我国水稻产业供给侧结构性改革的思考

[目的]文章在供给侧改革视角下对水稻供需的结构性矛盾等方面进行梳理,分析基于供给侧改革战略的关键环节、实施路径和未来发展趋势,以期为制定我国水稻供给侧改革战略提供参考。[方法]采用文献分析法和调查研究法,从我国水稻生产供求结构、价格"天花板"和成本"地板"双重挤压、水稻生产的资源环境、市场调节等方面分析了我国水稻产业供给侧的现状和存在的问题;通过日本、泰国、中国五常大米政策特点和经验教训的启示,提出了我国水稻产业供给侧结构性改革的策略。[结果]在分析我国水稻产业供给侧现状的基础上,总结得出水稻产业供给侧改革措施:优化水稻产业空间和功能布局,以项目带动水稻产业结构调整,提高和优化稻米品种品质结构、审定标准向抗性优质专用水稻品种倾斜,因地制宜调减水稻生产面积,调整国家收储稻米标准,延长水稻全产业链等。[结论]加速我国水稻产业供给侧改革,能促进稻米产业结构快速升级,有效破解稻米产业的结构性矛盾,增强我国稻米产业可持续发展能力和国际竞争力。     

Leadership succession planning for today’s digital transformation economy: Key factors to build for competency and innovation

Digital transformation is rapidly changing the competitive landscape and the war on talent for today’s organizations. As part of this economy, organizations and their HR units must continuously reevaluate leadership structures and practices that exploit core competencies while allowing for innovation (i.e., leadership ambidexterity) and incorporate big data with predictive analytics. In this vein, understanding how HR executives can create better solutions around this problem remains sparse. Specifically, what frameworks can HR executives apply to identify potential alignment failures in leadership succession planning in light of newer emerging markets? What internal decision-making traps need to be recognized? Finally, what specific forms of data and evidence must test these plans for relevance and recharge and renew the talent-to-strategy pipeline? In this article, we examine these questions by reviewing the gaps in the literature and identifying through our four-step model how organizations can incorporate ambidexterity-building as a leadership succession planning practice.     

基于PSO-SAS的联合侦察任务规划

针对联合侦察筹划中任务规划阶段机动侦察平台阵位与路线确定困难的问题，提出了一种基于粒子群优化-稀疏A星(Particle Swarm Optimization—Sparse A-star,PSO-SAS)算法的规划方法。该方法综合考虑侦察装备机动性能以及敌火力威胁、地形等因素，在侦察阵位规划上，建立了阵位综合评估模型，并利用粒子群算法进行阵位寻优；在路线规划上，采用稀疏A*算法进行航迹规划，通过将机动性能、安全距离、路程等约束引入搜索过程，缩短最优路线的计算时间。仿真试验验证了所提方法生成的侦察阵位和路线能够满足侦察任务要求。     

融合反距离加权和矩阵填充的位置指纹库构建

为解决位置指纹定位在离线阶段构建位置指纹库时耗费的人力和时间成本较大，构建指纹库效率低和利用空间插值法构建的指纹库精度不高的问题，提出了一种融合反距离加权和矩阵填充的位置指纹库构建算法。该算法仅需人工采集定位区域内少量参考点的接收信号强度值用作信标点指纹信息，结合反距离加权算法特性计算出次信标点指纹信息，根据位置指纹库数据矩阵的低秩性，应用奇异值阈值矩阵填充算法构建出位置指纹数据库。仿真实验结果表明，所提算法有效降低了矩阵填充算法构建位置指纹库所需的人工和时间成本，构建出的位置指纹库定位性能优于反距离加权和克里金空间插值法，接近传统人工采集法，显著地提高了位置指纹库的构建效率。     

沈阳城市周边耕地多功能评价

[目的]为探索城市化影响下城市周边耕地多功能的现状,分析其空间差异,为耕地保护及城市周边耕地发展提供参考。[方法]从耕地的生产、生态、社会和景观4个功能出发构建评价指标体系,利用熵权法确定指标权重,加权求和法计算单一功能和多功能值,并用ArcGIS进行空间分析,对沈阳城市周边50个乡镇(街道)的耕地多功能性进行综合评价。[结果](1)沈阳城市周边耕地的多功能性空间差异较为明显。生产功能远郊平原区最强,远郊山区和近郊区较弱;生态功能总体偏弱,个别乡镇较好;距离城市越远,社会功能越强;景观功能近郊区较强,远郊区较弱。(2)耕地的生态、社会和景观功能主要受距市中心距离的影响,生产功能受地形和距市中心距离的双重影响,而多功能则受地形、距市中心距离及各乡镇(街道)耕地主导功能等的综合影响。(3)沈阳城市周边的大多数耕地以农业生产为主导,景观文化功能整体相对较弱。近郊区耕地生态功能所占比重较大,但社会功能比重较小,远郊区则与之相反。[结论]沈阳城市周边耕地多功能性空间差异较为明显且不均衡,应科学规划城市周边耕地功能,优化空间布局,协调耕地各功能的关系,促进耕地多功能综合发展。     

Evaluating municipal landscape plans and their influence on selected aspects of landscape development – An empirical study from Germany

In this paper we examine the question of whether and how municipal landscape plans exert a positive influence on and/or correlate with selected aspects of the landscape. To this end, a representative sample of municipal landscape plans in Germany and a statistical-quantitative evaluation approach are used to uncover correlations between planning and landscape development. As a result, we can show that municipalities which draw up a landscape plan have a higher proportion of natural areas and a lower hemeroby index, i.e. a lower level of human influence. The model also reveals a significant relationship between the quality of the landscape plan as well as its duration of impact and the density of landscape structural elements. It is also determined that municipal landscape plans help protect grassland areas. The indicator-based method provides impulses for the international discussion on the evaluation of plans.     

全球价值链分工对国际经济周期协同性的影响研究

为考察全球价值链分工的宏观经济效应,本文基于2000—2014年全球102个经济体相关数据,探究了全球价值链贸易对国际经济周期协同性的影响。结果表明,全球价值链贸易深化了国际垂直型分工,显著提升了国际经济周期的协同性;无论是制造业还是服务业价值链贸易,对国际经济周期协同性都具有显著正向影响,侧面反映出服务业也在越来越深入地融入全球分工体系;价值链贸易对国际经济周期协同性的影响效应主要体现于发展中与发达经济体之间,发达经济体之间的经济周期协同性受其影响并不明显。     

Exploring the interdisciplinary potential of the Agenda2030—Interactions between five Danish societal demands for sustainable land use

This article explores the potential of the SDG framework for interdisciplinary research. The aim is to illustrate the process of creating a shared platform of operation by the clarifying the positive and negative interactions between societal demands for land use on a national and local level. The research question is answered by making use of the systemic approach introduced by Niklas Luhmann including his arguments about autopoietic communication systems reproducing themselves. An interdisciplinary research group is firstly applying the SDG framework to the demands for sustainable land use by activating the land consolidation in Denmark. By doing so a ‘national framework’ anchored in the SDG framework is created. Secondly, the national framework is applied to a multifunctional land consolidation project in a Danish case area. The findings from the mapping of interactions between societal demands on a concrete case area revealed that some indicators and societal demands are more prone to conflicts than others but also on the local level there may be variations. Thus, a localised and contextualised SDG framework has shown useful insight for future projects on sustainable land use including land consolidation projects. The paper concludes that the SDG framework may be used for facilitating interdisciplinary research, however there is also a need for guidelines and examples on how to integrate the framework in academia. The paper offers a suggestion for integrating the Agenda2030 and the SDG framework in projects about sustainable land use.     

Small Area Estimation for Disease Prevalence Mapping

Small area estimation (SAE) entails estimating characteristics of interest for domains, often geographical areas, in which there may be few or no samples available. SAE has a long history and a wide variety of methods have been suggested, from a bewildering range of philosophical standpoints. We describe design-based and model-based approaches and models that are specified at the area level and at the unit level, focusing on health applications and fully Bayesian spatial models. The use of auxiliary information is a key ingredient for successful inference when response data are sparse, and we discuss a number of approaches that allow the inclusion of covariate data. SAE for HIV prevalence, using data collected from a Demographic Health Survey in Malawi in 2015–2016, is used to illustrate a number of techniques. The potential use of SAE techniques for outcomes related to coronavirus disease 2019 is discussed.     

Geographies of Algorithmic Violence: Redlining the Smart City

City governments are embracing data-driven and algorithmic planning to tackle urban problems. Data-driven analytics have an unprecedented capacity to call urban futures into being. At the same time, they can depoliticize planning decisions. I argue that this shift calls urban studies scholars to investigate geographies of algorithmic violence—a repetitive and standardized form of violence that contributes to the racialization of space and spatialization of poverty. This article examines this broader phenomenon through the case of a proprietary market value assessment that is being used to guide development in cities across the United States. The assessment employs an algorithm that helps city officials make critical decisions about which neighborhoods to target for investment, disinvestment and public service upgrades or disconnections. I argue that the racial, infrastructural, and epistemological violence associated with this evaluation can potentially lead to a new kind of municipal redlining. The article brings insights from critical race theory into conversation with critical scholarship on algorithms by analyzing how algorithmic violence works through data-driven planning technologies to depoliticize and leverage power while further entrenching racism and inequality.