Usefulness of Procalcitonin Levels for Predicting the Microbiological Orientation in Patients with Sepsis.

The main objective of the study was to verify whether levels of procalcitonin (PCT) could guide us toward determining the type of bacteria causing the sepsis and to identify the discriminatory cut-off point in the first urgent laboratory test. This study is a single center retrospective analysis that includes 371 patients with a mean age of 71.7 ± 15.

Modeling the two- and three-dimensional displacement field in Lorca, Spain, subsidence and the global implications.

Land subsidence associated with overexploitation of aquifers is a hazard that commonly affects large areas worldwide. The Lorca area, located in southeast Spain, has undergone one of the highest subsidence rates in Europe as a direct consequence of long-term aquifer exploitation. Previous studies carried out on the region assumed that the ground deformation retrieved from satellite radar interferometry corresponds only to vertical displacement.

Assessment of Data Fusion Algorithms for Earth Observation Change Detection Processes.

In this work a parametric multi-sensor Bayesian data fusion approach and a Support Vector Machine (SVM) are used for a Change Detection problem. For this purpose two sets of SPOT5-PAN images have been used, which are in turn used for Change Detection Indices (CDIs) calculation. For minimizing radiometric differences, a methodology based on zonal "invariant features" is suggested.

Evaluation of a change detection methodology by means of binary thresholding algorithms and informational fusion processes.

Landcover is subject to continuous changes on a wide variety of temporal and spatial scales. Those changes produce significant effects in human and natural activities. Maintaining an updated spatial database with the occurred changes allows a better monitoring of the Earth's resources and management of the environment.

Characterizing olive grove canopies by means of ground-based hemispherical photography and spaceborne RADAR data.

One of the main strengths of active microwave remote sensing, in relation to frequency, is its capacity to penetrate vegetation canopies and reach the ground surface, so that information can be drawn about the vegetation and hydrological properties of the soil surface. All this information is gathered in the so called backscattering coefficient (σ(0)). The subject of this research have been olive groves canopies, where which types of canopy biophysical variables can be derived by a specific optical sensor and then integrated into microwave scattering models has been investigated.