Search results for " observation"

Spontaneous Meckel's cave hematoma: A rare cause of trigeminal neuralgia

2015

Background: The most common etiology of classic trigeminal neuralgia (TN) is vascular compression. However, other causes must be considered. Among these, spontaneous hematoma of the Meckel′s cave (MC) causing symptomatic TN is very rare. Case Description: We present the case of a 60-year-old woman with a 2-month history of left TN and diplopia. Neuroradiological examinations revealed a well-defined hematoma in the left MC. The patient underwent surgical decompression with a progressive neurological improvement. Conclusion: Despite the number of lesions potentially affecting the MC, spontaneous hemorrhage is rare but should be taken into account in the differential diagnosis.

Real-world evidence from a European cohort study of patients with treatment resistant depression: Baseline patient characteristics: Patient character…

2021

Background: Treatment resistant depression (TRD; failure to respond to ≥2 treatments) affects ~20% of patients with major depressive disorder (MDD). Real-world data could help describe patient characteristics and TRD disease burden, to assess the unmet needs of TRD patients in Europe. Methods: This observational study collected data from adults with moderate to severe TRD initiating a new treatment for depression, according to local standards of care. At baseline, socio-demographic characteristics, medical history, prior and current treatments were recorded. Disease severity, health-related quality of life (HRQoL), functionality and productivity were assessed. Results: Overall, 411 eligible…

English pronunciation teaching in Finland

2013

Directly Observed Physical Activity among 3-Year-Olds in Finnish Childcare

2014

The main purpose of the study was to determine 3-year-olds’ physical activity levels and how these vary across season, gender, time of day, location, and the physical and social environment in childcare settings in Finland. A modified version of the Observational System for Recording Physical Activity in Children-Preschool (OSRAC-P) was used to measure physical activity levels and contextual variables (e.g., group composition, prompts) of children attending childcare centres. In total, 81 children (42 boys and 39 girls) were observed in autumn and in winter. Three-level linear regression analyses were used to assess differences between the seasons in the association between the context vari…

Post-fire practices benefits on vegetation recovery and soil conservation in a Mediterranean area

2021

Financiado para publicación en acceso aberto: Universidade da Coruña/CISUG. [Abstract] Post-fire practices (PFP) aim to reduce soil erosion and favour vegetation recovery, but their effectiveness is spatially heterogeneous and under debate because of the economic and environmental costs. This study evaluates the different changes (Δ) of canopy cover (CC), sediment connectivity (SC) and local topography in four areas affected by the Pinet fire in eastern Spain (August 8th, 2018) and managed with: totally burnt with tree removal and long log erosion barriers (LEBs) (Pinet-1), partially burnt without PFP (Pinet-2), totally burnt with tree removal and short LEBs (Pinet-3), and totally burnt wit…

A Survey of Active Learning for Quantifying Vegetation Traits from Terrestrial Earth Observation Data

2021

The current exponential increase of spatiotemporally explicit data streams from satellite-based Earth observation missions offers promising opportunities for global vegetation monitoring. Intelligent sampling through active learning (AL) heuristics provides a pathway for fast inference of essential vegetation variables by means of hybrid retrieval approaches, i.e., machine learning regression algorithms trained by radiative transfer model (RTM) simulations. In this study we summarize AL theory and perform a brief systematic literature survey about AL heuristics used in the context of Earth observation regression problems over terrestrial targets. Across all relevant studies it appeared that…

Vegetation Types Mapping Using Multi-Temporal Landsat Images in the Google Earth Engine Platform

2021

Vegetation Types (VTs) are important managerial units, and their identification serves as essential tools for the conservation of land covers. Despite a long history of Earth observation applications to assess and monitor land covers, the quantitative detection of sparse VTs remains problematic, especially in arid and semiarid areas. This research aimed to identify appropriate multi-temporal datasets to improve the accuracy of VTs classification in a heterogeneous landscape in Central Zagros, Iran. To do so, first the Normalized Difference Vegetation Index (NDVI) temporal profile of each VT was identified in the study area for the period of 2018, 2019, and 2020. This data revealed strong se…

Comparative analysis of atmospheric radiative transfer models using the Atmospheric Look-up table Generator (ALG) toolbox (version 2.0)

2019

Abstract. Atmospheric radiative transfer models (RTMs) are software tools that help researchers in understanding the radiative processes occurring in the Earth's atmosphere. Given their importance in remote sensing applications, the intercomparison of atmospheric RTMs is therefore one of the main tasks used to evaluate model performance and identify the characteristics that differ between models. This can be a tedious tasks that requires good knowledge of the model inputs/outputs and the generation of large databases of consistent simulations. With the evolution of these software tools, their increase in complexity bears implications for their use in practical applications and model interco…

A Survey on Gaussian Processes for Earth-Observation Data Analysis: A Comprehensive Investigation

2016

Gaussian processes (GPs) have experienced tremendous success in biogeophysical parameter retrieval in the last few years. GPs constitute a solid Bayesian framework to consistently formulate many function approximation problems. This article reviews the main theoretical GP developments in the field, considering new algorithms that respect signal and noise characteristics, extract knowledge via automatic relevance kernels to yield feature rankings automatically, and allow applicability of associated uncertainty intervals to transport GP models in space and time that can be used to uncover causal relations between variables and can encode physically meaningful prior knowledge via radiative tra…

Clasificación de usos del suelo a partir de imágenes Sentinel-2

2017

[EN] Sentinel-2 (S2), a new ESA satellite for Earth observation, accounts with 13 bands which provide high-quality radiometric images with an excellent spatial resolution (10 and 20 m) ideal for classification purposes. In this paper, two objectives have been addressed: to determine the best classification method for S2, and to quantify its improve-ment with respect to the SPOT operational mission. To do so, four classifiers (LDA, RF, Decision Trees, K-NN) have been selected and applied to two different agricultural areas located in Valencia (Spain) and Buenos Aires (Argentina). All classifiers were tested using, on the one hand, all the S2 bands and, on the other hand, only selecting those…