Diffusion metamaterials for plasma transport

Plasma technology has found widespread applications in numerous domains, yet the techniques to manipulate plasma transport predominantly rely on magnetic control. In this review, we present a streamlined diffusion-migration method to characterize plasma transport. Based on this framework, the viability of the transformation theory for plasma transport is demonstrated. Highlighted within are three model devices designed to cloak, concentrate, and rotate plasmas without significantly altering the density profile of background plasmas. Additionally, insights regarding potential implications for novel physics are discussed. This review aims to contribute to advancements in plasma technology, especially in sectors like medicine and chemistry.Comment: For more details, see Chapter 15 of the forthcoming Springer monograph entitled "Diffusionics: Diffusion Process Controlled by Diffusion Metamaterials.

Bi-level Actor-Critic for Multi-agent Coordination

Coordination is one of the essential problems in multi-agent systems. Typically multi-agent reinforcement learning (MARL) methods treat agents equally and the goal is to solve the Markov game to an arbitrary Nash equilibrium (NE) when multiple equilibra exist, thus lacking a solution for NE selection. In this paper, we treat agents \emph{unequally} and consider Stackelberg equilibrium as a potentially better convergence point than Nash equilibrium in terms of Pareto superiority, especially in cooperative environments. Under Markov games, we formally define the bi-level reinforcement learning problem in finding Stackelberg equilibrium. We propose a novel bi-level actor-critic learning method that allows agents to have different knowledge base (thus intelligent), while their actions still can be executed simultaneously and distributedly. The convergence proof is given, while the resulting learning algorithm is tested against the state of the arts. We found that the proposed bi-level actor-critic algorithm successfully converged to the Stackelberg equilibria in matrix games and find an asymmetric solution in a highway merge environment

Probing the dipole portal to heavy neutral leptons via meson decays at the high-luminosity LHC

We consider the dipole portal to sterile neutrinos, also called heavy neutral leptons (HNLs). The dipole interaction with the photon leads to HNL production in meson decays, as well as triggers the HNL decay into an active neutrino and a photon. HNLs with masses of order of 0.01-1 GeV are naturally long-lived if the dipole coupling is sufficiently small. We perform Monte-Carlo simulations and derive the sensitivities of the proposed FASER2 and FACET long-lived particle experiments to HNLs produced via the dipole operator in meson decays at the high-luminosity LHC. Our findings show that these future detectors will be complementary to each other, as well as to existing experiments, and will be able to probe new parts of the parameter space, especially in the case of the dipole operator coupled to the tau neutrino.Comment: 16 pages+refs, 5 figures, 2 table

ProgressLabeller: Visual Data Stream Annotation for Training Object-Centric 3D Perception

Visual perception tasks often require vast amounts of labelled data, including 3D poses and image space segmentation masks. The process of creating such training data sets can prove difficult or time-intensive to scale up to efficacy for general use. Consider the task of pose estimation for rigid objects. Deep neural network based approaches have shown good performance when trained on large, public datasets. However, adapting these networks for other novel objects, or fine-tuning existing models for different environments, requires significant time investment to generate newly labelled instances. Towards this end, we propose ProgressLabeller as a method for more efficiently generating large amounts of 6D pose training data from color images sequences for custom scenes in a scalable manner. ProgressLabeller is intended to also support transparent or translucent objects, for which the previous methods based on depth dense reconstruction will fail. We demonstrate the effectiveness of ProgressLabeller by rapidly create a dataset of over 1M samples with which we fine-tune a state-of-the-art pose estimation network in order to markedly improve the downstream robotic grasp success rates. ProgressLabeller is open-source at https://github.com/huijieZH/ProgressLabeller.Comment: IROS 2022 accepted paper; project page: https://progress.eecs.umich.edu/projects/progress-labeller

TransNet: Transparent Object Manipulation Through Category-Level Pose Estimation

Transparent objects present multiple distinct challenges to visual perception systems. First, their lack of distinguishing visual features makes transparent objects harder to detect and localize than opaque objects. Even humans find certain transparent surfaces with little specular reflection or refraction, like glass doors, difficult to perceive. A second challenge is that depth sensors typically used for opaque object perception cannot obtain accurate depth measurements on transparent surfaces due to their unique reflective properties. Stemming from these challenges, we observe that transparent object instances within the same category, such as cups, look more similar to each other than to ordinary opaque objects of that same category. Given this observation, the present paper explores the possibility of category-level transparent object pose estimation rather than instance-level pose estimation. We propose \textit{\textbf{TransNet}}, a two-stage pipeline that estimates category-level transparent object pose using localized depth completion and surface normal estimation. TransNet is evaluated in terms of pose estimation accuracy on a large-scale transparent object dataset and compared to a state-of-the-art category-level pose estimation approach. Results from this comparison demonstrate that TransNet achieves improved pose estimation accuracy on transparent objects. Moreover, we use TransNet to build an autonomous transparent object manipulation system for robotic pick-and-place and pouring tasks

Phenomena of electrostatic perturbations before strong earthquakes (2005–2010) observed on DEMETER

International audienceDuring the DEMETER operating period in 2004– 2010, many strong earthquakes took place in the world. 69 strong earthquakes with a magnitude above 7.0 during January 2005 to February 2010 were collected and analysed. The orbits, recorded in local nighttime by satellite, were chosen by a distance of 2000 km to the epicentres during the 9 days around these earthquakes, with 7 days before and 1 day after. The anomaly is defined when the disturbances in the electric field PSD increased to at least 1 order of magnitude relative to the normal median level about 10 −2 µV 2 /m 2 /Hz at 19.5–250 Hz frequency band, and the starting point of perturbations not exceeding 10 • relative to the epicentral latitude. Among the 69 earthquakes, it is shown that electrostatic perturbations were detected at ULF-ultra low frequency and ELF-extremely low frequency band before the 32 earthquakes, nearly 46 %. Furthermore, we extended the searching scale of these perturbations to the globe, and it can be found that before some earthquakes, the electrostatic anomalies were distributed in a much larger area a few days before, and then they concentrated to the closest orbit when the earthquake would happen one day or a few hours later, which reflects the spatial developing feature during the seismic preparation process. The results in this paper contribute to a better description of the electromagnetic (EM) disturbances at an altitude of 660– 710 km in the ionosphere that can help towards a further understanding of the lithosphere-atmosphere-ionosphere (LAI) coupling mechanism

Learning to Select Cuts for Efficient Mixed-Integer Programming

Cutting plane methods play a significant role in modern solvers for tackling mixed-integer programming (MIP) problems. Proper selection of cuts would remove infeasible solutions in the early stage, thus largely reducing the computational burden without hurting the solution accuracy. However, the major cut selection approaches heavily rely on heuristics, which strongly depend on the specific problem at hand and thus limit their generalization capability. In this paper, we propose a data-driven and generalizable cut selection approach, named Cut Ranking, in the settings of multiple instance learning. To measure the quality of the candidate cuts, a scoring function, which takes the instance-specific cut features as inputs, is trained and applied in cut ranking and selection. In order to evaluate our method, we conduct extensive experiments on both synthetic datasets and real-world datasets. Compared with commonly used heuristics for cut selection, the learning-based policy has shown to be more effective, and is capable of generalizing over multiple problems with different properties. Cut Ranking has been deployed in an industrial solver for large-scale MIPs. In the online A/B testing of the product planning problems with more than $10^7$ variables and constraints daily, Cut Ranking has achieved the average speedup ratio of 12.42% over the production solver without any accuracy loss of solution.Comment: Paper accepted at Pattern Recognition journa

Biological Monitoring of Cadmium Exposed Workers in a Nickel-Cadmium Battery Factory in China

Abstract: Biological Monitoring of Cadmium Exposed Workers in a Nickel-Cadmium Battery Factory in China: Guicheng ZHANG, et al. School of Public Health, Curtin University of Technology-A cross-sectional study of renal damage in workers from a Chinese Ni-Cd battery factory is reported in this paper. The present exposure of surveyed workers to Cd may be likened to that of factories in developed countries prior to the 1950s. The results show urinary cadmium did not increase significantly with the years of exposure in aged workers exposed to cadmium. In these occupationally exposed workers urinary cadmium levels of 3 to 60 µg/g creatinine relate to between 15% and 20% of the workers having B 2 -MG proteinura, and blood cadmium levels less than 5 µg/l relate to more than 10% of the workers having B 2 -MG proteinura. The results suggest that a urinary cadmium concentration of 5 µg/g cr or a blood cadmium concentration of 5 µg/ l would not be a safe level. (J Occup Health 2002; 44: 15-21

Controlling mass and energy diffusion with metamaterials

Diffusion driven by temperature or concentration gradients is a fundamental mechanism of energy and mass transport, which inherently differs from wave propagation in both physical foundations and application prospects. Compared with conventional schemes, metamaterials provide an unprecedented potential for governing diffusion processes, based on emerging theories like the transformation and the scattering cancellation theory, which enormously expanded the original concepts and suggest innovative metamaterial-based devices. We hereby use the term ``diffusionics'' to generalize these remarkable achievements in various energy (e.g., heat) and mass (e.g., particles and plasmas) diffusion systems. For clarity, we categorize the numerous studies appeared during the last decade by diffusion field (i.e., heat, particles, and plasmas) and discuss them from three different perspectives: the theoretical perspective, to detail how the transformation principle is applied to each diffusion field; the application perspective, to introduce various intriguing metamaterial-based devices, such as cloaks and radiative coolers; and the physics perspective, to connect with concepts of recent concern, such as non-Hermitian topology, nonreciprocal transport, and spatiotemporal modulation. We also discuss the possibility of controlling diffusion processes beyond metamaterials. Finally, we point out several future directions for diffusion metamaterial research, including the integration with artificial intelligence and topology concepts.Comment: This review article has been accepted for publication in Rev. Mod. Phy

Preparation and electrochemical properties of pomegranate-shaped Fe₂O₃/C anodes for li-ion batteries

Due to the severe volume expansion and poor cycle stability, transition metal oxide anode is still not meeting the commercial utilization. We herein demonstrate the synthetic method of core-shell pomegranate-shaped Fe2O3/C nano-composite via one-step hydrothermal process for the first time. The electrochemical performances were measured as anode material for Li-ion batteries. It exhibits excellent cycling performance, which sustains 705 mAh g-1 reversible capacities after 100 cycles at 100 mA g-1. The anodes also showed good rate stability with discharge capacities of 480 mAh g-1 when cycling at a rate of 2000 mA g-1. The excellent Li storage properties can be attributed to the unique core-shell pomegranate structure, which can not only ensure good electrical conductivity for active Fe2O3, but also accommodate huge volume change during cycles as well as facilitate the fast diffusion of Li ion