December 2023 arXiv papers — page 111

Alexei Latyntsev

We develop vertex and factorisation algebra analogues of the theory of quasitriangular bialgebras. Analogously to the classical theory, we prove their categories of representations are controlled by spectral R-matrices. In the vertex algebra case this generalises previous notions due to Etingof-Kazhdan and Frenkel-Reshetikhin. Finally we give examples, inclu

Tuan Truong, Farnaz Khun Jush, Matthias Lenga

Near- and duplicate image detection is a critical concern in the field of medical imaging. Medical datasets often contain similar or duplicate images from various sources, which can lead to significant performance issues and evaluation biases, especially in machine learning tasks due to data leakage between training and testing subsets. In this paper, we pre

Qing-Hong Cao, Kun Cheng, Yandong Liu, Xiao-Rui Wang

The quartic Higgs-gauge-boson coupling $g_{hhWW}$ is sensitive to the electroweak symmetry breaking mechanism, however, it is challenging to be measured at the large hadron collider. We show that the coupling can be well probed at future lepton colliders through di-Higgs boson production via the vector boson fusion channel. We perform a detailed simulation o

Cheng Zeng, Yixuan Xu, Jiaqi Tian

This study explores the robustness of label noise classifiers, aiming to enhance model resilience against noisy data in complex real-world scenarios. Label noise in supervised learning, characterized by erroneous or imprecise labels, significantly impairs model performance. This research focuses on the increasingly pertinent issue of label noise's impact on

Cillian Doherty, Jason Miller

Suppose that $B$ is a one-dimensional Brownian motion and let $\Gamma = \{ (t, B_t) : t \in [0,1]\}$ be the graph of $B|_{[0,1]}$. We characterize the Sobolev removability properties of $\Gamma$ by showing that $\Gamma$ is almost surely not $W^{1,p}$--removable for all $p \in [1, \infty)$ but is almost surely $W^{1,\infty}$--removable.

Yuxuan Lu, Yuqing Kong

Peer review lies at the core of the academic process, but even well-intentioned reviewers can still provide noisy ratings. While ranking papers by average ratings may reduce noise, varying noise levels and systematic biases stemming from ``cheap'' signals (e.g. author identity, proof length) can lead to unfairness. Detecting and correcting bias is challengin

Paolo Bignardi, Andrea Moiola

We propose a new space-time variational formulation for wave equation initial-boundary value problems. The key property is that the formulation is coercive (sign-definite) and continuous in a norm stronger than $H^1(Q)$, $Q$ being the space-time cylinder. Coercivity holds for constant-coefficient impedance cavity problems posed in star-shaped domains, and fo

Xinyan Ma, Wei Li, Jian Zhong, Jinyu Li

The development of U.S. Army and NATO data link systems is introduced first, and then the development trend of future intelligent data link is summarized into integration, generalization, multifunctionality and high security. A unit-level combat system architecture based on the global combat cloud, which is capable of realizing the flexible scheduling of glo

Alexander R. Miller

If all of the entries of a large $S_n$ character table are covered up and you are allowed to uncover one entry at a time, then how can you quickly identify all of the indexing characters and conjugacy classes? We present a fast algorithmic solution that works even when n is so large that almost none of the entries of the character table can be computed. The

Joonhyun Jeong, Geondo Park, Jayeon Yoo, Hyungsik Jung

Open-vocabulary object detection (OVOD) aims to recognize novel objects whose categories are not included in the training set. In order to classify these unseen classes during training, many OVOD frameworks leverage the zero-shot capability of largely pretrained vision and language models, such as CLIP. To further improve generalization on the unseen novel c

Miao Du, Jiaxin Xu

In this paper, we deal with the planar Schr\"{o}dinger-Poisson system \begin{equation*}\begin{cases} -\Delta u + V(x) u + \phi u = b|u|^{p-2} u \ &\text{in}\ \mathbb{R}^{2},\\\Delta \phi= u^{2} &\text{in}\ \mathbb{R}^{2},\end{cases} \end{equation*} where $b \geq 0$, $p > 2 $ and $V \in C(\mathbb{R}^2, \mathbb{R})$ is a potential function with $\inf_{\mathbb{

Yuliang Gu, Zhichao Sun, Tian Chen, Xin Xiao

Semi-supervised image segmentation has attracted great attention recently. The key is how to leverage unlabeled images in the training process. Most methods maintain consistent predictions of the unlabeled images under variations (e.g., adding noise/perturbations, or creating alternative versions) in the image and/or model level. In most image-level variatio

Zhibo Chen, Frank Pfenning

Higher-order unification has been shown to be undecidable. Miller discovered the pattern fragment and subsequently showed that higher-order pattern unification is decidable and has most general unifiers. We extend the algorithm to higher-order rational terms (a.k.a. regular B\"{o}hm trees, a form of cyclic $\lambda$-terms) and show that pattern unification o

Takahiro Onizuka, Shintaro Hashimoto

Gaussian graphical model is one of the powerful tools to analyze conditional independence between two variables for multivariate Gaussian-distributed observations. When the dimension of data is moderate or high, penalized likelihood methods such as the graphical lasso are useful to detect significant conditional independence structures. However, the estimate

Huibert A. J. van Riessen, Yasemin Vardar

Wearable devices that relocate tactile feedback from fingertips can enable users to interact with their physical world augmented by virtual effects. While studies have shown that relocating same-modality tactile stimuli can influence the one perceived at the fingertip, the interaction of cross-modal tactile stimuli remains unclear. Here, we investigate how t

Dimitris M. Manias, Dimitris G. Patsatzis, Dimitris A. Goussis

The results of an alternative methodology for making predictions about the COVID-19 pandemic in Greece are presented. Instead of focusing on the various population profiles (subjected to instabilities introduced by the fitting process), this methodology focuses on the time scale that characterises the intensity and duration of the outbreak phase. Therefore,

Ping Li, Xiaomei Sun, Anqiang Zhu

We are concerned in this article with a classical topic in spectral geometry dating back to McKean-Singer, Patodi and Tanno: whether or not the constancy of sectional curvature (resp. holomorphic sectional curvature) of a compact Riemannian manifold (resp. K\"{a}hler manifold) can be completely determined by the eigenvalues of its $p$-Laplacian for a \emph{s

Renyang Liu, Wei Zhou, Sixin Wu, Jun Zhao

Extensive studies have demonstrated that deep neural networks (DNNs) are vulnerable to adversarial attacks, which brings a huge security risk to the further application of DNNs, especially for the AI models developed in the real world. Despite the significant progress that has been made recently, existing attack methods still suffer from the unsatisfactory p

Xiaofeng Zhang, Xiaoyi Tian, Qingxiang Xu

This paper deals mainly with some aspects of the adjointable operators on Hilbert $C^*$-modules. A new tool called the generalized polar decomposition for each adjointable operator is introduced and clarified. As an application, the general theory of the weakly complementable operators is set up in the framework of Hilbert $C^*$-modules. It is proved that th

Koki Shimura, Rina Tazai, Youichi Yamakawa, Seiichiro Onari

The charge loop current (cLC) state has attracted increasing attention in kagome metals. Here, we calculate the spontaneous currents along the nearest sites $i$ and $j$, $J_{i,j}$, induced by the cLC order that is the imaginary and odd-parity hopping integral modulation $\delta t_{i,j}$. We reveal that the magnitude of $J_{i,j}$ strongly depends on the neare

Jiacheng Ruan, Jingsheng Gao, Mingye Xie, Suncheng Xiang

The Parameter-Efficient Fine-Tuning (PEFT) method, which adjusts or introduces fewer trainable parameters to calibrate pre-trained models on downstream tasks, has become a recent research interest. However, existing PEFT methods within the traditional fine-tiuning framework have two main shortcomings: 1) They overlook the explicit association between trainab

Shengqiang Li, Chao Lei, Baozhong Ma, Binbin Zhang

This study describes our system for Task 1 Single-speaker Visual Speech Recognition (VSR) fixed track in the Chinese Continuous Visual Speech Recognition Challenge (CNVSRC) 2023. Specifically, we use intermediate connectionist temporal classification (Inter CTC) residual modules to relax the conditional independence assumption of CTC in our model. Then we us

Dominik Burek

We give new relations between geometric invariants of $K3$ surfaces with purely non-symplectic automorphisms of order 4 and 6. Our approach is based on a comparison of two methods of computation of formulas for the Euler characteristic of higher dimensional generalized Borcea-Vosin Calabi-Yau manifolds constructed in [Bur21].

Pascal Iversen, Simon Witzke, Katharina Baum, Bernhard Y. Renard

Explainability and uncertainty quantification are key to trustable artificial intelligence. However, the reasoning behind uncertainty estimates is generally left unexplained. Identifying the drivers of uncertainty complements explanations of point predictions in recognizing model limitations and enhancing transparent decision-making. So far, explanations of

J. Liu, W. Xu, Y. M. Xiao, L. Ding

In this paper, we examined the effects of proximity-induced interactions such as Rashba spin-orbit coupling (SOC) and effective Zeeman fields (EZFs) on the optical spectrum of $n$-type and $p$-type monolayer (ML)-MoS$_2$. The optical conductivity is evaluated using the standard Kubo formula under Random phase approximation (RPA) with including the effective

Lifeng Han, Serge Gladkoff, Gleb Erofeev, Irina Sorokina

We conduct investigations on clinical text machine translation by examining multilingual neural network models using deep learning such as Transformer based structures. Furthermore, to address the language resource imbalance issue, we also carry out experiments using a transfer learning methodology based on massive multilingual pre-trained language models (M

Kristian Uldall Kristiansen, Rafael Ortega

In this paper, we revisit the damped Kepler problem within a general family of nonlinear damping forces with magnitude $\delta \vert u\vert^{\beta}\vert \dot u\vert^{\alpha+1}$, depending on three parameters $\delta>0,\alpha\ge 0$ and $\beta\ge 0$, and address the general question of circularization whereby orbits tend to become more circular as they approac

Chengyang Ye, Qiang Ma

Representation learning plays a critical role in the analysis of time series data and has high practical value across a wide range of applications. including trend analysis, time series data retrieval and forecasting. In practice, data confusion is a significant issue as it can considerably impact the effectiveness and accuracy of data analysis, machine lear

So Katagiri

This paper explores the Bogoliubov transformation's extension to two-mode squeezed states, building on our previous work with Virasoro-squeezing. We establish the Virasoro-Bogoliubov transformation as a non-linear extension of the traditional Bogoliubov transformation, creating non-linear two-mode squeezed states. This research unveils novel quantum states w

Sunghwan Hong, Jaewoo Jung, Heeseong Shin, Jiaolong Yang

This work delves into the task of pose-free novel view synthesis from stereo pairs, a challenging and pioneering task in 3D vision. Our innovative framework, unlike any before, seamlessly integrates 2D correspondence matching, camera pose estimation, and NeRF rendering, fostering a synergistic enhancement of these tasks. We achieve this through designing an

Renyang Liu, Wei Zhou, Xin Jin, Song Gao

In generating adversarial examples, the conventional black-box attack methods rely on sufficient feedback from the to-be-attacked models by repeatedly querying until the attack is successful, which usually results in thousands of trials during an attack. This may be unacceptable in real applications since Machine Learning as a Service Platform (MLaaS) usuall

Gevin von Witte, Aaron Himmler, Sebastian Kozerke, Matthias Ernst

Dynamic nuclear polarization enables the hyperpolarization of nuclear spins beyond the thermal-equilibrium Boltzmann distribution. However, it is often unclear why the experimentally measured hyperpolarization is below the theoretical achievable maximum polarization. We report a (near-) resonant relaxation enhancement by microwave (MW) irradiation, leading t

Enshu Liu, Xuefei Ning, Huazhong Yang, Yu Wang

Recent years have witnessed the rapid progress and broad application of diffusion probabilistic models (DPMs). Sampling from DPMs can be viewed as solving an ordinary differential equation (ODE). Despite the promising performance, the generation of DPMs usually consumes much time due to the large number of function evaluations (NFE). Though recent works have

Sergei M. Kuzenko, Emmanouil S. N. Raptakis

We develop a superspace formulation for ${\cal N}=3$ conformal supergravity in four spacetime dimensions as a gauge theory of the superconformal group $\mathsf{SU}(2,2|3)$. Upon imposing certain covariant constraints, the algebra of conformally covariant derivatives $\nabla_A = (\nabla_a,\nabla_\alpha^i,\bar{\nabla}_i^{\dot \alpha})$ is shown to be determine

Ayumi Igarashi, Naoyuki Kamiyama, Warut Suksompong, Sheung Man Yuen

In the allocation of indivisible goods, a prominent fairness notion is envy-freeness up to one good (EF1). We initiate the study of reachability problems in fair division by investigating the problem of whether one EF1 allocation can be reached from another EF1 allocation via a sequence of exchanges such that every intermediate allocation is also EF1. We sho

Gordon Rausser, Galina Chebotareva, Wadim Strielkowski, Lubos Smutka

This paper explores the critical question of the sustainability of Russian solar energy initiatives in the absence of governmental financial support. The study aims to determine if Russian energy companies can maintain operations in the solar energy sector without relying on direct state subsidies. Methodologically, the analysis utilizes established investme

Susanne Liese, Xueping Zhao, Christoph A. Weber, Frank Jülicher

Wetting of liquid droplets on passive surfaces is ubiquitous in our daily lives, and the governing physical laws are well-understood. When surfaces become active, however, the governing laws of wetting remain elusive. Here we propose chemically active wetting as a new class of active systems where the surface is active due to a binding process that is mainta

Xiangming Kong, Zhaolong Liu, Xiangqi Liu, Chunqiang Xu

We report an unusual evolution of superconductivity (SC) in the three-dimensional Dirac semimetal PdTe with increasing pressure up to $\sim$50 GPa. The compressed PdTe exhibits a sudden reversal in the superconducting transition temperature $T\mathrm{_c}$, from an initial decrease with pressure to an increase above a critical pressure $P\mathrm{_c} \approx$

Victor Berezin, Inna Ivanova

Using a model for an ideal fluid with a variable number of particles, a phenomenological description of the processes of particle production in strong external fields is investigated. The conformal invariance of the creation law is shown, which imposes rather rigorous restrictions on the possible types of sources. It appears that the combinations with the pa

Daria Kubyshkina, Luca Fossati, Nikolai V. Erkaev

Observational breakthroughs in the exoplanet field of the last decade motivated the development of numerous theoretical models describing atmospheres and mass loss, which is believed to be one of the main drivers of planetary evolution. We aim to outline for which types of close-in planets in the Neptune-mass range the accurate treatment of photoionisation e

Layna Charlie Dennett, Dankmar Böhning

Capture-recapture methods for estimating the total size of elusive populations are widely-used, however, due to the choice of estimator impacting upon the results and conclusions made, the question of performance of each estimator is raised. Motivated by an application of the estimators which allow covariate information to meta-analytic data focused on the p

Jean Cazalis, Yahui Chai, Karl Jansen, Stefan Kühn

In this study, we consider a Gaussian Boson Sampler for solving a Flight Gate Assignment problem. We employ a Variational Quantum Eigensolver approach using the Conditional Value-at-risk cost function. We provide proof of principle by carrying out numerical simulations on randomly generated instances.

Nils Wilde, Javier Alonso-Mora

We study the problem of selecting a fleet of robots to service spatially distributed tasks with diverse requirements within time-windows. The problem of allocating tasks to a fleet of potentially heterogeneous robots and finding an optimal sequence for each robot is known as multi-robot task assignment (MRTA). Most state-of-the-art methods focus on the probl

Jonas Nehme

The periplectic Lie superalgebra $\mathfrak{p}(n)$ is one of the most mysterious and least understood simple classical Lie superalgebras with reductive even part. We approach the study of its finite dimensional representation theory in terms of Schur--Weyl duality. We provide an idempotent version of its centralizer, i.e. the super Brauer algebra. We use thi

Antonio Mancino, Luca Ciotti, Silvia Pellegrini, Federica Giannetti

In the homoeoidal expansion, a given ellipsoidally stratified density distribution, and its associated potential, are expanded in the (small) density flattening parameter $\eta$, and usually truncated at the linear order. The truncated density-potential pair obeys exactly the Poisson equation, and it can be interpreted as the first-order expansion of the ori

Reto Buzano, Sylvain Maillot

We prove that the moduli space of mean convex two-spheres embedded in complete, orientable 3-dimensional Riemannian manifolds with nonnegative Ricci curvature is path-connected. This result is sharp in the sense that neither of the conditions of (strict) mean convexity, completeness, and nonnegativity of the Ricci curvature can be dropped or weakened. We als

Shentong Mo, Enze Xie, Yue Wu, Junsong Chen

Diffusion Transformers have recently shown remarkable effectiveness in generating high-quality 3D point clouds. However, training voxel-based diffusion models for high-resolution 3D voxels remains prohibitively expensive due to the cubic complexity of attention operators, which arises from the additional dimension of voxels. Motivated by the inherent redunda

Johanna Knapp

We discuss a simple model for D-brane transport in non-abelian GLSMs. The model is the elliptic curve version of a non-abelian GLSM introduced by Hori and Tong and has gauge group U(2). It has two geometric phases, both of which describe the same elliptic curve, once realised as a codimension five complete intersection in G(2,5) and once as a determinantal v

Emilien Bodiot, Damien Simon

The theory of Markov processes on the square lattice has been given recently by the second author a new algebraic description in terms of operads. In particular, this new approach allows for a nice description of invariant boundary conditions and infinite-volume Gibbs measures. This theory comes with new algebraic objects which have not been constructed on a

Robert F. Schmidt, Henrik Kiefer, Robert Dalgliesh, Michael Gradzielski

Deviations between macrorheological and particle-based microrheological measurements are often considered a nuisance and neglected. We study aqueous poly(ethylene oxide) (PEO) hydrogels for varying PEO concentrations and chain lengths that contain microscopic tracer particles and show that these deviations in fact reveal the nanoscopic viscoelastic propertie

Imene Bensalem, Paolo Rosso, Hanane Zitouni

The detection of toxic language in the Arabic language has emerged as an active area of research in recent years, and reviewing the existing datasets employed for training the developed solutions has become a pressing need. This paper offers a comprehensive survey of Arabic datasets focused on online toxic language. We systematically gathered a total of 54 a

Nils Wilde, Stephen L. Smith, Javier Alonso-Mora

When designing a motion planner for autonomous robots there are usually multiple objectives to be considered. However, a cost function that yields the desired trade-off between objectives is not easily obtainable. A common technique across many applications is to use a weighted sum of relevant objective functions and then carefully adapt the weights. However

Kai Pan, Linyang Li, Li Lin, Pujin Cheng

Photoacoustic Microscopy (PAM) images integrating the advantages of optical contrast and acoustic resolution have been widely used in brain studies. However, there exists a trade-off between scanning speed and image resolution. Compared with traditional raster scanning, rotational scanning provides good opportunities for fast PAM imaging by optimizing the sc

Sarina M. Sutter, Markus Penz, Michael Ruggenthaler, Robert van Leeuwen

We provide a solution to the v-representability problem for a non-relativistic quantum many-particle system on a ring domain in terms of Sobolev spaces and their duals. Any one-particle density that is square-integrable, has a square-integrable weak derivative, and is gapped away from zero can be realized from the solution of a many-particle Schr\"odinger eq

Yuan Yue, Yong-Qiang Wang

Recently, the model of the Einstein-Bardeen theory minimally coupled to a complex, massive, free scalar field was investigated in arXiv:2305.19057. The introduction of a scalar field disrupts the formation of an event horizon, leaving only a type of solution referred to as a Bardeen-boson star. When the magnetic charge $q$ exceeds a certain critical value, t

Fausto Barbero

We investigate the generalization of causal models to the case of indeterministic causal laws that was suggested in Halpern (2000). We give an overview of what differences in modeling are enforced by this more general perspective, and propose an implementation of generalized models in the style of the causal team semantics of Barbero & Sandu (2020). In these

Ondřej Mokrý, Jiří Vitouš, Pavel Rajmic, Radovan Jiřík

A method for perfusion imaging with DCE-MRI is developed based on two popular paradigms: the low-rank + sparse model for optimisation-based reconstruction, and the deep unfolding. A learnable algorithm derived from a proximal algorithm is designed with emphasis on simplicity and interpretability. The resulting deep network is trained and evaluated using a si

Yuanbin Wang, Shaofei Huang, Yulu Gao, Zhen Wang

Traditional 3D segmentation methods can only recognize a fixed range of classes that appear in the training set, which limits their application in real-world scenarios due to the lack of generalization ability. Large-scale visual-language pre-trained models, such as CLIP, have shown their generalization ability in the zero-shot 2D vision tasks, but are still

Prashanthi S. K., Vinayaka Hegde, Keerthana Patchava, Ankita Das

Edge devices have typically been used for DNN inferencing. The increase in the compute power of accelerated edges is leading to their use in DNN training also. As privacy becomes a concern on multi-tenant edge devices, Docker containers provide a lightweight virtualization mechanism to sandbox models. But their overheads for edge devices are not yet explored

Houssine Zine, El Mehdi Lotfi, Delfim F. M. Torres, Noura Yousfi

Using the recent weighted generalized fractional order operators of Hattaf, a general fractional optimal control problem without constraints on the values of the control functions is formulated and a corresponding (weak) version of Pontryagin's maximum principle is proved. As corollaries, necessary optimality conditions for Caputo-Fabrizio, Atangana-Baleanu

Yuxi, Lu, Tobias Buck, David Nidever

It is well known that stars move away from their birth location over time via radial migration. This dynamical process makes computing the correct chemical evolution, e.g., metallicity gradients, of galaxies very difficult. This dynamical process makes inferring the chemical evolution of observed galaxies from their measured abundance gradients very difficul

Wei Ke

We consider the uniqueness of the following positive solutions of $m$-Laplacian equation: \begin{equation} \left\{ \begin{aligned} -\Delta _m u&=\lambda u^{m-1}+u^{p-1} \quad \text{in} \quad \Omega\\ u&=0 \quad \text{on} \quad \partial \Omega \end{aligned} \right. \qquad(0.1)\end{equation} where $m>1$ is a constant. When $p\rightarrow m$, the uniqueness of p

Rafael Bailo, José Antonio Carrillo, Andrea Medaglia, Mattia Zanella

We design a deterministic particle method for the solution of the spatially homogeneous Landau equation with uncertainty. The deterministic particle approximation is based on the reformulation of the Landau equation as a formal gradient flow on the set of probability measures, whereas the propagation of uncertain quantities is computed by means of a sg repre

Ivan De Martino

Axions, and axion-like particles, have come back into fashion in the last decades as a possible solution to the galactic-scale crisis suffered by the cold dark matter model. In the framework of the wave Dark Matter model, we have carried out a Jeans Analysis on eight dwarf spheroidal galaxies that are orbiting around the Milky Way, and we have constrained th

Daniel Gaspar-Figueiredo

The continuous adaptation of software systems to meet the evolving needs of users is very important for enhancing user experience (UX). User interface (UI) adaptation, which involves adjusting the layout, navigation, and content presentation based on user preferences and contextual conditions, plays an important role in achieving this goal. However, suggesti

Cong Xu, Zhaoqi Wu, Shao-Ming Fei

We establish tighter uncertainty relations for arbitrary finite observables via $(\alpha,\beta,\gamma)$ weighted Wigner-Yanase-Dyson ($(\alpha,\beta,\gamma)$WWYD) skew information. The results are also applicable to the $(\alpha,\gamma)$ weighted Wigner-Yanase-Dyson ($(\alpha,\gamma)$WWYD) skew information and the weighted Wigner-Yanase-Dyson (WWYD) skew inf

Ignacio Romero, Michael Ortiz

We introduce the energy-stepping Monte Carlo (ESMC) method, a Markov chain Monte Carlo (MCMC) algorithm based on the conventional dynamical interpretation of the proposal stage but employing an energy-stepping integrator. The energy-stepping integrator is quasi-explicit, symplectic, energy-conserving, and symmetry-preserving. As a result of the exact energy

Juan José López Escobar, Manuel Ricardo, Rui Campos, Felipe Gil-Castiñeira

Management of network resources in advanced IoT applications is a challenging topic due to their distributed nature from the Edge to the Cloud, and the heavy demand of real-time data from many sources to take action in the deployment. FANETs (Flying Ad-hoc Networks) are a clear example of heterogeneous multi-modal use cases, which require strict quality in t

Younes Lakhnati, Max Pascher, Jens Gerken

In a rapidly evolving digital landscape autonomous tools and robots are becoming commonplace. Recognizing the significance of this development, this paper explores the integration of Large Language Models (LLMs) like Generative pre-trained transformer (GPT) into human-robot teaming environments to facilitate variable autonomy through the means of verbal huma

Bihui Yu, Sibo Zhang, Lili Zhou, Jingxuan Wei

The continuous development of artificial intelligence has a profound impact on biomedicine and other fields, providing new research ideas and technical methods. Brain-inspired computing is an important intersection between multimodal technology and biomedical field. Focusing on the application scenarios of decoding text and speech from brain signals in human

Peiwen Sun, Yifan Zhang, Zishan Liu, Donghao Chen

The vanilla fusion methods still dominate a large percentage of mainstream audio-visual tasks. However, the effectiveness of vanilla fusion from a theoretical perspective is still worth discussing. Thus, this paper reconsiders the signal fused in the multimodal case from a bionics perspective and proposes a simple, plug-and-play, attention module for vanilla

Soham Sen, Sunandan Gangopadhyay

The effect of the noise induced by gravitons in the case of a freely falling particle from the viewpoint of an external observer has been recently calculated in \href{https://link.aps.org/doi/10.1103/PhysRevD.107.066024}{Phys. Rev. D 107 (2023) 066024}. There the authors have calculated the quantum gravity modified Newton's law of free fall where the spaceti

Martin Li, Davide Parise, Lorenzo Sarnataro

We study the boundary behavior of any limit-interface arising from a sequence of general critical points of the Allen-Cahn energy functionals on a smooth bounded domain. Given any such sequence with uniform energy bounds, we prove that the limit-interface is a free boundary varifold which is integer rectifiable up to the boundary. This extends earlier work o

Mikhail Luginin, Alexander Trokhimovskiy, Benjamin Taysum, Anna A. Fedorova

In 2020, hydrogen chloride (HCl) in the gas phase was discovered in the atmosphere of Mars with the Atmospheric Chemistry Suite (ACS) onboard the Trace Gas Orbiter (TGO) mission (Korablev et al., 2021). Its volume mixing ratio (VMR) shows a seasonal increase of up to 5 ppbv during the perihelion season, followed by a sudden drop to undetectable levels, contr

Lars E. Kruse, Sebastian Kühl, Annika Dochhan, Stephan Pachnicke

The demand for high-speed data is exponentially growing. To conquer this, optical networks underwent significant changes getting more complex and versatile. The increasing complexity necessitates the fault management to be more adaptive to enhance network assurance. In this paper, we experimentally compare the performance of soft-failure management of differ

Xiaojie Fang, Xingguo Song, Xiangyin Meng, Xu Fang

The low-level spatial detail information and high-level semantic abstract information are both essential to the semantic segmentation task. The features extracted by the deep network can obtain rich semantic information, while a lot of spatial information is lost. However, how to recover spatial detail information effectively and fuse it with high-level sema

Théo Verhelst, Denis Mercier, Jeevan Shrestha, Gianluca Bontempi

Uplift modeling, also known as individual treatment effect (ITE) estimation, is an important approach for data-driven decision making that aims to identify the causal impact of an intervention on individuals. This paper introduces a new benchmark dataset for uplift modeling focused on churn prediction, coming from a telecom company in Belgium, Orange Belgium

Suyash Shrestha, Joey Dekker, Marc Gerritsma, Steven Hulshoff

In this paper, we build on the work of [T. Hughes, G. Sangalli, VARIATIONAL MULTISCALE ANALYSIS: THE FINE-SCALE GREENS' FUNCTION, PROJECTION, OPTIMIZATION, LOCALIZATION, AND STABILIZED METHODS, SIAM Journal of Numerical Analysis, 45(2), 2007] dealing with the explicit computation of the Fine-Scale Green's function. The original approach chooses a set of func

V. Kumar, S. Basnet, E. Cortina Gil, P. Demin

This paper reports the latest developmental efforts for a position-sensitive glass-based Resistive Plate Chamber (RPC) and a multi-channel Data AcQuisition (DAQ) system tailored for muon tracking in muography applications. The designed setup prioritizes portability, aiming for field applications where both the detector and the DAQ operate effectively in exte

Zheru Qiu, Zihan Li, Rui Ning Wang, Xinru Ji

The advances in novel low-loss "on insulator" integrated photonics platforms beyond silicon, such as thin-film LiNbO3, LiTaO3, GaP and BaTiO3 have demonstrated major potential across a wide range of applications, due to their unique electro-optical or nonlinear optical properties. This has heralded novel devices, ranging from low-voltage and high-speed modul

Giulio Falcioni, Alexandra Georgescu, Emilia Molimpakis, Lev Gottlieb

This research report presents a proof-of-concept study on the application of machine learning techniques to video and speech data collected during diagnostic cognitive assessments of children with a neurodevelopmental disorder. The study utilised a dataset of 39 video recordings, capturing extensive sessions where clinicians administered, among other things,

Chetanya Rastogi, Prabhat Agarwal, Shreya Singh

In many applications, such as scientific literature management, researcher search, social network analysis and etc, Name Disambiguation (aiming at disambiguating WhoIsWho) has been a challenging problem. In addition, the growth of scientific literature makes the problem more difficult and urgent. Although name disambiguation has been extensively studied in a

San-Dong Guo, Yu-Ling Tao, Zi-Yang Zhuo, Gangqiang Zhu

The combination of antiferromagnetic (AFM) spintronics and anomalous valley Hall effect (AVHE) is of great significance for potential applications in valleytronics. Here, we propose a design principle for achieving AVHE in A-type hexagonal AFM monolayer. The design principle involves the introduction of layer-dependent electrostatic potential caused by out-o

Jia-Meng Yao, Qiong Li, Hao-Kun Mao, Ahmed A. Abd El-Latif

With the advancement of quantum computing, the security of public key cryptography is under serious threat. To guarantee security in the quantum era, Quantum Key Distribution has become a competitive solution. QKD networks can be classified into measurement-device-dependent network and measurement-device-independent network. In measurement-device-dependent n

Sheng Zhang, Hui Li

Code pre-trained language models (CPLMs) have received great attention since they can benefit various tasks that facilitate software development and maintenance. However, CPLMs are trained on massive open-source code, raising concerns about potential data infringement. This paper launches the study of detecting unauthorized code use in CPLMs, i.e., Code Memb

Ilektra Karasante, Lazaro Alonso, Ioannis Prapas, Akanksha Ahuja

The global occurrence, scale, and frequency of wildfires pose significant threats to ecosystem services and human livelihoods. To effectively quantify and attribute the antecedent conditions for wildfires, a thorough understanding of Earth system dynamics is imperative. In response, we introduce the SeasFire datacube, a meticulously curated spatiotemporal da

Roy Aleksan, Luis Oliver

We underline the theoretical and experimental interest of the vector-vector penguin decays ${\rm \overline{B}}_{d,s} \to {\rm K^{*0} \overline{K}^{*0}}$ for which the data show a strong U-spin violation. Indeed, with the latest LHCb data one has for these two modes very different longitudinal polarization fractions, $f_L^{exp}({\rm \overline{B}}_s \to {\rm K

Juan José López Escobar, Felipe Gil-Castiñeira, Rebeca P. Díaz-Redondo

The emergence of Low-Power Wide-Area Network (LPWAN) technologies allowed the development of revolutionary Internet Of Things (IoT) applications covering large areas with thousands of devices. However, connectivity may be a challenge for non-line-of-sight indoor operation or for areas without good coverage. Technologies such as LoRa and Sigfox allow connecti

Leonid Positselski

A general principle suggests that "anything flat is a directed colimit of countably presentable flats". In this paper, we consider resolutions and coresolutions of modules over a countably coherent ring $R$ (e.g., any coherent ring or any countably Noetherian ring). We show that any $R$-module of flat dimension $n$ is a directed colimit of countably presenta

Jose Aurelio Medina-Garrido, Jose Maria Biedma-Ferrer, Antonio Rafael Ramos-Rodriguez

This study analyzes the impact of work-family policies (WFP) on job performance, and the possible moderating role of gender and family responsibilities. Hypothesis testing was performed using a structural equation model based on a PLS-SEM approach applied to a sample of 1,511 employees of the Spanish banking sector. The results show that neither the existenc

Rufat Badal, Manuel Friedrich, Lennart Machill

We derive a von K\'arm\'an plate theory from a three-dimensional quasistatic nonlinear model for nonsimple thermoviscoelastic materials in the Kelvin-Voigt rheology, in which the elastic and the viscous stress tensor comply with a frame indifference principle [Mielke-Roub\'{i}\v{c}ek '20]. In a dimension-reduction limit, we show that weak solutions to the no

Siddharth Barman, Umang Bhaskar, Yeshwant Pandit, Soumyajit Pyne

Equitability (EQ) in fair division requires that items be allocated such that all agents value the bundle they receive equally. With indivisible items, an equitable allocation may not exist, and hence we instead consider a meaningful analog, EQx, that requires equitability up to any item. EQx allocations exist for monotone, additive valuations. However, if (

Tatjana Scheffler, Veronika Solopova, Mihaela Popa-Wyatt

In this working paper, we turn our attention to two exemplary, cross-media shitstorms directed against well-known individuals from the business world. Both have in common, first, the trigger, a controversial statement by the person who thereby becomes the target of the shitstorm, and second, the identity of this target as relatively privileged: cis-male, whi

Maryam Bajalan, Ivan Landjev, Edgar Martínez-Moro, Steve Szabo

In this paper, we study the algebraic structure of $(\sigma,\delta)$-polycyclic codes, defined as submodules in the quotient module $S/Sf$, where $S=R[x,\sigma,\delta]$ is the Ore extension ring, $f\in S$, and $R$ is a finite but not necessarily commutative ring. We establish that the Euclidean duals of $(\sigma,\delta)$-polycyclic codes are $(\sigma,\delta)

Pablo Picazo, Milan Groshev, Alejandro Blanco, Claudio Fiandrino

This paper presents the design, implementation and evaluation of waveSLAM, a low-cost mobile robot system that uses the millimetre wave (mmWave) communication devices to enhance the indoor mapping process targeting environments with reduced visibility or glass/mirror walls. A unique feature of waveSLAM is that it only leverages existing Commercial-Off-The-Sh

Olha Shulika, Michal Bujak, Farnoud Ghasemi, Rafal Kucharski

Ride-pooling systems, despite being an appealing urban mobility mode, still struggle to gain momentum. While we know the significance of critical mass in reaching system sustainability, less is known about the spatiotemporal patterns of system performance. Here, we use 1.5 million NYC taxi trips (sampled over a six-month period) and experiment to understand

Yuda Zou, Xin Xiao, Peilin Zhou, Zhichao Sun

Object counting typically uses 2D point annotations. The complexity of object shapes and the subjectivity of annotators may lead to annotation inconsistency, potentially confusing counting model training. Some sophisticated noise-resistance counting methods have been proposed to alleviate this issue. Differently, we aim to directly refine the initial point a

Edvin G. Idrisov, Ivan P. Levkivskyi, Eugene V. Sukhorukov

We address the experimentally relevant situation, where a non-equilibrium state is created at the edge of a quantum Hall system by injecting charge current into a chiral edge state with the help of a quantum point contact, quantum dots, or mesoscopic Ohmic contact. We show that the commonly accepted picture of the full equilibration of a non-equilibrium stat

Ye-Huang Pang, Xue Zhang, Qing-Guo Huang

Recently, the emergence of cosmological tension has raised doubts about the consistency of the $\Lambda$CDM model. In order to constrain the neutrino mass within a consistent cosmological framework, we investigate three massive neutrinos with normal hierarchy (NH) and inverted hierarchy (IH) in both the axion-like EDE (Axi-EDE) model and the AdS-EDE model. W

Yang Li, Guiling Chen

In this paper, we study boundedness, uniform stability and asymptotic stability of a class of nonlinear neutral delay differential equations by using Krasnoselskii's fixed point theorem. The results obtained in this paper extend and improve the work of Jin and Luo(Nonlinear Anal 68:3307-3315,2008), and Benhadri, Mimia(Differ Equ Dyn Syst 29:3-19,2021). An ex