山东省电力资源空间格局及环境成本分析

基于复杂网络理论,对山东省电力网络空间结构、分布特征进行了分析.结果发现：受资源禀赋的影响,山东省电力输出端主要分布在鲁西南地区,输入端主要集中在中东部重工业城市;电力网络拓扑结构具有较小的聚类系数和较大的平均路径长度,度分布呈现出不完全幂律分布,具有向无标度网络演化的特征;受电源结构的影响,各地市发电环境成本差异较大,尤其与火电发电规模紧密联系.     

Socio-environmental conflict in the construction of a power plant in Spain's Basque Country: strategies,expertise and certifications

Social and anthropological studies show a growing number of conflicts surrounding energy projects, as governments and companies insist on their implementation despite the concerns of local actors about their perceived socio-environmental risks. In this context, the purpose of this paper is to analyse the politicisation of expertise and certifications in a conflict over the construction of a combined cycle power plant by linking strategic assumptions from two particular sociological approaches. The first approach is based on the study of frame alignment in social movement organisations and the second on the translating interests in actor–network theory. These linked premises are examined in the conflict arising from the construction of a combined cycle natural gas plant in Boroa, in the Basque Country of Spain. This case study brings to light interesting findings on the strategies of the different agencies, certifications, politicisation of expertise and the increasing hostility in local conflicts.     

基于ANP和SPA的民航飞行员安全能力评价

飞行员安全能力是飞行员排班、机组搭配、掌握飞行员安全状态的重要依据,为客观、准确地对飞行员安全能力进行评价,对安全管理能力内涵进行了界定,找到了评价飞行员安全能力的4个二级指标,共17个三级指标。后来用网络层次分析法(ANP)对各影响因素的影响力进行排序,确定了指标的综合权重。综合考虑飞行员安全能力各影响因素之间的不确定性、模糊性,采用集对分析方法(SPA)进行评价。最后将集对分析法和网络层次分析结合构建的评价模型运用于某航空公司飞行员安全能力评价,结果与实际情况基本一致,说明了该方法的有效性。     

Prenatal screening and diagnosis of neural tube defects

This review article discusses prenatal screening and diagnosis of neural tube defects (NTD). High detection rates occur in countries operating ultrasound screening programmes because classical two-dimensional ultrasound cranial signs (lemon shaped head, banana cerebellum, ventriculomegaly) are important diagnostic clues to the presence of spina bifida. Careful evaluation of both the spine and a search for other abnormalities is warranted. Important prognostic information for spina bifida relates to the lesion level, with a “watershed” between L3 and L4 marking a very high chance of being wheelchair bound with the higher lesions. Three-dimensional ultrasound using multiplanar views can achieve diagnostic accuracy within one vertebral body in around 80% of patients. There are high rates of pregnancy termination for spina bifida in many European countries, but the use of new imagining techniques allow better prediction of outcome, and consequently a refinement of prenatal counselling. Copyright © 2009 John Wiley & Sons, Ltd.     

Forecasting the Risk of Brown Tree Snake Dispersal from Guam: a Mixed Transport-Establishment Model

Abstract:  The brown tree snake ( Boiga irregularis ) is a devastating invader that has ecologically and economically affected Guam and is poised to disperse further. Interdiction efforts are being conducted on Guam and some of the potential receiving sites, but no tools exist for evaluating the potential for snake incursion; thus, the amount of effort that should be invested in protecting particular sites is unknown. We devised a model that predicts the relative risk of establishment of the brown tree snake (BTS) at a given site. To calculate overall risk, we incorporated in the model information on the likelihood of an organism entering the transportation system, avoiding detection, surviving to arrive at another location, and establishing at the receiving end. On the basis of documented rates of snake arrival at receiving sites, the model produced realistic predictions of invasion risk. Model outputs can thus be used to prioritize interdiction efforts to focus on especially vulnerable receiving locations. We provide examples of the utility of the model in evaluating the impacts of changes in transportation parameters. Finally, the model can be used to evaluate the impacts that BTS establishment at an additional site and that creation of a new source of snakes would have. The use of qualitative inputs allows the model to be adapted by substituting data on other invasive species or transportation systems.     

Application of digital technologies about water network in steel industry

To improve the efficiency of water use and reuse, a digitalized water network system was implemented in a steel industrial complex. The system consisted of four parts: online instrument and sensing devices, programmable logic controller, data communication network and control center based on expert knowledge. The system achieved real-time monitoring, diagnosis, and early warning of cooling water system using data collected inline, and enabled data connectivity and transmission of self-developed software applications on personal computer. This research used a steel enterprise as a case study. After the analysis of its cooling water system and water-saving potential using water balance test, a digitalized water network was evaluated and implemented, and we believe this network can be suitable for steel industry in general.     

Using knowledge mapping to rethink the gap between science and action

Scholars have long stressed the need to bridge the gap between science and action and seek the most efficient use of knowledge for decision making. Many contributors have attempted to consider and understand the sociopolitical forces involved in knowledge generation and exchange. We argue, however, that a model is still needed to adequately conceptualize and frame the knowledge networks in which these processes are embedded. We devised a model for knowledge mapping as a prerequisite for knowledge management in the context of conservation. Using great ape conservation to frame our approach, we propose that knowledge mapping should be based on 2 key principles. First, each conservation network results from the conglomeration of subnetworks of expertise producing and using knowledge. Second, beyond the research-management gradient, other dimensions, such as the scale of operation, geographic location, and organizational characteristics, must also be considered. Assessing both knowledge production and trajectory across different dimensions of the network opens new space for investigating and reducing the gap between science and action.     

基于轴—辐理论的皖江城市带物流网络空间构建

大力发展现代物流业和皖江城市带承接产业转移示范区建设是两大重要国家级战略.首先对轴—辐理论的国内外研究现状进行了总结和归纳,分析了轴—辐网络的结构及其优劣势.其次,设计了物流中心性指数的评价指标体系,运用主成分分析法对皖江城市带的9个地级城市进行物流节点等级划分,根据分析结果的总得分和区位特征确定合肥、芜湖、安庆3个一级物流节点,形成轴三角.分析了各级物流节点间的干线及支线物流通道,构建了皖江城市带轴—辐物流网络空间.     

Projected Climate‐Induced Habitat Loss for Salmonids in the John Day River Network,Oregon, U.S.A.

Abstract: Climate change will likely have profound effects on cold‐water species of freshwater fishes. As temperatures rise, cold‐water fish distributions may shift and contract in response. Predicting the effects of projected stream warming in stream networks is complicated by the generally poor correlation between water temperature and air temperature. Spatial dependencies in stream networks are complex because the geography of stream processes is governed by dimensions of flow direction and network structure. Therefore, forecasting climate‐driven range shifts of stream biota has lagged behind similar terrestrial modeling efforts. We predicted climate‐induced changes in summer thermal habitat for 3 cold‐water fish species—juvenile Chinook salmon, rainbow trout, and bull trout (Oncorhynchus tshawytscha, O. mykiss, and Salvelinus confluentus, respectively)—in the John Day River basin, northwestern United States. We used a spatially explicit statistical model designed to predict water temperature in stream networks on the basis of flow and spatial connectivity. The spatial distribution of stream temperature extremes during summers from 1993 through 2009 was largely governed by solar radiation and interannual extremes of air temperature. For a moderate climate change scenario, estimated declines by 2100 in the volume of habitat for Chinook salmon, rainbow trout, and bull trout were 69–95%, 51–87%, and 86–100%, respectively. Although some restoration strategies may be able to offset these projected effects, such forecasts point to how and where restoration and management efforts might focus.     

基于BP模型的大气污染预报方法的研究

BP模型是目前最为广泛应用的神经网络模型之一,它是一种简单而又非常有效的算法.笔者将BP网络模型引入到大气污染预报领域,并根据大气污染物含量与气象要素的关系建立了大气污染物含量的神经网络预报模型.计算结果表明,BP模型应用于大气污染预报具有较高的预测精度和良好的泛化能力,它为信息社会的城市空气污染预报工作提供了一种全新的思路和方法.