Magnetic island formation and rotation braking induced by low-Z impurity penetration in an EAST plasma

Recent observations of the successive formations of the 4=1; 3=1, and 2=1 magnetic islands as well as the subsequent braking of the 2=1 mode during a low-Z impurity penetration process in EAST experiments are well reproduced in our 3D resistive MHD simulations. The enhanced parallel current perturbation induced by impurity radiation predominately contributes to the tearing mode growth, and the 2=1 island rotation is mainly damped by the impurity accumulation as results of the influence from high n modes.Comment: 21 pages, 9 figure

1-(3,5-Dimeth­oxy­benz­yl)-1H-pyrrole

The title compound, C13H15NO2, was synthesized from 3,5-dimeth­oxy­benzaldehyde. The dihedral angle between the pyrrole and benzene rings is 89.91 (5)°. In the crystal, weak C—H⋯O and C—H⋯π interactions link the mol­ecules into a three-dimensional network

Effects on the Physicochemical Properties of Hydrochar Originating from Deep Eutectic Solvent (Urea and ZnCl2)-Assisted Hydrothermal Carbonization of Sewage Sludge

Deep eutectic solvents (DESs) (ZnCl2 and urea) have been used to solubilize organic matter from sewage sludge (SS), followed by subsequent hydrothermal carbonization (HTC) to obtain low-nitrogen-content hydrochar. The nitrogen content in hydrochar obtained after DES addition decreased to 1.93 from 3.15% (no DES) at 210 °C. DES can notably dissolve proteins and lipids during HTC of SS. HTC of polysaccharides was enhanced, increasing the degree of carbonization. The key role of DES in SS during HTC was the dissolution of proteins, promoting carbonization of polysaccharides, Maillard reactions, deamination, and decarboxylation of proteins. ZnCl2 was probably converted into β-Zn(OH)C1 and ZnO during HTC. Results pointed to relevant enhancements when DES was added, useful for organic waste valorization such as SS, food waste, poultry manure, and related waste feedstock

Strengths-based leadership and employee work engagement:A multi-source study

Strengths-based leadership helps employees identify, utilize, and develop their strengths. Does such leadership facilitate employee work engagement and performance? In this study, we integrate Job Demands-Resources (JD-R) and Leader-Member Exchange (LMX) theories to hypothesize that strengths-based leadership is positively related to employee task performance through employee work engagement, and that this effect is moderated by LMX quality. We collected survey data at two time points – with one month interval – from 556 Chinese workers and their managers (N = 104 teams). The results of path modelling showed that strengths-based leadership was positively related to supervisor-ratings of employee task performance via employee work engagement. As predicted, the positive relation between strengths-based leadership and employee work engagement was stronger when LMX was of high-quality. However, the predicted moderated-mediation effect was not supported. We discuss the implications of these findings for research on strengths-based leadership, as well as the practical implications.</p

Advances in electronic skin research: a bibliometric analysis

Background: E-skin (electronic skin) is an active research area in human-computer interaction and artificial intelligence.Methods: A bibliometric analysis was performed to evaluate publications in the E-skin field between 2000 and 2021 based on the Web of Science (WoS) databases.Results: A total of 4,954 documents were identified. A detailed overview of E-skin research was presented from aspects of productive countries/regions, institutions, journals, citations, highly cited papers, keywords, and emerging topics. With the emergence of new functional materials, structural design, 3D printing, and nanofabrication techniques, E-skin research has achieved dramatic progress after 2013. Scholars and institutions in China, the United States and South Korea are leading the way in E-skin research. Pressure sensor, strain sensor, and flexible electronics are the most focused directions at present and Internet of things is the most emerging topic.Conclusion: E-skin research has achieved dramatic progress but there is still quite a challenging task in practical applications. Manufacturing process simplification, cost reduction, functional integration, energy supply, and biocompatibility are vital for the future development of E-skin

Learning Unorthogonalized Matrices for Rotation Estimation

Estimating 3D rotations is a common procedure for 3D computer vision. The accuracy depends heavily on the rotation representation. One form of representation -- rotation matrices -- is popular due to its continuity, especially for pose estimation tasks. The learning process usually incorporates orthogonalization to ensure orthonormal matrices. Our work reveals, through gradient analysis, that common orthogonalization procedures based on the Gram-Schmidt process and singular value decomposition will slow down training efficiency. To this end, we advocate removing orthogonalization from the learning process and learning unorthogonalized `Pseudo' Rotation Matrices (PRoM). An optimization analysis shows that PRoM converges faster and to a better solution. By replacing the orthogonalization incorporated representation with our proposed PRoM in various rotation-related tasks, we achieve state-of-the-art results on large-scale benchmarks for human pose estimation

Towards Large-scale Single-shot Millimeter-wave Imaging for Low-cost Security Inspection

Millimeter-wave (MMW) imaging is emerging as a promising technique for safe security inspection. It achieves a delicate balance between imaging resolution, penetrability and human safety, resulting in higher resolution compared to low-frequency microwave, stronger penetrability compared to visible light, and stronger safety compared to X ray. Despite of recent advance in the last decades, the high cost of requisite large-scale antenna array hinders widespread adoption of MMW imaging in practice. To tackle this challenge, we report a large-scale single-shot MMW imaging framework using sparse antenna array, achieving low-cost but high-fidelity security inspection under an interpretable learning scheme. We first collected extensive full-sampled MMW echoes to study the statistical ranking of each element in the large-scale array. These elements are then sampled based on the ranking, building the experimentally optimal sparse sampling strategy that reduces the cost of antenna array by up to one order of magnitude. Additionally, we derived an untrained interpretable learning scheme, which realizes robust and accurate image reconstruction from sparsely sampled echoes. Last, we developed a neural network for automatic object detection, and experimentally demonstrated successful detection of concealed centimeter-sized targets using 10% sparse array, whereas all the other contemporary approaches failed at the same sample sampling ratio. The performance of the reported technique presents higher than 50% superiority over the existing MMW imaging schemes on various metrics including precision, recall, and mAP50. With such strong detection ability and order-of-magnitude cost reduction, we anticipate that this technique provides a practical way for large-scale single-shot MMW imaging, and could advocate its further practical applications