A Hybrid N-body--Coagulation Code for Planet Formation

We describe a hybrid algorithm to calculate the formation of planets from an initial ensemble of planetesimals. The algorithm uses a coagulation code to treat the growth of planetesimals into oligarchs and explicit N-body calculations to follow the evolution of oligarchs into planets. To validate the N-body portion of the algorithm, we use a battery of tests in planetary dynamics. Several complete calculations of terrestrial planet formation with the hybrid code yield good agreement with previously published calculations. These results demonstrate that the hybrid code provides an accurate treatment of the evolution of planetesimals into planets.Comment: Astronomical Journal, accepted; 33 pages + 11 figure

The Merging History of Massive Black Holes

We investigate a hierarchical structure formation scenario describing the evolution of a Super Massive Black Holes (SMBHs) population. The seeds of the local SMBHs are assumed to be 'pregalactic' black holes, remnants of the first POPIII stars. As these pregalactic holes become incorporated through a series of mergers into larger and larger halos, they sink to the center owing to dynamical friction, accrete a fraction of the gas in the merger remnant to become supermassive, form a binary system, and eventually coalesce. A simple model in which the damage done to a stellar cusps by decaying BH pairs is cumulative is able to reproduce the observed scaling relation between galaxy luminosity and core size. An accretion model connecting quasar activity with major mergers and the observed BH mass-velocity dispersion correlation reproduces remarkably well the observed luminosity function of optically-selected quasars in the redshift range 1<z<5. We finally asses the potential observability of the gravitational wave background generated by the cosmic evolution of SMBH binaries by the planned space-born interferometer LISA.Comment: 4 pages, 2 figures, Contribute to "Multiwavelength Cosmology", Mykonos, Greece, June 17-20, 200

Human pulmonary responses to experimental inhalation of high concentration fine and ultrafine magnesium oxide particles.

Exposure to air polluted with particles less than 2.5 micron in size is associated epidemiologically with adverse cardiopulmonary health consequences in humans. The goal of this study was to characterize human pulmonary responses to controlled experimental high-dose exposure to fine and ultrafine magnesium oxide particles. We quantified bronchoalveolar lavage (BAL) cell and cytokine concentrations, pulmonary function, and peripheral blood neutrophil concentrations in six healthy volunteers 18 to 20 hr after inhalation of fine and ultrafine magnesium oxide particles produced from a furnace system model. We compared postexposure studies with control studies from the same six subjects. Mean +/- standard deviation (SD) cumulative magnesium dose was 4,138 +/- 2,163 min x mg/m3. By weight, 28% of fume particles were ultrafine (<0.1 micron in diameter) and over 98% of fume particles were fine (<2.5 micron in diameter). There were no significant differences in BAL inflammatory cell concentrations, BAL interleukin (IL)-1, IL-6, IL-8, tumor necrosis factor, pulmonary function, or peripheral blood neutrophil concentrations postexposure compared with control. Our findings suggest that high-dose fine and ultrafine magnesium oxide particle exposure does not produce a measurable pulmonary inflammatory response. These findings are in marked contrast with the well-described pulmonary inflammatory response following zinc oxide particle inhalation. We conclude that fine and ultrafine particle inhalation does not result in toxicity in a generic manner independent of particle composition. Our findings support the concept that particle chemical composition, in addition to particle size, is an important determinant of respiratory effects

Collisional Dark Matter and the Origin of Massive Black Holes

If the cosmological dark matter is primarily in the form of an elementary particle which has cross section and mass for self-interaction having a ratio similar to that of ordinary nuclear matter, then seed black holes (formed in stellar collapse) will grow in a Hubble time, due to accretion of the dark matter, to a mass range 10^6 - 10^9 solar masses. Furthermore, the dependence of the final black hole mass on the galaxy velocity dispersion will be approximately as observed and the growth rate will show a time dependence consistent with observations. Other astrophysical consequences of collisional dark matter and tests of the idea are noted.Comment: 7 pages, no figures, LaTeX2e, Accepted for publication in Phys. Rev. Lett. Changed conten

Robust Machine Learning Applied to Astronomical Datasets I: Star-Galaxy Classification of the SDSS DR3 Using Decision Trees

We provide classifications for all 143 million non-repeat photometric objects in the Third Data Release of the Sloan Digital Sky Survey (SDSS) using decision trees trained on 477,068 objects with SDSS spectroscopic data. We demonstrate that these star/galaxy classifications are expected to be reliable for approximately 22 million objects with r < ~20. The general machine learning environment Data-to-Knowledge and supercomputing resources enabled extensive investigation of the decision tree parameter space. This work presents the first public release of objects classified in this way for an entire SDSS data release. The objects are classified as either galaxy, star or nsng (neither star nor galaxy), with an associated probability for each class. To demonstrate how to effectively make use of these classifications, we perform several important tests. First, we detail selection criteria within the probability space defined by the three classes to extract samples of stars and galaxies to a given completeness and efficiency. Second, we investigate the efficacy of the classifications and the effect of extrapolating from the spectroscopic regime by performing blind tests on objects in the SDSS, 2dF Galaxy Redshift and 2dF QSO Redshift (2QZ) surveys. Given the photometric limits of our spectroscopic training data, we effectively begin to extrapolate past our star-galaxy training set at r ~ 18. By comparing the number counts of our training sample with the classified sources, however, we find that our efficiencies appear to remain robust to r ~ 20. As a result, we expect our classifications to be accurate for 900,000 galaxies and 6.7 million stars, and remain robust via extrapolation for a total of 8.0 million galaxies and 13.9 million stars. [Abridged]Comment: 27 pages, 12 figures, to be published in ApJ, uses emulateapj.cl

Effects of dilute Zn impurities on the uniform magnetic susceptibility of YBa2Cu3O{7-delta}

The effects of dilute Zn impurities on the uniform magnetic susceptibility are calculated in the normal metallic state for a model of the spin fluctuations of the layered cuprates. It is shown that scatterings from extended impurity potentials can lead to a coupling of the q~(pi,pi) and the q~0 components of the magnetic susceptibility chi(q). Within the presence of antiferromagnetic correlations, this coupling can enhance the uniform susceptibility. The implications of this result for the experimental data on Zn substituted YBa2Cu3O{7-delta} are discussed.Comment: 4 pages, 4 figure

Swift J164449.3+573451 event: generation in the collapsing star cluster?

We discuss the multiband energy release in a model of a collapsing galactic nucleus, and we try to interpret the unique super-long cosmic gamma-ray event Swift J164449.3+573451 (GRB 110328A by early classification) in this scenario. Neutron stars and stellar-mass black holes can form evolutionary a compact self-gravitating subsystem in the galactic center. Collisions and merges of these stellar remnants during an avalanche contraction and collapse of the cluster core can produce powerful events in different bands due to several mechanisms. Collisions of neutron stars and stellar-mass black holes can generate gamma-ray bursts (GRBs) similar to the ordinary models of short GRB origin. The bright peaks during the first two days may also be a consequence of multiple matter supply (due to matter release in the collisions) and accretion onto the forming supermassive black hole. Numerous smaller peaks and later quasi-steady radiation can arise from gravitational lensing, late accretion of gas onto the supermassive black hole, and from particle acceleration by shock waves. Even if this model will not reproduce exactly all the Swift J164449.3+573451 properties in future observations, such collapses of galactic nuclei can be available for detection in other events.Comment: 7 pages, replaced by the final versio

Online Human Activity Recognition using Low-Power Wearable Devices

Human activity recognition~(HAR) has attracted significant research interest due to its applications in health monitoring and patient rehabilitation. Recent research on HAR focuses on using smartphones due to their widespread use. However, this leads to inconvenient use, limited choice of sensors and inefficient use of resources, since smartphones are not designed for HAR. This paper presents the first HAR framework that can perform both online training and inference. The proposed framework starts with a novel technique that generates features using the fast Fourier and discrete wavelet transforms of a textile-based stretch sensor and accelerometer. Using these features, we design an artificial neural network classifier which is trained online using the policy gradient algorithm. Experiments on a low power IoT device (TI-CC2650 MCU) with nine users show 97.7% accuracy in identifying six activities and their transitions with less than 12.5 mW power consumption.Comment: This is in proceedings of ICCAD 2018. The datasets are available at https://github.com/gmbhat/human-activity-recognitio