RadOcc: Learning Cross-Modality Occupancy Knowledge through Rendering Assisted Distillation

3D occupancy prediction is an emerging task that aims to estimate the occupancy states and semantics of 3D scenes using multi-view images. However, image-based scene perception encounters significant challenges in achieving accurate prediction due to the absence of geometric priors. In this paper, we address this issue by exploring cross-modal knowledge distillation in this task, i.e., we leverage a stronger multi-modal model to guide the visual model during training. In practice, we observe that directly applying features or logits alignment, proposed and widely used in bird's-eyeview (BEV) perception, does not yield satisfactory results. To overcome this problem, we introduce RadOcc, a Rendering assisted distillation paradigm for 3D Occupancy prediction. By employing differentiable volume rendering, we generate depth and semantic maps in perspective views and propose two novel consistency criteria between the rendered outputs of teacher and student models. Specifically, the depth consistency loss aligns the termination distributions of the rendered rays, while the semantic consistency loss mimics the intra-segment similarity guided by vision foundation models (VLMs). Experimental results on the nuScenes dataset demonstrate the effectiveness of our proposed method in improving various 3D occupancy prediction approaches, e.g., our proposed methodology enhances our baseline by 2.2% in the metric of mIoU and achieves 50% in Occ3D benchmark.Comment: Accepted by AAAI 202

GSmoothFace: Generalized Smooth Talking Face Generation via Fine Grained 3D Face Guidance

Although existing speech-driven talking face generation methods achieve significant progress, they are far from real-world application due to the avatar-specific training demand and unstable lip movements. To address the above issues, we propose the GSmoothFace, a novel two-stage generalized talking face generation model guided by a fine-grained 3d face model, which can synthesize smooth lip dynamics while preserving the speaker's identity. Our proposed GSmoothFace model mainly consists of the Audio to Expression Prediction (A2EP) module and the Target Adaptive Face Translation (TAFT) module. Specifically, we first develop the A2EP module to predict expression parameters synchronized with the driven speech. It uses a transformer to capture the long-term audio context and learns the parameters from the fine-grained 3D facial vertices, resulting in accurate and smooth lip-synchronization performance. Afterward, the well-designed TAFT module, empowered by Morphology Augmented Face Blending (MAFB), takes the predicted expression parameters and target video as inputs to modify the facial region of the target video without distorting the background content. The TAFT effectively exploits the identity appearance and background context in the target video, which makes it possible to generalize to different speakers without retraining. Both quantitative and qualitative experiments confirm the superiority of our method in terms of realism, lip synchronization, and visual quality. See the project page for code, data, and request pre-trained models: https://zhanghm1995.github.io/GSmoothFace

Perinatal Exposure to Low-Dose Bisphenol A Impairs Spatial Learning and Memory in Male Rats

Bisphenol A (BPA) is an estrogenic endocrine disruptor used for producing polycarbonate plastics and epoxy resins. This study investigated the effects of perinatal BPA exposure on learning and memory, general activity, and emotionality in male Sprague Dawley rats using a battery of behavioral tests, including an appetite-motivated maze test (MAZE test) used to assess spatial learning and memory. Mother rats were orally administered BPA (50 or 500 μg・kg-1/day) or vehicle (1 ml・kg-1/day) from gestational day 10 to postnatal day 14. In the MAZE test, compared to the offspring of vehicle-treated rat mothers, male offspring of mothers exposed to 50 μg・kg-1/day of BPA, but not those of mothers exposed to 500 μg・kg-1/day of BPA, needed significantly more time to reach the reward. Although male offspring of mothers exposed to 50 μg・kg-1/day of BPA showed an increase in a behavioral measure of wariness after repeated testing in the open-field test, no significant effects were observed in locomotor activities. No significant differences were observed in any other behavioral test including the elevated plus-maze test. The present study suggests that perinatal exposure to low-dose BPA specifically and non-monotonically impairs spatial learning and memory in male offspring rats

Prehistoric trans-continental cultural exchange in the Hexi Corridor, northwest China

We report dozens of direct radiocarbon dates on charred grains from 22 archaeological sites of the Neolithic and Bronze Ages in the Hexi Corridor, northwest China, a key region for trans-Eurasian exchange in prehistoric and historical times. These charred grains include remains of wheat and barley domesticated in southwest Asia and broomcorn and foxtail millet which originated from north China. Together with previously published radiocarbon dates, we consider these newly obtained radiocarbon results in the context of material cultures associated with them, to explore an episode of trans-continental cultural exchange foci at the Hexi Corridor. Our results show that millet cultivators who used painted potteries from the western Loess Plateau first settled the Hexi Corridor around 4800 BP. Communities who cultivated wheat and barley moved into this region from the west around 4000 BP, bringing with them technologies and materials not seen in central China before, including bronze metallurgy, mud bricks, and mace heads. This was part of the east-west contact which became evident in the Hexi Corridor since the late fifth millennium BP, and continued over the subsequent two millennia, and predated the formation of the overland Silk Road in the Han Dynasty (202 BC-AD 220)

Measurements of the Cross Section for e+e- -> hadrons at Center-of-Mass Energies from 2 to 5 GeV

We report values of $R = \sigma(e^+e^-\to {hadrons})/\sigma(e^+e^-\to\mu^+\mu^-)$ for 85 center-of-mass energies between 2 and 5 GeV measured with the upgraded Beijing Spectrometer at the Beijing Electron-Positron Collider.Comment: 5 pages, 3 figure

Electroplastic Effects on the Mechanical Responses and Deformation Mechanisms of AZ31 Mg Foils

Electrical-assisted (EA) forming technology is a promising technology to improve the formability of hard-deformable materials, such as Mg alloys. Herein, EA micro tensile tests and various microstructure characterizations were conducted to study the electroplastic effect (EPE) and size effect on the mechanical responses, deformation mechanisms, and fracture characteristics of AZ31 Mg foils. With the assistance of electric currents, the ductility of the foils was significantly improved, the size effects caused by grain size and sample thickness were weakened, and the sigmoidal shape of the flow stress curves during the early deformation stage became less obvious. The EBSD characterization results showed that the shape change of the flow stress curves was due to the EPE suppressing the activation of extension twinning at the early deformation stage, especially for the coarse grain samples. The suppression of extension twinning resulted in a quick increase in flow stress due to the dislocation-dominant work hardening, and the increased flow stress eventually promoted extensive deformation twins at large deformation. Thus, as the sample strained to 10% tensile deformation, the EA-tested samples showed a larger volume fraction of deformation twins than the non-EA samples. The reference orientation deviation analysis verified that the deformation twins in the EA samples were formed in the large deformation stage. Combined with the fractography, the EPE also improved the ductility by suppressing the expansion of cleavage surfaces

EasiND: Neighbor Discovery in Duty-Cycled Asynchronous Multichannel Mobile WSNs

Neighbor discovery is one of the first steps to establish communication links between sensor nodes; thus it becomes a fundamental building block for wireless sensor networks (WSNs). Traditional neighbor discovery protocols mainly focus on static wireless networks or networks where all nodes operate on the same frequency. However, the proliferation of mobile devices and multichannel communications post new challenges to neighbor discovery problem. In this paper, we present a neighbor discovery protocol named EasiND for asynchronous duty-cycled multichannel mobile WSNs. First, we propose a neighbor discovery system based on quorum system, which can bound the discovery latency in multichannel scenarios with low power consumptions. Second, we design an optimal asynchronous neighbor discovery system for multichannel mobile WSNs based on cyclic difference set. It is optimal in the sense that it minimizes the power consumption with bounded discovery latency under desired duty cycles. Finally, we validate the performance of EasiND through both theoretical analysis and test-bed evaluations. EasiND provides a 33.3% reduction in power-latency product in theory compared to U-Connect. Meanwhile, test-bed evaluation results show that EasiND decreases average discovery latency by up to 86% compared to U-Connect and achieves at least 93.5% average fraction of discoveries in a predefined time limitation under various network conditions