Rank Aggregation for Pattern Classifier Selection in Remote Sensing Images

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Feature extraction in pressure signals for leak detection in water networks

Techniques based on signal analysis for leak detection in water supply systems typically use long pressure and/or flow data series of variable length. This paper presents the feature extraction from pressure signals and their application to the identification of changes related to the onset of a leak. Example signals were acquired from an experimental laboratory circuit, and features were extracted from temporal domain and from transformed signals. Statistical analysis of features values and a classification method were applied. It was verified the feasibility of using feature vectors for distinguish data acquired in the absence or presence of a leak.

Supervised variational relevance learning, an analytic geometric feature selection with applications to omic datasets

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Análise de formas planas em imagens digitais

Given the widespread use of computers, the visual pattern recognition task has been automated in order to address the huge amount of available digital images. Many applications use image processing techniques as well as feature extraction and visual pattern recognition algorithms in order to identify people, to make the disease diagnosis process easier, to classify objects, etc. based on digital images. Among the features that can be extracted and analyzed from images is the shape of objects or regions. In some cases, shape is the unique feature that can be extracted with a relatively high accuracy from the image. In this work we present some of most important shape analysis methods and compare their performance when applied on three well-known shape image databases. Finally, we propose the development of a new shape descriptor based on the Hough Transform.

Feature-oriented regional modeling and simulations (FORMS) for the western South Atlantic: Southeastern Brazil region

The multi-scale synoptic circulation system in the southeastern Brazil (SEBRA) region is presented using a feature-oriented approach. Prevalent synoptic circulation structures, or ""features,"" are identified from previous observational studies. These features include the southward-flowing Brazil Current (BC), the eddies off Cabo Sao Tome (CST - 22 degrees S) and off Cabo Frio (CF - 23 degrees S), and the upwelling region off CF and CST. Their synoptic water-mass (T-S) structures are characterized and parameterized to develop temperature-salinity (T-S) feature models. Following [Gangopadhyay, A., Robinson, A.R., Haley, PJ., Leslie, W.J., Lozano, C.j., Bisagni, J., Yu, Z., 2003. Feature-oriented regional modeling and simulation (forms) in the gulf of maine and georges bank. Cont. Shelf Res. 23 (3-4), 317-353] methodology, a synoptic initialization scheme for feature-oriented regional modeling and simulation (FORMS) of the circulation in this region is then developed. First, the temperature and salinity feature-model profiles are placed on a regional circulation template and objectively analyzed with available background climatology in the deep region. These initialization fields are then used for dynamical simulations via the Princeton Ocean Model (POM). A few first applications of this methodology are presented in this paper. These include the BC meandering, the BC-eddy interaction and the meander-eddy-upwelling system (MEUS) simulations. Preliminary validation results include realistic wave-growth and eddy formation and sustained upwelling. Our future plan includes the application of these feature models with satellite, in-situ data and advanced data-assimilation schemes for nowcasting and forecasting the SEBRA region. (c) 2008 Elsevier Ltd. All rights reserved.

Evolution of Body Elongation in Gymnophthalmid Lizards: Relationships with Climate

The evolution of elongated body shapes in vertebrates has intrigued biologists for decades and is particularly recurrent among squamates. Several aspects might explain how the environment influences the evolution of body elongation, but climate needs to be incorporated in this scenario to evaluate how it contributes to morphological evolution. Climatic parameters include temperature and precipitation, two variables that likely influence environmental characteristics, including soil texture and substrate coverage, which may define the selective pressures acting during the evolution of morphology. Due to development of geographic information system (GIS) techniques, these variables can now be included in evolutionary biology studies and were used in the present study to test for associations between variation in body shape and climate in the tropical lizard family Gymnophthalmidae. We first investigated how the morphological traits that define body shape are correlated in these lizards and then tested for associations between a descriptor of body elongation and climate. Our analyses revealed that the evolution of body elongation in Gymnophthalmidae involved concomitant changes in different morphological traits: trunk elongation was coupled with limb shortening and a reduction in body diameter, and the gradual variation along this axis was illustrated by less-elongated morphologies exhibiting shorter trunks and longer limbs. The variation identified in Gymnophthalmidae body shape was associated with climate, with the species from more arid environments usually being more elongated. Aridity is associated with high temperatures and low precipitation, which affect additional environmental features, including the habitat structure. This feature may influence the evolution of body shape because contrasting environments likely impose distinct demands for organismal performance in several activities, such as locomotion and thermoregulation. The present study establishes a connection between morphology and a broader natural component, climate, and introduces new questions about the spatial distribution of morphological variation among squamates.

An unusual feature of yolk sac placentation in Necromys lasiurus (Rodentia, Cricetidae, Sigmodontinae)

We studied the development of the inverted yolk sac in a New World rodent, Necromys lasiurus during early placentation. Ten implantation sites were investigated by means of histology, immunohistochemistry and electron microscopy. The yolk sac was villous near its attachment to the placenta. Elsewhere it was non-villous and closely attached to the uterus. The uterine glands were shallow and wide mouthed. They were associated with vessels and filled with secretion, suggesting the release of histotroph. This feature was absent at later stages. The intimate association of the yolk sac with specialized glandular regions of the uterus may represent a derived character condition of Necromys and/or sigmodont rodents. (C) 2012 Elsevier Ltd. All rights reserved.

Three-feature model to reproduce the topology of citation networks and the effects from authors' visibility on their h-index

Various factors are believed to govern the selection of references in citation networks, but a precise, quantitative determination of their importance has remained elusive. In this paper, we show that three factors can account for the referencing pattern of citation networks for two topics, namely "graphenes" and "complex networks", thus allowing one to reproduce the topological features of the networks built with papers being the nodes and the edges established by citations. The most relevant factor was content similarity, while the other two - in-degree (i.e. citation counts) and age of publication - had varying importance depending on the topic studied. This dependence indicates that additional factors could play a role. Indeed, by intuition one should expect the reputation (or visibility) of authors and/or institutions to affect the referencing pattern, and this is only indirectly considered via the in-degree that should correlate with such reputation. Because information on reputation is not readily available, we simulated its effect on artificial citation networks considering two communities with distinct fitness (visibility) parameters. One community was assumed to have twice the fitness value of the other, which amounts to a double probability for a paper being cited. While the h-index for authors in the community with larger fitness evolved with time with slightly higher values than for the control network (no fitness considered), a drastic effect was noted for the community with smaller fitness. (C) 2012 Elsevier Ltd. All rights reserved.

Breast imaging: is the sonographic descriptor of orientation valid for magnetic resonance imaging?

Purpose: To evaluate if the Breast Imaging Reporting and Data System (BI-RADS) ultrasound descriptor of orientation can be used in magnetic resonance imaging (MRI). Materials and Methods: We conducted a retrospective study to evaluate breast mass lesions identified by MRI from 2008 to 2010 who had ultrasound (US) and histopathologic confirmation. Lesions were measured in the craniocaudal (CC), anteroposterior (AP), and transverse (T) axes and classified as having a nonparallel orientation, longest axis perpendicular to Cooper's ligaments, or in a parallel orientation when the longest axis is parallel to Cooper's ligaments. The MR image data were correlated with the US orientation according to BI-RADS and histopathological diagnosis. Results: We evaluated 71 lesions in 64 patients. On MRI, 27 lesions (38.0%) were nonparallel (8 benign and 19 malignant), and 44 lesions (62.0%) were parallel (33 benign and 11 malignant). There was significant agreement between the lesion orientation on US and MRI (kappa value = 0.901). The positive predictive values (PPV) for parallel orientation malignancy on MR and US imaging were 70.4% and 73.1%, respectively. Conclusion: A descriptor of orientation for breast lesions can be used on MRI with PPV for malignant lesions similar to US. J. Magn. Reson. Imaging 2012; 36:13831388. (C) 2012 Wiley Periodicals, Inc.

Millennial-scale climate cycles in Permian-Carboniferous rhythmites: Permanent feature throughout geologic time?

Two late Paleozoic glacial rhythmite successions from the Itarare Group (Parana Basin, Brazil) were examined for paleoclimate variations. Paleomagnetic (characteristic remanent magnetization, ChRM) and magnetic susceptibility (K(z)) measurements taken from the rhythmites are interpreted as paleoclimatic proxies. Ratios of low-frequency components in the K(z) variations suggest Milankovitch periodicities; this leads to recognition of other, millennial-scale variations reminiscent of abrupt climate changes during late Quaternary time, and are suggestive of Bond cycles and the 2.4 k.y. solar cycle. We infer from these patterns that millennial-scale climate change is not restricted to the Quaternary Period, and that millennial forcing mechanisms may have been prevalent throughout geologic time.

MUSCLE HEMANGIOMATOSIS PRESENTING AS A SEVERE FEATURE IN A PATIENT WITH THE PTEN MUTATION: EXPANDING THE PHENOTYPE OF VASCULAR MALFORMATIONS IN BANNAYAN-RILEY-RUVALCABA SYNDROME

Bannayan-Riley-Ruvalcaba syndrome (BRRS) is a rare autosomal, dominantly-inherited, hamartoma syndrome with distinct phenotypic features. Mutations in the PTEN gene have been identified in PTEN hamartoma tumor syndromes. Our aim was to determine the correlation of phenotype-genotype relationships in a BRRS case. We have evaluated a PTEN mutation in a patient with vascular anomalies and the phenotypic findings of BRRS. We described an 8-year-old girl with the clinical features of BRRS, specifically with vascular anomalies. The mutation in the PTEN gene was identified by DNA sequencing. In our patient, we defined a de novo nonsense R335X (c. 1003 C>T) mutation in exon 8, which results in a premature termination codon. Due to vascular anomalies and hemangioma, the patient's left leg was amputated 1 year after the hemangioma diagnosis. Bannayan - Riley - Ruvalcaba syndrome patients with macrocephaly and vascular anomalies should be considered for PTEN mutation analysis and special medical care.

Uric acid biorhythm, a feature of long-term variation in a clinical laboratory database

Background: The biorhythm of serum uric acid was evaluated in a large sample of a clinical laboratory database by spectral analysis and the influence of the gender and age on uric acid variability. Methods: Serum uric acid values were extracted from a large database of a clinical laboratory from May 2000 to August 2006. Outlier values were excluded from the analysis and the remaining data (n = 73,925) were grouped by gender and age ranges. Rhythm components were obtained by the Lomb Scargle method and Cosinor analysis. Results: Serum uric acid was higher in men than in women older than 13 years (p<0.05). Compared with 0-12 year group, uric acid increased in men but not in women older than 13 years (p<0.05). Circannual (12 months) and transyear (17 months) rhythm components were detected, but they were significant only in adult individuals (>26 years, p<0.05). Cosinor analysis showed that midline estimating statistic of rhythm (MESOR) values were higher in men (range: 353-368 mu mol/L) than in women (range: 240-278 mu mol/L; p<0.05), independent of the age and rhythm component. The extent of predictable change within a cycle, approximated by the double amplitude, represented up to 20% of the corresponding MESOR. Conclusions: Serum uric acid biorhythm is dependent on gender and age and it may have relevant influence on preanalytical variability of clinical laboratory results.

New Insights on Nontechnical Losses Characterization Through Evolutionary-Based Feature Selection

Although nontechnical losses automatic identification has been massively studied, the problem of selecting the most representative features in order to boost the identification accuracy and to characterize possible illegal consumers has not attracted much attention in this context. In this paper, we focus on this problem by reviewing three evolutionary-based techniques for feature selection, and we also introduce one of them in this context. The results demonstrated that selecting the most representative features can improve a lot of the classification accuracy of possible frauds in datasets composed by industrial and commercial profiles.

A feature selection approach for identification of signature genes from SAGE data

Abstract Background One goal of gene expression profiling is to identify signature genes that robustly distinguish different types or grades of tumors. Several tumor classifiers based on expression profiling have been proposed using microarray technique. Due to important differences in the probabilistic models of microarray and SAGE technologies, it is important to develop suitable techniques to select specific genes from SAGE measurements. Results A new framework to select specific genes that distinguish different biological states based on the analysis of SAGE data is proposed. The new framework applies the bolstered error for the identification of strong genes that separate the biological states in a feature space defined by the gene expression of a training set. Credibility intervals defined from a probabilistic model of SAGE measurements are used to identify the genes that distinguish the different states with more reliability among all gene groups selected by the strong genes method. A score taking into account the credibility and the bolstered error values in order to rank the groups of considered genes is proposed. Results obtained using SAGE data from gliomas are presented, thus corroborating the introduced methodology. Conclusion The model representing counting data, such as SAGE, provides additional statistical information that allows a more robust analysis. The additional statistical information provided by the probabilistic model is incorporated in the methodology described in the paper. The introduced method is suitable to identify signature genes that lead to a good separation of the biological states using SAGE and may be adapted for other counting methods such as Massive Parallel Signature Sequencing (MPSS) or the recent Sequencing-By-Synthesis (SBS) technique. Some of such genes identified by the proposed method may be useful to generate classifiers.