Pulling force prediction using neural networks

Purpose. In ergonomics and human factors investigations, pulling force (PF) estimation has usually been achieved using various types of biomechanical models, and independent approximation of PF was done with the help of upper extremity joints. Recently, multiple regression methods have gained importance for task-relevant inputs in predicting PF. Artificial neural networks (ANNs) also play a vital role in fitting the data; however, their use in work-related biomechanics and ergonomics is inadequate. Therefore, the current research aimed to accomplish comparative investigation of ANN and regression models by assessing their capacity to predict PF values. Methods. Multipositional PF data were acquired from 200 subjects at three different handle heights and body locations. ANN and regression models were formed using a random sample of three subsets (75% training, 15% selection, 10% validation) for proving the outcomes. Results. The comparison of ANN and regression models shows that the predictions of ANN models had a profoundly explained variance and lower root mean square difference values for the PF data at three handle heights. Conclusions. These outcomes advise that ANNs offer a precise and robust substitute for regression methods, and should be considered a useful method in biomechanics and ergonomics task assessments.     

Beyond the material grave: Life Cycle Impact Assessment of leaching from secondary materials in road and earth constructions

In industrialized countries, large amounts of mineral wastes are produced. They are re-used in various ways, particularly in road and earth constructions, substituting primary resources such as gravel. However, they may also contain pollutants, such as heavy metals, which may be leached to the groundwater. The toxic impacts of these emissions are so far often neglected within Life Cycle Assessments (LCA) of products or waste treatment services and thus, potentially large environmental impacts are currently missed. This study aims at closing this gap by assessing the ecotoxic impacts of heavy metal leaching from industrial mineral wastes in road and earth constructions. The flows of metals such as Sb, As, Pb, Cd, Cr, Cu, Mo, Ni, V and Zn originating from three typical constructions to the environment are quantified, their fate in the environment is assessed and potential ecotoxic effects evaluated. For our reference country, Germany, the industrial wastes that are applied as Granular Secondary Construction Material (GSCM) carry more than 45,000 t of diverse heavy metals per year. Depending on the material quality and construction type applied, up to 150 t of heavy metals may leach to the environment within the first 100 years after construction. Heavy metal retardation in subsoil can potentially reduce the fate to groundwater by up to 100%. One major challenge of integrating leaching from constructions into macro-scale LCA frameworks is the high variability in micro-scale technical and geographical factors, such as material qualities, construction types and soil types. In our work, we consider a broad range of parameter values in the modeling of leaching and fate. This allows distinguishing between the impacts of various road constructions, as well as sites with different soil properties. The findings of this study promote the quantitative consideration of environmental impacts of long-term leaching in Life Cycle Assessment, complementing site-specific risk assessment, for the design of waste management strategies, particularly in the construction sector.     

The green state and industrial decarbonisation

ABSTRACT

The large share of carbon emitted by energy-intensive industries in the extraction and processing of basic materials must be limited to decarbonise society and the economy. Ways in which the state can govern industrial decarbonisation and contributes to green state theory are explored by addressing a largely ignored issue: the green state’s industrial relations and its role in industrial governance. With insights from a Swedish case study, the tension between the state’s economic imperative and ecological concerns in greening industry are shown to persist. However, as the energy-intensive industry’s previously privileged position in the economy is weakening, industry is opened to decarbonisation strategies. While the case exposes a number of governance challenges, it also suggests potential areas where the state can pursue decarbonisation in energy-intensive industry and points the way to an active role of the green state in governing industrial decarbonisation and greening industry.     

Renewable energy consumption and its environmental impacts: A meta-regression analysis

This study involves a meta-analytical review of several articles, using the closest assumptions for the independent variable (renewable energy consumption), to determine the relationship with its environmental impacts. Furthermore, Sustainable Development Goal (SDG) in 2015 pays attention to related problems in both developing and developed countries. The effects of carbon emissions, natural resources, renewable energy consumption, and non-renewable energy on the environment are also reviewed. Following the separation of studies, the closest assumption was observed for the independent variable (energy source applications) of renewable energy. The meta-analysis was obtained using OpenMEE and JASP, and the results show the observed outcome, which was expressed in percentage. Based on the analysis, the Renewable Energy model has a value of 0.15, with the largest forest plots of 0.73, 0.69, and 0.80, recorded for studies 13, 19, and 23, respectively, while the least forest plots were recorded for studies 6, 11, 12, 15, 20, 22, 24, 25, 26, and 28. Therefore, renewable energy consumption, specifically in the mining industry, has the capacity to influence global warming. The respective industry has a unique influence on the processes that require renewable energy, for instance, the coal mining industry produces a smaller forest plot value, compared to oil and gas, or other mineral industries.     

建筑施工中临边高处坠落危险源影响空间建模

将建筑施工中临边坠落的特性模型化,对于预防建筑施工中伤亡事故具有重要的意义。在分析人或物临边高处坠落事故特点的基础上,给出施工工作面内外2种危险源影响空间范围的定义及其数学表达函数,构建相应的危险源影响空间中危害能量分布的数学模型,提出它对人体不同部位伤害程度的评估分析思路,并在大面积碰撞和小面积碰撞2种情况下,建立该危害能量对人体头枕部伤害程度的评估分析方法。通过上海某个6层框架结构教学楼案例,对上述数学模型和评估分析方法进行验证。这为在进行施工计划安排时,考虑危险源影响空间的影响,降低安全事故发生的可能性创造条件,也为安全事故事前预防提供新思路。     

基于传感器的职业安全健康在线监测系统初探

在安全生产总体形势逐步好转的情况下,中国职业病危害致病因素中粉尘和噪声占有不可忽视的分量.本文通过对国内外在线监测技术的发展现状的详细分析,引入国内外先进的粉尘和噪声在线监测技术构建了职业安全健康在线监测系统基本架构,对其基本工作性能和实际能产生的工作效果进行描述,并对其产生的科技进步性进行阐述.     

点声源环境噪声声场区域二维图形化表征方法研究

针对环境噪声监测中单一点声源声场图形化表征机理,依据点声源衰减规律建立了点声源声场二维平面表征算法,据此以网格化区域范围内非均匀布置少量监测点方法确定声源点,再经克里金插值法反演点声源声场平面分布规律,最后通过ArcGIS软件平台实现噪声图形化展示.以5×5网格化区域为例,其非均匀布点数应不少于3个,最佳布点数为3组共计6个点,其实测值与理论值最大误差为4.3％.仿真试验验证表明,点声源图形表征符合实际声场分布规律.     

哈大齐工业走廊承接产业转移水环境风险评价

为了分析承接产业转移对水环境的影响,以哈大齐工业走廊为研究对象,在分析风险源、胁迫因子、生境、评价终点之间相互作用关系的基础上构建承接产业转移的水环境相对风险评价模型,并将研究区按照行政界线划分为3个风险评价单元,选取哈大齐地区重点承接的污染产业为风险源,选择水域作为风险受体,农田、林地、草地3种生境作为传播胁迫因子的媒介或载体,水质、水量、水生态为评价终点,对哈大齐承接产业转移水环境风险进行了定量评价.结果表明,哈尔滨市为最高风险区,其次是大庆市、齐齐哈尔市,相对风险分别为146.40、110.70和41.16.不同风险小区的最主要风险源不同,哈大齐3个城市主要风险源分别为医药制造业、化学原料与化学制品制造业及食品制造业.相反,各风险小区的主要胁迫因子大致相同,主要有需氧有机污染物、营养物质、生境破坏等.     

有机溶剂对过氧化环己酮热危险性的减敏效果评价

在纯过氧化环己酮(CYHPO)储运中常添加减敏剂,以降低其热危险性。为了对比评价减敏性能,采用绝热加速量热仪测试了纯CYHPO及加入等质量邻苯二甲酸二丁酯(DBP)、邻苯二甲酸二辛酯(DOP)、正己酸(HAA)和环己醇(CCH)后的热危险参数,并计算了上述5种样品的反应动力学常数和绝热校正数据,建立了包括初始放热温度T0和绝热反应加速度SARC的减敏效果判据,对4种减敏剂的热危险性减敏效果进行了评价。结果表明,DOP对CYHPO热危险性的减敏效果最好。     

Using social network analysis to examine planner involvement in environmentally oriented planning processes led by non-planning professions

Broad stakeholder involvement cannot be assumed in all environmental planning and management processes that have critical land use dimensions. This paper illustrates how concepts and techniques from social network analysis (SNA) can be used to examine and better understand the roles of one type of stakeholders, planners, in environmentally oriented planning and management processes led by other professions. Two cases of natural hazard mitigation planning led by emergency managers illustrate the usefulness of three SNA concepts of network structural characteristics in understanding how differences in planner involvement may influence incorporation of land use approaches in local natural hazard mitigation plans aimed at reducing long term risks from natural hazards.