信息时代的网络会计

随着因特网的普及和应用,网络会计应运而生。本文从网络会计的概念、特点、理论、目标、要求、问题和发展等方面,论述了网络会计将会得到更广泛的发展和应用,它将成为当代会计学中最有潜力的新领域。     

污水处理厂尾水细菌群落结构分析

城市尾水中含有大量的微生物,其中相当一部分为病原菌,其排入自然水体后给附近人群造成健康威胁.本研究采用建立16S rDNA克隆文库和PCR-RLFP技术对尾水的细菌群落结构进行分析,结果表明尾水中有59种细菌分别属于11个纲,其中44种细菌属于Proteobacteria门,约占85%(其中β-Proteobacteria和γ-Proteobacteria纲占绝对优势),7种细菌属于Clostridia纲占7.2%,而Actinobacteria、Bacteroidia、Gloeobacteria、Nitrospira、Planctomycetacia这5个纲的细菌所占数量都低于4%,尾水中的细菌大多来源于污水处理过程,因此各地区应该根据受纳水体的特点和净化能力选择合适的污水处理工艺;59种细菌中Legionella spp.占10%以上,其导致的退伍军人症可能成为尾水排放对附近人群健康的最大威胁,另外尾水中一些细菌能代谢次氯酸盐对氯气有一定抵抗能力,所以在选择消毒措施时应该选用氯气消毒与其他消毒工艺的组合;本研究中粪大肠杆菌、大肠埃希氏菌、沙门氏菌、志贺菌属、霍乱弧菌等致病菌在尾水中均未检出,因此对这些致病菌进行研究需要选择针对性更强的方法.     

大气污染总量控制规划智能决策支持系统的开发与研究

对大气污染总量控制规划智能决策支持系统的开发步骤和总体结构做了介绍。并描述了该系统中的知识库系统、模型库系统、数据库系统和图形库系统的设计思想,特别是对知识库的构造进行了较详细的叙述。还介绍了神经网络技术在该系统中的应用。指出大气污染总量控制规划智能决策支持系统将为大气污染总量控制提供更科学、更合理、更有效的规划方案。     

基于自适应遗传小波神经网络的水质评价建模

水环境污染过程的非确定性和非线性,使得传统的水质评价方法存在局限性。为了提高水质评价的准确性,提出了一种基于改进小波神经网络(wavelet neural network,WNN)的水质评价模型。采用自适应遗传算法(adaptive genetic algorithm,AGA)对小波神经网络的初始权值进行优化,再通过小波神经网络算法对网络进行训练,最后对训练好的网络展开测试。仿真结果表明,自适应遗传算法和小波神经网络的结合提高了网络的训练效率,该方法可以用于水质评价建模,并且评价结果具有较高的精度和准确性。     

哈尔滨松北区城市湿地的生态安全分析

以哈尔滨松北区城市湿地为研究对象,选择10个指标,采用因子分析法和聚类分析法,研究了松花江发生污染事故前后城市湿地的生态安全状况.结果表明:发生污染前哈尔滨松北区城市湿地东区的生态安全程度最高,发生污染后中区的生态安全程度最低;西区的抗干扰能力较差.各主因子中以水因子的下降幅度最大,说明水污染直接影响了哈尔滨松北区城市湿地的生态安全.最后有针对性地提出了哈尔滨松北区城市湿地的生态安全对策.      

大数据解析技术在大气环境监测中的应用研究

针对近年来新兴的大数据及挖掘、分析技术,对大数据解析技术在环境科学研究中的应用进行了分析和探析。以城市局部地区大气细颗粒污染物PM2.5浓度计算为例,筛选了PM2.5浓度历史数据、气象条件、交通状况、人群活动情况、网格道路状况等数据为影响特征量,分析了用神经网络法进行大数据解析和推演的原理和数学过程,是用数学、计算机、统计等方法研究解决多元、非线性复杂环境问题的一种新的探索。     

Monitoring Air Quality in Mountains: Designing an Effective Network

A quantitatively robust yet parsimonious air-quality monitoring network in mountainous regions requires special attention to relevant spatial and temporal scales of measurement and inference. The design of monitoring networks should focus on the objectives required by public agencies, namely: 1) determine if some threshold has been exceeded (e.g., for regulatory purposes), and 2) identify spatial patterns and temporal trends (e.g., to protect natural resources). A short-term, multi-scale assessment to quantify spatial variability in air quality is a valuable asset in designing a network, in conjunction with an evaluation of existing data and simulation-model output. A recent assessment in Washington state (USA) quantified spatial variability in tropospheric ozone distribution ranging from a single watershed to the western third of the state. Spatial and temporal coherence in ozone exposure modified by predictable elevational relationships ( 1.3 ppbv ozone per 100 m elevation gain) extends from urban areas to the crest of the Cascade Range. This suggests that a sparse network of permanent analyzers is sufficient at all spatial scales, with the option of periodic intensive measurements to validate network design. It is imperative that agencies cooperate in the design of monitoring networks in mountainous regions to optimize data collection and financial efficiencies.     

走滑断层作用下X80管道设计应变规律和神经网络预测

走滑断层是埋地管道常见的地质灾害威胁,断层作用下管道会发生较大的拉压应变而失效。为得到X80管道的设计应变,基于有限元方法建立了走滑断层作用下管道的应变响应数值计算模型,模型使用壳单元模拟管道,非线性弹簧单元模拟土壤约束,采用西二线实际工程的管道应变影响参数范围,计算了管道的设计应变;为预测管道的设计应变值,基于以上参数化分析得到的4 817组设计应变结果,采用人工神经网络建立了管道设计应变预测模型。结果表明:该神经网络模型预测结果的最大相对误差小于10%,预测准确性良好,且该方法具有较高的计算效率,可以为断层作用下埋地管道的应变设计与评估提供参考。     

人工神经网络在湖泊富营养化评价中的应用研究

运用人工神经网络技术评价湖泊富营养化程度。详细阐述了神经网络的结构设计，样本生成及学习算法，给出了通过训练得出的网络权和阈值，最后将此神经网络用于１２个湖泊的富营养化评价，取得了较好的评价结果。     

Delivering on the Promise of Agroforestry

Agroforestry – the traditional practice of growing trees on farms for the benefit of the farm family and for the environment – was brought from the realm of indigenous knowledge into the forefront of agricultural research less than two decades ago. It was promoted widely as a sustainability-enhancing practice that combines the best attributes of forestry and agriculture. Based on principles of natural resource management and process-oriented research, agroforestry is now recognized as an applied science, that is instrumental in assuring food security, reducing poverty and enhancing ecosystem resilience at the scale of thousands of smallholder farmers in the tropics.Trees on farms provide both products and services: they yield food, fuelwood, fodder, timber and medicines, which farm families can use at home or take to market to bring in much-needed cash; they replenish organic matter and nutrient levels in soils and they help control erosion and conserve water. The International Centre for Research in Agroforestry, and its partners, are working to integrate the functions of trees with policy and institutional improvements that aim at facilitating wide-scale adoption by farmers.Two examples described in this paper are replenishing soil fertility in sub-Saharan Africa using short-term improved tree and shrub fallows and the results of agroforestry research to support significant land tenure policy in southeast Asia.Although just one option in sustainable land-use, science-based agroforestry has the potential to produce economically, socially and environmentally sound results for the billions of people who depend on this ancient practice and modern science.