Approaching human language with complex networks

The interest in modeling and analyzing human language with complex networks is on the rise in recent years and a considerable body of research in this area has already been accumulated. We survey three major lines of linguistic research from the complex network approach: 1) characterization of human language as a multi-level system with complex network analysis; 2) linguistic typological research with the application of linguistic networks and their quantitative measures; and 3) relationships between the system-level complexity of human language (determined by the topology of linguistic networks) and microscopic linguistic (e.g., syntactic) features (as the traditional concern of linguistics). We show that the models and quantitative tools of complex networks, when exploited properly, can constitute an operational methodology for linguistic inquiry, which contributes to the understanding of human language and the development of linguistics. We conclude our review with suggestions for future linguistic research from the complex network approach: 1) relationships between the system-level complexity of human language and microscopic linguistic features; 2) expansion of research scope from the global properties to other levels of granularity of linguistic networks; and 3) combination of linguistic network analysis with other quantitative studies of language (such as quantitative linguistics).     

On a Generalized Model of Biological Evolution

A model for biological evolution with relative fitness between different species is proposed. It contains both negative interactions, e.g., predation, competition, etc., and positive interactions, e.g., mutualism, sharing, etc. This is called coevolution.     

Modeling the cultural evolution of language

The paper surveys recent research on language evolution, focusing in particular on models of cultural evolution and how they are being developed and tested using agent-based computational simulations and robotic experiments. The key challenges for evolutionary theories of language are outlined and some example results are discussed, highlighting models explaining how linguistic conventions get shared, how conceptual frameworks get coordinated through language, and how hierarchical structure could emerge. The main conclusion of the paper is that cultural evolution is a much more powerful process that usually assumed, implying that less innate structures or biases are required and consequently that human language evolution has to rely less on genetic evolution.     

Biological evolution and statistical physics

This review is an introduction to theoretical models and mathematical calculations for biological evolution, aimed at physicists. The methods in the field are naturally very similar to those used in statistical physics, although the majority of publications have appeared in biology journals. The review has three parts, which can be read independently. The first part deals with evolution in fitness landscapes and includes Fisher's theorem, adaptive walks, quasispecies models, effects of finite population sizes, and neutral evolution. The second part studies models of coevolution, including evolutionary game theory, kin selection, group selection, sexual selection, speciation, and coevolution of hosts and parasites. The third part discusses models for networks of interacting species and their extinction avalanches. Throughout the review, attention is paid to giving the necessary biological information, and to pointing out the assumptions underlying the models, and their limits of validity.     

Grounding language in action and perception: From cognitive agents to humanoid robots

In this review we concentrate on a grounded approach to the modeling of cognition through the methodologies of cognitive agents and developmental robotics. This work will focus on the modeling of the evolutionary and developmental acquisition of linguistic capabilities based on the principles of symbol grounding. We review cognitive agent and developmental robotics models of the grounding of language to demonstrate their consistency with the empirical and theoretical evidence on language grounding and embodiment, and to reveal the benefits of such an approach in the design of linguistic capabilities in cognitive robotic agents. In particular, three different models will be discussed, where the complexity of the agent's sensorimotor and cognitive system gradually increases: from a multi-agent simulation of language evolution, to a simulated robotic agent model for symbol grounding transfer, to a model of language comprehension in the humanoid robot iCub. The review also discusses the benefits of the use of humanoid robotic platform, and specifically of the open source iCub platform, for the study of embodied cognition.     

Towards a Computational Comparative Neuroprimatology: Framing the language-ready brain

We make the case for developing a Computational Comparative Neuroprimatology to inform the analysis of the function and evolution of the human brain.First, we update the mirror system hypothesis on the evolution of the language-ready brain by (i) modeling action and action recognition and opportunistic scheduling of macaque brains to hypothesize the nature of the last common ancestor of macaque and human (LCA-m); and then we (ii) introduce dynamic brain modeling to show how apes could acquire gesture through ontogenetic ritualization, hypothesizing the nature of evolution from LCA-m to the last common ancestor of chimpanzee and human (LCA-c). We then (iii) hypothesize the role of imitation, pantomime, protosign and protospeech in biological and cultural evolution from LCA-c to Homo sapiens with a language-ready brain.Second, we suggest how cultural evolution in Homo sapiens led from protolanguages to full languages with grammar and compositional semantics.Third, we assess the similarities and differences between the dorsal and ventral streams in audition and vision as the basis for presenting and comparing two models of language processing in the human brain: A model of (i) the auditory dorsal and ventral streams in sentence comprehension; and (ii) the visual dorsal and ventral streams in defining “what language is about” in both production and perception of utterances related to visual scenes provide the basis for (iii) a first step towards a synthesis and a look at challenges for further research.     

Phase-Field Modelling in Extractive Metallurgy

The phase-field method has already proven its usefulness to simulate microstructural evolution for several applications, e.g., during solidification, solid-state phase transformations, fracture, etc. This wide variety of applications follows from its diffuse-interface approach. Moreover, it is straightforward to take different driving forces into account. The purpose of this paper is to give an introduction to the phase-field modelling technique with particular attention for models describing phenomena important in extractive metallurgy. The concept of diffuse interfaces, the phase-field variables, the thermodynamic driving force for microstructure evolution and the phase-field equations are discussed. Some of the possibilities to solve the equations describing microstructural evolution are also described, followed by possibilities to make the phase-field models quantitative and the phase-field modelling of the microstructural phenomena important in extractive metallurgy, i.e., multiphase field models. Finally, this paper illustrates how the phase-field method can be applied to simulate several processes taking place in extractive metallurgy and how the models can contribute to the further development or improvement of these processes.     

Bounded fitness landscapes and the evolution of the linguistic diversity

We have recently introduced a simple spatial computer simulation model to study the evolution of the linguistic diversity. The model considers processes of selective geographic colonization, linguistic anomalous diffusion and mutation. In the approach, we ascribe to each language a fitness function which depends on the number of people that speak that language. Here, we extend the aforementioned model to examine the role of saturation of the fitness on the language dynamics. We found that the dependence of the linguistic diversity on the area after colonization displays a power law regime with a nontrivial exponent in very good agreement with the measured exponent associated with the actual distribution of languages on the Earth.     

From simple to complex oscillatory behavior in metabolic and genetic control networks

We present an overview of mechanisms responsible for simple or complex oscillatory behavior in metabolic and genetic control networks. Besides simple periodic behavior corresponding to the evolution toward a limit cycle we consider complex modes of oscillatory behavior such as complex periodic oscillations of the bursting type and chaos. Multiple attractors are also discussed, e.g., the coexistence between a stable steady state and a stable limit cycle (hard excitation), or the coexistence between two simultaneously stable limit cycles (birhythmicity). We discuss mechanisms responsible for the transition from simple to complex oscillatory behavior by means of a number of models serving as selected examples. The models were originally proposed to account for simple periodic oscillations observed experimentally at the cellular level in a variety of biological systems. In a second stage, these models were modified to allow for complex oscillatory phenomena such as bursting, birhythmicity, or chaos. We consider successively (1) models based on enzyme regulation, proposed for glycolytic oscillations and for the control of successive phases of the cell cycle, respectively; (2) a model for intracellular Ca(2+) oscillations based on transport regulation; (3) a model for oscillations of cyclic AMP based on receptor desensitization in Dictyostelium cells; and (4) a model based on genetic regulation for circadian rhythms in Drosophila. Two main classes of mechanism leading from simple to complex oscillatory behavior are identified, namely (i) the interplay between two endogenous oscillatory mechanisms, which can take multiple forms, overt or more subtle, depending on whether the two oscillators each involve their own regulatory feedback loop or share a common feedback loop while differing by some related process, and (ii) self-modulation of the oscillator through feedback from the system's output on one of the parameters controlling oscillatory behavior. However, the latter mechanism may also be viewed as involving the interplay between two feedback processes, each of which might be capable of producing oscillations. Although our discussion primarily focuses on the case of autonomous oscillatory behavior, we also consider the case of nonautonomous complex oscillations in a model for circadian oscillations subjected to periodic forcing by a light-dark cycle and show that the occurrence of entrainment versus chaos in these conditions markedly depends on the wave form of periodic forcing. (c) 2001 American Institute of Physics.     

Stability and Evolution of Synonyms and Homonyms in Signaling Game

Synonyms and homonyms appear in all natural languages. We analyze their evolution within the framework of the signaling game. Agents in our model use reinforcement learning, where probabilities of selection of a communicated word or of its interpretation depend on weights equal to the number of accumulated successful communications. When the probabilities increase linearly with weights, synonyms appear to be very stable and homonyms decline relatively fast. Such behavior seems to be at odds with linguistic observations. A better agreement is obtained when probabilities increase faster than linearly with weights. Our results may suggest that a certain positive feedback, the so-called Metcalfe’s Law, possibly drives some linguistic processes. Evolution of synonyms and homonyms in our model can be approximately described using a certain nonlinear urn model.     

Implications of a Higgs interpretation of the ζ(8.3)

We consider the implications if the new state seen by the Crystal Ball collaboration in radiative -decay, the ζ(8.3), is interpreted as a Higgs boson. We show that BR(ζ→gg)<0.06 or ζ(8.3) would already have been observed at FNAL. As a consequence, there would be very significant constraints on models which go beyond the standard model (supersymmetry, composite models, technicolor, …). In particular, the minimal two-higgs doublet low-energy supersymmetric models would be ruled out. We give a sum rule restricting the number of heavy colored states which couple to ζ(8.3); remarkably, only one further generation of heavy quarks could exist. It is crucial to detect the prompt semileptonic decays from charm to confirm a Higgs interpretation.     

Evolution of the Internet AS-level topology:From nodes and edges to components

Studying the topology of infrastructure communication networks(e.g., the Internet) has become a means to understand and develop complex systems. Therefore, investigating the evolution of Internet network topology might elucidate disciplines governing the dynamic process of complex systems. It may also contribute to a more intelligent communication network framework based on its autonomous behavior. In this paper, the Internet Autonomous Systems(ASes) topology from 1998 to 2013 was studied by deconstructing and analysing topological entities on three different scales(i.e., nodes,edges and 3 network components: single-edge component M1, binary component M2 and triangle component M3). The results indicate that: a) 95% of the Internet edges are internal edges(as opposed to external and boundary edges); b) the Internet network consists mainly of internal components, particularly M2 internal components; c) in most cases, a node initially connects with multiple nodes to form an M2 component to take part in the network; d) the Internet network evolves to lower entropy. Furthermore, we find that, as a complex system, the evolution of the Internet exhibits a behavioral series,which is similar to the biological phenomena concerned with the study on metabolism and replication. To the best of our knowledge, this is the first study of the evolution of the Internet network through analysis of dynamic features of its nodes,edges and components, and therefore our study represents an innovative approach to the subject.     

Elastic and magnetoelastic effects in invar alloys

A review of the elastic behaviour of Invar alloys is given. This includes (a) ferromagnetic alloys (Fe-Ni, Fe-Pt, stainless Invar); (b) antiferromagnetic alloys (Fe-Mn, Mn- and Cr-based alloys); (c) very weak ferromagnets (ZrZn₂, Ni₃Al, Ni-Pt); (d) amorphous alloys (Fe-B). It is shown that elastic anomalies (ΔE effects) can but need not occur simultaneously with a large thermal expansion anomaly. Various magnetoelastic contributions exist (ΔE_λ, ΔE_ω, ΔE_m) which are discussed in terms of existing theoretical models. The effect associated with a volume distortion, i.e. the bulk modulus anomaly, is shown to fit into the framework of the itinerant electron model.     

Quantum chemical modelling case studies relevant to metal oxide dissolution and catalysis

Over the past 20 years quantum-chemical methods have been developed sufficiently so that they can now be applied to the elucidation of the complex mechanistic processes that occur during metal oxide dissolution and catalysis reactions. Many of the reactions occurring during these processes are not directly accessible to experimental techniques and therefore quantum-chemical modelling can be applied to probe the individual reaction steps involved in the overall mechanism. Quantum chemistry provides the means of calculating the electronic properties of solids (e.g. band structures) structural properties of solids and surfaces (for instance surface relaxation and rumpling) heats of formation and reaction, activation energies, spectroscopic excitation energies and vibrational frequencies. Three case studies are described, which have been chosen to cover a range of quantum chemical applications and methodologies. These case studies are a) the dissolution mechanism of MgO, b) the parameterisation of titanium dioxide for the determination of electronic properties and c) the mechanism and energetics of adsorption of Pd onto rutile. These case studies utilise Hartree-Fock semiempirical andab initio quantum-chemical methods as well as density functional methodologies. A range of model types are used, namely cluster models embedded in pseudo-atoms, 3-dimensional periodic models and 2-dimensional periodic surface models.     

Piecewise Modeling the Accumulated Daily Growth of COVID-19 Deaths: The Case of the State of São Paulo,Brazil

The pandemic scenery caused by the new coronavirus, called SARS-CoV-2, increased interest in statistical models capable of projecting the evolution of the number of cases (and associated deaths) due to COVID-19 in countries, states and/or cities. This interest is mainly due to the fact that the projections may help the government agencies in making decisions in relation to procedures of prevention of the disease. Since the growth of the number of cases (and deaths) of COVID-19, in general, has presented a heterogeneous evolution over time, it is important that the modeling procedure is capable of identifying periods with different growth rates and proposing an adequate model for each period. Here, we present a modeling procedure based on the fit of a piecewise growth model for the cumulative number of deaths. We opt to focus on the modeling of the cumulative number of deaths because, other than for the number of cases, these values do not depend on the number of diagnostic tests performed. In the proposed approach, the model is updated in the course of the pandemic, and whenever a “new” period of the pandemic is identified, it creates a new sub-dataset composed of the cumulative number of deaths registered from the change point and a new growth model is chosen for that period. Three growth models were fitted for each period: exponential, logistic and Gompertz models. The best model for the cumulative number of deaths recorded is the one with the smallest mean square error and the smallest Akaike information criterion (AIC) and Bayesian information criterion (BIC) values. This approach is illustrated in a case study, in which we model the number of deaths due to COVID-19 recorded in the State of São Paulo, Brazil. The results have shown that the fit of a piecewise model is very effective for explaining the different periods of the pandemic evolution.     

Simulation of dual carbon–bromine stable isotope fractionation during 1,2-dibromoethane degradation*

We performed a model-based investigation to simultaneously predict the evolution of concentration, as well as stable carbon and bromine isotope fractionation during 1,2-dibromoethane (EDB, ethylene dibromide) transformation in a closed system. The modelling approach considers bond-cleavage mechanisms during different reactions and allows evaluating dual carbon–bromine isotopic signals for chemical and biotic reactions, including aerobic and anaerobic biological transformation, dibromoelimination by Zn(0) and alkaline hydrolysis. The proposed model allowed us to accurately simulate the evolution of concentrations and isotope data observed in a previous laboratory study and to successfully identify different reaction pathways. Furthermore, we illustrated the model capabilities in degradation scenarios involving complex reaction systems. Specifically, we examined (i) the case of sequential multistep transformation of EDB and the isotopic evolution of the parent compound, the intermediate and the reaction product and (ii) the case of parallel competing abiotic pathways of EDB transformation in alkaline solution.     

Atmospheric IR propagation

The state-of-the-art of IR atmospheric propagation modelling — important to both scientific and practical applications of IR radiation—is reviewed, based mainly on experimental work performed at the FfO. The main improvements of transmission models rely on the results of measurements, analysis and modelling of aerosol and other atmospheric particle size distributions (0.15 μm ⪷ dia ⪷ 12 mm) over land and sea, performed in the context of long-range transmission experiments and lidar probings. Remaining problem areas will be identified and discussed, e.g. continuum absorption and fog window. The modelling of turbulence-induced fluctuations of amplitude and phase is of increasing interest as related to IR atmospheric windows and relevant laser lines. Recent experimental results on phase fluctuations are discussed, especially in relation to attempts to derive a better modelling of atmospheric microturbulence (C_n).     

A New Method for the Solution of Models of Biological Evolution: Derivation of Exact Steady-State Distributions

We investigate well-known models of biological evolution and address the open problem of how construct a correct continuous analog of mutations in discrete sequence space. We deal with models where the fitness is a function of a Hamming distance from the reference sequence. The mutation-selection master equation in the discrete sequence space is replaced by a Hamilton-Jacobi equation for the logarithm of relative frequencies of different sequences. The steady-state distribution, mean fitness and the variance of fitness are derived. All our results are asymptotic in the large genome limit. A variety of important biological and biochemical models can be solved by this new approach. PACS numbers: 87.10.+e, 87.15.Aa, 87.23.Kg, 02.50.-r     

An inconsistence-free integral-based dynamic one- and two-parameter mixed model

The development of the dynamic procedure as well as the deeper understanding of the link between filtering, modelling and numerics, allowed Large Eddy Simulation (LES) to make great progresses during the last years. Among several modelling approaches, the scale-similar-based modelling is based on the observation that the smallest resolved scales are the most active in the interaction with the unresolved ones. Owing to the low dissipation introduced by the scale-similar models (SSMs), the coupling with the eddy-viscosity model is often used in the so-called mixed models. Dynamic version of mixed models is historically based on the application of the test-filtering on the differential form of the filtered momentum equation. Such an approach is used for both the one and the two-coefficients mixed models. The use of the differential form of the filtered equations produces the well-known mathematical inconsistence caused by the need to extract arbitrarily the model functions out of filtering. It is known that, along with the eddy viscosity assumption, the magnitude of the Germano identity error (GIE) is strongly influenced. The mathematical inconsistence in the extraction of the dynamic eddy viscosity coefficient was recently superseded by using the new integral-based formulation. However, owing to the intrinsic limits of the Smagorinsky model, also in those results, the GIE is still remarkable therefore, the present paper presents a new formulation to the integral-based dynamic procedure for both one and two-coefficients mixed models (IDMM). The original contributions of the present paper can be summarised: (1) A theoretical analysis comparing the spectral errors for the differential and integral-based SSM, assessing that the errors are less relevant for the integral form; (2) The implementation of one and two parameters IDMM for the simulation of turbulence in a plane channel flow, assessing the reduction of the GIE and the good behaviour of the statistics that are compared with those of the other LES codes used in the LESinItaly project.