Quantum-coherent mixtures of causal relations
MacLean, Jean-Philippe W; Spekkens, Robert W; Resch, Kevin J
2016-01-01
Understanding the causal influences that hold among the parts of a system is critical both to explaining that system's natural behaviour and to controlling it through targeted interventions. In a quantum world, understanding causal relations is equally important, but the set of possibilities is far richer. The two basic ways in which a pair of time-ordered quantum systems may be causally related are by a cause-effect mechanism or by a common cause acting on both. Here, we show that it is possible to have a coherent mixture of these two possibilities. We realize such a nonclassical causal relation in a quantum optics experiment and derive a set of criteria for witnessing the coherence based on a quantum version of Berkson's paradox. The interplay of causality and quantum theory lies at the heart of challenging foundational puzzles, such as Bell's theorem and the search for quantum gravity, but could also provide a resource for novel quantum technologies.
Iterative Mixture Component Pruning Algorithm for Gaussian Mixture PHD Filter
Xiaoxi Yan
2014-01-01
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 funct...
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.
Systems and methods for removing components of a gas mixture
Energy Technology Data Exchange (ETDEWEB)
None
2016-09-06
A system for removing components of a gaseous mixture is provided comprising: a reactor fluid containing vessel having conduits extending therefrom, aqueous fluid within the reactor, the fluid containing a ligand and a metal, and at least one reactive surface within the vessel coupled to a power source. A method for removing a component from a gaseous mixture is provided comprising exposing the gaseous mixture to a fluid containing a ligand and a reactive metal, the exposing chemically binding the component of the gaseous mixture to the ligand. A method of capturing a component of a gaseous mixture is provided comprising: exposing the gaseous mixture to a fluid containing a ligand and a reactive metal, the exposing chemically binding the component of the gaseous mixture to the ligand, altering the oxidation state of the metal, the altering unbinding the component from the ligand, and capturing the component.
Mixtures of Product Components versus Mixtures of Dependence Trees
Czech Academy of Sciences Publication Activity Database
Grim, Jiří; Pudil, P.
Cham: Springer, 2015, s. 365-382. (Studies in Computational Intelligence. 620). ISBN 978-3-319-26393-9. [IJCCI 2014 - International Joint Conference on Computational Intelligence (Rome/Italy). Rome (IT), 22.10.2014-24.10.2014] R&D Projects: GA ČR(CZ) GA14-02652S Grant ostatní: GA ČR(CZ) GAP403/12/1557 Institutional support: RVO:67985556 Keywords : Product mixtures * Mixtures of Dependence Trees * EM algorithm Subject RIV: BD - Theory of Information http://library.utia.cas.cz/separaty/2016/RO/grim-0452538.pdf
Independent components in spectroscopic analysis of complex mixtures
Monakhova, Yulia B; Astakhov, Sergey A.; Kraskov, Alexander; Mushtakova, Svetlana P.
2010-01-01
We applied two methods of "blind" spectral decomposition (MILCA and SNICA) to quantitative and qualitative analysis of UV absorption spectra of several non-trivial mixture types. Both methods use the concept of statistical independence and aim at the reconstruction of minimally dependent components from a linear mixture. We examined mixtures of major ecotoxicants (aromatic and polyaromatic hydrocarbons), amino acids and complex mixtures of vitamins in a veterinary drug. Both MICLA and SNICA w...
The separation of solid and liquid components of mixtures
International Nuclear Information System (INIS)
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.)
Independent components in spectroscopic analysis of complex mixtures
Monakhova, Yulia B; Kraskov, Alexander; Mushtakova, Svetlana P; 10.1016/j.chemolab.2010.05.023
2010-01-01
We applied two methods of "blind" spectral decomposition (MILCA and SNICA) to quantitative and qualitative analysis of UV absorption spectra of several non-trivial mixture types. Both methods use the concept of statistical independence and aim at the reconstruction of minimally dependent components from a linear mixture. We examined mixtures of major ecotoxicants (aromatic and polyaromatic hydrocarbons), amino acids and complex mixtures of vitamins in a veterinary drug. Both MICLA and SNICA were able to recover concentrations and individual spectra with minimal errors comparable with instrumental noise. In most cases their performance was similar to or better than that of other chemometric methods such as MCR-ALS, SIMPLISMA, RADICAL, JADE and FastICA. These results suggest that the ICA methods used in this study are suitable for real life applications.
Efficient speaker verification using Gaussian mixture model component clustering.
Energy Technology Data Exchange (ETDEWEB)
De Leon, Phillip L. (New Mexico State University, Las Cruces, NM); McClanahan, Richard D.
2012-04-01
In speaker verification (SV) systems that employ a support vector machine (SVM) classifier to make decisions on a supervector derived from Gaussian mixture model (GMM) component mean vectors, a significant portion of the computational load is involved in the calculation of the a posteriori probability of the feature vectors of the speaker under test with respect to the individual component densities of the universal background model (UBM). Further, the calculation of the sufficient statistics for the weight, mean, and covariance parameters derived from these same feature vectors also contribute a substantial amount of processing load to the SV system. In this paper, we propose a method that utilizes clusters of GMM-UBM mixture component densities in order to reduce the computational load required. In the adaptation step we score the feature vectors against the clusters and calculate the a posteriori probabilities and update the statistics exclusively for mixture components belonging to appropriate clusters. Each cluster is a grouping of multivariate normal distributions and is modeled by a single multivariate distribution. As such, the set of multivariate normal distributions representing the different clusters also form a GMM. This GMM is referred to as a hash GMM which can be considered to a lower resolution representation of the GMM-UBM. The mapping that associates the components of the hash GMM with components of the original GMM-UBM is referred to as a shortlist. This research investigates various methods of clustering the components of the GMM-UBM and forming hash GMMs. Of five different methods that are presented one method, Gaussian mixture reduction as proposed by Runnall's, easily outperformed the other methods. This method of Gaussian reduction iteratively reduces the size of a GMM by successively merging pairs of component densities. Pairs are selected for merger by using a Kullback-Leibler based metric. Using Runnal's method of reduction, we
Merging Mixture Components for Cell Population Identification in Flow Cytometry
Directory of Open Access Journals (Sweden)
Greg Finak
2009-01-01
Full Text Available We present a framework for the identification of cell subpopulations in flow cytometry data based on merging mixture components using the flowClust methodology. We show that the cluster merging algorithm under our framework improves model fit and provides a better estimate of the number of distinct cell subpopulations than either Gaussian mixture models or flowClust, especially for complicated flow cytometry data distributions. Our framework allows the automated selection of the number of distinct cell subpopulations and we are able to identify cases where the algorithm fails, thus making it suitable for application in a high throughput FCM analysis pipeline. Furthermore, we demonstrate a method for summarizing complex merged cell subpopulations in a simple manner that integrates with the existing flowClust framework and enables downstream data analysis. We demonstrate the performance of our framework on simulated and real FCM data. The software is available in the flowMerge package through the Bioconductor project.
Energy Technology Data Exchange (ETDEWEB)
Piepel, Gregory F.; Cooley, Scott K.; Vienna, John D.; Crum, Jarrod V.
2016-05-04
This article presents a case study of developing an experimental design for a constrained mixture experiment when the experimental region is defined by single-component constraints (SCCs), linear multiple-component constraints (MCCs), and a nonlinear MCC. Traditional methods and software for designing constrained mixture experiments with SCCs and linear MCCs are not directly applicable because of the nonlinear MCC. A modification of existing methodology to account for the nonlinear MCC was developed and is described in this article. The case study involves a 15-component nuclear waste glass example in which SO3 is one of the components. SO3 has a solubility limit in glass that depends on the composition of the balance of the glass. A goal was to design the experiment so that SO3 would not exceed its predicted solubility limit for any of the experimental glasses. The SO3 solubility limit had previously been modeled by a partial quadratic mixture (PQM) model expressed in the relative proportions of the 14 other components. The PQM model was used to construct a nonlinear MCC in terms of all 15 components. In addition, there were SCCs and linear MCCs. This article discusses the waste glass example and how a layered design was generated to (i) account for the SCCs, linear MCCs, and nonlinear MCC and (ii) meet the goals of the study.
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. PMID:26520533
Effective-Medium Approach for Conductivities in Multi-Component Granular Mixtures
International Nuclear Information System (INIS)
We apply the effective-medium theory to a multi-component mixture system, by which the effective longitudinal and Hall conductivities can be calculated. We find that there is more than one threshold in the multi-component mixture, and the maximum number of thresholds is one less than the component number. Further, the thresholds are mainly dependent on the relative volume ratio of the components when the conductivity ratios between any two components are far larger or smaller than one
Directory of Open Access Journals (Sweden)
Charlotte Sinding
Full Text Available Young and adult mammals are constantly exposed to chemically complex stimuli. The olfactory system allows for a dual processing of relevant information from the environment either as single odorants in mixtures (elemental perception or as mixtures of odorants as a whole (configural perception. However, it seems that human adults have certain limits in elemental perception of odor mixtures, as suggested by their inability to identify each odorant in mixtures of more than 4 components. Here, we explored some of these limits by evaluating the perception of three 6-odorant mixtures in human adults and newborn rabbits. Using free-sorting tasks in humans, we investigated the configural or elemental perception of these mixtures, or of 5-component sub-mixtures, or of the 6-odorant mixtures with modified odorants' proportion. In rabbit pups, the perception of the same mixtures was evaluated by measuring the orocephalic sucking response to the mixtures or their components after conditioning to one of these stimuli. The results revealed that one mixture, previously shown to carry the specific odor of red cordial in humans, was indeed configurally processed in humans and in rabbits while the two other 6-component mixtures were not. Moreover, in both species, such configural perception was specific not only to the 6 odorants included in the mixture but also to their respective proportion. Interestingly, rabbit neonates also responded to each odorant after conditioning to the red cordial mixture, which demonstrates their ability to perceive elements in addition to configuration in this complex mixture. Taken together, the results provide new insights related to the processing of relatively complex odor mixtures in mammals and the inter-species conservation of certain perceptual mechanisms; the results also revealed some differences in the expression of these capacities between species putatively linked to developmental and ecological constraints.
The D-optimal design of blocked and split-plot experiments with mixture components
Goos, Peter; Donev, AN
2003-01-01
So far, the optimal design of blocked and split-plot experiments involving mixture components has received scant attention. In this paper, an easy method to construct efficient blocked mixture experiments in the presence of fixed and/or random blocks is presented. The method can be used when qualitative variables are involved in a mixture experiment as well. It is also shown that orthogonally blocked mixture experiments are highly inefficient compared to D-optimal designs. Finally, the design...
Le Berre, E; Béno, N; Ishii, A; Chabanet, C; Etiévant, P; Thomas-Danguin, T
2008-04-01
The odors we perceive are mainly the result of mixtures of odorants that, however, are commonly perceived as single undivided entities; nevertheless, the processes involved remain poorly explored. It has been recently reported that perceptual blending based on configural olfactory processing can cause odorant mixtures to give rise to an emergent odor not present in the components. The present study examined whether specific component proportions are required to elicit an emergent odor. Starting from the composition of a ternary target mixture in which an emergent pineapple odor was perceived, 4 concentration levels of each component were chosen to elicit just noticeable differences (JNDs). Each combination of levels was used to design sample mixtures. Fifteen subjects evaluated the intensity, typicality, and pleasantness of each sample mixture against the target mixture in a paired-comparison protocol. Statistical modeling showed that a variation of less than 1 JND in one of the components was sufficient to induce a significant decrease in pineapple odor typicality in the ternary mixture. This finding confirms previous findings on perceptual blending in simple odorant mixtures and underscores the human ability to discriminate between odor percepts induced by mixtures including very similar odorant proportions. PMID:18304991
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.
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...
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.
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.)
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
Larabi, Mohamed Aziz; Mutschler, Dimitri; Mojtabi, Abdelkader
2016-06-28
Our present work focuses on the coupling between thermal diffusion and convection in order to improve the thermal gravitational separation of mixture components. The separation phenomenon was studied in a porous medium contained in vertical columns. We performed analytical and numerical simulations to corroborate the experimental measurements of the thermal diffusion coefficients of ternary mixture n-dodecane, isobutylbenzene, and tetralin obtained in microgravity in the international space station. Our approach corroborates the existing data published in the literature. The authors show that it is possible to quantify and to optimize the species separation for ternary mixtures. The authors checked, for ternary mixtures, the validity of the "forgotten effect hypothesis" established for binary mixtures by Furry, Jones, and Onsager. Two complete and different analytical resolution methods were used in order to describe the separation in terms of Lewis numbers, the separation ratios, the cross-diffusion coefficients, and the Rayleigh number. The analytical model is based on the parallel flow approximation. In order to validate this model, a numerical simulation was performed using the finite element method. From our new approach to vertical separation columns, new relations for mass fraction gradients and the optimal Rayleigh number for each component of the ternary mixture were obtained. PMID:27369539
Larabi, Mohamed Aziz; Mutschler, Dimitri; Mojtabi, Abdelkader
2016-06-01
Our present work focuses on the coupling between thermal diffusion and convection in order to improve the thermal gravitational separation of mixture components. The separation phenomenon was studied in a porous medium contained in vertical columns. We performed analytical and numerical simulations to corroborate the experimental measurements of the thermal diffusion coefficients of ternary mixture n-dodecane, isobutylbenzene, and tetralin obtained in microgravity in the international space station. Our approach corroborates the existing data published in the literature. The authors show that it is possible to quantify and to optimize the species separation for ternary mixtures. The authors checked, for ternary mixtures, the validity of the "forgotten effect hypothesis" established for binary mixtures by Furry, Jones, and Onsager. Two complete and different analytical resolution methods were used in order to describe the separation in terms of Lewis numbers, the separation ratios, the cross-diffusion coefficients, and the Rayleigh number. The analytical model is based on the parallel flow approximation. In order to validate this model, a numerical simulation was performed using the finite element method. From our new approach to vertical separation columns, new relations for mass fraction gradients and the optimal Rayleigh number for each component of the ternary mixture were obtained.
Directory of Open Access Journals (Sweden)
Varun Kumar Ojha
2012-07-01
Full Text Available The article presents performance analysis of a real valued neuro genetic algorithm applied for the detection of proportion of the gases found in manhole gas mixture. The neural network (NN trained using genetic algorithm (GA leads to concept of neuro genetic algorithm, which is used for implementing an intelligent sensory system for the detection of component gases present in manhole gas mixture Usually a manhole gas mixture contains several toxic gases like Hydrogen Sulfide, Ammonia, Methane, Carbon Dioxide, Nitrogen Oxide, and Carbon Monoxide. A semiconductor based gas sensor array used for sensing manhole gas components is an integral part of the proposed intelligent system. It consists of many sensor elements, where each sensor element is responsible for sensing particular gas component. Multiple sensors of different gases used for detecting gas mixture of multiple gases, results in cross-sensitivity. The crosssensitivity is a major issue and the problem is viewed as pattern recognition problem. The objective of this article is to present performance analysis of the real valued neuro genetic algorithm which is applied for multiple gas detection.
Directory of Open Access Journals (Sweden)
Varun Kumar Ojha
2012-08-01
Full Text Available The article presents performance analysis of a real valued neuro genetic algorithm applied for thedetection of proportion of the gases found in manhole gas mixture. The neural network (NN trained usinggenetic algorithm (GA leads to concept of neuro genetic algorithm, which is used for implementing anintelligent sensory system for the detection of component gases present in manhole gas mixture Usually amanhole gas mixture contains several toxic gases like Hydrogen Sulfide, Ammonia, Methane, CarbonDioxide, Nitrogen Oxide, and Carbon Monoxide. A semiconductor based gas sensor array used for sensingmanhole gas components is an integral part of the proposed intelligent system. It consists of many sensorelements, where each sensor element is responsible for sensing particular gas component. Multiple sensorsof different gases used for detecting gas mixture of multiple gases, results in cross-sensitivity. The crosssensitivity is a major issue and the problem is viewed as pattern recognition problem. The objective of thisarticle is to present performance analysis of the real valued neuro genetic algorithm which is applied formultiple gas detection.
Directory of Open Access Journals (Sweden)
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.
International Nuclear Information System (INIS)
The components of a mixture of n radioactive isotopes can be determined from the change in activity with time provided that the activity of at least n-1 components changes significantly during the period of observation, either by direct decay or by the growth of decay products. ft is possible to predict a set of possible components for each mixture encountered, based on considerations such as the origin and history of the mixture and the separation chemistry and counting technique(s) used. If such considerations are properly applied, the set of possible components will include all of the actual components in the mixture. The appropriate growth and/or decay equations can then be formulated and solved simultaneously to obtain each component, or the mixture can be resolved graphically by extrapolations of the linear portions of the total decay-growth curve. However, when the number of components is large and/or when complex decay schemes are involved, these two techniques either cannot be applied or the errors associated with the estimates cannot be assessed. Selection of decay components by a least-squares procedure provides better estimates than solution by simultaneous equations alone. Consequently, a least-squares Fortran computer programme (designated CORD) has been developed which solves the general problem: given the times and counts per unit time from a sample, the possible radioisotopic parents and decay schemes and all associated decay constants and detection efficiencies compute the amount of each parent actually present at a predetermined zero time. In addition, the programme yields the amounts of the parents and daughters present at all data times. Initially used with bioassay and environmental samples, the programme has been specifically designed for analysing count-rate data obtained by non-spectroscopic alpha- or beta-counting. However, it should be adaptable to total gamma and spectroscopic data, provided the energy ranges over which these
Jutten, Christian; Karhunen, Juha
2004-10-01
In this paper, we review recent advances in blind source separation (BSS) and independent component analysis (ICA) for nonlinear mixing models. After a general introduction to BSS and ICA, we discuss in more detail uniqueness and separability issues, presenting some new results. A fundamental difficulty in the nonlinear BSS problem and even more so in the nonlinear ICA problem is that they provide non-unique solutions without extra constraints, which are often implemented by using a suitable regularization. In this paper, we explore two possible approaches. The first one is based on structural constraints. Especially, post-nonlinear mixtures are an important special case, where a nonlinearity is applied to linear mixtures. For such mixtures, the ambiguities are essentially the same as for the linear ICA or BSS problems. The second approach uses Bayesian inference methods for estimating the best statistical parameters, under almost unconstrained models in which priors can be easily added. In the later part of this paper, various separation techniques proposed for post-nonlinear mixtures and general nonlinear mixtures are reviewed. PMID:15593377
Institute of Scientific and Technical Information of China (English)
Zhang Ke-Sheng; Wang Shu; Zhu Ming; Ding Yi; Hu Yi
2013-01-01
Decoupling the complicated vibrational-vibrational (V-V) coupling of a multimode vibrational relaxation remains a challenge for analyzing the sound relaxational absorption in multi-component gas mixtures.In our previous work [Acta Phys.Sin.61 174301 (2012)],an analytical model to predict the sound absorption from vibrational relaxation in a gas medium is proposed.In this paper,we develop the model to decouple the V-V coupled energy to each vibrationaltranslational deexcitation path,and analyze how the multimode relaxations form the peaks of sound absorption spectra in gas mixtures.We prove that a multimode relaxation is the sum of its decoupled single-relaxation processes,and only the decoupled process with a significant isochoric-molar-heat can be observed as an absorption peak.The decoupling model clarifies the essential processes behind the peaks in spectra arising from the multimode relaxations in multi-component gas mixtures.The simulation validates the proposed decoupling model.
Numerical simulation of nonlinear acoustic attenuation of multi-component gas mixture
Institute of Scientific and Technical Information of China (English)
YAN Shu; WANG Shu
2009-01-01
The direct simulation Monte Carlo (DSMC) method was introduced to model the acoustic propagation in multi-component gas mixtures. And a theoretical predictive model of acoustic attenuation was proposed, which does not rely on experiential parameters. The acoustic attenuation spectra of various multi-component gas mixtures, consisting of nitrogen, oxygen, carbon dioxide, methane and water, were estimated by the DSMC method. The sound frequency range of interest is from 8 MHz to 232 MHz. Compared with the result of the relaxation attenuation based on the DL model plus that of the classical attenuation calculated by the Stokes-Kirchhoff formula, the estimations of acoustic attenuation of our model agreed with them. The precision of the model depends upon the understanding of the physical mechanism of molecule collision from which the attenuation arises. In addition, the result of our model shows that the characters of the frequency-dependent acoustic attenuation rely on the composition of the gas mixtures. And this could lead to the development of smart acoustic gas sensors capable of quantitatively determining gas composition in various environments and processes.
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.
Kojima, Takehiro; Elliott, James A.
2013-06-01
Understanding the flow properties of two-component fine powder systems with micrometre-sized constituents is important for the quality control of electrophotographic printing applications such as photocopiers. In previous work, we studied the incipient flow properties of model powder mixtures of large (d50 ˜ 70 μm) and small (d50 ˜ 6-8 μm) particles under a consolidation stress of 2 kPa, and reported that they were strongly related to the properties of the small particles where the volume ratio of small powder (xs) exceeds ˜0.1 [1]. In this follow-up study, we examine the effect of changing the flowability of the smaller components on the structure and flow properties of the binary mixtures. For the smaller particles, we used poly(styrene-co-divinylbenzene) (PS-DVB) microspheres (d50 = 7.84 μm). The particle surfaces were modified by adding silica nanoparticles in order to prepare PS-DVB powders with a range of flowabilities. These were then mixed with glass ballotini (d50 = 71.9 μm), and the flow properties of these mixtures were evaluated using the shear testing technique. The cohesion of the mixtures showed essentially the same trend as reported in [1] in terms of their dependence on xs and was related to the number of contacts between the PS-DVB particles. Also, it was strongly dependent on the cohesion of the PS-DVB powders despite a very small xs (xs DVB powder was similar, it also showed a correlation with the number of contacts between PS-DVB particles.
A new blind fault component separation algorithm for a single-channel mechanical signal mixture
Wang, Dong; Tse, Peter W.
2012-10-01
A vibration signal collected from a complex machine consists of multiple vibration components, which are system responses excited by several sources. This paper reports a new blind component separation (BCS) method for extracting different mechanical fault features. By applying the proposed method, a single-channel mixed signal can be decomposed into two parts: the periodic and transient subsets. The periodic subset is related to the imbalance, misalignment and eccentricity of a machine. The transient subset refers to abnormal impulsive phenomena, such as those caused by localized bearing faults. The proposed method includes two individual strategies to deal with these different characteristics. The first extracts the sub-Gaussian periodic signal by minimizing the kurtosis of the equalized signals. The second detects the super-Gaussian transient signal by minimizing the smoothness index of the equalized signals. Here, the equalized signals are derived by an eigenvector algorithm that is a successful solution to the blind equalization problem. To reduce the computing time needed to select the equalizer length, a simple optimization method is introduced to minimize the kurtosis and smoothness index, respectively. Finally, simulated multiple-fault signals and a real multiple-fault signal collected from an industrial machine are used to validate the proposed method. The results show that the proposed method is able to effectively decompose the multiple-fault vibration mixture into periodic components and random non-stationary transient components. In addition, the equalizer length can be intelligently determined using the proposed method.
International Nuclear Information System (INIS)
A unified approach to the analysis of stellar populations through the application of finite mixture models is presented, and the statistical properties of univariate finite mixture models are examined. A review is presented of the analysis methods that are available, with emphasis on methods for estimating the parameters that describe the underlying stellar populations and for determining the number of discrete stellar populations. Attention is restricted to five variables: U, V, W, Fe/H, and age. Parameter and error estimation is demonstrated in two simulation experiments designed to assess the detectability of a thick disk in samples of solar neighborhood stars. 159 refs
ARTS: A System-Level Framework for Modeling MPSoC Components and Analysis of their Causality
DEFF Research Database (Denmark)
Mahadevan, Shankar; Storgaard, Michael; Madsen, Jan;
2005-01-01
Designing complex heterogeneousmultiprocessor Systemon- Chip (MPSoC) requires support for modeling and analysis of the different layers i.e. application, operating system (OS) and platform architecture. This paper presents an abstract system-level modeling framework, called ARTS, to support the...... MPSoC designers in modeling the different layers and understanding their causalities. While others have developed tools for static analysis and modeled limited correlations (processor-memory or processor-communication), our model captures the impact of dynamic and unpredictable OS behaviour on...... platform for a handheld terminal shows our frameworks co-exploration capabilities....
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.
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...
Lee, Jong-Hyeon; Landrum, Peter F
2006-02-15
A new mixture toxicity model was developed to predict the time-dependent toxicity of a mixture with toxicokinetic interactions directed specifically toward addressing biotransformation. The Damage Assessment Model (DAM), a toxicokinetic-toxicodynamic model that describes and predicts the time-dependent toxicity of a single compound, was extended to a multicomponent model for mixture toxicity. The model assumes that cumulative damage from the parent compound, metabolites, and/or a biotransformation inhibitor are additive, and the sum of the cumulative damage determines mixture toxicity. Since incorporation of the damage addition hypothesis into the DAM was equivalent to an independent action model for mixture toxicity, it was applied to describe the combined effect of mixture components with potentially dissimilar modes of action. From the multicomponent DAM, a time-dependent toxic unit model was derived and applied to determine the toxic units of mixture components. This model suggests a series of experimental designs required to assess the role of biotransformation in the toxicity of metabolized organic compounds and a data analysis method to separately estimate toxicodynamic parameters forthe parent compound and metabolites. PMID:16572795
International Nuclear Information System (INIS)
Sparse component analysis (SCA) is demonstrated for blind extraction of three pure component spectra from only two measured mixed spectra in 13C and 1H nuclear magnetic resonance (NMR) spectroscopy. This appears to be the first time to report such results and that is the first novelty of the paper. Presented concept is general and directly applicable to experimental scenarios that possibly would require use of more than two mixtures. However, it is important to emphasize that number of required mixtures is always less than number of components present in these mixtures. The second novelty is formulation of blind NMR spectra decomposition exploiting sparseness of the pure components in the wavelet basis defined by either Morlet or Mexican hat wavelet. This enabled accurate estimation of the concentration matrix and number of pure components by means of data clustering algorithm and pure components spectra by means of linear programming with constraints from both 1H and 13C NMR experimental data. The third novelty is capability of proposed method to estimate number of pure components in demanding underdetermined blind source separation (uBSS) scenario. This is in contrast to majority of the BSS algorithms that assume this information to be known in advance. Presented results are important for the NMR spectroscopy-associated data analysis in pharmaceutical industry, medicine diagnostics and natural products research.
DEFF Research Database (Denmark)
Rasmussen, Lauge Baungaard
2006-01-01
The lecture note explains how to use the causal mapping method as well as the theoretical framework aoosciated to the method......The lecture note explains how to use the causal mapping method as well as the theoretical framework aoosciated to the method...
McGivern, W. S.; Allison, T. C.; Radney, J. G.; Zangmeister, C. D.
2014-12-01
The aqueous reaction of methylglyoxal (MG) with ammonium sulfate has been suggested as a source of atmospheric ``brown carbon.'' We have utilized high-performance liquid chromatography coupled to ultraviolet-visible spectroscopy and tandem mass spectrometry to study the products of this reaction at high concentrations. The overall product spectrum shows a large number of distinct components; however, the visible absorption from this mixture is derived a very small number of components. The largest contributor is an imine-substituted (C=N-H) product of aldol condensation/facile dehydration reaction between the parent MG and a hydrated product of the MG + ammonia reaction. The asymmetric nature of this compound relative to the aldol condensation of two MG results in a sufficiently large redshift of the UV absorption spectrum that absorption of visible radiation can occur in the long-wavelength tail. The simplicity of the imine products is a result of a strong bias toward ketimine products due to the extensive hydration of the aldehydic moiety in the parent in aqueous solution. In addition, a strong pH dependence of the absorption cross section was observed with significantly greater absorption under more basic conditions. We have performed time-dependent density functional theory calculations to evaluate the absorption spectra of all of the possible condensation products and their respective ions, and the results are consistent with the experimental observations. We have also observed smaller concentrations of other condensation products of the imine-substituted parent species that do not contribute significantly to the visible absorption but have not been previously discussed.
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…
Fanood, Mohammad M Rafiee; Ram, N Bhargava; Lehmann, C Stefan; Powis, Ivan; Janssen, Maurice 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 enantiomers may be differentiated by mass-selected photoelectron circular dichroism using an electron-ion coincidence imaging spectrometer. As proof of concept, vapours containing ∼1% of two chiral monoterpene molecules, limonene and camphor, are irradiated by a circularly polarized femtosecond laser, resulting in multiphoton near-threshold ionization with little molecular fragmentation. Large chiral asymmetries (2-4%) are observed in the mass-tagged photoelectron angular distributions. These asymmetries switch sign according to the handedness (R- or S-) of the enantiomer in the mixture and scale with enantiomeric excess of a component. The results demonstrate that mass spectrometric identification of mixtures of chiral molecules and quantitative determination of enantiomeric excess can be achieved in a table-top instrument. PMID:26104140
Fanood, Mohammad M Rafiee; Ram, N. Bhargava; Lehmann, C. Stefan; Powis, Ivan; Janssen, Maurice 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 enantiomers may be differentiated by mass-selected photoelectron circular dichroism using an electron–ion coincidence imaging spectrometer. As proof of concept, vapours containing ∼1% of two chiral monoterpene molecules, limonene and camphor, are irradiated by a circularly polarized femtosecond laser, resulting in multiphoton near-threshold ionization with little molecular fragmentation. Large chiral asymmetries (2–4%) are observed in the mass-tagged photoelectron angular distributions. These asymmetries switch sign according to the handedness (R- or S-) of the enantiomer in the mixture and scale with enantiomeric excess of a component. The results demonstrate that mass spectrometric identification of mixtures of chiral molecules and quantitative determination of enantiomeric excess can be achieved in a table-top instrument. PMID:26104140
DeArmond, Patrick D.; West, Graham M.; Huang, Hai-Tsang; Fitzgerald, Michael C.
2011-03-01
Described here is a stable isotope labeling protocol that can be used with a chemical modification- and mass spectrometry-based protein-ligand binding assay for detecting and quantifying both the direct and indirect binding events that result from protein-ligand binding interactions. The protocol utilizes an H{2/16}O2 and H{2/18}O2 labeling strategy to evaluate the chemical denaturant dependence of methionine oxidation in proteins both in the presence and absence of a target ligand. The differential denaturant dependence to the oxidation reactions performed in the presence and absence of ligand provides a measure of the protein stability changes that occur as a result of direct interactions of proteins with the target ligand and/or as a result of indirect interactions involving other protein-ligand interactions that are either induced or disrupted by the ligand. The described protocol utilizes the 18O/16O ratio in the oxidized protein samples to quantify the ligand-induced protein stability changes. The ratio is determined using the isotopic distributions observed for the methionine-containing peptides used for protein identification in the LC-MS-based proteomics readout. The strategy is applied to a multi-component protein mixture in this proof-of-principle experiment, which was designed to evaluate the technique's ability to detect and quantify the direct binding interaction between cyclosporin A and cyclophilin A and to detect the indirect binding interaction between cyclosporin A and calcineurin (i.e., the protein-protein interaction between cyclophilin A and calcineurin that is induced by cyclosporin A binding to cyclophilin A).
Hong, Ban Zhen; Keong, Lau Kok; Shariff, Azmi Mohd
2016-05-01
The employment of different mathematical models to address specifically for the bubble nucleation rates of water vapour and dissolved air molecules is essential as the physics for them to form bubble nuclei is different. The available methods to calculate bubble nucleation rate in binary mixture such as density functional theory are complicated to be coupled along with computational fluid dynamics (CFD) approach. In addition, effect of dissolved gas concentration was neglected in most study for the prediction of bubble nucleation rates. The most probable bubble nucleation rate for the water vapour and dissolved air mixture in a 2D quasi-stable flow across a cavitating nozzle in current work was estimated via the statistical mean of all possible bubble nucleation rates of the mixture (different mole fractions of water vapour and dissolved air) and the corresponding number of molecules in critical cluster. Theoretically, the bubble nucleation rate is greatly dependent on components' mole fraction in a critical cluster. Hence, the dissolved gas concentration effect was included in current work. Besides, the possible bubble nucleation rates were predicted based on the calculated number of molecules required to form a critical cluster. The estimation of components' mole fraction in critical cluster for water vapour and dissolved air mixture was obtained by coupling the enhanced classical nucleation theory and CFD approach. In addition, the distribution of bubble nuclei of water vapour and dissolved air mixture could be predicted via the utilisation of population balance model.
Abramov, Y. V.; Tokmantsev, V. I.
2013-01-01
The separation of a binary gaseous mixture of uranium hexafluoride 238UF6 with different light components in a high-speed centrifuge, intended for separating heavy isotopes, is examined. The mass of the light impurities is varied in the range M 1 = 0.02-0.349 kg/mole. It is shown that as the impurity mass decreases the structure of the flow fields in the centrifuge rotor changes considerably. If in the case of a mixture of heavy isotopes convective transport has a determining effect on the co...
Hirota, Noriyuki; Chiba, Hayatoshi; Okada, Hidehiko; Ando, Tsutomu
2015-04-01
The magneto-Archimedes separation allows for separating mixtures of feeble magnetic materials into its components based on the difference of their densities and magnetic susceptibilities. So far, this technique was applied for the separation of relatively large particles of several millimeters in diameter. Here we apply this technique experimentally to the simultaneous quantitative analysis of multiple micrometer-sized particles in a fluid. It was confirmed that the magneto-Archimedes separation can be applied for the separation of mixture of microspheres larger than 20 μm. Further high performance separation efficiency is expected with the optimization of separation conditions including the control of the spatial distribution of the magnetic field.
Lennington, R. K.; Sorensen, C. T.; Heydorn, R. P.
1982-01-01
For the analysis of remotely sensed data, it is frequently necessary to design a classifier in order to locate a ground cover class of interest or to estimate the proportion of this ground cover class. Advantages of a mixture distribution formulation are discussed, and a description is presented of the results of estimating the proportion of small grains in ten Landsat data segments using the mixture model. It is found that the mixture model proportion estimates have a very low variance and coefficient of variation. The discussed investigation implies that the mixtures model is a viable method for determining the distributions of classes of interest in remote sensing problems and in estimating the proportions of these classes directly.
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.
Energy Technology Data Exchange (ETDEWEB)
Muppala, S.P.R.; Wen, J.X. [Faculty of Engineering, Kingston University, Friars Avenue, Roehampton Vale, London, SW15 3DW (United Kingdom); Nakahara, M. [Department of Engineering for Production and Environment, Ehime University 3, Bunkyo-cho, Matsuyama 790-8577 (Japan); Aluri, N.K. [Institut fuer Technische Verbrennung, Leibniz Universitaet Hannover Welfengarten 1 A, 30167 Hannover (Germany); Kido, H. [Kyushu Polytechnic College 1665-1, Shii, Kokuraminami-ku, Kitakyushu, 802-0985 790-8577 (Japan); Papalexandris, M.V. [Departement de Mecanique, Unite de Thermodynamique, Universite catholique de Louvain Place du Levant, 2; 1348 Louvain-la-Neuve (Belgium)
2009-11-15
In this paper, we present some experimental and analytical model results of two-component fuel mixtures of methane, propane and hydrogen. Experimentally obtained turbulent burning velocity S{sub T} for outwardly propagating spherical lean turbulent premixed flames is examined with an algebraic flame surface wrinkling reaction model using 1) mean local burning velocity, and 2) the critical chemical time scale from the leading edge model by Zel'dovich and Frank-Kamenetskii. Based on the latter approach, the time scale that characterizes the effects of preferential diffusion phenomenon in critically curved spherical flames is incorporated into the reaction model. For this, a proposed simple linear model is used for estimating the effective Lewis number of the two-component fuel (CH{sub 4}-H{sub 2} and C{sub 3}H{sub 8}-H{sub 2})/Air mixtures. In general, both approaches are effective ways in achieving qualitatively consistent S{sub T} trends for both mixtures. However, in the second approach, model predictions show large S{sub T} deviation especially at high turbulence. This may be attributed to the use of approximate values of activation temperature and for the use of the effective Lewis number of both mixtures based on the simple linear model. (author)
Asghari, E.; Ashassi-Sorkhabi, H.; Ahangari, M.; Bagheri, R.
2016-04-01
Factors such as inhibitor concentration, solution hydrodynamics, and temperature influence the performance of corrosion inhibitor mixtures. The simultaneous studying of the impact of different factors is a time- and cost-consuming process. The use of experimental design methods can be useful in minimizing the number of experiments and finding local optimized conditions for factors under the investigation. In the present work, the inhibition performance of a three-component inhibitor mixture against corrosion of St37 steel rotating disk electrode, RDE, was studied. The mixture was composed of citric acid, lanthanum(III) nitrate, and tetrabutylammonium perchlorate. In order to decrease the number of experiments, the L16 Taguchi orthogonal array was used. The "control factors" were the concentration of each component and the rotation rate of RDE and the "response factor" was the inhibition efficiency. The scanning electron microscopy and energy dispersive x-ray spectroscopy techniques verified the formation of islands of adsorbed citrate complexes with lanthanum ions and insoluble lanthanum(III) hydroxide. From the Taguchi analysis results the mixture of 0.50 mM lanthanum(III) nitrate, 0.50 mM citric acid, and 2.0 mM tetrabutylammonium perchlorate under the electrode rotation rate of 1000 rpm was found as optimum conditions.
International Nuclear Information System (INIS)
The magneto-Archimedes separation allows for separating mixtures of feeble magnetic materials into its components based on the difference of their densities and magnetic susceptibilities. So far, this technique was applied for the separation of relatively large particles of several millimeters in diameter. Here we apply this technique experimentally to the simultaneous quantitative analysis of multiple micrometer-sized particles in a fluid. It was confirmed that the magneto-Archimedes separation can be applied for the separation of mixture of microspheres larger than 20 μm. Further high performance separation efficiency is expected with the optimization of separation conditions including the control of the spatial distribution of the magnetic field. - Highlights: • The magneto-Archimedes separation is based on the magnetic levitation of materials. • It allows for separating mixtures into its components by the difference of properties. • The separation of mixture of spheres larger than 20 μm was confirmed experimentally. • It enables the simultaneous quantitative analysis of multiple particles
Energy Technology Data Exchange (ETDEWEB)
Hirota, Noriyuki, E-mail: hirota.noriyuki@nims.go.jp [Fine Particle Engineering Group, National Institute for Materials Science, 3-13 Sakura, Tsukuba (Japan); Chiba, Hayatoshi [Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa (Japan); Okada, Hidehiko [Fine Particle Engineering Group, National Institute for Materials Science, 3-13 Sakura, Tsukuba (Japan); Ando, Tsutomu [Department of Mechanical Engineering, Nihon University, 1-2-1 Izumicho, Narashino 275-8575 (Japan)
2015-04-15
The magneto-Archimedes separation allows for separating mixtures of feeble magnetic materials into its components based on the difference of their densities and magnetic susceptibilities. So far, this technique was applied for the separation of relatively large particles of several millimeters in diameter. Here we apply this technique experimentally to the simultaneous quantitative analysis of multiple micrometer-sized particles in a fluid. It was confirmed that the magneto-Archimedes separation can be applied for the separation of mixture of microspheres larger than 20 μm. Further high performance separation efficiency is expected with the optimization of separation conditions including the control of the spatial distribution of the magnetic field. - Highlights: • The magneto-Archimedes separation is based on the magnetic levitation of materials. • It allows for separating mixtures into its components by the difference of properties. • The separation of mixture of spheres larger than 20 μm was confirmed experimentally. • It enables the simultaneous quantitative analysis of multiple particles.
Sensory evaluation of character impact components in an apple model mixture
Bult, J.H.F.; Schifferstein, H.N.J.; Roozen, J.P.; Boronat, E.D.; Voragen, A.G.J.; Kroeze, J.H.A.
2002-01-01
Food aromas generally are complex mixtures of volatiles. In the present study, we investigated the joint effects of hexyl acetate, trans-2-hexenal and 1-hexanol on the multi-attribute perception of an apple aroma. The first two substances were identified earlier as positive contributors to the apple
Chi, Do Minh
2001-01-01
We advance a famous principle - causality principle - but under a new view. This principle is a principium automatically leading to most fundamental laws of the nature. It is the inner origin of variation, rules evolutionary processes of things, and the answer of the quest for ultimate theories of the Universe.
DEFF Research Database (Denmark)
Fettouhi, André; Thomsen, Kaj
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....
Energy Technology Data Exchange (ETDEWEB)
Patel, Sanjay V.; Jenkins, Mark W.; Hughes, Robert C.; Yelton, W. Graham; Ricco, Antonio J.
1999-07-19
We demonstrate a ''universal solvent sensor'' constructed from a small array of carbon/polymer composite chemiresistors that respond to solvents spanning a wide range of Hildebrand volubility parameters. Conductive carbon particles provide electrical continuity in these composite films. When the polymer matrix absorbs solvent vapors, the composite film swells, the average separation between carbon particles increases, and an increase in film resistance results, as some of the conduction pathways are broken. The adverse effects of contact resistance at high solvent concentrations are reported. Solvent vapors including isooctane, ethanol, dlisopropyhnethylphosphonate (DIMP), and water are correctly identified (''classified'') using three chemiresistors, their composite coatings chosen to span the full range of volubility parameters. With the same three sensors, binary mixtures of solvent vapor and water vapor are correctly classified, following classification, two sensors suffice to determine the concentrations of both vapor components. Polyethylene vinylacetate and polyvinyl alcohol (PVA) are two such polymers that are used to classify binary mixtures of DIMP with water vapor; the PVA/carbon-particle-composite films are sensitive to less than 0.25{degree}A relative humidity. The Sandia-developed VERI (Visual-Empirical Region of Influence) technique is used as a method of pattern recognition to classify the solvents and mixtures and to distinguish them from water vapor. In many cases, the response of a given composite sensing film to a binary mixture deviates significantly from the sum of the responses to the isolated vapor components at the same concentrations. While these nonlinearities pose significant difficulty for (primarily) linear methods such as principal components analysis, VERI handles both linear and nonlinear data with equal ease. In the present study the maximum speciation accuracy is achieved by an array
Volatility of components of saturated vapours of UCl4-CsCl and UCl4-LiCl molten mixtures
International Nuclear Information System (INIS)
The flow method has been used for measuring the volatility of the components from UCl4-CsCl and UCl4-LiCl melted mixtures containing 2.0, 5.0, 12.0, 25.0, 33.0, 50.0, 67.0, and 83.0 mol.% of UCl4 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 UCl4, LiCl, CsCl and Li2Cl2, Cs2Cl2 dimers of double compounds of the MeUCl5 most probable composition. Their absolute contribution into a total pressure above the UCl4-CsCl melted mixtures is considerably smaller than above the UCl4 -LiCl mixtures
Various formulations are used in horticultural potting media, with sphagnum peat moss, vermiculite and perlite currently among the most common components. We are examining a dried anaerobic digestate remaining after the fermentation of potato processing wastes to replace organic components such as p...
Isotropic-nematic phase equilibria of hard-sphere chain fluids-Pure components and binary mixtures.
Oyarzún, Bernardo; van Westen, Thijs; Vlugt, Thijs J H
2015-02-14
The isotropic-nematic phase equilibria of linear hard-sphere chains and binary mixtures of them are obtained from Monte Carlo simulations. In addition, the infinite dilution solubility of hard spheres in the coexisting isotropic and nematic phases is determined. Phase equilibria calculations are performed in an expanded formulation of the Gibbs ensemble. This method allows us to carry out an extensive simulation study on the phase equilibria of pure linear chains with a length of 7 to 20 beads (7-mer to 20-mer), and binary mixtures of an 8-mer with a 14-, a 16-, and a 19-mer. The effect of molecular flexibility on the isotropic-nematic phase equilibria is assessed on the 8-mer+19-mer mixture by allowing one and two fully flexible beads at the end of the longest molecule. Results for binary mixtures are compared with the theoretical predictions of van Westen et al. [J. Chem. Phys. 140, 034504 (2014)]. Excellent agreement between theory and simulations is observed. The infinite dilution solubility of hard spheres in the hard-sphere fluids is obtained by the Widom test-particle insertion method. As in our previous work, on pure linear hard-sphere chains [B. Oyarzún, T. van Westen, and T. J. H. Vlugt, J. Chem. Phys. 138, 204905 (2013)], a linear relationship between relative infinite dilution solubility (relative to that of hard spheres in a hard-sphere fluid) and packing fraction is found. It is observed that binary mixtures greatly increase the solubility difference between coexisting isotropic and nematic phases compared to pure components. PMID:25681939
Abed-Meraim K; Barkat B
2004-01-01
We propose novel algorithms to select and extract separately all the components, using the time-frequency distribution (TFD), of a given multicomponent frequency-modulated (FM) signal. These algorithms do not use any a priori information about the various components. However, their performances highly depend on the cross-terms suppression ability and high time-frequency resolution of the considered TFD. To illustrate the usefulness of the proposed algorithms, we applied them for the estimati...
Maltsev, Roman V
2013-01-01
A new approach to simulation of stationary flows by Direct Simulation Monte Carlo method is proposed. The idea is to specify an individual time step for each component of a gas mixture. The approach consists of modifications mainly to collision phase and recommendation on choosing time step ratios. It allows softening the demands on the computational resources for cases of disparate collision diameters of molecules and/or disparate molecular masses. These are the cases important in vacuum deposition technologies. Few tests of the new approach are made. Finally, the usage of new approach is demonstrated on a problem of silver nanocluster diffusion in carrier gas argon in conditions of silver deposition experiments.
Energy Technology Data Exchange (ETDEWEB)
Rautenbach, R.; Herion, C.; Janisch, I. (Technische Hochschule Aachen (Germany, F.R.). Lehrstuhl fuer Verfahrenstechnik 1 und Inst. fuer Verfahrenstechnik); Dahm, W. (Environ Consult Ingenieurgesellschaft, Aachen (Germany, F.R.))
1989-07-01
The maximum demand that can be placed on development of processes for removal of contaminants from waste water and waste gases is that the separated substances can be recovered for use. In this context, membrane processes are attracting steadily increasing interest because the separated substances are changed neither chemically, nor biologically, nor thermally. Two examples, in which solvent mixtures are recovered from waste water and waste gases by means of reverse osmosis, pervaporation, and gas permeation, are cited to demonstrate the potential of the method. The examles, are preceded by a joint consideration of the three above-mentioned membrane processes, which all use so-called pore-free solution-diffusion membranes. The limitations, which result from practical limits of the driving force and the respective resistances to transport are discussed in detail. (orig.).
Directory of Open Access Journals (Sweden)
B. Barkat
2004-10-01
Full Text Available We propose novel algorithms to select and extract separately all the components, using the time-frequency distribution (TFD, of a given multicomponent frequency-modulated (FM signal. These algorithms do not use any a priori information about the various components. However, their performances highly depend on the cross-terms suppression ability and high time-frequency resolution of the considered TFD. To illustrate the usefulness of the proposed algorithms, we applied them for the estimation of the instantaneous frequency coefficients of a multicomponent signal and the results are compared with those of the higher-order ambiguity function (HAF algorithm. Monte Carlo simulation results show the superiority of the proposed algorithms over the HAF.
Barkat, B.; Abed-Meraim, K.
2004-12-01
We propose novel algorithms to select and extract separately all the components, using the time-frequency distribution (TFD), of a given multicomponent frequency-modulated (FM) signal. These algorithms do not use any a priori information about the various components. However, their performances highly depend on the cross-terms suppression ability and high time-frequency resolution of the considered TFD. To illustrate the usefulness of the proposed algorithms, we applied them for the estimation of the instantaneous frequency coefficients of a multicomponent signal and the results are compared with those of the higher-order ambiguity function (HAF) algorithm. Monte Carlo simulation results show the superiority of the proposed algorithms over the HAF.
Riemann solvers for multi-component gas mixtures with temperature dependent heat capacities
International Nuclear Information System (INIS)
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)
New method for obtaining individual component spectra from those of complex mixtures
International Nuclear Information System (INIS)
In near-infrared reflectance analysis (NIRA), a computer is trained to recognize and quanitative the relationship between the near-infrared spectrum of a sample and the concentrations of one or more of the sample constituents. During this training process the computer implicitly generates the spectrum of the constituents in question, although this spectrum is ordinarily not available for operator inspection. In the present study, a method for displaying this implicit information is developed and evaluated. The resulting ''reconstructed spectrum'' can be of a specific chemical constituent in a sample or can be a composite spectrum of those components that collectively contribute to specific sample properties such as material strength or processing temperature, or to sensory characteristics such as the ''hotness'' of peppers. A comparison is made of this new spectral reconstruction to technique to established methods such as spectral stripping and factor analysis
Evaporation of multi-component mixtures and shell formation in spray dried droplets
Valente, Pedro; Duarte, Íris; Porfirio, Tiago; Temtem, Márcio
2015-11-01
Drug particles where the active pharmaceutical ingredient (APIs) is dispersed in a polymer matrix forming an amorphous solid dispersion (ASD) is a commonly used strategy to increase the solubility and dissolution rate of poorly water soluble APIs. However, the formation and stability of an amorphous solid dispersion depends on the polymer/API combination and process conditions to generate it. The focus of the present work is to further develop a numerical tool to predict the formation of ASDs by spray drying solutions of different polymer/API combinations. Specifically, the evaporation of a multi-component droplet is coupled with a diffusion law within the droplet that minimizes the Gibbs free energy of the polymer/API/solvents system, following the Flory-Huggins model. Prior to the shell formation, the evaporation of the solvents is modelled following the simplified approach proposed by Abramzon & Sirignano (1989) which accounts for the varying relative velocity between the droplet and the drying gas. After shell formation, the diffusion of the solvents across the porous shell starkly modifies the evaporative dynamics.
Use of two-component Weibull mixtures in the analysis of wind speed in the Eastern Mediterranean
Energy Technology Data Exchange (ETDEWEB)
Akdag, S.A. [Istanbul Technical University, Energy Institute, Ayazaga Campus, Maslak, Istanbul (Turkey); Bagiorgas, H.S.; Mihalakakou, G. [Department of Environmental and Natural Resources Management, University of Ioannina, 2 G. Sepheri Str., 30100 Agrinio (Greece)
2010-08-15
The statistical characteristics of wind speed data recorded at nine buoys, located in Ionian and Aegean Sea (Eastern Mediterranean) are analyzed in this paper, in order to present a more accurate method for estimation of wind speed characteristics, according to the suitability of the probability distribution functions (pdf). This article has focussed on wind regimes that present nearly zero percentages of null wind speeds. The selected distributions for examination are the typical two-parameter Weibull wind speed distribution (W-pdf) and the two-component mixture Weibull distribution (WW-pdf), involving five parameters (two shape parameters, two scale parameters, and one proportionality parameter). Suitable software, based on the maximum likelihood method, is used in order to estimate the aforementioned two-parameters of the typical W-pdf and the five parameters of the mixed WW-pdf. The suitability of the aforementioned distributions is judged from the coefficient of determination (R{sup 2}) and the fit standard error (RMSE) tests, which had been carried out between each one of the theoretical distributions and the corresponding experimental cumulative frequencies of the nine selected sites. From these tests it is clear that, in most cases (six experimental stations - having either unimodal or bimodal frequency distributions), mixed-Weibull distribution provides the highest degree of fit. In the other three cases, the mixing weight p of the two-component mixed Weibull density function equals to zero (p = 0), so the mixed-Weibull distribution is been transformed to the typical Simple-Weibull distribution. Hence, the general conclusion is that the aforementioned mixture of two Weibull distributions is more suitable for the description of such wind conditions and could offer less relative errors in determining the annual mean wind power density. (author)
Insel, Aysu; Soytaş, Mehmet Ali; Gündüz, Seda
2004-01-01
The purpose of this paper is the determination of sources and pattern of business cycle in Turkey throughout the period 1988-2002 using quarterly data. The question of the paper is Has financial liberalization increased the fragility of the financial and real sides of the Turkish economy? The quantitative analysis of the paper includes the cross correlation and causality analysis. Financial development indicators are the bank credits and capital flows, efficiency indicators are the domestic...
Adjei, A A; Yamauchi, K.; Chan, Y. C.; Konishi, M; Yamamoto, S.
1996-01-01
BACKGROUND--Nucleoside-nucleotide mixture has been shown to improve gut morphology and reduce the incidence of bacterial translocation in protein deficient mice. AIMS--To compare the reparative effect of nucleoside-nucleotide mixture and their individual components on maintenance of gut integrity and bacterial translocation based on their differential metabolism and utilisation. METHODS--ICR (CD-1) mice were randomised into eight groups of 10 animals each and fed 20% casein diet (control), pr...
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
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%.
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.
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.
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).
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...
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.
Jong, Sung-Ho; Sin, Kye-Ryong
2016-01-01
The second-order statistics (SOS) can be applied in estimation of the pure spectra of chemical components from the spectrum of their mixture, when SOS seems to be good at estimation of spectral patterns, but their peak directions are opposite in some cases. In this paper, one method for judgment of the peak direction of the pure spectra was proposed, where the base line of the pure spectra was drawn by using their histograms and the peak directions were chosen so as to make all of the pure spectra located upwards over the base line. Results of the SOS analysis on the visible hyperspectral images of the mixture composed of two or three chemical components showed that the present method offered the reasonable shape and direction of the pure spectra of its components.
International Nuclear Information System (INIS)
The paper presents a one-dimensional transient mathematical model of compressible thermal multi-component gas mixture flow in a shock tube. The set of mass, momentum and enthalpy conservation equations is solved for the gas phase. Thermo-physical properties of multi-component natural gas mixture are calculated by solving the Equation of State (EOS) in the form of the Soave-Redlich-Kwong (SRK-EOS) model. The proposed mathematical model is validated against the experiments where the decompression wave speed in dry natural gases was measured at low temperatures and shows a good agreement with the experimental data at high and low initial pressure. The effect of the initial temperature on rapid decompression process is investigated numerically using the proposed model. Numerical results show that the proposed model simulates the decompression in natural gases much better and accurate than other models, and shows a great potential because it can be extended on the case of gas–liquid two-phase flow in a shock tube. Highlights: ► 1D transient mathematical model of thermal multi-component gas mixture pipe flows is developed. ► The model is validated on the experiments on RGD in dry natural gases. ► Numerical analysis on RGD in dry natural gas mixtures is performed. ► Predictions fit to the experiments much better than any other models
The Equation of a State of Biogas (Mixture CH4 and CO2) for the Different Compositions Components
International Nuclear Information System (INIS)
The equation of a state of biogas (mixture CH4 and CO2) is offered. The application of the equation Benedict-Webb-Rubin (BWR) for a mixture CH4+CO2 in an interval of temperatures 10...250 degree C and pressure up to 100 atm is proved. For the concentration 20, 40, 60 and 80 % in the specified interval of pressure and temperatures are constructed isotherms, isohors and isoplets of biogas. A rejection of pressure from pressure of an ideal mixture Δ P (T, V) =P-Pid has negative value, that testifies to a primary attraction between molecules in the specified interval of temperatures. The received results can be used for construction of the tables of help given thermodynamic values for a mixture of various compositions
DEFF Research Database (Denmark)
Bordacconi, Mats Joe; Larsen, Martin Vinæs
2014-01-01
Humans are fundamentally primed for making causal attributions based on correlations. This implies that researchers must be careful to present their results in a manner that inhibits unwarranted causal attribution. In this paper, we present the results of an experiment that suggests regression...... models should note carefully both their models’ identifying assumptions and which causal attributions can safely be concluded from their analysis....
Chi, Do Minh
1999-01-01
We research the natural causality of the Universe. We find that the equation of causality provides very good results on physics. That is our first endeavour and success in describing a quantitative expression of the law of causality. Hence, our theoretical point suggests ideas to build other laws including the law of the Universe's evolution.
International Nuclear Information System (INIS)
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)
Lopes, J N Canongia; Gomes, Margarida F Costa; Husson, Pascale; Pádua, Agílio A H; Rebelo, Luis Paulo N; Sarraute, Sabine; Tariq, Mohammad
2011-05-19
In this study, we have focused on binary mixtures composed of 1-butyl-3-methylimidazolium bis(trifluoromethanesulfonyl)-imide, [C(4)C(1)im][Ntf(2)], and a selection of six molecular components (acetonitrile, dichloromethane, methanol, 1-butanol, t-butanol, and water) varying in polarity, size, and isomerism. Two Kamlet-Taft parameters, the polarizability π* and the hydrogen bond acceptor β coefficient were determined by spectroscopic measurements. In most cases, the solvent power (dipolarity/polarizability) of the ionic liquid is only slightly modified by the presence of the molecular component unless large quantities of this component are present. The viscosity and electrical conductivity of these mixtures were measured as a function of composition and the relationship between these two properties were studied through Walden plot curves. The viscosity of the ionic liquid dramatically decreases with the addition of the molecular component. This decrease is not directly related to the volumetric properties of each mixture or its interactions. The conductivity presents a maximum as a function of the composition and, except for the case of water, the conductivity maxima decrease for more viscous systems. The Walden plots indicate enhanced ionic association as the ionic liquid gets more diluted, a situation that is the inverse of that usually found for conventional electrolyte solutions. PMID:21517046
International Nuclear Information System (INIS)
A short-wave radiation model applied to well-mixed canopies including two species [Festuca arundinacea and Trifolium repens] is developed. It simulates the complete radiative balance of the mixture from input parameters as simple as possible: the crop is characterized by the LAI, the mean leaf inclination and the leaf optical properties of each component. Additional parameters are the soil reflectance and the incident radiation description. The model is applied to a white clover-tall fescue mixture as a test case. Since no device is available for the measurement of the light absorbed by each component of a mixed canopy, only partial or indirect evidence can be used as a test set. Measured and simulated interception efficiencies for the two species as a pure stand and for the mixed crop (considered as a whole) are in good agreement (partial direct validation). Additionally, the comparison for each species between the conversion efficiencies measured in pure stand and simulated in mixture is consistent with our current knowledge about these crops (indirect validation). Finally this model should provide the crop physiologist with a tool based on a simple canopy structure description and therefore easy to use for the analysis of the light competition in well-mixed canopies. To complete this tool, a simple analytical equation is proposed to describe the relation between the interception efficiency of a component as a function of the LAI of both species
Granger causality in wall-bounded turbulence
International Nuclear Information System (INIS)
Granger causality is based on the idea that if a variable helps to predict another one, then they are probably involved in a causality relationship. This technique is based on the identification of a predictive model for causality detection. The aim of this paper is to use Granger causality to study the dynamics and the energy redistribution between scales and components in wall-bounded turbulent flows. In order to apply it on flows, Granger causality is generalized for snapshot-based observations of large size using linear-model identification methods coming from model reduction. Optimized DMD, a variant of the Dynamic Mode Decomposition, is considered for building a linear model based on snapshots. This method is used to link physical events and extract physical mechanisms associated to the bursting process in the logarithmic layer of a turbulent channel flow.
Davidson, Russell
2013-01-01
The understanding of causal chains and mechanisms is an essential part of any scientific activity that aims at better explanation of its subject matter, and better understanding of it. While any account of causality requires that a cause should precede its effect, accounts of causality inphysics are complicated by the fact that the role of time in current theoretical physics has evolved very substantially throughout the twentieth century. In this article, I review the status of time and causa...
International Nuclear Information System (INIS)
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
Causality in Europeanization Research
DEFF Research Database (Denmark)
Lynggaard, Kennet
2012-01-01
Discourse analysis as a methodology is perhaps not readily associated with substantive causality claims. At the same time the study of discourses is very much the study of conceptions of causal relations among a set, or sets, of agents. Within Europeanization research we have seen endeavours to......, 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...
International Nuclear Information System (INIS)
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)
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…
Separation of the components of the TBP-H2 MBP-HDBP-H3PO4 mixture
International Nuclear Information System (INIS)
Several schemes for the separation of dibutylphosphoric acid (HDBP), monobutylphosphoric acid (H2MBP) and orthophosphoric acid (H3PO4) as hydrolytic and radiolytic degradation products from tri-n-butylphosphate (TBP) were studied. For the resolution of a HDBP, H2MPB and H3PO4 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)
DEFF Research Database (Denmark)
Nielsen, Max; Jensen, Frank; Setälä, Jari;
2011-01-01
to fish demand. On the German market for farmed trout and substitutes, it is found that supply sources, i.e. aquaculture and fishery, are not the only determinant of causality. Storing, tightness of management and aggregation level of integrated markets might also be important. The methodological......This article focuses on causality in demand. A methodology where causality is imposed and tested within an empirical co-integrated demand model, not prespecified, is suggested. The methodology allows different causality of different products within the same demand system. The methodology is applied...... implication is that more explicit focus on causality in demand analyses provides improved information. The results suggest that frozen trout forms part of a large European whitefish market, where prices of fresh trout are formed on a relatively separate market. Redfish is a substitute on both markets. The...
Causality and Composite Structure
Joglekar, Satish D
2007-01-01
We study the question of whether a composite structure of elementary particles, with a length scale $1/\\Lambda$, can leave observable effects of non-locality and causality violation at higher energies (but $\\lesssim \\Lambda$). We formulate a model-independent approach based on Bogoliubov-Shirkov formulation of causality. We analyze the relation between the fundamental theory (of finer constituents) and the derived theory (of composite particles). We assume that the fundamental theory is causal and formulate a condition which must be fulfilled for the derived theory to be causal. We analyze the condition and exhibit possibilities which fulfil and which violate the condition. We make comments on how causality violating amplitudes can arise.
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.
Jong, Sung-Ho; Ri, Yong-U; Sin, Kye-Ryong
2016-01-01
The second-order statistics (SOS) can be applied in estimation of the pure spectra of chemical components from the spectrum of their mixture, when SOS seems to be good at estimation of spectral patterns, but their peak directions are opposite in some cases. In this paper, one method for judgment of the peak direction of the pure spectra was proposed, where the base line of the pure spectra was drawn by using their histograms and the peak directions were chosen so as to make all of the pure sp...
Institute of Scientific and Technical Information of China (English)
P. K. Paul; Md. N. Islam; D. Bhattacharjee; S. A. Hussain
2007-01-01
We report the miscibility characteristics of two components in a binary mixture of 9-phenyl anthracene (PA) mixed with stearic acid (SA) or polymethyl methacrylate (PMMA). The behaviour of surface pressure versus area per molecule isotherms reveal that the area per molecule decreases systematically with increasing molefractions of PA. The characteristics of areas per molecule versus molefractions and collapse pressure vs molefraction indicate that various interactions involved among the sample and matrix molecules. The interaction scheme is found to change with the change in surface pressure and molefraction of mixing. Scanning electron microscopic study confirms the aggregation of PA molecules in the mixed films.
Ackerman, David G; Feigenson, Gerald W
2016-05-01
We used coarse-grained molecular dynamics simulations to examine the effects of transmembrane α-helical WALP peptides on the behavior of four-component lipid mixtures. These mixtures contain a high-melting temperature (high-Tm) lipid, a nanodomain-inducing low-Tm lipid, a macrodomain-inducing low-Tm lipid and cholesterol to model the outer leaflet of cell plasma membranes. In a series of simulations, we incrementally replace the nanodomain-inducing low-Tm lipid by the macrodomain-inducing low-Tm lipid and measure how lipid and phase properties are altered by the addition of WALPs of different length. Regardless of the ratio of the two low-Tm lipids, shorter WALPs increase domain size and all WALPs increase domain alignment between the two leaflets. These effects are smallest for the longest WALP tested, and increase with increasing WALP concentration. Thus, our simulations explain the experimental observation that WALPs induce macroscopic domains in otherwise nanodomain-forming lipid-only mixtures (unpublished). Since the cell plasma membrane contains a large fraction of transmembrane proteins, these findings link the behavior of lipid-only model membranes in vitro to phase behavior in vivo. PMID:27081858
Goracci, G.; Arbe, A.; Alegría, A.; Su, Y.; Gasser, U.; Colmenero, J.
2016-04-01
We have combined X-ray diffraction, neutron diffraction with polarization analysis, small angle neutron scattering, differential scanning calorimetry, and broad band dielectric spectroscopy to investigate the structure and dynamics of binary mixtures of poly(2-(dimethylamino)ethyl methacrylate) with either water or tetrahydrofuran (THF) at different concentrations. Aqueous mixtures are characterized by a highly heterogeneous structure where water clusters coexist with an underlying nano-segregation of main chains and side groups of the polymeric matrix. THF molecules are homogeneously distributed among the polymeric nano-domains for concentrations of one THF molecule/monomer or lower. A more heterogeneous situation is found for higher THF amounts, but without evidences for solvent clusters. In THF-mixtures, we observe a remarkable reduction of the glass-transition temperature which is enhanced with increasing amount of solvent but seems to reach saturation at high THF concentrations. Adding THF markedly reduces the activation energy of the polymer β-relaxation. The presence of THF molecules seemingly hinders a slow component of this process which is active in the dry state. The aqueous mixtures present a strikingly broad glass-transition feature, revealing a highly heterogeneous behavior in agreement with the structural study. Regarding the solvent dynamics, deep in the glassy state all data can be described by an Arrhenius temperature dependence with a rather similar activation energy. However, the values of the characteristic times are about three orders of magnitude smaller for THF than for water. Water dynamics display a crossover toward increasingly higher apparent activation energies in the region of the onset of the glass transition, supporting its interpretation as a consequence of the freezing of the structural relaxation of the surrounding matrix. The absence of such a crossover (at least in the wide dynamic window here accessed) in THF is attributed to
Fidorra, M; Seeger, H M
2007-01-01
Monte Carlo (MC) Simulations, Differential Scanning Calorimetry (DSC) and Fourier Transform InfraRed (FTIR) spectroscopy were used to study the melting behavior of single lipid components in two-component membranes of 1,2-Dimyristoyl-D54-sn-Glycero-3-Phosphocholine (DMPC-d54) and 1,2-Distearoyl-sn-Glycero-3-Phosphocholine (DSPC). Microscopic information on the temperature dependent melting of the single lipid species could be investigated using FTIR. The microscopic behavior measured could be well described by the results from the MC simulations. These simulations also allowed to calculate heat capacity profiles as determined with DSC. These ones provide macroscopic information about melting enthalpies and entropy changes which are not accessible with FTIR. Therefore, the MC simulations allowed us to link the two different experimental approaches of FTIR and DSC.
International Nuclear Information System (INIS)
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
Dynamics and causality constraints
International Nuclear Information System (INIS)
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)
Dynamics and causality constraints
De Souza, M M
2000-01-01
The physical meaning and the geometrical interpretation of causality implementation in classical field theories are discussed. Local causality are kinematical constraints dynamically implemented via solutions of the field equations, 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 and implies on deep implications to the nature of physical interactions.
Arrighi, Pablo
2016-01-01
Consider a graph having quantum systems lying at each node. Suppose that the whole thing evolves in discrete time steps, according to a global, unitary causal operator. By causal we mean that information can only propagate at a bounded speed, with respect to the distance given by the graph. Suppose, moreover, that the graph itself is subject to the evolution, and may be driven to be in a quantum superposition of graphs---in accordance to the superposition principle. We show that these unitary causal operators must decompose as a finite-depth circuit of local unitary gates. This unifies a result on Quantum Cellular Automata with another on Reversible Causal Graph Dynamics. Along the way we formalize a notion of causality which is valid in the context of quantum superpositions of time-varying graphs, and has a number of good properties. Keywords: Quantum Lattice Gas Automata, Block-representation, Curtis-Hedlund-Lyndon, No-signalling, Localizability, Quantum Gravity, Quantum Graphity, Causal Dynamical Triangula...
Causal Inference and Causal Explanation with Background Knowledge
Meek, Christopher
2013-01-01
This paper presents correct algorithms for answering the following two questions; (i) Does there exist a causal explanation consistent with a set of background knowledge which explains all of the observed independence facts in a sample? (ii) Given that there is such a causal explanation what are the causal relationships common to every such causal explanation?
Khadka, Nawal K; Ho, Chian Sing; Pan, Jianjun
2015-11-17
Much of lipid raft properties can be inferred from phase behavior of multicomponent lipid membranes. We use liquid compatible atomic force microscopy (AFM) to study a three-component system composed of 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC), egg sphingomyelin (eSM), and cholesterol. Specifically, we obtain macroscopic and nanoscopic heterogeneous structures in a broad compositional space of DOPC/eSM/cholesterol (23 °C). In the macroscopic liquid coexisting region, we quantify area fraction of the coexisting phases and determine a set of thermodynamic tie-lines. When lipid compositions are near the critical point, we obtain fluctuation-like nanoscopic structures. We also use AFM height images to explore the hypothetical three-phase coexisting region. Finally, we use fluorescence microscopy to compare the phase behavior from our AFM measurements to that in free-floating giant unilamellar vesicles (GUVs). Our results highlight the role of lipid composition in mediating lipid domain formation and stability. PMID:26506226
Shao, Jingwei; Zhou, Suxia; Jiang, Zhou; Chi, Ting; Ma, Ji; Kuo, Minliang; Lee, Alan Yueh-Luen; Jia, Lee
2016-01-01
We recently defined cancer metastatic chemoprevention as utilizing safe and effective molecules to comprehensively prevent the spark of activation-adhesion-extravasation-proliferation metastatic cascade caused by circulating tumor cells (CTCs). The strategy focuses on preventing the most important starting point of the cascade. We identified an extract from a well-known medical plant Murraya paniculata, which inhibited both embryonic implantation to human endometrium as traditionally-used for abortion and CTC adhesion to human endothelium. Here, we separated and characterized five coumarin-containing components (Z1-Z5) from the botanic extract. Flow cytometry revealed that within 1-100 μg/mL, Z3 and Z5 down-regulated EpCAM expression in human colon HCT116, whereas, Z1 and Z2 did oppositely. Warfarin and Z1-Z5 component mixture (CM) also down-regulated EpCAM expression. The down-regulation of EpCAM by Z3, Z5, CM and warfarin was confirmed by western blotting, and caused inhibition on adhesion of cancer cells to human endothelial cells. Rat coagulation study showed that warfarin prolonged prothrombin time, whereas, Z3 did not. The present studies revealed that, for the first time, warfarin and coumarin-like components Z3, Z5 and CM from Murraya paniculata could directly inhibit EpCAM-mediated cell-cell adhesion. PMID:27480614
Causality and the Doppler Peaks
Turok, Neil
1996-01-01
Could cosmic structure have formed by the action of causal physics within the standard hot big bang, or was a prior period of inflation required? Recently there has been some discussion of whether causal sources could reproduce the pattern of Doppler peaks of the standard scale-invariant adiabatic theory. This paper gives a rigorous definition of causality, and a causal decomposition of a general source. I present an example of a simple causal source which mimics the standard adiabatic theory...
Rideout, D
2002-01-01
The Causal Set approach to quantum gravity asserts that spacetime, at its smallest length scale, has a discrete structure. This discrete structure takes the form of a locally finite order relation, where the order, corresponding with the macroscopic notion of spacetime causality, is taken to be a fundamental aspect of nature. After an introduction to the Causal Set approach, this thesis considers a simple toy dynamics for causal sets. Numerical simulations of the model provide evidence for the existence of a continuum limit. While studying this toy dynamics, a picture arises of how the dynamics can be generalized in such a way that the theory could hope to produce more physically realistic causal sets. By thinking in terms of a stochastic growth process, and positing some fundamental principles, we are led almost uniquely to a family of dynamical laws (stochastic processes) parameterized by a countable sequence of coupling constants. This result is quite promising in that we now know how to speak of dynamics ...
Rideout, D P
2001-01-01
The Causal Set approach to quantum gravity asserts that spacetime, at its smallest length scale, has a discrete structure. This discrete structure takes the form of a locally finite order relation, where the order, corresponding with the macroscopic notion of spacetime causality, is taken to be a fundamental aspect of nature. After an introduction to the Causal Set approach, this thesis considers a simple toy dynamics for causal sets. Numerical simulations of the model provide evidence for the existence of a continuum limit. While studying this toy dynamics, a picture arises of how the dynamics can be generalized in such a way that the theory could hope to produce more physically realistic causal sets. By thinking in terms of a stochastic growth process, and positing some fundamental principles, we are led almost uniquely to a family of dynamical laws (stochastic processes) parameterized by a countable sequence of coupling constants. This result is quite promising in that we now know how to speak of dynamics ...
Biased causal inseparable game
Bhattacharya, Some Sankar
2015-01-01
Here we study the \\emph{causal inseparable} game introduced in [\\href{http://www.nature.com/ncomms/journal/v3/n10/full/ncomms2076.html}{Nat. Commun. {\\bf3}, 1092 (2012)}], but it's biased version. Two separated parties, Alice and Bob, generate biased bits (say input bit) in their respective local laboratories. Bob generates another biased bit (say decision bit) which determines their goal: whether Alice has to guess Bob's bit or vice-verse. Under the assumption that events are ordered with respect to some global causal relation, we show that the success probability of this biased causal game is upper bounded, giving rise to \\emph{biased causal inequality} (BCI). In the \\emph{process matrix} formalism, which is locally in agreement with quantum physics but assume no global causal order, we show that there exist \\emph{inseparable} process matrices that violate the BCI for arbitrary bias in the decision bit. In such scenario we also derive the maximal violation of the BCI under local operations involving tracele...
Harris, Herbert B.; Duffy, Robert T.; Erwin, Robert D., Jr.
1945-01-01
A continuous 50-hour test was conducted to determine the effect of maximum cruise-power operation at ultra-lean fuel-air mixture and increased spark advance on the mechanical conditions of cylinder components. The test was conducted on a nine-cylinder air-cooled radial engine at the following conditions:brake horsepower, 750; engine speed, 1900 rpm; brake mean effective pressure, 172 pounds per square inch; fuel-air ratio, 0.052; spark advance, 30 deg B.T.C.; and maximum rear-spark-plug-bushing temperature, 400 F. In addition to the data on corrosion and wear, data are presented and briefly discussed on the effect of engine operation at the conditions of this test on economy, knock, preignition, and mixture distribution. Cylinder, piston, and piston-ring wear was small and all cylinder component were in good condition at the conclusion of the 50-hour test except that all exhaust-valve guides were bellmouthed beyond the Army's specified limit and one exhaust-valve face was lightly burned. It is improbable that the light burning in one spot of the valve face would have progressed further because the burn was filled with a hard deposit so that the valve face formed an unbroken seal and the mating seat showed no evidence of burning. The bellmouthing of the exhaust-valve guides is believed to have been a result of the heavy carbon and lead-oxide deposits, which were present on the head end of the guided length of the exhaust-valve stem. Engine operational the conditions of this test was shown to result In a fuel saving of 16.8 percent on a cooled-power basis as compared with operation at the conditions recommended for this engine by the Army Air Forces for the same power.
International Nuclear Information System (INIS)
We discuss the geometry of trees endowed with a causal structure using the conventional framework of equilibrium statistical mechanics. We show how this ensemble is related to popular growing network models. In particular we demonstrate that on a class of afine attachment kernels the two models are identical but they can differ substantially for other choice of weights. We show that causal trees exhibit condensation even for asymptotically linear kernels. We derive general formulae describing the degree distribution, the ancestor--descendant correlation and the probability that a randomly chosen node lives at a given geodesic distance from the root. It is shown that the Hausdorff dimension dH of the causal networks is generically infinite. (author)
Bialas, Piotr
2003-10-01
We discuss the geometry of trees endowed with a causal structure using the conventional framework of equilibrium statistical mechanics. We show how this ensemble is related to popular growing network models. In particular we demonstrate that on a class of afine attachment kernels the two models are identical but they can differ substantially for other choice of weights. We show that causal trees exhibit condensation even for asymptotically linear kernels. We derive general formulae describing the degree distribution, the ancestor--descendant correlation and the probability that a randomly chosen node lives at a given geodesic distance from the root. It is shown that the Hausdorff dimension dH of the causal networks is generically infinite.
Arrighi, Pablo
2012-01-01
We generalize the theory of Cellular Automata to arbitrary, time-varying graphs. In other words we formalize, and prove theorems about, the intuitive idea of a labelled graph which evolves in time - but under the natural constraint that information can only ever be transmitted at a bounded speed, with respect to the distance given by the graph. The notion of translation-invariance is also generalized. The definition we provide for these `causal graph dynamics' is simple and axiomatic. The theorems we provide also show that it is robust. For instance, causal graph dynamics are stable under composition and under restriction to radius one. In the finite case some fundamental facts of Cellular Automata theory carry through: causal graph dynamics admit a characterization as continuous functions and they are stable under inversion. The provided examples suggest a wide range of applications of this mathematical object, from complex systems science to theoretical physics. Keywords: Dynamical networks, Boolean network...
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.
Brustein, Ram
2000-01-01
The identification of a causal-connection scale motivates us to propose a new covariant bound on entropy within a generic space-like region. This "causal entropy bound", scaling as the square root of EV, and thus lying around the geometric mean of Bekenstein's S/ER and holographic S/A bounds, is checked in various "critical" situations. In the case of limited gravity, Bekenstein's bound is the strongest while naive holography is the weakest. In the case of strong gravity, our bound and Bousso's holographic bound are stronger than Bekenstein's, while naive holography is too tight, and hence typically wrong.
Brustein, R; Veneziano, G
1999-01-01
The identification of a causal-connection scale motivates us to propose a new covariant bound on entropy within a generic space-like region. This "causal entropy bound", scaling as the square root of EV, and thus lying around the geometric mean of Bekenstein's S/ER and holographic S/A bounds, is checked in various "critical" situations. In the case of limited gravity, Bekenstein's bound is the strongest while naive holography is the weakest. In the case of strong gravity, our bound and Bousso...
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
Tachyon Kinematics and causality
International Nuclear Information System (INIS)
The chronological order of the events along a space-like path is not invariant under Lorentz transformations, as wellknown. This led to an early conviction that tachyons would give rise to causal anomalies. A relativistic version of the Stuckelberg-Feynman switching procedure (SWP) has been invoked as the suitable tool to eliminate those anomalies. The application of the SWP does eliminate the motions backwards in time, but interchanges the roles of source and dector. This fact triggered the proposal of a host of causal paradoxes. Till now, however, it has not been recognized that such paradoxes can be sensibly discussed (and completely solved, at least in microphysics) only after having properly developed the tachyon relativistic mechanics. We start by showing how to apply the SWP, both in the case of ordiry Special Relativity, and in the case with tachyons. Then, we carefully exploit the kinematics of the tachyon-exchange between to (ordinary) bodies. Being finally able to tackle the tachyon-causality problem, we successively solve the paradoxes: (i) by Tolman-Regge; (ii) by Pirani; (iii) by Edmonds; (iv) by Bell. At last, we discuss a further, new paradox associated with the transmission of signals by modulated tachyon beams
Liang, X San
2014-01-01
Given two time series, can one tell, in a rigorous and quantitative way, the cause and effect between them? Based on a recently rigorized physical notion namely information flow, we arrive at a concise formula and give this challenging question, which is of wide concern in different disciplines, a positive answer. Here causality is measured by the time rate of change of information flowing from one series, say, X2, to another, X1. The measure is asymmetric between the two parties and, particularly, if the process underlying X1 does not depend on X2, then the resulting causality from X2 to X1 vanishes. The formula is tight in form, involving only the commonly used statistics, sample covariances. It has been validated with touchstone series purportedly generated with one-way causality. It has also been applied to the investigation of real world problems; an example presented here is the cause-effect relation between two climate modes, El Ni\\~no and Indian Ocean Dipole, which have been linked to the hazards in f...
Causality in physiological signals.
Müller, Andreas; Kraemer, Jan F; Penzel, Thomas; Bonnemeier, Hendrik; Kurths, Jürgen; Wessel, Niels
2016-05-01
Health is one of the most important non-material assets and thus also has an enormous influence on material values, since treating and preventing diseases is expensive. The number one cause of death worldwide today originates in cardiovascular diseases. For these reasons the aim of understanding the functions and the interactions of the cardiovascular system is and has been a major research topic throughout various disciplines for more than a hundred years. The purpose of most of today's research is to get as much information as possible with the lowest possible effort and the least discomfort for the subject or patient, e.g. via non-invasive measurements. A family of tools whose importance has been growing during the last years is known under the headline of coupling measures. The rationale for this kind of analysis is to identify the structure of interactions in a system of multiple components. Important information lies for example in the coupling direction, the coupling strength, and occurring time lags. In this work, we will, after a brief general introduction covering the development of cardiovascular time series analysis, introduce, explain and review some of the most important coupling measures and classify them according to their origin and capabilities in the light of physiological analyses. We will begin with classical correlation measures, go via Granger-causality-based tools, entropy-based techniques (e.g. momentary information transfer), nonlinear prediction measures (e.g. mutual prediction) to symbolic dynamics (e.g. symbolic coupling traces). All these methods have contributed important insights into physiological interactions like cardiorespiratory coupling, neuro-cardio-coupling and many more. Furthermore, we will cover tools to detect and analyze synchronization and coordination (e.g. synchrogram and coordigram). As a last point we will address time dependent couplings as identified using a recent approach employing ensembles of time series. The
Energy Technology Data Exchange (ETDEWEB)
Ermler, Sibylle; Scholze, Martin; Kortenkamp, Andreas, E-mail: andreas.kortenkamp@brunel.ac.uk
2011-12-15
The risks associated with human exposures to chemicals capable of antagonising the effects of endogenous androgens have attracted considerable recent interest. Exposure is typically to large numbers of chemicals with androgen receptor (AR) antagonist activity, yet there is limited evidence of the combined effects of multi-component mixtures of these chemicals. A few in vitro studies with mixtures of up to six AR antagonists suggest that the concept of concentration addition (CA) provides good approximations of experimentally observed mixture effects, but studies with larger numbers of anti-androgens, and with more varied structural features, are missing. Here we show that the mixture effects of up to 17 AR antagonists, comprising compounds as diverse as UV-filter substances, parabens, perfluorinated compounds, bisphenol-A, benzo({alpha})pyrene, synthetic musks, antioxidants and polybrominated biphenyls, can be predicted well on the basis of the anti-androgenicity of the single components using the concept of CA. We tested these mixtures in an in vitro AR-dependent luciferase reporter gene assay, based on MDA-kb2 cells. The effects of further mixtures, composed of four and six anti-androgens, could be predicted accurately by CA. However, there was a shortfall from expected additivity with a ten-component mixture at two different mixture ratios, but attempts to attribute these deviations to differential expression of hormone-metabolising CYP isoforms did not produce conclusive results. CA provides good approximations of in vitro mixture effects of anti-androgens with varying structural features. -- Highlights: Black-Right-Pointing-Pointer Humans are exposed to a large number of androgen receptor antagonists. Black-Right-Pointing-Pointer There is limited evidence of the combined effects of anti-androgenic chemicals. Black-Right-Pointing-Pointer We modelled the predictability of combined effects of up to 17 anti-androgens. Black-Right-Pointing-Pointer We tested the
Revisiting Causality in Markov Chains
Shojaee, Abbas
2016-01-01
Identifying causal relationships is a key premise of scientific research. The growth of observational data in different disciplines along with the availability of machine learning methods offers the possibility of using an empirical approach to identifying potential causal relationships, to deepen our understandings of causal behavior and to build theories accordingly. Conventional methods of causality inference from observational data require a considerable length of time series data to capture cause-effect relationship. We find that potential causal relationships can be inferred from the composition of one step transition rates to and from an event. Also known as Markov chain, one step transition rates are a commonly available resource in different scientific disciplines. Here we introduce a simple, effective and computationally efficient method that we termed 'Causality Inference using Composition of Transitions CICT' to reveal causal structure with high accuracy. We characterize the differences in causes,...
Quantum information causality.
Pitalúa-García, Damián
2013-05-24
How much information can a transmitted physical system fundamentally communicate? We introduce the principle of quantum information causality, which states the maximum amount of quantum information that a quantum system can communicate as a function of its dimension, independently of any previously shared quantum physical resources. We present a new quantum information task, whose success probability is upper bounded by the new principle, and show that an optimal strategy to perform it combines the quantum teleportation and superdense coding protocols with a task that has classical inputs. PMID:23745844
Inferring deterministic causal relations
Daniusis, Povilas; Janzing, Dominik; Mooij, Joris; Zscheischler, Jakob; Steudel, Bastian; Zhang, Kun; Schoelkopf, Bernhard
2012-01-01
We consider two variables that are related to each other by an invertible function. While it has previously been shown that the dependence structure of the noise can provide hints to determine which of the two variables is the cause, we presently show that even in the deterministic (noise-free) case, there are asymmetries that can be exploited for causal inference. Our method is based on the idea that if the function and the probability density of the cause are chosen independently, then the ...
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.
Experimental test of nonlocal causality.
Ringbauer, Martin; Giarmatzi, Christina; Chaves, Rafael; Costa, Fabio; White, Andrew G; Fedrizzi, Alessandro
2016-08-01
Explaining observations in terms of causes and effects is central to empirical science. However, correlations between entangled quantum particles seem to defy such an explanation. This implies that some of the fundamental assumptions of causal explanations have to give way. We consider a relaxation of one of these assumptions, Bell's local causality, by allowing outcome dependence: a direct causal influence between the outcomes of measurements of remote parties. We use interventional data from a photonic experiment to bound the strength of this causal influence in a two-party Bell scenario, and observational data from a Bell-type inequality test for the considered models. Our results demonstrate the incompatibility of quantum mechanics with a broad class of nonlocal causal models, which includes Bell-local models as a special case. Recovering a classical causal picture of quantum correlations thus requires an even more radical modification of our classical notion of cause and effect. PMID:27532045
Relationship of causal effects in a causal chain and related inference
Institute of Scientific and Technical Information of China (English)
GENG; Zhi; HE; Yangbo; WANG; Xueli
2004-01-01
This paper discusses the relationship among the total causal effect and local causal effects in a causal chain and identifiability of causal effects. We show a transmission relationship of causal effects in a causal chain. According to the relationship, we give an approach to eliminating confounding bias through controlling for intermediate variables in a causal chain.
Relativistic hydrodynamics - causality and stability
Ván, P.; Biró, T. S.
2007-01-01
Causality and stability in relativistic dissipative hydrodynamics are important conceptual issues. We argue that causality is not restricted to hyperbolic set of differential equations. E.g. heat conduction equation can be causal considering the physical validity of the theory. Furthermore we propose a new concept of relativistic internal energy that clearly separates the dissipative and non-dissipative effects. We prove that with this choice we remove all known instabilities of the linear re...
Razhev, A. M.; Kargapol'tsev, E. S.; Churkin, D. S.
2016-03-01
Results of an experimental study of the influence of a gas mixture (laser active medium) composition on an output energy and total efficiency of gas-discharge excimer lasers on ArF* (193 nm), KrCl* (222 nm), KrF* (248 nm) and XeCl* (308 nm) molecules operating without a buffer gas are presented. The optimal ratios of gas components (from the viewpoint of a maximum output energy) of an active medium are found, which provide an efficient operation of laser sources. It is experimentally confirmed that for gas-discharge excimer lasers on halogenides of inert gases the presence of a buffer gas in an active medium is not a necessary condition for efficient operation. For the first time, in two-component gas mixtures of repetitively pulsed gas-discharge excimer lasers on electron transitions of excimer molecules ArF*, KrCl*, KrF* and XeCl*, the pulsed energy of laser radiation obtained under pumping by a transverse volume electric discharge in a low-pressure gas mixture without a buffer gas reached up to 170 mJ and a high pulsed output power (of up to 24 MW) was obtained at a FWHM duration of the KrF-laser pulse of 7 ns. The maximal total efficiency obtained in the experiment with two-component gas mixtures of KrF and XeCl lasers was 0.8%.
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
International Nuclear Information System (INIS)
Influence of argon content in Ar/O2 mixture on O2 dissociation degree and atomic oxygen concentration in the plasma of low pressure glow discharge with hollow cathode is determined experimentally and theoretically. It is found that atomic oxygen concentration dependence on argon content in the mixture exhibits non-monotonous behavior with a minimum at Ar/(Ar+O2) approx 50%. Results of calculation and experiment are in a good agreement
Inferring deterministic causal relations
Daniusis, Povilas; Mooij, Joris; Zscheischler, Jakob; Steudel, Bastian; Zhang, Kun; Schoelkopf, Bernhard
2012-01-01
We consider two variables that are related to each other by an invertible function. While it has previously been shown that the dependence structure of the noise can provide hints to determine which of the two variables is the cause, we presently show that even in the deterministic (noise-free) case, there are asymmetries that can be exploited for causal inference. Our method is based on the idea that if the function and the probability density of the cause are chosen independently, then the distribution of the effect will, in a certain sense, depend on the function. We provide a theoretical analysis of this method, showing that it also works in the low noise regime, and link it to information geometry. We report strong empirical results on various real-world data sets from different domains.
Thermophysical Properties of Hydrocarbon Mixtures
SRD 4 NIST Thermophysical Properties of Hydrocarbon Mixtures (PC database for purchase) Interactive computer program for predicting thermodynamic and transport properties of pure fluids and fluid mixtures containing up to 20 components. The components are selected from a database of 196 components, mostly hydrocarbons.
Causal Inference and Developmental Psychology
Foster, E. Michael
2010-01-01
Causal inference is of central importance to developmental psychology. Many key questions in the field revolve around improving the lives of children and their families. These include identifying risk factors that if manipulated in some way would foster child development. Such a task inherently involves causal inference: One wants to know whether…
Friederich, Simon
2015-01-01
There is widespread belief in a tension between quantum theory and special relativity, motivated by the idea that quantum theory violates J. S. Bell's criterion of local causality, which is meant to implement the causal structure of relativistic space-time. This paper argues that if one takes the es
Expert Causal Reasoning and Explanation.
Kuipers, Benjamin
The relationship between cognitive psychologists and researchers in artificial intelligence carries substantial benefits for both. An ongoing investigation in causal reasoning in medical problem solving systems illustrates this interaction. This paper traces a dialectic of sorts in which three different types of causal resaoning for medical…
The Visual Causality Analyst: An Interactive Interface for Causal Reasoning.
Wang, Jun; Mueller, Klaus
2016-01-01
Uncovering the causal relations that exist among variables in multivariate datasets is one of the ultimate goals in data analytics. Causation is related to correlation but correlation does not imply causation. While a number of casual discovery algorithms have been devised that eliminate spurious correlations from a network, there are no guarantees that all of the inferred causations are indeed true. Hence, bringing a domain expert into the casual reasoning loop can be of great benefit in identifying erroneous casual relationships suggested by the discovery algorithm. To address this need we present the Visual Causal Analyst-a novel visual causal reasoning framework that allows users to apply their expertise, verify and edit causal links, and collaborate with the causal discovery algorithm to identify a valid causal network. Its interface consists of both an interactive 2D graph view and a numerical presentation of salient statistical parameters, such as regression coefficients, p-values, and others. Both help users in gaining a good understanding of the landscape of causal structures particularly when the number of variables is large. Our framework is also novel in that it can handle both numerical and categorical variables within one unified model and return plausible results. We demonstrate its use via a set of case studies using multiple practical datasets. PMID:26529703
["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. PMID:1392028
International Nuclear Information System (INIS)
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
Tarnopolski, Mariusz
2015-01-01
Two classes of GRBs have been identified thus far and are prescribed to different physical scenarios $-$ NS-NS or NS-BH mergers, and collapse of massive stars, for short and long GRBs, respectively. A third, intermediate in durations class, was suggested to be present in previous catalogs, such as BATSE and Swift, based on statistical tests regarding a mixture of two or three normal distributions. However, this might possibly not be an adequate model. This paper investigates whether the distribution of $\\log T_{90}$ from Fermi shows evidence for a third, intermediate, class of GRBs. Mixtures of standard Gaussians, skew-normal, sinh-arcsinh and alpha-skew-normal distributions are fitted using a maximum likelihood method. The preferred model is chosen based on the Akaike information criterion. It is found that mixtures of two skew-normal or two sinh-arcsinh distributions are more likely to describe the observed duration distribution than a mixture of three standard Gaussians. Based on statistical reasoning, exi...
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. PMID:11890317
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 for...... 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 the...
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.
Guilloux, Marion; PROST, Carole; Courcoux, Philippe; Le Bail, Alain
2015-01-01
Salt reduction in food is a major concern for public health authorities but remains a challenge for the food industry. Aims of this study are to modulate salt distribution between the ingredients of salt-reduced pizza (-30%) by modifying the salt content of each ingredient without changing the total salt content of pizza using mixture experimental design, to demonstrate its impact on sensory properties, and to determine the formulation with sensory properties, evaluated by Quantitative Descri...
Palmer, Jason Allan
2006-01-01
This thesis considers representations of non-Gaussian probability densities for use in various estimation problems associated with the Bayesian Linear Model. We define a class of densities that we call Strongly Super- Gaussian, and show the relationship of these densities to Gaussian Scale Mixtures, and densities with positive kurtosis. Such densities have been used to model "sparse" random variables, with densities that are sharply peaked with heavy tails. We show that strongly super-Gaussia...
On causality of extreme events
Zanin, Massimiliano
2016-01-01
Multiple metrics have been developed to detect causality relations between data describing the elements constituting complex systems, all of them considering their evolution through time. Here we propose a metric able to detect causality within static data sets, by analysing how extreme events in one element correspond to the appearance of extreme events in a second one. The metric is able to detect both linear and non-linear causalities; to analyse both cross-sectional and longitudinal data sets; and to discriminate between real causalities and correlations caused by confounding factors. We validate the metric through synthetic data, dynamical and chaotic systems, and data representing the human brain activity in a cognitive task.
Causal 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 e...
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...
Realist Magic : Objects, Ontology, Causality
Morton, Timothy
2013-01-01
Object-oriented ontology offers a startlingly fresh way to think about causality that takes into account developments in physics since 1900. Causality, argues, Object Oriented Ontology (OOO), is aesthetic. In this book, Timothy Morton explores what it means to say that a thing has come into being, that it is persisting, and that it has ended. Drawing from examples in physics, biology, ecology, art, literature and music, Morton demonstrates the counterintuitive yet elegant explanatory power of...
Correlation Measure Equivalence in Dynamic Causal Structures
Gyongyosi, Laszlo
2016-01-01
We prove an equivalence transformation between the correlation measure functions of the causally-unbiased quantum gravity space and the causally-biased standard space. The theory of quantum gravity fuses the dynamic (nonfixed) causal structure of general relativity and the quantum uncertainty of quantum mechanics. In a quantum gravity space, the events are causally nonseparable and all time bias vanishes, which makes it no possible to use the standard causally-biased entropy and the correlation measure functions. Since a corrected causally-unbiased entropy function leads to an undefined, obscure mathematical structure, in our approach the correction is made in the data representation of the causally-unbiased space. We prove that the standard causally-biased entropy function with a data correction can be used to identify correlations in dynamic causal structures. As a corollary, all mathematical properties of the causally-biased correlation measure functions are preserved in the causally-unbiased space. The eq...
Causality, causality, causality: the view of education inputs and outputs from economics
Lisa Barrow; Cecilia Elena Rouse
2005-01-01
Educators and policy makers are increasingly intent on using scientifically-based evidence when making decisions about education policy. Thus, education research today must necessarily be focused on identifying the causal relationships between education inputs and student outcomes. In this paper we discuss methodologies for estimating the causal effect of resources on education outcomes; we also review what we believe to be the best evidence from economics on a few important inputs: spending,...
International Nuclear Information System (INIS)
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.
Analysis of asphalt mixtures on town roads
Glavica, Primož
2006-01-01
Asphalt mixtures are most commonly used composite for construction of top layers of different drive ways. By definition asphalt mixtures are composed of crushed rock, fill, bitumen and additives. Percentage of individual components wary according to the purpose asphalt mixture is to be used for. Asphalt mixtures must be capable of enduring different types of load. According to the type of load asphalt mixtures are divided into asphalt mixtures used for supporting layers and asp...
Sellami, Badreddine; Khazri, Abdelhafidh; Mezni, Amine; Louati, Héla; Dellali, Mohamed; Aissa, Patricia; Mahmoudi, Ezzeddine; Beyrem, Hamouda; Sheehan, David
2015-01-01
Anthracene (ANT) and permethrin (PER) are two of the more toxic compounds reaching the marine environment. This study aimed to determine the impact of these molecules on Venerupis decussata, an economically important species cultured on the Tunisian coast. Shell structure and its possible transformation upon exposure to the two contaminants were studied by X-ray diffraction and gravimetric analyses. Results revealed a phase transition in shell composition from aragonite to calcite after PER exposure, to a mixture of PER and ANT (Mix) but not for ANT alone. Catalase (CAT), superoxide dismutase (SOD) and glutathione transferase (GST) activities were determined in digestive gland and gills after exposure to ANT, PER and Mix to assess the impact of the contamination on the oxidative status of V. decussata. Enzyme activities increased in the digestive gland after PER treatment and in the gills after ANT treatment. PER exposure significantly reduced the levels of free thiols and increased levels of carbonylated proteins in the digestive gland, as compared to controls. In contrast, ANT exposure significantly reduced free thiols and increased the number of carbonylated proteins in the gills. Mix induced additive effects as measured by both enzymatic and proteomic approaches. The present study suggests that PER has a strong effect on shell structure; that PER and ANT exposure generate compound-dependent oxidative stress in the tissues of V. decussata and that a mixture of the two compounds has synergistic effects on biochemical response. PMID:25461742
Hierarchical organisation of causal graphs
International Nuclear Information System (INIS)
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
Mirjana N. Lukić-Anđelković
2009-01-01
U radu je prikazan način dobijanja i karakteristike trokomponentnih smeša RDX/Al/PS. Primenjen flegmatizator heksogena je termostabilni polimer polistiren čija je karakteristika da dobro prekriva. Primenjivan je konstantan sadržaj od 5% PS za različite sadržaje heksogena i aluminijuma. Sadržaj aluminijuma u smešama je 10, 15, 20 u 25% m/m. Ispitan je sastav i određena brzina detonacije. / The characteristics of three-component RDX/PS/Al mixtures have been described s well as the method for th...
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
Directory of Open Access Journals (Sweden)
Sangeet eKhemlani
2014-10-01
Full Text Available This paper outlines the model-based theory of causal reasoning. It postulates that the core meanings of causal assertions are deterministic and refer to temporally-ordered sets of possibilities: A causes B to occur means that given A, B occurs, whereas A enables B to occur means that given A, it is possible for B to occur. The paper shows how mental models represent such assertions, and how these models underlie deductive, inductive, and abductive reasoning yielding explanations. It reviews evidence both to corroborate the theory and to account for phenomena sometimes taken to be incompatible with it. Finally, it reviews neuroscience evidence indicating that mental models for causal inference are implemented within lateral prefrontal cortex.
Causal Models for Risk Management
Directory of Open Access Journals (Sweden)
Neysis Hernández Díaz
2013-12-01
Full Text Available In this work a study about the process of risk management in major schools in the world. The project management tools worldwide highlights the need to redefine risk management processes. From the information obtained it is proposed the use of causal models for risk analysis based on information from the project or company, say risks and the influence thereof on the costs, human capital and project requirements and detect the damages of a number of tasks without tribute to the development of the project. A study on the use of causal models as knowledge representation techniques causal, among which are the Fuzzy Cognitive Maps (DCM and Bayesian networks, with the most favorable MCD technique to use because it allows modeling the risk information witho ut having a knowledge base either itemize.
Directory of Open Access Journals (Sweden)
Mirjana N. Lukić-Anđelković
2009-10-01
Full Text Available U radu je prikazan način dobijanja i karakteristike trokomponentnih smeša RDX/Al/PS. Primenjen flegmatizator heksogena je termostabilni polimer polistiren čija je karakteristika da dobro prekriva. Primenjivan je konstantan sadržaj od 5% PS za različite sadržaje heksogena i aluminijuma. Sadržaj aluminijuma u smešama je 10, 15, 20 u 25% m/m. Ispitan je sastav i određena brzina detonacije. / The characteristics of three-component RDX/PS/Al mixtures have been described s well as the method for their preparation. Polystirene as a binder is a thermostable polymer with satisfactory characteristics for bonding explosives. The constant content of 5% m/m PS was applied for different contents of hexogen and aluminium. The content of Al in the mixtures was 10, 15, and 20% m/m. The composition of the bonded explosives was examined as well as the detonation velocity of these mixtures.
On Causality in Dynamical Systems
Harnack, Daniel
2016-01-01
Identification of causal links is fundamental for the analysis of complex systems. In dynamical systems, however, nonlinear interactions may hamper separability of subsystems which poses a challenge for attempts to determine the directions and strengths of their mutual influences. We found that asymmetric causal influences between parts of a dynamical system lead to characteristic distortions in the mappings between the attractor manifolds reconstructed from respective local observables. These distortions can be measured in a model-free, data-driven manner. This approach extends basic intuitions about cause-effect relations to deterministic dynamical systems and suggests a mathematically well defined explanation of results obtained from previous methods based on state space reconstruction.
Cohomology with causally restricted supports
Khavkine, Igor
2014-01-01
De Rham cohomology with spacelike compact and timelike compact supports has recently been noticed to be of importance for understanding the structure of classical and quantum field theories on curved spacetimes. We compute these cohomology groups for globally hyperbolic spacetimes in terms of their standard de Rham cohomologies. The calculation exploits the fact that the de Rham-d'Alambert wave operator can be extended to a chain map that is homotopic to zero and that its causal Green function fits into a convenient exact sequence. This method extends also to the Calabi (or Killing-Riemann-Bianchi) complex and possibly other differential complexes. We also discuss generalized causal structures and functoriality.
On the Axioms of Causal Set Theory
Dribus, Benjamin F
2013-01-01
This paper offers suggested improvements to the causal sets program in discrete gravity, which treats spacetime geometry as an emergent manifestation of causal structure at the fundamental scale. This viewpoint, which I refer to as the causal metric hypothesis, is summarized by Rafael Sorkin's phrase, "order plus number equals geometry." Proposed improvements include recognition of a generally nontransitive causal relation more fundamental than the causal order, an improved local picture of causal structure, development and use of relation space methods, and a new background-independent version of the histories approach to quantum theory. Besides causal set theory, \\`a la Bombelli, Lee, Meyer, and Sorkin, this effort draws on Isham's topos-theoretic framework for physics, Sorkin's quantum measure theory, Finkelstein's causal nets, and Grothendieck's structural principles. This approach circumvents undesirable structural features in causal set theory, such as the permeability of maximal antichains, studied by ...
Ness, Robert O; Sachs, Karen; Vitek, Olga
2016-03-01
Causal inference, the task of uncovering regulatory relationships between components of biomolecular pathways and networks, is a primary goal of many high-throughput investigations. Statistical associations between observed protein concentrations can suggest an enticing number of hypotheses regarding the underlying causal interactions, but when do such associations reflect the underlying causal biomolecular mechanisms? The goal of this perspective is to provide suggestions for causal inference in large-scale experiments, which utilize high-throughput technologies such as mass-spectrometry-based proteomics. We describe in nontechnical terms the pitfalls of inference in large data sets and suggest methods to overcome these pitfalls and reliably find regulatory associations. PMID:26731284
Causal feedbacks in climate change
Nes, van E.H.; Scheffer, M.; Brovkin, V.; Lenton, T.M.; Ye, H.; Deyle, E.; Sugihara, G.
2015-01-01
The statistical association between temperature and greenhouse gases over glacial cycles is well documented1, but causality behind this correlation remains difficult to extract directly from the data. A time lag of CO2 behind Antarctic temperature—originally thought to hint at a driving role for tem
Causal Behaviour on Carter spacetime
Blanco, Oihane F
2015-01-01
In this work we will focus on the causal character of Carter Spacetime (see B. Carter, Causal structure in space-time, Gen. Rel. Grav. 1 4 337-406, 1971). The importance of this spacetime is the following: for the causally best well behaved spacetimes (the globally hyperbolic ones), there are several characterizations or alternative definitions. In some cases, it has been shown that some of the causal properties required in these characterizations can be weakened. But Carter spacetime provides a counterexample for an impossible relaxation in one of them. We studied the possibility of Carter spacetime to be a counterexample for impossible lessening in another characterization, based on the previous results. In particular, we will prove that the time-separation or Lorentzian distance between two chosen points in Carter spacetime is infinite. Although this spacetime turned out not to be the counterexample we were looking for, the found result is interesting per se and provides ideas for alternate approaches to t...
Causality problem in Economic Science
Directory of Open Access Journals (Sweden)
JOSÉ LUIS RETOLAZA
2007-12-01
Full Text Available The main point of the paper is the problem of the economy to be consider like a science in the most strict term of the concept. In the first step we are going to tackle a presentation about what we understand by science to subsequently present some of the fallacies which have bring certain scepticism about the scientific character of the investigation in economy, to know: 1 The differences between hard and weak sciences -physics and social; 2 The differences between paradigm, —positivist and phenomenological— 3 The differences between physic causalityand historic causality. In the second step we are going to talk about two fundamental problems which are questioned: 1 the confusion between ontology and gnoseology and, 2 the erroneous concept of causality that commonly is used. In the last step of the paper we are going over the recent models of «causal explanation» and we suggest the probabilistic casualty development next with a more elaborated models of causal explanation, like a way to conjugate the scientific severity with the possibility to tackle complex economic realities.
Anticipation of physical causality guides eye movements
Wende, Kim; Theunissen, Laetitia; Missal, Marcus
2016-01-01
Causality is a unique feature of human perception. We present here a behavioral investigation of the influence of physical causality during visual pursuit of object collisions. Pursuit and saccadic eye movements of human subjects were recorded during ocular pursuit of two concurrently launched targets, one that moved according to the laws of Newtonian mechanics (the causal target) and the other one that moved in a physically implausible direction (the non-causal target). We found that anticip...
Causal discovery from medical textual data.
Mani, S.; Cooper, G. F.
2000-01-01
Medical records usually incorporate investigative reports, historical notes, patient encounters or discharge summaries as textual data. This study focused on learning causal relationships from intensive care unit (ICU) discharge summaries of 1611 patients. Identification of the causal factors of clinical conditions and outcomes can help us formulate better management, prevention and control strategies for the improvement of health care. For causal discovery we applied the Local Causal Discove...
Estimating causal structure using conditional DAG models
Oates, Chris J.; Smith, Jim Q.; Mukherjee, Sach
2014-01-01
This paper considers inference of causal structure in a class of graphical models called "conditional DAGs". These are directed acyclic graph (DAG) models with two kinds of variables, primary and secondary. The secondary variables are used to aid in estimation of causal relationships between the primary variables. We give causal semantics for this model class and prove that, under certain assumptions, the direction of causal influence is identifiable from the joint observational distribution ...
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
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.…
The argumentative impact of causal relations
DEFF Research Database (Denmark)
Nielsen, Anne Ellerup
1996-01-01
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....
Expectations and Interpretations during Causal Learning
Luhmann, Christian C.; Ahn, Woo-kyoung
2011-01-01
In existing models of causal induction, 4 types of covariation information (i.e., presence/absence of an event followed by presence/absence of another event) always exert identical influences on causal strength judgments (e.g., joint presence of events always suggests a generative causal relationship). In contrast, we suggest that, due to…
Principal Stratification in Causal Inference
Frangakis, Constantine E.; Rubin, Donald B.
2002-01-01
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 valu...
Entanglement, Holography and Causal Diamonds
de Boer, Jan; Heller, Michal P; Myers, Robert C
2016-01-01
We argue that the degrees of freedom in a d-dimensional CFT can be re-organized in an insightful way by studying observables on the moduli space of causal diamonds (or equivalently, the space of pairs of timelike separated points). This 2d-dimensional space naturally captures some of the fundamental nonlocality and causal structure inherent in the entanglement of CFT states. For any primary CFT operator, we construct an observable on this space, which is defined by smearing the associated one-point function over causal diamonds. Known examples of such quantities are the entanglement entropy of vacuum excitations and its higher spin generalizations. We show that in holographic CFTs, these observables are given by suitably defined integrals of dual bulk fields over the corresponding Ryu-Takayanagi minimal surfaces. Furthermore, we explain connections to the operator product expansion and the first law of entanglement entropy from this unifying point of view. We demonstrate that for small perturbations of the va...
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 reasoning and models of cognitive tasks for naval nuclear power plant operators
International Nuclear Information System (INIS)
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
Finitary Spacetime Sheaves of Quantum Causal Sets Curving Quantum Causality
Mallios, A
2001-01-01
A locally finite, causal and quantal substitute for a locally Minkowskian principal fiber bundle $\\cal{P}$ of modules of Cartan differential forms $\\omg$ over a bounded region $X$ of a curved $C^{\\infty}$-smooth differential manifold spacetime $M$ with structure group ${\\bf G}$ that of orthochronous Lorentz transformations $L^{+}:=SO(1,3)^{\\uparrow}$, is presented. ${\\cal{P}}$ is the structure on which classical Lorentzian gravity, regarded as a Yang-Mills type of gauge theory of a $sl(2,\\com)$-valued connection 1-form $\\cal{A}$, is usually formulated. The mathematical structure employed to model this replacement of ${\\cal{P}}$ is a principal finitary spacetime sheaf $\\vec{\\cal{P}}_{n}$ of quantum causal sets $\\amg_{n}$ with structure group ${\\bf G}_{n}$, which is a finitary version of the group ${\\bf G}$ of local symmetries of General Relativity, and a finitary Lie algebra ${\\bf g}_{n}$-valued connection 1-form ${\\cal{A}}_{n}$ on it, which is a section of its sub-sheaf $\\amg^{1}_{n}$. ${\\cal{A}}_{n}$ is phys...
The Impossibility of Causality Testing
Conway, Roger K.; P. A. V. B. Swamy; Yanagida, John F.; Muehlen, Peter von zur
1984-01-01
Causality tests developed by Sims and Granger are fatally flawed for several reasons First, when two variables, X and Y, are uncorrelated, X has no linear predictive value for Y, but X,and Y may be nonlinearly related unless they are statistically Independent, In which case X and Y are not related at all The light-hand side variables In a regression equation are exogenous If they are mean Independent of the disturbance term Mean Independence IS stronger than uncorrelatedness The proofs for de...
Breaking the arrows of causality
DEFF Research Database (Denmark)
Valsiner, Jaan
2014-01-01
Theoretical models of catalysis have proven to bring with them major breakthroughs in chemistry and biology, from the 1830s onward. It can be argued that the scientific status of chemistry has become established through the move from causal to catalytic models. Likewise, the central explanatory...... role of cyclical models in biology has made it possible to move from the idea of genetic determination to that of epigenetic negotiation as the core of biological theory. In psychology, catalytic thinking has been outside of the realm of accepted scientific schemes, as the axiomatic dependence upon the...
The Functions of Danish Causal Conjunctions
Directory of Open Access Journals (Sweden)
Rita Therkelsen
2004-01-01
Full Text Available In the article I propose an analysis of the Danish causal conjunctions fordi, siden and for based on the framework of Danish Functional Grammar. As conjunctions they relate two clauses, and their semantics have in common that it indicates a causal relationship between the clauses. The causal conjunctions are different as far as their distribution is concerned; siden conjoins a subordinate clause and a main clause, for conjoins two main clauses, and fordi is able to do both. Methodologically I have based my analysis on these distributional properties comparing siden and fordi conjoining a subordinate and a main clause, and comparing for and fordi conjoining two main clauses, following the thesis that they would establish a causal relationship between different kinds of content. My main findings are that fordi establishes a causal relationship between the events referred to by the two clauses, and the whole utterance functions as a statement of this causal relationship. Siden presupposes such a general causal relationship between the two events and puts forward the causing event as a reason for assuming or wishing or ordering the caused event, siden thus establishes a causal relationship between an event and a speech act. For equally presupposes a general causal relationship between two events and it establishes a causal relationship between speech acts, and fordi conjoining two main clauses is able to do this too, but in this position it also maintains its event-relating ability, the interpretation depending on contextual factors.
Space and time in perceptual causality
Directory of Open Access Journals (Sweden)
Benjamin Straube
2010-04-01
Full Text Available Inferring causality is a fundamental feature of human cognition that allows us to theorize about and predict future states of the world. Michotte suggested that humans automatically perceive causality based on certain perceptual features of events. However, individual differences in judgments of perceptual causality cast doubt on Michotte’s view. To gain insights in the neural basis of individual difference in the perception of causality, our participants judged causal relationships in animations of a blue ball colliding with a red ball (a launching event while fMRI-data were acquired. Spatial continuity and temporal contiguity were varied parametrically in these stimuli. We did not find consistent brain activation differences between trials judged as caused and those judged as non-caused, making it unlikely that humans have universal instantiation of perceptual causality in the brain. However, participants were slower to respond to and showed greater neural activity for violations of causality, suggesting that humans are biased to expect causal relationships when moving objects appear to interact. Our participants demonstrated considerable individual differences in their sensitivity to spatial and temporal characteristics in perceiving causality. These qualitative differences in sensitivity to time or space in perceiving causality were instantiated in individual differences in activation of the left basal ganglia or right parietal lobe, respectively. Thus, the perception that the movement of one object causes the movement of another is triggered by elemental spatial and temporal sensitivities, which themselves are instantiated in specific distinct neural networks.
Probabilistic causality and radiogenic cancers
International Nuclear Information System (INIS)
A review and scrutiny of the literature on probability and probabilistic causality shows that it is possible under certain assumptions to estimate the probability that a certain type of cancer diagnosed in an individual exposed to radiation prior to diagnosis was caused by this exposure. Diagnosis of this causal relationship like diagnosis of any disease - malignant or not - requires always some subjective judgments by the diagnostician. It is, therefore, illusory to believe that tables based on actuarial data can provide objective estimates of the chance that a cancer diagnosed in an individual is radiogenic. It is argued that such tables can only provide a base from which the diagnostician(s) deviate in one direction or the other according to his (their) individual (consensual) judgment. Acceptance of a physician's diagnostic judgment by patients is commonplace. Similar widespread acceptance of expert judgment by claimants in radiation compensation cases does presently not exist. Judicious use of the present radioepidemiological tables prepared by the Working Group of the National Institutes of Health or of updated future versions of similar tables may improve the situation. 20 references
Variational multi-fluid dynamics and causal heat conductivity
Andersson, N.; Comer, G. L.
2009-01-01
We discuss heat conductivity from the point of view of a variational multi-fluid model, treating entropy as a dynamical entity. We demonstrate that a two-fluid model with a massive fluid component and a massless entropy can reproduce a number of key results from extended irreversible thermodynamics. In particular, we show that the entropy entrainment is intimately linked to the thermal relaxation time that is required to make heat propagation in solids causal. We also discuss non-local terms ...
Granger Causality and the Capital Asset Pricing Model
Mihir Dash
2014-01-01
At the heart of the CAPM lies the concept of systematic risk. The systematic risk of a security is that component of the total risk of the security that is explained by market risk. This study investigates the econometrics of the CAPM. In particular, it analyses Granger causality from market returns to security returns, the absence of which would weaken the significance of beta, and undermine the foundations of the CAPM.
Dynamically redundant particle components in mixtures
International Nuclear Information System (INIS)
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)
Causal relationship: a new tool for the causal characterization of Lorentzian manifolds
International Nuclear Information System (INIS)
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
FDI and growth: a causal relationship
Chowdhury, Abdur; Mavrotas, George
2005-01-01
The paper examines the causal relationship between FDI and economic growth by using an innovative econometric methodology to study the direction of causality between the two variables. We apply our methodology, based on the Toda-Yamamoto test for causality, to time-series data covering the period 1969-2000 for three developing countries, namely Chile, Malaysia and Thailand, all of them major recipients of FDI with a different history of macroeconomic episodes, policy regimes and growth patter...
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
The problem of causality in cultivation research
Rossmann, Constanze; Brosius, Hans-Bernd
2004-01-01
This paper offers an up-to-date review of problems in determining causal relationships in cultivation research, and considers the research rationales of various approaches with special reference to causal interpretation. It describes in turn a number of methodologies for addressing the problem and resolving it as far as this is possible. The issue of causal inference arises not only in cultivation research, however, but is basic to all media effects theories and approaches primarily at the ma...
Causal inference in economics and marketing.
Varian, Hal R
2016-07-01
This is an elementary introduction to causal inference in economics written for readers familiar with machine learning methods. The critical step in any causal analysis is estimating the counterfactual-a prediction of what would have happened in the absence of the treatment. The powerful techniques used in machine learning may be useful for developing better estimates of the counterfactual, potentially improving causal inference. PMID:27382144
Causal inference in economics and marketing
Varian, Hal R.
2016-01-01
This is an elementary introduction to causal inference in economics written for readers familiar with machine learning methods. The critical step in any causal analysis is estimating the counterfactual—a prediction of what would have happened in the absence of the treatment. The powerful techniques used in machine learning may be useful for developing better estimates of the counterfactual, potentially improving causal inference. PMID:27382144
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...
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.
Causal ubiquity in quantum physics. A superluminal and local-causal physical ontology
International Nuclear Information System (INIS)
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.
Mixture Based Outlier Filtration
Directory of Open Access Journals (Sweden)
P. Pecherková
2006-01-01
Full Text Available Success/failure of adaptive control algorithms – especially those designed using the Linear Quadratic Gaussian criterion – depends on the quality of the process data used for model identification. One of the most harmful types of process data corruptions are outliers, i.e. ‘wrong data’ lying far away from the range of real data. The presence of outliers in the data negatively affects an estimation of the dynamics of the system. This effect is magnified when the outliers are grouped into blocks. In this paper, we propose an algorithm for outlier detection and removal. It is based on modelling the corrupted data by a two-component probabilistic mixture. The first component of the mixture models uncorrupted process data, while the second models outliers. When the outlier component is detected to be active, a prediction from the uncorrupted data component is computed and used as a reconstruction of the observed data. The resulting reconstruction filter is compared to standard methods on simulated and real data. The filter exhibits excellent properties, especially in the case of blocks of outliers.
Quantum retrodiction and causality principle
International Nuclear Information System (INIS)
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
Comparison theorems for causal diamonds
Berthiere, Clement; Solodukhin, Sergey N
2015-01-01
We formulate certain inequalities for the geometric quantities characterizing causal diamonds in curved and Minkowski spacetimes. These inequalities involve the red-shift factor which, as we show explicitly in the spherically symmetric case, is monotonic in the radial direction and it takes its maximal value at the centre. As a byproduct of our discussion we re-derive Bishop's inequality without assuming the positivity of the spatial Ricci tensor. We then generalize our considerations to arbitrary, static and not necessarily spherically symmetric, asymptotically flat spacetimes. In the case of spacetimes with a horizon our generalization involves the so-called {\\it domain of dependence}. The respective volume, expressed in terms of the duration measured by a distant observer compared with the volume of the domain in Minkowski spacetime, exhibits behaviours which differ if $d=4$ or $d>4$. This peculiarity of four dimensions is due to the logarithmic subleading term in the asymptotic expansion of the metric nea...
Optimal Parameters Multicomponent Mixtures Extruding
Directory of Open Access Journals (Sweden)
Ramil F. Sagitov
2013-01-01
Full Text Available Experimental research of multicomponent mixtures extruding from production wastes are carried out, unit for production of composites from different types of waste is presented. Having analyzed dependence of multicomponent mixtures extruding energy requirements on die length and components content at three values of angular rate of screw rotation, we received the values of energy requirements at optimal length of the die, angular speed and percent of binding additives.
The Power of Causal Beliefs and Conflicting Evidence on Causal Judgments and Decision Making
Garcia-Retamero, Rocio; Muller, Stephanie M.; Catena, Andres; Maldonado, Antonio
2009-01-01
In two experiments, we investigated the relative impact of causal beliefs and empirical evidence on both decision making and causal judgments, and whether this relative impact could be altered by previous experience. 2. Selected groups of participants in both experiments received pre-training with either causal or neutral cues, or no pre-training…
A nonlinear impact: evidences of causal effects of social media on market prices
Souza, Thársis T. P.; Aste, Tomaso
2016-01-01
Online social networks offer a new way to investigate financial markets' dynamics by enabling the large-scale analysis of investors' collective behavior. We provide empirical evidence that suggests social media and stock markets have a nonlinear causal relationship. We take advantage of an extensive data set composed of social media messages related to DJIA index components. By using information-theoretic measures to cope for possible nonlinear causal coupling between social media and stock m...
Spin foam models as energetic causal sets
Cortês, Marina; Smolin, Lee
2016-04-01
Energetic causal sets are causal sets endowed by a flow of energy-momentum between causally related events. These incorporate a novel mechanism for the emergence of space-time from causal relations [M. Cortês and L. Smolin, Phys. Rev. D 90, 084007 (2014); Phys. Rev. D 90, 044035 (2014)]. Here we construct a spin foam model which is also an energetic causal set model. This model is closely related to the model introduced in parallel by Wolfgang Wieland in [Classical Quantum Gravity 32, 015016 (2015)]. What makes a spin foam model also an energetic causal set is Wieland's identification of new degrees of freedom analogous to momenta, conserved at events (or four-simplices), whose norms are not mass, but the volume of tetrahedra. This realizes the torsion constraints, which are missing in previous spin foam models, and are needed to relate the connection dynamics to those of the metric, as in general relativity. This identification makes it possible to apply the new mechanism for the emergence of space-time to a spin foam model. Our formulation also makes use of Markopoulou's causal formulation of spin foams [arXiv:gr-qc/9704013]. These are generated by evolving spin networks with dual Pachner moves. This endows the spin foam history with causal structure given by a partial ordering of the events which are dual to four-simplices.
Controlling for causally relevant third variables.
Goodie, Adam S; Williams, Cristina C; Crooks, C L
2003-10-01
In 3 experiments, the authors tested the conditions under which 3rd variables are controlled for in making causal judgments. The authors hypothesized that 3rd variables are controlled for when the 3rd variables are themselves perceived as causal. In Experiment 1, the participants predicted test performance after seeing information about wearing a lucky garment, taking a test-preparation course, and staying up late. The course (perceived as more causally relevant) was controlled for more than was the garment (perceived as less causally relevant) in assessing the effectiveness of staying up late. In Experiments 2 and 3, to obviate the many alternative accounts that arise from the realistic cover story of Experiment 1, participants predicted flowers' blooming after the presentation or nonpresentation of liquids. When one liquid was trained as causal, it was controlled for more in judging another liquid than when it was trained as neutral. Overall, stimuli perceived as causal were controlled for more when judging other stimuli. The authors concluded that the effect of perceived causal relevance on causal conditionalizing is real and normatively reasonable. PMID:14672103
Causal processes and propensities in quantum mechanics
Directory of Open Access Journals (Sweden)
Mauricio SUÁREZ
2010-01-01
Full Text Available I offer an alternative interpretation of Van Fraassen's influential arguments against causal realism in quantum mechanics. These arguments provide in fact a good guide to the different causal models available for the Einstein-Podolsky-Rosen correlations, which in turn shed light on the nature of quantum propensities.
Compact Representations of Extended Causal Models
Halpern, Joseph Y.; Hitchcock, Christopher
2013-01-01
Judea Pearl (2000) was the first to propose a definition of actual causation using causal models. A number of authors have suggested that an adequate account of actual causation must appeal not only to causal structure but also to considerations of "normality." In Halpern and Hitchcock (2011), we offer a definition of actual causation…
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.
Causalities of the Taiwan Stock Market
Juhi-Lian Julian Ting
2003-01-01
Volatility, fitting with first order Landau expansion, stationarity, and causality of the Taiwan stock market (TAIEX) are investigated based on daily records. Instead of consensuses that consider stock market index change as a random time series we propose the market change as a dual time series consists of the index and the corresponding volume. Therefore, causalities between these two time series are investigated.
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…
Unpacking the causal chain of financial literacy
Carpena, Fenella; Cole, Shawn; Shapiro, Jeremy; Zia, Bilal
2011-01-01
A growing body of literature examines the causal impact of financial literacy on individual, household, and firm level outcomes. This paper unpacks the mechanism of impact by focusing on the first link in the causal chain. Specifically, it studies the experimental impact of financial literacy on three distinct dimensions of financial knowledge. The analysis finds that financial literacy do...
Causal random geometry from stochastic quantization
DEFF Research Database (Denmark)
Ambjørn, Jan; Loll, R.; Westra, W.; Zohren, S.
2010-01-01
in this short note we review a recently found formulation of two-dimensional causal quantum gravity defined through Causal Dynamical Triangulations and stochastic quantization. This procedure enables one to extract the nonperturbative quantum Hamiltonian of the random surface model including the...
B. Schmitt; Kiefer, C; Schütze, A.
2015-01-01
A novel sensor principle for determining binary fluid mixtures of known components is presented, making use of different thermal and rheological properties of the mixture's components. Using a microheater, a heat pulse is introduced in the mixture. The resulting temperature increase depends on the thermal properties of the mixture, allowing determination of the mixture ratio. Placing a bluff body in the fluid channel causes the formation of a stationary pair of vortices behi...
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
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
International Nuclear Information System (INIS)
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)
Liquid class predictor for liquid handling of complex mixtures
Seglke, Brent W.; Lekin, Timothy P.
2008-12-09
A method of establishing liquid classes of complex mixtures for liquid handling equipment. The mixtures are composed of components and the equipment has equipment parameters. The first step comprises preparing a response curve for the components. The next step comprises using the response curve to prepare a response indicator for the mixtures. The next step comprises deriving a model that relates the components and the mixtures to establish the liquid classes.
Causal localizations in relativistic quantum mechanics
Energy Technology Data Exchange (ETDEWEB)
Castrigiano, Domenico P. L., E-mail: castrig@ma.tum.de; Leiseifer, Andreas D., E-mail: andreas.leiseifer@tum.de [Fakultät für Mathematik, TU München, Boltzmannstraße 3, 85747 Garching (Germany)
2015-07-15
Causal localizations describe the position of quantum systems moving not faster than light. They are constructed for the systems with finite spinor dimension. At the center of interest are the massive relativistic systems. For every positive mass, there is the sequence of Dirac tensor-localizations, which provides a complete set of inequivalent irreducible causal localizations. They obey the principle of special relativity and are fully Poincaré covariant. The boosters are determined by the causal position operator and the other Poincaré generators. The localization with minimal spinor dimension is the Dirac localization. Thus, the Dirac equation is derived here as a mere consequence of the principle of causality. Moreover, the higher tensor-localizations, not known so far, follow from Dirac’s localization by a simple construction. The probability of localization for positive energy states results to be described by causal positive operator valued (PO-) localizations, which are the traces of the causal localizations on the subspaces of positive energy. These causal Poincaré covariant PO-localizations for every irreducible massive relativistic system were, all the more, not known before. They are shown to be separated. Hence, the positive energy systems can be localized within every open region by a suitable preparation as accurately as desired. Finally, the attempt is made to provide an interpretation of the PO-localization operators within the frame of conventional quantum mechanics attributing an important role to the negative energy states.
Mining Causality for Explanation Knowledge from Text
Institute of Scientific and Technical Information of China (English)
Chaveevan Pechsiri; Asanee Kawtrakul
2007-01-01
Mining causality is essential to provide a diagnosis. This research aims at extracting the causality existing within multiple sentences or EDUs (Elementary Discourse Unit). The research emphasizes the use of causality verbs because they make explicit in a certain way the consequent events of a cause, e.g., "Aphids suck the sap from rice leaves. Then leaves will shrink. Later, they will become yellow and dry.". A verb can also be the causal-verb link between cause and effect within EDU(s), e.g., "Aphids suck the sap from rice leaves causing leaves to be shrunk" ("causing" is equivalent to a causal-verb link in Thai). The research confronts two main problems: identifying the interesting causality events from documents and identifying their boundaries. Then, we propose mining on verbs by using two different machine learning techniques, Naive Bayes classifier and Support Vector Machine. The resulted mining rules will be used for the identification and the causality extraction of the multiple EDUs from text. Our multiple EDUs extraction shows 0.88 precision with 0.75 recall from Na'ive Bayes classifier and 0.89 precision with 0.76 recall from Support Vector Machine.
Causal localizations in relativistic quantum mechanics
International Nuclear Information System (INIS)
Causal localizations describe the position of quantum systems moving not faster than light. They are constructed for the systems with finite spinor dimension. At the center of interest are the massive relativistic systems. For every positive mass, there is the sequence of Dirac tensor-localizations, which provides a complete set of inequivalent irreducible causal localizations. They obey the principle of special relativity and are fully Poincaré covariant. The boosters are determined by the causal position operator and the other Poincaré generators. The localization with minimal spinor dimension is the Dirac localization. Thus, the Dirac equation is derived here as a mere consequence of the principle of causality. Moreover, the higher tensor-localizations, not known so far, follow from Dirac’s localization by a simple construction. The probability of localization for positive energy states results to be described by causal positive operator valued (PO-) localizations, which are the traces of the causal localizations on the subspaces of positive energy. These causal Poincaré covariant PO-localizations for every irreducible massive relativistic system were, all the more, not known before. They are shown to be separated. Hence, the positive energy systems can be localized within every open region by a suitable preparation as accurately as desired. Finally, the attempt is made to provide an interpretation of the PO-localization operators within the frame of conventional quantum mechanics attributing an important role to the negative energy states
Causality and momentum conservation from relative locality
Amelino-Camelia, Giovanni; Bianco, Stefano; Brighenti, Francesco; Buonocore, Riccardo Junior
2015-04-01
Theories involving curved momentum space, which recently became a topic of interest in the quantum-gravity literature, can, in general, violate many apparently robust aspects of our current description of the laws of physics, including relativistic invariance, locality, causality, and global momentum conservation. Here, we explore some aspects of the pathologies arising in generic theories involving curved momentum space for what concerns causality and momentum conservation. However, we also report results suggesting that when momentum space is maximally symmetric, and the theory is formulated relativistically, most notably including translational invariance with the associated relativity of spacetime locality, momentum is globally conserved and there is no violation of causality.
Causal localizations in relativistic quantum mechanics
International Nuclear Information System (INIS)
Sufficient and necessary conditions for causal localizations of massive relativistic systems are developed. It is proven that the Dirac- and the Dirac tensor-system are up to unitary equivalence the only irreducible causal localizations with finite spinor dimension which have a massive relativistic extension. A formula for this extension is given. The existence of arbitrarily good localized states of positive energy is shown. In the context of the causality condition a Paley-Wiener theorem for bounded measurable matrix-valued functions is proven.
The CMB in a Causal Set Universe
Zuntz, Joe
2007-01-01
We discuss Cosmic Microwave Background constraints on the causal set theory of quantum gravity, which has made testable predictions about the nature of dark energy. We flesh out previously discussed heuristic constraints by showing how the power spectrum of causal set dark energy fluctuations can be found from the overlap volumes of past light cones of points in the universe. Using a modified Boltzmann code we put constraints on the single parameter of the theory that are somewhat stronger than previous ones. We conclude that causal set theory cannot explain late-time acceleration without radical alterations to General Relativity.
Causality in 3D Massive Gravity Theories
Edelstein, Jose D; Kilicarslan, Ercan; Leoni, Matias; Tekin, Bayram
2016-01-01
We study the constraints coming from local causality requirement in various 2+1 dimensional dynamical theories of gravity. In Topologically Massive Gravity, with a single parity noninvariant massive degree of freedom, and in New Massive Gravity, with two massive spin-$2$ degrees of freedom, causality and unitarity are compatible with each other and they both require the Newton's constant to be negative. In their extensions, such as the Born-Infeld gravity and the minimal massive gravity the situation is similar and quite different from their higher dimensional counterparts, such as quadratic (e.g., Einstein-Gauss-Bonnet) or cubic theories, where causality and unitarity are in conflict.
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.
Causality, Knowledge and Coordination in Distributed Systems
Ben-Zvi, Ido
2011-01-01
Effecting coordination across remote sites in a distributed system is an essential part of distributed computing, and also an inherent challenge. In 1978, an analysis of communication in asynchronous systems was suggested by Leslie Lamport. Lamport's analysis determines a notion of temporal precedence, a sort of weak notion of time, which is otherwise missing in asynchronous systems. This notion has been extensively utilized in various applications. Yet the analysis is limited to systems that are asynchronous. In this thesis we go beyond by investigating causality in synchronous systems. In such systems, the boundaries of causal influence are not charted out exclusively by message passing. Here time itself, passing at a uniform (or almost uniform) rate for all processes, is also a medium by which causal influence may fan out. This thesis studies, and characterizes, the combinations of time and message passing that govern causal influence in synchronous systems. It turns out that knowledge based analysis [FHMV...
Wuthrich, Christian
2015-01-01
Unlike the relativity theory it seeks to replace, causal set theory has been interpreted to leave space for a substantive, though perhaps 'localized', form of 'becoming'. The possibility of fundamental becoming is nourished by the fact that the analogue of Stein's theorem from special relativity does not hold in causal set theory. Despite this, we find that in many ways, the debate concerning becoming parallels the well-rehearsed lines it follows in the domain of relativity. We present, however, some new twists and challenges. In particular, we show that a novel and exotic notion of becoming is compatible with causal sets. In contrast to the 'localized' becoming considered compatible with the dynamics of causal set theory by its advocates, our novel kind of becoming, while not answering to the typical A-theoretic demands, is 'global' and objective.
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.
Granger-causality maps of diffusion processes
Wahl, Benjamin; Feudel, Ulrike; Hlinka, Jaroslav; Wächter, Matthias; Peinke, Joachim; Freund, Jan A.
2016-02-01
Granger causality is a statistical concept devised to reconstruct and quantify predictive information flow between stochastic processes. Although the general concept can be formulated model-free it is often considered in the framework of linear stochastic processes. Here we show how local linear model descriptions can be employed to extend Granger causality into the realm of nonlinear systems. This novel treatment results in maps that resolve Granger causality in regions of state space. Through examples we provide a proof of concept and illustrate the utility of these maps. Moreover, by integration we convert the local Granger causality into a global measure that yields a consistent picture for a global Ornstein-Uhlenbeck process. Finally, we recover invariance transformations known from the theory of autoregressive processes.
The Gravity Dual of Boundary Causality
Engelhardt, Netta
2016-01-01
In gauge/gravity duality, points which are not causally related on the boundary cannot be causally related through the bulk; this is the statement of boundary causality. By the Gao-Wald theorem, the averaged null energy condition in the bulk is sufficient to ensure this property. Here we proceed in the converse direction: we derive a necessary as well as sufficient condition for the preservation of boundary causality under perturbative (quantum or stringy) corrections to the bulk. The condition that we find is a (background-dependent) constraint on the amount by which light cones can "open" over all null bulk geodesics. We show that this constraint is weaker than the averaged null energy condition.
Selecting appropriate cases when tracing causal mechanisms
DEFF Research Database (Denmark)
Beach, Derek; Pedersen, Rasmus Brun
2016-01-01
, ontological determinism, causal asymmetry and causal homogeneity and the importance of context. We then develop a set of case selection guidelines that are in methodological alignment with these underlying assumptions. Section 4 develops guidelines for research where the mechanism is the primary focus......The last decade has witnessed resurgence in the interest in studying the causal mechanisms linking causes and outcomes in the social sciences. This article explores the overlooked implications for case selection when tracing mechanisms using in-depth case studies. Our argument is that existing case...... selection guidelines are appropriate for research aimed at making cross-case claims about causal relationships, where case selection is primarily used to control for other causes. However, existing guidelines are not in alignment with case-based research that aims to trace mechanisms, where the goal is to...
Quantum probability assignment limited by relativistic causality.
Han, Yeong Deok; Choi, Taeseung
2016-01-01
Quantum theory has nonlocal correlations, which bothered Einstein, but found to satisfy relativistic causality. Correlation for a shared quantum state manifests itself, in the standard quantum framework, by joint probability distributions that can be obtained by applying state reduction and probability assignment that is called Born rule. Quantum correlations, which show nonlocality when the shared state has an entanglement, can be changed if we apply different probability assignment rule. As a result, the amount of nonlocality in quantum correlation will be changed. The issue is whether the change of the rule of quantum probability assignment breaks relativistic causality. We have shown that Born rule on quantum measurement is derived by requiring relativistic causality condition. This shows how the relativistic causality limits the upper bound of quantum nonlocality through quantum probability assignment. PMID:26971717
The Temporal Logic of Causal Structures
Kleinberg, Samantha
2012-01-01
Computational analysis of time-course data with an underlying causal structure is needed in a variety of domains, including neural spike trains, stock price movements, and gene expression levels. However, it can be challenging to determine from just the numerical time course data alone what is coordinating the visible processes, to separate the underlying prima facie causes into genuine and spurious causes and to do so with a feasible computational complexity. For this purpose, we have been developing a novel algorithm based on a framework that combines notions of causality in philosophy with algorithmic approaches built on model checking and statistical techniques for multiple hypotheses testing. The causal relationships are described in terms of temporal logic formulae, reframing the inference problem in terms of model checking. The logic used, PCTL, allows description of both the time between cause and effect and the probability of this relationship being observed. We show that equipped with these causal f...
Causality and the semantics of provenance
Cheney, James
2010-01-01
Provenance, or information about the sources, derivation, custody or history of data, has been studied recently in a number of contexts, including databases, scientific workflows and the Semantic Web. Many provenance mechanisms have been developed, motivated by informal notions such as influence, dependence, explanation and causality. However, there has been little study of whether these mechanisms formally satisfy appropriate policies or even how to formalize relevant motivating concepts such as causality. We contend that mathematical models of these concepts are needed to justify and compare provenance techniques. In this paper we review a theory of causality based on structural models that has been developed in artificial intelligence, and describe work in progress on a causal semantics for provenance graphs.
Causality and the Semantics of Provenance
Directory of Open Access Journals (Sweden)
James Cheney
2010-06-01
Full Text Available Provenance, or information about the sources, derivation, custody or history of data, has been studied recently in a number of contexts, including databases, scientific workflows and the Semantic Web. Many provenance mechanisms have been developed, motivated by informal notions such as influence, dependence, explanation and causality. However, there has been little study of whether these mechanisms formally satisfy appropriate policies or even how to formalize relevant motivating concepts such as causality. We contend that mathematical models of these concepts are needed to justify and compare provenance techniques. In this paper we review a theory of causality based on structural models that has been developed in artificial intelligence, and describe work in progress on using causality to give a semantics to provenance graphs.
Causality and the Semantics of Provenance
Cheney, James
2010-01-01
Provenance, or information about the sources, derivation, custody or history of data, has been studied recently in a number of contexts, including databases, scientific workflows and the Semantic Web. Many provenance mechanisms have been developed, motivated by informal notions such as influence, dependence, explanation and causality. However, there has been little study of whether these mechanisms formally satisfy appropriate policies or even how to formalize relevant motivating concepts such as causality. We contend that mathematical models of these concepts are needed to justify and compare provenance techniques. In this paper we review a theory of causality based on structural models that has been developed in artificial intelligence, and describe work in progress on using causality to give a semantics to provenance graphs.
Ten simple rules for dynamic causal modeling.
Stephan, K.E.; Penny, W.D.; Moran, R.J.; Ouden, H.E.M. den; Daunizeau, J.; Friston, K.J.
2010-01-01
Dynamic causal modeling (DCM) is a generic Bayesian framework for inferring hidden neuronal states from measurements of brain activity. It provides posterior estimates of neurobiologically interpretable quantities such as the effective strength of synaptic connections among neuronal populations and
A Causal Model for Diagnostic Reasoning
Institute of Scientific and Technical Information of China (English)
PENG Guoqiang; CHENG Hu
2000-01-01
Up to now, there have been many methods for knowledge representation and reasoning in causal networks, but few of them include the research on the coactions of nodes. In practice, ignoring these coactions may influence the accuracy of reasoning and even give rise to incorrect reasoning. In this paper, based on multilayer causal networks, the definitions on coaction nodes are given to construct a new causal network called Coaction Causal Network, which serves to construct a model of neural network for diagnosis followed by fuzzy reasoning, and then the activation rules are given and neural computing methods are used to finish the diagnostic reasoning. These methods are proved in theory and a method of computing the number of solutions for the diagnostic reasoning is given. Finally, the experiments and the conclusions are presented.
Causal Structure and Birefringence in Nonlinear Electrodynamics
de Melo, C. A. M.; Medeiros, L. G.; Pompeia, P. J.(Instituto de Fomento e Coordenação Industrial, Departamento de Ciência e Tecnologia Aeroespacial, Praça Mal. Eduardo Gomes 50, 12228-901, São José dos Campos, SP , Brazil)
2014-01-01
We investigate the causal structure of general nonlinear electrodynamics and determine which Lagrangians generate an effective metric conformal to Minkowski. We also proof that there is only one analytic nonlinear electrodynamics presenting no birefringence.
Deciding which chemical mixtures risk assessment methods work best for what mixtures
International Nuclear Information System (INIS)
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
The Causal Effects of Father Absence
McLanahan, Sara; TACH, LAURA; Schneider, Daniel
2013-01-01
The literature on father absence is frequently criticized for its use of cross-sectional data and methods that fail to take account of possible omitted variable bias and reverse causality. We review studies that have responded to this critique by employing a variety of innovative research designs to identify the causal effect of father absence, including studies using lagged dependent variable models, growth curve models, individual fixed effects models, sibling fixed effects models, natural ...
Inter-causal Independence and Heterogeneous Factorization
Zhang, Nevin Lianwen; Poole, David L
2013-01-01
It is well known that conditional independence can be used to factorize a joint probability into a multiplication of conditional probabilities. This paper proposes a constructive definition of inter-causal independence, which can be used to further factorize a conditional probability. An inference algorithm is developed, which makes use of both conditional independence and inter-causal independence to reduce inference complexity in Bayesian networks.
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 disorders and chronic fatigue syndrome, pain catastrophizing and causal beliefs were found to be related to perceived disability and prognosis. Furthermore, it has been argued with respect to whiplash t...
Causal Inference in Urban and Regional Economics
Nathaniel Baum-Snow; Fernando Ferreira
2014-01-01
Recovery of causal relationships in data is an essential part of scholarly inquiry in the social sciences. This chapter discusses strategies that have been successfully used in urban and regional economics for recovering such causal relationships. Essential to any successful empirical inquiry is careful consideration of the sources of variation in the data that identify parameters of interest. Interpretation of such parameters should take into account the potential for their heterogeneity as ...
Causal transmission in reduced-form models
Vassili Bazinas; Bent Nielsen
2015-01-01
We propose a method to explore the causal transmission of a catalyst variable through two endogenous variables of interest. The method is based on the reduced-form system formed from the conditional distribution of the two endogenous variables given the catalyst. The method combines elements from instru- mental variable analysis and Cholesky decomposition of structural vector autoregressions. We give conditions for uniqueness of the causal transmission.
Invited Commentary: Causal Diagrams and Measurement Bias
Hernán, Miguel A.; Cole, Stephen R.
2009-01-01
Causal inferences about the effect of an exposure on an outcome may be biased by errors in the measurement of either the exposure or the outcome. Measurement errors of exposure and outcome can be classified into 4 types: independent nondifferential, dependent nondifferential, independent differential, and dependent differential. Here the authors describe how causal diagrams can be used to represent these 4 types of measurement bias and discuss some problems that arise when using measured expo...
A Definition and Graphical Representation for Causality
Heckerman, David; Shachter, Ross D.
2013-01-01
We present a precise definition of cause and effect in terms of a fundamental notion called unresponsiveness. Our definition is based on Savage's (1954) formulation of decision theory and departs from the traditional view of causation in that our causal assertions are made relative to a set of decisions. An important consequence of this departure is that we can reason about cause locally, not requiring a causal explanation for every dependency. Such local reasoning can be beneficial because i...
Causales de ausencia de responsabilidad penal
Directory of Open Access Journals (Sweden)
Jaime Sandoval Fernández
2003-01-01
Full Text Available Este trabajo se ocupa de las causales de ausencia de responsabilidad penal, especialmente de aquellas que tienen efecto en el injusto. Como subtemas se delimita el concepto de responsabilidad penal y su ausencia. Se estudian las principales teorias a cerca de la relación tipicidad-antijuridicidad y su incidencia en el derecho penal colombiano. Por último contiene una propuesta acerca de cómo deberian agruparse las causales del arto 32 C. PlOO.
Mixture Density Mercer Kernels
National Aeronautics and Space Administration — We present a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian mixture...
Associative foundation of causal learning in rats.
Polack, Cody W; McConnell, Bridget L; Miller, Ralph R
2013-03-01
Are humans unique in their ability to interpret exogenous events as causes? We addressed this question by observing the behavior of rats for indications of causal learning. Within an operant motor-sensory preconditioning paradigm, associative surgical techniques revealed that rats attempted to control an outcome (i.e., a potential effect) by manipulating a potential exogenous cause (i.e., an intervention). Rats were able to generate an innocuous auditory stimulus. This stimulus was then paired with an aversive stimulus. The animals subsequently avoided potential generation of the predictive cue, but not if the aversive stimulus was subsequently devalued or the predictive cue was extinguished (Exp. 1). In Experiment 2, we demonstrated that the aversive stimulus we used was in fact aversive, that it was subject to devaluation, that the cue-aversive stimulus pairings did make the cue a conditioned stimulus, and that the cue was subject to extinction. In Experiments 3 and 4, we established that the decrease in leverpressing observed in Experiment 1 was goal-directed instrumental behavior rather than purely a product of Pavlovian conditioning. To the extent that interventions suggest causal reasoning, it appears that causal reasoning can be based on associations between contiguous exogenous events. Thus, contiguity appears capable of establishing causal relationships between exogenous events. Our results challenge the widely held view that causal learning is uniquely human, and suggest that causal learning is explicable in an associative framework. PMID:22562460
Some properties of explosive mixtures containing peroxides
International Nuclear Information System (INIS)
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, E0, 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 E0 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
Device-independent test of causal order and relations to fixed-points
Baumeler, Ämin; Wolf, Stefan
2016-03-01
Bell non-local correlations cannot be naturally explained in a fixed causal structure. This serves as a motivation for considering models where no global assumption is made beyond logical consistency. The assumption of a fixed causal order between a set of parties, together with free randomness, implies device-independent inequalities—just as the assumption of locality does. It is known that local validity of quantum theory is consistent with violating such inequalities. Moreover, for three parties or more, even the (stronger) assumption of local classical probability theory plus logical consistency allows for violating causal inequalities. Here, we show that a classical environment (with which the parties interact), possibly containing loops, is logically consistent if and only if whatever the involved parties do, there is exactly one fixed-point, the latter being representable as a mixture of deterministic fixed-points. We further show that the non-causal view allows for a model of computation strictly more powerful than computation in a world of fixed causal orders.
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...
Compositional Adjustment of Dirichlet Mixture Priors
Ye, Xugang; Yu, Yi-Kuo; Altschul, Stephen F.
2010-01-01
Dirichlet mixture priors provide a Bayesian formalism for scoring alignments of protein profiles to individual sequences, which can be generalized to constructing scores for multiple-alignment columns. A Dirichlet mixture is a probability distribution over multinomial space, each of whose components can be thought of as modeling a type of protein position. Applied to the simplest case of pairwise sequence alignment, a Dirichlet mixture is equivalent to an implied symmetric substitution matrix...
Recursive unsupervised learning of finite mixture models
Zivkovic, Zoran; Heijden, van der Ferdinand
2004-01-01
There are two open problems when finite mixture densities are used to model multivariate data: the selection of the number of components and the initialization. In this paper, we propose an online (recursive) algorithm that estimates the parameters of the mixture and that simultaneously selects the
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.
Quantum causality in closed timelike curves
Korotaev, S. M.; Kiktenko, E. O.
2015-08-01
Although general relativity allows the existence of closed timelike curves (CTCs), self-consistency problems arise (the ‘grandfather paradox’ among others). It is known that quantum mechanical consideration of the matter formally removes all the paradoxes, but the questions about causal structure remain. On the other hand, the idea of postselected CTCs (P-CTC) in quantum teleportation has know been put forward and experimentally implemented. We consider these problems with the aid of quantum causal analysis, where causality is defined without invoking the time relation. It implements the Cramer principle of weak causality, which admits time reversal in entangled states. We analyze Deutsch CTCs (D-CTC) with different kinds of interactions between the chronology-violating and chronology-respecting particles, with refined inferences about mixedness, quantum/classical correlations, entanglement and thermodynamics in the D-CTC. The main result is that time reversal causality can really exist, however, the final quantum state does not place retrospective constraints on the initial state, instead the final state can influence the state inside the D-CTC. This is effectively the implementation of Novikov self-consistency principle. The P-CTC has radically different properties; in particular, if the initial state was pure, the final state is always pure too. Self-consistency is controlled by the initial state-dependent traversability of the P-CTC.
Shear viscosity of liquid mixtures: Mass dependence
International Nuclear Information System (INIS)
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)
Causality, initial conditions and inflationary magnetogenesis
Tsagas, Christos G
2016-01-01
The post-inflationary evolution of inflation-produced magnetic fields, conventional or not, can change dramatically when two fundamental issues are accounted for. The first is causality, which demands that local physical processes can never affect superhorizon perturbations. The second is the nature of the transition from inflation to reheating and then to the radiation era, which determine the initial conditions at the start of these epochs. Technically, the latter issue can be addressed by appealing to Israel's junction conditions. Causality implies that inflationary magnetic fields dot not freeze into the matter until they have re-entered the causal horizon. The nature of cosmological transitions and the associated initial conditions, on the other hand, determine the large-scale magnetic evolution after inflation. Put together, the two can slow down the adiabatic decay of superhorizon-sized magnetic fields throughout their post-inflationary life and thus lead to considerably stronger residual strengths. Th...
Causal Mediation Analyses for Randomized Trials.
Lynch, Kevin G; Cary, Mark; Gallop, Robert; Ten Have, Thomas R
2008-01-01
In the context of randomized intervention trials, we describe causal methods for analyzing how post-randomization factors constitute the process through which randomized baseline interventions act on outcomes. Traditionally, such mediation analyses have been undertaken with great caution, because they assume that the mediating factor is also randomly assigned to individuals in addition to the randomized baseline intervention (i.e., sequential ignorability). Because the mediating factors are typically not randomized, such analyses are unprotected from unmeasured confounders that may lead to biased inference. We review several causal approaches that attempt to reduce such bias without assuming that the mediating factor is randomized. However, these causal approaches require certain interaction assumptions that may be assessed if there is enough treatment heterogeneity with respect to the mediator. We describe available estimation procedures in the context of several examples from the literature and provide resources for software code. PMID:19484136
Bulk viscous cosmology with causal transport theory
International Nuclear Information System (INIS)
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 || cb2 ∼−8
The causal meaning of Hamilton's rule.
Okasha, Samir; Martens, Johannes
2016-03-01
Hamilton's original derivation of his rule for the spread of an altruistic gene (rb>c) assumed additivity of costs and benefits. Recently, it has been argued that an exact version of the rule holds under non-additive pay-offs, so long as the cost and benefit terms are suitably defined, as partial regression coefficients. However, critics have questioned both the biological significance and the causal meaning of the resulting rule. This paper examines the causal meaning of the generalized Hamilton's rule in a simple model, by computing the effect of a hypothetical experiment to assess the cost of a social action and comparing it to the partial regression definition. The two do not agree. A possible way of salvaging the causal meaning of Hamilton's rule is explored, by appeal to R. A. Fisher's 'average effect of a gene substitution'. PMID:27069669
Causal inheritance in plane wave quotients
International Nuclear Information System (INIS)
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
Causal inheritence in plane wave quotients
Energy Technology Data Exchange (ETDEWEB)
Hubeny, Veronika E.; Rangamani, Mukund; Ross, Simon F.
2003-11-24
We investigate the appearance of closed timelike curves in quotients of plane waves along spacelike isometries. First we formulate a necessary and sufficient condition for a quotient of a general spacetime to preserve stable causality. We explicitly show that the plane waves are stably causal; in passing, we observe that some pp-waves are not even distinguishing. We then consider the classification of all quotients of the maximally supersymmetric ten-dimensional plane wave under a spacelike isometry, and show that the quotient will lead to closed timelike curves iff the isometry involves a translation along the u direction. The appearance of these closed timelike curves is thus connected to the special properties of the light cones in plane wave spacetimes. We show that all other quotients preserve stable causality.
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.
Hume’s understanding of causal explanation
Directory of Open Access Journals (Sweden)
Stefanović Igor
2015-01-01
Full Text Available This article deals with actuality of Hume’s positive thesis about causality, specifically in modern science. According to Dauer, Hume in his Treatise of Human Nature does not deal with scientific theory which allows us, in modern times, to come to the truth, and then necessity. Also, he claims that observation alone, without theory is useless, which is the reason why we need science to predict future events. I intend to show that all three claims are incorrect, and to show an intimate connection of causality and our intuitions.
A causally connected superluminal Warp Drive spacetime
Loup, F; Waite, D; Halerewicz, E F; Stabno, M; Kuntzman, M; Sims, R
2002-01-01
It will be shown that while horizons do not exist for warp drive spacetimes traveling at subluminal velocities horizons begin to develop when a warp drive spacetime reaches luminal velocities. However it will be shown that the control region of a warp drive ship lie within the portion of the warped region that is still causally connected to the ship even at superluminal velocities, therefore allowing a ship to slow to subluminal velocities. Further it is shown that the warped regions which are causally disconnected from a warp ship have no correlation to the ship velocity.
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....
Causal Entropy Bound for a Spacelike Region
Brustein, R.; Veneziano, G.
2000-06-01
The identification of a causal-connection scale motivates us to propose a new covariant bound on entropy within a generic spacelike region. This ``causal entropy bound,'' scaling as EV, and thus lying around the geometric mean of Bekenstein's S/ER and holographic S/A bounds, is checked in various ``critical'' situations. In the case of limited gravity, Bekenstein's bound is the strongest while naive holography is the weakest. In the case of strong gravity, our bound and Bousso's holographic bound are stronger than Bekenstein's, while naive holography is too tight, and hence typically wrong.
Mixture Experiments and their Application in Agricultural Research
Irum Raza; M. Asif Masood; Rashid Mahmood
2013-01-01
The present study was designed to show the applicability of Mixture designs in Agricultural Research System and to fit an appropriate mixture regression model making response variables as functions of the proportions of the mixture components. Data on four components namely neem oil, garlic oil, clove oil and tobacco extract (ml) were collected from field experiment conducted by Honeybee Research Institute, NARC. The main goal of the experiment was to check whether blending two components hav...
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...
Chowdhury, Enhad A.; Richardson, Judith D; Holman, Geoffrey D; Tsintzas, Kostas; Thompson, Dylan; Betts, James A
2016-01-01
Background: The causal nature of associations between breakfast and health remain unclear in obese individuals. Objective: We sought to conduct a randomized controlled trial to examine causal links between breakfast habits and components of energy balance in free-living obese humans. Design: The Bath Breakfast Project is a randomized controlled trial with repeated measures at baseline and follow-up among a cohort in South West England aged 21–60 y with dual-energy X-ray absorptiometry–derived...
A Causal Construction of Diffusion Processes
Banek, Tadeusz
2010-01-01
A simple nonlinear integral equation for Ito's map is obtained. Although, it does not include stochastic integrals, it does give causal construction of diffusion processes which can be easily implemented by iteration systems. Applications in financial modelling and extension to fBm are discussed.
Causal dissipative hydrodynamics for heavy ion collisions
Chaudhuri, A K
2011-01-01
We briefly discuss the recent developments in causal dissipative hydrodynamic for relativistic heavy ion collisions. Phenomenological estimate of QGP viscosity over entropy ratio from several experimental data, e.g. STAR's $\\phi$ meson data, centrality dependence of elliptic flow, universal scaling elliptic flow etc. are discussed. QGP viscosity, extracted from hydrodynamical model analysis can have very large systematic uncertainty due to uncertain initial conditions.
Causality and analyticity in quantum fields theory
International Nuclear Information System (INIS)
This is a presentation of results on the causal and analytical structure of Green functions and on the collision amplitudes in fields theories, for massive particles of one type, with a positive mass and a zero spin value. (A.B.)
Manipulation and the causal Markov condition
Hausman, Daniel; Woodward, James
2004-01-01
This paper explores the relationship between a manipulability conception of causation and the causal Markov condition (CM). We argue that violations of CM also violate widely shared expectations—implicit in the manipulability conception—having to do with the absence of spontaneous correlations. They also violate expectations concerning the connection between independence or dependence relationships in the presence and absence of interventions.
Escaping Myopia: Teaching Students about Historical Causality
Waring, Scott M.
2010-01-01
There are so many aspects to teaching history that are vital to creating well-rounded historical thinkers, but one of the most fundamental and most overlooked elements is the idea of causality. Far too many students do not understand the idea of causation, that there are multiple reasons for why historical events occurred and transpired in the way…
Causality and Teleology in High School Biology.
Tamir, Pinchas
1985-01-01
Ability to distinguish between causal (cause-effect) and teleological (means-ends) explanations was measured in 1905 twelfth-grade biology students and found to be dependent on student knowledge. Although the inability to make these distinctions contributes to misconceptions in biology, appropriate instruction can easily remedy the problem. Sample…
Causal and Teleological Explanations in Biology
Yip, Cheng-Wai
2009-01-01
A causal explanation in biology focuses on the mechanism by which a biological process is brought about, whereas a teleological explanation considers the end result, in the context of the survival of the organism, as a reason for certain biological processes or structures. There is a tendency among students to offer a teleological explanation…
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…
Heterogeneous Causal Effects and Sample Selection Bias
DEFF Research Database (Denmark)
Breen, Richard; Choi, Seongsoo; Holm, Anders
2015-01-01
The role of education in the process of socioeconomic attainment is a topic of long standing interest to sociologists and economists. Recently there has been growing interest not only in estimating the average causal effect of education on outcomes such as earnings, but also in estimating how cau...
Inferring causality from noisy time series data
DEFF Research Database (Denmark)
Mønster, Dan; Fusaroli, Riccardo; Tylén, Kristian;
2016-01-01
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...
Linear Response Laws and Causality in Electrodynamics
Yuffa, Alex J.; Scales, John A.
2012-01-01
Linear response laws and causality (the effect cannot precede the cause) are of fundamental importance in physics. In the context of classical electrodynamics, students often have a difficult time grasping these concepts because the physics is obscured by the intermingling of the time and frequency domains. In this paper, we analyse the linear…
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 setting.
Low temperature asphalt mixtures
Modrijan, Damjan
2006-01-01
This thesis presents the problem of manufacturing and building in the asphalt mixtures produced by the classical hot procedure and the possibility of manufacturing low temperature asphalt mixtures.We will see the main advantages of low temperature asphalt mixtures prepared with bitumen with organic addition Sasobit and compare it to the classical asphalt mixtures. The advantages and disadvantages of that are valued in the practical example in the conclusion.
Okpala, Chukwubuike
2015-01-01
This thesis work focuses on compounding a mechanical purge mixture for extruders. The base resin for making the purge mixture is recycled High Density Polyethylene chosen for its high density and good processing temperature. The additives are mainly clay and sili-con dioxide added as filler and scrubbing materials respectively. The purge mixture was produced by mixing the base resin and additives in percentage ratios into five places la-beled A, B, C, D, and E. the mixtures were extruded and ...
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.
The causal link between energy and output growth: Evidence from Markov switching Granger causality
International Nuclear Information System (INIS)
In this paper we empirically investigate the causal link between energy consumption and economic growth employing a Markov switching Granger causality analysis. We carry out our investigation using annual U.S. real GDP, total final energy consumption and total primary energy consumption data which cover the period between 1968 and 2010. We find that there are significant changes in the causal relation between energy consumption and economic growth over the sample period under investigation. Our results show that total final energy consumption and total primary energy consumption have significant predictive content for real economic activity in the U.S. economy. Furthermore, the causality running from energy consumption to output growth seems to be strongly apparent particularly during the periods of economic downturn and energy crisis. We also document that output growth has predictive power in explaining total energy consumption. Furthermore, the power of output growth in predicting total energy consumption is found to diminish after the mid of 1980s. - Highlights: • Total energy consumption has predictive content for real economic activity. • The causality from energy to output growth is apparent in the periods of recession. • The causality from energy to output growth is strong in the periods of energy crisis. • Output growth has predictive power in explaining total energy consumption. • The power of output growth in explaining energy diminishes after the mid of 1980s
Institute of Scientific and Technical Information of China (English)
王宝群; 罗保林; 林尊锦
2001-01-01
The maximum spouted pressure drop of multisi ze composition glass bead mixtures was investigated in a rectangularslot spout ed bed with a gas entry slot which width varies from 2mm to 6mm .The experimenta l results of single and multisize composition particle mixtures showed that th e maximum spouted pressure drop was strongly dependent on the particle size and its composition in the particle mixtures, the static bed height and the gas entr y slot. In the present work, regimes describing variation of maximum spouted pre ssure drop for multisize composition particle mixtures were obtained. An empir ical relation for the maximum spouted pressure drop ΔPms was determined t o be:ΔPms（1－ε）（ρs－ρf）gH＝0．023HDc－0．074HsDc0．028ρs－ρfρf－0．65∏ni＝1dpiDc－0．54Xi (n=3)%在150mm×50mm×1100mm的矩形喷动床中，研究了单一粒径体系和二组分及三组分混合粒径颗粒体系的最大喷动压降受颗粒粒径及粒度组成、静止床高和气体入口狭缝宽度的影响情况。实验采用宽度为2、4、6mm三种宽度的狭缝式气体分布板，实验物料为单一粒径分别为1、1.5、2mm的玻璃珠。实验表明矩形喷动床的最大喷动压降与上述三种影响因素都有关系。本文还给出了最大喷动压降随这三种因素变化的实验关联式。
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
Identification, Inference and Sensitivity Analysis for Causal Mediation Effects
Imai, Kosuke; Keele, Luke; Yamamoto, Teppei
2010-01-01
Causal mediation analysis is routinely conducted by applied researchers in a variety of disciplines. The goal of such an analysis is to investigate alternative causal mechanisms by examining the roles of intermediate variables that lie in the causal paths between the treatment and outcome variables. In this paper we first prove that under a particular version of sequential ignorability assumption, the average causal mediation effect (ACME) is nonparametrically identified. We compare our ident...
Institutional Investors and Stock Market Development: A Causality Study
Guler Aras; Alovsat Muslumov
2008-01-01
This article examines causality relationships between institutional investors and stock market development based on the panel data compiled from 23 OECD countries for the years 1982 through 2000. In order to test causality relationship, Sims’ causality test based on Granger definition of causality was used in our study. Our empirical results provide evidence that there are statistically significant positive relationship between institutional investors and stock market development. The develop...
Trimmed Granger causality between two groups of time series
Hung, Ying-Chao; Tseng, Neng-Fang; Balakrishnan, Narayanaswamy
2014-01-01
The identification of causal effects between two groups of time series has been an important topic in a wide range of applications such as economics, engineering, medicine, neuroscience, and biology. In this paper, a simplified causal relationship (called trimmed Granger causality) based on the context of Granger causality and vector autoregressive (VAR) model is introduced. The idea is to characterize a subset of “important variables” for both groups of time series so that the underlying cau...
A Bayesian Theory of Sequential Causal Learning and Abstract Transfer
Lu, Hongjing; Rojas, Randall R.; Beckers, Tom; Yuille, Alan L.
2016-01-01
Two key research issues in the field of causal learning are how people acquire causal knowledge when observing data that are presented sequentially, and the level of abstraction at which learning takes place. Does sequential causal learning solely involve the acquisition of specific cause-effect links, or do learners also acquire knowledge about…
Causality and Nonlocality as Axioms for Quantum Mechanics
Popescu, Sandu; Rohrlich, Daniel
1997-01-01
Quantum mechanics permits nonlocality - both nonlocal correlations and nonlocal equations of motion - while respecting relativistic causality. Is quantum mechanics the unique theory that reconciles nonlocality and causality? We consider two models, going beyond quantum mechanics, of nonlocality: "superquantum" correlations, and nonlocal "jamming" of correlations. These models are consistent with some definitions of nonlocality and causality.
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…
Sentencing goals, causal attributions, ideology, and personality.
Carroll, J S; Perkowitz, W T; Lurigio, A J; Weaver, F M
1987-01-01
Disparity in sentencing of criminals has been related to a variety of individual difference variables. We propose a framework establishing resonances or coherent patterns among sentencing goals, causal attributions, ideology, and personality. Two studies are described, one with law and criminology students, the other with probation officers. Relations among the different types of variables reveal two resonances among both students and officers. One comprises various conservative and moralistic elements: a tough, punitive stance toward crime; belief in individual causality for crime; high scores on authoritarianism, dogmatism, and internal locus of control; lower moral stage; and political conservatism. The second comprises various liberal elements: rehabilitation, belief in economic and other external determinants of crime, higher moral stage, and belief in the powers and responsibilities of government to correct social problems. Implications of these results are discussed for individual differences in sentencing, attribution theory, and attempts to reduce disparity. PMID:3820064
An insider's guide to quantum causal histories
International Nuclear Information System (INIS)
A review is given of recent work aimed at constructing a quantum theory of cosmology in which all observables refer to information measurable by observers inside the universe. At the classical level the algebra of observables should be modified to take into account the fact that observers can only give truth values to observables that have to do with their backwards light cone. The resulting algebra is a Heyting rather than a Boolean algebra. The complement is non-trivial and contains information about horizons and topology change. Representation of such observables quantum mechanically requires a many-Hilbert space formalism, in which different observers make measurements in different Hilbert spaces. I describe such a formalism, called 'quantum causal histories'; examples include causally evolving spin networks and quantum computers
Consistence beats causality in recommender systems
Zhu, Xuzhen; Hu, Zheng; Zhang, Ping; Zhou, Tao
2015-01-01
The explosive growth of information challenges people's capability in finding out items fitting to their own interests. Recommender systems provide an efficient solution by automatically push possibly relevant items to users according to their past preferences. Recommendation algorithms usually embody the causality from what having been collected to what should be recommended. In this article, we argue that in many cases, a user's interests are stable, and thus the previous and future preferences are highly consistent. The temporal order of collections then does not necessarily imply a causality relationship. We further propose a consistence-based algorithm that outperforms the state-of-the-art recommendation algorithms in disparate real data sets, including \\textit{Netflix}, \\textit{MovieLens}, \\textit{Amazon} and \\textit{Rate Your Music}.
A New Spin on Causality Constraints
Hartman, Thomas; Kundu, Sandipan
2016-01-01
Causality in a shockwave state is related to the analytic properties of a four-point correlation function. Extending recent results for scalar probes, we show that this constrains the couplings of the stress tensor to light spinning operators in conformal field theory, and interpret these constraints in terms of the interaction with null energy. For spin-1 and spin-2 conserved currents in four dimensions, the resulting inequalities are a subset of the Hofman-Maldacena conditions for positive energy deposition. It is well known that energy conditions in holographic theories are related to causality on the gravity side; our results make a connection on the CFT side, and extend it to non-holographic theories.
Normalizing the causality between time series
Liang, X San
2015-01-01
Recently, a rigorous yet concise formula has been derived to evaluate the information flow, and hence the causality in a quantitative sense, between time series. To assess the importance of a resulting causality, it needs to be normalized. The normalization is achieved through distinguishing three types of fundamental mechanisms that govern the marginal entropy change of the flow recipient. A normalized or relative flow measures its importance relative to other mechanisms. In analyzing realistic series, both absolute and relative information flows need to be taken into account, since the normalizers for a pair of reverse flows belong to two different entropy balances; it is quite normal that two identical flows may differ a lot in relative importance in their respective balances. We have reproduced these results with several autoregressive models. We have also shown applications to a climate change problem and a financial analysis problem. For the former, reconfirmed is the role of the Indian Ocean Dipole as ...
Closed timelike curves and causality violation
Lobo, Francisco S N
2010-01-01
The conceptual definition and understanding of time, both quantitatively and qualitatively is of the utmost difficulty and importance. As time is incorporated into the proper structure of the fabric of spacetime, it is interesting to note that General Relativity is contaminated with non-trivial geometries which generate closed timelike curves. A closed timelike curve (CTC) allows time travel, in the sense that an observer that travels on a trajectory in spacetime along this curve, may return to an event before his departure. This fact apparently violates causality, therefore time travel and it's associated paradoxes have to be treated with great caution. The paradoxes fall into two broad groups, namely the consistency paradoxes and the causal loops. A great variety of solutions to the Einstein field equations containing CTCs exist and it seems that two particularly notorious features stand out. Solutions with a tipping over of the light cones due to a rotation about a cylindrically symmetric axis and solution...
An insider's guide to quantum causal histories
Markopoulou, F
2000-01-01
A review is given of recent work aimed at constructing a quantum theory of cosmology in which all observables refer to information measurable by observers inside the universe. At the classical level the algebra of observables should be modified to take into account the fact that observers can only give truth values to observables that have to do with their backwards light cone. The resulting algebra is a Heyting rather than a Boolean algebra. The complement is non-trivial and contains information about horizons and topology change. Representation of such observables quantum mechanically requires a many-Hilbert space formalism, in which different observers make measurements in different Hilbert spaces. I describe such a formalism, called "quantum causal histories"; examples include causally evolving spin networks and quantum computers.
Tutorial for mixture-process experiments with an industrial application
Directory of Open Access Journals (Sweden)
Luiz Henrique Abreu Dal Bello
2011-12-01
Full Text Available This article presents a tutorial on mixture-process experiments and a case study of a chemical compound used in the delay mechanism for starting a rocket engine. The compound consists in a three-component mixture. Besides the mixture components, two process variables are considered. For the model selection, the use of an information criterion showed to be efficient in the case under study. A linear regression model was fitted. Through the developed model, the optimal proportions of the mixture components and the levels of the process variables were determined.
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 (2016), 022213/1-022213/9. ISSN 1539-3755 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: 2.288, year: 2014
Waves and causality in higher dimensions
Wesson, Paul S
2015-01-01
We give a new, wave-like solution of the field equations of five-dimensional relativity. In ordinary three-dimensional space, the waves resemble de Broglie or matter waves, whose puzzling behaviour can be better understood in terms of one or more extra dimensions. Causality is appropriately defined by a null higher-dimensional interval. It may be possible to test the properties of these waves in the laboratory.
Information causality as a physical principle.
Pawłowski, Marcin; Paterek, Tomasz; Kaszlikowski, Dagomir; Scarani, Valerio; Winter, Andreas; Zukowski, Marek
2009-10-22
Quantum physics has remarkable distinguishing characteristics. For example, it gives only probabilistic predictions (non-determinism) and does not allow copying of unknown states (no-cloning). Quantum correlations may be stronger than any classical ones, but information cannot be transmitted faster than light (no-signalling). However, these features do not uniquely define quantum physics. A broad class of theories exist that share such traits and allow even stronger (than quantum) correlations. Here we introduce the principle of 'information causality' and show that it is respected by classical and quantum physics but violated by all no-signalling theories with stronger than (the strongest) quantum correlations. The principle relates to the amount of information that an observer (Bob) can gain about a data set belonging to another observer (Alice), the contents of which are completely unknown to him. Using all his local resources (which may be correlated with her resources) and allowing classical communication from her, the amount of information that Bob can recover is bounded by the information volume (m) of the communication. Namely, if Alice communicates m bits to Bob, the total information obtainable by Bob cannot be greater than m. For m = 0, information causality reduces to the standard no-signalling principle. However, no-signalling theories with maximally strong correlations would allow Bob access to all the data in any m-bit subset of the whole data set held by Alice. If only one bit is sent by Alice (m = 1), this is tantamount to Bob's being able to access the value of any single bit of Alice's data (but not all of them). Information causality may therefore help to distinguish physical theories from non-physical ones. We suggest that information causality-a generalization of the no-signalling condition-might be one of the foundational properties of nature. PMID:19847260
Causal Mediation Analyses for Randomized Trials
Lynch, Kevin G.; Cary, Mark; Gallop, Robert; Ten Have, Thomas R.
2008-01-01
In the context of randomized intervention trials, we describe causal methods for analyzing how post-randomization factors constitute the process through which randomized baseline interventions act on outcomes. Traditionally, such mediation analyses have been undertaken with great caution, because they assume that the mediating factor is also randomly assigned to individuals in addition to the randomized baseline intervention (i.e., sequential ignorability). Because the mediating factors are t...
Isocausal spacetimes may have different causal boundaries
Energy Technology Data Exchange (ETDEWEB)
Flores, J L; Herrera, J [Departamento de Algebra, Geometria y Topologia, Facultad de Ciencias, Universidad de Malaga, Campus Teatinos, 29071 Malaga (Spain); Sanchez, M, E-mail: floresj@agt.cie.uma.es, E-mail: jherrera@uma.es, E-mail: sanchezm@ugr.es [Departamento de Geometria y Topologia, Facultad de Ciencias, Universidad de Granada, Avenida Fuentenueva s/n, 18071 Granada (Spain)
2011-09-07
We construct an example which shows that two isocausal spacetimes, in the sense introduced recently in GarcIa-Parrado and Senovilla (2003 Class. Quantum Grav. 20 625-64), may have c-boundaries which are not equal (more precisely, not equivalent, as no bijection between the completions can preserve all the binary relations induced by causality). This example also suggests that isocausality can be useful for the understanding and computation of the c-boundary.
Representation and reasoning: a causal model approach
Nikolic, M.
2014-01-01
How do we represent our world and how do we use these representations to reason about it? The three studies reported in this thesis explored different aspects of the answer to this question. Even though these investigations offered diverse angles, they all originated from the same psychological theory of representation and reasoning. This is the idea that people represent the world and reason about it by constructing dynamic qualitative causal networks. The first study investigated how mock j...
Reconstructing Causal Biological Networks through Active Learning
Cho, Hyunghoon; Berger, Bonnie; Peng, Jian
2016-01-01
Reverse-engineering of biological networks is a central problem in systems biology. The use of intervention data, such as gene knockouts or knockdowns, is typically used for teasing apart causal relationships among genes. Under time or resource constraints, one needs to carefully choose which intervention experiments to carry out. Previous approaches for selecting most informative interventions have largely been focused on discrete Bayesian networks. However, continuous Bayesian networks are ...
A causally connected superluminal Warp Drive spacetime
Loup, F.; Held, R.; Waite, D; Halerewicz, Jr., E.; Stabno, M.; Kuntzman, M.; Sims, R.
2002-01-01
It will be shown that while horizons do not exist for warp drive spacetimes traveling at subluminal velocities horizons begin to develop when a warp drive spacetime reaches luminal velocities. However it will be shown that the control region of a warp drive ship lie within the portion of the warped region that is still causally connected to the ship even at superluminal velocities, therefore allowing a ship to slow to subluminal velocities. Further it is shown that the warped regions which ar...
Extending Temporal Causal Graph For Diagnosis Problems
Belouaer, Lamia; Bouzid, Maroua; Mouhoub, Malek
2009-01-01
Poster International audience Abductive diagnosis (Brusoni et al. 1998) consists in finding explanations for given observations by using rules of inference based on the causal dependences of the system. Time is important for abductive diagnosis (Hamscher and Davis 1984), (Hamscher, Console, and Kleer 1992). There are few works in litterature handling temporal diagnosis (Kautz 1999). They differ in the expressiveness of the temporal knowledge. We propose a new approach for Temporal Diagn...
Imposing causality on a matrix model
International Nuclear Information System (INIS)
We introduce a new matrix model that describes Causal Dynamical Triangulations (CDT) in two dimensions. In order to do so, we introduce a new, simpler definition of 2D CDT and show it to be equivalent to the old one. The model makes use of ideas from dually weighted matrix models, combined with multi-matrix models, and can be studied by the method of character expansion.
Relativistic causality and position space renormalization
Todorov, Ivan
2016-01-01
We survey the causal position space renormalization with a special attention to the role of Raymond Stora in the development of the subject. Renormalization is effected by subtracting pole terms in analytically regularized amplitudes. Residues are identified with periods whose relation to recent development in number theory is emphasized. We demonstrate the possibility of integration over internal vertices in the case of a (massless) conformal theory and display the dilation and the conformal anomaly.
Extracting causal relationships from Chinese written text
Liu, X; Hoede, C.
2002-01-01
Expert systems form one of the most important research areas in Artificial Intelligence. The main parts in expert systems are knowledge bases and inference engines. In the knowledge bases the main knowledge is knowledge in the form of ``IF-THEN" statements. In knowledge graphs, a new form of knowledge representation, the ``IF-THEN" statements are tied up with causal operators (CAU-relations). In this paper, we picked out some Chinese operators with ``CAU" meaning, and investigated these opera...
Causality and the semantics of provenance
James Cheney
2010-01-01
Provenance, or information about the sources, derivation, custody or history of data, has been studied recently in a number of contexts, including databases, scientific workflows and the Semantic Web. Many provenance mechanisms have been developed, motivated by informal notions such as influence, dependence, explanation and causality. However, there has been little study of whether these mechanisms formally satisfy appropriate policies or even how to formalize relevant motivating concepts suc...
Ten simple rules for dynamic causal modeling
Stephan, K E; Penny, W.D.; Moran, R. J.; den Ouden, H.E.M.; Daunizeau, J.; Friston, K J
2010-01-01
Dynamic causal modeling (DCM) is a generic Bayesian framework for inferring hidden neuronal states from measurements of brain activity. It provides posterior estimates of neurobiologically interpretable quantities such as the effective strength of synaptic connections among neuronal populations and their context-dependent modulation. DCM is increasingly used in the analysis of a wide range of neuroimaging and electrophysiological data. Given the relative complexity of DCM, compared to convent...
Causality detection and turbulence in fusion plasmas
Van Milligen, B Ph; Birkenmeier, G.; Ramisch, M.; Estrada, T.; Hidalgo, C.; A. Alonso
2013-01-01
This work explores the potential of an information-theoretical causality detection method for unraveling the relation between fluctuating variables in complex nonlinear systems. The method is tested on some simple though nonlinear models, and guidelines for the choice of analysis parameters are established. Then, measurements from magnetically confined fusion plasmas are analyzed. The selected data bear relevance to the all-important spontaneous confinement transitions often observed in fusio...
York eHagmayer; Neele eEngelmann
2014-01-01
Cognitive psychological research focusses on causal learning and reasoning while cognitive anthropological and social science research tend to focus on systems of beliefs. Our aim was to explore how these two types of research can inform each other. Cognitive psychological theories (causal model theory and causal Bayes nets) were used to derive predictions for systems of causal beliefs. These predictions were then applied to lay theories of depression as a specific test case. A systematic...
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...
Causality, initial conditions, and inflationary magnetogenesis
Tsagas, Christos G.
2016-05-01
The post-inflationary evolution of inflation-produced magnetic fields, conventional or not, can change dramatically when two fundamental issues are accounted for. The first is causality, which demands that local physical processes can never affect superhorizon perturbations. The second is the nature of the transition from inflation to reheating and then to the radiation era, which determine the initial conditions at the start of these epochs. Causality implies that inflationary magnetic fields do not freeze into the matter until they have re-entered the causal horizon. The nature of the cosmological transitions and the associated initial conditions, on the other hand, determine the large-scale magnetic evolution after inflation. Put together, the two can slow down the adiabatic magnetic decay on superhorizon scales throughout the Universe's post-inflationary evolution and thus lead to considerably stronger residual magnetic fields. This is "good news" for both the conventional and the nonconventional scenarios of cosmic magnetogenesis. Mechanisms operating outside standard electromagnetism, in particular, do not need to enhance their fields too much during inflation in order to produce seeds that can feed the galactic dynamo today. In fact, even conventionally produced inflationary magnetic fields might be able to sustain the dynamo.
A causal dispositional account of fitness.
Triviño, Vanessa; Nuño de la Rosa, Laura
2016-09-01
The notion of fitness is usually equated to reproductive success. However, this actualist approach presents some difficulties, mainly the explanatory circularity problem, which have lead philosophers of biology to offer alternative definitions in which fitness and reproductive success are distinguished. In this paper, we argue that none of these alternatives is satisfactory and, inspired by Mumford and Anjum's dispositional theory of causation, we offer a definition of fitness as a causal dispositional property. We argue that, under this framework, the distinctiveness that biologists usually attribute to fitness-namely, the fact that fitness is something different from both the physical traits of an organism and the number of offspring it leaves-can be explained, and the main problems associated with the concept of fitness can be solved. Firstly, we introduce Mumford and Anjum's dispositional theory of causation and present our definition of fitness as a causal disposition. We explain in detail each of the elements involved in our definition, namely: the relationship between fitness and the functional dispositions that compose it, the emergent character of fitness, and the context-sensitivity of fitness. Finally, we explain how fitness and realized fitness, as well as expected and realized fitness are distinguished in our approach to fitness as a causal disposition. PMID:27338570
Bayesian Discovery of Linear Acyclic Causal Models
Hoyer, Patrik O
2012-01-01
Methods for automated discovery of causal relationships from non-interventional data have received much attention recently. A widely used and well understood model family is given by linear acyclic causal models (recursive structural equation models). For Gaussian data both constraint-based methods (Spirtes et al., 1993; Pearl, 2000) (which output a single equivalence class) and Bayesian score-based methods (Geiger and Heckerman, 1994) (which assign relative scores to the equivalence classes) are available. On the contrary, all current methods able to utilize non-Gaussianity in the data (Shimizu et al., 2006; Hoyer et al., 2008) always return only a single graph or a single equivalence class, and so are fundamentally unable to express the degree of certainty attached to that output. In this paper we develop a Bayesian score-based approach able to take advantage of non-Gaussianity when estimating linear acyclic causal models, and we empirically demonstrate that, at least on very modest size networks, its accur...
Reliability of the Granger causality inference
International Nuclear Information System (INIS)
How to characterize information flows in physical, biological, and social systems remains a major theoretical challenge. Granger causality (GC) analysis has been widely used to investigate information flow through causal interactions. We address one of the central questions in GC analysis, that is, the reliability of the GC evaluation and its implications for the causal structures extracted by this analysis. Our work reveals that the manner in which a continuous dynamical process is projected or coarse-grained to a discrete process has a profound impact on the reliability of the GC inference, and different sampling may potentially yield completely opposite inferences. This inference hazard is present for both linear and nonlinear processes. We emphasize that there is a hazard of reaching incorrect conclusions about network topologies, even including statistical (such as small-world or scale-free) properties of the networks, when GC analysis is blindly applied to infer the network topology. We demonstrate this using a small-world network for which a drastic loss of small-world attributes occurs in the reconstructed network using the standard GC approach. We further show how to resolve the paradox that the GC analysis seemingly becomes less reliable when more information is incorporated using finer and finer sampling. Finally, we present strategies to overcome these inference artifacts in order to obtain a reliable GC result
Cohomology Methods in Causal Perturbation Theory
International Nuclear Information System (INIS)
Various problems in perturbation theory of (quantum) gauge models can be rephrased in the language of cohomology theory. This was already noticed in the functional formulation of perturbative gauge theories. Causal perturbation theory is a fully quantum approach: is works only with the chronological products which are defined as operator-valued distributions in the Fock space of the model. The use of causal perturbation theory leads to similar cohomology problems; the main difference with respect to the functional methods comes from the fact that the gauge transformation of the causal approach is, essentially, the linear part of the non-linear BRST transformation.Using these methods it is possible to give a nice determination of the interaction Lagrangians for gauge models (Yang-Mills and gravitation in the linear approximation); one obtains with this method the unicity of the interaction Lagrangian up to trivial terms. The case of quantum gravity is highly non-trivial and can be generalized with this method to the massive graviton case. Going to higher orders of perturbation theory one finds quantum anomalies. Again the cohomological methods can be used to determine the generic form of these anomalies. Finally, one can investigate the arbitrariness of the chronological products in higher orders and reduce this problem to cohomology methods also.
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...... 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....
Mixture Multi-Step-Ahead Prediction
Czech Academy of Sciences Publication Activity Database
Nagy, Ivan; Suzdaleva, Evgenia; Mlynářová, Tereza
Piraeus: ISAST: International Society for the Advancement of Science and Technology, 2015, s. 727-738. ISBN 978-618-5180-05-8. [The 16th conference of the Applied Stochastic Models and Data Analysis (ASMDA) International Society. Piraeus (GR), 30.06.2015-4.07.2015] R&D Projects: GA ČR GA15-03564S; GA MŠk 7H14004; GA MŠk(BE) 7H14005 Institutional support: RVO:67985556 Keywords : mixture model * mixture prediction * recursive mixture estimation * dynamic pointer * active component Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2015/ZS/suzdaleva-0450479.pdf
Identifying causal variants at loci with multiple signals of association.
Hormozdiari, Farhad; Kostem, Emrah; Kang, Eun Yong; Pasaniuc, Bogdan; Eskin, Eleazar
2014-10-01
Although genome-wide association studies have successfully identified thousands of risk loci for complex traits, only a handful of the biologically causal variants, responsible for association at these loci, have been successfully identified. Current statistical methods for identifying causal variants at risk loci either use the strength of the association signal in an iterative conditioning framework or estimate probabilities for variants to be causal. A main drawback of existing methods is that they rely on the simplifying assumption of a single causal variant at each risk locus, which is typically invalid at many risk loci. In this work, we propose a new statistical framework that allows for the possibility of an arbitrary number of causal variants when estimating the posterior probability of a variant being causal. A direct benefit of our approach is that we predict a set of variants for each locus that under reasonable assumptions will contain all of the true causal variants with a high confidence level (e.g., 95%) even when the locus contains multiple causal variants. We use simulations to show that our approach provides 20-50% improvement in our ability to identify the causal variants compared to the existing methods at loci harboring multiple causal variants. We validate our approach using empirical data from an expression QTL study of CHI3L2 to identify new causal variants that affect gene expression at this locus. CAVIAR is publicly available online at http://genetics.cs.ucla.edu/caviar/. PMID:25104515
Perceptual processing strategy and exposure influence the perception of odor mixtures
Le Berre, Elodie; Thomas-Danguin, Thierry; Beno, Noëlle; Coureaud, Gérard; Etievant, Patrick; Prescott, John
2008-01-01
In flavor perception, both experience with the components of odor/taste mixtures and the cognitive strategy used to examine the interactions between the components influence the overall mixture perception. However, the effect of these factors on odor mixtures perception has never been studied. The present study aimed at evaluating whether 1) previous exposure to the odorants included in a mixture or 2) the synthetic or analytic strategy engaged during odorants mixture evaluation determines od...
Youssofzadeh, Vahab; Prasad, Girijesh; Naeem, Muhammad; Wong-Lin, KongFatt
2016-01-01
Partial Granger causality (PGC) has been applied to analyse causal functional neural connectivity after effectively mitigating confounding influences caused by endogenous latent variables and exogenous environmental inputs. However, it is not known how this connectivity obtained from PGC evolves over time. Furthermore, PGC has yet to be tested on realistic nonlinear neural circuit models and multi-trial event-related potentials (ERPs) data. In this work, we first applied a time-domain PGC technique to evaluate simulated neural circuit models, and demonstrated that the PGC measure is more accurate and robust in detecting connectivity patterns as compared to conditional Granger causality and partial directed coherence, especially when the circuit is intrinsically nonlinear. Moreover, the connectivity in PGC settles faster into a stable and correct configuration over time. After method verification, we applied PGC to reveal the causal connections of ERP trials of a mismatch negativity auditory oddball paradigm. The PGC analysis revealed a significant bilateral but asymmetrical localised activity in the temporal lobe close to the auditory cortex, and causal influences in the frontal, parietal and cingulate cortical areas, consistent with previous studies. Interestingly, the time to reach a stable connectivity configuration (~250–300 ms) coincides with the deviation of ensemble ERPs of oddball from standard tones. Finally, using a sliding time window, we showed higher resolution dynamics of causal connectivity within an ERP trial. In summary, time-domain PGC is promising in deciphering directed functional connectivity in nonlinear and ERP trials accurately, and at a sufficiently early stage. This data-driven approach can reduce computational time, and determine the key architecture for neural circuit modeling. PMID:26470866
Khan, Haider
2008-01-01
The purpose of this note is to clarify how the idea of "causal depth" can play a role in finding the more "approximately true" explanation through causal comparisons. It is not an exhaustive treatment but rather focuses on a few aspects that may be the most critical in evaluating the explanatory strengths of a theory in the social sciences. It presents a general argument which is anti-Humean on the critical side and scientific realist on the positive side. It also elucidates how explanations ...
Mehrara, Mohsen
2013-01-01
This paper investigates the causal relationship between education and GDP in a panel of 11 selected oil exporting countries by using panel unit root tests and panel cointegration analysis for the period 1970-2010. A three-variable model is formulated with oil exports as the third variable. The results show a strong causality from oil revenues and economic growth to education in the oil exporting countries. Yet, education does not have any significant effects on GDP in short- and long-run. It ...
Random sequential adsorption of polydisperse mixtures on discrete substrates.
Budinski-Petković, Lj; Vrhovac, S B; Loncarević, I
2008-12-01
We study random sequential adsorption of polydisperse mixtures of extended objects both on a triangular and on a square lattice. The depositing objects are formed by self-avoiding random walks on two-dimensional lattices. Numerical simulations were performed to determine the influence of the number of mixture components and length of the shapes making the mixture on the kinetics of the deposition process. We find that the late stage deposition kinetics follows an exponential law theta(t) approximately theta_{jam}-Aexp(-tsigma) not only for the whole mixture, but also for the individual components. We discuss in detail how the quantities such as jamming coverage theta_{jam} and the relaxation time sigma depend on the mixture composition. Our results suggest that the order of symmetry axis of the shape may exert a decisive influence on adsorption kinetics of each mixture component. PMID:19256849
Causal Loop Analysis of coastal geomorphological systems
Payo, Andres; Hall, Jim W.; French, Jon; Sutherland, James; van Maanen, Barend; Nicholls, Robert J.; Reeve, Dominic E.
2016-03-01
As geomorphologists embrace ever more sophisticated theoretical frameworks that shift from simple notions of evolution towards single steady equilibria to recognise the possibility of multiple response pathways and outcomes, morphodynamic modellers are facing the problem of how to keep track of an ever-greater number of system feedbacks. Within coastal geomorphology, capturing these feedbacks is critically important, especially as the focus of activity shifts from reductionist models founded on sediment transport fundamentals to more synthesist ones intended to resolve emergent behaviours at decadal to centennial scales. This paper addresses the challenge of mapping the feedback structure of processes controlling geomorphic system behaviour with reference to illustrative applications of Causal Loop Analysis at two study cases: (1) the erosion-accretion behaviour of graded (mixed) sediment beds, and (2) the local alongshore sediment fluxes of sand-rich shorelines. These case study examples are chosen on account of their central role in the quantitative modelling of geomorphological futures and as they illustrate different types of causation. Causal loop diagrams, a form of directed graph, are used to distil the feedback structure to reveal, in advance of more quantitative modelling, multi-response pathways and multiple outcomes. In the case of graded sediment bed, up to three different outcomes (no response, and two disequilibrium states) can be derived from a simple qualitative stability analysis. For the sand-rich local shoreline behaviour case, two fundamentally different responses of the shoreline (diffusive and anti-diffusive), triggered by small changes of the shoreline cross-shore position, can be inferred purely through analysis of the causal pathways. Explicit depiction of feedback-structure diagrams is beneficial when developing numerical models to explore coastal morphological futures. By explicitly mapping the feedbacks included and neglected within a
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
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.
Rapidity Correlation Structures from Causal Hydrodynamics
Gavin, Sean; Zin, Christopher
2016-01-01
Viscous diffusion can broaden the rapidity dependence of two-particle transverse momentum fluctuations. Surprisingly, measurements at RHIC by the STAR collaboration demonstrate that this broadening is accompanied by the appearance of unanticipated structure in the rapidity distribution of these fluctuations in the most central collisions. Although a first order classical Navier-Stokes theory can roughly explain the rapidity broadening, it cannot explain the additional structure. We propose that the rapidity structure can be explained using the second order causal Israel-Stewart hydrodynamics with stochastic noise.
Causality Green functions of bilocal fields
International Nuclear Information System (INIS)
It is shown by concrete examples, that the threshold value k-1 = 0 in the field quantum theory with three universal constants c, h, k, proposed in an other work, corresponding to the local theory, constitutes the bifurcation point: the causality Green function by the k finite value bifurcates into two parts: D-tildeLC and D-tildeEC. The Euclidean space-time R4 is a natural carrier of the latter one; its continuation from R4 onto R3.1 is regular, whereas the first one is singular in the zero and on the light cone and therefore it is rejected
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)
International Nuclear Information System (INIS)
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
Prediction of saturated liquid enthalpy of refrigerant mixtures
Institute of Scientific and Technical Information of China (English)
CHEN ZeShao; CHEN JianXin; HU Peng
2007-01-01
New corresponding temperature and corresponding enthalpy of refrigerant mixtures were defined. The relationship between saturated liquid corresponding enthalpy and corresponding temperature of refrigerant mixtures accorded with that of pure components. The characteristic parameters of saturated liquid enthalpy difference of refrigerant mixtures were calculated by three methods according to the different application conditions. The generalized equation of saturated liquid enthalpy of refrigerant mixtures was presented. The calculated values were compared with the values in literature for five ternary and binary refrigerant mixtures, namely R404A, R407A, R407B, R32/R134a, and R410A. The overall average absolute deviation was less than 1.0%.
International Nuclear Information System (INIS)
This paper investigates the causal relationship between economic growth, urbanisation and electricity consumption in the case of Angola, while utilizing the data over the period of 1971–2009. We have applied Lee and Strazicich (2003. The Review of Economics and Statistics 63, 1082–1089; 2004. Working Paper. Department of Economics, Appalachian State University) unit root tests to examine the stationarity properties of the series. Using the Gregory–Hansen structural break cointegration procedure as a complement, we employ the ARDL bounds test to investigate long run relationships. The VECM Granger causality test is subsequently used to examine the direction of causality between economic growth, urbanisation, and electricity consumption. Our results indicate the existence of long run relationships. We further observe evidence in favour of bidirectional causality between electricity consumption and economic growth. The feedback hypothesis is also found between urbanisation and economic growth. Urbanisation and electricity consumption Granger cause each other. We conclude that Angola is energy-dependent country. Consequently, the relevant authorities should boost electricity production as one of the means of achieving sustainable economic development in the long run. - Highlights: • We consider the link between electricity consumption and economic growth in Angola. • Urbanisation is added to turn the research into a trivariate investigation. • Various time series procedures are used. • Results show that increasing electricity will improve economic growth in Angola. • Results show urbanisations reduced economic growth during civil war
Luque, David; Cobos, Pedro L.; Lopez, Francisco J.
2008-01-01
In an interference-between-cues design (IbC), the expression of a learned Cue A-Outcome 1 association has been shown to be impaired if another cue, B, is separately paired with the same outcome in a second learning phase. The present study examined whether IbC could be caused by associative mechanisms independent of causal reasoning processes.…
Causal-Explanatory Pluralism: How Intentions, Functions, and Mechanisms Influence Causal Ascriptions
Lombrozo, Tania
2010-01-01
Both philosophers and psychologists have argued for the existence of distinct kinds of explanations, including teleological explanations that cite functions or goals, and mechanistic explanations that cite causal mechanisms. Theories of causation, in contrast, have generally been unitary, with dominant theories focusing either on counterfactual…
Causal mechanisms in airfoil-circulation formation
Zhu, J. Y.; Liu, T. S.; Liu, L. Q.; Zou, S. F.; Wu, J. Z.
2015-12-01
In this paper, we trace the dynamic origin, rather than any kinematic interpretations, of lift in two-dimensional flow to the physical root of airfoil circulation. We show that the key causal process is the vorticity creation by tangent pressure gradient at the airfoil surface via no-slip condition, of which the theoretical basis has been given by Lighthill ["Introduction: Boundary layer theory," in Laminar Boundary Layers, edited by L. Rosenhead (Clarendon Press, 1963), pp. 46-113], which we further elaborate. This mechanism can be clearly revealed in terms of vorticity formulation but is hidden in conventional momentum formulation, and hence has long been missing in the history of one's efforts to understand lift. By a careful numerical simulation of the flow around a NACA-0012 airfoil, and using both Eulerian and Lagrangian descriptions, we illustrate the detailed transient process by which the airfoil gains its circulation and demonstrate the dominating role of relevant dynamical causal mechanisms at the boundary. In so doing, we find that the various statements for the establishment of Kutta condition in steady inviscid flow actually correspond to a sequence of events in unsteady viscous flow.
Introducing mechanics by tapping core causal knowledge
International Nuclear Information System (INIS)
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
Emergent Horizons and Causal Structures in Holography
Banerjee, Avik; Kundu, Sandipan
2016-01-01
The open string metric arises kinematically in studying fluctuations of open string degrees of freedom on a D-brane. An observer, living on a probe D-brane, can send signals through the spacetime by using such fluctuations on the probe, that propagate in accordance with a metric which is conformal to the open string metric. Event horizons can emerge in the open string metric when one considers a D-brane with an electric field on its worldvolume. Here, we emphasize the role of and investigate, in details, the causal structure of the resulting open string event horizon and demonstrate, among other things, its close similarities to an usual black hole event horizon in asymptotically AdS-spaces. To that end, we analyze relevant geodesics, Penrose diagrams and various causal holographic observables for a given open string metric. For analytical control, most of our calculations are performed in an asymptotically AdS$_3$-background, however, we argue that the physics is qualitatively the same in higher dimensions. ...
Diagnostic reasoning using qualitative causal models
International Nuclear Information System (INIS)
The application of expert systems to reasoning problems involving real-time data from plant measurements has been a topic of much research, but few practical systems have been deployed. One obstacle to wider use of expert systems in applications involving real-time data is the lack of adequate knowledge representation methodologies for dynamic processes. Knowledge bases composed mainly of rules have disadvantages when applied to dynamic processes and real-time data. This paper describes a methodology for the development of qualitative causal models that can be used as knowledge bases for reasoning about process dynamic behavior. These models provide a systematic method for knowledge base construction, considerably reducing the engineering effort required. They also offer much better opportunities for verification and validation of the knowledge base, thus increasing the possibility of the application of expert systems to reasoning about mission critical systems. Starting with the Signed Directed Graph (SDG) method that has been successfully applied to describe the behavior of diverse dynamic processes, the paper shows how certain non-physical behaviors that result from abstraction may be eliminated by applying causal constraint to the models. The resulting Extended Signed Directed Graph (ESDG) may then be compiled to produce a model for use in process fault diagnosis. This model based reasoning methodology is used in the MOBIAS system being developed by Duke Power Company under EPRI sponsorship. 15 refs., 4 figs
EEG oscillations: From correlation to causality.
Herrmann, Christoph S; Strüber, Daniel; Helfrich, Randolph F; Engel, Andreas K
2016-05-01
Already in his first report on the discovery of the human EEG in 1929, Berger showed great interest in further elucidating the functional roles of the alpha and beta waves for normal mental activities. Meanwhile, most cognitive processes have been linked to at least one of the traditional frequency bands in the delta, theta, alpha, beta, and gamma range. Although the existing wealth of high-quality correlative EEG data led many researchers to the conviction that brain oscillations subserve various sensory and cognitive processes, a causal role can only be demonstrated by directly modulating such oscillatory signals. In this review, we highlight several methods to selectively modulate neuronal oscillations, including EEG-neurofeedback, rhythmic sensory stimulation, repetitive transcranial magnetic stimulation (rTMS), and transcranial alternating current stimulation (tACS). In particular, we discuss tACS as the most recent technique to directly modulate oscillatory brain activity. Such studies demonstrating the effectiveness of tACS comprise reports on purely behavioral or purely electrophysiological effects, on combination of behavioral effects with offline EEG measurements or on simultaneous (online) tACS-EEG recordings. Whereas most tACS studies are designed to modulate ongoing rhythmic brain activity at a specific frequency, recent evidence suggests that tACS may also modulate cross-frequency interactions. Taken together, the modulation of neuronal oscillations allows to demonstrate causal links between brain oscillations and cognitive processes and to obtain important insights into human brain function. PMID:25659527
Evidence for online processing during causal learning.
Liu, Pei-Pei; Luhmann, Christian C
2015-03-01
Many models of learning describe both the end product of learning (e.g., causal judgments) and the cognitive mechanisms that unfold on a trial-by-trial basis. However, the methods employed in the literature typically provide only indirect evidence about the unfolding cognitive processes. Here, we utilized a simultaneous secondary task to measure cognitive processing during a straightforward causal-learning task. The results from three experiments demonstrated that covariation information is not subject to uniform cognitive processing. Instead, we observed systematic variation in the processing dedicated to individual pieces of covariation information. In particular, observations that are inconsistent with previously presented covariation information appear to elicit greater cognitive processing than do observations that are consistent with previously presented covariation information. In addition, the degree of cognitive processing appears to be driven by learning per se, rather than by nonlearning processes such as memory and attention. Overall, these findings suggest that monitoring learning processes at a finer level may provide useful psychological insights into the nature of learning. PMID:25488021
Causal Conclusions that Flip Repeatedly and Their Justification
Kelly, Kevin T
2012-01-01
Over the past two decades, several consis- tent procedures have been designed to infer causal conclusions from observational data. We prove that if the true causal network might be an arbitrary, linear Gaussian net- work or a discrete Bayes network, then every unambiguous causal conclusion produced by a consistent method from non-experimental data is subject to reversal as the sample size increases any finite number of times. That result, called the causal flipping theorem, ex- tends prior results to the effect that causal discovery cannot be reliable on a given sam- ple size. We argue that since repeated flipping of causal conclusions is unavoidable in principle for consistent methods, the best possible discovery methods are consistent methods that retract their earlier conclusions no more than necessary. A series of sim- ulations of various methods across a wide range of sample sizes illustrates concretely both the theorem and the principle of com- paring methods in terms of retractions.
Comparison Analysis: Granger Causality and New Causality and Their Applications to Motor Imagery.
Hu, Sanqing; Wang, Hui; Zhang, Jianhai; Kong, Wanzeng; Cao, Yu; Kozma, Robert
2016-07-01
In this paper we first point out a fatal drawback that the widely used Granger causality (GC) needs to estimate the autoregressive model, which is equivalent to taking a series of backward recursive operations which are infeasible in many irreversible chemical reaction models. Thus, new causality (NC) proposed by Hu et al. (2011) is theoretically shown to be more sensitive to reveal true causality than GC. We then apply GC and NC to motor imagery (MI) which is an important mental process in cognitive neuroscience and psychology and has received growing attention for a long time. We study causality flow during MI using scalp electroencephalograms from nine subjects in Brain-computer interface competition IV held in 2008. We are interested in three regions: Cz (central area of the cerebral cortex), C3 (left area of the cerebral cortex), and C4 (right area of the cerebral cortex) which are considered to be optimal locations for recognizing MI states in the literature. Our results show that: 1) there is strong directional connectivity from Cz to C3/C4 during left- and right-hand MIs based on GC and NC; 2) during left-hand MI, there is directional connectivity from C4 to C3 based on GC and NC; 3) during right-hand MI, there is strong directional connectivity from C3 to C4 which is much clearly revealed by NC than by GC, i.e., NC largely improves the classification rate; and 4) NC is demonstrated to be much more sensitive to reveal causal influence between different brain regions than GC. PMID:26099149
Solubility modeling of refrigerant/lubricant mixtures
Energy Technology Data Exchange (ETDEWEB)
Michels, H.H.; Sienel, T.H.
1996-12-31
A general model for predicting the solubility properties of refrigerant/lubricant mixtures has been developed based on applicable theory for the excess Gibbs energy of non-ideal solutions. In our approach, flexible thermodynamic forms are chosen to describe the properties of both the gas and liquid phases of refrigerant/lubricant mixtures. After an extensive study of models for describing non-ideal liquid effects, the Wohl-suffix equations, which have been extensively utilized in the analysis of hydrocarbon mixtures, have been developed into a general form applicable to mixtures where one component is a POE lubricant. In the present study we have analyzed several POEs where structural and thermophysical property data were available. Data were also collected from several sources on the solubility of refrigerant/lubricant binary pairs. We have developed a computer code (NISC), based on the Wohl model, that predicts dew point or bubble point conditions over a wide range of composition and temperature. Our present analysis covers mixtures containing up to three refrigerant molecules and one lubricant. The present code can be used to analyze the properties of R-410a and R-407c in mixtures with a POE lubricant. Comparisons with other models, such as the Wilson or modified Wilson equations, indicate that the Wohl-suffix equations yield more reliable predictions for HFC/POE mixtures.
On the causal structure between CO2 and global temperature
Adolf Stips; Diego Macias; Clare Coughlan; Elisa Garcia-Gorriz; X. San Liang
2016-01-01
We use a newly developed technique that is based on the information flow concept to investigate the causal structure between the global radiative forcing and the annual global mean surface temperature anomalies (GMTA) since 1850. Our study unambiguously shows one-way causality between the total Greenhouse Gases and GMTA. Specifically, it is confirmed that the former, especially CO2, are the main causal drivers of the recent warming. A significant but smaller information flow comes from aeroso...
Non-parametric causal inference for bivariate time series
McCracken, James M
2015-01-01
We introduce new quantities for exploratory causal inference between bivariate time series. The quantities, called penchants and leanings, are computationally straightforward to apply, follow directly from assumptions of probabilistic causality, do not depend on any assumed models for the time series generating process, and do not rely on any embedding procedures; these features may provide a clearer interpretation of the results than those from existing time series causality tools. The penchant and leaning are computed based on a structured method for computing probabilities.
Finance and Growth: Institutional Considerations, Financial Policies and Causality
Philip Arestis; Panicos Demetriades
1999-01-01
Authors in this article suggest that country specific institutional factors and policies are likely to influence the causal nature of the relationship between financial development and economic growth. Authors conduct cointegration and causality tests using time series data for twelve representative countries. The empirical results show considerable variation of causality across countries which can be explained by institutional and policy differences, providing support to the main hypothesis.
—Causality, Unintended Consequences and Deducing Shared Causes
Steven M. Shugan
2007-01-01
Despite warnings against inferring causality from observed correlations or statistical dependence, some articles do. Observed correlation is neither necessary nor sufficient to infer causality as defined by the term's everyday usage. For example, a deterministic causal process creates pseudorandom numbers; yet, we observe no correlation between the numbers. Child height correlates with spelling ability because age causes both. Moreover, order is problematic—we hear train whistles before obser...
Dark matter perturbations and viscosity: a causal approach
Acquaviva, Giovanni; John, Anslyn; Pénin, Aurélie
2016-01-01
The inclusion of dissipative effects in cosmic fluids modifies their clustering properties and could have observable effects on the formation of large scale structures. We analyse the evolution of density perturbations of cold dark matter endowed with causal bulk viscosity. The perturbative analysis is carried out in the Newtonian approximation and the bulk viscosity is described by the causal Israel-Stewart (IS) theory. In contrast to the non-causal Eckart theory, we obtain a third order evo...
The Causality between Government Revenue and Government Expenditure in Iran
2012-01-01
The causal relationship between government revenue and government expenditure is an important subject in public economics especially to the control of budget deficit. The purpose of this study is to investigate the relationship between government revenue and government expenditure in Iran by applying the bounds testing approach to cointegration. The results of the causality test show that there is a bidirectional causal relationship between government expenditure and revenues in both long run...
Integrating Probabilistic, Taxonomic and Causal Knowledge in Abductive Diagnosis
Lin, Dekang; Goebel, Randy
2013-01-01
We propose an abductive diagnosis theory that integrates probabilistic, causal and taxonomic knowledge. Probabilistic knowledge allows us to select the most likely explanation; causal knowledge allows us to make reasonable independence assumptions; taxonomic knowledge allows causation to be modeled at different levels of detail, and allows observations be described in different levels of precision. Unlike most other approaches where a causal explanation is a hypothesis that one or more causat...
Rajagopal, KR
1995-01-01
This book presents a unified treatment of the mechanics of mixtures of several constituents within the context of continuum mechanics. After an introduction to the basic theory in the first few chapters, the book deals with a detailed exposition of the mechanics of a mixture of a fluid and an elastic solid, which is either isotropic or anisotropic and is capable of undergoing large deformations. Issues regarding the specification of boundary conditions for mixtures are discussed in detail and several boundary value and initial-boundary value problems are solved. The status of some special theo
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. PMID:25946227
Causal topology in future and past distinguishing spacetimes
International Nuclear Information System (INIS)
The causal structure of a strongly causal spacetime is particularly well endowed. Not only does it determine the conformal spacetime geometry when the spacetime dimension n > 2, as shown by Malament and Hawking-King-McCarthy (MHKM), but also the manifold dimension. The MHKM result, however, applies more generally to spacetimes satisfying the weaker causality condition of future and past distinguishability (FPD), and it is an important question whether the causal structure of such spacetimes can determine the manifold dimension. In this work, we show that the answer to this question is in the affirmative. We investigate the properties of future or past distinguishing spacetimes and show that their causal structures determine the manifold dimension. This gives a non-trivial generalization of the MHKM theorem and suggests that there is a causal topology for FPD spacetimes which encodes manifold dimension and which is strictly finer than the Alexandrov topology. We show that such a causal topology does exist. We construct it using a convergence criterion based on sequences of 'chain intervals' which are the causal analogues of null geodesic segments. We show that when the region of strong causality violation satisfies a local achronality condition, this topology is equivalent to the manifold topology in an FPD spacetime.
Investigations of reversible thermochromic mixtures
MacLaren, Douglas C.
Three-component organic thermochromic systems have potential applications in reversible, rewritable thermal printing. In principle, such mixtures could maintain a coloured or non-coloured state at ambient temperature depending on their thermal treatment. These systems generally consist of a functional dye (1--3 mol%), a weakly acidic colour developer (5--25 mol%), and a high-melting organic solvent (75--90 mol%). Colour development occurs at the fusion temperature of the mixture, which triggers the interaction of the dye and developer. Slow cooling of the melt results in an equilibrium state with low colour density, whereas rapid cooling of the melt results in a metastable state with high colour density. The metastable state can be decoloured by heating to an intermediate decolourisation temperature at which the coloured state becomes unstable. Barriers to the widespread use of reversible, rewritable thermochromic materials include problems with colour contrast, colour stability, and decolourisation rates. Development is hindered by a lack of detailed knowledge of the interactions between components in these systems. In this study the developer-dye and developer-solvent interactions were examined for an archetypal dye/developer/solvent thermochromic system. Vibrational spectroscopy, NMR, and thermal analysis were used to examine compounds formed in developer/dye and developer/solvent binary mixtures. Rewritable thermochromic properties such as metastable colour density, equilibrium colour density, and decolourisation rates were examined and discussed in terms of the thermodynamics of the developer/dye and developer/solvent interactions. Observed thermochromic properties are shown to be strongly correlated to a competition between the dye and the solvent for interaction with the developer. Increasing the attractive interaction between the solvent and developer results in enhanced rewritable thermochromic properties.
Causality and stability of cosmic jets
Porth, Oliver; Komissarov, Serguei S.
2015-09-01
In stark contrast to their laboratory and terrestrial counterparts, cosmic jets appear to be very stable. They are able to penetrate vast spaces, which exceed by up to a billion times the size of their central engines. We propose that the reason behind this remarkable property is the loss of causal connectivity across these jets, caused by their rapid expansion in response to fast decline of external pressure with the distance from the `jet engine'. In atmospheres with power-law pressure distribution, pext ∝ z-κ, the total loss of causal connectivity occurs, when κ > 2 - the steepness which is expected to be quite common for many astrophysical environments. This conclusion does not seem to depend on the physical nature of jets - it applies both to relativistic and non-relativistic flows, both magnetically dominated and unmagnetized jets. In order to verify it, we have carried out numerical simulations of moderately magnetized and moderately relativistic jets. The results give strong support to our hypothesis and provide with valuable insights. In particular, we find that the z-pinched inner cores of magnetic jets expand slower than their envelopes and become susceptible to instabilities even when the whole jet is stable. This may result in local dissipation and emission without global disintegration of the flow. Cosmic jets may become globally unstable when they enter flat sections of external atmospheres. We propose that the Fanaroff-Riley (FR) morphological division of extragalactic radio sources into two classes is related to this issue. In particular, we argue that the low power FR-I jets become reconfined, causally connected and globally unstable on the scale of galactic X-ray coronas, whereas more powerful FR-II jets reconfine much further out, already on the scale of radio lobes and remain largely intact until they terminate at hotspots. Using this idea, we derived the relationship between the critical jet power and the optical luminosity of the host
Quantum causality, stochastics, trajectories and information
International Nuclear Information System (INIS)
A history of the discovery of 'new' quantum mechanics and the paradoxes of its probabilistic interpretation are briefly reviewed from the modern point of view of quantum probability and information. Modern quantum theory, which has been developed during the last 20 years for the treatment of quantum open systems including quantum noise, decoherence, quantum diffusions and spontaneous jumps occurring under continuous in time observation, is not yet a part of the standard curriculum of quantum physics. It is argued that the conventional formalism of quantum mechanics is insufficient for the description of quantum events, such as spontaneous decays say, and the new experimental phenomena related to individual quantum measurements, but they have all received an adequate mathematical treatment in quantum stochastics of open systems. Moreover, the only reasonable probabilistic interpretation of quantum mechanics put forward by Max Born was, in fact, in irreconcilable contradiction with traditional mechanical reality and causality. This led to numerous quantum paradoxes, some of them due to the great inventors of quantum theory such as Einstein and Schroedinger. They are reconsidered in this paper from the modern point of view of quantum stochastics and information. The development of quantum measurement theory, initiated by von Neumann, indicated a possibility for resolution of this interpretational crisis by divorcing the algebra of the dynamical generators and the algebra of the actual observables, or Bell's beables. It is shown that within this approach quantum causality can be rehabilitated in the form of a superselection rule for compatibility of the actual histories with the potential future. This rule, together with the self-compatibility of the measurements ensuring the consistency of the histories, is called the nondemolition, or causality principle in modern quantum theory. The application of this rule in the form of dynamical commutation relations leads to the
Libertad de la voluntad y poderes causales Freedom of the will and causal powers
Directory of Open Access Journals (Sweden)
JOSÉ TOMÁS ALVARADO MARAMBIO
2012-03-01
Full Text Available Este trabajo discute una objeción bien conocida a la libertad de la voluntad libertaria en un mundo no determinista. En un mundo no determinista el estado de cosas total del mundo en un instante de tiempo t es compatible con diferentes estados de cosas totales alternativos en el futuro de t. Se ha argumentado que, en cuanto son posibles diferentes alternativas a una decisión libre, es una cuestión de azar y suerte que tal decisión se ha tomado. Si una decisión libre es una cuestión de suerte, entonces el agente no puede ser considerado responsable por ella. Se argumenta que la dificultad aparece en una concepción anti-realista de la causalidad, donde los hechos causales son supervenientes a regularidades o dependencias contrafácticas. Una concepción realista de la causalidad puede, por ello, explicar cómo el agente está en control causal de la decisión libre tomada, cuando la decisión no cae bajo una regularidad o una dependencia contrafáctica. Una vez considerado cómo es que el agente está en control de la decisión, se argumenta que no se puede decir que la decisión libre es una cuestión de suerte para el agente.This paper discusses a well-known objection to libertarian free will in a non-deterministic world. In a non-deterministic world the complete state of affairs of the world in an instant of time t is compatible with different alternative complete states of affairs in the future of t. It has been argued that, in so far as different alternatives are possible to a free decision, it is a matter of chance and luck that that decision is taken. If a free decision is a matter of luck, then the agent cannot be considered responsible for it. It is argued that the difficulty appears from an anti-realist conception of causality, where causal facts are supervenient on regularities or counterfactual dependences. A realist conception of causality can, then, explain how the agent is causally in control of the free decision taken when
International Nuclear Information System (INIS)
A theoretical study of the thermodynamic and hydrodynamic properties of 3He-4He II mixtures at temperatures below 250 mK is described. A hydrodynamic model is set up which incorporates mutual friction between the two components. Results of an investigation into the quantitative calculation of the mutual friction are reported. 148 refs.; 34 figs.; 4 tabs
Causality and hyperbolicity of Lovelock theories
International Nuclear Information System (INIS)
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)
On the Causal Set-Continuum Correspondence
Saravani, Mehdi
2014-01-01
We present two results which concern certain aspects of the question: when is a causal set well approximated by a Lorentzian manifold? The first result is a theorem which shows that the number-volume correspondence, if required to hold even for arbitrarily small regions, is best realized via Poisson sprinkling. The second result concerns a family of lattices in $1+1$ dimensional Minkowski space, known as Lorentzian lattices, which we show provide a much better number-volume correspondence than Poisson sprinkling for large volumes. We argue, however, that this feature should not persist in higher dimensions. We conclude by conjecturing a form of the aforementioned theorem that holds under weaker assumptions, namely that Poisson sprinkling provides the best number-volume correspondence in $3+1$ dimensions for spacetime regions with macroscopically large volumes.
Wiretap Channel with Causal State Information
Chia, Yeow-Khiang
2010-01-01
A lower bound on the secrecy capacity of the wiretap channel with state information available causally at both the encoder and decoder is established. The lower bound is shown to be strictly larger than that for the noncausal case by Liu and Chen. Achievability is proved using block Markov coding, Shannon strategy, and key generation from common state information. The state sequence available at the end of each block is used to generate a key, which is used to enhance the transmission rate of the confidential message in the following block. An upper bound on the secrecy capacity when the state is available noncausally at the encoder and decoder is established and is shown to coincide with the lower bound for several classes of wiretap channels with state.
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
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.
Exploring Torus Universes in Causal Dynamical Triangulations
Budd, T G
2013-01-01
Motivated by the search for new observables in nonperturbative quantum gravity, we consider Causal Dynamical Triangulations (CDT) in 2+1 dimensions with the spatial topology of a torus. This system is of particular interest, because one can study not only the global scale factor, but also global shape variables in the presence of arbitrary quantum fluctuations of the geometry. Our initial investigation focusses on the dynamics of the scale factor and uncovers a qualitatively new behaviour, which leads us to investigate a novel type of boundary conditions for the path integral. Comparing large-scale features of the emergent quantum geometry in numerical simulations with a classical minisuperspace formulation, we find partial agreement. By measuring the correlation matrix of volume fluctuations we succeed in reconstructing the effective action for the scale factor directly from the simulation data. Apart from setting the stage for the analysis of shape dynamics on the torus, the new set-up highlights the role o...
Causality constraints in conformal field theory
Hartman, Thomas; Jain, Sachin; Kundu, Sandipan
2016-05-01
Causality places nontrivial constraints on QFT in Lorentzian signature, for example fixing the signs of certain terms in the low energy Lagrangian. In d dimensional conformal field theory, we show how such constraints are encoded in crossing symmetry of Euclidean correlators, and derive analogous constraints directly from the conformal bootstrap (analytically). The bootstrap setup is a Lorentzian four-point function corresponding to propagation through a shockwave. Crossing symmetry fixes the signs of certain log terms that appear in the conformal block expansion, which constrains the interactions of low-lying operators. As an application, we use the bootstrap to rederive the well known sign constraint on the (∂ ϕ)4 coupling in effective field theory, from a dual CFT. We also find constraints on theories with higher spin conserved currents. Our analysis is restricted to scalar correlators, but we argue that similar methods should also impose nontrivial constraints on the interactions of spinning operators.
A study in cosmology and causal thermodynamics
International Nuclear Information System (INIS)
The especial relativity of thermodynamic theories for reversible and irreversible processes in continuous medium is studied. The formalism referring to equilibrium and non-equilibrium configurations, and theories which includes the presence of gravitational fields are discussed. The nebular model in contraction with dissipative processes identified by heat flux and volumetric viscosity is thermodymically analysed. This model is presented by a plane conformal metric. The temperature, pressure, entropy and entropy production within thermodynamic formalism which adopts the hypothesis of local equilibrium, is calculated. The same analysis is carried out considering a causal thermodynamics, which establishes a local entropy of non-equilibrium. Possible homogeneous and isotropic cosmological models, considering the new phenomenological equation for volumetric viscosity deriving from cause thermodynamics are investigated. The found out models have plane spatial section (K=0) and some ones do not have singularities. The energy conditions are verified and the entropy production for physically reasobable models are calculated. (M.C.K.)
Causality and local determinism versus quantum nonlocality
Kupczynski, Marian
2013-01-01
The entanglement and the violation of Bell and CHSH inequalities in spin polarization correlation experiments (SPCE) is considered to be one of the biggest mysteries of Nature and is called quantum nonlocality. In this paper we show once again that this conclusion is based on imprecise terminology and on the lack of understanding of probabilistic models used in various proofs of Bell and CHSH theorems. These models are inconsistent with experimental protocols used in SPCE. This is the only reason why Bell and CHSH inequalities are violated. A probabilistic non-signalling description of SPCE, consistent with quantum predictions, is possible and it depends explicitly on the context of each experiment. It is also deterministic in the sense that the outcome is determined by supplementary local parameters describing both a physical signals and measuring instruments. The existence of such description gives additional arguments that quantum theory is emergent from some more detailed theory respecting causality and l...
Causality Constraints in Conformal Field Theory
Hartman, Thomas; Kundu, Sandipan
2015-01-01
Causality places nontrivial constraints on QFT in Lorentzian signature, for example fixing the signs of certain terms in the low energy Lagrangian. In d-dimensional conformal field theory, we show how such constraints are encoded in crossing symmetry of Euclidean correlators, and derive analogous constraints directly from the conformal bootstrap (analytically). The bootstrap setup is a Lorentzian four-point function corresponding to propagation through a shockwave. Crossing symmetry fixes the signs of certain log terms that appear in the conformal block expansion, which constrains the interactions of low-lying operators. As an application, we use the bootstrap to rederive the well known sign constraint on the $(\\partial\\phi)^4$ coupling in effective field theory, from a dual CFT. We also find constraints on theories with higher spin conserved currents. Our analysis is restricted to scalar correlators, but we argue that similar methods should also impose nontrivial constraints on the interactions of spinning o...
Spectral mixture analysis of multispectral thermal infrared images
International Nuclear Information System (INIS)
Remote spectral measurements of light reflected or emitted from terrestrial scenes is commonly integrated over areas sufficiently large that the surface comprises more than one component. Techniques have been developed to analyze multispectral or imaging spectrometer data in terms of a wide range of mixtures of a limited number of components. Spectral mixture analysis has been used primarily for visible and near-infrared images, but it may also be applied to thermal infrared data. Two approaches are reviewed: binary mixing and a more general treatment for isothermal mixtures of a greater number of components
Nuclear fuel alloys or mixtures and method of making thereof
Energy Technology Data Exchange (ETDEWEB)
Mariani, Robert Dominick; Porter, Douglas Lloyd
2016-04-05
Nuclear fuel alloys or mixtures and methods of making nuclear fuel mixtures are provided. Pseudo-binary actinide-M fuel mixtures form alloys and exhibit: body-centered cubic solid phases at low temperatures; high solidus temperatures; and/or minimal or no reaction or inter-diffusion with steel and other cladding materials. Methods described herein through metallurgical and thermodynamics advancements guide the selection of amounts of fuel mixture components by use of phase diagrams. Weight percentages for components of a metallic additive to an actinide fuel are selected in a solid phase region of an isothermal phase diagram taken at a temperature below an upper temperature limit for the resulting fuel mixture in reactor use. Fuel mixtures include uranium-molybdenum-tungsten, uranium-molybdenum-tantalum, molybdenum-titanium-zirconium, and uranium-molybdenum-titanium systems.
The balanced survivor average causal effect.
Greene, Tom; Joffe, Marshall; Hu, Bo; Li, Liang; Boucher, Ken
2013-01-01
Statistical analysis of longitudinal outcomes is often complicated by the absence of observable values in patients who die prior to their scheduled measurement. In such cases, the longitudinal data are said to be "truncated by death" to emphasize that the longitudinal measurements are not simply missing, but are undefined after death. Recently, the truncation by death problem has been investigated using the framework of principal stratification to define the target estimand as the survivor average causal effect (SACE), which in the context of a two-group randomized clinical trial is the mean difference in the longitudinal outcome between the treatment and control groups for the principal stratum of always-survivors. The SACE is not identified without untestable assumptions. These assumptions have often been formulated in terms of a monotonicity constraint requiring that the treatment does not reduce survival in any patient, in conjunction with assumed values for mean differences in the longitudinal outcome between certain principal strata. In this paper, we introduce an alternative estimand, the balanced-SACE, which is defined as the average causal effect on the longitudinal outcome in a particular subset of the always-survivors that is balanced with respect to the potential survival times under the treatment and control. We propose a simple estimator of the balanced-SACE that compares the longitudinal outcomes between equivalent fractions of the longest surviving patients between the treatment and control groups and does not require a monotonicity assumption. We provide expressions for the large sample bias of the estimator, along with sensitivity analyses and strategies to minimize this bias. We consider statistical inference under a bootstrap resampling procedure. PMID:23658214
Recursive partitioning for heterogeneous causal effects.
Athey, Susan; Imbens, Guido
2016-07-01
In this paper we propose methods for estimating heterogeneity in causal effects in experimental and observational studies and for conducting hypothesis tests about the magnitude of differences in treatment effects across subsets of the population. We provide a data-driven approach to partition the data into subpopulations that differ in the magnitude of their treatment effects. The approach enables the construction of valid confidence intervals for treatment effects, even with many covariates relative to the sample size, and without "sparsity" assumptions. We propose an "honest" approach to estimation, whereby one sample is used to construct the partition and another to estimate treatment effects for each subpopulation. Our approach builds on regression tree methods, modified to optimize for goodness of fit in treatment effects and to account for honest estimation. Our model selection criterion anticipates that bias will be eliminated by honest estimation and also accounts for the effect of making additional splits on the variance of treatment effect estimates within each subpopulation. We address the challenge that the "ground truth" for a causal effect is not observed for any individual unit, so that standard approaches to cross-validation must be modified. Through a simulation study, we show that for our preferred method honest estimation results in nominal coverage for 90% confidence intervals, whereas coverage ranges between 74% and 84% for nonhonest approaches. Honest estimation requires estimating the model with a smaller sample size; the cost in terms of mean squared error of treatment effects for our preferred method ranges between 7-22%. PMID:27382149
World oil and agricultural commodity prices: Evidence from nonlinear causality
International Nuclear Information System (INIS)
The increasing co-movements between the world oil and agricultural commodity prices have renewed interest in determining price transmission from oil prices to those of agricultural commodities. This study extends the literature on the oil-agricultural commodity prices nexus, which particularly concentrates on nonlinear causal relationships between the world oil and three key agricultural commodity prices (corn, soybeans, and wheat). To this end, the linear causality approach of Toda-Yamamoto and the nonparametric causality method of Diks-Panchenko are applied to the weekly data spanning from 1994 to 2010. The linear causality analysis indicates that the oil prices and the agricultural commodity prices do not influence each other, which supports evidence on the neutrality hypothesis. In contrast, the nonlinear causality analysis shows that: (i) there are nonlinear feedbacks between the oil and the agricultural prices, and (ii) there is a persistent unidirectional nonlinear causality running from the oil prices to the corn and to the soybeans prices. The findings from the nonlinear causality analysis therefore provide clues for better understanding the recent dynamics of the agricultural commodity prices and some policy implications for policy makers, farmers, and global investors. This study also suggests the directions for future studies. - Research highlights: → This study determines the price transmission mechanisms between the world oil and three key agricultural commodity prices (corn, soybeans, and wheat). → The linear and nonlinear cointegration and causality methods are carried out. → The linear causality analysis supports evidence on the neutrality hypothesis. → The nonlinear causality analysis shows that there is a persistent unidirectional causality from the oil prices to the corn and to the soybeans prices.
Predicting skin permeability from complex chemical mixtures
International Nuclear Information System (INIS)
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 2H + bΣβ 2H + sπ 2H + rR 2 + vV x where Σα 2H is the hydrogen-bond donor acidity, Σβ 2H is the hydrogen-bond acceptor basicity, π 2H 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, R2 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 was
Velocity limitations in coaxial plasma gun experiments with gas mixtures
International Nuclear Information System (INIS)
The velocity limitations found in many crossed field plasma experiments with neutral gas present are studied for binary mixtures of H2, He, N2 O2, 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)
Directory of Open Access Journals (Sweden)
Bernard N. Iyke
2014-06-01
Full Text Available This paper examines the dynamic causal relationship between electricity consumption and economic growth in Ghana within a trivariate ARDL framework, for the period 1971–2012.The paper obviates the variable omission bias, and the use of cross-sectional techniques that characterise most existing studies. The results show that there is a distinct causal flow from economic growth to electricity consumption: both in the short run and in the long run. This finding supports the growth-led electricity consumption hypothesis, as documented in the literature. The paper urges policymakers in Ghana to resort to alternative sources of electric power generation, in order to reduce any future pressures on the current sources of electricity production. Appropriate monetary policies must also be put in place, in order to accommodate potential inflation hikes stemming from excessive demands for electricity in the near future.
Assessing evidence for a common function of delay in causal learning and reward discounting
Directory of Open Access Journals (Sweden)
WilliamJamesGreville
2012-11-01
Full Text Available Time occupies a central role in both the induction of causal relationships and determining the subjective value of rewards. Delays devalue rewards and also impair learning of relationships between events. The mathematical relation between the time until a delayed reward and its present value has been characterized as a hyperbola-like function, and increasing delays of reinforcement tend to elicit judgments or response rates that similarly show a negatively accelerated decay pattern. Furthermore, neurological research implicates both the hippocampus and pre-frontal cortex in both these processes. Since both processes are broadly concerned with the concepts of reward, value, and time, involve a similar functional form, and have been identified as involving the same specific brain regions, it seems tempting to assume that the two processes are underpinned by the same cognitive or neural mechanisms. We set out to determine experimentally whether a common cognitive mechanism underlies these processes, by contrasting individual performances on causal judgment and delay discounting tasks. Results from each task corresponded with previous findings in the literature, but no relation was found between the two tasks. The task was replicated and extended by including two further measures, the Barrett Impulsiveness Scale (BIS, and a causal attribution task. Performance on this latter task was correlated with results on the causal judgment task, and also with the non-planning component of the BIS, but the results from the delay discounting task was not correlated with either causal learning task nor the BIS. Implications for current theories of learning are considered.
Demirer, R Murat; Özerdem, Mehmet Siraç; Bayrak, Coskun; Mendi, Engin
2013-12-01
Analysis of directional information flow patterns among different regions of the brain is important for investigating the relation between ECoG (electrocorticographic) and mental activity. The objective is to study and evaluate the information flow activity at different frequencies in the primary motor cortex. We employed Granger causality for capturing the future state of the propagation path and direction between recording electrode sites on the cerebral cortex. A grid covered the right motor cortex completely due to its size (approx. 8 cm×8 cm) but grid area extends to the surrounding cortex areas. During the experiment, a subject was asked to imagine performing two activities: movement of the left small finger and/or movement of the tongue. The time series of the electrical brain activity was recorded during these trials using an 8×8 (0.016-300 Hz band with) ECoG platinum electrode grid, which was placed on the contralateral (right) motor cortex. For detection of information flow activity and communication frequencies among the electrodes, we have proposed a method based on following steps: (i) calculation of analytical time series such as amplitude and phase difference acquired from Hilbert transformation, (ii) selection of frequency having highest interdependence for the electrode pairs for the concerned time series over a sliding window in which we assumed time series were stationary, (iii) calculation of Granger causality values for each pair with selected frequency. The information flow (causal influence) activity and communication frequencies between the electrodes in grid were determined and shown successfully. It is supposed that information flow activity and communication frequencies between the electrodes in the grid are approximately the same for the same pattern. The successful employment of Granger causality and Hilbert transformation for the detection of the propagation path and direction of each component of ECoG among different sub
Separation of mass spectra of mixtures by factor analysis
International Nuclear Information System (INIS)
A method for the separation of mass spectra of mixtures is developed utilizing a factor analysis approach. It is shown to be possible, under certain conditions, to separate the data from mass spectra of mixtures into the mass spectra of the pure components and to give their respective concentrations. The technique is evaluated on an artifical data set and on data from mass spectra of mixtures previously reported in the literature. 6 tables
Bayesian D-Optimal Choice Designs for Mixtures
Ruseckaite, Aiste; Goos, Peter; 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 setting. Choice experiments may help to determine how the respondents' choice of a product or service is affected by the combination of ingredients. In such studies, individuals are confronted with sets of ...
A-optimal designs for an additive quadratic mixture model
Chan, LY; Guan, YN; Zhang, CQ
1998-01-01
Quadratic models are widely used in the analysis of experiments involving mixtures. This paper gives A-optimal designs for an additive quadratic mixture model for q ≥ 3 mixture components. It is proved that in these A-optimal designs, vertices of the simplex S q-1 are support points, and other support points shift gradually from barycentres of depth 1 to barycentres of depth 3 as q increases. A-optimal designs with minimal support are also discussed.
A classification system for tableting behaviors of binary powder mixtures
Changquan Calvin Sun
2016-01-01
The ability to predict tableting properties of a powder mixture from individual components is of both fundamental and practical importance to the efficient formulation development of tablet products. A common tableting classification system (TCS) of binary powder mixtures facilitates the systematic development of new knowledge in this direction. Based on the dependence of tablet tensile strength on weight fraction in a binary mixture, three main types of tableting behavior are identified. Eac...
Betts, James A; Richardson, Judith D; Chowdhury, Enhad A.; Holman, Geoffrey D; Tsintzas, Kostas; Thompson, Dylan
2014-01-01
Background: Popular beliefs that breakfast is the most important meal of the day are grounded in cross-sectional observations that link breakfast to health, the causal nature of which remains to be explored under real-life conditions. Objective: The aim was to conduct a randomized controlled trial examining causal links between breakfast habits and all components of energy balance in free-living humans. Design: The Bath Breakfast Project is a randomized controlled trial with repeated-measures...
Manifest Variable Granger Causality Models for Developmental Research: A Taxonomy
von Eye, Alexander; Wiedermann, Wolfgang
2015-01-01
Granger models are popular when it comes to testing hypotheses that relate series of measures causally to each other. In this article, we propose a taxonomy of Granger causality models. The taxonomy results from crossing the four variables Order of Lag, Type of (Contemporaneous) Effect, Direction of Effect, and Segment of Dependent Series…
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 Propagators for the Second Order Wilson Loop
Pimentel, B. M.; Tomazelli, J. L.
1996-01-01
We evaluate the Wilson loop at second order in general non-covariant gauges by means of the causal principal-value prescription for the gauge- dependent poles in the gauge-boson propagator and show that the result agrees with the usual causal prescriptions.
Evidence for Deductive Reasoning in Blocking of Causal Judgments
Mitchell, C.J.; Lovibond, P.F.; Condoleon, M.
2005-01-01
We have recently demonstrated that pre-training of additivity (the outcome of two causal cues is larger than one causal cue) greatly enhances blocking. This manipulation could work by removing a ceiling effect on the outcome, as proposed by Cheng (1997). Alternatively, it could remove the logical ambiguity associated with blocking under…
Time Symmetric Quantum Mechanics and Causal Classical Physics
Bopp, Fritz W
2016-01-01
A two boundary quantum mechanics without time ordered causal structure is advocated as consistent theory. The apparent causal structure of usual "near future" macroscopic phenomena is attributed to a cosmological asymmetry and to rules governing the transition between microscopic to macroscopic observations. Our interest is a heuristic understanding of the resulting macroscopic physics.
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…
The causal boundary and its relations with the conformal boundary
Energy Technology Data Exchange (ETDEWEB)
Herrera, J, E-mail: jherrera@agt.cie.uma.e [Departamento de Algebra, GeometrIa y TopologIa, Facultad de Ciencias, Universidad de Malaga, Campus Teatinos, 29071 Malaga (Spain)
2010-05-01
Our aim in this note is to present the results (obtained in [2]) which ensure that, under certain regularity conditions, the conformal boundary becomes equal to the causal boundary, not only as a point set, but in a topological and chronological level. In particular, under these conditions the conformal boundary becomes a powerful tool to compute the causal one.
Causal Discourse Analyzer: Improving Automated Feedback on Academic ESL Writing
Chukharev-Hudilainen, Evgeny; Saricaoglu, Aysel
2016-01-01
Expressing causal relations plays a central role in academic writing. While it is important that writing instructors assess and provide feedback on learners' causal discourse, it could be a very time-consuming task. In this respect, automated writing evaluation (AWE) tools may be helpful. However, to date, there have been no AWE tools capable of…
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…
From Blickets to Synapses: Inferring Temporal Causal Networks by Observation
Fernando, Chrisantha
2013-01-01
How do human infants learn the causal dependencies between events? Evidence suggests that this remarkable feat can be achieved by observation of only a handful of examples. Many computational models have been produced to explain how infants perform causal inference without explicit teaching about statistics or the scientific method. Here, we…
Temporal and Causal Reasoning in Deaf and Hearing Novice Readers
Sullivan, Susan; Oakhill, Jane; Arfé, Barbara; Boureux, Magali
2014-01-01
Temporal and causal information in text are crucial in helping the reader form a coherent representation of a narrative. Deaf novice readers are generally poor at processing linguistic markers of causal/temporal information (i.e., connectives), but what is unclear is whether this is indicative of a more general deficit in reasoning about…
[Construction of Three-Dimensional Isobologram for Ternary Pollutant Mixtures].
2015-12-01
Tongji University, Shanghai 200092, China) Isobolographic analysis was widely used in the interaction assessment of binary mixtures. However, how to construct a three-dimensional (3D) isobologram for the assessment of toxicity interaction within ternary mixtures is still not reported up to date. The main purpose of this paper is to develop a 3D isobologram where the relative concentrations of three components are acted as three coordinate axes in 3D space to examine the toxicity interaction within ternary mixtures. Taking six commonly used pesticides in China, including three herbicides (2, 4-D, desmetryne and simetryn) and three insecticides ( dimethoate, imidacloprid and propoxur) as the mixture components, the uniform design ray procedure (UD-Ray) was used to rationally design the concentration composition of various components in the ternary mixtures so that effectively and comprehensively reflected the variety of actual environmental concentrations. The luminescent inhibition toxicities of single pesticides and their ternary mixtures to Vibrio fischeri at various concentration levels were determined by the microplate toxicity analysis. Selecting concentration addition (CA) as the addition reference, 3D isobolograms were constructed to study the toxicity interactions of various ternary mixtures. The results showed that the 3D isobologram could clearly and directly exhibit the toxicity interactions of ternary mixtures, and extend the use of isobolographic analysis into the ternary mixtures. PMID:27011996
Quantum objects as elementary units of causality and locality
Diel, Hans H
2016-01-01
The author's attempt to construct a local causal model of quantum theory (QT) that includes quantum field theory (QFT) resulted in the identification of "quantum objects" as the elementary units of causality and locality. Quantum objects are collections of particles (including single particles) whose collective dynamics and measurement results can only be described by the laws of QT and QFT. Local causal models of quantum objects' internal dynamics are not possible if a locality is understood as a space-point locality. Within quantum objects, state transitions may occur which instantly affect the whole quantum object. The identification of quantum objects as the elementary units of causality and locality has two primary implications for a causal model of quantum objects: (1) quantum objects run autonomously with system-state update frequencies based on their local proper times and with either no or minimal dependency on external parameters. (2) The laws of physics that describe global (but relativistic) inter...
A causal net approach to relativistic quantum mechanics
Bateson, R. D.
2012-05-01
In this paper we discuss a causal network approach to describing relativistic quantum mechanics. Each vertex on the causal net represents a possible point event or particle observation. By constructing the simplest causal net based on Reichenbach-like conjunctive forks in proper time we can exactly derive the 1+1 dimension Dirac equation for a relativistic fermion and correctly model quantum mechanical statistics. Symmetries of the net provide various quantum mechanical effects such as quantum uncertainty and wavefunction, phase, spin, negative energy states and the effect of a potential. The causal net can be embedded in 3+1 dimensions and is consistent with the conventional Dirac equation. In the low velocity limit the causal net approximates to the Schrodinger equation and Pauli equation for an electromagnetic field. Extending to different momentum states the net is compatible with the Feynman path integral approach to quantum mechanics that allows calculation of well known quantum phenomena such as diffraction.
A causal net approach to relativistic quantum mechanics
International Nuclear Information System (INIS)
In this paper we discuss a causal network approach to describing relativistic quantum mechanics. Each vertex on the causal net represents a possible point event or particle observation. By constructing the simplest causal net based on Reichenbach-like conjunctive forks in proper time we can exactly derive the 1+1 dimension Dirac equation for a relativistic fermion and correctly model quantum mechanical statistics. Symmetries of the net provide various quantum mechanical effects such as quantum uncertainty and wavefunction, phase, spin, negative energy states and the effect of a potential. The causal net can be embedded in 3+1 dimensions and is consistent with the conventional Dirac equation. In the low velocity limit the causal net approximates to the Schrodinger equation and Pauli equation for an electromagnetic field. Extending to different momentum states the net is compatible with the Feynman path integral approach to quantum mechanics that allows calculation of well known quantum phenomena such as diffraction.
Multilevel Mixture Kalman Filter
Directory of Open Access Journals (Sweden)
Xiaodong Wang
2004-11-01
Full Text Available The mixture Kalman filter is a general sequential Monte Carlo technique for conditional linear dynamic systems. It generates samples of some indicator variables recursively based on sequential importance sampling (SIS and integrates out the linear and Gaussian state variables conditioned on these indicators. Due to the marginalization process, the complexity of the mixture Kalman filter is quite high if the dimension of the indicator sampling space is high. In this paper, we address this difficulty by developing a new Monte Carlo sampling scheme, namely, the multilevel mixture Kalman filter. The basic idea is to make use of the multilevel or hierarchical structure of the space from which the indicator variables take values. That is, we draw samples in a multilevel fashion, beginning with sampling from the highest-level sampling space and then draw samples from the associate subspace of the newly drawn samples in a lower-level sampling space, until reaching the desired sampling space. Such a multilevel sampling scheme can be used in conjunction with the delayed estimation method, such as the delayed-sample method, resulting in delayed multilevel mixture Kalman filter. Examples in wireless communication, specifically the coherent and noncoherent 16-QAM over flat-fading channels, are provided to demonstrate the performance of the proposed multilevel mixture Kalman filter.
Explaining slow convergence of EM in low noise linear mixtures
DEFF Research Database (Denmark)
Petersen, Kaare Brandt; Winther, Ole
2005-01-01
This report conducts an investigation of the convergence properties of the EM algorithm used for linear mixture models. Since the linear mixture model is a rather general approach, the analysis is relevant for a wide range of models which to some degree are subsets of each other: Independent...... Component Analysis (ICA), probabilistic PCA, Factor Analysis (FA), Independent Factor Analysis (IFA) and Mean Field ICA....
Degenerate atom-molecule mixture in a cold Fermi gas
International Nuclear Information System (INIS)
We show that the atom-molecule mixture formed in a degenerate atomic Fermi gas with interspecies repulsion near a Feshbach resonance constitutes a peculiar system where the atomic component is almost nondegenerate but quantum degeneracy of molecules is important. We develop a thermodynamic approach for studying this mixture, explain experimental observations, and predict optimal conditions for achieving molecular Bose-Einstein condensation
Degenerate Atom-Molecule Mixture in a Cold Fermi Gas
Kokkelmans, S.J.J.M.F.; Shlyapnikov, G. V.; Salomon, R.
2004-01-01
We show that the atom-molecule mixture formed in a degenerate atomic Fermi gas with interspecies repulsion near a Feshbach resonance, constitutes a peculiar system where the atomic component is almost non-degenerate but quantum degeneracy of molecules is important. We develop a thermodynamic approach for studying this mixture, explain experimental observations and predict optimal conditions for achieving molecular BEC.
Option Pricing with Asymmetric Heteroskedastic Normal Mixture Models
DEFF Research Database (Denmark)
Rombouts, Jeroen V. K; Stentoft, Lars
2015-01-01
2011, and compute dollar losses and implied standard deviation losses. We compare our results to those of existing mixture models and other benchmarks like component models and jump models. Using the model confidence set test, the overall dollar root mean squared error of the best performing benchmark...... model is significantly larger than that of the best mixture model....
Radio thermoluminescence of highly elastic polymer mixtures
International Nuclear Information System (INIS)
Modification of polymers by mixing with other polymers improves their electro physical and physical-mechanical properties. Under this mode modification is observed as critical phenomena in the properties that are associated with the interfacial structure of the components, the relaxation of internal connections and changing the degree of homogenization. Depending on the choice of the same polymer as a matrix or modifier may significantly distinguish properties of the composition. One of the most reliable methods of studying of the process of component compatibility of polymer mixtures are radio thermoluminescence (RTL). It is known that heterogeneous polymers and polymer mixtures are characterized by having two or more glass transition temperatures (Tc). On radiation curve of RTL is observed ρ - maximums, corresponding to each of the components.
International Nuclear Information System (INIS)
The possibility has been shown of using different-ligand complexes of rare earths with phthalexones and cetylpyridinium for differential spectrophotometric determination of rare earths in mixtures. The molar absorptivities of individual components of a mixture are not constant values if the total mixture concentration changes. The application of an equation for calculation of mixture absorbances makes it possible to change concentration of the components in mixtures over a wide range (the limit Me1:Me2 ratio is 1:50). Simultaneous nomographic determinations of gadolinium and dysprosium in their mixtures were carried out
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.
Dijk, van J.; Breedveld, P.C.
1991-01-01
The existence of zero-order causal paths in bond graphs of physical systems implies the set of state equations to be an implicit mixed set of Differential and Algebraic Equations (DAEs). In the block diagram expansion of such a bond graph, this type of causal path corresponds with a zero-order loop.
Sizochenko, Natalia; Gajewicz, Agnieszka; Leszczynski, Jerzy; Puzyn, Tomasz
2016-03-01
In this paper, we suggest that causal inference methods could be efficiently used in Quantitative Structure-Activity Relationships (QSAR) modeling as additional validation criteria within quality evaluation of the model. Verification of the relationships between descriptors and toxicity or other activity in the QSAR model has a vital role in understanding the mechanisms of action. The well-known phrase ``correlation does not imply causation'' reflects insight statistically correlated with the endpoint descriptor may not cause the emergence of this endpoint. Hence, paradigmatic shifts must be undertaken when moving from traditional statistical correlation analysis to causal analysis of multivariate data. Methods of causal discovery have been applied for broader physical insight into mechanisms of action and interpretation of the developed nano-QSAR models. Previously developed nano-QSAR models for toxicity of 17 nano-sized metal oxides towards E. coli bacteria have been validated by means of the causality criteria. Using the descriptors confirmed by the causal technique, we have developed new models consistent with the straightforward causal-reasoning account. It was proven that causal inference methods are able to provide a more robust mechanistic interpretation of the developed nano-QSAR models.In this paper, we suggest that causal inference methods could be efficiently used in Quantitative Structure-Activity Relationships (QSAR) modeling as additional validation criteria within quality evaluation of the model. Verification of the relationships between descriptors and toxicity or other activity in the QSAR model has a vital role in understanding the mechanisms of action. The well-known phrase ``correlation does not imply causation'' reflects insight statistically correlated with the endpoint descriptor may not cause the emergence of this endpoint. Hence, paradigmatic shifts must be undertaken when moving from traditional statistical correlation analysis to causal
Obesity and asthma: co-morbidity or causal relationship?
van Huisstede, A; Braunstahl, G J
2010-09-01
There is substantial evidence that obesity and asthma are related. "Obese asthma" may be a unique phenotype of asthma, characterized by decreased lung volumes, greater symptoms for a given degree of lung function impairment, destabilization or lack of asthma control, lack of eosinophilic inflammation and a different response to controller medication. Whether this relationship between obesity and asthma is causal or represents co-morbidity due to other factors is unclear. In previous reviews concerning the relationship between obesity and asthma, five hypotheses were put forth. One of these hypotheses is that a low grade systemic inflammation caused by adipokines from the fat tissue causes or enhances bronchial inflammation. In animal models, there is an increasing amount of evidence for the role of adipokines derived from fat tissue in the relationship between obesity and asthma. The data are conflicting in humans. Since obesity is a component of the metabolic syndrome and the metabolic syndrome is also a form of systemic inflammation, it is to be expected that there is a relationship between metabolic syndrome and asthma. The few data that are available show that there is no relationship between metabolic syndrome and asthma, but there is one between the metabolic syndrome and asthma-like symptoms. Further research is needed to confirm the relationship between obesity and asthma in humans, where a rigorous approach in the diagnosis of asthma is essential. PMID:21214041
G-computation demonstration in causal mediation analysis.
Wang, Aolin; Arah, Onyebuchi A
2015-10-01
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. PMID:26537707
G-computation demonstration in causal mediation analysis
International Nuclear Information System (INIS)
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
Generalized Causal Set d'Alembertians
Aslanbeigi, Siavash; Sorkin, Rafael D
2014-01-01
We introduce a family of generalized d'Alembertian operators in D-dimensional Minkowski spacetimes which are manifestly Lorentz-invariant, retarded, and non-local, the extent of the nonlocality being governed by a single parameter $\\rho$. The prototypes of these operators arose in earlier work as averages of matrix operators meant to describe the propagation of a scalar field in a causal set. We generalize the original definitions to produce an infinite family of ''Generalized Causet Box (GCB) operators'' parametrized by certain coefficients $\\{a,b_n\\}$, and we derive the conditions on the latter needed for the usual d'Alembertian to be recovered in the infrared limit. The continuum average of a GCB operator is an integral operator, and it is these continuum operators that we mainly study. To that end, we compute their action on plane waves, or equivalently their Fourier transforms g(p) [p being the momentum-vector]. For timelike p, g(p) has an imaginary part whose sign depends on whether p is past or future-...
Causal mediation analysis with a latent mediator.
Albert, Jeffrey M; Geng, Cuiyu; Nelson, Suchitra
2016-05-01
Health researchers are often interested in assessing the direct effect of a treatment or exposure on an outcome variable, as well as its indirect (or mediation) effect through an intermediate variable (or mediator). For an outcome following a nonlinear model, the mediation formula may be used to estimate causally interpretable mediation effects. This method, like others, assumes that the mediator is observed. However, as is common in structural equations modeling, we may wish to consider a latent (unobserved) mediator. We follow a potential outcomes framework and assume a generalized structural equations model (GSEM). We provide maximum-likelihood estimation of GSEM parameters using an approximate Monte Carlo EM algorithm, coupled with a mediation formula approach to estimate natural direct and indirect effects. The method relies on an untestable sequential ignorability assumption; we assess robustness to this assumption by adapting a recently proposed method for sensitivity analysis. Simulation studies show good properties of the proposed estimators in plausible scenarios. Our method is applied to a study of the effect of mother education on occurrence of adolescent dental caries, in which we examine possible mediation through latent oral health behavior. PMID:26363769
Reconstructing Causal Biological Networks through Active Learning.
Cho, Hyunghoon; Berger, Bonnie; Peng, Jian
2016-01-01
Reverse-engineering of biological networks is a central problem in systems biology. The use of intervention data, such as gene knockouts or knockdowns, is typically used for teasing apart causal relationships among genes. Under time or resource constraints, one needs to carefully choose which intervention experiments to carry out. Previous approaches for selecting most informative interventions have largely been focused on discrete Bayesian networks. However, continuous Bayesian networks are of great practical interest, especially in the study of complex biological systems and their quantitative properties. In this work, we present an efficient, information-theoretic active learning algorithm for Gaussian Bayesian networks (GBNs), which serve as important models for gene regulatory networks. In addition to providing linear-algebraic insights unique to GBNs, leading to significant runtime improvements, we demonstrate the effectiveness of our method on data simulated with GBNs and the DREAM4 network inference challenge data sets. Our method generally leads to faster recovery of underlying network structure and faster convergence to final distribution of confidence scores over candidate graph structures using the full data, in comparison to random selection of intervention experiments. PMID:26930205
Reconstructing Causal Biological Networks through Active Learning.
Directory of Open Access Journals (Sweden)
Hyunghoon Cho
Full Text Available Reverse-engineering of biological networks is a central problem in systems biology. The use of intervention data, such as gene knockouts or knockdowns, is typically used for teasing apart causal relationships among genes. Under time or resource constraints, one needs to carefully choose which intervention experiments to carry out. Previous approaches for selecting most informative interventions have largely been focused on discrete Bayesian networks. However, continuous Bayesian networks are of great practical interest, especially in the study of complex biological systems and their quantitative properties. In this work, we present an efficient, information-theoretic active learning algorithm for Gaussian Bayesian networks (GBNs, which serve as important models for gene regulatory networks. In addition to providing linear-algebraic insights unique to GBNs, leading to significant runtime improvements, we demonstrate the effectiveness of our method on data simulated with GBNs and the DREAM4 network inference challenge data sets. Our method generally leads to faster recovery of underlying network structure and faster convergence to final distribution of confidence scores over candidate graph structures using the full data, in comparison to random selection of intervention experiments.
Dynamic causal models and autopoietic systems.
David, Olivier
2007-01-01
Dynamic Causal Modelling (DCM) and the theory of autopoietic systems are two important conceptual frameworks. In this review, we suggest that they can be combined to answer important questions about self-organising systems like the brain. DCM has been developed recently by the neuroimaging community to explain, using biophysical models, the non-invasive brain imaging data are caused by neural processes. It allows one to ask mechanistic questions about the implementation of cerebral processes. In DCM the parameters of biophysical models are estimated from measured data and the evidence for each model is evaluated. This enables one to test different functional hypotheses (i.e., models) for a given data set. Autopoiesis and related formal theories of biological systems as autonomous machines represent a body of concepts with many successful applications. However, autopoiesis has remained largely theoretical and has not penetrated the empiricism of cognitive neuroscience. In this review, we try to show the connections that exist between DCM and autopoiesis. In particular, we propose a simple modification to standard formulations of DCM that includes autonomous processes. The idea is to exploit the machinery of the system identification of DCMs in neuroimaging to test the face validity of the autopoietic theory applied to neural subsystems. We illustrate the theoretical concepts and their implications for interpreting electroencephalographic signals acquired during amygdala stimulation in an epileptic patient. The results suggest that DCM represents a relevant biophysical approach to brain functional organisation, with a potential that is yet to be fully evaluated. PMID:18575681
Causality and supersymmetry in the superstring theory
International Nuclear Information System (INIS)
Reduction of the ten-dimensional, heterotic-superstring effective action S-circumflex including quartic higher-derivative terms R-circumflex4 yields a physical four-action S which is tachyon-free up to quadratic order R2 - the masses M0 and M2 of the spin-0 and spin-2 particles are both real - when the internal six-space is a Calabi-Yau metric g-barμν and N=1 supersymmetry is preserved via equation dH-bar≡tr(R-bar and R-bar)-Tr(F-bar and F-bar)/30=0, where H-barμνξ is the totally antisymmetric three-index field (while the bosonic string and type-II superstring may contain a spin-2 tachyon and a spin-0 tachyon, respectively). Here, we show that this crucial feature is independent of imposing supersymmetry, for if dH-bar≠ 0, there is an additional contribution to R2 which, however, produces no tachyons. Thus, the requirement of a stable, causal theory singles out the heterotic superstring irrespective of the requirement of N=1 supersymmetry, which is essential at high energies rather for its roles in the vanishing of the cosmological constant and the maintenance of the gauge hierarchy
Body selectivity in occipitotemporal cortex: Causal evidence.
Downing, Paul E; Peelen, Marius V
2016-03-01
Perception of others' bodies provides information that is useful for a number of important social-cognitive processes. Evidence from neuroimaging methods has identified focal cortical regions that are highly selective for perceiving bodies and body parts, including the extrastriate body area (EBA) and fusiform body area (FBA). Our understanding of the functional properties of these regions, and their causal contributions to behavior, has benefitted from the study of neuropsychological patients and particularly from investigations using transcranial magnetic stimulation (TMS). We review this evidence, focusing on TMS studies that are revealing of how (and when) activity in EBA contributes to detecting people in natural scenes; to resolving their body shape, movements, actions, individual parts, and identities; and to guiding goal-directed behavior. These findings are considered in reference to a framework for body perception in which the patterns of neural activity in EBA and FBA jointly serve to make explicit the elements of the visual scene that correspond to the body and its parts. These representations are modulated by other sources of information such as prior knowledge, and are shared with wider brain networks involved in many aspects of social cognition. PMID:26044771
Adaptive Gaussian Mixture Filter Based on Statistical Linearization
Huber, Marco F.
2012-01-01
Gaussian mixtures are a common density representation in nonlinear, non-Gaussian Bayesian state estimation. Selecting an appropriate number of Gaussian components, however, is difficult as one has to trade of computational complexity against estimation accuracy. In this paper, an adaptive Gaussian mixture filter based on statistical linearization is proposed. Depending on the nonlinearity of the considered estimation problem, this filter dynamically increases the number of components via spli...
STAR-POLYMER -- COLLOID MIXTURES
Directory of Open Access Journals (Sweden)
J.Dzubiella
2002-01-01
Full Text Available Recent results in theory and simulation of star-polymer--colloid mixtures are reviewed. We present the effective interaction between hard, colloidal particles and star polymers in a good solvent derived by monomer-resolved Molecular Dynamics simulations and theoretical arguments. The relevant parameters are the size ratio q between the stars and the colloids, as well as the number of polymeric arms f (functionality attached to the common center of the star. By covering a wide range of q's ranging from zero (star against a flat wall up to about 0.5, we establish analytical forms for the star-colloid interaction which are in excellent agreement with simulation results. By employing this cross interaction and the effective interactions between stars and colloids themselves, a demixing transition in the fluid phase is observed and systematically investigated for different arm numbers and size ratios. The demixing binodals are compared with experimental observations and found to be consistent. Furthermore, we map the full two-component system on an effective one-component description for the colloids, by inverting the two-component Ornstein-Zernike equations. Some recent results for the depletion interaction and freezing transitions are shown.
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...
Time reordered: Causal perception guides the interpretation of temporal order.
Bechlivanidis, Christos; Lagnado, David A
2016-01-01
We present a novel temporal illusion in which the perceived order of events is dictated by their perceived causal relationship. Participants view a simple Michotte-style launching sequence featuring 3 objects, in which one object starts moving before its presumed cause. Not only did participants re-order the events in a causally consistent way, thus violating the objective temporal order, but they also failed to recognise the clip they had seen, preferring a clip in which temporal and causal order matched. We show that the effect is not due to lack of attention to the presented events and we discuss the problem of determining whether causality affects temporal order at an early perceptual stage or whether it distorts an accurately perceived order during retrieval. Alternatively, we propose a mechanism by which temporal order is neither misperceived nor misremembered but inferred "on-demand" given phenomenal causality and the temporal priority principle, the assumption that causes precede their effects. Finally, we discuss how, contrary to theories of causal perception, impressions of causality can be generated from dynamic sequences with strong spatiotemporal deviations. PMID:26402648
Causality between Prices and Wages: VECM Analysis for EU-27
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Adriatik Hoxha
2010-09-01
Full Text Available The literature on causality as well as the empirical evidence clearly shows that there are two opposing groups of economists, who support different hypotheses with respect to the flow of causality in the price-wage causal relationship. The first group argues that causality runs from wages to prices, whereas the second argues that effect flows from prices to wages. Nonetheless, the literature review suggeststhat there is at least some consensus in that researcher’s conclusions may be contingent on the type of data employed, applied econometric model, or even that relationship may alter with economic cycles. This paper empirically examines theprice-wage causal relationship in EU-27, by using the OLS and VECM analysis, and it also provides robust evidence in support of a bilateral causal relationship between prices and wages, both in long-run as well as in the shortrun.Prior to designing and estimating the econometric model we have performed stationarity tests for the employed price, wage and productivity variables. Additionally, we have also specified the model taking into account the lag order as well as the rank of co-integration for the co-integrated variables. Furthermore, we have also applied respective restrictions on the parameters of estimatedVECM. The evidence resulting from model robustness checks indicates that results are statistically robust. Although far from closing the issue of causality between prices and wages, this paper at least provides some fresh evidence in the case of EU-27.
Causality between Prices and Wages: VECM Analysis for EU-12
Directory of Open Access Journals (Sweden)
Adriatik HOXHA
2010-05-01
Full Text Available The literature on causality as well as the empirical evidence clearly shows that there are two opposing groups of economists, who support different hypotheses with respect to the flow of causality in the price-wage causal relationship. The first group argues that causality runs from wages to price, whereas the second argue that effect flows from prices to wages. Nonetheless, there is at least some consensus that researchers conclusions may be contingent on the type of data employed, applied econometric model, or even that the relationship may vary through economic cycles. This paper empirically examines the pricewage causal relationship in EMU, by using OLS and VECM analysis, and also it provides robust evidence in support of a bilateral causal relationship between prices and wages, both in long-run as well as in the short-run. Prior to designing and estimating the econometric model we have performed stationarity tests for the employed price, wage and productivity variables. Additionally, we have also specified the model taking into account the lag order as well as the rank of co-integration for the co-integrated variables. Furthermore, we have also applied respective restrictions on the parameters of the estimated VECM and finally model robustness checks indicate that results are statistically robust. Although far from closing the issue of causality between prices and variables, this paper at least provides some fresh evidence for the case of EMU.
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
A Complex Systems Approach to Causal Discovery in Psychiatry.
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Glenn N Saxe
Full Text Available Conventional research methodologies and data analytic approaches in psychiatric research are unable to reliably infer causal relations without experimental designs, or to make inferences about the functional properties of the complex systems in which psychiatric disorders are embedded. This article describes a series of studies to validate a novel hybrid computational approach--the Complex Systems-Causal Network (CS-CN method-designed to integrate causal discovery within a complex systems framework for psychiatric research. The CS-CN method was first applied to an existing dataset on psychopathology in 163 children hospitalized with injuries (validation study. Next, it was applied to a much larger dataset of traumatized children (replication study. Finally, the CS-CN method was applied in a controlled experiment using a 'gold standard' dataset for causal discovery and compared with other methods for accurately detecting causal variables (resimulation controlled experiment. The CS-CN method successfully detected a causal network of 111 variables and 167 bivariate relations in the initial validation study. This causal network had well-defined adaptive properties and a set of variables was found that disproportionally contributed to these properties. Modeling the removal of these variables resulted in significant loss of adaptive properties. The CS-CN method was successfully applied in the replication study and performed better than traditional statistical methods, and similarly to state-of-the-art causal discovery algorithms in the causal detection experiment. The CS-CN method was validated, replicated, and yielded both novel and previously validated findings related to risk factors and potential treatments of psychiatric disorders. The novel approach yields both fine-grain (micro and high-level (macro insights and thus represents a promising approach for complex systems-oriented research in psychiatry.
Two-Microphone Separation of Speech Mixtures
DEFF Research Database (Denmark)
Pedersen, Michael Syskind; Wang, DeLiang; Larsen, Jan;
2008-01-01
Separation of speech mixtures, often referred to as the cocktail party problem, has been studied for decades. In many source separation tasks, the separation method is limited by the assumption of at least as many sensors as sources. Further, many methods require that the number of signals within...... been combined, independent component analysis (ICA) and binary time–frequency (T–F) masking. By estimating binary masks from the outputs of an ICA algorithm, it is possible in an iterative way to extract basis speech signals from a convolutive mixture. The basis signals are afterwards improved by...... grouping similar signals. Using two microphones, we can separate, in principle, an arbitrary number of mixed speech signals. We show separation results for mixtures with as many as seven speech signals under instantaneous conditions. We also show that the proposed method is applicable to segregate speech...
Causality and prediction: differences and points of contact
Directory of Open Access Journals (Sweden)
Luis Carlos Silva Ayçaguer, PhD
2014-09-01
Full Text Available This contribution presents the differences between those variables that might play a causal role in a certain process and those only valuable for predicting the outcome. Some considerations are made about the core intervention of the association and the temporal precedence and biases in both cases, the study of causality and predictive modeling. In that context, several relevant aspects related to the design of the corresponding studies are briefly reviewed and some of the mistakes that are often committed in handling both, causality and prediction, are illustrated.
Stock Market and Economic Growth in Malaysia: Causality Test
Har Wai Mun; Ee Chun Siong; Tan Chai Thing
2009-01-01
Stock market has been associated with economic growth through its role as source for new private capital. On the other hand, economic growth may be the catalyst for stock market growth. Thus, the purpose of this paper was to explore causal relationships between stock market and the economy using formal tests of causality developed by C. J. Granger and yearly Malaysia data for the period 1977-2006. Results show that stock market Granger-caused economic activity with no reverse causality obser...
Spatial Causality. An application to the Deforestation Process in Bolivia
Directory of Open Access Journals (Sweden)
Javier Aliaga
2011-01-01
Full Text Available This paper analyses the causes of deforestation for a representative set of Bolivian municipalities. The literature on environmental economics insists on the importance of physical and social factors. We focus on the last group of variables. Our objective is to identify causal mechanisms between these factors of risk and the problem of deforestation. To this end, we present a testing strategy for spatial causality, based on a sequence of Lagrange Multipliers. The results that we obtain for the Bolivian case confirm only partially the traditional view of the problem of deforestation. Indeed, we only find unequivocal signs of causality in relation to the structure of property rights.
Effects of inhomogeneity on the causal entropic prediction of Λ
Phillips, Daniel; Albrecht, Andreas
2011-12-01
The causal entropic principle aims to predict the unexpectedly small value of the cosmological constant Λ using a weighting by entropy increase on causal diamonds. The original work assumed a purely isotropic and homogeneous cosmology. But even the level of inhomogeneity observed in our universe forces reconsideration of certain arguments about entropy production. In particular, we must consider an ensemble of causal diamonds associated with each background cosmology and we can no longer immediately discard entropy production in the far future of the universe. Depending on our choices for a probability measure and our treatment of black hole evaporation, the prediction for Λ may be left intact or dramatically altered.
Quantitative measurement of mixtures by terahertz time-domain spectroscopy
Indian Academy of Sciences (India)
Guifeng Liu; Zengyan Zhang; Shihua Ma; Hongwei Zhao; Xiaojing Ma; Wenfeng Wang
2009-07-01
Terahertz time-domain spectroscopy (THz-TDS) was applied for quantitatively analysing a series of binary mixtures and a ternary mixture. Binary mixtures having different weight ratios of two components, -aminophenol and m-nitroaniline, were investigated by THz-TDS in the range of 0.3 to 1.5 THz, and it was found that the absorption coefficients of the components in each mixture were linearly proportional to their concentrations in the mixture. The results from analysis were in agreement with actual values with a relative error of less than 7%. The quantitative method will help in the detection of illegal drugs, poisons and dangerous materials that are wrapped or mixed with other materials.
Subband-based Single-channel Source Separation of Instantaneous Audio Mixtures
Taghia, Jalil; Doostari, Mohammad Ali
2009-01-01
In this paper, a new algorithm is developed to separate the audio sources from a single instantaneous mixture. The algorithm is based on subband decomposition and uses a hybrid system of Empirical Mode Decomposition (EMD) and Principle Component Analysis (PCA) to construct artificial observations from the single mixture. In the separation stage of algorithm, we use Independent Component Analysis (ICA) to find independent components. At first the observed mixture is divided into a finite numbe...
Yuan, Zhen
2014-03-01
Identifying directional influences in neural circuits from functional near infrared spectroscopy (fNIRS) recordings presents one of the main challenges for understanding brain dynamics. In this study a new strategy that combines Granger causality mapping (GCM) and independent component analysis (ICA) is proposed to reveal complex neural network dynamics underlying cognitive processes with fNIRS measurements. The GCM-ICA algorithm implements the following two procedures: (i) extraction of the region of interests (ROIs) of cortical activations by ICA, and (ii) estimation of the direct causal influences in local brain networks using Granger causality among voxels of ROIs. Our results show the use of GCM in conjunction with ICA is able to effectively capture the brain network dynamics in time-frequency domain with significantly reduced computational cost. We thus suggest that the GCM-ICA technique is a potentially valuable tool that could be used for the investigation of directional causality influences of brain network dynamics in biophotonics fields.
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.
Directory of Open Access Journals (Sweden)
Argyris Arnellos
2005-02-01
Full Text Available Initially, the analysis and development of adaptive artificial systems has been based in metaphors taken from philosophical schools as well as the disciplines of biology and cognitive science. So far, the dominant approaches exhibit many advantages in specific domains of application but there all have a certain drawback, which is their inability to produce an artificial system which will be able to internally ground its representations so as to use them to produce newer, more developed ones. The respective frameworks are studied in terms of this inability and it is concluded that the problem is traced in the purely causal treatment, function and creation of the notion of representation, wherever it is used. In the case of purely dynamic systems, where the representations seem not to be very useful, it is proposed that the incorporation of a special non-causal kind of representations would give a framework which seems promising in realizing real adaptation. The relevant architecture is analyzed and discussed mainly in terms of its functionality and its contribution to the integration of pragmatic meaning aspects in an artificial system's interaction.
Eventos Quânticos e Reducionismo Causal
Directory of Open Access Journals (Sweden)
Osvaldo Pessoa Jr.
2013-12-01
Full Text Available This paper is the first step in an investigation of whether microscopic events can be reduced to a mereological composition of elementary events, especially in biological systems. The hypothesis is made that, between events in which quanta are exchanged, there is causal flow, but strictly speaking no events take place. A causal event is characterized by the possibility of an intervention or manipulation. Thus, three types of quantum mechanical events may be found: (1 detection of a quantum of energy; (2 confinement by an apparatus in a Glauber coherent state; (3 null result measurement (without exchange of quanta. The paper explores these three types of elementary causal events, e sets forth as the next step the investigation of the causal events involved in the action of a molecular motor.
On the causal structure between CO2 and global temperature.
Stips, Adolf; Macias, Diego; Coughlan, Clare; Garcia-Gorriz, Elisa; Liang, X San
2016-01-01
We use a newly developed technique that is based on the information flow concept to investigate the causal structure between the global radiative forcing and the annual global mean surface temperature anomalies (GMTA) since 1850. Our study unambiguously shows one-way causality between the total Greenhouse Gases and GMTA. Specifically, it is confirmed that the former, especially CO2, are the main causal drivers of the recent warming. A significant but smaller information flow comes from aerosol direct and indirect forcing, and on short time periods, volcanic forcings. In contrast the causality contribution from natural forcings (solar irradiance and volcanic forcing) to the long term trend is not significant. The spatial explicit analysis reveals that the anthropogenic forcing fingerprint is significantly regionally varying in both hemispheres. On paleoclimate time scales, however, the cause-effect direction is reversed: temperature changes cause subsequent CO2/CH4 changes. PMID:26900086
Environment - Assisted Invariance, Causality, and Probabilities in Quantum Physics
Zurek, W. H.
2002-01-01
I introduce environment - assisted invariance -- a symmetry related to causality that is exhibited by correlated quantum states -- and describe how it can be used to understand the nature of ignorance and, hence, the origin of probabilities in quantum physics.
On the causal structure between CO2 and global temperature
Stips, Adolf; Macias, Diego; Coughlan, Clare; Garcia-Gorriz, Elisa; Liang, X. San
2016-02-01
We use a newly developed technique that is based on the information flow concept to investigate the causal structure between the global radiative forcing and the annual global mean surface temperature anomalies (GMTA) since 1850. Our study unambiguously shows one-way causality between the total Greenhouse Gases and GMTA. Specifically, it is confirmed that the former, especially CO2, are the main causal drivers of the recent warming. A significant but smaller information flow comes from aerosol direct and indirect forcing, and on short time periods, volcanic forcings. In contrast the causality contribution from natural forcings (solar irradiance and volcanic forcing) to the long term trend is not significant. The spatial explicit analysis reveals that the anthropogenic forcing fingerprint is significantly regionally varying in both hemispheres. On paleoclimate time scales, however, the cause-effect direction is reversed: temperature changes cause subsequent CO2/CH4 changes.
Holographic entanglement and causal information in coherent states
International Nuclear Information System (INIS)
Scalar solitons in global AdS4 are holographically dual to coherent states carrying a non-trivial condensate of a scalar operator. We study the holographic information content of these states, focusing on a particular spatial region, by examining the entanglement entropy and causal holographic information. We show generically that whenever the dimension of the condensed operator is sufficiently low (characterized by the double-trace operator becoming relevant), such coherent states have lower entanglement and causal holographic information than the vacuum state of the system, despite having greater energy. We also use these geometries to illustrate the fact that causal wedges associated with a simply-connected boundary region can have non-trivial topology even in causally trivial spacetimes
Causal association rule mining methods based on fuzzy state description
Institute of Scientific and Technical Information of China (English)
Liang Kaijian; Liang Quan; Yang Bingru
2006-01-01
Aiming at the research that using more new knowledge to develope knowledge system with dynamic accordance, and under the background of using Fuzzy language field and Fuzzy language values structure as description framework, the generalized cell Automation that can synthetically process fuzzy indeterminacy and random indeterminacy and generalized inductive logic causal model is brought forward. On this basis, a kind of the new method that can discover causal association rules is provded. According to the causal information of standard sample space and commonly sample space,through constructing its state (abnormality) relation matrix, causal association rules can be gained by using inductive reasoning mechanism. The estimate of this algorithm complexity is given,and its validity is proved through case.
Causality assessment: A brief insight into practices in pharmaceutical industry
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R Purushotham Naidu
2013-01-01
Full Text Available Healthcare industry is flooded with multitude of drugs, and the list is increasing day by day. Consumption of medications has enormously increased due to life style changes, having safer drugs is the need of the hour. Regulators and other authorities to have a check have put in stringent regulations and pharmacovigilance system in place. Eventhough there has been increase in adverse drug reactions (ADR reporting in the last decade, causality assessment has been the greater challenge for academicians and even industry. Causality is crucial for risk benefit assessment, particularly when it involves post marketing safety signals. Pharmaceutical companies have put in efforts to have a standardized approach for causality assessment. This article will provide some insight into the approaches for causality assessment from a pharma industry perspective.
Replicating the benefits of closed timelike curves without breaking causality
Yuan, Xiao; Thompson, Jayne; Haw, Jing Yan; Vedral, Vlatko; Ralph, Timothy C; Lam, Ping Koy; Weedbrook, Christian; Gu, Mile
2014-01-01
In general relativity, closed timelike curves can break causality with remarkable and unsettling consequences. At the classical level, they induce causal paradoxes disturbing enough to motivate conjectures that explicitly prevent their existence. At the quantum level, resolving such paradoxes induce radical benefits - from cloning unknown quantum states to solving problems intractable to quantum computers. Instinctively, one expects these benefits to vanish if causality is respected. Here we show that in harnessing entanglement, we can efficiently solve NP-complete problems and clone arbitrary quantum states - even when all time-travelling systems are completely isolated from the past. Thus, the many defining benefits of closed timelike curves can still be harnessed, even when causality is preserved. Our results unveil the subtle interplay between entanglement and general relativity, and significantly improve the potential of probing the radical effects that may exist at the interface between relativity and q...
Learning Why Things Change: The Difference-Based Causality Learner
Voortman, Mark; Druzdzel, Marek J
2012-01-01
In this paper, we present the Difference- Based Causality Learner (DBCL), an algorithm for learning a class of discrete-time dynamic models that represents all causation across time by means of difference equations driving change in a system. We motivate this representation with real-world mechanical systems and prove DBCL's correctness for learning structure from time series data, an endeavour that is complicated by the existence of latent derivatives that have to be detected. We also prove that, under common assumptions for causal discovery, DBCL will identify the presence or absence of feedback loops, making the model more useful for predicting the effects of manipulating variables when the system is in equilibrium. We argue analytically and show empirically the advantages of DBCL over vector autoregression (VAR) and Granger causality models as well as modified forms of Bayesian and constraintbased structure discovery algorithms. Finally, we show that our algorithm can discover causal directions of alpha r...
Experimental investigation of the critical ionization velocity in gas mixtures
International Nuclear Information System (INIS)
The critical ionization velocity which is of cosmogonic and astrophysical interest has hitherto mainly been investigated for pure gases. Since in space there are always gas mixtures, it is of interest also to study gas mixtures. The present report, which is a summary of a more detailed report (Axnas, 1976), summarizes the results of systematic experiments on the critical ionization velocity as a function of the mixing ratio for binary gas mixtures of H2, He, N2, O2, Ne and Ar. The apparatus used is a coaxial plasma gun with an azimuthal magnetic 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. (Auth.)
Causality and complexity: the myth of objectivity in science.
Mikulecky, Donald C
2007-10-01
Two distinctly different worldviews dominate today's thinking in science and in the world of ideas outside of science. Using the approach advocated by Robert M. Hutchins, it is possible to see a pattern of interaction between ideas in science and in other spheres such as philosophy, religion, and politics. Instead of compartmentalizing these intellectual activities, it is worthwhile to look for common threads of mutual influence. Robert Rosen has created an approach to scientific epistemology that might seem radical to some. However, it has characteristics that resemble ideas in other fields, in particular in the writings of George Lakoff, Leo Strauss, and George Soros. Historically, the atmosphere at the University of Chicago during Hutchins' presidency gave rise to Rashevsky's relational biology, which Rosen carried forward. Strauss was writing his political philosophy there at the same time. One idea is paramount in all this, and it is Lakoff who gives us the most insight into how the worldviews differ using this idea. The central difference has to do with causality, the fundamental concept that we use to build a worldview. Causal entailment has two distinct forms in Lakoff 's analysis: direct causality and complex causality. Rosen's writings on complexity create a picture of complex causality that is extremely useful in its detail, grounding in the ideas of Aristotle. Strauss asks for a return to the ancients to put philosophy back on track. Lakoff sees the weaknesses in Western philosophy in a similar way, and Rosen provides tools for dealing with the problem. This introduction to the relationships between the thinking of these authors is meant to stimulate further discourse on the role of complex causal entailment in all areas of thought, and how it brings them together in a holistic worldview. The worldview built on complex causality is clearly distinct from that built around simple, direct causality. One important difference is that the impoverished causal
Causality between Electricity Consumption & Economic growth : Empirical Evidence from India
Gupta, Geetu; Sahu, Naresh Chandra
2009-01-01
In this study ,an attempt has been made to investigate causality between electricity consumption and economic growth in India by adopting Granger Engel causality model for 1960-2006 period .Test results shows that electricity consumption has positive effect on economic growth. The paper support for the reforms in power sector and indicates that electricity act as a catalyst in realizing various social and economic goals.
The role of causal links in performance measurement models
Kasperskaya, Yulia; Tayles, Michael
2013-01-01
Abstract Purpose: Several well-known managerial accounting performance measurement models rely on causal assumptions. Whilst users of the models express satisfaction and link them with improved organizational performance, academic research, of the realworld applications, shows few reliable statistical associations. This paper provides a discussion on the"problematic" of causality in a performance measurement setting. Design/methodology/approach: This is a conceptual study based on an analysis...
Sensitivity analyses for parametric causal mediation effect estimation
Albert, Jeffrey M.; Wang, Wei
2014-01-01
Causal mediation analysis uses a potential outcomes framework to estimate the direct effect of an exposure on an outcome and its indirect effect through an intermediate variable (or mediator). Causal interpretations of these effects typically rely on sequential ignorability. Because this assumption is not empirically testable, it is important to conduct sensitivity analyses. Sensitivity analyses so far offered for this situation have either focused on the case where the outcome follows a line...
The Direction of Causality between Insider Ownership and Market Valuation
Pedersen, Torben; Thomsen, Steen; Kvist, Hans Kurt
2001-01-01
The causal relationship between insider ownership and market valuation is tested on a database of the largest EU and US companies. Using a Granger causality test insider ownership (measured by the fraction of closely held shares) is found to have a negative effect on market valuation (measured as the simple Tobin's Q ratio). And market valuation is found to have a negative effect on insider ownership. Consistent with an overall non-linear relationship as hypothesised by Morck e...
The Causal Relationship between Health and Education Expenditures in Malaysia
Chor Foon TANG; Yew Wah LAI
2011-01-01
A major macroeconomic policy in generating economic growth is to encourage investments on human capital such as health and education. This is because both health and education make significant contribution to increasing productivity of the labour force which ultimately exerts a positive effect on raising output levels. A question that arises is whether investments on health and education have a causal relationship and if so, what is the directional causality? The objective o...
Causal Structure and Gravitational Waves in Brane World Cosmology
Ichiki, Kiyotomo; Nakamura, Kouji
2003-01-01
The causal structure of the flat brane universe of RSII type is re-investigated to clarify the boundary conditions for stochastic gravitational waves. In terms of the Gaussian normal coordinate of the brane, a singularity of the equation for gravitational waves appears in the bulk. We show that this singularity corresponds to the ``seam singularity'' which is a singular subspace on the brane universe. Based upon the causal structure, we discuss the boundary conditions for gravitational waves ...
A Tool for Qualitative Causal Reasoning On Complex Systems
Tahar Guerram; Ramdane Maamri; Zaidi Sahnoun
2010-01-01
A cognitive map, also called a mental map, is a representation and reasoning model on causal knowledge. It is a directed, labeled and cyclic graph whose nodes represent causes or effects and whose arcs represent causal relations between these nodes such as "increases", "decreases", "supports", and "disadvantages". A cognitive map represents beliefs (knowledge) which we lay out about a given domain of discourse and is useful as a means of decision making support. There are several types of cog...
Causal Linkages Between Domestic Terrorism and Economic Growth
Thomas Gries; Tim Krieger; Daniel Meierrieks
2009-01-01
We use the Hsiao-Granger method to test for growth-terrorism causality for seven Western European countries. In bivariate settings, the impact of economic performance on domestic terrorism is very strong. In trivariate settings, the impact of performance on terrorism diminishes. Here, we find that economic performance leads terrorist violence in robust ways only for three out of seven countries. Terrorism is almost never found to causally influence growth in bivariate and trivariate specifica...
The Causal Relationship Between Government Revenue and Expenditure in Namibia
Eita, Joel Hinaunye; Mbazima, Daisy
2008-01-01
The relationship between government revenue and government expenditure is important, given its relevance for policy especially with respect to the budget deficit. The purpose of this paper is to investigate the relationship between government revenue and government expenditure in Namibia. It investigates the causal relationship between government revenue and government expenditure using Granger causality test through cointegrated vector autoregression (VAR) methods for the period the period 1...
The causal effect of teen motherhood on worklessness
WALKER, Ian; Zhu, Yu
2009-01-01
Teen motherhood continues to be high in the US and the UK relative to most other western European countries. While recent research has clarified how effective policies to reduce teen motherhood might be (Kearney (2009)), there remains little evidence that quantifies the causal effects of teen motherhood on such mothers and their first born children. This paper provides estimates of the causal effect of teen motherhood on worklessness and does so by exploiting the availability of two sources o...
Re-assessing causal accounts of learnt behavior in rats.
Burgess, K V; Dwyer, D M; Honey, R C
2012-04-01
Rats received either a common-cause (i.e., A→B, A→food) or a causal-chain training scenario (i.e., B→A, A→food) before their tendency to approach the food magazine during the presentation of B was assessed as a function of whether it was preceded by a potential alternative cause. Causal model theory predicts that the influence of an alternative cause should be restricted to the common-cause scenario. In Experiment 1, responding to B was reduced when it occurred after pressing a novel lever during the test phase. This effect was not influenced by the type of training scenario. In Experiment 2, rats were familiarized with the lever prior to test by training it as a potential cause of B. After this treatment, the lever now failed to influence test responding to B. In Experiment 3, rats given common-cause training responded more to B when it followed a cue that had previously been trained as a predictor of B, than when it followed another stimulus. This effect was not apparent in rats that received causal-chain training. This pattern of results is the opposite of that predicted by causal model theory. Thus, in three experiments, the presence of an alternative cause failed to influence test responding in manner consistent with causal model theory. These results undermine the application of causal model theory to rats, but are consistent with associative analyses. PMID:22486754
Causal quantum theory and the collapse locality loophole
International Nuclear Information System (INIS)
Causal quantum theory is an umbrella term for ordinary quantum theory modified by two hypotheses: state vector reduction is a well-defined process, and strict local causality applies. The first of these holds in some versions of Copenhagen quantum theory and need not necessarily imply practically testable deviations from ordinary quantum theory. The second implies that measurement events which are spacelike separated have no nonlocal correlations. To test this prediction, which sharply differs from standard quantum theory, requires a precise definition of state vector reduction. Formally speaking, any precise version of causal quantum theory defines a local hidden variable theory. However, causal quantum theory is most naturally seen as a variant of standard quantum theory. For that reason it seems a more serious rival to standard quantum theory than local hidden variable models relying on the locality or detector efficiency loopholes. Some plausible versions of causal quantum theory are not refuted by any Bell experiments to date, nor is it evident that they are inconsistent with other experiments. They evade refutation via a neglected loophole in Bell experiments--the collapse locality loophole--which exists because of the possible time lag between a particle entering a measurement device and a collapse taking place. Fairly definitive tests of causal versus standard quantum theory could be made by observing entangled particles separated by ≅0.1 light seconds
The label switching problem in mixture models
Ali Etemad; Gholamhossein Gholami; Hamideh Rasi
2014-01-01
Mixture models are fascinating objects in that, while based on elementary distributions, they of-fer a much wider range of modeling possibilities than their components. They also need both highlycomplex computational challenges and delicate inferential derivations . In Bayesian framework thiskind of models do not admit an analytical solution and one should content him/her self by an ap-proximative solution.In this work, we introduce denition of identiability in statistical model. We focus on ...
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
Symmetries, causality problems and neutrino fields in antipode universes
International Nuclear Information System (INIS)
The S3xR and H3xR Lie groups are characterized, and using continuous deformations of S3 and H3 subgroups algebra, Lorentz space-time metrics with gE left invariance and gD 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 gE and gD isometries, it is shown that in the class of metrics associated to H3xR topology, there is a particular case which accepts a G7 group of isometries. It is shown that the gE and gD 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 gE (gD) metric containing neutrinos, with determined helicity, to another one with gD (gE)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.)
Toxicological evaluation of chemical mixtures
Feron, V.J.; Groten, J.P.
2002-01-01
This paper addresses major developments in the safety evaluation of chemical mixtures during the past 15 years, reviews today's state of the art of mixture toxicology, and discusses challenges ahead. Well-thought-out tailor-made mechanistic and empirical designs for studying the toxicity of mixtures
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.
Directory of Open Access Journals (Sweden)
Ninke Stukker
2009-06-01
Full Text Available Dans une hypothèse de catégorisation linguistique, les connecteurs de cause sont pris comme des outils de catégorisation. En effet, des études sur corpus suggèrent que les connecteurs sont fortement spécialisés dans une seule catégorie de causalité spécifique, mais aussi que leur usage n'est pas limité aux catégories de causalité auxquelles ils sont prototypiquement associés. Si nous supposons que le sens des connecteurs causaux peut être adéquatement décrit en référence à des catégories conceptuelles bien définies, comment pouvons-nous expliquer qu’il y ait une variation dans leur usage réel? Nous mettons l'accent sur les relations de cohérence causale volitionnelle, qui constituent le contexte d'usage prototypique du connecteur néerlandais daarom ‘c'est pourquoi’. Un autre moyen d’expression des relations causales volitionnelles est le recours au connecteur dus ‘alors/donc’ qui est prototypiquement utilisé dans les relations de causalité épistémique. Notre hypothèse est que les relations de causalité volitionnelle exprimées par daarom vs dus diffèrent systématiquement en termes de subjectivité. Nous proposons un modèle d'analyse qui contient de multiples opérationnalisation de la notion de subjectivité et une distinction entre différents niveaux de complexité (sous-clause, clause, et discours. Nous constatons que les relations causales volitionnelles en dus contiennent plus souvent des éléments subjectifs que les relations causales volitionnelles en daarom. Nous interprétons cette distribution au sein d'un cadre théorique fondé sur l'usage (usage-based framework, et nous proposons d'analyser les cas volitionnels de dus comme des instanciations non-prototypiques du sens de dus,qui est donc intrinsèquement subjectif et prototypiquement épistémique.Under a linguistic categorization hypothesis causal connectives are taken as categorization devices. Indeed, corpus studies suggest that
Enhancing scientific reasoning by refining students' models of multivariable causality
Keselman, Alla
Inquiry learning as an educational method is gaining increasing support among elementary and middle school educators. In inquiry activities at the middle school level, students are typically asked to conduct investigations and infer causal relationships about multivariable causal systems. In these activities, students usually demonstrate significant strategic weaknesses and insufficient metastrategic understanding of task demands. Present work suggests that these weaknesses arise from students' deficient mental models of multivariable causality, in which effects of individual features are neither additive, nor constant. This study is an attempt to develop an intervention aimed at enhancing scientific reasoning by refining students' models of multivariable causality. Three groups of students engaged in a scientific investigation activity over seven weekly sessions. By creating unique combinations of five features potentially involved in earthquake mechanism and observing associated risk meter readings, students had to find out which of the features were causal, and to learn to predict earthquake risk. Additionally, students in the instructional and practice groups engaged in self-directed practice in making scientific predictions. The instructional group also participated in weekly instructional sessions on making predictions based on multivariable causality. Students in the practice and instructional conditions showed small to moderate improvement in their attention to the evidence and in their metastrategic ability to recognize effective investigative strategies in the work of other students. They also demonstrated a trend towards making a greater number of valid inferences than the control group students. Additionally, students in the instructional condition showed significant improvement in their ability to draw inferences based on multiple records. They also developed more accurate knowledge about non-causal features of the system. These gains were maintained
UMA TEORÍA CAUSAL PARA LOS CASOS FREGE
Directory of Open Access Journals (Sweden)
ABEL WAJNERMAN PAZ
2015-06-01
Full Text Available Fodor ha argumentado a favor de un par de tesis que pueden caracterizarse como constituyendo un dilema: Por un lado, si adoptamos una teoría funcional para los conceptos explicamos semánticamente los casos Frege pero caemos en el holismo semántico. Por otro lado, si adoptamos una teoría causal/informacional evitamos el holismo pero no explicamos los casos Frege semánticamente. Fodor (por ej, 1994, 1998 y 2008 intenta evitar la segunda parte del dilema argumentando que los casos de Frege pueden tener una explicación sintáctica y no semántica. En este trabajo intentaré ofrecer una salida alternativa al dilema fodoriano. Propondré una explicación semántica de los casos Frege que incorpora tanto elementos de una teoría causal como de una de rol funcional. Afirmaré que el contenido cognitivo o estrecho de un concepto (el tipo de contenido aparentemente exigido por los casos Frege es el conjunto de contenidos causales/informacionales de las representaciones que figuran en su rol funcional. Considero que individuar a las representaciones en los roles por medio de sus contenidos causales permite evitar el holismo (evitando el proceso de ramsificación típicamente empleado para individuar a los roles y que identificar el contenido cognitivo con contenidos causales/informacionales de las representaciones en los roles permite evitar el referencialismo de las propuestas causales (podemos distinguir sentido de referencia en términos causales.
General solutions and causality for a Voigt medium
Energy Technology Data Exchange (ETDEWEB)
Duren, R.E.; Heestand, R.L. [Exxon Production Co., Houston, TX (United States)
1995-01-01
A 1-D wave equation solution for a propagating seismic pulse in a Voigt medium can be obtained by using a separation of variables to find time harmonic particular solutions and then superimposing the particular solutions. This superposition is a time convolution of the boundary condition (or incident pulse) and the medium`s impulse response. Even though causality is not introduced during the solution of the wave equation, the general solution is causal since the boundary condition is causal and the medium`s impulse response can be shown to be causal. The relationship between attenuation and phase velocity as well as their dependence on frequency arise from the form chosen for the particular solutions. The arbitrary constants associated with the particular solutions are determined by the boundary condition, and the initial condition is also dependent on the boundary condition; however, the initial condition is properly determined and does not depend on times after the initial time (thereby satisfying causality). The convolutional nature of the general solution allows it to also be expressed as a time convolution of the boundary conditions`s time derivative and the medium`s step function response. This expression can be viewed as a superposition of step function responses where the step function response is a particular solution to the wave equation obtained using an approach that is similar to one recently developed for propagating electric pulses. This new solution is obtained with the initial and boundary conditions being independently introduced during the solution of the wave equation. There is no frequency dependence in this solution, and the general solution is causal since it is a superposition of causal step function responses.
Feshbach resonances in mixtures of 6Li and 40K
International Nuclear Information System (INIS)
We report on the measurement of Feshbach resonances in Fermi-Fermi mixtures. For this purpose we have created an ultracold mixture of the fermionic alkali isotopes 6Li and 40K in an optical dipole trap. In the same trap we have realized a three-component degenerate spin mixture of 40K -atoms at T 0.3TF. To create the mixture we start by loading a two-species magneto-optical trap (MOT) from two separate 2D-MOT sources. We realized for the first time a 2D-MOT source for lithium, yielding a large cold flux of up to 109 s-1. The mixture is then captured in an optically-plugged magnetic quadrupole trap. After sympathetic cooling of 6Li by 40K to T∝10μK the mixture is loaded into optical tweezers. The mixture is optically transported over a distance of 21.5 cm into a science cell where we measure Feshbach resonances using magnetic field coils designed for high homogeneity. We report on our progress measuring the width of Feshbach resonances in 6Li -40K mixtures and locating resonances in mixtures of 40K.
Gas-phase detonation propagation in mixture composition gradients.
Kessler, D A; Gamezo, V N; Oran, E S
2012-02-13
The propagation of detonations through several fuel-air mixtures with spatially varying fuel concentrations is examined numerically. The detonations propagate through two-dimensional channels, inside of which the gradient of mixture composition is oriented normal to the direction of propagation. The simulations are performed using a two-component, single-step reaction model calibrated so that one-dimensional detonation properties of model low- and high-activation-energy mixtures are similar to those observed in a typical hydrocarbon-air mixture. In the low-activation-energy mixture, the reaction zone structure is complex, consisting of curved fuel-lean and fuel-rich detonations near the line of stoichiometry that transition to decoupled shocks and turbulent deflagrations near the channel walls where the mixture is extremely fuel-lean or fuel-rich. Reactants that are not consumed by the leading detonation combine downstream and burn in a diffusion flame. Detonation cells produced by the unstable reaction front vary in size across the channel, growing larger away from the line of stoichiometry. As the size of the channel decreases relative to the size of a detonation cell, the effect of the mixture composition gradient is lessened and cells of similar sizes form. In the high-activation-energy mixture, detonations propagate more slowly as the magnitude of the mixture composition gradient is increased and can be quenched in a large enough gradient. PMID:22213660
Dynamic thermodiffusion model for binary liquid mixtures.
Eslamian, Morteza; Saghir, M Ziad
2009-07-01
Following the nonequilibrium thermodynamics approach, we develop a dynamic model to emulate thermo-diffusion process and propose expressions for estimating the thermal diffusion factor in binary nonassociating liquid mixtures. Here, we correlate the net heat of transport in thermodiffusion with parameters, such as the mixture temperature and pressure, the size and shape of the molecules, and mobility of the components, because the molecules have to become activated before they can move. Based on this interpretation, the net heat of transport of each component can be somehow related to the viscosity and the activation energy of viscous flow of the same component defined in Eyring's reaction-rate theory [S. Glasstone, K. J. Laidler, and H. Eyring, (McGraw-Hill, New York, 1941)]. This modeling approach is different from that of Haase and Kempers, in which thermodiffusion is considered as a function of the thermostatic properties of the mixture such as enthalpy. In simulating thermodiffusion, by correlating the net heat of transport with the activation energy of viscous flow, effects of the above mentioned parameters are accounted for, to some extent of course. The model developed here along with Haase-Kempers and Drickamer-Firoozabadi models linked with the Peng-Robinson equation of sate are evaluated against the experimental data for several recent nonassociating binary mixtures at various temperatures, pressures, and concentrations. Although the model prediction is still not perfect, the model is simple and easy to use, physically justified, and predicts the experimental data very good and much better than the existing models. PMID:19658691
Dynamic thermodiffusion model for binary liquid mixtures
Eslamian, Morteza; Saghir, M. Ziad
2009-07-01
Following the nonequilibrium thermodynamics approach, we develop a dynamic model to emulate thermo-diffusion process and propose expressions for estimating the thermal diffusion factor in binary nonassociating liquid mixtures. Here, we correlate the net heat of transport in thermodiffusion with parameters, such as the mixture temperature and pressure, the size and shape of the molecules, and mobility of the components, because the molecules have to become activated before they can move. Based on this interpretation, the net heat of transport of each component can be somehow related to the viscosity and the activation energy of viscous flow of the same component defined in Eyring’s reaction-rate theory [S. Glasstone, K. J. Laidler, and H. Eyring, The Theory of Rate Processes: The Kinetics of Chemical Reactions, Viscosity, Diffusion and Electrochemical Phenomena (McGraw-Hill, New York, 1941)]. This modeling approach is different from that of Haase and Kempers, in which thermodiffusion is considered as a function of the thermostatic properties of the mixture such as enthalpy. In simulating thermodiffusion, by correlating the net heat of transport with the activation energy of viscous flow, effects of the above mentioned parameters are accounted for, to some extent of course. The model developed here along with Haase-Kempers and Drickamer-Firoozabadi models linked with the Peng-Robinson equation of sate are evaluated against the experimental data for several recent nonassociating binary mixtures at various temperatures, pressures, and concentrations. Although the model prediction is still not perfect, the model is simple and easy to use, physically justified, and predicts the experimental data very good and much better than the existing models.
Perceptual processing strategy and exposure influence the perception of odor mixtures.
Le Berre, Elodie; Thomas-Danguin, Thierry; Béno, Noëlle; Coureaud, Gérard; Etiévant, Patrick; Prescott, John
2008-02-01
In flavor perception, both experience with the components of odor/taste mixtures and the cognitive strategy used to examine the interactions between the components influence the overall mixture perception. However, the effect of these factors on odor mixtures perception has never been studied. The present study aimed at evaluating whether 1) previous exposure to the odorants included in a mixture or 2) the synthetic or analytic strategy engaged during odorants mixture evaluation determines odor representation. Blending mixtures, in which subjects perceived a unique quality distinct from those of components, were chosen in order to induce a priori synthetic perception. In the first part, we checked whether the chosen mixtures presented blending properties for our subjects. In the second part, 3 groups of participants were either exposed to the odorants contributing to blending mixtures with a "pineapple" or a "red cordial" odor or nonexposed. In a following task, half of each group was assigned to a synthetic or an analytical task. The synthetic task consisted of rating how typical (i.e., representative) of the target odor name (pineapple or red cordial) were the mixtures and each of their components. The analytical task consisted of evaluating these stimuli on several scales labeled with the target odor name and odor descriptors of the components. Previous exposure to mixture components was found to decrease mixture typicality but only for the pineapple blending mixture. Likewise, subjects engaged in an analytical task rated both blending mixtures as less typical than did subjects engaged in a synthetic task. This study supports a conclusion that odor mixtures can be perceived either analytically or synthetically according to the cognitive strategy engaged. PMID:18071197
International Nuclear Information System (INIS)
The main features of the EPR concerning the fabrication of the reactor are: -) the size of the components, -) the modification of the design compared with classical PWR, and -) an intensive use of forging (in particular the cold and hot legs of the primary circuit are forged). This series of slides overviews the fabrication of the components for the EPR by highlighting the differences with the previous generation of reactors. 4 types of components are reviewed: the reactor vessel and internals, steam generators, primary circuit pipes, and primary coolant pumps. (A.C.)
The Shared Causal Pasts and Futures of Cosmological Events
Friedman, Andrew S; Gallicchio, Jason
2013-01-01
We derive criteria for whether two cosmological events can have a shared causal past or a shared causal future, assuming a Friedmann-Lemaitre-Robertson-Walker universe with best-fit \\Lambda CDM cosmological parameters from the Planck satellite. We further derive criteria for whether either cosmic event could have been in past causal contact with our own worldline since the time of the hot "big bang", which we take to be the end of early-universe inflation. We find that pairs of objects such as quasars on opposite sides of the sky with redshifts z >= 3.65 have no shared causal past with each other or with our past worldline. More complicated constraints apply if the objects are at different redshifts from each other or appear at some relative angle less than 180 degrees, as seen from Earth. We present examples of observed quasar pairs that satisfy all, some, or none of the criteria for past causal independence. Given dark energy and the recent accelerated expansion, our observable universe has a finite conform...
The causality between energy consumption and economic growth in Turkey
International Nuclear Information System (INIS)
This paper applies the causality test to examine the causal relationship between primary energy consumption (EC) and real Gross National Product (GNP) for Turkey during 1970-2006. We employ unit root tests, the augmented Dickey-Fuller (ADF) and the Philips-Perron (PP), Johansen cointegration test, and Pair-wise Granger causality test to examine relation between EC and GNP. Our empirical results indicate that the two series are found to be non-stationary. However, first differences of these series lead to stationarity. Further, the results indicate that EC and GNP are cointegrated and there is bidirectional causality running from EC to GNP and vice versa. This means that an increase in EC directly affects economic growth and that economic growth also stimulates further EC. This bidirectional causality relationship between EC and GNP determined for Turkey at 1970-2006 period is in accordance with the ones in literature reported for similar countries. Consequently, we conclude that energy is a limiting factor to economic growth in Turkey and, hence, shocks to energy supply will have a negative impact on economic growth
Causal interpretation of the modified Klein-Gordon equation
International Nuclear Information System (INIS)
A consistent causal interpretation of the Klein-Gordon equation treated as a field equation has been developed, and leads to a model of entities described by the Klein-Gordon equation, i.e., spinless, massive bosons, as objectively existing fields. The question arises, however, as to whether a causal interpretation based on a particle ontology of the Klein-Gordon equation is also possible. Our purpose in this article will be to indicate, by making what we believe is a best possible attempt at developing a particle interpretation of the Klein-Gordon equation, that such an interpretation is untenable. To resolve the nonpositive-definite probability density difficulties with the Klein-Gordon equation, we modify this equation by the introduction of an evolution parameter. We base our subsequent considerations on this modified Klein-Gordon equation. Partly to motivate the need for a relativistic causal interpretation and partly to give emphasis to aspects of the causal interpretation often overlooked, we begin our article with a brief historical survey of the causal interpretation
The Causal Relationship between Health and Education Expenditures in Malaysia
Directory of Open Access Journals (Sweden)
Chor Foon TANG
2011-08-01
Full Text Available A major macroeconomic policy in generating economic growth is to encourage investments on human capital such as health and education. This is because both health and education make significant contribution to increasing productivity of the labour force which ultimately exerts a positive effect on raising output levels. A question that arises is whether investments on health and education have a causal relationship and if so, what is the directional causality? The objective of this study is to examine the causal relationship between health and education expenditures in Malaysia. This study covered annual data from 1970 to 2007. Using Granger causality as well as Toda and Yamamoto MWALD causality approaches, this study suggests that education Granger-causes health expenditure in both the short run and long run. The findings of this study implied that the Malaysian society places preference on education expenditure rather than health. This preference is not unexpected as generally, an educated and knowledgeable society precedes a healthy one. Before a society has attained a relatively higher level of education, it is less aware of the importance of health. Thus, expenditure on education should lead expenditure on health.
Causality between public policies and exports of renewable energy technologies
International Nuclear Information System (INIS)
This article investigates the causal relationship between public policies and exports of renewable energy technologies using panel data from 18 countries for the period 1991–2007. A number of panel unit root and cointegration tests are applied. Time series data on public policies and exports are integrated and cointegrated. The dynamic OLS results indicate that in the long run, a 1% increase in government R and D expenditures (RAD) increases exports (EX) by 0.819%. EX and RAD variables respond to deviations from the long-run equilibrium in the previous period. Additionally, the Blundell–Bond system generalized methods of moments (GMM) is employed to conduct a panel causality test in a vector error-correction mechanism (VECM) setting. Evidence of a bidirectional and short-run, and strong causal relationship between EX and the contribution of renewable energy to the total energy supply (CRES) is uncovered. CRES has a negative effect on EX, whereas EX has a positive effect on CRES. We suggest some policy implications based on the results of this study. - Highlights: ► We model VECM to test the Granger causality between the policies and the export. ► Technology-push policy has a positive impact on export in the long-run. ► There are the short-run causal relationships between market-pull policy and export
Does stability of relativistic dissipative fluid dynamics imply causality?
International Nuclear Information System (INIS)
We investigate the causality and stability of relativistic dissipative fluid dynamics in the absence of conserved charges. We perform a linear stability analysis in the rest frame of the fluid and find that the equations of relativistic dissipative fluid dynamics are always stable. We then perform a linear stability analysis in a Lorentz-boosted frame. Provided that the ratio of the relaxation time for the shear stress tensor τπ to the sound attenuation length Γs=4η/3(ε+P) fulfills a certain asymptotic causality condition, the equations of motion give rise to stable solutions. Although the group velocity associated with perturbations may exceed the velocity of light in a certain finite range of wave numbers, we demonstrate that this does not violate causality, as long as the asymptotic causality condition is fulfilled. Finally, we compute the characteristic velocities and show that they remain below the velocity of light if the ratio τπ/Γs fulfills the asymptotic causality condition.
Corporate Governance and Financial Performance Nexus: Any Bidirectional Causality?
Directory of Open Access Journals (Sweden)
Alley Ibrahim S.
2016-06-01
Full Text Available Most studies on corporate governance recognize endogeneity in the nexus between corporate governance and financial performance. Little attention has, however, been paid to the direction of causality between the two phenomena, and hence the Vector Error Correction (VEC model, which allows for endogenous determination of the direction of causality, has not been widely employed. This study fills that gap by estimating the nexus and the direction of causality using the VEC model to analyze panel data on selected listed firms in Nigeria. The results agree with the findings of most previous studies that corporate governance significantly affects financial performance. Board skills, board composition and management skills enhanced financial performance indicators – return on equity (ROE, return on asset (ROA and net profit margin (NPM; in many occasions, significantly. Board size and audit committee size did not, and can actually undermine financial performance. More importantly, financial performance did not significantly affect corporate governance. On the basis of the lag structure of the VEC model, this study affirms unidirectional causality in the nexus, running from corporate governance to financial performance, nullifying the hypothesis of bidirectional causality in the nexus.
International Nuclear Information System (INIS)
This contribution investigates causal interdependence between energy consumption and economic growth in Liberia and proposes application of a bootstrap methodology. To better reflect causality, employment is incorporated as additional variable. The study demonstrates evidence of distinct bidirectional Granger causality between energy consumption and economic growth. Additionally, the results show that employment in Liberia Granger causes economic growth and apply irrespective of the short-run or long-run. Evidence from a Monte Carlo experiment reveals that the asymptotic Granger causality test suffers size distortion problem for Liberian data, suggesting that the bootstrap technique employed in this study is more appropriate. Given the empirical results, implications are that energy expansion policies like energy subsidy or low energy tariff for instance, would be necessary to cope with demand exerted as a result of economic growth in Liberia. Furthermore, Liberia might have the performance of its employment generation on the economy partly determined by adequate energy. Therefore, it seems fully justified that a quick shift towards energy production based on clean energy sources may significantly slow down economic growth in Liberia. Hence, the government’s target to implement a long-term strategy to make Liberia a carbon neutral country, and eventually less carbon dependent by 2050 is understandable. - Highlights: ► Causality between energy consumption and economic growth in Liberia investigated. ► There is bidirectional causality between energy consumption and economic growth. ► Energy expansion policies are necessary to cope with demand from economic growth. ► Asymptotic Granger causality test suffers size distortion problem for Liberian data. ► The bootstrap methodology employed in our study is more appropriate.
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.
Spinodal decomposition of chemically reactive binary mixtures
Lamorgese, A.; Mauri, R.
2016-08-01
We simulate the influence of a reversible isomerization reaction on the phase segregation process occurring after spinodal decomposition of a deeply quenched regular binary mixture, restricting attention to systems wherein material transport occurs solely by diffusion. Our theoretical approach follows a diffuse-interface model of partially miscible binary mixtures wherein the coupling between reaction and diffusion is addressed within the frame of nonequilibrium thermodynamics, leading to a linear dependence of the reaction rate on the chemical affinity. Ultimately, the rate for an elementary reaction depends on the local part of the chemical potential difference since reaction is an inherently local phenomenon. Based on two-dimensional simulation results, we express the competition between segregation and reaction as a function of the Damköhler number. For a phase-separating mixture with components having different physical properties, a skewed phase diagram leads, at large times, to a system converging to a single-phase equilibrium state, corresponding to the absolute minimum of the Gibbs free energy. This conclusion continues to hold for the critical phase separation of an ideally perfectly symmetric binary mixture, where the choice of final equilibrium state at large times depends on the initial mean concentration being slightly larger or less than the critical concentration.