Learning-Based Predictive Control with Gaussian Processes: An Application to Urban Drainage Networks

© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksMany traditional control solutions in urban drainage networks suffer from unmodelled nonlinear effects such as rain and wastewater infiltrating the system. These effects are challenging and often too complex to capture through physical modelling without using a high number of flow sensors. In this article, we use level sensors and design a stochastic model predictive controller by combining nominal dynamics (hydraulics) with unknown nonlinearities (hydrology) modelled as Gaussian processes. The Gaussian process model provides residual uncertainties trained via the level measurements and captures the effect of the hydrologic load and the transport dynamics in the network. To show the practical effectiveness of the approach, we present the improvement of the closed-loop control performance on an experimental laboratory setup using real rain and wastewater flow data.Peer ReviewedPostprint (author's final draft

Evolutionary-game-based dynamical tuning for multi-objective model predictive control

Model predictive control (MPC) is one of the most used optimization-based control strategies for large-scale systems, since this strategy allows to consider a large number of states and multi-objective cost functions in a straightforward way. One of the main issues in the design of multi-objective MPC controllers, which is the tuning of the weights associated to each objective in the cost function, is treated in this work. All the possible combinations of weights within the cost function affect the optimal result in a given Pareto front. Furthermore, when the system has time-varying parameters, e.g., periodic disturbances, the appropriate weight tuning might also vary over time. Moreover, taking into account the computational burden and the selected sampling time in the MPC controller design, the computation time to find a suitable tuning is limited. In this regard, the development of strategies to perform a dynamical tuning in function of the system conditions potentially improves the closed-loop performance. In order to adapt in a dynamical way the weights in the MPC multi-objective cost function, an evolutionary-game approach is proposed. This approach allows to vary the prioritization weights in the proper direction taking as a reference a desired region within the Pareto front. The proper direction for the prioritization is computed by only using the current system values, i.e., the current optimal control action and the measurement of the current states, which establish the system cost function over a certain point in the Pareto front. Finally, some simulations of a multi-objective MPC for a real multi-variable case study show a comparison between the system performance obtained with static and dynamical tuning.Peer ReviewedPostprint (author's final draft

Structural properties and stability of the betaine-urea natural deep eutectic solvents

Plant science

Natural deep eutectic solvents as biofilm structural breakers

Plant science

Tractostorm 2 : Optimizing tractography dissection reproducibility with segmentation protocol dissemination

The segmentation of brain structures is a key component of many neuroimaging studies. Consistent anatomical definitions are crucial to ensure consensus on the position and shape of brain structures, but segmentations are prone to variation in their interpretation and execution. White-matter (WM) pathways are global structures of the brain defined by local landmarks, which leads to anatomical definitions being difficult to convey, learn, or teach. Moreover, the complex shape of WM pathways and their representation using tractography (streamlines) make the design and evaluation of dissection protocols difficult and time-consuming. The first iteration of Tractostorm quantified the variability of a pyramidal tract dissection protocol and compared results between experts in neuroanatomy and nonexperts. Despite virtual dissection being used for decades, in-depth investigations of how learning or practicing such protocols impact dissection results are nonexistent. To begin to fill the gap, we evaluate an online educational tractography course and investigate the impact learning and practicing a dissection protocol has on interrater (groupwise) reproducibility. To generate the required data to quantify reproducibility across raters and time, 20 independent raters performed dissections of three bundles of interest on five Human Connectome Project subjects, each with four timepoints. Our investigation shows that the dissection protocol in conjunction with an online course achieves a high level of reproducibility (between 0.85 and 0.90 for the voxel-based Dice score) for the three bundles of interest and remains stable over time (repetition of the protocol). Suggesting that once raters are familiar with the software and tasks at hand, their interpretation and execution at the group level do not drastically vary. When compared to previous work that used a different method of communication for the protocol, our results show that incorporating a virtual educational session increased reproducibility. Insights from this work may be used to improve the future design of WM pathway dissection protocols and to further inform neuroanatomical definitions.Peer reviewe

Search for anomalous t t-bar production in the highly-boosted all-hadronic final state

A search is presented for a massive particle, generically referred to as a Z', decaying into a t t-bar pair. The search focuses on Z' resonances that are sufficiently massive to produce highly Lorentz-boosted top quarks, which yield collimated decay products that are partially or fully merged into single jets. The analysis uses new methods to analyze jet substructure, providing suppression of the non-top multijet backgrounds. The analysis is based on a data sample of proton-proton collisions at a center-of-mass energy of 7 TeV, corresponding to an integrated luminosity of 5 inverse femtobarns. Upper limits in the range of 1 pb are set on the product of the production cross section and branching fraction for a topcolor Z' modeled for several widths, as well as for a Randall--Sundrum Kaluza--Klein gluon. In addition, the results constrain any enhancement in t t-bar production beyond expectations of the standard model for t t-bar invariant masses larger than 1 TeV.Comment: Submitted to the Journal of High Energy Physics; this version includes a minor typo correction that will be submitted as an erratu

Estimating the delay between host infection and disease (incubation period) and assessing its significance to the epidemiology of plant diseases.

Knowledge of the incubation period of infectious diseases (time between host infection and expression of disease symptoms) is crucial to our epidemiological understanding and the design of appropriate prevention and control policies. Plant diseases cause substantial damage to agricultural and arboricultural systems, but there is still very little information about how the incubation period varies within host populations. In this paper, we focus on the incubation period of soilborne plant pathogens, which are difficult to detect as they spread and infect the hosts underground and above-ground symptoms occur considerably later. We conducted experiments on Rhizoctonia solani in sugar beet, as an example patho-system, and used modelling approaches to estimate the incubation period distribution and demonstrate the impact of differing estimations on our epidemiological understanding of plant diseases. We present measurements of the incubation period obtained in field conditions, fit alternative probability models to the data, and show that the incubation period distribution changes with host age. By simulating spatially-explicit epidemiological models with different incubation-period distributions, we study the conditions for a significant time lag between epidemics of cryptic infection and the associated epidemics of symptomatic disease. We examine the sensitivity of this lag to differing distributional assumptions about the incubation period (i.e. exponential versus Gamma). We demonstrate that accurate information about the incubation period distribution of a pathosystem can be critical in assessing the true scale of pathogen invasion behind early disease symptoms in the field; likewise, it can be central to model-based prediction of epidemic risk and evaluation of disease management strategies. Our results highlight that reliance on observation of disease symptoms can cause significant delay in detection of soil-borne pathogen epidemics and mislead practitioners and epidemiologists about the timing, extent, and viability of disease control measures for limiting economic loss.ML thanks the Institut Technique français de la Betterave industrielle (ITB) for funding this project. CAG and JANF were funded by the UK’s Biotechnology and Biological Sciences Research Council (BBSRC). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Evidence for Positive Selection in Putative Virulence Factors within the Paracoccidioides brasiliensis Species Complex

Paracoccidioides brasiliensis is a dimorphic fungus that is the causative agent of paracoccidioidomycosis, the most important prevalent systemic mycosis in Latin America. Recently, the existence of three genetically isolated groups in P. brasiliensis was demonstrated, enabling comparative studies of molecular evolution among P. brasiliensis lineages. Thirty-two gene sequences coding for putative virulence factors were analyzed to determine whether they were under positive selection. Our maximum likelihood–based approach yielded evidence for selection in 12 genes that are involved in different cellular processes. An in-depth analysis of four of these genes showed them to be either antigenic or involved in pathogenesis. Here, we present evidence indicating that several replacement mutations in gp43 are under positive balancing selection. The other three genes (fks, cdc42 and p27) show very little variation among the P. brasiliensis lineages and appear to be under positive directional selection. Our results are consistent with the more general observations that selective constraints are variable across the genome, and that even in the genes under positive selection, only a few sites are altered. We present our results within an evolutionary framework that may be applicable for studying adaptation and pathogenesis in P. brasiliensis and other pathogenic fungi

Participation of Actin on Giardia lamblia Growth and Encystation

BACKGROUND:Microfilaments play a determinant role in different cell processes such as: motility, cell division, phagocytosis and intracellular transport; however, these structures are poorly understood in the parasite Giardia lamblia. METHODOLOGY AND PRINCIPAL FINDINGS:By confocal microscopy using TRITC-phalloidin, we found structured actin distributed in the entire trophozoite, the label stand out at the ventral disc, median body, flagella and around the nuclei. During Giardia encystation, a sequence of morphological changes concurrent to modifications on the distribution of structured actin and in the expression of actin mRNA were observed. To elucidate whether actin participates actively on growth and encystation, cells were treated with Cytochalasin D, Latrunculin A and Jasplakinolide and analyzed by confocal and scanning electron microscopy. All drugs caused a growth reduction (27 to 45%) and changes on the distribution of actin. Besides, 60 to 80% of trophozoites treated with the drugs, exhibited damage at the caudal region, alterations in the flagella and wrinkles-like on the plasma membrane. The drugs also altered the cyst-yield and the morphology, scanning electron microscopy revealed diminished cytokinesis, cysts with damages in the wall and alterations in the size and on the intermembranal space. Furthermore, the drugs caused a significant reduction of the intensity of fluorescence-labeled CWP1 on ESV and on cyst wall, this was coincident with a reduction of CWP1 gene expression (34%). CONCLUSIONS AND SIGNIFICANCE:All our results, indicated an important role of actin in the morphology, growth and encystation and indirectly suggested an actin role in gene expression