980 resultados para Proximal Point Algorithm


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This paper proposes an automatic hand detection system that combines the Fourier-Mellin Transform along with other computer vision techniques to achieve hand detection in cluttered scene color images. The proposed system uses the Fourier-Mellin Transform as an invariant feature extractor to perform RST invariant hand detection. In a first stage of the system a simple non-adaptive skin color-based image segmentation and an interest point detector based on corners are used in order to identify regions of interest that contains possible matches. A sliding window algorithm is then used to scan the image at different scales performing the FMT calculations only in the previously detected regions of interest and comparing the extracted FM descriptor of the windows with a hand descriptors database obtained from a train image set. The results of the performed experiments suggest the use of Fourier-Mellin invariant features as a promising approach for automatic hand detection.

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L'algorisme de McLachlan per a l'alineament de dos conjunts de coordenades atòmiques és interpretat sota l'òptica de l'Anàlisi Multivariant, que posa de manifest que el plantejament d'aquest problema és equivalent al de l'anàlisi de Procrustes i que la solució proposada per Kabsch és anàloga a la de Sibson, desenvolupada independentment

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We investigated whether a single blood measurement using the minimally invasive technique of a finger prick to draw a blood sample of 5 µl (to yield a dried blood spot (DBS)) is suitable for the assessment of flurbiprofen (FLB) metabolic ratio (MR). Ten healthy volunteers who had been genotyped for CYP2C9 were recruited as subjects. They received FLB alone in session 1 and FLB with fluconazole in session 2. In session 3, the subjects were pretreated for 4 days with rifampicin and received FLB with the last dose of rifampicin on day 5. Plasma and DBS samples were obtained between 0 and 8 h after FLB administration, and urine was collected during the 8 h after administration. The pharmacokinetic profiles of the drugs were comparable in DBS and plasma. FLB's apparent clearance values decreased by 35% in plasma and DBS during session 2 and increased by 75% in plasma and by 30% in DBS during session 3. Good correlations were observed between MRs calculated from urine, plasma, and DBS samples.

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This report describes a short-term study undertaken to investigate the potential for using dense three-dimensional (3D) point clouds generated from light detection and ranging (LIDAR) and photogrammetry to assess roadway roughness. Spatially continuous roughness maps have potential for the identification of localized roughness features, which would be a significant improvement over traditional profiling methods. This report specifically illustrates the use of terrestrial laser scanning (TLS) and photogrammetry using a process known as structure from motion (SFM) to acquire point clouds and illustrates the use of these point clouds in evaluating road roughness. Five roadway sections were chosen for scanning and testing: three gravel road sections, one portland cement concrete (PCC) section, and one asphalt concrete (AC) section. To compare clouds obtained from terrestrial laser scanning and photogrammetry, the coordinates of the clouds for the same section on the same date were matched using open source computer code. The research indicates that the technologies described are very promising for evaluating road roughness. The major advantage of both technologies is the large amount of data collected, which allows the evaluation of the full surface. Additional research is needed to further develop the use of dense 3D point clouds for roadway assessment.

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In this paper, a hybrid simulation-based algorithm is proposed for the StochasticFlow Shop Problem. The main idea of the methodology is to transform the stochastic problem into a deterministic problem and then apply simulation to the latter. In order to achieve this goal, we rely on Monte Carlo Simulation and an adapted version of a deterministic heuristic. This approach aims to provide flexibility and simplicity due to the fact that it is not constrained by any previous assumption and relies in well-tested heuristics.

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This paper proposes an automatic hand detection system that combines the Fourier-Mellin Transform along with other computer vision techniques to achieve hand detection in cluttered scene color images. The proposed system uses the Fourier-Mellin Transform as an invariant feature extractor to perform RST invariant hand detection. In a first stage of the system a simple non-adaptive skin color-based image segmentation and an interest point detector based on corners are used in order to identify regions of interest that contains possible matches. A sliding window algorithm is then used to scan the image at different scales performing the FMT calculations only in the previously detected regions of interest and comparing the extracted FM descriptor of the windows with a hand descriptors database obtained from a train image set. The results of the performed experiments suggest the use of Fourier-Mellin invariant features as a promising approach for automatic hand detection.

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BACKGROUND: The cause of acute exacerbation of chronic obstructive pulmonary disease (COPD) is often difficult to determine. Pulmonary embolism may be a trigger of acute dyspnoea in patients with COPD. AIM: To determine the prevalence of pulmonary embolism in patients with acute exacerbation of COPD. METHODS: 123 consecutive patients admitted to the emergency departments of two academic teaching hospitals for acute exacerbation of moderate to very severe COPD were included. Pulmonary embolism was investigated in all patients (whether or not clinically suspected) following a standardised algorithm based on d-dimer testing, lower-limb venous ultrasonography and multidetector helical computed tomography scan. RESULTS: Pulmonary embolism was ruled out by a d-dimer value <500 microg/l in 28 (23%) patients and a by negative chest computed tomography scan in 91 (74%). Computed tomography scan showed pulmonary embolism in four patients (3.3%, 95% confidence interval (CI), 1.2% to 8%), including three lobar and one sub-segmental embolisms. The prevalence of pulmonary embolism was 6.2% (n = 3; 95% CI, 2.3% to 16.9%) in the 48 patients who had a clinical suspicion of pulmonary embolism and 1.3% (n = 1; 95% CI, 0.3% to 7.1%) in those not suspected. In two cases with positive computed tomography scan, the venous ultrasonography also showed a proximal deep-vein thrombosis. No other patient was diagnosed with venous thrombosis. CONCLUSIONS: The prevalence of unsuspected pulmonary embolism is very low in patients admitted in the emergency department for an acute exacerbation of their COPD. These results argue against a systematic examination for pulmonary embolism in this population.

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3 Summary 3. 1 English The pharmaceutical industry has been facing several challenges during the last years, and the optimization of their drug discovery pipeline is believed to be the only viable solution. High-throughput techniques do participate actively to this optimization, especially when complemented by computational approaches aiming at rationalizing the enormous amount of information that they can produce. In siiico techniques, such as virtual screening or rational drug design, are now routinely used to guide drug discovery. Both heavily rely on the prediction of the molecular interaction (docking) occurring between drug-like molecules and a therapeutically relevant target. Several softwares are available to this end, but despite the very promising picture drawn in most benchmarks, they still hold several hidden weaknesses. As pointed out in several recent reviews, the docking problem is far from being solved, and there is now a need for methods able to identify binding modes with a high accuracy, which is essential to reliably compute the binding free energy of the ligand. This quantity is directly linked to its affinity and can be related to its biological activity. Accurate docking algorithms are thus critical for both the discovery and the rational optimization of new drugs. In this thesis, a new docking software aiming at this goal is presented, EADock. It uses a hybrid evolutionary algorithm with two fitness functions, in combination with a sophisticated management of the diversity. EADock is interfaced with .the CHARMM package for energy calculations and coordinate handling. A validation was carried out on 37 crystallized protein-ligand complexes featuring 11 different proteins. The search space was defined as a sphere of 15 R around the center of mass of the ligand position in the crystal structure, and conversely to other benchmarks, our algorithms was fed with optimized ligand positions up to 10 A root mean square deviation 2MSD) from the crystal structure. This validation illustrates the efficiency of our sampling heuristic, as correct binding modes, defined by a RMSD to the crystal structure lower than 2 A, were identified and ranked first for 68% of the complexes. The success rate increases to 78% when considering the five best-ranked clusters, and 92% when all clusters present in the last generation are taken into account. Most failures in this benchmark could be explained by the presence of crystal contacts in the experimental structure. EADock has been used to understand molecular interactions involved in the regulation of the Na,K ATPase, and in the activation of the nuclear hormone peroxisome proliferatoractivated receptors a (PPARa). It also helped to understand the action of common pollutants (phthalates) on PPARy, and the impact of biotransformations of the anticancer drug Imatinib (Gleevec®) on its binding mode to the Bcr-Abl tyrosine kinase. Finally, a fragment-based rational drug design approach using EADock was developed, and led to the successful design of new peptidic ligands for the a5ß1 integrin, and for the human PPARa. In both cases, the designed peptides presented activities comparable to that of well-established ligands such as the anticancer drug Cilengitide and Wy14,643, respectively. 3.2 French Les récentes difficultés de l'industrie pharmaceutique ne semblent pouvoir se résoudre que par l'optimisation de leur processus de développement de médicaments. Cette dernière implique de plus en plus. de techniques dites "haut-débit", particulièrement efficaces lorsqu'elles sont couplées aux outils informatiques permettant de gérer la masse de données produite. Désormais, les approches in silico telles que le criblage virtuel ou la conception rationnelle de nouvelles molécules sont utilisées couramment. Toutes deux reposent sur la capacité à prédire les détails de l'interaction moléculaire entre une molécule ressemblant à un principe actif (PA) et une protéine cible ayant un intérêt thérapeutique. Les comparatifs de logiciels s'attaquant à cette prédiction sont flatteurs, mais plusieurs problèmes subsistent. La littérature récente tend à remettre en cause leur fiabilité, affirmant l'émergence .d'un besoin pour des approches plus précises du mode d'interaction. Cette précision est essentielle au calcul de l'énergie libre de liaison, qui est directement liée à l'affinité du PA potentiel pour la protéine cible, et indirectement liée à son activité biologique. Une prédiction précise est d'une importance toute particulière pour la découverte et l'optimisation de nouvelles molécules actives. Cette thèse présente un nouveau logiciel, EADock, mettant en avant une telle précision. Cet algorithme évolutionnaire hybride utilise deux pressions de sélections, combinées à une gestion de la diversité sophistiquée. EADock repose sur CHARMM pour les calculs d'énergie et la gestion des coordonnées atomiques. Sa validation a été effectuée sur 37 complexes protéine-ligand cristallisés, incluant 11 protéines différentes. L'espace de recherche a été étendu à une sphère de 151 de rayon autour du centre de masse du ligand cristallisé, et contrairement aux comparatifs habituels, l'algorithme est parti de solutions optimisées présentant un RMSD jusqu'à 10 R par rapport à la structure cristalline. Cette validation a permis de mettre en évidence l'efficacité de notre heuristique de recherche car des modes d'interactions présentant un RMSD inférieur à 2 R par rapport à la structure cristalline ont été classés premier pour 68% des complexes. Lorsque les cinq meilleures solutions sont prises en compte, le taux de succès grimpe à 78%, et 92% lorsque la totalité de la dernière génération est prise en compte. La plupart des erreurs de prédiction sont imputables à la présence de contacts cristallins. Depuis, EADock a été utilisé pour comprendre les mécanismes moléculaires impliqués dans la régulation de la Na,K ATPase et dans l'activation du peroxisome proliferatoractivated receptor a (PPARa). Il a également permis de décrire l'interaction de polluants couramment rencontrés sur PPARy, ainsi que l'influence de la métabolisation de l'Imatinib (PA anticancéreux) sur la fixation à la kinase Bcr-Abl. Une approche basée sur la prédiction des interactions de fragments moléculaires avec protéine cible est également proposée. Elle a permis la découverte de nouveaux ligands peptidiques de PPARa et de l'intégrine a5ß1. Dans les deux cas, l'activité de ces nouveaux peptides est comparable à celles de ligands bien établis, comme le Wy14,643 pour le premier, et le Cilengitide (PA anticancéreux) pour la seconde.

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In this paper, a hybrid simulation-based algorithm is proposed for the StochasticFlow Shop Problem. The main idea of the methodology is to transform the stochastic problem into a deterministic problem and then apply simulation to the latter. In order to achieve this goal, we rely on Monte Carlo Simulation and an adapted version of a deterministic heuristic. This approach aims to provide flexibility and simplicity due to the fact that it is not constrained by any previous assumption and relies in well-tested heuristics.

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Activation of the NF-kappaB pathway in T cells is required for induction of an adaptive immune response. Hematopoietic progenitor kinase (HPK1) is an important proximal mediator of T-cell receptor (TCR)-induced NF-kappaB activation. Knock-down of HPK1 abrogates TCR-induced IKKbeta and NF-kappaB activation, whereas active HPK1 leads to increased IKKbeta activity in T cells. Yet, the precise molecular mechanism of this process remains elusive. Here, we show that HPK1-mediated NF-kappaB activation is dependent on the adaptor protein CARMA1. HPK1 interacts with CARMA1 in a TCR stimulation-dependent manner and phosphorylates the linker region of CARMA1. Interestingly, the putative HPK1 phosphorylation sites in CARMA1 are different from known PKC consensus sites. Mutations of residues S549, S551, and S552 in CARMA1 abrogated phosphorylation of a CARMA1-linker construct by HPK1 in vitro. In addition, CARMA1 S551A or S5549A/S551A point mutants failed to restore HPK1-mediated and TCR-mediated NF-kappaB activation and IL-2 expression in CARMA1-deficient T cells. Thus, we identify HPK1 as a kinase specific for CARMA1 and suggest HPK1-mediated phosphorylation of CARMA1 as an additional regulatory mechanism tuning the NF-kappaB response upon TCR stimulation.

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On October 20–21, 2009, two road safety audits were conducted in Lee County, Iowa: one for a 6 mile section of County Road X-23 from IA 2 to the south corporate limits of West Point and one for a 9.7 mile section of County Road W-62 from US 218 to IA 27. Both roads have high severe crash histories for the years of 2001 through 2008. Using these crash data, the Iowa Department of Transportation (Iowa DOT) has identified County Road X-23 as being in the top 5 percent of similar roads for run-off-road crashes. The Iowa DOT lists County Road W-62 as a high-risk rural road that has above-average crash numbers and is eligible for funding under the Federal High-Risk Rural Road Program. Considering these issues, the Lee County Engineer and Iowa DOT requested that road safety audits be conducted to address the safety concerns and to suggest possible mitigation strategies.

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Based on provious (Hemelrijk 1998; Puga-González, Hildenbrant & Hemelrijk 2009), we have developed an agent-based model and software, called A-KinGDom, which allows us to simulate the emergence of the social structure in a group of non-human primates. The model includes dominance and affiliative interactions and incorporate s two main innovations (preliminary dominance interactions and a kinship factor), which allow us to define four different attack and affiliative strategies. In accordance with these strategies, we compared the data obtained under four simulation conditions with the results obtained in a provious study (Dolado & Beltran 2012) involving empirical observations of a captive group of mangabeys (Cercocebus torquatus)

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This paper discusses social representations in scientific communications and private ones that are linked to the individual imagination. Social representations, in a limited sense, are useful for the development of preventive messages, but of little benefit to clinical work. We highlight some non-explicit aspects of scientific discourse that impact on treatment: projected beliefs and values. We tackle the relationship between the concepts of representation, imagination, identity and temporality in the individual approach of the cancer patient.

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Global positioning systems (GPS) offer a cost-effective and efficient method to input and update transportation data. The spatial location of objects provided by GPS is easily integrated into geographic information systems (GIS). The storage, manipulation, and analysis of spatial data are also relatively simple in a GIS. However, many data storage and reporting methods at transportation agencies rely on linear referencing methods (LRMs); consequently, GPS data must be able to link with linear referencing. Unfortunately, the two systems are fundamentally incompatible in the way data are collected, integrated, and manipulated. In order for the spatial data collected using GPS to be integrated into a linear referencing system or shared among LRMs, a number of issues need to be addressed. This report documents and evaluates several of those issues and offers recommendations. In order to evaluate the issues associated with integrating GPS data with a LRM, a pilot study was created. To perform the pilot study, point features, a linear datum, and a spatial representation of a LRM were created for six test roadway segments that were located within the boundaries of the pilot study conducted by the Iowa Department of Transportation linear referencing system project team. Various issues in integrating point features with a LRM or between LRMs are discussed and recommendations provided. The accuracy of the GPS is discussed, including issues such as point features mapping to the wrong segment. Another topic is the loss of spatial information that occurs when a three-dimensional or two-dimensional spatial point feature is converted to a one-dimensional representation on a LRM. Recommendations such as storing point features as spatial objects if necessary or preserving information such as coordinates and elevation are suggested. The lack of spatial accuracy characteristic of most cartography, on which LRM are often based, is another topic discussed. The associated issues include linear and horizontal offset error. The final topic discussed is some of the issues in transferring point feature data between LRMs.

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The objective of the present work was to characterize banana accessions from the Germplasm Bank at Embrapa Mandioca e Fruticultura Tropical (Brazil), using agronomical, physical and physicochemical characteristics of fruit and simple sequence repeats (SSR) markers. Twenty-six accessions were analyzed, in which high genetic variability was found, especially for the agronomical characters number of fruit and weight of bunch. Accessions with high contents of carotenoids (diploid 'Jaran'), polyphenols (triploid 'Caipira' and tetraploid 'Teparod') and vitamin C (diploid 'Tuugia' and an unknown triploid AAA) in the fruit were identified. Thirteen microsatellite primers revealed an average of 7.23 alleles, which showed high variability. A dendrogram was prepared using the Gower algorithm for the distance matrices obtained from the agronomical, physical and physicolchemical analysis of fruit and SSR markers. Adopting the average genetic divergence as the cut-off point, three clusters were found: G1, formed by the diploids 'Jaran', 028003-01 and M-48; G2, by the diploids 'Malbut' and 'Ido 110'; and G3, by 21 tri-and tetraploid accessions, including one diploid, 'Tuugia'. The triploids with the B genome 'Thap Maeo', 'Walha', 'Pacha Nadan' and 'Champa Madras' were grouped in G2. Results from this work can be used for breeding hybrids with good agronomical traits and fruit quality.