We study a universal object for the genealogy of a sample in populations with mutations: the critical birth-death process with Poissonian mutations, conditioned on its population size at a fixed time horizon. We show how this process arises as the law of the genealogy of a sample in a large class of nearly critical branching populations with rare mutations at birth, namely populations converging, in a large population asymptotic, towards the continuum random tree. We extend this model to populations with random foundation times, with (potentially improper) prior distributions [Formula: see text], [Formula: see text], including the so-called uniform ([Formula: see text]) and log-uniform ([Formula: see text]) priors. We first investigate the mutational patterns arising from these models, by studying the site frequency spectrum of a sample with fixed size, i.e. the number of mutations carried by k individuals in the sample. Explicit formulae for the expected frequency spectrum of a sample are provided, in the cases of a fixed foundation time, and of a uniform and log-uniform prior on the foundation time. Second, we establish the convergence in distribution, for large sample sizes, of the (suitably renormalized) tree spanned by the sample with prior [Formula: see text] on the time of origin. We finally prove that the limiting genealogies with different priors can all be embedded in the same realization of a given Poisson point measure.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1007/s00285-015-0964-2 | DOI Listing |
Sci Rep
January 2025
Department of Anesthesiology, Changhua Christian Hospital, Changhua, 50050, Taiwan.
In the modern healthcare system, the rational allocation of emergency department (ED) resources is crucial for enhancing emergency response efficiency, ensuring patient safety, and improving the quality of medical services. This paper focuses on the issue of ED resource allocation and designs a priority sorting system for ED patients. The system classifies patients into two queues: urgent and routine.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Electrical Engineering, College of Engineering, Taif University, Taif, 21944, Saudi Arabia.
This paper presents a novel approach to modeling and controlling a solar photovoltaic conversion system(SPCS) that operates under real-time weather conditions. The primary contribution is the introduction of an uncertain model, which has not been published before, simulating the SPCS's actual functioning. The proposed robust control strategy involves two stages: first, modifying the standard Perturb and Observe (P&O) algorithm to generate an optimal reference voltage using real-time measurements of temperature, solar irradiance, and wind speed.
View Article and Find Full Text PDFSci Rep
January 2025
Institute of Biological and Chemical Systems - Functional Molecular Systems (IBCS-FMS), Karlsruhe Institute of Technology (KIT), Karlsruhe, 76344, Germany.
Multiple linear regression models were trained to predict the degree of substitution (DS) of cellulose acetate based on raw infrared (IR) spectroscopic data. A repeated k-fold cross validation ensured unbiased assessment of model accuracy. Using the DS obtained from H NMR data as reference, the machine learning model achieved a mean absolute error (MAE) of 0.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Mathematics and Statistics, College of Science, Taif University, P.O. Box 11099, 21944, Taif, Saudi Arabia.
The monkeypox virus (MPXV), which is a member of the Orthopoxvirus genus in the class Poxviridae, is the causative agent of the zoonotic viral infection MPXV. The disease is similar to smallpox, but it is usually less dangerous. This study examines the evolution of the MPXV epidemic in Canada with an emphasis on the effects of control employing actual data.
View Article and Find Full Text PDFSci Rep
January 2025
Center for Animal Welfare Science, Departments of Comparative Pathobiology and Animal Science, Purdue University, West Lafayette, IN, 47907, USA.
It is well established that maternal factors can affect the abilities of offspring to cope with stressors and can influence their overall welfare states. However, maternal effects have not been extensively explored in US commercial breeding kennels (CBKs). Therefore, the objective of this study was to identify if fear and stress in dams affected puppy welfare metrics in CBKs.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!