The Krause-Hegselmann Consensus Model with Discrete Opinions

The consensus model of Krause and Hegselmann can be naturally extended to the case in which opinions are integer instead of real numbers. Our algorithm is much faster than the original version and thus more suitable for applications. For the case of a society in which everybody can talk to everybody else, we find that the chance to reach consensus is much higher as compared to other models; if the number of possible opinions Q<=7, in fact, consensus is always reached, which might explain the stability of political coalitions with more than three or four parties. For Q>7 the number S of surviving opinions is approximately the same independently of the size N of the population, as long as Q<N. We considered as well the more realistic case of a society structured like a Barabasi-Albert network; here the consensus threshold depends on the outdegree of the nodes and we find a simple scaling law for S, as observed for the discretized Deffuant model.Comment: 12 pages, 6 figure

Universality of the Threshold for Complete Consensus for the Opinion Dynamics of Deffuant et al

In the compromise model of Deffuant et al., opinions are real numbers between 0 and 1 and two agents are compatible if the difference of their opinions is smaller than the confidence bound parameter \epsilon. The opinions of a randomly chosen pair of compatible agents get closer to each other. We provide strong numerical evidence that the threshold value of \epsilon above which all agents share the same opinion in the final configuration is 1/2, independently of the underlying social topology.Comment: 8 pages, 4 figures, to appear in Int. J. Mod. Phys. C 15, issue

Scattering lengths and universality in superdiffusive L\'evy materials

We study the effects of scattering lengths on L\'evy walks in quenched one-dimensional random and fractal quasi-lattices, with scatterers spaced according to a long-tailed distribution. By analyzing the scaling properties of the random-walk probability distribution, we show that the effect of the varying scattering length can be reabsorbed in the multiplicative coefficient of the scaling length. This leads to a superscaling behavior, where the dynamical exponents and also the scaling functions do not depend on the value of the scattering length. Within the scaling framework, we obtain an exact expression for the multiplicative coefficient as a function of the scattering length both in the annealed and in the quenched random and fractal cases. Our analytic results are compared with numerical simulations, with excellent agreement, and are supposed to hold also in higher dimensionsComment: 6 pages, 8 figure

Use of intraoral three-dimensional images for the identification of dental morphological traits related to ancestry estimation

Victim identification through dental features is one of the main objectives of forensic dentistry. In circumstances where information regarding antemortem dental records is missing, reconstruction of a biological profile can be useful as a first step toward personal identification. This reconstructive method provides valuable information, namely regarding the individual's ancestry, through the detection and degree of expression of dental morphological traits, which may help to restrict the number of candidates for identification. Technological advances allowed the development of alternative methods for dental evaluation, that complement or substitute those already in use in clinical practice. Among these, intraoral three-dimensional (3D) images are increasingly used in dentistry, as they have a high level of accuracy and are easy to obtain and store. However, a fundamental question regarding forensic dentistry is whether they allow recognition and analysis of dental morphological traits in detail, namely those related to ancestry. In this study, we evaluated 20 teeth morphological features using intraoral 3D imaging from 77 individuals from Northern Portugal. Our results showed that it was possible to identify and classify a large part of the main morphological traits used in the estimation of ancestry. As these 3D images present sufficient morphological detail to be classified, we believe that future applications of this technique can be expected in forensic dentistry

Number of spanning clusters at the high-dimensional percolation thresholds

A scaling theory is used to derive the dependence of the average number of spanning clusters at threshold on the lattice size L. This number should become independent of L for dimensions d<6, and vary as log L at d=6. The predictions for d>6 depend on the boundary conditions, and the results there may vary between L^{d-6} and L^0. While simulations in six dimensions are consistent with this prediction (after including corrections of order loglog L), in five dimensions the average number of spanning clusters still increases as log L even up to L = 201. However, the histogram P(k) of the spanning cluster multiplicity does scale as a function of kX(L), with X(L)=1+const/L, indicating that for sufficiently large L the average will approach a finite value: a fit of the 5D multiplicity data with a constant plus a simple linear correction to scaling reproduces the data very well. Numerical simulations for d>6 and for d=4 are also presented.Comment: 8 pages, 11 figures. Final version to appear on Physical Review

How the mere desire for certainty can lead to a preference for men in authority (particularly among political liberals)

Women are harmed by stereotypes about their fit for positions of authority and changing these stereotypes is not a simple task. As stereotypes have strong epistemic properties, individuals with a high need for cognitive closure (NCC; i.e., the desire for epistemic certainty) can be more likely to accept these stereotypes and, consequently, to prefer men in positions of authority. Consistent with the reactive liberal hypothesis, this effect could be actually more visible among individuals with both a high NCC and left-wing political orientations. We supported these hypotheses in a series of three studies. In Study 1 (N&nbsp;=&nbsp;217), we found that manipulated NCC predicted preference for men in authority through stereotypes of women as not being fit for authority in a measurement-of-mediation design. In Study 2 (N&nbsp;=&nbsp;151), we supported this effect in a mediation-as-process design. In Study 3 (N&nbsp;=&nbsp;391), we found the indirect NCC effect on preference for men in authority was more visible among political liberals. A major implication of this work is that ways of changing the effect of these stereotypes should take into account the NCC, but particularly among individuals with left-wing beliefs

Texture Evolution During Isothermal, Isostrain, and Isobaric Loading of Polycrystalline Shape Memory NiTi

In situ neutron diffraction was used to provide insights into martensite variant microstructures during isothermal, isobaric, and isostrain loading in shape memory NiTi. The results show that variant microstructures were equivalent for the corresponding strain, and more importantly, the reversibility and equivalency were immediately evident in variant microstructures that were first formed isobarically but then reoriented to near random self-accommodated microstructures following isothermal deformation. Variant microstructures formed isothermally were not significantly affected by a subsequent thermal cycle under constant strain. In all loading cases considered, the resulting variant microstructure correlated with strain and did not correlate with stress. Based on the ability to select a variant microstructure for a given strain despite thermomechanical loading history, the results demonstrated here can be obtained by following any sequence of thermomechanical loading paths over multiple cycles. Thus, for training shape memory alloys (repeating thermomechanical cycling to obtain the desired variant microstructure), optimal paths can be selected so as to minimize the number of training cycles required, thereby increasing the overall stability and fatigue life of these alloys in actuator or medical applications

An exploration of fractal-based prognostic model and comparative analysis for second wave of COVID-19 diffusion

The coronavirus disease 2019 (COVID-19) pandemic has fatalized 216 countries across the world and has claimed the lives of millions of people globally. Researches are being carried out worldwide by scientists to understand the nature of this catastrophic virus and find a potential vaccine for it. The most possible efforts have been taken to present this paper as a form of contribution to the understanding of this lethal virus in the first and second wave. This paper presents a unique technique for the methodical comparison of disastrous virus dissemination in two waves amid five most infested countries and the death rate of the virus in order to attain a clear view on the behaviour of the spread of the disease. For this study, the data set of the number of deaths per day and the number of infected cases per day of the most affected countries, the USA, Brazil, Russia, India, and the UK, have been considered in the first and second waves. The correlation fractal dimension has been estimated for the prescribed data sets of COVID-19, and the rate of death has been compared based on the correlation fractal dimension estimate curve. The statistical tool, analysis of variance, has also been used to support the performance of the proposed method. Further, the prediction of the daily death rate has been demonstrated through the autoregressive moving average model. In addition, this study also emphasis a feasible reconstruction of the death rate based on the fractal interpolation function. Subsequently, the normal probability plot is portrayed for the original data and the predicted data, derived through the fractal interpolation function to estimate the accuracy of the prediction. Finally, this paper neatly summarized with the comparison and prediction of epidemic curve of the first and second waves of COVID-19 pandemic to visualize the transmission rate in the both times