Sun Yat-sen University

About: Sun Yat-sen University is a education organization based out in Guangzhou, Guangdong, China. It is known for research contribution in the topics: Population & Cancer. The organization has 115149 authors who have published 113763 publications receiving 2286465 citations. The organization is also known as: Zhongshan University & SYSU.

N-, O-, and S-Tridoped Carbon-Encapsulated Co9S8 Nanomaterials: Efficient Bifunctional Electrocatalysts for Overall Water Splitting

Abstract: The development of highly active and stable earth-abundant catalysts to reduce or eliminate the reliance on noble-metal based ones in green and sustainable (electro)chemical processes is nowadays of great interest. Here, N-, O-, and S-tridoped carbon-encapsulated Co9S8 (Co9S8@NOSC) nanomaterials are synthesized via simple pyrolysis of S- and Co(II)-containing polypyrrole solid precursors, and the materials are proven to serve as noble metal-free bifunctional electrocatalysts for water splitting in alkaline medium. The nanomaterials exhibit remarkable catalytic performances for oxygen evolution reaction in basic electrolyte, with small overpotentials, high anodic current densities, low Tafel slopes as well as very high (nearly 100%) Faradic efficiencies. Moreover, the materials are found to efficiently electrocatalyze hydrogen evolution reaction in acidic as well as basic solutions, showing high activity in both cases and maintaining good stability in alkaline medium. A two-electrode electrolyzer assembled using the material synthesized at 900 °C (Co9S8@NOSC-900) as an electrocatalyst at both electrodes gives current densities of 10 and 20 mA cm−2 at potentials of 1.60 and 1.74 V, respectively. The excellent electrocatalytic activity exhibited by the materials is proposed to be mainly due to the synergistic effects between the Co9S8 nanoparticles cores and the heteroatom-doped carbon shells in the materials.

Genomes of the rice pest brown planthopper and its endosymbionts reveal complex complementary contributions for host adaptation

Abstract: The brown planthopper, Nilaparvata lugens, the most destructive pest of rice, is a typical monophagous herbivore that feeds exclusively on rice sap, which migrates over long distances. Outbreaks of it have re-occurred approximately every three years in Asia. It has also been used as a model system for ecological studies and for developing effective pest management. To better understand how a monophagous sap-sucking arthropod herbivore has adapted to its exclusive host selection and to provide insights to improve pest control, we analyzed the genomes of the brown planthopper and its two endosymbionts. We describe the 1.14 gigabase planthopper draft genome and the genomes of two microbial endosymbionts that permit the planthopper to forage exclusively on rice fields. Only 40.8% of the 27,571 identified Nilaparvata protein coding genes have detectable shared homology with the proteomes of the other 14 arthropods included in this study, reflecting large-scale gene losses including in evolutionarily conserved gene families and biochemical pathways. These unique genomic features are functionally associated with the animal’s exclusive plant host selection. Genes missing from the insect in conserved biochemical pathways that are essential for its survival on the nutritionally imbalanced sap diet are present in the genomes of its microbial endosymbionts, which have evolved to complement the mutualistic nutritional needs of the host. Our study reveals a series of complex adaptations of the brown planthopper involving a variety of biological processes, that result in its highly destructive impact on the exclusive host rice. All these findings highlight potential directions for effective pest control of the planthopper.

A DWT-DFT composite watermarking scheme robust to both affine transform and JPEG compression

Abstract: Robustness is a crucially important issue in watermarking. Robustness against geometric distortion and JPEG compression at the same time with blind extraction remains especially challenging. A blind discrete wavelet transform-discrete Fourier transform (DWT-DFT) composite image watermarking algorithm that is robust against both affine transformation and JPEG compression is proposed. The algorithm improves robustness by using a new embedding strategy, watermark structure, 2D interleaving, and synchronization technique. A spread-spectrum-based informative watermark with a training sequence is embedded in the coefficients of the LL subband in the DWT domain while a template is embedded in the middle frequency components in the DFT domain. In watermark extraction, we first detect the template in a possibly corrupted watermarked image to obtain the parameters of an affine transform and convert the image back to its original shape. Then, we perform translation registration using the training sequence embedded in the DWT domain, and, finally, extract the informative watermark. Experimental work demonstrates that the proposed algorithm generates a more robust watermark than other reported watermarking algorithms. Specifically it is robust simultaneously against almost all affine transform related testing functions in StirMark 3.1 and JPEG compression with quality factor as low as 10. While the approach is presented for gray-level images, it can also be applied to color images and video sequences.