995 resultados para Multi-configuration


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In fetal brain MRI, most of the high-resolution reconstruction algorithms rely on brain segmentation as a preprocessing step. Manual brain segmentation is however highly time-consuming and therefore not a realistic solution. In this work, we assess on a large dataset the performance of Multiple Atlas Fusion (MAF) strategies to automatically address this problem. Firstly, we show that MAF significantly increase the accuracy of brain segmentation as regards single-atlas strategy. Secondly, we show that MAF compares favorably with the most recent approach (Dice above 0.90). Finally, we show that MAF could in turn provide an enhancement in terms of reconstruction quality.

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This study shows the possibility offered by modern ultra-high performance supercritical fluid chromatography combined with tandem mass spectrometry in doping control analysis. A high throughput screening method was developed for 100 substances belonging to the challenging classes of anabolic agents, hormones and metabolic modulators, synthetic cannabinoids and glucocorticoids, which should be detected at low concentrations in urine. To selectively extract these doping agents from urine, a supported liquid extraction procedure was implemented in a 48-well plate format. At the tested concentration levels ranging from 0.5 to 5 ng/mL, the recoveries were better than 70% for 48-68% of the compounds and higher than 50% for 83-87% of the tested substances. Due to the numerous interferences related to isomers of steroids and ions produced by the loss of water in the electrospray source, the choice of SFC separation conditions was very challenging. After careful optimization, a Diol stationary phase was employed. The total analysis time for the screening assay was only 8 min, and interferences as well as susceptibility to matrix effect (ME) were minimized. With the developed method, about 70% of the compounds had relative ME within the range ±20%, at a concentration of 1 and 5 ng/mL. Finally, limits of detection achieved with the above-described strategy including 5-fold preconcentration were below 0.1 ng/mL for the majority of the tested compounds. Therefore, LODs were systematically better than the minimum required performance levels established by the World anti-doping agency, except for very few metabolites.

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Peer-reviewed

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The multi-element determination of Al, Cr, Mn, Ni, Cu, Zn, Cd, Ba, Pb, SO4= and Cl- in riverine water samples was accomplished by inductively coupled plasma mass spectrometry (ICP-MS). The sample passed through a column containing the anionic resin AG1-X8 and the metals were determined directly. The retained anionic species were eluted and SO4= and Cl- were determined at m/z 48 and 35 correspondent to the ions SO+ and Cl+ formed at the plasma. Accuracy for metals was assessed by analysing the certified reference TM-26 (National Water Research Institute of Canada). Results for SO4= and Cl- were in agreement with those obtained by turbidimetry and spectrophotometry. LOD's of 0.1 µg l-1 for Cd, Ba and Pb; 0.2 µg l-1 for Al, Mn and Cu; 0.5 µg l-1 for Cr; 0.9 for Zn; 2.0 µg l-1for Ni , 60 µg l-1 for S and 200 µg l-1 Cl were attained.

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Simultaneous localization and mapping(SLAM) is a very important problem in mobile robotics. Many solutions have been proposed by different scientists during the last two decades, nevertheless few studies have considered the use of multiple sensors simultane¬ously. The solution is on combining several data sources with the aid of an Extended Kalman Filter (EKF). Two approaches are proposed. The first one is to use the ordinary EKF SLAM algorithm for each data source separately in parallel and then at the end of each step, fuse the results into one solution. Another proposed approach is the use of multiple data sources simultaneously in a single filter. The comparison of the computational com¬plexity of the two methods is also presented. The first method is almost four times faster than the second one.

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Global warming mitigation has recently become a priority worldwide. A large body of literature dealing with energy related problems has focused on reducing greenhouse gases emissions at an engineering scale. In contrast, the minimization of climate change at a wider macroeconomic level has so far received much less attention. We investigate here the issue of how to mitigate global warming by performing changes in an economy. To this end, we make use of a systematic tool that combines three methods: linear programming, environmentally extended input output models, and life cycle assessment principles. The problem of identifying key economic sectors that contribute significantly to global warming is posed in mathematical terms as a bi criteria linear program that seeks to optimize simultaneously the total economic output and the total life cycle CO2 emissions. We have applied this approach to the European Union economy, finding that significant reductions in global warming potential can be attained by regulating specific economic sectors. Our tool is intended to aid policymakers in the design of more effective public policies for achieving the environmental and economic targets sought.

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Keeping track of software assets and managing software installations in IT environments can be a hard endeavor, especially when the size and diversity of the environment grows. How to install and uninstall software efficiently and cost effectively? Are there too few or too many software licenses purchased? If installed, is the software actually in use? Software Asset Management (SAM) is a process that involves managing and optimizing the purchase, deployment, maintenance, utilization, and disposal of software applications within an organization. This master’s thesis describes a special Software Lifecycle Management Framework to provide solutions to the multitude of challenges within SAM. The main objectives when designing the framework was to provide a set of tools to control the software assets during their entire lifecycle while trying to minimize the costs related to owning and managing them.

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Este trabajo de fin de grado plantea probar la viabilidad de realizar un sistema de almacenamiento y distribución de imágenes médicas, utilizando únicamente software de código abierto, libre distribución o gratuito.

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Este estudio aborda un doble objetivo: a) conocer si existe progresión signi+cativa entre tres valores correspondientes al índice de Borg elicitados por jóvenes deportistas con relación a tres actividades de intensidad creciente; b) analizar la relación existente entre el índice de masa corporal (IMC) de los participantes con los valores de frecuencia cardíaca (FC) y la percepción de intensidad del esfuerzo (RPE). Método: Treinta y cinco deportistas jóvenes con una edad media de 18 y 28 años (21±0,5), realizaron 3 actividades que exigían una intensidad creciente de ejercicio: leve, moderada y vigorosa (ACSM, 2011). Se controló la frecuencia cardíaca mediante el dispositivo telemétrico Polar Team 2 y al +nalizar las tres actividades se administró tres veces la escala de Borg para obtener la RPE para cada actividad. Se ha complementado la metodología observacional indirecta (índices de Borg) con la metodología cuasiexperimental para obtener inferencias causales mediante un diseño sincrónico de variable de asignación conocida y grupo único. Se ha realizado un análisis de regresión múltiple, considerando la FC y la RPE como variables predictoras del IMC. Resultados: la RPE es creciente, acorde a las actividades, en todos los participantes, aunque en ningún caso la tendencia es estadísticamente signi+cativa. Prácticamente la cuarta parte del IMC se puede explicar por la FC y la RPE puesto que los participantes que tienen valores más altos de FC y de índice de Borg tienen también mayores valores de IMC. Este estudio puede proporcionar una visión de evaluación integrada entre los factores IMC, FC y la RPE, que suelen investigarse de modo aislado.