质谱检测技术在火星探测中的应用

火星探测对人类寻找地外生命、探索行星产生和演化机制具有重要的科学意义.质谱技术已经在火星探测方面得到了实际应用,获得的数据正在改写着人类对火星的基本认识.本文综述了国内外质谱技术在火星探测任务中的应用现状,特别是我国学者的研究进展、存在问题和应对策略.     

基于宏微辨析核心素养分析高中《化学1(必修)》教材*

教材分析是连接教材和课程的桥梁,基于宏观辨识和微观探析核心素养,比较分析了2004年版和2019年版高中《化学1(必修)》教材的特点。通过运用“三序结合”原则,从静态视角对比教材栏目设置、内容组织形式、核心素养呈现方式、学生认知水平以及作业布置形式等5个维度要素在宏微辨析核心素养领域的建构。分析结果显示,2019年版《化学1(必修)》教材在以上要素方面均围绕宏微辨析核心素养,呈现不同水平阶梯型设置。建议在“宏微符”概念形成的过程中增设更为细致的过渡内容,以及更为详尽的与教材配套的辅助内容,便于教材的二次开发。     

基于证据推理的电化学综合实验探究

盐桥的作用众所周知,如果“将铜锌双液原电池的盐桥换成铜片后,电路中还有电流吗？两液中的铜片到底发生了什么反应？”,基于这些问题,开发了一系列实验,利用观察到的各种证据,如:生成的沉淀、溶液颜色的变化、电极质量的改变、溶液pH和电流计指针偏转方向等,引导学生对各个电极变化的反应进行假设,并设计新颖实验逐步探究证实,依据宏观实验现象的证据,开展问题驱动式学习,以此培育学生的科学探究与创新意识。     

A numerical exploration of secondary separation in starting flow around a flat plate by the discrete vortex model

In the present work, a further numerical simulation of the starting flow around a flat plate normal to the direction of motion in a uniform fluid has been made by means of the discrete vortex method. The secondary separation occurring at rear surface of the plate is explored, and predicted approximately using Thwait's method. The calculated results show that in the early stages of the flow secondary separation does occur. The evolution of flow field, the vortex growing process and the characteristics of secondary vortices have been described. The time dependent drag coefficients, the vorticity shed from the edges and rear surface, and the separation positions are calculated as well as the distributions of velocity and pressure on the plate. In the case of flow normal to the plate, the calculated secondary vortices are weak. Their existence will change the local velocity distributions and affect pressure distributions. However, the effect on drag coefficient is negligible.     

化工原理问题导向式线上教学的探索与实践*

以化学制药专科专业化工原理课程为例,阐述问题导向式线上教学的课程设计思路及框架,探索由被动教到主动学的线上教学途径。通过对“流体流动与输送单元”的教学设计,从课前、课中和课后论述了以“问题”为中心的线上教学过程和实施情况,并说明了线上授课的教学效果。     

An evidential approach to SLAM,path planning,and active exploration

Probability theory has become the standard framework in the field of mobile robotics because of the inherent uncertainty associated with sensing and acting. In this paper, we show that the theory of belief functions with its ability to distinguish between different types of uncertainty is able to provide significant advantages over probabilistic approaches in the context of robotics. We do so by presenting solutions to the essential problems of simultaneous localization and mapping (SLAM) and planning based on belief functions. For SLAM, we show how the joint belief function over the map and the robot's poses can be factored and efficiently approximated using a Rao-Blackwellized particle filter, resulting in a generalization of the popular probabilistic FastSLAM algorithm. Our SLAM algorithm produces occupancy grid maps where belief functions explicitly represent additional information about missing and conflicting measurements compared to probabilistic grid maps. The basis for this SLAM algorithm are forward and inverse sensor models, and we present general evidential models for range sensors like sonar and laser scanners. Using the generated evidential grid maps, we show how optimal decisions can be made for path planning and active exploration. To demonstrate the effectiveness of our evidential approach, we apply it to two real-world datasets where a mobile robot has to explore unknown environments and solve different planning problems. Finally, we provide a quantitative evaluation and show that the evidential approach outperforms a probabilistic one both in terms of map quality and navigation performance.     

生物基化工与材料产业技术的开发与探索

本文阐述了中国石油化工集团公司(中国石化)在生物基化工与材料领域的探索路径和发展战略,介绍了中国石化近年来在生物基单体、生物基材料与可降解材料等领域开展的创新实践及取得的阶段性成果,主要包括乳酸—聚乳酸、丁二酸/二元醇—生物可降解材料、长链二元酸—生物基尼龙以及生物质芳烃—聚对苯二甲酸乙二酯(PET)等技术领域.提出了建立生物基化工与材料科学技术平台、突破关键技术、发展新兴产业等建议.     

基于Matlab/Simulink的嫦娥二号探月轨道运动的动态仿真

建立了嫦娥二号卫星在有心力场中做轨道运动的动力学模型,使用MATLAB中的SIMU-LINK仿真工具实现了卫星在不同轨道的运动,并得到了卫星轨道运动的实时高度曲线。     

Biclustering Three-Dimensional Data Arrays With Plaid Models

Three-dimensional data arrays (collections of individual data matrices) are increasingly prevalent in modern data and pose unique challenges to pattern extraction and visualization. This article introduces a biclustering technique for exploration and pattern detection in such complex structured data. The proposed framework couples the popular plaid model together with tools from functional data analysis to guide the estimation of bicluster responses over the array. We present an efficient algorithm that first detects biclusters that exhibit strong deviations for some data matrices, and then estimates their responses over the entire data array. Altogether, the framework is useful to home in on and display underlying structure and its evolution over conditions/time. The methods are scalable to large datasets, and can accommodate a variety of dynamic patterns. The proposed techniques are illustrated on gene expression data and bilateral trade networks. Supplementary materials are available online.