Using Lexis Objects for Multi-State Models in R

The Lexis class in the R package Epi provides tools for creation, manipulation and display of data from multi-state models. Transitions between states are described by rates (intensities); Lexis objects represent this kind of data and provide tools to show states and transitions annotated by relevant summary numbers. Data can be transformed to a form that allows modelling of several transition rates with common parameters.

Lexis: An R Class for Epidemiological Studies with Long-Term Follow-Up

The Lexis class in the R package Epi provides an object-based framework for managing follow-up time on multiple time scales, which is an important feature of prospective epidemiological studies with long duration. Follow-up time may be split either into fixed time bands, or on individual event times and the split data may be used in Poisson regression models that account for the evolution of disease risk on multiple time scales. The summary and plot methods for Lexis objects allow inspection of the follow-up times.

Fisher-Wright model with deterministic seed bank and selection

Seed banks are a common characteristics to many plant species, which allow storage of genetic diversity in the soil as dormant seeds for various periods of time. We investigate an above-ground population following a Fisher-Wright model with selection coupled with a deterministic seed bank assuming the length of the seed bank is kept constant and the number of seeds is large. To assess the combined impact of seed banks and selection on genetic diversity, we derive a general diffusion model. The applied techniques outline a path of approximating a stochastic delay differential equation by an appropriately rescaled stochastic differential equation, which is a common issue in statistical physics. We compute the equilibrium solution of the site-frequency spectrum and derive the times to fixation of an allele with and without selection. Finally, it is demonstrated that seed banks enhance the effect of selection onto the site-frequency spectrum while slowing down the time until the mutation-selection equilibrium is reached

The Third Degree / words by Theo Bendix

Cover: photo of tree persons in the living room, two men standing and a woman sitting on a chair; Publisher: Theo Bendix Music Pub. (New York)https://egrove.olemiss.edu/sharris_b/1097/thumbnail.jp

Using neural networks for high-speed blood cell classification in a holographic-microscopy flow-cytometry system

High-throughput cell sorting with flow cytometers is an important tool in modern clinical cell studies. Most cytometers use biomarkers that selectively bind to the cell, but induce significant changes in morphology and inner cell processes leading sometimes to its death. This makes label-based cell sorting schemes unsuitable for further investigation. We propose a label-free technique that uses a digital inline holographic microscopy for cell imaging and an integrated, optical neural network for high-speed classification. The perspective of dense integration makes it attractive to ultrafast, large-scale cell sorting. Network simulations for a ternary classification task (monocytes/granulocytes/lymphocytes) resulted in 89% accuracy

High-field (high-frequency) EPR spectroscopy and structural characterization of a novel manganese(III) corrole

The X-ray structure, magnetic susceptibility, and high-field (high-frequency) EPR spectrum of manganese 5,10,15-tris(pentafluorophenyl) corrole unambiguously establish that the complex contains an isolated, slightly rhombic, manganese(III) center

The Great Name Waltzes

https://digitalcommons.library.umaine.edu/mmb-ps/3105/thumbnail.jp