On the convergence of an approximate deconvolution model to the 3D mean Boussinesq equations

In this paper, we study an LES model for the approximation of large scales of the 3D Boussinesq equations. This model is obtained using the approach first described by Stolz and Adams, based on the Van Cittern approximate deconvolution operators, and applied to the filtered Boussinesq equations. Existence and uniqueness of a regular weak solution are provided. Our main objective is to prove that this solution converges towards a solution of the filtered Boussinesq equations, as the deconvolution parameter goes to zero. Copyright © 2014 John Wiley & Sons, Ltd.     

Energy analysis and improved regularity estimates for multiscale deconvolution models of incompressible flows

This paper presents new analytical results and the first numerical results for a recently proposed multiscale deconvolution model (MDM) recently proposed. The model involves a large‐eddy simulation closure that uses a novel deconvolution approach based on the introduction of two distinct filtering length scales. We establish connections between the MDM and two other models, and, on the basis of one of these connections, we establish an improved regularity estimate for MDM solutions. We also prove that the MDM preserves Taylor‐eddy solutions of the Navier–Stokes equations and therefore does not distort this particular vortex structure. Simulations of the MDM are performed to examine the accuracy of the MDM and the effect of the filtering length scales on energy spectra for three‐dimensional homogeneous and isotropic flows. Numerical evidence for all tests clearly indicates that the MDM gives very accurate coarse‐mesh solutions and that this multiscale approach to deconvolution is effective. Copyright © 2015 John Wiley & Sons, Ltd.     

Automated instrumental method for on-line fraction analysis and peak deconvolution in gradient multicomponent overloaded high performance liquid chromatography

An automated method for deconvolution of overloaded band profiles in gradient elution is described. The instrumental set-up consists of a pseudo-bidimensional HPLC system, where overloaded band profiles generated in the first direction are sampled on the second one. The method, previously employed under isocratic conditions, has been now extended to gradient elution, where one has to face the problem of band compression (and possibly band interference) during gradient, which decreases the time-window available along the first direction for sampling the overloaded profiles. The effect of the gradient steepness on the problem of defining a minimum number of sampling points to reconstruct single component bands from overloaded profiles is investigated. This approach is particularly useful in the framework of using inverse method (IM) to determine adsorption isotherm parameters for preparative gradient elution. In fact, it allows for the gathering of the information necessary to run IM calculations with minimum efford, also in cases where the individual component forming the mixture have different UV spectra.     

One‐dimensional small‐angle X‐ray scattering tomography of dip‐coated polyamide 6 monofilaments

A synchrotron study is presented in which the concept of one‐dimensional tomographic reconstruction of small‐angle X‐ray scattering patterns is applied to investigate polyamide 6 monofilaments, dip‐coated with alumina particles. The filaments are scanned with a focused synchrotron beam and the resulting scattering patterns are recorded with a PILATUS 2M detector. The reconstructed sequence of SAXS images reflects the local nanostructure variation along the filament radius. In particular, the influence of coating process parameters on the polyamide 6 is investigated.     

Estimation of speed of sound in dual-layered media using medical ultrasound image deconvolution

The speed of sound in soft tissues is usually assumed to be 1540 m/s in medical pulse-echo ultrasound imaging systems. When the true speed is different, the mismatch can lead to distortions in the acquired images, and so reduce their clinical value. Previously we reported a new method of sound-speed estimation in the context of image deconvolution. Unlike most other sound-speed estimation methods, this enables the use of unmodified ultrasound machines and a normal scanning pattern. Our approach was validated for largely homogeneous media with single sound speeds. In this article, we demonstrate that sound speeds of dual-layered media can also be estimated through image deconvolution. An ultrasound simulator has been developed for layered media assuming that, for moderate speed differences, the reflection at the interface may be neglected. We have applied our dual-layer algorithm to simulations and in vitro phantoms. The speed of the top layer is estimated by our aforesaid method for homogeneous media. Then, when the layer boundary position is known, a series of deconvolutions are carried out with dual-layered point-spread functions having different lower-layer speeds. The best restoration is selected using a correlation metric. The error level (e.g., a mean error of −9 m/s with a standard deviation of 16 m/s) for in vitro phantoms is found to be not as good as that of our single-speed algorithm, but is comparable to other local speed estimation methods where the data acquisition may not be as simple as in our proposed method.     

Sequential stir bar extraction,thermal desorption and retention time locked GC–MS for determination of pesticides in water

A method based on sequential stir bar sorptive extraction followed by automated thermal desorption–GC–MS for the determination of pesticides in underground and superficial water samples has been developed. Retention time locked GC–MS and deconvolution Automated Mass Spectral Deconvolution and Identification System software allows the use of pesticide databases for identification and quantification in routine applications. Quantitation limits and repetitivity using full scan mass spectrometric determination guarantee the applicability of the method, which enables considerable savings to be made in total analysis time, with data processing times of around 2 min/sample.     

双线圈感应测井信号反褶积处理方法

在对于双线圈感应测井信号处理的研究中,提出两种对于几何因子信号反褶积处理的方法。包括了最佳维纳滤波反褶积与窗函数滤波反褶积对于背景电导率信号还原的处理方法。其特点在通过仿真,比较两种处理方法的有效性和各自的优势,有利于对于测量信号还原真电导率的实际应用,提高测量分辨率,使测量数据处理结果比传统处理更有利于薄层解析。     

De-noising techniques for terahertz responses of biological samples

Signal processing techniques may be used to improve the speed, resolution and noise robustness of pulsed terahertz (T-ray) imaging systems. Such systems have a wide range of applications and much recent interest has focussed on several promising biomedical fields. There are a number of significant challenges to be overcome before a commercial biomedical terahertz system can be realised. Recent research is focussed on the implementation of a high speed, compact and portable T-ray imaging system. This system will draw heavily on MOEMS technology. One of the major stages in the development of such a system is the design of efficient software algorithms to perform signal recognition and imaging operations in real time.

This paper considers a number of signal processing techniques suitable for de-noising and extracting information from the data obtained in a terahertz pulse imaging system. Two main de-noising techniques are considered. Wavelet de-noising and Wiener deconvolution algorithms are applied to the terahertz responses of biological samples including Spanish Serrano ham and an oak leaf.     

Employing the ForWaRD Method to Improve Resolution of Conventional OTDR for Application in SHM

As a fiber sensor,optical time domain reflectometer becomes more and more popular to measure parameters,such as strain and temperature in structural health monitoring(SHM) simultaneously.Since the accuracy of range resolution in optical time domain reflectometer(OTDR) is determined by the pulse width of laser,the range resolution in order of centimeter is achieved by employing of picoseconds lasers which are not commercial.In this paper,to achieve this accuracy with conventional OTDR,Fourier wavelet regular...     

Combined Wavelet Transform with Curve‐fitting for Objective Optimization of the Parameters in Fourier Self‐deconvolution

Fourier self‐deconvolution was the most effective technique in resolving overlapping bands, in which deconvolution function results in deconvolution and apodization smoothes the magnified noise. Yet, the choice of the original half‐width of each component and breaking point for truncation is often very subjective. In this paper, the method of combined wavelet transform with curve fitting was described with the advantages of an enhancement of signal to noise ratio as well as the improved fitting condition, and was applied to objective optimization of the original half‐widths of components in unresolved bands for Fourier self‐deconvolution. Again, a noise was separated from a noisy signal by wavelet transform, therefore, the breaking point of apodization function can be determined directly in frequency domain. Accordingly, some artifacts in Fourier self‐deconvolution were minimized significantly.