926 resultados para Topology-based methods


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Connectivity analysis on diffusion MRI data of the whole-brain suffers from distortions caused by the standard echo-planar imaging acquisition strategies. These images show characteristic geometrical deformations and signal destruction that are an important drawback limiting the success of tractography algorithms. Several retrospective correction techniques are readily available. In this work, we use a digital phantom designed for the evaluation of connectivity pipelines. We subject the phantom to a “theoretically correct” and plausible deformation that resembles the artifact under investigation. We correct data back, with three standard methodologies (namely fieldmap-based, reversed encoding-based, and registration- based). Finally, we rank the methods based on their geometrical accuracy, the dropout compensation, and their impact on the resulting connectivity matrices.

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The purpose of this study was to compare a number of state-of-the-art methods in airborne laser scan- ning (ALS) remote sensing with regards to their capacity to describe tree size inequality and other indi- cators related to forest structure. The indicators chosen were based on the analysis of the Lorenz curve: Gini coefficient ( GC ), Lorenz asymmetry ( LA ), the proportions of basal area ( BALM ) and stem density ( NSLM ) stocked above the mean quadratic diameter. Each method belonged to one of these estimation strategies: (A) estimating indicators directly; (B) estimating the whole Lorenz curve; or (C) estimating a complete tree list. Across these strategies, the most popular statistical methods for area-based approach (ABA) were used: regression, random forest (RF), and nearest neighbour imputation. The latter included distance metrics based on either RF (NN–RF) or most similar neighbour (MSN). In the case of tree list esti- mation, methods based on individual tree detection (ITD) and semi-ITD, both combined with MSN impu- tation, were also studied. The most accurate method was direct estimation by best subset regression, which obtained the lowest cross-validated coefficients of variation of their root mean squared error CV(RMSE) for most indicators: GC (16.80%), LA (8.76%), BALM (8.80%) and NSLM (14.60%). Similar figures [CV(RMSE) 16.09%, 10.49%, 10.93% and 14.07%, respectively] were obtained by MSN imputation of tree lists by ABA, a method that also showed a number of additional advantages, such as better distributing the residual variance along the predictive range. In light of our results, ITD approaches may be clearly inferior to ABA with regards to describing the structural properties related to tree size inequality in for- ested areas.

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In this paper three p-adaptation strategies based on the minimization of the truncation error are presented for high order discontinuous Galerkin methods. The truncation error is approximated by means of a ? -estimation procedure and enables the identification of mesh regions that require adaptation. Three adaptation strategies are developed and termed a posteriori, quasi-a priori and quasi-a priori corrected. All strategies require fine solutions, which are obtained by enriching the polynomial order, but while the former needs time converged solutions, the last two rely on non-converged solutions, which lead to faster computations. In addition, the high order method permits the spatial decoupling for the estimated errors and enables anisotropic p-adaptation. These strategies are verified and compared in terms of accuracy and computational cost for the Euler and the compressible Navier?Stokes equations. It is shown that the two quasi- a priori methods achieve a significant reduction in computational cost when compared to a uniform polynomial enrichment. Namely, for a viscous boundary layer flow, we obtain a speedup of 6.6 and 7.6 for the quasi-a priori and quasi-a priori corrected approaches, respectively.

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Presenilins have been implicated in the genesis of Alzheimer’s disease and in facilitating LIN-12/Notch activity during development. All presenilins have multiple hydrophobic regions that could theoretically span a membrane, and a description of the membrane topology is a crucial step toward deducing the mechanism of presenilin function. Previously, we proposed an eight-transmembrane-domain model for presenilin, based on studies of the Caenorhabditis elegans SEL-12 presenilin. Here, we describe experiments that support the view that two of the hydrophobic regions of SEL-12 function as the seventh and eighth transmembrane domains. Furthermore, we have shown that human presenilin 1 behaves like SEL-12 presenilin when analyzed by our methods. Our results provide additional experimental support for the eight-transmembrane-domain model of presenilin topology.

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As world communication, technology, and trade become increasingly integrated through globalization, multinational corporations seek employees with global leadership experience and skills. However, the demand for these skills currently outweighs the supply. Given the rarity of globally ready leaders, global competency development should be emphasized in higher education programs. The reality, however, is that university graduate programs are often outdated and focus mostly on cognitive learning. Global leadership competence requires moving beyond the cognitive domain of learning to create socially responsible and culturally connected global leaders. This requires attention to development methods; however, limited research in global leadership development methods has been conducted. A new conceptual model, the global leadership development ecosystem, was introduced in this study to guide the design and evaluation of global leadership development programs. It was based on three theories of learning and was divided into four development methodologies. This study quantitatively tested the model and used it as a framework for an in-depth examination of the design of one International MBA program. The program was first benchmarked, by means of a qualitative best practices analysis, against the top-ranking IMBA programs in the world. Qualitative data from students, faculty, administrators, and staff was then examined, using descriptive and focused data coding. Quantitative data analysis, using PASW Statistics software, and a hierarchical regression, showed the individual effect of each of the four development methods, as well as their combined effect, on student scores on a global leadership assessment. The analysis revealed that each methodology played a distinct and important role in developing different competencies of global leadership. It also confirmed the critical link between self-efficacy and global leadership development.

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Software for video-based multi-point frequency measuring and mapping: http://hdl.handle.net/10045/53429

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"Extracted from U. S. Fish Commission report for 1897, pages 1 to 340, plates 1 to 62 and I to XVIII."

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Mode of access: Internet.

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Mode of access: Internet.

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Genetic assignment methods use genotype likelihoods to draw inference about where individuals were or were not born, potentially allowing direct, real-time estimates of dispersal. We used simulated data sets to test the power and accuracy of Monte Carlo resampling methods in generating statistical thresholds for identifying F-0 immigrants in populations with ongoing gene flow, and hence for providing direct, real-time estimates of migration rates. The identification of accurate critical values required that resampling methods preserved the linkage disequilibrium deriving from recent generations of immigrants and reflected the sampling variance present in the data set being analysed. A novel Monte Carlo resampling method taking into account these aspects was proposed and its efficiency was evaluated. Power and error were relatively insensitive to the frequency assumed for missing alleles. Power to identify F-0 immigrants was improved by using large sample size (up to about 50 individuals) and by sampling all populations from which migrants may have originated. A combination of plotting genotype likelihoods and calculating mean genotype likelihood ratios (D-LR) appeared to be an effective way to predict whether F-0 immigrants could be identified for a particular pair of populations using a given set of markers.