May 2023 arXiv papers — page 149

Yutao Tang, Yicheng Zhang, Ruonan Li, Xinghu Wang

This paper aims at distributed algorithms for solving a system of linear algebraic equations. Different from most existing formulations for this problem, we assume that the local data at each node is not accurately measured but subject to some disturbances. To be specific, the local measurement consists of two parts: a nominal value and a multiple sinusoidal

Benjamin Gallusser, Max Stieber, Martin Weigert

State-of-the-art object detection and segmentation methods for microscopy images rely on supervised machine learning, which requires laborious manual annotation of training data. Here we present a self-supervised method based on time arrow prediction pre-training that learns dense image representations from raw, unlabeled live-cell microscopy videos. Our met

Serena Criscuoli, Sergey Marchenko, Matthew DeLand, Debi Choudhary

Precise, high-cadence, long-term records of stellar spectral variability at different temporal scales lead to better understanding of a wide variety of phenomena including stellar atmospheres and dynamos, convective motions, and rotational periods. Here, we investigate the variability of solar Balmer lines (H-$\alpha$, -$\beta$, -$\gamma$, -$\delta$) observe

Andrea Loi, Giovanni Placini, Michela Zedda

We study immersions of Sasakian manifolds into finite and infinite dimensional Sasakian space forms. After proving Calabi's rigidity results in the Sasakian setting, we characterise all homogeneous Sasakian manifolds which admit a (local) Sasakian immersion into a nonelliptic Sasakian space form. Moreover, we give a characterisation of homogeneous Sasakian m

Sigrid Dimce, Anatolij Zubow, Alireza Bayesteh, Giuseppe Caire

Channel splicing is a rather new and very promising concept. It allows to realize a wideband channel sounder by combining multiple narrow-band measurements. Among others, channel splicing is a sparse sensing techniques suggested for use in joint communication and sensing (JCAS), channel measurements and prediction using cheap hardware that cannot measure wid

Saul Youssef

We propose an axiomatic foundation of mathematics based on the finite sequence as the foundational concept, rather than based on logic and set, as in set theory, or based on type as in dependent type theories. Finite sequences lead to a concept of pure data, which is used to represent all mathematical objects. As an axiomatic system, the foundation has only

Marvin Xhemrishi, Johan Östman, Antonia Wachter-Zeh, Alexandre Graell i Amat

We propose FedGT, a novel framework for identifying malicious clients in federated learning with secure aggregation. Inspired by group testing, the framework leverages overlapping groups of clients to identify the presence of malicious clients in the groups via a decoding operation. The clients identified as malicious are then removed from the model training

Rawwad Alhejaili, Motaz Alfarraj, Hamzah Luqman, Ali Al-Shaikhi

The use of deep unfolding networks in compressive sensing (CS) has seen wide success as they provide both simplicity and interpretability. However, since most deep unfolding networks are iterative, this incurs significant redundancies in the network. In this work, we propose a novel recursion-based framework to enhance the efficiency of deep unfolding models

V. Picouet, S. Arnouts, E. Le Floch, T. Moutard

Star formation rate functions (SFRFs) give an instantaneous view of the distribution of star formation rates (SFRs) in galaxies at different epochs. They are a complementary and more stringent test for models than the galaxy stellar mass function, which gives an integrated view of the past star formation activity. However, the exploration of SFRFs has been l

Shiyi Qi, Yuanhang Yang, Shuzhzeng Gao, Cuiyun Gao

With the development of deep learning (DL), DL-based code search models have achieved state-of-the-art performance and have been widely used by developers during software development. However, the security issue, e.g., recommending vulnerable code, has not received sufficient attention, which will bring potential harm to software development. Poisoning-based

Hang-Xi Li, Daryoush Shiri, Sandoko Kosen, Marcus Rommel

In superconducting quantum processors, the predictability of device parameters is of increasing importance as many labs scale up their systems to larger sizes in a 3D-integrated architecture. In particular, the properties of superconducting resonators must be controlled well to ensure high-fidelity multiplexed readout of qubits. Here we present a method, bas

Sebastian Bahamonde, Jorge Gigante Valcarcel

We present a complete algebraic classification for the curvature tensor in Weyl-Cartan geometry, by applying methods of eigenvalues and principal null directions on its irreducible decomposition under the group of global Lorentz transformations, thus providing a full invariant characterisation of all the possible algebraic types of the torsion and nonmetrici

W. A. van Wijngaarden

The effect of changing greenhouse gas concentrations on climate was examined. Calculations of the climate sensitivity, the warming of the Earth due to a doubling of atmospheric CO2, are discussed. Ontario was responsible for 0.35% of the world's CO2 emissions in 2019 and this amount was 20% lower than in 2005. The predictions of Global Climate Models (GCM) w

Farhin Farhad Riya, Shahinul Hoque, Md Saif Hassan Onim, Edward Michaud

The widespread adoption of Image Processing has propelled Object Recognition (OR) models into essential roles across various applications, demonstrating the power of AI and enabling crucial services. Among the applications, traffic sign recognition stands out as a popular research topic, given its critical significance in the development of autonomous vehicl

Takami Tohyama, Kazuya Shinjo, Shigetoshi Sota, Seiji Yunoki

Photoinduced nonequilibrium states in the Mott insulators reflect the fundamental nature of competition between itinerancy and localization of the charge degrees of freedom. The spin degrees of freedom will also contribute to the competition in a different manner depending on lattice geometry. We investigate pulse-excited optical responses of a half-filled t

K. Jenni, S. Kunkemöller, A. Tewari, R. A. Ewings

The magnetic excitations in ferromagnetic SrRuO$_3$ were studied by inelastic neutron scattering combining experiments on triple-axis and time-of-flight spectrometers with and without polarization analysis. A quadratic spin-wave dispersion with an anisotropy gap describes the low-energy low-temperature response. The magnon dispersion extends to at least 35 m

Chaoya Jiang, Rui Xie, Wei Ye, Jinan Sun

Cross-modal contrastive learning in vision language pretraining (VLP) faces the challenge of (partial) false negatives. In this paper, we study this problem from the perspective of Mutual Information (MI) optimization. It is common sense that InfoNCE loss used in contrastive learning will maximize the lower bound of MI between anchors and their positives, wh

Boje Deforce, Bart Baesens, Jan Diels, Estefanía Serral Asensio

IoT data is a central element in the successful digital transformation of agriculture. However, IoT data comes with its own set of challenges. E.g., the risk of data contamination due to rogue sensors. A sensor is considered rogue when it provides incorrect measurements over time. To ensure correct analytical results, an essential preprocessing step when wor

Francesco Tarantelli, Ettore Vicari

We address the out-of-equilibrium dynamics arising from quantum-quench (QQ) protocols (instantaneous changes of the Hamiltonian parameters) in many-body systems within their quantum critical regime and in contact with thermal baths, homogeneously coupled to the systems. We consider two classes of QQ protocols. One of them uses the thermal bath to prepare the

Shuo Ma, Genyue Liu, Pai Peng, Bichen Zhang

The development of scalable, high-fidelity qubits is a key challenge in quantum information science. Neutral atom qubits have progressed rapidly in recent years, demonstrating programmable processors and quantum simulators with scaling to hundreds of atoms. Exploring new atomic species, such as alkaline earth atoms, or combining multiple species can provide

Zoltán M. Balogh, Tamás Titkos, Dániel Virosztek

This paper aims to study isometries of the $1$-Wasserstein space $\mathcal{W}_1(\mathbf{G})$ over Carnot groups endowed with horizontally strictly convex norms. Well-known examples of horizontally strictly convex norms on Carnot groups are the Heisenberg group $\mathbb{H}^n$ endowed with the Heisenberg-Kor\'anyi norm, or with the Naor-Lee norm; and $H$-type

M. Batelaan, K. U. Can, R. Horsley, Y. Nakamura

The Feynman--Hellmann approach to computing matrix elements in lattice QCD by first adding a perturbing operator to the action is described using the transition matrix and the Dyson expansion formalism. This perturbs the energies in the two-point baryon correlation function, from which the matrix element can be obtained. In particular at leading order in the

Katia Jodogne-Del Litto, Guillaume-Alexandre Bilodeau

Predicting a binary mask for an object is more accurate but also more computationally expensive than a bounding box. Polygonal masks as developed in CenterPoly can be a good compromise. In this paper, we improve over CenterPoly by enhancing the classical regression L1 loss with a novel region-based loss and a novel order loss, as well as with a new training

Jakob Roth, Philipp Arras, Martin Reinecke, Richard A. Perley

Context: Radio interferometers measure frequency components of the sky brightness, modulated by the gains of the individual radio antennas. Due to atmospheric turbulence and variations in the operational conditions of the antennas these gains fluctuate. Thereby the gains do not only depend on time but also on the spatial direction on the sky. To recover high

Jiaojiao Liu, Hongtao Liang, Jinfu Li, Brian B. Laird

The growing trend towards engineering interfacial complexion (or phase) transitions has been seen in the grain boundary and solid surface systems.Meanwhile, little attention has been paid to the chemically heterogeneous solid/liquid interfaces. In this work, novel in-plane multi-interfacial states coexist within the Cu(111)/Pb(l) interface at a temperature j

Lior Gishboliner, Nick Kushnir, Asaf Shapira

A distance estimator for a graph property $\mathcal{P}$ is an algorithm that given $G$ and $\alpha, \varepsilon >0$ distinguishes between the case that $G$ is $(\alpha-\varepsilon)$-close to $\mathcal{P}$ and the case that $G$ is $\alpha$-far from $\mathcal{P}$ (in edit distance). We say that $\mathcal{P}$ is estimable if it has a distance estimator whose qu

Piotr Rybak

Recently, open-domain question answering systems have begun to rely heavily on annotated datasets to train neural passage retrievers. However, manually annotating such datasets is both difficult and time-consuming, which limits their availability for less popular languages. In this work, we experiment with several methods for automatically collecting weakly

Samarth Kalluraya, George J. Pappas, Yiannis Kantaros

Several task and motion planning algorithms have been proposed recently to design paths for mobile robot teams with collaborative high-level missions specified using formal languages, such as Linear Temporal Logic (LTL). However, the designed paths often lack reactivity to failures of robot capabilities (e.g., sensing, mobility, or manipulation) that can occ

Hou Shengren, Pedro P. Vergara, Edgar Mauricio Salazar Duque, Peter Palensky

The massive integration of renewable-based distributed energy resources (DERs) inherently increases the energy system's complexity, especially when it comes to defining its operational schedule. Deep reinforcement learning (DRL) algorithms arise as a promising solution due to their data-driven and model-free features. However, current DRL algorithms fail to

Hlel Missaoui

In this paper, we study the following nonlinear Dirac-Bopp-Podolsky system \begin{equation*} \left\lbrace \begin{array}{rll} \displaystyle{ -i\sum_{k=1}^{3}\alpha_{k}\partial_{k}u+[V(x)+q]\beta u+wu-\phi u}&=f(x,u), \ \ &\text{in}\ \mathbb{R}^3, \ & \ & \ -\triangle\phi+a^2\triangle^2 \phi&=4\pi \vert u\vert^2,\ \ & \text{in}\ \mathbb{R}^3, \end{array} \righ

Yun Zeng, Deren Han, Yansheng Su, Jiaxin Xie

The stochastic heavy ball momentum (SHBM) method has gained considerable popularity as a scalable approach for solving large-scale optimization problems. However, one limitation of this method is its reliance on prior knowledge of certain problem parameters, such as singular values of a matrix. In this paper, we propose an adaptive variant of the SHBM method

Agnijo Banerjee

A family $\mathcal{F} \subset \mathcal{P}(n)$ is $r$-wise $k$-intersecting if $|A_1 \cap \dots \cap A_r| \geq k$ for any $A_1, \dots, A_r \in \mathcal{F}$. It is easily seen that if $\mathcal{F}$ is $r$-wise $k$-intersecting for $r \geq 2$, $k \geq 1$ then $|\mathcal{F}| \leq 2^{n-1}$. The problem of determining the maximal size of a family $\mathcal{F}$ tha

Jue Hou, Anisia Katinskaia, Anh-Duc Vu, Roman Yangarber

Language modeling is a fundamental task in natural language processing, which has been thoroughly explored with various architectures and hyperparameters. However, few studies focus on the effect of sub-word segmentation on the performance of language models (LMs). In this paper, we compare GPT and BERT models trained with the statistical segmentation algori

Anurag Gupta, Vikram Krishnamurthy

What are the optimal times for an Internet of Things (IoT) device to act as a blockchain miner? The aim is to minimize the energy consumed by low-power IoT devices that log their data into a secure (tamper-proof) distributed ledger. We formulate a multiple stopping time Bayesian sequential detection problem to address energy-efficient blockchain mining for I

L. Verra, S. Wyler, T. Nechaeva, J. Pucek

Self-modulation is a beam-plasma instability that is useful to drive large-amplitude wakefields with bunches much longer than the plasma skin depth. We present experimental results showing that, when increasing the ratio between the initial transverse size of the bunch and the plasma skin depth, the instability occurs later along the bunch, or not at all, ov

Elyakim Zlotnick, Boulat Bash, Uzi Pereg

We consider entanglement-assisted communication over the qubit depolarizing channel under the security requirement of covert communication, where not only the information is kept secret, but the transmission itself must be concealed from detection by an adversary. Previous work showed that $O(\sqrt{n})$ information bits can be reliably and covertly transmitt

C. Quesne

It is shown that rational extensions of the isotropic Dunkl oscillator in the plane can be obtained by adding some terms either to the radial equation or to the angular one obtained in the polar coordinates approach. In the former case, the isotropic harmonic oscillator is replaced by an isotropic anharmonic one, whose wavefunctions are expressed in terms of

Joshua Fass, Forrest York, Matthew Wittmann, Joseph Kaus

We describe a method that focuses sampling effort on a user-defined selection of a large system, which can lead to substantial decreases in computational effort by speeding up the calculation of nonbonded interactions. A naive approach can lead to incorrect sampling if the selection depends on the configuration in a way that is not accounted for. We avoid th

Aleksandra Chrabrowa, Tsimur Hadeliya, Dariusz Kajtoch, Robert Mroczkowski

Novel intent discovery automates the process of grouping similar messages (questions) to identify previously unknown intents. However, current research focuses on publicly available datasets which have only the question field and significantly differ from real-life datasets. This paper proposes methods to improve the intent discovery pipeline deployed in a l

Mehran Jalali Farahani, Christian Saemann, Martin Wolf

Semi-classically equivalent field theories are related by a quasi-isomorphism between their underlying $L_\infty$-algebras, but such a quasi-isomorphism is not necessarily a homotopy transfer. We demonstrate that all quasi-isomorphisms can be lifted to spans of $L_\infty$-algebras in which the quasi-isomorphic $L_\infty$-algebras are obtained from a correspo

Vincent Ouazan-Reboul, Ramin Golestanian, Jaime Agudo-Canalejo

Particles that are catalytically-active and chemotactic can interact through the concentration fields upon which they act, which in turn may lead to wide-scale spatial self-organization. When these active particles interact through several fields, these interactions gain an additional structure, which can result in new forms of collective behaviour. Here, we

Fernando Gonzalez, Zhijing Jin, Bernhard Schölkopf, Tom Hope

With the recent advances in natural language processing (NLP), a vast number of applications have emerged across various use cases. Among the plethora of NLP applications, many academic researchers are motivated to do work that has a positive social impact, in line with the recent initiatives of NLP for Social Good (NLP4SG). However, it is not always obvious

Florian Beißer, Dennis Haag, Rafael Ballabriga, Rolf Behrens

Eye lens dosimetry has been an important field of research in the last decade. Dose measurements with a prototype of an active personal eye lens dosemeter based on the Dosepix detector are presented. The personal dose equivalent at $3\,$mm depth of soft tissue, $H_\text{p}(3)$, was measured in the center front of a water-filled cylinder phantom with a height

Florent Bonnet

The study of partial differential equations (PDE) through the framework of deep learning emerged a few years ago leading to the impressive approximations of simple dynamics. Graph neural networks (GNN) turned out to be very useful in those tasks by allowing the treatment of unstructured data often encountered in the field of numerical resolutions of PDE. How

Lize Bian, Yong He, Jianghui Han

Let (M1,F1) and (M2,F2) be two Finsler manifolds. The twisted product Finsler metric of F1 and F2 is a Finsler metric F = (F1^2+ f^2F2^2)^1/2 endowed on the product manifold M1 * M2, where f is a positive smooth function on M1 * M2. In this paper, Landsberg curvature and mean Landsberg curvature of the twisted product Finsler metric are derived. Necessary an

Dong-Xu Chen, Yunlong Wang, Feiran Wang, Jun-Long Zhao

High-dimensional quantum systems offer many advantages over low-dimensional quantum systems. Meanwhile, unitary transformations on quantum states are important parts in various quantum information tasks, whereas they become technically infeasible as the dimensionality increases. The photonic orbital angular momentum (OAM), which is inherit in the transverse

Valeriano Antunes de Oliveira

In this work, optimality conditions and classical results from duality theory are derived for continuous-time linear optimization problems with inequality constraints. The optimality conditions are given in the Karush-Kuhn-Tucker form. Weak and strong duality properties, as well as, the complementary slackness theorem are established. A result concerning the

Nisha Huang, Yuxin Zhang, Weiming Dong

Large-scale text-to-video diffusion models have demonstrated an exceptional ability to synthesize diverse videos. However, due to the lack of extensive text-to-video datasets and the necessary computational resources for training, directly applying these models for video stylization remains difficult. Also, given that the noise addition process on the input

Amin Farajzadeh, Animesh Yadav, Halim Yanikomeroglu

In the ever-expanding landscape of the IoT, managing the intricate network of interconnected devices presents a fundamental challenge. This leads us to ask: "What if we invite the IoT devices to collaboratively participate in real-time network management and IoT data-handling decisions?" This inquiry forms the foundation of our innovative approach, addressin

Gholamhossein Haghighat, Reza Jafari, Hamzeh Khanpour, Mojtaba Mohammadi Najafabadi

In this paper, we use the charged-current Higgs boson production process at future electron-proton colliders, $e^-p \to H j \nu_e$, with the subsequent decay of the Higgs boson into a $b\bar{b}$ pair, to probe the Standard Model effective field theory with dimension-six operators involving the Higgs boson and the bottom quark. The study is performed for two

Kris Cao

This paper aims to benchmark recent progress in language understanding models that output contextualised representations at the character level. Many such modelling architectures and methods to train those architectures have been proposed, but it is currently unclear what the relative contributions of the architecture vs. the pretraining objective are to fin

Carlos O. Lousto, R. Missel, E. Zubieta, S. del Palacio

The Pulsar Monitoring in Argentina (PuMA) is a collaboration between the Argentine Institute for Radioastronomy (IAR) and the Rochester Institute of Technology (RIT) that since 2017 has been observing southern sky pulsars with high cadence using the two restored IAR antennas in the L-Band (1400MHz). We briefly review the first set of results of this program

Stefano Bonzio, Michele Pra Baldi

Bochvar algebras consist of the quasivariety BCA playing the role of equivalent algebraic semantics for Bochvar (external) logic, a logical formalism introduced by Bochvar in the realm of (weak) Kleene logics. In this paper, we provide an algebraic investigation of the structure of Bochvar algebras. In particular, we prove a representation theorem based on P

Chaochao Zheng, Luping Wang, Bin Liu

This technical report presents our Restormer-Plus approach, which was submitted to the GT-RAIN Challenge (CVPR 2023 UG$^2$+ Track 3). Details regarding the challenge are available at http://cvpr2023.ug2challenge.org/track3.html. Restormer-Plus outperformed all other submitted solutions in terms of peak signal-to-noise ratio (PSNR), and ranked 4th in terms of

B. Ruşen Argun, Antonia Statt

Nano- and microplastics are a growing threat for the environment, especially in aqueous habitats. For assessing the influence on the ecosystem and possible solution strategies, it is necessary to investigate the fate of microplastics (MP) in the environment. MPs are typically surrounded by natural organic matter, which can cause them to aggregate. However, t

Ben S. Southworth, HyeongKae Park, Svetlana Tokareva, Marc Charest

Radiation hydrodynamics are a challenging multiscale and multiphysics set of equations. To capture the relevant physics of interest, one typically must time step on the hydrodynamics timescale, making explicit integration the obvious choice. On the other hand, the coupled radiation equations have a scaling such that implicit integration is effectively necess

Marc Windsheimer, Fabian Brand, André Kaup

Most learning-based image compression methods lack efficiency for high image quality due to their non-invertible design. The decoding function of the frequently applied compressive autoencoder architecture is only an approximated inverse of the encoding transform. This issue can be resolved by using invertible latent variable models, which allow a perfect re

Noémie Ehstand, Reik V. Donner, Cristóbal López, Emilio Hernández-García

Functional networks are powerful tools to study statistical interdependency structures in spatially extended or multivariable systems. They have been used to get insights into the dynamics of complex systems in various areas of science. In particular, percolation properties of correlation networks have been employed to identify early warning signals of criti

Mauro Spreafico

We study the global analytic properties of a space $X$ with a horn type singularity. In particular, we introduce some de Rham complex of square integrable forms and we describe its homology and the spectral properties of the associated Hodge Laplace operator. All this is applied to produce a suitable description of the analytic torsion of $X$ and to prove an

Mario Suaza-Medina, F. Javier Zarazaga-Soria, Jorge Pinilla-Lopez, Francisco J. López-Pellicer

Spain is the third-largest producer of pork meat in the world, and many farms in several regions depend on the evolution of this market. However, the current pricing system is unfair, as some actors have better market information than others. In this context, historical pricing is an easy-to-find and affordable data source that can help all agents to be bett

Hung-Hsu Chou, Holger Rauhut, Rachel Ward

Overparameterized models may have many interpolating solutions; implicit regularization refers to the hidden preference of a particular optimization method towards a certain interpolating solution among the many. A by now established line of work has shown that (stochastic) gradient descent tends to have an implicit bias towards low rank and/or sparse soluti

Federico Gasparotto, Stefan Weinzierl, Xiaofeng Xu

We report on an exact calculation of lattice correlation functions on a finite four-dimensional lattice with either Euclidean or Minkowskian signature. The lattice correlation functions are calculated by the method of differential equations. This method can be used for Euclidean and Minkowskian signature alike. The lattice correlation functions have a power

Laurence Barker

The pointed fusion system of a block is a structure consisting of the fusions and relative multiplicities between the local pointed groups associated with a maximal Brauer pair. We show that the pointed fusion system is preserved by splendid Morita equivalences and part of the pointed fusion system is preserved by splendid stable equivalences of Morita type.

Jiazhi Guan, Zhanwang Zhang, Hang Zhou, Tianshu Hu

Despite recent advances in syncing lip movements with any audio waves, current methods still struggle to balance generation quality and the model's generalization ability. Previous studies either require long-term data for training or produce a similar movement pattern on all subjects with low quality. In this paper, we propose StyleSync, an effective framew

Tibor Kiss

In this paper we determine the solutions $(\varphi,f_1,f_2)$ of the Pexider functional equation \[\varphi\Big(\frac{x+y}2\Big)\big(f_1(x)-f_2(y)\big)=0,\qquad (x,y)\in I_1\times I_2,\] where $I_1$ and $I_2$ are nonempty open subintervals. Special cases of the above equation regularly arise in problems with two-variable means. We show that, under a rather wea

Heitor Guimarães, Arthur Pimentel, Anderson Avila, Mehdi Rezagholizadeh

Unsupervised speech models are becoming ubiquitous in the speech and machine learning communities. Upstream models are responsible for learning meaningful representations from raw audio. Later, these representations serve as input to downstream models to solve a number of tasks, such as keyword spotting or emotion recognition. As edge speech applications sta

Julian D. Schiller, Matthias A. Müller

We propose a time-discounted integral variant of incremental input/output-to-state stability (i-iIOSS) together with an equivalent Lyapunov function characterization. Continuity of the i-iIOSS Lyapunov function is ensured if the system satisfies a certain continuity assumption involving the Osgood condition. We show that the proposed i-iIOSS notion is a nece

B. L. Alterman, Mihir I. Desai, Maher A. Dayeh, G. M. Mason

We report on the annual variation of quiet-time suprathermal ion composition for C through Fe using Advanced Composition Explorer (ACE)/Ultra-Low Energy Isotope Spectrometer (ULEIS) data over the energy range 0.3 MeV/nuc to 1.28 MeV/nuc from 1998 through 2019, covering solar cycle 23's rising phase through Solar Cycle 24's declining phase. Our findings are (

Hannah Och, Shabhrish Reddy Uddehal, Tilo Strutz, André Kaup

Screen content images typically contain a mix of natural and synthetic image parts. Synthetic sections usually are comprised of uniformly colored areas and repeating colors and patterns. In the VVC standard, these properties are exploited using Intra Block Copy and Palette Mode. In this paper, we show that pixel-wise lossless coding can outperform lossy VVC

Huner Fanchiotti, Carlos A. García Canal, Vicente Vento

We study the energy loss of excited monopolium in an atomic medium. We perform a classical calculation in line with a similar calculation performed for charged particles which leads in the non relativistic limit to the Bethe-Bloch formula except for the density dependence of the medium, which we do not consider in this paper. Our result shows that for maxima

Maxime De Sousa, Aurélien Barrau, Killian Martineau

Group field theory has shown to be a promising framework to derive cosmological predictions from full quantum gravity. In this brief note, we revisit the background dynamics when interaction terms are taken into account and conclude that, although the bounce is clearly robust, providing a geometrical explanation for inflation seems to be very difficult. We c

Alkis S. Tersenov

The Dirichlet problem is considered both for degenerate and singular inhomogeneous quasilinear parabolic equations. We prove the existence of a solution $u$ such that $u_t$ belongs to $L_{\infty}$. The $L_{\infty}$ estimate of $u_t$ is obtained by introducing a new time variable.

Oscar Fuentealba, Marc Henneaux, Cédric Troessaert

The asymptotic symmetry algebra of four-dimensional Einstein gravity in the asymptotically flat context has been shown recently to be the direct sum of the Poincar\'e algebra and of an infinite-dimensional abelian algebra (with central charge) that includes the Bondi-Metzner-Sachs supertranslations. This result, obtained within the Hamiltonian formalism, yie

Cristina-Liliana Pripoae, Iulia-Elena Hirica, Gabriel-Teodor Pripoae, Vasile Preda

By replacing the internal energy with the free energy, as coordinates in a "space of observables", we slightly modify (the known three) non-holonomic geometrizations and show that the coefficients of the curvature tensor field, of the Ricci tensor field and the scalar curvature function still remain rational functions. In addition, we define and study a new

A. Di Giovanni, F. Arneodo, A. Al Qasim, H. Alblooshi

The Rapid Acquisition Atmospheric Detector (RAAD), onboard the LIGHT-1 3U CubeSat, detects photons between hard X-rays and soft gamma-rays, in order to identify and characterize Terrestrial Gamma Ray Flashes (TGFs). Three detector configurations are tested, making use of Cerium Bromide and Lanthanum BromoChloride scintillating crystals coupled to photomultip

Hailan Ma, Zhenhong Sun, Daoyi Dong, Chunlin Chen

Quantum state tomography (QST) is the process of reconstructing the state of a quantum system (mathematically described as a density matrix) through a series of different measurements, which can be solved by learning a parameterized function to translate experimentally measured statistics into physical density matrices. However, the specific structure of qua

Andrea Burns, Krishna Srinivasan, Joshua Ainslie, Geoff Brown

Webpages have been a rich resource for language and vision-language tasks. Yet only pieces of webpages are kept: image-caption pairs, long text articles, or raw HTML, never all in one place. Webpage tasks have resultingly received little attention and structured image-text data underused. To study multimodal webpage understanding, we introduce the Wikipedia

Álvaro Suárez, Arturo C. Marti, Kristina Zuza, Jenaro Guisasola

Textbooks play a fundamental role in teaching and learning in school science classrooms. In this paper we investigate the presentation of the nature of the electromagnetic field in a dozen of the world's most popular introductory university physics textbooks. We analyse, from an epistemologically based teaching approach, the didactic treatment of the electro

Raisa Fairooz Meem, Khandaker Tabin Hasan

Critical clinical decision points in haematology are influenced by the requirement of bone marrow cytology for a haematological diagnosis. Bone marrow cytology, however, is restricted to reference facilities with expertise, and linked to inter-observer variability which requires a long time to process that could result in a delayed or inaccurate diagnosis, l

Wout Merbis, Manlio de Domenico

The statistical field theory of information dynamics on complex networks concerns the dynamical evolution of large classes of models of complex systems. Previous work has focused on networks where nodes carry an information field, which describes the internal state of the node, and its dynamical evolution. In this work, we propose a more general mathematical

Wout Merbis, Manlio de Domenico

The information implicitly represented in the state of physical systems allows one to analyze them with analytical techniques from statistical mechanics and information theory. In the case of complex networks such techniques are inspired by quantum statistical physics and have been used to analyze biophysical systems, from virus-host protein-protein interact

Prabal Adhikari, Inga Strümke

We study three-flavor QCD in a uniform magnetic field using chiral perturbation theory ($\chi$PT). We construct the vacuum free energy density, quark condensate shifts induced by the magnetic field and the renormalized magnetization to $\mathcal{O}(p^6)$ in the chiral expansion. We find that the calculation of the free energy is greatly simplified by cancell

Heinrich Freistuhler

Ruggeri's hyperbolic Navier-Stokes equations are shown to possess, for any equilibrium state, smooth solutions in arbitrarily small $L^\infty$ neigborhoods of the reference state that in finite time cease to be differentiable.

Qiqi Dai, Yee Hui Lee, Hai-Han Sun, Genevieve Ow

The reconstruction of the 3D permittivity map from ground-penetrating radar (GPR) data is of great importance for mapping subsurface environments and inspecting underground structural integrity. Traditional iterative 3D reconstruction algorithms suffer from strong non-linearity, ill-posedness, and high computational cost. To tackle these issues, a 3D deep le

David Stojanovski, Uxio Hermida, Pablo Lamata, Arian Beqiri

We propose a novel pipeline for the generation of synthetic ultrasound images via Denoising Diffusion Probabilistic Models (DDPMs) guided by cardiac semantic label maps. We show that these synthetic images can serve as a viable substitute for real data in the training of deep-learning models for ultrasound image analysis tasks such as cardiac segmentation. T

Amanda Issac, Alireza Ebrahimi, Javad Mohammadpour Velni, Glen Rains

In this study, we propose a big data pipeline for cotton bloom detection using a Lambda architecture, which enables real-time and batch processing of data. Our proposed approach leverages Azure resources such as Data Factory, Event Grids, Rest APIs, and Databricks. This work is the first to develop and demonstrate the implementation of such a pipeline for pl

Luca Erculiani, Andrea Bontempelli, Andrea Passerini, Fausto Giunchiglia

We are interested in aligning how people think about objects and what machines perceive, meaning by this the fact that object recognition, as performed by a machine, should follow a process which resembles that followed by humans when thinking of an object associated with a certain concept. The ultimate goal is to build systems which can meaningfully interac

Iris de Gélis, Sébastien Lefèvre, Thomas Corpetti

In a constant evolving world, change detection is of prime importance to keep updated maps. To better sense areas with complex geometry (urban areas in particular), considering 3D data appears to be an interesting alternative to classical 2D images. In this context, 3D point clouds (PCs), whether obtained through LiDAR or photogrammetric techniques, provide

Vrunda Gadesha, Keyur D Joshi, Shefali Naik

'Mahabharata' is the most popular among many Indian pieces of literature referred to in many domains for completely different purposes. This text itself is having various dimension and aspects which is useful for the human being in their personal life and professional life. This Indian Epic is originally written in the Sanskrit Language. Now in the era of Na

C. Echeverria-Arrondo, H. Raebiger, J. Perez-Conde, C. Gomez-Polo

The magneto-optical properties of titanium dioxide systems are related to the presence of impurity states in the band gap due to oxygen vacancies. To understand about the interplay between localized electrons and structural distortions at the vacancy sites and the magneto-optical properties, we employ a self-interaction corrected density functional theory me

Charmaine Barker, Dimitar Kazakov

The presence of specific linguistic signals particular to a certain sub-group can become highly salient to language models during training. In automated decision-making settings, this may lead to biased outcomes when models rely on cues that correlate with protected characteristics. We investigate whether prompting ChatGPT to rewrite text using simplificatio

Yiming Jiang, Jinlan Liu, Dongpo Xu, Danilo P. Mandic

Adam-type algorithms have become a preferred choice for optimisation in the deep learning setting, however, despite success, their convergence is still not well understood. To this end, we introduce a unified framework for Adam-type algorithms (called UAdam). This is equipped with a general form of the second-order moment, which makes it possible to include

Alessio Cecconi, Luca Barbaro, Claudio Di Ciccio, Arik Senderovich

Declarative process specifications define the behavior of processes by means of rules based on Linear Temporal Logic on Finite Traces (LTLf). In a mining context, these specifications are inferred from, and checked on, multi-sets of runs recorded by information systems (namely, event logs). To this end, being able to gauge the degree to which process data co

Moritz Laupichler, Peter Sanders

We introduce KaRRi, an improved algorithm for scheduling a fleet of shared vehicles as it is used by services like UberXShare and Lyft Shared. We speed up the basic online algorithm that looks for all possible insertions of a new customer into a set of existing routes, we generalize the objective function, and efficiently support a large number of possible p

H. H. Li, J. G. Li, N. Michel, W. Zuo

Although they are part of the lightest nuclei, the hydrogen isotopes are not well understood both experimentally and theoretically. Indeed, besides deuteron and triton, all known hydrogen isotopes are resonances of complex structure. Even more elusive is 7H, which may have been observed experimentally and has been claimed to be a narrow resonance. Neverthele

G. Karapetyan

The electroexcitation of the ${\cal N}^*(1440)$ Roper resonance, which defines the first radially excited state of the nucleon, is examined within the soft-wall AdS/QCD model. Such excited Fock states are characterized by the leading three-quark component, which determines the main properties of Roper resonance. The differential configurational entropy (DCE)

Andreas Mueller

Modern geometric approaches to analytical mechanics rest on a bundle structure of the configuration space. The connection on this bundle allows for an intrinsic splitting of the reduced Euler-Lagrange equations. Hamel's equations, on the other hand, provide a universal approach to non-holonomic mechanics in local coordinates. The link between Hamel's formula

Yixuan Weng, Bin Li, Fei Xia, Minjun Zhu

The medical conversational question answering (CQA) system aims at providing a series of professional medical services to improve the efficiency of medical care. Despite the success of large language models (LLMs) in complex reasoning tasks in various fields, such as mathematics, logic, and commonsense QA, they still need to improve with the increased comple

Sushil Gorai, Golam Mostafa Mondal

In this paper, we first prove that the totally real discs lying in certain Levi flat hypersurfaces are polynomially convex. As applications we prove that the totally real discs lying in the boundary of certain polynomial polyhedra are polynomially convex. We also provide an if and only if condition for polynomial convexity of totally real discs lying in the

Xinrui Li, Zhenjun Dong, Yong Zeng, Shi Jin

In this paper, we investigate the near-field modelling and analyze the beam focusing pattern for modular extremely large-scale array (XL-array) communications. As modular XL-array is physically and electrically large in general, the accurate characterization of amplitude and phase variations across its array elements requires the non-uniform spherical wave (