农村景观规划与生态建设

介绍了农村景观的发展与变化 ,论述了农村景观生态规划的内容与原则 ,并介绍了 5种典型的景观生态建设模式。     

Optimizing the Monitoring Strategy of Wastewater Treatment Plants by Multiobjective Neural Networks Approach

This paper applies artificial neural network (ANN) to model the observed effluent quality data. The ANN’s structure, involving the number of hidden layer and node and their connection, is determined endogenously by resorting to the compromise of data cost minimization and prediction accuracy maximization. To obtain the best compromise possible, the model introduces an aspiration variable (μ) that represents the level of aspiration achieved in one objective and the conjugate of μ, (1 − μ), represents level of aspiration achieved in the other objective. Because a massive amount of calculation is required, the model applies genetic algorithm (GA) for its computational flexibility and capability to ensure global solution. Feasibility and practicality of the model is tested by a case study with a set of 150 daily observations on 17 operational variables and quality parameters at an industrial wastewater treatment plant (WTP) located in southern Taiwan. Of these 17 variables open to selection, only 6 variables, wastewater flow rate (Q), CN⁻, SS, MLSS, pH and COD are selected by the model to achieve the maximum accuracy of prediction, 0.94, with a total cost of 5,950 NT$. By constraining budget availability, the variables included in the model are reduced in number, causing a concomitant reduction in prediction accuracy, that is, by varying μ (aspiration level of accuracy), a trajectory of cost and accuracy is generated. The calculation results a cost of 3,650 NT$ and 0.54 accuracy for the case with variables including flow rate, SCN⁻ and SS in equalization basin; aeration tank hydraulic retention time (HRT) and percentage of returned sludge (R%) are selected for building the prediction model when the importance of required budget is equal to the accuracy of prediction model. In addition, when required cost for building ANN model is between 3,650 NT$ and 3,900 NT$, the marginal return of budget input is highest in the entire range of calculation.     

A comparative approach to assess drivers of success in mammalian conservation recovery programs

The outcomes of species recovery programs have been mixed; high‐profile population recoveries contrast with species‐level extinctions. Each conservation intervention has its own challenges, but to inform more effective management it is imperative to assess whether correlates of wider recovery program success or failure can be identified. To contribute to evidence‐based improvement of future conservation strategies, we conducted a global quantitative analysis of 48 mammalian recovery programs. We reviewed available scientific literature and conducted semistructured interviews with conservation professionals involved in different recovery programs to investigate ecological, management, and political factors associated with population recoveries or declines. Identifying and removing threats was significantly associated with increasing population trend and decreasing conservation dependence, emphasizing that populations are likely to continue to be compromised in the absence of effective threat mitigation and supporting the need for threat monitoring and adaptive management in response to new and potential threats. Lack of habitat and small population size were cited as limiting factors in 56% and 42% of recovery programs, respectively, and both were statistically associated with increased longer term dependence on conservation intervention, demonstrating the importance of increasing population numbers quickly and restoring and protecting habitat. Poor stakeholder coordination and management were also regularly cited by respondents as key weaknesses in recovery programs, indicating the importance of effective leadership and shared goals and management plans. Project outcomes were not influenced by biological or ecological variables such as body mass or habitat, which suggests that these insights into correlates of conservation success and failure are likely to be generalizable across mammals.     

Strategic environmental disclosure: Evidence from the DOE's voluntary greenhouse gas registry

Although mandatory disclosure programs have been studied extensively, strategic voluntary environmental disclosures by firms are not well understood. We study the motivations for and impacts of firms' strategic disclosure of greenhouse gas reductions to the US government. We first model firms' joint abatement and disclosure decisions, incorporating both economic and political incentives. We then use data from the Department of Energy's Voluntary Greenhouse Gas Registry to compare reported reductions to actual emissions. We find that participants in the program engage in highly selective reporting: in the aggregate, they increase emissions over time but report reductions. In contrast, non-participants decrease emissions over time. Participants tend to be large firms facing strong regulatory pressure; pressure from environmental groups reduces the likelihood of participation, suggesting such groups viewed the program as a form of greenwash. Participating in the 1605(b) program had no significant effect on a firm's changes in carbon intensity over time.     

大贵寺国家森林公园野生青檀居群的遗传多样性

利用ISSR分子标记技术对湖北省大贵寺国家森林公园野生青檀（Pteroceltis tatarinowii Maxim．）居群进行遗传多样性分析。用11条ISSR引物对6个青檀居群64个样品进行扩增,扩增片段长度在200bp至3000bp之间,检测到179个位点,其中多态位点165个,多态位点百分率（P）为92．14％。青檀在物种水平上的Nei基因多样性指数（胁）和Shannon信息指数∽分别为0．273和0．423,在居群水平上分别为0．225和0．343,显示出青檀有着较高的遗传多样性。居群间的遗传分化系数（Gsr）为0．192,表明青檀居群间存在着较大的遗传分化;UPGMA聚类分析表明遗传距离与海拔差距有一定的相关性,相邻海拔的青檀居群间遗传距离较近。不同海拔导致的异质生境可能是影响青檀居群遗传分化的主要原因。     

一种改进的斜支撑体系支护某超大深基坑的变形分析

济南某商业广场超过50000 m2的基坑采用一种改进的斜支撑支护体系进行支护,与普通斜支撑支护型式不同,该支护体系包括支护桩、斜撑、立柱与支撑桩.本文采用FLAC3D显式有限差分数值计算分析方法,并结合支护桩水平位移测斜数据,对该支护体系的变形特性进行分析研究,从中论证各支护单元在3个开挖阶段的运动学效应.研究结果表明...     

Optimization of test interval for ageing equipment: A multi-objective genetic algorithm approach

Reducing the unavailability of safety systems at nuclear power plants, by utilizing the probabilistic safety assessment (PSA) methodology, is one of the prime goals in the nuclear industry. In that sense, optimization of test and maintenance activities, which are defined within the technical specifications, represents quite popular and interesting domain. Obtaining optimal test and maintenance schedule is of great significance for improving system availability and performance as well as plant availability in general.On the other side, equipment aging has gradually become a major concern in the nuclear industry since the number of safety systems components, that are approaching their wear-out stage, is rising fast. Nuclear power plants life management programs, considering safety components aging, are being developed and employed. The immense uncertainty associated to the available component aging rates databases poses significant difficulties in the process of incorporation and quantification of the aging effect within the PSA and, subsequently, in the decision-making process.In this paper, an approach for optimization of surveillance test interval of standby equipment with highly uncertain aging parameters, based on genetic algorithm technique and PSA, is presented. A standard standby safety system in nuclear power plant is selected as a case study. A Monte Carlo simulation-based approach is used to assess uncertainty propagation on system level. Optimal test interval is derived on the basis of minimal system unavailability and minimal impact of components aging parameters uncertainty. The results obtained in this application indicate the fact that risk-informed surveillance requirements differ from existing ones in technical specifications as well as show the importance of considering aging data uncertainties in component aging modeling.     

Age and gender differences in conviction and crash occurrence subsequent to being directed to Iowa's driver improvement program

Introduction

This paper investigates potential gender and age differences in conviction and crash occurrence subsequent to being directed to attend Iowa's Driver Improvement Program (DIP).

Methods

Binary logit models were developed to investigate the factors that influence conviction occurrence after DIP by gender and age. Because of the low crash occurrence subsequent to DIP, association rules were applied to investigate the factors that influence crash occurrence subsequent to DIP, in lieu of econometric models.

Results

There were statistical significant differences by driver gender, age, and conviction history in the likelihood of subsequent convictions. However, this paper found no association between DIP outcome, crash history, and crash occurrence.

Impact on industry

Evaluating the differences in conviction and crash occurrence subsequent to DIP between female and male drivers, and among different age groups can lead to improvements of the effectiveness of DIPs and help to identify low-cost intervention measures, customized based on drivers’ gender and age, for improving driving behaviors.     

扩展性案例在《Web应用开发技术》课程教学中的应用

《Web应用开发技术》是一门实践性和综合性较强的课程,扩展性案例的选取对课程教学具有重要作用。以＂登录注册系统＂为例,通过不断扩展该案例的功能,把各章知识点逐步融入到扩展性案例当中,使学生对各章主要知识点的应用有一个清晰的整体认识,激发学生求知、求技、求异、求新的兴趣,实现理论与实践的统一。     

STOP行为观察卡在TFT-LCD企业安全管理中的应用

以新型制造业TFT-LCD行业为背景,研究了STOP(Safety、Training、Observation、Program)安全训练观察程序在企业安全管理中的应用方法及效果。结合企业实际安全管理状况,通过引入STOP安全训练观察程序,设计出一套适用于企业的STOP行为观察卡及其使用方式,进而建立起企业自身的不安全行为数据库。实践结果显示,通过STOP行为观察卡记录数据可分析企业的突出安全问题。该方法为企业的安全管理进行大数据分析提供了良好的技术手段,在企业安全管理中具有广泛的应用前景。