井下运输人—机—环境系统安全性灰色多层次综合评判

为了分析与评价井下运输系统的安全状况,笔者基于灰色关联分析理论,确定了井下运输系统安全状况综合评判的指标体系,建立了灰色多层次安全综合评判模型。通过对影响井下运输系统安全的人、机、环境的１１ 种因素进行的实际分析与计算,指出了井下不同运输子系统的安全状况及其薄弱环节。该方法使评判结果更具科学性、可比性和实用性,而且为进一步搞好安全评价工作提供了理论依据。     

Intergovernmental relationships after disaster: state and local government learning during flood recovery in Colorado

ABSTRACT

When communities experience disaster, emergency response and recovery are led internally, based on local-level policy decisions and priorities. Decisions about how or whether to rebuild are made by local governments. Higher governmental authorities such as states and provinces may institute their own disaster recovery processes and policies in addition to or in competition with local governments. Greater intergovernmental engagement could increase resources and knowledge, which would yield higher levels of learning and result in superior disaster recovery policy outcomes. The role of higher authorities, then, can have important implications for policy processes and outcomes. The learning literature includes a dearth of studies that analyze the relationships between state and local governments during disaster recovery. We move the learning literature forward by analyzing intergovernmental relationships during disaster recovery. We find that learning within local governments is associated with higher levels of resource flows from state agencies as well as more collaborative intergovernmental relationships. We also find that state governments can improve processes for disaster recovery assistance and bring together disaster-affected local governments to promote learning during the recovery process. While this study focused on relationships constrained by U.S. federal dynamics, the lessons are useful to other multilevel governance systems.     

Collaborative learning for policy innovations: sustainable urban drainage systems in Leicester,England

ABSTRACT

Collaboration among multiple stakeholders is crucial in decentralised governance settings. The success of such collaboration hinges upon collaborative learning – the acquiring, translating, and disseminating of policy-relevant knowledge. However, despite much research, a knowledge gap persists in the public policy literature on the relationship between learning and policy change. It is debated whether learning is necessary and sufficient for policy change, and if so, under what conditions. To contribute to this debate, this paper examined whether collaborative learning has had any impact on the emergence and implementation of sustainable urban drainage systems (SuDS) in Leicester, England. We first examined implementation of SuDS in Leicester, and then study collaborative learning focused on SuDS. We found that implementation of SuDS in Leicester is marginal despite active collaborative learning that has resulted in the change in beliefs and attitudes towards SuDS among all policy actors in the setting. Social dynamics factors and leadership of two SuDS champions proved crucial for collaborative learning. We conclude that collaborative learning, while essential for legitimacy of a policy innovation, is not sufficient for policy change and a national legal and institutional framework is required to incentivise broader SuDS practices in Leicester and England.     

How floral odours are learned inside the bumblebee (Bombus terrestris) nest

Recruitment in social insects often involves not only inducing nestmates to leave the nest, but also communicating crucial information about finding profitable food sources. Although bumblebees transmit chemosensory information (floral scent), the transmission mechanism is unknown as mouth-to-mouth fluid transfer (as in honeybees) does not occur. Because recruiting bumblebees release a pheromone in the nest that triggers foraging in previously inactive workers, we tested whether this pheromone helps workers learn currently rewarding floral odours, as found in food social learning in rats. We exposed colonies to artificial recruitment pheromone, paired with anise scent. The pheromone did not facilitate learning of floral scent. However, we found that releasing floral scent in the air of the colony was sufficient to trigger learning and that learning performance was improved when the chemosensory cue was provided in the nectar in honeypots; probably because it guarantees a tighter link between scent and reward, and possibly because gustatory cues are involved in addition to olfaction. Scent learning was maximal when anise-scented nectar was brought into the nest by demonstrator foragers, suggesting that previously unidentified cues provided by successful foragers play an important role in nestmates learning new floral odours.     

The effect of larval and early adult experience on behavioural plasticity of the aphid parasitoid <Emphasis Type="Italic">Aphidius ervi</Emphasis> (Hymenoptera,Braconidae, Aphidiinae)

The relevance of the integration of preimaginal and eclosion experiences on the subsequent habitat preferences and mate finding by the adult has been rarely tested in holometabolous insects. In this work, the effect of larval and early adult experiences on the behavioural responses of adult males of the aphid parasitoid, Aphidius ervi, towards volatiles from the host–plant complex (HPC) and from conspecific females were evaluated. Two experience factors were considered: host diet (normal diet=ND; artificial diet=AD), and eclosion, i.e. extraction or non-extraction of the parasitoid larva from the parasitised aphid (extracted=EX; non-extracted=NE). Thus, four treatments were set up: ND/NE, ND/EX, AD/NE and AD/EX. Glass Y-tube olfactometers were used to investigate the responses of adult A. ervi males to the odour sources used. Males from the ND/NE treatment showed a shorter latency to the first choice of olfactometer arms, displayed a marked preference towards the HPC olfactometer arm, and spent more time in the HPC arm than males from the other treatments. Only the interaction of host diet and eclosion experiences proved to be relevant in explaining the differences in latency to first choice, time spent in olfactometers arms, and behaviours displayed in the olfactometer arms. These results show the importance of the integration of larval and eclosion experiences in the development of stereotyped responses of the adults. This process may involve memory retention from the preimaginal and emergence period, but further research is needed to disentangle the contribution of each stage. The response to conspecific females was much less affected by the treatments in relation to first arm choice and times in olfactometer arms, suggesting a pheromone-mediated behaviour, even though a prompter and more intense wing fanning courtship behaviour was registered in the ND/NE males compared to males from the AD/NE treatment. These results show that sexual behaviours are less affected by early experiences than behaviours related with finding a HPC for foraging or oviposition. Taken together, our results demonstrate for first time that larval and eclosion experiences affect in a differential way the early responses of the adult towards environment-derived cues and mate related cues.     

吉林省COD排放环境学习曲线及减排潜力分析

基于2000-2009年吉林省9个市（州）COD排放量,对人均COD排放量和万元GDPCOD排放量的区域分布格局及其成因进行了定量分析;同时,基于2000-2009年COD排放量和人均GDP,建立了吉林省万元GDPCOD排放量随人均GDP变化的环境学习曲线,分析了2000-2009年COD排放环境负荷变化及减排潜力,对《吉林省国民经济和社会发展第十二五个五年规划纲要》确定的削减8．8％目标的可达性进行了预测。结果表明：在吉林省国民经济和社会发展指标条件下,目标值和预测值的误差小于2％,能够实现COD削减的约束性指标。     

太原市PM2.5浓度的气象特征影响分析及预报

利用2016～2020年太原市污染物浓度资料、以及国家基准气象观测站的同期地面气象资料,重点分析了太原市PM_2.5浓度的变化特征以及湿度、降水、风和混合层厚度等气象条件对PM_2.5浓度的影响,同时探讨了污染物浓度变化的成因,建立基于LSTM神经网络的PM_2.5浓度预报模型.结果表明,2016～2020年太原市区冬季出现的重污染天数最多,其中2017年冬季出现天数最多为28 d, PM_2.5浓度总体呈现出秋冬季节高,春夏季节低,周末PM_2.5浓度高于工作日浓度,PM_2.5浓度日变化大致呈现双峰型分布,分别出现在09:00左右和23:00至翌日01:00.除相对湿度和冬季气温外,其余气象要素与PM_2.5浓度在四季均表现为负相关.影响太原市区PM_2.5浓度升高的污染源主要位于其NE-ENE-E方向,西北部地区的相对不明显.汛期当达到中雨(降水量≥10 mm)以上级别的降水都对PM_2.5浓度降低有明...     

城市交通道路氮氧化物浓度的CART回归树预测研究

提出了基于CART回归树的氮氧化物(NO_x)浓度预测模型,利用杭州市延安路路边空气质量监测站2016年6—9月空气污染物监测数据和同期延安路路段车辆抓拍识别数据,通过数据处理、影响因素分析及CART回归树构造,搭建了NO_x浓度预测模型.实验分析结果表明,相对于支持向量机和BP神经网络预测模型,基于CART回归树的NO_x浓度预测模型的预测精度有大幅度提升,可决系数在0.92以上;同时,对环境条件差异较大的G20会议期间NO_x浓度进行预测分析,结果表明,CART回归树方法的预测精度比其它方法更高,能够适应不同条件下的预测需求.     

漫反射光谱手工与机器制样方法测试结果与对比分析

矿物含量及其变化有可能蕴藏着环境信息。赤铁矿和针铁矿是常见的两种化合物,在各种类型的沉积物中基本都有分布。在古气候研究中,赤铁矿和针铁矿的含量变化可以用来指示气候的干湿变化。漫反射光谱方法(DRS)可以进行赤铁矿和针铁矿含量测算,具有灵敏度高、速度快、准确度高等特点。这种方法虽然很实用,但是对于样品量比较大的研究来说,其手工磨样速度比较慢,而用机器研磨则会大幅提高样品制备效率,但是机器研磨是否会对分析结果产生影响尚未有研究报道。本文对30个河流相和湖泊相样品进行了漫反射光谱对比分析实验,发现手工和机器磨样在磁性矿物浓度上的变化趋势基本一致,但是两者之间存在一定的差异。因此,如果研究目的是希望从整体变化趋势来反演气候变化的过程,用机器研磨方法可以达到要求且效率明显提高;如果是进行浓度含量等其它方面的研究,则传统的手工方法是优先选择。     

基于关联向量机回归的水质预测模型

提出了一种基于关联向量机回归的水质时间序列预测模型,并以该模型对氢离子浓度指数(p H值)、溶解氧(DO)、高锰酸盐指数(CODMn)和氨氮(NH3-N)4种重要水质指标进行预测.首先采用国家环保部发布的四川攀枝花龙洞水质自动监测数据进行实验,对该模型的有效性进行了验证;然后将关联向量机回归预测模型与支持向量机回归预测模型进行比较.为了比较不同核函数的预测效果,实验中预测模型的核函数分别采用了线性函数和高斯函数.实验结果表明,关联向量机回归模型的预测效果不亚于支持向量机回归模型;且在给出预测值时,还能同时给出预测结果的可信程度.