MEVA - An interactive visualization application for validation of multifaceted meteorological data with multiple 3D devices

To achieve more realistic simulations, meteorologists develop and use models with increasing spatial and temporal resolution. The analyzing, comparing, and visualizing of resulting simulations becomes more and more challenging due to the growing amounts and multifaceted character of the data. Various data sources, numerous variables and multiple simulations lead to a complex database. Although a variety of software exists suited for the visualization of meteorological data, none of them fulfills all of the typical domain-specific requirements: support for quasi-standard data formats and different grid types, standard visualization techniques for scalar and vector data, visualization of the context (e.g., topography) and other static data, support for multiple presentation devices used in modern sciences (e.g., virtual reality), a user-friendly interface, and suitability for cooperative work

Geomechanical/ Geochemical Modeling Studies onducted Within the International DECOVALEX Project

The DECOVALEX project is an international cooperative project initiated by SKI, the Swedish Nuclear Power Inspectorate, with participation of about 10 international organizations. The general goal of this project is to encourage multidisciplinary interactive and cooperative research on modeling coupled thermo-hydro-mechanical-chemical (THMC) processes in geologic formations in support of the performance assessment for underground storage of radioactive waste. One of the research tasks, initiated in 2004 by the U.S. Department of Energy (DOE), addresses the long-term impact of geomechanical and geochemical processes on the flow conditions near waste emplacement tunnels. Within this task, four international research teams conduct predictive analysis of the coupled processes in two generic repositories, using multiple approaches and different computer codes. Below, we give an overview of the research task and report its current status

Results From an International Simulation Study on Couples Thermal, Hydrological, and Mechanical (THM) Processes Near Geological Nuclear Waste Repositories

As part of the ongoing international DECOVALEX project, four research teams used five different models to simulate coupled thermal, hydrological, and mechanical (THM) processes near waste emplacement drifts of geological nuclear waste repositories. The simulations were conducted for two generic repository types, one with open and the other with back-filled repository drifts, under higher and lower postclosure temperatures, respectively. In the completed first model inception phase of the project, a good agreement was achieved between the research teams in calculating THM responses for both repository types, although some disagreement in hydrological responses is currently being resolved. In particular, good agreement in the basic thermal-mechanical responses was achieved for both repository types, even though some teams used relatively simplified thermal-elastic heat-conduction models that neglected complex near-field thermal-hydrological processes. The good agreement between the complex and simplified process models indicates that the basic thermal-mechanical responses can be predicted with a relatively high confidence level

Artificial intelligence and visual analytics in geographical space and cyberspace: Research opportunities and challenges

In recent decades, we have witnessed great advances on the Internet of Things, mobile devices, sensor-based systems, and resulting big data infrastructures, which have gradually, yet fundamentally influenced the way people interact with and in the digital and physical world. Many human activities now not only operate in geographical (physical) space but also in cyberspace. Such changes have triggered a paradigm shift in geographic information science (GIScience), as cyberspace brings new perspectives for the roles played by spatial and temporal dimensions, e.g., the dilemma of placelessness and possible timelessness. As a discipline at the brink of even bigger changes made possible by machine learning and artificial intelligence, this paper highlights the challenges and opportunities associated with geographical space in relation to cyberspace, with a particular focus on data analytics and visualization, including extended AI capabilities and virtual reality representations. Consequently, we encourage the creation of synergies between the processing and analysis of geographical and cyber data to improve sustainability and solve complex problems with geospatial applications and other digital advancements in urban and environmental sciences

Risk Assessment for Patients with Chronic Respiratory Conditions in the Context of the SARS-CoV-2 Pandemic Statement of the German Respiratory Society with the Support of the German Association of Chest Physicians

Assessing the risk for specific patient groups to suffer from severe courses of COVID-19 is of major importance in the current SARS-CoV-2 pandemic. This review focusses on the risk for specific patient groups with chronic respiratory conditions, such as patients with asthma, chronic obstructive pulmonary disease, cystic fibrosis (CF), sarcoidosis, interstitial lung diseases, lung cancer, sleep apnea, tuberculosis, neuromuscular diseases, a history of pulmonary embolism, and patients with lung transplants. Evidence and recommendations are detailed in exemplary cases. While some patient groups with chronic respiratory conditions have an increased risk for severe courses of COVID-19, an increasing number of studies confirm that asthma is not a risk factor for severe COVID-19. However, other risk factors such as higher age, obesity, male gender, diabetes, cardiovascular diseases, chronic kidney or liver disease, cerebrovascular and neurological disease, and various immunodeficiencies or treatments with immunosuppressants need to be taken into account when assessing the risk for severe COVID-19 in patients with chronic respiratory diseases