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Los sistemas complejos se caracterizan por exhibir comportamientos a nivel macroscópico para los cuales es muy difícil obtener descripciones generalizadas partiendo de conocer la dinámica de sus componentes microscópicos. Un aspecto esencial de estos sistemas radica en las interacciones entre sus componentes, las que a su vez pueden cambiar en el tiempo en función del estado macroscópico al cual contribuyen. En este contexto, las ciencias de la complejidad han recurrido históricamente a modelos de simulación computacional en busca de un laboratorio in silico para aquellos fenómenos complejos que no admitan una descripción analítica ni técnicas de experimentación controlada y repetible en laboratorio. Si bien la experimentación numérica computacional cuenta con una madurez sustentada en más de 70 años de desarrollo, en gran medida los algoritmos de simulación permanecen -aún en la práctica actual- sujetos a ambigüedades y/o poca transparencia, propias del terreno de lo artesanal. Este aspecto exacerba las dificultades de proveer modelos de simulación fácilmente comprensibles y reproducibles por la comunidad científica, conduciendo frecuentemente a réplicas artesanales de algoritmos no exentas de la introducción de errores. En cambio, los métodos formales de modelado y simulación buscan mitigar estos problemas mediante protocolos estrictos que permitan reproducir simulaciones correctas y libres de ambigüedades, partiendo de especificaciones matemáticas formales de los modelos a ser simulados. En esta Tesis potenciamos las capacidades del formalismo de modelado y simulación DEVS (Discrete Event System Specification) basado en la Teoría General de Sistemas, extendiendo su aplicación al estudio de sistemas complejos adaptativos generalizados, es decir, aquellos en los que sus partes componentes pueden ser de naturaleza híbrida (continuas o discretas, determinísticas o estocásticas, de estructura fija o variable, con o sin retardos). Dotamos al formalismo con nuevas estructuras y funciones que permiten razonar sobre el comportamiento macroscópico emergente, permitiendo a su vez que dinámicas de nivel microscópico sean una función del nivel superior, dando así lugar a dinámicas micro-macro de realimentación a lazo cerrado. El resultado es EB-DEVS (por Emergent Behavior DEVS), un formalismo que permite expresar sistemas complejos de forma modular e incremental, con tantos niveles de jerarquía espacio-temporal como se requiera. Proveemos demostraciones de que EB-DEVS es equivalente a DEVS Clásico en términos de bisimulación, permitiendo así que nuevos modelos EB-DEVS sean compatibles e integrables con la gran base de conocimiento existente para modelos DEVS. Desde el punto de vista de las aplicaciones, presentamos resultados de modelado y simulación que extienden diferentes modelos clásicos en la literatura de sistemas complejos en ciencias sociales, biología e ingeniería, mediante los cuales introducimos buenas prácticas de modelado y mostramos ventajas y limitaciones de EB-DEVS, especialmente en lo relacionado a su capacidad de detección de propiedades emergentes en tiempo de simulación. En particular, exploramos la incorporación de un índice de desigualdad en el modelo Sugarscape, modas en el modelo de Diseminación de Cultura, una distribución de grados con sesgo de tamaño en un modelo Preferential Attachment, un índice de felicidad en el modelo de Segregación, cuarentenas en un modelo epidemiológico SIR, reactividad a la formación de grupos en el modelo de Flocking y homeostasis mitocondrial en un modelo celular. Finalmente, proponemos una metodología para aplicar el enfoque de sistemas complejos adaptativos a proyectos guiados por modelado y simulación de sistemas ingenieriles, específicamente en el ámbito de arquitecturas complejas de cómputo y redes de comunicaciones para un contexto de grandes datos en experimentos de Física de Altas Energías. Complex systems are characterized by behaviors at the macroscopic level for which it is very difficult to obtain generalized descriptions based on knowledge of the dynamics of their microscopic components. An essential aspect of these systems lies in the interactions between their components, which in turn can change over time depending on the macroscopic state to which they contribute. In this context, the complexity sciences have historically resorted to computational simulation models in the quest for an in silico laboratory for those complex phenomena that do not admit an analytical description or controlled and repeatable real-world experimental techniques. Although computational numerical experimentation has a maturity supported by more than 70 years of development, to a large extent simulation algorithms remain -even in current practice- subject to ambiguities and/or lack of transparency, typical of the field of craftsmanship. This aspect exacerbates the difficulties of providing simulation models that are easily understandable and reproducible by the scientific community, often leading to hand-crafted replications of algorithms that are not free from the introduction of errors. In contrast, formal modeling and simulation methods seek to mitigate these problems by means of strict protocols that allow reproducing correct and unambiguous simulations, starting from formal mathematical specifications of the models to be simulated. In this Thesis we enhance the capabilities of the DEVS (Discrete Event System Specification) modeling and simulation formalism based on General Systems Theory, extending its application to the study of generalized adaptive complex systems, i.e., those in which their component parts can be of hybrid nature (continuous or discrete, deterministic or stochastic, fixed or variable structure, with or without delays). We endow the formalism with new structures and functions that allow reasoning about the emerging macroscopic behavior, in turn allowing microscopic level dynamics to be a function of the higher level, thus giving rise to closed-loop feedback micro-macro dynamics. The result is EB-DEVS (Emergent Behavior DEVS), a formalism that allows complex systems to be expressed in a modular and incremental fashion, with as many levels of spatio-temporal hierarchy as required. We provide proofs that EB-DEVS is equivalent to Classical DEVS in terms of bisimulation, thus allowing new EB-DEVS models to be compatible and integrable with the large existing knowledge base for DEVS models. From an applications point of view, we present modeling and simulation results that extend different classical models in the literature of complex systems in social sciences, biology, and engineering, whereby we introduce good modeling practices and show advantages and limitations of EB-DEVS, especially as related to its ability to detect emergent properties at simulation time. In particular, we explore the incorporation of an inequality index in the Sugarscape model, fashion in the Culture Dissemination model, a size-biased degree distribution in a Preferential Attachment model, a happiness index in the Segregation model, quarantines in an epidemiological SIR model, reactivity to group formation in the Flocking model, and mitochondrial homeostasis in a cellular model. Finally, we propose a methodology to apply the complex adaptive systems approach to projects guided by modeling and simulation of engineering systems, specifically in the field of complex architectures of computation and communication networks for a context of big data in High Energy Physics experiments. Fil: Foguelman, Daniel Jacobo. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) The literature lacks details on how research and technology organizations (RTOs) of innovation systems in formation can coordinate resources, processes and practices, directing them to improve performance and competitiveness. In this thesis, concepts about success factors, challenges and managerial constraints are unfolded to elaborate an analysis model of Research, Development and Innovation (RD&I) operations management dynamics in Brazilian RTOs for the characterization of factors (drivers and constraints) that affect it. Its constructs are based on: i) operational components, managerial dimensions and articulations, representative of theirs specificities, systematically collected from specialized literature focused on the study objects, from the theory on complex adaptive systems and from contributions of an exploratory case study conducted in an university center of research and technology; and ii) propositions about relations that are established between managerial dimensions and articulations present in the operational dynamics of RD&I. They were verified by means of a detailed application, in a case study conducted in a research and technology institute of São Paulo, proving to be viable to the understanding proposed in the context studied, with considerations about its aspects that can be improved and that may be increased by new applications. This thesis raises up some recommendations and reflections for the strengthening of intra and inter-institutional articulations effectiveness for the cases conducted, confirming the usefulness and the originality of the model for the characterization of factors that affect the management of RD&I operations in RTOs. A literatura carece de detalhes sobre como institutos e centros de pesquisa e tecnologia (ICTs) de sistemas de inovação em formação podem coordenar recursos, processos e práticas, direcionando-os à melhoria de desempenho e de competitividade. Nesta tese, conceitos sobre fatores de sucesso, desafios e limitações gerenciais são desdobrados para a elaboração de um modelo de análise da dinâmica de gestão de operações de Pesquisa, Desenvolvimento e Inovação (PD&I) em ICTs brasileiros para a caracterização de fatores (drivers e limitadores) que a afetam. Os construtos do modelo baseiam-se em: i) componentes operacionais, dimensões gerenciais e articulações, representativos de especificidades de ICTs, levantados sistematicamente de literatura especializada, voltada aos objetos de estudo, de teoria sobre sistemas complexos adaptativos e de contribuições de um estudo de caso exploratório conduzido em um centro de pesquisa e tecnologia universitário; e ii) proposições sobre relações que se estabelecem entre dimensões gerenciais e articulações presentes na dinâmica operacional de PD&I. Eles foram verificados por meio de uma aplicação detalhada, em estudo de caso conduzido em um instituto de pesquisa e tecnologia paulista, mostrando-se viáveis à compreensão proposta no contexto estudado, sendo realizadas considerações sobre os seus aspectos passíveis de melhorias e que poderão ser incrementados por novas aplicações. Esta tese também levanta algumas recomendações e reflexões para o fortalecimento de articulações intra e interinstitucionais mais efetivas para os casos conduzidos, confirmando a utilidade e a originalidade do modelo para a caracterização de fatores que afetam a gestão de operações de PD&I em ICTs. CAPES: Código de Financiamento 001

Organismal ageing is associated with many physiological changes, including differences in the immune system of most animals. These differences are often considered to be a key cause of age-associated diseases as well as decreased vaccine responses in humans. The most often cited vaccine failure is seasonal influenza, but, while it is usually the case that the efficiency of this vaccine is lower in older than younger adults, this is not always true, and the reasons for the differential responses are manifold. Undoubtedly, changes in the innate and adaptive immune response with ageing are associated with failure to respond to the influenza vaccine, but the cause is unclear. Moreover, recent advances in vaccine formulations and adjuvants, as well as in our understanding of immune changes with ageing, have contributed to the development of vaccines, such as those against herpes zoster and SARS-CoV-2, that can protect against serious disease in older adults just as well as in younger people. In the present article, we discuss the reasons why it is a myth that vaccines inevitably protect less well in older individuals, and that vaccines represent one of the most powerful means to protect the health and ensure the quality of life of older adults., Inria Associated Team "NeuroTransSF"

Os estilos de aprendizagem significam que há muitas formas de aprender, o que incentiva os docentes a inovar e influencia o futuro da escola. Assim, as interações resultam em mudanças e inovações e constituem-se como liderança, o que desafia a visão tradicional em que os líderes formais determinam o futuro e o caminho para aí chegar. Isto traduz um sistema complexo (muitos agentes em interação) que se adapta em função dos estímulos que os alunos colocam, o que aconselha a que se reflita sobre as consequências da complexidade das escolas e aprendizagem na gestão e liderança educacional. São apresentadas as caraterísticas dos sistemas adaptativos complexos e discutidas as consequências da variabilidade e complexidade na liderança e documentos e processos estruturantes das organizações educativas. As conclusões sugerem que a pesquisa nestas áreas, à luz da teoria da complexidade, pode concorrer para que a organização das escolas favoreça os docentes que buscam adaptar-se aos estilos de aprendizagem. Learning styles means that there are many ways of learning, which encourages teachers to innovate and influences the future of schools. Thus, interactions result in changes and and can be seen as leadership, which challenges the traditional view that the formal leaders determine the future and the way to get there. This translates a complex system (many agents interacting) that adapts depending on the input stimuli of the students and recommends reflexion upon the consequences of the complexity of schools and learning in management and educational leadership. We present the characteristics of complex adaptive systems and discuss the consequences of the variability and complexity on leadership, documents and structuring processes of educational organizations. The conclusions suggest that research in these areas, in the light of complexity theory, can contribute, trough school organization, to teacher adaptation to pupils learning styles. info:eu-repo/semantics/publishedVersion

Is love predictable in its choices? Linear Determinism, Randomness or Complexity? By applying theoretical coordinates of current sociological interpretations of intimacy and conceptual categories of New General System Theory, the paper reflects on one-factor and linear determinism implicitly underlying mate selection processes in Structural Coupling Theory and its implications for Intimate Partner Violence (IPV). Assuming personality structure as the predictor of partner choice as well as victimization risk, SCT circumscribes victimization risk just to one category of women (insecure/avoidant women coupling with ambivalent partners). We propose that adaptive complex system and non-banal machine concepts are more effective to understand the mate selection process than linear deterministic approach, which appears too mechanistic for a process that exhibits an inextricable dimension of uncertainty and unpredictability. Research results on a sample of 100 victims of IPV do not corroborate the linear one-factor determinism underlying Structural Coupling Theory neither its implications. Rather they go in the direction of Complexity.

International audience; For the founder of Austrian economics, Carl Menger (1840-1921), many social institutions are “organic” in origin, not voluntarily created (not “pragmatic”). Today, they may be regarded as complex adaptive systems, pieces of evidence of evolutionism. Money (as Menger sees it) fits such an explanation and bears witness to emerging socio-economic phenomena. We regard present-day evolutionary systems, based upon three principles (variation, interaction and selection) as anticipated by Menger.; Pour le fondateur de l’école autrichienne, Carl Menger (1840-1921), nombre d’institutions sociales sont « organiques », non volontaires (« pragmatiques »). En épistémologie, aujourd’hui, elles peuvent s’interpréter comme systèmes adaptatifs complexes. Ainsi la monnaie selon Menger. On la confronte ici aux systèmes adaptatifs complexes vus comme évolutifs et fondés sur trois principes fondamentaux : variation, interaction et sélection. Menger les anticipe ou du moins conduit à eux en droit fil.

We are witness, and actors, in a changing world, different from that proceed and unpredictable, whose main characteristic is its complex nature. A changing world with a level of unprecedented interconnectedness and interdependence (cause of its complexity), with new structures (networks) and new social technologies that shape the Internet as a transformation digital infrastructure and also of adequation. As a result, a “new expanded and complex vital environment”, has a significant impact in the way we interact, live, work and learn. We are therefore facing a new class of situations or problems (complex) that, when we face the same, we need not only change how we think and perceive reality (systems thinking), but also the adoption of a new digital culture, where interdependence and sustainability prevails. We call “complexity gap”, the difficulty that entails the assimilation and practise of such requirements, which at the same time represents the main challenge we are faced with today. Referred to as “complexity gap”, the difficulty involved in the assimilation and practice of these requirements and, in turn, is the main challenge we face today. Finally, from an of organic growth perspective (“bottom-up”), considering the person as “complex adaptive system”, it is proposed profile “eAprendiz” as a strategy for adaptation and personal, and professional, empowerment, in the current global “extended and complex environment”. Finally, from an organizational development (“bottom-up”), and considering the person as “complex adaptive system”, it is proposed profile “eAprendiz” as a strategy for adaptation and personal, and professional, empowerment, in the current global, extended and complex environment., Estamos siendo testigos, y a la vez actores, de un mundo en transformación, distinto del que procedemos e impredecible, cuya característica principal es su naturaleza compleja. Un mundo en transformación con un nivel de interconexión e interdependencia sin precedentes (causa de su complejidad), con nuevas estructuras (redes) y con nuevas tecnologías sociales, que configuran a Internet como infraestructura digital de transformación (disruptiva) y, también, de adecuación. Como resultado de todo ello, un “nuevo ENTORNO vital, expandido y complejo”, impacta notablemente en la manera en que nos relacionamos, vivimos, trabajamos y aprendemos. Nos encontramos, pues, ante una nueva clase de situaciones o problemas (complejos) que, a la hora de enfrentarnos a los mismos, nos requiere no solo cambiar nuestra forma de pensar y percibir la realidad (pensamiento sistémico), sino también la adopción de una nueva cultura digital, de interdependencia y sostenibilidad. Denominamos como “brecha de la complejidad”, a la dificultad que conlleva la asimilación y práctica de dichos requerimientos y que, a su vez, constituye el principal reto al que nos enfrentamos en la actualidad. Por último, desde una perspectiva de desarrollo orgánico (“bottom- up”), y considerando a la persona como “sistema complejo adaptativo”, se propone el perfil “eAprendiz” como estrategia de adecuación y empoderamiento personal, y profesional, en el actual entorno global, “extendido y complejo”.

Pour le fondateur de l’école autrichienne, Carl Menger (1840-1921), nombre d’institutions sociales sont « organiques », non volontaires (« pragmatiques »). En épistémologie, aujourd’hui, elles peuvent s’interpréter comme systèmes adaptatifs complexes. Ainsi la monnaie selon Menger. On la confronte ici aux systèmes adaptatifs complexes vus comme évolutifs et fondés sur trois principes fondamentaux : variation, interaction et sélection. Menger les anticipe ou du moins conduit à eux en droit fil., For the founder of Austrian economics, Carl Menger (1840-1921), many social institutions are “organic” in origin, not voluntarily created (not “pragmatic”). Today, they may be regarded as complex adaptive systems, pieces of evidence of evolutionism. Money (as Menger sees it) fits such an explanation and bears witness to emerging socio-economic phenomena. We regard present-day evolutionary systems, based upon three principles (variation, interaction and selection) as anticipated by Menger.

Ce mémoire d’habilitation présente l’état de mes travaux sur l’ingénierie des connaissances pour traiter de l’hétérogénéité des données issues de systèmes sociaux.Mes travaux ont d’abord porté sur des algorithmes d’apprentissage, puis sur des systèmes d’agents en co-évolution avant que je ne modélise et ne simule des systèmes plus sophistiqués d’acteurs sous la forme de modèles spatiaux à trois niveaux correspondant à des phénomènes sociaux réels comme la mobilisation de masse en RDA en 1989. Ces recherches étaient réalisées en coordination avec Wolf-Dieter Eberwein, spécialiste en Sciences Politiques.Cette modélisation m’a amené à identifier le concept d’hétérarchie pour modéliser des systèmes hétérogènes multi-agents et multi-niveaux.J’ai également utilisé cette notion d’hétérarchie pour concevoir des modèles d’évolution du système juridique de gestion des données personnelles.Toujours dans le cadre de l’étude des hétérogénéités des données issues de systèmes sociaux j’ai ensuite travaillé avec Francis Rousseaux et Eddie Soulier sur des modèles d’ingénierie des connaissances s’appuyant sur l’intelligence territoriale et l’hétérogénéité des lieux, les hétérotopies.Ces travaux se poursuivent avec Francis Rousseaux et Jean Petit, un doctorant nouvellement inscrit.Mes travaux les plus récents avec Francis Rousseaux et Guillaume Blot, un doctorant que j’encadre, portent sur les hétérogénéités temporelles constatées lors de parcours de contenus de connaissance accessibles en e-learning.Ces recherches sur les systèmes multi-agents présentant différentes formes d’hétérogénéités m’ont amené à les replacer dans le contexte des systèmes plus classiques d’intelligence artificielle construits sur les capacités rationnelles individuelles des agents.Je dégage dans ce mémoire la notion d’altérité radicale qui fédère ces travaux sur les systèmes multi-agents hétérogènes et produit des données elles-mêmes hétérogènes pour des systèmes d’agents.Pour cette hétérogénéité je propose des familles d’opérateurs et je présente brièvement quelques-unes de leurs propriétés.J’indique enfin des travaux qui pourront faire l’objet de sujets de thèses à venir ou qui sont déjà en cours de traitement par des doctorants et qui mettent en jeu différentes formes d’hétérogénéité présentées ici.

We are witness, and actors, in a changing world, different from that proceed and unpredictable, whose main characteristic is its complex nature. A changing world with a level of unprecedented interconnectedness and interdependence (cause of its complexity), with new structures (networks) and new social technologies that shape the Internet as a transformation digital infrastructure and also of adequation. As a result, a “new expanded and complex vital environment”, has a significant impact in the way we interact, live, work and learn. We are therefore facing a new class of situations or problems (complex) that, when we face the same, we need not only change how we think and perceive reality (systems thinking), but also the adoption of a new digital culture, where interdependence and sustainability prevails. We call “complexity gap”, the difficulty that entails the assimilation and practise of such requirements, which at the same time represents the main challenge we are faced with today. Referred to as “complexity gap”, the difficulty involved in the assimilation and practice of these requirements and, in turn, is the main challenge we face today. Finally, from an of organic growth perspective (“bottom-up”), considering the person as “complex adaptive system”, it is proposed profile “eAprendiz” as a strategy for adaptation and personal, and professional, empowerment, in the current global “extended and complex environment”. Finally, from an organizational development (“bottom-up”), and considering the person as “complex adaptive system”, it is proposed profile “eAprendiz” as a strategy for adaptation and personal, and professional, empowerment, in the current global, extended and complex environment. Estamos siendo testigos, y a la vez actores, de un mundo en transformación, distinto del que procedemos e impredecible, cuya característica principal es su naturaleza compleja. Un mundo en transformación con un nivel de interconexión e interdependencia sin precedentes (causa de su complejidad), con nuevas estructuras (redes) y con nuevas tecnologías sociales, que configuran a Internet como infraestructura digital de transformación (disruptiva) y, también, de adecuación. Como resultado de todo ello, un “nuevo ENTORNO vital, expandido y complejo”, impacta notablemente en la manera en que nos relacionamos, vivimos, trabajamos y aprendemos. Nos encontramos, pues, ante una nueva clase de situaciones o problemas (complejos) que, a la hora de enfrentarnos a los mismos, nos requiere no solo cambiar nuestra forma de pensar y percibir la realidad (pensamiento sistémico), sino también la adopción de una nueva cultura digital, de interdependencia y sostenibilidad. Denominamos como “brecha de la complejidad”, a la dificultad que conlleva la asimilación y práctica de dichos requerimientos y que, a su vez, constituye el principal reto al que nos enfrentamos en la actualidad. Por último, desde una perspectiva de desarrollo orgánico (“bottom- up”), y considerando a la persona como “sistema complejo adaptativo”, se propone el perfil “eAprendiz” como estrategia de adecuación y empoderamiento personal, y profesional, en el actual entorno global, “extendido y complejo”.

Este artigo constitui-se numa investigação fundada na visão evolucionista sobre o crescimento econômico, inovação e competição. Nosso ponto de partida é a idéia de que o sistema econômico é composto por múltiplos agentes, diversos em habilidades e capacidades, interagindo e reagindo uns com os outros de forma a se adaptar ao ambiente em que estão inseridos. Neste processo, os agentes econômicos acabam por modificar os padrões de comportamento e as estruturas que eles próprios ajudaram a criar. O artigo está construído em torno de duas idéias principais. A primeira é a de que o processo de tomada de decisões deve ser analisado através do conjunto de regras e rotinas que os agentes econômicos – em particular, as empresas – dispõem para decidir qual o curso de ação que devem tomar. Este tratamento permite recuperar a questão da micro-diversidade e da relevância de padrões de conduta. A segunda idéia está relacionada à importância do crescimento econômico como um fenômeno emergente. Como tal, os processos de transformação podem ser divididos em três elementos: processos de seleção, processos de criação de novidades (micro-diversidade) e processos de desenvolvimento. A forma de interdependência entre estes elementos vai ajudar a definir a própria relação entre inovação, crescimento e competição. No contexto do artigo, a questão-chave está na especificação da concorrência como um processo de seleção. Para avaliar o crescimento e desenvolvimento de categorias relevantes dentro das populações tomamos como base os princípios de Fisher e seus desdobramentos nas equações de replier dynamics. Acreditamos que o artigo possa ajudar a esclarecer os elementos centrais presentes na teoria evolucionista do crescimento endógeno, estabelecendo seus fundamentos no processo de conhecimento.This paper reports on the initial investigation into an evolutionary adaptive account of economic growth, innovation and competition. It starts from the premise that the economy is a system comprising multiplicity of agents, diverse in abilities and capabilities, interacting, adapting, reacting and constantly modifying the patterns on structures that they help to create. Two themes in special are explored in this context. The first it is enterprise as the primum mobile of modern capitalist economies. The second relates to the importance of the economic growth as an emergent phenomenon. The transformation processes involved can be broken down into three elements: micro-diversity, selection processes and development processes. It is the manner of interdependence between these three elements that defines the relation between innovation, growth and competition. We explore these issues in a model of growth whose forms differ in three dimensions: efficiency, investment behavior and processes of cost reducing innovation. The dynamics of Fisher´s principles are explored in this context. The main result of this paper can be summarized as being a critical assessment of the knowledge foundations of endogenous growth theory, a clear statement of the core elements in an evolutionary adaptive theory of growth and the analysis of economic growth through the use of replier dynamic processes.

Signal distortions in communication systems occur between the transmitter and the receiver; these distortions normally cause bit errors at the receiver. In addition interference by other signals may add to the deterioration in performance of the communication link. In order to achieve reliable communication, the effects of the communication channel distortion and interfering signals must be reduced using different techniques. The aim of this paper is to introduce the fundamentals of Orthogonal Frequency Division Multiplexing (OFDM) and Orthogonal Frequency Division Multiple Access (OFDMA), to review and examine the effects of interference in a digital data communication link and to explore methods for mitigating or compensating for these effects.