December 2023 arXiv papers — page 73

Chengyuan Zhu, Yiyuan Yang, Kaixiang Yang, Haifeng Zhang

The application of artificial intelligence technology has greatly enhanced and fortified the safety of energy pipelines, particularly in safeguarding against external threats. The predominant methods involve the integration of intelligent sensors to detect external vibration, enabling the identification of event types and locations, thereby replacing manual

Christian Oswald, Mate Toth, Paul Meissner, Franz Pernkopf

In automotive applications, frequency modulated continuous wave (FMCW) radar is an established technology to determine the distance, velocity and angle of objects in the vicinity of the vehicle. The quality of predictions might be seriously impaired if mutual interference between radar sensors occurs. Previous work processes data from the entire receiver arr

Zimo Hao, Xicheng Zhang

Let $d\geq 2$. In this paper, we investigate the following stochastic differential equation (SDE) in ${\mathbb R}^d$ driven by Brownian motion $$ {\rm d} X_t=b(t,X_t){\rm d} t+\sqrt{2}{\rm d} W_t, $$ where $b$ belongs to the space ${\mathbb L}_T^q \mathbf{H}_p^\alpha$ with $\alpha \in [-1, 0]$ and $p,q\in[2, \infty]$, which is a distribution-valued and diver

Ari Kouts, Lonni Besançon, Michael Sedlmair, Benjamin Lee

We propose the concept of "LSDvis": the (highly exaggerated) visual blending of situated visualisations and the real-world environment to produce data representations that resemble hallucinations. Such hallucinatory visualisations incorporate elements of the physical environment, twisting and morphing their appearance such that they become part of the visual

Dillon Z. Chen, Sylvie Thiébaux, Felipe Trevizan

We present three novel graph representations of planning tasks suitable for learning domain-independent heuristics using Graph Neural Networks (GNNs) to guide search. In particular, to mitigate the issues caused by large grounded GNNs we present the first method for learning domain-independent heuristics with only the lifted representation of a planning task

Luis Lugo, Valentin Vielzeuf

Self-supervised learning enables the training of large neural models without the need for large, labeled datasets. It has been generating breakthroughs in several fields, including computer vision, natural language processing, biology, and speech. In particular, the state-of-the-art in several speech processing applications, such as automatic speech recognit

Maxime Gheysens, Bojana Pavlica, Christian Pech, Maja Pech

We introduce the notion of echeloned spaces - an order-theoretic abstraction of metric spaces. The first step is to characterize metrizable echeloned spaces. It turns out that morphisms between metrizable echeloned spaces are uniformly continuous or have a uniformly discrete image. In particular, every automorphism of a metrizable echeloned space is uniforml

Gyula Bencédi

Event classifiers based either on the charged-particle multiplicity or on event topologies, such as spherocity and underlying event, became very useful tools to study collective-like behaviors in small collision systems. However, multiplicity-based event classifiers were shown to bias the data sample in a way that can obscure the effects of multi-parton inte

Francesco Maggi, Michael Novack, Daniel Restrepo

We introduce a diffused interface formulation of the Plateau problem, where the Allen--Cahn energy $\mathcal{AC}_\varepsilon$ is minimized under a volume constraint $v$ and a spanning condition on the level sets of the densities. We discuss two singular limits of these Allen--Cahn Plateau problems: when $\varepsilon\to 0^+$, we prove convergence to the Gauss

Cheng Xue, Ekaterina Nikonova, Peng Zhang, Jochen Renz

Novelty adaptation is the ability of an intelligent agent to adjust its behavior in response to changes in its environment. This is an important characteristic of intelligent agents, as it allows them to continue to function effectively in novel or unexpected situations, but still stands as a critical challenge for deep reinforcement learning (DRL). To tackl

Abdelhakim Aknouche, Sonia Gouveia, Manuel Scotto

A common approach to analyze count time series is to fit models based on random sum operators. As an alternative, this paper introduces time series models based on a random multiplication operator, which is simply the multiplication of a variable operand by an integer-valued random coefficient, whose mean is the constant operand. Such operation is endowed in

Jun Zhang, Shuyang Jiang, Jiangtao Feng, Lin Zheng

Efficient attentions have greatly improved the computational efficiency of Transformers. However, most existing linear attention mechanisms suffer from an \emph{efficiency degradation} problem, leading to inefficiencies in causal language modeling and hindering their application in long-range language models. This problem is more pronounced under language mo

Madhukrishna Chakraborty, Subenoy Chakraborty

The paper aims to study the geometry and physics of the Raychaudhuri equation (RE) in the background of a homogeneous and anisotropic space-time described by Kantowski-Sachs (KS) metric. Role of anisotropy/shear in the context of convergence and possible avoidance of singularity has been analyzed subject to a physically motivated constraint. Moreover, using

Xander Byrne, Oliver Shorttle, Sean Jordan, Paul B. Rimmer

As the characterization of exoplanet atmospheres proceeds, providing insights into atmospheric chemistry and composition, a key question is how much deeper into the planet we might be able to see from its atmospheric properties alone. For small planets with modest atmospheres and equilibrium temperatures, the first layer below the atmosphere will be their ro

Adil Rengim Cetingoz, Olivier Guéant

Portfolio optimization methods have evolved significantly since Markowitz introduced the mean-variance framework in 1952. While the theoretical appeal of this approach is undeniable, its practical implementation poses important challenges, primarily revolving around the intricate task of estimating expected returns. As a result, practitioners and scholars ha

Rong-Gen Cai, Mei-Ning Duan, Li Li, Fu-Guo Yang

The study of the interior of hairy black holes has received significant attention recently. This paper builds upon our recent analytical approach to investigate the internal dynamics of charged black holes with scalar hair in general spacetime dimensions. The geometries of these hairy balck holes end at a spacelike singularity. We investigate the alternation

Stefan Bender, Patrick J. Espy, Larry J. Paxton

We present an empirical model for auroral (90--150 km) electron--ion pair production rates, ionization rates for short, derived from SSUSI (Special Sensor Ultraviolet Spectrographic Imager) electron energy and flux data. Using the Fang et al., 2010 parametrization for mono-energetic electrons, and the NRLMSISE-00 neutral atmosphere model, the calculated ioni

Vincenzo Sapienza, Marco Miceli, Aya Bamba, Salvatore Orlando

Supernova (SN) 1987A is one of the best candidates to exploit the capabilities of the freshly launched XRISM satellite. This celestial object offers the unique opportunity to study the evolution of a SN into a young supernova remnant. To date, the X-ray emission has been dominated by the shocked circumstellar medium (CSM), with no shocked ejecta firmly detec

Xiao Wang, Yao Rong, Shiao Wang, Yuan Chen

Pattern recognition based on RGB-Event data is a newly arising research topic and previous works usually learn their features using CNN or Transformer. As we know, CNN captures the local features well and the cascaded self-attention mechanisms are good at extracting the long-range global relations. It is intuitive to combine them for high-performance RGB-Eve

Sovit Bhandari, Thang X. Vu, Symeon Chatzinotas

The regenerative capabilities of next-generation satellite systems offer a novel approach to design low earth orbit (LEO) satellite communication systems, enabling full flexibility in bandwidth and spot beam management, power control, and onboard data processing. These advancements allow the implementation of intelligent spatial multiplexing techniques, addr

Keyi Ju, Xiaoqi Qin, Hui Zhong, Xinyue Zhang

Quantum computing revolutionizes the way of solving complex problems and handling vast datasets, which shows great potential to accelerate the machine learning process. However, data leakage in quantum machine learning (QML) may present privacy risks. Although differential privacy (DP), which protects privacy through the injection of artificial noise, is a w

Jiajun Zhu, Yanqun Tang, Xizhang Wei, Haoran Yin

Affine frequency division multiplexing (AFDM) is a recently proposed communication waveform for time-varying channel scenarios. As a chirp-based multicarrier modulation technique it can not only satisfy the needs of multiple scenarios in future mobile communication networks but also achieve good performance in radar sensing by adjusting the built-in paramete

Piotr A. Dybczyński, Małgorzata Królikowska, Przemysław Bartczak, Edyta Podlewska-Gaca

In the latest Gaia third data release one can find extremely small proper motion components for the star HD 7977. This, together with the radial velocity measurement lead to the conclusion that this star passed very close to the Sun in the recent past. Such a very close approach of a one solar mass star must result in noticeable changes in the motion of all

Guru Prakash Arumugam, Shuo-yiin Chang, Tara N. Sainath, Rohit Prabhavalkar

ASR models often suffer from a long-form deletion problem where the model predicts sequential blanks instead of words when transcribing a lengthy audio (in the order of minutes or hours). From the perspective of a user or downstream system consuming the ASR results, this behavior can be perceived as the model "being stuck", and potentially make the product h

Angelo Mozzillo, Luca Zecchini, Luca Gagliardelli, Adeel Aslam

Data preparation is a trial-and-error process that typically involves countless iterations over the data to define the best pipeline of operators for a given task. With tabular data, practitioners often perform that burdensome activity on local machines by writing ad hoc scripts with libraries based on the Pandas dataframe API and testing them on samples of

Tianyi Li, Alessandra S. Lanotte, Michele Buzzicotti, Fabio Bonaccorso

We address the problem of data augmentation in a rotating turbulence set-up, a paradigmatic challenge in geophysical applications. The goal is to reconstruct information in two-dimensional (2D) cuts of the three-dimensional flow fields, imagining to have spatial gaps present within each 2D observed slice. We evaluate the effectiveness of different data-drive

Willian Isao Tokura, Marcelo Bezerra Barboza

In this paper we investigate gradient Yamabe solitons, either steady or shrinking, that can be isometrically immersed into space forms as hypersurfaces that admit an upper bound on the norm of their second fundamental form. Those solitons satisfying an additional condition, that could be constant mean curvature or the number of critical points of the potenti

Fabrizio Russo, Francesca Toni

Causal Structure Learning (CSL), also referred to as causal discovery, amounts to extracting causal relations among variables in data. CSL enables the estimation of causal effects from observational data alone, avoiding the need to perform real life experiments. Constraint-based CSL leverages conditional independence tests to perform causal discovery. We pro

Xingxing Yang, Jie Chen, Zaifeng Yang

Existing learning-based hyperspectral reconstruction methods show limitations in fully exploiting the information among the hyperspectral bands. As such, we propose to investigate the chromatic inter-dependencies in their respective hyperspectral embedding space. These embedded features can be fully exploited by querying the inter-channel correlations in a c

Yotam Amitai, Yael Septon, Ofra Amir

Explainable reinforcement learning (XRL) methods aim to help elucidate agent policies and decision-making processes. The majority of XRL approaches focus on local explanations, seeking to shed light on the reasons an agent acts the way it does at a specific world state. While such explanations are both useful and necessary, they typically do not portray the

E. S. Benilov

It is argued that the van der Waals force exerted by the liquid and vapor/air on the molecules escaping from one phase into the other strongly affects the characteristics of evaporation. This is shown using two distinct descriptions of the van der Waals force: the Vlasov and diffuse-interface models, each of which is applied to two distinct settings: a liqui

Julien Antoine Raemy, Adrian Demleitner

As part of the Participatory Knowledge Practices in Analogue and Digital Image Archives (PIA) research project, we have been implementing Linked Open Usable Data (LOUD) standards including the International Image Interoperability Framework (IIIF) specifications to disseminate digital objects, their related metadata and streamline our processes. We have taken

Gaojun Luo, Bocong Chen, Martianus Frederic Ezerman, San Ling

Classical locally recoverable codes (LRCs) have become indispensable in distributed storage systems. They provide efficient recovery in terms of localized errors. Quantum LRCs have very recently been introduced for their potential application in quantum data storage. In this paper, we use classical LRCs to investigate quantum LRCs. We prove that the paramete

Antonio Rafael Ramos-Rodriguez, Jose Aurelio Medina-Garrido, Jose Ruiz-Navarro

The objective of this work is to assess the influence of certain factors on the likelihood of being a Hotels and Restaurants (H&R) entrepreneur. The factors evaluated are demographic and economic variables, variables related to perceptions of the environment and personal traits, and variables measuring the individual's intellectual and social capital. The wo

Aleksandar Radic, Sam M. Lambrick, Nick A. von Jeinsen, Andrew P. Jardine

Three-dimensional mapping of surface structures is important in a wide range of biological, technological, healthcare and research applications, including taxonomy, microfluidics and fabrication. Neutral helium atom beams have been established as a sensitive probe of topography and have already enabled structural information to be obtained from delicate samp

Thijs Beurskens, Tim Ophelders, Bettina Speckmann, Kevin Verbeek

Merge trees are a common topological descriptor for data with a hierarchical component, such as terrains and scalar fields. The interleaving distance, in turn, is a common distance for comparing merge trees. However, the interleaving distance for merge trees is solely based on the hierarchical structure, and disregards any other geometrical or topological pr

Lunhao Duan, Shanshan Zhao, Nan Xue, Mingming Gong

Transformers have been recently explored for 3D point cloud understanding with impressive progress achieved. A large number of points, over 0.1 million, make the global self-attention infeasible for point cloud data. Thus, most methods propose to apply the transformer in a local region, e.g., spherical or cubic window. However, it still contains a large numb

Cheng Li, Jindong Wang, Yixuan Zhang, Kaijie Zhu

Emotion significantly impacts our daily behaviors and interactions. While recent generative AI models, such as large language models, have shown impressive performance in various tasks, it remains unclear whether they truly comprehend emotions. This paper aims to address this gap by incorporating psychological theories to gain a holistic understanding of emo

Cheng Wang, Yi Wang, Changjun Jiang

Metcalfe's Law captures the relationship between the value of a network and its scale, asserting that a network's value is directly proportional to the square of its size. Over the past four decades, various researchers have proposed different scaling laws on this subject. Remarkably, these seemingly conflicting conclusions have all been substantiated by rob

Vijay Prakash Dwivedi, Yozen Liu, Anh Tuan Luu, Xavier Bresson

Transformers have recently emerged as powerful neural networks for graph learning, showcasing state-of-the-art performance on several graph property prediction tasks. However, these results have been limited to small-scale graphs, where the computational feasibility of the global attention mechanism is possible. The next goal is to scale up these architectur

Rob Romijnders, Christos Louizos, Yuki M. Asano, Max Welling

The pandemic in 2020 and 2021 had enormous economic and societal consequences, and studies show that contact tracing algorithms can be key in the early containment of the virus. While large strides have been made towards more effective contact tracing algorithms, we argue that privacy concerns currently hold deployment back. The essence of a contact tracing

Patrick Bastian, Rupsa Basu, Holger Dette

Injuries to the lower extremity joints are often debilitating, particularly for professional athletes. Understanding the onset of stressful conditions on these joints is therefore important in order to ensure prevention of injuries as well as individualised training for enhanced athletic performance. We study the biomechanical joint angles from the hip, knee

Antonino Sciarrino, Paul Sorba

Analyzing the codon usage frequencies of a specimen of 20 plants, for which the codon-anticodon pattern is known, we have remarked that the hierarchy of the usage frequencies present an almost "universal" behavior. Searching to explain this behavior, we assume that the codon usage probability results from the sum of two contributions: the first dominant term

Marco Praderio Bova

We develop tools to prove D\'iaz and Park's sharpness conjecture (see [8]) for fusion systems admitting tame families of fusion subsystems (see Theorem A). We use such tools to prove the conjecture for all Benson-Solomon fusion systems (see Theorem B) thus completing the work started by Henke, Libman and Lynd in [14, Theorems 1.1 and 1.4].

Jasmin Fiedler, Christian Weiß

Poissonian pair correlations have sparked interest within the mathematical community, because of their number theoretic properties, and their connections to quantum physics and probability theory, particularly uniformly distributed random numbers. Rather recently, several generalizations of the concept have been introduced, including weak Poissonian pair cor

Yakov Solomons, Inbar Shani, Ofer Firstenberg, Nir Davidson

We consider the coupling of light, via an optical cavity, to two-dimensional atomic arrays whose lattice spacing exceeds the wavelength of the light. Such 'superwavelength' spacing is typical of optical tweezer arrays. While subwavelength arrays exhibit strong atom-photon coupling, characterized by high optical reflectivity in free space, the coupling effici

Stefano Bagnasco, Antonella Bozzi, Tassos Fragos, Alba Gonzalvez

The discovery of gravitational waves, first observed in September 2015 following the merger of a binary black hole system, has already revolutionised our understanding of the Universe. This was further enhanced in August 2017, when the coalescence of a binary neutron star system was observed both with gravitational waves and a variety of electromagnetic coun

Giulia Torcolacci, Anna Guerra, Haiyang Zhang, Francesco Guidi

This paper addresses a near-field imaging problem utilizing extremely large-scale multiple-input multiple-output (XL-MIMO) antennas and reconfigurable intelligent surfaces (RISs) already in place for wireless communications. To this end, we consider a system with a fixed transmitting antenna array illuminating a region of interest (ROI) and a fixed receiving

Lyne Moser, Nima Rasekh, Martina Rovelli

We give a model-independent definition of limits for diagrams valued in an $(\infty,n)$-category. We show that this definition is compatible with the existing notion of homotopy 2-limits for 2-categories, with the existing notion of $(\infty,1)$-limits for $(\infty,1)$-categories, and with itself across different values of $n$.

Y. Alsayyid J. Ahmadi M. Soltani G. Rashedi Z. Noorinejad

In this paper, we investigate the Kane-Mele model and endeavor to demonstrate, through analytical calculations, how the presence of topological edge states influences the RKKY interaction. We illustrate that the effect diminishes as one moves away from the edges. To facilitate our analytical approach, we initially utilize a one-dimensional wire exhibiting li

Anna Pace, Lukas Proksch, Giorgio Grioli, Oskar C. Aszmann

Small obstacles on the ground often lead to a fall when caught with commercial prosthetic feet. Despite some recently developed feet can actively control the ankle angle, for instance over slopes, their flat and rigid sole remains a cause of instability on uneven grounds. Soft robotic feet were recently proposed to tackle that issue; however, they lack consi

Shinnosuke Yamamoto, Isso Saito, Eichi Takaya, Ayaka Harigai

[Purpose] To develop a fully automated semantic placenta segmentation model that integrates the U-Net and SegNeXt architectures through ensemble learning. [Methods] A total of 218 pregnant women with suspected placental anomalies who underwent magnetic resonance imaging (MRI) were enrolled, yielding 1090 annotated images for developing a deep learning model

Eric A. Carlen, Amy Novick-Cohen, Lydia Peres Hari

In modeling phase transitions, it is useful to be able to connect diffuse interface descriptions of the dynamics with corresponding limiting sharp interface motions. In the case of the deep quench obstacle problem (DQOP) and surface diffusion (SD), while a formal connection was demonstrated many years ago, rigorous proof of the connection has yet to be estab

Hossein Goodarzi-Hosseinabadi

Large scale molecular dynamics simulations on polyvinyl alcohol were used to investigate the distribution of unoccupied space under different heat treatments. Representative volume elements consisting of 3600 chains of 300 monomers were equilibrated at melt state and cooled by different cooling rates. The positions of center of mass of the monomers were extr

Fabrizio Albertetti, Lionel Grossrieder, Olivier Ribaux, Kilian Stoffel

The extension of traditional data mining methods to time series has been effectively applied to a wide range of domains such as finance, econometrics, biology, security, and medicine. Many existing mining methods deal with the task of change points detection, but very few provide a flexible approach. Querying specific change points with linguistic variables

V. E. Didenko, A. V. Korybut

We present a new vacuum of the bosonic higher-spin gauge theory in $d+1$ dimensions, which has leftover symmetry of the Poincar\'{e} algebra in $d$ dimensions. Its structure is very simple: the space-time geometry is that of $AdS$, while the only nonzero field is a scalar. The scalar extends along the Poincar\'{e} radial coordinate $z$ and is shown to be lin

Isaak H. Wolf

Let $G$ be a simple graph and let $n,m$ be two integers with $0<m<n$. We prove that $iso(G-S)\leq \frac{n}{m}|S|$ for every $S \subset V(G)$ if and only if $G$ has a $\{C_{2i+1},T \colon 1 \leq i < \frac{m}{n-m}, T\in\mathcal{T}_{\frac{n}{m}}\}$-factor, where $iso(G-S)$ denotes the number of isolated vertices of $G-S$ and $\mathcal{T}_{\frac{n}{m}}$ is a spe

Ankit Pulkit, Smita Naval, Vijay Laxmi

Side-channel attacks have become prominent attack surfaces in cyberspace. Attackers use the side information generated by the system while performing a task. Among the various side-channel attacks, cache side-channel attacks are leading as there has been an enormous growth in cache memory size in last decade, especially Last Level Cache (LLC). The adversary

Yan Xie, Minrui Lv, Chensong Zhang

This paper presents a learnable solver tailored to iteratively solve sparse linear systems from discretized partial differential equations (PDEs). Unlike traditional approaches relying on specialized expertise, our solver streamlines the algorithm design process for a class of PDEs through training, which requires only training data of coefficient distributi

Stefan Dawydiak

We reprove the surjectivity statement of Braverman-Kazhdan's spectral description of Lusztig's asymptotic Hecke algebra $J$ in the context of $p$-adic groups. The proof is based on Bezrukavnikov-Ostrik's description of $J$ in terms of equivariant $K$-theory. As a porism, we prove that the action of $J$ extends from the non-strictly positive unramified charac

Jakob Hollenstein, Georg Martius, Justus Piater

Proximal Policy Optimization (PPO), a popular on-policy deep reinforcement learning method, employs a stochastic policy for exploration. In this paper, we propose a colored noise-based stochastic policy variant of PPO. Previous research highlighted the importance of temporal correlation in action noise for effective exploration in off-policy reinforcement le

Michael K. Koch, Vibhav Bharadwaj, Alexander Kubanek

The coherent control of a two-level system is among the most essential challenges in modern quantum optics. Understanding its fundamental limitations is crucial, also for the realization of next generation quantum devices. The quantum coherence of a two level system is fragile in particular, when the two levels are connected via an optical transition. When s

Abhrojyoti Sen, Anupam Sen

This article addresses the question concerning the existence of global entropy solution for generalized Eulerian droplet models with air velocity depending on both space and time variables. When $f(u)=u,$ $\kappa(t)=const.$ and $u_a(x,t)=const.$ in (1.1), the study of the Riemann problem has been carried out by Keita and Bourgault [42] & Zhang et al. [38]. W

Buvarp Gohsh, Woods Ali, Anders Michael

The intricate hierarchical structure of syntax is fundamental to the intricate and systematic nature of human language. This study investigates the premise that language models, specifically their attention distributions, can encapsulate syntactic dependencies. We introduce Dynamic Syntax Mapping (DSM), an innovative approach for the agnostic induction of th

Lorenzo Cavallina, Giorgio Poggesi

We provide a full characterization of multi-phase problems under a large class of overdetermined Serrin-type conditions. Our analysis includes both symmetry and asymmetry (including bifurcation) results. A broad range of techniques is needed to obtain a full characterization of all the cases, including applications of results obtained via the moving planes m

Matthieu Guer, Martin Luttmann, Jean-François Hergott, Fabien Lepetit

We report on the generation of optical vortices with few-cycle pulse durations, 500$\mu$J per pulse, at a repetition rate of 1 kHz. To do so, a 25 fs laser beam at 800 nm is shaped with a helical phase and coupled into a hollow core fiber filled with argon gas, in which it undergoes self phase modulation. 5.5 fs long pulses are measured at the output of the

Jacob Focke, Florian Hörsch, Shaohua Li, Dániel Marx

The Multicut problem asks for a minimum cut separating certain pairs of vertices: formally, given a graph $G$ and demand graph $H$ on a set $T\subseteq V(G)$ of terminals, the task is to find a minimum-weight set $C$ of edges of $G$ such that whenever two vertices of $T$ are adjacent in $H$, they are in different components of $G\setminus C$. Colin de Verdi\

Krishna Jalan, Roji Pius

An AdS$_2$ black hole in equilibrium with a finite temperature non-gravitating bath comes with a Hawking-like information paradox. The resolution of this paradox requires introducing an island for the bath after the Page time. Since the island region contains the black hole interior, the consistency of the island paradigm demands the failure of any interior

Min Hua, Dong Chen, Xinda Qi, Kun Jiang

Connected and automated vehicles (CAVs) are considered a potential solution for future transportation challenges, aiming to develop systems that are efficient, safe, and environmentally friendly. However, CAV control presents significant challenges due to the complexity of interconnectivity and coordination required among vehicles. Multi-agent reinforcement

Diederick Vermetten, Furong Ye, Thomas Bäck, Carola Doerr

Choosing a set of benchmark problems is often a key component of any empirical evaluation of iterative optimization heuristics. In continuous, single-objective optimization, several sets of problems have become widespread, including the well-established BBOB suite. While this suite is designed to enable rigorous benchmarking, it is also commonly used for tes

Aleksandra Deptuch, Sebastian Lalik, Małgorzata Jasiurkowska-Delaporte, Magdalena Urbańska

Chiral liquid crystalline compounds belonging to the homologous series of (S)-4'-(1-methylheptyloxycarbonyl)biphenyl-4-yl 4-[m-(2,2,3,3,4,4,4-heptafluorobutoxy)alk-1-oxy]-2-fluorobenzoates show various behavior on cooling depending on the length of the CmH2m chain. The homologue with m = 2 crystallizes, while for m = 5, 6, 7, and presumably also for m = 3, t

Bishal Deb, Alexander Dyachenko, Mathias Pétréolle, Alan D. Sokal

We introduce a triangular array $\widehat{\sf L}^{(\alpha)}$ of 5-variable homogeneous polynomials that enumerate Laguerre digraphs (digraphs in which each vertex has out-degree 0 or 1 and in-degree 0 or 1) with separate weights for peaks, valleys, double ascents, double descents, and loops. These polynomials generalize the classical Laguerre polynomials as

Javier Junquera-Sánchez, Carlos Hernando-Ramiro, Óscar Gamallo-Palomares, José-Antonio Gómez-Sánchez

Quantum computing becomes more of a reality as time passes, bringing several cybersecurity challenges. Modern cryptography is based on the computational complexity of specific mathematical problems, but as new quantum-based computers appear, classical methods might not be enough to secure communications. In this paper, we analyse the state of the Galileo Ope

François Golse, Cyril Imbert, Luis Silvestre

We prove that the set of singular times for weak solutions of the homogeneous Boltzmann equation with very soft potentials constructed as in Villani (1998) has Hausdorff dimension at most $\frac{|\gamma+2s|}{2s}$ with $\gamma \in [-4s,-2s)$ and $s \in (0,1)$.

Boaz Lerner, Nir Darshan, Rami Ben-Ari

With such a massive growth in the number of images stored, efficient search in a database has become a crucial endeavor managed by image retrieval systems. Image Retrieval with Relevance Feedback (IRRF) involves iterative human interaction during the retrieval process, yielding more meaningful outcomes. This process can be generally cast as a binary classifi

Futoshi Hayasaka, Vijay Kodiyalam

We characterise ideals in two-dimensional regular local rings that arise as ideals of maximal minors of indecomposable integrally closed modules of rank three.

Julien Khamphousone, Fabian Andres Castano Giraldo, André Rossi, Sonia Toubaline

In this paper, we consider both the Resilient Ring Star Problem, in which a solution should be easy to fix when a single hub fails, and the Survivable Ring Star Problem, in which a solution guarantees that a Ring Star topology is available at no cost when a single hub fails. An ILP formulation is proposed for both problems, as well as a Benders decomposition

Héctor Cerezo-Costas, Ana Fernández Vilas, Manuela Martín-Vicente, Rebeca P. Díaz-Redondo

Citizens are actively interacting with their surroundings, especially through social media. Not only do shared posts give important information about what is happening (from the users' perspective), but also the metadata linked to these posts offer relevant data, such as the GPS-location in Location-based Social Networks (LBSNs). In this paper we introduce a

David Ponce, Thierry Etchegoyhen, Jesús Calleja Pérez, Harritxu Gete

The Split and Rephrase (SPRP) task, which consists in splitting complex sentences into a sequence of shorter grammatical sentences, while preserving the original meaning, can facilitate the processing of complex texts for humans and machines alike. It is also a valuable testbed to evaluate natural language processing models, as it requires modelling complex

Matteo Forconi, William Giarè, Olga Mena, Ruchika

The very first light captured by the James Webb Space Telescope (JWST) revealed a population of galaxies at very high redshifts more massive than expected in the canonical $\Lambda$CDM model of structure formation. Barring, among others, a systematic origin of the issue, in this paper, we test alternative cosmological perturbation histories. We argue that mo

Maximilien Bernard, Pierre Le Doussal, Alberto Rosso, Christophe Texier

We study a discrete model of an heterogeneous elastic line with internal disorder, submitted to thermal fluctuations. The monomers are connected through random springs with independent and identically distributed elastic constants drawn from $p(k)\sim k^{\mu-1}$ for $k\to0$. When $\mu>1$, the scaling of the standard Edwards-Wilkinson model is recovered. When

Jiafu Li, Abdusalam Abdukerim, Chen Cheng, Zihao Bo

Signal reconstruction through software processing is a crucial component of the background and signal models in the PandaX-4T experiment, which is a multi-tonne dark matter direct search experiment. The accuracy of signal reconstruction is influenced by various detector artifacts, including noise, dark count of photomultiplier, impurity photoionization in th

Andrei Ol'khovatov

This paper is a continuation of a series of works, devoted to various aspects of the 1908 Tunguska event. It is devoted to the Evenki accounts of the 1908 Tunguska event collected in 1920s - 1930s. It is important to research accounts of Evenki who were rather close to the epicenter. The Evenki accounts are important also, because Evenki are natural hunters

Lun Ji, Alexander Ostermann

The filtered Lie splitting scheme is an established method for the numerical integration of the periodic nonlinear Schr\"{o}dinger equation at low regularity. Its temporal convergence was recently analyzed in a framework of discrete Bourgain spaces in one and two space dimensions for initial data in $H^s$ with $0<s\leq 2$. Here, this analysis is extended to

Jakub Cimerman, Iurii Karpenko, Boris Tomasik, Pasi Huovinen

A novel three-fluid dynamical model for simulations of heavy-ion collisions at RHIC Beam Energy Scan programme, called MUFFIN, has been developed. The novelty consists of modular inclusion of the Equation of State, use of hyperbolic coordinates that allow to simulate higher collision energies, and fluctuating initial conditions. The model reproduces rapidity

Yiyi Chen, Johannes Bjerva

Colexification refers to linguistic phenomena where multiple concepts (meanings) are expressed by the same lexical form, such as polysemy or homophony. Colexifications have been found to be pervasive across languages and cultures. The problem of concreteness/abstractness of concepts is interdisciplinary, studied from a cognitive standpoint in linguistics, ps

Christine Poulard, Renard Benjamin, Gonzalez-Sosa Enrique, Caillouet Laurie

The "100-year flood" is commonly used, for instance in newspapers, but flood hazard assessment is more complex than it seems. We first describe an animation entitled "bag of floods" to make flood quantiles more concrete, using marbles whose colour corresponds to a class of return period. Discussing the analogies and differences between drawing a marble from

Vincent Berthet

Mixed martial arts (MMA) has been one of the fastest-growing sports in recent years and has become a mainstream sport on the global stage. The growth of MMA has been driven by the Ultimate Fighting Championship (UFC), which is currently the largest MMA promotion organization in the world. However, data collection and statistical modeling in MMA are still in

Siyuan Chen, Wei Xie, Ping Xu, Kun Wang

We consider the quantum memory assisted quantum state verification task, where an adversary prepare independent multipartite entangled states and send to the local verifiers, who then store several copies in the quantum memory and measure them collectively to make decision. We establish an exact analytic formula for optimizing two-copy state verification, wh

Alain Haraux

We recover the relativistic kinetic energy as the result of the work of a force.

Alberto Lastra, Stéphane Malek

The asymptotic behavior of the analytic solutions of a family of singularly perturbed q-difference-differential equations in the complex domain is studied. Different asymptotic expansions with respect to the perturbation parameter and to the time variable are provided: one of Gevrey nature, and another of mixed type Gevrey and q-Gevrey. This asymptotic pheno

Hanyu Li, Wenhan Huang, Zhijian Duan, David Henry Mguni

Nash equilibrium is one of the most influential solution concepts in game theory. With the development of computer science and artificial intelligence, there is an increasing demand on Nash equilibrium computation, especially for Internet economics and multi-agent learning. This paper reviews various algorithms computing the Nash equilibrium and its approxim

Nathan J. Mowry, Constantin R. Krüger, Gabriele Bongiovanni, Marcel Drabbels

Water can be vitrified if it is cooled at rates exceeding $3*10^5$ K/s. This makes it possible to outrun crystallization in so-called no man's land, a range of deeply supercooled temperatures where water crystallizes rapidly. One would naively assume that the process can simply be reversed by heating the resulting amorphous ice at a similar rate. We demonstr

Frank Mtumbuka, Steven Schockaert

Relation extraction is essentially a text classification problem, which can be tackled by fine-tuning a pre-trained language model (LM). However, a key challenge arises from the fact that relation extraction cannot straightforwardly be reduced to sequence or token classification. Existing approaches therefore solve the problem in an indirect way: they fine-t

Asen Nachkov, Martin Danelljan, Danda Pani Paudel, Luc Van Gool

The Bird-Eye-View (BEV) is one of the most widely-used scene representations for visual perception in Autonomous Vehicles (AVs) due to its well suited compatibility to downstream tasks. For the enhanced safety of AVs, modeling perception uncertainty in BEV is crucial. Recent diffusion-based methods offer a promising approach to uncertainty modeling for visua

Thomas Brunel, Charlie Prétot, Christophe Clanet, Baptiste Bolon

A propulsion model has been proposed for front crawl swimming (Carmigniani et al., 2020). The aim of this study is to validate this model through a progressive speed test using instrumented paddles to estimate the propulsion forces in swimming.

Yifei Zhao

We construct equivalences among four notions associated to a reductive group scheme $G$: factorization super central extensions of the loop group of $G$ by $\mathbb G_m$ subject to a condition on the commutator, factorization super line bundles on the affine Grassmannian of $G$, rigidified sections of a quotient of $2$-truncated K-theory over the Zariski cla

Jiachen Zhou, Peizhuo Lv, Yibing Lan, Guozhu Meng

Dataset sanitization is a widely adopted proactive defense against poisoning-based backdoor attacks, aimed at filtering out and removing poisoned samples from training datasets. However, existing methods have shown limited efficacy in countering the ever-evolving trigger functions, and often leading to considerable degradation of benign accuracy. In this pap

Vadym Zayets

This study introduces a method to measure strength of spin-orbit interaction (SO) in a nanomagnet, investigating fundamental phenomena governing magnetic anisotropy. The method explores the fundamental property of SO in its linear proportionality to the external magnetic field, a relationship validated through experimental observation. Systematic study of SO

Marco Marengo, Mauro Abela, Lucio Araneo, M. Bernagozzi

This paper shortly summarises the experimental results obtained since 2011 by a large European academic consortium for the scientific conceptualisation, the definition of the technical requirements, the generation of experimental data, and the validation of a numerical code, for the Pulsating Heat Pipes (PHP) experiment on the International Space Station (IS