An analytic method to predict the thermal map of cryosurgery iceballs in MR images

This paper presents a newly developed method to estimate, in magnetic resonance (MR) images, the temperatures reached within the volume of an iceball produced by a cryogenic probe. Building on the direct measurements of the MR signal intensity and its correlation with independent temperature variations at the phase transition from liquid to solid, the thermal information embedded in the images was accessed. The volume and diameter of the growing iceball were estimated from a time series of MR images. Using regressions over the volume in the time and thermal domains, this method predicted the cryogenic temperatures beyond the range of sensitivity of the MR signal itself. We present a validation of this method in samples of gelatin and ex vivo pig liver. Temperature predictions are shown to agree with independent thermosensor readings over a range extending from 20 degrees C down to -65 degrees C, with an average error of less than 6 degrees C.     

Denoising functional MR images: a comparison of wavelet denoising and Gaussian smoothing

We present a general wavelet-based denoising scheme for functional magnetic resonance imaging (fMRI) data and compare it to Gaussian smoothing, the traditional denoising method used in fMRI analysis. One-dimensional WaveLab thresholding routines were adapted to two-dimensional (2-D) images, and applied to 2-D wavelet coefficients. To test the effect of these methods on the signal-to-noise ratio (SNR), we compared the SNR of 2-D fMRI images before and after denoising, using both Gaussian smoothing and wavelet-based methods. We simulated a fMRI series with a time signal in an active spot, and tested the methods on noisy copies of it. The denoising methods were evaluated in two ways: by the average temporal SNR inside the original activated spot, and by the shape of the spot detected by thresholding the temporal SNR maps. Denoising methods that introduce much smoothness are better suited for low SNRs, but for images of reasonable quality they are not preferable, because they introduce heavy deformations. Wavelet-based denoising methods that introduce less smoothing preserve the sharpness of the images and retain the original shapes of active regions. We also performed statistical parametric mapping on the denoised simulated time series, as well as on a real fMRI data set. False discovery rate control was used to correct for multiple comparisons. The results show that the methods that produce smooth images introduce more false positives. The less smoothing wavelet-based methods, although generating more false negatives, produce a smaller total number of errors than Gaussian smoothing or wavelet-based methods with a large smoothing effect.     

Common-Mode Response Overlapping vs. Shaping in Rail-to-Rail Op-Amp Input Stages

In this paper, a circuit technique—common-mode (CM) response overlapping—for maintaining the small-signal behavior of rail-to-rail amplifiers nearly constant over the whole input CM range, is introduced. This technique modifies the CM response of the rail-to-rail input stage adequately by means of two constant input floating voltage sources, which are adjusted by using a static tuning section. Its performance is compared with a second technique—CM response shaping—, which is also based on two variable input floating voltage sources, but relies on a dynamic feedback tuning loop. Experimental results obtained from two 3-V 0.8-m CMOS single-stage rail-to-rail amplifiers, which operate with CM response overlapping and shaping, respectively, are provided.     

An inquiry of the opinions of the French and Belgian populations as regards risk

IRSN (France) and SCK-CEN (Belgium), two institutes of research and expertise in radiation protection and nuclear safety, simultaneously organised a very similar public opinion survey in their respective countries in November 2002. The study explores subjects such as: major people's concerns, perception of environmental risks, perception of risks in general, the role of experts in decision making, opinions on nuclear matters and aspects of nuclear emergency preparedness. In each country, more than 1000 citizens representing the general public have been consulted in face-to-face interviews. The field work has been performed by professional companies (BVA in France and Research International in Belgium). The paper shows that industrial and technological risks are not perceived as one of the major public concerns, although many other risks, of different nature are considered to be high. The actions of the authorities to provide protection against the consequences of many risks or disasters are not considered to be sufficient, and many respondents claim not to believe the information they receive. There exists a large difference between the opinion of French and Belgian public, and within the different language groups in Belgium, with regard to who should be in charge of the control of the hazardous industries. Many of the "actors" within the nuclear industry are not known by the respondents. The perception of the technical competence or the truth being told shows large variations between the main actors (such as members of the nuclear industry, the government or the media). Majorities within the population believe that a disaster as serious as the Chernobyl one can happen in their country and that in case of a nuclear accident, the authorities would not be capable to protect the population adequately.     

Phytotoxicity and heavy metals speciation of stabilised sewage sludges

The presence of heavy metals in the sludges produced in wastewater treatment restricts plants growth and hence their use for agricultural purposes. This study looks at different types of sludges (aerobic, anaerobic, unstabilised and sludge from a waste stabilisation pond) and compares the distribution of the heavy metals that they contain according to the treatment that they have undergone. The sewage sludges were subjected to chemical characterisation and phytotoxicity testing (in absence of substrate) to provide a preliminary assessment of their suitability for land application. In addition, the total quantity of metals (Cd, Cr, Cu, Ca, K, Fe, Mg, Ni, Na, Pb and Zn) was determined. The Community Bureau of Reference (BCR) method for heavy metal speciation was followed. It was confirmed that the total concentration of heavy metals did not exceed the limits set out by European legislation and that the stabilisation treatment undergone by the sludges strongly influenced the heavy metal distribution and the phases to which they were associated. The sludge extracts did not exert any significant adverse effect on the relative seed germination (RSG) of barley (Hordeum vulgare L.) or cress (Lepidium sativum L.), although the reduction in germination index (GI) indicates that some characteristics existed did have an adverse effect on root growth.     

Two-dimensional Fourier transform of scaled Dirac delta curves

We obtain a Fourier transform scaling relation to find analytically, numerically, or experimentally the spectrum of an arbitrary scaled two-dimensional Dirac delta curve from the spectrum of the nonscaled curve. An amplitude factor is derived and given explicitly in terms of the scaling factors and the angle of the forward tangent at each point of the curve about the positive x axis. With the scaling relation we determine the spectrum of an elliptic curve by a circular geometry instead of an elliptical one. The generalization to N-dimensional Dirac delta curves is also included.     

CPM: a deformable model for shape recovery and segmentation based on charged particles

A novel, physically motivated deformable model for shape recovery and segmentation is presented. The model, referred to as the charged-particle model (CPM), is inspired by classical electrodynamics and is based on a simulation of charged particles moving in an electrostatic field. The charges are attracted towards the contours of the objects of interest by an electrostatic field, whose sources are computed based on the gradient-magnitude image. The electric field plays the same role as the potential forces in the snake model, while internal interactions are modeled by repulsive Coulomb forces. We demonstrate the flexibility and potential of the model in a wide variety of settings: shape recovery using manual initialization, automatic segmentation, and skeleton computation. We perform a comparative analysis of the proposed model with the active contour model and show that specific problems of the latter are surmounted by our model. The model is easily extendable to 3D and copes well with noisy images.     

Formal verification of a generic framework to synthesize SAT-provers

We present in this paper an application of the ACL2 system to generate and reason about propositional satisfiability provers. For that purpose, we develop a framework in which we define a generic S AT-prover based on transformation rules, and we formalize this generic framework in the ACL2 logic, carrying out a formal proof of its termination, soundness, and completeness. This generic framework can be instantiated to obtain a number of verified and executable SAT-provers in ACL2, and this instantiation can be done in an automated way. Three instantiations of the generic framework are considered: semantic tableaux, sequent calculus, and Davis-Putnam-Logeman-Loveland methods.     

Minimax mutual information approach for independent component analysis

Minimum output mutual information is regarded as a natural criterion for independent component analysis (ICA) and is used as the performance measure in many ICA algorithms. Two common approaches in information-theoretic ICA algorithms are minimum mutual information and maximum output entropy approaches. In the former approach, we substitute some form of probability density function (pdf) estimate into the mutual information expression, and in the latter we incorporate the source pdf assumption in the algorithm through the use of nonlinearities matched to the corresponding cumulative density functions (cdf). Alternative solutions to ICA use higher-order cumulant-based optimization criteria, which are related to either one of these approaches through truncated series approximations for densities. In this article, we propose a new ICA algorithm motivated by the maximum entropy principle (for estimating signal distributions). The optimality criterion is the minimum output mutual information, where the estimated pdfs are from the exponential family and are approximate solutions to a constrained entropy maximization problem. This approach yields an upper bound for the actual mutual information of the output signals - hence, the name minimax mutual information ICA algorithm. In addition, we demonstrate that for a specific selection of the constraint functions in the maximum entropy density estimation procedure, the algorithm relates strongly to ICA methods using higher-order cumulants.