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.

Resequencing 50 accessions of cultivated and wild rice yields markers for identifying agronomically important genes

Abstract: Rice is a staple crop that has undergone substantial phenotypic and physiological changes during domestication. Here we resequenced the genomes of 40 cultivated accessions selected from the major groups of rice and 10 accessions of their wild progenitors (Oryza rufipogon and Oryza nivara) to >15 × raw data coverage. We investigated genome-wide variation patterns in rice and obtained 6.5 million high-quality single nucleotide polymorphisms (SNPs) after excluding sites with missing data in any accession. Using these population SNP data, we identified thousands of genes with significantly lower diversity in cultivated but not wild rice, which represent candidate regions selected during domestication. Some of these variants are associated with important biological features, whereas others have yet to be functionally characterized. The molecular markers we have identified should be valuable for breeding and for identifying agronomically important genes in rice.

Adaptive neural control of uncertain MIMO nonlinear systems

Abstract: In this paper, adaptive neural control schemes are proposed for two classes of uncertain multi-input/multi-output (MIMO) nonlinear systems in block-triangular forms. The MIMO systems consist of interconnected subsystems, with couplings in the forms of unknown nonlinearities and/or parametric uncertainties in the input matrices, as well as in the system interconnections without any bounding restrictions. Using the block-triangular structure properties, the stability analyses of the closed-loop MIMO systems are shown in a nested iterative manner for all the states. By exploiting the special properties of the affine terms of the two classes of MIMO systems, the developed neural control schemes avoid the controller singularity problem completely without using projection algorithms. Semiglobal uniform ultimate boundedness (SGUUB) of all the signals in the closed-loop of MIMO nonlinear systems is achieved. The outputs of the systems are proven to converge to a small neighborhood of the desired trajectories. The control performance of the closed-loop system is guaranteed by suitably choosing the design parameters. The proposed schemes offer systematic design procedures for the control of the two classes of uncertain MIMO nonlinear systems. Simulation results are presented to show the effectiveness of the approach.

Large-margin softmax loss for convolutional neural networks

Abstract: Cross-entropy loss together with softmax is arguably one of the most common used supervision components in convolutional neural networks (CNNs). Despite its simplicity, popularity and excellent performance, the component does not explicitly encourage discriminative learning of features. In this paper, we propose a generalized large-margin softmax (L-Softmax) loss which explicitly encourages intra-class compactness and inter-class separability between learned features. Moreover, L-Softmax not only can adjust the desired margin but also can avoid overfitting. We also show that the L-Softmax loss can be optimized by typical stochastic gradient descent. Extensive experiments on four benchmark datasets demonstrate that the deeply-learned features with L-softmax loss become more discriminative, hence significantly boosting the performance on a variety of visual classification and verification tasks.

A series of simple oligomer-like small molecules based on oligothiophenes for solution-processed solar cells with high efficiency.

Abstract: A series of acceptor-donor-acceptor simple oligomer-like small molecules based on oligothiophenes, namely, DRCN4T-DRCN9T, were designed and synthesized. Their optical, electrical, and thermal properties and photovoltaic performances were systematically investigated. Except for DRCN4T, excellent performances were obtained for DRCN5T-DRCN9T. The devices based on DRCN5T, DRCN7T, and DRCN9T with axisymmetric chemical structures exhibit much higher short-circuit current densities than those based on DRCN6T and DRCN8T with centrosymmetric chemical structures, which is attributed to their well-developed fibrillar network with a feature size less than 20 nm. The devices based on DRCN5T/PC71BM showed a notable certified power conversion efficiency (PCE) of 10.10% under AM 1.5G irradiation (100 mW cm(-2)) using a simple solution spin-coating fabrication process. This is the highest PCE for single-junction small-molecule-based organic photovoltaics (OPVs) reported to date. DRCN5T is a rather simpler molecule compared with all of the other high-performance molecules in OPVs to date, and this might highlight its advantage in the future possible commercialization of OPVs. These results demonstrate that a fine and balanced modification/design of chemical structure can make significant performance differences and that the performance of solution-processed small-molecule-based solar cells can be comparable to or even surpass that of their polymer counterparts.