Cervical musculoskeletal disorders and their relationships with personal and work-related factors among electronic assembly workers

IntroductionElectronics assembly workers are reported to have a high prevalence of musculoskeletal disorders (MSDs). This study investigated the prevalence of cervical MSDs and the complex relationships between cervical MSDs and individual, physical, psychosocial factors among electronics assembly workers. Methods: In this cross-sectional survey, self-administered questionnaires from 700 workers in electronics manufacturing workshops were analysed. Information concerning musculoskeletal symptoms, personal and work-related factors was collected. Finally, the prevalence of cervical MSDs was computed for different subgroups, and the relationships with different factors were analyzed using logistic regression and structural equation modeling (SEM). Results: The total 12 month prevalence of cervical MSDs among the survey population was 29.4%. Variables of gender, job tenure, twisting head frequently, neck flexion/extension for long time and work required to be done quickly showed significant associations with MSDs in a multivariate logistic regression (P < 0.05). The SEM analysis showed moderate and significant correlations between postural load (γ = 0.279), gender (γ = 0.233) and cervical MSDs, while there were weak but significant correlations between vibration (γ = 0.024), work stress (γ = 0.126), job tenure (γ = 0.024) and cervical MSDs. Both work stress and vibration affected the MSDs indirectly through postural load. Conclusions: The logistic regression results support previous general epidemiological MSD studies, and indicates that individual, physical, and psychosocial factors are related to cervical MSDs. The SEM provides a better approximation of the complexity of the relationship between risk factors and cervical MSDs. Improving awkward postures may be effective ways to control the influence of occupational stressors or vibration on MSDs. Practical Applications: The study is to improve prevention of MSDs among electronics assembly workers and promote their occupational health.     

细尾矿砂非饱和渗流稳态含水率二维解析解

为准确描述非饱和细尾矿砂内部含水率的空间分布规律,采用解析方法求解了非饱和尾矿砂的二维Richards方程,探讨了解析求解过程中方程和求解区域简化的思路,介绍了非饱和细尾矿砂含水率空间分布的实验结果,采用混沌粒子群优化算法计算了求解过程中引入的常数。研究结果表明:解析解具有无穷级数的形式,且级数的系数具有很好的收敛性,非饱和细尾矿砂含水率在水平和竖直方向上的分布均近似服从指数函数,混沌粒子群优化算法的误差收敛性明显,利用解析模型得到的各点含水率计算值与实验测量值均符合的比较好。所得解析公式能够很好地描述非饱和细尾矿砂内部含水率的空间分布规律。     

Environmental management in Brazil: is it a completely competitive priority?

Current studies indicate a need to integrate environmental management with manufacturing strategy, including topics like cross-functional integration, environmental impact, and waste reduction. Nevertheless, such studies are relatively rare, existing still a need for research in specific regional contexts. At the same time, the results found are not unanimous. Due to these gaps, the objective of this article is to analyze if environmental management can be considered a new competitive priority for manufacturing enterprises located in Brazil. A cross-sectional survey was conducted with Brazilian companies certified by ISO 14001. Sixty-five valid questionnaires were analyzed through Structural Equation Modelling (SEM). The first conclusion is that environmental management presents a preventive approach in the sample analyzed, focused on eco-efficiency, what potentially do not to create a competitive advantage. This preventive approach inhibits environmental management from being regarded as a new competitive manufacturing priority, in the full sense as defined by the literature. Another important result is that environmental management, although following a preventive focus, may influence positively the four manufacturing priorities: cost, quality, flexibility and delivery.     

基于结构方程模型的认知性VDT作业过程解析*

为实现通过过程控制和管理提高认知性视觉显示终端（VDT）作业人员可靠性和绩效的目标,应用结构方程模型（SEM）研究作业过程表征方法。构建认知性VDT作业的信息加工过程模型,抽取13个基本认知动素（CT）,提出CT概念结构模型假设,设计外显指标测试题项,运用问卷调查样本数据构建结构方程和测量方程;对测量数据与结构方程模型的拟合度进行分析,并训练BP神经网络模式识别模型对作业过程进行还原检验。结果表明:认知性VDT作业过程模型有效,元认知控制其他12个CT的结构关系成立,认知性VDT作业过程可由包括元认知在内的13个基本CT解析。     

Evaluating safety-influencing factors at stop-controlled intersections using automated video analysis

Introduction: Although stop signs are popular in North America, they have become controversial in cities like Montreal, Canada where they are often installed to reduce vehicular speeds and improve pedestrian safety despite limited evidence demonstrating their effectiveness. The purpose of this study is to evaluate the impact of stop-control configuration (and other features) on safety using statistical models and surrogate measures of safety (SMoS), namely vehicle speed, time-to-collision (TTC), and post-encroachment time (PET), while controlling for features of traffic, geometry, and built environment. Methods: This project leverages high-resolution user trajectories extracted from video data collected for 100 intersections, 336 approaches, and 130,000 road users in Montreal to develop linear mixed-effects regression models to account for within-site and within-approach correlations. This research proposes the Intersection Exposure Group (IEG) indicator, an original method for classifying microscopic exposure of pedestrians and vehicles. Results: Stop signs were associated with an average decrease in approach speed of 17.2 km/h and 20.1 km/h, at partially and fully stop-controlled respectively. Cyclist or pedestrian presence also significantly lower vehicle speeds. The proposed IEG measure was shown to successfully distinguish various types of pedestrian-vehicle interactions, allowing for the effect of each interaction type to vary in the model. Conclusions: The presence of stop signs significantly reduced approach speeds compared to uncontrolled approaches. Though several covariates were significantly related to TTC and PET for vehicle pairs, the models were unable to demonstrate a significant relationship between stop signs and vehicle–pedestrian interactions. Therefore, drawing conclusions regarding pedestrian safety is difficult. Practical Applications: As pedestrian safety is frequently used to justify new stop sign installations, this result has important policy implications. Policies implementing stop signs to reduce pedestrian crashes may be less effective than other interventions. Enforcement and education efforts, along with geometric design considerations, should accompany any changes in traffic control.     

How to evaluate models: Observed vs. predicted or predicted vs. observed?

A common and simple approach to evaluate models is to regress predicted vs. observed values (or vice versa) and compare slope and intercept parameters against the 1:1 line. However, based on a review of the literature it seems to be no consensus on which variable (predicted or observed) should be placed in each axis. Although some researchers think that it is identical, probably because r² is the same for both regressions, the intercept and the slope of each regression differ and, in turn, may change the result of the model evaluation. We present mathematical evidence showing that the regression of predicted (in the y-axis) vs. observed data (in the x-axis) (PO) to evaluate models is incorrect and should lead to an erroneous estimate of the slope and intercept. In other words, a spurious effect is added to the regression parameters when regressing PO values and comparing them against the 1:1 line. Observed (in the y-axis) vs. predicted (in the x-axis) (OP) regressions should be used instead. We also show in an example from the literature that both approaches produce significantly different results that may change the conclusions of the model evaluation.     

Identifying Biotic Integrity and Water Chemistry Relations in Nonwadeable Rivers of Wisconsin: Toward the Development of Nutrient Criteria

We sampled 41 sites on 34 nonwadeable rivers that represent the types of rivers in Wisconsin, and the kinds and intensities of nutrient and other anthropogenic stressors upon each river type. Sites covered much of United States Environmental Protection Agency national nutrient ecoregions VII—Mostly Glaciated Dairy Region, and VIII—Nutrient Poor, Largely Glaciated upper Midwest. Fish, macroinvertebrates, and three categories of environmental variables including nutrients, other water chemistry, and watershed features were collected using standard protocols. We summarized fish assemblages by index of biotic integrity (IBI) and its 10 component measures, and macroinvertebrates by 2 organic pollution tolerance and 12 proportional richness measures. All biotic and environmental variables represented a wide range of conditions, with biotic measures ranging from poor to excellent status, despite nutrient concentrations being consistently higher than reference concentrations reported for the regions. Regression tree analyses of nutrients on a suite of biotic measures identified breakpoints in total phosphorus (~0.06 mg/l) and total nitrogen (~0.64 mg/l) concentrations at which biotic assemblages were consistently impaired. Redundancy analyses (RDA) were used to identify the most important variables within each of the three environmental variable categories, which were then used to determine the relative influence of each variable category on the biota. Nutrient measures, suspended chlorophyll a, water clarity, and watershed land cover type (forest or row-crop agriculture) were the most important variables and they explained significant amounts of variation within the macroinvertebrate (R ² = 60.6%) and fish (R ² = 43.6%) assemblages. The environmental variables selected in the macroinvertebrate model were correlated to such an extent that partial RDA analyses could not attribute variation explained to individual environmental categories, assigning 89% of the explained variation to interactions among the categories. In contrast, partial RDA attributed much of the explained variation to the nutrient (25%) and other water chemistry (38%) categories for the fish model. Our analyses suggest that it would be beneficial to develop criteria based upon a suite of biotic and nutrient variables simultaneously to deem waters as not meeting their designated uses.     

中小城市居民垃圾分类行为影响因素——以张家港市为例

为识别中小城市居民分类行为的影响因素和决策机制,本文构建了中小城市居民垃圾分类行为决策模型,并以江苏省张家港市为例,运用结构方程拟合与修正,分析了主客观因素对居民分类行为的影响,并与大城市相关研究进行了比较.结果表明：张家港市垃圾分类参与率达95%,高于一、二线大城市.对于张家港市居民而言,“行为意愿”是影响其分类行为最显著的因素,其次是“环保意识”和“社会影响”;“经济回报”和“法规影响”的显著性较低,尚未发挥应有的激励作用;“分类知识掌握程度”和“时间花费”的影响不显著.总体来看,主观意识（敏感性系数：0.629）仍是影响中小城市居民分类行为的主导因素,但在强制垃圾分类背景下,随着分类设施的建设完善、法律法规的颁布和社区管制加强,其影响作用趋于减弱,而客观环境对应的显著观测变量更多,对居民分类行为的影响逐渐增强,将是政府制定管理政策的有效发力点.     

泥石流浆体屈服应力综合表达式的研究

根据野外泥石流浆体观测试验分析,通过对不同料径沙颗粒的甘油沙浆流变试验,以及动摩擦临界浓度和极限浓度的实验研究,导出了反映泥石流浆体结构强度的屈服应力综合表达式,以便为泥石流高浓度,高速机理探讨和泥石流防治工作的设计提供科学依据的参数。     

高梯度磁分离的过滤性能计算

文章分析了高梯度磁分离器的粒子捕获机理给出了性能计算方法。首先从ＨＧＭＳ的单线模型出发，导出表征ＨＧＭＳ性能的基本量磁速Ｖｍ，然后求出捕获半径ＲＣＯ，得出一系列磁性粒子的轨迹曲线，并且考虑了在ＨＧＭＳ工作状态时的粒子保持情况；再由物质平衡原理得出物质平衡方程。由分析ＨＧＭＳ的捕获几率得出速率方程，运用四阶龙格库塔法对磁分离方程进行数值解，求出穿透曲线；最后通过实验，与推导的结果作了比较。对运用高梯度磁分离器设计废水废气处理设备具有实际意义。