Consulta: subjectFacets:"SPM"
Registros recuperados: 2
Data/hora: 12/06/2024 16:24:09

Mercury in the Lot-Garonne River system (France): Sources, fluxes and anthropogenic component
Provedor de dados: 5
Autores: Schafer, J; Blanc, Gerard; Audry, S; Cossa, Daniel; Bossy, C.
Dissolved and particulate Hg fluxes in the Lot-Garonne-Gironde fluvial-estuarine system were obtained from observation of daily discharge and suspended particulate matter (SPM) concentrations. In addition to the measurements of the total dissolved (&lt; 0.45 gm) and particulate Hg (&gt; 0.45 gm), called HgTD and HgTp respectively, the dissolved inorganic Hg species (HgRD) were determined monthly. Geochemical background values for HgTp in sediments and SPM were similar to crustal values and to typical concentrations in SPM of non-contaminated river systems, respectively. The Riou Mort watershed already known as the origin of important historical polymetallic (e.g., Cd, Zn) pollution was identified as an important Hg point source. In the downstream Lot...
Tipo: Text
Palavras-chave: Lot; Garonne; SPM; River; Organic matter; Mercury.
Ano: 2006
URL: http://archimer.ifremer.fr/doc/2006/publication-1343.pdf

AUTOMATIC CLASSIFICATION OF STRUCTURAL MRI FOR DIAGNOSIS OF NEURODEGENERATIVE DISEASES
Provedor de dados: 37
Autores: DÍAZ,GLORIA; ROMERO,EDUARDO; HERNÁNDEZ-TAMAMES,JUAN ANTONIO; MOLINA,VICENTE; MALPICA,NORBERTO.
This paper presents an automatic approach which classifies structural Magnetic Resonance images into pathological or healthy controls. A classification model was trained to find the boundaries that allow to separate the study groups. The method uses the deformation values from a set of regions, automatically identified as relevant, in a process that selects the statistically significant regions of a t-test under the restriction that this significance must be spatially coherent within a neighborhood of 5 voxels. The proposed method was assessed to distinguish healthy controls from schizophrenia patients. Classification results showed accuracy between 74% and 89%, depending on the stage of the disease and number of training samples.
Tipo: Info:eu-repo/semantics/article
Palavras-chave: Neurodegenerative disease; Structural MRI; Pattern classification; SPM; VBM; DARTEL; Support vector machines.
Ano: 2010
URL: http://www.scielo.org.co/scielo.php?script=sci_arttext&pid=S0120-548X2010000300012