Applying network theory to prioritize multispecies habitat networks that are robust to climate and land‐use change

Designing connected landscapes is among the most widespread strategies for achieving biodiversity conservation targets. The challenge lies in simultaneously satisfying the connectivity needs of multiple species at multiple spatial scales under uncertain climate and land‐use change. To evaluate the contribution of remnant habitat fragments to the connectivity of regional habitat networks, we developed a method to integrate uncertainty in climate and land‐use change projections with the latest developments in network‐connectivity research and spatial, multipurpose conservation prioritization. We used land‐use change simulations to explore robustness of species’ habitat networks to alternative development scenarios. We applied our method to 14 vertebrate focal species of periurban Montreal, Canada. Accounting for connectivity in spatial prioritization strongly modified conservation priorities and the modified priorities were robust to uncertain climate change. Setting conservation priorities based on habitat quality and connectivity maintained a large proportion of the region's connectivity, despite anticipated habitat loss due to climate and land‐use change. The application of connectivity criteria alongside habitat‐quality criteria for protected‐area design was efficient with respect to the amount of area that needs protection and did not necessarily amplify trade‐offs among conservation criteria. Our approach and results are being applied in and around Montreal and are well suited to the design of ecological networks and green infrastructure for the conservation of biodiversity and ecosystem services in other regions, in particular regions around large cities, where connectivity is critically low.     

Ethanol mediated As(III) adsorption onto Zn-loaded pinecone biochar: Experimental investigation, modeling, and optimization using hybrid artificial neural network-genetic algorithm approach

Organic matters (OMs) and their oxidization products often influence the fate and transport of heavy metals in the subsurface aqueous systems through interaction with the mineral surfaces. This study investigates the ethanol (EtOH)-mediated As(III) adsorption onto Zn-loaded pinecone (PC) biochar through batch experiments conducted under Box–Behnken design. The effect of EtOH on As(III) adsorption mechanism was quantitatively elucidated by fitting the experimental data using artificial neural network and quadratic modeling approaches. The quadratic model could describe the limiting nature of EtOH and pH on As(III) adsorption, whereas neural network revealed the stronger influence of EtOH (64.5%) followed by pH (20.75%) and As(III) concentration (14.75%) on the adsorption phenomena. Besides, the interaction among process variables indicated that EtOH enhances As(III) adsorption over a pH range of 2 to 7, possibly due to facilitation of ligand–metal(Zn) binding complexation mechanism. Eventually, hybrid response surface model–genetic algorithm (RSM–GA) approach predicted a better optimal solution than RSM, i.e., the adsorptive removal of As(III) (10.47 μg/g) is facilitated at 30.22 mg C/L of EtOH with initial As(III) concentration of 196.77 μg/L at pH 5.8. The implication of this investigation might help in understanding the application of biochar for removal of various As(III) species in the presence of OM.     

基于遗传神经网络的除湿机故障诊断与寿命预测

目的识别除湿机的性能状态和预测吸附剂的剩余寿命。方法针对除湿机故障过程缓变的特点,提出一种基于数据驱动的遗传神经网络模型。首先,为解决设备失效程度划分模糊的问题,由5个热力参数组成反映吸附剂劣化程度的特征向量,关联分析得到除湿机的5类故障模式。其次,利用遗传神经网络建立状态参数和故障模式的映射关系。最后,对表征设备吸附能力的主参数进行外推预测。结果训练好的诊断网络可准确地识别出设备的劣化程度及其演变过程,预测网络的预测精度非常高。结论该方法可有效地实现对除湿机的故障诊断与预测。。     

电晕放电辐射信号的特征提取和模式识别方法研究

目的研究电晕放电辐射信号的特征提取和模式识别方法。方法在分析信号特征提取方法的基础上,对实测的电晕放电辐射信号特征提取,利用概率神经网络开展电晕放电辐射信号目标识别,检验特征提取的有效性。结果以奇异值作为输入特征量的PNN在整体上效果更优,稳定性好,对两类不同放电辐射信号的正确识别率均可达到80%以上,并且当输入特征量个数达到10个时,对实测样本的正确识别率均达到了最高值。电晕放电的正确识别率为96.7%,火花放电的正确识别率为93.3%。结论该方法能基本满足实际放电信号的识别应用。     

基于WebGIS的水环境模拟关键技术研究

近年来随着水环境模拟领域的发展出现了较多水环境数学模型,目前日益成熟的WebGIS技术是使模型使用变得简单化和直观化的一大途径.是在通过Flex和ArcGIS Server搭建WebGIS系统平台的基础上,利用PHP进行WebGIS和水环境模拟模型的数据交互,实现系统平台和数值模型的松散耦合.用户在浏览器端进行模型输入条件的设置,模型在远程服务器端进行运行计算,反馈的模拟结果通过RIA在WebGIS中进行多元化动态展示.该方法对一般模型具有适用性,可降低模型使用门槛,提高模拟结果展示和分析能力.     

基于T-S模糊神经网络的大沽河水质变化特征分析研究

基于T-S模糊神经网络,利用大沽河2010年-2015年水质监测数据,选取溶解氧、化学需氧量、高锰酸盐指数、氨氮、总氮、总磷对水质具有重要影响的6项指标,建立适用的水质评价模型,对大沽河水质变化特征进行分析.结果显示:上游水质评价结果明显优于中游、下游水质评价结果,网络评价水质等级变化趋势同真实指标数据变化趋势一致.验证结果充分表明了T-S模糊神经网络用于水质变化特征分析是可行、有效的.     

正常污泥和膨胀污泥中EPS膜污染特性及其与膜表面作用能分析

胞外聚合物(Extracellular polymeric substance,EPS)是导致膜污染的重要物质,且不同形态污泥的EPS具有不同的性质,研究正常污泥和膨胀污泥的EPS膜污染特性具有重要意义.因此,实验考察了正常污泥和膨胀污泥的膜污染速率.结果表明,膨胀污泥膜污染速率远高于正常污泥,膨胀污泥EPS(Bulking sludge-EPS,BS-EPS)浓度((172.9±10.4) mg·g-1)明显高于正常污泥EPS(Normal sludge-EPS,NS-EPS)浓度((95.9±6 6) mg·g-1),且膨胀污泥的蛋白质/多糖(Protein/Carbohydrate,P/C)值(2.26)高于正常污泥的P/C值(1 97)此外,通过序批式吸附实验研究了正常污泥和膨胀污泥的EPS膜污染差异,并基于Derjaguine-Landaue-Verweye-Overbeek (XDLVO)理论计算了EPS与PVDF膜表面之间的作用能结果表明,EPS-膜系统的总界面能为负值,即EPS-膜系统之间会发生自吸附行为,而膜与BS-EPS的总界面能(-63.943mJ.m2)较膜与NS-EPS(-56.366 mJ·m2)具有较高的能量,因此,BS-EPS与膜的吸附力较强;NS-EPS和BS-EPS主要能量壁垒分别为8.89 kT和7.51 kT,表明NS-EPS与膜之间的排斥力更强,因而BS-EPS更容易造成膜污染     

燃煤电厂电-袋复合式除尘器优化控制的仿真运行研究

以电-袋复合式除尘器为仿真研究对象,在Windows界面下利用Visual Basic6．0编程语言开发出燃煤电厂电-袋复合式除尘器优化控制的仿真运行软件。该软件通过建立数学模型,进行仿真实验,模拟工况变化、优化运行参数等对电-袋复合除尘系统进行整体的优化控制,并综合分析电-袋复合除尘器运行过程中的能耗以及运行费用,对运行电压、电流、运行阻力、喷吹周期等参数进行了优化。该仿真软件达到了电一袋除尘系统的节能降耗的目的,同时也降低了电～袋复合除尘器的运行成本。     

在用车I／M制度的脆性及脆性源研究

I／M制度作为一个系统存在着脆性源,如果该制度在运行过程中控制不好脆性源,则其有效实施将受到影响。利用系统脆性理论对该制度进行分析研究找出L／M制度系统的脆性源以及解决措施是其分析研究的目的。在系统子因子中从业人员素质、仪器设备是最大的脆性源,但是其均被维修企业和检测企业所包含。综合分析研究结果显示,由于其在维修企业的脆性度比在检测企业的脆性度大,所以维修企业是该制度最重要的脆性源。用系统脆性理论分析方法分析I／M制度的脆性是一种科学、有效和实用的方法,具有较好的应用前景,为保障更好的运行I／M制度以有效的控制在用车的排放提供了理论依据。     

博弈论在弹道导弹核潜艇威慑能力定性评估中的应用

以国际政治经济学领域常用的博弈论为基础,建立了不同情况下的弹道导弹核潜艇核威慑能力的定性分析模型,其核心是分析威慑双方的策略互动,以便能够更加客观地对弹道导弹核潜艇的威慑能力进行评估。针对信息完全和信息缺失的情况,博弈论模型能够简便快捷地对弹道导弹核潜艇的核威慑效果进行评估,并能够提出提高潜艇威慑效果的具体措施。