Prediction of hearing recovery in sudden deafness treated with intratympanic steroids

The present study aims to obtain a probability model allowing the prediction of the auditory recovery in patients affected by sudden sensorineural hearing loss treated exclusively with intratympanic steroids. A monocentric retrospective chart review of three-hundred eighty-one patients has been performed. A Probit model was used to investigate the correlation between the success of the treatment (marked or total recovery according to Furuashi's criteria), and the delay between the onset of disease and the beginning of therapy. The age of the patients and the audiometric curve shapes were included in the analysis. Results show that delay is negatively correlated with the variable success. Considering the entire sample, each day of delay decreases by 3% the probability of success. The prediction model shows that for every day that passes from the onset of the disease the probability of success declines in absence of the medical treatment, hence we conclude that early treatment is strongly recommended

CURVED PLANFORM WINGS WITH A HIGH ASPECT RATIO FOR AIRCRAFTS OPERATING IN THE TRANSONIC REGIME

The present invention concerns an innovative wing (1) specific for an aircraft operating in the transonic regime and comprising: - A root section ; - A tip section and; - A leading edge for connecting the root section to the tip section. In accordance with the invention, the curved leading edge is configured according to a line by which locally the angle (Λ) formed by the forwarding direction of the wing and the perpendicular to the tangent of the leading edge increases progressively from the root section to the tip section of the wing. In such a way, the speed component (Vu) of the asymptotic flow orthogonal to the leading edge decreases progressively from the root section to the tip section, thus reducing the local Mach number progressively

A Hard Medium Survey with ASCA. IV: the Radio-Loud Type 2 QSO AXJ0843+294 2

We discuss the X-ray, optical and radio properties of AX J0843+2942, a high luminosity Type 2 AGN found in the ASCA Hard Serendipitous Survey. The X-ray spectrum is best described by an absorbed power-law model with photon index of Gamma = 1.72 (+0.3 -0.6) and intrinsic absorbing column density of NH = 1.44 (+0.33 -0.52) x 10E23 cm-2. The intrinsic luminosity in the 0.5-10 keV energy band is ~ 3x10E45 erg s-1, well within the range of quasar luminosities. AX J0843+2942, positionally coincident with the core of a triple and strong (S_1.4 GHz ~ 1 Jy; P_1.4 GHz ~ 9 x 10E33 erg s-1 Hz-1) radio source, is spectroscopically identified with a Narrow Line object (intrinsic FWHM of all the permitted emission lines <= 1200 km s-1) at z=0.398, having line features and ratios typical of Seyfert-2 like objects. The high X-ray luminosity, coupled with the high intrinsic absorption, the optical spectral properties and the radio power, allow us to propose AX J0843+2942 as a Radio-Loud "Type 2 QSO". A discussion of the SED of this object is presented here together with a comparison with the SED of Ultra Luminous Infrared Galaxies, other "Type 2 QSO" candidates from the literature, and "normal" Radio-Quiet and Radio-Loud QSOs.Comment: 10 pages, 7 figures, Latex manuscript, Accepted for publication in Ast ronomy and Astrophysic

Emotion-based analysis of programming languages on Stack Overflow

When developing a software engineering project, selecting the most appropriate programming language is a crucial step. Most often, feeling at ease with the possible options becomes almost as relevant as the technical features of the language. Therefore, it appears to be worth analyzing the role that the emotional component plays in this process. In this article, we analyze the trend of the emotions expressed by developers in 2018 on the Stack Overflow platform in posts concerning 26 programming languages. To do so, we propose a learning model trained by distant supervision and the comparison of two different classifier architectures

Lazy Network: A Word Embedding-Based Temporal Financial Network to Avoid Economic Shocks in Asset Pricing Models

Public companies in the US stock market must annually report their activities and financial performances to the SEC by filing the so-called 10-K form. Recent studies have demonstrated that changes in the textual content of the corporate annual filing (10-K) can convey strong signals of companies’ future returns. In this study, we combine natural language processing techniques and network science to introduce a novel 10-K-based network, named Lazy Network, that leverages year-on-year changes in companies’ 10-Ks detected using a neural network embedding model. (e Lazy Network aims to capture textual changes derived from financial or economic changes on the equity market. Leveraging the Lazy Network, we present a novel investment strategy that attempts to select the least disrupted and stable companies by capturing the peripheries of the Lazy Network. We show that this strategy earns statistically significant risk-adjusted excess returns. Specifically, the proposed portfolios yield up to 95 basis points in monthly five-factor alphas (over 12% annually), outperforming similar strategies in the literature

1WGAJ1226.9+3332: a high redshift cluster discovered by Chandra

We report the detection of 1WGAJ1226.9+3332 as an arcminute scale extended X-ray source with the Chandra X-ray Observatory. The Chandra observation and R and K band imaging strongly support the identification of 1WGAJ1226.9+3332 as a high redshift cluster of galaxies, most probably at z=0.85 +- 0.15, with an inferred temperature kT =10 (+4;-3) keV and an unabsorbed luminosity (in a r=120" aperture) of 1.3 (+0.16;-0.14) x 1e45 erg/s (0.5-10 keV). This indication of redshift is also supported by the K and R band imaging, and is in agreement with the spectroscopic redshift of 0.89 found by Ebeling et al. (2001). The surface brightness profile is consistent with a beta-model with beta=0.770 +- 0.025, rc=(18.1 +-0.9)" (corresponding to 101 +- 5 kpc at z=0.89), and S(0)=1.02 +- 0.08 counts/arcsec**2. 1WGAJ1226.9+3332 was selected as an extreme X-ray loud source with FX/FV>60; this selection method, thanks to the large area sampled, seems to be a highly efficient method for finding luminous high z clusters of galaxies.Comment: 5 pages, 5 figures, 1 table. Accepted for publication in ApJ main journal. Uses emulateapj.st