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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 (Tc), 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, Tc, 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. 相似文献
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J.H. Trienekens P.M. WognumA.J.M. Beulens J.G.A.J. van der Vorst 《Advanced Engineering Informatics》2012,26(1):55-65
Food supply chains are increasingly complex and dynamic due to (i) increasing product proliferation to serve ever diversifying and globalising markets as a form of mass customisation with resulting global flows of raw materials, ingredients and products, and (ii) the need to satisfy changing and variable consumer and governmental demands with respect to food safety, animal welfare, and environmental impact. Transparency in the food supply chain is essential to guarantee food quality and provenance to all users of food and food products. Intensified information exchange and integrated information systems involving all chain actors are needed to achieve transparency with respect to a multitude of food properties.In this paper, specific challenges of food supply chains are highlighted. Major elements are addressed that support transparency to consumers, the government and food companies, which are considered the claimants of transparency. Elements considered to be enablers of transparency are governance mechanisms, quality and safety standards and information exchange. The paper specifies these transparency claimants and enablers for food supply chains and identifies major information system functions and information technology applications needed to comply with transparency demands. It thereby provides a framework for transparency analysis in food supply chains. 相似文献
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Nasir A. Al-geelani M. Afendi M. PiahRedhwan Q. Shaddad 《Applied Soft Computing》2012,12(4):1239-1246
A hybrid model incorporating wavelet and radial basis function neural network is presented which is used to detect, identify and characterize the acoustic signals due to surface discharge activity and hence differentiate abnormal operating conditions from the normal ones. The tests were carried out on cleaned and polluted high voltage glass insulators by using surface tracking and erosion test procedure of international electrotechnical commission 60587. A laboratory experiment was conducted by preparing the prototypes of the discharges. This study suggests a feature extraction and classification algorithm for surface discharge classification, which when combined together reduced the dimensionality of the feature space to a manageable dimension, by “marrying” the wavelet to radial basis function neural network very high levels of classification are achieved. Wavelet signal treatment toolbox is used to recover the surface discharge acoustic signals by eliminating the noisy portion and to reduce the dimension of the feature input vector. A radial basis function neural network classifier was used to classify the surface discharge and assess the suitability of this feature vector in classification. This learning method is proved to be effective by applying the wavelet radial basis function neural network in the classification of surface discharge fault data set. The test results show that the proposed approach is efficient and reliable. 相似文献
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Abhijit Majumdar Puneet Mishra Jürgen Meichsner 《Surface & coatings technology》2007,201(14):6437-6444
Carbon nitride films have been deposited by dielectric barrier discharge with a CH4/N2 gas mixture at different conditions. Fourier Transform Infrared (FTIR) spectroscopy, X-ray photo electron spectroscopy (XPS), Raman spectroscopy, Atomic force microscopy (AFM) and ellipsometry were used to systematically study chemical composition, bond structure and surface morphology of deposited films. Various bonds between carbon, nitrogen, hydrogen, and also oxygen were observed. 相似文献
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《The Electricity Journal》2021,34(3):106917
Legislative requirements in Maryland set very robust goals for the implementation of energy efficiency by utilities. Significant energy savings has been achieved in all customer sectors and efficiency gains have been made over time in equipment and building construction. Looking forward, utilities should implement programs to promote energy efficiency with a greater emphasis on GHG reductions. Feasibility studies need to occur, but flexibility is key given changing codes and standards and market transformation. 相似文献