Armando G. M. Neves

Bio: Armando G. M. Neves is an academic researcher from Universidade Federal de Minas Gerais. The author has contributed to research in topics: Population & Moran process. The author has an hindex of 6, co-authored 24 publications receiving 134 citations.

Extremely rare interbreeding events can explain neanderthal DNA in living humans.

Abstract: Considering the recent experimental discovery of Green et al that present-day non-Africans have 1 to of their nuclear DNA of Neanderthal origin, we propose here a model which is able to quantify the genetic interbreeding between two subpopulations with equal fitness, living in the same geographic region. The model consists of a solvable system of deterministic ordinary differential equations containing as a stochastic ingredient a realization of the neutral Wright-Fisher process. By simulating the stochastic part of the model we are able to apply it to the interbreeding ofthe African ancestors of Eurasians and Middle Eastern Neanderthal subpopulations and estimate the only parameter of the model, which is the number of individuals per generation exchanged between subpopulations. Our results indicate that the amount of Neanderthal DNA in living non-Africans can be explained with maximum probability by the exchange of a single pair of individuals between the subpopulations at each 77 generations, but larger exchange frequencies are also allowed with sizeable probability. The results are compatible with a long coexistence time of 130,000 years, a total interbreeding population of order individuals, and with all living humans being descendants of Africans both for mitochondrial DNA and Y chromosome.

Predicting the evolution of the COVID-19 epidemic with the A-SIR model: Lombardy, Italy and S\~ao Paulo state, Brazil

Abstract: The presence of a large number of infected individuals with few or no symptoms is an important epidemiological difficulty and the main mathematical feature of COVID-19. The A-SIR model, i.e. a SIR (Susceptible-Infected-Removed) model with a compartment for infected individuals with no symptoms or few symptoms was proposed by Giuseppe Gaeta, arXiv:2003.08720 [q-bio.PE] (2020). In this paper we investigate a slightly generalized version of the same model and propose a scheme for fitting the parameters of the model to real data using the time series only of the deceased individuals. The scheme is applied to the concrete cases of Lombardy, Italy and Sao Paulo state, Brazil, showing different aspects of the epidemics. For each case we show that we may have good fits to the data up to the present, but with very large differences in the future behavior. The reasons behind such disparate outcomes are the uncertainty on the value of a key parameter, the probability that an infected individual is fully symptomatic, and on the intensity of the social distancing measures adopted. This conclusion enforces the necessity of trying to determine the real number of infected individuals in a population, symptomatic or asymptomatic.

Eigenmodes and eigenfrequencies of vibrating elliptic membranes: a Klein oscillation theorem and numerical calculations

Abstract: We give a complete proof of the existence of an infinite set of eigenmodes for a vibrating elliptic membrane in one to one correspondence with the well-known eigenmodes for a circular membrane. More exactly, we show that for each pair $(m,n) \in \{0,1,2, \cdots\}^2$ there exists a unique even eigenmode with $m$ ellipses and $n$ hyperbola branches as nodal curves and, similarly, for each $(m,n) \in \{0,1,2, \cdots\}\times \{1,2, \cdots\}$ there exists a unique odd eigenmode with $m$ ellipses and $n$ hyperbola branches as nodal curves. Our result is based on directly using the separation of variables method for the Helmholtz equation in elliptic coordinates and in proving that certain pairs of curves in the plane of parameters $a$ and $q$ cross each other at a single point. As side effects of our proof, a new and precise method for numerically calculating the eigenfrequencies of these modes is presented and also approximate formulae which explain rather well the qualitative asymptotic behavior of the eigenfrequencies for large eccentricities.

Applications of the Galton–Watson process to human DNA evolution and demography

Abstract: We show that the problem of existence of a mitochondrial Eve can be understood as an application of the Galton‐Watson process and presents interesting analogies with critical phenomena in Statistical Mechanics. In the approximation of small survival probability, and assuming limited progeny, we are able to find for a genealogic tree the maximum and minimum survival probabilities over all probability distributions for the number of children per woman constrained to a given mean. As a consequence, we can relate existence of a mitochondrial Eve to quantitative demographic data of early mankind. In particular, we show that a mitochondrial Eve may exist even in an exponentially growing population, provided that the mean number of children per woman N is constrained to a small range depending on the probability p that a child is a female. Assuming that the value p … 0:488 valid nowadays has remained fixed for thousands of generations, the range where a mitochondrial Eve occurs with sizeable probability is 2:0492 < N < 2:0510. We also consider the problem of joint existence of a mitochondrial Eve and a Y chromosome Adam. We remark why this problem may not be treated by two independent Galton‐Watson processes and present some simulation results suggesting that joint existence of Eve and Adam occurs with sizeable probability in the same N range. Finally, we show that the Galton‐Watson process may be a useful approximation in treating biparental population models, allowing us to reproduce some results previously obtained by Chang and Derrida et al..

On the antiquity of language: The reinterpretation of Neandertal linguistic capacities and its consequences

Abstract: It is usually assumed that modern language is a recent phenomenon, coinciding with the emergence of modern humans themselves. Many assume as well that this is the result of a single, sudden mutation giving rise to the full "modern package." However, we argue here that recognizably modern language is likely an ancient feature of our genus pre-dating at least the common ancestor of modern humans and Neandertals about half a million years ago. To this end, we adduce a broad range of evidence from linguistics, genetics, paleontology, and archaeology clearly suggesting that Neandertals shared with us something like modern speech and language. This reassessment of the antiquity of modern language, from the usually quoted 50,000-100,000 years to half a million years, has profound consequences for our understanding of our own evolution in general and especially for the sciences of speech and language. As such, it argues against a saltationist scenario for the evolution of language, and toward a gradual process of culture-gene co-evolution extending to the present day. Another consequence is that the present-day linguistic diversity might better reflect the properties of the design space for language and not just the vagaries of history, and could also contain traces of the languages spoken by other human forms such as the Neandertals.

A Complete Bibliography of the Journal of Statistical Physics: 2000{2009

Abstract: (2 + 1) [XTpXpH12, CTH11]. + [Zuc11b]. 0 [Fed17]. 1 [BELP15, CAS11, Cor16, Fed17, GDL10, GBL16, Hau16, JV19, KT12, KM19c, Li19, MN14b, Nak17, Pal11, Pan14, RT14, RBS16b, RY12, SS18c, Sug10, dOP18]. 1 + 1 [Sak18, CP15b]. 1/2 [MD10]. 1/f [FDR12]. 1/n [Per17]. 1/|x− y| [MSV10, MSV13]. 13 [DFL17]. 1 ≤ p ≤ ∞ [Dud13]. 1/f [HPF15]. 2 [AB19, ADS19, BF12, BNT13, DSS15, EKD12, Her13, Ily12, Lan10, Li12, Li19, LZ11, Ny13, Ost16, PSS16, ST14, Sch13b, TJ15, WPB15, dWL10]. 2 + 1 [dWL14]. 2.5 [BC15a]. 2R [WLEC17]. 2× 2 [CLTT13]. 3 [BCF19, BLS17, ESPP14, Kar18, SH16, SWKS14, dCCS19]. 3/2 [DK10]. 38 [Cam13]. 4 [BBS14, Zha14]. 4× 4 [LN19a]. 5/2 [DK10, EKD12]. 6 [EC11]. 8 [Zha14]. 90◦ [YM11]. 3 [Afz12]. 1−x [EFO11]. 13 [CDCL18]. 2 [ML15, QR13, ST11c]. 4 [HBB10]. 6 [BCL10a, BCL10b, EFO11]. x [EFO11].

Mathematical population genetics.

Abstract: Contents Preface Introduction 1 Historical Background 1.1 Biometricians, Saltationists and Mendelians 1.2 The Hardy-Weinberg Law 1.3 The Correlation Between Relatives 1.4 Evolution 1.4.1 The Deterministic Theory 1.4.2 Non-Random-Mating Populations 1.4.3 The Stochastic Theory 1.5 Evolved Genetic Phenomena 1.6 Modelling 1.7 Overall Evolutionary Theories 2 Technicalities and Generalizations 2.1 Introduction 2.2 Random Union of Gametes 2.3 Dioecious Populations 2.4 Multiple Alleles 2.5 Frequency-Dependent Selection 2.6 Fertility Selection 2.7 Continuous-Time Models 2.8 Non-Random-Mating Populations 2.9 The Fundamental Theorem of Natural Selection 2.10 Two Loci 2.11 Genetic Loads 2.12 Finite Markov Chains 3 Discrete Stochastic Models 3.1 Introduction 3.2 Wright-Fisher Model: Two Alleles 3.3 The Cannings (Exchangeable) Model: Two Alleles 3.4 Moran Models: Two Alleles 3.5 K-Allele Wright-Fisher Models 3.6 Infinitely Many Alleles Models 3.6.1 Introduction 3.6.2 The Wright-Fisher In.nitely Many Alleles Model 3.6.3 The Cannings In.nitely Many Alleles Model 3.6.4 The Moran In.nitely Many Alleles Model 3.7 The Effective Population Size 3.8 Frequency-Dependent Selection 3.9 Two Loci 4 Diffusion Theory 4.1 Introduction 4.2 The Forward and Backward Kolmogorov Equations 4.3 Fixation Probabilities 4.4 Absorption Time Properties 4.5 The Stationary Distribution 4.6 Conditional Processes 4.7 Diffusion Theory 4.8 Multi-dimensional Processes 4.9 Time Reversibility 4.10 Expectations of Functions of Di.usion Variables 5 Applications of Diffusion Theory 5.1 Introduction 5.2 No Selection or Mutation 5.3 Selection 5.4 Selection: Absorption Time Properties 5.5 One-Way Mutation 5.6 Two-Way Mutation 5.7 Diffusion Approximations andBoundary Conditions 5.8 Random Environments 5.9 Time-Reversal and Age Properties 5.10 Multi-Allele Diffusion Processes 6 Two Loci 6.1 Introduction 6.2 Evolutionary Properties of Mean Fitness 6.3 Equilibrium Points 6.4 Special Models 6.5 Modifier Theory 6.6 Two-Locus Diffusion Processes 6.7 Associative Overdominance and Hitchhiking 6.8 The Evolutionary Advantage of Recombination 6.9 Summary 7 Many Loci 7.1 Introduction 7.2 Notation 7.3 The Random Mating Case 7.3.1 Linkage Disequilibrium, Means and Variances 7.3.2 Recurrence Relations for Gametic Frequencies 7.3.3 Components of Variance 7.3.4 Particular Models 7.4 Non-Random Mating 7.4.1 Introduction 7.4.2 Notation and Theory 7.4.3 Marginal Fitnesses and Average Effects 7.4.4 Implications 7.4.5 The Fundamental Theorem of Natural Selection 7.4.6 Optimality Principles 7.5 The Correlation Between Relatives 7.6 Summary 8 Further Considerations 8.1 Introduction 8.2 What is Fitness? 8.3 Sex Ratio 8.4 Geographical Structure 8.5 Age Structure 8.6 Ecological Considerations 8.7 Sociobiology 9 Molecular Population Genetics: Introduction 9.1 Introduction 9.2 Technical Comments 9.3 In.nitely Many Alleles Models: Population Properties 9.3.1 The Wright-Fisher Model 9.3.2 The Moran Model 9.4 In.nitely Many Sites Models: Population Properties 9.4.1 Introduction 9.4.2 The Wright-Fisher Model 9.4.3 The Moran Model 9.5 Sample Properties of In.nitely Many Alleles Models 9.5.1 Introduction 9.5.2 The Wright-Fisher Model 9.5.3 The Moran Model 9.6 Sample Properties of In.nitely Many Sites Models 9.6.1 Introduction 9.6.2 The Wright-Fisher Model 9.6.3 The Moran Model 9.7 Relation Between In.nitely Many Alleles and Infinitely Many Sites Models 9.8 Genetic Variation Within and Between

Condition number estimates for combined potential integral operators in acoustics and their boundary element discretisation

Abstract: We consider the classical coupled combined field integral equation formulations for time-harmonic acoustic scattering by a sound soft bounded obstacle In recent work we have proved lower and upper bounds on the L-2 condition numbers for these formulations and also on the norms of the classical acoustic single- and double-layer potential operators These bounds to some extent make explicit the dependence of condition numbers on the wave number k, the geometry of the scatterer and the coupling parameter For example with the usual choice of coupling parameter they show that while the condition number grows like k(1/3) as k -> infinity when the scatterer is a circle or sphere, It can grow as fast as k(7/5) for a class of trapping obstacles In this article, we prove further bounds, sharpening and extending our previous results In particular, we show that there exist trapping obstacles for which the condition numbers grow as fast as exp(gamma k) for some gamma > 0 as k -> infinity through some sequence This result depends on exponential localization bounds on Laplace eigenfunctions in an ellipse that we prove in the appendix We also clarify the correct choice of coupling parameter in 2D for low k In the second part of the article, we focus on the boundary element discretisation of these operators We discuss the extent to which the bounds on the continuous operators are also satisfied by their discrete counterparts and via numerical experiments we provide supporting evidence for some of the theoretical results, both quantitative and asymptotic, indicating further which of the upper and lower bounds may be sharper (C) 2010 Wiley Periodicals Inc Numer Methods Partial Differential Eq 27 31-69 2011

Demography and the Palaeolithic Archaeological Record

Abstract: Demographic change has recently re-emerged as a key explanation for socio-cultural changes documented in the prehistoric archaeological record. While the majority of studies of Pleistocene demography have been conducted by geneticists, the archaeological records of the Palaeolithic should not be ignored as a source of data on past population trends. This paper forms both a comprehensive synthesis and the first critical review of current archaeological research into Palaeolithic demography. Within prevailing archaeological frameworks of dual inheritance theory and human behavioural ecology, I review the ways in which demographic change has been used as an explanatory concept within Palaeolithic archaeology. I identify and discuss three main research areas which have benefitted from a demographic approach to socio-cultural change: (1) technological stasis in the Lower Palaeolithic, (2) the Neanderthal-Homo sapiens transition in Europe and (3) the emergence of behavioural modernity. I then address the ways in which palaeodemographic methods have been applied to Palaeolithic datasets, considering both general methodological concerns and the challenges specific to this time period. Finally, I discuss the ability of ethnographic analogy to aid research into Palaeolithic demography.