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Improving numerical forecast of the rainstorms induced by Mongolia cold vortex in North China with the frequency matching method 期刊论文
Atmospheric Research, 2021
作者:  Jing Cong, Zhenling Wu, Yuxia Ma, Shu Xu, ... Canqi Nie
收藏  |  浏览/下载:8/0  |  提交时间:2021/08/10
Different impacts of spring tropical Atlantic SST anomalies on Eurasia spring climate during the periods of 1970–1995 and 1996–2018 期刊论文
Atmospheric Research, 2021
作者:  Danni Qiu, Haiming Xu, Jiechun Deng, Jing Ma
收藏  |  浏览/下载:7/0  |  提交时间:2021/02/17
Downstream Impact of the North Pacific Subtropical Sea Surface Temperature Front on the North Atlantic Westerly Jet Stream in Winter 期刊论文
Atmospheric Research, 2021
作者:  Leying Zhang, Haiming Xu, Jing Ma, Jiuwei Zhao, Xia Xu
收藏  |  浏览/下载:7/0  |  提交时间:2021/02/17
Downstream impact of the North Pacific subtropical sea surface temperature front on the North Atlantic westerly jet stream in winter 期刊论文
Atmospheric Research, 2021
作者:  Leying Zhang, Haiming Xu, Jing Ma, Jiuwei Zhao, Xia Xu
收藏  |  浏览/下载:10/0  |  提交时间:2021/02/17
Influx of African biomass burning aerosol during the Amazonian dry season through layered transatlantic transport of black carbon-rich smoke 期刊论文
ATMOSPHERIC CHEMISTRY AND PHYSICS, 2020, 20 (8) : 4757-4785
作者:  Holanda, Bruna A.;  Poehlker, Mira L.;  Walter, David;  Saturno, Jorge;  Soergel, Matthias;  Ditas, Jeannine;  Ditas, Florian;  Schulz, Christiane;  Franco, Marco Aurelio;  Wang, Qiaoqiao;  Donth, Tobias;  Artaxo, Paulo;  Barbosa, Henrique M. J.;  Borrmann, Stephan;  Braga, Ramon;  Brito, Joel;  Cheng, Yafang;  Dollner, Maximilian;  Kaiser, Johannes W.;  Klimach, Thomas;  Knote, Christoph;  Krueger, Ovid O.;  Fuetterer, Daniel;  Lavric, Jost, V;  Ma, Nan;  Machado, Luiz A. T.;  Ming, Jing;  Morais, Fernando G.;  Paulsen, Hauke;  Sauer, Daniel;  Schlager, Hans;  Schneider, Johannes;  Su, Hang;  Weinzierl, Bernadett;  Walser, Adrian;  Wendisch, Manfred;  Ziereis, Helmut;  Zoeger, Martin;  Poeschl, Ulrich;  Andreae, Meinrat O.;  Poehlker, Christopher
收藏  |  浏览/下载:31/0  |  提交时间:2020/07/02
Nagaoka ferromagnetism observed in a quantum dot plaquette 期刊论文
NATURE, 2020, 579 (7800) : 528-533
作者:  Yu, Yong;  Ma, Fei;  Luo, Xi-Yu;  Jing, Bo;  Sun, Peng-Fei;  Fang, Ren-Zhou;  Yang, Chao-Wei;  Liu, Hui;  Zheng, Ming-Yang;  Xie, Xiu-Ping;  Zhang, Wei-Jun;  You, Li-Xing;  Wang, Zhen;  Chen, Teng-Yun;  Zhang, Qiang;  Bao, Xiao-Hui;  Pan, Jian-Wei
收藏  |  浏览/下载:30/0  |  提交时间:2020/07/03

A quantum dot device designed to host four electrons is used to demonstrate Nagaoka ferromagnetism-a model of itinerant magnetism that has so far been limited to theoretical investigation.


Engineered, highly controllable quantum systems are promising simulators of emergent physics beyond the simulation capabilities of classical computers(1). An important problem in many-body physics is itinerant magnetism, which originates purely from long-range interactions of free electrons and whose existence in real systems has been debated for decades(2,3). Here we use a quantum simulator consisting of a four-electron-site square plaquette of quantum dots(4) to demonstrate Nagaoka ferromagnetism(5). This form of itinerant magnetism has been rigorously studied theoretically(6-9) but has remained unattainable in experiments. We load the plaquette with three electrons and demonstrate the predicted emergence of spontaneous ferromagnetic correlations through pairwise measurements of spin. We find that the ferromagnetic ground state is remarkably robust to engineered disorder in the on-site potentials and we can induce a transition to the low-spin state by changing the plaquette topology to an open chain. This demonstration of Nagaoka ferromagnetism highlights that quantum simulators can be used to study physical phenomena that have not yet been observed in any experimental system. The work also constitutes an important step towards large-scale quantum dot simulators of correlated electron systems.


  
Improved protein structure prediction using potentials from deep learning 期刊论文
NATURE, 2020, 577 (7792) : 706-+
作者:  Ma, Runze;  Cao, Duanyun;  Zhu, Chongqin;  Tian, Ye;  Peng, Jinbo;  Guo, Jing;  Chen, Ji;  Li, Xin-Zheng;  Francisco, Joseph S.;  Zeng, Xiao Cheng;  Xu, Li-Mei;  Wang, En-Ge;  Jiang, Ying
收藏  |  浏览/下载:142/0  |  提交时间:2020/07/03

Protein structure prediction can be used to determine the three-dimensional shape of a protein from its amino acid sequence(1). This problem is of fundamental importance as the structure of a protein largely determines its function(2)  however, protein structures can be difficult to determine experimentally. Considerable progress has recently been made by leveraging genetic information. It is possible to infer which amino acid residues are in contact by analysing covariation in homologous sequences, which aids in the prediction of protein structures(3). Here we show that we can train a neural network to make accurate predictions of the distances between pairs of residues, which convey more information about the structure than contact predictions. Using this information, we construct a potential of mean force(4) that can accurately describe the shape of a protein. We find that the resulting potential can be optimized by a simple gradient descent algorithm to generate structures without complex sampling procedures. The resulting system, named AlphaFold, achieves high accuracy, even for sequences with fewer homologous sequences. In the recent Critical Assessment of Protein Structure Prediction(5) (CASP13)-a blind assessment of the state of the field-AlphaFold created high-accuracy structures (with template modelling (TM) scores(6) of 0.7 or higher) for 24 out of 43 free modelling domains, whereas the next best method, which used sampling and contact information, achieved such accuracy for only 14 out of 43 domains. AlphaFold represents a considerable advance in protein-structure prediction. We expect this increased accuracy to enable insights into the function and malfunction of proteins, especially in cases for which no structures for homologous proteins have been experimentally determined(7).


  
Ultrahigh-energy density lead-free dielectric films via polymorphic nanodomain design 期刊论文
SCIENCE, 2019, 365 (6453) : 578-582
作者:  Pan, Hao;  Li, Fei;  Liu, Yao;  Zhang, Qinghua;  Wang, Meng;  Lan, Shun;  Zheng, Yunpeng;  Ma, Jing;  Gu, Lin;  Shen, Yang;  Yu, Pu;  Zhang, Shujun;  Chen, Long-Qing;  Lin, Yuan-Hua;  Nan, Ce-Wen
收藏  |  浏览/下载:13/0  |  提交时间:2019/11/27
Black and brown carbon over central Amazonia: long-term aerosol measurements at the ATTO site 期刊论文
ATMOSPHERIC CHEMISTRY AND PHYSICS, 2018, 18 (17) : 12817-12843
作者:  Saturno, Jorge;  Holanda, Bruna A.;  Poehlker, Christopher;  Ditas, Florian;  Wang, Qiaoqiao;  Moran-Zuloaga, Daniel;  Brito, Joel;  Carbone, Samara;  Cheng, Yafang;  Chi, Xuguang;  Ditas, Jeannine;  Hoffmann, Thorsten;  de Angelis, Isabella Hrabe;  Koenemann, Tobias;  Lavric, Jost, V;  Ma, Nan;  Ming, Jing;  Paulsen, Hauke;  Poehlker, Mira L.;  Rizzo, Luciana, V;  Schlag, Patrick;  Su, Hang;  Walter, David;  Wolff, Stefan;  Zhang, Yuxuan;  Artaxo, Paulo;  Poeschl, Ulrich;  Andreae, Meinrat O.
收藏  |  浏览/下载:25/0  |  提交时间:2019/04/09
Single-crystal x-ray diffraction structures of covalent organic frameworks 期刊论文
SCIENCE, 2018, 361 (6397) : 48-52
作者:  Ma, Tianqiong;  Kapustin, Eugene A.;  Yin, Shawn X.;  Liang, Lin;  Zhou, Zhengyang;  Niu, Jing;  Li, Li-Hua;  Wang, Yingying;  Su, Jie;  Li, Jian;  Wang, Xiaoge;  Wang, Wei David;  Wang, Wei;  Sun, Junliang;  Yaghi, Omar M.
收藏  |  浏览/下载:8/0  |  提交时间:2019/11/27