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Institution

Dalian University of Technology

EducationDalian, China
About: Dalian University of Technology is a education organization based out in Dalian, China. It is known for research contribution in the topics: Catalysis & Finite element method. The organization has 60890 authors who have published 71921 publications receiving 1188356 citations. The organization is also known as: Dàlián Lǐgōng Dàxué.


Papers
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Journal ArticleDOI
TL;DR: This paper presents a discriminative appearance model based on superpixels, thereby facilitating a tracker to distinguish the target and the background with midlevel cues and facilitates foreground and background segmentation during tracking.
Abstract: While numerous algorithms have been proposed for object tracking with demonstrated success, it remains a challenging problem for a tracker to handle large appearance change due to factors such as scale, motion, shape deformation, and occlusion. One of the main reasons is the lack of effective image representation schemes to account for appearance variation. Most of the trackers use high-level appearance structure or low-level cues for representing and matching target objects. In this paper, we propose a tracking method from the perspective of midlevel vision with structural information captured in superpixels. We present a discriminative appearance model based on superpixels, thereby facilitating a tracker to distinguish the target and the background with midlevel cues. The tracking task is then formulated by computing a target-background confidence map, and obtaining the best candidate by maximum a posterior estimate. Experimental results demonstrate that our tracker is able to handle heavy occlusion and recover from drifts. In conjunction with online update, the proposed algorithm is shown to perform favorably against existing methods for object tracking. Furthermore, the proposed algorithm facilitates foreground and background segmentation during tracking.

311 citations

Journal ArticleDOI
TL;DR: Thermal stability of CO2 adducts of N-heterocyclic carbenes (NHCs) was studied by means of in situ FTIR method with monitoring of the nu(CO2) region of the infrared spectra under various conditions, and the relatively unstable IPr-CO2 exhibits the highest catalytic activity.
Abstract: Thermal stability of CO2 adducts of N-heterocyclic carbenes (NHCs) was studied by means of in situ FTIR method with monitoring of the nu(CO2) region of the infrared spectra under various conditions. 1,3-Bis(2,6-diisopropylphenyl)imidazolinium-2-carboxylate (SIPr-CO2) shows higher thermal stability compared with 1,3-bis(2,6-diisopropylphenyl)imidazolium-2-carboxylate (IPr-CO2). The presence of free CO2 can significantly inhibit the decomposition of NHC-CO2 adducts, while the addition of an epoxide such as propylene oxide has a negative effect on stabilizing these adducts. As zwitterionic compounds, NHC-CO2 adducts were also proved to be effective organic catalysts for the coupling reaction of CO2 and epoxides to afford cyclic carbonates, for which a possible mechanism was proposed. Among these NHC-CO2 adducts, the relatively unstable IPr-CO2 exhibits the highest catalytic activity. The presence of an electrophile such as SalenAlEt could greatly improve the catalytic activity of IPr-CO2 due to intermolecular cooperative catalysis of the binary components.

310 citations

Proceedings ArticleDOI
07 Jun 2015
TL;DR: A bootstrap learning algorithm for salient object detection in which both weak and strong models are exploited and a strong classifier based on samples directly from an input image is learned to detect salient pixels.
Abstract: We propose a bootstrap learning algorithm for salient object detection in which both weak and strong models are exploited. First, a weak saliency map is constructed based on image priors to generate training samples for a strong model. Second, a strong classifier based on samples directly from an input image is learned to detect salient pixels. Results from multiscale saliency maps are integrated to further improve the detection performance. Extensive experiments on six benchmark datasets demonstrate that the proposed bootstrap learning algorithm performs favorably against the state-of-the-art saliency detection methods. Furthermore, we show that the proposed bootstrap learning approach can be easily applied to other bottom-up saliency models for significant improvement.

310 citations

Journal ArticleDOI
TL;DR: Limits to treatment efficiencies with actual wastewaters caused by solution conductivity compared to laboratory experiments under more optimal conditions are demonstrated.
Abstract: Increased interest in sustainable agriculture and bio-based industries requires that we find more energy-efficient methods for treating cellulose-containing wastewaters. We examined the effectiveness of simultaneous electricity production and treatment of a paper recycling plant wastewater using microbial fuel cells. Treatment efficiency was limited by wastewater conductivity. When a 50 mM phosphate buffer solution (PBS, 5.9 mS/cm) was added to the wastewater, power densities reached 501 ± 20 mW/m2, with a coulombic efficiency of 16 ± 2%. There was efficient removal of soluble organic matter, with 73 ± 1% removed based on soluble chemical oxygen demand (SCOD) and only slightly greater total removal (76 ± 4%) based on total COD (TCOD) over a 500-h batch cycle. Cellulose was nearly completely removed (96 ± 1%) during treatment. Further increasing the conductivity (100 mM PBS) increased power to 672 ± 27 mW/m2. In contrast, only 144 ± 7 mW/m2 was produced using an unamended wastewater (0.8 mS/cm) with TCOD, SCOD, and cellulose removals of 29 ± 1%, 51 ± 2%, and 16 ± 1% (350-h batch cycle). These results demonstrate limitations to treatment efficiencies with actual wastewaters caused by solution conductivity compared to laboratory experiments under more optimal conditions.

308 citations

Journal ArticleDOI
TL;DR: The strategy of "barrier-free rotation" provides a new platform for future design of PTT agents for clinical cancer treatment and can lead to complete tumor ablation in tumor-bearing mice after intravenous injection of tfm-BDP NPs.
Abstract: Traditional photothermal therapy requires high-intensity laser excitation for cancer treatments due to the low photothermal conversion efficiency (PCE) of photothermal agents (PTAs). PTAs with ultra-high PCEs can decrease the required excited light intensity, which allows safe and efficient therapy in deep tissues. In this work, a PTA is synthesized with high PCE of 88.3% based on a BODIPY scaffold, by introducing a CF3 "barrier-free" rotor on the meso-position (tfm-BDP). In both the ground and excited state, the CF3 moiety in tfm-BDP has no energy barrier to rotation, allowing it to efficiently dissipate absorbed (NIR) photons as heat. Importantly, the barrier-free rotation of CF3 can be maintained after encapsulating tfm-BDP into polymeric nanoparticles (NPs). Thus, laser irradiation with safe intensity (0.3 W cm-2 , 808 nm) can lead to complete tumor ablation in tumor-bearing mice after intravenous injection of tfm-BDP NPs. This strategy of "barrier-free rotation" provides a new platform for future design of PTT agents for clinical cancer treatment.

308 citations


Authors

Showing all 61205 results

NameH-indexPapersCitations
Yang Yang1712644153049
Yury Gogotsi171956144520
Hui Li1352982105903
Michael I. Posner134414104201
Anders Hagfeldt12960079912
Jian Zhou128300791402
Chao Zhang127311984711
Bin Wang126222674364
Chi Lin1251313102710
Tao Zhang123277283866
Bo Wang119290584863
Zhenyu Zhang118116764887
Liang Cheng116177965520
Anthony G. Fane11256540904
Xuelong Li110104446648
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023167
2022836
20216,974
20206,457
20196,261
20185,375