May 2024 arXiv papers — page 128

Ali Forootani, Harshit Kapadia, Sridhar Chellappa, Pawan Goyal

Partial differential equation parameter estimation is a mathematical and computational process used to estimate the unknown parameters in a partial differential equation model from observational data. This paper employs a greedy sampling approach based on the Discrete Empirical Interpolation Method to identify the most informative samples in a dataset associ

Pablo L. Saldanha

The gauge invariance of the Aharonov-Bohm (AB) effect with a quantum treatment for the electromagnetic field is demonstrated. We provide an exact solution for the electromagnetic ground energy due to the interaction of the quantum electromagnetic field with the classical charges and currents that act as sources of the potentials in a classical description, i

Taesoo Song, Qi Zhou

Assuming that the number densities of heavy flavor in hadron gas and in QGP are same at $T_c$, we obtain the effective mass of heavy quark at $T_c$ from the comparison with the hadron resonance gas model which well describes particle yield in heavy-ion collisions. We find that charm quark mass at vanishing baryon chemical potential is around 1.8 GeV which is

James M. Cline

I review recent developments in the field of dark photons-here taken to be U(1) gauge bosons with mass less than the Z-including both kinetically mixed vectors and those that couple to anomaly-free U(1)'s. Distinctions between Higgs and Stueckelberg masses are highlighted, with discussion of swampland constraints, UV completions, and new experimental search

Sunyuan Qiang, Yanyan Liang, Jun Wan, Du Zhang

Class-incremental learning (CIL) has emerged as a means to learn new classes incrementally without catastrophic forgetting of previous classes. Recently, CIL has undergone a paradigm shift towards dynamic architectures due to their superior performance. However, these models are still limited by the following aspects: (i) Data augmentation (DA), which are ti

Valérie Berthé, Olivier Carton, Nicolas Chevallier, Wolfgang Steiner

In 1980, R. Tijdeman provided an on-line algorithm that generates sequences over a finite alphabet with minimal discrepancy, that is, such that the occurrence of each letter optimally tracks its frequency. In this article, we define discrete dynamical systems generating these sequences. The dynamical systems are defined as exchanges of polytopal pieces, yiel

Abhishek, Paul Stevenson, Yue Shi, Esra Yüksel

The Sky3D code has been widely used to describe nuclear ground states, collective vibrational excitations, and heavy-ion collisions. The approach is based on Skyrme forces or related energy density functionals. The static and dynamic equations are solved on a three-dimensional grid, and pairing is been implemented in the BCS approximation. This updated versi

Hyunmo Yang, Seungjun Oh, Eunbyung Park

Learning-based Neural Video Codecs (NVCs) have emerged as a compelling alternative to standard video codecs, demonstrating promising performance, and simple and easily maintainable pipelines. However, NVCs often fall short of compression performance and occasionally exhibit poor generalization capability due to inference-only compression scheme and their dep

Constantia Alexandrou, Simone Bacchio, Martha Constantinou, Joseph Delmar

We present the full decomposition of the momentum fraction carried by quarks and gluons in the pion and the kaon. We employ three gauge ensembles generated with $N_f=2+1+1$ Wilson twisted-mass clover-improved fermions at the physical quark masses. For both mesons we perform a continuum extrapolation directly at the physical pion mass, which allows us to dete

Juergen Mangler, Ronny Seiger, Janik-Vasily Benzin, Joscha Grüger

The IoT and Business Process Management (BPM) communities co-exist in many shared application domains, such as manufacturing and healthcare. The IoT community has a strong focus on hardware, connectivity and data; the BPM community focuses mainly on finding, controlling, and enhancing the structured interactions among the IoT devices in processes. While the

Arian Beckmann, Tilman Stephani, Felix Klotzsche, Yonghao Chen

Since the advent of Deepfakes in digital media, the development of robust and reliable detection mechanism is urgently called for. In this study, we explore a novel approach to Deepfake detection by utilizing electroencephalography (EEG) measured from the neural processing of a human participant who viewed and categorized Deepfake stimuli from the FaceForens

Karin Johansson, Raquel Breejon Robinson, Jon Back, Sarah Lynne Bowman

Live action roleplay (larp) has a wide range of applications, and can be relevant in relation to HCI. While there has been research about larp in relation to topics such as embodied interaction, playfulness and futuring published in HCI venues since the early 2000s, there is not yet a compilation of this knowledge. In this paper, we synthesise knowledge abou

Matteo Bonvini, Edward H. Kennedy, Oliver Dukes, Sivaraman Balakrishnan

We study the problem of constructing an estimator of the average treatment effect (ATE) with observational data. The celebrated doubly-robust, augmented-IPW (AIPW) estimator generally requires consistent estimation of both nuisance functions for standard root-n inference, and moreover that the product of the errors of the nuisances should shrink at a rate fa

Zhangni Pu, Xiaozhuo Zhang, Jiang Hu, Zhidong Bai

In this paper, we investigate the asymptotic behaviors of the extreme eigenvectors in a general spiked covariance matrix, where the dimension and sample size increase proportionally. We eliminate the restrictive assumption of the block diagonal structure in the population covariance matrix. Moreover, there is no requirement for the spiked eigenvalues and the

Janusz Uchmański

In this work, an individual-based model of forest insect outbreaks is presented. The results obtained show that the outbreak is an emerging feature of the system. It is a common product of the characteristics of insects, the environment in which the insects live, and the way insects behave in it. The outbreak dynamics is an effect of scale. In a sufficiently

John Ellis, Malcolm Fairbairn, Juan Urrutia, Ville Vaskonen

Many galaxies contain supermassive black holes (SMBHs), whose formation and history raise many puzzles. Pulsar timing arrays have recently discovered a low-frequency cosmological "hum" of gravitational waves that may be emitted by SMBH binary systems, and the JWST and other telescopes have discovered an unexpectedly large population of high-redshift SMBHs. W

Hiba Dakdouk, Mohamed Sana, Benoit Denis

Radio localization and sensing are anticipated to play a crucial role in enhancing radio resource management in future networks. In this work, we focus on millimeter-wave communications, which are highly vulnerable to blockages, leading to severe attenuation and performance degradation. In a previous work, we proposed a novel mechanism that senses the radio

Dimitrios Tyrovolas, Dimitrios Bozanis, Sotiris A. Tegos, Vasilis K. Papanikolaou

The evolution toward sixth-generation (6G) wireless networks has introduced programmable wireless environments (PWEs) and reconfigurable intelligent surfaces (RISs) as transformative elements for achieving near-deterministic wireless communications. However, the enhanced capabilities of RISs within PWEs, especially as we move toward more complex electromagne

Yiannis Charalambous, Edoardo Manino, Lucas C. Cordeiro

The next generation of AI systems requires strong safety guarantees. This report looks at the software implementation of neural networks and related memory safety properties, including NULL pointer deference, out-of-bound access, double-free, and memory leaks. Our goal is to detect these vulnerabilities, and automatically repair them with the help of large l

J. Aaron Mendoza-Rodarte, Katarzyna Gas, Manuel Herrera-Zaldívar, Detlef Hommel

Diluted magnetic semiconductors (DMS) have attracted significant attention for their potential in spintronic applications. Particularly, magnetically-doped GaN is highly attractive due to its high relevance for the CMOS industry and the possibility of developing advanced spintronic devices which are fully compatible with the current industrial procedures. De

Akansha Tyagi, Sachin Vashistha

This article aims to present the $AT$ algorithm, a novel two-step iterative approach for approximating fixed points of weak contractions within complete normed linear spaces. The article demonstrates the convergence of $AT$ algorithm towards fixed points of weak contractions. Notably, it establishes the algorithm's strong convergence properties, highlighting

Bing Liu, Furan Xie, Li Chai

In this paper, we study the privacy-preserving distributed optimization problem, aiming to prevent attackers from stealing the private information of agents. For this purpose, we propose a novel privacy-preserving algorithm based on the Advanced Encryption Standard (AES), which is both secure and computationally efficient. By appropriately constructing the u

P. Marchand, A. Coutens, J. Scigliuto, F. Cruz-Sáenz de Miera

Episodic accretion in protostars leads to luminosity outbursts that end up heating their surroundings. This rise in temperature pushes the snow lines back, enabling the desorption of chemical species from dust grain surfaces, which may significantly alter the chemical history of the accreting envelope. However, a limited number of extensive chemical surveys

Zhe Shen, Sen Lu, Xiong Xiong

Topological quasiparticles, including skyrmions and merons, are topological textures with sophisticated vectorial structures that can be used for high-density information storage, precision metrology, position sensing, etc. Here, we realized the optical generation and continuous transformation of plasmonic field skyrmions. We generated the isolated N\'eel-ty

Satadeep Bhattacharjee, Seung-Cheol Lee

Recent developments in the magnetization dynamics in spin textures, particularly skyrmions, offer promising new directions for magnetic storage technologies and spintronics. Skyrmions, characterized by their topological protection and efficient mobility at low current density, are increasingly recognized for their potential applications in next-generation lo

Colin Watson, Adam W Parnaby, Ahmed Kharrufa

There is a significant overlap between people who are supported by income-related social welfare benefits, often in precarious situations, and those who experience greater digital exclusion. We report on a study of claimants using the UK's Universal Credit online welfare benefit system designed as, and still, "digital by default". Through data collection inv

AmeerAli Khan, Qusai Ramadan, Cong Yang, Zeyd Boukhers

This paper aims to tackle the challenge posed by the increasing integration of software tools in research across various disciplines by investigating the application of Falcon-7b for the detection and classification of software mentions within scholarly texts. Specifically, the study focuses on solving Subtask I of the Software Mention Detection in Scholarly

Pengyuan Liu, Zhaodong Xu, Zhiqiang Sheng

We present a subspace method based on neural networks for solving the partial differential equation in weak form with high accuracy. The basic idea of our method is to use some functions based on neural networks as base functions to span a subspace, then find an approximate solution in this subspace. Training base functions and finding an approximate solutio

Yanchao Jiang, Pierluigi Poggiolini

We formulated a closed-form EGN model for nonlinear interference in ultra-wideband optical systems with arbitrary Raman amplification. This model enhanced the CISCO-POLITO-CFM5 performance by introducing a novel contribution attributed to the backward Raman amplification. It can handle the frequency-dependent fiber parameters and inter-channel stimulated Ram

A. Jaries, S. Nikas, A. Kankainen, T. Eronen

We have performed high-precision mass measurements of neutron-rich rare-earth Tb, Dy and Ho isotopes using the Phase-Imaging Ion-Cyclotron-Resonance technique at the JYFLTRAP double Penning trap. We report on the first experimentally determined mass values for $^{169}$Tb, $^{170}$Dy and $^{171}$Dy, as well as the first high-precision mass measurements of $^{

Xinxin Li, Zhen Deng, Yang Jiang, Chunhua Du

Quantum confinement is recognized to be an inherent property in low-dimensional structures. Traditionally it is believed that the carriers trapped within the well cannot escape due to the discrete energy levels. However, our previous research has revealed efficient carrier escape in low-dimensional structures, contradicting this conventional understanding. I

Hristu Culetu

A regular form of the Schwarzschild geometry is proposed. It is more suitable for application in microphysics because the source mass comes out both as a Schwarzschild radius and the Compton wavelength of the mass $m$. The Komar energy equals $mc^{2}$ in the classical situation ($\hbar = 0$).

Eleni Nisioti, Erwan Plantec, Milton Montero, Joachim Winther Pedersen

In biological evolution complex neural structures grow from a handful of cellular ingredients. As genomes in nature are bounded in size, this complexity is achieved by a growth process where cells communicate locally to decide whether to differentiate, proliferate and connect with other cells. This self-organisation is hypothesized to play an important part

D. Alfaya, L. A. Calvo, A. Martínez de Guinea, J. Rodrigo

We classify all solution triples with Fibonacci components to the equation $a^2+b^2+c^2=3abc+m,$ for positive $m$. We show that for $m=2$ they are precisely $(1,F(b),F(b+2))$, with even $b$; for $m=21$, there exist exactly two Fibonacci solutions $(1,2,8)$ and $(2,2,13)$ and for any other $m$ there exists at most one Fibonacci solution, which, in case it exi

Reinaldo Francener, Victor P. Goncalves, Diego R. Gratieri

Considering that the study of neutrino-nucleus interactions with incident neutrino energy ranges in the GeV-TeV range is feasible at the Large Hadron Collider, we investigate in this paper the degree of polarization ${\cal{P}}$ of the (anti) tau lepton produced in (anti) tau neutrino - tungsten interactions. We estimate the differential cross-sections and th

Agnieszka Majczyna, Jerzy Madej, Agata Różańska, Mirosław Należyty

Rapidly rotating neutron stars are similar to highly flattened ellipsoids. Observed spectra of flattened stars must exhibit effects of non spherical shape and the gravitational darkening. We examined in detail the influence of both effects on the observed central energies and profiles of lines of highly ionized iron, FeXXV and FeXXVI. We note that the gravit

Alexander E. Black, Niklas Lütjeharms, Raman Sanyal

Although simplices are trivial from a linear optimization standpoint, the simplex algorithm can exhibit quite complex behavior. In this paper we study the behavior of max-slope pivot rules on (products of) simplices and describe the associated pivot rule polytopes. For simplices, the pivot rule polytopes are combinatorially isomorphic to associahedra. To pro

Tolga Wagner, Hüseyin Çelik, Dirk Berger, Ines Häusler

Interference Gating or iGate is a unique method for ultrafast time-resolved electron holography in a transmission electron microscope enabling a spatiotemporal resolution in the nm and ns regime with a minimal technological effort. Here, iGate is used for the first image-based investigation of the local dynamics of the projected electric potential in the are

A. A. Saharian

We investigate the combined effects of spatial curvature and topology on the properties of the vacuum state for a charged scalar field localized on rotationally symmetric 2D curved tubes. For a general spatial geometry and for quasiperiodicity condition with a general phase, the representation of the Hadamard function is provided where the topological contri

Emilio Olivastri, Alberto Pretto

In SLAM (Simultaneous localization and mapping) problems, Pose Graph Optimization (PGO) is a technique to refine an initial estimate of a set of poses (positions and orientations) from a set of pairwise relative measurements. The optimization procedure can be negatively affected even by a single outlier measurement, with possible catastrophic and meaningless

Odysseas S. Chlapanis, Ion Androutsopoulos, Dimitrios Galanis

The SemEval task on Argument Reasoning in Civil Procedure is challenging in that it requires understanding legal concepts and inferring complex arguments. Currently, most Large Language Models (LLM) excelling in the legal realm are principally purposed for classification tasks, hence their reasoning rationale is subject to contention. The approach we advocat

Tolga Wagner, Tore Niermann, Felix Urban, Michael Lehmann

The interference gating is a novel method for robust time-resolved electron holographic measurements by directly switching the interference. Here, a new arrangement is presented in which a biprism in the condenser aperture as a fast electric phase shifter is used to control the interference pattern. High-frequency stimulation of the electric phase shifter in

Jiahui Luo, Zhaojie Xu, Zhenhu Jin, Mixia Wang

Due to their compact size and exceptional sensitivity at room temperature, magnetoresistance (MR) sensors have garnered considerable interest in numerous fields, particularly in the detection of weak magnetic signals in biological systems. The magnetrodes, integrating MR sensors with needle-shaped Si-based substrates, are designed to be inserted into the bra

Ziyang Zhu

We extend Latimer and MacDuffee's theorem to a general commutative domain and apply this result to study similarity of matrices over integral rings of number fields. We also conjecture similarity over discrete valuation rings can be descent by a finite covering and verify this conjecture for $2\times2$ matrices and separable characteristic polynomials.

Martin Hoferichter

Calculations based on the analytic properties of the required matrix elements allow for a wide range of applications constraining the hadronic contributions to the anomalous magnetic moment of the muon $a_\mu=(g-2)_\mu/2$, both hadronic vacuum polarization (HVP) and hadronic light-by-light (HLbL) scattering. Here, we discuss such recent applications, includi

Jian-Jian Miao, Wei-Qiang Chen

Motivated by the order fractionalization in Kitaev-Kondo model, we propose an exactly solvable spin-charge ladder model to study the order fractionalization with discrete symmetry. The spin-charge ladder is composed of a spin chain and a superconducting wire coupled via an Ising-type interaction, and we obtain the exact solution in the flat band limit. The e

Daqian Shao, Ashkan Soleymani, Francesco Quinzan, Marta Kwiatkowska

A common issue in learning decision-making policies in data-rich settings is spurious correlations in the offline dataset, which can be caused by hidden confounders. Instrumental variable (IV) regression, which utilises a key unconfounded variable known as the instrument, is a standard technique for learning causal relationships between confounded action, ou

Agne Knietaite, Adam Allsebrook, Anton Minkov, Adam Tomaszewski

Compositionality in language models presents a problem when processing idiomatic expressions, as their meaning often cannot be directly derived from their individual parts. Although fine-tuning and other optimization strategies can be used to improve representations of idiomatic expressions, this depends on the availability of relevant data. We present the N

Svetlana Petrenko, Karen M. Page

The rapid and complex patterning of biosilica in diatom frustules is of great interest in nanotechnology, although it remains incompletely understood. Specific organic molecules, including long-chain polyamines, silaffins, and silacidins are essential in this process. The molecular structure of the synthesized polyamines significantly affects the quantity, s

Y Monitar Singh, Mayengbam Kishan Singh, N Nimai Singh

A randomly generated complex symmetric matrix using Adaptive Monte Carlo method, is taken as a general form of Majorana neutrino mass matrix, which is diagonalized by the use of eigenvectors. We extract all the neutrino oscillation parameters i.e. two mass-squared differences ($\Delta m_{21}^2$ and $\Delta m_{32}^2$ ), three mixing angles ($\theta_{12}$, $\t

Lidiia L. Chinarova, Ivan L. Andronov

The primary sourcebook for developments based on the data of the world components "Theory of Intellectualities and Mathematical Statistics" (TIMS) collections of the Department of Mathematics, Physics and Astronomy of Odessky National Maritime University. Presented lecture material on basic axioms, theorems and formulas of statistical divisions and character

Ildar Rakhmatulin

The article presents an accessible route into the field of neuroscience through the JNEEG device. This device allows converting the Jetson Nano board into a brain-computer interface, making it easy to measure EEG, EMG, and ECG signals with 8 channels. With Jetson Nano is possible use deep learning for real-time signal processing and feature extraction from E

Danshi Wang, Yidi Wang, Xiaotian Jiang, Yao Zhang

Since the advent of GPT, large language models (LLMs) have brought about revolutionary advancements in all walks of life. As a superior natural language processing (NLP) technology, LLMs have consistently achieved state-of-the-art performance on numerous areas. However, LLMs are considered to be general-purpose models for NLP tasks, which may encounter chall

Cheng Li, Gudrid Moortgat-Pick

We study possible CP-violation effects of the 125 GeV Higgs to $Z$ boson coupling at the 250 GeV ILC with transverse and longitudinal beam polarisation via the process $e^+ e^- \rightarrow HZ \rightarrow H \mu^-\mu^+$. We explore the azimuthal angular distribution of the muon pair from the $Z$ boson decay, and constructe CP-odd observables sensitive to CP-vi

Qinfeng Zhu, Yuan Fang, Yuanzhi Cai, Cheng Chen

Deep learning methods, especially Convolutional Neural Networks (CNN) and Vision Transformer (ViT), are frequently employed to perform semantic segmentation of high-resolution remotely sensed images. However, CNNs are constrained by their restricted receptive fields, while ViTs face challenges due to their quadratic complexity. Recently, the Mamba model, fea

Felix Strnad, Kieran M. R. Hunt, Niklas Boers, Bedartha Goswami

The Indian Summer Monsoon (ISM) and the West African Monsoon (WAM) are dominant drivers of boreal summer precipitation variability in tropical and subtropical regions. Although the regional precipitation dynamics in these two regions have been extensively studied, the intraseasonal interactions between the ISM and WAM remain poorly understood. Here, we emplo

Sara R. Cabo, Sergio Luis Suarez Gomez, Laura Bonavera, Maria Luisa Sanchez

Cherenkov-type particle detectors or scintillators use as a fundamental element photomultiplier tubes, whose efficiency decreases when subjected to the Earth's magnetic field. This work develops a geomagnetic field compensation system based on coils for large scale cylindrical detectors. The effect of different parameters such as the size of the detector, th

Adamu Lawan, Juhua Pu, Haruna Yunusa, Jawad Muhammad

Aspect-Based Sentiment Analysis (ABSA) is increasingly crucial in Natural Language Processing (NLP) for applications such as customer feedback analysis and product recommendation systems. ABSA goes beyond traditional sentiment analysis by extracting sentiments related to specific aspects mentioned in the text; existing attention-based models often need help

Ulrich Krähmer, Myriam Mahaman

This article considers cuspidal curves whose coordinate rings are numerical semigroup algebras. Using a general result about descent of Hopf algebroid structures, their rings of differential operators are shown to be cocommutative and conilpotent left Hopf algebroids. If the semigroups are symmetric so that the curves are Gorenstein, they are full Hopf algeb

Han Li, Isla Barnard, Tyler Halliwell, Xinyu Zhang

Transcranial low-intensity focused ultrasound can deliver energy to the brain in a minimally invasive manner for neuromodulation applications. However, continuous sonication through the skull introduces significant wave interactions, complicating precise energy delivery to the target. We present a comprehensive examination of intracranial acoustic fields gen

Seonwoo Kim

This article is divided into two parts. In the first part, we study the hierarchical phenomenon of metastability in low-temperature lattice models in the most general setting. Given an abstract dynamical system governed by a Hamiltonian function, we prove that there exists a hierarchical decomposition of the collection of stable plateaux in the system into m

Mian Zou, Baosheng Yu, Yibing Zhan, Siwei Lyu

In recent years, deep learning has greatly streamlined the process of manipulating photographic face images. Aware of the potential dangers, researchers have developed various tools to spot these counterfeits. Yet, none asks the fundamental question: What digital manipulations make a real photographic face image fake, while others do not? In this paper, we p

Anri Patron, Ayush Prasad, Hoang Phuc Hau Luu, Kai Puolamäki

A fundamental problem in supervised learning is to find a good set of features or distance measures. If the new set of features is of lower dimensionality and can be obtained by a simple transformation of the original data, they can make the model understandable, reduce overfitting, and even help to detect distribution drift. We propose a supervised dimensio

Minh N. Dao, Tan Nhat Pham, Phan Thanh Tung

In this paper, we consider a class of structured nonconvex nonsmooth optimization problems whose objective function is the sum of three nonconvex functions, one of which is expressed in a difference-of-convex (DC) form. This problem class covers several important structures in the literature including the sum of three functions and the general DC program. We

Sheng-Chen Bai, Shi-Ju Ran

Replicating chaotic characteristics of non-linear dynamics by machine learning (ML) has recently drawn wide attentions. In this work, we propose that a ML model, trained to predict the state one-step-ahead from several latest historic states, can accurately replicate the bifurcation diagram and the Lyapunov exponents of discrete dynamic systems. The characte

Zong-Wei Hong, Yen-Yang Hung, Chu-Song Chen

In this work, we introduce a novel method for calculating the 6DoF pose of an object using a single RGB-D image. Unlike existing methods that either directly predict objects' poses or rely on sparse keypoints for pose recovery, our approach addresses this challenging task using dense correspondence, i.e., we regress the object coordinates for each visible pi

Pedro De la Torre Luque, Shyam Balaji, Pierluca Carenza, Leonardo Mastrototaro

The $\gamma$ ray emission originating from in-flight annihilation (IA) of positrons is a powerful observable for constraining high-energy positron production from exotic sources. By comparing diffuse $\gamma$ ray observations of INTEGRAL, COMPTEL and EGRET to theoretical predictions, we set the most stringent constraints on electrophilic feebly interacting p

Yury Kurochkin, Marios Papadovasilakis, Anton Trushechkin, Rodrigo Piera

In prepare-and-measure quantum key distribution systems, careful preparation of quantum states within the transmitter device is a significant driver of both complexity and cost. Moreover, the security guarantees of such systems rest on the correct operation of high speed quantum random number generators (QRNGs) and the high-fidelity modulation of weak optica

Tobias Dornheim, Panagiotis Tolias, Fotios Kalkavouras, Zhandos Moldabekov

We present the first quasi-exact \textit{ab initio} path integral Monte Carlo (PIMC) results for the dynamic local field correction $\widetilde{G}(\mathbf{q},z_l;r_s,\Theta)$ in the imaginary Matsubara frequency domain, focusing on the strongly coupled finite temperature uniform electron gas. These allow us to investigate the impact of dynamic exchange--corr

Chunlei Li

Since the introduction of the Kolmogorov complexity of binary sequences in the 1960s, there have been significant advancements in the topic of complexity measures for randomness assessment, which are of fundamental importance in theoretical computer science and of practical interest in cryptography. This survey reviews notable research from the past four dec

K. Akhila, Ranjeev Misra, Savithri H. Ezhikode, K. Jeena

We present the results from a long term X-ray analysis of Mrk 279 during the period 2018-2020. We use data from multiple missions - AstroSat, NuSTAR and XMM-Newton, for the purpose. The X-ray spectrum can be modelled as a double Comptonisation along with the presence of neutral Fe K${\alpha}$ line emission, at all epochs. We determined the source's X-ray flu

Andrea Piergentili, Beatrice Savoldi, Matteo Negri, Luisa Bentivogli

Machine translation (MT) models are known to suffer from gender bias, especially when translating into languages with extensive gendered morphology. Accordingly, they still fall short in using gender-inclusive language, also representative of non-binary identities. In this paper, we look at gender-inclusive neomorphemes, neologistic elements that avoid binar

Amlan Chakraborty, Anirban Das, Subinoy Das, Shiv K. Sethi

As one of the fundamental unknowns of our Universe, the mass of dark matter remains to be a topic of great interest. We consider the possibility of a time-variation of the dark matter mass. We study the cosmological constraints on a model where the dark matter mass transitions from zero to a finite value in the early Universe. In this model, the matter power

Daniella Bar-Lev, Tuvi Etzion, Eitan Yaakobi, Zohar Yakhini

Enzymatic DNA labeling is a powerful tool with applications in biochemistry, molecular biology, biotechnology, medical science, and genomic research. This paper contributes to the evolving field of DNA-based data storage by presenting a formal framework for modeling DNA labeling in strings, specifically tailored for data storage purposes. Our approach involv

Pukar Baral, Chen Zhao, Michele Esposito, Weihua Zhou

Purpose of Review Recently, machine learning has developed rapidly in the field of medicine, playing an important role in disease diagnosis. Our aim of this paper is to provide an overview of the advancements in machine learning techniques applied to invasive coronary angiography (ICA) for segmentation of coronary arteries and quantitative evaluation like fr

Hyeju Shin, Ibrahim Aliyu, Abubakar Isah, Jinsul Kim

With the emergence and proliferation of new forms of large-scale services such as smart homes, virtual reality/augmented reality, the increasingly complex networks are raising concerns about significant operational costs. As a result, the need for network management automation is emphasized, and Digital Twin Networks (DTN) technology is expected to become th

Jeanne Bourgeois, Maxime Lesur, Guillermo Cuerva Lazaro, Yusuke Kosuga

In magnetized plasmas, a radial gradient of parallel velocity, where parallel refers to the direction of magnetic field, can destabilise an electrostatic mode called Parallel Velocity Gradient (PVG). The theory of PVG has been mainly developed assuming a single species of ions. Here, the role of impurities is investigated based on a linear, local analysis, i

Marco Abbadini, Paolo Aglianò, Stefano Fioravanti

MV-monoids are algebras $\langle A,\vee,\wedge, \oplus,\odot, 0,1\rangle$ where $\langle A, \vee, \wedge, 0, 1\rangle$ is a bounded distributive lattice, both $\langle A, \oplus, 0 \rangle$ and $\langle A, \odot, 1\rangle$ are commutative monoids, and some further connecting axioms are satisfied. Every MV-algebra in the signature $\{\oplus,\neg,0\}$ is term

Sasindu Wijeratne, Rajgopal Kannan, Viktor Prasanna

Sparse Matricized Tensor Times Khatri-Rao Product (spMTTKRP) is the bottleneck kernel of sparse tensor decomposition. In this work, we propose a GPU-based algorithm design to address the key challenges in accelerating spMTTKRP computation, including (1) eliminating global atomic operations across GPU thread blocks, (2) avoiding the intermediate values being

Anisia Katinskaia, Roman Yangarber

This paper investigates the application of GPT-3.5 for Grammatical Error Correction (GEC) in multiple languages in several settings: zero-shot GEC, fine-tuning for GEC, and using GPT-3.5 to re-rank correction hypotheses generated by other GEC models. In the zero-shot setting, we conduct automatic evaluations of the corrections proposed by GPT-3.5 using sever

Kenza Amara, Rita Sevastjanova, Mennatallah El-Assady

The necessity for interpretability in natural language processing (NLP) has risen alongside the growing prominence of large language models. Among the myriad tasks within NLP, text generation stands out as a primary objective of autoregressive models. The NLP community has begun to take a keen interest in gaining a deeper understanding of text generation, le

Serge Massar, Bortolo Matteo Mognetti

Equilibrium propagation is a recently introduced method to use and train artificial neural networks in which the network is at the minimum (more generally extremum) of an energy functional. Equilibrium propagation has shown good performance on a number of benchmark tasks. Here we extend equilibrium propagation in two directions. First we show that there is a

Francesco Marchiori, Alessandro Brighente, Mauro Conti

Autonomous driving is a research direction that has gained enormous traction in the last few years thanks to advancements in Artificial Intelligence (AI). Depending on the level of independence from the human driver, several studies show that Autonomous Vehicles (AVs) can reduce the number of on-road crashes and decrease overall fuel emissions by improving e

Oliver Baumann, Durgesh Nandini, Anderson Rossanez, Mirco Schoenfeld

Traditional recommendation proposals, including content-based and collaborative filtering, usually focus on similarity between items or users. Existing approaches lack ways of introducing unexpectedness into recommendations, prioritizing globally popular items over exposing users to unforeseen items. This investigation aims to design and evaluate a novel lay

Yujian Chen, Joshua Lanier, John K. -H. Quah

A goodness-of-fit index measures the consistency of consumption data with a given model of utility-maximization. We show that for the class of well-behaved (i.e., continuous and increasing) utility functions there is no goodness-of-fit index that is continuous and accurate, where the latter means that a perfect score is obtained if and only if a dataset can

Zhikan Wang, Zhongyao Cheng, Jiajie Xiong, Xun Xu

In recent years, the rapid advancement of deepfake technology has revolutionized content creation, lowering forgery costs while elevating quality. However, this progress brings forth pressing concerns such as infringements on individual rights, national security threats, and risks to public safety. To counter these challenges, various detection methodologies

Alexander Stangl, Nicolas Nuns, Caroline Pirovano, Kosova Kreka

The exploitation of advanced materials for novel energy, health and computing applications requires fundamental understanding of enabling physicochemical mechanisms, including ionic and electronic conductivity, defect formation processes and reaction kinetics. Therefore, access to underlying constants of functional materials via advanced but straightforward

Luigi C. Berselli, Rossano Sannipoli

In this paper we consider the 3D Euler equations and we first prove a criterion for energy conservation for weak solutions with velocity satisfying additional assumptions in fractional Sobolev spaces with respect to the space variables, balanced by proper integrability with respect to time. Next, we apply the criterion to study the energy conservation of sol

Chenghao Zhu, Nuo Chen, Yufei Gao, Yunyi Zhang

The rapid advancement of Large Language Models (LLMs) has led to the development of benchmarks that consider temporal dynamics, however, there remains a gap in understanding how well these models can generalize across temporal contexts due to the inherent dynamic nature of language and information. This paper introduces the concept of temporal generalization

Paweł Dziewulski, Joshua Lanier, John K. -H. Quah

Afriat's Theorem (1967) states that a dataset can be thought of as being generated by a consumer maximizing a continuous and increasing utility function if and only if it is free of revealed preference cycles containing a strict relation. The latter property is often known by its acronym, GARP (for generalized axiom of revealed preference). This paper survey

Jin Wang, Bingfeng Zhang, Jian Pang, Honglong Chen

Few-shot segmentation remains challenging due to the limitations of its labeling information for unseen classes. Most previous approaches rely on extracting high-level feature maps from the frozen visual encoder to compute the pixel-wise similarity as a key prior guidance for the decoder. However, such a prior representation suffers from coarse granularity a

Yantao Cao, Huanpeng Bu, Zhendong Fu, Jinkui Zhao

Here we report the successful synthesis of large single crystals of triangular frustrated PrMgAl$_{11}$O$_{19}$ using the optical floating zone technique. Single crystal X-ray diffraction measurements unveiled the presence of quenched disorder within the mirror plane, specifically $\sim$7\% of Pr ions deviating from the ideal 2\textit{d} site towards the 6\t

Byoung S. Ham

Superresolution is a unique quantum feature generated by N00N states or phase-controlled coherent photons via projection measurements in a Mach-Zehnder interferometer (MZI). Superresolution has no direct relation with supersensitivity in quantum sensing and has a potential application for the precision measurement of an unknown signal frequency. Recently, ph

YingXing Cheng, Eric Cancès, Virginie Ehrlacher, Alston J. Misquitta

In this study, we analyze various Iterative Stockholder Analysis (ISA) methods for molecular density partitioning, focusing on the numerical performance of the recently proposed Linear approximation of Iterative Stockholder Analysis model (LISA) [J. Chem. Phys. 156, 164107 (2022)]. We first provide a systematic derivation of various iterative solvers to find

Christian Arnold, Andreas Küpfer

Political scientists increasingly analyze multimodal data. However, the effective analysis of such data requires aligning information across different modalities. In our paper, we demonstrate the significance of such alignment. Informed by a systematic review of 2,703 papers, we find that political scientists typically do not align their multimodal data. Int

B. Momo, I. Predebon

We compare three different approaches to describe a magnetic island in a generic toroidal plasma: (i) perturbative, from the perspective of the equilibrium magnetic field and the related action in a variational principle formulation, (ii) again perturbative, based on the integrability of a system with a single resonant mode and the application of a canonical

Laura Guislain, Eric Bertin

Systems with a complex dynamics like glasses or models of biological evolution are often pictured in terms of complex landscapes, with a large number of possible collective states. We show on the example of a stochastic spin model with non-reciprocal and heterogeneous interactions how the complex landscape notion can be generalized far from equilibrium, wher

Andrew J. Winter, Myriam Benisty, Sean M. Andrews

Planet formation occurs over a few Myr within protoplanetary discs of dust and gas, which are often assumed to evolve in isolation. However, extended gaseous structures have been uncovered around many protoplanetary discs, suggestive of late-stage in-fall from the interstellar medium (ISM). To quantify the prevalence of late-stage in-fall, we apply an excurs

Matteo Lapucci, Pierluigi Mansueto, Davide Pucci

In this manuscript, we address continuous unconstrained multi-objective optimization problems and we discuss descent type methods for the reconstruction of the Pareto set. Specifically, we analyze the class of Front Descent methods, which generalizes the Front Steepest Descent algorithm allowing the employment of suitable, effective search directions (e.g.,

Otto C. W. Kong

Dirac talked about q-numbers versus c-numbers. Quantum observables are q-number variables that generally do not commute among themselves. He was proposing to have a generalized form of numbers as elements of a noncommutative algebra. That was Dirac's appreciation of the mathematical properties of the physical quantities as presented in Heisenberg's new quant