Development of an airline revenue capability model for aircraft design

Typically value based approaches to the design of civil and commercial aircraft, be they net present value, surplus value, or any other utility based approach focus solely on the difference in cost between the alternatives, neglecting changes in revenue which might occur between the two concepts. Alternatively, if they do have a revenue focus, it is based upon simple relationships between payload capacity and revenue, assuming a either a fixed protfimargin or fixed yield. This approach works well when comparing two similar or closely related concepts, but falls apart when investigating more radically di erent systems, e.g. a cruise eficient short take-o and landing concept. By using a value based approach it is relatively simple to structure a decision model to incorporate changing revenue capability. However, the ability to investigate differences in design is very much dependent upon the revenue model and assumptions that are made. If the revenue elasticity is the same forthe two concepts then there is no benefi t in using a variable revenue approach. However, in the cases where the elasticity is different, the revenue approach offers the potential to more properly investigate some fundamentally different alternative concepts. © 2010 by Peter Sutcliffe & Peter Hollingsworth. Published by the American Institute of Aeronautics and Astronautics, Inc

Deliverable Raport D4.6 Tools for generating QMRF and QPRF reports

Scientific reports carry significant importance for the straightforward and effective transfer of knowledge, results and ideas. Good practice dictates that reports should be well-structured and concise. This deliverable describes the reporting services for models, predictions and validation tasks that have been integrated within the eNanoMapper (eNM) modelling infrastructure. Validation services have been added to the Jaqpot Quattro (JQ) modelling platform and the nano-lazar read-across framework developed within WP4 to support eNM modelling activities. Moreover, we have proceeded with the development of reporting services for predictions and models, respectively QPRF and QMRF reports. Therefore, in this deliverable, we first describe the three validation schemes created, namely training set split, cross- and external validation in detail and demonstrate their functionality both on API and UI levels. We then proceed with the description of the read across functionalities and finally, we present and describe the QPRF and QMRF reporting services

Spending time, spending money: passenger segmentation in an international airport

Changes within the air transport sector have required many European airports to either develop or expand their commercial activities. Strategies have included the expansion of retail space, a broadening of the tenant and merchandise mix and the development of a passenger segmentation strategy. This paper explores the efficacy of this approach by identifying the behaviour of different passenger segments while in an international airport. Using a framework of strategic market segmentation, it identifies how travellers allocate their time having entered 'airside' and details any purchases made. Using observational research and a face to face quantitative survey, 301 passengers were tracked and interviewed. Through a broad based, a priori form of segmentation, significant differences in shopping behaviour are identified. Such findings assist with the development of the airport's commercial strategy and allow a number of observations to be made about the value of market segmentation from both a theoretical and managerial perspective

Cabin crew collectivism: labour process and the roots of mobilization

The protracted dispute (2009–11) between British Airways and BASSA (British Airways Stewards and Stewardesses Association) was notable for the strength of collective action by cabin crew. In-depth interviews reveal collectivism rooted in the labour process and highlight the key agency of BASSA in effectively articulating worker interests. This data emphasizes crews’ relative autonomy, sustained by unionate on-board Cabin Service Directors who have defended the frontier of control against managerial incursions. Periodic attempts to re-configure the labour process, driven by cost cutting imperatives in an increasingly competitive airline industry, eroded crews’ organizational loyalties. When BA imposed radical changes to contracts and working arrangements, BASSA successfully mobilized its membership. The article contributes to labour process analysis by emphasizing the collective dimensions to emotional labour, restoring the ‘missing subject’, but also articulating the interconnections between labour process and mobilization and the role unions can play in providing the organizational and ideological resources to legitimate worker interest

Metadata stewardship in nanosafety research: learning from the past, preparing for an "on-the-fly" FAIR future

Introduction: Significant progress has been made in terms of best practice in research data management for nanosafety. Some of the underlying approaches to date are, however, overly focussed on the needs of specific research projects or aligned to a single data repository, and this “silo” approach is hampering their general adoption by the broader research community and individual labs. Methods: State-of-the-art data/knowledge collection, curation management FAIRification, and sharing solutions applied in the nanosafety field are reviewed focusing on unique features, which should be generalised and integrated into a functional FAIRification ecosystem that addresses the needs of both data generators and data (re)users. Results: The development of data capture templates has focussed on standardised single-endpoint Test Guidelines, which does not reflect the complexity of real laboratory processes, where multiple assays are interlinked into an overall study, and where non-standardised assays are developed to address novel research questions and probe mechanistic processes to generate the basis for read-across from one nanomaterial to another. By focussing on the needs of data providers and data users, we identify how existing tools and approaches can be re-framed to enable “on-the-fly” (meta) data definition, data capture, curation and FAIRification, that are sufficiently flexible to address the complexity in nanosafety research, yet harmonised enough to facilitate integration of datasets from different sources generated for different research purposes. By mapping the available tools for nanomaterials safety research (including nanomaterials characterisation, non-standard (mechanistic-focussed) methods, measurement principles and experimental setup, environmental fate and requirements from new research foci such as safe and sustainable by design), a strategy for integration and bridging between silos is presented. The NanoCommons KnowledgeBase has shown how data from different sources can be integrated into a one-stop shop for searching, browsing and accessing data (without copying), and thus how to break the boundaries between data silos. Discussion: The next steps are to generalise the approach by defining a process to build consensus (meta)data standards, develop solutions to make (meta)data more machine actionable (on the fly ontology development) and establish a distributed FAIR data ecosystem maintained by the community beyond specific projects. Since other multidisciplinary domains might also struggle with data silofication, the learnings presented here may be transferable to facilitate data sharing within other communities and support harmonization of approaches across disciplines to prepare the ground for cross-domain interoperability. Visit WorldFAIR online at http://worldfair-project.eu. WorldFAIR is funded by the EC HORIZON-WIDERA-2021-ERA-01-41 Coordination and Support Action under Grant Agreement No. 101058393

Metadata stewardship in nanosafety research: learning from the past, preparing for an "on-the-fly" FAIR future

Introduction: Significant progress has been made in terms of best practice in research data management for nanosafety. Some of the underlying approaches to date are, however, overly focussed on the needs of specific research projects or aligned to a single data repository, and this "silo" approach is hampering their general adoption by the broader research community and individual labs.Methods: State-of-the-art data/knowledge collection, curation management FAIrification, and sharing solutions applied in the nanosafety field are reviewed focusing on unique features, which should be generalised and integrated into a functional FAIRification ecosystem that addresses the needs of both data generators and data (re)users.Results: The development of data capture templates has focussed on standardised single-endpoint Test Guidelines, which does not reflect the complexity of real laboratory processes, where multiple assays are interlinked into an overall study, and where non-standardised assays are developed to address novel research questions and probe mechanistic processes to generate the basis for read-across from one nanomaterial to another. By focussing on the needs of data providers and data users, we identify how existing tools and approaches can be re-framed to enable "on-the-fly" (meta) data definition, data capture, curation and FAIRification, that are sufficiently flexible to address the complexity in nanosafety research, yet harmonised enough to facilitate integration of datasets from different sources generated for different research purposes. By mapping the available tools for nanomaterials safety research (including nanomaterials characterisation, nonstandard (mechanistic-focussed) methods, measurement principles and experimental setup, environmental fate and requirements from new research foci such as safe and sustainable by design), a strategy for integration and bridging between silos is presented. The NanoCommons KnowledgeBase has shown how data from different sources can be integrated into a one-stop shop for searching, browsing and accessing data (without copying), and thus how to break the boundaries between data silos.Discussion: The next steps are to generalise the approach by defining a process to build consensus (meta)data standards, develop solutions to make (meta)data more machine actionable (on the fly ontology development) and establish a distributed FAIR data ecosystem maintained by the community beyond specific projects. Since other multidisciplinary domains might also struggle with data silofication, the learnings presented here may be transferrable to facilitate data sharing within other communities and support harmonization of approaches across disciplines to prepare the ground for cross-domain interoperability

Managing urinary tract infections

Urinary tract infections (UTI) are common in childhood. Presence of pyuria and bacteriuria in an appropriately collected urine sample are diagnostic of UTI. The risk of UTI is increased with an underlying urological abnormality such as vesicoureteral reflux, constipation, and voiding dysfunction. Patients with acute pyelonephritis are at risk of renal scarring and subsequent complications such as hypertension, proteinuria with and without FSGS, pregnancy-related complications and even end-stage renal failure. The relevance and the sequence of the renal imaging following initial UTI, and the role of antimicrobial prophylaxis and surgical intervention are currently undergoing an intense debate. Prompt treatment of UTI and appropriate follow-up of those at increased risk of recurrence and/or renal scarring are important