744 research outputs found
Direct and Inverse Results on Bounded Domains for Meshless Methods via Localized Bases on Manifolds
This article develops direct and inverse estimates for certain finite
dimensional spaces arising in kernel approximation. Both the direct and inverse
estimates are based on approximation spaces spanned by local Lagrange functions
which are spatially highly localized. The construction of such functions is
computationally efficient and generalizes the construction given by the authors
for restricted surface splines on . The kernels for which the
theory applies includes the Sobolev-Mat\'ern kernels for closed, compact,
connected, Riemannian manifolds.Comment: 29 pages. To appear in Festschrift for the 80th Birthday of Ian Sloa
The generalized Robinson-Foulds metric
The Robinson-Foulds (RF) metric is arguably the most widely used measure of
phylogenetic tree similarity, despite its well-known shortcomings: For example,
moving a single taxon in a tree can result in a tree that has maximum distance
to the original one; but the two trees are identical if we remove the single
taxon. To this end, we propose a natural extension of the RF metric that does
not simply count identical clades but instead, also takes similar clades into
consideration. In contrast to previous approaches, our model requires the
matching between clades to respect the structure of the two trees, a property
that the classical RF metric exhibits, too. We show that computing this
generalized RF metric is, unfortunately, NP-hard. We then present a simple
Integer Linear Program for its computation, and evaluate it by an
all-against-all comparison of 100 trees from a benchmark data set. We find that
matchings that respect the tree structure differ significantly from those that
do not, underlining the importance of this natural condition.Comment: Peer-reviewed and presented as part of the 13th Workshop on
Algorithms in Bioinformatics (WABI2013
Jump at the onset of saltation
We reveal a discontinuous transition in the saturated flux for aeolian
saltation by simulating explicitly particle motion in turbulent flow. The
discontinuity is followed by a coexistence interval with two metastable
solutions. The modification of the wind profile due to momentum exchange
exhibits a second maximum at high shear strength. The saturated flux depends on
the strength of the wind as
Regularity for eigenfunctions of Schr\"odinger operators
We prove a regularity result in weighted Sobolev spaces (or
Babuska--Kondratiev spaces) for the eigenfunctions of a Schr\"odinger operator.
More precisely, let K_{a}^{m}(\mathbb{R}^{3N}) be the weighted Sobolev space
obtained by blowing up the set of singular points of the Coulomb type potential
V(x) = \sum_{1 \le j \le N} \frac{b_j}{|x_j|} + \sum_{1 \le i < j \le N}
\frac{c_{ij}}{|x_i-x_j|}, x in \mathbb{R}^{3N}, b_j, c_{ij} in \mathbb{R}. If u
in L^2(\mathbb{R}^{3N}) satisfies (-\Delta + V) u = \lambda u in distribution
sense, then u belongs to K_{a}^{m} for all m \in \mathbb{Z}_+ and all a \le 0.
Our result extends to the case when b_j and c_{ij} are suitable bounded
functions on the blown-up space. In the single-electron, multi-nuclei case, we
obtain the same result for all a<3/2.Comment: to appear in Lett. Math. Phy
Upside-down fluxes Down Under: CO2 net sink in winter and net source in summer in a temperate evergreen broadleaf forest
Predicting the seasonal dynamics of ecosystem carbon fluxes is challenging in broadleaved evergreen forests because of their moderate climates and subtle changes in canopy phenology. We assessed the climatic and biotic drivers of the seasonality of net ecosystem–atmosphere CO2 exchange (NEE) of a eucalyptus-dominated forest near Sydney, Australia, using the eddy covariance method. The climate is characterised by a mean annual precipitation of 800mm and a mean annual temperature of 18°C, hot summers and mild winters, with highly variable precipitation. In the 4-year study, the ecosystem was a sink each year (−225gCm−2yr−1 on average, with a standard deviation of 108gCm−2yr−1); inter-annual variations were not related to meteorological conditions. Daily net C uptake was always detected during the cooler, drier winter months (June through August), while net C loss occurred during the warmer, wetter summer months (December through February). Gross primary productivity (GPP) seasonality was low, despite longer days with higher light intensity in summer, because vapour pressure deficit (D) and air temperature (Ta) restricted surface conductance during summer while winter temperatures were still high enough to support photosynthesis. Maximum GPP during ideal environmental conditions was significantly correlated with remotely sensed enhanced vegetation index (EVI; r2 = 0.46) and with canopy leaf area index (LAI; r2= 0.29), which increased rapidly after mid-summer rainfall events. Ecosystem respiration (ER) was highest during summer in wet soils and lowest during winter months. ER had larger seasonal amplitude compared to GPP, and therefore drove the seasonal variation of NEE. Because summer carbon uptake may become increasingly limited by atmospheric demand and high temperature, and because ecosystem respiration could be enhanced by rising temperatures, our results suggest the potential for large-scale seasonal shifts in NEE in sclerophyll vegetation under climate change.The Australian Education Investment Fund,
Australian Terrestrial Ecosystem Research Network, Australian
Research Council and Hawkesbury Institute for the Environment
at Western Sydney University supported this work. We thank
Jason Beringer, Helen Cleugh, Ray Leuning and Eva van Gorsel for
advice and support. Senani Karunaratne provided soil classification
details
A Dimension-Adaptive Multi-Index Monte Carlo Method Applied to a Model of a Heat Exchanger
We present an adaptive version of the Multi-Index Monte Carlo method,
introduced by Haji-Ali, Nobile and Tempone (2016), for simulating PDEs with
coefficients that are random fields. A classical technique for sampling from
these random fields is the Karhunen-Lo\`eve expansion. Our adaptive algorithm
is based on the adaptive algorithm used in sparse grid cubature as introduced
by Gerstner and Griebel (2003), and automatically chooses the number of terms
needed in this expansion, as well as the required spatial discretizations of
the PDE model. We apply the method to a simplified model of a heat exchanger
with random insulator material, where the stochastic characteristics are
modeled as a lognormal random field, and we show consistent computational
savings
Discrete exterior calculus (DEC) for the surface Navier-Stokes equation
We consider a numerical approach for the incompressible surface Navier-Stokes
equation. The approach is based on the covariant form and uses discrete
exterior calculus (DEC) in space and a semi-implicit discretization in time.
The discretization is described in detail and related to finite difference
schemes on staggered grids in flat space for which we demonstrate second order
convergence. We compare computational results with a vorticity-stream function
approach for surfaces with genus 0 and demonstrate the interplay between
topology, geometry and flow properties. Our discretization also allows to
handle harmonic vector fields, which we demonstrate on a torus.Comment: 21 pages, 9 figure
Numerical Computations with H(div)-Finite Elements for the Brinkman Problem
The H(div)-conforming approach for the Brinkman equation is studied
numerically, verifying the theoretical a priori and a posteriori analysis in
previous work of the authors. Furthermore, the results are extended to cover a
non-constant permeability. A hybridization technique for the problem is
presented, complete with a convergence analysis and numerical verification.
Finally, the numerical convergence studies are complemented with numerical
examples of applications to domain decomposition and adaptive mesh refinement.Comment: Minor clarifications, added references. Reordering of some figures.
To appear in Computational Geosciences, final article available at
http://www.springerlink.co
Anxiolytic activity of pyridoindole derivatives SMe1EC2 and SMe1M2: behavioral analysis using rat model
Anxiety and mood disorders have become very significant affections in the last decades. According to WHO at least one mental disease occurred per year in 27% of EU inhabitants (more than 82 mil. people). It is estimated that by 2020, depression will be the main cause of morbidity in the developed countries. These circumstances call for research for new prospective drugs with anxiolytic and antidepressive properties exhibiting no toxicity and withdrawal effect and possessing beneficial properties, like antioxidant and/or neuroprotective effects. The aim of this study was to obtain information about psychopharmacological properties of pyridoindole derivatives SMe1EC2 and SMe1M2, using non-invasive behavioral methods in rats
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