An intervention may have an effect on units other than those to which it was administered. This phenomenon is called interference and it usually goes unmodeled. In this paper, we propose to combine Lauritzen-Wermuth-Frydenberg and Andersson-Madigan-Perlman chain graphs to create a new class of causal models that can represent both interference and non-interference relationships for Gaussian distributions. Specifically, we define the new class of models, introduce global and local and pairwise Markov properties for them, and prove their equivalence. (...) We also propose an algorithm for maximum likelihood parameter estimation for the new models, and report experimental results. Finally, we show how to compute the effects of interventions in the new models. (shrink)

Determining the nature of binding in grapheme-color synaesthesia has consequences for understanding the neural basis of synaesthesia and visual awareness in general. We evaluated type- and token-based letter-color binding using a synaesthetic version of the object-reviewing paradigm. Although mean response times failed to reveal any significant differences between synaesthetes and control participants, RT analyses with ex-Gaussian distributions revealed that the response facilitation in the synaesthesia group reflected type representations exclusively, while response facilitation in the control group, who learned (...) letter-color associations, was dominated by token representations. Thus, letter-color associations in associator synaesthetes are type-based, and do not involve binding to object tokens, consistent with their subjective reports. Contrary to recent studies that failed to find differences between synaesthetes and non-synaesthetes with behavioral measures, response time distribution analyses indicate that color sensations in synaesthetes are not simply the extreme form of normal letter-color associations, and cannot be attributed to demand characteristics. (shrink)

According to Bikas Chakrabarti (2005, p. 225), the term econophysics was neologized in 1995 at the second Statphys-Kolkata conference in Kolkata (formerly Calcutta), India by the physicist H. Eugene Stanley, who was also the first to use it in print (Stanley, 1996). Mantegna and Stanley (2000, pp. viii-ix) define “the multidisciplinary field of econophysics” as “a neologism that denotes the activities of physicists who are working on economics problems to test a variety of new conceptual approaches deriving from the physical (...) sciences.” The list of such problems has included distributions of returns in financial markets (Mantegna, 1991; Levy and Solomon, 1997; Bouchaud and Cont, 1998; Gopakrishnan, Plerou, Amaral, Meyer, and Stanley, 1999; Sornette and Johansen, 2001; Farmer and Joshi, 2004) the distribution of income and wealth (Drăgulescu and Yakovenko, 2001; Bouchaud and Mézard, 2000; Chatterjee, Yarlagadda, and Charkrabarti, 2005), the distribution of economic shocks and growth rate variations (Bak, Chen, Scheinkman, and Woodford, 1993; Canning, Amaral, Lee, Meyer, and Stanley, 1998), the distribution of firm sizes and growth rates (Stanley, Amaral, Buldyrev, Havlin, Leschhorn, Maass, Salinger, and Stanley, 1996; Takayasu and Okuyama, 1998; Botazzi and Secchi, 2003), the distribution of city sizes (Rosser, 1994; Gabaix, 1999), and the distribution of scientific discoveries (Plerou, Amaral, Gopakrishnan, Meyer, and Stanley, 1999; Sornette 1 and Zajdenweber, 1999), among other problems, all of which are seen at times not to follow normal or Gaussian patterns that can be described fully by mean and variance. The main sources of conceptual approaches from physics used by the econophysicists have been from models of statistical mechanics (Spitzer, 1971), geophysical models of earthquakes (Sornette, 2003), and “sandpile” models of avalanches, the latter involving self-organized criticality (Bak, 1996). An early physicist to assert the essential identity of statistical methods used in physics and the social sciences was Majorana (1942). A common theme among those who identify themselves as econophysicists is that standard economic theory has been inadequate or insufficient to explain the non-Gaussian distributions empirically observed for various of these phenomena, such as “excessive” skewness and leptokurtotic “fat tails” (McCauley, 2004).. (shrink)

In this chapter, one considers finance at its very foundations, namely, at the place where assumptions are being made about the ways to measure the two key ingredients of finance: risk and return. It is well known that returns for a large class of assets display a number of stylized facts that cannot be squared with the traditional views of 1960s financial economics (normality and continuity assumptions, i.e. Brownian representation of market dynamics). Despite the empirical counterevidence, normality and continuity assumptions (...) were part and parcel of financial theory and practice, embedded in all financial practices and beliefs. Our aim is to build on this puzzle for extracting some clues revealing the use of one research strategy in academic community, model tinkering defined as a particular research habit. We choose to focus on one specific moment of the scientific controversies in academic finance: the ‘leptokurtic crisis’ opened by Mandelbrot in 1962. The profoundness of the crisis came from the angle of the Mandelbrot’s attack: not only he emphasized an empirical inadequacy of the Brownian representation, but also he argued for an inadequate grounding of this representation. We give some insights in this crisis and display the model tinkering strategies of the financial academic community in the 1970s and the 1980s. (shrink)

Socioeconomic inequalities are functions not only of intrinsic differences between persons or groups, but also of the dynamics of their interactions. Inequalities can arise and become stabilized if there are advantages (such as generalized wealth including “human capital”) which are self-enhancing, whereas depletion of limiting resources is widely distributed. A recent theory of biological pattern formation has been generalized, adapted and applied to deal with this process. Applications include models for the non-Gaussian distribution of personal income and wealth, for (...) overall economic growth in relation to inequalities and for effects of uncoupling strategies between developing and developed countries. Note added after publication: The equations (14) for the model of the income distribution, with its characteristic non-Gaussian extension towards higher incomes (fig.4), are closely related to the Fokker-Planck equation that is widely applied in many fields of physics. (shrink)

It is universally accepted that genetic control over basic aspects of cell and molecular biology is the primary organizing principle in development and homeostasis of living systems. However, instances do exist where important aspects of biological order arise without explicit genetic instruction, emerging instead from simple physical principles, stochastic processes, or the complex self‐organizing interaction between random and seemingly unrelated parts. Being mostly resistant to direct genetic dissection, the analysis of such emergent processes falls into a grey area between mathematics, (...) physics and molecular cell biology and therefore remains very poorly understood. We recently proposed a mathematical model predicting the emergence of a specific non‐Gaussian distribution of polygonal cell shapes from the stochastic cell division process in epithelial cell sheets; this cell shape distribution appears to be conserved across a diverse set of animals and plants.1 The use of such topological models to study the process of cellular morphogenesis has a long history, starting almost a century ago, and many insights from those original works influence current experimental studies. Here we review current and past literature on this topic while exploring some new ideas on the origins and implications of topological order in proliferating epithelia. BioEssays 30:260–266, 2008. © 2008 Wiley Periodicals, Inc. (shrink)

Noise in behavior is often viewed as a nuisance: while the mind aims to take the best possible action, it is let down by unreliability in the sensory and response systems. How researchers study cognition reflects this viewpoint – averaging over trials and participants to discover the deterministic relationships between experimental manipulations and their behavioral consequences, with noise represented as additive, often Gaussian, and independent. Yet a careful look at behavioral noise reveals rich structure that defies easy explanation. First, (...) both perceptual and preferential judgments show that sensory and response noise may potentially only play minor roles, with most noise arising in the cognitive computations. Second, the functional form of the noise is both non-Gaussian and non-independent, with the distribution of noise being better characterized as heavy-tailed and as having substantial long-range autocorrelations. It is possible that this structure results from brains that are, for some reason, bedeviled by a fundamental design flaw, albeit one with intriguingly distinctive characteristics. Alternatively, noise might not be a bug but a feature: indeed, we suggest that noise is fundamental to how cognition works. Specifically, we propose that the brain approximates probabilistic inference with a local sampling algorithm, one that uses randomness to drive its exploration of alternative hypotheses. Reframing cognition in this way explains the rich structure of noise and leads to a surprising conclusion: that noise is not a symptom of cognitive malfunction but plays a central role in underpinning human intelligence. (shrink)

A longstanding paradox was first reported by David Miller in 1975 and highlighted by Karl Popper in 1979. Miller showed that the ranking of predictions from two theories, in terms of closeness to observation, appears to be reversed when the problem is transformed into a different mathematical space. He concluded that “… no false theory can … be closer to the truth than is another theory”. This flies in the face of normal scientific practice and is thus paradoxical; it is (...) named here the “Miller-Popper paradox”. This paper proposes a resolution of the paradox, through consideration of the inevitable errors and uncertainties in both observations and predictions. It is proved that, for linear transformations and Gaussian error distributions, the transformation between spaces creates no change in quantitative measures of “closeness-to-observation” when these measures are based in probability theory. The extension of this result to nonlinear transformations and to non-Gaussian error distributions is also discussed. These results demonstrate that concepts used in comparison of predictions with observations—concepts of “closeness”, “consistency”, “agreement”, “falsification”, etc.—all imply some knowledge of the uncertainty characteristics of both predictions and observations. (shrink)

An omnipresent, non-local/non-analytical energy that pervades everything enters the Universe through all infinitesimal points. Without determining its origin, our approach is to explain our gravity theory based on Einstein’s relativity theory and the behavior of space-time flow. This influx occurs continuously throughout all of space-time, making the universe expand. Our theory presents two kinds of expansion: (PUE) space-time primary universal expansion and the (VME) virtual matter expansion that occurs with the interaction of space-time with the matter. The internal space-time in (...) atoms produces a virtual slight broadening of the matter’s atoms. From our frame of reference, we can only distinguish the perturbation that occurs to the (PUE) primary universal expansion if it encounters matter. This perturbation finally is restored by a Gaussian distribution at the spherical environment. We call it the (STD) Space-time accelerated displacement. It is the inertial-gravity field. Thus, matter expands by the superposition of atoms (molecules). The accelerated expansion increases proportionally to the number of atoms that radially constitute matter. The effect is manifested immensely increased in the surface of the stellar objects. Then the surface of the massive stellar objects pushes and displaces the object’s external surrounding space-time. The acceleration of the (STD) space-time displacement decreases with the radius squared from the center of mass as it is distributed concentrically. The acceleration we feel at the Earth’s surface is permanently fixed, because when space expands, time also proportionally expands. The associated speed (ds/dt) is immersed in the accelerated expansion of space-time; the time base is the same as the acceleration of the PUE (space-time primary universal expansion) (d2s/dt2). Otherwise, in a short time, this acceleration and its associated velocity would reach the speed of light. Our theory introduces a different concept: “repulsion instead of attraction”. The expansion of space-time produces gravity instead of counteracting it. Finally, we explain using this gravity theory: Earth’s oceans, creating tidal bulges on opposite sides of the planet. (shrink)

Compared to constraint-based causal discovery, causal discovery based on functional causal models is able to identify the whole causal model under appropriate assumptions [Shimizu et al. 2006; Hoyer et al. 2009; Zhang and Hyvärinen 2009b]. Functional causal models represent the effect as a function of the direct causes together with an independent noise term. Examples include the linear non-Gaussian acyclic model, nonlinear additive noise model, and post-nonlinear model. Currently, there are two ways to estimate the parameters in the models: (...) dependence minimization and maximum likelihood. In this article, we show that for any acyclic functional causal model, minimizing the mutual information between the hypothetical cause and the noise term is equivalent to maximizing the data likelihood with a flexible model for the distribution of the noise term. We then focus on estimation of the PNL causal model and propose to estimate it with the warped Gaussian process with the noise modeled by the mixture of Gaussians. As a Bayesian nonparametric approach, it outperforms the previous one based on mutual information minimization with nonlinear functions represented by multilayer perceptrons; we also show that unlike the ordinary regression, estimation results of the PNL causal model are sensitive to the assumption on the noise distribution. Experimental results on both synthetic and real data support our theoretical claims. (shrink)

In this article, we propose a new method to learn the underlying acyclic mixed graph of a linear non-Gaussian structural equation model with given observational data. We build on an algorithm proposed by Wang and Drton, and we show that one can augment the hidden variable structure of the recovered model by learning multidirected edges rather than only directed and bidirected ones. Multidirected edges appear when more than two of the observed variables have a hidden common cause. We detect (...) the presence of such hidden causes by looking at higher order cumulants and exploiting the multi-trek rule. Our method recovers the correct structure when the underlying graph is a bow-free acyclic mixed graph with potential multidirected edges. (shrink)

ObjectiveThere is little literature on the validity of kurtosis-adjusted noise energy metrics in human studies. Therefore, this study aimed to validate the application of cumulative noise exposure adjusted by kurtosis in evaluating occupational hearing loss associated with non-Gaussian noise among manufacturing workers.MethodsA cross-sectional survey was conducted on 1,558 manufacturing workers exposed to noise from five industries to collect noise exposure and hearing loss data. Both CNE and kurtosis-adjusted CNE were collapsed into 2-dB∙year bins, and the mean noise-induced permanent threshold (...) shifts at 3, 4, and 6 kHz in each bin were calculated. The contributions of CNE and CNE′ to noise-induced hearing loss were compared using the multiple linear regression. The degree of overlap of two linear regression equations was used to evaluate the validity of the CNE′ using a stratified analysis based on age and sex.ResultsMultiple linear regression models showed that after kurtosis adjustment, the standardized regression coefficient of CNE increased from 0.230 to 0.255, and R2 increased from 0.147 to 0.153. The linear relationship between NIPTS346 and CNE′ or CNE showed that the regression line of non-Gaussian noise was closer to that of Gaussian noise when using CNE′ than using CNE. The mean difference in NIPTS346 between the equations of non-Gaussian noise and Gaussian noise was significantly reduced from 4.32 to 1.63 dB HL after kurtosis adjustment. Through a stratified analysis, these significant decreases were observed in male and female workers, and workers aged ≥30 years old.ConclusionAs a noise exposure metric combining noise energy and temporal characteristics, the kurtosis-adjusted-CNE metric was more effective than CNE alone in assessing occupational hearing loss among manufacturing workers in non-Gaussian noise environment. However, more studies are needed to verify the validity of the kurtosis-adjusted-CNE metric. (shrink)

Modelling of contagious disease usually employs compartmental SEIR-like models where the waiting times in respective compartments are exponentially distributed. In this paper, we are interested in investigating how the distributions of sojourn times in infective compartments affect the dynamics and persistence of the contagious bovine pleuropneumonia, a chronic respiratory disease of cattle. Two kinds of extreme distributions of the sojourn times are considered: a Dirac delta-function and truncated Gaussian function leading to a model with (non-constant) delay and (...) the classical exponential distribution that stands for a model without delay. Expressions of the basic reproductive numbers are derived and dynamical behaviours are discussed for the three models. It is found that the spreading of disease exhibits wave-like oscillations for the time-delay dynamics. In contrast, the disease appears to last longer when the spreading is described by the classical dynamics without delay. Subsequently, the time-delay dynamics turns out to be more appropriate for the description of an experimental epidemic of CBPP. (shrink)

We propose an adynamical, background independent approach to quantum gravity and unification whereby the fundamental elements of Nature are graphical units of space, time and sources. The transition amplitude for these elements of “spacetimesource” is computed using a path integral with discrete Gaussian graphical action. The unit of action for a spacetimesource element is constructed from a difference matrix K and source vector J on the graph, as in lattice gauge theory. K is constructed from graphical relations so that (...) it contains a non-trivial null space, and J is then restricted to the column space of K which ensures it is distributed in a divergence-free fashion over the spacetime defined by the element. This rule for the relational construct of K and J is our proposed fundamental axiom of physics and results in a self-consistency relationship between sources, the spacetime metric, and the stress-energy-momentum content of the element, rather than a dynamical law for time-evolved entities. In its most general form, the set of fundamental elements employed by lattice gauge theory contains scalar fields on nodes and links, and vector fields on nodes. To complete the fundamental set, we propose the addition of scalar fields on plaquettes and vector fields on links. We use this approach via modified Regge calculus to correct proper distance in the Einstein-deSitter cosmology model yielding a fit of the Union2 Compilation supernova data that matches ɅCDM without having to invoke accelerating expansion or dark energy. (shrink)

In this note, we study the complementedness and the distributivity of upper semilattices of Kleene degrees assuming V = L. K denotes the upper semilattice of all Kleene degrees. We prove that if V = L, then some sub upper semilattices of K are non-complemented and some are non-distributive.

In this paper we devise non-distributive relatives of Exactly true logic by Pietz and Riveccio and its dual Non-falsity logic by Shramko, Zaitsev and Belikov. We consider two pre-orders which are algebraic counterparts of the ETL’s and NFL’s entailment relations on the de Morgan lattice 4. We generalise these pre-orders and determine which distributive properties that hold on 4 are not forced by either of the pre-orders. We then construct relatives of ETL and NFL but lack such distributive properties. For (...) these logics we also devise a truth table semantics which uses non-distributive lattice M3 as their lattice of truth values. We also provide analytic tableaux systems which work with sequents of the form \. We then prove correctness and completeness results for these proof systems and provide a neat generalisation for non-distributive ETL- and NFL-like logics built over a certain family of non-distributive modular lattices. (shrink)

I adapt an old example of Frank Jackson's, in order to show that it is not only possible that actions with different individual agents are sub-optimal when each is not, but that they are impermissible when each is not, and blameworthy when each is not.

Various arguments have been provided for drawing non-humans such as animals and artificial agents into the sphere of moral consideration. In this paper, I argue for a shift from an ontological to a social-philosophical approach: instead of asking what an entity is, we should try to conceptually grasp the quasi-social dimension of relations between non-humans and humans. This allows me to reconsider the problem of justice, in particular distributive justice . Engaging with the work of Rawls, I show that an (...) expansion of the contractarian framework to non-humans causes an important problem for liberalism, but can be justified by a contractarian argument. Responding to Bell’s and Nussbaum’s comments on Rawls, I argue that we can justify drawing non-humans into the sphere of distributive justice by relying on the notion of a co-operative scheme. I discuss what co-operation between humans and non-humans can mean and the extent to which it depends on properties. I conclude that we need to imagine principles of ecological and technological distributive justice. (shrink)

The human ability to flexibly discover alternatives without fixating on a known solution supports a variety of human creative activities. Previous research has shown that people who discover an alternative procedure relax their attentional bias to information regarding the known solutions just prior to the discovery. This study examined whether the difference in the distribution of attention between the finders and non-finders of the alternative procedure is observed from the phase of solving the problem using the trained procedure. We evaluated (...) the characteristics of the finders' distribution of attention in situations where problem solving using a trained procedure was successful. This aspect has been little examined in previous research. Our study obtained empirical evidence for the fact that, compared to non-finders, finders pay more attention to information unrelated to the trained procedure acquired through knowledge and experience, even time when using a trained procedure. We also confirmed that this difference does not exist from the beginning of the task, but emerges during repeated use of familiar procedures. These findings indicate that in order to find an alternative procedure, one should not only divert attention from a familiar procedure just before the discovery but also pay a certain amount of attention to information unrelated to the familiar procedure even when the familiar procedure is functioning well. (shrink)

The distinction between distributive and non-distributive profiles figures prominently in current evaluations of the ethical and epistemological risks that are associated with automated profiling practices. The diagnosis that non-distributive profiles may coincidentally situate an individual in the wrong category is often perceived as the central shortcoming of such profiles. According to this diagnosis, most risks can be retraced to the use of non-universal generalisations and various other statistical associations. This article develops a top-down analysis of non-distributive profiles in which this (...) fallibility of non-distributive profiles is no longer central. Instead, it focuses on how profiling creates various asymmetries between an individual data-subject and a profiler. The emergence of informational, interest, and perspectival asymmetries between data-subject and profiler explains how non-distributive profiles weaken the epistemic position of a profiled individual. This alternative analysis provides a more balanced assessment of the epistemic risks associated with non-distributive profiles. (shrink)

This paper investigates the notion of ‘distributed cognition’—the idea that entities external to one’s organic brain participate in one’s overall cognitive functioning—and the challenges it poses to the notion of personhood. Related to this is also a consideration of the ever-increasing ways in which neuroprostheses replace and functionally replicate organic parts of the brain. However, the literature surrounding such issues has tended to take an almost exclusively physicalist approach. The common assumption is that, given that non-physicalist theories (chiefly, dualism, and (...) hylomorphism) postulate some form of immaterial ‘soul’, then they are immune from the challenges that these advances in cognitive science pose. The first aim of this paper, therefore, is to argue that this is not the case. The second aim of this paper is to attempt to elucidate a route available for the non-physicalists that will allow them to accept the notion of distributed cognition. By appealing to an Aristotelian framework, I propose that the non-physicalist can accept the notion of distributed cognition by appealing to the notion of ‘unitary life’ which I introduce, as well as to Aristotle’s dichotomy between active and passive mind. (shrink)

Children show a remarkable degree of consistency in learning some words earlier than others. What patterns of word usage predict variations among words in age of acquisition? We use distributional analysis of a naturalistic corpus of child‐directed speech to create quantitative features representing natural variability in word contexts. We evaluate two sets of features: One set is generated from the distribution of words into frames defined by the two adjacent words. These features primarily encode syntactic aspects of word usage. The (...) other set is generated from non‐adjacent co‐occurrences between words. These features encode complementary thematic aspects of word usage. Regression models using these distributional features to predict age of acquisition of 656 early‐acquired English words indicate that both types of features improve predictions over simpler models based on frequency and appearance in salient or simple utterance contexts. Syntactic features were stronger predictors of children's production than comprehension, whereas thematic features were stronger predictors of comprehension. Overall, earlier acquisition was predicted by features representing frames that select for nouns and verbs, and by thematic content related to food and face‐to‐face play topics; later acquisition was predicted by features representing frames that select for pronouns and question words, and by content related to narratives and object play. (shrink)

Resources are typically discussed in economics as factors of production. This article proposes defining resources from the perspective of human needs, thereby dividing resources into two categories: material resources and information resources. The key distinction lies in whether they can be replicated, which determines if their marginal cost of supply is zero, and leads to their different distribution in society. For material resources, the main indicator is wealth, and the distribution of wealth follows a power law. This means that a (...) small minority of people control a large amount of wealth, leading to severe inequality issues. This led to Karl Marx's idea of abolishing private property, which ultimately failed. For information resources, the article suggests that reputation can serve as a main indicator for observation and proposes an algorithm for calculating reputation scores. The article points out that the distribution of reputation scores does not follow a power law, contrary to wealth distribution, and results in a multi-centered, star-like social structure. A star chart model is introduced to visualize this structure, illustrating the roles of creators, reflectors, and recipients in information dissemination. Thus, the social structure resulting from information activities has a relatively low level of inequality. Furthermore, the modern information infrastructure has lowered barriers to knowledge acquisition and reputation building, potentially mitigating wealth inequality by providing new income channels. It also addresses challenges in the digital age, such as cyberbullying and misinformation, proposing principles for effective governance of online spaces. (shrink)

This paper develops my position on the ethics of price gouging in response to Jeremy Snyder's article, "What's the Matter with Price Gouging." First, it explains how the "nonworseness claim" supports the moral permissibility of price gouging, even if it does not show that price gougers are morally virtuous agents. Second, it argues that questions about price gouging and distributive justice must be answered in light of the relevant possible institutional alternatives, and that Snyder's proposed alternatives to price gouging fare (...) worse on the dimension of justice than a system in which goods are allocated by a system of market prices. (shrink)

The current UK policy for the distribution of scarce vaccination in an influenza pandemic is ethically dubious. It is based on the planned outcome of the maximum health benefit in terms of the saving of lives and the reduction of illness. To that end, the population is classified in terms of particular priority groups. An alternative policy with a non-consequentialist rationale is proposed in the present work. The state should give the vaccination, in the first instance, to those who are (...) at risk of catching the pandemic flu in the line of their duties of public employment. Thereafter, if there is not sufficient vaccine to give all citizens equally an effective dose, the state should give all citizens an equal chance of receiving an effective dose. This would be the just thing to do because the state has a duty to treat each and all of its citizens impartially and they have a corresponding right to such impartial treatment. Although this article specifically refers to the UK, it is considered that the suggested alternative policy would be applicable generally. The duty to act justly is not merely a local one. (shrink)

There are many conflicting views concerning the nature of distributed representation, its compatibility or otherwise with symbolic representation, and its importance in characterizing the nature of connectionist models and their relationship to more traditional symbolic approaches to understanding cognition. Many have simply assumed that distribution is merely an implementation issue, and that symbolic mechanisms can be designed to take advantage of the virtues of distribution if so desired. Others, meanwhile, see the use of distributed representation as marking a fundamental difference (...) between the two approaches. One reason for this diversity of opinion is the fact that the relevant notions - especially that of. (shrink)

The main goal of this paper is to explain the link between the algebraic models and the Kripke-style models for certain classes of propositional non-classical logics. We consider logics that are sound and complete with respect to varieties of distributive lattices with certain classes of well-behaved operators for which a Priestley-style duality holds, and present a way of constructing topological and non-topological Kripke-style models for these types of logics. Moreover, we show that, under certain additional assumptions on the variety of (...) the algerabic models of the given logics, soundness and completeness with respect to these classes of Kripke-style models follows by using entirely algebraical arguments from the soundness and completeness of the logic with respect to its algebraic models. (shrink)

The main goal of this paper is to explain the link between the algebraic and the Kripke-style models for certain classes of propositional logics. We start by presenting a Priestley-type duality for distributive lattices endowed with a general class of well-behaved operators. We then show that finitely-generated varieties of distributive lattices with operators are closed under canonical embedding algebras. The results are used in the second part of the paper to construct topological and non-topological Kripke-style models for logics that are (...) sound and complete with respect to varieties of distributive lattices with operators in the above-mentioned classes. (shrink)

This article was originally published in the Encyclopedia of Language & Linguistics, Second Edition, published by Elsevier, and the attached copy is provided by Elsevier for the author's benefit and for the benefit of the author's institution, for noncommercial research and educational use including without limitation use in instruction at your institution, sending it to specific colleagues who you know, and providing a copy to your institution’s administrator.

In this paper, we propose a general copula approach to accommodate non-normal continuous mixing distributions in multinomial probit models. In particular, we specify a multivariate mixing distribution that allows different marginal continuous parametric distributions for different coefficients. A new hybrid estimation technique is proposed to estimate the model, which combines the advantageous features of each of the maximum simulated likelihood inference technique and Bhat’s maximum approximate composite marginal likelihood inference approach. The effectiveness of our formulation and inference approach (...) is demonstrated through simulation exercises and an empirical application. (shrink)

This article addresses and resolves some issues of relational, Kripke-style, semantics for the logics of bounded lattice expansions with operators of well-defined distribution types, focusing on the case where the underlying lattice is not assumed to be distributive. It therefore falls within the scope of the theory of Generalized Galois Logics, introduced by Dunn, and it contributes to its extension. We introduce order-dual relational semantics and present a semantic analysis and completeness theorems for non-distributive lattice logic with n -ary additive (...) or multiplicative operators, with negation operators modally interpreted as impossibility and unnecessity, as well as with implication connectives. Order-dual relational semantics shares with the generalized Kripke frames, or the bi-approximation semantics approach, the use of both a satisfaction and a co-satisfaction relation, but it also responds to the recently voiced concerns of Craig, Haviar and Conradie about the relative non-intuitiveness of the 2-sorted semantics of the aforementioned approaches. In this article, we provide a standard interpretation of modalities and natural interpretations of both negation and implication, despite the absence of distribution. Thereby, our results contribute in creating the necessary background for research in non-distributive logics with modalities variously interpreted as dynamic, temporal etc, by analogy to the classical case. (shrink)

Recent studies of naturalistic face‐to‐face communication have demonstrated coordination patterns such as the temporal matching of verbal and non‐verbal behavior, which provides evidence for the proposal that verbal and non‐verbal communicative control derives from one system. In this study, we argue that the observed relationship between verbal and non‐verbal behaviors depends on the level of analysis. In a reanalysis of a corpus of naturalistic multimodal communication (Louwerse, Dale, Bard, & Jeuniaux, ), we focus on measuring the temporal patterns of specific (...) communicative behaviors in terms of their burstiness. We examined burstiness estimates across different roles of the speaker and different communicative modalities. We observed more burstiness for verbal versus non‐verbal channels, and for more versus less informative language subchannels. Using this new method for analyzing temporal patterns in communicative behaviors, we show that there is a complex relationship between verbal and non‐verbal channels. We propose a “temporal heterogeneity” hypothesis to explain how the language system adapts to the demands of dialog. (shrink)

We introduce game-theoretic semantics for systems without the conveniences of either a De Morgan negation, or of distribution of conjunction over disjunction and conversely. Much of game playing rests on challenges issued by one player to the other to satisfy, or refute, a sentence, while forcing him/her to move to some other place in the game’s chessboard-like configuration. Correctness of the game-theoretic semantics is proven for both a training game, corresponding to Positive Lattice Logic and for more advanced games for (...) the logics of lattices with weak negation and modal operators. (shrink)

Trajectories along which phase-space points of the Wigner distribution function move are computed for a Gaussian wave packet moving under the influence of a weak perturbative potential. The potentials considered are a potential step, a potential barrier, and a periodic potential. Trajectories computed exhibit the complex, nonlocal nature of quantum dynamics. It is seen that quantum interference, which takes place in the time development of the wave packet, is taken care of in a simple way by the Wigner trajectory (...) method presented here. (shrink)