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
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
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
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.
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
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.
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
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
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
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
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
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
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.
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.
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.
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.
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
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
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.
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
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....
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
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.
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
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.
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.
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
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.
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....
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
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.
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.).
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
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
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
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...
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
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
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.
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
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
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.
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
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
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...
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
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...
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
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)
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.
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...
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.
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
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.
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...
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
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
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
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
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
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
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
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
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,...
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
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
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
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
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.
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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.
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
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
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
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
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
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.