Dynamic analysis of the double crank mechanism with a 3D translational clearance joint employing a variable stiffness contact force model

Nonlinear Dynamics - Oblique collisions are more likely to happen in the realistic translational joint with clearance, compared to the full front impacts. It can be a quite demanding task to...     

A New Radar-Signal Parameter for Recognition of Wind-Related Weather Hazards

Radiophysics and Quantum Electronics - Wind-related weather hazards remain difficult to recognize targets for weather radars. Methods that use estimates of the width of the reflected-signal...     

Optical Multisensor Systems in Analytical Spectroscopy

Journal of Analytical Chemistry - A review of works in developing optical multisensor systems, a new class of specialized spectroscopic analyzers, is presented. The development and use of such...     

Asymptotic Behavior of Least Energy Solutions for a Fractional Laplacian Eigenvalue Problem on ℝN

Acta Mathematica Sinica, English Series - We are interested in the existence and asymptotic behavior for the least energy solutions of the following fractional eigenvalue problem $$\left({\rm{P}}...     

Numerical Simulation of Physical Fields by the Collocation Method

Russian Physics Journal - The article describes the collocation method for the numerical solution of mathematical physics boundary value problems. By arranging the collocation nodes in a special...     

基于电化学老化衰退模型的锂离子动力电池外特性

当前锂离子动力电池电化学模型存在模型复杂、建模难度大、计算效率低、老化评估效果差的问题,本文提出一种考虑电池衰退老化的机理模型(ADME).本文首先通过有限差分法对伪二维(P2D)电化学模型进行离散降阶处理,得到简化伪二维(SP2D)模型.在SP2D模型的基础上,基于阴阳两极发生的副反应导致的衰退老化现象,提出一种考虑电池衰退老化的机理模型.其次,使用多变量偏差补偿最小二乘法实现模型参数辨识.最后通过动力电池衰退老化性能循环实验,对比分析了恒流、脉冲工况下SP2D模型和ADME模型的终端电压输出.结果表明:ADME模型较为简单、计算效率和估算精度高,可以有效评估电池容量老化衰退,得到理想的锂离子动力电池外特性曲线.     

紫色球杆菌视紫红质光谱特性的机器学习研究

近年来，机器学习等人工智能技术被应用于蛋白质工程，其在蛋白质结构、功能预测、催化活性等研究中具有独特优势。在未知蛋白质结构的情况下，将蛋白质序列和功能特性与机器学习相结合，基于序列-活性关系（innovative sequence-activity relationship，ISAR）算法，将蛋白质氨基酸序列数字化，用快速傅里叶变换（fast four transform，FFT）进行预处理，再进行偏最小二乘回归建模，可在数据集较少情况下拟合得到最佳模型。通过机器学习对紫色球杆菌视紫红质（gloeobacter violaceus rhodopsin，GR）的突变体蛋白质氨基酸序列与光谱最大吸收波长进行建模，获得了最佳模型。用最佳索引LEVM760106建模得到的确定系数R² 为0.944，均方误差E为11.64。用小波变换进行的预处理，其R² 虽也约为0.944，但E大于11.64，不及FFT进行的预处理。方法较好地解决了蛋白质序列与功能特性之间的数学建模问题，在蛋白质工程中可为预测更优的突变体提供支持。     

Synthesis of Substituted Aminopyrimidines as Novel Promising Tyrosine Kinase Inhibitors

Russian Journal of Organic Chemistry - A procedure has been proposed for the synthesis of a series of substituted N-(1,3-thiazol-2-yl)-pyrimidin-2-amines and N-(pyrimidin-2-yl)thioureas by...