Perturbing Masses: A Study of Centered Co-Circular Configurations in Power-Law n-Body Problems

This research investigates centered co-circular central configurations in the general power-law potential $n$-body problem. Firstly, there are no such configurations when all masses are equal, except for two; secondly, unless all masses are equal, no such configurations exist when masses can be divided into two sets of equal masses. We adapt Wang's criterion and incorporate insights on cyclic quadrilaterals, alongside mathematical induction.Comment: 13 pages, 4 figure

Spiking NeRF: Making Bio-inspired Neural Networks See through the Real World

Spiking neuron networks (SNNs) have been thriving on numerous tasks to leverage their promising energy efficiency and exploit their potentialities as biologically plausible intelligence. Meanwhile, the Neural Radiance Fields (NeRF) render high-quality 3D scenes with massive energy consumption, and few works delve into the energy-saving solution with a bio-inspired approach. In this paper, we propose spiking NeRF (SpikingNeRF), which aligns the radiance ray with the temporal dimension of SNN, to naturally accommodate the SNN to the reconstruction of Radiance Fields. Thus, the computation turns into a spike-based, multiplication-free manner, reducing the energy consumption. In SpikingNeRF, each sampled point on the ray is matched onto a particular time step, and represented in a hybrid manner where the voxel grids are maintained as well. Based on the voxel grids, sampled points are determined whether to be masked for better training and inference. However, this operation also incurs irregular temporal length. We propose the temporal condensing-and-padding (TCP) strategy to tackle the masked samples to maintain regular temporal length, i.e., regular tensors, for hardware-friendly computation. Extensive experiments on a variety of datasets demonstrate that our method reduces the $76.74\%$ energy consumption on average and obtains comparable synthesis quality with the ANN baseline

INT: Towards Infinite-frames 3D Detection with An Efficient Framework

It is natural to construct a multi-frame instead of a single-frame 3D detector for a continuous-time stream. Although increasing the number of frames might improve performance, previous multi-frame studies only used very limited frames to build their systems due to the dramatically increased computational and memory cost. To address these issues, we propose a novel on-stream training and prediction framework that, in theory, can employ an infinite number of frames while keeping the same amount of computation as a single-frame detector. This infinite framework (INT), which can be used with most existing detectors, is utilized, for example, on the popular CenterPoint, with significant latency reductions and performance improvements. We've also conducted extensive experiments on two large-scale datasets, nuScenes and Waymo Open Dataset, to demonstrate the scheme's effectiveness and efficiency. By employing INT on CenterPoint, we can get around 7% (Waymo) and 15% (nuScenes) performance boost with only 2~4ms latency overhead, and currently SOTA on the Waymo 3D Detection leaderboard.Comment: accepted by ECCV202

SOTOPIA: Interactive Evaluation for Social Intelligence in Language Agents

Humans are social beings; we pursue social goals in our daily interactions, which is a crucial aspect of social intelligence. Yet, AI systems' abilities in this realm remain elusive. We present SOTOPIA, an open-ended environment to simulate complex social interactions between artificial agents and evaluate their social intelligence. In our environment, agents role-play and interact under a wide variety of scenarios; they coordinate, collaborate, exchange, and compete with each other to achieve complex social goals. We simulate the role-play interaction between LLM-based agents and humans within this task space and evaluate their performance with a holistic evaluation framework called SOTOPIA-Eval. With SOTOPIA, we find significant differences between these models in terms of their social intelligence, and we identify a subset of SOTOPIA scenarios, SOTOPIA-hard, that is generally challenging for all models. We find that on this subset, GPT-4 achieves a significantly lower goal completion rate than humans and struggles to exhibit social commonsense reasoning and strategic communication skills. These findings demonstrate SOTOPIA's promise as a general platform for research on evaluating and improving social intelligence in artificial agents.Comment: Preprint, 43 pages. The first two authors contribute equall

Auxetic interpenetrating composites: A new approach to non-porous materials with a negative or zero Poisson's ratio

In this research, the Poisson’s ratio of three different types of almost isotropic interpenetrating composites are designed to be either positive, or negative, or zero. As they are strengthened by a self-connected fibre-network and do not contain any pore in their structure, they all are stiffer than the conventional particle composites. In addition, structural hierarchy is also demonstrated to be able to significantly enhance the auxetic behaviour for the three types of interpenetrating composites. Thus, these composites could be used not only as functional materials, but also as structural materials in engineering applications

The near-isotropic elastic properties of interpenetrating composites reinforced by regular fibre-networks

It is highly demanding and challenging to maximise the stiffness of the interpenetrating phase composites (IPCs) while still keeping their isotropy. In this paper, the elastic properties of IPCs reinforced by three different types of regular lattice fibre networks are investigated by computer simulation and analytical methods. The numerical results indicate that the larger the difference between the Poisson’s ratios and the smaller the difference between the Young’s moduli of the constituent materials, the larger the Young’s moduli of these IPCs are. It is also found that structural hierarchy can enhance the stiffness of these IPCs by 30%. In addition, the three types of IPCs have Zener anisotropy factors in the range of in most cases, could have an almost isotropic Young’s modulus two times larger than the Voigt limit, and a Poisson’s ratio with a positive or negative or zero value. Moreover, they are easy to manufacture, their Young’s moduli are in general 1.0–3.0 times those of the conventional particle or short fibre reinforced composites and other types of IPCs including those reinforced by the triply periodic minimal surface (TPMS) shells, and the type of IPCs with the largest Young’s modulus has been identified

Regulatory controls of duplicated gene expression during fiber development in allotetraploid cotton.

Polyploidy complicates transcriptional regulation and increases phenotypic diversity in organisms. The dynamics of genetic regulation of gene expression between coresident subgenomes in polyploids remains to be understood. Here we document the genetic regulation of fiber development in allotetraploid cotton Gossypium hirsutum by sequencing 376 genomes and 2,215 time-series transcriptomes. We characterize 1,258 genes comprising 36 genetic modules that control staged fiber development and uncover genetic components governing their partitioned expression relative to subgenomic duplicated genes (homoeologs). Only about 30% of fiber quality-related homoeologs show phenotypically favorable allele aggregation in cultivars, highlighting the potential for subgenome additivity in fiber improvement. We envision a genome-enabled breeding strategy, with particular attention to 48 favorable alleles related to fiber phenotypes that have been subjected to purifying selection during domestication. Our work delineates the dynamics of gene regulation during fiber development and highlights the potential of subgenomic coordination underpinning phenotypes in polyploid plants. [Abstract copyright: © 2023. The Author(s).

Data Release of the AST3-2 Automatic Survey from Dome A, Antarctica

AST3-2 is the second of the three Antarctic Survey Telescopes, aimed at wide-field time-domain optical astronomy. It is located at Dome A, Antarctica, which is by many measures the best optical astronomy site on the Earth's surface. Here we present the data from the AST3-2 automatic survey in 2016 and the photometry results. The median 5$\sigma$ limiting magnitude in $i$-band is 17.8 mag and the light curve precision is 4 mmag for bright stars. The data release includes photometry for over 7~million stars, from which over 3,500 variable stars were detected, with 70 of them newly discovered. We classify these new variables into different types by combining their light curve features with stellar properties from surveys such as StarHorse.Comment: 16 pages, 20 figures, accepted for publication in MNRA