Eclipsing variables: Catalogue and classification

A new version of the Catalogue of Eclipsing Variables is presented. The catalogue contains parameters and morphological types of light curves for some 7200 stars. Spectral classification is also given when available. Recently published information about classification of 1352 systems is also included in the catalogue. Thus, the catalogue represents the largest list of eclipsing binaries classified from observations. The analysis of stellar parameter distributions of catalogued eclipsing systems has been performed, and an algorithm of eclipsing-variable classification has been developed. Classification of some systems is troublesome or contradictory due to lack of modern observational data or their possible rare evolutionary class. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

UHECR Acceleration in Dark Matter Filaments of Cosmological Structure Formation

A mechanism for proton acceleration to ~10^21eV is suggested. It may operate in accretion flows onto thin dark matter filaments of cosmic structure formation. The flow compresses the ambient magnetic field to strongly increase and align it with the filament. Particles begin the acceleration by the ExB drift with the accretion flow. The energy gain in the drift regime is limited by the conservation of the adiabatic invariant p_perp^2/B. Upon approaching the filament, the drift turns into the gyro-motion around the filament so that the particle moves parallel to the azimuthal electric field. In this 'betatron' regime the acceleration speeds up to rapidly reach the electrodynamic limit $cp_{max}=eBR$ for an accelerator with magnetic field $B$ and the orbit radius $R$ (Larmor radius). The periodic orbit becomes unstable and the particle slings out of the filament to the region of a weak (uncompressed) magnetic field, which terminates the acceleration. The mechanism requires pre-acceleration that is likely to occur in structure formation shocks upstream or nearby the filament accretion flow. Previous studies identify such shocks as efficient proton accelerators to a firm upper limit ~10^19.5 eV placed by the catastrophic photo-pion losses. The present mechanism combines explosive energy gain in its final (betatron) phase with prompt particle release from the region of strong magnetic field. It is this combination that allows protons to overcome both the photo-pion and the synchrotron-Compton losses and therefore attain energy 10^21 eV. A requirement on accelerator to reach a given E_max placed by the accelerator energy dissipation \propto E_{max}^{2}/Z_0 due to the finite vacuum impedance Z_0 is circumvented by the cyclic operation of the accelerator.Comment: 34 pages, 10 figures, to be published in JCA

PREPARATION A SERIES OF ATROPISOMERIC BIPY-DIOXIDES BY OXIDATIVE COUPLING AND THEIR APPLICATION IN ASYMMETRIC CATALYSIS

The authors thank the Russian Science Foundation for Grant No. 18-73-10156

Corrosion-electrochemical behavior of nickel in an alkali metal carbonate melt under a chlorine-containing atmosphere

The corrosion-electrochemical behavior of a nickel electrode is studied in the melt of lithium, sodium, and potassium (40: 30: 30 mol %) carbonates in the temperature range 500-600°C under an oxidizing atmosphere CO2 + 0.5O2 (2: 1), which is partly replaced by gaseous chlorine (30, 50, 70%) in some experiments. In other experiments, up to 5 wt % chloride of sodium peroxide is introduced in a salt melt. A change in the gas-phase composition is shown to affect the mechanism of nickel corrosion. © 2013 Pleiades Publishing, Ltd

Fine-structure in the nonthermal X-ray emission of SNR RX J1713.7-3946 revealed by Chandra

We present morphological and spectroscopic studies of the northwest rim of the supernova remnant RX J1713.7-3946 based on observations by the Chandra X-ray observatory. We found a complex network of nonthermal (synchrotron) X-ray filaments, as well as a 'void' type structure -- a dim region of a circular shape -- in the northwest rim. It is remarkable that despite distinct brightness variations, the X-ray spectra everywhere in this region can be well fitted with a power-law model with photon index around 2.3. We briefly discuss some implications of these results and argue that the resolved X-ray features in the northwest rim may challenge the perceptions of standard (diffusive shock-acceleration) models concerning the production, propagation and radiation of relativistic particles in supernova remnants.Comment: 8 pages, 9 figures; accepted for publication in A&A; significant additions for publication in Main journal (previous version was for A&A Letter); a manuscript (as a single PDF file, 501kb) including all figures is available at http://www.astro.isas.ac.jp/~uchiyama/publication/h4106.pd

Escape-limited Model of Cosmic-ray Acceleration Revisited

The spectrum of cosmic rays (CRs) is affected by their escape from an acceleration site. This may have been observed not only in the gamma-ray spectrum of young supernova remnants (SNRs) such as RX J1713.7-3946, but also in the spectrum of CRs showering on the Earth. The escape-limited model of cosmic-ray acceleration is studied in general. We discuss the spectrum of CRs running away from the acceleration site. The model may also constrain the spectral index at the acceleration site and the ansatz with respect to the unknown injection process into the particle acceleration. We apply our model to CR acceleration in SNRs and in active galactic nuclei (AGN), which are plausible candidates of Galactic and extragalactic CRs, respectively. In particular, for young SNRs, we take account of the shock evolution with cooling of escaping CRs in the Sedov phase. The spectrum of escaping CRs generally depends on the physical quantities at the acceleration site, such as the spectral index, the evolution of the maximum energy of CRs and the evolution of the number of CRs. It is found that the spectrum of run-away particles can be both softer and harder than that of the acceleration site. The model could explain spectral indices of both Galactic and extragalactic CRs produced by SNRs and AGNs, respectively, suggesting the unified picture of CR acceleration.Comment: 11 pages, 2 figures, submitted to Astronomy and Astrophysic

The multi-band nonthermal emission from the supernova remnant RX J1713.7-3946

Nonthermal X-rays and very high-energy (VHE) $\gamma$-rays have been detected from the supernova remnant (SNR) RX J1713.7-3946, and especially the recent observations with the \textit{Suzaku} satellite clearly reveal a spectral cutoff in the X-ray spectrum, which directly relates to the cutoff of the energy spectrum of the parent electrons. However, whether the origin of the VHE $\gamma$-rays from the SNR is hadronic or leptonic is still in debate. We studied the multi-band nonthermal emission from RX J1713.7-3946 based on a semi-analytical approach to the nonlinear shock acceleration process by including the contribution of the accelerated electrons to the nonthermal radiation. The results show that the multi-band observations on RX J1713.7-3946 can be well explained in the model with appropriate parameters and the TeV $\gamma$-rays have hadronic origin, i.e., they are produced via proton-proton (p-p) interactions as the relativistic protons accelerated at the shock collide with the ambient matter.Comment: 6 pages, 5 figures, accepted by MNRA

TeV cosmic-ray proton and helium spectra in the myriad model

Recent measurements of cosmic ray proton and helium spectra show a hardening above a few hundreds of GeV. This excess is hard to understand in the framework of the conventional models of Galactic cosmic ray production and propagation. We propose here to explain this anomaly by the presence of local sources (myriad model). Cosmic ray propagation is described as a diffusion process taking place inside a two-zone magnetic halo. We calculate the proton and helium fluxes at the Earth between 50 GeV and 100 TeV. Improving over a similar analysis, we consistently derive these fluxes by taking into account both local and remote sources for which a unique injection rate is assumed. We find cosmic ray propagation parameters compatible with B/C measurements and for which the proton and helium spectra remarkably agree with the PAMELA and CREAM measurements over four decades in energy.Comment: 5 pages, 3 figure

PinnerSage: Multi-Modal User Embedding Framework for Recommendations at Pinterest

Latent user representations are widely adopted in the tech industry for powering personalized recommender systems. Most prior work infers a single high dimensional embedding to represent a user, which is a good starting point but falls short in delivering a full understanding of the user's interests. In this work, we introduce PinnerSage, an end-to-end recommender system that represents each user via multi-modal embeddings and leverages this rich representation of users to provides high quality personalized recommendations. PinnerSage achieves this by clustering users' actions into conceptually coherent clusters with the help of a hierarchical clustering method (Ward) and summarizes the clusters via representative pins (Medoids) for efficiency and interpretability. PinnerSage is deployed in production at Pinterest and we outline the several design decisions that makes it run seamlessly at a very large scale. We conduct several offline and online A/B experiments to show that our method significantly outperforms single embedding methods.Comment: 10 pages, 7 figure

Knowledge is at the Edge! How to Search in Distributed Machine Learning Models

With the advent of the Internet of Things and Industry 4.0 an enormous amount of data is produced at the edge of the network. Due to a lack of computing power, this data is currently send to the cloud where centralized machine learning models are trained to derive higher level knowledge. With the recent development of specialized machine learning hardware for mobile devices, a new era of distributed learning is about to begin that raises a new research question: How can we search in distributed machine learning models? Machine learning at the edge of the network has many benefits, such as low-latency inference and increased privacy. Such distributed machine learning models can also learn personalized for a human user, a specific context, or application scenario. As training data stays on the devices, control over possibly sensitive data is preserved as it is not shared with a third party. This new form of distributed learning leads to the partitioning of knowledge between many devices which makes access difficult. In this paper we tackle the problem of finding specific knowledge by forwarding a search request (query) to a device that can answer it best. To that end, we use a entropy based quality metric that takes the context of a query and the learning quality of a device into account. We show that our forwarding strategy can achieve over 95% accuracy in a urban mobility scenario where we use data from 30 000 people commuting in the city of Trento, Italy.Comment: Published in CoopIS 201