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The Extended Quantum Molecular Dynamics (EQMD) model is one of the few QMD-like transport approaches that can describe the $\alpha$-clustering structure with efficient computational power. However, compared to most QMD-like models, the choice of equation of state (EOS) for nuclear matter is very limited. In this work, a Monte Carlo integral method is employed to calculate the density integration with non-integer exponent. We demonstrate the superiority of our approach by studying the isovector giant dipole resonance (IVGDR). This improvement will be beneficial for the EQMD model to study more valuable effects for heavy ion collisions in the near future., Comment: 10 pages, 8 figures

The extended quantum molecular dynamics (EQMD) model is one of the few quantum molecular dynamics (QMD)-like transport approaches that can be used to study the effective clustering structure as well as heavily deformed nuclei in both ground state nuclei and nuclear reactions. However, there are only two parameter sets that lead to hard incompressibility for long times. The aim of the present work is to obtain a soft equation of state (EoS) in the EQMD model. In this context, we take the isoscalar giant monopole resonance (ISGMR), which is sensitive to the EoS, as an example to check our work. By introducing a kind of standard Skyrme energy density functional with different parameter sets, such as SkP, SkT1, and SKXce, whose incompressibility value ranges from 200 to 268 MeV, the ISGMR of $^{208}$Pb and other nuclei are studied. When the SkP parameter sets are adopted, our new soft interaction in the EQMD model gives reasonable agreement with the experimental data in the heavy ion regime., Comment: 10 pages, 8 figures

Single-view clothed human reconstruction holds a central position in virtual reality applications, especially in contexts involving intricate human motions. It presents notable challenges in achieving realistic clothing deformation. Current methodologies often overlook the influence of motion on surface deformation, resulting in surfaces lacking the constraints imposed by global motion. To overcome these limitations, we introduce an innovative framework, Motion-Based 3D Clo}thed Humans Synthesis (MOSS), which employs kinematic information to achieve motion-aware Gaussian split on the human surface. Our framework consists of two modules: Kinematic Gaussian Locating Splatting (KGAS) and Surface Deformation Detector (UID). KGAS incorporates matrix-Fisher distribution to propagate global motion across the body surface. The density and rotation factors of this distribution explicitly control the Gaussians, thereby enhancing the realism of the reconstructed surface. Additionally, to address local occlusions in single-view, based on KGAS, UID identifies significant surfaces, and geometric reconstruction is performed to compensate for these deformations. Experimental results demonstrate that MOSS achieves state-of-the-art visual quality in 3D clothed human synthesis from monocular videos. Notably, we improve the Human NeRF and the Gaussian Splatting by 33.94% and 16.75% in LPIPS* respectively. Codes are available at https://wanghongsheng01.github.io/MOSS/., Comment: arXiv admin note: text overlap with arXiv:1710.03746 by other authors

The future interconnect links in intra- and inter-chip require the photodetector with high bandwidth, ultra-wide waveband, compact footprint, low-cost, and compatible integration process with silicon complementary metal-oxide-semiconductor (CMOS) technology. Here, we demonstrate a CMOS-compatible carbon nanotube (CNT) photodetector that exhibits high responsivity, high bandwidth and broad spectral operation over all optical telecommunication band based on high-purity CNT arrays. The ultrafast CNT photodetector demonstrates the 100 Gbit/s Nyquist-shaped on-off-keying (OOK) signal transmission, which can address the demand for high-speed optical interconnects in and between data centers. Furthermore, the photodetector exhibits a bandwidth over 60 GHz by scaling down the active area to 20 {\mu}m2. As the CNT photodetectors are fabricated by doping-free process, it also provides a cost-effective solution to integrate CNT photonic devices with CNT-based CMOS integrated circuits. Our work paves a way for future CNT-based high-speed optical interconnects and optoelectronic integrated circuits (OEICs)., Comment: 29 pages

Deep neural networks (DNNs) are vulnerable to adversarial attacks. In particular, object detectors may be attacked by applying a particular adversarial patch to the image. However, because the patch shrinks during preprocessing, most existing approaches that employ adversarial patches to attack object detectors would diminish the attack success rate on small and medium targets. This paper proposes a Frequency Module(FRAN), a frequency-domain attention module for guiding patch generation. This is the first study to introduce frequency domain attention to optimize the attack capabilities of adversarial patches. Our method increases the attack success rates of small and medium targets by 4.18% and 3.89%, respectively, over the state-of-the-art attack method for fooling the human detector while assaulting YOLOv3 without reducing the attack success rate of big targets., Comment: 10pages, 4 figures

In the field of Astrobiology, the precise location, prevalence and age of potential extraterrestrial intelligence (ETI) have not been explicitly explored. Here, we address these inquiries using an empirical galactic simulation model to analyze the spatial-temporal variations and the prevalence of potential ETI within the Galaxy. This model estimates the occurrence of ETI, providing guidance on where to look for intelligent life in the Search for ETI (SETI) with a set of criteria, including well-established astrophysical properties of the Milky Way. Further, typically overlooked factors such as the process of abiogenesis, different evolutionary timescales and potential self-annihilation are incorporated to explore the growth propensity of ETI. We examine three major parameters: 1) the likelihood rate of abiogenesis ({\lambda}A); 2) evolutionary timescales (Tevo); and 3) probability of self-annihilation of complex life (Pann). We found Pann to be the most influential parameter determining the quantity and age of galactic intelligent life. Our model simulation also identified a peak location for ETI at an annular region approximately 4 kpc from the Galactic center around 8 billion years (Gyrs), with complex life decreasing temporally and spatially from the peak point, asserting a high likelihood of intelligent life in the galactic inner disk. The simulated age distributions also suggest that most of the intelligent life in our galaxy are young, thus making observation or detection difficult.