May 2024 arXiv papers — page 118

Daniel Csillag, Claudio José Struchiner, Guilherme Tegoni Goedert

Many algorithms have been recently proposed for causal machine learning. Yet, there is little to no theory on their quality, especially considering finite samples. In this work, we propose a theory based on generalization bounds that provides such guarantees. By introducing a novel change-of-measure inequality, we are able to tightly bound the model loss in

Leonardo Prauchner, Eleonir Calegari, Julian Faundez, Sergio Magalhaes

In this study, we explore the impact of short-range antiferromagnetic correlations on the charge density wave (CDW) phase in strongly correlated electron systems exhibiting the pseudogap phenomenon. Our investigation employs a n-pole approximation to consider the repulsive Coulomb interaction $(U)$ and antiferromagnetic correlations. Utilizing a two-dimensio

Hongru Li, Jiawei Shao, Hengtao He, Shenghui Song

Task-oriented communication aims to extract and transmit task-relevant information to significantly reduce the communication overhead and transmission latency. However, the unpredictable distribution shifts between training and test data, including domain shift and semantic shift, can dramatically undermine the system performance. In order to tackle these ch

Theodoros Soultanis, Kiril Maltsev, Andreas Bauswein, Katerina Chatziioannou

We present a time-domain model for the gravitational waves emitted by equal-mass binary neutron star merger remnants for a fixed equation of state. We construct a large set of numerical relativity simulations for a single equation of state consistent with current constraints, totaling 157 equal-mass binary neutron star merger configurations. The gravitationa

Miguel M. Oliveira, Pedro Ribeiro, Stefan Kirchner

The non-thermal breakdown of a Mott insulator has been a topic of great theoretical and experimental interest with technological relevance. Recent experiments have found a sharp non-equilibrium insulator-to-metal transition that is accompanied by hysteresis, a negative differential conductance and lattice deformations. However, a thorough understanding of th

Jake A. Soloff, Rina Foygel Barber, Rebecca Willett

Model averaging techniques based on resampling methods (such as bootstrapping or subsampling) have been utilized across many areas of statistics, often with the explicit goal of promoting stability in the resulting output. We provide a general, finite-sample theoretical result guaranteeing the stability of bagging when applied to algorithms that return outpu

José Luis Montiel Olea, Mikkel Plagborg-Møller, Eric Qian, Christian K. Wolf

We consider impulse response inference in a locally misspecified vector autoregression (VAR) model. The conventional local projection (LP) confidence interval has correct coverage even when the misspecification is so large that it can be detected with probability approaching 1. This result follows from a "double robustness" property analogous to that of popu

Demi Zhang, Bushi Xiao, Chao Gao, Sangpil Youm

This study evaluates the performance of Recurrent Neural Network (RNN) and Transformer models in replicating cross-language structural priming, a key indicator of abstract grammatical representations in human language processing. Focusing on Chinese-English priming, which involves two typologically distinct languages, we examine how these models handle the r

Chester Palen-Michel, Lizzie Liang, Zhe Wu, Constantine Lignos

We present QueryNER, a manually-annotated dataset and accompanying model for e-commerce query segmentation. Prior work in sequence labeling for e-commerce has largely addressed aspect-value extraction which focuses on extracting portions of a product title or query for narrowly defined aspects. Our work instead focuses on the goal of dividing a query into me

Daniela Paoletti, Dhiraj Kumar Hazra, Fabio Finelli, George F. Smoot

We show that by jointly fitting cosmic microwave background (CMB) and astrophysical data - a compilation of UV luminosity data from the Hubble Frontier Field and neutral hydrogen data from distant sources-, we can infer on the shape of the evolution of the ionized hydrogen fraction with redshift in addition to constraining the average optical depth $\tau$.Fo

Song Yang, Xun Yu, Zigang Zhu

We show that smooth hypersurfaces in complex projective spaces with automorphism groups of maximum size are isomorphic to Fermat hypersurfaces, with a few exceptions. For the exceptions, we give explicitly the defining equations and automorphism groups.

Thorsten Wißmann, Stefan Milius

The initial algebra for an endofunctor F provides a recursion and induction scheme for data structures whose constructors are described by F. The initial-algebra construction by Ad\'amek (1974) starts with the initial object (e.g. the empty set) and successively applies the functor until a fixed point is reached, an idea inspired by Kleene's fixed point theo

Eva Durán-Camacho, Ana Duarte-Cabral, Alex R. Pettitt, Robin G. Treß

To advance our understanding of the evolution of the interstellar medium (ISM) of our Galaxy, numerical models of Milky Way (MW) type galaxies are widely used. However, most models only vaguely resemble the MW (e.g. in total mass), and often use imposed analytic potentials (which cannot evolve dynamically). This poses a problem in asserting their applicabili

Eleftheria Solomonidi

The study of processes involving the weak decays of the charm quark offers unique possibilities to test the Standard Model from the up-type sector and to probe different New Physics scenarios. In here we focus on the rare decays $D^0\to\pi^+\pi^-\ell^+\ell^-$. The effectiveness of the Glashow-Iliopoulos-Maiani mechanism in charm results in a series of observ

Younghun Jo

In this paper, we derive a precise estimate for the mean extinction time of the contact process with a fixed infection rate on a star graph with $N$ leaves. Specifically, we determine not only the exponential main factor but also the exact sub-exponential prefactor in the asymptotic expression for the mean extinction time as $N\to\infty$. Previously, such de

Larry G Epstein, Kaushil Patel

Given only aggregate choice data and limited information about how menus are distributed across the population, we describe what can be inferred robustly about the distribution of preferences (or more general decision rules). We strengthen and generalize existing results on such identification and provide an alternative analytical approach to study the probl

Elie Kfoury, Samia Choueiri, Ali Mazloum, Ali AlSabeh

The end of Moore's Law and Dennard Scaling has slowed processor improvements in the past decade. While multi-core processors have improved performance, they are limited by the application's level of parallelism, as prescribed by Amdahl's Law. This has led to the emergence of domain-specific processors that specialize in a narrow range of functions. Smart Net

Chayan Das, Abhishek, Dibyajyoti Saikia, Appala Naidu Gandi

The newly emerged two-dimensional (2D) materials family of MSi2N4, where M is a transition metal atom (i.e., Mo, W, etc.), has the potential to be named after the conventional and very popular transition metal di-chalcogenides (TMDC), which got their reputation for having bandgap tunability and high mobility. The HfSi2N4 and HfGe2N4 2D materials are members

Fei Shang, Haohua Du, Panlong Yang, Xin He

6G technology offers a broader range of possibilities for communication systems to perform ubiquitous sensing tasks, including health monitoring, object recognition, and autonomous driving. Since even minor environmental changes can significantly degrade system performance, and conducting long-term posterior experimental evaluations in all scenarios is often

Jonne Sälevä, Constantine Lignos

We introduce ParaNames, a massively multilingual parallel name resource consisting of 140 million names spanning over 400 languages. Names are provided for 16.8 million entities, and each entity is mapped from a complex type hierarchy to a standard type (PER/LOC/ORG). Using Wikidata as a source, we create the largest resource of this type to date. We describ

Maciej Grzenda, Marcin Luckner, Jakub Zawieska, Przemysław Wrona

Demand for sustainable mobility is particularly high in urban areas. Hence, there is a growing need to predict when people will decide to use different travel modes with an emphasis on environmentally friendly travel modes. As travel mode choice (TMC) is influenced by multiple factors, in a growing number of cases machine learning methods are used to predict

Marcus J. Hatton, Ian Hawke

We present a formulation of special relativistic, dissipative hydrodynamics (SRDHD) derived from the well-established M\"uller- Israel-Stewart (MIS) formalism using an expansion in deviations from ideal behaviour. By re-summing the non-ideal terms, our approach extends the Euler equations of motion for an ideal fluid through a series of additional source ter

Xinyang Dong, Emanuel Gull

The exploitation of space group symmetries in numerical calculations of periodic crystalline solids accelerates calculations and provides physical insight. We present results for a space-group symmetry adaptation of electronic structure calculations within the finite-temperature self-consistent GW method along with an efficient parallelization scheme on acce

Tiffany Tianhui Cai, Yuri Fonseca, Kaiwen Hou, Hongseok Namkoong

Popular debiased estimation methods for causal inference -- such as augmented inverse propensity weighting and targeted maximum likelihood estimation -- enjoy desirable asymptotic properties like statistical efficiency and double robustness but they can produce unstable estimates when there is limited overlap between treatment and control, requiring addition

Xingyu Li, Bo Tang

Deep neural networks suffer from the catastrophic forgetting problem in the field of continual learning (CL). To address this challenge, we propose MGSER-SAM, a novel memory replay-based algorithm specifically engineered to enhance the generalization capabilities of CL models. We first intergrate the SAM optimizer, a component designed for optimizing flatnes

John Ashley Navarro Capellan

A conjecture in [Ish20] states that for a finite subgroup $G$ of $GL(2; \mathbb{C})$, a resolution $Y$ of $\mathbb{C}^2/G$ is isomorphic to a moduli space $\mathcal{M}_{\theta}$ of $G$-constellations for some generic stability parameter $\theta$ if and only if $Y$ is dominated by the maximal resolution. This paper affirms the conjecture in the case of dihedr

Richard Heusdens, Guoqiang Zhang

In this paper we consider the problem of distributed nonlinear optimisation of a separable convex cost function over a graph subject to cone constraints. We show how to generalise, using convex analysis, monotone operator theory and fixed-point theory, the primal-dual method of multipliers (PDMM), originally designed for equality constraint optimisation and

Joshua Brody, Pat Devlin, Aditi Dudeja, Emmi Rivkin

In this paper we study $d$-dependent random graphs -- introduced by Brody and Sanchez -- which are the family of random graph distributions where each edge is present with probability $p$, and each edge is independent of all but at most $d$ other edges. For this random graph model, we analyze degree sequences, jumbledness, connectivity, and subgraph containm

Nuno Crokidakis

We propose a simple model to describe the dynamics of religious affiliation. For such purpose, we built a compartmental model with three distinct subpopulations, namely religious committed individuals, religious noncommitted individuals and not religious affiliated individuals. The transitions among the compartments are governed by probabilities, modeling so

Jiahao Nie, Shan Lin, Alex C. Kot

The primary color profile of the same identity is assumed to remain consistent in typical Person Re-identification (Person ReID) tasks. However, this assumption may be invalid in real-world situations and images hold variant color profiles, because of cross-modality cameras or identity with different clothing. To address this issue, we propose Color Space Le

Alexander Clifton, Hong Liu, Letícia Mattos, Michael Zheng

For a graph $G$ and a hereditary property $\mathcal{P}$, let $\text{ex}(G,\mathcal{P})$ denote the maximum number of edges of a subgraph of $G$ that belongs to $\mathcal{P}$. We prove that for every non-trivial hereditary property $\mathcal{P}$ such that $L \notin \mathcal{P}$ for some bipartite graph $L$ and for every fixed $p \in (0,1)$ we have \[\text{ex}

Chak Fung Choi, Chunxue Li, Chun Yip Yau, Zifeng Zhao

Change-point detection and estimation procedures have been widely developed in the literature. However, commonly used approaches in change-point analysis have mainly been focusing on detecting change-points within an entire time series (off-line methods), or quickest detection of change-points in sequentially observed data (on-line methods). Both classes of

Bastian B. Brandt, Gergely Endrődi, Eduardo Garnacho-Velasco, Gergely Markó

In this paper we investigate the chiral magnetic effect (CME): the generation of an electric current due to a homogeneous background magnetic field and a homogeneous chiral imbalance in QCD. We demonstrate that the leading coefficient describing the CME vanishes in equilibrium, both for free fermions as well as in full QCD. Our full QCD results are based on

Naman Awasthi, Saad Abrar, Daniel Smolyak, Vanessa Frias-Martinez

COVID-19 forecasting models have been used to inform decision making around resource allocation and intervention decisions e.g., hospital beds or stay-at-home orders. State of the art deep learning models often use multimodal data such as mobility or socio-demographic data to enhance COVID-19 case prediction models. Nevertheless, related work has revealed un

Donya Rooein, Paul Rottger, Anastassia Shaitarova, Dirk Hovy

Using large language models (LLMs) for educational applications like dialogue-based teaching is a hot topic. Effective teaching, however, requires teachers to adapt the difficulty of content and explanations to the education level of their students. Even the best LLMs today struggle to do this well. If we want to improve LLMs on this adaptation task, we need

E. Siri, N. Sadooghi

We study the thermodynamic properties of a rigidly rotating relativistic Bose gas. First, we derive the solution of the equation of motion corresponding to a rotating complex Klein-Gordon field and determine the free propagator of this model utilizing the Fock-Schwinger proper-time method. Using this propagator, we then obtain the thermodynamic potential of

L. Herrera, A. Di Prisco, J. Ospino

We explore an idea put forward many years ago by Zeldovich and Novikov concerning the existence of compact objects endowed with arbitrarily small mass. The energy-density of such objects, which we call ``Ghost stars'', is negative in some regions of the fluid distribution, producing a vanishing total mass. Thus, the interior is matched on the boundary surfac

Ivan Garashchuk, Alexey Kazakov, Dmitry Sinelshchikov

We study nonlinear dynamics in a model of three interacting encapsulated gas bubbles in a liquid. The model is a system of three coupled nonlinear oscillators with an external periodic force. Such bubbles have numerous applications, for instance, they are used as contrast agents in ultrasound visualization. Certain types of bubbles oscillations may be benefi

Huynh Anh N. Le, Chen Qin, Yongquan Xue, Shifu Zhu

We introduce our project, AGNSTRONG (Active Galactic Nuclei and STaR fOrmation in Nearby Galaxies). Our research goals encompass investigating the kinematic properties of ionized and molecular gas outflows, understanding the impact of AGN feedback, and exploring the coevolution dynamics between AGN strength activity and star formation activity. We aim to con

Shurong Wang, Yufei Zhang, Xuliang Huang, Hongwei Wang

Knowledge graph embedding (KGE) has caught significant interest for its effectiveness in knowledge graph completion (KGC), specifically link prediction (LP), with recent KGE models cracking the LP benchmarks. Despite the rapidly growing literature, insufficient attention has been paid to the cooperation between humans and AI on KG. However, humans' capabilit

Damien Hutsemékers, Dominique Sluse, Đorđe Savić

We analyzed the CIV line profile distortions due to microlensing in two quasars, J1339 and J1138. J1339 shows a strong, asymmetric line profile deformation, while J1138 shows a more modest, symmetric deformation. To probe the CIV broad line region (BLR), we compared the observed line profile deformations to simulated ones. The simulations are based on three

Chun-Yu Xiong, Tian-Yang Sun, Jing-Fei Zhang, Xin Zhang

Gravitational wave (GW) detection is of paramount importance in fundamental physics and GW astronomy, yet it presents formidable challenges. One significant challenge is the removal of noise transient artifacts known as glitches, which greatly impact the search and identification of GWs. Recent research has achieved remarkable results in data denoising, ofte

Ionut-Gabriel Farcas, Gabriele Merlo, Frank Jenko

We derive an advanced surrogate model for predicting turbulent transport at the edge of tokamaks driven by electron temperature gradient (ETG) modes.Our derivation is based on a recently developed sensitivity-driven sparse grid interpolation approach for uncertainty quantification and sensitivity analysis at scale, which informs the set of parameters that de

Burak Oğuz, Bayram Tekin

We study symmetry reductions in the context of Euclidean Chern-Simons gauge theories to obtain lower dimensional field theories. Symmetry reduction in certain gauge theories is a common tool for obtaining explicit soliton solutions. Although pure Chern-Simons theories do not admit solitonic solutions, symmetry reduction still leads to interesting results. We

Xinying Lin, Xuyang Liu, Hong Yang, Xiaohai He

With the advent of image super-resolution (SR) algorithms, how to evaluate the quality of generated SR images has become an urgent task. Although full-reference methods perform well in SR image quality assessment (SR-IQA), their reliance on high-resolution (HR) images limits their practical applicability. Leveraging available reconstruction information as mu

Luis B. Castro, Angel E. Obispo, Andrés G. Jirón

The quantum dynamics of charged scalar bosons in a Bonnor-Melvin-$\Lambda$ universe is considered. In this study, the behavior of charged scalar bosons is explored within the framework of the Duffin-Kemmer-Petiau (DKP) formalism. Adopting a conical approximation ($\Lambda\ll 1$), we are considered two scenarios for the vector potential: a linear and quadrati

Weifei Jin, Yuxin Cao, Junjie Su, Qi Shen

In light of the widespread application of Automatic Speech Recognition (ASR) systems, their security concerns have received much more attention than ever before, primarily due to the susceptibility of Deep Neural Networks. Previous studies have illustrated that surreptitiously crafting adversarial perturbations enables the manipulation of speech recognition

Yushi Yang, Francesco Turci, Erika Kague, Chrissy L. Hammond

Collective behaviour in living systems is observed across many scales, from bacteria to insects, to fish shoals. Zebrafish have emerged as a model system amenable to laboratory study. Here we report a three-dimensional study of the collective dynamics of fifty zebrafish. We observed the emergence of collective behaviour changing between \yy{ordered} to rando

Dimitrios Pesios, Ioannis Koutalios, Dimitris Kugiumtzis, Nikolaos Stergioulas

Gravitational waves in the postmerger phase of binary neutron star mergers may become detectable with planned upgrades of existing gravitational-wave detectors or with more sensitive next-generation detectors. The construction of template banks for the postmerger phase can facilitate signal detection and parameter estimation. Here, we investigate the perform

Victor Montesinos, Jing Song, Wei-Hong Liang, Eulogio Oset

We start from a recently favored picture in which the $\Lambda_c(2940)$ and $\Lambda_c(2910)$ correspond mostly to $ND^*$ bound states with $J^P = 1/2^-,\, 3/2^-$ and then add a $D$ as a third particle, looking for the possible binding of the $DND^*$ three body system within the framework of the Fixed Center Approximation. We find that the system is bound wi

Salvio Luna-Hernandez, Marco Enriquez, Oscar Rosas-Ortiz

We introduce a purely geometric formulation for two different measures addressed to quantify the entanglement between different parts of a tripartite qubit system. Our approach considers the entanglement-polytope defined by the smallest eigenvalues of the reduced density matrices of the qubit-components. The measures identify global and genuine entanglement,

Yifan Mao, Mengya Zhang, Shaileshh Bojja Venkatakrishnan, Zhiqiang Lin

Maximal extractable value (MEV) in which block proposers unethically gain profits by manipulating the order in which transactions are included within a block, is a key challenge facing blockchains such as Ethereum today. Left unchecked, MEV can lead to a centralization of stake distribution thereby ultimately compromising the security of blockchain consensus

Albert Williams, Nitish K. Panigrahy, Andrew McGregor, Don Towsley

As Low Earth Orbit (LEO) satellite mega constellations continue to be deployed for satellite internet and recent successful experiments in satellite-based quantum entanglement distribution emerge, a natural question arises: How should we coordinate transmissions and design scalable scheduling policies for a quantum satellite internet? In this work, we consid

Yan Kong, Sheng Wang, Jiangdong Cai, Zihao Zhao

Accurate detection of vulvovaginal candidiasis is critical for women's health, yet its sparse distribution and visually ambiguous characteristics pose significant challenges for accurate identification by pathologists and neural networks alike. Our eye-tracking data reveals that areas garnering sustained attention - yet not marked by experts after deliberati

Carter Ball, Thomas D. Cohen

Quantum simulation of lattice gauge theories is a promising tool for the study of many complicated problems including ones with real-time dynamics. For gauge theories, however, there is a major challenge in maintaining gauge invariance during time evolution. Such theories have a full Hilbert space that is larger than the physical space -- the set of states w

Vladimir S. Matveev

We construct an example of a Riemannian metric on the 2-torus such that its universal cover does not admit global Riemann normal coordinates.

Fei Guo, Michele Puppin, Lukas Hellbruck, Arnaud Magrez

Low-dimensional materials are susceptible to electronic instabilities such as charge density waves (CDWs), originating from a divergence in the Lindhard electron response function, combined with a finite electron-phonon coupling strength. In this report, we present a detailed characterisation of the CDW in the quasi-one-dimensional material CuTe, including (

Luca Cocconi, Henry Alston, Jacopo Romano, Thibault Bertrand

The Ornstein-Uhlenbeck (OU) process describes the dynamics of Brownian particles in a confining harmonic potential, thereby constituting the paradigmatic model of overdamped, mean-reverting Langevin dynamics. Despite its widespread applicability, this model falls short when describing physical systems where the confining potential is itself subjected to stoc

Xiaolin Qin, Jiacen Liu, Qianlei Wang, Shaolin Zhang

Glass largely blurs the boundary between the real world and the reflection. The special transmittance and reflectance quality have confused the semantic tasks related to machine vision. Therefore, how to clear the boundary built by glass, and avoid over-capturing features as false positive information in deep structure, matters for constraining the segmentat

Hasan Mujtaba Buttar, Muhammad Mahboob Ur Rahman, Muhammad Wasim Nawaz, Adnan Noor Mian

This paper is the first to present a novel, non-contact method that utilizes orthogonal frequency division multiplexing (OFDM) signals (of frequency 5.23 GHz, emitted by a software defined radio) to radio-expose the pulmonary patients in order to differentiate between five prevalent respiratory diseases, i.e., Asthma, Chronic obstructive pulmonary disease (C

Jing Pan, Zhaoyang Wang, Yuan Meng, Xing Fu

Topological orders emerge in both microscopic quantum dynamics and macroscopic materials as a fundamental principle to characterize intricate properties in nature with vital significance, for instance, the Landau levels of electron systems in magnetic field. Whilst, recent advances of synthetic photonic systems enable generalized concepts of Landau levels ac

Hiroyasu Matsushima, Yusuke Tajima, Xiao-Nan Lu, Masakazu Jimbo

Group testing is utilized in the case when we want to find a few defectives among large amount of items. Testing n items one by one requires n tests, but if the ratio of defectives is small, group testing is an efficient way to reduce the number of tests. Many research have been developed for group testing for a single type of defectives. In this paper, we c

Majid Zarharan, Pascal Wullschleger, Babak Behkam Kia, Mohammad Taher Pilehvar

This paper presents a comprehensive analysis of explainable fact-checking through a series of experiments, focusing on the ability of large language models to verify public health claims and provide explanations or justifications for their veracity assessments. We examine the effectiveness of zero/few-shot prompting and parameter-efficient fine-tuning across

Vladimir Jacimovic

We propose the idea of using Kuramoto models (including their higher-dimensional generalizations) for machine learning over non-Euclidean data sets. These models are systems of matrix ODE's describing collective motions (swarming dynamics) of abstract particles (generalized oscillators) on spheres, homogeneous spaces and Lie groups. Such models have been ext

Alexander R. Muñoz, Travis E. Jones

Electronic correlations and spin-orbit interactions in plutonium create variations in the bonding behavior of each of its allotropes. In $\delta$-Pu, the 5f electrons lie at the tipping point between itinerant and localized behavior which makes the creation of predictive models very difficult. We perform density functional theory calculations to study the ef

Rui-Qing Fu, Jun Zhan, Matteo Dürrnagel, Hendrik Hohmann

Recent experiments have identified fascinating electronic orders in kagome materials, including intriguing superconductivity, charge density wave (CDW) and nematicity. In particular, some experimental evidence for AV$_3$Sb$_5$ (A = K,Rb,Cs) and related kagome metals hints at the formation of orbital currents in the charge density wave ordered regime, providi

Shubham Kukreja, Afshin Besharat, Sung-Sik Lee

In metals, low-energy effective theories are characterized by a set of coupling functions. Among them, the angle-dependent Fermi momentum specifies the size and shape of Fermi surface. Since the Fermi momentum grows incessantly under the renormalization group flow, a metallic fixed point is defined only modulo a rescaling of Fermi momentum. In this paper, we

Luca Caloni, Patrick Stengel, Massimiliano Lattanzi, Martina Gerbino

Cosmological observations allow to measure the abundance of light relics produced in the early Universe. Most studies focus on the thermal freeze-out scenario, yet light relics produced by freeze-in are generic for models in which new light degrees of freedom do not couple strongly enough to the Standard Model (SM) plasma to allow for full thermalization in

Diego Corro, Jesús Núñez-Zimbrón, Jaime Santos-Rodríguez

We study $\mathsf{RCD}$-spaces $(X,d,\mathfrak{m})$ with group actions by isometries preserving the reference measure $\mathfrak{m}$ and whose orbit space has dimension one, i.e. cohomogeneity one actions. To this end we prove a Slice Theorem asserting that when $X$ is non-collapsed the slices are homeomorphic to metric cones over homogeneous spaces with $\m

Manabu Machida

Rotated reference frames offer fast algorithms for the radiative transport equation (RTE). We review the singular-eigenfunction approach and related numerical methods for the multi-dimensional RTE with rotated reference frames.

Yufeng Jiang, Yiqing Shen

Medical imaging data is inherently heterogeneous across different modalities and clinical centers, posing unique challenges for developing generalizable foundation models. Conventional entails training distinct models per dataset or using a shared encoder with modality-specific decoders. However, these approaches incur heavy computational overheads and suffe

Shun-Li Shang, Rushi Gong, Michael C. Gao, Darren C. Pagan

An innovative method is developed for accurate determination of thermodynamic properties as a function of temperature by revisiting the density functional theory (DFT) based quasiharmonic approach (QHA). The present methodology individually evaluates the contributions from static total energy, phonon, and thermal electron to free energy for increased efficie

Flavio Cirillo, Gürkan Solmaz, Yi-Hsuan Peng, Christian Bizer

The process of clearing areas, namely demining, starts by assessing and prioritizing potential hazardous areas (i.e., desk assessment) to go under thorough investigation of experts, who confirm the risk and proceed with the mines clearance operations. This paper presents Desk-AId that supports the desk assessment phase by estimating landmine risks using geos

Jun Zhang, Gang Yang, Qibin Ye, Yixuan Huang

Integrated sensing and communication (ISAC) is a main application scenario of the sixth-generation mobile communication systems. Due to the fast-growing number of antennas and subcarriers in cellular systems, the computational complexity of joint azimuth-range-velocity estimation (JARVE) in ISAC systems is extremely high. This paper studies the JARVE problem

Aqsa Kashaf, Aidan Walsh, Maria Apostolaki, Vyas Sekar

There is anecdotal evidence that attackers use reconnaissance to learn the capacity of their victims before DDoS attacks to maximize their impact. The first step to mitigate capacity reconnaissance attacks is to understand their feasibility. However, the feasibility of capacity reconnaissance in network functions (NFs) (e.g., firewalls, NATs) is unknown. To

Hojin Cho, Jong-Hak Woo

We investigate the black hole mass function (BHMF) and the Eddington ratio distribution function (ERDF), focusing on the intermediate-mass black holes (IMBHs) with masses down to $M_{\bullet}\sim10^4 M_\odot$. Based on the active galactic nuclei (AGNs) with a detected broad H$\alpha$ emission line, we construct a sample of 14,242 AGNs at redshift $z<0.35$, i

Eric A. Wolf, Ivan Biaggio

The geminate annihilation of two triplet excitons created by singlet exciton fission is affected by the dimensionality of transport as determined by typically anisotropic triplet exciton mobilities in organic molecular crystals. We analyze this process using a random-walk model where the time-dynamics of the geminate annihilation probability is determined by

Michiel van der Meer

Modern democracies face a critical issue of declining citizen participation in decision-making. Online discussion forums are an important avenue for enhancing citizen participation. This thesis proposal 1) identifies the challenges involved in facilitating large-scale online discussions with Natural Language Processing (NLP), 2) suggests solutions to these c

Manuel A. Estrada, Claudia A. Pérez-Pinacho, Christopher D. Cruz-Ancona, Leonid Fridman

Lyapunov redesign is a classical technique that uses a nominal control and its corresponding nominal Lyapunov function to design a discontinuous control, such that it compensates the uncertainties and disturbances. In this paper, the idea of Lyapunov redesign is used to propose an adaptive time-varying gain controller to stabilize a class of perturbed chain

Edwar Alexis Ramírez Ardila

We will see how to define the metric $\beta$, which turns the topological space of continuous functions whose domains are open subsets of a locally compact and second countable space $X$ to values in a polish space $Y$, called $(C_{od}(X,Y),\tau_{\iota,D})$ into a polish space. In particular, we will present a metric for the inverse semigroup of homeomorphis

João Domingos, João Xavier

We consider the problem of robustly fitting a model to data that includes outliers by formulating a percentile optimization problem. This problem is non-smooth and non-convex, hence hard to solve. We derive properties that the minimizers of such problems must satisfy. These properties lead to methods that solve the percentile formulation both for general res

M. L. Peñafiel, S. E. Perez Bergliaffa

The electric potential and the electromagnetic field for a linearly accelerated Born-Infeld charged particle are obtained in an inertial frame by a method that can, in principle, be applied to any electromagnetic theory. The method is based on (i) the fact that the metric near the horizon of a Schwarzschild black hole is equivalent to that of Rindler spaceti

Antonio Montero, Micael Toledo

Abstract polytopes are combinatorial objects that generalise geometric objects such as convex polytopes, maps on surfaces and tilings of the space. Chiral polytopes are those abstract polytopes that admit full combinatorial rotational symmetry but do not admit reflections. In this paper we build chiral polytopes whose facets (maximal faces) are isomorphic to

Sebastian Meyer

On a finite structure, the polymorphism invariant relations are exactly the primitively positively definable relations. On infinite structures, these two sets of relations are different in general. Infinitary primitively positively definable relations are a natural intermediate concept which extends primitive positive definability by infinite conjunctions. W

Baoxin Liu, Zhenyu Zhang, Xiang Zhou

The exact analytic form of cross sections including initial state radiation with Kuraev-Fadin radiative function are obtained for $e^+e^-$ annihilation around a resonance. Despite accounting for vacuum polarization and center-of-mass energy spread effects, the precision remains below 0.1\%, meeting the accuracy requirements of quantum electrodynamics correct

Chenhan Jiang

3D content creation plays a vital role in various applications, such as gaming, robotics simulation, and virtual reality. However, the process is labor-intensive and time-consuming, requiring skilled designers to invest considerable effort in creating a single 3D asset. To address this challenge, text-to-3D generation technologies have emerged as a promising

Hiba Dakdouk, Mohamed Sana, Mattia Merluzzi

In recent years, the integration of communication and control systems has gained significant traction in various domains, ranging from autonomous vehicles to industrial automation and beyond. Multi-armed bandit (MAB) algorithms have proven their effectiveness as a robust framework for solving control problems. In this work, we investigate the use of MAB algo

Tibor Bisztriczky

Cyclic polytopes have been studied since at least the early last century by Caratheodory and others.A generalization is a construction of a class of polytopes such that the polytopes have some of their properties.The best known example is the class of neighbourly polytopes. Cyclic polytopes have explicit facet structures, important properties and application

Mohamed Benslimane

Let $U$ be an absolute ultrafilter on the set of non-negative integers $\mathbb{N}$. For any sequence $x=(x_n)_{n\geq 0}$ of real numbers, let $U(x)$ denote the topological filter consisting of the open sets $W$ of $\mathbb{R}$ with $\{n \geq 0, x_n \in W\} \in U$. It turns out that for every $x \in \mathbb{R}^{\mathbb{N}}$, the hyperreal $\overline{x}$ asso

Gil Serrano, Marcelo Jacinto, Jose Ribeiro-Gomes, Joao Pinto

Recent advances in aerial robotics have enabled the use of multirotor vehicles for autonomous payload transportation. Resorting only to classical methods to reliably model a quadrotor carrying a cable-slung load poses significant challenges. On the other hand, purely data-driven learning methods do not comply by design with the problem's physical constraints

Marian Rockenhäuser, Felix Kogel, Tatsam Garg, Sebastián A. Morales-Ramírez

We demonstrate laser cooling of barium monofluoride (138BaF) molecules. We use serrodynes to synthesize time-sequenced optical spectra that can be precisely tailored to the hyperfine structure of this heaviest non-radioactive alkaline earth monofluoride. By optimizing these optical spectra, we realize strong Sisyphus cooling forces that efficiently collimate

Memoona Aziz, Umair Rehman, Muhammad Umair Danish, Katarina Grolinger

This paper introduces the Global-Local Image Perceptual Score (GLIPS), an image metric designed to assess the photorealistic image quality of AI-generated images with a high degree of alignment to human visual perception. Traditional metrics such as FID and KID scores do not align closely with human evaluations. The proposed metric incorporates advanced tran

Jianan Bai, Erik G. Larsson

The wireless channel is undergoing continuous changes, and the block-fading assumption, despite its popularity in theoretical contexts, never holds true in practical scenarios. This discrepancy is particularly critical for user activity detection in grant-free random access, where joint processing across multiple resource blocks is usually undesirable. In th

Subhankar Mondal

This paper is concerned with the inverse problem of retrieving the initial value of a time-fractional fourth order parabolic equation from source and final time observation. The considered problem is an {\it ill-posed problem.} We obtain regularized approximations for the sought initial value by employing the quasi-boundary value method, its modified version

Johannes Jakubik, Michael Vössing, Manil Maskey, Christopher Wölfle

Identifying and handling label errors can significantly enhance the accuracy of supervised machine learning models. Recent approaches for identifying label errors demonstrate that a low self-confidence of models with respect to a certain label represents a good indicator of an erroneous label. However, latest work has built on softmax probabilities to measur

Miroslav Popovic, Marko Popovic, Ivan Kastelan, Miodrag Djukic

Recently, Python Testbed for Federated Learning Algorithms emerged as a low code and generative large language models amenable framework for developing decentralized and distributed applications, primarily targeting edge systems, by nonprofessional programmers with the help of emerging artificial intelligence tools. This light framework is written in pure Py

D. E. Afanasev, M. O. Katanaev

New one parameter family of exact solutions in General Relativity with a scalar field is found. The metric is of Liouville type which admits complete separation of variables in the geodesic Hamilton-Jacobi equation. This solution exists for the exponential potential for a scalar field and is invariant with respect to global Lorentz transformations. It descri

Jef Laga, Ashvin A. Swaminathan

Let $\mathcal{F}_g$ be the family of monic odd-degree hyperelliptic curves of genus $g$ over $\mathbb{Q}$. Poonen and Stoll have shown that for every $g \geq 3$, a positive proportion of curves in $\mathcal{F}_g$ have no rational points except the point at infinity. In this note, we prove the analogue for quadratic points: for each $g\geq 4$, a positive prop

Sébastien Roux, Christophe Arnold, Etienne Carré, Alexandre Plaud

One of the main interests of 2D materials is their ability to be assembled with many degrees of freedom for tuning and manipulating excitonic properties. There is a need to understand how the structure of the interfaces between atomic layers influences exciton properties. Here we use cathodoluminescence and time-resolved cathodoluminescence experiments to st

Feng Guo, Jie Wang, Jianhao Zheng

This paper is devoted to the problem of minimizing a sum of rational functions over a basic semialgebraic set. We provide a hierarchy of sum of squares (SOS) relaxations that is dual to the generalized moment problem approach due to Bugarin, Henrion, and Lasserre. The investigation of the dual SOS aspect offers two benefits: 1) it allows us to conduct a conv