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美国国家大气研究中心开发先进的太阳能预测系统 快报文章
气候变化快报，2023年第12期
作者:  王田宇 刘燕飞
Microsoft Word(14Kb)  |  收藏  |  浏览/下载：574/0  |  提交时间：2023/06/20
solar energy forecasting  New York  NYSolarCast  solar irradiance  machine learning  
国际研究系统分析人类适应气候变化的科学文献 快报文章
气候变化快报，2021年第22期
作者:  廖琴
Microsoft Word(15Kb)  |  收藏  |  浏览/下载：645/0  |  提交时间：2021/11/20
Climate Change Adaptation  Supervised Machine Learning  
新研究利用机器学习系统分析全球气候与健康科学文献 快报文章
气候变化快报，2021年第15期
作者:  廖琴
Microsoft Word(17Kb)  |  收藏  |  浏览/下载：497/0  |  提交时间：2021/08/05
Machine Learning  Climate Change  Human Health  
Estimation of global coastal sea level extremes using neural networks 期刊论文
ENVIRONMENTAL RESEARCH LETTERS, 2020, 15 (7)
作者:  Bruneau, Nicolas;  Polton, Jeff;  Williams, Joanne;  Holt, Jason
收藏  |  浏览/下载：8/0  |  提交时间：2020/08/18
sea water anomaly  extremes  storm surges  GESLA database  machine learning  
Machine learning based estimation of land productivity in the contiguous US using biophysical predictors 期刊论文
ENVIRONMENTAL RESEARCH LETTERS, 2020, 15 (7)
作者:  Yang, Pan;  Zhao, Qiankun;  Cai, Ximing
收藏  |  浏览/下载：12/0  |  提交时间：2020/08/18
land productivity  marginal land  land use  machine learning  
Comparative assessment of environmental variables and machine learning algorithms for maize yield prediction in the US Midwest 期刊论文
ENVIRONMENTAL RESEARCH LETTERS, 2020, 15 (6)
作者:  Kang, Yanghui;  Ozdogan, Mutlu;  Zhu, Xiaojin;  Ye, Zhiwei;  Hain, Christopher;  Anderson, Martha
收藏  |  浏览/下载：15/0  |  提交时间：2020/07/02
crop yields  climate impact  machine learning  deep learning  data-driven  
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.


  
Potential for Early Forecast of Moroccan Wheat Yields Based on Climatic Drivers 期刊论文
GEOPHYSICAL RESEARCH LETTERS, 2020, 47 (12)
作者:  Lehmann, J.;  Kretschmer, M.;  Schauberger, B.;  Wechsung, F.
收藏  |  浏览/下载：15/0  |  提交时间：2020/05/20
causal discovery algorithms  teleconnections  seasonal forecast  machine learning  wheat forecast  climate precursors  
Detecting Slow Slip Events From Seafloor Pressure Data Using Machine Learning 期刊论文
GEOPHYSICAL RESEARCH LETTERS, 2020, 47 (11)
作者:  He, Bing;  Wei, Meng;  Watts, D. Randolph;  Shen, Yang
收藏  |  浏览/下载：9/0  |  提交时间：2020/05/13
slow slip events  seafloor geodesy  machine learning  seafloor pressure data  New Zealand  
Sentinel-1 observation frequency significantly increases burnt area detectability in tropical SE Asia 期刊论文
ENVIRONMENTAL RESEARCH LETTERS, 2020, 15 (5)
作者:  Carreiras, Joao M. B.;  Quegan, Shaun;  Tansey, Kevin;  Page, Susan
收藏  |  浏览/下载：8/0  |  提交时间：2020/07/02
burnt area  tropics  Sentinel-1  radar  machine learning  Indonesia