Component effects in mixture experiments
International Nuclear Information System (INIS)
Piepel, G.F.
1980-01-01
In a mixture experiment, the response to a mixture of q components is a function of the proportions x 1 , x 2 , ..., x/sub q/ of components in the mixture. Experimental regions for mixture experiments are often defined by constraints on the proportions of the components forming the mixture. The usual (orthogonal direction) definition of a factor effect does not apply because of the dependence imposed by the mixture restriction, /sup q/Σ/sub i=1/ x/sub i/ = 1. A direction within the experimental region in which to compute a mixture component effect is presented and compared to previously suggested directions. This new direction has none of the inadequacies or errors of previous suggestions while having a more meaningful interpretation. The distinction between partial and total effects is made. The uses of partial and total effects (computed using the new direction) in modification and interpretation of mixture response prediction equations are considered. The suggestions of the paper are illustrated in an example from a glass development study in a waste vitrification program. 5 figures, 3 tables
Iterative Mixture Component Pruning Algorithm for Gaussian Mixture PHD Filter
Directory of Open Access Journals (Sweden)
Xiaoxi Yan
2014-01-01
Full Text Available As far as the increasing number of mixture components in the Gaussian mixture PHD filter is concerned, an iterative mixture component pruning algorithm is proposed. The pruning algorithm is based on maximizing the posterior probability density of the mixture weights. The entropy distribution of the mixture weights is adopted as the prior distribution of mixture component parameters. The iterative update formulations of the mixture weights are derived by Lagrange multiplier and Lambert W function. Mixture components, whose weights become negative during iterative procedure, are pruned by setting corresponding mixture weights to zeros. In addition, multiple mixture components with similar parameters describing the same PHD peak can be merged into one mixture component in the algorithm. Simulation results show that the proposed iterative mixture component pruning algorithm is superior to the typical pruning algorithm based on thresholds.
Pearl, Judea
2000-03-01
Written by one of the pre-eminent researchers in the field, this book provides a comprehensive exposition of modern analysis of causation. It shows how causality has grown from a nebulous concept into a mathematical theory with significant applications in the fields of statistics, artificial intelligence, philosophy, cognitive science, and the health and social sciences. Pearl presents a unified account of the probabilistic, manipulative, counterfactual and structural approaches to causation, and devises simple mathematical tools for analyzing the relationships between causal connections, statistical associations, actions and observations. The book will open the way for including causal analysis in the standard curriculum of statistics, artifical intelligence, business, epidemiology, social science and economics. Students in these areas will find natural models, simple identification procedures, and precise mathematical definitions of causal concepts that traditional texts have tended to evade or make unduly complicated. This book will be of interest to professionals and students in a wide variety of fields. Anyone who wishes to elucidate meaningful relationships from data, predict effects of actions and policies, assess explanations of reported events, or form theories of causal understanding and causal speech will find this book stimulating and invaluable.
The separation of solid and liquid components of mixtures
International Nuclear Information System (INIS)
Hunter, W.M.
1980-01-01
An improved method of separating solid and liquid components of mixtures is described which is particularly suited for use in automated radioimmunoassay systems in the analysis of bound and free fractions. A second liquid, having a density intermediate between those of the solid and liquid components, is delivered to the solid/ liquid mixture to form a discrete layer below the mixture and the solid separates into this lower liquid layer assisted by centrifugal force. The second liquid of intermediate density is an aqueous solution of a highly hydrophilic and electrically non-polar solute, such as an aqueous sucrose solution. Further liquids of intermediate density and progressively higher density may be delivered to form further discrete layers below the initial layer of the second dense liquid. After separation of the solid and liquid components of the mixture, the supernatant liquid component of the original mixture is removed in a controlled and non-turbulent manner. The method is illustrated in radioimmunoassays for platelet β-thromboglobulin and human follicle stimulating hormone. (U.K.)
Analysis of Minor Component Segregation in Ternary Powder Mixtures
Directory of Open Access Journals (Sweden)
Asachi Maryam
2017-01-01
Full Text Available In many powder handling operations, inhomogeneity in powder mixtures caused by segregation could have significant adverse impact on the quality as well as economics of the production. Segregation of a minor component of a highly active substance could have serious deleterious effects, an example is the segregation of enzyme granules in detergent powders. In this study, the effects of particle properties and bulk cohesion on the segregation tendency of minor component are analysed. The minor component is made sticky while not adversely affecting the flowability of samples. The segregation extent is evaluated using image processing of the photographic records taken from the front face of the heap after the pouring process. The optimum average sieve cut size of components for which segregation could be reduced is reported. It is also shown that the extent of segregation is significantly reduced by applying a thin layer of liquid to the surfaces of minor component, promoting an ordered mixture.
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
International Nuclear Information System (INIS)
Piepel, Gregory F.; Cooley, Scott K.; Jones, Bradley
2004-01-01
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 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
Bonding and structure in dense multi-component molecular mixtures.
Meyer, Edmund R; Ticknor, Christopher; Bethkenhagen, Mandy; Hamel, Sebastien; Redmer, Ronald; Kress, Joel D; Collins, Lee A
2015-10-28
We have performed finite-temperature density functional theory molecular dynamics simulations on dense methane, ammonia, and water mixtures (CH4:NH3:H2O) for various compositions and temperatures (2000 K ≤ T ≤ 10,000 K) that span a set of possible conditions in the interiors of ice-giant exoplanets. The equation-of-state, pair distribution functions, and bond autocorrelation functions (BACF) were used to probe the structure and dynamics of these complex fluids. In particular, an improvement to the choice of the cutoff in the BACF was developed that allowed analysis refinements for density and temperature effects. We note the relative changes in the nature of these systems engendered by variations in the concentration ratios. A basic tenet emerges from all these comparisons that varying the relative amounts of the three heavy components (C,N,O) can effect considerable changes in the nature of the fluid and may in turn have ramifications for the structure and composition of various planetary layers.
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.
Two-component mixture cure rate model with spline estimated nonparametric components.
Wang, Lu; Du, Pang; Liang, Hua
2012-09-01
In some survival analysis of medical studies, there are often long-term survivors who can be considered as permanently cured. The goals in these studies are to estimate the noncured probability of the whole population and the hazard rate of the susceptible subpopulation. When covariates are present as often happens in practice, to understand covariate effects on the noncured probability and hazard rate is of equal importance. The existing methods are limited to parametric and semiparametric models. We propose a two-component mixture cure rate model with nonparametric forms for both the cure probability and the hazard rate function. Identifiability of the model is guaranteed by an additive assumption that allows no time-covariate interactions in the logarithm of hazard rate. Estimation is carried out by an expectation-maximization algorithm on maximizing a penalized likelihood. For inferential purpose, we apply the Louis formula to obtain point-wise confidence intervals for noncured probability and hazard rate. Asymptotic convergence rates of our function estimates are established. We then evaluate the proposed method by extensive simulations. We analyze the survival data from a melanoma study and find interesting patterns for this study. © 2011, The International Biometric Society.
Modelling the effect of mixture components on permeation through skin.
Ghafourian, T; Samaras, E G; Brooks, J D; Riviere, J E
2010-10-15
A vehicle influences the concentration of penetrant within the membrane, affecting its diffusivity in the skin and rate of transport. Despite the huge amount of effort made for the understanding and modelling of the skin absorption of chemicals, a reliable estimation of the skin penetration potential from formulations remains a challenging objective. In this investigation, quantitative structure-activity relationship (QSAR) was employed to relate the skin permeation of compounds to the chemical properties of the mixture ingredients and the molecular structures of the penetrants. The skin permeability dataset consisted of permeability coefficients of 12 different penetrants each blended in 24 different solvent mixtures measured from finite-dose diffusion cell studies using porcine skin. Stepwise regression analysis resulted in a QSAR employing two penetrant descriptors and one solvent property. The penetrant descriptors were octanol/water partition coefficient, logP and the ninth order path molecular connectivity index, and the solvent property was the difference between boiling and melting points. The negative relationship between skin permeability coefficient and logP was attributed to the fact that most of the drugs in this particular dataset are extremely lipophilic in comparison with the compounds in the common skin permeability datasets used in QSAR. The findings show that compounds formulated in vehicles with small boiling and melting point gaps will be expected to have higher permeation through skin. The QSAR was validated internally, using a leave-many-out procedure, giving a mean absolute error of 0.396. The chemical space of the dataset was compared with that of the known skin permeability datasets and gaps were identified for future skin permeability measurements. Copyright 2010 Elsevier B.V. All rights reserved.
Effect of the addition of mixture of plant components on the mechanical properties of wheat bread
Wójcik, Monika; Dziki, Dariusz; Biernacka, Beata; Różyło, Renata; Miś, Antoni; Hassoon, Waleed H.
2017-10-01
Instrumental methods of measuring the mechanical properties of bread can be used to determine changes in the properties of it during storage, as well as to determine the effect of various additives on the bread texture. The aim of this study was to investigate the effect of the mixture of plant components on the physical properties of wheat bread. In particular, the mechanical properties of the crumb and crust were studied. A sensory evaluation of the end product was also performed. The mixture of plant components included: carob fiber, milled grain red quinoa and black oat (1:2:2) - added at 0, 5, 10, 15, 20, 25 % - into wheat flour. The results showed that the increase of the addition of the proposed additive significantly increased the water absorption of flour mixtures. Moreover, the use of the mixture of plant components above 5% resulted in the increase of bread volume and decrease of crumb density. Furthermore, the addition of the mixture of plant components significantly affected the mechanical properties of bread crumb. The hardness of crumb also decreased as a result of the mixture of plant components addition. The highest cohesiveness was obtained for bread with 10% of additive and the lowest for bread with 25% of mixture of plant components. Most importantly, the enrichment of wheat flour with the mixture of plant components significantly reduced the crust failure force and crust failure work. The results of sensory evaluation showed that the addition of the mixture of plant components of up to 10% had little effect on bread quality.
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....
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 m...
XeCl Excimer Laser with Three- and Four-Component Mixture of Active Gases
International Nuclear Information System (INIS)
Iwanejko, L.; Pokora, L.
1998-01-01
Selected results of investigations of a XeCl excimer laser employing a new type (four-component)of mixture of gases, He-Kr:Xe-HCl, are presented. The mixture includes, instead of Xe, a mixture of not-separated Kr and Xe gases, much less expensive than pure xenon. A comparison of durations and energies of pulses generated in the XeCl excimer laser using three- or four-component gaseous active medium (He-Xe-HCl or He-Kr:Xe-HCl) is made. The investigations have been carried out with the use of a laser system with UV preionization and self sustained pumping discharge. (author)
Uniform phases in fluids of hard isosceles triangles: One-component fluid and binary mixtures
Martínez-Ratón, Yuri; Díaz-De Armas, Ariel; Velasco, Enrique
2018-05-01
We formulate the scaled particle theory for a general mixture of hard isosceles triangles and calculate different phase diagrams for the one-component fluid and for certain binary mixtures. The fluid of hard triangles exhibits a complex phase behavior: (i) the presence of a triatic phase with sixfold symmetry, (ii) the isotropic-uniaxial nematic transition is of first order for certain ranges of aspect ratios, and (iii) the one-component system exhibits nematic-nematic transitions ending in critical points. We found the triatic phase to be stable not only for equilateral triangles but also for triangles of similar aspect ratios. We focus the study of binary mixtures on the case of symmetric mixtures: equal particle areas with aspect ratios (κi) symmetric with respect to the equilateral one, κ1κ2=3 . For these mixtures we found, aside from first-order isotropic-nematic and nematic-nematic transitions (the latter ending in a critical point): (i) a region of triatic phase stability even for mixtures made of particles that do not form this phase at the one-component limit, and (ii) the presence of a Landau point at which two triatic-nematic first-order transitions and a nematic-nematic demixing transition coalesce. This phase behavior is analogous to that of a symmetric three-dimensional mixture of rods and plates.
International Nuclear Information System (INIS)
Piepel, Gregory F.; Cooley, Scott K.; Jones, Bradley
2005-01-01
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.)
A further component analysis for illicit drugs mixtures with THz-TDS
Xiong, Wei; Shen, Jingling; He, Ting; Pan, Rui
2009-07-01
A new method for quantitative analysis of mixtures of illicit drugs with THz time domain spectroscopy was proposed and verified experimentally. In traditional method we need fingerprints of all the pure chemical components. In practical as only the objective components in a mixture and their absorption features are known, it is necessary and important to present a more practical technique for the detection and identification. Our new method of quantitatively inspect of the mixtures of illicit drugs is developed by using derivative spectrum. In this method, the ratio of objective components in a mixture can be obtained on the assumption that all objective components in the mixture and their absorption features are known but the unknown components are not needed. Then methamphetamine and flour, a illicit drug and a common adulterant, were selected for our experiment. The experimental result verified the effectiveness of the method, which suggested that it could be an effective method for quantitative identification of illicit drugs. This THz spectroscopy technique is great significant in the real-world applications of illicit drugs quantitative analysis. It could be an effective method in the field of security and pharmaceuticals inspection.
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.
Mixture estimation with state-space components and Markov model of switching
Czech Academy of Sciences Publication Activity Database
Nagy, Ivan; Suzdaleva, Evgenia
2013-01-01
Roč. 37, č. 24 (2013), s. 9970-9984 ISSN 0307-904X R&D Projects: GA TA ČR TA01030123 Institutional support: RVO:67985556 Keywords : probabilistic dynamic mixtures, * probability density function * state-space models * recursive mixture estimation * Bayesian dynamic decision making under uncertainty * Kerridge inaccuracy Subject RIV: BC - Control Systems Theory Impact factor: 2.158, year: 2013 http://library.utia.cas.cz/separaty/2013/AS/nagy-mixture estimation with state-space components and markov model of switching.pdf
Measuring two-phase and two-component mixtures by radiometric technique
International Nuclear Information System (INIS)
Mackuliak, D.; Rajniak, I.
1984-01-01
The possibility was tried of the application of the radiometric method in measuring steam water content. The experiments were carried out in model conditions where steam was replaced with the two-component mixture of water and air. The beta radiation source was isotope 204 Tl (Esub(max)=0.765 MeV) with an activity of 19.35 MBq. Measurements were carried out within the range of the surface density of the mixture from 0.119 kg.m -2 to 0.130 kg.m -2 . Mixture speed was 5.1 m.s -1 to 7.1 m.s -1 . The observed dependence of relative pulse frequency on the specific water content in the mixture was approximated by a linear regression. (B.S.)
Nagy, Ivan
2017-01-01
This book provides a general theoretical background for constructing the recursive Bayesian estimation algorithms for mixture models. It collects the recursive algorithms for estimating dynamic mixtures of various distributions and brings them in the unified form, providing a scheme for constructing the estimation algorithm for a mixture of components modeled by distributions with reproducible statistics. It offers the recursive estimation of dynamic mixtures, which are free of iterative processes and close to analytical solutions as much as possible. In addition, these methods can be used online and simultaneously perform learning, which improves their efficiency during estimation. The book includes detailed program codes for solving the presented theoretical tasks. Codes are implemented in the open source platform for engineering computations. The program codes given serve to illustrate the theory and demonstrate the work of the included algorithms.
Rafiee Fanood, M.M.; Ram, N.B.; Lehmann, C.S.; Powis, I.; Janssen, M.H.M.
2015-01-01
Simultaneous, enantiomer-specific identification of chiral molecules in multi-component mixtures is extremely challenging. Many established techniques for single-component analysis fail to provide selectivity in multi-component mixtures and lack sensitivity for dilute samples. Here we show how
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.
Baldwin, Austin S; Rothman, Alexander J; Vander Weg, Mark W; Christensen, Alan J
2013-12-01
Self-persuasion-generating one's own arguments for engaging in a specific behavior-can be an effective strategy to promote health behavior change, yet the causal processes that explain why it is effective are not well-specified. We sought to elucidate specific causal components and a mediating process of self-persuasion in two health behavior domains: physical activity and smoking. In two experiments, participants were randomized to write or read arguments about regular exercise (Study 1: N = 76; college students) or smoking cessation (Study 2: N = 107; daily smokers). In Study 2, we also manipulated the argument content (matched vs. mismatched participants' own concerns about smoking) to isolate its effect from the effect of argument source (self vs. other). Study outcomes included participants' reports of argument ratings, attitudes, behavioral intentions (Studies 1 & 2), and cessation attempts at 1 month (Study 2). In Study 1, self-generated arguments about exercise were evaluated more positively than other arguments (p = .01, d = .63), and this biased processing mediated the self-generated argument effect on attitudes toward exercise (β = .08, 95% CI = .01, .18). In Study 2, the findings suggested that biased processing occurs because self-generated argument content matches people's own health concerns and not because of the argument source (self vs. other). In addition, self-generated arguments indirectly led to greater behavior change intentions (Studies 1 & 2) and a greater likelihood of a smoking cessation attempt (Study 2). The findings elucidate a causal component and a mediating process that explain why self-persuasion and related behavior change interventions, such as motivational interviewing, are effective. Findings also suggest that self-generated arguments may be an efficient way to deliver message interventions aimed at changing health behaviors.
Bayesian estimation of mixtures with dynamic transitions and known component parameters
Czech Academy of Sciences Publication Activity Database
Nagy, I.; Suzdaleva, Evgenia; Kárný, Miroslav
2011-01-01
Roč. 47, č. 4 (2011), s. 572-594 ISSN 0023-5954 R&D Projects: GA MŠk 1M0572; GA TA ČR TA01030123; GA ČR GA102/08/0567 Grant - others:Skoda Auto(CZ) ENS/2009/UTIA Institutional research plan: CEZ:AV0Z10750506 Keywords : mixture model * Bayesian estimation * approximation * clustering * classification Subject RIV: BC - Control Systems Theory Impact factor: 0.454, year: 2011 http://library.utia.cas.cz/separaty/2011/AS/nagy-bayesian estimation of mixtures with dynamic transitions and known component parameters.pdf
International Nuclear Information System (INIS)
Stehlik, M.; Ososkov, G.A.
2003-01-01
The statistical problem to expand the experimental distribution of transverse momenta into Rayleigh distribution is considered. A high-efficient testing procedure for testing the hypothesis of the homogeneity of the observed measurements which is optimal in the sense of Bahadur is constructed. The exact likelihood ratio (LR) test of the scale parameter of the Rayleigh distribution is proposed for cases when the hypothesis of homogeneity holds. Otherwise the efficient procedure for testing the number of components in the mixture is also proposed
Radiation-energy partition among mixture components: current ideas on an old question
International Nuclear Information System (INIS)
Swallow, A.J.
1988-01-01
We review the basis of the familiar idea that the energy partition among mixture components in the initial stage would be governed by the total electron fraction. For considerations of many problems in radiation chemistry, it is better to use the valence-electron fraction. We also point out recent developments in more detailed treatments, which indicate limitations of the very concept of the energy partition for the determination of the yields of initial molecular species that appear under irradiation. (author)
[Study of Determination of Oil Mixture Components Content Based on Quasi-Monte Carlo Method].
Wang, Yu-tian; Xu, Jing; Liu, Xiao-fei; Chen, Meng-han; Wang, Shi-tao
2015-05-01
Gasoline, kerosene, diesel is processed by crude oil with different distillation range. The boiling range of gasoline is 35 ~205 °C. The boiling range of kerosene is 140~250 °C. And the boiling range of diesel is 180~370 °C. At the same time, the carbon chain length of differentmineral oil is different. The carbon chain-length of gasoline is within the scope of C7 to C11. The carbon chain length of kerosene is within the scope of C12 to C15. And the carbon chain length of diesel is within the scope of C15 to C18. The recognition and quantitative measurement of three kinds of mineral oil is based on different fluorescence spectrum formed in their different carbon number distribution characteristics. Mineral oil pollution occurs frequently, so monitoring mineral oil content in the ocean is very important. A new method of components content determination of spectra overlapping mineral oil mixture is proposed, with calculation of characteristic peak power integrationof three-dimensional fluorescence spectrum by using Quasi-Monte Carlo Method, combined with optimal algorithm solving optimum number of characteristic peak and range of integral region, solving nonlinear equations by using BFGS(a rank to two update method named after its inventor surname first letter, Boyden, Fletcher, Goldfarb and Shanno) method. Peak power accumulation of determined points in selected area is sensitive to small changes of fluorescence spectral line, so the measurement of small changes of component content is sensitive. At the same time, compared with the single point measurement, measurement sensitivity is improved by the decrease influence of random error due to the selection of points. Three-dimensional fluorescence spectra and fluorescence contour spectra of single mineral oil and the mixture are measured by taking kerosene, diesel and gasoline as research objects, with a single mineral oil regarded whole, not considered each mineral oil components. Six characteristic peaks are
Efficient and robust relaxation procedures for multi-component mixtures including phase transition
International Nuclear Information System (INIS)
Han, Ee; Hantke, Maren; Müller, Siegfried
2017-01-01
We consider a thermodynamic consistent multi-component model in multi-dimensions that is a generalization of the classical two-phase flow model of Baer and Nunziato. The exchange of mass, momentum and energy between the phases is described by additional source terms. Typically these terms are handled by relaxation procedures. Available relaxation procedures suffer from efficiency and robustness resulting in very costly computations that in general only allow for one-dimensional computations. Therefore we focus on the development of new efficient and robust numerical methods for relaxation processes. We derive exact procedures to determine mechanical and thermal equilibrium states. Further we introduce a novel iterative method to treat the mass transfer for a three component mixture. All new procedures can be extended to an arbitrary number of inert ideal gases. We prove existence, uniqueness and physical admissibility of the resulting states and convergence of our new procedures. Efficiency and robustness of the procedures are verified by means of numerical computations in one and two space dimensions. - Highlights: • We develop novel relaxation procedures for a generalized, thermodynamically consistent Baer–Nunziato type model. • Exact procedures for mechanical and thermal relaxation procedures avoid artificial parameters. • Existence, uniqueness and physical admissibility of the equilibrium states are proven for special mixtures. • A novel iterative method for mass transfer is introduced for a three component mixture providing a unique and admissible equilibrium state.
Mixture modeling of multi-component data sets with application to ion-probe zircon ages
Sambridge, M. S.; Compston, W.
1994-12-01
A method is presented for detecting multiple components in a population of analytical observations for zircon and other ages. The procedure uses an approach known as mixture modeling, in order to estimate the most likely ages, proportions and number of distinct components in a given data set. Particular attention is paid to estimating errors in the estimated ages and proportions. At each stage of the procedure several alternative numerical approaches are suggested, each having their own advantages in terms of efficency and accuracy. The methodology is tested on synthetic data sets simulating two or more mixed populations of zircon ages. In this case true ages and proportions of each population are known and compare well with the results of the new procedure. Two examples are presented of its use with sets of SHRIMP U-238 - Pb-206 zircon ages from Palaeozoic rocks. A published data set for altered zircons from bentonite at Meishucun, South China, previously treated as a single-component population after screening for gross alteration effects, can be resolved into two components by the new procedure and their ages, proportions and standard errors estimated. The older component, at 530 +/- 5 Ma (2 sigma), is our best current estimate for the age of the bentonite. Mixture modeling of a data set for unaltered zircons from a tonalite elsewhere defines the magmatic U-238 - Pb-206 age at high precision (2 sigma +/- 1.5 Ma), but one-quarter of the 41 analyses detect hidden and significantly older cores.
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.
Coors, Anja; Vollmar, Pia; Heim, Jennifer; Sacher, Frank; Kehrer, Anja
2018-01-01
Biocidal products are mixtures of one or more active substances (a.s.) and a broad range of formulation additives. There is regulatory guidance currently under development that will specify how the combined effects of the a.s. and any relevant formulation additives shall be considered in the environmental risk assessment of biocidal products. The default option is a component-based approach (CBA) by which the toxicity of the product is predicted from the toxicity of 'relevant' components using concentration addition. Hence, unequivocal and practicable criteria are required for identifying the 'relevant' components to ensure protectiveness of the CBA, while avoiding unnecessary workload resulting from including by default components that do not significantly contribute to the product toxicity. The present study evaluated a set of different criteria for identifying 'relevant' components using confidential information on the composition of 21 wood preservative products. Theoretical approaches were complemented by experimentally testing the aquatic toxicity of seven selected products. For three of the seven tested products, the toxicity was underestimated for the most sensitive endpoint (green algae) by more than factor 2 if only the a.s. were considered in the CBA. This illustrated the necessity of including at least some additives along with the a.s. Considering additives that were deemed 'relevant' by the tentatively established criteria reduced the underestimation of toxicity for two of the three products. A lack of data for one specific additive was identified as the most likely reason for the remaining toxicity underestimation of the third product. In three other products, toxicity was overestimated by more than factor 2, while prediction and observation fitted well for the seventh product. Considering all additives in the prediction increased only the degree of overestimation. Supported by theoretical calculations and experimental verifications, the present
Analysis of Influence of Foaming Mixture Components on Structure and Properties of Foam Glass
Karandashova, N. S.; Goltsman, B. M.; Yatsenko, E. A.
2017-11-01
It is recommended to use high-quality thermal insulation materials to increase the energy efficiency of buildings. One of the best thermal insulation materials is foam glass - durable, porous material that is resistant to almost any effect of substance. Glass foaming is a complex process depending on the foaming mode and the initial mixture composition. This paper discusses the influence of all components of the mixture - glass powder, foaming agent, enveloping material and water - on the foam glass structure. It was determined that glass powder is the basis of the future material. A foaming agent forms a gas phase in the process of thermal decomposition. This aforementioned gas foams the viscous glass mass. The unreacted residue thus changes a colour of the material. The enveloping agent slows the foaming agent decomposition preventing its premature burning out and, in addition, helps to accelerate the sintering of glass particles. The introduction of water reduces the viscosity of the foaming mixture making it evenly distributed and also promotes the formation of water gas that additionally foams the glass mass. The optimal composition for producing the foam glass with the density of 150 kg/m3 is defined according to the results of the research.
O'Donnell, Katherine M; Thompson, Frank R; Semlitsch, Raymond D
2015-01-01
Detectability of individual animals is highly variable and nearly always 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 protocols that maximize species availability and conditional detection probability to increase population parameter estimate reliability.
Maximum likelihood estimation of semiparametric mixture component models for competing risks data.
Choi, Sangbum; Huang, Xuelin
2014-09-01
In the analysis of competing risks data, the cumulative incidence function is a useful quantity to characterize the crude risk of failure from a specific event type. In this article, we consider an efficient semiparametric analysis of mixture component models on cumulative incidence functions. Under the proposed mixture model, latency survival regressions given the event type are performed through a class of semiparametric models that encompasses the proportional hazards model and the proportional odds model, allowing for time-dependent covariates. The marginal proportions of the occurrences of cause-specific events are assessed by a multinomial logistic model. Our mixture modeling approach is advantageous in that it makes a joint estimation of model parameters associated with all competing risks under consideration, satisfying the constraint that the cumulative probability of failing from any cause adds up to one given any covariates. We develop a novel maximum likelihood scheme based on semiparametric regression analysis that facilitates efficient and reliable estimation. Statistical inferences can be conveniently made from the inverse of the observed information matrix. We establish the consistency and asymptotic normality of the proposed estimators. We validate small sample properties with simulations and demonstrate the methodology with a data set from a study of follicular lymphoma. © 2014, The International Biometric Society.
On-line component ratio measurement of oil/gas/water mixtures using an admittance sensor
Energy Technology Data Exchange (ETDEWEB)
Andersen, J A
1984-01-01
The operator of a production platform is primarily interested in which types of fluids a well is producing and how quickly these different components are being produced. The component ratio and production rate of a well vary during the life of a field. To optimize production, measurement of each well's output is thus desirable. Current designs for subsea production systems lack means of continuously measuring three-component flows. A new method of component ratio measurement is described. The fraction of oil, gas and water flowing between two insulated electrode plates is determined by measuring both the electrical conductance and suseptance across the sensor. A preliminary evaluation of the new measurement system has been performed using a process oil/ water/air mixture. The method is not limited to small pipe diameters. The only possible limitation is that for low velocities in very large pipe diameters an in-line mixer may be required. Advantages of this new system are that real-time measurement of void fraction and water content is possible if a non-intrusive rugged sensor is used, and there are no range limitations, as each component may be measured for any given concentration. 4 references.
Merrill, E A; Gearhart, J M; Sterner, T R; Robinson, P J
2008-07-01
n-Decane is considered a major component of various fuels and industrial solvents. These hydrocarbon products are complex mixtures of hundreds of components, including straight-chain alkanes, branched chain alkanes, cycloalkanes, diaromatics, and naphthalenes. Human exposures to the jet fuel, JP-8, or to industrial solvents in vapor, aerosol, and liquid forms all have the potential to produce health effects, including immune suppression and/or neurological deficits. A physiologically based pharmacokinetic (PBPK) model has previously been developed for n-decane, in which partition coefficients (PC), fitted to 4-h exposure kinetic data, were used in preference to measured values. The greatest discrepancy between fitted and measured values was for fat, where PC values were changed from 250-328 (measured) to 25 (fitted). Such a large change in a critical parameter, without any physiological basis, greatly impedes the model's extrapolative abilities, as well as its applicability for assessing the interactions of n-decane or similar alkanes with other compounds in a mixture model. Due to these limitations, the model was revised. Our approach emphasized the use of experimentally determined PCs because many tissues had not approached steady-state concentrations by the end of the 4-h exposures. Diffusion limitation was used to describe n-decane kinetics for the brain, perirenal fat, skin, and liver. Flow limitation was used to describe the remaining rapidly and slowly perfused tissues. As expected from the high lipophilicity of this semivolatile compound (log K(ow) = 5.25), sensitivity analyses showed that parameters describing fat uptake were next to blood:air partitioning and pulmonary ventilation as critical in determining overall systemic circulation and uptake in other tissues. In our revised model, partitioning into fat took multiple days to reach steady state, which differed considerably from the previous model that assumed steady-state conditions in fat at 4 h post
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
XeBr excilamp based on a non-toxic component mixture
Energy Technology Data Exchange (ETDEWEB)
Kelman, V A; Shpenik, Yu O; Zhmenyak, Yu V, E-mail: mironkle@rambler.ru [Institute of Electron Physics, National Academy of Sciences of Ukraine, Universitetska 21, 88017 Uzhgorod (Ukraine)
2011-06-29
This paper presents the results of experimental studies on obtaining UV luminescence of XeBr* molecules at the excitation of a non-toxic Xe-CsBr gas-vapour mixture by a longitudinal pulse-periodic discharge. Effective UV emission yield of the exciplex XeBr* molecules (spectral maximum at 282 nm) is observed within a wide range of excitation conditions. The spectral distribution in the UV emission under the optimal excitation conditions does not differ essentially from that in other XeBr excilamps based on toxic components. The emission of the B {yields} X band of the XeBr* molecules provides the main contribution to the total power of the discharge UV emission. The determined average power of the UV emission for the experimental discharge tube is 12 W at an efficiency of 1%. Spectral, power-related and time-dependent parameters of the laboratory excilamp are presented for a wide range of excitation parameters. A new mechanism of exciplex molecule formation at the excitation of a rare gas/alkali halide vapour mixture is discussed.
XeBr excilamp based on a non-toxic component mixture
International Nuclear Information System (INIS)
Kelman, V A; Shpenik, Yu O; Zhmenyak, Yu V
2011-01-01
This paper presents the results of experimental studies on obtaining UV luminescence of XeBr* molecules at the excitation of a non-toxic Xe-CsBr gas-vapour mixture by a longitudinal pulse-periodic discharge. Effective UV emission yield of the exciplex XeBr* molecules (spectral maximum at 282 nm) is observed within a wide range of excitation conditions. The spectral distribution in the UV emission under the optimal excitation conditions does not differ essentially from that in other XeBr excilamps based on toxic components. The emission of the B → X band of the XeBr* molecules provides the main contribution to the total power of the discharge UV emission. The determined average power of the UV emission for the experimental discharge tube is 12 W at an efficiency of 1%. Spectral, power-related and time-dependent parameters of the laboratory excilamp are presented for a wide range of excitation parameters. A new mechanism of exciplex molecule formation at the excitation of a rare gas/alkali halide vapour mixture is discussed.
CO2 Removal from Multi-component Gas Mixtures Utilizing Spiral-Wound Asymmetric Membranes
International Nuclear Information System (INIS)
Said, W.B.; Fahmy, M.F.M.; Gad, F.K.; EI-Aleem, G.A.
2004-01-01
A systematic procedure and a computer program have been developed for simulating the performance of a spiral-wound gas permeate for the CO 2 removal from natural gas and other hydrocarbon streams. The simulation program is based on the approximate multi-component model derived by Qi and Henson(l), in addition to the membrane parameters achieved from the binary simulation program(2) (permeability and selectivity). Applying the multi-component program on the same data used by Qi and Henson to evaluate the deviation of the approximate model from the basic transport model, showing results more accurate than those of the approximate model, and are very close to those of the basic transport model, while requiring significantly less than 1 % of the computation time. The program was successfully applied on the data of Salam gas plant membrane unit at Khalda Petroleum Company, Egypt, for the separation of CO 2 from hydrocarbons in an eight-component mixture to estimate the stage cut, residue, and permeate compositions, and gave results matched with the actual Gas Chromatography Analysis measured by the lab
International Nuclear Information System (INIS)
Cotterman, R.L.; Bender, R.; Prausnitz, J.M.
1984-01-01
For some multicomponent mixtures, where detailed chemical analysis is not feasible, the compositio of the mixture may be described by a continuous distribution function of some convenient macroscopic property suc as normal boiling point or molecular weight. To attain a quantitative description of phase equilibria for such mixtures, this work has developed thermodynamic procedures for continuous systems; that procedure is called continuous thermodynamics. To illustrate, continuous thermodynamics is used to calculate dew points for natural-gas mixtures, solvent loss in a high-pressure absorber, and liquid-liquid phase equilibria in a polymer fractionation process. Continuous thermodynamics provides a rational method for calculating phase equilibria for those mixtures where complete chemical analysis is not available but where composition can be given by some statistical description. While continuous thermodynamics is only the logical limit of the well-known pseudo-component method, it is more efficient than that method because it is less arbitrary and it often requires less computer time
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...
Ardhapurkar, P. M.; Sridharan, Arunkumar; Atrey, M. D.
2014-01-01
The recuperative heat exchanger governs the overall performance of the mixed refrigerant Joule-Thomson cryocooler. In these heat exchangers, the non-azeotropic refrigerant mixture of nitrogen-hydrocarbons undergoes boiling and condensation simultaneously at cryogenic temperature. Hence, the design of such heat exchanger is crucial. However, due to lack of empirical correlations to predict two-phase heat transfer coefficients of multi-component mixtures at low temperature, the design of such heat exchanger is difficult.
Energy Technology Data Exchange (ETDEWEB)
Holser, Ronald A.; King, J. W. (Jerry W.); Bost, G.
2002-01-01
The genus Hibiscus exhibits great diversity in the production of natural materials with edible and industrial applications. The seeds of twelve varieties of Hibiscus were investigated as a source for triglycerides and phospholipids that could be used in functional foods. Lipid components were extracted from seed samples ground to a nominal particle diameter of 0.1 mm. Extractions were performed with an ISCO model 3560 supercritical fluid extractor using carbon dioxide and a mixture of carbon dioxide modified with ethanol. The neutral lipids were extracted with carbon dioxide at 80 C and 5370 MPa for 45 min. Polar lipids were subsequently extracted with a mixture of carbon dioxide and 15% ethanol at the same temperature and pressure. High performance liquid chromatography (HPLC) was used to analyze extracts for major neutral and polar lipid classes. A silica column was used with a solvent gradient of hexane/isopropanol/ water and ultraviolet (UV) and evaporative light scattering detectors (ELSD). An aliquot of each triglyceride fraction was trans-methylated with sodium methoxide and analyzed by gas chromatography to obtain the corresponding fatty acid methyl esters. The total lipids extracted ranged from 8.5% for a variety indigenous to Madagascar (H. calyphyllus) to 20% for a hybrid species (Georgia Rose). The average oil yield was 11.4% for the other varieties tested. The fatty acid methyl ester analysis displayed a high degree of unsaturation for all varieties tested, e. g., 75 ' 83%. Oleic, linoleic, and linolenic fatty acids were the predominate unsaturated fatty acids with only minor amounts of C14, C18, and C20 saturated fatty acids measured. Palmitic acid was identified as the predominate saturated fatty acid. The distribution of the major phospholipids, i. e., phosphatidylethanolamine, phosphatidic acid, phosphatidylserine, phosphatidylcholine, and lysophosphatidylcholine, was found to vary significantly among the hibiscus species examined
Damage Detection of Refractory Based on Principle Component Analysis and Gaussian Mixture Model
Directory of Open Access Journals (Sweden)
Changming Liu
2018-01-01
Full Text Available Acoustic emission (AE technique is a common approach to identify the damage of the refractories; however, there is a complex problem since there are as many as fifteen involved parameters, which calls for effective data processing and classification algorithms to reduce the level of complexity. In this paper, experiments involving three-point bending tests of refractories were conducted and AE signals were collected. A new data processing method of merging the similar parameters in the description of the damage and reducing the dimension was developed. By means of the principle component analysis (PCA for dimension reduction, the fifteen related parameters can be reduced to two parameters. The parameters were the linear combinations of the fifteen original parameters and taken as the indexes for damage classification. Based on the proposed approach, the Gaussian mixture model was integrated with the Bayesian information criterion to group the AE signals into two damage categories, which accounted for 99% of all damage. Electronic microscope scanning of the refractories verified the two types of damage.
Gołaszewski, Jacek; Kostrzanowska-Siedlarz, Aleksandra; Ponikiewski, Tomasz; Miera, Patrycja
2017-10-01
The main goal of presented research was to examine usability of cements containing calcareous fly ash (W) from technological point of view. In the paper the results of tests concerning the influence of CEM II and CEM IV cements containing fly ash (W) on rheological properties, air content, setting times and plastic shrinkage of mortars are presented and discussed. Moreover, compatibility of plasticizers with cements containing fly ash (W) was also studied. Additionally, setting time and hydration heat of cements containing calcareous fly ash (W) were determined. In a broader aspect, the research contributes to promulgation of the possibility of using calcareous fly ash (W) in cement and concrete technology, what greatly benefits the environment protection (utilization of waste fly ash). Calcareous fly ash can be used successfully as the main component of cement. Cements produced by blending with processed fly ash or cements produced by interginding are characterized by acceptable technological properties. In respect to CEM I cements, cements containing calcareous fly ash worsen workability, decrease air content, delay setting time of mixtures. Cements with calcareous fly ash show good compatibility with plasticizers.
Investigations of an excimer laser working with a four-component gaseous mixture He-Kr:Xe-HCl
Iwanejko, Leszek; Pokora, Ludwik J.
1991-08-01
The paper presnts working conditions of an XCI excimer laser untypical gas mixture based on KrzXe instead of pure Xe. Such a choice was influenced by the necessity of Findin9 the way to replace imported and expensive Xe by gaseous components accesible in Poland. Determining the range of changes of laser extrnal parameters which enables its proper work with the new gas mixture was the aim of same investigations results of which are presented in this paper. The laser pulse output energy and the pulse duration as a Function of supply voltage and the mixture composition are presented. The range of proper conditions for the laser working with the new mixture He-Kr:Xe--HC1 was determined. The analysis of experimental results showed that using the new mixture ensures value of energy and pulse duration comparable with the ones obtained for the mixture He-''Xe--HCl. Spectral investigations showed the lack of influence of Kr presence in the mixture on the generation spectrum of the laser. L.
Directory of Open Access Journals (Sweden)
Artem O. Donskikh*
2017-10-01
Full Text Available The paper considers methods of classification of grain mixture components based on spectral analysis in visible and near-infrared wavelength ranges using various measurement approaches - reflection, transmission and combined spectrum methods. It also describes the experimental measuring units used and suggests the prototype of a multispectral grain mixture analyzer. The results of the spectral measurement were processed using neural network based classification algorithms. The probabilities of incorrect recognition for various numbers of spectral parts and combinations of spectral methods were estimated. The paper demonstrates that combined usage of two spectral analysis methods leads to higher classification accuracy and allows for reducing the number of the analyzed spectral parts. A detailed description of the proposed measurement device for high-performance real-time multispectral analysis of the components of grain mixtures is given.
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…
Bankefors, Johan; Nord, Lars I; Kenne, Lennart
2010-02-01
A method for separation and detection of major and minor components in complex mixtures has been developed, utilising two-dimensional high-performance liquid chromatography (2D-HPLC) combined with electrospray ionisation ion-trap multiple-stage mass spectrometry (ESI-ITMS(n)). Chromatographic conditions were matched with mass spectrometric detection to maximise the number of components that could be separated. The described procedure has proven useful to discern several hundreds of saponin components when applied to Quillaja saponaria Molina bark extracts. The discrimination of each saponin component relies on the fact that three coordinates (x, y, z) for each component can be derived from the retention time of the two chromatographic steps (x, y) and the m/z-values from the multiple-stage mass spectrometry (z(n), n=1, 2, ...). Thus an improved graphical representation was obtained by combining retention times from the two-stage separation with +MS(1) (z(1)) and the additional structural information from the second mass stage +MS(2) (z(2), z(3)) corresponding to the main fragment ions. By this approach three-dimensional plots can be made that reveal both the chromatographic and structural properties of a specific mixture which can be useful in fingerprinting of complex mixtures. 2009 Elsevier B.V. All rights reserved.
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.
Estimating alarm thresholds and the number of components in mixture distributions
Energy Technology Data Exchange (ETDEWEB)
Burr, Tom, E-mail: tburr@lanl.gov [Los Alamos National Laboratory, Mail Stop F600, Los Alamos, NM 87545 (United States); Hamada, Michael S. [Los Alamos National Laboratory, Mail Stop F600, Los Alamos, NM 87545 (United States)
2012-09-01
Mixtures of probability distributions arise in many nuclear assay and forensic applications, including nuclear weapon detection, neutron multiplicity counting, and in solution monitoring (SM) for nuclear safeguards. SM data is increasingly used to enhance nuclear safeguards in aqueous reprocessing facilities having plutonium in solution form in many tanks. This paper provides background for mixture probability distributions and then focuses on mixtures arising in SM data. SM data can be analyzed by evaluating transfer-mode residuals defined as tank-to-tank transfer differences, and wait-mode residuals defined as changes during non-transfer modes. A previous paper investigated impacts on transfer-mode and wait-mode residuals of event marking errors which arise when the estimated start and/or stop times of tank events such as transfers are somewhat different from the true start and/or stop times. Event marking errors contribute to non-Gaussian behavior and larger variation than predicted on the basis of individual tank calibration studies. This paper illustrates evidence for mixture probability distributions arising from such event marking errors and from effects such as condensation or evaporation during non-transfer modes, and pump carryover during transfer modes. A quantitative assessment of the sample size required to adequately characterize a mixture probability distribution arising in any context is included.
Cerdán, Mar; Alcañiz, Sara; Juárez, Margarita; Jordá, Juana D; Bermúdez, Dolores
2007-10-31
Ferric ethylenediamine- N, N'-bis-(o-hydroxyphenylacetic)acid chelate (Fe(o, o-EDDHA)) is one of the most effective Fe fertilizers in calcareous soils. However, humic substances are occasionally combined with iron chelates in drip irrigation systems in order to lower costs. The reactivity of iron chelate-humic substance mixtures in several soil components and in calcareous soils was investigated through interaction tests, and their behavior was compared to the application of iron chelates and humic substances separately. Two commercial humic substances and two Fe(o, o-EDDHA) chelates (one synthesized in the laboratory and one commercial) were used to prepare iron chelate-humic substance mixtures at 50% (w/w). Various soil components (calcium carbonate, gibbsite, amorphous iron oxide, hematite, tenorite, zincite, amorphous Mn oxide, and peat) and three calcareous soils were shaken for 15 days with the mixtures and with iron chelate and humic substance solutions. The kinetic behavior of Fe(o, o-EDDHA) and Fe non-(o,o-EDDHA) (Fe bonded to (o,p-EDDHA) and other polycondensated ligands) and of the different nutrients solubilized after the interaction assay was determined. The results showed that the mixtures did not significantly reduce the retention of Fe(o, o-EDDHA) and Fe non-(o,o-EDDHA) in the soil components and the calcareous soils compared to the iron chelate solutions, but they did produce changes in the retention rate. Moreover, the competition between humic substances and synthetic chelating agents for complexing metal cations limited the effectiveness of the mixtures to mobilize nutrients from the substrates. The presence of Fe(o, p-EDDHA) and other byproducts in the commercial iron chelate had an important effect on the evolution of Fe(o, o-EDDHA) and the nutrient solubilization process.
A study of chemical equilibrium of tri-component mixtures of hydrogen isotopes
International Nuclear Information System (INIS)
Cristescu, Ioana; Cristescu, I.; Peculea, M.
1998-01-01
In this paper we present a model for computing the equilibrium constants for chemical reactions between hydrogen's isotopes as function of temperature. The equilibrium constants were expressed with the aid of Gibbs potential and the partition function of the mixture. We assessed the partition function for hydrogen's isotopes having in view that some nuclei are fermions and other bosons. As results we plotted the values of equilibrium constants as function of temperature. Knowing these values we determined the deuterium distribution on species (for mixture H 2 -HD-D 2 ) as function of total deuterium concentration and the tritium distribution on species (for mixtures D 2 -DT-T 2 and H 2 -HT-T 2 ) as function of total tritium concentration. (authors)
Directory of Open Access Journals (Sweden)
Maya Nagaie
2014-10-01
Full Text Available Tobacco smoke is a complex mixture of numerous components. Nevertheless, most experiments have examined the effects of individual chemicals in tobacco smoke. The comprehensive effects of components on tooth movement and bone resorption remain unexplored. Here, we have shown that a comprehensive mixture of tobacco smoke components (TSCs attenuated bone resorption through osteoclastogenesis inhibition, thereby retarding experimental tooth movement in a rat model. An elastic power chain (PC inserted between the first and second maxillary molars robustly yielded experimental tooth movement within 10 days. TSC administration effectively retarded tooth movement since day 4. Histological evaluation disclosed that tooth movement induced bone resorption at two sites: in the bone marrow and the peripheral bone near the root. TSC administration significantly reduced the number of tartrate-resistant acid phosphatase (TRAP-positive osteoclastic cells in the bone marrow cavity of the PC-treated dentition. An in vitro study indicated that the inhibitory effects of TSCs on osteoclastogenesis seemed directed more toward preosteoclasts than osteoblasts. These results indicate that the comprehensive mixture of TSCs might be a useful tool for detailed verification of the adverse effects of tobacco smoke, possibly contributing to the development of reliable treatments in various fields associated with bone resorption.
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 usin...... 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....
International Nuclear Information System (INIS)
Furuta, Hiroshi; Yamamoto, Ichiro
1996-01-01
Diffusion coefficients in 4-component mixture D ij (4) were expressed explicitly in terms of binary diffusion coefficients and mole fractions by solving a ratio of determinants defined by Hirschfelder et al. The explicit expressions of D ij (4) were divided into two terms, a term due to the i-j pairs of attention and a term common to all the pairs out of the 4 components. The two terms of D ij (4) had extended structures similar to corresponding those of D ij (3) respectively. (author)
Volatility of components of saturated vapours of UCl4-CsCl and UCl4-LiCl molten mixtures
International Nuclear Information System (INIS)
Smirnov, M.V.; Kudyakov, V.Ya.; Salyulev, A.B.; Komarov, V.E.; Posokhin, Yu.V.; Afonichkin, V.K.
1979-01-01
The flow method has been used for measuring the volatility of the components from UCl 4 -CsCl and UCl 4 -LiCl melted mixtures containing 2.0, 5.0, 12.0, 25.0, 33.0, 50.0, 67.0, and 83.0 mol.% of UCl 4 within the temperature ranges of 903-1188 K and 740-1200 K, respectively. The chemical composition of saturated vapours above the melted salts has been determined. The melted mixtures in question exhibit negative deviation from ideal behaviour. Made was the conclusion about the presence in a vapour phase, along with monomeric UCl 4 , LiCl, CsCl and Li 2 Cl 2 , Cs 2 Cl 2 dimers of double compounds of the MeUCl 5 most probable composition. Their absolute contribution into a total pressure above the UCl 4 -CsCl melted mixtures is considerably smaller than above the UCl 4 -LiCl mixtures
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.
Energy Technology Data Exchange (ETDEWEB)
Wandas, R.; Surygala, J.; Sliwka, E. [Technical University of Wroclaw, Wroclaw (Poland). Inst. of Chemistry and Technology of Petroleum and Coal
1996-05-01
The hydroconversion of o-, m- and p-cresols in three-component model mixtures with naphthalene and n-hexadecane was investigated over a CoMo/Al{sub 2}O{sub 3} catalyst at 360{degree}C, a hydrogen pressure of 7 MPa and a reaction time of 60 min. The results were compared with those obtained for cresols and naphthalene as single model compounds. A lower efficiency of cresol hydrodeoxygenation as well as naphthalene hydrogenation in the mixtures was found than in the conversion of the single compounds. Conversion mechanisms of cresols in the mixtures with naphthalene are considerably more complex than for individual components. Beside typical catalytic reactions, they include radical reactions in which tetralin, formed by naphthalene hydrogenation, participates as a labile-hydrogen source. The cresol reaction products in such systems include phenol, xylenols, xylenes and dimethycyclohexanes, i.e. compounds essentially absent in hydroconversion of cresols as single substances. Under the experimental conditions, the hydrodeoxygenation efficiency of the cresol isomers decreases in the sequence: para {gt} metal {gt} ortho. 22 refs., 3 figs., 3 tabs.
Isolation of EPR spectra and estimation of spin-states in two-component mixtures of paramagnets.
Chabbra, Sonia; Smith, David M; Bode, Bela E
2018-04-26
The presence of multiple paramagnetic species can lead to overlapping electron paramagnetic resonance (EPR) signals. This complication can be a critical obstacle for the use of EPR to unravel mechanisms and aid the understanding of earth abundant metal catalysis. Furthermore, redox or spin-crossover processes can result in the simultaneous presence of metal centres in different oxidation or spin states. In this contribution, pulse EPR experiments on model systems containing discrete mixtures of Cr(i) and Cr(iii) or Cu(ii) and Mn(ii) complexes demonstrate the feasibility of the separation of the EPR spectra of these species by inversion recovery filters and the identification of the relevant spin states by transient nutation experiments. We demonstrate the isolation of component spectra and identification of spin states in a mixture of catalyst precursors. The usefulness of the approach is emphasised by monitoring the fate of the chromium species upon activation of an industrially used precatalyst system.
Czech Academy of Sciences Publication Activity Database
Grim, Jiří
2017-01-01
Roč. 31, č. 9 (2017), č. článku 1750028. ISSN 0218-0014 R&D Projects: GA ČR GA17-18407S Institutional support: RVO:67985556 Keywords : multivariate statistics * product mixtures * naive Bayes models * EM algorithm * pattern recognition * neural networks * expert systems * image analysis Subject RIV: IN - Informatics, Computer Science OBOR OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) Impact factor: 0.994, year: 2016 http://library.utia.cas.cz/separaty/2017/RO/grim-0475182.pdf
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.
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.
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
Causal and causally separable processes
International Nuclear Information System (INIS)
Oreshkov, Ognyan; Giarmatzi, Christina
2016-01-01
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)
Pattarino, Franco; Piepel, Gregory F.; Rinaldi, Maurizio
2018-05-01
The Foglio Bonda et al. (2016) (henceforth FB) paper discussed the use of mixture experiment design and modeling methods to study how the proportions of three components in an extemporaneous oral suspension affected the mean diameter of drug particles (the response variable of interest). The three components were itraconazole (ITZ), Tween 20 (TW20), and Methocel® E5 (E5). After publication of the FB paper, the second author of this corrigendum (not an author of the original paper) contacted the corresponding author to point out some errors as well as insufficient explanations in parts of the paper. This corrigendum was prepared to address these issues. The authors of the original paper apologize for any inconveniences to readers.
Directory of Open Access Journals (Sweden)
Manel Bautista
2012-12-01
Full Text Available Near infrared chemical imaging (NIR-CI has recently emerged as an effective technique for extracting spatial information from pharmaceutical products in an expeditious, non-destructive and non-invasive manner. These features have turned it into a useful tool for controlling various steps in drug production processes. Imaging techniques provide a vast amount of both spatial and spectral information that can be acquired in a very short time. Such a huge amount of data requires the use of efficient and fast methods to extract the relevant information. Chemometric methods have proved especially useful for this purpose. In this study, we assessed the usefulness of the correlation coefficient (CC between the spectra of samples, the pure spectra of the active pharmaceutical ingredient (API and we assessed the excipients to check for correct ingredient distribution in pharmaceutical binary preparations blended in the laboratory. Visual information about pharmaceutical component distribution can be obtained by using the CC. The performance of this model construction methodology for binary samples was compared with other various common multivariate methods including partial least squares, multivariate curve resolution and classical least squares. Based on the results, correlation coefficients are a powerful tool for the rapid assessment of correct component distribution and for quantitative analysis of pharmaceutical binary formulations. For samples of three or more components it has been shown that if the objective is only to determine uniformity of blending, then the CC image map is very good for this, and easy and fast to compute.
Riemann solvers for multi-component gas mixtures with temperature dependent heat capacities
International Nuclear Information System (INIS)
Beccantini, A.
2001-01-01
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)
Biofiltration of paint solvent mixtures in two reactor types: overloading by polar components.
Paca, Jan; Halecky, Martin; Misiaczek, Ondrej; Kozliak, Evguenii I; Jones, Kim
2012-01-01
Steady-state performances of a trickle bed reactor (TBR) and a biofilter (BF) in loading experiments with increasing inlet concentrations of polar solvents, acetone, methyl ethyl ketone, methyl isobutyl ketone and n-butyl acetate, were investigated, along with the system's dynamic responses. Throughout the entire experimentation time, a constant loading rate of aromatic components of 4 g(c)·m(-3)·h(-1) was maintained to observe the interactions between the polar substrates and aromatic hydrocarbons. Under low combined substrate loadings, the BF outperformed TBR not only in the removal of aromatic hydrocarbons but also in the removal of polar substrates. However, increasing the loading rate of polar components above the threshold value of 31-36 g(c)·m(-3)·h(-1) resulted in a steep and significant drop in the removal efficiencies of both polar (except for butyl acetate) and hydrophobic components, which was more pronounced in the BF; so the relative TBR/BF efficiency became reversed under such overloading conditions. A step-drop of the overall OL(POLAR) (combined loading by polar air pollutants) from overloading values to 7 g(c)·m(-3)·h(-1) resulted in an increase of all pollutant removal efficiencies, although in TBR the recovery was preceded by lag periods lasting between 5 min (methyl ethyl ketone) to 3.7 h (acetone). The occurrence of lag periods in the TBR recovery was, in part, due to the saturation of mineral medium with water-soluble polar solvents, particularly, acetone. The observed bioreactor behavior was consistent with the biological steps being rate-limiting.
Biofiltration of paint solvent mixtures in two reactor types: overloading by hydrophobic components.
Paca, Jan; Halecky, Martin; Misiaczek, Ondrej; Jones, Kim; Kozliak, Evguenii; Sobotka, Miroslav
2010-12-01
Steady-state performance characteristics of a trickle bed reactor (TBR) and a biofilter (BF) in loading experiments with increasing toluene/xylenes inlet concentrations while maintaining a constant loading rate of hydrophilic components (methyl ethyl and methyl isobutyl ketones, acetone, and n-butyl acetate) of 4 g m⁻³ h⁻¹ were evaluated and compared, along with the systems' dynamic responses. At the same combined substrate loading of 55 g m⁻³ h⁻¹ for both reactors, the TBR achieved more than 1.5 times higher overall removal efficiency (RE(W)) than the BF. Increasing the loading rate of aromatics resulted in a gradual decrease of their REs. The degradation rates of acetone and n-butyl acetate were also inhibited at higher loads of aromatics, thus revealing a competition in cell catabolism. A step-drop in loading of aromatics resulted in an immediate increase of RE(W) with variations in the TBR, while the new steady-state value in the BF took 6-7 h to achieve. The TBR consistently showed a greater performance than BF in removing toluene and xylenes. Increasing the loading rate of aromatics resulted in a gradual decrease of their REs. The degradation rates of acetone and n-butyl acetate were also lower at higher OL(AROM), revealing a competition in the cell catabolism. The results obtained are consistent with the proposed hypothesis of greater toxic effects under low water content, i.e., in the biofilter, caused by aromatic hydrocarbons in the presence of polar ketones and esters, which may improve the hydrocarbon partitioning into the aqueous phase.
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.
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
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.
Duann, Jeng-Ren; Jan, Chia-Ing; Ou-Yang, Mang; Lin, Chia-Yi; Mo, Jen-Feng; Lin, Yung-Jiun; Tsai, Ming-Hsui; Chiou, Jin-Chern
2013-12-01
Recently, hyperspectral imaging (HSI) systems, which can provide 100 or more wavelengths of emission autofluorescence measures, have been used to delineate more complete spectral patterns associated with certain molecules relevant to cancerization. Such a spectral fingerprint may reliably correspond to a certain type of molecule and thus can be treated as a biomarker for the presence of that molecule. However, the outcomes of HSI systems can be a complex mixture of characteristic spectra of a variety of molecules as well as optical interferences due to reflection, scattering, and refraction. As a result, the mixed nature of raw HSI data might obscure the extraction of consistent spectral fingerprints. Here we present the extraction of the characteristic spectra associated with keratinized tissues from the HSI data of tissue sections from 30 oral cancer patients (31 tissue samples in total), excited at two different wavelength ranges (330 to 385 and 470 to 490 nm), using independent and principal component analysis (ICA and PCA) methods. The results showed that for both excitation wavelength ranges, ICA was able to resolve much more reliable spectral fingerprints associated with the keratinized tissues for all the oral cancer tissue sections with significantly higher mean correlation coefficients as compared to PCA (p<0.001).
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.
International Nuclear Information System (INIS)
Iloukhani, H.; Khanlarzadeh, K.
2012-01-01
Highlights: ► Excess molar volume of quartenary mixtures of 1-chlorobutane, 2-chlorobutane, butylamine, and butylacetate was determined. ► The experimental data were correlated by some empirical and semi empirical models. ► A comparison with PFP theory has been successfully applied from binary data. - Abstract: Densities of the quaternary mixture consisting of {1-chlorobutane (1) + 2-chlorobutane (2) + butylamine (3) + butylacetate (4)} and related ternary mixtures of {1-chlorobutane (1) + 2-chlorobutane (2) + butylamine (3)}, {1-chlorobutane (1) + 2-chlorobutane (2) + butylacetate (4)}, {2-chlorobutane (2) + butylamine (3) + butylacetate (4)}, and binary systems of {1-chlorobutane (1) + 2-chlorobutane (2)}, {2-chlorobutane (2) + butylamine (3)}, were measured over the whole range of composition at T = 298.15 K and ambient pressure. Excess molar volumes, V m E , for the mixtures were derived and correlated as a function of mole fraction by using the Redlich–Kister and the Cibulka equations for binary and ternary mixtures, respectively. From the experimental data, partial molar volumes, V m,i and excess partial molar volumes, V m,i E were also calculated for binary systems. The experimental results of the constituted binary mixtures have been used to test the applicability of the Prigogine–Flory–Paterson (PFP) theory. A number of geometrical and empirical equations were also used to verify their ability to predict ternary and quaternary properties from their lower order mixtures. The experimental data were used to evaluate the nature and type of intermolecular interactions in multi-component mixtures.
Lapointe, Stephen L; Barros-Parada, Wilson; Fuentes-Contreras, Eduardo; Herrera, Heidy; Kinsho, Takeshi; Miyake, Yuki; Niedz, Randall P; Bergmann, Jan
2017-12-01
Field experiments were carried out to study responses of male moths of the carpenterworm, Chilecomadia valdiviana (Lepidoptera: Cossidae), a pest of tree and fruit crops in Chile, to five compounds previously identified from the pheromone glands of females. Previously, attraction of males to the major component, (7Z,10Z)-7,10-hexadecadienal, was clearly demonstrated while the role of the minor components was uncertain due to the use of an experimental design that left large portions of the design space unexplored. We used mixture designs to study the potential contributions to trap catch of the four minor pheromone components produced by C. valdiviana. After systematically exploring the design space described by the five pheromone components, we concluded that the major pheromone component alone is responsible for attraction of male moths in this species. The need for appropriate experimental designs to address the problem of assessing responses to mixtures of semiochemicals in chemical ecology is described. We present an analysis of mixture designs and response surface modeling and an explanation of why this approach is superior to commonly used, but statistically inappropriate, designs.
Dowling, Quinton M; Kramer, Ryan M
2017-01-01
Fourier transform infrared (FTIR) spectroscopy is widely used in the pharmaceutical industry for process monitoring, compositional quantification, and characterization of critical quality attributes in complex mixtures. Advantages over other spectroscopic measurements include ease of sample preparation, quantification of multiple components from a single measurement, and the ability to quantify optically opaque samples. This method describes the use of a multivariate model for quantifying a TLR4 agonist (GLA) adsorbed onto aluminum oxyhydroxide (Alhydrogel ® ) using FTIR spectroscopy that may be adapted to quantify other complex aluminum based adjuvant mixtures.
Paradoxical Behavior of Granger Causality
Witt, Annette; Battaglia, Demian; Gail, Alexander
2013-03-01
Granger causality is a standard tool for the description of directed interaction of network components and is popular in many scientific fields including econometrics, neuroscience and climate science. For time series that can be modeled as bivariate auto-regressive processes we analytically derive an expression for spectrally decomposed Granger Causality (SDGC) and show that this quantity depends only on two out of four groups of model parameters. Then we present examples of such processes whose SDGC expose paradoxical behavior in the sense that causality is high for frequency ranges with low spectral power. For avoiding misinterpretations of Granger causality analysis we propose to complement it by partial spectral analysis. Our findings are illustrated by an example from brain electrophysiology. Finally, we draw implications for the conventional definition of Granger causality. Bernstein Center for Computational Neuroscience Goettingen
International Nuclear Information System (INIS)
Ogawa, Masuro
1992-10-01
In the present paper, mass transfer has been numerically studied in a laminar flow through a circular graphite tube to evaluate graphite corrosion rate and generation rate of carbon monoxide during a pipe rupture accident in a high temperature gas cooled reactor. In the analysis, heterogeneous (graphite oxidation and graphite/carbon dioxide reaction) and homogeneous (carbon monoxide combustion) chemical reactions were dealt in the multi-component gas mixture; helium, oxygen, carbon monoxide and carbon dioxide. Multi-component diffusion coefficients were used in a diffusion term. Mass conservation equations of each gas component, mass conservation equation and momentum conservation equations of the gas mixture were solved by using SIMPLE algorism. Chemical reactions between graphite and oxygen, graphite and carbon dioxide, and carbon monoxide combustion were taken into account in the present numerical analysis. An energy equation for the gas mixture was not solved and temperature was held to be constant in order to understand basic mass transfer characteristics without heat transfer. But, an energy conservation equation for single component gas was added to know heat transfer characteristics without mass transfer. The effects of these chemical reactions on the mass transfer coefficients were quantitatively and qualitatively clarified in the range of 50 to 1000 of inlet Reynolds numbers, 0 to 0.5 of inlet oxygen mass fraction and 800 to 1600degC of temperature. (author)
Energy Technology Data Exchange (ETDEWEB)
Klyusov, A A; Bakshutov, V S; Kulyavtsev, V A
1980-10-23
A grouting mixture is proposed for low-temperature boreholes. The mixture contains cement, beta gypsum polyhydrate, and calcium chloride, so as to increase the water resistance and strength properties of expanding brick at conditions from 20 to -5/sup 0/ C, the components are in the following ratios: (by wt.-%): cement, 77.45-88.06; beta gypsum polyhydrate, 9.79-19.36; calcium chloride, 2.15-3.19. Grouting mortar for cold boreholes serves as the cement.
Directory of Open Access Journals (Sweden)
Mohammad Saleh Lubis
2014-05-01
Full Text Available Indonesia has more than 17,506 islands and 92 islands of them are outermost small islands. Lingayan is one of them located in Northwest of Sulawesi Island and it has geostrategic role to determine the sea boundaries of Indonesian State (NKRI including the territorial seas, the exclusive economic zone and the continental shelf. Recently, the coastal ecosystems of Lingayan has degraded and the island’s economy is weak so they cannot support the life’s survival of inhabiting people. This condition could weaken the geostrategic role in accordance with article 121 Chapter VIII of the United Nations Convention on the Law of the Sea (UNCLOS. Based on the above reasons, the study aim to examine and assess the causal relation of components in the socio-ecological and socio-economical systems as a basis for management of the Lingayan Island with target on conservation of coastal ecosystems and growth of inhabitant’ business economic. Causalities relations within components were built using Statistic Equation Model (SEM with AMOS method and 40 constructed indicators as well as determinate the suitability program using Analytical Hierarchy Process (AHP. The research showed that there is relationship between the components of socio-ecological systems as indicated by the fit model of causal relation path diagram that provides chi square value = 236.994, RMSEA = 0.083, GFI = 0.884. Furthermore, there is relationship between the components of socio-economical that provides chi square value = 192.824, RMSEA = 0.081, GFI = 0.900. The most appropriate programs are seaweed cultivation (34.0% and restoration (23.4%.
International Nuclear Information System (INIS)
Wakeley, L.D.; Roy, D.M.
1986-03-01
Using the interface zone as an indicator of compatibility, preliminary tests were run using cement-based formulations designed to be used for shaft sealing in conjunction with evaporite and clastic rocks of the Palo Duro Basin, one of several potential sites for a high-level radioactive waste repository. Emphasis focused on two formulations, both designed to be slightly expansive. Mixture 83-05 was tested in combination with anhydrite and siltstone. A comparable mixture (83-03) containing salt was used with the halite. Cement, rocks, and their respective interfaces were examined using x-ray diffraction, optical microscopy, and scanning electron microscopy. Bond strengths between rock and cement as well as between selected steels and grout were determined as a function of curing conditions and pretest surface treatment. Permeabilities of cement/rock and cement/steel composites were also determined. Bond strength and permeability were found to vary with curing conditions as well as surface treatment
International Nuclear Information System (INIS)
Zhavrin, Yu.I.; Kosov, V.N.; Kul'zhanov, D.U.; Karataev, K.K.
2000-01-01
Presence of two types of instabilities of mechanical equilibrium of a mixture experimentally is shown at an isothermal diffusion of multicomponent system with zero gradient of density/ Theoretically is proved, that partial Rayleigh numbers R 1 , R 2 having different signs, there are two areas with monotonous (R 1 2 < by 0) instability. The experimental data confirm presence of these areas and satisfactory are described by the represented theory. (author)
International Nuclear Information System (INIS)
Maurente, André; França, Francis H.R.; Miki, Kenji; Howell, John R.
2012-01-01
Approximations for joint cumulative k-distribution for mixtures are efficient for full spectrum k-distribution (FSK) computations. These approximations provide reduction of the database that is necessary to perform FSK computation when compared to the direct approach, which uses cumulative k-distributions computed from the spectrum of the mixture, and also less computational expensive when compared to techniques in which RTE's are required to be solved for each component of the mixture. The aim of the present paper is to extend the approximations for joint cumulative k-distributions for non-LTE media. For doing that, a FSK to non-LTE media formulation well-suited to be applied along with approximations for joint cumulative k-distributions is presented. The application of the proposed methodology is demonstrated by solving the radiation heat transfer in non-LTE high temperature plasmas composed of N, O, N 2 , NO, N 2 + and mixtures of these species. The two more efficient approximations, that is, the superposition and multiplication are employed and analyzed.
Volatility of components of saturated vapours of UCl/sub 4/-CsCl and UCl/sub 4/-LiCl molten mixtures
Energy Technology Data Exchange (ETDEWEB)
Smirnov, M V; Kudyakov, V Ya; Salyulev, A B; Komarov, V E; Posokhin, Yu V; Afonichkin, V K
1979-01-01
The flow method has been used for measuring the volatility of the components from UCl/sub 4/-CsCl and UCl/sub 4/-LiCl melted mixtures containing 2.0, 5.0, 12.0, 25.0, 33.0, 50.0, 67.0, and 83.0 mol.% of UCl/sub 4/ within the temperature ranges of 903-1188 K and 740-1200 K, respectively. The chemical composition of saturated vapours above the melted salts has been determined. The melted mixtures in question exhibit negative deviation from ideal behaviour. Made was the conclusion about the presence in a vapour phase, along with monomeric UCl/sub 4/, LiCl, CsCl and Li/sub 2/Cl/sub 2/, Cs/sub 2/Cl/sub 2/ dimers of double compounds of the MeUCl/sub 5/ most probable composition. Their absolute contribution into a total pressure above the UCl/sub 4/-CsCl melted mixtures is considerably smaller than above the UCl/sub 4/ -LiCl mixtures.
Causally nonseparable processes admitting a causal model
International Nuclear Information System (INIS)
Feix, Adrien; Araújo, Mateus; Brukner, Caslav
2016-01-01
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. (paper)
Separation of the components of the TBP-H2 MBP-HDBP-H3PO4 mixture
International Nuclear Information System (INIS)
Pires, M.A.F.; Abrao, A.
1981-04-01
Several schemes for the separation of dibutylphosphoric acid (HDBP), monobutylphosphoric acid (H 2 MBP) and orthophosphoric acid (H 3 PO 4 ) as hydrolytic and radiolytic degradation products from tri-n-butylphosphate (TBP) were studied. For the resolution of a HDBP, H 2 MPB and H 3 PO 4 mixture in TBP-diluent, or in TBP-diluent-heavy metal nitrate (U-VI, Th-IV or Zr-IV), techniques such as ion exchange chromatography, ion chromatography and separation onto a chromatographic alumina column were investigated. For the identification, determination and analytical resolution following up for the several systems studied, techniques such as refraction index measurement, electrical conductivity measurement, molecular spectrophotometry and gas chromatography were applied. Special emphasys was given to the separation using alumina column where the HDBP acid was retained and eluted selectively for its separation from TBP-varsol-uranyl nitrate mixtures. This analytical procedure was applied to the samples coming from the Uranium Purification Pilot Plant in operation at the Centro de Engenharia Quimica (IPEN). (Author) [pt
Sear, Richard P.
2018-04-01
I model the drying of a liquid film containing small and big colloid particles. Fortini et al. [Phys. Rev. Lett. 116, 118301 (2016)] studied these films with both computer simulation and experiment. They found that at the end of drying, the mixture had stratified with a layer of the smaller particles on top of the big particles. I develop a simple model for this process. The model has two ingredients: arrest of the diffusion of the particles at high density and diffusiophoretic motion of the big particles due to gradients in the volume fraction of the small particles. The model predicts that stratification only occurs over a range of initial volume fractions of the smaller colloidal species. Above and below this range, the downward diffusiophoretic motion of the big particles is too slow to remove the big particles from the top of the film, and so there is no stratification. In agreement with earlier work, the model also predicts that large Péclet numbers for drying are needed to see stratification.
Directory of Open Access Journals (Sweden)
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.
Directory of Open Access Journals (Sweden)
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.
Golker, Kerstin; Karlsson, Björn C G; Rosengren, Annika M; Nicholls, Ian A
2014-11-10
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.
Directory of Open Access Journals (Sweden)
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.
Frisch, Mathias
2014-01-01
Much has been written on the role of causal notions and causal reasoning in the so-called 'special sciences' and in common sense. But does causal reasoning also play a role in physics? Mathias Frisch argues that, contrary to what influential philosophical arguments purport to show, the answer is yes. Time-asymmetric causal structures are as integral a part of the representational toolkit of physics as a theory's dynamical equations. Frisch develops his argument partly through a critique of anti-causal arguments and partly through a detailed examination of actual examples of causal notions in physics, including causal principles invoked in linear response theory and in representations of radiation phenomena. Offering a new perspective on the nature of scientific theories and causal reasoning, this book will be of interest to professional philosophers, graduate students, and anyone interested in the role of causal thinking in science.
Jones, Robert
2010-03-01
There are a wide range of views on causality. To some (e.g. Karl Popper) causality is superfluous. Bertrand Russell said ``In advanced science the word cause never occurs. Causality is a relic of a bygone age.'' At the other extreme Rafael Sorkin and L. Bombelli suggest that space and time do not exist but are only an approximation to a reality that is simply a discrete ordered set, a ``causal set.'' For them causality IS reality. Others, like Judea Pearl and Nancy Cartwright are seaking to build a complex fundamental theory of causality (Causality, Cambridge Univ. Press, 2000) Or perhaps a theory of causality is simply the theory of functions. This is more or less my take on causality.
International Nuclear Information System (INIS)
Irvin, T.R.; Akgerman, A.
1991-01-01
Many adverse health effects caused by combustion-generated toxins have been recognized for some time. Acute pulmonary toxicity among urban populations has been repeatedly recorded during periods of high smoke, soot, and organo-particulate pollution. The combustion of coals and petroleum-derived fuels results in emission of particulate and organic vapor-phase components to the atmosphere. Isolation of these particle-absorbed compounds and subsequent toxicological testing has further indicated the importance of chronic, low-level exposure to airborne combustion-generated toxins in the etiology of many forms of human cancer; particulate phases of these emissions have been found to contain polycyclic aromatic hydrocarbons and heterocyclic organic compounds, absorbed onto the particle matrix, which possess potent carcinogenic and mutagenic properties. In this paper, the authors define a postimplantation rat embryo culture system constructed to identify prenatal toxic components of complex polycyclic aromatic hydrocarbon soots. Employing this culture system, we also describe its application to identify prenatal toxic components of diesel soot particulates
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.
Directory of Open Access Journals (Sweden)
Cristina Puente Águeda
2011-10-01
Full Text Available Causality is a fundamental notion in every field of science. Since the times of Aristotle, causal relationships have been a matter of study as a way to generate knowledge and provide for explanations. In this paper I review the notion of causality through different scientific areas such as physics, biology, engineering, etc. In the scientific area, causality is usually seen as a precise relation: the same cause provokes always the same effect. But in the everyday world, the links between cause and effect are frequently imprecise or imperfect in nature. Fuzzy logic offers an adequate framework for dealing with imperfect causality, so a few notions of fuzzy causality are introduced.
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...
Heping, Wang; Xiaoguang, Li; Duyang, Zang; Rui, Hu; Xingguo, Geng
2017-11-01
This paper presents an exploration for phase separation in a magnetic field using a coupled lattice Boltzmann method (LBM) with magnetohydrodynamics (MHD). The left vertical wall was kept at a constant magnetic field. Simulations were conducted by the strong magnetic field to enhance phase separation and increase the size of separated phases. The focus was on the effect of magnetic intensity by defining the Hartmann number (Ha) on the phase separation properties. The numerical investigation was carried out for different governing parameters, namely Ha and the component ratio of the mixed liquid. The effective morphological evolutions of phase separation in different magnetic fields were demonstrated. The patterns showed that the slant elliptical phases were created by increasing Ha, due to the formation and increase of magnetic torque and force. The dataset was rearranged for growth kinetics of magnetic phase separation in a plot by spherically averaged structure factor and the ratio of separated phases and total system. The results indicate that the increase in Ha can increase the average size of separated phases and accelerate the spinodal decomposition and domain growth stages. Specially for the larger component ratio of mixed phases, the separation degree was also significantly improved by increasing magnetic intensity. These numerical results provide guidance for setting the optimum condition for the phase separation induced by magnetic field.
Butakova, M. D.; Gorbunov, S. P.
2017-11-01
It is accepted to call concrete a special construction mix which consists of several main components - most often, these are cement, water and various fillers. As a result of grout hardening, the artificial stone, used in many areas where durability, stability and durability are required, is formed. To improve the main characteristics of concrete, various additives are added to the mix. These substances are also capable of accelerating the speed of construction and reducing the funds expenditure. It is especially important to apply additives at the installation of coverings to airfields, at the construction of moorings, roads, at the laying of pools or during other hydraulic engineering constructions, and also at the construction of monolithic industrial facilities and houses. The article deals with the composition and quantity of complex organomineral additives, the duration and conditions for the formation of composites’ structure.
Rehder, Bob
2017-01-01
This article assesses how people reason with categories whose features are related in causal cycles. Whereas models based on causal graphical models (CGMs) have enjoyed success modeling category-based judgments as well as a number of other cognitive phenomena, CGMs are only able to represent causal structures that are acyclic. A number of new…
Gill, Jatinder; Singh, Jagdev
2017-11-01
In this work, the experimental examination was carried out using a mixture of R134a and LPG refrigerant (consisting of R134a and LPG in a proportion of 28:72 by weight) as a replacement for R134a in a vapor compression refrigeration system. Exergy and energy tests were carried out at different evaporator and condenser temperatures with controlled environmental conditions. The results showed that the exergy destruction in the compressor, condenser, evaporator, and a capillary tube of the R134a / LPG refrigeration system was found lower by approximately 11.13-3.41%, 2.24-3.43%, 12.02-13.47% and 1.54-5.61% respectively. The compressor exhibits the highest level of destruction, accompanied by a condenser, an evaporator and a capillary tube in refrigeration systems. The refrigeration capacity, COP and power consumption of the compressor of the R134a /LPG refrigeration system were detected higher and lower compared to the R134a refrigeration system by about 7.04-11.41%, 15.1-17.82%, and 3.83-8.08% respectively. Also, the miscibility of R134a and LPG blend with mineral oil discovered good. The R134a and LPG refrigerant mixture proposed in this study perform superior to R134a from component-wise exergy and energy analyses under similar experimental conditions.
Gill, Jatinder; Singh, Jagdev
2018-05-01
In this work, the experimental examination was carried out using a mixture of R134a and LPG refrigerant (consisting of R134a and LPG in a proportion of 28:72 by weight) as a replacement for R134a in a vapor compression refrigeration system. Exergy and energy tests were carried out at different evaporator and condenser temperatures with controlled environmental conditions. The results showed that the exergy destruction in the compressor, condenser, evaporator, and a capillary tube of the R134a / LPG refrigeration system was found lower by approximately 11.13-3.41%, 2.24-3.43%, 12.02-13.47% and 1.54-5.61% respectively. The compressor exhibits the highest level of destruction, accompanied by a condenser, an evaporator and a capillary tube in refrigeration systems. The refrigeration capacity, COP and power consumption of the compressor of the R134a /LPG refrigeration system were detected higher and lower compared to the R134a refrigeration system by about 7.04-11.41%, 15.1-17.82%, and 3.83-8.08% respectively. Also, the miscibility of R134a and LPG blend with mineral oil discovered good. The R134a and LPG refrigerant mixture proposed in this study perform superior to R134a from component-wise exergy and energy analyses under similar experimental conditions.
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. Copyright © 2016 Elsevier B.V. All rights reserved.
Directory of Open Access Journals (Sweden)
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.
Causal imprinting in causal structure learning.
Taylor, Eric G; Ahn, Woo-Kyoung
2012-11-01
Suppose one observes a correlation between two events, B and C, and infers that B causes C. Later one discovers that event A explains away the correlation between B and C. Normatively, one should now dismiss or weaken the belief that B causes C. Nonetheless, participants in the current study who observed a positive contingency between B and C followed by evidence that B and C were independent given A, persisted in believing that B causes C. The authors term this difficulty in revising initially learned causal structures "causal imprinting." Throughout four experiments, causal imprinting was obtained using multiple dependent measures and control conditions. A Bayesian analysis showed that causal imprinting may be normative under some conditions, but causal imprinting also occurred in the current study when it was clearly non-normative. It is suggested that causal imprinting occurs due to the influence of prior knowledge on how reasoners interpret later evidence. Consistent with this view, when participants first viewed the evidence showing that B and C are independent given A, later evidence with only B and C did not lead to the belief that B causes C. Copyright © 2012 Elsevier Inc. All rights reserved.
Repeated causal decision making.
Hagmayer, York; Meder, Björn
2013-01-01
Many of our decisions refer to actions that have a causal impact on the external environment. Such actions may not only allow for the mere learning of expected values or utilities but also for acquiring knowledge about the causal structure of our world. We used a repeated decision-making paradigm to examine what kind of knowledge people acquire in such situations and how they use their knowledge to adapt to changes in the decision context. Our studies show that decision makers' behavior is strongly contingent on their causal beliefs and that people exploit their causal knowledge to assess the consequences of changes in the decision problem. A high consistency between hypotheses about causal structure, causally expected values, and actual choices was observed. The experiments show that (a) existing causal hypotheses guide the interpretation of decision feedback, (b) consequences of decisions are used to revise existing causal beliefs, and (c) decision makers use the experienced feedback to induce a causal model of the choice situation even when they have no initial causal hypotheses, which (d) enables them to adapt their choices to changes of the decision problem. (PsycINFO Database Record (c) 2013 APA, all rights reserved).
[Causal analysis approaches in epidemiology].
Dumas, O; Siroux, V; Le Moual, N; Varraso, R
2014-02-01
Epidemiological research is mostly based on observational studies. Whether such studies can provide evidence of causation remains discussed. Several causal analysis methods have been developed in epidemiology. This paper aims at presenting an overview of these methods: graphical models, path analysis and its extensions, and models based on the counterfactual approach, with a special emphasis on marginal structural models. Graphical approaches have been developed to allow synthetic representations of supposed causal relationships in a given problem. They serve as qualitative support in the study of causal relationships. The sufficient-component cause model has been developed to deal with the issue of multicausality raised by the emergence of chronic multifactorial diseases. Directed acyclic graphs are mostly used as a visual tool to identify possible confounding sources in a study. Structural equations models, the main extension of path analysis, combine a system of equations and a path diagram, representing a set of possible causal relationships. They allow quantifying direct and indirect effects in a general model in which several relationships can be tested simultaneously. Dynamic path analysis further takes into account the role of time. The counterfactual approach defines causality by comparing the observed event and the counterfactual event (the event that would have been observed if, contrary to the fact, the subject had received a different exposure than the one he actually received). This theoretical approach has shown limits of traditional methods to address some causality questions. In particular, in longitudinal studies, when there is time-varying confounding, classical methods (regressions) may be biased. Marginal structural models have been developed to address this issue. In conclusion, "causal models", though they were developed partly independently, are based on equivalent logical foundations. A crucial step in the application of these models is the
Causality, spin, and equal-time commutators
International Nuclear Information System (INIS)
Abdel-Rahman, A.M.
1975-01-01
We study the causality constraints on the structure of the Lorentz-antisymmetric component of the commutator of two conserved isovector currents between fermion states of equal momenta. We discuss the sum rules that follow from causality and scaling, using the recently introduced refined infinite-momentum technique. The complete set of sum rules is found to include the spin-dependent fixed-mass sum rules obtained from light-cone commutators. The causality and scaling restrictions on the structure of the electromagnetic equal-time commutators are discussed, and it is found, in particular, that causality requires the spin-dependent part of the matrix element for the time-space electromagnetic equal-time commutator to vanish identically. It is also shown, in comparison with the electromagnetic case, that the corresponding matrix element for the time-space isovector current equal-time commutator is required, by causality, to have isospin-antisymmetric tensor and scalar operator Schwinger terms
Causal 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
Repeated Causal Decision Making
Hagmayer, York; Meder, Bjorn
2013-01-01
Many of our decisions refer to actions that have a causal impact on the external environment. Such actions may not only allow for the mere learning of expected values or utilities but also for acquiring knowledge about the causal structure of our world. We used a repeated decision-making paradigm to examine what kind of knowledge people acquire in…
International Nuclear Information System (INIS)
Novello, M.; Salim, J.M.; Torres, J.; Oliveira, H.P. de
1989-01-01
A set of spatially homogeneous and isotropic cosmological geometries generated by a class of non-perfect is investigated fluids. The irreversibility if this system is studied in the context of causal thermodynamics which provides a useful mechanism to conform to the non-violation of the causal principle. (author) [pt
Causal Analysis After Haavelmo
Heckman, James; Pinto, Rodrigo
2014-01-01
Haavelmo's seminal 1943 and 1944 papers are the first rigorous treatment of causality. In them, he distinguished the definition of causal parameters from their identification. He showed that causal parameters are defined using hypothetical models that assign variation to some of the inputs determining outcomes while holding all other inputs fixed. He thus formalized and made operational Marshall's (1890) ceteris paribus analysis. We embed Haavelmo's framework into the recursive framework of Directed Acyclic Graphs (DAGs) used in one influential recent approach to causality (Pearl, 2000) and in the related literature on Bayesian nets (Lauritzen, 1996). We compare the simplicity of an analysis of causality based on Haavelmo's methodology with the complex and nonintuitive approach used in the causal literature of DAGs—the “do-calculus” of Pearl (2009). We discuss the severe limitations of DAGs and in particular of the do-calculus of Pearl in securing identification of economic models. We extend our framework to consider models for simultaneous causality, a central contribution of Haavelmo. In general cases, DAGs cannot be used to analyze models for simultaneous causality, but Haavelmo's approach naturally generalizes to cover them. PMID:25729123
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 in Europeanization Research
DEFF Research Database (Denmark)
Lynggaard, Kennet
2012-01-01
to develop discursive institutional analytical frameworks and something that comes close to the formulation of hypothesis on the effects of European Union (EU) policies and institutions on domestic change. Even if these efforts so far do not necessarily amount to substantive theories or claims of causality......Discourse analysis as a methodology is perhaps not readily associated with substantive causality claims. At the same time the study of discourses is very much the study of conceptions of causal relations among a set, or sets, of agents. Within Europeanization research we have seen endeavours......, it suggests that discourse analysis and the study of causality are by no means opposites. The study of Europeanization discourses may even be seen as an essential step in the move towards claims of causality in Europeanization research. This chapter deals with the question of how we may move from the study...
Directory of Open Access Journals (Sweden)
Thomas eWidlok
2014-11-01
Full Text Available Cognitive Scientists interested in causal cognition increasingly search for evidence from non-WEIRD people but find only very few cross-cultural studies that specifically target causal cognition. This article suggests how information about causality can be retrieved from ethnographic monographs, specifically from ethnographies that discuss agency and concepts of time. Many apparent cultural differences with regard to causal cognition dissolve when cultural extensions of agency and personhood to non-humans are taken into account. At the same time considerable variability remains when we include notions of time, linearity and sequence. The article focuses on ethnographic case studies from Africa but provides a more general perspective on the role of ethnography in research on the diversity and universality of causal cognition.
Directory of Open Access Journals (Sweden)
Ämin Baumeler
2017-07-01
Full Text Available Computation models such as circuits describe sequences of computation steps that are carried out one after the other. In other words, algorithm design is traditionally subject to the restriction imposed by a fixed causal order. We address a novel computing paradigm beyond quantum computing, replacing this assumption by mere logical consistency: We study non-causal circuits, where a fixed time structure within a gate is locally assumed whilst the global causal structure between the gates is dropped. We present examples of logically consistent non-causal circuits outperforming all causal ones; they imply that suppressing loops entirely is more restrictive than just avoiding the contradictions they can give rise to. That fact is already known for correlations as well as for communication, and we here extend it to computation.
Causality and headache triggers
Turner, Dana P.; Smitherman, Todd A.; Martin, Vincent T.; Penzien, Donald B.; Houle, Timothy T.
2013-01-01
Objective The objective of this study was to explore the conditions necessary to assign causal status to headache triggers. Background The term “headache trigger” is commonly used to label any stimulus that is assumed to cause headaches. However, the assumptions required for determining if a given stimulus in fact has a causal-type relationship in eliciting headaches have not been explicated. Methods A synthesis and application of Rubin’s Causal Model is applied to the context of headache causes. From this application the conditions necessary to infer that one event (trigger) causes another (headache) are outlined using basic assumptions and examples from relevant literature. Results Although many conditions must be satisfied for a causal attribution, three basic assumptions are identified for determining causality in headache triggers: 1) constancy of the sufferer; 2) constancy of the trigger effect; and 3) constancy of the trigger presentation. A valid evaluation of a potential trigger’s effect can only be undertaken once these three basic assumptions are satisfied during formal or informal studies of headache triggers. Conclusions Evaluating these assumptions is extremely difficult or infeasible in clinical practice, and satisfying them during natural experimentation is unlikely. Researchers, practitioners, and headache sufferers are encouraged to avoid natural experimentation to determine the causal effects of headache triggers. Instead, formal experimental designs or retrospective diary studies using advanced statistical modeling techniques provide the best approaches to satisfy the required assumptions and inform causal statements about headache triggers. PMID:23534872
D'Ariano, Giacomo Mauro
2018-07-13
Causality has never gained the status of a 'law' or 'principle' in physics. Some recent literature has even popularized the false idea that causality is a notion that should be banned from theory. Such misconception relies on an alleged universality of the reversibility of the laws of physics, based either on the determinism of classical theory, or on the multiverse interpretation of quantum theory, in both cases motivated by mere interpretational requirements for realism of the theory. Here, I will show that a properly defined unambiguous notion of causality is a theorem of quantum theory, which is also a falsifiable proposition of the theory. Such a notion of causality appeared in the literature within the framework of operational probabilistic theories. It is a genuinely theoretical notion, corresponding to establishing a definite partial order among events, in the same way as we do by using the future causal cone on Minkowski space. The notion of causality is logically completely independent of the misidentified concept of 'determinism', and, being a consequence of quantum theory, is ubiquitous in physics. In addition, as classical theory can be regarded as a restriction of quantum theory, causality holds also in the classical case, although the determinism of the theory trivializes it. I then conclude by arguing that causality naturally establishes an arrow of time. This implies that the scenario of the 'block Universe' and the connected 'past hypothesis' are incompatible with causality, and thus with quantum theory: they are both doomed to remain mere interpretations and, as such, are not falsifiable, similar to the hypothesis of 'super-determinism'.This article is part of a discussion meeting issue 'Foundations of quantum mechanics and their impact on contemporary society'. © 2018 The Author(s).
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. Published 2013. This article is a US Government work and is in the public domain in the USA.
International Nuclear Information System (INIS)
Maund, J.B.
1979-01-01
Although the existence of tachyons is not ruled out by special relativity, it appears that causal paradoxes will arise if there are tachyons. The usual solutions to these paradoxes employ some form of the reinterpretation principle. In this paper it is argued first that, the principle is incoherent, second, that even if it is not, some causal paradoxes remain, and third, the most plausible ''solution,'' which appeals to boundary conditions of the universe, will conflict with special relativity
Dynamics and causality constraints
International Nuclear Information System (INIS)
Sousa, Manoelito M. de
2001-04-01
The physical meaning and the geometrical interpretation of causality implementation in classical field theories are discussed. Causality in field theory are kinematical constraints dynamically implemented via solutions of the field equation, but in a limit of zero-distance from the field sources part of these constraints carries a dynamical content that explains old problems of classical electrodynamics away with deep implications to the nature of physicals interactions. (author)
Hund, E; Massart, D L; Smeyers-Verbeke, J
1999-10-01
The H-point standard additions method (HPSAM) and two versions of the generalized H-point standard additions method (GHPSAM) are evaluated for the UV-analysis of two-component mixtures. Synthetic mixtures of anhydrous caffeine and phenazone as well as of atovaquone and proguanil hydrochloride were used. Furthermore, the method was applied to pharmaceutical formulations that contain these compounds as active drug substances. This paper shows both the difficulties that are related to the methods and the conditions by which acceptable results can be obtained.
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.
A quantum causal discovery algorithm
Giarmatzi, Christina; Costa, Fabio
2018-03-01
Finding a causal model for a set of classical variables is now a well-established task—but what about the quantum equivalent? Even the notion of a quantum causal model is controversial. Here, we present a causal discovery algorithm for quantum systems. The input to the algorithm is a process matrix describing correlations between quantum events. Its output consists of different levels of information about the underlying causal model. Our algorithm determines whether the process is causally ordered by grouping the events into causally ordered non-signaling sets. It detects if all relevant common causes are included in the process, which we label Markovian, or alternatively if some causal relations are mediated through some external memory. For a Markovian process, it outputs a causal model, namely the causal relations and the corresponding mechanisms, represented as quantum states and channels. Our algorithm opens the route to more general quantum causal discovery methods.
Olafsson, Gestur; Helgason, Sigurdur
1996-01-01
This book is intended to introduce researchers and graduate students to the concepts of causal symmetric spaces. To date, results of recent studies considered standard by specialists have not been widely published. This book seeks to bring this information to students and researchers in geometry and analysis on causal symmetric spaces.Includes the newest results in harmonic analysis including Spherical functions on ordered symmetric space and the holmorphic discrete series and Hardy spaces on compactly casual symmetric spacesDeals with the infinitesimal situation, coverings of symmetric spaces, classification of causal symmetric pairs and invariant cone fieldsPresents basic geometric properties of semi-simple symmetric spacesIncludes appendices on Lie algebras and Lie groups, Bounded symmetric domains (Cayley transforms), Antiholomorphic Involutions on Bounded Domains and Para-Hermitian Symmetric Spaces
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.
International Nuclear Information System (INIS)
Kondrashina, Yu.G.; Mustafina, A.R.; Devyatov, F.V.; Vul'fson, S.G.; Kazanskij Gosudarstvennyj Univ., Kazan
1995-01-01
Data of pH-metric and magnetooptical analyses were used to evaluate stability and structure of benzoate and aminobenzoate dysprosium (3) complexes in water and water - 80 vol.% DMSO (DMFA) mixtures. Factors, dictating change of complex structure and stability when passing from water to organic water solvents, are discussed. 19 refs.; 2 figs.; 1 tab
Czech Academy of Sciences Publication Activity Database
Líbalová, Helena; Krčková, S.; Uhlířová, Kateřina; Milcová, Alena; Schmuczerová, Jana; Cigánek, M.; Kléma, J.; Machala, M.; Šrám, Radim; Topinka, Jan
2014-01-01
Roč. 225, č. 3 (2014), s. 350-357 ISSN 0378-4274 R&D Projects: GA ČR GAP503/11/0142 Institutional support: RVO:68378041 Keywords : air pollutin * DNA adducts * complex mixtures Subject RIV: DN - Health Impact of the Environment Quality Impact factor: 3.262, year: 2014
International Nuclear Information System (INIS)
He, Maogang; Xin, Nan; Wang, Chengjie; Liu, Yang; Zhang, Ying; Liu, Xiangyang
2016-01-01
Graphical abstract: Experimental critical pressures of 2-butanol + hexane + heptane system. - Highlights: • Critical properties of six binary systems and two ternary systems were measured. • Six binary systems containing 2-butanol show non-ideal behavior in their T c –x 1 curves. • Non-ideal behavior of mixtures with 2-butanol relies on azeotropy. • Experimental data for binary systems were fitted well with Redlich–Kister equation. • Critical surfaces of ternary systems were plotted using the Cibulka’s expressions. - Abstract: In this work, we used a flow method for measurement of critical properties of six binary mixtures (2-butanol + cyclohexane, 2-butanol + hexane, 2-butanol + heptane, 2-butanol + octane, 2-butanol + nonane and 2-butanol + decane) and two ternary mixtures (2-butanol + hexane + heptane and 2-butanol + octane + decane). The critical properties were determined by observing the disappearance and reappearance of the gas–liquid phase meniscus in a quartz glass tube. The standard uncertainties of temperatures and pressures for both binary and ternary mixtures were estimated to be less than 0.2 K and 5.2 kPa, respectively. These critical data provide the boundaries of the two-phase regions of the related mixture systems. Six binary systems show non-ideal behaviors in the loci of critical temperatures. We used the Redlich–Kister equations to correlate the critical temperatures and pressures of these systems and listed the binary interaction parameters. The maximum average absolute deviation (AAD) of each binary system between experimental data and calculated results from Redlich–Kister equations is 0.038% for critical temperatures, and 0.244% for critical pressures. Moreover, the two ternary systems were newly reported and correlated by Cibulka’s and Singh’s expressions. The maximum AAD of critical temperatures and critical pressures are 0.103% and 0.433%, respectively.
Seilkop, Steven K; Campen, Matthew J; Lund, Amie K; McDonald, Jacob D; Mauderly, Joe L
2012-04-01
Combustion emissions cause pro-atherosclerotic responses in apolipoprotein E-deficient (ApoE/⁻) mice, but the causal components of these complex mixtures are unresolved. In studies previously reported, ApoE⁻/⁻ mice were exposed by inhalation 6 h/day for 50 consecutive days to multiple dilutions of diesel or gasoline exhaust, wood smoke, or simulated "downwind" coal emissions. In this study, the analysis of the combined four-study database using the Multiple Additive Regression Trees (MART) data mining approach to determine putative causal exposure components regardless of combustion source is reported. Over 700 physical-chemical components were grouped into 45 predictor variables. Response variables measured in aorta included endothelin-1, vascular endothelin growth factor, three matrix metalloproteinases (3, 7, 9), metalloproteinase inhibitor 2, heme-oxygenase-1, and thiobarbituric acid reactive substances. Two or three predictors typically explained most of the variation in response among the experimental groups. Overall, sulfur dioxide, ammonia, nitrogen oxides, and carbon monoxide were most highly predictive of responses, although their rankings differed among the responses. Consistent with the earlier finding that filtration of particles had little effect on responses, particulate components ranked third to seventh in predictive importance for the eight response variables. MART proved useful for identifying putative causal components, although the small number of pollution mixtures (4) can provide only suggestive evidence of causality. The potential independent causal contributions of these gases to the vascular responses, as well as possible interactions among them and other components of complex pollutant mixtures, warrant further evaluation.
Maximally causal quantum mechanics
International Nuclear Information System (INIS)
Roy, S.M.
1998-01-01
We present a new causal quantum mechanics in one and two dimensions developed recently at TIFR by this author and V. Singh. In this theory both position and momentum for a system point have Hamiltonian evolution in such a way that the ensemble of system points leads to position and momentum probability densities agreeing exactly with ordinary quantum mechanics. (author)
DEFF Research Database (Denmark)
Nielsen, Max; Jensen, Frank; Setälä, Jari
2011-01-01
to fish demand. On the German market for farmed trout and substitutes, it is found that supply sources, i.e. aquaculture and fishery, are not the only determinant of causality. Storing, tightness of management and aggregation level of integrated markets might also be important. The methodological...
Czech Academy of Sciences Publication Activity Database
Hvorecký, Juraj
2012-01-01
Roč. 19, Supp.2 (2012), s. 64-69 ISSN 1335-0668 R&D Projects: GA ČR(CZ) GAP401/12/0833 Institutional support: RVO:67985955 Keywords : conciousness * free will * determinism * causality Subject RIV: AA - Philosophy ; Religion
Explaining through causal mechanisms
Biesbroek, Robbert; Dupuis, Johann; Wellstead, Adam
2017-01-01
This paper synthesizes and builds on recent critiques of the resilience literature; namely that the field has largely been unsuccessful in capturing the complexity of governance processes, in particular cause–effects relationships. We demonstrate that absence of a causal model is reflected in the
X-ray fluorescence analysis of Cr6+ component in mixtures of Cr2O3 and K2CrO4
International Nuclear Information System (INIS)
Tochio, Tatsunori; Sakakura, Shusuke; Oohashi, Hirofumi
2010-01-01
X-ray fluorescence analysis using Cr K α spectra was applied to the determination of the mixing ratio of Cr 6+ to (Cr 6+ + Cr 3+ ) in several mixtures of K 2 CrO 4 and Cr 2 O 3 . Because the powder of K 2 CrO 4 contained large particles that were more than 50 μm in diameter, it was ground between a pestle and a mortar for about 8 h. The coarse particles still remaining were removed by using a sieve with 325-mesh (44 μm) in order to reduce the difference in absorption effects between emissions from Cr 6+ and those from Cr 3+ . The mixing ratio, K 2 CrO 4 /(K 2 CrO 4 + Cr 2 O 3 ), of the five mixtures investigated is 0.50, 0.40, 0.20, 0.10, and 0.05 in weight, respectively. Each spectrum obtained was analyzed by decomposing it into two reference spectra, those of the two pure materials, K 2 CrO 4 and Cr 2 O 3 , with a constant background. The results for the mixtures containing K 2 CrO 4 of more than 20 wt% are that the relative deviation from the true value is less than ∼5%. On the other hand, when the content of K 2 CrO 4 decreases to less than 10 wt%, the relative deviation gets so large as 20 - 25%. The error coming from a peak separation of spectrum involved in our results were estimated by applying our method to five sets of data for each mixture computationally generated, taking into account the uncertainty in total counts of real measurements. (author)
X-ray fluorescence analysis of Cr(6+) component in mixtures of Cr(2)O(3) and K(2)CrO(4).
Tochio, Tatsunori; Sakakura, Shusuke; Oohashi, Hirofumi; Mizota, Hirohisa; Zou, Yanhui; Ito, Yoshiaki; Fukushima, Sei; Tanuma, Shigeo; Shoji, Takashi; Fujimura, Hajime; Yamashita, Michiru
2010-01-01
X-ray fluorescence analysis using Cr K(alpha) spectra was applied to the determination of the mixing ratio of Cr(6+) to (Cr(6+) + Cr(3+)) in several mixtures of K(2)CrO(4) and Cr(2)O(3). Because the powder of K(2)CrO(4) contained large particles that were more than 50 microm in diameter, it was ground between a pestle and a mortar for about 8 h. The coarse particles still remaining were removed by using a sieve with 325-mesh (44 microm) in order to reduce the difference in absorption effects between emissions from Cr(6+) and those from Cr(3+). The mixing ratio, K(2)CrO(4)/(K(2)CrO(4) + Cr(2)O(3)), of the five mixtures investigated is 0.50, 0.40, 0.20, 0.10, and 0.05 in weight, respectively. Each spectrum obtained was analyzed by decomposing it into two reference spectra, those of the two pure materials, K(2)CrO(4) and Cr(2)O(3), with a constant background. The results for the mixtures containing K(2)CrO(4) of more than 20 wt% are that the relative deviation from the true value is less than approximately 5%. On the other hand, when the content of K(2)CrO(4) decreases to less than 10 wt%, the relative deviation gets so large as 20 - 25%. The error coming from a peak separation of spectrum involved in our results were estimated by applying our method to five sets of data for each mixture computationally generated, taking into account the uncertainty in total counts of real measurements.
Optimal causal inference: estimating stored information and approximating causal architecture.
Still, Susanne; Crutchfield, James P; Ellison, Christopher J
2010-09-01
We introduce an approach to inferring the causal architecture of stochastic dynamical systems that extends rate-distortion theory to use causal shielding--a natural principle of learning. We study two distinct cases of causal inference: optimal causal filtering and optimal causal estimation. Filtering corresponds to the ideal case in which the probability distribution of measurement sequences is known, giving a principled method to approximate a system's causal structure at a desired level of representation. We show that in the limit in which a model-complexity constraint is relaxed, filtering finds the exact causal architecture of a stochastic dynamical system, known as the causal-state partition. From this, one can estimate the amount of historical information the process stores. More generally, causal filtering finds a graded model-complexity hierarchy of approximations to the causal architecture. Abrupt changes in the hierarchy, as a function of approximation, capture distinct scales of structural organization. For nonideal cases with finite data, we show how the correct number of the underlying causal states can be found by optimal causal estimation. A previously derived model-complexity control term allows us to correct for the effect of statistical fluctuations in probability estimates and thereby avoid overfitting.
Illness causal beliefs in Turkish immigrants
Directory of Open Access Journals (Sweden)
Klimidis Steven
2007-07-01
Full Text Available 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 Melbourne. The socio-demographic characteristics of the sample were broadly similar to those of the Melbourne Turkish community. Five issues were examined: the structure of causal beliefs; the relative frequency of natural, supernatural and metaphysical beliefs; ascription of somatic, mental, or both somatic and mental conditions to the various causes; the correlations of belief types with socio-demographic, modernizing and acculturation variables; and the relationship between causal beliefs and current illness. Results Principal components analysis revealed two broad factors, accounting for 58 percent of the variation in scores on illness belief scales, distinctly interpretable as natural and supernatural beliefs. Second, beliefs in natural causes were more frequent than beliefs in supernatural causes. Third, some causal beliefs were commonly linked to both somatic and mental conditions while others were regarded as more specific to either somatic or mental disorders. Last, there was a range of correlations between endorsement of belief types and factors defining heterogeneity within the community, including with demographic factors, indicators of modernizing and acculturative processes, and the current presence of illness. Conclusion Results supported the classification of causal beliefs proposed by Murdock, Wilson & Frederick, with a division into natural and supernatural causes. While belief in natural causes is more common, belief in supernatural causes
Illness causal beliefs in Turkish immigrants.
Minas, Harry; Klimidis, Steven; Tuncer, Can
2007-07-24
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. Causal beliefs about somatic and mental illness were examined in a sample of 444 members of the Turkish population of Melbourne. The socio-demographic characteristics of the sample were broadly similar to those of the Melbourne Turkish community. Five issues were examined: the structure of causal beliefs; the relative frequency of natural, supernatural and metaphysical beliefs; ascription of somatic, mental, or both somatic and mental conditions to the various causes; the correlations of belief types with socio-demographic, modernizing and acculturation variables; and the relationship between causal beliefs and current illness. Principal components analysis revealed two broad factors, accounting for 58 percent of the variation in scores on illness belief scales, distinctly interpretable as natural and supernatural beliefs. Second, beliefs in natural causes were more frequent than beliefs in supernatural causes. Third, some causal beliefs were commonly linked to both somatic and mental conditions while others were regarded as more specific to either somatic or mental disorders. Last, there was a range of correlations between endorsement of belief types and factors defining heterogeneity within the community, including with demographic factors, indicators of modernizing and acculturative processes, and the current presence of illness. Results supported the classification of causal beliefs proposed by Murdock, Wilson & Frederick, with a division into natural and supernatural causes. While belief in natural causes is more common, belief in supernatural causes persists despite modernizing and acculturative influences. Different
Operator ordering and causality
Plimak, L. I.; Stenholm, S. T.
2011-01-01
It is shown that causality violations [M. de Haan, Physica 132A, 375, 397 (1985)], emerging when the conventional definition of the time-normal operator ordering [P.L.Kelley and W.H.Kleiner, Phys.Rev. 136, A316 (1964)] is taken outside the rotating wave approximation, disappear when the amended definition [L.P. and S.S., Annals of Physics, 323, 1989 (2008)] of this ordering is used.
International Nuclear Information System (INIS)
Lucas, J.R.
1984-01-01
Originating from lectures given to first year undergraduates reading physics and philosophy or mathematics and philosophy, formal logic is applied to issues and the elucidation of problems in space, time and causality. No special knowledge of relativity theory or quantum mechanics is needed. The text is interspersed with exercises and each chapter is preceded by a suggested 'preliminary reading' and followed by 'further reading' references. (U.K.)
International Nuclear Information System (INIS)
Sellami, Badreddine; Khazri, Abdelhafidh; Mezni, Amine; Louati, Héla; Dellali, Mohamed; Aissa, Patricia; Mahmoudi, Ezzeddine; Beyrem, Hamouda; Sheehan, David
2015-01-01
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
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.
Analogy in causal inference: rethinking Austin Bradford Hill's neglected consideration.
Weed, Douglas L
2018-05-01
The purpose of this article was to rethink and resurrect Austin Bradford Hill's "criterion" of analogy as an important consideration in causal inference. In epidemiology today, analogy is either completely ignored (e.g., in many textbooks), or equated with biologic plausibility or coherence, or aligned with the scientist's imagination. None of these examples, however, captures Hill's description of analogy. His words suggest that there may be something gained by contrasting two bodies of evidence, one from an established causal relationship, the other not. Coupled with developments in the methods of systematic assessments of evidence-including but not limited to meta-analysis-analogy can be restructured as a key component in causal inference. This new approach will require that a collection-a library-of known cases of causal inference (i.e., bodies of evidence involving established causal relationships) be developed. This library would likely include causal assessments by organizations such as the International Agency for Research on Cancer, the National Toxicology Program, and the United States Environmental Protection Agency. In addition, a process for describing key features of a causal relationship would need to be developed along with what will be considered paradigm cases of causation. Finally, it will be important to develop ways to objectively compare a "new" body of evidence with the relevant paradigm case of causation. Analogy, along with all other existing methods and causal considerations, may improve our ability to identify causal relationships. Copyright © 2018 Elsevier Inc. All rights reserved.
Martínez, A; Patrykiejew, A; Sokolowski, S
2003-01-01
We investigate adsorption in slit-like pores of model symmetric binary mixtures exhibiting demixing in bulk phase, by using a density functional approach. Our focus is on the evaluation of the first-order phase transitions in adsorbed fluids and the lines separating mixed and demixed phases. The scenario for phase transitions is sensitive to the pore width and to the energy of adsorption. Both these parameters can change the phase diagrams of the confined fluid. In particular, for relatively wide pores and for strong wall-fluid interactions, the demixing line can precede the first-order transition. Moreover, a competition between layering transitions and demixing within particular layers also leads to further enrichment of the phase diagram.
Causal events enter awareness faster than non-causal events
Directory of Open Access Journals (Sweden)
Pieter Moors
2017-01-01
Full Text Available Philosophers have long argued that causality cannot be directly observed but requires a conscious inference (Hume, 1967. Albert Michotte however developed numerous visual phenomena in which people seemed to perceive causality akin to primary visual properties like colour or motion (Michotte, 1946. Michotte claimed that the perception of causality did not require a conscious, deliberate inference but, working over 70 years ago, he did not have access to the experimental methods to test this claim. Here we employ Continuous Flash Suppression (CFS—an interocular suppression technique to render stimuli invisible (Tsuchiya & Koch, 2005—to test whether causal events enter awareness faster than non-causal events. We presented observers with ‘causal’ and ‘non-causal’ events, and found consistent evidence that participants become aware of causal events more rapidly than non-causal events. Our results suggest that, whilst causality must be inferred from sensory evidence, this inference might be computed at low levels of perceptual processing, and does not depend on a deliberative conscious evaluation of the stimulus. This work therefore supports Michotte’s contention that, like colour or motion, causality is an immediate property of our perception of the world.
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.
Causal inference in public health.
Glass, Thomas A; Goodman, Steven N; Hernán, Miguel A; Samet, Jonathan M
2013-01-01
Causal inference has a central role in public health; the determination that an association is causal indicates the possibility for intervention. We review and comment on the long-used guidelines for interpreting evidence as supporting a causal association and contrast them with the potential outcomes framework that encourages thinking in terms of causes that are interventions. We argue that in public health this framework is more suitable, providing an estimate of an action's consequences rather than the less precise notion of a risk factor's causal effect. A variety of modern statistical methods adopt this approach. When an intervention cannot be specified, causal relations can still exist, but how to intervene to change the outcome will be unclear. In application, the often-complex structure of causal processes needs to be acknowledged and appropriate data collected to study them. These newer approaches need to be brought to bear on the increasingly complex public health challenges of our globalized world.
The causal structure of utility conditionals.
Bonnefon, Jean-François; Sloman, Steven A
2013-01-01
The psychology of reasoning is increasingly considering agents' values and preferences, achieving greater integration with judgment and decision making, social cognition, and moral reasoning. Some of this research investigates utility conditionals, ''if p then q'' statements where the realization of p or q or both is valued by some agents. Various approaches to utility conditionals share the assumption that reasoners make inferences from utility conditionals based on the comparison between the utility of p and the expected utility of q. This article introduces a new parameter in this analysis, the underlying causal structure of the conditional. Four experiments showed that causal structure moderated utility-informed conditional reasoning. These inferences were strongly invited when the underlying structure of the conditional was causal, and significantly less so when the underlying structure of the conditional was diagnostic. This asymmetry was only observed for conditionals in which the utility of q was clear, and disappeared when the utility of q was unclear. Thus, an adequate account of utility-informed inferences conditional reasoning requires three components: utility, probability, and causal structure. Copyright © 2012 Cognitive Science Society, Inc.
Causal Diagrams for Empirical Research
Pearl, Judea
1994-01-01
The primary aim of this paper is to show how graphical models can be used as a mathematical language for integrating statistical and subject-matter information. In particular, the paper develops a principled, nonparametric framework for causal inference, in which diagrams are queried to determine if the assumptions available are sufficient for identifiying causal effects from non-experimental data. If so the diagrams can be queried to produce mathematical expressions for causal effects in ter...
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
Causal electromagnetic interaction equations
International Nuclear Information System (INIS)
Zinoviev, Yury M.
2011-01-01
For the electromagnetic interaction of two particles the relativistic causal quantum mechanics equations are proposed. These equations are solved for the case when the second particle moves freely. The initial wave functions are supposed to be smooth and rapidly decreasing at the infinity. This condition is important for the convergence of the integrals similar to the integrals of quantum electrodynamics. We also consider the singular initial wave functions in the particular case when the second particle mass is equal to zero. The discrete energy spectrum of the first particle wave function is defined by the initial wave function of the free-moving second particle. Choosing the initial wave functions of the free-moving second particle it is possible to obtain a practically arbitrary discrete energy spectrum.
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…
A Bayesian nonparametric approach to causal inference on quantiles.
Xu, Dandan; Daniels, Michael J; Winterstein, Almut G
2018-02-25
We propose a Bayesian nonparametric approach (BNP) for causal inference on quantiles in the presence of many confounders. In particular, we define relevant causal quantities and specify BNP models to avoid bias from restrictive parametric assumptions. We first use Bayesian additive regression trees (BART) to model the propensity score and then construct the distribution of potential outcomes given the propensity score using a Dirichlet process mixture (DPM) of normals model. We thoroughly evaluate the operating characteristics of our approach and compare it to Bayesian and frequentist competitors. We use our approach to answer an important clinical question involving acute kidney injury using electronic health records. © 2018, The International Biometric Society.
Mixtures Estimation and Applications
Mengersen, Kerrie; Titterington, Mike
2011-01-01
This book uses the EM (expectation maximization) algorithm to simultaneously estimate the missing data and unknown parameter(s) associated with a data set. The parameters describe the component distributions of the mixture; the distributions may be continuous or discrete. The editors provide a complete account of the applications, mathematical structure and statistical analysis of finite mixture distributions along with MCMC computational methods, together with a range of detailed discussions covering the applications of the methods and features chapters from the leading experts on the subject
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…
Friederich, Simon
There is widespread belief in a tension between quantum theory and special relativity, motivated by the idea that quantum theory violates J. S. Bell's criterion of local causality, which is meant to implement the causal structure of relativistic space-time. This paper argues that if one takes the
Covariation in Natural Causal Induction.
Cheng, Patricia W.; Novick, Laura R.
1991-01-01
Biases and models usually offered by cognitive and social psychology and by philosophy to explain causal induction are evaluated with respect to focal sets (contextually determined sets of events over which covariation is computed). A probabilistic contrast model is proposed as underlying covariation computation in natural causal induction. (SLD)
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.
Energy Technology Data Exchange (ETDEWEB)
Olea, Roberto S.G.
1991-12-31
This work describes a methodology for the identification of tri terpenes complex mixtures by {sup 13} C NMR. The use of {sup 13} C NMR techniques, such as obtention of noise decoupled spectra, DEPT 135 and DEPT 90 sequences, allowed the identification of components of triterpene mixtures with identical functionality through comparison of observed {sup 13} C NMR chemical shifts with {sup 13} C NMR chemical shifts reported in the literature. The method proved to be specially helpful in the identification of triterpenes by analysis of chemical shifts assignable to doubly bonded carbons, since the particular position of such double bonds is characteristic of some triterpene skeletons. Application of this methodology indicated the presence of bauerenol, {alpha}-amyrin and {beta}-amyrin in Acmanthera latifolis Griseb. (Malpighiaceae); of germanicone, lupenone, {alpha}-amyrenone and {beta}-amyrenone in Alibertia macrophylla A. Rich. (Rubiaceae); of {alpha}-amyrin acetate, lupeol acetate and {beta}-amyrin acetate in Vernonia polyanthes Schreb. (Asteraceae); {alpha}-amyrenone, {beta}-amyrenone, boehmerone, friedelin, lupenone, {alpha}-amyrin, {beta}-amyrin and glutinol in Scoparia dulcis L. (Scrophulariaceae). (author). 37 refs., 93 figs.
Energy Technology Data Exchange (ETDEWEB)
Olea, Roberto S.G.
1990-12-31
This work describes a methodology for the identification of tri terpenes complex mixtures by {sup 13} C NMR. The use of {sup 13} C NMR techniques, such as obtention of noise decoupled spectra, DEPT 135 and DEPT 90 sequences, allowed the identification of components of triterpene mixtures with identical functionality through comparison of observed {sup 13} C NMR chemical shifts with {sup 13} C NMR chemical shifts reported in the literature. The method proved to be specially helpful in the identification of triterpenes by analysis of chemical shifts assignable to doubly bonded carbons, since the particular position of such double bonds is characteristic of some triterpene skeletons. Application of this methodology indicated the presence of bauerenol, {alpha}-amyrin and {beta}-amyrin in Acmanthera latifolis Griseb. (Malpighiaceae); of germanicone, lupenone, {alpha}-amyrenone and {beta}-amyrenone in Alibertia macrophylla A. Rich. (Rubiaceae); of {alpha}-amyrin acetate, lupeol acetate and {beta}-amyrin acetate in Vernonia polyanthes Schreb. (Asteraceae); {alpha}-amyrenone, {beta}-amyrenone, boehmerone, friedelin, lupenone, {alpha}-amyrin, {beta}-amyrin and glutinol in Scoparia dulcis L. (Scrophulariaceae). (author). 37 refs., 93 figs.
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.)
Directory of Open Access Journals (Sweden)
A. Jackson Stenner
2013-08-01
Full Text Available Rasch’s unidimensional models for measurement show how to connect object measures (e.g., reader abilities, measurement mechanisms (e.g., machine-generated cloze reading items, and observational outcomes (e.g., counts correct on reading instruments. Substantive theory shows what interventions or manipulations to the measurement mechanism can be traded off against a change to the object measure to hold the observed outcome constant. A Rasch model integrated with a substantive theory dictates the form and substance of permissible interventions. Rasch analysis, absent construct theory and an associated specification equation, is a black box in which understanding may be more illusory than not. Finally, the quantitative hypothesis can be tested by comparing theory-based trade-off relations with observed trade-off relations. Only quantitative variables (as measured support such trade-offs. Note that to test the quantitative hypothesis requires more than manipulation of the algebraic equivalencies in the Rasch model or descriptively fitting data to the model. A causal Rasch model involves experimental intervention/manipulation on either reader ability or text complexity or a conjoint intervention on both simultaneously to yield a successful prediction of the resultant observed outcome (count correct. We conjecture that when this type of manipulation is introduced for individual reader text encounters and model predictions are consistent with observations, the quantitative hypothesis is sustained.
Stenner, A Jackson; Fisher, William P; Stone, Mark H; Burdick, Donald S
2013-01-01
Rasch's unidimensional models for measurement show how to connect object measures (e.g., reader abilities), measurement mechanisms (e.g., machine-generated cloze reading items), and observational outcomes (e.g., counts correct on reading instruments). Substantive theory shows what interventions or manipulations to the measurement mechanism can be traded off against a change to the object measure to hold the observed outcome constant. A Rasch model integrated with a substantive theory dictates the form and substance of permissible interventions. Rasch analysis, absent construct theory and an associated specification equation, is a black box in which understanding may be more illusory than not. Finally, the quantitative hypothesis can be tested by comparing theory-based trade-off relations with observed trade-off relations. Only quantitative variables (as measured) support such trade-offs. Note that to test the quantitative hypothesis requires more than manipulation of the algebraic equivalencies in the Rasch model or descriptively fitting data to the model. A causal Rasch model involves experimental intervention/manipulation on either reader ability or text complexity or a conjoint intervention on both simultaneously to yield a successful prediction of the resultant observed outcome (count correct). We conjecture that when this type of manipulation is introduced for individual reader text encounters and model predictions are consistent with observations, the quantitative hypothesis is sustained.
Stenner, A. Jackson; Fisher, William P.; Stone, Mark H.; Burdick, Donald S.
2013-01-01
Rasch's unidimensional models for measurement show how to connect object measures (e.g., reader abilities), measurement mechanisms (e.g., machine-generated cloze reading items), and observational outcomes (e.g., counts correct on reading instruments). Substantive theory shows what interventions or manipulations to the measurement mechanism can be traded off against a change to the object measure to hold the observed outcome constant. A Rasch model integrated with a substantive theory dictates the form and substance of permissible interventions. Rasch analysis, absent construct theory and an associated specification equation, is a black box in which understanding may be more illusory than not. Finally, the quantitative hypothesis can be tested by comparing theory-based trade-off relations with observed trade-off relations. Only quantitative variables (as measured) support such trade-offs. Note that to test the quantitative hypothesis requires more than manipulation of the algebraic equivalencies in the Rasch model or descriptively fitting data to the model. A causal Rasch model involves experimental intervention/manipulation on either reader ability or text complexity or a conjoint intervention on both simultaneously to yield a successful prediction of the resultant observed outcome (count correct). We conjecture that when this type of manipulation is introduced for individual reader text encounters and model predictions are consistent with observations, the quantitative hypothesis is sustained. PMID:23986726
International Nuclear Information System (INIS)
Crawford, G.N.
1981-01-01
The analysis is directed at a causal description of photon diffraction, which is explained in terms of a wave exerting real forces and providing actual guidance to each quantum of energy. An undulatory PSI wave is associated with each photon, and this wave is assumed to imply more than an informative probability function, so that it actually carries real energy, in much the same way as does an electro-magnetic wave. Whether or not it may be in some way related to the electromagnetic wave is left as a matter of on-going concern. A novel application of the concept of a minimum energy configuration is utilized; that is, a system of energy quanta seeks out relative positions and orientations of least mutual energy, much as an electron seeks its Bohr radius as a position of least mutual energy. Thus the concept implies more a guiding interaction of the PSI waves than an interfering cancellation of these waves. Similar concepts have been suggested by L. de Broglie and D. Bohm
["Karoshi" and causal relationships].
Hamajima, N
1992-08-01
This paper aims to introduce a measure for use by physicians for stating the degree of probable causal relationship for "Karoshi", ie, a sudden death from cerebrovascular diseases or ischemic heart diseases under occupational stresses, as well as to give a brief description for legal procedures associated with worker's compensation and civil trial in Japan. It is a well-used measure in epidemiology, "attributable risk percent (AR%)", which can be applied to describe the extent of contribution to "Karoshi" of the excess occupational burdens the deceased worker was forced to bear. Although several standards such as average occupational burdens for the worker, average occupational burdens for an ordinary worker, burdens in a nonoccupational life, and a complete rest, might be considered for the AR% estimation, the average occupational burdens for an ordinary worker should normally be utilized as a standard for worker's compensation. The adoption of AR% could be helpful for courts to make a consistent judgement whether "Karoshi" cases are compensatable or not.
Structure and Strength in Causal Induction
Griffiths, Thomas L.; Tenenbaum, Joshua B.
2005-01-01
We present a framework for the rational analysis of elemental causal induction--learning about the existence of a relationship between a single cause and effect--based upon causal graphical models. This framework makes precise the distinction between causal structure and causal strength: the difference between asking whether a causal relationship…
Dynamics of Quantum Causal Structures
Castro-Ruiz, Esteban; Giacomini, Flaminia; Brukner, Časlav
2018-01-01
It was recently suggested that causal structures are both dynamical, because of general relativity, and indefinite, because of quantum theory. The process matrix formalism furnishes a framework for quantum mechanics on indefinite causal structures, where the order between operations of local laboratories is not definite (e.g., one cannot say whether operation in laboratory A occurs before or after operation in laboratory B ). Here, we develop a framework for "dynamics of causal structures," i.e., for transformations of process matrices into process matrices. We show that, under continuous and reversible transformations, the causal order between operations is always preserved. However, the causal order between a subset of operations can be changed under continuous yet nonreversible transformations. An explicit example is that of the quantum switch, where a party in the past affects the causal order of operations of future parties, leading to a transition from a channel from A to B , via superposition of causal orders, to a channel from B to A . We generalize our framework to construct a hierarchy of quantum maps based on transformations of process matrices and transformations thereof.
Dynamics of Quantum Causal Structures
Directory of Open Access Journals (Sweden)
Esteban Castro-Ruiz
2018-03-01
Full Text Available It was recently suggested that causal structures are both dynamical, because of general relativity, and indefinite, because of quantum theory. The process matrix formalism furnishes a framework for quantum mechanics on indefinite causal structures, where the order between operations of local laboratories is not definite (e.g., one cannot say whether operation in laboratory A occurs before or after operation in laboratory B. Here, we develop a framework for “dynamics of causal structures,” i.e., for transformations of process matrices into process matrices. We show that, under continuous and reversible transformations, the causal order between operations is always preserved. However, the causal order between a subset of operations can be changed under continuous yet nonreversible transformations. An explicit example is that of the quantum switch, where a party in the past affects the causal order of operations of future parties, leading to a transition from a channel from A to B, via superposition of causal orders, to a channel from B to A. We generalize our framework to construct a hierarchy of quantum maps based on transformations of process matrices and transformations thereof.
Principal stratification in causal inference.
Frangakis, Constantine E; Rubin, Donald B
2002-03-01
Many scientific problems require that treatment comparisons be adjusted for posttreatment variables, but the estimands underlying standard methods are not causal effects. To address this deficiency, we propose a general framework for comparing treatments adjusting for posttreatment variables that yields principal effects based on principal stratification. Principal stratification with respect to a posttreatment variable is a cross-classification of subjects defined by the joint potential values of that posttreatment variable tinder each of the treatments being compared. Principal effects are causal effects within a principal stratum. The key property of principal strata is that they are not affected by treatment assignment and therefore can be used just as any pretreatment covariate. such as age category. As a result, the central property of our principal effects is that they are always causal effects and do not suffer from the complications of standard posttreatment-adjusted estimands. We discuss briefly that such principal causal effects are the link between three recent applications with adjustment for posttreatment variables: (i) treatment noncompliance, (ii) missing outcomes (dropout) following treatment noncompliance. and (iii) censoring by death. We then attack the problem of surrogate or biomarker endpoints, where we show, using principal causal effects, that all current definitions of surrogacy, even when perfectly true, do not generally have the desired interpretation as causal effects of treatment on outcome. We go on to forrmulate estimands based on principal stratification and principal causal effects and show their superiority.
Discrete causal theory emergent spacetime and the causal metric hypothesis
Dribus, Benjamin F
2017-01-01
This book evaluates and suggests potentially critical improvements to causal set theory, one of the best-motivated approaches to the outstanding problems of fundamental physics. Spacetime structure is of central importance to physics beyond general relativity and the standard model. The causal metric hypothesis treats causal relations as the basis of this structure. The book develops the consequences of this hypothesis under the assumption of a fundamental scale, with smooth spacetime geometry viewed as emergent. This approach resembles causal set theory, but differs in important ways; for example, the relative viewpoint, emphasizing relations between pairs of events, and relationships between pairs of histories, is central. The book culminates in a dynamical law for quantum spacetime, derived via generalized path summation.
Causal boundary for stably causal space-times
International Nuclear Information System (INIS)
Racz, I.
1987-12-01
The usual boundary constructions for space-times often yield an unsatisfactory boundary set. This problem is reviewed and a new solution is proposed. An explicit identification rule is given on the set of the ideal points of the space-time. This construction leads to a satisfactory boundary point set structure for stably causal space-times. The topological properties of the resulting causal boundary construction are examined. For the stably causal space-times each causal curve has a unique endpoint on the boundary set according to the extended Alexandrov topology. The extension of the space-time through the boundary is discussed. To describe the singularities the defined boundary sets have to be separated into two disjoint sets. (D.Gy.) 8 refs
Causal boundary for strongly causal spacetimes: Pt. 1
International Nuclear Information System (INIS)
Szabados, L.B.
1989-01-01
In a previous paper an analysis of the general structure of the causal boundary constructions and a new explicit identification rule, built up from elementary TIP-TIF gluings, were presented. In the present paper we complete our identification by incorporating TIP-TIP and TIF-TIF gluings as well. An asymptotic causality condition is found which, for physically important cases, ensures the uniqueness of the endpoints of the non-spacelike curves in the completed spacetime. (author)
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...
Functional equations with causal operators
Corduneanu, C
2003-01-01
Functional equations encompass most of the equations used in applied science and engineering: ordinary differential equations, integral equations of the Volterra type, equations with delayed argument, and integro-differential equations of the Volterra type. The basic theory of functional equations includes functional differential equations with causal operators. Functional Equations with Causal Operators explains the connection between equations with causal operators and the classical types of functional equations encountered by mathematicians and engineers. It details the fundamentals of linear equations and stability theory and provides several applications and examples.
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.
Causal Modelling in Evaluation Research.
Winteler, Adolf
1983-01-01
A study applied path analysis methods, using new techniques of causal analysis, to the problem of predicting the achievement, dropout rate, and satisfaction of university students. Besides providing explanations, the technique indicates possible remedial measures. (MSE)
Consciousness and the "Causal Paradox"
Velmans, Max
1996-01-01
Viewed from a first-person perspective consciousness appears to be necessary for complex, novel human activity - but viewed from a third-person perspective consciousness appears to play no role in the activity of brains, producing a "causal paradox". To resolve this paradox one needs to distinguish consciousness of processing from consciousness accompanying processing or causing processing. Accounts of consciousness/brain causal interactions switch between first- and third-person perspectives...
Dynamically redundant particle components in mixtures
International Nuclear Information System (INIS)
Lukacs, B.; Martinas, K.
1984-10-01
Examples are shown for cases in which the number of different kinds of particles in a system is not necessarily equal to the number of particle degrees of freedom in thermodynamical sense, and at the same time, the observed dynamics of the evolution of the system does not indicate a definite number of degrees of freedeom. The possibility for introducing dynamically redundant particles is discussed. (author)
Regression to Causality : Regression-style presentation influences causal attribution
DEFF Research Database (Denmark)
Bordacconi, Mats Joe; Larsen, Martin Vinæs
2014-01-01
of equivalent results presented as either regression models or as a test of two sample means. Our experiment shows that the subjects who were presented with results as estimates from a regression model were more inclined to interpret these results causally. Our experiment implies that scholars using regression...... models – one of the primary vehicles for analyzing statistical results in political science – encourage causal interpretation. Specifically, we demonstrate that presenting observational results in a regression model, rather than as a simple comparison of means, makes causal interpretation of the results...... more likely. Our experiment drew on a sample of 235 university students from three different social science degree programs (political science, sociology and economics), all of whom had received substantial training in statistics. The subjects were asked to compare and evaluate the validity...
Putting a cap on causality violations in causal dynamical triangulations
International Nuclear Information System (INIS)
Ambjoern, Jan; Loll, Renate; Westra, Willem; Zohren, Stefan
2007-01-01
The formalism of causal dynamical triangulations (CDT) provides us with a non-perturbatively defined model of quantum gravity, where the sum over histories includes only causal space-time histories. Path integrals of CDT and their continuum limits have been studied in two, three and four dimensions. Here we investigate a generalization of the two-dimensional CDT model, where the causality constraint is partially lifted by introducing branching points with a weight g s , and demonstrate that the system can be solved analytically in the genus-zero sector. The solution is analytic in a neighborhood around weight g s = 0 and cannot be analytically continued to g s = ∞, where the branching is entirely geometric and where one would formally recover standard Euclidean two-dimensional quantum gravity defined via dynamical triangulations or Liouville theory
Bayesian networks improve causal environmental ...
Rule-based weight of evidence approaches to ecological risk assessment may not account for uncertainties and generally lack probabilistic integration of lines of evidence. Bayesian networks allow causal inferences to be made from evidence by including causal knowledge about the problem, using this knowledge with probabilistic calculus to combine multiple lines of evidence, and minimizing biases in predicting or diagnosing causal relationships. Too often, sources of uncertainty in conventional weight of evidence approaches are ignored that can be accounted for with Bayesian networks. Specifying and propagating uncertainties improve the ability of models to incorporate strength of the evidence in the risk management phase of an assessment. Probabilistic inference from a Bayesian network allows evaluation of changes in uncertainty for variables from the evidence. The network structure and probabilistic framework of a Bayesian approach provide advantages over qualitative approaches in weight of evidence for capturing the impacts of multiple sources of quantifiable uncertainty on predictions of ecological risk. Bayesian networks can facilitate the development of evidence-based policy under conditions of uncertainty by incorporating analytical inaccuracies or the implications of imperfect information, structuring and communicating causal issues through qualitative directed graph formulations, and quantitatively comparing the causal power of multiple stressors on value
Causality and analyticity in optics
International Nuclear Information System (INIS)
Nussenzveig, H.M.
In order to provide an overall picture of the broad range of optical phenomena that are directly linked with the concepts of causality and analyticity, the following topics are briefly reviewed, emphasizing recent developments: 1) Derivation of dispersion relations for the optical constants of general linear media from causality. Application to the theory of natural optical activity. 2) Derivation of sum rules for the optical constants from causality and from the short-time response function (asymptotic high-frequency behavior). Average spectral behavior of optical media. Applications. 3) Role of spectral conditions. Analytic properties of coherence functions in quantum optics. Reconstruction theorem.4) Phase retrieval problems. 5) Inverse scattering problems. 6) Solution of nonlinear evolution equations in optics by inverse scattering methods. Application to self-induced transparency. Causality in nonlinear wave propagation. 7) Analytic continuation in frequency and angular momentum. Complex singularities. Resonances and natural-mode expansions. Regge poles. 8) Wigner's causal inequality. Time delay. Spatial displacements in total reflection. 9) Analyticity in diffraction theory. Complex angular momentum theory of Mie scattering. Diffraction as a barrier tunnelling effect. Complex trajectories in optics. (Author) [pt
Hierarchical organisation of causal graphs
International Nuclear Information System (INIS)
Dziopa, P.
1993-01-01
This paper deals with the design of a supervision system using a hierarchy of models formed by graphs, in which the variables are the nodes and the causal relations between the variables of the arcs. To obtain a representation of the variables evolutions which contains only the relevant features of their real evolutions, the causal relations are completed with qualitative transfer functions (QTFs) which produce roughly the behaviour of the classical transfer functions. Major improvements have been made in the building of the hierarchical organization. First, the basic variables of the uppermost level and the causal relations between them are chosen. The next graph is built by adding intermediary variables to the upper graph. When the undermost graph has been built, the transfer functions parameters corresponding to its causal relations are identified. The second task consists in the upwelling of the information from the undermost graph to the uppermost one. A fusion procedure of the causal relations has been designed to compute the QFTs relevant for each level. This procedure aims to reduce the number of parameters needed to represent an evolution at a high level of abstraction. These techniques have been applied to the hierarchical modelling of nuclear process. (authors). 8 refs., 12 figs
Hyperactivity: is candy causal?
Krummel, D A; Seligson, F H; Guthrie, H A
1996-01-01
Adverse behavioral responses to ingestion of any kind of candy have been reported repeatedly in the lay press. Parents and teachers alike attribute excessive motor activity and other disruptive behaviors to candy consumption. However, anecdotal observations of this kind need to be tested scientifically before conclusions can be drawn, and criteria for interpreting diet behavior studies must be rigorous. Ingredients in nonchocolate candy (sugar, artificial food colors), components in chocolate candy (sugar, artificial food colors in coatings, caffeine), and chocolate itself have been investigated for any adverse effects on behavior. Feingold theorized that food additives (artificial colors and flavors) and natural salicylates caused hyperactivity in children and elimination of these components would result in dramatic improvement in behavior. Numerous double-blind studies of the Feingold hypothesis have led to the rejection of the idea that this elimination diet has any benefit beyond the normal placebo effect. Although sugar is widely believed by the public to cause hyperactive behavior, this has not been scientifically substantiated. Twelve double-blind, placebo-controlled studies of sugar challenges failed to provide any evidence that sugar ingestion leads to untoward behavior in children with Attention-Deficit Hyperactivity Disorder or in normal children. Likewise, none of the studies testing candy or chocolate found any negative effect of these foods on behavior. For children with behavioral problems, diet-oriented treatment does not appear to be appropriate. Rather, clinicians treating these children recommend a multidisciplinary approach. The goal of diet treatment is to ensure a balanced diet with adequate energy and nutrients for optimal growth.
Entropy for theories with indefinite causal structure
International Nuclear Information System (INIS)
Markes, Sonia; Hardy, Lucien
2011-01-01
Any theory with definite causal structure has a defined past and future, be it defined by light cones or an absolute time scale. Entropy is a concept that has traditionally been reliant on a definite notion of causality. However, without a definite notion of causality, the concept of entropy is not all lost. Indefinite causal structure results from combining probabilistic predictions and dynamical space-time. The causaloid framework lays the mathematical groundwork to be able to treat indefinite causal structure. In this paper, we build on the causaloid mathematics and define a causally-unbiased entropy for an indefinite causal structure. In defining a causally-unbiased entropy, there comes about an emergent idea of causality in the form of a measure of causal connectedness, termed the Q factor.
mediation: R package for causal mediation analysis
Tingley, Dustin; Yamamoto, Teppei; Hirose, Kentaro; Keele, Luke; Imai, Kosuke
2012-01-01
In this paper, we describe the R package mediation for conducting causal mediation analysis in applied empirical research. In many scientific disciplines, the goal of researchers is not only estimating causal effects of a treatment but also understanding the process in which the treatment causally affects the outcome. Causal mediation analysis is frequently used to assess potential causal mechanisms. The mediation package implements a comprehensive suite of statistical tools for conducting su...
International Nuclear Information System (INIS)
Machrafi, Hatim
2008-01-01
The parameters that are present in exhaust gas recirculation (EGR) are believed to provide an important contribution to control the auto-ignition process of the homogeneous charge compression ignition (HCCI) in an engine. For the investigation of the behaviour of the auto-ignition process, a kinetic multi-component mechanism has been developed in former work, containing 62 reactions and 49 species for mixtures of n-heptane, iso-octane and toluene. This paper presents an experimental validation of this mechanism, comparing the calculated pressure, heat release, ignition delays and CO 2 emissions with experimental data performed on a HCCI engine. The validation is performed in a broad range of EGR parameters by varying the dilution by N 2 and CO 2 from 0 to 46 vol.%, changing the EGR temperature from 30 to 120 deg. C, altering the addition of CO and NO from 0 to 170 ppmv and varying the addition of CH 2 O from 0 to 1400 ppmv. These validations were performed respecting the HCCI conditions for the inlet temperature and the equivalence ratio. The results showed that the mechanism is validated experimentally in dilution ranges going up to 21-30 vol.%, depending on the species of dilution and over the whole range of the EGR temperature. The mechanism is validated over the whole range of CO and CH 2 O addition. As for the addition of NO, the mechanism is validated quantitatively up to 50 ppmv and qualitatively up to 170 ppmv
Directory of Open Access Journals (Sweden)
José Tomás Alvarado
2009-08-01
Full Text Available This work presents a causal conception of metaphysical modality in which a state of affairs is metaphysically possible if and only if it can be caused (in the past, the present or the future by current entities. The conception is contrasted with what is called the “combinatorial” conception of modality, in which everything can co-exist with anything else. This work explains how the notion of ‘causality’ should be construed in the causal theory, what difference exists between modalities thus defined from nomological modality, how accessibility relations between possible worlds should be interpreted, and what is the relation between the causal conception and the necessity of origin.
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.
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. PMID:25389398
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.
Quantum theory and local causality
Hofer-Szabó, Gábor
2018-01-01
This book summarizes the results of research the authors have pursued in the past years on the problem of implementing Bell's notion of local causality in local physical theories and relating it to other important concepts and principles in the foundations of physics such as the Common Cause Principle, Bell's inequalities, the EPR (Einstein-Podolsky-Rosen) scenario, and various other locality and causality concepts. The book is intended for philosophers of science with an interest in the formal background of sciences, philosophers of physics and physicists working in foundation of physics.
International Nuclear Information System (INIS)
1981-01-01
Apparatus is described for the separation of a gaseous plasma mixture into components in some of which the original concentration of a specific ion has been greatly increased or decreased, comprising: a source for converting the gaseous mixture into a train of plasma packets; an open-ended vessel with a main section and at least one branch section, adapted to enclose along predetermined tracks the original plasma packets in the main section, and the separated plasma components in the branch sections; drive means for generating travelling magnetic waves along the predetermined tracks with the magnetic flux vector of the waves transverse to each of the tracks; and means for maintaining phase coherence between the plasma packets and the magnetic waves at a value needed for accelerating the components of the packets to different velocities and in such different directions that the plasma of each packet is divided into distinctly separate packets in some of which the original concentration of a specific ion has been greatly increased or decreased, and which plasma packets are collected from the branch sections of the vessels. (author)
Causal Reasoning with Mental Models
2014-08-08
The initial rubric is equivalent to an exclusive disjunction between the two causal assertions. It 488 yields the following two mental models: 489...are 575 important, whereas the functions of artifacts are important (Ahn, 1998). A genetic code is 576 accordingly more critical to being a goat than
Identity, causality, and pronoun ambiguity.
Sagi, Eyal; Rips, Lance J
2014-10-01
This article looks at the way people determine the antecedent of a pronoun in sentence pairs, such as: Albert invited Ron to dinner. He spent hours cleaning the house. The experiment reported here is motivated by the idea that such judgments depend on reasoning about identity (e.g., the identity of the he who cleaned the house). Because the identity of an individual over time depends on the causal-historical path connecting the stages of the individual, the correct antecedent will also depend on causal connections. The experiment varied how likely it is that the event of the first sentence (e.g., the invitation) would cause the event of the second (the house cleaning) for each of the two individuals (the likelihood that if Albert invited Ron to dinner, this would cause Albert to clean the house, versus cause Ron to clean the house). Decisions about the antecedent followed causal likelihood. A mathematical model of causal identity accounted for most of the key aspects of the data from the individual sentence pairs. Copyright © 2014 Cognitive Science Society, Inc.
Charged singularities: the causality violation
Energy Technology Data Exchange (ETDEWEB)
De Felice, F; Nobili, L [Padua Univ. (Italy). Ist. di Fisica; Calvani, M [Padua Univ. (Italy). Ist. di Astronomia
1980-12-01
A search is made for examples of particle trajectories which, approaching a naked singularity from infinity, make up for lost time before going back to infinity. In the Kerr-Newman metric a whole family of such trajectories is found showing that the causality violation is indeed a non-avoidable pathology.
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.
Entanglement, holography and causal diamonds
Energy Technology Data Exchange (ETDEWEB)
Boer, Jan de [Institute of Physics, Universiteit van Amsterdam,Science Park 904, 1090 GL Amsterdam (Netherlands); Haehl, Felix M. [Centre for Particle Theory & Department of Mathematical Sciences, Durham University,South Road, Durham DH1 3LE (United Kingdom); Heller, Michal P.; Myers, Robert C. [Perimeter Institute for Theoretical Physics,31 Caroline Street North, Waterloo, Ontario N2L 2Y5 (Canada)
2016-08-29
We argue that the degrees of freedom in a d-dimensional CFT can be re-organized in an insightful way by studying observables on the moduli space of causal diamonds (or equivalently, the space of pairs of timelike separated points). This 2d-dimensional space naturally captures some of the fundamental nonlocality and causal structure inherent in the entanglement of CFT states. For any primary CFT operator, we construct an observable on this space, which is defined by smearing the associated one-point function over causal diamonds. Known examples of such quantities are the entanglement entropy of vacuum excitations and its higher spin generalizations. We show that in holographic CFTs, these observables are given by suitably defined integrals of dual bulk fields over the corresponding Ryu-Takayanagi minimal surfaces. Furthermore, we explain connections to the operator product expansion and the first law of entanglement entropy from this unifying point of view. We demonstrate that for small perturbations of the vacuum, our observables obey linear two-derivative equations of motion on the space of causal diamonds. In two dimensions, the latter is given by a product of two copies of a two-dimensional de Sitter space. For a class of universal states, we show that the entanglement entropy and its spin-three generalization obey nonlinear equations of motion with local interactions on this moduli space, which can be identified with Liouville and Toda equations, respectively. This suggests the possibility of extending the definition of our new observables beyond the linear level more generally and in such a way that they give rise to new dynamically interacting theories on the moduli space of causal diamonds. Various challenges one has to face in order to implement this idea are discussed.
The 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...
Energy Technology Data Exchange (ETDEWEB)
Machrafi, Hatim [LGPPTS, Ecole Nationale Superieure de Chimie de Paris/ Universite Pierre et Marie Curie (Paris 6), 11, rue de Pierre et Marie Curie, 75231 Paris Cedex 05 (France)
2008-11-15
The parameters that are present in exhaust gas recirculation (EGR) are believed to provide an important contribution to control the auto-ignition process of the homogeneous charge compression ignition (HCCI) in an engine. For the investigation of the behaviour of the auto-ignition process, a kinetic multi-component mechanism has been developed in former work, containing 62 reactions and 49 species for mixtures of n-heptane, iso-octane and toluene. This paper presents an experimental validation of this mechanism, comparing the calculated pressure, heat release, ignition delays and CO{sub 2} emissions with experimental data performed on a HCCI engine. The validation is performed in a broad range of EGR parameters by varying the dilution by N{sub 2} and CO{sub 2} from 0 to 46 vol.%, changing the EGR temperature from 30 to 120 C, altering the addition of CO and NO from 0 to 170 ppmv and varying the addition of CH{sub 2}O from 0 to 1400 ppmv. These validations were performed respecting the HCCI conditions for the inlet temperature and the equivalence ratio. The results showed that the mechanism is validated experimentally in dilution ranges going up to 21-30 vol.%, depending on the species of dilution and over the whole range of the EGR temperature. The mechanism is validated over the whole range of CO and CH{sub 2}O addition. As for the addition of NO, the mechanism is validated quantitatively up to 50 ppmv and qualitatively up to 170 ppmv. (author)
4. VACUI RATIONE. OBSERVABILITY AND CAUSAL POWERS OF A NONENTITY
Directory of Open Access Journals (Sweden)
Enrico Pasini
2013-08-01
Full Text Available The notion of the vacuum is transmitted to early modern natural philosophy mainly in two versions: macroscopic void space, as a component of standard atomist theories; and microscopic void spaces interspersed within matter, that according to the pneumatic literature can be forcefully collected into artificial vacua of the first sort. Both kinds of natural vacua are directly or indirectly connected to causal effects, that may be attributed to different causal powers, directly or indirectly pertaining to the vacuum itself. The question also arises whether the purported physical vacuum ought to be observable, either directly or through the presence versus the testable absence of the same causal powers. In contrast to natural philosophy, within the medical discourse—more open to different interpretations of phenomena connected with the vacuum—even the question of observability might present unexpected facets.
Deciding which chemical mixtures risk assessment methods work best for what mixtures
International Nuclear Information System (INIS)
Teuschler, Linda K.
2007-01-01
The most commonly used chemical mixtures risk assessment methods involve simple notions of additivity and toxicological similarity. Newer methods are emerging in response to the complexities of chemical mixture exposures and effects. Factors based on both science and policy drive decisions regarding whether to conduct a chemical mixtures risk assessment and, if so, which methods to employ. Scientific considerations are based on positive evidence of joint toxic action, elevated human exposure conditions or the potential for significant impacts on human health. Policy issues include legislative drivers that may mandate action even though adequate toxicity data on a specific mixture may not be available and risk assessment goals that impact the choice of risk assessment method to obtain the amount of health protection desired. This paper discusses three important concepts used to choose among available approaches for conducting a chemical mixtures risk assessment: (1) additive joint toxic action of mixture components; (2) toxicological interactions of mixture components; and (3) chemical composition of complex mixtures. It is proposed that scientific support for basic assumptions used in chemical mixtures risk assessment should be developed by expert panels, risk assessment methods experts, and laboratory toxicologists. This is imperative to further develop and refine quantitative methods and provide guidance on their appropriate applications. Risk assessors need scientific support for chemical mixtures risk assessment methods in the form of toxicological data on joint toxic action for high priority mixtures, statistical methods for analyzing dose-response for mixtures, and toxicological and statistical criteria for determining sufficient similarity of complex mixtures
Spectral dimension in causal set quantum gravity
International Nuclear Information System (INIS)
Eichhorn, Astrid; Mizera, Sebastian
2014-01-01
We evaluate the spectral dimension in causal set quantum gravity by simulating random walks on causal sets. In contrast to other approaches to quantum gravity, we find an increasing spectral dimension at small scales. This observation can be connected to the nonlocality of causal set theory that is deeply rooted in its fundamentally Lorentzian nature. Based on its large-scale behaviour, we conjecture that the spectral dimension can serve as a tool to distinguish causal sets that approximate manifolds from those that do not. As a new tool to probe quantum spacetime in different quantum gravity approaches, we introduce a novel dimensional estimator, the causal spectral dimension, based on the meeting probability of two random walkers, which respect the causal structure of the quantum spacetime. We discuss a causal-set example, where the spectral dimension and the causal spectral dimension differ, due to the existence of a preferred foliation. (paper)
On causal nonrelativistic classical electrodynamics
International Nuclear Information System (INIS)
Goedecke, G.H.
1984-01-01
The differential-difference (DD) motion equations of the causal nonrelativistic classical electrodynamics developed by the author in 1975 are shown to possess only nonrunaway, causal solutions with no discontinuities in particle velocity or position. As an example, the DD equation solution for the problem of an electromagnetic shock incident on an initially stationary charged particle is contrasted with the standard Abraham-Lorentz equation solution. The general Cauchy problem for these DD motion equations is discussed. In general, in order to uniquely determine a solution, the initial data must be more detailed than the standard Cauchy data of initial position and velocity. Conditions are given under which the standard Cauchy data will determine the DD equation solutions to sufficient practical accuracy
Quantum mechanics, relativity and causality
International Nuclear Information System (INIS)
Tati, Takao.
1975-07-01
In quantum mechanics, the state is prepared by a measurement on a space-like surface sigma. What is that determines the surface sigma on which the measurement prepares the state It is considered either a mechanism proper to the measuring process (apparatus) or a universal property of space-time. In the former case, problems arise, concerning causality or conservation of probability due to that the velocity of reduction of wave-packet is considered to exceed the light velocity. The theory of finite degree of freedom proposed previously belongs to the latter case. In this theory, the surface sigma is restricted to the hyper-plane perpendicular to a universal time-like vector governing causal relations. We propose an experiment to discriminate between the above-mentioned two cases and to test the existence of the universal time-like vector. (auth.)
Causal Set Generator and Action Computer
Cunningham, William; Krioukov, Dmitri
2017-01-01
The causal set approach to quantum gravity has gained traction over the past three decades, but numerical experiments involving causal sets have been limited to relatively small scales. The software suite presented here provides a new framework for the generation and study of causal sets. Its efficiency surpasses previous implementations by several orders of magnitude. We highlight several important features of the code, including the compact data structures, the $O(N^2)$ causal set generatio...
Some properties of explosive mixtures containing peroxides
International Nuclear Information System (INIS)
Zeman, Svatopluk; Trzcinski, Waldemar A.; Matyas, Robert
2008-01-01
This study concerns mixtures of triacetone triperoxide (3,3,6,6,9,9-hexamethyl-1,2,4,5,7,8-hexoxonane, TATP) and ammonium nitrate (AN) with added water (W), as the case may be, and dry mixtures of TATP with urea nitrate (UN). Relative performances (RP) of the mixtures and their individual components, relative to TNT, were determined by means of ballistic mortar. The detonation energies, E 0 , and detonation velocities, D, were calculated for the mixtures studied by means of the thermodynamic code CHEETAH. Relationships have been found and are discussed between the RP and the E 0 values related to unit volume of gaseous products of detonation of these mixtures. These relationships together with those between RP and oxygen balance values of the mixtures studied indicate different types of participation of AN and UN in the explosive decomposition of the respective mixtures. Dry TATP/UN mixtures exhibit lower RP than analogous mixtures TATP/AN containing up to 25% of water. Depending on the water content, the TATP/AN mixtures possess higher detonability values than the ANFO explosives. A semi-logarithmic relationship between the D values and oxygen coefficients has been derived for all the mixtures studied at the charge density of 1000 kg m -3 . Among the mixtures studied, this relationship distinguishes several samples of the type of 'tertiary explosives' as well as samples that approach 'high explosives' in their performances and detonation velocities
Modeling of causality with metamaterials
International Nuclear Information System (INIS)
Smolyaninov, Igor I
2013-01-01
Hyperbolic metamaterials may be used to model a 2 + 1-dimensional Minkowski space–time in which the role of time is played by one of the spatial coordinates. When a metamaterial is built and illuminated with a coherent extraordinary laser beam, the stationary pattern of light propagation inside the metamaterial may be treated as a collection of particle world lines, which represents a complete ‘history’ of this 2 + 1-dimensional space–time. While this model may be used to build interesting space–time analogs, such as metamaterial ‘black holes’ and a metamaterial ‘big bang’, it lacks causality: since light inside the metamaterial may propagate back and forth along the ‘timelike’ spatial coordinate, events in the ‘future’ may affect events in the ‘past’. Here we demonstrate that a more sophisticated metamaterial model may fix this deficiency via breaking the mirror and temporal (PT) symmetries of the original model and producing one-way propagation along the ‘timelike’ spatial coordinate. The resulting 2 + 1-dimensional Minkowski space–time appears to be causal. This scenario may be considered as a metamaterial model of the Wheeler–Feynman absorber theory of causality. (paper)
THE CAUSAL ANALYSIS / DIAGNOSIS DECISION ...
CADDIS is an on-line decision support system that helps investigators in the regions, states and tribes find, access, organize, use and share information to produce causal evaluations in aquatic systems. It is based on the US EPA's Stressor Identification process which is a formal method for identifying causes of impairments in aquatic systems. CADDIS 2007 increases access to relevant information useful for causal analysis and provides methods and tools that practitioners can use to analyze their own data. The new Candidate Cause section provides overviews of commonly encountered causes of impairments to aquatic systems: metals, sediments, nutrients, flow alteration, temperature, ionic strength, and low dissolved oxygen. CADDIS includes new Conceptual Models that illustrate the relationships from sources to stressors to biological effects. An Interactive Conceptual Model for phosphorus links the diagram with supporting literature citations. The new Analyzing Data section helps practitioners analyze their data sets and interpret and use those results as evidence within the USEPA causal assessment process. Downloadable tools include a graphical user interface statistical package (CADStat), and programs for use with the freeware R statistical package, and a Microsoft Excel template. These tools can be used to quantify associations between causes and biological impairments using innovative methods such as species-sensitivity distributions, biological inferenc
Causal structure of analogue spacetimes
International Nuclear Information System (INIS)
Barcelo, Carlos; Liberati, Stefano; Sonego, Sebastiano; Visser, Matt
2004-01-01
The so-called 'analogue models of general relativity' provide a number of specific physical systems, well outside the traditional realm of general relativity, that nevertheless are well-described by the differential geometry of curved spacetime. Specifically, the propagation of perturbations in these condensed matter systems is described by 'effective metrics' that carry with them notions of 'causal structure' as determined by an exchange of quasi-particles. These quasi-particle-induced causal structures serve as specific examples of what can be done in the presence of a Lorentzian metric without having recourse to the Einstein equations of general relativity. (After all, the underlying analogue model is governed by its own specific physics, not necessarily by the Einstein equations.) In this paper we take a careful look at what can be said about the causal structure of analogue spacetimes, focusing on those containing quasi-particle horizons, both with a view to seeing what is different from standard general relativity, and what the similarities might be. For definiteness, and because the physics is particularly simple to understand, we will phrase much of the discussion in terms of acoustic disturbances in moving fluids, where the underlying physics is ordinary fluid mechanics, governed by the equations of traditional hydrodynamics, and the relevant quasi-particles are the phonons. It must however be emphasized that this choice of example is only for the sake of pedagogical simplicity and that our considerations apply generically to wide classes of analogue spacetimes
Obesity and infection: reciprocal causality.
Hainer, V; Zamrazilová, H; Kunešová, M; Bendlová, B; Aldhoon-Hainerová, I
2015-01-01
Associations between different infectious agents and obesity have been reported in humans for over thirty years. In many cases, as in nosocomial infections, this relationship reflects the greater susceptibility of obese individuals to infection due to impaired immunity. In such cases, the infection is not related to obesity as a causal factor but represents a complication of obesity. In contrast, several infections have been suggested as potential causal factors in human obesity. However, evidence of a causal linkage to human obesity has only been provided for adenovirus 36 (Adv36). This virus activates lipogenic and proinflammatory pathways in adipose tissue, improves insulin sensitivity, lipid profile and hepatic steatosis. The E4orf1 gene of Adv36 exerts insulin senzitizing effects, but is devoid of its pro-inflammatory modalities. The development of a vaccine to prevent Adv36-induced obesity or the use of E4orf1 as a ligand for novel antidiabetic drugs could open new horizons in the prophylaxis and treatment of obesity and diabetes. More experimental and clinical studies are needed to elucidate the mutual relations between infection and obesity, identify additional infectious agents causing human obesity, as well as define the conditions that predispose obese individuals to specific infections.
Behavioural Pattern of Causality Parameter of Autoregressive ...
African Journals Online (AJOL)
In this paper, a causal form of Autoregressive Moving Average process, ARMA (p, q) of various orders and behaviour of the causality parameter of ARMA model is investigated. It is deduced that the behaviour of causality parameter ψi depends on positive and negative values of autoregressive parameter φ and moving ...
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.…
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.
Causal knowledge and reasoning in decision making
Hagmayer, Y.; Witteman, C.L.M.
2017-01-01
Normative causal decision theories argue that people should use their causal knowledge in decision making. Based on these ideas, we argue that causal knowledge and reasoning may support and thereby potentially improve decision making based on expected outcomes, narratives, and even cues. We will
A theory of causal learning in children: causal maps and Bayes nets.
Gopnik, Alison; Glymour, Clark; Sobel, David M; Schulz, Laura E; Kushnir, Tamar; Danks, David
2004-01-01
The authors outline a cognitive and computational account of causal learning in children. They propose that children use specialized cognitive systems that allow them to recover an accurate "causal map" of the world: an abstract, coherent, learned representation of the causal relations among events. This kind of knowledge can be perspicuously understood in terms of the formalism of directed graphical causal models, or Bayes nets. Children's causal learning and inference may involve computations similar to those for learning causal Bayes nets and for predicting with them. Experimental results suggest that 2- to 4-year-old children construct new causal maps and that their learning is consistent with the Bayes net formalism.
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.
Seilkop, Steven K.; Campen, Matthew J.; Lund, Amie K.; McDonald, Jacob D.; Mauderly, Joe L.
2012-01-01
Combustion emissions cause pro-atherosclerotic responses in apolipoprotein E-deficient (ApoE/−) mice, but the causal components of these complex mixtures are unresolved. In studies previously reported, ApoE−/− mice were exposed by inhalation 6 h/day for 50 consecutive days to multiple dilutions of diesel or gasoline exhaust, wood smoke, or simulated “downwind” coal emissions. In this study, the analysis of the combined four-study database using the Multiple Additive Regression Trees (MART) da...
A theory of causal learning in children: Causal maps and Bayes nets
Gopnik, A; Glymour, C; Sobel, D M; Schulz, L E; Kushnir, T; Danks, D
2004-01-01
The authors outline a cognitive and computational account of causal learning in children. They propose that children use specialized cognitive systems that allow them to recover an accurate "causal map" of the world: an abstract, coherent, learned representation of the causal relations among events. This kind of knowledge can be perspicuously understood in terms of the formalism of directed graphical causal models, or Bayes nets. Children's causal learning and inference may involve computatio...
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.
Causal mediation analysis with multiple causally non-ordered mediators.
Taguri, Masataka; Featherstone, John; Cheng, Jing
2018-01-01
In many health studies, researchers are interested in estimating the treatment effects on the outcome around and through an intermediate variable. Such causal mediation analyses aim to understand the mechanisms that explain the treatment effect. Although multiple mediators are often involved in real studies, most of the literature considered mediation analyses with one mediator at a time. In this article, we consider mediation analyses when there are causally non-ordered multiple mediators. Even if the mediators do not affect each other, the sum of two indirect effects through the two mediators considered separately may diverge from the joint natural indirect effect when there are additive interactions between the effects of the two mediators on the outcome. Therefore, we derive an equation for the joint natural indirect effect based on the individual mediation effects and their interactive effect, which helps us understand how the mediation effect works through the two mediators and relative contributions of the mediators and their interaction. We also discuss an extension for three mediators. The proposed method is illustrated using data from a randomized trial on the prevention of dental caries.
Causal reasoning and models of cognitive tasks for naval nuclear power plant operators
International Nuclear Information System (INIS)
Salazar-Ferrer, P.
1995-06-01
In complex industrial process control, causal reasoning appears as a major component in operators' cognitive tasks. It is tightly linked to diagnosis, prediction of normal and failure states, and explanation. This work provides a detailed review of literature in causal reasoning. A synthesis is proposed as a model of causal reasoning in process control. This model integrates distinct approaches in Cognitive Science: especially qualitative physics, Bayesian networks, knowledge-based systems, and cognitive psychology. Our model defines a framework for the analysis of causal human errors in simulated naval nuclear power plant fault management. Through the methodological framework of critical incident analysis we define a classification of errors and difficulties linked to causal reasoning. This classification is based on shallow characteristics of causal reasoning. As an origin of these errors, more elementary component activities in causal reasoning are identified. The applications cover the field of functional specification for man-machine interfaces, operators support systems design as well as nuclear safety. In addition of this study, we integrate the model of causal reasoning in a model of cognitive task in process control. (authors). 106 refs., 49 figs., 8 tabs
An Algorithmic Information Calculus for Causal Discovery and Reprogramming Systems
Zenil, Hector
2017-09-08
We introduce a conceptual framework and an interventional calculus to steer and manipulate systems based on their intrinsic algorithmic probability using the universal principles of the theory of computability and algorithmic information. By applying sequences of controlled interventions to systems and networks, we estimate how changes in their algorithmic information content are reflected in positive/negative shifts towards and away from randomness. The strong connection between approximations to algorithmic complexity (the size of the shortest generating mechanism) and causality induces a sequence of perturbations ranking the network elements by the steering capabilities that each of them is capable of. This new dimension unmasks a separation between causal and non-causal components providing a suite of powerful parameter-free algorithms of wide applicability ranging from optimal dimension reduction, maximal randomness analysis and system control. We introduce methods for reprogramming systems that do not require the full knowledge or access to the system\\'s actual kinetic equations or any probability distributions. A causal interventional analysis of synthetic and regulatory biological networks reveals how the algorithmic reprogramming qualitatively reshapes the system\\'s dynamic landscape. For example, during cellular differentiation we find a decrease in the number of elements corresponding to a transition away from randomness and a combination of the system\\'s intrinsic properties and its intrinsic capabilities to be algorithmically reprogrammed can reconstruct an epigenetic landscape. The interventional calculus is broadly applicable to predictive causal inference of systems such as networks and of relevance to a variety of machine and causal learning techniques driving model-based approaches to better understanding and manipulate complex systems.
Method for separating gaseous mixtures of isotopes
International Nuclear Information System (INIS)
Neimann, H.J.; Schuster, E.; Kersting, A.
1976-01-01
A gaseous mixture of isotopes is separated by laser excitation of the isotope mixture with a narrow band of wavelengths, molecularly exciting mainly the isotope to be separated and thereby promoting its reaction with its chemical partner which is excited in a separate chamber. The excited isotopes and the chemical partner are mixed, perhaps in a reaction chamber to which the two excited components are conducted by very short conduits. The improvement of this method is the physical separation of the isotope mixture and its partner during excitation. The reaction between HCl and the mixture of 238 UF 6 and 235 UF 6 is discussed
Shear viscosity of liquid mixtures: Mass dependence
International Nuclear Information System (INIS)
Kaushal, Rohan; Tankeshwar, K.
2002-06-01
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. (author)
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.
The Functions of Danish Causal Conjunctions
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Rita Therkelsen
2004-01-01
Full Text Available In the article I propose an analysis of the Danish causal conjunctions fordi, siden and for based on the framework of Danish Functional Grammar. As conjunctions they relate two clauses, and their semantics have in common that it indicates a causal relationship between the clauses. The causal conjunctions are different as far as their distribution is concerned; siden conjoins a subordinate clause and a main clause, for conjoins two main clauses, and fordi is able to do both. Methodologically I have based my analysis on these distributional properties comparing siden and fordi conjoining a subordinate and a main clause, and comparing for and fordi conjoining two main clauses, following the thesis that they would establish a causal relationship between different kinds of content. My main findings are that fordi establishes a causal relationship between the events referred to by the two clauses, and the whole utterance functions as a statement of this causal relationship. Siden presupposes such a general causal relationship between the two events and puts forward the causing event as a reason for assuming or wishing or ordering the caused event, siden thus establishes a causal relationship between an event and a speech act. For equally presupposes a general causal relationship between two events and it establishes a causal relationship between speech acts, and fordi conjoining two main clauses is able to do this too, but in this position it also maintains its event-relating ability, the interpretation depending on contextual factors.
Space and time in perceptual causality
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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.
Causal diagrams in systems epidemiology
Directory of Open Access Journals (Sweden)
Joffe Michael
2012-03-01
Full Text Available Abstract Methods of diagrammatic modelling have been greatly developed in the past two decades. Outside the context of infectious diseases, systematic use of diagrams in epidemiology has been mainly confined to the analysis of a single link: that between a disease outcome and its proximal determinant(s. Transmitted causes ("causes of causes" tend not to be systematically analysed. The infectious disease epidemiology modelling tradition models the human population in its environment, typically with the exposure-health relationship and the determinants of exposure being considered at individual and group/ecological levels, respectively. Some properties of the resulting systems are quite general, and are seen in unrelated contexts such as biochemical pathways. Confining analysis to a single link misses the opportunity to discover such properties. The structure of a causal diagram is derived from knowledge about how the world works, as well as from statistical evidence. A single diagram can be used to characterise a whole research area, not just a single analysis - although this depends on the degree of consistency of the causal relationships between different populations - and can therefore be used to integrate multiple datasets. Additional advantages of system-wide models include: the use of instrumental variables - now emerging as an important technique in epidemiology in the context of mendelian randomisation, but under-used in the exploitation of "natural experiments"; the explicit use of change models, which have advantages with respect to inferring causation; and in the detection and elucidation of feedback.
Causal diagrams in systems epidemiology.
Joffe, Michael; Gambhir, Manoj; Chadeau-Hyam, Marc; Vineis, Paolo
2012-03-19
Methods of diagrammatic modelling have been greatly developed in the past two decades. Outside the context of infectious diseases, systematic use of diagrams in epidemiology has been mainly confined to the analysis of a single link: that between a disease outcome and its proximal determinant(s). Transmitted causes ("causes of causes") tend not to be systematically analysed.The infectious disease epidemiology modelling tradition models the human population in its environment, typically with the exposure-health relationship and the determinants of exposure being considered at individual and group/ecological levels, respectively. Some properties of the resulting systems are quite general, and are seen in unrelated contexts such as biochemical pathways. Confining analysis to a single link misses the opportunity to discover such properties.The structure of a causal diagram is derived from knowledge about how the world works, as well as from statistical evidence. A single diagram can be used to characterise a whole research area, not just a single analysis - although this depends on the degree of consistency of the causal relationships between different populations - and can therefore be used to integrate multiple datasets.Additional advantages of system-wide models include: the use of instrumental variables - now emerging as an important technique in epidemiology in the context of mendelian randomisation, but under-used in the exploitation of "natural experiments"; the explicit use of change models, which have advantages with respect to inferring causation; and in the detection and elucidation of feedback.
Probabilistic causality and radiogenic cancers
International Nuclear Information System (INIS)
Groeer, P.G.
1986-01-01
A review and scrutiny of the literature on probability and probabilistic causality shows that it is possible under certain assumptions to estimate the probability that a certain type of cancer diagnosed in an individual exposed to radiation prior to diagnosis was caused by this exposure. Diagnosis of this causal relationship like diagnosis of any disease - malignant or not - requires always some subjective judgments by the diagnostician. It is, therefore, illusory to believe that tables based on actuarial data can provide objective estimates of the chance that a cancer diagnosed in an individual is radiogenic. It is argued that such tables can only provide a base from which the diagnostician(s) deviate in one direction or the other according to his (their) individual (consensual) judgment. Acceptance of a physician's diagnostic judgment by patients is commonplace. Similar widespread acceptance of expert judgment by claimants in radiation compensation cases does presently not exist. Judicious use of the present radioepidemiological tables prepared by the Working Group of the National Institutes of Health or of updated future versions of similar tables may improve the situation. 20 references
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...
Mixtures and their risk assessment in toxicology.
Mumtaz, Moiz M; Hansen, Hugh; Pohl, Hana R
2011-01-01
For communities generally and for persons living in the vicinity of waste sites specifically, potential exposures to chemical mixtures are genuine concerns. Such concerns often arise from perceptions of a site's higher than anticipated toxicity due to synergistic interactions among chemicals. This chapter outlines some historical approaches to mixtures risk assessment. It also outlines ATSDR's current approach to toxicity risk assessment. The ATSDR's joint toxicity assessment guidance for chemical mixtures addresses interactions among components of chemical mixtures. The guidance recommends a series of steps that include simple calculations for a systematic analysis of data leading to conclusions regarding any hazards chemical mixtures might pose. These conclusions can, in turn, lead to recommendations such as targeted research to fill data gaps, development of new methods using current science, and health education to raise awareness of residents and health care providers. The chapter also provides examples of future trends in chemical mixtures assessment.
Linear causal modeling with structural equations
Mulaik, Stanley A
2009-01-01
Emphasizing causation as a functional relationship between variables that describe objects, Linear Causal Modeling with Structural Equations integrates a general philosophical theory of causation with structural equation modeling (SEM) that concerns the special case of linear causal relations. In addition to describing how the functional relation concept may be generalized to treat probabilistic causation, the book reviews historical treatments of causation and explores recent developments in experimental psychology on studies of the perception of causation. It looks at how to perceive causal
Causal relationship: a new tool for the causal characterization of Lorentzian manifolds
International Nuclear Information System (INIS)
Garcia-Parrado, Alfonso; Senovilla, Jose M M
2003-01-01
We define and study a new kind of relation between two diffeomorphic Lorentzian manifolds called a causal relation, which is any diffeomorphism characterized by mapping every causal vector of the first manifold onto a causal vector of the second. We perform a thorough study of the mathematical properties of causal relations and prove in particular that two given Lorentzian manifolds (say V and W) may be causally related only in one direction (say from V to W, but not from W to V). This leads us to the concept of causally equivalent (or isocausal in short) Lorentzian manifolds as those mutually causally related and to a definition of causal structure over a differentiable manifold as the equivalence class formed by isocausal Lorentzian metrics upon it. Isocausality is a more general concept than the conformal relationship, because we prove the remarkable result that a conformal relation φ is characterized by the fact of being a causal relation of the particular kind in which both φ and φ -1 are causal relations. Isocausal Lorentzian manifolds are mutually causally compatible, they share some important causal properties, and there are one-to-one correspondences, which are sometimes non-trivial, between several classes of their respective future (and past) objects. A more important feature is that they satisfy the same standard causality constraints. We also introduce a partial order for the equivalence classes of isocausal Lorentzian manifolds providing a classification of all the causal structures that a given fixed manifold can have. By introducing the concept of causal extension we put forward a new definition of causal boundary for Lorentzian manifolds based on the concept of isocausality, and thereby we generalize the traditional Penrose constructions of conformal infinity, diagrams and embeddings. In particular, the concept of causal diagram is given. Many explicit clarifying examples are presented throughout the paper
International Nuclear Information System (INIS)
Bombelli, L.; Lee, J.; Meyer, D.; Sorkin, R.D.
1987-01-01
We propose that space-time at the smallest scales is in reality a causal set: a locally finite set of elements endowed with a partial order corresponding to the macroscopic relation that defines past and future. We explore how a Lorentzian manifold can approximate a causal set, noting in particular that the thereby defined effective dimensionality of a given causal set can vary with length scale. Finally, we speculate briefly on the quantum dynamics of causal sets, indicating why an appropriate choice of action can reproduce general relativity in the classical limit
Amodal causal capture in the tunnel effect.
Bae, Gi Yeul; Flombaum, Jonathan I
2011-01-01
In addition to identifying individual objects in the world, the visual system must also characterize the relationships between objects, for instance when objects occlude one another or cause one another to move. Here we explored the relationship between perceived causality and occlusion. Can one perceive causality in an occluded location? In several experiments, observers judged whether a centrally presented event involved a single object passing behind an occluder, or one object causally launching another (out of view and behind the occluder). With no additional context, the centrally presented event was typically judged as a non-causal pass, even when the occluding and disoccluding objects were different colors--an illusion known as the 'tunnel effect' that results from spatiotemporal continuity. However, when a synchronized context event involved an unambiguous causal launch, participants perceived a causal launch behind the occluder. This percept of an occluded causal interaction could also be driven by grouping and synchrony cues in the absence of any explicitly causal interaction. These results reinforce the hypothesis that causality is an aspect of perception. It is among the interpretations of the world that are independently available to vision when resolving ambiguity, and that the visual system can 'fill in' amodally.
Electromagnetic pulses, localized and causal
Lekner, John
2018-01-01
We show that pulse solutions of the wave equation can be expressed as time Fourier superpositions of scalar monochromatic beam wave functions (solutions of the Helmholtz equation). This formulation is shown to be equivalent to Bateman's integral expression for solutions of the wave equation, for axially symmetric solutions. A closed-form one-parameter solution of the wave equation, containing no backward-propagating parts, is constructed from a beam which is the tight-focus limit of two families of beams. Application is made to transverse electric and transverse magnetic pulses, with evaluation of the energy, momentum and angular momentum for a pulse based on the general localized and causal form. Such pulses can be represented as superpositions of photons. Explicit total energy and total momentum values are given for the one-parameter closed-form pulse.
Quantum retrodiction and causality principle
International Nuclear Information System (INIS)
Shirokov, M.I.
1994-01-01
Quantum mechanics is factually a predictive science. But quantum retrodiction may also be needed, e.g., for the experimental verification of the validity of the Schroedinger equation for the wave function in the past if the present state is given. It is shown that in the retrodictive analog of the prediction the measurement must be replaced by another physical process called the retromeasurement. In this process, the reduction of a state vector into eigenvectors of a measured observable must proceed in the opposite direction of time as compared to the usual reduction. Examples of such processes are unknown. Moreover, they are shown to be forbidden by the causality principle stating that the later event cannot influence the earlier one. So quantum retrodiction seems to be unrealizable. It is demonstrated that the approach to the retrodiction given by S.Watanabe and F.Belinfante must be considered as an unsatisfactory ersatz of retrodicting. 20 refs., 3 figs
Energy Technology Data Exchange (ETDEWEB)
Terrones, M G.H.; Brune, W; Souza Barcellos, E de; Almeida, P G.V. de [Vicosa Univ., MG (Brazil). Dept. de Quimica; Fabris, J D [EMBRAPA, Sete Lagoas, MG (Brazil)
1988-12-31
This paper deals with the energy required to separate ethanol from an aqueous solution in a distillation column containing a solid phase. The solid phases evaluated consisted of either an amylatious (ground corn) or a cellulose (sugar cane bagasse) absorber whit particle sizes smaller than 4 mm. The water-retention capacity of each solid phase was measured by passing vapors or ethanol-water mixtures through the solid phase. When starting with initial concentrations bellow the azeotropic point, ethanol concentrations up to 99,5% (on corn) and 97,2% (on sugar cane) were achieved. The water content was evaluated potentiometrically (Karl`Fischer). Regarding the 2-4 mm ground corn solid phase column, the energy consumed was estimated to be reduced by 15,6% and 60% (by weight) ethanol-water mixture respectively. (author) 11 refs., 2 figs., 2 tabs
Causal ubiquity in quantum physics. A superluminal and local-causal physical ontology
International Nuclear Information System (INIS)
Neelamkavil, Raphael
2014-01-01
A fixed highest criterial velocity (of light) in STR (special theory of relativity) is a convention for a layer of physical inquiry. QM (Quantum Mechanics) avoids action-at-a-distance using this concept, but accepts non-causality and action-at-a-distance in EPR (Einstein-Podolsky-Rosen-Paradox) entanglement experiments. Even in such allegedly [non-causal] processes, something exists processually in extension-motion, between the causal and the [non-causal]. If STR theoretically allows real-valued superluminal communication between EPR entangled particles, quantum processes become fully causal. That is, the QM world is sub-luminally, luminally and superluminally local-causal throughout, and the Law of Causality is ubiquitous in the micro-world. Thus, ''probabilistic causality'' is a merely epistemic term.
Causal ubiquity in quantum physics. A superluminal and local-causal physical ontology
Energy Technology Data Exchange (ETDEWEB)
Neelamkavil, Raphael
2014-07-01
A fixed highest criterial velocity (of light) in STR (special theory of relativity) is a convention for a layer of physical inquiry. QM (Quantum Mechanics) avoids action-at-a-distance using this concept, but accepts non-causality and action-at-a-distance in EPR (Einstein-Podolsky-Rosen-Paradox) entanglement experiments. Even in such allegedly [non-causal] processes, something exists processually in extension-motion, between the causal and the [non-causal]. If STR theoretically allows real-valued superluminal communication between EPR entangled particles, quantum processes become fully causal. That is, the QM world is sub-luminally, luminally and superluminally local-causal throughout, and the Law of Causality is ubiquitous in the micro-world. Thus, ''probabilistic causality'' is a merely epistemic term.
Bayesian D-Optimal Choice Designs for Mixtures
A. Ruseckaite (Aiste); P.P. Goos (Peter); D. Fok (Dennis)
2014-01-01
markdownabstract__Abstract__ Consumer products and services can often be described as mixtures of ingredients. Examples are the mixture of ingredients in a cocktail and the mixture of different components of waiting time (e.g., in-vehicle and out-of-vehicle travel time) in a transportation
Separation of organic azeotropic mixtures by pervaporation
Energy Technology Data Exchange (ETDEWEB)
Baker, R.W.
1991-12-01
Distillation is a commonly used separation technique in the petroleum refining and chemical processing industries. However, there are a number of potential separations involving azetropic and close-boiling organic mixtures that cannot be separated efficiently by distillation. Pervaporation is a membrane-based process that uses selective permeation through membranes to separate liquid mixtures. Because the separation process is not affected by the relative volatility of the mixture components being separated, pervaporation can be used to separate azetropes and close-boiling mixtures. Our results showed that pervaporation membranes can be used to separate azeotropic mixtures efficiently, a result that is not achievable with simple distillation. The membranes were 5--10 times more permeable to one of the components of the mixture, concentrating it in the permeate stream. For example, the membrane was 10 times more permeable to ethanol than methyl ethyl ketone, producing 60% ethanol permeate from an azeotropic mixture of ethanol and methyl ethyl ketone containing 18% ethanol. For the ethyl acetate/water mixture, the membranes showed a very high selectivity to water (> 300) and the permeate was 50--100 times enriched in water relative to the feed. The membranes had permeate fluxes on the order of 0.1--1 kg/m{sup 2}{center dot}h in the operating range of 55--70{degrees}C. Higher fluxes were obtained by increasing the operating temperature.
A Theory of Causal Learning in Children: Causal Maps and Bayes Nets
Gopnik, Alison; Glymour, Clark; Sobel, David M.; Schulz, Laura E.; Kushnir, Tamar; Danks, David
2004-01-01
The authors outline a cognitive and computational account of causal learning in children. They propose that children use specialized cognitive systems that allow them to recover an accurate "causal map" of the world: an abstract, coherent, learned representation of the causal relations among events. This kind of knowledge can be perspicuously…
International Nuclear Information System (INIS)
Garcia-Parrado, Alfonso; Sanchez, Miguel
2005-01-01
Recently (Garcia-Parrado and Senovilla 2003 Class. Quantum Grav. 20 625-64) the concept of causal mapping between spacetimes, essentially equivalent in this context to the chronological map defined in abstract chronological spaces, and the related notion of causal structure, have been introduced as new tools to study causality in Lorentzian geometry. In the present paper, these tools are further developed in several directions such as (i) causal mappings-and, thus, abstract chronological ones-do not preserve two levels of the standard hierarchy of causality conditions (however, they preserve the remaining levels as shown in the above reference), (ii) even though global hyperbolicity is a stable property (in the set of all time-oriented Lorentzian metrics on a fixed manifold), the causal structure of a globally hyperbolic spacetime can be unstable against perturbations; in fact, we show that the causal structures of Minkowski and Einstein static spacetimes remain stable, whereas that of de Sitter becomes unstable, (iii) general criteria allow us to discriminate different causal structures in some general spacetimes (e.g. globally hyperbolic, stationary standard); in particular, there are infinitely many different globally hyperbolic causal structures (and thus, different conformal ones) on R 2 (iv) plane waves with the same number of positive eigenvalues in the frequency matrix share the same causal structure and, thus, they have equal causal extensions and causal boundaries
Causal models in epidemiology: past inheritance and genetic future
Directory of Open Access Journals (Sweden)
Kriebel David
2006-07-01
Full Text Available Abstract The eruption of genetic research presents a tremendous opportunity to epidemiologists to improve our ability to identify causes of ill health. Epidemiologists have enthusiastically embraced the new tools of genomics and proteomics to investigate gene-environment interactions. We argue that neither the full import nor limitations of such studies can be appreciated without clarifying underlying theoretical models of interaction, etiologic fraction, and the fundamental concept of causality. We therefore explore different models of causality in the epidemiology of disease arising out of genes, environments, and the interplay between environments and genes. We begin from Rothman's "pie" model of necessary and sufficient causes, and then discuss newer approaches, which provide additional insights into multifactorial causal processes. These include directed acyclic graphs and structural equation models. Caution is urged in the application of two essential and closely related concepts found in many studies: interaction (effect modification and the etiologic or attributable fraction. We review these concepts and present four important limitations. 1. Interaction is a fundamental characteristic of any causal process involving a series of probabilistic steps, and not a second-order phenomenon identified after first accounting for "main effects". 2. Standard methods of assessing interaction do not adequately consider the life course, and the temporal dynamics through which an individual's sufficient cause is completed. Different individuals may be at different stages of development along the path to disease, but this is not usually measurable. Thus, for example, acquired susceptibility in children can be an important source of variation. 3. A distinction must be made between individual-based and population-level models. Most epidemiologic discussions of causality fail to make this distinction. 4. At the population level, there is additional
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
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…
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 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…
A General Approach to Causal Mediation Analysis
Imai, Kosuke; Keele, Luke; Tingley, Dustin
2010-01-01
Traditionally in the social sciences, causal mediation analysis has been formulated, understood, and implemented within the framework of linear structural equation models. We argue and demonstrate that this is problematic for 3 reasons: the lack of a general definition of causal mediation effects independent of a particular statistical model, the…
A Causal Model of Faculty Research Productivity.
Bean, John P.
A causal model of faculty research productivity was developed through a survey of the literature. Models of organizational behavior, organizational effectiveness, and motivation were synthesized into a causal model of productivity. Two general types of variables were assumed to affect individual research productivity: institutional variables and…
Counterfactual overdetermination vs. the causal exclusion problem.
Sparber, Georg
2005-01-01
This paper aims to show that a counterfactual approach to causation is not sufficient to provide a solution to the causal exclusion problem in the form of systematic overdetermination. Taking into account the truthmakers of causal counterfactuals provides a strong argument in favour of the identity of causes in situations of translevel, causation.
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)…
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…
Determining Directional Dependency in Causal Associations
Pornprasertmanit, Sunthud; Little, Todd D.
2012-01-01
Directional dependency is a method to determine the likely causal direction of effect between two variables. This article aims to critique and improve upon the use of directional dependency as a technique to infer causal associations. We comment on several issues raised by von Eye and DeShon (2012), including: encouraging the use of the signs of…
Optimal designs for linear mixture models
Mendieta, E.J.; Linssen, H.N.; Doornbos, R.
1975-01-01
In a recent paper Snee and Marquardt [8] considered designs for linear mixture models, where the components are subject to individual lower and/or upper bounds. When the number of components is large their algorithm XVERT yields designs far too extensive for practical purposes. The purpose of this
Optimal designs for linear mixture models
Mendieta, E.J.; Linssen, H.N.; Doornbos, R.
1975-01-01
In a recent paper Snee and Marquardt (1974) considered designs for linear mixture models, where the components are subject to individual lower and/or upper bounds. When the number of components is large their algorithm XVERT yields designs far too extensive for practical purposes. The purpose of
Heterogeneous Causal Effects and Sample Selection Bias
DEFF Research Database (Denmark)
Breen, Richard; Choi, Seongsoo; Holm, Anders
2015-01-01
The role of education in the process of socioeconomic attainment is a topic of long standing interest to sociologists and economists. Recently there has been growing interest not only in estimating the average causal effect of education on outcomes such as earnings, but also in estimating how...... causal effects might vary over individuals or groups. In this paper we point out one of the under-appreciated hazards of seeking to estimate heterogeneous causal effects: conventional selection bias (that is, selection on baseline differences) can easily be mistaken for heterogeneity of causal effects....... This might lead us to find heterogeneous effects when the true effect is homogenous, or to wrongly estimate not only the magnitude but also the sign of heterogeneous effects. We apply a test for the robustness of heterogeneous causal effects in the face of varying degrees and patterns of selection bias...
Repair of Partly Misspecified Causal Diagrams.
Oates, Chris J; Kasza, Jessica; Simpson, Julie A; Forbes, Andrew B
2017-07-01
Errors in causal diagrams elicited from experts can lead to the omission of important confounding variables from adjustment sets and render causal inferences invalid. In this report, a novel method is presented that repairs a misspecified causal diagram through the addition of edges. These edges are determined using a data-driven approach designed to provide improved statistical efficiency relative to de novo structure learning methods. Our main assumption is that the expert is "directionally informed," meaning that "false" edges provided by the expert would not create cycles if added to the "true" causal diagram. The overall procedure is cast as a preprocessing technique that is agnostic to subsequent causal inferences. Results based on simulated data and data derived from an observational cohort illustrate the potential for data-assisted elicitation in epidemiologic applications. See video abstract at, http://links.lww.com/EDE/B208.
Dilepton production in schematic causal viscous hydrodynamics
International Nuclear Information System (INIS)
Song, Taesoo; Han, Kyong Chol; Ko, Che Ming
2011-01-01
Assuming that in the hot dense matter produced in relativistic heavy-ion collisions, the energy density, entropy density, and pressure as well as the azimuthal and space-time rapidity components of the shear tensor are uniform in the direction transversal to the reaction plane, we derive a set of schematic equations from the Isreal-Stewart causal viscous hydrodynamics. These equations are then used to describe the evolution dynamics of relativistic heavy-ion collisions by taking the shear viscosity to entropy density ratio of 1/4π for the initial quark-gluon plasma (QGP) phase and of 10 times this value for the later hadron-gas (HG) phase. Using the production rate evaluated with particle distributions that take into account the viscous effect, we study dilepton production in central heavy-ion collisions. Compared with results from the ideal hydrodynamics, we find that although the dilepton invariant mass spectra from the two approaches are similar, the transverse momentum spectra are significantly enhanced at high transverse momenta by the viscous effect. We also study the transverse momentum dependence of dileptons produced from QGP for a fixed transverse mass, which is essentially absent in the ideal hydrodynamics, and find that this so-called transverse mass scaling is violated in the viscous hydrodynamics, particularly at high transverse momenta.
Some properties of explosive mixtures containing peroxides
Energy Technology Data Exchange (ETDEWEB)
Zeman, Svatopluk [Institute of Energetic Materials, Faculty of Chemical Technology, University of Pardubice, CZ-532 10 Pardubice (Czech Republic)], E-mail: svatopluk.zeman@upce.cz; Trzcinski, Waldemar A. [Institute of Chemistry, Military University of Technology, PL-00-908 Warsaw 49 (Poland); Matyas, Robert [Institute of Energetic Materials, Faculty of Chemical Technology, University of Pardubice, CZ-532 10 Pardubice (Czech Republic)
2008-06-15
This study concerns mixtures of triacetone triperoxide (3,3,6,6,9,9-hexamethyl-1,2,4,5,7,8-hexoxonane, TATP) and ammonium nitrate (AN) with added water (W), as the case may be, and dry mixtures of TATP with urea nitrate (UN). Relative performances (RP) of the mixtures and their individual components, relative to TNT, were determined by means of ballistic mortar. The detonation energies, E{sub 0}, and detonation velocities, D, were calculated for the mixtures studied by means of the thermodynamic code CHEETAH. Relationships have been found and are discussed between the RP and the E{sub 0} values related to unit volume of gaseous products of detonation of these mixtures. These relationships together with those between RP and oxygen balance values of the mixtures studied indicate different types of participation of AN and UN in the explosive decomposition of the respective mixtures. Dry TATP/UN mixtures exhibit lower RP than analogous mixtures TATP/AN containing up to 25% of water. Depending on the water content, the TATP/AN mixtures possess higher detonability values than the ANFO explosives. A semi-logarithmic relationship between the D values and oxygen coefficients has been derived for all the mixtures studied at the charge density of 1000 kg m{sup -3}. Among the mixtures studied, this relationship distinguishes several samples of the type of 'tertiary explosives' as well as samples that approach 'high explosives' in their performances and detonation velocities.
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
Causality violations in Lovelock theories
Brustein, Ram; Sherf, Yotam
2018-04-01
Higher-derivative gravity theories, such as Lovelock theories, generalize Einstein's general relativity (GR). Modifications to GR are expected when curvatures are near Planckian and appear in string theory or supergravity. But can such theories describe gravity on length scales much larger than the Planck cutoff length scale? Here we find causality constraints on Lovelock theories that arise from the requirement that the equations of motion (EOM) of perturbations be hyperbolic. We find a general expression for the "effective metric" in field space when Lovelock theories are perturbed around some symmetric background solution. In particular, we calculate explicitly the effective metric for a general Lovelock theory perturbed around cosmological Friedman-Robertson-Walker backgrounds and for some specific cases when perturbed around Schwarzschild-like solutions. For the EOM to be hyperbolic, the effective metric needs to be Lorentzian. We find that, unlike for GR, the effective metric is generically not Lorentzian when the Lovelock modifications are significant. So, we conclude that Lovelock theories can only be considered as perturbative extensions of GR and not as truly modified theories of gravity. We compare our results to those in the literature and find that they agree with and reproduce the results of previous studies.
Mixture toxicity of PBT-like chemicals
DEFF Research Database (Denmark)
Syberg, Kristian; Dai, Lina; Ramskov, Tina
addition is a suitable model for default estimations of mixture effects. One of the major challenges is therefore how to select specific chemicals for actual mixture toxicity assessments. Persistant chemicals are likely to be present in the environment for an extended period of time, thus increasing...... the likelihood of them being present in environmentally found mixtures. Persistant, bioaccumulative and toxic (PBT) chemicals are therefore a highly relevant group of chemicals to consider for mixture toxicity regulation. The present study evaluates to what extent a number of PBT-like chemicals posess concern...... 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...
Lotfy, Hayam M.; Mohamed, Dalia; Elshahed, Mona S.
2018-01-01
In the presented work several spectrophotometric methods were performed for the quantification of canagliflozin (CGZ) and metformin hydrochloride (MTF) simultaneously in their binary mixture. Two of these methods; response correlation (RC) and advanced balance point-spectrum subtraction (ABP-SS) were developed and introduced for the first time in this work, where the latter method (ABP-SS) was performed on both the zero order and the first derivative spectra of the drugs. Besides, two recently established methods; advanced amplitude modulation (AAM) and advanced absorbance subtraction (AAS) were also accomplished. All the proposed methods were validated in accordance to the ICH guidelines, where all methods were proved to be accurate and precise. Additionally, the linearity range, limit of detection and limit of quantification were determined and the selectivity was examined through the analysis of laboratory prepared mixtures and the combined dosage form of the drugs. The proposed methods were capable of determining the two drugs in the ratio present in the pharmaceutical formulation CGZ:MTF (1:17) without the requirement of any preliminary separation, further dilution or standard spiking. The results obtained by the proposed methods were in compliance with the reported chromatographic method when compared statistically, proving the absence of any significant difference in accuracy and precision between the proposed and reported methods.
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....
Causal localizations in relativistic quantum mechanics
Castrigiano, Domenico P. L.; Leiseifer, Andreas D.
2015-07-01
Causal localizations describe the position of quantum systems moving not faster than light. They are constructed for the systems with finite spinor dimension. At the center of interest are the massive relativistic systems. For every positive mass, there is the sequence of Dirac tensor-localizations, which provides a complete set of inequivalent irreducible causal localizations. They obey the principle of special relativity and are fully Poincaré covariant. The boosters are determined by the causal position operator and the other Poincaré generators. The localization with minimal spinor dimension is the Dirac localization. Thus, the Dirac equation is derived here as a mere consequence of the principle of causality. Moreover, the higher tensor-localizations, not known so far, follow from Dirac's localization by a simple construction. The probability of localization for positive energy states results to be described by causal positive operator valued (PO-) localizations, which are the traces of the causal localizations on the subspaces of positive energy. These causal Poincaré covariant PO-localizations for every irreducible massive relativistic system were, all the more, not known before. They are shown to be separated. Hence, the positive energy systems can be localized within every open region by a suitable preparation as accurately as desired. Finally, the attempt is made to provide an interpretation of the PO-localization operators within the frame of conventional quantum mechanics attributing an important role to the negative energy states.
Can chance cause cancer? A causal consideration.
Stensrud, Mats Julius; Strohmaier, Susanne; Valberg, Morten; Aalen, Odd Olai
2017-04-01
The role of randomness, environment and genetics in cancer development is debated. We approach the discussion by using the potential outcomes framework for causal inference. By briefly considering the underlying assumptions, we suggest that the antagonising views arise due to estimation of substantially different causal effects. These effects may be hard to interpret, and the results cannot be immediately compared. Indeed, it is not clear whether it is possible to define a causal effect of chance at all. Copyright © 2017 Elsevier Ltd. All rights reserved.
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.
Mathematical implications of Einstein-Weyl causality
International Nuclear Information System (INIS)
Borchers, H.J.; Sen, R.N.
2006-01-01
The present work is the first systematic attempt at answering the following fundamental question: what mathematical structures does Einstein-Weyl causality impose on a point-set that has no other previous structure defined on it? The authors propose an axiomatization of Einstein-Weyl causality (inspired by physics), and investigate the topological and uniform structures that it implies. Their final result is that a causal space is densely embedded in one that is locally a differentiable manifold. The mathematical level required of the reader is that of the graduate student in mathematical physics. (orig.)
The mistake of the causal relationship
Directory of Open Access Journals (Sweden)
О. Д. Комаров
2015-03-01
Full Text Available The article deals with issues of the mistake of the causal relationship. The modern criminal law science approaches to the content of the mistake of the causal relationship and its significance to the qualification of the crime are described. It is proved that in cases of dolus generalis different mental attitude of the guilty person to two separate acts of his conduct exist. Consequently, in mentioned above cases mistake of the causal relationship does not have place. The rules of qualification of the crimes commited with the mistake of causation and in cases of dolus generalis are proposed .
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. Copyright © 2015 Elsevier B.V. All rights reserved.
Strategies to intervene on causal systems are adaptively selected.
Coenen, Anna; Rehder, Bob; Gureckis, Todd M
2015-06-01
How do people choose interventions to learn about causal systems? Here, we considered two possibilities. First, we test an information sampling model, information gain, which values interventions that can discriminate between a learner's hypotheses (i.e. possible causal structures). We compare this discriminatory model to a positive testing strategy that instead aims to confirm individual hypotheses. Experiment 1 shows that individual behavior is described best by a mixture of these two alternatives. In Experiment 2 we find that people are able to adaptively alter their behavior and adopt the discriminatory model more often after experiencing that the confirmatory strategy leads to a subjective performance decrement. In Experiment 3, time pressure leads to the opposite effect of inducing a change towards the simpler positive testing strategy. These findings suggest that there is no single strategy that describes how intervention decisions are made. Instead, people select strategies in an adaptive fashion that trades off their expected performance and cognitive effort. Copyright © 2015 Elsevier Inc. All rights reserved.
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.
Violation of causality in f(T) gravity
Energy Technology Data Exchange (ETDEWEB)
Otalora, G. [Pontificia Universidad Catolica de Valparaiso, Instituto de Fisica, Valparaiso (Chile); Reboucas, M.J. [Centro Brasileiro de Pesquisas Fisicas, Rio de Janeiro, RJ (Brazil)
2017-11-15
In the standard formulation, the f(T) field equations are not invariant under local Lorentz transformations, and thus the theory does not inherit the causal structure of special relativity. Actually, even locally violation of causality can occur in this formulation of f(T) gravity. A locally Lorentz covariant f(T) gravity theory has been devised recently, and this local causality problem seems to have been overcome. The non-locality question, however, is left open. If gravitation is to be described by this covariant f(T) gravity theory there are a number of issues that ought to be examined in its context, including the question as to whether its field equations allow homogeneous Goedel-type solutions, which necessarily leads to violation of causality on non-local scale. Here, to look into the potentialities and difficulties of the covariant f(T) theories, we examine whether they admit Goedel-type solutions. We take a combination of a perfect fluid with electromagnetic plus a scalar field as source, and determine a general Goedel-type solution, which contains special solutions in which the essential parameter of Goedel-type geometries, m{sup 2}, defines any class of homogeneous Goedel-type geometries. We show that solutions of the trigonometric and linear classes (m{sup 2} < 0 and m = 0) are permitted only for the combined matter sources with an electromagnetic field matter component. We extended to the context of covariant f(T) gravity a theorem which ensures that any perfect-fluid homogeneous Goedel-type solution defines the same set of Goedel tetrads h{sub A}{sup μ} up to a Lorentz transformation. We also showed that the single massless scalar field generates Goedel-type solution with no closed time-like curves. Even though the covariant f(T) gravity restores Lorentz covariance of the field equations and the local validity of the causality principle, the bare existence of the Goedel-type solutions makes apparent that the covariant formulation of f(T) gravity
Assessing students' beliefs, emotions and causal attribution ...
African Journals Online (AJOL)
Keywords: academic emotion; belief; causal attribution; statistical validation; students' conceptions of learning ... Sadi & Lee, 2015), through their effect on motivation and learning strategies .... to understand why they may or may not be doing.
Granger Causality Testing with Intensive Longitudinal Data.
Molenaar, Peter C M
2018-06-01
The availability of intensive longitudinal data obtained by means of ambulatory assessment opens up new prospects for prevention research in that it allows the derivation of subject-specific dynamic networks of interacting variables by means of vector autoregressive (VAR) modeling. The dynamic networks thus obtained can be subjected to Granger causality testing in order to identify causal relations among the observed time-dependent variables. VARs have two equivalent representations: standard and structural. Results obtained with Granger causality testing depend upon which representation is chosen, yet no criteria exist on which this important choice can be based. A new equivalent representation is introduced called hybrid VARs with which the best representation can be chosen in a data-driven way. Partial directed coherence, a frequency-domain statistic for Granger causality testing, is shown to perform optimally when based on hybrid VARs. An application to real data is provided.
Causality Between Urban Concentration and Environmental Quality
Directory of Open Access Journals (Sweden)
Amin Pujiati
2015-08-01
Full Text Available Population is concentrated in urban areas can cause the external diseconomies on environment if it exceeds the carrying capacity of the space and the urban economy. Otherwise the quality of the environment is getting better, led to the concentration of population in urban areas are increasingly high. This study aims to analyze the relationship of causality between the urban concentration and environmental quality in urban agglomeration areas. The data used in the study of secondary data obtained from the Central Bureau of statistics and the City Government from 2000 to 2013. The analytical method used is the Granger causality and descriptive. Granger causality study results showed no pattern of reciprocal causality, between urban concentration and the quality of the environment, but there unidirectional relationship between the urban concentration and environmental quality. This means that increasing urban concentration led to decreased environmental quality.
Selecting appropriate cases when tracing causal mechanisms
DEFF Research Database (Denmark)
Beach, Derek; Pedersen, Rasmus Brun
2016-01-01
The last decade has witnessed resurgence in the interest in studying the causal mechanisms linking causes and outcomes in the social sciences. This article explores the overlooked implications for case selection when tracing mechanisms using in-depth case studies. Our argument is that existing case...... selection guidelines are appropriate for research aimed at making cross-case claims about causal relationships, where case selection is primarily used to control for other causes. However, existing guidelines are not in alignment with case-based research that aims to trace mechanisms, where the goal...... is to unpack the causal mechanism between X and Y, enabling causal inferences to be made because empirical evidence is provided for how the mechanism actually operated in a particular case. The in-depth, within-case tracing of how mechanisms operate in particular cases produces what can be termed mechanistic...
Rate-Agnostic (Causal) Structure Learning.
Plis, Sergey; Danks, David; Freeman, Cynthia; Calhoun, Vince
2015-12-01
Causal structure learning from time series data is a major scientific challenge. Extant algorithms assume that measurements occur sufficiently quickly; more precisely, they assume approximately equal system and measurement timescales. In many domains, however, measurements occur at a significantly slower rate than the underlying system changes, but the size of the timescale mismatch is often unknown. This paper develops three causal structure learning algorithms, each of which discovers all dynamic causal graphs that explain the observed measurement data, perhaps given undersampling. That is, these algorithms all learn causal structure in a "rate-agnostic" manner: they do not assume any particular relation between the measurement and system timescales. We apply these algorithms to data from simulations to gain insight into the challenge of undersampling.
K-causality and degenerate spacetimes
Dowker, H. F.; Garcia, R. S.; Surya, S.
2000-11-01
The causal relation K+ was introduced by Sorkin and Woolgar to extend the standard causal analysis of C2 spacetimes to those that are only C0. Most of their results also hold true in the case of metrics with degeneracies which are C0 but vanish at isolated points. In this paper we seek to examine K+ explicitly in the case of topology-changing `Morse histories' which contain degeneracies. We first demonstrate some interesting features of this relation in globally Lorentzian spacetimes. In particular, we show that K+ is robust and the Hawking and Sachs characterization of causal continuity translates into a natural condition in terms of K+. We then examine K+ in topology-changing Morse spacetimes with the degenerate points excised and then for the Morse histories in which the degenerate points are reinstated. We find further characterizations of causal continuity in these cases.
Efficient nonparametric estimation of causal mediation effects
Chan, K. C. G.; Imai, K.; Yam, S. C. P.; Zhang, Z.
2016-01-01
An essential goal of program evaluation and scientific research is the investigation of causal mechanisms. Over the past several decades, causal mediation analysis has been used in medical and social sciences to decompose the treatment effect into the natural direct and indirect effects. However, all of the existing mediation analysis methods rely on parametric modeling assumptions in one way or another, typically requiring researchers to specify multiple regression models involving the treat...
Inference of Boundaries in Causal Sets
Cunningham, William
2017-01-01
We investigate the extrinsic geometry of causal sets in $(1+1)$-dimensional Minkowski spacetime. The properties of boundaries in an embedding space can be used not only to measure observables, but also to supplement the discrete action in the partition function via discretized Gibbons-Hawking-York boundary terms. We define several ways to represent a causal set using overlapping subsets, which then allows us to distinguish between null and non-null bounding hypersurfaces in an embedding space...
The Continuum Limit of Causal Fermion Systems
Finster, Felix
2016-01-01
This monograph introduces the basic concepts of the theory of causal fermion systems, a recent approach to the description of fundamental physics. The theory yields quantum mechanics, general relativity and quantum field theory as limiting cases and is therefore a candidate for a unified physical theory. From the mathematical perspective, causal fermion systems provide a general framework for describing and analyzing non-smooth geometries and "quantum geometries." The dynamics is described by...
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.
Causal strength induction from time series data.
Soo, Kevin W; Rottman, Benjamin M
2018-04-01
One challenge when inferring the strength of cause-effect relations from time series data is that the cause and/or effect can exhibit temporal trends. If temporal trends are not accounted for, a learner could infer that a causal relation exists when it does not, or even infer that there is a positive causal relation when the relation is negative, or vice versa. We propose that learners use a simple heuristic to control for temporal trends-that they focus not on the states of the cause and effect at a given instant, but on how the cause and effect change from one observation to the next, which we call transitions. Six experiments were conducted to understand how people infer causal strength from time series data. We found that participants indeed use transitions in addition to states, which helps them to reach more accurate causal judgments (Experiments 1A and 1B). Participants use transitions more when the stimuli are presented in a naturalistic visual format than a numerical format (Experiment 2), and the effect of transitions is not driven by primacy or recency effects (Experiment 3). Finally, we found that participants primarily use the direction in which variables change rather than the magnitude of the change for estimating causal strength (Experiments 4 and 5). Collectively, these studies provide evidence that people often use a simple yet effective heuristic for inferring causal strength from time series data. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
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.
Causality violation, gravitational shockwaves and UV completion
Energy Technology Data Exchange (ETDEWEB)
Hollowood, Timothy J.; Shore, Graham M. [Department of Physics, Swansea University,Swansea, SA2 8PP (United Kingdom)
2016-03-18
The effective actions describing the low-energy dynamics of QFTs involving gravity generically exhibit causality violations. These may take the form of superluminal propagation or Shapiro time advances and allow the construction of “time machines”, i.e. spacetimes admitting closed non-spacelike curves. Here, we discuss critically whether such causality violations may be used as a criterion to identify unphysical effective actions or whether, and how, causality problems may be resolved by embedding the action in a fundamental, UV complete QFT. We study in detail the case of photon scattering in an Aichelburg-Sexl gravitational shockwave background and calculate the phase shifts in QED for all energies, demonstrating their smooth interpolation from the causality-violating effective action values at low-energy to their manifestly causal high-energy limits. At low energies, these phase shifts may be interpreted as backwards-in-time coordinate jumps as the photon encounters the shock wavefront, and we illustrate how the resulting causality problems emerge and are resolved in a two-shockwave time machine scenario. The implications of our results for ultra-high (Planck) energy scattering, in which graviton exchange is modelled by the shockwave background, are highlighted.
On the non-causal link between volatility and growth
DEFF Research Database (Denmark)
Posch, Olaf; Wälde, Klaus
A model highlighting the endogeneity of both volatility and growth is presented. Volatility and growth are therefore correlated but there is no causal link from volatility to growth. This joint endogeneity is illustrated by working out the effects through which economies with different tax levels...... di er both in their volatility and growth. Using a continuous-time DSGE model with plausible parametric restrictions, we obtain closedform measures of macro volatility based on cyclical components and output growth rates. Given our results, empirical volatility-growth analysis should include controls...
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. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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. © The Author 2014. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Heat transfer from a high temperature condensable mixture
International Nuclear Information System (INIS)
Chan, S.H.; Cho, D.H.; Condiff, D.W.
1980-01-01
Bulk condensation and heat transfer in a very hot gaseous mixture that contains a vapor component condensable at high temperature are investigated. A general formulation of the problem is presented in various forms. Analytical solutions for three specific cases involving both one- and two-component two-phase mixtures are obtained. It is shown that a detached fog formation is induced by rapid radiative cooling from the mixture. The formation of radiatively induced fog is found to be an interesting and important phenomenon as it not only exhibits unique features different from the conventional diffusion induced fog, but also greatly enhances heat transfer from the mixture to the boundary. (author)
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)
Entanglement entropy in causal set theory
Sorkin, Rafael D.; Yazdi, Yasaman K.
2018-04-01
Entanglement entropy is now widely accepted as having deep connections with quantum gravity. It is therefore desirable to understand it in the context of causal sets, especially since they provide in a natural manner the UV cutoff needed to render entanglement entropy finite. Formulating a notion of entanglement entropy in a causal set is not straightforward because the type of canonical hypersurface-data on which its definition typically relies is not available. Instead, we appeal to the more global expression given in Sorkin (2012 (arXiv:1205.2953)) which, for a Gaussian scalar field, expresses the entropy of a spacetime region in terms of the field’s correlation function within that region (its ‘Wightman function’ W(x, x') ). Carrying this formula over to the causal set, one obtains an entropy which is both finite and of a Lorentz invariant nature. We evaluate this global entropy-expression numerically for certain regions (primarily order-intervals or ‘causal diamonds’) within causal sets of 1 + 1 dimensions. For the causal-set counterpart of the entanglement entropy, we obtain, in the first instance, a result that follows a (spacetime) volume law instead of the expected (spatial) area law. We find, however, that one obtains an area law if one truncates the commutator function (‘Pauli–Jordan operator’) and the Wightman function by projecting out the eigenmodes of the Pauli–Jordan operator whose eigenvalues are too close to zero according to a geometrical criterion which we describe more fully below. In connection with these results and the questions they raise, we also study the ‘entropy of coarse-graining’ generated by thinning out the causal set, and we compare it with what one obtains by similarly thinning out a chain of harmonic oscillators, finding the same, ‘universal’ behaviour in both cases.
Fayed, Ahmed Salah; Hegazy, Maha Abdel-Monem; Wahab, Nada Sayed Abdel
2016-11-01
New, simple, highly sensitive, precise, and accurate gradient reversed-phase chromatographic methods were developed using HPLC and ultra-HPLC (UPLC) systems for the determination of five components, namely thiamine, pyridoxine, cyanocobalamin, benfotiamine, and diclofenac in tablets and capsules. The methods were compared for their efficiency in the separation and determination of these five compounds using two different C18 columns (250 × 4.6 mm, 5 μm; and 100 × 4.6 mm, 2.6 μm) for HPLC and UPLC, respectively. Chromatographic separation was performed with a mobile phase containing acetonitrile and 0.025 M phosphate buffer (pH 3.5), with a gradient program and a flow rate of 1.5 and 1.0 mL/min for both methods, respectively. The methods were validated according to International Conference on Harmonization guidelines. Linearity was achieved in the range of 5.00 to 150.00 μg/mL for each of the five compounds. Ruggedness and intermediate precision were confirmed by different analysts on different columns on different days. Moreover, the components were subjected to an accelerated stability study under acidic, alkaline, and oxidative stress conditions and no interfering peaks were observed. The five compounds were efficiently separated in <20 min by HPLC, whereas for UPLC, separation was achieved in <8 min, which dramatically decreased the consumption of organic solvents.
The Relevance of Causal Social Construction
Directory of Open Access Journals (Sweden)
Marques Teresa
2017-02-01
Full Text Available Social constructionist claims are surprising and interesting when they entail that presumably natural kinds are in fact socially constructed. The claims are interesting because of their theoretical and political importance. Authors like Díaz-León argue that constitutive social construction is more relevant for achieving social justice than causal social construction. This paper challenges this claim. Assuming there are socially salient groups that are discriminated against, the paper presents a dilemma: if there were no constitutively constructed social kinds, the causes of the discrimination of existing social groups would have to be addressed, and understanding causal social construction would be relevant to achieve social justice. On the other hand, not all possible constitutively socially constructed kinds are actual social kinds. If an existing social group is constitutively constructed as a social kind K, the fact that it actually exists as a K has social causes. Again, causal social construction is relevant. The paper argues that (i for any actual social kind X, if X is constitutively socially constructed as K, then it is also causally socially constructed; and (ii causal social construction is at least as relevant as constitutive social construction for concerns of social justice. For illustration, I draw upon two phenomena that are presumed to contribute towards the discrimination of women: (i the poor performance effects of stereotype threat, and (ii the silencing effects of gendered language use.
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.
Gravity and matter in causal set theory
International Nuclear Information System (INIS)
Sverdlov, Roman; Bombelli, Luca
2009-01-01
The goal of this paper is to propose an approach to the formulation of dynamics for causal sets and coupled matter fields. We start from the continuum version of the action for a Klein-Gordon field coupled to gravity, and rewrite it first using quantities that have a direct correspondent in the case of a causal set, namely volumes, causal relations and timelike lengths, as variables to describe the geometry. In this step, the local Lagrangian density L(f;x) for a set of fields f is recast into a quasilocal expression L 0 (f;p,q) that depends on pairs of causally related points pprq and is a function of the values of f in the Alexandrov set defined by those points, and whose limit as p and q approach a common point x is L(f;x). We then describe how to discretize L 0 (f;p,q) and use it to define a causal-set-based action.
A frequency domain subspace algorithm for mixed causal, anti-causal LTI systems
Fraanje, Rufus; Verhaegen, Michel; Verdult, Vincent; Pintelon, Rik
2003-01-01
The paper extends the subspacc identification method to estimate state-space models from frequency response function (FRF) samples, proposed by McKelvey et al. (1996) for mixed causal/anti-causal systems, and shows that other frequency domain subspace algorithms can be extended similarly. The method
Causal relations among events and states in dynamic geographical phenomena
Huang, Zhaoqiang; Feng, Xuezhi; Xuan, Wenling; Chen, Xiuwan
2007-06-01
There is only a static state of the real world to be recorded in conventional geographical information systems. However, there is not only static information but also dynamic information in geographical phenomena. So that how to record the dynamic information and reveal the relations among dynamic information is an important issue in a spatio-temporal information system. From an ontological perspective, we can initially divide the spatio-temporal entities in the world into continuants and occurrents. Continuant entities endure through some extended (although possibly very short) interval of time (e.g., houses, roads, cities, and real-estate). Occurrent entities happen and are then gone (e.g., a house repair job, road construction project, urban expansion, real-estate transition). From an information system perspective, continuants and occurrents that have a unique identity in the system are referred to as objects and events, respectively. And the change is represented implicitly by static snapshots in current spatial temporal information systems. In the previous models, the objects can be considered as the fundamental components of the system, and the change is modeled by considering time-varying attributes of these objects. In the spatio-temporal database, the temporal information that is either interval or instant is involved and the underlying data structures and indexes for temporal are considerable investigated. However, there is the absence of explicit ways of considering events, which affect the attributes of objects or the state. So the research issue of this paper focuses on how to model events in conceptual models of dynamic geographical phenomena and how to represent the causal relations among events and the objects or states. Firstly, the paper reviews the conceptual modeling in a temporal GIS by researchers. Secondly, this paper discusses the spatio-temporal entities: objects and events. Thirdly, this paper investigates the causal relations amongst
How causal analysis can reveal autonomy in models of biological systems
Marshall, William; Kim, Hyunju; Walker, Sara I.; Tononi, Giulio; Albantakis, Larissa
2017-11-01
Standard techniques for studying biological systems largely focus on their dynamical or, more recently, their informational properties, usually taking either a reductionist or holistic perspective. Yet, studying only individual system elements or the dynamics of the system as a whole disregards the organizational structure of the system-whether there are subsets of elements with joint causes or effects, and whether the system is strongly integrated or composed of several loosely interacting components. Integrated information theory offers a theoretical framework to (1) investigate the compositional cause-effect structure of a system and to (2) identify causal borders of highly integrated elements comprising local maxima of intrinsic cause-effect power. Here we apply this comprehensive causal analysis to a Boolean network model of the fission yeast (Schizosaccharomyces pombe) cell cycle. We demonstrate that this biological model features a non-trivial causal architecture, whose discovery may provide insights about the real cell cycle that could not be gained from holistic or reductionist approaches. We also show how some specific properties of this underlying causal architecture relate to the biological notion of autonomy. Ultimately, we suggest that analysing the causal organization of a system, including key features like intrinsic control and stable causal borders, should prove relevant for distinguishing life from non-life, and thus could also illuminate the origin of life problem. This article is part of the themed issue 'Reconceptualizing the origins of life'.
Causal inheritance in plane wave quotients
International Nuclear Information System (INIS)
Hubeny, Veronika E.; Rangamani, Mukund; Ross, Simon F.
2003-01-01
We investigate the appearance of closed timelike curves in quotients of plane waves along spacelike isometries. First we formulate a necessary and sufficient condition for a quotient of a general spacetime to preserve stable causality. We explicitly show that the plane waves are stably causal; in passing, we observe that some pp-waves are not even distinguishing. We then consider the classification of all quotients of the maximally supersymmetric ten-dimensional plane wave under a spacelike isometry, and show that the quotient will lead to closed timelike curves iff the isometry involves a translation along the u direction. The appearance of these closed timelike curves is thus connected to the special properties of the light cones in plane wave spacetimes. We show that all other quotients preserve stable causality
Inference of boundaries in causal sets
Cunningham, William J.
2018-05-01
We investigate the extrinsic geometry of causal sets in (1+1) -dimensional Minkowski spacetime. The properties of boundaries in an embedding space can be used not only to measure observables, but also to supplement the discrete action in the partition function via discretized Gibbons–Hawking–York boundary terms. We define several ways to represent a causal set using overlapping subsets, which then allows us to distinguish between null and non-null bounding hypersurfaces in an embedding space. We discuss algorithms to differentiate between different types of regions, consider when these distinctions are possible, and then apply the algorithms to several spacetime regions. Numerical results indicate the volumes of timelike boundaries can be measured to within 0.5% accuracy for flat boundaries and within 10% accuracy for highly curved boundaries for medium-sized causal sets with N = 214 spacetime elements.
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.
Spatial hypersurfaces in causal set cosmology
International Nuclear Information System (INIS)
Major, Seth A; Rideout, David; Surya, Sumati
2006-01-01
Within the causal set approach to quantum gravity, a discrete analogue of a spacelike region is a set of unrelated elements, or an antichain. In the continuum approximation of the theory, a moment-of-time hypersurface is well represented by an inextendible antichain. We construct a richer structure corresponding to a thickening of this antichain containing non-trivial geometric and topological information. We find that covariant observables can be associated with such thickened antichains and transitions between them, in classical sequential growth models of causal sets. This construction highlights the difference between the covariant measure on causal set cosmology and the standard sum-over-histories approach: the measure is assigned to completed histories rather than to histories on a restricted spacetime region. The resulting re-phrasing of the sum-over-histories may be fruitful in other approaches to quantum gravity
Testing the causal theory of reference.
Domaneschi, Filippo; Vignolo, Massimiliano; Di Paola, Simona
2017-04-01
Theories of reference are a crucial research topic in analytic philosophy. Since the publication of Kripke's Naming and Necessity, most philosophers have endorsed the causal/historical theory of reference. The goal of this paper is twofold: (i) to discuss a method for testing experimentally the causal theory of reference for proper names by investigating linguistic usage and (ii) to present the results from two experiments conducted with that method. Data collected in our experiments confirm the causal theory of reference for people proper names and for geographical proper names. A secondary but interesting result is that the semantic domain affects reference assignment: while with people proper names speakers tend to assign the semantic reference, with geographical proper names they are prompted to assign the speaker's reference. Copyright © 2016 Elsevier B.V. All rights reserved.
Bulk viscous cosmology with causal transport theory
International Nuclear Information System (INIS)
Piattella, Oliver F.; Fabris, Júlio C.; Zimdahl, Winfried
2011-01-01
We consider cosmological scenarios originating from a single imperfect fluid with bulk viscosity and apply Eckart's and both the full and the truncated Müller-Israel-Stewart's theories as descriptions of the non-equilibrium processes. Our principal objective is to investigate if the dynamical properties of Dark Matter and Dark Energy can be described by a single viscous fluid and how such description changes when a causal theory (Müller-Israel-Stewart's, both in its full and truncated forms) is taken into account instead of Eckart's non-causal one. To this purpose, we find numerical solutions for the gravitational potential and compare its behaviour with the corresponding ΛCDM case. Eckart's and the full causal theory seem to be disfavoured, whereas the truncated theory leads to results similar to those of the ΛCDM model for a bulk viscous speed in the interval 10 −11 || cb 2 ∼ −8
Causal inheritance in plane wave quotients
Hubeny, Veronika E.; Rangamani, Mukund; Ross, Simon F.
2004-01-01
We investigate the appearance of closed timelike curves in quotients of plane waves along spacelike isometries. First we formulate a necessary and sufficient condition for a quotient of a general space-time to preserve stable causality. We explicitly show that the plane waves are stably causal; in passing, we observe that some pp waves are not even distinguishing. We then consider the classification of all quotients of the maximally supersymmetric ten-dimensional plane wave under a spacelike isometry, and show that the quotient will lead to closed timelike curves iff the isometry involves a translation along the u direction. The appearance of these closed timelike curves is thus connected to the special properties of the light cones in plane wave space-times. We show that all other quotients preserve stable causality.
Two-Microphone Separation of Speech Mixtures
DEFF Research Database (Denmark)
Pedersen, Michael Syskind; Wang, DeLiang; Larsen, Jan
2008-01-01
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...
Detecting causal drivers and empirical prediction of the Indian Summer Monsoon
Di Capua, G.; Vellore, R.; Raghavan, K.; Coumou, D.
2017-12-01
The Indian summer monsoon (ISM) is crucial for the economy, society and natural ecosystems on the Indian peninsula. Predict the total seasonal rainfall at several months lead time would help to plan effective water management strategies, improve flood or drought protection programs and prevent humanitarian crisis. However, the complexity and strong internal variability of the ISM circulation system make skillful seasonal forecasting challenging. Moreover, to adequately identify the low-frequency, and far-away processes which influence ISM behavior novel tools are needed. We applied a Response-Guided Causal Precursor Detection (RGCPD) scheme, which is a novel empirical prediction method which unites a response-guided community detection scheme with a causal discovery algorithm (CEN). These tool allow us to assess causal pathways between different components of the ISM circulation system and with far-away regions in the tropics, mid-latitudes or Arctic. The scheme has successfully been used to identify causal precursors of the Stratospheric polar vortex enabling skillful predictions at (sub) seasonal timescales (Kretschmer et al. 2016, J.Clim., Kretschmer et al. 2017, GRL). We analyze observed ISM monthly rainfall over the monsoon trough region. Applying causal discovery techniques, we identify several causal precursor communities in the fields of 2m-temperature, sea level pressure and snow depth over Eurasia. Specifically, our results suggest that surface temperature conditions in both tropical and Arctic regions contribute to ISM variability. A linear regression prediction model based on the identified set of communities has good hindcasting skills with 4-5 months lead times. Further we separate El Nino, La Nina and ENSO-neutral years from each other and find that the causal precursors are different dependent on ENSO state. The ENSO-state dependent causal precursors give even higher skill, especially for La Nina years when the ISM is relatively strong. These
Neural correlates of continuous causal word generation.
Wende, Kim C; Straube, Benjamin; Stratmann, Mirjam; Sommer, Jens; Kircher, Tilo; Nagels, Arne
2012-09-01
Causality provides a natural structure for organizing our experience and language. Causal reasoning during speech production is a distinct aspect of verbal communication, whose related brain processes are yet unknown. The aim of the current study was to investigate the neural mechanisms underlying the continuous generation of cause-and-effect coherences during overt word production. During fMRI data acquisition participants performed three verbal fluency tasks on identical cue words: A novel causal verbal fluency task (CVF), requiring the production of multiple reasons to a given cue word (e.g. reasons for heat are fire, sun etc.), a semantic (free association, FA, e.g. associations with heat are sweat, shower etc.) and a phonological control task (phonological verbal fluency, PVF, e.g. rhymes with heat are meat, wheat etc.). We found that, in contrast to PVF, both CVF and FA activated a left lateralized network encompassing inferior frontal, inferior parietal and angular regions, with further bilateral activation in middle and inferior as well as superior temporal gyri and the cerebellum. For CVF contrasted against FA, we found greater bold responses only in the left middle frontal cortex. Large overlaps in the neural activations during free association and causal verbal fluency indicate that the access to causal relationships between verbal concepts is at least partly based on the semantic neural network. The selective activation in the left middle frontal cortex for causal verbal fluency suggests that distinct neural processes related to cause-and-effect-relations are associated with the recruitment of middle frontal brain areas. Copyright © 2012 Elsevier Inc. All rights reserved.
BOLD Granger causality reflects vascular anatomy.
Directory of Open Access Journals (Sweden)
J Taylor Webb
Full Text Available A number of studies have tried to exploit subtle phase differences in BOLD time series to resolve the order of sequential activation of brain regions, or more generally the ability of signal in one region to predict subsequent signal in another region. More recently, such lag-based measures have been applied to investigate directed functional connectivity, although this application has been controversial. We attempted to use large publicly available datasets (FCON 1000, ADHD 200, Human Connectome Project to determine whether consistent spatial patterns of Granger Causality are observed in typical fMRI data. For BOLD datasets from 1,240 typically developing subjects ages 7-40, we measured Granger causality between time series for every pair of 7,266 spherical ROIs covering the gray matter and 264 seed ROIs at hubs of the brain's functional network architecture. Granger causality estimates were strongly reproducible for connections in a test and replication sample (n=620 subjects for each group, as well as in data from a single subject scanned repeatedly, both during resting and passive video viewing. The same effect was even stronger in high temporal resolution fMRI data from the Human Connectome Project, and was observed independently in data collected during performance of 7 task paradigms. The spatial distribution of Granger causality reflected vascular anatomy with a progression from Granger causality sources, in Circle of Willis arterial inflow distributions, to sinks, near large venous vascular structures such as dural venous sinuses and at the periphery of the brain. Attempts to resolve BOLD phase differences with Granger causality should consider the possibility of reproducible vascular confounds, a problem that is independent of the known regional variability of the hemodynamic response.
Predicting skin permeability from complex chemical mixtures
International Nuclear Information System (INIS)
Riviere, Jim E.; Brooks, James D.
2005-01-01
Occupational and environmental exposure to topical chemicals is usually in the form of complex chemical mixtures, yet risk assessment is based on experimentally derived data from individual chemical exposures from a single, usually aqueous vehicle, or from computed physiochemical properties. We present an approach using hybrid quantitative structure permeation relationships (QSPeR) models where absorption through porcine skin flow-through diffusion cells is well predicted using a QSPeR model describing the individual penetrants, coupled with a mixture factor (MF) that accounts for physicochemical properties of the vehicle/mixture components. The baseline equation is log k p = c + mMF + aΣα 2 H + bΣβ 2 H + sπ 2 H + rR 2 + vV x where Σα 2 H is the hydrogen-bond donor acidity, Σβ 2 H is the hydrogen-bond acceptor basicity, π 2 H is the dipolarity/polarizability, R 2 represents the excess molar refractivity, and V x is the McGowan volume of the penetrants of interest; c, m, a, b, s, r, and v are strength coefficients coupling these descriptors to skin permeability (k p ) of 12 penetrants (atrazine, chlorpyrifos, ethylparathion, fenthion, methylparathion, nonylphenol, ρ-nitrophenol, pentachlorophenol, phenol, propazine, simazine, and triazine) in 24 mixtures. Mixtures consisted of full factorial combinations of vehicles (water, ethanol, propylene glycol) and additives (sodium lauryl sulfate, methyl nicotinate). An additional set of 4 penetrants (DEET, SDS, permethrin, ricinoleic acid) in different mixtures were included to assess applicability of this approach. This resulted in a dataset of 16 compounds administered in 344 treatment combinations. Across all exposures with no MF, R 2 for absorption was 0.62. With the MF, correlations increased up to 0.78. Parameters correlated to the MF include refractive index, polarizability and log (1/Henry's Law Constant) of the mixture components. These factors should not be considered final as the focus of these studies
Causal interpretation of stochastic differential equations
DEFF Research Database (Denmark)
Sokol, Alexander; Hansen, Niels Richard
2014-01-01
We give a causal interpretation of stochastic differential equations (SDEs) by defining the postintervention SDE resulting from an intervention in an SDE. We show that under Lipschitz conditions, the solution to the postintervention SDE is equal to a uniform limit in probability of postintervention...... structural equation models based on the Euler scheme of the original SDE, thus relating our definition to mainstream causal concepts. We prove that when the driving noise in the SDE is a Lévy process, the postintervention distribution is identifiable from the generator of the SDE....
Morse theory on timelike and causal curves
International Nuclear Information System (INIS)
Everson, J.; Talbot, C.J.
1976-01-01
It is shown that the set of timelike curves in a globally hyperbolic space-time manifold can be given the structure of a Hilbert manifold under a suitable definition of 'timelike.' The causal curves are the topological closure of this manifold. The Lorentzian energy (corresponding to Milnor's energy, except that the Lorentzian inner product is used) is shown to be a Morse function for the space of causal curves. A fixed end point index theorem is obtained in which a lower bound for the index of the Hessian of the Lorentzian energy is given in terms of the sum of the orders of the conjugate points between the end points. (author)
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...
Poisson Mixture Regression Models for Heart Disease Prediction.
Mufudza, Chipo; Erol, Hamza
2016-01-01
Early heart disease control can be achieved by high disease prediction and diagnosis efficiency. This paper focuses on the use of model based clustering techniques to predict and diagnose heart disease via Poisson mixture regression models. Analysis and application of Poisson mixture regression models is here addressed under two different classes: standard and concomitant variable mixture regression models. Results show that a two-component concomitant variable Poisson mixture regression model predicts heart disease better than both the standard Poisson mixture regression model and the ordinary general linear Poisson regression model due to its low Bayesian Information Criteria value. Furthermore, a Zero Inflated Poisson Mixture Regression model turned out to be the best model for heart prediction over all models as it both clusters individuals into high or low risk category and predicts rate to heart disease componentwise given clusters available. It is deduced that heart disease prediction can be effectively done by identifying the major risks componentwise using Poisson mixture regression model.
mixtools: An R Package for Analyzing Mixture Models
Directory of Open Access Journals (Sweden)
Tatiana Benaglia
2009-10-01
Full Text Available The mixtools package for R provides a set of functions for analyzing a variety of finite mixture models. These functions include both traditional methods, such as EM algorithms for univariate and multivariate normal mixtures, and newer methods that reflect some recent research in finite mixture models. In the latter category, mixtools provides algorithms for estimating parameters in a wide range of different mixture-of-regression contexts, in multinomial mixtures such as those arising from discretizing continuous multivariate data, in nonparametric situations where the multivariate component densities are completely unspecified, and in semiparametric situations such as a univariate location mixture of symmetric but otherwise unspecified densities. Many of the algorithms of the mixtools package are EM algorithms or are based on EM-like ideas, so this article includes an overview of EM algorithms for finite mixture models.
Mixture of Regression Models with Single-Index
Xiang, Sijia; Yao, Weixin
2016-01-01
In this article, we propose a class of semiparametric mixture regression models with single-index. We argue that many recently proposed semiparametric/nonparametric mixture regression models can be considered special cases of the proposed model. However, unlike existing semiparametric mixture regression models, the new pro- posed model can easily incorporate multivariate predictors into the nonparametric components. Backfitting estimates and the corresponding algorithms have been proposed for...
Velocity limitations in coaxial plasma gun experiments with gas mixtures
International Nuclear Information System (INIS)
Axnaes, I.
1976-04-01
The velocity limitations found in many crossed field plasma experiments with neutral gas present are studied for binary mixtures of H 2 , He, N 2 O 2 , Ne and Ar. The apparatus used is a coaxial plasma gun with an azimuthal magnetic bias field. The discharge parameters are chosen so that the plasma is weakly ionized. In some of the mixtures it is found that one of the components tends to dominate in the sense that only a small amount (regarding volume) of that component is needed for the discharge to adopt a limiting velocity close to that for the pure component. Thus in a mixture between a heavy and a light component having nearly equal ionization potentials the heavy component dominates. Also if there is a considerable difference in ionization potential between the components, the component with the lowest ionization potential tends to dominate. (author)
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)
Information-causality and extremal tripartite correlations
International Nuclear Information System (INIS)
Yang, Tzyh Haur; Cavalcanti, Daniel; Almeida, Mafalda L; Teo, Colin; Scarani, Valerio
2012-01-01
We study the principle of information-causality (IC) in the presence of extremal no-signaling correlations on a tripartite scenario. We prove that all, except one, of the non-local correlations lead to violation of IC. The remaining non-quantum correlation is shown to satisfy any bipartite physical principle. (paper)
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…
Inductive reasoning about causally transmitted properties.
Shafto, Patrick; Kemp, Charles; Bonawitz, Elizabeth Baraff; Coley, John D; Tenenbaum, Joshua B
2008-11-01
Different intuitive theories constrain and guide inferences in different contexts. Formalizing simple intuitive theories as probabilistic processes operating over structured representations, we present a new computational model of category-based induction about causally transmitted properties. A first experiment demonstrates undergraduates' context-sensitive use of taxonomic and food web knowledge to guide reasoning about causal transmission and shows good qualitative agreement between model predictions and human inferences. A second experiment demonstrates strong quantitative and qualitative fits to inferences about a more complex artificial food web. A third experiment investigates human reasoning about complex novel food webs where species have known taxonomic relations. Results demonstrate a double-dissociation between the predictions of our causal model and a related taxonomic model [Kemp, C., & Tenenbaum, J. B. (2003). Learning domain structures. In Proceedings of the 25th annual conference of the cognitive science society]: the causal model predicts human inferences about diseases but not genes, while the taxonomic model predicts human inferences about genes but not diseases. We contrast our framework with previous models of category-based induction and previous formal instantiations of intuitive theories, and outline challenges in developing a complete model of context-sensitive reasoning.
Exploring Causal Models of Educational Achievement.
Parkerson, Jo Ann; And Others
1984-01-01
This article evaluates five causal model of educational productivity applied to learning science in a sample of 882 fifth through eighth graders. Each model explores the relationship between achievement and a combination of eight constructs: home environment, peer group, media, ability, social environment, time on task, motivation, and…
Sequential causal learning in humans and rats
Lu, H.; Rojas, R.R.; Beckers, T.; Yuille, A.; Love, B.C.; McRae, K.; Sloutsky, V.M.
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.
The Causal Foundations of Structural Equation Modeling
2012-02-16
and Baumrind (1993).” This, together with the steady influx of statisticians into the field, has left SEM re- searchers in a quandary about the...considerations. Journal of Personality and Social Psychology 51 1173–1182. Baumrind , D. (1993). Specious causal attributions in social sciences: The
Causal Measurement Models: Can Criticism Stimulate Clarification?
Markus, Keith A.
2016-01-01
In their 2016 work, Aguirre-Urreta et al. provided a contribution to the literature on causal measurement models that enhances clarity and stimulates further thinking. Aguirre-Urreta et al. presented a form of statistical identity involving mapping onto the portion of the parameter space involving the nomological net, relationships between the…
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.
A Causal Model of Faculty Turnover Intentions.
Smart, John C.
1990-01-01
A causal model assesses the relative influence of individual attributes, institutional characteristics, contextual-work environment variables, and multiple measures of job satisfaction on faculty intentions to leave their current institutions. Factors considered include tenure status, age, institutional status, governance style, organizational…
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
Probable autoimmune causal relationship between periodontitis and ...
African Journals Online (AJOL)
Periodontitis is a multifactorial disease with microbial dental plaque as the initiator of periodontal disease. However, the manifestation and progression of the disease is influenced by a wide variety of determinants and factors. The strongest type of causal relationship is the association of systemic and periodontal disease.
On minimizers of causal variational principles
International Nuclear Information System (INIS)
Schiefeneder, Daniela
2011-01-01
Causal variational principles are a class of nonlinear minimization problems which arise in a formulation of relativistic quantum theory referred to as the fermionic projector approach. This thesis is devoted to a numerical and analytic study of the minimizers of a general class of causal variational principles. We begin with a numerical investigation of variational principles for the fermionic projector in discrete space-time. It is shown that for sufficiently many space-time points, the minimizing fermionic projector induces non-trivial causal relations on the space-time points. We then generalize the setting by introducing a class of causal variational principles for measures on a compact manifold. In our main result we prove under general assumptions that the support of a minimizing measure is either completely timelike, or it is singular in the sense that its interior is empty. In the examples of the circle, the sphere and certain flag manifolds, the general results are supplemented by a more detailed analysis of the minimizers. (orig.)
Causality and analyticity in quantum fields theory
International Nuclear Information System (INIS)
Iagolnitzer, D.
1992-01-01
This is a presentation of results on the causal and analytical structure of Green functions and on the collision amplitudes in fields theories, for massive particles of one type, with a positive mass and a zero spin value. (A.B.)
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 logi...
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'…
Black Hole Complementarity and Violation of Causality
Rozenblit, Moshe
2017-01-01
Analysis of a massive shell collapsing on a solid sphere shows that black hole complementarity (BHC) violates causality in its effort to save information conservation. In particular, this note describes a hypothetical contraption based on BHC that would allow the transfer of information from the future to the present.
Encoding dependence in Bayesian causal networks
Bayesian networks (BNs) represent complex, uncertain spatio-temporal dynamics by propagation of conditional probabilities between identifiable states with a testable causal interaction model. Typically, they assume random variables are discrete in time and space with a static network structure that ...
Causality in the semantics of Esterel : revisited
Mousavi, M.R.; Klin, B.; Sobocinski, P.
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
Scalar field Green functions on causal sets
International Nuclear Information System (INIS)
Nomaan Ahmed, S; Surya, Sumati; Dowker, Fay
2017-01-01
We examine the validity and scope of Johnston’s models for scalar field retarded Green functions on causal sets in 2 and 4 dimensions. As in the continuum, the massive Green function can be obtained from the massless one, and hence the key task in causal set theory is to first identify the massless Green function. We propose that the 2d model provides a Green function for the massive scalar field on causal sets approximated by any topologically trivial 2-dimensional spacetime. We explicitly demonstrate that this is indeed the case in a Riemann normal neighbourhood. In 4d the model can again be used to provide a Green function for the massive scalar field in a Riemann normal neighbourhood which we compare to Bunch and Parker’s continuum Green function. We find that the same prescription can also be used for de Sitter spacetime and the conformally flat patch of anti-de Sitter spacetime. Our analysis then allows us to suggest a generalisation of Johnston’s model for the Green function for a causal set approximated by 3-dimensional flat spacetime. (paper)
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
Causality relationship between energy demand and economic ...
African Journals Online (AJOL)
This paper attempts to examine the causal relationship between electricity demand and economic growth in Nigeria using data for 1970 – 2003. The study uses the Johansen cointegration VAR approach. The ADF and Phillips – Perron test statistics were used to test for stationarity of the data. It was found that the data were ...
Self-consistent calculation of atomic structure for mixture
International Nuclear Information System (INIS)
Meng Xujun; Bai Yun; Sun Yongsheng; Zhang Jinglin; Zong Xiaoping
2000-01-01
Based on relativistic Hartree-Fock-Slater self-consistent average atomic model, atomic structure for mixture is studied by summing up component volumes in mixture. Algorithmic procedure for solving both the group of Thomas-Fermi equations and the self-consistent atomic structure is presented in detail, and, some numerical results are discussed
PREDICTING EVAPORATION RATES AND TIMES FOR SPILLS OF CHEMICAL MIXTURES
Spreadsheet and short-cut methods have been developed for predicting evaporation rates and evaporation times for spills (and constrained baths) of chemical mixtures. Steady-state and time-varying predictions of evaporation rates can be made for six-component mixtures, includ...
Structural properties of dendrimer-colloid mixtures
International Nuclear Information System (INIS)
Lenz, Dominic A; Blaak, Ronald; Likos, Christos N
2012-01-01
We consider binary mixtures of colloidal particles and amphiphilic dendrimers of the second generation by means of Monte Carlo simulations. By using the effective interactions between monomer-resolved dendrimers and colloids, we compare the results of simulations of mixtures stemming from a full monomer-resolved description with the effective two-component description at different densities, composition ratios, colloid diameters and interaction strengths. Additionally, we map the two-component system onto an effective one-component model for the colloids in the presence of the dendrimers. Simulations based on the resulting depletion potentials allow us to extend the comparison to yet another level of coarse graining and to examine under which conditions this two-step approach is valid. In addition, a preliminary outlook into the phase behavior of this system is given. (paper)
Robust classification using mixtures of dependency networks
DEFF Research Database (Denmark)
Gámez, José A.; Mateo, Juan L.; Nielsen, Thomas Dyhre
2008-01-01
Dependency networks have previously been proposed as alternatives to e.g. Bayesian networks by supporting fast algorithms for automatic learning. Recently dependency networks have also been proposed as classiﬁcation models, but as with e.g. general probabilistic inference, the reported speed......-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...
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. © The Author(s) 2016.
GOOS, Peter; JONES, Bradley; SYAFITRI, Utami
2013-01-01
In mixture experiments, the factors under study are proportions of the ingredients of a mixture. The special nature of the factors in a mixture experiment necessitates specific types of regression models, and specific types of experimental designs. Although mixture experiments usually are intended to predict the response(s) for all possible formulations of the mixture and to identify optimal proportions for each of the ingredients, little research has been done concerning their I-optimal desi...
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
Li, Tong; Liu, Shu-Shen; Qu, Rui; Liu, Hai-Ling
2017-10-01
The toxicity of a mixture depends not only on the mixture concentration level but also on the mixture ratio. For a multiple-component mixture (MCM) system with a definite chemical composition, the mixture toxicity can be predicted only if the global concentration additivity (GCA) is validated. The so-called GCA means that the toxicity of any mixture in the MCM system is the concentration additive, regardless of what its mixture ratio and concentration level. However, many mixture toxicity reports have usually employed one mixture ratio (such as the EC 50 ratio), the equivalent effect concentration ratio (EECR) design, to specify several mixtures. EECR mixtures cannot simulate the concentration diversity and mixture ratio diversity of mixtures in the real environment, and it is impossible to validate the GCA. Therefore, in this paper, the uniform design ray (UD-Ray) was used to select nine mixture ratios (rays) in the mixture system of five nitrobenzene derivatives (NBDs). The representative UD-Ray mixtures can effectively and rationally describe the diversity in the NBD mixture system. The toxicities of the mixtures to Vibrio qinghaiensis sp.-Q67 were determined by the microplate toxicity analysis (MTA). For each UD-Ray mixture, the concentration addition (CA) model was used to validate whether the mixture toxicity is additive. All of the UD-Ray mixtures of five NBDs are global concentration additive. Afterwards, the CA is employed to predict the toxicities of the external mixtures from three EECR mixture rays with the NOEC, EC 30 , and EC 70 ratios. The predictive toxicities are in good agreement with the experimental toxicities, which testifies to the predictability of the mixture toxicity of the NBDs. Copyright © 2017. Published by Elsevier Inc.
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. Copyright © 2013 Elsevier Inc. All rights reserved.
The causal link between energy and output growth: Evidence from Markov switching Granger causality
International Nuclear Information System (INIS)
Kandemir Kocaaslan, Ozge
2013-01-01
In this paper we empirically investigate the causal link between energy consumption and economic growth employing a Markov switching Granger causality analysis. We carry out our investigation using annual U.S. real GDP, total final energy consumption and total primary energy consumption data which cover the period between 1968 and 2010. We find that there are significant changes in the causal relation between energy consumption and economic growth over the sample period under investigation. Our results show that total final energy consumption and total primary energy consumption have significant predictive content for real economic activity in the U.S. economy. Furthermore, the causality running from energy consumption to output growth seems to be strongly apparent particularly during the periods of economic downturn and energy crisis. We also document that output growth has predictive power in explaining total energy consumption. Furthermore, the power of output growth in predicting total energy consumption is found to diminish after the mid of 1980s. - Highlights: • Total energy consumption has predictive content for real economic activity. • The causality from energy to output growth is apparent in the periods of recession. • The causality from energy to output growth is strong in the periods of energy crisis. • Output growth has predictive power in explaining total energy consumption. • The power of output growth in explaining energy diminishes after the mid of 1980s
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 PEER EFFECTS IN FINANCIAL DECISION MAKING
Directory of Open Access Journals (Sweden)
Ana Njegovanović
2016-03-01
Full Text Available The research paper connects three key elements from the study (conducted using neural database of experimental asset market that have tested the fundamental mechanisms that generate peer effect, the neural database was measured using functional magnetic resonance imaging (fMRI; Cary Frydman, 2015- University of Southern California-Marshall School of Business relating to: experimental control in the laboratory of random peer assignment,; neural activity in testing new prediction explaining peer effect and neural activity in the conduct of trade. The methodology used in the research of peer effect relies on the theory of predicting error, the signal which measures changes in anticipation of the net present value which generates new information. Cognitive neuroscience shows that the prediction error is measured in a certain part of the brain known as the ventral striatum. Measuring the potential value gives insights to economists on which factors affecting the subjective utility. Testing is constructed with 48 patients who were given $ 100 of experimental money and they were given the opportunity to invest in two separate assets in over two hundred experiments. The experiment showed that subjects converted their final portfolio from experimental currency to real dollars using the exchange rate of 5: 1. In addition to profits from the experiment, subjects were paid a fixed "show-up" fee of $ 20. There are two difficulties in identifying causal peer effect in economic behavior (Minsk, 1993. Correlated behavior between two representatives may potentially be the engine by common shocks of the peer group or endogenous election in the peer group. In addition to the prediction that deals with causal peer effect, there have been further developed predictions that generate different mechanisms of peer effects using neural database. Focus on neural prediction is the neural activity that generates the moment when peers allocation investment is published
Volatilization of multicomponent mixtures in soil vapor extraction applications
International Nuclear Information System (INIS)
Bass, D.H.
1995-01-01
In soil vapor extraction (SVE) applications involving multicomponent mixtures, prediction of mass removal by volatilization as a function remediation extent is required to estimate remediation time and to size offgas treatment equipment. SVE is a commonly used remediation technology which volatilizes and enhances aerobic biodegradation of contamination adsorbed to vadose zone soils. SVE is often applied at sites contaminated with petroleum products, which are usually mixtures of many different compounds with vapor pressures spanning several orders of magnitude. The most volatile components are removed first, so the vapor pressure of the remaining contaminant continually decreases over the course of the remediation. A method for assessing how vapor pressure, and hence the rate of volatilization, of a multicomponent mixture changes over the course of a vapor extraction remedy has been developed. Each component is listed, alone, with its mass fraction in the mixture, in decreasing order of pure component vapor pressure (where component analyses are unavailable, model compounds can be used), For most petroleum distillates, the vapor pressure for each component plotted against the cumulative mass fraction of the component in the mixture on semilog coordinates will produce a straight line with a high correlation coefficient. This regression can be integrated to produce an expression for vapor pressure of the overall mixture as a function of extent or remediation
Elements of Causal Inference: Foundations and Learning Algorithms
DEFF Research Database (Denmark)
Peters, Jonas Martin; Janzing, Dominik; Schölkopf, Bernhard
A concise and self-contained introduction to causal inference, increasingly important in data science and machine learning......A concise and self-contained introduction to causal inference, increasingly important in data science and machine learning...
The causal relationship between Foreign Direct Investment (FDI ...
African Journals Online (AJOL)
The causal relationship between Foreign Direct Investment (FDI) and the ... of selected west African countries: Panel ARDL/Granger Causality Analysis. ... among this developing countries and an important revelation for policy implication.
The Hankel transform of causal distributions
Directory of Open Access Journals (Sweden)
Manuel A. Aguirre T.
2012-03-01
Full Text Available In this note we evaluate the unidimensional distributional Hankel transform of \\dfrac{x^{\\alpha-1}_{+}}{\\Gamma^{\\alpha}},\\dfrac{x^{\\alpha-1}_{-}}{\\Gamma^{\\alpha}},dfrac{|x|^{\\alpha-1}}{\\Gamma^{\\frac{\\alpha}{2}}},dfrac{|x|^{\\alpha-1}sgn(x}{\\Gamma^{\\frac{\\alpha +1}{2}}} and (x± i0^{\\alpha-1} and then we extend the formulae to certain kinds of n-dimensional distributions calles "causal" and "anti-causal" distributions. We evaluate the distributional Handel transform of \\dfrac{(m^2+P^{\\alpha -1}_{-}}{\\Gamma^{(\\alpha} }, \\dfrac{|m^2+P|^{\\alpha -1}_{-}}{\\Gamma^{(\\frac{\\alpha}{2}}}, \\dfrac{|m^2+P|^{\\alpha -1}sgn(m^2+P}{\\Gamma (\\frac{\\alpha +1}{2 }} and (m^2+P±i0^{\\alpha-1}
A new spin on causality constraints
Energy Technology Data Exchange (ETDEWEB)
Hartman, Thomas; Jain, Sachin; Kundu, Sandipan [Department of Physics, Cornell University, Ithaca, New York (United States)
2016-10-26
Causality in a shockwave state is related to the analytic properties of a four-point correlation function. Extending recent results for scalar probes, we show that this constrains the couplings of the stress tensor to light spinning operators in conformal field theory, and interpret these constraints in terms of the interaction with null energy. For spin-1 and spin-2 conserved currents in four dimensions, the resulting inequalities are a subset of the Hofman-Maldacena conditions for positive energy deposition. It is well known that energy conditions in holographic theories are related to causality on the gravity side; our results make a connection on the CFT side, and extend it to non-holographic theories.
Reciprocity, passivity and causality in Willis materials.
Muhlestein, Michael B; Sieck, Caleb F; Alù, Andrea; Haberman, Michael R
2016-10-01
Materials that require coupling between the stress-strain and momentum-velocity constitutive relations were first proposed by Willis (Willis 1981 Wave Motion 3 , 1-11. (doi:10.1016/0165-2125(81)90008-1)) and are now known as elastic materials of the Willis type, or simply Willis materials. As coupling between these two constitutive equations is a generalization of standard elastodynamic theory, restrictions on the physically admissible material properties for Willis materials should be similarly generalized. This paper derives restrictions imposed on the material properties of Willis materials when they are assumed to be reciprocal, passive and causal. Considerations of causality and low-order dispersion suggest an alternative formulation of the standard Willis equations. The alternative formulation provides improved insight into the subwavelength physical behaviour leading to Willis material properties and is amenable to time-domain analyses. Finally, the results initially obtained for a generally elastic material are specialized to the acoustic limit.
Segregation of granular binary mixtures by a ratchet mechanism.
Farkas, Zénó; Szalai, Ferenc; Wolf, Dietrich E; Vicsek, Tamás
2002-02-01
We report on a segregation scheme for granular binary mixtures, where the segregation is performed by a ratchet mechanism realized by a vertically shaken asymmetric sawtooth-shaped base in a quasi-two-dimensional box. We have studied this system by computer simulations and found that most binary mixtures can be segregated using an appropriately chosen ratchet, even when the particles in the two components have the same size and differ only in their normal restitution coefficient or friction coefficient. These results suggest that the components of otherwise nonsegregating granular mixtures may be separated using our method.
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.
Granger-Causality Maps of Diffusion Processes
Czech Academy of Sciences Publication Activity Database
Wahl, B.; Feudel, U.; Hlinka, Jaroslav; Wächter, M.; Peinke, J.; Freund, J.A.
2016-01-01
Roč. 93, č. 2 16 February (2016), č. článku 022213. ISSN 2470-0045 R&D Projects: GA ČR GA13-23940S; GA MZd(CZ) NV15-29835A Institutional support: RVO:67985807 Keywords : Granger causality * stochastic process * diffusion process * nonlinear dynamical systems Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 2.366, year: 2016
Improved gas mixtures for gas-filled particle detectors
Christophorou, L.G.; McCorkle, D.L.; Maxey, D.V.; Carter, J.G.
Improved binary and tertiary gas mixture for gas-filled particle detectors are provided. The components are chosen on the basis of the principle that the first component is one gas or mixture of two gases having a large electron scattering cross section at energies of about 0.5 eV and higher, and the second component is a gas (Ar) having a very small cross section at and below about 0.5 eV; whereby fast electrons in the gaseous mixture are slowed into the energy range of about 0.5 eV where the cross section for the mixture is small and hence the electron mean free path is large. The reduction in both the cross section and the electron energy results in an increase in the drift velocity of the electrons in the gas mixtures over that for the separate components for a range of E/P (pressure-reduced electron field) values. Several gas mixtures are provided that provide faster response in gas-filled detectors for convenient E/P ranges as compared with conventional gas mixtures.
Curvature constraints from the causal entropic principle
International Nuclear Information System (INIS)
Bozek, Brandon; Albrecht, Andreas; Phillips, Daniel
2009-01-01
Current cosmological observations indicate a preference for a cosmological constant that is drastically smaller than what can be explained by conventional particle physics. The causal entropic principle (Bousso et al.) provides an alternative approach to anthropic attempts to predict our observed value of the cosmological constant by calculating the entropy created within a causal diamond. We have extended this work to use the causal entropic principle to predict the preferred curvature within the 'multiverse'. We have found that values larger than ρ k =40ρ m are disfavored by more than 99.99% peak value at ρ Λ =7.9x10 -123 and ρ k =4.3ρ m for open universes. For universes that allow only positive curvature or both positive and negative curvature, we find a correlation between curvature and dark energy that leads to an extended region of preferred values. Our universe is found to be disfavored to an extent depending on the priors on curvature. We also provide a comparison to previous anthropic constraints on open universes and discuss future directions for this work.
Structure induction in diagnostic causal reasoning.
Meder, Björn; Mayrhofer, Ralf; Waldmann, Michael R
2014-07-01
Our research examines the normative and descriptive adequacy of alternative computational models of diagnostic reasoning from single effects to single causes. Many theories of diagnostic reasoning are based on the normative assumption that inferences from an effect to its cause should reflect solely the empirically observed conditional probability of cause given effect. We argue against this assumption, as it neglects alternative causal structures that may have generated the sample data. Our structure induction model of diagnostic reasoning takes into account the uncertainty regarding the underlying causal structure. A key prediction of the model is that diagnostic judgments should not only reflect the empirical probability of cause given effect but should also depend on the reasoner's beliefs about the existence and strength of the link between cause and effect. We confirmed this prediction in 2 studies and showed that our theory better accounts for human judgments than alternative theories of diagnostic reasoning. Overall, our findings support the view that in diagnostic reasoning people go "beyond the information given" and use the available data to make inferences on the (unobserved) causal rather than on the (observed) data level. (c) 2014 APA, all rights reserved.
Causal inference of asynchronous audiovisual speech
Directory of Open Access Journals (Sweden)
John F Magnotti
2013-11-01
Full Text Available During speech perception, humans integrate auditory information from the voice with visual information from the face. This multisensory integration increases perceptual precision, but only if the two cues come from the same talker; this requirement has been largely ignored by current models of speech perception. We describe a generative model of multisensory speech perception that includes this critical step of determining the likelihood that the voice and face information have a common cause. A key feature of the model is that it is based on a principled analysis of how an observer should solve this causal inference problem using the asynchrony between two cues and the reliability of the cues. This allows the model to make predictions abut the behavior of subjects performing a synchrony judgment task, predictive power that does not exist in other approaches, such as post hoc fitting of Gaussian curves to behavioral data. We tested the model predictions against the performance of 37 subjects performing a synchrony judgment task viewing audiovisual speech under a variety of manipulations, including varying asynchronies, intelligibility, and visual cue reliability. The causal inference model outperformed the Gaussian model across two experiments, providing a better fit to the behavioral data with fewer parameters. Because the causal inference model is derived from a principled understanding of the task, model parameters are directly interpretable in terms of stimulus and subject properties.
Mind and Meaning: Piaget and Vygotsky on Causal Explanation.
Beilin, Harry
1996-01-01
Piaget's theory has been characterized as descriptive and not explanatory, not qualifying as causal explanation. Piaget was consistent in showing how his theory was both explanatory and causal. Vygotsky also endorsed causal-genetic explanation but, on the basis of knowledge of only Piaget's earliest works, he claimed that Piaget's theory was not…
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…
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…
Yield and competition in barley variety mixtures
Directory of Open Access Journals (Sweden)
Kari Jokinen
1991-09-01
Full Text Available Competition between spring barley varieties and yield performance of two-, three and four-variety mixtures were studied in two replacement series field experiments. In the first experiment, repeated in three successive years (1983 —85 the components were the six-row varieties Agneta, Arra, Hja-673 and Porno. In the second experiment (1984, including two nitrogen doses (50 and 100 kgN/ha, both six-row (Agneta, Pomo and two-row (Ida, Kustaa varieties were used. Arra in the first and Agneta in the second experiment were the most competitive varieties. The results suggested that the fast growth of Arra at the beginning promoted its competitive ability. Increase in available nitrogen usually strengthened the competitiveness of Agneta. The observed competitive differences between varieties were not related to the earliness of a variety, neither to the morphological characters (two- and six-row varieties nor to the grain yield of a variety grown alone. The competitive ability was not always a stable character, the dominant suppression relationship varying from one environment to another (e.g. growing season, nitrogen dose. The observed overyielding was not statistically significant. The ratio of actual to expected yield and the relative yield total of several mixtures exceeded slightly one. As a conclusion, the yield advantage of mixtures was marginal. As a rule, the mixtures were not more stable than monocultures as determined by the coefficient of variation. However, the yield of some mixtures varied less than the yield of the most stable monoculture.
Mixture based outlier filtration
Czech Academy of Sciences Publication Activity Database
Pecherková, Pavla; Nagy, Ivan
2006-01-01
Roč. 46, č. 2 (2006), s. 30-35 ISSN 1210-2709 R&D Projects: GA MŠk 1M0572; GA MDS 1F43A/003/120 Institutional research plan: CEZ:AV0Z10750506 Keywords : data filtration * system modelling * mixture models Subject RIV: BD - Theory of Information http://library.utia.cas.cz/prace/20060165.pdf
Yang, Hsiao-Yu; Chen, Pau-Chung; Wang, Jung-Der
2014-01-01
Herbal remedies containing aristolochic acid (AA) have been designated to be a strong carcinogen. This review summarizes major epidemiologic evidence to argue for the causal association between AA exposure and urothelial carcinoma as well as nephropathy. The exposure scenarios include the following: Belgian women taking slimming pills containing single material Guang Fang Ji, consumptions of mixtures of Chinese herbal products in the general population and patients with chronic renal failure ...
Hagmayer, York; Engelmann, Neele
2014-01-01
Cognitive psychological research focuses on causal learning and reasoning while cognitive anthropological and social science research tend to focus on systems of beliefs. Our aim was to explore how these two types of research can inform each other. Cognitive psychological theories (causal model theory and causal Bayes nets) were used to derive predictions for systems of causal beliefs. These predictions were then applied to lay theories of depression as a specific test case. A systematic lite...
A Bayesian Theory of Sequential Causal Learning and Abstract Transfer.
Lu, Hongjing; Rojas, Randall R; Beckers, Tom; Yuille, Alan L
2016-03-01
Two key research issues in the field of causal learning are how people acquire causal knowledge when observing data that are presented sequentially, and the level of abstraction at which learning takes place. Does sequential causal learning solely involve the acquisition of specific cause-effect links, or do learners also acquire knowledge about abstract causal constraints? Recent empirical studies have revealed that experience with one set of causal cues can dramatically alter subsequent learning and performance with entirely different cues, suggesting that learning involves abstract transfer, and such transfer effects involve sequential presentation of distinct sets of causal cues. It has been demonstrated that pre-training (or even post-training) can modulate classic causal learning phenomena such as forward and backward blocking. To account for these effects, we propose a Bayesian theory of sequential causal learning. The theory assumes that humans are able to consider and use several alternative causal generative models, each instantiating a different causal integration rule. Model selection is used to decide which integration rule to use in a given learning environment in order to infer causal knowledge from sequential data. Detailed computer simulations demonstrate that humans rely on the abstract characteristics of outcome variables (e.g., binary vs. continuous) to select a causal integration rule, which in turn alters causal learning in a variety of blocking and overshadowing paradigms. When the nature of the outcome variable is ambiguous, humans select the model that yields the best fit with the recent environment, and then apply it to subsequent learning tasks. Based on sequential patterns of cue-outcome co-occurrence, the theory can account for a range of phenomena in sequential causal learning, including various blocking effects, primacy effects in some experimental conditions, and apparently abstract transfer of causal knowledge. Copyright © 2015
Bright solitons in Bose-Fermi mixtures
International Nuclear Information System (INIS)
Karpiuk, Tomasz; Brewczyk, Miroslaw; RzaPewski, Kazimierz
2006-01-01
We consider the formation of bright solitons in a mixture of Bose and Fermi degenerate gases confined in a three-dimensional elongated harmonic trap. The Bose and Fermi atoms are assumed to effectively attract each other whereas bosonic atoms repel each other. Strong enough attraction between bosonic and fermionic components can change the character of the interaction within the bosonic cloud from repulsive to attractive making thus possible the generation of bright solitons in the mixture. On the other hand, such structures might be in danger due to the collapse phenomenon existing in attractive gases. We show, however, that under some conditions (defined by the strength of the Bose-Fermi components attraction) the structures which neither spread nor collapse can be generated. For elongated enough traps the formation of solitons is possible even at the 'natural' value of the mutual Bose-Fermi ( 87 Rb- 40 K in our case) scattering length
Mixture for plugging absorption zones
Energy Technology Data Exchange (ETDEWEB)
Sitinkov, G V; Kovalenko, N G; Makarov, L V; Zinnatulchin, Ts Kh
1981-01-17
A mixture is proposed for plugging absorption zones. The mixture contains synthetic polymer and a solvent. So as to increase the penetrability of the mixture through a reduction in its viscosity and an increase in insulation properties, the compound contains either Capron or Neilon as the synthetic polyamide resin polmyer, and concentrated chloride as the solvent. The mixture is prepared in a special AzINMASh-30 unit (acid cart). After the mixture has been produced, it is injected into the borehole by means of an acid cart pump. So as to prevent coaggulation at the point when the mixture in injected into the stratum through tubes, the mixture is placed betwen chemically inert fluids, for example, a clay mortar. The inert and compressed fluids are injected by means of a cementing unit. The entire process of production and application of the mixture is simple and fully automated through the use of well-known equipment.
Information causality from an entropic and a probabilistic perspective
International Nuclear Information System (INIS)
Al-Safi, Sabri W.; Short, Anthony J.
2011-01-01
The information causality principle is a generalization of the no-signaling principle which implies some of the known restrictions on quantum correlations. But despite its clear physical motivation, information causality is formulated in terms of a rather specialized game and figure of merit. We explore different perspectives on information causality, discussing the probability of success as the figure of merit, a relation between information causality and the nonlocal ''inner-product game,'' and the derivation of a quadratic bound for these games. We then examine an entropic formulation of information causality with which one can obtain the same results, arguably in a simpler fashion.
International Nuclear Information System (INIS)
Anon.
1993-01-01
This chapter includes descriptions of electronic and mechanical components which do not merit a chapter to themselves. Other hardware requires mention because of particularly high tolerance or intolerance of exposure to radiation. A more systematic analysis of radiation responses of structures which are definable by material was given in section 3.8. The components discussed here are field effect transistors, transducers, temperature sensors, magnetic components, superconductors, mechanical sensors, and miscellaneous electronic components
Interactions of information transfer along separable causal paths
Jiang, Peishi; Kumar, Praveen
2018-04-01
Complex systems arise as a result of interdependences between multiple variables, whose causal interactions can be visualized in a time-series graph. Transfer entropy and information partitioning approaches have been used to characterize such dependences. However, these approaches capture net information transfer occurring through a multitude of pathways involved in the interaction and as a result mask our ability to discern the causal interaction within a subgraph of interest through specific pathways. We build on recent developments of momentary information transfer along causal paths proposed by Runge [Phys. Rev. E 92, 062829 (2015), 10.1103/PhysRevE.92.062829] to develop a framework for quantifying information partitioning along separable causal paths. Momentary information transfer along causal paths captures the amount of information transfer between any two variables lagged at two specific points in time. Our approach expands this concept to characterize the causal interaction in terms of synergistic, unique, and redundant information transfer through separable causal paths. Through a graphical model, we analyze the impact of the separable and nonseparable causal paths and the causality structure embedded in the graph as well as the noise effect on information partitioning by using synthetic data generated from two coupled logistic equation models. Our approach can provide a valuable reference for an autonomous information partitioning along separable causal paths which form a causal subgraph influencing a target.
The selective power of causality on memory errors.
Marsh, Jessecae K; Kulkofsky, Sarah
2015-01-01
We tested the influence of causal links on the production of memory errors in a misinformation paradigm. Participants studied a set of statements about a person, which were presented as either individual statements or pairs of causally linked statements. Participants were then provided with causally plausible and causally implausible misinformation. We hypothesised that studying information connected with causal links would promote representing information in a more abstract manner. As such, we predicted that causal information would not provide an overall protection against memory errors, but rather would preferentially help in the rejection of misinformation that was causally implausible, given the learned causal links. In two experiments, we measured whether the causal linkage of information would be generally protective against all memory errors or only selectively protective against certain types of memory errors. Causal links helped participants reject implausible memory lures, but did not protect against plausible lures. Our results suggest that causal information may promote an abstract storage of information that helps prevent only specific types of memory errors.
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...
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 t...
Causal asymmetry across cultures: Assigning causal roles in symmetric physical settings
Directory of Open Access Journals (Sweden)
Andrea eBender
2011-09-01
Full Text Available In the cognitive sciences, causal cognition in the physical domain has featured as a core research topic, but the impact of culture has been rarely ever explored. One case in point for a topic on which this neglect is pronounced is the pervasive tendency of people to consider one of two (equally important entities as more important for bringing about an effect. In order to scrutinize how robust such tendencies are across cultures, we asked German and Tongan participants to assign prime causality in nine symmetric settings. For most settings, strong asymmetries in both cultures were found, but not always in the same direction, depending on the task content. This indicates that causal asymmetries, while indeed being a robust phenomenon across cultures, are also subject to culture-specific concepts. Moreover, the asymmetries were found to be modulated by figure-ground relations, but not by marking agency.
How multiple causes combine: independence constraints on causal inference.
Liljeholm, Mimi
2015-01-01
According to the causal power view, two core constraints-that causes occur independently (i.e., no confounding) and influence their effects independently-serve as boundary conditions for causal induction. This study investigated how violations of these constraints modulate uncertainty about the existence and strength of a causal relationship. Participants were presented with pairs of candidate causes that were either confounded or not, and that either interacted or exerted their influences independently. Consistent with the causal power view, uncertainty about the existence and strength of causal relationships was greater when causes were confounded or interacted than when unconfounded and acting independently. An elemental Bayesian causal model captured differences in uncertainty due to confounding but not those due to an interaction. Implications of distinct sources of uncertainty for the selection of contingency information and causal generalization are discussed.
Mixture toxicity revisited from a toxicogenomic perspective.
Altenburger, Rolf; Scholz, Stefan; Schmitt-Jansen, Mechthild; Busch, Wibke; Escher, Beate I
2012-03-06
The advent of new genomic techniques has raised expectations that central questions of mixture toxicology such as for mechanisms of low dose interactions can now be answered. This review provides an overview on experimental studies from the past decade that address diagnostic and/or mechanistic questions regarding the combined effects of chemical mixtures using toxicogenomic techniques. From 2002 to 2011, 41 studies were published with a focus on mixture toxicity assessment. Primarily multiplexed quantification of gene transcripts was performed, though metabolomic and proteomic analysis of joint exposures have also been undertaken. It is now standard to explicitly state criteria for selecting concentrations and provide insight into data transformation and statistical treatment with respect to minimizing sources of undue variability. Bioinformatic analysis of toxicogenomic data, by contrast, is still a field with diverse and rapidly evolving tools. The reported combined effect assessments are discussed in the light of established toxicological dose-response and mixture toxicity models. Receptor-based assays seem to be the most advanced toward establishing quantitative relationships between exposure and biological responses. Often transcriptomic responses are discussed based on the presence or absence of signals, where the interpretation may remain ambiguous due to methodological problems. The majority of mixture studies design their studies to compare the recorded mixture outcome against responses for individual components only. This stands in stark contrast to our existing understanding of joint biological activity at the levels of chemical target interactions and apical combined effects. By joining established mixture effect models with toxicokinetic and -dynamic thinking, we suggest a conceptual framework that may help to overcome the current limitation of providing mainly anecdotal evidence on mixture effects. To achieve this we suggest (i) to design studies to
Separation of organic azeotropic mixtures by pervaporation. Final technical report
Energy Technology Data Exchange (ETDEWEB)
Baker, R.W.
1991-12-01
Distillation is a commonly used separation technique in the petroleum refining and chemical processing industries. However, there are a number of potential separations involving azetropic and close-boiling organic mixtures that cannot be separated efficiently by distillation. Pervaporation is a membrane-based process that uses selective permeation through membranes to separate liquid mixtures. Because the separation process is not affected by the relative volatility of the mixture components being separated, pervaporation can be used to separate azetropes and close-boiling mixtures. Our results showed that pervaporation membranes can be used to separate azeotropic mixtures efficiently, a result that is not achievable with simple distillation. The membranes were 5--10 times more permeable to one of the components of the mixture, concentrating it in the permeate stream. For example, the membrane was 10 times more permeable to ethanol than methyl ethyl ketone, producing 60% ethanol permeate from an azeotropic mixture of ethanol and methyl ethyl ketone containing 18% ethanol. For the ethyl acetate/water mixture, the membranes showed a very high selectivity to water (> 300) and the permeate was 50--100 times enriched in water relative to the feed. The membranes had permeate fluxes on the order of 0.1--1 kg/m{sup 2}{center_dot}h in the operating range of 55--70{degrees}C. Higher fluxes were obtained by increasing the operating temperature.
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
Prevalence Incidence Mixture Models
The R package and webtool fits Prevalence Incidence Mixture models to left-censored and irregularly interval-censored time to event data that is commonly found in screening cohorts assembled from electronic health records. Absolute and relative risk can be estimated for simple random sampling, and stratified sampling (the two approaches of superpopulation and a finite population are supported for target populations). Non-parametric (absolute risks only), semi-parametric, weakly-parametric (using B-splines), and some fully parametric (such as the logistic-Weibull) models are supported.
A Causal Theory of Mnemonic Confabulation
Directory of Open Access Journals (Sweden)
Sven Bernecker
2017-07-01
Full Text Available This paper attempts to answer the question of what defines mnemonic confabulation vis-à-vis genuine memory. The two extant accounts of mnemonic confabulation as “false memory” and as ill-grounded memory are shown to be problematic, for they cannot account for the possibility of veridical confabulation, ill-grounded memory, and well-grounded confabulation. This paper argues that the defining characteristic of mnemonic confabulation is that it lacks the appropriate causal history. In the confabulation case, there is no proper counterfactual dependence of the state of seeming to remember on the corresponding past representation.
De Broglie's causal interpretations of quantum mechanics
International Nuclear Information System (INIS)
Ben-Dov, Y.
1989-01-01
In this article we trace the history of de Broglie's two causal interpretations of quantum mechanics, namely the double solution and the pilot wave theories, at the two periods in which he developed them: 1924-27 and 1952 onwards. Examining the reasons for which he always preferred the first theory to the second, reasons that are mainly concerned with the question of the physical nature of the quantum wave function, we try to show the continuity and the coherence of his underlying vision
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.
Conditional Granger Causality of Diffusion Processes
Czech Academy of Sciences Publication Activity Database
Wahl, B.; Feudel, U.; Hlinka, Jaroslav; Wächter, M.; Peinke, J.; Freund, J.A.
2017-01-01
Roč. 90, č. 10 (2017), č. článku 197. ISSN 1434-6028 R&D Projects: GA ČR GA13-23940S; GA MZd(CZ) NV15-29835A Institutional support: RVO:67985807 Keywords : Granger causality * stochastic process * diffusion process * nonlinear dynamical systems Subject RIV: BB - Applied Statistics, Operational Research OBOR OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) Impact factor: 1.461, year: 2016
Initiation of explosive mixtures having multi-sized structures
Vasil'ev, A. A.; Vasiliev, V. A.; Trotsyuk, A. V.
2016-10-01
Theory of strong blast was used as the basis for the experimental method of determining of the energy of source which provides the initiation of combustible mixture. For mono-fuel mixtures the following parameters were experimentally determined at testing: the critical initiation energy of a cylindrical detonation wave in mixtures 2H2+O2 and C2H2+2.5O2 (exploding wire); the critical initiation energy of a spherical detonation in a mixture of C2H2+2.5O2 (electrical discharge). Similarly, for the double-fuel mixtures of acetylene - nitrous oxide - oxygen (having bifurcation cellular structures) the critical initiation energy of spherical wave was determined also. It was found that for the stoichiometric mixture on both fuel components the critical energy of mixture with the bifurcation structure was undervalued by several times in comparison with the value of the critical energy for the mono-fuel mixture, in which the cell size at a given pressure is determined by the large scale of bifurcation cells. This result shows the decrease of the critical energy with an increase of the number of "hot spots", which are the numerous areas of collision of the transverse waves of large and small scales in a mixture with bifurcation properties.
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
¿CONFIEREN PODERES CAUSALES LOS UNIVERSALES TRASCENDENTES?
Directory of Open Access Journals (Sweden)
José Tomás Alvarado Marambio
2013-11-01
Full Text Available This work discusses the so-called ‘Eleatic’ argument against the existence of transcendent universals, i. e. universals which does not require instantiation for its existence. The Eleatic Principle states that everything produces a difference in the causal powers of something. As transcendent universals seem not to produce such a difference, transcendent universals seem not to exist. The argument depends crucially on the justification and the interpretation of the Eleatic Principle. It is argued, first, that it is not very clear that the principle is justified, and, second, that there are several alternatives for its interpretation, in relation with the different theories one can endorse about modality or causality. Anti-realist theories of modality or causality are not very appropriate for the understanding of what should be a ‘causal power’. Neither does a realist theory of causality conjoined with a combinatorial theory of possible worlds. A ‘causal power’ seems to be better understood in connection with a realist –non-reductionist– theory of causality and a causal theory of modality. Taken in this way the Eleatic Principle, nonetheless, it is argued that transcendent universals do ‘produce’ a difference in causal powers, for every causal connection requires such universals for its existence.
Are bruxism and the bite causally related?
Lobbezoo, F; Ahlberg, J; Manfredini, D; Winocur, E
2012-07-01
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] AND (Dental Occlusion [Majr] OR Malocclusion [Majr])', yielded 93 articles, of which 46 papers were finally included in the present review*. Part of the included publications dealt with the possible associations between bruxism and aspects of occlusion, from which it was concluded that neither for occlusal interferences nor for factors related to the anatomy of the oro-facial skeleton, there is any evidence available that they are involved in the aetiology of bruxism. Instead, there is a growing awareness of other factors (viz. psychosocial and behavioural ones) being important in the aetiology of bruxism. Another part of the included papers assessed the possible mediating role of occlusion between bruxism and its purported consequences (e.g. tooth wear, loss of periodontal tissues, and temporomandibular pain and dysfunction). Even though most dentists agree that bruxism may have several adverse effects on the masticatory system, for none of these purported adverse effects, evidence for a mediating role of occlusion and articulation has been found to date. Hence, based on this review, it should be concluded that to date, there is no evidence whatsoever for a causal relationship between bruxism and the bite. © 2012 Blackwell Publishing Ltd.
[Antibibiotic resistance by nosocomial infections' causal agents].
Salazar-Holguín, Héctor Daniel; Cisneros-Robledo, María Elena
2016-01-01
The antibibiotic resistance by nosocomial infections (NI) causal agents constitutes a seriously global problematic that involves the Mexican Institute of Social Security's Regional General Hospital 1 in Chihuahua, Mexico; although with special features that required to be specified and evaluated, in order to concrete an effective therapy. Observational, descriptive and prospective study; by means of active vigilance all along 2014 in order to detect the nosocomial infections, for epidemiologic study, culture and antibiogram to identify its causal agents and antibiotics resistance and sensitivity. Among 13527 hospital discharges, 1079 displayed NI (8 %), standed out: the related on vascular lines, of surgical site, pneumonia and urinal track; they added up two thirds of the total. We carried out culture and antibiogram about 300 of them (27.8 %); identifying 31 bacterian species, mainly seven of those (77.9 %): Escherichia coli, Staphylococcus aureus and epidermidis, Pseudomonas aeruginosa, Acinetobacter baumannii, Klebsiella pneumoniae and Enterobacter cloacae; showing multiresistance to 34 tested antibiotics, except in seven with low or without resistance at all: vancomycin, teicoplanin, linezolid, quinupristin-dalfopristin, piperacilin-tazobactam, amikacin and carbapenems. When we contrasted those results with the recommendations in the clinical practice guides, it aroused several contradictions; so they must be taken with reserves and has to be tested in each hospital, by means of cultures and antibiograms in practically every case of nosocomial infection.
Diagnostic reasoning using qualitative causal models
International Nuclear Information System (INIS)
Sudduth, A.L.
1992-01-01
The application of expert systems to reasoning problems involving real-time data from plant measurements has been a topic of much research, but few practical systems have been deployed. One obstacle to wider use of expert systems in applications involving real-time data is the lack of adequate knowledge representation methodologies for dynamic processes. Knowledge bases composed mainly of rules have disadvantages when applied to dynamic processes and real-time data. This paper describes a methodology for the development of qualitative causal models that can be used as knowledge bases for reasoning about process dynamic behavior. These models provide a systematic method for knowledge base construction, considerably reducing the engineering effort required. They also offer much better opportunities for verification and validation of the knowledge base, thus increasing the possibility of the application of expert systems to reasoning about mission critical systems. Starting with the Signed Directed Graph (SDG) method that has been successfully applied to describe the behavior of diverse dynamic processes, the paper shows how certain non-physical behaviors that result from abstraction may be eliminated by applying causal constraint to the models. The resulting Extended Signed Directed Graph (ESDG) may then be compiled to produce a model for use in process fault diagnosis. This model based reasoning methodology is used in the MOBIAS system being developed by Duke Power Company under EPRI sponsorship. 15 refs., 4 figs
Introducing mechanics by tapping core causal knowledge
International Nuclear Information System (INIS)
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 its own accord (i.e. its force-free motion), and (b) an incentive to search, where the motion deviates from the assumed force-free motion, for recurring configurations with which such deviations can be correlated (interaction theory). Various assumptions can be made concerning both the force-free motion and the interaction theory, thus giving rise to a variety of specific explanations. Kepler's semi-implicit intuition about the force-free motion is rest, Newton's explicit assumption is uniform rectilinear motion, while in everyday explanations a diversity of pragmatic suggestions can be recognized. The idea is that the explanatory strategy, once made explicit by drawing on students' intuitive causal knowledge, can be made to function for students as an advance organizer, in the sense of a general scheme that they recognize but do not yet know how to detail for scientific purposes
Causal Inference in the Perception of Verticality.
de Winkel, Ksander N; Katliar, Mikhail; Diers, Daniel; Bülthoff, Heinrich H
2018-04-03
The perceptual upright is thought to be constructed by the central nervous system (CNS) as a vector sum; by combining estimates on the upright provided by the visual system and the body's inertial sensors with prior knowledge that upright is usually above the head. Recent findings furthermore show that the weighting of the respective sensory signals is proportional to their reliability, consistent with a Bayesian interpretation of a vector sum (Forced Fusion, FF). However, violations of FF have also been reported, suggesting that the CNS may rely on a single sensory system (Cue Capture, CC), or choose to process sensory signals based on inferred signal causality (Causal Inference, CI). We developed a novel alternative-reality system to manipulate visual and physical tilt independently. We tasked participants (n = 36) to indicate the perceived upright for various (in-)congruent combinations of visual-inertial stimuli, and compared models based on their agreement with the data. The results favor the CI model over FF, although this effect became unambiguous only for large discrepancies (±60°). We conclude that the notion of a vector sum does not provide a comprehensive explanation of the perception of the upright, and that CI offers a better alternative.
Colwell, Morris A
1976-01-01
Electronic Components provides a basic grounding in the practical aspects of using and selecting electronics components. The book describes the basic requirements needed to start practical work on electronic equipment, resistors and potentiometers, capacitance, and inductors and transformers. The text discusses semiconductor devices such as diodes, thyristors and triacs, transistors and heat sinks, logic and linear integrated circuits (I.C.s) and electromechanical devices. Common abbreviations applied to components are provided. Constructors and electronics engineers will find the book useful
Quantum causality conceptual issues in the causal theory of quantum mechanics
Riggs, Peter J; French, Steven RD
2009-01-01
This is a treatise devoted to the foundations of quantum physics and the role that causality plays in the microscopic world governed by the laws of quantum mechanics. The book is controversial and will engender some lively debate on the various issues raised.
Links between causal effects and causal association for surrogacy evaluation in a gaussian setting.
Conlon, Anna; Taylor, Jeremy; Li, Yun; Diaz-Ordaz, Karla; Elliott, Michael
2017-11-30
Two paradigms for the evaluation of surrogate markers in randomized clinical trials have been proposed: the causal effects paradigm and the causal association paradigm. Each of these paradigms rely on assumptions that must be made to proceed with estimation and to validate a candidate surrogate marker (S) for the true outcome of interest (T). We consider the setting in which S and T are Gaussian and are generated from structural models that include an unobserved confounder. Under the assumed structural models, we relate the quantities used to evaluate surrogacy within both the causal effects and causal association frameworks. We review some of the common assumptions made to aid in estimating these quantities and show that assumptions made within one framework can imply strong assumptions within the alternative framework. We demonstrate that there is a similarity, but not exact correspondence between the quantities used to evaluate surrogacy within each framework, and show that the conditions for identifiability of the surrogacy parameters are different from the conditions, which lead to a correspondence of these quantities. Copyright © 2017 John Wiley & Sons, Ltd.
Causal inference in nonlinear systems: Granger causality versus time-delayed mutual information
Li, Songting; Xiao, Yanyang; Zhou, Douglas; Cai, David
2018-05-01
The Granger causality (GC) analysis has been extensively applied to infer causal interactions in dynamical systems arising from economy and finance, physics, bioinformatics, neuroscience, social science, and many other fields. In the presence of potential nonlinearity in these systems, the validity of the GC analysis in general is questionable. To illustrate this, here we first construct minimal nonlinear systems and show that the GC analysis fails to infer causal relations in these systems—it gives rise to all types of incorrect causal directions. In contrast, we show that the time-delayed mutual information (TDMI) analysis is able to successfully identify the direction of interactions underlying these nonlinear systems. We then apply both methods to neuroscience data collected from experiments and demonstrate that the TDMI analysis but not the GC analysis can identify the direction of interactions among neuronal signals. Our work exemplifies inference hazards in the GC analysis in nonlinear systems and suggests that the TDMI analysis can be an appropriate tool in such a case.
International Nuclear Information System (INIS)
Solarin, Sakiru Adebola; Shahbaz, Muhammad
2013-01-01
This paper investigates the causal relationship between economic growth, urbanisation and electricity consumption in the case of Angola, while utilizing the data over the period of 1971–2009. We have applied Lee and Strazicich (2003. The Review of Economics and Statistics 63, 1082–1089; 2004. Working Paper. Department of Economics, Appalachian State University) unit root tests to examine the stationarity properties of the series. Using the Gregory–Hansen structural break cointegration procedure as a complement, we employ the ARDL bounds test to investigate long run relationships. The VECM Granger causality test is subsequently used to examine the direction of causality between economic growth, urbanisation, and electricity consumption. Our results indicate the existence of long run relationships. We further observe evidence in favour of bidirectional causality between electricity consumption and economic growth. The feedback hypothesis is also found between urbanisation and economic growth. Urbanisation and electricity consumption Granger cause each other. We conclude that Angola is energy-dependent country. Consequently, the relevant authorities should boost electricity production as one of the means of achieving sustainable economic development in the long run. - Highlights: • We consider the link between electricity consumption and economic growth in Angola. • Urbanisation is added to turn the research into a trivariate investigation. • Various time series procedures are used. • Results show that increasing electricity will improve economic growth in Angola. • Results show urbanisations reduced economic growth during civil war
Causality as a Rigorous Notion and Quantitative Causality Analysis with Time Series
Liang, X. S.
2017-12-01
Given two time series, can one faithfully tell, in a rigorous and quantitative way, the cause and effect between them? Here we show that this important and challenging question (one of the major challenges in the science of big data), which is of interest in a wide variety of disciplines, has a positive answer. Particularly, for linear systems, the maximal likelihood estimator of the causality from a series X2 to another series X1, written T2→1, turns out to be concise in form: T2→1 = [C11 C12 C2,d1 — C112 C1,d1] / [C112 C22 — C11C122] where Cij (i,j=1,2) is the sample covariance between Xi and Xj, and Ci,dj the covariance between Xi and ΔXj/Δt, the difference approximation of dXj/dt using the Euler forward scheme. An immediate corollary is that causation implies correlation, but not vice versa, resolving the long-standing debate over causation versus correlation. The above formula has been validated with touchstone series purportedly generated with one-way causality that evades the classical approaches such as Granger causality test and transfer entropy analysis. It has also been applied successfully to the investigation of many real problems. Through a simple analysis with the stock series of IBM and GE, an unusually strong one-way causality is identified from the former to the latter in their early era, revealing to us an old story, which has almost faded into oblivion, about "Seven Dwarfs" competing with a "Giant" for the computer market. Another example presented here regards the cause-effect relation between the two climate modes, El Niño and Indian Ocean Dipole (IOD). In general, these modes are mutually causal, but the causality is asymmetric. To El Niño, the information flowing from IOD manifests itself as a propagation of uncertainty from the Indian Ocean. In the third example, an unambiguous one-way causality is found between CO2 and the global mean temperature anomaly. While it is confirmed that CO2 indeed drives the recent global warming
Predicting diffusivities in dense fluid mixtures
Directory of Open Access Journals (Sweden)
C. DARIVA
1999-09-01
Full Text Available In this work the Enskog solution of the Boltzmann equation, as corrected by Speedy, together with the Weeks-Chandler-Andersen (WCA perturbation theory of liquids is employed in correlating and predicting self-diffusivities of dense fluids. Afterwards this theory is used to estimate mutual diffusion coefficients of solutes at infinite dilution in sub and supercritical solvents. We have also investigated the behavior of Fick diffusion coefficients in the proximity of a binary vapor-liquid critical point since this subject is of great interest for extraction purposes. The approach presented here, which makes use of a density and temperature dependent hard-sphere diameter, is shown to be excellent for predicting diffusivities in dense pure fluids and fluid mixtures. The calculations involved highly nonideal mixtures as well as systems with high molecular asymmetry. The predicted diffusivities are in good agreement with the experimental data for the pure and binary systems. The methodology proposed here makes only use of pure component information and density of mixtures. The simple algebraic relations are proposed without any binary adjustable parameters and can be readily used for estimating diffusivities in multicomponent mixtures.
Pool Boiling of Hydrocarbon Mixtures on Water
Energy Technology Data Exchange (ETDEWEB)
Boee, R.
1996-09-01
In maritime transport of liquefied natural gas (LNG) there is a risk of spilling cryogenic liquid onto water. The present doctoral thesis discusses transient boiling experiments in which liquid hydrocarbons were poured onto water and left to boil off. Composition changes during boiling are believed to be connected with the initiation of rapid phase transition in LNG spilled on water. 64 experimental runs were carried out, 14 using pure liquid methane, 36 using methane-ethane, and 14 using methane-propane binary mixtures of different composition. The water surface was open to the atmosphere and covered an area of 200 cm{sup 2} at 25 - 40{sup o}C. The heat flux was obtained by monitoring the change of mass vs time. The void fraction in the boiling layer was measured with a gamma densitometer, and a method for adapting this measurement concept to the case of a boiling cryogenic liquid mixture is suggested. Significant differences in the boil-off characteristics between pure methane and binary mixtures revealed by previous studies are confirmed. Pure methane is in film boiling, whereas the mixtures appear to enter the transitional boiling regime with only small amounts of the second component added. The results indicate that the common assumption that LNG will be in film boiling on water because of the high temperature difference, may be questioned. Comparison with previous work shows that at this small scale the results are influenced by the experimental apparatus and procedures. 66 refs., 76 figs., 28 tabs.
Innovative aspects of protein stability in ionic liquid mixtures.
Kumar, Awanish; Venkatesu, Pannuru
2018-06-01
Mixtures of ionic liquids (ILs) have attracted our attention because of their extraordinary performances in extraction technologies and in absorbing large amount of CO 2 gas. It has been observed that when two or more ILs are mixed in different proportions, a new solvent is obtained which is much better than that of each component of ILs from which the mixture is obtained. Within a mixture of ILs, several unidentified interactions occur among several ions which give rise to unique solvent properties to the mixture. Herein, in this review, we have highlighted the utilization of the advantageous properties of the IL mixtures in protein stability studies. This approach is exceptional and opens new directions to the use of ILs in biotechnology.
Causality, Randomness, Intelligibility, and the Epistemology of the Cell
Dougherty, Edward R; Bittner, Michael L
2010-01-01
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. PMID:21119887
Thermogravimetric analysis of combustible waste components
DEFF Research Database (Denmark)
Munther, Anette; Wu, Hao; Glarborg, Peter
In order to gain fundamental knowledge about the co-combustion of coal and waste derived fuels, the pyrolytic behaviors of coal, four typical waste components and their mixtures have been studied by a simultaneous thermal analyzer (STA). The investigated waste components were wood, paper, polypro......In order to gain fundamental knowledge about the co-combustion of coal and waste derived fuels, the pyrolytic behaviors of coal, four typical waste components and their mixtures have been studied by a simultaneous thermal analyzer (STA). The investigated waste components were wood, paper...
Research of Deformation of Clay Soil Mixtures Mixtures
Romas Girkontas; Tadas Tamošiūnas; Andrius Savickas
2014-01-01
The aim of this article is to determine clay soils and clay soils mixtures deformations during drying. Experiments consisted from: a) clay and clay mixtures bridges (height ~ 0,30 m, span ~ 1,00 m); b) tiles of clay and clay, sand and straw (height, length, wide); c) cylinders of clay; clay and straw; clay, straw and sand (diameter; height). According to the findings recommendations for clay and clay mixtures drying technology application were presented. During the experiment clay bridge bear...
Parvez, Shahid; Venkataraman, Chandra; Mukherji, Suparna
2009-06-01
The concentration addition (CA) and the independent action (IA) models are widely used for predicting mixture toxicity based on its composition and individual component dose-response profiles. However, the prediction based on these models may be inaccurate due to interaction among mixture components. In this work, the nature and prevalence of non-additive effects were explored for binary, ternary and quaternary mixtures composed of hydrophobic organic compounds (HOCs). The toxicity of each individual component and mixture was determined using the Vibrio fischeri bioluminescence inhibition assay. For each combination of chemicals specified by the 2(n) factorial design, the percent deviation of the predicted toxic effect from the measured value was used to characterize mixtures as synergistic (positive deviation) and antagonistic (negative deviation). An arbitrary classification scheme was proposed based on the magnitude of deviation (d) as: additive (50%, class-IV) antagonistic/synergistic. Naphthalene, n-butanol, o-xylene, catechol and p-cresol led to synergism in mixtures while 1, 2, 4-trimethylbenzene and 1, 3-dimethylnaphthalene contributed to antagonism. Most of the mixtures depicted additive or antagonistic effect. Synergism was prominent in some of the mixtures, such as, pulp and paper, textile dyes, and a mixture composed of polynuclear aromatic hydrocarbons. The organic chemical industry mixture depicted the highest abundance of antagonism and least synergism. Mixture toxicity was found to depend on partition coefficient, molecular connectivity index and relative concentration of the components.
Mutagenicity of complex mixtures
International Nuclear Information System (INIS)
Pelroy, R.A.
1985-01-01
The effect of coal-derived complex chemical mixtures on the mutagenicity of 6-aminochrysene (6-AC) was determined with Salmonella typhimurium TA98. Previous results suggested that the mutagenic potency of 6-AC for TA98 in the standard microsomal activation (Ames) assay increased if it was presented to the cells mixed with high-boiling coal liquids (CL) from the solvent refined coal (SRC) process. In this year's work, the apparent mutational synergism of CL and 6-AC was independently verified in a fluctuation bioassay which allowed quantitation of mutational frequencies and cell viability. The results of this assay system were similar to those in the Ames assay. Moreover, the fluctation assay revealed that mutagenesis and cellular toxicity induced by 6-AC were both strongly enhanced if 6-AC was presented to the cells mixed in a high-boiling CL. 4 figures
International Nuclear Information System (INIS)
Dergiades, Theologos; Martinopoulos, Georgios; Tsoulfidis, Lefteris
2013-01-01
The objective of this paper is to contribute towards the understanding of the linear and non-linear causal linkages between energy consumption and economic activity, making use of annual time series data of Greece for the period 1960–2008. Two are the salient features of our study: first, the total energy consumption has been adjusted for qualitative differences among its constituent components through the thermodynamics of energy conversion. In doing so, we rule out the possibility of a misleading inference with respect to causality due to aggregation bias. Second, the investigation of the causal linkage between economic growth and the adjusted for quality total energy consumption is conducted within a non-linear context. Our empirical results reveal significant unidirectional both linear and non-linear causal linkages running from total useful energy to economic growth. These findings may provide valuable information for the contemplation of more effective energy policies with respect to both the consumption of energy and environmental protection. - Highlights: ► The energy consumption and economic growth nexus is investigated for Greece. ► A quality-adjusted energy series is used in our analysis. ► The causality testing procedure is conducted within a non-linear context. ► A causality running from energy consumption to economic growth is verified
Entanglement, non-Markovianity, and causal non-separability
Milz, Simon; Pollock, Felix A.; Le, Thao P.; Chiribella, Giulio; Modi, Kavan
2018-03-01
Quantum mechanics, in principle, allows for processes with indefinite causal order. However, most of these causal anomalies have not yet been detected experimentally. We show that every such process can be simulated experimentally by means of non-Markovian dynamics with a measurement on additional degrees of freedom. In detail, we provide an explicit construction to implement arbitrary a causal processes. Furthermore, we give necessary and sufficient conditions for open system dynamics with measurement to yield processes that respect causality locally, and find that tripartite entanglement and nonlocal unitary transformations are crucial requirements for the simulation of causally indefinite processes. These results show a direct connection between three counter-intuitive concepts: entanglement, non-Markovianity, and causal non-separability.
Gaussian Process-Mixture Conditional Heteroscedasticity.
Platanios, Emmanouil A; Chatzis, Sotirios P
2014-05-01
Generalized autoregressive conditional heteroscedasticity (GARCH) models have long been considered as one of the most successful families of approaches for volatility modeling in financial return series. In this paper, we propose an alternative approach based on methodologies widely used in the field of statistical machine learning. Specifically, we propose a novel nonparametric Bayesian mixture of Gaussian process regression models, each component of which models the noise variance process that contaminates the observed data as a separate latent Gaussian process driven by the observed data. This way, we essentially obtain a Gaussian process-mixture conditional heteroscedasticity (GPMCH) model for volatility modeling in financial return series. We impose a nonparametric prior with power-law nature over the distribution of the model mixture components, namely the Pitman-Yor process prior, to allow for better capturing modeled data distributions with heavy tails and skewness. Finally, we provide a copula-based approach for obtaining a predictive posterior for the covariances over the asset returns modeled by means of a postulated GPMCH model. We evaluate the efficacy of our approach in a number of benchmark scenarios, and compare its performance to state-of-the-art methodologies.
Causal mapping of emotion networks in the human brain: Framework and initial findings.
Dubois, Julien; Oya, Hiroyuki; Tyszka, J Michael; Howard, Matthew; Eberhardt, Frederick; Adolphs, Ralph
2017-11-13
Emotions involve many cortical and subcortical regions, prominently including the amygdala. It remains unknown how these multiple network components interact, and it remains unknown how they cause the behavioral, autonomic, and experiential effects of emotions. Here we describe a framework for combining a novel technique, concurrent electrical stimulation with fMRI (es-fMRI), together with a novel analysis, inferring causal structure from fMRI data (causal discovery). We outline a research program for investigating human emotion with these new tools, and provide initial findings from two large resting-state datasets as well as case studies in neurosurgical patients with electrical stimulation of the amygdala. The overarching goal is to use causal discovery methods on fMRI data to infer causal graphical models of how brain regions interact, and then to further constrain these models with direct stimulation of specific brain regions and concurrent fMRI. We conclude by discussing limitations and future extensions. The approach could yield anatomical hypotheses about brain connectivity, motivate rational strategies for treating mood disorders with deep brain stimulation, and could be extended to animal studies that use combined optogenetic fMRI. Copyright © 2017 Elsevier Ltd. All rights reserved.
Equation of state of strongly coupled plasma mixtures
International Nuclear Information System (INIS)
DeWitt, H.E.
1984-01-01
Thermodynamic properties of strongly coupled (high density) plasmas of mixtures of light elements have been obtained by Monte Carlo simulations. For an assumed uniform charge background the equation of state of ionic mixtures is a simple extension of the one-component plasma EOS. More realistic electron screening effects are treated in linear response theory and with an appropriate electron dielectric function. Results have been obtained for the ionic pair distribution functions, and for the electric microfield distribution
SANS studies of critical phenomena in ternary mixtures
Bulavyn, L A; Hohryakov, A; Garamus, V; Avdeev, M; Almasy, L
2002-01-01
Critical behaviour of a quasi-binary liquid mixture is investigated by small-angle neutron scattering. Analysis of the changes of the critical parameters, caused by addition of a small amount of electrolyte into the binary mixture 3-methylpyridine-heavy water, shows that the third component does not change the 3D Ising-type behaviour of the system; a crossover towards the mean-field behaviour is not observed. (orig.)
Causal theory in (2+1)-dimensional Qed
International Nuclear Information System (INIS)
Scharf, G.; Wreszinski, W.F.
1994-01-01
The program of constructing the S-matrix by means of causality in quantum field theory goes back to Stueckelberg and Bogoliubov. Epstein and Glaser proposed an axiomatic construct where ultraviolet divergences do not appear, leading directly to the renormalized perturbation series. They have shown that in the causal theory the UV problem is a consequence of incorrect distribution splitting. This paper studies the causal theory in (2+1)D Qed
Causal knowledge and the development of inductive reasoning
Bright, Aimée K.; Feeney, Aidan
2014-01-01
We explored the development of sensitivity to causal relations in children’s inductive reasoning. Children (5-, 8-, and 12-year-olds) and adults were given trials in which they decided whether a property known to be possessed by members of one category was also possessed by members of (a) a taxonomically related category or (b) a causally related category. The direction of the causal link was either predictive (prey → predator) or diagnostic (predator → prey), and the property that participan...
Automatic Control of the Concrete Mixture Homogeneity in Cycling Mixers
Anatoly Fedorovich, Tikhonov; Drozdov, Anatoly
2018-03-01
The article describes the factors affecting the concrete mixture quality related to the moisture content of aggregates, since the effectiveness of the concrete mixture production is largely determined by the availability of quality management tools at all stages of the technological process. It is established that the unaccounted moisture of aggregates adversely affects the concrete mixture homogeneity and, accordingly, the strength of building structures. A new control method and the automatic control system of the concrete mixture homogeneity in the technological process of mixing components have been proposed, since the tasks of providing a concrete mixture are performed by the automatic control system of processing kneading-and-mixing machinery with operational automatic control of homogeneity. Theoretical underpinnings of the control of the mixture homogeneity are presented, which are related to a change in the frequency of vibrodynamic vibrations of the mixer body. The structure of the technical means of the automatic control system for regulating the supply of water is determined depending on the change in the concrete mixture homogeneity during the continuous mixing of components. The following technical means for establishing automatic control have been chosen: vibro-acoustic sensors, remote terminal units, electropneumatic control actuators, etc. To identify the quality indicator of automatic control, the system offers a structure flowchart with transfer functions that determine the ACS operation in transient dynamic mode.
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.
Explaining quantum correlations through evolution of causal models
Harper, Robin; Chapman, Robert J.; Ferrie, Christopher; Granade, Christopher; Kueng, Richard; Naoumenko, Daniel; Flammia, Steven T.; Peruzzo, Alberto
2017-04-01
We propose a framework for the systematic and quantitative generalization of Bell's theorem using causal networks. We first consider the multiobjective optimization problem of matching observed data while minimizing the causal effect of nonlocal variables and prove an inequality for the optimal region that both strengthens and generalizes Bell's theorem. To solve the optimization problem (rather than simply bound it), we develop a genetic algorithm treating as individuals causal networks. By applying our algorithm to a photonic Bell experiment, we demonstrate the trade-off between the quantitative relaxation of one or more local causality assumptions and the ability of data to match quantum correlations.
A general, multivariate definition of causal effects in epidemiology.
Flanders, W Dana; Klein, Mitchel
2015-07-01
Population causal effects are often defined as contrasts of average individual-level counterfactual outcomes, comparing different exposure levels. Common examples include causal risk difference and risk ratios. These and most other examples emphasize effects on disease onset, a reflection of the usual epidemiological interest in disease occurrence. Exposure effects on other health characteristics, such as prevalence or conditional risk of a particular disability, can be important as well, but contrasts involving these other measures may often be dismissed as non-causal. For example, an observed prevalence ratio might often viewed as an estimator of a causal incidence ratio and hence subject to bias. In this manuscript, we provide and evaluate a definition of causal effects that generalizes those previously available. A key part of the generalization is that contrasts used in the definition can involve multivariate, counterfactual outcomes, rather than only univariate outcomes. An important consequence of our generalization is that, using it, one can properly define causal effects based on a wide variety of additional measures. Examples include causal prevalence ratios and differences and causal conditional risk ratios and differences. We illustrate how these additional measures can be useful, natural, easily estimated, and of public health importance. Furthermore, we discuss conditions for valid estimation of each type of causal effect, and how improper interpretation or inferences for the wrong target population can be sources of bias.
Delinquency among pathological gamblers: A causal approach.
Meyer, G; Fabian, T
1992-03-01
In a comprehensive research project on gamblers in self-help groups in West Germany one object of investigation was the question of whether or not pathological gambling has a criminogenic effect. 54.5% of the 437 members of Gamblers Anonymous interviewed stated that they had committed illegal actions in order to obtain money for gambling. Comparisons of this sub-group with those interviewees who did not admit having committed criminal offences show distinct differences: Those who admitted illegal action were more excessive in their gambling behavior and experienced a higher degree of subjective satisfaction through gambling. They also showed a more pronounced problem behavior and more psychosocial problems because of gambling. A multiple regression within the framework of path analysis was computed in order to explore causal links between pathological gambling and delinquency. The results support the hypothesis that pathological gambling can lead to delinquent behavior. Forensic implications are discussed.
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....... Apart from setting the stage for the analysis of shape dynamics on the torus, the new set-up highlights the role of nontrivial boundaries and topology....
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...
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.
The emerging causal understanding of institutional objects.
Noyes, Alexander; Keil, Frank C; Dunham, Yarrow
2018-01-01
Institutional objects, such as money, drivers' licenses, and borders, have functions because of their social roles rather than their immediate physical properties. These objects are causally different than standard artifacts (e.g. hammers, chairs, and cars), sharing more commonality with other social roles. Thus, they inform psychological theories of human-made objects as well as children's emerging understanding of social reality. We examined whether children (N=180, ages 4-9) differentiate institutional objects from standard artifacts. Specifically, we examine whether children understand that mutual intentions (i.e., the intentions of a social collective) underlie the functional affordances of institutional objects in ways that they do not for standard artifacts. We find that young children assimilate institutional objects into their intuitive theories of standard artifacts; children begin to differentiate between the domains in the elementary school years. Published by Elsevier B.V.
A study in cosmology and causal thermodynamics
International Nuclear Information System (INIS)
Oliveira, H.P. de.
1986-01-01
The especial relativity of thermodynamic theories for reversible and irreversible processes in continuous medium is studied. The formalism referring to equilibrium and non-equilibrium configurations, and theories which includes the presence of gravitational fields are discussed. The nebular model in contraction with dissipative processes identified by heat flux and volumetric viscosity is thermodymically analysed. This model is presented by a plane conformal metric. The temperature, pressure, entropy and entropy production within thermodynamic formalism which adopts the hypothesis of local equilibrium, is calculated. The same analysis is carried out considering a causal thermodynamics, which establishes a local entropy of non-equilibrium. Possible homogeneous and isotropic cosmological models, considering the new phenomenological equation for volumetric viscosity deriving from cause thermodynamics are investigated. The found out models have plane spatial section (K=0) and some ones do not have singularities. The energy conditions are verified and the entropy production for physically reasobable models are calculated. (M.C.K.) [pt
Equity Theory Ratios as Causal Schemas.
Arvanitis, Alexios; Hantzi, Alexandra
2016-01-01
Equity theory approaches justice evaluations based on ratios of exchange inputs to exchange outcomes. Situations are evaluated as just if ratios are equal and unjust if unequal. We suggest that equity ratios serve a more fundamental cognitive function than the evaluation of justice. More particularly, we propose that they serve as causal schemas for exchange outcomes, that is, they assist in determining whether certain outcomes are caused by inputs of other people in the context of an exchange process. Equality or inequality of ratios in this sense points to an exchange process. Indeed, Study 1 shows that different exchange situations, such as disproportional or balanced proportional situations, create perceptions of give-and-take on the basis of equity ratios. Study 2 shows that perceptions of justice are based more on communicatively accepted rules of interaction than equity-based evaluations, thereby offering a distinction between an attribution and an evaluation cognitive process for exchange outcomes.
Causality and hyperbolicity of Lovelock theories
International Nuclear Information System (INIS)
Reall, Harvey S; Tanahashi, Norihiro; Way, Benson
2014-01-01
In Lovelock theories, gravity can travel faster or slower than light. The causal structure is determined by the characteristic hypersurfaces. We generalize a recent result of Izumi to prove that any Killing horizon is a characteristic hypersurface for all gravitational degrees of freedom of a Lovelock theory. Hence gravitational signals cannot escape from the region inside such a horizon. We investigate the hyperbolicity of Lovelock theories by determining the characteristic hypersurfaces for various backgrounds. First we consider Ricci flat type N spacetimes. We show that characteristic hypersurfaces are generically all non-null and that Lovelock theories are hyperbolic in any such spacetime. Next we consider static, maximally symmetric black hole solutions of Lovelock theories. Again, characteristic surfaces are generically non-null. For some small black holes, hyperbolicity is violated near the horizon. This implies that the stability of such black holes is not a well-posed problem. (paper)
Causality constraints in conformal field theory
Energy Technology Data Exchange (ETDEWEB)
Hartman, Thomas; Jain, Sachin; Kundu, Sandipan [Department of Physics, Cornell University,Ithaca, New York (United States)
2016-05-17
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){sup 4} coupling in effective field theory, from a dual CFT. We also find constraints on theories with higher spin conserved currents. Our analysis is restricted to scalar correlators, but we argue that similar methods should also impose nontrivial constraints on the interactions of spinning operators.
NMRI Measurements of Flow of Granular Mixtures
Nakagawa, Masami; Waggoner, R. Allen; Fukushima, Eiichi
1996-01-01
We investigate complex 3D behavior of granular mixtures in shaking and shearing devices. NMRI can non-invasively measure concentration, velocity, and velocity fluctuations of flows of suitable particles. We investigate origins of wall-shear induced convection flow of single component particles by measuring the flow and fluctuating motion of particles near rough boundaries. We also investigate if a mixture of different size particles segregate into their own species under the influence of external shaking and shearing disturbances. These non-invasive measurements will reveal true nature of convecting flow properties and wall disturbance. For experiments in a reduced gravity environment, we will design a light weight NMR imager. The proof of principle development will prepare for the construction of a complete spaceborne system to perform experiments in space.
Diagnostic causal reasoning with verbal information.
Meder, Björn; Mayrhofer, Ralf
2017-08-01
In diagnostic causal reasoning, the goal is to infer the probability of causes from one or multiple observed effects. Typically, studies investigating such tasks provide subjects with precise quantitative information regarding the strength of the relations between causes and effects or sample data from which the relevant quantities can be learned. By contrast, we sought to examine people's inferences when causal information is communicated through qualitative, rather vague verbal expressions (e.g., "X occasionally causes A"). We conducted three experiments using a sequential diagnostic inference task, where multiple pieces of evidence were obtained one after the other. Quantitative predictions of different probabilistic models were derived using the numerical equivalents of the verbal terms, taken from an unrelated study with different subjects. We present a novel Bayesian model that allows for incorporating the temporal weighting of information in sequential diagnostic reasoning, which can be used to model both primacy and recency effects. On the basis of 19,848 judgments from 292 subjects, we found a remarkably close correspondence between the diagnostic inferences made by subjects who received only verbal information and those of a matched control group to whom information was presented numerically. Whether information was conveyed through verbal terms or numerical estimates, diagnostic judgments closely resembled the posterior probabilities entailed by the causes' prior probabilities and the effects' likelihoods. We observed interindividual differences regarding the temporal weighting of evidence in sequential diagnostic reasoning. Our work provides pathways for investigating judgment and decision making with verbal information within a computational modeling framework. Copyright © 2017 Elsevier Inc. All rights reserved.
The balanced survivor average causal effect.
Greene, Tom; Joffe, Marshall; Hu, Bo; Li, Liang; Boucher, Ken
2013-05-07
Statistical analysis of longitudinal outcomes is often complicated by the absence of observable values in patients who die prior to their scheduled measurement. In such cases, the longitudinal data are said to be "truncated by death" to emphasize that the longitudinal measurements are not simply missing, but are undefined after death. Recently, the truncation by death problem has been investigated using the framework of principal stratification to define the target estimand as the survivor average causal effect (SACE), which in the context of a two-group randomized clinical trial is the mean difference in the longitudinal outcome between the treatment and control groups for the principal stratum of always-survivors. The SACE is not identified without untestable assumptions. These assumptions have often been formulated in terms of a monotonicity constraint requiring that the treatment does not reduce survival in any patient, in conjunction with assumed values for mean differences in the longitudinal outcome between certain principal strata. In this paper, we introduce an alternative estimand, the balanced-SACE, which is defined as the average causal effect on the longitudinal outcome in a particular subset of the always-survivors that is balanced with respect to the potential survival times under the treatment and control. We propose a simple estimator of the balanced-SACE that compares the longitudinal outcomes between equivalent fractions of the longest surviving patients between the treatment and control groups and does not require a monotonicity assumption. We provide expressions for the large sample bias of the estimator, along with sensitivity analyses and strategies to minimize this bias. We consider statistical inference under a bootstrap resampling procedure.
Electron thermalization in rare gases and their mixtures
International Nuclear Information System (INIS)
Bronic, I.K.; Kimura, M.
1996-01-01
The time evolution and temperature dependence of electron energy distribution functions (EDFs) are studied in pure rare gases (He, Ne, Ar, Kr, Xe) as well as in their mixtures by using solutions of the Boltzmann equation. A clear difference between the gases having the Ramsauer endash Townsend (RT) minimum in the momentum-transfer cross section, (RT gases: Ar, Kr, and Xe), and those without the RT minimum (non-RT gases: He and Ne) is pointed out. The influence of the position and the depth of the RT minimum on the EDF and time evolution is studied for three different initial electron energies. A formula proposed for describing thermalization time in a mixture is tested on (i) a non-RT endash non-RT gas mixture, (ii) a RT endash non-RT mixture and (iii) a RT endash RT gas mixture. The linear combination of the reciprocal thermalization times in gas mixture with the component concentrations as weighting factors is found to be valid for gases with a similar energy dependence of the momentum-transfer cross section, σ m , and also for all rare-gas binary mixtures if the initial electron energy is sufficiently below the RT minimum. Conspicuous deviations from the linear relationship are observed in mixtures of gases whose energy dependence of σ m (or the stopping cross section) are different, and theoretical rationales for these findings are provided. copyright 1996 American Institute of Physics
World oil and agricultural commodity prices: Evidence from nonlinear causality
International Nuclear Information System (INIS)
Nazlioglu, Saban
2011-01-01
The increasing co-movements between the world oil and agricultural commodity prices have renewed interest in determining price transmission from oil prices to those of agricultural commodities. This study extends the literature on the oil-agricultural commodity prices nexus, which particularly concentrates on nonlinear causal relationships between the world oil and three key agricultural commodity prices (corn, soybeans, and wheat). To this end, the linear causality approach of Toda-Yamamoto and the nonparametric causality method of Diks-Panchenko are applied to the weekly data spanning from 1994 to 2010. The linear causality analysis indicates that the oil prices and the agricultural commodity prices do not influence each other, which supports evidence on the neutrality hypothesis. In contrast, the nonlinear causality analysis shows that: (i) there are nonlinear feedbacks between the oil and the agricultural prices, and (ii) there is a persistent unidirectional nonlinear causality running from the oil prices to the corn and to the soybeans prices. The findings from the nonlinear causality analysis therefore provide clues for better understanding the recent dynamics of the agricultural commodity prices and some policy implications for policy makers, farmers, and global investors. This study also suggests the directions for future studies. - Research highlights: → This study determines the price transmission mechanisms between the world oil and three key agricultural commodity prices (corn, soybeans, and wheat). → The linear and nonlinear cointegration and causality methods are carried out. → The linear causality analysis supports evidence on the neutrality hypothesis. → The nonlinear causality analysis shows that there is a persistent unidirectional causality from the oil prices to the corn and to the soybeans prices.
International Nuclear Information System (INIS)
Springer, D.L.
1987-01-01
The objective of the project is to identify potential adverse biological activities associated with human exposures to complex organic mixtures (COM) from energy-related industries. Studies to identify the influence of chemical class fractions from a COM on the initiating activity of a known carcinogen, benzo(a)pyrene (BaP), demonstrated that the polycyclic aromatic hydrocarbons (PAH) and nitrogen-containing polycyclic aromatic compound (NPAC) fractions were the most effective inhibitors of initiation. In an effort to determine the contribution of BaP to the initiating activity of the COM, binding of radiolabeled BaP to mouse skin DNA was measured. Results indicated that binding of BaP to DNA decreased in the presence of the COM so that at initiating COM doses, BaP binding was near the limit detection. Addition of unlabeled BaP to the COM at an amount similar to that originally present in the COM did not significantly increase the binding. Studies to determine the rates of disappearance of carcinogenic PAH from the site of application on the skin indicated that half-lives for PAH differed by a factor of about 2. Analytical methods developed to identify PAH from COM which covalently bind to DNA demonstrated that the lower level of detection is approximately 200 picograms. Developmental studies demonstrated that both pregnant rats and mice treated dermally with a high-boiling COM developed fetuses with major malformations including cleft palate, small lungs, edema, and sagittal suture hemorrhages. 3 figures, 5 tables
Tachyon kinematics and causality: a systematic thorough analysis of the tachyon causal paradoxes
International Nuclear Information System (INIS)
Recami, E.
1987-01-01
The chronological order of the events along a spacelike path is not invariant under Lorentz transformations, as is well known. This led to an early conviction that tachyons would give rise to causal anomalies. A relativistic version of the Stueckelberg-Feynman switching procedure (SWP) has been invoked as the suitable tool to eliminate those anomalies. The application of the SWP does eliminate the motions backwards in time, but interchanges the roles of source and detector. This fact triggered the proposal of a host of causal paradoxes. Till now, however, it has not been recognized that such paradoxes can be sensibly discussed (and completely solved, at least in microphysics) only after the tachyon relativistic mechanics has been properly developed. They start by showing how to apply the SWP, both in the case of ordinary special relativity and in the case with tachyons. Then they carefully exploit the kinetics of the tachyon exchange between two (ordinary) bodies. Being finally able to tackle the tachyon causality problem, they successively solve the paradoxes of: (i) Tolman-Regge, (ii) Pirani, (iii) Edmonds, and (iv) Bell. Finally, they discuss a further, new paradox associated with the transmission of signals by modulated tachyon beams
Mixtures of skewed Kalman filters
Kim, Hyoungmoon; Ryu, Duchwan; Mallick, Bani K.; Genton, Marc G.
2014-01-01
Normal state-space models are prevalent, but to increase the applicability of the Kalman filter, we propose mixtures of skewed, and extended skewed, Kalman filters. To do so, the closed skew-normal distribution is extended to a scale mixture class
Easy and flexible mixture distributions
DEFF Research Database (Denmark)
Fosgerau, Mogens; Mabit, Stefan L.
2013-01-01
We propose a method to generate flexible mixture distributions that are useful for estimating models such as the mixed logit model using simulation. The method is easy to implement, yet it can approximate essentially any mixture distribution. We test it with good results in a simulation study...
Directory of Open Access Journals (Sweden)
Paolo Vineis
2017-06-01
Full Text Available Abstract In the last decades, Systems Biology (including cancer research has been driven by technology, statistical modelling and bioinformatics. In this paper we try to bring biological and philosophical thinking back. We thus aim at making different traditions of thought compatible: (a causality in epidemiology and in philosophical theorizing—notably, the “sufficient-component-cause framework” and the “mark transmission” approach; (b new acquisitions about disease pathogenesis, e.g. the “branched model” in cancer, and the role of biomarkers in this process; (c the burgeoning of omics research, with a large number of “signals” and of associations that need to be interpreted. In the paper we summarize first the current views on carcinogenesis, and then explore the relevance of current philosophical interpretations of “cancer causes”. We try to offer a unifying framework to incorporate biomarkers and omic data into causal models, referring to a position called “evidential pluralism”. According to this view, causal reasoning is based on both “evidence of difference-making” (e.g. associations and on “evidence of underlying biological mechanisms”. We conceptualize the way scientists detect and trace signals in terms of information transmission, which is a generalization of the mark transmission theory developed by philosopher Wesley Salmon. Our approach is capable of helping us conceptualize how heterogeneous factors such as micro and macro-biological and psycho-social—are causally linked. This is important not only to understand cancer etiology, but also to design public health policies that target the right causal factors at the macro-level.
A study of finite mixture model: Bayesian approach on financial time series data
Phoong, Seuk-Yen; Ismail, Mohd Tahir
2014-07-01
Recently, statistician have emphasized on the fitting finite mixture model by using Bayesian method. Finite mixture model is a mixture of distributions in modeling a statistical distribution meanwhile Bayesian method is a statistical method that use to fit the mixture model. Bayesian method is being used widely because it has asymptotic properties which provide remarkable result. In addition, Bayesian method also shows consistency characteristic which means the parameter estimates are close to the predictive distributions. In the present paper, the number of components for mixture model is studied by using Bayesian Information Criterion. Identify the number of component is important because it may lead to an invalid result. Later, the Bayesian method is utilized to fit the k-component mixture model in order to explore the relationship between rubber price and stock market price for Malaysia, Thailand, Philippines and Indonesia. Lastly, the results showed that there is a negative effect among rubber price and stock market price for all selected countries.
Is there a causal relationship between alcohol and HIV? Implications ...
African Journals Online (AJOL)
There is now conclusive evidence of a causal linkage between heavy drinking patterns and/or alcohol use disorders and the worsening of the disease course for HIV. However, while alcohol usage is consistently associated with the prevalence and incidence of HIV, further research is needed to substantiate causality in ...
An Information Processing Approach to Children's Causal Reasoning.
Siegler, Robert S.
This paper questions evidence for the thesis that causal reasoning of older children is more logical than that of younger ones, and describes two experiments which attempted to determine (1) whether there are true developmental differences in causal reasoning, and (2) what explanations for developmental differences can be supported. In the first…
The relative performance of bivariate causality tests in small samples
Bult, J..R.; Leeflang, P.S.H.; Wittink, D.R.
1997-01-01
Causality tests have been applied to establish directional effects and to reduce the set of potential predictors, For the latter type of application only bivariate tests can be used, In this study we compare bivariate causality tests. Although the problem addressed is general and could benefit
Child Care Subsidy Use and Child Development: Potential Causal Mechanisms
Hawkinson, Laura E.
2011-01-01
Research using an experimental design is needed to provide firm causal evidence on the impacts of child care subsidy use on child development, and on underlying causal mechanisms since subsidies can affect child development only indirectly via changes they cause in children's early experiences. However, before costly experimental research is…
Causal Effect Inference with Deep Latent-Variable Models
Louizos, C; Shalit, U.; Mooij, J.; Sontag, D.; Zemel, R.; Welling, M.
2017-01-01
Learning individual-level causal effects from observational data, such as inferring the most effective medication for a specific patient, is a problem of growing importance for policy makers. The most important aspect of inferring causal effects from observational data is the handling of
Optimal relaxed causal sampler using sampled-date system theory
Shekhawat, Hanumant; Meinsma, Gjerrit
This paper studies the design of an optimal relaxed causal sampler using sampled data system theory. A lifted frequency domain approach is used to obtain the existence conditions and the optimal sampler. A state space formulation of the results is also provided. The resulting optimal relaxed causal
Temporal and Statistical Information in Causal Structure Learning
McCormack, Teresa; Frosch, Caren; Patrick, Fiona; Lagnado, David
2015-01-01
Three experiments examined children's and adults' abilities to use statistical and temporal information to distinguish between common cause and causal chain structures. In Experiment 1, participants were provided with conditional probability information and/or temporal information and asked to infer the causal structure of a 3-variable mechanical…
Non-Bayesian Inference: Causal Structure Trumps Correlation
Bes, Benedicte; Sloman, Steven; Lucas, Christopher G.; Raufaste, Eric
2012-01-01
The study tests the hypothesis that conditional probability judgments can be influenced by causal links between the target event and the evidence even when the statistical relations among variables are held constant. Three experiments varied the causal structure relating three variables and found that (a) the target event was perceived as more…
Weighting-Based Sensitivity Analysis in Causal Mediation Studies
Hong, Guanglei; Qin, Xu; Yang, Fan
2018-01-01
Through a sensitivity analysis, the analyst attempts to determine whether a conclusion of causal inference could be easily reversed by a plausible violation of an identification assumption. Analytic conclusions that are harder to alter by such a violation are expected to add a higher value to scientific knowledge about causality. This article…
Causal inference in biology networks with integrated belief propagation.
Chang, Rui; Karr, Jonathan R; Schadt, Eric E
2015-01-01
Inferring causal relationships among molecular and higher order phenotypes is a critical step in elucidating the complexity of living systems. Here we propose a novel method for inferring causality that is no longer constrained by the conditional dependency arguments that limit the ability of statistical causal inference methods to resolve causal relationships within sets of graphical models that are Markov equivalent. Our method utilizes Bayesian belief propagation to infer the responses of perturbation events on molecular traits given a hypothesized graph structure. A distance measure between the inferred response distribution and the observed data is defined to assess the 'fitness' of the hypothesized causal relationships. To test our algorithm, we infer causal relationships within equivalence classes of gene networks in which the form of the functional interactions that are possible are assumed to be nonlinear, given synthetic microarray and RNA sequencing data. We also apply our method to infer causality in real metabolic network with v-structure and feedback loop. We show that our method can recapitulate the causal structure and recover the feedback loop only from steady-state data which conventional method cannot.
On the conceptual distinction of general causality orientations
DEFF Research Database (Denmark)
Olesen, Martin Hammershøj
electronic questionnaires of dispositional personality traits (NEO-FFI) and general causality orientations (GCOS). Proposed separate latent models and alternative shared latent models of the underlying individual differences constructs had been developed in a previous exploratory study (Olesen, Thomsen......, that is general causality orientations can be understood as characteristic adaptations of dispositional traits....
Theories of conduct disorder: a causal modelling analysis
Krol, N.P.C.M.; Morton, J.; Bruyn, E.E.J. De
2004-01-01
Background: If a clinician has to make decisions on diagnosis and treatment, he or she is confronted with a variety of causal theories. In order to compare these theories a neutral terminology and notational system is needed. The Causal Modelling framework involving three levels of description –
Financial networks based on Granger causality: A case study
Papana, A.; Kyrtsou, C.; Kugiumtzis, D.; Diks, C.
Connectivity analysis is performed on a long financial record of 21 international stock indices employing a linear and a nonlinear causality measure, the conditional Granger causality index (CGCI) and the partial mutual information on mixed embedding (PMIME), respectively. Both measures aim to
Causal pathways between substance use disorders and personality pathology
Verheul, R.; van den Brink, W.
2005-01-01
A high co-occurrence between personality and substance use disorders suggests causal relationships between these conditions. Most empirical evidence strongly supports causal pathways in which (pathological) personality traits contribute to the development of a substance use disorder (i.e., primary
Nonparametric Identification of Causal Effects under Temporal Dependence
Dafoe, Allan
2018-01-01
Social scientists routinely address temporal dependence by adopting a simple technical fix. However, the correct identification strategy for a causal effect depends on causal assumptions. These need to be explicated and justified; almost no studies do so. This article addresses this shortcoming by offering a precise general statement of the…
Causal inference in survival analysis using pseudo-observations
DEFF Research Database (Denmark)
Andersen, Per K; Syriopoulou, Elisavet; Parner, Erik T
2017-01-01
Causal inference for non-censored response variables, such as binary or quantitative outcomes, is often based on either (1) direct standardization ('G-formula') or (2) inverse probability of treatment assignment weights ('propensity score'). To do causal inference in survival analysis, one needs ...
Thinking Fast and Slow about Causality: Response to Palinkas
Marsh, Jeanne C.
2014-01-01
Larry Palinkas advances the developing science of social work by providing an explanation of how social science research methods, both qualitative and quantitative, can improve our capacity to draw casual inferences. Understanding causal relations and making causal inferences--with the promise of being able to predict and control outcomes--is…
Ends, Principles, and Causal Explanation in Educational Justice
Dum, Jenn
2017-01-01
Many principles characterize educational justice in terms of the relationship between educational inputs, outputs and distributive standards. Such principles depend upon the "causal pathway view" of education. It is implicit in this view that the causally effective aspects of education can be understood as separate from the normative…
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…
A note on mental content in the Causal Theory
African Journals Online (AJOL)
A note on mental content in the Causal Theory. JP Smit. Department of Philosophy, Stellenbosch University, Private Bag X1, 7600 Matieland, South Africa. E-mail: jps@sun.ac.za. Kripke's causal theory requires that downstream users of a name must have the intention to use the name in the same way that upstream users ...
Sartre's Contingency of Being and Asouzu's Principle of Causality ...
African Journals Online (AJOL)
The position of this work is that all contingent beings have a causal agent. This position is taken as a result of trying to delve into the issue of contingency and causality of being which has been discussed by many philosophers of diverse epochs of philosophy. This work tries to participate in the debate of whether contingent ...
The importance of causal connections in the comprehension of spontaneous spoken discourse.
Cevasco, Jazmin; van den Broek, Paul
2008-11-01
In this study, we investigated the psychological processes in spontaneous discourse comprehension through a network theory of discourse representation. Existing models of narrative comprehension describe the importance of causality processing for forming a representation of a text, but usually in the context of deliberately composed texts rather than in spontaneous, unplanned discourse. Our aim was to determine whether spontaneous discourse components with many causal connections are represented more strongly than components with few connections--similar to the findings in text comprehension literature--and whether any such effects depend on the medium in which the spontaneous discourse is presented (oral vs. written). Participants either listened to or read a transcription of a section of a radio transmission. They then recalled the spontaneous discourse material and answered comprehension questions. Results indicate that the processing of causal connections plays an important role in the comprehension of spontaneous spoken discourse, and do not indicate that their effects on recall are weaker in the comprehension of oral discourse than in the comprehension of written discourse.
Capeans, M; Mandelli, B
2012-01-01
The importance of the correct gas mixture for the Resistive Plate Chamber (RPC) detector systems is fundamental for their correct and safe operation. A small change in the percentages of the gas mixture components can alter the RPC performance and this will rebound on the data quality in the ALICE, ATLAS and CMS experiments at CERN. A constant monitoring of the gas mixture injected in the RPCs would avoid such kind of problems. A systematic study has been performed to understand RPC performances with several gas mixture compositions and in the presence of common gas impurities. The systematic analysis of several RPC performance parameters in different gas mixtures allows the rapid identification of any variation in the RPC gas mixture. A set-up for the online monitoring of the RPC gas mixture in the LHC gas systems is also proposed.
Causal Relationship Between Relative Price Variability and Inflation in Turkey:
Directory of Open Access Journals (Sweden)
Nebiye Yamak
2016-09-01
Full Text Available This study investigates the causal relationship between inflation and relative price variability in Turkey for the period of January 2003-January 2014, by using panel data. In the study, a Granger (1969 non-causality test in heterogeneous panel data models developed by Dumitrescu and Hurlin (2012 is utilized to determine the causal relations between inflation rate relative price variability. The panel data consists of 4123 observations: 133 time observations and 31 cross-section observations. The results of panel causality test indicate that there is a bidirectional causality between inflation rate and relative price variability by not supporting the imperfection information model of Lucas and the menu cost model of Ball and Mankiw.
Statistical causal inferences and their applications in public health research
Wu, Pan; Chen, Ding-Geng
2016-01-01
This book compiles and presents new developments in statistical causal inference. The accompanying data and computer programs are publicly available so readers may replicate the model development and data analysis presented in each chapter. In this way, methodology is taught so that readers may implement it directly. The book brings together experts engaged in causal inference research to present and discuss recent issues in causal inference methodological development. This is also a timely look at causal inference applied to scenarios that range from clinical trials to mediation and public health research more broadly. In an academic setting, this book will serve as a reference and guide to a course in causal inference at the graduate level (Master's or Doctorate). It is particularly relevant for students pursuing degrees in Statistics, Biostatistics and Computational Biology. Researchers and data analysts in public health and biomedical research will also find this book to be an important reference.
Causal Relationship between Construction Production and GDP in Turkey
Directory of Open Access Journals (Sweden)
Hakkı Kutay Bolkol
2015-12-01
Full Text Available This study empirically investigates the causal relationship between construction production and GDP for Turkey during 2005Q1-2013Q4 period. Because it is found that, there is no cointegration which means there is no long run relationship between variables, VAR Granger Causality Method is used to test the causality in short run. The findings reveal that, the causality runs from GDP to Building Production and Building Production to Non-Building Production (i.e. bidirectional relationship. Findings of this paper suggest that, because there is no long run relationship between Construction Production (Building and Non-Building and GDP and also in short run the causality runs from GDP to Construction Production, the growth strategy based on mainly Construction Sector growth is not a good idea for Turkey.
Causal Relationship between Construction Production and GDP in Turkey
Directory of Open Access Journals (Sweden)
Hakkı Kutay Bolkol
2015-09-01
Full Text Available This study empirically investigates the causal relationship between construction production and GDP for Turkey during 2005Q1-2013Q4 period. Because it is found that, there is no cointegration which means there is no long run relationship between variables, VAR Granger Causality Method is used to test the causality in short run. The findings reveal that, the causality runs from GDP to Building Production and Building Production to Non-Building Production (i.e. bidirectional relationship. Findings of this paper suggest that, because there is no long run relationship between Construction Production (Building and Non-Building and GDP and also in short run the causality runs from GDP to Construction Production, the growth strategy based on mainly Construction Sector growth is not a good idea for Turkey.
Combustion of powdery tungsten in pyrotechnic mixtures
International Nuclear Information System (INIS)
Ivanov, G.V.; Reshetov, A.A.; Viktorenko, A.M.; Surkov, V.G.; Karmadonov, L.N.
1982-01-01
The basic regularities of tungsten burning (powder 2-5 μm) with oxidizers most typical for pyrotechnics: nitrates, lead and barium peroxides (powder, 2-8 μm) and potassium perchlorate (powder, 2-8 μm) are studied. Dependences of burning rate as a function of pressure and ratio of components are established. It is supposed that tungsten burning in mixtures with the mentioned nitrates is a complex and multistage process the rate of which is determined by tungsten dissolution in nitrate melts. Analysis of burning products using available methods is complex
Pycnonuclear reaction rates for binary ionic mixtures
Ichimaru, S.; Ogata, S.; Van Horn, H. M.
1992-01-01
Through a combination of compositional scaling arguments and examinations of Monte Carlo simulation results for the interparticle separations in binary-ionic mixture (BIM) solids, we have derived parameterized expressions for the BIM pycnonuclear rates as generalizations of those in one-component solids obtained previously by Salpeter and Van Horn and by Ogata et al. We have thereby discovered a catalyzing effect of the heavier elements, which enhances the rates of reactions among the lighter elements when the charge ratio exceeds a critical value of approximately 2.3.
G-computation demonstration in causal mediation analysis
International Nuclear Information System (INIS)
Wang, Aolin; Arah, Onyebuchi A.
2015-01-01
Recent work has considerably advanced the definition, identification and estimation of controlled direct, and natural direct and indirect effects in causal mediation analysis. Despite the various estimation methods and statistical routines being developed, a unified approach for effect estimation under different effect decomposition scenarios is still needed for epidemiologic research. G-computation offers such unification and has been used for total effect and joint controlled direct effect estimation settings, involving different types of exposure and outcome variables. In this study, we demonstrate the utility of parametric g-computation in estimating various components of the total effect, including (1) natural direct and indirect effects, (2) standard and stochastic controlled direct effects, and (3) reference and mediated interaction effects, using Monte Carlo simulations in standard statistical software. For each study subject, we estimated their nested potential outcomes corresponding to the (mediated) effects of an intervention on the exposure wherein the mediator was allowed to attain the value it would have under a possible counterfactual exposure intervention, under a pre-specified distribution of the mediator independent of any causes, or under a fixed controlled value. A final regression of the potential outcome on the exposure intervention variable was used to compute point estimates and bootstrap was used to obtain confidence intervals. Through contrasting different potential outcomes, this analytical framework provides an intuitive way of estimating effects under the recently introduced 3- and 4-way effect decomposition. This framework can be extended to complex multivariable and longitudinal mediation settings
Symmetries, causality problems and neutrino fields in antipode universes
International Nuclear Information System (INIS)
Sasse, F.D.
1986-01-01
The S 3 xR and H 3 xR Lie groups are characterized, and using continuous deformations of S 3 and H 3 subgroups algebra, Lorentz space-time metrics with g E left invariance and g D right invariance are introduced. The topology of sections of these space-time is investigated and its relation with global causality problems is shown. In the search of g E and g D isometries, it is shown that in the class of metrics associated to H 3 xR topology, there is a particular case which accepts a G 7 group of isometries. It is shown that the g E and g D metrics characterize universes which vortices of cosmological fluid (when it is present), in relation to the inertial compass, are opposite. In the particular coordinate system, that is used, these metrics differs only by a coordinate inversion transformation. Neutrinos interacting with the geometry of these spaces times is considered. It is shown that the physical transformation which consists in to reverse the universe rotation and to reverse a determined component of neutrino momentum, leads the universe with g E (g D ) metric containing neutrinos, with determined helicity, to another one with g D (g E )metric containing neutrinos, with opposite helicity from the original. Thus, neutrinos can be used to distinguish physically these two universes, supposing that in a given universe neutrinos there is always a type of helicity. (M.C.K.) [pt
Probing the Cultural Constitution of Causal Cognition – A Research Program
Bender, Andrea; Beller, Sieghard
2016-01-01
To what extent is the way people perceive, represent, and reason about causal relationships dependent on culture? While there have been sporadic attempts to explore this question, a systematic investigation is still lacking. Here, we propose that human causal cognition is not only superficially affected by cultural background, but that it is co-constituted by the cultural nature of the human species. To this end, we take stock of on-going research, with a particular focus on the methodological approaches taken: cross-species comparisons, archeological accounts, developmental studies, cross-cultural, and cross-linguistic experiments, as well as in-depth within-culture analyses of cognitive concepts, processes, and changes over time. We argue that only a combination of these approaches will allow us to integrate different components of cognition, levels of analysis, and points of view—the key requirements for a comprehensive, interdisciplinary research program to advance this field. PMID:26941695
Beyond Markov: Accounting for independence violations in causal reasoning.
Rehder, Bob
2018-06-01
Although many theories of causal cognition are based on causal graphical models, a key property of such models-the independence relations stipulated by the Markov condition-is routinely violated by human reasoners. This article presents three new accounts of those independence violations, accounts that share the assumption that people's understanding of the correlational structure of data generated from a causal graph differs from that stipulated by causal graphical model framework. To distinguish these models, experiments assessed how people reason with causal graphs that are larger than those tested in previous studies. A traditional common cause network (Y 1 ←X→Y 2 ) was extended so that the effects themselves had effects (Z 1 ←Y 1 ←X→Y 2 →Z 2 ). A traditional common effect network (Y 1 →X←Y 2 ) was extended so that the causes themselves had causes (Z 1 →Y 1 →X←Y 2 ←Z 2 ). Subjects' inferences were most consistent with the beta-Q model in which consistent states of the world-those in which variables are either mostly all present or mostly all absent-are viewed as more probable than stipulated by the causal graphical model framework. Substantial variability in subjects' inferences was also observed, with the result that substantial minorities of subjects were best fit by one of the other models (the dual prototype or a leaky gate models). The discrepancy between normative and human causal cognition stipulated by these models is foundational in the sense that they locate the error not in people's causal reasoning but rather in their causal representations. As a result, they are applicable to any cognitive theory grounded in causal graphical models, including theories of analogy, learning, explanation, categorization, decision-making, and counterfactual reasoning. Preliminary evidence that independence violations indeed generalize to other judgment types is presented. Copyright © 2018 Elsevier Inc. All rights reserved.
Binary and ternary gas mixtures for use in glow discharge closing switches
Hunter, S.R.; Christophorou, L.G.
1988-04-27
Highly efficient binary and ternary gas mixtures for use in diffuse glow discharge closing switches are disclosed. The binary mixtures are combinations of helium or neon and selected perfluorides. The ternary mixtures are combinations of helium, neon, or argon, a selected perfluoride, and a small amount of gas that exhibits enhanced ionization characteristics. These mixtures are shown to be the optimum choices for use in diffuse glow discharge closing switches by virtue if the combines physio-electric properties of the mixture components. 9 figs.
Hallin, M.; Hörmann, S.; Piegorsch, W.; El Shaarawi, A.
2012-01-01
Principal Components are probably the best known and most widely used of all multivariate analysis techniques. The essential idea consists in performing a linear transformation of the observed k-dimensional variables in such a way that the new variables are vectors of k mutually orthogonal
Grotzer, Tina A.; Tutwiler, M. Shane
2014-01-01
This article considers a set of well-researched default assumptions that people make in reasoning about complex causality and argues that, in part, they result from the forms of causal induction that we engage in and the type of information available in complex environments. It considers how information often falls outside our attentional frame…
Triantafillou, Sofia; Lagani, Vincenzo; Heinze-Deml, Christina; Schmidt, Angelika; Tegner, Jesper; Tsamardinos, Ioannis
2017-01-01
Learning the causal relationships that define a molecular system allows us to predict how the system will respond to different interventions. Distinguishing causality from mere association typically requires randomized experiments. Methods for automated causal discovery from limited experiments exist, but have so far rarely been tested in systems biology applications. In this work, we apply state-of-the art causal discovery methods on a large collection of public mass cytometry data sets, measuring intra-cellular signaling proteins of the human immune system and their response to several perturbations. We show how different experimental conditions can be used to facilitate causal discovery, and apply two fundamental methods that produce context-specific causal predictions. Causal predictions were reproducible across independent data sets from two different studies, but often disagree with the KEGG pathway databases. Within this context, we discuss the caveats we need to overcome for automated causal discovery to become a part of the routine data analysis in systems biology.
Directory of Open Access Journals (Sweden)
York eHagmayer
2014-11-01
Full Text Available Cognitive psychological research focusses on causal learning and reasoning while cognitive anthropological and social science research tend to focus on systems of beliefs. Our aim was to explore how these two types of research can inform each other. Cognitive psychological theories (causal model theory and causal Bayes nets were used to derive predictions for systems of causal beliefs. These predictions were then applied to lay theories of depression as a specific test case. A systematic literature review on causal beliefs about depression was conducted, including original, quantitative research. Thirty-six studies investigating 13 non-Western and 32 Western cultural groups were analysed by classifying assumed causes and preferred forms of treatment into common categories. Relations between beliefs and treatment preferences were assessed. Substantial agreement between cultural groups was found with respect to the impact of observable causes. Stress was generally rated as most important. Less agreement resulted for hidden, especially supernatural causes. Causal beliefs were clearly related to treatment preferences in Western groups, while evidence was mostly lacking for non-Western groups. Overall predictions were supported, but there were considerable methodological limitations. Pointers to future research, which may combine studies on causal beliefs with experimental paradigms on causal reasoning, are given.
Triantafillou, Sofia
2017-09-29
Learning the causal relationships that define a molecular system allows us to predict how the system will respond to different interventions. Distinguishing causality from mere association typically requires randomized experiments. Methods for automated causal discovery from limited experiments exist, but have so far rarely been tested in systems biology applications. In this work, we apply state-of-the art causal discovery methods on a large collection of public mass cytometry data sets, measuring intra-cellular signaling proteins of the human immune system and their response to several perturbations. We show how different experimental conditions can be used to facilitate causal discovery, and apply two fundamental methods that produce context-specific causal predictions. Causal predictions were reproducible across independent data sets from two different studies, but often disagree with the KEGG pathway databases. Within this context, we discuss the caveats we need to overcome for automated causal discovery to become a part of the routine data analysis in systems biology.
Sanders, T.J.M.|info:eu-repo/dai/nl/075243911; Spooren, W.P.M.S.
Many languages of the world have connectives to express causal relations at the discourse level. Often, language users systematically prefer one lexical item (because) over another (even highly similar) one (since) to express a causal relationship. Such choices provide a window on speakers'