Abstract

Materials Cloud is a platform designed to enable open and seamless sharing of resources for computational science, driven by applications in materials modelling. It hosts 1) archival and dissemination services for raw and curated data, together with their provenance graph, 2) modelling services and virtual machines, 3) tools for data analytics, and pre-/post-processing, and 4) educational materials. Data is citable and archived persistently, providing a comprehensive embodiment of the FAIR principles that extends to computational workflows. Materials Cloud leverages the AiiDA framework to record the provenance of entire simulation pipelines (calculations performed, codes used, data generated) in the form of graphs that allow to retrace and reproduce any computed result. When an AiiDA database is shared on Materials Cloud, peers can browse the interconnected record of simulations, download individual files or the full database, and start their research from the results of the original authors. The infrastructure is agnostic to the specific simulation codes used and can support diverse applications in computational science that transcend its initial materials domain. Comment: 19 pages, 8 figure Document type: Article

Abstract

Initiatives in the smart mobility domain are increasingly characterized by a service-dominant mindset, focusing explicitly on the value that is created for the customer. As a result, the business models of these initiatives become more agile in nature, forcing them to be continuously and rapidly redesigned. However, given the wide landscape of potential stakeholders in the smart mobility domain, it may prove difficult to identify the stakeholders that should be considered for viable business model design. In response, this paper proposes a reference business model for the smart mobility domain which elaborates on a generic set of stakeholder categories and their characteristics to guide the design of these models. Following a design science research approach, we iteratively derived and evaluated the validity of the reference model using a set of business model design workshops. We illustrate the applicability of the reference model by means of a business model design case.

Abstract

Multi-product pipelines are a significant and extensive mean of transporting petroleum based products from refineries to distribution centers. Previous contributions on tree-like pipeline scheduling problem have considered a simple structure with a single refinery connected to a mainline and some secondary lines only emerged from the mainline. In practice, however, a tree-like pipeline may also have several branches on a secondary line resulting in a complex structure, the so called multi-level tree-like pipeline. This paper addresses the short-term scheduling of multi-level tree-like pipelines with multiple refineries through a continuous time mixed-integer linear programming (MILP) model that considers multiple intermediate due dates for product demands. The objective is to satisfy product demands on time at the minimum operational costs, such as pumping, interface and backorder costs. The proposed model performance’s is shown by solving four examples. Document type: Article

Abstract

BSTRACT"/jats:title""jats:p"The field of Pharmacogenomics presents great challenges for researchers that are willing to make their studies reproducible and shareable. This is attributed to the generation of large volumes of high-throughput multimodal data, and the lack of standardized workflows that are robust, scalable, and flexible to perform large-scale analyses. To address this issue, we developed pharmacogenomic workflows in the Common Workflow Language to process two breast cancer datasets in a reproducible and transparent manner. Our pipelines combine both pharmacological and molecular profiles into a portable data object that can be used for future analyses in cancer research. Our data objects and workflows are shared on Harvard Dataverse and Code Ocean where they have been assigned a unique Digital Object Identifier, providing a level of data provenance and a persistent location to access and share our data with the community. Document type: Preprint

Abstract

ording to the International Air Transport Association, the industry fuel bill accounts for more than 25% of the annual airline operating costs. In times of severe economic constraints and increasing fuel costs, air carriers are looking for ways to reduce costs and improve fuel efficiency without putting flight safety into jeopardy. In particular, this is inducing discussions on how much additional fuel to put in a planned route to avoid diverting to an alternate airport due to Air Traffic Flow Management delays. We provide here a general model to support such decisions. We illustrate it with a case study and provide comparison with the current practice, showing the relevance of our approach. Peer Reviewed

Abstract

In this paper, we analyze symmetric frequency equilibria in airline markets; these equilibria are derived as multiproduct oligopoly solutions in a spatial competition model. Competitive equilibria are compared with a regulated equilibrium; in order to assess the welfare implications of European air transport liberalization, we compute numerical solutions using data for 21 regulated European interstate routes in 1990. We conclude that, following the introduction of competition in these markets, consumer welfare is significantly higher due to frequency increases and fare decreases. Profits decrease and, as a result of higher departure frequencies, environmental costs increase. However, the gains in consumer welfare more than compensate the decrease in profits and the rise in environmental costs. © 2006 Elsevier Ltd. All rights reserved.