Spatial Pattern and Time Series Dynamics of Spondylis buprestoides Adults

Spondylis buprestoides adults in Pians masoniana forests in Xianju Dabei Dixi Forestry Center were continuously investigated during 2006 and 2011. According to the survey data, multiple spatial pattern indicators of adult population were calculated, and the relationship between various indicators and density was analyzed. The K values of negative binomial distribution less affected by density were selected to describe the spatial pattern and time series dynamics of S. buprestoides adults. The results indicated that S. buprestoides adults showed aggregated distribution in the forest, but the aggregation degree varied with the season. There were 2 obvious diffusion peaks during May and June as well as September and October each year. The aggregation trend within a generation was aggregation-diffusion-aggregation.

Space-time Dynamics of Dendroctonus valens Population in China and Spatial Sampling Technique based on Its Spatial Distribution Pattern

Red turpentine beetle （RTB）, Dendroctongs valens LeConte, is a destructive forest invasive species in China, it mainly attacks Pings tabuliformis and P. bungeana. So far it has spread rapidly to the provinces of Shanxi, Hebei, Henan, Shanxi and Beijing since its first outbreak in Shanxi Province in 1998, and has caused extensive tree mortality. Space-time dynamics of D. valens population and spatial sampling technique based on its spatial distribution pattern were ana- lyzed using geostatistical methods in the pure P. tabuliforis forests and mixedwood stands which were at different damage levels. According to the spatial distribu- tion of D. valeas population, the specific spatial sampling technique was also studied, and then was compared with traditional sampling technique. The spatial sam- piing technique combined with sampling theory and the biological characteristics of D. valens population, which not only could calcnlate the error of the sampling, but also could discuss the optimal sampling number and the optimum size of plot according to different damage levels and different stand types. This helps to explain population expansion and colonization mechanism of D. valens, and to provide a good reference for adopting snitable control measures.

Discrete time transfer matrix method for dynamics of multibody system with flexible beams moving in space

In this paper, by defining new state vectors and developing new transfer matrices of various elements mov- ing in space, the discrete time transfer matrix method of multi-rigid-flexible-body system is expanded to study the dynamics of multibody system with flexible beams moving in space. Formulations and numerical example of a rigid- flexible-body three pendulums system moving in space are given to validate the method. Using the new method to study the dynamics of multi-rigid-flexible-body system mov- ing in space, the global dynamics equations of system are not needed, the orders of involved matrices of the system are very low and the computational speed is high, irrespec- tive of the size of the system. The new method is simple, straightforward, practical, and provides a powerful tool for multi-rigid-flexible-body system dynamics.

Quantitative division of succession and spatial patterns among different stand developmental stages in Changbai Mountains

Broadleaf-Korean pine forests exhibit high species richness and distinctive species composition, which are currently becoming more dominant among natural forests in Changbai Mountains of northeastern China. Understanding the ecological process of restored vegetation is quite important for ecosystem reconstruction. Distinguishing stand development stages and analyzing the dynamic spatial patterns could provide insights into significant community coexistence mechanisms. In the present study, eight permanent study areas were established according to the substituting space for time method in Changbai Mountains of north-eastern China. The optimal division method was used to quantify the successional series into different stand development stages, and the point pattern analysis method(L(r) function) was used to analyse the dynamic changes in spatial patterns and interspecific associations. Our results suggested that:(1) The stand development process was divided into five stages: the first three stages were poplar-birch secondary forests in different stages of recovery, the fourth stage was thespruce-fir mixed forest, and the last stage was the primary broadleaf-Korean pine forest;(2) The spatial pattern showed an aggregated distribution at a small scale and changed to a random distribution as the scale increased in poplar-birch secondary forests, but the spatial pattern appeared to be randomly distributed in spruce-fir mixed forest and broadleafKorean pine forest;(3) The interspecific associations between pioneer species and climax species changed from negative to positive among the different stand stages, and environmental resources were shared among these species. Interspecific differences in shade tolerance among the tree species were key determinants of forest dynamics and structure. Our study is vital to the understanding of the forest development;thus, the spatial change features should receive greater attention when forest management is being planned and restoration strategies are being developed for the Changbai Mountains.

Dynamic Stability Analysis of Linear Time-varying Systems via an Extended Modal Identification Approach

The problem of linear time-varying（LTV） system modal analysis is considered based on time-dependent state space representations, as classical modal analysis of linear time-invariant systems and current LTV system modal analysis under the ＂frozen-time＂ assumption are not able to determine the dynamic stability of LTV systems. Time-dependent state space representations of LTV systems are first introduced, and the corresponding modal analysis theories are subsequently presented via a stabilitypreserving state transformation. The time-varying modes of LTV systems are extended in terms of uniqueness, and are further interpreted to determine the system＇s stability. An extended modal identification is proposed to estimate the time-varying modes, consisting of the estimation of the state transition matrix via a subspace-based method and the extraction of the time-varying modes by the QR decomposition. The proposed approach is numerically validated by three numerical cases, and is experimentally validated by a coupled moving-mass simply supported beam exper- imental case. The proposed approach is capable of accurately estimating the time-varying modes, and provides anew way to determine the dynamic stability of LTV systems by using the estimated time-varying modes.

A novel robust fixed time synchronization of complex network subject to input nonlinearity in the presence of uncertainties and external disturbances

This paper studies the global fixed time synchronization of complex dynamical network,including non-identical nodes with disturbances and uncertainties as well as input nonlinearity.First,a novel fixed time sliding manifold is constructed to achieve the fixed time synchronization of complex dynamical network with disturbances and uncertainties.Second,a novel sliding mode controller is proposed to realize the global fixed time reachability of sliding surfaces.The outstanding feature of the designed control is that the fixed convergence time of both reaching and sliding modes can be adjusted to the desired values in advance by choosing the explicit parameters in the controller,which does not rest upon the initial conditions and the topology of the network.Finally,the effectiveness and validity of the obtained results are demonstrated by corresponding numerical simulations.

The Dynamic Relationship of Brain Networks Across Time Windows During Product-Based Creative Thinking

Consensus of creativity research suggests that the measurement of both originality and valuableness is necessary when designing creativity tasks.However,few studies have emphasized valuableness when exploring underlying neural substrates of creative thinking.The present study employs product-based creativity tasks that measure both originality and valuableness in an exploration of the dynamic relationship between the default mode(DMN),executive control(ECN),and salience(SN)networks through time windows.This methodology highlights relevance,or valuableness,in creativity evaluation as opposed to divergent thinking tasks solely measuring originality.The researchers identified seven brain regions belonging to the ECN,DMN,and SN as regions of interest(ROIs),as well as four representative seeds to analyze functional connectivity in 25 college student participants.Results showed that all of the identified ROIs were involved during the creative task.The insula,precuneus,and ventrolateral prefrontal cortex(vlPFC)remained active across all stages of product-based creative thinking.Moreover,the connectivity analyses revealed varied interaction patterns of DMN,ECN,and SN at different thinking stages.The integrated findings of the whole brain,ROI,and connectivity analyses suggest a trend that the DMN and SN(which relate to bottom-up thinking)attenuate as time proceeds,whereas the vlPFC(which relates to top-down thinking)gets stronger at later stages;these findings reflect the nature of our creativity tasks and decision-making of valuableness in later stages.Based on brain region activation throughout execution of the task,we propose that product-based creative process may include three stages:exploration and association,incubation and insight,and finally,evaluation and decision making.This model provides a thinking frame for further research and classroom instruction.

A Multi-Hop Dynamic Path-Selection (MHDP) Algorithm for the Augmented Lifetime of Wireless Sensor Networks

In Wireless Sensor Networks (WSN), the lifetime of sensors is the crucial issue. Numerous schemes are proposed to augment the life time of sensors based on the wide range of parameters. In majority of the cases, the center of attraction will be the nodes’ lifetime enhancement and routing. In the scenario of cluster based WSN, multi-hop mode of communication reduces the communication cast by increasing average delay and also increases the routing overhead. In this proposed scheme, two ideas are introduced to overcome the delay and routing overhead. To achieve the higher degree in the lifetime of the nodes, the residual energy (remaining energy) of the nodes for multi-hop node choice is taken into consideration first. Then the modification in the routing protocol is evolved (Multi-Hop Dynamic Path-Selection Algorithm—MHDP). A dynamic path updating is initiated in frequent interval based on nodes residual energy to avoid the data loss due to path extrication and also to avoid the early dying of nodes due to elevation of data forwarding. The proposed method improves network’s lifetime significantly. The diminution in the average delay and increment in the lifetime of network are also accomplished. The MHDP offers 50% delay lesser than clustering. The average residual energy is 20% higher than clustering and 10% higher than multi-hop clustering. The proposed method improves network lifetime by 40% than clustering and 30% than multi-hop clustering which is considerably much better than the preceding methods.

Fixed Time Control of Dynamic Positioning Ship with Unknown Interference

This paper proposes a fixed-time control scheme to ensure that the dynamic positioning can accurately reach the specified position under external interference. A fixed-time state observer was developed to accurately estimate the total external unknown interference. Based on the dynamic positioning ship motion model, the inversion design method is used to ensure the stability of the system and eliminate various uncertain effects. A fixed-time backstepping sliding mode controller is designed. Finally, the simulation results show that the method has good performance and advantages.

Dynamic obstacles detection of tram based on laser radar

The detection of obstacles in a dynamic environment is a hot and difficult problem.A method of autonomously detecting obstacles based on laser radar is proposed as a safety auxiliary structure of tram.The nearest neighbor method is used for spatial obstacles clustering from laser radar data.By analyzing the characteristics of obstacles,the types of obstacles are determined by time correlation.Experiments were carried out on the developed unmanned aerial vehicle(UAV),and the experimental results verify the effectiveness of the proposed method.

Spatial Accessibility to Shopping Malls in Nanjing,China:Comparative Analysis with Multiple Transportation Modes

This study attempts to evaluate the rationality of the spatial layout of shopping malls and identify the urban area with poor shopping mall accessibility,as well as to provide a reference and assist decision-making for planning.Using the case of Nanjing,China,this study developed a method to evaluate the accessibility of shopping malls by three transport modes(car traffic,public transit,and bicycle).Specially,we divide the urban space into a regular hexagonal grid and harvest the total travel time from each of 7204 hexagon centroids to each of 129 shopping malls using the Baidu Internet map.The door-to-door travel time approach is used to evaluate all travel stages(walking,waiting,transfer,and transportation)based on travel time calculations.We further divide the shopping malls into two levels(super-regional and regional)based on the Dianping App’s information and develop the indicator of accessibility to shopping malls:the number of shopping malls within tolerance time thresholds and apply the closest facility and cumulative opportunities methods to measure accessibility scores.The results show that the accessibility estimations vary greatly with transport modes.The accessibility of shopping malls presents a concentric ring trend centered on the city center under the car traffic and bicycle modes.And public transit accessibility tends to axially extend due to the topology of bus routes and metro lines.In particular,we observe that the accessibility of shopping malls in Nanjing has an uneven spatial distribution pattern,with high accessibility values in the central urban areas and lots of underserved areas in urban fringe regions.Based on the accessibility measurements,we finally map the poor accessibility area and propose corresponding implications for urban planning.

基于EOF-DBSCAN-GRU的分布式光伏集群出力预测方法研究

提出一种基于EOF-DBSCAN划分集群的改进统计升尺度的光伏集群出力预测建模方法。针对传统统计升尺度方法子集群中光伏电站出力特性不一致问题,通过皮尔逊相关系数和经验正交函数(EOF)优化特征空间,再根据密度聚类模型(DBSCAN)对区域内光伏电站划分集群,从而增强光伏电站聚类后集群出力特性的一致性。针对待预测日权重系数时间序列动态特性的提取、预测问题,提出一种基于动态时间规整(DTW)的相似日选取算法。最后利用循环神经网络(GRU)模型进行光伏电站出力预测。实验表明该集群预测方法的平均误差百分数(MAPE)约为6.33%,均方根误差(RMSE)约为13.93 kW,均方误差(MSE)为194.25 kW,通过实际光伏电站数据证明了所提方法的准确性和有效性。

Seeing through dynamics scattering media:Suppressing diffused reflection based on decorrelation time difference

We observed a phenomenon that different scattering components have different decorrelation time.Based on decorrelation time difference,we proposed a method to image an object hidden behind a turbid medium in a reflection mode.In order to suppress the big disturbance calused by reflection and back scattering,two framnes of speckles are recorded in sequence,and their difference is used for image reconstruction.Our method is immune to both medium motions and object movements.

中蒙干旱半干旱区降水的时空变化特征(Ⅰ):年降水特征及5～9月降水的REOF分析

此系姐妹篇文章的上篇,利用中蒙地区106站1954—2005年间的实测降水资料,使用EOF及REOF等统计方法,整体地分析了中蒙干旱半干旱区降水的时空变化特征。结果表明:(1)中蒙干旱区的降水分布很不均匀(我国西北区尤甚),从该区东南侧最湿的陕南向南疆盆地东端极端干旱区过渡,年雨量从922mm锐减到25mm以下,最干的托克逊仅6.9mm;蒙古国以中北部最湿,年雨量达400mm以上,到南部仅100mm左右,再到西南角仅30mm左右。(2)该区降水分布受不同尺度地形影响大,降水的年及年际变化也大。约80%的降水集中在夏半年(5～9月),南疆盆地东端干中心区的年降水相对变率最大,接近0.80,远高于蒙古国和我国其他地区,也高于全球明显增暖前。其干旱程度及降水变率居世界8大干旱区前列。(3)该区降水异常分布的局域特征明显。区内夏半年的降水异常分布常出现河东、南疆、汉中关中、北疆、蒙古国中北部、河西阿拉善,以及柴达木等7个模态。(4)过去50余年来,中蒙地区东北部的降水总体呈线性减少趋势,而西南部则呈增加趋势。

Optimal Predictive Control for Path Following of a Full Drive-by-Wire Vehicle at Varying Speeds

The current research of the global chassis control problem for the full drive-by-wire vehicle focuses on the control allocation （CA） of the four-wheel-distributed trac- tion/braking/steering systems. However, the path following performance and the handling stability of the vehicle can be enhanced a step further by automatically adjusting the vehicle speed to the optimal value. The optimal solution for the combined longitudinal and lateral motion control （MC） problem is given. First, a new variable step-size spatial transformation method is proposed and utilized in the prediction model to derive the dynamics of the vehicle with respect to the road, such that the tracking errors can be explicitly obtained over the prediction horizon at varying speeds. Second, a nonlinear model predictive con- trol （NMPC） algorithm is introduced to handle the non- linear coupling between any two directions of the vehicular planar motion and computes the sequence of the optimal motion states for following the desired path. Third, a hierarchical control structure is proposed to separate the motion controller into a NMPC based path planner and a terminal sliding mode control （TSMC） based path fol- lower. As revealed through off-line simulations, the hier- archical methodology brings nearly 1700% improvement in computational efficiency without loss of control per- formance. Finally, the control algorithm is verified through a hardware in-the-loop simulation system. Double-lane- change （DLC） test results show that by using the optimalpredictive controller, the root-mean-square （RMS） values of the lateral deviations and the orientation errors can be reduced by 41% and 30%, respectively, comparing to those by the optimal preview acceleration （OPA） driver model with the non-preview speed-tracking method. Additionally, the average vehicle speed is increased by 0.26 km/h with the peak sideslip angle suppressed to 1.9~. This research proposes a novel motion controller, which provides the full drive-by-wire vehicle with better lane-keeping and colli- sion-avoidance capabilities during autonomous driving.

Climate Patterns: Origin and Forcing

This brief review described spatial-time climate patterns generated by the dynamics and thermodynamics of the Earth’s climate system and methods of identifying these patterns. Specifically, it does discuss the following major climate patterns: El Ni?o-Southern Oscillation (ENSO), Cold Ocean-Warm Land (COWL) pattern, Northern and Southern Annular Patterns (NAM and SAM), Atlantic Multidecadal Oscillation (AMO) and Atlantic Meridional Overturning Circulation (AMOC), Pacific North-American Pattern (PNA) and Pacific Decadal Oscillation Pattern (PDO). In view of an extensive number of publications on some climate patterns, such as the ENSO, which discussed in many hundred of publications, this review is not intended to cover all the details of individual climate patterns but intends only to give a general overview of their structure, mechanisms of their formation and response to external forcing. It is assumed that the climate patterns can be treated as attractors of dynamical systems allowing us to extract and predict some specific features of the patterns such as the origin and evolution of the climate patterns and their role in climate change. Thus the knowledge of patterns allows the climate prediction on long time scales and understanding of how an external forcing affects the frequency of occurrence of climate patterns and their magnitude but not the spatial structure.

基于新型TSM的船舶动力定位系统控制研究

复杂海洋情况下,水面船的动力定位系统存在定位精度低、收敛速度慢的问题,难以保持期望船位与艏向。为了提高系统的收敛速度减少跟踪误差,提出一种基于新型固定时间稳定的非奇异快速终端滑模(TSM)控制方法。该方法采用新型固定时间稳定算法获得收敛时间的上界,选择固定时间扩张状态观测器,对船舶航行速度和海洋干扰力进行估计,进一步提出一种固定时间非奇异快速终端滑模输出反馈控制器,避免奇异性问题同时减弱抖振现象,实现了收敛时间的预先设定;在此基础上,通过辅助动态系统对控制器输出的力和力矩进行饱和补偿。较传统方法,该方法可有效提升系统的控制精度和收敛速度,对船舶动力定位系统的研究具有一定的参考价值。

基于慢速时变动力学的空间结构施工过程精细化分析方法研究

针对空间结构施工过程模拟问题,依据时变力学基本原理,提出了基于慢速时变动力学的动态施工过程精细化分析方法。该新方法通过设置与实际施工动态过程相一致的分析时长,引入惯性力和阻尼力,实现时变结构几何、物理及边界等因素间的动态耦联,以达到真正意义上的施工全过程精细化分析。由此给出了该方法的求解思路和实现流程。通过对复杂大跨斜交连廊结构的施工过程分析,并对比施工实测数据,结果表明:该方法的计算值与传统静力施工过程分析方法相吻合,且总体上更接近工程实际,因此可用于空间结构的施工过程分析与安全评估;与传统静力施工过程分析方法相比,该方法一方面能够更准确反映实际施工过程中结构响应的动态累积效应,并获取任意时刻的结构受力和变形情况,另一方面,还可适用于强非线性的复杂施工过程分析(大变形、超大位移、机构位移等),从而避免了传统静力施工过程分析方法中非线性求解的收敛性难题。

基于水资源空间均衡的“四水四定”调控模型构建

为实现未来不同时间尺度下的水资源空间均衡与动态调控,创建了一套完整严谨、可动态调控的“四水四定”模型体系。通过模糊信息粒化窗口的支持向量机模型预测区域未来总用水量,利用基于时间序列相似性分析的自回归支持向量机模型预测区域未来分用水量,并对两类数据进行不确定性分析;构建了复杂回归函数对各类用水指标进行情景预测,经统计检验后将其作为当前用水模式下未来用水指标;构建了“四水四定”水资源承载力模型和水资源空间均衡模型,基于未来总用水量、未来各分用水量、未来用水指标,选用水资源负载系数、用水效益和水土资源匹配系数3个指标,结合基尼系数量化水资源空间均衡度,分析当前用水模式下未来水资源均衡度;构建了最优化模型,以最小化基尼系数为目标函数调整未来用水模式,实现水资源动态调控。所创建的模型体系可以实现未来不同时间尺度下的水资源空间均衡与动态调控。

稀溶液中大幅拉伸高分子单链的弛豫动力学

针对大幅拉伸的高分子单链在Θ溶剂和良溶剂中的弛豫过程,分别通过解析理论和分子动力学模拟方法研究了弛豫动力学.对比研究发现,相对于研究高分子链在平衡态下的弛豫动力学(利用有关物理量的自关联函数),本文的非平衡态方法可以明确地揭示弛豫时间与简正模式之间标度行为的动态演化.结果表明,相关的物理量在弛豫初期均受到非平衡态的影响,而在较长时间后,高分子链的弛豫动力学则与平衡态下的结果相吻合;在高分子链的最长弛豫时间与链长的标度关系方面,平衡态和非平衡态两种方法的研究结果也一致.研究结果表明,高分子链在非平衡态下的短时和长时弛豫动力学可以更加细致地阐明弛豫全过程,给出更加丰富的结构-特征关系,从而为深入探讨高分子链的非平衡弛豫提供可借鉴的线索.