A level playing field for comparing air and rail travel times

The research project was funded by the International Union of Railways (UIC).Background: Shifting travellers from air to rail can reduce environmental impacts and is an important European Union goal. Online travel planning applications allow travellers to easily compare air and rail transport choices, however, they may not accurately consider time travellers spend at the airport or railway station since these depend on buffer times travellers use to protect against delays. Methods: This research investigated the actual time spent at airports and railway stations to analyse the accuracy of travel planning applications and help improve the quality of travel time estimates. The research used a travel time recording application to determine the time spent by passengers at airports and railway stations. Data was collected for 312 trips. The research was supplemented by an extensive literature review of dwell times and multimodal travel planning applications. Results: The research found that travellers spent an average of 157 minutes at airports and 32 minutes at railway stations. Comparing these results to travel planning application, the information shows that the applications significantly underestimate time spent at airports and slightly underestimate time spent at railway stations. The use of unrealistic airport waiting times in travel planning applications distorts traveller perception in favour of air travel. Conclusion: Therefore, railway operators should support the development of improved travel planning applications that better consider waiting times. Improving these applications would be much more cost effective than infrastructure improvements designed to save a few minutes of travel time

IDARE2—Simultaneous Visualisation of Multiomics Data in Cytoscape

Visual integration of experimental data in metabolic networks is an important step to understanding their meaning. As genome-scale metabolic networks reach several thousand reactions, the task becomes more difficult and less revealing. While databases like KEGG and BioCyc provide curated pathways that allow a navigation of the metabolic landscape of an organism, it is rather laborious to map data directly onto those pathways. There are programs available using these kind of databases as a source for visualization; however, these programs are then restricted to the pathways available in the database. Here, we present IDARE2 a cytoscape plugin that allows the visualization of multiomics data in cytoscape in a user-friendly way. It further provides tools to disentangle highly connected network structures based on common properties of nodes and retains structural links between the generated subnetworks, offering a straightforward way to traverse the splitted network. The tool is extensible, allowing the implementation of specialised representations and data format parsers. We present the automated reproduction of the original IDARE nodes using our tool and show examples of other data being mapped on a network of E. coli. The extensibility is demonstrated with two plugins that are available on github. IDARE2 provides an intuitive way to visualise data from multiple sources and allows one to disentangle the often complex network structure in large networks using predefined properties of the network nodes

IDARE2—Simultaneous Visualisation of Multiomics Data in Cytoscape

Visual integration of experimental data in metabolic networks is an important step to understanding their meaning. As genome-scale metabolic networks reach several thousand reactions, the task becomes more difficult and less revealing. While databases like KEGG and BioCyc provide curated pathways that allow a navigation of the metabolic landscape of an organism, it is rather laborious to map data directly onto those pathways. There are programs available using these kind of databases as a source for visualization; however, these programs are then restricted to the pathways available in the database. Here, we present IDARE2 a cytoscape plugin that allows the visualization of multiomics data in cytoscape in a user-friendly way. It further provides tools to disentangle highly connected network structures based on common properties of nodes and retains structural links between the generated subnetworks, offering a straightforward way to traverse the splitted network. The tool is extensible, allowing the implementation of specialised representations and data format parsers. We present the automated reproduction of the original IDARE nodes using our tool and show examples of other data being mapped on a network of E. coli. The extensibility is demonstrated with two plugins that are available on github. IDARE2 provides an intuitive way to visualise data from multiple sources and allows one to disentangle the often complex network structure in large networks using predefined properties of the network nodes

Delaytainment an Flughäfen: Die Notwendigkeit eines Verspätungsservices und erste Gestaltungsideen

Der Luftverkehr ist ein internationaler Wachstumsmarkt. Eng damit verbunden sind schwerwiegende, strukturell begründete Kapazitätsprobleme der Luftver-kehrsinfrastrukturen, die chronische – in Zeiten starker Nachfrage sogar kata-strophale – Engpass- und Verspätungssituationen herbeiführen. Mittel- bis lang-fristig ist auch trotz der Ereignisse rund um den 11. September nicht von einer Verbesserung der Pünktlichkeitswerte auszugehen. Im Gegenteil wird der Luft-verkehr zukünftig noch stärker im Stau stecken als bislang schon. Das vorlie-gende Papier beleuchtet die strukturellen Gründe dieser Verspätungsproblematik. Ausgehend von diesem Befund werden sodann auf der Grundlage der Ergebnisse einer qualitativen empirischen Erhebung Vorschläge verspätungsbezogener Ser-viceinitiativen entwickelt, die an die zunehmenden Tendenzen zur erlebnis-orientierten „Entertainisierung“ von Wartesituationen in allen Lebensbereichen anschließen. Dieser sogenannte „Delaytainment“-Ansatz speist sich aus der Überzeugung, dass die handlungsmächtigen Akteure des Systems – die Luftver-kehrsgesellschaften und Flughafengesellschaften – bislang mitnichten alle Mög-lichkeiten verspätungsbezogener Serviceinitiativen ausschöpfen. Nach Ansicht der Autoren reicht es heute nicht mehr aus, allein Massnahmen zur Verspä-tungsvermeidung zu entwickeln. Vielfältige Möglichkeiten zur sofortigen Lin-derung der Situation bleiben ungenutzt. Der derzeitigen Verspätungssituation angemessen muss gleichzeitig das in den Verkehrswissenschaften häufig gescholtene „Reparaturdienstverhalten“ durch ein geeignetes Notfallmanagement verbessert werden. Oder anders gesagt: Kein Arzt würde, nur weil er primär an der Heilung der die Schmerzen verursachenden Krankheit interessiert ist, die ihre Folgen lindernden Schmerzmittel in seiner Therapie vernachlässigen. Dies scheint aber im derzeitigen Verspätungsmanagement des Luftverkehrs der Fall zu sein. Die hier vorgestellten Lösungsansätze zielen auf eine Verbesserung dieser Situ-ation. Auch die Adaption der grundlegenden Gestaltungsphilosophien auf Verspä-tungssituationen im Bereich der anderen Verkehrsträger erscheint aus dieser Sicht wünschenswert. -- Air Passenger Traffic is a strongly growing international market. Such growth creates delay and capacity problems, issues of increasing political and scientific interest. In this paper the structural reasons of the delay-problem are examined. On the basis of a qualitative empirical investigation a so-called „Delaytainment“-approach is developed, aiming to relieve – not to cure – the structural problems which can only be solved in middle and long term perspektives.

Telemedicine and Online Platforms as an Opportunity to Optimise Qualitative Data Collection, Explore and Understand Disease Pathways in a Novel Pandemic Like COVID-19

This article explores digital technology used in the health sector today. There are several ways digital technology is being used for quantitative study aims during the current COVID-19 Pandemic e.g. online symptom checkers. The knowledge gap in COVID-19 as in all novel conditions, consist of both quantitative and qualitative attributes. Digital tool use is prevalent during the COVID-19 Pandemic but most of the data being collected is quantitative in nature. We therefore recommend taking advantage of this telemedicine era and explore optimisation of qualitative data collection, for the purpose of gaining a better understanding of the phenomenon

DCcov: Repositioning of Drugs and Drug Combinations for SARS-CoV-2 Infected Lung through Constraint-Based Modelling

The 2019 coronavirus disease (COVID-19) became a worldwide pandemic with currently no effective antiviral drug except treatments for symptomatic therapy. Flux balance analysis is an efficient method to analyze metabolic networks. It allows optimizing for a metabolic function and thus e.g., predicting the growth rate of a specific cell or the production rate of a metabolite of interest. Here flux balance analysis was applied on human lung cells infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to reposition metabolic drugs and drug combinations against the replication of the SARS-CoV-2 virus within the host tissue. Making use of expression data sets of infected lung tissue, genome-scale COVID-19-specific metabolic models were reconstructed. Then host-specific essential genes and gene-pairs were determined through in-silico knockouts that permit reducing the viral biomass production without affecting the host biomass. Key pathways that are associated with COVID-19 severity in lung tissue are related to oxidative stress, as well as ferroptosis, sphingolipid metabolism, cysteine metabolism, and fat digestion. By in-silico screening of FDA approved drugs on the putative disease-specific essential genes and gene-pairs, 45 drugs and 99 drug combinations were predicted as promising candidates for COVID-19 focused drug repositioning (https://github.com/sysbiolux/DCcov). Among the 45 drug candidates, six antiviral drugs were found and seven drugs that are being tested in clinical trials against COVID-19. Other drugs like gemcitabine, rosuvastatin and acetylcysteine, and drug combinations like azathioprine-pemetrexed might offer new chances for treating COVID-19

Disease spread through animal movements: a static and temporal network analysis of pig trade in Germany

Background: Animal trade plays an important role for the spread of infectious diseases in livestock populations. As a case study, we consider pig trade in Germany, where trade actors (agricultural premises) form a complex network. The central question is how infectious diseases can potentially spread within the system of trade contacts. We address this question by analyzing the underlying network of animal movements. Methodology/Findings: The considered pig trade dataset spans several years and is analyzed with respect to its potential to spread infectious diseases. Focusing on measurements of network-topological properties, we avoid the usage of external parameters, since these properties are independent of specific pathogens. They are on the contrary of great importance for understanding any general spreading process on this particular network. We analyze the system using different network models, which include varying amounts of information: (i) static network, (ii) network as a time series of uncorrelated snapshots, (iii) temporal network, where causality is explicitly taken into account. Findings: Our approach provides a general framework for a topological-temporal characterization of livestock trade networks. We find that a static network view captures many relevant aspects of the trade system, and premises can be classified into two clearly defined risk classes. Moreover, our results allow for an efficient allocation strategy for intervention measures using centrality measures. Data on trade volume does barely alter the results and is therefore of secondary importance. Although a static network description yields useful results, the temporal resolution of data plays an outstanding role for an in-depth understanding of spreading processes. This applies in particular for an accurate calculation of the maximum outbreak size.Comment: main text 33 pages, 17 figures, supporting information 7 pages, 7 figure

Extending the MVC Design Pattern towards a Task-Oriented Development Approach for Pervasive Computing Applications

This paper addresses the implementation of pervasive Java Web applications using a development approach that is based on the Model-View- Controller (MVC) design pattern. We combine the MVC methodology with a hierarchical task-based state transition model in order to achieve the distinction between the task state and the view state of an application. More precisely, we propose to add a device-independent TaskStateBean and a device-specific ViewStateBean for each task state as an extension to the J2EE Service to Worker design pattern. Furthermore, we suggest representing the task state and view state transition models as finite state automata in two sets of XML files