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We present the eclipsing Heartbeat Star KIC 9704906 with tidally excited oscillations (TEOs) and gamma Doradus/delta Scuti hybrid pulsations. The derived parameters show that it has an orbital period of $P$=8.7529108(1) days, a high eccentricity of $e$=0.467(3), and a high inclination of $i$=78$^{\circ}$.81(6). The mass ratio $q$=0.981(5), the relative radii (radius divided by semi-major axis) $r_1$=0.0639(2), and $r_2$=0.0715(4) indicate that the secondary component has a less mass and a larger radius, and may have evolved off the main sequence. The eight derived TEO candidates, $n$ = 3, 4, 5, 6, 7, 12, 40, and 44 harmonics, are consistent with or close to the dominant spherical harmonic $l=2$, $m=0$, or $\pm2$, assuming that the spin and orbital axes are aligned, and the pulsations are adiabatic and standing waves. We also identify ten independent frequency candidates, but one of them, $\mathit{f_{7}}$, is more like a modulation of a quasi-periodic signal and the orbits. According to the g-mode frequencies, we find that the rotation period of one component is 11.52(29) days. Although the masses and radii cannot be further constrained due to the lack of sufficient high-precision spectra, the fascinating phenomena in the Fourier spectra are evident and valuable in this system., Comment: submit to AJ. 14 pages, 8 figures

Atmospheric neutrinos contribute significantly to irreducible backgrounds through their neutral-current (NC) interactions with $^{12}$C nuclei in liquid-scintillator detectors, impacting diffuse supernova neutrino background, nucleon decay, and reactor neutrinos. This paper extends our prior work by systematically studying the NC backgrounds towards the MeV region of reactor neutrinos. We employ contemporary neutrino generator models from GENIE and NuWro for calculations, with a focus on predicting NC background in experimental searches for inverse-beta-decay signals below 100 MeV visible energy. We estimate the systematic uncertainty to our estimation of the NC background using various data-driven neutrino generator models, addressing factors such as the initial neutrino-nucleon NC interaction, the nuclear model, the final-state interaction model, the nucleus deexcitation, and the secondary interaction on final-state particles., Comment: 26 pages, 10 figures

Multilingual Large Language Models are capable of using powerful Large Language Models to handle and respond to queries in multiple languages, which achieves remarkable success in multilingual natural language processing tasks. Despite these breakthroughs, there still remains a lack of a comprehensive survey to summarize existing approaches and recent developments in this field. To this end, in this paper, we present a thorough review and provide a unified perspective to summarize the recent progress as well as emerging trends in multilingual large language models (MLLMs) literature. The contributions of this paper can be summarized: (1) First survey: to our knowledge, we take the first step and present a thorough review in MLLMs research field according to multi-lingual alignment; (2) New taxonomy: we offer a new and unified perspective to summarize the current progress of MLLMs; (3) New frontiers: we highlight several emerging frontiers and discuss the corresponding challenges; (4) Abundant resources: we collect abundant open-source resources, including relevant papers, data corpora, and leaderboards. We hope our work can provide the community with quick access and spur breakthrough research in MLLMs.

This paper introduces a cooperative sensing framework designed for integrated sensing and communication cellular networks. The framework comprises one base station (BS) functioning as the sensing transmitter, while several nearby BSs act as sensing receivers. The primary objective is to facilitate cooperative target localization by enabling each receiver to share specific information with a fusion center (FC) over a limited capacity backhaul link. To achieve this goal, we propose an advanced cooperative sensing design that enhances the communication process between the receivers and the FC. Each receiver independently estimates the time delay and the reflecting coefficient associated with the reflected path from the target. Subsequently, each receiver transmits the estimated values and the received signal samples centered around the estimated time delay to the FC. To efficiently quantize the signal samples, a Karhunen-Lo\`eve Transform coding scheme is employed. Furthermore, an optimization problem is formulated to allocate backhaul resources for quantizing different samples, improving target localization. Numerical results validate the effectiveness of our proposed advanced design and demonstrate its superiority over a baseline design, where only the locally estimated values are transmitted from each receiver to the FC., Comment: This paper has been published in 2023 IEEE 98th Vehicular Technology Conference (VTC2023-Fall)

Exploring ultrafast magnetization control in two-dimensional (2D) magnets through optically driven coherent phonons has been well-established. Yet, the microscopic interplay between spin dynamics and lattice degrees of freedom remains less explored. Employing real-time time-dependent density functional theory (rt-TDDFT) coupled with Ehrenfest dynamics, we systematically investigate laser-induced spin-nuclei dynamics with coherent phonon excitation in the 2D ferromagnet Fe3GeTe2. We found that selectively pre-exciting three typical coherent phonon modes results in up to a 53% additional spin moment loss in an out-of-plane A2 1g mode within ~50 fs. Coherent phonon control of spin dynamics is closely linked to laser pulse parameters. The underlying microscopic mechanism of this phenomenon is primarily governed by coherent phonon-induced asymmetric spin-resolved charge transfer following the disappearance of the laser pulse, thereby enabling effective control of the spin moment loss. Our findings offer a novel insight into the coupling of coherent phonons with spin systems in 2D limits on femtosecond timescales.

In this paper, we study the Cauchy problem of the Euler-Poincar\'{e} equations in $\R^d$ with initial data belonging to the Triebel-Lizorkin spaces. We prove the local-in-time unique existence of solutions to the Euler-Poincar\'{e} equations in $F^s_{p,r}(\R^d)$. Furthermore, we obtain that the data-to-solution of this equation is continuous but not uniformly continuous in these spaces., Comment: 17pages

Hybrid beamforming is vital in modern wireless systems, especially for massive MIMO and millimeter-wave deployments, offering efficient directional transmission with reduced hardware complexity. However, effective beamforming in multi-user scenarios relies heavily on accurate channel state information, the acquisition of which often incurs excessive pilot overhead, degrading system performance. To address this and inspired by the spatial congruence between sub-6GHz (sub-6G) and mmWave channels, we propose a Sub-6G information Aided Multi-User Hybrid Beamforming (SA-MUHBF) framework, avoiding excessive use of pilots. SA-MUHBF employs a convolutional neural network to predict mmWave beamspace from sub-6G channel estimate, followed by a novel multi-layer graph neural network for analog beam selection and a linear minimum mean-square error algorithm for digital beamforming. Numerical results demonstrate that SA-MUHBF efficiently predicts the mmWave beamspace representation and achieves superior spectrum efficiency over state-of-the-art benchmarks. Moreover, SA-MUHBF demonstrates robust performance across varied sub-6G system configurations and exhibits strong generalization to unseen scenarios., Comment: 13 pages, 12 figures, submitted

Within the Electronic Design Automation (EDA) domain, AI-driven solutions have emerged as formidable tools, yet they typically augment rather than redefine existing methodologies. These solutions often repurpose deep learning models from other domains, such as vision, text, and graph analytics, applying them to circuit design without tailoring to the unique complexities of electronic circuits. Such an AI4EDA approach falls short of achieving a holistic design synthesis and understanding, overlooking the intricate interplay of electrical, logical, and physical facets of circuit data. This paper argues for a paradigm shift from AI4EDA towards AI-native EDA, integrating AI at the core of the design process. Pivotal to this vision is the development of a multimodal circuit representation learning technique, poised to provide a comprehensive understanding by harmonizing and extracting insights from varied data sources, such as functional specifications, RTL designs, circuit netlists, and physical layouts. We champion the creation of large circuit models (LCMs) that are inherently multimodal, crafted to decode and express the rich semantics and structures of circuit data, thus fostering more resilient, efficient, and inventive design methodologies. Embracing this AI-native philosophy, we foresee a trajectory that transcends the current innovation plateau in EDA, igniting a profound shift-left in electronic design methodology. The envisioned advancements herald not just an evolution of existing EDA tools but a revolution, giving rise to novel instruments of design tools that promise to radically enhance design productivity and inaugurate a new epoch where the optimization of circuit performance, power, and area (PPA) is achieved not incrementally, but through leaps that redefine the benchmarks of electronic systems' capabilities., Comment: The authors are ordered alphabetically. Contact: qxu@cse[dot]cuhk[dot]edu[dot]hk, gluo@pku[dot]edu[dot]cn, yuan.mingxuan@huawei[dot]com

We perform a comprehensive investigation of the PSF smoothing effect on the measurement of concentration-related parameters ($C$, Gini, $M_{20}$) of high redshift galaxies in the HST and JWST surveys. Our sample contains massive galaxies from the CANDELS/EGS survey (0 < z < 2), and the CEERS survey (1 < z < 3). The non-parametric concentration-related parameters ($C$, Gini, $M_{20}$) and the model-dependent parameters (n, Re) of these galaxies are derived from Statmorph and GALFIT, respectively. We try to evaluate the PSF smoothing effect by comparing the concentration-related parameters to the S\'{e}rsic index in both observations and mock images. We find that the concentration index is generally underestimated, especially for smaller galaxies with higher S\'{e}rsic index (eventually converging to the concentration index of the PSF). However, galaxies with lower S\'{e}rsic index ($n \leq 1$) or larger relative size are less affected by the PSF smoothing effect. The Gini coefficient and the absolute $M_{20}$ statistic also show similar behaviour as the concentration index. Caution should be taken for the possible correction of the concentration-related parameters, where both the relative size and the S\'{e}rsic index of the galaxy are important. Compared to the HST images, the PSF smoothing is much less severe for images in the CEERS survey due to the much higher spatial resolution. In fact, it is better to use the S\'{e}rsic index rather than the non-parametric morphology indicators to trace the light concentration for galaxies at high redshifts. From the single S\'{e}rsic modelling of the HST and JWST images, we also confirm that galaxies at higher redshift are more compact with smaller $R_e$. The lower mass galaxies are more disc-like ($n\sim1$) compared to the higher mass galaxies that are more spheroid dominated ($n\sim3$)., Comment: Accepted by A&A, 21 pages, 20 figures. Comments are welcome

The objective of the invariant ellipsoid method is to minimize the smallest invariant and attractive set of a linear control system operating under the influence of bounded external disturbances. In this paper, this method is extended into the leader-following consensus problem. Initially, a linear control protocol is designed for the Multi-agent System without disturbances. Subsequently, in the presence of bounded disturbances, by employing a similar linear control protocol, a necessary and sufficient condition is introduced to derive the optimal control parameters for the MAS such that the state of followers converge and remain in an minimal invariant ellipsoid around the state of the leader.

Assertion-based verification (ABV) is a critical method for ensuring design circuits comply with their architectural specifications, which are typically described in natural language. This process often requires significant interpretation by engineers to convert these specifications into functional verification assertions. Existing methods for generating assertions from natural language specifications are limited to sentences extracted by engineers, discouraging the practical application. In this work, we present AssertLLM, an automatic assertion generation framework for complete specification files. AssertLLM breaks down the complex task into three phases, incorporating three customized Large Language Models (LLMs) for extracting structural specifications, mapping signal definitions, and generating assertions. Additionally, we provide an open-source benchmark for assessing assertion generation capabilities. Our evaluation of AssertLLM on a full design, encompassing 23 signals, demonstrates that 89% of the generated assertions are both syntactically and functionally accurate.

In this paper, we investigate the continuity of solution to the Euler-Poincar\'{e} equations. We show that the continuity of the solution cannot be improved to the H\"{o}lder continuity. That is, the solution of the Euler-Poincar\'{e} equations with initial data $u_0\in B^s_{p,r}$ belongs to $\mathcal{C}([0,T];B^s_{p,r}(\mathbb R^d))$ but not to $\mathcal{C}^\alpha([0,T];B^s_{p,r}(\mathbb R^d))$ with any $\alpha\in(0,1)$., Comment: 10 pages

The emergence of novel the dummy data injection attack (DDIA) poses a severe threat to the secure and stable operation of power systems. These attacks are particularly perilous due to the minimal Euclidean spatial separation between the injected malicious data and legitimate data, rendering their precise detection challenging using conventional distance-based methods. Furthermore, existing research predominantly focuses on various machine learning techniques, often analyzing the temporal data sequences post-attack or relying solely on Euclidean spatial characteristics. Unfortunately, this approach tends to overlook the inherent topological correlations within the non-Euclidean spatial attributes of power grid data, consequently leading to diminished accuracy in attack localization. To address this issue, this study takes a comprehensive approach. Initially, it examines the underlying principles of these new DDIAs on power systems. Here, an intricate mathematical model of the DDIA is designed, accounting for incomplete topological knowledge and alternating current (AC) state estimation from an attacker's perspective. Subsequently, by integrating a priori knowledge of grid topology and considering the temporal correlations within measurement data and the topology-dependent attributes of the power grid, this study introduces temporal and spatial attention matrices. These matrices adaptively capture the spatio-temporal correlations within the attacks. Leveraging gated stacked causal convolution and graph wavelet sparse convolution, the study jointly extracts spatio-temporal DDIA features. Finally, the research proposes a DDIA localization method based on spatio-temporal graph neural networks. The accuracy and effectiveness of the DDIA model are rigorously demonstrated through comprehensive analytical cases., Comment: Accepted by Applied Energy

Tidally excited oscillations (TEOs) in Heartbeat Stars (HBSs) are an essential probe of the internal properties of the systems, but their potential has yet to be fully exploited. Based on the orbital parameters of TEO candidates from our previous works, we identify the pulsation phases and amplitudes of TEOs in fourteen Kepler HBSs. Most pulsation phases of most systems can be explained by the dominant being $l=2$, $m=0$, or $\pm2$ spherical harmonic, assuming that the spin and orbital axes are aligned, and the pulsations are adiabatic and standing waves. The largest deviation ($>6\sigma$) occurs in KIC 8459354, which can be explained by the spin-orbit misalignment, and KIC 5877364 has a similar scenario. For KIC 11122789, almost half of the harmonics show large deviations; we cautiously suggest that these harmonics may not be considered TEO candidates. A similar scenario also exists in KIC 6290740. This phases and mode identification approach can also be used inversely to verify the TEO candidates derived by the Fourier analysis. Furthermore, the harmonics with large deviations ($>2\sigma$) in KIC 4377638, KIC 5090937, and KIC 11403032 can be expected to be travelling waves rather than standing waves. In addition, we also suggest that the apsidal motion could cause large deviations in TEO phases from theoretical values., Comment: published on MNRAS

TV Col is a long-period eclipsing intermediate polar (IPs) prototype star for the negative superhump (NSH) system. We investigate the eclipse minima, eclipse depth, and NSH amplitude based on TESS photometry. Using the same analytical method as SDSS J081256.85+191157.8, we find periodic variations of the O-C for eclipse minima and NSH amplitudes with periods of 3.939(25) d and 3.907(30) d, respectively. The periodic variation of the NSH amplitude of TV Col confirms that periodic NSH amplitude changes in response to the tilted disk precession may be universal, which is another evidence that the origin of the NSHs is related to the tilted disk precession. We suggest that the NSH amplitude variation may be similar to the superorbital signal, coming from the periodic change in visual brightness of the energy released by streams touching the tilted disk with tilted disk precession. Finally, we find for the first time that the eclipse depth exhibits bi-periodic variations with periods of P1 = 3.905(11) d and P2 = 1.953(4) d, respectively. P2 is about half of P1 and the disk precession period (P1~ Pprec ~ 2 * P2). We suggest that P1 may come from the periodic change in the brightness of the eclipse center due to tilted disk precession, while P2 may come from two accretion curtains precessing together with the tilted disk, but more verification and discussion are necessary. The discovery of bi-periodic variations in eclipse depth provides a new window for studying IPs and tilted disk precession., Comment: 18 pages, 7 figures, 3 tables; Accepted for publication in The Astrophysical Journal

Accurate and robust prediction of drug-target interactions (DTIs) plays a vital role in drug discovery. Despite extensive efforts have been invested in predicting novel DTIs, existing approaches still suffer from insufficient labeled data and cold start problems. More importantly, there is currently a lack of studies focusing on elucidating the mechanism of action (MoA) between drugs and targets. Distinguishing the activation and inhibition mechanisms is critical and challenging in drug development. Here, we introduce a unified framework called DTIAM, which aims to predict interactions, binding affinities, and activation/inhibition mechanisms between drugs and targets. DTIAM learns drug and target representations from large amounts of label-free data through self-supervised pre-training, which accurately extracts the substructure and contextual information of drugs and targets, and thus benefits the downstream prediction based on these representations. DTIAM achieves substantial performance improvement over other state-of-the-art methods in all tasks, particularly in the cold start scenario. Moreover, independent validation demonstrates the strong generalization ability of DTIAM. All these results suggested that DTIAM can provide a practically useful tool for predicting novel DTIs and further distinguishing the MoA of candidate drugs. DTIAM, for the first time, provides a unified framework for accurate and robust prediction of drug-target interactions, binding affinities, and activation/inhibition mechanisms.

We consider the Cauchy problem of the Euler-Poincar\'e equations in $\mathbb{R}^d$ with a varying dispersion parameter $\alpha$. Based on the convex entropy structure and the modified commutator estimates, we have proved that the Euler-Poincar\'e equations have a uniform existence time with respect to $\alpha$ in Sobolev spaces $H^s.$ Combined with the Bona-Simth method, we obtain convergence of the solutions to the Euler-Poincar\'e equations as $\alpha\to 0$ in the same space where the initial data are located.

Water Cherenov detector is a vital part in most of neutrino or cosmic ray research. As detectors grow in size, the water attenuation length (WAL) becomes increasingly essential for detector performance. It is essential to measure or monitor the WAL. While many experiments have measured WAL in the lab or detector, only the Super-Kamiokande experiment has achieved values exceeding 50 meters in the detector with a moving light source. However, it is impractical for many experiments to place a moving light source inside the detector, necessitating an alternative method for investigating long WAL. A novel system has been proposed to address the challenge of investigating long WAL. This system focuses on ample water Cherenkov detectors and features a fixed light source and photomultiplier tubes (PMTs) at varying distances, eliminating the need for moving parts. The static setup demands high precision for accurate measurement of long WAL. Each component, including LED, diffuse ball, PMTs, and fibers, is introduced to explain uncertainty control. Based on lab tests, the system's uncertainty has been controlled within 5\%. Additionally, camera technology is also used during the evaluation of the system uncertainty, which has the potential to replace PMTs in the future for this measurement. Monte Carlo simulations have shown that the system can achieve a 5\% measurement uncertainty at WAL of 80 meters and 8\% at WAL of 100 meters. This system can be used in experiments with large Cherenkov detectors such as JUNO water veto and Hyper-K.

The scalars $f_0$ closest to 1.5 GeV contain the mesons $f_0(1370)$, $f_0(1500)$ and $f_0(1710)$, and the latter two ones are usually viewed as the potential candidates for the scalar glueballs. In this work, by including the important contributions from the vertex corrections, we study the decays $B^0 \to J/\psi f_0$ within the improved perturbative QCD approach and analyze the possible scalar glueball hunting. Together with the two mixing models, namely, $f_0(1500) (f_0(1710))$ being the primary scalar glueball in model I (II), and two classification scenarios, namely, $f_0$ being the $q\bar q$ excited (ground) states in scenario 1 (2), the branching fractions associated with their ratios for $B^0 \to J/\psi f_0$ are evaluated comprehensively. The predictions with still large uncertainties in the considered two mixing models are roughly consistent with currently limited data, which indicates that both more rich data and more precise predictions are urgently demanded to figure out the scalar glueball clearly in the future. Moreover, several interesting ratios between the branching fractions of $B^0 \to J/\psi f_0(\to \pi^+ \pi^-/K^+ K^-)$ and $B^0 \to J/\psi \rho^0/\phi (\to \pi^+ \pi^-/ K^+ K^-)$ that could help us to understand the nature of scalar $f_0$ are defined and predicted theoretically. These ratios should be examined in future experiments., Comment: 28 pages, 3 figures, 6 tables; revised version according to referee's comments; contents improved and references added

Effective user representations are pivotal in personalized advertising. However, stringent constraints on training throughput, serving latency, and memory, often limit the complexity and input feature set of online ads ranking models. This challenge is magnified in extensive systems like Meta's, which encompass hundreds of models with diverse specifications, rendering the tailoring of user representation learning for each model impractical. To address these challenges, we present Scaling User Modeling (SUM), a framework widely deployed in Meta's ads ranking system, designed to facilitate efficient and scalable sharing of online user representation across hundreds of ads models. SUM leverages a few designated upstream user models to synthesize user embeddings from massive amounts of user features with advanced modeling techniques. These embeddings then serve as inputs to downstream online ads ranking models, promoting efficient representation sharing. To adapt to the dynamic nature of user features and ensure embedding freshness, we designed SUM Online Asynchronous Platform (SOAP), a latency free online serving system complemented with model freshness and embedding stabilization, which enables frequent user model updates and online inference of user embeddings upon each user request. We share our hands-on deployment experiences for the SUM framework and validate its superiority through comprehensive experiments. To date, SUM has been launched to hundreds of ads ranking models in Meta, processing hundreds of billions of user requests daily, yielding significant online metric gains and infrastructure cost savings., Comment: 8 pages, 3 figures

End-to-end task-oriented dialogue (EToD) can directly generate responses in an end-to-end fashion without modular training, which attracts escalating popularity. The advancement of deep neural networks, especially the successful use of large pre-trained models, has further led to significant progress in EToD research in recent years. In this paper, we present a thorough review and provide a unified perspective to summarize existing approaches as well as recent trends to advance the development of EToD research. The contributions of this paper can be summarized: (1) \textbf{\textit{First survey}}: to our knowledge, we take the first step to present a thorough survey of this research field; (2) \textbf{\textit{New taxonomy}}: we first introduce a unified perspective for EToD, including (i) \textit{Modularly EToD} and (ii) \textit{Fully EToD}; (3) \textbf{\textit{New Frontiers}}: we discuss some potential frontier areas as well as the corresponding challenges, hoping to spur breakthrough research in EToD field; (4) \textbf{\textit{Abundant resources}}: we build a public website\footnote{We collect the related papers, baseline projects, and leaderboards for the community at \url{https://etods.net/}.}, where EToD researchers could directly access the recent progress. We hope this work can serve as a thorough reference for the EToD research community., Comment: Accepted at EMNLP2023

In this paper, we investigate a self-sensing intelligent reflecting surface (IRS) aided millimeter wave (mmWave) integrated sensing and communication (ISAC) system. Unlike the conventional purely passive IRS, the self-sensing IRS can effectively reduce the path loss of sensing-related links, thus rendering it advantageous in ISAC systems. Aiming to jointly sense the target/scatterer/user positions as well as estimate the sensing and communication (SAC) channels in the considered system, we propose a two-phase transmission scheme, where the coarse and refined sensing/channel estimation (CE) results are respectively obtained in the first phase (using scanning-based IRS reflection coefficients) and second phase (using optimized IRS reflection coefficients). For each phase, an angle-based sensing turbo variational Bayesian inference (AS-TVBI) algorithm, which combines the VBI, messaging passing and expectation-maximization (EM) methods, is developed to solve the considered joint location sensing and CE problem. The proposed algorithm effectively exploits the partial overlapping structured (POS) sparsity and 2-dimensional (2D) block sparsity inherent in the SAC channels to enhance the overall performance. Based on the estimation results from the first phase, we formulate a Cram\'{e}r-Rao bound (CRB) minimization problem for optimizing IRS reflection coefficients, and through proper reformulations, a low-complexity manifold-based optimization algorithm is proposed to solve this problem. Simulation results are provided to verify the superiority of the proposed transmission scheme and associated algorithms.

Quantitative susceptibility mapping (QSM) is a post-processing technique for deriving tissue magnetic susceptibility distribution from MRI phase measurements. Deep learning (DL) algorithms hold great potential for solving the ill-posed QSM reconstruction problem. However, a significant challenge facing current DL-QSM approaches is their limited adaptability to magnetic dipole field orientation variations during training and testing. In this work, we propose a novel Orientation-Adaptive Latent Feature Editing (OA-LFE) module to learn the encoding of acquisition orientation vectors and seamlessly integrate them into the latent features of deep networks. Importantly, it can be directly Plug-and-Play (PnP) into various existing DL-QSM architectures, enabling reconstructions of QSM from arbitrary magnetic dipole orientations. Its effectiveness is demonstrated by combining the OA-LFE module into our previously proposed phase-to-susceptibility single-step instant QSM (iQSM) network, which was initially tailored for pure-axial acquisitions. The proposed OA-LFE-empowered iQSM, which we refer to as iQSM+, is trained in a self-supervised manner on a specially-designed simulation brain dataset. Comprehensive experiments are conducted on simulated and in vivo human brain datasets, encompassing subjects ranging from healthy individuals to those with pathological conditions. These experiments involve various MRI platforms (3T and 7T) and aim to compare our proposed iQSM+ against several established QSM reconstruction frameworks, including the original iQSM. The iQSM+ yields QSM images with significantly improved accuracies and mitigates artifacts, surpassing other state-of-the-art DL-QSM algorithms., Comment: 13pages, 9figures

The full disk, full of gas and dust, determines the upper limit of planet masses, and its lifetime is critical for planet formation, especially for giant planets. In this work, we studied the evolutionary timescales of the full disks of T Tauri stars (TTSs) and their relations to accretion. Combined with Gaia EDR3, 2MASS, and WISE data, 1077 disk-bearing TTS candidates were found in LAMOST DR8, and stellar parameters were obtained. Among them, 783 are newly classified by spectra as classical T Tauri stars (CTTSs; 169) or weak-lined T Tauri stars (WTTSs). Based on EW and FWHM of Ha, 157 TTSs in accretion were identified, with ~ 82% also having full disks. For TTSs with M<0.35 Mo, about 80% seem to already lose their full disks at ~ 0.1 Myr, which may explain their lower mass, while the remaining 20% with full disks evolve at similar rates of non-full disks within 5 Myr, possibly suffice to form giant planets. The fraction of accreting TTSs to disk-bearing TTSs is stable at ~10% and can last $\sim$ 5-10 Myr, suggesting that full disks and accretion evolve with similar rates as non-full disks. For TTSs with M>0.35Mo, almost all full disks can survive more than 0.1 Myr, most for 1 Myr and some even for 20 Myr, which implies planets are more likely to be formed in their disks than those of M<0.35 Mo, and thus M dwarfs with M>0.35Mo can have more planets. The fraction of full-disk TTSs to disk-bearing TTSs decreases with age following the relation $f\propto t^{-0.35}$, and similar relations existed in the fraction of accreting TTSs and the fraction of full-disk CTTSs, suggesting faster full disks and accretion evolution than non-full disks. For full disk stars, the ratio of accretion of lower-mass stars is systematically lower than that of higher-mass stars, confirming the dependence of accretion on stellar mass., Comment: 19 pages, 12 figures, 1 table

Satellite-based greenhouse gases (GHG) sensing technologies play a critical role in the study of global carbon emissions and climate change. However, none of the existing satellite-based GHG sensing technologies can achieve the measurement of broad bandwidth, high temporal-spatial resolution, and high sensitivity at the same time. Recently, dual-comb spectroscopy (DCS) has been proposed as a superior candidate technology for GHG sensing because it can measure broadband spectra with high temporal-spatial resolution and high sensitivity. The main barrier to DCS's display on satellites is its short measurement distance in open air achieved thus far. Prior research has not been able to implement DCS over 20 km of open-air path. Here, by developing a bistatic setup using time-frequency dissemination and high-power optical frequency combs, we have implemented DCS over a 113 km turbulent horizontal open-air path. Our experiment successfully measured GHG with 7 nm spectral bandwidth and a 10 kHz frequency and achieved a CO2 sensing precision of <2 ppm in 5 minutes and <0.6 ppm in 36 minutes. Our results represent a significant step towards advancing the implementation of DCS as a satellite-based technology and improving technologies for GHG monitoring, Comment: 24 pages, 6 figures

In this paper, we focus on zero-filter limit problem for the Camassa-Holm equation in the more general Besov spaces. We prove that the solution of the Camassa-Holm equation converges strongly in $L^\infty(0,T;B^s_{2,r}(\R))$ to the inviscid Burgers equation as the filter parameter $\alpha$ tends to zero with the given initial data $u_0\in B^s_{2,r}(\R)$. Moreover, we also show that the zero-filter limit for the Camassa-Holm equation does not converges uniformly with respect to the initial data in $B^s_{2,r}(\R)$.

Anchor-based detectors have been continuously developed for object detection. However, the individual anchor box makes it difficult to predict the boundary's offset accurately. Instead of taking each bounding box as a closed individual, we consider using multiple boxes together to get prediction boxes. To this end, this paper proposes the \textbf{Box Decouple-Couple(BDC) strategy} in the inference, which no longer discards the overlapping boxes, but decouples the corner points of these boxes. Then, according to each corner's score, we couple the corner points to select the most accurate corner pairs. To meet the BDC strategy, a simple but novel model is designed named the \textbf{Anchor-Intermediate Detector(AID)}, which contains two head networks, i.e., an anchor-based head and an anchor-free \textbf{Corner-aware head}. The corner-aware head is able to score the corners of each bounding box to facilitate the coupling between corner points. Extensive experiments on MS COCO show that the proposed anchor-intermediate detector respectively outperforms their baseline RetinaNet and GFL method by $\sim$2.4 and $\sim$1.2 AP on the MS COCO test-dev dataset without any bells and whistles. Code is available at: https://github.com/YilongLv/AID., Comment: Submitted 29 September, 2023; originally announced October 2023. Accepted by ICCV2023

Negative superhumps (NSHs) are signals a few percent shorter than the orbital period of a binary star and are considered to originate from the reverse precession of the tilted disk. Based on TESS photometry, we find nine new cataclysmic variable stars (CVs) with NSHs. Three (ASAS J1420, TZ Per, and V392 Hya) of these stars similar to AH Her still have NSHs during dwarf nova outbursts, and the NSH amplitude varies with the outburst. The variation in the radius of the accretion disk partially explains this phenomenon. However, it does not explain the rebound of the NSH amplitude after the peak of the outburst and the fact that the NSH amplitude of the quiescence is sometimes not the largest, and it is necessary to combine the disk instability model (DIM) and add other ingredients. Therefore, we suggest that the variation of NSH amplitude with outburst can be an essential basis for studying the origin of NSHs and improving the DIM. The six ( ASASSN-V J1137, ASASSN-V J0611, 2MASS J0715, LAMOST J0925, ASASSN-17qj, and ZTF18acakuxo) remaining stars have been poorly studied, and for the first time we determine their orbital periods, NSHs and Superorbital signal (SOR) periods. The NSH periods and amplitudes of ASASSN-V J1137 and ASASSN-17qj vary with the SOR, and based on the comparison of the observations with the theory, we suggest that a single change in tilted disk angle does not explain the observations of the SOR and that other ingredients need to be considered as well., Comment: 21 pages, 12 figures, accepted for publication in the Astrophysical Journal