Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigating stellar‐mass black hole kicks

We investigate whether stellar-mass black holes have to receive natal kicks in order to explain the observed distribution of low-mass X-ray binaries containing black holes within our Galaxy. Such binaries are the product of binary evolution, where the massive primary has exploded forming a stellar-mass black hole, probably after a common envelope phase where the system contracted down to separations of the order of 10-30 R-circle dot. We perform population synthesis calculations of these binaries, applying both kicks due to supernova mass-loss and natal kicks due to the newly formed black hole. We then integrate the trajectories of the binary systems within the Galactic potential. We find that natal kicks are in fact necessary to reach the large distances above the Galactic plane achieved by some binaries. Further, we find that the distribution of natal kicks would seem to be similar to that of neutron stars, rather than one where the kick velocities are reduced by the ratio of black hole to neutron star mass (i.e. where the kicks have the same momentum). This result is somewhat surprising; in many pictures of stellar-mass black hole formation, one might have expected black holes to receive kicks having the same momentum (rather than the same speed) as those given to neutron stars. (Less)
On-off intermittency and amplitude-phase synchronization in Keplerian shear flows

We study the development of coherent structures in local simulations of the magnetorotational instability in accretion discs in regimes of on-off intermittency. In a previous paper [Chian et al., Phys. Rev. Lett. 104, 254102 (2010)], we have shown that the laminar and bursty states due to the on-off spatiotemporal intermittency in a one-dimensional model of nonlinear waves correspond, respectively, to nonattracting coherent structures with higher and lower degrees of amplitude-phase synchronization. In this paper we extend these results to a three-dimensional model of magnetized Keplerian shear flows. Keeping the kinetic Reynolds number and the magnetic Prandtl number fixed, we investigate two different intermittent regimes by varying the plasma beta parameter. The first regime is characterized by turbulent patterns interrupted by the recurrent emergence of a large-scale coherent structure known as two-channel flow, where the state of the system can be described by a single Fourier mode. The second regime is dominated by the turbulence with sporadic emergence of coherent structures with shapes that are reminiscent of a perturbed channel flow. By computing the Fourier power and phase spectral entropies in three-dimensions, we show that the large-scale coherent structures are characterized by a high degree of amplitude-phase synchronization.
High-order optical processes in intense laser field: Towards nonperturbative nonlinear optics

We develop an approach describing nonlinear-optical processes in the strong-field domain characterized by the nonperturbative field-with-matter interaction. The polarization of an isolated atom in the external field calculated via the numerical solution of the time-dependent Schr\"odinger equation agrees with our analytical findings. For the practically important case of one strong laser field and several weaker fields, we derive and analytically solve propagation equations describing high-order (HO) wave mixing, HO parametric amplification, and HO stimulated scattering. These processes provide a way of efficient coherent xuv generation. Some properties of HO processes are new in nonlinear optics: essentially complex values of the coefficients in the propagation equations, the superexponential (hyperbolic) growing solutions, etc. Finally, we suggest conditions for the practical realization of these processes and discuss published numerical and experimental results where such processes could have been observed.
The Technology Transfer Network Dynamic in the Information The Technology Transfer Network Dynamic in the Information Technology Industry of Yucatan, Mexico Technology Industry of Yucatan, Mexico

The present paper explores the technology transfer linkages among universities, research centers, and private companies in Yucatan, Mexico's information technology industry. Social network analysis (SNA) was used as a method to identify the structural characteristics of the technology transfer collaborations, and the changes in the patterns of interactions among institutions over the years. Data were obtained from the National Council for Science and Technology repository (CONACYT). Associations formed to enhance technology advancement and innovation practices between 2010 and 2018 were analyzed in this study. Network transitivity, the patterns of triadic configurations, and heterophily were compared to uncover the evolution of the innovation and technology transfer network of Yucatan, Mexico. Results indicate that the number of transitive triads has increased significantly since 2012, suggesting that a greater number of firms are networking with more than one university or research center. The degree of homophily showed a decreasing trend, mainly as a result of the increment in the proportion of associations among universities and research centers. This study aims to provide insights into the technology transfer network dynamics over the past decade that can support future efforts to enhance innovation and technology development in technology-based industries in the region.
Coverage and factors in�uencing uptake of the optimal dose of intermittent preventive treatment with sulfadoxine-pyrimethamine in rural areas before the adoption of the new World Health Organization guidelines in Burkina Faso

Malaria in pregnancy is a major public health problem in developing countries, with a high impact on maternal and child morbidity and mortality. Intermittent Preventive Treatment with Sulfadoxine-Pyrimethamine during pregnancy (IPTp-SP) is one of the strategies recommended by the World Health Organization (WHO) to �ght against this �ail. However, data on its use in rural Burkina Faso are scarce. The aim of our study was to determine the coverage and factors associated with uptake of the optimal dose (2 doses) of IPTp-SP in the Rural Health District of Houndé before the adoption of the new WHO guidelines. A cross-sectional study was conducted from 1 January 2006 to 31 December 2012 among 7188 pregnant women who showed up at least once for an antenatal consultation (ANC) in �ve rural primary healthcare centres in Health District of Houndé and for whom information on dispensation was available. Sociodemographic and IPTp-SP data were collected from ANC registries using a structured collection form. Factors in�uencing uptake of the optimal dose of IPTp-SP were explored using logistic regression.
Confining potential from interacting magnetic and torsion fields

Adopting the gauge-invariant but path-dependent variables formalism, we study the coupling of torsion fields with photons in the presence of an external background electromagnetic. We explicitly show that, in the case of a constant electric field strength expectation value, the static potential remains Coulombic, while in the case of a constant magnetic field strength expectation value a confining potential is obtained. This result displays a marked qualitative departure from the usual coupling of axionlike particles with photons in the presence of an external magnetic field.
The prosodic expressions of negative micro-sentiment vary across corpora

Dialog systems could benefit from the ability to detect instantaneous user dissatisfaction and other negative micro-sentiments. While this ability has been developed for some specific corpora, the question of generality has not previously been examined. In this paper we investigate whether the prosodic expression of negative microsentiment is similar across three diverse corpora: of commercial dialogs, cooperative gameplay
A LIGHT WEIGHT CONVOLUTION NEURAL NTWORK FOR FACIAL EMOTION DETECTION

- A Lightweight Convolution Neural Network for real-time facial expression detection employs multi-task cascaded convolution networks (MTCNN) to complete face detection and transmit the obtained face coordinates to the facial emotions’ classification model. To replace the fully connected layer in the standard deep CNN, this model uses Global Average Pooling. To some extent, each channel of the feature map is associated with the corresponding category, removing the black box features of a completely connected layer. This model combines residual modules and depth-wise separable convolutions, resulting in a smaller number of parameters and a more portable model. Because it has good detection and recognition effects, we choose the FER-2013 dataset.
INTELLIGENT SURVILLENCE SYSTEM

: In contemporary modern-day world, safety and safety are fundamental worries. To be economically robust, a rustic have to provide a secure and secure environment for investors and tourists. Closed Circuit television (CCTV) cameras, however, are used for surveillance and monitoring sports. A large number of surveillance cameras are to be had in numerous locations, but all of them simplest file footage. To analyse these videos, a large quantity of manpower is required, that's constantly unwanted because of time and labour waste. As a end result, having a system that detects crime in real time and signals the user is advantageous. This paper proposes a device for automatically detecting crime from surveillance digital camera pictures. The device has been pre-trained to hit upon crimes in real time and makes each online and offline alerts, that's useful in decreasing the opportunity of criminals escaping and quickly arrest them. If the lacking person enters the premises, the system detects her or him.
Decision-Making and Life Satisfaction: The Role of General Decision-Making Styles and Maximizing Tendency as Predictors

However, research that focused on testing the role of decision-making on life satisfaction was still limited, even though almost every aspect of human life involves decision-making, and the results could determine one's life situation. There were prior studies that attempted to explore the relationships between life satisfaction and decision-making; however, the results were not conclusive. Therefore, the research aimed to test the relationship between decision-making styles and life satisfaction. Convenience sampling was used in data collection, and 154 university students participated in the research. It used a cross-sectional survey design to test the research hypothesis. The survey consisted of research information, informed consent, demographic, and measuring instrument for research variables. Decision-making styles are measured using General Decision-Making Styles and Maximizing Scale. Life satisfaction was measured using the Satisfaction with Life Scale. The result of multiple linear regression analysis shows that rational decision-making style and tendency to satisfice significantly predict higher levels of life satisfaction, while spontaneous decision-making style and tendency to maximize predict lower levels of life satisfaction. On the other hand, intuitive, dependent, and avoidant decision-making styles do not significantly predict life satisfaction. The implication and direction for future research are discussed.
A Comparative Analysis of Different Machine Learning Classification Models for Sentiment Analysis

: With the world transforming into a digital age, the generation of textual documents is increasing at an unprecedented rate. This has consequently given rise to the need to organize these documents into proper categories and structure. Text classification, also known as text categorization, is the process of categorizing text into organized groups. In this paper, IMDB dataset of fifty thousand movie reviews is assessed and a classification system is designed. It compares Linear SVC, Bernoulli Naive Bayes, Logistic Regression, Multinomial Naïve Bayes and Random Forest as classification algorithms for applying sentiment analysis and finding the polarity of the given review. These classifiers were tested, analysed and compared with each other and finally a conclusion was obtained.The authors decided to show the comparison based on several parameters such as precision, accuracy, F1-score, recall and confusion matrix. The classifier which gets the highest among all these parameters is termed as the best machine learning algorithm for the text sentiment analysis of IMDB review data set.
Intrinsic rotation in tokamaks: theory

Self-consistent equations for intrinsic rotation in tokamaks with small poloidal magnetic field Bp compared to the total magnetic field B are derived. The model gives the momentum redistribution due to turbulence, collisional transport and energy injection. Intrinsic rotation is determined by the balance between the momentum redistribution and the turbulent diffusion and convection. Two different turbulence regimes are considered: turbulence with characteristic perpendicular lengths of the order of the ion gyroradius, ρi, and turbulence with characteristic lengths of the order of the poloidal gyroradius, (B/Bp)ρi. Intrinsic rotation driven by gyroradius scale turbulence is mainly due to the effect of neoclassical corrections and of finite orbit widths on turbulent momentum transport, whereas for the intrinsic rotation driven by poloidal gyroradius scale turbulence, the slow variation of turbulence characteristics in the radial and poloidal directions and the turbulent particle acceleration can be become as important as the neoclassical and finite orbit width effects. The magnetic drift is shown to be indispensable for the intrinsic rotation driven by the slow variation of turbulence characteristics and the turbulent particle acceleration. The equations are written in a form conducive to implementation in a flux tube code, and the effect of the radial variation of the turbulence is included in a novel way that does not require a global gyrokinetic formalism.
ON THE TIDAL ORIGIN OF HOT JUPITER STELLAR OBLIQUITY TRENDS

It is debated whether the two hot Jupiter populations—those on orbits misaligned from their host star's spin axis and those well-aligned—result from two migration channels or from two tidal realignment regimes. Here I demonstrate that equilibrium tides raised by a planet on its star can account for three observed spin–orbit alignment trends: the aligned orbits of hot Jupiters orbiting cool stars, the planetary mass cut-off for retrograde planets, and the stratification by planet mass of cool host stars' rotation frequencies. The first trend can be caused by strong versus weak magnetic braking (the Kraft break), rather than realignment of the star's convective envelope versus the entire star. The second trend can result from a small effective stellar moment of inertia participating in the tidal realignment in hot stars, enabling massive retrograde planets to partially realign to become prograde. The third trend is attributable to higher-mass planets more effectively counteracting braking to spin up their stars. Both hot and cool stars require a small effective stellar moment of inertia participating in the tidal realignment, e.g., an outer layer weakly coupled to the interior. I demonstrate via Monte Carlo that this model can match the observed trends and distributions of sky-projected misalignments and stellar rotation frequencies. I discuss implications for inferring hot Jupiter migration mechanisms from obliquities, emphasizing that even hot stars do not constitute a pristine sample.
Diagnosing failures of fairness transfer across distribution shift in real-world medical settings

Diagnosing and mitigating changes in model fairness under distribution shift is an important component of the safe deployment of machine learning in healthcare settings. Importantly, the success of any mitigation strategy strongly depends on the structure of the shift. Despite this, there has been little discussion of how to empirically assess the structure of a distribution shift that one is encountering in practice. In this work, we adopt a causal framing to motivate conditional independence tests as a key tool for characterizing distribution shifts. Using our approach in two medical applications, we show that this knowledge can help diagnose failures of fairness transfer, including cases where real-world shifts are more complex than is often assumed in the literature. Based on these results, we discuss potential remedies at each step of the machine learning pipeline.
A HARD AND VARIABLE X-RAY EMISSION FROM THE MASSIVE EMISSION-LINE STAR HD 157832

We report the discovery with XMM-Newton of a hard-thermal (T ∼ 130 MK) and variable X-ray emission from the Be star HD 157832, a new member of the puzzling class of γ-Cas-like Be/X-ray systems. Recent optical spectroscopy reveals the presence of a large/dense circumstellar disk seen at intermediate/high inclination. With a B1.5V spectral type, HD 157832 is the coolest γ-Cas analog known. In addition, its non-detection in the ROSAT all-sky survey shows that its average soft X-ray luminosity varied by a factor larger than ∼3 over a time interval of 14 yr. These two remarkable features, “low” effective temperature, and likely high X-ray variability turn HD 157832 into a promising object for understanding the origin of the unusually high-temperature X-ray emission in these systems.
Quantum Enhanced Energy Distribution for Information Heat Engines

A new scenario for energy distribution, security and shareability is presented that assumes the availability of quantum information heat engines and a thermal bath. It is based on the convertibility between entropy and work in the presence of a thermal reservoir. Our approach to the informational content of physical systems that are distributed between users is complementary to the conventional perspective of quantum communication. The latter places the value on the unpredictable content of the transmitted quantum states, while our interest focuses on their certainty. Some well-known results in quantum communication are reused in this context. Particularly, we describe a way to securely distribute quantum states to be used for unlocking energy from thermal sources. We also consider some multi-partite entangled and classically correlated states for a collaborative multi-user sharing of work extraction possibilities. Besides, the relation between the communication and work extraction capabilities is analyzed and written as an equation.
Natural extension of the generalized uncertainty principle

We discuss a gedanken experiment for the simultaneous measurement of the position and momentum of a particle in de Sitter spacetime. We propose an extension of the so-called generalized uncertainty principle (GUP) which implies the existence of a minimum observable momentum. The new GUP is directly connected to the nonzero cosmological constant, which becomes a necessary ingredient for a more complete picture of the quantum spacetime.
THE ARAUCARIA PROJECT. A DISTANCE DETERMINATION TO THE LOCAL GROUP SPIRAL M33 FROM NEAR-INFRARED PHOTOMETRY OF CEPHEID VARIABLES

Motivated by an amazing range of reported distances to the nearby Local Group spiral galaxy M33, we have obtained deep near-infrared photometry for 26 long-period Cepheids in this galaxy with the ESO Very Large Telescope. From the data, we constructed period–luminosity relations in the J and K bands which together with previous optical VI photometry for the Cepheids by Macri et al. were used to determine the true distance modulus of M33, and the mean reddening affecting the Cepheid sample with the multiwavelength fit method developed in the Araucaria Project. We find a true distance modulus of 24.62 for M33, with a total uncertainty of ±0.07 mag which is dominated by the uncertainty on the photometric zero points in our photometry. The reddening is determined as E(B − V) = 0.19 ± 0.02, in agreement with the value used by the Hubble Space Telescope Key Project of Freedman et al. but in some discrepancy with other recent determinations based on blue supergiant spectroscopy and an O-type eclipsing binary which yielded lower reddening values. Our derived M33 distance modulus is extremely insensitive to the adopted reddening law. We show that the possible effects of metallicity and crowding on our present distance determination are both at the 1%–2% level and therefore minor contributors to the total uncertainty of our distance result for M33.
Asteroseismic Properties of Solar-type Stars Observed with the NASA K2 Mission: Results from Campaigns 1–3 and Prospects for Future Observations

We present an asteroseismic analysis of 33 solar-type stars observed in short cadence (SC) during Campaigns (C) 1–3 of the NASA K2 mission. We were able to extract both average seismic parameters and individual mode frequencies for stars with dominant frequencies up to ∼3300 μHz, and we find that data for some targets are good enough to allow for a measurement of the rotational splitting. Modeling of the extracted parameters is performed by using grid-based methods using average parameters and individual frequencies together with spectroscopic parameters. For the target selection in C3, stars were chosen as in C1 and C2 to cover a wide range in parameter space to better understand the performance and noise characteristics. For C3 we still detected oscillations in 73% of the observed stars that we proposed. Future K2 campaigns hold great promise for the study of nearby clusters and the chemical evolution and age–metallicity relation of nearby field stars in the solar neighborhood. We expect oscillations to be detected in ∼388 SC targets if the K2 mission continues until C18, which will greatly complement the ∼500 detections of solar-like oscillations made for SC targets during the nominal Kepler mission. For ∼30–40 of these, including several members of the Hyades open cluster, we furthermore expect that inference from interferometry should be possible.
Fallopia ×moravica (Polygonaceae), a new hybrid between Fallopia compacta and F. sachalinensis

A new knotweed hybrid originating from the crossing of Fallopia compacta and F. sachalinensis is described based on plant material collected in the Moravia region in the Czech Republic as F. ×moravica. In addition to the Czech Republic, the hybrid has also been reported previously from the United Kingdom and New Zealand; however, it was not distinguished from F. ×bohemica, a hybrid between F. japonica and F. sachalinensis, since its one parent (F. compacta) has been generally treated only as a variety of F. japonica. F. ×moravica differs from the morphologically most similar hexaploid (2n = 6x = 66) F. ×bohemica by its tetraploid (2n = 4x = 44) number of chromosomes and by the constant absence of purple spots on stem internodes (which are usually present in F. ×bohemica). The new hybrid also differs from F. ×bohemica as well as other European Fallopia members by its unique relative genome size. Other potential morphological and cytological differences of F. ×moravica from the related F. ×bohemica are discussed.
Topological Quantum Numbers of Dyonic Fields Over Taub-NUT and Taub-Bolt Spaces

We study the global structure of dyonic fields on a Taub-Bolt background, and compare our results with similar fields over Taub-NUT and Schwarzschild spaces. It is shown that the electric and magnetic charges are quantized and lead to a classification of dyonic Taub-Bolt configurations. The quantization condition for the magnetic charge is similar to that of Dirac's monopole.