Cliques in high-dimensional random geometric graphs

International audienceRandom geometric graphs have become now a popular object of research. Defined rather simply, these graphs describe real networks much better than classical Erdős–Rényi graphs due to their ability to produce tightly connected communities. The $n$ vertices of a random geometric graph are points in $d$-dimensional Euclidean space, and two vertices are adjacent if they are close to each other. Many properties of these graphs have been revealed in the case when $d$ is fixed. However, the case of growing dimension $d$ is practically unexplored. This regime corresponds to a real-life situation when one has a data set of n observations with a significant number of features, a quite common case in data science today. In this paper, we study the clique structure of random geometric graphs when $n \to \infty$, and $d \to \infty$, and average vertex degree grows significantly slower than $n$. We show that under these conditions, random geometric graphs do not contain cliques of size 4 a.s. if only $d >> \log^{1+\epsilon}(n)$. As for the cliques of size 3, we present new bounds on the expected number of triangles in the case $\log^2(n) << d << \log^3(n)$ that improve previously known results. In addition, we provide new numerical results showing that the underlying geometry can be detected using the number of triangles even for small $n$

Genome-wide analyses identify a role for SLC17A4 and AADAT in thyroid hormone regulation.

Thyroid dysfunction is an important public health problem, which affects 10% of the general population and increases the risk of cardiovascular morbidity and mortality. Many aspects of thyroid hormone regulation have only partly been elucidated, including its transport, metabolism, and genetic determinants. Here we report a large meta-analysis of genome-wide association studies for thyroid function and dysfunction, testing 8 million genetic variants in up to 72,167 individuals. One-hundred-and-nine independent genetic variants are associated with these traits. A genetic risk score, calculated to assess their combined effects on clinical end points, shows significant associations with increased risk of both overt (Graves' disease) and subclinical thyroid disease, as well as clinical complications. By functional follow-up on selected signals, we identify a novel thyroid hormone transporter (SLC17A4) and a metabolizing enzyme (AADAT). Together, these results provide new knowledge about thyroid hormone physiology and disease, opening new possibilities for therapeutic targets

On the mechanisms governing gas penetration into a tokamak plasma during a massive gas injection

A new 1D radial fluid code, IMAGINE, is used to simulate the penetration of gas into a tokamak plasma during a massive gas injection (MGI). The main result is that the gas is in general strongly braked as it reaches the plasma, due to mechanisms related to charge exchange and (to a smaller extent) recombination. As a result, only a fraction of the gas penetrates into the plasma. Also, a shock wave is created in the gas which propagates away from the plasma, braking and compressing the incoming gas. Simulation results are quantitatively consistent, at least in terms of orders of magnitude, with experimental data for a D 2 MGI into a JET Ohmic plasma. Simulations of MGI into the background plasma surrounding a runaway electron beam show that if the background electron density is too high, the gas may not penetrate, suggesting a possible explanation for the recent results of Reux et al in JET (2015 Nucl. Fusion 55 093013)

Calibration and Characterization of the Radiation Assessment Detector (RAD) on Curiosity

The Radiation Assessment Detector, RAD, is one of the ten instruments that make up the science payload of the Mars Science Laboratory Curiosity rover. RAD is an energetic particle detector, capable of measuring the charged and neutral particles that make significant contributions to the radiation dose that will be received by future human explorers when they visit Mars. Prior to the launch of MSL in November 2011, RAD and its nearidentical twin flight spare unit were calibrated using laboratory sources, charged particle beams, and neutron fields. The initial calibration parameters obtained in these tests were used for real-time data analysis by the instrument’s onboard software. These parameters have subsequently been refined using data obtained during the cruise to Mars and during Curiosity’s mission on the surface of Mars. The most critical use of calibration is in the dosimetry analysis performed onboard. Calibration is also used in onboard analysis to determine which events should be stored for telemetry to Earth. Accelerator data obtained with the flight spare unit after Curiosity was launched provide detailed information about the response of the organic and inorganic scintillators to ion beams over a wide range of charge and energy. Here we report on the methods used to determine calibration parameters, the results obtained, as well as providing an overview of the modifications to the instrument’s software and configuration that have been made over the course of the mission

Observation of the rare decay K-S -> pi(0)e(+)e(-)

A search for the decay Ks->pi0e+e- has been made by the NA48/1 experiment at the CERN SPS accelerator. Using data collected during 89 days in 2002 with a high-intensity Ks beam, 7 events were found with a background of 0.15 events. The branching fraction BR(Ks->pi0e+e-, m(ee) > 0.165 GeV/c^2) = (3.0^{+1.5}_{-1.2}(stat) +/-0.2 (syst)) x 10^{-9} has been measured. Using a vector matrix element and a form factor equal to one, the measurement gives BR(Ks->pi0e+e-) = (5.8^{+2.9}_{-2.4}) x 10^{-9}.Comment: 15 pages, 7 figures. Accepted for publication in Physics Letters