A time-stepping method for non-smooth mechanical systems

International audienceTime-stepping algorithms allow a robust simulation of dynamical problems with many unilateral constraints and friction. Its idea is to calculate velocity updates instead of accelerations. As a consequence, contact behaviour and impact can be treated by the same equations

Formulation and Preparation for Numerical Evaluation of Linear Complementarity Systems in Dynamics

In this paper, we provide a full instruction on how to formulate and evaluate planar frictional contact problems in the spirit of non-smooth dynamics. By stating the equations of motion as an equality of measures, frictional contact reactions are taken into account by Lagrangian multipliers. Contact kinematics is formulated in terms of gap functions, and normal and tangential relative velocities. Associated frictional contact laws are stated as inclusions, incorporating impact behavior in form of Newtonian kinematic impacts. Based on this inequality formulation, a linear complementarity problem in standard form is presented, combined with Moreau's time stepping method for numerical integration. This approach has been applied to the woodpecker toy, of which a complete parameter list and numerical results are given in the pape

Synergistic Knowledge

In formal epistemology, group knowledge is often modelled as the knowledge that the group would have, if the agents shared all their individual knowledge. However, this interpretation does not account for relations between agents. In this work, we propose the notion of synergistic knowledge which makes it possible to model those relationships

Step size adjustment and extrapolation for time-stepping schemes in non-smooth dynamics

International audienceIn this paper we use step size adjustment and extrapolation methods to improve Moreau's time-stepping scheme for the numerical integration of non-smooth mechanical systems, i.e. systems with impact and friction. The scheme yields a system of inclusions, which is transformed into a system of projective equations. These equations are solved iteratively. Switching points are time instants for which the structure of the mechanical system changes, for example, time instants for which a sticking friction element begins to slide. We show how switching points can be localized and how these points can be resolved by choosing a minimal step size. In order to improve the integration of non-smooth systems in the smooth parts, we show how the time-stepping method can be used as a base integration scheme for extrapolation methods, which allow for an increase in the integration order. Switching points are processed by a small time step, while time intervals during which the structure of the system does not change are computed with a larger step size and improved integration order. The overall algorithm, which consists of a time-stepping module, an extrapolation module and a step size adjustment module, is discussed in detail and some examples are given

Sclerosing Epithelioid Fibrosarcoma: Case Presentation and a Systematic Review

In sclerosing epithelioid fibrosarcoma (SEF), a rare variant of low-grade fibrosarcoma, treatment results and therapeutic options are poorly characterized. We systematically analyzed the data of all 89 patients (43 female, 46 male; mean age, 47years [range, 14-87years]) reported in the literature concerning clinical presentation, histopathology, differential diagnosis, treatment, survival rates, and prognosis, and we present an additional case. Information detailing treatment, disease control, and followup was available in 60 (67%), 75 (84%), and 68 patients (76%), respectively. Case history was variable with one-third of patients reporting a painful, enlarging mass. Ten patients (13%) presented with metastases, 23 (31%) had metastases develop after diagnosis, and 28 (37%) had local recurrence. Low cellularity, mild pleomorphy, and sclerotic hyaline matrix of SEF suggest a benign clinical behavior, and cell morphology allows for the wide differential diagnosis of benign, pseudosarcomatous, and malignant proliferations. In addition to surgery, 11 patients (15%) had chemotherapy, 22 (29%) had postoperative radiation therapy, and three (4%) had a combination of both. Twenty-three patients (34%) died from their disease after a mean of 46months, 24 (35%) were alive with disease, and 20 (31%) were alive without evidence of disease. Patients with SEF of the head and neck had the worst prognosis. Level of Evidence: Level III, prognostic study. See the Guidelines for Authors for a complete description of levels of evidenc

Illusion of control affects ERP amplitude reductions for auditory outcomes of self-generated actions.

AbstractThe reduction of neural responses to self‐generated stimuli compared to external stimuli is thought to result from the matching of motor‐based sensory predictions and sensory reafferences and to serve the identification of changes in the environment as caused by oneself. The amplitude of the auditory event‐related potential (ERP) component N1 seems to closely reflect this matching process, while the later positive component (P2/ P3a) has been associated with judgments of agency, which are also sensitive to contextual top‐down information. In this study, we examined the effect of perceived control over sound production on the processing of self‐generated and external stimuli, as reflected in these components. We used a new version of a classic two‐button choice task to induce different degrees of the illusion of control (IoC) and recorded ERPs for the processing of self‐generated and external sounds in a subsequent task. N1 amplitudes were reduced for self‐generated compared to external sounds, but not significantly affected by IoC. P2/3a amplitudes were affected by IoC: We found reduced P2/3a amplitudes after a high compared to a low IoC induction training, but only for self‐generated, not for external sounds. These findings suggest that prior contextual belief information induced by an IoC affects later processing as reflected in the P2/P3a, possibly for the formation of agency judgments, while early processing reflecting motor‐based predictions is not affected

L’impact des contraintes économiques sur les garant·e·s de l’aide sociale valaisanne

Les assistant·e·s sociales et sociaux sont au milieu des tensions entre les institutions qui les engagent, le cadre légal et les attentes des bénéficiaires de l’aide sociale. La question se pose si ces pressions sont réelles ou simplement un ressenti de la part des professionnel·le·s. Est-il possible qu’elles soient dues à un manque de capacité à s’adapter au contexte actuel ? En Valais, l’aide sociale est de plus en plus montrée du doigt, du fait de l’augmentation des coûts d’année en année. Ainsi le pouvoir législatif cherche des moyens d’endiguer ses dépenses, mais cela semble être au détriment des personnes concernées. Il s’agit de traiter les symptômes sans pour autant chercher la source de l’augmentation des personnes qui se retrouvent à l’aide sociale. D’une part, dans la presse écrite les termes : d’abus, de fraudes, d’octrois abusifs sont souvent associés à l’aide sociale. D’autre part, l’aide sociale est un enjeu économique, dont les dépenses poussent les politiciens à vouloir agir pour réduire les coûts. Ces deux facteurs noircissent l’image de l’aide sociale dont le but est d’aider les personnes dans le besoin et rendent d’autant plus complexe le travail des assistant·e·s sociales et sociaux, qui se voient ôter de plus en plus de moyens. La question se pose comment les professionnel·le·s de l’aide sociale peuvent allier les attentes de rentabilité avec l’encadrement social qui doit porter ses fruits

Lamellar body ultrastructure revisited: high-pressure freezing and cryo-electron microscopy of vitreous sections

Lamellar bodies are the storage sites for lung surfactant within type II alveolar epithelial cells. The structure-function models of lamellar bodies are based on microscopic analyses of chemically fixed tissue. Despite available alternative fixation methods that are less prone to artifacts, such as cryofixation by high-pressure freezing, the nature of the lung, being mostly air filled, makes it difficult to take advantage of these improved methods. In this paper, we propose a new approach and show for the first time the ultrastructure of intracellular lamellar bodies based on cryo-electron microscopy of vitreous sections in the range of nanometer resolution. Thus, unspoiled by chemical fixation, dehydration and contrasting agents, a close to native structure is revealed. Our approach uses perfluorocarbon to substitute the air in the alveoli. Lung tissue was subsequently high-pressure frozen, cryosectioned and observed in a cryo-electron microscope. The lamellar bodies clearly show a tight lamellar morphology. The periodicity of these lamellae was 7.3nm. Lamellar bifurcations were observed in our cryosections. The technical approach described in this paper allows the examination of the native cellular ultrastructure of the surfactant system under near in vivo conditions, and therefore opens up prospectives for scrutinizing various theories of lamellar body biogenesis, exocytosis and recyclin

Self-rule to multi-adapt: Generalized multi-source feature learning using unsupervised domain adaptation for colorectal cancer tissue detection.

Supervised learning is constrained by the availability of labeled data, which are especially expensive to acquire in the field of digital pathology. Making use of open-source data for pre-training or using domain adaptation can be a way to overcome this issue. However, pre-trained networks often fail to generalize to new test domains that are not distributed identically due to tissue stainings, types, and textures variations. Additionally, current domain adaptation methods mainly rely on fully-labeled source datasets. In this work, we propose Self-Rule to Multi-Adapt (SRMA), which takes advantage of self-supervised learning to perform domain adaptation, and removes the necessity of fully-labeled source datasets. SRMA can effectively transfer the discriminative knowledge obtained from a few labeled source domain's data to a new target domain without requiring additional tissue annotations. Our method harnesses both domains' structures by capturing visual similarity with intra-domain and cross-domain self-supervision. Moreover, we present a generalized formulation of our approach that allows the framework to learn from multiple source domains. We show that our proposed method outperforms baselines for domain adaptation of colorectal tissue type classification in single and multi-source settings, and further validate our approach on an in-house clinical cohort. The code and trained models are available open-source: https://github.com/christianabbet/SRA