Immersed boundary method: performance analysis of popular finite element spaces

The aim of this paper is to understand the performances of different finite elements in the space discretization of the Finite Element Immersed Boundary Method. In this exploration we will analyze two popular solution spaces: Hood-Taylor and Bercovier- Pironneau (P1-iso-P2). Immersed boundary solution is characterized by pressure discontinuities at fluid structure interface. Due to such a discontinuity a natural enrichment choice is to add piecewise constant functions to the pressure space. Results show that P1 + P0 pressure spaces are a significant cure for the well known “boundary leakage” affecting IBM. Convergence analysis is performed, showing how the discontinuity in the pressure is affecting the convergence rate for our finite element approximation

Mass preserving distributed langrage multiplier approach to immersed boundary method

This research is devoted to mass conservation and CFL properties of the Finite Elements Immersed Boundary Method. We first explore an enhanced higher order scheme applied to the Finite Element Immersed Boundary Method technique introduced by Boffi and Gastaldi. This technique is based on a Pointwise (PW) formulation of the kinematic condition, and higher order elements show better conservation properties than the original scheme. A further improvement with respect to the classical PW formulation is achieved introducing a fully variational Distributed Lagrange Multiplier (DLM) formulation. Numerical experiments show that DLM is not affected by any CFL condition. Furthermore the mass conservation properties of this method are extremely competitive

A Platform for 3D Tracking of Single Molecules in Living Cells

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PLANT: A Method for Detecting Changes of Slope in Noisy Trajectories

Time traces obtained from a variety of biophysical experiments contain valuable information on underlying processes occurring at the molecular level. Accurate quantification of these data can help explain the details of the complex dynamics of biological systems. Here, we describe PLANT (Piecewise Linear Approximation of Noisy Trajectories), a segmentation algorithm that allows the reconstruction of time-trace data with constant noise as consecutive straight lines, from which changes of slopes and their respective durations can be extracted. We present a general description of the algorithm and perform extensive simulations to characterize its strengths and limitations, providing a rationale for the performance of the algorithm in the different conditions tested. We further apply the algorithm to experimental data obtained from tracking the centroid position of lymphocytes migrating under the effect of a laminar flow and from single myosin molecules interacting with actin in a dual-trap force-clamp configuration.The authors gratefully acknowledge financial support fromthe European Commission (FP7-ICT-2011-7, grant number 288263), Erasmus Mundus Doctorate Program Europhoton-ics (grant number 159224-1-2009-1-FR-ERA MUNDUS-EMJD), Spanish Ministry of Economy and Competi-tiveness (“Severo Ochoa” Programme for Centres of Excellence in Research & Development SEV-2015-0522,and FIS2014-56107-R grants), Generalitat de Catalunyathrough the CERCA program, Italian Ministry of Uni-versity and Research (FIRB “Futuro in Ricerca” 2013grant n. RBFR13V4M2 and Flagship Project NANOMAX),Fundaci ́o Privada CELLEX (Barcelona), Ente Cassa diRisparmio di Firenze, Human Frontier Science Program (GARGP0027/2012) and LaserLab Europe 4 (GA 654148). C.M.acknowledges funding from the Spanish Ministry of Econ-omy and Competitiveness (MINECO) and the EuropeanSocial Fund (ESF) through the Ram ́on y Cajal program 2015(RYC-2015-17896).Peer ReviewedPostprint (author's final draft

Spatial, spatio-temporal, and origin-destination flow analyses of patients with severe acute respiratory syndrome hospitalized for COVID-19 in Southeastern Brazil, 2020-2021

Brazil experienced one of the fastest increasing numbers of coronavirus disease (COVID-19) cases worldwide. The Sao Paulo State (SPS) reported a high incidence, particularly in Sao Paulo municipality. This study aimed to identify clusters of incidence and mortality of hospitalized patients with severe acute respiratory syndrome for COVID-19 in the SPS, in 2020–2021, and describe the origin flow pattern of the cases. Cases and mortality risk area clusters were identified through different analyses (spatial clusters, spatio-temporal clusters, and spatial variation in temporal trends) by weighting areas. Ripley’s K12-function verified the spatial dependence between the cases and infrastructure. There were 517,935 reported cases, with 152,128 cases resulting in death. Of the 470,441 patients hospitalized and residing in the SPS, 357,526 remained in the original municipality, while 112,915 did not. Cases and death clusters were identified in the Sao Paulo metropolitan region (SPMR) and Baixada Santista region in the first study period, and in the SPMR and the Campinas, Sao Jose do Rio Preto, Barretos, and Sorocaba municipalities during the second period. We highlight the priority areas for control and surveillance actions for COVID-19, which could lead to better outcomes in future outbreaks