April 2024 arXiv papers — page 14

Anil Khachi

This paper introduces students and instructors to the use of Scilab for calculating phase shifts from phenomenological potentials in nuclear, atomic, and molecular scattering, beginning with a Riccati-type nonlinear differential equation derived from the time-independent Schr$\ddot{\text{o}}$dinger equation. For spherically symmetric potentials, this equatio

Tobias Hilgart, Volker Ziegler

Related to Shank's notion of simplest cubic fields, the family of parametrised Diophantine equations, \[ x^3 - (n-1) x^2 y - (n+2) xy^2 - 1 = \left( x - \lambda_0 y\right) \left(x-\lambda_1 y\right) \left(x - \lambda_2 y\right) = \pm 1, \] was studied and solved effectively by Thomas and later solved completely by Mignotte. An open conjecture of Levesque and

Nicolás Andruskiewitsch, Ken A. Brown

We exhibit a PI Hopf algebra that is not a finite module over its center. We survey some ring-theoretical properties of the bosonizations of enveloping algebras of Lie superalgebras.

Jin Huang, Harrie Oosterhuis, Masoud Mansoury, Herke van Hoof

Two typical forms of bias in user interaction data with recommender systems (RSs) are popularity bias and positivity bias, which manifest themselves as the over-representation of interactions with popular items or items that users prefer, respectively. Debiasing methods aim to mitigate the effect of selection bias on the evaluation and optimization of RSs. H

Paula Strohbeck, Iryna Rybak

Coupled systems of free flow and porous media arise in a variety of technical and environmental applications. For laminar flow regimes, such systems are described by the Stokes equations in the free-flow region and Darcy's law in the porous medium. An appropriate set of coupling conditions is needed on the fluid-porous interface. Discretisations of the Stoke

Sunil Kumar Kopparapu, Ashish Panda

Unlike hybrid speech recognition systems where the use of tokens was restricted to phones, biphones or triphones the choice of tokens in the end-to-end ASR systems is derived from the text corpus of the training data. The use of tokenization algorithms like Byte Pair Encoding (BPE) and WordPiece is popular in identifying the tokens that are used in the overa

Sina Gholamian, Domingo Huh

Large Language Models (LLMs) encapsulate an extensive amount of world knowledge, and this has enabled their application in various domains to improve the performance of a variety of Natural Language Processing (NLP) tasks. This has also facilitated a more accessible paradigm of conversation-based interactions between humans and AI systems to solve intended p

Yoann Piétri, Matteo Schiavon, Valentina Marulanda Acosta, Baptiste Gouraud

Quantum Key Distribution (QKD) enables secret key exchange between two remote parties with information-theoretic security rooted in the laws of quantum physics. Encoding key information in continuous variables (CV), such as the values of quadrature components of coherent states of light, brings implementations much closer to standard optical communication sy

Giovanni Rodari, Leonardo Novo, Riccardo Albiero, Alessia Suprano

Multiphoton indistinguishability is a central resource for quantum enhancement in sensing and computation. Developing and certifying large scale photonic devices requires reliable and accurate characterization of this resource, preferably using methods that are robust against experimental errors. Here, we propose a set of methods for the characterization of

Stephen Serjeant, James Pearson, Hugh Dickinson, Johanna Jarvis

Major European Union-funded research infrastructure and open science projects have traditionally included dissemination work, for mostly one-way communication of the research activities. Here we present and review our radical re-envisioning of this work, by directly engaging citizen science volunteers into the research. We summarise the citizen science in th

Carlo Bellingeri, Hannes Kern

We extend the stochastic reconstruction theorem to a setting where the underlying family of distributions satisfies some natural conditions involving rectangular increments. This allows us to prove the well-posedness of a new class of mixed stochastic partial differential of hyperbolic type which combines standard Walsh stochastic integration and Young produ

Itamar Kolvin, Mokhtar Adda-Bedia

The interaction of crack fronts with asperities is central to the criteria of fracture in heterogeneous materials and for predicting fracture surface formation. It is known how dynamic crack fronts respond to small, 1st-order, perturbations. However, large and localized disturbances to crack motion induce dynamic and geometric nonlinear effects beyond the ex

Chandni Menapara, Ajay Kumar Rai

Hadron spectroscopy is an important tool towards the study of internal quark dynamics in a composite system. The present article focuses on the study of resonance spectra of strange baryons with S=-2, -3. The non-relativistic approach utilizes screened potential as hypercentral one to obtain masses. The spin-dependent part for all possible hyperfine states h

Jorn-Jan van de Beld, Shreyasi Pathak, Jeroen Geerdink, Johannes H. Hegeman

Surgery to treat elderly hip fracture patients may cause complications that can lead to early mortality. An early warning system for complications could provoke clinicians to monitor high-risk patients more carefully and address potential complications early, or inform the patient. In this work, we develop a multimodal deep-learning model for post-operative

Wenbo Wang, Hsuan-I Ho, Chen Guo, Boxiang Rong

The studies of human clothing for digital avatars have predominantly relied on synthetic datasets. While easy to collect, synthetic data often fall short in realism and fail to capture authentic clothing dynamics. Addressing this gap, we introduce 4D-DRESS, the first real-world 4D dataset advancing human clothing research with its high-quality 4D textured sc

Logan Numerow, Yue Li, Stelian Coros, Bernhard Thomaszewski

Navigating topological transitions in cellular mechanical systems is a significant challenge for existing simulation methods. While abstract models lack predictive capabilities at the cellular level, explicit network representations struggle with topology changes, and per-cell representations are computationally too demanding for large-scale simulations. To

Antoine Maiorca, Seyed Abolfazl Ghasemzadeh, Thierry Ravet, François Cresson

Virtual Reality (VR) applications have revolutionized user experiences by immersing individuals in interactive 3D environments. These environments find applications in numerous fields, including healthcare, education, or architecture. A significant aspect of VR is the inclusion of self-avatars, representing users within the virtual world, which enhances inte

Marisel Di Pietro Martínez, Alexis Wartelle, Nicolas Mille, Stefan Stanescu

Polarized X-rays allow for imaging birefringent or dichroic properties of materials with nanometric resolution. To disentangle these properties from the electronic density, either a polarization analyzer or several measurements with different polarizations (typically two, or more) are needed. Here we demonstrate that ptychography can disentangle these from a

Yufan Luo

This paper studies the Unramified Fontaine-Mazur Conjecture for $ p $-adic Galois representations and its generalizations. We prove some basic cases of the conjecture and provide some useful criterions for verifying it. In addition, we propose several different strategies to attack the conjecture and reduce it to some special cases. We also prove many new re

Philipp Öffner, Louis Petri, Davide Torlo

In this manuscript, we present the development of implicit and implicit-explicit ADER and DeC methodologies within the DeC framework using the two-operators formulation, with a focus on their stability analysis both as solvers for ordinary differential equations (ODEs) and within the context of linear partial differential equations (PDEs). To analyze their s

Théodore Cherrière

Hybrid-excited electrical machines aim to combine the advantages of permanent magnet machines (high efficiency and torque density) with those of separately excited machines (ease of flux-weakening at high speed). These machines are of interest to electric vehicles, and only parametric approaches are available in the literature for their optimization. This wo

I. Ioannou Sougleridis, O. Richoux, V. Achilleos G. Theocharis, D. J. Frantzeskakis

We study the propagation of both low- and high-amplitude ring-shaped sound waves in a 2D square lattice of acoustic waveguides with Helmholtz resonators. We show that the inclusion of the Helmholtz resonators suppresses the inherent anisotropy of the system in the low frequency regime allowing for radially symmetric solutions. By employing the electroacousti

Letitia Parcalabescu, Anette Frank

Vision and language model (VLM) decoders are currently the best-performing architectures on multimodal tasks. Next to answers, they are able to produce natural language explanations, either in post-hoc or CoT settings. However, it is not clear to what extent they are using the input vision and text modalities when generating answers or explanations. In this

Shankey Kumar, Saminathan Ponnusamy, G. Brock Williams

In this paper, we study the Bohr inequality with lacunary series to the single valued (resp. vector-valued) holomorphic function defined in unit ball of finite dimensional Banach sequence space. Also, we extend the Bohr inequality with an alternating series to the higher-dimensional space.

Saeid Alikhani, Nima Ghanbari, Mohammad Ali Dehghanizadeh

Let $G$ be a simple graph with vertex set $V(G) = \{v_1, v_2,\ldots, v_n\}$. The elliptic Sombor matrix of $G$, denoted by $A_{ESO}(G)$, is defined as the $n\times n$ matrix whose $(i,j)$-entry is $(d_i+d_j)\sqrt{d_i^2+d_j^2}$ if $v_i$ and $v_j$ are adjacent and $0$ for another cases. Let the eigenvalues of the elliptic Sombor matrix $A_{ESO}(G)$ be $\rho_1\

Daniel Collins, Sandu Popescu

In the paradigmatic example of quantum measurements, whenever one measures a system which starts in a superposition of two states of a conserved quantity, it jumps to one of the two states, implying different final values for the quantity that should have been conserved. The standard law of conservation for quantum mechanics handles this jump by stating only

Yichen Ouyang, jianhao Yuan, Hao Zhao, Gaoang Wang

Generating long and consistent videos has emerged as a significant yet challenging problem. While most existing diffusion-based video generation models, derived from image generation models, demonstrate promising performance in generating short videos, their simple conditioning mechanism and sampling strategy-originally designed for image generation-cause se

M. Lovšin, A. Petelin, B. Berteloot, N. Osterman

Ferroelectric nematic liquid crystals exhibit unique non-linear optical properties, with the potential to become transformative materials for photonic applications. A promising direction relies on the fabrication of tailored polar orientational patterns via photoalignment, thus shaping the non-linear optical susceptibility through thin slabs of the ferroelec

Klaus Mattis

We show that for a large class of $\infty$-topoi there exist unstable arithmetic fracture squares, i.e. squares which recover a nilpotent sheaf $F$ as the pullback of the rationalization of $F$ with the product of the $p$-completions of $F$ ranging over all primes $p\in\mathbb Z$.

Yunshuang Yuan, Monika Sester

Collective Perception has attracted significant attention in recent years due to its advantage for mitigating occlusion and expanding the field-of-view, thereby enhancing reliability, efficiency, and, most crucially, decision-making safety. However, developing collective perception models is highly resource demanding due to extensive requirements of processi

Jin-Xin Hu, Oles Matsyshyn, Justin C. W. Song

Supercurrent flow can induce a nonvanishing spin magnetization in noncentrosymmetric superconductors with spin-orbit interaction. Often known as the non-dissipative magnetoelectric effect, these are most commonly found at linear order in supercurrent flow. Here, we propose that a {\it nonlinear} superconducting magnetoelectric (NSM) effect can naturally mani

Yifan Zhang

Political and advertising campaigns increasingly exploit social networks to spread information and persuade people. This paper studies a persuasion model to examine whether such a strategy is better than simply sending public signals. Receivers in the model have heterogeneous priors and will pass on a signal if they are persuaded by it to take sender's prefe

Bashar Alhafni, Reem Hazim, Juan Piñeros Liberato, Muhamed Al Khalil

We present the SAMER Corpus, the first manually annotated Arabic parallel corpus for text simplification targeting school-aged learners. Our corpus comprises texts of 159K words selected from 15 publicly available Arabic fiction novels most of which were published between 1865 and 1955. Our corpus includes readability level annotations at both the document a

Jean Goubault-Larrecq

A class of topological spaces is projective (resp., $\omega$-projective) if and only if projective systems of spaces (resp., with a countable cofinal subset of indices) in the class are still in the class. A certain number of classes of Hausdorff spaces are known to be, or not to be, ($\omega$-) projective. We examine classes of spaces that are not necessari

Roba Abukwaik, Elias Vera-Siguenza, Daniel Tennant, Fabian Spill

Cancer cells exhibit significant alterations in their metabolism, characterised by a reduction in oxidative phosphorylation (OXPHOS) and an increased reliance on glycolysis, even in the presence of oxygen. This metabolic shift, known as the Warburg effect, is pivotal in fuelling cancer's uncontrolled growth, invasion, and therapeutic resistance. While dysreg

Chuheng Chen, Xinxing Chen, Shucong Yin, Yuxuan Wang

Environment awareness is crucial for enhancing walking safety and stability of amputee wearing powered prosthesis when crossing uneven terrains such as stairs and obstacles. However, existing environmental perception systems for prosthesis only provide terrain types and corresponding parameters, which fails to prevent potential collisions when crossing uneve

Kento Yasuda, Kenta Ishimoto, Shigeyuki Komura

Onsager's variational principle (OVP) provides us with a systematic way to derive dynamical equations for various soft matter and active matter. By reformulating the Onsager-Machlup variational principle (OMVP), which is a time-global principle, we propose a new method to incorporate thermal fluctuations. To demonstrate the utility of the statistical formula

Yue Li, Logan Numerow, Bernhard Thomaszewski, Stelian Coros

Computing intrinsic distances on discrete surfaces is at the heart of many minimization problems in geometry processing and beyond. Solving these problems is extremely challenging as it demands the computation of on-surface distances along with their derivatives. We present a novel approach for intrinsic minimization of distance-based objectives defined on t

Hiroki Matsui

Recent analysis of quantum cosmology has focused on the Lorentzian path integral formulations of both the no-boundary and tunneling proposals. However, it has been criticized that the wave function for linearized perturbations around a homogeneous and isotropic background leads to an inverse Gaussian distribution. This results in divergent correlation functi

P. B. Covas, R. Prix, J. Martins

Searches for continuous gravitational waves from unknown neutron stars are limited in sensitivity due to their high computational cost. For this reason, developing new methods or improving existing ones can increase the probability of making a detection. In this paper we present a new framework that uses MCMC or nested sampling methods to follow-up candidate

Zhi-Wei Liu, Jun-Xu Lu, Ming-Zhu Liu, Li-Sheng Geng

There have been extended and heated discussions on the nature of the two exotic states, $Z_c(3900)$ and $Z_{cs}(3985)$, particularly whether they are near-threshold resonances, virtual states, or bound states. In this work, we demonstrate for the first time that the femtoscopic technique can be employed to distinguish between these three scenarios. More conc

Farook Rahaman, Bikramarka S Choudhury

We analyze traversable wormholes defined by the dynamic line elements that asymptotically approaches Friedmann-Robertson-Walker (FRW) universe. This dynamical wormholes is supported by the galactic dark matter as well as perfect isotropic fluid. We will discuss several evolving Lorentzian wormholes comprising with different perfect isotropic fluids in additi

Km Nitu Rai, Soumen Basak, Subrata Sarangi, Prasenjit Saha

The correlation of light from two sources leads to an interference pattern if they belong to a specific time interval known as the coherence time, denoted as $\Delta \tau$. The relationship governing this phenomenon is $\Delta \tau \Delta \nu \approx 1$, where $\Delta \nu$ represents the bandwidth of the light. This requirement is not satisfied, and hence, i

Ivan Smiljanic, Ivanka Bozovic, Goran Kacarevic

In order to measure integrated luminosity with a required precision of $10^{-4}$ at the $Z^0$ pole, proposed CEPC $e^{+}e^{-}$ collider requires a luminometer, a specially designed calorimeter placed in the very forward region to identify Bhabha scattering at low polar angles. Usually, such a device is placed at the outgoing beams, to keep the spatial symmet

Xiangyu Liang, Wenlin Zhuang, Tianyong Wang, Guangxing Geng

Speech-driven 3D facial animation technology has been developed for years, but its practical application still lacks expectations. The main challenges lie in data limitations, lip alignment, and the naturalness of facial expressions. Although lip alignment has seen many related studies, existing methods struggle to synthesize natural and realistic expression

Laslo Hunhold

Recent evaluations have highlighted the tapered posit number format as a promising alternative to the uniform precision IEEE 754 floating-point numbers, which suffer from various deficiencies. Although the posit encoding scheme offers superior coding efficiency at values close to unity, its efficiency markedly diminishes with deviation from unity. This reduc

Lorenzo Alvisi, Serena Tardelli, Maurizio Tesconi

Telegram has grown into a significant platform for news and information sharing, favored for its anonymity and minimal moderation. This openness, however, makes it vulnerable to misinformation and conspiracy theories. In this study, we explore the dynamics of conspiratorial narrative dissemination within Telegram, focusing on Italian and English landscapes.

Sabin Cautis, Rachel Ollivier

We identify the rigid dualizing complex of the (generic) affine Hecke algebra $H_q$ attached to a reduced root system and deduce some structural properties as a consequence. For example, we show that the classical Hecke algebra $H_{q^\pm}$ as well as $H_q/q$ are, under a certain condition on the root system, Frobenius over their centers with Nakayama automor

Vivek Dey, Steffen Kampman, Rafael Gutierrez, Gianaurelio Cuniberti

Brain-like self-assembled networks can infer and analyze information out of unorganized noisy signals with minimal power consumption. These networks are characterized by spatiotemporal avalanches and their crackling behavior, and their physical models are expected to predict and understand their computational capabilities. Here, we use a network theory-based

Debayan Bhattacharya, Finn Behrendt, Benjamin Tobias Becker, Lennart Maack

Purpose: Paranasal anomalies, frequently identified in routine radiological screenings, exhibit diverse morphological characteristics. Due to the diversity of anomalies, supervised learning methods require large labelled dataset exhibiting diverse anomaly morphology. Self-supervised learning (SSL) can be used to learn representations from unlabelled data. Ho

Tianyidan Xie, Rui Ma, Qian Wang, Xiaoqian Ye

Recent advancements in image-conditioned image generation have demonstrated substantial progress. However, foreground-conditioned image generation remains underexplored, encountering challenges such as compromised object integrity, foreground-background inconsistencies, limited diversity, and reduced control flexibility. These challenges arise from current e

Robin Guehne, Jonathan Noky, Changjiang Yi, Chandra Shekhar

The Kagome network is a unique platform in solid state physics that harbors a diversity of special electronic states due to its inherent band structure features comprising Dirac cones, van-Hove singularities, and flat bands. Some Kagome-based non-magnetic metals have recently been found to exhibit favorable properties, including unconventional superconductiv

Mohammad Rezaalipour, Carlo A. Furia

This paper presents FauxPy, a fault localization tool for Python programs. FauxPy supports seven well-known fault localization techniques in four families: spectrum-based, mutation-based, predicate switching, and stack trace fault localization. It is implemented as plugin of the popular Pytest testing framework, but also works with tests written for Unittest

Rowan Batzofin, Pierre Cristofari, Kathrin Egberts, Constantin Steppa

Supernova remnants (SNRs) are likely to be significant sources of cosmic rays up to the knee of the local cosmic-ray (CR) spectrum. They produce gamma-rays in the very-high-energy (VHE) ($E>0.1$ TeV) range via: hadronic interactions with the interstellar medium and leptonic interactions with soft photons. Current observations have lead to the detection of ab

Kazuma Nagao, Seiji Yunoki

Nonequilibrium dynamics of highly-controlled quantum systems is a challenging issue in statistical physics and quantum many-body physics, relevant to recent experimental developments of analog and digital quantum simulations. In this work, we develop a discrete phase-space approach for general SU($N$) spin systems that utilizes cluster mean field equations,

Edwin Kipchirchir, Jonathan Liebeton, Dirk Söffker

Dynamic fluctuations in the wind field to which a wind turbine (WT) is exposed to are responsible for fatigue loads on its components. To reduce structural loads in WTs, advanced control schemes have been proposed. In recent years, prognosis-based lifetime control of WTs has become increasingly important. In this approach, the prognostic controller gains are

Zhicheng Zhang, Mingsheng Ying

Atomicity is a ubiquitous assumption in distributed computing, under which actions are indivisible and appear sequential. In classical computing, this assumption has several theoretical and practical guarantees. In quantum computing, although atomicity is still commonly assumed, it has not been seriously studied, and a rigorous basis for it is missing. Class

Patrice Porion, Joël Puibasset

The freezing/melting transition is at the heart of many natural and industrial processes. In the classical picture, the transition proceeds via the nucleation of the new phase, which has to overcome a barrier associated to the free energy cost of the growing nucleus. The total nucleation rate is also influenced by a kinetic factor which somehow depends on th

Yasha Neiman

We study the higher-spin extension of self-dual General Relativity (GR) with cosmological constant, proposed by Krasnov, Skvortsov and Tran. We show that this theory is actually a gauge-fixing of a 6d diffeomorphism-invariant Abelian theory, living on (4d spacetime)x(2d spinor space) modulo a finite group. On the other hand, we point out that the theory resp

Martin Huesmann, Thomas Leblé

We investigate the interplay between three possible properties of stationary point processes: i) Finite Coulomb energy with short-scale regularization, ii) Finite $2$-Wasserstein transportation distance to the Lebesgue measure and iii) Hyperuniformity. In dimension $2$, we prove that i) implies ii), which is known to imply iii), and we provide simple counter

Zhenyao He, Wei Xu, Zhaohui Yang, Hong Shen

The exploration of extremely large antenna arrays (ELAAs) using high-frequency spectrum has led to a paradigm shift in electromagnetic radiation field, transitioning from the common use case of far-field propagation to near-field propagation. This shift necessitates the modification of the conventional planar-wavefront approximation to more accurate spherica

En-Jui Chang, Ching-Yi Lai

Gaussian quantum information processing with continuous-variable (CV) quantum information carriers holds significant promise for applications in quantum communication and quantum internet. However, applying Gaussian state distillation and quantum error correction (QEC) faces limitations imposed by no-go results concerning local Gaussian unitary operations an

Wei Zhou, Mohsen Mesgar, Heike Adel, Annemarie Friedrich

Table Question Answering (TQA) aims at composing an answer to a question based on tabular data. While prior research has shown that TQA models lack robustness, understanding the underlying cause and nature of this issue remains predominantly unclear, posing a significant obstacle to the development of robust TQA systems. In this paper, we formalize three maj

Benoît Barbot, Damien Busatto-Gaston, Catalin Dima, Youssouf Oualhadj

We consider the synthesis problem on timed automata with B\"uchi objectives, where delay choices made by a controller are subjected to small perturbations. Usually, the controller needs to avoid punctual guards, such as testing the equality of a clock to a constant. In this work, we generalize to a robustness setting that allows for punctual transitions in t

Maximilian Bernhard, Tanveer Hannan, Niklas Strauß, Matthias Schubert

Remote sensing projects typically generate large amounts of imagery that can be used to train powerful deep neural networks. However, the amount of labeled images is often small, as remote sensing applications generally require expert labelers. Thus, semi-supervised learning (SSL), i.e., learning with a small pool of labeled and a larger pool of unlabeled da

Philipp Berghofer, Jordan François

There is solid consensus among physicists and philosophers that, in gauge field theory, for a quantity to be physically meaningful or real, it must be gauge-invariant. Yet, every "elementary" field in the Standard Model of particle physics is actually gauge-variant. This has led a number of researchers to insist that new manifestly gauge-invariant approaches

E. Reyes-Rodríguez, J. E. Méndez-Delgado, J. García-Rojas, L. Binette

Context. Carbon is the fourth most abundant element in the universe and its distribution is critical to understanding stellar evolution and nucleosynthesis. In optical studies of ionized nebulae, the only way to determine the C/H abundance is by using faint CII recombination lines (RLs). However, these lines give systematically higher abundances than their c

Yongjian Zhu, Hao Cheng, Feitian Zhang

Miniature robotic blimps, as one type of lighter-than-air aerial vehicles, have attracted increasing attention in the science and engineering community for their enhanced safety, extended endurance, and quieter operation compared to quadrotors. Accurately modeling the dynamics of these robotic blimps poses a significant challenge due to the complex aerodynam

Hao Wang, Yun-Song Piao

Recently, Dark Energy Spectroscopic Instrument (DESI) collaboration based on their first year data has reported a $\gtrsim 3\sigma$ evidence for an evolving dark energy (DE) against the cosmological constant (CC), so the standard $\Lambda$CDM model. However, it is necessary to access the impact of DESI data on the state equation $w_0$-$w_a$ of DE in the Hubb

Guangyao Huang, Jibang Fu, Xiaofeng Yi, Weichen Wang

Majorana zero modes (MZMs), promising for topological quantum computation, are naturally hosted in vortices of two-dimensional topological superconductors (TSCs). However, precise control and braiding of these vortex-bound MZMs remains a significant challenge. This work proposes and numerically demonstrates a novel braiding scheme utilizing a programmable ma

Stefano Carlo Lambertenghi, Andrea Stocco

Simulation-based testing of automated driving systems (ADS) is the industry standard, being a controlled, safe, and cost-effective alternative to real-world testing. Despite these advantages, virtual simulations often fail to accurately replicate real-world conditions like image fidelity, texture representation, and environmental accuracy. This can lead to s

Mateja Dumbovic, Luci Karbonini, Jasa Calogovic, Filip Matkovic

We compile the catalog of Hvar Observatory solar observations in the time period corresponding to regular digitally stored chromospheric and photospheric observations 2010-2019. We make basic characterisation of observed phenomena and compare them to catalogs which are based on full disc solar images. We compile a catalog of observed ARs consisting of 1100 e

Hassen Nigatu

This study presents a comparison between the Sprint Z3 and A3 head parallel kinematics machines, distinguished by their joint sequence. The analysis focuses on performance attributes critical for precision machining specifically, parasitic motion, workspace capability, stiffness performance over the independent and parasitic spaces, and condition number dist

Florian Rupp, Kai Eckert

Game economy design significantly shapes the player experience and progression speed. Modern game economies are becoming increasingly complex and can be very sensitive to even minor numerical adjustments, which may have an unexpected impact on the overall gaming experience. Consequently, thorough manual testing and fine-tuning during development are essentia

Arpit Aggarwal

There are several improvements proposed over the baseline Absolute Positional Encoding (APE) method used in original transformer. In this study, we aim to investigate the implications of inadequately representing positional encoding in higher dimensions on crucial aspects of the attention mechanism, the model's capacity to learn relative positional informati

Ruben Grewal, Paolo Tonella, Andrea Stocco

The automated real-time recognition of unexpected situations plays a crucial role in the safety of autonomous vehicles, especially in unsupported and unpredictable scenarios. This paper evaluates different Bayesian uncertainty quantification methods from the deep learning domain for the anticipatory testing of safety-critical misbehaviours during system-leve

Gevik Grigorian, Sandip V. George, Simon Arridge

Data-driven modelling and scientific machine learning have been responsible for significant advances in determining suitable models to describe data. Within dynamical systems, neural ordinary differential equations (ODEs), where the system equations are set to be governed by a neural network, have become a popular tool for this challenge in recent years. How

Francesco Periti, Pierluigi Cassotti, Haim Dubossarsky, Nina Tahmasebi

Modern language models are capable of contextualizing words based on their surrounding context. However, this capability is often compromised due to semantic change that leads to words being used in new, unexpected contexts not encountered during pre-training. In this paper, we model \textit{semantic change} by studying the effect of unexpected contexts intr

Yanchen He, Paul Houston, Christoph Schwab, Thomas P. Wihler

We study the fully explicit numerical approximation of a semilinear elliptic boundary value model problem, which features a monomial reaction and analytic forcing, in a bounded polygon $\Omega\subset\mathbb{R}^2$ with a finite number of straight edges. In particular, we analyze the convergence of $hp$-type iterative linearized Galerkin ($hp$-ILG) solvers. Ou

Fei Xu, Manting Xie, Meiling Yue

In this paper, a novel multigrid method based on Newton iteration is proposed to solve nonlinear eigenvalue problems. Instead of handling the eigenvalue $\lambda$ and eigenfunction $u$ separately, we treat the eigenpair $(\lambda, u)$ as one element in a product space $\mathbb R \times H_0^1(\Omega)$. Then in the presented multigrid method, only one discrete

Ioannis Korontanis, Antonios Makris, Konstantinos Tserpes

In recent years, there has been a concerted effort in both industry and research sectors to innovate new approaches to DevOps. The primary aim is to facilitate developers in transitioning their applications to Cloud or Edge platforms utilizing Docker or Kubernetes. This paper presents a tool called Converter, designed to interpret a TOSCA extension called CE

Md Imran Hossen, Sai Venkatesh Chilukoti, Liqun Shan, Sheng Chen

Instruction-tuned Large Language Models designed for coding tasks are increasingly employed as AI coding assistants. However, the cybersecurity vulnerabilities and implications arising from the widespread integration of these models are not yet fully understood due to limited research in this domain. This work investigates novel techniques for transitioning

Michael Elbracht, Michael Potthoff

We numerically study the relaxation dynamics of impurity-host systems, focusing on the presence of long-lived metastable states in the non-equilibrium dynamics after an initial excitation of the impurities. In generic systems, an excited impurity coupled to a large bath at zero temperature is expected to relax and approach its ground state over time. However

Dawei Shen

In 1993, the global stability of Minkowski spacetime was proved in the celebrated work of Christodoulou and Klainerman. In 2003, Klainerman and Nicol\`o revisited Minkowski stability in the exterior of an outgoing null cone. In 2023, the author extended the results of Christodoulou-Klainerman to minimal decay assumptions. In this paper, we prove that the ext

Julien Heyd, Joel Merker

We determine all affinely homogeneous hypersurfaces S^3 in R^4 whose Hessian is (invariantly) of constant rank 2, including the simply transitive ones. We find 34 inequivalent terminal branches yielding each to a nonempty moduli space of homogeneous models of hypersurfaces S^3 in R^4, sometimes parametrized by a certain complicated algebraic variety, especia

Wen-Yu Chang, Yun-Nung Chen

Recent research in dialogue systems and corpora has focused on two main categories: task-oriented (TOD) and open-domain (chit-chat) dialogues. TOD systems help users accomplish specific tasks, while open-domain systems aim to create engaging conversations. However, in real-world scenarios, user intents are often revealed during interactions. A recent study i

Z. Q. Qu, H. Su, Y. Liang, Z. Xu

Solar corona has been judged to consist of free electrons and highly ionized ions with extremely high temperature as a widely accepted knowledge. This view is changed by our eclipse observations. Distributions of cool matter represented by neutral iron atoms in hot inner solar corona are presented via derived global maps of solar Fraunhofer(F-) and Emission(

Fátima Rodríguez-Galán, Ama Bandara, Elana Pereira de Santana, Peter Haring Bolívar

Wireless Network-on-Chip (WNoC) has been proposed as a low-latency, versatile, and broadcast-capable complement to current interconnects in the quest for satisfying the ever-increasing communications needs of modern computing systems. However, to realize the promise of WNoC, multiple wireless links operating at several tens of Gb/s need to be created within

Zhenxi Song, Ruihan Qin, Huixia Ren, Zhen Liang

Cross-center data heterogeneity and annotation unreliability significantly challenge the intelligent diagnosis of diseases using brain signals. A notable example is the EEG-based diagnosis of neurodegenerative diseases, which features subtler abnormal neural dynamics typically observed in small-group settings. To advance this area, in this work, we introduce

Guangchen Wang, Shujun Wang, Jie Xiong

A linear quadratic (LQ) stochastic optimization system involving large population, which is driven by forward-backward stochastic differential equation (FBSDE), is investigated in this paper. Agents cooperate with each other to minimize the so-called social objective, which is rather different from mean field (MF) game. Employing forward-backward person-by-p

Xin Chen, Chunfeng Cui, Deren Han, Liqun Qi

Pose graph optimization (PGO) is a well-known technique for solving the pose-based simultaneous localization and mapping (SLAM) problem. In this paper, we represent the rotation and translation by a unit quaternion and a three-dimensional vector, and propose a new PGO model based on the von Mises-Fisher distribution. The constraints derived from the unit qua

João M. Alves

In this paper, we introduce Unitary Flavour Violation to produce Multi-Higgs Doublets Models where all flavour parameters are contained within three unitary matrices. After that, we identify two of its subclasses, the left and right models, which have naturally suppressed tree-level Flavour Changing Neutral Couplings that easily avoid the experimental constr

Sergio Morales, Robert Clarisó, Jordi Cabot

The integration of Large Language Models (LLMs) into various software applications raises concerns about their potential biases. Typically, those models are trained on a vast amount of data scrapped from forums, websites, social media and other internet sources, which may instill harmful and discriminating behavior into the model. To address this issue, we p

Stefano Bannò, Hari Krishna Vydana, Kate M. Knill, Mark J. F. Gales

Automated essay scoring (AES) to evaluate second language (L2) proficiency has been a firmly established technology used in educational contexts for decades. Although holistic scoring has seen advancements in AES that match or even exceed human performance, analytic scoring still encounters issues as it inherits flaws and shortcomings from the human scoring

Daniel Goldsmith, M M Hassan Mahmud

Quantum machine learning (QML) is a promising early use case for quantum computing. There has been progress in the last five years from theoretical studies and numerical simulations to proof of concepts. Use cases demonstrated on contemporary quantum devices include classifying medical images and items from the Iris dataset, classifying and generating handwr

Cameron Ruether

Working over an arbitrary base scheme, we provide an alternative development of triality which does not use Octonion algebras or symmetric composition algebras. Instead, we use the Clifford algebra of the split hyperbolic quadratic form of rank 8 and computations with Chevalley generators of groups of type $D_4$. Following the strategy of The Book of Involut

Gareth Davies

Autoregressive Recurrent Neural Networks are widely employed in time-series forecasting tasks, demonstrating effectiveness in univariate and certain multivariate scenarios. However, their inherent structure does not readily accommodate the integration of future, time-dependent covariates. A proposed solution, outlined by Salinas et al 2019, suggests forecast

Manos Schinas, Symeon Papadopoulos

The generative AI technology offers an increasing variety of tools for generating entirely synthetic images that are increasingly indistinguishable from real ones. Unlike methods that alter portions of an image, the creation of completely synthetic images presents a unique challenge and several Synthetic Image Detection (SID) methods have recently appeared t

Nguyen Thanh Luan, Kim Hong Joo, Lee Hyun Su, Jin Jegal

The NaI:Tl crystals were early investigated and used for wide application fields due to high light yield and crystal growth advantages. So far, the absolute light yields of NaI:Tl crystal have typically been known to be 40 ph/keV. However, it varies widely, far from the theoretical estimation. Since the high light yield and better sensitivity of NaI:Tl cryst

Artur Grigorev, Adriana-Simona Mihaita Khaled Saleh, Yuming Ou

The proposed IncidentResponseGPT framework - a novel system that applies generative artificial intelligence (AI) to potentially enhance the efficiency and effectiveness of traffic incident response. This model allows for synthesis of region-specific incident response guidelines and generates incident response plans adapted to specific area, aiming to expedit