What can we learn about gravitational wave physics with an elastic spherial antenna?

A general formalism is set up to analyze the response of an arbitrary solid elastic body to an arbitrary metric gravitational wave (GW) perturbation, which fully displays the details of the interaction antenna wave. The formalism is applied to the spherical detector, whose sensitivity parameters are thereby scrutinized. A multimode transfer function is defined to study the amplitude sensitivity, and absorption cross sections are calculated for a general metric theory of GW physics. Their scaling properties are shown to be independent of the underlying theory, with interesting consequences for future detector design. The GW incidence direction deconvolution problem is also discussed, always within the context of a general metric theory of the gravitational field.

Proposed gravitational wave observatory based on solid elastic spheres

Spherical gravitational wave (GW) detectors offer a wealth of so far unexplored possibilities to detect gravitational radiation. We find that a sphere can be used as a powerful testbed for any metric theory of gravity, not only general relativity as considered so far, by making use of a deconvolution procedure for all the electric components of the Riemann tensor. We also find that the spheres cross section is large at two frequencies, and advantageous at higher frequencies in the sense that a single antenna constitutes a real xylophone in its own. Proposed GW networks will greatly benefit from this. The main features of a two large sphere observatory are reported.

Source-wavelet estimation during full-waveform inversion of ground-penetrating radar data

A major issue in the application of waveform inversion methods to crosshole ground-penetrating radar (GPR) data is the accurate estimation of the source wavelet. Here, we explore the viability and robustness of incorporating this step into a recently published time-domain inversion procedure through an iterative deconvolution approach. Our results indicate that, at least in non-dispersive electrical environments, such an approach provides remarkably accurate and robust estimates of the source wavelet even in the presence of strong heterogeneity of both the dielectric permittivity and electrical conductivity. Our results also indicate that the proposed source wavelet estimation approach is relatively insensitive to ambient noise and to the phase characteristics of the starting wavelet. Finally, there appears to be little to no trade-off between the wavelet estimation and the tomographic imaging procedures.

Rapid sample pre-treatment prior to GC-MS and GC-MS/MS urinary toxicological screening.

Drug screening is an important issue in clinical and forensic toxicology. Gas chromatography coupled to mass spectrometry (GC-MS) remains the gold standard technique for the screening of unknown compounds in urine samples. However, this technique requires substantial sample preparation, which is time consuming. Moreover, some common drugs such as cannabis cannot be easily detected in urine using general procedures. In this work, a sample preparation protocol for treating 200 μL of urine in less than 30 min is described. The enzymatic hydrolysis of glucuro-conjugates was performed in 5 min thanks to the use of microwaves. The use of a deconvolution software allowed reducing the GC-MS run to 10 min, without impairing the quality of the compound identifications. Comparing the results from 139 authentic urine samples to those obtained using the current routine analysis indicated this method performed well. Moreover, additional 5-min GC-MS/MS programs are described, enabling a very sensitive target screening of 54 drugs, including THC-COOH or buprenorphine, without further sample preparation. These methods appeared as an interesting alternative to immuno-assays based screening. The analytical strategy presented in this article proved to be a promising approach for systematic toxicological analysis (STA) of drugs in urine.

A Fast Gradient Approximation for Nonlinear Blind Signal Processing

When dealing with nonlinear blind processing algorithms (deconvolution or post-nonlinear source separation), complex mathematical estimations must be done giving as a result very slow algorithms. This is the case, for example, in speech processing, spike signals deconvolution or microarray data analysis. In this paper, we propose a simple method to reduce computational time for the inversion of Wiener systems or the separation of post-nonlinear mixtures, by using a linear approximation in a minimum mutual information algorithm. Simulation results demonstrate that linear spline interpolation is fast and accurate, obtaining very good results (similar to those obtained without approximation) while computational time is dramatically decreased. On the other hand, cubic spline interpolation also obtains similar good results, but due to its intrinsic complexity, the global algorithm is much more slow and hence not useful for our purpose.

A Canonical Genetic Algorithm for Blind Inversion of Linear Channels

It is well known the relationship between source separation and blind deconvolution: If a filtered version of an unknown i.i.d. signal is observed, temporal independence between samples can be used to retrieve the original signal, in the same manner as spatial independence is used for source separation. In this paper we propose the use of a Genetic Algorithm (GA) to blindly invert linear channels. The use of GA is justified in the case of small number of samples, where other gradient-like methods fails because of poor estimation of statistics.

A comparison of alpha and gamma spectrometry for environmental natural radioactivity surveys.

An alpha-spectrometry, using automated borate fusion and sequential extraction and exchange chromatography, was used to determine the uranium and thorium based on environmental radioactivity of 20 soil samples. The same set of the samples was analysed using gamma-spectrometry with an HPGe detector. The two data sets were checked for coherence using Z-score and chi2 statistical tests. We show that gamma-spectrometry is a valid alternative to time-consuming alpha-spectrometry for the determination of natural uranium and thorium activity in soil (activity range: 12.5-58.2 Bq/kg). The measured activities were compared with the theoretical activities to ensure secular equilibrium in the 238U and 232Th series. For 226Ra, a special study was made on deconvolution of the 186 keV multiplet with the Levenberg-Marquardt algorithm. Finally, the combined use of Z-score and chi2-tests was found to be a powerful tool for comparing the results obtained with two different methods.

Simultaneous measurement of regional cerebral blood flow by perfusion CT and stable xenon CT: a validation study.

BACKGROUND AND PURPOSE: Knowledge of cerebral blood flow (CBF) alterations in cases of acute stroke could be valuable in the early management of these cases. Among imaging techniques affording evaluation of cerebral perfusion, perfusion CT studies involve sequential acquisition of cerebral CT sections obtained in an axial mode during the IV administration of iodinated contrast material. They are thus very easy to perform in emergency settings. Perfusion CT values of CBF have proved to be accurate in animals, and perfusion CT affords plausible values in humans. The purpose of this study was to validate perfusion CT studies of CBF by comparison with the results provided by stable xenon CT, which have been reported to be accurate, and to evaluate acquisition and processing modalities of CT data, notably the possible deconvolution methods and the selection of the reference artery. METHODS: Twelve stable xenon CT and perfusion CT cerebral examinations were performed within an interval of a few minutes in patients with various cerebrovascular diseases. CBF maps were obtained from perfusion CT data by deconvolution using singular value decomposition and least mean square methods. The CBF were compared with the stable xenon CT results in multiple regions of interest through linear regression analysis and bilateral t tests for matched variables. RESULTS: Linear regression analysis showed good correlation between perfusion CT and stable xenon CT CBF values (singular value decomposition method: R(2) = 0.79, slope = 0.87; least mean square method: R(2) = 0.67, slope = 0.83). Bilateral t tests for matched variables did not identify a significant difference between the two imaging methods (P >.1). Both deconvolution methods were equivalent (P >.1). The choice of the reference artery is a major concern and has a strong influence on the final perfusion CT CBF map. CONCLUSION: Perfusion CT studies of CBF achieved with adequate acquisition parameters and processing lead to accurate and reliable results.

Source separation techniques applied to linear prediction

The prediction filters are well known models for signal estimation, in communications, control and many others areas. The classical method for deriving linear prediction coding (LPC) filters is often based on the minimization of a mean square error (MSE). Consequently, second order statistics are only required, but the estimation is only optimal if the residue is independent and identically distributed (iid) Gaussian. In this paper, we derive the ML estimate of the prediction filter. Relationships with robust estimation of auto-regressive (AR) processes, with blind deconvolution and with source separation based on mutual information minimization are then detailed. The algorithm, based on the minimization of a high-order statistics criterion, uses on-line estimation of the residue statistics. Experimental results emphasize on the interest of this approach.

Nonlinear prediction based on score function

The linear prediction coding of speech is based in the assumption that the generation model is autoregresive. In this paper we propose a structure to cope with the nonlinear effects presents in the generation of the speech signal. This structure will consist of two stages, the first one will be a classical linear prediction filter, and the second one will model the residual signal by means of two nonlinearities between a linear filter. The coefficients of this filter are computed by means of a gradient search on the score function. This is done in order to deal with the fact that the probability distribution of the residual signal still is not gaussian. This fact is taken into account when the coefficients are computed by a ML estimate. The algorithm based on the minimization of a high-order statistics criterion, uses on-line estimation of the residue statistics and is based on blind deconvolution of Wiener systems [1]. Improvements in the experimental results with speech signals emphasize on the interest of this approach.

The Coordinated Radio and Infrared Survey for High-mass Star Formation. II. Source Catalog

The CORNISH project is the highest resolution radio continuum survey of the Galactic plane to date. It is the 5 GHz radio continuum part of a series of multi-wavelength surveys that focus on the northern GLIMPSE region (10° < l < 65°), observed by the Spitzer satellite in the mid-infrared. Observations with the Very Large Array in B and BnA configurations have yielded a 1.''5 resolution Stokes I map with a root mean square noise level better than 0.4 mJy beam 1. Here we describe the data-processing methods and data characteristics, and present a new, uniform catalog of compact radio emission. This includes an implementation of automatic deconvolution that provides much more reliable imaging than standard CLEANing. A rigorous investigation of the noise characteristics and reliability of source detection has been carried out. We show that the survey is optimized to detect emission on size scales up to 14'' and for unresolved sources the catalog is more than 90% complete at a flux density of 3.9 mJy. We have detected 3062 sources above a 7σ detection limit and present their ensemble properties. The catalog is highly reliable away from regions containing poorly sampled extended emission, which comprise less than 2% of the survey area. Imaging problems have been mitigated by down-weighting the shortest spacings and potential artifacts flagged via a rigorous manual inspection with reference to the Spitzer infrared data. We present images of the most common source types found: H II regions, planetary nebulae, and radio galaxies. The CORNISH data and catalog are available online at http://cornish.leeds.ac.uk.

Estimativa por infravermelho da concentração da unidade estrutural b-O-4 em ligninas de angiospermas tropicais

Five Björkman lignins, codified as AM, LL, GG, PP and AP, were isolated from wood species of Aspidosperma macrocarpum Mart., Lophanthera lactescens Ducke, Gallesia gorazema (Vell.) Miq., Peltogyne paniculata Bth. and Aspidosperma polyneuron Muell. Arg., respectively. Analyses of the lignins were carried out by Fourier transformed infrared spectroscopy using an experimental technique, Diffusely Reflected Infrared Fourier Transformed (DRIFT), admitting in the original spectra a band at 1500 cm-1 as an internal reference. Application of a deconvolution technique made possible to estimate the percentage per mol of b-O-4 unit content around 65.5% to AM, 68.0% to LL, 71.0% to GG. 73.4% to PP and 75.0% to AP, toward AM

Estudo de métodos de aumento de resolução de espectros de FTIR para análise de estruturas secundárias de proteínas

The FTIR spectroscopy has been used to quantify the secondary structures of proteins, using amide I band (1600 - 1700 cm-1). The resolution enhancement methods have been used to resolve the individual components of this band that correlate to the secondary structure. In this paper we discuss the methods of derivative, Fourier deconvolution and fitting with simulated spectra. The results shows that they have serious problems and can be used only as a qualitative or semiquatitative method.

Metodologias eletroanalíticas para a determinação de herbicidas triazínicos por voltametria de onda quadrada e técnicas de deconvolução

This work describes the development of electroanalytical methodologies for the determination of atrazine, ametrine and simazine by square wave voltammetry on a mercury electrode. For pure atrazine and pure ametrine, the detection limits (DL) were 3.7 and 4.3 µg L-1, respectively, while they increased to 4.8 and 6.5 µg L-1 in the presence of 3.0 x 10-6 mol L-1 of the other component (a mathematical deconvolution program was used in the mixture cases). The voltammetric response for simazine could not be separated from that of atrazine and measurements were carried out only in pure simazine solutions (DL: 7.5 µg L-1).

COMPARAÇÃO DE PROCESSAMENTOS MATEMÁTICOS DE DADOS VOLTAMÉTRICOS: APLICAÇÃO NA DETERMINAÇÃO SIMULTÂNEA DE FLUOROQUINOLONAS

This paper describes a comparative study between the procedures of deconvolution and the second-order derivative of square wave voltammograms to achieve separation of the voltammetric peaks of levofloxacin (LEVO) and norfloxacin (NOR), for their simultaneous quantification in urine samples. The obtained results indicate that the use of second-derivative voltammograms coupled with carbon screen-printed electrodes is the most efficient approach for completely separating the voltammetric peaks of LEVO and NOR. In addition, this approach has produced detection limits lower than 1.0 µmol L-1 and a wide linear range for both drugs. The proposed method was successfully used to simultaneously determine LEVO and NOR in spiked human and bovine urine samples with recovery percentages close to 100% for all analyzed samples.