931 research outputs found
Convergence of statistical moments of particle density time series in scrape-off layer plasmas
Particle density fluctuations in the scrape-off layer of magnetically
confined plasmas, as measured by gas-puff imaging or Langmuir probes, are
modeled as the realization of a stochastic process in which a superposition of
pulses with a fixed shape, an exponential distribution of waiting times and
amplitudes represents the radial motion of blob-like structures. With an
analytic formulation of the process at hand, we derive expressions for the
mean-squared error on estimators of sample mean and sample variance as a
function of sample length, sampling frequency, and the parameters of the
stochastic process. % Employing that the probability distribution function of a
particularly relevant shot noise process is given by the gamma distribution, we
derive estimators for sample skewness and kurtosis, and expressions for the
mean-squared error on these estimators.
Numerically generated synthetic time series are used to verify the proposed
estimators, the sample length dependency of their mean-squared errors, and
their performance.
We find that estimators for sample skewness and kurtosis based on the gamma
distribution are more precise and more accurate than common estimators based on
the method of moments.Comment: 31 pages, 10 figure
Allocating Interventions Based on Counterfactual Predictions: A Case Study on Homelessness Services
Modern statistical and machine learning methods are increasingly capable of modeling individual or personalized treatment effects by predicting counterfactual outcomes. These counterfactual predictions could be used to allocate different interventions across populations based on individual characteristics. In many domains, like social services, the availability of possible interventions can be severely resource limited. This thesis considers possible improvements to the allocation of such services in the context of homelessness service provision in a major metropolitan area. Using data from the homeless system, I show potential for substantial predicted benefits in terms of reducing the number of families who experience repeat episodes of homelessness by choosing optimal allocations (based on predicted outcomes) to a fixed number of beds in different types of homelessness service facilities. Such changes in the allocation mechanism would not be without tradeoffs, however; a significant fraction of households are predicted to have a higher probability of reentry in the optimal allocation than in the original one. I discuss the efficiency, equity and fairness issues that arise and consider potential implications for policy
Intermittent fluctuations in the Alcator C-Mod scrape-off layer for ohmic and high confinement mode plasmas
Plasma fluctuations in the scrape-off layer of the Alcator C-Mod tokamak in
ohmic and high confinement modes have been analyzed using gas puff imaging
data. In all cases investigated, the time series of emission from a single
spatially-resolved view into the gas puff are dominated by large-amplitude
bursts, attributed to blob-like filament structures moving radially outwards
and poloidally. There is a remarkable similarity of the fluctuation statistics
in ohmic plasmas and in edge localized mode-free and enhanced D-alpha high
confinement mode plasmas. Conditionally averaged wave forms have a two-sided
exponential shape with comparable temporal scales and asymmetry, while the
burst amplitudes and the waiting times between them are exponentially
distributed. The probability density functions and the frequency power spectral
densities are self-similar for all these confinement modes. These results are
strong evidence in support of a stochastic model describing the plasma
fluctuations in the scrape-off layer as a super-position of uncorrelated
exponential pulses. Predictions of this model are in excellent agreement with
experimental measurements in both ohmic and high confinement mode plasmas. The
stochastic model thus provides a valuable tool for predicting
fluctuation-induced plasma-wall interactions in magnetically confined fusion
plasmas.Comment: 17 pages, 10 figure
Vector chiral order in frustrated spin chains
By means of a numerical analysis using a non-Abelian symmetry realization of
the density matrix renormalization group, we study the behavior of vector
chirality correlations in isotropic frustrated chains of spin S=1 and S=1/2,
subject to a strong external magnetic field. It is shown that the field induces
a phase with spontaneously broken chiral symmetry, in line with earlier
theoretical predictions. We present results on the field dependence of the
order parameter and the critical exponents.Comment: 8 pages, 9 figure
Comparison between mirror Langmuir probe and gas puff imaging measurements of intermittent fluctuations in the Alcator C-Mod scrape-off layer
Statistical properties of the scrape-off layer (SOL) plasma fluctuations are
studied in ohmically heated plasmas in the Alcator C-Mod tokamak. For the first
time, plasma fluctuations as well as parameters that describe the fluctuations
are compared across measurements from a mirror Langmuir probe (MLP) and from
gas-puff imaging (GPI) that sample the same plasma discharge. This comparison
is complemented by an analysis of line emission time-series data, synthesized
from the MLP electron density and temperature measurements. The fluctuations
observed by the MLP and GPI typically display relative fluctuation amplitudes
of order unity together with positively skewed and flattened probability
density functions. Such data time series are well described by an established
stochastic framework which model the data as a superposition of uncorrelated,
two-sided exponential pulses. The most important parameter of the process is
the intermittency parameter, {\gamma} = {\tau}d / {\tau}w where {\tau}d denotes
the duration time of a single pulse and {\tau}w gives the average waiting time
between consecutive pulses. Here we show, using a new deconvolution method,
that these parameters can be consistently estimated from different statistics
of the data. We also show that the statistical properties of the data sampled
by the MLP and GPI diagnostic are very similar. Finally, a comparison of the
GPI signal to the synthetic line-emission time series suggests that the
measured emission intensity can not be explained solely by a simplified model
which neglects neutral particle dynamics
Analyses of the vrl gene cluster in Desulfococcus multivorans: Homologous to the virulence-associated locus of the ovine footrot pathogen Dichelobacter nodosus strain A198
Major parts of the virulence-associated vrl locus known from the gammaproteobacterium Dichelobacter nodosus, the causative agent of ovine footrot, were analyzed in the genome of the sulfate-reducing deltaproteobacterium Desulfococcus multivorans. In the genome of D. multivorans 13 of the 19 vrl genes described for D. nodosus are present and highly conserved with respect to gene sequence and order. The vrl locus and its flanking regions suggest a bacteriophage-mediated transfer into the genome of D. multivorans. Comparative analysis of the deduced Vrl proteins reveals a wide distribution of parts of the virulence-associated vrl locus in distantly related bacteria. Horizontal transfer is suggested as driving mechanism for the circulation of the vrl genes in bacteria. Except for the vrlBMN genes D. multivorans and Desulfovibrio desulfuricans G20 together contain all vrl genes displaying a high degree of similarity. For D. multivorans it could be shown that guanine plus cytosine (GC) content, GC skew, di-, tri- or tetranucleotide distribution did not differ between the vrl locus and its flanking sequences. This could be a hint that the vrl locus originated from a related organism or at least a genome with similar characteristics. The conspicuous high degree of conservation of the analyzed vrl genes may result from a recent transfer event or reflect a function of the vrl genes, which is still unknown and not necessarily disease associated. The latter is supported by the evidence for expression of the vrl genes in D. multivorans, which has not been described as pathogen or to be associated to any disease pattern before
Outlier classification using Autoencoders: application for fluctuation driven flows in fusion plasmas
Understanding the statistics of fluctuation driven flows in the boundary
layer of magnetically confined plasmas is desired to accurately model the
lifetime of the vacuum vessel components. Mirror Langmuir probes (MLPs) are a
novel diagnostic that uniquely allow to sample the plasma parameters on a time
scale shorter than the characteristic time scale of their fluctuations. Sudden
large-amplitude fluctuations in the plasma degrade the precision and accuracy
of the plasma parameters reported by MLPs for cases in which the probe bias
range is of insufficient amplitude. While some data samples can readily be
classified as valid and invalid, we find that such a classification may be
ambiguous for up to 40% of data sampled for the plasma parameters and bias
voltages considered in this study. In this contribution we employ an
autoencoder (AE) to learn a low-dimensional representation of valid data
samples. By definition, the coordinates in this space are the features that
mostly characterize valid data. Ambiguous data samples are classified in this
space using standard classifiers for vectorial data. This way, we avoid to
define complicate threshold rules to identify outliers, which requires strong
assumptions and introduce biases in the analysis. Instead, these rules are
learned from the data by statistical inference By removing the outliers that
are identified in the latent low-dimensional space of the AE, we find that the
average conductive and convective radial heat flux are between approximately 5
and 15% lower as when removing outliers identified by threshold values. For
contributions to the radial heat flux due to triple correlations, the
difference is up to 40%
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Commuters route choice behaviour
The paper reports laboratory experiments with a two route choice scenario. In each session 18 subjects had to choose between a main road M and a side road S. The capacity of M was larger. Feedback was given in treatment I only on the subjects' own travel time and in treatment II on travel time for M and S. The main results are as follows:
• Mean numbers on M and S are near to pure equilibrium.
• Fluctuations persist until the end of the sessions.
• The total number of changes is significantly greater in treatment I.
• Subjects' road changes and payoffs are negatively correlated.
• A direct response mode results in more changes for bad payoffs whereas a contrary response mode shows opposite reactions.
• Simulations of an extended payoff sum learning model fits the main results of the statistical evaluation of the data
Burst statistics in Alcator C-Mod SOL turbulence
Bursty fluctuations in the scrape-off layer (SOL) of Alcator C-Mod have been
analyzed using gas puff imaging data. This reveals many of the same fluctuation
properties as Langmuir probe measurements, including normal distributed
fluctuations in the near SOL region while the far SOL plasma is dominated by
large amplitude bursts due to radial motion of blob-like structures.
Conditional averaging reveals burst wave forms with a fast rise and slow decay
and exponentially distributed waiting times. Based on this, a stochastic model
of burst dynamics is constructed. The model predicts that fluctuation
amplitudes should follow a Gamma distribution. This is shown to be a good
description of the gas puff imaging data, validating this aspect of the model.Comment: 8 pages, 6 figure
Blob sizes and velocities in the Alcator C-Mod scrape-off layer
A new blob-tracking algorithm for the GPI diagnostic installed in the outboard-midplane of Alcator C-Mod is developed. I t tracks large-amplitude fluctuations propagating through the scrape-off layer and calculates blob sizes and velocities. We compare the results of this method to a blob velocity scaling from a simple blob-model for sheath-connected blobs. We further present initial results from a fully three-dimensional blob model that features plasma resistivity as a free parameter
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