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LiDAR-based SLAM is recognized as one effective method to offer localization guidance in rough environments. However, off-the-shelf LiDAR-based SLAM methods suffer from significant pose estimation drifts, particularly components relevant to the vertical direction, when passing to uneven terrains. This deficiency typically leads to a conspicuously distorted global map. In this article, a LiDAR-based SLAM method is presented to improve the accuracy of pose estimations for ground vehicles in rough terrains, which is termed Rotation-Optimized LiDAR-Only (ROLO) SLAM. The method exploits a forward location prediction to coarsely eliminate the location difference of consecutive scans, thereby enabling separate and accurate determination of the location and orientation at the front-end. Furthermore, we adopt a parallel-capable spatial voxelization for correspondence-matching. We develop a spherical alignment-guided rotation registration within each voxel to estimate the rotation of vehicle. By incorporating geometric alignment, we introduce the motion constraint into the optimization formulation to enhance the rapid and effective estimation of LiDAR's translation. Subsequently, we extract several keyframes to construct the submap and exploit an alignment from the current scan to the submap for precise pose estimation. Meanwhile, a global-scale factor graph is established to aid in the reduction of cumulative errors. In various scenes, diverse experiments have been conducted to evaluate our method. The results demonstrate that ROLO-SLAM excels in pose estimation of ground vehicles and outperforms existing state-of-the-art LiDAR SLAM frameworks., Comment: This article has been accepted by Journal of Field Robotics

Sound decision-making relies on accurate prediction for tangible outcomes ranging from military conflict to disease outbreaks. To improve crowdsourced forecasting accuracy, we developed SAGE, a hybrid forecasting system that combines human and machine generated forecasts. The system provides a platform where users can interact with machine models and thus anchor their judgments on an objective benchmark. The system also aggregates human and machine forecasts weighting both for propinquity and based on assessed skill while adjusting for overconfidence. We present results from the Hybrid Forecasting Competition (HFC) - larger than comparable forecasting tournaments - including 1085 users forecasting 398 real-world forecasting problems over eight months. Our main result is that the hybrid system generated more accurate forecasts compared to a human-only baseline which had no machine generated predictions. We found that skilled forecasters who had access to machine-generated forecasts outperformed those who only viewed historical data. We also demonstrated the inclusion of machine-generated forecasts in our aggregation algorithms improved performance, both in terms of accuracy and scalability. This suggests that hybrid forecasting systems, which potentially require fewer human resources, can be a viable approach for maintaining a competitive level of accuracy over a larger number of forecasting questions., Comment: 20 pages, 6 figures, 4 tables

The exact-exchange relativistic density functional theory (Ex-RDFT) of atomic nuclei has been solved in three-dimensional lattice space for the first time. The exchange energy is treated within the framework of the orbital-dependent relativistic Kohn-Sham density functional theory, wherein the local Lorentz scalar and vector potentials are derived using the relativistic optimized effective potential method. The solutions of binding energies, charge radii, and density distributions are benchmarked against the traditional relativistic Hartree-Fock approach for spherical and axially deformed nuclei. Furthermore, the triaxial neutron-rich $^{104-120}\text{Ru}$ isotopes are investigated with the exchange correlations, which is beyond the current capacity of the traditional relativistic Hartree-Fock approach. The results notably indicate the $\gamma$-softness of these neutron-rich nuclei, which is consistent with experimental observations. This novel approach establishes a foundation for the study of nuclei without imposing any symmetry restrictions employing relativistic density functional with exchange correlations., Comment: 8 pages, 3 figures

Understanding the physical and chemical processes at the interface of metals and topological insulators is crucial for developing the next generation of topological quantum devices. Here we report the discovery of robust superconductivity in Pd/Bi$_2$Se$_3$ bilayers fabricated by sputtering Pd on the surface of Bi$_2$Se$_3$. Through transmission electron microscopy measurements, we identify that the observed interfacial superconductivity originates from the diffusion of Pd into Bi$_2$Se$_3$. In the diffusion region, Pd chemically reacts with Bi$_2$Se$_3$ and forms a layer of PdBiSe, a known su-perconductor with a bulk transition temperature of 1.5 K. Our work provides a method for in-troducing superconductivity into Bi$_2$Se$_3$, laying the foundation for developing sophisticated Bi$_2$Se$_3$-based topological devices.

Online shopping platforms, such as Amazon and AliExpress, are increasingly prevalent in society, helping customers purchase products conveniently. With recent progress in natural language processing, researchers and practitioners shift their focus from traditional product search to conversational product search. Conversational product search enables user-machine conversations and through them collects explicit user feedback that allows to actively clarify the users' product preferences. Therefore, prospective research on an intelligent shopping assistant via conversations is indispensable. Existing publications on conversational product search either model conversations independently from users, queries, and products or lead to a vocabulary mismatch. In this work, we propose a new conversational product search model, ConvPS, to assist users in locating desirable items. The model is first trained to jointly learn the semantic representations of user, query, item, and conversation via a unified generative framework. After learning these representations, they are integrated to retrieve the target items in the latent semantic space. Meanwhile, we propose a set of greedy and explore-exploit strategies to learn to ask the user a sequence of high-performance questions for conversations. Our proposed ConvPS model can naturally integrate the representation learning of the user, query, item, and conversation into a unified generative framework, which provides a promising avenue for constructing accurate and robust conversational product search systems that are flexible and adaptive. Experimental results demonstrate that our ConvPS model significantly outperforms state-of-the-art baselines., Comment: Accepted by ACM TOIS

Underwater acoustic target recognition based on passive sonar faces numerous challenges in practical maritime applications. One of the main challenges lies in the susceptibility of signal characteristics to diverse environmental conditions and data acquisition configurations, which can lead to instability in recognition systems. While significant efforts have been dedicated to addressing these influential factors in other domains of underwater acoustics, they are often neglected in the field of underwater acoustic target recognition. To overcome this limitation, this study designs auxiliary tasks that model influential factors (e.g., source range, water column depth, or wind speed) based on available annotations and adopts a multi-task framework to connect these factors to the recognition task. Furthermore, we integrate an adversarial learning mechanism into the multi-task framework to prompt the model to extract representations that are robust against influential factors. Through extensive experiments and analyses on the ShipsEar dataset, our proposed adversarial multi-task model demonstrates its capacity to effectively model the influential factors and achieve state-of-the-art performance on the 12-class recognition task.

Underwater acoustic target recognition has emerged as a prominent research area within the field of underwater acoustics. However, the current availability of authentic underwater acoustic signal recordings remains limited, which hinders data-driven acoustic recognition models from learning robust patterns of targets from a limited set of intricate underwater signals, thereby compromising their stability in practical applications. To overcome these limitations, this study proposes a recognition framework called M3 (Multi-task, Multi-gate, Multi-expert) to enhance the model's ability to capture robust patterns by making it aware of the inherent properties of targets. In this framework, an auxiliary task that focuses on target properties, such as estimating target size, is designed. The auxiliary task then shares parameters with the recognition task to realize multi-task learning. This paradigm allows the model to concentrate on shared information across tasks and identify robust patterns of targets in a regularized manner, thereby enhancing the model's generalization ability. Moreover, M3 incorporates multi-expert and multi-gate mechanisms, allowing for the allocation of distinct parameter spaces to various underwater signals. This enables the model to process intricate signal patterns in a fine-grained and differentiated manner. To evaluate the effectiveness of M3, extensive experiments were implemented on the ShipsEar underwater ship-radiated noise dataset. The results substantiate that M3 has the ability to outperform the most advanced single-task recognition models, thereby achieving the state-of-the-art performance.

Magnetic kagome materials provide a fascinating playground for exploring the interplay of magnetism, correlation and topology. Many magnetic kagome systems have been reported including the binary FemXn (X=Sn, Ge; m:n = 3:1, 3:2, 1:1) family and the rare earth RMn6Sn6 (R = rare earth) family, where their kagome flat bands are calculated to be near the Fermi level in the paramagnetic phase. While partially filling a kagome flat band is predicted to give rise to a Stoner-type ferromagnetism, experimental visualization of the magnetic splitting across the ordering temperature has not been reported for any of these systems due to the high ordering temperatures, hence leaving the nature of magnetism in kagome magnets an open question. Here, we probe the electronic structure with angle-resolved photoemission spectroscopy in a kagome magnet thin film FeSn synthesized using molecular beam epitaxy. We identify the exchange-split kagome flat bands, whose splitting persists above the magnetic ordering temperature, indicative of a local moment picture. Such local moments in the presence of the topological flat band are consistent with the compact molecular orbitals predicted in theory. We further observe a large spin-orbital selective band renormalization in the Fe d_xy+d_(x^2-y^2 ) spin majority channel reminiscent of the orbital selective correlation effects in the iron-based superconductors. Our discovery of the coexistence of local moments with topological flat bands in a kagome system echoes similar findings in magic-angle twisted bilayer graphene, and provides a basis for theoretical effort towards modeling correlation effects in magnetic flat band systems.

The ionic selectivity of nanopores is crucial for the energy conversion based on nanoporous membranes. It can be significantly affected by various parameters of nanopores and the applied fields driving ions through porous membranes. Here, with finite element simulations, the selective transport of ions through nanopores is systematically investigated under three common fields, i.e. the electric field (V), hydrostatic pressure (p), and concentration gradient (C). For negatively charged nanopores, through the quantitative comparison of the cation selectivity (t+) under the three fields, the cation selectivity of nanopores follows the order of t+V > t+c > t+p. This is due to the transport characteristics of cations and anions through the nanopores. Because of the strong transport of counterions in electric double layers under electric fields and concentration gradients, the nanopore exhibits a relatively higher selectivity to counterions. We also explored the modulation of t+ on the properties of nanopores and solutions. Under all three fields, t+ is directly proportional to the pore length and surface charge density, and inversely correlated to the pore diameter and salt concentration. Under both the electric field and hydrostatic pressure, t+ has almost no dependence on the applied field strength or ion species, which can affect t+ in the case of the concentration gradient. Our results provide detailed insights into the comparison and regulation of ionic selectivity of nanopores under three fields which can be useful for the design of high-performance devices for energy conversion based on nanoporous membranes., Comment: 28 pages, 5 figures

We present the analysis of three intermediate-mass quiescent galaxies (QGs) with stellar masses of $\sim10^{10}M_{\rm \odot}$ at redshifts $z\sim 3 - 4$ using NIRSpec low-resolution spectroscopy. Utilising the SED fitting code BAGPIPES, we confirm these target galaxies are consistent with quiescent population, with their specific star formation rates (sSFR) falling below 2-dex the star-forming main sequence at the same redshifts. Additionally, we identify these QGs to be less massive than those discovered in previous works, particularly prior to the JWST era. Two of our target galaxies exhibit the potentially-blended H${\alpha}$+[NII] emission line within their spectra with $S/N>5$. We discuss whether this feature comes from an Active Galactic Nucleus (AGN) or star formation although future high-resolution spectroscopy is required to reach a conclusion. One of the target galaxies is covered by JWST/NIRCam imaging of the PRIMER survey. Using the 2D profile fitting code Galfit, we examine its morphology, revealing a disc-like profile with a S\'{e}rsic index of $n=1.1 \pm 0.1$. On the size-mass relation, we find a potential distinction between less-massive ($\log_{10}{(M_*/M_\odot)}<10.3$) and massive ($\log_{10}{(M_*/M_\odot)}>10.3$) QGs in their evolutionary pathways. The derived quenching timescales for our targets are less than 1 Gyr. This may result from these galaxies being quenched by AGN feedback, supporting the AGN scenario of the emission line features., Comment: MNRAS accepted

Spins in strongly frustrated systems are of intense interest due to the emergence of intriguing quantum states including superconductivity and quantum spin liquid. Herein we report the discovery of cascade of phase transitions and large magnetic anisotropy in the averievite CsClCu5P2O10 single crystals. Under zero field, CsClCu5P2O10 undergoes a first-order structural transition at around 225 K from high temperature centrosymmetric P-3m1 to low temperature noncentrosymmetric P321, followed by an AFM transition at 13.6 K, another structural transition centering at ~3 K, and another AFM transition at ~2.18 K. Based upon magnetic susceptibility and magnetization data with magnetic fields perpendicular to the ab plane, a phase diagram, consisting of a paramagnetic state, two AFM states and four field-induced states including two magnetization plateaus, has been constructed. Our findings demonstrate that the quasi-2D CsClCu5P2O10 exhibits rich structural and metamagnetic transitions and the averievite family is a fertile platform for exploring novel quantum states., Comment: 15 pages, 5 figures

Using $pp$ collision data at $\sqrt{s}=13$ TeV, recorded by the LHCb experiment between 2016 and 2018 and corresponding to an integrated luminosity of $5.4$ fb$^{-1}$, the forward-backward asymmetry in the $pp \to Z/\gamma^{*} \to \mu^+\mu^-$ process is measured. The measurement is carried out in ten intervals of the difference between the muon pseudorapidities, within a fiducial region covering dimuon masses between $66$ and $116$ GeV, muon pseudorapidities between $2.0$ and $4.5$ and muon transverse momenta above $20$ GeV. These forward-backward asymmetries are compared with predictions, at next-to-leading order in the strong and electroweak couplings. The measured effective leptonic weak mixing angle is $\sin^2\theta_{\rm eff}^\ell = 0.23147 \pm 0.00044 \pm 0.00005 \pm 0.00023$, where the first uncertainty is statistical, the second arises from systematic uncertainties associated with the asymmetry measurement, and the third arises from uncertainties in the fit model used to extract $\sin^2\theta_{\rm eff}^\ell$ from the asymmetry measurement. This result is based on an arithmetic average of results using the CT18, MSHT20, and NNPDF31 parameterisations of the proton internal structure, and is consistent with previous measurements and with predictions from the global electroweak fit., Comment: All figures and tables, along with machine-readable versions and any supplementary material and additional information, are available at https://lbfence.cern.ch/alcm/public/analysis/full-details/3360/ (LHCb public pages)

We develop off-lattice simulations of semiflexible polymer chains subjected to applied mechanical forces using Markov Chain Monte Carlo. Our approach models the polymer as a chain of fixed-length bonds, with configurations updated through adaptive non-local Monte Carlo moves. This proposed method enables precise calculation of a polymer's response to a wide range of mechanical forces, which traditional on-lattice models cannot achieve. Our approach has shown excellent agreement with theoretical predictions of persistence length and end-to-end distance in quiescent states, as well as stretching distances under tension. Moreover, our model eliminates the orientational bias present in on-lattice models, which significantly impacts calculations such as the scattering function, a crucial technique for revealing polymer conformation., Comment: 16 pages, 7 figures

SrRuO$_3$ is a prototypical transition metal oxide which hosts rich physical properties including itinerant ferromagnetism, high conductivity, and intrinsic Hall effect originating in the Weyl points. Recently, high-quality SrRuO$_3$ films with residual resistivity ratios of more than 50 have been reported to exhibit quantum oscillations at low temperatures in spite of its strong electron correlation. While the origin of the oscillations has been discussed in relation to Weyl orbits based on the Weyl semimetal band structure, so far experimentally reported results are neither consistent with each other nor with theoretically expected behavior, leaving the origin of the oscillations in SrRuO$_3$ films still elusive. In this report, we have carefully evaluated the quantum oscillations observed in three-dimensional thick SrRuO$_3$ films with a high residual resistivity ratio of RRR = 82. We reveal the coexistence of two oscillation components both derived from two-dimensional electronic states and with slightly different masses, suggesting the involvement of the surface Fermi arc states formed between different Weyl point pairs., Comment: 13 pages, 3 figures

Using $e^+e^-$ collision data collected by the BESIII detector at BEPCII corresponding to an integrated luminosity of 30 $\rm fb^{-1}$, we measure Born cross sections and effective form factors for the process $e^+e^-\to\Xi^0\bar{\Xi}^0$ at forty-five center-of-mass energies between 3.51 and 4.95 GeV. The dressed cross section is fitted, assuming a power-law function plus a charmonium(-like) state, i.e., $\psi(3770)$, $\psi(4040)$, $\psi(4160)$, $\psi(4230)$, $\psi(4360)$, $\psi(4415)$ or $\psi(4660)$. No significant charmonium(-like) state decaying into $\Xi^0\bar\Xi^0$ is observed. Upper limits at the 90% confidence level on the product of the branching fraction and the electronic partial width are provided for each decay. In addition, ratios of the Born cross sections and the effective form factors for $e^+e^-\to\Xi^0\bar{\Xi}^0$ and $e^+e^-\to\Xi^-\bar{\Xi}^+$ are also presented to test isospin symmetry and the vector meson dominance model., Comment: 23 pages, 2 tables, 4 figures, consistent with the publication in JHEP05(2024)022

Context: Online collaborative creation of models is becoming commonplace. Collaborative modeling using chatbots and natural language may lower the barriers to modeling for users from different domains. Objective: We compare the perceived usability of two similarly online collaborative modeling tools, the SOCIO chatbot and the Creately web-based tool. Method: We conducted a crossover experiment with 66 participants. The evaluation instrument was based on the System Usability Scale (SUS). We performed a quantitative and qualitative exploration, employing inferential statistics and thematic analysis. Results: The results indicate that chatbots enabling natural language communication enhance communication and collaboration efficiency and improve the user experience. Conclusion: Chatbots need to improve guidance and help for novices, but they appear beneficial for enhancing user experience.

We present a novel scattering emulator utilizing the complex scaling method to enhance nuclear reaction analysis. This approach leverages a single set of reduced bases, allowing for efficient and simultaneous emulation across multiple channels and potential parameters, significantly reducing computational storage and accelerating calculations. Demonstrated through \(n\)+\(^{40}\)Ca and \(^{11}\)Be+\(^{64}\)Zn elastic scattering, our method achieves high accuracy and efficiency. This emulator exhibits stable and reliable performance without anomalies inherent in other techniques, showcasing its robustness., Comment: 5 pages, 3 figures, published in Phys. Lett. B 858, 139070(2024)

Noncollinear ferroic materials are sought after as testbeds to explore the intimate connections between topology and symmetry, which result in electronic, optical and magnetic functionalities not observed in collinear ferroic materials. For example, ferroaxial materials have ordered rotational structural distortions that break mirror symmetry and induce chirality. When ferroaxial order is coupled with ferroelectricity arising from a broken inversion symmetry, it offers the prospect of electric-field-control of the ferroaxial distortions and opens up new tunable functionalities. However, chiral multiferroics, especially ones stable at room temperature, are rare. We report the discovery of a strain-stabilized, room-temperature chiral multiferroic phase in single crystals of BaTiS$_3$, a quasi-one-dimensional (1D) hexagonal chalcogenide. Using first-principles calculations, we predict the stabilization of this multiferroic phase having $P6_3$ space group for biaxial tensile strains exceeding 1.5% applied on the basal ab-plane of the room temperature $P6_3cm$ phase of BaTiS$_3$. The chiral multiferroic phase is characterized by rotational distortions of select TiS$_6$ octahedra around the long $c$-axis and polar displacement of Ti atoms along the $c$-axis. We used an innovative approach using focused ion beam milling to make appropriately strained samples of BaTiS$_3$. The ferroaxial and ferroelectric distortions, and their domains in $P6_3$-BaTiS$_3$ were directly resolved using atomic resolution scanning transmission electron microscopy. Landau-based phenomenological modeling predicts a strong coupling between the ferroelectric and the ferroaxial order making $P6_3$-BaTiS$_3$ an attractive test bed for achieving electric-field control of chirality-related phenomena such as circular photo-galvanic current and the Rashba effect., Comment: 20 pages, 4 figures

Close white dwarf binaries (CWDBs) are considered to be progenitors of several exotic astronomical phenomena (e.g., type Ia supernovae, cataclysmic variables). These violent events are broadly used in studies of general relativity and cosmology. However, obtaining precise stellar parameter measurements for both components of CWDBs is a challenging task given their low luminosities, swift time variation, and complex orbits. High-resolution spectra (R$> 20 000$) are preferred but expensive, resulting in a sample size that is insufficient for robust population study. To release the full potential of the less expensive low-resolution spectroscopic surveys, and thus greatly expand the CWDB sample size, it is necessary to develop a robust pipeline for spectra decomposition and analysis. We used an artificial neural network (ANN) to build spectrum generators for DA/DB white dwarfs and main-sequence stars. The best-fit stellar parameters were obtained by finding the least $\chi^2$ solution to these feature lines and the continuum simultaneously. We demonstrate the reliability of our code with two well-studied CWDBs, WD 1534+503 and PG 1224+309. We also estimate the stellar parameters of 14 newly identified CWDB candidates, most of which are fitted with double component models for the first time. Our estimates agree with previous results for the common stars and follow the statistical distribution in the literature. The application of our code to a large volume of white dwarf binary candidates will offer important statistic samples to stellar evolution studies and future gravitational wave monitoring., Comment: 14pages, 12 figures, 2 tables.Accepted by A&A

In this study, high-quality thin films of the topological semimetal phase NiTe$_2$ were prepared using molecular beam epitaxy (MBE) technique, confirmed through X-ray diffraction with pronounced Laue oscillations. Electrical transport experiments reveal that thick films have properties similar to bulk materials. By employing co-deposition, we introduced either magnetic or non-magnetic elements during the growth of thinner films, significantly altering their electrical properties. Notably, magnetic element Cr induces long-range ferromagnetic ordering, leading to the observation of significant anomalous Hall effect in NiTe2 thin films. The Hall conductivity remains nearly constant well below the Curie temperature, indicating the correlation with the intrinsic topological nature of the band structure. Theoretical first principles band calculations support the generation of the Weyl semimetal state in the material through magnetic doping. These findings pave the way for exploring more magnetic Weyl semimetal materials and related low-dimensional quantum devices based on topological semimetal materials., Comment: 14 panges, 4 figures