Elysium: Exploring Object-level Perception in Videos via MLLM

Multi-modal Large Language Models (MLLMs) have demonstrated their ability to perceive objects in still images, but their application in video-related tasks, such as object tracking, remains understudied. This lack of exploration is primarily due to two key challenges. Firstly, extensive pretraining on large-scale video datasets is required to equip MLLMs with the capability to perceive objects across multiple frames and understand inter-frame relationships. Secondly, processing a large number of frames within the context window of Large Language Models (LLMs) can impose a significant computational burden. To address the first challenge, we introduce ElysiumTrack-1M, a large-scale video dataset supported for three tasks: Single Object Tracking (SOT), Referring Single Object Tracking (RSOT), and Video Referring Expression Generation (Video-REG). ElysiumTrack-1M contains 1.27 million annotated video frames with corresponding object boxes and descriptions. Leveraging this dataset, we conduct training of MLLMs and propose a token-compression model T-Selector to tackle the second challenge. Our proposed approach, Elysium: Exploring Object-level Perception in Videos via MLLM, is an end-to-end trainable MLLM that attempts to conduct object-level tasks in videos without requiring any additional plug-in or expert models. All codes and datasets are available at https://github.com/Hon-Wong/Elysium

Numerical Investigations on Wedge Control of Separation of a Missile from an Aircraft

To make the missile safely separate from the internal weapons bay, a wedge flow control device is mounted on the front of the bay to control the variation of flow during the separation. The numerical simulations of missile separation without and with wedge flow control device under different sizes are carried out. The flow fields of different separation processes are obtained and discussed; the aerodynamic parameters and trajectory parameters of missile of different cases are illustrated and compared. Results show that, the wedge flow control device can accelerate the missile separation and has the effect of regulating the angular motion of missile. The influence of the wedge height is stronger than that of its length on the center of gravity motion and angular motion of missile

Guided Time-optimal Model Predictive Control of a Multi-rotor

Time-optimal control of a multi-rotor remains an open problem due to the under-actuation and nonlinearity of its dynamics, which make it difficult to solve this problem directly. In this paper, the time-optimal control problem of the multi-rotor is studied. Firstly, a thrust limit optimal decomposition method is proposed, which can reasonably decompose the limited thrust into three directions according to the current state and the target state. As a result, the thrust limit constraint is decomposed as a linear constraint. With the linear constraint and decoupled dynamics, a time-optimal guidance trajectory can be obtained. Then, a cost function is defined based on the time-optimal guidance trajectory, which has a quadratic form and can be used to evaluate the time-optimal performance of the system outputs. Finally, based on the cost function, the time-optimal control problem is reformulated as an MPC (Model Predictive Control) problem. The experimental results demonstrate the feasibility and validity of the proposed methods.Comment: 6 pages, 5 figure

Non-equispaced Fourier Neural Solvers for PDEs

Solving partial differential equations is difficult. Recently proposed neural resolution-invariant models, despite their effectiveness and efficiency, usually require equispaced spatial points of data. However, sampling in spatial domain is sometimes inevitably non-equispaced in real-world systems, limiting their applicability. In this paper, we propose a Non-equispaced Fourier PDE Solver (\textsc{NFS}) with adaptive interpolation on resampled equispaced points and a variant of Fourier Neural Operators as its components. Experimental results on complex PDEs demonstrate its advantages in accuracy and efficiency. Compared with the spatially-equispaced benchmark methods, it achieves superior performance with $42.85\%$ improvements on MAE, and is able to handle non-equispaced data with a tiny loss of accuracy. Besides, to our best knowledge, \textsc{NFS} is the first ML-based method with mesh invariant inference ability to successfully model turbulent flows in non-equispaced scenarios, with a minor deviation of the error on unseen spatial points.Comment: 27 page

A Deep Spatiotemporal Attention Network for Mild Cognitive Impairment Identification

Mild cognitive impairment (MCI) is a nervous system disease, and its clinical status can be used as an early warning of Alzheimer's disease (AD). Subtle and slow changes in brain structure between patients with MCI and normal controls (NCs) deprive them of effective diagnostic methods. Therefore, the identification of MCI is a challenging task. The current functional brain network (FBN) analysis to predict human brain tissue structure is a new method emerging in recent years, which provides sensitive and effective medical biomarkers for the diagnosis of neurological diseases. Therefore, to address this challenge, we propose a novel Deep Spatiotemporal Attention Network (DSTAN) framework for MCI recognition based on brain functional networks. Specifically, we first extract spatiotemporal features between brain functional signals and FBNs by designing a spatiotemporal convolution strategy (ST-CONV). Then, on this basis, we introduce a learned attention mechanism to further capture brain nodes strongly correlated with MCI. Finally, we fuse spatiotemporal features for MCI recognition. The entire network is trained in an end-to-end fashion. Extensive experiments show that our proposed method significantly outperforms current baselines and state-of-the-art methods, with a classification accuracy of 84.21%

Effect of potassium simplex optimization medium (KSOM) and embryo screening on the production of human lactoferrin transgenic cloned dairy goats

In this study, we produced cloned transgenic dairy goat based on dairy goat ear skin fibroblast as donor cells for nuclear transfer (NT), which were modified by human lactoferrin (hLF) gene. The developmental competence of NT embryos was compared with either between different embryo culture medium, potassium simplex optimization medium (KSOM) and tissue culture medium (TCM 199), or different classification of NT embryos (48 h after fusion). First we cultured NT embryos to cleavage stage (48 h after fusion) by TCM 199 supplemented with 1 mg/ml bovine serum albumin BSA and KSOM, then used TCM 199 supplemented with 10% FBS to culture them to blastula stage. The results show that the NT embryos in KSOM (19.5%) were superior to TCM 199 (10.6%) in blastulation. In the second experiment, we found that the growth rate of NT embryos (48 h after fusion) was different, then we divided them into four groups: 2-cell, 3- to 4-cell, 5- to 8-cell and >8-cell in stereo microscope and cultured them in vitro respectively. The results show day-2 embryos at 3-4cell and 5-8cell stage (31.9 and 28.2%, P < 0.05) had higher blastocyst formation rates than those at both 2-cell (9.1%) and >8-cell (8.3%) stage, and finally three healthy cloned transgenic goat were successfully produced using 3-8 cell embryos at Day-2 (82%). Using Hoechst 33342 staining, we also found that the >8 cells embryos at Day- 2 demonstrated higher frequency of fragmentation, which may be the one cause of the low blastocyst formation rate. This study therefore demonstrates that KSOM medium could be selected as the early embryo culture medium, and 3-8 cell embryos at day-2 (48 h after fusion) may be the suitable embryos for transplantation, which could reduce the nuclei fragmentation and result in good quality blastocysts that may also enhance the efficiency of transgenic cloned dairy goats production, as well as decrease the economic loss due to embryonic mortality when embryos are transferred to synchronized recipients.Key words: Nuclear transfer, KSOM, transgenic, human lactoferrin, dairy goat

Flexural Properties of ECC-Concrete Composite Beam

Rebar corrosion-induced durability issue is a major concern for bridges. The ECC cover was employed to prevent the intrusion of the corrosive agent. This paper studied the flexural behavior of ECC-concrete composite beam. The effects of bonding at the interface and fiber mesh reinforcement on the flexural properties and cracking pattern were investigated. The strain distribution and midspan deflection were evaluated. Test results show that the bonded composite beam had a higher loading capacity. But the unbonded composite beam showed better postcrack energy absorption capacity with higher midspan deflection. The fiber mesh reinforcement could further improve the flexural properties regardless of the bonding condition. The strain at the bottom of the unbonded beam was much smaller than that of the bonded beam. The penetrated cracks were observed at the ECC layer of the bonded composited beam