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.     

Strategies for synthesizing non-bioaccumulable alternatives to PFOA and PFOS

This minireview describes the strategies for synthesis of fiuorinated surfactants potentially nonbioaccumulable.Various strategies have been focused on(Ⅰ) reducing the length of the perfluorocarbon chain,(Ⅱ) introducing hetero atoms into the fluorocarbon chain,(Ⅲ) introducing branch(herein and after branch means the fluoro-carbon chain section is not straight).In most cases,the surface tensions versus the surfactant concentrations have been assessed.These above strategies led to various highly fiuorinated(perfluorinated or not perfluorinated) surfactants whose chemical changes enabled to obtain novel alternatives to perfluorooctanoic acid(PFOA) and perfluorooctane sulphonate(PFOS).     

Dynamical analysis of boundary behaviors of current-controlled DC–DC buck converter

Nonlinear Dynamics - In this paper, the current-controlled DC–DC buck converter from a new perspective are studied through the switching theory of flow, and the analytical conditions of the...     

化学法改性煤沥青脱除苯并芘的研究

在管式反应器中采用苯甲酸、聚乙二醇、固体古马隆树脂（S）、液体古马隆树脂（L）为添加剂来降低煤沥青中有害物质苯并芘的含量，以期使得煤沥青可绿色化应用。采用紫外-可见分光光度计分析煤沥青中苯并芘含量。考察了反应温度、反应时间、添加剂添加量、催化剂等工艺条件对添加剂脱除煤沥青中苯并芘的影响。结果表明，不同工艺条件能降低煤沥青中苯并芘的含量。在优化条件下，不同添加剂对苯并芘脱除率由高到低依次为：液体古马隆树脂、聚乙二醇、苯甲酸和固体古马隆树脂。分析其反应机理，这与催化剂的酸性相关，发生亲电取代反应。结果表明，液体古马隆树脂（L）在催化剂存在下对煤沥青中苯并芘脱除率可达73.0%，显示了良好的应用前景。     

基于深度学习的ELM实时识别研究

基于深度学习的方法，在HL-2A装置上开发出了一套边缘局域模(ELM)实时识别算法。算法使用5200次放电数据(约24.19万数据切片)进行学习，得到一个深度为22层的卷积神经网络。为衡量算法的识别能力，识别了HL-2A装置自2009年实现稳定ELMy H模放电以来所有历史数据(约26000次放电数据)，共识别出1665次H模放电，其中误识别35次，误报率为2.10%。在实际的1634次H模放电中，漏识别4次，漏识别率为0.24%。该误报率和漏报率可以满足ELM实时识别的精度要求。识别算法在实时控制环境下，对单个时间点的平均计算时间为0.46ms，可以满足实时控制的计算速度要求。     

Highly Luminescent Red Phosphorescent OLED with Interfacial Layers for Hole Transport and Electron Injection

Four kinds of red phosphorescent organic light-emitting devices were fabricated and compared to investigate the effect of interfacial layers for hole transport and electron injection. 1 nm-thick LiF in the device A and C and 1 nm-thick Cs₂CO₃ in the device B and D were deposited as an electron injection layer between the anode and the electron transport layer, and 5 nm-thick layer of dipyrazion[2,3-f:2′,2′-h]quinoxaline-2,3,6,7,10,11-hexacarbonitrile[HATCN] was inserted as a hole transport interfacial layer between the hole injection layer and the hole transport layer only in the device C and D. Under a luminance of 1000 cd/m², the power efficiencies were 7.6 lm/W and 8.5 lm/W in the device A and B, and 8.6 lm/W and 13.4 lm/W in the device C and D. The quantum efficiency of the device D was 15.8% under 1000 cd/m² which was somewhat lower than those of the device A and C, but a little higher than that of the device B. The luminance of the device D was much higher than those of the other devices at a given votage. The luminance of the device D at 7 V was 23,710 cd/m², which was 13.0, 3.4, and 4.0 times higher than those of the device A, B, and C at the same voltage, respectively.     

基于时变Copula模型的 基金收益率相依关系的应用研究

基于时变Copula模型,获得预测方差,确定单个基金收益率序列的边缘分布.利用常见的静态Copula和时变Copula模型对基金收益率序列间两两相依关系进行建模并进行对比分析.应用研究表明,基于MCMC方法的时变Copula模型能更有效地度量基金收益率序列的风险.