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.     

基于混合优化算法的关节臂式测量机参数标定

为进一步提高关节臂式坐标测量机等高机动性精密测量设备的测量精度,使用D-H矩阵法建立其关节坐标转换数学模型并据此推导出参数误差模型.针对非线性多参数标定问题,通过变换分析消除了最小二乘法求解时矩阵中的冗余参数,降低了计算的复杂性.设定判定准则并实现最小二乘法和模拟退火算法的混合,提出了一种基于混合优化算法的参数标定方法,解决了LM算法的初值设定和SA算法的搜索效率逐步降低的问题.实验结果表明:关节臂式测量机参数经混合优化算法标定后,参数的误差范围有了显著的缩小,单点重复性误差的平均值减小了1.746 mm,长度误差的平均值减小了0.941 mm,测量误差得到了进一步的抑制.     

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。     

A Shell-by-Shell Approach for Synthesis of Mesoporous Multi-Shelled Hollow MOFs for Catalytic Applications

Over the past two decades, advanced materials with hollow interiors have received significant attention in materials research owing to their great application potential across a vast number of technological fields. Though with great difficulty, multi-shelled hollow metal–organic frameworks (MSHMs) have also been successfully synthesized in recent years. Herein, a rational shell-by-shell soft-templating protocol has been devised to fabricate highly uniform multi-shelled hollow cobalt-imidazole-based MOF (ZIF-67). For the first time, it has become possible to endow mesoporosity to this new type of functional material (i.e., mesoporous MOFs). When used as carrier materials in catalytic reactions, in principle, these mesoporous MSHMs with high surface area not only improve the dispersity of metal nanoparticles (NPs), but also efficiently facilitate the mass diffusion of the reactions, resulting in enhanced catalyst activity. Moreover, the obtained MSHMs/M nanocomposites serve as base-metal bifunctional catalysts for one-pot oxidation-Knoevenagel condensation cascade reaction, in which the MSHMs itself serves as a pristine active catalyst in addition to its role of catalyst support. The results demonstrate that excellent multifunctional catalysts can be achieved via preparing intrinsically microporous bulk MOFs into extrinsically mesoporous MSHMs which possess many structural merits that conventional bulk MOFs do not have.     

In vivo comprehensive multiphase NMR

Traditionally, due to different hardware requirements, nuclear magnetic resonance (NMR) has developed as two separate fields: one dealing with solids, and one with solutions. Comprehensive multiphase (CMP) NMR combines all electronics and hardware (magic angle spinning [MAS], gradients, high power Radio Frequency (RF) handling, lock, susceptibility matching) into a universal probe that permits a comprehensive study of all phases (i.e., liquid, gel-like, semisolid, and solid), in intact samples. When applied in vivo, it provides unique insight into the wide array of bonds in a living system from the most mobile liquids (blood, fluids) through gels (muscle, tissues) to the most rigid (exoskeleton, shell). In this tutorial, the practical aspects of in vivo CMP NMR are discussed including: handling the organisms, rotor preparation, sample spinning, water suppression, editing experiments, and finishes with a brief look at the potential of other heteronuclei (²H, ¹⁵N, ¹⁹F, ³¹P) for in vivo research. The tutorial is aimed as a general resource for researchers interested in developing and applying MAS-based approaches to living organisms. Although the focus here is CMP NMR, many of the approaches can be adapted (or directly applied) using conventional high-resolution magic angle spinning, and in some cases, even standard solid-state NMR probes.     

高温作用后砂岩物理力学性质阈值温度的确定——基于机器学习算法

通过采用机器学习算法，提出了高温作用后砂岩物理力学性质变化的阈值温度的确定方法。基于Python语言，利用K-Means、SVM算法，实现了对样本数据的分类和聚类，确定了阈值温度区间，验证了二分类法的合理性和准确性.结果表明，砂岩样本的阈值温度区间为400~600 ℃，阈值温度上下砂岩的物理力学性质存在显著差异，体现为阈值温度区间以下的岩样物理力学性质较为分散，而阈值温度区间以上的岩样物理力学性质较为集中.     

高速电主轴热特性仿真与实验研究

对高速电主轴温度场分布随转速的变化规律进行了研究。通过在外壳上布置一定数量的温度传感器,对不同转速下的外壳温度进行实时测量,并将实验结果与ANSYS的模拟结果进行对比,验证了采用在电主轴外壳上布置多个测点测量与仿真相结合的方法来预测电主轴内部温度场分布的可行性;另外还分析了在不同转速下,高速电主轴关键部位的温升,仿真结果表明:主轴在6000~10000 r/min时,温升呈线性增加,在大于10000 r/min后,温升以指数规律增加。     

Anticancer SAR establishment and novel accruing signal transduction model of drug action using biscoumarin scaffold

In this paper, we have established methylenebis (4-hydroxy-2H-chromen-2-one) as a promising anticancer scaffold with kinesin spindle protein (KSP) inhibitory activity under malignant condition. A series of biscoumarin derivatives (MN1 to MN30) with different substituent were synthesized, and their anticancer activity was explored. Six biscoumarin derivatives that were found active were further selected to formulate organic nanoparticles (ONPs). Anticancer activity of both the forms (viz conventional and ONPs) was compared. MN30 was found most potent whereby MN10 showed good anticancer activity in both, i.e., conventional and ONP form; the structural activity relationship (SAR) study has been established. Computational investigation revealed biscoumarin scaffold as a suitable pharmacophore to bind against KSP protein. Molecular dynamics simulation studies revealed protein-ligand stability and dynamic behavior of biscoumarin-KSP complex. Finally, accruing signal transduction model was formulated to explain the observed MTT trend of conventional and ONP form. The model seems useful towards solving population specific varied results of chemotherapeutic agents. According to the model, MN10 and MN30 derivatives have good pharmacodynamics inertia and therefore, both the molecules were able to provide dose-dependent cytotoxic results.     

智能高速罐身电阻焊机数字化控制系统

提出了以国产MCT80 0 0F8运动控制器为核心的智能高速罐身电阻焊机数字化控制系统 ,并介绍了系统的组成、工作原理、硬件接口、电机控制方法以及伺服电机的运动关系数学模型 .新的系统有利于提高罐身电阻焊机的制罐生产速度 ,并具有功能全面、可靠性高、控制精确、开放性好以及成本较低等优点     

西文期刊回溯建库中几个重要项目的著录

在实践的基础上，从期刊的出版日期、出版周期、卷、期、年、月及其他标识、ISSN、增刊、出版者以及期刊的历史发展等方面对西文期刊机读目录的标准化著录问题进行了探讨。