Let $\{X_α\}$ be a family of random variables satisfying some distribution with a parameter $α$, $E(X_α)$ be the expectation, and $Var(X_α)$ be the variance. In this paper, we study the infimum values of three probability functions: $P(X_α\leq y E(X_α))$, $P\left(|X_α-E(X_α)|\leq y\sqrt{Var(X_α)}\right)$ and $P\left(|X_α-E(X_α)|\geq y\sqrt{Var(X_α)}\right), \forall y>0$, with respect to the parameter $α$ for the Laplace distribution and the student's $t$ distribution. Our motivation comes from three former conjectures: Chvátal's conjecture, Tomaszewski's conjecture and Hitczenko-Kwapień's conjecture.

Ion implantation is a powerful approach for tuning the electrical properties of materials through controlled doping and defect engineering, with applications in thermoelectrics and microelectronics. Scandium nitride (ScN) is particularly sensitive to irradiation-induced disorder, with transport properties spanning several orders of magnitude and multiple conduction mechanisms involved. In this study, we investigate the evolution of electrical transport in epitaxial ScN thin films undergoing accumulated irradiation damage at an initial defect state. A phenomenological damage-accumulation model was successfully combined with temperature dependent resistivity and Hall effect measurements to elucidate the impact of defect buildup on electrical transport and to provide physically grounded, quantitative insight into the nature and accumulation of irradiation-induced defects. It reveals two distinct defects-generation regimes of electrically active defects. At low doses, direct-impact damage produces stable and isolated acceptor-type complex defects, (VSc-X) with VSc a scandium vacancy and X denoting residual impurities, leading to a gradual increase in resistivity. At higher doses, defect accumulation dominates through a multi-hit process, giving rise to point-defect buildup and carrier localization, resulting in hopping-dominated transport. This localized regime is thermally unstable and recovers upon low-temperature annealing. We further demonstrate that the residual defect landscape strongly influences both the critical dose for the metal-insulator transition and the localization strength: films grown on Al2O3 exhibit an earlier transition and weaker localization than those grown on MgO. These results highlight ion implantation as an effective route for engineering disorder-induced localization in ScN, with the initial film quality playing a decisive role.

In this work, we analyze a multi-functional reconfigurable intelligent surface (MF-RIS)-enabled radar and communication coexistence (RCC) system, detailing the key aspects of its phase synthesis codebook generation and the implemented localization algorithm for real-time user tracking based on density-based spatial clustering of applications with noise (DBSCAN), which features a Kalman filter for the prediction of user mobility. We derived a 3GPP-compatible radar cross-section (RCS) and re-radiation pattern-based channel model for the described MF-RIS system, supplementing it with channel measurements. We obtained large and small-scale characteristics, including path loss, shadow fading, Rician K-factor, cluster powers, and RMS delay spread. The study finds that Sub-6 GHz indoor propagation is largely free of blind spots, even with a blocked line-of-sight (LoS) path. Therefore, the proposed channel model includes non-line-of-sight (NLoS) paths, including the ones created by the MF-RIS. We also performed an experimental evaluation of the channel throughput in a fifth generation (5G) new radio (NR) single user multiple-input-multiple-output (SU-MIMO) system, reporting a 74\% reduction in throughput variance and a 12.5\% sum-rate improvement within the MF-RIS near-field compared to the no-RIS setup. This result shows that the MF-RIS can minimize delay spread and increase the coherence bandwidth by creating virtual-LoS (vLoS) path for the moving user, thereby effectively hardening wireless MIMO channels.

The electrostatic interactions of phosphate groups and counter ions critically affect the structure, function and reactivity of DNA or RNA. We present a joint experimental-theoretical investigation of dimethyl phosphate (DMP-) in aqueous solution, an established model system of the sugar-phosphate backbone. Utilizing 31P-NMR spectroscopy as probe of phosphate-ion association, variations of Mg2+ and Ca2+ content exhibit a systematic shielding of the 31P chemical shift (δiso(31P)) with moderate temperature dependence. Enhanced sampling molecular dynamics (MD) and ab initio (GIAO-DF-LMP2) level of theory are used to reveal the microscopic mechanism. Simulations are performed for a configurational ensemble of DMP-ion geometries and their first solvation shells, demonstrating (i) the spatial convergence of changes of the nuclear shielding constant σiso(31P), (ii) the intramolecular geometric origin of short-timescale σiso(31P) fluctuations and (iii) an average shift of σiso(31P) of about 3-5 ppm upon contact ion pair formation with Mg2+ or Ca2+ ions. A quantitative analysis of δiso(31P) for varying ion content and temperature allows us to extract the temperature-dependent fraction of the contact ion pair species, indicating that solvent separated or free ion pairs are the energetically preferred species. The results impose boundary conditions for improvements of phosphate ion force fields and establish the interactions underlying the changes of δiso(31P).

In 1998, Benyamini introduced and proved the existence of universal interpolating functions. In the note we prove that the set of universal interpolating functions is nowhere dense in the space of continuous functions on $\mathbb{R}$. Several extensions and generalisations are also considered.

Recent progress in ML and LLMs has improved vulnerability detection, and recent datasets have reduced label noise and unrelated code changes. However, most existing approaches still operate at the function level, where models are asked to predict whether a single function is vulnerable without inter-procedural context. In practice, vulnerability presence and root cause often depend on contextual information. Naively appending such context is not a reliable solution: real-world context is long, redundant, and noisy, and we find that unstructured context frequently degrades the performance of strong fine-tuned code models. We present CPRVul, a context-aware vulnerability detection framework that couples Context Profiling and Selection with Structured Reasoning. CPRVul constructs a code property graph, and extracts candidate context. It then uses an LLM to generate security-focused profiles and assign relevance scores, selecting only high-impact contextual elements that fit within the model's context window. In the second phase, CPRVul integrates the target function, the selected context, and auxiliary vulnerability metadata to generate reasoning traces, which are used to fine-tune LLMs for reasoning-based vulnerability detection. We evaluate CPRVul on three high-quality vulnerability datasets: PrimeVul, TitanVul, and CleanVul. Across all datasets, CPRVul consistently outperforms function-only baselines, achieving accuracies ranging from 64.94% to 73.76%, compared to 56.65% to 63.68% for UniXcoder. Specifically, on the challenging PrimeVul benchmark, CPRVul achieves 67.78% accuracy, outperforming prior state-of-the-art approaches, improving accuracy from 55.17% to 67.78% (22.9% improvement). Our ablations further show that neither raw context nor processed context alone benefits strong code models; gains emerge only when processed context is paired with structured reasoning.

For a hypergraph $\mathcal{H}$, the DP color function $P_{DP}(\mathcal{H},k)$ of $\mathcal{H}$ is an extension of the chromatic polynomial $P(\mathcal{H},k)$ with the property that $P_{DP}(\mathcal{H},k) \le P(\mathcal{H},k)$ for all positive integers $k$. In this article, we primarily investigate the influence of the minimum cycle length on the DP-coloring function, as well as the relevant properties of the DP-coloring function of $\mathcal{H} \vee K_p$ (i.e., the join of $\mathcal{H}$ and $K_p$). We show that for any linear and uniform hypergraph $\mathcal H$ with even girth, there exists a positive integer $N$ such that $P_{DP} (\mathcal H, k) < P(\mathcal H, k)$ for all integers $k\ge N$, and this conclusion also holds for any hypergraph $\mathcal{H}$ that contains an edge $e$ with the properties that $\mathcal{H}-e$ has exactly $|e|-1$ components and any shortest cycle in $\mathcal{H}$ containing $e$ is an even cycle. For the hypergraph $\mathcal{H}\vee K_p$, we prove that if $\mathcal{H}$ is uniform, then there exist positive integers $p$ and $N$ such that $P_{DP}(\mathcal{H} \vee K_p,k)=P(\mathcal{H} \vee K_p,k)$ holds for all integers $k\geq N$.

In cavity quantum electrodynamics (QED), photons leaving the cavity can be irreversibly lost or reused as a power source. This dichotomy is reflected in two different thermodynamic bookkeepings of the light field, both corresponding to valid thermodynamic frameworks. In this work, we formulate a rigorous semi-classical limit of cavity QED and show that the resulting thermodynamic description may qualitatively differ from that of the fully quantised model. We find that violations of the thermodynamic uncertainty relations are recovered in the semi-classical limit only by one of the two thermodynamic frameworks: the one which treats part of the photon flux as a power source. We illustrate our findings in a three-level system coupled to a driven cavity.

Structural bias (SB) refers to systematic preferences of an optimisation algorithm for particular regions of the search space that arise independently of the objective function. While SB has been studied extensively in single-objective optimisation, its role in multi-objective optimisation remains largely unexplored. This is problematic, as dominance relations, diversity preservation and Pareto-based selection mechanisms may introduce or amplify structural effects. In this paper, we extend the concept of structural bias to the multi-objective setting and propose a methodology to study it in isolation from fitness-driven guidance. We introduce a suite of synthetic multi-objective test problems with analytically controlled Pareto fronts and deliberately uninformative objective values. These problems are designed to decouple algorithmic behaviour from problem structure, allowing bias induced purely by algorithmic operators and design choices to be observed. The test suite covers a range of Pareto front shapes, densities and noise levels, enabling systematic analysis of different manifestations of structural bias. We discuss methodological challenges specific to the multi-objective case and outline how existing SB detection approaches can be adapted. This work provides a first step towards behaviour-based benchmarking of multi-objective optimisers, complementing performance-based evaluation and informing more robust algorithm design.

In recent years, hybrid organic-inorganic metal halides have been at the forefront of materials research. Typically, the functional (e.g., optoelectronic) properties of hybrid halides are derived from the inorganic structural part, whereas the organic structural units can add extra advantages in terms of stability, rigidity, and processability. Here, we report the design, synthesis, and characterization of two new hybrid materials in which the outstanding photophysical properties originate from the organic structural part. The new compounds, (C15H16N)2CdCl4 and ((Br)C15H15N)2CdCl4, have 2D layered Ruddlesden-Poppertype perovskite structures. These hybrids are blue-white light emitters just like their corresponding pure organic salts, but with much improved emission efficiencies. Optical spectroscopy and density functional theory (DFT) studies confirm that photoemission comes from the trans-stilbene organic cations. The photoluminescence quantum yield (PLQY) values of these new materials are among the highest known, 50.83 % and 26.60 % for (C15H16N)2CdCl4 and ((Br)C15H15N)2CdCl4, respectively. This is up to a 5-fold increase as compared to the light emission efficiency of the precursor salt C15H16NCl (PLQY of 10.33 %). Alongside their outstanding optical properties, their environmental and thermal stability allow their consideration for potential practical applications such as radiation detection. This work shows that hybrid metal halides can be compositionally and structurally engineered to have highly efficient photoemission originating from the organic components for fast scintillation applications.

Photoemission spectroscopy is a powerful technique for studying electronic structure and spin-state transitions, as it reveals changes in the orbital configuration accompanying a spin-state crossover. In this report, we combine excitation-energy-, temperature-, and geometry-dependent photoemission measurements to probe the electronic structure of LaCoO3 across its thermally driven spin-state transition. By systematically comparing valence-band spectra across a wide photon-energy window - from surface-sensitive soft x-ray photoemission spectroscopy (SXPS) to bulk-sensitive hard x-ray photoemission spectroscopy (HAXPES) - we identify the Co 3d-derived feature (A) along with the O 2p-dominated features (B and C), and explain their relative evolution in terms of photon-energy-dependent photo-ionization cross-section ratios. The thermally induced spin-state crossover is demonstrated using temperature-dependent SXPS valence-band spectra, which show a progressive suppression of the feature A with heating. Geometry-dependent HAXPES measurements further clarify how the signature of the spin-state transition in LaCoO3 is intricately linked to the orbital-selective response of the t2g and eg states. Additionally, angular-dependent photo-ionization cross-section analysis provides a consistent description of the polarization dependence observed in HAXPES. Finally, configuration-interaction analysis of the Co 2p core-level spectra reveals that LaCoO3 evolves from a predominantly low-spin ground state at low temperature to a mixed low-spin/high-spin configuration at elevated temperatures, with the high-spin fraction reaching about 30 percent at 400 K. The temperature evolution of the core-level line shape thus establishes Co 2p photoemission as a sensitive quantitative probe of spin-state transitions in LaCoO3.

A large proportion of observed white dwarfs (WDs) show evidence of debris disks, remnants of the former planetary systems, and/or signatures of heavy elements in their atmospheres, induced by the accretion of planetary matter onto their surfaces. The observed abundances are the result of the balance between the accretion flux and the dilution of this planetary material by internal transport processes. A recent study showed that more massive DA WDs are less polluted than smaller mass ones. It was suggested that the reason could be related to the formation of planetary systems when these stars were on the main sequence. The aim of this work is to test how internal dilution processes, including thermohaline convection, change with WD masses, and whether such an effect could account for variations in the observed pollution. We computed the efficiency of atomic diffusion and thermohaline convection after the accretion of heavy elements onto WDs using static DA models with various masses, effective temperatures, and hydrogen contents. We confirm that thermohaline convection is always more efficient in diluting accreted elements than atomic diffusion, as previously shown in the literature. However, we find that element dilution by thermohaline convection is less efficient in massive WDs than in smaller mass ones, due to their larger internal density. We showed that the differences in observed heavy element pollution in WDs according to their masses cannot be explained by the dilution induced by atomic diffusion and thermohaline mixing alone. Indeed, the pollution by planetary system accretion should be more easily detectable in massive WDs than in low-mass ones. We discuss other processes that should be taken into account before drawing any conclusion about the occurrences of planetary systems according to the mass of the star on the main sequence.

Semisimple Dubrovin-Frobenius manifolds can be used to construct integrable hierarchies, following the work of Dubrovin-Zhang and Buryak. Examples of such hierarchies include the Kac-Wakimoto hierarchies, the KP hierarchy, among others. In all these examples, the Saito theory of isolated singularities played a crucial role. In this note, we show that the BKP and CKP hierarchies can likewise be constructed from Dubrovin-Frobenius manifolds. This new construction, however, utilizes the orbifold version of Saito theory for isolated singularities endowed with a symmetry group.

Visualizations have become an indispensable part of the scientific process. A vibrant ecosystem of visualization tools exists, catering to a wide variety of different needs. Real-time visualizations of numerical simulations offer scientists immediate feedback about the status of their simulations and can also be valuable educational and outreach tools. Developing a visualization tool with support for different operating systems, CPU/GPU architectures, and programming languages can be a challenge. It is common to use one or more graphics or UI libraries to act as abstraction layers and hide the underlying complexity. Whereas external libraries greatly simplify the initial programming effort, we argue that relying on them introduces new dependencies and problems, such as a higher entry barriers for new developers and users, and uncertainty regarding long-term support. In this paper we present a new approach for real time visualizations which we have implemented for the N-body package REBOUND. We propose to use a web browser to handle GPU accelerated rendering. This enables us to offer 3D, interactive visualizations on all major operating systems. What makes our new approach unique is that we achieve this without the need for any external libraries. We utilize WebAssembly to reuse existing OpenGL visualization code. Using communication via HTTP and a custom built-in web server, we are able to provide both local and remote real time visualizations. In addition to the browser based real time visualization, our approach offers other additional operating modes, including simulations running entirely within the browser, visualizations within jupyter notebooks, and traditional standalone visualizations using OpenGL. We focus on the implementation in REBOUND but the concepts and ideas discussed can be applied to many other areas in need of scientific and non-scientific real time visualizations.

Generative AI is reshaping education, but it also raises concerns about instability and overreliance. In programming classrooms, we aim to leverage its feedback capabilities while reinforcing the educator's role in guiding student-AI interactions. We developed ClassAid, a real-time orchestration system that integrates TA Agents to provide personalized support and an AI-driven dashboard that visualizes student-AI interactions, enabling instructors to dynamically adjust TA Agent modes. Instructors can configure the Agent to provide technical feedback (direct coding solutions), heuristic feedback (hint-based guidance), automatic feedback (autonomously selecting technical or heuristic support), or silent operation (no AI support). We evaluated ClassAid through three aspects: (1) the TA Agents' performance, (2) feedback from 54 students and one instructor during a classroom deployment, and (3) interviews with eight educators. Results demonstrate that dynamic instructor control over AI supports effective real-time personalized feedback and provides design implications for integrating AI into authentic educational settings.

Acousto-optic modulation in photonic integrated circuits harness the applications that include signal processing, quantum photonics and microwave photonics. However, silicon nitride ($\rm{Si_3N_4}$), as a main-stream low-loss scalable photonic platform, suffers from the lack of piezoelectric effect and therefore the hybrid co-integration with other materials is always required for acousto-optic modulation. Here, we employed thermoelastic surface acoustic waves (SAW) in a 8 dB/m propagation loss $\rm{Si_3N_4}$ integrated circuits without adding extra materials. A phase modulation efficiency enhancement of 13.6 dB is realized with a multi-pass configuration. Furthermore, a single-sideband intermodal scattering with a suppression ratio of 8 dB is measured and an intensity modulation is observed by incorporating the phase modulation into a ring resonator spectral. This thermoelastic SAW technique, as an initial step of acousto-optic modulation in low-loss $\rm{Si_3N_4}$ platform, is promising for integrated microwave photonics and programmable photonics applications.

Tilt-to-length (TTL) noise induced by angular jitter of spacecraft and test masses can affect the sensitivity of space-based gravitational-wave detectors such as LISA, Taiji, and TianQin. Such angular jitter can be measured using the differential wavefront sensing technique, enabling the modeling and subtraction of TTL noise from the data. However, owing to the multiple degrees of freedom of the detector constellation, a linear TTL model requires at least 24 parameters, while a higher-fidelity quadratic model involves up to 60 coefficients, rendering parameter estimation computationally expensive. To accelerate parameter determination, we propose a modified parameter set obtained via a linear transformation of the original angular coupling coefficients, which effectively reduces correlations among TTL noise components. In addition, we perform parameter fitting using an alternative second-generation time-delay interferometry configuration, PD4L, rather than the fiducial Michelson configuration. These two improvements enhance the convergence speed of the fitting procedure by a factor of approximately 10 for the linear model and approximately 18 for the quadratic model. The proposed approach can therefore substantially improve the efficiency of TTL noise calibration in space-based gravitational-wave detectors.

Performativity means that the deployment of a predictive model incentivizes agents to strategically adapt their behavior, thereby inducing a model-dependent distribution shift. Practitioners often repeatedly retrain the model on data samples to adapt to evolving distributions. In this paper, we develop a Wasserstein distributionally robust optimization framework for performative prediction, where the prediction model is optimized over the worst-case distribution within a Wasserstein ambiguity set. We allow the ambiguity radius to depend on the prediction model, which subsumes the constant-radius formulation as a special case. By leveraging strong duality, the intractable robust objective is reformulated as a computationally tractable minimization problem. Based on this formulation, we develop distributionally robust repeated risk minimization (DR-RRM) and repeated gradient descent (DR-RGD), to iteratively find an equilibrium between distributional shifts and model retraining. Theoretical analyses demonstrate that, under standard regularity conditions, both algorithms converge to a unique robust performative stable point. Our analysis explicitly accounts for inner-loop approximation errors and shows convergence to a neighborhood of the stable point in inexact settings. Additionally, we establish theoretical bounds on the suboptimality gap between the stable point and the global performative optimum. Finally, numerical simulations of a dynamic credit scoring problem demonstrate the efficacy of the method.

In this study, we report on the growth of ternary caesium lithium iodide ($Cs_2Li_3I_5$, CLI) bulk crystals, both undoped and doped with thallium (Tl) and indium (In), using the miniaturised vertical Bridgman method (mVB). X-ray Powder Diffraction (XRPD) confirmed the presence of the ternary CLI phase in all three crystals, with CLI : In appearing homogeneous structure-wise throughout the entire ingot. Measurements of radioluminescence (RL), photoluminescence emission (PL), photoluminescence excitation (PLE) spectra, and photoluminescence decay kinetics (PL decay) demonstrated that the primary luminescence centers originate from the matrix itself. When doped with thallium, the efficiency of the luminescence was significantly increased. Furthermore, CLI : Tl and CLI : In crystals exhibited emission spectra similar to those of their doped caesium iodide counterparts, CsI : Tl and CsI : In, respectively. The main component of the PL decay was 523 ns, 557 ns, and 554 ns for the undoped, Tl+-doped, and In+-doped crystals, respectively. It is worthy of note that only CLI : Tl exhibited a single exponential decay. Differential Scanning Calorimetry (DSC) measurements revealed two endothermic peaks corresponding to the eutectic and liquidus temperature for CLI and CLI : In, indicating that this ternary compound has a congruent melting behaviour. Finally, the melting point of CLI was estimated to be approximately 220 °C.

The topic of this paper is the subtle interplay between countability and representations. In particular, we establish that the definition of countability of a certain set $X$ crucially hinges on the associated equivalence relation $=_{X}$. Armed with this knowledge, we study well-known and basic principles about countable sets, going back to Cantor, Sierpiński, and König, working in Kohlenbach's higher-order Reverse Mathematics. While these principles are relatively weak in second-order Reverse Mathematics, we obtain equivalences involving countable choice and Feferman's projection principle. The latter are essentially the strongest axioms studied in higher-order Reverse Mathematics and usually only come to the fore when dealing with the uncountable.

We consider the $\mathcal{N}=4$ SYM theory with gauge group $Sp(N)$ and the $\mathcal{N}=2$ superconformal field theory consisting of four hypermultiplets in the fundamental representation and one hypermultiplet in the rank-two antisymmetric representation of the $Sp(N)$ gauge group. Building on previous results obtained via supersymmetric localization and a Toda equation, we determine the leading non-perturbative corrections at strong coupling to the integrated correlator between a Wilson line and two Higgs-branch moment map operators. In the case of the $\mathcal{N}=2$ SCFT, the presence of truncated asymptotic expansions led us to develop a resurgent method complementary to Cheshire cat resurgence. This approach has the advantage of yielding an exact expression for the correlator in terms of an analytic function, which can subsequently be expanded in the strong-coupling regime.

Nuclear quantum effects (NQEs) play an essential role in many atomistic systems, yet their explicit inclusion in molecular simulations remains challenging. Path-integral molecular dynamics (PIMD) provides a rigorous framework for incorporating NQEs, but its practical applicability is often limited by the slow and strongly system-dependent convergence with respect to the number of beads. Here we introduce path-integral generalized smoothed trajectory analysis (PIGSTA), a post-processing framework for the systematic incorporation of NQEs into atomistic simulations, using either classical or path-integral molecular dynamics trajectories. By applying analytically defined convolution kernels to simulation trajectories, PIGSTA corrects the frequency-dependent discretization error associated with a finite number of beads, without modifying the underlying dynamics. For harmonic systems, PIGSTA recovers the exact quantum-mechanical limit at any bead number, whereas standard PIMD becomes exact only in the infinite-bead limit. More generally, the method significantly improves the convergence of thermodynamic and structural observables at finite bead numbers and provides an internal, reference-free diagnostic of bead-number convergence based on the consistency of energy and force estimators. We assess PIGSTA for ambient liquid water and for the Zundel cation at ultralow temperature, representing a particularly demanding case for bead-number convergence. In both systems, PIGSTA reproduces the converged PIMD limit and enables physically consistent results at reduced bead numbers when convergence criteria are satisfied. Owing to its post-processing nature and negligible additional computational cost, PIGSTA offers a practical and broadly applicable approach for incorporating NQEs into atomistic simulations.

$Lu_2S_3$ material from the family of sesquisulfide hosts appears to be a promising low-phonon material for use as a laser gain medium allowing for a laser emission over a broad spectral range from ultraviolet to far mid-infrared wavelengths. In this paper, a praseodymium-ion doped $Lu_2S_3$ single crystal grown by micro-pulling down technique is investigated with focus on its spectroscopic properties. The Raman, excitation, and luminescence spectra are presented. By selective excitation of the main energy levels of $Pr^{3+}$-ions, 26 luminescence transitions of the $Pr:Lu_2S_3$ crystal spanning the 0.49 to 5.5 $μ$m wavelength range have been identified. The correct assignment of the observed luminescence spectra to the respective $Pr^{3+}$ energy-level transitions was confirmed by the calculation of the optimized squared reduced-matrix elements for the tensor operators U(k) and L + gS.

The stellar mass-size relation is a sensitive probe of how environment shapes galaxy structure. We analyse this relation in the local Universe for galaxies in compact groups (CGs), low-mass groups ($M_{\rm vir} \leq 10^{13}~M_{\odot}$), and high-mass groups, comparing them to field galaxies using data from the Southern Photometric Local Universe Survey. Galaxies are classified as early types (ETGs; $n \geq 2.5$, $(u-r)_0 \geq 2.3$), late types (LTGs; $n < 2.5$, $(u-r)_0 < 2.3$), transition galaxies (TGs; $n < 2.5$, $(u-r)_0 \geq 2.3$), and others (OGs; $n \geq 2.5$, $(u-r)_0 < 2.3$). We find that ETGs and OGs show no significant environmental dependence: their mass-size slopes and intercepts are statistically consistent across CGs, groups, and the field. LTGs also follow similar relations in the field and in most groups, with only a modest tendency for LTGs in CGs to be smaller at fixed stellar mass. By contrast, TGs display a clear environmental signal: in groups the slope steepens to $α\sim 0.4$ (versus $α\sim 0.2$ in the field) and their sizes are smaller than in the field, with non-overlapping 95\% posterior intervals. These trends suggest that TGs in denser environments are more structurally evolved, likely owing to enhanced bulge prominence and fading of the outer disc, consistent with the Sérsic-index distributions, which show an excess of TGs with $n_r \gtrsim 1.5$ in groups and CGs. Our findings highlight TGs as an environmentally sensitive population, providing insight into the structural transformation of galaxies in group environments.

Session types express and enforce safe communication in concurrent message-passing systems by statically capturing the interaction protocols between processes in the type. Recent works extend session types with arithmetic refinements, which enable additional fine-grained description of communication, but impose additional annotation burden on the programmer. To alleviate this burden, we propose a type inference algorithm for a session type system with arithmetic refinements. We develop a theory of subtyping for session types, including an algorithm which we prove sound with respect to a semantic definition based on type simulation. We also provide a formal inference algorithm that generates type and arithmetic constraints, which are then solved using the Z3 SMT solver. The algorithm has been implemented on top of the Rast language, and includes 3 key optimizations that make inference feasible and practical. We evaluate the efficacy of our inference engine by evaluating it on 6 challenging benchmarks, ranging from unary and binary natural numbers to linear $λ$-calculus. We show the performance benefits provided by our optimizations in coercing Z3 into solving the arithmetic constraints in reasonable time.

LLM-based agents can complete tasks correctly yet still frustrate users through poor interaction patterns, such as excessive confirmations, opaque reasoning, or misaligned pacing. Current benchmarks evaluate task accuracy but overlook how agents interact: whether they infer preferences from implicit cues, adapt dynamically, or maintain fine-grained interaction quality. We introduce Prefix, a configurable environment that evaluates both what agents accomplish and how they interact. Central to Prefix is the Interaction-as-a-Tool (IaaT) paradigm, which treats interaction behaviors as structured tool calls, unifying them with existing evaluation frameworks. We define 31 preference settings across 14 attributes and formalize user experience (UX) as a core metric alongside task accuracy. A composite LLM-as-a-Judge mechanism across seven UX dimensions achieves strong aggregate reliability (ICC > 0.79), high internal consistency (alpha = 0.943), and human correlation (rho = 0.52-0.78). Preference-aware agents show 7.6% average UX improvement and 18.5% gain in preference alignment. Our work is openly accessible.

Chiral topological semimetals hosting multifold fermions and exotic surface states represent a frontier in topological materials research. Among them, noncentrosymmetric cubic B20 compounds-notably transition-metal silicides and germanides-offer a unique platform for realizing symmetry-protected topological phases and unconventional optoelectronic responses. Here, we report the physical properties of RhGe and CoGe single crystals with B20 structure in detail. Transport measurements reveal metallic behavior with characteristic Fermi-liquid scaling at low temperatures, while magnetization results confirm paramagnetism in both compounds. In addition, both of materials exhibit low carrier concentrations with small electronic specific heat coefficient, indicating their semimetal feature with weak electronic correlations. Such high-quality CoGe and RhGe single crystals provide a material platform to explore the evolution of multifold fermions and the instability of helicoid-arc surface states with spin-orbit coupling and surface environment in B20 material systems.

Dissipative Kerr solitons (DKSs) have emerged as the preferred solution for on-chip integrated optical frequency comb (OFC) generation in metrology. A multi-pumped DKS enables either all-optical trapping in the Kerr-induced synchronization regime, or a multi-component OFC with \greg{a locked repetition rate yet with constant frequency offsets between the components} in the multi-color DKS regime. The multi-color DKS regime is of particular interest since nonlinear mixing between the DKS and the secondary pumped component generates idler waves at different frequencies that are useful for spectral extension of the DKS comb. Here, we explore multi-color idler generation at frequencies in which the resonator free spectral range matches that at the DKS. We demonstrate theoretically and experimentally that without phase matching, the idler forms a bright pulse fundamentally bound to the bright DKS through parametric interaction, despite occurring in normal dispersion. Our work can enable new applications in metrology and spectroscopy of quantum systems toward visible wavelengths, as the parametric nature of our bright-bright state eliminates dependence on dispersion regime or visible wavelength pumping.

The emergence of the terahertz (THz) ratchet effect is a rapidly expanding field of research that utilizes broken spatial symmetry in low-dimensional materials to rectify alternating current (AC) induced by THz fields into direct current (DC). This mechanism is highly promising for next-generation, room-temperature terahertz applications, particularly in high-speed, sensitive detection and imaging. In this work, we explore a ratchet effect generated in two dimensional tellurene, a novel promising semiconductor material consisting of helical atomic chains, creating a structure with inherent chirality. As a key result, the DC circular ratchet current flowing in the chiral axis direction $c$ is determined by the helicity of the radiation and can be reversed by switching the helicity from right to left handed. The circular ratchet effect excited by THz laser radiation is demonstrated for room temperature. The effect is demonstrated at various gate voltages when the Fermi level lies in vicinity of the Weyl point in the conduction band, in the band gap, and in the valence band with almost parabolic energy dispersion. The results are described by the developed microscopic theory based on the Boltzmann kinetic equation approach.

CI/CD pipeline failure management is time-consuming when performed manually. Automating this process is non-trivial because the information required for effective failure management is unstructured and cannot be automatically processed by traditional programs. With their ability to process unstructured data, large language models (LLMs) have shown promising results for automated failure management by previous work. Following these studies, we evaluated whether an LLM-based system could automate failure management in a CI/CD pipeline in the context of a large industrial software project, namely SAP HANA. We evaluated the ability of the LLM-based system to identify the error location and to propose exact solutions that contain no unnecessary actions. To support the LLM in generating exact solutions, we provided it with different types of domain knowledge, including pipeline information, failure management instructions, and data from historical failures. We conducted an ablation study to determine which type of domain knowledge contributed most to solution accuracy. The results show that data from historical failures contributed the most to the system's accuracy, enabling it to produce exact solutions in 92.1% of cases in our dataset. The system correctly identified the error location with 97.4% accuracy when provided with domain knowledge, compared to 84.2% accuracy without it. In conclusion, our findings indicate that LLMs, when provided with data from historical failures, represent a promising approach for automating CI/CD pipeline failure management.