991 resultados para Cryptography, Discrete Logarithm, Extension Fields, Karatsuba Multiplication, Normal Basis


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The double spin-echo point resolved spectroscopy sequence (PRESS) is a widely used method and standard in clinical MR spectroscopy. Existence of important J-modulations at constant echo times, depending on the temporal delays between the rf-pulses, have been demonstrated recently for strongly coupled spin systems and were exploited for difference editing, removing singlets from the spectrum (strong-coupling PRESS, S-PRESS). A drawback of this method for in vivo applications is that large signal modulations needed for difference editing occur only at relatively long echo times. In this work we demonstrate that, by simply adding a third refocusing pulse (3S-PRESS), difference editing becomes possible at substantially shorter echo times while, as applied to citrate, more favorable lineshapes can be obtained. For the example of an AB system an analytical description of the MR signal, obtained with this triple refocusing sequence (3S-PRESS), is provided.

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Purpose: To date, the genotype/phenotype correlation of p.G56R-linked autosomal dominant retinitis pigmentosa (ADRP) is limited to less than 10 kindred. The purpose of this study is to report an unusual appearance of fundus autofluorescence (AF) with NR2E3 p.G56R-linked ADRP in a single kindred.Methods: Patients were enrolled among three generations in a previously unreported family. Molecular diagnosis was performed on all exons of NR2E3 and a p.G56R mutation was identified in affected family members only. Examinations included fundus photography, visual fields, optical coherence tomography, AF, near-infrared AF and ISCEV-standard electrophysiology (ERG).Results: Among 10 examined family members, 5 were affected. The youngest and oldest patients were 16 and 65 years old, respectively. Fundus examination revealed a range of retinal disorder from normal to optic nerve pallor, attenuated arterial caliber and bone spicule-like pigment deposits. In all patients, AF showed a double hyperfluorescent ring; an inner paramacular ring which extension was comparable among patients and an outer ring along the vascular arcades which extended towards periphery in older patients and became hypofluorescent. Maximal scotopic ERGs when recordable showed an increased a/b wave ratio.Conclusions: A double hyperfluorescent ring on AF is an uncommon observation and might be a specific clinical finding in NR2E3 p.G56R-linked ADRP. The consistency of that finding in all affected members of our 3-generation family confirms a previous study. Further analysis is required to determine whether AF changes are associated with particular retinal layer abnormalities.

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This paper presents multiple kernel learning (MKL) regression as an exploratory spatial data analysis and modelling tool. The MKL approach is introduced as an extension of support vector regression, where MKL uses dedicated kernels to divide a given task into sub-problems and to treat them separately in an effective way. It provides better interpretability to non-linear robust kernel regression at the cost of a more complex numerical optimization. In particular, we investigate the use of MKL as a tool that allows us to avoid using ad-hoc topographic indices as covariables in statistical models in complex terrains. Instead, MKL learns these relationships from the data in a non-parametric fashion. A study on data simulated from real terrain features confirms the ability of MKL to enhance the interpretability of data-driven models and to aid feature selection without degrading predictive performances. Here we examine the stability of the MKL algorithm with respect to the number of training data samples and to the presence of noise. The results of a real case study are also presented, where MKL is able to exploit a large set of terrain features computed at multiple spatial scales, when predicting mean wind speed in an Alpine region.

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Here we report the discovery of and phenotypic characterization of a retinal disorder of unknown origin in adults using clinical, electrophysiological and psychophysical techniques, and to seek the presence of circulating retinal autoantibodies in the sera of these patients. Sixteen patients were identified with progressive bilateral visual loss over a period of months. Ten of the patients were male, and the average age was 55.3 years (range from 43 to 76 years). Known causes such as carcinoma-associated retinopathy, acute zonal occult outer retinopathy and hereditary cone dystrophy appeared unlikely. Investigations included electrophysiology, fundus autofluorescence imaging and psychophysical tests. The sera of these patients were analyzed with indirect immunocytochemistry and Western immunoblot analysis on murine (BALB/c) retinal tissue for the presence of retinal autoantibodies. Bilateral visual loss and photophobia progressed over a period of months to years (average 28.7 months, range 3-67) and subsequently stabilized. No abnormality was observed by biomicroscopy, angiography or autofluorescence imaging. Electrophysiology indicated predominant cone-system dysfunction, either macular or generalized, and post-phototransduction involvement in 9 patients (56%). Photopic and scotopic visual fields and dark adaptation kinetics showed both cone and rod system involvement in all cases. Heterogeneous immunohistochemical staining patterns were seen with the sera of these patients as compared with controls. A majority of the affected patients (9/15) stained with an antinuclear pattern. The retinal autoantibodies from the sera of most patients reacted with the retinal proteins of molecular weight between 34 and 40 kDa. The aetiology of this distinctive retinal disorder therefore appears to be mediated through an autoimmune mechanism.

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In this paper, we present an efficient numerical scheme for the recently introduced geodesic active fields (GAF) framework for geometric image registration. This framework considers the registration task as a weighted minimal surface problem. Hence, the data-term and the regularization-term are combined through multiplication in a single, parametrization invariant and geometric cost functional. The multiplicative coupling provides an intrinsic, spatially varying and data-dependent tuning of the regularization strength, and the parametrization invariance allows working with images of nonflat geometry, generally defined on any smoothly parametrizable manifold. The resulting energy-minimizing flow, however, has poor numerical properties. Here, we provide an efficient numerical scheme that uses a splitting approach; data and regularity terms are optimized over two distinct deformation fields that are constrained to be equal via an augmented Lagrangian approach. Our approach is more flexible than standard Gaussian regularization, since one can interpolate freely between isotropic Gaussian and anisotropic TV-like smoothing. In this paper, we compare the geodesic active fields method with the popular Demons method and three more recent state-of-the-art algorithms: NL-optical flow, MRF image registration, and landmark-enhanced large displacement optical flow. Thus, we can show the advantages of the proposed FastGAF method. It compares favorably against Demons, both in terms of registration speed and quality. Over the range of example applications, it also consistently produces results not far from more dedicated state-of-the-art methods, illustrating the flexibility of the proposed framework.

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The present study discusses retention criteria for principal components analysis (PCA) applied to Likert scale items typical in psychological questionnaires. The main aim is to recommend applied researchers to restrain from relying only on the eigenvalue-than-one criterion; alternative procedures are suggested for adjusting for sampling error. An additional objective is to add evidence on the consequences of applying this rule when PCA is used with discrete variables. The experimental conditions were studied by means of Monte Carlo sampling including several sample sizes, different number of variables and answer alternatives, and four non-normal distributions. The results suggest that even when all the items and thus the underlying dimensions are independent, eigenvalues greater than one are frequent and they can explain up to 80% of the variance in data, meeting the empirical criterion. The consequences of using Kaiser"s rule are illustrated with a clinical psychology example. The size of the eigenvalues resulted to be a function of the sample size and the number of variables, which is also the case for parallel analysis as previous research shows. To enhance the application of alternative criteria, an R package was developed for deciding the number of principal components to retain by means of confidence intervals constructed about the eigenvalues corresponding to lack of relationship between discrete variables.

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Due to the advances in sensor networks and remote sensing technologies, the acquisition and storage rates of meteorological and climatological data increases every day and ask for novel and efficient processing algorithms. A fundamental problem of data analysis and modeling is the spatial prediction of meteorological variables in complex orography, which serves among others to extended climatological analyses, for the assimilation of data into numerical weather prediction models, for preparing inputs to hydrological models and for real time monitoring and short-term forecasting of weather.In this thesis, a new framework for spatial estimation is proposed by taking advantage of a class of algorithms emerging from the statistical learning theory. Nonparametric kernel-based methods for nonlinear data classification, regression and target detection, known as support vector machines (SVM), are adapted for mapping of meteorological variables in complex orography.With the advent of high resolution digital elevation models, the field of spatial prediction met new horizons. In fact, by exploiting image processing tools along with physical heuristics, an incredible number of terrain features which account for the topographic conditions at multiple spatial scales can be extracted. Such features are highly relevant for the mapping of meteorological variables because they control a considerable part of the spatial variability of meteorological fields in the complex Alpine orography. For instance, patterns of orographic rainfall, wind speed and cold air pools are known to be correlated with particular terrain forms, e.g. convex/concave surfaces and upwind sides of mountain slopes.Kernel-based methods are employed to learn the nonlinear statistical dependence which links the multidimensional space of geographical and topographic explanatory variables to the variable of interest, that is the wind speed as measured at the weather stations or the occurrence of orographic rainfall patterns as extracted from sequences of radar images. Compared to low dimensional models integrating only the geographical coordinates, the proposed framework opens a way to regionalize meteorological variables which are multidimensional in nature and rarely show spatial auto-correlation in the original space making the use of classical geostatistics tangled.The challenges which are explored during the thesis are manifolds. First, the complexity of models is optimized to impose appropriate smoothness properties and reduce the impact of noisy measurements. Secondly, a multiple kernel extension of SVM is considered to select the multiscale features which explain most of the spatial variability of wind speed. Then, SVM target detection methods are implemented to describe the orographic conditions which cause persistent and stationary rainfall patterns. Finally, the optimal splitting of the data is studied to estimate realistic performances and confidence intervals characterizing the uncertainty of predictions.The resulting maps of average wind speeds find applications within renewable resources assessment and opens a route to decrease the temporal scale of analysis to meet hydrological requirements. Furthermore, the maps depicting the susceptibility to orographic rainfall enhancement can be used to improve current radar-based quantitative precipitation estimation and forecasting systems and to generate stochastic ensembles of precipitation fields conditioned upon the orography.

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BACKGROUND: Optic perineuritis is an uncommon variety of orbital inflammatory disease that is distinct from demyelinating optic neuritis. OBJECTIVE: To describe the clinical and radiographic features of idiopathic optic perineuritis, with particular emphasis on those features that help to distinguish this condition from optic neuritis. METHODS: We reviewed the medical records of 14 patients with optic perineuritis who were seen in 2 neuro-ophthalmology clinics. RESULTS: Patients ranged in age from 24 to 60 years; 5 were older than 50 years. All patients had visual loss, eye pain, or both. The visual acuity was 20/20 or better in 8 of the 15 eyes. The results of visual field testing were normal in 2 eyes, and a paracentral scotoma or an arcuate defect was seen in 7. Magnetic resonance imaging scans demonstrated circumferential enhancement around the optic nerve, sometimes with intraorbital extension. Response to corticosteroids was dramatic; however, 4 patients had a relapse with lowering of the dose. CONCLUSIONS: In contrast to those with optic neuritis, patients with optic perineuritis are often older at onset and are more likely to show sparing of central vision. Magnetic resonance imaging scans demonstrate enhancement around, rather than within, the optic nerve. Response to corticosteroids is more dramatic than in patients with optic neuritis, and patients are more likely to experience recurrence after stopping treatment.

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The silicon photomultiplier (SiPM) is a novel detector technology that has undergone a fast development in the last few years, owing to its single-photon resolution and ultra-fast response time. However, the typical high dark count rates of the sensor may prevent the detection of low intensity radiation fluxes. In this article, the time-gated operation with short active periods in the nanosecond range is proposed as a solution to reduce the number of cells fired due to noise and thus increase the dynamic range. The technique is aimed at application fields that function under a trigger command, such as gated fluorescence lifetime imaging microscopy.

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The silicon photomultiplier (SiPM) is a novel detector technology that has undergone a fast development in the last few years, owing to its single-photon resolution and ultra-fast response time. However, the typical high dark count rates of the sensor may prevent the detection of low intensity radiation fluxes. In this article, the time-gated operation with short active periods in the nanosecond range is proposed as a solution to reduce the number of cells fired due to noise and thus increase the dynamic range. The technique is aimed at application fields that function under a trigger command, such as gated fluorescence lifetime imaging microscopy.

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The analysis of paraxial Gaussian beams features in most undergraduate courses in laser physics, advanced optics and photonics. These beams provide a simple model of the field generated in the resonant cavities of lasers, thus constituting a basic element for understanding laser theory. Usually, uniformly polarized beams are considered in the analytical calculations, with the electric field vibrating at normal planes to the propagation direction. However, such paraxial fields do not verify the Maxwell equations. In this paper we discuss how to overcome this apparent contradiction and evaluate the longitudinal component that any paraxial Gaussian beam should exhibit. Despite the fact that the assumption of a purely transverse paraxial field is useful and accurate, the inclusion of the above issue in the program helps students to clarify the importance of the electromagnetic nature of light, thus providing a more complete understanding of the paraxial approach.

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The basic goal of this study is to extend old and propose new ways to generate knapsack sets suitable for use in public key cryptography. The knapsack problem and its cryptographic use are reviewed in the introductory chapter. Terminology is based on common cryptographic vocabulary. For example, solving the knapsack problem (which is here a subset sum problem) is termed decipherment. Chapter 1 also reviews the most famous knapsack cryptosystem, the Merkle Hellman system. It is based on a superincreasing knapsack and uses modular multiplication as a trapdoor transformation. The insecurity caused by these two properties exemplifies the two general categories of attacks against knapsack systems. These categories provide the motivation for Chapters 2 and 4. Chapter 2 discusses the density of a knapsack and the dangers of having a low density. Chapter 3 interrupts for a while the more abstract treatment by showing examples of small injective knapsacks and extrapolating conjectures on some characteristics of knapsacks of larger size, especially their density and number. The most common trapdoor technique, modular multiplication, is likely to cause insecurity, but as argued in Chapter 4, it is difficult to find any other simple trapdoor techniques. This discussion also provides a basis for the introduction of various categories of non injectivity in Chapter 5. Besides general ideas of non injectivity of knapsack systems, Chapter 5 introduces and evaluates several ways to construct such systems, most notably the "exceptional blocks" in superincreasing knapsacks and the usage of "too small" a modulus in the modular multiplication as a trapdoor technique. The author believes that non injectivity is the most promising direction for development of knapsack cryptosystema. Chapter 6 modifies two well known knapsack schemes, the Merkle Hellman multiplicative trapdoor knapsack and the Graham Shamir knapsack. The main interest is in aspects other than non injectivity, although that is also exploited. In the end of the chapter, constructions proposed by Desmedt et. al. are presented to serve as a comparison for the developments of the subsequent three chapters. Chapter 7 provides a general framework for the iterative construction of injective knapsacks from smaller knapsacks, together with a simple example, the "three elements" system. In Chapters 8 and 9 the general framework is put into practice in two different ways. Modularly injective small knapsacks are used in Chapter 9 to construct a large knapsack, which is called the congruential knapsack. The addends of a subset sum can be found by decrementing the sum iteratively by using each of the small knapsacks and their moduli in turn. The construction is also generalized to the non injective case, which can lead to especially good results in the density, without complicating the deciphering process too much. Chapter 9 presents three related ways to realize the general framework of Chapter 7. The main idea is to join iteratively small knapsacks, each element of which would satisfy the superincreasing condition. As a whole, none of these systems need become superincreasing, though the development of density is not better than that. The new knapsack systems are injective but they can be deciphered with the same searching method as the non injective knapsacks with the "exceptional blocks" in Chapter 5. The final Chapter 10 first reviews the Chor Rivest knapsack system, which has withstood all cryptanalytic attacks. A couple of modifications to the use of this system are presented in order to further increase the security or make the construction easier. The latter goal is attempted by reducing the size of the Chor Rivest knapsack embedded in the modified system. '

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We present an analytical procedure to perform the local noise analysis of a semiconductor junction when both the drift and diffusive parts of the current are important. The method takes into account space-inhomogeneous and hot-carriers conditions in the framework of the drift-diffusion model, and it can be effectively applied to the local noise analysis of different devices: n+nn+ diodes, Schottky barrier diodes, field-effect transistors, etc., operating under strongly inhomogeneous distributions of the electric field and charge concentration

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We present an analytical procedure to perform the local noise analysis of a semiconductor junction when both the drift and diffusive parts of the current are important. The method takes into account space-inhomogeneous and hot-carriers conditions in the framework of the drift-diffusion model, and it can be effectively applied to the local noise analysis of different devices: n+nn+ diodes, Schottky barrier diodes, field-effect transistors, etc., operating under strongly inhomogeneous distributions of the electric field and charge concentration

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The objective of this work was to establish an efficient protocol for in vitro multiplication and rooting, as well as ex vitroacclimatization of Aegiphila verticillata, a woody species found in Brazilian rocky fields. Aseptic cultures were established by seeds and two multiplication analyses were performed. In the first, we employed 6-benzylaminopurine (BAP – 0, 2.5, 5 and 7.5 μM) + α-naphthalene acetic acid (NAA – 0, 0.2, 0.4 and 0.6 μM) and, in the second, were studied adenine sulfate, kinetin and thidiazuron (0, 5, 7.5, 10 and 12.5 μM). After 90 days, we assessed the quantitative and qualitative shoot propagation. There were more than 90% seed germination and low contamination (2%). In multiplication phase, the culture medium that promoted the best quantitative and qualitative culture development was supplemented with 7.5 μM BAP + 0.4 μM NAA. In the rooting assay, were used NAA, indole-3-acetic acid (IAA) and indole-3-butyric acid (IBA) (0, 0.1, 0.2, 0.3 or 0.4 μM). After 90 days, the root number and rooting quality were evaluated. In this analysis, differences were not found between the control and the other treatments. Rooted plantlets were acclimatized in styrofoam trays for 30 days, after which they were transferred to pots in the greenhouse. Only 3% of the plants subjected to initial acclimatization died and 70% of the plants transferred to the field conditions survived and showed normal development. The results founded in this work are the first involving in vitro propagation and ex vitroacclimatization of Aegiphila verticillata and provide a continuous supply of this medicinal native species, endangered due anthropogenic activities.