In the real world, there exist numerous multi-objective optimization problems (MOPs), and some representative multi-objective optimizers are proposed to meet the challenge. In this paper, an improved multi-objective f...
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Disulfide bonds are vital for protein functions, but locating the linkage sites has been a challenge in protein chemistry, especially when the quantity of a sample is small or the complexity is high. In 2015,our labor...
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Disulfide bonds are vital for protein functions, but locating the linkage sites has been a challenge in protein chemistry, especially when the quantity of a sample is small or the complexity is high. In 2015,our laboratory developed a sensitive and efficient method for mapping protein disulfide bonds from simple or complex samples(Lu et al. in Nat Methods 12:329, 2015). This method is based on liquid chromatography–mass spectrometry(LC–MS) and a powerful data analysis software tool named p *** facilitate application of this method, we present step-by-step disulfide mapping protocols for three types of samples—purified proteins in solution, proteins in SDS-PAGE gels, and complex protein mixtures in solution. The minimum amount of protein required for this method can be as low as several hundred nanograms for purified proteins, or tens of micrograms for a mixture of hundreds of *** entire workflow—from sample preparation to LC–MS and data analysis—is described in great detail. We believe that this protocol can be easily implemented in any laboratory with access to a fastscanning, high-resolution, and accurate-mass LC–MS system.
作者:
Xiaoping SunHai ZhugeKnowledge Grid Group
Key Lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China KLIIP
Institute of Computing Technology University of Chinese Academy of Sciences Chinese Academy of Sciences China Aston University Birmingham UK
With rapid expansion of scientific papers, making a survey from a large collection of papers on a given research issue or domain becomes more and more important for researchers. This paper proposes a template-based fr...
ISBN:
(数字)9781728158235
ISBN:
(纸本)9781728158242
With rapid expansion of scientific papers, making a survey from a large collection of papers on a given research issue or domain becomes more and more important for researchers. This paper proposes a template-based framework for automatically generating survey paper. It allows users to compose a template tree as a syllabus for the required survey. Each tree node corresponds to a section to be composed in the survey therefore the whole tree defines the section structure of the survey. The template consists of two types of nodes, dimension node and topic node, which filter contents of papers. A recursive procedure along the survey generation template tree paths is conducted to process documents, rank sentences, and compose sections. We apply the approach to generating the survey of the reference papers of a survey paper and compare the result with the survey paper. Experiments show improvement over several baseline methods.
Fully Convolutional Neural Network (FCN) has been widely applied to salient object detection recently by virtue of high-level semantic feature extraction, but existing FCN-based methods still suffer from continuous st...
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How to identify high-potential talent (HIPO) earlier in their career always has strategic importance for human resource management. While tremendous efforts have been made in this direction, most existing approaches a...
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How to identify high-potential talent (HIPO) earlier in their career always has strategic importance for human resource management. While tremendous efforts have been made in this direction, most existing approaches are still based on the subjective selection of human resource experts. This could lead to unintentional bias and inconsistencies. To this end, in this paper, we propose a neural network based dynamic social profiling approach for quantitatively identifying HIPOs from the newly-enrolled employees by modeling the dynamics of their behaviors in organizational social networks. A basic assumption is that HIPOs usually perform more actively and have higher competencies than their peers to accumulate their social capitals during their daily work practice. Along this line, we first propose to model the social profiles of employees with both Graph Convolutional Network (GCN) and social centrality analysis in a comprehensive way. Then, an adaptive Long Short Term Memory (LSTM) network with global attention mechanism is designed to capture the profile dynamics of employees in the organizational social networks during their early career. Finally, extensive experiments on real-world data clearly validate the effectiveness of our approach as well as the interpretability of our results.
Benefitted from its great success on many tasks, deep learning is increasingly used on low-computational-cost devices, e.g. smartphone, embedded devices, etc. To reduce the high computational and memory cost, in this ...
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ISBN:
(纸本)9781728132945
Benefitted from its great success on many tasks, deep learning is increasingly used on low-computational-cost devices, e.g. smartphone, embedded devices, etc. To reduce the high computational and memory cost, in this work, we propose a fully learnable group convolution module (FLGC for short) which is quite efficient and can be embedded into any deep neural networks for acceleration. Specifically, our proposed method automatically learns the group structure in the training stage in a fully end-to-end manner, leading to a better structure than the existing pre-defined, two-steps, or iterative strategies. Moreover, our method can be further combined with depthwise separable convolution, resulting in 5 times acceleration than the vanilla Resnet50 on single CPU. An additional advantage is that in our FLGC the number of groups can be set as any value, but not necessarily 2^k as in most existing methods, meaning better tradeoff between accuracy and speed. As evaluated in our experiments, our method achieves better performance than existing learnable group convolution and standard group convolution when using the same number of groups.
In recent years,compositional time series(CTS)prediction has become a widely applied data analysis method for modeling tactile sequence data[1],hydrological time series data using a four-
In recent years,compositional time series(CTS)prediction has become a widely applied data analysis method for modeling tactile sequence data[1],hydrological time series data using a four-
Direct speech-to-image translation without text is an interesting and useful topic due to the potential applications in human-computer interaction, art creation, computer-aided design. etc. Not to mention that many la...
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Video rain/snow removal from surveillance videos is an important task in the computer vision community since rain/snow existed in videos can severely degenerate the performance of many surveillance system. Various met...
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