1,4-Bis(dimethyl­silyl)-2,5-diphenyl­benzene

The mol­ecule of the title compound, C22H26Si2, is centrosymmetric. The dihedral angle between the central benzene ring and its phenyl substituents is 67.7 (2)°. The crystal packing is stabilized by van der Waals forces

Joint Source-Relay Design for Full-Duplex MIMO AF Relay Systems

The performance of full-duplex (FD) relay systems can be greatly impacted by the self-interference (SI) at relays. By exploiting multiple antennas, the spectral efficiency of FD relay systems can be enhanced through spatial SI mitigation. This paper studies joint source transmit beamforming and relay processing to achieve rate maximization for FD multiple-input-multiple-output (MIMO) amplify-and-forward (AF) relay systems with consideration of relay processing delay. The problem is difficult to solve mainly due to the SI constraint induced by the relay processing delay. In this paper, we first present a sufficient condition under which the relay amplification matrix has rank-one structure. Then, for the case of rank-one amplification matrix, the rate maximization problem is equivalently simplified into an unconstrained problem that can be locally solved using the gradient ascent method. Next, we propose a penalty-based algorithmic framework, named P-BSUM, for a class of constrained optimization problems that have difficult equality constraints in addition to some convex constraints. By rewriting the rate maximization problem with a set of auxiliary variables, we apply the P-BSUM algorithm to the rate maximization problem in the general case. Finally, numerical results validate the efficiency of the proposed algorithms and show that the joint source-relay design approach under the rankone assumption could be strictly suboptimal as compared to the P-BSUM-based joint source-relay design approach

Moby: Empowering 2D Models for Efficient Point Cloud Analytics on the Edge

3D object detection plays a pivotal role in many applications, most notably autonomous driving and robotics. These applications are commonly deployed on edge devices to promptly interact with the environment, and often require near real-time response. With limited computation power, it is challenging to execute 3D detection on the edge using highly complex neural networks. Common approaches such as offloading to the cloud induce significant latency overheads due to the large amount of point cloud data during transmission. To resolve the tension between wimpy edge devices and compute-intensive inference workloads, we explore the possibility of empowering fast 2D detection to extrapolate 3D bounding boxes. To this end, we present Moby, a novel system that demonstrates the feasibility and potential of our approach. We design a transformation pipeline for Moby that generates 3D bounding boxes efficiently and accurately based on 2D detection results without running 3D detectors. Further, we devise a frame offloading scheduler that decides when to launch the 3D detector judiciously in the cloud to avoid the errors from accumulating. Extensive evaluations on NVIDIA Jetson TX2 with real-world autonomous driving datasets demonstrate that Moby offers up to 91.9% latency improvement with modest accuracy loss over state of the art.Comment: Accepted to ACM International Conference on Multimedia (MM) 202

Phenomenological study on the significance of the scalar potential and Lamb shift

We indicated in our previous work that for QED the contributions of the scalar potential which appears at the loop level is much smaller than that of the vector potential and in fact negligible. But the situation may be different for QCD, one reason is that the loop effects are more significant because $\alpha_s$ is much larger than $\alpha$, and secondly the non-perturbative QCD effects may induce the scalar potential. In this work, we phenomenologically study the contribution of the scalar potential to the spectra of charmonia. Taking into account both vector and scalar potentials, by fitting the well measured charmonia spectra, we re-fix the relevant parameters and test them by calculating other states of the charmonia family. We also consider the role of the Lamb shift and present the numerical results with and without involving the Lamb shift

SafeCrowdNav: safety evaluation of robot crowd navigation in complex scenes

Navigating safely and efficiently in dense crowds remains a challenging problem for mobile robots. The interaction mechanisms involved in collision avoidance require robots to exhibit active and foresighted behaviors while understanding the crowd dynamics. Deep reinforcement learning methods have shown superior performance compared to model-based approaches. However, existing methods lack an intuitive and quantitative safety evaluation for agents, and they may potentially trap agents in local optima during training, hindering their ability to learn optimal strategies. In addition, sparse reward problems further compound these limitations. To address these challenges, we propose SafeCrowdNav, a comprehensive crowd navigation algorithm that emphasizes obstacle avoidance in complex environments. Our approach incorporates a safety evaluation function to quantitatively assess the current safety score and an intrinsic exploration reward to balance exploration and exploitation based on scene constraints. By combining prioritized experience replay and hindsight experience replay techniques, our model effectively learns the optimal navigation policy in crowded environments. Experimental outcomes reveal that our approach enables robots to improve crowd comprehension during navigation, resulting in reduced collision probabilities and shorter navigation times compared to state-of-the-art algorithms. Our code is available at https://github.com/Janet-xujing-1216/SafeCrowdNav