Financial inclusion has expanded significantly across Africa through mobile money services delivered primarily via USSD technology. However, visually impaired individuals continue to face accessibility and security barriers when conducting financial transactions. Current USSD systems are not designed for non-visual interaction, forcing users to rely on third-party assistance even for PIN entry, thereby increasing fraud exposure and reducing transaction confidence. Although alternative assistive technologies such as screen readers exist, they are not compatible with USSD operations, often causing sessions to time out before the user can complete a transaction. This paper presents an Android-based intelligent middleware that automates USSD transactions, integrates biometric-secured PIN injection, and introduces a privacy-preserving screen-dimming mechanism: Blackout Mode. The system leverages Android Accessibility Services, hardware-backed Keystore security, and on-device natural language parsing to enable independent, secure voice-based mobile money access. We show that the proposed solution improves task success rates from 65-75% to more than 90% and reduces transaction completion time from 40-60 seconds to 12-15 seconds, while also improving perceived security.

We study the full-plane two-state fuzzy $4$-Potts model, obtained by assigning independent balanced $\{\pm1\}$ spins to the open clusters of a critical $q=4$ random-cluster configuration. This model corresponds exactly to the single-spin projection of the isotropic Ashkin-Teller model at its Potts point. We prove that, after proper normalization, all even multi-point spin correlation functions converge to explicit conformally covariant Coulomb-gas type neutral charge sums. As a consequence, we prove convergence in law of the rescaled magnetization field and identify the moments of the limiting field. The proof combines the Baxter-Kelland-Wu coupling, convergence of the six-vertex height function to the Gaussian free field, and a charge-completion mechanism: an enlarged discrete sum over charge assignments with total charge in $4\mathbb Z$ produces a combinatorial cancellation of connection patterns, while only the neutral charge sector survives in the scaling limit.

In the context of hyperbolic numbers we define the concept of negation of finite hyperbolicvalued probability distributions that is based on the partial order induced by the idempotent structure of hyperbolic numbers. Then, a hyperbolic majorization and general hyperbolic negators are introduced. For a broad class of generated negators, we prove that the original distribution majorizes its negation. This comparison yields that entropy increase for the strong hyperbolic Shannon entropy and the hyperbolic Gini-Simpson entropy, and it implies component-wise uniformization of the iterated negation. Finally, we analyze involutive property of hyperbolic negators and prove that are structurally distinct from the generated negators responsible for the entropy increase. These results show that hyperbolic probabilistic negation is not merely a component-wise copy of the real case, but a theory governed by the interaction between idempotent decomposition, partial order, and entropy measure.

We are interested in the generic simplicity of the spectrum of self-adjoint operators under bounded potential perturbations. More precisely, given a semibounded self-adjoint operator with compact resolvent and a suitable space of real-valued bounded perturbations, we study whether all eigenvalues of the perturbed operator are simple for a generic choice of the potential. In the first part of this paper we prove an abstract criterion which ensures that the set of perturbations giving only simple eigenvalues is residual. In the second part, we apply this criterion to several geometric and analytic settings, including sub-Laplacians and maximally hypoelliptic operators on compact manifolds, Laplacians on bounded domains with different boundary conditions, and Schrödinger-type operators on non-compact spaces.

This paper proposes an integrated sensing and communication (ISAC)-enabled grant-free uplink framework based on artificial-path delay modulation. A grant-free user equipment (g-UE) conveys uplink information by modulating the delay of a controllable artificial path derived from the scheduled downlink waveform. In contrast to conventional superposition-based schemes with successive interference cancellation, the proposed method enables uplink-downlink coexistence in the delay-sensing domain. By introducing a single weak artificial path confined within the cyclic prefix (CP), the g-UE allows the access point (AP) to decode uplink symbols from CSI perturbations while causing only limited degradation to the scheduled user equipment (s-UE) in the downlink. To support reliable finite-alphabet delay detection under unknown path gain and off-grid leakage, we develop a baseline delay calibration procedure and a normalized matched-filter detector. Results show that reflection power determines the reliability trade-off between the g-UE and the s-UE, whereas the delay step mainly controls the g-UE reliability-efficiency trade-off with little additional impact on the downlink s-UE. Even with an artificial path 15 dB weaker than the scheduled downlink signal, the g-UE achieves lower BER than the s-UE at an effective modulation order of 16-QAM. The proposed framework thus offers a low-complexity, SIC-free, and downlink-friendly solution for grant-free uplink in ISAC systems.

In this article, we study the existence and global regularity results for the fully nonlinear elliptic Grad--Mercier type equations with oblique boundary conditions in the context of weighted Orlicz spaces. Our approach employs an asymptotic analysis in which global regularity is transferred from a limit profile, namely, the recession operator associated with the governing operator, using topological and stability methods. In addition to the main regularity result, we derive global weighted Orlicz estimates for the Hessian and establish global Morrey-type estimates for the problem. This article extends the results established by Caffarelli--Tomasetti (Comm. Pure Appl. Math. 76 (3): 604--615, 2023), Zhang et al. (Nonlinearity 39 (2): 025011, 2026), and Bessa (J. Funct. Anal. 286 (4): 110295, 2024).

The knee feature in the cosmic-ray energy spectrum around 4 PeV is widely believed to have a Galactic origin, but the acceleration mechanism and identification of PeVatrons remain key open questions in high-energy astrophysics. Recent precise measurements by LHAASO reveal that the proton and helium spectra exhibit a common rigidity-dependent spectral break at ~ 3.5 PV, imposing a stringent constraint on source models. In this work, we construct, for the first time, a time-dependent cosmic-ray injection model that incorporates the full evolution of massive stars together with the dynamical development of wind termination shocks. We find that stellar winds of individual massive stars cannot explain the common spectral break observed by LHAASO, as they yield distinct rigidity cutoffs for protons and helium. By contrast, collective winds of massive star clusters naturally reconcile this discrepancy through the mixing effect of stars at different evolutionary stages. We propose a stellar-dominated model in which supernova remnants dominate the GeV-TeV range, individual stellar winds dominate the TeV range, and collective cluster winds dominate the PeV knee region. This model successfully reproduces the rigidity-dependent spectral features of various species near 100 GV and 0.1 PV. It further makes two testable predictions for future observations. Around 0.5 PV, the energy spectra of carbon and oxygen are expected to exhibit hardening similar to that of helium, which can be verified by LHAASO observations. In the multi-TV range, the energy spectrum of magnesium is not expected to show hardening similar to that observed for helium, carbon, and oxygen, which can be tested by DAMPE observations.

We provide a complementary result to the quasi-invariance of Gaussian measures supported on Sobolev spaces with high regularity under the dynamics of the three-dimensional periodic defocusing nonlinear wave equation from Gunaratnam-Oh-Tzvetkov-Weber (2022). Namely, given $p$ and $σ$ large enough, we prove the existence of dense sets of Sobolev spaces $W^{σ,p}(\mathbb{T}^3)$ which do not preserve the regularity $σ$ throughout the aforementioned dynamics. This is in sharp contrast with the propagation under the flow of almost sure properties.

Periodic Ge modulations within strained Si quantum wells in SiGe heterostructures offer a route to deterministically enhance conduction-band valley splitting in Si, a key requirement for scalable spin-qubit quantum computing. Efficient enhancement requires modulations in the order of the Si valley wavevector $k_0$ (9.7 nm$^{-1}$), corresponding to a period of 0.64 nm and near-monolayer growth control. Using nuclear-spin-free molecular beam epitaxy with $^{28}$Si and $^{72}$Ge, we demonstrate Ge-modulated Si quantum wells with periods from 2.00 to 0.49 nm, including modulations at $k_0$ and $2k_0/3$. Synchrotron X-ray techniques and scanning transmission electron microscopy reveal laterally homogeneous Ge modulations over micrometer scales, with amplitudes up to 10 at-% and gradients reaching 20 at-%/nm. Two-bands $\mathbf{k}\cdot\mathbf{p}$ simulations suggest deterministic enhancement of valley splittings in steep trapezoidal $2k_0/3$ heterostructures, while the effect in $k_0$-type quantum wells is much weaker.

Universality classes of new physics models featuring narrow boson resonances produced through strongly interacting initial states in proton-proton collisions and with enhanced decays to di-tau final states are classified. Spin-zero scalar or pseudoscalar bosons with chirality-violating fermion couplings can induce potentially significant di-lepton non-universality in the bottomonium mass region, with up to many hundreds of nanobarns of direct production total cross section in proton-proton collisions at the Large Hadron Collider. Conversely, mass suppressed chirality-violating couplings of spin-zero bosons to di-electrons maintain di-lepton universality to a high degree in the same mass region at electron-positron colliders. Simultaneous measurement and comparison of integrated resonant prompt di-electron, di-muon, and di-tau mass spectra at the Large Hadron Collider in the bottomonium mass region could be sensitive to the existence of new boson resonances with enhanced di-tau decays, or likewise bottomonium states with non-Standard Model enhanced di-tau decay modes.

In this work, we build a bridge between the Pólya--Schur program and Voiculescu's free probability theory. A cornerstone of the former is the Pólya--Benz Theorem, classifying a central family of real-root preserving operators on the space of polynomials, as those given by $f(\partial_z)$ for a Laguerre--Pólya function $f$ and the derivative operator $\partial_{z}$. We prove that any free (additive) infinitely divisible distribution can be attained as the weak limit of root distributions of Appell polynomials $f_n(\partial_z)z^n$ as $n\to\infty$, for a suitably chosen sequence $f_n$ of Laguerre--Pólya functions. Such questions on the (global) limiting distributions of real rooted polynomials belong to the active research area of finite free probability. In contrast to its standard tools, our approach allows for non-compactly supported limiting distributions, (barely) complex rooted polynomials and even provides the full microscopic description of the roots. Moreover, we extend our results to differential operators generating free multiplicative infinitely divisible distributions, to the rectangular free convolution, and to $f_n(\partial_z)p_n$ for real rooted polynomials $p_n$, implying a generalization of the recent connections between the heat flow and free Brownian motion to any free Lévy process. As corollaries, we identify free stable distributions by choosing $f_n$ to be a fixed rescaled Laguerre--Pólya function, and we prove various convergence results on the zero distributions of Jensen polynomials, e.g. the limiting root distribution of Jensen polynomial of the Riemann $Ξ$-function is given by the Cauchy distribution.

In monostatic, decision-aided, or known-waveform integrated sensing and communications (ISAC) formulations, the sensing receiver is often modeled as knowing the transmitted waveform. This assumption is not suitable for passive, bistatic, or distributed settings where the sensing receiver knows the signaling rule but not the transmitted symbols. We study such a symbol-unaware ISAC model, where sensing is measured by the unconditioned mutual information $I(S;V)$ rather than the symbol-aware quantity $I(S;V|X)$. For discrete-input memoryless channels, we characterize the capacity-sensing region through an auxiliary time-sharing variable, showing that the optimal upper boundary is the upper concave envelope of the single-mode frontier. Thus, explicit time sharing is unnecessary when the single-mode frontier is already concave, but strictly beneficial when its upper concave envelope strictly dominates the frontier. For Rayleigh-fading BPSK, we further show that the curvature of the single-mode boundary is determined by the stochastic ordering of the communication- and sensing-side effective SNR distributions. Communication-side dominance yields a concave single-mode frontier and no time-sharing gain, sensing-side dominance yields a convex single-mode frontier and a strict time-sharing gain, and equality yields a linear boundary. The result extends to SIMO-BPSK through the ordering of post-combining SNR distributions. These findings explain when symbol-unaware ISAC optimally moves from data-symbol transmission to pilot-like sensing modes.

Metal film on nanosphere (MFON) plasmonic systems have emerged as nanostructures with useful properties for molecular detection. This work presents the optimisation and discussion of the characterisation results of Au-film on nanosphere (AuFON) systems. Through experiments and numerical simulations, the resonance energies of localised surface plasmon modes and the spatial distribution of light on the nanostructured surface were identified. The results highlight the dependence of these modes on changes in nanostructure dimensions and the optical conditions of the incident radiation, thereby optimising the amplification of optical signals for applications in molecular detection.

We show that the cohomology of the finite element Stokes complex consisting of piecewise polynomials spaces on an Alfeld split mesh from Fu, Guzmán, & Neilan (2020, Math. Comp., 89, 1059--1091) is isomorphic to the cohomologies of the continuous Stokes and de Rham complexes. We also construct novel "minimal" conforming finite element complexes where the $H^1$-conforming space is the lowest-order space from Guzmán & Neilan (2018, SIAM J. Numer. Anal., 56, 2826--2844) and the $L^2$-conforming space is piecewise constants. These minimal complexes also have cohomologies isomorphic to the continuous Stokes and de Rham complexes. We further construct local, bounded, cochain projections for the minimal complexes. All the results hold for strongly Lipschitz domains with nontrivial topologies and in the presence of mixed boundary conditions.

The rapid development of quantum computers and sensors urges for the development of a quantum Internet capable of transmitting quantum bits over long distances. Photons used for quantum data transfer are fragile over time and sensitive to their environment, so that they cannot be directly used over long distances. To remedy this problem, long distance paths are segmented into shorter links and entangled pairs of photons are distributed over these links and swapped to create end-to-end entangled pairs over long distances, eventually used for teleportation. In this paper, we develop an existing protocol taking account of fidelity and imperfect memories. We shorten the execution time and thus increase its link success probability creating the so-called Locally Heralded Distribution (LHD). It turns out that the proposed protocol outperforms some previous protocols. We benchmark through simulation the performances of protocols considered in this paper by using a blind entanglement protocol as a baseline.

In this paper, we consider a large family of real-valued spin models on general transitive graphs. We show that, in the subcritical regime $β<β_c$, the correlations of the model decay exponentially fast. To prove this result, we consider the random cluster (a.k.a. FK percolation) representation of the model and obtain an inequality that generalises the OSSS inequality to monotonic measures with random connection probabilities, thus extending the inequality of Duminil-Copin, Raoufi, and Tassion. Our results apply in particular to the Blume--Capel model and general $P(φ)$ models, going beyond the cases of the Ising and $φ^4$ models treated by Aizenman, Barsky, and Fernández.

Single electron spins can be used to encode and process information in semiconductor quantum devices. Progress has been hindered by materials challenges, such as the small energy splitting between low-lying valley states and hyperfine coupling to nuclear spins. Here we use density functional theory to optimize the valley splitting and spin dephasing time in realistic Si/SiGe heterostructures. Reductions in the Si quantum well width generally increase the valley splitting. However, in narrow quantum wells, a larger fraction of the electronic wavefunction resides in the SiGe buffer layers, which increases the hyperfine coupling with spinful $^{73}$Ge. Our work shows that Si/SiGe heterostructures with 3~--~4~nm wide quantum wells and $^{73}$Ge and $^{29}$Si concentrations of 50 ppm should support average valley splittings $E_{v}$~$>$~500~$μ$eV and spin dephasing times $T_2^*$ exceeding 15~$μ$s assuming an effective quantum dot area of 700 nm$^2$. In addition, sharper Si/SiGe interfaces in general result in larger valley splittings and longer spin dephasing times.

Longitudinal data are useful for capturing and analyzing patterns of change over time. Often, these patterns follow a nonlinear form. One useful and commonly applied nonlinear function is the piecewise function, which assumes growth occurs in distinct phases, each with its own functional form. Past literature has established that Bayesian inference is preferred over likelihood-based methods for estimating piecewise models. To address this, we developed the R package BEND - Bayesian Estimation of Nonlinear Data (available on CRAN). The purpose of BEND is to provide a user friendly software for estimating nonlinear longitudinal models using a Bayesian inference approach. Given the flexibility and practicality of the piecewise models, BEND includes several extensions of it to accommodate various types of complex longitudinal datasets and applications. Bayes_PREM() can empirically identify the number and location of random changepoints in a piecewise random effects model. This function can also model multiple latent classes with different longitudinal growth patterns and incorporate covariates to predict the outcome and latent class membership. Bayes_BPREM() can jointly model the longitudinal piecewise trajectories of two interrelated outcomes. Lastly, Bayes_CREM() can estimate the impact of group membership on longitudinal growth. This paper provides an overview of the functions included in BEND and empirical examples of how to apply these models in practice.

Periodic network-wide dissemination of node location data is crucial for shared situational awareness and collaborative mapping in mobile ad hoc and mesh networks for public safety, disaster relief, and military. A key challenge is to provide maximally accurate location information with minimal energy expenditure on part of the nodes. We present SQEEZ: a mechanism for reducing the Position Location Information (PLI) load that combines two orthogonal techniques: (1) adaptive suppression of location updates; and (2) temporal and inline compression of update packets. We describe the SQEEZ suppression and compression algorithms, analyze the tradeoff between location error and energy consumption, and introduce a new metric called \textit{Error-Penalized-Energy (EPE)} that normalizes the energy metric using the error incurred. Our simulation results show that, in the range of parameters studied, SQEEZ improves the EPE-efficiency and scalability in a 30-node random waypoint scenario by up to 4.4x and 2.3x respectively; and increases the EPE-efficiency by 7.5x in a 9-node real-world network trace. Compression provides larger improvements than suppression at high mobilities and vice-versa at low mobilities.

Reliable identification of encrypted data fragments is essential in cybersecurity, with applications to ransomware detection, digital forensics, and large-scale data analysis. Distinguishing encrypted from compressed fragments is particularly challenging, as short fragments lack structural data and exhibit low statistical redundancy. Traditional statistical methods based on byte-level distributions show limited effectiveness on this task. Recent machine learning approaches improve performance by learning subtle patterns from raw bytes, but predominantly rely on single-modal representations, implicitly assuming that a single view of the data is sufficient for accurate classification. This paper shows that this assumption becomes a fundamental limitation in low-information settings, when only small fragments of data are available (512--2048 Bytes). We propose Triumvir, a multi-modal, uncertainty-aware ensemble architecture that integrates statistical, sequential, and spatial representations of raw byte fragments. Extensive experimental analysis demonstrates that Triumvir consistently outperforms state-of-the-art methods with gains of up to +4.5pp in binary and +6.4pp in multiclass classification. Ablation studies confirm that combining modalities is critical, yielding improvements of up to +5pp over partial configurations.

We perform a stress test of gravothermal collapse in self-interacting dark matter (SIDM) halos under baryonic feedback using a semi-analytical oscillating-potential model in controlled N-body simulations. For high-concentration halos, where the SIDM thermalization timescale is short, gravothermal collapse is only mildly delayed and never stalled, even under extremely strong feedback. In contrast, the collapse of a median-concentration halo can be significantly delayed, but it resumes once feedback ceases. The final density profile of such halos depends sensitively on the episodic feedback history, producing a broad diversity in central densities. These results strengthen the interpretation of dense compact perturbers identified in recent strong-lensing observations as core-collapsed SIDM halos.

This paper establishes foundational analytic and geometric results for a broad class of reasonable flows of Spin($7$)-structures. We first prove Shi-type derivative estimates, showing that a uniform bound on the quantity \[ Λ(x,t)=\left(|\mathrm{Riem}(x,t)|_{g(t)}^2+|T(x,t)|_{g(t)}^4+|\nabla T(x,t)|_{g(t)}^2\right)^{1/2} \] implies bounds on all covariant derivatives of the Riemann curvature tensor $\mathrm{Riem}$ and the torsion tensor $T$. We show further that $Λ(x,t)$ must blow up at any finite-time singularity, and we establish a lower bound on the blow-up rate. We also prove a compactness theorem for solutions of such flows and apply these results to the analysis of finite-time singularities. These results provide a general analytic framework for studying flows of Spin($7$)-structures; once a proposed flow is shown to satisfy the reasonable condition, our estimates, compactness theorems, and singularity analysis apply.

Morier-Genoud and Ovsienko introduced q-deformations of continued fractions, Farey labelings, and Conway--Coxeter friezes, and established relationships among them in restricted settings associated with triangulations having exactly two exterior cells. In this paper, we extend these correspondences to arbitrary subsequences of quiddities arising from general triangulations. We show that the numerator and denominator polynomials of q-deformed continued fractions coincide with entries of q-deformed Conway--Coxeter friezes, while the corresponding polynomials in q-Farey labelings agree with them up to explicit powers of q. These powers are described combinatorially in terms of the number of diagonals in the triangulation, or equivalently, the number of entries equal to 1 in the associated frieze. Furthermore, we determine the minimum and maximum degrees of these polynomials in terms of the same combinatorial data.

Advances in myoelectric prosthetic technology have substantially increased the functional potential of modern devices. Accordingly, heightened control demands have led to the acknowledgement of pre-prosthetic training as a key stage in the acquisition of myoelectric skills. Existing training paradigms largely emphasize internal muscle activation while external, goal-directed outcomes required for effective real-world use are often neglected. We address this gap by introducing a virtual pre-prosthetic training platform that integrates EMG-driven cursor with animated hand gestures, enabling the delivery of both muscle-level and functional-level feedback. In this proof-of-concept study, participants were assigned to one of two focus of attention (FoA) protocols, each incorporating both feedback types but differing in whether internal or external FoA was emphasised. Participants successfully acquired and retained myoelectric skill across both protocols, but distinct performance characteristics and learning strategies emerged, indicating that both FoAs contribute meaningfully to learning and that their timing may play an important role. External FoA was positively associated with retention, suggesting that it may strengthen the link between training and skill acquisition. Together, the results demonstrate the feasibility of an FoA-based virtual training platform for pre-prosthetic applications and indicate that it can provide a foundation for designing training protocols that better prepare users for prosthetic use.

In this paper we derived the corrections to the Reissner-Nordström black hole when higher-derivative $RF^2$ terms (contractions of the Riemann tensor with the Maxwell field strength squared) are added to the Einstein-Maxwell action. Such terms arise naturally in the context of effective field theories. We used wordline QFT methods to obtain the leading order post-Minkowskian corrections. We verified these results by solving the modified Einstein-Maxwell field equations in closed form, to all orders in Newton's constant $G$. We discussed the first law and computed the entropy of the perturbed black holes. The extremal black hole temperature is non-negative precisely when the weak gravity conjecture is satisfied. This condition on the extremal black hole temperature rules out Drummond-Hathrell theory.

Detecting unauthorized UAV flights is critical for surveillance, security, and airspace management. Acoustic drone detection, which relies on the distinctive propeller and motor sounds of UAVs, provides a low-cost, passive solution that requires no line of sight. A central challenge is generalization: reliably distinguishing drone signatures from ambient noise across unseen recording setups, environments, and UAV types (out-of-domain). Inspired by advances in large-scale audio pretraining, we develop a compact DNN-based detector and improve its generalization by (1) pretraining the model for broad sound-event classification before fine-tuning on diverse in-house and public drone recordings, and (2) applying on-the-fly augmentations (pitch shifting, noise mixing, microphone transfer function simulation, spectrogram augmentation) to expose the model to varied acoustic conditions. An ablation study quantifies the impact of each augmentation. For evaluation, we set target false-positive rates (FPR) aligned with real-world surveillance needs and report true-positive rates (TPR) on both in-domain data (public IDMT Berne 2022) and out-of-domain data (public AuDroK). Our results show that pretraining is the dominant factor for robust detection, yielding substantial TPR improvements over training from scratch on all benchmarks. The full augmentation chain provides additional gains on acoustically mismatched out-of-domain data, achieving the best mean TPR on the AuDroK subsets and the largest improvements on the most challenging scenarios. We further validate real-world applicability by measuring false positives on public non-drone corpora (IDMT-TRAFFIC and ESC-50), demonstrating equally low FPR on unfamiliar backgrounds. A distance-dependent analysis on IDMT Berne 2022 shows effective detection at distances up to 150 m.

The ICARUS detector, a key component of the Short Baseline Neutrino (SBN) Program at Fermi National Acelerator Laboratory (FNAL), is a 600-ton Liquid Argon Time Projection Chamber (LArTPC) equipped with a Light Detection System (LDS) that uses 360 Hamamatsu R5912-MOD 8-inch photomultiplier tubes (PMTs), specifically designed to operate under cryogenic conditions ($\sim 87 \ K$). These PMTs feed the trigger signal to the readout, improve the spatial and timing resolution of the events, and contribute to cosmic rays mitigation. During operation at FNAL, a progressive degradation in the PMT gain was observed. We developed an experimental setup to investigate the temperature dependence of PMT performance. Gain measurements were carried out from room temperature to $-70 ^\circ C$ using an environmental chamber. The results show that, while the PMTs exhibit stable performance at room temperature, a significant and irreversible reduction in gain emerges at lower temperatures. Al though $-70 ^\circ C$ remains above the liquid argon temperatures, the trend clearly reveals a gain-sensitive degradation mechanism. A simplified physical model was developed to reproduce and interpret the observed behavior. Based on these findings, a series of mitigation strategies were implemented in the ICARUS detector to preserve PMT performance and ensure reliable operation under cryogenic conditions.

The IETF standard Manufacturer Usage Description (MUD) enables manufacturers to equip IoT devices with certified URLs that provide traffic profiles for those devices, helping administrators enforce network access control. However, MUD assumes devices operate on full IP stacks and therefore does not account for constrained IoT devices running Thread--the dominant low-power mesh networking standard--which lacks complete TCP/IP functionality. While prior work proposes extensions to support MUD in Thread environments, these approaches are limited to simple topologies with a single border router and do not scale to realistic deployments with multiple, heterogeneous border routers. We introduce MeshGuard, a framework enabling MUD-based access control in complex Thread networks, with any number of border routers. MeshGuard extends the Mesh Link Establishment (MLE) protocol to deliver MUD information from constrained devices to border routers regardless of network topology. Moreover, MeshGuard leverages Software-Defined Networking (SDN) to synchronize access control lists across all routers. Experiments on our proof-of-concept with real devices (nRF5340, nRF52833, Raspberry-Pi 3) demonstrate enhanced security, minimal overhead, and linear scalability compared to state-of-the-art approaches.

We present \texttt{HAPS-hFF1.0}, a new global QCD analysis of unidentified charged-hadron fragmentation functions (FFs) using single-inclusive electron-positron annihilation (SIA) data together with the modern COMPASS semi-inclusive deep-inelastic scattering (SIDIS) multiplicities. The COMPASS input consists of the 2025 proton-target measurement and the revised isoscalar-target multiplicities provided in the COMPASS addendum 2026. The extraction is performed at both next-to-leading order (NLO) and next-to-next-to-leading order (NNLO), allowing us to study the perturbative stability of the QCD fit and the impact of the updated SIDIS information on the flavor structure of the FFs. We find that the modern COMPASS multiplicities can be consistently described together with the SIA data and provide important charge-separated constraints on the light-quark and antiquark FFs. The comparison between the NLO and NNLO extractions indicates a stable quark-sector determination, while the gluon FF remains less directly constrained in the present SIA+SIDIS analysis. Our results highlight the importance of the modern COMPASS SIDIS multiplicities for precision studies of unidentified charged-hadron fragmentation and for future global FF determinations. The resulting \texttt{HAPS-hFF1.0} replicas are publicly available in standard LHAPDF format.

Time-reversed stochastic inflation solves the stochastic evolution of the inflationary universe backward in time, by counting the number of e-folds from the end of quantum diffusion towards some initial state. The point of view of observers attached to the end-of-inflation hypersurface is thus enforced. In this work, we exactly solve time-reversed stochastic inflation in a flat and bounded potential, the so-called quantum well. At given lifetime, the field behaviour is found to be either indistinguishable from the one obtained in a semi-infinite flat potential, or, subject to enhanced stochasticity where any memory of the initial state is erased. The derived distribution of curvature perturbations reduces to the semi-infinite result for small fluctuations while it develops exponential tails for the large ones. Such tails arise for both positive and negative values, and decay twice as fast as the one obtained in the standard forward stochastic inflation. These differences may have important consequences for tail-sensitive phenomena, such as primordial black hole formation.