Miracle-dz/UniFAR-FTUs huggingface dataset:
The pulse profile and spin evolution of the accreting pulsar in Terzan 5, IGR J17480-2446, during its 2010 outburst

We analyse the spectral and pulse properties of the 11 Hz transient accreting pulsar, IGR J17480-2446, in the globular cluster Terzan 5, considering all the available Rossi X-ray Timing Explorer, Swift and INTEGRAL observations performed during the outburst shown between October and November, 2010. By measuring the pulse phase evolution we conclude that the NS spun up at an average rate of = 1.48(2) × 10 12 Hz s 1 , compatible with the accretion of the Keplerian angular momentum of matter at the inner disc boundary. This confirms the trend previously observed by Papitto et al. (2011), who considered only the fir st few weeks of the outburst. Similar to other accreting pulsars, the stability of the pul se phases determined by using the second harmonic component is higher than that of the phases based on the fundamental frequency. Under the assumption that the second harmonic is a good tracer of the neutron star spin frequency, we successfully model its evolution in terms of a luminosity dependent accretion torque. If the NS accretes the specific Keplerian ang ular momentum of the in-flowing matter, we estimate the inner disc radius to lie between 47 and 93 km when the luminosity attains its peak value. Smaller values are obtained if the in teraction between the magnetic field lines and the plasma in the disc is considered. The phase-averaged spectrum is described by thermal Comptonization of photons with energy of � 1 keV. A hard to soft state transition is observed during the outburst rise. The Comptonized spectrum evolves from a Comptonizing cloud at an electron temperature of � 20 keV towards an optically denser cloud at kTe � 3 keV. At the same time, the pulse amplitude decreases from 27% to few per cent, as already noted by Papitto et al. (2011), and becomes strongly energy dependent. We discuss various possibilities to explain such a behaviour, proposing that at large accretion luminosities a s ignificant fraction of the in-falling matter is not channelled towards the magnetic poles, but rather accretes more evenly onto the NS surface.
A deep all-sky census of the Hyades

Aims. On the basis of the PPMXL catalogue we perform an all-sky census of the Hyades down to masses of about 0.2 m⊙ in a region up to 30 pc from the cluster centre. Methods. We use the proper motions from PPMXL in the convergent point method to determine probable kinematic members. From 2MASS photometry and CMC14r ′ -band photometry, we derive empirical colour-absolute magnitude diagrams and, finally, determine photometric membership for all kinematic candidates. Results. This is the first deep (r ′ ≤ 17) all-sky survey of the Hyades allowing a full three-dimensional analysis of the cluster. The survey is complete down to at least MKs = 7.3 or 0.25 m⊙. We find 724 stellar systems co-moving with the bulk Hyades sp ace velocity, which represent a total mass of 435 m⊙. The tidal radius is about 9 pc, and 275 m⊙ (364 systems) are gravitationally bound. This is the cluster proper. Its mass density profile is perfectly fitted b y a Plummer model with a central density of 2.21 m⊙pc −3 and a core radius of rco = 3.10 pc, while the half-mass radius is r h = 4.1 pc. There are another 100 m⊙ in a volume between one and two tidal radii (halo), and another 60 m⊙ up to a distance of 30 pc from the centre. Strong mass segregation is inherent in the cluster. The present-day luminosity and mass functions are noticeably different in various parts of the cluster (core, corona, halo, an d co-movers). They are strongly evolved compared to presently favoured initial mass functions. The analysis of the velocity dispersion of the cluster shows that about 20% of its members must be binaries. As a by-product, we find that presently available theoretical isochrones a re not able to adequately describe the near-infrared colour-absolute magnitude relation for those cluster stars that are less mas sive than about 0.6 m⊙.
Voltage and temperature dependencies of conductivity in gated graphene

The resistivity of gated graphene is studied taking into account electron and hole scattering by short- and long-range structural imperfections (the characteristics of disorder were taken from the scanning tunneling microscopy data) and by acoustic phonons. The calculations are based on the quasiclassical kinetic equation with the normalization condition fixed by surface charge. The gate-voltage and temperature effects on the resistance peak, which is centered at the point of intrinsic conductivity, are found to be in agreement with the transport measurements.
A SECOND GIANT PLANET IN 3:2 MEAN-MOTION RESONANCE IN THE HD 204313 SYSTEM

We present eight years of high-precision radial velocity (RV) data for HD 204313 from the 2.7 m Harlan J. Smith Telescope at McDonald Observatory. The star is known to have a giant planet (Msin i = 3.5 MJ) on a ∼1900 day orbit, and a Neptune-mass planet at 0.2 AU. Using our own data in combination with the published CORALIE RVs of Ségransan et al., we discover an outer Jovian (Msin i = 1.6 MJ) planet with P ∼ 2800 days. Our orbital fit suggests that the planets are in a 3:2 mean motion resonance, which would potentially affect their stability. We perform a detailed stability analysis and verify that the planets must be in resonance.
Energy aware service based information systems

The problem of Information Technology energy consumption has gained much attention recently due to the always increasing use of IT both for business and for personal reasons. In particular, data centers are now playing a much more important role in the modern society, where the information is available all the time and everywhere. In parallel with this scenario, governmental institutions have launched many international programs and regulations in order to measure and to reduce energy consumption in many areas, including Information and Communication Technology. In this context, the aim of this thesis is to study energy efficiency issues within data centers from the Information System perspective. The proposed approach integrates the application and infrastructure capabilities through Business Process co-design, in which the enactment of adaptation mechanisms is aligned with the business process requirements. Based on both energy and quality dimensions of service-based applications, we propose a model based approach and formulate a new constrained optimization problem that takes into consideration over-constrained solutions where the goal is to obtain the better trade-off between energy consumption and performance. These ideas are combined within a framework in which energy and performance do not always represent opposite objectives, but they are context dependent. Such dependencies are represented as a goal-based model, in which time-based analysis allow the identification of potential system threats and drive the selection of adaptation actions improving global quality and energy indicators. In addition, the framework includes an evolution mechanism that is able to evaluate past decisions feedback in order to adjust the model according to the current underlying environment. Finally, the benefits of the approach are analyzed in an experimental setting.
Observation and analysis of Fano-like lineshapes in the Raman spectra of molecules adsorbed at metal interfaces

Surface-enhanced Raman scattering (SERS) from bipyridyl ethylene adsorbed on gold dumbbells shows Fano-like spectra at high incident light intensity. This is accompanied by an increased electronic temperature, while no vibrational anti-Stokes scattering is observed. Theory indicates that interference between vibrational and electronic Raman scattering can yield such asymmetric scattering lineshapes. The best fit to observations is however obtained by disregarding this coupling and accounting for the detailed lineshape of the continuous electronic component of the SERS.
Transformers for Lexical Complexity Prediction in Spanish Language

: In this article we have presented a contribution to the prediction of the complexity of simple words in the Spanish language whose foundation is based on the combination of a large number of features of different types. We obtained the results after run the fined models based on Transformers and executed on the pre-trained models BERT, XLM-RoBERTa, and RoBERTa-large-BNE in the different datasets in Spanish and executed on several regression algorithms. The evaluation of the results determined that a good performance was achieved with a Mean Absolute Error (MAE) = 0.1598 and Pearson = 0.9883 achieved with the training and evaluation of the Random Forest Regressor algorithm for the refined BERT model. As a possible alternative proposal to achieve a better prediction of lexical complexity, we are very interested in continuing to carry out experimentations with data sets for Spanish, testing state-of-the-art Transformer models.
Techniques for high speed and low power digital to analog converters

The extraordinary evolution of today communication systems towards higher levels of integration is increasingly leading to the implementation of more and more complex functions in the digital domain. This process drives the need for the realization of high performance data converters in low-cost ultrascaled nanometer CMOS processes, connecting the systems digital core to the real analog world. In particular, academic and industrial research in the field of high-speed Nyquist-rate Digital-to-Analog Converters (DACs) is pushed forward by the growing interest in multi-carrier multi-band transmitters, for both wireless and wireline systems. Several communications standards have been recently developed requiring a DAC in the transmitter path with a sampling frequency in the GS/s range, while posing, at the same time, extremely stringent constraints on resolution, linearity and power. Unfortunately, the feature device scaling and the supply voltage reduction, in addition to the typically noise environment of large Systems-on-Chips (SoCs), are introducing critical issues on the design of such converters. More precisely, the analysis of state-of-the-art CMOS DACs reveals two fundamental trade-offs limiting their performances: the first one between low-frequency and high-frequency linearity while the second one between linearity and power efficiency. The essential objective of this thesis is the definition and the development of new design methodologies and techniques for the realization of high-speed highperformance DACs suitable for the integration in ultra-scaled CMOS technologies, which allow overcoming the fundamental trade-offs limiting performances. In particular, the thesis core will be the introduction of a new digital technique for the linearization of DAC static characteristic, which is based on the extensive use of digital adaptive filtering. As static non-linearity due to analog circuits impairments is canceled out in digital domain, a design full-oriented at optimizing high-frequency performances is allowed. Furthermore, the digital style of the proposed method particularly fits into integration in nanometer
Multi-Level Design of Process-Oriented Enterprise Information Systems Essential Guidelines and two Case Studies based on the FMMLx and the XModelerML

This paper presents prototypical multi-level models of two uses cases. They comprise models of business processes and models that represent the context required to execute a business process. On the one hand, the context consists of the organizational units that are responsible for the execution of processes. They are represented by a model of organizational structures. On the other hand, the context includes the artifacts that are needed or manipulated by processes. The models serve to demonstrate the specific power of multi-level modeling. First, they integrate models on higher levels, which correspond to domain-specific modeling languages, with those on lower levels. Second, models are supplemented with objects on L0 to demonstrate how these can be integrated. Third, the models are executable without the need to generate code, since models and corresponding program code share the same representation, thus demonstrating the possibility of advanced application system architectures, which allow users to navigate a comprehensive representation of the system they work with at runtime. The presentation of the models is supplemented with a general evaluation of multi-level concepts. The design of the models was inspired by the EMISA process challenge. Therefore, they are evaluated against the requirements defined with the challenge. In addition, a challenge is discussed that goes beyond the challenge, that is, the design of multi-level models of behavior.
Strain Control and Layer-Resolved Switching of Negative Capacitance in BaTiO$_3$/SrTiO$_3$ Superlattices.

Negative capacitance in BaTiO$_3$/SrTiO$_3$ superlattices is investigated by Monte Carlo simulations in an atomistic effective Hamiltonian model, using fluctuation formulas for responses to the local macroscopic field that incorporates depolarizing fields. We show epitaxial strain can tune the negative capacitance of the BaTiO$_3$ ferroelectric layer and the overall capacitance of the system over a broad temperature range. In addition, we predict and explain an original switching of the negative capacitance from the BaTiO$_3$ layer to the SrTiO$_3$ layer at low temperatures for intermediate strains. Our results indicate how the diffusive character of the multidomain transition in these superlattices improves their viability for capacitance applications.
Application-Specific Error Control in Inverse Identification

In this contribution we will employ the idea of adaptive modeling in the context of a two-step computation consisting of (i) a parameter identification problem where the identified parameters are used as inputs in (s) a subsequent simulation. Hence, in the result from the simulation in (s), we can expect two sources of error; the classical discretization error arising from the introduction of an FE-approximation in (s), and errors in the identified parameters stemming from (i). In a slightly more formal setting, we want to analyze the system
Tobacco Retail License Recognition Based on Dual Attention Mechanism

Images of tobacco retail licenses have complex unstructured characteristics, which is an urgent technical problem in the robot process automation of tobacco marketing. In this paper, a novel recognition approach using a double attention mechanism is presented to realize the automatic recognition and information extraction from such images. First, we utilized a DenseNet network to extract the license information from the input tobacco retail license data. Second, bi-directional long short-term memory was used for coding and decoding using a continuous decoder integrating dual attention to realize the recognition and information extraction of tobacco retail license images without segmentation. Finally, several performance experiments were conducted using a largescale dataset of tobacco retail licenses. The experimental results show that the proposed approach achieves a correction accuracy of 98.36% on the ZY-LQ dataset, outperforming most existing methods.
Sound texture synthesis from summary statistics. (Synthèse de textures sonores à partir de statistiques temps-fréquence)

This report is centered around a new method for sound texture synthesis : since it has been shown that only a handful of statistics (namely correlations and moments) from the envelopes of the frequency sub-bands of an audio signal were necessary to identify it as belonging to a given type of texture, the algorithm imposes those statistics upon a white noise to synthesize an output signal that is recognized as being of the same type as the analyzed sound texture. Since too strong of an imposition resulted in a synthesized signal being identical to the analyzed one, this internship mostly focused on developing a method which automatically selected the correlations needing to be imposed and the error that the gradient descent should aim for : this was done through the deﬁnition of a correlation score, the use of the standard deviation of the statistics as target error and the use of the Itakuro-Saito distance.
EVPI‐based importance sampling solution proceduresfor multistage stochastic linear programmeson parallel MIMD architectures

Multistage stochastic linear programming has many practical applications for problemswhose current decisions have to be made under future uncertainty. There are a variety ofmethods for solving the deterministic equivalent forms of these dynamic problems, includingthe simplex and interior‐point methods and nested Benders decomposition, which decomposesthe original problem into a set of smaller linear programming problems and hasrecently been shown to be superior to the alternatives for large problems. The Benderssubproblems can be visualised as being attached to the nodes of a tree which is formed fromthe realisations of the random data process determining the uncertainty in the problem. Thispaper describes a parallel implementation of the nested Benders algorithm which employsa farming technique to parallelize nodal subproblem solutions. Differing structures of thetest problems cause differing levels of speed‐up on a variety of multicomputing platforms:problems with few variables and constraints per node do not gain from this parallelisation.We therefore employ stage aggregation to such problems to improve their parallel solutionefficiency by increasing the size of the nodes and therefore the time spent calculating relativeto the time spent communicating between processors. A parallel version of a sequentialimportance sampling solution algorithm based on local expected value of perfect information(EVPI) is developed which is applicable to extremely large multistage stochastic linearprogrammes which either have too many data paths to solve directly or a continuous distributionof possible realisations. It utilises the parallel nested Benders algorithm and a parallelversion of an algorithm designed to calculate the local EVPI values for the nodes of the treeand achieves near linear speed‐up.
Topics in analytic number theory

In this thesis we prove several results in analytic number theory. 1. We show that there exist 3-digit palindromic primes in base b for a set of b having density 1 and that if b is sufficiently large then there is a $3$-digit palindrome in base b having precisely two prime factors. 2. We prove various estimates for averages of sums of Kloosterman fractions over primes. The first of these improves previous results of Fouvry-Shparlinski and Baker. 3. By using the q-analogue of van der Corput's method to estimate short Kloosterman sums we study the divisor function in an arithmetic progression to modulus q. We show that the expected asymptotic formula holds for a larger range of q than was previously known, provided that q has a certain factorisation. 4 Let ‖x‖ denote the distance from x to the nearest integer. We show that for any irrational α and any ϴ 5. By establishing an improved level of distribution we study almost-primes of the form f(p,n) where f is an irreducible binary form over Z. 6. We show that for an irreducible cubic f ? Z[x] and a full norm form $mathbf N$ for a number field $K/Q$, satisfying certain hypotheses, the variety $$f(t)=mathbf N(x_1,ldots,x_k) e 0$$ satisfies the Hasse principle. Our proof uses sieve methods.
A Methodology for the Automatic Annotation of Factuality in Spanish

: In the last decade, factuality has undeniably been an area of growing interest in Natural Language Processing. This paper describes a rule-based tool to automatically identify the factual status of events in Spanish text, understood with respect to the degree of commitment with which a narrator presents situations. Fac-tuality is represented compositionally, considering the following semantic categories: commitment, polarity, event structure, and time. In contrast with neural machine learning approaches, this tool is entirely based on manually created lexico-syntactic rules that systematize semantic and syntactic patterns of factuality. Thus, it is able to provide explanations for automatic decisions, which are very valuable to guarantee accountability of the system. We evaluate the performance of the system by comparison with a manually annotated Gold Standard, obtaining results that are comparable, if not better, to machine learning approaches for a related task, the FACT 2019 challenge at the IBERLEF evaluation forum.
The luminosity function of Swift long gamma-ray bursts

The formation rate of long gamma-ray bursts (GRBs) could follow the cosmic star formation rate (SFR) incorporating with cosmic metallicity evolution. Therefore, the luminosity function (LF) of GRBs can in principle be explored by modeling the redshift-luminosity distributions of Swift observed GRBs. For an assumed LF form as �z(L) / e −L p/L (L=Lp) −� (1 + z) � , we found that (1) the approximate broken-power law distribution of the luminosities of the Swift observed GRBs is probably caused by the luminosity selection of the telescope by reducing the number of the GRBs with low luminosities, (2) the evolution of the LF could approach to be very weak, i.e., � � 0, if the GRB environments are metal-poor as Z < (0:1 0:3)Z� , and (3) the slope of the LF can be derived to be within � � (1:55 1:72) by fitting the redshift distribution of the GRBs and qualitatively explaining the luminosity distribution. Finally, we also suggest an empirical detection efficiency as a function of flux for the Swift Burst Alert Telescope (BAT) in order to model the logN logP distribution of the GRBs.
Detection of trace explosives on relevant substrates using a mobile platform for photothermal infrared imaging spectroscopy (PT-IRIS)

This manuscript describes the results of recent tests regarding standoff detection of trace explosives on relevant substrates using a mobile platform. We are developing a technology for detection based on photo-thermal infrared (IR) imaging spectroscopy (PT-IRIS). This approach leverages one or more microfabricated IR quantum cascade lasers, tuned to strong absorption bands in the analytes and directed to illuminate an area on a surface of interest. An IR focal plane array is used to image the surface thermal emission upon laser illumination. The PT-IRIS signal is processed as a hyperspectral image cube comprised of spatial, spectral and temporal dimensions as vectors within a detection algorithm. Increased sensitivity to explosives and selectivity between different analyte types is achieved by narrow bandpass IR filters in the collection path. We have previously demonstrated the technique at several meters of stand-off distance indoors and in field tests, while operating the lasers below the infrared eye-safe intensity limit (100 mW/cm2). Sensitivity to explosive traces as small as a single 10 μm diameter particle (~1 ng) has been demonstrated. Analytes tested here include RDX, TNT, ammonium nitrate and sucrose. The substrates tested in this current work include metal, plastics, glass and painted car panels.