Search

The Fitzhugh-Nagumo neuronal model is used to explore the influence of the electric field on thermosensitive neurons' dynamics. This study investigates how the electric field affects polarization modulation in cell media induced by changes in ion charge density by adding electrical field as a new variable. Driven by a voltage source acting as an external stimulus current, different firing mode responses of the proposed model are analyzed when an external electrical field is applied. Through computational analysis, the study evaluates the impact of parameters such as cell radius, stimulus voltage source amplitude, frequency, and as well as the presence of an external electric field. The results demonstrate distinct mode transitions of isolated neurons ranging from spiking to bursting, regular and chaotic oscillations. These findings suggest that the firing mode is triggered by periodic external electric fields and cell radius, with the electric field's involvement enhanced to regulate neuron activity and control the dynamics. External electric fields and stimuli play a crucial role in neuronal firing dynamics, affecting the transition between different firing modes. Understanding these effects contributes to the comprehension of neural processes and the potential manipulation of neural activity for various applications in neuroscience and biophysics.

Experiments on field electron emission from single-tip nanoemitters have typically been carried out using a counter-electrode with a finite curvature radius $R$, positioned at a distance $d_{\rm{gap}}$ from the emitter's apex. The effects of the counter-electrode's curvature on the apex field enhancement factor ($\gamma_{\rm{Ca}}$) of the emitter are still not understood. In this Letter, we theoretically explore how the apex field enhancement factor of an emitter, represented by a hemisphere on a cylindrical post (HCP) with apex radius $r_{\rm{a}} = 50$nm, is influenced by the curvature of a spherical-shaped counter-electrode. Importantly, our results show that for HCPs with sharpness aspect ratios typically between $10^2$ and $10^3$, there is a universal scaling such that $\gamma_{\rm{Ca}} = \gamma_{\rm{Pa}} \Psi\left({R}/{d_{\rm{gap}}} \right)$, where $\gamma_{\rm{Pa}}$ represents the apex field enhancement factor for the emitter assuming a planar counter-electrode, and $\Psi\left({R}/{d_{\rm{gap}}} \right)$ is a universal scaling function such that $\Psi \sim 1$ for ${R}/{d_{\rm{gap}}} \gg 1$ and $\Psi \sim \left({R}/{d_{\rm{gap}}} \right)^{\alpha}$, with $\alpha$ close to unity, for $ {R}/{d_{\rm{gap}}} \ll 1$. These findings help partially explain discrepancies observed in orhtodox field electron emission experiments, who reported that the effective $\gamma_{\rm{Ca}}$ values extracted from the current-voltage characteristics of single-tip carbon nanotubes typically underestimate the theoretical $\gamma_{\rm{Pa}}$ values when $R \sim d_{\rm{gap}} \gg r_{\rm{a}}$, a trend that is predicted by our results., Comment: This is a revised version of our original Letter submitted to Applied Physics Letters on December 9, 2024. This revised version was resubmitted to Applied Physics Letters on January 20, 2025

Systems of oscillators whose internal phases and spatial dynamics are coupled, swarmalators, present diverse collective behaviors which in some cases lead to explosive synchronization in a finite population as a function of the coupling parameter between internal phases. Near the synchronization transition, the phase energy of the particles is represented by the XY model, and they undergo a transition which can be of the first order or second depending on the distribution of natural frequencies of their internal dynamics. The first order transition is obtained after an intermediate state (Static Wings Phase Wave state (SWPW)) from which the nodes, in cascade over time, achieve complete phase synchronization at a precise value of the coupling constant. For a particular case of natural frequencies distribution, a new phenomenon of Rotational Splintered Phase Wave state (RSpPW) is observed and leads progressively to synchronization through clusters switching alternatively from one to two and for which the frequency decreases as the phase coupling increases.

Graphics Processing Units (GPUs) are over-stressed to accelerate High-Performance Computing applications and are used to accelerate Deep Neural Networks in several domains where they have a life expectancy of many years. These conditions expose the GPUs hardware to (premature) aging, causing permanent faults to arise after the usual end-of-manufacturing test. Techniques to assess the impact of permanent faults in GPUs are then strongly required, thus allowing to estimate the reliability risk and to possibly mitigate it. In this paper, we present a method to evaluate the effects of permanent faults affecting the GPU scheduler and control units, which are the most peculiar and stressed resources, along with the first figures that allow quantifying these effects. We characterize over 5.83x10^5 permanent fault effects in the scheduler and controllers of a gate-level GPU model. Then, we map the observed error categories in software by instrumenting the code of 13 applications and two convolutional neural networks, injecting more than 1.65x10^5 permanent errors. Our two-level fault injection strategy reduces the evaluation time from hundreds of years of gate-level evaluation to hundreds of hours.We found that faults in the GPU parallelism management units can modify the opcode, the addresses, and the status of thread(s) and warp(s). The large majority (up to 99%) of these hardware permanent errors impacts the running software execution. Errors affecting the instruction operation or resource management hang the code, while 45% of errors in the parallelism management or control-flow induce silent data corruptions.

We derived the geometrical parameters on the tube connections that homogenize the pressure drop in a multi-chamber vacuum system, where each chamber has a distinct volume and all are connected to the same vacuum pump. We start deriving the pressure drop in a single chamber for a tube with finite conductance. Next, we derive a solution that provides the radius and length for each tube connection between the chambers and the pump that homogenize the pressure drop in all chambers., Comment: 14 pages, 4 figures, 1 Table, 5 references

When solving the Laplace equation numerically via computer simulation, in order to determine the field values at the surface of a shape model that represents a field emitter, it is necessary to define a simulation box and, within this, a simulation domain. This domain must not be so small that the box boundaries have an undesirable influence on the predicted field values. A recent paper discussed the situation of cylindrically symmetric emitter models that stand on one of a pair of well-separated parallel plates. This geometry can be simulated by using two-dimensional domains. For a cylindrical simulation box, formulae have previously been presented that define the minimum domain dimensions (MDD) (height and radius) needed to evaluate the apex value of the field enhancement factor for this type of model, with an error-magnitude never larger than a "tolerance" $\epsilon_{\rm{tol}}$. This MDD criterion helps to avoid inadvertent errors and oversized domains. The present article discusses (in greater depth than previously) a significant improvement in the MDD method; this improvement has been called the MDD Extrapolation Technique (MDDET). By carrying out two simulations with relatively small MDD values, it is possible to achieve a level of precision comparable with the results of carrying out a single simulation using a much larger simulation domain. For some simulations, this could result in significant savings of memory requirements and computing time. Following a brief restatement of the original MDD method, the MDDET method is illustrated by applying it to the hemiellipsoid-on-plane (HEP) and hemisphere-on-cylindrical-post (HCP) emitter shape models., Comment: 9 pages, 4 figures. Accepted for publication in JVSTB

This paper presents the optimal control and synchronization problem of a multilevel network of R\"ossler chaotic oscillators. Using the Hamilton-Jacobi-Bellman (HJB) technique, the optimal control law with three-state variables feedback is designed such that the trajectories of all the R\"ossler oscillators in the network are optimally synchronized in each level. Furthermore, we provide numerical simulations to demonstrate the effectiveness of the proposed approach for the cases of one and three networks. A perfect correlation between the MATLAB and the PSPICE results was obtained, thus allowing the experimental validation of our designed controller and shows the effectiveness of the theoretical results.

The dynamics of competing opinions in social network play an important role in society, with many applications in diverse social contexts as consensus, elections, morality and so on. Here we study a model of interacting agents connected in networks to analyze their decision stochastic process. We consider a first-neighbor interaction between agents in a one-dimensional network with a shape of ring topology. Moreover, some agents are also connected to a hub, or master node, that has preferential choice or bias. Such connections are quenched. As the main results, we observed a continuous non-equilibrium phase transition to an absorbing state as a function of control parameters. By using the finite size scaling method, we analyzed the static and dynamic critical exponents to show that this model probably cannot match any universality class already known., Comment: 14 pages, 5 tables, 4 figures

The diffusion motion of spin-bearing molecules is considerably affected in confined environments. In Nuclear Magnetic Resonance (NMR) experiments, under the presence of magnetic field gradients, this movement can be encoded in spin phase and the NMR signal attenuation due to diffusion can be evaluated. This paper considered this effect in both normal and anomalous diffusion by means of the Langevin stochastic model within the Gaussian phase approximation (GPA) for a constant gradient temporal profile. The phenomenological approach illustrates the emergence of fractional order exponential decay in the NMR signal and retrieves the classical result from Hanh echo., Comment: 8 pages, 2 figures

This review of quantitative field emitter electrostatics, covering analytical, numerical and fitted-formula approaches, is thought the first of its kind. The review relates chiefly to situations where emitters operate in an electronically ideal manner, and zero-current electrostatics is applicable. Terminology is carefully described and is polarity independent; thus the review applies to both field electron and field ion emitters. It also applies more generally to charged, pointed electron-conductors that exhibit the "electrostatic lightning-rod effect", but are poorly discussed in general electricity and magnetism literature. Modern electron-conductor electrostatics is an application of the chemical thermodynamics and statistical mechanics of electrons. The review focuses chiefly on the electrostatics of two common basic emitter forms: the needle-shaped emitters used in traditional projection technologies; and the post-shaped emitters often used in modelling large-area multi-emitter electron sources. In the post-on-plane context, we consider in detail both the electrostatics of the single post and the interaction between two identical posts that occurs as a result of electrostatic depolarization (often called "screening" or "shielding"). Core to the review are discussions of the "minimum domain dimensions" method for implementing effective finite-element-method electrostatic simulations, and of the variant that leads to very precise estimates of dimensionless field enhancement factors (error typically less than 0.001 % in situations where analytical comparisons exist). Brief outline discussions, and core references, are given for each of many "related considerations" that are relevant to the electrostatic situations, methods and results described. Many areas of field emitter electrostatics are suggested where further research and/or separate mini-reviews would probably be useful., Comment: 39 pages, 24 figures. Invited Review, submitted for refereeing

The partially-averaged Navier-Stokes (PANS) equations are used to predict the variable-density Rayleigh-Taylor (RT) flow at Atwood number 0.5 and maximum Reynolds number $500$. This is a prototypical problem of material mixing featuring laminar, transitional, and turbulent flow, instabilities and coherent structures, density fluctuations, and production of turbulence kinetic energy by both shear and buoyancy mechanisms. These features pose numerous challenges to modeling and simulation, making the RT flow ideal to develop the validation space of the recently proposed PANS BHR-LEVM closure. The numerical simulations are conducted at different levels of physical resolution and test three approaches to set the parameters $f_\phi$ defining the range of physically resolved scales. The computations demonstrate the efficiency (accuracy vs. cost) of the PANS model predicting the spatio-temporal development of the RT flow. Results comparable to large-eddy simulations and direct numerical simulations are obtained, at significantly lower physical resolution without the limitations of the Reynolds-averaged Navier-Stokes equations in these transitional flows. The data also illustrate the importance of appropriate selection of the physical resolution and the resolved fraction of each dependent quantity $\phi$ of the turbulent closure, $f_\phi$. These two aspects determine the ability of the model to resolve the flow phenomena not amenable to modeling by the closure and, as such, the computations' fidelity.

This article proposes an artificial data generating algorithm that is simple and easy to customize. The fundamental concept is to perform random permutation of Monte Carlo generated random numbers which conform to the unconditional probability distribution of the original real time series. Similar to constraint surrogate methods, random permutations are only accepted if a given objective function is minimized. The objective function is selected in order to describe the most important features of the stochastic process. The algorithm is demonstrated by producing simulated log-returns of the S\&P 500 stock index., Comment: 2 columns, 6 pages, 6 figures

Dependency links in single-layer networks offer a convenient way of modeling nonlocal percolation effects in networked systems where certain pairs of nodes are only able to function together. We study the percolation properties of the weak variant of this model: nodes with dependency neighbours may continue to function if at least one of their dependency neighbours is active. We show that this relaxation of the dependency rule allows for more robust structures and a rich variety of critical phenomena, as percolation is not determined strictly by finite dependency clusters. We study Erd\"os-R\'enyi and random scale-free networks with an underlying Erd\"os-R\'enyi network of dependency links. We identify a special "cusp" point above which the system is always stable, irrespective of the density of dependency links. We find continuous and discontinuous hybrid percolation transitions, separated by a tricritical point for Erd\"os-R\'enyi networks. For scale-free networks with a finite degree cutoff we observe the appearance of a critical point and corresponding double transitions in a certain range of the degree distribution exponent. We show that at a special point in the parameter space, where the critical point emerges, the giant viable cluster has the unusual critical singularity $S-S_c \propto (p-p_c)^{1/4}$. We study the robustness of networks where connectivity degrees and dependency degrees are correlated and find that scale-free networks are able to retain their high resilience for strong enough positive correlation, i.e., when hubs are protected by greater redundancy., Comment: 18 pages, 10 figures

In this letter we present emergent screening of magnetic monopole and dipole by the presence of 20nm aluminum cover layer. Our results were obtained in base of magnetic atomic force measurements, performed after external magnetic field steps application. We show that the evolution of magnetization and monopole population is affected by the aluminum presence and attribute that phenomena to the proximity effect, which is responsible for the magnetization vanish of the firstatomic layers at the interface. Using experimental values to estimate the decrease in the nano-magnetic dipole value used in an emergent excitation model and in the switching field distribution heterogeneity used in simulations, we observe a very good agreement among experimental and simulation results. The presented emergent screening could be used in new ASI geometries for thermodynamic activation or proposition of devices with selective magnetic monopole mobility., Comment: 6 pages

We present a 2-dimensional chemical evolution code applied to a Milky Way type galaxy, incorporating the role of spiral arms in shaping azimuthal abundance variations, and confront the predicted behaviour with recent observations taken with integral field units. To the usual radial distribution of mass, we add the surface density of the spiral wave and study its effect on star formation and elemental abundances. We compute five different models: one with azimuthal symmetry which depends only on radius, while the other four are subjected to the effect of a spiral density wave. At early times, the imprint of the spiral density wave is carried by both the stellar and star formation surface densities; conversely, the elemental abundance pattern is less affected. At later epochs, however, differences among the models are diluted, becoming almost indistinguishable given current observational uncertainties. At the present time, the largest differences appear in the star formation rate and/or in the outer disc (R$\ge$ 18\,kpc). The predicted azimuthal oxygen abundance patterns for $t \le 2$\,Gyr are in reasonable agreement with recent observations obtained with VLT/MUSE for NGC 6754, Comment: 19 pages, 12 figures, MNRAS to be published

We present a detailed study of the performance of a trading rule that uses moving average of past returns to predict future returns on stock indexes. Our main goal is to link performance and the stochastic process of the traded asset. Our study reports short, medium and long term effects by looking at the Sharpe ratio (SR). We calculate the Sharpe ratio of our trading rule as a function of the probability distribution function of the underlying traded asset and compare it with data. We show that if the performance is mainly due to presence of autocorrelation in the returns of the traded assets, the SR as a function of the portfolio formation period (look-back) is very different from performance due to the drift (average return). The SR shows that for look-back periods of a few months the investor is more likely to tap into autocorrelation. However, for look-back larger than few months, the drift of the asset becomes progressively more important. Finally, our empirical work reports a new long-term effect, namely oscillation of the SR and propose a non-stationary model to account for such oscillations., Comment: 32 pages, 14 figures, accepted for publication in Quantitative Finance on 12/2017. Result of research initiated in 2013 which generated several conference presentations and working papers. This effort is substantially extended, edited and updated. arXiv admin note: substantial text overlap with arXiv:1402.3030

In this article, we point out an interesting solution for the dynamics of a racecar in a banked circular track with banking angle well over 90o. We call this track configuration an Inverted Track, at which a racecar can drive partially upside-down. We show an experimental setup where we made a toy car to circulate upside-down held only by its friction to the track. We discuss the viability to perform the abovementioned stunt with a real racecar in terms of the velocities required, dimensions of the track and safety; provided a passionate motorsport related company to commission it. For most racecars, the aerodynamic down-force is significant and it is included in our analysis., Comment: 14 pages, 8 figures, 1 video from the authors is cited in the text and referenced

We consider a first neighbor interaction where agents are spread through a uni-dimensional network. Some agents are also connected to a hub, or master node, who has preferential values (or orientation). The role of master node is to persuade some individuals to follow a specific orientation, subject to a probability of successful persuasion. The connections between master node and the network society are quenched in disorder. Despite its simplicity, we found a phase transition from disorder to order for three different control parameters. We also discuss how this model may be useful as a framework to study the spread of morality, innovation, opinion formation and consensus. Is important to recall the route from disorder to order in social systems still a great challenge. We hope to contribute with a novel approach to model a this issues., Comment: 7 pages, 6 figures and 1 table

In the literature about field emission, finite elements and finite differences techniques are being increasingly employed to understand the local field enhancement factor (FEF) via numerical simulations. In theoretical analyses, it is usual to consider the emitter as isolated, i.e, a single tip field emitter infinitely far from any physical boundary, except the substrate. However, simulation domains must be finite and the simulation boundaries influences the electrostatic potential distribution. In either finite elements or finite differences techniques, there is a systematic error ($\epsilon$) in the FEF caused by the finite size of the simulation domain. It is attempting to oversize the domain to avoid any influence from the boundaries, however, the computation might become memory and time consuming, especially in full three dimensional analyses. In this work, we provide the minimum width and height of the simulation domain necessary to evaluate the FEF with $\epsilon$ at the desired tolerance. The minimum width ($A$) and height ($B$) are given relative to the height of the emitter ($h$), that is, $(A/h)_{min} \times (B/h)_{min}$ necessary to simulate isolated emitters on a substrate. We also provide the $(B/h)_{min}$ to simulate arrays and the $(A/h)_{min}$ to simulate an emitter between an anode-cathode planar capacitor. At last, we present the formulae to obtain the minimal domain size to simulate clusters of emitters with precision $\epsilon_{tol}$. Our formulae account for ellipsoidal emitters and hemisphere on cylindrical posts. In the latter case, where an analytical solution is not known at present, our results are expected to produce an unprecedented numerical accuracy in the corresponding local FEF.

Recent analyses of the field enhancement factor (FEF) from multiple emitters have revealed that the depolarization effect is more persistent with respect to the separation between the emitters than originally assumed. It has been shown that, at sufficiently large separations, the fractional reduction of the FEF decays with the inverse cube power of separation, rather than exponentially. The behavior of the fractional reduction of the FEF encompassing both the range of technological interest $0

Numerical simulations are important when assessing the many characteristics of field emission related phenomena. In small simulation domains, the electrostatic effect from the boundaries is known to influence the calculated apex field enhancement factor (FEF) of the emitter, but no established dependence has been reported at present. In this work, we report the dependence of the lateral size, $L$, and the height, $H$, of the simulation domain on the apex-FEF of a single conducting ellipsoidal emitter. Firstly, we analyze the error, $\varepsilon$, in the calculation of the apex-FEF as a function of $H$ and $L$. Importantly, our results show that the effects of $H$ and $L$ on $\varepsilon$ are scale invariant, allowing one to predict $\varepsilon$ for ratios $L/h$ and $H/h$, where $h$ is the height of the emitter. Next, we analyze the fractional change of the apex-FEF, $\delta$, from a single emitter, $\gamma_1$, and a pair, $\gamma_2$. We show that small relative errors in $\gamma_1$ (i.e., $\varepsilon\approx0.5\%$), due to the finite domain size, are sufficient to alter the functional dependence $\delta(c)$, where $c$ is the distance from the emitters in the pair. We show that $\delta(c)$ obeys a recently proposed power law decay in the limit of infinite domain size ($\varepsilon=0$, say), in contrast to a long time established exponential decay. Thus, power law functional dependence, $-\delta \sim c^{-n}$, with $n=3$, is suggested to be a universal signature of the charge-blunting effect, at sufficient large distances between similar emitters with any shape. These results explain the origin of the discrepancies in the literature and improves the scientific understanding of the field electron emission theory, for accurate characterization of emitters in small clusters or arrays.

This work presents an accurate numerical study of the electrostatics of systems formed by individual nanostructure mounted on support substrate tip, a theoretical prototype for applications in field electron emission or for construction of tips in probe microscopy requiring high resolution. We modeled substrate tip with height $h_1$, radius $r_{1}$ and characteristic field enhancement factor (FEF) $\gamma_1$, and the top nanostructure with height $h_2$, radius $r_{2}

A majority of studied models for scale-free networks have degree distributions with exponents greater than $2$. Real networks, however, can demonstrate essentially more heavy-tailed degree distributions. We explore two models of scale-free equilibrium networks that have the degree distribution exponent $\gamma = 1$, $P(q) \sim q^{-\gamma}$. Such degree distributions can be identified in empirical data only if the mean degree of a network is sufficiently high. Our models exploit a rewiring mechanism. They are local in the sense that no knowledge of the network structure, apart from the immediate neighbourhood of the vertices, is required. These models generate uncorrelated networks in the infinite size limit, where they are solved explicitly. We investigate finite size effects by the use of simulations. We find that both models exhibit disassortative degree-degree correlations for finite network sizes. In addition, we observe a markedly degree-dependent clustering in the finite networks. We indicate a real-world network with a similar degree distribution., Comment: 8 pages, 8 figures

The interplay between energy efficiency and evolutionary mechanisms is addressed. One important question is how evolutionary mechanisms can select for the optimised usage of energy in situations where it does not lead to immediate advantage. For example, this problem is of great importance to improve our understanding about the major transition from unicellular to multicellular form of life. The immediate advantage of gathering efficient individuals in an energetic context is not clear. Although this process increases relatedness among individuals, it also increases local competition. To address this question, we propose a model of two competing metabolic strategies that makes explicit reference to the resource usage. We assume the existence of an efficient strain, which converts resource into energy at high efficiency but displays a low rate of resource consumption, and an inefficient strain, which consumes resource at a high rate with a low efficiency in converting it to energy. We explore the dynamics in both well-mixed and structured populations. The selection for optimised energy usage is measured by the likelihood of that an efficient strain can invade a population only comprised by inefficient strains. It is found that the region of the parameter space at which the efficient strain can thrive in structured populations is always larger than observed in well-mixed populations. In fact, in well-mixed populations the efficient strain is only evolutionarily stable in the domain whereupon there is no evolutionary dilemma. We also observe that small group sizes enhance the chance of invasion by the efficient strain in spite of increasing the competition among relatives. This outcome corroborates the key role played by kin selection and shows that the group dynamics relied on group expansion, overlapping generations and group split can balance the negative effects of local competition., Comment: 32 pages, 7 figures

This work presents a theoretical explanation for a crossover in the linear behavior in Fowler-Nordheim (FN) plots based on cold field electron emission (CFE) experimental data. It is characterized by a clear change in the decay rate of usually single-slope FN plots, and has been reported when non-uniform nano-emitters are subject to high macroscopic electric field $F_M$. We assume that the number of emitting spots, which defines an apparent formal area efficiency of CFE surfaces, depends on the macroscopic electric field. Non-uniformity is described by local enhancement factors $\left\{\gamma_j\right\}$, which are randomly assigned to each distinct emitter of a conducting CFE surface, from a discrete probability distribution $\rho{(\gamma_{j})}$, with $j=1,2$. It is assumed that $\rho{(\gamma_{1})} < \rho{(\gamma_{2})}$, and that $\gamma_{1} > \gamma_{2}$. The local current density is evaluated by considering a usual Schottky-Nordheim barrier. The results reproduce the two distinct slope regimes in FN plots when $F_M \in $ $[2,20]$ V/$\mu$m and are analyzed by taking into account the apparent formal area efficiency, the distribution $\rho$, and the slopes in the corresponding FN plot. Finally, we remark that our results from numerical solution of Laplace's equation, for an array of conducting nano-emitters with uniform apex radii $50$ nm but different local height, supports our theoretical assumptions and could used in orthodox CFE experiments to test our predictions.

In this paper we extend the promotion cure rate model proposed by Chen et al (1999), by incorporating excess of zeros in the modelling. Despite allowing to relate the covariates to the fraction of cure, the current approach, which is based on a biological interpretation of the causes that trigger the event of interest, does not enable to relate the covariates to the fraction of zeros. The presence of zeros in survival data, unusual in medical studies, can frequently occur in banking loan portfolios, as presented in Louzada et al (2015), where they deal with propensity to fraud in lending loans in a major Brazilian bank. To illustrate the new cure rate survival method, the same real dataset analyzed in Louzada et al (2015) is fitted here, and the results are compared., Comment: 13 pages, 2 figures, 6 tables. arXiv admin note: text overlap with arXiv:1509.05244

In this paper, we introduce a methodology based on the zero-inflated cure rate model to detect fraudsters in bank loan applications. In fact, our approach enables us to accommodate three different types of loan applicants, i.e., fraudsters, those who are susceptible to default and finally, those who are not susceptible to default. An advantage of our approach is to accommodate zero-inflated times, which is not possible in the standard cure rate model. To illustrate the proposed method, a real dataset of loan survival times is fitted by the zero-inflated Weibull cure rate model. The parameter estimation is reached by maximum likelihood estimation procedure and Monte Carlo simulations are carried out to check its finite sample performance., Comment: 19 pages, 4 figures

The mixing of materials due to the Richtmyer-Meshkov instability and the ensuing turbulent behavior is of intense interest in a variety of physical systems including inertial confinement fusion, combustion, and the final stages of stellar evolution. Extensive numerical and laboratory studies of shock-driven mixing have demonstrated the rich behavior associated with the onset of turbulence due to the shocks. Here we report on progress in understanding shock-driven mixing at interfaces between fluids of differing densities through 3D numerical simulations using the RAGE code in the implicit large eddy simulation context. We consider a shock tube configuration with a band of high density gas (SF$_6$) embedded in low density gas (air). Shocks with a Mach number of 1.26 are passed through SF$_6$ bands, resulting in transition to turbulence driven by the Richtmyer-Meshkov instability. The system is followed as a rarefaction wave and a reflected secondary shock from the back wall pass through the SF$_6$ band. We apply a variety of initial perturbations to the interfaces between the two fluids in which the physical standard deviation, wave number range, and the spectral slope of the perturbations are held constant, but the number of modes initially present is varied. By thus decreasing the density of initial spectral modes of the interface, we find that we can achieve as much as 25\% less total mixing at late times. This has potential direct implications for the treatment of initial conditions applied to material interfaces in both 3D and reduced dimensionality simulation models., Comment: 17 pages, 12 figures, accepted for publication Physical Review E

In the past 20 years, momentum or trend following strategies have become an established part of the investor toolbox. We introduce a new way of analyzing momentum strategies by looking at the information ratio (IR, average return divided by standard deviation). We calculate the theoretical IR of a momentum strategy, and show that if momentum is mainly due to the positive autocorrelation in returns, IR as a function of the portfolio formation period (look-back) is very different from momentum due to the drift (average return). The IR shows that for look-back periods of a few months, the investor is more likely to tap into autocorrelation. However, for look-back periods closer to 1 year, the investor is more likely to tap into the drift. We compare the historical data to the theoretical IR by constructing stationary periods. The empirical study finds that there are periods/regimes where the autocorrelation is more important than the drift in explaining the IR (particularly pre-1975) and others where the drift is more important (mostly after 1975). We conclude our study by applying our momentum strategy to 100 plus years of the Dow-Jones Industrial Average. We report damped oscillations on the IR for look-back periods of several years and model such oscilations as a reversal to the mean growth rate., Comment: 23 pages, 8 figures;v2:revised text

The importance of considering the volumes to analyze stock prices movements can be considered as a well-accepted practice in the financial area. However, when we look at the scientific production in this field, we still cannot find a unified model that includes volume and price variations for stock assessment purposes. In this paper we present a computer model that could fulfill this gap, proposing a new index to evaluate stock prices based on their historical prices and volumes traded. Besides the model can be considered mathematically very simple, it was able to improve significantly the performance of agents operating with real financial data. Based on the results obtained, and also on the very intuitive logic of our model, we believe that the index proposed here can be very useful to help investors on the activity of determining ideal price ranges for buying and selling stocks in the financial market., Comment: 9 pages, 15 figures

Following the thermodynamic formulation of multifractal measure that was shown to be capable of detecting large fluctuations at an early stage, here we propose a new index which permits us to distinguish events like financial crisis in real time . We calculate the partition function from where we obtain thermodynamic quantities analogous to free energy and specific heat. The index is defined as the normalized energy variation and it can be used to study the behavior of stochastic time series, such as financial market daily data. Famous financial market crashes - Black Thursday (1929), Black Monday (1987) and Subprime crisis (2008) - are identified with clear and robust results. The method is also applied to the market fluctuations of 2011. From these results it appears as if the apparent crisis of 2011 is of a different nature from the other three. We also show that the analysis has forecasting capabilities., Comment: 8 pages, 6 figures

In this work we study the local coupled Kuramoto model with periodic boundary conditions. Our main objective is to show how analytical solutions may be obtained from symmetry assumptions, and while we proceed on our endeavor we show apart from the existence of local attractors, some unexpected features resulting from the symmetry properties, such as intermittent and chaotic period phase slips, degeneracy of stable solutions and double bifurcation composition. As a result of our analysis, we show that stable fixed points in the synchronized region may be obtained with just a small amount of the existent solutions, and for a class of natural frequencies configuration we show analytical expressions for the critical synchronization coupling as a function of the number of oscillators, both exact and asymptotic., Comment: 15 pages, 12 figures

A system of nearest neighbors Kuramoto-like coupled oscillators placed in a ring is studied above the critical synchronization transition. We find a richness of solutions when the coupling increases, which exists only within a solvability region (SR). We also find that they posses different characteristics, depending on the section of the boundary of the SR where the solutions appear. We study the birth of these solutions and how they evolve when {K} increases, and determine the diagram of solutions in phase space., Comment: 8 pages, 10 figures

In this work we study an economic agent based model under different asymmetric information degrees. This model is quite simple and can be treated analytically since the buyers evaluate the quality of a certain good taking into account only the quality of the last good purchased plus her perceptive capacity \beta . As a consequence the system evolves according to a stationary Markovian stochastic process. The value of a product offered by the seller increases with quality according to the exponent \alpha, which is a measure of technology. It incorporates all the technological capacity of production systems such as education, scientific development and techniques that change the productivity growth. The technological level plays an important role to explain how the asymmetry of information may affect the market evolution in this model. We observe that, for high technological levels, the market can control adverse selection. The model allows us to compute the maximum asymmetric information degree before market collapse. Below this critical point the market evolves during a very limited time and then dies out completely. When \beta is closer to 1(symmetric information), the market becomes more profitable for high quality goods, although high and low quality markets coexist. All the results we obtained from the model are analytical and the maximum asymmetric information level is a consequence of an ergodicity breakdown in the process of quality evaluation., Comment: 13 pages and 4 figures

We investigate synchronization in a Kuramoto-like model with nearest neighbour coupling. Upon analyzing the behaviour of individual oscillators at the onset of complete synchronization, we show that the time interval between bursts in the time dependence of the frequencies of the oscillators exhibits universal scaling and blows up at the critical coupling strength. We also bring out a key mechanism that leads to phase locking. Finally, we deduce forms for the phases and frequencies at the onset of complete synchronization., Comment: 6 pages, 4 figures, to appear in CHAOS

The search for more realistic modeling of financial time series reveals several stylized facts of real markets. In this work we focus on the multifractal properties found in price and index signals. Although the usual Minority Game (MG) models do not exhibit multifractality, we study here one of its variants that does. We show that the nonsynchronous MG models in the nonergodic phase is multifractal and in this sense, together with other stylized facts, constitute a better modeling tool. Using the Structure Function (SF) approach we detected the stationary and the scaling range of the time series generated by the MG model and, from the linear (nonlinear) behavior of the SF we identified the fractal (multifractal) regimes. Finally, using the Wavelet Transform Modulus Maxima (WTMM) technique we obtained its multifractal spectrum width for different dynamical regimes., Comment: 14 pages, 6 figures

Here we present a system of coupled phase oscillators with nearest neighbors coupling, which we study for different boundary conditions. We concentrate at the transition to total synchronization. We are able to develop exact solutions for the value of the coupling parameter when the system becomes completely synchronized, for the case of periodic boundary conditions as well as for an open chain with fixed ends. We compare the results with those calculated numerically., Comment: 5 pages, 3 figures

The analysis of one-, two-, and three-dimensional coupled map lattices is here developed under a statistical and dynamical perspective. We show that the three-dimensional CML exhibits low dimensional behavior with long range correlation and the power spectrum follows $1/f$ noise. This approach leads to an integrated understanding of the most important properties of these universal models of spatiotemporal chaos. We perform a complete time series analysis of the model and investigate the dependence of the signal properties by change of dimension., Comment: 7 pages, 6 figures (revised)

We study analytically and numerically Minority Games in which agents may invest in different assets (or markets), considering both the canonical and the grand-canonical versions. We find that the likelihood of agents trading in a given asset depends on the relative amount of information available in that market. More specifically, in the canonical game players play preferentially in the stock with less information. The same holds in the grand canonical game when agents have positive incentives to trade, whereas when agents payoff are solely related to their speculative ability they display a larger propensity to invest in the information-rich asset. Furthermore, in this model one finds a globally predictable phase with broken ergodicity., Comment: 6 pages, 5 figures

In the paper we considere three state $p$-adic Potts model with competing interactions on a Cayley tree of order two. We reduce a problem of describing of the $p$-adic Gibbs measures to the solution of certain recursive equation, and using it we will prove that a phase transition occurs if and only if $p=3$ for any value (non zero) of interactions. As well, we completely solve the uniqueness problem for the considered model in a $p$-adic context. Namely, if $p\neq 3$ then there is only a unique Gibbs measure the model., Comment: 12 pages, to appear in the Proceedings of the '2nd International Conference on p-Adic Mathematical Physics' (Belgrade, 15-21 September 2005) published by AIP Conference Proceedings

The minority game (MG) model introduced recently provides promising insights into the understanding of the evolution of prices, indices and rates in the financial markets. In this paper we perform a time series analysis of the model employing tools from statistics, dynamical systems theory and stochastic processes. Using benchmark systems and a financial index for comparison, several conclusions are obtained about the generating mechanism for this kind of evolut ion. The motion is deterministic, driven by occasional random external perturbation. When the interval between two successive perturbations is sufficiently large, one can find low dimensional chaos in this regime. However, the full motion of the MG model is found to be similar to that of the first differences of the SP500 index: stochastic, nonlinear and (unit root) stationary., Comment: LaTeX 2e (elsart), 17 pages, 3 EPS figures and 2 tables, accepted for publication in Physica A

The statistical properties of the energy landscape of the low autocorrelated binary string problem (LABSP) are studied numerically and compared with those of several classic disordered models. Using two global measures of landscape structure which have been introduced in the Simulated Annealing literature, namely, depth and difficulty, we find that the landscape of LABSP, except perhaps for a very large degeneracy of the local minima energies, is qualitatively similar to some well-known landscapes such as that of the mean-field 2-spin glass model. Furthermore, we consider a mean-field approximation to the pure model proposed by Bouchaud and Mezard (1994, J. Physique I France 4 1109) and show both analytically and numerically that it describes extremely well the statistical properties of LABSP.

The goal of this work was to use data-driven methods to automatically detect and isolate faults in the J-2X rocket engine. It was decided to use decision trees, since they tend to be easier to interpret than other data-driven methods. The decision tree algorithm automatically "learns" a decision tree by performing a search through the space of possible decision trees to find one that fits the training data. The particular decision tree algorithm used is known as C4.5. Simulated J-2X data from a high-fidelity simulator developed at Pratt & Whitney Rocketdyne and known as the Detailed Real-Time Model (DRTM) was used to "train" and test the decision tree. Fifty-six DRTM simulations were performed for this purpose, with different leak sizes, different leak locations, and different times of leak onset. To make the simulations as realistic as possible, they included simulated sensor noise, and included a gradual degradation in both fuel and oxidizer turbine efficiency. A decision tree was trained using 11 of these simulations, and tested using the remaining 45 simulations. In the training phase, the C4.5 algorithm was provided with labeled examples of data from nominal operation and data including leaks in each leak location. From the data, it "learned" a decision tree that can classify unseen data as having no leak or having a leak in one of the five leak locations. In the test phase, the decision tree produced very low false alarm rates and low missed detection rates on the unseen data. It had very good fault isolation rates for three of the five simulated leak locations, but it tended to confuse the remaining two locations, perhaps because a large leak at one of these two locations can look very similar to a small leak at the other location.

Schedule Report Generator provides simple method for generating periodic schedule reports. Enables engineering manager to monitor tasks assigned to staff members on weekly basis. Sorts three types of reports by use of one or more data fields as sorting keys. Schedule Organizer (SO) (COSMIC program MSC-21525), Schedule Tracker (ST) (COSMIC program MSC-21526), and Schedule Report Generator (SRG) computer programs manipulating data-base files in ways advantageous in scheduling. Written in PL/1 and DEC Command Language (DCL).

Schedule Organizer provides simple method for generating distribution lists. Contains readers' names for each task schedule defined by input files. Schedule Organizer (SO), Schedule Tracker (ST) (COSMIC program MSC-21526), and Schedule Report Generator (SRG) (COSMIC program MSC-21527) computer programs manipulating data-base files in ways advantageous in scheduling. Written in PL/1 and DEC Command Language (DCL).

Schedule Tracker provides effective method for tracking tasks "past due" and/or "near term". Generates reports for each responsible staff member having one or more assigned tasks falling within two listed categories. Schedule Organizer (SO) (COSMIC program MSC-21525), Schedule Tracker (ST), and Schedule Report Generator (SRG) (COSMIC program MSC-21527) computer programs manipulating data-base files in ways advantageous in scheduling. Written in PL/1 and DEC Command Language (DCL).