作业疲劳测量方法对比研究

作业疲劳是导致生产效率下降、事故发生的重要原因之一。研究作业疲劳对提高生产效率、减少事故的发生,以及保护劳动者安全和健康具有重要意义。而作业疲劳测量方法是作业疲劳研究的前提和基础。因此,本文首先对作业疲劳的分类及其导致疲劳的原因进行了简单概述,并归纳总结了目前常用的几种作业疲劳测量方法,包括：主观感觉询问表评价法、生理参数测试法、生物化学测试法、心理学测试方法以及几种方法相结合的综合测试方法,并分析了上述几种作业疲劳测量方法的测量目的、适用范围、以及各自的优缺点,且针对不同研究目的提出了作业疲劳测量方法的选择和使用原则,并探讨了几个重点作业疲劳测量方法的研究方向,以及作业疲劳测量方法的完善方法。     

The causes of food waste in the supplier-retailer interface: Evidences from the UK and Spain

Food and drink waste is a significant problem for economic, environmental and food security reasons. Government efforts have focused on diverting waste away from landfill through regulation, taxation and public awareness. However, efforts to understand why waste occurs have been limited, particularly in the interface between retailers and suppliers. This research aims to address this problem by identifying the main root causes of waste in the supplier-retailer interface.The research is exploratory in nature as there is a paucity of studies focusing on food waste across the supply chain. Data were collected through 43 interviews with managers in food manufacturing, wholesaling and retailing in two countries: the UK (24) and Spain (19). Data from the interviews and supplementary documentation were analyzed using causal maps. This approach helped to identify the main root causes of waste which were categorized into three groups: (1) mega-trends in the marketplace, (2) natural causes related to the products and processes, and (3) management root causes on which practitioners have a direct impact.The paper discusses the root causes of food waste and good practices identified from the interviews. Differences between the UK and Spain are discussed, presenting potential learning opportunities for practitioners in these countries and highlighting opportunities for further research.     

Designing a mixed performance measurement system for environmental supply chain management using evolutionary game theory and balanced scorecard: A case study of an auto industry supply chain

This paper proposes a mixed performance measurement system using a combination of evolutionary game theory and the balanced scorecard (BSC) in environmental supply chain management (ESCM) that measures and evaluates business operations using the four different perspectives of finance, customer, internal business process, and learning and growth. ESCM plays an important role in the supply chain which leads to the reduction, reuse and recycling of resources involved in both upstream and downstream activities. This paper presents guidance for practical managers in evaluating and measuring ESCM by developing a knowledge-based BSC and evolutionary game theory. The primary purpose of this paper is to apply the proposed method in a case study to one of Iran's biggest auto industry supply chain SAIPA Company. The results of this study indicate that the adoption of ESCM, in the absence of regulatory pressures and cost-saving measures is triggered by public pressures and its implementation is limited by organizational factors and strategic myopia.     

高校环境专业实验教学存在的问题及对策

实验教学在高校环境专业教学工作中发挥着越来越重要的作用。通过对高校环境专业实验教学的现状和所存在的问题进行分析,提出了优化实验教学内容、改进实验教学方法和考核方式等改进措施,以提高高校环境专业实验教学水平。     

Ecosystem states: Creating a data-derived, ecosystem-scale ecological response model that is explicit in space and time

Increasing difficulties associated with balancing consumptive demands for water and achieving ecological benefits in aquatic ecosystems provide opportunities for new ecosystem-scale ecological response models to assist managers. Using an Australian estuary as a case study, we developed a novel approach to create a data-derived state-and-transition model. The model identifies suites of co-occurring birds, fish, benthic invertebrates and aquatic macrophytes (as ‘states’) and the changing physico-chemical conditions that are associated with each (‘transitions’). The approach first used cluster analysis to identify sets of co-occurring biota. Differences in the physico-chemical data associated with each state were identified using classification trees, with the biotic distinctness of the resultant statistical model tested using analysis of similarities. The predictive capacity of the model was tested using new cases. Two models were created using different time-steps (annual and quarterly) and then combined to capture both longer-term trends and more-recent declines in ecological condition. We identified eight ecosystem states that were differentiated by a mix of water-quantity and water-quality variables. Each ecosystem state represented a distinct biotic assemblage under well-defined physico-chemical conditions. Two ‘basins of attraction’ were identified, with four tidally-influenced states, and another four independent of tidal influence. Within each basin, states described a continuum of relative health, manifest through declining taxonomic diversity and abundances. The main threshold determining relative health was whether freshwater flows had occurred in the region during the previous 339 days. Canonical analyses of principal coordinates tested the predictive capacity of the model and demonstrated that the variance in the environmental data set was well captured (87%) with 52% of the variance in the biological data set also captured. The latter increased to >80% when long- and short-term biological data were analysed separately, indicating that the model described the available data for the Coorong well. This approach thus created a data-derived, multivariate model, where neither states nor transitions were determined a priori. The approach did not over-fit the data, was robust to patchy or missing data, the choice of initial clustering technique and random errors in the biological data set, and was well-received by local natural resource managers. However, the model did not capture causal relationships and requires additional testing, particularly during future episodes of ecological recovery. The approach shows significant promise for simplifying management definitions of ecological condition and, via scenario analyses, can be used to assist in manager decision-making of large, complex aquatic ecosystems in the future.     

Development of a coupled reservoir operation and water diversion model: Balancing human and environmental flow requirements

Maintaining a natural flow regime helps preserve the health of riverine ecosystems. Conventional studies on reservoir operations have focused mainly on identifying optimal operational schemes for satisfying human water demands. To systematically reflect the ecological effects of both natural and human-induced hydrologic alterations, water diversions downstream of the reservoirs should be considered as well. This research focused on a coupled reservoir operation and water diversion (CROWD) model, created through the integration of a reservoir operation model and a water diversion model. The proposed model considers both human and environmental flow requirements, and represents a compromise that balances ecological protection (preservation of the natural flow regime of a river) and human needs (reduced water shortages). In the reservoir operation model, the reservoir space is divided into three zones and different operating rules are developed for directing reservoir operation when water levels are in different zones; in the water diversion model, different water users are assigned different supply priorities with the instream flows no more than the minimum environmental flows having the highest priority; and the two models are coupled by the water mass balance between the two hydraulic facilities. The non-dominated-sorting genetic algorithm II (NSGA-II) was used to determine the parameters of the developed CROWD model and the model was applied to support the joint operational management of the Tanghe Reservoir and the Liaoyang Diversion in the Tang river basin, China. The resulting reservoir operation and water diversion schemes indicate that the CROWD model is useful for optimizing the operation of reservoirs and water diversion schemes. Moreover, it helps to analyze tradeoffs between human and environmental water needs, resulting in solutions that reduce the risk of water shortages and minimize ecological integrity disturbances.     

Incorporating low-resolution historic species location data decreases performance of distribution models

Developing robust species distribution models is important as model outputs are increasingly being incorporated into conservation policy and management decisions. A largely overlooked component of model assessment and refinement is whether to include historic species occurrence data in distribution models to increase the data sample size. Data of different temporal provenance often differ in spatial accuracy and precision. We test the effect of inclusion of historic coarse-resolution occurrence data on distribution model outputs for 187 species of birds in Australian tropical savannas. Models using only recent (after 1990), fine-resolution data had significantly higher model performance scores measured with area under the receiver operating characteristic curve (AUC) than models incorporating both fine- and coarse-resolution data. The drop in AUC score is positively correlated with the total area predicted to be suitable for the species (R² = 0.163-0.187, depending on the environmental predictors in the model), as coarser data generally leads to greater predicted areas. The remaining unexplained variation is likely to be due to the covariate errors resulting from resolution mismatch between species records and environmental predictors. We conclude that decisions regarding data use in species distribution models must be conscious of the variation in predictions that mixed-scale datasets might cause.     

Factors Affecting Stream Nutrient Loads: A Synthesis of Regional SPARROW Model Results for the Continental United States1

Preston, Stephen D., Richard B. Alexander, Gregory E. Schwarz, and Charles G. Crawford, 2011. Factors Affecting Stream Nutrient Loads: A Synthesis of Regional SPARROW Model Results for the Continental United States. Journal of the American Water Resources Association (JAWRA) 47(5):891‐915. DOI: 10.1111/j.1752‐1688.2011.00577.x Abstract: We compared the results of 12 recently calibrated regional SPARROW (SPAtially Referenced Regressions On Watershed attributes) models covering most of the continental United States to evaluate the consistency and regional differences in factors affecting stream nutrient loads. The models – 6 for total nitrogen and 6 for total phosphorus – all provide similar levels of prediction accuracy, but those for major river basins in the eastern half of the country were somewhat more accurate. The models simulate long‐term mean annual stream nutrient loads as a function of a wide range of known sources and climatic (precipitation, temperature), landscape (e.g., soils, geology), and aquatic factors affecting nutrient fate and transport. The results confirm the dominant effects of urban and agricultural sources on stream nutrient loads nationally and regionally, but reveal considerable spatial variability in the specific types of sources that control water quality. These include regional differences in the relative importance of different types of urban (municipal and industrial point vs. diffuse urban runoff) and agriculture (crop cultivation vs. animal waste) sources, as well as the effects of atmospheric deposition, mining, and background (e.g., soil phosphorus) sources on stream nutrients. Overall, we found that the SPARROW model results provide a consistent set of information for identifying the major sources and environmental factors affecting nutrient fate and transport in United States watersheds at regional and subregional scales.     

Regulatory attitudes and environmental innovation in a model combining internal and external R&D

The extent to which environmental regulatory institutions are either ‘green’ or ‘brown’ impacts not just the intensity of regulation at any moment, but also the incentives for the development of new pollution-control technologies. We set up a strategic model of R&D in which a polluter can deploy technologies developed in-house, or license technologies developed by specialist outsiders (an ‘eco-industry’). Polluters exert R&D effort and may even develop redundant technologies to improve the terms on which they procure technology from outside. We find that, while regulatory bias has an ambiguous impact on the best-available technology, strategic delegation to systematically biased regulators can improve social welfare.     

厦门水库水体颗粒物分布特征及其与环境因子的关系研究

研究了厦门湖边水库、石兜-坂头水库水体颗粒物的分布特征及其与环境因子之间的关系。结果表明:(1)水体颗粒物平均含量以坂头库区最高,石兜库区次之,湖边水库最低,平均含量分别为31.9、27.7和23.1mg/L;在空间分布上,不同水库或库区、不同采样站位间,由于水体颗粒物的来源成因不同,其分布规律呈现出明显的差异。(2)从水体颗粒物与环境因子的关联度分析,湖边水库及石兜-坂头水库两个库区的水体颗粒物与总氮和总磷都有较大关联性。(3)利用Pearson积矩相关系数(两尾)进行检验,湖边水库及石兜-坂头水库两个库区的水体颗粒物均与总氮呈显著或极显著相关,与透明度呈显著负相关,与叶绿素a均呈负相关,与其它因子的相关规律性不明显。(4)水体颗粒物与环境因子的逐步回归分析表明,在不同的水库或库区,对水体颗粒物有显著影响的环境因子各不相同,湖边水库是高锰酸盐指数和总氮,石兜库区是高锰酸盐指数、总氮和总磷,坂头库区是pH、溶解氧和总磷。