• Publications
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Primary air pollutant emissions of coal-fired power plants in China: Current status and future prediction
Abstract To explore the atmospheric emissions of coal-fired power sector in China, a unit-based method was developed based on detailed information of unit type, fuel quality, emission controlExpand
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PLGA nanoparticles simultaneously loaded with vincristine sulfate and verapamil hydrochloride: systematic study of particle size and drug entrapment efficiency.
PLGA nanoparticles simultaneously loaded with vincristine sulfate (VCR) and verapamil hydrochloride (VRP) were prepared via combining O/W emulsion solvent evaporation and salting-out method. TenExpand
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Investigation on Single-Mode-Multimode-Single-Mode Fiber Structure
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Supervised Dictionary Learning for Inferring Concurrent Brain Networks
TLDR
In this paper, we propose a novel supervised dictionary learning and sparse coding method for inferring functional networks from tfMRI data, which takes both of the advantages of model- driven method and data-driven method. Expand
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Boron-doped carbon nanotubes as metal-free electrocatalysts for the oxygen reduction reaction.
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Surface chemistry and corrosion behaviour of 304 stainless steel in simulated seawater containing inorganic sulphide and sulphate-reducing bacteria
Abstract Although many studies have been carried out regarding the role of sulphide anions in promoting microbial corrosion of various metal substrates, very little is known about the differencesExpand
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Surface characterization and performance evaluation of commercial fouling resistant low-pressure RO membranes
This paper describes the characterization and evaluation of various RO/NF membranes for the treatment of seasonally brackish surface water with high organic contents (TOC ≈21 mg/L). TwentyExpand
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Automatic Recognition of fMRI-Derived Functional Networks Using 3-D Convolutional Neural Networks
  • Yu Zhao, Qinglin Dong, +7 authors T. Liu
  • Computer Science, Medicine
  • IEEE Transactions on Biomedical Engineering
  • 1 September 2018
TLDR
We design, apply, and evaluate a deep 3-D CNN framework for automatic, effective, and accurate classification and recognition of large number of functional brain networks reconstructed by sparse representation of whole-brain fMRI signals. Expand
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Modeling 4D fMRI Data via Spatio-Temporal Convolutional Neural Networks (ST-CNN)
  • Yu Zhao, Xiang Li, +5 authors T. Liu
  • Computer Science
  • MICCAI
  • 31 May 2018
TLDR
We propose a deep spatiotemporal convolutional neural network (ST-CNN) to model the spatio-temporal variation patterns of brain functional network from 4D fMRI data. Expand
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Synergistic Mercury Removal by Conventional Pollutant Control Strategies for Coal-Fired Power Plants in China
Abstract China’s 11th 5-yr plan has regulated total sulfur dioxide (SO2) emissions by installing flue gas desulfurization (FGD) devices and shutting down small thermal power units. These controlExpand
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