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Sökning: WFRF:(Johansson H) > Annan publikation

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  • Bugaytsova, Jeanna, et al. (författare)
  • pH regulated H. pylori adherence : implications for persistent infection and disease
  • Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
    • Helicobacter pylori’s BabA adhesin binds strongly to gastric mucosal ABH/Leb glycans on the stomach epithelium and overlying mucus, materials continuously shed into the acidic gastric lumen. Here we report that this binding is acid labile, acid inactivation is fully reversible; and acid lability profiles vary with BabA sequence and correlate with disease patterns. Isogenic H. pylori strains from the gastric antrum and more acidic corpus were identified that differed in acid lability of receptor binding and in sequence near BabA’s carbohydrate binding domain. We propose that reversible acid inactivation of receptor binding helps H. pylori avoid clearance by mucosal shedding, and that strain differences in acid lability affect tissue tropism and the spectrum of associated gastric diseases.
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  • Fonseca, Joana, et al. (författare)
  • Adaptive Sampling of Algal Blooms Using Autonomous Underwater Vehicle and Satellite Imagery : Experimental Validation in the Baltic Sea
  • Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
    • This paper investigates using satellite data to improve adaptive sampling missions, particularly for front tracking scenarios such as with algal blooms. Our proposed solution to find and track algal bloom fronts uses an Autonomous Underwater Vehicle (AUV) equipped with a sensor that measures the concentration of chlorophyll a and satellite data. The proposed method learns the kernel parameters for a Gaussian process (GP) model using satellite images of chlorophyll a from the previous days. Then, using the data collected by the AUV, it models chlorophyll a concentration online. We take the gradient of this model to obtain the direction of the algal bloom front and feed it to our control algorithm. The performance of this method is evaluated through realistic simulations for an algal bloom front in the Baltic sea, using the models of the AUV and the chlorophyll a sensor. We compare the performance of different estimation methods, from GP to curve interpolation using least squares. Sensitivity analysis is performed to evaluate the impact of sensor noise on the methods’ performance. We implement our method on an AUV and run experiments in the Stockholm archipelago in the summer of 2022. 
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  • Gao, Yulong, et al. (författare)
  • Robust Tube Model Predictive Control with Uncertainty Quantification for Discrete-Time Linear Systems
  • Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
    • This paper is concerned with model predictive control (MPC) of discrete-time linear systems subject to bounded additive disturbance and hard constraints on the state and input, whereas the true disturbance set is unknown. Unlike most existing work on robust MPC, we propose an MPC algorithm incorporating online uncertainty quantification that builds on prior knowledge of the disturbance, i.e., a known but conservative disturbance set. We approximate the true disturbance set at each time step with a parameterised set, which is referred to as a quantified disturbance set, using the scenario approach with additional disturbance realisations collected online. A key novelty of this paper is that the parameterisation of these quantified disturbance sets enjoy desirable properties such that the quantified disturbance set and its corresponding rigid tube bounding disturbance propagation can be efficiently updated online. We provide statistical gaps between the true and quantified disturbance sets, based on which, probabilistic recursive feasibility of MPC optimisation problems are discussed. Numerical simulations are provided to demonstrate the efficacy of our proposed algorithm and compare with conventional robust MPC algorithms.
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  • Resultat 1-10 av 35
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