Class Of Sources Research Articles

A game theory enhanced domain adaptation network for mechanical fault diagnosis

Transfer learning technology has been successfully applied to address the domain adaptation (DA) problem in machinery fault diagnosis. However, the partial DA problem is more suitable for industrial applications, where the target data only covers a subset of the source classes, which makes it difficult to know where to transfer the target data. To overcome this problem, a novel game theory enhanced DA network (GT-DAN) is proposed in this paper. Based on different metrics, including the maximum mean discrepancy, Jensen–Shannon divergence and Wasserstein distance, three attention matrices are constructed to describe the distribution discrepancies between the source domain and the target domain. The optimal coordination between these attention matrices is achieved by a combined weighting based on game theory to generate the optimal probability weights, which can act as a guide to filter out the irrelevant source examples in DA. Two experiments show that the proposed GT-DAN is superior to existing methods in partial DA diagnosis performance.

An updated comprehensive IVOC emission inventory for mobile sources in China

Intermediate volatility organic compounds (IVOCs) from mobile sources contribute significantly to secondary organic aerosol (SOA) formation. However, the assessments of IVOC emissions remain considerably uncertain due to the lack of localized measured data and detailed emission source classifications. This study established a comprehensive database of IVOC emission factors (EFs) for mobile sources based on the diversified measured EFs and correlations with hydrocarbons. The provincial-level IVOC emission inventories over China were further established by integrating activity data of various mobile sources. The national mobile source IVOC emissions were 507.5 Gg in 2017. The IVOC emissions of on-road and non-road mobile sources were roughly the same. Trucks and non-road construction machineries were the major contributors to IVOC emissions, accounting for >66 % of the total. The IVOC emission characteristics and spatial distributions from various mobile sources varied significantly with different types and usages. The IVOC emission inventories with detailed classifications can be used to evaluate emission control policies for mobile sources. Incorporating localized measured data would be beneficial for a better understanding for the atmospheric impacts of mobile source IVOC emissions.

Search for Gamma-ray Emission from Accretion Flares of Tidal Disruption Events Possibly Associated with the IceCube Neutrinos

Outflows or disk-coronas generated in tidal disruption events (TDEs) of supermassive black holes have been suggested as possible sites of high-energy neutrinos. Three TDEs (AT2019dsg, AT2019fdr and AT2019aalc) have been claimed to be associated with high-energy astrophysical neutrinos in multi-messenger follow-ups. No GeV photons have been detected accompanying the neutrino for the three sources. In this work, we searched for the high-energy gamma-ray emission from a larger sample of TDE candidates observed by the Zwicky Transient Facility (ZTF). No significant GeV emission was observed, and the upper limits of the gamma-ray emission flux are reported. We then performed a stacking analysis for the sample sources and found that the collective gamma-ray emission of this class of sources was also not bright enough to be detected by the Fermi Large Area Telescope (Fermi-LAT). The nondetection of the high-energy gamma-ray emission from the sample TDEs could be due to the fact that the high-energy gamma rays are absorbed by soft photons in the source. Using a model-based hypothesis, the upper limit on the emission radius of the neutrino production is obtained for these TDEs: R<1016 cm for typical TDE parameter values.

Catalog of X-Ray Detected Be Stars (XDBS)

We present a catalog of X-ray Detected Be Stars (XDBS) with 161 Be stars from the Be Star Spectra (BeSS) database having X-ray counterparts in the Chandra Source Catalog v2.0, XMM-Newton 4XMM-DR11 Catalog, or Swift 2SXPS Catalog. The multi-wavelength catalog includes accurate optical positions, X-ray properties (fluxes, photon indices and hardness ratios), optical, near-infrared and infrared photometry, source classifications (when available), and other properties including proper motions, effective temperatures, X-ray to optical flux ratios as well. We also provide a convenient https://home.gwu.edu/~kargaltsev/XDBS/graphical user interface which allows for easy visualization of the catalog content.

The physics of pulsar halos: Research progress and prospect

Diffusive TeV gamma-ray emissions have been recently discovered extending beyond the pulsar wind nebulae of a few middle-aged pulsars, implying that energetic electron/ positron pairs are escaping from the pulsar wind nebulae and radiating in the ambient interstellar medium. It has been suggested that these extended emissions constitute a distinct class of nonthermal sources, termed “pulsar halos”. In this paper, I will review the research progress on pulsar halos and discuss our current understanding on their physics, including the multiwavelength observations, different theoretical models, as well as implications for the origin of cosmic-ray positron excess and Galactic diffuse gamma-ray emission.

The sources of apparently non-repeating FRB

ABSTRACT Repeating and apparently non-repeating fast radio bursts (FRBs) differ qualitatively and are produced by distinct classes of sources. Apparently non-repeating FRBs must actually repeat many times in their lifetimes because there are insufficient catastrophic events to explain their rate. Yet no such infrequent repetitions, in contrast to the frequent activity of FRBs known to repeat, have been observed, constraining their repetition rates. The large gap in energy between FRB 200428 and its much weaker repetitions resembles the large gap in energy between rare giant outbursts of soft gamma repeaters (SGRs) and their lesser outbursts. This phenomenological similarity suggests that the sources of apparently non-repeating FRBs are related to SGRs. Apparently non-repeating FRBs are associated with SGR outbursts more energetic than the 2020 April 28 outburst of SGR 1935+2154 associated with FRB 200428 but less energetic than the 2004 outburst of SGR 1806−20 that had no associated FRB. At 20–1000 times its actual distance, FRB 200428 would have been an apparent non-repeater.

Stable Numerical Identification of Sources in Non-Homogeneous Media

In this work, we present a numerical algorithm to solve the inverse problem of volumetric sources from measurements on the boundary of a non-homogeneous conductive medium, which is made of conductive layers with constant conductivity in each layer. This inverse problem is ill-posed since there is more than one source that can generate the same measurement. Furthermore, the ill-posedness is due to the fact that small variations (or errors) in the measurement (input data) can produce substantial variations in the identified source location. We propose two steps to solve this inverse problem in some classes of sources: we first recover the harmonic part of the volumetric source, and, in a second step, we compute the non-harmonic part of the source. For the reconstruction of the harmonic part of the source, we follow a variational approach based on the reformulation of the inverse problem as a distributed control problem, for which the cost function incorporates a penalized term with the input data on the boundary. This cost function is minimized by a conjugate gradient algorithm in combination with a finite element discretization. We recover the non-harmonic component of the source using a priori information and an iterative algorithm for some particular classes of sources. To validate the numerical methodology, we develop synthetic examples both in circular (simple) and irregular (complex) regions. The numerical results show that the proposed methodology allows to recover the complete source and produce stable and accurate numerical solutions.

Improved treatment of home-made glow discharge ion source

For a better treatment, a new class of DC ion source (DCIS) was developed and adapted to provide low-power, highly-density plasma and ion-current applications. Such an ion source operates under the mode of abnormal glow discharge being of the self-extraction category, with specific features such as simple operation, stable discharge, and the ability to use for a variety of plasma, ion, and electron beam applications. A teflon disc with different diameters has been installed in between the two electrodes. This disc covered the cathode area, reducing the discharge area on the cathode surface for discharge confinement, and thus allowing for a higher output ion beam current. Pressures of 10−4 mbar, a 3 mm gap between the electrodes, and a 5 mm teflon diameter were observed to be the optimal operating conditions. At this ideal distance, hydrogen, nitrogen, and argon gases were used to investigate internal and external operational parameters. Finally, the Paschen curves were determined for hydrogen, air, as well as nitrogen gases.

Zero-shot unsupervised image-to-image translation via exploiting semantic attributes

Recent studies have shown remarkable success in unsupervised image-to-image translation. However, if there is no access to enough images in target classes, learning a mapping from source classes to the target classes always suffers from mode collapse, especially the zero shot case, which limits the application of the existing methods. In this work, we propose a zero-shot unsupervised image-to-image translation framework to address this limitation, by effectively associating categories with their side information like attributes. To generalize the translator to previously unseen classes, we introduce two strategies for exploiting the semantic attribute space. First, we propose to preserve semantic relations to the visual space for effective guidance on where to map the input image. Second, expanding attribute space is introduced by utilizing attribute vectors of unseen classes, which alleviates the mapping bias for unseen classes. Both of these strategies encourage the translator to explore the modes of unseen classes. Quantitative and qualitative results on different datasets validate the effectiveness of our proposed approach. Moreover, we demonstrate that our framework can be applied to fashion design task. The code is available at https://github.com/cyq373/ZUNIT . • A framework for zero-shot unsupervised image-to-image translation • Preserving semantic relations to the visual space • Expanding attribute space using attribute vectors of unseen classes • Capable of fashion design task

Gaia Data Release 3: Summary of the content and survey properties

We present the third data release of the European Space Agency's Gaia mission, GDR3. The GDR3 catalogue is the outcome of the processing of raw data collected with the Gaia instruments during the first 34 months of the mission by the Gaia Data Processing and Analysis Consortium. The GDR3 catalogue contains the same source list, celestial positions, proper motions, parallaxes, and broad band photometry in the G, G$_{BP}$, and G$_{RP}$ pass-bands already present in the Early Third Data Release. GDR3 introduces an impressive wealth of new data products. More than 33 million objects in the ranges $G_{rvs} < 14$ and $3100 <T_{eff} <14500 $, have new determinations of their mean radial velocities based on data collected by Gaia. We provide G$_{rvs}$ magnitudes for most sources with radial velocities, and a line broadening parameter is listed for a subset of these. Mean Gaia spectra are made available to the community. The GDR3 catalogue includes about 1 million mean spectra from the radial velocity spectrometer, and about 220 million low-resolution blue and red prism photometer BPRP mean spectra. The results of the analysis of epoch photometry are provided for some 10 million sources across 24 variability types. GDR3 includes astrophysical parameters and source class probabilities for about 470 million and 1500 million sources, respectively, including stars, galaxies, and quasars. Orbital elements and trend parameters are provided for some $800\,000$ astrometric, spectroscopic and eclipsing binaries. More than $150\,000$ Solar System objects, including new discoveries, with preliminary orbital solutions and individual epoch observations are part of this release. Reflectance spectra derived from the epoch BPRP spectral data are published for about 60\,000 asteroids. Finally, an additional data set is provided, namely the Gaia Andromeda Photometric Survey (abridged)

Real-Time Classification of Anthropogenic Seismic Sources from Distributed Acoustic Sensing Data: Application for Pipeline Monitoring

Abstract Distributed Acoustic Sensing (DAS) is an innovative method to record acoustic waves using an optical fiber as a network of sensors. Current DAS devices can monitor up to 50 km of optical fiber and the use of optical repeaters can raise even more this length, while allowing a spatial discretization of the order of a meter. Handling such amount of data is a challenge in terms of data management and data analysis (such as event source identification), more specifically for monitoring applications such as infrastructures or natural hazards. In this work, we propose a processing chain for real-time classification of anthropogenic sources using a combination of Random Forest (RF) and Random Markov Field (RMF). To develop the method, we choose to focus on the application of pipeline monitoring. The algorithm is therefore trained to recognize six classes of seismic sources: pedestrian, impact, backhoe, compactor, leak, and noise. All the sources were triggered and recorded on our own test bench under controlled conditions. The average sensitivity of our processing chain reaches 83% with the use of only RF and achieves 87% in combination with RMF. Classification maps show that the RMF approach can increase the average sensitivity by removing isolated signals. In addition to this improvement in sensitivity, this new approach also permits to identify synchronous events taking place at nearby positions, which is difficult with classical methods.

For how long are particles accelerated in shells of recurrent novae?

ABSTRACT Galactic novae are at present a well established class of γ-ray sources. We wonder for how long the mechanism of acceleration of electrons operates in the shells of novae. In order to put constraints on the time-scale of the electron acceleration, we consider a specific model for the injection and propagation of electrons within the shell of the recurrent nova RS Ophiuchi. We calculate the equilibrium spectra of electrons within the nova shell and the γ-ray fluxes produced by these electrons in the Comptonization of the soft radiation from the red giant within a nova binary system and also radiation from the nova photosphere. We investigate a two-component time-dependent model in which a spherically ejected nova shell propagates freely in the polar region of a nova binary system. However, the shell is significantly decelerated in the dense equatorial region of the binary system. We discuss the conditions under which electrons can produce γ-rays that might be detectable by present and/or future γ-ray observatories. It is concluded that freely expanding shells of novae in the optimal case (strongly magnetized shell and efficiency of acceleration of electrons of the order of 10 per cent) can produce TeV γ-rays within the sensitivity of the Cherenkov Telescope Array within 1–2 yr of explosion only. On the other hand, decelerated shells of novae have a chance to be detected during the whole recurrence period of RS Ophiuchi, i.e. ∼15 yr.

A probabilistic method of background removal for high energy astrophysics data

ABSTRACT We present a new statistical method for constructing background subtracted measurements from event list data gathered by X-ray and gamma-ray observatories. This method was initially developed specifically to construct images that account for the high background fraction and low overall count rates observed in survey data from the Mikhail Pavlinsky ART-XC telescope aboard the Spektrum Röntgen Gamma (SRG) mission, although the mathematical underpinnings are valid for data taken with other imaging missions and analysis applications. This method fully accounts for the expected Poisson fluctuations in both the sky photon and non-X-ray background count rates in a manner that does not result in unphysical negative counts. We derive the formulae for arbitrary confidence intervals for the source counts and show that our new measurement converges exactly to the standard background subtraction calculation in the high signal limit. Utilizing these results, we discuss several variants of images designed to optimize different science goals for both pointed and slewing telescopes. Using realistic simulated data of a galaxy cluster as observed by ART-XC, we show that our method provides a more significant and robust detection of the cluster emission as compared to a standard background subtraction. We also demonstrate its advantages using real observations of a point source from the ART-XC telescope. These calculations may have widespread applications for a number of source classes observed with high energy telescopes.

Complexities of information sources

ABSTRACT Calculating the entropy for complex systems is a significant problem in science and engineering problems. However, this calculation is usually computationally expensive when the entropy is computed directly. This paper introduces three classes of information sources that for all members of each class, the entropy value is the same. These classes are characterized according to special dynamics created by three kinds of self-mappings on Ω, and A, where Ω is a probability space and A is a finite set. An approximation of rank variables of the product of information sources is made, and it is proved that the topological entropy of the product of two information sources is equal to the summation of their topological entropies.

Fast beta-emitter Monte Carlo simulations and full patient dose calculations of targeted radionuclide therapy: introducing egs_mird.

Targeted radionuclide therapy (TRT) is a fast-growing field garnering much interest, with several clinical trials currently underway, that has a steady increase in development of treatment techniques. Unfortunately, within the field and many clinical trials, the dosimetry calculation techniques used remain relatively simple, often using a mix of S-value calculations and kernelconvolutions. The common TRT calculation techniques, although very quick, can often ignore important aspects of patient anatomy and radionuclide distribution, as well as the interplay there-in. This paper introduces egs_mird, a new Monte Carlo (MC) application built in EGSnrc which allows users to model full patient tissue and density (using clinical CT images) and radionuclide distribution (using clinical PET images) for fast and detailed dose TRT calculation. The novel application egs_mird is introduced along with a general outline of the structure of egs_mird simulations. The general structure of the code, and the track-length (TL) estimator scoring implementation for variance reduction, is described. A new egs++ source class egs_internal_source, created to allow detailed patient-wide source distribution, and a modified version of egs_radionuclide_source, changed to be able to work with egs_internal_source, are also described. The new code is compared to other MC calculations of S-values kernels of 131 I, 90 Y, and 177 Lu in the literature, along with further self-validation using a histogram variant of the electron Fano test. Several full patient prostate 177 Lu TRT prostate cancer treatment simulations are performed using a single set of patient DICOM CT and [18 F]-DCFPyL PETdata. Good agreement is found between S-value kernels calculated using egs_mird with egs_internal_source and those found in the literature. Calculating 1000 doses (individual voxel uncertainties of ∼0.05%) in a voxel grid Fano test for monoenergetic 500keV electrons and 177 Lu electrons results in 94% and 99% of the doses being within 0.1% of the expected dose, respectively. For a hypothetical 177 Lu treatment, patient prostate, rectum, bone marrow, and bladder dose volume histograms (DVHs) results did not vary significantly when using the TL estimator and not modeling electron transport, modeling bone marrow explicitly (rather than using generic tissue compositions), and reducing activity to voxels containing partial or full calcifications to half or none, respectively. Dose profiles through different regions demonstrate there are some differences with model choices not seen in the DVH. Simulations using the TL estimator can be completed in under 15 min (∼30 min when using standard interaction scoring). This work shows egs_mird to be a reliable MC code for computing TRT doses as realistically as the patient Computed Tomography (CT) and Positron Emission Tomography (PET) data allow. Furthermore, the code can compute doses to sub-1% uncertainty within 15 min, with little to no optimization. Thus, this work supports the use of egs_mird for dose calculations inTRT.

Prevalence of Laribacter hongkongensis in food and environmental matrices: A systematic review and meta-analysis

Laribacter hongkongensis is a human pathogen harboured in food and environmental matrices. This present study aimed to meta-analysed the prevalence of L. hongkongensis in humans, aquatic products, food/non-food animals, and environmental waters to provide update information on the pathogen. Nine electronic databases were systematically searched for articles on L. hongkongensis and a random-effects-model meta-analysis on its prevalence was conducted. Assessment of heterogeneities and publication biases across the studies was determined by using the I2 statistic and Egger's regression/rank correlation tests of funnel plot, respectively. Furthermore, a meta-regression model was explored to unravel factors influencing the prevalence. A total of 39 documents were identified, of which, 33 articles were included as 98 sub-studies for the meta-analysis, and 87 sub-studies for subgroup-analysis. Overall, the prevalence of L. hongkongesis in human, aquatic products, food/non-food animals, and environmental waters was 8.5% (95% CI: 5.8–11.7). The leave-one-out influence analysis yielded a pooled prevalence of L. hongkongensis ranging from 8.1% (95% CI: 5.4–11.3) – 8.8% (95% CI: 5.8–12.3). Sub-group analysis found that the prevalence of L. hongkongensis was highest in Amphibian (54.6%, 95% CI: 41.3–67.6), followed by Pisces (7.9%, 95% CI: 5.3–10.9), Avian (0.5%, 95% CI: 0–5.8), and Mammal (0.5%, 95% CI: 0–3.6). In addition, Egger's regression-test of funnel plot suggests presence of publication (z = 4.2, p < 0.0001) in mammal subgroup. Multivariate meta-regression showed that the prevalence was significantly influenced by source type, class, and identification/detection method with the source type, class, and detection method specifically accounted for 25.49%, 11.28%, and 3.84% of the heterogeneity, respectively. Conclusively, the prevalence of L. hongkongensis decrease in order of Amphibian (54.6%), Pisces (7.9%), Avian (0.5%) and Mammal (0.5%). Aquatic products and environments are essential sources of the pathogen.

Beginning a Journey Across the Universe: The Discovery of Extragalactic Neutrino Factories

Neutrinos are the most elusive particles in the universe, capable of traveling nearly unimpeded across it. Despite the vast amount of data collected, a long-standing and unsolved issue is still the association of high-energy neutrinos with the astrophysical sources that originate them. Among the candidate sources of neutrinos, there are blazars, a class of extragalactic sources powered by supermassive black holes that feed highly relativistic jets, pointed toward Earth. Previous studies appear controversial, with several efforts claiming a tentative link between high-energy neutrino events and individual blazars, and others putting into question such relation. In this work, we show that blazars are unambiguously associated with high-energy astrophysical neutrinos at an unprecedented level of confidence, i.e., a chance probability of 6 × 10−7. Our statistical analysis provides the observational evidence that blazars are astrophysical neutrino factories and hence, extragalactic cosmic-ray accelerators.

The Isotropic γ-ray Emission above 100 GeV: Where Do Very High-energy γ-rays Come From?

Astrophysical sources of very high energy (VHE; >100 GeV) γ-rays are rare, since GeV and TeV photons can be only emitted in extreme circumstances involving interactions of relativistic particles with local radiation and magnetic fields. In the context of the Fermi Large Area Telescope (LAT), only a few sources are known to be VHE emitters, where the largest fraction belongs to the rarest class of active galactic nuclei: the blazars. In this work, we explore Fermi-LAT data for energies >100 GeV and Galactic latitudes b > ∣50°∣ in order to probe the origin of the extragalactic isotropic γ-ray emission. Since the production of such VHE photons requires very specific astrophysical conditions, we would expect that the majority of the VHE photons from the isotropic γ-ray emission originate from blazars or other extreme objects like star-forming galaxies, γ-ray bursts, and radio galaxies, and that the detection of a single VHE photon at the adopted Galactic latitudes would be enough to unambiguously trace the presence of such a counterpart. Our results suggest that blazars are, by far, the dominant class of sources above 100 GeV, although they account for only % of the extragalactic VHE photons. The remaining of the VHE photons still have an unknown origin.

ContrastNet: A Contrastive Learning Framework for Few-Shot Text Classification

Few-shot text classification has recently been promoted by the meta-learning paradigm which aims to identify target classes with knowledge transferred from source classes with sets of small tasks named episodes. Despite their success, existing works building their meta-learner based on Prototypical Networks are unsatisfactory in learning discriminative text representations between similar classes, which may lead to contradictions during label prediction. In addition, the task-level and instance-level overfitting problems in few-shot text classification caused by a few training examples are not sufficiently tackled. In this work, we propose a contrastive learning framework named ContrastNet to tackle both discriminative representation and overfitting problems in few-shot text classification. ContrastNet learns to pull closer text representations belonging to the same class and push away text representations belonging to different classes, while simultaneously introducing unsupervised contrastive regularization at both task-level and instance-level to prevent overfitting. Experiments on 8 few-shot text classification datasets show that ContrastNet outperforms the current state-of-the-art models.

Electroluminescence from Single-Walled Carbon Nanotubes with Quantum Defects.

Individual single-walled carbon nanotubes with covalent sidewall defects have emerged as a class of photon sources whose photoluminescence spectra can be tailored by the carbon nanotube chirality and the attached functional group/molecule. Here we present electroluminescence spectroscopy data from single-tube devices based on (7, 5) carbon nanotubes, functionalized with dichlorobenzene molecules, and wired to graphene electrodes. We observe electrically generated, defect-induced emissions that are controllable by electrostatic gating and strongly red-shifted compared to emissions from pristine nanotubes. The defect-induced emissions are assigned to excitonic and trionic recombination processes by correlating electroluminescence excitation maps with electrical transport and photoluminescence data. At cryogenic conditions, additional gate-dependent emission lines appear, which are assigned to phonon-assisted hot-exciton electroluminescence from quasi-levels. Similar results were obtained with functionalized (6, 5) nanotubes. We also compare functionalized (7, 5) electroluminescence data with photoluminescence of pristine and functionalized (7, 5) nanotubes redox-doped using gold(III) chloride solution. This work shows that electroluminescence excitation is selective toward neutral defect-state configurations with the lowest transition energy, which in combination with gate-control over neutral versus charged defect-state emission leads to high spectral purity.