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See detailPro239Ser: a novel recessive mutation of the Pit-1 gene in seven Middle Eastern children with growth hormone, prolactin, and thyrotropin deficiency
Pernasetti, Flavia; Milner, Robert DG; al Ashwal, Abdullah A Z et al

in Journal of Clinical Endocrinology and Metabolism (1998), 83(6), 2079-83

Pit-1, a member of the POU-homeo domain protein family, is one of the transcription factors responsible for anterior pituitary development and pituitary-specific gene expression. Here, we describe seven ... [more ▼]

Pit-1, a member of the POU-homeo domain protein family, is one of the transcription factors responsible for anterior pituitary development and pituitary-specific gene expression. Here, we describe seven children with GH, PRL, and TSH deficiency from three, reportedly unrelated, Middle Eastern families, harboring a newly recognized Pro- > Ser recessive mutation in codon 239 of the Pit-1 gene. The mutated residue is located at the beginning of the second alpha-helix of the POU-homeodomain and is strictly conserved among all POU proteins. The Pro239Ser mutant binds DNA normally but is unable to stimulate transcription. [less ▲]

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See detailProanthocyanidins from Ribes nigrum 1 Isolation and structure determination
Tits, Monique ULg; Angenot, Luc ULg; Warin, Roger et al

Poster (1992, May)

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See detailProanthocyanidins from Ribes nigrum 2. TLC Analysis
Tits, Monique ULg; Poukens, Pascale; Angenot, Luc ULg

Poster (1990, July)

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See detailProanthocyanidins from Ribes nigrum leaves
Tits, Monique ULg; Poukens, Pascale; Angenot, Luc ULg

Poster (1992, May)

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See detailProanthocyanidins from Ribes nigrum leaves - Isolation and structure determination
Tits, Monique ULg; Angenot, Luc ULg; Warin, Roger et al

in Bulletin de Liaison Groupe Polyphenols (1992)

In summary, the antiinflammatory activity of Ribes nigrum leaves is mainly due to proanthocyanidins which are the major oligomers in the proanthocyanidins fraction

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See detailProanthocyanidins from Ribes nigrum leaves 1. Isolation and structure determination
Tits, Monique ULg; Angenot, Luc ULg; Warin, Roger et al

Poster (1990, July)

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See detailProanthocyanidins from Ribes nigrum leaves : TLC Analysis
Tits, Monique ULg; Poukens, Pascale; Angenot, Luc ULg

in Bulletin de Liaison - Groupe Polyphenols (1992)

In summary, the main oligomeric prodelphinidins of Ribes nigrum leaves can be identified by HPTLC; this method could also be utilized as a proanthocyanidin screen for determining their occurrence in other ... [more ▼]

In summary, the main oligomeric prodelphinidins of Ribes nigrum leaves can be identified by HPTLC; this method could also be utilized as a proanthocyanidin screen for determining their occurrence in other plants and for quantification of the major dimers. [less ▲]

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See detailProanthocyanidins, from Ribes Nigrum Leaves, Reduce Endothelial Adhesion Molecules Icam-1 and Vcam-1
Garbacki, Nancy ULg; Kinet, Marie; Nusgens, Betty ULg et al

in Journal of Inflammation (London, England) (2005), 2

BACKGROUND: The effects of proanthocyanidins (PACs), isolated from blackcurrant (Ribes nigrum L.) leaves, on neutrophil accumulation during inflammatory processes were investigated in vivo and in vitro ... [more ▼]

BACKGROUND: The effects of proanthocyanidins (PACs), isolated from blackcurrant (Ribes nigrum L.) leaves, on neutrophil accumulation during inflammatory processes were investigated in vivo and in vitro. METHODS: In vivo studies were performed using carrageenin-induced pleurisy in rats pre-treated with PACs. Exudate volume and PMNs accumulation were measured. Leukocyte cell adhesion molecules (LFA-1, Mac-1 and VLA-4) mobilization in circulating granulocytes were analysed by flow cytometry and endothelial cell adhesion molecules (ICAM-1 and VCAM-1) were detected by immunohistochemistry on lung sections. In vitro studies were conducted on endothelial LT2 cells, stimulated with TNF-alpha, to evaluate ICAM-1, IL-8 and VEGF mRNA expression upon PACs treatment. Data sets were examined by one-way analysis of variance (ANOVA) followed by a Scheffe post-hoc test. RESULTS: Pretreatment of the animals with PACs (10, 30 and 60 mg/kg) inhibited dose-dependently carrageenin-induced pleurisy in rats by reducing pleural exudate formation and PMNs infliltration. Leukocyte cell adhesion molecules mobilization was not down-regulated on granulocytes by PACs. Immunohistochemistry on lung sections showed a decreased production of endothelial cell adhesion molecules. In vitro experiments demonstrated that PACs were able to significantly inhibit ICAM-1 but not IL-8 and VEGF165 mRNA expression. Moreover, VEGF121 mRNA expression was dose-dependently enhanced. CONCLUSION: This study provides evidence to support the anti-inflammatory activity of proanthocyanidins is related to an inhibition of leukocyte infiltration which can be explained at least in part by a down-regulation of endothelial adhesion molecules, ICAM-1 and VCAM-1 and that these compounds are capable of modulating TNF-alpha-induced VEGF transcription. [less ▲]

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See detailThe proapoptotic C16-ceramide-dependent pathway requires the death-promoting factor Btf in colon adenocarcinoma cells.
Renert, Anne-Francoise; Leprince, Pierre ULg; Dieu, Marc et al

in Journal of Proteome Research (2009), 8(10), 4810-22

Ceramides are central molecules in sphingolipid metabolism. They are involved in the regulation of cancer-cell growth, differentiation, senescence and apoptosis. To better understand how these secondary ... [more ▼]

Ceramides are central molecules in sphingolipid metabolism. They are involved in the regulation of cancer-cell growth, differentiation, senescence and apoptosis. To better understand how these secondary messengers induce their biological effects, adenocarcinoma cells (HCT116) were treated with exogenous long-chain ceramides (C16-ceramide) in order to mimic endogenous sphingolipids. This treatment induced a decrease of cell viability partly due to apoptosis as shown by PARP cleavage and a decrease of pro-caspase 3. Two-dimensional differential in-gel electrophoresis (2D-DIGE) revealed the differential expression of 51 proteins in response to C16-ceramide. These proteins are notably involved in cell proliferation, apoptosis, protein transport and transcriptional regulation. Among them, the cell death-promoting factor Btf was found to be implicated in the apoptotic signal triggered by ceramide. In adenocarcinoma cells, Btf regulates apoptosis related proteins such as Mdm2, p53, BAX and pBcl-2 and thus plays an important role in the ceramide mediated cell death. These findings bring new insight into the proapoptotic ceramide-dependent signaling pathway. [less ▲]

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See detailA Probabilistic Approach to Integrating Multiple Cues in Visual Tracking
Du, Wei ULg; Piater, Justus ULg

in 10th European Conference on Computer Vision (2008)

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See detailA probabilistic approach to power system network planning under uncertainties
Vassena, Stefano; Mack, Philippe; Druet, Christophe et al

in Proceedings of the IEEE Bologna Power Tech Conference (2003)

This work proposes a methodology and a practical tool for the study of long-term network planning under uncertainties. In this approach the major external uncertainties during the planning horizon are ... [more ▼]

This work proposes a methodology and a practical tool for the study of long-term network planning under uncertainties. In this approach the major external uncertainties during the planning horizon are modeled as macroscenarios at different future time instants. On the other hand, the random nature of actual operating conditions is taken into account by using a probabilistic model of microscenarios based on past statistics. Massive Monte-Carlo simulations are used to generate and simulate a large number of scenarios and store the detailed results in a relational database. Data mining techniques are then applied to extract information from the database so as to rank scenarios and network reinforcements according to different criteria. [less ▲]

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See detailProbabilistic Assessment of the Lifetime of Low-Earth-Orbit Spacecraft: Uncertainty Characterization
Dell'Elce, Lamberto ULg; Arnst, Maarten ULg; Kerschen, Gaëtan ULg

in Journal of Guidance Control & Dynamics (2014)

Orbital lifetime estimation is a problem of great timeliness and importance in astrodynamics. In view of the stochastic nature of the thermosphere and of the complexity of drag modeling, any deterministic ... [more ▼]

Orbital lifetime estimation is a problem of great timeliness and importance in astrodynamics. In view of the stochastic nature of the thermosphere and of the complexity of drag modeling, any deterministic assessment of orbital lifetime is likely to be bound to failure. This is why the present paper performs uncertainty quantification of satellite orbital lifetime estimation. Specifically, this paper focuses on the probabilistic characterization of the dominant sources of uncertainty inherent to low-altitude satellites. Uncertainties in the initial state of the satellite and in the atmospheric drag force, as well as uncertainties introduced by modeling limitations associated with atmospheric density models, are considered. Mathematical statistics methods, in conjunction with mechanical modeling considerations, are used to infer the probabilistic characterization of these uncertainties from experimental data and atmospheric density models. This characterization step facilitates the application of uncertainty propagation and sensitivity analysis methods, which in turn allows gaining insight into the impact that these uncertainties have on the orbital lifetime. The proposed developments are illustrated using one CubeSat of the QB50 constellation. [less ▲]

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See detailA probabilistic characterization, propagation, and sensitivity analysis of uncertainties in a metal forming application
Arnst, Maarten ULg; Ponthot, Jean-Philippe ULg

Conference (2013, September 05)

In metal forming processes, after leaving the tooling, formed pieces of metal have a tendency to partially return to their original shape because of their elastic recovery. This phenomenon, referred to as ... [more ▼]

In metal forming processes, after leaving the tooling, formed pieces of metal have a tendency to partially return to their original shape because of their elastic recovery. This phenomenon, referred to as the springback, is quite complex and depends not only on material properties such as Young's modulus and yield stress but also on many process parameters such as sheet thickness and bending angles. The springback is difficult to predict and is a major quality concern in forming processes because when the springback is smaller or larger than expected, it can cause serious problems to subsequent assembly processes due to geometry mismatches. In this communication, we present a probabilistic analysis of a metal forming application. We consider the bending of a metal sheet with uncertain elastoplastic material properties. First, we use methods from mathematical statistics to obtain a probabilistic characterization of the elastoplastic material properties from data. Next, we map this probabilistic representation of the elastoplastic material properties into a probabilistic representation of the deformed shape of the metal sheet through a mechanical model implemented using the Metafor software. Finally, we conduct a stochastic sensitivity analysis to determine which elastoplastic material properties are most influential in driving uncertainty in the deformed shape after the springback. Our probabilistic analysis involves so called nonintrusive methods, that is, methods that can be implemented as wrappers around the Metafor software without requiring modification of its source code. Further, it includes recent methods for the propagation and sensitivity analysis of uncertainties characterized by arbitrary probability distributions that may exhibit statistical dependence. [less ▲]

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See detailProbabilistic design of power-system special stability controls
Wehenkel, Louis ULg; Lebrevelec, Cyril; Trotignon, Marc et al

in Control Engineering Practice (1999), 7(2), 183-194

A probabilistic approach to the design of power-system special stability controls is presented here. Using Monte-Carlo simulations, it takes into account all the potential causes of blackouts, slow and ... [more ▼]

A probabilistic approach to the design of power-system special stability controls is presented here. Using Monte-Carlo simulations, it takes into account all the potential causes of blackouts, slow and fast dynamics, and modeling uncertainties. A large number of scenarios are simulated in parallel by time-domain numerical integration, and the relevant parameters of the resulting system trajectories are stored in a database. Data-mining tools are used to identify the most important system weaknesses and possible improvements. The approach is tested on a large-scale study on the SouthÐEastern part of the extra-high-voltage system of Electricité de France. [less ▲]

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See detailProbabilistic Electromechanical Modeling of Nanostructures with Random Geometry
Arnst, Maarten ULg; Ghanem, Roger

in Journal of Computational and Theoretical Nanoscience (2009), 6(10), 2256-2272

This article is concerned with the probabilistic modeling of the electromechanical behavior of nanostructures to assess the effect of variations in geometrical characteristics on the device performance ... [more ▼]

This article is concerned with the probabilistic modeling of the electromechanical behavior of nanostructures to assess the effect of variations in geometrical characteristics on the device performance. The topological uncertainty that may be present in the position of the boundaries of nanostructures is accommodated by treating these boundaries as stochastic processes. It is shown how the probabilistic electromechanical models thus obtained can be discretized with the help of Galerkin projections on polynomial chaos expansions. An illustration is provided to demonstrate the proposed framework. [less ▲]

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See detailProbabilistic equivalence and stochastic model reduction in multiscale analysis
Arnst, Maarten ULg; Ghanem, Roger

in Computer Methods in Applied Mechanics & Engineering (2008), 197(43-44), 3584-3592

This paper presents a probabilistic upscaling of mechanics models. A reduced-order probabilistic model is constructed as a coarse-scale representation of a specified fine-scale model whose probabilistic ... [more ▼]

This paper presents a probabilistic upscaling of mechanics models. A reduced-order probabilistic model is constructed as a coarse-scale representation of a specified fine-scale model whose probabilistic structure can be accurately determined. Equivalence of the fine- and coarse-scale representations is identified such that a reduction in the requisite degrees of freedom can be achieved while accuracy in certain quantities of interest is maintained. A significant stochastic model reduction can a priori be expected if a separation of spatial and temporal scales exists between the fine- and coarse-scale representations. The upscaling of probabilistic models is subsequently formulated as an optimization problem suitable for practical computations. An illustration in stochastic structural dynamics is provided to demonstrate the proposed framework. [less ▲]

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See detailA Probabilistic Framework for 3D Visual Object Representation
Detry, Renaud ULg; Pugeault, Nicolas; Piater, Justus ULg

in IEEE Transactions on Pattern Analysis & Machine Intelligence (2009)

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See detailProbabilistic model for MEMS micro-beam resonance frequency made of polycrystalline linear anisotropic material
Lucas, Vincent ULg; Wu, Ling ULg; Arnst, Maarten ULg et al

Conference (2013, December)

In order to ensure the accuracy of MEMS vibrometers, the first resonance frequency should be predicted at the design phase. However, this prediction cannot be deterministic: there is a scatter in the ... [more ▼]

In order to ensure the accuracy of MEMS vibrometers, the first resonance frequency should be predicted at the design phase. However, this prediction cannot be deterministic: there is a scatter in the reached value resulting from the uncertainties involved in the manufacturing process. The purpose of this work is to take into account these uncertainties of the microstructure and to propagate them up to the micro-beam resonance frequency. The objective is a non-deterministic model that can be used since the design stage. Towards this end a 3-scales stochastic model predicting the resonance frequency of a micro-beam made of a polycrystalline linear anisotropic material is described. Uncertainties are related to the sizes and orientations of the grains. The first part of the problem is a homogenization procedure performed on a volume which is not representative, due to the small scale of the problem inherent in MEMS. The method is thus non-deterministic and a meso-scale probabilistic elasticity tensor is predicted. This stage is followed by a perturbation stochastic finite element procedure to propagate the meso-scale uncertainties to the macro-scale, leading to a probabilistic model of the resonance frequency of the MEMS. [less ▲]

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See detailA probabilistic model of the adhesive contact forces between rough surfaces in the MEMS stiction context
Hoang Truong, Vinh ULg; Wu, Ling ULg; Arnst, Maarten ULg et al

Conference (2014, June 26)

Stiction is a common failure mechanism in microelectromechanical systems (MEMS) in which two interacting bodies permanently adhere together. This problem is due to the comparability of adhesive surface ... [more ▼]

Stiction is a common failure mechanism in microelectromechanical systems (MEMS) in which two interacting bodies permanently adhere together. This problem is due to the comparability of adhesive surface forces (e.g. Van der Waals forces, capillary forces) and body forces in the MEMS context. To predict the adhesive contact forces coupled with stiction phenomenon, the combination of the Nayak statistical approach with the asperity-based theories is a common solution. However, this method contains some limitations due to the underlying assumptions: infinite size of the interacting rough surfaces and negligibility of asperity interactions. Furthermore, the Nayak solution suffers from a considerable dependency on the choice of the minimum wave length considered in the surface representation, which remains diXcult to select. The main goal of our research is to propose an improved method (i) which accounts for the Vnite size of the interacting surfaces, (ii) accounts for the uncertainties related to these surface topologies, (iii) in which the minimum wave length selection is physically based, and (iv) in which the validity of the asperity-based theories is demonstrated. From the topology measurements of MEMS samples, an analysis of the power spectral density function is carried out to determine the minimum relevant wave length for the problem of interest (here capillary stiction). We also show that at this scale of interest the asperity-based theories remain valid for polysilicon materials. Moreover, instead of considering inVnite surfaces as in the Nayak approach, a set of surfaces, whose sizes are representative of the MEMS structure, is generated based on the approximated power spectral density analysis and using the Monte Carlo method. From this description of the contacting surfaces, the adhesive contact forces can be evaluated by applying the asperity contact theories, leading to a probabilistic distribution of the adhesive contact forces. In addition, as the contact forces are rooted from the micro-scale adhesive forces, while their consequence, stiction, happens at the macro-scale of the considered device, the multi-scale nature of the phenomenon is accounted for. To predict this macro-scale behavior in a probabilistic form, the uncertainty quantiVcation process is coupled with a multiscale analysis. [less ▲]

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See detailProbabilistic Models of Visual Appearance For Object Identity, Class, and Pose Inference
Teney, Damien ULg

Doctoral thesis (2013)

The topic of object recognition is a central challenge of computer vision. In addition to being studied as a scientific problem in its own right, it also counts many direct practical applications. We ... [more ▼]

The topic of object recognition is a central challenge of computer vision. In addition to being studied as a scientific problem in its own right, it also counts many direct practical applications. We specifically consider robotic applications involving the manipulation, and grasping of everyday objects, in the typical situations that would be encountered by personal service robots. Visual object recognition, in the large sense, is then paramount to provide a robot the sensing capabilities for scene understanding, the localization of objects of interests and the planning of actions such as the grasping of such objects. This thesis presents a number of methods that tackle the related tasks of object detection, localization, recognition, and pose estimation in 2D images, of both specific objects and of object categories. We aim at providing techniques that are the most generally applicable, by considering those different tasks as different sides of a same problem, and by not focusing on a specific type of image information or image features. We first address the use of 3D models of objects for continuous pose estimation. We represent an object by a constellation of points, corresponding to potentially observable features, which serve to define a continuous probability distribution of such features in 3D. This distribution can be projected onto the image plane, and the task of pose estimation is then to maximize its “match” with the test image. Applied to the use of edge segments as observable features, the method is capable of localizing and estimating the pose of non-textured objects, while the probabilistic formulation offers an elegant way of dealing with uncertainty in the definition of the models, which can be learned from observations — as opposed to being available as hand-made CAD models. We also propose a method, framed in a similar probabilistic formulation, in order to obtain, or reconstruct such 3D models, using multiple calibrated views of the object of interest. A larger part of this thesis is then interested in exemplar-based recognition methods, using directly 2D example images for training, without any explicit 3D information. The appearance of objects is also defined as probability distributions of observable features, defined in a nonparametric manner through kernel density estimation, using image features from multiple training examples as supporting particles. The task of object localization is cast as the cross-correlation of distributions of features of the model and of the test image, which we efficiently solve through a voting-based algorithm. We then propose several techniques to perform continuous pose estimation, yielding a precision well beyond a mere classification among the discrete, trained viewpoints. One of the proposed method in this regard consists in a generative model of appearance, capable of interpolating the appearance of learned objects (or object categories), which then allows optimizing explicitly for the pose of the object in the test image. Our model of appearance, initially defined in general terms, is applied to the use of edge segments and of intensity gradients as image features. We are particularly interested in the use of gradients extracted at a coarse scale, and defined densely across images, as they can effectively represent shape as they capture the shading onto smooth non-textured surfaces. This allows handling some cases, common in robotic applications, of objects of primitive shapes with little texture and few discriminative details, which are challenging to recognize with most existing methods. The proposed contributions, which all integrate seamlessly in a same coherent framework, proved successful on a number of tasks and datasets. Most interestingly, we obtain performance on well-studied tasks of localization in clutter and pose estimation, well above baseline methods, often on par with or superior to state-of-the-art method individually designed for each of those specific tasks, whereas the proposed framework is similarly applied to a wide range of problems. [less ▲]

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