A Probabilistic Particle Tracking Framework for Guided and Brownian Motion Systems with High Particle Densities

This paper presents a new framework for particle tracking based on a Gaussian Mixture Model (GMM). It is an extension of the state-of-the-art iterative reconstruction of individual particles by a continuous modeling of the particle trajectories considering the position and velocity as coupled quantities. The proposed approach includes an initialization and a processing step. In the first step, the velocities at the initial points are determined after iterative reconstruction of individual particles of the first four images to be able to generate the tracks between these initial points. From there on, the tracks are extended in the processing step by searching for and including new points obtained from consecutive images based on continuous modeling of the particle trajectories with a Gaussian Mixture Model. The presented tracking procedure allows to extend existing trajectories interactively with low computing effort and to store them in a compact representation using little memory space. To demonstrate the performance and the functionality of this new particle tracking approach, it is successfully applied to a synthetic turbulent pipe flow, to the problem of observing particles corresponding to a Brownian motion (e.g., motion of cells), as well as to problems where the motion is guided by boundary forces, e.g., in the case of particle tracking velocimetry of turbulent Rayleigh–Bénard convection.

C-STABILITY an innovative modeling framework to leverage the continuous representation of organic matter

The understanding of soil organic matter (SOM) dynamics has considerably advanced in recent years. It was previously assumed that most SOM consisted of recalcitrant compounds, whereas the emerging view considers SOM as a range of polymers continuously processed into smaller molecules by decomposer enzymes. Mainstreaming this new paradigm in current models is challenging because of their ill-adapted framework. We propose the C-STABILITY model to resolve this issue. Its innovative framework combines compartmental and continuous modeling approaches to accurately reproduce SOM cycling processes. C-STABILITY emphasizes the influence of substrate accessibility on SOM turnover and makes enzymatic and microbial biotransformations of substrate explicit. Theoretical simulations provide new insights on how depolymerization and decomposers ecology impact organic matter chemistry and amount during decomposition and at steady state. The flexible mathematical structure of C-STABILITY offers a promising foundation for exploring new mechanistic hypotheses and supporting the design of future experiments.

Numerical analyses of two-pile caps considering lateral friction between the piles and soil

abstract: Pile caps are structural elements used to transfer loads from the superstructure to a group of piles. The design of caps is normally based on analytical formulations, considering the strut and tie method. Through the advance of computational technology, the use of an integrated soil and foundation model may suggest a behavioral trend to obtain a more realistic modeling for the structural element being studied. This work aimed at analyzing, in numerical fashion, the structural behavior of reinforced concrete two-pile caps considering the lateral friction between the piles and the ground through a continuous modeling, as well as to analyze the portion of the load that is transferred to the ground directly by the cap. The lateral friction was modeled considering node coupling and through contact elements. Simulations were performed considering three soil types (sandy, clayish, and soilless), three cap heights, and three pile lengths. Soil parameters were obtained through semi-empirical correlations. Through these analyses, the conclusion was reached that, on average, 4.50% of the force applied to the pillar is transferred directly to the ground by cap. In terms of the principal compression stresses, in the superior nodal region, the strut tends to form beyond the section of the column. Alternatively, increasing cap stiffness provided, on average, an increase in the load carrying capacity of the models.

Confinement-induced self-organization in growing bacterial colonies

We investigate the emergence of global alignment in colonies of dividing rod-shaped cells under confinement. Using molecular dynamics simulations and continuous modeling, we demonstrate that geometrical anisotropies in the confining environment give rise to an imbalance in the normal stresses, which, in turn, drives a collective rearrangement of the cells. This behavior crucially relies on the colony’s solid-like mechanical response at short time scales and can be recovered within the framework of active hydrodynamics upon modeling bacterial colonies as growing viscoelastic gels characterized by Maxwell-like stress relaxation.

Short-Term Projection of COVID 19 Cases in Kenya using an Exponential Model

Introduction: The COVID-19 disease has spread to over 200 countries and territories since the first case was recorded in Wuhan, China in December 2019. In Kenya, the first case of COVID-19 was recorded on 13th March 2020, since then over one hundred cases have been confirmed, and three deaths recorded as of 2nd April 2020. With the rapid changing situation, timely and reliable data is required for monitoring, planning and rapid decision making with an aim of reversing the already deteriorating situation (economic, health, learning among others) in the country. Methods: The study used the exponential model to project the expected daily cumulative cases in Kenya within the first 40 days. The study opted to do a short time prediction owing to the fact that the scenario is rapidly changing. Data used in the analysis was obtained from the daily updates by the Kenya Ministry of Health, and analysis was done using Stata Version 15 and MS Excel 2010. Results: The Case Fatality Rate on day 21 was estimated as 2.7% (95% CI 0.01 – 7.80), with varying daily estimates as expected. The model estimated that the 1,000 confirmed cases will be reached by 14th April 2020 while the 4,000 cases will be reached by 21st April 2020. The results indicate that it will take 33 days for Kenya to reach the 1,000 confirmed cases and 40 days to reach the 4,000 casesConclusion: Massive screening and contact tracing of all individuals who entered the country within 28 days prior to the mandatory screening should be planned and implemented immediately with an aim of increasing the chances of getting active cases, and possible transmission through such contacts. Continuous modeling of data is needed in order to cater for other factors which were not considered in this study such as the impact of mandatory quarantine, night curfews and suspension of international flights