79 research outputs found
Measurement of Mercury in Flue Gas Based on an Aluminum Matrix Sorbent
The measurement of total mercury in flue gas based on an economical aluminum matrix sorbent was developed in this paper. A sorbent trap consisted of three tubes was employed to capture Hg from flue gas. Hg trapped on sorbent was transferred into solution by acid leaching and then detected by CVAAS. Hg adsorbed on sorbent was recovered completely by leaching process. The 87.7% recovery of Hg in flue gas by tube 1 and tube 2 was obtained on the equipment of coal combustion and sampling in lab. In order to evaluate the ability to recover and accurately quantify Hg0 on the sorbent media, the analytical bias test on tube 3 spiked with Hg0 was also performed and got the average recovery of 97.1%. Mercury measurements based on this method were conducted for three coal-fired power plants in China. The mercury in coal is distributed into bottom ash, electrostatic precipitator (ESP) ash, wet flue gas desulfurization (WFGD) reactant, and flue gas, and the relative distribution varied depending on factors such as the coal type and the operation conditions of plants. The mercury mass balances of three plants were also calculated which were 91.6%, 77.1%, and 118%, respectively. The reliability of this method was verified by the Ontario Hydro (OH) method either in lab or in field
PanoVOS: Bridging Non-panoramic and Panoramic Views with Transformer for Video Segmentation
Panoramic videos contain richer spatial information and have attracted
tremendous amounts of attention due to their exceptional experience in some
fields such as autonomous driving and virtual reality. However, existing
datasets for video segmentation only focus on conventional planar images. To
address the challenge, in this paper, we present a panoramic video dataset,
PanoVOS. The dataset provides 150 videos with high video resolutions and
diverse motions. To quantify the domain gap between 2D planar videos and
panoramic videos, we evaluate 15 off-the-shelf video object segmentation (VOS)
models on PanoVOS. Through error analysis, we found that all of them fail to
tackle pixel-level content discontinues of panoramic videos. Thus, we present a
Panoramic Space Consistency Transformer (PSCFormer), which can effectively
utilize the semantic boundary information of the previous frame for pixel-level
matching with the current frame. Extensive experiments demonstrate that
compared with the previous SOTA models, our PSCFormer network exhibits a great
advantage in terms of segmentation results under the panoramic setting. Our
dataset poses new challenges in panoramic VOS and we hope that our PanoVOS can
advance the development of panoramic segmentation/tracking
Leveraging Multimodal Features and Item-level User Feedback for Bundle Construction
Automatic bundle construction is a crucial prerequisite step in various
bundle-aware online services. Previous approaches are mostly designed to model
the bundling strategy of existing bundles. However, it is hard to acquire
large-scale well-curated bundle dataset, especially for those platforms that
have not offered bundle services before. Even for platforms with mature bundle
services, there are still many items that are included in few or even zero
bundles, which give rise to sparsity and cold-start challenges in the bundle
construction models. To tackle these issues, we target at leveraging multimodal
features, item-level user feedback signals, and the bundle composition
information, to achieve a comprehensive formulation of bundle construction.
Nevertheless, such formulation poses two new technical challenges: 1) how to
learn effective representations by optimally unifying multiple features, and 2)
how to address the problems of modality missing, noise, and sparsity problems
induced by the incomplete query bundles. In this work, to address these
technical challenges, we propose a Contrastive Learning-enhanced Hierarchical
Encoder method (CLHE). Specifically, we use self-attention modules to combine
the multimodal and multi-item features, and then leverage both item- and
bundle-level contrastive learning to enhance the representation learning, thus
to counter the modality missing, noise, and sparsity problems. Extensive
experiments on four datasets in two application domains demonstrate that our
method outperforms a list of SOTA methods. The code and dataset are available
at https://github.com/Xiaohao-Liu/CLHE
Bismuth-induced phase control of GaAs nanowires grown by molecular beam epitaxy
In this work, the crystal structure of GaAs nanowires grown by molecular beam epitaxy has been tailored only by bismuth without changing the growth temperature and V/III flux ratio. The introduction of bismuth can lead to the formation of zinc-blende GaAs nanowires, while the removal of bismuth changes the structure into a 4H polytypism before it turns back to the wurtzite phase eventually. The theoretical calculation shows that it is the steadiest for bismuth to adsorb on the GaAs(111) B surface compared to the liquid gold catalyst surface and the interface between the gold catalyst droplet and the nanowire, and these adsorbed bismuth could decrease the diffusion length of adsorbed Ga and hence the supersaturation of Ga in the gold catalyst droplet. (C) 2014 AIP Publishing LLC
The Large Hadron-Electron Collider at the HL-LHC
The Large Hadron-Electron Collider (LHeC) is designed to move the field of deep inelastic scattering (DIS) to the energy and intensity frontier of particle physics. Exploiting energy-recovery technology, it collides a novel, intense electron beam with a proton or ion beam from the High-Luminosity Large Hadron Collider (HL-LHC). The accelerator and interaction region are designed for concurrent electron-proton and proton-proton operations. This report represents an update to the LHeC's conceptual design report (CDR), published in 2012. It comprises new results on the parton structure of the proton and heavier nuclei, QCD dynamics, and electroweak and top-quark physics. It is shown how the LHeC will open a new chapter of nuclear particle physics by extending the accessible kinematic range of lepton-nucleus scattering by several orders of magnitude. Due to its enhanced luminosity and large energy and the cleanliness of the final hadronic states, the LHeC has a strong Higgs physics programme and its own discovery potential for new physics. Building on the 2012 CDR, this report contains a detailed updated design for the energy-recovery electron linac (ERL), including a new lattice, magnet and superconducting radio-frequency technology, and further components. Challenges of energy recovery are described, and the lower-energy, high-current, three-turn ERL facility, PERLE at Orsay, is presented, which uses the LHeC characteristics serving as a development facility for the design and operation of the LHeC. An updated detector design is presented corresponding to the acceptance, resolution, and calibration goals that arise from the Higgs and parton-density-function physics programmes. This paper also presents novel results for the Future Circular Collider in electron-hadron (FCC-eh) mode, which utilises the same ERL technology to further extend the reach of DIS to even higher centre-of-mass energies.Peer reviewe
Nanofluids: synthesis, characterization and thermal conductivity
published_or_final_versionMechanical EngineeringDoctoralDoctor of Philosoph
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