Based on the fundamental equations of piezoelasticity of quasicrystal material,we investigated the interaction between a screw dislocation and a wedge-shaped crack in the piezoelectricity of one-dimensional hexagonal ...Based on the fundamental equations of piezoelasticity of quasicrystal material,we investigated the interaction between a screw dislocation and a wedge-shaped crack in the piezoelectricity of one-dimensional hexagonal quasicrystals.Explicit analytical solutions are obtained for stress and electric displacement intensity factors of the crack,as well as the force on dislocation.The derivation is based on the conformal mapping method and the perturbation technique.The influences of the wedge angle and dislocation location on the image force are also discussed.The results obtained in this paper can be fully reduced to some special cases already available or deriving new ones.展开更多
We analyze the electromagnetic interaction between local surface plasmon polaritons （SPPs） and an atmospheric surface wave plasma jet （ASWPJ） in combination with our designed discharge device. Before discharge, th...We analyze the electromagnetic interaction between local surface plasmon polaritons （SPPs） and an atmospheric surface wave plasma jet （ASWPJ） in combination with our designed discharge device. Before discharge, the excitation of the SPPs and the spatial distribution of the enhanced electric field are analyzed. During discharge, the critical breakdown electric field of the gases at atmospheric gas pressure and the surface wave of the SPPs converted into electron plasma waves at resonant points are studied. After discharge, the ionization development process of the ASWPJ is simulated using a two- dimensional fluid model. Our results suggest that the local enhanced electric field of SPPs is merely the precondition of gas breakdown, and the key mechanism in maintaining the discharge development of a low-power ASWPJ is the wave-mode conversion of the local enhanced electric field at the resonant point.展开更多
The interaction energy of two molecules system plays a critical role in analyzing the interacting effect in molecular dynamic simulation.Since the limitation of quantum mechanics calculating resources,the interaction ...The interaction energy of two molecules system plays a critical role in analyzing the interacting effect in molecular dynamic simulation.Since the limitation of quantum mechanics calculating resources,the interaction energy based on quantum mechanics can not be merged into molecular dynamic simulation for a long time scale.A deep learning framework,deep tensor neural network,is applied to predict the interaction energy of three organic related systems within the quantum mechanics level of accuracy.The geometric structure and atomic types of molecular conformation,as the data descriptors,are applied as the network inputs to predict the interaction energy in the system.The neural network is trained with the hierarchically generated conformations data set.The complex tensor hidden layers are simplified and trained in the optimization process.The predicted results of different molecular sys tems indica te that deep t ensor neural net work is capable to predic t the interaction energy with 1 kcal/mol of the mean absolute error in a relatively short time.The prediction highly improves the efficiency of interaction energy calculation.The whole proposed framework provides new insights to introducing deep learning technology into the interaction energy calculation.展开更多
Investigation of charge-transfer （CT） complexes of drugs has been recognized as an important phenomenon in understanding of the drug-receptor binding mechanism. Structural, thermal, morpholo-gical and biological beh...Investigation of charge-transfer （CT） complexes of drugs has been recognized as an important phenomenon in understanding of the drug-receptor binding mechanism. Structural, thermal, morpholo-gical and biological behavior of CT complexes formed between drug quinidine （Qui） as a donor and quinol （QL）, picric acid （PA） or dichlorodicyanobenzoquinone （DDQ） as acceptors were reported. The newly synthesized CT complexes have been spectroscopically characterized via elemental analysis;infrared （IR）, Raman, 1H NMR and electronic absorption spectroscopy; powder X-ray diffraction （PXRD）;thermogravimetric （TG） analysis and scanning electron microscopy （SEM）. It was found that the obtained complexes are nanoscale, semi-crystalline particles, thermally stable and spontaneous. The molecular composition of the obtained complexes was determined using spectrophotometric titration method and was found to be 1：1 ratios （donor：acceptor）. Finally, the biological activities of the obtained CT complexes were tested for their antibacterial activities. The results obtained herein are satisfactory for estimation of drug Qui in the pharmaceutical form展开更多
目的唐卡作为人类非物质文化遗产热贡艺术的重要表现形式之一,承载着重要的历史文化价值。在实地采集过程中发现,由于保存条件有限,许多唐卡作品出现裂痕、破损、水渍及霉点等问题,传统手工的修复方式效率低,且存在导致唐卡二次受损的...目的唐卡作为人类非物质文化遗产热贡艺术的重要表现形式之一,承载着重要的历史文化价值。在实地采集过程中发现,由于保存条件有限,许多唐卡作品出现裂痕、破损、水渍及霉点等问题,传统手工的修复方式效率低,且存在导致唐卡二次受损的风险。此外,使用传统图像修复方法和基于深度学习的图像自动修复方法修复唐卡时,往往产生不符合唐卡纹理结构的结果。鉴于此,提出一种线稿引导的交互式唐卡图像修复网络LSFNet(an image restoration network that combines line restoration,style and texture restoration,and fine restoration)。方法该方法由3部分组成,首先是唐卡艺术家指导的交互式线稿修复,使得修复的线结构更加接近真实唐卡图像;其次是风格纹理修复阶段,通过构建空间风格纹理模块学习唐卡图像整体风格和特征,并结合通道注意力和全连接层,捕获全局信息并进行融合,获得初步修复特征;最后是精修复阶段,引入线性注意力模块,实现全局信息传递,增强模型对唐卡图像内容的理解能力。结果以在青海采集的唐卡图像为基础,创建了唐卡修复数据集,并通过模拟破损区域,制作了掩码数据集,在创建的数据集上进行训练测试。与DeepFillv2、EdgeConnect、DFNet(deep fusion network)、HiFill及T-Former等图像修复方法进行定量、定性和主观实验对比分析。结果表明,该方法有良好的修复效果,在唐卡数据集上的PSNR(peak signal to noise ratio)、SSIM(structural similarity)和LPIPS(learned perceptual image patch similarity)3个评价指标结果均优于对比方法。与性能第2的模型相比,PSNR和SSIM分别提高10.55%和1.8%,LPIPS降低57.98%。此外,消融实验进一步验证了交互式线稿修复、风格纹理修复和精修复3个模块的有效性。结论通过采用交互式线稿修补的方法,能够有效地对破损唐卡图像进行修复,获得符合唐卡内容风格的修复结果。展开更多
基金Project supported by the National Natural Science Foundation of China(Grant Nos.11262017,11262012,and 11462020)the Natural Science Foundation of Inner Mongolia Autonomous Region,China(Grant No.2015MS0129)+1 种基金the Programme of Higher-level Talents of Inner Mongolia Normal University(Grant No.RCPY-2-2012-K-035)the Key Project of Inner Mongolia Normal University(Grant No.2014ZD03)
文摘Based on the fundamental equations of piezoelasticity of quasicrystal material,we investigated the interaction between a screw dislocation and a wedge-shaped crack in the piezoelectricity of one-dimensional hexagonal quasicrystals.Explicit analytical solutions are obtained for stress and electric displacement intensity factors of the crack,as well as the force on dislocation.The derivation is based on the conformal mapping method and the perturbation technique.The influences of the wedge angle and dislocation location on the image force are also discussed.The results obtained in this paper can be fully reduced to some special cases already available or deriving new ones.
基金Project supported by the National Natural Science Foundation of China(Grant No.11105002)the Open-end Fund of State Key Laboratory of Structural Analysis for Industrial Equipment,China(Grant No.GZ1215)+1 种基金the Natural Science Foundation for University in Anhui Province of China(Grant No.KJ2013A106)the Doctoral Scientific Research Funds of Anhui University of Science and Technology,China
文摘We analyze the electromagnetic interaction between local surface plasmon polaritons （SPPs） and an atmospheric surface wave plasma jet （ASWPJ） in combination with our designed discharge device. Before discharge, the excitation of the SPPs and the spatial distribution of the enhanced electric field are analyzed. During discharge, the critical breakdown electric field of the gases at atmospheric gas pressure and the surface wave of the SPPs converted into electron plasma waves at resonant points are studied. After discharge, the ionization development process of the ASWPJ is simulated using a two- dimensional fluid model. Our results suggest that the local enhanced electric field of SPPs is merely the precondition of gas breakdown, and the key mechanism in maintaining the discharge development of a low-power ASWPJ is the wave-mode conversion of the local enhanced electric field at the resonant point.
基金This work was supported by the National Natural Science Foundation of China(No.21933010 to Guo-hui Li).
文摘The interaction energy of two molecules system plays a critical role in analyzing the interacting effect in molecular dynamic simulation.Since the limitation of quantum mechanics calculating resources,the interaction energy based on quantum mechanics can not be merged into molecular dynamic simulation for a long time scale.A deep learning framework,deep tensor neural network,is applied to predict the interaction energy of three organic related systems within the quantum mechanics level of accuracy.The geometric structure and atomic types of molecular conformation,as the data descriptors,are applied as the network inputs to predict the interaction energy in the system.The neural network is trained with the hierarchically generated conformations data set.The complex tensor hidden layers are simplified and trained in the optimization process.The predicted results of different molecular sys tems indica te that deep t ensor neural net work is capable to predic t the interaction energy with 1 kcal/mol of the mean absolute error in a relatively short time.The prediction highly improves the efficiency of interaction energy calculation.The whole proposed framework provides new insights to introducing deep learning technology into the interaction energy calculation.
文摘Investigation of charge-transfer （CT） complexes of drugs has been recognized as an important phenomenon in understanding of the drug-receptor binding mechanism. Structural, thermal, morpholo-gical and biological behavior of CT complexes formed between drug quinidine （Qui） as a donor and quinol （QL）, picric acid （PA） or dichlorodicyanobenzoquinone （DDQ） as acceptors were reported. The newly synthesized CT complexes have been spectroscopically characterized via elemental analysis;infrared （IR）, Raman, 1H NMR and electronic absorption spectroscopy; powder X-ray diffraction （PXRD）;thermogravimetric （TG） analysis and scanning electron microscopy （SEM）. It was found that the obtained complexes are nanoscale, semi-crystalline particles, thermally stable and spontaneous. The molecular composition of the obtained complexes was determined using spectrophotometric titration method and was found to be 1：1 ratios （donor：acceptor）. Finally, the biological activities of the obtained CT complexes were tested for their antibacterial activities. The results obtained herein are satisfactory for estimation of drug Qui in the pharmaceutical form
文摘目的唐卡作为人类非物质文化遗产热贡艺术的重要表现形式之一,承载着重要的历史文化价值。在实地采集过程中发现,由于保存条件有限,许多唐卡作品出现裂痕、破损、水渍及霉点等问题,传统手工的修复方式效率低,且存在导致唐卡二次受损的风险。此外,使用传统图像修复方法和基于深度学习的图像自动修复方法修复唐卡时,往往产生不符合唐卡纹理结构的结果。鉴于此,提出一种线稿引导的交互式唐卡图像修复网络LSFNet(an image restoration network that combines line restoration,style and texture restoration,and fine restoration)。方法该方法由3部分组成,首先是唐卡艺术家指导的交互式线稿修复,使得修复的线结构更加接近真实唐卡图像;其次是风格纹理修复阶段,通过构建空间风格纹理模块学习唐卡图像整体风格和特征,并结合通道注意力和全连接层,捕获全局信息并进行融合,获得初步修复特征;最后是精修复阶段,引入线性注意力模块,实现全局信息传递,增强模型对唐卡图像内容的理解能力。结果以在青海采集的唐卡图像为基础,创建了唐卡修复数据集,并通过模拟破损区域,制作了掩码数据集,在创建的数据集上进行训练测试。与DeepFillv2、EdgeConnect、DFNet(deep fusion network)、HiFill及T-Former等图像修复方法进行定量、定性和主观实验对比分析。结果表明,该方法有良好的修复效果,在唐卡数据集上的PSNR(peak signal to noise ratio)、SSIM(structural similarity)和LPIPS(learned perceptual image patch similarity)3个评价指标结果均优于对比方法。与性能第2的模型相比,PSNR和SSIM分别提高10.55%和1.8%,LPIPS降低57.98%。此外,消融实验进一步验证了交互式线稿修复、风格纹理修复和精修复3个模块的有效性。结论通过采用交互式线稿修补的方法,能够有效地对破损唐卡图像进行修复,获得符合唐卡内容风格的修复结果。
