Zhihong Jiang
Datos Biográficos
| ID | 6958410 |
|---|---|
| NOMBRE | Zhihong Jiang |
| NOMBRES | Zhihong |
| APELLIDO | Jiang |
| FIRMA | JIANG Z |
| AFILIACIONES | Nanjing University of Information Science and Technology |
| ORCID | 0000-0001-7864-2300 |
| VERIFICADO | Sí |
| TOTAL DE OBRAS | 7 |
| TOTAL DE CITAS | 0 |
| TOTAL COMO AUTOR | 7 |
| TOTAL COMO EDITOR | 0 |
| PRIMER AÑO DE PUBLICACIÓN | 2008 |
| AÑO MÁS RECIENTE DE PUBLICACIÓN | 2026 |
| ÍNDICE H | 0 |
From diagnosis to action
Facing the "one-size-fits-all" dilemma in China's building-sector carbon governance, we propose a replicable spatio-temporal targeting framework that translates diagnostic analytics into actionable mitigation levers. Using 2006–2022 data for 30 provinces, we first quantify carbon-reduction performance through an economy-adjusted Tapio index, then map inter-provincial spillover channels via a modified gravity-SNA network. Temporal clustering emplo…
East African population exposure to precipitation extremes under 1.5 °C and 2.0 °C warming levels based on CMIP6 models
Understanding population exposure to precipitation-related extreme events is important for effective climate change adaptation and mitigation measures. We analyze extreme precipitation using indices (EPIs), including consecutive dry days (CDD), annual total precipitation, simple daily intensity, and the number of extremely wet days, under the past and future climatic conditions over East Africa. The exposure of the East African population to thes…
Machine learning to optimize climate projection over China with multi-model ensemble simulations
The multi-model ensemble approach is generally considered as the best way to explore the advantage and to avoid the weakness of each individual model, and ultimately to achieve the best climate projection. But the design of an optimal strategy and its practical implementation still constitutes a challenge. Here we use the random forest (RF) algorithm (from the category of machine learning) to explore the information offered by the multi-model ens…
Aurantiamide acetate from baphicacanthus cusia root exhibits anti-inflammatory and anti-viral effects via inhibition of the NF-κB signaling pathway in Influenza A virus-infected cells
An Improved Variable Spring Balance Position Impedance Control for a Complex Docking Structure
Lariciresinol-4-O-β-D-glucopyranoside from the root of Isatis indigotica inhibits influenza A virus-induced pro-inflammatory response
Ethnobotanical study of medicinal plants used by Hakka in Guangdong, China
Sin obras prominentes en esta página.
Ethnobotanical study of medicinal plants used by Hakka in Guangdong, China
Lariciresinol-4-O-β-D-glucopyranoside from the root of Isatis indigotica inhibits influenza A virus-induced pro-inflammatory response
An Improved Variable Spring Balance Position Impedance Control for a Complex Docking Structure
Aurantiamide acetate from baphicacanthus cusia root exhibits anti-inflammatory and anti-viral effects via inhibition of the NF-κB signaling pathway in Influenza A virus-infected cells
Machine learning to optimize climate projection over China with multi-model ensemble simulations
The multi-model ensemble approach is generally considered as the best way to explore the advantage and to avoid the weakness of each individual model, and ultimately to achieve the best climate projection. But the design of an optimal strategy and its practical implementation still constitutes a challenge. Here we use the random forest (RF) algorithm (from the category of machine learning) to explore the information offered by the multi-model ens…
East African population exposure to precipitation extremes under 1.5 °C and 2.0 °C warming levels based on CMIP6 models
Understanding population exposure to precipitation-related extreme events is important for effective climate change adaptation and mitigation measures. We analyze extreme precipitation using indices (EPIs), including consecutive dry days (CDD), annual total precipitation, simple daily intensity, and the number of extremely wet days, under the past and future climatic conditions over East Africa. The exposure of the East African population to thes…
From diagnosis to action
Facing the "one-size-fits-all" dilemma in China's building-sector carbon governance, we propose a replicable spatio-temporal targeting framework that translates diagnostic analytics into actionable mitigation levers. Using 2006–2022 data for 30 provinces, we first quantify carbon-reduction performance through an economy-adjusted Tapio index, then map inter-provincial spillover channels via a modified gravity-SNA network. Temporal clustering emplo…
Biology (4 obras) · China (3 obras) · Geography (3 obras) · Artificial Intelligence (2 obras) · Climate change (2 obras) · Climate model (2 obras) · Climate variability and models (2 obras) · Climatology (2 obras) · Computer Science (2 obras) · Coupled model intercomparison project (2 obras)