May 2024 arXiv papers — page 106

Luoqi Wang, Haipeng Li, Linshu Hu, Jiarui Cai

The reconstruction of Earth's history faces significant challenges due to the nonunique interpretations often derived from rock records. The problem has long been recognized but there are no systematic solutions in practice. This study introduces an innovative approach that leverages Large Language Models (LLMs) along with retrieval augmented generation and

Francesco Leofante, Hamed Ayoobi, Adam Dejl, Gabriel Freedman

AI has become pervasive in recent years, but state-of-the-art approaches predominantly neglect the need for AI systems to be contestable. Instead, contestability is advocated by AI guidelines (e.g. by the OECD) and regulation of automated decision-making (e.g. GDPR). In this position paper we explore how contestability can be achieved computationally in and

Daniel Spector, Dmitriy Stolyarov

In this paper, we define spaces of measures $DS_\beta(\mathbb{R}^d)$ with dimensional stability $\beta \in (0,d)$. These spaces bridge between $M_b(\mathbb{R}^d)$, the space of finite Radon measures, and $DS_d(\mathbb{R}^d)= \mathrm{H}^1(\mathbb{R}^d)$, the real Hardy space. We show the spaces $DS_\beta(\mathbb{R}^d)$ support Sobolev inequalities for $\beta

Yaning Xu, Yuanyuan Chen, Xi Chen

In this study, we investigate the dynamics of tunable spin-orbit-coupled spin-1 Bose-Einstein condensates confined within a harmonic trap, focusing on rapid transport, spin manipulation, and splitting dynamics. Using shortcuts to adiabaticity, we design time-dependent trap trajectories and spin-orbit-coupling strength to facilitate fast transport with simult

Naoya Hiramae

In this paper, we show that weakly symmetric $\tau$-tilting finite algebras have positive definite Cartan matrices, which implies that we can prove $\tau$-tilting infiniteness of weakly symmetric algebras by calculating their Cartan matrices. Similarly, we obtain the condition on Cartan matrices that selfinjective algebras are $\tau$-tilting infinite. By app

Bishwaranjan Bhattacharjee, Aashka Trivedi, Masayasu Muraoka, Muthukumaran Ramasubramanian

Large language models (LLMs) trained on general domain corpora showed remarkable results on natural language processing (NLP) tasks. However, previous research demonstrated LLMs trained using domain-focused corpora perform better on specialized tasks. Inspired by this insight, we developed INDUS, a comprehensive suite of LLMs tailored for the closely-related

Mieke Wessel

We prove some new instances of a conjecture of Bachoc, Couvreur and Z\'emor that generalizes Freiman's $3k-4$ Theorem to a multiplicative version in a function field setting. As a consequence we find that if $F$ is a rational function field over an algebraically closed field $K$ and $S \subset F$ a finite dimensional $K$-vector space such that $\dim S^2 = 2\

Antoine Legouhy, Ross Callaghan, Whitney Stee, Philippe Peigneux

Modern diffusion MRI sequences commonly acquire a large number of volumes with diffusion sensitization gradients of differing strengths or directions. Such sequences rely on echo-planar imaging (EPI) to achieve reasonable scan duration. However, EPI is vulnerable to off-resonance effects, leading to tissue susceptibility and eddy-current induced distortions.

Wolfgang Kreuzer

The Burton-Miller method is a widely used approach in acoustics to enhance the stability of the boundary element method for exterior Helmholtz problems at so-called critical frequencies. This method depends on a coupling parameter $\eta$ and it can be shown that as long as $\eta$ has an imaginary part different from 0, the boundary integral formulation for t

Samuel Lai, Christopher A. Onken, Christian Wolf, Fuyan Bian

We investigate the black hole mass function at $z\sim5$ using XQz5, our recent sample of the most luminous quasars between the redshifts $4.5 < z < 5.3$. We include 72 quasars with black hole masses estimated from velocity-broadened emission-line measurements and single-epoch virial prescriptions in the footprint of a highly complete parent survey. The sampl

Alexander Alexandrov, Boris Bychkov, Petr Dunin-Barkowski, Maxim Kazarian

We review the notion of symplectic duality earlier introduced in the context of topological recursion. We show that the transformation of symplectic duality can be expressed as a composition of $x-y$ dualities in a broader context of log topological recursion. As a corollary, we establish nice properties of symplectic duality: various convenient explicit for

Ivan Buntic, Martin Schneider, Bernd Flemisch, Rainer Helmig

Vertical equilibrium models have proven to be well suited for simulating fluid flow in subsurface porous media such as saline aquifers with caprocks. However, in most cases the dimensionally reduced model lacks the accuracy to capture the dynamics of a system. While conventional full-dimensional models have the ability to represent dynamics, they come at the

Kaveh S. Nobari, Alex Gibberd

We study an $\ell_{1}$-regularized generalized least-squares (GLS) estimator for high-dimensional regressions with autocorrelated errors. Specifically, we consider the case where errors are assumed to follow an autoregressive process, alongside a feasible variant of GLS that estimates the structure of this process in a data-driven manner. The estimation proc

Sen Fang, Chen Chen, Lei Wang, Ce Zheng

In this paper, we propose SignLLM, a multilingual Sign Language Production (SLP) large language model, which includes two novel multilingual SLP modes MLSF and Prompt2LangGloss that allow sign language gestures generation from query texts input and question-style prompts input respectively. Both modes can use a new RL loss based on reinforcement learning and

Yves Kini, Tuomo Salmi, Serena Vinciguerra, Anna L. Watts

Pulse profile modelling (PPM) is a comprehensive relativistic ray-tracing technique employed to determine the properties of neutron stars. In this study, we apply this technique to the Type I X-ray burster and accretion-powered millisecond pulsar XTE J1814-338, extracting its fundamental properties using PPM of its thermonuclear burst oscillations. Using dat

Zehua Dou, Hannes Rox, Zyzi Ramos, Robert Baumann

Improved understanding of gas/liquid transport in electrochemical gas-evolving systems is increasingly demanded for optimizing device performance. However, high-resolution measurement techniques for in-situ imaging remain limited. This work demonstrates the use of volumetric scanning acoustic microscopy (SAM) for quantifying hydrogen bubble evolution in poro

Harini Raghavan, Michael C. D. Tayler, Kostas Mouloudakis, Rachel Rae

We describe micro-fabricated rubidium vapor cells with integrated temperature-control functionality and demonstrate their suitability for use in miniaturized ultra-sensitive magnetometers. These functionalized vapor cells (FVCs) embody a dual-chamber design in low-conductivity silicon with anti-permeation coatings and micro-structured thin-film platinum surf

Hassan Haji Mohammadi, Alireza Talebpour, Ahmad Mahmoudi Aznaveh, Samaneh Yazdani

Coreference resolution, critical for identifying textual entities referencing the same entity, faces challenges in pronoun resolution, particularly identifying pronoun antecedents. Existing methods often treat pronoun resolution as a separate task from mention detection, potentially missing valuable information. This study proposes the first end-to-end neura

A Akanbi

Drought is a complex environmental phenomenon that affects millions of people and communities all over the globe and is too elusive to be accurately predicted. This is mostly due to the scalability and variability of the web of environmental parameters that directly/indirectly causes the onset of different categories of drought. Since the dawn of man, effort

Jonas R. Brehmer, Kristof Kraus, Tilmann Gneiting, Marcus Herrmann

Testing earthquake forecasts is essential to obtain scientific information on forecasting models and sufficient credibility for societal usage. We aim at enhancing the testing phase proposed by the Collaboratory for the Study of Earthquake Predictability (CSEP, Schorlemmer et al., 2018) with new statistical methods supported by mathematical theory. To demons

Daniele Lamberto, Omar Di Stefano, Stephen Hughes, Franco Nori

A potential phase transition between a normal ground state and a photon-condensed ground state in many-dipole light-matter systems is a topic of considerable controversy, exasperated by conflicting no-go and counter no-go theorems and often ill-defined models. We clarify this long-lasting debate by analyzing two specific arrangements of atoms, including a 3D

Nour Alnajjarine, Michel Lavrauw

This paper is a contribution towards a solution for the longstanding open problem of classifying linear systems of conics over finite fields initiated by L. E. Dickson in 1908, through his study of the projective equivalence classes of pencils of conics in $\mathrm{PG}(2,q)$, for $q$ odd. In this paper a set of complete invariants is determined for the proje

Aleksei Chernov

Basic idea of $CP$ violation and its importance for cosmology, Standard Model and possible New Physics are introduced. Recent (2019) discovery of CP violation in charm in the $\Delta A_{CP}$ between $D^0\rightarrow K^-K^+$ and $D^0\rightarrow \pi^+\pi^-$ decay channels and evidence for direct CP violation in $D^0\rightarrow \pi^-\pi^+$ decays in 2023 is disc

Bangti Jin, Xiliang Lu, Qimeng Quan, Zhi Zhou

In this work, we investigate a numerical procedure for recovering a space-dependent diffusion coefficient in a (sub)diffusion model from the given terminal data, and provide a rigorous numerical analysis of the procedure. By exploiting decay behavior of the observation in time, we establish a novel H{\"o}lder type stability estimate for a large terminal time

Mengxi Zhang, Heqing Lian, Yiming Liu, Jie Chen

Referring image segmentation (RIS) aims to locate the particular region corresponding to the language expression. Existing methods incorporate features from different modalities in a \emph{bottom-up} manner. This design may get some unnecessary image-text pairs, which leads to an inaccurate segmentation mask. In this paper, we propose a referring image segme

Sebastian Tschiatschek, Eugenia Stamboliev, Timothée Schmude, Mark Coeckelbergh

We discuss the role of humans in algorithmic decision-making (ADM) for socially relevant problems from a technical and philosophical perspective. In particular, we illustrate tensions arising from diverse expectations, values, and constraints by and on the humans involved. To this end, we assume that a strategic decision-maker (SDM) introduces ADM to optimiz

Farid Bozorgnia, Vyacheslav Kungurtsev

We consider an optimal control problem where the state is governed by a free boundary problem called the two-phase membrane problem and the control appears in the coefficients of the characteristic function of the positivity and negativity parts of the solution. Our investigation focuses on various properties associated with the control-to-state map. Due to

Yannis Spyridis, Jean-Paul, Haneen Deeb, Vasileios Argyriou

The classification of statements provided by individuals during police interviews is a complex and significant task within the domain of natural language processing (NLP) and legal informatics. The lack of extensive domain-specific datasets raises challenges to the advancement of NLP methods in the field. This paper aims to address some of the present challe

Rina Mudi, Alessandro Carpentiero, Monica Bollani, Mario Barozzi

We report the existence of optical Tamm states (OTS) in inverse opal (IO) - based three-dimensional photonic crystal on a flat metal substrate, validated through both numerical simulations and experimental observations. Our fabrication approach for the Tamm inverse opal (Tamm-IO) structure is notably straightforward and does not involve corrosive chemicals.

Michael Shliselberg, Ashkan Kazemi, Scott A. Hale, Shiri Dori-Hacohen

Diaspora communities are disproportionately impacted by off-the-radar misinformation and often neglected by mainstream fact-checking efforts, creating a critical need to scale-up efforts of nascent fact-checking initiatives. In this paper we present SynDy, a framework for Synthetic Dynamic Dataset Generation to leverage the capabilities of the largest fronti

Connor P. Fallows, Jason L. Sanders

With the plentiful information available in the Gaia BP/RP spectra, there is significant scope for applying discriminative models to extract stellar atmospheric parameters and abundances. We describe an approach to leverage an `Uncertain Neural Network' model trained on APOGEE data to provide high-quality predictions with robust estimates for per-prediction

Connor Roberts, Emir Sezik, Eloise Lardet

We model an overdamped Brownian particle that is subject to resetting facilitated by a ratchet potential on a spatially periodic domain. This asymmetric potential switches on with a constant rate, but switches off again only upon the particle's first passage to a resetting point at the minimum of the potential. Repeating this cycle sustains a non-equilibrium

Zheng-Chuan Wang

Based on the adiabatic geometric phase concerning with density matrix[1] , we extend it to the sub-geometric phase in the non-adiabatic case. It is found that whatever the real part or imaginary part of the sub-geometric phase can play an important role in quantum transition. The imaginary part of sub-geometric phase can deviate the resonance peak in the qua

Tayab Uddin Wara, Ababil Hossain Fahad, Adri Shankar Das, Md. Mehedi Hasan Shawon

Sleep is vital for people's physical and mental health, and sound sleep can help them focus on daily activities. Therefore, a sleep study that includes sleep patterns and sleep disorders is crucial to enhancing our knowledge about individuals' health status. This study aims to provide a comprehensive, systematic review of the recent literature to analyze the

Yi Yao, Jun Wang, Yabai Hu, Lifeng Wang

The evolution of software testing from manual to automated methods has significantly influenced quality assurance (QA) practices. However, challenges persist in post-execution phases, particularly in result analysis and reporting. Traditional post-execution validation phases require manual intervention for result analysis and report generation, leading to in

Yannis Spyridis, Vasileios Argyriou, Antonios Sarigiannidis, Panagiotis Radoglou

The escalating volumes of textile waste globally necessitate innovative waste management solutions to mitigate the environmental impact and promote sustainability in the fashion industry. This paper addresses the inefficiencies of traditional textile sorting methods by introducing an autonomous textile analysis pipeline. Utilising robotics, spectral imaging,

Thrassos K. Oikonomou, Dimitrios Tyrovolas, Sotiris A. Tegos, Panagiotis D. Diamantoulakis

In the evolving landscape of sixth-generation (6G) wireless networks, which demand ultra high data rates, this study introduces the concept of super constellation communications. Also, we present super amplitude phase shift keying (SAPSK), an innovative modulation technique designed to achieve these ultra high data rate demands. SAPSK is complemented by the

Smiljana Jakšić, Stevan Pilipović, Nenad Teofanov, Đorđe Vučković

We use the iterates of the Laguerre operator to introduce Pilipovi\'c spaces on positive orthants. It is shown that such spaces coincide with $G-$type spaces $g_\alpha^\alpha(\mathbb{R}^d_+)$ and $G_\alpha^\alpha(\mathbb{R}^d_+)$, when $\alpha > 1$, and $\alpha \geq 1$, respectively. However, in contrast to $G$-type spaces, Pilipovi\'c spaces on positive ort

Harry C. Shaw

In this paper we give an asymptotic formula for the quantity of diagonal del Pezzo surfaces of degree 2 which have a Brauer-Manin obstruction to the Hasse principle when ordered by height.

Yurino Mizuguchi, Tomoaki Murata, Yuichiro Tada

We develop a C++ package of the STOchastic LAttice Simulation (STOLAS) of cosmic inflation. It performs the numerical lattice simulation in the application of the stochastic-$\delta N$ formalism. STOLAS can directly compute the three-dimensional map of the observable curvature perturbation without estimating its statistical properties. In its application to

Zihao Zhu, Tianli Tao, Yitian Tao, Haowen Deng

The infant brain undergoes rapid development in the first few years after birth.Compared to cross-sectional studies, longitudinal studies can depict the trajectories of infants brain development with higher accuracy, statistical power and flexibility.However, the collection of infant longitudinal magnetic resonance (MR) data suffers a notorious dropout probl

Faegheh Sardari, Armin Mustafa, Philip J. B. Jackson, Adrian Hilton

Weakly supervised audio-visual video parsing (AVVP) methods aim to detect audible-only, visible-only, and audible-visible events using only video-level labels. Existing approaches tackle this by leveraging unimodal and cross-modal contexts. However, we argue that while cross-modal learning is beneficial for detecting audible-visible events, in the weakly sup

Mehrdad Agha Mohammad Ali Kermani, Hamid Reza Seddighi, Mehrdad Maghsoudi

In the rapidly evolving field of business process management, there is a growing need for analytical tools that can transform complex data into actionable insights. This research introduces a novel approach by integrating Large Language Models (LLMs), such as ChatGPT, into process mining tools, making process analytics more accessible to a wider audience. Th

Samrat Sen, Avijeet Prasad, Valeriia Liakh, Rony Keppens

The formation of the MFRs in the pre-flare stage, and how this leads to coronal rain in a post-eruption magnetic loop is not fully understood. We explore the formation, and eruption of MFRs, followed by the appearance of coronal rain in the post-flare loops, to understand the magnetic and thermodynamic properties of eruptive events and their multi-thermal as

Florian Tönnies, Adam Brown, Baris Kiyim, Fabian Kuger

The largest direct dark matter search experiments to date employ dual-phase time projection chambers (TPCs) with liquid noble gas targets. These detect both the primary photons generated by particle interactions in the liquid target, as well as proportional secondary scintillation light created by the ionization electrons in a strong electric field in the ga

Eveline Mayner, Nathan Ronceray, Martina Lihter, Tzu-Heng Chen

Electrochemical techniques conventionally lack spatial resolution and average local information over an entire electrode. While advancements in spatial resolution have been made through scanning probe methods, monitoring dynamics over large areas is still challenging, and it would be beneficial to be able to decouple the probe from the electrode itself. In t

Simone Rijavec, Giuseppe Di Pietra

We propose a collision model to investigate the information dynamics of a system coupled to an environment with varying degrees of non-Markovianity. We control the degree of non-Markovianity by applying a depolarising channel to a fixed and rigid reservoir of qubits. We characterise the effect of the depolarising channel and apply the model to study the cohe

Simona Paiano, Renato Falomo, Aldo Treves, Riccardo Scarpa

Following the high activity of the gamma-ray Fermi source 4FGL J0449.1+1121 (PKS 0446+112), possibly associated with a IceCube neutrino event IC-240105A, we obtained optical spectroscopy with the Gran Telescopio Canarias of the counterpart. We detect a clear emission line at 3830 Ang identified as Ly$\alpha$ that confirms the redshift of source at z=2.153. C

I. Ruffa, T. A. Davis

Local early-type galaxies (ETGs) are mostly populated by old stars, with little or no recent star formation activity. For this reason, they have historically been believed to be essentially devoid of cold gas, that is the fuel for the formation of new stars. Over the past two decades, however, increasingly-sensitive instrumentation observing the sky at (sub-

Aitor Erkoreka, Josu Martinez-Perdiguero

Ferroelectric nematic liquid crystals are currently being subject to a plethora of investigations since they are of great fundamental interest and could potentially foster promising applications. However, many basic aspects are still poorly understood, among which the problem of the dielectric constant stands out. Ferroelectric nematics exhibit giant dielect

XiaoYu Wang, YongHui Guo, Hui Sheng, Peili Lv

Real-time Bidding (RTB) advertisers wish to \textit{know in advance} the expected cost and yield of ad campaigns to avoid trial-and-error expenses. However, Campaign Performance Forecasting (CPF), a sequence modeling task involving tens of thousands of ad auctions, poses challenges of evolving user interest, auction representation, and long context, making c

Nadège Meunier, Anne-Marie Lagrange, Xavier Dumusque, Sophia Sulis

Stellar variability strongly impacts the search for low-mass exoplanets with radial velocity techniques. Two types of planet-free time series can be used to quantify this impact: models and direct solar observations after a subtraction of the Solar System planetary contribution. Comparing these approaches is necessary for simulations. Our objective is to val

Theodoros Zafeiriou, Dimitris Kalles

Our study focuses on comparing the performance and resource requirements between different Long Short-Term Memory (LSTM) neural network architectures and an ANN specialized architecture for forex market prediction. We analyze the execution time of the models as well as the resources consumed, such as memory and computational power. Our aim is to demonstrate

Mou Li, He Wang, Peter K. Jimack

We present a new deep learning paradigm for the generation of sparse approximate inverse (SPAI) preconditioners for matrix systems arising from the mesh-based discretization of elliptic differential operators. Our approach is based upon the observation that matrices generated in this manner are not arbitrary, but inherit properties from differential operator

Carlos Alberto Durigan Junior, Fernando Jose Barbin Laurindo

Cryptocurrency can be understood as a digital asset transacted among participants in the crypto economy. Every cryptocurrency must have an associated Blockchain. Blockchain is a Distributed Ledger Technology (DLT) which supports cryptocurrencies, this may be considered as the most promising disruptive technology in the industry 4.0 context. Decentralized fin

Dorsaf Cherif, Emmanuel Lepinette

In this paper, we introduce a large class of (so-called) conditional indicators, on a complete probability space with respect to a sub $\sigma$-algebra. A conditional indicator is a positive mapping, which is not necessary linear, but may share common features with the conditional expectation, such as the tower property or the projection property. Several ch

Meihuizi He, Songfen Liu, Fan Xia, Zongyu Yang

During the operation of tokamak devices, addressing the thermal load issues caused by Edge Localized Modes (ELMs) eruption is crucial. Ideally, mitigation and suppression measures for ELMs should be promptly initiated as soon as the first low-to-high confinement (L-H) transition occurs, which necessitates the real-time monitoring and accurate identification

X. H. Verbeek, D. Voderholzer, S. Schären, Y. Gachnang

We show that hematite, $\alpha$-Fe$_2$O$_3$, below its Morin transition, has a ferroic ordering of rank-5 magnetic triakontadipoles on the Fe ions. In the absence of spin-orbit coupling, these are the lowest-order ferroically aligned magnetic multipoles, and they give rise to the $g$-wave non-relativistic spin splitting in hematite. We find that the ferroica

Rui Sun, Yumin Zhang, Tejal Shah, Jiahao Sun

With impressive achievements made, artificial intelligence is on the path forward to artificial general intelligence. Sora, developed by OpenAI, which is capable of minute-level world-simulative abilities can be considered as a milestone on this developmental path. However, despite its notable successes, Sora still encounters various obstacles that need to b

Carlos Alberto Durigan Junior, Kumiko Oshio Kissimoto, Fernando Jose Barbin Laurindo

The fourth industrial revolution promotes the integration of Information Technology (IT) and strategic resources. New IT demands and uses have been leading to changes in business processes and corporate governance. Lately, the financial industry has adopted a new integrated banking model known as Open Banking (OB) and the advent of cryptocurrencies has led t

Valeria S. Kostiuk, Alexander A. Marchuk, Alexander S. Gusev

A co-rotation radius is a key characteristic of disc galaxies that is essential to determine the angular speed of the spiral structure $\Omega_{p}$, and therefore understand its nature. In the literature, there are plenty of methods to estimate this value, but do these measurements have any consistency? In this work, we collected a dataset of corotation radi

Pietro Talli, Edoardo David Santi, Federico Chiariotti, Touraj Soleymani

Pragmatic or goal-oriented communication can optimize communication decisions beyond the reliable transmission of data, instead aiming at directly affecting application performance with the minimum channel utilization. In this paper, we develop a general theoretical framework for the remote control of finite-state Markov processes, using pragmatic communicat

Carlos Herdeiro, Hyat Huang, Jutta Kunz, Eugen Radu

We consider a model with two real Maxwell fields (or equivalently, a complex Maxwell field) minimally coupled to Einsteins gravity with a negative cosmological constant in four spacetime dimensions. Assuming a specific harmonic dependence of the vector fields, we show the existence of asymptotically anti-de Sitter (AdS) self-gravitating boson-star-like solit

Jackson A. Mickley, Waseem Kamleh, Derek B. Leinweber

The geometry of centre vortices is studied in $\mathrm{SU(3)}$ gauge theory at finite temperature to capture the key structural changes that occur through the deconfinement phase transition. Visualisations of the vortex structure in temporal and spatial slices of the lattice reveal a preference for the vortex sheet to align with the temporal dimension above

Peter Hintz

We develop a general theory for the existence, uniqueness, and higher regularity of solutions to wave-type equations on Lorentzian manifolds with timelike curves of cone-type singularities. These singularities may be of geometric type (cone points with time-dependent cross sectional metric), of analytic type (such as asymptotically inverse square singulariti

L. A. Leppin, T. Görler, L. Frassinetti, S. Saarelma

Turbulent transport is a decisive factor in determining the pedestal structure of H-modes. Here, we present the first comprehensive characterization of gyrokinetic turbulent transport in a JET hybrid H-mode pedestal. Local, linear simulations are performed to identify instabilities and global, nonlinear electromagnetic simulations reveal the turbulent heat a

Lukas Cvitkovich, Peter Stano, Christoph Wilhelmer, Dominic Waldhör

On the quest to understand and reduce environmental noise in Si spin qubits, hyperfine interactions between electron and nuclear spins impose a major challenge. Silicon is a promising host material because one can enhance the spin coherence time by removing spinful $^{29}$Si isotopes. As more experiments rely on isotopic purification of Si, the role of other

Carlos Alberto Durigan Junior, Mauro De Mesquita Spinola, Rodrigo Franco Gonçalves, Fernando José Barbin Laurindo

Central Bank Digital Currency (CBDC) can be defined as a virtual currency based on node network and digital encryption algorithm issued by a country which has a legal credit protection. CBDCs are supported by Distributed Ledger Technologies (DLTs), and they may allow a universal means of payments for the digital era. There are many ways to proceed, they all

Ljubica Djurović, Maja Laković, Nenad Stojanović

In our work, we continue to explore the properties of interval-valued fuzzy soft sets, which are obtained by combining interval-valued fuzzy sets and soft sets. We introduce the concept of energy of an interval-valued fuzzy soft set, as well as pessimistic and optimistic energy, enabling us to construct an effective decision-making algorithm. Through example

I. T. Habibullin, A. U. Sakieva

The article considers lattices of the two-dimensional Toda type, which can be interpreted as dressing chains for spatially two-dimensional generalizations of equations of the class of nonlinear Schr\"odinger equations. The well-known example of this kind of generalization is the Davey-Stewartson equation. It turns out that the finite-field reductions of thes

Mihir Mandar Kulkarni, Ankit Anil Chaudhari, Karthik K. Srinivasan, Bhargava Rama Chilukuri

Most car-following models were originally developed for lane-based traffic. Over the past two decades, efforts have been made to calibrate car-following models for non-lane-based traffic. However, traffic conditions with varying vehicle dimensions, intermittent following, and multiple leaders often occur and make subjective Leader-Follower (LF) pair identifi

Tao Huang, Pengfei Chen, Kyoka Gong, Jocky Hawk

Since the increasing popularity of large language model (LLM) backend systems, it is common and necessary to deploy stable serverless serving of LLM on multi-GPU clusters with autoscaling. However, there exist challenges because the diversity and co-location of applications in multi-GPU clusters will lead to low service quality and GPU utilization. To addres

Kyeongsu Choi, Dong-Hwi Seo, Wei-Bo Su, Kai-Wei Zhao

In this paper, we prove that an ancient smooth curve shortening flow with finite-entropy embedded in $\mathbb{R}^2$ has a unique tangent flow at infinity. To this end, we show that its rescaled flows backwardly converge to a line with multiplity $m\geq 3$ exponentially fast in any compact region, unless the flow is a shrinking circle, a static line, a paper

J. Wang, D. W. Xu, Xinwu Cao, C. Gao

The origin of the "Changing-look" (CL) phenomenon in supermassive black holes (SMBHs) remains an open issue. This study aims to shed light on this phenomenon by focusing on a sample that encompasses all known repeating CL active galactic nuclei (AGNs). Through the identification of a characteristic time scale for the CL phenomenon, it was observed that large

Mojtaba Hosseini, Seyed Yaser Ayazi, Ahmad Mohamadnejad

We consider a first order phase transition (FOPT) for a Vector Dark Matter (VDM) in the early universe in which its mass may partially arise from such mechanism in the hidden sector. We calculate the ratio of VDM that may enter the bubble for various bubble wall velocities as well as various nucleation temperatures that produce the measured dark matter relic

Marco Eilers, Malte Schwerhoff, Peter Müller

Most automated program verifiers for separation logic use either symbolic execution or verification condition generation to extract proof obligations, which are then handed over to an SMT solver. Existing verification algorithms are designed to be sound, but differ in performance and completeness. These characteristics may also depend on the programs and pro

Vitezslav Kala, Om Prakash

We study the universality of forms of degrees greater than 2 over rings of integers of totally real number fields. We show that such universal forms always exist, but cannot be characterized by any variant of the 290-Theorem of Bhargava-Hanke.

Tinh Son Luong, Thanh-Thien Le, Linh Ngo Van, Thien Huu Nguyen

Large language models (LLMs) have become integral to our professional workflows and daily lives. Nevertheless, these machine companions of ours have a critical flaw: the huge amount of data which endows them with vast and diverse knowledge, also exposes them to the inevitable toxicity and bias. While most LLMs incorporate defense mechanisms to prevent the ge

Mohammad Hasan Ahmadilivani, Seyedhamidreza Mousavi, Jaan Raik, Masoud Daneshtalab

Convolutional Neural Networks (CNNs) have become integral in safety-critical applications, thus raising concerns about their fault tolerance. Conventional hardware-dependent fault tolerance methods, such as Triple Modular Redundancy (TMR), are computationally expensive, imposing a remarkable overhead on CNNs. Whereas fault tolerance techniques can be applied

Chiara Guidolin, Emmanuelle Rio, Roberto Cerbino, Anniina Salonen

We investigate the ultraslow structural relaxation of ageing foams with rheologically-tunable continuous phases. We probe the bubble dynamics associated with pressure-driven foam coarsening using differential dynamic microscopy, which allows characterizing the sample dynamics in the reciprocal space with imaging experiments. Similar to other out-of-equilibri

Bo Lu, Kazuki Maeda, Hiroyuki Ito, Keiji Yada

We study the Josephson effect in a superconductor/altermagnet/superconductor (S/AM/S) junction. We find anomalous phenomena including $0$-$\pi$ transition as well as multi-nodal current-phase relations. Similar to $d$-wave superconductor, $d$-wave altermagnet can support $\varphi$ junction where free energy minima locate neither $\varphi=0$ nor $\pm \pi$ wit

Carlos Alberto Durigan Junior, André Taue Saito, Daniel Reed Bergmann, Nuno Manoel Martins Dias Fouto

The main objective of this paper is to Identify which macroe conomic factors and industrial indexes influenced the total Brazilian banking spread between March 2011 and March 2015. This paper considers subclassification of industrial activities in Brazil. Monthly time series data were used in multivariate linear regression models using Eviews (7.0). Eighteen

Salma Elomari-Kessab, Guillaume Maitrier, Julius Bonart, Jean-Philippe Bouchaud

Understanding the micro-dynamics of asset prices in modern electronic order books is crucial for investors and regulators. In this paper, we use an order by order Eurostoxx database spanning over 3 years to analyze the joint dynamics of prices and order flow. In order to alleviate various problems caused by high-frequency noise, we propose a double coarse-gr

David Martínez-Crespo, Cesare Tronci

We consider the dynamics of interacting quantum and classical systems in the Heisenberg representation. Unlike the usual construction in standard quantum mechanics, mixed quantum-classical systems involve the interplay of unitary operators acting on the quantum observables and the Lagrangian trajectories sweeping the classical degrees of freedom. This interp

Rupert L. Frank, Fedor Sukochev, Dmitriy Zanin

We study trace ideal properties of the commutators $[(-\Delta)^{\frac{\epsilon}{2}},M_f]$ of a power of the Laplacian with the multiplication operator by a function $f$ on $\mathbb R^d$. For a certain range of $\epsilon\in\mathbb R$, we show that this commutator belongs to the weak Schatten class $\mathcal L_{\frac d{1-\epsilon},\infty}$ if and only if the d

Nuno Costa Dias, Maurice de Gosson, João Nuno Prata

We derive Heisenberg uncertainty principles for pairs of Linear Canonical Transforms of a given function, by resorting to the fact that these transforms are just metaplectic operators associated with free symplectic matrices. The results obtained synthesize and generalize previous results found in the literature, because they apply to all signals, in arbitra

Ziyao Xu, Houfeng Wang

Compositional generalization is an important ability of language models and has many different manifestations. For data-to-text generation, previous research on this ability is limited to a single manifestation called Systematicity and lacks consideration of large language models (LLMs), which cannot fully cover practical application scenarios. In this work,

Amin Ghodousian, Sara Zal

In this paper, we investigate nonlinear optimization problems whose constraints are defined as fuzzy relational equations (FRE) with max-min composition. Since the feasible solution set of the FRE is often a non-convex set and the resolution of the FREs is an NP-hard problem, conventional nonlinear approaches may involve high computational complexity. Based

Gal Morgenstern, Tirza Routtenberg

This paper investigates the recovery of a node-domain sparse graph signal from the output of a graph filter. This problem, which is often referred to as the identification of the source of a diffused sparse graph signal, is seminal in the field of graph signal processing (GSP). Sparse graph signals can be used in the modeling of a variety of real-world appli

Naeimeh Omidvar, Mahdieh Ahmadi, Seyed Mohammad Hosseini

We study joint optimization of service placement, request routing, and CPU sizing in a cooperative MEC system. The problem is considered from the perspective of the service provider (SP), which delivers heterogeneous MEC-enabled delay-sensitive services, and needs to pay for the used resources to the mobile network operators and the cloud provider, while ear

Haoyue Song, Jiacheng Wang, Liansheng Wang

Federated Learning (FL) has gained attention for addressing data scarcity and privacy concerns. While parallel FL algorithms like FedAvg exhibit remarkable performance, they face challenges in scenarios with diverse network speeds and concerns about centralized control, especially in multi-institutional collaborations like the medical domain. Serial FL prese

B. G. Konopelchenko, G. Ortenzi

Hodograph equations for the n-dimensional Euler equations with the constant pressure and external force linear in velocity are presented. They provide us with solutions of the Euler in implicit form and information on existence or absence of gradient catastrophes. It is shown that in even dimensions the constructed solutions are periodic in time for particul

Harris Bin Munawar, Nikolaos Misirlis

In the era of exponential technology growth, one unexpected guest has claimed a seat in classrooms worldwide, Artificial Intelligence. Generative AI, such as ChatGPT, promises a revolution in education, yet it arrives with a double-edged sword. Its potential for personalized learning is offset by issues of cheating, inaccuracies, and educators struggling to

Hoshang Sahib, Laurent Schlur, Kumara Cordero, Nathalie Viart

Following the discovery of superconductivity in hole-doped NdNiO$_2$ infinite-layer thin films, extensive research has been conducted particularly to compare these materials with cuprates. Superconductivity has also been observed in nickelate thin films with other rare-earth elements like Pr and La, but not in their bulk forms, suggesting a critical role for

Ran Yan, Minda Ma

This study explores the historical emission patterns and decarbonization efforts of China and India, the largest emerging emitters in residential building operations. Using a novel carbon intensity model and structural decomposition approach, it assesses the operational decarbonization progress over the past two decades. Results show significant decarbonizat

Gaurav M. Vaidya, Simon B. Jäger, Athreya Shankar

We study the phenomenon of quantum synchronization from the viewpoint of quantum metrology. By interpreting quantum self-sustained oscillators as dissipative quantum sensors, we develop a framework to characterize several aspects of quantum synchronization. We show that the quantum Fisher information (QFI) serves as a system-agnostic measure of quantum synch

V. A. Babkin, V. M. Baryshnikov, M. G. Buryakov, A. S. Burdyko

Identification of particles generated by ion collisions in the NICA collider is one of the basic functions of the Multipurpose Detector (MPD). The main means of identification in MPD are the time-of-flight system (TOF) and the time-projection chamber (TPC). The article considers the optimization of the algorithms of particles identification by these systems.

Chuang Liu, Zelin Yao, Xueqi Ma, Mukun Chen

Graph Masked Autoencoders (GMAEs) have emerged as a notable self-supervised learning approach for graph-structured data. Existing GMAE models primarily focus on reconstructing node-level information, categorizing them as single-scale GMAEs. This methodology, while effective in certain contexts, tends to overlook the complex hierarchical structures inherent i

Ada Canet, Jacobo Varela, Ana I. Gómez De Castro

Stellar rotation at early ages plays a crucial role in the survival of primordial atmospheres around Earth-mass exoplanets. Earth-like planets orbiting fast-rotating stars may undergo complete photoevaporation within the first few hundred Myr driven by the enhanced stellar XUV radiation, while planets orbiting slow-rotating stars are expected to experience d

Tianfu Wang, Liwei Deng, Chao Wang, Jianxun Lian

As the non-fungible token (NFT) market flourishes, price prediction emerges as a pivotal direction for investors gaining valuable insight to maximize returns. However, existing works suffer from a lack of practical definitions and standardized evaluations, limiting their practical application. Moreover, the influence of users' multi-behaviour transactions th