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The age of information (AoI) performance analysis is essential for evaluating the information freshness in the large-scale mobile edge computing (MEC) networks. This work proposes the earliest analysis of the mean AoI (MAoI) performance of large-scale partial offloading MEC networks. Firstly, we derive and validate the closed-form expressions of MAoI by using queueing theory and stochastic geometry. Based on these expressions, we analyse the effects of computing offloading ratio (COR) and task generation rate (TGR) on the MAoI performance and compare the MAoI performance under the local computing, remote computing, and partial offloading schemes. The results show that by jointly optimising the COR and TGR, the partial offloading scheme outperforms the local and remote computing schemes in terms of the MAoI, which can be improved by up to 51% and 61%, respectively. This encourages the MEC networks to adopt the partial offloading scheme to improve the MAoI performance.

Inverse design of solid-state materials with desired properties represents a formidable challenge in materials science. Although recent generative models have demonstrated potential, their adoption has been hindered by limitations such as inefficiency, architectural constraints and restricted open-source availability. The representation of crystal structures using the SLICES (Simplified Line-Input Crystal-Encoding System) notation as a string of characters enables the use of state-of-the-art natural language processing models, such as Transformers, for crystal design. Drawing inspiration from the success of GPT models in generating coherent text, we trained a generative Transformer on the next-token prediction task to generate solid-state materials with targeted properties. We demonstrate MatterGPT's capability to generate de novo crystal structures with targeted single properties, including both lattice-insensitive (formation energy) and lattice-sensitive (band gap) properties. Furthermore, we extend MatterGPT to simultaneously target multiple properties, addressing the complex challenge of multi-objective inverse design of crystals. Our approach showcases high validity, uniqueness, and novelty in generated structures, as well as the ability to generate materials with properties beyond the training data distribution. This work represents a significant step forward in computational materials discovery, offering a powerful and open tool for designing materials with tailored properties for various applications in energy, electronics, and beyond., Comment: 20 pages, 6 figures

Encouraged by the growing availability of pre-trained 2D diffusion models, image-to-3D generation by leveraging Score Distillation Sampling (SDS) is making remarkable progress. Most existing methods combine novel-view lifting from 2D diffusion models which usually take the reference image as a condition while applying hard L2 image supervision at the reference view. Yet heavily adhering to the image is prone to corrupting the inductive knowledge of the 2D diffusion model leading to flat or distorted 3D generation frequently. In this work, we reexamine image-to-3D in a novel perspective and present Isotropic3D, an image-to-3D generation pipeline that takes only an image CLIP embedding as input. Isotropic3D allows the optimization to be isotropic w.r.t. the azimuth angle by solely resting on the SDS loss. The core of our framework lies in a two-stage diffusion model fine-tuning. Firstly, we fine-tune a text-to-3D diffusion model by substituting its text encoder with an image encoder, by which the model preliminarily acquires image-to-image capabilities. Secondly, we perform fine-tuning using our Explicit Multi-view Attention (EMA) which combines noisy multi-view images with the noise-free reference image as an explicit condition. CLIP embedding is sent to the diffusion model throughout the whole process while reference images are discarded once after fine-tuning. As a result, with a single image CLIP embedding, Isotropic3D is capable of generating multi-view mutually consistent images and also a 3D model with more symmetrical and neat content, well-proportioned geometry, rich colored texture, and less distortion compared with existing image-to-3D methods while still preserving the similarity to the reference image to a large extent. The project page is available at https://isotropic3d.github.io/. The code and models are available at https://github.com/pkunliu/Isotropic3D., Comment: Project page: https://isotropic3d.github.io/ Source code: https://github.com/pkunliu/Isotropic3D

This paper introduces a novel neural audio codec targeting high waveform sampling rates and low bitrates named APCodec, which seamlessly integrates the strengths of parametric codecs and waveform codecs. The APCodec revolutionizes the process of audio encoding and decoding by concurrently handling the amplitude and phase spectra as audio parametric characteristics like parametric codecs. It is composed of an encoder and a decoder with the modified ConvNeXt v2 network as the backbone, connected by a quantizer based on the residual vector quantization (RVQ) mechanism. The encoder compresses the audio amplitude and phase spectra in parallel, amalgamating them into a continuous latent code at a reduced temporal resolution. This code is subsequently quantized by the quantizer. Ultimately, the decoder reconstructs the audio amplitude and phase spectra in parallel, and the decoded waveform is obtained by inverse short-time Fourier transform. To ensure the fidelity of decoded audio like waveform codecs, spectral-level loss, quantization loss, and generative adversarial network (GAN) based loss are collectively employed for training the APCodec. To support low-latency streamable inference, we employ feed-forward layers and causal deconvolutional layers in APCodec, incorporating a knowledge distillation training strategy to enhance the quality of decoded audio. Experimental results confirm that our proposed APCodec can encode 48 kHz audio at bitrate of just 6 kbps, with no significant degradation in the quality of the decoded audio. At the same bitrate, our proposed APCodec also demonstrates superior decoded audio quality and faster generation speed compared to well-known codecs, such as Encodec, AudioDec and DAC., Comment: Published at IEEE/ACM Transactions on Audio, Speech, and Language Processing

*This paper is from 2018* In this paper, we try to classify moduli spaces of arrangements of $12$ lines with sextic points. We show that moduli spaces of arrangements of $12$ lines with sextic points can consist of more than two connected components. We also present defining equations of the arrangements whose moduli spaces are not irreducible taking quotients by the complex conjugation by supply some potential Zariski pairs. Through complex conjugation we take quotients and supply some potential Zariski pairs., Comment: *A paper from 2018*. arXiv admin note: text overlap with arXiv:1206.2486

Since the commencement of the first SETI observation in 2019, China's Search for Extraterrestrial Intelligence program has garnered momentum through domestic support and international collaborations. Several observations targeting exoplanets and nearby stars have been conducted with the FAST. In 2023, the introduction of the Far Neighbour Project(FNP) marks a substantial leap forward, driven by the remarkable sensitivity of the FAST telescope and some of the novel observational techniques. The FNP seeks to methodically detect technosignatures from celestial bodies, including nearby stars, exoplanetary systems, Milky Way globular clusters, and more. This paper provides an overview of the progress achieved by SETI in China and offers insights into the distinct phases comprising the FNP. Additionally, it underscores the significance of this project's advancement and its potential contributions to the field., Comment: Submitted for publication in Journal of Physics: Conference Series (HAPP 10th Anniversary Commemorative Volume). Invited talk online discussion panel on "Searching for Extraterrestrial Intelligence Over a Century" at the Centre for the History and Philosophy of Physics (HAPP) at the University of Oxford on Saturday 27th November 2021

Search for extraterrestrial intelligence (SETI) has been mainly focused on nearby stars and their planets in recent years. Barnard's star is the second closest star system to the sun and the closest star in the FAST observable sky which makes the minimum Equivalent Isotropic Radiated Power (EIRP) required for a hypothetical radio transmitter from Barnard's star to be detected by FAST telescope a mere 4.36x10^8 W. In this paper, we present the Five-hundred-meter Aperture Spherical radio Telescope (FAST) telescope as the most sensitive instrument for radio SETI observations toward nearby star systems and conduct a series of observations to Barnard's star (GJ 699). By applying the multi-beam coincidence matching (MBCM) strategy on the FAST telescope, we search for narrow-band signals (~Hz) in the frequency range of 1.05-1.45 GHz, and two orthogonal linear polarization directions are recorded. Despite finding no evidence of radio technosignatures in our series of observations, we have developed predictions regarding the hypothetical extraterrestrial intelligence (ETI) signal originating from Barnard's star. These predictions are based on the star's physical properties and our observation strategy., Comment: 10 pages, 5 figures. matches the published version. arXiv admin note: text overlap with arXiv:2208.02421

In this paper, we propose a novel method for distinguishing extraterrestrial intelligence (ETI) signals from radio frequency interference (RFI) by leveraging polarization features. We exploit the sinusoidal variation of the linearly polarized components of Stokes parameters with the parallactic angle as a characteristic signature of ETI signals, while such linearly polarized components remain relatively stable for terrestrial RFI. Typically, a minimum of 4-8 hours of observation time is required to detect these sinusoidal variations. The polarization approach in the search for extraterrestrial intelligence (SETI) also enables us to study the radio stellar bursts emitted by M-type stars as ancillary science, which is relevant to assessing the habitability of exoplanets. Compared to the frequency drift method, the polarization method effectively reduces the required observation time for signal identification while improving the signal identification process., Comment: 8 pages, 2 figures, published in The Astronomical Journal. Using polarization features as the criterion in SETI research

This paper considers the regularization continuation method and the trust-region updating strategy for the nonlinearly equality-constrained optimization problem. Namely, it uses the inverse of the regularization quasi-Newton matrix as the pre-conditioner to improve its computational efficiency in the well-posed phase, and it adopts the inverse of the regularization two-sided projection of the Hessian as the pre-conditioner to improve its robustness in the ill-conditioned phase. Since it only solves a linear system of equations at every iteration and the sequential quadratic programming (SQP) needs to solve a quadratic programming subproblem at every iteration, it is faster than SQP. Numerical results also show that it is more robust and faster than SQP (the built-in subroutine fmincon.m of the MATLAB2020a environment and the subroutine SNOPT executed in GAMS v28.2 (2019) environment). The computational time of the new method is about one third of that of fmincon.m for the large-scale problem. Finally, the global convergence analysis of the new method is also given., Comment: arXiv admin note: substantial text overlap with arXiv:2106.01122

The search for extraterrestrial intelligence (SETI) is to search for technosignatures associated with extraterrestrial life, such as engineered radio signals. In this paper, we apply the multibeam coincidence matching (MBCM) strategy, and propose a new search mode based on the MBCM which we call MBCM blind search mode. In our recent targeted SETI research, 33 exoplanet systems are observed by the Five-hundred-meter Aperture Spherical radio Telescope (FAST). With this blind search mode, we search for narrowband drifting signals across $1.05-1.45$ GHz in two orthogonal linear polarization directions separately. There are two special signals, one of which can only be detected by the blind search mode while the other can be found by both blind and targeted search modes. This result reveals huge advantages of the new blind search mode. However, we eliminate the possibility of the special signals being ETI signals based on much evidence, such as the polarization, drift, frequency and beam coverage characteristics. Our observations achieve an unprecedented sensitivity and our work provides a deeper understanding to the polarization analysis of extraterrestrial signals., Comment: 15 pages, 1 table, 7 figures. Matches AJ published version. Based on MBCM strategy by Zhen-Zhao Tao et al (2022 AJ 164 160), we propose a new search mode: MBCM blind search mode for FAST SETI observations

In this article, we consider the residual regularization path-following method with the trust-region updating strategy for the linear complementarity problem. This time-stepping selection based on the trust-region updating strategy overcomes the shortcoming of the line search method, which consumes the unnecessary trial steps in the transient-state phase. In order to improve the robustness of the path-following method, we use the residual regularization parameter to replace the traditional complementarity regularization parameter. Moreover, we prove the global convergence of the new method under the standard assumptions without the traditional assumption condition of the priority to feasibility over complementarity. Numerical results show that the new method is robust and efficient for the linear complementarity problem, especially for the dense cases. And it is more robust and faster than some state-of-the-art solvers such as the built-in subroutines PATH and MILES of the GAMS v28.2 (2019) environment. The computational time of the new method is about 1/3 to 1/10 of that of PATH for the dense linear complementarity problem.