Collective decision-making and spatial patterns in orientation of an endemic ungulate on the Tibetan Plateau

Group living animals form striking aggregation patterns and display synchronization,polarization,and collective intelligence.Though many col-lective behavioral studies have been conducted on small animals like insects and fish,research on large animals is still rare due to the limited availability of field collective data.We used drones to record videos and analyzed the decision-making and behavioral spatial patterns in orienta-tion of Kiang(Tibetan wild ass,Equus kiang).Leadership is unevenly distributed among Kiang,with the minority initiating majority behavior-shift decisions.Decisions of individual to join are driven by imitation between group members,and are largely dependent on the number of members who have already joined.Kiang respond to the behavior and position of neighbors through different strategies.They strongly polarize when moving,therefore adopting a linear alignment.When vigilant,orientation deviation increases as they form a tighter group.They remain scattered while feeding and,in that context,adopt a side-by-side alignment.This study reveals partially-shared decision-making among Kiang,whereby copying neighbors provides the wisdom to thrive in harsh conditions.This study also suggests that animals'spatial patterns in orientation depend largely ontheirbehavioral states inachieving synchronization.

Strength failure of spatial reticulated structures under multi-support excitation

Under strong earthquakes, long-span spatial latticed structures may collapse due to dynamic instability or strength failure. The elasto-plastic dynamic behaviors of three spatial latticed structures, including two double-layer cylindrical shells and one spherical shell constructed for the 2008 Olympic Games in Beijing, were quantitatively examined under multi-support excitation （MSE） and uniform support excitation （USE）. In the numerical analyses, several important parameters were investigated such as the peak acceleration and displacement responses at key joints, the number and distribution of plastic members, and the deformation of the shell at the moment of collapse. Analysis results reveal the features and the failure mechanism of the spatial latticed structures under MSE and USE. In both scenarios, the double-layer reticulated shell collapses in the ＂overflow＂ mode, and the collapse is governed by the number of invalid plastic members rather than the total number of plastic members, beginning with damage to some of the local regions near the supports. By comparing the numbers and distributions of the plastic members under MSE to those under USE, it was observed that the plastic members spread more sufficiently and the internal forces are more uniform under MSE, especially in cases of lower apparent velocities in soils. Due to the effects of pseudo-static displacement, the stresses in the members near the supports under MSE are higher than those under USE.

Spatial prediction of landslide susceptibility in western Serbia using hybrid support vector regression(SVR)with GWO,BAT and COA algorithms

In this study,we developed multiple hybrid machine-learning models to address parameter optimization limitations and enhance the spatial prediction of landslide susceptibility models.We created a geographic information system database,and our analysis results were used to prepare a landslide inventory map containing 359 landslide events identified from Google Earth,aerial photographs,and other validated sources.A support vector regression(SVR)machine-learning model was used to divide the landslide inventory into training(70%)and testing(30%)datasets.The landslide susceptibility map was produced using 14 causative factors.We applied the established gray wolf optimization(GWO)algorithm,bat algorithm(BA),and cuckoo optimization algorithm(COA)to fine-tune the parameters of the SVR model to improve its predictive accuracy.The resultant hybrid models,SVR-GWO,SVR-BA,and SVR-COA,were validated in terms of the area under curve(AUC)and root mean square error(RMSE).The AUC values for the SVR-GWO(0.733),SVR-BA(0.724),and SVR-COA(0.738)models indicate their good prediction rates for landslide susceptibility modeling.SVR-COA had the greatest accuracy,with an RMSE of 0.21687,and SVR-BA had the least accuracy,with an RMSE of 0.23046.The three optimized hybrid models outperformed the SVR model(AUC=0.704,RMSE=0.26689),confirming the ability of metaheuristic algorithms to improve model performance.

Application of geographical information system technology to epidemiological surveillance and prevention and cure decision-making for SARS

Objective:To expound geographical information system (GIS) technology is a very important tool when it was employed to assist to present the distribution by time and place and the model of transmission of infectious disease. Methods: We illustrated the assistant decision-making support function of GIS with an example of the spatial decision support system for SARS controlling in Shaanxi province of China which was developed by us. Results: The spatial decision support system established by applying GIS technology fulfilled the needs of real-time collection and management and dissemination SARS information and of surveillance and analysis the epidemic situation of SARS. Conclusion: Occurrence and epidemic of diseases, implement prevention and intervention measures and collocation hygienic resources are all with the characteristic of the variation of time and space, therefore, GIS technology has become a powerful tool for identifying risk factors of diseases, providing clues of causation of diseases , evaluating the effects of intervention measures and drawing a health management plan.

A new spatial coherence model and analytical coeffi cients for multi-support response spectrum combination

In this paper, a new spatial coherence model of seismic ground motions is proposed by a fitting procedure. The analytical expressions of modal combination （correlation） coefficients of structural response are developed for multi-support seismic excitations. The coefficients from both the numerical integration and analytical solutions are compared to verify the accuracy of the solutions. It is shown that the analytical expressions of numerical modal combination coefficients are of high accuracy. The results of random responses of an example bridge show that the analytical modal combination coefficients developed in this paper are accurate enough to meet the requirements needed in practice. In addition, the computational efficiency of the analytical solutions of the modal combination coefficients is demonstrated by the response computation of the example bridge. It is found that the time required for the structural response analysis by using the analytical modal combination coefficients is less than 1/20 of that using numerical integral methods.

Spatial Decision Support Applications Based on Three-Dimensional City Models

The basic mathematic models, such as the statistic model, the time\|serial model, the spatial dynamic model etc., and some typical analysis methods based on 3DCM are proposed and discussed. A few typical spatial decision making methods integrating the spatial analysis and the basic mathematical models are also introduced, e.g. visual impact assessment, dispersion of noise immissions, base station plan for wireless communication. In addition, a new idea of expectation of further applications and add\|in\|value service of 3DCM is promoted. As an example, the sunshine analysis is studied and some helpful conclusions are drawn.

A Decision Support System for Spatial Analysis of Agricultural Production in Madagascar

In this article, our research aims to set up a geo-decisional system, more precisely we are particularly interested in the spatial analysis system of agricultural production in Madagascar. For this, we used the spatial data warehouse technique based on the SOLAP spatial analysis tool. After having defined the concepts underlying these systems, we propose to address the research issues related to them from four points of view: needs study of the Malagasy Ministry of Agriculture, modeling of a multidimensional conceptual model according to the MultiDim model and the implementation of the system studied using GeoKettle, PostGIS, GeoServer, SPAGO BI and Géomondrian technologies. This new system helps improve the decision-making process for agricultural production in Madagascar.

Territorial Planning for Coastal Zones in Chile:The Need for Geographical-Environmental and Natural Risk Indicators for Spatial Decision Support Systems

Coastal zones are very dynamic and fragile environments, constituting a landscape ever more heterogeneous, fragmented and with increasing levels of complexity due to the changing relationship between man and nature. Integrated coastal zone management therefore requires detailed knowledge of the system and its components, based—to a large extent—on technical and scientific information. However, the information generated must be in line with the political requirements necessary for decision-making and planning. Thus the use of indicators to give a simplified view of the many components of the territory, and at the same time to provide important information about patterns or trends, becomes a tool of the utmost importance. These indicators can be understood as measurable characteristics of the environment, which facilitate comprehension of the processes occurring at different scales and serve as a reference to inform the population and support decision-making. The aim of the present note is to demonstrate briefly the need to develop geographical-environmental and natural risk indicators to facilitate comprehension of the dynamic of spatial and temporal landscape patterns, particularly in coastal environments. This approach offers an historical summary of the natural, socio-economic and political processes which currently make up the territory, and which without doubt will continue to influence it in the future. At the same time, it is proposed that information should be integrated on the basis of this framework with a view to generating spatial decision support systems in a context of planning and integrated management of the coastal zones of Chile.

大口径反射镜Bipod支撑结构的装调与检测方法

随着我国遥感卫星对地观测分辨率的不断提升,空间遥感相机的有效口径逐步增大,为有效应对相机在地表装调时的重力误差干扰,大口径遥感相机的装调方式逐步从光轴水平形式转变为光轴竖直形式,与之对应的,相机主反射镜支撑结构与装配需求也在不断革新。为满足反射镜支撑与减重需求,在1 m及以上口径的反射镜支撑形式中,Bipod结构是较为常见的一种结构形式,不同于传统的框式支撑形式,它在光机结构粘接与结构位置标定需求上都有了巨大变革。为保证Bipod支撑结构下反射镜的装配定位精度和面形变化满足系统指标要求,提出了一种结合多目标空间位置转换和Stewart结构运动反演的大口径反射镜组件装调方法,该方法可在有效保证光机结构粘接点精度的同时,仅依靠反射镜自身支撑结构,实现反射镜与主承力板之间的高精度六维调节,系统装调误差可控制在0.04 mm左右。在遥感相机的实际装调过程中,通过分析主反射镜在系统中的装调误差区间,并以此为标准制定了反射镜Bipod结构的定位、粘接、调整和检测方案,实践结果表明该方法可有效控制反射镜的装配定位精度和面形误差,装调结果能够满足大口径遥感相机的系统成像需求。

中国乡村创新创业发展:指数构建与测度分析

鼓励乡村创新创业是推进乡村振兴战略的重要抓手,但尚未有科学严谨的研究全面揭示中国乡村创新创业的发展程度和时空特征。通过构建包括2个一级指标、7个二级指标和21个三级指标的乡村创新创业指标体系,计算2014—2021年中国县、市、省级三个层面的乡村创新创业指数,并对其发展趋势、空间特征等展开分析。研究发现:中国乡村创新创业总体上蓬勃发展,但区域间存在差异;乡村振兴示范县的创新创业程度要显著高于其他县,国家重点帮扶县的创新创业增长速度要显著高于非重点帮扶县;乡村创新创业活动存在明显的空间集聚现象,同时也表现出区域收敛的趋势。乡村创新创业指数已向社会开放,将为各界研究中国乡村创新创业提供基础性数据。

基于碳汇潜力的碳排放空间关联网络结构特征及影响因素——以长江中游城市群为例

考虑碳汇潜力的碳排放空间关联是促进城市群协同减排的重要基础,更是实现碳中和的有力抓手。以长江中游城市群为研究区,对传统引力模型进行修正,构建兼具碳汇潜力的碳排放空间关联网络,采用社会网络分析(SNA)和二次指派程序方法(QAP)探究长江中游城市群碳排放空间关联网络的时空特征与影响因素。结果表明:①研究期间长江中游城市群碳排放网络关联关系数、网络密度和网络关联度呈增长趋势,网络效率和网络等级度不断下降,且网络等级度在2010年后始终为0,表明碳排放空间关联网络日益稠密、网络通达性较强,存在多重叠加的溢出渠道,但等级结构并不森严。基于碳汇潜力的长江中游城市群碳排放空间关联网络从“双核化”向“多极化、多线程”网络形态发展,核心城市的扩散作用不断增强。此外,以抚州、宜昌、鹰潭、上饶和吉安等为代表的高碳生态承载力地区,在碳排放空间关联网络中的受益关联性大于溢出关联性。②2020年,长江中游城市群碳排放空间关联网络形成四大板块,相较于板块内部成员间的碳排放空间关联效应,板块间的碳排放空间关联效应更为明显,即板块间的“碳排放转移”效应较为普遍。净溢出板块主要分布在武汉都市圈、宜荆荆都市圈和长株潭城市群外围城市,处于网络核心圈层位置;净受益板块主要分布在环鄱阳湖城市群东部,“碳排放避难所”效应显著。经纪人板块集中在环鄱阳湖城市群西部,板块间表现出“净溢出板块→经纪人板块→净受益板块”的碳排放传递路径,呈现出明显的“梯度转移”特征。双向溢出板块主要位于长江中游城市群西部,对净溢出和净受益板块都存在碳排放的空间溢出。研究期内,净溢出板块的成员虽然有所变化但总数保持不变,经纪人板块的成员有所增加,而净受益和双向溢出板块的成员均减少,环鄱阳湖城市群的“碳排放避难所”效应有所弱化。③地理邻近关系能够促进城市间碳排放关联关系的建立,而城市间的经济集聚程度、土地利用强度和经济发展水平上的互补性,促使碳排放空间关联网络随着城市间分工与协作的加强而呈现出千里“碳缘”一线牵的特点。

考虑土性参数空间变异性的珠三角软土地区土钉支护结构可靠度分析

如何定量定性描述软土土性参数空间变异性对准确确定软土土性参数和合理评价软土地区土钉支护结构稳定性至关重要。采用既有统计分析方法定量描述空间变异性通常需要大量数据,难以满足。本文基于随机场理论模拟软土土性参数空间变异性,建立了一套考虑土性空间变异性的软土地区土钉支护结构可靠度设计方法,最后以MATLAB软件包为平台进行计算程序的开发与工程实例研究。分析结果表明,本文采用随机场方法模拟软土土体固有空间变异性及其在土钉支护结构可靠度分析中的应用具有合理性与普适性。

海州湾及邻近海域金乌贼的空间分布特征及其与环境因子的关系

研究根据2013—2020年在海州湾及其邻近海域进行的渔业资源和栖息环境综合调查数据,采用支持向量机(Support vector machine,SVM)模型,通过交叉验证,结合赤池信息准则(Akaike information criterion,AIC)等评判指标,构建了金乌贼(Sepia esculenta)的空间分布模型,并分析环境因子对其空间分布的影响,旨在探究海州湾金乌贼的空间分布特征及其与环境因子的关系。结果表明,水深对金乌贼空间分布的影响最大,底层盐度次之,其次是底层水温和离岸距离。金乌贼的相对资源密度随水深的增大呈现先升高后降低的趋势,随盐度的升高而增大,随底层水温的升高而减小。在海州湾水深约27 m,离岸距离约40 km的海域,金乌贼的相对资源密度较高,其分布格局呈现出在东部和中北部海域丰度高,而西南部近岸海域丰度低的特点。研究将有助于深入了解海州湾金乌贼的空间分布规律,为其资源的合理利用和科学养护提供参考依据。

基于光谱—空间特征的ASTER影像岩性分类研究——以甘肃北山白峡尼山地区为例

遥感岩性制图是地质填图中的重要工作,基于光谱特征的岩性分类易受到色调、纹理等因素影响导致精度不佳。前人进行岩性自动分类研究多关注影像的光谱特征,而忽略空间特征,笔者等基于甘肃北山白峡尼山地区ASTER影像,将支持向量机、极限学习机两种机器学习分类方法与基于空间特征的快速漂移算法相结合进行岩性分类。结果表明支持向量机分类总体精度为89.17%;极限学习机不但具有需调节参数少的优势,且分类精度和速度均优于支持向量机,分类总体精度达96.70%;利用快速漂移算法提取的影像空间特征可有效减少错分区,提升岩性分类效果。研究证实将基于光谱特征的极限学习机和基于空间特征的快速漂移算法结合的岩性分类方法具有客观、高效、高精度等优势,可为后续地质填图和找矿勘查工作提供可靠数据支撑,在遥感岩性分类领域具有较高的推广价值。

价值发现、主体联动与制度支持:乡村公共空间再造的内在机制研究——基于H省Y村的空间治理实践

快速城镇化的背景下,乡村公共空间陷入持续衰落和活力不足的境地,极大地影响乡村振兴进程和乡村建设的最终成效。通过建立“价值发现—主体联动—制度支持”分析框架,系统剖析乡村公共空间再造的整体过程,深入探究乡村公共空间活力提升的内在机制。研究发现,存在一种“自下而上”的乡村公共空间再造机制,其中社会主体是公共空间再造的“初级行动主体”,基于自身技能和需求对公共空间进行识别,发掘公共空间多元价值;在空间价值发现的基础上,通过利益平衡和关系契约两种动员机制,实现多元社会主体在公共空间再造过程中形成合力、共同行动;政府和公共部门是公共空间再造的“次级行动主体”,运用丰富的政策工具提供一系列正式制度支持,同时借助非正式制度实现政策的有效运转。

绿色创新与绿色金融支持共生的空间溢出效应

绿色创新与绿色金融是低碳战略的双引擎,对中国实现“双碳”目标具有重要影响。该研究基于低碳城市试点政策背景,利用共生模型测度了2004—2019年各低碳城市的共生水平,采用空间杜宾模型研究了政策实施前后不同绿色金融支持对绿色创新企业的直接效应和空间溢出效应。结果表明:①低碳城市试点政策实施后,大部分低碳城市的共生水平都有所提升,低碳城市内部的政策性、银行业、保险业和碳金融支持均能促进绿色创新企业的发展。②低碳城市试点政策实施后,低碳城市之间的政策性、债券业和基金业金融支持表现出正向的空间溢出效应,但政策性金融支持的空间溢出效应略有下降,而碳金融支持却表现出负向的空间溢出效应。③机制及经济后果检验发现,绿色金融支持通过增加低碳城市的研发强度来促进绿色创新企业的发展,进而提升城市绿色产业的创新程度。因此,在中国实现“双碳”目标的关键时期,为了提高绿色金融支持对绿色创新企业的推动作用。一方面,各低碳城市应构建多元化绿色金融体系,不断创新绿色金融产品,拓宽绿色创新企业的融资渠道。另一方面,各低碳城市应加强企业之间的绿色技术创新交流,推动科技成果权属改革,进而促进绿色创新成果的市场化运用,打破绿色技术创新的省界壁垒。

纵向框架连接系对露顶式弧形钢闸门静动力特性影响分析

弧形钢闸门是水利枢纽中重要的泄水建筑物,根据事故案例发现弧形钢闸门多因支臂失稳而发生破坏,布置支臂连接系在一定程度上可以增强闸门稳定性,但目前连接系种类众多且无明确规范布置方法。以露顶式三支臂弧门为研究对象,采用CAD-CAE联合仿真的数值模拟方法综合探究了不同形式连接系对该闸门静动力特性的影响。结果表明:连接系的布置可以显著提高闸门刚度,改变闸门结构应力分布,降低最大应力;支臂内部腹杆和斜杆对闸门静动力特性提升效果显著,应进行优先布置;在数值模拟中支臂连接系等构件对模拟结果影响较大,采用空间有限元法对弧形闸门支臂校核时应尽量避免对支臂连接系进行过度简化。研究成果对弧形钢闸门支臂连接系布置及有限元计算具有一定参考意义。

上海某超深基坑分区开挖数值计算及模型参数分析

以上海某挖深超过40m的超深基坑为分析案例,建立了超深基坑精细化流固耦合数值分析方法,通过实测数据和参数反演分析,研究了超深基坑多因素叠加耦合效应的围护结构变形分布规律和变形模式。研究表明:相较于浅层土体开挖,深层土体开挖的变形效应更加明显,分层开挖的变形量和变形速率逐渐增加;模拟基坑开挖变形效应时,考虑围护结构的刚度折减是必要的,坑底承压水层降水有利于控制基坑变形,降水后深层土体开挖变形速率显著减小;围护结构变形的空间效应显著,地下连续墙角部几何形式对围护结构侧移影响较大;计算结果可以较好拟合实测结果,预测最大误差可控制在20%以内。

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。

基于共空间模式的脑电信号疲劳检测

因脑电信号更能直接反映大脑皮层疲劳状况,论文提出了一种基于共空间模式的脑电信号疲劳检测方法。该方法首先对数据集进行滤波等预处理操作,然后应用共空间模式提取特征,最后用支持向量机对提取到的有效空间特征二分类。此外,实验还采用了5折和10折交叉验证法进行评估;探索了脑电疲劳特征阶数相关系数m的取值;划分了脑区并对各区域疲劳识别准确率进行了比较。研究结果表明:论文方法的识别率高于基于样本熵、模糊熵等方法的识别率,疲劳检测准确率均值可达98.54%,全头皮疲劳识别率最高,额区疲劳识别率优于其他区域,可达92.54%。论文研究可为疲劳检测设备的研发提供更简单准确的检测方法,有助于促进可穿戴脑机接口在疲劳驾驶预警中的应用。