Geodata Infrastructure for the Management of Railway Assets-Related Research Data

A system containing updated information on railway assets, including their condition, contributes significantly to the maintenance of railway networks and to ensure continuous service. The Institute of Transportation Systems (DLR-TS) of the German Aerospace Center (DLR) carries out research in the area of condition monitoring using in-service trains. Massive amounts of measurement data are collected from various sensors mounted railway vehicles. There is an ever-growing amount of data, as several terabytes of measurement data are collected every year as a part of multiple projects. Furthermore, static and semi-static data on railway networks such as the topology of the network, the infrastructure elements in the network and their conditions are also gathered. Here arises a need for sustainable management of the raw datasets and the generated results to make them Findable, Accessible, Interoperable and Reusable (FAIR) over time to researchers within the DLR, and other stakeholders such as project partners, funding organizations and the public. This poster addresses the topic of management of railway infrastructure and measurement data through the development of a system called “Transportation Infrastructure Data Platform” (TRIDAP) that enables the storage, analysis and sharing of data in a FAIR-compatible way. The platform is setup using open-source software such as PostgreSQL, Apache Kafka, Apache Spark, GeoServer, GeoNetwork and Prometheus to name a few. DLR-TS is actively developing this platform. Datasets from DLR-TS and few other DLR institutes are planned to be stored in the platform during the course of the DLR-funded cross-domain project “Digitaler Atlas 2.0”

Geodata Infrastructure for the Management of Research Data in Railway Domain

A system containing updated information on railway assets, including their condition, contributes significantly to the maintenance of railway networks and to ensure continuous service. The Institute of Transportation Systems (DLR-TS) of the German Aerospace Center (DLR) carries out research in the area of condition monitoring using in-service trains. Massive amounts of measurement data are collected from various sensors mounted railway vehicles. There is an ever-growing amount of data, as several terabytes of measurement data are collected every year as a part of multiple projects. Furthermore, static and semi-static data on railway networks such as the topology of the network, the infrastructure elements in the network and their conditions are also gathered. Here arises a need for sustainable management of the raw datasets and the generated results to make them Findable, Accessible, Interoperable and Reusable (FAIR) over time to researchers within the DLR, and other stakeholders such as project partners, funding organizations and the public. This presentation addresses the topic of management of railway infrastructure and measurement data through the development of a system called "Transportation Infrastructure Data Plat-form" (TRIDAP) that enables the storage, analysis and sharing of data in a FAIR-compatible way. The platform is setup using open-source software such as PostgreSQL, Apache Kafka, Apache Spark, GeoServer, GeoNetwork and Prometheus to name a few. DLR-TS is actively developing this platform. Datasets from DLR-TS and few other DLR institutes are planned to be stored in the platform during the course of the DLR-funded cross-domain project "Digitaler Atlas 2.0"

Rail2X - SmartServices (Projektabschlussbericht)

V2X (Vehicle2Everything) ist ein WLAN-ähnlicher Standard, der im Automobilbereich für den Informationsaustausch zwischen Fahrzeugen und / oder Infrastruktur genutzt wird. Beispiels-weise findet dieser Nachrichtenstandard im Straßenverkehr Anwendung, um den Autofahrer rechtzeitig vor kritischen Situationen zu warnen und so zu unterstützen. V2X-Komponenten befinden sich daher seit mehreren Jahren in der Entwicklung und Erpro-bung. Jedoch ist dieser Kommunikationsstandard nicht ausschließlich auf den Automobilbe-reich begrenzt, sondern verkehrsträgerunabhängig ausgelegt. Über das Projekt Rail2X-Smart Services wurde die Nutzung der V2X-Kommunikation für den Eisenbahnsektor evaluiert. Ziel des Projektkonsortiums war die Erforschung und Erweiterung von V2X als Rail2X in den Bahnbereich, um den Komfort sowie die Effektivität und Wirtschaftlichkeit des Bahnbetriebs im Regionalverkehr zu steigern. Grundsätzlich wurde ein Verkehrsträger und Verkehrsmittel übergreifender Informationsaustausch ermöglicht. Sowohl die Nutzung einheitlicher Standards als auch die Verknüpfung mit einem zentralen Datenmanagementsystem, das Daten bearbeitet und mit anderen Datenquellen wie der mCLOUD korreliert, spielten dabei eine zentrale Rolle. Für die Erprobung und Evaluierung wurden drei relevanten Anwendungsfällen im Bahnbereich definiert und ausgestaltet die durch die V2X-Anwendung einen wirtschaftlichen Betrieb ermöglichen. Mittels dieser Anwendungsfälle konnte gezeigt werden, dass einerseits die Nutzung des V2X-Standards möglich und andererseits die Anwendung von kostengünstigen Standardkomponenten aus dem Automobilbereich auch im Bahnbereich zielführend ist

Albiglutide and cardiovascular outcomes in patients with type 2 diabetes and cardiovascular disease (Harmony Outcomes): a double-blind, randomised placebo-controlled trial

Background: Glucagon-like peptide 1 receptor agonists differ in chemical structure, duration of action, and in their effects on clinical outcomes. The cardiovascular effects of once-weekly albiglutide in type 2 diabetes are unknown. We aimed to determine the safety and efficacy of albiglutide in preventing cardiovascular death, myocardial infarction, or stroke. Methods: We did a double-blind, randomised, placebo-controlled trial in 610 sites across 28 countries. We randomly assigned patients aged 40 years and older with type 2 diabetes and cardiovascular disease (at a 1:1 ratio) to groups that either received a subcutaneous injection of albiglutide (30–50 mg, based on glycaemic response and tolerability) or of a matched volume of placebo once a week, in addition to their standard care. Investigators used an interactive voice or web response system to obtain treatment assignment, and patients and all study investigators were masked to their treatment allocation. We hypothesised that albiglutide would be non-inferior to placebo for the primary outcome of the first occurrence of cardiovascular death, myocardial infarction, or stroke, which was assessed in the intention-to-treat population. If non-inferiority was confirmed by an upper limit of the 95% CI for a hazard ratio of less than 1·30, closed testing for superiority was prespecified. This study is registered with ClinicalTrials.gov, number NCT02465515. Findings: Patients were screened between July 1, 2015, and Nov 24, 2016. 10 793 patients were screened and 9463 participants were enrolled and randomly assigned to groups: 4731 patients were assigned to receive albiglutide and 4732 patients to receive placebo. On Nov 8, 2017, it was determined that 611 primary endpoints and a median follow-up of at least 1·5 years had accrued, and participants returned for a final visit and discontinuation from study treatment; the last patient visit was on March 12, 2018. These 9463 patients, the intention-to-treat population, were evaluated for a median duration of 1·6 years and were assessed for the primary outcome. The primary composite outcome occurred in 338 (7%) of 4731 patients at an incidence rate of 4·6 events per 100 person-years in the albiglutide group and in 428 (9%) of 4732 patients at an incidence rate of 5·9 events per 100 person-years in the placebo group (hazard ratio 0·78, 95% CI 0·68–0·90), which indicated that albiglutide was superior to placebo (p<0·0001 for non-inferiority; p=0·0006 for superiority). The incidence of acute pancreatitis (ten patients in the albiglutide group and seven patients in the placebo group), pancreatic cancer (six patients in the albiglutide group and five patients in the placebo group), medullary thyroid carcinoma (zero patients in both groups), and other serious adverse events did not differ between the two groups. There were three (<1%) deaths in the placebo group that were assessed by investigators, who were masked to study drug assignment, to be treatment-related and two (<1%) deaths in the albiglutide group. Interpretation: In patients with type 2 diabetes and cardiovascular disease, albiglutide was superior to placebo with respect to major adverse cardiovascular events. Evidence-based glucagon-like peptide 1 receptor agonists should therefore be considered as part of a comprehensive strategy to reduce the risk of cardiovascular events in patients with type 2 diabetes. Funding: GlaxoSmithKline

A multi-country test of brief reappraisal interventions on emotions during the COVID-19 pandemic.

The COVID-19 pandemic has increased negative emotions and decreased positive emotions globally. Left unchecked, these emotional changes might have a wide array of adverse impacts. To reduce negative emotions and increase positive emotions, we tested the effectiveness of reappraisal, an emotion-regulation strategy that modifies how one thinks about a situation. Participants from 87 countries and regions (n = 21,644) were randomly assigned to one of two brief reappraisal interventions (reconstrual or repurposing) or one of two control conditions (active or passive). Results revealed that both reappraisal interventions (vesus both control conditions) consistently reduced negative emotions and increased positive emotions across different measures. Reconstrual and repurposing interventions had similar effects. Importantly, planned exploratory analyses indicated that reappraisal interventions did not reduce intentions to practice preventive health behaviours. The findings demonstrate the viability of creating scalable, low-cost interventions for use around the world

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

DLR grundfinanziertes Projekt Digitaler Atlas 2.0

Vorstellung von dem Projekt Digitaler Atlas 2.0

Next Generation Traffic Data Plattform (ngTDP)

Die zunehmende Menge an Daten durch die Digitalisierung in allen Bereichen fordert die Integration einer zentralen Datenplattform. Eine Datenplattform trägt die Informationen aus verschiedenen Quellen zusammen. Diese Daten werden unstrukturiert in einem Datensee oder harmonisiert in verwendbare, einheitliche und relationale Strukturen gespeichert. Um auf die Informationen zuzugreifen, bietet die Datenplattform diverse technisch standardisierte und abgesicherte Schnittstellen an. Diesen Gedanken folgend, entwickelt unser DLR-Institut für Verkehrssystemtechnik seit mehr als 10 Jahren aktiv an der Traffic Data Platform mit dem Fokus Verkehrsmanagement. Um die Daten aus den Forschungsbereichen Bahnverkehr und virtuelle Welt mit seinen hochgenauen Karten zu integrieren, findet aktuell die Entwicklung der neuen Next Generation Traffic Data Platform statt

Zentrales Echtzeit-Datenmanagement für Anwendungen im Bahnverkehr

Die zentrale Erfassung, Verarbeitung und Integration heterogener Daten zur Generierung von Mehrwertanwendungen spielt auch im Schienenverkehr eine zunehmend wichtigere Rolle. Das DLR hat mit dem Bahnserver ein zentrales Datenmanagement-System entwickelt, welches statische und dynamische Daten unterschiedlicher Herkunft organisiert, miteinander kombiniert und für den Nutzer in einer grafischen Oberfläche veranschaulicht. Bei Import und Darstellung von Geodaten lag der Fokus auf der Einbindung offener Datenquellen und Formate, um eine einfache und schnelle Mehrfachnutzung des Bahnservers zu garantieren. Das Herzstück der Echtzeitdaten-Verwaltung bildet ein Mandanten-basiertes Datenzugriffskonzept, welches ein anwendungsorientiertes Management der erfassten Daten gewährleistet