2,499 research outputs found
Multiscale Bayesian State Space Model for Granger Causality Analysis of Brain Signal
Modelling time-varying and frequency-specific relationships between two brain
signals is becoming an essential methodological tool to answer heoretical
questions in experimental neuroscience. In this article, we propose to estimate
a frequency Granger causality statistic that may vary in time in order to
evaluate the functional connections between two brain regions during a task. We
use for that purpose an adaptive Kalman filter type of estimator of a linear
Gaussian vector autoregressive model with coefficients evolving over time. The
estimation procedure is achieved through variational Bayesian approximation and
is extended for multiple trials. This Bayesian State Space (BSS) model provides
a dynamical Granger-causality statistic that is quite natural. We propose to
extend the BSS model to include the \`{a} trous Haar decomposition. This
wavelet-based forecasting method is based on a multiscale resolution
decomposition of the signal using the redundant \`{a} trous wavelet transform
and allows us to capture short- and long-range dependencies between signals.
Equally importantly it allows us to derive the desired dynamical and
frequency-specific Granger-causality statistic. The application of these models
to intracranial local field potential data recorded during a psychological
experimental task shows the complex frequency based cross-talk between amygdala
and medial orbito-frontal cortex.
Keywords: \`{a} trous Haar wavelets; Multiple trials; Neuroscience data;
Nonstationarity; Time-frequency; Variational methods
The published version of this article is
Cekic, S., Grandjean, D., Renaud, O. (2018). Multiscale Bayesian state-space
model for Granger causality analysis of brain signal. Journal of Applied
Statistics. https://doi.org/10.1080/02664763.2018.145581
Approximation Algorithms for Energy Minimization in Cloud Service Allocation under Reliability Constraints
We consider allocation problems that arise in the context of service
allocation in Clouds. More specifically, we assume on the one part that each
computing resource is associated to a capacity constraint, that can be chosen
using Dynamic Voltage and Frequency Scaling (DVFS) method, and to a probability
of failure. On the other hand, we assume that the service runs as a set of
independent instances of identical Virtual Machines. Moreover, there exists a
Service Level Agreement (SLA) between the Cloud provider and the client that
can be expressed as follows: the client comes with a minimal number of service
instances which must be alive at the end of the day, and the Cloud provider
offers a list of pairs (price,compensation), this compensation being paid by
the Cloud provider if it fails to keep alive the required number of services.
On the Cloud provider side, each pair corresponds actually to a guaranteed
success probability of fulfilling the constraint on the minimal number of
instances. In this context, given a minimal number of instances and a
probability of success, the question for the Cloud provider is to find the
number of necessary resources, their clock frequency and an allocation of the
instances (possibly using replication) onto machines. This solution should
satisfy all types of constraints during a given time period while minimizing
the energy consumption of used resources. We consider two energy consumption
models based on DVFS techniques, where the clock frequency of physical
resources can be changed. For each allocation problem and each energy model, we
prove deterministic approximation ratios on the consumed energy for algorithms
that provide guaranteed probability failures, as well as an efficient
heuristic, whose energy ratio is not guaranteed
A refutation of the practice style hypothesis: the case of antibiotics prescription by French general practitioners for acute rhinopharyngitis
Many researches in France or abroad have highlighted the medical practice variation (MPV)phenomenon, or even the inappropriateness of certain medical decisions. There is no consensus on the origin of this MPV between preference-centred versus opportunities and constraints approaches. This study principal purpose is to refute hypothesis which assume that physicians adopt for their patient a uniform practice style for each similar clinical decision beyond the time. More specifically, multilevel models are estimated: First to measure variability of antibiotics prescription by French general practitioners for acute rhinopharyngitis, a clinical decision making context with weak uncertainty, and to tests its significance; Second to prioritize its determinants, especially those relating to GP or its practice setting environment, by controlling visit or patient confounders. The study was based on the 2001 activity data, added by an ad hoc questionnaire, of a sample of 778 GPs arising from a panel of 1006 computerized French GPs. We observe that a great part of the total variation was due to intra-physician variability (70%). Hence, in the French general practice context, we find empirical support for the rejection of the âpractice styleâ, the âenthusiasmâ or the âsurgical signatureâ hypothesis. Thus, it is patients' characteristics that largely explain the prescription, even if physicians' characteristics (area of practice, level of activity, network participation, participation in ongoing medical training) and environmental factors (recent visit from pharmaceutical sales representatives) also exert considerable influence. The latter suggest that MPV are partly caused by differences in the type of dissemination or diffusion of information. Such findings may help us to develop and identify facilitators for promoting a better use of antibiotics in France and, more generally, for influencing GPs practice when it is of interest.Medical practice variation, Multilevel analysis, Upper respiratory tract infections, Rhinopharyngitis, Antibiotics, General practitioners, Panel, France
3D numerical simulation of Circulating Fluidized Bed: comparison between theoretical results and experimental measurements of hydrodynamic
This work was realized in the frame of the European GAYA project supported by ADEME. This paper presents a description of the hydrodynamic into a CFB according to experimental measurements of gas pressure and solid mass flux. These experimental data are compared to three dimensional numerical simulation with an Eulerian approach. The obtained numerical results show that the applied mathematical models are able to predict the complex gas-solid behavior in the CFB and highlight the large influence of the particle wall boundary condition. Indeed,
it is shown that free slip wall boundary condition gives a good prediction a solid mass flux profile in comparison with experimental measurements nevertheless a convex shape. Moreover, the numerical solid hold-up is underestimated compared to the experimental data. On the contrary, a no-slip boundary condition improves the profile shape of solid mass flux but highly overestimates its intensity and the solid hold-up. A compromise appears to be a friction
particle-wall boundary condition such as Johnson and Jackson (1) but the model parameters have to be chosen very carefully especially the restitution coefficient
Endogenous structural change and climate targets.
This paper envisages endogenous technical change as resulting from the interplay between the economic growth engine, consumption, technology and localization patterns. We perform numerical simulations with the recursive dynamic general equilibrium model IMACLIM-R to study how modeling induced technical change affects costs of CO2 stabilization. IMACLIM-R incorporates innovative specifications about final consumption of transportation and energy to represent critical stylized facts such as rebound effects and demand induction by infrastructures and equipments. Doing so brings to light how induced technical change may not only lower stabilization costs thanks to pure technological progress, but also triggers induction of final demand - effects critical to both the level of the carbon tax and the costs of policy given a specific stabilization target. Finally, we study the sensitivity of total stabilization costs to various parameters including both technical assumptions as accelerated turnover of equipments and non-energy choices as alternative infrastructure policies.induced technical change; structural change; climate policy; carbon tax;transportation; infrastructures
There has been a substantial drop in EU legislative output since 2010
A common argument made against the European Union by Eurosceptic politicians is that the EU creates a burden on citizens and businesses by producing too much legislation. But how much legislation does the EU actually produce? Renaud Dehousse and Olivier Rozenberg present data on both the raw number of EU acts adopted since 1996, and a measure of the burden produced by this legislation. They note that contrary to expectations, there has been a substantial fall in the EUâs legislative output since 2010, raising questions over the motivations underpinning the European Commissionâs legislative agenda
Permutation Tests for Regression, ANOVA, and Comparison of Signals: The permuco Package
Recent methodological researches produced permutation methods to test parameters in presence of nuisance variables in linear models or repeated measures ANOVA. Permutation tests are also particularly useful to overcome the multiple comparisons problem as they are used to test the effect of factors or variables on signals while controlling the family-wise error rate (FWER). This article introduces the permuco package which implements several permutation methods. They can all be used jointly with multiple comparisons procedures like the cluster-mass tests or threshold-free cluster enhancement (TFCE). The permuco package is designed, first, for univariate permutation tests with nuisance variables, like regression and ANOVA; and secondly, for comparing signals as required, for example, for the analysis of event-related potential (ERP) of experiments using electroencephalography (EEG). This article describes the permutation methods and the multiple comparisons procedures implemented. A tutorial for each of theses cases is provided
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