中文版 | English

在结果中检索

GSTDTAP

浏览/检索结果: 共177条，第1-10条 帮助

限定条件    
已选(0)清除 条数/页：   排序方式：
Automatic precursor recognition and real-time forecasting of sudden explosive volcanic eruptions at Whakaari, New Zealand 期刊论文
NATURE COMMUNICATIONS, 2020, 11 (1)
作者:  Dempsey, D. E.;  Cronin, S. J.;  Mei, S.;  Kempa-Liehr, A. W.
收藏  |  浏览/下载：10/0  |  提交时间：2020/07/21
Characterizing soundscapes across diverse ecosystems using a universal acoustic feature set 期刊论文
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2020, 117 (29) : 17049-17055
作者:  Sethi, Sarab S.;  Jones, Nick S.;  Fulcher, Ben D.;  Picinali, Lorenzo;  Clink, Dena Jane;  Klinck, Holger;  Orme, C. David L.;  Wrege, Peter H.;  Ewers, Robert M.
收藏  |  浏览/下载：24/0  |  提交时间：2020/07/09
machine learning  acoustic  soundscape  monitoring  ecology  
Stable machine-learning parameterization of subgrid processes for climate modeling at a range of resolutions 期刊论文
NATURE COMMUNICATIONS, 2020, 11 (1)
作者:  Yuval, Janni;  39;Gorman, Paul A.
收藏  |  浏览/下载：4/0  |  提交时间：2020/07/06
Quantifying the drivers and predictability of seasonal changes in African fire 期刊论文
NATURE COMMUNICATIONS, 2020, 11 (1)
作者:  Yu, Yan;  Mao, Jiafu;  Thornton, Peter E.;  Notaro, Michael;  Wullschleger, Stan D.;  Shi, Xiaoying;  Hoffman, Forrest M.;  Wang, Yaoping
收藏  |  浏览/下载：9/0  |  提交时间：2020/06/16
Real-time data from mobile platforms to evaluate sustainable transportation infrastructure 期刊论文
NATURE SUSTAINABILITY, 2020, 3 (6) : 463-+
作者:  Asensio, Omar Isaac;  Alvarez, Kevin;  Dror, Arielle;  Wenzel, Emerson;  Hollauer, Catharina;  Ha, Sooji
收藏  |  浏览/下载：8/0  |  提交时间：2020/06/09
Nearest neighbours reveal fast and slow components of motor learning 期刊论文
NATURE, 2020, 577 (7791) : 526-+
作者:  Kollmorgen, Sepp;  Hahnloser, Richard H. R.;  Mante, Valerio
收藏  |  浏览/下载：4/0  |  提交时间：2020/07/03

A new method for analysing change in high-dimensional data is based on nearest-neighbour statistics and is applied here to song dynamics during vocal learning in zebra finches, but could potentially be applied to other biological and artificial behaviours.


Changes in behaviour resulting from environmental influences, development and learning(1-5) are commonly quantified on the basis of a few hand-picked features(2-4,6,7) (for example, the average pitch of acoustic vocalizations(3)), assuming discrete classes of behaviours (such as distinct vocal syllables)(2,3,8-10). However, such methods generalize poorly across different behaviours and model systems and may miss important components of change. Here we present a more-general account of behavioural change that is based on nearest-neighbour statistics(11-13), and apply it to song development in a songbird, the zebra finch(3). First, we introduce the concept of '  repertoire dating'  , whereby each rendition of a behaviour (for example, each vocalization) is assigned a repertoire time, reflecting when similar renditions were typical in the behavioural repertoire. Repertoire time isolates the components of vocal variability that are congruent with long-term changes due to vocal learning and development, and stratifies the behavioural repertoire into '  regressions'  , '  anticipations'  and '  typical renditions'  . Second, we obtain a holistic, yet low-dimensional, description of vocal change in terms of a stratified '  behavioural trajectory'  , revealing numerous previously unrecognized components of behavioural change on fast and slow timescales, as well as distinct patterns of overnight consolidation(1,2,4,14,15) across the behavioral repertoire. We find that diurnal changes in regressions undergo only weak consolidation, whereas anticipations and typical renditions consolidate fully. Because of its generality, our nonparametric description of how behaviour evolves relative to itself-rather than to a potentially arbitrary, experimenter-defined goal(2,3,14,16)-appears well suited for comparing learning and change across behaviours and species(17,18), as well as biological and artificial systems(5).


  
Clonally expanded CD8 T cells patrol the cerebrospinal fluid in Alzheimer's disease 期刊论文
NATURE, 2020, 577 (7790) : 399-+
作者:  Gate, David;  Saligrama, Naresha;  Leventhal, Olivia;  Yang, Andrew C.;  Unger, Michael S.;  Middeldorp, Jinte;  Chen, Kelly;  Lehallier, Benoit;  Channappa, Divya;  De Los Santos, Mark B.;  McBride, Alisha;  Pluvinage, John;  Elahi, Fanny;  Tam, Grace Kyin-Ye;  Kim, Yongha;  Greicius, Michael;  Wagner, Anthony D.;  Aigner, Ludwig;  Galasko, Douglas R.;  Davis, Mark M.;  Wyss-Coray, Tony
收藏  |  浏览/下载：6/0  |  提交时间：2020/07/03

Alzheimer'  s disease is an incurable neurodegenerative disorder in which neuroinflammation has a critical function(1). However, little is known about the contribution of the adaptive immune response in Alzheimer'  s disease(2). Here, using integrated analyses of multiple cohorts, we identify peripheral and central adaptive immune changes in Alzheimer'  s disease. First, we performed mass cytometry of peripheral blood mononuclear cells and discovered an immune signature of Alzheimer'  s disease that consists of increased numbers of CD8(+) T effector memory CD45RA(+) (T-EMRA) cells. In a second cohort, we found that CD8(+) T-EMRA cells were negatively associated with cognition. Furthermore, single-cell RNA sequencing revealed that T cell receptor (TCR) signalling was enhanced in these cells. Notably, by using several strategies of single-cell TCR sequencing in a third cohort, we discovered clonally expanded CD8(+) T-EMRA cells in the cerebrospinal fluid of patients with Alzheimer'  s disease. Finally, we used machine learning, cloning and peptide screens to demonstrate the specificity of clonally expanded TCRs in the cerebrospinal fluid of patients with Alzheimer'  s disease to two separate Epstein-Barr virus antigens. These results reveal an adaptive immune response in the blood and cerebrospinal fluid in Alzheimer'  s disease and provide evidence of clonal, antigen-experienced T cells patrolling the intrathecal space of brains affected by age-related neurodegeneration.


  
Global reconstruction reduces the uncertainty of oceanic nitrous oxide emissions and reveals a vigorous seasonal cycle 期刊论文
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2020, 117 (22) : 11954-11960
作者:  Yang, Simon;  Chang, Bonnie X.;  Warner, Mark J.;  Weber, Thomas S.;  Bourbonnais, Annie M.;  Santoro, Alyson E.;  Kock, Annette;  Sonnerup, Rolf E.;  Bullister, John L.;  Wilson, Samuel T.;  Bianchi, Daniele
收藏  |  浏览/下载：13/0  |  提交时间：2020/05/20
nitrous oxide  air-sea gas exchange  seasonal variability  nitrogen cycle  greenhouse gases  
Accelerated discovery of CO2 electrocatalysts using active machine learning 期刊论文
NATURE, 2020, 581 (7807) : 178-+
作者:  Lan, Jun;  Ge, Jiwan;  Yu, Jinfang;  Shan, Sisi;  Zhou, Huan;  Fan, Shilong;  Zhang, Qi;  Shi, Xuanling;  Wang, Qisheng;  Zhang, Linqi;  Wang, Xinquan
收藏  |  浏览/下载：89/0  |  提交时间：2020/07/03

The rapid increase in global energy demand and the need to replace carbon dioxide (CO2)-emitting fossil fuels with renewable sources have driven interest in chemical storage of intermittent solar and wind energy(1,2). Particularly attractive is the electrochemical reduction of CO2 to chemical feedstocks, which uses both CO2 and renewable energy(3-8). Copper has been the predominant electrocatalyst for this reaction when aiming for more valuable multi-carbon products(9-16), and process improvements have been particularly notable when targeting ethylene. However, the energy efficiency and productivity (current density) achieved so far still fall below the values required to produce ethylene at cost-competitive prices. Here we describe Cu-Al electrocatalysts, identified using density functional theory calculations in combination with active machine learning, that efficiently reduce CO2 to ethylene with the highest Faradaic efficiency reported so far. This Faradaic efficiency of over 80 per cent (compared to about 66 per cent for pure Cu) is achieved at a current density of 400 milliamperes per square centimetre (at 1.5 volts versus a reversible hydrogen electrode) and a cathodic-side (half-cell) ethylene power conversion efficiency of 55 +/- 2 per cent at 150 milliamperes per square centimetre. We perform computational studies that suggest that the Cu-Al alloys provide multiple sites and surface orientations with near-optimal CO binding for both efficient and selective CO2 reduction(17). Furthermore, in situ X-ray absorption measurements reveal that Cu and Al enable a favourable Cu coordination environment that enhances C-C dimerization. These findings illustrate the value of computation and machine learning in guiding the experimental exploration of multi-metallic systems that go beyond the limitations of conventional single-metal electrocatalysts.


  
The proteome landscape of the kingdoms of life 期刊论文
NATURE, 2020
作者:  Arzi, Anat;  Rozenkrantz, Liron;  Gorodisky, Lior;  Rozenkrantz, Danit;  Holtzman, Yael;  Ravia, Aharon;  Bekinschtein, Tristan A.;  Galperin, Tatyana;  Krimchansky, Ben-Zion;  Cohen, Gal;  Oksamitni, Anna;  Aidinoff, Elena;  Sacher, Yaron;  Sobel, Noam
收藏  |  浏览/下载：14/0  |  提交时间：2020/07/03

Proteins carry out the vast majority of functions in all biological domains, but for technological reasons their large-scale investigation has lagged behind the study of genomes. Since the first essentially complete eukaryotic proteome was reported(1), advances in mass-spectrometry-based proteomics(2)have enabled increasingly comprehensive identification and quantification of the human proteome(3-6). However, there have been few comparisons across species(7,8), in stark contrast with genomics initiatives(9). Here we use an advanced proteomics workflow-in which the peptide separation step is performed by a microstructured and extremely reproducible chromatographic system-for the in-depth study of 100 taxonomically diverse organisms. With two million peptide and 340,000 stringent protein identifications obtained in a standardized manner, we double the number of proteins with solid experimental evidence known to the scientific community. The data also provide a large-scale case study for sequence-based machine learning, as we demonstrate by experimentally confirming the predicted properties of peptides fromBacteroides uniformis. Our results offer a comparative view of the functional organization of organisms across the entire evolutionary range. A remarkably high fraction of the total proteome mass in all kingdoms is dedicated to protein homeostasis and folding, highlighting the biological challenge of maintaining protein structure in all branches of life. Likewise, a universally high fraction is involved in supplying energy resources, although these pathways range from photosynthesis through iron sulfur metabolism to carbohydrate metabolism. Generally, however, proteins and proteomes are remarkably diverse between organisms, and they can readily be explored and functionally compared at www.proteomesoflife.org.