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See detailPromouvoir la santé à l'école
Vandoorne, Chantal ULg; Melen, Geoffroy ULg

Learning material (2009)

Detailed reference viewed: 48 (26 ULg)
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See detailPromouvoir le BIEN-ÊTRE et la réussite scolaire
Vandoorne, Chantal ULg

Conference (2012, November 22)

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See detailPromouvoir les dialectes à l'école en 2009 ?
Baiwir, Esther ULg

in Wallonnes : Chronique de la Société de Langue et de Littérature Wallonnes (2009), 4

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See detailPromouvoir les pédagogies actives comme soutien à la pratique réflexive et à l'apprentissage en profondeur
Jouquan, Jean; VIERSET, Viviane ULg; Jaffrelot, Morgan et al

in Parent, Florence; Jouquan, Jean (Eds.) Penser la formation des professionnels de la santé (2013)

Detailed reference viewed: 39 (4 ULg)
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See detailPromouvoir un style de vie actif chez les jeunes : place et rôle des différents opérateurs de l’activité physique
Cloes, Marc ULg

Conference given outside the academic context (2007)

Detailed reference viewed: 7 (1 ULg)
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See detailPROMPT New means to PROMote Pedestrian Traffic in cities
Rauhala, Kari; Martincigh, Lucia; Hüsler, Willi et al

Report (2005)

The main objective of the PROMPT project was to develop new innovative tools and solutions to improve the conditions of walking in cities. Their scope ranges from the urban level to the detailed street ... [more ▼]

The main objective of the PROMPT project was to develop new innovative tools and solutions to improve the conditions of walking in cities. Their scope ranges from the urban level to the detailed street level. They are aimed at problem identification, design and planning as well as at the implementation of considered measures in widely different situations. [less ▲]

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See detailPrompting reflection through annotations in formal online learning
Verpoorten, Dominique ULg; Westera, W; Specht, M

in Reinhardt, R; Ullmann, U; Scott, P (Eds.) et al Proceedings of the 1st European Workshop on Awareness and Reflection in Learning Networks (ARNets11) (2011, September 21)

This article explores the role of annotations as reflection amplifiers while studying in an Open Educational Resources distance course. A controlled experiment reveals that the treatment groups using ... [more ▼]

This article explores the role of annotations as reflection amplifiers while studying in an Open Educational Resources distance course. A controlled experiment reveals that the treatment groups using frequent and local annotations did not perform better at the test. However, measures within the treatments exhibit a moderate but significant improvement of the mark in the group composed of high annotators. [less ▲]

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See detailProneural bHLH and Brn proteins coregulate a neurogenic program through cooperative binding to a conserved DNA motif.
Castro, Diogo S; Skowronska-Krawczyk, Dorota; Armant, Olivier et al

in Developmental Cell (2006), 11(6), 831-44

Proneural proteins play a central role in vertebrate neurogenesis, but little is known of the genes that they regulate and of the factors that interact with proneural proteins to activate a neurogenic ... [more ▼]

Proneural proteins play a central role in vertebrate neurogenesis, but little is known of the genes that they regulate and of the factors that interact with proneural proteins to activate a neurogenic program. Here, we demonstrate that the proneural protein Mash1 and the POU proteins Brn1 and Brn2 interact on the promoter of the Notch ligand Delta1 and synergistically activate Delta1 transcription, a key step in neurogenesis. Overexpression experiments in vivo indicate that Brn2, like Mash1, regulates additional aspects of neurogenesis, including the division of progenitors and the differentiation and migration of neurons. We identify by in silico screening a number of additional candidate target genes, which are recognized by Mash1 and Brn proteins through a DNA-binding motif similar to that found in the Delta1 gene and present a broad range of activities. We thus propose that Mash1 synergizes with Brn factors to regulate multiple steps of neurogenesis. [less ▲]

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See detailPronominal reference in Dutch: a corpus-based study of resemanticisation
De Vos, Lien ULg

E-print/Working paper (2012)

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See detailPronominale hersemantisering in het Nederlandse genussysteem
De Vos, Lien ULg

Master's dissertation (2008)

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See detailPronostic des infarctus myocardiques de petite taille
Pierard, Luc ULg; Dubois, Christophe ULg; Albert, Adelin ULg et al

Poster (1987, April)

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Peer Reviewed
See detailPronostic des patients récupérant du coma
Bruno, Marie-Aurélie ULg; Ledoux, Didier; Vanhaudenhuyse, Audrey ULg et al

in Schnakers, Caroline; Laureys, Steven (Eds.) Coma et états de conscience altérée (2011)

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See detailPronostic et traitement de la decompensation cardiaque en 1987.
Pierard, Luc ULg

in Revue medicale de Liege (1987), 42(9), 396-402

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See detailPronostic Implications of semi-supine stress echocardiography for evaluation of chest pain in the emergency room
LANCELLOTTI, Patrizio ULg; HOFFER, E; APPELTANS, H et al

in European Journal of Echocardiography (1999)

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See detailPronostic value of echocardiographic and Doppler parameters in colic horses with endotoxic shock: A preliminary study
Borde, Laura ULg; Amory, Hélène ULg; Leroux, Aurélia ULg et al

Conference (2011, February 05)

Endotoxemia is the first mortality cause in equine intensive care. In humans with septic shock, some echocardiographic indicators are used to predict the efficiency of fluid resuscitation and outcome ... [more ▼]

Endotoxemia is the first mortality cause in equine intensive care. In humans with septic shock, some echocardiographic indicators are used to predict the efficiency of fluid resuscitation and outcome, allowing an early-goal-directed therapy. Echocardiography has never been investigated for this indication in horses. The aim of this study was to assess the prognosis value of echocardiographic and Doppler parameters of left ventricular (LV) function in horses with severe endotoxic shock. Twenty-one horses admitted to the clinic for colic with clinical signs of severe endotoxic shock underwent Doppler echocardiographic examination. LV echocardiographic and Doppler parameters were compared between the survivors (n=6) and the non-survivors (n=15) horses using a multivariable ANOVA analysis. The pre-ejection period to ejection time ratio (PEP/ET) of the Doppler aortic flow was significantly higher in the non-survivors than in the survivors group. All other measured parameters (including heart rate and end-diastolic-volume) were not significantly different between the groups. Doppler parameters of left ventricular function are subject to high variability and low repeatability in horses. This might explain that most variables were not significantly different between the two groups. Moreover, the number of investigated horses was limited, especially in the survivors group. However, with comparable HR and LV preload, a higher PEP/ET suggested a more compromised systolic dysfunction in the non-survivors. PEP/ET is often considered to be one of the best indicators of systolic function in horses and its measurement might therefore be useful in indicating the need for inotropic support in the management of horses with endotoxic shock. [less ▲]

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See detailPRoNTo: Pattern Recognition for Neuroimaging Toolbox
Schrouff, Jessica ULg; Rosa, Maria Joao; Rondina, Jane et al

Software (2012)

PRoNTo (Pattern Recognition for Neuroimaging Toolbox) is a software toolbox based on pattern recognition techniques for the analysis of neuroimaging data. Statistical pattern recognition is a field within ... [more ▼]

PRoNTo (Pattern Recognition for Neuroimaging Toolbox) is a software toolbox based on pattern recognition techniques for the analysis of neuroimaging data. Statistical pattern recognition is a field within the area of machine learning which is concerned with automatic discovery of regularities in data through the use of computer algorithms, and with the use of these regularities to take actions such as classifying the data into different categories. In PRoNTo, brain scans are treated as spatial patterns and statistical learning models are used to identify statistical properties of the data that can be used to discriminate between experimental conditions or groups of subjects (classification models) or to predict a continuous measure (regression models). PRoNTo aims to facilitate the interaction between machine learning and neuroimaging communities. On one hand, the machine learning community can contribute to the toolbox with novel machine learning models. On the other hand, the toolbox provides a variety of tools for the neuroscience and clinical neuroscience communities, enabling them to ask new questions that cannot be easily investigated using existing software and analysis tools. PRoNTo is distributed for free as copyright software under the terms of the GNU General Public License as published by the Free Software Foundation. The development of the toolbox has been supported by the PASCAL Harvest framework and The Wellcome Trust. [less ▲]

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See detailPRoNTo: Pattern Recognition for Neuroimaging Toolbox
Schrouff, Jessica ULg; Rosa, Maria Joao; Rondina, Jane et al

in Neuroinformatics (2013)

In the past years, mass univariate statistical analyses of neuroimaging data have been complemented by the use of multivariate pattern analyses, especially based on machine learning models. While these ... [more ▼]

In the past years, mass univariate statistical analyses of neuroimaging data have been complemented by the use of multivariate pattern analyses, especially based on machine learning models. While these allow an increased sensitivity for the detection of spatially distributed effects compared to univariate techniques, they lack an established and accessible software framework. The goal of this work was to build a toolbox comprising all the necessary functionalities formultivariate analyses of neuroimaging data, based on machine learning models. The “Pattern Recognition for Neuroimaging Toolbox” (PRoNTo) is open-source, cross-platform, MATLAB-based and SPM compatible, therefore being suitable for both cognitive and clinical neuroscience research. In addition, it is designed to facilitate novel contributions from developers, aiming to improve the interaction between the neuroimaging and machine learning communities. Here, we introduce PRoNTo by presenting examples of possible research questions that can be addressed with the machine learning framework implemented in PRoNTo, and cannot be easily investigated with mass univariate statistical analysis. [less ▲]

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See detailPRoNTo: Pattern Recognition for Neuroimaging Toolbox
Schrouff, Jessica ULg; Rosa, Maria J; Rondina, Jane et al

Poster (2012, June 12)

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See detailA proof of concept of Iterative DSM improvement through SAR scene simulation
De Rauw, Dominique ULg

in ISPRS Journal of Photogrammetry & Remote Sensing (2009), XXXVIII(3/W4), 121-126

In Very High Resolution (VHR) Synthesis Aperture Radar (SAR) context, very fine and accurate georeferencing and geoprojection processes are required. Both operations are only applicable if accurate local ... [more ▼]

In Very High Resolution (VHR) Synthesis Aperture Radar (SAR) context, very fine and accurate georeferencing and geoprojection processes are required. Both operations are only applicable if accurate local heights are known. 3D information may be derived from SAR interferometry (InSAR), But in VHR context, InSAR reveals to be inaccurate mostly due to phase unwrapping problems and to phase/height noise. Generated InSAR Digital Surface Models (DSM) can only be considered as a first good approximation of the observed surface. Therefore, we proposed to start from the InSAR DSM, to project it on ground range on a given datum, to model the observed scene using this projected DSM, then to simulate in slant range the intensity image issued from this structure model. Comparison between simulated and observed intensity image can then be used as a criterion to modify and improve the considered underlying DSM. In this paper, we present the different steps of the proposed approach and results obtained so far, showing that the proposed process can be run iteratively to modify the DSM and reach a stable solution. [less ▲]

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