Search

We present a sample of 2700 Ap stars in the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) DR9 catalog. The candidates are first selected to be in a temperature range typical of Ap stars by using the BP − RP color index from Gaia DR3. Then the 5200 Å flux depression features characteristic of Ap stars are visually checked in LAMOST DR9 spectra. The detailed spectral features are given by applying a modified spectral classification program, MKCLASS. The stellar parameters of these Ap stars, such as the T eff, log g , [Fe/H], [Si/H], and v sin i , are either extracted from a hot star catalog or derived through empirical relations and then a statistical analysis is carried out. The evolutionary stages are also discussed. Finally, we discuss the rotation and pulsation features of those that have TESS or Kepler light curves. Among these Ap stars, we find seven new rotation variables, one new roAp star, and a new δ Scuti pulsation of a previously known roAp star.

Aiming at the existing malware variants detection method based on deep convolutional neural networks (DCNN) has the problem of large computational resource consumption, a decomposing deep neural network (Dec-DCNN) is proposed for optimization. The computational cost was reduced by using single value decomposition (SVD) to split the pre-trained standard convolution operation into two simpler convolution operations. And the optimized network after decomposition does no need to be retrained, which can reduce the number of parameters and calculations while maintaining the detection accuracy of the pre-trained model. Experimental results show that the Dec-DCNN had a detection time of only 46% of DCNN with an overall detection accuracy of 98.5%. At the same time, compared with the current mainstream malicious variant detection model, Dec-DCNN has a stronger ability to express texture features of malware images.

We thank the anonymous referee for a careful reading of the manuscript. DLH acknowledges financial support from the Science and Technology Facilities Council (STFC) via grant ST/M000877/1. MSC acknowledges the support by FCT/MCTES through the research grants UIDB/04434/2020, UIDP/04434/2020, and PTDC/FIS-AST/30389/2017, and by FEDER - Fundo Europeu de Desenvolvimento Regional through COMPETE2020 - Programa Operacional Competitividade e Internacionalizacao (grant: POCI01-0145-FEDER-030389). MSC is supported by national funds through FCT in the form of a work contract. VA was supported by a research grant (00028173) fromVILLUMFONDEN. Funding for the Stellar Astrophysics Centre is provided by The Danish National Research Foundation (Grant agreement no.: DNRF106). The research leading to these results has received funding from the Research Foundation Flanders (FWO) by means of a senior postdoctoral fellowship to DMB with grant agreement No. 1286521N. This project has been supported by the Lendulet Program of the Hungarian Academy of Sciences, project No. LP2018-7/2020 and by the EU's MW-Gaia COST Action (CA18104). ASG acknowledges financial support from the Max Planck Society under grant 'Preparations for PLATO science' and from ALMA-CONICYT under grant #31170029. ZsB acknowledges the support by the Janos Bolyai Research Scholarship of the Hungarian Academy of Sciences. LFM acknowledges the financial support from the UNAM under grant PAPIIT IN100918. CCL acknowledges the support of the Natural Sciences and Engineering Research Council of Canada (NSERC). DM acknowledges the support of the National Astronomical Research Institute of Thailand (NARIT). JPG acknowledges funding support from Spanish public funds for research from project PID2019-107061GB-C63 from the 'Programas Estatales de Generacion de Conocimiento y Fortalecimiento Cientifico y Tecnologico del Sistema de I+D+i y de I+D+i Orientada a los Retos de la Sociedad', and from the State Agency for Research through the Center of Excellence Severo Ochoa' award to the Instituto de Astrof ' isica de Andaluc ' ia (SEV2017-0709), all from the Spanish Ministry of Science, Innovation and Universities (MCIU). TRY acknowledges support from the NSF REU program, grant number PHY-1359195. The material is based upon work supported by NASA under award number 80GSFC21M0002. AD was supported by the UNKP-20-5 New National Excellence Program of the Ministry of Human Capacities and the J ' anos Bolyai Research Scholarship of the Hungarian Academy of Sciences. AD would like to thank the City of Szombathely for support under Agreement No. 67.177-21/2016. AGH acknowledges support from 'FEDER/Junta de Andalucia-Consejeria de Economia y Conocimiento' under project E-FQM-041-UGR18 by Universidad de Granada and from Spanish public funds (including FEDER funds) for research under project ESP2017-87676-C5-2-R. ARB acknowledges funding support from Spanish public funds for research through the research grant PRE2018-084322, through projects ESP2017-87676-C5-5-R and PID2019-107061GB-C63, and from the State Agency for Research through the `Center of Excellence Severo Ochoa' award to the Instituto de Astrof ' isica de Andaluc ' ia (SEV-2017-0709), all from the Spanish Ministry of Science, Innovation and Universities (MCIU). We are grateful to Sowgata Chowdhury, supported by Polish NCN grant 2015/18/A/ST9/00578, for conducting some spectroscopic observations that are reported in this work. This paper includes data collected by the TESS mission, which are publicly available from the Mikulski Archive for Space Telescopes (MAST). Funding for the TESS mission is provided by NASA's Science Mission directorate. Funding for the TESS Asteroseismic Science Operations Centre is provided by the Danish National Research Foundation (Grant agreement no.: DNRF106), ESA PRODEX (PEA 4000119301) and Stellar Astrophysics Centre (SAC) at Aarhus University. We thank the TESS team and staff and TASC/TASOC for their support of this work. This research has made use of the SIMBAD data base, operated at CDS, Strasbourg, France. This work has made use of data from the European Space Agency (ESA) mission Gaia (https://www.cosmos.esa.int/gaia), processed by the Gaia Data Processing and Analysis Consortium (DPAC, https://www.cosmos.esa.int/web/gaia/dpac/consortium).Funding for the DPAC has been provided by national institutions, in particular the institutions participating in the Gaia Multilateral Agreement., We present the results of a systematic search for new rapidly oscillating Ap (roAp) stars using the 2-min cadence data collected by the Transiting Exoplanet Survey Satellite (TESS) during its Cycle 1 observations. We identify 12 new roAp stars. Amongst these stars we discover the roAp star with the longest pulsation period, another with the shortest rotation period, and six with multiperiodic variability. In addition to these new roAp stars, we present an analysis of 44 known roAp stars observed by TESS during Cycle 1, providing the first high-precision and homogeneous sample of a significant fraction of the known roAp stars. The TESS observations have shown that almost 60 per cent (33) of our sample of stars are multiperiodic, providing excellent cases to test models of roAp pulsations, and from which the most rewarding asteroseismic results can be gleaned. We report four cases of the occurrence of rotationally split frequency multiplets that imply different mode geometries for the same degree modes in the same star. This provides a conundrum in applying the oblique pulsator model to the roAp stars. Finally, we report the discovery of non-linear mode interactions in α Cir (TIC 402546736, HD128898) around the harmonic of the principal mode – this is only the second case of such a phenomenon., UK Research & Innovation (UKRI), Science & Technology Facilities Council (STFC), Science and Technology Development Fund (STDF) ST/M000877/1, Portuguese Foundation for Science and Technology, European Commission UIDB/04434/2020 UIDP/04434/2020 PTDC/FIS-AST/30389/2017, FEDER - Fundo Europeu de Desenvolvimento Regional through COMPETE2020 - Programa Operacional Competitividade e Internacionalizacao POCI-01-0145-FEDER-030389, European Commission, VILLUMFONDEN 00028173, Danmarks Grundforskningsfond DNRF106 FWO 1286521N, Lendulet Program of the Hungarian Academy of Sciences LP2018-7/2020, EU's MW-Gaia COST Action CA18104, Max Planck Society, Foundation CELLEX, ALMA-CONICYT 31170029, Hungarian Academy of Sciences, UNAM under grant PAPIIT IN100918, Natural Sciences and Engineering Research Council of Canada (NSERC), National Astronomical Research Institute of Thailand (NARIT), Spanish public funds the Spanish Ministry of Science, Innovation and Universities (MCIU) PID2019-107061GB-C63 PRE2018-084322 ESP2017-87676-C5-5-R, 'Programas Estatales de Generacion de Conocimiento y Fortalecimiento Cientifico y Tecnologico del Sistema de I+D+i y de I+D+i Orientada a los Retos de la Sociedad' from the Spanish Ministry of Science, Innovation and Universities (MCIU), State Agency for Research through the 'Center of Excellence Severo Ochoa' award from the Spanish Ministry of Science, Innovation and Universities (MCIU) SEV-2017-0709, National Science Foundation (NSF), NSF - Office of the Director (OD) PHY-1359195, National Aeronautics & Space Administration (NASA) 80GSFC21M0002, New National Excellence Program of the Ministry of Human Capacities UNKP-20-5, City of Szombathely 67.177-21/2016, 'FEDER/Junta de Andalucia-Consejeria de Economia y Conocimiento' by Universidad de Granada E-FQM-041-UGR18, Spanish public funds (FEDER) ESP2017-87676-C5-2-R, Polish NCN 2015/18/A/ST9/00578, NASA's Science Mission directorate, European Space Agency PEA 4000119301, Stellar Astrophysics Centre (SAC) at Aarhus University

KIC 10685175 (TIC 264509538) was discovered to be a rapidly oscillating Ap star from Kepler long-cadence data using super-Nyquist frequency analysis. It was reobserved by the Transiting Exoplanet Survey Satellite (TESS) with 2 minute cadence data in Sectors 14 and 15. We analyzed the TESS light curves, finding that the previously determined frequency is a Nyquist alias. The revised pulsation frequency is 191.5151 ± 0.0005 day−1 (P = 7.52 minutes) and the rotation frequency is 0.32229 ± 0.00005 day−1 (P rot = 3.1028 days). The star is an oblique pulsator with a pulsation amplitude modulated by the rotation, reaching a maximum pulsation amplitude at the time of the rotational light minimum. The oblique pulsation generates a frequency quintuplet split by exactly the rotation frequency. The phases of sidelobes, the pulsation phase modulation, and a spherical harmonic decomposition all show this star to be pulsating in a distorted quadrupole mode. Following the oblique pulsator model, we calculated the rotation inclination i and magnetic oblique β of this star, which provide detailed information of pulsation geometry. The i and β derived by the best fit of pulsation amplitude and phase modulation through a theoretical model differ from those calculated for a pure quadrupole, indicating the existence of strong magnetic distortion. The model also predicts the polar magnetic field strength is as high as about 6 kG which is predicted to be observed in a high-resolution spectrum of this star.

We report the frequency analysis of a known roAp star, HD 86181 (TIC 469246567), with new inferences from TESS data. We derive the rotation frequency to be νrot = 0.48753 ± 0.00001d−1. The pulsation frequency spectrum is rich, consisting of two doublets and one quintuplet, which we interpret to be oblique pulsation multiplets from consecutive, high-overtone dipole, quadrupole and dipole modes. The central frequency of the quintuplet is 232.7701d−1 (2.694 mHz). The phases of the sidelobes, the pulsation phase modulation, and a spherical harmonic decomposition all show that the quadrupole mode is distorted. Following the oblique pulsator model, we calculate the rotation inclination, i, and magnetic obliquity, β, of this star, which provide detailed information about the pulsation geometry. The i and β derived from the best fit of the pulsation amplitude and phase modulation to a theoretical model, including the magnetic field effect, slightly differ from those calculated for a pure quadrupole, indicating the contributions from l = 4, 6, 8, ... are small. Non-adiabatic models with different envelope convection conditions and physics configurations were considered for this star. It is shown that models with envelope convection almost fully suppressed can explain the excitation at the observed pulsation frequencies.

Aiming at the problem of large computational resource consumption in the existing object detection network for driver smoking detection, a decomposing YOLOv5 network (Dec-YOLOv5) is proposed for optimization. This method uses singular value decomposition (SVD) to split the standard convolution in the pre-trained YOLOv5 network into two simpler convolution operations to reduce the computational cost. The optimized network generated after decomposition does not need to be retrained, which can reduce the number of parameters and calculations while maintaining the detection accuracy of the pre-trained model. The experimental results show that the detection time of Dec-YOLOv5 is only 80% of the original YOLOv5 when the overall detection accuracy reaches 93.5%. At the same time, compared with the current mainstream object detection model, the Dec-YOLOv5 network has a better ability to express the characteristics of the driver’s cigarettes, and the detection accuracy is higher.