Optimal approach to rotational state reconstruction of linear molecules

We present a simulation for the reconstruction of the rotational quantum state of linear molecules to retrieve the density matrix. An optimal approach in the sense of minimal error limit is proposed, in which a variable set of angular frequency is properly chosen and the least square inversion is then applied. This approach of reconstruction from time-dependent molecular-axis angular distribution is proved adaptable for various object states, which has a good numerical stability independent of the selected rotational space.

State reconstruction of molecular spatial rotation

We establish a reconstruction approach for the rotational quantum state of linear molecules possessing a magnetic manifold. Our approximate method contains an iteration with generalized matrix inverses, processing the tomographic integral of the time-dependent molecular-axis distribution in a polar angle. As shown in a simulated example for an alignment state, the density matrix is determined in a high fidelity. An analytic tomographic formula is also derived for the symmetric top rotation. The state coherent in the quantum space of both the angular momentum and its magnetic projection can be approximately retrieved from the observable time-resolved solid-angle distribution of the molecular axis.

State Reconstruction for Complex Dynamical Networks with Noises

The state reconstruction problem is addressed for complex dynamical networks coupled with states and outputs respectively, in a noisy transmission channel. By using Lyapunov stability theory and H∞ performance, two schemes of state reconstruction are proposed for the complex dynamical networks with the nodes coupled by states and outputs respectively, and the estimation errors are convergent to zeros with H∞ performance index. A numerical simulation demonstrates the effectiveness of the proposed observers.

Challenges in estimating ancestral state reconstructions:the evolution of migration in Sylvia warblers as a study case

Our current understanding of how species have evolved is mainly based on comparative phylogenetic methods,which use phylogenies to infer the evolution of traits.The development of ancestral state reconstruction(ASR)methods has provided the tools to reconstruct trait evolution,which are widely used in fields like evolutionary biology,macroecology and paleontology.As there are different elements involved in those analyses,with different levels of uncertainty(i.e.relating to branch length estimation,trait coding,statistical framework,taxon sampling or software),the various combinations of these elements likely have a strong impact on the reconstruction of the evolution of traits,potentially leading to opposite conclusions.To assess the impact of these different elements in ASR,we performed a set of analyses,including all possible combinations of such elements and using the evolution of migratory behavior in Sylvia warblers as a case study,which was coded as a continuous or as a discrete character.Our results show that taxon sampling,character coding,tree shape,statistical framework and software all significantly affect ASR,both individually and in combination.Not all reconstructed tree nodes show discrepancies,but in the critical ones most pairwise comparisons between analyses lead to conflicting and unexpectedly antagonistic results(zero migration vs fully migratory),thus challenging interpretations of trait evolution.We propose some possible solutions to partly inform decisions,involving the method selection and the incorporation of biological or fossil evidence regarding how traits evolve,but our results demand serious rethinking about how the research community currently uses ASR.

THE STATE SPACE RECONSTRUCTION TECHNOLOGY OF DIFFERENT KINDS OF CHAOTIC DATA OBTAINED FROM DYNAMICAL SYSTEM

Certain deterministic nonlinear systems may show chaotic behavior. We consider the motion of qualitative information and the practicalities of extracting a part from chaotic experimental data. Our approach based on a theorem of Takens draws on the ideas from the generalized theory of information known as singular system analysis. We illustrate this technique by numerical data from the chaotic region of the chaotic experimental data. The method of the singular-value decomposition is used to calculate the eigenvalues of embedding space matrix. The corresponding concrete algorithm to calculate eigenvectors and to obtain the basis of embedding vector space is proposed in this paper. The projection on the orthogonal basis generated by eigenvectors of timeseries data and concrete paradigm are also provided here. Meanwhile the state space reconstruction technology of different kinds of chaotic data obtained from dynamical system has also been discussed in detail.

AN ANALYTIC AND APPLICATION TO STATE SPACE RECONSTRUCTION ABOUT CHAOTIC TIME SERIES

The state space, reconstruction is the major important quantitative index for describing non-linear chaotic time series. Based on the work of many scholars, such as: AT. H. Packard, F. Takens, M. Casdagli, J. F. Gibson, CHEN Yu-shu et al, the state space was reconstructed using the method of Legendre coordinate. Several different scaling regimes for lag time tau were identified. The influence for state space reconstruction of lag time tau was discussed. The result tells us that is a good practical method for state space reconstruction.

RAD-seq data reveals robust phylogeny and morphological evolutionary history of Rhododendron

Rhododendron is famous for its high ornamental value.However,the genus is taxonomically difficult and the relationships within Rhododendron remain unresolved.In addition,the origin of key morphological characters with high horticulture value need to be explored.Both problems largely hinder utilization of germplasm resources.Most studies attempted to disentangle the phylogeny of Rhododendron,but only used a few genomic markers and lacked large-scale sampling,resulting in low clade support and contradictory phylogenetic signals.Here,we used restriction-site associated DNA sequencing(RAD-seq)data and morphological traits for 144 species of Rhododendron,representing all subgenera and most sections and subsections of this species-rich genus,to decipher its intricate evolutionary history and reconstruct ancestral state.Our results revealed high resolutions at subgenera and section levels of Rhododendron based on RAD-seq data.Both optimal phylogenetic tree and split tree recovered five lineages among Rhododendron.Subg.Therorhodion(cladeⅠ)formed the basal lineage.Subg.Tsutsusi and Azaleastrum formed cladeⅡand had sister relationships.CladeⅢincluded all scaly rhododendron species.Subg.Pentanthera(cladeⅣ)formed a sister group to Subg.Hymenanthes(cladeⅤ).The results of ancestral state reconstruction showed that Rhododendron ancestor was a deciduous woody plant with terminal inflorescence,ten stamens,leaf blade without scales and broadly funnelform corolla with pink or purple color.This study shows significant distinguishability to resolve the evolutionary history of Rhododendron based on high clade support of phylogenetic tree constructed by RAD-seq data.It also provides an example to resolve discordant signals in phylogenetic trees and demonstrates the application feasibility of RAD-seq with large amounts of missing data in deciphering intricate evolutionary relationships.Additionally,the reconstructed ancestral state of six important characters provides insights into the innovation of key characters in Rhododendron.

引入风流热流耦合特性的智能通风系统状态重构参数修正

为精准定量重构时间序列下实际矿井通风系统状态,以实时反映风网运行特征,基于实际矿井中风流的空气动力耦合热力流动特征,提出了时空特征下风流状态属性变化式,以井下网络和通风动力参数作为修正指标,以动态风流状态属性为修正变量,提出了通风系统状态重构参数点修正模型。为表述通风系统的动态连续运行状态,在点修正基础上引入连续时间特征,构建状态重构参数区间映射修正模型,以求解出时间序列下的系统状态重构参数波动区间来完成精准状态重构。为验证修正模型可靠性,以常村煤矿为工程对象进行状态重构,结果验证了井下风流的动态热流耦合特征及提出的风流状态属性变化式的可靠性,得出了状态重构参数波动区间,达到了实时准确构建风网运行状态的目的,有效提高了后续风网实时解算和控风决策的本质精度。

基于RSS_GN RRT算法的狭长空间路径规划

针对RRT算法在狭长空间中存在的收敛速度慢及规划路径不平滑的问题,提出了一种RSS_GN RRT算法。为了提升算法的收敛速度,提出了引导节点导向策略与分区域采样策略,极大地减少了算法对无效区域的搜索;其次,算法引入了采样角度约束策略来提高规划路径的质量,并采用父节点拓展选择的方法有效解决了由角度约束引起的迭代次数增加的问题。此外,算法可根据感知信息进行地图地动态重构并规划避障路径,提高了算法在低速动态环境中的适应性。仿真结果显示,在狭长通道环境中,RSS_GN RRT算法在规划路径的耗时上比RRT、Goal_bias RRT、角度约束下的RRT、Informed RRT*及DR-RRT算法分别减少了77.3%,51.9%,84.7%,98.8%和60.3%。在迭代次数上,相比于上述算法,分别减少了95.9%,92%,98.3%,98.3%和89.5%。路径的平均曲率也分别降低了94.1%,93.2%,88.7%,91%和92.9%。仿真结果证明了RSS_GN RRT算法在提升规划速度和改善路径质量方面具有显著优势。同时,本文采用了阿克曼模型的小车实测了算法的局部避障能力。经测试,小车可对行驶途中出现的障碍物进行合理避让。

Reconstructing ancestral ranges in historical biogeography:properties and prospects

Recent years have witnessed a proliferation of quantitative methods for biogeographic inference. In particular, novel parametric approaches represent exciting new opportunities for the study of range evolution. Here, we review a selection of current methods for biogeographic analysis and discuss their respective properties. These methods include generalized parsimony approaches, weighted ancestral area analysis, dispersal-vicariance analysis, the dispersal--extinction--cladogenesis model and other maximum likelihood approaches, and Bayesian stochastic mapping of ancestral ranges, including a novel approach to inferring range evolution in the context of island biogeography. Some of these methods were developed specifically for problems of ancestral range reconstruction, whereas others were designed for more general problems of character state reconstruction and subsequently applied to the study of ancestral ranges. Methods for reconstructing ancestral history on a phylogenetic tree differ not only in the types of ancestral range states that are allowed, but also in the various historical events that may change the ancestral ranges. We explore how the form of allowed ancestral ranges and allowed transitions can both affect the outcome of ancestral range estimation. Finally, we mention some promising avenues for future work in the development of model-based approaches to biogeographic analysis.

动态障碍物状态空间重构的无人车路径规划

为了保证无人驾驶汽车在动态障碍物的环境下,实现安全的避障路径规划,提出了一种基于动态障碍物状态空间重构的避障路径规划方法。该避障路径规划方法,以前轮偏角为控制量,运用模型预测控制(MPC)方法,忽略车身尺寸信息建立点质量模型,主要在规划层中利用车载传感器的采集信息,对动态障碍物状态空间信息进行重构,研究不同重构构型对避障效果以及“穿越”现象的影响问题。在特定行驶工况中,采用CarSim和Simulink进行联合仿真,以低中高三种速度进行动态障碍物避障稳定性分析,仿真结果表明,所提出的避障路径规划方法对于存在动态障碍物环境下是有效的,避免了由于忽略车身尺寸所导致的“穿越”现象,通过与传统人工势场法比较,验证了本方法规划的路径更短,避障曲率更优。基于动态障碍物状态空间重构的避障路径规划具有安全性和稳定性。

双循环背景下城市群的空间重构与规划应对——基于新国家空间理论

基于新国家空间理论,构建了“资本循环-空间建构-规划应对”的分析框架,审视由“外循环”向“双循环”转变过程中城市群的空间重构需求,提出相应的规划编制策略。研究发现:双循环新发展格局下,中国城市群在全球、国家和区域尺度均面临多重挑战。现阶段中国19个国家级城市群在经济循环中需担任不同的角色:成熟型城市群参与外循环,发展型城市群驱动内循环,培育型城市群组织微循环。为实现城市群空间重构,3种类型的城市群需有不同的国家空间工程构建逻辑和规划传导原则,以及国家空间策略部署途径和规划编制重点。本文的研究结果填补了空间规划服务于国家新发展格局的理论空白,从城市群角度为双循环战略提供重要理论和规划支撑。

改进Tikhonov正则化方法在结构激励识别与响应重构中的应用

为了改善传递矩阵的病态性,实现利用结构有限测量信息对结构外部激励与未知响应的有效重构,提出了一种用于结构激励识别与响应重构的改进Tikhonov正则化方法。首先,基于状态空间模型构建传递矩阵,并推导结构外部激励识别与响应重构方程。其次,采用改进Tikhonov正则化方法改善传递矩阵的病态性,得到激励方程的正则化解,并结合结构需重构位置对应的传递矩阵重构未知加速度响应。最后,分别对平面二维桁架和简支梁进行数值仿真和试验分析,验证所提方法的可行性。结果表明所提方法能够改善传递矩阵的病态性,提高结构激励识别与响应重构的精度。

电流传感器故障状态下内嵌式永磁同步电机的无位置传感器容错控制算法研究

为了解决在永磁同步电机(PMSM)驱动控制中,电流传感器可能出现故障导致系统失控的问题,提出一种变参数的相电流重构方法,对定子电流进行精确观测,实现PMSM在无位置传感器控制下的电流传感器容错控制。研究了电机参数扰动和无位置传感器控制观测误差等非理想因素对直接搭建龙贝格观测器精度的影响。分析了观测电流的幅值误差和角度误差特性,通过引入2个自适应变化参数以调整重构电流的幅值,消除非理想因素对重构电流精度的影响。搭建仿真和实验平台验证算法有效性。实验结果表明,电流传感器故障后,电角度观测误差仅增加1°,dq轴电流波动峰峰值仅增加0.1 A。该算法能够实现电机的转速、位置及电流信息的准确观测,使得系统具有良好的稳态精度和动态性能。

负反馈和状态空间重构的UPWM失真问题校正方法

针对数字D类音频功率放大器中的均匀采样脉冲宽度调制(Uniform-Sampling Pulse Width Modulation,UPWM)失真,提出了一种负反馈和状态空间重构的全数字UPWM失真问题校正方法。该方法利用数字Σ-Δ(Sigma-Delta)调制器的高开环增益特性,通过构造包含数字Σ-Δ调制器和UPWM发生器的闭环负反馈环路,使得环路的输入与输出近似呈线性关系,从而校正UPWM产生的失真。在构造闭环时,通过对数字Σ-Δ调制器的状态空间表达式进行重构,并添加插零值模块和抽取模块使该环路在保持稳定性的同时,拥有与原数字Σ-Δ调制器相同的噪声整形效果。实验结果表明,该方法相比其他的UPWM失真校正方法,不仅能降低谐波失真,还能大幅降低数字UPWM调制器输出信号的本底噪声,从而可使数字UPWM调制器在频率6 kHz和幅度为满量程的-5 dB的正弦数字信号输入情况下,输出信噪失真比达到95.26 dB,同时所提方法可全数字电路实现、硬件实现简单且易于移植。

基于CT扫描研究颗粒形状对砂土力学性质的影响

为了探究颗粒形状对砂土力学性质的影响,选取玻璃珠、石英砂、玻璃渣3种颗粒形状差异较大的砂土作为研究对象。首先通过计算机断层(computed tomography,CT)扫描重构了3种砂土的三维结构,选取了伸长率(EI)、扁度(FI)、球度(S)3个表征颗粒形状参数的均值作为砂土颗粒整体形状参数(overall regularity,OR),并对整体形状参数OR进行统计分析。然后配制7种不同形状参数的砂土进行了常规三轴压缩试验得到了其力学强度参数,研究砂土颗粒形状对其力学强度的影响规律。结果表明:7种砂土的应力-应变曲线均为应变软化型,都呈现出先剪缩后剪胀的特性;整体形状参数OR能较好反映砂土的力学特征,即随着整体形状参数OR的减小,应变软化现象变得不明显,但其峰值偏应力呈增大的趋势;砂土的内摩擦角随整体形状参数OR的减小呈线性增长,表观黏聚力急剧增大,但最大剪胀角随OR的减小而减小。此外,将临界内摩擦角与整体形状参数OR进行线性拟合,得到了两者较好的线性关系。

智能汽车信息物理系统状态估计与执行器攻击重构

针对含有网络攻击的非线性广义系统形式描述的信息物理系统,本文研究其状态估计和攻击信号重构问题。首先,将广义系统形式上写成一般系统,利用中间变量重构攻击信号,设计出中间变量观测器;而后,通过线性矩阵不等式得出观测器增益矩阵存在的充分条件;最后,利用数值仿真验证所提方法的可行性。仿真分析中,针对智能汽车的车道保持系统进行建模,将车辆动力模型和车辆保持模型转化为动力系统的形式,从信息物理系统的角度出发,研究车辆的安全状态估计问题。当系统含有网络攻击时,利用所提观测器对车道保持系统状态进行估计,结果表明设计的中间变量观测器能够准确地估计系统状态和攻击信号,且误差系统均在4 s内趋于稳定。

保通状态下高速公路改扩建路面拼宽施工技术研究

针对高速公路改扩建路面拼宽施工高低差较大影响路面通行质量的问题,文章研究了保通状态下高速公路改扩建路面拼宽施工技术。通过采取布置高速公路改扩建路面拼接段隔离墩,拆除改建段中原限速标志,增设限速标志与临时隔离设施,铣刨高速公路原路面重新加铺稳定碎石基层,铣刨旧路部分,并加铺碎石沥青混凝土基层。拼接高速公路改扩建路面面层,在面层之间洒布黏层油,确保面层之间的拼接效果,最后对实例进行分析,验证了该技术的施工质量。

电能计量装置异常状态监测方法研究

电能计量装置计量过程中,受功率谱谐波震颤强度影响,其状态指标数据呈现高度混沌状态,导致监测性能较差。为此,提出基于改进聚类分析的电能计量装置异常状态监测方法。通过构建电能计量装置状态评估体系,选取具有评估价值的技术指标及其对应的参数指标,并将相关指标参数视为待分类对象,以获取电能计量装置运行状态的混沌样本数据。利用蚁群算法优化K-Means聚类方法的聚类指标数据,实现电能计量装置状态监测。试验结果表明:该方法应用后的电能计量装置异常状态检出率较高,并且预测值与实际值的拟合率、准确率均较高。该方法监测性能较好。

美国联邦政府与研究型大学的关系重构——万尼瓦尔·布什革新美国科研管理体制的理念与实践研究

伴随知识经济的崛起,大学日益成为社会的轴心机构。政府与大学建立何种关系,成为各国重构社会秩序和政治经济体系的过程中必须直面的问题。万尼瓦尔·布什革新美国科研管理体制的过程中,不仅从知识转化的模式调整、学术生产的范式变革和研究型大学的国家战略地位等方面论证了联邦政府参与研究型大学管理的应然性,而且建构了以学术逻辑为核心的科研管理模式、政府调控的科研成果转换机制、开放合作的科学信息交流机制,凸显了美国联邦政府在参与研究型大学管理体系中以基础研究为核心的科研取向、以“文化绅士”为核心的人才培养取向、以国家利益为导向的社会服务取向。