Turbid but accurate: automating lysostaphin quantification including uncertainty quantification [PDF]
Microbial Cell FactoriesConventional methods for measuring antibacterial activity, such as disk-diffusion assays, have limitations in quantitative reliability and require long incubation times making them unsuitable for high-throughput applications. To address these limitations,
Lisa Prigolovkin +8 more
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Uncertainty quantification and Heston model [PDF]
Journal of Mathematics in Industry, 2018 In this paper, we study the impact of the parameters involved in Heston model by means of Uncertainty Quantification. The Stochastic Collocation Method already used for example in computational fluid dynamics, has been applied throughout this work in ...
María Suárez-Taboada +3 more
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How is a global sensitivity analysis of a catchment-scale, distributed pesticide transfer model performed? Application to the PESHMELBA model [PDF]
Geoscientific Model Development, 2023 Pesticide transfers in agricultural catchments are responsible for diffuse but major risks to water quality. Spatialized pesticide transfer models are useful tools to assess the impact of the structure of the landscape on water quality.
E. Rouzies +3 more
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Research on application method of uncertainty quantification technology in equipment test identification [PDF]
MATEC Web of Conferences, 2021 This paper introduces the concepts of equipment test qualification and uncertainty quantification, and the analysis framework and process of equipment test uncertainty quantification.
Wang Jiajia +3 more
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Benchmarking uncertainty quantification for protein engineering. [PDF]
PLoS Computational BiologyMachine learning sequence-function models for proteins could enable significant advances in protein engineering, especially when paired with state-of-the-art methods to select new sequences for property optimization and/or model improvement. Such methods
Kevin P Greenman +2 more
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Impact of ploidy and pathogen life cycle on resistance durability
Peer Community Journal, 2021 The breeding of resistant hosts based on the gene-for-gene interaction is crucial to address epidemics of plant pathogens in agroecosystems. Resistant host deployment strategies are developed and studied worldwide to decrease the probability of ...
Saubin, Méline +4 more
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loopUI-0.1: indicators to support needs and practices in 3D geological modelling uncertainty quantification [PDF]
Geoscientific Model Development, 2022 To support the needs of practitioners regarding 3D geological modelling and uncertainty quantification in the field, in particular from the mining industry, we propose a Python package called loopUI-0.1 that provides a set of local and global indicators ...
G. Pirot +13 more
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Mapping the drivers of uncertainty in atmospheric selenium deposition with global sensitivity analysis [PDF]
Atmospheric Chemistry and Physics, 2020 An estimated 0.5–1 billion people globally have inadequate intakes of selenium (Se), due to a lack of bioavailable Se in agricultural soils. Deposition from the atmosphere, especially through precipitation, is an important source of Se to soils. However,
A. Feinberg +8 more
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Uncertainty Quantification of Reactivity Scales [PDF]
ChemPhysChem, 2021 AbstractThe front cover artwork is provided by Prof. Ricardo A. Mata from the University of Göttingen. The image contrasts single‐valued reactivity parameters and distributions thereof. The latter allow chemists to better assess relative reactivity and, therefore, support synthesis planning.
Proppe, Jonny +3 more
openaire +4 more sources
The Gaussian Process Modeling Module in UQLab [PDF]
Journal of Soft Computing in Civil Engineering, 2018 We introduce the Gaussian process (GP) modeling module developed within the UQLab software framework. The novel design of the GP-module aims at providing seamless integration of GP modeling into any uncertainty quantification workflow, as well as a ...
Christos Lataniotis +2 more
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