We introduce a new algorithm for computing persistent homology of Vietoris--Rips filtrations, which in many cases offers a considerable speedup over the existing implementation of the persistence pairing algorithm. The key innovation, called active enumeration, is made possible by a new theoretical framework of Reduction to Zero Differentials (hence RedZeD) in which to view persistent homology.

This paper develops a stochastic-geometry framework for high-altitude platform station (HAPs) networks in which platforms execute cyclic patrol trajectories anchored to designated service regions. We introduce two small-circle ring Cox process models on the spherical Earth. In the small-circle ring Poisson Cox process (SCR-PCP), platforms form one-dimensional Poisson point processes on localized patrol rings, whereas in the small-circle ring binomial Cox process (SCR-BCP), each ring contains a fixed number of uniformly distributed platforms. We establish the isotropy of both models and derive spatial statistics, including the distributions of the nearest-anchor, nearest-ring, and nearest-HAPs distances, together with the joint serving distance and serving ring angle distribution required for SCR-BCP analysis. Building on these results, we derive coverage probability expressions under nearest-HAPs association by decomposing aggregate interference into same-ring and other-ring components and characterizing their conditional Laplace transforms. To account for the flight dynamics of patrol-based HAPs, we integrate a steady circular flight propulsion model with the communication analysis and introduce a coverage energy efficiency (CEE) metric. This yields an analytical condition for the energy-optimal patrol radius that balances coverage performance against the propulsion cost of circular flight. Numerical results reveal fundamental differences between intensity-driven (SCR-PCP) and finite-fleet (SCR-BCP) deployments and demonstrate that patrol geometry, platform density, and cruising velocity should be jointly optimized to achieve energy-efficient HAPs operation.

We report the detection of a short optical burst in TESS data of IGR J17014-4306, the eclipsing intermediate polar with the longest known orbital period. The burst lasts 1.56 d and shows multiple peaks, reaching $(9.3 \pm 0.2) \times 10^{33}$ erg s$^{-1}$, and releases a total energy of $(3.25 \pm 0.01) \times 10^{38}$ erg. The burst parameters are consistent with those of a micronova eruption, currently understood as a thermonuclear runaway in the magnetically-confined accretion column. From its energy, we infer a burned column mass of $\sim 1.6 \times 10^{-11}$ M$_\odot$, which implies a recurrence time of $\sim 20$ d. Our search for similar events in long-term Gaia, ASAS-SN, and AAVSO light curves reveals 16 possible fast brightenings over $\sim 11$ yr, suggesting that micronova events may be frequent in IGR J17014-4306. Timing analysis of the TESS data shows that the white-dwarf spin period remains stable before and after the burst. During the burst, however, the power spectrum becomes more complex and exhibits multiple peaks. The classification of IGR J17014-4306 as a micronova brings the total number of confirmed systems to eight. Its extreme orbital period and eclipsing nature make it an ideal test-bed for further studies of magnetically confined thermonuclear burning on white dwarfs.

We investigate the excitation modes of confined synthetic-antiferromagnetic (SAF) skyrmions using micromagnetic eigenvalue and ringdown simulations. Starting from a single skyrmion in a ferromagnetic layer, where the lowest-frequency modes are a gyrotropic and a breathing mode, we study how antiferromagnetic interlayer coupling modifies the dynamics in SAF bilayers. We consider several geometries: single SAF skyrmions in square and rectangular confinement, unequal layer thicknesses, and strips containing multiple skyrmions. The antiferromagnetic coupling strongly modifies the low-frequency dynamics. The square geometry exhibits two nearly degenerate gyrotropic modes, where in each both layers have the same rotation sense. In rectangular geometries, we instead find nearly linear SAF skyrmion translation emerging from opposite gyration sense in the two layers. These translational modes become the characteristic low-frequency excitations of SAF skyrmion chains. For skyrmion chains, we identify collective translational and breathing modes with standing-wave-like spatial profiles. Beyond ferromagnetic-like breathing modes, the SAF geometry supports breathing oscillations in which the two layers oscillate out of phase. We further demonstrate signal propagation along extended SAF skyrmion chains with propagation velocities comparable to ferromagnetic skyrmion chains. These results provide a systematic description of the collective dynamics of SAF skyrmions arising from the interplay of geometric confinement, intralayer, and interlayer coupling.

Agentic AI is increasingly being integrated into software engineering workflows. In crowdsourced testing, however, the large volume and uneven quality of submitted reports still create a substantial review burden for developers. In prior work, we developed and validated a multi-agent assessment backbone based on the LLM-as-a-Judge paradigm. That backbone assesses reports along three dimensions--textuality, adequacy, and competitiveness--and was shown to align well with human consensus while substantially reducing assessment effort. Yet reliable automated judging does not by itself show whether agent outputs can improve human work when embedded into workflow. This paper studies that missing question in the context of crowdsourced testing. We investigate whether assessment-derived, actionable feedback can improve how testers revise reports, perform on later tasks, and transfer reporting practices across applications. To do so, we conducted a controlled four-stage human-subject study with 20 testers across three real-world applications. The results show that agent-generated feedback supports immediate improvements in revised reports, better first submissions on a new task after prior feedback exposure, and evidence of partial but meaningful transfer to a later application. A post-task questionnaire completed by 17 participants complements these artifact-based findings by suggesting that the feedback was generally understandable, acted upon in revision, and carried into later tasks, while also revealing remaining friction in specificity and execution. Overall, the study provides empirical evidence that, in the studied crowdsourced testing setting, assessment agents can serve not only as post-hoc judges but also as workflow-integrated feedback providers that support upstream report-quality improvement.

A \emph{$k$-cactus} generalizes forests and cacti by allowing each edge to lie on at most $k$ cycles. The maximum number of edges is classical for forests and cacti, but for $k$-cacti was known only for $k\le 4$. In this note we treat general $k$. The key idea is that bounding the cycles through each edge forces a $k$-cactus to exclude a large complete minor; in particular, the class of $k$-cacti is minor-closed. From this we prove that every $n$-vertex $k$-cactus has $O\!\left(\frac{\log k}{\sqrt{\log\log k}}\,n\right)$ edges for all sufficiently large $k$, and a construction shows this is optimal up to a factor of $\sqrt{\log\log k}$.

In the fields of vision science, cognitive psychology, and psycholinguistics, the accurate measurement of reading speed is frequently hampered by the limitations of static reading charts. Repeated testing often leads to memorization effects, while the requirement for oral recitation introduces speech-motor confounds that obscure true information processing speed. To address these methodological hurdles, this paper introduces an open-source MATLAB toolbox that adapts the sentence generation paradigm originally proposed by Perrin, Paillé, and Baccino (2014) for the English language. This system utilizes a semantic ontology and a "proto-truth" logic to autonomously generate thousands of unique, grammatically simple sentences with unambiguous truth values. Beyond the original scope of Maximum Reading Speed (MRS) measurement, this implementation introduces band-pass psycholinguistic filtering and specific logic to resolve semantic ambiguities unique to English. We present this complete software package as an open platform for the scientific community to validate and refine.

Let $Ω\subset\C$ be a bounded domain whose boundary is an oval of a real algebraic curve. We study when the exterior Cauchy transform \[ \ct_Ω(z)=\frac1π\int_Ω\frac{dA(ζ)}{z-ζ} \] is algebraic. The boundary formula identifies this transform with a Cauchy-type integral on the normalization $X$ of the relevant irreducible component of the Schwarz correspondence $P(z,w)=0$. The main point is that $X$ is fixed while only the divisor $π^{-1}(z)$ of moving poles varies. Thus the natural monodromy is point-pushing on a punctured fixed surface and becomes trivial on absolute homology after the moving punctures are filled; in particular, the usual Picard--Lefschetz transvection picture does not produce absolute cycles in this problem. The principal theorem is a residue criterion: if the lifted boundary is separating, i.e., if it bounds an integral two-chain on $X$ disjoint from the fixed polar divisor, then the exterior Cauchy transform is algebraic and is given by an explicit residue sum with chain multiplicities. This implies, in particular, algebraicity for every smooth oval on a rational real algebraic curve and for separating ovals in positive genus. We also record the corresponding complete-real-locus statement for dividing real curves, with the necessary affine-plane caveats. Nonseparating ovals are treated as a conjectural period problem: we formulate a period-rank test which can detect possible Abelian contributions. The examples include the ellipse, the nodal cubic logarithm, a smooth Weierstrass cubic as an elliptic-period test case, and a conditional positive-genus construction illustrating algebraic transforms beyond quadrature domains.

In this paper we present a sharp mixed inequality relating successive minima and quotient covering radii of origin-symmetric convex bodies with respect to lattices. The inequality interpolates between the (classical) covering-density lower bound and the lower bound in Minkowski's second theorem.

Accumulating evidence suggests that large-scale brain activity exhibits scale-invariant dynamics consistent with operation in a near-critical regime. Such dynamics have been associated with long-range correlations, efficient information processing, and the emergence of collective organization. While altered criticality-related measures have been reported in psychiatric disorders, previous findings remain fragmented across observables and modalities, making it unclear whether different scaling measures capture a common alteration of large-scale brain dynamics. Here, we investigated scaling properties in resting-state fMRI data from individuals with early psychosis and healthy controls. We combined a phenomenological renormalization group (PRG) framework with power spectral density (PSD) and detrended fluctuation analysis (DFA) to characterize collective dynamics across scales. In healthy controls, resting-state activity exhibited non-trivial scaling behavior consistent with critical-like organization. Early psychosis participants showed the same overall phenomenology of scale-invariant organization, but with systematic shifts in scaling exponents across multiple observables. These findings indicate that early psychosis is not characterized by a simple loss of critical-like dynamics, but rather by a reorganization of collective dynamics within a preserved scaling regime. More broadly, our results suggest that combining coarse-graining approaches with temporal scaling analyses provides a principled framework for studying large-scale brain dynamics in psychiatric disorders.

Moiré superlattices formed at the interfaces of mismatched lattices have attracted significant interest over the past decade due to their large tunability of band parameters and interactions among electrons, spins, and lattices. Superlattices made from twisted perovskite oxides may have strong structure and potential modulation, but evidence of such modulation over macroscopic areas, particularly at large twisting angles, has not been clearly demonstrated so far. Here, we fabricated millimeter-scale twisted oxide bilayers at $36^\circ$ angle, close to the simple coincidence site lattice condition $\Sigma5$, from freestanding SrTiO$_3$ membranes. We discovered new low-frequency vibrational modes whose Raman activity, according to molecular dynamics simulations, is greatly enhanced by an asymmetric, twisted interface between the SrO and TiO$_2$ layers. Such an interface is energetically favorable from first-principles calculations and is corroborated by the observation of strong second harmonic generation from the interface comparable to that from the SrTiO$_3$ surface throughout the bilayer region. The results are consistent with interlayer coupling enhanced by high-temperature annealing and confirmed by cross-sectional scanning transmission electron microscopy imaging. Our work sheds light on the structural behavior of twisted oxides and provides directions for tuning their phononic and nonlinear optical properties in future studies.

We derive dissipative relativistic hydrodynamic equations in the presence of multiple conserved charges, i.e., baryon number ($B$), electric charge ($Q$), and strangeness ($S$), using the Chapman-Enskog (CE) method within the kinetic theory approach. The relativistic Boltzmann equation is solved within the relaxation-time approximation with a momentum-independent relaxation time in the collision term. We derive both first-order (Navier-Stokes limit) and second-order dissipative hydrodynamic equations. Within the kinetic theory framework, using the Boltzmann's H-theorem, and by demanding that for a dissipative system, the entropy must be produced, we find different transport coefficients at the first-order and second-order gradient expansion of the out-of-equilibrium distribution function around the local equilibrium. Apart from the well-known transport coefficients, the shear ($η$) and the bulk ($ζ$) viscosities , we also find the diffusion matrix elements ($κ_{qq^{\prime}}$) for the conserved charges $B$, $Q$ and $S$. The diffusion matrix elements ($κ_{qq^{\prime}}$) are important to model the multi-component diffusion dynamics sourced by inhomogeneous baryon stopping in the initial state of heavy-ion collisions. We estimate the temperature ($T$) and chemical potential dependence of diagonal and off-diagonal elements of the diffusion matrix elements for the (2+1) flavor quark-gluon plasma. We further estimate the ratio $κ_{qq^{\prime}}T/η$ for a wide range of temperature and chemical potentials to show the relative importance of the diffusion matrix elements compared to other transport coefficients.

Cosmological correlators receive contributions from both field interactions in the bulk of quasi-de Sitter (dS) spacetime and boundary terms at the end of inflation. While most of the research efforts focus on the former, boundary contributions are normally believed to be negligible or related to field redefinitions that are associated with redundancies of the bulk Lagrangian. In this paper, we revisit this topic in the light of the cosmological bootstrap. We first establish the correspondence between boundary terms and field redefinitions for cosmological correlators. This result provides a set of criteria for determining when boundary terms lead to non-vanishing contributions to cosmological observables. Next, we apply this general understanding to concrete examples of correlators from massive-exchange diagrams, in both dS-invariant and boost-breaking scenarios. For theories with dS isometries, both IBP and field redefinitions are used to relate derivative and non-derivative exchange diagrams, from which the leading boundary contributions and IR-divergent pieces are extracted; we also derive recursion relations among higher-derivative exchange correlators. For theories with broken dS boosts, we use IBP and EoM to reduce exchange diagrams to a basis of independent templates, and then present a classification of the boundary contributions in the general effective field theory framework. These results pave the way for a more systematic investigation on the boundary physics of the inflationary spacetime.

In this paper, we investigate the problem of finding a zero of the sum of a maximal monotone operator $A$ and a cocoercive operator $\Bm$ in a Hilbert space. This formulation naturally captures stochastic optimization problems with decision-dependent distributions, often referred to as performative prediction. We propose and analyze continuous-time second-order dynamics governed by a distributionally evaluated forward-backward splitting operator. We establish the existence and uniqueness of the equilibrium point under a general uniform monotonicity assumption. In this setting, employing a vanishing viscous damping coefficient, we prove the strong convergence of the trajectories to the equilibrium, accompanied by fast asymptotic convergence rates for the velocities. Furthermore, when the regularizing operator is strongly monotone, we consider a constant Polyak-type damping coefficient and we establish global exponential convergence rates for the dynamical system.

Hidden order typically manifests as a thermodynamic phase transition without a conventional order parameter, leaving its true nature concealed even at the lowest temperatures. In the frustrated Shastry-Sutherland magnet Nd$_2$Be$_2$GeO$_7$, we observe a related yet fundamentally distinct phenomenon. A sharp specific-heat anomaly appears at 250 mK, but zero-field neutron diffraction and muon spin relaxation detect no static magnetism down to 100 and 30 mK, respectively, pointing to a hidden-order state. Remarkably, this hidden order does not emerge under an applied magnetic field, but instead reveals itself only after the field is applied and subsequently removed where magnetic Bragg peaks appear, albeit with strongly suppressed moments. A glassy state is ruled out by ac susceptibility and specific heat measurements. Complementary $μ$SR measurements reveal coherent spin fluctuations at a rate on the order of gigahertz. Taken together, these results suggest that the system lies in close proximity to the quantum spin liquid and long-range magnetic order state such that a small perturbation can effectively drive the system towards distinct ground states. These findings also distinguish Nd$_2$Be$_2$GeO$_7$ from known frustrated systems, establishing it as a unique platform where the synergistic interplay among the spin-orbit coupling, crystal field, and magnetic frustration leads to unexpected quantum states.

This note contains the perturbative computation of the 2D non-linear sigma model (NLSM) energy-density in a chemical potential $h$, at the fourth order in the coupling constant expansion. The result is in fully agreement with the $h\rightarrow \infty$ asymptotics extracted from the thermodynamical Bethe ansatz (TBA).

We construct a two sided categorical action of the Hall algebra of semistable coherent sheaves of fixed slope on a curve X on the derived category of certain Quot spaces in tilted hearts on X. Following the philosophy in arXiv:2207.08926v2, the action is induced by correspondence stacks that parameterize extensions of such quotients by semistable sheaves. In the process, we compare different moduli spaces on X: Quot spaces, Bradlow pairs, and stable pairs in the sense of arXiv:2207.08926v2.

Student engagement is critical for effective learning in software modelling, yet fostering motivation and inclusivity remains a challenge. While existing research has focused on modelling tools, notations, and assessment, little attention has been given to how the choice of problem domains and the diversity, relatability, and cultural perspectives they bring shape students' learning experiences. This study explores how problem domains and teaching methods influence motivation, engagement, inclusiveness, and feedback in modelling education. To investigate these dimensions, we conducted parallel surveys with 90 students and 22 educators. Our findings reveal disconnects between educator assumptions and student preferences: Students show greatest motivation for socially relevant domains and prefer choice in selection, while educators overestimate interest in study-related domains. The study identifies how minor design choices can exclude students. Students perceive feedback as meaningful when visibly acted upon. These findings suggest inclusive domain selection is central to student motivation; thus, we recommend student-centred domain selection.

We prove the existence of the C-type renormalisation two-cycle, helping to establish the universality of the C-type route to chaos in families of non-invertible maps of the plane. Families of two-dimensional non-invertible maps, with at least two parameters and critical points of fold type, exhibit a distinct type of critical scaling, the C-type. An accumulation of parameter values leads to an infinite collection of coexisting attracting cycles of periods $4^n$ or $2\cdot 4^n$. Asymptotically, period quadrupling is accompanied by parameter-space scaling and state-space scaling governed by particular universal constants. Kuznetsov et. al. explained this phenomenon in terms of a stationary orbit of period two of the renormalisation group (RG) transformation for period-doubling. We prove the existence of the corresponding renormalisation two-cycle in a Banach space of analytic maps and gain rigorous bounds on the corresponding universal state space scaling constants. This result provides a further step in proving a series of outstanding conjectures concerning distinct universality classes for period-doubling. It extends the recent results for unidirectionally-coupled maps (the FS-type) to bidirectionally-coupled maps, and generalises the framework from fixed points to periodic orbits of the corresponding renormalisation operators. It also provides a further step in establishing the conjectured picture that the C-type universality class is born from the FS-type class via a period-doubling bifurcation in the dynamics of the RG transformation itself. The proof relies on rigorous computations to establish that a variant of Newton's method for the two-cycle is a contraction map. The C-type scaling regularity is known to occur in a number of dynamical systems of interest, perhaps most notably in biologically-plausible models of nephron blood pressure autoregulation.

In Petitjean (2026, arXiv:2605.12188)), we revisited the origin of proximate damped Lyman-alpha absorbers (PDLAs), which trace cold gas within 3000 km/s of the quasar redshift, and interpreted their kinematics and physical properties within a unified framework. We showed that most PDLAs are associated with the environment of the AGN and/or the quasar host galaxy. We also provided the first census and characterization of absorption systems exhibiting strong absorption from excited levels of atomic ground states among quasar-associated absorbers. Among these, ghostly and coronagraphic systems arise in dense, compact gas that partially covers the quasar emission regions. Most systems are associated with outflows reaching velocities up to -2000 km/s, while a smaller fraction of inflowing clouds extends to velocities of up to +1200 km/s. In the present work, we provide an updated classification of PDLAs, including a revised catalogue of ghostly systems that more than doubles the number of previously known detections. We investigate the properties of these systems by measuring and discussing the equivalent widths of the detected absorption lines in both stacked spectra and individual ghostly systems. In particular, we show that although most ghostly systems are bona fide DLAs, this is not always the case.

Physics-informed neural networks (PINNs) have been widely applied to solve Navier-Stokes equations by enforcing outputs and gradients of deep models to satisfy target equations. However, conventional PINNs only constrain the boundary terms by means of the $L^2$-norm when addressing the equations with non-homogeneous boundary conditions. This single constraint strategy may cause inaccurate boundary simulation, further resulting in the decline of prediction accuracy. To resolve this critical issue, this paper proposes an improved physics-informed neural network by correcting the error of the boundary value, which is called Tr-PINNs. Based on the results of nonhomogeneous Stokes problem, the algorithm error analysis of Tr-PINNs is established. The efficacy of the Tr-PINNs algorithm is demonstrated via numerical experiments, which further demonstrate that the Tr-PINNs algorithm achieves a remarkable improvement in computational accuracy.

Evasion attacks present a significant challenge to the robustness of machine learning (ML)-based classifiers, particularly in critical applications such as fraud detection and cybersecurity. Although existing defense mechanisms are effective in some settings, they often suffer from limited generalizability and do not systematically improve model robustness across diverse attack scenarios. To address these limitations, we introduce Robust Ensemble of Selectively Strengthened and Augmented Predictors (RESSAP), a novel framework that transforms a single classifier into an ensemble of robust classifiers. Each classifier in the ensemble is trained on a carefully selected subset of features, where feature selection is guided by a resilience metric that accounts for both feature importance and robustness. During inference, a random subset of these classifiers is used to make predictions, increasing unpredictability and improving resistance to adversarial manipulation. In addition, noise-based data augmentation is applied during training to strengthen decision boundaries and improve generalization. Our experimental results demonstrate that RESSAP significantly improves robustness against adversarial evasion attacks while maintaining strong accuracy on clean data. Overall, this model-agnostic framework provides a scalable and flexible defense strategy for enhancing the security of machine learning systems without requiring major changes to existing architectures.

This addendum extends the spectral lower bounds established in the original paper to the Neumann problem. Under the formal positivity assumption on the elliptic tuple, we prove that the same bounds hold for Neumann boundary conditions as for the Dirichlet case.

The spin-orbit correlation (SOC) provides a unique probe into the internal spin structure of hadrons. Defined via the parity-odd (P-odd) energy-momentum tensor (EMT), this observable can remain non-vanishing even in systems where the total angular momentum is zero. In this study, we connect the formal field-theoretical definition of the SOC to a non-perturbative quantum many-body framework utilizing light-front dynamics. Furthermore, we show how the SOC can be extracted directly from the hadronic matrix elements of the P-odd EMT, establishing a pathway to access this observable within the partonic picture. As a practical application, we compute the transverse and longitudinal SOC distributions for charmonium and $B_c$ mesons. While our findings align with rough estimates based on the Clebsch-Gordan decomposition, we demonstrate that these observables yield rich, non-trivial information regarding partonic dynamics.

Climate change and extreme weather are increasing the vulnerability of power systems globally, particularly in emerging economies such as Indonesia. Yet, existing studies often assess these impacts in isolation, focusing on individual components or specific hazards, leaving system-level implications under-examined. To address this gap, we develop an integrated, spatially explicit approach to assess an energy system's climate-related vulnerabilities and their impacts, and apply the approach to Indonesia. We quantify climate-based vulnerabilities in generation and transmission infrastructure as well as in demand by distinguishing stressors (temperature rise) and shocks (disruptive hazards due to sea-level rise, flooding, and landslides). Through geospatial data analysis, derating models, and regression analysis, we examine existing and planned assets and demand under historical and future climate conditions. Results indicate that both existing and planned generation are likely to experience stress, which implies a reduction in usable capacity, even as electricity demand increases due to temperature rise, and transmission assets face potential disruption from climate change-induced shocks. Together, these effects erode reserve margins by up to 36 percentage points under the 10-year plan, indicating a substantial reduction in system resilience. The largest system, Jawa-Madura-Bali, experiences a 20.8 percentage point decline, leaving a remaining margin of 26.5%, below the 10-year planning threshold. Importantly, the findings suggest that a growing share of future capacity expansion may be absorbed by climate-induced losses, implying that adaptation-related investments may increasingly be required simply to maintain existing supply levels rather than meet future requirements. We conclude that there is an urgent need to embed climate considerations more explicitly into power sector planning.

Standard objective collapse models offer a unified approach to the quantum measurement problem but predict an unphysical, indefinite increase in the energy of the system. The dissipative Diósi-Penrose (dDP) model resolves this heating issue by introducing a linear friction mechanism. However, this modification induces complex, non-Gaussian phase-space dynamics. We rigorously establish the thermodynamic consistency of this friction mechanism -- extended to the CSL model -- across both weakly and strongly non-Gaussian regimes. Using the Wigner phase-space formalism, we go significantly beyond the quadratic approximation and, to bypass the failure of perturbative methods under strong dissipation, introduce a novel exact pseudo-spectral simulation approach. Our analysis reveals that the system subjected to the dDP mechanism does not thermalize, but rather settles into a non-equilibrium steady-state (NESS) where the asymptotic non-Gaussianity scales as the third power of the dissipation parameter $β$. By evaluating the Wigner entropy production, we confirm the thermodynamic validity of the model and demonstrate that highly sensitive information-theoretic quantities require exact numerical methods to accurately capture the key non-Gaussian tails of the distribution.

Fluid pressurization can reactivate subcritically stressed granular layers in faults, slopes, and injection-perturbed reservoirs, but grain-scale feedbacks among pressure diffusion, drainage, and contact-network degradation remain unresolved. Here, 3D coupled CFD-DEM simulations investigate pore-pressure-induced reactivation of confined, fluid-saturated granular shear layers under imposed shear stress. Strain-controlled tests define the Mohr-Coulomb strength envelope; stress-controlled simulations then impose subcritical shear stresses while basal pore pressure increases under drained and undrained conditions. Instability is governed not by pore pressure alone, but by its coupled evolution with effective stress, drainage, dilation or compaction, hydraulic connectivity, and granular fabric. Undrained boundaries retain excess pore pressure, whereas drained boundaries maintain vertical gradients and suppress excess pressure. Internal fields reveal alternating dilation and compaction bands and reorganization of a porosity-derived permeability proxy, showing that hydraulic pathways evolve during deformation. Micromechanical diagnostics identify localized particle rotation, force-chain reorganization, porosity redistribution, and coordination-number variations controlled mainly by imposed shear-stress level rather than drainage. Second-order fabric metrics show that post-failure weakening coincides with loss of directional force-chain organization, especially at lower shear. Friction-velocity and friction-porosity trajectories indicate a transition from dilatancy-dominated strengthening to pore-pressure-driven weakening. Viscous-number scaling partially organizes the low-Iv creeping response, 10^-8 <= Iv <= 10^-5, but not onto a unique local rheology. These results clarify how drainage-controlled hydromechanical feedbacks and fabric degradation convert pore-pressure forcing into instability.

Large code language models (CodeLLMs) can generate and rewrite programs, enabling functionality-preserving code mutation that may be used to create diverse malware variants and evade signature-based detection. A key security question is whether this mutation capability survives model compression, which would make deployment feasible under limited hardware budgets. We propose SecRL-Prune, a structured pruning framework for CodeLLMs that operates on feed-forward (MLP/FFN) channels. Starting from a pretrained teacher, it learns a layer-wise pruning policy with reinforcement learning using a teacher-student KL-divergence reward. To improve efficiency, we cache the teacher's top-P predictions once and compare the pruned student against this compact target, avoiding simultaneous teacher-student residency in GPU memory. We evaluate SecRL-Prune on HumanEval using pass@k for execution correctness and var@k for code diversity across three 7B CodeLLMs at 10-30% compression. SecRL-Prune consistently preserves higher pass@k and var@k than recent structured pruning baselines under aggressive pruning. In a case study on real malware samples, semantics-preserving mutations from 20%-pruned models substantially reduced detections. These results show that code mutation capability can survive significant structured pruning, highlighting the security relevance of compressed CodeLLMs.

We present a systematic study of how the Galactic bar affects the orientation of tidal tails of open clusters and assess the power of tail morphology to constrain the bar's pattern speed. Using test-particle simulations, we follow the evolution of $\sim 1450$ observed open clusters from the Hunt & Reffert (2024) catalogue in an axisymmetric reference potential and in eight barred potentials with pattern speeds ranging from $Ω_b = 20$ km/s/kpc to $Ω_b = 55$ km/s/kpc. We quantify the bar effect through the deflection angle -- the rotation of the tail orientation in the barred model relative to the axisymmetric case. The deflection angle varies systematically with bar pattern speed and cluster guiding radius. The largest deflections occur for clusters near the outer Lindblad resonance (OLR), with the sign of the angle set by the orientation of the orbit's pericentre relative to the bar's major axis. For each cluster we measure the distance from the centre beyond which different bar models produce distinguishable tail orientations, and classify each cluster as bar-sensitive or bar-insensitive based on its maximum absolute deflection across the bar models. Comparing with observed tidal tails from the literature, we find that the extended tails of NGC 2632 and the Hyades disfavour moderate pattern speeds. We provide a catalogue of deflection angles, minimal tail extents, and bar-sensitivity flags to guide future observational searches and the re-assessment of existing tidal tail catalogues.

In this paper, a high-order Fourier Continuation (FC) algorithm is introduced into the spectral smoothed particle hydrodynamics (SPH) scheme to simulate the wall-bounded incompressible flows. This work aims to extend the spectral ISPH scheme towards the high-order simulation of flows with non-periodic wall boundary conditions. Herein, a polynomial-based Fourier continuation technique is applied to the velocity and pressure to make the domain both periodic and Cp smooth. The spatial SPH discretisation is performed subsequently in the frequency space on the FC-extended domain by building upon the convolution theorem using fast Fourier transform (FFT). The incorporation of Neumann boundary conditions is straightforward, and more generally, the FC method enforces periodicity across the domain regardless of the boundary condition type. The convergence order, additional computational cost, and implementation technique of the FC method are also discussed. Combined with a projection-based time integration scheme and a spectral PPE solver, the FC-based spectral ISPH framework is validated against several classical CFD benchmarks. The principal finding of this work is that the incorporation of FC techniques enables the spectral ISPH scheme to simulate wall-bounded flows with high-order convergence, and accurately capturing complex vortex dynamics. This work therefore represents a step towards a fully high-order spectral Lagrangian SPH solver with complex geometries