Pipette‐tip solid‐phase extraction based on deep eutectic solvent modified graphene for the determination of sulfamerazine in river water

A green and novel deep eutectic solvent modified graphene was prepared and used as a neutral adsorbent for the rapid determination of sulfamerazine in a river water sample by pipette‐tip solid‐phase extraction. Compared with conventional graphene, deep eutectic solvent modified graphene can change the surface of graphene with wrinkled structure and higher selective extraction ability. The properties of deep eutectic solvent modified graphene and graphene were characterized by scanning electron microscopy, Fourier transform infrared spectroscopy, and thermogravimetric analysis. Static adsorption showed deep eutectic solvent modified graphene had a higher adsorption ability (18.62 mg/g) than graphene. Under the optimum conditions, factors such as kinds of washing solvents and elution solvents and volume of elution solvent were evaluated. The limits of detection and quantification were 0.01 and 0.03 μg/mL, respectively. The method recoveries of sulfamerazine were in the range of 91.01–96.82% with associated intraday relative standard deviations ranging from 1.63 to 3.46% and interday relative standard deviations ranging from 0.68 to 3.84%. Deep eutectic solvent modified graphene showed satisfactory results (recovery was 95.38%) and potential for rapid purification of sulfamerazine in river water sample in combination with the pipette‐tip solid‐phase extraction method.     

Exploration of a ternary deep eutectic solvent of methyltriphenylphosphonium bromide/chalcone/formic acid for the selective recognition of rutin and quercetin in Herba Artemisiae Scopariae

Methyltriphenylphosphonium bromide/chalcone/formic acid, a green ternary deep eutectic solvent, was applied as a functional monomer and dummy template simultaneously in the synthesis of a new molecularly imprinted polymer. Ternary deep eutectic solvent based molecularly imprinted polymers are used as a solid‐phase extraction sorbent in the separation and purification of rutin and quercetin from Herba Artemisiae Scopariae combined with high‐performance liquid chromatography. Fourier transform infrared spectroscopy and field‐emission scanning electron microscopy were applied to characterize the deep eutectic solvent based molecularly imprinted polymers synthesized using different molar ratios of chalcone. The static and competitive adsorption tests were performed to examine the recognition ability of the molecularly imprinted polymers to rutin and quercetin. The ternary deep eutectic solvent consisting of formic acid/chalcone/methyltriphenylphosphonium bromide (1:0.05:0.5) had the best molecular recognition effect. After optimization of the washing solvents (methanol/water, 1:9) and eluting solvents (acetonitrile/acetic acid, 9:1), a reliable analytical method was developed for strong recognition towards rutin and quercetin in Herba Artemisiae Scopariae with satisfactory extraction recoveries (rutin: 92.48%, quercetin: 94.23%). Overall, the chalcone ternary deep eutectic solvent‐based molecularly imprinted polymer coupled with solid‐phase extraction is an effective method for the selective purification of multiple bioactive compounds in complex samples.     

基于模糊灰色新陈代谢FGM(1,1)模型预测及应用探讨

巷道围岩变形是煤矿开采普遍存在的问题,巷道开挖过程中围岩会出现破裂现象.主要探讨模糊灰色系统的深部巷道围岩变形预测模型及应用,通过分析模糊数学理论、灰色理论,给出模糊灰色系统预测新陈代谢模型.     

某软土深基坑工程时间效应有限元分析

软土地区的深基坑因土体的固结作用和流变性而具有了时间效应。本文以Biot固结有限元法为基础,用三元件模型中的第一个线性弹簧模拟固结作用,弹性模量考虑了开挖应力路径和应力历史的影响;另外一部分(KELVIN模型)来模拟土体的流变性,以实际变形的反演来得到两个参数的大致取值,再对基坑的变形情况以及进一步开挖进行分析。假定为正常固结饱和粘土,平面应变问题。通过对某饱和软粘土地基深基坑开挖工程实例的分析,得到的挡墙水平位移曲线与实测曲线很吻合,表明程序较好地反映出基坑的时间效应。     

Stress state of a cylindrical composite panel weakened by a circular hole

The paper studies the stress-strain state of a deep cylindrical panel weakened by a hole and subjected to a tensile load at the outer boundary. A variational difference method is used. A numerical analysis is carried out for an orthotropic panel with low shear stiffness __________ Translated from Prikladnaya Mekhanika, Vol. 42, No. 5, pp. 73–78, May 2006.     

Unsteady Behavior of an Elastic Beam Floating on the Surface of an Infinitely Deep Fluid

The effect of initial disturbances and unsteady external loading on an elastic beam of finite length which floats freely on the surface of an ideal incompressible fluid is studied in a linear treatment. The fluid flow is considered potential. The beam deflection is sought in the form of an expansion in the eigenfunctions of beam vibrations in vacuum with time-dependent amplitudes. The problem reduces to solving an infinite system of integrodifferential equations for unknown amplitudes. The memory functions entering this system are determined by solving the radiation problem. The beam behavior is studied for various loads with and without allowance for the weight of the fluid. The effect of fluid depth on beam deformation was determined by comparing with the previously obtained solutions of the unsteady problem for a beam floating in shallow water. __________ Translated from Prikladnaya Mekhanika i Tekhnicheskaya Fizika, Vol. 47, No. 1, pp. 85–94, January–February, 2006.     

岩爆与围岩分类

岩爆是高地应力条件下完整脆性硬质围岩失稳的一种表现型式,岩爆烈度如何影响围岩类别尚不清楚,探索岩爆与围岩分类的关系,对准确判别高地应力条件下的围岩类别有着重要意义。本文以某深埋隧洞围岩分类为依据,对我国水利水电地下洞室围岩分类中岩爆烈度与围岩类别的关系、岩爆判别指标的选取等问题进行了探讨。     

A REVIEW ON THE APPLICATIONS OF DEEP LEARNING IN AIRCRAFT DYNAMICS AND CONTROL

飞行器动力学与控制历经多年的发展取得辉煌成就,也面临着一系列亟需解决的难题。深度学习基于存储、记忆、预训练的新模式为动力学与控制难题的解决提供了新途径。本文以提升飞行器控制自主性和智能水平为研究主题,从三个方面总结了深度学习在飞行器动力学与控制中的应用,包括：在动力学建模中应用深度学习来提升模型计算效率和建模精度、求解模型反问题;在最优控制中应用深度学习来提升轨迹规划速度、最优控制实时性和自主性;在飞行器任务设计中应用深度学习来提升任务优化的计算效率和决策水平。在此基础上,梳理了各个方案的优缺点和部分代表性成果。最后,给出了深度学习应用于飞行器动力学与控制的四点建议。     

Deep Learning for Real-Time Crime Forecasting and Its Ternarization

Real-time crime forecasting is important. However, accurate prediction of when and where the next crime will happen is difficult. No known physical model provides a reasonable approximation to such a complex system. Historical crime data are sparse in both space and time and the signal of interests is weak. In this work, the authors first present a proper representation of crime data. The authors then adapt the spatial temporal residual network on the well represented data to predict the distribution of crime in Los Angeles at the scale of hours in neighborhood-sized parcels. These experiments as well as comparisons with several existing approaches to prediction demonstrate the superiority of the proposed model in terms of accuracy. Finally, the authors present a ternarization technique to address the resource consumption issue for its deployment in real world. This work is an extension of our short conference proceeding paper [Wang, B., Zhang, D., Zhang, D. H., et al., Deep learning for real time Crime forecasting, 2017, arXiv: 1707.03340].     

主动抛光盘面形测试技术的研究

主动抛光盘技术是新发展起来的一种能够根据需要将抛光盘面实时地主动变形成离轴非球面来磨制深非球度高精度天文镜面的磨制技术。简单介绍了抛光盘变形控制结构和面形检测机构，对深非球面度面形变形进行了精度分析，探讨了主动抛光盘的动态响应和校正，并对抛光盘的改造提出了一些建议。