Multidrug-resistant Bacteroides fragilis group on the rise in Europe?

We report a case of multidrug-resistance (MDR) in a strain of Bacteroides fragilis from a blood culture and abdominal fluid in a Danish patient. The patient had not been travelling for several years and had not received antibiotics prior to the present case. We also summarize the cases that have been reported to date of MDR B. fragilis group in Europe. As far as we know, a case like this with MDR B. fragilis has not been described in Scandinavia before. © 2012

Bootstrapping Conditional GANs for Video Game Level Generation

Generative Adversarial Networks (GANs) have shown im-pressive results for image generation. However, GANs facechallenges in generating contents with certain types of con-straints, such as game levels. Specifically, it is difficult togenerate levels that have aesthetic appeal and are playable atthe same time. Additionally, because training data usually islimited, it is challenging to generate unique levels with cur-rent GANs. In this paper, we propose a new GAN architec-ture namedConditional Embedding Self-Attention Genera-tive Adversarial Network(CESAGAN) and a new bootstrap-ping training procedure. The CESAGAN is a modification ofthe self-attention GAN that incorporates an embedding fea-ture vector input to condition the training of the discriminatorand generator. This allows the network to model non-localdependency between game objects, and to count objects. Ad-ditionally, to reduce the number of levels necessary to trainthe GAN, we propose a bootstrapping mechanism in whichplayable generated levels are added to the training set. Theresults demonstrate that the new approach does not only gen-erate a larger number of levels that are playable but also gen-erates fewer duplicate levels compared to a standard GAN

Investigation of factors influencing the immunogenicity of hCG as a potential cancer vaccine

Human hCG and its β‐subunit (hCGβ) are tumour autocrine growth factors whose presence in the serum of cancer patients has been linked to poorer prognosis. Previous studies have shown that vaccines, which target these molecules and/or the 37 amino acid C‐terminal hCGβ peptide (hCGβCTP), induce antibody responses in a majority of human recipients. Here we explored whether the immunogenicity of vaccines containing an hCGβ mutant (hCGβR68E, designed to eliminate cross‐reactivity with luteinizing hormone) or hCGβCTP could be enhanced by coupling the immunogen to different carriers (KLH or Hsp70) using different cross‐linkers (EDC or GAD) and formulated with different adjuvants (RIBI or Montanide ISA720). While there was little to choose between KLH and Hsp70 as carriers, their influence on the effectiveness of a vaccine containing the BAChCGβR68E mutant was less marked, presumably because being a foreign species, this mutant protein itself might provide T‐helper epitopes. The mutant provided a significantly better vaccine than the hCGβCTP peptide irrespective of the carrier used, how it was cross‐linked to the carrier or which adjuvant was used when hCG was the target. Nonetheless, for use in humans where hCG is a tolerated self‐protein, the need for a carrier is of fundamental importance. Highest antibody titres were obtained by linking the BAChCGβR68E to Hsp70 as a carrier by GAD and using RIBI as the adjuvant, which also resulted in antibodies with significantly higher affinity than those elicited by hCGβCTP peptide vaccine. This makes this mutant vaccine a promising candidate for therapeutic studies in hCGβ‐positive cancer patients

Constraints on the Obliquities of Kepler Planet-Hosting Stars

Stars with hot Jupiters have obliquities ranging from 0-180 degrees, but relatively little is known about the obliquities of stars with smaller planets. Using data from the California-Kepler Survey, we investigate the obliquities of stars with planets spanning a wide range of sizes, most of which are smaller than Neptune. First, we identify 156 planet hosts for which measurements of the projected rotation velocity (vsini) and rotation period are both available. By combining estimates of v and vsini, we find nearly all the stars to be compatible with high inclination, and hence, low obliquity (less than about 20 degrees). Second, we focus on a sample of 159 hot stars (> 6000K) for which vsini is available but not necessarily the rotation period. We find 6 stars for which vsini is anomalously low, an indicator of high obliquity. Half of these have hot Jupiters, even though only 3% of the stars that were searched have hot Jupiters. We also compare the vsini distribution of the hot stars with planets to that of 83 control stars selected without prior knowledge of planets. The mean vsini of the control stars is lower than that of the planet hosts by a factor of approximately pi/4, as one would expect if the planet hosts have low obliquities. All these findings suggest that the Kepler planet-hosting stars generally have low obliquities, with the exception of hot stars with hot Jupiters.Comment: AJ, in pres

Quantum fingerprinting

Classical fingerprinting associates with each string a shorter string (its fingerprint), such that, with high probability, any two distinct strings can be distinguished by comparing their fingerprints alone. The fingerprints can be exponentially smaller than the original strings if the parties preparing the fingerprints share a random key, but not if they only have access to uncorrelated random sources. In this paper we show that fingerprints consisting of quantum information can be made exponentially smaller than the original strings without any correlations or entanglement between the parties: we give a scheme where the quantum fingerprints are exponentially shorter than the original strings and we give a test that distinguishes any two unknown quantum fingerprints with high probability. Our scheme implies an exponential quantum/classical gap for the equality problem in the simultaneous message passing model of communication complexity. We optimize several aspects of our scheme.Comment: 8 pages, LaTeX, one figur

EPIC 219217635: A Doubly Eclipsing Quadruple System Containing an Evolved Binary

We have discovered a doubly eclipsing, bound, quadruple star system in the field of K2 Campaign 7. EPIC 219217635 is a stellar image with $Kp = 12.7$ that contains an eclipsing binary (`EB') with $P_A = 3.59470$ d and a second EB with $P_B = 0.61825$ d. We have obtained followup radial-velocity (`RV') spectroscopy observations, adaptive optics imaging, as well as ground-based photometric observations. From our analysis of all the observations, we derive good estimates for a number of the system parameters. We conclude that (1) both binaries are bound in a quadruple star system; (2) a linear trend to the RV curve of binary A is found over a 2-year interval, corresponding to an acceleration, $\dot \gamma = 0.0024 \pm 0.0007$ cm s$^{-2}$; (3) small irregular variations are seen in the eclipse-timing variations (`ETVs') detected over the same interval; (4) the orbital separation of the quadruple system is probably in the range of 8-25 AU; and (5) the orbital planes of the two binaries must be inclined with respect to each other by at least 25$^\circ$. In addition, we find that binary B is evolved, and the cooler and currently less massive star has transferred much of its envelope to the currently more massive star. We have also demonstrated that the system is sufficiently bright that the eclipses can be followed using small ground-based telescopes, and that this system may be profitably studied over the next decade when the outer orbit of the quadruple is expected to manifest itself in the ETV and/or RV curves.Comment: Accepted for publication in MNRA

Warm-Start AlphaZero Self-Play Search Enhancements

Recently, AlphaZero has achieved landmark results in deep reinforcement learning, by providing a single self-play architecture that learned three different games at super human level. AlphaZero is a large and complicated system with many parameters, and success requires much compute power and fine-tuning. Reproducing results in other games is a challenge, and many researchers are looking for ways to improve results while reducing computational demands. AlphaZero's design is purely based on self-play and makes no use of labeled expert data ordomain specific enhancements; it is designed to learn from scratch. We propose a novel approach to deal with this cold-start problem by employing simple search enhancements at the beginning phase of self-play training, namely Rollout, Rapid Action Value Estimate (RAVE) and dynamically weighted combinations of these with the neural network, and Rolling Horizon Evolutionary Algorithms (RHEA). Our experiments indicate that most of these enhancements improve the performance of their baseline player in three different (small) board games, with especially RAVE based variants playing strongly