Synchronisation and control of proliferation in cycling cell population models with age structure

International audienceWe present and analyse in this article a mathematical question with a biological origin, the theoretical treatment of which may have far-reaching implications in the practical treatment of cancers. Starting from biological and clinical observations on cancer cells, tumourbearing laboratory rodents, and patients with cancer, we ask from a theoretical biology viewpoint questions that may be transcribed, using physiologically based modelling of cell proliferation dynamics, into mathematical questions. We then show how recent fluorescence-based image modelling techniques performed at the single cell level in proliferating cell populations allow to identify model parameters and how this may be applied to investigate healthy and cancer cell populations. Finally, we show how this modelling approach allows us to design original optimisation methods for anticancer therapeutics, in particular chronotherapeutics, by controlling eigenvalues of the differential operators underlying the cell proliferation dynamics, in tumour and in healthy cell populations. We propose a numerical algorithm to implement these principles

An in situ study of abyssal turbidity-current sediment plumes generated by a deep seabed polymetallic nodule mining preprototype collector vehicle

An in situ study to investigate the dynamics of sediment plumes near the release from a deep seabed polymetallic nodule mining preprototype collector vehicle was conducted in the Clarion Clipperton Zone in the Pacific Ocean 4500-m deep. The experiments reveal that the excess density of the released sediment-laden water leads to a low-lying, laterally spreading turbidity current. At the time of measurement, 2 to 8% of the sediment mass were detected 2 m or higher above the seabed and were not observed to settle over several hours, with the remaining 92 to 98% below 2 m and some fraction of that locally deposited. Our results suggest that turbidity current dynamics sets the fraction of sediment remaining suspended and the scale of the subsequent ambient sediment plume. The implications of this process, which is characteristically overlooked in previous modeling efforts, are substantial for plume modeling that will lie at the heart of environmental impact statements for regulatory consideration

Sensitivity study on the main tidal constituents of the Gulf of Tonkin by using the frequency-domain tidal solver in T-UGOm

International audienc

STochastic OPTimization library in C++

The STochastic OPTimization library (StOpt) aims at providing tools in C++ for solving somestochastic optimization problems encountered in finance or in the industry.A python binding is available for some C++ objects provided permitting to easily solve an optimization problem by regression.Different methods are available : dynamic programming methods based on Monte Carlo with regressions (global, local and sparse regressors), for underlying states following some uncontrolled Stochastic Differential Equations (python binding provided). Semi-Lagrangian methods for Hamilton Jacobi Bellman general equations for underlying states following some controlled Stochastic Differential Equations (C++ only) Stochastic Dual Dynamic Programming methods to deal with stochastic stocks management problems in high dimension. A SDDP module in python is provided. To use this module, the transitional optimization problem has to written in C++ and mapped to python (examples provided). Some methods are provided to solve by Monte Carlo some problems where the underlying stochastic state is controlled. Some pure Monte Carlo Methods are proposed to solve some non linear PDEsFor each method, a framework is provided to optimize the problem and then simulate it out of the sample using the optimal commands previously calculated.Parallelization methods based on OpenMP and MPI are provided in this framework permitting to solve high dimensional problems on clusters.The library should be flexible enough to be used at different levels depending on the user's willingness

STochastic OPTimization library in C++

The STochastic OPTimization library (StOpt) aims at providing tools in C++ for solving somestochastic optimization problems encountered in finance or in the industry.A python binding is available for some C++ objects provided permitting to easily solve an optimization problem by regression.Different methods are available :<ul><li> dynamic programming methods based on Monte Carlo with regressions (global, local and sparse regressors), for underlying states following some uncontrolled Stochastic Differential Equations (python binding provided).<li> Semi-Lagrangian methods for Hamilton Jacobi Bellman general equations for underlying states following some controlled Stochastic Differential Equations (C++ only)<li> Stochastic Dual Dynamic Programming methods to deal with stochastic stocks management problems in high dimension. A SDDP module in python is provided. To use this module, the transitional optimization problem has to written in C++ and mapped to python (examples provided).<li> Some methods are provided to solve by Monte Carlo some problems where the underlying stochastic state is controlled.<li> Some pure Monte Carlo Methods are proposed to solve some non linear PDEs</ul>For each method, a framework is provided to optimize the problem and then simulate it out of the sample using the optimal commands previously calculated.Parallelization methods based on OpenMP and MPI are provided in this framework permitting to solve high dimensional problems on clusters.The library should be flexible enough to be used at different levels depending on the user's willingness

Water mass circulation and residence time using Eulerian approach in a large coastal lagoon (Nokoué Lagoon, Benin, West Africa)

International audienceSeasonal water circulation and residence times in the large (150 km$^2$) and shallow (1.3 m average dry season depth) Nokoué Lagoon (Benin) are analyzed by means of numerical simulations using the three-dimensional SYMPHONIE model. The average circulation during the four primary hydrological periods throughout the year are studied in detail. Despite the lagoon's shallowness, significant disparities between surface and bottom conditions are observed. During the flood season (September-November), substantial river inflow (∼1200 m$^3$/s) leads to nearly barotropic currents (∼7 cm/s), ‘directly’ linking rivers to the Atlantic Ocean. Rapid flushing results in short water residence times ranging from 3 to 16 days, with freshwater inflow and winds driving lagoon dynamics. During the salinization period (December-January) the circulation transforms into an estuarine pattern, characterized by surface water exiting and oceanic water entering the lagoon at the bottom. Average currents (∼2 cm/s) and recirculation cells are relatively weak, resulting in a prolonged residence time of approximately 4 months. Circulation during this time is dominated by tides, the ocean-lagoon salinity gradient, wind, and river discharge (∼100 m3/s). During low-water months (February to June), minimal river inflow and low lagoon water-levels prevail. Predominant southwest winds generate a small-scale circulation (∼3 cm/s) with a complex pattern of multiple recirculation and retention cells. Residence times vary from 1 to 4 months, declining from February to June. During the lagoon's desalination season (July-August), increasing river inflows again establish a direct river-ocean connection, and average residence times reduce to ∼20 days. Notably, a critical river discharge threshold (∼50-100 m$^3$/s) is identified, beyond which the lagoon empties within days. This study highlights how wind-driven circulation between December and June can trap water along with potential pollutants, while river inflows, tides, and the ocean-lagoon salinity gradient facilitate water discharge. Additionally, it explores the differences between residence and flushing times, as well as some of the limitations identified in the simulations use

Modelado del penacho del río Ebro. Validación con medidas de campo

The spreading of the plume induced by the freshwater discharge from the Ebro River into northwestern Mediterranean coastal waters was modelled using two numerical codes. The coastal current field was obtained with a finite difference hydrodynamic model based on a steady-state version of the shallow-water equations, whereas the freshwater dispersion was calculated with a Lagrangian code that solves the 3D convection-diffusion equation and reproduces turbulent diffusion using a random-walk algorithm. The agreement obtained between numerical results, satellite observations and field measurements allows an analysis of the more relevant physical mechanisms and the corresponding tuning of the two models. The results show that local hydrodynamics near the river mouth, and consequently the spreading of the river plume, are highly dependent on the driving river discharge and wind field characteristics.Se presenta la simulación del penacho de agua dulce resultante de la descarga del río Ebro en el Mediterráneo mediante el uso secuencial de dos modelos numéricos. La hidrodinámica costera ha sido obtenida con un modelo en diferencias finitas, basado en una versión estacionaria de las ecuaciones para aguas someras, mientras que la dispersión del agua aportada por el Ebro se ha calculado con un modelo lagrangiano de partículas que resuelve la ecuación de transporte 3D. El ajuste obtenido entre los resultados numéricos, medidas de campo y observaciones desde satélite permiten analizar los mecanismos físicos más relevantes, así como realizar el correspondiente calibrado de ambos modelos. Los resultados muestran que la hidrodinámica local cerca de la desembocadura del río y, por consiguiente, la dispersión del penacho del río, dependen principalmente del volumen de descarga del río y de la características del viento dominante

Modelling of the Ebro River plume. Validation with field observations

The spreading of the plume induced by the freshwater discharge from the Ebro River into northwestern Mediterranean coastal waters was modelled using two numerical codes. The coastal current field was obtained with a finite difference hydrodynamic model based on a steady-state version of the shallow-water equations, whereas the freshwater dispersion was calculated with a Lagrangian code that solves the 3D convection-diffusion equation and reproduces turbulent diffusion using a random-walk algorithm. The agreement obtained between numerical results, satellite observations and field measurements allows an analysis of the more relevant physical mechanisms and the corresponding tuning of the two models. The results show that local hydrodynamics near the river mouth, and consequently the spreading of the river plume, are highly dependent on the driving river discharge and wind field characteristics