A scoping review of post-disaster social support investigations conducted after disasters that struck the Australia and Oceania continent

This scoping review provides a summary of research findings on social support dynamics in the wake of disasters that occurred on the continent of Australia and Oceania between 1983 and 2013. Forty-one studies, quantitative and qualitative, were summarised, investigating different facets of post-disaster supportive interactions. All inquiries assessed disasters resulting from natural hazards, with the majority of them conducted following events in Australia and New Zealand. The review revealed similar patterns of post-disaster social support dynamics that routinely unfold after disastrous incidents all over the world. Consistent with the disaster mental health literature, the documentation of social support mobilisation and social support deterioration processes was common. Salutary direct effects of supportive behaviours on post-disaster psychological distress were also highly evident. Most studies, however, posed research questions or hypotheses that lacked empirical or theoretical grounding. In conclusion, the review offers several recommendations on how to advance research on post-disaster social support.     

Climate policy support under political consensus: exploring the varying effect of partisanship and party cues

By creating attitudinal rifts among partisan voters, political polarization is expected to negatively affect chances of effectively mitigating climate change. While such expectations generally have found support, less attention has been paid to the opposite claim that political consensus should eliminate the partisan dimension in climate change politics. This study tests this claim by studying how party identification, and party cues specifically, affects public policy attitudes in a context defined by political consensus. Using data from a large online access panel in Sweden, party identification and party cues are shown to matter for policy attitudes even in a consensus context. This effect is not limited to certain issues but is found across a wide range of policies, and the effect of party cues, for a given issue, varies across parties. The implications of this study and areas for future work are discussed.     

Monitoring,imperfect detection,and risk optimization of a Tasmanian devil insurance population

Most species are imperfectly detected during biological surveys, which creates uncertainty around their abundance or presence at a given location. Decision makers managing threatened or pest species are regularly faced with this uncertainty. Wildlife diseases can drive species to extinction; thus, managing species with disease is an important part of conservation. Devil facial tumor disease (DFTD) is one such disease that led to the listing of the Tasmanian devil (Sarcophilus harrisii) as endangered. Managers aim to maintain devils in the wild by establishing disease‐free insurance populations at isolated sites. Often a resident DFTD‐affected population must first be removed. In a successful collaboration between decision scientists and wildlife managers, we used an accessible population model to inform monitoring decisions and facilitate the establishment of an insurance population of devils on Forestier Peninsula. We used a Bayesian catch‐effort model to estimate population size of a diseased population from removal and camera trap data. We also analyzed the costs and benefits of declaring the area disease‐free prior to reintroduction and establishment of a healthy insurance population. After the monitoring session in May–June 2015, the probability that all devils had been successfully removed was close to 1, even when we accounted for a possible introduction of a devil to the site. Given this high probability and the baseline cost of declaring population absence prematurely, we found it was not cost‐effective to carry out any additional monitoring before introducing the insurance population. Considering these results within the broader context of Tasmanian devil management, managers ultimately decided to implement an additional monitoring session before the introduction. This was a conservative decision that accounted for uncertainty in model estimates and for the broader nonmonetary costs of mistakenly declaring the area disease‐free.     

Effective conservation planning of Iberian amphibians based on a regionalization of climate-driven range shifts

Amphibians are severely affected by climate change, particularly in regions where droughts prevail and water availability is scarce. The extirpation of amphibians triggers cascading effects that disrupt the trophic structure of food webs and ecosystems. Dedicated assessments of the spatial adaptive potential of amphibian species under climate change are, therefore, essential to provide guidelines for their effective conservation. I used predictions about the location of suitable climates for 27 amphibian species in the Iberian Peninsula from a baseline period to 2080 to typify shifting species’ ranges. The time at which these range types are expected to be functionally important for the adaptation of a species was used to identify full or partial refugia; areas most likely to be the home of populations moving into new climatically suitable grounds; areas most likely to receive populations after climate adaptive dispersal; and climatically unsuitable areas near suitable areas. I implemented an area prioritization protocol for each species to obtain a cohesive set of areas that would provide maximum adaptability and where management interventions should be prioritized. A connectivity assessment pinpointed where facilitative strategies would be most effective. Each of the 27 species had distinct spatial requirements but, common to all species, a bottleneck effect was predicted by 2050 because source areas for subsequent dispersal were small in extent. Three species emerged as difficult to maintain up to 2080. The Iberian northwest was predicted to capture adaptive range for most species. My study offers analytical guidelines for managers and decision makers to undertake systematic assessments on where and when to intervene to maximize the persistence of amphibian species and the functionality of the ecosystems that depend on them.     

基于GM-SVR的小样本条件下化工设备可靠性预测

为了准确预测化工设备可靠性趋势，针对化工设备失效寿命数据为小样本的情形，基于灰色估计法与支持向量回归机在小样本数据处理中的优势，建立了失效寿命时间服从三参数威布尔分布的化工设备可靠性模型；结合GM（1，1）和SVR对模型进行参数估计，在压缩机可靠性分析中进行了实例应用，对比分析了最小二乘法、灰色估计法和GM-SVR的估计效果。研究结果表明:GM-SVR对威布尔分布参数的估计精度明显优于最小二乘法和灰色估计法，可以有效地应用于化工设备失效数据为小样本时的可靠性预测。     

组织支持感对建筑业农民工不安全行为的影响*

为对建筑业农民工的不安全行为进行科学有效的管理，探讨组织支持感、自我效能感与建筑业农民工不安全行为之间的关系，防止因建筑业农民工不安全行为造成的不安全事件发生，从组织行为学和计划行为学视角出发，以218名一线建筑业农民工为研究对象，通过构建结构方程模型进行实证分析。结果表明:组织支持感的3个维度均可直接对建筑业农民工的不安全行为产生负向显著影响，其中关心利益维度影响最大，工作支持维度次之；建筑业农民工的自我效能感在其组织支持感与不安全行为的负向关系中起到中介作用。     

基于SVM的矿井通风阻力系数影响因素分析与预测

矿井通风阻力系数是通风安全最重要的基础参数之一，为了实现矿井通风阻力系数简单准确地预测，提出了利用支持向量机（SVM）来预测矿井通风阻力系数的方法。通过分析影响因子与矿井通风阻力系数的相关性关系，并利用MATLAB逐步建立单影响因素与矿井通风阻力系数、多影响因素与矿井通风阻力系数之间的SVM预测模型，对比分析各预测模型的相对误差，确定最佳矿井通风阻力系数预测模型，即当输入模型影响因素为巷道断面积、周长和支护方式时，预测相对误差小于10%的样本数占测试样本的76%，相对误差小于20%的样本数占测试样本的90%。结果表明:该预测方法在矿井通风阻力系数预测中是可行的，并具较高的准确性。     

超前支架迈步过程稳定控制方法研究

为提高巷道超前支架迈步前移过程的稳定性和安全性,建立一种基于液压油液体积平均释放原则的迈步稳定控制方法。用软件仿真及样机实测的方法,检验所提出控制方法的控制效果。结果表明,与传统的直线、对数曲线、指数曲线的阀芯位移控制方法相比,应用所建立的方法,设备迈步过程支撑力波动最小,稳定过程耗时最短,为2.2 s,顶板变形量最小,最大值约为4.74 mm。而采用对数曲线控制方式效果最差,稳定过程耗时3.8 s,顶板变形量最大值达到9.48 mm。     

基于AHP-联系熵的应急预案实施过程风险评估

应急预案制定后的实施对于事故发生后预案的顺利运行至关重要，因此，有必要对应急预案实施过程的风险水平进行度量。以应急预案实施过程作为研究对象，基于风险理论与AHP-联系熵耦合方法开展风险评估。以应急预案实施过程风险水平为目标层，应急预案的宣传教育和培训、应急资源的定期检查落实、应急演习训练、应急预案的实用性检验、应急预案电子化、事故回顾等过程要素作为策略层，实施方法科学高效、调动工作者积极的态度、领导的重视和能力、设备的完整性作为方案层，形成应急预案实施过程风险评估三级模型；运用联系熵表征风险标准与应急预案实施过程风险水平这2个集对之间的关联性，在AHP结构模型和权重分配的基础上计算加权熵并得到目标层的总联系熵，对比标准熵区间得到应急预案实施过程的整体风险等级。结果表明，采用AHP-联系熵度量方法提高了评价结果的结构性和准确性，比传统直接加权的方法更符合实际情况。     

新型机械澄清池设备的设计及在尾矿水处理中的应用

国内现有的机械加速澄清池因池体及设备结构的原因,存在刮泥耙直径小、驱动扭矩低,高负荷时排泥差等问题,不能满足用户对设备大池径（大于Ф29m）、大处理量、高效澄清、多用途的要求。介绍了新型澄清池设备的工艺、结构设计及特点。新型机械澄清池设备通过对池体结构的改进设计,及对刮泥机、提升搅拌机、排泥防堵搅拌机三者同心套装结构,扭矩可达百万牛顿米的带齿回转支承及多组电机同步驱动的刮泥耙驱动机构,池周边增设斜板及集水装置等方面的设计,实现了池径大于qb29in机械澄清池的设计制造,填补了国内该项目的空白,经矿山尾矿水处理实际应用证明效果理想。