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Stability of selected volatile breath constituents in Tedlar, Kynar and Flexfilm sampling bags
(2013)
Post-operative isoflurane has been observed to be present in the end-tidal breath of patients who have undergone major surgery, for several weeks after the surgical procedures. A major new noncontrolled, non-randomized, and open-label approved study will recruit patients undergoing various surgeries under different inhalation anaesthetics, with two key objectives, namely to record the washout characteristics following surgery, and to investigate the influence of a patient’s health and the duration and type of surgery on elimination. In preparation for this breath study using proton transfer reaction time-of-flight mass spectrometry (PTR-TOF-MS), it is important to identify first the analytical product ions that need to be monitored and under what operating conditions. In this first paper of this new research programme, we present extensive PTR-TOF-MS studies of three major
anaesthetics used worldwide, desflurane (CF3CHFOCHF2), sevoflurane ((CF3)2CHOCH2F), and isoflurane (CF3CHClOCHF2) and a fourth one, which is used less extensively, enflurane (CHF2OCF2CHFCl), but is of interest because it is an isomer of isoflurane. Product ions are identified as a function of reduced electric field (E/N) over the range of approximately 80 Td to 210 Td, and the effects of operating the drift tube under ‘normal’ or ‘humid’ conditions on the intensities of the product ions are presented. To aid in the analyses, density functional theory (DFT) calculations of the proton affinities and the gas-phase basicities of the anaesthetics have been determined. Calculated energies for the ion-molecule reaction pathways leading to key product ions, identified as ideal for monitoring the inhalation anaesthetics in breath with a high sensitivity and selectivity, are also presented.
With the emergence of the recent Industry 4.0 movement, data integration is now also being driven along the production line, made possible primarily by the use of established concepts of intelligent supply chains, such as the digital avatars. Digital avatars – sometimes also called Digital Twins or more broadly Cyber-Physical Systems (CPS) – are already successfully used in holistic systems for intelligent transport ecosystems, similar to the use of Big Data and artificial intelligence technologies interwoven with modern production and supply chains. The goal of this paper is to describe how data from interwoven, autonomous and intelligent supply chains can be integrated into the diverse data ecosystems of the Industry 4.0, influenced by a multitude of data exchange formats and varied data schemas. In this paper, we describe how a framework for supporting SMEs was established in the Lake Constance region and describe a demonstrator sprung from the framework. The demonstrator project’s goal is to exhibit and compare two different approaches towards optimisation of manufacturing lines. The first approach is based upon static optimisation of production demand, i.e. exact or heuristic algorithms are used to plan and optimise the assignment of orders to individual machines. In the second scenario, we use real-time situational awareness – implemented as digital avatar – to assign local intelligence to jobs and raw materials in order to compare the results to the traditional planning methods of scenario one. The results are generated using event-discrete simulation and are compared to common (heuristic) job scheduling algorithms.
Through mandatory ESG (environmental, social, governance) reporting large companies must disclose their ESG activities showing how sustainability risks are incorporated in their decision-making and production processes. This disclosure obligation, however, does not apply to small and medium-sized enterprises (SME), creating a gap in the ESG dataset. Banks are therefore required to collect sustainability data of their SME customers independently to ensure complete ESG integration in the risk analysis process for loans. In this paper, we examine ESG risk analysis through a smart science approach laying the focus on possible value outcomes of sustainable smart services for banks as well as for their (SME) customers. The paper describes ESG factors, how services can be derived from them, targeted metrics of ESG and an ESG Service Creation Framework (business ecosystem building, process model, and value creation). The description of an exemplary use case highlighting the necessary ecosystem for service creation as well as the created value concludes the paper.
For a given set of banks, how big can losses in bad economic or financial scenarios possibly get, and what are these bad scenarios? These are the two central questions of stress tests for banks and the banking system. Current stress tests select stress scenarios in a way which might leave aside many dangerous scenarios and thus create an illusion of safety; and which might consider highly implausible scenarios and thus trigger a false alarm. We show how to select scenarios systematically for a banking system in a context of multiple credit exposures. We demonstrate the application of our method in an example on the Spanish and Italian residential real estate exposures of European banks. Compared to the EBA 2016 stress test our method produces scenarios which are equally plausible as the EBA stress scenario but yield considerably worse system wide losses.