Ionic Polymerization in Ionic Liquids

Ionic liquids have emerged as a new class of solvents for ionic polymerization due to their low volatility, chemical stability, high conductivity, wide electrochemical window. The advantages and limitations of application of ionic liquids as solvents for ionic polymerization processes are critically discussed in this chapter. The field of cationic polymerization in ionic liquid has undergone rapid growth in recent years. The most important types of cationic monomers, such as styrene and its derivatives, vinyl ethers and isobutylene have been polymerized in ionic liquids; even undergo living polymerization. Corresponding elementary reactions of cationic polymerization in ionic liquids were proposed. Methyl methacrylate and styrene can undergo anionic polymerization in ionic liquids. However, ionic liquids seem unsuitable solvents for anionic polymerization

Water use efficiency of China\u27s terrestrial ecosystems and responses to drought

Water use efficiency (WUE) measures the trade-off between carbon gain and water loss of terrestrial ecosystems, and better understanding its dynamics and controlling factors is essential for predicting ecosystem responses to climate change. We assessed the magnitude, spatial patterns, and trends of WUE of China’s terrestrial ecosystems and its responses to drought using a process-based ecosystem model. During the period from 2000 to 2011, the national average annual WUE (net primary productivity (NPP)/evapotranspiration (ET)) of China was 0.79 g C kg−1 H2O. Annual WUE decreased in the southern regions because of the decrease in NPP and the increase in ET and increased in most northern regions mainly because of the increase in NPP. Droughts usually increased annual WUE in Northeast China and central Inner Mongolia but decreased annual WUE in central China. “Turning-points” were observed for southern China where moderate and extreme droughts reduced annual WUE and severe drought slightly increased annual WUE. The cumulative lagged effect of drought on monthly WUE varied by region. Our findings have implications for ecosystem management and climate policy making. WUE is expected to continue to change under future climate change particularly as drought is projected to increase in both frequency and severity

Attention-Set based Metric Learning for Video Face Recognition

Face recognition has made great progress with the development of deep learning. However, video face recognition (VFR) is still an ongoing task due to various illumination, low-resolution, pose variations and motion blur. Most existing CNN-based VFR methods only obtain a feature vector from a single image and simply aggregate the features in a video, which less consider the correlations of face images in one video. In this paper, we propose a novel Attention-Set based Metric Learning (ASML) method to measure the statistical characteristics of image sets. It is a promising and generalized extension of Maximum Mean Discrepancy with memory attention weighting. First, we define an effective distance metric on image sets, which explicitly minimizes the intra-set distance and maximizes the inter-set distance simultaneously. Second, inspired by Neural Turing Machine, a Memory Attention Weighting is proposed to adapt set-aware global contents. Then ASML is naturally integrated into CNNs, resulting in an end-to-end learning scheme. Our method achieves state-of-the-art performance for the task of video face recognition on the three widely used benchmarks including YouTubeFace, YouTube Celebrities and Celebrity-1000.Comment: modify for ACP

Application of SWATH Proteomics to Mouse Biology.

The quantitative measurement of the proteome has been shown to yield new insights into physiology and cell biology that cannot be determined from the genome and transcriptome because the quantitative relationship between transcriptome and proteome is complex. MS-based proteomics techniques, such as SWATH-MS, have recently advanced to the point at which they may be reliably applied by biologists who are not specialists in mass spectrometry. Here we provide standard protocols for preparation of tissue samples for input into the SWATH-MS analytical pipeline. These protocols are designed for high-throughput processing of tissues with >/=5 mg of sample available for analysis. Studies with extremely limited amounts of tissue should consider PCT-SWATH. An experienced single user should be able to process 48 samples per day for injection into the mass spectrometer, or up to 144 samples a week. The machine time necessary for running these samples with SWATH is approximately 1.5 hr per sample. Data acquisition protocols are also provided. (c) 2017 by John Wiley & Sons, Inc