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。     

外军装备维修及对我军弹药维修的启示

首先介绍了外军装备维修的现状和发展趋势,之后指出了我军弹药维修存在的问题,最后得出对我军弹药维修保障发展的启示。认为我军弹药维修保障应向军民一体化方向发展,开展全寿命保障,提高保障信息化水平,进行弹药两级维修体制的论证,并倡导绿色维修的新理念。     

湿地基质及阴极面积对人工湿地型微生物燃料电池去除偶氮染料同步产电的影响

本研究采用人工湿地型微生物燃料电池处理偶氮染料X-3B,实现降解偶氮染料同步产电的效果.为了构建性能最优的人工湿地型微生物燃料电池(CW-MFC)系统,本研究主要从湿地基质和阴极面积两个方面研究系统构型对去除X-3B同步产电的影响,提高系统性能.研究表明以粒径10 mm、孔隙率30%的小石子作为湿地基质构造的CW-MFC系统微生物生物量最大,去除X-3B效果最好,脱色率高达92.70%,但其产电性能最差.较小的粒径和孔隙率使底层微生物生物量增加,促进X-3B的去除,但随着湿地基质粒径和孔隙率的减小,导致阴阳极营养物质不足,系统传质阻力增加,抑制了系统产电性能.X-3B的去除效果随着阴极面积的增加而提高直到阴极面积为594 cm~2时取得最大脱色率99.41%.当阴极面积继续增加时,CW-MFC系统产电性能上升趋势趋于平缓,X-3B去除效果呈现下降趋势,这是因为阴极反应过快导致更多的阳极电子输送到阴极用于产生电流,与X-3B发生反应的电子减少,阳极成为提高CW-MFC系统性能的限制因素.     

基于距离相关系数和支持向量机回归的PM2.5浓度滚动统计预报方案

针对目前空气质量统计预报方法存在的主要缺陷,本文提出了距离相关系数和支持向量机回归相结合的统计预报方案DC-SVR.利用淮安市2013年1—12月PM_(2.5)观测资料和常规气象观测资料,首先在选入预报当日气象要素的基础上,增加选取前期污染物和气象要素作为预报因子,再采用距离相关系数分季节从预报因子中筛选出重要预报因子,最后采用支持向量机回归对PM_(2.5)浓度值进行逐日滚动统计预报.研究发现,淮安地区气温和气压对PM_(2.5)的距离相关性要高于其他气象要素,夏秋季PM_(2.5)与气象要素的距离相关性较春冬季好.基于距离相关系数和支持向量机回归建立DC-SVR模型,PM_(2.5)的试预报值和实测值的全年相关系数高达0.76,平均偏差仅为1.13μg·m~(-3),平均绝对误差为23.47μg·m~(-3).通过与支持向量机回归、人工神经网络的统计预报效果对比,DC-SVR模型有效降低预报因子维数且能自适应选取最佳参数,预报精度显著优于其他3种统计预报方案,可为业务化预报提供参考.     

论可持续发展视野中的农村社会支持

本文阐述了如何可持续发展观来指导农村社会支持,并提出在农村社会支持活动中,引进社会保险、社会服务、生态保护和心理培育等新的机制,运用综合性评价指标体系对各种农村社会支持项目及其结果进行经济效益、社会效益和心理效益三个方面的分析。     

Framing of Geoengineering Affects Support for Climate Change Mitigation

The growing recognition that climate change mitigation alone will be inadequate has led scientists and policymakers to discuss climate geoengineering. An experiment with a US sample found, contrary to previous research, that reading about geoengineering did not reduce conservatives’ skepticism about the existence of anthropogenic climate change. Moreover, depending on how it is framed, geoengineering can reduce support for mitigation among both conservatives and non-conservatives. When geoengineering is framed as a major solution, people worry less about climate change, leading to reduced mitigation support. When framed as disastrous, people perceived geoengineering as riskier, also leading to a decrease in mitigation support. A more moderate framing of geoengineering as a partial solution is less susceptible to moral hazard effects. Overall, results suggest that geoengineering will not lessen political polarization over anthropogenic climate change, and could undercut support for mitigation efforts. Instead, framing geoengineering as a small piece to solving a big puzzle seems to be the best strategy to weaken this potential moral hazard.     

A spatially explicit backcasting approach for sustainable land-use planning

General backcasting as a decision support and planning method starts from desired future states and simulates developments backwards until reaching the present state. Development pathways that reveal steps to be taken to reach a certain future state, and milestones that serve as interim goals, are created during the process. Backcasting has hitherto only been applied in workshops or as a theoretical framework and no spatially explicit backcasting model has previously been established. This paper presents the development of a spatially explicit backcasting model. The proposed model first creates a future scenario utilizing an agent-based model and then simulates backwards. It is implemented using the programming language Python. The model has been applied to a case study for sustainable land-use planning in Salzburg, Austria. The results of the model run show a successful backcasting of land-use classes from a future state back to the present, in 10 year time steps.     

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.     

Optimizing mixture properties of biodiesel production using genetic algorithm-based evolutionary support vector machine

Nowadays, biodiesel is used as one of the alternative renewable energy due to the increasing energy demand. However, optimum production of biodiesel still requires a huge number of expensive and time-consuming laboratory tests. To address the problem, this research develops a novel Genetic Algorithm-based Evolutionary Support Vector Machine (GA-ESIM). The GA-ESIM is an Artificial Intelligence (AI)-based tool that combines K-means Chaotic Genetic Algorithm (KCGA) and Evolutionary Support Vector Machine Inference Model (ESIM). The ESIM is utilized as a supervised learning technique to establish a highly accurate prediction model between the input--output of biodiesel mixture properties; and the KCGA is used to perform the simulation to obtain the optimum mixture properties based on the prediction model. A real biodiesel experimental data is provided to validate the GA-ESIM performance. Our simulation results demonstrate that the GA-ESIM establishes a prediction model with better accuracy than other AI-based tool and thus obtains the mixture properties with the biodiesel yield of 99.9%, higher than the best experimental data record, 97.4%.     

纳米晶粒TiO2多孔微球的制备及其光催化性能的研究进展

介绍了纳米晶粒TiO2多孔微球的主要制备方法、主要参量及表征、光催化性能研究进展,指出了纳米晶粒TiO2多孔微球制备过程的技术关键与基本参量的功能。针对目前存在的问题,提出了今后的主要研究方向,并展望了纳米晶粒TiO2多孔微球在水处理领域的应用前景。