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The Lower Meuse Valley crosses the Roer Valley Rift System and provides an outstanding example of well-preserved late glacial and Holocene river terraces. The formation, preservation, and morphology of these terraces vary due to reach-specific conditions, a phenomenon that has been underappreciated in past studies. A detailed palaeogeographic reconstruction of the terrace series over the full length of the Lower Meuse Valley has been performed. This reconstruction provides improved insight into successive morphological responses to combined climatic and tectonic external forcing, as expressed and preserved in different ways along the river. New field data and data obtained from past studies were integrated using a digital mapping method in GIS. Results show that late glacial river terraces with diverse fluvial styles are best preserved in the Lower Meuse Valley downstream sub-reaches (traversing the Venlo Block and Peel Block), while Holocene terrace remnants are well-developed and preserved in the upstream sub-reaches (traversing the Campine Block and Roer Valley Graben). This reach-to-reach spatial variance in river terrace preservation and morphology can be ascribed to tectonically driven variations in river gradient and subsurface lithology, and to river-driven throughput of sediment supply.
OBJECTIVES/SPECIFIC AIMS: The study aimed to determine the effects of bilateral frontal active transcranial direct current stimulation (tDCS) at 2 mA for 12 minute Versus sham stimulation on functional connectivity of the working memory network during an fMRI N-Back task. METHODS/STUDY POPULATION: Stimulation was delivered over bilateral frontal dorsolateral prefrontal cortex via and MRI-compatible tDCS device during an fMRI working memory task in healthy older adults in a within-subject design. RESULTS/ANTICIPATED RESULTS: Active stimulation compared with sham resulted in significant increases in functional connectivity in working memory related brain regions during the N-Back task. DISCUSSION/SIGNIFICANCE OF IMPACT: Older adults typically have reduced functional connectivity compared with young adults. Our findings demonstrate that a single session of tDCS can increase functional connectivity of the working memory network in older adults. Based on this mechanism of effect, tDCS may serve as an adjunctive method for interventions aiming to enhance cognitive processes in older adults.
To develop a disaster triage tool for the evacuation of hospitalized neonatal and pediatric populations.
We expanded an existing neonatal disaster triage tool for the evacuation of a children’s hospital. We assessed inpatients using bedside visual assessments and chart review to categorize patients transport level based on local emergency medical services protocols and expert opinion. The tool was refined by using multiple Plan Do Study Act cycles. Primary outcome was the number of each level of transport required for hospital evacuation. Secondary outcome was improved efficiency of obtaining information about specific transport needs for evacuation.
We evaluated 1382 patients both visually and through electronic chart review over 10 random days. Accordance between visual assessment and electronic chart review reached 96.3%. During a 2 hour statewide disaster drill, no hospital units completed self-assessed transport needs for their patients; a single nurse used Triage by Resource Allocation in INpatients to determine transportation needs in less than 1 hour. (Disaster Med Public Health Preparedness. 2018;12:692-696)
Throughout the twentieth century, and even earlier, adults have attempted to publicly control, and even censor, teenagers' access to various artifacts of mass culture—including magazines, music, comic books, movies, television and radio programs, and books. The motivation has been twofold: to shield the young from certain perceived pernicious influences and to encourage a national cultural uniformity/conformity heavily motivated by Christian morality and the dread of racial (and class) mixing. Fears of youthful extremism, sparked by corrupting influences, have waxed and waned, depending on various social, political, economic, cultural, technological, and other configurations. But attempts at censorship have generally continued, earmarking even newer forms of mass communication, most recently cable television and the computer Internet. Any understanding of this development must take into consideration both the fears and motivations of the adult majority, as well as the complexities of modern youth culture, all within a larger national matrix. Adults' fear of youthful rebellion and their urge to control youth became particularly glaring during the 1950s, when the winds of change seemed particularly brisk.
Parametrized families of PDEs arise in various contexts such as inverse problems, control and optimization, risk assessment, and uncertainty quantification. In most of these applications, the number of parameters is large or perhaps even infinite. Thus, the development of numerical methods for these parametric problems is faced with the possible curse of dimensionality. This article is directed at (i) identifying and understanding which properties of parametric equations allow one to avoid this curse and (ii) developing and analysing effective numerical methods which fully exploit these properties and, in turn, are immune to the growth in dimensionality.
Part I of this article studies the smoothness and approximability of the solution map, that is, the map
is the parameter value and
is the corresponding solution to the PDE. It is shown that for many relevant parametric PDEs, the parametric smoothness of this map is typically holomorphic and also highly anisotropic, in that the relevant parameters are of widely varying importance in describing the solution. These two properties are then exploited to establish convergence rates of
-term approximations to the solution map, for which each term is separable in the parametric and physical variables. These results reveal that, at least on a theoretical level, the solution map can be well approximated by discretizations of moderate complexity, thereby showing how the curse of dimensionality is broken. This theoretical analysis is carried out through concepts of approximation theory such as best
-term approximation, sparsity, and
-widths. These notions determine a priori the best possible performance of numerical methods and thus serve as a benchmark for concrete algorithms.
Part II of this article turns to the development of numerical algorithms based on the theoretically established sparse separable approximations. The numerical methods studied fall into two general categories. The first uses polynomial expansions in terms of the parameters to approximate the solution map. The second one searches for suitable low-dimensional spaces for simultaneously approximating all members of the parametric family. The numerical implementation of these approaches is carried out through adaptive and greedy algorithms. An a priori analysis of the performance of these algorithms establishes how well they meet the theoretical benchmarks.
The numerical approximation of parametric partial differential equations is a
computational challenge, in particular when the number of involved parameter is large.
This paper considers a model class of second order, linear, parametric, elliptic PDEs on a
bounded domain D with diffusion coefficients depending on the parameters
in an affine manner. For such models, it was shown in [9, 10] that under very weak assumptions
on the diffusion coefficients, the entire family of solutions to such equations can be
simultaneously approximated in the Hilbert space
V = H01(D) by multivariate sparse polynomials in the parameter
vector y with a controlled number N of terms. The
convergence rate in terms of N does not depend on the number of
parameters in V, which may be arbitrarily large or countably infinite,
thereby breaking the curse of dimensionality. However, these approximation results do not
describe the concrete construction of these polynomial expansions, and should therefore
rather be viewed as benchmark for the convergence analysis of numerical methods. The
present paper presents an adaptive numerical algorithm for constructing a sequence of
sparse polynomials that is proved to converge toward the solution with the optimal
benchmark rate. Numerical experiments are presented in large parameter dimension, which
confirm the effectiveness of the adaptive approach.