大气质量污染损失率评价模型参数的GA优化

设定各项污染物在大气环境质量污染损失率评价模型中有相同参数值,采用具有全局优化的遗传算法(GA)对模型中的参数进行优化,得出了对各种大气污染物均适用的大气环境质量污染损失率计算公式及大气环境质量综合评价模型。该模型与其他多种评价模型用于大气环境实例进行评价比较,结果表明:该评价方法不仅原理直观,评价结果准确,而且计算简便,实用性强。      

矿井通风系统风流控制的改进算法

介绍了矿井通风系统风流控制的基本数学模型和计算方法,指出了常规计算方法的不足,提出了一种能够避免大量矩阵运算、适用于实际通风网络的新算法,程序简单,计算时间省,并结合实例阐述了算法原理。     

福田保税区污水处理厂工艺选择

针对福田保税区的敏感地理位置 ,阐述了在该区域建设污水处理厂所采用工艺的确定过程和选择依据 ,并对第二阶段的比选工艺作了较为详细的比较 ,最终选出满足要求的SBR处理工艺     

Applying deep learning to right whale photo identification

Photo identification is an important tool for estimating abundance and monitoring population trends over time. However, manually matching photographs to known individuals is time-consuming. Motivated by recent developments in image recognition, we hosted a data science challenge on the crowdsourcing platform Kaggle to automate the identification of endangered North Atlantic right whales (Eubalaena glacialis). The winning solution automatically identified individual whales with 87% accuracy with a series of convolutional neural networks to identify the region of interest on an image, rotate, crop, and create standardized photographs of uniform size and orientation and then identify the correct individual whale from these passport-like photographs. Recent advances in deep learning coupled with this fully automated workflow have yielded impressive results and have the potential to revolutionize traditional methods for the collection of data on the abundance and distribution of wild populations. Presenting these results to a broad audience should further bridge the gap between the data science and conservation science communities.     

危化品道路运输事故应急救援中心选址模型研究

为快速提高危化品道路运输事故应急救援能力,降低事故后果,文章基于目前应急救援中心选址模型的不足,提出了一种新的双目标决策救援中心选址模型。通过综合考虑应急响应时间及应急处理能力对救援能力的影响,建立了救援中心点的最大网络覆盖模型;并采用较优的邻域搜索算法求解救援中心点的合理位置。最后以某地危化品运输路网为例,利用所建模型对事故应急救援中心的合理布局计算求解。结果表明:考虑应急响应时间及应急处理能力限制的应急救援中心选址模型,能够有效提高救援中心的综合应急能力,为有关部门合理规划危化品道路运输事故应急救援中心布局提供理论参考和决策依据。     

Selecting for Tolerance against Pathogens and Herbivores to Enhance Success of Reintroduction and Translocation

Abstract: Some species have insufficient defenses against climate change, emerging infectious diseases, and non‐native species because they have not been exposed to these factors over their evolutionary history, and this can decrease their likelihood of persistence. Captive breeding programs are sometimes used to reintroduce individuals back into the wild; however, successful captive breeding and reintroduction can be difficult because species or populations often cannot coexist with non‐native pathogens and herbivores without artificial selection. In captive breeding programs, breeders can select for host defenses that prevent or reduce pathogen or herbivore burden (i.e., resistance) or traits that limit the effects of parasitism or herbivory on host fitness (i.e., tolerance). We propose that selection for host tolerance may enhance the success of reintroduction or translocation because tolerant hosts generally have neutral effects on introduced pathogens and herbivores. The release of resistant hosts would have detrimental effects on their natural enemies, promoting rapid evolution to circumvent the host resistance that may reduce the long‐term probability of persistence of the reintroduced or translocated species. We examined 2 case studies, one on the pathogenic amphibian chytrid fungus ( Batrachochytrium dendrobatidis [Bd]) and the other on the herbivorous cactus moth ( Cactoblastis cactorum) in the United States, where it is not native. In each case study, we provide recommendations for how captive breeders and managers could go about selecting for host tolerance. Selecting for tolerance may offer a promising tool to rescue hosts species from invasive natural enemies as well as new natural enemies associated with climate change‐induced range shifts.     

Testing the presence of marine protected areas against their ability to reduce pressures on biodiversity

Marine protected areas (MPAs) are the preferred tool for preventing marine biodiversity loss, as reflected in international protected area targets. Although the area covered by MPAs is expanding, there is a concern that opposition from resource users is driving them into already low-use locations, whereas high-pressure areas remain unprotected, which has serious implications for biodiversity conservation. We tested the spatial relationships between different human-induced pressures on marine biodiversity and global MPAs. We used global, modeled pressure data and the World Database on Protected Areas to calculate the levels of 15 different human-induced pressures inside and outside the world's MPAs. We fitted binomial generalized linear models to the data to determine whether each pressure had a positive or negative effect on the likelihood of an area being protected and whether this effect changed with different categories of protection. Pelagic and artisanal fishing, shipping, and introductions of invasive species by ships had a negative relationship with protection, and this relationship persisted under even the least restrictive categories of protection (e.g., protected areas classified as category VI under the International Union for Conservation of Nature, a category that permits sustainable use). In contrast, pressures from dispersed, diffusive sources (e.g., pollution and ocean acidification) had positive relationships with protection. Our results showed that MPAs are systematically established in areas where there is low political opposition, limiting the capacity of existing MPAs to manage key drivers of biodiversity loss. We suggest that conservation efforts focus on biodiversity outcomes and effective reduction of pressures rather than prescribing area-based targets, and that alternative approaches to conservation are needed in areas where protection is not feasible.     

基于成本-效益准则的高层RC框架结构优化设计(Ⅰ)——方法

成本-效益准则是基于性能的抗震设计的重要原则,该准则在设计中除了考虑技术要素外,还考虑经济、社会等诸多因素,它所追求的设计目标为结构在其寿命周期内的总造价最小.因此,结构全寿命造价评估是基于性能的抗震设计的基本问题.在已有全寿命造价优化模型的基础上,提出了三目标函数全寿命造价优化模型.与已有的全寿命造价模型相比,该模型除考虑结构初始造价、损失期望外,还考虑了反映结构设计与施工复杂性的构件截面类型数量;另外,还将结构在其运行期间的检查、维护费用及由于优化导致建筑使用面积变化所引起的租金收益影响也列入到结构全寿命造价中.最后,基于所提出的优化模型,给出了以多目标遗传算法为搜索引擎、运用MATLAB语言开发的高层RC框架结构基于成本-效益准则的自动优化程序流程图.     

Metric-topological interaction model of collective behavior

Many simulations of collective behavior have been presented in recent years. Recently, a pioneering study by [Ballerini et al., 2008a] and [Ballerini et al., 2008b] suggested that the interactions of birds in a flock should be modeled using the topological distance rather than the metric distance. The concept of topological distance is deemed important for explaining collective behavior. However, few studies have discussed the distinctions between the metric and topological distances. In this paper, we clarify the difference between models based on the topological and metric distances and propose a new hybrid model of these models. The agent of our model switches between these two interactions by tuning the threshold parameters. We show that this hybrid flocking model has the medium property between the metric and the topological distance. In other words, the agents of our hybrid model can dramatically make and divide flock by tuning their neighborhoods. This result suggests that making and dividing flock would be deeply connected with animal's cognition.     

Inverse modeling for effective dispersal: Do we need tree size to estimate fecundity?

The estimation of the dispersal kernel for the seedling and sapling stages of the recruitment process was made possible through the application of inverse modeling to dispersal data. This method uses the spatial coordinates of adult trees and the counts of seedlings (or saplings) in small quadrats to estimate the dispersal kernel. The unknown number of recruits produced by an adult tree (the fecundity) is estimated - simultaneously with the dispersal kernel - via an allometric linear model relating the unknown quantity with a (easily) measured characteristic of the adult tree (usually the basal area). However, the allometric relation between tree size and reproductive success in the sapling (or seedling) stage may not be strong enough when numerous, well-documented, post-dispersal processes (such as safe-site limitation for recruitment) cause large post-dispersal seedling mortality, which is usually unrelated to the size of the tree that dispersed them. In this paper we hypothesize that when tree size and reproductive success in the seedling/sapling stage are not well correlated then the use of allometry in inverse modeling is counter-productive and may lead to poor model fits. For these special cases we suggest using a new model for effective dispersal that we term the unrestricted fecundity (UF) model that, contrary to allometric models, makes no assumptions on the fecundities; instead they are allowed to vary freely from one tree to another and even to be zero for trees that are reproductively inactive. Based on this model, we examine the hypothesis that when tree size and reproductive success are weakly correlated and the fecundities are estimated independently of tree size the goodness-of-fit and the ecological meaning of dispersal models (in the seedling or sapling stage) may be enhanced. Parameters of the UF model are estimated through the EM algorithm and their standard errors are approximated via the observed information matrix. We fit the UF model to a dataset from an expanding European beech population of central Spain as well as to a set of simulated dispersal data were the correlation between reproductive success and tree size was moderate. In comparisons with a simple allometric model, the UF model fitted the data better and the parameter estimates were less biased. We suggest using this new approach for modeling dispersal in the seedling and sapling stages when tree size (or other adult-specific covariates) is not deemed to be in strong relation to the reproductive success of adults. Models that use covariates for modeling the fecundity of adults should be preferred when reproductive success and tree size guard a strong relationship.