Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta

Adhesion to the extracellular matrix is positively regulated by retinoic acid in HepG2 cells

Aims: In this work, we aimed to investigate the possible modulation of cell–matrix interactions by retinoic acid (RA), in view of the well-known role of the extracellular matrix (ECM) and integrins in hepatocyte differentiation and proliferation. For this purpose, we analysed the adhesion ability of HepG2 cells on different substrates in the presence and absence of RA evaluating both the expression and cellular localisation of major proteins involved in focal contacts, using Western blot and confocal microscopy. Results: A positive and substratedependent effect of RA on cell–matrix adhesion was observed after long-term culture. The increased adhesiveness in the treated cells was accompanied by an enhanced expression of b1 and a3 integrin subunits, together with a redistribution of b1 receptors clustered at the basal surface. In contrast, the levels of focal adhesion kinase (FAK), paxillin and a-actinin were unchanged, as was the phosphorylation state of FAK. Nonetheless, a stronger association between b1 integrin and intracytoplasmatic proteins of focal contacts was observed in coimmunoprecipitation experiments after RA treatment, suggesting improved connection with the actin cytoskeleton.These results are consistent with previously described antiproliferative and differentiative effects of RA on transformed hepatocytes, and confirm the hypothesis of a direct influence of RA on specific adhesion molecules

Forex exchange rate forecasting using deep recurrent neural networks

Deep learning has substantially advanced the state of the art in computer vision, natural language processing, and other fields. The paper examines the potential of deep learning for exchange rate forecasting. We systematically compare long short-term memory networks and gated recurrent units to traditional recurrent network architectures as well as feedforward networks in terms of their directional forecasting accuracy and the profitability of trading model predictions. Empirical results indicate the suitability of deep networks for exchange rate forecasting in general but also evidence the difficulty of implementing and tuning corresponding architectures. Especially with regard to trading profit, a simpler neural network may perform as well as if not better than a more complex deep neural network.Peer Reviewe

The MOLLER Experiment: An Ultra-Precise Measurement of the Weak Mixing Angle Using Møller Scattering

The physics case and an experimental overview of the MOLLER (Measurement Of a Lepton Lepton Electroweak Reaction) experiment at the 12 GeV upgraded Jefferson Lab are presented. A highlight of the Fundamental Symmetries subfield of the 2007 NSAC Long Range Plan was the SLAC E158 measurement of the parity-violating asymmetry $A_{PV}$ in polarized electron-electron (M{\o}ller) scattering. The proposed MOLLER experiment will improve on this result by a factor of five, yielding the most precise measurement of the weak mixing angle at low or high energy anticipated over the next decade. This new result would be sensitive to the interference of the electromagnetic amplitude with new neutral current amplitudes as weak as $\sim 10^{-3}\cdot G_F$ from as yet undiscovered dynamics beyond the Standard Model. The resulting discovery reach is unmatched by any proposed experiment measuring a flavor- and CP-conserving process over the next decade, and yields a unique window to new physics at MeV and multi-TeV scales, complementary to direct searches at high energy colliders such as the Large Hadron Collider (LHC). The experiment takes advantage of the unique opportunity provided by the upgraded electron beam energy, luminosity, and stability at Jefferson Laboratory and the extensive experience accumulated in the community after a round of recent successfully completed parity-violating electron scattering experiment