The tensile property of bi-axial warp knitted fabrics is tested and compared with that of the plain weave fabric. The results show that there are obvious differences between the tensile property of a bi-axial warp kni...The tensile property of bi-axial warp knitted fabrics is tested and compared with that of the plain weave fabric. The results show that there are obvious differences between the tensile property of a bi-axial warp knitted fabric and that of a plain weave fabric.The former can give fuller play to the property of a high modulus yarn than the latter. The tensile strength of a bi-axial warp knitted fabric is linear with the number of yarns in the direction of force.展开更多
In view of the problems of multi-scale changes of segmentation targets,noise interference,rough segmentation results and slow training process faced by medical image semantic segmentation,a multi-scale residual aggreg...In view of the problems of multi-scale changes of segmentation targets,noise interference,rough segmentation results and slow training process faced by medical image semantic segmentation,a multi-scale residual aggregation U-shaped attention network structure of MAAUNet(MultiRes aggregation attention UNet)is proposed based on MultiResUNet.Firstly,aggregate connection is introduced from the original feature aggregation at the same level.Skip connection is redesigned to aggregate features of different semantic scales at the decoder subnet,and the problem of semantic gaps is further solved that may exist between skip connections.Secondly,after the multi-scale convolution module,a convolution block attention module is added to focus and integrate features in the two attention directions of channel and space to adaptively optimize the intermediate feature map.Finally,the original convolution block is improved.The convolution channels are expanded with a series convolution structure to complement each other and extract richer spatial features.Residual connections are retained and the convolution block is turned into a multi-channel convolution block.The model is made to extract multi-scale spatial features.The experimental results show that MAAUNet has strong competitiveness in challenging datasets,and shows good segmentation performance and stability in dealing with multi-scale input and noise interference.展开更多
The nodes number of the hidden layer in a deep learning network is quite difficult to determine with traditional methods. To solve this problem, an improved Kullback-Leibler divergence sparse autoencoder （KL-SAE） is...The nodes number of the hidden layer in a deep learning network is quite difficult to determine with traditional methods. To solve this problem, an improved Kullback-Leibler divergence sparse autoencoder （KL-SAE） is proposed in this paper, which can be applied to battle damage assessment （BDA）. This method can select automatically the hidden layer feature which contributes most to data reconstruction, and abandon the hidden layer feature which contributes least. Therefore, the structure of the network can be modified. In addition, the method can select automatically hidden layer feature without loss of the network prediction accuracy and increase the computation speed. Experiments on University ofCalifomia-Irvine （UCI） data sets and BDA for battle damage data demonstrate that the method outperforms other reference data-driven methods. The following results can be found from this paper. First, the improved KL-SAE regression network can guarantee the prediction accuracy and increase the speed of training networks and prediction. Second, the proposed network can select automatically hidden layer effective feature and modify the structure of the network by optimizing the nodes number of the hidden layer.展开更多
In the eukaryotic cell nucleus, chromatin and its associated macromolecules must be organized into a higher-ordered conformation to function normally. However, mechanisms underlying the organization and dynamics of th...In the eukaryotic cell nucleus, chromatin and its associated macromolecules must be organized into a higher-ordered conformation to function normally. However, mechanisms underlying the organization and dynamics of the nucleus remain unclear. Long noncoding RNAs(lnc RNAs), i.e., transcripts longer than 200 nucleotides with little or no protein-coding capacity, are increasingly recognized as important regulators in diverse biological processes. Recent studies have shown that some lnc RNAs are involved in various aspects of genome organization, including the facilitation of chromosomal interactions and establishment of nuclear bodies, suggesting that lnc RNAs act as general organizers of the nuclear architecture. Here, we discuss recent advances in this emerging and intriguing field.展开更多
A commentarial project commissioned by emperor Ming Taizu （r.1368-1398） in 1377, which was dedicated to the Prajnaparamita-hrdaya-sutra, theVajracchedika-prajfiaparamita-sutra, and the Lankavatara-sutra, defined coh...A commentarial project commissioned by emperor Ming Taizu （r.1368-1398） in 1377, which was dedicated to the Prajnaparamita-hrdaya-sutra, theVajracchedika-prajfiaparamita-sutra, and the Lankavatara-sutra, defined coherent standards of Buddhist learning by reference to early Chinese translations and Indian commentarial literature. In order to provide a clear-cut basis for the education of the clergy, its selective and reductive approach aimed at a standardization of doctrine and homogenization of terminology. Production and purport of the commentarial project are documented in a series of paratexts, prefaces, colophons, production notes and memoranda. They indicate a strong consciousness for the institutional, ideological and political aspects of the production procedure and its benefits for controlling the formation of Buddhist authority. Such decidedly functional under- standing of the institutional aspects of the production of exegesis leads to the conclusion that besides the normativity of doctrinal knowledge the main objective was to establish a basis for institutional integration of those who are in the privileged position to select whom they allow to assume authority, and to define the selection standards as well.展开更多
文摘The tensile property of bi-axial warp knitted fabrics is tested and compared with that of the plain weave fabric. The results show that there are obvious differences between the tensile property of a bi-axial warp knitted fabric and that of a plain weave fabric.The former can give fuller play to the property of a high modulus yarn than the latter. The tensile strength of a bi-axial warp knitted fabric is linear with the number of yarns in the direction of force.
基金National Natural Science Foundation of China(No.61806006)Jiangsu University Superior Discipline Construction Project。
文摘In view of the problems of multi-scale changes of segmentation targets,noise interference,rough segmentation results and slow training process faced by medical image semantic segmentation,a multi-scale residual aggregation U-shaped attention network structure of MAAUNet(MultiRes aggregation attention UNet)is proposed based on MultiResUNet.Firstly,aggregate connection is introduced from the original feature aggregation at the same level.Skip connection is redesigned to aggregate features of different semantic scales at the decoder subnet,and the problem of semantic gaps is further solved that may exist between skip connections.Secondly,after the multi-scale convolution module,a convolution block attention module is added to focus and integrate features in the two attention directions of channel and space to adaptively optimize the intermediate feature map.Finally,the original convolution block is improved.The convolution channels are expanded with a series convolution structure to complement each other and extract richer spatial features.Residual connections are retained and the convolution block is turned into a multi-channel convolution block.The model is made to extract multi-scale spatial features.The experimental results show that MAAUNet has strong competitiveness in challenging datasets,and shows good segmentation performance and stability in dealing with multi-scale input and noise interference.
基金Project supported by the National Basic Research Program （973） of China （No. 61331903） and the National Natural Science Foundation of China （Nos. 61175008 and 61673265）
文摘The nodes number of the hidden layer in a deep learning network is quite difficult to determine with traditional methods. To solve this problem, an improved Kullback-Leibler divergence sparse autoencoder （KL-SAE） is proposed in this paper, which can be applied to battle damage assessment （BDA）. This method can select automatically the hidden layer feature which contributes most to data reconstruction, and abandon the hidden layer feature which contributes least. Therefore, the structure of the network can be modified. In addition, the method can select automatically hidden layer feature without loss of the network prediction accuracy and increase the computation speed. Experiments on University ofCalifomia-Irvine （UCI） data sets and BDA for battle damage data demonstrate that the method outperforms other reference data-driven methods. The following results can be found from this paper. First, the improved KL-SAE regression network can guarantee the prediction accuracy and increase the speed of training networks and prediction. Second, the proposed network can select automatically hidden layer effective feature and modify the structure of the network by optimizing the nodes number of the hidden layer.
基金supported by the National Basic Research Program of China(2011CBA011002015CB943000)+3 种基金National Natural Science Foundation of China(3137129691019001)Shanghai New Excellent Medicine Talents Program(XYQ2011036)Outstanding Doctoral Dissertation Author Fund of China(201131)
文摘In the eukaryotic cell nucleus, chromatin and its associated macromolecules must be organized into a higher-ordered conformation to function normally. However, mechanisms underlying the organization and dynamics of the nucleus remain unclear. Long noncoding RNAs(lnc RNAs), i.e., transcripts longer than 200 nucleotides with little or no protein-coding capacity, are increasingly recognized as important regulators in diverse biological processes. Recent studies have shown that some lnc RNAs are involved in various aspects of genome organization, including the facilitation of chromosomal interactions and establishment of nuclear bodies, suggesting that lnc RNAs act as general organizers of the nuclear architecture. Here, we discuss recent advances in this emerging and intriguing field.
文摘A commentarial project commissioned by emperor Ming Taizu （r.1368-1398） in 1377, which was dedicated to the Prajnaparamita-hrdaya-sutra, theVajracchedika-prajfiaparamita-sutra, and the Lankavatara-sutra, defined coherent standards of Buddhist learning by reference to early Chinese translations and Indian commentarial literature. In order to provide a clear-cut basis for the education of the clergy, its selective and reductive approach aimed at a standardization of doctrine and homogenization of terminology. Production and purport of the commentarial project are documented in a series of paratexts, prefaces, colophons, production notes and memoranda. They indicate a strong consciousness for the institutional, ideological and political aspects of the production procedure and its benefits for controlling the formation of Buddhist authority. Such decidedly functional under- standing of the institutional aspects of the production of exegesis leads to the conclusion that besides the normativity of doctrinal knowledge the main objective was to establish a basis for institutional integration of those who are in the privileged position to select whom they allow to assume authority, and to define the selection standards as well.
