17,837 research outputs found
Using the Expectation Maximization Algorithm with Heterogeneous Mixture Components for the Analysis of Spectrometry Data
Coupling a multi-capillary column (MCC) with an ion mobility (IM)
spectrometer (IMS) opened a multitude of new application areas for gas
analysis, especially in a medical context, as volatile organic compounds (VOCs)
in exhaled breath can hint at a person's state of health. To obtain a potential
diagnosis from a raw MCC/IMS measurement, several computational steps are
necessary, which so far have required manual interaction, e.g., human
evaluation of discovered peaks. We have recently proposed an automated pipeline
for this task that does not require human intervention during the analysis.
Nevertheless, there is a need for improved methods for each computational step.
In comparison to gas chromatography / mass spectrometry (GC/MS) data, MCC/IMS
data is easier and less expensive to obtain, but peaks are more diffuse and
there is a higher noise level. MCC/IMS measurements can be described as samples
of mixture models (i.e., of convex combinations) of two-dimensional probability
distributions. So we use the expectation-maximization (EM) algorithm to
deconvolute mixtures in order to develop methods that improve data processing
in three computational steps: denoising, baseline correction and peak
clustering. A common theme of these methods is that mixture components within
one model are not homogeneous (e.g., all Gaussian), but of different types.
Evaluation shows that the novel methods outperform the existing ones. We
provide Python software implementing all three methods and make our evaluation
data available at http://www.rahmannlab.de/research/ims
Treatment of bimodality in proficiency test of pH in bioethanol matrix
The pH value in bioethanol is a quality control parameter related to its
acidity and to the corrosiveness of vehicle engines when it is used as fuel. In
order to verify the comparability and reliability of the measurement of pH in
bioethanol matrix among some experienced chemical laboratories, reference
material (RM) of bioethanol developed by Inmetro - the Brazilian National
Metrology Institute - was used in a proficiency testing (PT) scheme. There was
a difference of more than one unit in the value of the pH measured due to the
type of internal filling electrolytic solutions (potassium chloride, KCl or
lithium chloride, LiCl) from the commercial pH combination electrodes used by
the participant laboratories. Therefore, bimodal distribution has occurred from
the data of this PT scheme. This work aims to present the possibilities that a
PT scheme provider can use to overcome the bimodality problem. Data from the PT
of pH in bioethanol were treated by two different statistical approaches:
kernel density model and the mixture of distributions. Application of these
statistical treatments improved the initial diagnoses of PT provider, by
solving bimodality problem and contributing for a better performance evaluation
in measuring pH of bioethanol.Comment: 20 pages, 6 figures, Accepted for publication in Accreditation and
Quality Assurance (ACQUAL
Optimizing gravitational-wave searches for a population of coalescing binaries: Intrinsic parameters
We revisit the problem of searching for gravitational waves from inspiralling
compact binaries in Gaussian coloured noise. For binaries with quasicircular
orbits and non-precessing component spins, considering dominant mode emission
only, if the intrinsic parameters of the binary are known then the optimal
statistic for a single detector is the well-known two-phase matched filter.
However, the matched filter signal-to-noise ratio is /not/ in general an
optimal statistic for an astrophysical population of signals, since their
distribution over the intrinsic parameters will almost certainly not mirror
that of noise events, which is determined by the (Fisher) information metric.
Instead, the optimal statistic for a given astrophysical distribution will be
the Bayes factor, which we approximate using the output of a standard template
matched filter search. We then quantify the possible improvement in number of
signals detected for various populations of non-spinning binaries: for a
distribution of signals uniformly distributed in volume and with component
masses distributed uniformly over the range ,
at fixed expected SNR, we find more
signals at a false alarm threshold of Hz in a single detector. The
method may easily be generalized to binaries with non-precessing spins.Comment: Version accepted by Phys. Rev.
Common Arc Method for Diffraction Pattern Orientation
Very short pulses of x-ray free-electron lasers opened the way to obtain
diffraction signal from single particles beyond the radiation dose limit. For
3D structure reconstruction many patterns are recorded in the object's unknown
orientation. We describe a method for orientation of continuous diffraction
patterns of non-periodic objects, utilizing intensity correlations in the
curved intersections of the corresponding Ewald spheres, hence named Common Arc
orientation. Present implementation of the algorithm optionally takes into
account the Friedel law, handles missing data and is capable to determine the
point group of symmetric objects. Its performance is demonstrated on simulated
diffraction datasets and verification of the results indicates high orientation
accuracy even at low signal levels. The Common Arc method fills a gap in the
wide palette of the orientation methods.Comment: 16 pages, 10 figure
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