October 2024 arXiv papers — page 39

Chuang Zhao, Xing Su, Ming He, Hongke Zhao

Owing to the impressive general intelligence of large language models (LLMs), there has been a growing trend to integrate them into recommender systems to gain a more profound insight into human interests and intentions. Existing LLMs-based recommender systems primarily leverage item attributes and user interaction histories in textual format, improving the

Md Abdur Rahman, Fan Wu, Alfredo Cuzzocrea, Sheikh Iqbal Ahamed

Large language models (LLMs) are becoming a popular tool as they have significantly advanced in their capability to tackle a wide range of language-based tasks. However, LLMs applications are highly vulnerable to prompt injection attacks, which poses a critical problem. These attacks target LLMs applications through using carefully designed input prompts to

Soham Ghosh, Uttaran Chatterjee, Jyotishka Datta

In astronomical observations, the estimation of distances from parallaxes is a challenging task due to the inherent measurement errors and the non-linear relationship between the parallax and the distance. This study leverages ideas from robust Bayesian inference to tackle these challenges, investigating a broad class of prior densities for estimating distan

Eduardo Ochoa Rivera, Ambuj Tewari

Bandit algorithms have garnered significant attention due to their practical applications in real-world scenarios. However, beyond simple settings such as multi-arm or linear bandits, optimal algorithms remain scarce. Notably, no optimal solution exists for pure exploration problems in the context of generalized linear model (GLM) bandits. In this paper, we

Soumalya Bose, Soham Basu, Indranil Bera, Sambit Mallick

This paper addresses the medical imaging problem of joint detection in the upper limbs, viz. elbow, shoulder, wrist and finger joints. Localization of joints from X-Ray and Computerized Tomography (CT) scans is an essential step for the assessment of various bone-related medical conditions like Osteoarthritis, Rheumatoid Arthritis, and can even be used for a

Mautushi Das, Fang-Ling Chloe Liu, Charly Hartle, Chin-Cheng Scotty Yang

Ant foraging behavior is essential to understanding ecological dynamics and developing effective pest management strategies, but quantifying this behavior is challenging due to the labor-intensive nature of manual counting, especially in densely populated images. This study presents an automated approach using computer vision to count ants and analyze their

Yuzhen Zhang, Yingfei Gu

Magic refers to the degree of "quantumness" in a system that cannot be fully described by stabilizer states and Clifford operations alone. In quantum computing, stabilizer states and Clifford operations can be efficiently simulated on a classical computer, even though they may appear complicated from the perspective of entanglement. In this sense, ma

Shuning Cai, Joakim S. Jestilä, Peter Liljeroth, Adam S. Foster

Carbohydrates, essential biological building blocks, exhibit functional mechanisms tied to their intricate stereochemistry. Subtle stereochemical differences, such as those between the anomers maltose and cellobiose, lead to distinct properties due to their differing glycosidic bonds; the former is digestible by humans, while the latter is not. This undersco

Jaspreet Ranjit, Brihi Joshi, Rebecca Dorn, Laura Petry

Warning: Contents of this paper may be upsetting. Public attitudes towards key societal issues, expressed on online media, are of immense value in policy and reform efforts, yet challenging to understand at scale. We study one such social issue: homelessness in the U.S., by leveraging the remarkable capabilities of large language models to assist social work

Olaf Lipinski, Adam J. Sobey, Federico Cerutti, Timothy J. Norman

Effective communication requires the ability to refer to specific parts of an observation in relation to others. While emergent communication literature shows success in developing various language properties, no research has shown the emergence of such positional references. This paper demonstrates how agents can communicate about spatial relationships with

Vikraman Balaji, Yashonidhi Pandey

Let $k$ be a perfect field. Assume that the characteristic of $k$ satisfies certain tameness assumptions \eqref{tameness}. Let $\mathcal O_{_n} := k\llbracket z_{_1}, \ldots, z_{_n}\rrbracket$ and set $K_{_n} := \text{Fract}~\cO_{_n}$. Let $G$ be an almost-simple, simply-connected affine Chevalley group scheme with a maximal torus $T$ and a Borel subgroup $B

J. Llibre, Adrian C. Murza

We extend to the $n$-dimensional ellipsoid contained in $\R^{n+1},$ the Darboux theory of integrability for polynomial vector fields in the $n$-dimensional sphere (Llibre et al., 2018). New results on the maximum number of invariant parallels and meridians of polynomial vector fields $\X$ on the invariant $n-$dimensional ellipsoid, as a function of its degre

Ioannis Raptis

This paper explores the observability and estimation capability of dynamical systems using predominantly relative measurements of the system's state-space variables, with minimal to no reliance on absolute measurements of these variables. We concentrate on linear time-invariant systems, in which the observation matrix serves as the algebraic representation o

David Noever

This research tests the role of Large Language Models (LLMs) as formal second opinion tools in professional decision-making, particularly focusing on complex medical cases where even experienced physicians seek peer consultation. The work analyzed 183 challenging medical cases from Medscape over a 20-month period, testing multiple LLMs' performance against c

Rufus Cheuk Yin Wong, Mayank Sewlia, Adrian Wiltz, Dimos V. Dimarogonas

Optimal path planning is prone to convergence to local, rather than global, optima. This is often the case for mobile manipulators due to nonconvexities induced by obstacles, robot kinematics and constraints. This paper focuses on planning under end effector path constraints and attempts to circumvent the issue of converging to a local optimum. We propose a

Alex Lewandowski, Dale Schuurmans, Marlos C. Machado

Deep neural networks can struggle to learn continually in the face of non-stationarity. This phenomenon is known as loss of plasticity. In this paper, we identify underlying principles that lead to plastic algorithms. In particular, we provide theoretical results showing that linear function approximation, as well as a special case of deep linear networks, d

Faisal Munir Bhutta, Abdur Rehman, M. Jamil Aslam, Ishtiaq Ahmed

Recent measurements of the lepton flavor universality ratios $R^{\mu e}_{K}$ and $R^{\mu e}_{K^*}$ in $B\to \left(K, K^*\right)\mu^{+}\mu^{-}\left(e^+e^-\right)$ at LHCb align with the Standard Model predictions, necessitating search for the complementary decay modes. In this context, we derive the angular decay distributions of the four-fold $B \to K_{1}(12

Qinghui Sun, Yuan-Sen Ting, Fan Liu, Sharon Xuesong Wang

Planet engulfment has been identified as one of the mechanisms for enhancing lithium abundance in stars. However, comprehensive investigations into lithium signatures following such events remain limited. Stars born together, sharing a common origin and stellar characteristics, provide a unique opportunity to study these signatures and compare lithium abunda

Tianhao Zhang, Zhixiang Chen, Lyudmila S. Mihaylova

Vision Transformers (ViTs) have achieved remarkable success over various vision tasks, yet their robustness against data distribution shifts and inherent inductive biases remain underexplored. To enhance the robustness of ViT models for image Out-of-Distribution (OOD) detection, we introduce a novel and generic framework named Prior-augmented Vision Transfor

Yanlin Qu, Tomas Rokicki, Hillary Yang

Scrambling the standard 3x3x3 Rubik's Cube corresponds to a random walk on a group containing approximately 43 quintillion elements. Viewing the random walk as a Markov chain, its mixing time determines the number of random moves required to sufficiently scramble a solved cube. With the aid of a supercomputer, we show that the mixing time is at least 26, pro

Akanksha Agrawal, Daniel Lokshtanov, Fahad Panolan, Saket Saurabh

The classic greedy coloring (first-fit) algorithm considers the vertices of an input graph $G$ in a given order and assigns the first available color to each vertex $v$ in $G$. In the {\sc Grundy Coloring} problem, the task is to find an ordering of the vertices that will force the greedy algorithm to use as many colors as possible. In the {\sc Partial Grund

Ignacio Garrón, C. Vladimir Rodríguez-Caballero, Esther Ruiz

In a globalised world, inflation in a given country may be becoming less responsive to domestic economic activity, while being increasingly determined by international conditions. Consequently, understanding the international sources of vulnerability of domestic inflation is turning fundamental for policy makers. In this paper, we propose the construction of

Ruixuan Han, Hongxiang Li, Bin Xie

Networks representation aims to encode vertices into a low-dimensional space, while preserving the original network structures and properties. Most existing methods focus on static network structure without considering temporal dynamics. However, in real world, most networks (e.g., social and biological networks) are dynamic in nature and are constantly evol

Yang Xu, Fatemeh Pourahmadian

A deep learning framework is developed for multiscale characterization of poroelastic media from full waveform data which is known as poroelastography. Special attention is paid to heterogeneous environments whose multiphase properties may drastically change across several scales. Described in space-frequency, the data takes the form of focal solid displacem

Juntong Shi, Minkai Xu, Harper Hua, Hengrui Zhang

Synthesizing high-quality tabular data is an important topic in many data science tasks, ranging from dataset augmentation to privacy protection. However, developing expressive generative models for tabular data is challenging due to its inherent heterogeneous data types, complex inter-correlations, and intricate column-wise distributions. In this paper, we

Jui-Nan Yen, Si Si, Zhao Meng, Felix Yu

Low-rank adaption (LoRA) is a widely used parameter-efficient finetuning method for LLM that reduces memory requirements. However, current LoRA optimizers lack transformation invariance, meaning the actual updates to the weights depends on how the two LoRA factors are scaled or rotated. This deficiency leads to inefficient learning and sub-optimal solutions

Jessie Yuan, Janavi Gupta, Akhil Padmanabha, Zulekha Karachiwalla

Physically assistive robots present an opportunity to significantly increase the well-being and independence of individuals with motor impairments or other forms of disability who are unable to complete activities of daily living (ADLs). Speech interfaces, especially ones that utilize Large Language Models (LLMs), can enable individuals to effectively and na

Nikolas Kuhn

We define spin structures on perfect complexes outside of characteristic two, generalizing the usual notion for vector bundles. We give an explicit local characterization of spin structures, and show that for an oriented quadratic complex $E$ on an algebraic stack, spin structures on $E$ are parametrized by a degree $2$ gerbe. As an application, we show how

Jia-Jie Zhu, Alexander Mielke

The purpose of this paper is to answer a few open questions in the interface of kernel methods and PDE gradient flows. Motivated by recent advances in machine learning, particularly in generative modeling and sampling, we present a rigorous investigation of Fisher-Rao and Wasserstein type gradient flows concerning their gradient structures, flow equations, a

Anirudh Thatipelli, Shao-Yuan Lo, Amit K. Roy-Chowdhury

Egocentric vision captures the scene from the point of view of the camera wearer, while exocentric vision captures the overall scene context. Jointly modeling ego and exo views is crucial to developing next-generation AI agents. The community has regained interest in the field of egocentric vision. While the third-person view and first-person have been thoro

Pratim Guha Niyogi, Muraleetharan Sanjayan, Dmitri Volfson, Kathryn C. Fitzgerald

Research on modeling the distributional aspects in sensor-based digital health (sDHT) data has grown significantly in recent years. Most existing approaches focus on using individual-specific density or quantile functions. However, there has been limited exploration to assess the practical utility of alternative distributional representations in clinical con

Keisuke Okamura

Addressing global societal challenges necessitates insights and expertise that transcend the boundaries of individual disciplines. In recent decades, interdisciplinary collaboration has been recognised as a vital driver of innovation and effective problem-solving, with the potential to profoundly influence policy and practice worldwide. However, quantitative

Sanjana Das, Cosmin Pohoata, Adam Sheffer

The expansion of bivariate polynomials is well-understood for sets with a linear-sized product set. In contrast, not much is known for sets with small sumset. In this work, we provide expansion bounds for polynomials of the form $f(x, y) = g(x + p(y)) + h(y)$ for sets with small sumset. In particular, we prove that when $|A|$, $|B|$, $|A + A|$, and $|B + B|$

Getachew K. Befekadu

We consider a class of learning problem of point estimation for modeling high-dimensional nonlinear functions, whose learning dynamics is guided by model training dataset, while the estimated parameter in due course provides an acceptable prediction accuracy on a different model validation dataset. Here, we establish an evidential connection between such a l

Julian Demeio

We show that the map $\operatorname{Br} T \to (\operatorname{Br} T_{\bar k})^{\Gamma_k}$ is surjective for a torus $T$ defined over a field $k$ of characteristic $0$ when $k$ is a local or global field or $T$ is quasi-trivial.

Chunmei Wang, Shangyou Zhang

This paper presents an efficient weak Galerkin (WG) finite element method with reduced stabilizers for solving the time-harmonic Maxwell equations on both convex and non-convex polyhedral meshes. By employing bubble functions as a critical analytical tool, the proposed method enhances efficiency by partially eliminating the stabilizers traditionally used in

Ram Nandan Kumar, Jeeban Kumar Nayak, Subhasish Dutta Gupta, Nirmalya Ghosh

We introduce a new class of optical micromotors driven by the spin-orbit interaction of light and spin-driven fluid flows leading to simultaneous rotation and revolution of the micromotors. The micromotors are essentially birefringent liquid crystal particles (LC) that can efficiently convert the angular momentum of light into high-frequency rotational motio

Bernhard Aigner, Marcus Waurick

We review $H^{1}$-well-posedness for initial value problems of ordinary differential equations with state-dependent right-hand side. We streamline known approaches to infer existence and uniqueness of solutions for small times given a Lipschitz-continuous prehistory. The paramount feature is a reduction of the differential equation to a fixed point problem t

Salah Chaib, Ana Cristina Ferreira, Abdelghani Zeghib

Let us call pseudo-homothetic group the non-unimodular 3-dimensional Lie group that is the semi-direct product of $\mathbb{R}$ acting non-semisimply on $\mathbb{R}^2$. In this article, we solve the geodesic completeness problem on this Lie group. In particular, we exhibit a family of complete metrics such that all geodesics have bounded velocity. As an appli

Vasilios Mavroudis

Zero-Trust Network Access (ZTNA) marks a significant shift in network security by adopting a "never trust, always verify" approach. This work provides an in-depth analysis of ZTNA, offering a comprehensive framework for understanding its principles, architectures, and applications. We discuss its role in securing modern, complex network environments, which i

C. M. Newman, D. L. Stein

We show that the notion of critical droplets is central to an understanding of the nature of ground states in the Edwards-Anderson Ising model of a spin glass in arbitrary dimension. Given a specific ground state, suppose the coupling value for a given edge is varied with all other couplings held fixed. Beyond some specific value of the coupling, a droplet w

Jinhong Lin, Cheng-En Wu, Yibing Wei, Pedro Morgado

Our work tackles the computational challenges of contrastive learning methods, particularly for the pretraining of Vision Transformers (ViTs). Despite the effectiveness of contrastive learning, the substantial computational resources required for training often hinder their practical application. To mitigate this issue, we propose an acceleration framework,

Nick Seymour, Jess W. Broderick, Gael Noirot, Ross J. Turner

The bright radio source, GLEAM J091734-001243 (hereafter GLEAM J0917-0012), was previously selected as a candidate ultra-high redshift (z>5) radio galaxy due to its compact radio size and faint magnitude (K(AB)=22.7). Its redshift was not conclusively determined from follow-up millimetre and near-infrared spectroscopy. Here we present new HST WFC3 G141 grism

Siyuan Deng, Gregory Reid

Lie symmetry transformations that leave a differential equation invariant play a fundamental role in science and mathematics. Such Lie symmetry groups uniquely determine their Lie symmetry algebras. Exact differential elimination algorithms have been developed to determine the dimension and structure constants of the Lie symmetry algebra of an exact polynomi

Kenta Hagiwara, Ying-Jiun Chen, Dongwook Go, Xin Liang Tan

Chirality is ubiquitous in nature and manifests in a wide range of phenomena including chemical reactions, biological processes, and quantum transport of electrons. In quantum materials, the chirality of fermions, given by the relative directions between the electron spin and momentum, is connected to the band topology of electronic states. Here, we show tha

Yifei Huang, Liping Tong, Jie Yang

In the context of paid research studies and clinical trials, budget considerations often require patient sampling from available populations which comes with inherent constraints. We introduce the R package CDsampling, which is the first to our knowledge to integrate optimal design theories within the framework of constrained sampling. This package offers th

Gabriel Fernández-Blanco, Iván Froiz-Míguez, Paula Fraga-Lamas, Tiago M. Fernández-Caramés

The educational system manages extensive documentation and paperwork, which can lead to human errors and sometimes abuse or fraud, such as the falsification of diplomas, certificates or other credentials. In fact, in the last years, multiple cases of fraud have been detected, which have a significant cost to society, since they harm the trustworthiness of ce

Mateusz Wiśniewski, Jakub Spiechowicz

Dynamics of non-Markovian systems is a classic problem yet it attracts an everlasting activity in physics and beyond. A powerful tool for modeling such setups is the Generalized Langevin Equation, however, its analysis typically poses a major challenge even for numerical means. For this reason, various approximations have been proposed over the years that si

Tatiana Podladchikova, Shantanu Jain, Astrid M. Veronig, Stefan Purkhart

This study examines the relationship between early solar coronal mass ejection (CME) propagation, the associated filament eruption, and coronal dimming in the rare event observed on March 28, 2022, which featured a three-part CME in the low corona of active region AR 12975, including a bright core/filament, dark cavity, and bright front edge. We employ 3D fi

Jonas Mücke, Marcin Nawrocki, Raphael Hiesgen, Thomas C. Schmidt

In this paper, we present a detailed performance analysis of QUIC instant ACK, a standard-compliant approach to reduce waiting times during the QUIC connection setup in common CDN deployments. To understand the root causes of the performance properties, we combine numerical analysis and the emulation of eight QUIC implementations using the QUIC Interop Runne

CMS Collaboration

A search is presented for the pair production of new heavy resonances, each decaying into a top quark (t) or antiquark and a gluon (g). The analysis uses data recorded with the CMS detector from proton-proton collisions at a center-of-mass energy of 13 TeV at the LHC, corresponding to an integrated luminosity of 138 fb$^{-1}$. Events with one muon or electro

Harshvardhan Mestha, Karan Bania, Shreyas V Sathyanarayana, Sidong Liu

Our interest is in the design of software systems involving a human-expert interacting -- using natural language -- with a large language model (LLM) on data analysis tasks. For complex problems, it is possible that LLMs can harness human expertise and creativity to find solutions that were otherwise elusive. On one level, this interaction takes place throug

Alice James, Avishkar Seth, Endrowednes Kuantama, Subhas Mukhopadhyay

In this paper, we address the challenge of navigating through unknown indoor environments using autonomous aerial robots within confined spaces. The core of our system involves the integration of key sensor technologies, including depth sensing from the ZED 2i camera, IMU data, and LiDAR measurements, facilitated by the Robot Operating System (ROS) and RTAB-

Zihan Wang, Xuri Ge, Joemon M. Jose, Haitao Yu

Retrieval-augmented generation (RAG) has gained wide attention as the key component to improve generative models with external knowledge augmentation from information retrieval. It has shown great prominence in enhancing the functionality and performance of large language model (LLM)-based applications. However, with the comprehensive application of RAG, mor

Dragos Gorduza, Yaxuan Kong, Xiaowen Dong, Stefan Zohren

We investigate the effectiveness of a momentum trading signal based on the coverage network of financial analysts. This signal builds on the key information-brokerage role financial sell-side analysts play in modern stock markets. The baskets of stocks covered by each analyst can be used to construct a network between firms whose edge weights represent the n

Chu Xin Cheng, Raul Astudillo, Thomas Desautels, Yisong Yue

We consider Bayesian algorithm execution (BAX), a framework for efficiently selecting evaluation points of an expensive function to infer a property of interest encoded as the output of a base algorithm. Since the base algorithm typically requires more evaluations than are feasible, it cannot be directly applied. Instead, BAX methods sequentially select eval

Camilo Espinosa-Curilem, Millaray Curilem, Daniel Basualto

In volcano monitoring, effective recognition of seismic events is essential for understanding volcanic activity and raising timely warning alerts. Traditional methods rely on manual analysis, which can be subjective and labor-intensive. Furthermore, current automatic approaches often tackle detection and classification separately, mostly rely on single stati

Paula Fraga-Lamas, Sérgio Ivan Lopes, Tiago M. Fernández-Caramés

Decentralized Metaverses, built on Web 3.0 and Web 4.0 technologies, have attracted significant attention across various fields. This innovation leverages blockchain, Decentralized Autonomous Organizations (DAOs), Extended Reality (XR) and advanced technologies to create immersive and interconnected digital environments that mirror the real world. This artic

Meng Wei, Qianyi Wu, Jianmin Zheng, Hamid Rezatofighi

Rendering and reconstruction are long-standing topics in computer vision and graphics. Achieving both high rendering quality and accurate geometry is a challenge. Recent advancements in 3D Gaussian Splatting (3DGS) have enabled high-fidelity novel view synthesis at real-time speeds. However, the noisy and discrete nature of 3D Gaussian primitives hinders acc

Randy L. Caga-anan

This study presents a neural network-enhanced approach to modeling disease spread dynamics over time and space. Neural networks are used to estimate time-varying parameters, with two calibration methods explored: Approximate Bayesian Computation (ABC) with Trust Region Reflective (TRF) optimization, and backpropagation with the Adam optimizer. Simulations sh

Anton Freund, Patrick Uftring

We prove conservativity results for weak K\H{o}nig's lemma that extend the celebrated result of Harrington (for $\Pi^1_1$-statements) and are somewhat orthogonal to the extension by Simpson, Tanaka and Yamazaki (for statements of the form $\forall X\exists!Y\psi$ with arithmetical $\psi$). In particular, we show that $\mathsf{WKL}_0$ is conservative over $\m

T. Blum, P. A. Boyle, M. Bruno, B. Chakraborty

We provide the first ab-initio calculation of the Euclidean long-distance window of the isospin symmetric light-quark connected contribution to the hadronic vacuum polarization for the muon $g-2$ and find $a_\mu^{\rm LD,iso,conn,ud} = 411.4(4.3)(2.4) \times 10^{-10}$. We also provide the currently most precise calculation of the total isospin symmetric light

A. Mura, A. Moirano, V. Hue, C. Castagnoli

We report the first observation of the vertical and temporal structure of the H3+ emission at the auroral footprint of Io, as observed by Juno/JIRAM. The brightness vertical profile shows a maximum at 600 km above 1 bar, with no apparent difference between the Main Alfv\'en Wing spot emission and the tail of the footprint. This observation is more compatible

Jonathan S. Gómez, Gustavo Yepes, A. Jiménez Muñoz, Weiguang Cui

The new generation of upcoming deep photometric and spectroscopic surveys will allow us to measure the astrophysical properties of faint galaxies in massive clusters. This would demand to produce simulations of galaxy clusters with better mass resolution than the ones available today if we want to make comparisons between the upcoming observations and predic

Peter Holderrieth, Marton Havasi, Jason Yim, Neta Shaul

We introduce Generator Matching, a modality-agnostic framework for generative modeling using arbitrary Markov processes. Generators characterize the infinitesimal evolution of a Markov process, which we leverage for generative modeling in a similar vein to flow matching: we construct conditional generators which generate single data points, then learn to app

Tanjina Azad, Yue Ling

The interfacial instability in a two-phase mixing layers between parallel gas and liquid streams is important to two-phase atomization. Depending on the inflow conditions and fluid properties, interfacial instability can be convective or absolute. The goal of the present study is to investigate the impact of gas viscosity on the interfacial instability. Both

Ahmed. S Benmessaoud, Farida Medjani, Yahia Bousseloub, Khalid Bouaita

Electrocardiogram (ECG) is a reliable tool for medical professionals to detect and diagnose abnormal heart waves that may cause cardiovascular diseases. This paper proposes a methodology to create a new high-quality heartbeat dataset from all 48 of the MIT-BIH recordings. The proposed approach computes an optimal heartbeat size, by eliminating outliers and c

Bradley Boyd, Sid Becker, Yue Ling

Aerodynamic breakup of vaporizing drops is commonly seen in many spray applications. While it is well known that vaporization can modulate interfacial instabilities, the impact of vaporization on drop aerobreakup is poorly understood. Detailed interface-resolved simulations were performed to systematically study the effect of vaporization, characterized by t

Avishkar Seth, Alice James, Endrowednes Kuantama, Subhas Mukhopadhyay

In an era of rapid urbanization and e-commerce growth, efficient parcel delivery methods are crucial. This paper presents a detailed study of the aerodynamics and sensing analysis of drones for parcel delivery. Utilizing Computational Fluid Dynamics (CFD), the study offers a comprehensive airflow analysis, revealing the aerodynamic forces affecting drone sta

Taehyun Kim, Dimitri A. Gadotti, Yun Hee Lee, Carlos López-Cobá

Galactic bars induce characteristic motions deviating from pure circular rotation, known as non-circular motions. As bars are non-axisymmetric structures, stronger bars are expected to show stronger non-circular motions. However, this has not yet been confirmed by observations. We use a bisymmetric model to account for the stellar kinematics of 14 barred gal

Dmitry A. Prokhorov, Yi-Jung Yang, Riccardo Ferrazzoli, Jacco Vink

Synchrotron X-ray emission has been detected from nearly a dozen young supernova remnants (SNRs). X-rays of synchrotron origin exhibit linear polarization in a regular, non-randomly oriented magnetic field. The significant polarized X-ray emission from four such SNRs has already been reported on the basis of observations with the Imaging X-ray Polarimetry Ex

Tiago M. Fernández-Caramés, Paula Fraga-Lamas

Although Blockchain has been successfully used in many different fields and applications, it has been traditionally regarded as an energy-intensive technology, essentially due to the past use of inefficient consensus algorithms that prioritized security over sustainability. However, in the last years, thanks to the significant progress made on key blockchain

Zongyi Xiang, Yan Zhang, Lixin Duan, Hongzhi Yin

Discovering user preferences across different domains is pivotal in cross-domain recommendation systems, particularly when platforms lack comprehensive user-item interactive data. The limited presence of shared users often hampers the effective modeling of common preferences. While leveraging shared items' attributes, such as category and popularity, can enh

Shi-ang Qi, Yakun Yu, Russell Greiner

Survival prediction often involves estimating the time-to-event distribution from censored datasets. Previous approaches have focused on enhancing discrimination and marginal calibration. In this paper, we highlight the significance of conditional calibration for real-world applications -- especially its role in individual decision-making. We propose a metho

Ivan Kukanov, Janne Laakkonen, Tomi Kinnunen, Ville Hautamäki

Current speech deepfake detection approaches perform satisfactorily against known adversaries; however, generalization to unseen attacks remains an open challenge. The proliferation of speech deepfakes on social media underscores the need for systems that can generalize to unseen attacks not observed during training. We address this problem from the perspect

Nimish Nazirkar, Viet Tran, Pascal Bassene, Atoumane Ndiaye

The dynamic control of novel states of matter beyond thermodynamic equilibrium is a fundamental pursuit in condensed matter physics. Intense terahertz fields have enabled metal-insulator transitions, superconductivity, quantum paraelectric ferroelectricity, and room-temperature magnetization via circularly polarized terahertz electric fields. These effects h

Siddharth Gautam, Lukas Vlcek, Eugene Mamontov, David Cole

We report here a molecular dynamics simulation study on water and aqueous LiCl solutions confined in 1.6 nm cylindrical pores of silica to investigate a dynamical cross-over, observed earlier experimentally, wherein LiCl slows down confined water at high temperatures but makes it faster at lower temperatures. The cross-over observed in the experiments is rep

Janis Adamek, Philipp Binfet, Nils Schlüter, Moritz Schulze Darup

Encrypted computation opens up promising avenues across a plethora of application domains, including machine learning, health-care, finance, and control. Arithmetic homomorphic encryption, in particular, is a natural fit for cloud-based computational services. However, computations are essentially limited to polynomial circuits, while comparisons, transcende

Po-Yu Liang, Jun Bai

Biologists frequently desire protein inhibitors for a variety of reasons, including use as research tools for understanding biological processes and application to societal problems in agriculture, healthcare, etc. Immunotherapy, for instance, relies on immune checkpoint inhibitors to block checkpoint proteins, preventing their binding with partner proteins

I. K. Kozlov

We prove that any bi-Hamiltonian system $v = \left(\mathcal{A} + \lambda \mathcal{B}\right)dH_{\lambda}$ that is Hamiltonian with respect all Poisson brackets $\mathcal{A} + \lambda \mathcal{B}$ is locally bi-integrable in both the real smooth case, when all eigenvalues of the Poisson pencil $\mathcal{P} = \left\{\mathcal{A} + \lambda \mathcal{B}\right\}$ ar

Mohammad Hassan Vali, Tom Bäckström

Generative adversarial networks (GANs) learn a latent space whose samples can be mapped to real-world images. Such latent spaces are difficult to interpret. Some earlier supervised methods aim to create an interpretable latent space or discover interpretable directions, which requires exploiting data labels or annotated synthesized samples for training. Howe

Naum Dimitrieski, Michael Reyer, Mohamed-Ali Belabbas, Christian Ebenbauer

In this paper a novel stochastic optimization and extremum seeking algorithm is presented, one which is based on time-delayed random perturbations and step size adaptation. For the case of a one-dimensional quadratic unconstrained optimization problem, global exponential convergence in expectation and global exponential practical convergence of the variance

Lucy Jiang, Jon E. Froehlich, Leah Findlater

Public artwork, from vibrant wall murals to captivating sculptures, can enhance the aesthetic of urban spaces, foster a sense of community and cultural identity, and help attract visitors. Despite its benefits, most public art is visual, making it often inaccessible to blind and low vision (BLV) people. In this workshop paper, we first draw on art literature

Neil Krishnan, Rupert Li

Friends-and-strangers graphs, coined by Defant and Kravitz, are denoted by $\mathsf{FS}(X,Y)$ where $X$ and $Y$ are both graphs on $n$ vertices. The graph $X$ represents positions and edges mark adjacent positions while the graph $Y$ represents people and edges mark friendships. The vertex set of $\mathsf{FS}(X,Y)$ consists of all one-to-one placements of pe

Michele Benzi, Daniele La Pegna, Paolo Maria Mariano

We consider the dynamics of bodies with "active" microstructure described by vector-valued phase fields. For waves with time-varying amplitude, the associated evolution equation involves a matrix that can be non-normal, depending on the constitutive choices adopted for the microstructural actions associated with the considered phase field. The occurrence of

Catinca Mujdei

We study Kloosterman sums on the orthogonal groups $SO_{3,3}$ and $SO_{4,2}$, associated to short elements of their respective Weyl groups. An explicit description for these sums is obtained in terms of multi-dimensional exponential sums. These are bounded by a combination of methods from algebraic geometry and $p$-adic analysis.

Carmel Shabalin, Israel Shenkman, Ilan Shelef, Gal Ben-Arie

Low back pain is the symptom that is the second most frequently reported to primary care physicians, effecting 50 to 80 percent of the population in a lifetime, resulting in multiple referrals of patients suffering from back problems, to CT and MRI scans, which are then examined by radiologists. The radiologists examining these spinal scans naturally focus o

Yi-Hao Chen, Frank Wise

Noise can play an important role in nonlinear pulse propagation. It is not only the origin of fluctuations in supercontinuum but can also determine the generated signal amplitude and phase, as seen in phenomena such as noise-seeded four-wave mixing and spontaneous Raman scattering. Current models rely on input-pulse shot noise and Raman Langevin term to simu

Zainab S. M., Ali N. Sabbar, Ali Mahdi Abdul Hussein

Current work includes a study of the very rare case called intruder nuclear levels, where there are only seven nuclei in nature. Such cases occur when the first excited state is . The current study included only three nuclei: . The nuclear model used to explore and investigate nuclei in this work is the second interacting boson. The experimental data and the

Tamal K. Dey, Tao Hou, Dmitriy Morozov

Zigzag filtrations of simplicial complexes generalize the usual filtrations by allowing simplex deletions in addition to simplex insertions. The barcodes computed from zigzag filtrations encode the evolution of homological features. Although one can locate a particular feature at any index in the filtration using existing algorithms, the resulting representa

Sadia Nowrin, Keith Vertanen

Conversational systems rely heavily on speech recognition to interpret and respond to user commands and queries. Despite progress on speech recognition accuracy, errors may still sometimes occur and can significantly affect the end-user utility of such systems. While visual feedback can help detect errors, it may not always be practical, especially for peopl

Charlotte Dietze, Larry Read

We consider a compact Riemannian manifold with boundary and a metric that is singular at the boundary. The associated Laplace-Beltrami operator is of the form of a Grushin operator plus a singular potential. In a supercritical parameter regime, we identify the rate of concentration and profile of the high-frequency eigenfunctions that accumulate at the bound

Mikhail V. Bondarko, Stepan V. Shamov

We study a weight-exact localization pi of a well generated triangulated category C along with the embedding of the hearts of adjacent t-structures coming from the functor right adjoint to pi. We prove that the functors relating the corresponding four hearts are completely determined by the heart Hw of the weight structure on C along with the set of Hw-morph

David Dekker, Carl Henrik Häll, Anders Peterson, Christiane Schmidt

A seemingly simple, yet widely applicable subroutine in automated train scheduling is the insertion of a new train path to a timetable in a railway network. We believe it to be the first step towards a new train-rerouting framework in case of large disturbances or maintenance works. Other applications include handling ad-hoc requests and modifying train path

Junren Chen, Giacomo Indiveri

1T1R (1-transistor-1-resistor) memory crossbar arrays represent a promising solution for compute-in-memory matrix-vector multiplication accelerators and embedded or storage-class memory. However, the size and scaling of these arrays are hindered by critical challenges, such as the IR drop on metal lines and the accumulation of leakage current from the transi

A. Aguilar-Arevalo, M. Aoki, M. Blecher, D. I. Britton

Measurements of the response function of the PIENU NaI(T$\ell$) and CsI crystal calorimeter using a monochromatic 70 MeV/c positron beam at various incidence angles are described. The experimental setup and relevant physical processes involved were simulated using Geant4 to reproduce positron energy spectra. Monte Carlo simulations were compared with experim

Ivan Grega, William F. Whitney, Vikram S. Deshpande

Interrupted X-ray computed tomography (X-CT) has been the common way to observe the deformation of materials during an experiment. While this approach is effective for quasi-static experiments, it has never been possible to reconstruct a full 3d tomography during a dynamic experiment which cannot be interrupted. In this work, we propose that neural rendering

Nicholas Z. Rui, Jim Fuller, J. J. Hermes

The origin of magnetic fields in white dwarfs (WDs) remains mysterious. Magnetic WDs are traditionally associated with field strengths $\gtrsim1\,\mathrm{MG}$, set by the sensitivity of typical spectroscopic magnetic field measurements. Informed by recent developments in red giant magnetoasteroseismology, we revisit the use of WD pulsations as a seismic magn

Alexey D. Nekrasov, Viacheslav V. Zhuravlev, Sergei B. Popov

An accretion disk can be formed around a secondary star in a binary system when the primary companion leaves the Main sequence and starts to lose mass at an enhanced rate. We study the accretion disk evolution and planetary migration in wide binaries. We use a numerical model of a non-stationary alpha-disk with a variable mass inflow. We take into account th

Yaser Baseri, Abdelhakim Senhaji Hafid, Dimitrios Makrakis

User profiling is a critical component of adaptive risk-based authentication, yet it raises significant privacy concerns, particularly when handling sensitive data. Profiling involves collecting and aggregating various user features, potentially creating quasi-identifiers that can reveal identities and compromise privacy. Even anonymized profiling methods re