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Sequential Two-Scale Data Assimilation
No full textIn this paper, we introduce Two Scale Data Assimilation (TSDA), a novel methodology to improve classical data assimilation methods in terms of performance while being computationally cheaper, when considering two scale problems. TSDA combines two-scale information and dynamics (microscopic and macroscopic) in order to produce better state estimates at each scale. This methodology uses the mathematical relationship between each scale using methods from homogenization theory in order to benefit from the accuracy of the microscopic observations and the low computational cost of the macroscopic dynamics with the end goal of improving the quality of the two-scale state estimate. Our conducted experiments on generated datasets considering eight realities have given a promising results.</div
Systematization of Nursing Care for Pregnant Women in Primary Health Care: An Integrative Literature Review
No full textInternational audienceThis study aimed to identify and analyze scientific productions that discuss the systematization of nursing care (SNC) for pregnant women within the scope of primary health care (PHC). This is an integrative literature review (ILR) carried out through searches in the Virtual Health Library (VHL), SciELO, PubMed and Google Scholar databases. Descriptors validated in DeCS/MeSH in Portuguese and English were used, such as: Systematization of Nursing Care, Pregnant Woman and Primary Health Care. The combination of Boolean operators “AND” and “OR” was used to refine data collection in the mentioned descriptors. For data analysis, "Content Analysis" was used, allowing the categorization of findings. The PRISMA Flow Diagram 2020 was used to guide the organization and selection of texts. The results were organized into five categories: 1. Impact of SNC on the quality of prenatal care; 2. Protagonism and autonomy of nurses in providing care to pregnant women; 3. Challenges in implementing SNC in PHC; 4. Contributions of SNC to promoting maternal health and preventing injuries; 5. SNC and comprehensiveness and equity of care in PHC. It is concluded that the use of SNC in PHC qualifies prenatal care, promoting nurse autonomy and better maternal and child outcomes. Its implementation contributes to the humanization and safety of care
Orr-Sommerfeld equation and complex deformation
No full textFor shear flows in a 2D channel, we define resonances near regular values of the shear profile for the Rayleigh equation under an analyticity assumption. This is done via complex deformation of the interval on which Rayleigh equation is considered. We show such resonances are inviscid limits of the eigenvalues of the corresponding Orr--Sommerfeld equation
A Novel Approach to Guidance and Control of USVs Combining Flatness-Based and Model-Free Controllers
No full textInternational audienceThis work presents a new approach to the guidance and control of marine craft by combining Flatness-Based and Model-Free controllers. Its goal is to develop a general regulator for Unmanned Surface Vehicles (USV). To do so, the well-known USV maneuvering model is simplified and proven to be flat. A flatness-based controller is derived for the simplified USV model and the loop is closed via an intelligent proportional derivative (iPD) regulator derived from model-free control. We thus associate the well-documented natural robustness of flatness-based control and adaptivity of iPDs. The controller is applied in simulation to two surface vessels, one meeting the simplifying hypotheses, the other one being a generic USV of the literature, and is shown to stabilize both systems even in the presence of unmodeled environmental disturbances
Phycobiostimulants: Next-Generation Sustainable Agricultural Inputs
No full textInternational audiencePlant biostimulants are a novel class of naturally derived agricultural inputs. The grouping of categories within the regulatory term “biostimulant” contains disparate inputs, such as humates, amino acids, bacteria, and algal extracts (i.e., many extraction processes applied to a relatively small group of selected seaweeds/microalgae). All seem to have the ability to improve the health and abiotic stress resistance of the treated plants. Even extracts of seaweeds (phycobiostimulants) are considerably different from one another (they are not all the same yet commonly referred to as seaweed extract, even in peer-reviewed publications), and current commercial offerings are available from a select group of green, red, and brown seaweeds. Commercial formulations combine different seaweed extracts and increasingly leverage synergies by blending biostimulants with other agricultural inputs and agrochemicals. Extensive research highlights that various algal-based extracts can effectively support both abiotic and biotic stress resistance when applied to both treated terrestrial plants and other cultivated algae. This article explores the scientific nuances of phycobiostimulants, challenging traditional regulatory classifications and emphasizing their essential role in sustainable agronomy, growing phyconomy, and global food security
Derivation of Born/von Kármán difference equations through consistent lattice angular interactions
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Identifier les dégradateurs de plastique marin par marquage isotopique de l'ADN
No full textInternational audiencePlastic biodegradation in natural environments is performed by the microbial biofilm living on its surface. This study identifies for the first time plastic degraders in marine environment, by using stable isotope tracers. Polyhydroxybutyrate (PHB) biodegradation was proved by monitoring microbial cell growth (via scanning electron microscopy and flow cytometry) and activities (via continuous oxygen consumption measurements and 3 H-leucine incorporation for protein synthesis) during 90 days. We successfully synthetized 13 C-labeled PHB and conducted DNA-stable isotope probing (DNA-SIP) experiments over different time points, which permitted the first description of key PHB degraders belonging to Marinobacter sp. and Cellvibrionaceae together with Glaciecola sp., Pseudoalteromonas sp., Celeribacter sp. and Alteromonas sp. Overall, SIP labeling combined with metabarcoding proved to be a useful tool for discovering and characterizing active plastic degraders from complex marine communities
Biodegradability of tomato stem-reinforced composites: Towards a virtuous approach to local and circular waste upcycling
No full textInternational audienceThe current method of producing tomatoes in greenhouses uses petro-sourced plastic accessories that contaminate plant waste when the greenhouses are emptied. For this reason, this study aims to develop a biodegradable material to replace plastic accessories. To evaluate the feasibility of using tomato byproduct as reinforcements in a range of biobased and biodegradable thermoplastic materials, the compound degradability was investigated though biochemical and imaging approaches. The first set of experiments carried out on the tomato stem showed that the enzymatic degradation by a mixture of cellulases and pectinases efficiently removed constitutive biopolymers, and that the average size and the polydispersity decreased during treatment. The largest particles became more irregular, highlighting the enzyme-recalcitrant domains. When compounded with different matrix polymers (PBS, PBAT/PHA or PBAT/PLA), tomato stem particles remained susceptible to enzymatic degradation. Tomography analysis showed that all the degraded samples exhibited a large increase in porosity, the largest increase being observed in the PLA-containing specimens.This fully circular approach from waste to useful compounds for horticulture and market gardening is a promising way of upcycling tomato biomass, compatible with end-of-life composting
Breaking onset and breaking strength of focused wave packets: Linear prediction model and nonlinear numerical simulations
No full textInternational audienceThe possibility of predicting the occurrence of wave breaking and the intensity of the breaking events using linear wave models is investigated. For this purpose, a new linear breaking onset criterion is proposed, based on the definition of a linear-equivalent wave, which has the same energy and impulse as the associated nonlinear wave. The strength of breaking is characterized by the parameter introduced by Derakhtiet al. (2018) and we derive an empirical law to estimate the breaking strength from the linear-equivalent wave model. The predictive ability of this criterion is assessed through comparisons with results of fully nonlinear potential flow simulations, for focused wave packets of various characteristics. For the considered configurations, the proposed approach is able to predict the onset and strength of breaking with good accuracy
Bow Echo Alarm System Using Topological Data Analysis - V2
No full textInternational audienceThis study examines the extremely severe storm that hit Corsica in the early hours of August 18, 2022.A "derecho" is a powerful storm system known for producing long-lasting and widespread destructive winds. In this case, the storm was driven by a large cluster of thunderstorms that organized into a fast-moving structure, leading to intense wind gusts across the region. The associated radar signatures generally exhibit linear characteristics, often displaying "bow echo" shapes. In this work, we study the formation and evolution of the bow echo that struck the Corsican coast, causing significant damage and multiple fatalities. Bow echoes are notoriously difficult to predict, as they can form quickly and remain quite localized. We propose using Topological Data Analysis (TDA,specifically, persistent homology, to characterize the shape evolution of a bow echo over time.From weather radar images of reflectivity, we generate point clouds corresponding to the most intense precipitation cells and compute their persistence diagrams via Vietoris-Rips filtrations. We compare persistence diagrams using the Bottleneck distance, the Wasserstein distance, and the kernel approach: the Persistence Weighted Gaussian Kernel (PWGK), the Sliced Wasserstein Kernel (SWK) and the Pertinence Fisher Kernel (PFK). We then apply hierarchical clustering, principal component analysis (PCA), and change-point detection to these distances in order to highlight major structural transitions and detect the moment when the bow echo forms. Additionally, we incorporate a curvature-based metric by measuring the ratio between the arc length and the straight length of the arc shape. We show that combining TDA-based distances with curvature measurements provides valuable insight into the storm's evolution. Finally, we introduce a discussion on triggering an alert based on the topological analysis of the bow echo. Our results suggest that TDA-based methods can help identify distinct structural changes in complex meteorological phenomena.</p