Flexible Hierarchical(灵活的分层)研究综述
Flexible Hierarchical 灵活的分层 - In this work, flexible hierarchically porous carbon polyhedra embedded carbon nanofibers doped with N and S (NSCPCNF) were synthesized by electrospinning a metal–organic framework ZIF-67 and a thiourea incorporated polyacrylonitrile precursor with subsequent carbonization. [1]在这项工作中，通过静电纺丝金属有机框架 ZIF-67 和掺入硫脲的聚丙烯腈前体并随后碳化，合成了柔性多面体嵌入的 N 和 S 碳纳米纤维（NSCPCNF）。 [1]
flexible hierarchical structure 灵活的层次结构
Individual linguistic axiological spheres are examined in terms of flexible hierarchical structures, the dynamism of which is determined by the characters’ life experience. [1] The polarity, roughness and wettability of CFs surface as well as the thickness of intermediate layer in composite have been significantly increased after rigid-flexible hierarchical structure was constructed. [2] The development of CM models on the basis of the von Mises distribution has allowed to integrate flexible hierarchical structures accounting for different sources of variation and affecting both mean and dispersion terms. [3] Thai public sector always described as a highly centralized system, with an inflexible hierarchical structure and high levels of formal relationships channeling its communications through public enterprises and institutions. [4]个人语言价值论领域根据灵活的等级结构进行检查，其活力取决于人物的生活经历。 [1] 构建刚柔结合的分层结构后，CFs表面的极性、粗糙度和润湿性以及复合材料中的中间层厚度显着增加。 [2] 基于 von Mises 分布的 CM 模型的开发允许集成灵活的层次结构，以解决不同的变异来源并影响均值和离散项。 [3] 泰国公共部门一直被描述为一个高度集中的系统，具有不灵活的等级结构和高水平的正式关系，通过公共企业和机构进行沟通。 [4]
flexible hierarchical bayesian 灵活的分层贝叶斯
We estimate the effectiveness of 17 NPIs in Europe’s second wave from subnational case and death data by introducing a flexible hierarchical Bayesian transmission model and collecting the largest dataset of NPI implementation dates across Europe. [1] To take advantage of data collected at monitoring stations and the effect of secondary information such as meteorological factors, this paper proposes a flexible hierarchical Bayesian model (HBM) which can predict air pollutant concentrations in space and time. [2] We systematically revisited stroke outcome predictions by casting the data in a less confounded form and employing more integrative and flexible hierarchical Bayesian models. [3]我们通过引入灵活的分层贝叶斯传输模型并收集欧洲最大的 NPI 实施日期数据集，根据地方病例和死亡数据估计欧洲第二波中 17 个 NPI 的有效性。 [1] 为了利用监测站采集的数据和气象因素等二次信息的影响，本文提出了一种灵活的分层贝叶斯模型（HBM），可以预测空气污染物在空间和时间上的浓度。 [2] 我们系统地重新审视了卒中结果预测，方法是以一种不那么混乱的形式投射数据，并采用更综合和灵活的分层贝叶斯模型。 [3]
flexible hierarchical model
Stochastic differential equation mixed-effects models (SDEMEMs) are flexible hierarchical models that are able to account for random variability inherent in the underlying time-dynamics, as well as the variability between experimental units and, optionally, account for measurement error. [1] SDEMEMs are flexible hierarchical models that are able to account for random variability inherent in the underlying time-dynamics, as well as the variability between experimental units and, optionally, account for measurement error. [2]随机微分方程混合效应模型 (SDEMEM) 是灵活的层次模型，能够解释潜在时间动态中固有的随机变异性，以及实验单位之间的变异性，并且可以选择解释测量误差。 [1] SDEMEM 是灵活的分层模型，能够解释潜在时间动态中固有的随机变异性，以及实验单元之间的变异性，并且可以选择解释测量误差。 [2]