A5078257410- Remote Sensing in Agriculture
- Air Quality and Health Impacts
- Air Quality Monitoring and Forecasting
- Atmospheric chemistry and aerosols
- Bioinformatics and Genomic Networks
- Gene Regulatory Network Analysis
- Remote-Sensing Image Classification
- Microbial Metabolic Engineering and Bioproduction
- Land Use and Ecosystem Services
- Marine and coastal ecosystems
- Climate Change and Health Impacts
- Plant Water Relations and Carbon Dynamics
- Time Series Analysis and Forecasting
- Leaf Properties and Growth Measurement
- Semantic Web and Ontologies
- Scientific Computing and Data Management
- Climate change impacts on agriculture
- Gene expression and cancer classification
- Spectroscopy and Chemometric Analyses
- Fire effects on ecosystems
- Bladder and Urothelial Cancer Treatments
- Cancer Immunotherapy and Biomarkers
- Computational Physics and Python Applications
- Remote Sensing and LiDAR Applications
- Inflammatory Biomarkers in Disease Prognosis
Xi'an Jiaotong University
2022-2024
University of Pittsburgh
2018-2024
Guangzhou Medical University
2022
Second Affiliated Hospital of Guangzhou Medical University
2022
First Affiliated Hospital of Guangzhou Medical University
2022
China University of Geosciences (Beijing)
2017-2021
University of Waterloo
2019-2021
Chinese People's Armed Police Force Engineering University
2021
Beijing Jiaotong University
2020
Heavy metal stress in crops is a worldwide problem that requires accurate and timely monitoring. This study aimed to improve the accuracy of monitoring heavy levels rice by using multiple Sentinel-2 images. The selected areas are Zhuzhou City, Hunan Province, China. Six images were acquired 2017, concentrations soil measured. A novel vegetation index called sensitive (HMSSI) was proposed. HMSSI ratio between two red-edge spectral indices, namely chlorophyll (CIred-edge) plant senescence...
Precise simulation of crop growth is crucial to yield estimation, agricultural field management, and climate change. Although assimilation model remote sensing data has been applied in simulation, few studies have considered optimizing the with respect phenology. In this study, we assimilated phenological information obtained from Moderate Resolution Imaging Spectroradiometer (MODIS) time series into World Food Study (WOFOST) improve accuracy rice at regional scale. The particle swarm...
Multisource satellite images provide abundant and complementary earth observations, while nonlinear radiometric geometric distortions (such as scale rotation variations) between these multimodal pose remarkable challenges for further remote sensing applications, such change detection. We therefore proposed a template matching algorithm based on self-attention interactive fusion network, named SIFNet, to align multisource images. First, feature pyramid network was first conducted extract...
Remote sensing reflectance (Rrs) is an essential parameter in ocean color remote and a fundamental input for the estimation of elements. Predicting Rrs has potential to enable simultaneous prediction multiple marine environmental parameters, facilitating multi-perspective analysis changes. This paper proposes spatiotemporal attention-augmented ConvLSTM-based model prediction. The developed can predict up seven days by simultaneously learning features from time series auxiliary variables....
Timely assessment of crop growth conditions under heavy metal pollution is great significance for agricultural decision-making and estimation productivity. The object this study to assess the effects stress on physiological functions rice through spatial-temporal analysis fraction absorbed photosynthetically active radiation (FAPAR). calculation daily FAPAR conducted based a coupled model consisting leaf-canopy radiative transfer World Food Study Model (WOFOST). These two models are...
New discoveries and knowledge are summarized in thousands of published papers per year scientific domain, making it incomprehensible for scientists to account all available relevant their studies. In this paper, we present ACCORDION ( ACC elerating O ptimizing model R ecommen D at ION s), a novel methodology an expert system that retrieves selects from literature databases recommend models with correct structure accurate behavior, enabling mechanistic explanations predictions, advancing...
Due to the molecular heterogeneity, most bladder cancer (BLCA) patients show no pathological responses immunotherapy and chemotherapy yet suffer from their toxicity. This study identified validated three distinct stable clusters of BLCA in cross-platform databases based on personalized immune inflammatory characteristics. H&E-stained histopathology images confirmed infiltration cells among clusters. Cluster-A was characterized by a favorable prognosis low but showed highest abundance...
Carbon sequestration reflecting vegetation productivity is essential for global carbon cycle and terrestrial ecosystems. Exploring the spatial temporal variation of corresponding ecological values yields insights policy formulation to mitigate emission achieve neutrality. Hence, taking Shaanxi China as case study, we developed an integrated index (named C-GDP) based on estimated by CASA model prices acquired from trading market in explore tradeoffs between economic development. The...
Satellite-derived Chlorophyll-a concentration (Chla) time series products are essential for large-scale marine environmental monitoring. However, the plenty of missing pixels in current satellite Chla severely hinder their applications research, due to cloud contamination, solar glint, and unfavorable observation conditions. This study proposed a gap-filling method MODIS 8-day composite product by integrating spatiotemporal information (STGF). employed spatially neighboring with similar...
Forecast of passenger flow in holidays plays an important role controlling for the urban rail transit operation department. It can effectively guide department to make a good plan advance, and formulate implement appropriate management organization based on forecast. Different forecasting models are suitable different scenarios. By comparing characteristics analyzing at stations during holidays, forecast model holiday support vector machine is constructed. At last, prediction Chengdu Metro...
Monitoring and classifying disturbed forests can provide information support for not only sustainable forest management but also global carbon sequestration assessments. In this study, we propose an autoencoder-based model disturbance detection, which considers disturbances as anomalous events in temporal trajectories. The autoencoder network is established trained to reconstruct intact Then, the detection threshold derived by Tukey's method based on reconstruction error of trajectory....
Ambient suspended fine particulate matter (PM2.5) is a greatest environmental risk factor for premature mortality. We adopted aerosol optical depth (AOD) retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument to produce annual-mean PM2.5 concentrations 2012 2017 with spatial resolution of 3km. A geographically weighted regression model was conducted using vertical- and hydroscopic-corrected AOD meteorological data. The estimates were validated by ground...
Computational modeling seeks to construct and simulate intracellular signaling networks understand health disease. The scientific literature contains descriptions of experimental results that can be interpreted by machines using NLP or LLMs itemize molecular interactions. This machine readable output then used assess, update improve existing biological models if there is a tool for comparing the model with information extracted from papers. Here we describe VIOLIN classifying outputs...
A bstract The BioRECIPE (Biological system Representation for Evaluation, Curation, Interoperability, Preserving, and Execution) knowledge representation format was introduced to facilitate seamless human-machine interaction while creating, verifying, evaluating, curating, expanding executable models of intra- intercellular signaling. This allows a human user easily preview modify any model component, it is at the same time readable by machines can be processed suite development analysis...
Accurate assessment of Fraction Absorbed Photosynthetically Active Radiation (FAPAR) in large scale is significant for crop productivity estimation and climate change analysis. The object study to simulate FAPAR the rice growth period exploring photosynthetic capacity large-scale. daily calculated based on a coupled model consisting leaf-canopy radiative transfer (PROSAIL) World Food Study Model (WOFOST). Due limitation PROSAIL WOFOST model, we introduced remote sensing data assimilation...
Understanding sensitivity is an important step to study system robustness and adaptability. In this work, we model investigate intra-cellular networks via discrete modeling approach, which assigns a set of values deterministic update rule each element. The models can be analyzed formally or simulated in stochastic manner. We propose comprehensive framework these models. the framework, define element influence (activity) with respect state distribution modeled system. Previous analysis...
The large amount of knowledge contained in the scientific literature can be mined using natural language processing and utilized to automatically construct models complex networks order obtain a greater understanding systems. In this paper, we describe Dynamic System Explanation (DySE) framework, which configures hybrid executes simulations over time, relying on granular computing approach range different element update functions. A standardized tabular format assembles collected into for...
Abstract New discoveries and knowledge are summarized in thousands of published papers per year scientific domain, making it incomprehensible for scientists to account all available relevant their studies. In this paper, we present ACCORDION ( ACC elerating O ptimizing model R ecommen D at ION s), a novel methodology an expert system that retrieves selects from literature databases recommend models with correct structure accurate behavior, enabling mechanistic explanations predictions,...
High carbon emissions (CE) have unbalanced the cycle patterns on Earth, resulting in global warming and extreme weather events. However, disparity inequalities of barely been explored from environmental justice perspective, which can help to formulate a more equitable policy. Therefore, satellite-based ODIAC dataset was adopted first analyze spatiotemporal characteristics CE China between 2010 2019; then spatial disparities were during study period. The results show that increased by 13.74%...