The Pirapama system in Pernambuco, Northeast Brazil, is one of the last major sources of adequate water supply in the state. A reservoir was constructed to store water for domestic, agricultural and industrial use. However, the formation of the reservoir pool flooded the marginal vegetation, starting an organic matter mineralization process, which resulted in eutrophication of the waters and depletion of dissolved oxygen concentrations, reaching anoxic conditions near the reservoir bed. This water body is also impacted by upstream inputs of domestic sewage, agricultural run-off and effluents from sugar-cane mills and distilleries. This work applied a one-dimensional vertical approach (CE-QUAL-R1) in order to simulate the formation of the reservoir pool, analysing the different operational alternatives. Eutrophication, anoxia and stratification potentials were studied. Water quality data obtained during 17 months are used to adjust the model rates and parameters. After model calibration-validation, hypothetical operational scenarios were simulated, taking into account different ways for water pumping (outtake elevations) and for discharging outflow excess (spillways or bottom outlet). Strong anoxic conditions (DO concentrations of less than 1.0 mg.L -1 ), associated to high eutrophication levels (high PO 4 and Chlorophyll-a concentrations), were found in all simulated scenarios. Regarding water quality conditions in the reservoir, the use of bottom outlet for reservoir water releases presented better results than the other operational alternatives, since it makes possible releasing anoxic waters from the deepest layers of the reservoir pool. However, in these conditions, the water quality downstream from the reservoir was severely compromised.
Segmentation methods have assumed an important role in image-based diagnosis of several cardiovascular diseases. Particularly, the segmentation of the boundary of the carotid artery is demanded in the detection and characterization of atherosclerosis and assessment of the disease progression. In this article, a fully automatic approach for the segmentation of the carotid artery boundary in Proton Density Weighted Magnetic Resonance Images is presented. The approach relies on the expansion of the lumen contour based on a distance map built using the gray-weighted distance relative to the centre of the identified lumen region in the image under analysis. Then, a Snake model with a modified weighted external energy based on the combination of a balloon force along with a Gradient Vector Flow-based external energy is applied to the expanded contour towards the correct boundary of the carotid artery. The average values of the Dice coefficient, Polyline distance, mean contour distance and centroid distance found in the segmentation of 139 carotid arteries were 0.83 ± 0.11, 2.70 ± 1.69 pixels, 2.79 ± 1.89 pixels and 3.44 ± 2.82 pixels, respectively. The segmentation results of the proposed approach were also compared against the ones obtained by related approaches found in the literature, which confirmed the outstanding performance of the new approach. Additionally, the proposed weighted external energy for the Snake model was shown to be also robust to carotid arteries with large thickness and weak boundary image edges.
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