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

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

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

COVID-19 no estado de São Paulo: a evolução de uma pandemia

OBJECTIVES: To describe retrospectively severe hospitalized cases and deaths related to the COVID-19 epidemic in the state of São Paulo, starting from the date of the first record with symptoms onset on 02/10/2020 up to 05/20/2021 records. METHODS: This is a descriptive study. The data source used was from the Influenza Epidemiological Surveillance System (SIVEP-Gripe). The rates of incidence, mortality and accumulated incidence in the period were calculated, stratified by age group and Regional Health Department (DRS). In addition, severe cases were geocoded to analyze their spread across the state; and the Effective R, which determines the spread potential of a virus within a population, was calculated. RESULTS: There was a significant increase in severe cases and deaths recorded in the period of one year, with incidence and mortality rates being heterogeneous within the state. The most critical periods regarding the incidence of severe cases occurred between May and July 2020 and between March and April 2021. The DRSs in São José do Rio Preto, Grande São Paulo and Araçatuba concentrated the highest incidence and mortality rates. Severe cases and deaths were more frequent in men and in the population over 60 years, while the main risk conditions related to deaths were heart disease (59%) and diabetes (42,8%). CONCLUSIONS: These results not only provide a detailed profile for more efficient control action plan, but will also allow the historical understanding of the COVID-19 evolution within the state of São Paulo.OBJETIVOS: Descrever, de forma retrospectiva, os casos graves hospitalizados e óbitos relacionados à epidemia de COVID-19 no estado de São Paulo, desde a data do primeiro registro com início de sintomas em 10/02/2020 até registros disponíveis em 20/05/2021. MÉTODOS: Trata-se de um estudo descritivo realizado por meio da base de dados do Sistema de Vigilância Epidemiológica da Gripe (SIVEP-Gripe). Foram calculadas as taxas de incidência, mortalidade e incidência acumulada no período, estratificadas por faixa etária e Departamento Regional de Saúde (DRS). Os casos graves foram geocodificados para análise de seu espalhamento pelo estado e foi calculado o R Efetivo, que estima o potencial de propagação de um vírus dentro de uma população. RESULTADOS: Houve um aumento significativo dos casos graves e óbitos registrados no período de um ano, sendo que as taxas de incidência e mortalidade foram heterogêneas dentro do estado. Os períodos mais críticos em relação à incidência de casos graves ocorreram entre maio e julho de 2020 e entre março e abril de 2021. Os DRS de São José do Rio Preto, Grande São Paulo e Araçatuba concentraram as maiores taxas de incidência e mortalidade. Os casos graves e óbitos foram mais frequentes nos homens e na população acima de 60 anos, e as principais condições de risco relacionadas aos óbitos foram cardiopatia (59%) e diabetes (42,8%). CONCLUSÕES: Espera-se que esses resultados ofereçam embasamento e possam contribuir para uma ação de controle mais eficiente, além de permitir o entendimento histórico da evolução da COVID-19 no estado