Gravitational waves emitted by distorted black holes---such as those arising from the coalescence of two neutron stars or black holes---carry not only information about the corresponding spacetime but also about the underlying theory of gravity. Although general relativity remains the simplest, most elegant and viable theory of gravitation, there are generic and robust arguments indicating that it is not the ultimate description of the gravitational universe. Here we focus on a particularly appealing extension of general relativity, which corrects Einstein's theory through the addition of terms which are second order in curvature: the topological Gauss-Bonnet invariant coupled to a dilaton. We study gravitational-wave emission from black holes in this theory, and {\bf(i)} find strong evidence that black holes are linearly (mode) stable against both axial and polar perturbations; {\bf(ii)} discuss how the quasinormal modes of black holes can be excited during collisions involving black holes, and finally {\bf(iii)} show that future ringdown detections with large signal-to-noise ratio would improve current constraints on the coupling parameter of the theory.

Active Malware Analysis involves modeling malware behavior by executing actions to trigger responses and explore multiple execution paths. One of the aims is making the action selection more efficient. This paper treats Active Malware Analysis as a Bayes-Active Markov Decision Process and uses a Bayesian Model Combination approach to train an analyzer agent. We show an improvement in performance against other Bayesian and stochastic approaches to Active Malware Analysis.

The authors of (Cho et al., 2014a) have shown that the recently introduced neural network translation systems suffer from a significant drop in translation quality when translating long sentences, unlike existing phrase-based translation systems. In this paper, we propose a way to address this issue by automatically segmenting an input sentence into phrases that can be easily translated by the neural network translation model. Once each segment has been independently translated by the neural machine translation model, the translated clauses are concatenated to form a final translation. Empirical results show a significant improvement in translation quality for long sentences.

This article presents two studies conducted with an affective dialogue system in which text-based system-user communication was used to model, generate, and present different affective and social interaction scenarios. We specifically investigated the influence of interaction context and roles assigned to the system and the participants, as well as the impact of pre-structured social interaction patterns that were modelled to mimic aspects of 'social exclusion' scenarios. The results of the first study demonstrate that both the social context of the interaction and the roles assigned to the system influence the system evaluation, interaction patterns, textual expressions of affective states, as well as emotional self-reports. The results observed for the second study show the system's ability to partially exclude a participant from a triadic conversation without triggering significantly different affective reactions or a more negative system evaluation. The experimental evidence provides insights on the perception, modelling and generation of affective and social cues in artificial systems that can be realized in different modalities, including the text modality, thus delivering valuable input for applying affective dialogue systems as tools for studying affect and social aspects in online communication.

High synchrotron peaked blazars (HSPs or HBLs) play a central role in very high energy (VHE) gamma-ray astronomy, and likely in neutrino astronomy. Currently, the largest compilation of HSP blazars, the 2WHSP sample, includes 1691 sources, but it is not complete neither in the radio nor in the X-ray band. In order to provide a more sizable and more accurate set of HSP blazars that is useful for future statistical studies and to plan for VHE/TeV observations, we present the largest sample of extreme and high synchrotron peaked (EHSP;HSP) blazars and blazar candidates: the 3HSP catalogue. The 3HSP catalogue includes 2013 sources, 88% of which with a redshift estimation, a much larger percentage than in any other list of HSP blazars. All new {\gamma}-ray detections are described in the First and Second Brazil ICRANet gamma-ray blazar catalogues (1BIGB & 2BIGB) also taking into account the 4FGL list of {\gamma}-ray sources published by the Fermi large area telescope (Fermi-LAT) team. Moreover, the cross-matching between the 2WHSP, 2FHL HSPs, and IceCube neutrinos position has suggested that HSPs are likely counterparts of neutrino events, which implies the 3HSP catalogue is useful also in that respect. The 3HSP catalogue features improved completeness compared to its predecessors, the 1WHSP and 2WHSP catalogues, and follows the track of their increasing relevance for VHE astronomy.

Active Malware Analysis involves modeling malware behavior by executing actions to trigger responses and explore multiple execution paths. One of the aims is making the action selection more efficient. This paper treats Active Malware Analysis as a Bayes-Active Markov Decision Process and uses a Bayesian Model Combination approach to train an analyzer agent. We show an improvement in performance against other Bayesian and stochastic approaches to Active Malware Analysis.

We introduce two Python frameworks to train neural networks on large datasets: Blocks and Fuel. Blocks is based on Theano, a linear algebra compiler with CUDA-support. It facilitates the training of complex neural network models by providing parametrized Theano operations, attaching metadata to Theano's symbolic computational graph, and providing an extensive set of utilities to assist training the networks, e.g. training algorithms, logging, monitoring, visualization, and serialization. Fuel provides a standard format for machine learning datasets. It allows the user to easily iterate over large datasets, performing many types of pre-processing on the fly.

(abridged) The ICM has been suggested to be buoyantly unstable in the presence of magnetic field and anisotropic thermal conduction. We perform first cosmological simulations of galaxy cluster formation that simultaneously include magnetic fields, radiative cooling and anisotropic thermal conduction. In isolated and idealized cluster models, the magnetothermal instability (MTI) tends to reorient the magnetic fields radially. Using cosmological simulations of the Santa Barbara cluster we detect radial bias in the velocity and magnetic fields. Such radial bias is consistent with either the inhomogeneous radial gas flows due to substructures or residual MTI-driven field rearangements that are expected even in the presence of turbulence. Although disentangling the two scenarios is challenging, we do not detect excess bias in the runs that include anisotropic thermal conduction. The anisotropy effect is potentially detectable via radio polarization measurements with LOFAR and SKA and future X-ray spectroscopic studies with the IXO. We demonstrate that radiative cooling boosts the amplification of the magnetic field by about two orders of magnitude beyond what is expected in the non-radiative cases. At z=0 the field is amplified by a factor of about 10^6 compared to the uniform magnetic field evolved due to the universal expansion alone. Interestingly, the runs that include both radiative cooling and anisotropic thermal conduction exhibit stronger magnetic field amplification than purely radiative runs at the off-center locations. In these runs, shallow temperature gradients away from the cluster center make the ICM neutrally buoyant. The ICM is more easily mixed in these regions and the winding up of the frozen-in magnetic field is more efficient resulting in stronger magnetic field amplification.

It has been shown in the literature that the event horizon of an extremal asymptotically flat Reissner-Nordstrom black hole is also a stable photon sphere. We further clarify this statement and give a general proof that this holds for a large class of static spherically symmetric black hole spacetimes with an extremal horizon. In contrast, in the Doran frame, an extremal asymptotically flat Kerr black hole has an unstable photon orbit on the equatorial plane of its horizon. In addition, we show that an extremal asymptotically flat Kerr-Newman black hole exhibits two equatorial photon orbits if a < M/2, one of which is on the extremal horizon in the Doran frame and is stable, whereas the second one outside the horizon is unstable. For a > M/2, there is only one equatorial photon orbit, located on the extremal horizon, and it is unstable. There can be no photon orbit on the horizon of a non-extremal Kerr-Newman black hole.

Gauge theories can often be formulated in different but physically equivalent ways, a concept referred to as duality. Using a formalism based on graded geometry, we provide a unified treatment of all parent theories for different types of standard and exotic dualizations. Our approach is based on treating tensor fields as functions of a certain degree on graded supermanifolds equipped with a suitable number of odd coordinates. We present a universal two-parameter first order action for standard and exotic electric/magnetic dualizations and prove in full generality that it yields two dual second order theories with the desired field content and dynamics. Upon choice of parameters, the parent theory reproduces (i) the standard and exotic duals for p-forms and (ii) the standard and double duals for (p,1) bipartite tensor fields, such as the linearized graviton and the Curtright field. Moreover, we discuss how deformations related to codimension-1 branes are included in the parent theory.

We have analysed all the X-ray images centred on Gamma Ray Bursts generated by Swift over the last 15 years using automatic tools that do not require any expertise in X-ray astronomy, producing results in excellent agreement with previous findings. This work, besides presenting the largest medium-deep survey of the X-ray sky and a complete sample of blazars, wishes to be a step in the direction of achieving the ultimate goal of the Open Universe Initiative, that is to enable non expert people to fully benefit of space science data, possibly extending the potential for scientific discovery, currently confined within a small number of highly specialised teams, to a much larger population. We have used the Swift_deepsky Docker container encapsulated pipeline to build the largest existing flux-limited and unbiased sample of serendipitous X-ray sources. Swift_deepsky runs on any laptop or desktop computer with a modern operating system. The tool automatically downloads the data and the calibration files from the archives, runs the official Swift analysis software and produces a number of results including images, the list of detected sources, X-ray fluxes, SED data, and spectral slope estimations. We used our source list to build the LogN-LogS of extra-galactic sources, which perfectly matches that estimated by other satellites. Combining our survey with multi-frequency data we selected a complete radio flux-density limited sample of High Energy Peaked (HBL) blazars.

Open Universe for blazars is a set of high-transparency data products for blazar science, and the tools designed to generate them. Blazar astrophysics is becoming increasingly data driven, depending on the integration and combined analysis of large quantities of data from the entire span of observational astrophysics techniques. The project was therefore chosen as one of the pilot activities within the United Nations Open Universe Initiative. In this work we developed a data analysis pipeline called Swift_deepsky, based on the Swift XRTDAS software and the XIMAGE package, encapsulated into a Docker container. Swift_deepsky, downloads and reads low-level data, generates higher-level products, detects X-ray sources and estimates several intensity and spectral parameters for each detection, thus facilitating the generation of complete and up-to-date science-ready catalogues from an entire space-mission dataset. The Docker version of the pipeline and its derived products is publicly available from the Open Universe Website at this http URL. We present the results of a detailed X-ray image analysis based on Swift_deepsky on all Swift XRT observations including a known blazar, carried out during the first 14 years of operations of the Swift Observatory. The resulting database includes over 27,000 images integrated in different X-ray bands, and a catalogue, called 1OUSXB, that provides intensity and spectral information for 33,396 X-ray sources, 8,896 of which are single or multiple detections of 2,308 distinct blazars. All the results can be accessed on-line in a variety of ways: e.g., from the Open Universe portal at this http URL, through Virtual Observatory services, via the VOU-Blazar tool and the SSDC SED builder. One of the most innovative aspects of this work is that the results can be safely reproduced and extended by anyone.

Blazars research is one of the hot topics of contemporary extra-galactic astrophysics. That is because these sources are the most abundant type of extra-galactic gamma-ray sources and are suspected to play a central role in multi-messenger astrophysics. We have used swift_xrtproc, a tool to carry out an accurate spectral and photometric analysis of the Swift-XRT data of all blazars observed by Swift at least 50 times between December 2004 and the end of 2020. We present a database of X-ray spectra, best-fit parameter values, count-rates and flux estimations in several energy bands of over 31,000 X-ray observations and single snapshots of 65 blazars. The results of the X-ray analysis have been combined with other multi-frequency archival data to assemble the broad-band Spectral Energy Distributions (SEDs) and the long-term light-curves of all sources in the sample. Our study shows that large X-ray luminosity variability on different timescales is present in all objects. Spectral changes are also frequently observed with a "harder-when-brighter" or "softer-when-brighter" behavior depending on the SED type of the blazars. The peak energy of the synchrotron component nu_peak in the SED of HBL blazars, estimated from the log-parabolic shape of their X-ray spectra, also exhibits very large changes in the same source, spanning a range of over two orders of magnitude in Mrk421 and Mrk501, the objects with the best data sets in our sample.

In the previous papers, we tried to analyze the complete loop counting functions that count all the loops in an infinite random walk represented by digits of a real number. In this paper, the consideration will be restricted to the partial loop counting functions $V$ that count the returns to the origin only. This simplification allows us to find closed-form expressions for various integrals related to $V$. Some applications to the complete loop counting functions, in particular, their connections with Bernoulli polynomials, are also provided.

We consider the Nelson model with ultraviolet cutoff, which describes the interaction between non-relativistic particles and a positive or zero mass quantized scalar field. We take the non-relativistic particles to obey Fermi statistics and discuss the time evolution in a mean-field limit of many fermions. In this case, the limit is known to be also a semiclassical limit. We prove convergence in terms of reduced density matrices of the many-body state to a tensor product of a Slater determinant with semiclassical structure and a coherent state, which evolve according to a fermionic version of the Schroedinger-Klein-Gordon equations.

Over the years, there have been campaigns to include the African languages in the growing research on machine translation (MT) in particular, and natural language processing (NLP) in general. Africa has the highest language diversity, with 1500-2000 documented languages and many more undocumented or extinct languages(Lewis, 2009; Bendor-Samuel, 2017). This makes it hard to keep track of the MT research, models and dataset that have been developed for some of them. As the internet and social media make up the daily lives of more than half of the world(Lin, 2020), as well as over 40% of Africans(Campbell, 2019), online platforms can be useful in creating accessibility to researches, benchmarks and datasets in these African languages, thereby improving reproducibility and sharing of existing research and their results. In this paper, we introduce Lanfrica, a novel, on-going framework that employs a participatory approach to documenting researches, projects, benchmarks and dataset on African languages.

Over the years, there have been campaigns to include the African languages in the growing research on machine translation (MT) in particular, and natural language processing (NLP) in general. Africa has the highest language diversity, with 1500-2000 documented languages and many more undocumented or extinct languages(Lewis, 2009; Bendor-Samuel, 2017). This makes it hard to keep track of the MT research, models and dataset that have been developed for some of them. As the internet and social media make up the daily lives of more than half of the world(Lin, 2020), as well as over 40% of Africans(Campbell, 2019), online platforms can be useful in creating accessibility to researches, benchmarks and datasets in these African languages, thereby improving reproducibility and sharing of existing research and their results. In this paper, we introduce Lanfrica, a novel, on-going framework that employs a participatory approach to documenting researches, projects, benchmarks and dataset on African languages.