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The field of single-cell biology is growing rapidly and is generating large amounts of data from a variety of species, disease conditions, tissues, and organs. Coordinated efforts such as CZI CELLxGENE, HuBMAP, Broad Institute Single Cell Portal, and DISCO, allow researchers to access large volumes of curated datasets. Although the majority of the data is from scRNAseq experiments, a wide range of other modalities are represented as well. These resources have created an opportunity to build and expand the computational biology ecosystem to develop tools necessary for data reuse, and for extracting novel biological insights. Here, we highlight achievements made so far, areas where further development is needed, and specific challenges that need to be overcome.

The properties of super-Eddington accretion disks exhibit substantial distinctions from the sub- Eddington ones. In this paper, we investigate the accretion process of a magnetized neutron star (NS) surrounded by a super-Eddington disk. By constructing self-similar solutions for the disk structure, we study in detail an interaction between the NS magnetosphere and the inner region of the disk, revealing that this interaction takes place within a thin boundary layer. The magnetosphere truncation radius is found to be approximately proportional to the Alfv\'en radius, with a coefficient ranging between 0.34-0.71, influenced by the advection and twisting of a magnetic field, NS rotation, and radiation emitted from an NS accretion column. Under super-Eddington accretion, the NS can readily spin up to become a rapid rotator. The proposed model can be employed to explore the accretion and evolution of NSs in diverse astrophysical contexts, such as ultraluminous X-ray binaries or active galactic nucleus disks., Comment: 14 pages, 7 figures, accepted for publication in ApJ

Face reenactment refers to the process of transferring the pose and facial expressions from a reference (driving) video onto a static facial (source) image while maintaining the original identity of the source image. Previous research in this domain has made significant progress by training controllable deep generative models to generate faces based on specific identity, pose and expression conditions. However, the mechanisms used in these methods to control pose and expression often inadvertently introduce identity information from the driving video, while also causing a loss of expression-related details. This paper proposes a new method based on Stable Diffusion, called AniFaceDiff, incorporating a new conditioning module for high-fidelity face reenactment. First, we propose an enhanced 2D facial snapshot conditioning approach by facial shape alignment to prevent the inclusion of identity information from the driving video. Then, we introduce an expression adapter conditioning mechanism to address the potential loss of expression-related information. Our approach effectively preserves pose and expression fidelity from the driving video while retaining the identity and fine details of the source image. Through experiments on the VoxCeleb dataset, we demonstrate that our method achieves state-of-the-art results in face reenactment, showcasing superior image quality, identity preservation, and expression accuracy, especially for cross-identity scenarios. Considering the ethical concerns surrounding potential misuse, we analyze the implications of our method, evaluate current state-of-the-art deepfake detectors, and identify their shortcomings to guide future research.

We introduce RoScenes, the largest multi-view roadside perception dataset, which aims to shed light on the development of vision-centric Bird's Eye View (BEV) approaches for more challenging traffic scenes. The highlights of RoScenes include significantly large perception area, full scene coverage and crowded traffic. More specifically, our dataset achieves surprising 21.13M 3D annotations within 64,000 $m^2$. To relieve the expensive costs of roadside 3D labeling, we present a novel BEV-to-3D joint annotation pipeline to efficiently collect such a large volume of data. After that, we organize a comprehensive study for current BEV methods on RoScenes in terms of effectiveness and efficiency. Tested methods suffer from the vast perception area and variation of sensor layout across scenes, resulting in performance levels falling below expectations. To this end, we propose RoBEV that incorporates feature-guided position embedding for effective 2D-3D feature assignment. With its help, our method outperforms state-of-the-art by a large margin without extra computational overhead on validation set. Our dataset and devkit will be made available at https://github.com/xiaosu-zhu/RoScenes., Comment: ECCV 2024. Extended version. 33 pages, 21 figures, 13 tables. https://github.com/xiaosu-zhu/RoScenes

Critical systems near quantum phase transitions were predicted to be useful for improvement of metrological precision, thanks to their ultra-sensitive response to a tiny variation of the control Hamiltonian. Despite the promising perspective, realization of criticality-enhanced quantum metrology is an experimentally challenging task, mainly owing to the extremely long time needed to encode the signal to some physical quantity of a critical system. We here circumvent this problem by making use of the critical behaviors in the Jaynes-Cummings model, comprising a single qubit and a photonic resonator, to which the signal field is coupled. The information about the field amplitude is encoded in the qubit's excitation number in the dark state, which displays a divergent changing rate at the critical point. The most remarkable feature of this critical sensor is that the performance is insensitive to the leakage to bright eigenstates, caused by decoherence and non-adiabatic effects. We demonstrate such a metrological protocol in a superconducting circuit, where an Xmon qubit, interacting with a resonator, is used as a probe for estimating the amplitude of a microwave field coupled to the resonator. The measured quantum Fisher information exhibits a critical quantum enhancement, confirming the potential of this system for quantum metrology., Comment: 13 pages, 11 figures

The bond-dependent Kitaev interaction $K$ is familiar in the effective spin model of transition metal compounds with octahedral ligands. In this work, we find a peculiar non-coplanar magnetic order can be formed with the help of $K$ and next-nearest neighbor Heisenberg coupling $J_2$ on the triangular lattice. It can be seen as a miniature version of skyrmion crystal, since it has nine spins and an integer topological number in a magnetic unit cell. The magnon excitations in such an order are studied by the linear spin-wave theory. Of note is that the change in the relative size of $J_2$ and $K$ produces topological magnon phase transitions although the topological number remains unchanged. We also calculated the experimentally observable thermal Hall conductivity, and found that the signs of thermal Hall conductivity will change with topological phase transitions or temperature changes in certain regions.

Parametrically driven nonlinear resonators represent a building block for realizing fault-tolerant quantum computation and are useful for critical quantum sensing. From a fundamental viewpoint, the most intriguing feature of such a system is perhaps the critical phenomena, which can occur without interaction with any other quantum system. The non-analytic behaviors of its eigenspectrum have been substantially investigated, but those associated with the ground state wavefunction have largely remained unexplored. Using the quantum ground state geometric tensor as an indicator, we comprehensively establish a phase diagram involving the driving parameter $\varepsilon$ and phase $\phi$. The results reveal that with the increase in $\varepsilon$, the system undergoes a quantum phase transition from the normal to the superradiant phase, with the critical point unaffected by $\phi$. Furthermore, the critical exponent and scaling dimension are obtained by an exact numerical method, which is consistent with previous works. Our numerical results show that the phase transition falls within the universality class of the quantum Rabi model. This work reveals that the quantum metric and Berry curvature display diverging behaviors across the quantum phase transition., Comment: Any comments or suggestions are welcome !

The noncollinear spin textures provide promising avenues to stabilize exotic magnetic phases and excitations. They have attracted vast attention owning to their nontrivial band topology in the past decades. Distinct from the conventional route of involving the Dzyaloshinskii-Moriya interaction in a honeycomb magnet, the interplay of bond-dependent Kitaev and $\Gamma$ interactions, originating from the spin-orbit coupling and octahedra crystal field in real materials, has demonstrated to be another source to generate noncollinear spin textures with multiple spins in a magnetic unit cell. Notably, earlier works have revealed a triple-meron crystal (TmX) consisting of eighteen spins in the frustrated Kitaev-$\Gamma$ model. Aligning with previous efforts, here we attempt to identify that the TmX hosts several peculiar features with the help of the linear spin-wave theory. To begin with, the symmetric anisotropic exchanges are beneficial for the existence of nonreciprocal magnons, which are stabilized by an external magnetic field. Further, within the regime of TmX, successive topological phase transitions occur, accompanied by the changes of Chern number in value and thermal Hall conductivity in sign. In addition, topological nature of magnons is also verified by the onset of chiral edge modes in a nanoribbon geometry. Our findings pave the way to study topological phenomena of noncollinear spin textures in potential Kitaev materials., Comment: 11 pages, 6+3 figures

The disk of an active galactic nucleus (AGN) is widely regarded as a prominent formation channel of binary black hole (BBH) mergers that can be detected through gravitational waves (GWs). Besides, the presence of dense environmental gas offers the potential for an embedded BBH merger to produce electromagnetic (EM) counterparts. In this paper, we investigate EM emission powered by the kicked remnant of a BBH merger occurring within the AGN disk. The remnant BH will launch a jet via accreting magnetized medium as it traverses the disk. The resulting jet will decelerate and dissipate energy into a lateral cocoon during its propagation. We explore three radiation mechanisms of the jet cocoon system: jet breakout emission, disk cocoon cooling emission, and jet cocoon cooling emission, and find that the jet cocoon cooling emission is more likely to be detected in its own frequency bands. We predict a soft X-ray transient, lasting for O($10^3$) s, to serve as an EM counterpart, of which the time delay O(10) days after the GW trigger contributes to follow-up observations. Consequently, BBH mergers in the AGN disk represent a novel multimessenger source. In the future, enhanced precision in measuring and localizing GWs, coupled with diligent searches for such associated EM signal, will effectively validate or restrict the origin of BBH mergers in the AGN disk., Comment: 19 pages, 9 figures, accepted for publication in ApJ

Pre-trained language models (PLMs) have established the new paradigm in the field of NLP. For more powerful PLMs, one of the most popular and successful way is to continuously scale up sizes of the models and the pre-training corpora. These large corpora are generally obtained by converging smaller ones from multiple sources, they are thus growing increasingly diverse. However, the side-effects of these colossal converged corpora remain understudied. In this paper, we identify the disadvantage of heterogeneous corpora from multiple sources for pre-training PLMs. Towards coordinated pre-training on diverse corpora, we further propose source prompts (SP), which explicitly prompt the model of the data source at the pre-training and fine-tuning stages. Results of extensive experiments demonstrate that PLMs pre-trained with SP on diverse corpora gain significant improvement in various downstream tasks.

The monitoring of data generated by a large number of devices in Internet of Things (IoT) systems is an important and complex issue. Several studies have explored the use of generic rule engine, primarily based on the RETE algorithm, for monitoring the flow of device data. In order to solve the performance problem of the RETE algorithm in IoT scenarios, some studies have also proposed improved RETE algorithms. However, implementing modifications to the general rule engine remains challenges in practical applications. The Thingsboard open-source platform introduces an IoT-specific rule engine that does not rely on the RETE algorithm. Its interactive mode attracted attention from developers and researchers. However, the close integration between its rule module and the platform, as well as the difficulty in formulating rules for multiple devices, limits its flexibility. This paper presents an adaptable and user-friendly rule engine framework for monitoring and control IoT device data flows. The framework is easily extensible and allows for the formulation of rules contain multiple devices. We designed a Domain-Specific Language (DSL) for rule description. A prototype system of this framework was implemented to verify the validity of theoretical method. The framework has potential to be adaptable to a wide range of IoT scenarios and is especially effective in where real-time control demands are not as strict., Comment: 15 pages,10 figures

Critical phenomena of quantum systems are useful for enhancement of quantum sensing. However, experimental realizations of criticality enhancement have been confined to very few systems, owing to the stringent requirements, including the thermodynamical or scaling limit, and fine control of interacting quantum susystems or particles. We here propose a simple critical quantum sensing scheme that requires neither of these conditions. The critical system is realized with a single parametrically-driven bosonic mode involving many non-interacting bosons. We calculate the quantum Fisher information, and perform a simulation, which confirms the criticality-enabled enhancement. We further detail the response of one of the quadratures to the variation of the control parameter. The numerical results reveal that its inverted variance exhibits a diverging behavior at the critical point. Based on the presently available control techniques of parametric driving, we expect our scheme can be realized in different systems, e.g., ion traps and superconducting circuits., Comment: 6 pages, 4 figures

Compact objects (COs) can exist and evolve in an active galactic nuclei (AGN) disk, triggering a series of attractive CO-related multi-messenger events around a supermassive black hole. To better understand the nature of an embedded CO and its surroundings and to investigate CO-related events more accurately, in this paper, we study the specific accretion process of a CO in an AGN disk and explore the role of outflow feedback. We show that the asymptotically isotropic outflow generated from the CO hyper-Eddington accretion would truncate the circum-CO disk and push out its surrounding gas, resulting in recurrent formation and refilling of an outflow cavity to intermittently stop the accretion. Applying this universal cyclic process to black holes (BHs) and neutron stars (NSs), we find that, even if it is above the Eddington rate, the mass rate accreted onto a BH is dramatically reduced compared with the initial gas captured rate and thus consumes few mass of the AGN disk; outflow feedback on a NS is generally similar, but possesses complexities on the existence of a stellar magnetic field and hard surface. We demonstrate that although outflow feedback itself may be unobservable, it remarkably alters the CO evolution via reducing its mass growth rate, and the AGN disk can survive from the otherwise drastic CO accretion overlooking outflow. In addition, we discuss the potential influence of underdense cavity on CO-related events, which embodies the significant role of outflow feedback as well., Comment: 25 pages, 13 figures, accepted for publication in ApJ

We investigate the dynamics and electromagnetic (EM) signatures of neutron star-neutron star (NS-NS) or neutron star-black hole (NS-BH) merger ejecta that occurs in the accretion disk of an active galactic nucleus (AGN). We find that the interaction between ejecta and disk gas leads to important effects on the dynamics and radiation. We show five stages of the ejecta dynamics: gravitational slowing down, coasting, Sedov-Taylor deceleration in the disk, re-acceleration after the breakout from the disk surface, and momentum-conserved snowplow phase. Meanwhile, the radiation from the ejecta is so bright that its typical peak luminosity reaches a few times $10^{43}-10^{44}~\rm erg~s^{-1}$. Since most of the radiation energy has converted from the kinetic energy of merger ejecta, we call such an explosive phenomenon an interacting kilonova (IKN). It should be emphasized that IKNe are very promising, bright EM counterparts to NS-NS/BH-NS merger events in AGN disks. The bright peak luminosity and long rising time (i.e., ten to twenty days in UV bands, thirty to fifty days in optical bands, and one hundred days to hundreds of days in IR bands) allow most survey telescopes to have ample time to detect an IKN. However, the peak brightness, peak time, and evolution pattern of the light curve of an IKN are similar to a superluminous supernova in a galactic nucleus and a tidal disruption event making it difficult to distinguish between them. But it also suggests that IKNe might have been present in recorded AGN transients., Comment: ApJL accepted

Robotic force-based compliance control is a preferred approach to achieve high-precision assembly tasks. When the geometric features of assembly objects are asymmetric or irregular, reinforcement learning (RL) agents are gradually incorporated into the compliance controller to adapt to complex force-pose mapping which is hard to model analytically. Since force-pose mapping is strongly dependent on geometric features, a compliance controller is only optimal for current geometric features. To reduce the learning cost of assembly objects with different geometric features, this paper is devoted to answering how to reconfigure existing controllers for new assembly objects with different geometric features. In this paper, model-based parameters are first reconfigured based on the proposed Equivalent Theory of Compliance Law (ETCL). Then the RL agent is transferred based on the proposed Weighted Dimensional Policy Distillation (WDPD) method. The experiment results demonstrate that the control reconfiguration method costs less time and achieves better control performance, which confirms the validity of proposed methods.

Traditional control methods of robotic peg-in-hole assembly rely on complex contact state analysis. Reinforcement learning (RL) is gradually becoming a preferred method of controlling robotic peg-in-hole assembly tasks. However, the training process of RL is quite time-consuming because RL methods are always globally connected, which means all state components are assumed to be the input of policies for all action components, thus increasing action space and state space to be explored. In this paper, we first define continuous space serialized Shapley value (CS3) and construct a connection graph to clarify the correlativity of action components on state components. Then we propose a local connection reinforcement learning (LCRL) method based on the connection graph, which eliminates the influence of irrelevant state components on the selection of action components. The simulation and experiment results demonstrate that the control strategy obtained through LCRL method improves the stability and rapidity of the control process. LCRL method will enhance the data-efficiency and increase the final reward of the training process.

Spin textures with nontrivial topology hold great promise in future spintronics applications since they are robust against local deformations. The meron, as one of such spin textures, is widely believed to appear in pairs due to its topological equivalence to a half skyrmion. Motivated by recent progresses in high-spin Kitaev magnets, here we investigate numerically a classical Kitaev-$\Gamma$ model with a single-ion anisotropy. An exotic spin texture including three merons is discovered. Such a state features a peculiar property with an odd number of merons in one magnetic unit cell and it can induce the topological Hall effect.Therefore, these merons cannot be dissociated from skyrmions as reported in the literature and a general mechanism for such a deconfinement phenomenon calls for further studies. Our work demonstrates that high-spin Kitaev magnets can host robust unconventional spin textures and thus they offer a versatile platform not only for exploring exotic states in spintronics but also for understanding the deconfinement mechanism in the condensed-matter physics and the field theory., Comment: Suggestions and comments are welcome