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Thierry Meyer - One of the best experts on this subject based on the ideXlab platform.

  • Engineered nanomaterials: toward effective safety management in Research Laboratories
    Journal of Nanobiotechnology, 2016
    Co-Authors: Amela Groso, Alke Petri-fink, Barbara Rothen-rutishauser, Heath Hofmann, Thierry Meyer
    Abstract:

    BackgroundIt is still unknown which types of nanomaterials and associated doses represent an actual danger to humans and environment. Meanwhile, there is consensus on applying the precautionary principle to these novel materials until more information is available. To deal with the rapid evolution of Research, including the fast turnover of collaborators, a user-friendly and easy-to-apply risk assessment tool offering adequate preventive and protective measures has to be provided.ResultsBased on new information concerning the hazards of engineered nanomaterials, we improved a previously developed risk assessment tool by following a simple scheme to gain in efficiency. In the first step, using a logical decision tree, one of the three hazard levels, from H1 to H3, is assigned to the nanomaterial. Using a combination of decision trees and matrices, the second step links the hazard with the emission and exposure potential to assign one of the three nanorisk levels (Nano 3 highest risk; Nano 1 lowest risk) to the activity. These operations are repeated at each process step, leading to the laboratory classification. The third step provides detailed preventive and protective measures for the determined level of nanorisk.ConclusionsWe developed an adapted simple and intuitive method for nanomaterial risk management in Research Laboratories. It allows classifying the nanoactivities into three levels, additionally proposing concrete preventive and protective measures and associated actions. This method is a valuable tool for all the participants in nanomaterial safety. The users experience an essential learning opportunity and increase their safety awareness. Laboratory managers have a reliable tool to obtain an overview of the operations involving nanomaterials in their Laboratories; this is essential, as they are responsible for the employee safety, but are sometimes unaware of the works performed. Bringing this risk to a three-band scale (like other types of risks such as biological, radiation, chemical, etc.) facilitates the management for occupational health and safety specialists. Institutes and school managers can obtain the necessary information to implement an adequate safety management system. Having an easy-to-use tool enables a dialog between all these partners, whose semantic and priorities in terms of safety are often different.

Richard Harper - One of the best experts on this subject based on the ideXlab platform.

  • looking at ourselves an examination of the social organisation of two Research Laboratories
    Conference on Computer Supported Cooperative Work, 1992
    Co-Authors: Richard Harper
    Abstract:

    This paper reports findings from ongoing examinations into the social organization of Research Laboratories. Two case studies are discussed, and it is suggested that although there are differences between the two sites, commonalities are shown in their hierarchical nature and in the status of Researchers. It is argued that Researchers form a professional group with all that entails in terms of rights and privileges. More generally it is argued that the social organization of Research Laboratories is resistant to change. The consequences of this on the testing and development of systems that have the potential to transform hierarchical relations is briefly discussed and how this resistance and its causes differentiate Research Laboratories from other work places remarked.

  • CSCW - Looking at ourselves: an examination of the social organisation of two Research Laboratories
    Proceedings of the 1992 ACM conference on Computer-supported cooperative work - CSCW '92, 1992
    Co-Authors: Richard Harper
    Abstract:

    This paper reports findings from ongoing examinations into the social organization of Research Laboratories. Two case studies are discussed, and it is suggested that although there are differences between the two sites, commonalities are shown in their hierarchical nature and in the status of Researchers. It is argued that Researchers form a professional group with all that entails in terms of rights and privileges. More generally it is argued that the social organization of Research Laboratories is resistant to change. The consequences of this on the testing and development of systems that have the potential to transform hierarchical relations is briefly discussed and how this resistance and its causes differentiate Research Laboratories from other work places remarked.

Nancy J. Nersessian - One of the best experts on this subject based on the ideXlab platform.

  • How do engineering scientists think? Model-based simulation in biomedical engineering Research Laboratories
    Topics in Cognitive Science, 2009
    Co-Authors: Nancy J. Nersessian
    Abstract:

    Designing, building, and experimenting with physical simulation models are central problem-solving practices in the engineering sciences. Model-based simulation is an epistemic activity that includes exploration, generation and testing of hypotheses, explanation, and inference. This paper argues that to interpret and understand how these simulation models function in creating knowledge and technologies requires construing problem solving as accomplished by a Researcherartifact system. It draws on and further develops the framework of distributed cognition to interpret data collected in ethnographic and cognitive-historical studies of two biomedical engineering Research Laboratories, and articulates the notion of distributed model-based cognition to answer the question posed in the title.

  • Research Laboratories as evolving distributed cognitive systems
    Proceedings of the Annual Meeting of the Cognitive Science Society, 2003
    Co-Authors: Nancy J. Nersessian, Elke Kurzmilcke, Wendy C Newstetter, Jim Davies
    Abstract:

    We are carrying out a Research project aimed at understanding reasoning and representational practices employed in problem solving in biomedical engineering (BME) Laboratories. These Laboratories are best construed as evolving distributed cognitive systems: the laboratory is not simply a physical space, but a problem space, the components of which change over time; cognition is distributed among people and artifacts; and the cognitive partnerships between the technological artifacts and the Researchers in the system evolve. To investigate this evolving cognitive system we use both ethnography and cognitive-historical analysis. Understanding practices in innovative Research Laboratories requires in-depth observation of the lab as it presently exists, as well as Research into the histories of the experimental devices used in it. We are aiming here for relational accounts (‘biographies’) of the distributed cognitive systems within the lab as they change in time. In this we find that one cannot divorce Research from learning in the context of the laboratory, where learning involves building relationships with artifacts.

Amela Groso - One of the best experts on this subject based on the ideXlab platform.

  • Engineered nanomaterials: toward effective safety management in Research Laboratories
    Journal of Nanobiotechnology, 2016
    Co-Authors: Amela Groso, Alke Petri-fink, Barbara Rothen-rutishauser, Heath Hofmann, Thierry Meyer
    Abstract:

    BackgroundIt is still unknown which types of nanomaterials and associated doses represent an actual danger to humans and environment. Meanwhile, there is consensus on applying the precautionary principle to these novel materials until more information is available. To deal with the rapid evolution of Research, including the fast turnover of collaborators, a user-friendly and easy-to-apply risk assessment tool offering adequate preventive and protective measures has to be provided.ResultsBased on new information concerning the hazards of engineered nanomaterials, we improved a previously developed risk assessment tool by following a simple scheme to gain in efficiency. In the first step, using a logical decision tree, one of the three hazard levels, from H1 to H3, is assigned to the nanomaterial. Using a combination of decision trees and matrices, the second step links the hazard with the emission and exposure potential to assign one of the three nanorisk levels (Nano 3 highest risk; Nano 1 lowest risk) to the activity. These operations are repeated at each process step, leading to the laboratory classification. The third step provides detailed preventive and protective measures for the determined level of nanorisk.ConclusionsWe developed an adapted simple and intuitive method for nanomaterial risk management in Research Laboratories. It allows classifying the nanoactivities into three levels, additionally proposing concrete preventive and protective measures and associated actions. This method is a valuable tool for all the participants in nanomaterial safety. The users experience an essential learning opportunity and increase their safety awareness. Laboratory managers have a reliable tool to obtain an overview of the operations involving nanomaterials in their Laboratories; this is essential, as they are responsible for the employee safety, but are sometimes unaware of the works performed. Bringing this risk to a three-band scale (like other types of risks such as biological, radiation, chemical, etc.) facilitates the management for occupational health and safety specialists. Institutes and school managers can obtain the necessary information to implement an adequate safety management system. Having an easy-to-use tool enables a dialog between all these partners, whose semantic and priorities in terms of safety are often different.

Stephen J. Appold - One of the best experts on this subject based on the ideXlab platform.

  • Research parks and the location of industrial Research Laboratories an analysis of the effectiveness of a policy intervention
    Research Policy, 2004
    Co-Authors: Stephen J. Appold
    Abstract:

    Utilizing county-level data, this paper predicts the growth in the number of private industrial Research Laboratories between 1960 and 1985. This was a period of rapid growth and spatial reorganization in industrial Research activity. A multi-equation model which allows the influence of unmeasured factors and selectivity to be taken into account is used to test the ability of a policy intervention, Research parks, to affect the growth in the number of local Laboratories. Although the presence of Research parks is correlated with the number of Laboratories, the analysis indicates that Research parks were not effective local development tools but instead benefitted from the growth of Research activity. © 2003 Elsevier B.V. All rights reserved.

  • The location processes of industrial Research Laboratories
    The Annals of Regional Science, 1991
    Co-Authors: Stephen J. Appold
    Abstract:

    This paper examines the location of industrial Research Laboratories in order to make inferences about the location decision process. Utilizing data gathered fromIndustrial Research Laboratories of the United States, the analysis of spatial point patterns reveals that labs are clustered within roughly equivalent local environments leading to the conclusion that labs are imitating each other. The hypothesis is that uncertainty about environmental hospitality leads to the observed clustering behavior resulting in location patterns that do not reflect actual constraints or preferences.