First 230 GHz VLBI Fringes on 3C 279 using the APEX Telescope

We report about a 230 GHz very long baseline interferometry (VLBI) fringe finder observation of blazar 3C 279 with the APEX telescope in Chile, the phased submillimeter array (SMA), and the SMT of the Arizona Radio Observatory (ARO). We installed VLBI equipment and measured the APEX station position to 1 cm accuracy (1 sigma). We then observed 3C 279 on 2012 May 7 in a 5 hour 230 GHz VLBI track with baseline lengths of 2800 M$\lambda$ to 7200 M$\lambda$ and a finest fringe spacing of 28.6 micro-arcseconds. Fringes were detected on all baselines with SNRs of 12 to 55 in 420 s. The correlated flux density on the longest baseline was ~0.3 Jy/beam, out of a total flux density of 19.8 Jy. Visibility data suggest an emission region <38 uas in size, and at least two components, possibly polarized. We find a lower limit of the brightness temperature of the inner jet region of about 10^10 K. Lastly, we find an upper limit of 20% on the linear polarization fraction at a fringe spacing of ~38 uas. With APEX the angular resolution of 230 GHz VLBI improves to 28.6 uas. This allows one to resolve the last-photon ring around the Galactic Center black hole event horizon, expected to be 40 uas in diameter, and probe radio jet launching at unprecedented resolution, down to a few gravitational radii in galaxies like M 87. To probe the structure in the inner parsecs of 3C 279 in detail, follow-up observations with APEX and five other mm-VLBI stations have been conducted (March 2013) and are being analyzed.Comment: accepted for publication in A&

Divisible E-Cash from Constrained Pseudo-Random Functions

International audienceElectronic cash (e-cash) is the digital analogue of regular cash which aims at preservingusers’ privacy. Following Chaum’s seminal work, several new features were proposed for e-cash toaddress the practical issues of the original primitive. Among them,divisibilityhas proved very usefulto enable efficient storage and spendings. Unfortunately, it is also very difficult to achieve and, todate, quite a few constructions exist, all of them relying on complex mechanisms that can only beinstantiated in one specific setting. In addition security models are incomplete and proofs sometimeshand-wavy.In this work, we first provide a complete security model for divisible e-cash, and we study the linkswith constrained pseudo-random functions (PRFs), a primitive recently formalized by Boneh andWaters. We exhibit two frameworks of divisible e-cash systems from constrained PRFs achievingsome specific properties: either key homomorphism or delegability. We then formally prove theseframeworks, and address two main issues in previous constructions: two essential security notionswere either not considered at all or not fully proven. Indeed, we introduce the notion ofclearing,which should guarantee that only the recipient of a transaction should be able to do the deposit,and we show theexculpability, that should prevent an honest user to be falsely accused, was wrongin most proofs of the previous constructions. Some can easily be repaired, but this is not the casefor most complex settings such as constructions in the standard model. Consequently, we providethe first construction secure in the standard model, as a direct instantiation of our framework

Instrumental drift in untargeted metabolomics: optimizing data quality with intrastudy QC samples

Untargeted metabolomics is an important tool in studying health and disease and is employed in fields such as biomarker discovery and drug development, as well as precision medicine. Although significant technical advances were made in the field of mass-spectrometry driven metabolomics, instrumental drifts, such as fluctuations in retention time and signal intensity, remain a challenge, particularly in large untargeted metabolomics studies. Therefore, it is crucial to consider these variations during data processing to ensure high-quality data. Here, we will provide recommendations for an optimal data processing workflow using intrastudy quality control (QC) samples that identifies errors resulting from instrumental drifts, such as shifts in retention time and metabolite intensities. Furthermore, we provide an in-depth comparison of the performance of three popular batch-effect correction methods of different complexity. By using different evaluation metrics based on QC samples and a machine learning approach based on biological samples, the performance of the batch-effect correction methods were evaluated. Here, the method TIGER demonstrated the overall best performance by reducing the relative standard deviation of the QCs and dispersion-ratio the most, as well as demonstrating the highest area under the receiver operating characteristic with three different probabilistic classifiers (Logistic regression, Random Forest, and Support Vector Machine). In summary, our recommendations will help to generate high-quality data that are suitable for further downstream processing, leading to more accurate and meaningful insights into the underlying biological processes

Toxicity Detection in Multiplayer Online Games

Social interactions in multiplayer online games are an essential feature for a growing number of players world-wide. However, this interaction between the players might lead to the emergence of undesired and unintended behavior, particularly if the game is designed to be highly competitive. Communication channels might be abused to harass and verbally assault other players, which negates the very purpose of entertainment games by creating a toxic player-community. By using a novel natural language processing framework, we detect profanity in chat-logs of a popular Multiplayer Online Battle Arena (MOBA) game and develop a method to classify toxic remarks. We show how toxicity is non-trivially linked to game success.Network Architectures and ServicesDistributed System

The Power of Social Features in Online Gaming

Within the vast and rich field of online gaming, a new generation of Online Social Games (OSGs) is emerging that have in common a core of social interaction, sometimes explicit, other times implicit. This common core of social experience promises to become at least as important as the experience derived from the game-­‐world itself. In this chapter, we consider the social side of OSGs and provide the following contributions: 1.We motivate the importance of taking social features into account to improve the quality of experience in online gaming. 2.We discuss the various dimensions of (player experience in) OSGs.3.We describe a social network analysis methodology for identifying relations in OSGs and indicate how this methodology could be used to improve the game-­‐play experience. 4.We also consider and illustrate how certain “social” behaviour, like toxicity, is negative and may harm the game-­‐play experience, if not adequately addressed. 5.We mention several directions for future research to put the power of social features in OSGs to good use.Embedded and Networked SystemsNetwork Architectures and ServicesDistributed System

Modification of translation factor aIF5A from Sulfolobus solfataricus

Eukaryotic eIF5A and its bacterial orthologue EF-P are translation elongation factors whose task is to rescue ribosomes from stalling during the synthesis of proteins bearing particular sequences such as polyproline stretches. Both proteins are characterized by unique post-translational modifications, hypusination and lysinylation, respectively, which are essential for their function. An orthologue is present in all Archaea but its function is poorly understood. Here, we show that aIF5A of the crenarchaeum Sulfolobus solfataricus is hypusinated and forms a stable complex with deoxyhypusine synthase, the first enzyme of the hypusination pathway. The recombinant enzyme is able to modify its substrate in vitro resulting in deoxyhypusinated aIF5A. Moreover, with the aim to identify the enzyme involved in the second modification step, i.e. hypusination, a set of proteins interacting with aIF5A was identified

Search for a grand tour of the Jupiter Galilean moons

We make use of self-adaptation in a Differential Evolution algorithm and of the asynchronous island model to design a complex interplanetary trajectory touring the Galilean Jupiter moons (Io, Europa, Ganymede and Callisto) using the multiple gravity assist technique. Such a problem was recently the subject of an international competition organized by the Jet Propulsion Laboratory (NASA) and won by a trajectory designed by aerospace experts and reaching the final score of 311/324. We apply our method to the very same problem finding new surprising designs and orbital strategies and a score of up to 316/324. Copyright © 2013 ACM

The OPS-SAT case: A data-centric competition for onboard satellite image classification

OnlinePublWhile novel artificial intelligence and machine learning techniques are evolving and disrupting established terrestrial technologies at an unprecedented speed, their adaptation onboard satellites is seemingly lagging. A major hindrance in this regard is the need for high-quality annotated data for training such systems, which makes the development process of machine learning solutions costly, time-consuming, and inefficient. This paper presents “the OPS-SAT case”, a novel data-centric competition that seeks to address these challenges. The powerful computational capabilities of the European Space Agency’s OPS-SAT satellite are utilized to showcase the design of machine learning systems for space by using only the small amount of available labeled data, relying on the widely adopted and freely available open-source software. The generation of a suitable dataset, design and evaluation of a public data-centric competition, and results of an onboard experimental campaign by using the competition winners’ machine learning model directly on OPS-SAT are detailed. The results indicate that adoption of open standards and deployment of advanced data augmentation techniques can retrieve meaningful onboard results comparatively quickly, simplifying and expediting an otherwise prolonged development period.Gabriele Meoni, Marcus Märtens, Dawa Derksen, Kenneth See, Toby Lightheart, Anthony Sécher, Arnaud Martin, David Rijlaarsdam, Vincenzo Fanizza, and Dario Izz

SiMeEx, a simplified method for metabolite extraction of adherent mammalian cells

A reliable method for metabolite extraction is central to mass spectrometry-based metabolomics. However, existing methods are lengthy, mostly due to the step of scraping cells from cell culture vessels, which restricts metabolomics in broader application such as lower cell numbers and high-throughput studies. Here, we present a simplified metabolite extraction (SiMeEx) method, to efficiently and quickly extract metabolites from adherent mammalian cells. Our method excludes the cell scraping step and therefore allows for a more efficient extraction of polar metabolites in less than 30 min per 12-well plate. We demonstrate that SiMeEx achieves the same metabolite recovery as using a standard method containing a scraping step, in various immortalized and primary cells. Omitting cell scraping does not compromise the performance of non-targeted and targeted GC-MS analysis, but enables metabolome analysis of cell culture on smaller well sizes down to 96-well plates. Therefore, SiMeEx demonstrates advantages not only on time and resources, but also on the applicability in high-throughput studies