We extend Hacon--M\textsuperscript{c}Kernan's rational chain connectedness theorem to the complex analytic setting. As a consequence, we prove that the fibers of any resolution of singularities of complex analytic kawamata log terminal singularities are rationally chain connected. In contrast to the original approach, we avoid the use of extension theorems and instead rely on the minimal model program.

In this article, we consider the reciprocal antisymmetric polynomial \[P(z) = \sum_{j = 0}^{s}(-1)^jγ_j\left(z^j - z^{N + s + 1 - j}\right), \ γ_0 = 1.\] It is shown that if all the zeros of $P(z)$ are located on the unit circle, that $\displaystyle\left|γ_j\right| \leq {s \choose j}\left({N + s + 1 \choose j}\right)^{-1}$, $j = 1,\ldots,s$; moreover, these estimates cannot be improved in the general case. Factorization formulas for extremal polynomials are given: \[ \begin{align} \phantom{a} & \sum_{j = 0}^{s}(-1)^j{s \choose j}\left({N + s + 1 \choose j}\right)^{-1}\left(z^j - z^{N + s + 1 - j}\right) \\ &= (1 - z)^{2s + 1} \prod_{j = 1}^{\left[\frac{N - s}{2}\right]} \left[z^2 + 1 + 2z(1 - 2(ν_j)^2)\right] \begin{cases} (1 + z), & N - s \mbox{ is odd} \\ 1, & N - s \mbox{ is even} \end{cases} \end{align} \] where $\left\{ν_j\right\}_{j = 1}^{\left[\frac{N - s}{2}\right]}$ is the set of positive zeros of the polynomial $U_N^{(s)}(z)$ given $\displaystyle U_N(z) = \sum_{j = 0}^{\left[\frac{N}{2}\right]} (-1)^j \frac{(N - j)!}{j!(N - 2j)!}(2z)^{N - 2j}$ are the Chebyshev Polynomials of the Second Kind and $U_N^{(s)}(z)$ is the $s$th derivative of $U_N(z)$. As an application of the results, formulas were obtained expressing the derivatives of Chebyshev polynomials of the second kind through linear combinations of Chebyshev polynomials of the second kind: \[\frac{2^s}{s!}(1 - z^2)^sU_N^{(s)}(z) = (-1)^s \sum_{j = 0}^{s}(-1)^j{N-j \choose N-s} {N+s+1 \choose j} U_{N + s - 2j}(z). \]

Developers often extract methods to improve readability, understanding, and reuse, while inlining keeps logic in one block. Prior work based on static metrics has not shown clear differences between these practices, and the human side of comprehension and navigation remains underexplored. We investigate Inline Method vs. Extract Method refactorings using a dynamic approach: eye tracking while participants read and solve tasks. We analyze key code areas and compare visual effort and reading behavior (fixation duration and count, regressions, revisits), alongside time and attempts. We ran a controlled experiment with 32 Java novices, followed by short interviews. Each participant solved eight simple tasks across four programs presented in an inlined version and four in an extracted version. We also surveyed 58 additional novices for complementary quantitative and qualitative data. Results show that effects depend on task difficulty. In two tasks, method extraction improved performance and reduced visual effort, with time decreasing by up to 78.8% and regressions by 84.6%. For simpler tasks (e.g., square area), extraction hurt performance: time increased by up to 166.9% and regressions by 200%. Even with meaningful method names, novices often switched back and forth between call sites and extracted methods, increasing navigation and cognitive load. Preferences frequently favored extraction for readability and reuse, but did not always match measured performance. These findings suggest educators should be cautious about premature modularization for novices and highlight eye tracking as a useful complement to static metrics.

We study preference learning through recommendations in multi-agent game settings, where a moderator repeatedly interacts with agents whose utility functions are unknown. In each round, the moderator issues action recommendations and observes whether agents follow or deviate from them. We consider two canonical behavioral feedback models-best response and quantal response-and study how the information revealed by each model affects the learnability of agents' utilities. We show that under quantal-response feedback the game is learnable, up to a positive affine equivalence class, with logarithmic sample complexity in the desired precision, whereas best-response feedback can only identify a larger set of agents' utilities. We give a complete geometric characterization of this set. Moreover, we introduce a regret notion based on agents' incentives to deviate from recommendations and design an online algorithm with low regret under both feedback models, with bounds scaling linearly in the game dimension and logarithmically in time. Our results lay a theoretical foundation for AI recommendation systems in strategic multi-agent environments, where recommendation compliances are shaped by strategic interaction.

What, if anything, should a frequentist say about a single realized confidence interval (CI) and its chance of having covered the parameter? Jerzy Neyman's original answer was to refuse any nondegenerate probability for coverage ex post and, instead, to "state that the interval covers". In this paper I argue that the usual frequentist machinery already supports a different reading. I treat the coverage event as a Bernoulli random variable, with the nominal level 1-alpha as its design-based success probability, and view "confidence" as a probability forecast for that Bernoulli outcome. Using strictly proper scoring rules, I show that 1-alpha is the unique optimal constant forecast for coverage, both before and after observing the data, and that it remains optimal post-trial in common unbounded, translation-invariant models with pivot-based CIs. When the design yields a theta-free statistic--such as the relative width of the interval in a finite-window uniform model--the conditional coverage given that statistic provides a nonconstant, design-based refinement of 1-alpha that strictly improves predictive performance. Two thought experiments, a Monty Hall-style shell game and the "lost submarine" example of Morey et al. (2016), illustrate how this perspective resolves familiar interpretational puzzles about CIs without appealing to priors or single-case subjective degrees of belief. I conclude with simple "what to do when you see an interval" guidance for applied work and some implications for teaching confidence intervals as tools for forecasting long-run coverage. Keywords: Confidence intervals, coverage probability, proper scoring rules, probabilistic forecasting, frequentist inference Disclaimer: The findings and conclusions in this report are those of the author and do not necessarily represent the official position of the Centers for Disease Control and Prevention

We revisit textbook claims that entropy must increase and show that, under time-reversal invariant microscopic dynamics, no universal trajectory-wise or statistical assertion that the coarse-grained entropy $S(t)$ is non-decreasing can hold. The core is a mirror-state construction: for any microstate $A$ one constructs its time-reversed partner $B$ (momenta inverted); requiring $S(t)$ to be non-decreasing for both $A$ and $B$ forces every time to be a local minimum of $S$ and hence makes $S(t)$ constant along the trajectory. The consistent picture is that entropy is a stochastic variable described by a probability distribution $P(S)$ whose shape depends on constraints and boundary conditions; entropy-based regularities are emergent summaries of constraint-dependent microscopic dynamics, and in practice it is constraints and boundaries -- not entropy itself -- that one manipulates to achieve mixing, separation, or self-organization. Working with Boltzmann (coarse-grained) entropy on the energy shell, we then derive from first principles how constraints reshape the long-time entropy distribution $P_{\infty}(S;λ)$ by altering the invariant measure through changes in the Hamiltonian and/or the accessible phase space. In the microcanonical setting we obtain a sharp criterion: the \emph{only} way $P_{\infty}^{(E)}(S;λ)$ can remain the same up to translation is when all accessible macrostate volumes are scaled by a common factor; otherwise the distribution changes structurally. We connect this framework to experiments on asymmetric nanopores and molecular gates, to macroscopic examples from civil engineering (windbreak forests, dikes, vortex suppression, traffic-flow control), and to natural phenomena such as lightning guided to lightning rods, snowflake and mineral-veil growth, and the sudden crystallisation of supercooled water.

Inelastic neutron scattering experiments with a large set of comounted Na$_2$IrO$_3$ crystals reveal the low-energy magnon dispersion in this candidate material for Kitaev physics. The magnon gap amounts to 1.7(1) meV and can be interpreted similarly to the sister compound $α$-RuCl$_{3}$ to stem from the zone boundaries in the antiferromagnetic zigzag structure. The neutron experiments find no evidence for low-energy excitations with ferromagnetic character, which contrasts to the findings in $α$-RuCl$_{3}$. Our results are consistent with a recently proposed microscopic model that involves an antiferromagnetic Heisenberg nearest-neighbor exchange in Na$_2$IrO$_3$ in contrast to the ferromagnetic one considered for $α$-RuCl$_{3}$. Although the magnetic response shows the signatures of bond-directional anisotropy in both materials the different relative signs of Kitaev and Heisenberg interaction result in different deviations from the initial Kitaev model. Low-energy ferromagnetic fluctuations cannot be considered as a fingerprint of ferromagnetic Kitaev interaction.

We present a complete classification of the distributed computational complexity of local optimization problems in directed cycles for both the deterministic and the randomized LOCAL model. We show that for any local optimization problem $Π$ (that can be of the form min-sum, max-sum, min-max, or max-min, for any local cost or utility function over some finite alphabet), and for any constant approximation ratio $α$, the task of finding an $α$-approximation of $Π$ in directed cycles has one of the following complexities: 1. $O(1)$ rounds in deterministic LOCAL, $O(1)$ rounds in randomized LOCAL, 2. $Θ(\log^* n)$ rounds in deterministic LOCAL, $O(1)$ rounds in randomized LOCAL, 3. $Θ(\log^* n)$ rounds in deterministic LOCAL, $Θ(\log^* n)$ rounds in randomized LOCAL, 4. $Θ(n)$ rounds in deterministic LOCAL, $Θ(n)$ rounds in randomized LOCAL. Moreover, for any given $Π$ and $α$, we can determine the complexity class automatically, with an efficient (centralized, sequential) meta-algorithm, and we can also efficiently synthesize an asymptotically optimal distributed algorithm. Before this work, similar results were only known for local search problems (e.g., locally checkable labeling problems). The family of local optimization problems is a strict generalization of local search problems, and it contains numerous commonly studied distributed tasks, such as the problems of finding approximations of the maximum independent set, minimum vertex cover, minimum dominating set, and minimum vertex coloring.

This brief report examines the influence of Ga/N flux conditions on Mn incorporation in GaN. Mn-doped GaN layers were grown at 680$^{\circ}$C by molecular beam epitaxy on a Ga-polar GaN(0001) template substrate under Ga-rich, N-rich, and no-flux conditions (i.e., Mn $δ$ doping). Mn incorporation was highest under N-rich condition, lowest under Ga-rich condition, and intermediate in the absence of Ga and N fluxes. For the growth conditions examined in this study, the corresponding Mn sticking coefficients, relative to that of the N-rich condition, were determined to be 0.31 for no-flux growth and 0.01 for the Ga-rich growth.

We examine the stability of a class of quasilinear parabolic partial differential equations under perturbations. We are interested in the behavior of viscosity solutions as the perturbation parameter vanishes and establish explicit convergence rates by adapting standard comparison arguments. Despite the possible singular or degenerate nature of the parabolic operator, our framework covers, in particular, both the normalized and the variational $p$-parabolic equations, providing quantitative estimates for perturbations of the exponent $p$ and limits arising from regularized approximations.

Diagnosing solar flare conditions is essential for understanding coronal energy release. Using combined microwave and X-ray data, we reconstruct three-dimensional maps of the magnetic field and plasma parameters in the SOL2021-05-07 flare. We use imaging spectroscopy from the Expanded Owens Valley Solar Array (EOVSA) to derive spatial maps of the magnetic field strength, thermal and nonthermal electron densities, and the power-law index of nonthermal electrons through gyrosynchrotron modeling. Simultaneous X-ray observations from Hinode/XRT and Solar Orbiter/STIX, obtained from different vantage points, enable a stereoscopic reconstruction of the flaring loop. By correlating the positions of microwave and thermal X-ray sources, we associate the three-dimensional coordinates with the microwave-derived plasma parameters. We derive observational three-dimensional maps of magnetic field strength, Alfvén speed, and plasma beta in the flaring volume, revealing a magnetically dominated environment. These spatially resolved diagnostics provide valuable constraints for models of magnetic reconnection and flare dynamics and represent a step toward a realistic three-dimensional characterization of energy release in solar eruptive events.

The uncertainty principle constitutes a fundamental pillar of quantum theory, representing one of the most distinctive features that differentiates quantum mechanics from classical physics. In this study, we firstly propose a novel generalized entropic uncertainty relation (EUR) for arbitrary multi-measurement in the many-body systems, and rigorously derive a significantly tighter bound compared to existing formulations. Specifically, we discuss the proposed EUR in the context of Schwarzschild black hole, where we demonstrate the superior tightness of our derived bound. The study further elucidates the dynamical evolution of multipartite quantum coherence and entanglement in the curved spacetime. A particularly noteworthy finding reveals the exact equivalence between entanglement and $l_1$-norm coherence for arbitrary $N$-partite Greenberger-Horne-Zeilinger-type (GHZ-type) states. Moreover, we find that quantum coherence is significantly diminished and the measurement uncertainty increases to a stable maximum with increasing Hawking temperature. Thus, the findings of this study contribute to a deeper understanding of non-classicality and quantum resources in black holes.

Consider a subfield of the field of rational functions in several indeterminates. We present an algorithm that, given a set of generators of such a subfield, finds a simple generating set. We provide an implementation of the algorithm and show that it improves upon the state of the art both in efficiency and the quality of the results. Furthermore, we demonstrate the utility of simplified generators through several case studies from different application domains, such as structural parameter identifiability. The main algorithmic novelties include performing only partial Gröbner basis computation via sparse interpolation and efficient search for polynomials of a fixed degree in a subfield of the rational function field.

We analyze the stability and bifurcation structure of steady states in a mechanochemical model of pattern formation in regenerating tissue spheroids. The model couples morphogen dynamics with tissue mechanics via a positive feedback loop: mechanical stretching enhances morphogen production, while morphogen concentration modulates tissue elasticity. Global strain conservation implements a nonlocal inhibitory effect, realizing a mechanochemical variant of the local activation--long-range inhibition mechanism. For exponential elasticity-morphogen coupling, the system admits a variational formulation. We prove existence of nonconstant steady states for small diffusion and uniqueness of the homogeneous state for large diffusion. Linear stability analysis shows that only unimodal patterns are stable, while multimodal solutions are unstable. Bifurcation analysis reveals subcritical and supercritical pitchforks, with fold bifurcations generating bistable regimes. Our results demonstrate that mechanochemical feedback provides a robust mechanism for single-peaked pattern formation without requiring a second diffusible inhibitor.

Stellarator optimization is a multi-objective, non-convex problem characterized by a complex objective landscape containing many local minima. The solution resulting from a single optimization is highly sensitive to factors such as the initial guess, objective weights, and the optimization method employed. However, merely varying these factors does not guarantee that a physically distinct minimum will be found; optimizations often fail to converge to good minima or simply return to the same or very similar local minima despite large-scale parameter scans. This paper presents a novel application of deflation methods to effectively explore this landscape. By modifying the objective function to penalize and "deflate" away already-found solutions, this technique encourages the optimizer towards attractive, distinct new minima while using a single initial guess and optimization setup. We provide a primer on deflation for nonlinear systems and non-convex optimization before applying it to non-axisymmetric equilibrium and stellarator optimization problems. Key results include the discovery of families of global equilibria with similar core characteristics and the convergence to helical core equilibria without prescient initial guesses. Furthermore, we demonstrate that augmenting stage-one stellarator and stage-two coil optimization with deflation constraints readily produces multiple high-quality, distinct solutions, establishing the method's efficacy and ease of use.

We investigate the reflection theory of Nichols algebras over arbitrary coquasi-Hopf algebras with bijective antipode, generalizing previous results restricted to the pointed cosemisimple setting [47]. By establishing a braided monoidal equivalence between categories of rational Yetter-Drinfeld modules via a dual pair, we demonstrate that a tuple of finite-dimensional irreducible Yetter-Drinfeld modules admitting all reflections gives rise to a semi-Cartan graph. As an application, we consider an explicit example of a rank three Nichols algebra from [41]. We show that it yields a standard Cartan graph and prove that it is, in fact, an affine Nichols algebra.

The temporal stability and reproducibility of qubit parameters are critical for the long-term operation and maintenance of superconducting quantum processors. In this work, we present a comprehensive longitudinal characterization of 27 frequency-tunable transmon qubits spanning over one year across four thermal cycles. Our results establish a distinct hierarchy of stability for superconducting hardware. We find that the intrinsic device parameters determining the qubit frequency and the baseline energy relaxation times ($T_1$) exhibit high robustness against thermal stress, characterized by frequency deviations typically confined within 0.5\% and non-degraded coherence baselines. In stark contrast, the environmental variables, specifically the background magnetic flux offsets and the microscopic landscape of two-level system (TLS) defects, undergo a significant stochastic reconfiguration after each cycle. By employing frequency-dependent relaxation spectroscopy and a quantitative metric, the $T_1$ Spectral Topography Fidelity, we demonstrate that thermal cycling acts as a ``hard reset'' for the local defect environment. This process introduces a level of spectral randomization equivalent to thousands of hours of continuous low-temperature evolution. These findings confirm that while the fabrication quality is preserved, the specific noise realization is statistically distinct for each thermal cycle, necessitating automated recalibration strategies for large-scale quantum systems.

There might exist non-rational Virasoro CFTs in two dimensions with a $(\text{Fib} \boxtimes \text{Fib}) \rtimes S_2$ categorical symmetry. We calculate the necessary ingredients for a modular conformal bootstrap analysis of these theories. After reviewing the basics of fusion categories, we present the irreducible representations, the lasso maps that intertwine between different Hilbert spaces, and finally the 22-by-22 modular S matrix. We highlight the peculiarities introduced by the non-invertible nature of the symmetry. This paper is written in a pedagogical manner and can therefore serve as an accessible entry point into the literature.

We study a rigidity problem for functions \(F:\R_{>0}\to\R_{\ge 0}\) that penalize deviation of a positive ratio from equilibrium \(x=1\). Assuming (i) a d'Alembert-type composition law on \(\R_{>0}\), and (ii) a single quadratic calibration at the identity (in logarithmic coordinates), we prove that \(F\) is uniquely determined. The composition law implies the normalization $F(1)=0.$ The unique solution is called the canonical reciprocal cost, namely the difference between the arithmetic and geometric means of \(x\) and its reciprocal. Our proof uses the logarithmic coordinates \(H(t)=F(e^t)+1\), where the composition law becomes d'Alembert's functional equation on \(\R\). The calibration provides the minimal regularity needed to invoke the classical classification of continuous solutions and fixes the remaining scaling freedom, selecting the hyperbolic-cosine branch. We also establish necessity of each assumption: without calibration the composition law admits a continuous one-parameter family, without the composition law the calibration does not determine the global form, and without regularity the composition law admits pathological non-measurable solutions. Finally, we establish a stability estimate for approximate solutions under bounded defect and characterize some properties of the canonical cost.

The Rashba-split two-dimensional electron gas (2DEG) at the surface and interface of insulating oxides like KTaO$_{3}$ (KTO) shows great promise for all-oxide spintronics. However, efficient spin current injection into the adjacent 2DEG remains a key challenge. In this study, we report the spin-pumping experiments on a 2DEG formed on the (001)KTO surface via Ar$^+$ irradiation. We observed a significant increase in magnetic damping in the Ar$^+$-KTO/Py bilayer compared to a non-irradiated KTO/Py control sample, confirming spin pumping into the 2DEG. We demonstrate that the spin-mixing conductance ($g_{\uparrow\downarrow}^r$) can be substantially enhanced by controlling the Ar$^+$ irradiation time. The enhancement is attributed to increased 2DEG conductance, which results from a higher concentration of oxygen vacancies with longer irradiation times. This work provides crucial guidance for optimizing spin-to-charge conversion in KTO-based systems, highlighting the potential of Ar$^+$-irradiated KTO 2DEGs for future oxide spintronics.

This paper is devoted to studying the deformation behavior of pseudo-effective canonical divisors and volumes of adjoint classes in Kähler families. Based on recent developments in the Kähler minimal model program, for flat families with fiberwise canonical singularities, we establish the global stability of the pseudo-effectivity of canonical divisors and uniruledness, assuming in addition that one fiber is projective, while the same conclusion for Kähler threefolds is also true without the projectivity assumption of the central fiber. For a smooth Kähler family whose central fiber is projective with a big adjoint class, we show that its volume remains locally constant. Finally, using the (relative) minimal model program for Kähler threefolds, we verify the deformation invariance of volumes of adjoint classes and plurigenera for smooth families of Kähler threefolds, thereby confirming Siu's invariance of plurigenera conjecture in dimension three.

The universal property for the Bénabou bicategory of distributors (although we call them "modules") presented here is somewhat implicitly spread over a series of papers and yet, to my knowledge, does not appear in print. The inclusion of a bicategory $\mathscr{W}$ into the bicategory $\mathscr{W}\text{-}\mathrm{Mod}$ of $\mathscr{W}$-enriched categories and modules between them does have a completion property with respect to freely adjoining lax colimits (collages). Here we are interested in the universal property of the construction of $\mathscr{W}\text{-}\mathrm{Mod}$ from $\mathscr{W}\text{-}\mathrm{Cat}$. What we have in mind is an objective version of the notion of {\em homological functor} used by André Joyal in 1985.

We demonstrate height-controlled topological switching of plasmonic spin meron lattices above a metallic square coupling structure under circularly polarized illumination. Near the interface, an evanescent surface plasmon polariton (SPP) channel yields a Néel-type meron lattice with $\pm\frac{1}{2}$ like effective site charges. At larger heights, diffracted fields from the square edges dominate and convert the lattice into a Bloch-type configuration. Over a range of intermediate heights, crossover between the evanescent SPP and edge diffraction gives rise to rich rapid topology evolutions. The switching is accompanied by nucleation of off-boundary vortex-anti vortex pairs in the in-plane spin phase, producing height-dependent fractional site charges. Our findings are analytically formulated by linear superposition of SPPs in the plasmonic regime and Stratton-Chu model in diffraction regime and confirmed via full-wave finite-difference time-domain simulations.

This scientometric study analyzes Avian Influenza research from 2014 to 2023 using bibliographic data from the Web of Science database. We examined publication trends, sources, authorship, collaborative networks, document types, and geographical distribution to gain insights into the global research landscape. Results reveal a steady increase in publications, with high contributions from Chinese and American institutions. Journals such as PLoS One and the Journal of Virology published the highest number of studies, indicating their influence in this field. The most prolific institutions include the Chinese Academy of Sciences and the University of Hong Kong, while the College of Veterinary Medicine at South China Agricultural University emerged as the most productive department. China and the USA lead in publication volume, though developed nations like the United Kingdom and Germany exhibit a higher rate of international collaboration. "Articles" are the most common document type, constituting 84.6% of the total, while "Reviews" account for 7.6%. This study provides a comprehensive view of global trends in Avian Influenza research, emphasizing the need for collaborative efforts across borders.

In quantum physics, multiparticle systems are described by quantum states acting on tensor products of Hilbert spaces. This product structure leads to the distinction between product states and entangled states; moreover, one can quantify entanglement by considering the distance of a quantum state to the set of product states. The underlying optimization problem occurs frequently in physics and beyond, for instance in the computation of the injective tensor norm in multilinear algebra. Here, we introduce a method to determine the maximal overlap of a pure multiparticle quantum state with product states based on considering several copies of the pure state. This leads to three types of hierarchical approximations to the problem, all of which we prove to converge to the actual value. Besides allowing for the computation of the geometric measure of entanglement, our results can be used to tackle optimizations over stochastic local transformations, to find entanglement witnesses for weakly entangled bipartite states, and to design strong separability tests for mixed multiparticle states. Finally, our approach sheds light on the complexity of separability tests.

Absorption profiles of vector light upon interaction with atomic vapor carries distinct signatures of external magnetic field vector. However, this signature becomes ambiguous for anti parallel magnetic field vectors of equal magnitude, which makes their absorption profiles visually indistinguishable. To resolve this ambiguity, we present theoretical analysis of the interaction of vector light with optically polarized atoms immersed in reference and test magnetic fields. Furthermore, we demonstrate the complete characterization of the arbitrarily oriented test magnetic field via Fourier analysis of the absorption profile. This analysis reveals a one to one correspondence between the magnetic field properties and the profiles contrast and rotational angle. Our findings open an avenue to design an optical vector atomic magnetometer based on structured light fields.

We report a comprehensive investigation of the physical properties of the Dirac semimetal compound EuAuBi single crystals, using neutron diffraction, magnetization, electrical transport, and specific heat measurements. EuAuBi crystallizes in a hexagonal structure with space group P63mc (No. 186). First-principles calculations using density functional theory characterize it as a Dirac semimetal, with a notable band-crossing in proximity to the Fermi level (EF ) along the Γ-A direction. The crystal exhibits three distinct magnetic phases at 4 K (TN1), 3.5 K (TN2), and 2.8 K (TN3)as observed from magnetic and specific heat measurements. However, zero-field neutron diffraction resolves only two magnetic phases: a commensurate antiferromagnetic phase and a canted antiferromagnetic phase. Field-dependent ac and dc magnetization measurements uncover field-induced non-trivial spin textures in the magnetic field range 1.5 to 3 T, manifested as a tilted plateau in the magnetization curves. The interplay between conduction carriers and these spin textures is further evidenced by unique features in the magnetic field-dependent longitudinal resistivity in the system. Finally, we present a comprehensive magnetic phase diagram of EuAuBi, highlighting diverse spin alignments present in the material. EuAuBi thus emerges as a rare material system in which both momentum-space and real-space Berry curvature effects may coexist, providing a unique opportunity to investigate their interplay.

How do individuals recover from cybercrimes? Victims experience various types of harm after cybercrimes, including monetary loss, data breaches, negative emotions, and even psychological trauma. The aspects that support their recovery process and contribute to individual cyber resilience remain underinvestigated. To address this gap, we interviewed 18 cybercrime victims from Western Europe using a trauma-informed approach. We identified four common stages following victimization: recognition, coping, processing, and recovery. Participants adopted various strategies to mitigate the impact of cybercrime and used different indicators to describe recovery. While they mostly relied on social support and self-regulation for emotional coping, service providers largely determined whether victims were able to recover their money. Internal factors, external support, and context sensitivity collectively contribute to individuals' cyber resilience. We recommend trauma-informed support for cybercrime victims. Extending our conceptualization of individual cyber resilience, we propose collaborative and context-sensitive strategies to address the harmful impacts of cybercrime.

Stochastic kinetic models describe systems across biology, chemistry, and physics where discrete events and small populations render deterministic approximations inadequate. Parameter inference and inverse design in these systems require optimizing over trajectories generated by the Stochastic Simulation Algorithm, but the discrete reaction events involved are inherently non-differentiable. We present an approach based on straight-through Gumbel-Softmax estimation that maintains exact stochastic simulations in the forward pass while approximating gradients through a continuous relaxation applied only in the backward pass. We demonstrate robust performance on parameter inference in stochastic gene expression, first recovering kinetic rates of telegraph promoter models from both moment statistics and full steady-state distributions across diverse and challenging synthetic parameter regimes, then inferring the kinetic parameters of a four-state promoter model from experimental single-molecule RNA timecourse measurements. We further apply the method to inverse design in stochastic thermodynamics, optimizing non-equilibrium currents in an interacting particle system under kinetic resource constraints and recovering known analytical bounds. The ability to efficiently differentiate through exact stochastic simulations provides a foundation for systematic scalable inference and rational design across the many domains governed by continuous-time Markov dynamics.

In this extended abstract, we propose a novel research topic in the field of agentic AI, which we refer to as self-coding information systems. These systems will be able to dynamically adapt their structure or behavior by evaluating potential adaptation decisions, generate source code, test, and (re)deploy their source code autonomously, at runtime, reducing the time to market of new features. Here we motivate the topic, provide a formal definition of self-coding information systems, discuss some expected impacts of the new technology, and indicate potential research directions.