In this paper, we investigate the stationary profiles of a convection-diffusion model for unidirectional pedestrian flows in domains with a single entrance and exit. The inflow and outflow conditions at both the entrance and exit as well as the shape of the domain have a strong influence on the structure of stationary profiles, in particular on the formation of boundary layers. We are able to relate the location and shape of these layers to the inflow and outflow conditions as well as the shape of the domain using geometric singular perturbation theory. Furthermore, we confirm and exemplify our analytical results by means of computational experiments.

Plant-soil feedback is recognized as a causal mechanism for the emergence of vegetation patterns of the same species especially when water is not a limiting resource (e.g. humid environments). Nevertheless, in the field, plants rarely grow in monoculture but compete with other plant species. In these cases, plant-soil feedback was shown to play a key role in plant-species coexistence. Using a mathematical model consisting of four PDEs, we investigate mechanisms of inter- and intra-specific plant-soil feedback on the coexistence of two competing plant species. In particular, the model takes into account both negative and positive feedback influencing the growth of the same and the other plant species. Both the coexistence of the plant species and the dominance of a particular plant species is examined with respect to all model parameters together with the emergence of spatial vegetation patterns.

The study of the internal structure of hadronic jets has become in recent years a very active area of research in particle physics. Jet substructure techniques are increasingly used in experimental analyses by the LHC collaborations, both in the context of searching for new physics and for Standard Model measurements. On the theory side, the quest for a deeper understanding of jet substructure algorithms has contributed to a renewed interest in all-order calculations in QCD. This has resulted in new ideas about how to design better observables and how to provide a solid theoretical description for them. In the last years, jet substructure has seen its scope extended, for example, with an increasing impact in the study of heavy-ion collisions, or with the exploration of deep-learning techniques. Furthermore, jet physics is an area in which experimental and theoretical approaches meet together, where cross-pollination and collaboration between the two communities often bear the fruits of innovative techniques. Despite the wealth of literature on this topic, we feel that a comprehensive and, at the same time, pedagogical introduction to jet substructure is still missing. This makes the endeavour of approaching the field particularly hard, as newcomers have to digest an increasing number of substructure algorithms and techniques, too often characterised by opaque terminology and jargon. Furthermore, while first-principle calculations in QCD have successfully been applied in order to understand and characterise the substructure of jets, they often make use of calculational techniques, such as resummation, which are not the usual textbook material. Thus, the idea of combining our experience in different aspects of jet substructure phenomenology to put together this set of lecture notes, which we hope could help and guide someone who moves their first steps in the physics of jet substructure.

Micro-Electro Mechanical Systems (MEMS) are defined as very small structures that combine electrical and mechanical components on a common substrate. Here, the electrostatic-elastic case is considered, where an elastic membrane is allowed to deflect above a ground plate under the action of an electric potential, whose strength is proportional to a parameter $λ$. Such devices are commonly described by a parabolic partial differential equation that contains a singular nonlinear source term. The singularity in that term corresponds to the so-called "touchdown" phenomenon, where the membrane establishes contact with the ground plate. Touchdown is known to imply the non-existence of steady state solutions and blow-up of solutions in finite time. We study a recently proposed extension of that canonical model, where such singularities are avoided due to the introduction of a regularizing term involving a small "regularization" parameter $\varepsilon$. Methods from dynamical systems and geometric singular perturbation theory, in particular the desingularization technique known as "blow-up", allow for a precise description of steady-state solutions of the regularized model, as well as for a detailed resolution of the resulting bifurcation diagram. The interplay between the two main model parameters $\varepsilon$ and $λ$ is emphasized; in particular, the focus is on the singular limit as both parameters tend to zero.

In this paper we study the long-time behavior of a nonlocal Cahn-Hilliard system with singular potential, degenerate mobility, and a reaction term. In particular, we prove the existence of a global attractor with finite fractal dimension, the existence of an exponential attractor, and convergence to equilibria for two physically relevant classes of reaction terms.

In this paper we introduce the responsive graphical user interface (ReGUI) approach to creating applications, and demonstrate how this approach can be implemented in MATLAB. The same general technique can be used in other programming languages.

We investigate a singularly perturbed, non-convex variational problem arising in materials science with a combination of geometrical and numerical methods. Our starting point is a work by Stefan Müller, where it is proven that the solutions of the variational problem are periodic and exhibit a complicated multi-scale structure. In order to get more insight into the rich solution structure, we transform the corresponding Euler-Lagrange equation into a Hamiltonian system of first order ODEs and then use geometric singular perturbation theory to study its periodic solutions. Based on the geometric analysis we construct an initial periodic orbit to start numerical continuation of periodic orbits with respect to the key parameters. This allows us to observe the influence of the parameters on the behavior of the orbits and to study their interplay in the minimization process. Our results confirm previous analytical results such as the asymptotics of the period of minimizers predicted by Müller. Furthermore, we find several new structures in the entire space of admissible periodic orbits.

Mobile traffic prediction is a fundamental yet challenging problem for wireless network planning and optimization. Existing models focus on learning static long-term temporal patterns in mobile traffic series, which limits their ability to capture the dynamics between mobile traffic and network parameter adjustments. In this paper, we propose MobiWM, a world model for mobile networks. Taking mobile traffic as the system state, MobiWM models the dynamics between the states and network parameter actions, including power, azimuth, mechanical tilt, and electrical tilt through a predictive backbone. It fuses multimodal environmental contexts, comprising both image and sequential data, with encoded actions, leveraging shared spatial semantics to enhance spatial understanding. Leveraging the capacity of world models to capture real-world operational dynamics, MobiWM supports unlimited-horizon rollout over continuous network-adjustment action trajectories, providing operators with an explorable counterfactual simulation environment for network planning and optimization. Extensive experiments on variable-parameter mobile traffic data covering 31,900 cells across 9 districts demonstrate that MobiWM achieves the best distributional fidelity across all evaluation scenarios, significantly outperforming existing traffic prediction baselines and representative world models. A downstream RL-based case study further validates MobiWM as a simulation environment for network optimization, establishing a new paradigm for digital twin-driven wireless network management.

In this paper, we study the dynamics of a finite number of spherical bubbles in a compressible fluid within a bounded open domain of R 3 . The fluid-bubble interaction is described by a system of nonlinear partial differential equations (PDEs) and ordinary differential equations (ODEs) coupling the fluid's density, velocity and pressure to the bubble's translational, rotational and radial velocities. We prove the existence of weak solutions for this model until the collision or collapse of the bubbles. The formulation of the fluid-bubble system, along with the techniques used for the existence proof, is inspired by penalization methods developed for fluid-solid interaction. The main contribution of this work is the addition of a radial expansion-contraction mode in the bubble motion, which introduces new nonlinear terms in the momentum equations that need to be treated carefully in the compactness arguments.

Millimeter-wave (mmWave) communication enables high data rates through large bandwidths and highly directional beamforming, but its sensitivity to blockage and mobility makes reliable beam alignment a central challenge. Limited-probing beam management is a fundamental problem in codebook-based mmWave systems, where only a small subset of beams can be evaluated simultaneously, and the serving decision is restricted to the probed set. Under mobility and noisy feedback, this leads to a sequential and partially observable decision problem in which performance depends critically on the quality of the proposed beam candidates. In this paper, we consider limited-probing beam management and develop a history-conditioned discrete denoising diffusion probabilistic model for beam candidate generation. The proposed method learns from logged probing histories a conditional distribution over promising beam indices, which is then used to construct probing candidates online. Numerical analysis shows that the proposed approach consistently achieves better signal-to-noise ratio, beam-miss probability, and conditional probe regret under tight probing budgets compared with strong learning-based and discriminative baselines. The gains are especially pronounced in low-probing regimes, where accurate candidate generation is most critical.

The design of contact interfaces that meet quantitatively a specified friction law (friction force vs normal force) is challenging due to the multi-scale and multi-physics nature of contact interactions. Recently, a concept was proposed to address this question in the case of dry elastic microarchitected contact interfaces, so-called metainterfaces. These take their macroscopic friction properties from an array of discrete asperities whose geometrical descriptors are optimized through an inverse design phase. Such design is based on the experimentally-observed proportionality between friction force and real contact area under pure compression, reducing the friction problem to a simpler contact mechanics problem of designing the contact area. In this context, the design strategy assumes that asperities are placed on a linear elastic half-space and behave independently from each other. Both assumptions are likely to fail in experimental realizations of metainterfaces, potentially inducing discrepancies between the actual and target behaviours. Here, we use full 3D finite element modelling to critically assess the validity of those two assumptions in existing experimental metainterfaces, and their potential impact on the design quality. The results first confirm the validity of the strategy, in the conditions in which it was used in the literature. Then, by systematically varying the spatial arrangement of asperities, their interdistance and the size of their elastic base, we identify conditions under which the literature assumptions fail. Our findings provide critical insights into the robustness and practical limitations of the metainterface design strategy and guidelines for its future improvements.

The Majoron is a hypothetical (pseudo) Nambu-Goldstone boson arising from the spontaneous breaking of a global lepton number symmetry, and is known as a candidate for dark matter in our Universe. In this paper, we investigate the possibility of probing the Majoron dark matter with a linear optical cavity used in the interferometric gravitational wave detectors. We consider a scenario in which the Majoron dark matter couples to photons through a QED anomaly, leading to an oscillatory photon birefringence induced by the coherent dark matter background. The anomaly coefficient is fixed by requiring the model to simultaneously reproduce the electroweak Higgs scale and a typical right-handed Majorana neutrino mass scale, and the resulting dark matter-photon coupling naturally falls within the sensitivity range of optical interferometers. By incorporating additional optics to extract the birefringence signal, we find that ground-based laser interferometers such as Advanced LIGO, KAGRA, as well as future detectors, can probe a region of the parameter space of Majoron dark matter.

We have developed a vacuum-ultraviolet spectropolarimeter to measure the linear polarization of spectral lines around the Lyman-$α$ wavelength. The main components for polarimetry are a rotatable MgF$_2$ waveplate and a SiO$_2$/MgF$_2$ multilayer-coated fused silica plate that functions as a reflective polarizer. A grazing-incidence grating is mounted between them to provide wavelength dispersion. The polarization is determined from the intensity modulation of the spectral line as the waveplate is rotated. The performance of the spectropolarimeter was demonstrated by measuring the polarization of the $2s$--$2p_{3/2}$ transition in Li-like N$^{4+}$ (124~nm) excited by a 1000~eV electron beam in an electron beam ion trap. Clear modulation of the line intensity was observed as a function of the waveplate rotation angle. From the measured modulation amplitude, the degree of linear polarization was determined to be $P=-(0.178^{+0.012}_{-0.005})$, with the negative sign indicating that the emission is polarized predominantly perpendicular to the electron beam. This result demonstrates the capability of the present spectropolarimeter to determine polarizations with an absolute uncertainty $ΔP$ on the order of $0.01$. This instrument provides a useful tool for polarization diagnostics of vacuum-ultraviolet emission lines from laboratory plasmas.

We review the current state of knowledge of the long-term evolution of the small bodies that give rise to comets and exocomets, as well as their reservoirs. The active cometary phase is only transitory, and bodies that become comets pass from a source population, such as the Kuiper Belt, Oort Cloud or their extra-solar analogues, through the active cometary phase, to eventual dormancy or destruction. We discuss dynamical delivery channels that can move comets from their source reservoirs to orbits with small periapsides, and the depletion of these reservoirs by dynamical and collisional means. We also discuss the physical evolution of cometary nuclei, especially in light of recent advances from missions to Solar System comets such as Rosetta's visit to 67P. We then describe our current knowledge of interstellar objects, which can originate from the same source regions as exocomets but be amenable to detailed study when they enter the Solar System. We include a summary of stellar winds emanating from different types of stars, which become increasingly strong once stars leave the Main Sequence. This is followed by a description of how small bodies are affected by stellar evolution, and the range of comet-like phenomena observed towards white dwarf stars. Overall, while we have an increasingly good picture of the physical and dynamical evolution of Solar System comets, a number of large gaps remain in our knowledge of the physics of exocomets, related to our inability to directly probe these bodies and many of the planets that might be affecting their orbits.

This work explores the potential of integrating an Intelligent Transmissive Surface (ITS) into an antenna array to improve beamforming performance. We show that integrating a moderate number of passive refractive elements into a small antenna array can significantly improve the Weighted Sum Rate (WSR). We investigate the optimization of the WSR under two distinct operational constraints: a Radiated Power (RP) constraint and a Transmitted Power (TP) constraint. Our analysis reveals that the choice between these constraints significantly impacts the design parameters of the ITS-aided array. By contrasting these approaches, we explore critical design and material parameters, including the array geometry, surface loss, and illumination strategies.

Gas hydrates are of great relevance to both the oil industry and the environment. Understanding how these solid structures nucleate from aqueous solutions is essential to controlling their formation. Experimental studies have often suggested that hydrate nucleation originates at the interface between the aqueous phase and the guest-molecule reservoir. To assess this hypothesis, we perform molecular dynamics simulations of CO$_2$ hydrate nucleation. First, we place hydrate seeds at different positions relative to the interface and monitor their evolution, finding that seeds embedded in the bulk are more likely to grow than those located near or at the interface. Second, we analyse spontaneous nucleation simulations with and without an interface. Our previous work showed that nucleation rates are indistinguishable in both systems, strongly indicating that the interface does not play a role. Here, trajectory analysis reveals that hydrates nucleate in regions of locally high CO$_2$ concentration, which arise spontaneously in the bulk and are not associated with the interface. Our results indicate that hydrate nucleation does not preferentially occur at the interface, at least at the at deep supercooling conditions explored in this work. Further work at higher temperatures, and considering alternative nucleation locations, is needed to reconcile experiments and simulations, and thereby reach a deep understanding of the mechanism of hydrate formation.

The escalating computational demands and energy footprint of GPU-accelerated computing systems complicate informed design and operational decisions. We present the first release of Wattlytics (https://wattlytics.netlify.app), an interactive, browser-based decision-support system. Unlike existing procurement-oriented calculators, Wattlytics uniquely integrates benchmark-driven GPU performance scaling, dynamic voltage and frequency scaling (DVFS)-aware piecewise power modeling, and multi-year total cost of ownership (TCO) analysis within a single interactive environment. Users can configure heterogeneous systems across contemporary GPU architectures (GH200, H100, L40S, L40, A40, A100, and L4), select representative scientific workloads (e.g., GROMACS, AMBER), and explore deployment scenarios under constraints such as energy prices, system lifetime, and frequency scaling. Wattlytics computes multidimensional decision metrics (TCO breakdown, work-per-TCO, power-per-TCO, and work-per-watt-per-TCO) and supports design-space exploration, what-if scenarios, sensitivity metrics (elasticity, Sobol indices, Monte Carlo) and collaborative features to guide realistic cluster design and procurement under uncertainty. We demonstrate selected scenarios comparing deployment strategies under different operational modes: ixed budget, fixed GPU count, fixed performance, and fixed power. Our case studies show that, under budget or energy constraints, optimally deployed energy-efficient GPUs can outperform higher-performance alternatives in overall cost-effectiveness. Wattlytics helps users explore the design parameter space and distinguish between cost- and risk-driving factors, turning HPC design into a well-informed and explainable decision-making process.

Quantum computing is becoming strategically relevant to finance because several core financial bottlenecks are already defined by combinatorial search, expectation estimation, rare-event analysis, representation learning, and long-horizon cryptographic resilience. This review examines that landscape across five connected domains: constrained portfolio optimisation, derivative pricing, tail-risk and scenario estimation, quantum machine learning, and post-quantum security. Rather than treating these topics as isolated demonstrations, the article studies them as linked layers of a financial-computation stack. Across all five domains, the review applies a common evaluative logic: identify the financial bottleneck, specify the relevant quantum primitive, compare it with an explicit classical benchmark, and assess the result under realistic implementation and governance constraints. The main conclusion is measured but consequential. The strongest near-term case for quantum finance lies in carefully designed hybrid workflows rather than blanket claims of universal advantage. Quantum optimisation is most credible when constrained search dominates; amplitude-estimation methods matter most when repeated expectation evaluation is the binding cost; quantum machine learning remains task dependent; and post-quantum cryptography is already strategically necessary because financial infrastructures must migrate before fault-tolerant attacks arrive. By combining system-level synthesis with locally reproducible small-scale case studies on simulated qubit registers, the article is intended both as a review of the field and as a handbook-style entry point for future work.

GW231123 is the strongest current candidate for a lensed gravitational wave event and a unique case for testing how point-mass lensing affects propagation-based tests of gravity. In the real GW231123 data, an unlensed IMRPhenomXPHM analysis yields an apparent nonzero graviton mass posterior. We show that this anomaly is naturally explained by unmodeled point-mass lensing: once lensing is included, the apparent graviton mass signal disappears. In GW231123-like injection-recovery tests, a lensed NRSur7dq4 signal with zero graviton mass, recovered with the same unlensed IMRPhenomXPHM template, produces a similarly pronounced spurious graviton mass posterior, whereas lensing-included analyses with IMRPhenomXPHM, IMRPhenomXO4a, and NRSur7dq4 remain mutually consistent with no evidence for nonzero graviton mass. The similarity between the injected and real data posteriors shows that unmodeled point-mass lensing can mimic modified gravitational wave propagation. These results identify a concrete failure mode in tests of gravity and strengthen the interpretation of GW231123 as a lensed candidate.

In current MIMO mobile communication systems, phase noise can significantly impair performance. To allow for compensation of these impairments, accurate phase noise modeling is necessary. Numerical modeling of the phase noise process at a phase-locked loop (PLL) output is established in the literature and commonly represented by an Ornstein-Uhlenbeck (OU) process. The corresponding spectrum can be represented by a multi-pole/zero model. This work presents a least squares (LS) method for estimating the PLL parameters such as oscillator constants or PLL bandwidth from a measured phase noise spectrum. The method is applied on the MAX2870 and MAX2871 PLL chips and parameter estimates such as oscillator constants and PLL bandwidths are provided. The resulting parameter set enables both time- and frequency-domain numerical simulations.

Ordinary differential equations (ODE's) are a cornerstone of systems and control theory. Accordingly, they are standard material in undergraduate programs in engineering and there is abundant didactic literature about this topic. Yet, the solution methods and formulas prescribed in this didactic literature are unclear about the assumptions behind their derivation and thus about the limits of their applicability. Specifically, smoothness of the input is rarely discussed, even though it is a critical property to define the character of the solutions and the validity of the methods and formulas prescribed. On the other hand, the relationships with the state space representation (SSR) of linear systems is absent from this same literature and only marginally discussed in more advanced texts. In this paper we detail these gaps left behind in the didactic literature, then we provide a formal delimitation of the boundaries of the standard solutions and methods for linear ODE's. Our analysis relies on some key properties of state space representations, so we establish the formal connections between ODEs and SSR's, defining an equivalence between the two that is absent in the literature and is of conceptual interest by itself.

A population of Galactic gamma-ray binaries is currently emerging due to ever increasing sensitivity of gamma-ray observatories. The detection of very high energy (VHE) photons with energies well above 10 TeV from a dozen of sources and the estimated power of those sources make them potentially interesting cosmic ray accelerators. Multi-wavelength observations of gamma-ray binaries revealed that most of them include a young massive star in pair with a relativistic companion, either a black hole or energetic pulsar. Fast stellar winds interacting with powerful relativistic outflows from pulsars or the black hole jets in microquasars are favorable sites for VHE particle acceleration. To estimate the expected number of gamma-ray binaries, we present results of population synthesis calculations of Galactic binaries in which a young massive OB- or Be-star is accompanied by a pulsar capable of producing a powerful relativistic outflow. The distributions over the binary eccentricities, orbital periods, Be-disk inclinations, and the pulsar braking energy losses are taken into account. Conditions for a binary to accelerate VHE particles, radiate and absorb the non-thermal photons that may reach the observer are discussed. We model the anisotropic structure of the zone of interaction of the relativistic pulsar wind with the strongly magnetized massive star's wind. The stellar winds with strong ($\sim$ Gauss) magnetic fields at $\sim$ AU distances colliding with powerful pulsar outflows are capable of accelerating particles up to PeV energies at some orbital configurations and phases. The strong magnetic field in the interaction region produces a highly anisotropic structure of the particle accelerator and emitter in the pulsar outflow. The anisotropic radiation pattern may affect the gamma-ray photon absorption and the number of the observed gamma-ray loud systems.

We construct a consistent anti-de Sitter completion of the static and spherically symmetric black-hole solution sourced by the Palatini-inspired nonlinear electrodynamics \(Y^n\) model. Starting from the Einstein--Hilbert action with a negative cosmological constant and the first-order PINLED sector, we derive the full set of field equations and show that the nonlinear electromagnetic solution preserves its original parametric structure, while the lapse function acquires the standard AdS contribution. We then analyze the horizon structure, Hawking temperature, extended phase-space thermodynamics, and the associated equation of state. In addition, we investigate null and timelike geodesics, with emphasis on the effective potentials, photon sphere, shadow radius for a static observer at finite distance, and innermost stable circular orbit. The resulting framework furnishes the exact AdS extension of the asymptotically flat PINLED black hole and provides a coherent basis for numerical and phenomenological studies of its thermodynamic, optical, and orbital properties.

Simplicial homology is a classical tool that assigns a sequence of modules to a simplicial complex, providing invariants for the study of its topological properties. In this article, we introduce the notion of L-fuzzy simplicial homology, a generalization of simplicial homology for L-fuzzy subcomplexes, in which each simplex is assigned a value from a completely distributive lattice L. We present its definition and main properties and describe methods to compute its structure. In addition, we interpret filtrations over a poset and chromatic datasets in this setting, opening a door to further applications in topological data analysis.

We develop a nonlinear evolution framework for nonlinear parabolic equations with unbounded drift terms formulated in Lorentz spaces. The main contribution lies in the construction of uniformly m-accretive operators based on Lorentz-Sobolev embeddings, which allows us to apply the Crandall-Liggett generation theorem for nonlinear evolution equations. Within this framework, we establish existence, uniqueness, and stability of mild solutions. We further show that these mild solutions coincide with weak solutions, ensuring consistency with the variational formulation. Finally, we investigate the long-time asymptotic behavior of solutions.

We derive asymptotic models for the ultimate regimes in horizontal convection (HC) and pure internally heated convection (IHC), in analogy with our recent (2024) extension of the ultimate-regime model for Rayleigh-Benard convection (RBC). To derive the corresponding models for HC and IHC, we combine turbulent boundary-layer relations with the exact dissipation balances for these two systems. For HC, the resulting scaling relations are consistent with the rigorous transport bound of Siggers et al. (2004). For pure IHC, they are consistent with the exact HC-IHC balance analogy of Wang et al. (2021) and with the rigorous bounds on the convective-flux asymmetry in the equal-temperature-plates configuration (Arslan et al 2021). The main difference between RBC and HC/IHC is that, in the latter two cases, the global kinetic-energy balance does not contain the additional response factor (dimensionless convective heat flux in HC or inverse bulk temperature in IHC), whereas it does in RBC. As a consequence, for fixed Pr, the ultimate-regime scaling exponent is 1/3 for both HC and IHC, rather than 1/2 as in RBC.

High-entropy perovskites (HEPs) offer a unique platform for exploring magnetic phenomena arising from extreme B-site chemical disorder. In Sm(M7)O$_3$, where there are 7 cations in equal amounts at the B-site; M = Ti, Cr, Mn, Fe, Co, Ni, Cu), we observe long-range antiferromagnetic ordering near 105 K accompanied by a small but robust excess magnetic moment intrinsic to the chemically disordered lattice. This uncompensated moment is evident from ZFC-FC irreversibility, shifts in the isothermal M(H) loops, and discrete remanent states identified through direct-current-demagnetization measurements. Remarkably, cooling fields as small as $\pm$ 20 Oe are sufficient to select the direction of the excess moment, and the chosen magnetic state remains stable against applied fields up to 50 kOe. A low-temperature anomaly in the remanent magnetization further reveals a secondary contribution from the Sm$^{3+}$ sublattice, although the primary origin of the excess moment resides in the B-site AFM sublattice.

This study develops a Bayesian, uncertainty-aware framework for tendon breakage localization in pre-stressed concrete members using high-resolution data from distributed fiber-optic sensors (DFOS). DFOS enable full-field monitoring of strain changes on the surface of pre-stressed concrete members due to such failure. A finite element model (FEM) of an experimental tendon-breakage test is constructed, and model parameters are calibrated probabilistically against DFOS measurements. To capture model-form uncertainty (MFU), stochastic perturbations are embedded directly into material parameters, enabling the joint inference of physical properties and MFU within a unified probabilistic framework. Gaussian Process surrogates are employed to efficiently emulate the nonlinear FEM response, supporting computationally tractable Bayesian inference. A $ϕ$-divergence-based influence analysis identifies the DFOS measurements that most strongly shape the posterior distributions, providing interpretable diagnostics of sensor informativeness and model adequacy. The calibrated parameters and embedded uncertainties are then transferred to a FEM of a full-scale structural configuration, enabling prediction of tendon breakage localization under realistic conditions. A separability analysis of the predictive strain distributions quantifies the identifiability of tendon breakage at varying depths, assessing the confidence with which different damage scenarios can be distinguished given the propagated uncertainties. Results demonstrate that the framework achieves robust parameter calibration, interpretable diagnostics, and uncertainty-informed damage detection, integrating experimental data, embedded MFU, and probabilistic modeling. By systematically propagating both experimental and model uncertainties, the approach supports reliable tendon breakage localization and optimal DFOS placement.

This paper studies joint range-angle estimation and communication in the NF ISAC systems, where the BS serves a single UE whose position is simultaneously estimated via monostatic sensing. Unlike the ULA, the UCA provides an angle-invariant NF region due to its rotational symmetry. To capture the full wideband NF propagation environment, we develop a continuous-time channel model incorporating per-element delay, Doppler shifts, and spherical wavefront geometry under OFDM signaling. Building on this model, we derive the closed-form CRLB for joint range-angle estimation of the UE position, design an optimal transmit beamformer via Riemannian gradient descent, and formulate a joint range-angle ML estimator. Monte Carlo simulations confirm a fundamental aperture-versus-SNR trade-off in NF-ISAC: while a larger UCA radius tightens the CRLB, it simultaneously reduces the received SNR at any given distance, pushing the maximum likelihood estimator below its convergence threshold and degrading practical performance. Among the evaluated configurations, R = 0.5 m achieves the best joint estimation and communication performance at the BS} by sustaining the highest received SNR throughout the evaluated range.

DustPedia and LVL are two samples representative of the local galaxy population, including in total 1011 unique objects of all morphological types, with a wide range of stellar masses ($M_*$) and star-formation activity, and a spectral coverage from the FUV to the FIR. The purpose of this work is to show that these samples cover two complementary ranges in $M_*$ and morphology, making them an ideal set for constraining the dominant processes in the evolution of the galactic dust content. Using the multiwavelength data provided by the two surveys, we fitted the galaxies' spectral energy distribution and estimated their physical properties, in particular the $M_*$, $sM_\mathrm{dust}=M_\mathrm{dust}/M_*$, and sSFR = SFR$/M_*$. By combining DustPedia and LVL, we highlight that the $\log_{10}(sM_{\rm dust})$-$\log_{10}(M_*)$ trend is not monotonic. Thanks to a large number of objects across a wide range of $M_*$, we have been able to fit two smoothly-joined linear correlations: a positive for $\log_{10}(M_{*}/$M$_\odot)\lesssim9.5$ (mainly LVL late spirals and irregulars), and a negative one for larger-mass, mainly DustPedia spirals (early types are distinct and more dispersed in the same mass regime). For $\log_{10}(M_{*}/$M$_\odot)>9.5$, we confirm a strong sM_{\rm dust}-sSFR correlation; dwarf galaxies, instead, lie below this trend, with a large scatter of $sM_{\rm dust}$, for -10.5<$\log_{10}$(sSFR/yr$^{-1}$)<-9.0. By using chemical evolution models we find that the observed $\log_{10}(sM_{\rm dust})$-$\log_{10}(M_{*})$ and $\log_{10}(sM_{\rm dust})$-$\log_{10}$(sSFR) trends can be interpreted mainly by variations in the initial gas mass budget and the galaxy ages, respectively. Low-mass Sm-Irr galaxies with low $sM_{\rm dust}$ and high sSFR can only be reproduced by the models by assuming high photofragmentation rate of large grains, and/or low grain-growth in clouds.