926 resultados para Multidimensional scaling (MDS)


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We analyze the statistics of rain-event sizes, rain-event durations, and dry-spell durations in a network of 20 rain gauges scattered in an area situated close to the NW Mediterranean coast. Power-law distributions emerge clearly for the dryspell durations, with an exponent around 1.50 ± 0.05, although for event sizes and durations the power-law ranges are rather limited, in some cases. Deviations from power-law behavior are attributed to finite-size effects. A scaling analysis helps to elucidate the situation, providing support for the existence of scale invariance in these distributions. It is remarkable that rain data of not very high resolution yield findings in agreement with self-organized critical phenomena.

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We use numerical simulations to investigate how the chain length and topology of freely fluctuating knotted polymer rings affect their various spatial characteristics such as the radius of the smallest sphere enclosing momentary configurations of simulated polymer chains. We describe how the average value of a characteristic changes with the chain size and how this change depends on the topology of the modeled polymers. Although the scaling profiles of a spatial characteristic for distinct knot types do not intersect (at least, in the range of our data), the profiles for nontrivial knots intersect the corresponding profile obtained for phantom polymers, i.e., those that are free to explore all available topological states. For each knot type, this point of intersection defines its equilibrium length with respect to the spatial characteristic. At this chain length, a polymer forming a given knot type will not tend to increase or decrease. on average, the value of the spatial characteristic when the polymer is released from its topological constraint. We show interrelations between equilibrium lengths defined with respect to spatial characteristics of different character and observe that they are related to the lengths of ideal geometric configurations of the corresponding knot types.

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We explore in depth the validity of a recently proposed scaling law for earthquake inter-event time distributions in the case of the Southern California, using the waveform cross-correlation catalog of Shearer et al. Two statistical tests are used: on the one hand, the standard two-sample Kolmogorov-Smirnov test is in agreement with the scaling of the distributions. On the other hand, the one-sample Kolmogorov-Smirnov statistic complemented with Monte Carlo simulation of the inter-event times, as done by Clauset et al., supports the validity of the gamma distribution as a simple model of the scaling function appearing on the scaling law, for rescaled inter-event times above 0.01, except for the largest data set (magnitude greater than 2). A discussion of these results is provided.

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Myelodysplastic syndromes (MDS) with del(5q) are considered to have a benign course of the disease. In order to address the issue of the propensity of those patients to progress to acute myeloid leukemia (AML), data on 381 untreated patients with MDS and del(5q) characterized by low or intermediate I International Prognostic Scoring System (IPSS) risk score were collected from nine centers and registries. Median survival of the entire group was 74 months. Transfusion-dependent patients had a median survival of 44 months vs 97 months for transfusion-independent patients (P<0.0001). Transfusion need at diagnosis was the most important patient characteristic for survival. Of the 381 patients, 48 (12.6%) progressed to AML. The cumulative progression rate calculated using the Kaplan-Meier method was 4.9% at 2 years and 17.6% at 5 years. Factors associated with the risk of AML transformation were high-risk World Health Organization adapted Prognostic Scoring System (WPSS) score, marrow blast count >5% and red-cell transfusion dependency at diagnosis. In conclusion, patients with MDS and del(5q) are facing a considerable risk of AML transformation. More detailed cytogenetic and molecular studies may help to identify the patients at risk of progression.

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In most psychological tests and questionnaires, a test score is obtained bytaking the sum of the item scores. In virtually all cases where the test orquestionnaire contains multidimensional forced-choice items, this traditionalscoring method is also applied. We argue that the summation of scores obtained with multidimensional forced-choice items produces uninterpretabletest scores. Therefore, we propose three alternative scoring methods: a weakand a strict rank preserving scoring method, which both allow an ordinalinterpretation of test scores; and a ratio preserving scoring method, whichallows a proportional interpretation of test scores. Each proposed scoringmethod yields an index for each respondent indicating the degree to whichthe response pattern is inconsistent. Analysis of real data showed that withrespect to rank preservation, the weak and strict rank preserving methodresulted in lower inconsistency indices than the traditional scoring method;with respect to ratio preservation, the ratio preserving scoring method resulted in lower inconsistency indices than the traditional scoring method

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Evaluation of segmentation methods is a crucial aspect in image processing, especially in the medical imaging field, where small differences between segmented regions in the anatomy can be of paramount importance. Usually, segmentation evaluation is based on a measure that depends on the number of segmented voxels inside and outside of some reference regions that are called gold standards. Although some other measures have been also used, in this work we propose a set of new similarity measures, based on different features, such as the location and intensity values of the misclassified voxels, and the connectivity and the boundaries of the segmented data. Using the multidimensional information provided by these measures, we propose a new evaluation method whose results are visualized applying a Principal Component Analysis of the data, obtaining a simplified graphical method to compare different segmentation results. We have carried out an intensive study using several classic segmentation methods applied to a set of MRI simulated data of the brain with several noise and RF inhomogeneity levels, and also to real data, showing that the new measures proposed here and the results that we have obtained from the multidimensional evaluation, improve the robustness of the evaluation and provides better understanding about the difference between segmentation methods.

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La localitat de Cumbe és una comunitat tradicional que es troba al tram baix del riu Jaguaribe situat a l’estat de Ceará (Brasil) i que ha viscut centenars d’anys a partir de les pràctiques extractives que es porten a terme a l’ecosistema del manglar. Fa 20 anys va aparèixer a la regió una nova economia basada en l’explotació intensiva. L’aqüicultura destinada a la cria de gamba està causant danys severs a l’ecosistema del manglar i perjudicant greument la font d’ingressos de moltes famílies, amenaçant la continuïtat de l’economia local i deteriorant la qualitat de vida de les persones que s’hi dediquen. A partir de l’observació personal i la immersió en aquesta societat s’ha detectat que l’economia tradicional està infravalorada pel govern i per les persones que donen suport a l’aqüicultura. Per aquest motiu s’han creat una sèrie d’indicadors, a partir de les activitats extractives del cranc, que posin en valor aquesta economia tradicional envers la nova economia emergent.

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AIMS: Adolescent mental health problems require treatment and care that are adapted to their needs. To evaluate this issue, it was decided to implement a multidimensional instrument focused on a global approach to adolescent social and behavioural functioning, combined with the ICD-10 classification. METHODS: The combination of an assessment interview and a classification tool enabled the method to integrate the measurement of several domains of patient-based outcome rather than focus on the measurement of symptoms. A group of 68 adolescents from an inpatient unit were compared with 67 adolescents from the general population. RESULTS: Results suggest that adolescents from the care unit adopt significantly riskier behaviour compared with adolescents from the control group. As expected, the main problems identified refer to the psychological and familial areas. A cluster analysis was performed and provided three different profiles: a group with externalizing disorders and two groups with internalizing disorders. On the basis of a structured interview it was possible to obtain information in a systematic way about the adolescents' trajectory (delinquency, physical and sexual abuse, psychoactive substance use). CONCLUSION: It was shown that treatment and care should not focus exclusively on mental health symptoms, but also upon physical, psychological and social aspects of the adolescent. A global approach helps in the consideration of the multitude of factors which must be taken into account when working with people with serious mental health problems and may help to turn the care unit's activity more specifically towards the needs of these adolescents.

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This paper examines properties of optimal poverty assistance programs under different informational environments using an income maintenanceframework. To that end, we make both the income generating ability andthe disutility of labor of individuals unobservable, and compare theresulting benefit schedules with those of programs found in the UnitedStates since Welfare Reform (1996). We find that optimal programs closelyresemble a Negative Income Tax with a Benefit Reduction rate that dependson the distribution of population characteristics. A policy of workfare(unpaid public sector work) is inefficient when disutility of labor isunobservable, but minimum work requirements (for paid work) may be usedin that same environment. The distortions to work incentives and thepresence of minimum work requirements depend on the observability andrelative importance of the population's characteristics.

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Dual scaling of a subjects-by-objects table of dominance data (preferences,paired comparisons and successive categories data) has been contrasted with correspondence analysis, as if the two techniques were somehow different. In this note we show that dual scaling of dominance data is equivalent to the correspondence analysis of a table which is doubled with respect to subjects. We also show that the results of both methods can be recovered from a principal components analysis of the undoubled dominance table which is centred with respect to subject means.

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Two methods were evaluated for scaling a set of semivariograms into a unified function for kriging estimation of field-measured properties. Scaling is performed using sample variances and sills of individual semivariograms as scale factors. Theoretical developments show that kriging weights are independent of the scaling factor which appears simply as a constant multiplying both sides of the kriging equations. The scaling techniques were applied to four sets of semivariograms representing spatial scales of 30 x 30 m to 600 x 900 km. Experimental semivariograms in each set successfully coalesced into a single curve by variances and sills of individual semivariograms. To evaluate the scaling techniques, kriged estimates derived from scaled semivariogram models were compared with those derived from unscaled models. Differences in kriged estimates of the order of 5% were found for the cases in which the scaling technique was not successful in coalescing the individual semivariograms, which also means that the spatial variability of these properties is different. The proposed scaling techniques enhance interpretation of semivariograms when a variety of measurements are made at the same location. They also reduce computational times for kriging estimations because kriging weights only need to be calculated for one variable. Weights remain unchanged for all other variables in the data set whose semivariograms are scaled.