12 research outputs found

    MICROSTRUCTURE AND CORROSION PERFORMANCE OF SILICA COATINGS ON ALUMINUM SURFACE PREPARED BY PLASMA ELECTROLYSIS TECHNIQUE

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    Abstract Silica phases were precipitated on aluminum surface by potentiostatic plasma electrolysis technique. Aqueous sodium silicate solutions with different concentrations were used for this purpose. SEM, EDS, XRD, surface profiles and polarization curves were used to study coatings properties. The results showed that the growth of the silica containing phases on aluminum surface was promoted by increasing sodium silicate content of the electrolyte. However, in very high concentration solutions, the morphology of the oxide films changed and the roughness of the coating increased. Moreover, the amorphous compounds were substituted for crystalline phases. Coated specimens showed high corrosion resistance in 3.5 % NaCl media

    Three-dimensional and two-dimensional relationships of gangliogenesis with folliculogenesis in mature mouse ovary: a Golgi–Cox staining approach

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    The present study was set out to investigate two-dimensional (2D) and three-dimensional (3D) evaluations of ovarian nervous network development and the structural relationship between folliculogenesis and gangliogenesis in mouse ovaries. Adult mice ovarian tissue samples were collected from follicular and luteal phases after cardiac perfusion. Ovarian samples were stained by a Golgi–Cox protocol. Following staining, tissues were serially sectioned for imaging. Neural filaments and ganglia were present in the ovaries. In both 2D and 3D studies, an increase in the number and area of ganglia was seen during the follicular growth. The same pattern was also seen in corpora lutea development. However, in some cases such as ratio of ganglia number to follicle area, the ratio of ganglia area to follicular area, 2D findings were different compared with the 3D results. 3D analysis of ovarian gangliogenesis showed the possible direct effect of them on folliculogenesis. Golgi–Cox staining was used in this study for 3D evaluation in non-brain tissue. The results of 3D analysis of the present study showed that, in some cases, the information provided by 2D analysis does not match the reality of ovarian neuronal function. This confirmed the importance of 3D analysis for evaluation of ovarian functio

    Characterising droughts in Central America with uncertain hydro-meteorological data

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    Central America is frequently affected by droughts that cause significant socio-economic and environmental problems. Drought characterisation, monitoring and forecasting are potentially useful to support water resource management. Drought indices are designed for these purposes, but their ability to characterise droughts depends on the characteristics of the regional climate and the quality of the available data. Local comprehensive and high-quality observational networks of meteorological and hydrological data are not available, which limits the choice of drought indices and makes it important to assess available datasets. This study evaluated which combinations of drought index and meteorological dataset were most suitable for characterising droughts in the region. We evaluated the standardised precipitation index (SPI), a modified version of the deciles index (DI), the standardised precipitation evapotranspiration index (SPEI) and the effective drought index (EDI). These were calculated using precipitation data from the Climate Hazards Group Infra-Red Precipitation with Station (CHIRPS), the CRN073 dataset, the Climate Research Unit (CRU), ECMWF Reanalysis (ERA-Interim) and a regional station dataset, and temperature from the CRU and ERA-Interim datasets. The gridded meteorological precipitation datasets were compared to assess how well they captured key features of the regional climate. The performance of all the drought indices calculated with all the meteorological datasets was then evaluated against a drought index calculated using river discharge data. Results showed that the selection of database was more important than the selection of drought index and that the best combinations were the EDI and DI calculated with CHIRPS and CRN073. Results also highlighted the importance of including indices like SPEI for drought assessment in Central America.Universidad de Costa Rica/[805-B0-810]/UCR/Costa RicaUniversidad de Costa Rica/[805-A9-532]/UCR/Costa RicaUniversidad de Costa Rica/[805-B3-600]/UCR/Costa RicaUniversidad de Costa Rica/[805-B0-065]/UCR/Costa RicaUniversidad de Costa Rica/[805-B3-413]/UCR/Costa RicaUniversidad de Costa Rica/[805-B4-227]/UCR/Costa RicaUniversidad de Costa Rica/[805-B4-228]/UCR/Costa RicaUniversidad de Costa Rica/[805-B5-295]/UCR/Costa RicaUppsala University/[54100006]//SueciaMarie Curie Intra-European Fellowship/[No.329762]//EuropaUCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Básicas::Centro de Investigaciones Geofísicas (CIGEFI)UCR::Vicerrectoría de Docencia::Ciencias Básicas::Facultad de Ciencias::Escuela de Físic
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