Les modèles biomécaniques éléments finis (EF) sont couramment utilisés dans de nombreux domaines. Ces modèles tendent depuis quelques années à être actifs, capable donc de générer des efforts musculaires et des mouvements. L’étape suivante consiste à rendre ces modèles réactifs, c’est-à-dire capable de réagir à une situation quelconque par des contractions musculaires et des mouvements. C’est dans cet optique que ce projet a été décomposé en 3 étapes. La première consistait à réaliser un modèle biomécanique détaillé capable de contractions musculaires et de mouvements. La seconde étape consistait à introduire des réflexes. Pour cela des modèles de capteurs sensoriels (fuseaux neuromusculaires et organes tendineux de golgi) et les réflexes associés (réflexes myotatiques et myotatiques inverses) ont ensuite été introduits au sein même du modèle. Le modèle ainsi obtenu a pu ensuite être validé grâce à une campagne expérimentale de quantification du réflexe d’étirement du tendon du biceps brachial. La dernière étape consistait à introduire des réactions de niveau supérieur, c’est-à-dire des mouvements volontaires. Pour cela une méthode de contrôle basée sur de l’apprentissage et l’optimisation a permis de générer ces mouvements et de les contrôler.En conclusion, l’introduction de boucles sensorielles et motrices de différents niveaux dans un modèle EF permet de rendre ce dernier réactif à son environnement. En effet, le modèle est ainsi capable de générer un mouvement selon des objectifs et des contraintes. Il est également capable d’adapter la contraction musculaire en fonction des évènements intervenant lors de la réalisation du mouvement. / Biomechanical finite elements (FE) models are commonly used in the field of road safety, sport and medicine. These models tended in recent years to be active, i.e. able to generate muscular efforts or movements. The next step is to make these models reactive, i.e. able to react to a situation with muscle contractions and movement. It is in this context that this project was broken down into 3 steps. The first step was to create a detailed biomechanical model capable of movements and muscle contractions. The second step was to introduce reflexes. For this, physiological sensors models (neuromuscular spindles and golgi tendon organs) and the associated reflexes associated (myotatic and inverse myotatic reflexes) were then integrated into the model. The model thus obtained could then be validated thanks to an experimental campaign of characterization of the deep tendon reflex of the biceps brachial. The last step was to introduce higher-level reactions, i.e. voluntary movements. For this purpose, a control method based on learning and optimization has made it possible to generate and control these movements.In conclusion, the introduction of sensory and motor loops of different into an FE model makes the latter reactive to its environment. Indeed, the model is thus able to generate a movement according to objectives and constraints. He is also able to adapt the muscular contraction according to the events intervening during the realization of the movement.

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O presente trabalho propõe-se a oferecer respostas à questão de como a informação é preservada num sistema, focalizando-se na distinção entre os papéis desempenhados pelos constituintes elementares e pelos estruturais na preservação da memória desse sistema. Os sistema simulados circunscreveram-se a malhas, com diferentes graus de regularidade, compostas pelo acoplamento de osciladores não-lineares que apresentam comportamento coerente no estado de equilíbrio. Malhas de Sincronismo de Fase, também conhecidas por PLLs (Phase Locked Loops), foram adotadas como elementos constituintes básicos dos sistemas analisados. Para tanto, utilizou-se a plataforma de cálculo MATLAB-SIMULINK, acompanhando-se as evoluções dos diversos sistemas e de seus parâmetros dinâmicos associados, possibilitando o estabelecimento da correspondência entre os valores dos referidos parâmetros dinâmicos com parâmetros gráficos \"sensíveis\" à estrutura das malhas. Os resultados obtidos indicam a coexistência/cooperação das componentes estrutural e elementar na determinação dos valores dos parâmetros dinâmicos no estado de equilíbrio do sistema. No entanto, evidencia-se que tais componentes apresentam importâncias distintas na determinação dos diferentes parâmetros dinâmicos. / This work was conceived aiming to present some answers to how the information is preserved in a system. The focus was laid on the distinction between the tasks played by the elementary components and the structure of the system. The simulated systems were composed by coupled oscillators, more precisely by PLLs (Phase Locked Loops), arranged in networks of different regularities. Simulations were performed using Matlab-Simulink software to build a correlation between the final state dynamical parameters of the system and its degree of regularity. Results show the influence of both elementary and structural components on the system attained state. However the responses of characteristics parameters of the system to changes in the regularity of the structured network may greatly differ from one parameter to another. This behavior may suggest different strategies to preserve information of the system according to the information to be kept.

In recent years, neuromorphic architectures have been an increasingly effective tool used to solve big data problems. Hardware neural networks have not been able to fully exploit the power efficient properties of the neural paradigm, however, due to limitations in standard CMOS. One of the largest challenges is the quadratic scaling of the synapses in a neural network. There has been some work in using post CMOS technology as synapses to overcome this limitation, but systems to date have not been scalable due to the design of their neurons. This dissertation aims to design and build scalable neural network architectures that can use emerging resistive memory technology as synapses. Using analog computing techniques to build networks is promising, especially due to the development of dense, CMOS compatible analog resistive memories. Building functional analog networks in advanced technology nodes, however, is challenging due to the relatively poor performance of analog components in these nodes. This work explores oscillatory neural networks (ONNs), which use phase as the analog state variable instead of voltage or current, reducing the number of traditional analog components required and making the networks better-suited for advanced nodes. This thesis develops additional ONN theory with regard to hardware networks, since previous work did not consider the effect of transmission delay on network dynamics. Transmission delay is proven to cause desynchronization in unmodified ONNs, and the theoretical analysis suggests ways to build networks which do synchronize. Conclusions from the theoretical development are used to build a PLL-based ONN in hardware. The PLL-based ONN is more energy efficient than comparable systems implemented in digital CMOS, although the neuron area is somewhat larger. The measurement of the PLL-based ONN also reveals additional poorly-studied facets of ONN dynamics. Using the knowledge gained from the PLL-based ONN, a larger, PLL-free ONN is built in the same technology. Removing the PLL in each neuron reduces the power and area consumption without sacrificing any functionality.This dissertation demonstrates that ONNs are well-suited to take advantage of emerging resistive memory technology to build efficient hardware neural networks.

As some of the most important and widely utilised intercellular signalling molecules, transforming growth factor βs (TGFβs) play critical roles in normal development and in human disease. Establishing appropriate levels of signalling involves positive and negative feedback, driven by the same signal transduction components, but whether or how the two are distinguished has not previously been understood. Here we show that LIM domain binding proteins (Ldbs) drive the Smad6/7-mediated negative feedback of TGFβ signalling, but they are not required for the ligand-driven positive feedback or other downstream transcriptional activation. In Ldb-deficient zebrafish embryos, the homeostasis of TGFβ signalling is perturbed. As a consequence, signalling of TGFβ family members, Nodal and BMP, is stably enhanced, giving rise to excess mesoderm and endoderm, an effect that can be rescued by reducing Nodal and BMP. Later in development, conditional ldb2a knockdown causes defective vascular, angiogenic and haemogenic development, likely also by elevating TGFβ signalling. Thus, Ldbs control the homeostatic regulation of TGFβ signalling and therefore play critical roles in diverse developmental processes.

The gauge/string duality, a.k.a. the holographic principle is a profound assertion that emerged from string theory. It relates strongly-coupled gauge theories to weakly coupled string theories living in a higher-dimensional curved geometry. Nevertheless, it is a conjecture, and only a few instances of its more concrete form, the AdS/CFT correspondence, are well-understood. The most well-studied example is the duality between N=4 SYM, which is a CFT, and type IIB string theory in AdS5xS5 background. Generalization to less symmetric cases is a must, and the next logical step is to add a mass scale to N=4 SYM, therefore breaking its conformal symmetry and leading to N=2* SYM, the theory we study in this thesis. It is supersymmetric enough to employ the powerful localization method that reduces its partition function to a matrix model. We will see that the mass scale causes non-trivial phase structures in its vacuum configuration, visible in the holographic regime. We will probe them using Wilson loops in different representations of the gauge group. On the other hand, the dual supergravity background was derived by Pilch-Warner, making N=2* theory an explicitly testable non-conformal holographic case, which is a rare example. We will prove that the duality works for the dual observables (string action, D-branes) we managed to compute, even at a quantum-level.

Thesis: M.S., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 1976 / Includes bibliographical references. / M.S. / M.S. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science

This essay is one part of my Bachelor's degree project, the other part being the work LOOPAR that was premiered in January of 2021 at Stockholm University of the Arts. The text expands and articulates the thinking processes and conversations in relation to the work. The aim of the text is to acknowledge and reflect the thoughts around the work with other people, dancers, and thinkers, and to scrutinize the main questions of the work: How can we think of repetition in relation to subject formation? And how does repetition and looping construct and affect world making? The essay begins by introducing the main concepts of the work such as 'performativity’, ’subject’, ‘storytelling’, ‘branding’, ‘repetition’ and ‘looping’. In the text, loops can be seen as actions, habits, repeated thinking processes, understandings of norms or different kinds of interactions, which change and transform our perception and understanding constantly about ourselves and the world we live in through persistent repetition. The essay observes how our experiences of ourselves and the world are affected by multiple contexts and felt-sensed experiences and interactions. It further explores the potentialities to decentralize the focus of the individualistic point of views of world making and it moves towards relational ways of thinking. The main references and conversation partners to many of the topics discussed in the essay are Argentine feminist philosopher and activist María Lugones, American professor of Feminist studies, Philosophy and History of Consciousness with a Ph.D. in Physics Karen Barad, and American philosopher and gender theorist Judith Butler. Further the essay reflects the work and methods used in praxis in relation to the thinking processes introduced in the text. At the end the essay asks the two following questions: How we can practice active consciousness and responsibility towards a subject’s positionality and interactions in dancing? And how can dancing together and alone be understood as entangled and overlapped?

The growing interest in sustainability amounts pressure on organisations to operate in more environmentally friendly ways, sparking the need for radical sustainable change. The purpose of this study is to discover what factors and conditions facilitate and hinder organisational learning for sustainability transitions (ST), a topic that has caught recent academic attention and thus needs further interdisciplinary research. The conceptual framework derives inspiration from the Four Factors of Learning for ST whilst the Competing Values Framework and the Three Loops of Learning are used as additional lens to better understand the conditions of learning for ST. The thesis will take a qualitative approach through conducting a content analysis of three company documents and seven semi-structured interviews with employees from a public service agency in Scandinavia currently implementing a transition lab. A descriptive analysis of the coded data highlights the levels of understanding and acceptance towards sustainability transitions from the case organisation and the conditions that facilitate and hinder organisational learning. The results show that the most prominent of the Four Factors of Learning for ST in the early phase of a sustainability transition is interpersonal, followed by material, institutional and intrapersonal. Within these factors, the discussion further highlights the most prevalent sub-codes and themes that reoccur in the data. Moreover, five key findings under the themes of flexibility versus control, resource availability through digitalisation, communication, collaboration and facing complexity using institutional logics were identified as the primary facilitating and hindering factors that promote learning for STs. Finally, recommendations are presented to inform both theory, and practice, as further analysing learning for ST is of high relevance to better understand and design these learning journeys and a more sustainable (organisational) future.