This paper presents a statistical approach to identify the underlying roughness characteristics in synthetic aperture radar (SAR) intensity data. The physical modeling of this kind of data allows the ...use of the Gamma distribution in the presence of fully developed speckle, i.e., when there are infinitely many independent backscatterers per resolution cell, and none dominates the return. Such areas are often called “homogeneous” or “textureless” regions. The GI0 distribution is also a widely accepted law for heterogeneous and extremely heterogeneous regions, i.e., areas where the fully developed speckle hypotheses do not hold. We propose three test statistics to distinguish between homogeneous and inhomogeneous regions, i.e., between gamma and GI0 distributed data, both with a known number of looks. The first test statistic uses a bootstrapped non-parametric estimator of Shannon entropy, providing a robust assessment in uncertain distributional assumptions. The second test uses the classical coefficient of variation (CV). The third test uses an alternative form of estimating the CV based on the ratio of the mean absolute deviation from the median to the median. We apply our test statistic to create maps of p-values for the homogeneity hypothesis. Finally, we show that our proposal, the entropy-based test, outperforms existing methods, such as the classical CV and its alternative variant, in identifying heterogeneity when applied to both simulated and actual data.
The scaled complex Wishart distribution is a widely used model for multilook full polarimetric synthetic aperture radar data whose adequacy is attested in this paper. Classification, segmentation, ...and image analysis techniques that depend on this model are devised, and many of them employ some type of dissimilarity measure. In this paper, we derive analytic expressions for four stochastic distances between relaxed scaled complex Wishart distributions in their most general form and in important particular cases. Using these distances, inequalities are obtained that lead to new ways of deriving the Bartlett and revised Wishart distances. The expressiveness of the four analytic distances is assessed with respect to the variation of parameters. Such distances are then used for deriving new tests statistics, which are proved to have asymptotic chi-square distribution. Adopting the test size as a comparison criterion, a sensitivity study is performed by means of Monte Carlo experiments suggesting that the Bhattacharyya statistic outperforms all the others. The power of the tests is also assessed. Applications to actual data illustrate the discrimination and homogeneity identification capabilities of these distances.
White adipose tissue (WAT) plays a fundamental role in maintaining energy balance and important endocrine functions. The loss of WAT modifies adipokine secretion and disrupts homeostasis, potentially ...leading to severe metabolic effects and a reduced quality of life. Doxorubicin is a chemotherapeutic agent used clinically because of its good effectiveness against various types of cancer. However, doxorubicin has deleterious effects in many healthy tissues, including WAT, liver, and skeletal and cardiac muscles. Our objective was to investigate the effects of doxorubicin on white adipocytes through in vivo and in vitro experiments. Doxorubicin reduced the uptake of glucose by retroperitoneal adipocytes and 3T3-L1 cells via the inhibition of AMP-activated protein kinase Thr172 phosphorylation and glucose transporter 4 content. Doxorubicin also reduced the serum level of adiponectin and, to a greater extent, the expression of genes encoding lipogenic (Fas and Acc) and adipogenic factors (Pparg, C/ebpa, and Srebp1c) in retroperitoneal adipose tissue. In addition, doxorubicin inhibited both lipogenesis and lipolysis and reduced the hormone-sensitive lipase and adipose tissue triacylglycerol lipase protein levels. Therefore, our results demonstrate the impact of doxorubicin on WAT. These results are important to understand some side effects observed in patients receiving chemotherapy and should encourage new adjuvant treatments that aim to inhibit these side effects.
Images obtained from coherent illumination processes are contaminated with speckle. A prominent example of such imagery systems is the polarimetric synthetic aperture radar (PolSAR). For such a ...remote sensing tool, the speckle interference pattern appears in the form of a positive-definite Hermitian matrix, which requires specialized models and makes change detection a hard task. The scaled complex Wishart distribution is a widely used model for PolSAR images. Such a distribution is defined by two parameters: the number of looks and the complex covariance matrix. The last parameter contains all the necessary information to characterize the backscattered data, and thus, identifying changes in a sequence of images can be formulated as a problem of verifying whether the complex covariance matrices differ at two or more takes. This paper proposes a comparison between a classical change detection method based on the likelihood ratio and three statistical methods that depend on information-theoretic measures: the Kullback-Leibler (KL) distance and two entropies. The performance of these four tests was quantified in terms of their sample test powers and sizes using simulated data. The tests are then applied to actual PolSAR data. The results provide evidence that tests based on entropies may outperform those based on the KL distance and likelihood ratio statistics.
Effective vaccination against coronavirus mitigates the risk of hospitalisation and mortality; however, it is unclear whether vaccination status influences long COVID symptoms in patients who require ...hospitalisation. The available evidence is limited to outpatients with mild disease. Here, we evaluated 412 patients (age: 60 ± 16 years, 65% males) consecutively admitted to two Hospitals in Brazil due to confirmed coronavirus disease 2019 (COVID-19). Compared with patients with complete vaccination (n = 185) before infection or hospitalisation, those with no or incomplete vaccination (n = 227) were younger and had a lower frequency of several comorbidities. Data during hospitalisation revealed that the no or incomplete vaccination group required more admissions to the intensive care unit (ICU), used more corticosteroids, and had higher rates of pulmonary embolism or deep venous thrombosis than the complete vaccination group. Ninety days after hospital discharge, patients with no or incomplete vaccination presented a higher frequency of symptoms (≥ 1) than patients with complete vaccination (40 vs. 27%; p = 0.013). After adjusting for confounders, no or incomplete vaccination (odds ratio OR 1.819; 95% confidence interval CI 1.175-2.815), female sex (OR 2.435; 95% CI 1.575-3.764) and ICU admission during hospitalisation (OR 1.697; 95% CI 1.062-2.712) were independently associated with ≥ 1 symptom 90 days after hospital discharge. In conclusion, even in patients with severe COVID-19, vaccination mitigates the probability of long COVID symptoms.
Polarimetric Synthetic Aperture Radar (PolSAR) is one of the most important remote sensing tools. However, PolSAR images are strongly contaminated by a multidimensional interference (called speckle ...noise), making their processing (e.g. in the classification context) difficult. In terms of structure, multilook PolSAR data follow a definite positive hermitian behaviour and, therefore, require tailored classifiers for their features. Some classic classifiers - such as Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA), K-Nearest Neighbours (KNN), and Support Vector Machine (SVM) - have been yielding unacceptable performance to these data, when applied directly. One justification is because they do not often take into account neither the speckle presence nor properties which are inherent to under-study relieves. This paper addresses a collection of PolSAR divergence-based classifiers, deduced from the normal, skew-normal, t-Student, and skew-t vector models as well as the scaled complex Wishart (SCW) distribution. The last model is a standard supposition to describe multilook PolSAR data, having two parameters: covariance matrix (which is directed to data nature) and number of looks (which controls the speckle noise effect). The considered remainder laws aim to model the main diagonal of these data, known as multivariate intensities. The performance of proposed methods is quantified and compared with those due to the Kullback-Leibler (KL) distance for multivariate normal distribution and to LDA, QDA, KNN, and SVM methods. Experiments with both artificial and real PolSAR data are considered. Results favour optimal Rényi classifiers for an Airborne Synthetic Aperture Radar (AIRSAR) image of San Francisco and the t-Student KL classifier for an SAR image system of the Electromagnetics Institute (EMISAR) image of Foulum.
Images obtained with coherent illumination, as is the case of sonar, ultrasound-B, laser, and synthetic aperture radar, are affected by speckle noise which reduces the ability to extract information ...from the data. Specialized techniques are required to deal with such imagery, which has been modeled by the G 0 distribution and, under which, regions with different degrees of roughness and mean brightness can be characterized by two parameters; a third parameter, which is the number of looks, is related to the overall signal-to-noise ratio. Assessing distances between samples is an important step in image analysis; they provide grounds of the separability and, therefore, of the performance of classification procedures. This paper derives and compares eight stochastic distances and assesses the performance of hypothesis tests that employ them and maximum likelihood estimation. We conclude that tests based on the triangular distance have the closest empirical size to the theoretical one, while those based on the arithmetic-geometric distances have the best power. Since the power of tests based on the triangular distance is close to optimum, we conclude that the safest choice is using this distance for hypothesis testing, even when compared with classical distances as Kullback-Leibler and Bhattacharyya.
Abstract Objective The aim of the present study was to assess the influence of diet in tooth erosion presence in children and adolescents by meta-analysis and meta-regression. Data Two reviewers ...independently performed the selection process and the quality of studies was assessed. Sources Studies published until May 2014 were identified in electronic databases: Pubmed, EBSHost, Scopus, Science direct, Web of Science and Scielo, using keywords. Study selection Criteria used included: observational studies, tooth erosion and diet, subject age range 8–19 years old, permanent dentition and index. Meta-analysis was performed and in case of heterogeneity a random-effects model was used. Thirteen studies that fulfilled the inclusion criteria were selected. Higher consumption of carbonated drinks ( p = 0.001) or acid snacks/sweets ( p = 0.01 and for acid fruit juices ( p = 0.03)) increased the odds for tooth erosion, while higher intake of milk ( p = 0.028) and yogurt ( p = 0.002) reduced the erosion occurrence. Heterogeneity was observed in soft drinks, confectionary and snacks and acidic fruit juices models. Methodological issues regarding the questionnaires administration and the inclusion of other variables, such as food groups and tooth brushing, explained partially the heterogeneity observed. Conclusions Some dietary components (carbonated drinks, acid snacks/sweets and natural acidic fruits juice) increased erosion occurrence while milk and yogurt had a protective effect. Methods to assess diet could influence the homogeneity of the studies and should be considered during the study design. Clinical significance The method to assess diet should be carefully considered and well conducted as part of the clinical assessment of tooth erosion, since diet could influence the occurrence of tooth erosion.
In Compost-Bedded Pack Barn (CBP) systems, air velocity is linked with the thermal comfort of housed dairy cattle and bedding quality and, therefore, assessing ventilation efficiency is essential. In ...this context, the objective of this study was to evaluate and characterize dependence and spatial distribution of air velocity at the 1.5 m height (vair,M) and at bedding level (vair,B) in an open CBP system with positive pressure ventilation. The study was conducted in 2021, in a facility located in the Zona da Mata region, Minas Gerais, Brazil. The facility area was divided into a mesh composed of 55 equidistant points, where vair,M and vair,B data were collected in the morning (09:00 a.m.) and afternoon (03:00 p.m.) periods, during three weeks in Brazilian winter. Geostatistics techniques were used to assess dependence and spatial distribution. In both periods evaluated, there were a strong occurrence of spatial dependence and non-uniform vair,M and vair,B distributions. The vair,M and vair,B values were lower than recommended (1.8 m∙s-1) in more than 65.0% of the area. Adequate ventilation levels were observed only in the first 20.0 m of the facility, from Southeast to Northwest, because of the fan lines present.
The polarimetric synthetic aperture radar (PolSAR) system is one of the most successful tools for solving remote-sensing issues. However, the images produced by this system - which uses coherent ...illumination - are corrupted by the multidimensional speckle noise that gives PolSAR data a multiplicative character. Therefore, tailored processing of PolSAR images is required, e.g. improved hypothesis testing and change detectors. In this work, we propose a novel bivariate distribution - called
McKay bivariate (
MB) - to describe a joint distribution arising from two components of the total scattering power image (SPAN). We derive closed-form expressions for the Kullback-Leibler and Rényi divergences for the
MB law. We provide new two-sample divergence-based hypothesis tests and evaluate their performance using Monte Carlo experiments. Finally, we apply the new tests to real PolSAR images to evaluate the changes caused by urbanization processes in the Los Angeles and California regions. Results show that our proposals to detect changes in PolSAR images outperform the one based on the likelihood ratio.
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