Events, processes, and the time of a killing

The paper proposes a novel solution to the problem of the time of a killing (ToK), which persistently besets theories of act-individuation. The solution proposed claims to expose a crucial wrong-headed assumption in the debate, according to which ToK is essentially a problem of locating some event that corresponds to the killing. The alternative proposal put forward here turns on recognizing a separate category of dynamic occurents, viz. processes. The paper does not aim to mount a comprehensive defense of process ontology, relying instead on extant defenses. The primary aim is rather to put process ontology to work in diagnosing the current state of play over ToK, and indeed in solving it

Coccidioidomycosis Incidence in Arizona Predicted by Seasonal Precipitation

The environmental mechanisms that determine the inter-annual and seasonal variability in incidence of coccidioidomycosis are unclear. In this study, we use Arizona coccidioidomycosis case data for 1995–2006 to generate a timeseries of monthly estimates of exposure rates in Maricopa County, AZ and Pima County, AZ. We reveal a seasonal autocorrelation structure for exposure rates in both Maricopa County and Pima County which indicates that exposure rates are strongly related from the fall to the spring. An abrupt end to this autocorrelation relationship occurs near the the onset of the summer precipitation season and increasing exposure rates related to the subsequent season. The identification of the autocorrelation structure enabled us to construct a “primary” exposure season that spans August-March and a “secondary” season that spans April–June which are then used in subsequent analyses. We show that October–December precipitation is positively associated with rates of exposure for the primary exposure season in both Maricopa County (R = 0.72, p = 0.012) and Pima County (R = 0.69, p = 0.019). In addition, exposure rates during the primary exposure seasons are negatively associated with concurrent precipitation in Maricopa (R = −0.79, p = 0.004) and Pima (R = −0.64, p = 0.019), possibly due to reduced spore dispersion. These associations enabled the generation of models to estimate exposure rates for the primary exposure season. The models explain 69% (p = 0.009) and 54% (p = 0.045) of the variance in the study period for Maricopa and Pima counties, respectively. We did not find any significant predictors for exposure rates during the secondary season. This study builds on previous studies examining the causes of temporal fluctuations in coccidioidomycosis, and corroborates the “grow and blow” hypothesis

Artificial Neural Network to predict mean monthly total ozone in Arosa, Switzerland

Present study deals with the mean monthly total ozone time series over Arosa, Switzerland. The study period is 1932-1971. First of all, the total ozone time series has been identified as a complex system and then Artificial Neural Networks models in the form of Multilayer Perceptron with back propagation learning have been developed. The models are Single-hidden-layer and Two-hidden-layer Perceptrons with sigmoid activation function. After sequential learning with learning rate 0.9 the peak total ozone period (February-May) concentrations of mean monthly total ozone have been predicted by the two neural net models. After training and validation, both of the models are found skillful. But, Two-hidden-layer Perceptron is found to be more adroit in predicting the mean monthly total ozone concentrations over the aforesaid period.Comment: 22 pages, 14 figure

On the growth kinetics of Ni(Pt) silicide thin films

We report on the effect of Pt on the growth kinetics of δ-Ni2Si and Ni 1−xPtxSi thin films formed by solid phase reaction of a Ni(Pt) alloyed thin film on Si(100). The study was performed by real-time Rutherford backscattering spectrometry examining the silicide growth rates for initial Pt concentrations of 0, 1, 3, 7, and 10 at. % relative to the Ni content. Pt was found to exert a drastic effect on the growth kinetics of both phases. δ-Ni2Si growth is slowed down tremendously, which results in the simultaneous growth of this phase with Ni 1−xPtxSi. Activation energies extracted for the Ni 1−xPtxSi growth process exhibit an increase from Ea = 1.35 ± 0.06 eV for binary NiSi to Ea = 2.7 ± 0.2 eV for Ni 1−xPtxSi with an initial Pt concentration of 3 at. %. Further increasing the Pt content to 10 at. % merely increases the activation energy for Ni 1−xPtxSi growth to Ea = 3.1 ± 0.5 eV

RISK MANAGEMENT FOR CHIROPRACTORS AND OSTEOPATHS: Imaging Guidelines for Conditions Commonly Seen in Practice

This article is the second in a series of articles dealing with risk management in the practise of chiropractic and osteopathy, prepared by the COCA Risk Management Subcommittee

Animacy effects on the processing of intransitive verbs:An eye-tracking study

<p>This paper tested an assumption of the gradient model of split intransitivity put forward by Sorace (“Split Intransitivity Hierarchy” (SIH), 2000, 2004), namely that agentivity is a fundamental feature for unergatives but not for unaccusatives. According to this hypothesis, the animacy of the verb’s argument should affect the processing of unergative verbs to a greater extent than unaccusative verbs. By using eye-tracking methodology we monitored the online processing and integration costs of the animacy of the verb’s argument in intransitive verbs. We observed that inanimate subjects caused longer reading times only for unergative verbs, whereas the animacy of the verb’s argument did not influence the pattern of results for unaccusatives. In addition, the unergative verb data directly support the existence of gradient effects on the processing of the subject argument.</p

Exploring and interrogating astrophysical data in virtual reality

Scientists across all disciplines increasingly rely on machine learning algorithms to analyse and sort datasets of ever increasing volume and complexity. Although trends and outliers are easily extracted, careful and close inspection will still be necessary to explore and disentangle detailed behaviour, as well as identify systematics and false positives. We must therefore incorporate new technologies to facilitate scientific analysis and exploration. Astrophysical data is inherently multi-parameter, with the spatial-kinematic dimensions at the core of observations and simulations. The arrival of mainstream virtual-reality (VR) headsets and increased GPU power, as well as the availability of versatile development tools for video games, has enabled scientists to deploy such technology to effectively interrogate and interact with complex data. In this paper we present development and results from custom-built interactive VR tools, called the iDaVIE suite, that are informed and driven by research on galaxy evolution, cosmic large-scale structure, galaxy–galaxy interactions, and gas/kinematics of nearby galaxies in survey and targeted observations. In the new era of Big Data ushered in by major facilities such as the SKA and LSST that render past analysis and refinement methods highly constrained, we believe that a paradigm shift to new software, technology and methods that exploit the power of visual perception, will play an increasingly important role in bridging the gap between statistical metrics and new discovery. We have released a beta version of the iDaVIE software system that is free and open to the community

Drawing Boundaries

In “On Drawing Lines on a Map” (1995), I suggested that the different ways we have of drawing lines on maps open up a new perspective on ontology, resting on a distinction between two sorts of boundaries: fiat and bona fide. “Fiat” means, roughly: human-demarcation-induced. “Bona fide” means, again roughly: a boundary constituted by some real physical discontinuity. I presented a general typology of boundaries based on this opposition and showed how it generates a corresponding typology of the different sorts of objects which boundaries determine or demarcate. In this paper, I describe how the theory of fiat boundaries has evolved since 1995, how it has been applied in areas such as property law and political geography, and how it is being used in contemporary work in formal and applied ontology, especially within the framework of Basic Formal Ontology

An outline of an asymmetric two-component theory of aspect

The paper presents the bases of an asymmetric two-component model of aspect. The main theoretical conclusion of the study is that (grammatical) viewpoint aspect and situation aspect are not independent aspectual levels, since the former often modifies the input situation aspect of the phrase/sentence. As it is shown, besides the arguments and adjuncts of the predicate, viewpoint aspect is also an important factor in compositionally marking situation aspect. The aspectual framework put forward in the paper is verified and illustrated on the basis of the aspectual system of Hungarian and some examples taken from English linguistic data

Individual biases, cultural evolution, and the statistical nature of language universals: the case of colour naming systems

Language universals have long been attributed to an innate Universal Grammar. An alternative explanation states that linguistic universals emerged independently in every language in response to shared cognitive or perceptual biases. A computational model has recently shown how this could be the case, focusing on the paradigmatic example of the universal properties of colour naming patterns, and producing results in quantitative agreement with the experimental data. Here we investigate the role of an individual perceptual bias in the framework of the model. We study how, and to what extent, the structure of the bias influences the corresponding linguistic universal patterns. We show that the cultural history of a group of speakers introduces population-specific constraints that act against the pressure for uniformity arising from the individual bias, and we clarify the interplay between these two forces