学生参与电气人才创新能力培养的探索

基于“以学生为本”的OBE教育理念，本文对电气人才创新能力培养进行了探索。整个过程将专业课程体系契合学业规划以明确学生学习目标；学生参与理论、实践教学和平台搭建，在夯实其理论知识的同时丰富教学资源；在创新考核中采用“螺旋递进式”的师生互动模式，全程培养学生自主的创新能力。多年实践探索表明学生在课程实践、学科竞赛、论文发表和申报专利等方面的创新能力得到显著提升。     

Nymphoides peltatum as a novel feedstock for biomethane production via anaerobic co-digestion with waste sludge

Nymphoides peltatum (NP) is exploited as a novel feedstock for biomethane production via anaerobic co-digestion with waste sludge (WS). Batch experiments are conducted under mesophilic condition at NP/WS of 1/3, 2/2, 3/1, 0/4 and 4/0 based on volatile solids (VS). Prior to anaerobic digestion (AD), NP undergoes only natural drying and grinding. The maximum net cumulative methane yield (265.16 mL CH₄·g VS_added^?1) and the highest gross VS removal rate (56.12%) are obtained at NP/WS of 1/3. The kinetic analysis by the modified Gompertz model fit hinted that 28 days is adequate for methane recovery and co-digestion significantly accelerates the digestion rate. Synergetic effect is corroborated to exist in co-digestion due to amiable conditions in term of total ammonia nitrogen, free ammonia, pH, volatile fatty acids and total alkalinity. High-throughput 16S rRNA pyrosequencing reveals that Bacteroidetes, Firmicutes, Methanosarcina and Methanosaeta are conducive to AD of NP.     

基于动态距离的模糊社区识别算法

社区识别技术是公共安全领域潜在危害行为预警预测和已发生危害行为追踪溯源的基础，针对传统社区识别算法将社区视作单一集合而无法描述社区主次成员的问题，提出一种基于动态距离的模糊社区识别算法。该算法将传统的单一社区结构划分为核心区域和边际区域，以边际区域来描述社区的模糊区间。该算法首先将网络设想为动态演变模型，网络中的任意节点均会与其他节点产生互动，互动将改变各节点间距离，距离也反过来影响互动。在阈值的界定下，受到多个社区吸引的节点被划分到边际区域，最终距离分布趋于稳定，各个社区结构得以显现。通过对比实验验证了CDFDD算法在社区识别上的有效性。     

Developing social impact assessment guidelines in a pre-existing policy context

Few jurisdictions have translated internationally agreed social impact assessment (SIA) principles into statutory provisions. Governments and regulatory bodies tend to provide developers with high-level frameworks, or require that social impacts be ‘considered’, without specifying how this is to be done. In Australia, this lack of clarity leaves all parties uncertain about requirements for SIA. The New South Wales (NSW) Government’s 2017 release of the SIA guideline for State-significant mining, petroleum and extractive industry development represents an attempt to clarify requirements and provide guidance. In this paper, we describe the process of bringing this guideline to fruition from the perspective of being directly involved in its development, and highlight the challenges involved in integrating leading-practice principles into the state’s pre-existing policy framework. While the guideline represents a significant advance in policy-based SIA guidance, some aspects leave room for improvement. The real test of the guideline’s impact will lie in its influence on SIA practice in NSW, and ultimately in social outcomes for communities affected by resources projects.     

培养原料种类的减少对人工窖泥发酵剂菌群结构的影响

为实现人工窖泥发酵剂（APMSC）的品质控制，从前期开发的发酵剂配方中分别取出老熟窖泥、曲药、酒糟和黄水初步形成4个简化配方，采用扩增子测序和色谱技术比较了各配方发酵剂的微生物群落结构及香味物质含量差异。结果显示，各配方发酵剂样品中共检测到70个微生物操作分类单元（OTU），其中71.43%为各组样品共有，未检测到独有OTU。各配方样品的优势微生物均存在于其余分组中，仅物种相对丰度有所差异。根据酿酒有益微生物的丰度高低，选择了一种简化配方（无老熟窖泥作原料）发酵剂养护窖池，使酿造白酒的主体香味物质含量得到显著提高。结果表明，即使缺失了某一种培养原料，人工窖泥发酵剂的功能微生物物种也可能由其他原料补充，而原料种类的减少是实现发酵剂品质控制的主要途径。     

以风化煤为底物制取生物甲烷的潜力分析

我国拥有丰富的风化煤储量,因其高度被氧化的独特性质,可应用的领域极为有限,目前主要被作为改善土壤性质的肥料和制取腐殖酸的来源。以风化煤为底物制取生物甲烷是一种具有探索性的全新生物发酵工艺,探究其可行性及模拟实验过程中风化煤的物性特征变化有利于拓宽风化煤的资源利用和环境改善,并可以进一步丰富煤生物产气理论。实验选取内蒙古乌海和山西晋城两地不同风化程度煤样,以煤层矿井水为菌种来源,在适宜环境条件下开展模拟产气实验,通过生物产气模拟和红外光谱测试,分析不同风化程度煤的生物产气能力及其内在因素,以揭示其产气潜力及物性变化特征。结果表明:①随着煤的风化程度加深,可燃基CH 4产气量明显增加,两组煤样中可燃基CH 4生成量最高分别达到7.13,4.20 mL/g;②不同风化程度的煤样均出现了产气高峰,时间基本都出现在15~30 d,各组中随着煤样风化程度不断加深,产气高峰出现时间也越来越早;③随着煤的风化程度加深,煤中芳环被不断打开,大分子结构被破坏,同时煤中羟基、氨基等基团含量趋于降低,脂碳结构逐渐解体,含氧官能团成为主要结构,氧含量比例不断增高,更容易被微生物降解;④菌群鉴定表明风化煤不仅含有大量产生生物气所需的第1阶段和第2阶段细菌,更含有甲烷杆菌属、甲烷球菌属等多种类型的产甲烷菌群,具有把风化煤转化为生物甲烷的环境条件。实验结果最终反映了风化煤具有转化为生物甲烷的潜力,并有利于提高我国风化煤的资源利用率。     

Governance choices and policy outcomes in the Latin American and caribbean electricity sector

The paper first provides, for Latin America and the Caribbean, country-specific synthetic quantitative measures of the degree of adoption of governance reforms in the electricity sector, focusing on four key dimensions (market structure, private sector participation (PSP), regulatory autonomy and operational organization). These measures are then correlated with standard policy performance outcomes measures. The findings suggest that, the reforms, considered jointly, were statistically significantly associated with higher technical and process quality but not with social or service improvements. Considered individually, increased regulatory autonomy enjoyed the highest positive correlation with desirable outcomes, but PSP has no significant correlation with any of the outcomes. In sum, as of 2018, governance reforms, considered jointly, had still not delivered on some promised payoffs, notably in addressing energy poverty, although the sensitivity analysis suggests that, for some indicators, the relationships are stronger for larger than for smaller countries.     

Estimating posterior inference quality of the relational infinite latent feature model for overlapping community detection

Overlapping community detection has become a very hot research topic in recent decades, and a plethora of methods have been proposed. But, a common challenge in many existing overlapping community detection approaches is that the number of communities K must be predefinedmanually. We propose a flexible nonparametric Bayesian generative model for count-value networks, which can allow K to increase as more and more data are encountered instead of to be fixed in advance. The Indian buffet process was used to model the community assignment matrix Z, and an uncollapsed Gibbs sampler has been derived.However, as the community assignment matrix Z is a structured multi-variable parameter, how to summarize the posterior inference results and estimate the inference quality about Z, is still a considerable challenge in the literature. In this paper, a graph convolutional neural network based graph classifier was utilized to help to summarize the results and to estimate the inference quality about Z. We conduct extensive experiments on synthetic data and real data, and find that empirically, the traditional posterior summarization strategy is reliable.