Development of an integrated decision-support model for density management within jack pine stand-types

The objectives of this study were to (1) develop a modular-based structural stand density management model (SSDMM) and corresponding algorithmic analogue for natural (naturally regenerated stands without a history of density regulation) and managed (naturally or artificially regenerated stands with a history of density regulation) jack pine (Pinus banksiana Lamb.) stand-types, and (2) demonstrate the utility of the model in operational density management decision-making. Employing an Ontario-centric database consisting of 262 and 221 tree-list measurements obtained from 91 and 139 permanent and temporary sample plots situated within natural and managed stand-types, respectively, combined with data derived from density control experiments and sawmill simulation studies, six integrated estimation modules were constructed: Module A consisted of the parameterization of the core yield–density relationships which together drive the entire yield prediction system (e.g., size–density relationships for quadratic mean diameter, dominant height, mean volume, and mean live crown ratio, and site-specific height–age relationships); Module B consisted of the development of Weibull-based parameter prediction equation systems for recovering diameter distributions and composite height-diameter equations for height estimation; Module C consisted of the development of composite taper equations for predicting log products and stem volumes; Module D consisted of the development of allometric-based composite biomass equations for each above-ground component (bark, stem, branch and foliage) from which biomass estimates and associated carbon-based equivalents were derived; Module E consisted of the development of sawmill-specific composite equations for estimating chip and lumber volumes; and Module F consisted of the development of composite equations for estimating wood density and mean maximum branch diameter. The utility of the model was demonstrated by simultaneously contrasting a set of complex density management regimes (commercial thinning and variable planting densities) in terms of a broad array of stand-level yield outcomes and performance measures: overall productivity, log-product distributions, biomass production and carbon yields, recoverable products (chip and lumber volumes) and associated monetary values, economic efficiency, duration of optimal site occupancy, structural stability, and fibre attributes (wood density and mean maximum branch diameter). In summary, the modular-based SSDMM provides the analytical foundation for evaluating the likelihood of realizing a multitude of stand-level objectives when designing density control regimes for jack pine stand-types.     

工业碳减排绩效及其影响因素动态分解

进入21 世纪以来,中国工业碳排放总量仍在波动中增长。为了考查近10 a 来中国工业碳减排绩效,并定量分析影响工业碳减排的主要因素对碳减排的贡献变化情况,论文通过构建中国工业碳排放数据库并运用“精确”的Laspeyres 分解方法,对中国2001-2010 年36 个工业行业CO₂减排的影响因素进行了动态分解,研究结果表明：①虽然中国工业CO₂排放总量在不断增加,但CO₂排放增长率和工业碳排放强度双双降低,在考察周期内,CO₂排放总量从2001 年 2.89×10⁹ t 增长到2010 年7.16×10⁹ t,工业碳排放量增长率则从2003 年最高值18.86%持续下降至2009 年的5.77%,工业整体碳排放强度由2001 年的29.14 t/104元下降到2010 年的18.12 t/10⁴ 元;②工业经济规模不断增加是工业CO₂排放增加的主导因素,技术进步和结构调整则有效抑制了CO₂的增加,10 a 间规模效应对CO₂排放总量增加的贡献度年均达到191.81%,但是由于受到技术进步效应和结构调整效应的共同作用,10 a 来总效应值年均只有109.15%;③较之技术进步效应,结构调整效应对工业CO₂减排的贡献度更大,结构调整效应累计促进碳减排达2.07× 10⁹ t,而技术进步效应促进减排的总量只有1.14×10⁹ t。论文认为,着力中长期减排政策的制定,以保证技术进步在碳减排中持续发挥作用,同时充分挖掘结构调整对减排作用潜力是中国实现工业碳减排的务实选择。     

工作压力、安全注意力与不安全行为的影响机理模型

为探索矿工工作压力、安全注意力与不安全行为之间的深层次逻辑关系,在文献梳理和开放式访谈的基础上,采用结构方程构建工作压力、安全注意力与不安全行为的影响机理模型。采用多阶段随机抽样,抽取矿工650名,对矿工的工作压力、安全注意力和不安全行为进行问卷调查。结果表明:矿工工作压力的安全管理方式、无效能感、干部风格、组织支持和角色冲突均显著负向影响安全注意力,影响程度依次减弱;安全注意力的安全信息刺激显著负向影响不安全行为;工作压力通过安全注意力的自身素养和安全监管显著正向影响不安全行为。安全注意力是矿工工作压力和不安全行为的部分中介变量。有效减轻工作压力和控制安全注意力水平,可以有效干预不安全行为。     

ISM耦合ANP矿工安全注意力衰减影响因素模型

为了减少煤矿安全事故的发生,从“纵向过程观”角度,引入矿工安全注意力控制空间、安全信息分配空间和安全行为结果空间,建立矿工安全注意力衰减影响因素模型。首先,基于文献研究,建立矿工安全注意力衰减影响因素体系,一共包含12个指标;其次,利用解释结构模型（ISM）构建矿工安全注意力衰减的3级递阶有向图;最后,采用网络层次分析法（ANP）构建矿工安全注意力衰减影响因素的权重模型,并借助Super Decision（SD）软件求解。结果表明:安全自制力、行为习惯、工作负荷、风险应对力以及安全信息刺激频率为表层直接影响因素;安全认知、工作要求、作业环境特征、安全信息变化多样性和风险感知力为中层间接影响因素;管理方式和安全信息刺激强度为深层根本影响因素。主要影响因素有:安全认知、安全自制力、行为习惯、管理方式、安全信息刺激频率以及风险感知力。     

人因脆弱性对安全注意力衰减的SEM研究

为深入研究人因脆弱性影响因素对安全注意力衰减的深层次作用关系,基于复杂系统脆弱性（CSV）理论,采用因子分析法对人因脆弱性进行主成分分析,提取8个人因脆弱性因子;然后,引入安全注意力配置作为中介变量,借助结构方程模型技术建立人因脆弱性对安全注意力衰减的SEM。结果表明:安全注意力配置与安全素质、安全意识、受教育程度、工作年限、安全知识、工作倦怠、安全心理等因子显著相关;安全注意力衰减与安全意识、安全自制力、工作倦怠、安全心理等因子显著相关;安全注意力配置与安全自制力的关系不显著;安全注意力衰减与安全素质、受教育程度、工作年限、安全知识的关系不显著。     

基于CA-SEM的煤矿安全事故风险因素结构模型

围绕煤矿安全风险管理的内涵,通过因子分析和层次聚类分析,识别煤矿安全事故风险主要包含人因风险、管理风险、信息风险、环境风险和设备风险5个风险因素层的22项风险因子。以人因风险层的6个风险因素为内源潜变量,其他4个风险层的16个风险因素为外源潜变量,构建煤矿安全事故风险因素的CA-SEM模型。运用SPASS17.0和AMOS7.0剖析各风险因素层以及各风险因子对煤矿安全事故风险的综合影响及其作用机理,从而为实现煤矿本质化安全提供决策依据。     

Understanding the effects of rainfall on elephant-vegetation interactions around waterholes

The distribution of surface water affects herbivore-vegetation interactions in arid and semi-arid regions. Limited access to surface water typically results in the emergence of vegetation gradients around natural and artificial water sources. In particular, African elephants can create large-scale gradients of woody vegetation. Understanding the dynamics of these gradients is of particular importance for the conservation of other, less mobile herbivores that depend on woody vegetation in areas close to water. While rainfall is known to be a key determinant of herbivore-vegetation interactions in dry areas, we only have limited understanding on how it impacts woody vegetation gradients around waterholes. To address this problem, we developed a deterministic simulation model that describes the interplay of rainfall, elephants and woody vegetation in the vicinity of waterholes. The model is based on elephant telemetry data and the ecological conditions in Etosha National Park (ENP), Namibia. We found that decreasing amounts of rainfall led to an increased degradation of woody vegetation, which was particularly severe in areas close to water. Based on this result we conclude that low rainfall was an important driver of recently observed patterns of vegetation degradation in ENP. More generally, rainfall appears to be a key factor that determines elephant-vegetation interactions and thus dynamics of woody vegetation gradients around waterholes. Using long-term rainfall data from ENP, we also demonstrate that an increase in the number of water sources during periods of low rainfall can mitigate the destructive impact of elephants in areas close to water. However, more research is required to assess the sustainability and effectiveness of rainfall-adapted strategies of artificial water provisioning in more detail. In particular it is important to investigate potential effects on elephant population dynamics.     

A numerical investigation of fluid-structure coupling of 3 MW wind turbine blades

In this paper, computational modeling is created for 3 MW wind turbine blade using the software Solidworks, and the computations are carried out using Workbench for the fluid–structure interaction of blades due to both the rated and the extreme wind load. The methods developed are applied to the simulation of the NREL Phase VI wind turbine blades, and validation against published data is presented. Moreover, the static structural analysis for wind turbine rotor is performed using Mechanical APDL. The results show that the maximum values of stress reach 458 MPa and 76.9 MPa due to the rated and extreme wind load, respectively, which are lower than 78.3 MPa, the flexural strength of Swancor 2511-A epoxy resin for blade material.     

分布式认知理论框架下农户土地转出意愿影响因素研究——基于SEM模型的武汉城市圈典型地区实证分析

基于分布式认知理论,从"个人力"、"地域力"、"文化力"三个层次构建农户土地流转认知的影响因素理论框架,利用"武汉城市圈"典型地区土地流转调查数据构建结构方程模型(Structural Equation Model,SEM),定量分析各影响因素在农户土地流转认知中的作用。研究证实:不同农户认知群体之间存在不同流转认知偏好,"无文化的老农民"相对于"有文化的年轻职业者"在土地流转认知中更加保守;农户对土地的需求普遍偏向土地的资产属性和财产权利,农村土地流转具备内在动力;然而,出于对土地社会保障功能的需求,农户不会因为其家庭生产方式和经济来源明显脱离土地而产生强烈的土地转出愿意,农户的家庭生计条件及"土地情节"在一定程度上制约了土地流转;村镇干部"取信于民"是农户获得"安全感",克服风险规避心理促进土地流转认知的最重要因素;流转价格是对农户在土地流转中物质与精神"双重损失"的资金补偿,两者的匹配程度对农户的认知具有重要作用。在此基础上,得出要规范流转程序、健全流转监督机制、保护农民利益,加强农村社会保障制度建设以确保农民获得公平的社会保障,加快推进和支持农村教育以提高农村劳动力素质,建立和完善土地流转制度保障和农业经营扶持机制等政策启示。     

Comparative study on consumption behaviors in private car markets between large and medium–small cities in China

With the economic development and the acceleration of motorization in China, the number of private cars increases rapidly in urban areas. However, the limit of urban resources and the contradiction between traffic supply and demand are increasingly prominent in large cities, while private car consumption has been a new “light” in medium and small cities. Consumers’ behaviors differ from region to region. Aiming at the above problems, we formulate structural equation modeling and carry out empirical research. In this paper, a comparative study about the main influential factors that affect the consumption of private cars in large and small cities in China is made, and it is hoped that some guidance for policy recommendations can be obtained.