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Huimin Wang

Researcher at Chinese Academy of Sciences

Publications -  285
Citations -  8221

Huimin Wang is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Ecosystem & Soil water. The author has an hindex of 35, co-authored 249 publications receiving 5335 citations. Previous affiliations of Huimin Wang include Northeastern University & Northeastern University (China).

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The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

Gilberto Pastorello, +303 more
- 09 Jul 2020 - 
TL;DR: The FLUXNET2015 dataset provides ecosystem-scale data on CO 2 , water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe, and is detailed in this paper.
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Spatial patterns and climate drivers of carbon fluxes in terrestrial ecosystems of China

TL;DR: The results indicate that gross ecosystem productivity (GEP), ecosystem respiration (ER), and netcosystem productivity (NEP) of terrestrial ecosystems in China showed a significantly latitudinal pattern, declining linearly with the increase of latitude, but GEP, ER, and NEP did not present a clear longitudinal pattern.
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DNAzyme-Loaded Metal–Organic Frameworks (MOFs) for Self-Sufficient Gene Therapy

TL;DR: A self-sufficient MOF-based chlorin e6-modified DNAzyme (Ce6-DNAzyme) therapeutic nanosystem for combined gene therapy and photodynamic therapy (PDT) and the ZIF-8 nanoparticles (NPs) could efficiently deliver the therapeutic DNAzyme without degradation into cancer cells.
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Effect of Different Fertilizer Application on the Soil Fertility of Paddy Soils in Red Soil Region of Southern China

TL;DR: Organic manure should be recommended to improve soil fertility in this region and K fertilizer should be simultaneously applied considering the soil K contents, according to the effects of five fertilization treatments from 1998 to 2009.
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Spatiotemporal pattern of gross primary productivity and its covariation with climate in China over the last thirty years.

TL;DR: A machine learning algorithm was applied developing a new GPP dataset for China with 0.1° spatial resolution and monthly temporal frequency based on eddy flux measurements from 40 sites in China and surrounding countries, most of which have not been explored in previous global GPP datasets.