基于多重交叉残差方法的空间目标旋转特性分析

针对传统的频谱分析和自相关函数反演周期时常出现虚假周期的问题，提出了多重交叉残差法处理空间旋转目标雷达散射截面(Radar Cross Section，RCS)的时间序列。以空间跟踪和监视系统(Space Tracking and Surveillance System,STSS)卫星为例，仿真了空间目标失稳旋转状态，对比了频谱分析、自相关函数和多重交叉残差3种方法的处理结果，发现当目标存在进动运动时多重交叉残差法抗干扰能力更强。在此基础上，进一步研究了不同章动角时多重交叉残差法对旋转周期的反演效果，结果表明章动角大小会影响旋转周期的反演准确度，且章动角达到一定数值后，卫星进动幅度过大导致RCS序列周期性模糊，无法用多重交叉残差法反演出旋转周期。     

Prioritization of government expenditure on health in India: A fiscal space perspective

Unequal distribution of fiscal resources and lower prioritization of budget towards healthcare are the most important challenges in achieving universal health coverage in India. This study has examined relationships between government health expenditure and fiscal space (i.e. tax revenue, non-tax revenue, fiscal transfer, and borrowings) in twenty-one states of India for the period of 1980–2014. Our panel regression results imply that mobilization of tax revenue has a positive impact, while borrowings have a negative impact on the allocation of government expenditure on healthcare in the long-run. The panel quantile regression results show that states associated with the low and middle level of revenue growth have been mobilizing finance through central government transfer and borrowings in short-run. Further, the panel vector error correction models show that sum of the lagged coefficients of borrowings have a greater impact on health financing process as compared to other sources of fiscal space at short-run, and the speed of adjustment towards long-run equilibrium is relatively slower. The overall analysis concludes that less domestic revenue mobilization and higher dependency of borrowings for healthcare financing may create fiscal stress on state finances in the long-run, and thereby it could possibly reduce the prioritization of spending. Therefore, improvement in revenue growth and proper utilization of fiscal transfer would be appropriate policy implications from this study.     

空间目标的联合矩阵束极点估计

极点作为谐振区雷达目标的最主要电磁特性，具有很大的空间目标识别前景。但是在使用频域观测数据提取目标极点时，存在虚假极点和估计精度问题。针对上述问题，首先通过加窗和截断改进了后时响应信号的获取流程，抑制了虚假极点影响；然后采用最小描述长度法（MDL）估计极点个数，避免了定阶错误引起的虚假极点；最后采用联合矩阵束法估计极点，有效减少了单角度数据估计极点时存在的遗漏极点和虚假极点问题。FEKO软件验证表明，所提算法具有更高的精度和抗噪能力。     

Convex duality and Orlicz spaces in expected utility maximization

In this paper, we report further progress toward a complete theory of state‐independent expected utility maximization with semimartingale price processes for arbitrary utility function. Without any technical assumptions, we establish a surprising Fenchel duality result on conjugate Orlicz spaces, offering a new economic insight into the nature of primal optima and providing a fresh perspective on the classical papers of Kramkov and Schachermayer. The analysis points to an intriguing interplay between no‐arbitrage conditions and standard convex optimization and motivates the study of the fundamental theorem of asset pricing for Orlicz tame strategies.     

Bridging the valuescape with digital technology: A mixed methods study on customers’ value creation process in the physical retail space

This mixed methods study investigated how value is created in the physical retail space and how the customer experience is influenced by digital technology. A cross-sectional survey, with both qualitative and quantitative components, was distributed across a heterogeneous sample of 832 customers. The results revealed an overarching model comprised of three interrelated clusters: customer, service provider, and digital technology. We propose that this model can be understood as a valuescape, where customers' specific goals, needs, and desires drive them to interact and co-create value with service providers in the physical retail space, with digital technology either enhancing or disrupting this value co-creation process. The results also show that the importance of aligning digital solutions with customers’ drives increases at the same pace as reliance on technology. The findings offer guidelines on how to utilize digitalization to leverage customer experiences and thus strengthen the attractiveness of physical retail spaces.     

自然生态空间用途管制分区划定研究——以平潭岛为例

研究目的:在明确自然生态空间内涵和分类的基础上,探讨自然生态空间用途管制分区划定的逻辑框架和技术方法,提出自然生态空间分类、分级管制规则。研究方法:文献综述与GIS空间分析。研究结果:根据不同自然生态系统类型及其空间分布特征将自然生态空间类型划分为森林生态空间、草地生态空间、湿地生态空间和荒地生态空间;基于景观功能识别并按不同管控等级将自然生态空间管制类型区划分为红线区、橙线区和黄线区;同时,依据不同地块主要功能进一步确定自然生态空间用途管制分级,划定用途管制分区结果。研究结论:基于"区域主体功能—景观主导功能—地块主要功能"的自然生态空间管制分区划定逻辑框架,可为构建以功能分类、用途分区、管控分级为导向的自然生态空间用途管制体系提供理论依据和实践借鉴。     

叶尔羌河平原绿洲土地生态安全预警演变与时空格局分析

[目的]探索叶尔羌河平原绿洲土地生态安全预警问题及其时空格局变化,旨在为叶尔羌河平原绿洲土地生态安全及可持续利用提供科学的参考依据。[方法]文章运用PSR模型构建预警指标体系,采用熵值法测算各指标权重,对2000—2016年叶尔羌河平原绿洲土地生态安全警情格局进行综合分析,并利用GIS技术分析其2000年、2005年、2010年和2016年土地生态安全空间格局变化,最后运用障碍度模型探索其障碍因子。[结果](1)2000—2016年叶尔羌河平原绿洲土地生态安全综合预警指数总体呈上升态势,生态预警状态由"较不安全"转为"临界安全",警度亦由"重警"变为"中警"。(2)从空间格局来看,空间上各县域土地生态安全水平差异明显,研究初期西部地区土地生态安全状态优于东部地区, 2016年呈现出中部高、东北—西南部低的态势。(3)近17年叶尔羌河平原绿洲各县域土地生态环境状况有所改善,安全状态经历了"极不安全—临界安全—较安全"的发展历程。(4)影响土地生态安全的主要障碍因子包括单位面积耕地农药负荷、人口密度、单位面积耕地化肥负荷、土地垦殖率、人口自然增长率和单位面积耕地地膜负荷等。[结论]研究期间叶尔羌河平原绿洲土地生态安全得到明显的提升与改善,并在良好的方向发展。     

Modeling node heterogeneity in latent space models for multidimensional networks

Multidimensional network data can have different levels of complexity, as nodes may be characterized by heterogeneous individual-specific features, which may vary across the networks. This article introduces a class of models for multidimensional network data, where different levels of heterogeneity within and between networks can be considered. The proposed framework is developed in the family of latent space models, and it aims to distinguish symmetric relations between the nodes and node-specific features. Model parameters are estimated via a Markov Chain Monte Carlo algorithm. Simulated data and an application to a real example, on fruits import/export data, are used to illustrate and comment on the performance of the proposed models.     

Factor state–space models for high-dimensional realized covariance matrices of asset returns

We propose a dynamic factor state–space model for high-dimensional covariance matrices of asset returns. It makes use of observed risk factors and assumes that the latent integrated joint covariance matrix of the assets and the factors is observed through their realized covariance matrix with a Wishart measurement density. For the latent integrated covariance matrix of the assets we impose a strict factor structure allowing for dynamic variation in the covariance matrices of the factors and the residual components as well as in the factor loadings. This factor structure translates into a factorization of the Wishart measurement density which facilitates statistical inference based on simple Bayesian MCMC procedures making the approach scalable w.r.t. the number of assets. An empirical application to realized covariance matrices for 60 NYSE traded stocks using the Fama–French factors and sector-specific factors represented by Exchange Traded Funds (ETFs) shows that the model performs very well in- and out of sample.     

政府质量、科技创新与绿色GDP——中国省际空间溢出效应及区域差异对比

通过构建嵌入政府质量和科技创新因素的经济增长模型，利用中国30个省份2004~2017年的平衡面板数据，实证检验政府质量、科技创新对绿色GDP发展的影响。研究发现：中国绿色GDP存在显著的空间集聚性及明显的区域差异性。在经济权重矩阵影响下，不同地区的政府效率、市场化程度、公平程度和腐败程度对绿色GDP的影响不同，其中政府效率、公平程度能有效促进经济发展较好地区的绿色GDP增长，却会抑制比较落后地区绿色GDP的增长；市场化程度对大部分地区绿色GDP呈现促进作用；腐败程度对地区绿色GDP增长呈阻碍作用。科技创新对各地区绿色GDP均起到积极的促进作用。因此，提升绿色GDP发展水平不仅需要提高地方政府质量，为绿色GDP发展提供符合实际的政策指导意见，还需激活企业科技创新能力，为绿色GDP发展提供有力科技保障。