926 resultados para Shiryaev rule


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Drosophila pair-rule genes are expressed in striped patterns with a precise order of overlap between stripes of different genes. We investigated the role of Giant (Gt) in the regulation of even-skipped, hairy, runt, and fushi tarazu stripes formed in the vicinity of Gt expression domains. In gt null embryos, specific stripes of eve, h, run, and ftz are disrupted. With an ectopic expression system, we verified that stripes affected in the mutant are also repressed. Simultaneously hybridizing gt misxpressing embryos with two pair-rule gene probes, we were able to distinguish differences in the repression of pairs of stripes that overlap extensively. Together, our results showed Gt repression roles in the regulation of two groups of partially overlapping stripes and that Gt morphogen activity is part of the mechanism responsible for the differential positioning of these stripes borders. We discuss the possibility that other factors regulate Gt stripe targets as well. Developmental Dynamics 239:2989-2999, 2010. (C) 2010 Wiley-Liss, Inc.

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The first problem of the Seleucid mathematical cuneiform tablet BM 34 568 calculates the diagonal of a rectangle from its sides without resorting to the Pythagorean rule. For this reason, it has been a source of discussion among specialists ever since its first publication. but so far no consensus in relation to its mathematical meaning has been attained. This paper presents two new interpretations of the scribe`s procedure. based on the assumption that he was able to reduce the problem to a standard Mesopotamian question about reciprocal numbers. These new interpretations are then linked to interpretations of the Old Babylonian tablet Plimpton 322 and to the presence of Pythagorean triples in the contexts of Old Babylonian and Hellenistic mathematics. (C) 2007 Elsevier Inc. All rights reserved.

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This paper describes the modeling of a weed infestation risk inference system that implements a collaborative inference scheme based on rules extracted from two Bayesian network classifiers. The first Bayesian classifier infers a categorical variable value for the weed-crop competitiveness using as input categorical variables for the total density of weeds and corresponding proportions of narrow and broad-leaved weeds. The inferred categorical variable values for the weed-crop competitiveness along with three other categorical variables extracted from estimated maps for the weed seed production and weed coverage are then used as input for a second Bayesian network classifier to infer categorical variables values for the risk of infestation. Weed biomass and yield loss data samples are used to learn the probability relationship among the nodes of the first and second Bayesian classifiers in a supervised fashion, respectively. For comparison purposes, two types of Bayesian network structures are considered, namely an expert-based Bayesian classifier and a naive Bayes classifier. The inference system focused on the knowledge interpretation by translating a Bayesian classifier into a set of classification rules. The results obtained for the risk inference in a corn-crop field are presented and discussed. (C) 2009 Elsevier Ltd. All rights reserved.

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The interlayer magnetoresistance of the quasi-two-dimensional metal alpha-(BEDT-TTF)(2)KHg(SCN)(4) is considered. In the temperature range from 0.5 to 10 K and for fields up to 10 T the magnetoresistance has a stronger temperature dependence than the zero-field resistance. Consequently Kohler's rule is not obeyed for any range of temperatures or fields. This means that the magnetoresistance cannot be described in terms of semiclassical transport on a single Fermi surface with a single scattering time. Possible explanations for the violations of Kohler's rule are considered, both within the framework of semiclassical transport theory and involving incoherent interlayer transport. The issues considered are similar to those raised by the magnetotransport of the cuprate superconductors. [S0163-1829(98)13219-8].

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Subcycling algorithms which employ multiple timesteps have been previously proposed for explicit direct integration of first- and second-order systems of equations arising in finite element analysis, as well as for integration using explicit/implicit partitions of a model. The author has recently extended this work to implicit/implicit multi-timestep partitions of both first- and second-order systems. In this paper, improved algorithms for multi-timestep implicit integration are introduced, that overcome some weaknesses of those proposed previously. In particular, in the second-order case, improved stability is obtained. Some of the energy conservation properties of the Newmark family of algorithms are shown to be preserved in the new multi-timestep extensions of the Newmark method. In the first-order case, the generalized trapezoidal rule is extended to multiple timesteps, in a simple way that permits an implicit/implicit partition. Explicit special cases of the present algorithms exist. These are compared to algorithms proposed previously. (C) 1998 John Wiley & Sons, Ltd.

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In this work, we take advantage of association rule mining to support two types of medical systems: the Content-based Image Retrieval (CBIR) systems and the Computer-Aided Diagnosis (CAD) systems. For content-based retrieval, association rules are employed to reduce the dimensionality of the feature vectors that represent the images and to improve the precision of the similarity queries. We refer to the association rule-based method to improve CBIR systems proposed here as Feature selection through Association Rules (FAR). To improve CAD systems, we propose the Image Diagnosis Enhancement through Association rules (IDEA) method. Association rules are employed to suggest a second opinion to the radiologist or a preliminary diagnosis of a new image. A second opinion automatically obtained can either accelerate the process of diagnosing or to strengthen a hypothesis, increasing the probability of a prescribed treatment be successful. Two new algorithms are proposed to support the IDEA method: to pre-process low-level features and to propose a preliminary diagnosis based on association rules. We performed several experiments to validate the proposed methods. The results indicate that association rules can be successfully applied to improve CBIR and CAD systems, empowering the arsenal of techniques to support medical image analysis in medical systems. (C) 2009 Elsevier B.V. All rights reserved.

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In this paper, we propose a method based on association rule-mining to enhance the diagnosis of medical images (mammograms). It combines low-level features automatically extracted from images and high-level knowledge from specialists to search for patterns. Our method analyzes medical images and automatically generates suggestions of diagnoses employing mining of association rules. The suggestions of diagnosis are used to accelerate the image analysis performed by specialists as well as to provide them an alternative to work on. The proposed method uses two new algorithms, PreSAGe and HiCARe. The PreSAGe algorithm combines, in a single step, feature selection and discretization, and reduces the mining complexity. Experiments performed on PreSAGe show that this algorithm is highly suitable to perform feature selection and discretization in medical images. HiCARe is a new associative classifier. The HiCARe algorithm has an important property that makes it unique: it assigns multiple keywords per image to suggest a diagnosis with high values of accuracy. Our method was applied to real datasets, and the results show high sensitivity (up to 95%) and accuracy (up to 92%), allowing us to claim that the use of association rules is a powerful means to assist in the diagnosing task.

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Reaching out to grasp an object (prehension) is a deceptively elegant and skilled behavior. The movement prior to object contact can be described as having two components [1], the movement of the hand to an appropriate location for gripping the object, the transport component, and the opening and closing of the aperture between the fingers as they prepare to grip the target, the grasp component. The grasp component is sensitive to the size of the object, so that a larger grasp aperture is formed for wider objects [1]; the maximum grasp aperture (MGA) is a little wider than the width of the target object and occurs later in the movement for larger objects [1, 2]. We present a simple model that can account for the temporal relationship between the transport and grasp components, We report the results of an experiment providing empirical support for our rule of thumb. The model provides a simple, but plausible, account of a neural control strategy that has been the center of debate over the last two decades.

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The relation between patient and physician in most modern Health Care Sys- tems is sparse, limited in time and very in exible. On the other hand, and in contradiction with several recent studies, most physicians do not rely their patient diagnostics evaluations on intertwined psychological and social nature factors. Facing these problems and trying to improve the patient/physician relation we present a mobile health care solution to im- prove the interaction between the physician and his patients. The solution serves not only as a privileged mean of communication between physicians and patients but also as an evolutionary intelligent platform delivering a mobile rule based system.

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Purpose - This study aims to investigate the influence of tube potential (kVp) variation in relation to perceptual image quality and effective dose (E) for pelvis using automatic exposure control (AEC) and non-AEC in a Computed Radiography (CR) system. Methods and materials - To determine the effects of using AEC and non-AEC by applying the 10 kVp rule in two experiments using an anthropomorphic pelvis phantom. Images were acquired using 10 kVp increments (60–120 kVp) for both experiments. The first experiment, based on seven AEC combinations, produced 49 images. The mean mAs from each kVp increment were used as a baseline for the second experiment producing 35 images. A total of 84 images were produced and a panel of 5 experienced observers participated for the image scoring using the two alternative forced choice (2AFC) visual grading software. PCXMC software was used to estimate E. Results - A decrease in perceptual image quality as the kVp increases was observed both in non-AEC and AEC experiments, however no significant statistical differences (p > 0.05) were found. Image quality scores from all observers at 10 kVp increments for all mAs values using non-AEC mode demonstrates a better score up to 90 kVp. E results show a statistically significant decrease (p = 0.000) on the 75th quartile from 0.37 mSv at 60 kVp to 0.13 mSv at 120 kVp when applying the 10 kVp rule in non-AEC mode. Conclusion - Using the 10 kVp rule, no significant reduction in perceptual image quality is observed when increasing kVp whilst a marked and significant E reduction is observed.

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Purpose - To compare the image quality and effective dose applying the 10 kVp rule with manual mode acquisition and AEC mode in PA chest X-ray. Method - 68 images (with and without lesions) were acquired using an anthropomorphic chest phantom using a Wolverson Arcoma X-ray unit. These images were compared against a reference image using the 2 alternative forced choice (2AFC) method. The effective dose (E) was calculated using PCXMC software using the exposure parameters and the DAP. The exposure index (lgM provided by Agfa systems) was recorded. Results - Exposure time decreases more when applying the 10 kVp rule with manual mode (50%–28%) when compared with automatic mode (36%–23%). Statistical differences for E between several ionization chambers' combinations for AEC mode were found (p = 0.002). E is lower when using only the right AEC ionization chamber. Considering the image quality there are no statistical differences (p = 0.348) between the different ionization chambers' combinations for AEC mode for images with no lesions. Considering lgM values, it was demonstrated that they were higher when the AEC mode was used compared to the manual mode. It was also observed that lgM values obtained with AEC mode increased as kVp value went up. The image quality scores did not demonstrate statistical significant differences (p = 0.343) for the images with lesions comparing manual with AEC mode. Conclusion - In general the E is lower when manual mode is used. By using the right AEC ionising chamber under the lung the E will be the lowest in comparison to other ionising chambers. The use of the 10 kVp rule did not affect the visibility of the lesions or image quality.

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Background - Pelvis and hip radiography are consistently found to be amongst the highest contributors to the collective effective dose (E) in all ten DOSE DATAMED countries in Europe, representing 2.8 to 9.4% of total collective dose (S) in the TOP 20 exams list. The level of image quality should provide all the diagnostic information in order not to jeopardise the diagnosis, but being able to provide the needed clinical information with the minimum dose. A recent study suggests further research to determine whether the “10 kVp rule” would have value for a range of examinations using Computed Radiography (CR) systems. As a “rule of thumb” increasing the kVp by 10 whilst halving the mAs is suggested to give a similar perceptual image quality when compared to the original exposure factors. Aims - In light of the 10kVp rule, this study aims to investigate the influence of tube potential (kVp) variation in relation to perceptual image quality and E for pelvis imaging using automatic exposure control (AEC) and non-AEC in a Computed Radiography (CR) system. Research questions - Does the 10kVp rule works for the pelvis in relation to image quality in a CR system? Does the image quality differs when the AEC is used instead of manual mode using the 10kVp rule and how this impacts on E?

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Purpose: To compare image quality and effective dose when the 10 kVp rule is applied with manual and AEC mode in PA chest X-ray. Methods and Materials: A total of 68 images (with and without lesions) were acquired of an anthropomorphic chest phantom in a Wolverson Arcoma X-ray unit. The images were evaluated against a reference image using image quality criteria and the 2 alternative forced choice (2 AFC) method by five radiographers. The effective dose was calculated using PCXMC software using the exposure parameters and DAP. The exposure index (lgM) was recorded. Results: Exposure time decreases considerably when applying the 10 kVp rule in manual mode (50%-28%) compared to AEC mode (36%-23%). Statistical differences for effective dose between several AEC modes were found (p=0.002). The effective dose is lower when using only the right AEC ionization chamber. Considering image quality, there are no statistical differences (p=0.348) between the different AEC modes for images with no lesions. Using a higher kVp value the lgM values will also increase. The lgM values showed significant statistical differences (p=0.000). The image quality scores did not present statistically significant differences (p=0.043) for the images with lesions when comparing manual with AEC modes. Conclusion: In general, the dose is lower in the manual mode. By using the right AEC ionising chamber the effective dose will be the lowest in comparison to other ionising chambers. The use of the 10 kVp rule did not affect the detectability of the lesions.

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Purpose: This study aims to investigate the influence of tube potential (kVp) variation in relation to perceptual image quality and effective dose for pelvis using automatic exposure control (AEC) and non-AEC in a computed radiography (CR) system. Methods and Materials: To determine the effects of using AEC and non-AEC by applying the 10 kVp rule in two experiments using an anthropomorphic pelvis phantom. Images were acquired using 10 kVp increments (60-120 kVp) for both experiments. The first experiment, based on seven AEC combinations, produced 49 images. The mean mAs from each kVp increment were used as a baseline for the second experiment producing 35 images. A total of 84 images were produced and a panel of 5 experienced observers participated for the image scoring using the 2 AFC visual grading software. PCXMC software was used to estimate the effective dose. Results: A decrease in perceptual image quality as the kVp increases was observed both in non-AEC and AEC experiments, however no significant statistical differences (p> 0.05) were found. Image quality scores from all observers at 10 kVp increments for all mAs values using non-AEC mode demonstrates a better score up to 90 kVp. Effective dose results show a statistical significant decrease (p=0.000) on the 75th quartile from 0.3 mSv at 60 kVp to 0.1 mSv at 120 kVp when applying the 10 kVp rule in non-AEC mode. Conclusion: No significant reduction in perceptual image quality is observed when increasing kVp whilst a marked and significant effective dose reduction is observed.