1,096 research outputs found
Numerical discretization of rotated diffusion operators in ocean models
A method to improve the behavior of the numerical discretization of a rotated diffusion operator such as, for example, the isopycnal diffusion parameterization used in large-scale ocean models based on the so-called z-coordinate system is presented. The authors then focus exclusively on the dynamically passive tracers and analyze some different approaches to the numerical discretization. Monotonic schemes are designed but are found to be rather complex, while simpler, linear schemes are shown to produce unphysical undershooting and overshooting. It is suggested that the choice of an appropriate discretization method depends on the importance of the rotated diffusion in a given simulation, whether the field to be diffused is dynamically active or not
A Simple Empirical Calibration of Energy Dispersive X-Ray Analysis (EDXA) on the Cornea
Monitoring of the corneal electrolyte content is important for the study of chemical eye burns. This paper describes quantitative measurements on gelatin standards, corneas and a cornea homogenate with an energy dispersive X-ray analyzer (EDX) in the scanning electron microscope (SEM). Ten micrometers thick cryosections were freeze-dried and mounted on solid carbon supports. The applied quantification procedure was a local peak background analysis with a specifically designed computer program. Similar chemical and physical properties of gelatin, cornea homogenate, and cornea were proven by EDX-analysis and wet chemical analysis. Gelatin standards with known concentrations of different added salts showed linear correlations with a correlation coefficient higher than 0.95 for all considered elements. The local background generation on carbon supports was the same for gelatin standards and corneal tissue. The results demonstrate that quantitative EDX analysis of semi-thin samples, mounted on neutral carbon supports, can be reliably used for the assessment of the corneal mineral composition
Numerical issues of the Total Exchange Flow (TEF) analysis framework for quantifying estuarine circulation
For more than a century, estuarine exchange flow has been quantified by means
of the Knudsen relations which connect bulk quantities such as inflow and
outflow volume fluxes and salinities. These relations are closely linked to
estuarine mixing. The recently developed Total Exchange Flow (TEF) analysis framework, which uses
salinity coordinates to calculate these bulk quantities, allows an exact
formulation of the Knudsen relations in realistic cases. There are however
numerical issues, since the original method does not converge to the TEF bulk
values for an increasing number of salinity classes. In the present study,
this problem is investigated and the method of dividing salinities,
described by MacCready et al. (2018), is mathematically introduced. A
challenging yet compact analytical scenario for a well-mixed estuarine
exchange flow is investigated for both methods, showing the proper
convergence of the dividing salinity method. Furthermore, the dividing
salinity method is applied to model results of the Baltic Sea to demonstrate
the analysis of realistic exchange flows and exchange flows with more than
two layers.</p
Segmentation of Retinal Low-Cost Optical Coherence Tomography Images using Deep Learning
The treatment of age-related macular degeneration (AMD) requires continuous
eye exams using optical coherence tomography (OCT). The need for treatment is
determined by the presence or change of disease-specific OCT-based biomarkers.
Therefore, the monitoring frequency has a significant influence on the success
of AMD therapy. However, the monitoring frequency of current treatment schemes
is not individually adapted to the patient and therefore often insufficient.
While a higher monitoring frequency would have a positive effect on the success
of treatment, in practice it can only be achieved with a home monitoring
solution. One of the key requirements of a home monitoring OCT system is a
computer-aided diagnosis to automatically detect and quantify pathological
changes using specific OCT-based biomarkers. In this paper, for the first time,
retinal scans of a novel self-examination low-cost full-field OCT (SELF-OCT)
are segmented using a deep learning-based approach. A convolutional neural
network (CNN) is utilized to segment the total retina as well as pigment
epithelial detachments (PED). It is shown that the CNN-based approach can
segment the retina with high accuracy, whereas the segmentation of the PED
proves to be challenging. In addition, a convolutional denoising autoencoder
(CDAE) refines the CNN prediction, which has previously learned retinal shape
information. It is shown that the CDAE refinement can correct segmentation
errors caused by artifacts in the OCT image.Comment: Accepted for SPIE Medical Imaging 2020: Computer-Aided Diagnosi
Bit-Vector Model Counting using Statistical Estimation
Approximate model counting for bit-vector SMT formulas (generalizing \#SAT)
has many applications such as probabilistic inference and quantitative
information-flow security, but it is computationally difficult. Adding random
parity constraints (XOR streamlining) and then checking satisfiability is an
effective approximation technique, but it requires a prior hypothesis about the
model count to produce useful results. We propose an approach inspired by
statistical estimation to continually refine a probabilistic estimate of the
model count for a formula, so that each XOR-streamlined query yields as much
information as possible. We implement this approach, with an approximate
probability model, as a wrapper around an off-the-shelf SMT solver or SAT
solver. Experimental results show that the implementation is faster than the
most similar previous approaches which used simpler refinement strategies. The
technique also lets us model count formulas over floating-point constraints,
which we demonstrate with an application to a vulnerability in differential
privacy mechanisms
A non-variational approach to nonlinear stability in stellar dynamics applied to the King model
In previous work by Y. Guo and G. Rein, nonlinear stability of equilibria in
stellar dynamics, i.e., of steady states of the Vlasov-Poisson system, was
accessed by variational techniques. Here we propose a different,
non-variational technique and use it to prove nonlinear stability of the King
model against a class of spherically symmetric, dynamically accessible
perturbations. This model is very important in astrophysics and was out of
reach of the previous techniques
A detailed view of filaments and sheets in the warm-hot intergalactic medium. I. Pancake formation
Numerical simulations predict a considerable fraction of the missing baryons
at redshift z ~ 0 resting in the so called warm-hot intergalactic medium
(WHIM). The filaments and sheets of the WHIM have high temperatures 10^5 - 10^7
K) and a high degree of ionization while having only low to intermediate
densities. The particular physical conditions of the WHIM structures, e.g.
density and temperature profiles, velocity fields, are expected to leave their
special imprint on spectroscopic observations. In order to get further insight
into these conditions, we perform hydrodynamical simulations of the WHIM.
Instead of analyzing large simulations of cosmological structure formation, we
simulate particular well-defined structures and study the impact of different
physical processes as well as of the scale dependencies. We start with the
comprehensive study of the one-dimensional collapse (pancake) and examine the
influence of radiative cooling, heating due to an UV background, and thermal
conduction. We investigate the effect of small scale perturbations given
according to the initial cosmological power spectrum. If the initial
perturbation length scale L exceeds ~ 2 Mpc the collapse leads to shock
confined structures. As a result of radiative cooling and of heating due to an
UV background a relatively cold and dense core forms in the one-dimensional
case. The properties of the core (extension, density, and temperature) are
correlated with L. For larger L the core sizes are more concentrated. Thermal
conduction enhances this trend and may even result in an evaporation of the
core. Our estimates predict that a core may start to evaporate for perturbation
lengths larger than L ~ 30 Mpc. The obtained detailed profiles for density and
temperature for prototype WHIM structures allow for the determination of
possible spectral signatures by the WHIM.Comment: 14 pages, 9 figures, accepted for publication in A&
Topological effects in ring polymers: A computer simulation study
Unconcatenated, unknotted polymer rings in the melt are subject to strong
interactions with neighboring chains due to the presence of topological
constraints. We study this by computer simulation using the bond-fluctuation
algorithm for chains with up to N=512 statistical segments at a volume fraction
\Phi=0.5 and show that rings in the melt are more compact than gaussian chains.
A careful finite size analysis of the average ring size R \propto N^{\nu}
yields an exponent \nu \approx 0.39 \pm 0.03 in agreement with a Flory-like
argument for the topologica interactions. We show (using the same algorithm)
that the dynamics of molten rings is similar to that of linear chains of the
same mass, confirming recent experimental findings. The diffusion constant
varies effectively as D_{N} \propto N^{-1.22(3) and is slightly higher than
that of corresponding linear chains. For the ring sizes considered (up to 256
statistical segments) we find only one characteristic time scale \tau_{ee}
\propto N^{2.0(2); this is shown by the collapse of several mean-square
displacements and correlation functions onto corresponding master curves.
Because of the shrunken state of the chain, this scaling is not compatible with
simple Rouse motion. It applies for all sizes of ring studied and no sign of a
crossover to any entangled regime is found.Comment: 20 Pages,11 eps figures, Late
- …