基于多源数据的城市空间活力时空特征分析——以南京市河西、仙林新城为例

采用微信宜出行数据、传统规划数据,探索南京市河西和仙林新城的空间活力时空特征。结果发现:(1)在空间层面,河西呈"东高西低、北高南低"的集聚特征,仙林活力分布与高校区位高度匹配。(2)在时间层面,河西呈"降—升—降—升—降"的波动特征,仙林呈"降—升—平缓"的波动特征。(3)工作日的河西活力集中在居住区,休息日集中在商业区;仙林在工作日和休息日无差异,均分布在高校区及其周边的商业区。     

资源产业集聚对资源型城市经济增长的影响--基于夜间灯光数据的实证研究

在资源依赖背景下,发挥好资源产业集聚的正向作用,是资源型城市实现经济可持续增长的关键。基于2005—2017年山西省11个地级市面板数据,采用校正整合的夜间灯光数据度量城市经济增长,并运用系统广义矩估计法(SYS-GMM)检验了资源产业集聚对城市经济增长的影响。结果表明:资源产业集聚对资源型城市经济增长影响显著,呈“先上升,后下降”的倒“U”型关系,在资源产业集聚初期将推动城市经济增长,但过度集聚反而会抑制经济增长。     

我国环境规制强度测度及其对就业规模的影响——基于省际动态面板数据的实证分析

本文建立模型具体测算了我国30个省(区、市)自2003年至2016年的环境规制强度指标,发现全国环境规制强度整体呈上升趋势,其中东部省份强度最大,中部地区的环境规制强度低于东部而略高于西部地区。进一步构建动态面板计量模型进行实证分析,结果显示,环境规制对就业的影响具有明显的U形特征,即随着环境规制强度的提高,其对就业起着先抑制后促进的作用。而经济发展水平、人口规模、产业结构的优化升级以及平均工资水平的提高均能显著促进全样本的就业增长,但对外依存度对各样本而言都明显不利于就业规模的扩张。     

Automated conservation assessment of the orchid family with deep learning

International Union for Conservation of Nature (IUCN) Red List assessments are essential for prioritizing conservation needs but are resource intensive and therefore available only for a fraction of global species richness. Automated conservation assessments based on digitally available geographic occurrence records can be a rapid alternative, but it is unclear how reliable these assessments are. We conducted automated conservation assessments for 13,910 species (47.3% of the known species in the family) of the diverse and globally distributed orchid family (Orchidaceae), for which most species (13,049) were previously unassessed by IUCN. We used a novel method based on a deep neural network (IUC-NN). We identified 4,342 orchid species (31.2% of the evaluated species) as possibly threatened with extinction (equivalent to IUCN categories critically endangered [CR], endangered [EN], or vulnerable [VU]) and Madagascar, East Africa, Southeast Asia, and several oceanic islands as priority areas for orchid conservation. Orchidaceae provided a model with which to test the sensitivity of automated assessment methods to problems with data availability, data quality, and geographic sampling bias. The IUC-NN identified possibly threatened species with an accuracy of 84.3%, with significantly lower geographic evaluation bias relative to the IUCN Red List and was robust even when data availability was low and there were geographic errors in the input data. Overall, our results demonstrate that automated assessments have an important role to play in identifying species at the greatest risk of extinction.     

Ethics and governance for internet-based conservation science research

Internet-based research is increasingly important for conservation science and has wide-ranging applications and contexts, including culturomics, illegal wildlife trade, and citizen science. However, online research methods pose a range of ethical and legal challenges. Online data may be protected by copyright, database rights, or contract law. Privacy rights may also restrict the use and access of data, as well as ethical requirements from institutions. Online data have real-world meaning, and the ethical treatment of individuals and communities must not be marginalized when conducting internet-based research. As ethics frameworks originally developed for biomedical applications are inadequate for these methods, we propose that research activities involving the analysis of preexisting online data be treated analogous to offline social science methods, in particular, nondeceptive covert observation. By treating internet users and their data with respect and due consideration, conservationists can uphold the public trust needed to effectively address real-world issues.     

大数据发展的信息安全风险防御探析

大数据的发展及广泛应用加大了信息化系统及数据的脆弱性,信息安全风险向系统化、复杂化方向发展。在搜集、整理国内外相关研究成果基础上,系统辨识数据采集、数据传输、数据存储、数据分析4个大数据核心环节的信息安全风险,围绕“风险辨识、脆弱性降低、风险沟通、强化风险管理”的风险治理流程,以防范与化解信息安全风险为目标,提出大数据发展的信息安全防御策略。研究结果表明:大数据全生命周期是信息安全风险辨识的起点,强化大数据发展的信息安全风险防御,需要在风险辨识基础上,积极推进预防准备、风险沟通、信息安全事件处置及恢复总结。     

地面气象观测资料在空气法规模型的标准化研究

以云量、风速、风向、温度3类地面气象观测数据的获取方法为研究对象,探讨如何规范地面气象观测数据在模型中的标准化应用.结合我国2008年颁布的《环境影响评价技术导则 大气环境》推荐的模型AERMOD对所需要的地面气象数据需求,并以内蒙古自治区正蓝旗上都电厂SO2实测数据为验证数据,在模型其他输入参数不变的情况下,利用试验站10min和1h地面气象数据,并分别以低云量和总云量代替蔽光云量,设置4种情景.其中,情景一使用试验站10min地面气象数据,并用低云量代替蔽光云量.与情景一相比,情景二使用总云量代替蔽光云量,情景三使用1h地面气象数据,情景四使用试验站1h地面气象数据,并用总云量代替蔽光云量.4种情景除了上述不同点,其他地面气象参数均相同.结果表明,在4种情景中,情景二、三、四的FB值均小于情景一,更靠近0.关于RHCR值,情景三和四更靠近于1,分别为1.33和1.41,表明在预测高端值时,情景三和四的效果更好.情景二的RHCR值为1.51,大于情景三,说明风相较于云对模型模拟结果影响更大.由FB值、RHCR值以及Q—Q图的综合分析得出,情景四的模拟值更接近实际监测值,其采用的地面气象数据全面符合本研究所推荐的数据标准化应用方法, 规范了模型数据标准化应用,提升了大气环境影响评价预测精度.     

基于Profibus-DP的废钢破碎线控制系统设计与实现

江苏鼎豪再生资源设备有限公司2012年成功开发了大型废钢破碎线,采用PLC并基于Profibus-DP总线构成监督控制与采集（SCADA）系统。用模糊控制思想实现了破碎机的自动加料控制,并采用组态软件WINCC开发了操作、监控界面,在控制室实现了对整条破碎生产线进行控制与监控。     

Identifying Conservation Areas on the Basis of Alternative Distribution Data Sets

Abstract:  Distribution data on biodiversity features is a major component of conservation planning that are often inaccurate; thus, the true distribution of each feature is commonly over- or underrepresented. The selection of distribution data sets may therefore lead to variability in the spatial configuration and size of proposed reserve networks and uncertainty regarding the extent to which these networks actually contain the biodiversity features they were identified to protect. Our goals were to investigate the impact on reserve selection of choosing different distribution data sets and to propose novel methods to minimize uncertainty about target attainment within reserves. To do so, we used common prioritization methods (richness mapping, systematic reserve design, and a novel approach that integrates multiple types of distribution data) and three types of data on the distribution of mammals (predicted distribution models, occurrence records, and a novel combination of the two) to simulate the establishment of regional biodiversity reserves for the state of Arizona (U.S.A.). Using the results of these simulations, we explored variability in reserve placement and size as a function of the distribution data set. Spatial overlap of reserve networks identified with only predicted distribution data or only occurrence distribution data never exceeded 16%. In pairwise comparisons between reserves created with all three types of distribution data, overlap never achieved 50%. The reserve size required to meet conservation targets also varied with the type of distribution data used and the conservation goal; the largest reserve system was 10 times the smallest. Our results highlight the impact of employing different types of distribution data and identify novel tools for application to existing distribution data sets that can minimize uncertainty about target attainment.     

河流水环境有机污染物的自组织预测模型及应用

自组织预测模型是前苏联学者伊万年科提出的一种非线性建模预测方法,它能有效地解决复杂非线性系统的数据处理和建模问题。该文应用它进行水环境有机污染物预测,以实际监测数据为基础,建立了一个河流有机物浓度预测的自组织模型,其检验样本的预测误差在５％以内