1，4二环己基取代六元瓜环与Na(Ⅰ)自组装实体的合成与晶体结构

A novel complex of a new 1,4-dicyclohexyl cucurbituril(DCYQ[6]) with sodium(Ⅰ) ion was synthesized, and the crystal structure was determined by X-ray diffraction technique. In this self-assembled entity both the cavity interaction of DCYQ[6] included a nitrate anion and the portal interaction of the dipole carbonyls of DCYQ[6] with sodium cations lead to form self assembled molecular capsules. The crystal structure of the entity shows a packing of the self assembled molecular capsules connected by hydrogen bonds of water molecules. CCDC: 271400.     

Molecular entity vacancy model

A novel molecular entity vacancy model was proposed to describe thermodynamic properties in a multicomponent solution system using its binary interaction parameters only. A derivation of the model for its general expression has been shown in detail. Under some special conditions, this model may be reduced to Flory–Huggins equation, Wilson equation and non-random two liquids (NRTL) equation as well as molecular interaction volume model (MIVM), respectively, and can be verified by Gibbs–Duhem equation, and can express thermodynamic properties of partially miscible systems. The predicted activities are in good agreement with experimental data of some liquid alloys. The results show that the model is of better predictability and reliability because it has a certain physical basis.     

Optical microscopy to study single nanoparticles electrochemistry: From reaction to motion

Nanoparticles (NPs)-based electrochemical devices are generating a growing interest and optical microscopy has recently proven to be a powerful tool to apprehend their electrochemical behavior. Through several striking examples, this review demonstrates how label-free optical imaging coupled to an electrochemical actuation can be used to probe operando the physical and electrochemical properties of single NPs, with high resolution and sensitivity and without additional emitters. Such an approach can be particularly relevant to establish clear structure-motion/reactivity relationships required to optimize NPs exploited as electrode materials.     

基于联合神经网络学习的中文电力计量命名实体识别

随着电力计量业务的不断扩展,迫切需要由业务信息、技术知识、行业标准及其内在联系所组成的电力计量知识图谱,为电网的决策和发展提供更为全面有效的支持。命名实体识别是构建知识图谱的基础。针对电力计量领域需要,结合中文分词技术特点,基于联合学习思想,提出了一种基于联合学习的中文电力计量命名实体识别技术。该技术联合CNN-BLSTM-CRF模型与整合词典知识的分词模型,使其共享实体类别和置信度;同时将2个模型的先后计算顺序改为并行计算,减少了识别误差累积。结果表明,在不需要人工构建特征的情况下,方法的正确率、召回率、F值等均显著优于以往方法。     

A Bayesian record linkage model incorporating relational data

In this article, we introduce a novel Bayesian approach for linking multiple social networks in order to discover the same real world person having different accounts across networks. In particular, we develop a latent model that allows us to jointly characterize the network and linkage structures relying on both relational and profile data. In contrast to other existing approaches in the machine learning literature, our Bayesian implementation naturally provides uncertainty quantification via posterior probabilities for the linkage structure itself or any function of it. Our findings clearly suggest that our methodology can produce accurate point estimates of the linkage structure even in the absence of profile information, and also, in an identity resolution setting, our results confirm that including relational data into the matching process improves the linkage accuracy. We illustrate our methodology using real data from popular social networks such as Twitter , Facebook , and YouTube .     

基于网络技术的虚拟实验设计

介绍了所设计的虚拟实验系统,对系统方案、基本功能以及在设计过程中所遇到的一些设计问题进行分析并提出了解决方法。     

多源异构土地基础数据一体化管理检索方法研究

为了从多源异构的复杂土地基础数据中快速准确地提取用户所需信息,提出了基于元数据的一体化管理检索方法.在元数据信息提取、元数据加权索引、实体同义词扩展检索3个环节中,结合土地领域专业知识和用户实际需求,设计和开发了共享元数据表结构、加权元数据中字段相对重要性和信息熵因子,构建地名实体和专题数据层实体同义词库,并集成到包括中文分词、实体识别、同义词扩展、索引检索和相似度计算的一体化管理检索框架中,解决了多源异构土地基础数据统一管理和精确检索的问题.实践表明,该方法较传统的通用信息检索方法具有更好的适用性和更高的准确率.     

Combinatorial chemistry: oh what a decade or two can do

This short commentary takes a stroll through the early days of the field of combinatorial chemistry and molecular diversity. It offers a high-level perspective on the field’s beginnings—and its future—as it relates to journals, books, pioneers, and advances.     

关于数学哲学的新思考

本文以计算机软件 ,程序语言等作类比 ,提出数学命题是一种“概念实在”,以阐明数学对象的本体论地位 ;并根据自然科学只能基于现有的数学理论而建构这一事实 ,对数学在自然科学中的超前性和有效性作出了新的解释 .同时 ,本文勾划了一种新的数学哲学的轮廓 ,它以数学中引入新结构 ,提出猜想等创造性活动为课题 ,以数学史材料研究为方法 ,以探求数学发展的内在统一性为目的 .     

Two-phase biomedical named entity recognition using CRFs

As a fundamental step of biomedical text mining, Biomedical Named Entity Recognition (Bio-NER) remains a challenging task. This paper explores a so-called two-phase approach to identify biomedical entities, in which the recognition task is divided into two subtasks: Named Entity Detection (NED) and Named Entity Classification (NEC). And the two subtasks are finished in two phases. At the first phase, we try to identify each named entity with a Conditional Random Fields (CRFs) model without identifying its type; at the second phase, another CRFs model is used to determine the correct entity type for each identified entity. This treatment can reduce the training time significantly and furthermore, more relevant features can be selected for each subtask. In order to achieve a better performance, post-processing algorithms are employed before NEC subtask. Experiments conducted on JNLPBA2004 datasets show that our two-phase approach can achieve an F-score of 74.31%, which outperforms most of the state-of-the-art systems.