Airborne Exposures to Monoethanolamine, Glycol Ethers, and Benzyl Alcohol During Professional Cleaning: A Pilot Study

A growing body of epidemiologic evidence suggests an association between exposure to cleaning products and respiratory dysfunction. Due to the lack of quantitative assessments of respiratory exposures to airborne irritants and sensitizers among professional cleaners, the culpable substances have yet to be identified. Purpose: Focusing on previously identified irritants, our aims were to determine (i) airborne concentrations of monoethanolamine (MEA), glycol ethers, and benzyl alcohol (BA) during different cleaning tasks performed by professional cleaning workers and assess their determinants; and (ii) air concentrations of formaldehyde, a known indoor air contaminant. Methods: Personal air samples were collected in 12 cleaning companies, and analyzed by conventional methods. Results: Nearly all air concentrations [MEA (n = 68), glycol ethers (n = 79), BA (n = 15), and formaldehyde (n = 45)] were far below (<1/10) of the corresponding Swiss occupational exposure limits (OEL), except for ethylene glycol mono-n-butyl ether (EGBE). For butoxypropanol and BA, no OELs exist. Although only detected once, EGBE air concentrations (n = 4) were high (49.48-58.72mg m−3), and close to the Swiss OEL (49mg m−3). When substances were not noted as present in safety data sheets of cleaning products used but were measured, air concentrations showed no presence of MEA, while the glycol ethers were often present, and formaldehyde was universally detected. Exposure to MEA was affected by its amount used (P = 0.036), and spraying (P = 0.000) and exposure to butoxypropanol was affected by spraying (P = 0.007) and cross-ventilation (P = 0.000). Conclusions: Professional cleaners were found to be exposed to multiple airborne irritants at low concentrations, thus these substances should be considered in investigations of respiratory dysfunctions in the cleaning industry; especially in specialized cleaning tasks such as intensive floor cleanin

DETC2011/MESA-47286 CRONE CONTROL-SYSTEM DESIGN TOOLBOX FOR THE CONTROL ENGINEERING COMMUNITY

ABSTRACT The CRONE CSD methodology proposes to design robust controllers by using fractional order operators. A Matlab toolbox has been developed based on this methodology and is freely available for the international scientific and industrial communities. This paper presents both the methodology and the toolbox. The design of two robust controllers for irrigation canals show how the toolbox can be used. INTRODUCTION The CRONE Toolbox, developed gradually since the ninetie

CONCEPTION D’UNE COQUE EN BÉTON TEXTILE

Le béton textile est un nouveau matériau à haute performance composé d’une matrice cimentaire et d’une armature en fibres synthétique. L’état des connaissances est encore trop peu avancé pour une utilisation à grande échelle mais les nouvelles opportunités offertes par ce matériau sont telles qu’il est nécessaire de les compléter. Le béton textile offre d’une part de nouvelles possibilités architecturales grâce à sa flexibilité et sa finesse et d’autre part pourrait aider à diminuer l’empreinte écologique du domaine de la construction en utilisant moins de ciment et en construisant des structures plus durables. Dans ce projet, on veut à la fois mettre en valeur le matériau et tester ses limites en construisant un abri soumis à des charges importantes et ayant une forme telle que seul le béton textile soit intéressant pour la réaliser. On en profitera pour explorer différentes méthodes de construction en béton textile en faisant varier le mortier et les techniques de coffrage. Dans un premier temps, on conçoit la forme et les dimensions principales puis on construit la coque avant de la tester. En parallèle, on réalise des tests pour caractériser les matériaux utilisés et à partir de ces résultats on construit un modèle éléments finis ainsi qu’un modèle de résistance à la flexion composée. Sur la base de ces deux modèles, on vérifie le dimensionnement de la structure effectué et conçoit un agrandissement de la coque en multipliant sa taille par trois

Évitement d'obstacle dans un environnement 3D dynamique

International audienc

Fractional modeling of wind speed turbulence

This paper proposes a method to design a wind turbulence model based on real wind spectral characteristics. It uses models based on Cole-Cole fractional functions to approximate the wind turbulence power spectral density. Von Kármán model is the most commonly used model but originally designed for aircraft in high altitude. Therefore, it is not suitable for systems operating at low altitude, hence the need for more accurate models in these specific conditions. Shaping filters issued from the fractional models are employed to generate realistic random wind speed turbulence from a random white noise input. Then, a grey box model is proposed from physical parameters such as the classic von Kármán ones (mean speed, turbulence intensity and length scale)

Truncation of fractional derivative for online system identification

Fractional derivatives are non local operators that has compacity property in terms of parameter number for modeling diffusive phenomenon with very few parameters. One of its main properties is its non-local behavior, as it can be exploited to model long-memory phenomena such as heat transfers. However, such non-locality implies a constant knowledge of the full past of the function to be differentiated. In the context of real-time system identification, this may limit the experiences as calculations become slower as time progresses. This study deals with the relationship between frequency content of a signal and its truncation error in order to obtain real-time exploitable algorithms

Long-memory recursive prediction error method for identification of continuous-time fractional models

This paper deals with recursive continuous-time system identification using fractional-order models. Long-memory recursive prediction error method is proposed for recursive estimation of all parameters of fractional-order models. When differentiation orders are assumed known, least squares and prediction error methods, being direct extensions to fractional-order models of the classic methods used for integer-order models, are compared to our new method, the long-memory recursive prediction error method. Given the long-memory property of fractional models, Monte Carlo simulations prove the efficiency of our proposed algorithm. Then, when the differentiation orders are unknown, two-stage algorithms are necessary for both parameter and differentiation-order estimation. The performances of the new proposed recursive algorithm are studied through Monte Carlo simulations. Finally, the proposed algorithm is validated on a biological example where heat transfers in lungs are modeled by using thermal two-port network formalism with fractional models

Modeling thermal systems with fractional models: human bronchus application

System thermal modeling allows heat and temperature simulations for many applications, such as refrigeration design, heat dissipation in power electronics, melting processes and bio-heat transfers. Sufficiently accurate models are especially needed in open-heart surgery where lung thermal modeling will prevent pulmonary cell dying. For simplicity purposes, simple RC circuits are often used, but such models are too simple and lack of precision in dynamical terms. A more complete description of conductive heat transfer can be obtained from the heat equation by means of a two-port network. The analytical expressions obtained from such circuit models are complex and nonlinear in the frequency ω. This complexity in Laplace domain is difficult to handle when it comes to control applications and more specifically during surgery, as heat transfer and temperature control of a tissue may help in reducing necrosis and preserving a greater amount of a given organ. Therefore, a frequency-domain analysis of the series and shunt impedances will be presented and different techniques of approximations will be explored in order to obtain simple but sufficiently precise linear fractional transfer function models. Several approximations are proposed to model heat transfers of a human middle bronchus and will be quantified by the absolute errors

DETC2005-84864 FRACTIONAL MODEL OF A GASTROCNEMIUS MUSCLE FOR TETANUS PATTERN

ABSTRACT This study talks about gastrocnemius muscle identification. During biological activation, every contractile structure is unsynchronized. Likewise, contraction and relaxation phases depend on all contractile elements, the activation type and the state of health. Moreover, gastrocnemius muscle is composed of three fibre types: Fast Fatigable (FF), Fast Resistant (FR) and Slow (S) fibres. Some recent works highlight a fractal structure of the muscle, which consolidate the approach based on the use of a non integer (or fractal) model to characterize its dynamic behavior. A fractional structure model, due to its infinite dimension nature, is particularly adapted to model complex systems with few parameters and to obtain a real time exploitable model. According to its complexity, muscle structure and activation mechanisms, and to these previous considerations, an identification based on fractional model is presented. A model is proposed for the tetanus pattern response in a high tiredness state. It is based on a multi-model structure, which corresponds to the decomposition in contraction and relaxation phases. This multi-model structure is expected to be included subsequently in agonist-antagonist structure