South China University of Technology

About: South China University of Technology is a education organization based out in Guangzhou, China. It is known for research contribution in the topics: Catalysis & Adsorption. The organization has 62343 authors who have published 69468 publications receiving 1251592 citations. The organization is also known as: SCUT & Huánán Lǐgōng Dàxué.

Synthesis and luminescence mechanism of multicolor-emitting g-C3N4 nanopowders by low temperature thermal condensation of melamine

Abstract: Graphite like C3N4 (g-C3N4) was synthesized facilely via the low temperature thermal condensation of melamine between 300–650°C The results showed that the products maintained as melamine when the temperature is below 300°C With the increase of temperature, the products were transformed into carbon nitride and amorphous g-C3N4 successively The morphology of products was changed from spherical nanoparticles of melamine into layer carbon nitride and g-C3N4 with the increase of temperature The photoluminescence spectra showed that the carbon nitride products have continuous tunable photoluminescence properties in the visible region with increasing temperature With the help of steady state, transient state time-resolved photoluminescence spectra and Raman microstructural characterization, a novel tunable photoluminescence mechanism was founded systematically, which is mainly related to the two dimensional π-conjugated polymeric network and the lone pair of the carbon nitride

Characterization of Lignin Structures and Lignin–Carbohydrate Complex (LCC) Linkages by Quantitative 13C and 2D HSQC NMR Spectroscopy

Abstract: To characterize the lignin structures and lignin-carbohydrate complex (LCC) linkages, milled wood lignin (MWL) and mild acidolysis lignin (MAL) with a high content of associated carbohydrates were sequentially isolated from ball-milled poplar wood. Quantification of their structural features has been achieved by using a combination of quantitative (13)C and 2D HSQC NMR techniques. The results showed that acetylated 4-O-methylgluconoxylan is the main carbohydrate associated with lignins, and acetyl groups frequently acylate the C2 and C3 positions. MWL and MAL exhibited similar structural features. The main substructures were β-O-4' aryl ether, resinol, and phenylcoumaran, and their abundances per 100 Ar units changed from 41.5 to 43.3, from 14.6 to 12.7, and from 3.7 to 4.0, respectively. The S/G ratios were estimated to be 1.57 and 1.62 for MWL and MAL, respectively. Phenyl glycoside and benzyl ether LCC linkages were clearly quantified, whereas the amount of γ-ester LCC linkages was ambiguous for quantification.

Integrated Profiling of MicroRNAs and mRNAs: MicroRNAs Located on Xq27.3 Associate with Clear Cell Renal Cell Carcinoma

Abstract: Background With the advent of second-generation sequencing, the expression of gene transcripts can be digitally measured with high accuracy. The purpose of this study was to systematically profile the expression of both mRNA and miRNA genes in clear cell renal cell carcinoma (ccRCC) using massively parallel sequencing technology. Methodology The expression of mRNAs and miRNAs were analyzed in tumor tissues and matched normal adjacent tissues obtained from 10 ccRCC patients without distant metastases. In a prevalence screen, some of the most interesting results were validated in a large cohort of ccRCC patients. Principal Findings A total of 404 miRNAs and 9,799 mRNAs were detected to be differentially expressed in the 10 ccRCC patients. We also identified 56 novel miRNA candidates in at least two samples. In addition to confirming that canonical cancer genes and miRNAs (including VEGFA, DUSP9 and ERBB4; miR-210, miR-184 and miR-206) play pivotal roles in ccRCC development, promising novel candidates (such as PNCK and miR-122) without previous annotation in ccRCC carcinogenesis were also discovered in this study. Pathways controlling cell fates (e.g., cell cycle and apoptosis pathways) and cell communication (e.g., focal adhesion and ECM-receptor interaction) were found to be significantly more likely to be disrupted in ccRCC. Additionally, the results of the prevalence screen revealed that the expression of a miRNA gene cluster located on Xq27.3 was consistently downregulated in at least 76.7% of ~50 ccRCC patients. Conclusions Our study provided a two-dimensional map of the mRNA and miRNA expression profiles of ccRCC using deep sequencing technology. Our results indicate that the phenotypic status of ccRCC is characterized by a loss of normal renal function, downregulation of metabolic genes, and upregulation of many signal transduction genes in key pathways. Furthermore, it can be concluded that downregulation of miRNA genes clustered on Xq27.3 is associated with ccRCC.

Graph Convolutional Networks for Temporal Action Localization

Abstract: Most state-of-the-art action localization systems process each action proposal individually, without explicitly exploiting their relations during learning. However, the relations between proposals actually play an important role in action localization, since a meaningful action always consists of multiple proposals in a video. In this paper, we propose to exploit the proposal-proposal relations using GraphConvolutional Networks (GCNs). First, we construct an action proposal graph, where each proposal is represented as a node and their relations between two proposals as an edge. Here, we use two types of relations, one for capturing the context information for each proposal and the other one for characterizing the correlations between distinct actions. Then we apply the GCNs over the graph to model the relations among different proposals and learn powerful representations for the action classification and localization. Experimental results show that our approach significantly outperforms the state-of-the-art on THUMOS14(49.1% versus 42.8%). Moreover, augmentation experiments on ActivityNet also verify the efficacy of modeling action proposal relationships.