To shed some light on the John-Nirenberg space,the authors of this article introduce the John-Nirenberg-Q space via congruent cubes,JNQp,qα(Rn),which,when p=∞and q=2,coincides with the space Qα(Rn)introduced by Ess...To shed some light on the John-Nirenberg space,the authors of this article introduce the John-Nirenberg-Q space via congruent cubes,JNQp,qα(Rn),which,when p=∞and q=2,coincides with the space Qα(Rn)introduced by Essen,Janson,Peng and Xiao in[Indiana Univ Math J,2000,49(2):575-615].Moreover,the authors show that,for some particular indices,JNQp,qα(Rn)coincides with the congruent John-Nirenberg space,or that the(fractional)Sobolev space is continuously embedded into JNQp,qα(Rn).Furthermore,the authors characterize JNQp,qα(Rn)via mean oscillations,and then use this characterization to study the dyadic counterparts.Also,the authors obtain some properties of composition operators on such spaces.The main novelties of this article are twofold:establishing a general equivalence principle for a kind of’almost increasing’set function that is here introduced,and using the fine geometrical properties of dyadic cubes to properly classify any collection of cubes with pairwise disjoint interiors and equal edge length.展开更多
Many approaches have been proposed to pre-compute data cubes in order to efficiently respond to OLAP queries in data warehouses. However, few have proposed solutions integrating all of the possible outcomes, and it is...Many approaches have been proposed to pre-compute data cubes in order to efficiently respond to OLAP queries in data warehouses. However, few have proposed solutions integrating all of the possible outcomes, and it is this idea that leads the integration of hierarchical dimensions into these responses. To meet this need, we propose, in this paper, a complete redefinition of the framework and the formal definition of traditional database analysis through the prism of hierarchical dimensions. After characterizing the hierarchical data cube lattice, we introduce the hierarchical data cube and its most concise reduced representation, the closed hierarchical data cube. It offers compact replication so as to optimize storage space by removing redundancies of strongly correlated data. Such data are typical of data warehouses, and in particular in video games, our field of study and experimentation, where hierarchical dimension attributes are widely represented.展开更多
Instead of the energy-intensive Haber-Bosch process,the researchers proposed a way to produce ammonia using water and nitrogen as feedstock,powered by electricity,without polluting the environment.Nevertheless,how to ...Instead of the energy-intensive Haber-Bosch process,the researchers proposed a way to produce ammonia using water and nitrogen as feedstock,powered by electricity,without polluting the environment.Nevertheless,how to design efficient electrocatalyst for electrocatalytic nitrogen reduction reaction(NRR)is still urgent and challenging.Herein,a strategy is proposed to adjust the morphology and surface electronic structure of electrocatalyst by optimizing material synthesis method.LiNbO3(lithium niobate,LN)cubes with oxygen-rich vacancy and regular morphology were synthesized by hydrothermal synthesis and followed molten salt calcination process,which were used for electrocatalytic NRR under mild conditions.Compared with LN nanoparticles synthesized by solid phase reaction,LN cubes exhibit better NRR performance,with the highest ammonia yield rate(13.74μg.h^(-1).mg^(-1))at the best potential of-0.45V(vs.reversible hydrogen electrode,RHE)and the best Faradaic efficiency(85.43%)at-0.4 V.Moreover,LN cubes electrocatalyst also demonstrates high stability in 7 cycles and 18 h current-time tests.Further investigation of the reaction mechanism confirmed that the structure of oxygen vacancy could adjust the electronic structure of the electrocatalyst,which was conducive to the adsorption and activation of N_(2) molecule and also increased the ECSA of electrocatalyst,thus providing more active sites for the NRR process.展开更多
目的:研究MRI 3D CUBE T_(2)序列检查在踝关节外伤患者韧带损伤诊断中的价值。方法:选择2020年4月—2023年4月于白银市第一人民医院就诊的226例踝关节外伤拟行手术术前患者作为研究对象,按照不同检查方式将患者分为观察组(n=126)与对照...目的:研究MRI 3D CUBE T_(2)序列检查在踝关节外伤患者韧带损伤诊断中的价值。方法:选择2020年4月—2023年4月于白银市第一人民医院就诊的226例踝关节外伤拟行手术术前患者作为研究对象,按照不同检查方式将患者分为观察组(n=126)与对照组(n=100)。观察组采用MRI 3D CUBE T_(2)序列检查,对照组采取常规MRI检查。比较两组患侧、健侧距腓前韧带测量结果、诊断效能。结果:两组患侧、健侧距腓前韧带宽度及厚度比较,差异无统计学意义(P>0.05)。观察组Ⅰ级踝关节外伤患者韧带损伤诊断准确度、敏感度、特异度、阳性预测值、阴性预测值高于对照组,Ⅱ级患者准确度、敏感度、阴性预测值高于对照组,Ⅲ级患者准确度、特异度、阳性预测值高于对照组,差异有统计学意义(P<0.05)。结论:MRI 3D CUBE T_(2)序列检查踝关节外伤患者韧带损伤诊断效能高于常规MRI检查,可作为治疗效果评价及康复治疗的重要依据。展开更多
随着互联网的快速发展,人们对个性化网页搜索、个性化广告投放、个性化社会标注等三维推荐服务的需求越来越紧迫。这些三维立方体数据高度稀疏,且与二维推荐系统相比三维推荐系统中对象之间的关系更加复杂。为了更好地模拟三维对象之间...随着互联网的快速发展,人们对个性化网页搜索、个性化广告投放、个性化社会标注等三维推荐服务的需求越来越紧迫。这些三维立方体数据高度稀疏,且与二维推荐系统相比三维推荐系统中对象之间的关系更加复杂。为了更好地模拟三维对象之间的关系并解决三维数据高度稀疏的问题,提出了一种新的三维协同过滤推荐算法CubeALS(cube alternating least squares)。该算法对三维协同过滤推荐算法CubeSVD(cube singular value decomposition)进行了改进,尝试使用不同于SVD的算法进行矩阵分解。在真实的个性化社会标注数据集上的实验结果表明,与CubeSVD算法相比,CubeALS的性能得到了显著提高。展开更多
在数据仓库系统中,数据立方体(Cube)及其预聚集处理在OLAP起到非常重要的作用.对于一个d维的data Cube可以生成2d个聚集Cuboids和multiply from i=1 to d(|Di|+1)个聚集数据单元,但对于一个高维Cube,要创建这些所有聚集Cuboids是不现实...在数据仓库系统中,数据立方体(Cube)及其预聚集处理在OLAP起到非常重要的作用.对于一个d维的data Cube可以生成2d个聚集Cuboids和multiply from i=1 to d(|Di|+1)个聚集数据单元,但对于一个高维Cube,要创建这些所有聚集Cuboids是不现实的.提出通过共享分段立方体Mini-Cube的高维Cube并行分布式存储结构(DHMC),将高维Cube划分成若干个低维共享分段立方体Mini-Cube,利用并行分布式处理技术来创建这些分割的分段共享Mini-Cube及其聚集Cuboids,来实现高维Cube的并行创建和增量更新维护,从而解决高维OLAP聚集海量数据的存储与查询问题.理论分析与实验结果均表明DHMC性能最佳.展开更多
基金partially supported by the National Natural Science Foundation of China(12122102 and 11871100)the National Key Research and Development Program of China(2020YFA0712900)。
文摘To shed some light on the John-Nirenberg space,the authors of this article introduce the John-Nirenberg-Q space via congruent cubes,JNQp,qα(Rn),which,when p=∞and q=2,coincides with the space Qα(Rn)introduced by Essen,Janson,Peng and Xiao in[Indiana Univ Math J,2000,49(2):575-615].Moreover,the authors show that,for some particular indices,JNQp,qα(Rn)coincides with the congruent John-Nirenberg space,or that the(fractional)Sobolev space is continuously embedded into JNQp,qα(Rn).Furthermore,the authors characterize JNQp,qα(Rn)via mean oscillations,and then use this characterization to study the dyadic counterparts.Also,the authors obtain some properties of composition operators on such spaces.The main novelties of this article are twofold:establishing a general equivalence principle for a kind of’almost increasing’set function that is here introduced,and using the fine geometrical properties of dyadic cubes to properly classify any collection of cubes with pairwise disjoint interiors and equal edge length.
文摘Many approaches have been proposed to pre-compute data cubes in order to efficiently respond to OLAP queries in data warehouses. However, few have proposed solutions integrating all of the possible outcomes, and it is this idea that leads the integration of hierarchical dimensions into these responses. To meet this need, we propose, in this paper, a complete redefinition of the framework and the formal definition of traditional database analysis through the prism of hierarchical dimensions. After characterizing the hierarchical data cube lattice, we introduce the hierarchical data cube and its most concise reduced representation, the closed hierarchical data cube. It offers compact replication so as to optimize storage space by removing redundancies of strongly correlated data. Such data are typical of data warehouses, and in particular in video games, our field of study and experimentation, where hierarchical dimension attributes are widely represented.
基金the financial support from the National Natural Science Foundation of China(22075196,21878204)Key Research and Development Program of Shanxi Province(International Cooperation,201903D421073)Research Project Supported by Shanxi Scholarship Council of China(2022-050).
文摘Instead of the energy-intensive Haber-Bosch process,the researchers proposed a way to produce ammonia using water and nitrogen as feedstock,powered by electricity,without polluting the environment.Nevertheless,how to design efficient electrocatalyst for electrocatalytic nitrogen reduction reaction(NRR)is still urgent and challenging.Herein,a strategy is proposed to adjust the morphology and surface electronic structure of electrocatalyst by optimizing material synthesis method.LiNbO3(lithium niobate,LN)cubes with oxygen-rich vacancy and regular morphology were synthesized by hydrothermal synthesis and followed molten salt calcination process,which were used for electrocatalytic NRR under mild conditions.Compared with LN nanoparticles synthesized by solid phase reaction,LN cubes exhibit better NRR performance,with the highest ammonia yield rate(13.74μg.h^(-1).mg^(-1))at the best potential of-0.45V(vs.reversible hydrogen electrode,RHE)and the best Faradaic efficiency(85.43%)at-0.4 V.Moreover,LN cubes electrocatalyst also demonstrates high stability in 7 cycles and 18 h current-time tests.Further investigation of the reaction mechanism confirmed that the structure of oxygen vacancy could adjust the electronic structure of the electrocatalyst,which was conducive to the adsorption and activation of N_(2) molecule and also increased the ECSA of electrocatalyst,thus providing more active sites for the NRR process.
文摘目的:研究MRI 3D CUBE T_(2)序列检查在踝关节外伤患者韧带损伤诊断中的价值。方法:选择2020年4月—2023年4月于白银市第一人民医院就诊的226例踝关节外伤拟行手术术前患者作为研究对象,按照不同检查方式将患者分为观察组(n=126)与对照组(n=100)。观察组采用MRI 3D CUBE T_(2)序列检查,对照组采取常规MRI检查。比较两组患侧、健侧距腓前韧带测量结果、诊断效能。结果:两组患侧、健侧距腓前韧带宽度及厚度比较,差异无统计学意义(P>0.05)。观察组Ⅰ级踝关节外伤患者韧带损伤诊断准确度、敏感度、特异度、阳性预测值、阴性预测值高于对照组,Ⅱ级患者准确度、敏感度、阴性预测值高于对照组,Ⅲ级患者准确度、特异度、阳性预测值高于对照组,差异有统计学意义(P<0.05)。结论:MRI 3D CUBE T_(2)序列检查踝关节外伤患者韧带损伤诊断效能高于常规MRI检查,可作为治疗效果评价及康复治疗的重要依据。
文摘随着互联网的快速发展,人们对个性化网页搜索、个性化广告投放、个性化社会标注等三维推荐服务的需求越来越紧迫。这些三维立方体数据高度稀疏,且与二维推荐系统相比三维推荐系统中对象之间的关系更加复杂。为了更好地模拟三维对象之间的关系并解决三维数据高度稀疏的问题,提出了一种新的三维协同过滤推荐算法CubeALS(cube alternating least squares)。该算法对三维协同过滤推荐算法CubeSVD(cube singular value decomposition)进行了改进,尝试使用不同于SVD的算法进行矩阵分解。在真实的个性化社会标注数据集上的实验结果表明,与CubeSVD算法相比,CubeALS的性能得到了显著提高。
文摘在数据仓库系统中,数据立方体(Cube)及其预聚集处理在OLAP起到非常重要的作用.对于一个d维的data Cube可以生成2d个聚集Cuboids和multiply from i=1 to d(|Di|+1)个聚集数据单元,但对于一个高维Cube,要创建这些所有聚集Cuboids是不现实的.提出通过共享分段立方体Mini-Cube的高维Cube并行分布式存储结构(DHMC),将高维Cube划分成若干个低维共享分段立方体Mini-Cube,利用并行分布式处理技术来创建这些分割的分段共享Mini-Cube及其聚集Cuboids,来实现高维Cube的并行创建和增量更新维护,从而解决高维OLAP聚集海量数据的存储与查询问题.理论分析与实验结果均表明DHMC性能最佳.
