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Making the hard problem of consciousness easier 期刊论文
Science, 2021
作者:  Lucia Melloni;  Liad Mudrik;  Michael Pitts;  Christof Koch
收藏  |  浏览/下载:208/0  |  提交时间:2021/06/07
Miniaturization of optical spectrometers 期刊论文
Science, 2021
作者:  Zongyin Yang;  Tom Albrow-Owen;  Weiwei Cai;  Tawfique Hasan
收藏  |  浏览/下载:18/0  |  提交时间:2021/02/17
A Synthetic Dataset Inspired by Satellite Altimetry and Impacts of Sampling on Global Spaceborne Discharge Characterization 期刊论文
Water Resources Research, 2020
作者:  Md. Safat Sikder;  Matthew Bonnema;  Charlotte M. Emery;  ;  dric H. David;  Peirong Lin;  Ming Pan;  Sylvain Biancamaria;  Michelle M. Gierach
收藏  |  浏览/下载:11/0  |  提交时间:2020/12/22
Global Surface Soil Moisture Drydown Patterns 期刊论文
Water Resources Research, 2020
作者:  Vinit Sehgal;  Nandita Gaur;  Binayak P. Mohanty
收藏  |  浏览/下载:7/0  |  提交时间:2020/12/07
Economic development and converging household carbon footprints in China 期刊论文
NATURE SUSTAINABILITY, 2020, 3 (7) : 529-537
作者:  Mi, Zhifu;  39;Maris
收藏  |  浏览/下载:16/0  |  提交时间:2020/05/13
Tele-connecting urban food consumption to land use at multiple spatial scales: A case study of beef in Taiwan 期刊论文
ECOLOGICAL ECONOMICS, 2020, 169
作者:  Chung, Yessica C. Y.;  Lee, Tsung-Chen
收藏  |  浏览/下载:5/0  |  提交时间:2020/07/02
Urban land teleconnection  Beef consumption  Multiple spatial scales  
On sustainability interpretations of the Ecological Footprint 期刊论文
ECOLOGICAL ECONOMICS, 2020, 169
作者:  Syrovatka, Miroslav
收藏  |  浏览/下载:10/0  |  提交时间:2020/07/02
Ecological Footprint  Sustainability  Sustainability indicator  Global justice  
Physical and virtual carbon metabolism of global cities 期刊论文
NATURE COMMUNICATIONS, 2020, 11 (1)
作者:  Chen, Shaoqing;  Chen, Bin;  Feng, Kuishuang;  Liu, Zhu;  Fromer, Neil;  Tan, Xianchun;  Alsaedi, Ahmed;  Hayat, Tasawar;  Weisz, Helga;  Schellnhuber, Hans Joachim;  Hubacek, Klaus
收藏  |  浏览/下载:6/0  |  提交时间:2020/05/13
Constructing protein polyhedra via orthogonal chemical interactions 期刊论文
NATURE, 2020, 578 (7793) : 172-+
作者:  Mooley, K. P.;  Deller, A. T.;  Gottlieb, O.;  Nakar, E.;  Hallinan, G.;  Bourke, S.;  Frail, D. A.;  Horesh, A.;  Corsi, A.;  Hotokezaka, K.
收藏  |  浏览/下载:7/0  |  提交时间:2020/07/03

Many proteins exist naturally as symmetrical homooligomers or homopolymers(1). The emergent structural and functional properties of such protein assemblies have inspired extensive efforts in biomolecular design(2-5). As synthesized by ribosomes, proteins are inherently asymmetric. Thus, they must acquire multiple surface patches that selectively associate to generate the different symmetry elements needed to form higher-order architectures(1,6)-a daunting task for protein design. Here we address this problem using an inorganic chemical approach, whereby multiple modes of protein-protein interactions and symmetry are simultaneously achieved by selective, '  one-pot'  coordination of soft and hard metal ions. We show that a monomeric protein (protomer) appropriately modified with biologically inspired hydroxamate groups and zinc-binding motifs assembles through concurrent Fe3+ and Zn2+ coordination into discrete dodecameric and hexameric cages. Our cages closely resemble natural polyhedral protein architectures(7,8) and are, to our knowledge, unique among designed systems(9-13) in that they possess tightly packed shells devoid of large apertures. At the same time, they can assemble and disassemble in response to diverse stimuli, owing to their heterobimetallic construction on minimal interprotein-bonding footprints. With stoichiometries ranging from [2 Fe:9 Zn:6 protomers] to [8 Fe:21 Zn:12 protomers], these protein cages represent some of the compositionally most complex protein assemblies-or inorganic coordination complexes-obtained by design.


An inorganic chemical approach to biomolecular design is used to generate '  cages'  that can simultaneously promote symmetry and multiple modes of protein interactions.


  
Gap-filling approaches for eddy covariance methane fluxes: A comparison of three machine learning algorithms and a traditional method with principal component analysis 期刊论文
GLOBAL CHANGE BIOLOGY, 2019
作者:  Kim, Yeonuk;  Johnson, Mark S.;  Knox, Sara H.;  Black, T. Andrew;  Dalmagro, Higo J.;  Kang, Minseok;  Kim, Joon;  Baldocchi, Dennis
收藏  |  浏览/下载:16/0  |  提交时间:2019/11/27
artificial neural network  comparison of gap-filling techniques  eddy covariance  machine learning  marginal distribution sampling  methane flux  random forest  support vector machine