Effects of Coastal Lighting on Foraging Behaviorof Beach Mice

Abstract:  Introduction of artificial light into wildlife habitat represents a rapidly expanding form of human encroachment, particularly in coastal systems. Light pollution alters the behavior of sea turtles during nesting; therefore, long-wavelength lights—low-pressure sodium vapor and bug lights—that minimize impacts on turtles are required for beach lighting in Florida (U.S.A.). We investigated the effects of these two kinds of lights on the foraging behavior of Santa Rosa beach mice (  Peromyscus polionotus leucocephalus ). We compared patch use and giving-up densities of mice for experimental food patches established along a gradient of artificial light in the field. Mice exploited fewer food patches near both types of artificial light than in areas with little light and harvested fewer seeds within patches near bug lights. Our results show that artificial light affects the behavior of terrestrial species in coastal areas and that light pollution deserves greater consideration in conservation planning.     

Stability of a Coal Waste Artificial Reef

The feasibility of using U.K. coal-fired power station waste materials for artificial reef production is being examined. in June, 1989, an experimental artificial reef was constructed in Poole Bay, off the central south coast of the U.K., using three different mixtures of pulverised fuel ash (PFA), flue gas desulphurisation (FGD) gypsum and slurry, stabilized with cement and formed into blocks. Fifty tonnes of 40 × 20 × 20 cm blocks were formed into eight conical reef units replicating three different PFA/gypsum mixtures and one concrete control. the reef structure is 10m below chart datum on a flat sandy sea-bed.

Combustion of coal concentrates the heavy metal content in the resultant ash. the purpose of stabilization of the ash as blocks is twofold: to immobilize heavy metals (or other components) and to provide hard substratum for the attachment of organisms. to examine the effectiveness of this stabilization and hence the environmental compatibility of the block materials, heavy metal (Cd, Cr, Cu, Pb, Mn, Ni, Zn) content of the blocks has been monitored routinely over two years, to determine leaching rates. Sectional profiles indicate partial replacement of calcium content by magnesium. Associated with this there has also been some redistribution of heavy metals. Only in the case of cadmium has there been a detectable loss from the surface of blocks. Chromium and manganese concentrations appear to have increased. the metal content of the reef epibiota (including ascidians, Ascidia mentula; hydroids, Halecium spp.; bryozoans, Bugula spp. and red algae) growing on the ash blocks has been compared to that of epibiota attached to the concrete controls and surrounding sea-bed. to date no evidence of excess bioaccumulation of metals has been detected.

The physical integrity of the ash reef blocks has been maintained. There is evidence that the blocks are increasing in compressive strength.

An indication of the fishery enhancement potential of the experimental structure is given by the presence of eight commercially fished species (crustaceans and molluscs) including lobsters (Homarus gammarus).     

基于人工神经网络的行业无害化生产能力评价模型研究

利用BP前向人工神经网络方法 ,建立了一种全新的基于人工神经网络的行业无害化生产能力评价模型 ,该模型采用动量梯度下降反向传播和学习速率自适应调整相结合的训练学习算法。最后 ,以造纸及纸制品业为例 ,对中国各省市造纸行业的无害化生产能力进行评价 ;并进一步分析中国各省造纸行业无害化生产能力的时空分布规律 ,为我国行业规划、布局决策提供科学依据。     

基于神经网络的压铸合金选择

在归纳总结压铸合金选择经验和知识的基础上 ,对压铸合金性能进行评价。采用BP神经网络方法建立了快捷的压铸合金材料选择系统 ,提出了一种将模糊化性能要求量化 ,增加训练样本集的方法。     

人工智能在金属塑性加工领域中的应用

概述了人工智能及其 2个主要分支 (专家系统和人工神经网络 ) ,讨论了遗传算法与专家系统集成以及神经网络与模糊逻辑、专家系统集成的必要性和集成方法 ,分别介绍了专家系统和人工神经网络在塑性加工领域中的应用现状。     

人工神经网络模型和公路复垦土地适宜性评价

提出了人工神经网络用于公路临时用地复垦土地适宜性评价，利用该模型对京大高速公路山西段复垦山西段复垦土地进行了适宜性评价，探讨了人工神经网络在土地复垦适宜性评价时的特点和注意问题。     

Prediction of the concentration of chlorophyll-α for Liuhai urban lakes in Beijing City

Introduction The eutrophication of fresh w ater has becom e a m ain w ater environm ental problem in the w orld. The m ain negative im pacts of fresh w ater eutrophication are w ater quality deterioration and the decrease of hydrophytes and aquatic specie…     

青藏高原生态资产地域划分中的SOFM网络技术

针对目前地域划分中存在的问题,论文尝试以人工神经网络技术作为区划工作的理论支撑,构建了自组织特征映射SOFM网络,以青藏高原环境与生态系统资产作为待分客体,探索了新技术和方法在生态资产地域划分中的应用。结果表明,对于自然界中广泛存在的非线性问题,SOFM网络具有比聚类分析等线性分类器更强的适应性。应用SOFM网络在对待分客体生态资产进行类型划分的基础上,使用策略性循环尺度转换(SCS)范式对其进行了区域转换,最终完成了青藏高原范围内生态资产的地域划分。     

人工神经元网络对水处理系统建模适应性的研究

针对水处理系统的特点和研究中的难点，引入人工神经元网络的理论和思想，提出了水处理系统的神经网络分析方法．通过建立基于ＢＰ人工神经元网络的臭氧生物活性炭系统的模型，具体地考察了人工神经元网络对水处理系统建模的适应性，使水处理系统的研究迈向智能化和控制化．     

特大火灾定量与定性风险管理技术应用探讨

定量化风险管理技术有其无可比拟的优势，但无法对风险因素中的人为因素进行管理。本文通过分析量化管理的缺陷和定性化管理的优势，提出应根据具体情况，采用定量化与定性化管理相结合的管理方式，并提出定性化管理的具体方法。