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Hydropower Production Benefits More From 1.5 degrees C than 2 degrees C Climate Scenario 期刊论文
WATER RESOURCES RESEARCH, 2020, 56 (5)
作者:  Meng, Ying;  Liu, Junguo;  Leduc, Sylvain;  Mesfun, Sennai;  Kraxner, Florian;  Mao, Ganquan;  Qi, Wei;  Wang, Zifeng
收藏  |  浏览/下载:26/0  |  提交时间:2020/05/13
global warming  hydropower(sic)hydro-economic modeling  optimization model  ISIMIP  PCR-GLOBWB  protected areas  
Blind to carbon risk? An analysis of stock market reaction to the Paris Agreement 期刊论文
ECOLOGICAL ECONOMICS, 2020, 170
作者:  Monasterolo, Irene;  de Angelis, Luca
收藏  |  浏览/下载:46/0  |  提交时间:2020/07/02
Asset pricing  Paris Agreement announcement  Low-carbon indices  Carbon-intensive indices  Systematic risk  Markowitz'  s portfolio optimization  Market model  Fama-French five-factor model  Risk-adjusted return  Stranded assets  
Virtual discovery of melatonin receptor ligands to modulate circadian rhythms 期刊论文
NATURE, 2020, 579 (7800) : 609-+
作者:  Huang, Weijiao;  Masureel, Matthieu;  Qu, Qianhui;  Janetzko, John;  Inoue, Asuka;  Kato, Hideaki E.;  Robertson, Michael J.;  Nguyen, Khanh C.;  Glenn, Jeffrey S.;  Skiniotis, Georgios;  Kobilka, Brian K.
收藏  |  浏览/下载:39/0  |  提交时间:2020/07/03

The neuromodulator melatonin synchronizes circadian rhythms and related physiological functions through the actions of two G-protein-coupled receptors: MT1 and MT2. Circadian release of melatonin at night from the pineal gland activates melatonin receptors in the suprachiasmatic nucleus of the hypothalamus, synchronizing the physiology and behaviour of animals to the light-dark cycle(1-4). The two receptors are established drug targets for aligning circadian phase to this cycle in disorders of sleep(5,6) and depression(1-4,7-9). Despite their importance, few in vivo active MT1-selective ligands have been reported(2,8,10-12), hampering both the understanding of circadian biology and the development of targeted therapeutics. Here we docked more than 150 million virtual molecules to an MT1 crystal structure, prioritizing structural fit and chemical novelty. Of these compounds, 38 high-ranking molecules were synthesized and tested, revealing ligands with potencies ranging from 470 picomolar to 6 micromolar. Structure-based optimization led to two selective MT1 inverse agonists-which were topologically unrelated to previously explored chemotypes-that acted as inverse agonists in a mouse model of circadian re-entrainment. Notably, we found that these MT1-selective inverse agonists advanced the phase of the mouse circadian clock by 1.3-1.5 h when given at subjective dusk, an agonist-like effect that was eliminated in MT1- but not in MT2-knockout mice. This study illustrates the opportunities for modulating melatonin receptor biology through MT1-selective ligands and for the discovery of previously undescribed, in vivo active chemotypes from structure-based screens of diverse, ultralarge libraries. A computational screen of an ultra-large virtual library against the structure of the melatonin receptor found nanomolar ligands, and ultimately two selective MT1 inverse agonists that induced phase advancement of the mouse circadian clock when given at subjective dusk.


  
Analysis of China's olefin industry with a system optimization model With different scenarios of dynamic oil and coal prices 期刊论文
ENERGY POLICY, 2019, 135
作者:  Xu, Zhongming;  Zhang, Yaru;  Fang, Chenhao;  Yu, Yadong;  Ma, Tieju
收藏  |  浏览/下载:30/0  |  提交时间:2020/02/17
Olefin industry  System optimization model  Carbon emission  Oil price  
Policy implications for achieving the carbon emission reduction target by 2030 in Japan-Analysis based on a bilevel equilibrium model 期刊论文
ENERGY POLICY, 2019, 134
作者:  Xu, Zhongwen;  Yao, Liming;  Liu, Qiaoling;  Long, Yin
收藏  |  浏览/下载:21/0  |  提交时间:2020/02/17
Carbon emission quotas  Zero sum gains-data envelopment analysis  Particle swarm optimization method  Biobjective bilevel equilibrium model  Regional energy policy  
Modelling carbon and water balance of Eucalyptus plantations at regional scale: Effect of climate, soil and genotypes 期刊论文
FOREST ECOLOGY AND MANAGEMENT, 2019, 449
作者:  Attia, Ahmed;  Nouvellon, Yann;  Cuadra, Santiago;  Cabral, Osvaldo;  Laclau, Jean-Paul;  Guillemot, Joannes;  Campoe, Otavio;  Stape, Jose-Luiz;  Galdos, Marcelo;  Lamparelli, Rubens;  le Maire, Guerric
收藏  |  浏览/下载:26/0  |  提交时间:2019/11/27
Eucalyptus plantations  Ecophysiological model  G'  DAY  Optimization  Productivity  
Carbon payments for extended rotations in forest plantations: Conflicting insights from a theoretical model 期刊论文
ECOLOGICAL ECONOMICS, 2019, 163: 70-76
作者:  West, Thales A. P.;  Wilson, Chris;  Vrachioli, Maria;  Grogan, Kelly A.
收藏  |  浏览/下载:26/0  |  提交时间:2019/11/27
Payments for environmental services  Faustmann model  REDD  Forest management optimization  Climate change mitigation  
Identification and application of the most suitable entropy model for precipitation complexity measurement 期刊论文
ATMOSPHERIC RESEARCH, 2019, 221: 88-97
作者:  Zhang, Liangliang;  Li, Heng;  Liu, Dong;  Fu, Qiang;  Li, Mo;  Faiz, Muhammad Abrar;  Khan, Muhammad Imran;  Li, Tianxiao
收藏  |  浏览/下载:18/0  |  提交时间:2019/11/26
Precipitation  Complexity measurement  Entropy theory  Multi-model optimization  Impact factor  
The Improved Freeze-Thaw Process of a Climate-Vegetation Model: Calibration and Validation Tests in the Source Region of the Yellow River 期刊论文
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2018, 123 (23) : 13346-13367
作者:  Yang, Q.;  Dan, L.;  Wu, J.;  Jiang, R.;  Dan, J.;  Li, W.;  Yang, F.;  Yang, X.;  Xia, L.
收藏  |  浏览/下载:26/0  |  提交时间:2019/04/09
freeze-thaw process  the AVIM model  particle swarm optimization (PSO) method  calibration  validation  source region of the Yellow River  
Realizing China's goals on energy saving and pollution reduction: Industrial structure multi-objective optimization approach 期刊论文
ENERGY POLICY, 2018, 122: 300-312
作者:  Yu, Shiwei;  Zheng, Shuhong;  Zhang, Xuejiao;  Gong, Chengzhu;  Cheng, Jinhua
收藏  |  浏览/下载:18/0  |  提交时间:2019/04/09
Energy saving and pollutant reduction  Industrial restructuring  Dynamic input-output model  Multi-objective optimization  Reduction goals