Miracle-dz/UniFAR-FTUs huggingface dataset:
Spatial patterns of red fox (Vulpes vulpes) dens in a semi-arid landscape of North Africa

Abstract Different patterns of the use of space by red foxes (Vulpesvulpes) depend mainly on the distribution and availabilityof food patches. Nevertheless, other key resources such assuitable areas for dens can also inﬂuence the territory sizeand social organization of this predator. In fact, landscapemodiﬁcations such as habitat patchiness made by humanactivities (agricultural practices, urbanization) shouldcreate ample unfavourable zones for den settlement. Sev-eral studies focused on the distribution and use of dens bythe red fox in different habitat types but we do not haveany data on the den settlement and habitat composition inthe semi-arid regions of North Africa. This study wascarried out at Djerba island (SE Tunisia), virtually deprivedof surface water and with a semi-arid climate because ofthe bordering Sahara desert. We used line and randomtransects to ﬁnd fox dens. The spatial pattern of dens variedmainly in different habitat types and geoclimatic regions.Highly fragmented areas were also occupied by foxes thatbuilt dens close together inside small suitable patches. Foxdens had fewer entrances in more arid regions and theymainly faced the south. Habitat selection was inﬂuencedby water availability and irrigated tree plantations thatmodify soil textures allowing digging of dens. Moreover,asphalt roads limit den settlements. We suggest that thechoice of denning sites by foxes depends on persistingharsh conditions and human activities.Key words: den settlement, habitat types, patchiness, redfox, roads, Tunisia
Pulsar Candidate Sifting Using Multi-input Convolution Neural Networks

Pulsar candidate sifting is an essential process for discovering new pulsars. It aims to search for the most promising pulsar candidates from an all-sky survey, such as the High Time Resolution Universe (HTRU), Green Bank Northern Celestial Cap (GBNCC), Five-hundred-meter Aperture Spherical Radio Telescope, etc. Recently, machine learning (ML) has become a hot topic in investigations of pulsar candidate sifting. However, one typical challenge in ML for pulsar candidate sifting comes from the learning difficulty arising from the high class imbalance between the observed numbers of pulsars and non-pulsars. Therefore, this work proposes a novel framework for candidate sifting, named Multi-input Convolutional Neural Networks (MICNN). MICNN is an architecture of deep learning with four diagnostic plots of a pulsar candidate as its inputs. To train our MICNN on a highly class-imbalanced data set, a novel image augmentation technique is proposed, as well as a three-stage training strategy. Experiments on observations from HTRU and GBNCC show the effectiveness and robustness of these proposed techniques. In the experiments on HTRU, our MICNN model achieves a recall rate of 0.962 and a precision rate of 0.967 even in a highly class-imbalanced test data set.
Rate-dependent Stick-slips in Steady Shearing: Signature of Transition between Granular Solid and Fluid.

Despite extensive studies on either smooth granular-fluid flow or the solid-like deformation at the slow limit, the change between these two extremes remains largely unexplored. By systematically investigating the fluctuations of tightly packed grains under steady shearing, we identify a transition zone with prominent stick-slip avalanches. We establish a state diagram, and propose a new dimensionless shear rate based on the speed dependence of inter-particle friction and particle size. With fluid-immersed particles confined in a fixed volume and forced to "flow" at viscous numbers $J$ decades below reported values, we answer how a granular system can transition to the regime sustained by solid-to-solid friction that goes beyond existing paradigms based on suspension rheology.
Very high redshift quasars and the rapid emergence of super-massive black holes

The observation of quasars at very high redshift such as Pōniuā’ena is a challenge for models of supermassive black hole (SMBH) formation. This work presents a study of SMBH formation via known physical processes in starburst clusters formed at the onset of the formation of their hosting galaxy. While at the early stages hypermassive starburst clusters reach the luminosities of quasars, once their massive stars die, the ensuing gas accretion from the still forming host galaxy compresses its stellar black hole (BH) component to a compact state overcoming heating from the BH–BH binaries such that the cluster collapses, forming a massive SMBH-seed within about a hundred Myr. Within this scenario, the SMBH–spheroid correlation emerges near to exactly. The highest redshift quasars may thus be hypermassive starburst clusters or young ultracompact dwarf galaxies (UCDs), being the precursors of the SMBHs that form therein within about 200 Myr of the first stars. For spheroid masses |${\lesssim }10^{9.6}\, \mathrm{M}_\odot$|⁠, an SMBH cannot form and instead only the accumulated nuclear cluster remains. The number evolution of the quasar phases with redshift is calculated and the possible problem of missing quasars at very high redshift is raised. SMBH-bearing UCDs and the formation of spheroids are discussed critically in view of the high-redshift observations. A possible tension is found between the high star formation rates (SFRs) implied by downsizing and the observed SFRs, which may be alleviated within the IGIMF theory and if the downsizing times are somewhat longer.
The effect of tides on near-core rotation: analysis of 35 Kepler γ Doradus stars in eclipsing and spectroscopic binaries

We systematically searched for gravity- and Rossby-mode period spacing patterns in Kepler eclipsing binaries with γ Doradus pulsators. These stars provide an excellent opportunity to test the theory of tidal synchronization and angular momentum transport in F- and A-type stars. We discovered 35 systems that show clear patterns, including the spectroscopic binary KIC 10080943. Combined with 45 non-eclipsing binaries with γ Dor components that have been found using pulsation timing, we measured their near-core rotation rates and asymptotic period spacings. We find that many stars are tidally locked if the orbital periods are shorter than 10 d, in which the near-core rotation periods given by the traditional approximation of rotation are consistent with the orbital period. Compared to the single stars, γ Dor stars in binaries tend to have slower near-core rotation rates, likely a consequence of tidal spin-down. We also find three stars that have extremely slow near-core rotation rates. To explain these, we hypothesize that unstable tidally excited oscillations can transfer angular momentum from the star to the orbit, and slow the star below synchronism, a process we refer to as ‘inverse tides’.
Detecting bearish and bullish markets in financial time series using hierarchical hidden Markov models

Financial markets exhibit alternating periods of rising and falling prices. Stock traders seeking to make profitable investment decisions have to account for those trends, where the goal is to accurately predict switches from bullish to bearish markets and vice versa. Popular tools for modelling financial time series are hidden Markov models, where a latent state process is used to explicitly model switches among different market regimes. In their basic form, however, hidden Markov models are not capable of capturing both short- and long-term trends, which can lead to a misinterpretation of short-term price fluctuations as changes in the long-term trend. In this article, we demonstrate how hierarchical hidden Markov models can be used to draw a comprehensive picture of market behaviour, which can contribute to the development of more sophisticated trading strategies. The feasibility of the suggested approach is illustrated in two real-data applications, where we model data from the Deutscher Aktienindex and the Deutsche Bank stock. The proposed methodology is implemented in the R package fHMM, which is available on CRAN.
Families of Gröbner Degenerations, Grassmannians and Universal Cluster Algebras

Let $V$ be the weighted projective variety defined by a weighted homogeneous ideal $J$ and $C$ a maximal cone in the Grobner fan of $J$ with $m$ rays. We construct a flat family over $\mathbb A^m$ that assembles the Grobner degenerations of $V$ associated with all faces of $C$. This is a multi-parameter generalization of the classical one-parameter Grobner degeneration associated to a weight. We show that our family can be constructed from Kaveh-Manon's recent work on the classification of toric flat families over toric varieties: it is the pullback of a toric family defined by a Rees algebra with base $X_C$ (the toric variety associated to $C$) along the universal torsor $\mathbb A^m \to X_C$. We apply this construction to the Grassmannians ${\rm Gr}(2,\mathbb C^n)$ with their Plucker embeddings and the Grassmannian ${\rm Gr}(3,\mathbb C^6)$ with its cluster embedding. In each case there exists a unique maximal Grobner cone whose associated initial ideal is the Stanley-Reisner ideal of the cluster complex. We show that the corresponding cluster algebra with universal coefficients arises as the algebra defining the flat family associated to this cone. Further, for ${\rm Gr}(2,\mathbb C^n)$ we show how Escobar-Harada's mutation of Newton-Okounkov bodies can be recovered as tropicalized cluster mutation.
Neutrinoless double-electron capture

Double-beta processes play a key role in the exploration of neutrino and weak interaction properties, and in the searches for effects beyond the Standard Model. During the last half century many attempts were undertaken to search for double-beta decay with emission of two electrons, especially for its neutrinoless mode ($0\nu2\beta^-$), the latter being still not observed. Double-electron capture (2EC) was not in focus so far because of its in general lower transition probability. However, the rate of neutrinoless double-electron capture ($0\nu2$EC) can experience a resonance enhancement by many orders of magnitude in case the initial and final states are energetically degenerate. In the resonant case, the sensitivity of the $0\nu2$EC process can approach the sensitivity of the $0\nu2\beta^-$ decay in the search for the Majorana mass of neutrinos, right-handed currents, and other new physics. We present an overview of the main experimental and theoretical results obtained during the last decade in this field. The experimental part outlines search results of 2EC processes and measurements of the decay energies for possible resonant $0\nu$2EC transitions. An unprecedented precision in the determination of decay energies with Penning traps has allowed one to refine the values of the degeneracy parameter for all previously known near-resonant decays and has reduced the rather large uncertainties in the estimate of the $0\nu2$EC half-lives. The theoretical part contains an updated analysis of the electron shell effects and an overview of the nuclear structure models, in which the nuclear matrix elements of the $0\nu2$EC decays are calculated. One can conclude that the decay probability of $0\nu$2EC can experience a significant enhancement in several nuclides.
Peristaltic pumping in thin non-axisymmetric annular tubes

Abstract The two-dimensional laminar flow of a viscous fluid induced by peristalsis due to a moving wall wave has been studied previously for a rectangular channel, a circular tube and a concentric circular annulus. Here, we study peristaltic flow in a non-axisymmetric annular tube: in this case, the flow is three-dimensional, with motions in the azimuthal direction. This type of geometry is motivated by experimental observations of the pulsatile flow of cerebrospinal fluid along perivascular spaces surrounding arteries in the brain, which is at least partially driven by peristaltic pumping due to pulsations of the artery. These annular perivascular spaces are often eccentric and the outer boundary is seldom circular: their cross-sections can be well matched by a simple, adjustable model consisting of an inner circle (the outer wall of the artery) and an outer ellipse (the outer edge of the perivascular space), not necessarily concentric. We use this geometric model as a basis for numerical simulations of peristaltic flow: the adjustability of the model makes it suitable for other applications. We concentrate on the general effects of the non-axisymmetric configuration on the flow and do not attempt to specifically model perivascular pumping. We use a finite-element scheme to compute the flow in the annulus driven by a propagating sinusoidal radial displacement of the inner wall. Unlike the peristaltic flow in a concentric circular annulus, the flow is fully three-dimensional: azimuthal pressure variations drive an oscillatory flow in and out of the narrower gaps, inducing an azimuthal wiggle in the streamlines. We examine the dependence of the flow on the elongation of the outer elliptical wall and the eccentricity of the configuration. We find that the time-averaged volumetric flow is always in the same direction as the peristaltic wave and decreases with increasing ellipticity or eccentricity. The additional shearing motion in the azimuthal direction will increase mixing and enhance Taylor dispersion in these flows, effects that might have practical applications.
On the Maximal Operators of T Means with Respect to Walsh–Kaczmarz System

In this paper we prove and discuss some new (Hp, Lp,∞) type inequalities of the maximal operators of T means with monotone coefficients with respect to Walsh–Kaczmarz system. It is also proved that these results are the best possible in a special sense. As applications, both some well-known and new results are pointed out. In particular, we apply these results to prove a.e. convergence of such T means.
Re-observing the NLS1 galaxy RE J1034+396 – II. New insights on the soft X-ray excess, QPO, and the analogy with GRS 1915+105

RE J1034+396 displays the so far detected most significant X-ray Quasi-Periodic Oscillation (QPO) in AGN. We perform a detailed spectral-timing analysis on the data using recent simultaneous XMM-Newton, NuSTAR and Swift observations. We present the detailed energy dependence of the QPO's frequency, rms, coherence and phase lag. We construct various frequency-resolved variability spectra, which are modelled together with the time-averaged spectra. Our study shows that four components are required to fit all the spectra, including an inner disc component (diskbb), two warm corona components (CompTT-1 and CompTT-2) and a hot corona component (nthComp). An important discovery is that within the two warm corona components, CompTT-2 (the hotter, less luminous component) contains the QPO signal, while the stochastic variability is concentrated in CompTT-1. These components also allow us to fit the lag-energy spectra, as well as being able to describe the previous observation of a strong QPO in 2007, and the absent QPO observations, by varying only the relative normalizations of these components. Our multi-wavelength study shows that the QPO's detectability does not depend on the contemporaneous mass accretion rate through the outer disc as estimated from the UV flux. We do not detect a significant Iron K$\alpha$ line, nor any significant reflection component hump. Finally, we show that the rms and lag spectra of RE J1034+396 in the recent observation are very similar to the 67 Hz QPO in the micro-quasar GRS 1915+105. These new results reinforce the physical analogy between the two sources. We speculate that the QPO in both sources is due to expansion/contraction of the inner disc vertical structure.
Efficiency of COVID-19 mobile contact tracing containment by measuring time-dependent doubling time

The COVID-19 epidemic of the novel coronavirus (severe acute respiratory syndrome SARS-CoV-2) has spread around the world. While different containment policies using non-pharmaceutical interventions have been applied, their efficiencies are not known quantitatively. We show that the doubling time Td(t) with the success s factor, the characteristic time of the exponential growth of Td(t) in the arrested regime, is a reliable tool for early predictions of epidemic spread time evolution and provides a quantitative measure of the success of different containment measures. The efficiency of the containment policy lockdown case finding mobile tracing (LFT) using mandatory mobile contact tracing is much higher than that of the lockdown stop and go policy proposed by the Imperial College team in London. A very low s factor was reached by the LFT policy, giving the shortest time width of the positive case curve and the lowest number of fatalities. The LFT policy was able to reduce the number of fatalities by a factor of 100 in the first 100 d of the COVID-19 epidemic, reduce the time width of the COVID-19 pandemic curve by a factor 2.5, and rapidly stop new outbreaks and thereby avoid a second wave to date.
Transaction-level Model Simulator for Communication-Limited Accelerators

Rapid design space exploration in early design stage is critical to algorithm-architecture co-design for accelerators. In this work, a pre-RTL cycle-accurate accelerator simulator based on SystemC transaction-level modeling (TLM), AccTLMSim, is proposed for convolutional neural network (CNN) accelerators. The accelerator simulator keeps track of each bus transaction between accelerator and DRAM, taking into account the communication bandwidth. The simulation results are validated against the implementation results on the Xilinx Zynq. Using the proposed simulator, it is shown that the communication bandwidth is severely affected by DRAM latency and bus protocol overhead. In addition, the loop tiling is optimized to maximize the performance under the constraint of on-chip SRAM size. Furthermore, a new performance estimation model is proposed to speed up the design space exploration. Thanks to the proposed simulator and performance estimation model, it is possible to explore a design space of millions of architectural options within a few tens of minutes.
A Subspace Acceleration Method for Minimization Involving a Group Sparsity-Inducing Regularizer

We consider the problem of minimizing an objective function that is the sum of a convex function and a group sparsity-inducing regularizer. Problems that integrate such regularizers arise in modern machine learning applications, often for the purpose of obtaining models that are easier to interpret and that have higher predictive accuracy. We present a new method for solving such problems that utilize subspace acceleration, domain decomposition, and support identification. Our analysis shows, under common assumptions, that the iterate sequence generated by our framework is globally convergent, converges to an $\epsilon$-approximate solution in at most $O(\epsilon^{-(1+p)})$ (respectively, $O(\epsilon^{-(2+p)})$) iterations for all $\epsilon$ bounded above and large enough (respectively, all $\epsilon$ bounded above) where $p > 0$ is an algorithm parameter, and exhibits superlinear local convergence. Preliminary numerical results for the task of binary classification based on regularized logistic regression show that our approach is efficient and robust, with the ability to outperform a state-of-the-art method.
Few-Shot Keyword Spotting With Prototypical Networks

Recognizing a particular command or a keyword, keyword spotting has been widely used in many voice interfaces such as Amazon’s Alexa and Google Home. In order to recognize a set of keywords, most of the recent deep learning based approaches use a neural network trained with a large number of samples to identify certain pre-defined keywords. This restricts the system from recognizing new, user-defined keywords. Therefore, we first formulate this problem as a few-shot keyword spotting and approach it using metric learning. To enable this research, we also synthesize and publish a Few-shot Google Speech Commands dataset. We then propose a solution to the few-shot keyword spotting problem using temporal and dilated convolutions on prototypical networks. Our comparative experimental results demonstrate keyword spotting of new keywords using just a small number of samples. We report 94% accuracy on the task of 2-way 5-shot keyword spotting.
Exponential Sums with Sparse Polynomials over Finite Fields

We obtain new bounds of exponential sums modulo a prime $p$ with sparse polynomials $a_0x^{n_0} + \cdots + a_{\nu}x^{n_\nu}$. The bounds depend on various greatest common divisors of exponents $n_0, \ldots, n_\nu$ and their differences. In particular, two new bounds for binomials are obtained, improving previous results in broad ranges of parameters.
Pharmacological effects of gallic acid in health and diseases: A mechanistic review

Objective(s): Gallic acid is a natural phenolic compound found in several fruits and medicinal plants. It is reported to have several health-promoting effects. This review aims to summarize the pharmacological and biological activities of gallic acid in vitro and animal models to depict the pharmacological status of this compound for future studies. Materials and Methods: All relevant papers in the English language were collected up to June 2018. The keywords of gallic acid, antioxidant, anticancer, antimicrobial, gastrointestinal-, cardiovascular-, metabolic-, neuropsychological-, and miscellaneous- diseases were searched in Google Scholar, PubMed, and Scopus. Results: Several beneficial effects are reported for gallic acid, including antioxidant, anti-inflammatory, and antineoplastic properties. This compound has been reported to have therapeutic activities in gastrointestinal, neuropsychological, metabolic, and cardiovascular disorders. Conclusion: Current evidence confirms the pharmacological and therapeutic interventions of gallic acid in multiple health complications; however, available data are limited to just cellular and animal studies. Future investigations are essential to further define the safety and therapeutic efficacy of gallic acid in humans.
NGTS-11 b (TOI-1847 b): A Transiting Warm Saturn Recovered from a TESS Single-transit Event

We report the discovery of NGTS-11 b (=TOI-1847b), a transiting Saturn in a 35.46 day orbit around a mid K-type star ( = 5050 ± 80 K). We initially identified the system from a single-transit event in a TESS full-frame image light curve. Following 79 nights of photometric monitoring with an NGTS telescope, we observed a second full transit of NGTS-11 b approximately one year after the TESS single-transit event. The NGTS transit confirmed the parameters of the transit signal and restricted the orbital period to a set of 13 discrete periods. We combined our transit detections with precise radial-velocity measurements to determine the true orbital period and measure the mass of the planet. We find NGTS-11 b has a radius of , a mass of , and an equilibrium temperature of just K, making it one of the coolest known transiting gas giants. NGTS-11 b is the first exoplanet to be discovered after being initially identified as a TESS single-transit event, and its discovery highlights the power of intense photometric monitoring in recovering longer-period transiting exoplanets from single-transit events.