Uncertainty quantification patterns for multiscale models

Uncertainty quantification (UQ) is a key component when using computational models that involve uncertainties, e.g. in decision-making scenarios. In this work, we present uncertainty quantification patterns (UQPs) that are designed to support the analysis of uncertainty in coupled multi-scale and multi-domain applications. UQPs provide the basic building blocks to create tailored UQ for multiscale models. The UQPs are implemented as generic templates, which can then be customized and aggregated to create a dedicated UQ procedure for multiscale applications. We present the implementation of the UQPs with multiscale co

Land–sea coupling of early Pleistocene glacial cycles in the southern North Sea exhibit dominant Northern Hemisphere forcing

We assess the disputed phase relations between forcing and climatic response in the early Pleistocene with a spliced Gelasian (∼ 2.6–1.8 Ma) multi-proxy record from the southern North Sea basin. The cored sections couple climate evolution on both land and sea during the intensification of Northern Hemisphere glaciation (NHG) in NW Europe, providing the first well-constrained stratigraphic sequence of the classic terrestrial Praetiglian stage. Terrestrial signals were derived from the Eridanos paleoriver, a major fluvial system that contributed a large amount of freshwater to the northeast Atlantic. Due to its latitudinal position, the Eridanos catchment was likely affected by early Pleistocene NHG, leading to intermittent shutdown and reactivation of river flow and sediment transport. Here we apply organic geochemistry, palynology, carbonate isotope geochemistry, and seismostratigraphy to document both vegetation changes in the Eridanos catchment and regional surface water conditions and relate them to early Pleistocene glacial–interglacial cycles and relative sea level changes. Paleomagnetic and palynological data provide a solid integrated timeframe that ties the obliquity cycles, expressed in the borehole geophysical logs, to Marine Isotope Stages (MIS) 103 to 92, independently confirmed by a local benthic oxygen isotope record. Marine and terrestrial palynological and organic geochemical records provide high-resolution reconstructions of relative terrestrial and sea surface temperature (TT and SST), vegetation, relative sea level, and coastal influence.During the prominent cold stages MIS 98 and 96, as well as 94, the record indicates increased non-arboreal vegetation, low SST and TT, and low relative sea level. During the warm stages MIS 99, 97, and 95 we infer increased stratification of the water column together with a higher percentage of arboreal vegetation, high SST, and relative sea level maxima. The early Pleistocene distinct warm–cold alterations are synchronous between land and sea, but lead the relative sea level change by 3000–8000 years. The record provides evidence for a dominantly Northern Hemisphere-driven cooling that leads the glacial buildup and varies on the obliquity timescale. Southward migration of Arctic surface water masses during glacials, indicated by cool-water dinoflagellate cyst assemblages, is furthermore relevant for the discussion on the relation between the intensity of the Atlantic meridional overturning circulation and ice sheet growth

Tutorial applications for Verification, Validation and Uncertainty Quantification using VECMA toolkit

The VECMA toolkit enables automated Verification, Validation and Uncertainty Quantification (VVUQ) for complex applications that can be deployed on emerging exascale platforms and provides support for software applications for any domain of interest. The toolkit has four main components including EasyVVUQ for VVUQ workflows, FabSim3 for automation and tool integration, MUSCLE3 for coupling multiscale models and QCG tools to execute application workflows on high performance computing (HPC). A more recent addition to the VECMAtk is EasySurrogate for various types of surrogate methods. In this paper, we present five tutorials from different application domains that apply these VECMAtk components to perform uncertainty quantification analysis, use surrogate models, couple multiscale models and execute sensitivity analysis on HPC. This paper aims to provide hands-on experience for practitioners aiming to test and contrast with their own applications

Validity of the Patient Experiences and Satisfaction with Medications (PESaM) Questionnaire

Background: This study assessed the validity and reliability of the generic module of the recently developed Patient Experiences and Satisfaction with Medications (PESaM) questionnaire in a sample of patients in the Netherlands. Methods: The generic module of the PESaM questionnaire consists of 18 items related to the domains effectiveness, side effects and ease of use of medications. It assesses patients’ experiences regarding the impact of the medication on daily life, health and satisfaction. In 2017, the PESaM questionnaire was sent out to idiopathic pulmonary fibrosis patients using pirfenidone or nintedanib, atypical haemolytic uraemic syndrome patients receiving eculizumab and patients using tacrolimus after kidney transplantation. Mean scores for each domain were calculated applying a scoring algorithm. Construct validity and reliability were assessed using recommended methods. Results: 188 participants completed the generic module, of whom 48% used pirfenidone, 36% nintedanib, 11% tacrolimus and 5% eculizumab. The generic module has good structural properties. Internal consistency values of the domains were satisfactory (i.e. Cronbach’s coefficient alpha above 0.7). Confirmatory factor analysis provided further evidence for construct validity, with good convergent and discriminant validity. The PESaM questionnaire also showed different scores for patients using different medications, in line with expectations, and was therefore able to differentiate between patient groups. Test–retest reliability of the items and domains were rated as moderate to fair (i.e. intraclass coefficients ranged between 0.18 and 0.76). Conclusions: The PESaM questionnaire is a unique patient-reported outcome measure evaluating patient experiences and satisfaction with medications. It has been developed in conjunction with patients, ensuring coverage of domains and issues relevant from the patient’s perspective. This study has shown promising validity of the generic module of the PESaM questionnaire. Further research is recommended to assess reliability in greater detail as well as the responsiveness of the measure. Trial registration: The study

YAtiML: Mapping YAML to Python and back, with validation.

YAtiML YAML-based file formats can be very handy, as YAML is easy to write by humans, and parsing support for it is widely available. Just read your YAML file into a document structure (a tree of nested dicts and lists), and manipulate that in your code. As long as that YAML file contains exactly what you expect, that works fine. But if it contains a mistake, then you're likely to crash the program with a cryptic error message, or worse (especially if the YAML file was loaded from the Internet) it may do something unexpected. To avoid that, you can validate your YAML using various schema checkers. You write a description of what your YAML file must look like, then feed that to a library which checks the incoming file against the description. That gives you a better error message, but it's a lot of work. YAtiML takes a different approach. Instead of a schema, you write a Python class. You probably already know how to do that, so no need to learn anything. YAtiML then generates loading and dumping functions for you, which convert between YAML and Python objects. If needed, you can add some extra code to make the YAML look nicer or implement special features. 0.10.0 Incompatible changes Ignore abstract base classes (abc.ABC and/or abstractmethod) New functionality Easier-to-understand error messages Installation via Conda (already worked, now documented) Small documentation improvements Python 3.11 support Compatibility with ruamel.yaml 0.17 Fixes Bug in map_attribute_to_index Removed Support for Python 3.6 </ul

MDStudio

A general framework for microservice based distributed applications

Non-intrusive and semi-intrusive uncertainty quantification of a multiscale in-stent restenosis model

The In-Stent Restenosis 2D model is a full y coupled multiscale simulation of post-stenting tissue growth, in which the most costly submodel is the blood flow simulation. This paper presents uncertainty estimations of the response of this model, as obtained by both non-intrusive and semi-intrusive uncertainty quantification. A surrogate model based on Gaussian process regression for non-intrusive uncertainty quantification takes the whole model as a black-box and maps directly the three uncertain inputs to the quantity of interest, the neointimal area. The corresponding uncertain estimates matched the results from quasi-Monte Carlo simulations well. In the semi-intrusive uncertaint