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Lysine succinylation is a typical protein post-translational modification and plays a crucial role of regulation in the cellular process. Identifying succinylation sites is fundamental to explore its functions. Although many computational methods were developed to deal with this challenge, few considered semantic relationship between residues. We combined long short-term memory (LSTM) and convolutional neural network (CNN) into a deep learning method for predicting succinylation site. The proposed method obtained a Matthews correlation coefficient of 0.2508 on the independent test, outperforming state of the art methods. We also performed the enrichment analysis of succinylation proteins. The results showed that functions of succinylation were conserved across species but differed to a certain extent with species. On basis of the proposed method, we developed a user-friendly web server for predicting succinylation sites.

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Abstract. The AHS (Airborne Hyperspectral Scanner) instrument has 80 spectral bands covering the visible and near infrared (VNIR), short wave infrared (SWIR), mid infrared (MIR) and thermal infrared (TIR) spectral range. The instrument is operated by Instituto Nacional de Técnica Aerospacial (INTA), and it has been involved in several field campaigns since 2004.This paper presents an overview of the work performed with the AHS thermal imagery provided in the framework of the SPARC and SEN2FLEX campaigns, carried out respectively in 2004 and 2005 over an agricultural area in Spain. The data collected in both campaigns allowed for the first time the development and testing of algorithms for land surface temperature and emissivity retrieval as well as the estimation of evapotranspiration from AHS data. Errors were found to be around 1.5 K for land surface temperature and 1 mm/day for evapotranspiration.

With the rapid development of micro‐electromechanical systems (MEMS), micro/nanoscale fabrication of 3D metallic structures with complex structures and multifunctions is becoming more and more important due to the recent trend of product miniaturization. As a promising micromanufacturing approach based on plastic deformation, micro/nanoforming shows the attractive advantages of high productivity, low cost, near‐net‐shape, and excellent mechanical properties, compared with other non‐silicon‐based micromanufacturing technologies. However, micro/nanoforming is far less established due to the so‐called size effects in terms of materials models, process laws, tooling design, etc. The understanding of basic issues on micro/nanoforming is not yet mature, and it is currently a topic of rigorous investigation. Here, a systematic review on the micro/nanoforming processes of 3D structures with multifunctional properties is presented, wherein also a critical examination of the interplay between relevant length scales and size effects affecting the structural integrity of micro/mesoscale metallic systems is also provided. Finally, the challenges of micro/nanoscale fabrication are proposed, including the development trends of new micro/nanoforming processes, multiple field coupling effects, and theoretical modeling at the trans‐scale.