Radar shadow detection in SAR images using DEM and projections

Synthetic aperture radar (SAR) images are widely used in target recognition tasks nowadays. In this letter, we propose an automatic approach for radar shadow detection and extraction from SAR images utilizing geometric projections along with the digital elevation model (DEM) which corresponds to the given geo-referenced SAR image. First, the DEM is rotated into the radar geometry so that each row would match that of a radar line of sight. Next, we extract the shadow regions by processing row by row until the image is covered fully. We test the proposed shadow detection approach on different DEMs and a simulated 1D signals and 2D hills and volleys modeled by various variance based Gaussian functions. Experimental results indicate the proposed algorithm produces good results in detecting shadows in SAR images with high resolution.Comment: 10 pages, 6 figure

A Brazilian anuran (Hylodes magalhaesi: Leptodactylidae) infected by Batrachochytrium dendrobatidis: a conservation concern

Several studies have associated the chytrid fungus Batrachochytrium dendrobatidis with anuran population declines worldwide. To date, the fungus has been found in Africa, the Americas, Australia, and Europe. However, it has never been reported to occur in the Atlantic forest or Brazil. Based on morphological, histological, and molecular data, we encountered evidence of B. dendrobatidis infection in a high-altitude stream-dwelling Brazilian anuran species, Hylodes magalhaesi (Leptodactylidae). One population (Municipality of Camanducaia, State of Minas Gerais) was surveyed from 2001 to 2005. Tadpoles lacking teeth were observed and collected in 2004. Histological and molecular analyses identified infection by B. dendrobatidis. Although infected tadpoles seem nowadays to co-exist with the disease, our results are alarming due to the highly endangered situation of the Brazilian Atlantic forest and its fauna. Effects of the chytrid infection on the studied population are still unknown. Further investigations are needed to provide information on its distribution in relation to other populations of H. magalhaesi

ESTIMATION RADAR DES PRECIPITATIONS PAR LA METHODE DES AIRES FRACTIONNELLES

RESUME Ce papier porte sur l'estimation de la moyenne des précipitations dans la région de Sidi-Aich (Algérie) à partir des données radar. Pour ce faire, nous utilisons la méthode des aires fractionnelles (MAF), basée sur le concept que l'aire occupée par la pluie d'intensité supérieure à un seuil donné dans une région est une mesure de l'intensité de pluie moyenne dans cette région. Pour une utilisation adéquate et optimale du radar, nous avons effectué au préalable son étalonnage en utilisant la méthode d'approche probabiliste. Notre base de données est constituée d'images prises par le radar de Sétif au cours du mois de Janvier 2001 et de données au sol collectées durant la même période. Le résultat d'étalonnage du radar est en adéquation avec l'expression proposée pour les climats tempérés. L'application de la MAF montre que le seuil le plus adapté pour l'application de cette technique varie autour de la moyenne climatologique des précipitations dans la zone d'étude. L'erreur d'estimation varie entre 3% et 20%, selon les fenêtres d'analyse et les seuils choisis. De même, nous avons constaté que la constante climatologique est fortement liée au type de nuages c'est-à-dire stratiforme ou convectifs. Mots clés : radar météorologique; approche probabiliste; réflectivité radar; précipitations; aire fractionnelle

Characterization of polymorphic microsatellite markers for the Neotropical leaf-frog Phyllomedusa burmeisteri and cross-species amplification

Twelve polymorphic tetranucleotide microsatellite loci were isolated and characterized for the leaf-frog Phyllomedusa burmeisteri, an endemic species of the Brazilian Atlantic forest. These loci were screened in 25 individuals from two populations of the Minas Gerais State (Carangola and Juiz de Fora). The number of alleles per locus ranged from 3 to 16 (mean = 8). Observed and expected heterozygosities ranged from 0.25 to 0.92 and 0.56 to 0.92, respectively. Evidence for both the presence of null alleles and Hardy-Weinberg equilibrium deviations were found in loci Phybu4, Phybu17, and Phybu21. Genotypic disequilibrium for each pair of loci across populations was not significant. Cross-species amplification was successful for 11 of the 12 developed loci for the sister-species, P. bahiana. These microsatellites will be important for future fine-scale population structure analyses

Quasienergy spectra of a charged particle in planar honeycomb lattices

The low energy spectrum of a particle in planar honeycomb lattices is conical, which leads to the unusual electronic properties of graphene. In this letter we calculate the quasienergy spectra of a charged particle in honeycomb lattices driven by a strong AC field, which is of fundamental importance for its time-dependent dynamics. We find that depending on the amplitude, direction and frequency of external field, many interesting phenomena may occur, including band collapse, renormalization of velocity of ``light'', gap opening etc.. Under suitable conditions, with increasing the magnitude of the AC field, a series of phase transitions from gapless phases to gapped phases appear alternatively. At the same time, the Dirac points may disappear or change to a line. We suggest possible realization of the system in Honeycomb optical lattices.Comment: 4+ pages, 5 figure

Efficacy and safety of vandetanib in progressive and symptomatic medullary thyroid Cancer: Post hoc analysis from the ZETA trial

PURPOSE We conducted a post hoc analysis of the vandetanib phase III trial involving patients with advanced medullary thyroid cancer (MTC) to assess the efficacy and safety of vandetanib in patients with progressive and symptomatic MTC. The primary objective of the analysis was to determine progression-free survival (PFS) of these patients. PATIENTS AND METHODS Eligible patients from the ZETA trial were divided into 4 disease severity subgroups: progression and symptoms, symptoms only, progression only, and no progression and no symptoms assessed at baseline. PFS, determined from objective tumor measurements performed by the local investigator, overall survival (OS), time to worsening of pain (TWP), and objective response rate (ORR) were evaluated. RESULTS Of the 331 patients in this trial, 184 had symptomatic and progressive disease at baseline. In this subgroup, results were similar in magnitude to those observed in the overall trial for PFS (hazard ratio [HR], 0.43; 95% CI, 0.28 to 0.64; P, .0001), OS (HR, 1.08; 95% CI, 0.72 to 1.61; P 5 .71), and TWP (HR, 0.67; 95% CI, 0.43 to 1.04; P 5 .07), and the observed adverse events were consistent with the known safety profile of vandetanib. In this subgroup, the ORR was 37% in the treatment arm versus 2% in the placebo arm. CONCLUSION Vandetanib demonstrated clinical benefit—specifically, increased PFS—in patients with symptomatic and progressive MTC

Sensitivity of non-conditional climatic variables to climate-change deep uncertainty using Markov Chain Monte Carlo simulation

This is the final version. Available on open access from Nature Research via the DOI in this recordData availability: The data that support the findings of this study are available from the corresponding author upon reasonable request.There is substantial evidence suggesting climate change is having an adverse impact on the world's water resources. One must remember, however, that climate change is beset by uncertainty. It is therefore meaningful for climate change impact assessments to be conducted with stochastic-based frameworks. The degree of uncertainty about the nature of a stochastic phenomenon may differ from one another. Deep uncertainty refers to a situation in which the parameters governing intervening probability distributions of the stochastic phenomenon are themselves subjected to some degree of uncertainty. In most climatic studies, however, the assessment of the role of deep-uncertain nature of climate change has been limited. This work contributes to fill this knowledge gap by developing a Markov Chain Monte Carlo (MCMC) analysis involving Bayes' theorem that merges the stochastic patterns of historical data (i.e., the prior distribution) and the regional climate models' (RCMs') generated climate scenarios (i.e., the likelihood function) to redefine the stochastic behavior of a non-conditional climatic variable under climate change conditions (i.e., the posterior distribution). This study accounts for the deep-uncertainty effect by evaluating the stochastic pattern of the central tendency measure of the posterior distributions through regenerating the MCMCs. The Karkheh River Basin, Iran, is chosen to evaluate the proposed method. The reason for selecting this case study was twofold. First, this basin has a central role in ensuring the region's water, food, and energy security. The other reason is the diverse topographic profile of the basin, which imposes predictive challenges for most RCMs. Our results indicate that, while in most seasons, with the notable exception of summer, one can expect a slight drop in the temperature in the near future, the average temperature would continue to rise until eventually surpassing the historically recorded values. The results also revealed that the 95% confidence interval of the central tendency measure of computed posterior probability distributions varies between 0.1 and 0.3 °C. The results suggest exercising caution when employing the RCMs' raw projections, especially in topographically diverse terrain.Iran National Science Foundation (INSF

Avaliação da resistência do maracujazeiro à fusariose em condições de campo.

A produção nacional de maracujá é de cerca de 714 mil toneladas, sendo a região Nordeste responsável por aproximadamente 73% dessa produção. Apesar desse destaque, a produtividade média nacional é baixa, comparada ao potencial de produção da cultura