372 research outputs found
Le sérieux du rire : la comédie polémique et les convulsionnaires de Saint-Médard
Il peut paraĂźtre curieux que la querelle entourant l'Ă©pisode convulsionnaire du jansĂ©nisme des LumiĂšres se soit trouvĂ©e Ă s'exprimer en comĂ©dies, mais cela se comprend lorsque l'on examine l'itinĂ©raire gĂ©nĂ©ral du jansĂ©nisme, et le parcours particulier des comĂ©dies en tant que telles. Les deux comĂ©dies, une Ă©crite par un pĂšre jĂ©suite et l'autre par un jansĂ©niste inconnu, ouvrent une fenĂȘtre inusitĂ©e sur le phĂ©nomĂšne convulsionnaire, la rĂ©ception sociale qu'il connut et les malaises politico-religieux qu'il souleva. Les Ă©chos littĂ©raires de la querelle jansĂ©niste rĂ©vĂšlent un dĂ©placement de ses lieux et modalitĂ©s habituels d'affrontements. La querelle jansĂ©niste du XVIIIe siĂšcle laisse place Ă une polĂ©mique furieuse qui investit l'espace public. La discussion thĂ©ologique de la premiĂšre querelle reste prĂ©sente, mais elle sert davantage de paysage dans lequel se dessinent de nouveaux motifs de disputes tels que le rĂŽle des miracles, la paix de l'Ăglise et la question de l'autoritĂ©. La guerre entre jansĂ©nistes tourne autour de lieux communs et de caricatures qui couraient Ă l'Ă©poque. L'application comique Ă travers une intrigue exagĂ©rĂ©e et des personnages stĂ©rĂ©otypĂ©s sert davatage la polĂ©mique. Les comĂ©dies furent reçues comme de la littĂ©rature polĂ©mique autour d'un sujet d'actualitĂ©. Elles sont une tentative rĂ©ussie d'ouvrir la querelle prĂ©cise de Saint-MĂ©dard Ă un certain public. Plus encore, elles sont une rĂ©flexion sur la reconnaissance du public comme instance nouvelle d'autoritĂ© et sur les moyens lĂ©gitimes de lui parler
A cable-suspended intelligent crane assist device for the intuitive manipulation of large payloads
This paper presents a cable-suspended crane system to assist operators in moving and lifting large payloads. The main objective of this work is to develop a simple and reliable system to help operators in industry to be more productive while preventing injuries. The system is based on the development of a precise and reliable cable angle sensor and a complete dynamic model of the system. Adaptive horizontal and vertical controllers designed for direct physical human-robot interaction are then proposed. Different techniques are then proposed to estimate the payload acceleration in order to increase the controller performances. Finally, experiments performed on a full-scale industrial system are presented
Neural computations in prosopagnosia
We report an investigation of the neural processes involved in the processing of faces and objects of brain-lesioned patient PS, a well-documented case of pure acquired prosopagnosia. We gathered a substantial dataset of high-density electrophysiological recordings from both PS and neurotypicals. Using representational similarity analysis, we produced time-resolved brain representations in a format that facilitates direct comparisons across time points, different individuals, and computational models. To understand how the lesions in PSâs ventral stream affect the temporal evolution of her brain representations, we computed the temporal generalization of her brain representations. We uncovered that PSâs early brain representations exhibit an unusual similarity to later representations, implying an excessive generalization of early visual patterns. To reveal the underlying computational deficits, we correlated PSâ brain representations with those of deep neural networks (DNN). We found that the computations underlying PSâ brain activity bore a closer resemblance to early layers of a visual DNN than those of controls. However, the brain representations in neurotypicals became more akin to those of the later layers of the model compared to PS. We confirmed PSâs deficits in high-level brain representations by demonstrating that her brain representations exhibited less similarity with those of a DNN of semantics
Neural computations in prosopagnosia
We report an investigation of the neural processes involved in the processing of faces and objects of brain-lesioned patient PS, a well-documented case of pure acquired prosopagnosia. We gathered a substantial dataset of high-density electrophysiological recordings from both PS and neurotypicals. Using representational similarity analysis, we produced time-resolved brain representations in a format that facilitates direct comparisons across time points, different individuals, and computational models. To understand how the lesions in PSâs ventral stream affect the temporal evolution of her brain representations, we computed the temporal generalization of her brain representations. We uncovered that PSâs early brain representations exhibit an unusual similarity to later representations, implying an excessive generalization of early visual patterns. To reveal the underlying computational deficits, we correlated PSâ brain representations with those of deep neural networks (DNN). We found that the computations underlying PSâ brain activity bore a closer resemblance to early layers of a visual DNN than those of controls. However, the brain representations in neurotypicals became more akin to those of the later layers of the model compared to PS. We confirmed PSâs deficits in high-level brain representations by demonstrating that her brain representations exhibited less similarity with those of a DNN of semantics
An articulated assistive robot for intuitive hands-on-payload manipulation
This paper presents an intelligent assistive robot designed to help operators in lifting and moving large payloads through direct physical contact (hands-on-payload mode). The mechanical design of the robot is first presented. Although its kinematics are similar to that of a cable-suspended system, the proposed mechanism is based on articulated linkages, thereby allowing the payload to be offset from the rail support on which it is suspended. A dynamic model of the robot is then developed. It is shown that a simplified dynamic model can be obtained using geometric assumptions. Based on the simplified dynamic model, a controller is then presented that handles the physical human-robot interaction and that provides the operator with an intuitive direct control of the payload. Experimental validation on a full-scale prototype is presented in order to demonstrate the effectiveness of the proposed robot and controller
Decoding face recognition abilities in the human brain
Why are some individuals better at recognizing faces? Uncovering the neural mechanisms supporting face recognition ability has proven elusive. To tackle this challenge, we used a multimodal data-driven approach combining neuroimaging, computational modeling, and behavioral tests. We recorded the high-density electroencephalographic brain activity of individuals with extraordinary face recognition abilitiesâsuper-recognizersâand typical recognizers in response to diverse visual stimuli. Using multivariate pattern analyses, we decoded face recognition abilities from 1â
s of brain activity with up to 80% accuracy. To better understand the mechanisms subtending this decoding, we compared representations in the brains of our participants with those in artificial neural network models of vision and semantics, as well as with those involved in human judgments of shape and meaning similarity. Compared to typical recognizers, we found stronger associations between early brain representations of super-recognizers and midlevel representations of vision models as well as shape similarity judgments. Moreover, we found stronger associations between late brain representations of super-recognizers and representations of the artificial semantic model as well as meaning similarity judgments. Overall, these results indicate that important individual variations in brain processing, including neural computations extending beyond purely visual processes, support differences in face recognition abilities. They provide the first empirical evidence for an association between semantic computations and face recognition abilities. We believe that such multimodal data-driven approaches will likely play a critical role in further revealing the complex nature of idiosyncratic face recognition in the human brain
Decoding face recognition abilities in the human brain
Why are some individuals better at recognising faces? Uncovering the neural mechanisms supporting face recognition ability has proven elusive. To tackle this challenge, we used a multi-modal data-driven approach combining neuroimaging, computational modelling, and behavioural tests. We recorded the high-density electroencephalographic brain activity of individuals with extraordinary face recognition abilitiesâsuper-recognisersâand typical recognisers in response to diverse visual stimuli. Using multivariate pattern analyses, we decoded face recognition abilities from 1â
second of brain activity with up to 80% accuracy. To better understand the mechanisms subtending this decoding, we compared representations in the brains of our participants with those in artificial neural network models of vision and semantics, as well as with those involved in human judgments of shape and meaning similarity. Compared to typical recognisers, we found stronger associations between early brain representations of super-recognisers and mid-level representations of vision models as well as shape similarity judgments. Moreover, we found stronger associations between late brain representations of super-recognisers and representations of the artificial semantic model as well as meaning similarity judgments. Overall, these results indicate that important individual variations in brain processing, including neural computations extending beyond purely visual processes, support differences in face recognition abilities. They provide the first empirical evidence for an association between semantic computations and face recognition abilities. We believe that such multi-modal data-driven approaches will likely play a critical role in further revealing the complex nature of idiosyncratic face recognition in the human brain
Training physicians in behavioural change counseling: A systematic review
Background: Poor health behaviours (e.g., smoking, physical inactivity) represent major underlying causes of non-communicable chronic diseases (NCDs). Prescriptive behaviour change interventions employed by physicians show limited effectiveness. Physician training in evidence-based behaviour change counselling (BCC) may improve behavioural risk factor management, but the efficacy and feasibility of current programs remains unclear.
Objective: (1) To systematically review the efficacy of BCC training programs for physicians, and (2) to describe program content, dose and structure, informing better design and dissemination.
Methods: Using PRISMA guidelines, a database search up to January 2018, yielded 1889 unique articles, screened by 2 authors; 9 studies met inclusion criteria and were retained for analysis.
Results: 100% of studies reported significant improvements in BCC skills among physicians, most programs targeting provider-patient collaboration, supporting patient autonomy, and use of open questions to elicit âchange-talkâ. Limitation included: poor reporting quality, high program heterogeneity, small sample sizes, 78% of studies having no comparison group, and less than 30% of skills taught being formally assessed.
Conclusion: Training programs were efficacious, but methodological weaknesses limit the ability to determine content and delivery. Caution is necessary when interpreting the results
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