In the past two years,significant progresses have been achieved in high-performance cast and wrought magnesium and magnesium alloys,magnesium-based composites,advanced cast technologies,advanced processing technologie...In the past two years,significant progresses have been achieved in high-performance cast and wrought magnesium and magnesium alloys,magnesium-based composites,advanced cast technologies,advanced processing technologies,and functional magnesium materials,such as Mg ion batteries,hydrogen storage Mg materials,bio-magnesium alloys,etc.Great contributions to the development of new magnesium alloys and their processing technologies have been made by Chongqing University,Shanghai Jiaotong University,Chinese Academy of Sciences,Helmholtz Zentrum Geesthacht,Queensland University,Brunel University,etc.This review paper is aimed to summarize the latest important advances in cast magnesium alloys,wrought magnesium alloys and functional magnesium materials worldwide in 2018–2019,including both the development of new materials and the innovation of their processing technologies.Based on the issues and challenges identified here,some future research directions are suggested,including further development of high-performance magnesium alloys having high strength and superior plasticity together with high corrosion resistance and low cost,and fundamental research on the phase diagram,diffusion,precipitation,etc.,as well as the development of advanced welding and joining technology.展开更多
Recently, the emergence of pre-trained models(PTMs) has brought natural language processing(NLP) to a new era. In this survey, we provide a comprehensive review of PTMs for NLP. We first briefly introduce language rep...Recently, the emergence of pre-trained models(PTMs) has brought natural language processing(NLP) to a new era. In this survey, we provide a comprehensive review of PTMs for NLP. We first briefly introduce language representation learning and its research progress. Then we systematically categorize existing PTMs based on a taxonomy from four different perspectives. Next,we describe how to adapt the knowledge of PTMs to downstream tasks. Finally, we outline some potential directions of PTMs for future research. This survey is purposed to be a hands-on guide for understanding, using, and developing PTMs for various NLP tasks.展开更多
The current research and development of magnesium alloys is summarized. Several aspects of magnesium alloys are described： cast Mg alloy, wrought Mg alloy, and novel processing. The subjects are discussed individuall...The current research and development of magnesium alloys is summarized. Several aspects of magnesium alloys are described： cast Mg alloy, wrought Mg alloy, and novel processing. The subjects are discussed individually and recommendations for further study are listed in the final section.展开更多
The fractional Fourier transform is a generalization of the classical Fourier transform, which is introduced from the mathematic aspect by Namias at first and has many applications in optics quickly. Whereas its poten...The fractional Fourier transform is a generalization of the classical Fourier transform, which is introduced from the mathematic aspect by Namias at first and has many applications in optics quickly. Whereas its potential appears to have remained largely unknown to the signal processing community until 1990s. The fractional Fourier transform can be viewed as the chirp-basis expansion directly from its definition, but essentially it can be interpreted as a rotation in the time-frequency plane, i.e. the unified time-frequency transform. With the order from 0 increasing to 1, the fractional Fourier transform can show the characteristics of the signal changing from the time domain to the frequency domain. In this research paper, the fractional Fourier transform has been comprehensively and systematically treated from the signal processing point of view. Our aim is to provide a course from the definition to the applications of the fractional Fourier transform, especially as a reference and an introduction for researchers and interested readers.展开更多
The irregular domain and lack of ordering make it challenging to design deep neural networks for point cloud processing.This paper presents a novel framework named Point Cloud Transformer(PCT)for point cloud learning....The irregular domain and lack of ordering make it challenging to design deep neural networks for point cloud processing.This paper presents a novel framework named Point Cloud Transformer(PCT)for point cloud learning.PCT is based on Transformer,which achieves huge success in natural language processing and displays great potential in image processing.It is inherently permutation invariant for processing a sequence of points,making it well-suited for point cloud learning.To better capture local context within the point cloud,we enhance input embedding with the support of farthest point sampling and nearest neighbor search.Extensive experiments demonstrate that the PCT achieves the state-of-the-art performance on shape classification,part segmentation,semantic segmentation,and normal estimation tasks.展开更多
基金The content in this review is financially supported by the National Key Research and Development Program of China(No.2016YFB0301100,2017YFF0209100)the National Science Foundation for Scientists of China(No.51531002,51474043,51701027,51971042,51901028)the Chongqing Academician Special Fund(cstc2018jcyj-yszxX0007,cstc2019yszxjcyjX0004).
文摘In the past two years,significant progresses have been achieved in high-performance cast and wrought magnesium and magnesium alloys,magnesium-based composites,advanced cast technologies,advanced processing technologies,and functional magnesium materials,such as Mg ion batteries,hydrogen storage Mg materials,bio-magnesium alloys,etc.Great contributions to the development of new magnesium alloys and their processing technologies have been made by Chongqing University,Shanghai Jiaotong University,Chinese Academy of Sciences,Helmholtz Zentrum Geesthacht,Queensland University,Brunel University,etc.This review paper is aimed to summarize the latest important advances in cast magnesium alloys,wrought magnesium alloys and functional magnesium materials worldwide in 2018–2019,including both the development of new materials and the innovation of their processing technologies.Based on the issues and challenges identified here,some future research directions are suggested,including further development of high-performance magnesium alloys having high strength and superior plasticity together with high corrosion resistance and low cost,and fundamental research on the phase diagram,diffusion,precipitation,etc.,as well as the development of advanced welding and joining technology.
基金the National Natural Science Foundation of China(Grant Nos.61751201 and 61672162)the Shanghai Municipal Science and Technology Major Project(Grant No.2018SHZDZX01)and ZJLab。
文摘Recently, the emergence of pre-trained models(PTMs) has brought natural language processing(NLP) to a new era. In this survey, we provide a comprehensive review of PTMs for NLP. We first briefly introduce language representation learning and its research progress. Then we systematically categorize existing PTMs based on a taxonomy from four different perspectives. Next,we describe how to adapt the knowledge of PTMs to downstream tasks. Finally, we outline some potential directions of PTMs for future research. This survey is purposed to be a hands-on guide for understanding, using, and developing PTMs for various NLP tasks.
基金the Chinese Foundation Research ProjectionMagnesium Elektron Ltd. and the Manchester Materials Science Center of University of Manchester.
文摘The current research and development of magnesium alloys is summarized. Several aspects of magnesium alloys are described： cast Mg alloy, wrought Mg alloy, and novel processing. The subjects are discussed individually and recommendations for further study are listed in the final section.
基金supported by the National Natural Science Foundation of China(Grant Nos.60232010 and 60572094)the Teaching and Research Award for 0utstanding Young Teachers in Higher Education Institutions of M0E,P.R.C.the Ministerial Foundation of China(Grant No.6140445).
文摘The fractional Fourier transform is a generalization of the classical Fourier transform, which is introduced from the mathematic aspect by Namias at first and has many applications in optics quickly. Whereas its potential appears to have remained largely unknown to the signal processing community until 1990s. The fractional Fourier transform can be viewed as the chirp-basis expansion directly from its definition, but essentially it can be interpreted as a rotation in the time-frequency plane, i.e. the unified time-frequency transform. With the order from 0 increasing to 1, the fractional Fourier transform can show the characteristics of the signal changing from the time domain to the frequency domain. In this research paper, the fractional Fourier transform has been comprehensively and systematically treated from the signal processing point of view. Our aim is to provide a course from the definition to the applications of the fractional Fourier transform, especially as a reference and an introduction for researchers and interested readers.
基金supported by the National Natural Science Foundation of China(Project Number 61521002)the Joint NSFC–DFG Research Program(Project Number 61761136018).
文摘The irregular domain and lack of ordering make it challenging to design deep neural networks for point cloud processing.This paper presents a novel framework named Point Cloud Transformer(PCT)for point cloud learning.PCT is based on Transformer,which achieves huge success in natural language processing and displays great potential in image processing.It is inherently permutation invariant for processing a sequence of points,making it well-suited for point cloud learning.To better capture local context within the point cloud,we enhance input embedding with the support of farthest point sampling and nearest neighbor search.Extensive experiments demonstrate that the PCT achieves the state-of-the-art performance on shape classification,part segmentation,semantic segmentation,and normal estimation tasks.
