Yitao Li

Zhejiang University of Science and Technology

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Hua Wu

University of Electronic Science and Technology of China

Pei Leng

Institute of Agricultural Resources and Regional Planning

Ronglin Tang

Institute of Geographic Sciences and Natural Resources Research

Chenghu Zhou

Chinese Academy of Sciences

Xiangyang Liu

Chinese Academy of Agricultural Sciences

Menglin Si

Institute of Geographic Sciences and Natural Resources Research

Mengci Li

Shanghai Sixth People's Hospital

Cheng Hu

Shanghai Jiao Tong University

Tianlu Chen

Shanghai Sixth People's Hospital

Jia Wang

Shanghai Sixth People's Hospital

Cooperative Institutions

Chinese Academy of Sciences

Shanghai Jiao Tong University

University of Chinese Academy of Sciences

Shanghai Sixth People's Hospital

Institute of Geographic Sciences and Natural Resources Research

Peking University

Chinese Academy of Agricultural Sciences

Institute of Agricultural Resources and Regional Planning

Zhejiang University

Ministry of Agriculture and Rural Affairs

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Local temperature responses to actual land cover changes present significant latitudinal variability and asymmetry

Science Bulletin (2023)

Xiangyang Liu Zhao-Liang Li Yitao Li Hua Wu Chenghu Zhou

Land Cover

10.1016/j.scib.2023.09.046

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Citations (19)

Recent climate change strengthens the local cooling of European forests

Research Square (Research Square) (2025)

Zhao-Liang Li Yitao Li Jun Ge Hua Wu Ronglin Tang

Abstract Forests exhibit cooling or warming effects compared to adjacent openlands through biophysical processes. The local temperature effects are predicted by earth system models to evolve in response to climate change. However, these temporal dynamic patterns remain unconstrained by observations and have not been detected in historical records. Here, we provide satellite evidence of emergent negative trends in local land surface temperature (LST) effects of European forests from 2003–2023. The daytime cooling effects have significantly intensified in both winter (-0.17 K/decade) and summer (-0.22 K/decade). The enhanced winter cooling is attributed to the reduced shortwave radiative forcing in forests due to decreasing snow cover. In the summertime, the vegetation physiological response to increased atmospheric vapor pressure deficit boosts evaporative cooling in forests. The negative trends in LST effects of European forests are roughly supported by four state-of-the-art earth system models. However, considerable biases and intermodel spread in the representation of underlying biophysical processes. Given the continued climate change, we emphasize the need to consider their impacts on biophysical effect dynamics when comprehensive forest-related climate mitigation policies are formed.

10.21203/rs.3.rs-5281378/v1

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Darwin3: a large-scale neuromorphic chip with a novel ISA and on-chip learning

National Science Review (2024)

De Ma Xiaofei Jin Shichun Sun Yitao Li Xundong Wu

ABSTRACT Spiking neural networks (SNNs) are gaining increasing attention for their biological plausibility and potential for improved computational efficiency. To match the high spatial-temporal dynamics in SNNs, neuromorphic chips are highly desired to execute SNNs in hardware-based neuron and synapse circuits directly. This paper presents a large-scale neuromorphic chip named Darwin3 with a novel instruction set architecture, which comprises 10 primary instructions and a few extended instructions. It supports flexible neuron model programming and local learning rule designs. The Darwin3 chip architecture is designed in a mesh of computing nodes with an innovative routing algorithm. We used a compression mechanism to represent synaptic connections, significantly reducing memory usage. The Darwin3 chip supports up to 2.35 million neurons, making it the largest of its kind on the neuron scale. The experimental results showed that the code density was improved by up to 28.3× in Darwin3, and that the neuron core fan-in and fan-out were improved by up to 4096× and 3072× by connection compression compared to the physical memory depth. Our Darwin3 chip also provided memory saving between 6.8× and 200.8× when mapping convolutional spiking neural networks onto the chip, demonstrating state-of-the-art performance in accuracy and latency compared to other neuromorphic chips.

Neuromorphic engineering

10.1093/nsr/nwae102

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A potential damage mechanism of rubberized cement under freeze-thaw cycle

Construction and Building Materials (2020)

Linxin Hua Feipeng Xiao Yitao Li Hongbin Huang Kewei Zhao

Brittleness

10.1016/j.conbuildmat.2020.119054

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Biophysical Impact of Multiple Surface Forcings on Land Surface Temperature Over Eastern China

Journal of Geophysical Research Atmospheres (2023)

Yitao Li Zhao‐Liang Li Hua Wu Xiangyang Liu Menglin Si

Abstract Over the past decades, human activities have directly or indirectly driven the land surface changes in eastern China. These anthropogenic forcings could trigger biochemical feedback and alter the surface biophysical properties, thus affecting local temperature. However, the latter is recognized as the “noise” and ignored when assessing historical or future climate. Here, we adopt the “observation minus reanalysis” (OMR) method to isolate the biophysical temperature footprint of multiple surface changes in eastern China over 2001–2018, using remote sensing land surface temperature and reanalysis skin temperature. A spatial regression model was used to separate the contributions from different processes. We find the biophysical feedbacks of surface changes have an annual cooling effect of −0.072 K/decade in eastern China, and the contributions from urban expansion, agricultural development, and natural vegetation greening are 0.042, −0.042, and −0.072 K/decade, correspondingly. The Northeast Plain shows agricultural activities induced cooling of −0.040 K/decade; the Loess Plateau shows natural vegetation recovery dominated cooling of −0.145 K/decade; the Huang‐Huai‐Hai Plain demonstrates a predominant urbanization warming effect of 0.124 K/decade; the Middle‐lower Yangtze shows natural vegetation greening related cooling of −0.106 K/decade. Both the intensity of the land surface changes and the temperature sensitivities drive the large spatial variability of the temperature effect. Overall, the temperature effects of surface changes are spatially heterogeneous and show considerable magnitudes. We emphasize that vegetation changes in eastern China show a strong surface cooling effect, and may contribute to the regional climate mitigation in the context of global warming.

Urban Heat Island

10.1029/2023jd039315

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Gut microbiota-bile acid crosstalk contributes to the rebound weight gain after calorie restriction in mice

Nature Communications (2022)

Mengci Li Shouli Wang Yitao Li Mingliang Zhao Junliang Kuang

Abstract Calorie restriction (CR) and fasting are common approaches to weight reduction, but the maintenance is difficult after resuming food consumption. Meanwhile, the gut microbiome associated with energy harvest alters dramatically in response to nutrient deprivation. Here, we reported that CR and high-fat diet (HFD) both remodeled the gut microbiota with similar microbial composition, Parabacteroides distasonis was most significantly decreased after CR or HFD. CR altered microbiota and reprogramed metabolism, resulting in a distinct serum bile acid profile characterized by depleting the proportion of non-12α-hydroxylated bile acids, ursodeoxycholic acid and lithocholic acid. Downregulation of UCP1 expression in brown adipose tissue and decreased serum GLP-1 were observed in the weight-rebound mice. Moreover, treatment with Parabacteroides distasonis or non-12α-hydroxylated bile acids ameliorated weight regain via increased thermogenesis. Our results highlighted the gut microbiota-bile acid crosstalk in rebound weight gain and Parabacteroides distasonis as a potential probiotic to prevent rapid post-CR weight gain.

10.1038/s41467-022-29589-7

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A Regional Zenith Tropospheric Delay (ZTD) Model Based on GPT3 and ANN

Remote Sensing (2021)

Fei Yang Jiming Guo Chaoyang Zhang Yitao Li Jun Li

The delays of radio signals transmitted by global navigation satellite system (GNSS) satellites and induced by neutral atmosphere, which are usually represented by zenith tropospheric delay (ZTD), are required as critical information both for GNSS positioning and navigation and GNSS meteorology. Establishing a stable and reliable ZTD model is one of the interests in GNSS research. In this study, we proposed a regional ZTD model that makes full use of the ZTD calculated from regional GNSS data and the corresponding ZTD estimated by global pressure and temperature 3 (GPT3) model, adopting the artificial neutral network (ANN) to construct the correlation between ZTD derived from GPT3 and GNSS observations. The experiments in Hong Kong using Satellite Positioning Reference Station Network (SatRet) were conducted and three statistical values, i.e., bias, root mean square error (RMSE), and compound relative error (CRE) were adopted for our comparisons. Numerical results showed that the proposed model outperformed the parameter ZTD model (Saastamoinen model) and the empirical ZTD model (GPT3 model), with an approximately 56%/52% and 52%/37% RMSE improvement in the internal and external accuracy verification, respectively. Moreover, the proposed method effectively improved the systematic deviation of GPT3 model and achieved better ZTD estimation in both rainy and rainless conditions.

Zenith

Precise Point Positioning

10.3390/rs13050838

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A Robust Framework for Resolution Enhancement of Land Surface Temperature by Combining Spatial Downscaling and Spatiotemporal Fusion Methods

IEEE Transactions on Geoscience and Remote Sensing (2023)

Yitao Li Hua Wu Hong Chen Xinming Zhu

Land surface temperature (LST) products with high spatial resolution and short revisiting cycles are crucial for environmental studies. However, due to the tradeoff between spatial and temporal resolutions of satellite observations, such data are not directly available. Spatial downscaling and spatiotemporal fusion methods are existing solutions for this problem, but their robustness is limited under different surface conditions. Here, we propose a Robust Framework for Combining Downscaling and spatiotemporal Fusion methods (RFCDF) to generate the synthesized daily high-resolution LST with high accuracy in different landscapes. RFCDF introduces a novel weighting strategy that determines pixel-level weights using an empirical function under the constraint of the image-level weights of two predictions. We implement the framework using the thermal sharpening algorithm (TsHARP) and Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) with Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Moderate Resolution Imaging Spectroradiometer (MODIS) data in Beijing and Baotou, as well as Landsat 8 and simulated coarse resolution imagery in nine sub-regions with different surface landscapes in Beijing. Our results demonstrate that RFCDF can generate more accurate estimations and preserve more spatial details than either individual or combination methods, improving accuracy by 0.1–0.6 K and 0.4–1.3 K in the two study areas, respectively. Moreover, the proposed framework is robust, reducing the root mean square error of estimations by 8-24% under different surface conditions. RFCDF can also generate dense high-resolution LST time series, which is crucial for studying the surface thermal environment at a finer scale.

Moderate-resolution imaging spectroradiometer

Robustness

Sensor Fusion

10.1109/tgrs.2023.3283614

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Biophysical impacts of earth greening can substantially mitigate regional land surface temperature warming

Nature Communications (2023)

Yitao Li Zhao-Liang Li Hua Wu Chenghu Zhou Xiangyang Liu

Abstract Vegetation change can alter surface energy balance and subsequently affect the local climate. This biophysical impact has been well studied for forestation cases, but the sign and magnitude for persistent earth greening remain controversial. Based on long-term remote sensing observations, we quantify the unidirectional impact of vegetation greening on radiometric surface temperature over 2001–2018. Here, we show a global negative temperature response with large spatial and seasonal variability. Snow cover, vegetation greenness, and shortwave radiation are the major driving factors of the temperature sensitivity by regulating the relative dominance of radiative and non-radiative processes. Combined with the observed greening trend, we find a global cooling of −0.018 K/decade, which slows down 4.6 ± 3.2% of the global warming. Regionally, this cooling effect can offset 39.4 ± 13.9% and 19.0 ± 8.2% of the corresponding warming in India and China. These results highlight the necessity of considering this vegetation-related biophysical climate effect when informing local climate adaptation strategies.

Shortwave radiation

10.1038/s41467-023-35799-4

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Citations (102)

Hyocholic acid species as novel biomarkers for metabolic disorders

Nature Communications (2021)

Xiaojiao Zheng Tianlu Chen Aihua Zhao Zhangchi Ning Junliang Kuang

Hyocholic acid (HCA) is a major bile acid (BA) species in the BA pool of pigs, a species known for its exceptional resistance to spontaneous development of diabetic phenotypes. HCA and its derivatives are also present in human blood and urine. We investigate whether human HCA profiles can predict the development of metabolic disorders. We find in the first cohort (n = 1107) that both obesity and diabetes are associated with lower serum concentrations of HCA species. A separate cohort study (n = 91) validates this finding and further reveals that individuals with pre-diabetes are associated with lower levels of HCA species in feces. Serum HCA levels increase in the patients after gastric bypass surgery (n = 38) and can predict the remission of diabetes two years after surgery. The results are replicated in two independent, prospective cohorts (n = 132 and n = 207), where serum HCA species are found to be strong predictors for metabolic disorders in 5 and 10 years, respectively. These findings underscore the association of HCA species with diabetes, and demonstrate the feasibility of using HCA profiles to assess the future risk of developing metabolic abnormalities.

Metabolic disorder

10.1038/s41467-021-21744-w

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Citations (107)