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$^{0}$, 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

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

Nutrigenomics 2.0: The Need for Ongoing and Independent Evaluation and Synthesis of Commercial Nutrigenomics Tests' Scientific Knowledge Base for Responsible Innovation

Nutrigenomics is an important strand of precision medicine that examines the bidirectional interactions of the genome and nutritional exposures, and attendant health and disease outcomes. This perspectives article presents the new concept of "Nutrigenomics 2.0," so as to cultivate and catalyze the next generation research and funding priorities for responsible and sustainable knowledge-based innovations. We further contextualize our recent study of the 38 genes included in commercially available nutrigenomics tests, and offer additional context in relation to the 2014 American Academy of Nutrition and Dietetics position. Finally, we make a call in the best interest of the nutrigenomics science community, governments, global society, and commercial nutrigenomics test providers that new evidence evaluation and synthesis platforms are created concerning nutrigenomics tests before they become commercially available. The proposed assessment and synthesis of nutrigenomics data should be carried out on an ongoing dynamic basis with periodic intervals and/or when there is a specific demand for evidence synthesis, and importantly, in ways that are transparent where conflict of interests are disclosed fully by the involved parties, be they scientists, industry, governments, citizens, social scientists, or ethicists. We submit that this will cultivate responsible innovation, and business models that are sustainable, robust, and stand the test of time and context