Effect of temperature on the interactions between cellulose and lignin via molecular dynamics simulations

Cellulose - Heating is essential in various biomass pre-treatments and thermal conversion processes. It is of practical significance to study the characteristics of cellulose-lignin and...     

Singular soliton,shock-wave,breather-stripe soliton,hybrid solutions and numerical simulations for a (2+1)-dimensional Caudrey–Dodd–Gibbon–Kotera–Sawada system in fluid mechanics

Nonlinear Dynamics - In this paper, a (2+1)-dimensional Caudrey–Dodd–Gibbon–Kotera–Sawada system is investigated in fluid mechanics via the symbolic computation. With the...     

A Novel Ternary Composite of Polyurethane/Polyaniline/Nanosilica with Antistatic Property and Excellent Mechanical Strength: Preparation and Mechanism

Chinese Journal of Polymer Science - Antistatic and strength properties are of vital importance for polyurethane rubber used in moving parts of many industrial instruments. Herein, polyurethane was...     

Auto-deposition of 210Bi and 210Po on nickel discs and their application in the analysis of natural waters

Journal of Radioanalytical and Nuclear Chemistry - This study presents a time-efficient method of analysing 210Pb, 210Bi, and 210Po in natural waters. The optimum pH (1.00), temperature...     

基于深度学习的中医古文献临床经验抽取

中医古文献蕴藏着丰富的临床经验，是古代中医在行医过程中对临床诊疗的经验性总结，体现了中医学形成和发展的理论框架和思想基础.然而这些宝贵的临床经验不仅量大，而且分散在不同的文献中，使得中医从业者手工很难快速全面地获取它们，文献检索工具也只能提供文档级别的信息筛选，无法为这种细粒度的信息获取提供支持.此外，古汉语相对于现代汉语的不同特点也限制了主流文本分析工具的使用效果.为此本文提出面向临床经验获取的中医古文献信息抽取任务，用于识别古文献中描述临床经验的文本片段，手工标注了样本数据用于这种抽取模型的训练和测试，并设计了基于深度学习的序列标注器用于完成该任务.考虑到标注数据量小可能带来的过度拟合问题，本文引入对抗训练和虚拟对抗训练来增强模型的泛化能力.一系列充分的实验验证了模型的有效性，表明利用信息抽取技术从古文献获取中医临床经验具有可行性，为这一新的信息抽取任务提供了有希望的研究基线和可复用的标注数据集.     

基于GA_XGBoost模型的大学生科研能力预测问题研究

科学评价大学生科研创新能力对我国科研水平的提高具有重要意义.采用机器学习模型来预测大学生科研能力可以起到良好的效果,提出一种GAXGBoost模型来实现对大学生的科研能力预测.此模型是以Xgboost算法为基础,然后充分利用遗传算法的全局搜索能力自动搜索Xgboost最优超参数,避免了人为经验调参不准确的缺陷,最后采用精英选择策略以此确保每一轮都是最佳的进化结果.通过分析表明,所采用的GAXGBoost模型在大学生科研能力预测的结果中具有很高的精度,将此模型与Logistic Regression、Random Forest、SVM等模型进行对比,GAXGBoost模型的预测精度最高.     

Visible light-driven acridone catalysis for atom transfer radical polymerization

Acridone as a new kind of visible light photocatalyst has been developed to catalyze metal free atom transfer radical polymerization (ATRP). The photocatalyst possess low excited state potential as can undergo an oxidative quenching pathway to initiate ATRP of vinyl monomers. Kinetic study and light on/off reaction demonstrate the “living”/controlled nature of the polymerization by light. Block copolymers can be achieved by using PMMA as macroinitiator to reinitiate polymerization of other vinyl monomers, which shows highly preserved Br chain-end functionality in the synthesized polymers. Moreover, the polymerization can be conducted under air atmosphere as most photocatalysts need anaerobic condition, which may give inspiration of further application of this kind of photocatalyst.     

Dynamic mechanism of epileptic seizures generation and propagation after ischemic stroke

Nonlinear Dynamics - Epilepsy is the second largest neurological disease which seriously threatens human life and health. The one important reason of inducing epileptic seizures is ischemic stroke...     

大学生童年受忽视经历对自尊的影响:应对方式的中介作用

为研究大学生在童年时受到忽视与自尊水平、应对方式之间的关系,采用方便抽样法,向430名学生发放童年受忽视量表、简易应对方式量表和自尊量表,使用统计软件SPSS17.0进行数据整理与分析,结果表明,大学生在童年时受到的忽视与自尊、处理应对的积极方式是负相关关系(r=-0.164,r=-0.246,P<0.01),忽视与消极应对方式呈正相关关系(r=0.152,P<0.01);自尊与大学生采用积极的应对方式呈正相关关系(r=0.398,P<0.01),与采用消极的应对方式呈负相关关系(r=-0.217,P<0.01);不同的应对方式在面临忽视与自尊之间起着协调作用,积极应对方式的协调效果有29.4%,而消极应对方式的协调效果则只有12.6%,差距十分明显。因此,大学生在童年时受到忽视与自尊、不同的应对方式会收到完全不同的协调效果。