ShantanuT01/DACTYL-Pretraining huggingface dataset:
We investigate the efficiency of galactic mass loss, triggered by ram-pressure stripping and galactic winds of cluster galaxies, on the chemical enrichment of the intra-cluster medium (ICM). We combine N-body and hydrodynamic simulations with a semi-numerical galaxy formation model. By including simultaneously different enrichment processes, namely ram-pressure stripping and galactic winds, in galaxy-cluster simulations, we are able to reproduce the observed metal distribution in the ICM. We find that the mass loss by galactic winds in the redshift regime z>2 is ~10% to 20% of the total galactic wind mass loss, whereas the mass loss by ram-pressure stripping in the same epoch is up to 5% of the total ram-pressure stripping mass loss over the whole simulation time. In the cluster formation epochs z<2 ram-pressure stripping becomes more dominant than galactic winds. We discuss the non-correlation between the evolution of the mean metallicity of galaxy clusters and the galactic mass losses. For comparison with observations we present two dimensional maps of the ICM quantities and radial metallicity profiles. The shape of the observed profiles is well reproduced by the simulations in the case of merging systems. In the case of cool-core clusters the slope of the observed profiles are reproduced by the simulation at radii below ~300 kpc, whereas at larger radii the observed profiles are shallower. We confirm the inhomogeneous metal distribution in the ICM found in observations. To study the robustness of our results, we investigate two different descriptions for the enrichment process interaction.
Training object detectors with only image-level annotations is very challenging because the target objects are often surrounded by a large number of background clutters. Many existing approaches tackle this problem through object proposal mining. However, the collected positive regions are either low in precision or lack of diversity, and the strategy of collecting negative regions is not carefully designed, neither. Moreover, training is often slow because region selection and object detector training are processed separately. In this context, the primary contribution of this work is to improve weakly supervised detection with an optimized region selection strategy. The proposed method collects purified positive training regions by progressively removing easy background clutters, and selects discriminative negative regions by mining class-specific hard samples. This region selection procedure is further integrated into a CNN-based weakly supervised detection (WSD) framework, and can be performed in each stochastic gradient descent mini-batch during training. Therefore, the entire model can be trained end-to-end efficiently. Extensive evaluation results on PASCAL VOC 2007, VOC 2010 and VOC 2012 datasets are presented which demonstrate that the proposed method effectively improves WSD.
Results for the dynamic structure factor of a one-component plasma are presented for the situations of strong coupling and weak degeneracy and strong degeneracy and weak coupling. Possibilities to obtain rigorous results when both, coupling and degeneracy are large are discussed.
In this paper, we present a simple model of a three-dimensional insulating magnetic structure which represents a magnonic analog of the layered electronic system described in [Phys. Rev. Lett. {\bf 107}, 127205 (2011)]. In particular, our model realizes Weyl magnons as well as surface states with a Dirac spectrum. In this model, the Dzyaloshinskii-Moriya interaction is responsible for the separation of opposite Weyl points in momentum space. We calculate the intrinsic (due to the Berry curvature) transport properties of Weyl and so-called anomalous Hall effect (AHE) magnons. The results are compared with fermionic analogs.
We present a new data-driven video inpainting method for recovering missing regions of video frames. A novel deep learning architecture is proposed which contains two sub-networks: a temporal structure inference network and a spatial detail recovering network. The temporal structure inference network is built upon a 3D fully convolutional architecture: it only learns to complete a low-resolution video volume given the expensive computational cost of 3D convolution. The low resolution result provides temporal guidance to the spatial detail recovering network, which performs image-based inpainting with a 2D fully convolutional network to produce recovered video frames in their original resolution. Such two-step network design ensures both the spatial quality of each frame and the temporal coherence across frames. Our method jointly trains both sub-networks in an end-to-end manner. We provide qualitative and quantitative evaluation on three datasets, demonstrating that our method outperforms previous learning-based video inpainting methods.
This paper proposes a new approach to automatically quantify the severity of knee osteoarthritis (OA) from radiographs using deep convolutional neural networks (CNN). Clinically, knee OA severity is assessed using Kellgren \& Lawrence (KL) grades, a five point scale. Previous work on automatically predicting KL grades from radiograph images were based on training shallow classifiers using a variety of hand engineered features. We demonstrate that classification accuracy can be significantly improved using deep convolutional neural network models pre-trained on ImageNet and fine-tuned on knee OA images. Furthermore, we argue that it is more appropriate to assess the accuracy of automatic knee OA severity predictions using a continuous distance-based evaluation metric like mean squared error than it is to use classification accuracy. This leads to the formulation of the prediction of KL grades as a regression problem and further improves accuracy. Results on a dataset of X-ray images and KL grades from the Osteoarthritis Initiative (OAI) show a sizable improvement over the current state-of-the-art.
Deep learning based methods have significantly boosted the study of automatic building extraction from remote sensing images. However, delineating vectorized and regular building contours like a human does remains very challenging, due to the difficulty of the methodology, the diversity of building structures, and the imperfect imaging conditions. In this paper, we propose the first end-to-end learnable building contour extraction framework, named BuildMapper, which can directly and efficiently delineate building polygons just as a human does. BuildMapper consists of two main components: 1) a contour initialization module that generates initial building contours; and 2) a contour evolution module that performs both contour vertex deformation and reduction, which removes the need for complex empirical post-processing used in existing methods. In both components, we provide new ideas, including a learnable contour initialization method to replace the empirical methods, dynamic predicted and ground truth vertex pairing for the static vertex correspondence problem, and a lightweight encoder for vertex information extraction and aggregation, which benefit a general contour-based method; and a well-designed vertex classification head for building corner vertices detection, which casts light on direct structured building contour extraction. We also built a suitable large-scale building dataset, the WHU-Mix (vector) building dataset, to benefit the study of contour-based building extraction methods. The extensive experiments conducted on the WHU-Mix (vector) dataset, the WHU dataset, and the CrowdAI dataset verified that BuildMapper can achieve a state-of-the-art performance, with a higher mask average precision (AP) and boundary AP than both segmentation-based and contour-based methods.
MnO thin films with various thicknesses and strains were grown on MgO substrates by pulsed laser deposition, then characterized using x-ray diffraction and infrared reflectance spectroscopy. Films grown on (001)-oriented MgO substrates exhibit homogenous biaxial compressive strain which increases as the film thickness is reduced. For that reason, the frequency of doubly-degenerate phonon increases with the strain, and splits below N\'eel temperature TN due to the magnetic-exchange interaction. Films grown on (110)-oriented MgO substrates exhibit a huge phonon splitting already at room temperature due to the anisotropic in-plane compressive strain. Below TN, additional phonon is activated in the IR spectra; this trend is evidence for a spin-order-induced structural phase transition from tetragonal to monoclinic phase. Total phonon splitting is 55 cm-1 in (110)-oriented MnO film, which is more than twice the value in bulk MnO. This result is evidence that the nearest neighbor exchange interaction, which is responsible for the magnetically driven phonon splitting, is greatly increased in compressively strained films.
The dynamical equivalence between modified and scalar-tensor gravity theories is revisited and it is concluded that it breaks down in the limit to general relativity. A gauge-independent analysis of cosmological perturbations in both classes of theories lends independent support to this conclusion. As a consequence, the PPN formalism of scalar-tensor gravity and Solar System experiments do not veto modified gravity, as previously thought.
We analyze the reliability of oxygen abundances and ionization parameters obtained from different diagnostic diagrams. For this, we compiled from the literature observational emission line intensities and oxygen abundance of 446 star-forming regions whose O/H abundance was determined by direct estimation of electron temperature. The abundances compiled were compared with the values calculated in this work using different diagnostic diagrams in combination with results from a grid of photoionization models. We found that the [\ion{O}{iii}]/[\ion{O}{ii}] vs. [\ion{N}{ii}]/[\ion{O}{ii}], [\ion{O}{iii}]/H$\beta$ vs. [\ion{N}{ii}]/[\ion{O}{ii}], and ([\ion{O}{iii}]/H$\beta$)/([\ion{N}{ii}]/H$\alpha$) vs. [\ion{S}{ii}]/[\ion{S}{iii}] diagnostic diagrams give O/H values close to the $T_{\rm e}$-method, with differences of about 0.04 dex and dispersion of about 0.3 dex. Similar results were obtained by detailed models but with a dispersion of 0.08 dex. The origin of the dispersion found in the use of diagnostic diagrams is probably due to differences between the real N/O-O/H relation of the sample and the one assumed in the models. This is confirmed by the use of detailed models that do not have a fixed N/O-O/H relation. We found no correlation between ionization parameter and the metallicity for the objects of our sample. We conclude that the combination of two line ratio predicted by photoionization models, one sensitive to the metallicity and another sensitive to the ionization parameter, which takes into account the physical conditions of star-forming regions, gives O/H estimates close to the values derived using direct detections of electron temperatures.
We study absorbing phase transitions in systems of branching annihilating random walkers and pair contact process with diffusion on a one dimensional ring, where the walkers hop to their nearest neighbor with a bias $\epsilon$. For $\epsilon=0$, three universality classes: directed percolation (DP), parity conserving (PC) and pair contact process with diffusion (PCPD) are typically observed in such systems. We find that the introduction of $\epsilon$ does not change the DP universality class but alters the other two universality classes. For non-zero $\epsilon$, the PCPD class crosses over to DP and the PC class changes to a new universality class.
To realize first-order electroweak phase transition, it is necessary to generate a barrier in the thermal Higgs potential, which is usually triggered by scalar degree of freedom. We instead investigate phase transition patterns in pure fermion extensions of the standard model, and find that additional fermions with mass hierarchy and mixing could develop such barrier and realize strongly first-order phase transition in such models. In the Higgs potential with polynomial parametrization, the barrier can be generated in the following two patterns: (I) positive quadratic term, negative cubic term and positive quartic term or (II) positive quadratic term, negative quartic term and positive higher dimensional term, such as dimensional 6 operator.
We obtain some results that answer certain questions of Lorenzini on wild quotient singularities in dimension two. Using Kato's theory of log structures and log regularity, we prove that the dual graph of exceptional curves on the resolution of singularities contains at least one node. Furthermore, we show that diagonal quotients for Hermitian curves by analogues of Heisenberg groups lead to examples of wild quotient singularities where the dual graph contains at least two nodes.
The mass and anisotropy of an elliptical galaxy can be simultaneously determined from velocity dispersion and line profile shape measurements. We describe the principles, techniques, and limitations of this approach, and the results obtained sofar. We briefly discuss how best to combine these stellar-dynamical results with X-ray measurements and gravitational lensing analyses.
We show that the steady-state distribution of the join-the-shortest-queue (JSQ) system converges, in the Halfin-Whitt regime, to its diffusion limit at a rate of at least $1/\sqrt{n}$, where $n$ is the number of servers. Our proof uses Stein's method and, specifically, the recently proposed prelimit generator comparison approach. The JSQ system is non-trivial, high-dimensional, and has a state-space collapse component, and our analysis may serve as a helpful example to readers wishing to apply the approach to their own setting.
Lithium abundances are presented for a sample of 181 nearby F and G dwarfs with accurate {\it Hipparcos} parallaxes. The stars are on circular orbits about the Galactic centre and, hence, are identified as belonging to the thin disk.   This sample is combined with two published surveys to provide a catalogue of lithium abundances, metallicities ([Fe/H]), masses, and ages for 451 F-G dwarfs, almost all belonging to the thin disk. The lithium abundances are compared and contrasted with published lithium abundances for F and G stars in local open clusters. The field stars span a larger range in [Fe/H] than the clusters for which [Fe/H] $\simeq 0.0\pm0.2$. The initial (i.e., interstellar) lithium abundance of the solar neighborhood, as derived from stars for which astration of lithium is believed to be unimportant, is traced from $\log\epsilon$(Li) = 2.2 at [Fe/H] = -1 to $\log\epsilon$(Li) = 3.2 at $+0.1$. This form for the evolution is dependent on the assumption that astration of lit hium is negligible for the stars defining the relation. An argument is advanced that this latter assumption may not be entirely correct, and, the evolution of lithium with [Fe/H] may be flatter than previously supposed. A sharp Hyades-like Li-dip is not seen among the field stars and appears to be replaced by a large spread among lithium abundances of stars more massive than the lower mass limit of the dip. Astration of lithium by stars of masses too low to participate in the Li-dip is discussed. These stars show little to no spread in lithium abundance at a given [Fe/H] and mass.
For a class of large closed Jackson networks submitted to capacity constraints, asymptotic independence of the nodes in normal traffic phase is proved at stationarity under mild assumptions, using a Local Limit Theorem. The limiting distributions of the queues are explicit. In the Statistical Mechanics terminology, the equivalence of ensembles - canonical and grand canonical - is proved for specific marginals. The framework includes the case of networks with two types of nodes: single server/finite capacity nodes and infinite servers/infinite capacity nodes, that can be taken as basic models for bike-sharing systems. The effect of local saturation is modeled by generalized blocking and rerouting procedures, under which the stationary state is proved to have product-form. The grand canonical approximation can then be used for adjusting the total number of bikes and the capacities of the stations to the expected demand.
A mass formula (BWM) without shell effect is employed to study the variation of the shell effect in Pb isotopes through comparison with the experimental data. Unlike other macroscopic formulae, the BWM reproduces the general trend of the binding energy versus neutron number curves of all the nuclei from Li to Bi. The shell effect in Pb-isotopes reduces to ~56 keV at N=106 but, increases gradually for N<106, indicating increasing shell effect in Pb near the proton drip line.
We study the competition of hole capture between an In(Ga)As quantum dot and a directly adjacent ionized impurity in view of spin-photon interfaces. The Kerr rotation noise spectroscopy at 4.2 K shows that the hole-capture probability of the In(Ga)As quantum dot is about one order of magnitude higher compared to the hole-capture probability of the ionized impurity and suggests that a simultaneous occupation of quantum dot and impurity by a hole is efficiently suppressed due to Coulomb interaction. A theoretical model of interconnected spin and charge noise allows the quantitative specification of all relevant time scales.
We show that there exist six parallel textures of the charged lepton and neutrino mass matrices with six vanishing entries, whose phenomenological consequences are exactly the same. These {\it isomeric} lepton mass matrices are compatible with current experimental data at the $3\sigma$ level. If the seesaw mechanism and the Fukugita-Tanimoto-Yanagida hypothesis are taken into account, it will be possible to fit the experimental data at or below the $2\sigma$ level. In particular, the maximal atmospheric neutrino mixing can be reconciled with a strong neutrino mass hierarchy in the seesaw case.
The development of electronic devices, especially those that involve heterogeneous integration of materials, has led to increased challenges in addressing their thermal operational-temperature demands. The heat flow in these systems is significantly influenced or even dominated by thermal boundary resistance at interface between dissimilar materials. However, controlling and tuning heat transport across an interface and in the adjacent materials has so far drawn limited attention. In this work, we grow chemical-vapor-deposited (CVD) diamond on silicon substrates by graphoepitaxy and experimentally demonstrate tunable thermal transport across diamond membranes and diamond-silicon interfaces. We observed the highest diamond-silicon thermal boundary conductance (TBC) measured to date and increased diamond thermal conductivity due to strong grain texturing in the diamond near the interface. Additionally, non-equilibrium molecular-dynamics (NEMD) simulations and a Landauer approach are used to understand the diamond-silicon TBC. These findings pave the way for tuning or increasing thermal conductance in heterogeneously integrated electronics that involve polycrystalline materials and will impact applications including electronics thermal management and diamond growth.
In this paper, we present statistics of soft gamma repeater (SGR) bursts from SGR J1550-5418, SGR 1806-20 and SGR 1900+14 by adding new bursts from K{\i}rm{\i}z{\i}bayrak et al. (2017) detected with the Rossi X-ray Timing Explorer (RXTE). We find that the fluence distributions of magnetar bursts are well described by power-law functions with indices 1.84, 1.68, and 1.65 for SGR J1550-5418, SGR 1806-20 and SGR 1900+14, respectively. The duration distributions of magnetar bursts also show power-law forms. Meanwhile, the waiting time distribution can be described by a non-stationary Poisson process with an exponentially growing occurrence rate. These distributive features indicate that magnetar bursts can be regarded as a self-organizing critical process. We also compare these distributions with the repeating FRB 121102. The statistical properties of repeating FRB 121102 are similar with magentar bursts, combing with the large required magnetic filed ($B\geq 10^{14}$G) of neutron star for FRB 121102, which indicates that the central engine of FRB 121102 may be a magnetar.
N-methylformamide, CH3NHCHO, may be an important molecule for interstellar pre-biotic chemistry because it contains a peptide bond. The rotational spectrum of the most stable trans conformer of CH3NHCHO is complicated by strong torsion-rotation interaction due to the low barrier of the methyl torsion. We use two absorption spectrometers in Kharkiv and Lille to measure the rotational spectra over 45--630 GHz. The analysis is carried out using the Rho-axis method and the RAM36 code. We search for N-methylformamide toward the hot molecular core Sgr B2(N2) using a spectral line survey carried out with ALMA. The astronomical results are put into a broader astrochemical context with the help of a gas-grain chemical kinetics model. The laboratory data set for the trans conformer of CH3NHCHO consists of 9469 line frequencies with J <= 62, including the first assignment of the rotational spectra of the first and second excited torsional states. All these lines are fitted within experimental accuracy. We report the tentative detection of CH3NHCHO towards Sgr B2(N2). We find CH3NHCHO to be more than one order of magnitude less abundant than NH2CHO, a factor of two less abundant than CH3NCO, but only slightly less abundant than CH3CONH2. The chemical models indicate that the efficient formation of HNCO via NH + CO on grains is a necessary step in the achievement of the observed gas-phase abundance of CH3NCO. Production of CH3NHCHO may plausibly occur on grains either through the direct addition of functional-group radicals or through the hydrogenation of CH3NCO. Provided the detection of CH3NHCHO is confirmed, the only slight underabundance of this molecule compared to its more stable structural isomer acetamide and the sensitivity of the model abundances to the chemical kinetics parameters suggest that the formation of these two molecules is controlled by kinetics rather than thermal equilibrium.
We examine how the abilities of an SDC-like detector to discover and identify the origin of a new neutral gauge boson are affected by $Z_1-Z_2 $ mixing and by variations in detector parameters such as lepton pair mass resolution, particle identification efficiency, and rapidity coverage. Also examined is the sensitivity of these results to variations in structure function uncertainties and uncertainties in the machine integrated luminosity. Such considerations are of importance when dealing with the issues of detector descoping and design.
The recent discovery of high thermoelectric performance in Mg$_3$Sb$_2$ has been critically enabled by the success in $n$-type doping of this material, which is achieved under Mg-rich growth conditions, typically with chalcogens (Se, Te) as extrinsic dopants. Using first-principles defect calculations, we previously predicted that higher electron concentrations ($\sim10^{20}$ cm$^{-3}$) can be achieved in Mg$_3$Sb$_2$ by doping with La instead of Se or Te. Subsequent experiments showed that free electron concentration in La-doped Mg$_3$Sb$_{2-x}$Bi$_x$ indeed exceeds those in the Te-doped material. Herein, we further investigate $n$-type doping of Mg$_3$Sb$_2$ and predict that, in addition to La, other group-3 elements (Sc, Y) are also effective as $n$-type dopants; Y is as good as La while Sc slightly less. Overall, we find that doping with any group-3 elements should lead to higher free electron concentrations than doping with chalcogens.