ShantanuT01/DACTYL-Pretraining huggingface dataset:
In May/June 2005, after 10 years of inactivity, the Be/X-ray binary system A 0535+26 underwent a major X-ray outburst. In this paper data are presented from 10 years of optical, IR and X-ray monitoring showing the behaviour of the system during the quiescent epoch and the lead up to the new outburst. The results show the system going through a period when the Be star in the system had a minimal circumstellar disk and then a dramatic disk recovery leading, presumably, to the latest flare up of X-ray emission. The data are interpreted in terms of the state of the disk and its interaction with the neutron star companion.
Do very high accuracies of deep networks suggest pride of effective AI or are deep networks prejudiced? Do they suffer from in-group biases (own-race-bias and own-age-bias), and mimic the human behavior? Is in-group specific information being encoded sub-consciously by the deep networks?   This research attempts to answer these questions and presents an in-depth analysis of `bias' in deep learning based face recognition systems. This is the first work which decodes if and where bias is encoded for face recognition. Taking cues from cognitive studies, we inspect if deep networks are also affected by social in- and out-group effect. Networks are analyzed for own-race and own-age bias, both of which have been well established in human beings. The sub-conscious behavior of face recognition models is examined to understand if they encode race or age specific features for face recognition. Analysis is performed based on 36 experiments conducted on multiple datasets. Four deep learning networks either trained from scratch or pre-trained on over 10M images are used. Variations across class activation maps and feature visualizations provide novel insights into the functioning of deep learning systems, suggesting behavior similar to humans. It is our belief that a better understanding of state-of-the-art deep learning networks would enable researchers to address the given challenge of bias in AI, and develop fairer systems.
Action segmentation is the task of predicting an action label for each frame of an untrimmed video. As obtaining annotations to train an approach for action segmentation in a fully supervised way is expensive, various approaches have been proposed to train action segmentation models using different forms of weak supervision, e.g., action transcripts, action sets, or more recently timestamps. Timestamp supervision is a promising type of weak supervision as obtaining one timestamp per action is less expensive than annotating all frames, but it provides more information than other forms of weak supervision. However, previous works assume that every action instance is annotated with a timestamp, which is a restrictive assumption since it assumes that annotators do not miss any action. In this work, we relax this restrictive assumption and take missing annotations for some action instances into account. We show that our approach is more robust to missing annotations compared to other approaches and various baselines.
It has been proposed that the scattering of electromagnetic zero-point radiation by accelerating objects results in a reaction force that may account, at least in part, for inertia [1,2,3]. This arises because of asymmetries in the electromagnetic zero-point field (ZPF) or electromagnetic quantum vacuum as perceived from an accelerating reference frame. In such a frame, the Poynting vector and momentum flux of the ZPF become non-zero. If one assumes that scattering of the ZPF radiation takes place at the level of quarks and electrons constituting matter, then it is possible for both Newton's equation of motion, ${\bf f}=m{\bf a}$, and its relativistic covariant generalization, ${\cal F}=d{\cal P}/d\tau$, to be obtained as a consequence of the non-zero ZPF momentum flux. We now conjecture that this scattering must take place at the Compton frequency of a particle, and that this interpretation of mass leads directly to the de Broglie relation characterizing the wave nature of that particle in motion, $\lambda_B=h/p$. This suggests a perspective on a connection between electrodynamics and the quantum wave nature of matter. Attempts to extend this perspective to other aspects of the vacuum are left for future consideration.
We propose to use a simple observable, the fractional area of "hot spots" in weak gravitational lensing mass maps which are detected with high significance, to determine background cosmological parameters. Because these high-convergence regions are directly related to the physical nonlinear structures of the universe, they derive cosmological information mainly from the nonlinear regime of density fluctuations. We show that in combination with future cosmic microwave background anisotropy measurements, this method can place constraints on cosmological parameters that are comparable to those from the redshift distribution of galaxy cluster abundances. The main advantage of the statistic proposed in this paper is that projection effects, normally the main source of uncertainty when determining the presence and the mass of a galaxy cluster, here serve as a source of information.
We present some congruences modulo $p^{6-d}$ for sums of the type $\sum_{k=0}^{(p-3)/2}x^k{2k\choose k}/(2k+1)^d$, for $d=1,2,3$ where $p>5$ is a prime.
We study the geometry of some moduli spaces of twisted sheaves on K3 surfaces. In particular we introduce induced automorphisms from a K3 surface on moduli spaces of twisted sheaves on this K3 surface. As an application we prove the unirationality of moduli spaces of irreducible holomorphic symplectic manifolds of $K3^{[2]}$-type admitting non symplectic involutions with invariant lattices $U(2)\oplus D_4(-1)$ or $U(2)\oplus E_8(-2)$. This complements the results obtained in [Mongardi and Wandel 2015], [Bossiere et al 2016], and the results from [arXiv:1603.00403] about the geometry of IHS fourfolds constructed using the Hilbert scheme of $(1,1)$ conics on Verra fourfolds. As a byproduct we find that IHS fourfolds of $K3^{[2]}$-type with Picard lattice $U(2)\oplus E_8(-2)$ naturally contain non-nodal Enriques surfaces.
Diffusion effect on chirality selection in a two-dimensional reaction-diffusion model is studied by the Monte Carlo simulation. The model consists of achiral reactants A which turn into either of the chiral products, R or S, in a solvent of chemically inactive vacancies V. The reaction contains the nonlinear autocatalysis as well as recycling process, and the chiral symmetry breaking is monitored by an enantiomeric excess $\phi$.   Without dilution a strong nonlinear autocatalysis ensures chiral symmetry breaking. By dilution, the chiral order $\phi$ decreases, and the racemic state is recovered below the critical concentration $c_c$. Diffusion effectively enhances the concentration of chiral species, and $c_c$ decreases as the diffusion coefficient $D$ increases. The relation between $\phi$ and $c$ for a system with a finite $D$ fits rather well to an interpolation formula between the diffusionless(D=0) and homogeneous ($D=\infty$) limits.
We determine the critical coupling constant above which dynamical chiral symmetry breaking occurs in a class of QCD motivated models where the gluon propagator has an enhanced infrared behavior. Using methods of bifurcation theory we find that the critical value of the coupling constant is always smaller than the one obtained for QCD.
We systematically study a natural problem in extremal graph theory, to minimize the number of edges in a graph with a fixed number of vertices, subject to a certain local condition: each vertex must be in a copy of a fixed graph $H$. We completely solve this problem when $H$ is a clique, as well as more generally when $H$ is any regular graph with degree at least about half its number of vertices. We also characterize the extremal graphs when $H$ is an Erd\H{o}s-R\'enyi random graph. The extremal structures turn out to have the similar form as the conjectured extremal structures for a well-studied but elusive problem of similar flavor with local constraints: to maximize the number of copies of a fixed clique in graphs in which all degrees have a fixed upper bound.
It has been recently proposed that the reduced density matrix may be used to derive the order parameter of a condensed matter system. Here we propose order parameters for the phases of a topological insulator, specifically a spinless Su-Schrieffer-Heeger (SSH) model, and consider the effect of short-range interactions. All the derived order parameters and their possible corresponding quantum phases are verified by the entanglement entropy and electronic configuration analysis results. The order parameter appropriate to the topological regions is further proved by calculating the Berry phase under twisted boundary conditions. It is found that the topological non-trivial phase is robust to the introduction of repulsive inter-site interactions, and can appear in the topological trivial parameter region when appropriate interactions are added.
We upgraded the chemical network from the UMIST Database for Astrochemistry 2006 to include isotopes such as ^{13}C and ^{18}O. This includes all corresponding isotopologues, their chemical reactions and the properly scaled reaction rate coefficients. We study the fractionation behavior of astrochemically relevant species over a wide range of model parameters, relevant for modelling of photo-dissociation regions (PDRs). We separately analyze the fractionation of the local abundances, fractionation of the total column densities, and fractionation visible in the emission line ratios. We find that strong C^+ fractionation is possible in cool C^+ gas. Optical thickness as well as excitation effects produce intensity ratios between 40 and 400. The fractionation of CO in PDRs is significantly different from the diffuse interstellar medium. PDR model results never show a fractionation ratio of the CO column density larger than the elemental ratio. Isotope-selective photo-dissociation is always dominated by the isotope-selective chemistry in dense PDR gas. The fractionation of C, CH, CH^+, and HCO^+ is studied in detail, showing that the fractionation of C, CH and CH^+ is dominated by the fractionation of their parental species. The light hydrides chemically derive from C^+, and, consequently, their fractionation state is coupled to that of C^+. The fractionation of C is a mixed case depending on whether formation from CO or HCO^+ dominates. Ratios of the emission lines of [C II], [C I], ^{13}CO, and H^{13}CO^+ provide individual diagnostics to the fractionation status of C^+, C, and CO.
In the present work, we consider a model with a fermionic field that is non-minimally coupled to gravity in the framework of teleparallel gravity. In order to determine forms of the coupling and potential function of fermionic field for the considered model, we use Noether symmetry approach. By applying this approach, for the Friedman-Robertson-Walker metric, we obtain respective potential and coupling function as a linear and power-law form of the bilinear $\Psi$. Further we search the exact cosmological solution of the model. It is shown that the fermionic field plays role of the dark energy.
U-statistics of spatial point processes given by a density with respect to a Poisson process are investigated. In the first half of the paper general relations are derived for the moments of the functionals using kernels from the Wiener-Ito chaos expansion. In the second half we obtain more explicit results for a system of U-statistics of some parametric models in stochastic geometry. In the logaritmic form functionals are connected to Gibbs models. There is an inequality between moments of Poisson and non-Poisson functionals in this case, and we have a version of the central limit theorem in the Poisson case.
Generalizations of the Schwarzschild and Kerr black holes are discussed in an astrophysically viable generalized theory of gravity, which includes higher curvature corrections in the form of the Gauss-Bonnet term, coupled to a dilaton. The angular momentum of these black holes can slightly exceed the Kerr bound. The location and the orbital frequency of particles in their innermost stable circular orbits can deviate significantly from the respective Kerr values. Study of the quasinormal modes of the static black holes gives strong evidence that they are mode stable against polar and axial perturbations. Future gravitational wave observations should improve the current bound on the Gauss-Bonnet coupling constant, based on observations of the low-mass x-ray binary A 0620-00.
In this article, we study the behavior of the stability of pullback of a vector bundle under a finite morphism from a (not necessarily smooth) stacky curve to an orbifold curve. We establish a categorical equivalence between proper formal orbifold curves and proper orbifold curves in the sense of Deligne-Mumford stacks. Using this identification, we define the notion of slope $P$-(semi)stability of vector bundles on proper formal orbifold curves $(X,P)$. We establish some equivalent conditions for a stacky genuinely ramified morphism, analogous to the case of curves. Finally, we show that for a cover of an orbifold curve arising as a cartesian pullback via a genuinely ramified morphism of smooth projective connected curves, the orbifold slope stability is preserved under the pullback.
Human action recognition from RGB-D (Red, Green, Blue and Depth) data has attracted increasing attention since the first work reported in 2010. Over this period, many benchmark datasets have been created to facilitate the development and evaluation of new algorithms. This raises the question of which dataset to select and how to use it in providing a fair and objective comparative evaluation against state-of-the-art methods. To address this issue, this paper provides a comprehensive review of the most commonly used action recognition related RGB-D video datasets, including 27 single-view datasets, 10 multi-view datasets, and 7 multi-person datasets. The detailed information and analysis of these datasets is a useful resource in guiding insightful selection of datasets for future research. In addition, the issues with current algorithm evaluation vis-\'{a}-vis limitations of the available datasets and evaluation protocols are also highlighted; resulting in a number of recommendations for collection of new datasets and use of evaluation protocols.
In this work we present different results concerning mixing properties of multivariate infinitely divisible (ID) stationary random fields. First, we derive some necessary and sufficient conditions for mixing of stationary ID multivariate random fields in terms of their spectral representation. Second, we prove that (linear combinations of independent) mixed moving average fields are mixing. Further, using a simple modification of the proofs of our results we are able to obtain weak mixing versions of our results. Finally, we prove the equivalence of ergodicity and weak mixing for multivariate ID stationary random fields.
We study the entropy time evolution of a quantum mechanical model, which is frequently used as a prototype for Anderson's localization. Recently Latora and Baranger [V. Latora, M. Baranger, Phys. Rev.Lett. 82, 520(1999)] found that there exist three entropy regimes, a transient regime of passage from dynamics to thermodynamics, a linear in time regime of entropy increase, namely a thermodynamic regime of Kolmogorov kind, and a saturation regime. We use the non-extensive entropic indicator recently advocated by Tsallis [ C. Tsallis, J. Stat. Phys. 52, 479 (1988)] with a mobile entropic index q, and we find that with the adoption of the ``magic'' value q = Q = 1/2 the Kolmogorov regime becomes more extended and more distinct than with the traditional entropic index q = 1. We adopt a two-site model to explain these properties by means of an analytical treatment and we argue that Q =1/2 might be a typical signature of the occurrence of Anderson's localization.
A dynamical model based on effective Lagrangians is proposed to describe the bremsstrahlung reaction $ \pi N \to \pi N \gamma$ at low energies. The $\Delta(1232)$ degrees of freedom are incorporated in a way consistent with both, electromagnetic gauge invariance and invariance under contact transformations. The model also includes the initial and final state rescattering of hadrons via a T-matrix with off the momentum-shell effects. The double differential distribution of photons is computed for three different T-matrix models and the results are compared with the soft photon approximation, and with experimental data. The aim of this analysis is to test the off-shell behaviour of the different T-matrices under consideration. Finally an alternative simpler dynamical model that incorporates the unstable character of the isobar-$\Delta(1232)$ through a complex mass, is presented. As we will see it is suitable for the study of the magnetic moment of the resonance.
We specialize the radiation-reaction part of the Arnowitt-Deser-Misner (ADM) Hamiltonian for many non-spinning point-like bodies, calculated by Jaranowski and Schaefer [1], to third-and-a-half post-Newtonian approximation to general relativity, to binary systems. This Hamiltonian is used for the computation of the instantaneous gravitational energy loss of a binary to 1PN reactive order. We also derive the equations of motion, which include PN reactive terms via Hamiltonian and Euler-Lagrangian approaches. The results are consistent with the expressions for reactive acceleration provided by Iyer-Will formalism in Ref. [2] in a general class of gauges.
We have conducted a survey of the CCS $J_N = 3_2-2_1$ line toward 11 dark clouds and star-forming regions at 30 arcsec spatial resolution and 0.054 km/s velocity resolution. CCS was only detected in quiescent clouds, not in active star-forming regions. The CCS distribution shows remarkable clumpy structure, and 25 clumps are identified in 7 clouds. Seven clumps with extremely narrow nonthermal linewidths < 0.1 km/s are among the most quiescent clumps ever found. The CCS clumps tend to exist around the higher density regions traced by NH_3 emission or submillimeter continuum sources, and the distribution is not spherically symmetric. Variation of the CCS abundance was suggested as an indicator of the evolutionary status of star formation. However, we can only find a weak correlation between N(CCS) and $n_{H_2,vir}$. The velocity distributions of CCS clouds reveal that a systematic velocity pattern generally exists. The most striking feature in our data is a ring structure in the position-velocity diagram of L1544 with an well-resolved inner hole of 0.04 pc x 0.13 km/s and an outer boundary of 0.16 pc x 0.55 km/s. This position-velocity structure clearly indicates an edge-on disk or ring geometry, and it can be interpreted as a collapsing disk with an infall velocity $\gtrsim$ 0.1 km/s and a rotational velocity less than our velocity resolution. Nonthermal linewidth distribution is generally coherent in CCS clouds, which could be evidence for the termination of Larson's Law at small scales, $\sim$ 0.1 pc.
Metal-oxide-semiconductor field-effect transistors (MOSFET's) using atomic-layer-deposited (ALD) Al$_2$O$_3$ as the gate dielectric are fabricated on the Si/Si$_{1-x}$Ge$_x$ heterostructures. The low-temperature carrier density of a two-dimensional electron system (2DES) in the strained Si quantum well can be controllably tuned from 2.5$\times10^{11}$cm$^{-2}$ to 4.5$\times10^{11}$cm$^{-2}$, virtually without any gate leakage current. Magnetotransport data show the homogeneous depletion of 2DES under gate biases. The characteristic of vertical modulation using ALD dielectric is shown to be better than that using Schottky barrier or the SiO$_2$ dielectric formed by plasma-enhanced chemical-vapor-deposition(PECVD).
We present a technique for jointly denoising bursts of images taken from a handheld camera. In particular, we propose a convolutional neural network architecture for predicting spatially varying kernels that can both align and denoise frames, a synthetic data generation approach based on a realistic noise formation model, and an optimization guided by an annealed loss function to avoid undesirable local minima. Our model matches or outperforms the state-of-the-art across a wide range of noise levels on both real and synthetic data.
Segmentation of focal (localized) brain pathologies such as brain tumors and brain lesions caused by multiple sclerosis and ischemic strokes are necessary for medical diagnosis, surgical planning and disease development as well as other applications such as tractography. Over the years, attempts have been made to automate this process for both clinical and research reasons. In this regard, machine learning methods have long been a focus of attention. Over the past two years, the medical imaging field has seen a rise in the use of a particular branch of machine learning commonly known as deep learning. In the non-medical computer vision world, deep learning based methods have obtained state-of-the-art results on many datasets. Recent studies in computer aided diagnostics have shown deep learning methods (and especially convolutional neural networks - CNN) to yield promising results. In this chapter, we provide a survey of CNN methods applied to medical imaging with a focus on brain pathology segmentation. In particular, we discuss their characteristic peculiarities and their specific configuration and adjustments that are best suited to segment medical images. We also underline the intrinsic differences deep learning methods have with other machine learning methods.
The present paper aims at the investigation of the global stability of large solutions to the compressible Navier-Stokes equations in the whole space. Our main results and innovations can be concluded as follows:   Under the assumption that the density $\rho(t,x)$ verifies $\rho(0,x)\ge c>0$ and $\sup_{t\ge0}\|\rho(t)\|_{C^\alpha}\le M$ with $\alpha$ sufficiently small, we establish a new mechanism for the convergence of the solution to its associated equilibrium with an explicit decay rate which is as the same as that for the heat equation. The main idea of the proof relies on the basic energy identity, techniques from blow-up criterion and a new estimate for the low frequency part of the solution.   We prove the global-in-time stability for the equations, i.e, any perturbed solution will remain close to the reference solution if initially they are close to each other. Our result implies that the set of the smooth and bounded solutions is an open set.   Going beyond the close-to-equilibrium setting, we construct the global large solutions to the equations with a class of initial data in $L^p$ type critical spaces. Here the "large solution" means that the vertical component of the velocity could be arbitrarily large initially.
This paper presents a robust multi-class multi-object tracking (MCMOT) formulated by a Bayesian filtering framework. Multi-object tracking for unlimited object classes is conducted by combining detection responses and changing point detection (CPD) algorithm. The CPD model is used to observe abrupt or abnormal changes due to a drift and an occlusion based spatiotemporal characteristics of track states. The ensemble of convolutional neural network (CNN) based object detector and Lucas-Kanede Tracker (KLT) based motion detector is employed to compute the likelihoods of foreground regions as the detection responses of different object classes. Extensive experiments are performed using lately introduced challenging benchmark videos; ImageNet VID and MOT benchmark dataset. The comparison to state-of-the-art video tracking techniques shows very encouraging results.