Scientific Publications of the University of Toulouse II Le Mirail
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The independence of involuntary unemployment from nominal or real wages: a general equilibrium model
No full textInternational audienceKeynes’s ‘conjecture’ that there are general equilibria of involuntary unemployment that are resistant to falling wages has now been demonstrated, albeit at the cost of making relatively restrictive assumptions about how markets or anticipation functions operate. This article aims to show that a general equilibrium model can be constructed based on assumptions widely accepted by economists, such as rejecting the Keynesian ‘second classical postulate’ and differentiating between households of employees and shareholders. In this model, involuntary unemployment is independent of wages. In this model, unemployment is explained solely by the determinants of effective demand: households’ marginal propensities to consume, the incentive to invest, and the interest rate. This marginal modification of the general equilibrium model calls into question the first welfare theorem, specifically the Pareto optimality of general equilibrium
A Set of Robotic Inductive Tasks to Monitor Human Cognitive Effort
No full textInternational audienceMental state monitoring methods are particularly promising for Human-Robot Interaction (HRI). Indeed, evaluating users' mental states in real-time using portable acquisition devices would help to build a better model of the ongoing interaction. Yet, the study of human mental state requires standardized inductive tasks in order to produce a robust ground truth for baseline measurements. Hence cognitive effort is often induced using dual-task paradigms, where the robot has a limited impact in the inductive process and that do not allow to modulate human mental state through robot behavior. To address such an issue, this study proposes to validate three inductive tasks adapted from neuropsychology to HRI: the N-Back Task, the Sternberg Task, and the Cognitive Shifting Task. Each task was designed to induce cognitive effort through robot behavior only, avoiding the need for dual-task paradigms. The validation involved 24 participants per task, performing both the original version and the robot one with robot video clips. Expected outcomes included a decreased accuracy, as well as increased response times and subjective effort at higher difficulty levels. Results confirmed that the robotic tasks effectively induce cognitive effort, though they also introduce stronger cognitive demands than traditional letter-based tasks. The validated tasks provide novel robust tools for HRI research, with all resources and data openly accessible for community use, therefore paving the way for promoting reproducibility and replicability of HRI research
Un oeil numérique sur les cimes: Comment le non-invasifs redéfinit la carte archéologique en montagne
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Reclaiming Software Engineering as the Enabling Technology for the Digital Age
No full textInternational audienceSoftware engineering is the invisible infrastructure of the digital age. Every breakthrough in artificial intelligence, quantum computing, photonics, and cybersecurity relies on advances in software engineering, yet the field is too often treated as a supportive digital component rather than as a strategic, enabling discipline. In policy frameworks, including major European programmes, software appears primarily as a building block within other technologies, while the scientific discipline of software engineering remains largely absent. This position paper argues that the long-term sustainability, dependability, and sovereignty of digital technologies depend on investment in software engineering research. It is a call to reclaim the identity of software engineering
Modélisation en comportement et neurosciences : une introduction avec applications
No full textCe polycopié a été développé dans le cadre de l'enseignement de la modélisation des comportements collectifs à l'Université de Toulouse dans les Masters BEE (Biologie, écologie, évolution) et Neurosciences. Il vise le public de biologistes pour les familiariser avec les modèles types individu centré et type équations différentielles, ainsi de faire le lien entre ces deux types de modèle. L'annexe fait quelques rappels des outils mathématiques utilisés dans ce polycopié
From innovation to exnovation: insights from post-growth food enterprises in Australia
No full textInternational audienceThis study explores systemic barriers and enablers of post-growth food enterprises in Australia. We analyse three different case studies that offer alternative models of entrepreneurial approaches for achieving sustainability outcomes as a higher priority than economic growth. We identified three post-growth food enterprises that operate at different stages of the food supply chain. We found that these enterprises work towards various, interconnected, sustainability goals by embedding diverse principles into their organisational structure and operations. Their not-for-profit structure enables them to avoid trade-offs between financial extractivism and socio-ecological well-being goals. Additionally, we explored the systemic barriers faced by these enterprises, recognising that they are embedded in an economic system that favours and rewards the pursuit of economic growth. To navigate these barriers, the cases analysed adopted various innovative approaches, such as fostering alternative funding schemes, ways to acquire farmland and technology. While their bottom-up approaches are important, the inertia of dominant food systems impedes transitions to alternatives. We suggest that exnovation - the process of deliberately phasing out unsustainable practices - warrants more attention. For example, exnovating goals, policies, and performance metrics that prioritise economic growth at the expense of sustainability could play a crucial role in unlocking post-growth models. This study provides an orientation for further theoretical and empirical research about post-growth food systems transitions and stresses the value of engaging more with the wider political, economic, and legal foundations of transitions
A lateral porous silicon electrokinetic molecular valve
No full textInternational audienceIn this study, we introduce an Electrokinetic Molecular Valve (EMV) based on Lateral Porous Silicon (LPSi) membranes. The LPSi membranes are fabricated and monolithically integrated into silicon microfluidic chips , featuring an average pore size of 25 nm. Upon proper oxidation, LPSi membranes exhibit a relative perm-selectivity of 48% in physiological solution, comparable to that of Nafion. The LPSi chip is able to extract and concentrate 1.5 fmol of fluorescein from 180 nL into 1.3 nL within 10 minutes, and to achieve a concentration factor of more than 120 at voltages less than 4.2 V. A simplified numerical model is developed to describe the electrokinetic behavior of the EMV. The model exibites good qualitative agreement with experimental results. By varying parameters within this framework (the applied voltage, membrane charge density, background ion concentration, and membrane position), the preconcentration performance of the EMV can be reliably predicted. Distinct from conventional electrokinetic concentrators, the EMV architecture mandates that the entire fluid flow through the LPSi nanochannels. This configuration enables high ion selectivity and low voltage operation, while leveraging the Donnan exclusion effect for precise molecular control, concentration, and release. With continued advancements in electrical insulation and membrane charge density, the proposed EMV holds considerable promise for integration into portable µTAS and biosensors
TD-CD-MPPI: Temporal-Difference Constraint-Discounted Model Predictive Path Integral Control
No full textInternational audiencePath Integral methods have demonstrated remarkable capabilities for solving non-linear stochastic optimal control problems through sampling-based optimization. However, their computational complexity grows linearly with the prediction horizon, limiting long-term reasoning, while constraints are merely enforced through handcrafted penalties.In this work, we propose a unified and efficient framework for enabling long-horizon reasoning and constraint enforcement within Model Predictive Path Integral (MPPI) control. First, we introduce a practical method to incorporate a terminal value function, learned offline via temporal-difference learning, to approximate the long-term cost-to-go. This allows for significantly shorter roll-outs while enabling infinite-horizon reasoning, thereby improving computational efficiency and motion performance. Second, we propose a discount modulation strategy that adjusts the return of sampled trajectories based on constraint violations. This provides a more interpretable and effective mechanism for enforcing constraints compared to traditional cost shaping. Our formulation retains the flexibility and sampling efficiency of MPPI while supporting structured integration of long-term objectives and constraint handling. We validate our approach on both simulated and real-world robotic locomotion tasks, demonstrating improved performance, constraint-awareness, and generalization under reduced computational budgets