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Institution

Sichuan University

EducationChengdu, China
About: Sichuan University is a education organization based out in Chengdu, China. It is known for research contribution in the topics: Population & Catalysis. The organization has 107623 authors who have published 102844 publications receiving 1612131 citations. The organization is also known as: Sìchuān Dàxué.


Papers
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Journal ArticleDOI
TL;DR: The index of local Moran's I is a useful tool for identifying pollution hotspots of Pb pollution in urban soils, and for classifying them into spatial clusters and spatial outliers, but it is hard to decide the best way of using this index.

284 citations

Journal ArticleDOI
TL;DR: In this consensus reaching model, a selection process is proposed to obtain the individual preference vectors, to divide decision makers into different clusters, and to yield the preference vector of the large group.
Abstract: Nowadays, societal and technological trends demand the management of large scale of decision makers in group decision-making (GDM) contexts. In a large-scale GDM, decision makers often have individual concerns and satisfactions, and also they will use heterogeneous preference representation structures to express their preferences. Meanwhile, it is difficult to set the numerical consensus threshold to judge whether a consensus degree can be acceptable or not in the consensus reaching process in a large-scale GDM. This study proposes a novel consensus reaching model for the heterogeneous large-scale GDM with the individual concerns and satisfactions. In this consensus reaching model, a selection process is proposed to obtain the individual preference vectors, to divide decision makers into different clusters, and to yield the preference vector of the large group. Following this, a consensus measure method that considers the individual concerns on alternatives is defined for measuring the consensus degree, and a linguistic approach is developed to measure the individual and collective satisfactions regarding the consensus degree. Finally, a feedback adjustment process is proposed and utilized to help decision makers adjust their preferences. A practical example and a simulation analysis are presented to demonstrate the validity of the proposed consensus reaching model.

284 citations

Journal ArticleDOI
TL;DR: A relationship between functional connectivity and disease severity was found in specific regions of RSNs, including medial and lateral prefrontal cortex, as well as parietal and occipital regions.

284 citations

Journal ArticleDOI
TL;DR: These understandings would help researchers to further uncover the underlying mechanisms and interactions in nano-CaP stem cell constructs in vitro and in vivo, tailor nano- CaP composite construct design and stem cell type selection to enhance cell function and bone regeneration, and translate laboratory findings to clinical treatments.
Abstract: Tissue engineering is promising to meet the increasing need for bone regeneration. Nanostructured calcium phosphate (CaP) biomaterials/scaffolds are of special interest as they share chemical/crystallographic similarities to inorganic components of bone. Three applications of nano-CaP are discussed in this review: nanostructured calcium phosphate cement (CPC); nano-CaP composites; and nano-CaP coatings. The interactions between stem cells and nano-CaP are highlighted, including cell attachment, orientation/morphology, differentiation and in vivo bone regeneration. Several trends can be seen: (i) nano-CaP biomaterials support stem cell attachment/proliferation and induce osteogenic differentiation, in some cases even without osteogenic supplements; (ii) the influence of nano-CaP surface patterns on cell alignment is not prominent due to non-uniform distribution of nano-crystals; (iii) nano-CaP can achieve better bone regeneration than conventional CaP biomaterials; (iv) combining stem cells with nano-CaP accelerates bone regeneration, the effect of which can be further enhanced by growth factors; and (v) cell microencapsulation in nano-CaP scaffolds is promising for bone tissue engineering. These understandings would help researchers to further uncover the underlying mechanisms and interactions in nano-CaP stem cell constructs in vitro and in vivo, tailor nano-CaP composite construct design and stem cell type selection to enhance cell function and bone regeneration, and translate laboratory findings to clinical treatments.

284 citations

Journal ArticleDOI
Kai Li1, Zuojia Li1, Kui Feng1, Xiaopeng Xu1, Lingyan Wang1, Qiang Peng1 
TL;DR: The synthesis and characterization of two conjugated copolymers, PBD TFBZO and PBDTFBZS, consisting of dialkylthiol substituted benzo[1,2-b:4,5-b']dithiophene donor and monofluorinated benzotriazole acceptor blocks are demonstrated, indicating that they are promising polymer donor materials for future application of large-area polymer solar cells.
Abstract: We demonstrated the synthesis and characterization of two conjugated copolymers, PBDTFBZO and PBDTFBZS, consisting of dialkylthiol substituted benzo[1,2-b:4,5-b′]dithiophene donor and monofluorinated benzotriazole acceptor blocks. The resulting copolymers show large band gaps, deep HOMO and LUMO energy levels. Improved Voc, Jsc, and FF were obtained at the same time to increase overall efficiencies of their single and tandem polymer solar cells. The enhanced Voc can be ascribed to a low-lying HOMO energy level by incorporating dialkylthiol and fluorine substituents on the polymer backbone. The improvement in Jsc and FF are likely due to high carrier mobility, suppressed charge recombination, and fine nanostructure morphology. A 7.74% PCE was achieved from the regular single device based on PBDTFBZS:PC71BM blend film with 3% 1,8-diiodooctane (DIO) additive. In combination with low band gap diketopyrrolopyrrole (DPP)-based copolymer, tandem devices based on PBDTFBZS exhibited high PCE up to 9.40%. The resul...

283 citations


Authors

Showing all 108474 results

NameH-indexPapersCitations
Jie Zhang1784857221720
Robin M. Murray1711539116362
Xiang Zhang1541733117576
Rui Zhang1512625107917
Xiaoyuan Chen14999489870
Yi Yang143245692268
Xinliang Feng13472173033
Chuan He13058466438
Lei Zhang130231286950
Jian Zhou128300791402
Shaobin Wang12687252463
Yi Xie12674562970
Pak C. Sham124866100601
Wei Chen122194689460
Bo Wang119290584863
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023339
20221,712
202113,846
202011,702
20199,714
20187,906