Two Optimal Value Functions in Parametric Conic Linear Programming

Journal of Optimization Theory and Applications - We consider the conic linear program given by a closed convex cone in an Euclidean space and a matrix, where vector on the right-hand side of the...     

New Approach to Calculating the Double Coaxial Resonator with a Shortening Capacitance

Russian Physics Journal - The double coaxial resonator with a shortening capacitance is calculated by the partial volume method. The double resonator is represented by two single coaxial resonators...     

新型含吡啶基团二羧酸配体的合成及单晶培养

以1，4-二溴-2，5-二甲基苯和4-吡啶硼酸为原料，经两步合成了一种新颖的含吡啶基团的二羧酸配体。通过核磁共振氢谱及傅里叶变换红外光谱对配体结构进行表征，通过热重分析对配体的热稳定性进行了测试；通过溶剂热法对配体的单晶进行培养，并考察反应温度、时间、pH和溶剂等条件对单晶培养的影响。结果表明：在反应温度为80 ℃，反应时间为12 h、溶剂为蒸馏水、溶液pH=5的条件下可获得高质量单晶。该配体为单斜晶系，属于C2/c空间群，结构中含有4个氧原子和2个氮原子，可为金属离子的配位提供足够的位点，有望应用于配合物的设计或催化、吸附和医药载体等行业。     

Predicting 19F NMR Chemical Shifts: A Combined Computational and Experimental Study of a Trypanosomal Oxidoreductase–Inhibitor Complex

The absence of fluorine from most biomolecules renders it an excellent probe for NMR spectroscopy to monitor inhibitor–protein interactions. However, predicting the binding mode of a fluorinated ligand from a chemical shift (or vice versa) has been challenging due to the high electron density of the fluorine atom. Nonetheless, reliable ¹⁹F chemical-shift predictions to deduce ligand-binding modes hold great potential for in silico drug design. Herein, we present a systematic QM/MM study to predict the ¹⁹F NMR chemical shifts of a covalently bound fluorinated inhibitor to the essential oxidoreductase tryparedoxin (Tpx) from African trypanosomes, the causative agent of African sleeping sickness. We include many protein–inhibitor conformations as well as monomeric and dimeric inhibitor–protein complexes, thus rendering it the largest computational study on chemical shifts of ¹⁹F nuclei in a biological context to date. Our predicted shifts agree well with those obtained experimentally and pave the way for future work in this area.     

NUMERICAL SIMULATION OF FIBROBLAST DUROTAXIS MIGRATION INDUCED BY STIFFNESS GRADIENT OF SUBSTRATE1)

建立了一种细胞趋硬性迁移的理论模型和有限元分析框架,为连续变刚度人工基质的试验设计提供理论依据。考虑了细胞体的黏弹性属性,以及细胞与基质间的配受体动态反应过程,并以配受体合成时间为时间步长,将细胞运动方程化为静力学形式进行求解。对有限元过程提出一种动约束,便于消除其结构矩阵的奇异性。结果表明,模型能够模拟黏着斑内部力的快速波动现象,细胞的运动速度与观测数据一致,可有效模拟20,h以上的长时程问题。     

4D Printing based piezoelectric composite for medical applications

Additive manufacturing (AM), otherwise known as three‐dimensional (3D) printing, is driving major innovations in many areas, such as engineering, manufacturing, art, education, and medicine. Although a considerable amount of progress has been made in this field, additional research work is required to overcome various remaining challenges. Recently, one of the actively researched areas lies in the AM of smart materials and structures. Electroactive materials incorporated in 3D printing have given birth to 4D printing, where 3D printed structures can perform as actuating and/or sensing systems, making it possible to deliver electrical signals under external mechanical stimuli and vice versa. In this paper, we present a lightweight, low cost piezoelectric material based on the dispersion of inorganic ferroelectric submicron particles in a polymer matrix. We report on how the proposed material is compatible with the AM process. Finally, we discuss its potential applications for healthcare, especially in smart implants prostheses. © 2018 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2019 , 57, 109–115     

Data assimilation and pollution forecasting in Burgers' equation with model error function

This article presents a correction method for a better resolution of the problem of estimating and predicting pollution, governed by Burgers' equations. The originality of the method consists in the introduction of an error function into the system's equations of state to model uncertainty in the model. The initial conditions and diffusion coefficients, present in the equations for pollution and concentration, and also those in the model error equations, are estimated by solving a data assimilation problem. The efficiency of the correction method is compared with that produced by the traditional method without introduction of an error function.Three test cases are presented in this study in order to compare the performances of the proposed methods. In the first two tests, the reference is the analytical solution and the last test is formulated as part of the “twin experiment”.The numerical results obtained confirm the important role of the model error equation for improving the prediction capability of the system, in terms of both accuracy and speed of convergence.