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Hantaviruses are zoonotic agents responsible for causing Hantavirus Cardiopulmonary Syndrome (HCPS) in the Americas, with Brazil ranking first in number of confirmed HCPS cases in South America. In this study, we simulate the monthly spread of highly lethal hantavirus in natural hosts by conjugating a Kermack-McCormick SIR model with a cellular automata model (CA), therefore simultaneously evaluating both in-cell and between-cell infection dynamics in host populations, using recently compiled data on main host species abundances and confirmed deaths by hantavirus infection. For both host species, our models predict an increase in the area of infection, with 22 municipalities where no cases have been confirmed to date expected to have at least one case in the next decade, and a reduction in infection in 11 municipalities. Our findings support existing research and reveal new areas where hantavirus is likely to spread within recognized epicenters. Highlighting spatial-temporal trends and potential expansion, we emphasize the increased risk due to pervasive habitat fragmentation and agricultural expansion. Consistent prevention efforts and One Health actions are crucial, especially in newly identified high-risk municipalities.

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Image segmentation is a computer vision technique that involves dividing an image into distinct and meaningful regions or segments. The objective was to partition the image into areas that share similar visual characteristics. Noise and undesirable artifacts introduce inconsistencies and irregularities in image data. These inconsistencies severely affect the ability of most segmentation algorithms to distinguish between true image features, leading to less reliable and lower-quality results. Cellular Automata (CA) is a computational concept that consists of a grid of cells, each of which can be in a finite number of states. These cells evolve over discrete time steps based on a set of predefined rules that dictate how a cell's state changes according to its own state and the states of its neighboring cells. In this paper, a new segmentation approach based on the CA model was introduced. The proposed approach consisted of three phases. In the initial two phases of the process, the primary objective was to eliminate noise and undesirable artifacts that can interfere with the identification of regions exhibiting similar visual characteristics. To achieve this, a set of rules is designed to modify the state value of each cell or pixel based on the states of its neighboring elements. In the third phase, each element is assigned a state that is chosen from a set of predefined states. These states directly represent the final segmentation values for the corresponding elements. The proposed method was evaluated using different images, considering important quality indices. The experimental results indicated that the proposed approach produces better-segmented images in terms of quality and robustness.

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The innate immune response is recognized as a key driver in controlling an influenza virus infection in a host. However, the mechanistic action of such innate response is not fully understood. Infection experiments on ex vivo explants from swine trachea represent an efficient alternative to animal experiments, as the explants conserved key characteristics of an organ from an animal. In the present work we compare three cellular automata models of influenza virus dynamics. The models are fitted to free virus and infected cells data from ex vivo swine trachea experiments. Our findings suggest that the presence of an immune response is necessary to explain the observed dynamics in ex vivo organ culture. Moreover, such immune response should include a refractory state for epithelial cells, and not just a reduced infection rate. Our results may shed light on how the immune system responds to an infection event.

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Cellular automata models have emerged as a valuable tool in corrosion management. This manuscript provides an overview of the application of cellular automata models in corrosion research, highlighting their benefits and contributions to understanding the complex nature of corrosion processes. Cellular automata models offer a computational approach to simulating corrosion behavior at the microscale, capturing the intricate interactions between electrochemical reactions, material properties, and environmental factors and generating a new vision of predictive maintenance. It reviews the key features of cellular automata, such as the grid-based representation of the material surface, the definition of state variables, and the rules governing cell-state transitions. The ability to model local interactions and emergent global behavior makes cellular automata particularly suitable for simulating corrosion processes. Finally, cellular automata models offer a powerful and versatile approach to studying corrosion processes, expanding models that can continue to enhance our understanding of corrosion and contribute to the development of effective corrosion prevention and control strategies.

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There are many security challenges in IoT, especially related to the authentication of restricted devices in long-distance and low-throughput networks. Problems such as impersonation, privacy issues, and excessive battery usage are some of the existing problems evaluated through the threat modeling of this work. A formal assessment of security solutions for their compliance in addressing such threats is desirable. Although several works address the verification of security protocols, verifying the security of components and their non-locking has been little explored. This work proposes to analyze the design-time security of the components of a multi-factor authentication mechanism with a reputation regarding security requirements that go beyond encryption or secrecy in data transmission. As a result, it was observed through temporal logic that the mechanism is deadlock-free and meets the requirements established in this work. Although it is not a work aimed at modeling the security mechanism, this document provides the necessary details for a better understanding of the mechanism and, consequently, the process of formal verification of its security properties.

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Cell-based models provide a helpful approach for simulating complex systems that exhibit adaptive, resilient qualities, such as cancer. Their focus on individual cell interactions makes them a particularly appropriate strategy to study cancer therapies' effects, which are often designed to disrupt single-cell dynamics. In this work, we propose them as viable methods for studying the time evolution of cancer imaging biomarkers (IBM). We propose a cellular automata model for tumor growth and three different therapies: chemotherapy, radiotherapy, and immunotherapy, following well-established modeling procedures documented in the literature. The model generates a sequence of tumor images, from which a time series of two biomarkers: entropy and fractal dimension, is obtained. Our model shows that the fractal dimension increased faster at the onset of cancer cell dissemination. At the same time, entropy was more responsive to changes induced in the tumor by the different therapy modalities. These observations suggest that the prognostic value of the proposed biomarkers could vary considerably with time. Thus, it is essential to assess their use at different stages of cancer and for different imaging modalities. Another observation derived from the results was that both biomarkers varied slowly when the applied therapy attacked cancer cells scattered along the automatons' area, leaving multiple independent clusters of cells at the end of the treatment. Thus, patterns of change of simulated biomarkers time series could reflect on essential qualities of the spatial action of a given cancer intervention.

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We study a variant of the classical membership problem in automata theory, which consists of deciding whether a given input word is accepted by a given automaton. We do so through the lenses of parameterized dynamic data structures: we assume that the automaton is fixed and its size is the parameter, while the input word is revealed as in a stream, one symbol at a time following the natural order on positions. The goal is to design a dynamic data structure that can be efficiently updated upon revealing the next symbol, while maintaining the answer to the query on whether the word consisting of symbols revealed so far is accepted by the automaton. We provide complexity bounds for this dynamic acceptance problem for timed automata that process symbols interleaved with time spans. The main contribution is a dynamic data structure that maintains acceptance of a fixed one-clock timed automaton  A with amortized update time  2 O ( | A | ) per input symbol.

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BACKGROUND: The egg-parasitoid wasp Telenomus podisi has received attention as a biological-control agent for one of the most important soybean pests in Brazil, the stink bug Euschistus heros. As yet, no studies have conclusively established strategies for the release of T. podisi. We developed a computational model using cellular automata in the C programming language to investigate release strategies for T. podisi in soybean crops, in order to optimize the use of these wasps in managing E. heros, assuming a two-dimensional grid of cells corresponding to a soybean field. RESULTS: The release strategies capable of maintaining an E. heros population below the Economic Threshold level involved releasing a total of at least 15 000 female parasitoids per hectare, in three or four releases of 5000 or more (equivalent to approximately 7142 or more male and female parasitoids per hectare, assuming a sex ratio of 0.70). A 25-m spacing between release points or strips was indicated. The model is very sensitive to the variation in the number of parasitoids per release and in the number of releases, but little sensitive to the release mode and spacing values. CONCLUSION: The theoretical results produced by the computational model are expected to guide future field studies to improve T. podisi release plans for managing E. heros in soybeans. Therefore, we recommend the release strategy of three to four releases of 5000 or more female parasitoids per hectare, at points or strips spaced 25 m apart, to be tested in field experiments for proper implementation by producers. © 2022 Society of Chemical Industry.

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BACKGROUND AND OBJECTIVE: Dengue fever is a disease in which individuals' spatial distribution and Aedes aegypti mosquitoes breeding places are important factors for the disease dynamics. Typically urban, dengue is a problem for least developed countries due to the ineffectiveness in controlling the vector and disorderly urbanization processes. The result is a composition of urban sanitation problems and areas with high demographic densities and intense flows of people. This paper explores the spatial distribution of vector breeding places to evaluate introducing a new dengue serotype to a population at equilibrium for a pre-existing serotype. The paper's objective is to analyze the spatial dynamics of dengue using variations of the basic reproduction number. METHODS: A model based on probabilistic cellular automata is proposed to permitting the necessary flexibility to consider some spatial distributions of vector breeding places. Then, ordinary differential equations are used as a mean-field approach of the model, and the basic reproduction number (R0) is derived considering the next-generation matrix method. A spatial approach for R0 is also proposed, and the model is tested in a neighbourhood from the city of São Paulo, Brazil, to examine the potential risks of vector breeding cells distribution. RESULTS: The results indicated that the more spread out these places, the higher are the values of R0. When the model is applied to a neighbourhood in São Paulo, residential areas may boost the infections and must be under public vigilance to combat vector breeding sites. CONCLUSIONS: Considering the mean-field approximation of the cellular automata model by ordinary differential equations, the basic reproduction number derived returned an estimative of the disease dynamics in the population. However, the spatial basic reproduction number was more assertive in showing areas with a higher disease incidence. Moreover, the model could be easily adapted to be used in real maps enabling simulations closer to real problems.

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The novel coronavirus disease 2019 (COVID-19) still challenges researchers due to its spread and deaths. Hence, the classical epidemic SIR and SEIRD models inspired by the epidemic's outbreak are widely used to predict the evolution of the disease. In addition to classical approaches, describing complex phenomena through Cellular Automata (CA) is a highly effective way to understand the iterations on a populated system. The present research analyzed the usage of CA to generate an epidemic-computational model from a micro perspective based on parameters obtained through a statistical fit from a macro perspective. After validating SIR and SEIRD models with the government official data for Brasilia, Brazil, the authors applied the obtained parameters to the Cellular Automata model. The CA model simulated the spread of the virus from infected to uninfected people in a restrained environment (i.e., a supermarket) under several varied conditions applying an approach never adopted before. The manner of applying CA in this research proved to represent an essential tool in predicting the spread of the coronavirus in confined spaces with random movements of people. The CA numerical open-source presented has the purpose of clarifying how the spread occurs not only as a mathematical curve but in an organic way. The numerical simulations from the CA model allowed the authors to conclude that markets and stores are relevant places where might be infections. Thus, every local store and the market owner should reason about the aspects that could avoid the spread of the disease, coming up with efficient solutions. Each environment has specific features that only those who know them are the ones capable of managing.

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The Flexible Job Shop Scheduling Problem (FJSP) is a combinatorial problem that continues to be studied extensively due to its practical implications in manufacturing systems and emerging new variants, in order to model and optimize more complex situations that reflect the current needs of the industry better. This work presents a new metaheuristic algorithm called the global-local neighborhood search algorithm (GLNSA), in which the neighborhood concepts of a cellular automaton are used, so that a set of leading solutions called smart-cells generates and shares information that helps to optimize instances of the FJSP. The GLNSA algorithm is accompanied by a tabu search that implements a simplified version of the Nopt1 neighborhood defined in Mastrolilli & Gambardella (2000) to complement the optimization task. The experiments carried out show a satisfactory performance of the proposed algorithm, compared with other results published in recent algorithms, using four benchmark sets and 101 test problems.

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The current study implements a cellular automata-based model for the development of land use/land cover (LULC) future scenarios using a Remote Sensing (RS) Imagery series (1985 to 2018) as data input and focusing on human activities drivers in a 6700-km2 watershed vital for the water security of Paraiba state, Brazil. The methodology has three stages: the first stage is the pre-processing of images and preparing them as data input for the cellular automata land use model built in the R software environment (SIMLANDER); the stage of calibration establishes the variables and verifies the influence of each one on the LULC of the region; the last step corresponds to the validation procedures. After model calibration, land use maps for future scenarios (2019 to 2045) were simulated. The results estimate a reduction of 737 km2 of natural land cover between the years 2019 and 2045. The spatial distribution of anthropogenic interference predicted a more significant degradation in the central region of the basin. This fact can be potentially attributed by the water availability increasing from the São Francisco River diversion. It is possible to identify an ascending trend of anthropogenic actions in the semi-arid region, which host the exclusively Brazilian biome-Caatinga-and contains biodiversity that cannot be found anywhere else on the Earth. The model helps large-scale LULC modelling based on RS products and expands the possibilities of hydrological, urban and social modelling in the Brazilian context.

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Background and objective Many countries around the world experienced a high increase in the number of COVID-19 cases after a few weeks of the first case, and along with it, excessive pressure on the healthcare systems. While medicines, drugs, and vaccines against the COVID-19 are being developed, social isolation has become the most used method for controlling the virus spreading. With the social isolation, authorities aimed to slow down the spreading, avoiding saturation of the healthcare system, and allowing that all critical COVID-19 cases could be appropriately treated. By tuning the proposed model to fit Brazil's initial COVID-19 data, the objectives of the paper are to analyze the impact of the social isolation features on the population dynamics; simulate the number of deaths due to COVID-19 and due to the lack of healthcare infrastructure; study combinations of the features for the healthcare system does not collapse; and analyze healthcare system responses for the crisis. Methods In this paper, a Susceptible-Exposed-Infected-Removed model is described in terms of probabilistic cellular automata and ordinary differential equations for the transmission of COVID-19, flexible enough for simulating different scenarios of social isolation according to the following features: the start day for the social isolation after the first death, the period for the social isolation campaign, and the percentage of the population committed to the campaign. Results Results showed that efforts in the social isolation campaign must be concentrated both on the isolation percentage and campaign duration to delay the healthcare system failure. For the hospital situation in Brazil at the beginning of the pandemic outbreak, a rate of 200 purchases per day of intensive care units and mechanical ventilators is the minimum rate to prevent the collapse of the healthcare system. Conclusions By using the model for different scenarios, it is possible to estimate the impact of social isolation campaign adhesion. For instance, if the social isolation percentage increased from 40% to 50% in Brazil, the purchase rate of 150 intensive care units and mechanical ventilators per day would be enough to prevent the healthcare system to collapse. Moreover, results showed that a premature relaxation of the social isolation campaign can lead to subsequent waves of contamination.

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In this work we propose a mathematical model to simulate Chikungunya spread; the spread model is implemented in a C++ cellular automata code defined on unstructured triangular grids and space visualizations are performed with Python. In order to simulate the time space spread of the Chikungunya diseases we include assumptions such as: heterogeneous human and vector densities, population mobility, geographically localized points of infection using geographical information systems, changes in the probabilities of infection, extrinsic incubation and mosquito death rate due to environmental variables. Numerical experiments reproduce the qualitative behavior of diseases spread and provide an insight to develop strategies to prevent the diseases spread.

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Cell migration has been a subject of study in a broad variety of biological systems, from morphogenetic events during development to cancer progression. In this work, we describe single-cell movement in a modular framework from which we simulate the collective behavior of glioblastoma cells, the most prevalent and malignant primary brain tumor. We used the U87 cell line, which can be grown as a monolayer or spatially closely packed and organized in 3D structures called spheroids. Our integrative model considers the most relevant mechanisms involved in cell migration: chemotaxis of attractant factor, mechanical interactions and random movement. The effect of each mechanism is integrated into the overall probability of the cells to move in a particular direction, in an automaton-like approach. Our simulations fit and reproduced the emergent behavior of the spheroids in a set of migration assays where single-cell trajectories were tracked. We also predicted the effect of migration inhibition on the colonies from simple experimental characterization of single treated cell tracks. The development of tools that allow complementing molecular knowledge in migratory cell behavior is relevant for understanding essential cellular processes, both physiological (such as organ formation, tissue regeneration among others) and pathological perspectives. Overall, this is a versatile tool that has been proven to predict individual and collective behavior in U87 cells, but that can be applied to a broad variety of scenarios.

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The loss of temperate forests of Mexico has continued in recent decades despite wide recognition of their importance to maintaining biodiversity. This study analyzes land use/land cover change scenarios, using satellite images from the Landsat sensor. Images corresponded to the years 1990, 2005 and 2017. The scenarios were applied for the temperate forests with the aim of getting a better understanding of the patterns in land use/land cover changes. The Support Vector Machine (SVM) multispectral classification technique served to determine the land use/land cover types, which were validated through the Kappa Index. For the simulation of land use/land cover dynamics, a model developed in Dinamica-EGO was used, which uses stochastic models of Markov Chains, Cellular Automata and Weight of Evidences. For the study, a stationary, an optimistic and a pessimistic scenario were proposed. The projections based on the three scenarios were simulated for the year 2050. Five types of land use/land cover were identified and evaluated. They were primary forest, secondary forest, human settlements, areas without vegetation and water bodies. Results from the land use/land cover change analysis show a substantial gain for the secondary forest. The surface area of the primary forest was reduced from 55.8% in 1990 to 37.7% in 2017. Moreover, the three projected scenarios estimate further losses of the surface are for the primary forest, especially under the stationary and pessimistic scenarios. This highlights the importance and probably urgent implementation of conservation and protection measures to preserve these ecosystems and their services. Based on the accuracy obtained and on the models generated, results from these methodologies can serve as a decision tool to contribute to the sustainable management of the natural resources of a region.

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The foremost objective of this study was to analyze the performance of a Markov chain/cellular automata model for predicting land use/land cover changes in environments predisposed to desertification. The study area is the Vieira river basin, located in Montes Claros (MG, Brazil). Land use/land cover prognosis was performed for the year 2005 so that this result could be compared with the ranked image for the same year, taken as ground truth. Kappa indices were used to evaluate the change level that occurred between these two cases. Results from cellular automata were evaluated from those of the Markov chain model. The latter proved to be efficient in the quantitative prediction of changes in land use/land cover. Regarding the cellular automata, an average performance was noted in the spatial distribution of classes. Specifically, with regard to desertification, the use of the CA-Markov model was effective at estimating the total area of the most susceptible class to this process, Bare Soil; however, it was inefficient in its spatialization. Even with the caveats related to the performance of cellular automata, the overall prediction capacity of CA-Markov models can be considered as good.

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Neste escrito, visamos a explorar os desdobramentos da figura do autômato no cinema e o fascínio que ele desperta. Sob a forma de ensaio, traçamos a genealogia do autômato na cultura, da Grécia antiga a Hollywood, e examinamos sua aparição ao longo da história do cinema, assinalando alguns dos filmes em que suas diversas facetas encontram-se representadas. Do precipitado formado pela incidência fílmica do autômato, sublinhamos os traços conferidos na Contemporaneidade a essa composição, acentuando a filiação ao homem, a natureza robótica e a obediência ao desígnio. Dialogando com a psicanálise, examinamos o conceito de duplo e de compulsão à repetição, assinalando a figura do autômato como duplo do sujeito da Contemporaneidade, encarnando a fantasia de denegação do mal-estar produzida como legado do tecnicismo, do cientificismo e do capitalismo tardio. Concluímos que os autômatos do cinema desvelam uma verdade sob o caráter de ficção: os sujeitos da Contemporaneidade fantasiam os ideais da condição maquínica.

In this article we intend to explore the displays of automaton figure on movies and the passion it arouses. Written in the form of an essay, this paper traces the automaton genealogy inside our culture, from Ancient Greece to Hollywood, and his presence in cinema history, pointing out some of the movies where its multiple appearances are represented. We have highlighted from the automaton occurrence on movies, the traces checked at contemporary times in this composition, underlining the filiation to mankind, the robotic nature and the submission to fate. Keeping a dialogue with psychoanalytical theory, the authors explore the concepts of the double and the repetition compulsion, marking the automaton figure as a double of the contemporary subject, embodying the fantasy of denying the uneasiness produced as a legacy of technicality, scientism and late capitalism. Our conclusion is that the movies automata unveil the truth hiding under the status of fiction: contemporary subjects fantasize the ideals of machinic condition

En este escrito nos proponemos estudiar, con la ayuda del psicoanálisis, los desdoblamientos de la figura del autómata en el cine y la fascinación que provoca. En forma de ensayo, rastreamos la genealogía del autómata en la cultura, desde la antigua Grecia a Hollywood, y su aparición en la historia del cine, enumerando algunas de las películas en las que sus diversas facetas son representadas. De la observación de la incidencia del autómata en películas, se destacan los rasgos que hoy en día son conferidos para esta composición, subrayando la filiación al hombre, la naturaleza robótica y la obediencia a su destino. Dialogando con el psicoanálisis, examinamos los conceptos de doble y de compulsión de repetición, teniendo en cuenta el autómata como el doble del sujeto de la actualidad, que incorpora la fantasía de negación del malestar producida como un legado del tecnicismo, del cientificismo y del capitalismo tardío. Llegamos a la conclusión de que los autómatas del cine dieron a conocer una verdad bajo el status de ficción: los sujetos contemporáneos fantasean con los ideales de la condición maquínica.

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The objective of this study was to develop an agent based modeling (ABM) framework to simulate the behavior of patients who leave a public hospital emergency department (ED) without being seen (LWBS). In doing so, the study complements computer modeling and cellular automata (CA) techniques to simulate the behavior of patients in an ED. After verifying and validating the model by comparing it with data from a real case study, the significance of four preventive policies including increasing number of triage nurses, fast-track treatment, increasing the waiting room capacity and reducing treatment time were investigated by utilizing ordinary least squares regression. After applying the preventing policies in ED, an average of 42.14% reduction in the number of patients who leave without being seen and 6.05% reduction in the average length of stay (LOS) of patients was reported. This study is the first to apply CA in an ED simulation. Comparing the average LOS before and after applying CA with actual times from emergency department information system showed an 11% improvement. The simulation results indicated that the most effective approach to reduce the rate of LWBS is applying fast-track treatment. The ABM approach represents a flexible tool that can be constructed to reflect any given environment. It is also a support system for decision-makers to assess the relative impact of control strategies.

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O artigo propõe-se a pensar algo do pathos da Modernidade ­ a paixão pelo autômato ­, à luz do conceito nietzschiano Morte de Deus. Nesse sentido, toma como matéria de análise dois clássicos do cinema de ficção científica: 2001: uma odisseia no espaço, de Stanley Kubrick, e Blade runner, de Ridley Scott. Se a paixão pelo autômato consiste em uma forma do sujeito moderno denegar a finitude, nos filmes em debate tal condição é elaborada de um modo muito singular. 2001 e Blade runner oferecem ao espectador a possibilidade de resistir à assunção dessa inclinação da subjetividade moderna. Em 2001, o autômato é demasiado humano e uma narrativa trágica promove outro modo de enfrentar a finitude. Em Blade runner, o autômato é o portador das angústias fundamentais do sujeito moderno ­ origem e finitude ­ e a identificação a ele permite ao espectador ir além do homem. (AU)

The article proposes to address an issue from Modernity pathos ­ the passion for the automaton ­, in the light of Nietzschian Death of God concept. In this sense, it analyses two science fiction classic movies: 2001: a space odyssey, by Stanley Kubrick, and Blade runner, by Ridley Scott. If passion for the automaton consists in a form of the modern subject to deny finitude, in the films here discussed such condition is elaborated in a very peculiar way. 2001 and Blade runner offer the spectator the possibility of resisting the assumption of such tendency of modern subjectivity. In 2001, the automaton is too human and a tragic narrative promotes another way of tackling finitude. In Blade runner, the automaton is the bearer of fundamental anguishes of the modern subject ­ origin and finitude ­ and by identifying with him the viewer is allowed to go beyond man. (AU)

El artículo se propone a pensar algo respecto al pathos de la Modernidad ­ la pasión por lo autómata ­ bajo el concepto de Nietzsche Muerte de Dios. En este sentido, el análisis toma como materia dos clásicos del cine de ciencia ficción: 2001: una odisea del espacio, de Stanley Kubrick, y Blade runner, de Ridley Scott. Si la pasión por lo autómata consiste en una forma del sujeto moderno denegar la finitud, en esas películas tal condición es elaborada de una manera muy singular. 2001 y Blade runner ofrecen al espectador la posibilidad de resistir a la asunción de tal inclinación de la subjetividad moderna. En 2001, el autómata es demasiado humano y una narrativa trágica promueve otro modo de enfrentar la finitud. En Blade runner, el autómata es el portador de las angustias fundamentales del sujeto moderno ­ de origen y finitud ­ y la identificación a él le permite al espectador ir más allá del hombre. (AU)

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