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PubblicazioneFull-sky Models of Galactic Microwave Emission and Polarization at Sub-arcminute Scales for the Python Sky Model( 2025)Polarized foreground emission from the Galaxy is one of the biggest challenges facing current and upcoming cosmic microwave background (CMB) polarization experiments. We develop new models of polarized Galactic dust and synchrotron emission at CMB frequencies that draw on the latest observational constraints; that employ the “polarization fraction tensor” framework to couple intensity and polarization in a physically motivated way; and that allow for stochastic realizations of small-scale structure at subarcminute angular scales currently unconstrained by full-sky data. We implement these models into the publicly available Python Sky Model (PySM) software and additionally provide PySM interfaces to select models of dust and CO emission from the literature. We characterize the behavior of each model by quantitatively comparing it to observational constraints in both maps and power spectra, demonstrating an overall improvement over previous PySM models. Finally, we synthesize models of the various Galactic foreground components into a coherent suite of three plausible microwave skies that span a range of astrophysical complexity allowed by current data. Author contributions to this paper can be found at the end of this work.
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PubblicazionePIEZO2 channels: mediators of mechanotransduction and cell-cell communication as revealed by localized mechanical stimulation( 2025)Understanding the gating mechanism of the mechanosensitive ion channel PIEZO2 is crucial because of its involvement in key physiological and pathological processes. The use of a bead-functionalized cantilever by atomic force microscopy (AFM) provides a well-defined contact area, enabling accurate and reproducible force delivery to the cell surface. This approach enables the application of a spatiotemporally controlled mechanical stimulation to single PIEZO2-transfected HEK-293 cell at short (0.5s) and long (10s) stimulus duration, while monitoring the channel activity in single stimulated cell and neighboring cells by calcium signal. Two distinct dyes were used: Rhod-3AM restricted to the cytoplasm and Rhod-2AM permeable to whole cell including organelles. We observed that in a single cell, a 50nN local force elicited stronger responses with short stimuli, particularly with the organelle-permeable dye. Moreover, upon mechanical stimulation of a single PIEZO2-overexpressing cell, calcium transients were also detected in neighboring, non-stimulated cells, particularly with a dye permeable to organelles, thus suggesting a mechanosensitive intercellular communication pathway. These results confirmed that PIEZO2 channels are highly sensitive, efficiently respond to short-duration stimuli, and are involved in a mechanosensitive cell-cell communication.
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PubblicazioneGenerative Models for Parameter Space Reduction Applied to Reduced Order Modelling(Springer Science and Business Media Deutschland GmbH, 2026)Solving and optimising Partial Differential Equations (PDEs) in geometrically parameterised domains often requires iterative methods, leading to high computational and time complexities. One potential solution is to learn a direct mapping from the parameters to the PDE solution. Two prominent methods for this are Data-driven Non-Intrusive Reduced Order Models (DROMs) and Parametrised Physics Informed Neural Networks (PPINNs). However, their accuracy tends to degrade as the number of geometric parameters increases. To address this, we propose adopting Generative Models to create new geometries, effectively reducing the number of parameters, and improving the performance of DROMs and PPINNs. The first section briefly reviews the general theory of Generative Models and provides some examples, whereas the second focusses on their application to geometries with fixed or variable points, emphasising their integration with DROMs and PPINNs. DROMs trained on geometries generated by these models demonstrate enhanced accuracy due to reduced parameter dimensionality. For PPINNs, we introduce a methodology that leverages Generative Models to reduce the parameter dimensions and improve convergence. This approach is tested on a Poisson equation defined over deformed Stanford Bunny domains.
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PubblicazioneHow bad could it be? Modelling the 3D complexity of the polarised dust signal using moment expansion( 2024)The variation of the physical conditions across the three dimensions of our Galaxy is a major source of complexity for the modelling of the foreground signal facing the cosmic microwave background (CMB). In the present work, we demonstrate that the spin-moment expansion formalism provides a powerful framework to model and understand this complexity, and we put special focus on the effects that arise from variations of the physical conditions along each line of sight on the sky. We performed the first application of the moment expansion to reproduce a thermal dust model largely used by the CMB community, demonstrating its power as a minimal tool to compress, understand, and model the information contained within any foreground model. Furthermore, we used this framework to produce new models of thermal dust emission containing the maximal amount of complexity allowed by the current data while remaining compatible with the observed angular power spectra by the Planck mission. By assessing the impact of these models on the performance of component separation methodologies, we conclude that the additional complexity contained within the third dimension could represent a significant challenge for future CMB experiments and that different component separation approaches are sensitive to different properties of the moments.
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PubblicazioneA Variational Approach to the Stability in the Homogenization of Some Hamilton–Jacobi Equations( 2026)We investigate the stability with respect to homogenization of classes of integrals arising in the control-theoretic interpretation of some Hamilton--Jacobi equations. The prototypical case is the homogenization of energies with a Lagrangian consisting of the sum of a kinetic term and a highly oscillatory potential V = Vper + W, where Vper is periodic and W is a nonnegative perturbation thereof. We assume that W has zero average in tubular domains oriented along a dense set of directions. Stability then holds true; that is, the resulting homogenized functional is identical to that for W = 0. We consider various extensions of this case. As a consequence of our results, we obtain stability for the homogenization of some steady-state and time-dependent, first-order Hamilton--Jacobi equations with convex Hamiltonians and perturbed periodic potentials. Finally, we show with an example that, for negative W, stability may not hold. Our study revisits and, depending on the different assumptions, complements results obtained by P.-L. Lions, P. Souganidis, and their collaborators using PDE techniques.