5,564 research outputs found
Delay-Coordinates Embeddings as a Data Mining Tool for Denoising Speech Signals
In this paper we utilize techniques from the theory of non-linear dynamical
systems to define a notion of embedding threshold estimators. More specifically
we use delay-coordinates embeddings of sets of coefficients of the measured
signal (in some chosen frame) as a data mining tool to separate structures that
are likely to be generated by signals belonging to some predetermined data set.
We describe a particular variation of the embedding threshold estimator
implemented in a windowed Fourier frame, and we apply it to speech signals
heavily corrupted with the addition of several types of white noise. Our
experimental work seems to suggest that, after training on the data sets of
interest,these estimators perform well for a variety of white noise processes
and noise intensity levels. The method is compared, for the case of Gaussian
white noise, to a block thresholding estimator
Detecting periodicity in experimental data using linear modeling techniques
Fourier spectral estimates and, to a lesser extent, the autocorrelation
function are the primary tools to detect periodicities in experimental data in
the physical and biological sciences. We propose a new method which is more
reliable than traditional techniques, and is able to make clear identification
of periodic behavior when traditional techniques do not. This technique is
based on an information theoretic reduction of linear (autoregressive) models
so that only the essential features of an autoregressive model are retained.
These models we call reduced autoregressive models (RARM). The essential
features of reduced autoregressive models include any periodicity present in
the data. We provide theoretical and numerical evidence from both experimental
and artificial data, to demonstrate that this technique will reliably detect
periodicities if and only if they are present in the data. There are strong
information theoretic arguments to support the statement that RARM detects
periodicities if they are present. Surrogate data techniques are used to ensure
the converse. Furthermore, our calculations demonstrate that RARM is more
robust, more accurate, and more sensitive, than traditional spectral
techniques.Comment: 10 pages (revtex) and 6 figures. To appear in Phys Rev E. Modified
styl
Influence of composite particle formation on the performance and economics of grit removal
Grit is routinely removed at the headworks of municipal wastewater treatment works to limit its onerous impact on downstream processes. Grit separation technologies are normally based on sedimentation of a homogeneous material (usually sand). However, in practice inorganic grit particles are likely to be combined with organic matter, such as fats oils and grease (FOG), producing a composite particle whose settling properties vary with the inorganic/organic content.
A study of the impact of particle composition on its sedimentation has been conducted encompassing theoretical description (for particle settling in transitional flow), practical measurement and economic analysis. Practical measurement included sedimentation tests of homogeneous and composite particles along with characterisation of accumulated granular material sampled from actual municipal wastewater treatment works. The economic assessment was based on data from full-scale installations in the UK and US pertaining to remedial measures undertaken as a result of grit impacts, primarily accumulation in vessels and channels and damage of mechanical equipment through abrasion.
Practical tests revealed coating of the sand grains with a FOG analogue (candlewax) to generate composite particles containing 45% wax by weight. The coated particles were then 30% less dense, 22% larger and 14% less settleable, on average, than the uncoated particles. Samples of accumulated grit taken from anaerobic digesters and aeration lanes from a full-scale plant indicated a FOG content (43%) similar to that of the waxed particles in the bench-scale tests, thus leading to a similar grain retardation of 14% assuming the FOG to be entirely associated with the grit. An assessment of the impact of the consequential breakthrough of grit particles due to buoyancy generated by composite particle formation indicated a $1.1 increase in operating costs per megalitre (ML) wastewater
Geometric scaling in the spectrum of an electron captured by a stationary finite dipole
We examine the energy spectrum of a charged particle in the presence of a
{\it non-rotating} finite electric dipole. For {\emph{any}} value of the dipole
moment above a certain critical value p_{\mathrm{c}}$ an infinite series of
bound states arises of which the energy eigenvalues obey an Efimov-like
geometric scaling law with an accumulation point at zero energy. These
properties are largely destroyed in a realistic situation when rotations are
included. Nevertheless, our analysis of the idealised case is of interest
because it may possibly be realised using quantum dots as artificial atoms.Comment: 5 figures; references added, outlook section reduce
Machine Learning-Based Signal Degradation Models for Attenuated Underwater Optical Communication OAM Beams
Signal attenuation in underwater communications is a problem that degrades classification performance. Several novel CNN-based (SMART) models are developed to capture the physics of the attenuation process. One model is built and trained using automatic differentiation and another uses the radon cumulative distribution transform. These models are inserted in the classifier training pipeline. It is shown that including these attenuation models in classifier training significantly improves classification performance when the trained model is tested with environmentally attenuated images. The improved classification accuracy will be important in future OAM underwater optical communication applications
N-Terminal Pro–B-Type Natriuretic Peptide in the Emergency Department: The ICON-RELOADED Study
Background
Contemporary reconsideration of diagnostic N-terminal pro–B-type natriuretic peptide (NT-proBNP) cutoffs for diagnosis of heart failure (HF) is needed.
Objectives
This study sought to evaluate the diagnostic performance of NT-proBNP for acute HF in patients with dyspnea in the emergency department (ED) setting.
Methods
Dyspneic patients presenting to 19 EDs in North America were enrolled and had blood drawn for subsequent NT-proBNP measurement. Primary endpoints were positive predictive values of age-stratified cutoffs (450, 900, and 1,800 pg/ml) for diagnosis of acute HF and negative predictive value of the rule-out cutoff to exclude acute HF. Secondary endpoints included sensitivity, specificity, and positive (+) and negative (−) likelihood ratios (LRs) for acute HF.
Results
Of 1,461 subjects, 277 (19%) were adjudicated as having acute HF. The area under the receiver-operating characteristic curve for diagnosis of acute HF was 0.91 (95% confidence interval [CI]: 0.90 to 0.93; p < 0.001). Sensitivity for age stratified cutoffs of 450, 900, and 1,800 pg/ml was 85.7%, 79.3%, and 75.9%, respectively; specificity was 93.9%, 84.0%, and 75.0%, respectively. Positive predictive values were 53.6%, 58.4%, and 62.0%, respectively. Overall LR+ across age-dependent cutoffs was 5.99 (95% CI: 5.05 to 6.93); individual LR+ for age-dependent cutoffs was 14.08, 4.95, and 3.03, respectively. The sensitivity and negative predictive value for the rule-out cutoff of 300 pg/ml were 93.9% and 98.0%, respectively; LR− was 0.09 (95% CI: 0.05 to 0.13).
Conclusions
In acutely dyspneic patients seen in the ED setting, age-stratified NT-proBNP cutpoints may aid in the diagnosis of acute HF. An NT-proBNP <300 pg/ml strongly excludes the presence of acute HF
Emergence and rapid global dissemination of CTX-M-15-associated Klebsiella pneumoniae strain ST307
Abstract Recent reports indicate the emergence of a new carbapenemase producing Klebsiella pneumoniae clone, ST307. Here we show that ST307 emerged in the mid-1990s (nearly 20 years prior to its first report), is already globally distributed and is intimately associated with a conserved plasmid harbouring the bla CTX-M-15 extended-spectrum beta-lactamase (ESBL) gene plus other antimicrobial resistance determinants. Our findings support the need for enhanced surveillance of this widespread ESBL clone in which carbapenem resistance is now emerging
Solving OLG Models with Many Cohorts, Asset Choice and Large Shocks
The paper presents a computationally efficient method to solve overlapping generations models with asset choice. The method is used to study an OLG economy with many cohorts, up to 3 different assets, stochastic volatility, short-sale constraints, and subject to rather large technology shocks.
On the methodological side, the main findings are that global projection methods with polynomial approximations of degree 3 are sufficient to provide a very precise solution, even in the case of large shocks. Globally linear approximations, in contrast to local linear approximations, are sufficient to capture the most important financial statistics, including not only the average risk premium, but also the variation of the risk premium over the cycle. However, global linear approximations are not sufficient to reliably pin down asset choices.
With a risk aversion parameter of only 4, the model generates a price of risk, measured as the Sharpe ratio, that is almost half of what it is for US stocks. However, the asset price fluctuations and the equity premium are much smaller than in US data
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