December 2024 arXiv papers — page 175

Turgay Akyar

In this paper we examine the topology of Brill-Noether varieties associated to real trigonal curves. More precisely, we aim to count the connected components of the real locus of the varieties parametrizing linear systems of degree $d$ and dimension at least $r$. We do this count when the relations $m=g-d+r-1\leq d-2r-1$ are satisfied, where $m$ is the Maron

Serhii Svystun, Oleksandr Melnychenko, Pavlo Radiuk, Oleg Savenko

The inspection of wind turbine blades (WTBs) is crucial for ensuring their structural integrity and operational efficiency. Traditional inspection methods can be dangerous and inefficient, prompting the use of unmanned aerial vehicles (UAVs) that access hard-to-reach areas and capture high-resolution imagery. In this study, we address the challenge of enhanc

Jiayu Liu, Yong Wang, Nianbin Wang, Jing Yang

Federated Learning (FL) is an innovative distributed machine learning paradigm that enables neural network training across devices without centralizing data. While this addresses issues of information sharing and data privacy, challenges arise from data heterogeneity across clients and increasing network scale, leading to impacts on model performance and tra

Erlend Storvik, Carina Bringedal

In this letter, we derive the sharp-interface limit of the Cahn-Hilliard-Biot equations using formal matched asymptotic expansions. We find that in each sub-domain, the quasi-static Biot equations are obtained with domain-specific material parameters. Moreover, across the interface, material displacement and pore pressure are continuous, while volumetric flu

Abhijeet Parida, Daniel Capellán-Martín, Zhifan Jiang, Austin Tapp

Gliomas, a kind of brain tumor characterized by high mortality, present substantial diagnostic challenges in low- and middle-income countries, particularly in Sub-Saharan Africa. This paper introduces a novel approach to glioma segmentation using transfer learning to address challenges in resource-limited regions with minimal and low-quality MRI data. We lev

Jiajun Chen, Yik-Cheung Tam

We propose utilizing background operators for mathematical reasoning in large language models (LLMs). To achieve this, we define a set of fundamental mathematical predicates as the basic building blocks. For each mathematical problem, we develop a Prolog solution that includes problem-specific predicates and intermediate predicates derived from these backgro

Yael Travis-Lumer, Micha Mandel, Rebecca A. Betensky

The pseudo-observations approach has been gaining popularity as a method to estimate covariate effects on censored survival data. It is used regularly to estimate covariate effects on quantities such as survival probabilities, restricted mean life, cumulative incidence, and others. In this work, we propose to generalize the pseudo-observations approach to si

Xie He, Jiaqi Zheng, Dace Su, Jianwei Ying

The precision measurement of real-time electron temporal profiles is crucial for advancing electron and X-ray devices used in ultrafast imaging and spectroscopy. While high temporal resolution and large temporal window can be achieved separately using different technologies, real-time measurement enabling simultaneous high resolution and large window remains

Yuhao Wang, Junwei Pan, Pengyue Jia, Wanyu Wang

Sequential Recommendation (SR) aims to leverage the sequential patterns in users' historical interactions to accurately track their preferences. However, the primary reliance of existing SR methods on collaborative data results in challenges such as the cold-start problem and sub-optimal performance. Concurrently, despite the proven effectiveness of large la

Philipp S. Joschko, J. M. Diederik Kruijssen, Sebastian Trujillo-Gomez, Joel L. Pfeffer

We present a comprehensive analysis of globular cluster (GC) formation and evolution across the $34^3$ Mpc$^3$ volume of the E-MOSAICS galaxy formation simulations. Defining GCs as surviving, high-mass ($>10^5$ M$_\odot$) clusters, we analyse their formation histories as a function of their metallicity and host galaxy mass, also distinguishing between centra

Franck Laloë

We revisit an argument proposed by Hardy \cite{Hardy-1} concerning local realistic theories, but in terms of the motion of the probability fluid and its current within standard quantum mechanic. We emphasize surprising properties of the flux lines of this current in configuration space, in particular (quasi) discontinuous variations when the context (the exp

Karthik V, Amal Medhi

We consider a restricted Boltzmann Machine (RBM) correlated BCS wave function as the ground state of the two-dimensional Hubbard model and study its electronic and magnetic properties as a function of hole doping. We compare the results with those obtained by using conventional Jastrow projectors. The results show that the RBM wave function outperforms the J

Jonas H. Fritz, Benjamin Ertel, Udo Seifert

Estimating entropy production from real observation data can be difficult due to finite resolution in both space and time and finite measurement statistics. We characterize the statistical error introduced by finite sample size and compare the performance of three different entropy estimators under these limitations for two different paradigmatic systems, a

Eugene Wu

We draw a connection between data modeling and visualization, namely that a visualization specification defines a mapping from database constraints to visual representations of those constraints. Using this formalism, we show how many visualization design decisions are, in fact, data modeling choices and extend data visualization from single-dataset visualiz

Atharva Mehta, Shivam Chauhan, Monojit Choudhury

Recent advances in generative AI have sparked renewed interest and expanded possibilities for music generation. However, the performance and versatility of these systems across musical genres are heavily influenced by the availability of training data. We conducted an extensive analysis of over one million hours of audio datasets used in AI music generation

M. Rahimi, C. L. Reichardt

Since the first detection by the DASI experiment in 2002, measurements of the polarization of the cosmic microwave background (CMB) have grown into an important role in testing our understanding of conditions in the early universe and cosmology. The field has seen rapid experimental progress, driven in large part by the desire to make increasingly precise me

Eyad Gomaa, Gomaa Salah

We present Quasar-1, a novel architecture that introduces temperature-guided reasoning to large language models through the Token Temperature Mechanism (TTM) and Guided Sequence of Thought (GSoT). Our approach leverages the concept of hot and cold tokens, where hot tokens are prioritized for their contextual relevance, while cold tokens provide supplementary

Joseph Alec Wilcox, Lukas Schneider, Estefani Marchiori, Vadim Plastovets

Ferromagnetic superconductors are exceptionally rare because the strong ferromagnetic exchange field usually destroys singlet superconductivity. EuFe$_2$(As$_{1-x}$P$_x$)$_2$, an iron-based superconductor with a maximum critical temperature of 25 K, uniquely exhibits full coexistence with ferromagnetic order below $T_\mathrm{FM}$ $\simeq$ $19$ K. The interpl

Meenakshi Gupta, Mingyuan Lei, Tat-Jen Cham, Hwee Kuan Lee

This paper introduces a novel framework named D-LORD (Double Latent Optimization for Representation Disentanglement), which is designed for motion stylization (motion style transfer and motion retargeting). The primary objective of this framework is to separate the class and content information from a given motion sequence using a data-driven latent optimiza

O. Petruk, M. Patrii, T. Kuzyo, A. Baldyniuk

The three-dimensional velocity structure of the shock-heated Si-reach and S-reach ejecta were reconstructed in Tycho supernova remnant from Doppler-shifted lines. The vector components along the line of sight were restored from the spatially resolved spectral analysis of the Doppler shifts of Si XIII and S XV lines. The components in the plane of the sky wer

Hamid Gadirov, Qi Wu, David Bauer, Kwan-Liu Ma

We present HyperFLINT (Hypernetwork-based FLow estimation and temporal INTerpolation), a novel deep learning-based approach for estimating flow fields, temporally interpolating scalar fields, and facilitating parameter space exploration in spatio-temporal scientific ensemble data. This work addresses the critical need to explicitly incorporate ensemble param

Zhifan Jiang, Daniel Capellán-Martín, Abhijeet Parida, Austin Tapp

Accurate and automatic segmentation of brain tumors in multi-parametric magnetic resonance imaging (mpMRI) is essential for quantitative measurements, which play an increasingly important role in clinical diagnosis and prognosis. The International Brain Tumor Segmentation (BraTS) Challenge 2024 offers a unique benchmarking opportunity, including various type

Chris Sypherd, Vaishak Belle

As the strength of Large Language Models (LLMs) has grown over recent years, so too has interest in their use as the underlying models for autonomous agents. Although LLMs demonstrate emergent abilities and broad expertise across natural language domains, their inherent unpredictability makes the implementation of LLM agents challenging, resulting in a gap b

Bram Vanroy

Language models have rapidly evolved, predominantly focusing on English while often neglecting extensive pretraining in other languages. This approach has required initiatives to adapt powerful, English-centric models to other linguistic contexts through finetuning. For Dutch, such a recent endeavour is ``GEITje'' a model originally derived from the English-

Haowen Chen, Yuhang Li, Benjamin Böhm, Tao Li

Particle velocimetry is essential in solid fuel combustion studies, however, the accurate detection and tracking of particles in high Particle Number Density (PND) combustion scenario remain challenging. The current study advances the machine-learning approaches for precise velocity measurements of solid particles. For this, laser imaging experiments were pe

Bingchen Li, Xin Li, Yiting Lu, Zhibo Chen

We present the first loss agent, dubbed LossAgent, for low-level image processing tasks, e.g., image super-resolution and restoration, intending to achieve any customized optimization objectives of low-level image processing in different practical applications. Notably, not all optimization objectives, such as complex hand-crafted perceptual metrics, text de

Hanamichi Kawamura, Anju Yokoi

Ohno-Wakabayashi's cyclic sum formula for multiple zeta-star values is generalized by Igarashi with one or two parameters. In this article, we give a possible answer for one of his problems about a generalization with three parameters.

Mohit Singh Bisht, A. Raj, F. M. Walter, D. Bisht

In this work, optical observations of the nova V5584 Sgr are presented. These observations cover different phases including pre-maximum, early decline, and nebular. The spectra are dominated by hydrogen Balmer, Fe II, and O I lines with P-Cygni profiles in the early phase, which are subsequently observed in complete emission. The presence of numerous Fe II l

Ivan I. Vrubel, Evgeniia D. Cherotchenko, Ksenia V. Kusakina, Saausan H. Abdulrazak

In this work, we provide a simplified theoretical analytical estimation of the quantum cascade laser build-up time, accurately taking into account the main effects: the QCL overheating during the pump pulse and the photon mode filling effect. The non-trivial interplay of the mentioned effects brings about a variety of possible experimental build-up time beha

Nefeli Andreou, Varsha Vivek, Ying Wang, Alex Vorobiov

Accurately generating images of human bodies from text remains a challenging problem for state of the art text-to-image models. Commonly observed body-related artifacts include extra or missing limbs, unrealistic poses, blurred body parts, etc. Currently, evaluation of such artifacts relies heavily on time-consuming human judgments, limiting the ability to b

Chon-Fai Kam, Xuedong Hu

By analytically solving the quantum Rabi model, we investigate the photonic properties of its ground eigenstate. In particular, we find that in the deep strong coupling regime, where the coupling strength $g$ exceeds the mode frequency $\omega$, the photonic state is effectively squeezed in one of its quadratures. The squeezing reaches its maximum at the cur

Jianing Hao, Manling Yang, Qing Shi, Yuzhe Jiang

Graphical overlays that layer visual elements onto charts, are effective to convey insights and context in financial narrative visualizations. However, automating graphical overlays is challenging due to complex narrative structures and limited understanding of effective overlays. To address the challenge, we first summarize the commonly used graphical overl

Serafim S. Babkin, Benjamin Joecker, Karsten Flensberg, Maksym Serbyn

Technology involving hybrid superconductor-semiconductor materials is a promising avenue for engineering quantum devices for information storage, manipulation, and transmission. Proximity-induced superconducting correlations are an essential part of such devices. While the proximity effect in the conduction band of common semiconductors is well understood, i

Hirunima Jayasekara, Khoi Pham, Nirat Saini, Abhinav Shrivastava

Open-World Compositional Zero-Shot Learning (OW-CZSL) addresses the challenge of recognizing novel compositions of known primitives and entities. Even though prior works utilize language knowledge for recognition, such approaches exhibit limited interactions between language-image modalities. Our approach primarily focuses on enhancing the inter-modality int

Wenlong Lyu, Yuheng Jia

Symmetric nonnegative matrix factorization (SymNMF) is a powerful tool for clustering, which typically uses the $k$-nearest neighbor ($k$-NN) method to construct similarity matrix. However, $k$-NN may mislead clustering since the neighbors may belong to different clusters, and its reliability generally decreases as $k$ grows. In this paper, we construct the

Nikolaos Pavlidis, Vasileios Perifanis, Selim F. Yilmaz, Francesc Wilhelmi

The increasing demand for efficient resource allocation in mobile networks has catalyzed the exploration of innovative solutions that could enhance the task of real-time cellular traffic prediction. Under these circumstances, federated learning (FL) stands out as a distributed and privacy-preserving solution to foster collaboration among different sites, thu

Yi-Bao Zhang, Yaning Fan, Jinghong Su, Heng-Dong Xi

We present an experimental study on the drag reduction by polymers in Taylor-Couette turbulence at Reynolds numbers ($Re$) ranging from $4\times 10^3$ to $2.5\times 10^4$. In this $Re$ regime, the Taylor vortex is present and accounts for more than 50\% of the total angular velocity flux. Polyacrylamide polymers with two different average molecular weights a

Chantal Tinner, André Galli, Fiona Bär, Antoine Pommerol

Irradiation by energetic ions, electrons, and UV photons induces sputtering and chemical processes (radiolysis) in the surfaces of icy moons, comets, and icy grains. Laboratory experiments, both of ideal surfaces and of more complex and realistic analog samples, are crucial to understand the interaction of surfaces of icy moons and comets with their space en

Shicheng Zhou, Jingju Liu, Yuliang Lu, Jiahai Yang

With increasing numbers of vulnerabilities exposed on the internet, autonomous penetration testing (pentesting) has emerged as a promising research area. Reinforcement learning (RL) is a natural fit for studying this topic. However, two key challenges limit the applicability of RL-based autonomous pentesting in real-world scenarios: (a) training environment

Seokju Yun, Seunghye Chae, Dongheon Lee, Youngmin Ro

Domain generalization (DG) aims to adapt a model using one or multiple source domains to ensure robust performance in unseen target domains. Recently, Parameter-Efficient Fine-Tuning (PEFT) of foundation models has shown promising results in the context of DG problem. Nevertheless, existing PEFT methods still struggle to strike a balance between preserving g

Weihua Wang, Qiuyu Liang, Feilong Bao, Guanglai Gao

Quaternion contains one real part and three imaginary parts, which provided a more expressive hypercomplex space for learning knowledge graph. Existing quaternion embedding models measure the plausibility of a triplet either through semantic matching or geometric distance scoring functions. However, it appears that semantic matching diminishes the separabili

Yoav Kan-Tor, Michael Morris Danziger, Eden Zohar, Matan Ninio

The application of deep learning methods, particularly foundation models, in biological research has surged in recent years. These models can be text-based or trained on underlying biological data, especially omics data of various types. However, comparing the performance of these models consistently has proven to be a challenge due to differences in trainin

Xiaowen Ye, Yuyi Mao, Xianghao Yu, Shu Sun

This paper studies an integrated sensing and communications (ISAC) system for low-altitude economy (LAE), where a ground base station (GBS) provides communication and navigation services for authorized unmanned aerial vehicles (UAVs), while sensing the low-altitude airspace to monitor the unauthorized mobile target. The expected communication sum-rate over a

A. Enes Doruk, Erhan Oztop, Hasan F. Ates

Unsupervised Domain Adaptation (UDA) aims to utilize labeled data from a source domain to solve tasks in an unlabeled target domain, often hindered by significant domain gaps. Traditional CNN-based methods struggle to fully capture complex domain relationships, motivating the shift to vision transformers like the Swin Transformer, which excel in modeling bot

Mingcheng Qu, Yuncong Wu, Donglin Di, Anyang Su

Spatial transcriptomics (ST) has emerged as an advanced technology that provides spatial context to gene expression. Recently, deep learning-based methods have shown the capability to predict gene expression from WSI data using ST data. Existing approaches typically extract features from images and the neighboring regions using pretrained models, and then de

Gali Shmueli, Sarah Libanore, Ely D. Kovetz

Accurately determining neutrino masses is a main objective of contemporary cosmology. Since massive neutrinos affect structure formation and evolution, probes of large scale structure are sensitive to the sum of their masses. In this work, we explore future constraints on $\sum m_\nu$ utilizing line-intensity mapping (LIM) as a promising emerging probe of th

Celsa Pardo Araujo, Michele Ronchi, Vanessa Graber, Nanda Rea

The properties of the entire neutron star population can be inferred by modeling their evolution, from birth to the present, through pulsar population synthesis. This involves simulating a mock population, applying observational filters, and comparing the resulting sources to the limited subset of detected pulsars. We specifically focus on the magneto-rotati

Xiao-Yu Guo, Yi-Fan Li, Yuan Liu, Xiaoyong Pan

Protein design has become a critical method in advancing significant potential for various applications such as drug development and enzyme engineering. However, protein design methods utilizing large language models with solely pretraining and fine-tuning struggle to capture relationships in multi-modal protein data. To address this, we propose ProtDAT, a d

J. Otero-Santos, C. M. Raiteri, A. Tramacere, J. Escudero Pedrosa

The BL Lac object 3C 371 is one of the targets that are regularly monitored by the Whole Earth Blazar Telescope (WEBT) Collaboration to study blazar variability on both short and long timescales. We aim to evaluate the long-term multiwavelength (MWL) behaviour of 3C 371, comparing it with the results derived for its optical emission in our previous study. Fo

Amnon Bleich, Antje Linnemann, Bjoern H. Diem, Tim OF Conrad

Recent advances in deep learning and natural language generation have significantly improved image captioning, enabling automated, human-like descriptions for visual content. In this work, we apply these captioning techniques to generate clinician-like interpretations of ECG data. This study leverages existing ECG datasets accompanied by free-text reports au

Attila Jung, Dömötör Pálvölgyi

We prove that fractional Helly and $(p,q)$-theorems imply $(\aleph_0,q)$-theorems in an entirely abstract setting. We give a plethora of applications, including reproving almost all earlier $(\aleph_0,q)$-theorems about geometric hypergraphs that were proved recently. Some of the corollaries are new results, for example, we prove that if $\mathcal{F}$ is an

Zeel B Patel, Rishabh Mondal, Shataxi Dubey, Suraj Jaiswal

Air pollution kills 7 million people annually. The brick kiln sector significantly contributes to economic development but also accounts for 8-14\% of air pollution in India. Policymakers have implemented compliance measures to regulate brick kilns. Emission inventories are critical for air quality modeling and source apportionment studies. However, the larg

Arseny Skryagin, Felix Divo, Mohammad Amin Ali, Devendra Singh Dhami

Graph Neural Networks (GNNs) are non-Euclidean deep learning models for graph-structured data. Despite their successful and diverse applications, oversmoothing prohibits deep architectures due to node features converging to a single fixed point. This severely limits their potential to solve complex tasks. To counteract this tendency, we propose a plug-and-pl

Kevin Benson, Ing-Haw Cheng, John Hull, Charles Martineau

We study the drivers of the Gilchrist and Zakraj\v{s}ek (2012) excess bond premium (EBP) through the lens of the news. The monthly attention the news pays to 180 topics (Bybee et al., 2024) captures up to 80% of the variation in the EBP, and this component of variation forecasts macroeconomic movements. Greater news attention to financial intermediaries and

Yefei He, Feng Chen, Yuanyu He, Shaoxuan He

In this paper, we propose ZipAR, a training-free, plug-and-play parallel decoding framework for accelerating auto-regressive (AR) visual generation. The motivation stems from the observation that images exhibit local structures, and spatially distant regions tend to have minimal interdependence. Given a partially decoded set of visual tokens, in addition to

Charlotte Dietze, Konstantin Pankrashkin

Let $\Omega\subset\mathbb{R}^n$ with $n\ge 2$ be a bounded Lipschitz domain with outer unit normal $\nu$. For $\alpha\in\mathbb{R}$ let $R_\Omega^\alpha$ be the Laplacian in $\Omega$ with the Robin boundary condition $\partial_\nu u+\alpha u=0$, and denote by $E(R^\alpha_\Omega)$ its principal eigenvalue. In 2017 Bucur, Freitas and Kennedy stated the followi

Gaole Dai, Huatao Xu, Yifan Yang, Rui Tan

Expanding existing learning systems to provide high-quality customized models for more domains, such as new users, is challenged by the limited labeled data and the data and device heterogeneities. While knowledge distillation methods could overcome label scarcity and device heterogeneity, they assume the teachers are fully reliable and overlook the data het

G. Stratta, A. M. Nicuesa Guelbenzu, S. Klose, A. Rossi

GRB 191019A was a long Gamma-ray burst (GRB) lasting about 65 s and, as such, originally thought to be linked to a core-collapse supernova. However, even though follow-up observations identified the optical counterpart close to the bright nucleus of a nearby ancient galaxy (z=0.248), no associated supernova was found. This led to the suggestion that the burs

Nikola Sadovek, Pablo Soberón

In this paper, we prove a result on the bisection of mass assignments by parallel hyperplanes on Euclidean vector bundles. Our methods consist of the development of a novel lifting method to define the configuration space--test map scheme, which transforms the problem to a Borsuk--Ulam-type question on equivariant fiber bundles, along with a new computation

Manuel Eberhardinger, James Goodman, Alexander Dockhorn, Diego Perez-Liebana

Large language models (LLMs) have shown impressive capabilities in generating program code, opening exciting opportunities for applying program synthesis to games. In this work, we explore the potential of LLMs to directly synthesize usable code for a wide range of gaming applications, focusing on two programming languages, Python and Java. We use an evoluti

Siamak Khatami, Christopher Frantz

This document contains detailed information about the prompts used in the experimental process discussed in the paper "Toward Automating Agent-based Model Generation: A Benchmark for Model Extraction using Question-Answering Techniques". The paper aims to utilize Question-answering (QA) models to extract the necessary information to implement Agent-based Mod

Andrzej Bis, Henk Bruin

In 2007, Ye \& Zhang introduced a version of local topological entropy. Since their entropy function is, as we show under mild conditions, constant for topologically transitive dynamical systems, we propose to adjust the notion in a way that does not neglect the initial transient part of an orbit. We investigate the properties of this ``transient'' version,

Gaurav Sharma, P R Kumar

In this paper, we consider the problem of preferentially utilizing intermittent renewable power, such as wind, optimally to support thermal inertial loads in a microgrid environment. Thermal inertial loads can be programmed to preferentially consume from renewable sources. The flexibility in power consumption of inertial loads therefore can be used to absorb

Aniket Chatterjee, Jonathan Schwinger, Yvonne Y. Gao

Measurement is an essential component of robust and practical quantum computation. For superconducting qubits, the measurement process involves the effective manipulation of the joint qubit-resonator dynamics, and it should ideally provide the highest quality for qubit state discrimination with the shortest readout pulse and resonator reset time. Here, we ha

Yongliang Wang, Hamidreza Kasaei

Robotic grasping in densely cluttered environments is challenging due to scarce collision-free grasp affordances. Non-prehensile actions can increase feasible grasps in cluttered environments, but most research focuses on single-arm rather than dual-arm manipulation. Policies from single-arm systems fail to fully leverage the advantages of dual-arm coordinat

Makan Rafiee, Lars Hupel

Central Bank Digital Currency (CBDC) is a new form of money, issued by a country's or region's central bank, that can be used for a variety of payment scenarios. Depending on its concrete implementation, there are many participants in a production CBDC ecosystem, including the central bank, commercial banks, merchants, individuals, and wallet providers. Ther

Xiaoxu Dai, Bo Qian, Arkadz Kirshtein, Qingcheng Yang

In the manufacturing process of high-performance particulate materials, viscous sintering plays a crucial role, particularly in fields such as polymer processing and additive manufacturing. The interactions between microscopic particles, their flow behavior, and the evolution of porosity during the viscous sintering process directly influence the material's

Junichi Harada

This paper investigates the asymptotic behavior of solutions to $u_t=\Delta u+|u|^{p-1}u$ in the Sobolev critical case. Our main result is a classification of the dynamics near the ground states in the six dimensional case. It is shown that if the initial data $u_0\in H^1(\mathbb{R}^6)$ satisfies $\|u_0-{\sf Q}\|_{\dot H^1(\mathbb{R}^6)}\ll1$, then the solut

Sascha Mücke, Felix Finkeldey, Nico Piatkowski, Tobias Siebrecht

In this article, we propose a novel quantum regression model by extending the Real-Part Quantum SVM. We apply our model to the problem of stability limit prediction in milling processes, a key component in high-precision manufacturing. To train our model, we use a custom data set acquired by an extensive series of milling experiments using different spindle

Alessandro De Gregorio, Francesco Iafrate

Sparse parametric models are of great interest in statistical learning and are often analyzed by means of regularized estimators. Pathwise methods allow to efficiently compute the full solution path for penalized estimators, for any possible value of the penalization parameter $\lambda$. In this paper we deal with the pathwise optimization for bridge-type pr

Mugdha Pandya, Mali Jin, Kalina Bontcheva, Diana Maynard

Numerous politicians use social media platforms, particularly X, to engage with their constituents. This interaction allows constituents to pose questions and offer feedback but also exposes politicians to a barrage of hostile responses, especially given the anonymity afforded by social media. They are typically targeted in relation to their governmental rol

Alexandros Menelaos Tzortzis, Georgios Kormpakis, Sotiris Pelekis, Ariadni Michalitsi-Psarrou

AI4EF, Artificial Intelligence for Energy Efficiency, is an advanced, user-centric tool designed to support decision-making in building energy retrofitting and efficiency optimization. Leveraging machine learning (ML) and data-driven insights, AI4EF enables stakeholders such as public sector representatives, energy consultants, and building owners to model,

Karol Kozioł, Jacek Rzadkiewicz

High-accuracy Multi-Configuration Dirac-Hartree-Fock with Configuration Interaction calculations of level energies and transition rates have been carried out for iodine $I^{8+}$ through $I^{12+}$ ions related to the [Kr]4d$^n$ ($n$ = 5-9) configurations. For $I^{10+}$ through $I^{12+}$ ions the present data fill up the lack of such data in the literature.

Dianhong Dong, Hushan Wang, Bing Xue, Kotaro Imasaka

The generation of gigawatt-class isolated attosecond pulses (IAPs) is vital for attosecond pump-probe experiments. In such experiments, the temporal duration of IAPs must be determined quickly and accurately. In this study, we developed a perturbed three-channel waveform synthesizer for efficient IAPs generation and characterization at low repetition rates (

Yasuaki Kobayashi, Yuto Okada, Alexander Wolff

The crossing number of a graph is the least number of crossings over all drawings of the graph in the plane. Computing the crossing number of a given graph is NP-hard, but fixed-parameter tractable (FPT) with respect to the natural parameter. Two well-known variants of the problem are 2-layer crossing minimization and circular crossing minimization, where ev

Le Qiu, Emmanuele Chersoni

Technical analysis in finance, which aims at forecasting price movements in the future by analyzing past market data, relies on the insights that can be gained from the interpretation of stock charts; therefore, non-expert investors could greatly benefit from AI tools that can assist with the captioning of such charts. In our work, we introduce a new dataset

T. Möller, P. Schilke, Á. Sánchez-Monge, A. Schmiedeke

The giant molecular cloud complex Sagittarius B2 (Sgr~B2) in the central molecular zone of our Galaxy hosts several high-mass star formation sites, with Sgr~B2(M) and Sgr~B2(N) being the main centers of activity. This analysis aims to comprehensively model each core spectrum, considering molecular lines, dust attenuation, and free-free emission interactions.

Sofia Sartore, Franziska Teichmann, Gerhard Stock

When clustering molecular dynamics (MD) trajectories into a few metastable conformational states, the Markov state models (MSMs) assumption of timescale separation between fast intrastate fluctuations and rarely occurring interstate transitions is often not valid. Hence, the naive estimation of the macrostate transition matrix via simply counting transitions

Yiping Li, Romy van Jaarsveld, Ronald de Jong, Jasper Bongers

Robotic-assisted minimally invasive esophagectomy (RAMIE) is a recognized treatment for esophageal cancer, offering better patient outcomes compared to open surgery and traditional minimally invasive surgery. RAMIE is highly complex, spanning multiple anatomical areas and involving repetitive phases and non-sequential phase transitions. Our goal is to levera

Christina Surulescu, Michael Winkler

We propose a mathematical model for tumor invasion supported by angiogenesis and interactions with the surrounding tissue. For the model deduction we employ a multiscale approach starting from lower scales and obtaining by an informal parabolic upscaling a system of reaction-diffusion-taxis equations with a so-called 'taxis cascade', where one species is per

Charul Rathod, M. Mishra, Prasanta Kumar Das, Captain R. Singh

The present study explores the thermal evolution and emission properties of neutron stars within the framework of modified $f(R, T)$ gravity by solving the coupled energy-balance and heat-transport equations. We compute stellar mass and pressure profiles by solving the Tolman-Oppenheimer-Volkoff equations in both Einstein gravity and modified gravity, employ

Yongming Zhu, Longhao Zhang, Zhengkun Rong, Tianshu Hu

Imagine having a conversation with a socially intelligent agent. It can attentively listen to your words and offer visual and linguistic feedback promptly. This seamless interaction allows for multiple rounds of conversation to flow smoothly and naturally. In pursuit of actualizing it, we propose INFP, a novel audio-driven head generation framework for dyadi

Bufang Yang, Yunqi Guo, Lilin Xu, Zhenyu Yan

Social interactions are fundamental to human life. The recent emergence of large language models (LLMs)-based virtual assistants has demonstrated their potential to revolutionize human interactions and lifestyles. However, existing assistive systems mainly provide reactive services to individual users, rather than offering in-situ assistance during live soci

Bingquan Peng, Yinshuo Li, Liang Chen

Bismuth telluride-based materials is the only commercially viable room-temperature thermoelectric material, despite its limited tellurium and poor mechanical properties. The search for materials with a high figure of merit (zT > 1.00) near room temperature remains a major challenge. In this work, we systematically investigate the structural stability and the

Yunhua Pei, Jin Zheng, John Cartlidge

Temporal Graph Learning (TGL) is crucial for capturing the evolving nature of stock markets. Traditional methods often ignore the interplay between dynamic temporal changes and static relational structures between stocks. To address this issue, we propose the Dynamic Graph Representation with Contrastive Learning (DGRCL) framework, which integrates dynamic a

NA62 Collaboration

The NA62 experiment at the CERN SPS reports the first detection of a tagged neutrino candidate based on the data collected in 2022. The candidate consists of a $K^+ \rightarrow \mu^+ \nu_\mu$ decay where the charged particles are reconstructed and the neutrino is detected through a charged-current interaction in a liquid krypton calorimeter.

Brune Massoulié

We compute the mixing time of the Facilitated Exclusion Process (FEP) and obtain cutoff and pre-cutoff in different regimes. The main tool to obtain this result is a new bijective, deterministic mapping between the joint law of an ergodic FEP and its current through the origin, and the joint law of a Symmetric Simple Exclusion Process (SSEP) and its current

Puspanjali Ghoshal, Ashok Singh Sairam

In a Multi-Agent System (MAS), individual agents observe various aspects of the environment and transmit this information to a central entity responsible for aggregating the data and deducing system parameters. To improve overall efficiency, agents may append certain private parameters to their observations. For example, in a crowd-sourced traffic monitoring

Théo Sourget, Michelle Hestbek-Møller, Amelia Jiménez-Sánchez, Jack Junchi Xu

The development of larger models for medical image analysis has led to increased performance. However, it also affected our ability to explain and validate model decisions. Models can use non-relevant parts of images, also called spurious correlations or shortcuts, to obtain high performance on benchmark datasets but fail in real-world scenarios. In this wor

Giulio Corsi, Kyle Kilian, Richard Mallah

The rapid advancement of artificial intelligence (AI) technologies presents profound challenges to societal safety. As AI systems become more capable, accessible, and integrated into critical services, the dual nature of their potential is increasingly clear. While AI can enhance defensive capabilities in areas like threat detection, risk assessment, and aut

Kento Fujita, Yoshinori Hashimoto

We interpret the coupled Ding semistability and the reduced coupled uniform Ding stability of log Fano pairs in the notion of coupled stability thresholds and reduced coupled stability thresholds. As a corollary, we solve a modified version of the conjecture by Hultgren and Witt Nystr\"om for coupled K\"ahler--Einstein metrics on Fano manifolds.

L. Velilla-Prieto, J. P. Fonfría, M. Agúndez, A. Castro-Carrizo

During their thermally pulsing phase, Asymptotic Giant Branch (AGB) stars eject material that forms extended dusty envelopes. Visible polarimetric imaging found clumpy dust clouds within two stellar radii of several oxygen-rich stars. Inhomogeneous molecular gas has also been observed in multiple emission lines within several stellar radii of different oxyge

Jiang Liu, Bobo Li, Xinran Yang, Na Yang

Multimodal information extraction (IE) tasks have attracted increasing attention because many studies have shown that multimodal information benefits text information extraction. However, existing multimodal IE datasets mainly focus on sentence-level image-facilitated IE in English text, and pay little attention to video-based multimodal IE and fine-grained

Mugdha Pandya, Nafise Sadat Moosavi, Diana Maynard

Resolving disagreement in manual annotation typically consists of removing unreliable annotators and using a label aggregation strategy such as majority vote or expert opinion to resolve disagreement. These may have the side-effect of silencing or under-representing minority but equally valid opinions. In this paper, we study the impact of standard label agg

Pierre Tapie, Diogo Barreiros Scatamburlo, Antoine Chateauminois, Elie Wandersman

We mimic the mechanical response of touch mechanoreceptors by that of a gas cavity embedded in an elastic semi-cylinder, as a fingertip analogue. Using tribological experiments combined with optical imaging, we measure the dynamics and deformation of the cavity as the semi-cylinder is put in static contact or slid against model rough surfaces at constant nor

Olger Siebinga

When two pedestrians approach each other on the sidewalk head-on, they sometimes engage in an awkward interaction, both deviating to the same side (repeatedly) to avoid a collision. This phenomenon is known as the sidewalk salsa. Although well known, no existing model describes how this "dance" arises. Such a model must capture the nuances of individual inte

Stalin Abraham, Ameeya A. Bhagwat

$2\times2$ matrix polynomials of the form $P_{n}(z)= \Sigma^{n}_{j=0}\,\sigma_{j}\,z^{j}$, for the cases $n=1,2,3$ are constructed, and the nature of PT-symmetry is examined across different points $z=(x,y)$ in the complex plane. The PT-symmetric properties of $P_{n}(z)$ can be characterized by two functions, denoted by $s(x,y)$ and $h(x,y)$. If the trace of

Qian Li, Xin Wang, Xiaodong Li, Jiacheng Ding

In 21cm intensity mapping of the large-scale structure (LSS), regions in Fourier space could be compromised by foreground contamination. In interferometric observations, this contamination, known as the foreground wedge, is exacerbated by the chromatic response of antennas, leading to substantial data loss. Meanwhile, the baryonic acoustic oscillation (BAO)

Kangan Qian, Jinyu Miao, Xinyu Jiao, Ziang Luo

Understanding the spatial dynamics of cars within urban systems is essential for optimizing infrastructure management and resource allocation. Recent empirical approaches for analyzing traffic patterns have gained traction due to their applicability to city-scale policy development. However, conventional methodologies often rely on fragmented grid-based tech

Kento Fujita

In this paper, we see several basic properties of graded linear series. We firstly see that, if a graded linear series contains an ample series, then so are the pullbacks of the system under birational morphisms. Using this proposition, we define the refinements of graded linear series with respects to primitive flags. Moreover, we give several formulas to c