March 2024 arXiv papers — page 76

Siqi Qu, Mathias Staudigl

Solving equilibrium problems under constraints is an important problem in optimization and optimal control. In this context an important practical challenge is the efficient incorporation of constraints. We develop a continuous-time method for solving constrained variational inequalities based on a new penalty regulated dynamical system in a general potentia

Antonio Capolupo, Aniello Quaranta

We reveal the presence of a new source of axial current due to the condensed vacuum generated by the spin-spin interaction. To show this, we consider a quartic Dirac Lagrangian containing a spin-spin interaction term, possibly originating from torsion in Einstein-Cartan-like theories. We use a mean field approach to analyze the quantized theory. We show that

Christopher Bülte, Nina Horat, Julian Quinting, Sebastian Lerch

Artificial intelligence (AI)-based data-driven weather forecasting models have experienced rapid progress over the last years. Recent studies, with models trained on reanalysis data, achieve impressive results and demonstrate substantial improvements over state-of-the-art physics-based numerical weather prediction models across a range of variables and evalu

Yulun Wu, Bican Xia, Jiale Xu, Bohua Zhan

We present OSVAuto for automatic proofs about functional specifications that commonly arise when verifying operating system kernels. The algorithm behind OSVAuto is designed to support natively those data types that commonly occur in OS verification, including sequences, maps, structures and enumerations. Propositions about these data are encoded into a form

Chang-Le Liu, Wen-Xuan Zhang, Duojie Jia

In this work, we study masses and decays of triply-heavy pentaquarks $QQQn\bar{n}(Q=b,c)$ in the unified MIT bag model. We construct the color-spin wave functions of the triply-heavy pentaquarks we address and use numerical variational method to compute all ground-state masses of these system. By excluding the scattering states in these configurations, we co

Yuan Li, Anke Zhao, Yingjian Wang, Ziyi Xu

Swarm robots have sparked remarkable developments across a range of fields. While it is necessary for various applications in swarm robots, a fast and robust coordinate initialization in vision-based drone swarms remains elusive. To this end, our paper proposes a complete system to recover a swarm's initial relative pose on platforms with size, weight, and p

Thomas Saupe, Sebastian Götschel, Thibaut Lunet, Daniel Ruprecht

Spectral Deferred Correction (SDC) is an iterative method for the numerical solution of ordinary differential equations. It works by refining the numerical solution for an initial value problem by approximately solving differential equations for the error, and can be interpreted as a preconditioned fixed-point iteration for solving the fully implicit colloca

Peter West

I give an account of what it was like to be a PhD student of Abdus Salam and also to take part during the early stages of the development of supersymmetry.

Luca Mozzarelli, Luca Cattaneo, Matteo Corno, Sergio Matteo Savaresi

Despite the number of works published in recent years, vehicle localization remains an open, challenging problem. While map-based localization and SLAM algorithms are getting better and better, they remain a single point of failure in typical localization pipelines. This paper proposes a modular localization architecture that fuses sensor measurements with t

Yusuke Yamada

We show that electric fields in compactified spaces may produce Kaluza-Klein (KK) particles even when the energy of electric fields is smaller than KK scale. As an illustrating example, we consider a charged massless complex scalar coupled to U(1) gauge theory in $\mathbb{R}^{1,3}\times {\mathbb S}^1$ and discuss the effect of background gauge potential alon

Dhruv Patel

In this paper a Complex Network approach is taken to understand the salient features of Indian Water Dam Networks. Detailed analysis of 15 river basin networks have been carried out. The data has been taken from "River Basin Atlas of India" compiled by the Indian Space Research Organisation (ISRO) and Central Water Commission (CWC), Ministry of Water Resourc

Pavlos Cheimonidis, Kontantinos Rantos

The convergence of information and communication technologies has introduced new and advanced capabilities to Industrial Control Systems. However, concurrently, it has heightened their vulnerability to cyber attacks. Consequently, the imperative for new security methods has emerged as a critical need for these organizations to effectively identify and mitiga

Jordan Gué, Aurélien Hees, Peter Wolf, Etienne Savalle

A vector dark matter candidate, also known as dark photon, would induce an oscillating electric field through kinetic mixing. One detection strategy uses a spherical reflector to focus the induced emission at its center of curvature. On one hand, we investigate the effects of diffraction in this type of experiment from an analytical standpoint, making use of

Wenqiao Zhang, Tianwei Lin, Jiang Liu, Fangxun Shu

Recent advancements indicate that scaling up Multimodal Large Language Models (MLLMs) effectively enhances performance on downstream multimodal tasks. The prevailing MLLM paradigm, \emph{e.g.}, LLaVA, transforms visual features into text-like tokens using a \emph{static} vision-language mapper, thereby enabling \emph{static} LLMs to develop the capability to

Luyang Lin, Lingzhi Wang, Jinsong Guo, Jing Li

In the age of information overload and polarized discourse, understanding media bias has become imperative for informed decision-making and fostering a balanced public discourse. However, without the experts' analysis, it is hard for the readers to distinguish bias from the news articles. This paper presents IndiTag, an innovative online media bias analysis

Biswarup Mukhopadhyaya, Sirshendu Samanta, Tousik Samui, Ritesh K. Singh

The exotic decay modes of the already discovered 125-GeV scalar into a pair of light pseudoscalars is a good probe of those new physics scenarios where such pseudoscalars exist. Searches in the mass region where the pseudoscalar ($A$) is lighter than 62.5 GeV have yielded null findings so far. No search has yet examined $m_A > 62.5$ GeV where the cross secti

Elad Hirsch, Gefen Dawidowicz, Ayellet Tal

Generating medical reports for X-ray images presents a significant challenge, particularly in unpaired scenarios where access to paired image-report data for training is unavailable. Previous works have typically learned a joint embedding space for images and reports, necessitating a specific labeling schema for both. We introduce an innovative approach that

Xiaoyu Li, Dedong Liu, Yitao Wu, Xian Wu

3D Multi-Object Tracking (MOT) captures stable and comprehensive motion states of surrounding obstacles, essential for robotic perception. However, current 3D trackers face issues with accuracy and latency consistency. In this paper, we propose Fast-Poly, a fast and effective filter-based method for 3D MOT. Building upon our previous work Poly-MOT, Fast-Poly

J. W. Zhou, S. Dib, M. Juvela, P. Sanhueza

The massive star-forming region G332.83-0.55 contains at least two levels of hub-filament structures. The hub-filament structures may form through the "gravitational focusing" process. High-resolution LAsMA and ALMA observations can directly trace the gas inflows from cloud to core scales. We investigated the effects of shear and tides from the protocluster

Adrian Wurm

In this paper we investigate formal verification problems for Neural Network computations. Of central importance will be various robustness and minimization problems such as: Given symbolic specifications of allowed inputs and outputs in form of Linear Programming instances, one question is whether there do exist valid inputs such that the network computes a

Andreas Bathelt, Vimukthi Herath, Thomas Dallmann

Due to its description of a synchronization between oscillators, the Kuramoto model is an ideal choice for a synchronisation algorithm in networked systems. This requires to achieve not only a frequency synchronization but also a phase synchronization - something the standard Kuramoto model can not provide for a finite number of agents. In this case, a remai

Natascha Jeziorski, Claudia Redenbach

Training defect detection algorithms for visual surface inspection systems requires a large and representative set of training data. Often there is not enough real data available which additionally cannot cover the variety of possible defects. Synthetic data generated by a synthetic visual surface inspection environment can overcome this problem. Therefore,

BESIII Collaboration, M. Ablikim, M. N. Achasov, P. Adlarson

Using $(27.12 \pm 0.14) \times 10^{8}$ $\psi(3686)$ events collected by the BESIII detector at the center-of-mass energy of $\sqrt{s} = 3.686$ GeV, we search for the first time for two nonleptonic hyperon decays that change strangeness by two units, $\Omega^-\to\Sigma^{0}\pi^-$ and $\Omega^-\to nK^{-}$. No significant signal is observed. The upper limits on

Yao Wang, Baolei Liu, Lei Ding, Chaohao Chen

Super-resolution fluorescence microscopy is of great interest in life science studies for visualizing subcellular structures at the nanometer scale. Among various kinds of super-resolution approaches, image scanning microscopy (ISM) offers a doubled resolution enhancement in a simple and straightforward manner, based on the commonly used confocal microscopes

Takahiro Orito, Yoshihito Kuno, Ikuo Ichinose

We extensively study long-time dynamics and fate of topologically-ordered state in toric code model evolving through projective measurement-only circuit. The circuit is composed of several measurement operators corresponding to each term of toric code Hamiltonian with magnetic-field perturbations, which is a gauge-fixed version of a (2+1)-dimensional gauge-H

Abigail Langbridge, Anthony Quinn, Robert Shorten

With the advent of the AI Act and other regulations, there is now an urgent need for algorithms that repair unfairness in training data. In this paper, we define fairness in terms of conditional independence between protected attributes ($S$) and features ($X$), given unprotected attributes ($U$). We address the important setting in which torrents of archiva

Mayura Manawadu, Sieun Park, Soon-Yong Park

This study addresses the challenge of accurate 6D pose estimation in Augmented Reality (AR), a critical component for seamlessly integrating virtual objects into real-world environments. Our research primarily addresses the difficulty of estimating 6D poses from uncontrolled RGB images, a common scenario in AR applications, which lacks metadata such as focal

Zhouhong Gu, Xiaoxuan Zhu, Haoran Guo, Lin Zhang

Language significantly influences the formation and evolution of Human emergent behavior, which is crucial in understanding collective intelligence within human societies. Considering that the study of how language affects human behavior needs to put it into the dynamic scenarios in which it is used, we introduce AgentGroupChat in this paper, a simulation th

Martina Freund, Zhuocheng Xie, Pei-Ling Sun, Lukas Berners

The influence of chemical composition changes on the room temperature mechanical proper-ties in the C15 CaAl2 Laves phase were investigated in two off-stoichiometric compositions with 5.7 at.-% Mg addition (Ca33Al61Mg6) and 10.8 at.-% Mg and 3.0 at.-% Ca addition (Ca36Al53Mg11) and compared to the stoichiometric (Ca33Al67) composition. Cubic Ca-Al-Mg Laves p

Luca Mozzarelli, Simone Specchia, Matteo Corno, Sergio Matteo Savaresi

A fundamental prerequisite for safe and efficient navigation of mobile robots is the availability of reliable navigation maps upon which trajectories can be planned. With the increasing industrial interest in mobile robotics, especially in urban environments, the process of generating navigation maps has become of particular interest, being a labor intensive

Di Wang, Jing Zhang, Minqiang Xu, Lin Liu

Foundation models have reshaped the landscape of Remote Sensing (RS) by enhancing various image interpretation tasks. Pretraining is an active research topic, encompassing supervised and self-supervised learning methods to initialize model weights effectively. However, transferring the pretrained models to downstream tasks may encounter task discrepancy due

Kaushalya Kularatnam, Tania Stathaki

As algorithmic trading and electronic markets continue to transform the landscape of financial markets, detecting and deterring rogue agents to maintain a fair and efficient marketplace is crucial. The explosion of large datasets and the continually changing tricks of the trade make it difficult to adapt to new market conditions and detect bad actors. To tha

Moshe Labaz, Pavel Sidorenko

We report on a comprehensive experimental investigation into the spatial-spectral complexity of the laser beam during Kerr-induced beam self-cleaning in graded-index multimode fibers. We demonstrate the self-cleaning of beams using both transform-limited and chirped femtosecond pulses. By utilizing the spectrally resolved imaging technique, we examine variat

Lei Han, Xizhi Fu, Wenqing He, Yuxiang Zhu

Anomalous Nernst effect (ANE), a widely investigated transverse thermoelectric effect that converts waste heat into electrical energy with remarkable flexibility and integration capability, has been extended to antiferromagnets with non-collinear spin texture recently. ANE in compensated magnet with collinear N\'eel vector will bring more opportunities to co

Jade Brisson, Bruno Colbois, Katie Gittins

We investigate upper bounds for the spectral ratios and gaps for the Steklov eigenvalues of balls with revolution-type metrics. We do not impose conditions on the Ricci curvature or on the convexity of the boundary. We obtain optimal upper bounds for the Steklov spectral ratios in dimensions 3 and higher. In dimension 3, we also obtain optimal upper bounds f

Larissa A. Meinicke, Ian J. Hayes

Distributive laws are important for algebraic reasoning in arithmetic and logic. They are equally important for algebraic reasoning about concurrent programs. In existing theories such as Concurrent Kleene Algebra, only partial correctness is handled, and many of its distributive laws are weak, in the sense that they are only refinements in one direction, ra

Tengzhou Hu

A Lie algebroid is a generalization of Lie algebra that provides a general framework to describe the symmetries of a manifold. In this paper, we introduce Lie algebroid index theory and study the Lie algebroid Dolbeault operator. We also introduce Connes' index theory on regular foliated manifolds to obtain a generalized Riemann-Roch theorem on manifolds wit

Xun Gong, Yu Wu, Jinyu Li, Shujie Liu

In this paper, we propose two novel approaches, which integrate long-content information into the factorized neural transducer (FNT) based architecture in both non-streaming (referred to as LongFNT ) and streaming (referred to as SLongFNT ) scenarios. We first investigate whether long-content transcriptions can improve the vanilla conformer transducer (C-T)

Jesus Etxebarria

The stationary states of a particle in a central potential are usually taken as a product of an angular part Phi and a radial part R. The function R satisfies the so-called radial equation and is usually solved by demanding R to be finite at the origin. In this work we examine the reason for this requirement in the case of a two-dimensional (2D) central forc

Yimin Tang, Zhenghong Yu, Yi Zheng, T. K. Satish Kumar

Multi-Agent Path Finding (MAPF), which involves finding collision-free paths for multiple robots, is crucial in various applications. Lifelong MAPF, where targets are reassigned to agents as soon as they complete their initial targets, offers a more accurate approximation of real-world warehouse planning. In this paper, we present a novel mechanism named Cac

Shumo Cui, Alexander Kurganov, Kailiang Wu

Central-upwind (CU) schemes are Riemann-problem-solver-free finite-volume methods widely applied to a variety of hyperbolic systems of PDEs. Exact solutions of these systems typically satisfy certain bounds, and it is highly desirable or even crucial for the numerical schemes to preserve these bounds. In this paper, we develop and analyze bound-preserving (B

Ankit Singh, Shreya Davessar, Mamta Gulati, Jasjeet Singh Bagla

Comprehensive observations of galaxy clusters suggest that gas deficiency in the galaxies could be due to ram pressure stripping due to the high-pressure intra-cluster medium acting on the galactic discs. The presence of gas in galaxies is essential for star formation. The net force due to ram pressure is dependent on the ambient medium and the orbit followe

J. Blunier, A. Neronov

Outflows from galaxies, driven by active galactic nuclei and star formation activity, spread magnetic fields into the intergalactic medium. Importance of this process can be assessed using cosmological magneto-hydrodynamic numerical modelling of the baryonic feedback on the Large Scale Structure, like that of Illustris-TNG simulations. We use the Faraday Rot

Virgile Tapiero

Let $f$ be a holomorphic endomorphism of $\mathbb{P}^2$, let $T$ be its Green current and $\mu=T\wedge T$ be its equilibrium measure. We prove that if $\mu$ has a local product structure with respect to $T$ then (an iterate of) $f$ preserves a local foliation $\mathcal{F}$ on a neighborhood of $\mathrm{Supp}(T )\backslash\mathcal{E}$,where $\mathcal{E}$ deno

Aldrin Joar R. Taduran

The development of a microcontroller-based smoked fish machine aims to combine and automate the boiling, smoking, and drying. The machine consists of an Arduino microcontroller, heater, spark gap igniter, stepper motor with motor driver, temperature sensor, exhaust fan, DC converter, relay module, power supply, and controller box. The main mechanism of the s

Yicheng Wu, Xiangde Luo, Zhe Xu, Xiaoqing Guo

Annotation ambiguity due to inherent data uncertainties such as blurred boundaries in medical scans and different observer expertise and preferences has become a major obstacle for training deep-learning based medical image segmentation models. To address it, the common practice is to gather multiple annotations from different experts, leading to the setting

Séverin Benzoni, Emmanuel Roy, Thierry de la Rue

This paper follows on from our previous work, where we introduced the notion of \emph{confined extensions}, and our purpose is to widen the context in which such extensions appear. We do so in the setup of Poisson suspensions: we take a $\sigma$-finite measure-preserving dynamical system $(X, \mu, T)$ and a compact extension $(X \times G, \mu \otimes m_G, T_

Meriem El Karoui, Ignacio Madrid, Sylvie Méléard

Under low concentrations of antibiotics causing DNA damage, \textit{Escherichia coli} bacteria can trigger stochastically a stress response known as the SOS response. While the expression of this stress response can make individual cells transiently able to overcome antibiotic treatment, it can also delay cell division, thus impacting the whole population's

Manabu Saito, Ryoichi Kurose

The computational cost of the boundary-condition-enforced immersed boundary method (IBM) increases in the order of $\mathcal{O}(N^2)$ as the number of Lagrangian points, $N$, increases. This is due to the time-consuming calculation of the correction operator in the diffuse-interface IBM to enforce the no-slip boundary condition. In this study, a computationa

Z. Baki, M. N. M. van Lieshout

To monitor the seismic hazard in the Groningen gas field, we modify the rate-and-state model that relates changes in pore pressure to induced seismic hazard by allowing for noise in pore pressure measurements and by explicitly taking into account gas production volumes. We analyse the first and second-moment structure of the resulting Cox process, propose an

Kaito Shiku, Hiromitsu Shirai, Takeshi Ishihara, Ryoma Bise

3D cell tracking in a living organism has a crucial role in live cell image analysis. Cell tracking in C. elegans has two difficulties. First, cell migration in a consecutive frame is large since they move their head during scanning. Second, cell detection is often inconsistent in consecutive frames due to touching cells and low-contrast images, and these in

Niraj Kumar, Chuanchao Gao, Arvind Easwaran

This work studies fixed priority (FP) scheduling of real-time jobs with end-to-end deadlines in a distributed system. Specifically, given a multi-stage pipeline with multiple heterogeneous resources of the same type at each stage, the problem is to assign priorities to a set of real-time jobs with different release times to access a resource at each stage of

Shivam Ratnakant Mhaskar, Nirmesh J. Shah, Mohammadi Zaki, Ashishkumar P. Gudmalwar

Traditional Automatic Video Dubbing (AVD) pipeline consists of three key modules, namely, Automatic Speech Recognition (ASR), Neural Machine Translation (NMT), and Text-to-Speech (TTS). Within AVD pipelines, isometric-NMT algorithms are employed to regulate the length of the synthesized output text. This is done to guarantee synchronization with respect to t

Duc Trong Dang, Van Ha Hoang, Phuc Hung Thai

This paper focuses on estimating the invariant density function $f_X$ of the strongly mixing stationary process $X_t$ in the multiplicative measurement errors model $Y_t = X_t U_t$, where $U_t$ is also a strongly mixing stationary process. We propose a novel approach to handle non-independent data, typical in real-world scenarios. For instance, data collecte

Y. Tu, B. Wu, W. Ai, E. Martínez-Pañeda

Core-shell electrode particle designs offer a route to improved lithium-ion battery performance. However, they are susceptible to mechanical damage such as fracture and debonding, which can significantly reduce their lifetime. Using a coupled finite element model, we explore the impacts of diffusion-induced stresses on the failure mechanisms of an exemplar s

Haoran Lang, Yuxuan Ge, Zheng Tian

Diffusion models have achieved great success in image generation. However, when leveraging this idea for video generation, we face significant challenges in maintaining the consistency and continuity across video frames. This is mainly caused by the lack of an effective framework to align frames of videos with desired temporal features while preserving consi

Sergio Cía

We prove a Mackey formula for representations of finite groups of Lie type, in the case where the groups come from disconnected reductive groups.

Thomas Bellotti, Philippe Helluy, Laurent Navoret

We present a novel framework for the development of fourth-order lattice Boltzmann schemes to tackle multidimensional nonlinear systems of conservation laws. As for other numerical schemes for hyperbolic problems, high-order accuracy applies only to smooth solutions. Our numerical schemes preserve two fundamental characteristics inherent in classical lattice

Yamin Mao, Zhihua Liu, Weiming Li, SoonYong Cho

Depth-based 3D hand pose estimation is an important but challenging research task in human-machine interaction community. Recently, dense regression methods have attracted increasing attention in 3D hand pose estimation task, which provide a low computational burden and high accuracy regression way by densely regressing hand joint offset maps. However, large

Jérôme Vaillant, Clémence Mornet, Thomas Decroux, Didier Hérault

Development of small pixels for high resolution image sensors implies a lot of challenges. A high level of performance should be guaranteed whereas the overall size must be reduced and so the degree of freedom in design and process. One key parameter of this constant improvement is the knowledge and the control of the crosstalk between pixels. In this paper,

Simon Guilloud, Sankalp Gambhir, Andrea Gilot, Viktor Kunčak

We present a mechanized embedding of higher-order logic (HOL) and algebraic data types (ADT) into first-order logic with ZFC axioms. We implement this in the Lisa proof assistant for schematic first-order logic and its library based on axiomatic set theory. HOL proof steps are implemented as proof producing tactics in Lisa, and the types are interpreted as s

Yizhu Wen, Kai Yi, Jing Ke, Yiqing Shen

Tabular data plays a crucial role in various domains but often suffers from missing values, thereby curtailing its potential utility. Traditional imputation techniques frequently yield suboptimal results and impose substantial computational burdens, leading to inaccuracies in subsequent modeling tasks. To address these challenges, we propose DiffImpute, a no

Philippe Laurençot, Christian Stinner

Convergence of solutions to a partially diffusive chemotaxis system with indirect signal production and phenotype switching is shown in a two-dimensional setting when the switching rate increases to infinity, thereby providing a rigorous justification of formal computations performed in the literature. The expected limit system being the classical parabolic-

Filipe Soares, Vincent Debut

The radiation efficiency from simple vibrating planar surfaces is often used as a basis to describe the sound radiation from more complex structures, having important applications in various fields of acoustics. The low-frequency radiation efficiency of a baffled piston can easily be represented by a simple monopole source. Notably, the equivalent source str

Danqi Lang, Le Chen, Jingyuan Li

It is well-known that intrinsically disordered proteins (IDP) are highly dynamic, which is related to their functionality in various biological processes. However, the characterization of the intricate structures of IDP has been a challenge. Here, we analyze the chain topology of IDPs to characterize their conformations, in combination with molecular dynamic

Khalil Guetari, Yannis Tevissen, Frédéric Petitpont

We propose a novel approach for automatic chaptering of TV newscast videos, addressing the challenge of structuring and organizing large collections of unsegmented broadcast content. Our method integrates both audio and visual cues through a two-stage process involving frozen neural networks and a trained LSTM network. The first stage extracts essential feat

Yannis Tevissen, Khalil Guetari, Marine Tassel, Erwan Kerleroux

Image captioning models are widely used to describe recent and archived pictures with the objective of improving their accessibility and retrieval. Yet, these approaches tend to be inefficient and biased at retrieving people's names. In this work we introduce AstroCaptions, a dataset for the image captioning task. This dataset specifically contains thousands

G. Milcareck, S. Guerlet, F. Montmessin, A. Spiga

The observations made during the Voyager 2 flyby have shown that the stratosphere of Uranus and Neptune are warmer than expected by previous models. In addition, no seasonal variability of the thermal structure has been observed on Uranus since Voyager 2 era and significant subseasonal variations have been revealed on Neptune. In this paper, we evaluate diff

Aixian Chen, Xia Cui, Guangren Yang

We investigate the bounding problem of causal effects in experimental studies in which the outcome is truncated by death, meaning that the subject dies before the outcome can be measured. Causal effects cannot be point identified without instruments and/or tight parametric assumptions but can be bounded under mild restrictions. Previous work on partial ident

Viviana Grasselli

We consider the Schr{\"o}dinger operator --$\Delta$ + V on the Euclidean space with potential in the Lorentz space L^{n/2,1} and we find necessary and sufficient conditions for zero to be a resonance or an eigenvalue. We consider functions with gradient in L^2 and that verify the equation (--$\Delta$ + V)$\psi$ = 0, namely the kernel of (--$\Delta$ + V) in t

Jérôme Vaillant, Lucie Dilhan, Alain Ostrovsky, Quentin Abadie

In this paper we present two design generations of metasurface-based planar microlenses implemented on Front-Side Illumination SPAD pixels. This kind of microlens is an alternative to conventional reflow microlens. It offers more degrees of freedom in term of design, especially the capability to design off-axis microlens to gather light around the SPAD photo

Alberto García-Hernández, Riccardo Giubilato, Klaus H. Strobl, Javier Civera

Perceptual aliasing and weak textures pose significant challenges to the task of place recognition, hindering the performance of Simultaneous Localization and Mapping (SLAM) systems. This paper presents a novel model, called UMF (standing for Unifying Local and Global Multimodal Features) that 1) leverages multi-modality by cross-attention blocks between vis

Sawan, M. Bregant, J. L. Bouly, O. Bourrion

This work reports the testing of a Forward Calorimeter (FoCal) prototype based on an n-type Si pad array detector at the CERN PS accelerator. The FoCal is a proposed upgrade in the ALICE detector operating within the pseudorapidity range of 3.2 < $\mathrm{\eta}$ < 5.8. It aims to measure direct photons, neutral hadrons, vector mesons, and jets for the study

Luidnel Maignan, Antoine Spicher

On the one side, the formalism of Global Transformations comes with the claim of capturing any transformation of space that is local, synchronous and deterministic. The claim has been proven for different classes of models such as mesh refinements from computer graphics, Lindenmayer systems from morphogenesis modeling and cellular automata from biological, p

Wenqi Zhao

In order to improve the robustness of traditional image segmentation models to noise, this paper models the illumination term in intensity inhomogeneity images. Additionally, to enhance the model's robustness to noisy images, we incorporate the binary level set model into the proposed model. Compared to the traditional level set, the binary level set elimina

Daniel Barlet

This text is a presentation (without proofs) of some of my recent results on the singular terms of asymptotic expansions of period-integrals using (a,b)-modules. I try to explain why this simple algebraic structure is interesting and useful.

Sungjae Bae, Junu Jeong, Younggeun Kim, SungWoo Youn

Axions are hypothesized particles believed to potentially resolve two major puzzles in modern physics: the strong CP problem and the nature of dark matter. Cavity-based axion haloscopes represent the most sensitive tools for probing their theoretically favored couplings to photons in the microelectronvolt range. However, as the search mass (or frequency) inc

Emma Pearce, Osian Wolley, Simon P. Mekhail, Thomas Gregory

Imaging with undetected photons relies upon nonlinear interferometry to extract the spatial image from an infrared probe beam and reveal it in the interference pattern of an easier-to-detect visible beam. Typically, the transmission and phase images are extracted using phase-shifting techniques and combining interferograms from multiple frames. Here we show

Guohui Guan, Lin He, Zongxia Liang, Litian Zhang

This paper studies a variable proportion portfolio insurance (VPPI) strategy. The objective is to determine the risk multiplier by maximizing the extended Omega ratio of the investor's cushion, using a binary stochastic benchmark. When the stock index declines, investors aim to maintain the minimum guarantee. Conversely, when the stock index rises, investors

A. V. Snegirev, V. M. Kovalev, M. V. Entin, E. B. Olshanetsky

The semimetal quantum well (QW) based on HgTe structures exhibiting unusual transport properties at low temperature is examined experimentally. It demonstrates either a linear or quadratic growth of resistance with temperature at different top-gate voltages in the semimetal regime. We develop a theoretical model of HgTe-based semimetal QW resistance temperat

Robert Denk, Markus Kunze, Michael Kupper

We introduce the concept evolutionary semigroups on path spaces, generalizing the notion of transition semigroups to possibly non-Markovian stochastic processes. We study the basic properties of evolutionary semigroups and, in particular, prove that they always arise as the composition of the shift semigroup and a single operator called the expectation opera

Guillaume Lauga, Audrey Repetti, Elisa Riccietti, Nelly Pustelnik

This paper presents a multilevel algorithm specifically designed for radio-interferometric imaging in astronomy. The proposed algorithm is used to solve the uSARA (unconstrained Sparsity Averaging Reweighting Analysis) formulation of this image restoration problem. Multilevel algorithms rely on a hierarchy of approximations of the objective function to accel

Usman Akhtar, Farnoud Ghasemi, Rafal Kucharski

Ride-pooling, to gain momentum, needs to be attractive for all the parties involved. This includes also drivers, who are naturally reluctant to serve pooled rides. This can be controlled by the platform's pricing strategy, which can stimulate drivers to serve pooled rides. Here, we propose an agent-based framework, where drivers serve rides that maximise the

François Maucourant

Pick a random matrix $\gamma$ in $\Gamma={\rm SL}(2,\mathbb{Z})$. Denote by $\mathcal{O}_K$ the Dedekind ring generated by its eigenvalues, and let $\Delta_K$, $\Delta_\gamma$ and $\Delta = {\rm Tr}(\gamma)^2-4$ be the respective discriminant of the rings $\mathcal{O}_K$, the multiplier ring $M(2,\mathbb{Z})\cap \mathbb{Q}[\gamma]$ and $\mathbb{Z}[\gamma]$.

Moulay A. Barkatou, Lucas Legrand, Tristan Vaccon

Polyhedral affinoid algebras have been introduced by Einsiedler, Kapranov and Lind to connect rigid analytic geometry (analytic geometry over non-archimedean fields) and tropical geometry. In this article, we present a theory of Gr{\"o}bner bases for polytopal affinoid algebras that extends both Caruso et al.'s theory of Gr{\"o}bner bases on Tate algebras an

Tudor-Bogdan Airimitoaie, Bernard Vau, Dariusz Bismor, Gabriel Buche

The paper explores in detail the use of dynamic adaptation gain/step size (DAG) for improving the adaptation transient performance of variable step-size LMS (VS-LMS) adaptation algorithms. A generic form for the implementation of the DAG within the VS-LMS algorithms is provided. Criteria for the selection of the coefficients of the DAG filter which is requir

Jingxiang Shen, Wei Kang

For the data analysis problem of shock-ramp compression, i.e., ramp compression after a relatively strong initial shock, a characteristics-based method that strictly deals with the initial hydrodynamic shock is described in detail. Validation of this analysis method using simulated shock-ramp data generated by molecular dynamics and one-dimensional radiation

Audrey Gardahaut, Hugues Lourme, Steve Mahaut, Masaki Nagai

Widely present in the primary circuit of Nuclear Power Plants (NPP), Dissimilar Metal Welds (DMW) are inspected using Ultrasonic nondestructive Testing (UT) techniques to ensure the integrity of the structure and detect defects such as Stress Corrosion Cracking (SCC).In a previous collaborative research, CRIEPI and CEA have worked on the understanding of the

Feng Liu, Xiaobin Chang

Semantic image synthesis aims to generate high-quality images given semantic conditions, i.e. segmentation masks and style reference images. Existing methods widely adopt generative adversarial networks (GANs). GANs take all conditional inputs and directly synthesize images in a single forward step. In this paper, semantic image synthesis is treated as an im

Michael Cuntz, Piotr Pokora

In this paper we focus on various aspects of singular complex plane curves, mostly in the context of their homological properties and the associated combinatorial structures. We formulate some challenging open problems that can point to new directions in research, for example by introducing weak Ziegler pairs of curve arrangements. Moreover, we construct new

Jannik Presberger, Rashmiparvathi Keshara, David Stein, Yung Hae Kim

In biological and medical research, scientists now routinely acquire microscopy images of hundreds of morphologically heterogeneous organoids and are then faced with the task of finding patterns in the image collection, i.e., subsets of organoids that appear similar and potentially represent the same morphological class. We adopt models and algorithms for co

Jiawei Zhou, Wuzhou Li, Yi Cao, Hongtao Cai

Few-shot object detection (FSOD) has garnered significant research attention in the field of remote sensing due to its ability to reduce the dependency on large amounts of annotated data. However, two challenges persist in this area: (1) axis-aligned proposals, which can result in misalignment for arbitrarily oriented objects, and (2) the scarcity of annotat

Shiyuan Zuo, Xingrun Yan, Rongfei Fan, Han Hu

This paper addresses federated learning (FL) in the context of malicious Byzantine attacks and data heterogeneity. We introduce a novel Robust Average Gradient Algorithm (RAGA), which uses the geometric median for aggregation and {allows flexible round number for local updates.} Unlike most existing resilient approaches, which base their convergence analysis

Yuxuan Luo, Zekun Wu, Zhouhui Lian

Human-like planning skills and dexterous manipulation have long posed challenges in the fields of robotics and artificial intelligence (AI). The task of reinterpreting calligraphy presents a formidable challenge, as it involves the decomposition of strokes and dexterous utensil control. Previous efforts have primarily focused on supervised learning of a sing

Rahul Wagh

Electric vehicles (EVs) have emerged as a transformative force in India's transportation sector, offering a sustainable solution to the country's growing energy and environmental challenges. Against the backdrop of rapid urbanization, rising pollution levels, and the need for energy security, EVs have gained traction as a viable alternative to traditional in

Yaowei Zheng, Richong Zhang, Junhao Zhang, Yanhan Ye

Efficient fine-tuning is vital for adapting large language models (LLMs) to downstream tasks. However, it requires non-trivial efforts to implement these methods on different models. We present LlamaFactory, a unified framework that integrates a suite of cutting-edge efficient training methods. It provides a solution for flexibly customizing the fine-tuning

Johan Bylin, Rebecka Lindblad, Lennart Spode, Ralph H. Scheicher

We investigate the influence of hydrogen on the electronic structure of a binary transition metallic glass of V$_{80}$Zr$_{20}$. We examine the hybridization between the hydrogen and metal atoms with the aid of hard x-ray photoelectron spectroscopy. Combined with ab initio density functional theory, we are able to show and predict the formation of $s$-$d$ hy

Kaito Shiku, Shinnosuke Matsuo, Daiki Suehiro, Ryoma Bise

The paper proposes a novel problem in multi-class Multiple-Instance Learning (MIL) called Learning from the Majority Label (LML). In LML, the majority class of instances in a bag is assigned as the bag's label. LML aims to classify instances using bag-level majority classes. This problem is valuable in various applications. Existing MIL methods are unsuitabl

Phillip Richter-Pechanski, Philipp Wiesenbach, Dominic M. Schwab, Christina Kiriakou

Automatic extraction of medical information from clinical documents poses several challenges: high costs of required clinical expertise, limited interpretability of model predictions, restricted computational resources and privacy regulations. Recent advances in domain-adaptation and prompting methods showed promising results with minimal training data using

Shaonan Wang, Jingyuan Sun, Yunhao Zhang, Nan Lin

Despite differing from the human language processing mechanism in implementation and algorithms, current language models demonstrate remarkable human-like or surpassing language capabilities. Should computational language models be employed in studying the brain, and if so, when and how? To delve into this topic, this paper reviews efforts in using computati