边缘化地区特征、形成机制与影响--以安徽省池州市为例

边缘化地区是指在区域发展中,与核心地区的差距正在逐步拉大的地区。以安徽省池州市为例,分析其空间边缘化的主要表现,即区域社会经济发展缓慢、处于长江经济带的发展低谷,主要经济指标在全省的比重持续下降,居民生活水平和地方管理水平等方面均明显滞后于时代的发展,交通区位边缘性日益增强等。并对区域空间边缘化形成的主要机制进行探讨,认为空间过程缓慢是边缘化形成的历史基础,城镇体系发育不良是边缘化形成的空间因素,行政区划频繁变动是边缘化形成的人为因素,产业结构低级无序化是边缘化形成的经济原因等。区域空间边缘化对区域社会经济发展的负面影响主要表现为：空间边缘化与区域社会经济发展之间的恶性循环,空间结构不稳定性增强和无序化发展。     

Data fusion modeling for groundwater systems

Engineering projects involving hydrogeology are faced with uncertainties because the earth is heterogeneous, and typical data sets are fragmented and disparate. In theory, predictions provided by computer simulations using calibrated models constrained by geological boundaries provide answers to support management decisions, and geostatistical methods quantify safety margins. In practice, current methods are limited by the data types and models that can be included, computational demands, or simplifying assumptions. Data Fusion Modeling (DFM) removes many of the limitations and is capable of providing data integration and model calibration with quantified uncertainty for a variety of hydrological, geological, and geophysical data types and models. The benefits of DFM for waste management, water supply, and geotechnical applications are savings in time and cost through the ability to produce visual models that fill in missing data and predictive numerical models to aid management optimization. DFM has the ability to update field-scale models in real time using PC or workstation systems and is ideally suited for parallel processing implementation. DFM is a spatial state estimation and system identification methodology that uses three sources of information: measured data, physical laws, and statistical models for uncertainty in spatial heterogeneities. What is new in DFM is the solution of the causality problem in the data assimilation Kalman filter methods to achieve computational practicality. The Kalman filter is generalized by introducing information filter methods due to Bierman coupled with a Markov random field representation for spatial variation. A Bayesian penalty function is implemented with Gauss–Newton methods. This leads to a computational problem similar to numerical simulation of the partial differential equations (PDEs) of groundwater. In fact, extensions of PDE solver ideas to break down computations over space form the computational heart of DFM. State estimates and uncertainties can be computed for heterogeneous hydraulic conductivity fields in multiple geological layers from the usually sparse hydraulic conductivity data and the often more plentiful head data. Further, a system identification theory has been derived based on statistical likelihood principles. A maximum likelihood theory is provided to estimate statistical parameters such as Markov model parameters that determine the geostatistical variogram. Field-scale application of DFM at the DOE Savannah River Site is presented and compared with manual calibration. DFM calibration runs converge in less than 1 h on a Pentium Pro PC for a 3D model with more than 15,000 nodes. Run time is approximately linear with the number of nodes. Furthermore, conditional simulation is used to quantify the statistical variability in model predictions such as contaminant breakthrough curves.     

安徽地区近45年蒸发皿蒸发量变化特征及影响因素初探

利用线性倾向性估计和Mann Kendal检验方法,研究了过去的45年（1963~2007年）安徽地区32个代表站 20 cm 口径蒸发皿蒸发量的变化特征。结果表明：（1）安徽地区蒸发皿蒸发量呈现明显下降趋势（-65.3 mm/10 a，信度001），年蒸发总量在1976年发生突变，1982年显著减少，夏季突变最为明显；（2）32个代表台站中24个台站蒸发皿蒸发量表现为显著下降趋势，仅1个表现为上升趋势（信度005），在空间上减少趋势基本呈现“北多南少”的态势。结合其它气候要素研究发现：气温显著升高，蒸发量明显减少，即安徽地区存在“蒸发悖论”规律，但气温与蒸发量之间相关性不明显；日照，日较差和风速存在显著减少趋势，相关性〖JP+1〗分析表明它们是影响蒸发皿蒸发量减少的最重要因子；低云量，降水量和相对湿度等要素本身没有明显变化趋势但对蒸发皿蒸发量的减少作用也不可忽视。     

非电力驱动多用途系列喷射式吸风器研制与应用

给出喷射式吸风器的结构及其工作原理;介绍了喷射器的性能与特点;笔者运用喷射器在大型化肥塔类设备内外施焊、等离子切割、球罐喷砂、箱式电炉模壳焙烧及马达线圈高温浸漆等10个不同施工场所进行了实际应用和验证,结果表明,该系列吸风器通风换气或排烟、排尘、排毒等性能安全可靠,且使用效果良好;同时,进一步研讨了改进和完善喷射式吸风器的有关技术问题。     

A Comparison of Statistical Approaches for Predicting Stream Temperatures Across Heterogeneous Landscapes1

Abstract: Estimating stream temperatures across broad spatial extents is important for regional conservation of running waters. Although statistical models can be useful in this endeavor, little information exists to aid in the selection of a particular statistical approach. Our objective was to compare the accuracy of ordinary least‐squares multiple linear regression, generalized additive modeling, ordinary kriging, and linear mixed modeling (LMM) using July mean stream temperatures in Michigan and Wisconsin. Although LMM using low‐rank thin‐plate smoothing splines to measure the spatial autocorrelation in stream temperatures was the most accurate modeling approach; overall, there were only slight differences in prediction accuracy among the evaluated approaches. This suggests that managers and researchers can select a stream temperature modeling approach that meets their level of expertise without sacrificing substantial amounts of prediction accuracy. The most accurate models for Michigan and Wisconsin had root mean square errors of 2.0‐2.3°C, suggesting that only relatively coarse predictions can be produced from landscape‐based statistical models at regional scales. Explaining substantially more variability in stream temperatures likely will require the collection of finer‐scale hydrologic and physiographic data, which may be cost prohibitive for monitoring and assessing stream temperatures at regional scales.     

Good deposits are not enough: Mining labor productivity analysis in the copper industry in Chile and Peru 1992–2009

Chile and Peru produce almost 45% of world’s mine copper output. This situation reflects their natural endowment and mining tradition, but is also the result of development processes undertaken over the last decades. As a result, both countries multiplied its mine copper production in more than 3 times in the last 20 years. Mining labor productivity played a central role achieving these amazing growth rates. Although there is a consensus about the relevance of this variable for the mining industry, the specific factors behind labor productivity changes are not completely understood.     

长三角地区城市土地开发强度特征及影响因素分析

合理控制土地开发强度是提高土地利用效率和改善环境质量的重要手段。以建设用地面积占该区域土地总面积的比例为土地开发强度的表征指标，运用GIS软件和经济计量模型，探讨了1996~2008年长三角地区城市土地开发强度的特征及其影响因素。结果表明：长三角城市土地开发强度总体上呈增长趋势，城市间土地开发强度差异明显，并且具有空间集聚特征，形成了以上海、杭州为中心的高强度地区，这与目前长三角经济增长极相吻合。同时，经济增长、城镇化、产业结构与城市土地开发强度之间显著正相关，行政区划调整与城市土地开发强度在短期内表现为负相关关系，土地管理政策的影响尚不显著。今后，只有转变经济发展方式，严格执行土地管理政策和城市规划，合理推动城镇化和城市产业布局，才能使城市土地开发强度保持在合理水平。将为长三角地区城市土地可持续利用提供参考，对控制城市建设用地规模和发展方向，也有一定的理论和现实指导意义     

融雪剂对大叶黄杨生长和生理特性的影响

为了研究融雪剂对道路绿化植物的影响,以大叶黄杨（Euonymus japonicus Thunb）为研究材料,研究了其在3种融雪剂（JLR-01、LBR-4、芦笛一号）不同施用量影响下的生长量和生理特性。结果表明：随着融雪剂LBR-4和芦笛一号的施用量的增大,大叶黄杨叶片的相对生长量和株高相对生长量、光合速率（Pn）、水分利用效率（WUE）、蒸腾速率（Tr）和气孔导度（Gs）随之减小,而低施用量的融雪剂JLR-01对大叶黄杨生长量、Pn、WUE和Tr有促进作用。随着融雪剂作用时间的延长,3种融雪剂的Pn和WUE也随之减小,Tr则是先减小后有所增大。当融雪剂施用量较小和胁迫时间较短时,Pn下降是因为气孔关闭;而当施用量较大和胁迫时间较长时,Pn下降是因为叶肉同化能力下降;3种融雪剂对大叶黄杨的胁迫程度由大到小的次序为：芦笛一号〉LBR-4〉JLR-01;大叶黄杨对3种融雪剂施用量的忍耐阈值在80 g.m-2左右,大叶黄杨对施用LBR-4和芦笛一号的耐受时间阈值大约为3周,对施用JLR-01的耐受时间阈值为3周以上。     

气象条件对沈阳市环境空气臭氧浓度影响研究

利用2013年沈阳市环境空气监测点位臭氧监测数据,分析沈阳臭氧浓度变化特征,结合气象资料分析了其对臭氧浓度的影响。结果表明,沈阳市不同区域臭氧浓度变化特征基本一致。臭氧浓度日变化呈单峰趋势,最大值出现在14:00左右,最小值出现在6:00左右;臭氧浓度变化具有明显的季节特征,夏季臭氧浓度最高,春秋次之,冬季最低;臭氧浓度受温度、风速、湿度、能见度、天气情况影响,臭氧浓度变化是多因素共同作用的结果。     

我国安全生产基本特征规律研究

从经济社会发展视角,分析安全生产基本特征规律,指出安全生产随产业结构呈现不均衡分布特点,劳动力结构制约安全生产,城市化进程增加安全生产不稳定因素.安全生产与GDP对比分析表明,党和国家采取的一系列重大措施有效抑制了经济快速增长给安全生产带来的负面作用,我国安全生产提前进入事故波动期.通过研究区域经济与安全生产关系,得出我国4大经济区域社会经济发展水平与安全生产之间存在规律性分布特征.该研究的成果为建立安全生产长效机制,实现我国经济社会与生产安全协调发展探讨新的途径.