Tootfinder

EvoFormer: Learning Dynamic Graph-Level Representations with Structural and Temporal Bias Correction
Haodi Zhong, Liuxin Zou, Di Wang, Bo Wang, Zhenxing Niu, Quan Wang
https://arxiv.org/abs/2508.15378 …

EvoFormer: Learning Dynamic Graph-Level Representations with Structural and Temporal Bias Correction
Dynamic graph-level embedding aims to capture structural evolution in networks, which is essential for modeling real-world scenarios. However, existing methods face two critical yet under-explored issues: Structural Visit Bias, where random walk sampling disproportionately emphasizes high-degree nodes, leading to redundant and noisy structural representations; and Abrupt Evolution Blindness, the failure to effectively detect sudden structural changes due to rigid or overly simplistic temporal m…

Measuring LLM Code Generation Stability via Structural Entropy
Yewei Song, Tiezhu Sun, Xunzhu Tang, Prateek Rajput, Tegawende F. Bissyande, Jacques Klein
https://arxiv.org/abs/2508.14288

Measuring LLM Code Generation Stability via Structural Entropy
Assessing the stability of code generation from large language models (LLMs) is essential for judging their reliability in real-world development. We extend prior "structural-entropy concepts" to the program domain by pairing entropy with abstract syntax tree (AST) analysis. For any fixed prompt, we collect the multiset of depth-bounded subtrees of AST in each generated program and treat their relative frequencies as a probability distribution. We then measure stability in two complementary way…

The Exponential Hyper-Zagreb Indices and Structural Properties of Trees and Bipartite Graphs
Jasem Hamoud
https://arxiv.org/abs/2508.14238 https://arxiv.or…

The Exponential Hyper-Zagreb Indices and Structural Properties of Trees and Bipartite Graphs
In this paper, we investigate the structural properties of trees and bipartite graphs through the lens of topological indices and combinatorial graph theory. We focus on the First and Second Hyper-Zagreb indices, $HM_1(G)$ and $HM_2(G)$, for trees $T \in T(n, Δ)$ with $n$ vertices and maximum degree $Δ$. Key propositions demonstrate that the presence of end-support or support vertices of degree at least three, distinct from a vertex of maximum degree, implies the existence of another tree $T'…

StructInbet: Integrating Explicit Structural Guidance into Inbetween Frame Generation
Zhenglin Pan, Haoran Xie
https://arxiv.org/abs/2507.13377 https://

StructInbet: Integrating Explicit Structural Guidance into Inbetween Frame Generation
In this paper, we propose StructInbet, an inbetweening system designed to generate controllable transitions over explicit structural guidance. StructInbet introduces two key contributions. First, we propose explicit structural guidance to the inbetweening problem to reduce the ambiguity inherent in pixel trajectories. Second, we adopt a temporal attention mechanism that incorporates visual identity from both the preceding and succeeding keyframes, ensuring consistency in character appearance.

Simulating from marginal structural models for hazards, cause-specific hazards and subdistribution hazards using general copulas
Shaun R Seaman
https://arxiv.org/abs/2508.15145 …

Simulating from marginal structural models for hazards, cause-specific hazards and subdistribution hazards using general copulas
Seaman and Keogh (Biometrical Journal 2024) proposed a method for simulating data compatible with a marginal structural model (MSM) for the hazard of a survival time outcome. In this short report, I propose two extensions of this method. First, Seaman and Keogh favoured the use of a Gaussian copula, because this enables the function of the confounder history through which the hazard of failure depends on confounders to be interpreted as a risk score. Here, I describe how this interpretation can…

Deep Generative Models in Condition and Structural Health Monitoring: Opportunities, Limitations and Future Outlook
Xin Yang, Chen Fang, Yunlai Liao, Jian Yang, Konstantinos Gryllias, Dimitrios Chronopoulos
https://arxiv.org/abs/2507.15026

Deep Generative Models in Condition and Structural Health Monitoring: Opportunities, Limitations and Future Outlook
Condition and structural health monitoring (CM/SHM) is a pivotal component of predictive maintenance (PdM) strategies across diverse industrial sectors, including mechanical rotating machinery, airplane composite wings, offshore wind turbines, and civil engineering structures. Conventional deep learning models, while effective in fault diagnosis and anomaly detection through supervised feature extraction and rule-based data augmentation, often struggle with operational variability, imbalanced o…

On consistency of the MLE under finite mixtures of location-scale distributions with a structural parameter
Guanfu Liu, Pengfei Li, Yukun Liu, Xiaolong Pu
https://arxiv.org/abs/2507.13764

On consistency of the MLE under finite mixtures of location-scale distributions with a structural parameter
We provide a general and rigorous proof for the strong consistency of maximum likelihood estimators of the cumulative distribution function of the mixing distribution and structural parameter under finite mixtures of location-scale distributions with a structural parameter. The consistency results do not require the parameter space of location and scale to be compact. We illustrate the results by applying them to finite mixtures of location-scale distributions with the component density functio…

Fusing Structural Phenotypes with Functional Data for Early Prediction of Primary Angle Closure Glaucoma Progression
Swati Sharma, Thanadet Chuangsuwanich, Royston K. Y. Tan, Shimna C. Prasad, Tin A. Tun, Shamira A. Perera, Martin L. Buist, Tin Aung, Monisha E. Nongpiur, Micha\"el J. A. Girard
https://arxiv.org/abs/2508.14922

Fusing Structural Phenotypes with Functional Data for Early Prediction of Primary Angle Closure Glaucoma Progression
Purpose: To classify eyes as slow or fast glaucoma progressors in patients with primary angle closure glaucoma (PACG) using an integrated approach combining optic nerve head (ONH) structural features and sector-based visual field (VF) functional parameters. Methods: PACG patients with >5 reliable VF tests over >5 years were included. Progression was assessed in Zeiss Forum, with baseline VF within six months of OCT. Fast progression was VFI decline <-2.0% per year; slow progression >-2.0% per y…

The GECKOS Survey: revealing the formation history of a barred galaxy via structural decomposition and resolved spectroscopy
A. Fraser-McKelvie, D. A. Gadotti, F. Fragkoudi, C. de S\'a-Freitas, M. Martig, T. Davis, R. Elliott, D. Fisher, M. R. Hayden, J. van de Sande, A. B. Watts
https://arxiv.org/abs/2509.15976

The GECKOS Survey: revealing the formation history of a barred galaxy via structural decomposition and resolved spectroscopy
Disentangling the (co-)evolution of individual galaxy structural components remains a difficult task owing to the inability to cleanly isolate light from spatially overlapping components. In this pilot study of PGC 044931, observed as part of the GECKOS survey, we utilise VIRCAM $H$-band imaging to decompose the galaxy into five photometric components, three of which contribute $>50\%$ of light in given regions: a main disc, a boxy/peanut bulge, and a nuclear disc. When the photometric decompos…

If you lock up your bike indoors (garage or home) what do you lock it up to?
I think a friend of mine locks his up to four other bikes but let's pretend that's not an option for everyone. 😅
What large, heavy, or structural thing do you lock your bike to in your garage or home?
#BikeNitePQ

Structural Foundations for Leading Digit Laws: Beyond Probabilistic Mixtures
Vladimir Berman
https://arxiv.org/abs/2508.13237 https://arxiv.org/pdf/2508.13…

Structural Foundations for Leading Digit Laws: Beyond Probabilistic Mixtures
This article presents a modern deterministic framework for the study of leading significant digit distributions in numerical data. Rather than relying on traditional probabilistic or mixture-based explanations, we demonstrate that the observed frequencies of leading digits are determined by the underlying arithmetic, algorithmic, and structural properties of the data-generating process. Our approach centers on a shift-invariant functional equation, whose general solution is given by explicit af…

Sensitivity of Perron and Fiedler eigenpairs to structural perturbations of a network
Silvia Noschese, Lothar Reichel
https://arxiv.org/abs/2509.16024 https://

Sensitivity of Perron and Fiedler eigenpairs to structural perturbations of a network
One can estimate the change of the Perron and Fiedler values for a connected network when the weight of an edge is perturbed by analyzing relevant entries of the Perron and Fiedler vectors. This is helpful for identifying edges whose weight perturbation causes the largest change in the Perron and Fiedler values. It also is important to investigate the sensitivity of the Perron and Fiedler vectors to perturbations. Applications of the perturbation analysis include the identification of edges tha…

Contact point geometry governs structural build-up at rest in Portland cement-limestone blends
Luca Michel, Antoine Sanner, Franco Zunino, Robert J. Flatt, David S. Kammer
https://arxiv.org/abs/2507.14029

Contact point geometry governs structural build-up at rest in Portland cement-limestone blends
The early stiffening of fresh cement paste plays a key role in shaping and stability during casting and 3D printing. In Portland cement systems, this phenomenon arises from the formation of calcium-silicate-hydrate (C-S-H), which stiffens grain-to-grain contacts. However, the role of powder characteristics such as particle size and morphology remains poorly understood. Here, we vary the fineness and grain shape by blending Portland cement with either coarse or fine limestone, leveraging the aff…

Structural Abstraction and Refinement for Probabilistic Programs
Guanyan Li, Juanen Li, Zhilei Han, Peixin Wang, Hongfei Fu, Fei He
https://arxiv.org/abs/2508.12344 https://

Structural Abstraction and Refinement for Probabilistic Programs
In this paper, we present structural abstraction refinement, a novel framework for verifying the threshold problem of probabilistic programs. Our approach represents the structure of a Probabilistic Control-Flow Automaton (PCFA) as a Markov Decision Process (MDP) by abstracting away statement semantics. The maximum reachability of the MDP naturally provides a proper upper bound of the violation probability, termed the structural upper bound. This introduces a fresh ``structural'' characterizati…

#ScribesAndMakers 22
Show us something you've created. Tell us the story behind it.
https://cs.wellesley.edu/~pmwh/labyrinfinite/
I was thinking on a dog walk about how most games with procedurally generated content like Minecraft get pretty repetitive at some point if you zoom out far enough, and large-scale structures that have structural constraints like rivers are very hard to generate piecemeal. So I wanted to come up with an algorithm that could generate globally-consistent structures piece-by-piece, with consistency even if pieces were generated out-of-order, while maintaining only a fixed amount of context no matter how far from the origin you went. This demo is *almost* that, except the amount of context scales logarithmically with the distance-from-origin, which I find a very acceptable compromise. In the demo, there's a single infinitely-long path that eventually touches every cell of the infinite 2D grid (okay, computer limitations mean it's not really infinite, but mathematically it could be). You can get different path structures from different random seeds, although the generation trick does constrain things a lot relative to the set of all possible such paths (notice that in each 5x5 region it touches every cell before leaving; that's not in general necessary).

Assessing Historical Structural Oppression Worldwide via Rule-Guided Prompting of Large Language Models
Sreejato Chatterjee, Linh Tran, Quoc Duy Nguyen, Roni Kirson, Drue Hamlin, Harvest Aquino, Hanjia Lyu, Jiebo Luo, Timothy Dye
https://arxiv.org/abs/2509.15216

Assessing Historical Structural Oppression Worldwide via Rule-Guided Prompting of Large Language Models
Traditional efforts to measure historical structural oppression struggle with cross-national validity due to the unique, locally specified histories of exclusion, colonization, and social status in each country, and often have relied on structured indices that privilege material resources while overlooking lived, identity-based exclusion. We introduce a novel framework for oppression measurement that leverages Large Language Models (LLMs) to generate context-sensitive scores of lived historical…

WorldWeaver: Generating Long-Horizon Video Worlds via Rich Perception
Zhiheng Liu, Xueqing Deng, Shoufa Chen, Angtian Wang, Qiushan Guo, Mingfei Han, Zeyue Xue, Mengzhao Chen, Ping Luo, Linjie Yang
https://arxiv.org/abs/2508.15720

WorldWeaver: Generating Long-Horizon Video Worlds via Rich Perception
Generative video modeling has made significant strides, yet ensuring structural and temporal consistency over long sequences remains a challenge. Current methods predominantly rely on RGB signals, leading to accumulated errors in object structure and motion over extended durations. To address these issues, we introduce WorldWeaver, a robust framework for long video generation that jointly models RGB frames and perceptual conditions within a unified long-horizon modeling scheme. Our training fra…

Series C, Episode 10 - Ultraworld
TARRANT: So you know our names. What about you?
ULTRA 1: We are the Ultra.
TARRANT: So you said.
ULTRA 1: Our sole function and purpose is to gather and accumulate information.
https://blake.torpidity.net/m/310/162 B7B2

What You See Is What It Does: A Structural Pattern for Legible Software
Eagon Meng, Daniel Jackson
https://arxiv.org/abs/2508.14511 https://arxiv.org/pdf/2…

What You See Is What It Does: A Structural Pattern for Legible Software
The opportunities offered by LLM coders (and their current limitations) demand a reevaluation of how software is structured. Software today is often "illegible" - lacking a direct correspondence between code and observed behavior - and insufficiently modular, leading to a failure of three key requirements of robust coding: incrementality (the ability to deliver small increments by making localized changes), integrity (avoiding breaking prior increments) and transparency (making clear what has c…

A Proof System with Causal Labels (Part II): checking Counterfactual Fairness
Leonardo Ceragioli, Giuseppe Primiero
https://arxiv.org/abs/2507.14655 https:…

A Proof System with Causal Labels (Part II): checking Counterfactual Fairness
In this article we propose an extension to the typed natural deduction calculus TNDPQ to model verification of counterfactual fairness in probabilistic classifiers. This is obtained formulating specific structural conditions for causal labels and checking that evaluation is robust under their variation.

Hardness and Structural Properties of Fuzzy Edge Contraction
Shanookha Ali
https://arxiv.org/abs/2509.16185 https://arxiv.org/pdf/2509.16185

Hardness and Structural Properties of Fuzzy Edge Contraction
We investigate the computational complexity of edge-deletion and edge-contraction problems in fuzzy graphs. For any graph property Π that is hereditary under contractions (or deletions) and determined by 3-connected components, the corresponding fuzzy edge-deletion (FPED) and fuzzy edge-contraction (FPEC) problems are NP- hard. Our results hold under both fixed-threshold (α_0) and all-threshold (\forall α) semantics, and apply even to restricted classes of fuzzy graphs such as fuzzy 3-connec…

AdapTT: Functoriality for Dependent Type Casts
Arthur Adjedj, Meven Lennon-Bertrand, Thibaut Benjamin, Kenji Maillard
https://arxiv.org/abs/2507.13774 http…

AdapTT: Functoriality for Dependent Type Casts
The ability to cast values between related types is a leitmotiv of many flavors of dependent type theory, such as observational type theories, subtyping, or cast calculi for gradual typing. These casts all exhibit a common structural behavior that boils down to the pervasive functoriality of type formers. We propose and extensively study a type theory, called AdapTT, which makes systematic and precise this idea of functorial type formers, with respect to an abstract notion of adapters relating …

Investigating the sliding behavior of graphene nanoribbons
Gourav Yadav (Department of Mechanical Engineering, Indian Institute of Technology Kanpur, UP, India), Aningi Mokhalingam (Department of Mechanical Engineering, Maulana Azad National Institute of Technology Bhopal, MP, India), Roger A. Sauer (Institute for Structural Mechanics, Ruhr University Bochum, Bochum, Germany, Department of Structural Mechanics, Gda\'nsk University of Technology, Gda\'nsk, Poland, Department of …

Investigating the sliding behavior of graphene nanoribbons
This work presents a Euler-Bernoulli beam finite element (FE) model to study the interlayer interaction mechanics of graphene nanoribbon (GNR) over a graphene substrate. The FE model is calibrated using molecular dynamics (MD) simulations employing the potential of Kolmogorov and Crespi. This study focuses mainly on the effect of boundary conditions on sliding behavior and strain transfer between layers when the substrate is subjected to uniform biaxial deformations. The interlayer shearing or …

Optimizing Compilation for Distributed Quantum Computing via Clustering and Annealing
Ruilin Zhou, Jinglei Cheng, Yuhang Gan, Junyu Liu, Chen Qian
https://arxiv.org/abs/2508.15267

Optimizing Compilation for Distributed Quantum Computing via Clustering and Annealing
Efficiently mapping quantum programs onto Distributed quantum computing (DQC) are challenging, particularly when considering the heterogeneous quantum processing units (QPUs) with different structures. In this paper, we present a comprehensive compilation framework that addresses these challenges with three key insights: exploiting structural patterns within quantum circuits, using clustering for initial qubit placement, and adjusting qubit mapping with annealing algorithms. Experimental result…

When Does Selfishness Align with Team Goals? A Structural Analysis of Equilibrium and Optimality
Gehui Xu, Thomas Parisini, Andreas A. Malikopoulos
https://arxiv.org/abs/2508.13450

When Does Selfishness Align with Team Goals? A Structural Analysis of Equilibrium and Optimality
This paper investigates the relationship between the team-optimal solution and the Nash equilibrium (NE) to assess the impact of self-interested decisions on team performance. In classical team decision problems, team members typically act cooperatively towards a common objective to achieve a team-optimal solution. However, in practice, members may behave selfishly by prioritizing their goals, resulting in an NE under a non-cooperative game. To study this misalignment, we develop a parameterize…

Uniform and Tunable Structural Colors based on Ultrathin Lignin Optical Coatings
Bang An, Anran Mao, Torbjorn Pettersson, Wei Li, Shouxin Liu, Anna J. Svagan, Ravi Shanker
https://arxiv.org/abs/2508.12902

Uniform and Tunable Structural Colors based on Ultrathin Lignin Optical Coatings
Structural coloration offers a sustainable and non-fading alternative to conventional pigment- and dye-based colorants. In this study, we present a scalable strategy for generating vivid, tunable structural colors using ultrathin films of industrial kraft lignin. By employing solvent fractionation to isolate a methanol-soluble lignin fraction, followed by spin-coating onto silicon substrates, we achieve highly uniform films with controllable thickness. The observed colors originate from thin-fi…

Crosslisted article(s) found for math.LO. https://arxiv.org/list/math.LO/new
[1/1]:
- Hardness and Structural Properties of Fuzzy Edge Contraction
Shanookha Ali

Revisit Choice Network for Synthesis and Technology Mapping
Chen Chen, Jiaqi Yin, Cunxi Yu
https://arxiv.org/abs/2508.14068 https://arxiv.org/pdf/2508.1406…

Revisit Choice Network for Synthesis and Technology Mapping
Choice network construction is a critical technique for alleviating structural bias issues in Boolean optimization, equivalence checking, and technology mapping. Previous works on lossless synthesis utilize independent optimization to generate multiple snapshots, and use simulation and SAT solvers to identify functionally equivalent nodes. These nodes are then merged into a subject graph with choice nodes. However, such methods often neglect the quality of these choices, raising the question of…

Graph Neural Network for Product Recommendation on the Amazon Co-purchase Graph
Mengyang Cao, Frank F. Yang, Yi Jin, Yijun Yan
https://arxiv.org/abs/2508.14059 https://

Graph Neural Network for Product Recommendation on the Amazon Co-purchase Graph
Identifying relevant information among massive volumes of data is a challenge for modern recommendation systems. Graph Neural Networks (GNNs) have demonstrated significant potential by utilizing structural and semantic relationships through graph-based learning. This study assessed the abilities of four GNN architectures, LightGCN, GraphSAGE, GAT, and PinSAGE, on the Amazon Product Co-purchase Network under link prediction settings. We examined practical trade-offs between architectures, model …

Gravitational Influence from Planets on the Measured Rates of Period Change of Pulsating White Dwarfs
Ling Xuan Yao, Keaton J. Bell, Andrew Dublin
https://arxiv.org/abs/2508.14195

Gravitational Influence from Planets on the Measured Rates of Period Change of Pulsating White Dwarfs
The measured rates of period change, $\dot{P}$, in the signals of pulsating white dwarf stars are often interpreted as direct detections of structural changes from secular cooling. Due to the intrinsic nature of this quantity, $\dot{P}$ analysis has been used to probe fundamental physics, such as constraining the mass of hypothetical axion particles. However, most white dwarfs are expected to host planets that could induce an external source of period change, caused by the light travel time var…

Modeling and Verification of Lumped-Parameter, Multibody Structural Dynamics for Offshore Wind Turbines
Saad Rahman, Doyal Sarker, Tri Ngo, Roger Bergua, Daniel Zalkind, Jason Jonkman, Tuhin Das
https://arxiv.org/abs/2509.13558

Modeling and Verification of Lumped-Parameter, Multibody Structural Dynamics for Offshore Wind Turbines
This paper presents the modeling and verification of multibody structural dynamics for offshore wind turbines. The flexible tower and support structure of a monopile-based offshore wind turbine are modeled using an acausal, lumped-parameter, multibody approach that incorporates structural flexibility, soil-structure interaction, and hydrodynamic models. Simulation results are benchmarked against alternative modeling approaches, demonstrating the model's ability to accurately capture both static…

Khovanov homology of tangles: algorithm and computation
Li Shen, Jian Liu, Guo-Wei Wei
https://arxiv.org/abs/2508.14404 https://arxiv.org/pdf/2508.14404

Khovanov homology of tangles: algorithm and computation
Knot, link, and tangle theory is crucial in both mathematical theory and practical application, including quantum physics, molecular biology, and structural chemistry. Unlike knots and links, tangles impose more relaxed constraints, allowing the presence of arcs, which makes them particularly valuable for broader applications. Although Khovanov homology for knots and links has been extensively studied, its computation for tangles remains largely unexplored. In our recent work, we provide a topo…

Tight Bounds for Answering Adaptively Chosen Concentrated Queries
Emma Rapoport, Edith Cohen, Uri Stemmer
https://arxiv.org/abs/2507.13700 https://

Tight Bounds for Answering Adaptively Chosen Concentrated Queries
Most work on adaptive data analysis assumes that samples in the dataset are independent. When correlations are allowed, even the non-adaptive setting can become intractable, unless some structural constraints are imposed. To address this, Bassily and Freund [2016] introduced the elegant framework of concentrated queries, which requires the analyst to restrict itself to queries that are concentrated around their expected value. While this assumption makes the problem trivial in the non-adaptive …

BEAM-Net: A Deep Learning Framework with Bone Enhancement Attention Mechanism for High Resolution High Frame Rate Ultrasound Beamforming
Midhila Madhusoodanan, Mahesh Raveendranatha Panicker, Pisharody Harikrishnan Gopalakrishnan, Abhilash Rakkunedeth Hareendranathan
https://arxiv.org/abs/2507.15306

BEAM-Net: A Deep Learning Framework with Bone Enhancement Attention Mechanism for High Resolution High Frame Rate Ultrasound Beamforming
Pocket-sized, low-cost point-of-care ultrasound (POCUS) devices are increasingly used in musculoskeletal (MSK) applications for structural examination of bone tissue. However, the image quality in MSK ultrasound is often limited by speckle noise, low resolution, poor contrast, and anisotropic reflections, making bone images difficult to interpret without additional post-processing. Typically, medical ultrasound systems use delay and sum beamforming (DASB) for image reconstruction, which is not …

Regional compositional trajectories and structural change: A spatiotemporal multivariate autoregressive framework
Matthias Eckardt, Philipp Otto
https://arxiv.org/abs/2507.14389

Regional compositional trajectories and structural change: A spatiotemporal multivariate autoregressive framework
Compositional data, such as regional shares of economic sectors or property transactions, are central to understanding structural change in economic systems across space and time. This paper introduces a spatiotemporal multivariate autoregressive model tailored for panel data with composition-valued responses at each areal unit and time point. The proposed framework enables the joint modelling of temporal dynamics and spatial dependence under compositional constraints and is estimated via a qua…

Project-connex Decompositions and Tractability of Aggregate Group-by Conjunctive Queries
Diego Figueira, Cibele Freire
https://arxiv.org/abs/2507.14101 htt…

Project-connex Decompositions and Tractability of Aggregate Group-by Conjunctive Queries
We introduce 'project-connex' tree-width as a measure of tractability for counting and aggregate conjunctive queries over semirings with 'group-by' projection (also known as 'AJAR' or 'FAQ' queries). This elementary measure allows to obtain comparable complexity bounds to the ones obtained by previous structural conditions tailored for efficient evaluation of semiring aggregate queries, enumeration algorithms of conjunctive queries, and tractability of counting answers to conjunctive queries. …

Structural contribution to light-induced gap suppression in Ta$_2$NiSe$_5$
Chen Zijing, Xu Chenhang, Xie Chendi, Tang Weichen, Liu Qiaomei, Wu Dong, Xu Qing, Jiang Tao, Zhu Pengfei, Zou Xiao, Li Jun, Wang Zhiwei, Wang Nanlin, Qian Dong, Zong Alfred, Xiang Dao
https://arxiv.org/abs/2508.12363

Structural contribution to light-induced gap suppression in Ta$_2$NiSe$_5$
An excitonic insulator is a material that hosts an exotic ground state, where an energy gap opens due to spontaneous condensation of bound electron-hole pairs. Ta$_2$NiSe$_5$ is a promising candidate for this type of material, but the coexistence of a structural phase transition with the gap opening has led to a long-standing debate regarding the origin of the insulating gap. Here we employ MeV ultrafast electron diffraction to obtain quantitative insights into the atomic displacements in Ta$_2…

Hierarchical Planning and Scheduling for Reconfigurable Multi-Robot Disassembly Systems under Structural Constraints
Takuya Kiyokawa, Tomoki Ishikura, Shingo Hamada, Genichiro Matsuda, Kensuke Harada
https://arxiv.org/abs/2509.14564

Hierarchical Planning and Scheduling for Reconfigurable Multi-Robot Disassembly Systems under Structural Constraints
This study presents a system integration approach for planning schedules, sequences, tasks, and motions for reconfigurable robots to automatically disassemble constrained structures in a non-destructive manner. Such systems must adapt their configuration and coordination to the target structure, but the large and complex search space makes them prone to local optima. To address this, we integrate multiple robot arms equipped with different types of tools, together with a rotary stage, into a re…

Algebraic description of the triaxially to axially rotational shape phase transition
Yu Zhang, Yu Xin Liu, Feng Pan, J. P. Draayer
https://arxiv.org/abs/2508.15426 https://

Algebraic description of the triaxially to axially rotational shape phase transition
Within the framework of the interacting boson model, we propose a novel algebraic scheme to describe spin-dependent structural evolutions in triaxial nuclei. Our analysis demonstrates that a triaxially to axially rotational shape phase transition can be induced by the high-order correction which is microscopically motivated by the pairing interaction on the $γ$-unstable rotation. This prescription is further applied to describe the structural evolutions along the yrast sequences of $^{132}$Ba …

MP-GCAN: a highly accurate classifier for $\alpha$-helical membrane proteins and $\beta$-barrel proteins
Kunyang Li, Hongfu Lou, Dinan Peng
https://arxiv.org/abs/2507.14269

MP-GCAN: a highly accurate classifier for $α$-helical membrane proteins and $β$-barrel proteins
Membrane protein classification is a fundamental task in structural bioinformatics, critical to understanding protein functions and accelerating drug discovery. In this study, we propose MP-GCAN, a novel graph-based classification model that leverages both spatial and sequential features of proteins. MP-GCAN combines GCN, GAT, and GIN layers to capture hierarchical structural representations from 3D protein graphs, constructed from high-resolution PDB files with $α$-carbon coordinates and resi…

Parsec-scale jet precession and a putative supermassive binary black hole system in the blazar AO 0235 164
Flavio Benevenuto da Silva Junior, Anderson Caproni
https://arxiv.org/abs/2508.14178

Parsec-scale jet precession and a putative supermassive binary black hole system in the blazar AO 0235+164
The blazar AO 0235+164 is a key source for studying the interplay between multi-wavelength variability in its light curves and changes in the position angles and apparent velocities of its parsec-scale jet components. In this work, we analyse public interferometric radio maps of AO 0235+164 at 15 and 43 GHz, using the Cross Entropy global optimisation technique to determine the structural parameters of its jet components. We identified 36 kinematically distinct jet components across all sky qua…

Full-field rheo-optical analysis of wormlike and networked micellar structures under uniaxial extensional flow
Masakazu Muto, Naoki Kako, Tatsuya Yoshino, Shinji Tamano
https://arxiv.org/abs/2507.15562

Full-field rheo-optical analysis of wormlike and networked micellar structures under uniaxial extensional flow
The present study proposes a novel full-field extensional rheo-optical technique to investigate the relationship between the rheological properties and internal structural deformation of complex fluids under uniaxial extensional flow. Macroscopic viscoelasticity from rheological measurements and microscopic birefringence from optical measurements are integrated to evaluate the microstructural deformation and orientation of the fluids under extensional stress. The proposed technique integrates a…

The Small-World Beneath LEO Satellite Coverage: Ground Hubs in Multi-Shell Constellations
Hailong Su, Jinshu Su, Yusheng Xia, Haibin Li
https://arxiv.org/abs/2508.14335 https://…

The Small-World Beneath LEO Satellite Coverage: Ground Hubs in Multi-Shell Constellations
In recent years, the emergence of large-scale Low-Earth-Orbit (LEO) satellite constellations has introduced unprecedented opportunities for global connectivity. However, routing efficiency and inter-shell communication remain key challenges in multi-shell architectures. This paper investigates the structural properties and network dynamics of a representative six-shell mega-constellation composed of 10,956 satellites and 198 gateway stations (GSs). Leveraging tools from complex network analysis…

Comprehensive Privacy Risk Assessment in Social Networks Using User Attributes Social Graphs and Text Analysis
Md Jahangir Alam, Ismail Hossain, Sai Puppala, Sajedul Talukder
https://arxiv.org/abs/2507.15124

Comprehensive Privacy Risk Assessment in Social Networks Using User Attributes Social Graphs and Text Analysis
The rise of social networking platforms has amplified privacy threats as users increasingly share sensitive information across profiles, content, and social connections. We present a Comprehensive Privacy Risk Scoring (CPRS) framework that quantifies privacy risk by integrating user attributes, social graph structures, and user-generated content. Our framework computes risk scores across these dimensions using sensitivity, visibility, structural similarity, and entity-level analysis, then aggre…

The Chapman-Enskog Divergence Problem in Plasma Transport: Structural Limitations and a Practical Regularization Approach
Justo Karell
https://arxiv.org/abs/2508.12390 https://

The Chapman-Enskog Divergence Problem in Plasma Transport: Structural Limitations and a Practical Regularization Approach
We calculate transport coefficients from the Chapman--Enskog expansion with BGK collision operators, obtaining exactly $κ= \frac{5nT}{2mν}$, and show that maximum entropy closure yields identical results when applied with the same collision operator. Through structural arguments, we suggest that this $1/ν$ divergence extends to other local collision operators of the form $\mathcal{L} = ν\hat{L}$, making the divergence fundamental to the Chapman--Enskog approach rather than a closure artifac…

Replaced article(s) found for econ.EM. https://arxiv.org/list/econ.EM/new
[1/1]:
- Assignment at the Frontier: Identifying the Frontier Structural Function and Bounding Mean Deviat...
Dan Ben-Moshe, David Genesove

A Century of Evolution in the Complexity of the United States Legal Code
Dawoon Jeong, James Holehouse, Jisung Yoon, Chris Kempes, Geoffrey B West, Hyejin Youn
https://arxiv.org/abs/2507.14342

A Century of Evolution in the Complexity of the United States Legal Code
As societies confront increasingly complex regulatory demands in domains such as digital governance, climate policy, and public health, there is a pressing need to understand how legal systems evolve, where they concentrate regulatory attention, and how their institutional architectures shape capacity for adaptation. Yet, the long-term structural dynamics of law remain empirically underexplored. Here, we provide a versioned, machine-readable record of the United States Code (U.S. Code), the pri…

Borderline regularity in singular free boundary problems
Dami\~ao J. Ara\'ujo, Aelson Sobral, Eduardo V. Teixeira, Jos\'e Miguel Urbano
https://arxiv.org/abs/2508.14736 …

Borderline regularity in singular free boundary problems
In this paper, we investigate the borderline regularity of local minimizers of energy functionals under minimal assumptions on the potential term $σ$. When $σ$ is merely bounded and measurable, we show that sign-changing minimizers are Log-Lipschitz continuous, which represents the optimal regularity in this general setting. In the one-phase case, however, we establish gradient bounds for minimizers along their free boundaries, revealing a structural gain in regularity. Most notably, we prove…

On hollowness in multiplicative lattices
Amartya Goswami, Joseph Zelezniak
https://arxiv.org/abs/2508.15718 https://arxiv.org/pdf/2508.15718

On hollowness in multiplicative lattices
The aim of this article is to extend the notions of strongly hollow and completely strongly hollow ideals of commutative rings to multiplicative lattices. We investigate their basic structural properties and prove several characterizations in terms of localizations at maximal elements and the behaviour of residuals. In particular, we study properties of strongly hollow elements in various types of $C$-lattices: Gelfand, semi-simple, and Prüfer. We also provide characterizations of quasi-local …

AdaSports-Traj: Role- and Domain-Aware Adaptation for Multi-Agent Trajectory Modeling in Sports
Yi Xu, Yun Fu
https://arxiv.org/abs/2509.16095 https://arxi…

AdaSports-Traj: Role- and Domain-Aware Adaptation for Multi-Agent Trajectory Modeling in Sports
Trajectory prediction in multi-agent sports scenarios is inherently challenging due to the structural heterogeneity across agent roles (e.g., players vs. ball) and dynamic distribution gaps across different sports domains. Existing unified frameworks often fail to capture these structured distributional shifts, resulting in suboptimal generalization across roles and domains. We propose AdaSports-Traj, an adaptive trajectory modeling framework that explicitly addresses both intra-domain and inte…

Multimodal Quantum Vision Transformer for Enzyme Commission Classification from Biochemical Representations
Murat Isik, Mandeep Kaur Saggi, Humaira Gowher, Sabre Kais
https://arxiv.org/abs/2508.14844

Multimodal Quantum Vision Transformer for Enzyme Commission Classification from Biochemical Representations
Accurately predicting enzyme functionality remains one of the major challenges in computational biology, particularly for enzymes with limited structural annotations or sequence homology. We present a novel multimodal Quantum Machine Learning (QML) framework that enhances Enzyme Commission (EC) classification by integrating four complementary biochemical modalities: protein sequence embeddings, quantum-derived electronic descriptors, molecular graph structures, and 2D molecular image representa…

Q&A with researcher Petter Törnberg on his pre-print study showing how social media's structural architecture creates problematic outcomes like echo chambers (Jennifer Ouellette/Ars Technica)
https://arstechnica.com/science/2025/08/study-social-medi…

Study: Social media probably can’t be fixed
“The [structural] mechanism producing these problematic outcomes is really robust and hard to resolve.”…

Time for another round of critical AI weekend reading:
Crashing hard: why talking about bubbles obscures the real social cost of overinvesting into “Artificial Intelligence”
Aline Blankertz (@…)

Crashing hard: why talking about bubbles obscures the real social cost of overinvesting into “Artificial Intelligence”
More and more commentators talk about and warn of an “AI bubble”, and everybody seems to congratulate each other on being such a smart financial analyst. BUT: A bubble pops and you are left with air and maybe a splash of soap somewhere on the floor. A fairly clean affair. This kind of investor speak

Structural and Connectivity Patterns in the Maven Central Software Dependency Network
Daniel Ogenrwot, John Businge, Shaikh Arifuzzaman
https://arxiv.org/abs/2508.13819 https://…

Structural and Connectivity Patterns in the Maven Central Software Dependency Network
Understanding the structural characteristics and connectivity patterns of large-scale software ecosystems is critical for enhancing software reuse, improving ecosystem resilience, and mitigating security risks. In this paper, we investigate the Maven Central ecosystem, one of the largest repositories of Java libraries, by applying network science techniques to its dependency graph. Leveraging the Goblin framework, we extracted a sample consisting of the top 5,000 highly connected artifacts base…

Dynamic Latent Class Structural Equation Modeling: A Hands-On Tutorial for Modeling Intensive Longitudinal Data
Roberto Faleh, Sofia Morelli, Vivato Andriamiarana, Zachary J. Roman, Christoph Fl\"uckiger, Holger Brandt
https://arxiv.org/abs/2508.12983

Dynamic Latent Class Structural Equation Modeling: A Hands-On Tutorial for Modeling Intensive Longitudinal Data
In this tutorial, we provide a hands-on guideline on how to implement complex Dynamic Latent Class Structural Equation Models (DLCSEM) in the Bayesian software JAGS. We provide building blocks starting with simple Confirmatory Factor and Time Series analysis, and then extend these blocks to Multilevel Models and Dynamic Structural Equation Models (DSEM). Leading through the tutorial is an example from clinical psychology using data on a generalized anxiety treatment that includes scales on anxi…

Reliable generation of isomorphic physics problems using ChatGPT with prompt-chaining and tool use
Zhongzhou Chen
https://arxiv.org/abs/2508.14755 https://…

Reliable generation of isomorphic physics problems using ChatGPT with prompt-chaining and tool use
We present a method for generating large numbers of isomorphic physics problems using ChatGPT through prompt chaining and tool use. This approach enables precise control over structural variations-such as numeric values and spatial relations-while supporting diverse contextual variations in the problem body. By utilizing the Python code interpreter, the method supports automatic solution validation and simple diagram generation, addressing key limitations in existing LLM-based methods. We gener…

A Proof System with Causal Labels (Part I): checking Individual Fairness and Intersectionality
Leonardo Ceragioli, Giuseppe Primiero
https://arxiv.org/abs/2507.14650

A Proof System with Causal Labels (Part I): checking Individual Fairness and Intersectionality
In this article we propose an extension to the typed natural deduction calculus TNDPQ to model verification of individual fairness and intersectionality in probabilistic classifiers. Their interpretation is obtained by formulating specific conditions for the application of the structural rule of Weakening. Such restrictions are given by causal labels used to check for conditional independence between protected and target variables.

How do Language Models Generate Slang: A Systematic Comparison between Human and Machine-Generated Slang Usages
Siyang Wu, Zhewei Sun
https://arxiv.org/abs/2509.15518 https://…

How do Language Models Generate Slang: A Systematic Comparison between Human and Machine-Generated Slang Usages
Slang is a commonly used type of informal language that poses a daunting challenge to NLP systems. Recent advances in large language models (LLMs), however, have made the problem more approachable. While LLM agents are becoming more widely applied to intermediary tasks such as slang detection and slang interpretation, their generalizability and reliability are heavily dependent on whether these models have captured structural knowledge about slang that align well with human attested slang usage…

Conformal Contraction for Robust Nonlinear Control with Distribution-Free Uncertainty Quantification
Sihang Wei, Melkior Ornik, Hiroyasu Tsukamoto
https://arxiv.org/abs/2507.13613

Conformal Contraction for Robust Nonlinear Control with Distribution-Free Uncertainty Quantification
We present a novel robust control framework for continuous-time, perturbed nonlinear dynamical systems with uncertainty that depends nonlinearly on both the state and control inputs. Unlike conventional approaches that impose structural assumptions on the uncertainty, our framework enhances contraction-based robust control with data-driven uncertainty prediction, remaining agnostic to the models of the uncertainty and predictor. We statistically quantify how reliably the contraction conditions …

AnchorSync: Global Consistency Optimization for Long Video Editing
Zichi Liu, Yinggui Wang, Tao Wei, Chao Ma
https://arxiv.org/abs/2508.14609 https://arxiv…

AnchorSync: Global Consistency Optimization for Long Video Editing
Editing long videos remains a challenging task due to the need for maintaining both global consistency and temporal coherence across thousands of frames. Existing methods often suffer from structural drift or temporal artifacts, particularly in minute-long sequences. We introduce AnchorSync, a novel diffusion-based framework that enables high-quality, long-term video editing by decoupling the task into sparse anchor frame editing and smooth intermediate frame interpolation. Our approach enforce…

Comprehensive Structural Characterization of Charged Polymers Involved in Moisture-Driven Direct Air Capture
Gayathri Yogaganeshan, Rui Zhang, Raimund Fromme, Sharang Sharang, Jamie Ford, Douglas M Yates, Marlene Velazco Medel, Martin Uher, Justin Flory, Jennifer Wade, Petra Fromme
https://arxiv.org/abs/2508.11809

Comprehensive Structural Characterization of Charged Polymers Involved in Moisture-Driven Direct Air Capture
The rise in atmospheric carbon dioxide (CO2) levels has led to urgent calls for effective carbon capture methods, with direct air capture (DAC) emerging as a promising solution. This study focuses on the structural characterization of commercially available alkaline anion-exchange membrane (AEM) polymers, Fumasep FAA-3 and IRA 900, for use in low-energy, moisture-driven DAC applications. A combination of X-ray diffraction, small and wide-angle X-ray scattering (SAXS/WAXS), atomic force microsco…

Real-Time Thermal State Estimation and Forecasting in Laser Powder Bed Fusion
Yukta Pareek, Abdul Malik Al Mardhouf Al Saadi, Amrita Basak, Satadru Dey
https://arxiv.org/abs/2509.16114

Real-Time Thermal State Estimation and Forecasting in Laser Powder Bed Fusion
Laser Powder Bed Fusion (L-PBF) is a widely adopted additive manufacturing process for fabricating complex metallic parts layer by layer. Effective thermal management is essential to ensure part quality and structural integrity, as thermal gradients and residual stresses can lead to defects such as warping and cracking. However, existing experimental or computational techniques lack the ability to forecast future temperature distributions in real time, an essential capability for proactive proc…

Towards Temporal Knowledge Graph Alignment in the Wild
Runhao Zhao, Weixin Zeng, Wentao Zhang, Xiang Zhao, Jiuyang Tang, Lei Chen
https://arxiv.org/abs/2507.14475

Towards Temporal Knowledge Graph Alignment in the Wild
Temporal Knowledge Graph Alignment (TKGA) seeks to identify equivalent entities across heterogeneous temporal knowledge graphs (TKGs) for fusion to improve their completeness. Although some approaches have been proposed to tackle this task, most assume unified temporal element standards and simplified temporal structures across different TKGs. They cannot deal with TKGA in the wild (TKGA-Wild), where multi-scale temporal element entanglement and cross-source temporal structural imbalances are c…

Graph Structure Learning with Temporal Graph Information Bottleneck for Inductive Representation Learning
Jiafeng Xiong, Rizos Sakellariou
https://arxiv.org/abs/2508.14859 https…

Graph Structure Learning with Temporal Graph Information Bottleneck for Inductive Representation Learning
Temporal graph learning is crucial for dynamic networks where nodes and edges evolve over time and new nodes continuously join the system. Inductive representation learning in such settings faces two major challenges: effectively representing unseen nodes and mitigating noisy or redundant graph information. We propose GTGIB, a versatile framework that integrates Graph Structure Learning (GSL) with Temporal Graph Information Bottleneck (TGIB). We design a novel two-step GSL-based structural enha…

Nuclear discs in disc galaxies: structural properties and scaling relations
Dimitri A. Gadotti (Durham University), Camila de S\'a-Freitas (ESO)
https://arxiv.org/abs/2509.14319

Nuclear discs in disc galaxies: structural properties and scaling relations
The presence of nuclear discs in barred disc galaxies has been demonstrated in studies on stellar structures and kinematics. It is thus imperative to establish their fundamental properties and scaling relations, which can help understanding their connection to other central stellar structures, including nuclear star clusters. In this Letter, we use results from the structural analysis and star formation histories of a sample of galaxies with nuclear discs to show the distributions of fundamenta…

The Digital Sous Chef -- A Comparative Study on Fine-Tuning Language Models for Recipe Generation
Shubham Pundhir, Ganesh Bagler
https://arxiv.org/abs/2508.14718 https://…

The Digital Sous Chef -- A Comparative Study on Fine-Tuning Language Models for Recipe Generation
We established a rigorous benchmark for text-based recipe generation, a fundamental task in natural language generation. We present a comprehensive comparative study contrasting a fine-tuned GPT-2 large (774M) model against the GPT-2 small (124M) model and traditional LSTM/RNN baselines on the 5-cuisine corpus from RecipeDB. Our key contribution is a targeted tokenization strategy that augments the vocabulary with 23 common fraction tokens and custom structural markers. This approach addresses …

Low Speed Oblique Impact Behavior On Granular Media Across Gravitational Conditions; The role of cohesion
Seungju Yeo, Rachel Glade, Alice Quillen, Hesam Askari
https://arxiv.org/abs/2507.14645

Low Speed Oblique Impact Behavior On Granular Media Across Gravitational Conditions; The role of cohesion
Analyses of impact provide rich insights from the evolution of granular bodies to their structural properties of the surface and subsurface layers of celestial bodies. Although chemical cohesive bonding has been observed in asteroid samples, and low-speed impact has been a subject of many studies, our understanding of the role of cohesion in these dynamics is limited, especially at small gravities such as those observed on asteroid surfaces. In this work, we use numerical discrete element metho…

More on Nosal's spectral theorem: Books and $4$-cycles
Yongtao Li, Hong Liu, Shengtong Zhang
https://arxiv.org/abs/2508.14366 https://arxiv.org/pdf/250…

More on Nosal's spectral theorem: Books and $4$-cycles
Spectral graph theory studies how the eigenvalues of a graph relate to the structural properties of a graph. In this paper, we solve three open problems in spectral extremal graph theory which generalize the classical Turán-type supersaturation results. (a) We prove that every $m$-edge graph $G$ with the spectral radius $λ(G) > \sqrt{m}$ contains at least $\frac{1}{144} \sqrt{m}$ triangles sharing a common edge. This result confirms a conjecture of Nikiforov, and Li and Peng. Moreover, the …

Leveraging the Spatial Hierarchy: Coarse-to-fine Trajectory Generation via Cascaded Hybrid Diffusion
Baoshen Guo, Zhiqing Hong, Junyi Li, Shenhao Wang, Jinhua Zhao
https://arxiv.org/abs/2507.13366

Leveraging the Spatial Hierarchy: Coarse-to-fine Trajectory Generation via Cascaded Hybrid Diffusion
Urban mobility data has significant connections with economic growth and plays an essential role in various smart-city applications. However, due to privacy concerns and substantial data collection costs, fine-grained human mobility trajectories are difficult to become publicly available on a large scale. A promising solution to address this issue is trajectory synthesizing. However, existing works often ignore the inherent structural complexity of trajectories, unable to handle complicated hig…

Polarization-Resolved Chlorophyll Imaging for Non-Invasive Plant Tissue Assessment Using a Silicon-Rich Nitride Metalens Array
Alireza Khalilian, Mehdi Sh. Yeganeh, Konstantin Tsoi, Bowen Yu, Joe Lo, Yasha Yi
https://arxiv.org/abs/2508.14191

Polarization-Resolved Chlorophyll Imaging for Non-Invasive Plant Tissue Assessment Using a Silicon-Rich Nitride Metalens Array
Polarization-sensitive imaging enhances contrast and reveals structural features in biological tissues that are often missed by intensity-based methods, but its adoption is limited by bulky optics. We present a compact silicon-rich nitride (SRN) metalens array for high-resolution, polarization-resolved imaging of plant tissue at the chlorophyll absorption peak (660\,nm). The array integrates orthogonally sensitive metalenses to simultaneously capture X- and Y-linearly polarized transmission ima…

To What Extent Can Public Equity Indices Statistically Hedge Real Purchasing Power Loss in Compounded Structural Emerging-Market Crises? An Explainable ML-Based Assessment
Artem Alkhamov, Boris Kriuk
https://arxiv.org/abs/2507.13055

To What Extent Can Public Equity Indices Statistically Hedge Real Purchasing Power Loss in Compounded Structural Emerging-Market Crises? An Explainable ML-Based Assessment
This study investigates the extent to which local public equity indices can statistically hedge real purchasing power loss during compounded structural macro-financial collapses in emerging markets. We employ a non-linear multiplicative real return calculations consistent with Fisher-parity logics for both domestic and foreign investors with a principled quantile regression, tail dependence copula analysis, and Shapley Additive Explanations (SHAP) to assess the explanatory power of macro variab…

SATURN: Autoregressive Image Generation Guided by Scene Graphs
Thanh-Nhan Vo, Trong-Thuan Nguyen, Tam V. Nguyen, Minh-Triet Tran
https://arxiv.org/abs/2508.14502 https://…

SATURN: Autoregressive Image Generation Guided by Scene Graphs
State-of-the-art text-to-image models excel at photorealistic rendering but often struggle to capture the layout and object relationships implied by complex prompts. Scene graphs provide a natural structural prior, yet previous graph-guided approaches have typically relied on heavy GAN or diffusion pipelines, which lag behind modern autoregressive architectures in both speed and fidelity. We introduce SATURN (Structured Arrangement of Triplets for Unified Rendering Networks), a lightweight exte…

A Severity-Aware Reliability Index for Risk-Informed Structural Design
Moussa Leblouba, Samer Barakat, Raghad Awad
https://arxiv.org/abs/2508.12068 https://

A Severity-Aware Reliability Index for Risk-Informed Structural Design
Classical measures of structural reliability, such as the probability of failure and the related reliability index, are still widely applied in practice. However, these measures are frequency-based only, and they do not give information about the severity of failure once it happens. This missing aspect can cause underestimation of risks, in particular when rare events produce very undesirable consequences. In this paper, a new reliability framework is proposed to address this issue. The framewo…

Blended Point Cloud Diffusion for Localized Text-guided Shape Editing
Etai Sella, Noam Atia, Ron Mokady, Hadar Averbuch-Elor
https://arxiv.org/abs/2507.15399

Blended Point Cloud Diffusion for Localized Text-guided Shape Editing
Natural language offers a highly intuitive interface for enabling localized fine-grained edits of 3D shapes. However, prior works face challenges in preserving global coherence while locally modifying the input 3D shape. In this work, we introduce an inpainting-based framework for editing shapes represented as point clouds. Our approach leverages foundation 3D diffusion models for achieving localized shape edits, adding structural guidance in the form of a partial conditional shape, ensuring th…

TabStruct: Measuring Structural Fidelity of Tabular Data
Xiangjian Jiang, Nikola Simidjievski, Mateja Jamnik
https://arxiv.org/abs/2509.11950 https://arxiv…

TabStruct: Measuring Structural Fidelity of Tabular Data
Evaluating tabular generators remains a challenging problem, as the unique causal structural prior of heterogeneous tabular data does not lend itself to intuitive human inspection. Recent work has introduced structural fidelity as a tabular-specific evaluation dimension to assess whether synthetic data complies with the causal structures of real data. However, existing benchmarks often neglect the interplay between structural fidelity and conventional evaluation dimensions, thus failing to prov…

An Efficient Algorithm for Generating Minimal Unique-Cause MC/DC Test cases for Singular Boolean Expressions
Robin Lee, Youngho Nam
https://arxiv.org/abs/2507.14687

An Efficient Algorithm for Generating Minimal Unique-Cause MC/DC Test cases for Singular Boolean Expressions
Modified Condition/Decision Coverage (MC/DC) is a mandatory structural coverage criterion for ensuring the reliability and safety of critical systems. While its strictest form, Unique-Cause MC/DC, offers the highest assurance, research on its efficient test generation has been lacking. This gap is particularly significant, as an analysis of large-scale avionics systems shows that 99.7% of all conditional decisions are, in fact, Singular Boolean Expressions (SBEs) the ideal structure for applyin…

Real time observation of glass-like carbon formation from SU-8 using X-ray and ultraviolet photoelectron spectroscopy
Simon Astley, Jaspa Stritt, Soumen Mandal, Jerome A. Cuenca, D. Andrew Evans, Oliver A. Williams
https://arxiv.org/abs/2507.14053

Real time observation of glass-like carbon formation from SU-8 using X-ray and ultraviolet photoelectron spectroscopy
The structural development and change in elemental composition of SU-8 3005 photoresist into glass-like carbon due to pyrolysis up to 1000~$\degree$C is investigated utilising \textit{in-situ} x-ray and ultraviolet photoelectron spectroscopy (XPS/UPS) under ultra-high vacuum (UHV). XPS spectra were analysed in order to investigate changes to elemental composition and physical structure. Peak asymmetry in the measured C 1s spectra is found to be a clear indicator of a transition in both physical…

Clasificaci\'on por 2-switch-degree de grafos split
Victor Nicolas Schv\"ollner
https://arxiv.org/abs/2507.13479 https://arx…

Clasificación por 2-switch-degree de grafos split
The 2-switch-degree of $G$ is the number of distinct 2-switches acting on a graph $G$. In this work we study structural properties of the 2-switch-degree, with a focus on split graphs. Our approach is motivated by the Tyshkevich decomposition, which uniquely expresses any graph as a composition $G_r \circ \ldots \circ G_1$ of irreducible graphs, where $G_2, \ldots, G_r$ are split. Our key tool is the factor graph $Φ(S)$, a multigraph associated with a split graph $S$ that encodes 2-switch-degr…

Data augmentation enables label-specific generation of homologous protein sequences
Lorenzo Rosset, Martin Weigt, Francesco Zamponi
https://arxiv.org/abs/2507.15651

Data augmentation enables label-specific generation of homologous protein sequences
Accurately annotating and controlling protein function from sequence data remains a major challenge, particularly within homologous families where annotated sequences are scarce and structural variation is minimal. We present a two-stage approach for semi-supervised functional annotation and conditional sequence generation in protein families using representation learning. First, we demonstrate that protein language models, pretrained on large and diverse sequence datasets and possibly finetune…

Handy Relation Between Binary Black Hole Merger Times and Host Galaxy Properties
Kelly Holley-Bockelmann (Department of Physics and Astronomy, Vanderbilt University, Nashville, TN, Department of Physics, Fisk University, Nashville, TN), Fazeel Khan (New York University Abu Dhabi, United Arab Emirates, Center for Astrophysics and Space Science), Isaiah Williams (Department of Physics and Astronomy, Vanderbilt University, Nashville, TN), Jaelyn Roth (Department of Physics and Astronomy, …

Handy Relation Between Binary Black Hole Merger Times and Host Galaxy Properties
Over the past 15 years, the evidence has clearly demonstrated that massive black hole (MBH) binary merger timescales depend strongly on the structural and kinematic properties of their host galaxy. Stellar density, gas content, shape and kinematics all play a role, combining in non-linear ways to effect the evolution of the binary. The binary properties themselves, such as eccentricity, mass ratio, and orbital plane, all matter as well. This makes it nontrivial to estimate accurate cosmological…

GOGS: High-Fidelity Geometry and Relighting for Glossy Objects via Gaussian Surfels
Xingyuan Yang, Min Wei
https://arxiv.org/abs/2508.14563 https://arxiv.o…

GOGS: High-Fidelity Geometry and Relighting for Glossy Objects via Gaussian Surfels
Inverse rendering of glossy objects from RGB imagery remains fundamentally limited by inherent ambiguity. Although NeRF-based methods achieve high-fidelity reconstruction via dense-ray sampling, their computational cost is prohibitive. Recent 3D Gaussian Splatting achieves high reconstruction efficiency but exhibits limitations under specular reflections. Multi-view inconsistencies introduce high-frequency surface noise and structural artifacts, while simplified rendering equations obscure mate…

Replaced article(s) found for cond-mat.soft. https://arxiv.org/list/cond-mat.soft/new
[1/1]:
- Structural Anisotropy Stabilises Asymmetric Beating in Instability Driven Filaments
Bethany Clarke, Yongyun Hwang, Eric E Keaveny

On-Demand Inverse Design for Narrowband Nanophotonic Structures Based on Generative Model and Tandem Network
Yuxiao Li, Taeyoon Kim, Allen Zhang, Zengbo Wang, Yongmin Liu
https://arxiv.org/abs/2507.14761

On-Demand Inverse Design for Narrowband Nanophotonic Structures Based on Generative Model and Tandem Network
Inverse design in nanophotonics remains challenging due to its ill-posed nature and sensitivity to input inaccuracies. We present a novel framework that combines a Conditional Variational Autoencoder (CVAE) with a tandem network, enabling robust and efficient on-demand inverse design of photonic structures. Unlike prior approaches that use CVAEs or tandem networks in isolation, our method integrates spectral adjustment and structural prediction in a unified architecture. Specifically, the CVAE …

TableDART: Dynamic Adaptive Multi-Modal Routing for Table Understanding
Xiaobo Xing, Wei Yuan, Tong Chen, Quoc Viet Hung Nguyen, Xiangliang Zhang, Hongzhi Yin
https://arxiv.org/abs/2509.14671

TableDART: Dynamic Adaptive Multi-Modal Routing for Table Understanding
Modeling semantic and structural information from tabular data remains a core challenge for effective table understanding. Existing Table-as-Text approaches flatten tables for large language models (LLMs), but lose crucial structural cues, while Table-as-Image methods preserve structure yet struggle with fine-grained semantics. Recent Table-as-Multimodality strategies attempt to combine textual and visual views, but they (1) statically process both modalities for every query-table pair within a…

Joint Learning of Panel VAR models with Low Rank and Sparse Structure
Yuchen Xu, George Michailidis
https://arxiv.org/abs/2509.15402 https://arxiv.org/pdf/…

Joint Learning of Panel VAR models with Low Rank and Sparse Structure
Panel vector auto-regressive (VAR) models are widely used to capture the dynamics of multivariate time series across different subpopulations, where each subpopulation shares a common set of variables. In this work, we propose a panel VAR model with a shared low-rank structure, modulated by subpopulation-specific weights, and complemented by idiosyncratic sparse components. To ensure parameter identifiability, we impose structural constraints that lead to a nonsmooth, nonconvex optimization pro…

Erd\H{o}s's unit distance problem and rigidity
J\'anos Pach, Orit E. Raz, J\'ozsef Solymosi
https://arxiv.org/abs/2507.15679 https://

Erdős's unit distance problem and rigidity
According to a classical result of Spencer, Szemerédi, and Trotter (1984), the maximum number of times the unit distance can occur among $n$ points in the plane is $O(n^{4/3})$. This is far from Erdős's lower bound, $n^{1+O(1/\log\log n)}$, which is conjectured to be optimal. We prove a structural result for point sets with nearly $n^{4/3}$ unit distances and use it to reduce the problem to a conjecture on rigid frameworks. This conjecture, if true, would yield the first improvement on the bo…

NMR evidence for an antisite-induced magnetic moment on Bi in a topological insulator heterostructures MnBi2Te4/(Bi2Te3)n
R. Kalvig, E. Jedryka, A. Lynnyk, P. Skupinski, K. Grasza, M. Wojcik
https://arxiv.org/abs/2508.15527

NMR evidence for an antisite-induced magnetic moment on Bi in a topological insulator heterostructures MnBi2Te4/(Bi2Te3)n
MnBi2Te4 (MBT) is the first intrinsic magnetic topological insulator, combining a topologically protected surface metallic state and intrinsic magnetic order. A structural compatibility with the nonmagnetic Bi2Te4 (BT) parent compound gives a possibility to create MBT/BT heterostructures and manipulate their magnetic state in view of optimizing the Quantum Anomalous Hall Effect (QAHE). In this work an extensive NMR study, supported by the bulk magnetization measurements has been performed at 4.…

PBPU Elastomer Network Architecture Determination via Corresponding States Analysis of Mechanical Behavior
Sushanta Das (Department of Chemical Engineering, Indian Institute of Technology Bombay, Mumbai, Maharashtra, India Defence Research,Development Organization, New Delhi, India), Hari Ramakrishna Sudhakar (Department of Chemical Engineering, Indian Institute of Technology Bombay, Mumbai, Maharashtra, India), Hemant Nanavati (Department of Chemical Engineering, Indian Institute of T…

PBPU Elastomer Network Architecture Determination via Corresponding States Analysis of Mechanical Behavior
In this work we examine the effect of R=[NCO]/[OH] in the R=<1 regime, on the resultant structural topology of polybutadiene polyurethane (PBPU) elastomer networks based on hydroxy-terminated polybutadiene (HTPB). We employ stress-elongation behavior and its modeling, as a tool. We examine this property via a combination of our model for the finite chain phantom networks incorporating the HTPB structural information, with the slip-tube model from the literature, suitably modified phenomenologic…

Hardness, Structural Knowledge, and Opportunity: An Analytical Framework for Modular Performance Modeling
Omid Gheibi, Christian K\"astner, Pooyan Jamshidi
https://arxiv.org/abs/2509.11000

Hardness, Structural Knowledge, and Opportunity: An Analytical Framework for Modular Performance Modeling
Performance-influence models are beneficial for understanding how configurations affect system performance, but their creation is challenging due to the exponential growth of configuration spaces. While gray-box approaches leverage selective "structural knowledge" (like the module execution graph of the system) to improve modeling, the relationship between this knowledge, a system's characteristics (we call them "structural aspects"), and potential model improvements is not well understood. Thi…

A rutile-based homologous series Na(PtO$_2$)$_{2\it{n} 1}$ discovered by computationally assisted high-pressure synthesis
Yasuhito Kobayashi, Hidefumi Takahashi, Shunsuke Kitou, Akitoshi Nakano, Hajime Sagayama, Yuichi Yamasaki, Shintaro Ishiwata
https://arxiv.org/abs/2508.15223

A rutile-based homologous series Na(PtO$_2$)$_{2\it{n}+1}$ discovered by computationally assisted high-pressure synthesis
Layered transition metal oxides typified by the Ruddlesden-Popper phase have been extensively studied for its applications in high-temperature superconductivity, catalysis, and battery technologies. Despite the remarkable structural diversity and catalytic functionality of platinum oxides, the exploration of layered polymorphs has remained significantly constrained mainly due to the high inertness of platinum. Here, we discover a new homologous series of layered ternary oxides, Na(PtO$_2$)$_{2\…

A Remedy for Over-Squashing in Graph Learning via Forman-Ricci Curvature based Graph-to-Hypergraph Structural Lifting
Michael Banf, Dominik Filipiak, Max Schattauer, Liliya Imasheva
https://arxiv.org/abs/2508.11390

A Remedy for Over-Squashing in Graph Learning via Forman-Ricci Curvature based Graph-to-Hypergraph Structural Lifting
Graph Neural Networks are highly effective at learning from relational data, leveraging node and edge features while maintaining the symmetries inherent to graph structures. However, many real-world systems, such as social or biological networks, exhibit complex interactions that are more naturally represented by higher-order topological domains. The emerging field of Geometric and Topological Deep Learning addresses this challenge by introducing methods that utilize and benefit from higher-ord…

Relationship between Structure and Dynamics of an Icosahedral Quasicrystal using Unsupervised Machine Learning
Edwin A. Bedolla-Montiel, Susana Mar\'in-Aguilar, Marjolein Dijkstra
https://arxiv.org/abs/2507.15731

Relationship between Structure and Dynamics of an Icosahedral Quasicrystal using Unsupervised Machine Learning
We present a comprehensive study of the structure, formation, and dynamics of a one-component model system that self-assembles into an icosahedral quasicrystal (IQC). Using molecular dynamics simulations combined with unsupervised machine learning techniques, we identify and characterize the unique structural motifs of IQCs, including icosahedral and dodecahedral arrangements, and quantify the evolution of local environments during the IQC formation process. Our analysis reveals that the format…

Fair Play in the Newsroom: Actor-Based Filtering Gender Discrimination in Text Corpora
Stefanie Urchs, Veronika Thurner, Matthias A{\ss}enmacher, Christian Heumann, Stephanie Thiemichen
https://arxiv.org/abs/2508.13169

Fair Play in the Newsroom: Actor-Based Filtering Gender Discrimination in Text Corpora
Large language models are increasingly shaping digital communication, yet their outputs often reflect structural gender imbalances that originate from their training data. This paper presents an extended actor-level pipeline for detecting and mitigating gender discrimination in large-scale text corpora. Building on prior work in discourse-aware fairness analysis, we introduce new actor-level metrics that capture asymmetries in sentiment, syntactic agency, and quotation styles. The pipeline supp…

Charge density wave in intermetallic oxides R$_5$Pb$_3$O (R = La and Ce)
Rafaela F. S. Penacchio, Siham Mohamed, Haley A. Harms, Lin-Lin Wang, Sergey L. Bud'ko, Paul. C Canfield, Tyler J. Slade
https://arxiv.org/abs/2507.15817

Charge density wave in intermetallic oxides R$_5$Pb$_3$O (R = La and Ce)
The R$_5$Pb$_3$O family was discovered decades ago, but has remained largely unexplored. Here, we report single crystal growth and basic characterization for the La and Ce members of this family. At room temperature, these compounds adopt a tetragonal structure (I4/mcm), where R and Pb atoms form linear chains along the c-axis. We identify a second-order structural phase transition at 260 K and 145 K for R = La and Ce, respectively. Single crystal X-ray diffraction reveals a lattice modulation …

3DViT-GAT: A Unified Atlas-Based 3D Vision Transformer and Graph Learning Framework for Major Depressive Disorder Detection Using Structural MRI Data
Nojod M. Alotaibi, Areej M. Alhothali, Manar S. Ali
https://arxiv.org/abs/2509.12143

3DViT-GAT: A Unified Atlas-Based 3D Vision Transformer and Graph Learning Framework for Major Depressive Disorder Detection Using Structural MRI Data
Major depressive disorder (MDD) is a prevalent mental health condition that negatively impacts both individual well-being and global public health. Automated detection of MDD using structural magnetic resonance imaging (sMRI) and deep learning (DL) methods holds increasing promise for improving diagnostic accuracy and enabling early intervention. Most existing methods employ either voxel-level features or handcrafted regional representations built from predefined brain atlases, limiting their a…

Competing Length Scales and Symmetry Frustration Govern Non-Universal Melting in 2D Core-softened Colloidal Crystals
Thiago Puccinelli, Alexandre V. Ilha, Jos\'e Rafael Bordin
https://arxiv.org/abs/2507.13573

Competing Length Scales and Symmetry Frustration Govern Non-Universal Melting in 2D Core-softened Colloidal Crystals
We investigate the melting behavior of two-dimensional colloidal crystals stabilized by a core-softened potential featuring two competing interaction length scales. Using molecular dynamics simulations, we analyze three polymorphic solid phases -- low-density triangular, stripe, and kagome -- and uncover distinct melting pathways. The triangular and kagome crystals undergo abrupt first-order transitions, driven by the interplay between energetic frustration and structural reorganization. In par…

Multi-User Contextual Cascading Bandits for Personalized Recommendation
Jiho Park, Huiwen Jia
https://arxiv.org/abs/2508.13981 https://arxiv.org/pdf/2508.1…

Multi-User Contextual Cascading Bandits for Personalized Recommendation
We introduce a Multi-User Contextual Cascading Bandit model, a new combinatorial bandit framework that captures realistic online advertising scenarios where multiple users interact with sequentially displayed items simultaneously. Unlike classical contextual bandits, MCCB integrates three key structural elements: (i) cascading feedback based on sequential arm exposure, (ii) parallel context sessions enabling selective exploration, and (iii) heterogeneous arm-level rewards. We first propose Uppe…

Moir\'e-Induced Magnetoelectricity in Twisted Bilayer NiI2
Haiyan Zhua, Hongyu Yua, Weiqin Zhua, Guoliang Yua, Changsong Xu, Hongjun Xiang
https://arxiv.org/abs/2507.13709

Moiré-Induced Magnetoelectricity in Twisted Bilayer NiI2
Twisted magnetic van der Waals (vdW) materials offer a promising route for multiferroic engineering, yet modeling large-scale moiré superlattices remains challenging. Leveraging a newly developed SpinGNN++ framework that effectively handles spin-lattice coupled systems, we develop a comprehensive interatomic machine learning (ML) potential and apply it to twisted bilayer NiI2 (TBN). Structural relaxation introduces moiré-periodic "bumps" that modulate the interlayer spacing by about 0.55~Å a…

DashCam Video: A complementary low-cost data stream for on-demand forest-infrastructure system monitoring
Durga Joshi (Department of Natural Resources and the Environment, Eversource Energy Center, University of Connecticut, Storrs, CT, USA), Chandi Witharana (Department of Natural Resources and the Environment, Eversource Energy Center, University of Connecticut, Storrs, CT, USA), Robert Fahey (Department of Natural Resources and the Environment, Eversource Energy Center, University o…

DashCam Video: A complementary low-cost data stream for on-demand forest-infrastructure system monitoring
Our study introduces a novel, low-cost, and reproducible framework for real-time, object-level structural assessment and geolocation of roadside vegetation and infrastructure with commonly available but underutilized dashboard camera (dashcam) video data. We developed an end-to-end pipeline that combines monocular depth estimation, depth error correction, and geometric triangulation to generate accurate spatial and structural data from street-level video streams from vehicle-mounted dashcams. D…

Phase stability and structural properties of the K$_{x}$Ca$_{1-x}$N novel ferromagnetic alloy from first-principles
K. Larbaoui, A. Lakdja, G. Bassou
https://arxiv.org/abs/2509.13728

Phase stability and structural properties of the K$_{x}$Ca$_{1-x}$N novel ferromagnetic alloy from first-principles
We study the structural properties and phase stability of the K$_{x}$Ca$_{1-x}$N alloy using the regular-solution model based on the total energy of the mixing. The pseudopotential approach was used along with PBE functional of Perdew, Burke, and Ernzerhof (PBE). We investigated the bond-lengths distribution as a function of composition $x$. We also predicted the phase separation of the two partially miscible components and calculated the enthalpy $ΔH$ using the interaction parameter $Ω$. We …