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We uncover a hub-filament system associated with massive star formation in the G083.097$+$03.270. Diagnosed with simultaneous $^{12}$CO, $^{13}$CO, and C$^{18}$O line observations, the region is found to host two distinct and elongated filaments having separate velocity components, interacting spatially and kinematically, that appear to have seeded the formation of a dense hub at the intersection. A large velocity spread at the hub in addition to clear bridging feature connecting the filaments in velocity are indicating merging of filaments. Along the filaments axis, the velocity gradient reveals a global gas motion with an increasing velocity dispersion inward to the hub signifying turbulence. Altogether, the clustering of Class I sources, a high excitation temperature, a high column density, and presence of a massive outflow at the central hub suggest enhanced star formation. We propose that merging of large-scale filaments and velocity gradients along filaments are the driving factors in the mass accumulation process at the hub that have sequentially led to the massive star formation. With two giant filaments merging to coincide with a hub therein with ongoing star formation, this site serves as a benchmark for the `filaments to clusters' star-forming paradigm., Comment: 12 pages, 7 figures, 1 table, accepted for publication in ApJ

X-ray powder diffraction, electrical resistivity, magnetization, and thermodynamic measurements were conducted to investigate the structure and superconducting properties of TiHfNbTaMo, a novel high-entropy alloy possessing a valence electron count (VEC) of 4.8. The TiHfNbTaMo HEA was discovered to have a body-centered cubic structure and a microscopically homogeneous distribution of the constituent elements. This material shows type-II superconductivity with Tc = 3.42 K, lower critical field with 22.8 mT, and upper critical field with 3.95 T. Low-temperature specific heat measurements show that the alloy is a conventional s-wave type with a moderately coupled superconductor. First-principles calculations show that the density of states (DOS) of the TiHfNbTaMo alloy is dominated by hybrid d orbitals of these five metal elements. Additionally, the TiHfNbTaMo HEA exhibits three van Hove singularities. Furthermore, the VEC and the composition of the elements (especially the Nb elemental content) affect the Tc of the bcc-type HEA., Comment: 19 pages, 6 figures,The manuscript with the same title will be published by Advanced Quantum Technologies

According to the structures traced by $^{13}$CO spectral lines within the $^{12}$CO molecular clouds (MCs), we investigate the contributions of their internal gas motions and relative motions to the total velocity dispersions of $^{12}$CO MCs. Our samples of 2851 $^{12}$CO MCs harbor a total of 9556 individual $^{13}$CO structures, among which 1848 MCs ($\sim$ 65$\%$) have one individual $^{13}$CO structure and the other 1003 MCs ($\sim$ 35$\%$) have multiple $^{13}$CO structures. We find that the contribution of the relative motion between $^{13}$CO structures ($\sigma_{\rm ^{13}CO, re}$) is larger than that from their internal gas motion ($\sigma_{\rm ^{13}CO, in}$) in $\sim$ 62$\%$ of 1003 MCs in the `multiple' regime. In addition, we find the $\sigma_{\rm ^{13}CO, re}$ tends to increase with the total velocity dispersion($\sigma_{\rm ^{12}CO, tot}$) in our samples, especially for the MCs having multiple $^{13}$CO structures. This result provides a manifestation of the macro-turbulent within MCs, which gradually becomes the dominant way to store the kinetic energy along with the development of MC scales., Comment: 15 pages, 13 figures, accepted for publication in ApJ

Gait recognition is a promising biometric technology for identification due to its non-invasiveness and long-distance. However, external variations such as clothing changes and viewpoint differences pose significant challenges to gait recognition. Silhouette-based methods preserve body shape but neglect internal structure information, while skeleton-based methods preserve structure information but omit appearance. To fully exploit the complementary nature of the two modalities, a novel triple branch gait recognition framework, TriGait, is proposed in this paper. It effectively integrates features from the skeleton and silhouette data in a hybrid fusion manner, including a two-stream network to extract static and motion features from appearance, a simple yet effective module named JSA-TC to capture dependencies between all joints, and a third branch for cross-modal learning by aligning and fusing low-level features of two modalities. Experimental results demonstrate the superiority and effectiveness of TriGait for gait recognition. The proposed method achieves a mean rank-1 accuracy of 96.0% over all conditions on CASIA-B dataset and 94.3% accuracy for CL, significantly outperforming all the state-of-the-art methods. The source code will be available at https://github.com/feng-xueling/TriGait/., Comment: Accepted by IJCB 2023

We present the results of an unbiased $^{12}$CO/$^{13}$CO/C$^{18}$O ($J$ = 1-0) survey in a portion of the third Galactic quadrant (TGQ): $l$ = [219.75, 229.75]$^\circ$ and $b$ = [-5.25, 5.25]$^\circ$. The high-resolution and high-sensitivity data sets help to unravel the distributions and physical properties of the molecular clouds (MCs) in the mapped area. In the LSR velocity range from -1 to 85 km/s, the molecular material successfully traces the Local, Perseus, and Outer arms. In the TGQ, the Outer arm appears to be more prominent than that in the second Galactic quadrant (SGQ), but the Perseus arm is not as conspicuous as that in the SGQ. A total of 1,502 $^{12}$CO, 570 $^{13}$CO, and 53 C$^{18}$O molecular structures are identified, spanning over $\sim2$ and $\sim6$ orders of magnitude in size and mass, respectively. Tight mass-radius correlations and virial parameter-mass anticorrelations are observable. Yet, it seems that no clear correlations between velocity dispersion and effective radius can be found over the full dynamic range. The vertical distribution of the MCs renders evident pictures of the Galactic warp and flare., Comment: 22 pages, 13 figures, 7 tables (with machine-readable versions), published in ApJS

The recent experimental claim of room-temperature ambient-pressure superconductivity in a Cu-doped lead-apatite (LK-99) has ignited substantial research interest in both experimental and theoretical domains. Previous density functional theory (DFT) calculations with the inclusion of an on-site Hubbard interaction $U$ consistently predict the presence of flat bands crossing the Fermi level. This is in contrast to DFT plus dynamical mean field theory calculations, which reveal the Mott insulating behavior for the stoichiometric Pb$_{9}$Cu(PO$_4$)$_6$O compound. Nevertheless, the existing calculations are all based on the $P6_3/m$ structure, which is argued to be not the ground-state structure. Here, we revisit the electronic structure of Pb$_{9}$Cu(PO$_4$)$_6$O with the energetically more favorable $P\bar{3}$ structure, fully taking into account electronic symmetry breaking. We examine all possible configurations for Cu substituting the Pb sites. Our results show that the doped Cu atoms exhibit a preference for substituting the Pb2 sites than the Pb1 sites. In both cases, the calculated substitutional formation energies are large, indicating the difficulty in incorporating Cu at the Pb sites. We find that most of structures with Cu at the Pb2 site tend to be insulating, while the structures with both two Cu atoms at the Pb1 sites (except one configuration) are predicted to be metallic by DFT+$U$ calculations. However, when accounting for the electronic symmetry breaking, some Cu-doped configurations previously predicted to be metallic (including the structure studied in previous DFT+$U$ calculations) become insulating. Our work highlights the importance of symmetry breaking in obtaining correct electronic state for Pb$_{9}$Cu(PO$_4$)$_6$O, thereby reconciling previous DFT+$U$ and DFT+DMFT calculations., Comment: 19 pages, 9 figures (including Supplementary Material)

This paper aims to tackle a novel task - Temporal Sentence Grounding in Streaming Videos (TSGSV). The goal of TSGSV is to evaluate the relevance between a video stream and a given sentence query. Unlike regular videos, streaming videos are acquired continuously from a particular source, and are always desired to be processed on-the-fly in many applications such as surveillance and live-stream analysis. Thus, TSGSV is challenging since it requires the model to infer without future frames and process long historical frames effectively, which is untouched in the early methods. To specifically address the above challenges, we propose two novel methods: (1) a TwinNet structure that enables the model to learn about upcoming events; and (2) a language-guided feature compressor that eliminates redundant visual frames and reinforces the frames that are relevant to the query. We conduct extensive experiments using ActivityNet Captions, TACoS, and MAD datasets. The results demonstrate the superiority of our proposed methods. A systematic ablation study also confirms their effectiveness., Comment: Accepted by ACM MM 2023

In the last few decades, basic ideas of topology have completely transformed the prediction of quantum transport phenomena. Following this trend, we go deeper into the incorporation of modern mathematics into quantum material science focusing on geometry. Here we investigate the relation between the geometrical type of the Fermi surface and Anomalous and Spin Hall Effects. An index, $\mathbb{H}_F$, quantifying the hyperbolic geometry of the Fermi surface, shows a universal correlation (R$^2$ = 0.97) with the experimentally measured intrinsic anomalous Hall conductivity, of 16 different compounds spanning a wide variety of crystal, chemical, and electronic structure families, including those where topological methods give R$^2$ = 0.52. This raises a question about the predictive limits of topological physics and its transformation into a wider study of bandstructures' and Fermi surfaces' geometries, opening horizon for prediction of phenomena beyond topological understanding., Comment: Submission to SciPost. arXiv admin note: substantial text overlap with arXiv:2007.05525

We universally search for evidence of kinematic and spatial correlation of supernova remnant (SNR) and molecular cloud (MC) associations for nearly all SNRs in the coverage of the MWISP CO survey, i.e. 149 SNRs, 170 SNR candidates, and 18 pure pulsar wind nebulae (PWNe) in 1 deg < l < 230 deg and -5.5 deg < b < 5.5 deg. Based on high-quality and unbiased 12CO/13CO/C18O (J = 1--0) survey data, we apply automatic algorithms to identify broad lines and spatial correlations for molecular gas in each SNR region. The 91% of SNR-MC associations detected previously are identified in this paper by CO line emission. Overall, there could be as high as 80% of SNRs associated with MCs. The proportion of SNRs associated with MCs is high within the Galactic longitude less than ~50 deg. Kinematic distances of all SNRs that are associated with MCs are estimated based on systemic velocities of associated MCs. The radius of SNRs associated with MCs follows a lognormal distribution, which peaks at ~8.1 pc. The progenitor initial mass of these SNRs follows a power-law distribution with an index of ~-2.3 that is consistent with the Salpeter index of -2.35. We find that SNR-MC associations are mainly distributed in a thin disk along the Galactic plane, while a small amount distributed in a thick disk. With the height of these SNRs from the Galactic plane below ~45 pc, the distribution of the average radius relative to the height of them is roughly flat, and the average radius increases with the height when above ~45 pc., Comment: 77 pages, 20 figures, 4 tables (with machine-readable versions), accepted for publication in ApJS

Adaptive optimization has achieved notable success for distributed learning while extending adaptive optimizer to federated Learning (FL) suffers from severe inefficiency, including (i) rugged convergence due to inaccurate gradient estimation in global adaptive optimizer; (ii) client drifts exacerbated by local over-fitting with the local adaptive optimizer. In this work, we propose a novel momentum-based algorithm via utilizing the global gradient descent and locally adaptive amended optimizer to tackle these difficulties. Specifically, we incorporate a locally amended technique to the adaptive optimizer, named Federated Local ADaptive Amended optimizer (\textit{FedLADA}), which estimates the global average offset in the previous communication round and corrects the local offset through a momentum-like term to further improve the empirical training speed and mitigate the heterogeneous over-fitting. Theoretically, we establish the convergence rate of \textit{FedLADA} with a linear speedup property on the non-convex case under the partial participation settings. Moreover, we conduct extensive experiments on the real-world dataset to demonstrate the efficacy of our proposed \textit{FedLADA}, which could greatly reduce the communication rounds and achieves higher accuracy than several baselines., Comment: IEEE Transactions on Pattern Analysis and Machine Intelligence

Recently, Lee et al. reported the experimental discovery of room-temperature ambient-pressure superconductivity in a Cu-doped lead-apatite (LK-99) (arXiv:2307.12008, arXiv:2307.12037). Remarkably, the superconductivity persists up to 400 K at ambient pressure. Despite strong experimental evidence, the electronic structure of LK-99 has not yet been studied. Here, we investigate the electronic structures of LK-99 and its parent compound using first-principles calculations, aiming to elucidate the doping effects of Cu. Our results reveal that the parent compound Pb$_{10}$(PO$_4$)$_6$O is an insulator, while Cu doping induces an insulator-metal transition and thus volume contraction. The band structures of LK-99 around the Fermi level are featured by a half-filled flat band and a fully-occupied flat band. These two flat bands arise from both the $2p$ orbitals of $1/4$-occupied O atoms and the hybridization of the $3d$ orbitals of Cu with the $2p$ orbitals of its nearest-neighboring O atoms. Interestingly, we observe four van Hove singularities on these two flat bands. Furthermore, we show that the flat band structures can be tuned by including electronic correlation effects or by doping different elements. We find that among the considered doping elements (Ni, Cu, Zn, Ag, and Au), both Ni and Zn doping result in the gap opening, whereas Au exhibits doping effects more similar to Cu than Ag. Our work provides a foundation for future studies on the role of unique electronic structures of LK-99 in superconductivity.

Gait recognition is one of the most promising video-based biometric technologies. The edge of silhouettes and motion are the most informative feature and previous studies have explored them separately and achieved notable results. However, due to occlusions and variations in viewing angles, their gait recognition performance is often affected by the predefined spatial segmentation strategy. Moreover, traditional temporal pooling usually neglects distinctive temporal information in gait. To address the aforementioned issues, we propose a novel gait recognition framework, denoted as GaitASMS, which can effectively extract the adaptive structured spatial representations and naturally aggregate the multi-scale temporal information. The Adaptive Structured Representation Extraction Module (ASRE) separates the edge of silhouettes by using the adaptive edge mask and maximizes the representation in semantic latent space. Moreover, the Multi-Scale Temporal Aggregation Module (MSTA) achieves effective modeling of long-short-range temporal information by temporally aggregated structure. Furthermore, we propose a new data augmentation, denoted random mask, to enrich the sample space of long-term occlusion and enhance the generalization of the model. Extensive experiments conducted on two datasets demonstrate the competitive advantage of proposed method, especially in complex scenes, i.e. BG and CL. On the CASIA-B dataset, GaitASMS achieves the average accuracy of 93.5\% and outperforms the baseline on rank-1 accuracies by 3.4\% and 6.3\%, respectively, in BG and CL. The ablation experiments demonstrate the effectiveness of ASRE and MSTA. The source code is available at https://github.com/YanSungithub/GaitASMS.

We report a study on low-temperature heat transport of Kitaev magnet Na$_2$Co$_2$TeO$_6$, with the heat current and magnetic fields along the honeycomb spin layer (the $ab$ plane). The zero-field thermal conductivity of $\kappa^a_{xx}$ and $\kappa^{a*}_{xx}$ display similar temperature dependence and small difference in their magnitudes; whereas, their magnetic field (parallel to the heat current) dependence are quite different and are related to the field-induced magnetic transitions. The $\kappa^a_{xx}(B)$ data for $B \parallel a$ at very low temperatures have an anomaly at 10.25--10.5 T, which reveals an unexplored magnetic transition. The planar thermal Hall conductivity $\kappa^a_{xy}$ and $\kappa^{a*}_{xy}$ show very weak signals at low fields and rather large values with sign change at high fields. This may point to a possible magnetic structure transition or the change of the magnon band topology that induces a radical change of magnon Berry curvature distribution before entering the spin polarized state. These results put clear constraints on the high-field phase and the theoretical models for Na$_2$Co$_2$TeO$_6$., Comment: 7 pages, 4 figures

Recently, the giant intrinsic anomalous Hall effect (AHE) has been observed in the materials with kagome lattice. In this study, we systematically investigate the influence of high pressure on the AHE in the ferromagnet LiMn6Sn6 with clean Mn kagome lattice. Our in-situ high-pressure Raman spectroscopy indicates that the crystal structure of LiMn6Sn6 maintains a hexagonal phase under high pressures up to 8.51 GPa. The anomalous Hall conductivity (AHC) {\sigma}xyA remains around 150 {\Omega}-1 cm-1, dominated by the intrinsic mechanism. Combined with theoretical calculations, our results indicate that the stable AHE under pressure in LiMn6Sn6 originates from the robust electronic and magnetic structure., Comment: 11 pages 5 figures

Federated learning (FL) is a distributed paradigm that coordinates massive local clients to collaboratively train a global model via stage-wise local training processes on the heterogeneous dataset. Previous works have implicitly studied that FL suffers from the ``client-drift'' problem, which is caused by the inconsistent optimum across local clients. However, till now it still lacks solid theoretical analysis to explain the impact of this local inconsistency. To alleviate the negative impact of the ``client drift'' and explore its substance in FL, in this paper, we first design an efficient FL algorithm \textit{FedInit}, which allows employing the personalized relaxed initialization state at the beginning of each local training stage. Specifically, \textit{FedInit} initializes the local state by moving away from the current global state towards the reverse direction of the latest local state. This relaxed initialization helps to revise the local divergence and enhance the local consistency level. Moreover, to further understand how inconsistency disrupts performance in FL, we introduce the excess risk analysis and study the divergence term to investigate the test error of the proposed \textit{FedInit} method. Our studies show that optimization error is not sensitive to this local inconsistency, while it mainly affects the generalization error bound in \textit{FedInit}. Extensive experiments are conducted to validate this conclusion. Our proposed \textit{FedInit} could achieve state-of-the-art~(SOTA) results compared to several advanced benchmarks without any additional costs. Meanwhile, stage-wise relaxed initialization could also be incorporated into the current advanced algorithms to achieve higher performance in the FL paradigm., Comment: 32 pages

We present maps and spectra of the HCN(1-0) and HCO$^+$(1-0) lines in the extreme outer Galaxy, at galactocentric radii between 14 and 22 kpc, with the 13.7 meter Delingha telescope. The 9 molecular clouds were selected from a CO/$^{13}$CO survey of the outer quadrants. The goal is to better understand the structure of molecular clouds in these poorly studied subsolar metallicity regions and the relation with star formation. The lines are all narrow, less than 2km/s at half power, enabling detection of the HCN hyperfine structure in the stronger sources and allowing us to observationally test hyperfine collision rates. The hyperfine line ratios show that the HCN emission is optically thin with column densities estimated at N(HCN)~$3x10^{12}$\scm. The HCO$^+$ emission is approximately twice as strong as the HCN (taken as the sum of all components), in contrast with the inner Galaxy and nearby galaxies where they are similarly strong. For an abundance ratio $\chi_{HCN}/\chi_{HCO^+} = 3$, this requires a relatively low density solution for the dense gas, with n(H2) $\sim 10^3 - 10^4$\ccm. The $^{12}$CO/$^{13}$CO line ratios are similar to solar neighborhood values, roughly 7.5, despite the low $^{13}$CO abundance expected at such large radii. The HCO$^+$/CO and HCO$^+$/$^{13}$CO integrated intensity ratios are also standard at about 1/35 and 1/5 respectively. HCN is weak compared to the CO emission, with HCN/CO $\sim 1/70$ even after summing all hyperfine components. At the parsec scales observed here, the correlation between star formation, as traced by 24~$\mu$m emission as is standard in extragalactic work, and dense gas via the HCN or HCO$^+$ emission, is poor, perhaps due to the lack of dynamic range. We find that the lowest dense gas fractions are in the sources at high galactic latitude (b>2, h>300pc above the plane), possibly due to lower pressure., Comment: 17 pages, 14 figures