23 resultados para rank transform

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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Right ventricular (RV) systolic function is prognostically important, but its assessment by echocardiography remains challenging, in part because of the multitude of available measurement methods. The purpose of this prospective study was to rank these methods against the reference of RV ejection fraction (EF) as obtained in a broad clinical population by magnetic resonance imaging (MRI).

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A high resolution luminescence study of NaLaF4: 1%Pr3+, 5%Yb3+ and NaLaF4: 1%Ce3+, 5%Yb3+ in the UV to NIR spectral range using a InGaAs detector and a fourier transform interferometer is reported. Although the Pr3+(P-3(0) -> (1)G(4), Yb3+(F-2(7/2) -> F-2(5/2)) energy transfer step takes place, significant Pr3+ (1)G(4) emission around 993, 1330 and 1850 nm is observed. No experimental proof for the second energy transfer step in the down-conversion process between Pr3+ and Yb3+ can be given. In the case of NaLaF4: Ce3+, Yb3+ it is concluded that the observed Yb3+ emission upon Ce3+ 5d excitation is the result of a charge transfer process instead of down-conversion. (C) 2010 Elsevier B.V. All rights reserved.

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The Institute of Applied Physics observes middle atmospheric trace gases, such as ozone and water vapour, by microwave radiometry. We report on the comparison of measurements using a novel digital Fast Fourier Transform and accousto optical spectrometers. First tests made on ground are presented as well as first experience about the use of such spectrometers under aircraft conditions.

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OBJECTIVE: To determine if the receptor activator of nuclear factor-kappaB-receptor activator of nuclear factor-kappaB ligand-osteoprotegerin (RANK-RANKL-OPG) system is active in bone remodeling in dogs and, if so, whether differences in expression of these mediators occur in healthy and arthritic joints. STUDY DESIGN: Experimental study. SAMPLE POPULATION: Fragmented processus coronoidei (n=20) were surgically removed from dogs with elbow arthritis and 5 corresponding healthy samples from dogs euthanatized for reasons other than elbow joint disease. METHODS: Bright-field immunohistochemistry and high-resolution fluorescence microscopy were used to investigate the distribution of RANK, RANKL, and OPG in healthy and arthritic joints. RESULTS: All 3 molecules were identified by immunostaining of canine bone tissue. In elbow dysplasia, the number of RANK-positive osteoclasts was increased. In their vicinity, cells expressing RANKL, a mediator of osteoclast activation, were abundant whereas the number of osteoblasts having the potential to limit osteoclastogenesis and bone resorption via OPG was few. CONCLUSIONS: The RANK-RANKL-OPG system is active in bone remodeling in dogs. In elbow dysplasia, a surplus of molecules promoting osteoclastogenesis was evident and is indicative of an imbalance between the mediators regulating bone resorption and bone formation. Both OPG and neutralizing antibodies against RANKL have the potential to counterbalance bone resorption. CLINICAL RELEVANCE: Therapeutic use of neutralizing antibodies against RANKL to inhibit osteoclast activation warrants further investigation.

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In this article, the authors evaluate a merit function for 2D/3D registration called stochastic rank correlation (SRC). SRC is characterized by the fact that differences in image intensity do not influence the registration result; it therefore combines the numerical advantages of cross correlation (CC)-type merit functions with the flexibility of mutual-information-type merit functions. The basic idea is that registration is achieved on a random subset of the image, which allows for an efficient computation of Spearman's rank correlation coefficient. This measure is, by nature, invariant to monotonic intensity transforms in the images under comparison, which renders it an ideal solution for intramodal images acquired at different energy levels as encountered in intrafractional kV imaging in image-guided radiotherapy. Initial evaluation was undertaken using a 2D/3D registration reference image dataset of a cadaver spine. Even with no radiometric calibration, SRC shows a significant improvement in robustness and stability compared to CC. Pattern intensity, another merit function that was evaluated for comparison, gave rather poor results due to its limited convergence range. The time required for SRC with 5% image content compares well to the other merit functions; increasing the image content does not significantly influence the algorithm accuracy. The authors conclude that SRC is a promising measure for 2D/3D registration in IGRT and image-guided therapy in general.

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Objectives The aim of this study was to measure the degree of conversion (DC) of five dual-curing resin cements after different curing modes with a second- and a third-generation light-emitting diode (LED) curing unit. Additionally, irradiance of both light curing units was measured at increasing distances and through discs of two glass ceramics for computer-aided design/manufacturing (CAD/CAM). Materials and methods Irradiance and spectra of the Elipar FreeLight 2 (Standard Mode (SM)) and of the VALO light curing unit (High Power Mode (HPM) and Xtra Power Mode (XPM)) were measured with a MARC radiometer. Irradiance was measured at increasing distances (control) and through discs (1.5 to 6 mm thickness) of IPS Empress CAD and IPS e.max CAD. DC of Panavia F2.0, RelyX Unicem 2 Automix, SpeedCEM, BisCem, and BeautiCem SA was measured with an attenuated total reflectance–Fourier transform infrared spectrometer when self-cured (negative control) or light cured in SM for 40 s, HPM for 32 s, or XPM for 18 s. Light curing was performed directly (positive control) or through discs of either 1.5- or 3-mm thickness of IPS Empress CAD or IPS e.max CAD. DC was analysed with Kruskal–Wallis tests followed by pairwise Wilcoxon rank sum tests (α = 0.05). Results Maximum irradiances were 1,545 mW/cm2 (SM), 2,179 mW/cm2 (HPM), and 4,156 mW/cm2 (XPM), and all irradiances decreased by >80 % through discs of 1.5 mm, ≥95 % through 3 mm, and up to >99 % through 6 mm. Generally, self-curing resulted in the lowest DC. For some cements, direct light curing did not result in higher DC compared to when light cured through ceramic discs. For other cements, light curing through ceramic discs of 3 mm generally reduced DC. Conclusions Light curing was favourable for dual-curing cements. Some cements were more susceptible to variations in curing mode than others. Clinical relevance When light curing a given cement, the higher irradiances of the third-generation LED curing unit resulted in similar DC compared to the second-generation one, though at shorter light curing times.

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ABSTRACT: Fourier transform infrared spectroscopy (FTIRS) can provide detailed information on organic and minerogenic constituents of sediment records. Based on a large number of sediment samples of varying age (0�340 000 yrs) and from very diverse lake settings in Antarctica, Argentina, Canada, Macedonia/Albania, Siberia, and Sweden, we have developed universally applicable calibration models for the quantitative determination of biogenic silica (BSi; n = 816), total inorganic carbon (TIC; n = 879), and total organic carbon (TOC; n = 3164) using FTIRS. These models are based on the differential absorbance of infrared radiation at specific wavelengths with varying concentrations of individual parameters, due to molecular vibrations associated with each parameter. The calibration models have low prediction errors and the predicted values are highly correlated with conventionally measured values (R = 0.94�0.99). Robustness tests indicate the accuracy of the newly developed FTIRS calibration models is similar to that of conventional geochemical analyses. Consequently FTIRS offers a useful and rapid alternative to conventional analyses for the quantitative determination of BSi, TIC, and TOC. The rapidity, cost-effectiveness, and small sample size required enables FTIRS determination of geochemical properties to be undertaken at higher resolutions than would otherwise be possible with the same resource allocation, thus providing crucial sedimentological information for climatic and environmental reconstructions.

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Abstract We demonstrate the use of Fourier transform infrared spectroscopy (FTIRS) to make quantitative measures of total organic carbon (TOC), total inorganic carbon (TIC) and biogenic silica (BSi) concentrations in sediment. FTIRS is a fast and costeffective technique and only small sediment samples are needed (0.01 g). Statistically significant models were developed using sediment samples from northern Sweden and were applied to sediment records from Sweden, northeast Siberia and Macedonia. The correlation between FTIRS-inferred values and amounts of biogeochemical constituents assessed conventionally varied between r = 0.84–0.99 for TOC, r = 0.85– 0.99 for TIC, and r = 0.68–0.94 for BSi. Because FTIR spectra contain information on a large number of both inorganic and organic components, there is great potential for FTIRS to become an important tool in paleolimnology.

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We consider the problem of fitting a union of subspaces to a collection of data points drawn from one or more subspaces and corrupted by noise and/or gross errors. We pose this problem as a non-convex optimization problem, where the goal is to decompose the corrupted data matrix as the sum of a clean and self-expressive dictionary plus a matrix of noise and/or gross errors. By self-expressive we mean a dictionary whose atoms can be expressed as linear combinations of themselves with low-rank coefficients. In the case of noisy data, our key contribution is to show that this non-convex matrix decomposition problem can be solved in closed form from the SVD of the noisy data matrix. The solution involves a novel polynomial thresholding operator on the singular values of the data matrix, which requires minimal shrinkage. For one subspace, a particular case of our framework leads to classical PCA, which requires no shrinkage. For multiple subspaces, the low-rank coefficients obtained by our framework can be used to construct a data affinity matrix from which the clustering of the data according to the subspaces can be obtained by spectral clustering. In the case of data corrupted by gross errors, we solve the problem using an alternating minimization approach, which combines our polynomial thresholding operator with the more traditional shrinkage-thresholding operator. Experiments on motion segmentation and face clustering show that our framework performs on par with state-of-the-art techniques at a reduced computational cost.