A Phylogenetic Model of the Evolution of Discrete Matrices for the Joint Inference of Lexical and Phonological Language Histories

We propose a model of the evolution of a matrix along a phylogenetic tree, in which transformations affect either entire rows or columns of the matrix. This represents the change of both lexical and phonological aspects of linguistic data, by allowing for new words to appear and for systematic phonological changes to affect the entire vocabulary. We implement a Sequential Monte Carlo method to sample from the posterior distribution, and infer jointly the phylogeny, model parameters, and latent variables representing cognate births and phonological transformations. We successfully apply this method to synthetic and real data of moderate size

Bayesian Imputation of Revolving Doors

Political scientists and sociologists study how individuals switch back and forth between public and private organizations, for example between regulator and lobbyist positions, a phenomenon called "revolving doors". However, they face an important issue of data missingness, as not all data relevant to this question is freely available. For example, the nomination of an individual in a given public-sector position of power might be publically disclosed, but not their subsequent positions in the private sector. In this article, we adopt a Bayesian data augmentation strategy for discrete time series and propose measures of public-private mobility across the French state at large, mobilizing administrative and digital data. We relax homogeneity hypotheses of traditional hidden Markov models and implement a version of a Markov switching model, which allows for varying parameters across individuals and time and auto-correlated behaviors. We describe how the revolving doors phenomenon varies across the French state and how it has evolved between 1990 and 2022.Comment: 29 pages, 6 figures and 6 table

TraitLab: a Matlab package for fitting and simulating binary tree-like data

TraitLab is a software package for simulating, fitting and analysing tree-like binary data under a stochastic Dollo model of evolution. The model also allows for rate heterogeneity through catastrophes, evolutionary events where many traits are simultaneously lost while new ones arise, and borrowing, whereby traits transfer laterally between species as well as through ancestral relationships. The core of the package is a Markov chain Monte Carlo (MCMC) sampling algorithm that enables the user to sample from the Bayesian joint posterior distribution for tree topologies, clade and root ages, and the trait loss, catastrophe and borrowing rates for a given data set. Data can be simulated according to the fitted Dollo model or according to a number of generalized models that allow for heterogeneity in the trait loss rate, biases in the data collection process and borrowing of traits between lineages. Coupled pairs of Markov chains can be used to diagnose MCMC mixing and convergence and to debias MCMC estimators. The raw data, MCMC run output, and model fit can be inspected using a number of useful graphical and analytical tools provided within the package or imported into other popular analysis programs. TraitLab is freely available and runs within the Matlab computing environment with its Statistics and Machine Learning toolbox, no other additional toolboxes are required.Comment: Manual describing the TraitLab software for phylogenetic inferenc

Galactic chemical abundance evolution in the solar neighborhood up to the Iron peak

We have developed a detailed standard chemical evolution model to study the evolution of all the chemical elements up to the iron peak in the solar vicinity. We consider that the Galaxy was formed through two episodes of exponentially decreasing infall, out of extragalactic gas. In a first infall episode, with a duration of $\sim$ 1 Gyr, the halo and the thick disk were assembled out of primordial gas, while the thin disk formed in a second episode of infall of slightly enriched extragalactic gas, with much longer timescale. The model nicely reproduces the main observational constraints of the solar neighborhood, and the calculated elemental abundances at the time of the solar birth are in excellent agreement with the solar abundances. By the inclusion of metallicity dependent yields for the whole range of stellar masses we follow the evolution of 76 isotopes of all the chemical elements between hydrogen and zinc. Those results are confronted with a large and recent body of observational data, and we discuss in detail the implications for stellar nucleosynthesis.Comment: 19 pages, 14 figures, submitted to A&

Revisiting and modelling the woodland farming system of the early Neolithic Linear Pottery Culture (LBK), 5600–4900 B.C

International audienceThis article presents the conception and the conceptual results of a modelling representation of the farming systems of the Linearbandkeramik Culture (LBK). Assuming that there were permanent fields (PF) then, we suggest four ways that support the sustainability of such a farming system over time: a generalized pollarding and coppicing of trees to increase the productivity of woodland areas for foddering more livestock, which itself can then provide more manure for the fields, a generalized use of pulses grown together with cereals during the same cropping season, thereby reducing the needs for manure. Along with assumptions limiting bias on village and family organizations, the conceptual model which we propose for human environment in the LBK aims to be sustainable for long periods and can thereby overcome doubts about the PFs hypothesis for the LBK farming system. Thanks to a reconstruction of the climate of western Europe and the consequent vegetation pattern and productivity arising from it, we propose a protocol of experiments and validation procedures for both testing the PFs hypothesis and defining its eco-geographical area

A nationwide study of adults admitted to hospital with diabetic ketoacidosis or hyperosmolar hyperglycaemic state and COVID‐19

AimsTo investigate characteristics of people hospitalized with coronavirus-disease-2019 (COVID-19) and diabetic ketoacidosis (DKA) or hyperosmolar hyperglycaemic state (HHS), and to identify risk factors for mortality and intensive care admission.Materials and methodsRetrospective cohort study with anonymized data from the Association of British Clinical Diabetologists nationwide audit of hospital admissions with COVID-19 and diabetes, from start of pandemic to November 2021. The primary outcome was inpatient mortality. DKA and HHS were adjudicated against national criteria. Age-adjusted odds ratios were calculated using logistic regression.ResultsIn total, 85 confirmed DKA cases, and 20 HHS, occurred among 4073 people (211 type 1 diabetes, 3748 type 2 diabetes, 114 unknown type) hospitalized with COVID-19. Mean (SD) age was 60 (18.2) years in DKA and 74 (11.8) years in HHS (p < .001). A higher proportion of patients with HHS than with DKA were of non-White ethnicity (71.4% vs 39.0% p = .038). Mortality in DKA was 36.8% (n = 57) and 3.8% (n = 26) in type 2 and type 1 diabetes respectively. Among people with type 2 diabetes and DKA, mortality was lower in insulin users compared with non-users [21.4% vs. 52.2%; age-adjusted odds ratio 0.13 (95% CI 0.03-0.60)]. Crude mortality was lower in DKA than HHS (25.9% vs. 65.0%, p = .001) and in statin users versus non-users (36.4% vs. 100%; p = .035) but these were not statistically significant after age adjustment.ConclusionsHospitalization with COVID-19 and adjudicated DKA is four times more common than HHS but both associate with substantial mortality. There is a strong association of previous insulin therapy with survival in type 2 diabetes-associated DKA