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Nonlinear dynamics in an environmental overlapping generations model with technology choice
No full textThis paper introduces an overlapping generations model to explore the interplay between economic growth, the environment, and endogenous technology adoption. Considering an economy with physical capital and publicly funded human capital, the analytical framework extends Prieur and Bréchet (2013, Macroeconomic Dynamics 17, 1135--1157) by incorporating the endogenous technology choice mechanism from Umezuki and Yokoo (2019, Journal of Economic Dynamics & Control 100, 164--175). The analysis focuses on how the choice of capital-intensive technologies impacts environmental dynamics. The model reveals complex equilibrium dynamics, driven by a core trade-off between individuals' resource allocation on consumption versus environmental protection and firms' technology decisions
Optimal solar system escape trajectories for gradient-index solar sails via saturation functions
No full textSolar System escape is a necessary step for interstellar missions and requires long-term, advanced spacecraft propulsion capabilities when the heliocentric trajectory does not include gravity assist maneuvers. In this context, solar sails are becoming an attractive option due to their increasing technological maturity, which enables their effective use in interplanetary missions. Among these propellantless propulsion systems, the gradient-index solar sail is a promising concept capable of providing a transverse component of the thrust vector even when the sail is in a (passively stable) Sun-facing attitude. The presence of this transverse thrust component enhances escape performance compared to a classical reflective solar sail with a fixed Sun-facing orientation or a piecewise-constant attitude profile. This paper investigates the capabilities of a Sun-facing gradient-index solar sail for escaping the Solar System. The problem is formulated within the framework of indirect optimal control to determine the time-optimal escape trajectory. Additionally, a path inequality constraint limiting the minimum solar distance is handled using a saturation function and incorporated into the mathematical model
Turning Stress Into Signal: Mechanochromic Materials in Commodity and Technologically Relevant Polymers
No full textThis review explores the development and application of mechanochromic materials on the basis of commodity and industrially relevant polymers. Mechanochromic polymers, which exhibit visible color changes under mechanical stress, offer promising avenues for creating smart, responsive materials with real-world utility. The review begins by detailing the fundamental mechanisms of mechanochromism, focusing on the role of mechanophores-molecular units that change their optical properties when subjected to force-and their interaction with polymer matrices. Two primary strategies are discussed: physical dispersion of chromogenic dyes and covalent incorporation of mechanophores, each offering distinct advantages in terms of sensitivity, reversibility, and scalability. Special attention is given to commodity plastics, which provide cost-effective platforms for mechanoresponsive technologies. The review also highlights the role of computational modeling in understanding mechanophore activation and guiding material design. Emerging applications in damage sensing, soft robotics, and flexible electronics are examined, demonstrating how mechanochromic systems can bridge scientific innovation and practical deployment. Future challenges and opportunities-such as enhancing sensitivity, improving durability, and integrating sustainable materials-are outlined to inform the next generation of smart mechanochromic devices
The quadruple helix and the role of HEIs as innovation brokers in disadvantaged areas
No full textThis conceptual paper explores the drivers and barriers of university–business collaboration in disadvantaged areas, emphasising its potential to foster inclusive local development. Starting from a review of the academic and policy literature, it proposes a framework that situates higher education institutions as innovation brokers, crucial actors in building trust, facilitating coordination and translating knowledge across quadruple helix stakeholders. The study underscores the need for place-based strategies and multi-stakeholder coalitions to address complex challenges and support co-creation in regional innovation ecosystems
Hyperspectral Image Synthesis Through Blind Unmixing Dictionary and Deep Diffusion Models
No full textThe capability to generate realistic hyperspectral (HS) imagery plays a prominent role in applications to sensor and mission development as well as in the training of machine learning models. Yet, it is a challenging task due to the high dimensionality and complex spectral–spatial structure of the data. This letter proposes a novel unsupervised deep learning framework for generating realistic HS imagery based on blind HS unmixing and denoising diffusion probabilistic models. First, the approach extracts both endmembers and abundance maps from HS data through a dictionary of HS unmixing algorithms. The extracted abundances are then used as inputs for a guided diffusion model (DM), which serves as the generative framework with the goal of producing realistic synthetic abundance maps. Finally, the generation of synthetic HS images is accomplished by integrating the generated abundance maps with the extracted endmember set and by suitably conditioning the probabilistic formulation of the guided DM as a function of the unmixing algorithms in the aforementioned dictionary. By combining a collection of blind linear unmixing techniques with the generative capabilities of DMs, the proposed methodology aims to address key challenges in simulating HS sensor outputs. The methodology was validated experimentally using real satellite HS imagery from the PRISMA mission of Italian Space Agency. The results confirm the effectiveness of the approach in generating realistic synthetic HS images associated with various land covers
Optimized sparse 2D antenna array design via beampattern matching
No full textEmerging millimeter-wave (mmWave) MIMO radars combine the benefits of large bandwidth available at mmWave frequencies with the spatial diversity provided by MIMO architectures, significantly enhancing radar capabilities for automotive, surveillance, and imaging applications. However, deploying large numbers of antennas and transceivers at these high frequencies substantially increases chip complexity and hardware costs. In this paper, we address the design of sparse two-dimensional (2D) antenna arrays that retain the desirable beampattern characteristics of fully populated arrays – namely, narrow mainlobes and low sidelobes – while significantly reducing the required number of antenna elements. We formulate the sparse array design problem as a beampattern matching optimization, which selects optimal subsets of transmit and receive antenna positions from an initial dense grid. To efficiently solve this challenging nonconvex optimization problem, we introduce an iterative algorithm combining Majorization–Minimization (MM) and Alternating Optimization (AO) techniques. We provide theoretical guarantees for convergence to at least a local optimum. Additionally, we propose a weighting vector optimization step to further enhance sidelobe suppression. Numerical simulations confirm that the proposed method maintains angular resolution and Sidelobe Levels (SLLs) comparable to those of full arrays, while substantially reducing hardware complexity and cost. Performance comparisons against existing methods demonstrate notable improvements in sidelobe suppression and computational efficiency without compromising processing gain
Feedback stabilization for entropy solutions of a 2 × 2 hyperbolic system of conservation laws at a junction
No full textWe consider the p-system in Eulerian coordinates on a star-shaped network. Under suitable transmission conditions at the junction and dissipative boundary conditions at the exterior vertices, we show that the entropy solutions of the system are exponentially stabilizable. Our proof extends the strategy by Coron et al. (2017) and is based on a front-tracking algorithm used to construct approximate piecewise constant solutions whose BV norms are controlled through a suitable exponentially-weighted Glimm-type Lyapunov functional.Nous considérons le p-système en coordonnées eulériennes sur un réseau en étoile. Sous des conditions de transmission appropriées au nœud et des conditions aux limites dissipatives aux sommets extérieurs, nous montrons que les solutions d'entropie du système sont exponentiellement stabilisables. Notre démonstration étend la stratégie de Coron et al. (2017) et repose sur un algorithme de suivi de fronts permettant de construire des solutions approximatives constantes par morceaux, dont les normes de variation bornée sont contrôlées à l'aide d'une fonctionnelle de Lyapunov de type Glimm, pondérée exponentiellement de manière appropriée
