Application of epidemic models to phase transitions

The Susceptible-Infected-Recovered (SIR) and Susceptible-Exposed-Infected-Recovered (SEIR) models describe the spread of epidemics in a society. In the typical case, the ratio of the susceptible individuals fall from a value S ₀ close to 1 to a final value S_f , while the ratio of recovered individuals rise from 0 to R_f?=?1???S_f . The sharp passage from the level zero to the level R_f allows also the modeling of phase transitions by the number of “recovered” individuals R(t) of the SIR or SEIR model. In this article, we model the sol–gel transition for polyacrylamide–sodium alginate (SA) composite with different concentrations of SA as SIR and SEIR dynamical systems by solving the corresponding differential equations numerically and we show that the phase transitions of “classical” and “percolation” types are represented, respectively, by the SEIR and SIR models.     

From the eden model to the kinetic growth walk: A generalized growth model with a finite lifetime of growth sites

We propose a new class of cluster growth models where growth sites have a finite lifetime , which contains as special cases the Eden model ( = ) and the kinetic growth walk ( = 1). For finite but large values the growth process can be characterized by a crossover timet _X; for times belowt _X an Eden-type cluster is formed, while for times abovet _X the growth process belongs to the universality class of the self-avoiding random walk. The crossover time increases monotonically with . We develop a scaling theory for the time evolution of the mean end-to-end distance between the seed and the last-added site, and for the average number of growth sites by which the kinetics of the growth process can be characterized. We test this scaling theory by extensive Monte Carlo simulations. We also extend our results to inhomogeneous media (percolation systems).     

The parallel complexity of growth models

This paper investigates the parallel complexity of several nonequilibrium growth models.Invasion percolation, Eden growth, ballistic deposition, andsolid-on-solid growth are all seemingly highly sequential processes that yield self-similar or self-affine random clusters. Nonetheless, we present fast parallel randomized algorithms for generating these clusters. The running times of the algorithms scale asO(log² N), whereN is the system size, and the number of processors required scales as a polynomial inN. The algorithms are based on fast parallel procedures for finding minimum-weight paths; they illuminate the close connection between growth models and self-avoiding paths in random environments. In addition to their potential practical value, our algorithms serve to classify these growth models as less complex than other growth models, such asdiffusion-limited aggregation, for which fast parallel algorithms probably do not exist.     

Mathematical models for dengue fever epidemiology: A 10-year systematic review

Mathematical models have a long history in epidemiological research, and as the COVID-19 pandemic progressed, research on mathematical modeling became imperative and very influential to understand the epidemiological dynamics of disease spreading.Mathematical models describing dengue fever epidemiological dynamics are found back from 1970. Dengue fever is a viral mosquito-borne infection caused by four antigenically related but distinct serotypes (DENV-1 to DENV-4). With 2.5 billion people at risk of acquiring the infection, it is a major international public health concern. Although most of the cases are asymptomatic or mild, the disease immunological response is complex, with severe disease linked to the antibody-dependent enhancement (ADE) - a disease augmentation phenomenon where pre-existing antibodies to previous dengue infection do not neutralize but rather enhance the new infection. Here, we present a 10-year systematic review on mathematical models for dengue fever epidemiology. Specifically, we review multi-strain frameworks describing host-to-host and vector-host transmission models and within-host models describing viral replication and the respective immune response.Following a detailed literature search in standard scientific databases, different mathematical models in terms of their scope, analytical approach and structural form, including model validation and parameter estimation using empirical data, are described and analyzed.Aiming to identify a consensus on infectious diseases modeling aspects that can contribute to public health authorities for disease control, we revise the current understanding of epidemiological and immunological factors influencing the transmission dynamics of dengue. This review provide insights on general features to be considered to model aspects of real-world public health problems, such as the current epidemiological scenario we are living in.     

Quiescent cells: A natural way to resist chemotherapy

Most chemotherapeutic treatments use drugs that target proliferating cancer cells. Therefore, they do not affect quiescent cells which are naturally resistant. Surviving cancer cells can reactivate their cell cycles in the intervals between doses, becoming proliferative again and thus restarting tumor growth. In this work, we present a mathematical model to study the impact of quiescent cells on chemotherapy effectiveness. Our simulations show that, although tumor growth is delayed after the beginning of each dose, the resistance of quiescent cells is enough to reactivate it due to accelerated repopulation, eventually causing therapy failure even in the absence of acquired resistance.     

Parallel optimization of underwater acoustic models: A survey

Underwater acoustic models are effective tools for simulating underwater sound propagation. More than 50 years of research have been conducted on the theory and computational models of sound propagation in the ocean. Unfortunately, underwater sound propagation models were unable to solve practical large-scale three-dimensional problems for many years due to limited computing power and hardware conditions. Since the mid-1980s, research on high performance computing for acoustic propagation models in the field of underwater acoustics has flourished with the emergence of high-performance computing platforms, enabling underwater acoustic propagation models to solve many practical application problems that could not be solved before. In this paper, the contributions of research on high-performance computing for underwater acoustic propagation models since the 1980s are thoroughly reviewed and the possible development directions for the future are outlined.     

Effect of anti-virus software on infectious nodes in computer network: A mathematical model

An e-epidemic model of malicious codes in the computer network through vertical transmission is formulated. We have observed that if the basic reproduction number is less than unity, the infected proportion of computer nodes disappear and malicious codes die out and also the malicious codes-free equilibrium is globally asymptotically stable which leads to its eradication. Effect of anti-virus software on the removal of the malicious codes from the computer network is critically analyzed. Analysis and simulation results show some managerial insights that are helpful for the practice of anti-virus in information sharing networks.     

Reformulation of the path probability method and its application to crystal growth models

The microscopic master equation of a system is derived within the framework of the path probability method (PPM). Then, by extending Morita's method in equilibrium statistical mechanics, the path probability function constructed microscopically can be systematically decomposed to result in the conventional path probability function of cluster approximation when correlations larger than the chosen basic cluster are neglected. In order to critically compare the master equation method with the PPM, the triangle approximation is treated by both methods for crystal growth models. It is found that the PPM gives physically satisfactory kinetic equations, while the master equation (supplemented with a cluster probability in the superposition approximation) does not. The triangle PPM calculation considerably improves the result of the pair approximation for crystal growth velocity in the solid-on-solid model, and compares well with Monte Carlo results.     

Scaling behavior of two-dimensional domain growth: Computer simulation of vertex models

Computer simulations are performed for vertex models which are coarse-grained models for dynamical cellular patterns in two dimensions. By simulating large systems, we obtain conclusive evidence of scaling behavior, that is, a power law for the growth of the average cell size and the scaling properties for the distribution functions of edge number and size of cells. Several versions of the vertex models are obtained by making some approximations for the equation of motion of a vertex, and we compare the statistical properties of the patterns in the scaling regime.     

Spatial fluctuations in reaction-diffusion systems: A model for exponential growth

The spatial fluctuations in an exactly soluble model for the irreversible aggregation of clusters are treated. The model is characterized byrate constants K _ij =i+j for the clustering of ani- and aj-mer, anddiffusion constants D _j =D. It is assumed thatD1 (reaction-limited aggregation). Explicit expressions for the correlation functions at equal and at different times are calculated. The equal-time correlation functions show scaling behavior in the scaling limit. The correlation length remains finite ast, and the fluctuations becomelarge at large times (tt _D ) inany dimension. The crossover timet _D , at which the mean field theory (Smoluchowski's equation) breaks down, is given byt _D InD. These exact results imply that the upper critical dimension of this model isd _c= and, hence, that there isno unique upper critical dimension in models for the irreversible aggregation of clusters.     

Determination of growth modes via spectroscopy: new simple analytical models

Analytical models for the determination of thin film growth modes were developed on the basis of the simultaneous multilayer (SM) growth model. The models take into account up-step and down-step diffusion, enabling quick identification of the growth modes from experimentally obtained spectroscopic data. We tested the models by applying them to growth data from the literature that had been recorded via Auger electron spectroscopy (AES), X-ray photoelectron spectroscopy (XPS), and low-energy ion scattering (LEIS). We discuss the applicability of the new analytical models in comparison with the diffusion-corrected simultaneous multilayer (DCSM) model.     

Hypercube stacking: A potts-spin model for surface growth

We present a deposition and evaporation model for surface growth under a solid-on-solid constraint. We generalize the Ising-spin representation of a two-dimensional surface by Blöte and Hilhorst to ad-dimensional surface of a (d+1)-dimensional hypercubic lattice. The allowed surface configurations correspond to the (degenerate) ground states of a chirald-state Potts model. We describe a vectorized multisite-coding implementation for the corresponding kinetic Potts-spin model ford=2 andd=3. For thed=2 equilibrium surface our simulation results show excellent agreement with an exact analysis.     

New developments on size-dependent growth applied to the crystallization of sucrose

The effect of crystal size on the growth rate of sucrose (C₁₂H₂₂O₁₁) at 40 °C is investigated from a theoretical and an experimental point of view. Based on new perspectives resulting from the recently introduced spiral nucleation model [P.M. Martins, F. Rocha, Surf. Sci. 601 (2007) 3400], crystal growth rates are expressed in terms of mass deposition per time and crystal volume units. This alternative definition is demonstrated to be size-independent over the considered supersaturation range. The conventional overall growth rate expressed per surface area units is found to be linearly dependent on crystal size. The advantages of the “volumetric” growth rate concept are discussed. Sucrose dissolution rates were measured under reciprocal conditions of the growth experiments in order to investigate the two-way effect of crystal size on mass transfer rates and on the integration kinetics. Both effects are adequately described by combining a well-established diffusion-integration model and the spiral nucleation mechanism.     

Molecular basis of structural make-up of feeds in relation to nutrient absorption in ruminants,revealed with advanced molecular spectroscopy: A review on techniques and models

Progress in ruminant feed research is no more feasible only based on wet chemical analysis, which is merely able to provide information on chemical composition of feeds regardless of their digestive features and nutritive value in ruminants. Studying internal structural make-up of functional groups/feed nutrients is often vital for understanding the digestive behaviors and nutritive values of feeds in ruminant because the intrinsic structure of feed nutrients is more related to its overall absorption. In this article, the detail information on the recent developments in molecular spectroscopic techniques to reveal microstructural information of feed nutrients and the use of nutrition models in regards to ruminant feed research was reviewed. The emphasis of this review was on (1) the technological progress in the use of molecular spectroscopic techniques in ruminant feed research; (2) revealing spectral analysis of functional groups of biomolecules/feed nutrients; (3) the use of advanced nutrition models for better prediction of nutrient availability in ruminant systems; and (4) the application of these molecular techniques and combination of nutrient models in cereals, co-products and pulse crop research. The information described in this article will promote better insight in the progress of research on molecular structural make-up of feed nutrients in ruminants.     

Nonlinear physics approach to RNA cross-replication: Marginal stability, generalized logistic growth, and impacts of degradation

It is nowadays believed that the evolution of life involved as an intermediate step an RNA world. In such an RNA world RNA molecules replicate themselves in catalytic reactions. Recent experiments on cross-replicating RNA support the RNA world hypothesis. We derive a nonlinear mass-action kinetics model to explain logistic growth patterns and non-symmetric saturation levels observed in those experiments. We also demonstrate that fixed points of the RNA growth process are only marginally stable rather than asymptotically stable.     

Phase-field study of free growth in a channel: from thermal to chemical solidification

The thermal and the chemical phase-field models for free growth in a two-dimensional channel are both studied in their one-sided version for which diffusion only occurs in the liquid. We compare the steady state fingers obtained in our phase-field simulations with the results of boundary integral techniques available in the literature. The excellent agreement found between both methods provides a valuable benchmark of the one-sided thin-interface phase model which makes use of an antitrapping current. Coexistence of several steady states predicted by the Green’s function calculations is also recovered. The dynamical stability of two competing modes (symmetric and asymmetric finger) is studied and the extension of their respective basins of attraction is evaluated. General implications of our results for a large class of isotropic systems are discussed.     

Fitting models to correlated data III: A comparison between residual analysis and other methods

Applications of the χ² test, the F test, the Durbin-Watson d test, and the f (or Sign) test, to examples of correlated data treatment, show important drawbacks with the d test and (apparently) with the f test. An analytical approach based on residual analysis suggests an improvement in their use that leads to better results at lowest order; it also points out a distinction between goodness-of-fit tests, as the f test, and goodness-of-modeling tests, as the χ² and F tests. The residual analysis method is applied to the same examples; it looks faster, simpler, and often more accurate than the classical ones.     

Do the simple and 2/3 majority models belong to the same universality class?: A monte carlo approach

We extend the majority model (introduced by Tsallis in 1982) in the sense that the required majority might be different from the simple majority. We simulate these models for typical cases which include simple and 2/3 majorities. We exhibit the average cluster size as well as the order parameter as functions ofp, the concentration of one of the two possible constituents. No crossover exists between the simple- and non-simple-majority models.