Comparison of three internationally certified firefighter protective ensembles: Physiological responses,mobility, and comfort

BackgroundFire protective ensembles (FPEs) are essential to safely perform firefighting job tasks; however, they are often burdensome to the workers. The aim of this study was to compare three internationally certified fire protective ensembles from the European Union (EU), South Korea (SK), and United States (US) on physiological responses, mobility, and comfort.MethodsTen male professional firefighters performed a battery of exercises in the laboratory following the ASTM F3031-17 standard to evaluate mobility, occupation-specific performance, and physiological responses (body weight, heart rate (HR), core temperature (T_c), breathing rate (BR), and rating of perceived exertion (RPE)) to 20 min of treadmill walking (3.2 mph, 5% incline). All participants carried out the evaluation wearing each FPE in a random order. Mixed effects models examined time (pre-vs. post-) by ensemble (EU, SK, US) interactions for all physiological variables and compared comfort, performance, and subjective variables across ensembles.ResultsNo interaction effects were observed for body weight, HR, T_c, BR, or RPE (p = 0.890, p = 0.994, p = 0.897, p = 0.435, and p = 0.221; respectively). SK had greater trunk flexion than EU (78.4° vs. 74.6°, p = 0.026) and US had lower standing reach than EU (105.5 cm vs. 115.4 cm, p = 0.004). Agility circuit time was lower in US (9.3 s) compared to EU (9.8 s) or SK (9.9 s) (p = 0.051 and p = 0.019, respectively).ConclusionsThe findings suggest that physiological burden remained largely unchanged across the international FPEs. However, mobility, performance, and comfort may be significantly influenced across types. International stakeholders and end users should consider design implications when choosing fire protective ensembles.     

Investigation of oil palm harvesting tools design and technique on work-related musculoskeletal disorders of the upper body

The oil palm industry is one of the important sectors in Malaysia. The growth and development of this industry shows that Malaysia is the world second-largest oil palm producers. However, in the fresh fruit bunch (FFB) harvesting process, the harvesters are exposed to many types of work-related musculoskeletal disorders (WMSDs). The FFB harvesters tend to develop WMSDs especially the shoulders and trunk. Hence, it is important to identify the exposure levels, awkward postures and the reaction forces of muscle activity based on the posture and movement of the harvesters when using pole, chisel and loading spike during the harvesting process. The objective of this study was to investigate the effect of the design of oil palm FFB harvesting tools on WMSDs of the upper body. Rapid Upper Limb Analysis (RULA) was used to investigate and assess the exposure level on the harvester body during the harvesting process. The assessment showed that the shoulders and trunk have high exposure level and undergo awkward posture. Human Musculoskeletal Model Analysis (HMMA) was used to identify the reaction force exerted on the muscle during the FFB harvesting process. In this study, 4 muscles were analysed including Triceps, Biceps, Erector Spinae and Psoas Major. The highest reaction force of 16.36 N was found on the left triceps when handling a loading spike. In conclusion, it is important to address the risks by reviewing all possible aspects that contribute to the WMSDs and interventions on the tool design, task and working shifts may be required.     

Short-term load forecasting using bayesian neural networks learned by Hybrid Monte Carlo algorithm

This paper presents a short term load forecasting model based on Bayesian neural network (shorted as BNN) learned by the Hybrid Monte Carlo (shorted as HMC) algorithm. The weight vector parameter of the Bayesian neural network is a multi-dimensional random variable. In learning process, the Bayesian neural network is considered as a special Hamiltonian dynamical system, and the weights vector as the system position variable. The HMC algorithm is used to learn the weight vector parameter with respect to Normal prior distribution and Cauchy prior distribution, respectively. The Bayesian neural networks learned by Laplace algorithm and HMC algorithm and the artificial neural network (ANN) learned by the BP algorithm were used to forecast the hourly load of 25 days of April (Spring), August (Summer), October (Autumn) and January (Winter), respectively. The roots mean squared error (RMSE) and the mean absolute percent errors (MAPE) were used to measured the forecasting performance. The experimental result shows that the BNNs learned by HMC algorithm have far better performance than the BNN learned by Laplace algorithm and the neural network learned BP algorithm and the BNN learned by HMC has powerful generalizing capability, it can welly solve the overfitting problem.     

基于非参数乘法回归模型的农业景观步甲空间分布模拟

农业生产引起的景观变化是导致生物多样性丧失的重要原因,为评估农业景观结构变化对物种多样性的影响,探索农业景观物种空间模拟的方法,研究应用非参数乘法回归(NPMR)模型结合田间步甲取样数据,分析了步甲群落多样性、主要物种存在/不存在与取样点周围边长为200 m景观内景观结构之间的关系,建立研究区物种-景观分布预测模型,结合地理信息系统(GIS)技术建立研究区群落/物种空间分布预测图。结果表明:在群落水平上,景观结构对步甲群落多样性的影响不显著; 在物种水平上,黄斑青步甲(Chlaenius micans)、淡鞘婪步甲(Harpalus pallidipennis)受斑块密度的影响显著(p<0.05),黄斑青步甲、后斑青步甲(Chlaenius posticalis)和单齿婪步甲(Harpalus simplicide)受半自然生境类型数的影响显著(p<0.05),单齿蝼步甲(Scarites terricola)受半自然生境比例的影响显著(p<0.05),而蠋步甲(Dolichus halensis)受景观结构的影响较为复杂。通过模型预测,输出研究区域6个主要物种的空间分布模拟图,进一步分析发现在研究区域内,对景观结构较为敏感的6个步甲物种主要分布在农田与半自然生境相接的狭长地带。因此,利用非参数乘法回归模型可以很好地模拟步甲物种对农田景观结构的响应及其在景观中的空间分布变化。200 m×200 m尺度下,尽管步甲群落多样性不受景观结构的显著影响,但是存在部分步甲物种对景观结构响应显著,但不同物种对景观结构的响应不同。增加农田地块间半自然生境,并合理改善景观配置异质性将有利于对景观结构变化敏感步甲物种的维持。     

Dissolved and emitted methane in the Poyang Lake

Science China Technological Sciences - Lake waters often act as important methane sources for global greenhouse gas emission, but it would be more complex as lakes are regulated by rivers. In this...     

Nickel-Carnosine complex:A new carrier for enzymes immobilization by affinity adsorption

Immobilization is an effective method to promote the application of enzyme industry for improving the stability and realizing recovery of enzyme.To some extent,the performance of immobilized enzyme depends on the choice of carrier material.Therefore,the development of new carrier materials has been one of the key issues concerned by enzyme immobilization researchers.In this work,a novel organic-inorganic hybrid material,nickel-carnosine complex (NiCar),was synthesized for the first time by solvothermal method.The obtained NiCar exhibits spherical morphology,hierarchical porosity and abun-dant unsaturated coordination nickel ions,which provide excellent anchoring sites for the immobiliza-tion of proteins.His-tagged organophosphate-degrading enzyme (OpdA) and ω-transaminase (ω-TA)were used as model enzymes to evaluate the performance of NiCar as a carrier.By a simple adsorption process,the enzyme molecules can be fixed on the particles of NiCar,and the stability and reusability are significantly improved.The analysis of protein adsorption on NiCar verified that the affinity adsorp-tion between the imidazole functional group on the protein and the unsaturated coordination nickel ions on NiCar was the main force in the immobilization process,which provided an idea way for the develop-ment of new enzyme immobilization carriers.     

抗生素菌渣水热催化产油及其特性

探究了菌渣的水热液化转换成生物油燃料的过程。结果表明,抗生素菌渣在260 ℃、保留时间是135 min时,获得最大的生物油产率（28.01%）。通过6种不同的催化剂进行催化,加入催化剂后,生物油产率最大的是Na₂CO₃（36.06%）和NaOH（36.31%）。碱催化的生物油的含氮化合物的质量分数在41.16%～49.74%之间,而酸催化产生的生物油含氮化合物的量在57.62%～59.32%之间。通过调节催化剂Na₂CO₃、NaOH的添加量发现,在投加量为8%时,生物油含氮量均最低,Na₂CO₃和NaOH催化产生的生物油组分的含氮化合物质量分数分别为29.12%和35.67%。在催化剂投加量为10%时,对氧的脱除效果都最好,分别为32.12%和29.02%,此时产生的生物油的热值达到最大（达到33.3220和34.7320 MJ?kg?1）。      

“十三五”期间我国铅锌硫化矿选矿技术进展

“十三五”期间,为实现我国铅锌硫化矿的高效选别、选矿过程的节能降耗、废水废渣的循环利用,我国选矿工作者进行了大量研究工作,并取得了较大的进展。本文通过梳理“十三五”期间我国铅锌硫化矿选矿新技术进展,系统地论述了铅锌硫化矿的高效选别技术、清洁选矿技术和节能降耗技术等。相关新技术的应用,解决了我国铅锌矿产资源主金属回收率与伴生资源综合利用率低、选矿成本与设备能耗高、选矿废水治理与回用困难等问题,全面提高了我国铅锌硫化矿资源的开发利用水平,具有良好的应用推广价值。      

镧负载D201树脂同步脱硝除磷的性能对比

采用La3+、La（OH）₃以及La₂（CO₃）₃对D201树脂进行改性,并从吸附动力学、等温线、共存离子影响以及再生等方面系统地对比3种La负载树脂的同步脱硝除磷性能。扫描电镜及成分分析结果表明,D201表面能够负载不同形态的La,以La₂（CO₃）₃形态负载时La含量最高。吸附数据表明,La₂（CO₃）₃型D201树脂除磷效果优越,吸附容量高且受干扰离子影响小。经Na₂CO₃溶液再生5次后,各树脂均能保持良好的再生吸附效果,同步脱硝除磷性能稳定。树脂中季铵官能团（-R₄N+）对硝酸根选择性较高,使得硝氮吸附受共存离子的影响较弱;磷酸根吸附归因于与-R₄N+静电作用及与负载的各形态La形成沉淀、发生配体交换等,受体系pH值变化较为敏感,弱碱性条件可促进吸附。      

面向钢铁烧结烟气NOx吸附净化的吸附剂特性

吸附法是有望同时实现烟气NO_x超低排放深度净化与资源化的关键技术,高效NO_x吸附剂是其核心关键,然而目前针对满足应用需求的NO_x吸附剂仍缺乏系统认识。本文基于烟气NO_x净化效率及材料热稳定性实际需求,分析挑选了沸石、金属氧化物、硅铝胶等代表性吸附剂,研究了NO_x在各吸附剂上的吸附穿透、吸附量、程序升温脱附等关键特性,结合吸附剂孔道特性对比发现,中低硅H-ZSM-5沸石兼具较高NO_x净化深度、NO_x吸附量、较低脱附温度且可获得更易于资源化的NO_x解吸气,因而可作为优选NO_x吸附剂。进一步地,随着吸附温度升高,硅铝比(w(SiO₂)/w(Al₂O₃) )为25、38的H-ZSM-5的NO_x吸附量均降低,其中低硅H-ZSM-5的NO_x吸附量较高,但吸附传质系数较低。本文可为烟气NO_x吸附净化的效益环保技术提供指导。