The centre comonad model provided the first concrete cohesive linear $\infty$-topos, settling an open problem of Schreiber. However, the model is degenerate: the quantum modality annihilates all non-commutative algebras, and the associated linear logic collapses to classical cartesian logic. In this paper we give a complete mathematical diagnosis of this degeneracy. We prove that the centre comonad sends the representable sheaf of a simple non-commutative algebra to the empty presheaf, and that the state space of any such algebra is empty. We then prove that the Day convolution on the classical core is cartesian, forcing the Seely isomorphism to hold trivially and collapsing the linear logic. We isolate the structural reason behind this collapse: whenever the opposite of the classical core is monoidally equivalent to a cartesian monoidal category, any coreflective precomposition comonad will exhibit the same degeneracy. We conclude that a non-degenerate quantum modality must be constructed without precomposition, and we briefly discuss possible directions.

Riemannian optimization provides a powerful framework for constrained optimization by incorporating problem-specific structure directly into the geometry of the search space. In many applications, however, the explicit evaluation or application of the Riemannian metric can be computationally expensive or numerically unstable, limiting the practical efficiency of otherwise well-founded algorithms. Motivated by such settings, this work investigates to what extent classical Riemannian optimization algorithms can be reformulated without explicitly applying the metric. We show that many first-order components of Riemannian optimization only rely on the differential of the objective function and access to the Riemannian gradient, but not on explicit metric application. Based on this observation, we develop metric-free formulations and generalize optimization approaches to Finsler and Banach manifolds. Numerical experiments demonstrate that the proposed metric-free strategies retain the effectiveness of their metric-dependent counterparts while significantly reducing computational overhead. These results highlight that a substantial portion of Riemannian optimization can be carried out independently of explicit metric application, broadening its applicability to problems with expensive or implicitly defined metrics.

Observations of wide post-interaction binaries show an unexpected feature; orbital eccentricity, which is not understood theoretically. A promising resolution to this long-standing puzzle is eccentric mass transfer (MT). Here the first complete framework for MT in orbits with arbitrary eccentricity, the general mass-transfer (GeMT) model, is confronted with the latest observations of hot subdwarfs of spectral type B (sdB) with main-sequence (MS) companions in wide orbits. SdBs are excellent benchmarks for binary evolution models, since their progenitors provide unique constraints on their formation histories. We show that the GeMT model naturally reproduces all orbital parameters of wide sdB+MS binaries without fine-tuning and that nonzero eccentricity is a natural outcome of MT. We further demonstrate that post-MT eccentricities depend directly on key MT parameters, including transferred mass, accretion efficiency, and angular momentum loss. Given the multitude of eccentric post-MT binaries with components ranging from low- to high-mass stars to compact objects, we propose that post-MT eccentricities offer a new window onto binary evolution, presenting a powerful tool to constrain highly uncertain binary-evolution parameters and mass-transfer formation histories across diverse populations. Post-MT eccentricity should therefore be embraced as a key observable, rather than treated as a problem to be corrected.

With the rise of new industries, often new jobs emerge. Evolutionary Economic Geography and in particular Industry Life Cycle perspectives predict that these activities first emerge in a limited number of cities to then diffuse to other locations as job descriptions become more standardized. Here, we focus on a particularly important new industry: software development, an activity that is economically important, quickly changing, and has a pronounced spatial concentration in a small number of global IT hubs. We use an online database of over 60 million questions and answers about problems in software development that yields a longitudinal dataset of 237 software skills. By geo-locating 3 million posting users at regular intervals, we link these skills to cities worldwide. We find that, in spite of its digital nature, the software industry exhibits similar spatial regularities as previously observed in more traditional sectors. First, cities diversify into skills that are related to their existing ones. Second, new skills first emerge in cities with large and diversified software sectors, and later diffuse -- mostly unhindered by geographical distance -- to smaller cities specialized in closely related skills. We find suggestive but limited support for a windows of locational opportunity account: although even brand-new skills still emerge first in cities with strong prior specialization in related skills, concentrations of related activities impact less the emergence of new skills than the diffusion of existing ones.

Recently, a number of spin chain models have been discovered that are solvable via hidden free-fermionic structures, going beyond the Jordan-Wigner paradigm. However, all examples in the literature displayed degeneracies that grow exponentially with the volume and that are homogeneous in the spectrum (identical degeneracies for all energy levels). In this note we present a model that can be solved by ``free fermions in disguise'' (FFD), such that the spectrum is free from exponential degeneracies for generic coupling constants. The model can be seen as a particular perturbation of two Ising chains. Alternatively, it can be realized as an interpolation between a standard Jordan-Wigner solvable chain and the original FFD model of Fendley. We used ChatGPT Pro 5.4 and 5.5 as a research assistant; in the Supplemental Material we provide details about the collaboration between the AI and the human author.

We investigate a novel class of boosted-object signatures at the LHC, where a high-$p_{\text{T}}$ fat-jet contains an identifiable hadron or quarkonium state originating from rare or semi-exclusive decays. Unlike conventional boosted jet studies, which focus on multi-prong partonic substructure, our approach probes hybrid configurations such as $W^{\pm}\toπ^{\pm}γ$, where a localized hadronic or quarkonium signal is embedded within a collimated jet. By fine-tuning the signature-oriented, pre-trained Sophon AI model optimized for large-radius jets, and combining it with an event-level BDT and a soft-drop-mass shape fit, we obtain an expected 95\% CL upper limit of ${\cal B}(W^{\pm}\toπ^{\pm}γ)<2.78\times10^{-5}$ for $450\,\mathrm{fb}^{-1}$ in our nominal setup. This study serves as a first proof-of-principle demonstration of the ``hadron-in-fat-jet'' paradigm; substantial gains in sensitivity are expected from improved trigger strategies, additional production channels, and dedicated taggers, while the methodology itself is broadly applicable to a wide range of rare Standard Model processes and searches for light or exotic resonances at present and future collider experiments.

Many parcel networks dispatch vehicles on \emph{fixed routes} using a simple load-accumulation rule: a truck leaves the depot for a fixed route as soon as the volume (or item count) waiting for that route crosses a threshold. The threshold is usually parameterised as an affine function of route length, $τ_r=β+γ\,d_r$, and the pair $(β,γ)$ is chosen once and frozen into production. This paper studies how good that frozen choice actually is, treating the question as a data-intensive, data-driven decision-making problem over a full month of real operational flow. Using a discrete-event simulator that replays the recorded arrival stream and reconstructs every trip, we sweep the $(β,γ)$ design space, evaluate the two competing objectives -- company operating cost and average parcel lead time -- and recover the Pareto frontier of efficient policies for two deployed variants (volume-triggered and item-count-triggered). The two policies turn out to be in strikingly different states of tune. The volume-threshold configuration lies on its own Pareto frontier: the simulator finds no $(β,γ)$ pair that strictly dominates it, so the deployed policy is \emph{already Pareto-efficient} -- an unusual positive audit result. The item-count configuration is the opposite: it is dominated by a concrete simulated configuration that is both faster and cheaper, and the available cost saving at equal lead time is about \num{5.0}\,\pct{}. We trace the item-count policy's inefficiency to a base that is too large and a length coefficient that is too small for the deployed truck capacity, and show that a \emph{steeper} threshold -- lower base, higher slope -- is preferable. Because the remedy is a two-scalar reconfiguration, the analysis converts directly into an actionable, zero-capital recurring saving.

This paper axiomatizes the bid-ask market maker's quoting rule. A quoting rule maps the maker's state, namely inventory, belief, variance, trade intensity, and informed-trader fraction, to a bid-ask pair. Eight natural axioms, together with six environmental assumptions on the maker's inventory cost, force a unique three-parameter family: the mid-quote is linear in inventory, and the spread decomposes additively into inventory and adverse-selection components. Each of the three parameters is identified from a distinct moment of the observable quoting rule, with the three identifications mutually decoupled. The eight axioms partition into a four-axiom indispensable core, one structural choice, and three modularity extensions. Two structural corollaries follow: the latent inventory cost function is recoverable from the limit order book, and a sharp phase transition separates a functioning regime from a frozen one. A closing meta-theorem identifies four features invariant across all admissible structural primitives within the axiom system. To our knowledge, this is the first forced-uniqueness axiomatization of the quoting rule.

Defensive pressure on the ball carrier is a fundamental component of soccer tactics. Existing pressure measures often involve additional modeling assumptions, which may reduce interpretability. In this study, we quantify defensive pressure as the opponent minimum arrival time to the ball-carrier location, computed from a physics-based motion model. Using synchronized event and tracking data from all 306 matches in the top division of the Japan Professional Football League during the 2023 season, we analyze the statistical characteristics and temporal evolution of this quantity during ball-possession intervals. The results show that the opponent minimum arrival time tends to decrease during possession and to increase again at the start of the next possession after ball release. We also find that possessions starting under stronger defensive pressure tend to yield smaller ball progression, and that, for intentional open-play passes, possessions ending under stronger pressure are more likely to be lost. These findings indicate that minimum arrival time provides an interpretable and physically grounded measure of immediate defensive pressure on the ball carrier. The proposed framework provides a simple and interpretable baseline for quantifying pressing dynamics from tracking data.

Algebraic Geometry (AG) codes (i.e. linear codes from algebraic function fields) in the Hamming metric were proposed by Goppa in 1980 and have been intensively studied ever since. Linearized Algebraic Geometry codes, the analogue of AG codes in the sum-rank metric, were instead introduced more recently [9], using quotients of the ring of Ore polynomials with coefficients in an algebraic function field. In this paper, we further investigate the results in [9], providing explicit, optimal and asymptotic constructions.

We present a full-relativistic waveform model for extreme mass-ratio inspirals (EMRIs) by self-consistently combining the effective one-body (EOB) formalism with the Teukolsky equation. The model incorporates analytical, mass-ratio-informed geodesic solutions within a deformed Kerr metric into the source term of the Teukolsky equation, establishing a direct connection between finite-mass-ratio orbital dynamics and gravitational-wave emission. The resulting frequency-domain formulation is coupled to a high-performance solver for the homogeneous Teukolsky equation, enabling rapid evaluation of the tens of thousands of modes required for accurate EMRI waveforms. We generate waveforms and radiation fluxes for generic Kerr orbits and investigate the influence of finite-mass-ratio corrections beyond the test-particle limit. The results show that mass-ratio-dependent deformations produce measurable modifications to radiation fluxes, and accumulated waveform phases over observationally relevant timescales. Our framework provides a generic-orbit EOB--Teukolsky waveform model for future space-based GW data analysis.

Phase contrast MRI (PC MRI) enables quantitative assessment of tissue motion and strain. Although it is increasingly used, standardized, vendor-agnostic pipelines for accelerated acquisitions remain scarce. We present a fully open-source 4D flow PC-MRI pipeline integrating a compressed sensing-accelerated sequence implemented in PyPulseq, BART-based reconstruction, and strain analysis. Additionally, a gradient probing sequence was developed to ensure correct velocity sign assignment across scanner orientations and vendors. The pipeline was validated across two Siemens MRI systems (3T MAGNETOM Prisma and 3T Vida Fit) in two anatomical applications: forearm (Flexor Digitorum Superficialis, n=9) and thigh (Vastus Lateralis, n=10) during Neuromuscular Electrical Stimulation (NMES)-induced contractions. Compressed sensing reduced acquisition times from 35 and 80 minutes to 5 and 11 minutes for the arm and leg acquisitions, respectively. Muscle strain maps and sigmoid-fitted strain curves enabled extraction of peak strain, mean strain, and buildup rate. Strains in the Vastus Lateralis were approximately one order of magnitude higher than in the Flexor Digitorum Superficialis (median peak strain 0.49 vs. 0.063, mean strain 0.31 vs. 0.031). The pipeline demonstrates multi-platform compatibility and provides a reproducible, open framework for quantitative muscle imaging.

We analytically study the Widom line and supercritical crossover of noncommutative charged AdS black holes. Treating the noncommutative parameter $α$ perturbatively, we compute thermodynamic quantities and the scaled variance $Ω$ in both canonical and extended ensembles. The Widom line is identified as the extremum of $Ω$. Using a Landau expansion near the critical point, we derive the two symmetric crossover branches $L^{\pm}$, which obey $δT\sim \left|ΔQ\right|^{β+γ}$, $δS\sim \left|ΔQ \right|^β$ in the canonical ensemble and $δP\sim \left|ΔT\right|^{β+γ}$, $δρ\sim \left|ΔT\right|^β$ in the extended ensemble. These scaling relations conform to the mean-field universality class ($β=1/2$, $γ=1$), and the noncommutative parameter only shifts subleading amplitudes without altering the universality class. Numerical verification and complete supercritical phase diagrams are also presented using supercritical crossover lines. Our results show that noncommutative corrections preserve the mean-field universality of black hole supercriticality.

This paper presents a focused investigation of a conservative chaotic system, specifically within the context of a two-dimensional harmonic potential well. We analyse the emergence of chaos from a straightforward, non-chaotic harmonic potential well when subjected to perturbations introduced by two Gaussian-like terms in the system's Hamiltonian. The Gaussian-perturbed system serves as a foundation for further inquiries rooted in the cymatics mechanism. In this study, we examine the effects of deformations arising from Gaussian perturbations on the development of chaotic dynamics. These deformations are produced through various configurations of Gaussian bumps in different geometric shapes, along with the modulation of the amplitude of the perturbed term shifting from positive to negative values.

This paper presents a novel framework to track the effective surface area of non-convex satellites, enabling the use of aerodynamic drag in low Earth orbit for orbital control. The proposed framework enables the satellite to track the effective surface area while simultaneously performing other maneuvers. We introduce this framework through a backstepping control algorithm, and exemplify its advantages with an extension, to simultaneously maximize solar panel exposure. The equilibria of the closed-loop systems are shown to be asymptotically stable, and simulation results confirm the effectiveness of the proposed framework.

In this paper we clarify the relation between Geometric Thermodynamics and Information Geometry based on the Fisher matrix. On the macroscopic odd-dimensional contact manifold of thermodynamic variables, we introduce for the first time a metric, whose pull-back on the isoentropic symplectic submanifolds transverse to the Reeb field is Kählerian. The pull-back of such metric on equilibrium states, that are lagrangian submanifolds, is the Fisher Hessian. Then we consider the Souriau-like Thermodynamics that uses Calabi-Vesentini (CV) manifolds as Kaehlerian microscopic event manifolds and the Killing moment maps as observable functions. A systematic use of the theory of compact abelian structures and the setup of Special Kähler Geometry in which CV manifolds are encoded allows us to perform the explicit integration defining the partition function for any entry in the CV Tits Satake universality class. The additional actions completing the abelian structure are non linear Casimir functions of the Killing moment-maps and suggest a generalization of Souriau thermodynamics that partially breaks the isometry group symmetry by means of the non vanishing mean values of the Casimir functions in a manner similar to the spontaneous magnetization in ferromagnetism. Our new exact Gibbs distributions provide the analogue for Cartan Neural Networks of the Gaussian probability distributions in flat space used in conventional Machine Learning.

Let $f(n,H)$ be the maximum number of copies of a graph $H$ in a planar graph of order $n$. When $H$ is a connected graph on four vertices, $f(n,H)$ has been completely determined except for two cases: $K_{1,3}^+$ (the claw graph $K_{1,3}$ with one additional edge) and $K_4^-$ (the complete graph $K_4$ with one edge removed). Here, we address these two cases and establish that for all $n\ge4$, $$f(n,K_{1,3}^+) = 4n^2-12n-4 \textrm{ and } f(n,K_4^-) =\frac{1}{2}(n^2+9n-40).$$

The emerging AC/multi-terminal DC grids are regarded as a promising solution for accommodating the increasing integration of renewable energy sources. This work proposes an optimization framework to address transmission switching (TS) problems arising in practical operational scenarios, such as maintenance scheduling, contingency management, and fault restoration. Unlike most existing studies, the proposed framework considers the role of communication networks in TS operations and develops an optimal information-power flow (OIPF) model. The OIPF model captures the impact of information flows on circuit breaker actions while incorporating communication-related costs, thereby better reflecting practical operational decision-making processes. To ensure computational tractability, the resulting optimization problem is formulated as a mixed-integer second-order cone programming (MISOCP) model through convex relaxations, polygonal approximations, and Big-M reformulations. Numerical case studies illustrate the applicability of the proposed OIPF model and indicate its potential in supporting transmission switching decisions.

The BCS-motivated idea of Weinberg and Salam on dynamical EW symmetry breaking is revived: The Higgs sector of the EW gauge model of three fermion flavors (families) is replaced with the chiral gauge $SU(3)_f$ quantum flavor dynamics (QFD) strongly coupled at a huge scale $Λ$. I. With all chiral fermions in flavor triplets the anomaly freedom demands the welcome BSM extension of the SM fermion sector by one EW-sterile neutrino $ν_R$ per flavor. II. The QFD distinguishes flavors by generating at strong coupling the chirality-prohibited (i.e. calculable) fermion masses: Three different Majorana masses $M_f \sim Λ$ of $ν_R$, and three different, arguably small Dirac masses $m_f$ of SM fermions degenerate for all species in each flavor. 1. Complete spontaneous breakdown of $SU(3)_f \times U(1)$ by $M_f$ implies: (i) All flavor gluons acquire self-consistently masses $\sim M_f$. (ii) There is the $ν_R$-composite pseudo-NG Majoron. (iii) There are three very heavy $0^{+}$ $ν_R$-composite Higgs bosons. 2. Spontaneous breakdown of the EW $SU(2)_L \times U(1)_Y$ symmetry to $U(1)_{em}$ by $m_f$, in sharp contrast with the Higgs mechanism, implies: (i) The $W$ and $Z$ bosons acquire masses $\sim g(\sum m^2_f)^{1/2}$ and $\sim (g^2+g^{'2})^{1/2}(\sum m^2_f)^{1/2}$ respectively, defining the effective Fermi scale $v=246 \rm GeV$. (ii) There are three SM-fermion-composite $0^{+}$ Higgs bosons $h_f$ at this scale. III. The UV-finite EW dynamical perturbation theory of Pagels and Stokar splits the flavor-degenerate masses of SM-fermions by their electric charges and the ratios $m_f/m_{W,Z}$. Six Majorana neutrino masses are calculable by seasaw.

We investigate late-Universe dynamics in which the dark matter component is described by axion particles. The proposed framework departs from the standard $Λ$CDM paradigm due to a small fraction of axions driving the system away from thermal equilibrium. We analyze the evolution of the axion energy density using both a kinetic and a classical field approach, yielding an identical macroscopic evolution equation for the dark matter density. The resulting scenario modifies $Λ$CDM dynamics in the late Universe (specifically at $z \lesssim 1$), while asymptotically recovering the standard baseline at earlier cosmic epochs. We compare the theoretical predictions of our formulation against a comprehensive suite of late-Universe datasets. Our statistical analysis reveals that when the SH0ES local calibration is included, the collisional axion model becomes significantly favored over $Λ$CDM, yielding a best-fit Hubble constant of $H_0 \simeq 73~{\rm km\,s^{-1}\,Mpc^{-1}}$. Ultimately, this cosmological scenario successfully accommodates local distance-ladder measurements while maintaining excellent agreement with Baryon Acoustic Oscillation data from the DESI Collaboration.

The Central Molecular Zone of the Milky Way is shaped by the interplay of bar-driven inflows, shocks, and star formation. At Galactic longitude l=1.3, gas inflowing along the near-side dust lane has been proposed to interact with the CMZ boundary and overshoot above the Galactic plane, making this a key site to investigate how large-scale gas dynamics regulates star formation. We aim to investigate the presence of Class I methanol maser emission in this transitional region, testing whether large-scale gas interactions in the CMZ can trigger widespread maser activity via star formation or shocks. We conducted a dedicated search for the 36.2 and 44.1 GHz Class I CH3OH maser lines, along with the 48.4 GHz thermal transition, using the Yebes 40m telescope. We complemented these data with archival data from the Herschel-HiGAL survey and the CHIMPS2 survey to explore links between masers, shocks, and star formation. We detect widespread 36.2 GHz maser emission and two candidate 44.1 GHz masers in a region extending several parsecs. The brightest maser has an isotropic luminosity 0.9x10^-3 L_Sun, placing it among the most luminous Galactic Class I masers. Thermal CH3OH and SiO emission extend over mapped area of 24 pc, with both species showing enhanced fractional abundances. CO position-velocity analysis further shows that the masers are associated with an extended velocity feature at VLSR~100 km/s. We conclude that the observed masers are primarily associated with shock-processed gas in a kinematically complex bar-CMZ interface region. Large-scale gas interactions are likely to play an important role in producing the maser emission, although a subset of the masers may also be linked to shocks driven by local star-formation activity. This region therefore provides a promising Galactic analogue of shock-dominated Class I CH3OH maser environments observed in nuclear regions of barred galaxies.

Monochromators are routinely used in Transmission Electron Microscopy and Electron Energy Loss Spectroscopy, to improve both spatial and energy resolution. State-of-the-art monochromators, however, are complex instruments that typically require additional electron optical correctors, limiting their implementation to the high-end, most expensive microscopes. Miniaturized monochromation relying on purely electrostatic fringe fields has recently been proposed as a means to realize a simpler and thereby more cost-effective and easier to operate high-resolution monochromator. Here, we present a design for such a compact, fully electrostatic fringe-field based monochromator. Our design consists of a superposition of an Einzel lens with a series of electrostatic deflectors and is entirely based on dimensions that can be realized with MEMS fabrication technology. Thanks to mild mechanical and electrostatic potential tolerances, the MEMS-fabricated electrodes can be passively aligned and only need seven regular power supplies. We present an analysis of spectral broadening due to diffraction in our monochromator design as well as particle simulations including stochastic Coulomb interactions. This analysis shows that our design can achieve a resolution of 19 meV while maintaining 128 pA of beam current and thus potentially achieve energy filtering comparable to state-of-the-art monochromators. Our MEMS monochromator could therefore bring the application of energy filtering into the domain of SEM and specifically allow higher resolution imaging in chromatic-aberration dominated low-voltage SEM.

Benchmarking forecasting architectures for daily equity portfolios is not just a prediction exercise. It also asks which model remains usable after preferences, costs, and portfolio constraints are imposed. We build a CRSP daily-stock benchmark for 15 deep and statistical time-series architectures over 2018--2024. The protocol combines common-window decile portfolios, stochastic multi-criteria acceptability analysis, a deployment-adjusted acceptability index, and a constrained quadratic portfolio layer with capacity, beta, industry, risk, leverage, and turnover controls. The index starts from the SMAA rank-acceptability distribution and downweights models whose criteria-level wins produce high portfolio regret; its Gibbs form is characterized as an entropic update from the SMAA prior. Empirically, no architecture dominates the raw benchmark: TransEnc-8 has the largest rank-1 acceptability, 0.352, and no model exceeds about 0.36. Rankings vary with preferences, market state, feature universe, and transaction costs. In the promoted five-model constrained-portfolio comparison, TransEnc-8 is selected throughout, while return-oriented raw rankings can favor TS-RIDGE. Broad-universe decile signals can survive costs, but the baseline constrained-QP net Sharpe at 20 bps is negative for every promoted model. The benchmark supports model selection and diagnosis rather than a standalone trading-strategy claim.

Given a smooth curve $C$ on a polarized abelian variety $(A,θ),$ we show that that quotient between the Seshadri constant of $(A,θ)$ and the degree of $C$ is bounded above by an intrinsic invariant of $C.$ This invariant is defined in terms of the (non) surjectivity of certain high order Gauß-Wahl maps on the curve. As a consequence, we prove a sharp Castelnuovo-type inequality for hyperelliptic curves on abelian varieties and characterize the cases in which we have equality. This is an extension to higher dimensions of the fact that smooth hyperelliptic curves on abelian surfaces have genus at most five. At the end, we compare this result to the conjectural picture about polarized abelian varieties with small Seshadri constant.

Resolving in a strong sense an old problem of Gyárfás from the 1980s on the union of two perfect graphs, we prove that for every pair of positive integers $d$ and $k$, there is a graph $G$ with clique number $k$ and chromatic number $k^d$ that is the union of $d$ comparability graphs.

Decomposing active galactic nucleus (AGN) emission from host-galaxy light is essential for identifying AGN-dominated systems and accurately deriving host-galaxy physical properties. However, estimating AGN contributions from multi-wavelength photometry remains challenging due to inherent parameter degeneracies in spectral energy distribution (SED) fitting. In this work, we establish a unified framework for estimating AGN contribution fractions and host-galaxy properties by combining complementary diagnostics: SED decomposition with two independent fitting codes, CIGALE and GRAHSP, and deep-learning-based imaging decomposition. We apply this framework to galaxies in the COSMOS-Web field using multi-wavelength photometry from the ultraviolet to the far-infrared. We calculate the AGN contribution fraction in the JWST/NIRCam F150W filter and compare the SED-derived estimates with independent AGN fractions obtained from deep-learning image decomposition. Our results reveal significant degeneracies in current SED-fitting approaches based on empirical or theoretical AGN templates and demonstrate that incorporating independent morphological information can help break these degeneracies and improve the reliability of AGN and host-galaxy property estimates.

Pharmacovigilance systems handle sensitive healthcare and drug-safety data, including adverse event reports and clinical observations. As quantum computing advances, classical public-key cryptographic systems such as RSA and elliptic-curve cryptography may become vulnerable, creating long-term risks for healthcare data that must remain confidential for many years. This paper presents an educational prototype of a post-quantum secure pharmacovigilance data pipeline. The system uses ML-KEM-768 for post-quantum key establishment, HKDF-SHA-256 for deriving an AES key, AES-256-GCM for efficient file encryption, and ML-DSA-65 for digital signatures and tamper detection. The pipeline supports multiple file formats, including TXT, CSV, JSON, and PDF, by treating files as raw bytes and preserving metadata for reconstruction at the receiver. The prototype includes separate hospital, gateway, pharma receiver, attacker, benchmarking, and dashboard components. We evaluate the system using synthetic pharmacovigilance datasets of different sizes and formats. Our results show that ML-KEM adds a small constant overhead, while AES encryption and ML-DSA signing dominate runtime as file size increases. This work is not a production-ready healthcare system, but rather an educational systems-level exploration of how post-quantum cryptographic primitives can be integrated into healthcare-style data pipelines.

This paper introduces a novel class of delayed functional observers specifically designed to reconstruct delayed control laws under severe output measurement lags, directly complementing recent literature \cite{trinhnn26, trinhnam26}. By systematically mitigating simultaneous, unequal delays across both the actuator and sensor channels, the proposed architecture resolves dual-channel latency without requiring full-state estimation or computationally intensive real-time distributed integration. Ultimately, this work provides a powerful, low-order framework that bridges the gap between idealized control theory and the practical constraints of modern networked engineering systems.

Alternating current (AC)/multi-terminal direct current (MTDC) hybrid power systems (HPSs) play a crucial role in enabling long-distance power transmission and flexible interconnections between AC grids. However, the challenges that HPSs encountered are numerous, with stability and harmonic issues being particularly prominent. Traditional electromagnetic transient (EMT) tools have struggled to accommodate small-signal stability problems and the potential issues of the optimal interactions among converters. To address this gap, HARMONY ("HARMONic stabilitY assessment of PE-penetrated power systems") has been developed for the advanced simulation and analysis of interconnected AC/MTDC HPSs as a comprehensive mathematical framework based on C++ programming language. The primary goals of Harmony are to provide faster and trusted stability analyses, and address the analytical difficulties associated with converter control dynamics, converter-driven stability, and interoperability in HPSs. This framework is intended to be open source, therefore broadening collaboration for researchers, and to contribute to the community of power systems engineers. In this paper, we demonstrate two core functionalities featured in HARMONY, that are optimal power flow (OPF) and harmonic stability analyses (HAS). The underlying analysis models and computational methodologies for both functionalities are presented in detail to help future readers and users gain a clear understanding of mathematical fundamentals of HARMONY. Furthermore, we introduce the integrated framework of OPF and HAS designed in HARMONY, along with representative printed analysis results, to demonstrate the appealing capabilities of HARMONY.

In the paper, we study the problem of recovering the Sturm-Liouville operator on a star-graph from the Weyl vector. It generalizes the problem of recovering the classical Sturm-Liouville operator on an interval from the Weyl function, and the problems of recovering from other spectral data can be reduced to this problem. The uniqueness and the constructive method for solving the problem under study were previously obtained by V.A. Yurko in the case of a tree (Inverse Problems, 2005). Here, we prove its uniform stability, which includes Lipschitz estimates with a constant depending only on the number bounding the norms of the potentials. Stability results are necessary for justifying the well-posedness of the problem statement, and they are important for developing numerical methods. As auxiliary results, we obtain the uniform stability of the direct problem, as well as the uniform stability of the partial derivatives of the transmutation operator kernel related to the classical Sturm-Liouville operator.