922 research outputs found
Existence of Monetary Steady States in a Matching Model: Indivisible Money
Existence of a monetary steady state is established for a random matching model with divisible goods, indivisible money, and take-it-or-leave-it offers by consumers. There is no restriction on individual money holdings. The background environment is that in papers by Shi and by Trejos and Wright. The monetary steady state shown to exist has nice properties: the value function, defined on money holdings, is increasing and strictly concave, and the measure over money holdings has full support.
Reformulation in planning
Reformulation of a problem is intended to make the problem more amenable to efficient solution. This is equally true in the special case of reformulating a planning problem. This paper considers various ways in which reformulation can be exploited in planning
Improving Reliability of Subject-Level Resting-State fMRI Parcellation with Shrinkage Estimators
A recent interest in resting state functional magnetic resonance imaging
(rsfMRI) lies in subdividing the human brain into anatomically and functionally
distinct regions of interest. For example, brain parcellation is often used for
defining the network nodes in connectivity studies. While inference has
traditionally been performed on group-level data, there is a growing interest
in parcellating single subject data. However, this is difficult due to the low
signal-to-noise ratio of rsfMRI data, combined with typically short scan
lengths. A large number of brain parcellation approaches employ clustering,
which begins with a measure of similarity or distance between voxels. The goal
of this work is to improve the reproducibility of single-subject parcellation
using shrinkage estimators of such measures, allowing the noisy
subject-specific estimator to "borrow strength" in a principled manner from a
larger population of subjects. We present several empirical Bayes shrinkage
estimators and outline methods for shrinkage when multiple scans are not
available for each subject. We perform shrinkage on raw intervoxel correlation
estimates and use both raw and shrinkage estimates to produce parcellations by
performing clustering on the voxels. Our proposed method is agnostic to the
choice of clustering method and can be used as a pre-processing step for any
clustering algorithm. Using two datasets---a simulated dataset where the true
parcellation is known and is subject-specific and a test-retest dataset
consisting of two 7-minute rsfMRI scans from 20 subjects---we show that
parcellations produced from shrinkage correlation estimates have higher
reliability and validity than those produced from raw estimates. Application to
test-retest data shows that using shrinkage estimators increases the
reproducibility of subject-specific parcellations of the motor cortex by up to
30%.Comment: body 21 pages, 11 figure
Surface-induced charge state conversion of nitrogen-vacancy defects in nanodiamonds
We present a study of the charge state conversion of single nitrogen-vacancy
(NV) defects hosted in nanodiamonds (NDs). We first show that the proportion of
negatively-charged NV defects, with respect to its neutral counterpart
NV, decreases with the size of the ND. We then propose a simple model
based on a layer of electron traps located at the ND surface which is in good
agreement with the recorded statistics. By using thermal oxidation to remove
the shell of amorphous carbon around the NDs, we demonstrate a significant
increase of the proportion of NV defects in 10-nm NDs. These results are
invaluable for further understanding, control and use of the unique properties
of negatively-charged NV defects in diamondComment: 6 pages, 4 figure
Template Independent Component Analysis: Targeted and Reliable Estimation of Subject-level Brain Networks using Big Data Population Priors
Large brain imaging databases contain a wealth of information on brain
organization in the populations they target, and on individual variability.
While such databases have been used to study group-level features of
populations directly, they are currently underutilized as a resource to inform
single-subject analysis. Here, we propose leveraging the information contained
in large functional magnetic resonance imaging (fMRI) databases by establishing
population priors to employ in an empirical Bayesian framework. We focus on
estimation of brain networks as source signals in independent component
analysis (ICA). We formulate a hierarchical "template" ICA model where source
signals---including known population brain networks and subject-specific
signals---are represented as latent variables. For estimation, we derive an
expectation maximization (EM) algorithm having an explicit solution. However,
as this solution is computationally intractable, we also consider an
approximate subspace algorithm and a faster two-stage approach. Through
extensive simulation studies, we assess performance of both methods and compare
with dual regression, a popular but ad-hoc method. The two proposed algorithms
have similar performance, and both dramatically outperform dual regression. We
also conduct a reliability study utilizing the Human Connectome Project and
find that template ICA achieves substantially better performance than dual
regression, achieving 75-250% higher intra-subject reliability
Novel Layers for Dies Used in Electromagnetic Sheet Metal Forming Processes
Due to the high forming velocities during electromagnetic sheet metal forming processes, a high impact force acts between workpiece and die. Here, the die surface sustains high damages shown by high wear and galling of the workpiece on the die surface. To enhance the die lifetime, a novel coating concept based on the PVD (physical vapour deposition) process was developed. In doing so, the hardness and the toughness of the designed layers were varied and adjusted to the demands of AlMg-sheet forming process
Measurement of the CMS Magnetic Field
The measurement of the magnetic field in the tracking volume inside the
superconducting coil of the Compact Muon Solenoid (CMS) detector under
construction at CERN is done with a fieldmapper designed and produced at
Fermilab. The fieldmapper uses 10 3-D B-sensors (Hall probes) developed at
NIKHEF and calibrated at CERN to precision 0.05% for a nominal 4 T field. The
precise fieldmapper measurements are done in 33840 points inside a cylinder of
1.724 m radius and 7 m long at central fields of 2, 3, 3.5, 3.8, and 4 T. Three
components of the magnetic flux density at the CMS coil maximum excitation and
the remanent fields on the steel-air interface after discharge of the coil are
measured in check-points with 95 3-D B-sensors located near the magnetic flux
return yoke elements. Voltages induced in 22 flux-loops made of 405-turn
installed on selected segments of the yoke are sampled online during the entire
fast discharge (190 s time-constant) of the CMS coil and integrated offline to
provide a measurement of the initial magnetic flux density in steel at the
maximum field to an accuracy of a few percent. The results of the measurements
made at 4 T are reported and compared with a three-dimensional model of the CMS
magnet system calculated with TOSCA.Comment: 4 pages, 5 figures, 15 reference
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