136 resultados para Gradient Descent method
em Université de Lausanne, Switzerland
Resumo:
We present a novel filtering method for multispectral satellite image classification. The proposed method learns a set of spatial filters that maximize class separability of binary support vector machine (SVM) through a gradient descent approach. Regularization issues are discussed in detail and a Frobenius-norm regularization is proposed to efficiently exclude uninformative filters coefficients. Experiments carried out on multiclass one-against-all classification and target detection show the capabilities of the learned spatial filters.
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Abstract : This work is concerned with the development and application of novel unsupervised learning methods, having in mind two target applications: the analysis of forensic case data and the classification of remote sensing images. First, a method based on a symbolic optimization of the inter-sample distance measure is proposed to improve the flexibility of spectral clustering algorithms, and applied to the problem of forensic case data. This distance is optimized using a loss function related to the preservation of neighborhood structure between the input space and the space of principal components, and solutions are found using genetic programming. Results are compared to a variety of state-of--the-art clustering algorithms. Subsequently, a new large-scale clustering method based on a joint optimization of feature extraction and classification is proposed and applied to various databases, including two hyperspectral remote sensing images. The algorithm makes uses of a functional model (e.g., a neural network) for clustering which is trained by stochastic gradient descent. Results indicate that such a technique can easily scale to huge databases, can avoid the so-called out-of-sample problem, and can compete with or even outperform existing clustering algorithms on both artificial data and real remote sensing images. This is verified on small databases as well as very large problems. Résumé : Ce travail de recherche porte sur le développement et l'application de méthodes d'apprentissage dites non supervisées. Les applications visées par ces méthodes sont l'analyse de données forensiques et la classification d'images hyperspectrales en télédétection. Dans un premier temps, une méthodologie de classification non supervisée fondée sur l'optimisation symbolique d'une mesure de distance inter-échantillons est proposée. Cette mesure est obtenue en optimisant une fonction de coût reliée à la préservation de la structure de voisinage d'un point entre l'espace des variables initiales et l'espace des composantes principales. Cette méthode est appliquée à l'analyse de données forensiques et comparée à un éventail de méthodes déjà existantes. En second lieu, une méthode fondée sur une optimisation conjointe des tâches de sélection de variables et de classification est implémentée dans un réseau de neurones et appliquée à diverses bases de données, dont deux images hyperspectrales. Le réseau de neurones est entraîné à l'aide d'un algorithme de gradient stochastique, ce qui rend cette technique applicable à des images de très haute résolution. Les résultats de l'application de cette dernière montrent que l'utilisation d'une telle technique permet de classifier de très grandes bases de données sans difficulté et donne des résultats avantageusement comparables aux méthodes existantes.
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We present a new framework for large-scale data clustering. The main idea is to modify functional dimensionality reduction techniques to directly optimize over discrete labels using stochastic gradient descent. Compared to methods like spectral clustering our approach solves a single optimization problem, rather than an ad-hoc two-stage optimization approach, does not require a matrix inversion, can easily encode prior knowledge in the set of implementable functions, and does not have an ?out-of-sample? problem. Experimental results on both artificial and real-world datasets show the usefulness of our approach.
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Invasive mold infections are life-threatening diseases for which appropriate antifungal therapy is crucial. Their epidemiology is evolving, with the emergence of triazole-resistant Aspergillus spp. and multidrug-resistant non-Aspergillus molds. Despite the lack of interpretive criteria, antifungal susceptibility testing of molds may be useful in guiding antifungal therapy. The standard broth microdilution method (BMD) is demanding and requires expertise. We assessed the performance of a commercialized gradient diffusion method (Etest method) as an alternative to BMD. The MICs or minimal effective concentrations (MECs) of amphotericin B, voriconazole, posaconazole, caspofungin, and micafungin were assessed for 290 clinical isolates of the most representative pathogenic molds (154 Aspergillus and 136 non-Aspergillus isolates) with the BMD and Etest methods. Essential agreements (EAs) within ±2 dilutions of ≥90% between the two methods were considered acceptable. EAs for amphotericin B and voriconazole were >90% for most potentially susceptible species. For posaconazole, the correlation was acceptable for Mucoromycotina but Etest MIC values were consistently lower for Aspergillus spp. (EAs of <90%). Excellent EAs were found for echinocandins with highly susceptible (MECs of <0.015 μg/ml) or intrinsically resistant (MECs of >16 μg/ml) strains. However, MEC determinations lacked consistency between methods for strains exhibiting mid-range MECs for echinocandins. We concluded that the Etest method is an appropriate alternative to BMD for antifungal susceptibility testing of molds under specific circumstances, including testing with amphotericin B or triazoles for non-Aspergillus molds (Mucoromycotina and Fusarium spp.). Additional study of molecularly characterized triazole-resistant Aspergillus isolates is required to confirm the ability of the Etest method to detect voriconazole and posaconazole resistance among Aspergillus spp.
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Among the various determinants of treatment response, the achievement of sufficient blood levels is essential for curing malaria. For helping us at improving our current understanding of antimalarial drugs pharmacokinetics, efficacy and toxicity, we have developed a liquid chromatography-tandem mass spectrometry method (LC-MS/MS) requiring 200mul of plasma for the simultaneous determination of 14 antimalarial drugs and their metabolites which are the components of the current first-line combination treatments for malaria (artemether, artesunate, dihydroartemisinin, amodiaquine, N-desethyl-amodiaquine, lumefantrine, desbutyl-lumefantrine, piperaquine, pyronaridine, mefloquine, chloroquine, quinine, pyrimethamine and sulfadoxine). Plasma is purified by a combination of protein precipitation, evaporation and reconstitution in methanol/ammonium formate 20mM (pH 4.0) 1:1. Reverse-phase chromatographic separation of antimalarial drugs is obtained using a gradient elution of 20mM ammonium formate and acetonitrile both containing 0.5% formic acid, followed by rinsing and re-equilibration to the initial solvent composition up to 21min. Analyte quantification, using matrix-matched calibration samples, is performed by electro-spray ionization-triple quadrupole mass spectrometry by selected reaction monitoring detection in the positive mode. The method was validated according to FDA recommendations, including assessment of extraction yield, matrix effect variability, overall process efficiency, standard addition experiments as well as antimalarials short- and long-term stability in plasma. The reactivity of endoperoxide-containing antimalarials in the presence of hemolysis was tested both in vitro and on malaria patients samples. With this method, signal intensity of artemisinin decreased by about 20% in the presence of 0.2% hemolysed red-blood cells in plasma, whereas its derivatives were essentially not affected. The method is precise (inter-day CV%: 3.1-12.6%) and sensitive (lower limits of quantification 0.15-3.0 and 0.75-5ng/ml for basic/neutral antimalarials and artemisinin derivatives, respectively). This is the first broad-range LC-MS/MS assay covering the currently in-use antimalarials. It is an improvement over previous methods in terms of convenience (a single extraction procedure for 14 major antimalarials and metabolites reducing significantly the analytical time), sensitivity, selectivity and throughput. While its main limitation is investment costs for the equipment, plasma samples can be collected in the field and kept at 4 degrees C for up to 48h before storage at -80 degrees C. It is suited to detecting the presence of drug in subjects for screening purposes and quantifying drug exposure after treatment. It may contribute to filling the current knowledge gaps in the pharmacokinetics/pharmacodynamics relationships of antimalarials and better define the therapeutic dose ranges in different patient populations.
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MRI visualization of devices is traditionally based on signal loss due to T(2)* effects originating from local susceptibility differences. To visualize nitinol devices with positive contrast, a recently introduced postprocessing method is adapted to map the induced susceptibility gradients. This method operates on regular gradient-echo MR images and maps the shift in k-space in a (small) neighborhood of every voxel by Fourier analysis followed by a center-of-mass calculation. The quantitative map of the local shifts generates the positive contrast image of the devices, while areas without susceptibility gradients render a background with noise only. The positive signal response of this method depends only on the choice of the voxel neighborhood size. The properties of the method are explained and the visualizations of a nitinol wire and two stents are shown for illustration.
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BACKGROUND: The efficacy of angiotensin-converting enzyme (ACE) inhibitors in decreasing blood pressure in African patients is controversial. OBJECTIVE: We examined the ambulatory blood pressure (ABP) response to a diuretic and an ACE inhibitor in hypertensive patients of East African descent and evaluated the individual characteristics that determined treatment efficacy. DESIGN: A single-blind randomized AB/BA crossover design. SETTING: Hypertensive families of East African descent from the general population in the Seychelles. PARTICIPANTS: Fifty-two (29 men and 23 women) out of 62 eligible hypertensive patients were included.Main outcome measures ABP response to 20 mg lisinopril (LIS) daily and 25 mg hydrochlorothiazide (HCT) daily given for a 4-week period.Results The daytime systolic/diastolic ABP response to HCT was 4.9 [95% confidence interval (CI) 1.2-8.6]/3.6 (1.0-6.2) mmHg for men and 12.9 (9.2-16.6)/6.3 (3.7-8.8) mmHg for women. With LIS the response was 18.8 (15.0-22.5)/14.6 (12.0-17.1) mmHg for men and 12.4 (8.7-16.2)/7.7 (5.1-10.2) mmHg for women. The night-time systolic/diastolic response to HCT was 5.0 (0.6-9.4)/2.7 [(-0.4)-5.7] mmHg for men and 11.5 (7.1-16.0)/5.7 (2.6-8.8) mmHg for women, and to LIS was 18.7 (14.2-22.1)/15.4 (12.4-18.5) mmHg for men and 3.5 [(-1.0)-7.9]/2.3 [(-0.8)-5.4] mmHg for women. Linear regression analyses showed that gender is an independent predictor of the ABP responses to HCT and to LIS. CONCLUSIONS: Hypertensive patients of African descent responded better to LIS than to HCT. Men responded better to LIS than to HCT and women responded similarly to both drugs.
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Objectives. The goal of this study is to evaluate a T2-mapping sequence by: (i) measuring the reproducibility intra- and inter-observer variability in healthy volunteers in two separate scanning session with a T2 reference phantom; (2) measuring the mean T2 relaxation times by T2-mapping in infarcted myocardium in patients with subacute MI and compare it with patient's the gold standard X-ray coronary angiography and healthy volunteers results. Background. Myocardial edema is a consequence of an inflammation of the tissue, as seen in myocardial infarct (MI). It can be visualized by cardiovascular magnetic resonance (CMR) imaging using the T2 relaxation time. T2-mapping is a quantitative methodology that has the potential to address the limitation of the conventional T2-weighted (T2W) imaging. Methods. The T2-mapping protocol used for all MRI scans consisted in a radial gradient echo acquisition with a lung-liver navigator for free-breathing acquisition and affine image registration. Mid-basal short axis slices were acquired.T2-maps analyses: 2 observers semi- automatically segmented the left ventricle in 6 segments accordingly to the AHA standards. 8 healthy volunteers (age: 27 ± 4 years; 62.5% male) were scanned in 2 separate sessions. 17 patients (age : 61.9 ± 13.9 years; 82.4% male) with subacute STEMI (70.6%) and NSTEMI underwent a T2-mapping scanning session. Results. In healthy volunteers, the mean inter- and intra-observer variability over the entire short axis slice (segment 1 to 6) was 0.1 ms (95% confidence interval (CI): -0.4 to 0.5, p = 0.62) and 0.2 ms (95% CI: -2.8 to 3.2, p = 0.94, respectively. T2 relaxation time measurements with and without the correction of the phantom yielded an average difference of 3.0 ± 1.1 % and 3.1 ± 2.1 % (p = 0.828), respectively. In patients, the inter-observer variability in the entire short axis slice (S1-S6), was 0.3 ms (95% CI: -1.8 to 2.4, p = 0.85). Edema location as determined through the T2-mapping and the coronary artery occlusion as determined on X-ray coronary angiography correlated in 78.6%, but only in 60% in apical infarcts. All except one of the maximal T2 values in infarct patients were greater than the upper limit of the 95% confidence interval for normal myocardium. Conclusions. The T2-mapping methodology is accurate in detecting infarcted, i.e. edematous tissue in patients with subacute infarcts. This study further demonstrated that this T2-mapping technique is reproducible and robust enough to be used on a segmental basis for edema detection without the need of a phantom to yield a T2 correction factor. This new quantitative T2-mapping technique is promising and is likely to allow for serial follow-up studies in patients to improve our knowledge on infarct pathophysiology, on infarct healing, and for the assessment of novel treatment strategies for acute infarctions.
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We present the first approach to the genetic diversity and structure of the Balearic toad (Bufo balearicus Boettger, 1880) for the island of Menorca. Forty-one individ- uals from 21 localities were analyzed for ten microsatellite loci. We used geo-refer- enced individual multilocus genotypes and a model-based clustering method for the inference of the number of populations and of the spatial location of genetic dis- continuities between those populations.¦Only six of the microsatellites analyzed were polymorphic. We revealed a northwest- ern area inhabited by a single population with several well-connected localities and another set of populations in the southeast that includes a few unconnected small units with genetically significant differences among them as well as with the individ- uals from the northwest of the island. The observed fragmentation may be explained by shifts from agricultural to tourism practices that have been taking place on the island of Menorca since the 1960s. The abandonment of rural activities in favor of urbanization and concomitant service areas has mostly affected the southeast of the island and is currently threatening the overall geographic connectivity between the different farming areas of the island that are inhabited by the Balearic toad.
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Accurate modeling of flow instabilities requires computational tools able to deal with several interacting scales, from the scale at which fingers are triggered up to the scale at which their effects need to be described. The Multiscale Finite Volume (MsFV) method offers a framework to couple fine-and coarse-scale features by solving a set of localized problems which are used both to define a coarse-scale problem and to reconstruct the fine-scale details of the flow. The MsFV method can be seen as an upscaling-downscaling technique, which is computationally more efficient than standard discretization schemes and more accurate than traditional upscaling techniques. We show that, although the method has proven accurate in modeling density-driven flow under stable conditions, the accuracy of the MsFV method deteriorates in case of unstable flow and an iterative scheme is required to control the localization error. To avoid large computational overhead due to the iterative scheme, we suggest several adaptive strategies both for flow and transport. In particular, the concentration gradient is used to identify a front region where instabilities are triggered and an accurate (iteratively improved) solution is required. Outside the front region the problem is upscaled and both flow and transport are solved only at the coarse scale. This adaptive strategy leads to very accurate solutions at roughly the same computational cost as the non-iterative MsFV method. In many circumstances, however, an accurate description of flow instabilities requires a refinement of the computational grid rather than a coarsening. For these problems, we propose a modified iterative MsFV, which can be used as downscaling method (DMsFV). Compared to other grid refinement techniques the DMsFV clearly separates the computational domain into refined and non-refined regions, which can be treated separately and matched later. This gives great flexibility to employ different physical descriptions in different regions, where different equations could be solved, offering an excellent framework to construct hybrid methods.
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To study the stress-induced effects caused by wounding under a new perspective, a metabolomic strategy based on HPLC-MS has been devised for the model plant Arabidopsis thaliana. To detect induced metabolites and precisely localise these compounds among the numerous constitutive metabolites, HPLC-MS analyses were performed in a two-step strategy. In a first step, rapid direct TOF-MS measurements of the crude leaf extract were performed with a ballistic gradient on a short LC-column. The HPLC-MS data were investigated by multivariate analysis as total mass spectra (TMS). Principal components analysis (PCA) and hierarchical cluster analysis (HCA) on principal coordinates were combined for data treatment. PCA and HCA demonstrated a clear clustering of plant specimens selecting the highest discriminating ions given by the complete data analysis, leading to the specific detection of discrete-induced ions (m/z values). Furthermore, pool constitution with plants of homogeneous behaviour was achieved for confirmatory analysis. In this second step, long high-resolution LC profilings on an UPLC-TOF-MS system were used on pooled samples. This allowed to precisely localise the putative biological marker induced by wounding and by specific extraction of accurate m/z values detected in the screening procedure with the TMS spectra.
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Much of the analytical modeling of morphogen profiles is based on simplistic scenarios, where the source is abstracted to be point-like and fixed in time, and where only the steady state solution of the morphogen gradient in one dimension is considered. Here we develop a general formalism allowing to model diffusive gradient formation from an arbitrary source. This mathematical framework, based on the Green's function method, applies to various diffusion problems. In this paper, we illustrate our theory with the explicit example of the Bicoid gradient establishment in Drosophila embryos. The gradient formation arises by protein translation from a mRNA distribution followed by morphogen diffusion with linear degradation. We investigate quantitatively the influence of spatial extension and time evolution of the source on the morphogen profile. For different biologically meaningful cases, we obtain explicit analytical expressions for both the steady state and time-dependent 1D problems. We show that extended sources, whether of finite size or normally distributed, give rise to more realistic gradients compared to a single point-source at the origin. Furthermore, the steady state solutions are fully compatible with a decreasing exponential behavior of the profile. We also consider the case of a dynamic source (e.g. bicoid mRNA diffusion) for which a protein profile similar to the ones obtained from static sources can be achieved.
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Contemporary coronary magnetic resonance angiography techniques suffer from signal-to-noise ratio (SNR) constraints. We propose a method to enhance SNR in gradient echo coronary magnetic resonance angiography by using sensitivity encoding (SENSE). While the use of sensitivity encoding to improve SNR seems counterintuitive, it can be exploited by reducing the number of radiofrequency excitations during the acquisition window while lowering the signal readout bandwidth, therefore improving the radiofrequency receive to radiofrequency transmit duty cycle. Under certain conditions, this leads to improved SNR. The use of sensitivity encoding for improved SNR in three-dimensional coronary magnetic resonance angiography is investigated using numerical simulations and an in vitro and an in vivo study. A maximum 55% SNR enhancement for coronary magnetic resonance angiography was found both in vitro and in vivo, which is well consistent with the numerical simulations. This method is most suitable for spoiled gradient echo coronary magnetic resonance angiography in which a high temporal and spatial resolution is required.
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The aim of this retrospective study was to compare the clinical and radiographic results after TKA (PFC, DePuy), performed either by computer assisted navigation (CAS, Brainlab, Johnson&Johnson) or by conventional means. Material and methods: Between May and December 2006 we reviewed 36 conventional TKA performed between 2002 and 2003 (group A) and 37 navigated TKA performed between 2005 and 2006 (group B) by the same experienced surgeon. The mean age in group A was 74 years (range 62-90) and 73 (range 58-85) in group B with a similar age distribution. The preoperative mechanical axes in group A ranged from -13° varus to +13° valgus (mean absolute deviation 6.83°, SD 3.86), in group B from -13° to +16° (mean absolute deviation 5.35, SD 4.29). Patients with a previous tibial osteotomy or revision arthroplasty were excluded from the study. Examination was done by an experienced orthopedic resident independent of the surgeon. All patients had pre- and postoperative long standing radiographs. The IKSS and the WOMAC were utilized to determine the clinical outcome. Patient's degree of satisfaction was assessed on a visual analogous scale (VAS). Results: 32 of the 37 navigated TKAs (86,5%) showed a postoperative mechanical axis within the limits of 3 degrees of valgus or varus deviation compared to only 24 (66%) of the 36 standard TKAs. This difference was significant (p = 0.045). The mean absolute deviation from neutral axis was 3.00° (range -5° to +9°, SD: 1.75) in group A in comparison to 1.54° (range -5° to +4°, SD: 1.41) in group B with a highly significant difference (p = 0.000). Furthermore, both groups showed a significant postoperative improvement of their mean IKSS-values (group A: 89 preoperative to 169 postoperative, group B 88 to 176) without a significant difference between the two groups. Neither the WOMAC nor the patient's degree of satisfaction - as assessed by VAS - showed significant differences. Operation time was significantly higher in group B (mean 119.9 min.) than in group A (mean 99.6 min., p <0.000). Conclusion: Our study showed consistent significant improvement of postoperative frontal alignment in TKA by computer assisted navigation (CAS) compared to standard methods, even in the hands of a surgeon well experienced in standard TKA implantation. However, the follow-up time of this study was not long enough to judge differences in clinical outcome. Thus, the relevance of computer navigation for clinical outcome and survival of TKA remains to be proved in long term studies to justify the longer operation time. References 1 Stulberg SD. Clin Orth Rel Res. 2003;(416):177-84. 2 Chauhan SK. JBJS Br. 2004;86(3):372-7. 3 Bäthis H, et al. Orthopäde. 2006;35(10):1056-65.
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Drug abuse is a widespread problem affecting both teenagers and adults. Nitrous oxide is becoming increasingly popular as an inhalation drug, causing harmful neurological and hematological effects. Some gas chromatography-mass spectrometry (GC-MS) methods for nitrous oxide measurement have been previously described. The main drawbacks of these methods include a lack of sensitivity for forensic applications; including an inability to quantitatively determine the concentration of gas present. The following study provides a validated method using HS-GC-MS which incorporates hydrogen sulfide as a suitable internal standard allowing the quantification of nitrous oxide. Upon analysis, sample and internal standard have similar retention times and are eluted quickly from the molecular sieve 5Å PLOT capillary column and the Porabond Q column therefore providing rapid data collection whilst preserving well defined peaks. After validation, the method has been applied to a real case of N2O intoxication indicating concentrations in a mono-intoxication.