1,283 research outputs found
The effects of solar incidence angle over digital processing of LANDSAT data
A technique to extract the topography modulation component from digital data is described. The enhancement process is based on the fact that the pixel contains two types of information: (1) reflectance variation due to the target; (2) reflectance variation due to the topography. In order to enhance the signal variation due to topography, the technique recommends the extraction from original LANDSAT data of the component resulting from target reflectance. Considering that the role of topographic modulation over the pixel information will vary with solar incidence angle, the results of this technique of digital processing will differ from one season to another, mainly in highly dissected topography. In this context, the effects of solar incidence angle over the topographic modulation technique were evaluated. Two sets of MSS/LANDSAT data, with solar elevation angles varying from 22 to 41 deg were selected to implement the digital processing at the Image-100 System. A secondary watershed (Rio Bocaina) draining into Rio Paraiba do Sul (Sao Paulo State) was selected as a test site. The results showed that the technique used was more appropriate to MSS data acquired under higher Sun elevation angles. Topographic modulation components applied to low Sun elevation angles lessens rather than enhances topography
Application of remote sensing to hydrological problems and floods
The main applications of remote sensors to hydrology are identified as well as the principal spectral bands and their advantages and disadvantages. Some examples of LANDSAT data applications to flooding-risk evaluation are cited. Because hydrology studies the amount of moisture and water involved in each phase of hydrological cycle, remote sensing must be emphasized as a technique for hydrological data acquisition
Usefulness of regional right ventricular and right atrial strain for prediction of early and late right ventricular failure following a left ventricular assist device implant: A machine learning approach
Background: Identifying candidates for left ventricular assist device surgery at risk of right ventricular failure remains difficult. The aim was to identify the most accurate predictors of right ventricular failure among clinical, biological, and imaging markers, assessed by agreement of different supervised machine learning algorithms. Methods: Seventy-four patients, referred to HeartWare left ventricular assist device since 2010 in two Italian centers, were recruited. Biomarkers, right ventricular standard, and strain echocardiography, as well as cath-lab measures, were compared among patients who did not develop right ventricular failure (N = 56), those with acute–right ventricular failure (N = 8, 11%) or chronic–right ventricular failure (N = 10, 14%). Logistic regression, penalized logistic regression, linear support vector machines, and naïve Bayes algorithms with leave-one-out validation were used to evaluate the efficiency of any combination of three collected variables in an “all-subsets” approach. Results: Michigan risk score combined with central venous pressure assessed invasively and apical longitudinal systolic strain of the right ventricular–free wall were the most significant predictors of acute–right ventricular failure (maximum receiver operating characteristic–area under the curve = 0.95, 95% confidence interval = 0.91–1.00, by the naïve Bayes), while the right ventricular–free wall systolic strain of the middle segment, right atrial strain (QRS-synced), and tricuspid annular plane systolic excursion were the most significant predictors of Chronic-RVF (receiver operating characteristic–area under the curve = 0.97, 95% confidence interval = 0.91–1.00, according to naïve Bayes). Conclusion: Apical right ventricular strain as well as right atrial strain provides complementary information, both critical to predict acute–right ventricular failure and chronic–right ventricular failure, respectively
Computational assessment of the retinal vascular tortuosity integrating domain-related information
[Abstract] The retinal vascular tortuosity presents a valuable potential as a clinical biomarker of many relevant vascular and systemic diseases. Commonly, the existent approaches face the tortuosity quantification by means of fully mathematical representations of the vessel segments. However, the specialists, based on their diagnostic experience, commonly analyze additional domain-related information that is not represented in these mathematical metrics of reference. In this work, we propose a novel computational tortuosity metric that outperforms the mathematical metrics of reference also incorporating anatomical properties of the fundus image such as the distinction between arteries and veins, the distance to the optic disc, the distance to the fovea, and the vessel caliber. The evaluation of its prognostic performance shows that the integration of the anatomical factors provides an accurate tortuosity assessment that is more adjusted to the specialists’ perception.Instituto de Salud Carlos II; DTS18/00136Ministerio de Ciencia, Innovación y Universidades; DPI2015-69948-RMinisterio de Ciencia, Innovación y Universidades; RTI2018-095894-B-I00Xunta de Galicia; ED431G/01Xunta de Galicia; ED431C 2016-04
A comparative analysis of cylindrical CFS-PML ABC for finite volume simulations in the frequency domain
Limited genomic divergence between intraspecific forms of Culex pipiens under different ecological pressures
Abstract
Background: Divergent selection can be a major driver of ecological speciation. In insects of medical importance,
understanding the speciation process is both of academic interest and public health importance. In the West Nile
virus vector Culex pipiens, intraspecific pipiens and molestus forms vary in ecological and physiological traits.
Populations of each form appear to share recent common ancestry but patterns of genetic differentiation across
the genome remain unknown. Here, we undertook an AFLP genome scan on samples collected from both
sympatric and allopatric populations from Europe and the USA to quantify the extent of genomic differentiation
between the two forms.
Results: The forms were clearly differentiated but each exhibited major population sub-structuring between
continents. Divergence between pipiens and molestus forms from USA was higher than in both inter- and
intra-continental comparisons with European samples. The proportion of outlier loci between pipiens and molestus
(≈3 %) was low but consistent in both continents, and similar to those observed between sibling species of other
mosquito species which exhibit contemporary gene flow. Only two of the outlier loci were shared between
inter-form comparisons made within Europe and USA.
Conclusion: This study supports the molestus and pipiens status as distinct evolutionary entities with low genomic
divergence. The low number of shared divergent loci between continents suggests a relatively limited number of
genomic regions determining key typological traits likely to be driving incipient speciation and/or adaptation of
molestus to anthropogenic habitats
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