OPTIMAL INVESTMENT IN THE PROTECTION OF A VULNERABLE BIOLOGICAL RESOURCE

It is assumed that the probability of destruction of a biological asset by natural hazards can be reduced through investment in protection. Specifically a model, in which the hazard rate depends on both the age of the asset and the accumulated invested protection capital, is assumed. The protection capital depreciates through time and its effectiveness in reducing the hazard rate is subject to diminishing returns. It is shown how the investment schedule to maximize the expected net present value of the asset can be determined using the methods of deterministic optimal control, with the survival probability regarded as a state variable. The optimal investment pattern involves “bang-bang-singular” control. A numerical scheme for determining jointly the optimal investment policy and the optimal harvest (or replacement) age is outlined and a numerical example involving forest fire protection is given.     

Feature Selection Using Tree Model and Classification Through Convolutional Neural Network for Structural Damage Detection

Structural damage detection(SDD)remains highly challenging,due to the difficulty in selecting the optimal damage features from a vast amount of information.In this study,a tree model-based method using decision tree and random forest was employed for feature selection of vibration response signals in SDD.Signal datasets were obtained by numerical experiments and vibration experiments,respectively.Dataset features extracted using this method were input into a convolutional neural network to determine the location of structural damage.Results indicated a 5％to 10％improvement in detection accuracy compared to using original datasets without feature selection,demonstrating the feasibility of this method.The proposed method,based on tree model and classification,addresses the issue of extracting effective information from numerous vibration response signals in structural health monitoring.     

基于云计算的城建档案应用系统

在信息技术(IT)高速发展的时代,云计算技术在全世界范围内已经成为信息技术中的一大热点,笔者通过解析各种云计算方案的原理,对云计算在城建档案信息化管理中的应用进行了研究。以石家庄市城建档案馆基于云计算的城建档案数字化管理信息系统为例,分析了城建档案管理业务,介绍了云计算的概念、特点、服务模式及其体系结构,结合云计算应用架构和各级城建档案馆管理的实际需求,给出了基于云计算平台的城建档案管理信息系统整体解决方案,并提出了云计算技术在城建档案信息系统应用中还需要继续解决的问题和发展方向。     

长白山重点国有林区森林资源动态分析--以临江林业局为例

以临江林业局为例,分析了1977—2008年长白山重点国有林区森林资源动态变化情况,并提出今后森林资源经营管理的建议.结果表明:临江林业局林业用地面积和有林地面积均呈先下降后上升趋势,林地利用效率逐渐提高.1977—1997年,天然林面积逐年大幅减少,减少率约为37%,而后逐年上升;阔叶林蓄积所占比例大幅减少,针叶林蓄积比例大幅增加,针阔混交林蓄积占比趋向合理;1987年,中龄林面积和蓄积比例均很大;2008年林分各龄组面积和蓄积占比趋向合理.     

次生栎林酸沉降中SO2-4含量和pH值的变化特征

对下蜀次生栎林不同降水组份中硫含量和ｐＨ 值进行连续的观测与分析;揭示了ＳＯ２ －４ 和ｐＨ 值在不同降水组份中的变化规律以及ＳＯ２ －４ 与其它化学成分的相互关系,结果为进一步阐明本区酸性沉降物对森林生态系统的影响提供了理论依据。     

Analytical Determination and Bio-Monitoring of Platinum Group Elements in Roadside Grass Using Microwave Assisted Digestion and Electrothermal Atomic Absorption Spectrometry

The analytical conditions that enable the determination of traffic related platinum group elements (PGEs) in roadside grass using microwave digestion and electrothermal atomic absorption spectrometry were evaluated as an alternative to the biomonitoring of traffic related PGEs and Pb levels in urban areas. To optimize the analytical conditions and account for matrix effects that could import error in the analysis, method optimization was based on matrix simulation through analyte recovery from spiked unpolluted samples against a matrix blank. A mixture of nitric and hydrofluoric acid under progressively increasing microwave irradiation was optimized to afford the quantitative extraction of platinum group elements from plant matrix. Due to the low levels of platinum group elements in real samples, preconcentration was accomplished using sample evaporation followed by dissolution in dilute nitric acid prior to deliverance to the atomic detector. Quantitation limits below 1 ng g^?1 for Pd and Rh and lower than 2 ng g^?1 for Pt, were accomplished, enabling the monitoring of platinum group elements bioaccumulation in roadside grass with satisfactory recoveries, as determined from the analysis of spiked samples. The results from method application in an annual monitoring survey of PGEs and Pb levels in urban flora and other roadside media are presented and discussed.     

Determination of Pt in urine of tram drivers by sector field inductively coupled plasma mass spectrometry

The Platinum Group Elements (PGEs) used in automotive catalytic converters are partly emitted into the air during use and can enter the human respiratory system. Due to the increasing use of automotive catalytic converters, the importance of this problem cannot be overlooked.The goal of this investigation was to determine the concentration of Pt in the urine of individuals occupationally exposed to urban air with heavy traffic. Sector field inductively coupled plasma mass spectrometry (SF–ICP–MS) was used for determination of Pt in the urine of tram drivers. 38 and 34 subjects were investigated in Vienna and Budapest, respectively. Samples were taken from the tram drivers both before and after the shift.The results for Pt were compared to those from a previous study performed by our team. The comparison showed that the concentration medians were 4 times higher than the previous ones. Moreover, the values in Budapest were about twice as high as those from Vienna. A partly significant change could be observed between the two sets of data: before, and after the shift.