462 resultados para Bayesian approaches


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This thesis considers and evaluates different approaches to regulating online gaming communities, including traditional top-down regulation, as well as bottom-up and hybrid forms led by participants. I examine the regulatory environment in both the video game and gambling industries through case studies of the science fiction, massively multiplayer game Eve Online and offshore gambling platforms and their community sites. I identify that the participant driven approach to regulation sometimes used in the offshore gambling industry was dependent on a number of factors, notably the strength of the community and the risks to platform operators of negative publicity. By subsequently comparing this to the video gaming industry, I suggest that participant driven processes may be an appropriate way to resolve disputes in the games industry, and show how these are – to a limited extent – already being applied.

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Radical-directed dissociation of gas phase ions is emerging as a powerful and complementary alternative to traditional tandem mass spectrometric techniques for biomolecular structural analysis. Previous studies have identified that coupling of 2-[(2,2,6,6-tetramethylpiperidin-1-oxyl)methyl] benzoic acid (TEMPO-Bz) to the N-terminus of a peptide introduces a labile oxygen-carbon bond that can be selectively activated upon collisional activation to produce a radical ion. Here we demonstrate that structurally-defined peptide radical ions can also be generated upon UV laser photodissociation of the same TEMPO-Bz derivatives in a linear ion-trap mass spectrometer. When subjected to further mass spectrometric analyses, the radical ions formed by a single laser pulse undergo identical dissociations as those formed by collisional activation of the same precursor ion, and can thus be used to derive molecular structure. Mapping the initial radical formation process as a function of photon energy by photodissociation action spectroscopy reveals that photoproduct formation is selective but occurs only in modest yield across the wavelength range (300-220 nm), with the photoproduct yield maximised between 235 and 225 nm. Based on the analysis of a set of model compounds, structural modifications to the TEMPO-Bz derivative are suggested to optimise radical photoproduct yield. Future development of such probes offers the advantage of increased sensitivity and selectivity for radical-directed dissociation. © 2014 the Owner Societies.

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This is a discussion of the journal article: "Construcing summary statistics for approximate Bayesian computation: semi-automatic approximate Bayesian computation". The article and discussion have appeared in the Journal of the Royal Statistical Society: Series B (Statistical Methodology).

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We present a novel approach for developing summary statistics for use in approximate Bayesian computation (ABC) algorithms using indirect infer- ence. We embed this approach within a sequential Monte Carlo algorithm that is completely adaptive. This methodological development was motivated by an application involving data on macroparasite population evolution modelled with a trivariate Markov process. The main objective of the analysis is to compare inferences on the Markov process when considering two di®erent indirect mod- els. The two indirect models are based on a Beta-Binomial model and a three component mixture of Binomials, with the former providing a better ¯t to the observed data.

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Measuring Earth material behaviour on time scales of millions of years transcends our current capability in the laboratory. We review an alternative path considering multiscale and multiphysics approaches with quantitative structure-property relationships. This approach allows a sound basis to incorporate physical principles such as chemistry, thermodynamics, diffusion and geometry-energy relations into simulations and data assimilation on the vast range of length and time scales encountered in the Earth. We identify key length scales for Earth systems processes and find a substantial scale separation between chemical, hydrous and thermal diffusion. We propose that this allows a simplified two-scale analysis where the outputs from the micro-scale model can be used as inputs for meso-scale simulations, which then in turn becomes the micro-model for the next scale up. We present two fundamental theoretical approaches to link the scales through asymptotic homogenisation from a macroscopic thermodynamic view and percolation renormalisation from a microscopic, statistical mechanics view.

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Geoscientists are confronted with the challenge of assessing nonlinear phenomena that result from multiphysics coupling across multiple scales from the quantum level to the scale of the earth and from femtoseconds to the 4.5 Ga of history of our planet. We neglect in this review electromagnetic modelling of the processes in the Earth’s core, and focus on four types of couplings that underpin fundamental instabilities in the Earth. These are thermal (T), hydraulic (H), mechanical (M) and chemical (C) processes which are driven and controlled by the transfer of heat to the Earth’s surface. Instabilities appear as faults, folds, compaction bands, shear/fault zones, plate boundaries and convective patterns. Convective patterns emerge from buoyancy overcoming viscous drag at a critical Rayleigh number. All other processes emerge from non-conservative thermodynamic forces with a critical critical dissipative source term, which can be characterised by the modified Gruntfest number Gr. These dissipative processes reach a quasi-steady state when, at maximum dissipation, THMC diffusion (Fourier, Darcy, Biot, Fick) balance the source term. The emerging steady state dissipative patterns are defined by the respective diffusion length scales. These length scales provide a fundamental thermodynamic yardstick for measuring instabilities in the Earth. The implementation of a fully coupled THMC multiscale theoretical framework into an applied workflow is still in its early stages. This is largely owing to the four fundamentally different lengths of the THMC diffusion yardsticks spanning micro-metre to tens of kilometres compounded by the additional necessity to consider microstructure information in the formulation of enriched continua for THMC feedback simulations (i.e., micro-structure enriched continuum formulation). Another challenge is to consider the important factor time which implies that the geomaterial often is very far away from initial yield and flowing on a time scale that cannot be accessed in the laboratory. This leads to the requirement of adopting a thermodynamic framework in conjunction with flow theories of plasticity. This framework allows, unlike consistency plasticity, the description of both solid mechanical and fluid dynamic instabilities. In the applications we show the similarity of THMC feedback patterns across scales such as brittle and ductile folds and faults. A particular interesting case is discussed in detail, where out of the fluid dynamic solution, ductile compaction bands appear which are akin and can be confused with their brittle siblings. The main difference is that they require the factor time and also a much lower driving forces to emerge. These low stress solutions cannot be obtained on short laboratory time scales and they are therefore much more likely to appear in nature than in the laboratory. We finish with a multiscale description of a seminal structure in the Swiss Alps, the Glarus thrust, which puzzled geologists for more than 100 years. Along the Glarus thrust, a km-scale package of rocks (nappe) has been pushed 40 km over its footwall as a solid rock body. The thrust itself is a m-wide ductile shear zone, while in turn the centre of the thrust shows a mm-cm wide central slip zone experiencing periodic extreme deformation akin to a stick-slip event. The m-wide creeping zone is consistent with the THM feedback length scale of solid mechanics, while the ultralocalised central slip zones is most likely a fluid dynamic instability.

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Obtaining attribute values of non-chosen alternatives in a revealed preference context is challenging because non-chosen alternative attributes are unobserved by choosers, chooser perceptions of attribute values may not reflect reality, existing methods for imputing these values suffer from shortcomings, and obtaining non-chosen attribute values is resource intensive. This paper presents a unique Bayesian (multiple) Imputation Multinomial Logit model that imputes unobserved travel times and distances of non-chosen travel modes based on random draws from the conditional posterior distribution of missing values. The calibrated Bayesian (multiple) Imputation Multinomial Logit model imputes non-chosen time and distance values that convincingly replicate observed choice behavior. Although network skims were used for calibration, more realistic data such as supplemental geographically referenced surveys or stated preference data may be preferred. The model is ideally suited for imputing variation in intrazonal non-chosen mode attributes and for assessing the marginal impacts of travel policies, programs, or prices within traffic analysis zones.

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Alcohol accounts for major disability worldwide and available treatments are insufficient. A massive growth in the area of addiction neuroscience over the last several decades has not resulted in a corresponding expansion of treatment options available to patients. In this chapter, we describe our experience with building translational research programs aimed at developing novel pharmacotherapies for alcoholism. The narrative is based on experience and considerations made in the course of building these programs, and work on four mechanisms targeted by our libraries: cholinergic nicotine receptors, receptors for corticotropin-releasing hormone (CRH), neurokinin 1 (NK1) receptors for substance P (SP) and hypocretin/orexin receptors. Around this experience, we discuss issues we believe to be critical for successful translation of basic addiction neuroscience into treatments, and complementarities between academic and other actors that in our assessment need to be harnessed in order to bring treatments to the clinic.

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Background Many studies have found associations between climatic conditions and dengue transmission. However, there is a debate about the future impacts of climate change on dengue transmission. This paper reviewed epidemiological evidence on the relationship between climate and dengue with a focus on quantitative methods for assessing the potential impacts of climate change on global dengue transmission. Methods A literature search was conducted in October 2012, using the electronic databases PubMed, Scopus, ScienceDirect, ProQuest, and Web of Science. The search focused on peer-reviewed journal articles published in English from January 1991 through October 2012. Results Sixteen studies met the inclusion criteria and most studies showed that the transmission of dengue is highly sensitive to climatic conditions, especially temperature, rainfall and relative humidity. Studies on the potential impacts of climate change on dengue indicate increased climatic suitability for transmission and an expansion of the geographic regions at risk during this century. A variety of quantitative modelling approaches were used in the studies. Several key methodological issues and current knowledge gaps were identified through this review. Conclusions It is important to assemble spatio-temporal patterns of dengue transmission compatible with long-term data on climate and other socio-ecological changes and this would advance projections of dengue risks associated with climate change. Keywords: Climate; Dengue; Models; Projection; Scenarios

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This paper presents a robust place recognition algorithm for mobile robots that can be used for planning and navigation tasks. The proposed framework combines nonlinear dimensionality reduction, nonlinear regression under noise, and Bayesian learning to create consistent probabilistic representations of places from images. These generative models are incrementally learnt from very small training sets and used for multi-class place recognition. Recognition can be performed in near real-time and accounts for complexity such as changes in illumination, occlusions, blurring and moving objects. The algorithm was tested with a mobile robot in indoor and outdoor environments with sequences of 1579 and 3820 images, respectively. This framework has several potential applications such as map building, autonomous navigation, search-rescue tasks and context recognition.

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We provide the first molecular phylogeny of the clerid lineage (Coleoptera: Cleridae, Thanerocleridae) within the superfamily Cleroidea to examine the two most recently-proposed hypotheses of higher-level classification. Phylogenetic relationships of checkered beetles were inferred from approximately ~5,000nt of both nuclear and mitochondrial rDNA (28S, 16S, and 12S) and the mitochondrial protein-coding gene COI. A worldwide sample of ~70 genera representing almost a quarter of generic diversity of the clerid lineage was included and phylogenies were reconstructed using Bayesian and Maximum Likelihood approaches. Results support the monophyly of many proposed subfamilies but were not entirely congruent with either current classification system. The subfamilial relationships within the Cleridae are resolved with support for three main lineages. Tillinae are supported as the sister group to all other subfamilies within the Cleridae, whereas Thaneroclerinae, Korynetinae and a new subfamily formally described here, Epiclininae subf. n, form a sister group to Clerinae + Hydnocerinae.

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A method is proposed to describe force or compound muscle action potential (CMAP) trace data collected in an electromyography study for motor unit number estimation (MUNE). Experimental data was collected using incre- mental stimulation at multiple durations. However, stimulus information, vital for alternate MUNE methods, is not comparable for multiple duration data and therefore previous methods of MUNE (Ridall et al., 2006, 2007) cannot be used with any reliability. Hypothesised ring combinations of motor units are mod- elled using a multiplicative factor and Bayesian P-spline formulation. The model describes the process for force and CMAP in a meaningful way.

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Scaffolds play a pivotal role in tissue engineering, promoting the synthesis of neo extra-cellular matrix (ECM), and providing temporary mechanical support for the cells during tissue regeneration. Advances introduced by additive manufacturing techniques have significantly improved the ability to regulate scaffold architecture, enhancing the control over scaffold shape and porosity. Thus, considerable research efforts have been devoted to the fabrication of 3D porous scaffolds with optimized micro-architectural features. This chapter gives an overview of the methods for the design of additively manufactured scaffolds and their applicability in tissue engineering (TE). Along with a survey of the state of the art, the Authors will also present a recently developed method, called Load-Adaptive Scaffold Architecturing (LASA), which returns scaffold architectures optimized for given applied mechanical loads systems, once the specific stress distribution is evaluated through Finite Element Analysis (FEA).