previous hierarchical binomial mixture models to account for multiple sources of variation in detectability. The state process of the hierarchical model describes ecological mechanisms that generate spatial and temporal patterns in abundance, while the observation model accounts for the imperfect nature of counting individuals due to temporary emigration and false absences. We illustrate our model's potential advantages, including the allowance of temporary emigration between sampling periods, with a case study of southern red-backed salamanders Plethodon serratus. We fit our model and a standard binomial mixture model to counts of terrestrial salamanders surveyed at 40 sites during 3-5 surveys each spring and fall 2010-2012. Our models generated similar parameter estimates to standard binomial mixture models. Aspect was the best predictor of salamander abundance in our case study; abundance increased as aspect became more northeasterly. Increased time-since-rainfall strongly decreased salamander surface activity (i.e. availability for sampling, while higher amounts of woody cover objects and rocks increased conditional detection probability (i.e. probability of capture, given an animal is exposed to sampling. By explicitly accounting for both components of detectability, we increased congruence between our statistical modeling and our ecological understanding of the system. We stress the importance of choosing survey locations and
Bellotti, Filipe F.; Dehkharghani, Amin S.; Zinner, Nikolaj T.
2017-02-01
We investigate one-dimensional harmonically trapped two-component systems for repulsive interaction strengths ranging from the non-interacting to the strongly interacting regime for Fermi-Fermi mixtures. A new and powerful mapping between the interaction strength parameters from a continuous Hamiltonian and a discrete lattice Hamiltonian is derived. As an example, we show that this mapping does not depend neither on the state of the system nor on the number of particles. Energies, density profiles and correlation functions are obtained both numerically (density matrix renormalization group (DMRG) and exact diagonalization) and analytically. Since DMRG results do not converge as the interaction strength is increased, analytical solutions are used as a benchmark to identify the point where these calculations become unstable. We use the proposed mapping to set a quantitative limit on the interaction parameter of a discrete lattice Hamiltonian above which DMRG gives unrealistic results.
ARTS: A System-Level Framework for Modeling MPSoC Components and Analysis of their Causality
DEFF Research Database (Denmark)
Mahadevan, Shankar; Storgaard, Michael; Madsen, Jan;
2005-01-01
the MPSoC designers in modeling the different layers and understanding their causalities. While others have developed tools for static analysis and modeled limited correlations (processor-memory or processor-communication), our model captures the impact of dynamic and unpredictable OS behaviour...
Zeliger, Harold I
2011-01-01
In this important reference work, Zeliger catalogs the known effects of chemical mixtures on the human body and also proposes a framework for understanding and predicting their actions in terms of lipophile (fat soluble)/hydrophile (water soluble) interactions. The author's focus is on illnesses that ensue following exposures to mixtures of chemicals that cannot be attributed to any one component of the mixture. In the first part the mechanisms of chemical absorption at a molecular and macromolecular level are explained, as well as the body's methods of defending itself against xenobiotic intrusion. Part II examines the sources of the chemicals discussed, looking at air and water pollution, food additives, pharmaceuticals, etc. Part III, which includes numerous case studies, examines specific effects of particular mixtures on particular body systems and organs and presents a theoretical framework for predicting what the effects of uncharacterized mixtures might be. Part IV covers regulatory requirements and t...
Energy Technology Data Exchange (ETDEWEB)
Piepel, Gregory F.(BATTELLE (PACIFIC NW LAB)); Cooley, Scott K.(BATTELLE (PACIFIC NW LAB)); Peeler, David K.(Savannah River Technology Center); Vienna, John D.(BATTELLE (PACIFIC NW LAB)); Edwards, Tommy B.(Savannah River Technology Center)
2002-01-01
A glass composition variation study (CVS) for high-level waste (HLW) stored in Idaho is being statistically designed and performed in phases over several years. The purpose of the CVS is to investigate and model how HLW-glass properties depend on glass composition. The resulting glass property-composition models will be used to develop desirable glass formulations and for other purposes. Phases 1 and 2 of the CVS have been completed and are briefly described. This paper focuses on the CVS Phase 3 experimental design, which was chosen to augment the Phase 1 and 2 data with additional data points, as well as to account for additional glass components not studied in Phases 1 and/or 2. In total, 16 glass components were varied in the Phase 3 experimental design. The paper describes how these Phase 3 experimental design augmentation challenges were addressed using the previous data, preliminary property-composition models, and statistical mixture experiment and optimal experimental design methods and software.
Gomez Osorio, Martin Alonso
Chemical process design requires mathematical models for predicting thermophysical properties. Those models, called equations of state (EoS), need experimental data for parameter estimation and validation. This work presents a detailed description of a vibrating tube densimeter, which is an alternative technique for measurement of p-rho-T data in gases at critical conditions. This apparatus can measure fluids in a temperature range of 300 K to 470 K and pressures up to 140 MPa. This work calibrates the vibrating tube using a physical-based methodology with nitrogen, methane and argon measurements. Carbon dioxide and ethane p-rho-T data validate calibration procedures covering a wide range in density and pressure. The vibrating tube densimeter performs density measurements for nitrogen + methane mixtures for pressures up to 140 MPa. This work also presents a new equation of state (EoS) having a rational form that can describe properties with accuracy comparable to the best multi-parametric equations with less mathematical complexity. This EoS presents the Helmholtz residual energy as a ratio of two polynomial functions in density (no exponential terms in density are included), which can describe the behavior of pure components. The EoS can be transformed to describe other thermophysical properties as pressure, compressibility factor, heat capacity and speed of sound. Also this equation can calculate saturated liquid-vapor properties with 20 times less computational time. This work presents rational EoS for nitrogen, argon and methane applicable in wide ranges of pressure and temperature. Finally, this work proposes a new mixing rule for binary mixtures of gases based upon a quadratic combination of residual Helmholtz energy. This approach divides the energy contribution between interactions of same species and interaction of different species molecules. A rational form is proposed for description of energy interaction between molecules of different species. The
McGivern, W. S.; Allison, T. C.; Radney, J. G.; Zangmeister, C. D.
2014-12-01
The aqueous reaction of methylglyoxal (MG) with ammonium sulfate has been suggested as a source of atmospheric ``brown carbon.'' We have utilized high-performance liquid chromatography coupled to ultraviolet-visible spectroscopy and tandem mass spectrometry to study the products of this reaction at high concentrations. The overall product spectrum shows a large number of distinct components; however, the visible absorption from this mixture is derived a very small number of components. The largest contributor is an imine-substituted (C=N-H) product of aldol condensation/facile dehydration reaction between the parent MG and a hydrated product of the MG + ammonia reaction. The asymmetric nature of this compound relative to the aldol condensation of two MG results in a sufficiently large redshift of the UV absorption spectrum that absorption of visible radiation can occur in the long-wavelength tail. The simplicity of the imine products is a result of a strong bias toward ketimine products due to the extensive hydration of the aldehydic moiety in the parent in aqueous solution. In addition, a strong pH dependence of the absorption cross section was observed with significantly greater absorption under more basic conditions. We have performed time-dependent density functional theory calculations to evaluate the absorption spectra of all of the possible condensation products and their respective ions, and the results are consistent with the experimental observations. We have also observed smaller concentrations of other condensation products of the imine-substituted parent species that do not contribute significantly to the visible absorption but have not been previously discussed.
Jha, Anjani K.
Particulate materials are routinely handled in large quantities by industries such as, agriculture, electronic, ceramic, chemical, cosmetic, fertilizer, food, nutraceutical, pharmaceutical, power, and powder metallurgy. These industries encounter segregation due to the difference in physical and mechanical properties of particulates. The general goal of this research was to study percolation segregation in multi-size and multi-component particulate mixtures, especially measurement, sampling, and modeling. A second generation primary segregation shear cell (PSSC-II), an industrial vibrator, a true cubical triaxial tester, and two samplers (triers) were used as primary test apparatuses for quantifying segregation and flowability; furthermore, to understand and propose strategies to mitigate segregation in particulates. Toward this end, percolation segregation in binary, ternary, and quaternary size mixtures for two particulate types: urea (spherical) and potash (angular) were studied. Three coarse size ranges 3,350-4,000 mum (mean size = 3,675 mum), 2,800-3,350 mum (3,075 mum), and 2,360-2,800 mum (2,580 mum) and three fines size ranges 2,000-2,360 mum (2,180 mum), 1,700-2,000 mum (1,850 mum), and 1,400-1,700 mum (1,550 mum) for angular-shaped and spherical-shaped were selected for tests. Since the fines size 1,550 mum of urea was not available in sufficient quantity; therefore, it was not included in tests. Percolation segregation in fertilizer bags was tested also at two vibration frequencies of 5 Hz and 7Hz. The segregation and flowability of binary mixtures of urea under three equilibrium relative humidities (40%, 50%, and 60%) were also tested. Furthermore, solid fertilizer sampling was performed to compare samples obtained from triers of opening widths 12.7 mm and 19.1 mm and to determine size segregation in blend fertilizers. Based on experimental results, the normalized segregation rate (NSR) of binary mixtures was dependent on size ratio, mixing ratio
Heckman, James J.
2008-01-01
This paper presents the econometric approach to causal modeling. It is motivated by policy problems. New causal parameters are defined and identified to address specific policy problems. Economists embrace a scientific approach to causality and model the preferences and choices of agents to infer subjective (agent) evaluations as well as objective outcomes. Anticipated and realized subjective and objective outcomes are distinguished. Models for simultaneous causality are developed. The paper ...
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.
Directory of Open Access Journals (Sweden)
Van der Merwe, Karl Robert
2014-05-01
Full Text Available Although it is generally accepted that lean manufacturing improves operational performance, many organisations are struggling to adapt to the lean philosophy. The purpose of this study is to contribute to a more effective strategy for implementing the lean manufacturing improvement philosophy. The study sets out both to integrate well-researched findings and theories related to generic organisational culture with more recent research and experience related to lean culture, and to examine the role that culture plays in the effective implementation of lean manufacturing principles and techniques. The ultimate aim of this exercise is to develop a theoretical lean culture causal framework.
Pacot, Giselle Mae M.; Lee, Lyn May; Chin, Sung-Tong; Marriott, Philip J.
2016-01-01
Gas chromatography-mass spectrometry (GC-MS) and GC-tandem MS (GC-MS/MS) are useful in many separation and characterization procedures. GC-MS is now a common tool in industry and research, and increasingly, GC-MS/MS is applied to the measurement of trace components in complex mixtures. This report describes an upper-level undergraduate experiment…
Hong, Ban Zhen; Keong, Lau Kok; Shariff, Azmi Mohd
2016-05-01
The employment of different mathematical models to address specifically for the bubble nucleation rates of water vapour and dissolved air molecules is essential as the physics for them to form bubble nuclei is different. The available methods to calculate bubble nucleation rate in binary mixture such as density functional theory are complicated to be coupled along with computational fluid dynamics (CFD) approach. In addition, effect of dissolved gas concentration was neglected in most study for the prediction of bubble nucleation rates. The most probable bubble nucleation rate for the water vapour and dissolved air mixture in a 2D quasi-stable flow across a cavitating nozzle in current work was estimated via the statistical mean of all possible bubble nucleation rates of the mixture (different mole fractions of water vapour and dissolved air) and the corresponding number of molecules in critical cluster. Theoretically, the bubble nucleation rate is greatly dependent on components' mole fraction in a critical cluster. Hence, the dissolved gas concentration effect was included in current work. Besides, the possible bubble nucleation rates were predicted based on the calculated number of molecules required to form a critical cluster. The estimation of components' mole fraction in critical cluster for water vapour and dissolved air mixture was obtained by coupling the enhanced classical nucleation theory and CFD approach. In addition, the distribution of bubble nuclei of water vapour and dissolved air mixture could be predicted via the utilisation of population balance model.
K-causality coincides with stable causality
Minguzzi, E
2008-01-01
It is proven that K-causality coincides with stable causality, and that in a K-causal spacetime the relation K^+ coincides with the Seifert's relation. As a consequence the causal relation "the spacetime is strongly causal and the closure of the causal relation is transitive" stays between stable causality and causal continuity.
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.
Energy Technology Data Exchange (ETDEWEB)
Hirota, Noriyuki, E-mail: hirota.noriyuki@nims.go.jp [Fine Particle Engineering Group, National Institute for Materials Science, 3-13 Sakura, Tsukuba (Japan); Chiba, Hayatoshi [Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa (Japan); Okada, Hidehiko [Fine Particle Engineering Group, National Institute for Materials Science, 3-13 Sakura, Tsukuba (Japan); Ando, Tsutomu [Department of Mechanical Engineering, Nihon University, 1-2-1 Izumicho, Narashino 275-8575 (Japan)
2015-04-15
The magneto-Archimedes separation allows for separating mixtures of feeble magnetic materials into its components based on the difference of their densities and magnetic susceptibilities. So far, this technique was applied for the separation of relatively large particles of several millimeters in diameter. Here we apply this technique experimentally to the simultaneous quantitative analysis of multiple micrometer-sized particles in a fluid. It was confirmed that the magneto-Archimedes separation can be applied for the separation of mixture of microspheres larger than 20 μm. Further high performance separation efficiency is expected with the optimization of separation conditions including the control of the spatial distribution of the magnetic field. - Highlights: • The magneto-Archimedes separation is based on the magnetic levitation of materials. • It allows for separating mixtures into its components by the difference of properties. • The separation of mixture of spheres larger than 20 μm was confirmed experimentally. • It enables the simultaneous quantitative analysis of multiple particles.
Asghari, E.; Ashassi-Sorkhabi, H.; Ahangari, M.; Bagheri, R.
2016-04-01
Factors such as inhibitor concentration, solution hydrodynamics, and temperature influence the performance of corrosion inhibitor mixtures. The simultaneous studying of the impact of different factors is a time- and cost-consuming process. The use of experimental design methods can be useful in minimizing the number of experiments and finding local optimized conditions for factors under the investigation. In the present work, the inhibition performance of a three-component inhibitor mixture against corrosion of St37 steel rotating disk electrode, RDE, was studied. The mixture was composed of citric acid, lanthanum(III) nitrate, and tetrabutylammonium perchlorate. In order to decrease the number of experiments, the L16 Taguchi orthogonal array was used. The "control factors" were the concentration of each component and the rotation rate of RDE and the "response factor" was the inhibition efficiency. The scanning electron microscopy and energy dispersive x-ray spectroscopy techniques verified the formation of islands of adsorbed citrate complexes with lanthanum ions and insoluble lanthanum(III) hydroxide. From the Taguchi analysis results the mixture of 0.50 mM lanthanum(III) nitrate, 0.50 mM citric acid, and 2.0 mM tetrabutylammonium perchlorate under the electrode rotation rate of 1000 rpm was found as optimum conditions.
Directory of Open Access Journals (Sweden)
Ghenadie Bulgac
2006-12-01
Full Text Available In this paper we find the analytical solution of simple one-dimensional unsteady elastic problem of two-component mixture using Laplace integral transformation. The integral transformations simplify the initial motion systems for finding analytical solutions. The analytical solutions are represented as the graphic on time dependence in the fixed point of medium, and the graphic on the horizontal coordinate at the fixed time.
Causal and causally separable processes
Oreshkov, Ognyan; Giarmatzi, Christina
2016-09-01
The idea that events are equipped with a partial causal order is central to our understanding of physics in the tested regimes: given two pointlike events A and B, either A is in the causal past of B, B is in the causal past of A, or A and B are space-like separated. Operationally, the meaning of these order relations corresponds to constraints on the possible correlations between experiments performed in the vicinities of the respective events: if A is in the causal past of B, an experimenter at A could signal to an experimenter at B but not the other way around, while if A and B are space-like separated, no signaling is possible in either direction. In the context of a concrete physical theory, the correlations compatible with a given causal configuration may obey further constraints. For instance, space-like correlations in quantum mechanics arise from local measurements on joint quantum states, while time-like correlations are established via quantum channels. Similarly to other variables, however, the causal order of a set of events could be random, and little is understood about the constraints that causality implies in this case. A main difficulty concerns the fact that the order of events can now generally depend on the operations performed at the locations of these events, since, for instance, an operation at A could influence the order in which B and C occur in A’s future. So far, no formal theory of causality compatible with such dynamical causal order has been developed. Apart from being of fundamental interest in the context of inferring causal relations, such a theory is imperative for understanding recent suggestions that the causal order of events in quantum mechanics can be indefinite. Here, we develop such a theory in the general multipartite case. Starting from a background-independent definition of causality, we derive an iteratively formulated canonical decomposition of multipartite causal correlations. For a fixed number of settings and
Energy Technology Data Exchange (ETDEWEB)
Piepel, Gregory F.
2007-12-01
A mixture experiment involves combining two or more components in various proportions or amounts and then measuring one or more responses for the resulting end products. Other factors that affect the response(s), such as process variables and/or the total amount of the mixture, may also be studied in the experiment. A mixture experiment design specifies the combinations of mixture components and other experimental factors (if any) to be studied and the response variable(s) to be measured. Mixture experiment data analyses are then used to achieve the desired goals, which may include (i) understanding the effects of components and other factors on the response(s), (ii) identifying components and other factors with significant and nonsignificant effects on the response(s), (iii) developing models for predicting the response(s) as functions of the mixture components and any other factors, and (iv) developing end-products with desired values and uncertainties of the response(s). Given a mixture experiment problem, a practitioner must consider the possible approaches for designing the experiment and analyzing the data, and then select the approach best suited to the problem. Eight possible approaches include 1) component proportions, 2) mathematically independent variables, 3) slack variable, 4) mixture amount, 5) component amounts, 6) mixture process variable, 7) mixture of mixtures, and 8) multi-factor mixture. The article provides an overview of the mixture experiment designs, models, and data analyses for these approaches.
DEFF Research Database (Denmark)
Fettouhi, André; Thomsen, Kaj
2010-01-01
In the creation of liquefied natural gas the formation of solids play a substantial role, hence detailed knowledge is needed about solid-liquid equilibria (SLE). In this abstract we shortly summarize the work we have carried out at CERE over the past year with SLE for many-component mixtures using...... the Cubic-Plus-Association (CPA) equation of state. Components used in this work are highly relevant to the oil and gas industry and include light and heavy hydrocarbons, alcohols, water and carbon dioxide....
DEFF Research Database (Denmark)
Rasmussen, Lauge Baungaard
2006-01-01
The lecture note explains how to use the causal mapping method as well as the theoretical framework aoosciated to the method......The lecture note explains how to use the causal mapping method as well as the theoretical framework aoosciated to the method...
Energy Technology Data Exchange (ETDEWEB)
Patel, Sanjay V.; Jenkins, Mark W.; Hughes, Robert C.; Yelton, W. Graham; Ricco, Antonio J.
1999-07-19
We demonstrate a ''universal solvent sensor'' constructed from a small array of carbon/polymer composite chemiresistors that respond to solvents spanning a wide range of Hildebrand volubility parameters. Conductive carbon particles provide electrical continuity in these composite films. When the polymer matrix absorbs solvent vapors, the composite film swells, the average separation between carbon particles increases, and an increase in film resistance results, as some of the conduction pathways are broken. The adverse effects of contact resistance at high solvent concentrations are reported. Solvent vapors including isooctane, ethanol, dlisopropyhnethylphosphonate (DIMP), and water are correctly identified (''classified'') using three chemiresistors, their composite coatings chosen to span the full range of volubility parameters. With the same three sensors, binary mixtures of solvent vapor and water vapor are correctly classified, following classification, two sensors suffice to determine the concentrations of both vapor components. Polyethylene vinylacetate and polyvinyl alcohol (PVA) are two such polymers that are used to classify binary mixtures of DIMP with water vapor; the PVA/carbon-particle-composite films are sensitive to less than 0.25{degree}A relative humidity. The Sandia-developed VERI (Visual-Empirical Region of Influence) technique is used as a method of pattern recognition to classify the solvents and mixtures and to distinguish them from water vapor. In many cases, the response of a given composite sensing film to a binary mixture deviates significantly from the sum of the responses to the isolated vapor components at the same concentrations. While these nonlinearities pose significant difficulty for (primarily) linear methods such as principal components analysis, VERI handles both linear and nonlinear data with equal ease. In the present study the maximum speciation accuracy is achieved by an array
Heck, W. W.
1980-01-01
The possible biologic effects of exhaust products from solid rocket motor (SRM) burns associated with the space shuttle are examined. The major components of the exhaust that might have an adverse effect on vegetation, HCl and Al2O3 are studied. Dose response curves for native and cultivated plants and selected insects exposed to simulated exhaust and component chemicals from SRM exhaust are presented. A system for dispensing and monitoring component chemicals of SRM exhaust (HCl and Al2O3) and a system for exposing test plants to simulated SRM exhaust (controlled fuel burns) are described. The effects of HCl, Al2O3, and mixtures of the two on the honeybee, the corn earworm, and the common lacewing and the effects of simulated exhaust on the honeybee are discussed.
Isotropic-nematic phase equilibria of hard-sphere chain fluids-Pure components and binary mixtures.
Oyarzún, Bernardo; van Westen, Thijs; Vlugt, Thijs J H
2015-02-14
The isotropic-nematic phase equilibria of linear hard-sphere chains and binary mixtures of them are obtained from Monte Carlo simulations. In addition, the infinite dilution solubility of hard spheres in the coexisting isotropic and nematic phases is determined. Phase equilibria calculations are performed in an expanded formulation of the Gibbs ensemble. This method allows us to carry out an extensive simulation study on the phase equilibria of pure linear chains with a length of 7 to 20 beads (7-mer to 20-mer), and binary mixtures of an 8-mer with a 14-, a 16-, and a 19-mer. The effect of molecular flexibility on the isotropic-nematic phase equilibria is assessed on the 8-mer+19-mer mixture by allowing one and two fully flexible beads at the end of the longest molecule. Results for binary mixtures are compared with the theoretical predictions of van Westen et al. [J. Chem. Phys. 140, 034504 (2014)]. Excellent agreement between theory and simulations is observed. The infinite dilution solubility of hard spheres in the hard-sphere fluids is obtained by the Widom test-particle insertion method. As in our previous work, on pure linear hard-sphere chains [B. Oyarzún, T. van Westen, and T. J. H. Vlugt, J. Chem. Phys. 138, 204905 (2013)], a linear relationship between relative infinite dilution solubility (relative to that of hard spheres in a hard-sphere fluid) and packing fraction is found. It is observed that binary mixtures greatly increase the solubility difference between coexisting isotropic and nematic phases compared to pure components.
Ishanu Chattopadhyay
2014-01-01
While correlation measures are used to discern statistical relationships between observed variables in almost all branches of data-driven scientific inquiry, what we are really interested in is the existence of causal dependence. Designing an efficient causality test, that may be carried out in the absence of restrictive pre-suppositions on the underlying dynamical structure of the data at hand, is non-trivial. Nevertheless, ability to computationally infer statistical prima facie evidence of...
Maltsev, Roman V
2013-01-01
A new approach to simulation of stationary flows by Direct Simulation Monte Carlo method is proposed. The idea is to specify an individual time step for each component of a gas mixture. The approach consists of modifications mainly to collision phase and recommendation on choosing time step ratios. It allows softening the demands on the computational resources for cases of disparate collision diameters of molecules and/or disparate molecular masses. These are the cases important in vacuum deposition technologies. Few tests of the new approach are made. Finally, the usage of new approach is demonstrated on a problem of silver nanocluster diffusion in carrier gas argon in conditions of silver deposition experiments.
Pucci, G N; Pucci, O H
2003-01-01
The complex composition of the crude oil and the hydrocarbons that integrate the waste of the different stages of the oil industry turn this product a mixture that presents different difficulties for its elimination by biological methods. The objective of this paper was to study the biodegradation potential of autochthonous bacterial communities on hydrocarbons obtained from four polluted places and subjected to landfarming biorremediation system during a decade. The results showed a marked difference in biodegradability of the three main fractions of crude oil, aliphatic, aromatic, and polar fractions, obtained by column chromatography. All fractions were used as carbon source and energy. There were variations in the production of biomass among the different fractions as well as in the kinetics of biodegradation, according to the composition of each fraction.
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.
Wilde, Marcelo L; Schneider, Mandy; Kümmerer, Klaus
2017-04-01
Pharmaceuticals do not occur isolated in the environment but in multi-component mixtures and may exhibit antagonist, synergistic or additive behavior. Knowledge on this is still scarce. The situation is even more complicated if effluents or potable water is treated by oxidative processes or such transformations occur in the environment. Thus, determining the fate and effects of parent compounds, metabolites and transformation products (TPs) formed by transformation and degradation processes in the environment is needed. This study investigated the fate and preliminary ecotoxicity of the phenothiazine pharmaceuticals, Promazine (PRO), Promethazine (PRM), Chlorpromazine (CPR), and Thioridazine (THI) as single and as components of the resulting mixtures obtained from their treatment by Fenton process. The Fenton process was carried out at pH7 and by using 0.5-2mgL(-1) of [Fe(2+)]0 and 1-12.5mgL(-1) of [H2O2]0 at the fixed ratio [Fe(2+)]0:[H2O2]0 of 1:10 (w:w). No complete mineralization was achieved. Constitutional isomers and some metabolite-like TPs formed were suggested based on their UHPLC-HRMS(n) data. A degradation pathway was proposed considering interconnected mechanisms such as sulfoxidation, hydroxylation, N-dealkylation, and dechlorination steps. Aerobic biodegradation tests (OECD 301 D and OECD 301 F) were applied to the parent compounds separately, to the mixture of parent compounds, and for the cocktail of TPs present after the treatment by Fenton process. The samples were not readily biodegradable. However, LC-MS analysis revealed that abiotic transformations, such hydrolysis, and autocatalytic transformations occurred. The initial ecotoxicity tested towards Vibrio fischeri as individual compounds featured a reduction in toxicity of PRM and CPR by the treatment process, whereas PRO showed an increase in acute luminescence inhibition and THI a stable luminescence inhibition. Concerning effects of the mixture components, reduction in toxicity by the
Malaska, M.; Radebaugh, J.; Barnes, J.; Mitchell, K.
2012-03-01
A multi-component mixture of organic compounds in heptanes was evaporated to simulate the formation of an evaporite playa on Titan. The deposition sequence of the analog materials and their implications for Titan geology will be presented.
Adaptive blind separation of underdetermined mixtures based on sparse component analysis
Institute of Scientific and Technical Information of China (English)
YANG ZuYuan; HE ZhaoShui; XIE ShengLi; FU YuLi
2008-01-01
The independence priori is very often used in the conventional blind source sepa-ration (BSS). Naturally, independent component analysis (ICA) is also employed to perform BSS very often. However, ICA is difficult to use in some challenging cases, such as underdetermined BSS or blind separation of dependent sources. Recently, sparse component analysis (SCA) has attained much attention because it is theo-retically available for underdetermined BSS and even for blind dependent source separation sometimes. However, SCA has not been developed very sufficiently. Up to now, there are only few existing algorithms and they are also not perfect as well in practice. For example, although Lewicki-Sejnowski's natural gradient for SCA is superior to K-mean clustering, it is just an approximation without rigorously theo-retical basis. To overcome these problems, a new natural gradient formula is pro-posed in this paper. This formula is derived directly from the cost function of SCA through matrix theory. Mathematically, it is more rigorous. In addition, a new and robust adaptive BSS algorithm is developed based on the new natural gradient. Simulations illustrate that this natural gradient formula is more robust and reliable than Lewicki-Sejnowski's gradient.
Chi, Do Minh
2001-01-01
We advance a famous principle - causality principle - but under a new view. This principle is a principium automatically leading to most fundamental laws of the nature. It is the inner origin of variation, rules evolutionary processes of things, and the answer of the quest for ultimate theories of the Universe.
Zhang, Hui; Wang, Shao-Qing; Liu, Ying; Luo, Li-Ping; Liu, Peng; Qi, Lian-Wen; Li, Ping
2012-11-01
Trace constituents are widely present in complex mixtures, and trace analysis is challenging because of the unpredictable matrix. In this work, a high-component filtering strategy was developed for improved analysis of trace constituents in complex sample by liquid chromatography-mass spectrometry (LC-MS). Using a specifically designed chromatographic apparatus, the high-abundant fractions were filtered prior to LC-MS analysis. The samples complexity was reduced and the sample-loading amount for the rest low-level fractions can be considerably increased. The application of this approach was illustrated with an analytically challenging sample, a traditional Chinese herbal medicine named Compound Danshen Sample. We observed that the loss rate for 12 analytes during the filtering procedure ranged from 6.54 to 26.11%, but showed a stable repeatability with RSDanalysis, allowing six low compounds that cannot be quantified by the traditional methods to be tested by the filtering method. It can be predicted that the qualitative and quantitative trace analysis will be greatly improved when the loading samples is increased resulting from the filtration of high-level targets. The proposed strategy is promising to monitor trace constituents in diverse complex mixtures in the analytical field of pharmaceutics, metabonomics and environments.
Institute of Scientific and Technical Information of China (English)
Wang Liguo; Cheng Yuanping; Li Wei; Lu Shouqing; Xu Chao
2013-01-01
Adsorption-desorption experiments on CO2-CH4 gas mixtures with varying compositions have been conducted to study the fractionation characteristics of CO2-CH4 on Haishiwan coal samples.These were carried out at constant temperature but different equilibrium pressure conditions.Based on these experimental results,the temporal evolution of component fractionation in the field was investigated.The results show that the CO2 concentration in the adsorbed phase is always greater than that in the original gas mixture during the desorption process,while CH4 shows the opposite characteristics.This has confirmed that CO2,with a greater adsorption ability has a predominant position in the competition with CH4 under different pressures.Where gas drainage is employed,the ratio of CO2 to CH4 varies with time and space in floor roadways used for gas drainage,and in the ventilation air in Nos.1 and 2 coal seams,which is consistent with laboratory results.
Carmona, M D; Llorach, R; Obon, C; Rivera, D
2005-12-01
In Unani system of medicine, drugs consist of complex formulae with more than three components, for which, literature analysing these mixtures as they are sold in the market is scarce. In this paper, the main botanical components of the herbal tea known as "Zahraa" in Damascus, which contains between 6 and 14 species components is elucidated: Alcea damascena (Mout.) Mout. (Malvaceae), Aloysia triphylla (L'Herit.) Britt. (Malvaceae), Astragalus cf. amalecitanus Boiss., Cercis siliquastrum L. subsp. hebecarpa (Bornm.) Yalt. and subsp. siliquastrum. (Leguminosae), Colutea cilicica Boiss. et Bal. in Boiss. (Leguminosae), Crataegus aronia (L.) Bosc. ex DC. (Rosaceae), Cytisopsis pseudocytisus (Boiss.) Fertig. (Leguminosae), Eleagnus angustifolia L. (Eleagnaceae), Equisetum telmateia Ehrh. (Equisetaceae), Helichrysum stoechas (L.) Moench. subsp. barrelieri (Ten.) Nyman. (Compositae), Matricaria recutita L. (Compositae), Mentha longifolia L. subsp. noeana (Boiss. ex. Briq.) Briq. (Labiatae), Mentha spicata L. subsp. condensata (Briq.) Greuter and Burdet (Labiatae), Micromeria myrtifolia Boiss. and Hohen. in Boiss. (Labiatae), Paronychia argentea Lam. (Caryophyllaceae), Phlomis syriaca Boiss. (Labiatae), Rosa damascena Mill. (Rosaceae), Salvia fruticosa Mill. (Labiatae), Sambucus nigra L. (Caprifoliaceae), Spartium junceum L. (Leguminosae), Zea mays L. (Gramineae).
Evaporation of multi-component mixtures and shell formation in spray dried droplets
Valente, Pedro; Duarte, Íris; Porfirio, Tiago; Temtem, Márcio
2015-11-01
Drug particles where the active pharmaceutical ingredient (APIs) is dispersed in a polymer matrix forming an amorphous solid dispersion (ASD) is a commonly used strategy to increase the solubility and dissolution rate of poorly water soluble APIs. However, the formation and stability of an amorphous solid dispersion depends on the polymer/API combination and process conditions to generate it. The focus of the present work is to further develop a numerical tool to predict the formation of ASDs by spray drying solutions of different polymer/API combinations. Specifically, the evaporation of a multi-component droplet is coupled with a diffusion law within the droplet that minimizes the Gibbs free energy of the polymer/API/solvents system, following the Flory-Huggins model. Prior to the shell formation, the evaporation of the solvents is modelled following the simplified approach proposed by Abramzon & Sirignano (1989) which accounts for the varying relative velocity between the droplet and the drying gas. After shell formation, the diffusion of the solvents across the porous shell starkly modifies the evaporative dynamics.
O'Connell, Marie-Louise; Howley, Tom; Ryder, Alan G.; Leger, Marc N.; Madden, Michael G.
2005-06-01
The quantitative analysis of illicit materials using Raman spectroscopy is of widespread interest for law enforcement and healthcare applications. One of the difficulties faced when analysing illicit mixtures is the fact that the narcotic can be mixed with many different cutting agents. This obviously complicates the development of quantitative analytical methods. In this work we demonstrate some preliminary efforts to try and account for the wide variety of potential cutting agents, by discrimination between the target substance and a wide range of excipients. Near-infrared Raman spectroscopy (785 nm excitation) was employed to analyse 217 samples, a number of them consisting of a target analyte (acetaminophen) mixed with excipients of different concentrations by weight. The excipients used were sugars (maltose, glucose, lactose, sorbitol), inorganic materials (talcum powder, sodium bicarbonate, magnesium sulphate), and food products (caffeine, flour). The spectral data collected was subjected to a number of pre-treatment statistical methods including first derivative and normalisation transformations, to make the data more suitable for analysis. Various methods were then used to discriminate the target analytes, these included Principal Component Analysis (PCA), Principal Component Regression (PCR) and Support Vector Machines.
Directory of Open Access Journals (Sweden)
G. David
2013-07-01
Full Text Available During transport by advection, atmospheric nonspherical particles, such as volcanic ash, desert dust or sea-salt particles experience several chemical and physical processes, leading to a complex vertical atmospheric layering at remote sites where intrusion episodes occur. In this paper, a new methodology is proposed to analyse this complex vertical layering in the case of a two/three-component particle external mixtures. This methodology relies on an analysis of the spectral and polarization properties of the light backscattered by atmospheric particles. It is based on combining a sensitive and accurate UV-VIS polarization lidar experiment with T-matrix numerical simulations and air mass back trajectories. The Lyon UV-VIS polarization lidar is used to efficiently partition the particle mixture into its nonspherical components, while the T-matrix method is used for simulating the backscattering and depolarization properties of nonspherical volcanic ash, desert dust and sea-salt particles. It is shown that the particle mixtures' depolarization ratio δ p differs from the nonspherical particles' depolarization ratio δns due to the presence of spherical particles in the mixture. Hence, after identifying a tracer for nonspherical particles, particle backscattering coefficients specific to each nonspherical component can be retrieved in a two-component external mixture. For three-component mixtures, the spectral properties of light must in addition be exploited by using a dual-wavelength polarization lidar. Hence, for the first time, in a three-component external mixture, the nonsphericity of each particle is taken into account in a so-called 2β + 2δ formalism. Applications of this new methodology are then demonstrated in two case studies carried out in Lyon, France, related to the mixing of Eyjafjallajökull volcanic ash with sulfate particles (case of a two-component mixture and to the mixing of dust with sea-salt and water-soluble particles
Energy Technology Data Exchange (ETDEWEB)
Ryu, Sang Kyu [Division of Chemical Engineering and Molecular Thermodynamics Laboratory, Hanyang University, Seoul 133-791 (Korea, Republic of); Bae, Young Chan, E-mail: ycbae@hanyang.ac.kr [Division of Chemical Engineering and Molecular Thermodynamics Laboratory, Hanyang University, Seoul 133-791 (Korea, Republic of)
2012-05-25
Highlights: Black-Right-Pointing-Pointer We have developed a close-packed lattice model for chain-like molecules. Black-Right-Pointing-Pointer The chain length dependence determined from Monte-Carlo simulation results were used. Black-Right-Pointing-Pointer To consider the volume effect, hole theory and two mixing steps were used. Black-Right-Pointing-Pointer A lattice fluid equation of state (LF-EoS) is presented for VLE of hydrocarbon mixtures. Black-Right-Pointing-Pointer Correlation of pure polymer solutions data with use of the LF-EoS. - Abstract: In our previous work, a new close-packed lattice model was developed for multi-component system of chain fluids with taking the chain length dependence from Monte-Carlo (MC) simulation results into account. In this work, we further extend this model to describe pressure, volume and temperature (PVT) properties, such as vapor-liquid equilibrium (VLE). To consider the effect of pressure on the phase behavior, the volume change effect is taken into account by introducing holes into the incompressible lattice model with two mixing steps. The corresponding new lattice fluid equation of state (LF-EoS) is applied to predict the thermodynamic properties of pure and binary mixtures of hydrocarbons as well as pure polymer solutions. The results of the proposed model are compared to other predictive approaches based on VLE calculations using predetermined pure model parameters without further adjustment. Thermodynamic properties predicted using the method developed in this work are consistent with the experimental data.
Johnson, Nicholas S.; Tix, John A.; Hlina, Benjamin L.; Wagner, C. Michael; Siefkes, Michael J.; Wang, Huiyong; Li, Weiming
2015-01-01
Spermiating male sea lamprey (Petromyzon marinus) release a sex pheromone, of which a component, 7α, 12α, 24-trihydoxy-3-one-5α-cholan-24-sulfate (3kPZS), has been identified and shown to induce long distance preference responses in ovulated females. However, other pheromone components exist, and when 3kPZS alone was used to control invasive sea lamprey populations in the Laurentian Great Lakes, trap catch increase was significant, but gains were generally marginal. We hypothesized that free-ranging sea lamprey populations discriminate between a partial and complete pheromone while migrating to spawning grounds and searching for mates at spawning grounds. As a means to test our hypothesis, and to test two possible uses of sex pheromones for sea lamprey control, we asked whether the full sex pheromone mixture released by males (spermiating male washings; SMW) is more effective than 3kPZS in capturing animals in traditional traps (1) en route to spawning grounds and (2) at spawning grounds. At locations where traps target sea lampreys en route to spawning grounds, SMW-baited traps captured significantly more sea lampreys than paired 3kPZS-baited traps (~10 % increase). At spawning grounds, no difference in trap catch was observed between 3kPZS and SMW-baited traps. The lack of an observed difference at spawning grounds may be attributed to increased pheromone competition and possible involvement of other sensory modalities to locate mates. Because fishes often rely on multiple and sometimes redundant sensory modalities for critical life history events, the addition of sex pheromones to traditionally used traps is not likely to work in all circumstances. In the case of the sea lamprey, sex pheromone application may increase catch when applied to specifically designed traps deployed in streams with low adult density and limited spawning habitat.
Rabolt, John F.; Tsao, Mei-Wei; Hoffmann, Catherine L.; Johnson, Harry E.; Castner, David G.; Ringsdorf, Helmut
1997-03-01
The structure, orientation and morphology of self-assembled monolayers of a semifluorinated n-alkythiol, F(CF_2)8 (CH_2)_11 SH (F8H11SH), have been investigated by polarized IR, angular dependent XPS, time-of-flight SIMS, contact angle and ellipsometric measurements. The orientation of the all trans hydrocarbon segment was found to be tilted much less from the surface normal than the 30 degree tilt found for octadecylthiol. This has been attributed to the steric constraints imposed by the larger cross section fluorocarbon helices which subsequently are tilted from the surface normal. In addition, studies of dual component mixtures of F8H11SH/F8SH and F8SH/F8H2SH have revealed that competitive adsorption occurs in the former producing monolayers which are deficient in the shorter F8SH molecules while in the latter equal representation of both F8SH and F8H2SH molecules are found on the surface due to their similar molecular lengths. These well-defined surfaces were investigated as alignment media for liquid crystals and a number of these templates have shown homeotropic and degenerate planar alignment of adjacent liquid crystal layers. The morphology of these surface layer is found to be very important in controlling the liquid crystal alignment.
Kou, Jisheng
2015-08-01
Surface tension significantly impacts subsurface flow and transport, and it is the main cause of capillary effect, a major immiscible two-phase flow mechanism for systems with a strong wettability preference. In this paper, we consider the numerical simulation of the surface tension of multi-component mixtures with the gradient theory of fluid interfaces. Major numerical challenges include that the system of the Euler-Lagrange equations is solved on the infinite interval and the coefficient matrix is not positive definite. We construct a linear transformation to reduce the Euler-Lagrange equations, and naturally introduce a path function, which is proven to be a monotonic function of the spatial coordinate variable. By using the linear transformation and the path function, we overcome the above difficulties and develop the efficient methods for calculating the interface and its interior compositions. Moreover, the computation of the surface tension is also simplified. The proposed methods do not need to solve the differential equation system, and they are easy to be implemented in practical applications. Numerical examples are tested to verify the efficiency of the proposed methods. © 2014 Elsevier B.V.
Causality constraints on TMD PDF
Efremov, A V
2013-01-01
In this short note, we discuss constraints on the transverse momentum dependent factorization formulae coming from the causality properties for the hadronic tensor. We show that the range of definition of the TMD PDFs in the transverse coordinate plane is wider that it is allowed by the causality. It indicates the presents of the large compensating corrections for the TMD PDF factorization theorem and/or overestimation of the transverse component dependence of TMD PDF.
Podlaski, Rafał; Roesch, Francis A
2014-03-01
In recent years finite-mixture models have been employed to approximate and model empirical diameter at breast height (DBH) distributions. We used two-component mixtures of either the Weibull distribution or the gamma distribution for describing the DBH distributions of mixed-species, two-cohort forest stands, to analyse the relationships between the DBH components, age cohorts and dominant species, and to assess the significance of differences between the mixture distributions and the kernel density estimates. The data consisted of plots from the Świętokrzyski National Park (Central Poland) and areas close to and including the North Carolina section of the Great Smoky Mountains National Park (USA; southern Appalachians). The fit of the mixture Weibull model to empirical DBH distributions had a precision similar to that of the mixture gamma model, slightly less accurate estimate was obtained with the kernel density estimator. Generally, in the two-cohort, two-storied, multi-species stands in the southern Appalachians, the two-component DBH structure was associated with age cohort and dominant species. The 1st DBH component of the mixture model was associated with the 1st dominant species sp1 occurred in young age cohort (e.g., sweetgum, eastern hemlock); and to a lesser degree, the 2nd DBH component was associated with the 2nd dominant species sp2 occurred in old age cohort (e.g., loblolly pine, red maple). In two-cohort, partly multilayered, stands in the Świętokrzyski National Park, the DBH structure was usually associated with only age cohorts (two dominant species often occurred in both young and old age cohorts). When empirical DBH distributions representing stands of complex structure are approximated using mixture models, the convergence of the estimation process is often significantly dependent on the starting strategies. Depending on the number of DBHs measured, three methods for choosing the initial values are recommended: min.k/max.k, 0.5/1.5/mean
Directory of Open Access Journals (Sweden)
Kopriva Ivica
2011-12-01
Full Text Available Abstract Background Bioinformatics data analysis is often using linear mixture model representing samples as additive mixture of components. Properly constrained blind matrix factorization methods extract those components using mixture samples only. However, automatic selection of extracted components to be retained for classification analysis remains an open issue. Results The method proposed here is applied to well-studied protein and genomic datasets of ovarian, prostate and colon cancers to extract components for disease prediction. It achieves average sensitivities of: 96.2 (sd = 2.7%, 97.6% (sd = 2.8% and 90.8% (sd = 5.5% and average specificities of: 93.6% (sd = 4.1%, 99% (sd = 2.2% and 79.4% (sd = 9.8% in 100 independent two-fold cross-validations. Conclusions We propose an additive mixture model of a sample for feature extraction using, in principle, sparseness constrained factorization on a sample-by-sample basis. As opposed to that, existing methods factorize complete dataset simultaneously. The sample model is composed of a reference sample representing control and/or case (disease groups and a test sample. Each sample is decomposed into two or more components that are selected automatically (without using label information as control specific, case specific and not differentially expressed (neutral. The number of components is determined by cross-validation. Automatic assignment of features (m/z ratios or genes to particular component is based on thresholds estimated from each sample directly. Due to the locality of decomposition, the strength of the expression of each feature across the samples can vary. Yet, they will still be allocated to the related disease and/or control specific component. Since label information is not used in the selection process, case and control specific components can be used for classification. That is not the case with standard factorization methods. Moreover, the component selected by proposed method
Jong, Sung-Ho; Sin, Kye-Ryong
2016-01-01
The second-order statistics (SOS) can be applied in estimation of the pure spectra of chemical components from the spectrum of their mixture, when SOS seems to be good at estimation of spectral patterns, but their peak directions are opposite in some cases. In this paper, one method for judgment of the peak direction of the pure spectra was proposed, where the base line of the pure spectra was drawn by using their histograms and the peak directions were chosen so as to make all of the pure spectra located upwards over the base line. Results of the SOS analysis on the visible hyperspectral images of the mixture composed of two or three chemical components showed that the present method offered the reasonable shape and direction of the pure spectra of its components.
Causal Effect Estimation Methods
2014-01-01
Relationship between two popular modeling frameworks of causal inference from observational data, namely, causal graphical model and potential outcome causal model is discussed. How some popular causal effect estimators found in applications of the potential outcome causal model, such as inverse probability of treatment weighted estimator and doubly robust estimator can be obtained by using the causal graphical model is shown. We confine to the simple case of binary outcome and treatment vari...
SOBCZAK, Paweł; ZAWIŚLAK, Kazimierz; ŻUKIEWICZ-SOBCZAK, Wioletta; Jacek Mazur; Rafał Nadulski; Kozak, Marta
2016-01-01
Microorganisms which contaminate animal feeds pose a threat not only to animals but also indirectly to humans through their consumption of products of animal origin. The aim of the present study was to assess microbiological cleanness of selected resources and ready-made feed mixtures before and after thermal processing. The results indicated that the most bacteriologically contaminated resources were oats (Avena sativa), wheat middlings, wheat (Triticum vulgare), and poultry feed mixture KDK...
Directory of Open Access Journals (Sweden)
Gérard eCoureaud
2014-06-01
Full Text Available Interacting with the mother during the daily nursing, newborn rabbits experience her body odour cues. In particular, the mammary pheromone (MP contained in rabbit milk triggers the typical behaviour which helps to localize and seize the nipples. It also promotes the very rapid appetitive learning of simple or complex stimuli (odorants or mixtures through associative conditioning. We previously showed that 24h after MP-induced conditioning to odorants A (ethyl isobutyrate or B (ethyl maltol, newborn rabbits perceive the AB mixture in a weak configural way, i.e. they perceive the odour of the AB configuration in addition to the odours of the elements. Moreover, after conditioning to the mixture, elimination of the memories of A and B does not affect the memory of AB, suggesting independent elemental and configural memories of the mixture. Here, we evaluated whether configural memory persistence differs from elemental one. First, whereas 1 or 3-day-old pups conditioned to A or B maintained their responsiveness to the conditioned odorant for 4 days, those conditioned to AB did not respond to the mixture after the same retention period. Second, the pups conditioned to AB still responded to A and B 4 days after conditioning, which indicates stronger retention of the elements than of the configuration when all information are learned together. Third, we determined whether the memory of the elements competes with the memory of the configuration: after conditioning to AB, when the memories of A and B were erased using pharmacological treatment, the memory of the mixture was extended to day 5. Thus, newborn rabbits have access to both elemental and configural information in certain odour mixtures, and competition between these distinct representations of the mixture influences the persistence of their memories. Such effects certainly occur in the natural context of mother-pup interactions and may contribute to early acquisition of knowledge about the
Thomas, R
2006-07-01
The problem of disentangling complex dynamic systems is addressed, especially with a view to identifying those variables that take part in the essential qualitative behaviour of systems. The author presents a series of reflections about the methods of formalisation together with the principles that govern the global operation of systems. In particular, a section on circuits, nuclei, and circular causality and a rather detailed description of the analytic use of the generalised asynchronous logical description, together with a brief description of its synthetic use (OreverseO logic). Some basic rules are recalled, such as the fact that a positive circuit is a necessary condition of multistationarity. Also, the interest of considering as a model, rather than a well-defined set of differential equations, a variety of systems that differ from each other only by the values of constant terms is emphasised. All these systems have a common Jacobian matrix and for all of them phase space has exactly the same structure. It means that all can be partitioned in the same way as regards the signs of the eigenvalues and thus as regards the precise nature of any steady states that might be present. Which steady states are actually present, depends on the values of terms of order zero in the ordinary differential equations (ODEs), and it is easy to find for which values of these terms a given point in phase space is steady. Models can be synthesised first at the level of the circuits involved in the Jacobian matrix (that determines which types and numbers of steady states are consistent with the model), then only at the level of terms of order zero in the ODE's (that determines which of the steady states actually exist), hence the title 'Circular casuality'.
Causally nonseparable processes admitting a causal model
Feix, Adrien; Araújo, Mateus; Brukner, Časlav
2016-08-01
A recent framework of quantum theory with no global causal order predicts the existence of ‘causally nonseparable’ processes. Some of these processes produce correlations incompatible with any causal order (they violate so-called ‘causal inequalities’ analogous to Bell inequalities) while others do not (they admit a ‘causal model’ analogous to a local model). Here we show for the first time that bipartite causally nonseparable processes with a causal model exist, and give evidence that they have no clear physical interpretation. We also provide an algorithm to generate processes of this kind and show that they have nonzero measure in the set of all processes. We demonstrate the existence of processes which stop violating causal inequalities but are still causally nonseparable when mixed with a certain amount of ‘white noise’. This is reminiscent of the behavior of Werner states in the context of entanglement and nonlocality. Finally, we provide numerical evidence for the existence of causally nonseparable processes which have a causal model even when extended with an entangled state shared among the parties.
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R’afat Mahmoud Nejem
2017-01-01
Full Text Available In this paper a simple method was developed for the simultaneous determination of five-component mixtures, without prior separation steps. The method is based on the combination of double divisor-ratio derivative method and mean centering of ratio spectra method. The mathematical explanation of the procedure is illustrated. The linear determination ranges were 0–30, 0–20, 0–20, 0–45 and 0–100 μg ml−1 for paracetamol, methylparaben, propylparaben, chloropheniramine maleate and pseudoephedrine hydrochloride in 0.1 M HCl, respectively. The proposed method was validated by using synthetic five-component mixtures and applied to the simultaneous determination of these drugs in Decamol Flu syrup. No published spectrophotometric method has been reported for simultaneous determination of the five components of this mixture. So the results of the double divisor mean centering of ratio method (DD-MCR were statistically compared with those of a proposed classical least squares method (CLS.
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.
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.
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...
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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.
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Tibor Tot
2011-01-01
Full Text Available A unique case of metaplastic breast carcinoma with an epithelial component showing tumoral necrosis and neuroectodermal stromal component is described. The tumor grew rapidly and measured 9 cm at the time of diagnosis. No lymph node metastases were present. The disease progressed rapidly and the patient died two years after the diagnosis from a hemorrhage caused by brain metastases. The morphology and phenotype of the tumor are described in detail and the differential diagnostic options are discussed.
Ortega, Pedro A
2011-01-01
Discovering causal relationships is a hard task, often hindered by the need for intervention, and often requiring large amounts of data to resolve statistical uncertainty. However, humans quickly arrive at useful causal relationships. One possible reason is that humans use strong prior knowledge; and rather than encoding hard causal relationships, they encode beliefs over causal structures, allowing for sound generalization from the observations they obtain from directly acting in the world. In this work we propose a Bayesian approach to causal induction which allows modeling beliefs over multiple causal hypotheses and predicting the behavior of the world under causal interventions. We then illustrate how this method extracts causal information from data containing interventions and observations.
Institute of Scientific and Technical Information of China (English)
P. K. Paul; Md. N. Islam; D. Bhattacharjee; S. A. Hussain
2007-01-01
We report the miscibility characteristics of two components in a binary mixture of 9-phenyl anthracene (PA) mixed with stearic acid (SA) or polymethyl methacrylate (PMMA). The behaviour of surface pressure versus area per molecule isotherms reveal that the area per molecule decreases systematically with increasing molefractions of PA. The characteristics of areas per molecule versus molefractions and collapse pressure vs molefraction indicate that various interactions involved among the sample and matrix molecules. The interaction scheme is found to change with the change in surface pressure and molefraction of mixing. Scanning electron microscopic study confirms the aggregation of PA molecules in the mixed films.
Sunda, Anurag Prakash; Venkatnathan, Arun
2011-11-30
Triflic acid is a functional group of perflourosulfonated polymer electrolyte membranes where the sulfonate group is responsible for proton conduction. However, even at extremely low hydration, triflic acid exists as a triflate ion. In this work, we have developed a force-field for triflic acid and triflate ion by deriving force-field parameters using ab initio calculations and incorporated these parameters with the Optimized Potentials for Liquid Simulations - All Atom (OPLS-AA) force-field. We have employed classical molecular dynamics (MD) simulations with the developed force field to characterize structural and dynamical properties of triflic acid (270-450 K) and triflate ion/water mixtures (300 K). The radial distribution functions (RDFs) show the hydrophobic nature of CF(3) group and presence of strong hydrogen bonding in triflic acid and temperature has an insignificant effect. Results from our MD simulations show that the diffusion of triflic acid increases with temperature. The RDFs from triflate ion/water mixtures shows that increasing hydration causes water molecules to orient around the SO(3)(-) group of triflate ions, solvate the hydronium ions, and other water molecules. The diffusion of triflate ions, hydronium ion, and water molecules shows an increase with hydration. At λ = 1, the diffusion of triflate ion is 30 times lower than the diffusion of triflic acid due to the formation of stable triflate ion-hydronium ion complex. With increasing hydration, water molecules break the stability of triflate ion-hydronium ion complex leading to enhanced diffusion. The RDFs and diffusion coefficients of triflate ions, hydronium ions and water molecules resemble qualitatively the previous findings using per-fluorosulfonated membranes.
Causality for nonlocal phenomena
Eckstein, Michał
2015-01-01
Drawing from the theory of optimal transport we propose a rigorous notion of a causal relation for Borel probability measures on a given spacetime. To prepare the ground, we explore the borderland between causality, topology and measure theory. We provide various characterisations of the proposed causal relation, which turn out to be equivalent if the underlying spacetime has a sufficiently robust causal structure. We also present the notion of the 'Lorentz-Wasserstein distance' and study its basic properties. Finally, we discuss how various results on causality in quantum theory, aggregated around Hegerfeldt's theorem, fit into our framework.
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Kerstin Golker
2014-11-01
Full Text Available In this report, principal component analysis (PCA has been used to explore the influence of template complexation in the pre-polymerization phase on template molecularly imprinted polymer (MIP recognition and polymer morphology. A series of 16 bupivacaine MIPs were studied. The ethylene glycol dimethacrylate (EGDMA-crosslinked polymers had either methacrylic acid (MAA or methyl methacrylate (MMA as the functional monomer, and the stoichiometry between template, functional monomer and crosslinker was varied. The polymers were characterized using radioligand equilibrium binding experiments, gas sorption measurements, swelling studies and data extracted from molecular dynamics (MD simulations of all-component pre-polymerization mixtures. The molar fraction of the functional monomer in the MAA-polymers contributed to describing both the binding, surface area and pore volume. Interestingly, weak positive correlations between the swelling behavior and the rebinding characteristics of the MAA-MIPs were exposed. Polymers prepared with MMA as a functional monomer and a polymer prepared with only EGDMA were found to share the same characteristics, such as poor rebinding capacities, as well as similar surface area and pore volume, independent of the molar fraction MMA used in synthesis. The use of PCA for interpreting relationships between MD-derived descriptions of events in the pre-polymerization mixture, recognition properties and morphologies of the corresponding polymers illustrates the potential of PCA as a tool for better understanding these complex materials and for their rational design.
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Justin M Calabrese
Full Text Available It is well known that parasites are often highly aggregated on their hosts such that relatively few individuals host the large majority of parasites. When the parasites are vectors of infectious disease, a key consequence of this aggregation can be increased disease transmission rates. The cause of this aggregation, however, is much less clear, especially for parasites such as arthropod vectors, which generally spend only a short time on their hosts. Regression-based analyses of ticks on various hosts have focused almost exclusively on identifying the intrinsic host characteristics associated with large burdens, but these efforts have had mixed results; most host traits examined have some small influence, but none are key. An alternative approach, the Poisson-gamma mixture distribution, has often been used to describe aggregated parasite distributions in a range of host/macroparasite systems, but lacks a clear mechanistic basis. Here, we extend this framework by linking it to a general model of parasite accumulation. Then, focusing on blacklegged ticks (Ixodes scapularis on mice (Peromyscus leucopus, we fit the extended model to the best currently available larval tick burden datasets via hierarchical Bayesian methods, and use it to explore the relative contributions of intrinsic and extrinsic factors on observed tick burdens. Our results suggest that simple bad luck-inhabiting a home range with high vector density-may play a much larger role in determining parasite burdens than is currently appreciated.
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OANA Dorina
2016-05-01
Full Text Available The main physical-mechanical properties of the yarns are: linear density (Tex, tensile strength, tenacity, elongation at break, twisting and mechanical work of fracture, there is a strong correlation between them. The tensile properties are the basic characteristics of yarns, influencing how they behave in the technological processes of mechanical processing (preparation for weaving or knitting, proper weaving or knitting determining the technological parameters of equipment adjusting during the technological processes and also their productivity. The tensile properties of yarns constitute qualitative characteristics, because their value depends on the quality of the yarn and also on the finite product obtained from processing yarns. In this paper was done a comparative study of the tensile properties of two batches of mixed woolen yarns (wool with polyester and wool with polyamide, the mixture being in the same proportions, but the yarns have different fineness and have very close twist values, both batches of yarns were designed for knitted products. Batch I consists of 70% wool yarns and 30% polyester, linear density Ttex = 55.56 tex and twist of 350 twists/meter. Batch II consists of 70% wool yarns and 30% polyamide, a linear density of Ttex = 71.34 tex and twist of 330 twists/meter (so a thicker yarn than the one from batch I. Following the analysis between the two batches is clear that the woolen yarns in batch II have much higher tensile properties.
González-Vidal, Juan José; Pérez-Pueyo, Rosanna; Soneira, María José; Ruiz-Moreno, Sergio
2015-03-01
A new method has been developed to automatically identify Raman spectra, whether they correspond to single- or multicomponent spectra. The method requires no user input or judgment. There are thus no parameters to be tweaked. Furthermore, it provides a reliability factor on the resulting identification, with the aim of becoming a useful support tool for the analyst in the decision-making process. The method relies on the multivariate techniques of principal component analysis (PCA) and independent component analysis (ICA), and on some metrics. It has been developed for the application of automated spectral analysis, where the analyzed spectrum is provided by a spectrometer that has no previous knowledge of the analyzed sample, meaning that the number of components in the sample is unknown. We describe the details of this method and demonstrate its efficiency by identifying both simulated spectra and real spectra. The method has been applied to artistic pigment identification. The reliable and consistent results that were obtained make the methodology a helpful tool suitable for the identification of pigments in artwork or in paint in general.
Prieto-Blanco, M C; Argente-García, A; Campíns-Falcó, P
2016-01-29
A method for quantifying benzalkonium chloride (BAK), an alkyl dimethyl benzyl ammonium compound, in several biocides formulations is proposed. A tertiary amine like N-(3-aminopropyl)-N-dodecyl-1,3-propanediamine (TA) and a straight-chain alkyl ammonium compound like trimethyl-tetradecyl ammonium chloride (TMTDAC), have been employed as trade surfactants besides BAK. Two capillary analytical columns with different polarities are tested: inertsil CN-3 capillary column (150mm×0.5mm i.d., 3μm particle diameter) and a non endcapped Zorbax C18 capillary column (35mm×0.5mm i.d., 5μm particle diameter). This latter column provided the best separation of the BAK homologues in less than 12min using acetonitrile:acetate buffer (50mM, pH 5) 85:15 at 20μLmin(-1). The proposed method combines on-line in-tube solid-phase microextraction (IT-SPME) coupled to capillary liquid chromatography (CapLC) and UV diode array detection. Matrix effect was present when TA were in excess to BAK. If TMTDAC is the co-biocide, matrix effect is always present. A decreasing of analytical response mainly for C12-BAK homologue was found using both chromatographic columns. The charged amount of mixture in the system was the most important parameter for obtaining reliable results. 1mL was the on line processed sample volume optimum for concentrations lower than 35μgmL(-1) of total surfactants. LODs were 0.03μgmL(-1) and 0.006μgmL(-1) for C12-BAK and C14-BAK, respectively. This method is also of use to evaluate the unwanted presence of BAK in biocide formulations due to industrial processes.
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Rejane Rodrigues da Costa e Carvalho
2013-01-01
Full Text Available Essential oils of Lippia sidoides, Lippia gracilis and their main chemical components were investigated for in vitro control of Thielaviopsis paradoxa. Mycelial growth and a number of pathogen conidia were inhibited by the essential oil of L. sidoides at all concentrations tested (0.2; 0.5; 1.0; 3.0 µL mL-1. L. sidoides oil contained 42.33% thymol and 4.56% carvacrol, while L. gracilis oil contained 10% thymol and 41.7% carvacrol. Mycelial growth and conidial production of T. paradoxa were completely inhibited by thymol at a 0.3 µL m-1 concentration. The results suggest that thymol could potentially be used for controlling coconut stem bleeding.
Cortês, Marina
2013-01-01
We propose an approach to quantum theory based on the energetic causal sets, introduced in Cort\\^{e}s and Smolin (2013). Fundamental processes are causal sets whose events carry momentum and energy, which are transmitted along causal links and conserved at each event. Fundamentally there are amplitudes for such causal processes, but no space-time. An embedding of the causal processes in an emergent space-time arises only at the semiclassical level. Hence, fundamentally there are no commutation relations, no uncertainty principle and, indeed, no hbar. All that remains of quantum theory is the relationship between the absolute value squared of complex amplitudes and probabilities. Consequently, we find that neither locality, nor non locality, are primary concepts, only causality exists at the fundamental level.
2015-01-01
Uncovering causal relationships in data is a major objective of data analytics. Causal relationships are normally discovered with designed experiments, e.g. randomised controlled trials, which, however are expensive or infeasible to be conducted in many cases. Causal relationships can also be found using some well designed observational studies, but they require domain experts' knowledge and the process is normally time consuming. Hence there is a need for scalable and automated methods for c...
Kinsler, Paul
2011-01-01
I explain a simple definition of causality in widespread use, and indicate how it links to the Kramers Kronig relations. The specification of causality in terms of temporal differential eqations then shows us the way to write down dynamical models so that their causal nature in the sense used here should be obvious to all. In particular, I apply this reasoning to Maxwell's equations, which is an instructive example since their casual properties are sometimes debated.
López-Calzada, G; Hernandez-Martínez, A R; Cruz-Soto, M; Ramírez-Cardona, M; Rangel, D; Molina, G A; Luna-Barcenas, G; Estevez, M
2016-04-01
Despite the significant advances in the meniscus tissue engineering field, it is difficult to recreate the complex structure and organization of the collagenous matrix of the meniscus. In this work, we developed a meniscus prototype to be used as substitute or scaffold for the regeneration of the meniscal matrix, recreating the differential morphology of the meniscus by electrospinning. Synthetic biocompatible polymers were combined with the extracellular matrix component, collagen and used to replicate the meniscus. We studied the correlation between mechanical and structural properties of the polymer blend as a function of collagen concentration. Fibers were collected on a surface of a rapidly rotating precast mold, to accurately replicate each sectional morphology of the meniscus; different electro-tissues were produced. Detailed XRD analyses exhibited structural changes developed by electrospinning. We achieved to integrate all these electro-tissues to form a complete synthetic meniscus. Vascularization tests were performed to assess the potential use of our novel polymeric blend for promising meniscus regeneration.
Shao, Jingwei; Zhou, Suxia; Jiang, Zhou; Chi, Ting; Ma, Ji; Kuo, Minliang; Lee, Alan Yueh-Luen; Jia, Lee
2016-08-02
We recently defined cancer metastatic chemoprevention as utilizing safe and effective molecules to comprehensively prevent the spark of activation-adhesion-extravasation-proliferation metastatic cascade caused by circulating tumor cells (CTCs). The strategy focuses on preventing the most important starting point of the cascade. We identified an extract from a well-known medical plant Murraya paniculata, which inhibited both embryonic implantation to human endometrium as traditionally-used for abortion and CTC adhesion to human endothelium. Here, we separated and characterized five coumarin-containing components (Z1-Z5) from the botanic extract. Flow cytometry revealed that within 1-100 μg/mL, Z3 and Z5 down-regulated EpCAM expression in human colon HCT116, whereas, Z1 and Z2 did oppositely. Warfarin and Z1-Z5 component mixture (CM) also down-regulated EpCAM expression. The down-regulation of EpCAM by Z3, Z5, CM and warfarin was confirmed by western blotting, and caused inhibition on adhesion of cancer cells to human endothelial cells. Rat coagulation study showed that warfarin prolonged prothrombin time, whereas, Z3 did not. The present studies revealed that, for the first time, warfarin and coumarin-like components Z3, Z5 and CM from Murraya paniculata could directly inhibit EpCAM-mediated cell-cell adhesion.
Blaisdell, A.P.; Beckers, T.
2009-01-01
The article discusses various reports published within the issue, including one on psychological approaches to causal discovery in humans, one on the representational and reasoning capacities that underlie causal cognition in rats and one on the generality of knowledge of Great Ape.
Causality in Classical Electrodynamics
Savage, Craig
2012-01-01
Causality in electrodynamics is a subject of some confusion, especially regarding the application of Faraday's law and the Ampere-Maxwell law. This has led to the suggestion that we should not teach students that electric and magnetic fields can cause each other, but rather focus on charges and currents as the causal agents. In this paper I argue…
Causality and Lifshitz Holography
Energy Technology Data Exchange (ETDEWEB)
Koroteev, Peter [Department of Physics and Astronomy, University of Minnesota, 116 Church Street S.E., Minneapolis, MN 55455 (United States)
2011-07-15
We study signal propagation in theories with Lifshitz scaling using the gravity dual and show that backgrounds with z<1 are incompatible with causality of the strongly coupled theory. We argue that causality violations in z<1 theories show up in boundary correlation functions as superluminal modes.
Causality in Europeanization Research
DEFF Research Database (Denmark)
Lynggaard, Kennet
2012-01-01
Discourse analysis as a methodology is perhaps not readily associated with substantive causality claims. At the same time the study of discourses is very much the study of conceptions of causal relations among a set, or sets, of agents. Within Europeanization research we have seen endeavours...... to develop discursive institutional analytical frameworks and something that comes close to the formulation of hypothesis on the effects of European Union (EU) policies and institutions on domestic change. Even if these efforts so far do not necessarily amount to substantive theories or claims of causality......, it suggests that discourse analysis and the study of causality are by no means opposites. The study of Europeanization discourses may even be seen as an essential step in the move towards claims of causality in Europeanization research. This chapter deals with the question of how we may move from the study...
DEFF Research Database (Denmark)
Nielsen, Max; Jensen, Frank; Setälä, Jari;
2011-01-01
This article focuses on causality in demand. A methodology where causality is imposed and tested within an empirical co-integrated demand model, not prespecified, is suggested. The methodology allows different causality of different products within the same demand system. The methodology is applied...... to fish demand. On the German market for farmed trout and substitutes, it is found that supply sources, i.e. aquaculture and fishery, are not the only determinant of causality. Storing, tightness of management and aggregation level of integrated markets might also be important. The methodological...... implication is that more explicit focus on causality in demand analyses provides improved information. The results suggest that frozen trout forms part of a large European whitefish market, where prices of fresh trout are formed on a relatively separate market. Redfish is a substitute on both markets...
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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.
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Bordacconi, Mats Joe; Larsen, Martin Vinæs
2014-01-01
Humans are fundamentally primed for making causal attributions based on correlations. This implies that researchers must be careful to present their results in a manner that inhibits unwarranted causal attribution. In this paper, we present the results of an experiment that suggests regression...... models – one of the primary vehicles for analyzing statistical results in political science – encourage causal interpretation. Specifically, we demonstrate that presenting observational results in a regression model, rather than as a simple comparison of means, makes causal interpretation of the results...... of equivalent results presented as either regression models or as a test of two sample means. Our experiment shows that the subjects who were presented with results as estimates from a regression model were more inclined to interpret these results causally. Our experiment implies that scholars using regression...
Causal inference, probability theory, and graphical insights.
Baker, Stuart G
2013-11-10
Causal inference from observational studies is a fundamental topic in biostatistics. The causal graph literature typically views probability theory as insufficient to express causal concepts in observational studies. In contrast, the view here is that probability theory is a desirable and sufficient basis for many topics in causal inference for the following two reasons. First, probability theory is generally more flexible than causal graphs: Besides explaining such causal graph topics as M-bias (adjusting for a collider) and bias amplification and attenuation (when adjusting for instrumental variable), probability theory is also the foundation of the paired availability design for historical controls, which does not fit into a causal graph framework. Second, probability theory is the basis for insightful graphical displays including the BK-Plot for understanding Simpson's paradox with a binary confounder, the BK2-Plot for understanding bias amplification and attenuation in the presence of an unobserved binary confounder, and the PAD-Plot for understanding the principal stratification component of the paired availability design.
Causal Networks with Selectively Influenced Components
2012-02-29
Program, Arlington, VA, January. Viau-Quesnel, C., Schweickert, R., & Fortin, C. (2010). L’étude des réseaux sociaux en psychologie cognitive...un exemple basé sur l’étude de l’organisation des rêves. Société Québécoise pour la Recherche en Psychologie . Montreal, April. Schweickert, R
Vinš, Václav; Planková, Barbora; Hrubý, Jan
2013-05-01
In this study, the Cahn-Hilliard density gradient theory (GT) is used for predicting the surface tension of various binary mixtures at relatively wide temperature ranges and for testing the application of the GT for predictions of homogeneous nucleation. The GT was combined with two physically based equations of state (EoS), namely the perturbed-chain (PC) statistical associating fluid theory (SAFT) and its modification for polar substances the perturbed-chain polar (PCP) SAFT. The GT applied to the planar phase interface was employed to predict the interfacial tension for various quadrupolar (CO2 and benzene) and dipolar (difluoromethane, i.e., R32; pentafluoroethane, i.e., R125; and 1,1,1,2-tetrafluoroethane, i.e., R134a) substances and for five binary mixtures including polar components ( n-decane + CO2, benzene + CO2, R32 + R125, R32 + R134a, R134a + R125). The PCP-SAFT EoS combined with the GT provides more accurate results for both the quadrupolar and dipolar substances than the original PC-SAFT EoS. Besides the planar phase interface, the GT was also applied to the spherical phase interface simulating a critical cluster occurring in homogeneous nucleation of droplets. Carbon dioxide was considered, because it has a relatively high quadrupole moment and because of its relevance to natural gas processing. Application of the PCP-SAFT EoS provides a significant improvement compared to the PC-SAFT EoS, and it is clearly superior to the classical cubic Peng-Robinson EoS, which is still used for modeling droplet nucleation.
Energy Technology Data Exchange (ETDEWEB)
Tipler, F.J.
1977-08-01
Causally symmetric spacetimes are spacetimes with J/sup +/(S) isometric to J/sup -/(S) for some set S. We discuss certain properties of these spacetimes, showing for example that, if S is a maximal Cauchy surface with matter everywhere on S, then the spacetime has singularities in both J/sup +/(S) and J/sup -/(S). We also consider totally vicious spacetimes, a class of causally symmetric spacetimes for which I/sup +/(p) =I/sup -/(p) = M for any point p in M. Two different notions of stability in general relativity are discussed, using various types of causally symmetric spacetimes as starting points for perturbations.
Zinoviev, Yury M
2012-01-01
The equations of the relativistic causal Newton gravity law for the planets of the solar system are studied in the approximation when the Sun rests at the coordinates origin and the planets do not iteract between each other.
Immirzi, Giorgio
2016-01-01
I discuss how to impose causality on spin-foam models, separating forward and backward propagation, turning a given triangulation to a 'causal set', and giving asymptotically the exponential of the Regge action, not a cosine. I show the equivalence of the prescriptions which have been proposed to achieve this. Essential to the argument is the closure condition for the 4-simplices, all made of space-like tetrahedra.
Primordial Magnetic Fields and Causality
Durrer, R; Durrer, Ruth; Caprini, Chiara
2003-01-01
In this letter we discuss the implications of causality on a primordial magnetic field. We show that the residual field on large scales is much stronger suppressed than usually assumed and that a helical component is even suppressed even more than the parity even part. We show that due to this strong suppression, even maximal primordial fields generated at the electroweak phase transition can just marginally seed the fields in galaxies and clusters, but they cannot leave any detectable imprint on the cosmic microwave background.
Arrighi, Pablo
2016-01-01
Consider a graph having quantum systems lying at each node. Suppose that the whole thing evolves in discrete time steps, according to a global, unitary causal operator. By causal we mean that information can only propagate at a bounded speed, with respect to the distance given by the graph. Suppose, moreover, that the graph itself is subject to the evolution, and may be driven to be in a quantum superposition of graphs---in accordance to the superposition principle. We show that these unitary causal operators must decompose as a finite-depth circuit of local unitary gates. This unifies a result on Quantum Cellular Automata with another on Reversible Causal Graph Dynamics. Along the way we formalize a notion of causality which is valid in the context of quantum superpositions of time-varying graphs, and has a number of good properties. Keywords: Quantum Lattice Gas Automata, Block-representation, Curtis-Hedlund-Lyndon, No-signalling, Localizability, Quantum Gravity, Quantum Graphity, Causal Dynamical Triangula...
Essays on Finite Mixture Models
A. van Dijk (Bram)
2009-01-01
textabstractFinite mixture distributions are a weighted average of a ¯nite number of distributions. The latter are usually called the mixture components. The weights are usually described by a multinomial distribution and are sometimes called mixing proportions. The mixture components may be the sam
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Ermler, Sibylle; Scholze, Martin; Kortenkamp, Andreas, E-mail: andreas.kortenkamp@brunel.ac.uk
2011-12-15
The risks associated with human exposures to chemicals capable of antagonising the effects of endogenous androgens have attracted considerable recent interest. Exposure is typically to large numbers of chemicals with androgen receptor (AR) antagonist activity, yet there is limited evidence of the combined effects of multi-component mixtures of these chemicals. A few in vitro studies with mixtures of up to six AR antagonists suggest that the concept of concentration addition (CA) provides good approximations of experimentally observed mixture effects, but studies with larger numbers of anti-androgens, and with more varied structural features, are missing. Here we show that the mixture effects of up to 17 AR antagonists, comprising compounds as diverse as UV-filter substances, parabens, perfluorinated compounds, bisphenol-A, benzo({alpha})pyrene, synthetic musks, antioxidants and polybrominated biphenyls, can be predicted well on the basis of the anti-androgenicity of the single components using the concept of CA. We tested these mixtures in an in vitro AR-dependent luciferase reporter gene assay, based on MDA-kb2 cells. The effects of further mixtures, composed of four and six anti-androgens, could be predicted accurately by CA. However, there was a shortfall from expected additivity with a ten-component mixture at two different mixture ratios, but attempts to attribute these deviations to differential expression of hormone-metabolising CYP isoforms did not produce conclusive results. CA provides good approximations of in vitro mixture effects of anti-androgens with varying structural features. -- Highlights: Black-Right-Pointing-Pointer Humans are exposed to a large number of androgen receptor antagonists. Black-Right-Pointing-Pointer There is limited evidence of the combined effects of anti-androgenic chemicals. Black-Right-Pointing-Pointer We modelled the predictability of combined effects of up to 17 anti-androgens. Black-Right-Pointing-Pointer We tested the
[Clinical research III. The causality studies].
Talavera, Juan O; Wacher-Rodarte, Niels H; Rivas-Ruiz, Rodolfo
2011-01-01
The need to solve a clinical problem leads us to establish a starting point to address (risk, prognosis or treatment studies), all these cases seek to attribute causality. Clinical reasoning described in the book Clinical Epidemiology. The architecture of clinical research, offers a simple guide to understanding this phenomenon. And proposes three basic components: baseline, maneuver and outcome. In this model, different systematic errors (bias) are described, which may be favored by omitting characteristics of the three basic components. Thus, omissions in the baseline characteristics cause an improper assembly of the population and susceptibility bias, omissions in the application or evaluation of the maneuver provoke performance bias, and omissions in the assessment of out-come cause detection bias and transfer bias. Importantly, if this way of thinking facilitates understanding of the causal phenomenon, the appropriateness of the variables to be selected in the studies to which attribute or not causality, require additional arguments for evaluate clinical relevance.
2012-01-01
The causal assumptions, the study design and the data are the elements required for scientific inference in empirical research. The research is adequately communicated only if all of these elements and their relations are described precisely. Causal models with design describe the study design and the missing data mechanism together with the causal structure and allow the direct application of causal calculus in the estimation of the causal effects. The flow of the study is visualized by orde...
Directory of Open Access Journals (Sweden)
Túlio Aguiar
2003-12-01
Full Text Available Neste artigo, examinamos o aspecto assimétrico da relação causal, confrontando-o com o ponto de vista humiano e neo-humiano. Seguindo Hausman e Ehring, favorecemos uma abordagem situacional para a assimetria causal. Nós exploramos a análise do famoso exemplo do mastro (Flagpole, esclarecendo as conexões entre causação e explicação. Nosso diagnóstico geral é que a tradição neo-humiana supõe, equivocadamente, que as relações nômicas, com exceção de pequenos detalhes, exaurem as relações causais.This paper examines the asymmetrical aspect of causal relation, confronting it to Humean and Neo-Humean's view. Following Hausman and Ehring, we favor a situational approach to causal asymmetry. We explore the Hausman's analysis of flagpole's example, clearing the connexions between causation and explanation. Our general diagnosis is that the Neo-humean tradition wrongly supposes that nomic relations, with the exception of minor details, exhaust the causal relations.
Biased causal inseparable game
Bhattacharya, Some Sankar
2015-01-01
Here we study the \\emph{causal inseparable} game introduced in [\\href{http://www.nature.com/ncomms/journal/v3/n10/full/ncomms2076.html}{Nat. Commun. {\\bf3}, 1092 (2012)}], but it's biased version. Two separated parties, Alice and Bob, generate biased bits (say input bit) in their respective local laboratories. Bob generates another biased bit (say decision bit) which determines their goal: whether Alice has to guess Bob's bit or vice-verse. Under the assumption that events are ordered with respect to some global causal relation, we show that the success probability of this biased causal game is upper bounded, giving rise to \\emph{biased causal inequality} (BCI). In the \\emph{process matrix} formalism, which is locally in agreement with quantum physics but assume no global causal order, we show that there exist \\emph{inseparable} process matrices that violate the BCI for arbitrary bias in the decision bit. In such scenario we also derive the maximal violation of the BCI under local operations involving tracele...
Causality discovery technology
Chen, M.; Ertl, T.; Jirotka, M.; Trefethen, A.; Schmidt, A.; Coecke, B.; Bañares-Alcántara, R.
2012-11-01
Causality is the fabric of our dynamic world. We all make frequent attempts to reason causation relationships of everyday events (e.g., what was the cause of my headache, or what has upset Alice?). We attempt to manage causality all the time through planning and scheduling. The greatest scientific discoveries are usually about causality (e.g., Newton found the cause for an apple to fall, and Darwin discovered natural selection). Meanwhile, we continue to seek a comprehensive understanding about the causes of numerous complex phenomena, such as social divisions, economic crisis, global warming, home-grown terrorism, etc. Humans analyse and reason causality based on observation, experimentation and acquired a priori knowledge. Today's technologies enable us to make observations and carry out experiments in an unprecedented scale that has created data mountains everywhere. Whereas there are exciting opportunities to discover new causation relationships, there are also unparalleled challenges to benefit from such data mountains. In this article, we present a case for developing a new piece of ICT, called Causality Discovery Technology. We reason about the necessity, feasibility and potential impact of such a technology.
Causal inference in econometrics
Kreinovich, Vladik; Sriboonchitta, Songsak
2016-01-01
This book is devoted to the analysis of causal inference which is one of the most difficult tasks in data analysis: when two phenomena are observed to be related, it is often difficult to decide whether one of them causally influences the other one, or whether these two phenomena have a common cause. This analysis is the main focus of this volume. To get a good understanding of the causal inference, it is important to have models of economic phenomena which are as accurate as possible. Because of this need, this volume also contains papers that use non-traditional economic models, such as fuzzy models and models obtained by using neural networks and data mining techniques. It also contains papers that apply different econometric models to analyze real-life economic dependencies.
Arrighi, Pablo
2012-01-01
We generalize the theory of Cellular Automata to arbitrary, time-varying graphs. In other words we formalize, and prove theorems about, the intuitive idea of a labelled graph which evolves in time - but under the natural constraint that information can only ever be transmitted at a bounded speed, with respect to the distance given by the graph. The notion of translation-invariance is also generalized. The definition we provide for these `causal graph dynamics' is simple and axiomatic. The theorems we provide also show that it is robust. For instance, causal graph dynamics are stable under composition and under restriction to radius one. In the finite case some fundamental facts of Cellular Automata theory carry through: causal graph dynamics admit a characterization as continuous functions and they are stable under inversion. The provided examples suggest a wide range of applications of this mathematical object, from complex systems science to theoretical physics. Keywords: Dynamical networks, Boolean network...
Complementarity, causality, and explanation
Losee, John
2013-01-01
Prior to the work of Niels Bohr, discussions on the relationship of cause and effect presupposed that successful causal attribution implies explanation. The success of quantum theory challenged this presupposition. In this succinct review of the history of these discussions, John Losee presents the philosophical background of debates over the cause-effect relation. He reviews the positions of Aristotle, René Descartes, Isaac Newton, David Hume, Immanuel Kant, and John Stuart Mill. He shows how nineteenth-century theories in physics and chemistry were informed by a dominant theory of causality
Kaufmann, Stefan
2013-08-01
The rise of causality and the attendant graph-theoretic modeling tools in the study of counterfactual reasoning has had resounding effects in many areas of cognitive science, but it has thus far not permeated the mainstream in linguistic theory to a comparable degree. In this study I show that a version of the predominant framework for the formal semantic analysis of conditionals, Kratzer-style premise semantics, allows for a straightforward implementation of the crucial ideas and insights of Pearl-style causal networks. I spell out the details of such an implementation, focusing especially on the notions of intervention on a network and backtracking interpretations of counterfactuals.
Energy Technology Data Exchange (ETDEWEB)
Razhev, A M; Kargapol' tsev, E S [Institute of Laser Physics, Siberian Branch, Russian Academy of Sciences, Novosibirsk (Russian Federation); Churkin, D S [Novosibirsk State University, Novosibirsk (Russian Federation)
2016-03-31
Results of an experimental study of the influence of a gas mixture (laser active medium) composition on an output energy and total efficiency of gas-discharge excimer lasers on ArF* (193 nm), KrCl* (222 nm), KrF* (248 nm) and XeCl* (308 nm) molecules operating without a buffer gas are presented. The optimal ratios of gas components (from the viewpoint of a maximum output energy) of an active medium are found, which provide an efficient operation of laser sources. It is experimentally confirmed that for gas-discharge excimer lasers on halogenides of inert gases the presence of a buffer gas in an active medium is not a necessary condition for efficient operation. For the first time, in two-component gas mixtures of repetitively pulsed gas-discharge excimer lasers on electron transitions of excimer molecules ArF*, KrCl*, KrF* and XeCl*, the pulsed energy of laser radiation obtained under pumping by a transverse volume electric discharge in a low-pressure gas mixture without a buffer gas reached up to 170 mJ and a high pulsed output power (of up to 24 MW) was obtained at a FWHM duration of the KrF-laser pulse of 7 ns. The maximal total efficiency obtained in the experiment with two-component gas mixtures of KrF and XeCl lasers was 0.8%. (lasers)
Razhev, A. M.; Kargapol'tsev, E. S.; Churkin, D. S.
2016-03-01
Results of an experimental study of the influence of a gas mixture (laser active medium) composition on an output energy and total efficiency of gas-discharge excimer lasers on ArF* (193 nm), KrCl* (222 nm), KrF* (248 nm) and XeCl* (308 nm) molecules operating without a buffer gas are presented. The optimal ratios of gas components (from the viewpoint of a maximum output energy) of an active medium are found, which provide an efficient operation of laser sources. It is experimentally confirmed that for gas-discharge excimer lasers on halogenides of inert gases the presence of a buffer gas in an active medium is not a necessary condition for efficient operation. For the first time, in two-component gas mixtures of repetitively pulsed gas-discharge excimer lasers on electron transitions of excimer molecules ArF*, KrCl*, KrF* and XeCl*, the pulsed energy of laser radiation obtained under pumping by a transverse volume electric discharge in a low-pressure gas mixture without a buffer gas reached up to 170 mJ and a high pulsed output power (of up to 24 MW) was obtained at a FWHM duration of the KrF-laser pulse of 7 ns. The maximal total efficiency obtained in the experiment with two-component gas mixtures of KrF and XeCl lasers was 0.8%.
Understanding Causal Coherence Relations
Mulder, G.
2008-01-01
The research reported in this dissertation focuses on the cognitive processes and representations involved in understanding causal coherence relations in text. Coherence relations are the meaning relations between the information units in the text, such as Cause-Consequence. These relations can be m
Causality: Physics and Philosophy
Chatterjee, Atanu
2013-01-01
Nature is a complex causal network exhibiting diverse forms and species. These forms or rather systems are physically open, structurally complex and naturally adaptive. They interact with the surrounding media by operating a positive-feedback loop through which, they adapt, organize and self-organize themselves in response to the ever-changing…
Thermophysical Properties of Hydrocarbon Mixtures
SRD 4 NIST Thermophysical Properties of Hydrocarbon Mixtures (PC database for purchase) Interactive computer program for predicting thermodynamic and transport properties of pure fluids and fluid mixtures containing up to 20 components. The components are selected from a database of 196 components, mostly hydrocarbons.
Causal diagrams for physical models
Kinsler, Paul
2015-01-01
I present a scheme of drawing causal diagrams based on physically motivated mathematical models expressed in terms of temporal differential equations. They provide a means of better understanding the processes and causal relationships contained within such systems.
Information causality and noisy computations
Energy Technology Data Exchange (ETDEWEB)
Hsu, Li-Yi [Department of Physics, Chung Yuan Christian University, Chung-li 32023, Taiwan (China); Yu, I-Ching; Lin, Feng-Li [Department of Physics, National Taiwan Normal University, Taipei 116, Taiwan (China)
2011-10-15
We reformulate the information causality in a more general framework by adopting the results of signal propagation and computation in a noisy circuit. In our framework, the information causality leads to a broad class of Tsirelson inequalities. This fact allows us to subject information causality to experimental scrutiny. A no-go theorem for reliable nonlocal computation is also derived. Information causality prevents any physical circuit from performing reliable computations.
Spectral Geometry and Causality
Kopf, T
1996-01-01
For a physical interpretation of a theory of quantum gravity, it is necessary to recover classical spacetime, at least approximately. However, quantum gravity may eventually provide classical spacetimes by giving spectral data similar to those appearing in noncommutative geometry, rather than by giving directly a spacetime manifold. It is shown that a globally hyperbolic Lorentzian manifold can be given by spectral data. A new phenomenon in the context of spectral geometry is observed: causal relationships. The employment of the causal relationships of spectral data is shown to lead to a highly efficient description of Lorentzian manifolds, indicating the possible usefulness of this approach. Connections to free quantum field theory are discussed for both motivation and physical interpretation. It is conjectured that the necessary spectral data can be generically obtained from an effective field theory having the fundamental structures of generalized quantum mechanics: a decoherence functional and a choice of...
Pitalúa-García, Damián
2012-01-01
How much information can a transmitted physical system fundamentally communicate? We introduce the principle of quantum information causality, which states the maximum amount of quantum information that a quantum system can communicate as a function of its dimension, independently of any previously shared quantum physical resources. We present a new quantum information task, whose success probability is upper bounded by the new principle, and show that an optimal strategy to perform it combin...
Liang, X San
2014-01-01
Given two time series, can one tell, in a rigorous and quantitative way, the cause and effect between them? Based on a recently rigorized physical notion namely information flow, we arrive at a concise formula and give this challenging question, which is of wide concern in different disciplines, a positive answer. Here causality is measured by the time rate of change of information flowing from one series, say, X2, to another, X1. The measure is asymmetric between the two parties and, particularly, if the process underlying X1 does not depend on X2, then the resulting causality from X2 to X1 vanishes. The formula is tight in form, involving only the commonly used statistics, sample covariances. It has been validated with touchstone series purportedly generated with one-way causality. It has also been applied to the investigation of real world problems; an example presented here is the cause-effect relation between two climate modes, El Ni\\~no and Indian Ocean Dipole, which have been linked to the hazards in f...
Causality in physiological signals.
Müller, Andreas; Kraemer, Jan F; Penzel, Thomas; Bonnemeier, Hendrik; Kurths, Jürgen; Wessel, Niels
2016-05-01
Health is one of the most important non-material assets and thus also has an enormous influence on material values, since treating and preventing diseases is expensive. The number one cause of death worldwide today originates in cardiovascular diseases. For these reasons the aim of understanding the functions and the interactions of the cardiovascular system is and has been a major research topic throughout various disciplines for more than a hundred years. The purpose of most of today's research is to get as much information as possible with the lowest possible effort and the least discomfort for the subject or patient, e.g. via non-invasive measurements. A family of tools whose importance has been growing during the last years is known under the headline of coupling measures. The rationale for this kind of analysis is to identify the structure of interactions in a system of multiple components. Important information lies for example in the coupling direction, the coupling strength, and occurring time lags. In this work, we will, after a brief general introduction covering the development of cardiovascular time series analysis, introduce, explain and review some of the most important coupling measures and classify them according to their origin and capabilities in the light of physiological analyses. We will begin with classical correlation measures, go via Granger-causality-based tools, entropy-based techniques (e.g. momentary information transfer), nonlinear prediction measures (e.g. mutual prediction) to symbolic dynamics (e.g. symbolic coupling traces). All these methods have contributed important insights into physiological interactions like cardiorespiratory coupling, neuro-cardio-coupling and many more. Furthermore, we will cover tools to detect and analyze synchronization and coordination (e.g. synchrogram and coordigram). As a last point we will address time dependent couplings as identified using a recent approach employing ensembles of time series. The
Revisiting Causality in Markov Chains
Shojaee, Abbas
2016-01-01
Identifying causal relationships is a key premise of scientific research. The growth of observational data in different disciplines along with the availability of machine learning methods offers the possibility of using an empirical approach to identifying potential causal relationships, to deepen our understandings of causal behavior and to build theories accordingly. Conventional methods of causality inference from observational data require a considerable length of time series data to capture cause-effect relationship. We find that potential causal relationships can be inferred from the composition of one step transition rates to and from an event. Also known as Markov chain, one step transition rates are a commonly available resource in different scientific disciplines. Here we introduce a simple, effective and computationally efficient method that we termed 'Causality Inference using Composition of Transitions CICT' to reveal causal structure with high accuracy. We characterize the differences in causes,...
Johnston, Steven
2010-01-01
Causal set theory provides a model of discrete spacetime in which spacetime events are represented by elements of a causal set---a locally finite, partially ordered set in which the partial order represents the causal relationships between events. The work presented here describes a model for matter on a causal set, specifically a theory of quantum scalar fields on a causal set spacetime background. The work starts with a discrete path integral model for particles on a causal set. Here quantum mechanical amplitudes are assigned to trajectories within the causal set. By summing these over all trajectories between two spacetime events we obtain a causal set particle propagator. With a suitable choice of amplitudes this is shown to agree (in an appropriate sense) with the retarded propagator for the Klein-Gordon equation in Minkowski spacetime. This causal set propagator is then used to define a causal set analogue of the Pauli-Jordan function that appears in continuum quantum field theories. A quantum scalar fi...
Howard, Eric M
2016-01-01
We analyze spacetimes with horizons and study the thermodynamic aspects of causal horizons, suggesting that the resemblance between gravitational and thermodynamic systems has a deeper quantum mechanical origin. We find that the observer dependence of such horizons is a direct consequence of associating a temperature and entropy to a spacetime. The geometrical picture of a horizon acting as a one-way membrane for information flow can be accepted as a natural interpretation of assigning a quantum field theory to a spacetime with boundary, ultimately leading to a close connection with thermodynamics.
Quantum information causality.
Pitalúa-García, Damián
2013-05-24
How much information can a transmitted physical system fundamentally communicate? We introduce the principle of quantum information causality, which states the maximum amount of quantum information that a quantum system can communicate as a function of its dimension, independently of any previously shared quantum physical resources. We present a new quantum information task, whose success probability is upper bounded by the new principle, and show that an optimal strategy to perform it combines the quantum teleportation and superdense coding protocols with a task that has classical inputs.
Causality and Micro-Causality in Curved Spacetime
Hollowood, Timothy J.; Shore, Graham M.
2007-01-01
We consider how causality and micro-causality are realised in QED in curved spacetime. The photon propagator is found to exhibit novel non-analytic behaviour due to vacuum polarization, which invalidates the Kramers-Kronig dispersion relation and calls into question the validity of micro-causality in curved spacetime. This non-analyticity is ultimately related to the generic focusing nature of congruences of geodesics in curved spacetime, as implied by the null energy condition, and the exist...
DEFF Research Database (Denmark)
Nielsen, Ulla Gro; Hazell, Alan Charles; Skibsted, Jørgen Bengaard
2010-01-01
resonances are sensitive to intermolecular interactions specific to each crystal phase. The solid-state V-51 MAS NMR spectroscopic data show that the different phases do not co-precipitate but the concentration of the solute (which can be either 1 or 2) can vary. Thus co-crystallised mixtures of 1 and 2 can...... be classed as a molecular mixture capable of forming continuous solid solutions....... for the vanadium atoms of the two complexes mean that V-51 solution state and MAS NMR spectroscopy can be used to determine the concentration of 1 and 2 in bulk samples. Significantly, however, V-51 MAS NMR spectroscopy also reports on the identity of the crystal phase. This is possible because the isotropic V-51...
Energy Technology Data Exchange (ETDEWEB)
Khayrullin, S.R.; Firsov, I.A.; Ongoyev, V.M.; Shekhtman, E.N.; Taskarin, B.T.
1983-01-01
A plugging mixture is proposed which contains triethanolamine, caustic soda, water and an additive. It is distinguished by the fact that in order to reduce the cost of the mixture while preserving its operational qualities, it additionally contains clay powder and as the additive, ground limestone with the following component ratio in percent by mass: ground limestone, 50 to 60; triethanolamine, 0.1 to 0.15; caustic soda, 2 to 3; clay powder, 8 to 10 and water the remainder. The mixture is distinguished by the fact that the ground limestone has a specific surface of 2,000 to 3,000 square centimeters per gram.
Causal events enter awareness faster than non-causal events
Wagemans, Johan; de-Wit, Lee
2017-01-01
Philosophers have long argued that causality cannot be directly observed but requires a conscious inference (Hume, 1967). Albert Michotte however developed numerous visual phenomena in which people seemed to perceive causality akin to primary visual properties like colour or motion (Michotte, 1946). Michotte claimed that the perception of causality did not require a conscious, deliberate inference but, working over 70 years ago, he did not have access to the experimental methods to test this claim. Here we employ Continuous Flash Suppression (CFS)—an interocular suppression technique to render stimuli invisible (Tsuchiya & Koch, 2005)—to test whether causal events enter awareness faster than non-causal events. We presented observers with ‘causal’ and ‘non-causal’ events, and found consistent evidence that participants become aware of causal events more rapidly than non-causal events. Our results suggest that, whilst causality must be inferred from sensory evidence, this inference might be computed at low levels of perceptual processing, and does not depend on a deliberative conscious evaluation of the stimulus. This work therefore supports Michotte’s contention that, like colour or motion, causality is an immediate property of our perception of the world. PMID:28149698
Friston, K J; Harrison, L; Penny, W
2003-08-01
In this paper we present an approach to the identification of nonlinear input-state-output systems. By using a bilinear approximation to the dynamics of interactions among states, the parameters of the implicit causal model reduce to three sets. These comprise (1) parameters that mediate the influence of extrinsic inputs on the states, (2) parameters that mediate intrinsic coupling among the states, and (3) [bilinear] parameters that allow the inputs to modulate that coupling. Identification proceeds in a Bayesian framework given known, deterministic inputs and the observed responses of the system. We developed this approach for the analysis of effective connectivity using experimentally designed inputs and fMRI responses. In this context, the coupling parameters correspond to effective connectivity and the bilinear parameters reflect the changes in connectivity induced by inputs. The ensuing framework allows one to characterise fMRI experiments, conceptually, as an experimental manipulation of integration among brain regions (by contextual or trial-free inputs, like time or attentional set) that is revealed using evoked responses (to perturbations or trial-bound inputs, like stimuli). As with previous analyses of effective connectivity, the focus is on experimentally induced changes in coupling (cf., psychophysiologic interactions). However, unlike previous approaches in neuroimaging, the causal model ascribes responses to designed deterministic inputs, as opposed to treating inputs as unknown and stochastic.
Relationship of causal effects in a causal chain and related inference
Institute of Scientific and Technical Information of China (English)
GENG Zhi; HE Yangbo; WANG Xueli
2004-01-01
This paper discusses the relationship among the total causal effect and local causal effects in a causal chain and identifiability of causal effects. We show a transmission relationship of causal effects in a causal chain. According to the relationship, we give an approach to eliminating confounding bias through controlling for intermediate variables in a causal chain.
Experimental test of nonlocal causality.
Ringbauer, Martin; Giarmatzi, Christina; Chaves, Rafael; Costa, Fabio; White, Andrew G; Fedrizzi, Alessandro
2016-08-01
Explaining observations in terms of causes and effects is central to empirical science. However, correlations between entangled quantum particles seem to defy such an explanation. This implies that some of the fundamental assumptions of causal explanations have to give way. We consider a relaxation of one of these assumptions, Bell's local causality, by allowing outcome dependence: a direct causal influence between the outcomes of measurements of remote parties. We use interventional data from a photonic experiment to bound the strength of this causal influence in a two-party Bell scenario, and observational data from a Bell-type inequality test for the considered models. Our results demonstrate the incompatibility of quantum mechanics with a broad class of nonlocal causal models, which includes Bell-local models as a special case. Recovering a classical causal picture of quantum correlations thus requires an even more radical modification of our classical notion of cause and effect.
Experimental test of nonlocal causality
Ringbauer, Martin; Giarmatzi, Christina; Chaves, Rafael; Costa, Fabio; White, Andrew G.; Fedrizzi, Alessandro
2016-01-01
Explaining observations in terms of causes and effects is central to empirical science. However, correlations between entangled quantum particles seem to defy such an explanation. This implies that some of the fundamental assumptions of causal explanations have to give way. We consider a relaxation of one of these assumptions, Bell’s local causality, by allowing outcome dependence: a direct causal influence between the outcomes of measurements of remote parties. We use interventional data from a photonic experiment to bound the strength of this causal influence in a two-party Bell scenario, and observational data from a Bell-type inequality test for the considered models. Our results demonstrate the incompatibility of quantum mechanics with a broad class of nonlocal causal models, which includes Bell-local models as a special case. Recovering a classical causal picture of quantum correlations thus requires an even more radical modification of our classical notion of cause and effect. PMID:27532045
Causal 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.
Analysis of asphalt mixtures on town roads
Glavica, Primož
2006-01-01
Asphalt mixtures are most commonly used composite for construction of top layers of different drive ways. By definition asphalt mixtures are composed of crushed rock, fill, bitumen and additives. Percentage of individual components wary according to the purpose asphalt mixture is to be used for. Asphalt mixtures must be capable of enduring different types of load. According to the type of load asphalt mixtures are divided into asphalt mixtures used for supporting layers and asp...
Causal evolution of wave packets
Eckstein, Michał
2016-01-01
Drawing from the optimal transport theory adapted to the relativistic setting we formulate the principle of a causal flow of probability and apply it in the wave packet formalism. We demonstrate that whereas the Dirac system is causal, the relativistic-Schr\\"odinger Hamiltonian impels a superluminal evolution of probabilities. We quantify the causality breakdown in the latter system and argue that, in contrast to the popular viewpoint, it is not related to the localisation properties of the states.
Granger causality for circular variables
Energy Technology Data Exchange (ETDEWEB)
Angelini, Leonardo; Pellicoro, Mario [Istituto Nazionale di Fisica Nucleare, Sezione di Bari (Italy); Dipartimento di Fisica, University of Bari (Italy); Stramaglia, Sebastiano, E-mail: sebastiano.stramaglia@ba.infn.i [Istituto Nazionale di Fisica Nucleare, Sezione di Bari (Italy); Dipartimento di Fisica, University of Bari (Italy)
2009-06-29
In this Letter we discuss the use of Granger causality to the analyze systems of coupled circular variables, by modifying a recently proposed method for multivariate analysis of causality. We show the application of the proposed approach on several Kuramoto systems, in particular one living on networks built by preferential attachment and a model for the transition from deeply to lightly anaesthetized states. Granger causalities describe the flow of information among variables.
Causality Statistical Perspectives and Applications
Berzuini, Carlo; Bernardinell, Luisa
2012-01-01
A state of the art volume on statistical causality Causality: Statistical Perspectives and Applications presents a wide-ranging collection of seminal contributions by renowned experts in the field, providing a thorough treatment of all aspects of statistical causality. It covers the various formalisms in current use, methods for applying them to specific problems, and the special requirements of a range of examples from medicine, biology and economics to political science. This book:Provides a clear account and comparison of formal languages, concepts and models for statistical causality. Addr
Energy Technology Data Exchange (ETDEWEB)
Sellami, Badreddine, E-mail: sellamibadreddine@gmail.com [Laboratory of Environment Biomonitoring, Coastal Ecology Unit, Faculty of Sciences of Bizerta, University of Carthage, 7021 Zarzouna (Tunisia); Khazri, Abdelhafidh [Laboratory of Environment Biomonitoring, Coastal Ecology Unit, Faculty of Sciences of Bizerta, University of Carthage, 7021 Zarzouna (Tunisia); Mezni, Amine [Unit of Research 99/UR12-30, Department of Chemistry, Faculty of Sciences of Bizerte, 7021 Jarzouna (Tunisia); Louati, Héla; Dellali, Mohamed; Aissa, Patricia; Mahmoudi, Ezzeddine; Beyrem, Hamouda [Laboratory of Environment Biomonitoring, Coastal Ecology Unit, Faculty of Sciences of Bizerta, University of Carthage, 7021 Zarzouna (Tunisia); Sheehan, David, E-mail: d.sheehan@ucc.ie [Environmental Research Institute and Department of Biochemistry, University College Cork, Western Gateway Building, Western Road, Cork (Ireland)
2015-01-15
Highlights: • We assessed toxicity of anthracene, permethrin and their mixture on clams. • Tissue and stressor-dependent changes were observed in biochemical responses. • Permethrin induces phase transition from aragonite to calcite in shell structure. • Interactive effects were observed on digestive gland and gill biomarkers. • Both approaches give new vision to risk assessment of organic pollution. - Abstract: Anthracene (ANT) and permethrin (PER) are two of the more toxic compounds reaching the marine environment. This study aimed to determine the impact of these molecules on Venerupis decussata, an economically important species cultured on the Tunisian coast. Shell structure and its possible transformation upon exposure to the two contaminants were studied by X-ray diffraction and gravimetric analyses. Results revealed a phase transition in shell composition from aragonite to calcite after PER exposure, to a mixture of PER and ANT (Mix) but not for ANT alone. Catalase (CAT), superoxide dismutase (SOD) and glutathione transferase (GST) activities were determined in digestive gland and gills after exposure to ANT, PER and Mix to assess the impact of the contamination on the oxidative status of V. decussata. Enzyme activities increased in the digestive gland after PER treatment and in the gills after ANT treatment. PER exposure significantly reduced the levels of free thiols and increased levels of carbonylated proteins in the digestive gland, as compared to controls. In contrast, ANT exposure significantly reduced free thiols and increased the number of carbonylated proteins in the gills. Mix induced additive effects as measured by both enzymatic and proteomic approaches. The present study suggests that PER has a strong effect on shell structure; that PER and ANT exposure generate compound-dependent oxidative stress in the tissues of V. decussata and that a mixture of the two compounds has synergistic effects on biochemical response.
Kamio, Michiya; Ko, Ko-Chun; Zheng, Shilong; Wang, Binghe; Collins, Stacy L; Gadda, Giovanni; Tai, Phang C; Derby, Charles D
2009-01-01
Escapin is an L-amino acid oxidase in the ink of a marine snail, the sea hare Aplysia californica, which oxidizes L-lysine (1) to produce a mixture of chemicals which is antipredatory and antimicrobial. The goal of our study was to determine the identity and relative abundance of the constituents of this mixture, using molecules generated enzymatically with escapin and also using products of organic syntheses. We examined this mixture under the natural range of pH values for ink-from approximately 5 at full strength to approximately 8 when fully diluted in sea water. The enzymatic reaction likely forms an equilibrium mixture containing the linear form alpha-keto-epsilon-aminocaproic acid (2), the cyclic imine Delta(1)-piperidine-2-carboxylic acid (3), the cyclic enamine Delta(2)-piperidine-2-carboxylic acid (4), possibly the linear enol 6-amino-2-hydroxy-hex-2-enoic acid (7), the alpha-dihydroxy acid 6-amino-2,2-dihydroxy-hexanoic acid (8), and the cyclic aminol 2-hydroxy-piperidine-2-carboxylic acid (9). Using NMR and mass spectroscopy, we show that 3 is the major component of this enzymatic product at any pH, but at more basic conditions, the equilibrium shifts to produce relatively more 4, and at acidic conditions, the equilibrium shifts to produce relatively more 2, 7, and/or 9. Studies of escapin's enzyme kinetics demonstrate that because of the high concentrations of escapin and L-lysine in the ink secretion, millimolar concentrations of 3, H(2)O(2), and ammonia are produced, and also lower concentrations of 2, 4, 7, and 9 as a result. We also show that reactions of this mixture with H(2)O(2) produce delta-aminovaleric acid (5) and delta-valerolactam (6), with 6 being the dominant component under the naturally acidic conditions of ink. Thus, the product of escapin's action on L-lysine contains an equilibrium mixture that is more complex than previously known for any L-amino acid oxidase.
Structural Equations and Causal Explanations: Some Challenges for Causal SEM
Markus, Keith A.
2010-01-01
One common application of structural equation modeling (SEM) involves expressing and empirically investigating causal explanations. Nonetheless, several aspects of causal explanation that have an impact on behavioral science methodology remain poorly understood. It remains unclear whether applications of SEM should attempt to provide complete…
The Cradle of Causal Reasoning: Newborns' Preference for Physical Causality
Mascalzoni, Elena; Regolin, Lucia; Vallortigara, Giorgio; Simion, Francesca
2013-01-01
Perception of mechanical (i.e. physical) causality, in terms of a cause-effect relationship between two motion events, appears to be a powerful mechanism in our daily experience. In spite of a growing interest in the earliest causal representations, the role of experience in the origin of this sensitivity is still a matter of dispute. Here, we…
Identifiability of causal effect for a simple causal model
Institute of Scientific and Technical Information of China (English)
郑忠国; 张艳艳; 童行伟
2002-01-01
Counterfactual model is put forward to discuss the causal inference in the directed acyclic graph and its corresponding identifiability is thus studied with the ancillary information based on conditional independence. It is shown that the assumption of ignorability can be expanded to the assumption of replaceability,under which the causal efiects are identifiable.
Inferring deterministic causal relations
Daniusis, Povilas; Mooij, Joris; Zscheischler, Jakob; Steudel, Bastian; Zhang, Kun; Schoelkopf, Bernhard
2012-01-01
We consider two variables that are related to each other by an invertible function. While it has previously been shown that the dependence structure of the noise can provide hints to determine which of the two variables is the cause, we presently show that even in the deterministic (noise-free) case, there are asymmetries that can be exploited for causal inference. Our method is based on the idea that if the function and the probability density of the cause are chosen independently, then the distribution of the effect will, in a certain sense, depend on the function. We provide a theoretical analysis of this method, showing that it also works in the low noise regime, and link it to information geometry. We report strong empirical results on various real-world data sets from different domains.
Sellami, Badreddine; Khazri, Abdelhafidh; Mezni, Amine; Louati, Héla; Dellali, Mohamed; Aissa, Patricia; Mahmoudi, Ezzeddine; Beyrem, Hamouda; Sheehan, David
2015-01-01
Anthracene (ANT) and permethrin (PER) are two of the more toxic compounds reaching the marine environment. This study aimed to determine the impact of these molecules on Venerupis decussata, an economically important species cultured on the Tunisian coast. Shell structure and its possible transformation upon exposure to the two contaminants were studied by X-ray diffraction and gravimetric analyses. Results revealed a phase transition in shell composition from aragonite to calcite after PER exposure, to a mixture of PER and ANT (Mix) but not for ANT alone. Catalase (CAT), superoxide dismutase (SOD) and glutathione transferase (GST) activities were determined in digestive gland and gills after exposure to ANT, PER and Mix to assess the impact of the contamination on the oxidative status of V. decussata. Enzyme activities increased in the digestive gland after PER treatment and in the gills after ANT treatment. PER exposure significantly reduced the levels of free thiols and increased levels of carbonylated proteins in the digestive gland, as compared to controls. In contrast, ANT exposure significantly reduced free thiols and increased the number of carbonylated proteins in the gills. Mix induced additive effects as measured by both enzymatic and proteomic approaches. The present study suggests that PER has a strong effect on shell structure; that PER and ANT exposure generate compound-dependent oxidative stress in the tissues of V. decussata and that a mixture of the two compounds has synergistic effects on biochemical response.
Griffiths, Thomas L.; Tenenbaum, Joshua B.
2009-01-01
Inducing causal relationships from observations is a classic problem in scientific inference, statistics, and machine learning. It is also a central part of human learning, and a task that people perform remarkably well given its notorious difficulties. People can learn causal structure in various settings, from diverse forms of data: observations…
Expert Causal Reasoning and Explanation.
Kuipers, Benjamin
The relationship between cognitive psychologists and researchers in artificial intelligence carries substantial benefits for both. An ongoing investigation in causal reasoning in medical problem solving systems illustrates this interaction. This paper traces a dialectic of sorts in which three different types of causal resaoning for medical…
Introduction to causal dynamical triangulations
DEFF Research Database (Denmark)
Görlich, Andrzej
2013-01-01
The method of causal dynamical triangulations is a non-perturbative and background-independent approach to quantum theory of gravity. In this review we present recent results obtained within the four dimensional model of causal dynamical triangulations. We describe the phase structure of the mode...
Friederich, Simon
2015-01-01
There is widespread belief in a tension between quantum theory and special relativity, motivated by the idea that quantum theory violates J. S. Bell's criterion of local causality, which is meant to implement the causal structure of relativistic space-time. This paper argues that if one takes the es
Causal Inference and Developmental Psychology
Foster, E. Michael
2010-01-01
Causal inference is of central importance to developmental psychology. Many key questions in the field revolve around improving the lives of children and their families. These include identifying risk factors that if manipulated in some way would foster child development. Such a task inherently involves causal inference: One wants to know whether…
Heck, W. W.; Knott, W. M.; Stahel, E. P.; Ambrose, J. T.; Mccrimmon, J. N.; Engle, M.; Romanow, L. A.; Sawyer, A. G.; Tyson, J. D.
1980-01-01
The effects of solid rocket fuel (SRF) exhaust on selected plant and and insect species in the Merritt Island, Florida area was investigated in order to determine if the exhaust clouds generated by shuttle launches would adversely affect the native, plants of the Merritt Island Wildlife Refuge, the citrus production, or the beekeeping industry of the island. Conditions were simulated in greenhouse exposure chambers and field chambers constructed to model the ideal continuous stirred tank reactor. A plant exposure system was developed for dispensing and monitoring the two major chemicals in SRF exhaust, HCl and Al203, and for dispensing and monitoring SRF exhaust (controlled fuel burns). Plants native to Merritt Island, Florida were grown and used as test species. Dose-response relationships were determined for short term exposure of selected plant species to HCl, Al203, and mixtures of the two to SRF exhaust.
On causality of extreme events
Directory of Open Access Journals (Sweden)
Massimiliano Zanin
2016-06-01
Full Text Available Multiple metrics have been developed to detect causality relations between data describing the elements constituting complex systems, all of them considering their evolution through time. Here we propose a metric able to detect causality within static data sets, by analysing how extreme events in one element correspond to the appearance of extreme events in a second one. The metric is able to detect non-linear causalities; to analyse both cross-sectional and longitudinal data sets; and to discriminate between real causalities and correlations caused by confounding factors. We validate the metric through synthetic data, dynamical and chaotic systems, and data representing the human brain activity in a cognitive task. We further show how the proposed metric is able to outperform classical causality metrics, provided non-linear relationships are present and large enough data sets are available.
On causality of extreme events
2016-01-01
Multiple metrics have been developed to detect causality relations between data describing the elements constituting complex systems, all of them considering their evolution through time. Here we propose a metric able to detect causality within static data sets, by analysing how extreme events in one element correspond to the appearance of extreme events in a second one. The metric is able to detect non-linear causalities; to analyse both cross-sectional and longitudinal data sets; and to discriminate between real causalities and correlations caused by confounding factors. We validate the metric through synthetic data, dynamical and chaotic systems, and data representing the human brain activity in a cognitive task. We further show how the proposed metric is able to outperform classical causality metrics, provided non-linear relationships are present and large enough data sets are available. PMID:27330866
Directory of Open Access Journals (Sweden)
Mirjana N. Lukić-Anđelković
2009-10-01
Full Text Available U radu je prikazan način dobijanja i karakteristike trokomponentnih smeša RDX/Al/PS. Primenjen flegmatizator heksogena je termostabilni polimer polistiren čija je karakteristika da dobro prekriva. Primenjivan je konstantan sadržaj od 5% PS za različite sadržaje heksogena i aluminijuma. Sadržaj aluminijuma u smešama je 10, 15, 20 u 25% m/m. Ispitan je sastav i određena brzina detonacije. / The characteristics of three-component RDX/PS/Al mixtures have been described s well as the method for their preparation. Polystirene as a binder is a thermostable polymer with satisfactory characteristics for bonding explosives. The constant content of 5% m/m PS was applied for different contents of hexogen and aluminium. The content of Al in the mixtures was 10, 15, and 20% m/m. The composition of the bonded explosives was examined as well as the detonation velocity of these mixtures.
CausalTrail: Testing hypothesis using causal Bayesian networks.
Stöckel, Daniel; Schmidt, Florian; Trampert, Patrick; Lenhof, Hans-Peter
2015-01-01
Summary Causal Bayesian Networks are a special class of Bayesian networks in which the hierarchy directly encodes the causal relationships between the variables. This allows to compute the effect of interventions, which are external changes to the system, caused by e.g. gene knockouts or an administered drug. Whereas numerous packages for constructing causal Bayesian networks are available, hardly any program targeted at downstream analysis exists. In this paper we present CausalTrail, a tool for performing reasoning on causal Bayesian networks using the do-calculus. CausalTrail's features include multiple data import methods, a flexible query language for formulating hypotheses, as well as an intuitive graphical user interface. The program is able to account for missing data and thus can be readily applied in multi-omics settings where it is common that not all measurements are performed for all samples. Availability and Implementation CausalTrail is implemented in C++ using the Boost and Qt5 libraries. It can be obtained from https://github.com/dstoeckel/causaltrail.
Qiu, Y.T.; Smallegange, R.C.; Loon, van J.J.A.; Takken, W.
2011-01-01
Host-seeking behaviour of the anthropophilic malaria vector Anopheles gambiae sensu stricto (Diptera: Culicidae) is mediated predominantly by olfactory cues. Several hundreds of odour components have been identified from human emanations, but only a few have been proven to act as attractants or syne
The causal pie model: an epidemiological method applied to evolutionary biology and ecology.
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.
Energy Technology Data Exchange (ETDEWEB)
Steinberg, Aephraim M. [Institute for Experimental Physics, University of Vienna, Vienna (Austria)
2003-12-01
Experiment confirms that information cannot be transmitted faster than the speed of light. Ever since Einstein stated that nothing can travel faster than light, physicists have delighted in finding exceptions. One after another, observations of such 'superluminal' propagation have been made. However, while some image or pattern- such as the motion of a spotlight projected on a distant wall - might have appeared to travel faster than light, it seemed that there was no way to use the superluminal effect to transmit energy or information. In recent years, the superluminal propagation of light pulses through certain media has led to renewed controversy. In 1995, for example, Guenther Nimtz of the University of Cologne encoded Mozart's 40th Symphony on a microwave beam, which he claimed to have transmitted at a speed faster than light. Others maintain that such a violation of Einstein's speed limit would wreak havoc on our most fundamental ideas about causality, allowing an effect to precede its cause. Relativity teaches us that sending a signal faster than light would be equivalent to sending it backwards in time. (U.K.)
History, causality, and sexology.
Money, John
2003-08-01
In 1896, Krafft-Ebing published Psychopathia Sexualis. Popularly defined as hereditary weakness or taintedness in the family pedigree, degeneracy was called upon as a causal explanation for perversions of the sexual instinct. Although Krafft-Ebing accepted Karl Ulrichs proposal that homosexuality could be innate and probably located in the brain, he paid little attention to neuropathological sexology. Alfred Binet challenged Krafft-Ebing's orthodoxy by explaining fetishism in terms of associative learning, to which Krafft-Ebing's response was that only those with a hereditary taint would be vulnerable. Thus did the venerable nature-nurture antithesis maintain its rhetoric, even to the present day. Krafft-Ebing died too soon to meet the Freudian challenge of endopsychic determinism, and too soon also to encounter the idea of a developmental multivariate outcome of what I have termed the lovemap. Like other brain maps, for example the languagemap, the lovemap requires an intact human brain in which to develop. The personalized content of the lovemap has access to the brain by way of the special senses.
Causal Selection and Counterfactual Reasoning
Directory of Open Access Journals (Sweden)
William Jiménez-Leal
2013-01-01
Full Text Available El trabajo defiende la posición según la cual el pensamiento contrafactual depende de nuestra representación causal del mundo y, en este sentido, argumenta que existe una estrecha relación entre el razonamiento causal y el contrafactual. Se lleva a cabo una crítica a la teoría de la disociación de juicios de Mandel (Mandel, 2003b, que defiende la independencia funcional entre el proceso de selección causal y el razonamiento contrafactual en el contexto de la selección causal. En los experimentos realizados se manipularon algunos elementos de la semántica de la tarea con el fin de ilustrar aquellos casos en los que no se da la disociación entre el razonamiento causal y el contrafactual. En el Experimento 1, el nivel de descripción del evento objetivo se manipuló en una tarea de generación de listas y evaluación. El Experimento 2 replicó los hallazgos del Experimento 1 utilizando un sistema de codificación alternativo, mientras que el Experimento 3 realizó lo mismo utilizando un formato de respuesta alternativo. Los resultados de los experimentos apoyan la concepción del entendimiento causal propuesta por los modelos mentales causales.
Energy Technology Data Exchange (ETDEWEB)
Goracci, G., E-mail: sckgorag@ehu.es; Arbe, A. [Centro de Física de Materiales (CFM), CSIC–UPV/EHU–Materials Physics Center - MPC, Paseo Manuel de Lardizabal 5, 20018 San Sebastián (Spain); Alegría, A. [Centro de Física de Materiales (CFM), CSIC–UPV/EHU–Materials Physics Center - MPC, Paseo Manuel de Lardizabal 5, 20018 San Sebastián (Spain); Departamento de Física de Materiales (UPV/EHU), Apartado 1072, 20080 San Sebastián (Spain); Lohstroh, W. [Heinz Maier-Leibnitz Zentrum, Technische Universität München, Lichtenbergstraße 1, D-85748 Garching (Germany); Su, Y. [Jülich Centre for Neutron Science JCNS, Forschungszentrum Jülich GmbH, Outstation at MLZ, Lichtenbergstraße 1, 85747 Garching (Germany); Colmenero, J. [Centro de Física de Materiales - CFM, CSIC–UPV/EHU–Materials Physics Center - MPC, Paseo Manuel de Lardizabal 5, 20018 San Sebastián (Spain); Departamento de Física de Materiales (UPV/EHU), Apartado 1072, 20080 San Sebastián (Spain); Donostia International Physics Center, Paseo Manuel de Lardizabal 4, 20018 San Sebastián (Spain)
2015-09-07
We have investigated a mixture of poly(2-(dimethylamino)ethyl methacrylate) (PDMAEMA) and tetrahydrofuran (THF) (70 wt. % PDMAEMA/30 wt. % THF) by combining dielectric spectroscopy and quasielastic neutron scattering (QENS) on a labelled sample, focusing on the dynamics of the THF molecules. Two independent processes have been identified. The “fast” one has been qualified as due to an internal motion of the THF ring leading to hydrogen displacements of about 3 Å with rather broadly distributed activation energies. The “slow” process is characterized by an Arrhenius-like temperature dependence of the characteristic time which persists over more than 9 orders of magnitude in time. The QENS results evidence the confined nature of this process, determining a size of about 8 Å for the volume within which THF hydrogens’ motions are restricted. In a complementary way, we have also investigated the structural features of the sample. This study suggests that THF molecules are well dispersed among side-groups nano-domains in the polymer matrix, ruling out a significant presence of clusters of solvent. Such a good dispersion, together with a rich mobility of the local environment, would prevent cooperativity effects to develop for the structural relaxation of solvent molecules, frustrating thereby the emergence of Vogel-Fulcher-like behavior, at least in the whole temperature interval investigated.
The Central Dogma as a thesis of causal specificity.
Weber, Marcel
2006-01-01
I present a reconstruction of F.H.C. Crick's two 1957 hypotheses 'Sequence Hypothesis' and 'Central Dogma' in terms of a contemporary philosophical theory of causation. Analyzing in particular the experimental evidence that Crick cited, I argue that these hypotheses can be understood as claims about the actual difference-making cause in protein synthesis. As these hypotheses are only true if restricted to certain nucleic acids in certain organisms, I then examine the concept of causal specificity and its potential to counter claims about causal parity of DNA and other cellular components. I first show that causal specificity is a special kind of invariance under interventions, namely invariance of generalizations that range over finite sets of discrete variables. Then, I show that this notion allows the articulation of a middle ground in the debate over causal parity.
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...
On causality of extreme events
Zanin, Massimiliano
2016-01-01
Multiple metrics have been developed to detect causality relations between data describing the elements constituting complex systems, all of them considering their evolution through time. Here we propose a metric able to detect causality within static data sets, by analysing how extreme events in one element correspond to the appearance of extreme events in a second one. The metric is able to detect both linear and non-linear causalities; to analyse both cross-sectional and longitudinal data sets; and to discriminate between real causalities and correlations caused by confounding factors. We validate the metric through synthetic data, dynamical and chaotic systems, and data representing the human brain activity in a cognitive task.
Fluctuations in Relativistic Causal Hydrodynamics
Kumar, Avdhesh; Mishra, Ananta P
2013-01-01
The formalism to calculate the hydrodynamics fluctuation using the quasi-stationary fluctuation theory of Onsager to the relativistic Navier-Stokes hydrodynamics is already known. In this work we calculate hydrodynamic fluctuations in relativistic causal theory of Muller, Israel and Stewart and other related causal hydrodynamic theories. We show that expressions for the Onsager coefficients and the correlation functions have form similar to the ones obtained by using Navier-Stokes equation. However, temporal evolution of the correlation functions obtained using MIS and the other causal theories can be significantly different than the correlation functions obtained using the Navier-Stokes equation. Finally, as an illustrative example, we explicitly plot the correlation functions obtained using the causal-hydrodynamics theories and compare them with correlation functions obtained by earlier authors using the expanding boost-invariant (Bjorken) flows.
Correlation Measure Equivalence in Dynamic Causal Structures
Gyongyosi, Laszlo
2016-01-01
We prove an equivalence transformation between the correlation measure functions of the causally-unbiased quantum gravity space and the causally-biased standard space. The theory of quantum gravity fuses the dynamic (nonfixed) causal structure of general relativity and the quantum uncertainty of quantum mechanics. In a quantum gravity space, the events are causally nonseparable and all time bias vanishes, which makes it no possible to use the standard causally-biased entropy and the correlation measure functions. Since a corrected causally-unbiased entropy function leads to an undefined, obscure mathematical structure, in our approach the correction is made in the data representation of the causally-unbiased space. We prove that the standard causally-biased entropy function with a data correction can be used to identify correlations in dynamic causal structures. As a corollary, all mathematical properties of the causally-biased correlation measure functions are preserved in the causally-unbiased space. The eq...
Bianchi-I cosmology from causal thermodynamics
Bittencourt, Eduardo; Klippert, Renato
2016-01-01
We investigate diagonal Bianchi-I spacetimes in the presence of viscous fluids by using the shear and the anisotropic pressure components as the basic variables, where the viscosity is driven by the (second-order) causal thermodynamics. A few exact solutions are presented, among which we mention the anisotropic versions of de Sitter/anti-de Sitter geometries as well as an asymptotically isotropic spacetime presenting an effective constant cosmic acceleration without any cosmological constant. The qualitative analysis of the solutions for barotropic fluids with linear equations of state suggests that the behaviour is quite general.
An introduction to causal inference.
Pearl, Judea
2010-02-26
This paper summarizes recent advances in causal inference and underscores the paradigmatic shifts that must be undertaken in moving from traditional statistical analysis to causal analysis of multivariate data. Special emphasis is placed on the assumptions that underlie all causal inferences, the languages used in formulating those assumptions, the conditional nature of all causal and counterfactual claims, and the methods that have been developed for the assessment of such claims. These advances are illustrated using a general theory of causation based on the Structural Causal Model (SCM) described in Pearl (2000a), which subsumes and unifies other approaches to causation, and provides a coherent mathematical foundation for the analysis of causes and counterfactuals. In particular, the paper surveys the development of mathematical tools for inferring (from a combination of data and assumptions) answers to three types of causal queries: those about (1) the effects of potential interventions, (2) probabilities of counterfactuals, and (3) direct and indirect effects (also known as "mediation"). Finally, the paper defines the formal and conceptual relationships between the structural and potential-outcome frameworks and presents tools for a symbiotic analysis that uses the strong features of both. The tools are demonstrated in the analyses of mediation, causes of effects, and probabilities of causation.
Causality and Tense - two temporal structure builders
Oversteegen, E.
2005-01-01
By force of causes precede effects, causality contributes to the temporal meaning of discourse. In case of semantic causal relations, this contribution is straightforward, but in case of epistemic causal relations, it is not. In order to gain insight into the semantics of epistemic causal relations,
Zhao, An-Xin; Tang, Xiao-Jun; Zhang, Zhong-Hua; Liu, Jun-Hua
2014-10-01
The generalized two-dimensional correlation spectroscopy and Fourier transform infrared were used to identify hydrocarbon isomers in the mixed gases for absorption spectra resolution enhancement. The Fourier transform infrared spectrum of n-butane and iso-butane and the two-dimensional correlation infrared spectrum of concentration perturbation were used for analysis as an example. The all band and the main absorption peak wavelengths of Fourier transform infrared spectrum for single component gas showed that the spectra are similar, and if they were mixed together, absorption peaks overlap and peak is difficult to identify. The synchronous and asynchronous spectrum of two-dimensional correlation spectrum can clearly identify the iso-butane and normal butane and their respective characteristic absorption peak intensity. Iso-butane has strong absorption characteristics spectrum lines at 2,893, 2,954 and 2,893 cm(-1), and n-butane at 2,895 and 2,965 cm(-1). The analysis result in this paper preliminary verified that the two-dimensional infrared correlation spectroscopy can be used for resolution enhancement in Fourier transform infrared spectrum quantitative analysis.
Causal Stability Conditions for General Relativistic Spacetimes
Howard, E M
2016-01-01
A brief overview of some open questions in general relativity with important consequences for causality theory is presented, aiming to a better understanding of the causal structure of the spacetime. Special attention is accorded to the problem of fundamental causal stability conditions. Several questions are raised and some of the potential consequences of recent results regarding the causality problem in general relativity are presented. A key question is whether causality violating regions are locally allowed. The new concept of almost stable causality is introduced; meanwhile, related conditions and criteria for the stability and almost stability of the causal structure are discussed.
Human causal discovery from observational data.
1996-01-01
Utilizing Bayesian belief networks as a model of causality, we examined medical students' ability to discover causal relationships from observational data. Nine sets of patient cases were generated from relatively simple causal belief networks by stochastic simulation. Twenty participants examined the data sets and attempted to discover the underlying causal relationships. Performance was poor in general, except at discovering the absence of a causal relationship. This work supports the poten...
The Geometry of Small Causal Cones
Jubb, Ian
2016-01-01
We derive a formula for the spacetime volume of a small causal cone. We use this formula within the context of causal set theory to construct causal set expressions for certain geometric quantities relating to a spacetime with a spacelike hypersurface. We also consider a scalar field on the causal set, and obtain causal set expressions relating to its normal derivatives with respect to the hypersurface.
Causality and Primordial Tensor Modes
Baumann, Daniel
2009-01-01
We introduce the real space correlation function of $B$-mode polarization of the cosmic microwave background (CMB) as a probe of superhorizon tensor perturbations created by inflation. By causality, any non-inflationary mechanism for gravitational wave production after reheating, like global phase transitions or cosmic strings, must have vanishing correlations for angular separations greater than the angle subtended by the particle horizon at recombination, i.e. $\\theta \\gtrsim 2^\\circ$. Since ordinary $B$-modes are defined non-locally in terms of the Stokes parameters $Q$ and $U$ and therefore don't have to respect causality, special care is taken to define `causal $\\tilde B$-modes' for the analysis. We compute the real space $\\tilde B$-mode correlation function for inflation and discuss its detectability on superhorizon scales where it provides an unambiguous test of inflationary gravitational waves. The correct identification of inflationary tensor modes is crucial since it relates directly to the energy s...
Causal reasoning with mental models.
Khemlani, Sangeet S; Barbey, Aron K; Johnson-Laird, Philip N
2014-01-01
This paper outlines the model-based theory of causal reasoning. It postulates that the core meanings of causal assertions are deterministic and refer to temporally-ordered sets of possibilities: A causes B to occur means that given A, B occurs, whereas A enables B to occur means that given A, it is possible for B to occur. The paper shows how mental models represent such assertions, and how these models underlie deductive, inductive, and abductive reasoning yielding explanations. It reviews evidence both to corroborate the theory and to account for phenomena sometimes taken to be incompatible with it. Finally, it reviews neuroscience evidence indicating that mental models for causal inference are implemented within lateral prefrontal cortex.
Causal reasoning with mental models
Directory of Open Access Journals (Sweden)
Sangeet eKhemlani
2014-10-01
Full Text Available This paper outlines the model-based theory of causal reasoning. It postulates that the core meanings of causal assertions are deterministic and refer to temporally-ordered sets of possibilities: A causes B to occur means that given A, B occurs, whereas A enables B to occur means that given A, it is possible for B to occur. The paper shows how mental models represent such assertions, and how these models underlie deductive, inductive, and abductive reasoning yielding explanations. It reviews evidence both to corroborate the theory and to account for phenomena sometimes taken to be incompatible with it. Finally, it reviews neuroscience evidence indicating that mental models for causal inference are implemented within lateral prefrontal cortex.
Causal Models for Risk Management
Directory of Open Access Journals (Sweden)
Neysis Hernández Díaz
2013-12-01
Full Text Available In this work a study about the process of risk management in major schools in the world. The project management tools worldwide highlights the need to redefine risk management processes. From the information obtained it is proposed the use of causal models for risk analysis based on information from the project or company, say risks and the influence thereof on the costs, human capital and project requirements and detect the damages of a number of tasks without tribute to the development of the project. A study on the use of causal models as knowledge representation techniques causal, among which are the Fuzzy Cognitive Maps (DCM and Bayesian networks, with the most favorable MCD technique to use because it allows modeling the risk information witho ut having a knowledge base either itemize.
Gravitation, Causality, and Quantum Consistency
Hertzberg, Mark P
2016-01-01
We examine the role of consistency with causality and quantum mechanics in determining the properties of gravitation. We begin by constructing two different classes of interacting theories of massless spin 2 particles -- gravitons. One involves coupling the graviton with the lowest number of derivatives to matter, the other involves coupling the graviton with higher derivatives to matter, making use of the linearized Riemann tensor. The first class requires an infinite tower of terms for consistency, which is known to lead uniquely to general relativity. The second class only requires a finite number of terms for consistency, which appears as a new class of theories of massless spin 2. We recap the causal consistency of general relativity and show how this fails in the second class for the special case of coupling to photons, exploiting related calculations in the literature. In an upcoming publication [1] this result is generalized to a much broader set of theories. Then, as a causal modification of general ...
Statistics, Causality and Bell's theorem
Gill, Richard D
2012-01-01
Bell's (1964) theorem is popularly supposed to establish the non-locality of quantum physics as a mathematical-physical theory. Building from this, observed violation of Bell's inequality in experiments such as that of Aspect and coworkers (1982) is popularly supposed to provide empirical proof of non-locality in the real world. This paper reviews recent work on Bell's theorem, linking it to issues in causality as understood by statisticians. The paper starts with a new proof of a strong (finite sample) version of Bell's theorem which relies only on elementary arithmetic and (counting) probability. This proof underscores the fact that Bell's theorem tells us that quantum theory is incompatible with the conjunction of three cherished and formerly uncontroversial physical principles, nicknamed here locality, realism, and freedom. The first, locality, is obviously connected to causality: causal influences need time to propagate spatially. Less obviously, the other two principles, realism and freedom, are also fo...
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.
On Causality in Dynamical Systems
Harnack, Daniel
2016-01-01
Identification of causal links is fundamental for the analysis of complex systems. In dynamical systems, however, nonlinear interactions may hamper separability of subsystems which poses a challenge for attempts to determine the directions and strengths of their mutual influences. We found that asymmetric causal influences between parts of a dynamical system lead to characteristic distortions in the mappings between the attractor manifolds reconstructed from respective local observables. These distortions can be measured in a model-free, data-driven manner. This approach extends basic intuitions about cause-effect relations to deterministic dynamical systems and suggests a mathematically well defined explanation of results obtained from previous methods based on state space reconstruction.
Cohomology with causally restricted supports
Khavkine, Igor
2014-01-01
De Rham cohomology with spacelike compact and timelike compact supports has recently been noticed to be of importance for understanding the structure of classical and quantum field theories on curved spacetimes. We compute these cohomology groups for globally hyperbolic spacetimes in terms of their standard de Rham cohomologies. The calculation exploits the fact that the de Rham-d'Alambert wave operator can be extended to a chain map that is homotopic to zero and that its causal Green function fits into a convenient exact sequence. This method extends also to the Calabi (or Killing-Riemann-Bianchi) complex and possibly other differential complexes. We also discuss generalized causal structures and functoriality.
Kolmogorov Complexity, Causality And Spin
Shayda, Dara O
2012-01-01
A novel topological and computational method for 'motion' is described. Motion is constrained by inequalities in terms of Kolmogorov Complexity. Causality is obtained as the output of a high-pass filter, passing through only high values of Kolmogorov Complexity. Motion under the electromagnetic field described with immediate relationship with Subscript[G, 2] Holonomy group and its corresponding dense free 2-subgroup. Similar to Causality, Spin emerges as an immediate and inevitable consequence of high values of Kolmogorov Complexity. Consequently, the physical laws are nothing but a low-pass filter for small values of Kolmogorov Complexity.
Information thermodynamics on causal networks.
Ito, Sosuke; Sagawa, Takahiro
2013-11-01
We study nonequilibrium thermodynamics of complex information flows induced by interactions between multiple fluctuating systems. Characterizing nonequilibrium dynamics by causal networks (i.e., Bayesian networks), we obtain novel generalizations of the second law of thermodynamics and the fluctuation theorem, which include an informational quantity characterized by the topology of the causal network. Our result implies that the entropy production in a single system in the presence of multiple other systems is bounded by the information flow between these systems. We demonstrate our general result by a simple model of biochemical adaptation.
Local Causality, Probability and Explanation
Healey, Richard A
2016-01-01
In papers published in the 25 years following his famous 1964 proof John Bell refined and reformulated his views on locality and causality. Although his formulations of local causality were in terms of probability, he had little to say about that notion. But assumptions about probability are implicit in his arguments and conclusions. Probability does not conform to these assumptions when quantum mechanics is applied to account for the particular correlations Bell argues are locally inexplicable. This account involves no superluminal action and there is even a sense in which it is local, but it is in tension with the requirement that the direct causes and effects of events are nearby.
Causality and micro-causality in curved spacetime
Energy Technology Data Exchange (ETDEWEB)
Hollowood, Timothy J. [Department of Physics, University of Wales Swansea, Swansea, SA2 8PP (United Kingdom)], E-mail: t.hollowood@swansea.ac.uk; Shore, Graham M. [Department of Physics, University of Wales Swansea, Swansea, SA2 8PP (United Kingdom)], E-mail: g.m.shore@swansea.ac.uk
2007-10-25
We consider how causality and micro-causality are realised in QED in curved spacetime. The photon propagator is found to exhibit novel non-analytic behaviour due to vacuum polarization, which invalidates the Kramers-Kronig dispersion relation and calls into question the validity of micro-causality in curved spacetime. This non-analyticity is ultimately related to the generic focusing nature of congruences of geodesics in curved spacetime, as implied by the null energy condition, and the existence of conjugate points. These results arise from a calculation of the complete non-perturbative frequency dependence of the vacuum polarization tensor in QED, using novel world-line path integral methods together with the Penrose plane-wave limit of spacetime in the neighbourhood of a null geodesic. The refractive index of curved spacetime is shown to exhibit superluminal phase velocities, dispersion, absorption (due to {gamma}{yields}e{sup +}e{sup -}) and bi-refringence, but we demonstrate that the wavefront velocity (the high-frequency limit of the phase velocity) is indeed c, thereby guaranteeing that causality itself is respected.
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...
Causality problem in Economic Science
Directory of Open Access Journals (Sweden)
JOSÉ LUIS RETOLAZA
2007-12-01
Full Text Available The main point of the paper is the problem of the economy to be consider like a science in the most strict term of the concept. In the first step we are going to tackle a presentation about what we understand by science to subsequently present some of the fallacies which have bring certain scepticism about the scientific character of the investigation in economy, to know: 1 The differences between hard and weak sciences -physics and social; 2 The differences between paradigm, —positivist and phenomenological— 3 The differences between physic causalityand historic causality. In the second step we are going to talk about two fundamental problems which are questioned: 1 the confusion between ontology and gnoseology and, 2 the erroneous concept of causality that commonly is used. In the last step of the paper we are going over the recent models of «causal explanation» and we suggest the probabilistic casualty development next with a more elaborated models of causal explanation, like a way to conjugate the scientific severity with the possibility to tackle complex economic realities.
Causal Categories: Relativistically Interacting Processes
Coecke, Bob; Lal, Raymond
2013-04-01
A symmetric monoidal category naturally arises as the mathematical structure that organizes physical systems, processes, and composition thereof, both sequentially and in parallel. This structure admits a purely graphical calculus. This paper is concerned with the encoding of a fixed causal structure within a symmetric monoidal category: causal dependencies will correspond to topological connectedness in the graphical language. We show that correlations, either classical or quantum, force terminality of the tensor unit. We also show that well-definedness of the concept of a global state forces the monoidal product to be only partially defined, which in turn results in a relativistic covariance theorem. Except for these assumptions, at no stage do we assume anything more than purely compositional symmetric-monoidal categorical structure. We cast these two structural results in terms of a mathematical entity, which we call a causal category. We provide methods of constructing causal categories, and we study the consequences of these methods for the general framework of categorical quantum mechanics.
Causal feedbacks in climate change
Nes, van E.H.; Scheffer, M.; Brovkin, V.; Lenton, T.M.; Ye, H.; Deyle, E.; Sugihara, G.
2015-01-01
The statistical association between temperature and greenhouse gases over glacial cycles is well documented1, but causality behind this correlation remains difficult to extract directly from the data. A time lag of CO2 behind Antarctic temperature—originally thought to hint at a driving role for tem
An Introduction to Causal Inference
2009-11-02
legitimize causal inference, has removed causation from its natural habitat, and distorted its face beyond recognition. This exclusivist attitude is...In contrast, when the mediation problem is approached from an exclusivist potential-outcome viewpoint, void of the structural guidance of Eq. (28
Breaking the arrows of causality
DEFF Research Database (Denmark)
Valsiner, Jaan
2014-01-01
Theoretical models of catalysis have proven to bring with them major breakthroughs in chemistry and biology, from the 1830s onward. It can be argued that the scientific status of chemistry has become established through the move from causal to catalytic models. Likewise, the central explanatory...
Learning a Theory of Causality
Goodman, Noah D.; Ullman, Tomer D.; Tenenbaum, Joshua B.
2011-01-01
The very early appearance of abstract knowledge is often taken as evidence for innateness. We explore the relative learning speeds of abstract and specific knowledge within a Bayesian framework and the role for innate structure. We focus on knowledge about causality, seen as a domain-general intuitive theory, and ask whether this knowledge can be…
Noldus, Johan
2013-01-01
We construct a Dirac theory on causal sets; a key element in the construction being that the causet must be regarded as emergent in an appropriate sense too. We further notice that mixed norm spaces appear in the construction allowing for negative norm particles and "ghosts".
Temkin, Alexis M.; Bowers, Robert R.; Magaletta, Margaret E.; Holshouser, Steven; Maggi, Adriana; Ciana, Paolo; Guillette, Louis J.; Bowden, John A.; Kucklick, John R.; Baatz, John E.; Spyropoulos, Demetri D.
2015-01-01
adipocyte differentiation. Conclusions We conclude that DOSS is a putative obesogen worthy of further study, including epidemiological and clinical investigations into laxative prescriptions consisting of DOSS. Citation Temkin AM, Bowers RR, Magaletta ME, Holshouser S, Maggi A, Ciana P, Guillette LJ, Bowden JA, Kucklick JR, Baatz JE, Spyropoulos DD. 2016. Effects of crude oil/dispersant mixture and dispersant components on PPARγ activity in vitro and in vivo: identification of dioctyl sodium sulfosuccinate (DOSS; CAS #577-11-7) as a probable obesogen. Environ Health Perspect 124:112–119; http://dx.doi.org/10.1289/ehp.1409672 PMID:26135921
Entanglement, holography and causal diamonds
de Boer, Jan; Haehl, Felix M.; Heller, Michal P.; Myers, Robert C.
2016-08-01
We argue that the degrees of freedom in a d-dimensional CFT can be reorganized in an insightful way by studying observables on the moduli space of causal diamonds (or equivalently, the space of pairs of timelike separated points). This 2 d-dimensional space naturally captures some of the fundamental nonlocality and causal structure inherent in the entanglement of CFT states. For any primary CFT operator, we construct an observable on this space, which is defined by smearing the associated one-point function over causal diamonds. Known examples of such quantities are the entanglement entropy of vacuum excitations and its higher spin generalizations. We show that in holographic CFTs, these observables are given by suitably defined integrals of dual bulk fields over the corresponding Ryu-Takayanagi minimal surfaces. Furthermore, we explain connections to the operator product expansion and the first law of entanglemententropy from this unifying point of view. We demonstrate that for small perturbations of the vacuum, our observables obey linear two-derivative equations of motion on the space of causal diamonds. In two dimensions, the latter is given by a product of two copies of a two-dimensional de Sitter space. For a class of universal states, we show that the entanglement entropy and its spin-three generalization obey nonlinear equations of motion with local interactions on this moduli space, which can be identified with Liouville and Toda equations, respectively. This suggests the possibility of extending the definition of our new observables beyond the linear level more generally and in such a way that they give rise to new dynamically interacting theories on the moduli space of causal diamonds. Various challenges one has to face in order to implement this idea are discussed.
Causal inference in obesity research.
Franks, P W; Atabaki-Pasdar, N
2017-03-01
Obesity is a risk factor for a plethora of severe morbidities and premature death. Most supporting evidence comes from observational studies that are prone to chance, bias and confounding. Even data on the protective effects of weight loss from randomized controlled trials will be susceptible to confounding and bias if treatment assignment cannot be masked, which is usually the case with lifestyle and surgical interventions. Thus, whilst obesity is widely considered the major modifiable risk factor for many chronic diseases, its causes and consequences are often difficult to determine. Addressing this is important, as the prevention and treatment of any disease requires that interventions focus on causal risk factors. Disease prediction, although not dependent on knowing the causes, is nevertheless enhanced by such knowledge. Here, we provide an overview of some of the barriers to causal inference in obesity research and discuss analytical approaches, such as Mendelian randomization, that can help to overcome these obstacles. In a systematic review of the literature in this field, we found: (i) probable causal relationships between adiposity and bone health/disease, cancers (colorectal, lung and kidney cancers), cardiometabolic traits (blood pressure, fasting insulin, inflammatory markers and lipids), uric acid concentrations, coronary heart disease and venous thrombosis (in the presence of pulmonary embolism), (ii) possible causal relationships between adiposity and gray matter volume, depression and common mental disorders, oesophageal cancer, macroalbuminuria, end-stage renal disease, diabetic kidney disease, nuclear cataract and gall stone disease, and (iii) no evidence for causal relationships between adiposity and Alzheimer's disease, pancreatic cancer, venous thrombosis (in the absence of pulmonary embolism), liver function and periodontitis.
LEARNING GRANGER CAUSALITY GRAPHS FOR MULTIVARIATE NONLINEAR TIME SERIES
Institute of Scientific and Technical Information of China (English)
Wei GAO; Zheng TIAN
2009-01-01
An information theory method is proposed to test the. Granger causality and contemporaneous conditional independence in Granger causality graph models. In the graphs, the vertex set denotes the component series of the multivariate time series, and the directed edges denote causal dependence, while the undirected edges reflect the instantaneous dependence. The presence of the edges is measured by a statistics based on conditional mutual information and tested by a permutation procedure. Furthermore, for the existed relations, a statistics based on the difference between general conditional mutual information and linear conditional mutual information is proposed to test the nonlinearity. The significance of the nonlinear test statistics is determined by a bootstrap method based on surrogate data. We investigate the finite sample behavior of the procedure through simulation time series with different dependence structures, including linear and nonlinear relations.
Mixture Based Outlier Filtration
Directory of Open Access Journals (Sweden)
P. Pecherková
2006-01-01
Full Text Available Success/failure of adaptive control algorithms – especially those designed using the Linear Quadratic Gaussian criterion – depends on the quality of the process data used for model identification. One of the most harmful types of process data corruptions are outliers, i.e. ‘wrong data’ lying far away from the range of real data. The presence of outliers in the data negatively affects an estimation of the dynamics of the system. This effect is magnified when the outliers are grouped into blocks. In this paper, we propose an algorithm for outlier detection and removal. It is based on modelling the corrupted data by a two-component probabilistic mixture. The first component of the mixture models uncorrupted process data, while the second models outliers. When the outlier component is detected to be active, a prediction from the uncorrupted data component is computed and used as a reconstruction of the observed data. The resulting reconstruction filter is compared to standard methods on simulated and real data. The filter exhibits excellent properties, especially in the case of blocks of outliers.
Information flow and causality as rigorous notions ab initio
Liang, X. San
2016-11-01
Information flow or information transfer the widely applicable general physics notion can be rigorously derived from first principles, rather than axiomatically proposed as an ansatz. Its logical association with causality is firmly rooted in the dynamical system that lies beneath. The principle of nil causality that reads, an event is not causal to another if the evolution of the latter is independent of the former, which transfer entropy analysis and Granger causality test fail to verify in many situations, turns out to be a proven theorem here. Established in this study are the information flows among the components of time-discrete mappings and time-continuous dynamical systems, both deterministic and stochastic. They have been obtained explicitly in closed form, and put to applications with the benchmark systems such as the Kaplan-Yorke map, Rössler system, baker transformation, Hénon map, and stochastic potential flow. Besides unraveling the causal relations as expected from the respective systems, some of the applications show that the information flow structure underlying a complex trajectory pattern could be tractable. For linear systems, the resulting remarkably concise formula asserts analytically that causation implies correlation, while correlation does not imply causation, providing a mathematical basis for the long-standing philosophical debate over causation versus correlation.
Causal inference in economics and marketing.
Varian, Hal R
2016-07-05
This is an elementary introduction to causal inference in economics written for readers familiar with machine learning methods. The critical step in any causal analysis is estimating the counterfactual-a prediction of what would have happened in the absence of the treatment. The powerful techniques used in machine learning may be useful for developing better estimates of the counterfactual, potentially improving causal inference.
Exploring Individual Differences in Preschoolers' Causal Stance
Alvarez, Aubry; Booth, Amy E.
2016-01-01
Preschoolers, as a group, are highly attuned to causality, and this attunement is known to facilitate memory, learning, and problem solving. However, recent work reveals substantial individual variability in the strength of children's "causal stance," as demonstrated by their curiosity about and preference for new causal information. In…
Representing Personal Determinants in Causal Structures.
Bandura, Albert
1984-01-01
Responds to Staddon's critique of the author's earlier article and addresses issues raised by Staddon's (1984) alternative models of causality. The author argues that it is not the formalizability of causal processes that is the issue but whether cognitive determinants of behavior are reducible to past stimulus inputs in causal structures.…
Designing Effective Supports for Causal Reasoning
Jonassen, David H.; Ionas, Ioan Gelu
2008-01-01
Causal reasoning represents one of the most basic and important cognitive processes that underpin all higher-order activities, such as conceptual understanding and problem solving. Hume called causality the "cement of the universe" [Hume (1739/2000). Causal reasoning is required for making predictions, drawing implications and…
Designing Effective Supports for Causal Reasoning
Jonassen, David H.; Ionas, Ioan Gelu
2008-01-01
Causal reasoning represents one of the most basic and important cognitive processes that underpin all higher-order activities, such as conceptual understanding and problem solving. Hume called causality the "cement of the universe" [Hume (1739/2000). Causal reasoning is required for making predictions, drawing implications and inferences, and…
Decomposing Granger Causality over the Spectrum
A. Lemmens (Aurélie); C. Croux (Christophe); M.G. Dekimpe (Marnik)
2004-01-01
textabstractWe develop a bivariate spectral Granger-causality test that can be applied at each individual frequency of the spectrum. The spectral approach to Granger causality has the distinct advantage that it allows to disentangle (potentially) di®erent Granger- causality relationships over di®ere
Expectations and Interpretations during Causal Learning
Luhmann, Christian C.; Ahn, Woo-kyoung
2011-01-01
In existing models of causal induction, 4 types of covariation information (i.e., presence/absence of an event followed by presence/absence of another event) always exert identical influences on causal strength judgments (e.g., joint presence of events always suggests a generative causal relationship). In contrast, we suggest that, due to…
Causality analysis in business performance measurement system using system dynamics methodology
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.
Velocity requirements for causality violation
Modanese, Giovanni
2013-01-01
It is known that the hypothetical existence of superluminal signals would imply the logical possibility of active causal violation: an observer in relative motion with respect to a primary source could in principle emit secondary superluminal signals (triggered by the primary ones) which go back in time and deactivate the primary source before the initial emission. This is a direct consequence of the structure of the Lorentz transformations, sometimes called "Regge-Tolman paradox". It is straightforward to find a formula for the velocity of the moving observer required to produce the causality violation. When applied to some recent claims of slight superluminal propagation, this formula yields a required velocity very close to the speed of light; this raises some doubts about the real physical observability of such violations. We re-compute this velocity requirement introducing a realistic delay between the reception of the primary signal and the emission of the secondary. It turns out that for -any- delay it...
Painless causality in defect calculations
Cheung, C; Cheung, Charlotte; Magueijo, Joao
1997-01-01
Topological defects must respect causality, a statement leading to restrictive constraints on the power spectrum of the total cosmological perturbations they induce. Causality constraints have for long been known to require the presence of an under-density in the surrounding matter compensating the defect network on large scales. This so-called compensation can never be neglected and significantly complicates calculations in defect scenarios, eg. computing cosmic microwave background fluctuations. A quick and dirty way to implement the compensation are the so-called compensation fudge factors. Here we derive the complete photon-baryon-CDM backreaction effects in defect scenarios. The fudge factor comes out as an algebraic identity and so we drop the negative qualifier ``fudge''. The compensation scale is computed and physically interpreted. Secondary backreaction effects exist, and neglecting them constitutes the well-defined approximation scheme within which one should consider compensation factor calculatio...
Confounding Equivalence in Causal Inference
Pearl, Judea
2012-01-01
The paper provides a simple test for deciding, from a given causal diagram, whether two sets of variables have the same bias-reducing potential under adjustment. The test re- quires that one of the following two condi- tions holds: either (1) both sets are admis- sible (i.e., satisfy the back-door criterion) or (2) the Markov boundaries surrounding the manipulated variable(s) are identical in both sets. Applications to covariate selection and model testing are discussed.
Phenomenology of Causal Dynamical Triangulations
Mielczarek, Jakub
2015-01-01
The four dimensional Causal Dynamical Triangulations (CDT) approach to quantum gravity is already more than ten years old theory with numerous unprecedented predictions such as non-trivial phase structure of gravitational field and dimensional running. Here, we discuss possible empirical consequences of CDT derived based on the two features of the approach mentioned above. A possibility of using both astrophysical and cosmological observations to test CDT is discussed. We show that scenarios which can be ruled out at the empirical level exist.
Causality and primordial tensor modes
Energy Technology Data Exchange (ETDEWEB)
Baumann, Daniel; Zaldarriaga, Matias, E-mail: dbaumann@physics.harvard.edu, E-mail: mzaldarriaga@cfa.harvard.edu [Department of Physics, Harvard University, 17 Oxford Street, Cambridge, MA 02138, U.S.A. and Center for Astrophysics, Harvard University, 60 Garden Street, Cambridge, MA 02138 (United States)
2009-06-01
We introduce the real space correlation function of B-mode polarization of the cosmic microwave background (CMB) as a probe of superhorizon tensor perturbations created by inflation. By causality, any non-inflationary mechanism for gravitational wave production after reheating, like global phase transitions or cosmic strings, must have vanishing correlations for angular separations greater than the angle subtended by the particle horizon at recombination, i.e. θ ∼> 2°. Since ordinary B-modes are defined non-locally in terms of the Stokes parameters Q and U and therefore don't have to respect causality, special care is taken to define 'causal B-tilde -modes' for the analysis. We compute the real space B-tilde -mode correlation function for inflation and discuss its detectability on superhorizon scales where it provides an unambiguous test of inflationary gravitational waves. The correct identification of inflationary tensor modes is crucial since it relates directly to the energy scale of inflation. Wrongly associating tensor modes from causal seeds with inflation would imply an incorrect inference of the energy scale of inflation. We find that the superhorizon B-tilde -mode signal is above cosmic variance for the angular range 2° < θ < 4° and is therefore in principle detectable. In practice, the signal will be challenging to measure since it requires accurately resolving the recombination peak of the B-mode power spectrum. However, a future CMB satellite (CMBPol), with noise level Δ{sub P} ≅ 1μK-arcmin and sufficient resolution to efficiently correct for lensing-induced B-modes, should be able to detect the signal at more than 3σ if the tensor-to-scalar ratio isn't smaller than r ≅ 0.01.
Modeling of causality with metamaterials
Smolyaninov, Igor I.
2013-02-01
Hyperbolic metamaterials may be used to model a 2 + 1-dimensional Minkowski space-time in which the role of time is played by one of the spatial coordinates. When a metamaterial is built and illuminated with a coherent extraordinary laser beam, the stationary pattern of light propagation inside the metamaterial may be treated as a collection of particle world lines, which represents a complete ‘history’ of this 2 + 1-dimensional space-time. While this model may be used to build interesting space-time analogs, such as metamaterial ‘black holes’ and a metamaterial ‘big bang’, it lacks causality: since light inside the metamaterial may propagate back and forth along the ‘timelike’ spatial coordinate, events in the ‘future’ may affect events in the ‘past’. Here we demonstrate that a more sophisticated metamaterial model may fix this deficiency via breaking the mirror and temporal (PT) symmetries of the original model and producing one-way propagation along the ‘timelike’ spatial coordinate. The resulting 2 + 1-dimensional Minkowski space-time appears to be causal. This scenario may be considered as a metamaterial model of the Wheeler-Feynman absorber theory of causality.
Entanglement, Holography and Causal Diamonds
de Boer, Jan; Heller, Michal P; Myers, Robert C
2016-01-01
We argue that the degrees of freedom in a d-dimensional CFT can be re-organized in an insightful way by studying observables on the moduli space of causal diamonds (or equivalently, the space of pairs of timelike separated points). This 2d-dimensional space naturally captures some of the fundamental nonlocality and causal structure inherent in the entanglement of CFT states. For any primary CFT operator, we construct an observable on this space, which is defined by smearing the associated one-point function over causal diamonds. Known examples of such quantities are the entanglement entropy of vacuum excitations and its higher spin generalizations. We show that in holographic CFTs, these observables are given by suitably defined integrals of dual bulk fields over the corresponding Ryu-Takayanagi minimal surfaces. Furthermore, we explain connections to the operator product expansion and the first law of entanglement entropy from this unifying point of view. We demonstrate that for small perturbations of the va...
Experimental verification of an indefinite causal order
Rubino, Giulia; Rozema, Lee A.; Feix, Adrien; Araújo, Mateus; Zeuner, Jonas M.; Procopio, Lorenzo M.; Brukner, Časlav; Walther, Philip
2017-01-01
Investigating the role of causal order in quantum mechanics has recently revealed that the causal relations of events may not be a priori well defined in quantum theory. Although this has triggered a growing interest on the theoretical side, creating processes without a causal order is an experimental task. We report the first decisive demonstration of a process with an indefinite causal order. To do this, we quantify how incompatible our setup is with a definite causal order by measuring a “causal witness.” This mathematical object incorporates a series of measurements that are designed to yield a certain outcome only if the process under examination is not consistent with any well-defined causal order. In our experiment, we perform a measurement in a superposition of causal orders—without destroying the coherence—to acquire information both inside and outside of a “causally nonordered process.” Using this information, we experimentally determine a causal witness, demonstrating by almost 7 SDs that the experimentally implemented process does not have a definite causal order.
Gulliver, Eric A.
particle-size distributions or mixture composition. Control charts based on tessellation measurements were used for direct, quantitative comparisons between real and simulated mixtures. Four sets of simulated and real mixtures were examined. Data from real mixture was matched with simulated data when the samples were well mixed and the particle size distributions and volume fractions of the components were identical. Analysis of mixture components that occupied less than approximately 10 vol% of the mixture was not practical unless the particle size of the component was extremely small and excellent quality high-resolution compositional micrographs of the real sample are available. These methods of analysis should allow future researchers to systematically evaluate and predict the impact and importance of variables such as component volume fraction and component particle size distribution as they pertain to the uniformity of powder mixture microstructures.
Norms and customs: causally important or causally impotent?
Jones, Todd
2010-01-01
In this article, I argue that norms and customs, despite frequently being described as being causes of behavior in the social sciences and ordinary conversation, cannot really cause behavior. Terms like "norms" and the like seem to refer to philosophically disreputable disjunctive properties. More problematically, even if they do not, or even if there can be disjunctive properties after all, I argue that norms and customs still cannot cause behavior. The social sciences would be better off without referring to properties like norms and customs as if they could be causal.
Supercritical separation process for complex organic mixtures
Chum, Helena L.; Filardo, Giuseppe
1990-01-01
A process is disclosed for separating low molecular weight components from complex aqueous organic mixtures. The process includes preparing a separation solution of supercritical carbon dioxide with an effective amount of an entrainer to modify the solvation power of the supercritical carbon dioxide and extract preselected low molecular weight components. The separation solution is maintained at a temperature of at least about 70.degree. C. and a pressure of at least about 1,500 psi. The separation solution is then contacted with the organic mixtures while maintaining the temperature and pressure as above until the mixtures and solution reach equilibrium to extract the preselected low molecular weight components from the organic mixtures. Finally, the entrainer/extracted components portion of the equilibrium mixture is isolated from the separation solution.
Independence and dependence in human causal reasoning.
Rehder, Bob
2014-07-01
Causal graphical models (CGMs) are a popular formalism used to model human causal reasoning and learning. The key property of CGMs is the causal Markov condition, which stipulates patterns of independence and dependence among causally related variables. Five experiments found that while adult's causal inferences exhibited aspects of veridical causal reasoning, they also exhibited a small but tenacious tendency to violate the Markov condition. They also failed to exhibit robust discounting in which the presence of one cause as an explanation of an effect makes the presence of another less likely. Instead, subjects often reasoned "associatively," that is, assumed that the presence of one variable implied the presence of other, causally related variables, even those that were (according to the Markov condition) conditionally independent. This tendency was unaffected by manipulations (e.g., response deadlines) known to influence fast and intuitive reasoning processes, suggesting that an associative response to a causal reasoning question is sometimes the product of careful and deliberate thinking. That about 60% of the erroneous associative inferences were made by about a quarter of the subjects suggests the presence of substantial individual differences in this tendency. There was also evidence that inferences were influenced by subjects' assumptions about factors that disable causal relations and their use of a conjunctive reasoning strategy. Theories that strive to provide high fidelity accounts of human causal reasoning will need to relax the independence constraints imposed by CGMs.
Space and time in perceptual causality
Directory of Open Access Journals (Sweden)
Benjamin Straube
2010-04-01
Full Text Available Inferring causality is a fundamental feature of human cognition that allows us to theorize about and predict future states of the world. Michotte suggested that humans automatically perceive causality based on certain perceptual features of events. However, individual differences in judgments of perceptual causality cast doubt on Michotte’s view. To gain insights in the neural basis of individual difference in the perception of causality, our participants judged causal relationships in animations of a blue ball colliding with a red ball (a launching event while fMRI-data were acquired. Spatial continuity and temporal contiguity were varied parametrically in these stimuli. We did not find consistent brain activation differences between trials judged as caused and those judged as non-caused, making it unlikely that humans have universal instantiation of perceptual causality in the brain. However, participants were slower to respond to and showed greater neural activity for violations of causality, suggesting that humans are biased to expect causal relationships when moving objects appear to interact. Our participants demonstrated considerable individual differences in their sensitivity to spatial and temporal characteristics in perceiving causality. These qualitative differences in sensitivity to time or space in perceiving causality were instantiated in individual differences in activation of the left basal ganglia or right parietal lobe, respectively. Thus, the perception that the movement of one object causes the movement of another is triggered by elemental spatial and temporal sensitivities, which themselves are instantiated in specific distinct neural networks.
How prescriptive norms influence causal inferences.
Samland, Jana; Waldmann, Michael R
2016-11-01
Recent experimental findings suggest that prescriptive norms influence causal inferences. The cognitive mechanism underlying this finding is still under debate. We compare three competing theories: The culpable control model of blame argues that reasoners tend to exaggerate the causal influence of norm-violating agents, which should lead to relatively higher causal strength estimates for these agents. By contrast, the counterfactual reasoning account of causal selection assumes that norms do not alter the representation of the causal model, but rather later causal selection stages. According to this view, reasoners tend to preferentially consider counterfactual states of abnormal rather than normal factors, which leads to the choice of the abnormal factor in a causal selection task. A third view, the accountability hypothesis, claims that the effects of prescriptive norms are generated by the ambiguity of the causal test question. Asking whether an agent is a cause can be understood as a request to assess her causal contribution but also her moral accountability. According to this theory norm effects on causal selection are mediated by accountability judgments that are not only sensitive to the abnormality of behavior but also to mitigating factors, such as intentionality and knowledge of norms. Five experiments are presented that favor the accountability account over the two alternative theories.
Random number generators and causality
Energy Technology Data Exchange (ETDEWEB)
Larrondo, H.A. [Facultad de Ingenieria, Universidad Nacional de Mar del Plata, Juan B. Justo 4302, 7600 Mar del Plata (Argentina)]. E-mail: larrondo@fi.mdp.edu.ar; Martin, M.T. [Instituto de Fisica (IFLP), Facultad de Ciencias Exactas, Universidad Nacional de La Plata and Argentina' s National Council (CONICET), C.C. 727, 1900 La Plata (Argentina)]. E-mail: mtmartin@venus.unlp.edu.ar; Gonzalez, C.M. [Facultad de Ingenieria, Universidad Nacional de Mar del Plata, Juan B. Justo 4302, 7600 Mar del Plata (Argentina)]. E-mail: cmgonzal@fi.mdp.edu.ar; Plastino, A. [Instituto de Fisica (IFLP), Facultad de Ciencias Exactas, Universidad Nacional de La Plata and Argentina' s National Council (CONICET), C.C. 727, 1900 La Plata (Argentina)]. E-mail: plastino@venus.unlp.edu.ar; Rosso, O.A. [Chaos and Biology Group, Instituto de Calculo, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Pabellon II, Ciudad Universitaria, 1428 Ciudad de Buenos Aires (Argentina)]. E-mail: oarosso@fibertel.com.ar
2006-04-03
We advance a prescription to randomize physical or algorithmic Random Number Generators (RNG's) that do not pass Marsaglia's DIEHARD test suite and discuss a special physical quantifier, based on an intensive statistical complexity measure, that is able to adequately assess the improvements produced thereby. Eight RNG's are evaluated and the associated results are compared to those obtained by recourse to Marsaglia's DIEHARD test suite. Our quantifier, which is evaluated using causality arguments, can forecast whether a given RNG will pass the above mentioned test.
Random number generators and causality
Larrondo, H. A.; Martín, M. T.; González, C. M.; Plastino, A.; Rosso, O. A.
2006-04-01
We advance a prescription to randomize physical or algorithmic Random Number Generators (RNG's) that do not pass Marsaglia's DIEHARD test suite and discuss a special physical quantifier, based on an intensive statistical complexity measure, that is able to adequately assess the improvements produced thereby. Eight RNG's are evaluated and the associated results are compared to those obtained by recourse to Marsaglia's DIEHARD test suite. Our quantifier, which is evaluated using causality arguments, can forecast whether a given RNG will pass the above mentioned test.
Mixture Density Mercer Kernels
National Aeronautics and Space Administration — We present a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian mixture...
Modeling of causality with metamaterials
Smolyaninov, Igor I
2012-01-01
Hyperbolic metamaterials may be used to model a 2+1 dimensional Minkowski spacetime in which the role of time is played by one of the spatial coordinates. When a metamaterial is built and illuminated with a coherent extraordinary laser beam, the stationary pattern of light propagation inside the metamaterial may be treated as a collection of particle world lines, which represents a complete history of this 2+1 dimensional spacetime. While this model may be used to build interesting spacetime analogs, such as metamaterial black holes and big bang, it lacks causality: since light inside the metamaterial may propagate back and force along the timelike spatial coordinate, events in the future may affect events in the past. Here we demonstrate that a more sophisticated metamaterial model may fix this deficiency via breaking the mirror and temporal (PT) symmetries of the original model and producing one-way propagation along the timelike spatial coordinate. Resulting 2+1 Minkowski spacetime appears to be causal. Th...
Causal viscous cosmology without singularities
Laciana, Carlos E
2016-01-01
An isotropic and homogeneous cosmological model with a source of dark energy is studied. That source is simulated with a viscous relativistic fluid with minimal causal correction. In this model the restrictions on the parameters coming from the following conditions are analized: a) energy density without singularities along time, b) scale factor increasing with time, c) universe accelerated at present time, d) state equation for dark energy with "w" bounded and close to -1. It is found that those conditions are satified for the following two cases. i) When the transport coefficient ({\\tau}_{{\\Pi}}), associated to the causal correction, is negative, with the aditional restriction {\\zeta}|{\\tau}_{{\\Pi}}|>2/3, where {\\zeta} is the relativistic bulk viscosity coefficient. The state equation is in the "phantom" energy sector. ii) For {\\tau}_{{\\Pi}} positive, in the "k-essence" sector. It is performed an exact calculation for the case where the equation of state is constant, finding that option (ii) is favored in r...
Spin foam models as energetic causal sets
Cortês, Marina
2014-01-01
Energetic causal sets are causal sets endowed by a flow of energy-momentum between causally related events. These incorporate a novel mechanism for the emergence of space-time from causal relations. Here we construct a spin foam model which is also an energetic causal set model. This model is closely related to the model introduced by Wieland, and this construction makes use of results used there. What makes a spin foam model also an energetic causal set is Wieland's identification of new momenta, conserved at events (or four-simplices), whose norms are not mass, but the volume of tetrahedra. This realizes the torsion constraints, which are missing in previous spin foam models, and are needed to relate the connection dynamics to those of the metric, as in general relativity. This identification makes it possible to apply the new mechanism for the emergence of space-time to a spin foam model.
Causal inference in economics and marketing
Varian, Hal R.
2016-01-01
This is an elementary introduction to causal inference in economics written for readers familiar with machine learning methods. The critical step in any causal analysis is estimating the counterfactual—a prediction of what would have happened in the absence of the treatment. The powerful techniques used in machine learning may be useful for developing better estimates of the counterfactual, potentially improving causal inference. PMID:27382144
Linear causal modeling with structural equations
Mulaik, Stanley A
2009-01-01
Emphasizing causation as a functional relationship between variables that describe objects, Linear Causal Modeling with Structural Equations integrates a general philosophical theory of causation with structural equation modeling (SEM) that concerns the special case of linear causal relations. In addition to describing how the functional relation concept may be generalized to treat probabilistic causation, the book reviews historical treatments of causation and explores recent developments in experimental psychology on studies of the perception of causation. It looks at how to perceive causal
Identifying Causal Effects with Computer Algebra
García-Puente, Luis David; Sullivant, Seth
2010-01-01
The long-standing identification problem for causal effects in graphical models has many partial results but lacks a systematic study. We show how computer algebra can be used to either prove that a causal effect can be identified, generically identified, or show that the effect is not generically identifiable. We report on the results of our computations for linear structural equation models, where we determine precisely which causal effects are generically identifiable for all graphs on three and four vertices.
Scalar Curvature of a Causal Set
Benincasa, Dionigi M. T.; Dowker, Fay
2010-05-01
A one parameter family of retarded linear operators on scalar fields on causal sets is introduced. When the causal set is well approximated by 4 dimensional Minkowski spacetime, the operators are Lorentz invariant but nonlocal, are parametrized by the scale of the nonlocality, and approximate the continuum scalar D’Alembertian □ when acting on fields that vary slowly on the nonlocality scale. The same operators can be applied to scalar fields on causal sets which are well approximated by curved spacetimes in which case they approximate □-(1)/(2)R where R is the Ricci scalar curvature. This can used to define an approximately local action functional for causal sets.
Methods for Assessing Curvature and Interaction in Mixture Experiments
Energy Technology Data Exchange (ETDEWEB)
Piepel, Gregory F.(BATTELLE (PACIFIC NW LAB)); Hicks, Ruel D.(ASSOC WESTERN UNIVERSITY); Szychowski, Jeffrey M.(ASSOC WESTERN UNIVERSITY); Loeppky, Jason L.(ASSOC WESTERN UNIVERSITY)
2002-05-01
The terms curvature and interaction traditionally are not defined or used in the context of mixture experiments because curvature and interaction effects are partially confounded due to the mixture constrain that the component proportions sum to 1.
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.
Robust classification using mixtures of dependency networks
DEFF Research Database (Denmark)
Gámez, José A.; Mateo, Juan L.; Nielsen, Thomas Dyhre
2008-01-01
-ups are often obtained at the expense of accuracy. In this paper we try to address this issue through the use of mixtures of dependency networks. To reduce learning time and improve robustness when dealing with data sparse classes, we outline methods for reusing calculations across mixture components. Finally...
Comparison theorems for causal diamonds
Berthiere, Clement; Solodukhin, Sergey N
2015-01-01
We formulate certain inequalities for the geometric quantities characterizing causal diamonds in curved and Minkowski spacetimes. These inequalities involve the red-shift factor which, as we show explicitly in the spherically symmetric case, is monotonic in the radial direction and it takes its maximal value at the centre. As a byproduct of our discussion we re-derive Bishop's inequality without assuming the positivity of the spatial Ricci tensor. We then generalize our considerations to arbitrary, static and not necessarily spherically symmetric, asymptotically flat spacetimes. In the case of spacetimes with a horizon our generalization involves the so-called {\\it domain of dependence}. The respective volume, expressed in terms of the duration measured by a distant observer compared with the volume of the domain in Minkowski spacetime, exhibits behaviours which differ if $d=4$ or $d>4$. This peculiarity of four dimensions is due to the logarithmic subleading term in the asymptotic expansion of the metric nea...
Energy Technology Data Exchange (ETDEWEB)
Garcia-Parrado, Alfonso [Departamento de Fisica Teorica, Universidad del Pais Vasco, Apartado 644, 48080 Bilbao (Spain); Sanchez, Miguel [Departamento de Geometria y Topologia, Facultad de Ciencias, Universidad de Granada, Avenida Fuentenueva s/n, 18071 Granada (Spain)
2005-11-07
Recently (Garcia-Parrado and Senovilla 2003 Class. Quantum Grav. 20 625-64) the concept of causal mapping between spacetimes, essentially equivalent in this context to the chronological map defined in abstract chronological spaces, and the related notion of causal structure, have been introduced as new tools to study causality in Lorentzian geometry. In the present paper, these tools are further developed in several directions such as (i) causal mappings-and, thus, abstract chronological ones-do not preserve two levels of the standard hierarchy of causality conditions (however, they preserve the remaining levels as shown in the above reference), (ii) even though global hyperbolicity is a stable property (in the set of all time-oriented Lorentzian metrics on a fixed manifold), the causal structure of a globally hyperbolic spacetime can be unstable against perturbations; in fact, we show that the causal structures of Minkowski and Einstein static spacetimes remain stable, whereas that of de Sitter becomes unstable, (iii) general criteria allow us to discriminate different causal structures in some general spacetimes (e.g. globally hyperbolic, stationary standard); in particular, there are infinitely many different globally hyperbolic causal structures (and thus, different conformal ones) on R{sup 2} (iv) plane waves with the same number of positive eigenvalues in the frequency matrix share the same causal structure and, thus, they have equal causal extensions and causal boundaries.
The Power of Causal Beliefs and Conflicting Evidence on Causal Judgments and Decision Making
Garcia-Retamero, Rocio; Muller, Stephanie M.; Catena, Andres; Maldonado, Antonio
2009-01-01
In two experiments, we investigated the relative impact of causal beliefs and empirical evidence on both decision making and causal judgments, and whether this relative impact could be altered by previous experience. 2. Selected groups of participants in both experiments received pre-training with either causal or neutral cues, or no pre-training…
"Comments on Slavin": Synthesizing Causal Inferences
Briggs, Derek C.
2008-01-01
When causal inferences are to be synthesized across multiple studies, efforts to establish the magnitude of a causal effect should be balanced by an effort to evaluate the generalizability of the effect. The evaluation of generalizability depends on two factors that are given little attention in current syntheses: construct validity and external…
Structural intervention distance for evaluating causal graphs
DEFF Research Database (Denmark)
Peters, Jonas; Bühlmann, Peter
2015-01-01
Causal inference relies on the structure of a graph, often a directed acyclic graph (DAG). Different graphs may result in different causal inference statements and different intervention distributions. To quantify such differences, we propose a (pre-)metric between DAGs, the structural interventi...... implementation with software code available on the first author's home page....
On the spectral formulation of Granger causality.
Chicharro, D
2011-12-01
Spectral measures of causality are used to explore the role of different rhythms in the causal connectivity between brain regions. We study several spectral measures related to Granger causality, comprising the bivariate and conditional Geweke measures, the directed transfer function, and the partial directed coherence. We derive the formulation of dependence and causality in the spectral domain from the more general formulation in the information-theory framework. We argue that the transfer entropy, the most general measure derived from the concept of Granger causality, lacks a spectral representation in terms of only the processes associated with the recorded signals. For all the spectral measures we show how they are related to mutual information rates when explicitly considering the parametric autoregressive representation of the processes. In this way we express the conditional Geweke spectral measure in terms of a multiple coherence involving innovation variables inherent to the autoregressive representation. We also link partial directed coherence with Sims' criterion of causality. Given our results, we discuss the causal interpretation of the spectral measures related to Granger causality and stress the necessity to explicitly consider their specific formulation based on modeling the signals as linear Gaussian stationary autoregressive processes.
Causal Moderation Analysis Using Propensity Score Methods
Dong, Nianbo
2012-01-01
This paper is based on previous studies in applying propensity score methods to study multiple treatment variables to examine the causal moderator effect. The propensity score methods will be demonstrated in a case study to examine the causal moderator effect, where the moderators are categorical and continuous variables. Moderation analysis is an…
Quasi-Experimental Designs for Causal Inference
Kim, Yongnam; Steiner, Peter
2016-01-01
When randomized experiments are infeasible, quasi-experimental designs can be exploited to evaluate causal treatment effects. The strongest quasi-experimental designs for causal inference are regression discontinuity designs, instrumental variable designs, matching and propensity score designs, and comparative interrupted time series designs. This…
Causal Mediation Analysis: Warning! Assumptions Ahead
Keele, Luke
2015-01-01
In policy evaluations, interest may focus on why a particular treatment works. One tool for understanding why treatments work is causal mediation analysis. In this essay, I focus on the assumptions needed to estimate mediation effects. I show that there is no "gold standard" method for the identification of causal mediation effects. In…
Campbell's and Rubin's Perspectives on Causal Inference
West, Stephen G.; Thoemmes, Felix
2010-01-01
Donald Campbell's approach to causal inference (D. T. Campbell, 1957; W. R. Shadish, T. D. Cook, & D. T. Campbell, 2002) is widely used in psychology and education, whereas Donald Rubin's causal model (P. W. Holland, 1986; D. B. Rubin, 1974, 2005) is widely used in economics, statistics, medicine, and public health. Campbell's approach focuses on…
Essays on Causal Inference for Public Policy
Zajonc, Tristan
2012-01-01
Effective policymaking requires understanding the causal effects of competing proposals. Relevant causal quantities include proposals' expected effect on different groups of recipients, the impact of policies over time, the potential trade-offs between competing objectives, and, ultimately, the optimal policy. This dissertation studies causal…
Causal random geometry from stochastic quantization
DEFF Research Database (Denmark)
Ambjørn, Jan; Loll, R.; Westra, W.
2010-01-01
in this short note we review a recently found formulation of two-dimensional causal quantum gravity defined through Causal Dynamical Triangulations and stochastic quantization. This procedure enables one to extract the nonperturbative quantum Hamiltonian of the random surface model including the...
The causal order on the ambient boundary
Antoniadis, Ignatios; Papadopoulos, Kyriakos
2016-01-01
We analyse the causal structure of the ambient boundary, the conformal infinity of the ambient (Poincar\\'e) metric. Using topological tools we show that the only causal relation compatible with the global topology of the boundary spacetime is the horismos order. This has important consequences for the notion of time in the conformal geometry of the ambient boundary.
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 Indicators Can Help to Interpret Factors
Bentler, Peter M.
2016-01-01
The latent factor in a causal indicator model is no more than the latent factor of the factor part of the model. However, if the causal indicator variables are well-understood and help to improve the prediction of individuals' factor scores, they can help to interpret the meaning of the latent factor. Aguirre-Urreta, Rönkkö, and Marakas (2016)…
A Causal Alternative to Feynman's Propagator
Koksma, Jurjen F
2010-01-01
The Feynman propagator used in the conventional in-out formalism in quantum field theory is not a causal propagator as wave packets are propagated virtually instantaneously outside the causal region of the initial state. We formulate a causal in-out formalism in quantum field theory by making use of the Wheeler propagator, the time ordered commutator propagator, which is manifestly causal. Only free scalar field theories and their first quantization are considered. We identify the real Klein Gordon field itself as the wave function of a neutral spinless relativistic particle. Furthermore, we derive a probability density for our relativistic wave packet using the inner product between states that live on a suitably defined Hilbert space of real quantum fields. We show that the time evolution of our probability density is governed by the Wheeler propagator, such that it behaves causally too.
Causality, Bell's theorem, and Ontic Definiteness
Henson, Joe
2011-01-01
Bell's theorem shows that the reasonable relativistic causal principle known as "local causality" is not compatible with the predictions of quantum mechanics. It is not possible maintain a satisfying causal principle of this type while dropping any of the better-known assumptions of Bell's theorem. However, another assumption of Bell's theorem is the use of classical logic. One part of this assumption is the principle of "ontic definiteness", that is, that it must in principle be possible to assign definite truth values to all propositions treated in the theory. Once the logical setting is clarified somewhat, it can be seen that rejecting this principle does not in any way undermine the type of causal principle used by Bell. Without ontic definiteness, the deterministic causal condition known as Einstein Locality succeeds in banning superluminal influence (including signalling) whilst allowing correlations that violate Bell's inequalities. Objections to altering logic, and the consequences for operational and...
A Brief Introduction to Temporality and Causality
Karimi, Kamran
2010-01-01
Causality is a non-obvious concept that is often considered to be related to temporality. In this paper we present a number of past and present approaches to the definition of temporality and causality from philosophical, physical, and computational points of view. We note that time is an important ingredient in many relationships and phenomena. The topic is then divided into the two main areas of temporal discovery, which is concerned with finding relations that are stretched over time, and causal discovery, where a claim is made as to the causal influence of certain events on others. We present a number of computational tools used for attempting to automatically discover temporal and causal relations in data.
Towards Spectral Geometry for Causal Sets
Yazdi, Yasaman K
2016-01-01
We show that the Feynman propagator (or the d'Alembertian) of a causal set contains the complete information about the causal set. Intuitively, this is because the Feynman propagator, being a correlator that decays with distance, provides a measure for the invariant distance between pairs of events. Further, we show that even the spectra alone (of the self-adjoint and anti-self-adjoint parts) of the propagator(s) and d'Alembertian already carry large amounts of geometric information about their causal set. This geometric information is basis independent and also gauge invariant in the sense that it is relabeling invariant (which is analogue to diffeomorphism invariance). We provide numerical evidence that the associated spectral distance between causal sets can serve as a measure for the geometric similarity between causal sets.
Causality Violation, Gravitational Shockwaves and UV Completion
Hollowood, Timothy J
2015-01-01
The effective actions describing the low-energy dynamics of QFTs involving gravity generically exhibit causality violations. These may take the form of superluminal propagation or Shapiro time advances and allow the construction of "time machines", i.e. spacetimes admitting closed non-spacelike curves. Here, we discuss critically whether such causality violations may be used as a criterion to identify unphysical effective actions or whether, and how, causality problems may be resolved by embedding the action in a fundamental, UV complete QFT. We study in detail the case of photon scattering in an Aichelburg-Sexl gravitational shockwave background and calculate the phase shifts in QED for all energies, demonstrating their smooth interpolation from the causality-violating effective action values at low-energy to their manifestly causal high-energy limits. At low energies, these phase shifts may be interpreted as backwards-in-time coordinate jumps as the photon encounters the shock wavefront, and we illustrate h...
Shear viscosity of liquid mixtures Mass dependence
Kaushal, R
2002-01-01
Expressions for zeroth, second, and fourth sum rules of transverse stress autocorrelation function of two component fluid have been derived. These sum rules and Mori's memory function formalism have been used to study shear viscosity of Ar-Kr and isotopic mixtures. It has been found that theoretical result is in good agreement with the computer simulation result for the Ar-Kr mixture. The mass dependence of shear viscosity for different mole fraction shows that deviation from ideal linear model comes even from mass difference in two species of fluid mixture. At higher mass ratio shear viscosity of mixture is not explained by any of the emperical model.
Causal ubiquity in quantum physics a superluminal and local-causal physical ontology
Neelamkavil, Raphael
2014-01-01
A fixed highest criterial velocity (of light) in STR (special theory of relativity) is a convention for a layer of physical inquiry. QM (Quantum Mechanics) avoids action-at-a-distance using this concept, but accepts non-causality and action-at-a-distance in EPR (Einstein-Podolsky-Rosen-Paradox) entanglement experiments. Even in such allegedly non-causal processes, something exists processually in extension-motion, between the causal and the non-causal. If STR theoretically allows real-valued superluminal communication between EPR entangled particles, quantum processes become fully causal. That
Janardhan, Sujatha
2012-01-01
We present a short review of geometric and algebraic approach to causal cones and describe cone preserving transformations and their relationship with causal structure related to special and general theory of relativity. We describe Lie groups, especially matrix Lie groups, homogeneous and symmetric spaces and causal cones and certain implications of these concepts in special and general theory of relativity related to causal structure and topology of space-time. We compare and contrast the results on causal relations with those in the literature for general space-times and compare these relations with K-causal maps. We also describe causal orientations and their implications for space-time topology and discuss some more topologies on space-time which arise as an application of domain theory.
Causal systems categories: differences in novice and expert categorization of causal phenomena.
Rottman, Benjamin M; Gentner, Dedre; Goldwater, Micah B
2012-07-01
We investigated the understanding of causal systems categories--categories defined by common causal structure rather than by common domain content--among college students. We asked students who were either novices or experts in the physical sciences to sort descriptions of real-world phenomena that varied in their causal structure (e.g., negative feedback vs. causal chain) and in their content domain (e.g., economics vs. biology). Our hypothesis was that there would be a shift from domain-based sorting to causal sorting with increasing expertise in the relevant domains. This prediction was borne out: the novice groups sorted primarily by domain and the expert group sorted by causal category. These results suggest that science training facilitates insight about causal structures.
Chen, Qingfei; Liang, Xiuling; Lei, Yi; Li, Hong
2015-05-01
Causally related concepts like "virus" and "epidemic" and general associatively related concepts like "ring" and "emerald" are represented and accessed separately. The Evoked Response Potential (ERP) procedure was used to examine the representations of causal judgment and associative judgment in semantic memory. Participants were required to remember a task cue (causal or associative) presented at the beginning of each trial, and assess whether the relationship between subsequently presented words matched the initial task cue. The ERP data showed that an N400 effect (250-450 ms) was more negative for unrelated words than for all related words. Furthermore, the N400 effect elicited by causal relations was more positive than for associative relations in causal cue condition, whereas no significant difference was found in the associative cue condition. The centrally distributed late ERP component (650-750 ms) elicited by the causal cue condition was more positive than for the associative cue condition. These results suggested that the processing of causal judgment and associative judgment in semantic memory recruited different degrees of attentional and executive resources.
Do trend extraction approaches affect causality detection in climate change studies?
Huang, Xu; Hassani, Hossein; Ghodsi, Mansi; Mukherjee, Zinnia; Gupta, Rangan
2017-03-01
Various scientific studies have investigated the causal link between solar activity (SS) and the earth's temperature (GT). Results from literature indicate that both the detected structural breaks and existing trend have significant effects on the causality detection outcomes. In this paper, we make a contribution to this literature by evaluating and comparing seven trend extraction methods covering various aspects of trend extraction studies to date. In addition, we extend previous work by using Convergent Cross Mapping (CCM) - an advanced non-parametric causality detection technique to provide evidence on the effect of existing trend in global temperature on the causality detection outcome. This paper illustrates the use of a method to find the most reliable trend extraction approach for data preprocessing, as well as provides detailed analyses of the causality detection of each component by this approach to achieve a better understanding of the causal link between SS and GT. Furthermore, the corresponding CCM results indicate increasing significance of causal effect from SS to GT since 1880 to recent years, which provide solid evidences that may contribute on explaining the escalating global tendency of warming up recent decades.
Sinha, B K; Pal, Manisha; Das, P
2014-01-01
The book dwells mainly on the optimality aspects of mixture designs. As mixture models are a special case of regression models, a general discussion on regression designs has been presented, which includes topics like continuous designs, de la Garza phenomenon, Loewner order domination, Equivalence theorems for different optimality criteria and standard optimality results for single variable polynomial regression and multivariate linear and quadratic regression models. This is followed by a review of the available literature on estimation of parameters in mixture models. Based on recent research findings, the volume also introduces optimal mixture designs for estimation of optimum mixing proportions in different mixture models, which include Scheffé’s quadratic model, Darroch-Waller model, log- contrast model, mixture-amount models, random coefficient models and multi-response model. Robust mixture designs and mixture designs in blocks have been also reviewed. Moreover, some applications of mixture desig...
Bound on genuine multipartite correlations from the principle of information causality
Xiang, Yang
2011-01-01
Quantum mechanics is not the unique no-signaling theory which is endowed with stronger-than-classical correlations, and there exists a broad class of no-signaling theories allowing even stronger-than-quantum correlations. The principle of information causality has been suggested to distinguish quantum theory from these nonphysical theories, together with an elegant information-theoretic proof of the quantum bound of two-particle correlations. In this work, we extend this to genuine $N$-particle correlations that cannot be reduced to mixtures of states in which a smaller number of particles are entangled. The violation of Svetlichny's inequality is a confirmation of genuine multipartite correlations. We first express Svetlichny's inequality in terms of multipartite no-signaling boxes, then prove that the strongest genuine multipartite correlations lead to the maximal violation of information causality. The maximal genuine multipartite correlations under the constraint of information causality is found to be eq...
A cold energy mixture theory for the equation of state in solid and porous metal mixtures
Zhang, X. F.; Qiao, L.; Shi, A. S.; Zhang, J.; Guan, Z. W.
2011-07-01
Porous or solid multi-component mixtures are ubiquitous in nature and extensively used as industrial materials such as multifunctional energetic structural materials (MESMs), metallic and ceramic powder for shock consolidation, and porous armor materials. In order to analyze the dynamic behavior of a particular solid or porous metal mixture in any given situation, a model is developed to calculate the Hugoniot data for solid or porous mixtures using only static thermodynamic properties of the components. The model applies the cold energy mixture theory to calculate the isotherm of the components to avoid temperature effects on the mixtures. The isobaric contribution from the thermodynamic equation of state is used to describe the porous material Hugoniot. Dynamic shock responses of solid or porous powder mixtures compacted by shock waves have been analyzed based on the mixture theory and Hugoniot for porous materials. The model is tested on both single-component porous materials such as aluminum 2024, copper, and iron; and on multi-component mixtures such as W/Cu, Fe/Ni, and Al/Ni. The theoretical calculations agree well with the corresponding experimental and simulation results. The present model produces satisfactory correlation with the experimentally obtained Hugoniot data for solid porous materials over a wide pressure range.
Spread of entanglement and causality
Casini, Horacio; Mezei, Márk
2015-01-01
We investigate causality constraints on the time evolution of entanglement entropy after a global quench in relativistic theories. We first provide a general proof that the so-called tsunami velocity is bounded by the speed of light. We then generalize the free particle streaming model of arXiv:cond-mat/0503393 to general dimensions and to an arbitrary entanglement pattern of the initial state. In more than two spacetime dimensions the spread of entanglement in these models is highly sensitive to the initial entanglement pattern, but we are able to prove an upper bound on the normalized rate of growth of entanglement entropy, and hence the tsunami velocity. The bound is smaller than what one gets for quenches in holographic theories, which highlights the importance of interactions in the spread of entanglement in many-body systems. We propose an interacting model which we believe provides an upper bound on the spread of entanglement for interacting relativistic theories. In two spacetime dimensions with multi...
Spread of entanglement and causality
Casini, Horacio; Liu, Hong; Mezei, Márk
2016-07-01
We investigate causality constraints on the time evolution of entanglement entropy after a global quench in relativistic theories. We first provide a general proof that the so-called tsunami velocity is bounded by the speed of light. We then generalize the free particle streaming model of [1] to general dimensions and to an arbitrary entanglement pattern of the initial state. In more than two spacetime dimensions the spread of entanglement in these models is highly sensitive to the initial entanglement pattern, but we are able to prove an upper bound on the normalized rate of growth of entanglement entropy, and hence the tsunami velocity. The bound is smaller than what one gets for quenches in holographic theories, which highlights the importance of interactions in the spread of entanglement in many-body systems. We propose an interacting model which we believe provides an upper bound on the spread of entanglement for interacting relativistic theories. In two spacetime dimensions with multiple intervals, this model and its variations are able to reproduce intricate results exhibited by holographic theories for a significant part of the parameter space. For higher dimensions, the model bounds the tsunami velocity at the speed of light. Finally, we construct a geometric model for entanglement propagation based on a tensor network construction for global quenches.
Yazdani, Azam; Yazdani, Akram; Samiei, Ahmad; Boerwinkle, Eric
2016-04-01
Understanding causal relationships among large numbers of variables is a fundamental goal of biomedical sciences and can be facilitated by Directed Acyclic Graphs (DAGs) where directed edges between nodes represent the influence of components of the system on each other. In an observational setting, some of the directions are often unidentifiable because of Markov equivalency. Additional exogenous information, such as expert knowledge or genotype data can help establish directionality among the endogenous variables. In this study, we use the method of principle component analysis to extract information across the genome in order to generate a robust statistical causal network among phenotypes, the variables of primary interest. The method is applied to 590,020 SNP genotypes measured on 1596 individuals to generate the statistical causal network of 13 cardiovascular disease risk factor phenotypes. First, principal component analysis was used to capture information across the genome. The principal components were then used to identify a robust causal network structure, GDAG, among the phenotypes. Analyzing a robust causal network over risk factors reveals the flow of information in direct and alternative paths, as well as determining predictors and good targets for intervention. For example, the analysis identified BMI as influencing multiple other risk factor phenotypes and a good target for intervention to lower disease risk.
Entanglement Entropy in Causal Set Theory
Sorkin, Rafael D
2016-01-01
Entanglement entropy is now widely accepted as having deep connections with quantum gravity. It is therefore desirable to understand it in the context of causal sets, especially since they provide in a natural manner the UV cutoff needed to render entanglement entropy finite. Defining entropy in a causal set is not straightforward because the type of canonical hypersurface-data on which definitions of entanglement typically rely is not available in a causal set. Instead, we will appeal to a more global expression given in arXiv:1205.2953 which, for a gaussian scalar field, expresses the entropy of a spacetime region in terms of the field's correlation function within that region. Carrying this formula over to the causal set, one obtains an entanglement entropy which is both finite and of a Lorentz invariant nature. Herein we evaluate this entropy for causal sets of 1+1 dimensions, and specifically for order-intervals ("causal diamonds") within the causal set, finding in the first instance an entropy that obey...
Causal localizations in relativistic quantum mechanics
Energy Technology Data Exchange (ETDEWEB)
Castrigiano, Domenico P. L., E-mail: castrig@ma.tum.de; Leiseifer, Andreas D., E-mail: andreas.leiseifer@tum.de [Fakultät für Mathematik, TU München, Boltzmannstraße 3, 85747 Garching (Germany)
2015-07-15
Causal localizations describe the position of quantum systems moving not faster than light. They are constructed for the systems with finite spinor dimension. At the center of interest are the massive relativistic systems. For every positive mass, there is the sequence of Dirac tensor-localizations, which provides a complete set of inequivalent irreducible causal localizations. They obey the principle of special relativity and are fully Poincaré covariant. The boosters are determined by the causal position operator and the other Poincaré generators. The localization with minimal spinor dimension is the Dirac localization. Thus, the Dirac equation is derived here as a mere consequence of the principle of causality. Moreover, the higher tensor-localizations, not known so far, follow from Dirac’s localization by a simple construction. The probability of localization for positive energy states results to be described by causal positive operator valued (PO-) localizations, which are the traces of the causal localizations on the subspaces of positive energy. These causal Poincaré covariant PO-localizations for every irreducible massive relativistic system were, all the more, not known before. They are shown to be separated. Hence, the positive energy systems can be localized within every open region by a suitable preparation as accurately as desired. Finally, the attempt is made to provide an interpretation of the PO-localization operators within the frame of conventional quantum mechanics attributing an important role to the negative energy states.
Mining Causality for Explanation Knowledge from Text
Institute of Scientific and Technical Information of China (English)
Chaveevan Pechsiri; Asanee Kawtrakul
2007-01-01
Mining causality is essential to provide a diagnosis. This research aims at extracting the causality existing within multiple sentences or EDUs (Elementary Discourse Unit). The research emphasizes the use of causality verbs because they make explicit in a certain way the consequent events of a cause, e.g., "Aphids suck the sap from rice leaves. Then leaves will shrink. Later, they will become yellow and dry.". A verb can also be the causal-verb link between cause and effect within EDU(s), e.g., "Aphids suck the sap from rice leaves causing leaves to be shrunk" ("causing" is equivalent to a causal-verb link in Thai). The research confronts two main problems: identifying the interesting causality events from documents and identifying their boundaries. Then, we propose mining on verbs by using two different machine learning techniques, Naive Bayes classifier and Support Vector Machine. The resulted mining rules will be used for the identification and the causality extraction of the multiple EDUs from text. Our multiple EDUs extraction shows 0.88 precision with 0.75 recall from Na'ive Bayes classifier and 0.89 precision with 0.76 recall from Support Vector Machine.
A Simple Test for Causality in Volatility
Directory of Open Access Journals (Sweden)
Chia-Lin Chang
2017-03-01
Full Text Available An early development in testing for causality (technically, Granger non-causality in the conditional variance (or volatility associated with financial returns was the portmanteau statistic for non-causality in the variance of Cheng and Ng (1996. A subsequent development was the Lagrange Multiplier (LM test of non-causality in the conditional variance by Hafner and Herwartz (2006, who provided simulation results to show that their LM test was more powerful than the portmanteau statistic for sample sizes of 1000 and 4000 observations. While the LM test for causality proposed by Hafner and Herwartz (2006 is an interesting and useful development, it is nonetheless arbitrary. In particular, the specification on which the LM test is based does not rely on an underlying stochastic process, so the alternative hypothesis is also arbitrary, which can affect the power of the test. The purpose of the paper is to derive a simple test for causality in volatility that provides regularity conditions arising from the underlying stochastic process, namely a random coefficient autoregressive process, and a test for which the (quasi- maximum likelihood estimates have valid asymptotic properties under the null hypothesis of non-causality. The simple test is intuitively appealing as it is based on an underlying stochastic process, is sympathetic to Granger’s (1969, 1988 notion of time series predictability, is easy to implement, and has a regularity condition that is not available in the LM test.
Diagnosis and causal explanation in psychiatry.
Maung, Hane Htut
2016-12-01
In clinical medicine, a diagnosis can offer an explanation of a patient's symptoms by specifying the pathology that is causing them. Diagnoses in psychiatry are also sometimes presented in clinical texts as if they pick out pathological processes that cause sets of symptoms. However, current evidence suggests the possibility that many diagnostic categories in psychiatry are highly causally heterogeneous. For example, major depressive disorder may not be associated with a single type of underlying pathological process, but with a range of different causal pathways, each involving complex interactions of various biological, psychological, and social factors. This paper explores the implications of causal heterogeneity for whether psychiatric diagnoses can be said to serve causal explanatory roles in clinical practice. I argue that while they may fall short of picking out a specific cause of the patient's symptoms, they can nonetheless supply different sorts of clinically relevant causal information. In particular, I suggest that some psychiatric diagnoses provide negative information that rules out certain causes, some provide approximate or disjunctive information about the range of possible causal processes, and some provide causal information about the relations between the symptoms themselves.
An Empirical Investigation into Causality of Unsafe Act and Recovery during EOP Simulation
Energy Technology Data Exchange (ETDEWEB)
Choi, Sun Yeong; Jung, Won Dea [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)
2014-08-15
A data collection worksheet and guideline to collect HRA (Human Reliability Analysis) data with simulator data sources were developed for the HRA data handbook project by KAERI. Using the data worksheet, simulator data were collected and analyzed for an HRA qualitative database. The purpose of this paper is to define the causalities of operators' UAs (Unsafe Acts) ending in an inappropriate component manipulation and recovery during an EOP (Emergency Operating Procedure) operation, and to show some results for the causality from a case study. The reason we suggest the causality of an UA is because an inappropriate manipulation during an EOP operation can be resulted by the causality among operators in an MCR (Main Control Room). Therefore, a 'causality' data field was inserted into the data worksheet to identify the real initiator, and related operators for an inappropriate component manipulation. With this 'causality' data field, an HRA analyzer can establish who caused an UA (or a recovery) and who was involved in the process. They can also calculate the HEP (Human Error Probability) grouped by the initiator if they are interested in the HEP by the initiator.
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.
Barć, Justyna; Gregoraszczuk, Ewa Łucja
2014-08-01
In this study we tried to answer a question which component of Halowax 1051 is responsible for, observed in previously published study, androgenic effects of the mixture, and whether it is possible to draw conclusions about the action of mixtures by examining the effect of an indicator congener. Ovarian follicles were incubated with individual congeners of an artificial mixture for 6-24h. At the end of the incubation period, media were collected for determination of progesterone (P4), androstenedione (A4), testosterone (T) and estradiol (E2) levels by enzyme immunoassay, and follicles were retained for an examination of aryl hydrocarbon receptor (AHR), cytochrome p450 enzymes (CYP1A1, CYP17, CYP19), and 17β-hydroxysteroid dehydrogenase (17β-HSD) protein expression by Western blotting. CN73 in dose 50pg/ml after 6h had no effect and decreased AHR expression after 24h, while at dose 400pg/ml increased AHR protein expression after 6h of exposure which remained elevated after 24h. CN74 and CN75 at both concentrations tested (25 and 50pg/ml) stimulated AHR protein expression after 6h and decreased it after 24h of exposure. Individual congeners induced a rapid increase in CYP1A1 protein expression, with a rank order of efficacy of CN73>CN74=CN75. All congeners increased P4/A4 and T/E2 secretion ratios in association with a decrease in the A4/T ratio, pointing to androgenic and anti-estrogenic properties of PCNs in ovarian follicles. The most potent congener in this context was CN73. The effects of mixtures were comparable to those of CN74 and CN75, and were not as strong as those observed for CN73. Collectively, these data suggest antagonistic actions of single congeners in a mixture, indicating that the actions of a mixture cannot be predicted based on the actions of individual congeners.
Analytical processing of binary mixture information by olfactory bulb glomeruli.
Directory of Open Access Journals (Sweden)
Max L Fletcher
Full Text Available Odors are rarely composed of a single compound, but rather contain a large and complex variety of chemical components. Often, these mixtures are perceived as having unique qualities that can be quite different than the combination of their components. In many cases, a majority of the components of a mixture cannot be individually identified. This synthetic processing of odor information suggests that individual component representations of the mixture must interact somewhere along the olfactory pathway. The anatomical nature of sensory neuron input into segregated glomeruli with the bulb suggests that initial input of odor information into the bulb is analytic. However, a large network of interneurons within the olfactory bulb could allow for mixture interactions via mechanisms such as lateral inhibition. Currently in mammals, it is unclear if postsynaptic mitral/tufted cell glomerular mixture responses reflect the analytical mixture input, or provide the initial basis for synthetic processing with the olfactory system. To address this, olfactory bulb glomerular binary mixture representations were compared to representations of each component using transgenic mice expressing the calcium indicator G-CaMP2 in olfactory bulb mitral/tufted cells. Overall, dorsal surface mixture representations showed little mixture interaction and often appeared as a simple combination of the component representations. Based on this, it is concluded that dorsal surface glomerular mixture representations remain largely analytical with nearly all component information preserved.
Scalar Field Green Functions on Causal Sets
Ahmed, S. Nomaan; Dowker, Fay; Surya, Sumati
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 2-d model provides a Green function for the massive scalar field on causal sets approximated by any topologically trivial 2 dimensional spacetime. We explicitly ...
On the origin of Hill's causal criteria.
Morabia, A
1991-09-01
The rules to assess causation formulated by the eighteenth century Scottish philosopher David Hume are compared to Sir Austin Bradford Hill's causal criteria. The strength of the analogy between Hume's rules and Hill's causal criteria suggests that, irrespective of whether Hume's work was known to Hill or Hill's predecessors, Hume's thinking expresses a point of view still widely shared by contemporary epidemiologists. The lack of systematic experimental proof to causal inferences in epidemiology may explain the analogy of Hume's and Hill's, as opposed to Popper's, logic.
Intrinsic Universality of Causal Graph Dynamics
Directory of Open Access Journals (Sweden)
Simon Martiel
2013-09-01
Full Text Available Causal graph dynamics are transformations over graphs that capture two important symmetries of physics, namely causality and homogeneity. They can be equivalently defined as continuous and translation invariant transformations or functions induced by a local rule applied simultaneously on every vertex of the graph. Intrinsic universality is the ability of an instance of a model to simulate every other instance of the model while preserving the structure of the computation at every step of the simulation. In this work we present the construction of a family of intrinsically universal instances of causal graphs dynamics, each instance being able to simulate a subset of instances.
Hubeny, V E; Hubeny, Veronika E.; Rangamani, Mukund
2002-01-01
We discuss the causal structure of pp-wave spacetimes using the ideal point construction outlined by Geroch, Kronheimer, and Penrose. This generalizes the recent work of Marolf and Ross, who considered similar issues for plane wave spacetimes. We address the question regarding the dimension of the causal boundary for certain specific pp-wave backgrounds. In particular, we demonstrate that the pp-wave spacetime which gives rise to the N = 2 sine-Gordon string world-sheet theory is geodesically complete and has a one-dimensional causal boundary.
Dual Causality and the Autonomy of Biology.
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.
Causality in 3D Massive Gravity Theories
Edelstein, Jose D; Kilicarslan, Ercan; Leoni, Matias; Tekin, Bayram
2016-01-01
We study the constraints coming from local causality requirement in various 2+1 dimensional dynamical theories of gravity. In Topologically Massive Gravity, with a single parity noninvariant massive degree of freedom, and in New Massive Gravity, with two massive spin-$2$ degrees of freedom, causality and unitarity are compatible with each other and they both require the Newton's constant to be negative. In their extensions, such as the Born-Infeld gravity and the minimal massive gravity the situation is similar and quite different from their higher dimensional counterparts, such as quadratic (e.g., Einstein-Gauss-Bonnet) or cubic theories, where causality and unitarity are in conflict.
Granger causality and contiguity between stochastic processes
Energy Technology Data Exchange (ETDEWEB)
Triacca, Umberto [Universita di L' Aquila, Roio Poggio, I-67040 L' Aquila (Italy)]. E-mail: triacca@ec.univaq.it
2007-03-05
Although according to many econometricians the definition of causality proposed by Granger differs from other definitions of causation in the philosophy of science, in this Letter we argue that it is not completely lacking in philosophical legitimacy. We attempt to shed new light on the nexus between Granger causality and the concept of contiguity. In particular, we prove that the existence of a Granger causal link between two stochastic processes requires that these be 'contiguous' or that there exist a chain of processes, one contiguous to the next, which link the two processes.
Causality and Time in Historical Institutionalism
DEFF Research Database (Denmark)
Mahoney, James; Mohamedali, Khairunnisa; Nguyen, Christoph
2016-01-01
This chapter explores the dual concern with causality and time in historical institutionalism using a graphical approach. The analysis focuses on three concepts that are central to this field: critical junctures, gradual change, and path dependence. The analysis makes explicit and formal the logic...... underlying studies that use these “causal-temporal” concepts. The chapter shows visually how causality and temporality are linked to one another in varying ways depending on the particular pattern of change. The chapter provides new tools for describing and understanding change in historical- institutional...
Atomistic Simulations of Bicelle Mixtures
Jiang, Yong; Wang, Hao; Kindt, James T.
2010-01-01
Mixtures of long- and short-tail phosphatidylcholine lipids are known to self-assemble into a variety of aggregates combining flat bilayerlike and curved micellelike features, commonly called bicelles. Atomistic simulations of bilayer ribbons and perforated bilayers containing dimyristoylphosphatidylcholine (DMPC, di-C14 tails) and dihexanoylphosphatidylcholine (DHPC, di-C6 tails) have been carried out to investigate the partitioning of these components between flat and curved microenvironmen...
Transfer effects between moral dilemmas: a causal model theory.
Wiegmann, Alex; Waldmann, Michael R
2014-04-01
Evaluations of analogous situations are an important source for our moral intuitions. A puzzling recent set of findings in experiments exploring transfer effects between intuitions about moral dilemmas has demonstrated a striking asymmetry. Transfer often occurred with a specific ordering of moral dilemmas, but not when the sequence was reversed. In this article we present a new theory of transfer between moral intuitions that focuses on two components of moral dilemmas, namely their causal structure and their default evaluations. According to this theory, transfer effects are expected when the causal models underlying the considered dilemmas allow for a mapping of the highlighted aspect of the first scenario onto the causal structure of the second dilemma, and when the default evaluations of the two dilemmas substantially differ. The theory's key predictions for the occurrence and the direction of transfer effects between two moral dilemmas are tested in five experiments with various variants of moral dilemmas from different domains. A sixth experiment tests the predictions of the theory for how the target action in the moral dilemmas is represented.
A Multivariate Granger Causality Concept towards Full Brain Functional Connectivity.
Schmidt, Christoph; Pester, Britta; Schmid-Hertel, Nicole; Witte, Herbert; Wismüller, Axel; Leistritz, Lutz
2016-01-01
Detecting changes of spatially high-resolution functional connectivity patterns in the brain is crucial for improving the fundamental understanding of brain function in both health and disease, yet still poses one of the biggest challenges in computational neuroscience. Currently, classical multivariate Granger Causality analyses of directed interactions between single process components in coupled systems are commonly restricted to spatially low- dimensional data, which requires a pre-selection or aggregation of time series as a preprocessing step. In this paper we propose a new fully multivariate Granger Causality approach with embedded dimension reduction that makes it possible to obtain a representation of functional connectivity for spatially high-dimensional data. The resulting functional connectivity networks may consist of several thousand vertices and thus contain more detailed information compared to connectivity networks obtained from approaches based on particular regions of interest. Our large scale Granger Causality approach is applied to synthetic and resting state fMRI data with a focus on how well network community structure, which represents a functional segmentation of the network, is preserved. It is demonstrated that a number of different community detection algorithms, which utilize a variety of algorithmic strategies and exploit topological features differently, reveal meaningful information on the underlying network module structure.
A Multivariate Granger Causality Concept towards Full Brain Functional Connectivity.
Directory of Open Access Journals (Sweden)
Christoph Schmidt
Full Text Available Detecting changes of spatially high-resolution functional connectivity patterns in the brain is crucial for improving the fundamental understanding of brain function in both health and disease, yet still poses one of the biggest challenges in computational neuroscience. Currently, classical multivariate Granger Causality analyses of directed interactions between single process components in coupled systems are commonly restricted to spatially low- dimensional data, which requires a pre-selection or aggregation of time series as a preprocessing step. In this paper we propose a new fully multivariate Granger Causality approach with embedded dimension reduction that makes it possible to obtain a representation of functional connectivity for spatially high-dimensional data. The resulting functional connectivity networks may consist of several thousand vertices and thus contain more detailed information compared to connectivity networks obtained from approaches based on particular regions of interest. Our large scale Granger Causality approach is applied to synthetic and resting state fMRI data with a focus on how well network community structure, which represents a functional segmentation of the network, is preserved. It is demonstrated that a number of different community detection algorithms, which utilize a variety of algorithmic strategies and exploit topological features differently, reveal meaningful information on the underlying network module structure.
Low temperature asphalt mixtures
Modrijan, Damjan
2006-01-01
This thesis presents the problem of manufacturing and building in the asphalt mixtures produced by the classical hot procedure and the possibility of manufacturing low temperature asphalt mixtures.We will see the main advantages of low temperature asphalt mixtures prepared with bitumen with organic addition Sasobit and compare it to the classical asphalt mixtures. The advantages and disadvantages of that are valued in the practical example in the conclusion.
A Causal Model for Diagnostic Reasoning
Institute of Scientific and Technical Information of China (English)
PENG Guoqiang; CHENG Hu
2000-01-01
Up to now, there have been many methods for knowledge representation and reasoning in causal networks, but few of them include the research on the coactions of nodes. In practice, ignoring these coactions may influence the accuracy of reasoning and even give rise to incorrect reasoning. In this paper, based on multilayer causal networks, the definitions on coaction nodes are given to construct a new causal network called Coaction Causal Network, which serves to construct a model of neural network for diagnosis followed by fuzzy reasoning, and then the activation rules are given and neural computing methods are used to finish the diagnostic reasoning. These methods are proved in theory and a method of computing the number of solutions for the diagnostic reasoning is given. Finally, the experiments and the conclusions are presented.
The Temporal Logic of Causal Structures
Kleinberg, Samantha
2012-01-01
Computational analysis of time-course data with an underlying causal structure is needed in a variety of domains, including neural spike trains, stock price movements, and gene expression levels. However, it can be challenging to determine from just the numerical time course data alone what is coordinating the visible processes, to separate the underlying prima facie causes into genuine and spurious causes and to do so with a feasible computational complexity. For this purpose, we have been developing a novel algorithm based on a framework that combines notions of causality in philosophy with algorithmic approaches built on model checking and statistical techniques for multiple hypotheses testing. The causal relationships are described in terms of temporal logic formulae, reframing the inference problem in terms of model checking. The logic used, PCTL, allows description of both the time between cause and effect and the probability of this relationship being observed. We show that equipped with these causal f...
Identifiability of Causal Graphs using Functional Models
Peters, Jonas; Janzing, Dominik; Schoelkopf, Bernhard
2012-01-01
This work addresses the following question: Under what assumptions on the data generating process can one infer the causal graph from the joint distribution? The approach taken by conditional independence-based causal discovery methods is based on two assumptions: the Markov condition and faithfulness. It has been shown that under these assumptions the causal graph can be identified up to Markov equivalence (some arrows remain undirected) using methods like the PC algorithm. In this work we propose an alternative by defining Identifiable Functional Model Classes (IFMOCs). As our main theorem we prove that if the data generating process belongs to an IFMOC, one can identify the complete causal graph. To the best of our knowledge this is the first identifiability result of this kind that is not limited to linear functional relationships. We discuss how the IFMOC assumption and the Markov and faithfulness assumptions relate to each other and explain why we believe that the IFMOC assumption can be tested more eas...
Selecting appropriate cases when tracing causal mechanisms
DEFF Research Database (Denmark)
Beach, Derek; Pedersen, Rasmus Brun
2016-01-01
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......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...... 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...
Causality Between Urban Concentration and Environmental Quality
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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.
Risk and causality in newspaper reporting.
Boholm, Max
2009-11-01
The study addresses the textual representation of risk and causality in news media reporting. The analytical framework combines two theoretical perspectives: media frame analysis and the philosophy of causality. Empirical data derive from selected newspaper articles on risks in the Göta älv river valley in southwest Sweden from 1994 to 2007. News media content was coded and analyzed with respect to causal explanations of risk issues. At the level of individual articles, this study finds that the media provide simple causal explanations of risks such as water pollution, landslides, and flooding. Furthermore, these explanations are constructed, or framed, in various ways, the same risk being attributed to different causes in different articles. However, the study demonstrates that a fairly complex picture of risks in the media emerges when extensive material is analyzed systematically.
The Gravity Dual of Boundary Causality
Engelhardt, Netta
2016-01-01
In gauge/gravity duality, points which are not causally related on the boundary cannot be causally related through the bulk; this is the statement of boundary causality. By the Gao-Wald theorem, the averaged null energy condition in the bulk is sufficient to ensure this property. Here we proceed in the converse direction: we derive a necessary as well as sufficient condition for the preservation of boundary causality under perturbative (quantum or stringy) corrections to the bulk. The condition that we find is a (background-dependent) constraint on the amount by which light cones can "open" over all null bulk geodesics. We show that this constraint is weaker than the averaged null energy condition.
Synergy, redundancy and unnormalized Granger causality
Stramaglia, Sebastiano; Cortés, Jesus M; Marinazzo, Daniele
2015-01-01
We analyze by means of Granger causality the effect of synergy and redundancy in the inference (from time series data) of the information flow between subsystems of a complex network. Whilst fully conditioned Granger causality is not affected by synergy, the pairwise analysis fails to put in evidence synergetic effects. We show that maximization of the total Granger causality to a given target, over all the possible partitions of the set of driving variables, puts in evidence redundant multiplets of variables influencing the target, provided that an {\\it unnormalized} definition of Granger causality is adopted. Along the same lines we also introduce a pairwise index of synergy (w.r.t. to information flow to a third variable) which is zero when two independent sources additively influence a common target, differently from previous definitions of synergy.
The Scalar Curvature of a Causal Set
Benincasa, Dionigi M T
2010-01-01
A one parameter family of retarded linear operators on scalar fields on causal sets is introduced. When the causal set is well-approximated by 4 dimensional Minkowski spacetime, the operators are Lorentz invariant but nonlocal, are parametrised by the scale of the nonlocality and approximate the continuum scalar D'Alembertian, $\\Box$, when acting on fields that vary slowly on the nonlocality scale. The same operators can be applied to scalar fields on causal sets which are well-approximated by curved spacetimes in which case they approximate $\\Box - {{1/2}}R$ where $R$ is the Ricci scalar curvature. This can used to define an approximately local action functional for causal sets.
Vitalistic causality in young children's naive biology.
Inagaki, Kayoko; Hatano, Giyoo
2004-08-01
One of the key issues in conceptual development research concerns what kinds of causal devices young children use to understand the biological world. We review evidence that children predict and interpret biological phenomena, especially human bodily processes, on the basis of 'vitalistic causality'. That is, they assume that vital power or life force taken from food and water makes humans active, prevents them from being taken ill, and enables them to grow. These relationships are also extended readily to other animals and even to plants. Recent experimental results show that a majority of preschoolers tend to choose vitalistic explanations as most plausible. Vitalism, together with other forms of intermediate causality, constitute unique causal devices for naive biology as a core domain of thought.
The Causal Foundations of Structural Equation Modeling
2012-02-16
The Causal Foundations of Structural Equation Modeling Judea Pearl University of California, Los Angeles Computer Science Department Los Angeles, CA...Handbook of Structural Equation Modeling . New York: Guilford Press. TECHNICAL REPORT R-370 February 2012 Report Documentation Page Form...COVERED 00-00-2012 to 00-00-2012 4. TITLE AND SUBTITLE The Causal Foundations of Structural Equation Modeling 5a. CONTRACT NUMBER 5b. GRANT
Locally Causal Dynamical Triangulations in Two Dimensions
Loll, Renate
2015-01-01
We analyze the universal properties of a new two-dimensional quantum gravity model defined in terms of Locally Causal Dynamical Triangulations (LCDT). Measuring the Hausdorff and spectral dimensions of the dynamical geometrical ensemble, we find numerical evidence that the continuum limit of the model lies in a new universality class of two-dimensional quantum gravity theories, inequivalent to both Euclidean and Causal Dynamical Triangulations.
Causales de ausencia de responsabilidad penal
Jaime Sandoval Fernández
2003-01-01
Este trabajo se ocupa de las causales de ausencia de responsabilidad penal, especialmente de aquellas que tienen efecto en el injusto. Como subtemas se delimita el concepto de responsabilidad penal y su ausencia. Se estudian las principales teorias a cerca de la relación tipicidad-antijuridicidad y su incidencia en el derecho penal colombiano. Por último contiene una propuesta acerca de cómo deberian agruparse las causales del arto 32 C. PlOO.
Causales de ausencia de responsabilidad penal
Directory of Open Access Journals (Sweden)
Jaime Sandoval Fernández
2003-01-01
Full Text Available Este trabajo se ocupa de las causales de ausencia de responsabilidad penal, especialmente de aquellas que tienen efecto en el injusto. Como subtemas se delimita el concepto de responsabilidad penal y su ausencia. Se estudian las principales teorias a cerca de la relación tipicidad-antijuridicidad y su incidencia en el derecho penal colombiano. Por último contiene una propuesta acerca de cómo deberian agruparse las causales del arto 32 C. PlOO.
Illness causal beliefs in Turkish immigrants
Klimidis Steven; Minas Harry; Tuncer Can
2007-01-01
Abstract Background People hold a wide variety of beliefs concerning the causes of illness. Such beliefs vary across cultures and, among immigrants, may be influenced by many factors, including level of acculturation, gender, level of education, and experience of illness and treatment. This study examines illness causal beliefs in Turkish-immigrants in Australia. Methods Causal beliefs about somatic and mental illness were examined in a sample of 444 members of the Turkish population of Melbo...
Causal Structures in Gauss-Bonnet gravity
Izumi, Keisuke
2014-01-01
We analyze causal structures in Gauss-Bonnet gravity. It is known that Gauss-Bonnet gravity potentially has superluminal propagation of gravitons due to its non-canonical kinetic terms. In a theory with superluminal modes, an analysis of causality based on null curves makes no sense, and thus, we need to analyse them in a different way. In this paper, using the method of the characteristics, we analyze the causal structure in Gauss-Bonnet gravity. We have the result that, on a Killing horizon, gravitons can propagate in the null direction tangent to the Killing horizon. Therefore, a Killing horizon can be a causal edge as in the case of general relativity, i.e. a Killing horizon is the "event horizon" in the sense of causality. We also analyze causal structures on dynamical solutions with $(D-2)$-dimensional maximal symmetry, including spherically symmetric and flat spaces. If the geometrical null energy condition, $R_{AB}N^AN^B \\ge 0$ for any null vector $N^A$, is satisfied, the radial velocity of gravitons ...
Kant on causal laws and powers.
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.
Rowlinson, J S; Baldwin, J E; Buckingham, A D; Danishefsky, S
2013-01-01
Liquids and Liquid Mixtures, Third Edition explores the equilibrium properties of liquids and liquid mixtures and relates them to the properties of the constituent molecules using the methods of statistical thermodynamics. Topics covered include the critical state, fluid mixtures at high pressures, and the statistical thermodynamics of fluids and mixtures. This book consists of eight chapters and begins with an overview of the liquid state and the thermodynamic properties of liquids and liquid mixtures, including vapor pressure and heat capacities. The discussion then turns to the thermodynami
Model structure selection in convolutive mixtures
DEFF Research Database (Denmark)
Dyrholm, Mads; Makeig, Scott; Hansen, Lars Kai
2006-01-01
The CICAAR algorithm (convolutive independent component analysis with an auto-regressive inverse model) allows separation of white (i.i.d) source signals from convolutive mixtures. We introduce a source color model as a simple extension to the CICAAR which allows for a more parsimoneous represent......The CICAAR algorithm (convolutive independent component analysis with an auto-regressive inverse model) allows separation of white (i.i.d) source signals from convolutive mixtures. We introduce a source color model as a simple extension to the CICAAR which allows for a more parsimoneous...... representation in many practical mixtures. The new filter-CICAAR allows Bayesian model selection and can help answer questions like: 'Are we actually dealing with a convolutive mixture?'. We try to answer this question for EEG data....
Model structure selection in convolutive mixtures
DEFF Research Database (Denmark)
Dyrholm, Mads; Makeig, S.; Hansen, Lars Kai
2006-01-01
The CICAAR algorithm (convolutive independent component analysis with an auto-regressive inverse model) allows separation of white (i.i.d) source signals from convolutive mixtures. We introduce a source color model as a simple extension to the CICAAR which allows for a more parsimonious represent......The CICAAR algorithm (convolutive independent component analysis with an auto-regressive inverse model) allows separation of white (i.i.d) source signals from convolutive mixtures. We introduce a source color model as a simple extension to the CICAAR which allows for a more parsimonious...... representation in many practical mixtures. The new filter-CICAAR allows Bayesian model selection and can help answer questions like: ’Are we actually dealing with a convolutive mixture?’. We try to answer this question for EEG data....
Modeling methods for mixture-of-mixtures experiments applied to a tablet formulation problem.
Piepel, G F
1999-01-01
During the past few years, statistical methods for the experimental design, modeling, and optimization of mixture experiments have been widely applied to drug formulation problems. Different methods are required for mixture-of-mixtures (MoM) experiments in which a formulation is a mixture of two or more "major" components, each of which is a mixture of one or more "minor" components. Two types of MoM experiments are briefly described. A tablet formulation optimization example from a 1997 article in this journal is used to illustrate one type of MoM experiment and corresponding empirical modeling methods. Literature references that discuss other methods for MoM experiments are also provided.
Fitting mixture distributions to phenylthiocarbamide (PTC) sensitivity.
Jones, P N; G.J. McLachlan
1991-01-01
A technique for fitting mixture distributions to phenylthiocarbamide (PTC) sensitivity is described. Under the assumptions of Hardy-Weinberg equilibrium, a mixture of three normal components is postulated for the observed distribution, with the mixing parameters corresponding to the proportions of the three genotypes associated with two alleles A and a acting at a single locus. The corresponding genotypes AA, Aa, and aa are then considered to have separate means and variances. This paper is c...
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.
Causal impressions: predicting when, not just whether.
Young, Michael E; Rogers, Ester T; Beckmann, Joshua S
2005-03-01
In 1739, David Hume established the so-called cues to causality--environmental cues that are important to the inference of causality. Although this descriptive account has been corroborated experimentally, it has not been established why these cues are useful, except that they may reflect statistical regularities in the environment. One of the cues to causality, covariation, helps predict whether an effect will occur, but not its time of occurrence. In the present study, evidence is provided that spatial and temporal contiguity improve an observer's ability to predict when an effect will occur, thus complementing the utility of covariation as a predictor of whether an effect will occur. While observing Michotte's (1946/1963) launching effect, participants showed greater accuracy and precision in their predictions of the onset of movement by the launched object when there was spatial and temporal contiguity. Furthermore, when auditory cues that bridged a delayed launch were included, causal ratings and predictability were similarly affected. These results suggest that the everyday inference of causality relies on our ability to predict whether and when an effect will occur.
Reducing the Bias of Causality Measures
Papana, A; Larsson, P G
2011-01-01
Measures of the direction and strength of the interdependence between two time series are evaluated and modified in order to reduce the bias in the estimation of the measures, so that they give zero values when there is no causal effect. For this, point shuffling is employed as used in the frame of surrogate data. This correction is not specific to a particular measure and it is implemented here on measures based on state space reconstruction and information measures. The performance of the causality measures and their modifications is evaluated on simulated uncoupled and coupled dynamical systems and for different settings of embedding dimension, time series length and noise level. The corrected measures, and particularly the suggested corrected transfer entropy, turn out to stabilize at the zero level in the absence of causal effect and detect correctly the direction of information flow when it is present. The measures are also evaluated on electroencephalograms (EEG) for the detection of the information fl...
Normalizing the causality between time series
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.
Noncommutative geometry, Lorentzian structures and causality
Franco, Nicolas
2014-01-01
The theory of noncommutative geometry provides an interesting mathematical background for developing new physical models. In particular, it allows one to describe the classical Standard Model coupled to Euclidean gravity. However, noncommutative geometry has mainly been developed using the Euclidean signature, and the typical Lorentzian aspects of space-time, the causal structure in particular, are not taken into account. We present an extension of noncommutative geometry \\`a la Connes suitable the for accommodation of Lorentzian structures. In this context, we show that it is possible to recover the notion of causality from purely algebraic data. We explore the causal structure of a simple toy model based on an almost commutative geometry and we show that the coupling between the space-time and an internal noncommutative space establishes a new `speed of light constraint'.
Causal binding of actions to their effects.
Buehner, Marc J; Humphreys, Gruffydd R
2009-10-01
According to widely held views in cognitive science harking back to David Hume, causality cannot be perceived directly, but instead is inferred from patterns of sensory experience, and the quality of these inferences is determined by perceivable quantities such as contingency and contiguity. We report results that suggest a reversal of Hume's conjecture: People's sense of time is warped by the experience of causality. In a stimulus-anticipation task, participants' response behavior reflected a shortened experience of time in the case of target stimuli participants themselves had generated, relative to equidistant, equally predictable stimuli they had not caused. These findings suggest that causality in the mind leads to temporal binding of cause and effect, and extend and generalize beyond earlier claims of intentional binding between action and outcome.
Causal inheritence in plane wave quotients
Energy Technology Data Exchange (ETDEWEB)
Hubeny, Veronika E.; Rangamani, Mukund; Ross, Simon F.
2003-11-24
We investigate the appearance of closed timelike curves in quotients of plane waves along spacelike isometries. First we formulate a necessary and sufficient condition for a quotient of a general spacetime to preserve stable causality. We explicitly show that the plane waves are stably causal; in passing, we observe that some pp-waves are not even distinguishing. We then consider the classification of all quotients of the maximally supersymmetric ten-dimensional plane wave under a spacelike isometry, and show that the quotient will lead to closed timelike curves iff the isometry involves a translation along the u direction. The appearance of these closed timelike curves is thus connected to the special properties of the light cones in plane wave spacetimes. We show that all other quotients preserve stable causality.
Diabetes: the layperson's theories of causality.
Mercado-Martinez, Francisco J; Ramos-Herrera, Igor Martin
2002-07-01
The authors examine laypersons' perspectives of illness: the content of causal explanations of diabetes and differences in explanations according to gender. Qualitative research was carried out in Guadalajara, Mexico. A nonprobabilistic sample of 20 diabetic individuals participated in interviews, and the content of the interviews was analyzed. On the origin of their condition, participants offered explanations that match neither the biomedical model nor any other formal causal theory. Participants attributed the onset of diabetes to socioemotional circumstances linked to their life experiences and practices. Men attributed causality to work and social circumstances outside the home; women attributed it to family life and domestic circumstances. The authors discuss how lay theories can be useful for the reorganization of health services.
Causality, initial conditions and inflationary magnetogenesis
Tsagas, Christos G
2016-01-01
The post-inflationary evolution of inflation-produced magnetic fields, conventional or not, can change dramatically when two fundamental issues are accounted for. The first is causality, which demands that local physical processes can never affect superhorizon perturbations. The second is the nature of the transition from inflation to reheating and then to the radiation era, which determine the initial conditions at the start of these epochs. Technically, the latter issue can be addressed by appealing to Israel's junction conditions. Causality implies that inflationary magnetic fields dot not freeze into the matter until they have re-entered the causal horizon. The nature of cosmological transitions and the associated initial conditions, on the other hand, determine the large-scale magnetic evolution after inflation. Put together, the two can slow down the adiabatic decay of superhorizon-sized magnetic fields throughout their post-inflationary life and thus lead to considerably stronger residual strengths. Th...
Metrics and causality on Moyal planes
Franco, Nicolas
2015-01-01
Metrics structures stemming from the Connes distance promote Moyal planes to the status of quantum metric spaces. We discuss this aspect in the light of recent developments, emphasizing the role of Moyal planes as representative examples of a recently introduced notion of quantum (noncommutative) locally compact space. We move then to the framework of Lorentzian noncommutative geometry and we examine the possibility of defining a notion of causality on Moyal plane, which is somewhat controversial in the area of mathematical physics. We show the actual existence of causal relations between the elements of a particular class of pure (coherent) states on Moyal plane with related causal structure similar to the one of the usual Minkowski space, up to the notion of locality.
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...... injections in intermediate-to-strongly coupled systems could enable more accurate causal inferences. Given the inherent noisy nature of real-world systems, our findings enable a more accurate evaluation of CCM applicability and advance suggestions on how to overcome its weaknesses....
Causality bounds for neutron-proton scattering
Energy Technology Data Exchange (ETDEWEB)
Elhatisari, S.; Lee, D. [North Carolina State University, Department of Physics, Raleigh, NC (United States)
2012-08-15
We consider the constraints of causality and unitarity for the low-energy interactions of protons and neutrons. We derive a general theorem that non-vanishing partial-wave mixing cannot be reproduced with zero-range interactions without violating causality or unitarity. We define and calculate interaction length scales which we call the causal range and the Cauchy-Schwarz range for all spin channels up to J=3. For some channels we find that these length scales are as large as 5fm. We investigate the origin of these large lengths and discuss their significance for the choice of momentum cutoff scales in effective field theory and universality in many-body Fermi systems. (orig.)
Causalities of the Taiwan stock market
Ting, Julian Juhi-Lian
2003-06-01
Volatility, fitting with first-order Landau expansion, stationarity, and causality of the Taiwan stock market (TAIEX) are investigated based on daily records. Instead of consensuses that consider stock market index change as a random time series we propose the market change as a dual time series consists of the index and the corresponding volume. Therefore, causalities between these two time series are investigated. Our results suggest the volume time series is of second-order importance than the index time series. The index time series receives slightly stronger influence from the previous 67th trading day, while the volume time series is slightly stronger influenced by the previous 62nd trading day.
Dynamics and causality constraints in field theory
De Souza, M M
1997-01-01
We discuss the physical meaning and the geometric interpretation of causality implementation in classical field theories. Causality is normally implemented through kinematical constraints on fields but we show that in a zero-distance limit they also carry a dynamical information, which calls for a revision of our standard concepts of interacting fields. The origin of infinities and other inconsistencies in field theories is traced to fields defined with support on the lightcone; a finite and consistent field theory requires a lightcone generator as the field support.
Cosmic Time Machines: the Causality Issue
Directory of Open Access Journals (Sweden)
Felice Fernando de
2013-09-01
Full Text Available Continued gravitational collapse gives rise to curvature singularities. If a curvature singularity is globally naked then the space-time may be causally future illbehaved admitting closed time-like or null curves which extend to asymptotic distances and generate a Cosmic Time Machine (de Felice (1995 Lecture Notes in Physics 455, 99 [6]. The existence of Cosmic Time Machines makes it plausible the violation of causality. I conjecture that this circumstance is prevented by some, yet unknown, physical process and show that such a mechanism indeed exists in the Kerr spacetime.
Papular urticaria: A review of causal agents in Colombia.
Lozano, Ana Milena; López, Juan Felipe; Zakzuk, Josefina; García, Elizabeth
2016-12-01
Papular urticaria is a chronic allergic reaction induced by insect bites, which is common in the tropics. The objective of this review was to deepen on epidemiological and immunological aspects of this disease, focused on data published in Latin American countries.We conducted a non-systematic review of the literature through electronic search on the epidemiology of papular urticaria, the entomological characteristics of the causative agents and associated immunological mechanisms.Several reports from medical centers suggest that papular urticaria is common in Latin America. Only one epidemiological survey designed to estimate prevalence of papular urticaria has been published, reporting that about a quarter of children under six years of age is affected by this condition in Bogotá. There is evidence on the causal relationship among exposure to indoor fleas, poverty and papular urticaria in Bogotá, a representative city of the Andean altitudes. Information about causal insects in tropical warmer areas is scarce, although from clinical reports Aedes aegypti and Culex quienquefasciatus appear to be the most common. Th2 cellular-mediated mechanisms are involved in its pathogenesis, which explains its delayed hypersensitivity. The role of immunoglobulin E is not clear in this disease. Insect-derived antigens directly involved in papular urticaria etiology are unknown. However, it is possible that common molecules among causal insects mediate cross-reactive reactions, such as Cte f 2 allergen, found in cat fleas, and its counterparts in mosquitoes.Papular urticaria is a frequent disease in Latin America that should be further investigated. Immunological characterization of the molecular components that cause this condition may solve questions about its pathogenesis.
Neural Connectivity in Epilepsy as Measured by Granger Causality
Coben, Robert; Mohammad-Rezazadeh, Iman
2015-01-01
Epilepsy is a chronic neurological disorder characterized by repeated seizures or excessive electrical discharges in a group of brain cells. Prevalence rates include about 50 million people worldwide and 10% of all people have at least one seizure at one time in their lives. Connectivity models of epilepsy serve to provide a deeper understanding of the processes that control and regulate seizure activity. These models have received initial support and have included measures of EEG, MEG, and MRI connectivity. Preliminary findings have shown regions of increased connectivity in the immediate regions surrounding the seizure foci and associated low connectivity in nearby regions and pathways. There is also early evidence to suggest that these patterns change during ictal events and that these changes may even by related to the occurrence or triggering of seizure events. We present data showing how Granger causality can be used with EEG data to measure connectivity across brain regions involved in ictal events and their resolution. We have provided two case examples as a demonstration of how to obtain and interpret such data. EEG data of ictal events are processed, converted to independent components and their dipole localizations, and these are used to measure causality and connectivity between these locations. Both examples have shown hypercoupling near the seizure foci and low causality across nearby and associated neuronal pathways. This technique also allows us to track how these measures change over time and during the ictal and post-ictal periods. Areas for further research into this technique, its application to epilepsy, and the formation of more effective therapeutic interventions are recommended. PMID:26236211
Dinç, Erdal; Ertekin, Zehra Ceren; Büker, Eda
2016-09-01
Two-way and three-way calibration models were applied to ultra high performance liquid chromatography with photodiode array data with coeluted peaks in the same wavelength and time regions for the simultaneous quantitation of ciprofloxacin and ornidazole in tablets. The chromatographic data cube (tensor) was obtained by recording chromatographic spectra of the standard and sample solutions containing ciprofloxacin and ornidazole with sulfadiazine as an internal standard as a function of time and wavelength. Parallel factor analysis and trilinear partial least squares were used as three-way calibrations for the decomposition of the tensor, whereas three-way unfolded partial least squares was applied as a two-way calibration to the unfolded dataset obtained from the data array of ultra high performance liquid chromatography with photodiode array detection. The validity and ability of two-way and three-way analysis methods were tested by analyzing validation samples: synthetic mixture, interday and intraday samples, and standard addition samples. Results obtained from two-way and three-way calibrations were compared to those provided by traditional ultra high performance liquid chromatography. The proposed methods, parallel factor analysis, trilinear partial least squares, unfolded partial least squares, and traditional ultra high performance liquid chromatography were successfully applied to the quantitative estimation of the solid dosage form containing ciprofloxacin and ornidazole.
Prediction of saturated liquid enthalpy of refrigerant mixtures
Institute of Scientific and Technical Information of China (English)
CHEN ZeShao; CHEN JianXin; HU Peng
2007-01-01
New corresponding temperature and corresponding enthalpy of refrigerant mixtures were defined. The relationship between saturated liquid corresponding enthalpy and corresponding temperature of refrigerant mixtures accorded with that of pure components. The characteristic parameters of saturated liquid enthalpy difference of refrigerant mixtures were calculated by three methods according to the different application conditions. The generalized equation of saturated liquid enthalpy of refrigerant mixtures was presented. The calculated values were compared with the values in literature for five ternary and binary refrigerant mixtures, namely R404A, R407A, R407B, R32/R134a, and R410A. The overall average absolute deviation was less than 1.0%.
The scent of mixtures: rules of odour processing in ants.
Perez, Margot; Giurfa, Martin; d'Ettorre, Patrizia
2015-03-02
Natural odours are complex blends of numerous components. Understanding how animals perceive odour mixtures is central to multiple disciplines. Here we focused on carpenter ants, which rely on odours in various behavioural contexts. We studied overshadowing, a phenomenon that occurs when animals having learnt a binary mixture respond less to one component than to the other, and less than when this component was learnt alone. Ants were trained individually with alcohols and aldehydes varying in carbon-chain length, either as single odours or binary mixtures. They were then tested with the mixture and the components. Overshadowing resulted from the interaction between chain length and functional group: alcohols overshadowed aldehydes, and longer chain lengths overshadowed shorter ones; yet, combinations of these factors could cancel each other and suppress overshadowing. Our results show how ants treat binary olfactory mixtures and set the basis for predictive analyses of odour perception in insects.
Are bruxism and the bite causally related?
Lobbezoo, F.; Ahlberg, J.; Manfredini, D.; Winocur, E.
2012-01-01
In the dental profession, the belief that bruxism and dental (mal-)occlusion (‘the bite’) are causally related is widespread. The aim of this review was to critically assess the available literature on this topic. A PubMed search of the English-language literature, using the query ‘Bruxism [Majr] AN
Causal interpretation of stochastic differential equations
DEFF Research Database (Denmark)
Sokol, Alexander; Hansen, Niels Richard
2014-01-01
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....
On Measurement Bias in Causal Inference
Pearl, Judea
2012-01-01
This paper addresses the problem of measurement errors in causal inference and highlights several algebraic and graphical methods for eliminating systematic bias induced by such errors. In particulars, the paper discusses the control of partially observable confounders in parametric and non parametric models and the computational problem of obtaining bias-free effect estimates in such models.
Causal Poisson bracket via deformation quantization
Berra-Montiel, Jasel; Molgado, Alberto; Palacios-García, César D.
2016-06-01
Starting with the well-defined product of quantum fields at two spacetime points, we explore an associated Poisson structure for classical field theories within the deformation quantization formalism. We realize that the induced star-product is naturally related to the standard Moyal product through an appropriate causal Green’s functions connecting points in the space of classical solutions to the equations of motion. Our results resemble the Peierls-DeWitt bracket that has been analyzed in the multisymplectic context. Once our star-product is defined, we are able to apply the Wigner-Weyl map in order to introduce a generalized version of Wick’s theorem. Finally, we include some examples to explicitly test our method: the real scalar field, the bosonic string and a physically motivated nonlinear particle model. For the field theoretic models, we have encountered causal generalizations of the creation/annihilation relations, and also a causal generalization of the Virasoro algebra for the bosonic string. For the nonlinear particle case, we use the approximate solution in terms of the Green’s function, in order to construct a well-behaved causal bracket.
A quantum probability model of causal reasoning.
Trueblood, Jennifer S; Busemeyer, Jerome R
2012-01-01
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.
Inductive Reasoning about Causally Transmitted Properties
Shafto, Patrick; Kemp, Charles; Bonawitz, Elizabeth Baraff; Coley, John D.; Tenenbaum, Joshua B.
2008-01-01
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'…
Objective reality, causality and the aspect experiment
Pegg, D. T.
1980-08-01
It is argued that, in the framework of Wheeler-Feynman electrodynamics objective reality and causality in the strict sense are consistent with the outcome of atomic cascade photon correlation experiments, provided this outcome is not altered by the Aspect experimental modification.
Introducing Mechanics by Tapping Core Causal Knowledge
Klaassen, Kees; Westra, Axel; Emmett, Katrina; Eijkelhof, Harrie; Lijnse, Piet
2008-01-01
This article concerns an outline of an introductory mechanics course. It is based on the argument that various uses of the concept of force (e.g. from Kepler, Newton and everyday life) share an explanatory strategy based on core causal knowledge. The strategy consists of (a) the idea that a force causes a deviation from how an object would move of…
Pride and Prejudice and Causal Indicators
Lee, Nick; Chamberlain, Laura
2016-01-01
Aguirre-Urreta, Rönkkö, and Marakas' (2016) paper in "Measurement: Interdisciplinary Research and Perspectives" (hereafter referred to as ARM2016) is an important and timely piece of scholarship, in that it provides strong analytic support to the growing theoretical literature that questions the underlying ideas behind causal and…
Catastrophizing and Causal Beliefs in Whiplash
Buitenhuis, J.; de Jong, P. J.; Jaspers, J. P. C.; Groothoff, J. W.
2008-01-01
Study Design. Prospective cohort study. Objective. This study investigates the role of pain catastrophizing and causal beliefs with regard to severity and persistence of neck complaints after motor vehicle accidents. Summary of Background Data. In previous research on low back pain, somatoform disor
Marriage and Anomie: A Causal Argument
Lee, Gary R.
1974-01-01
A sample of 394 married couples is employed to test the possibility of an association between marital satisfaction and personal (attitudinal) anomie. The hypothesis is supported. Conclusions are offered relevant to anomie theory, and to utilization of marital and family phenomena as independent variables in causal explanations of nonfamily events.…
Causality and the speed of sound
Ellis, G; MacCallum, M; Callum, Malcolm Mac; Ellis, George; Maartens, Roy
2007-01-01
A usual causal requirement on a viable theory of matter is that the speed of sound be at most the speed of light. In view of various recent papers querying this limit, the question is revisited here. We point to various issues confronting theories that violate the usual constraint.
A Quantum Probability Model of Causal Reasoning
Trueblood, Jennifer S.; Busemeyer, Jerome R.
2012-01-01
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. PMID:22593747
Causality in the Semantics of Esterel: Revisited
Mousavi, MohammadReza
2010-01-01
We re-examine the challenges concerning causality in the semantics of Esterel and show that they pertain to the known issues in the semantics of Structured Operational Semantics with negative premises. We show that the solutions offered for the semantics of SOS also provide answers to the semantic challenges of Esterel and that they satisfy the intuitive requirements set by the language designers.
Causal Meta-Analysis : Methodology and Applications
Bax, L.J.
2009-01-01
Meta-analysis is a statistical method to summarize research data from multiple studies in a quantitative manner. This dissertation addresses a number of methodological topics in causal meta-analysis and reports the development and validation of meta-analysis software. In the first (methodological) p
Causal and Teleological Explanations in Biology
Yip, Cheng-Wai
2009-01-01
A causal explanation in biology focuses on the mechanism by which a biological process is brought about, whereas a teleological explanation considers the end result, in the context of the survival of the organism, as a reason for certain biological processes or structures. There is a tendency among students to offer a teleological explanation…
The metagenomic approach and causality in virology
Directory of Open Access Journals (Sweden)
Silvana Beres Castrignano
2015-01-01
Full Text Available Nowadays, the metagenomic approach has been a very important tool in the discovery of new viruses in environmental and biological samples. Here we discuss how these discoveries may help to elucidate the etiology of diseases and the criteria necessary to establish a causal association between a virus and a disease.
Comments: Causal Interpretations of Mediation Effects
Jo, Booil; Stuart, Elizabeth A.
2012-01-01
The authors thank Dr. Lindsay Page for providing a nice illustration of the use of the principal stratification framework to define causal effects, and a Bayesian model for effect estimation. They hope that her well-written article will help expose education researchers to these concepts and methods, and move the field of mediation analysis in…
Geometry of the Infalling Causal Patch
Freivogel, B.; Jefferson, R.A.; Kabir, L.; Yang, I.S.
2015-01-01
The firewall paradox states that an observer falling into an old black hole must see a violation of unitarity, locality, or the equivalence principle. Motivated by this remarkable conflict, we analyze the causal structure of black hole spacetimes in order to determine whether all the necessary ingre
Sequential causal learning in humans and rats
H. Lu; R.R. Rojas; T. Beckers; A. Yuille
2008-01-01
Recent experiments (Beckers, De Houwer, Pineño, & Miller, 2005;Beckers, Miller, De Houwer, & Urushihara, 2006) have shown that pretraining with unrelated cues can dramatically influence the performance of humans in a causal learning paradigm and rats in a standard Pavlovian conditioning paradigm. Su
Spectral Dimension from Causal Set Nonlocal Dynamics
Belenchia, Alessio; Marciano, Antonino; Modesto, Leonardo
2015-01-01
We investigate the spectral dimension obtained from non-local continuum d'Alembertians derived from causal sets. We find a universal dimensional reduction to 2 dimensions, in all dimensions. We conclude by discussing the validity and relevance of our results within the broader context of quantum field theories based on these nonlocal dynamics.
From causality to time and back
Energy Technology Data Exchange (ETDEWEB)
Minguzzi, Ettore, E-mail: ettore.minguzzi@unifi.i [Dipartimento di Matematica Applicata, Universita degli Studi di Firenze, Via S. Marta 3, I-50139 Firenze (Italy)
2010-05-01
In this work the problem of the existence of a (semi-)time function on spacetime is investigated together with the problem of recovering the causal structure from the set of time functions allowed by the spacetime. These problems are solved thanks also to a mathematical correspondence with utility theory.
Linear Response Laws and Causality in Electrodynamics
Yuffa, Alex J.; Scales, John A.
2012-01-01
Linear response laws and causality (the effect cannot precede the cause) are of fundamental importance in physics. In the context of classical electrodynamics, students often have a difficult time grasping these concepts because the physics is obscured by the intermingling of the time and frequency domains. In this paper, we analyse the linear…
The metagenomic approach and causality in virology
Castrignano, Silvana Beres; Nagasse-Sugahara, Teresa Keico
2015-01-01
Nowadays, the metagenomic approach has been a very important tool in the discovery of new viruses in environmental and biological samples. Here we discuss how these discoveries may help to elucidate the etiology of diseases and the criteria necessary to establish a causal association between a virus and a disease. PMID:25902566
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.
Mixture risk assessment: a case study of Monsanto experiences.
Nair, R S; Dudek, B R; Grothe, D R; Johannsen, F R; Lamb, I C; Martens, M A; Sherman, J H; Stevens, M W
1996-01-01
Monsanto employs several pragmatic approaches for evaluating the toxicity of mixtures. These approaches are similar to those recommended by many national and international agencies. When conducting hazard and risk assessments, priority is always given to using data collected directly on the mixture of concern. To provide an example of the first tier of evaluation, actual data on acute respiratory irritation studies on mixtures were evaluated to determine whether the principle of additivity was applicable to the mixture evaluated. If actual data on the mixture are unavailable, extrapolation across similar mixtures is considered. Because many formulations are quite similar in composition, the toxicity data from one mixture can be extended to a closely related mixture in a scientifically justifiable manner. An example of a family of products where such extrapolations have been made is presented to exemplify this second approach. Lastly, if data on similar mixtures are unavailable, data on component fractions are used to predict the toxicity of the mixture. In this third approach, process knowledge and scientific judgement are used to determine how the known toxicological properties of the individual fractions affect toxicity of the mixture. Three examples of plant effluents where toxicological data on fractions were used to predict the toxicity of the mixture are discussed. The results of the analysis are used to discuss the predictive value of each of the above mentioned toxicological approaches for evaluating chemical mixtures.
Perception of trigeminal mixtures.
Filiou, Renée-Pier; Lepore, Franco; Bryant, Bruce; Lundström, Johan N; Frasnelli, Johannes
2015-01-01
The trigeminal system is a chemical sense allowing for the perception of chemosensory information in our environment. However, contrary to smell and taste, we lack a thorough understanding of the trigeminal processing of mixtures. We, therefore, investigated trigeminal perception using mixtures of 3 relatively receptor-specific agonists together with one control odor in different proportions to determine basic perceptual dimensions of trigeminal perception. We found that 4 main dimensions were linked to trigeminal perception: sensations of intensity, warmth, coldness, and pain. We subsequently investigated perception of binary mixtures of trigeminal stimuli by means of these 4 perceptual dimensions using different concentrations of a cooling stimulus (eucalyptol) mixed with a stimulus that evokes warmth perception (cinnamaldehyde). To determine if sensory interactions are mainly of central or peripheral origin, we presented stimuli in a physical "mixture" or as a "combination" presented separately to individual nostrils. Results showed that mixtures generally yielded higher ratings than combinations on the trigeminal dimensions "intensity," "warm," and "painful," whereas combinations yielded higher ratings than mixtures on the trigeminal dimension "cold." These results suggest dimension-specific interactions in the perception of trigeminal mixtures, which may be explained by particular interactions that may take place on peripheral or central levels.
Prenatal nutrition, epigenetics and schizophrenia risk: can we test causal effects?
Kirkbride, James B; Susser, Ezra; Kundakovic, Marija; Kresovich, Jacob K; Davey Smith, George; Relton, Caroline L
2012-06-01
We posit that maternal prenatal nutrition can influence offspring schizophrenia risk via epigenetic effects. In this article, we consider evidence that prenatal nutrition is linked to epigenetic outcomes in offspring and schizophrenia in offspring, and that schizophrenia is associated with epigenetic changes. We focus upon one-carbon metabolism as a mediator of the pathway between perturbed prenatal nutrition and the subsequent risk of schizophrenia. Although post-mortem human studies demonstrate DNA methylation changes in brains of people with schizophrenia, such studies cannot establish causality. We suggest a testable hypothesis that utilizes a novel two-step Mendelian randomization approach, to test the component parts of the proposed causal pathway leading from prenatal nutritional exposure to schizophrenia. Applied here to a specific example, such an approach is applicable for wider use to strengthen causal inference of the mediating role of epigenetic factors linking exposures to health outcomes in population-based studies.
Causal knowledge and the development of inductive reasoning.
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.
Energy Technology Data Exchange (ETDEWEB)
Beccantini, A
2001-07-01
This thesis represents a contribution to the development of upwind splitting schemes for the Euler equations for ideal gaseous mixtures and their investigation in computing multidimensional flows in irregular geometries. In the preliminary part we develop and investigate the parameterization of the shock and rarefaction curves in the phase space. Then, we apply them to perform some field-by-field decompositions of the Riemann problem: the entropy-respecting one, the one which supposes that genuinely-non-linear (GNL) waves are both shocks (shock-shock one) and the one which supposes that GNL waves are both rarefactions (rarefaction-rarefaction one). We emphasize that their analysis is fundamental in Riemann solvers developing: the simpler the field-by-field decomposition, the simpler the Riemann solver based on it. As the specific heat capacities of the gases depend on the temperature, the shock-shock field-by-field decomposition is the easiest to perform. Then, in the second part of the thesis, we develop an upwind splitting scheme based on such decomposition. Afterwards, we investigate its robustness, precision and CPU-time consumption, with respect to some of the most popular upwind splitting schemes for polytropic/non-polytropic ideal gases. 1-D test-cases show that this scheme is both precise (exact capturing of stationary shock and stationary contact) and robust in dealing with strong shock and rarefaction waves. Multidimensional test-cases show that it suffers from some of the typical deficiencies which affect the upwind splitting schemes capable of exact capturing stationary contact discontinuities i.e the developing of non-physical instabilities in computing strong shock waves. In the final part, we use the high-order multidimensional solver here developed to compute fully-developed detonation flows. (author)
Does Causality Matter More Now? Increase in the Proportion of Causal Language in English Texts.
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.
Institute of Scientific and Technical Information of China (English)
田金星; 谭旭升
2014-01-01
The batch grinding kinetic equation based on Reid balance calculus was used to study the grinding dynamics behavior of graphite in a mixed material of graphite-calcite. The results show that, for the function on the broken rate Si, the fracture rate of graphite components in function expression is related to timet, which shows the nonlinear relationship between lnmi andt. The simulation values and experiment values of graphite component nonlinear fracture results are well agree with each other. For the fracture distribution functionbij, the fracture distribution functions of graphite components in the mixed material grinding and separate mineral grinding are basically the same. The aforementioned conclusion can take theoretical guide for the production practice of graphite grinding.%利用Reid总体平衡微积分分批磨碎动力学方程，研究石墨−方解石物料混合磨碎时，石墨的磨碎动力学行为。结果表明：对碎裂速率函数S i而言，混合磨碎时石墨组分的碎裂速率函数Si表现为与时间t相关，即ln mi与t的关系曲线呈非线性关系。同时，模型仿真结果表明，石墨组分表现的非线性碎裂结果的模拟值与实验值吻合度较高；而石墨组分混合磨碎的碎裂分布函数b ij则与单独磨碎时的碎裂分布函数b ij基本相同。该结论可作为石墨磨碎生产实践的理论指导。
Inability of the entropy vector method to certify nonclassicality in linelike causal structures
Weilenmann, Mirjam; Colbeck, Roger
2016-10-01
Bell's theorem shows that our intuitive understanding of causation must be overturned in light of quantum correlations. Nevertheless, quantum mechanics does not permit signaling and hence a notion of cause remains. Understanding this notion is not only important at a fundamental level, but also for technological applications such as key distribution and randomness expansion. It has recently been shown that a useful way to decide which classical causal structures could give rise to a given set of correlations is to use entropy vectors. These are vectors whose components are the entropies of all subsets of the observed variables in the causal structure. The entropy vector method employs causal relationships among the variables to restrict the set of possible entropy vectors. Here, we consider whether the same approach can lead to useful certificates of nonclassicality within a given causal structure. Surprisingly, we find that for a family of causal structures that includes the usual bipartite Bell structure they do not. For all members of this family, no function of the entropies of the observed variables gives such a certificate, in spite of the existence of nonclassical correlations. It is therefore necessary to look beyond entropy vectors to understand cause from a quantum perspective.
Causal inference algorithms can be useful in life course epidemiology
la Bastide-van Gemert, Sacha; Stolk, Ronald P.; van den Heuvel, Edwin R.; Fidler, Vaclav
2014-01-01
Objectives: Life course epidemiology attempts to unravel causal relationships between variables observed over time. Causal relationships can be represented as directed acyclic graphs. This article explains the theoretical concepts of the search algorithms used for finding such representations, discu
Atomistic simulations of bicelle mixtures.
Jiang, Yong; Wang, Hao; Kindt, James T
2010-06-16
Mixtures of long- and short-tail phosphatidylcholine lipids are known to self-assemble into a variety of aggregates combining flat bilayerlike and curved micellelike features, commonly called bicelles. Atomistic simulations of bilayer ribbons and perforated bilayers containing dimyristoylphosphatidylcholine (DMPC, di-C(14) tails) and dihexanoylphosphatidylcholine (DHPC, di-C(6) tails) have been carried out to investigate the partitioning of these components between flat and curved microenvironments and the stabilization of the bilayer edge by DHPC. To approach equilibrium partitioning of lipids on an achievable simulation timescale, configuration-bias Monte Carlo mutation moves were used to allow individual lipids to change tail length within a semigrand-canonical ensemble. Since acceptance probabilities for direct transitions between DMPC and DHPC were negligible, a third component with intermediate tail length (didecanoylphosphatidylcholine, di-C(10) tails) was included at a low concentration to serve as an intermediate for transitions between DMPC and DHPC. Strong enrichment of DHPC is seen at ribbon and pore edges, with an excess linear density of approximately 3 nm(-1). The simulation model yields estimates for the onset of edge stability with increasing bilayer DHPC content between 5% and 15% DHPC at 300 K and between 7% and 17% DHPC at 323 K, higher than experimental estimates. Local structure and composition at points of close contact between pores suggest a possible mechanism for effective attractions between pores, providing a rationalization for the tendency of bicelle mixtures to aggregate into perforated vesicles and perforated sheets.
Exploratory Causal Analysis in Bivariate Time Series Data
McCracken, James M.
Many scientific disciplines rely on observational data of systems for which it is difficult (or impossible) to implement controlled experiments and data analysis techniques are required for identifying causal information and relationships directly from observational data. This need has lead to the development of many different time series causality approaches and tools including transfer entropy, convergent cross-mapping (CCM), and Granger causality statistics. In this thesis, the existing time series causality method of CCM is extended by introducing a new method called pairwise asymmetric inference (PAI). It is found that CCM may provide counter-intuitive causal inferences for simple dynamics with strong intuitive notions of causality, and the CCM causal inference can be a function of physical parameters that are seemingly unrelated to the existence of a driving relationship in the system. For example, a CCM causal inference might alternate between ''voltage drives current'' and ''current drives voltage'' as the frequency of the voltage signal is changed in a series circuit with a single resistor and inductor. PAI is introduced to address both of these limitations. Many of the current approaches in the times series causality literature are not computationally straightforward to apply, do not follow directly from assumptions of probabilistic causality, depend on assumed models for the time series generating process, or rely on embedding procedures. A new approach, called causal leaning, is introduced in this work to avoid these issues. The leaning is found to provide causal inferences that agree with intuition for both simple systems and more complicated empirical examples, including space weather data sets. The leaning may provide a clearer interpretation of the results than those from existing time series causality tools. A practicing analyst can explore the literature to find many proposals for identifying drivers and causal connections in times series data
Mixture Experiment Alternatives to the Slack Variable Approach
Energy Technology Data Exchange (ETDEWEB)
Piepel, Gregory F.; Landmesser, Samantha M.
2009-07-01
A mixture experiment involves mixing two or more components in various proportions and measuring one or more response variables on each mixture. This article presents mixture-experiment approaches for designing experiments and/or modeling the resulting data in situations where the slack-variable (SV) approach has been used. With the SV approach, one mixture component is designated the SV and the experiment is designed and/or the data are analyzed in terms of the remaining components. In a SV design, the proportion of the SV is obtained by subtracting from one the sum of the proportions of the remaining components, thus "taking up the slack". With the mixture-experiment approach, the experiment is designed and the data are analyzed using all of the mixture components. The article considers four situations in which the SV approach has been used, and explains for each situation that it is generally preferable to use an appropriate mixture-experiment approach. For each situation, the recommended mixture-experiment approach is discussed and compared to the SV approach using an example.
Institutional Investors and Stock Market Development: A Causality Study
Guler Aras; Alovsat Muslumov
2008-01-01
This article examines causality relationships between institutional investors and stock market development based on the panel data compiled from 23 OECD countries for the years 1982 through 2000. In order to test causality relationship, Sims’ causality test based on Granger definition of causality was used in our study. Our empirical results provide evidence that there are statistically significant positive relationship between institutional investors and stock market development. The develop...
Assessing statistical significance in causal graphs
Directory of Open Access Journals (Sweden)
Chindelevitch Leonid
2012-02-01
Full Text Available Abstract Background Causal graphs are an increasingly popular tool for the analysis of biological datasets. In particular, signed causal graphs--directed graphs whose edges additionally have a sign denoting upregulation or downregulation--can be used to model regulatory networks within a cell. Such models allow prediction of downstream effects of regulation of biological entities; conversely, they also enable inference of causative agents behind observed expression changes. However, due to their complex nature, signed causal graph models present special challenges with respect to assessing statistical significance. In this paper we frame and solve two fundamental computational problems that arise in practice when computing appropriate null distributions for hypothesis testing. Results First, we show how to compute a p-value for agreement between observed and model-predicted classifications of gene transcripts as upregulated, downregulated, or neither. Specifically, how likely are the classifications to agree to the same extent under the null distribution of the observed classification being randomized? This problem, which we call "Ternary Dot Product Distribution" owing to its mathematical form, can be viewed as a generalization of Fisher's exact test to ternary variables. We present two computationally efficient algorithms for computing the Ternary Dot Product Distribution and investigate its combinatorial structure analytically and numerically to establish computational complexity bounds. Second, we develop an algorithm for efficiently performing random sampling of causal graphs. This enables p-value computation under a different, equally important null distribution obtained by randomizing the graph topology but keeping fixed its basic structure: connectedness and the positive and negative in- and out-degrees of each vertex. We provide an algorithm for sampling a graph from this distribution uniformly at random. We also highlight theoretical
Second-order model selection in mixture experiments
Energy Technology Data Exchange (ETDEWEB)
Redgate, P.E.; Piepel, G.F.; Hrma, P.R.
1992-07-01
Full second-order models for q-component mixture experiments contain q(q+l)/2 terms, which increases rapidly as q increases. Fitting full second-order models for larger q may involve problems with ill-conditioning and overfitting. These problems can be remedied by transforming the mixture components and/or fitting reduced forms of the full second-order mixture model. Various component transformation and model reduction approaches are discussed. Data from a 10-component nuclear waste glass study are used to illustrate ill-conditioning and overfitting problems that can be encountered when fitting a full second-order mixture model. Component transformation, model term selection, and model evaluation/validation techniques are discussed and illustrated for the waste glass example.
Mixture toxicity of PBT-like chemicals
DEFF Research Database (Denmark)
Syberg, Kristian; Dai, Lina; Ramskov, Tina;
beyond that of the individual components. Firstly, the effects of three chemicals with PBT-like properties (acetyl cedrene, pyrene and triclosan) was examined on the freshwater snail, Potamopyrgus antipodarum. Secondly, mixture bioaccumulation of the same three chemicals were assessed experimentally...
Nuclear fuel alloys or mixtures and method of making thereof
Mariani, Robert Dominick; Porter, Douglas Lloyd
2016-04-05
Nuclear fuel alloys or mixtures and methods of making nuclear fuel mixtures are provided. Pseudo-binary actinide-M fuel mixtures form alloys and exhibit: body-centered cubic solid phases at low temperatures; high solidus temperatures; and/or minimal or no reaction or inter-diffusion with steel and other cladding materials. Methods described herein through metallurgical and thermodynamics advancements guide the selection of amounts of fuel mixture components by use of phase diagrams. Weight percentages for components of a metallic additive to an actinide fuel are selected in a solid phase region of an isothermal phase diagram taken at a temperature below an upper temperature limit for the resulting fuel mixture in reactor use. Fuel mixtures include uranium-molybdenum-tungsten, uranium-molybdenum-tantalum, molybdenum-titanium-zirconium, and uranium-molybdenum-titanium systems.
Mixtures of Common Skew-t Factor Analyzers
Murray, Paula M.; McNicholas, Paul D.; Browne, Ryan P.
2013-01-01
A mixture of common skew-t factor analyzers model is introduced for model-based clustering of high-dimensional data. By assuming common component factor loadings, this model allows clustering to be performed in the presence of a large number of mixture components or when the number of dimensions is too large to be well-modelled by the mixtures of factor analyzers model or a variant thereof. Furthermore, assuming that the component densities follow a skew-t distribution allows robust clusterin...
Interpretational Confounding or Confounded Interpretations of Causal Indicators?
Bainter, Sierra A.; Bollen, Kenneth A.
2014-01-01
In measurement theory, causal indicators are controversial and little understood. Methodological disagreement concerning causal indicators has centered on the question of whether causal indicators are inherently sensitive to interpretational confounding, which occurs when the empirical meaning of a latent construct departs from the meaning…
Causal Relations and Feature Similarity in Children's Inductive Reasoning
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…
The Effect of Causal Diagrams on Text Learning
McCrudden, Matthew T.; Schraw, Gregory; Lehman, Stephen; Poliquin, Anne
2007-01-01
We examined the effect of studying a causal diagram on comprehension of causal relationships from an expository science text. A causal diagram is a type of visual display that explicitly represents cause-effect relationships. In Experiment 1, readers between conditions did not differ with respect to memory for main ideas, but the readers who…
Omission of Causal Indicators: Consequences and Implications for Measurement
Aguirre-Urreta, Miguel I.; Rönkkö, Mikko; Marakas, George M.
2016-01-01
One of the central assumptions of the causal-indicator literature is that all causal indicators must be included in the research model and that the exclusion of one or more relevant causal indicators would have severe negative consequences by altering the meaning of the latent variable. In this research we show that the omission of a relevant…
Rationales in Children's Causal Learning from Others' Actions
Sobel, David M.; Sommerville, Jessica A.
2009-01-01
Shown commensurate actions and information by an adult, preschoolers' causal learning was influenced by the pedagogical context in which these actions occurred. Four-year-olds who were provided with a reason for an experimenter's action relevant to learning causal structure showed more accurate causal learning than children exposed to the same…
Implications of the Changing Conversation about Causality for Evaluators
Gates, Emily; Dyson, Lisa
2017-01-01
Making causal claims is central to evaluation practice because we want to know the effects of a program, project, or policy. In the past decade, the conversation about establishing causal claims has become prominent (and problematic). In response to this changing conversation about causality, we argue that evaluators need to take up some new ways…
How to Be Causal: Time, Spacetime and Spectra
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…
A Quantitative Causal Model Theory of Conditional Reasoning
Fernbach, Philip M.; Erb, Christopher D.
2013-01-01
The authors propose and test a causal model theory of reasoning about conditional arguments with causal content. According to the theory, the acceptability of modus ponens (MP) and affirming the consequent (AC) reflect the conditional likelihood of causes and effects based on a probabilistic causal model of the scenario being judged. Acceptability…
Toward an Intersectional Understanding of Process Causality and Social Context
Anderson, Gary L.; Scott, Janelle
2012-01-01
Maxwell and Donmoyer both argue in this issue of "Qualitative Inquiry" that narrow definitions of causality in educational research tend to disqualify qualitative research from influence (and funding) among policy makers. They propose a process view of causality that would allow qualitative researchers to make causal claims more grounded in the…
Normalizing the causality between time series
Liang, X San
2015-01-01
Recently, a rigorous yet concise formula has been derived to evaluate the information flow, and hence the causality in a quantitative sense, between time series. To assess the importance of a resulting causality, it needs to be normalized. The normalization is achieved through distinguishing three types of fundamental mechanisms that govern the marginal entropy change of the flow recipient. A normalized or relative flow measures its importance relative to other mechanisms. In analyzing realistic series, both absolute and relative information flows need to be taken into account, since the normalizers for a pair of reverse flows belong to two different entropy balances; it is quite normal that two identical flows may differ a lot in relative importance in their respective balances. We have reproduced these results with several autoregressive models. We have also shown applications to a climate change problem and a financial analysis problem. For the former, reconfirmed is the role of the Indian Ocean Dipole as ...
Finite quantum electrodynamics the causal approach
Scharf, Günter
2014-01-01
In this classic text for advanced undergraduates and graduate students of physics, author Günter Scharf carefully analyzes the role of causality in quantum electrodynamics. His approach offers full proofs and detailed calculations of scattering processes in a mathematically rigorous manner. This third edition contains Scharf's revisions and corrections plus a brief new Epilogue on gauge invariance of quantum electrodynamics to all orders. The book begins with Dirac's theory, followed by the quantum theory of free fields and causal perturbation theory, a powerful method that avoids ultraviolet divergences and solves the infrared problem by means of the adiabatic limit. Successive chapters explore properties of the S-matrix — such as renormalizability, gauge invariance, and unitarity — the renormalization group, and interactive fields. Additional topics include electromagnetic couplings and the extension of the methods to non-abelian gauge theories. Each chapter is supplemented with problems, and four appe...
Consistence beats causality in recommender systems
Zhu, Xuzhen; Hu, Zheng; Zhang, Ping; Zhou, Tao
2015-01-01
The explosive growth of information challenges people's capability in finding out items fitting to their own interests. Recommender systems provide an efficient solution by automatically push possibly relevant items to users according to their past preferences. Recommendation algorithms usually embody the causality from what having been collected to what should be recommended. In this article, we argue that in many cases, a user's interests are stable, and thus the previous and future preferences are highly consistent. The temporal order of collections then does not necessarily imply a causality relationship. We further propose a consistence-based algorithm that outperforms the state-of-the-art recommendation algorithms in disparate real data sets, including \\textit{Netflix}, \\textit{MovieLens}, \\textit{Amazon} and \\textit{Rate Your Music}.
Localizing epileptic seizure onsets with Granger causality
Adhikari, Bhim M.; Epstein, Charles M.; Dhamala, Mukesh
2013-09-01
Accurate localization of the epileptic seizure onset zones (SOZs) is crucial for successful surgery, which usually depends on the information obtained from intracranial electroencephalography (IEEG) recordings. The visual criteria and univariate methods of analyzing IEEG recordings have not always produced clarity on the SOZs for resection and ultimate seizure freedom for patients. Here, to contribute to improving the localization of the SOZs and to understanding the mechanism of seizure propagation over the brain, we applied spectral interdependency methods to IEEG time series recorded from patients during seizures. We found that the high-frequency (>80 Hz) Granger causality (GC) occurs before the onset of any visible ictal activity and causal relationships involve the recording electrodes where clinically identifiable seizures later develop. These results suggest that high-frequency oscillatory network activities precede and underlie epileptic seizures, and that GC spectral measures derived from IEEG can assist in precise delineation of seizure onset times and SOZs.
A new spin on causality constraints
Hartman, Thomas; Jain, Sachin; Kundu, Sandipan
2016-10-01
Causality in a shockwave state is related to the analytic properties of a four-point correlation function. Extending recent results for scalar probes, we show that this constrains the couplings of the stress tensor to light spinning operators in conformal field theory, and interpret these constraints in terms of the interaction with null energy. For spin-1 and spin-2 conserved currents in four dimensions, the resulting inequalities are a subset of the Hofman-Maldacena conditions for positive energy deposition. It is well known that energy conditions in holographic theories are related to causality on the gravity side; our results make a connection on the CFT side, and extend it to non-holographic theories.
A New Spin on Causality Constraints
Hartman, Thomas; Kundu, Sandipan
2016-01-01
Causality in a shockwave state is related to the analytic properties of a four-point correlation function. Extending recent results for scalar probes, we show that this constrains the couplings of the stress tensor to light spinning operators in conformal field theory, and interpret these constraints in terms of the interaction with null energy. For spin-1 and spin-2 conserved currents in four dimensions, the resulting inequalities are a subset of the Hofman-Maldacena conditions for positive energy deposition. It is well known that energy conditions in holographic theories are related to causality on the gravity side; our results make a connection on the CFT side, and extend it to non-holographic theories.
Dietary relevant mixtures of phytoestrogens inhibit adipocyte differentiation in vitro
DEFF Research Database (Denmark)
Taxvig, Camilla; Specht, Ina Olmer; Boberg, Julie
2013-01-01
Phytoestrogens (PEs) are naturally occurring plant components, with the ability to induce biological responses in vertebrates by mimicking or modulating the action of endogenous hormones.Single isoflavones have been shown to affect adipocyte differentiation, but knowledge on the effect of dietary...... as tested for their PPARγ activating abilities. The results showed that mixtures of isoflavonoid parent compounds and metabolites, respectively, a mixture of lignan metabolites, as well as coumestrol concentration-dependently inhibited adipocyte differentiation. Furthermore, a mixture of isoflavonoid parent...
Confounding and Collapsibility in Causal Inference
Greenland, Sander; Robins, James M; Pearl, Judea
1999-01-01
Consideration of confounding is fundamental to the design and analysis of studies of causal effects. Yet, apart from confounding in experimental designs, the topic is given little or no discussion in most statistics texts. We here provide an overview of confounding and related concepts based on a counterfactual model for causation. Special attention is given to definitions of confounding, problems in control of confounding, the relation of confounding to exchangeability and ...
A Study of Causality in Military Planning
2012-06-08
Regional and local governance established Establish police forces training Counter organized crime Integrate trained police into operations...richer way to think about causality in military planning and operations. Uncovering an ontology has become an increasingly employed tactic in...political theory.21 In this context, an ontology is simply a way in which the world is viewed, “the most basic conceptualizations of self, other, and
Consistence beats causality in recommender systems
Zhu, Xuzhen; Tian, Hui; Hu, Zheng; Zhang, Ping; Zhou, Tao
2015-01-01
The explosive growth of information challenges people's capability in finding out items fitting to their own interests. Recommender systems provide an efficient solution by automatically push possibly relevant items to users according to their past preferences. Recommendation algorithms usually embody the causality from what having been collected to what should be recommended. In this article, we argue that in many cases, a user's interests are stable, and thus the previous and future prefere...
Isocausal spacetimes may have different causal boundaries
Energy Technology Data Exchange (ETDEWEB)
Flores, J L; Herrera, J [Departamento de Algebra, Geometria y Topologia, Facultad de Ciencias, Universidad de Malaga, Campus Teatinos, 29071 Malaga (Spain); Sanchez, M, E-mail: floresj@agt.cie.uma.es, E-mail: jherrera@uma.es, E-mail: sanchezm@ugr.es [Departamento de Geometria y Topologia, Facultad de Ciencias, Universidad de Granada, Avenida Fuentenueva s/n, 18071 Granada (Spain)
2011-09-07
We construct an example which shows that two isocausal spacetimes, in the sense introduced recently in GarcIa-Parrado and Senovilla (2003 Class. Quantum Grav. 20 625-64), may have c-boundaries which are not equal (more precisely, not equivalent, as no bijection between the completions can preserve all the binary relations induced by causality). This example also suggests that isocausality can be useful for the understanding and computation of the c-boundary.
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 cau......, and we illustrate our arguments and our method using National Longitudinal Survey of Youth 1979 (NLSY79) data....
Assessing Causality in a Complex Security Environment
2015-01-01
Fidel Castro popular revolt. Of course, the Bay of Pigs invasion was a disastrous failure, one that humiliated the new President. The NIE went as...and place great reliance on it. The Castro regime is steadily losing popularity. . . . housewives and servants must stand in line for hours to...was evaluating the possibility of an anti- Castro uprising. What is the causal connection between soap lines and a readiness to spontane- ously
Waves and causality in higher dimensions
Wesson, Paul S
2015-01-01
We give a new, wave-like solution of the field equations of five-dimensional relativity. In ordinary three-dimensional space, the waves resemble de Broglie or matter waves, whose puzzling behaviour can be better understood in terms of one or more extra dimensions. Causality is appropriately defined by a null higher-dimensional interval. It may be possible to test the properties of these waves in the laboratory.
Imposing causality on a matrix model
Energy Technology Data Exchange (ETDEWEB)
Benedetti, Dario [Perimeter Institute for Theoretical Physics, 31 Caroline St. N, N2L 2Y5, Waterloo ON (Canada)], E-mail: dbenedetti@perimeterinstitute.ca; Henson, Joe [Perimeter Institute for Theoretical Physics, 31 Caroline St. N, N2L 2Y5, Waterloo ON (Canada)
2009-07-13
We introduce a new matrix model that describes Causal Dynamical Triangulations (CDT) in two dimensions. In order to do so, we introduce a new, simpler definition of 2D CDT and show it to be equivalent to the old one. The model makes use of ideas from dually weighted matrix models, combined with multi-matrix models, and can be studied by the method of character expansion.
Waves and causality in higher dimensions
Energy Technology Data Exchange (ETDEWEB)
Wesson, Paul S., E-mail: psw.papers@yahoo.ca [Department of Physics and Astronomy, University of Waterloo, Waterloo, ON, N2L 3G1 (Canada); Overduin, James M., E-mail: joverduin@towson.edu [Department of Physics, Astronomy and Geosciences, Towson University, Towson, MD, 21252 (United States); Department of Physics and Astronomy, Johns Hopkins University, 3400 N. Charles St., Baltimore, MD, 21218 (United States)
2015-11-12
We give a new, wave-like solution of the field equations of five-dimensional relativity. In ordinary three-dimensional space, the waves resemble de Broglie or matter waves, whose puzzling behaviour can be better understood in terms of one or more extra dimensions. Causality is appropriately defined by a null higher-dimensional interval. It may be possible to test the properties of these waves in the laboratory.
Bayesian Discovery of Linear Acyclic Causal Models
Hoyer, Patrik O
2012-01-01
Methods for automated discovery of causal relationships from non-interventional data have received much attention recently. A widely used and well understood model family is given by linear acyclic causal models (recursive structural equation models). For Gaussian data both constraint-based methods (Spirtes et al., 1993; Pearl, 2000) (which output a single equivalence class) and Bayesian score-based methods (Geiger and Heckerman, 1994) (which assign relative scores to the equivalence classes) are available. On the contrary, all current methods able to utilize non-Gaussianity in the data (Shimizu et al., 2006; Hoyer et al., 2008) always return only a single graph or a single equivalence class, and so are fundamentally unable to express the degree of certainty attached to that output. In this paper we develop a Bayesian score-based approach able to take advantage of non-Gaussianity when estimating linear acyclic causal models, and we empirically demonstrate that, at least on very modest size networks, its accur...
[Causality in cardiology: concepts in evolution].
Méndez, Gustavo F
2005-01-01
This paper describes several concepts about causality from Empedocles, Aristoteles and Galeno, to Koch and Hill and the evolution of these concepts related to cardiovascular diseases. Also defines cause and risk, and the philosophical theories about scientific knowledge: inductive versus refutation analysis. On these basis, the study of cardiovascular disease's causality, especially coronary heart disease, allows us the identification of several risk factors involved in its development. However, even with the presently coronary heart disease risk charts (from Framingham and European studies) the higher probability for the development of a cardiovascular ischemic event is around 40%, establishing an important degree of uncertainty. With the improvement in molecular biology techniques, genetics have attempted to analyse several genetic polymorphisms in search of the origin of coronary heart disease. Unfortunately, less than 10% of these polymorphisms have had a positive correlation with coronary heart disease being of minor risk that those obtained for having the diagnosis of type 2 diabetes mellitus or hypercholesterolemia. On these basis, the requirement of new population research projects in which clinical and genetic risk factors are to be studied for the appropriate understanding of the causality process of cardiovascular diseases must be a worldwide priority.
A causal dispositional account of fitness.
Triviño, Vanessa; Nuño de la Rosa, Laura
2016-09-01
The notion of fitness is usually equated to reproductive success. However, this actualist approach presents some difficulties, mainly the explanatory circularity problem, which have lead philosophers of biology to offer alternative definitions in which fitness and reproductive success are distinguished. In this paper, we argue that none of these alternatives is satisfactory and, inspired by Mumford and Anjum's dispositional theory of causation, we offer a definition of fitness as a causal dispositional property. We argue that, under this framework, the distinctiveness that biologists usually attribute to fitness-namely, the fact that fitness is something different from both the physical traits of an organism and the number of offspring it leaves-can be explained, and the main problems associated with the concept of fitness can be solved. Firstly, we introduce Mumford and Anjum's dispositional theory of causation and present our definition of fitness as a causal disposition. We explain in detail each of the elements involved in our definition, namely: the relationship between fitness and the functional dispositions that compose it, the emergent character of fitness, and the context-sensitivity of fitness. Finally, we explain how fitness and realized fitness, as well as expected and realized fitness are distinguished in our approach to fitness as a causal disposition.
Identifiability of large phylogenetic mixture models.
Rhodes, John A; Sullivant, Seth
2012-01-01
Phylogenetic mixture models are statistical models of character evolution allowing for heterogeneity. Each of the classes in some unknown partition of the characters may evolve by different processes, or even along different trees. Such models are of increasing interest for data analysis, as they can capture the variety of evolutionary processes that may be occurring across long sequences of DNA or proteins. The fundamental question of whether parameters of such a model are identifiable is difficult to address, due to the complexity of the parameterization. Identifiability is, however, essential to their use for statistical inference.We analyze mixture models on large trees, with many mixture components, showing that both numerical and tree parameters are indeed identifiable in these models when all trees are the same. This provides a theoretical justification for some current empirical studies, and indicates that extensions to even more mixture components should be theoretically well behaved. We also extend our results to certain mixtures on different trees, using the same algebraic techniques.
[Construction of Three-Dimensional Isobologram for Ternary Pollutant Mixtures].
2015-12-01
Tongji University, Shanghai 200092, China) Isobolographic analysis was widely used in the interaction assessment of binary mixtures. However, how to construct a three-dimensional (3D) isobologram for the assessment of toxicity interaction within ternary mixtures is still not reported up to date. The main purpose of this paper is to develop a 3D isobologram where the relative concentrations of three components are acted as three coordinate axes in 3D space to examine the toxicity interaction within ternary mixtures. Taking six commonly used pesticides in China, including three herbicides (2, 4-D, desmetryne and simetryn) and three insecticides ( dimethoate, imidacloprid and propoxur) as the mixture components, the uniform design ray procedure (UD-Ray) was used to rationally design the concentration composition of various components in the ternary mixtures so that effectively and comprehensively reflected the variety of actual environmental concentrations. The luminescent inhibition toxicities of single pesticides and their ternary mixtures to Vibrio fischeri at various concentration levels were determined by the microplate toxicity analysis. Selecting concentration addition (CA) as the addition reference, 3D isobolograms were constructed to study the toxicity interactions of various ternary mixtures. The results showed that the 3D isobologram could clearly and directly exhibit the toxicity interactions of ternary mixtures, and extend the use of isobolographic analysis into the ternary mixtures.
Information causality from an entropic and a probabilistic perspective
Energy Technology Data Exchange (ETDEWEB)
Al-Safi, Sabri W.; Short, Anthony J. [DAMTP, Centre for Mathematical Sciences, Wilberforce Road, Cambridge CB3 0WA (United Kingdom)
2011-10-15
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.
Explaining slow convergence of EM in low noise linear mixtures
Petersen, Kaare Brandt; Winther, Ole
2005-01-01
This report conducts an investigation of the convergence properties of the EM algorithm used for linear mixture models. Since the linear mixture model is a rather general approach, the analysis is relevant for a wide range of models which to some degree are subsets of each other: Independent Component Analysis (ICA), probabilistic PCA, Factor Analysis (FA), Independent Factor Analysis (IFA) and Mean Field ICA.
Learning High-Dimensional Mixtures of Graphical Models
Anandkumar, A; Kakade, S M
2012-01-01
We consider the problem of learning mixtures of discrete graphical models in high dimensions and propose a novel method for estimating the mixture components with provable guarantees. The method proceeds mainly in three stages. In the first stage, it estimates the union of the Markov graphs of the mixture components (referred to as the union graph) via a series of rank tests. It then uses this estimated union graph to compute the mixture components via a spectral decomposition method. The spectral decomposition method was originally proposed for latent class models, and we adapt this method for learning the more general class of graphical model mixtures. In the end, the method produces tree approximations of the mixture components via the Chow-Liu algorithm. Our output is thus a tree-mixture model which serves as a good approximation to the underlying graphical model mixture. When the union graph has sparse node separators, we prove that our method has sample and computational complexities scaling as poly(p, ...
Carbon Emissions and Economic Growth: Causality Testing in Heterogenous Panels
Energy Technology Data Exchange (ETDEWEB)
David Maddison; Katrin Rehdanz [Department of Economics, University of Birmingham, Birmingham (United Kingdom)
2008-09-30
Numerous papers have examined data on energy and GDP for evidence of Granger causality. Using time series techniques these analyses not infrequently reach differing conclusions concerning the existence and direction of Granger causality. This paper presents a heterogenous panel approach to Granger causality testing. This technique is used to examine a panel of data for evidence of a causal relationship between GDP and carbon emissions per capita allowing for heterogeneity in short run dynamics and even the long run cointegrating vector. This technique is compared to the standard fixed dynamic effects approach to pooling individual error correction models. In one important case the heterogenous panel test for Granger causality reaches conclusions quite different to those from conventional tests of Granger causality. Except for Asia there is strong evidence for the existence of a bidirectional causal relationship between GDP per capita and CO{sub 2} emissions per capita.
Comparison of Slack Variable and Mixture Experiment Approaches
Energy Technology Data Exchange (ETDEWEB)
Landmesser, Samantha; Piepel, Gregory F.
2008-10-31
In a mixture experiment, the response variable depends on the proportions of the components, which must sum to one. Because of this constraint, standard polynomial models cannot be used to analyze mixture experiment data. To get around this, some researchers ignore one of the components and use standard polynomial models in the remaining components. Because the component proportions must sum to one, the ignored component (referred to as the slack variable (SV)) makes up the remaining proportion of the mixture. In the literature, there have been many examples of researchers using the SV approach instead of a mixture approach. We have analyzed data from several of these examples using both approaches. For examples whose goal was to screen the mixture components (screening examples), we fit full linear models and identified which components were important using both approaches. In the screening examples, the mixture approach revealed that the SV had a significant effect on the response. For examples that had sufficient data to fit quadratic models to the data (quadratic examples), we used stepwise regression to develop reduced quadratic models for the SV approach, and partial quadratic mixture (PQM) models for the mixture approach. In three quadratic examples, the PQM models identified the SV and/or one of its quadratic blending terms as having a significant effect on the response variable. Hence, by completely ignoring a component’s effect on the response, SV analysis carries an inherent risk of wrong conclusions. There are fewer possible reduced quadratic SV models than possible PQM models because the reduced quadratic SV models are a subset of the class of PQM models. As a result, the PQM models will always fit the data as well as, or better than, the best reduced quadratic SV model. Our research concludes that it is better to analyze mixture experiments using methods specifically developed for them instead of using standard methods with the SV approach.
Mixture for removing tar and paraffin deposits
Energy Technology Data Exchange (ETDEWEB)
kamenshchikov, F.A.; Frolov, M.A.; Golovin, I.N.; Khusainov, Z.M.; Smirnov, Ya.L.; Suchkov, B.M.
1981-05-23
Mixture is claimed for removing tar and paraffin deposits (TPD) on the basis of the butyl-benzene fraction (BBF), which is intended to more efficiently remove TPD from the surface of refinery equipment, additionally has piperylene, isoprene and isoamine with the following ratio of the components: piperylene, 19-31%; isoprene, 8-12%; isoamines, 8-12%, while BBF, the rest. The efficiency of the given compositions was assessed by the rate at which the plates were cleaned of TPD and pure commercial paraffin. It has been shown that BBF dissolves 4-6 times faster in the given mixture than in BBF and pyperylene.
Emergent Geometry from Entropy and Causality
Engelhardt, Netta
In this thesis, we investigate the connections between the geometry of spacetime and aspects of quantum field theory such as entanglement entropy and causality. This work is motivated by the idea that spacetime geometry is an emergent phenomenon in quantum gravity, and that the physics responsible for this emergence is fundamental to quantum field theory. Part I of this thesis is focused on the interplay between spacetime and entropy, with a special emphasis on entropy due to entanglement. In general spacetimes, there exist locally-defined surfaces sensitive to the geometry that may act as local black hole boundaries or cosmological horizons; these surfaces, known as holographic screens, are argued to have a connection with the second law of thermodynamics. Holographic screens obey an area law, suggestive of an association with entropy; they are also distinguished surfaces from the perspective of the covariant entropy bound, a bound on the total entropy of a slice of the spacetime. This construction is shown to be quite general, and is formulated in both classical and perturbatively quantum theories of gravity. The remainder of Part I uses the Anti-de Sitter/ Conformal Field Theory (AdS/CFT) correspondence to both expand and constrain the connection between entanglement entropy and geometry. The AdS/CFT correspondence posits an equivalence between string theory in the "bulk" with AdS boundary conditions and certain quantum field theories. In the limit where the string theory is simply classical General Relativity, the Ryu-Takayanagi and more generally, the Hubeny-Rangamani-Takayanagi (HRT) formulae provide a way of relating the geometry of surfaces to entanglement entropy. A first-order bulk quantum correction to HRT was derived by Faulkner, Lewkowycz and Maldacena. This formula is generalized to include perturbative quantum corrections in the bulk at any (finite) order. Hurdles to spacetime emergence from entanglement entropy as described by HRT and its quantum
Foundational perspectives on causality in large-scale brain networks.
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
Foundational perspectives on causality in large-scale brain networks
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
Groten, J.P.
2000-01-01
Drinking water can be considered as a complex mixture that consists of tens, hundreds or thousands of chemicals of which the composition is qualitatively and quantitatively not fully known. From a public health point of view it is most relevant to answer the question of whether chemicals in drinking
Neuroleptic malignant syndrome: mechanisms, interactions, and causality.
Gillman, P Ken
2010-09-15
This review focuses on new data from recent publications concerning how compounding interactions between different thermoregulatory pathways influence the development of hyperthermia and/or neuroleptic malignant syndrome (NMS), and the fundamental issue of the presumed causal role of antipsychotic drugs. The formal criteria for substantiating cause-effect relationships in medical science, established by Hill, are applied to NMS and, for comparison, also to malignant hyperthermia and serotonin toxicity. The risk of morbidities related to hyperthermia is reviewed from human and experimental data: temperatures in excess of 39.5°C cause physiological and cellular dysfunction and high mortality. The most temperature-sensitive elements of neural cells are mitochondrial and plasma membranes, in which irreversible changes occur around 40°C. Temperatures of up to 39°C are "normal" in mammals, so, the term hyperthermia should be reserved for temperatures of 39.5°C or greater. The implicitly accepted presumption that NMS is a hypermetabolic and hyperthermic syndrome is questionable and does not explain the extensive morbidity in the majority of cases, where the temperature is less than 39°C. The thermoregulatory effects of dopamine and acetylcholine are outlined, especially because they are probably the main pathways by which neuroleptic drugs might affect thermoregulation. It is notable that even potent antagonism of these mechanisms rarely causes temperature elevation and that multiple mechanisms, including the acute phase response, stress-induced hyperthermia, drugs effects, etc., involving compounding interactions, are required to precipitate hyperthermia. The application of the Hill criteria clearly supports causality for drugs inducing both MH and ST but do not support causality for NMS.
Causal Loop Analysis of coastal geomorphological systems
Payo, Andres; Hall, Jim W.; French, Jon; Sutherland, James; van Maanen, Barend; Nicholls, Robert J.; Reeve, Dominic E.
2016-03-01
As geomorphologists embrace ever more sophisticated theoretical frameworks that shift from simple notions of evolution towards single steady equilibria to recognise the possibility of multiple response pathways and outcomes, morphodynamic modellers are facing the problem of how to keep track of an ever-greater number of system feedbacks. Within coastal geomorphology, capturing these feedbacks is critically important, especially as the focus of activity shifts from reductionist models founded on sediment transport fundamentals to more synthesist ones intended to resolve emergent behaviours at decadal to centennial scales. This paper addresses the challenge of mapping the feedback structure of processes controlling geomorphic system behaviour with reference to illustrative applications of Causal Loop Analysis at two study cases: (1) the erosion-accretion behaviour of graded (mixed) sediment beds, and (2) the local alongshore sediment fluxes of sand-rich shorelines. These case study examples are chosen on account of their central role in the quantitative modelling of geomorphological futures and as they illustrate different types of causation. Causal loop diagrams, a form of directed graph, are used to distil the feedback structure to reveal, in advance of more quantitative modelling, multi-response pathways and multiple outcomes. In the case of graded sediment bed, up to three different outcomes (no response, and two disequilibrium states) can be derived from a simple qualitative stability analysis. For the sand-rich local shoreline behaviour case, two fundamentally different responses of the shoreline (diffusive and anti-diffusive), triggered by small changes of the shoreline cross-shore position, can be inferred purely through analysis of the causal pathways. Explicit depiction of feedback-structure diagrams is beneficial when developing numerical models to explore coastal morphological futures. By explicitly mapping the feedbacks included and neglected within a
On asymmetric causal relationships in Petropolitics
Directory of Open Access Journals (Sweden)
Balan Feyza
2016-01-01
Full Text Available The aim of this paper is to examine whether the First Law of Petropolitics denominated by Friedman in 2006 is valid for OPEC countries. To do this, this paper analyses the relationship between political risk and oil supply by applying the asymmetric panel causality test suggested by Hatemi-J (2011 to these countries for the period 1984-2014. The results show that the First Law of Petropolitics is valid for Angola, Iraq, Kuwait, Libya, Nigeria, Qatar, Saudi Arabia, and the UAE, given that positive oil supply shocks significantly lead to negative political stability shocks, and negative oil supply shocks significantly lead to positive shocks in political stability.
Qualitative analysis of causal cosmological models
Triginer, J
1996-01-01
The Einstein's field equations of Friedmann-Robertson-Walker universes filled with a dissipative fluid described by both the {\\em truncated} and {\\em non-truncated} causal transport equations are analyzed using techniques from dynamical systems theory. The equations of state, as well as the phase space, are different from those used in the recent literature. In the de Sitter expansion both the hydrodynamic approximation and the non-thermalizing condition can be fulfilled simultaneously. For \\Lambda=0 these expansions turn out to be stable provided a certain parameter of the fluid is lower than 1/2. The more general case \\Lambda>0 is studied in detail as well.
Relativistic causality and position space renormalization
Todorov, Ivan
2016-11-01
The paper gives a historical survey of the causal position space renormalization with a special attention to the role of Raymond Stora in the development of this subject. Renormalization is reduced to subtracting the pole term in analytically regularized primitively divergent Feynman amplitudes. The identification of residues with "quantum periods" and their relation to recent developments in number theory are emphasized. We demonstrate the possibility of integration over internal vertices (that requires control over the infrared behavior) in the case of the massless φ4 theory and display the dilation and the conformal anomaly.
On causality, unitarity and perturbative expansions
Energy Technology Data Exchange (ETDEWEB)
Danilkin, Igor; Gasparyan, Ashot; Lutz, Matthias [GSI, Planck Str. 1, 64291 Darmstadt (Germany)
2011-07-01
We present a pedagogical case study how to combine micro-causality and unitarity based on a perturbative approach. The method we advocate constructs an analytic extrapolation of partial-wave scattering amplitudes that is constrained by the unitarity condition. Suitably constructed conformal mappings help to arrive at a systematic approximation of the scattering amplitude. The technique is illustrated at hand of a Yukawa interaction. The typical case of a superposition of strong short-range and weak long-range forces is investigated.
Rapidity Correlation Structures from Causal Hydrodynamics
Gavin, Sean; Zin, Christopher
2016-01-01
Viscous diffusion can broaden the rapidity dependence of two-particle transverse momentum fluctuations. Surprisingly, measurements at RHIC by the STAR collaboration demonstrate that this broadening is accompanied by the appearance of unanticipated structure in the rapidity distribution of these fluctuations in the most central collisions. Although a first order classical Navier-Stokes theory can roughly explain the rapidity broadening, it cannot explain the additional structure. We propose that the rapidity structure can be explained using the second order causal Israel-Stewart hydrodynamics with stochastic noise.
On causality, unitarity and perturbative expansions
Energy Technology Data Exchange (ETDEWEB)
Danilkin, I.V.; Gasparyan, A.M. [GSI Helmholtzzentrum fuer Schwerionenforschung GmbH, Planck Str. 1, 64291 Darmstadt (Germany); Institute for Theoretical and Experimental Physics, 117259, B. Cheremushkinskaya 25, Moscow (Russian Federation); Lutz, M.F.M., E-mail: m.lutz@gsi.d [GSI Helmholtzzentrum fuer Schwerionenforschung GmbH, Planck Str. 1, 64291 Darmstadt (Germany)
2011-02-28
We present a pedagogical case study how to combine micro-causality and unitarity based on a perturbative approach. The method we advocate constructs an analytic extrapolation of partial-wave scattering amplitudes that is constrained by the unitarity condition. Suitably constructed conformal mappings help to arrive at a systematic approximation of the scattering amplitude in a quantum-field theoretical context. The technique is illustrated at hand of a Yukawa interaction. The typical case of a superposition of strong short-range and weak long-range forces is investigated.
Gauge invariance, causality and gluonic poles
Energy Technology Data Exchange (ETDEWEB)
Anikin, I.V., E-mail: anikin@theor.jinr.r [Bogoliubov Laboratory of Theoretical Physics, JINR, 141980 Dubna (Russian Federation); Teryaev, O.V., E-mail: teryaev@theor.jinr.r [Bogoliubov Laboratory of Theoretical Physics, JINR, 141980 Dubna (Russian Federation)
2010-07-05
We explore the electromagnetic gauge invariance of the hadron tensor of the Drell-Yan process with one transversely polarized hadron. The special role is played by the contour gauge for gluon fields. The prescription for the gluonic pole in the twist 3 correlator is related to causality property and compared with the prescriptions for exclusive hard processes. As a result we get the extra contributions, which naively do not have an imaginary phase. The single spin asymmetry for the Drell-Yan process is accordingly enhanced by the factor of two.
How Many Separable Sources? Model Selection In Independent Components Analysis
DEFF Research Database (Denmark)
Woods, Roger P.; Hansen, Lars Kai; Strother, Stephen
2015-01-01
Unlike mixtures consisting solely of non-Gaussian sources, mixtures including two or more Gaussian components cannot be separated using standard independent components analysis methods that are based on higher order statistics and independent observations. The mixed Independent Components Analysi...... might otherwise be questionable. Failure of the Akaike Information Criterion in model selection also has relevance in traditional independent components analysis where all sources are assumed non-Gaussian.......Unlike mixtures consisting solely of non-Gaussian sources, mixtures including two or more Gaussian components cannot be separated using standard independent components analysis methods that are based on higher order statistics and independent observations. The mixed Independent Components Analysis....../Principal Components Analysis (mixed ICA/PCA) model described here accommodates one or more Gaussian components in the independent components analysis model and uses principal components analysis to characterize contributions from this inseparable Gaussian subspace. Information theory can then be used to select from...
Two-Microphone Separation of Speech Mixtures
DEFF Research Database (Denmark)
Pedersen, Michael Syskind; Wang, DeLiang; Larsen, Jan
2008-01-01
Separation of speech mixtures, often referred to as the cocktail party problem, has been studied for decades. In many source separation tasks, the separation method is limited by the assumption of at least as many sensors as sources. Further, many methods require that the number of signals within...... the recorded mixtures be known in advance. In many real-world applications, these limitations are too restrictive. We propose a novel method for underdetermined blind source separation using an instantaneous mixing model which assumes closely spaced microphones. Two source separation techniques have been...... combined, independent component analysis (ICA) and binary time–frequency (T–F) masking. By estimating binary masks from the outputs of an ICA algorithm, it is possible in an iterative way to extract basis speech signals from a convolutive mixture. The basis signals are afterwards improved by grouping...
Evaluation of vapor compression cycles using nonazeotropic refrigerant mixtures
Merriam, Richard L.
A comprehensive investigation is carried out, on a systematic and consistent basis, to explore a range of advanced heat pump cycle concepts using nonazeotropic refrigerants for COP enhancement and capacity modulation along with the trade-offs associated with refrigerant mixture selection. The objectives of the study were to: identify candidate nonazeotropic mixtures and advanced heat pump cycle concepts with emphasis on their potential for single-speed capacity modulation with mixture composition control; assess the effect of conjunction with nonazeotropic mixture cycles; evaluate the cycles analytically and recommend the most promising cycles and mixtures for further development; and provide recommendations relating to the needs for additional refrigerant property data, experimental studies of basic heat transfer phenomena with mixed refrigerants, development of system components, and/or more detailed modeling of specific components.
Quantitative measurement of mixtures by terahertz time-domain spectroscopy
Indian Academy of Sciences (India)
Guifeng Liu; Zengyan Zhang; Shihua Ma; Hongwei Zhao; Xiaojing Ma; Wenfeng Wang
2009-07-01
Terahertz time-domain spectroscopy (THz-TDS) was applied for quantitatively analysing a series of binary mixtures and a ternary mixture. Binary mixtures having different weight ratios of two components, -aminophenol and m-nitroaniline, were investigated by THz-TDS in the range of 0.3 to 1.5 THz, and it was found that the absorption coefficients of the components in each mixture were linearly proportional to their concentrations in the mixture. The results from analysis were in agreement with actual values with a relative error of less than 7%. The quantitative method will help in the detection of illegal drugs, poisons and dangerous materials that are wrapped or mixed with other materials.
God Does Not Play Dice: Causal Determinism and Preschoolers' Causal Inferences
Schulz, Laura E.; Sommerville, Jessica
2006-01-01
Three studies investigated children's belief in causal determinism. If children are determinists, they should infer unobserved causes whenever observed causes appear to act stochastically. In Experiment 1, 4-year-olds saw a stochastic generative cause and inferred the existence of an unobserved inhibitory cause. Children traded off inferences…
Maximum likelihood estimation of finite mixture model for economic data
Phoong, Seuk-Yen; Ismail, Mohd Tahir
2014-06-01
Finite mixture model is a mixture model with finite-dimension. This models are provides a natural representation of heterogeneity in a finite number of latent classes. In addition, finite mixture models also known as latent class models or unsupervised learning models. Recently, maximum likelihood estimation fitted finite mixture models has greatly drawn statistician's attention. The main reason is because maximum likelihood estimation is a powerful statistical method which provides consistent findings as the sample sizes increases to infinity. Thus, the application of maximum likelihood estimation is used to fit finite mixture model in the present paper in order to explore the relationship between nonlinear economic data. In this paper, a two-component normal mixture model is fitted by maximum likelihood estimation in order to investigate the relationship among stock market price and rubber price for sampled countries. Results described that there is a negative effect among rubber price and stock market price for Malaysia, Thailand, Philippines and Indonesia.
Immunity in arterial hypertension: associations or causalities?
Anders, Hans-Joachim; Baumann, Marcus; Tripepi, Giovanni; Mallamaci, Francesca
2015-12-01
Numerous studies describe associations between markers of inflammation and arterial hypertension (aHT), but does that imply causality? Interventional studies that reduce blood pressure reduced also markers of inflammation, but does immunosuppression improve hypertension? Here, we review the available mechanistic data. Aberrant immunity can trigger endothelial dysfunction but is hardly ever the primary cause of aHT. Innate and adaptive immunity get involved once hypertension has caused vascular wall injury as immunity is a modifier of endothelial dysfunction and vascular wall remodelling. As vascular remodelling progresses, immunity-related mechanisms can become significant cofactors for cardiovascular (CV) disease progression; vice versa, suppressing immunity can improve hypertension and CV outcomes. Innate and adaptive immunity both contribute to vascular wall remodelling. Innate immunity is driven by danger signals that activate Toll-like receptors and other pattern-recognition receptors. Adaptive immunity is based on loss of tolerance against vascular autoantigens and includes autoreactive T-cell immunity as well as non-HLA angiotensin II type 1 receptor-activating autoantibodies. Such processes involve numerous other modulators such as regulatory T cells. Together, immunity is not causal for hypertension but rather an important secondary pathomechanism and a potential therapeutic target in hypertension.
Causality and stability of cosmic jets
Porth, O
2014-01-01
In stark contrast to their laboratory and terrestrial counterparts, the cosmic jets appear to be very stable. The are able to penetrate vast spaces, which exceed by up to a billion times the size of their central engines. We propose that the reason behind this remarkable property is the loss of causal connectivity across these jets, caused by their rapid expansion in response to fast decline of external pressure with the distance from the "jet engine". In atmospheres with power-law pressure distribution, the total loss of causal connectivity occurs, when the power index k>2 - the steepness which is expected to be quite common for many astrophysical environments. This conclusion does not seem to depend on the physical nature of jets - it applies both to relativistic and non-relativistic flows, both magnetically-dominated and unmagnetized jets. In order to verify it, we have carried out numerical simulations of moderately magnetized and moderately relativistic jets. Their results give strong support to our hypo...
Emergent Horizons and Causal Structures in Holography
Banerjee, Avik; Kundu, Sandipan
2016-01-01
The open string metric arises kinematically in studying fluctuations of open string degrees of freedom on a D-brane. An observer, living on a probe D-brane, can send signals through the spacetime by using such fluctuations on the probe, that propagate in accordance with a metric which is conformal to the open string metric. Event horizons can emerge in the open string metric when one considers a D-brane with an electric field on its worldvolume. Here, we emphasize the role of and investigate, in details, the causal structure of the resulting open string event horizon and demonstrate, among other things, its close similarities to an usual black hole event horizon in asymptotically AdS-spaces. To that end, we analyze relevant geodesics, Penrose diagrams and various causal holographic observables for a given open string metric. For analytical control, most of our calculations are performed in an asymptotically AdS$_3$-background, however, we argue that the physics is qualitatively the same in higher dimensions. ...
Legendrian links, causality, and the Low conjecture
Chernov, Vladimir
2008-01-01
Let $(X^{m+1}, g)$ be a globally hyperbolic spacetime with Cauchy surface diffeomorphic to an open subset of $\\mathbb R^m$. The Legendrian Low conjecture formulated by Nat\\'ario and Tod says that two events $x,y\\in X$ are causally related if and only if the Legendrian link of spheres $\\mathfrak S_x, \\mathfrak S_y$ whose points are light geodesics passing through $x$ and $y$ is non-trivial in the contact manifold of all light geodesics in $X$. The Low conjecture says that for $m=2$ the events $x,y$ are causally related if and only if $\\mathfrak S_x, \\mathfrak S_y$ is non-trivial as a topological link. We prove the Low and the Legendrian Low conjectures. We also show that similar statements hold for any globally hyperbolic $(X, g)$ such that the universal cover of its Cauchy surface is diffeomorphic to an open domain of $\\mathbb R^m.$
Causality, randomness, intelligibility, and the epistemology of the cell.
Dougherty, Edward R; Bittner, Michael L
2010-06-01
Because the basic unit of biology is the cell, biological knowledge is rooted in the epistemology of the cell, and because life is the salient characteristic of the cell, its epistemology must be centered on its livingness, not its constituent components. The organization and regulation of these components in the pursuit of life constitute the fundamental nature of the cell. Thus, regulation sits at the heart of biological knowledge of the cell and the extraordinary complexity of this regulation conditions the kind of knowledge that can be obtained, in particular, the representation and intelligibility of that knowledge. This paper is essentially split into two parts. The first part discusses the inadequacy of everyday intelligibility and intuition in science and the consequent need for scientific theories to be expressed mathematically without appeal to commonsense categories of understanding, such as causality. Having set the backdrop, the second part addresses biological knowledge. It briefly reviews modern scientific epistemology from a general perspective and then turns to the epistemology of the cell. In analogy with a multi-faceted factory, the cell utilizes a highly parallel distributed control system to maintain its organization and regulate its dynamical operation in the face of both internal and external changes. Hence, scientific knowledge is constituted by the mathematics of stochastic dynamical systems, which model the overall relational structure of the cell and how these structures evolve over time, stochasticity being a consequence of the need to ignore a large number of factors while modeling relatively few in an extremely complex environment.
Non-parametric causal inference for bivariate time series
McCracken, James M
2015-01-01
We introduce new quantities for exploratory causal inference between bivariate time series. The quantities, called penchants and leanings, are computationally straightforward to apply, follow directly from assumptions of probabilistic causality, do not depend on any assumed models for the time series generating process, and do not rely on any embedding procedures; these features may provide a clearer interpretation of the results than those from existing time series causality tools. The penchant and leaning are computed based on a structured method for computing probabilities.
On the causal structure between CO2 and global temperature
Adolf Stips; Diego Macias; Clare Coughlan; Elisa Garcia-Gorriz; X. San Liang
2016-01-01
We use a newly developed technique that is based on the information flow concept to investigate the causal structure between the global radiative forcing and the annual global mean surface temperature anomalies (GMTA) since 1850. Our study unambiguously shows one-way causality between the total Greenhouse Gases and GMTA. Specifically, it is confirmed that the former, especially CO2, are the main causal drivers of the recent warming. A significant but smaller information flow comes from aeroso...
Missing Data as a Causal and Probabilistic Problem
2015-07-01
graphs and missingness models to formally define missing data as a type of causal inference problem where only interventions on certain variables are...approach of [7] of representing missing data problems to causal models where only interventions on missingness indicators are allowed. We further use this... Missing Data as a Causal and Probabilistic Problem Ilya Shpitser Mathematical Sciences University of Southampton Southampton, UK SO14 6WD i.shpitser
Botrytis cinerea: Causal agent of small fruit grey mould
Tanović, Brankica
2012-01-01
Small fruits growing in Serbia is an important and profitable business. However, disease causal agents, pests and weeds often threaten production profitability. A common problem in production of most important small fruit species is a polyfagous, phytopathogenic fungal species Botrytis cinerea, the causal agent of grey mould disease of fruits. Present knowledge on the causal agent, its morphological, ecological and epidemiological characteristics are systematized in the paper. Infection proce...
"Foreign and Public Deficits in Greece: In Search of Causality"
2013-01-01
The paper discusses the trajectories of the Greek public deficit and sovereign debt over the last three decades and its connection to the political and economic environment of the same period. We pay special attention to the causality between the public and the foreign deficit. We argue that from 1980 to 1995 causality ran from the public deficit to the foreign deficit, but that due to the European monetary unification process and the adoption of the common currency, causality has reversed si...
The Causality between Government Revenue and Government Expenditure in Iran
Elyasi, Yousef; Rahimi, Mohammad
2012-01-01
The causal relationship between government revenue and government expenditure is an important subject in public economics especially to the control of budget deficit. The purpose of this study is to investigate the relationship between government revenue and government expenditure in Iran by applying the bounds testing approach to cointegration. The results of the causality test show that there is a bidirectional causal relationship between government expenditure and revenues in both long run...
Pointer Sentinel Mixture Models
Merity, Stephen; Xiong, Caiming; Bradbury, James; Socher, Richard
2016-01-01
Recent neural network sequence models with softmax classifiers have achieved their best language modeling performance only with very large hidden states and large vocabularies. Even then they struggle to predict rare or unseen words even if the context makes the prediction unambiguous. We introduce the pointer sentinel mixture architecture for neural sequence models which has the ability to either reproduce a word from the recent context or produce a word from a standard softmax classifier. O...
Granger causality and transfer entropy are equivalent for Gaussian variables.
Barnett, Lionel; Barrett, Adam B; Seth, Anil K
2009-12-01
Granger causality is a statistical notion of causal influence based on prediction via vector autoregression. Developed originally in the field of econometrics, it has since found application in a broader arena, particularly in neuroscience. More recently transfer entropy, an information-theoretic measure of time-directed information transfer between jointly dependent processes, has gained traction in a similarly wide field. While it has been recognized that the two concepts must be related, the exact relationship has until now not been formally described. Here we show that for Gaussian variables, Granger causality and transfer entropy are entirely equivalent, thus bridging autoregressive and information-theoretic approaches to data-driven causal inference.
Granger causality and transfer entropy are equivalent for Gaussian variables
Barnett, Lionel; Seth, Anil
2009-01-01
Granger causality is a statistical notion of causal influence based on prediction via vector autoregression. Developed originally in the field of econometrics, it has since found application in a broader arena, particularly in neuroscience. More recently transfer entropy, an information-theoretic measure of time-directed information transfer between jointly dependent processes, has gained traction in a similarly wide field. It has always seemed plausible that the two concepts ought to be related. Here we show that for Gaussian variables, Granger causality and transfer entropy are entirely equivalent, thus bridging autoregressive and information-theoretic approaches to data-driven causal inference.
Linkage intensity learning approach with genetic algorithm for causality diagram
Institute of Scientific and Technical Information of China (English)
WANG Cheng-liang; CHEN Juan-juan
2007-01-01
The causality diagram theory, which adopts graphical expression of knowledge and direct intensity of causality, overcomes some shortages in belief network and has evolved into a mixed causality diagram methodology for discrete and continuous variable. But to give linkage intensity of causality diagram is difficult, particularly in many working conditions in which sampling data are limited or noisy. The classic learning algorithm is hard to be adopted. We used genetic algorithm to learn linkage intensity from limited data. The simulation results demonstrate that this algorithm is more suitable than the classic algorithm in the condition of sample shortage such as space shuttle's fault diagnoisis.
Noether-Like Theorems for Causal Variational Principles
Finster, Felix
2015-01-01
The connection between symmetries and conservation laws as made by Noether's theorem is extended to the context of causal variational principles and causal fermion systems. Different notions of continuous symmetries are introduced. It is proven that these symmetries give rise to corresponding conserved quantities, expressed in terms of so-called surface layer integrals. In a suitable limiting case, the Noether-like theorems for causal fermion systems reproduce charge conservation and the conservation of energy and momentum in Minkowski space. Thus the conservation of charge and energy-momentum are found to be special cases of general conservation laws which are intrinsic to causal fermion systems.
Carbon Emissions and Economic Growth: Alternative Approaches to Causality Testing
Energy Technology Data Exchange (ETDEWEB)
Rehdanz, Katrin (Christian-Albrechts Univ., Kiel (Germany)); Maddison, David J. (Univ. of Birmingham, Dept. of Economics, Birmingham (United Kingdom))
2008-07-01
Numerous papers have examined data on energy and GDP for evidence of Granger causality. More recently this technique has been extended to looking at the relationship between carbon emissions and GDP per capita. These analyses frequently reach differing conclusions concerning the existence and direction of Granger causality. This paper compares the standard fixed-dynamic-effects approach to a heterogenous panel approach testing for evidence of a causal relationship between GDP per capita and carbon emissions per capita allowing for heterogeneity. Overall there is strong evidence for the existence of a bidirectional causal relationship between GDP per capita and CO{sub 2} emissions per capita
Lattice Model for water-solute mixtures
Furlan, A. P.; Almarza, N. G.; M. C. Barbosa
2016-01-01
A lattice model for the study of mixtures of associating liquids is proposed. Solvent and solute are modeled by adapting the associating lattice gas (ALG) model. The nature of interaction solute/solvent is controlled by tuning the energy interactions between the patches of ALG model. We have studied three set of parameters, resulting on, hydrophilic, inert and hydrophobic interactions. Extensive Monte Carlo simulations were carried out and the behavior of pure components and the excess proper...
Quantum Causality, Stochastics, Trajectories and Information
Belavkin, V P
2002-01-01
A history of the discovery of quantum mechanics and paradoxes of its interpretation is reconsidered from the modern point of view of quantum stochastics and information. It is argued that in the orthodox quantum mechanics there is no place for quantum phenomenology such as events. The development of quantum measurement theory, initiated by von Neumann, and Bell's conceptual critics of hidden variable theories indicated a possibility for resolution of this crisis. This can be done by divorcing the algebra of the dynamical generators and an extended algebra of the potential (quantum) and the actual (classical) observables. The latter, called beables, form the center of the algebra of all observables, as the only visible (macroscopic) observables must be compatible with any hidden (microscopic) observable. It is shown that within this approach quantum causality can be rehabilitated within an extended quantum mechanics (eventum mechanics) in the form of a superselection rule for compatibility of the consistent hi...
Causal structure and electrodynamics on Finsler spacetimes
Pfeifer, Christian; Wohlfarth, Mattias N. R.
2011-08-01
We present a concise new definition of Finsler spacetimes that generalizes Lorentzian metric manifolds and provides consistent backgrounds for physics. Extending standard mathematical constructions known from Finsler spaces, we show that geometric objects like the Cartan nonlinear connection and its curvature are well defined almost everywhere on Finsler spacetimes, including their null structure. This allows us to describe the complete causal structure in terms of timelike and null curves; these are essential to model physical observers and the propagation of light. We prove that the timelike directions form an open convex cone with a null boundary, as is the case in Lorentzian geometry. Moreover, we develop action integrals for physical field theories on Finsler spacetimes, and tools to deduce the corresponding equations of motion. These are applied to construct a theory of electrodynamics that confirms the claimed propagation of light along Finsler null geodesics.
Causal structure and electrodynamics on Finsler spacetimes
Pfeifer, Christian
2011-01-01
We present a concise new definition of Finsler spacetimes that generalize Lorentzian metric manifolds and provide consistent backgrounds for physics. Extending standard mathematical constructions known from Finsler spaces we show that geometric objects like the Cartan non-linear connection and its curvature are well-defined almost everywhere on Finsler spacetimes, also on their null structure. This allows us to describe the complete causal structure in terms of timelike and null curves; these are essential to model physical observers and the propagation of light. We prove that the timelike directions form an open convex cone with null boundary as is the case in Lorentzian geometry. Moreover, we develop action integrals for physical field theories on Finsler spacetimes, and tools to deduce the corresponding equations of motion. These are applied to construct a theory of electrodynamics that confirms the claimed propagation of light along Finsler null geodesics.
Fabry's disease and psychosis: causality or coincidence?
Gairing, S; Wiest, R; Metzler, S; Theodoridou, A; Hoff, P
2011-01-01
A 21-year-old female with Fabry's disease (FD) presented acute psychotic symptoms such as delusions, auditory hallucinations and formal thought disorders. Since the age of 14, she had suffered from various psychiatric symptoms increasing in frequency and intensity. We considered the differential diagnoses of prodromal symptoms of schizophrenia and organic schizophrenia-like disorder. Routine examinations including cognitive testing, electroencephalography and structural magnetic resonance imaging revealed no pathological findings. Additional structural and functional imaging demonstrated a minor CNS involvement of FD, yet without functional limitations. In summary our examination results support the thesis that in the case of our patient a mere coincidence of FD and psychotic symptoms is more likely than a causal connection.
Wiretap Channel with Causal State Information
Chia, Yeow-Khiang
2010-01-01
A lower bound on the secrecy capacity of the wiretap channel with state information available causally at both the encoder and decoder is established. The lower bound is shown to be strictly larger than that for the noncausal case by Liu and Chen. Achievability is proved using block Markov coding, Shannon strategy, and key generation from common state information. The state sequence available at the end of each block is used to generate a key, which is used to enhance the transmission rate of the confidential message in the following block. An upper bound on the secrecy capacity when the state is available noncausally at the encoder and decoder is established and is shown to coincide with the lower bound for several classes of wiretap channels with state.
Equity Theory Ratios as Causal Schemas
Directory of Open Access Journals (Sweden)
Alexios Arvanitis
2016-08-01
Full Text Available Equity theory approaches justice evaluations based on ratios of exchange inputs to exchange outcomes. Situations are evaluated as just if ratios are equal and unjust if unequal. We suggest that equity ratios serve a more fundamental cognitive function than the evaluation of justice. More particularly, we propose that they serve as causal schemas for exchange outcomes, that is, they assist in determining whether certain outcomes are caused by inputs of other people in the context of an exchange process. Equality or inequality of ratios in this sense points to an exchange process. Indeed, Study 1 shows that different exchange situations, such as disproportional or balanced proportional situations, create perceptions of give-and-take on the basis of equity ratios. Study 2 shows that perceptions of justice are based more on communicatively accepted rules of interaction than equity-based evaluations, thereby offering a distinction between an attribution and an evaluation cognitive process for exchange outcomes.
Flux Analysis in Process Models via Causality
Kahramanoğullari, Ozan
2010-01-01
We present an approach for flux analysis in process algebra models of biological systems. We perceive flux as the flow of resources in stochastic simulations. We resort to an established correspondence between event structures, a broadly recognised model of concurrency, and state transitions of process models, seen as Petri nets. We show that we can this way extract the causal resource dependencies in simulations between individual state transitions as partial orders of events. We propose transformations on the partial orders that provide means for further analysis, and introduce a software tool, which implements these ideas. By means of an example of a published model of the Rho GTP-binding proteins, we argue that this approach can provide the substitute for flux analysis techniques on ordinary differential equation models within the stochastic setting of process algebras.
Causality Constraints in Conformal Field Theory
CERN. Geneva
2015-01-01
Causality places nontrivial constraints on QFT in Lorentzian signature, for example fixing the signs of certain terms in the low energy Lagrangian. In d-dimensional conformal field theory, we show how such constraints are encoded in crossing symmetry of Euclidean correlators, and derive analogous constraints directly from the conformal bootstrap (analytically). The bootstrap setup is a Lorentzian four-point function corresponding to propagation through a shockwave. Crossing symmetry fixes the signs of certain log terms that appear in the conformal block expansion, which constrains the interactions of low-lying operators. As an application, we use the bootstrap to rederive the well known sign constraint on the (∂φ)4 coupling in effective field theory, from a dual CFT. We also find constraints on theories with higher spin conserved currents. Our analysis is restricted to scalar correlators, but we argue that similar methods should also impose nontrivial constraints on the interactions of spinni...
Causality Constraints in Conformal Field Theory
Hartman, Thomas; Kundu, Sandipan
2015-01-01
Causality places nontrivial constraints on QFT in Lorentzian signature, for example fixing the signs of certain terms in the low energy Lagrangian. In d-dimensional conformal field theory, we show how such constraints are encoded in crossing symmetry of Euclidean correlators, and derive analogous constraints directly from the conformal bootstrap (analytically). The bootstrap setup is a Lorentzian four-point function corresponding to propagation through a shockwave. Crossing symmetry fixes the signs of certain log terms that appear in the conformal block expansion, which constrains the interactions of low-lying operators. As an application, we use the bootstrap to rederive the well known sign constraint on the $(\\partial\\phi)^4$ coupling in effective field theory, from a dual CFT. We also find constraints on theories with higher spin conserved currents. Our analysis is restricted to scalar correlators, but we argue that similar methods should also impose nontrivial constraints on the interactions of spinning o...
Exploring Torus Universes in Causal Dynamical Triangulations
DEFF Research Database (Denmark)
Budd, Timothy George; Loll, R.
2013-01-01
Motivated by the search for new observables in nonperturbative quantum gravity, we consider Causal Dynamical Triangulations (CDT) in 2+1 dimensions with the spatial topology of a torus. This system is of particular interest, because one can study not only the global scale factor, but also global...... shape variables in the presence of arbitrary quantum fluctuations of the geometry. Our initial investigation focusses on the dynamics of the scale factor and uncovers a qualitatively new behaviour, which leads us to investigate a novel type of boundary conditions for the path integral. Comparing large......-scale features of the emergent quantum geometry in numerical simulations with a classical minisuperspace formulation, we find partial agreement. By measuring the correlation matrix of volume fluctuations we succeed in reconstructing the effective action for the scale factor directly from the simulation data...
Exploring Torus Universes in Causal Dynamical Triangulations
Budd, T G
2013-01-01
Motivated by the search for new observables in nonperturbative quantum gravity, we consider Causal Dynamical Triangulations (CDT) in 2+1 dimensions with the spatial topology of a torus. This system is of particular interest, because one can study not only the global scale factor, but also global shape variables in the presence of arbitrary quantum fluctuations of the geometry. Our initial investigation focusses on the dynamics of the scale factor and uncovers a qualitatively new behaviour, which leads us to investigate a novel type of boundary conditions for the path integral. Comparing large-scale features of the emergent quantum geometry in numerical simulations with a classical minisuperspace formulation, we find partial agreement. By measuring the correlation matrix of volume fluctuations we succeed in reconstructing the effective action for the scale factor directly from the simulation data. Apart from setting the stage for the analysis of shape dynamics on the torus, the new set-up highlights the role o...
World oil and agricultural commodity prices: Evidence from nonlinear causality
Energy Technology Data Exchange (ETDEWEB)
Nazlioglu, Saban, E-mail: snazlioglu@pau.edu.t [Department of Econometrics, Pamukkale University, Denizli (Turkey)
2011-05-15
The increasing co-movements between the world oil and agricultural commodity prices have renewed interest in determining price transmission from oil prices to those of agricultural commodities. This study extends the literature on the oil-agricultural commodity prices nexus, which particularly concentrates on nonlinear causal relationships between the world oil and three key agricultural commodity prices (corn, soybeans, and wheat). To this end, the linear causality approach of Toda-Yamamoto and the nonparametric causality method of Diks-Panchenko are applied to the weekly data spanning from 1994 to 2010. The linear causality analysis indicates that the oil prices and the agricultural commodity prices do not influence each other, which supports evidence on the neutrality hypothesis. In contrast, the nonlinear causality analysis shows that: (i) there are nonlinear feedbacks between the oil and the agricultural prices, and (ii) there is a persistent unidirectional nonlinear causality running from the oil prices to the corn and to the soybeans prices. The findings from the nonlinear causality analysis therefore provide clues for better understanding the recent dynamics of the agricultural commodity prices and some policy implications for policy makers, farmers, and global investors. This study also suggests the directions for future studies. - Research highlights: {yields} This study determines the price transmission mechanisms between the world oil and three key agricultural commodity prices (corn, soybeans, and wheat). {yields} The linear and nonlinear cointegration and causality methods are carried out. {yields} The linear causality analysis supports evidence on the neutrality hypothesis. {yields} The nonlinear causality analysis shows that there is a persistent unidirectional causality from the oil prices to the corn and to the soybeans prices.
Assessing thalamocortical functional connectivity with Granger causality.
Chen, Cheng; Maybhate, Anil; Israel, David; Thakor, Nitish V; Jia, Xiaofeng
2013-09-01
Assessment of network connectivity across multiple brain regions is critical to understanding the mechanisms underlying various neurological disorders. Conventional methods for assessing dynamic interactions include cross-correlation and coherence analysis. However, these methods do not reveal the direction of information flow, which is important for studying the highly directional neurological system. Granger causality (GC) analysis can characterize the directional influences between two systems. We tested GC analysis for its capability to capture directional interactions within both simulated and in vivo neural networks. The simulated networks consisted of Hindmarsh-Rose neurons; GC analysis was used to estimate the causal influences between two model networks. Our analysis successfully detected asymmetrical interactions between these networks ( , t -test). Next, we characterized the relationship between the "electrical synaptic strength" in the model networks and interactions estimated by GC analysis. We demonstrated the novel application of GC to monitor interactions between thalamic and cortical neurons following ischemia induced brain injury in a rat model of cardiac arrest (CA). We observed that during the post-CA acute period the GC interactions from the thalamus to the cortex were consistently higher than those from the cortex to the thalamus ( 1.983±0.278 times higher, p = 0.021). In addition, the dynamics of GC interactions between the thalamus and the cortex were frequency dependent. Our study demonstrated the feasibility of GC to monitor the dynamics of thalamocortical interactions after a global nervous system injury such as CA-induced ischemia, and offers preferred alternative applications in characterizing other inter-regional interactions in an injured brain.
[Antibibiotic resistance by nosocomial infections' causal agents].
Salazar-Holguín, Héctor Daniel; Cisneros-Robledo, María Elena
2016-01-01
Introducción: la resistencia a antimicrobianos por agentes causales de infección nosocomial (IN) constituye un grave problemática global que involucra al HGR 1 del IMSS en Chihuahua, México; si bien con particularidades que requirieron especificarla y evaluarla, a fin de concretar una terapéutica eficaz. Métodos: estudio observacional, descriptivo y prospectivo; se llevó a cabo mediante vigilancia activa durante 2014 para la detección de infecciones nosocomiales, su estudio epidemiológico, cultivo y antibiograma para identificar al agente causal y su resistencia a los antibióticos. Resultados: de 13527 egresos hospitalarios, 1079 presentaron IN (8 por 100 egresos) y de ellas destacaron: de líneas vasculares, quirúrgicas, neumonía y de vías urinarias; sumando dos tercios del total. Se realizó cultivo y antibiograma en 300 de ellas (27.8 %); identificando 31 especies bacterianas, siendo siete las principales (77.9 %): Escherichia coli, Staphylococcus aureus y epidermidis, Pseudomonas aeruginosa, Acinetobacter baumannii, Klebsiella pneumoniae y Enterobacter cloacae; mostrando multirresistencia a 34 antibióticos probados, excepto en siete con baja o nula resistencia: vancomicina, teicoplanina, linezolid, quinupristina-dalfopristina, piperacilina–tazobactam, amikacina y carbapenémicos. Conclusiones: al contrastar tales resultados ante las recomendaciones de las guías de práctica clínica, surgieron contradicciones; por lo que deben tomarse con reserva y ser probadas en cada hospital, mediante cultivos y antibiogramas en prácticamente todos los casos de infección nosocomial.
Toxicological evaluation of chemical mixtures
Feron, V.J.; Groten, J.P.
2002-01-01
This paper addresses major developments in the safety evaluation of chemical mixtures during the past 15 years, reviews today's state of the art of mixture toxicology, and discusses challenges ahead. Well-thought-out tailor-made mechanistic and empirical designs for studying the toxicity of mixtures
Mixtures of truncated basis functions
DEFF Research Database (Denmark)
Langseth, Helge; Nielsen, Thomas Dyhre; Rumí, Rafael
2012-01-01
In this paper we propose a framework, called mixtures of truncated basis functions (MoTBFs), for representing general hybrid Bayesian networks. The proposed framework generalizes both the mixture of truncated exponentials (MTEs) framework and the mixture of polynomials (MoPs) framework. Similar...
Separating Underdetermined Convolutive Speech Mixtures
DEFF Research Database (Denmark)
Pedersen, Michael Syskind; Wang, DeLiang; Larsen, Jan
2006-01-01
a method for underdetermined blind source separation of convolutive mixtures. The proposed framework is applicable for separation of instantaneous as well as convolutive speech mixtures. It is possible to iteratively extract each speech signal from the mixture by combining blind source separation...
Yu, Wen; Chen, Kani; Sobel, Michael E; Ying, Zhiliang
2015-03-01
We consider causal inference in randomized survival studies with right censored outcomes and all-or-nothing compliance, using semiparametric transformation models to estimate the distribution of survival times in treatment and control groups, conditional on covariates and latent compliance type. Estimands depending on these distributions, for example, the complier average causal effect (CACE), the complier effect on survival beyond time t, and the complier quantile effect are then considered. Maximum likelihood is used to estimate the parameters of the transformation models, using a specially designed expectation-maximization (EM) algorithm to overcome the computational difficulties created by the mixture structure of the problem and the infinite dimensional parameter in the transformation models. The estimators are shown to be consistent, asymptotically normal, and semiparametrically efficient. Inferential procedures for the causal parameters are developed. A simulation study is conducted to evaluate the finite sample performance of the estimated causal parameters. We also apply our methodology to a randomized study conducted by the Health Insurance Plan of Greater New York to assess the reduction in breast cancer mortality due to screening.
Cause and Event: Supporting Causal Claims through Logistic Models
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…