Prediction methods and applications in the science of science: A survey

Science of science has become a popular topic that attracts great attentions from the research community. The development of data analytics technologies and the readily available scholarly data enable the exploration of data-driven prediction, which plays a pivotal role in finding the trend of scientific impact. In this paper, we analyse methods and applications in data-driven prediction in the science of science, and discuss their significance. First, we introduce the background and review the current state of the science of science. Second, we review data-driven prediction based on paper citation count, and investigate research issues in this area. Then, we discuss methods to predict scholar impact, and we analyse different approaches to promote the scholarly collaboration in the collaboration network. This paper also discusses open issues and existing challenges, and suggests potential research directions.     

Synthesis and Application of Methyl N,O-Hydroxylamine Muramyl Peptides

The innate immune system's interaction with bacterial cells plays a pivotal role in a variety of human diseases. Carbohydrate units derived from a component of bacterial cell wall, peptidoglycan (PG), are known to stimulate an immune response. Nonetheless, access to modified late-stage peptidoglycan intermediates is limited due to their synthetic complexity. A method to rapidly functionalize PG fragments is needed to better understand the natural host–PG interactions. Here methyl N,O-hydroxylamine linkers are incorporated onto a synthetic PG derivative, muramyl dipeptide (MDP). The modification of MDP maintained the ability to stimulate a nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) immune response dependent on the expression of nucleotide-binding oligomerization domain-containing protein 2 (Nod2). Intrigued by this modification's maintenance of biological activity, several applications were explored. Methyl N,O-hydroxylamine MDP was amendable to N-hydroxylsuccinimide (NHS) chemistry for bioconjugation to fluorophores as well as a self-assembled monolayer for Nod2 surface plasmon resonance analysis. Finally, linker incorporation was applicable to larger PG fragments, both enzymatically generated from Escherichia coli or chemically synthesized. This methodology provides rapid access to PG probes in one step and allows for the installation of a variety of chemical handles to advance the molecular understanding of PG and the innate immune system.     

时态神经网络模型及其在股票分类预测上应用

对具有时间属性的数据进行数据挖掘称为时态数据挖掘，用以发现数据在时间上的知识，当数据变化不规律时，如股票交易数据,就很难发现有价值的规律与规则。而神经网络具有并行、容错、可以硬件实现以及自我学习的优点,可作为股票分类预测应用的一种方法。通过将股票数据与时态型相结合，将股票数据转换成时态型股票数据，提出时态神经网络模型的分类方法，对收集的若干上市公司十年内的股票数据进行分析，构建了时态股票数据神经网络分类器对股票进行分类预测。经过实验验证，相比改进前的神经网络和支持向量机方法，该分类器具有更高的分类准确率。结果证明，这种时态数据神经网络模型对于多只股票的分类预测是非常有效的，可以很好地运用到股票市场的分类预测中。     

基于平面不封闭图形切割的路径规划

在平面切割环节中，如何确定更短切割路径以减少加工成本、降低设备损耗和提升切割质量是工业应用和学术研究的重点。目前国内外对平面切割路径的研究主要集中于封闭图形，为此，针对在激光刀模行业中不封闭图形的问题，提出一种基于禁忌搜索的贪婪算法和贪婪准则的局部优化。首先使用构建型的贪婪算法和改进型的禁忌搜索算法相结合的方式对加工过程中的图元路径进行优化排序，随后提出贪婪准则的局部优化系数，削弱贪婪算法的“贪心”思想，解决加工路径的规划和优化问题。实验数据表明，禁忌搜索的贪婪算法和局部优化在对切割路径的规划和空行程优化上有显著效果，空行程减少50%以上，并且其优化性能和图元数量成正比，能有效地解决刀模行业以及其他激光雕刻行业中图形不封闭的切割难题。     

Misconceptions of human factors concepts

Abstract

Like many scientific topics, Human Factors, and Ergonomics concepts are susceptible to being misunderstood by people unfamiliar with the subject matter. Most of the time these misunderstandings are harmless, like when a safety poster within a work setting encourages employees to 'overcome complacency'. This misunderstanding of complacency suggests it is a motivational aspect of human behaviour correctable with encouragement, whereas the human factors approach to overcoming complacency would be to evaluate how task design could diminish the destructive consequences of unexpected changes within a routine setting. No harm comes from the message within the safety poster, other than some wasted ink and paper, but misconceptions among particular audiences can eventually result in dire consequences for the human operator. This paper presents recent evidence that the concepts are being misapplied by casual consumers of human factors, particularly in the aftermath of accidents within complex systems, in ways detrimental to the core mission of improving the well-being of the human operator. Later, because this special issue presents new ways to demonstrate value via return on investment, practical efforts we can take to overcome such misconceptions are suggested.     

海洋非成岩天然气水合物原位快速制备实验及评价

我国的海洋天然气水合物（以下简称水合物）资源主要分布在沿海大陆架水深介于300～3 000 m的深水区，具有弱胶结、非成岩的特征，为了测试和研究该类型水合物必须原位、大量、快速制备样品，而目前常用的搅拌法、喷淋法、鼓泡法等制备技术却存在着生成速度慢、储气密度低等问题。为此，自主设计、研制了1 062 L非成岩水合物快速制备釜，针对我国南海非成岩水合物的物性特征，开展了搅拌法、鼓泡法、喷淋法单一制备方法及“三合一”法（上述3种方法相结合）水合物制备实验，测试了实验过程中温度、压力、电阻率及反应时间等数据，分析比较了几种不同制备方法的水合物生成情况与制备效率。实验结果表明：①搅拌法、鼓泡法、喷淋法制备水合物过程中，生成的水合物均缓慢增加并逐渐铺满整个液面；②搅拌法制备过程中可以观测到明显的诱导期，而喷淋法、鼓泡法及“三合一”法却无明显的诱导期；③单一制备方法及“三合一”法制备水合物过程中，电阻率均随反应时间的增加而增加，其变化趋势亦与水合物制备速率基本一致；④“三合一”法的制备周期明显短于单一制备方法（搅拌法、喷淋法、鼓泡法单一方法的制备时间分别约为“三合一”法的5.14倍、3.59倍、3.16倍）。结论认为，所研制的1 062 L水合物快速制备釜能够实现海洋非成岩水合物样品的原位、快速制备；较之于单一制备方法，“三合一”法大大提高了水合物的制备效率。     

Influence of lanthanum on enhancement of mechanical and electrical properties of Cu-Al_2O_3 composites

Two kinds of Cu-Al_2O_3 composites(with and without La) were prepared via mechanical alloying-spark plasma sintering(MA-SPS) method. Microstructure, mechanical properties and electrical resistivity were investigated systematically using metallography, scanning electron microscopy, transmission electron microscopy, mechanical and electrical properties testing. The results indicate that an appropriate amount of La can homogenize the distribution of Al_2O_3. As such, yield strength, ultimate tensile strength and elongation of Cu-Al_2O_3-La are greatly increased. Some semi-coherent interface between Cu and Al_2O_3 is found, which means a low interface energy. The grain shape of Cu changes to irregular band with the addition of La. This change results in a density decrease of grain boundary and reduces electrical resistance. Lanthanum may exist in the form of La_2O_3.     

Ontology-based approach for the provision of simulation knowledge acquired by Data and Text Mining processes

Numerical simulation techniques such as Finite Element Analyses are essential in today's engineering design practices. However, comprehensive knowledge is required for the setup of reliable simulations to verify strength and further product properties. Due to limited capacities, design-accompanying simulations are performed too rarely by experienced simulation engineers. Therefore, product models are not sufficiently verified or the simulations lead to wrong design decisions, if they are applied by less experienced users. This results in belated redesigns of already detailed product models and to highly cost- and time-intensive iterations in product development.Thus, in order to support less experienced simulation users in setting up reliable Finite Element Analyses, a novel ontology-based approach is presented. The knowledge management tools developed on the basis of this approach allow an automated acquisition and target-oriented provision of necessary simulation knowledge. This knowledge is acquired from existing simulation models and text-based documentations from previous product developments by Text and Data Mining. By offering support to less experienced simulation users, the presented approach may finally lead to a more efficient and extensive application of reliable FEA in product development.