Searches for Gravitational Waves from Binary Neutron Stars: A Review

A new generation of observatories is looking for gravitational waves. These waves, emitted by highly relativistic systems, will open a new window for ob- servation of the cosmos when they are detected. Among the most promising sources of gravitational waves for these observatories are compact binaries in the final min- utes before coalescence. In this article, we review in brief interferometric searches for gravitational waves emitted by neutron star binaries, including the theory, instru- mentation and methods. No detections have been made to date. However, the best direct observational limits on coalescence rates have been set, and instrumentation and analysis methods continue to be refined toward the ultimate goal of defining the new field of gravitational wave astronomy.Comment: 30 pages, 5 Figures, to appear in "Short-Period Binary Stars: Observations, Analyses, and Results", Ed.s Eugene F. Milone, Denis A. Leahy, David W. Hobil

Electrospun nanosized cellulose fibers using ionic liquids at room temperature

Aiming at replacing the noxious solvents commonly employed, ionic-liquid-based solvents have been recently explored as novel non-volatile and non-flammable media for the electrospinning of polymers. In this work, nanosized and biodegradable cellulose fibers were obtained by electrospinning at room temperature using a pure ionic liquid or a binary mixture of two selected ionic liquids. The electrospinning of 8 wt% cellulose in 1-ethyl-3-methylimidazolium acetate medium (a low viscosity and room temperature ionic liquid capable of efficiently dissolving cellulose) showed to produce electrospun fibers with average diameters within (470 ± 110) nm. With the goal of tailoring the surface tension of the spinning dope, a surface active ionic liquid was further added in a 0.10 : 0.90 mole fraction ratio. Electrospun cellulose fibers from the binary mixture composed of 1-ethyl-3-methylimidazolium acetate and 1-decyl-3-methylimidazolium chloride ionic liquids presented average diameters within (120 ± 55) nm. Scanning electron microscopy, X-ray diffraction analysis, nuclear magnetic resonance spectroscopy, Fourier transform infrared spectroscopy, and thermogravimetric assays were used as core methods to evaluate the structural integrity, morphology and crystallinity of the raw, electrospun, and regenerated samples of cellulose. Moreover, the photoluminescence spectra of both raw and electrospun fibers were acquired, and compared, indicating that the cellulose emitting centers are not affected by the dissolution of cellulose in ionic liquids. Finally, the use of non-volatile solvents in electrospinning coupled to a water coagulation bath allows the recovery of the ionic fluid, and represents a step forward into the search of environmentally friendly alternatives to the conventional approaches

The cyclic GMP modulators YC-1 and zaprinast reduce vessel remodeling through anti-proliferative and pro-apoptotic effects

Guanosine-specific cyclic nucleotide signaling is suggested to serve protective actions in the vasculature; however, the influence of selective pharmacologic modulation of cyclic guanosine monophosphate (GMP)-synthesizing soluble guanylate cyclase (sGC) or cyclic GMP-degrading phosphodiesterase (PDE) on vessel remodeling has not been thoroughly examined. In this study, rat carotid artery balloon injury was performed and the growth-modulating effects of the sGC stimulator YC-1 or the cGMP-dependent PDE-V inhibitor zaprinast were examined. YC-1 or zaprinast elevated vessel cyclic GMP content, reduced medial wall and neointimal cell proliferation, stimulated medial and neointimal cellular apoptosis, and markedly attenuated neointimal remodeling in comparable fashion. Interestingly, sGC inhibition by ODQ failed to noticeably alter neointimal growth, and concomitant zaprinast with YC-1 did not modify any parameter compared to individual treatments. These results provide novel in vivo evidence that YC-1 and zaprinast inhibit injury-induced vascular remodeling through anti-mitogenic and pro-apoptotic actions and may offer promising therapeutic approaches against vasoproliferative disorders. Originally published J Cardiovasc Pharmacol Ther, Vol. 14, No. 2, June 200

Limits and dynamics of stochastic neuronal networks with random heterogeneous delays

Realistic networks display heterogeneous transmission delays. We analyze here the limits of large stochastic multi-populations networks with stochastic coupling and random interconnection delays. We show that depending on the nature of the delays distributions, a quenched or averaged propagation of chaos takes place in these networks, and that the network equations converge towards a delayed McKean-Vlasov equation with distributed delays. Our approach is mostly fitted to neuroscience applications. We instantiate in particular a classical neuronal model, the Wilson and Cowan system, and show that the obtained limit equations have Gaussian solutions whose mean and standard deviation satisfy a closed set of coupled delay differential equations in which the distribution of delays and the noise levels appear as parameters. This allows to uncover precisely the effects of noise, delays and coupling on the dynamics of such heterogeneous networks, in particular their role in the emergence of synchronized oscillations. We show in several examples that not only the averaged delay, but also the dispersion, govern the dynamics of such networks.Comment: Corrected misprint (useless stopping time) in proof of Lemma 1 and clarified a regularity hypothesis (remark 1

SpikingLab: modelling agents controlled by Spiking Neural Networks in Netlogo

The scientific interest attracted by Spiking Neural Networks (SNN) has lead to the development of tools for the simulation and study of neuronal dynamics ranging from phenomenological models to the more sophisticated and biologically accurate Hodgkin-and-Huxley-based and multi-compartmental models. However, despite the multiple features offered by neural modelling tools, their integration with environments for the simulation of robots and agents can be challenging and time consuming. The implementation of artificial neural circuits to control robots generally involves the following tasks: (1) understanding the simulation tools, (2) creating the neural circuit in the neural simulator, (3) linking the simulated neural circuit with the environment of the agent and (4) programming the appropriate interface in the robot or agent to use the neural controller. The accomplishment of the above-mentioned tasks can be challenging, especially for undergraduate students or novice researchers. This paper presents an alternative tool which facilitates the simulation of simple SNN circuits using the multi-agent simulation and the programming environment Netlogo (educational software that simplifies the study and experimentation of complex systems). The engine proposed and implemented in Netlogo for the simulation of a functional model of SNN is a simplification of integrate and fire (I&F) models. The characteristics of the engine (including neuronal dynamics, STDP learning and synaptic delay) are demonstrated through the implementation of an agent representing an artificial insect controlled by a simple neural circuit. The setup of the experiment and its outcomes are described in this work

A Note on Thermodynamics of Black Holes in Lovelock Gravity

The Lovelock gravity consists of the dimensionally extended Euler densities. The geometry and horizon structure of black hole solutions could be quite complicated in this gravity, however, we find that some thermodynamic quantities of the black holes like the mass, Hawking temperature and entropy, have simple forms expressed in terms of horizon radius. The case with black hole horizon being a Ricci flat hypersurface is particularly simple. In that case the black holes are always thermodynamically stable with a positive heat capacity and their entropy still obeys the area formula, which is no longer valid for black holes with positive or negative constant curvature horizon hypersurface. In addition, for black holes in the gravity theory of Ricci scalar plus a $2n$-dimensional Euler density with a positive coefficient, thermodynamically stable small black holes always exist in $D=2n+1$ dimensions, which are absent in the case without the Euler density term, while the thermodynamic properties of the black hole solutions with the Euler density term are qualitatively similar to those of black holes without the Euler density term as $D>2n+1$.Comment: Latex, 10 pages, v2: typos corrected, references added, to appear in PL

Holography of AdS vacuum bubbles

We consider the fate of AdS vacua connected by tunneling events. A precise holographic dual of thin-walled Coleman--de Luccia bounces is proposed in terms of Fubini instantons in an unstable CFT. This proposal is backed by several qualitative and quantitative checks, including the precise calculation of the instanton action appearing in evaluating the decay rate. Big crunches manifest themselves as time dependent processes which reach the boundary of field space in a finite time. The infinite energy difference involved is identified on the boundary and highlights the ill-defined nature of the bulk setup. We propose a qualitative scenario in which the crunch is resolved by stabilizing the CFT, so that all attempts at crunching always end up shielded from the boundary by the formation of black hole horizons. In all these well defined bulk processes the configurations have the same asymptotics and are finite energy excitations.Comment: version submitted to journal. Note added referring to previous work on holographic instantons

The complete mitochondrial genome of the foodborne parasitic pathogen Cyclospora cayetanensis

Cyclospora cayetanensis is a human-specific coccidian parasite responsible for several food and water-related outbreaks around the world, including the most recent ones involving over 900 persons in 2013 and 2014 outbreaks in the USA. Multicopy organellar DNA such as mitochondrion genomes have been particularly informative for detection and genetic traceback analysis in other parasites. We sequenced the C. cayetanensis genomic DNA obtained from stool samples from patients infected with Cyclospora in Nepal using the Illumina MiSeq platform. By bioinformatically filtering out the metagenomic reads of non-coccidian origin sequences and concentrating the reads by targeted alignment, we were able to obtain contigs containing Eimeria-like mitochondrial, apicoplastic and some chromosomal genomic fragments. A mitochondrial genomic sequence was assembled and confirmed by cloning and sequencing targeted PCR products amplified from Cyclospora DNA using primers based on our draft assembly sequence. The results show that the C. cayetanensis mitochondrion genome is 6274 bp in length, with 33% GC content, and likely exists in concatemeric arrays as in Eimeria mitochondrial genomes. Phylogenetic analysis of the C. cayetanensis mitochondrial genome places this organism in a tight cluster with Eimeria species. The mitochondrial genome of C. cayetanensis contains three protein coding genes, cytochrome (cytb), cytochrome C oxidase subunit 1 (cox1), and cytochrome C oxidase subunit 3 (cox3), in addition to 14 large subunit (LSU) and nine small subunit (SSU) fragmented rRNA genes

Brown dwarf census with the Dark Energy Survey year 3 data and the thin disc scale height of early L types

27 pages, 18 figuresIn this paper we present a catalogue of 11 745 brown dwarfs with spectral types ranging from L0 to T9, photometrically classified using data from the Dark Energy Survey (DES) year 3 release matched to the Vista Hemisphere Survey (VHS) DR3 and Wide-field Infrared Survey Explorer (WISE) data, covering ≈2400 deg2 up to iAB = 22. The classification method follows the same phototype method previously applied to SDSS-UKIDSS-WISE data. The most significant difference comes from the use of DES data instead of SDSS, which allow us to classify almost an order of magnitude more brown dwarfs than any previous search and reaching distances beyond 400 pc for the earliest types. Next, we also present and validate the GalmodBD simulation, which produces brown dwarf number counts as a function of structural parameters with realistic photometric properties of a given survey. We use this simulation to estimate the completeness and purity of our photometric LT catalogue down to iAB = 22, as well as to compare to the observed number of LT types. We put constraints on the thin disc scale height for the early L (L0–L3) population to be around 450 pc, in agreement with previous findings. For completeness, we also publish in a separate table a catalogue of 20 863 M dwarfs that passed our colour cut with spectral types greater than M6. Both the LT and the late M catalogues are found at DES release page https://des.ncsa.illinois.edu/releases/other/y3-mlt.Peer reviewedFinal Published versio

Transfer learning for galaxy morphology from one survey to another

© 2018 The Author(s). Published by Oxford University Press on behalf of the Royal Astronomical Society.Deep Learning (DL) algorithms for morphological classification of galaxies have proven very successful, mimicking (or even improving) visual classifications. However, these algorithms rely on large training samples of labelled galaxies (typically thousands of them). A key question for using DL classifications in future Big Data surveys is how much of the knowledge acquired from an existing survey can be exported to a new dataset, i.e. if the features learned by the machines are meaningful for different data. We test the performance of DL models, trained with Sloan Digital Sky Survey (SDSS) data, on Dark Energy survey (DES) using images for a sample of $\sim$5000 galaxies with a similar redshift distribution to SDSS. Applying the models directly to DES data provides a reasonable global accuracy ($\sim$ 90%), but small completeness and purity values. A fast domain adaptation step, consisting in a further training with a small DES sample of galaxies ($\sim$500-300), is enough for obtaining an accuracy > 95% and a significant improvement in the completeness and purity values. This demonstrates that, once trained with a particular dataset, machines can quickly adapt to new instrument characteristics (e.g., PSF, seeing, depth), reducing by almost one order of magnitude the necessary training sample for morphological classification. Redshift evolution effects or significant depth differences are not taken into account in this study.Peer reviewedFinal Accepted Versio