December 2025 arXiv papers — page 80

Roman Akramov, Artem Khamatullin, Svetlana Glazyrina, Maksim Kryzhanovskiy

Choosing the number of topics $T$ in Latent Dirichlet Allocation (LDA) is a key design decision that strongly affects both the statistical fit and interpretability of topic models. In this work, we formulate the selection of $T$ as a discrete black-box optimization problem, where each function evaluation corresponds to training an LDA model and measuring its

Yadong Li, Tong Zhang, Bo Huang, Zhen Cui

Deep multi-agent reinforcement learning (MARL) algorithms are booming in the field of collaborative intelligence, and StarCraft multi-agent challenge (SMAC) is widely-used as the benchmark therein. However, imaginary opponents of MARL algorithms are practically configured and controlled in a fixed built-in AI mode, which causes less diversity and versatility

Shangxun Li, Youngjung Uh

Text-to-image diffusion models excel at generating high-quality images from natural language descriptions but often fail to preserve subject consistency across multiple outputs, limiting their use in visual storytelling. Existing approaches rely on model fine-tuning or image conditioning, which are computationally expensive and require per-subject optimizati

Allard Oelen, Sören Auer

The rapidly growing popularity of adopting Artificial Intelligence (AI), and specifically Large Language Models (LLMs), is having a widespread impact throughout society, including the academic domain. AI-supported research has the potential to support researchers with tasks across the entire research life cycle. In this work, we demonstrate the TIB AIssistan

Miquel Llorens-Monteagudo, Alejandro Torres-Forné, José A. Font

The post-merger phase of binary neutron star (BNS) mergers encodes valuable information about the equation of state (EOS) of supranuclear matter. Extracting this information from the analysis of the post-merger waveforms remains challenging due to the high-frequency limitations of current detectors. Future third-generation observatories, such as the Einstein

Keegan S. Trehaeven, Cyril Tasse, Oleg Smirnov, Tiziana Venturi

With the increasing sensitivity of modern radio interferometers, it has become important to image objects larger than the field of view while optimising sensitivity and image fidelity. We present a coherent visibility plane direction-dependent imaging, calibration and mosaicing framework. Our simulations and application to real MeerKAT data show that this jo

Hao Li, Yubing Ren, Yanan Cao, Yingjie Li

Benefiting from the superior capabilities of large language models in natural language understanding and generation, Embeddings-as-a-Service (EaaS) has emerged as a successful commercial paradigm on the web platform. However, prior studies have revealed that EaaS is vulnerable to imitation attacks. Existing methods protect the intellectual property of EaaS t

Shaoxiong Chen, Zhipeng Yang, Xi Zhang

In this paper we study the following fractional Choquard equation with mixed nonlinearities: \[ \left\{ \begin{array}{l} (-\Delta)^s u = \lambda u + \alpha \left( I_\mu * |u|^q \right) |u|^{q-2} u + \left( I_\mu * |u|^p \right) |u|^{p-2} u, \quad x \in \mathbb{R}^N, \\[4pt] \displaystyle \int_{\mathbb{R}^N} |u|^2 \,\mathrm{d}x = c^2 > 0. \end{array} \right.

Jordan Abarca-Albores, Danna Cristina Gutiérrez Cabrera, Luis Antonio Salazar-Licea, Dante Ruiz-Robles

This paper presents a novel methodology for detecting faults in wind turbine blades using com-putational learning techniques. The study evaluates two models: the first employs logistic regression, which outperformed neural networks, decision trees, and the naive Bayes method, demonstrating its effectiveness in identifying fault-related patterns. The second m

Chen Liang, Zhaonan Luo, Zhaoyang Yin

This paper is devoted to the uniform vanishing damping limit of the 2D inviscid Oldroyd-B model with fractional stress tensor diffusion. Firstly, we find that fractional stress tensor diffusion helps to reduce the global regularity of the 2D Oldroyd-B model with damping coefficient $a\in[0,1]$. By virtue of improved Fourier splitting method, we then prove th

Marcelo Cerda Castillo

Short-term prediction (nowcasting) of low-visibility and precipitation events is critical for aviation safety and operational efficiency. Current operational approaches rely on computationally intensive numerical weather prediction guidance and human-issued TAF products, which often exhibit conservative biases and limited temporal resolution. This study pres

Mahmood Hasani, Hadis Salasi, Negar Ashari Astani

Four decades after Richard Feynman's famous remark, we have reached a stage at which nature can be simulated quantum mechanically. Quantum simulation is among the most promising applications of quantum computing. However, like many quantum algorithms, it is severely constrained by noise in near-term hardware. Quantum-inspired algorithms provide an attractive

Ángel Borrego, Cristóbal Urbano

OpenAlex is an open bibliographic database that has been proposed as an alternative to commercial platforms in a context defined by the aim of transforming science evaluation systems into more transparent sources based on open data. This paper analyses its features, information sources, entities, advantages and limitations. The results reveal numerous record

Maeve Madigan, Parameswaran Kamalaruban, Glenn Moynihan, Tom Kempton

Multi-agent systems have demonstrated the ability to improve performance on a variety of predictive tasks by leveraging collaborative decision making. However, the lack of effective evaluation methodologies has made it difficult to estimate the risk of bias, making deployment of such systems unsafe in high stakes domains such as consumer finance, where biase

Nils Foix-Colonier, Sébastien Bourguignon

Linear spectral unmixing under nonnegativity and sum-to-one constraints is a convex optimization problem for which many algorithms were proposed. In practice, especially for supervised unmixing (i.e., with a large dictionary), solutions tend to be sparse due to the nonnegativity of the abundances, thereby motivating the use of an active-set solver. Given the

Wanying Chen, Hongyun Zhang, Jinxi Lu, Yu Gu

Twisted MoTe$_2$ hosts intriguing correlated quantum phenomena including the fractional quantum anomalous Hall effect in twisted bilayer (t-BL) MoTe$_2$ near 3.7$^\circ$, which is sensitive to the twist angle and moir\'e superlattices. Here, we directly visualize the twist-angle-modulated electronic structure of t-BL and twisted double-bilayer (t-DBL) near t

Filippo Zacchei, Paolo Conti, Attilio Alberto Frangi, Andrea Manzoni

Inverse uncertainty quantification (UQ) tasks such as parameter estimation are computationally demanding whenever dealing with physics-based models, and typically require repeated evaluations of complex numerical solvers. When partial differential equations are involved, full-order models such as those based on the Finite Element Method can make traditional

Tsuyoshi Miyatsu, Myung-Ki Cheoun, Kyungsik Kim, Koichi Saito

We investigate the nuclear equation of state (EoS) for isospin-asymmetric matter using a new set of RMF interactions with the $\sigma$-$\delta$ and $\omega$-$\rho$ mixing, referred to as the OMEG family. These interactions are optimized so as to reproduce both terrestrial nuclear measurements and astrophysical constraints extracted from NICER and GW170817. T

Juan J. Font, Sergio Macario

In this paper we provide new several Jackson-type approximations results for continuous fuzzy-number-valued functions which improve several previous ones. We use alternative techniques adapted from Interval Analysis which rely on the gH-difference (which might not exist) and the generalized difference (which might lack the cancellation law ) of fuzzy numbers

Xin Miao, Pawan Kumar Mishra

Since Generative AI came out it has quickly embedded itself in our social fabric, triggering lots of discussions, predictions, and efforts from research, industry, government and capital market to experiment and embrace the technology. The question for the global K12 education is, what and how should our children learn in this fast changing world to be prepa

Andrey I. Bondarev

The first measurements of the magnetic dipole hyperfine structure constants A in singly ionized thulium revealed substantial discrepancies with the corresponding calculations [Mansour et al., NIMB 40, 252 (1989)]. More recent measurements [Kebapc{\i} et al., ApJ 970, 23 (2024)] expanded very limited dataset of that work and demonstrated that two of the previ

Allard Oelen, Mohamad Yaser Jaradeh, Sören Auer

As the volume of published scholarly literature continues to grow, finding relevant literature becomes increasingly difficult. With the rise of generative Artificial Intelligence (AI), and particularly Large Language Models (LLMs), new possibilities emerge to find and explore literature. We introduce ASK (Assistant for Scientific Knowledge), an AI-driven sch

Nguyen Xuan-Vu, Daniel Armstrong, Milena Wehrbach, Andres M Bran

Computer-aided synthesis planning (CASP) has long been envisioned as a complementary tool for synthetic chemists. However, existing frameworks often lack mechanisms to allow interaction with human experts, limiting their ability to integrate chemists' insights. In this work, we introduce Synthelite, a synthesis planning framework that uses large language mod

Juan J. Font, Sergio Macario, Manuel Sanchis

We extend Cardaliaguet-Euvrard neural network operators to the context of fuzzy number valued continuous functions and study their behaviour. We focus on level continuous, sendograph continuous and endograph continuous functions and obtain Jackson-type results in all these cases.

Robert J. J. Grand, Martin Roth

Spiral arms are the defining features of broad morphological classes of disc galaxies, but their nature and influence on galaxy evolution is still under debate. A key diagnostic for their nature is the spiral arm pattern speed: the radial profile of the angular rotation rate of spiral features. This profile determines the location and number of dynamical res

Akila Wickramasekara, Tharusha Mihiranga, Aruna Withanage, Buddhima Weerasinghe

The National Institute of Standards and Technology (NIST) Computer Forensic Tool Testing (CFTT) programme has become the de facto standard for providing digital forensic tool testing and validation. However to date, no comprehensive framework exists to automate benchmarking across the diverse forensic tasks included in the programme. This gap results in inco

O. Sohier, A. Y. Jaziri, L. Vettier, A. Chatain

Characterizing temperate exoplanet atmospheres remains challenging due to their small size and low temperatures. Recent JWST observations provide valuable data, but their interpretation has led to diverging conclusions. Complementary approaches combining laboratory experiments and photochemical modeling are essential for constraining atmospheric chemistry an

Kaspar Rosager Ludvigsen

The use of Large Language Models (LLM) by providers of cybersecurity and digital infrastructures of all kinds is an ongoing development. It is suggested and on an experimental basis used to write the code for the systems, and potentially fed with sensitive data or what would otherwise be considered trade secrets. Outside of these obvious points, this paper a

Xiongfang Liu, Shengwei Zeng, Xun Liu, Kun Han

High-temperature superconductivity in cuprate materials remains a major challenge in physics due to the complexity of their strongly correlated electronic states. Interfacial strain is a powerful lever for tuning electronic correlations in complex oxides, offering new pathways to control emergent quantum phases. Here, we report the discovery of interfacial s

Vincent Van Eylen, Richard Massey, Saeeda Awan, Jo Bartlett

Habitable Worlds Observatory (HWO) will be NASA's flagship space telescope of the 2040s, designed to search for life on other planets and to transform broad areas of astrophysics. NASA are seeking international partners, and the UK is well-placed to lead the design and construction of its imaging camera - which is likely to produce the mission's most visible

Jannes Malanowski

Democracy relies on making collective decisions through voting. In addition, voting procedures have further applications, for example in the training of artificial intelligence. An essential criterion for determining the winner of a fair election is that all alternatives are treated equally: this is called neutrality. The established Ranked Pairs voting meth

Rahim Kargar

We investigate the higher-order Volterra-type integral operator $T_{g,n}$ on the unit disk, defined for $n\in\mathbb N$ by \[ T_{g,n}[f](z) := \underbrace{\int_{0}^{z}\int_{0}^{t_1}\cdots\int_{0}^{t_{n-1}}}_{n\ \text{times}} f(t_n)g'(t_n)\,dt_n\cdots dt_1,\quad z\in\mathbb D, \] where $f$ and $g$ are analytic in the unit disk $\mathbb D$. We establish sharp

Sergio Macario, Manuel Sanchis

The authors introduced in a previous paper the notion of fuzzy Gromov-Hausdorff distance between non-Archimedean compact fuzzy metric spaces, presenting a fuzzy version of the Gromov's completeness theorem. In this paper we present a fuzzy version of the Gromov's precompactness theorem which allows to deduce the classical theorem for compact metric spaces by

Hao Tang, Jiongyu Zhu, Zimeng Feng, Hao Li

Neural operators have emerged as powerful tools for learning mappings between function spaces, enabling efficient solutions to partial differential equations across varying inputs and domains. Despite the success, existing methods often struggle with non-periodic excitations, transient responses, and signals defined on irregular or non-Euclidean geometries.

Ruifeng Xu, Liang He

Effective irrigation and nitrogen fertilization have a significant impact on crop yield. However, existing research faces two limitations: (1) the high complexity of optimizing water-nitrogen combinations during crop growth and poor yield optimization results; and (2) the difficulty in quantifying mild stress signals and the delayed feedback, which results i

J. Sumaya-Martinez, J. Mulia-Rodriguez

The scattering of electromagnetic waves by subwavelength rectangular grooves has been extensively studied, yet its physical interpretation has largely relied on field-intensity distributions. Here we demonstrate that the transition from concave to convex scattering profiles observed as the groove width approaches the wavelength is governed by a topological r

Joachim Winther Pedersen, Erwan Plantec, Eleni Nisioti, Marcello Barylli

How can neural networks evolve themselves without relying on external optimizers? We propose Self-Referential Graph HyperNetworks, systems where the very machinery of variation and inheritance is embedded within the network. By uniting hypernetworks, stochastic parameter generation, and graph-based representations, Self-Referential GHNs mutate and evaluate t

Robert Rugg, Shambel Akalu, Amare Abebe

This work investigates the nonlinearity of the power-law model of F(T) gravity, highlighting the inability of the Boltzmann solver CLASS to handle nonlinear models. As a workaround, a second-order Taylor expansion is applied to the nonlinear field equations, under the assumption that the extra degree of freedom n, which quantifies deviations from the current

Matthew Edmonds, James Bateman

Laser-induced acoustic desorption (LIAD) enables loading nanoparticles into optical traps under vacuum for levitated optomechanics experiments. Current LIAD systems rely on empirical optimization using available laboratory lasers rather than systematic theoretical design, resulting in large systems incompatible with portable or space-based applications. We d

Andres Lizano-Villalobos, Fangyuan Ma, Wentao Tang, Wei Sun

Achieving precise control of colloidal self-assembly into specific patterns remains a longstanding challenge due to the complex process dynamics. Recently, machine learning-based state representation and reinforcement learning-based control strategies have started to accumulate popularity in the field, showing great potential in achieving an automatable and

Miguel A. González-Casado, Angel Sánchez, Santo Fortunato

We study the structure of personal relationships among 1068 high school students using a dataset that contains the network of self-reported friendly and conflictive relationships, with information on their directionality and intensity. We analyse the resulting weighted, directed, and signed network using a Bayesian stochastic block model framework, which ena

Raphael Yuster

For graphs $F$ and $H$, let $i(F)$ denote the inducibility of $F$ and let $i_H(F)$ denote the inducibility of $F$ over $H$-free graphs. We prove that for almost all graphs $F$ on a given number of vertices, $i_{K_k}(F)$ attains infinitely many values as $k$ varies. For complete partite graphs $F$ (and, more generally, for symmetrizable families of graphs $F$

Haodi He, Jihun Yu, Ronald Fedkiw

We leverage increasingly popular three-dimensional neural representations in order to construct a unified and consistent explanation of a collection of uncalibrated images of the human face. Our approach utilizes Gaussian Splatting, since it is more explicit and thus more amenable to constraints than NeRFs. We leverage segmentation annotations to align the s

Anup Singh, Vipul Arora, Kris Demuynck

Fast and accurate spoken content retrieval is vital for applications such as voice search. Query-by-Example Spoken Term Detection (STD) involves retrieving matching segments from an audio database given a spoken query. Token-based STD systems, which use discrete speech representations, enable efficient search but struggle with robustness to noise and reverbe

Suleiman Saka, Sanchari Das

The Internet of Things (IoT) has the potential to enhance older adults' independence and quality of life, but it also exposes them to security, privacy, accessibility, and usability (SPAU) risks. We conducted a systematic review of 44 peer-reviewed studies published between 2004 and 2024 using a five-phase screening pipeline. From each study, we extracted da

Zhanwei Li, Liang Li, Jiawan Zhang

High-quality annotated data plays a crucial role in achieving accurate segmentation. However, such data for medical image segmentation are often scarce due to the time-consuming and labor-intensive nature of manual annotation. To address this challenge, we propose the Adaptive Frequency Domain Alignment Network (AFDAN)--a novel domain adaptation framework de

Mohammad-Javad Rezaei, Mozafar Bag-Mohammadi

In this paper, a new metaheuristic optimization algorithm, called Path Construction Imitation Algorithm (PCIA), is proposed. PCIA is inspired by how humans construct new paths and use them. Typically, humans prefer popular transportation routes. In the event of a path closure, a new route is built by mixing the existing paths intelligently. Also, humans sele

Dhruv Deshmukh, Saurabh Goyal, Nipun Kwatra, Ramachandran Ramjee

Attention is the dominant source of latency during long-context LLM inference, an increasingly popular workload with reasoning models and RAG. We propose Kascade, a training-free sparse attention method that leverages known observations such as 1) post-softmax attention is intrinsically sparse, and 2) the identity of high-weight keys is stable across nearby

Maxime Siber, Olivier J. J. Ronsin, Gitti L. Frey, Jens Harting

Tailoring the nanomorphology of organic photoactive layers through a specialized chain of processing steps is an imperative challenge on the path towards reliable and performant organic electronic manufacturing. This hurdle generally proves delicate to be overcome, as organic materials can be subject to many different phase transformation phenomena that are

Li-Chen Huang, Yanshen Li

The Marangoni instability of cylindrical drops in vertical Hele-Shaw cells immersed in stably stratified liquids has been studied previously, yet the underlying mechanism has not been explored thoroughly. Here we study the onset of the Marangoni instability of such a system by experimentally explore the parameter space of the drop radius and concentration gr

Kazuki Nakazawa, Terufumi Yamaguchi, Ai Yamakage

In recent years, counterparts of phenomena studied in spintronics have been actively explored in the orbital sector. The relationship between orbital degrees of freedom and crystal chirality has also been intensively investigated, although the distinction from gyrotropic properties has not been fully clarified. In this work, we investigate spin and orbital E

Zhenjiang Zhao, Takahisa Toda, Takashi Kitamura

This work focuses on quantitative verification of fairness in tree ensembles. Unlike traditional verification approaches that merely return a single counterexample when the fairness is violated, quantitative verification estimates the ratio of all counterexamples and characterizes the regions where they occur, which is important information for diagnosing an

Xiao-Wen Shang, Jian-Peng Dou, Feng Lu, Sen Lin

Quantum tunnelling, a hallmark phenomenon of quantum mechanics, allows particles to pass through the classically forbidden region. It underpins fundamental processes ranging from nuclear fusion and photosynthesis to the operation of superconducting qubits. Yet the underlying dynamics of particle motion during tunnelling remain subtle and are still the subjec

Takuya Kanazawa

Quantifying predictive uncertainty is essential for safe and trustworthy real-world AI deployment. Yet, fully nonparametric estimation of conditional distributions remains challenging for multivariate targets. We propose Tomographic Quantile Forests (TQF), a nonparametric, uncertainty-aware, tree-based regression model for multivariate targets. TQF learns co

Satakshi Pandey, Antoine Barbier, Anne Forget, Brice Sarpi

Rare-earth iron garnet (RE3Fe5O12) films are promising insulating ferrimagnets. They can show low magnetic damping, perpendicular magnetic anisotropy, and ultrafast spin dynamics, which makes them ideal for spin transport applications. In this work, we investigate the interaction between the magnetic sublattices in Er3Fe5O12 thin films grown by pulsed laser

Zhihao Wang, Alessandro Cornacchia, Alessio Sacco, Franco Galante

Agentic systems, powered by Large Language Models (LLMs), assist network engineers with network configuration synthesis and network troubleshooting tasks. For network troubleshooting, progress is hindered by the absence of standardized and accessible benchmarks for evaluating LLM agents in dynamic network settings at low operational effort. We present NIKA,

Stefano Lionetti

Chiral and conformal anomalies are fundamental phenomena that span multiple disciplines, including high-energy physics, condensed matter theory and cosmology. These anomalies play a crucial role in understanding fundamental interactions and manifest themselves through divergences and traces of correlation functions. In this thesis, we investigate these pheno

Manuel G. Satué, Manuel R. Arahal, Luis F. Acedo, Manuel G. Ortega

Economic model predictive control has been proposed as a means for solving the unit loading and unit allocation problem in multi-chiller cooling plants. The adjective economic stems from the use of financial cost due to electricity consumption in a time horizon, such is the loss function minimized at each sampling period. The energetic approach is rarely enc

Sara Papi, Javier Garcia Gilabert, Zachary Hopton, Vilém Zouhar

As Large Language Models (LLMs) expand beyond text, integrating speech as a native modality has given rise to SpeechLLMs, which directly process spoken language and enable speech-to-text translation (ST) and other downstream tasks, bypassing traditional transcription-based pipelines. Whether this integration improves ST quality over established cascaded arch

Selçuk Parlak, Abhishek Kumar, Runhan Li, Maia G. Vergniory

Recently, two unusual features were theoretically predicted for the Raman response of out-of-plane phonons in magnetic two-dimensional materials hosting massive Dirac fermions. First, the phase difference between certain Raman tensor elements was found to be quantized to $\pm \pi/2$, sensitive only to the sign of the Dirac fermion mass. Second, a selection r

Tatsuo Kobayashi, Hajime Otsuka

We study a framework in which fields are labeled by basis elements of a fusion algebra with non-invertible fusion rules. In particular, we consider the case where fields are labeled by conjugacy classes of a finite group rather than its irreducible representations. When the fusion rules possess a $\mathbb{Z}_2$ symmetry identified with charge conjugation, a

Yotham Cohen, Ealeal Bear, Noam Soker

Simulating one-dimensional stellar evolution models with MESA, we show that removing the outer inflated envelope of a mass-accreting evolved stripped-envelope star, like a Wolf-Rayet (WR) star, substantially moderates the stellar expansion during accretion at high-mass accretion rates. We study the accretion onto a star via an accretion disk, which launches

Kensuke Arakawa, Victor Carmona, Francesca Pratali

Given a (colored) operad and a set of unary operations, we can form an associated $\infty$-operad via localization. We show that localization determines an equivalence of homotopy theories of relative operads and $\infty$-operads. As an application, we give an affirmative answer to an open question by Harpaz, proving that Lurie's operadic nerve functor deter

Faisal Ahmed

Magnetic Resonance Imaging (MRI) plays a pivotal role in the early diagnosis and monitoring of Alzheimer's disease (AD). However, the subtle structural variations in brain MRI scans often pose challenges for conventional deep learning models to extract discriminative features effectively. In this work, we propose PseudoColorViT-Alz, a colormap-enhanced Visio

Andrea Vismara, Ola Ali, Carsten Källner, Guillermo Prieto-Viertel

International remittances represent a vital source of disaster adaptation finance for households around the world, yet their responsiveness to environmental disasters remains poorly quantified. We reveal a previously unmeasured global macro-financial system of international migrant diasporas remittances response to the occurrence of disasters in the country

Mariam Hassan, Bastien Van Delft, Wuyang Li, Alexandre Alahi

State-of-the-art Text-to-Video (T2V) diffusion models can generate visually impressive results, yet they still frequently fail to compose complex scenes or follow logical temporal instructions. In this paper, we argue that many errors, including apparent motion failures, originate from the model's inability to construct a semantically correct or logically co

Maxime Siber, Olivier J. J. Ronsin, Jens Harting

The Flory-Huggins theory is a well-established lattice model that is commonly used to study the mixing of distinct chemical species. It can successfully predict phase separation phenomena in blends of incompatible materials. However, it is limited to amorphous mixtures, excluding systems where the phase segregation is shaped by the concurrent crystallization

Moritz Müller-Brus, Lisa Bruder, Caspar Schutijser, Ralph Koning

The RPKI is crucial for securing the routing system of the Internet. With the RPKI, owners of Internet resources can make cryptographically backed claims, for example about the legitimate origin of their IP space. Thousands of networks use this information to detect malicious or accidental route hijacks. The RPKI consists out of 100 distributed repositories.

Sijia Chen, Wei Dong

It's a practical approach using the ground-aerial collaborative system to enhance the localization robustness of flying robots in cluttered environments, especially when visual sensors degrade. Conventional approaches estimate the flying robot's position using fixed cameras observing pre-attached markers, which could be constrained by limited distance and su

Omar Namnakani, Yasmeen Abdrabou, Cristina Fiani, John H. Williamson

Dwell input shows promise for handheld mobile contexts, but its performance is impacted by target size and viewing distance. While fixed target sizes suffice in static setups, in mobile settings, frequent posture changes alter viewing distances, which in turn distort perceived size and hinder dwell performance. We address this through GAUI, a Gaze-based Adap

Mikołaj Sienicki, Krzysztof Sienicki

We read Karen Crowther's \emph{Another 100 Years of Quantum Interpretation?} with two practical goals. First, we spell out what she means by interpretation'': an attempt to provide understanding (not just predictions), which may be representationalist or non-representationalist, and which she contrasts with deeper \emph{reductive} (inter-theoretic) explanati

F. Arevalo-Gonzalez, R. Tripodi, M. Llerena, L. Pentericci

The semi-forbidden CIII] $\lambda\lambda$1907,1909 doublet is a key tracer of high-ionization emission in the early universe. We present a study of CIII] emission in galaxies at z=5-7, using publicly available JWST/NIRSpec prism data from programs including CEERS, JADES, RUBIES and CAPERS. We built a sample of 61 CIII]-emitting galaxies, and we classified th

M. Rodríguez Martín, T. A. Zaleski

Interacting bosons in optical lattices directly expose quantum phases in a clean, highly controllable environment. This requires engineering systems with very low entropies, but the resulting temperature--interaction ratios $T/U$ of present experiments remain well above the domain where zero-temperature theories are expected to be reliable. The quantum-rotor

Guanghui Wang, Mengtao Wen, Changliang Zou

We study inference with a small labeled sample, a large unlabeled sample, and high-quality predictions from an external model. We link prediction-powered inference with empirical likelihood by stacking supervised estimating equations based on labeled outcomes with auxiliary moment conditions built from predictions, and then optimizing empirical likelihood un

Rositsa Miteva

The aim of the present report is to outline the observational methods used to determine the solar origin - in terms of flares and coronal mass ejections (CMEs) - of the in situ observed solar energetic protons. Several widely used guidelines are given and different sources of uncertainties are summarized and discussed. In the present study, a new quality fac

Markus Janson, Enric Palle, Thomas Henning, Sascha Quanz

The ELT will provide groundbreaking science across a wide range of areas, including small habitable-zone exoplanets; however, true Earth analogs in the habitable zones of Sun-like stars are generally beyond the reach even of the ELT, due to the extreme contrast ratio and small angular separation between the planet and star. Here, we note that the combination

Haotian Ling, Zequn Chen, Qiuying Chen, Donglin Di

Consistent pose-driven character animation has achieved remarkable progress in single-character scenarios. However, extending these advances to multi-character settings is non-trivial, especially when position swap is involved. Beyond mere scaling, the core challenge lies in enforcing correct Identity Correspondence (IC) between characters in reference and g

Amelie Porfetye, Zhuyan Tang, Shaoshuai Chu, Christiane Helzel

We propose new fully discrete third-order accurate Active Flux and WENO methods based on truly multidimensional evolution operators for the two-dimensional acoustic equations. Building on the method of bicharacteristics, several approximate evolution operators are derived that yield an improved stability of the resulting schemes. A linear stability analysis

Florian Pausinger

The sequence $A067549$ of The On-Line Encyclopedia of Integer Sequences is defined as $(a_k)_{k \geq 1}$ with $a_k$ being the determinant of the $k \times k$ matrix whose diagonal contains the first $k$ prime numbers and all other elements are ones. We relate this sequence to a concrete counting problem. Choose an arbitrary residue class $r_i$ for each prime

Manuel R. Arahal, Manuel G. Satué, Manuel G. Ortega

Scheduling and loading of chillers in a multi-chiller plant is considered. A new framework is introduced considering an extended set of independent variables for the optimization problem of energy consumption. In this way the number of decision variables is increased, providing extra degrees of freedom to optimize cooling plant operation. The dynamic effects

Jeannette Jansen, Olga Sokol, Yolanda Prezado, Marco Durante

Accelerated charged particles offer significant physical advantages over X-rays in radiotherapy. In addition to their superior depth-dose distribution, heavy ions provide notable biological benefits compared to protons. Specifically, at therapeutic energies, very heavy ions are expected to exhibit high relative biological effectiveness and a low oxygen enhan

Severin Barmeier, Sibylle Schroll, Zhengfang Wang

We give a complete description of the A$_\infty$ deformation theory of partially wrapped Fukaya categories of graded surfaces. We show that any abstract A$_\infty$ deformation is "geometric", namely it is equivalent to the partially wrapped Fukaya category of an orbifold surface obtained as a partial compactification of the original surface. For certain genu

Francisco J. Suárez-Grau

We consider a micropolar fluid flow in a media perforated by periodically distributed obstacles of size $\varepsilon$. A non-homogeneous boundary condition for microrotation is considered: the microrotation is assumed to be proportional to the rotation rate of the velocity on the boundary of the obstacles. The existence and uniqueness of solution is analyzed

Anshu Kumar, Kemi Olimba, Vyacheslav Kungurtsev, Fabio V. Difonzo

Computational fluid dynamics (CFD) has become a cornerstone of modern water engineering, providing quantitative tools for the analysis, prediction, and management of complex hydraulic systems across a wide range of spatial and temporal scales. This survey reviews the mathematical models and numerical methods that underpin CFD applications in water engineerin

Lingfang Wang, Tianyou Tang, Huizong Zhu, Juanjuan Lu

We demonstrate, for the first time, supercontinuum generation spanning more than three octaves in dispersion-engineered thin-film lithium tantalate (TFLT) waveguides. Pumped by a femtosecond laser at 1560 nm, the waveguides yield a spectrum from 240 nm in the ultraviolet to beyond 2400 nm in the near-infrared. The spectral evolution is mapped from low-power

Shayan Azizi, Norihiro Okui, Masataka Nakahara, Ayumu Kubota

Identifying devices such as cameras, printers, voice assistants, or health monitoring sensors, collectively known as the Internet of Things (IoT), within a network is a critical operational task, particularly to manage the cyber risks they introduce. While behavioral fingerprinting based on network traffic analysis has shown promise, most existing approaches

The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, A. G. Abac

Gravitational waves can be gravitationally lensed by massive objects along their path. Depending on the lens mass and the lens--source geometry, this can lead to the observation of a single distorted signal or multiple repeated events with the same frequency evolution. We present the results for gravitational-wave lensing searches on the data from the first

Shaoshuai Chu, Alexander Kurganov, Maria Lukacova-Medvidova, Mingye Na

We introduce a locally divergence-free local characteristic decomposition based path-conservative central-upwind (LCD-PCCU) scheme for ideal magnetohydrodynamics (MHD) equations. The proposed method is a low-dissipation extension of the recently proposed locally divergence-free PCCU scheme. To reduce the numerical dissipation, we incorporate the LCD into the

Zonglin Liu, Kyra Borchhardt, Olaf Stursberg

This paper provides conditions to ensure contractive behavior of Filippov solutions generated by multi-modal piecewise smooth (PWS) systems. These conditions are instrumental in analyzing the asymptotic behavior of PWS systems, such as convergence towards an equilibrium point or a limit cycle. The work is motivated by a known principle for contraction analys

Peter Coveney, Roger Highfield

Artificial intelligence (AI) is commonly depicted as transformative. Yet, after more than a decade of hype, its measurable impact remains modest outside a few high-profile scientific and commercial successes. The 2024 Nobel Prizes in Chemistry and Physics recognized AI's potential, but broader assessments indicate the impact to date is often more promotional

Kai Hong Law

A selection of new results from the CMS experiment is presented. These results focus on searches for dark-sector particles using Run 2 or Run 3 data. Dedicated data streams were utilised to explore the low-mass parameter space. Machine learning techniques were employed to discriminate between signal and background.

Christian Attiogbé

Rigorous modelling of natural and industrial systems still conveys various challenges related to abstractions, methods to proceed with and easy-to-use tools to build, compose and reason on models. Operads are mathematical structures that provide such abstractions to compose various objects and garanteeing well-formedness. Concrete implementations of operads

Chang-Yu Guo, Ming-Lun Liu, Chang-Lin Xiang

In a recent interesting work [15], W.Y. He established the important partial regularity theory and the almost optimal higher regularity theory for energy minimizing harmonic almost complex structures. Based on a new observation on the structure of equations, we give an easier new proof of the partial regularity theorem, and adapting the powerful quantitative

Louise Linsell, Noman Paracha, Jamie Grossman, Carsten Bokemeyer

Objectives To investigate the use of a Bayesian joint modelling approach to predict overall survival (OS) from immature clinical trial data using an intermediate biomarker. To compare the results with a typical parametric approach of extrapolation and observed survival from a later datacut. Methods Data were pooled from three phase I/II open-label trials eva

Lin Zhang, Zhe Cao, Jianhua Liu, Nees Jan van Eck

OpenAlex, launched in 2022 as a fully open scholarly data source, promises greater inclusiveness compared to traditional proprietary databases. This study evaluates whether OpenAlex delivers on that promise by examining its coverage and metadata quality for Chinese-language journals and their articles. Using the 2023 edition of A Guide to the Core Journals o

Edwin Baum, Zonglin Liu, Yuzhen Qin, Olaf Stursberg

This paper investigates contraction properties of switched dynamical systems for the case that all modes are non-contracting, thereby extending existing results that require at least one mode to be contracting. Leveraging the property that unstable systems may still exhibit stable behavior within certain subspaces, conditions are provided which ensure contra

Nikoloz Kurtskhalia, Nikolai Maltsev, Zaza N. Osmanov

We examine the motion of an electron constrained to follow a magnetic field line near a primordial sub-stellar mass black hole. Earlier studies treated the problem in flat (Minkowski) spacetime, yielding qualitatively correct results and introducing a light cylinder (LC), a hypothetical surface where the linear velocity of rotation equals the speed of light.

J. A. Christen, F. J. Rubio

The hazard function is central to the formulation of commonly used survival regression models such as the proportional hazards and accelerated failure time models. However, these models rely on a shared baseline hazard, which, when specified parametrically, can only capture limited shapes. To overcome this limitation, we propose a general class of parametric

Yibiao Yang, Qingyang Li, Maolin Sun, Jiangchang Wu

Background: Compilers are fundamental to software development, translating high-level source code into executable software systems. Faults in compilers can have severe consequences and thus effective localization and resolution of compiler bugs are crucial. Problem: In practice, developers often examine version history to identify and investigate bug-inducin

Rawan Hoteit, Andrea Balestra, Nathan Mingard, Efe C. Balta

Various defects occur during material extrusion additive manufacturing processes that degrade the quality of the 3D printed parts and lead to significant material waste. This motivates feedback control of the extrusion process to mitigate defects and prevent print failure. We propose a linear quadratic regulator (LQR) for closed-loop control with force feedb