986 resultados para World Modeling


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We investigated the physiological consequences of the most challenging mountain ultra-marathon (MUM) in the world: a 330-km trail run with 24000 m of positive and negative elevation change. Neuromuscular fatigue (NMF) was assessed before (Pre-), during (Mid-) and after (Post-) the MUM in experienced ultra-marathon runners (n = 15; finish time = 122.43 hours +/-17.21 hours) and in Pre- and Post- in a control group with a similar level of sleep deprivation (n = 8). Blood markers of muscle inflammation and damage were analyzed at Pre- and Post-. Mean +/- SD maximal voluntary contraction force declined significantly at Mid- (-13+/-17% and -10+/-16%, P<0.05 for knee extensor, KE, and plantar flexor muscles, PF, respectively), and further decreased at Post- (-24+/-13% and -26+/-19%, P<0.01) with alteration of the central activation ratio (-24+/-24% and -28+/-34% between Pre- and Post-, P<0.05) in runners whereas these parameters did not change in the control group. Peripheral NMF markers such as 100 Hz doublet (KE: -18+/-18% and PF: -20+/-15%, P<0.01) and peak twitch (KE: -33+/-12%, P<0.001 and PF: -19+/-14%, P<0.01) were also altered in runners but not in controls. Post-MUM blood concentrations of creatine kinase (3719+/-3045 Ul.1), lactate dehydrogenase (1145+/-511 UI.L-1), C-Reactive Protein (13.1+/-7.5 mg.L-1) and myoglobin (449.3+/-338.2 microg.L-1) were higher (P<0.001) than at Pre- in runners but not in controls. Our findings revealed less neuromuscular fatigue, muscle damage and inflammation than in shorter MUMs. In conclusion, paradoxically, such extreme exercise seems to induce a relative muscle preservation process due likely to a protective anticipatory pacing strategy during the first half of MUM and sleep deprivation in the second half.

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Global human genetic variation is greatly influenced by geography, with genetic differentiation between populations increasing with geographic distance and within-population diversity decreasing with distance from Africa. In fact, these 'clines' can explain most of the variation in human populations. Despite this, population genetics inferences often rely on models that do not take geography into account, which could result in misleading conclusions when working at global geographic scales. Geographically explicit approaches have great potential for the study of human population genetics. Here, we discuss the most promising avenues of research in the context of human settlement history and the detection of genomic elements under natural selection. We also review recent technical advances and address the challenges of integrating geography and genetics.

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The Iowa Department of Education has joined the Office of the Governor to prepare a set of legislative proposals that will bring Iowa closer to its goal of providing a world-class education to all children, no mater where they live. This legislative brief serves as an overview of the legislation, which I encourage you to read and discuss in greater detail. the goals behind these policies are straightforward: Comprehensive and systematically raise and support the teaching profession while expanding efforts to customize instruction to every student's passion and talents. Iowa's children deserve the best education can provide so they leave our schools with the knowledge and skills necessary for successful and rewarding lives. Iowa has many good schools with hard-working, talented educators who deserves our respect and appreciation. While we honor the past work of generations of Iowans who built a strong foundation, it is our responsibility - and our turn - to make a focused, dedicated effort to improve Iowa's schools. We stand at a pivotal moment in Iowa storied education history, in which we have the opportunity and will as community to make the transition from being "good" to being "great".

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Objectives: Acetate brain metabolism has the particularity to occur specifically in glial cells. Labeling studies, using acetate labeled either with 13C (NMR) or 11C (PET), are governed by the same biochemical reactions and thus follow the same mathematical principles. In this study, the objective was to adapt an NMR acetate brain metabolism model to analyse [1-11C]acetate infusion in rats. Methods: Brain acetate infusion experiments were modeled using a two-compartment model approach used in NMR.1-3 The [1-11C]acetate labeling study was done using a beta scintillator.4 The measured radioactive signal represents the time evolution of the sum of all labeled metabolites in the brain. Using a coincidence counter in parallel, an arterial input curve was measured. The 11C at position C-1 of acetate is metabolized in the first turn of the TCA cycle to the position 5 of glutamate (Figure 1A). Through the neurotransmission process, it is further transported to the position 5 of glutamine and the position 5 of neuronal glutamate. After the second turn of the TCA cycle, tracer from [1-11C]acetate (and also a part from glial [5-11C]glutamate) is transferred to glial [1-11C]glutamate and further to [1-11C]glutamine and neuronal glutamate through the neurotransmission cycle. Brain poster session: oxidative mechanisms S460 Journal of Cerebral Blood Flow & Metabolism (2009) 29, S455-S466 Results: The standard acetate two-pool PET model describes the system by a plasma pool and a tissue pool linked by rate constants. Experimental data are not fully described with only one tissue compartment (Figure 1B). The modified NMR model was fitted successfully to tissue time-activity curves from 6 single animals, by varying the glial mitochondrial fluxes and the neurotransmission flux Vnt. A glial composite rate constant Kgtg=Vgtg/[Ace]plasma was extracted. Considering an average acetate concentration in plasma of 1 mmol/g5 and the negligible additional amount injected, we found an average Vgtg = 0.08±0.02 (n = 6), in agreement with previous NMR measurements.1 The tissue time-activity curve is dominated by glial glutamate and later by glutamine (Figure 1B). Labeling of neuronal pools has a low influence, at least for the 20 mins of beta-probe acquisition. Based on the high diffusivity of CO2 across the blood-brain barrier; 11CO2 is not predominant in the total tissue curve, even if the brain CO2 pool is big compared with other metabolites, due to its strong dilution through unlabeled CO2 from neuronal metabolism and diffusion from plasma. Conclusion: The two-compartment model presented here is also able to fit data of positron emission experiments and to extract specific glial metabolic fluxes. 11C-labeled acetate presents an alternative for faster measurements of glial oxidative metabolism compared to NMR, potentially applicable to human PET imaging. However, to quantify the relative value of the TCA cycle flux compared to the transmitochondrial flux, the chemical sensitivity of NMR is required. PET and NMR are thus complementary.

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PURPOSE: Ocular anatomy and radiation-associated toxicities provide unique challenges for external beam radiation therapy. For treatment planning, precise modeling of organs at risk and tumor volume are crucial. Development of a precise eye model and automatic adaptation of this model to patients' anatomy remain problematic because of organ shape variability. This work introduces the application of a 3-dimensional (3D) statistical shape model as a novel method for precise eye modeling for external beam radiation therapy of intraocular tumors. METHODS AND MATERIALS: Manual and automatic segmentations were compared for 17 patients, based on head computed tomography (CT) volume scans. A 3D statistical shape model of the cornea, lens, and sclera as well as of the optic disc position was developed. Furthermore, an active shape model was built to enable automatic fitting of the eye model to CT slice stacks. Cross-validation was performed based on leave-one-out tests for all training shapes by measuring dice coefficients and mean segmentation errors between automatic segmentation and manual segmentation by an expert. RESULTS: Cross-validation revealed a dice similarity of 95% ± 2% for the sclera and cornea and 91% ± 2% for the lens. Overall, mean segmentation error was found to be 0.3 ± 0.1 mm. Average segmentation time was 14 ± 2 s on a standard personal computer. CONCLUSIONS: Our results show that the solution presented outperforms state-of-the-art methods in terms of accuracy, reliability, and robustness. Moreover, the eye model shape as well as its variability is learned from a training set rather than by making shape assumptions (eg, as with the spherical or elliptical model). Therefore, the model appears to be capable of modeling nonspherically and nonelliptically shaped eyes.

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The present research deals with the review of the analysis and modeling of Swiss franc interest rate curves (IRC) by using unsupervised (SOM, Gaussian Mixtures) and supervised machine (MLP) learning algorithms. IRC are considered as objects embedded into different feature spaces: maturities; maturity-date, parameters of Nelson-Siegel model (NSM). Analysis of NSM parameters and their temporal and clustering structures helps to understand the relevance of model and its potential use for the forecasting. Mapping of IRC in a maturity-date feature space is presented and analyzed for the visualization and forecasting purposes.

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M. Díaz-Andreu plantea un análisis de las implicaciones académicas, sociales y políticas de la arqueología (entendiendo como tal la investigación estricta, pero también el coleccionismo de obras de arte) entre finales del siglo XVIII y el inicio de la Primera Guerra Mundial, período durante el cual la formación y expansión de los imperios coloniales constituyó uno de los elementos clave en el discurso ideológico de los estados europeos. Su trabajo continúa la línea marcada por estudios suyos anteriores, esencialmente Nationalism and Archaeology in Europe (Díaz-Andreu & T. Champion [eds.], 1996) y Excavating Women. A History in European Archaeology (Díaz-Andreu & M. L. S. Sorensen, 1998), en los que combinaba el análisis historiográfico de diferentes aspectos y personajes clave de la arqueología europea desde la perspectiva de la organización de las redes sociales entre investigadores, con la reflexión sobre las implicaciones de la arqueología como ciencia en la definición y defensa de diferentes credos políticos, y el papel de la mujer en la investigación.

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Ten years ago, the first cellular receptor for the prototypic arenavirus lymphocytic choriomeningitis virus (LCMV) and the highly pathogenic Lassa virus (LASV) was identified as alpha-dystroglycan (alpha-DG), a versatile receptor for proteins of the extracellular matrix (ECM). Biochemical analysis of the interaction of alpha-DG with arenaviruses and ECM proteins revealed a strikingly similar mechanism of receptor recognition that critically depends on specific sugar modification on alpha-DG involving a novel class of putative glycosyltransferase, the LARGE proteins. Interestingly, recent genome-wide detection and characterization of positive selection in human populations revealed evidence for positive selection of a locus within the LARGE gene in populations from Western Africa, where LASV is endemic. While most enveloped viruses that enter the host cell in a pH-dependent manner use clathrin-mediated endocytosis, recent studies revealed that the Old World arenaviruses LCMV and LASV enter the host cell predominantly via a novel and unusual endocytotic pathway independent of clathrin, caveolin, dynamin, and actin. Upon internalization, the virus is rapidly delivered to endosomes via an unusual route of vesicular trafficking that is largely independent of the small GTPases Rab5 and Rab7. Since infection of cells with LCMV and LASV depends on DG, this unusual endocytotic pathway could be related to normal cellular trafficking of the DG complex. Alternatively, engagement of arenavirus particles may target DG for an endocytotic pathway not normally used in uninfected cells thereby inducing an entry route specifically tailored to the pathogen's needs.

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Debris flows and related landslide processes occur in many regions all over Norway and pose a significant hazard to inhabited areas. Within the framework of the development of a national debris flows susceptibility map, we are working on a modeling approach suitable for Norway with a nationwide coverage. The discrimination of source areas is based on an index approach, which includes topographic parameters and hydrological settings. For the runout modeling, we use the Flow-R model (IGAR, University of Lausanne), which is based on combined probabilistic and energetic algorithms for the assessment of the spreading of the flow and maximum runout distances. First results for different test areas have shown that runout distances can be modeled reliably. For the selection of source areas, however, additional factors have to be considered, such as the lithological and quaternary geological setting, in order to accommodate the strong variation in debris flow activity in the different geological, geomorphological and climate regions of Norway.