May 2024 arXiv papers — page 86

Hoang Ngo, Dat Quoc Nguyen

We present the first domain-adapted and fully-trained large language model, RecGPT-7B, and its instruction-following variant, RecGPT-7B-Instruct, for text-based recommendation. Experimental results on rating prediction and sequential recommendation tasks show that our model, RecGPT-7B-Instruct, outperforms previous strong baselines. We are releasing our RecG

Hsuan-Cheng Wu, Jingyao Wang, Xiantao Li

In this paper, we explore the embedding of nonlinear dynamical systems into linear ordinary differential equations (ODEs) via the Carleman linearization method. Under dissipative conditions, numerous previous works have established rigorous error bounds and linear convergence for Carleman linearization, which have facilitated the identification of quantum ad

Andreas W M Sauter, Erman Acar, Aske Plaat

Research on causal effects often relies on synthetic data due to the scarcity of real-world datasets with ground-truth effects. Since current data-generating tools do not always meet all requirements for state-of-the-art research, ad-hoc methods are often employed. This leads to heterogeneity among datasets and delays research progress. We address the shortc

Peng Gao, Yujian Lee, Hui Zhang, Xubo Liu

Visible-infrared person re-identification (VI-ReID) aims to match people with the same identity between visible and infrared modalities. VI-ReID is a challenging task due to the large differences in individual appearance under different modalities. Existing methods generally try to bridge the cross-modal differences at image or feature level, which lacks exp

Ranim Khojah, Francisco Gomes de Oliveira Neto, Philipp Leitner

Software developers use natural language to interact not only with other humans, but increasingly also with chatbots. These interactions have different properties and flow differently based on what goal the developer wants to achieve and who they interact with. In this paper, we aim to understand the dynamics of conversations that occur during modern softwar

Meng Shang, Lenore Dedeyne, Jolan Dupont, Laura Vercauteren

The Otago Exercise Program (OEP) serves as a vital rehabilitation initiative for older adults, aiming to enhance their strength and balance, and consequently prevent falls. While Human Activity Recognition (HAR) systems have been widely employed in recognizing the activities of individuals, existing systems focus on the duration of macro activities (i.e. a s

Haonan Zhang, Pengpeng Zeng, Lianli Gao, Jingkuan Song

Adapting large-scale image-text pre-training models, e.g., CLIP, to the video domain represents the current state-of-the-art for text-video retrieval. The primary approaches involve transferring text-video pairs to a common embedding space and leveraging cross-modal interactions on specific entities for semantic alignment. Though effective, these paradigms e

Anthony Mallama, Richard E. Cole

Starlink satellites can become extremely bright when sunlight reflects specularly to an observer on the ground. The observed brightness of such flares is consistent with a bidirectional reflectance function of the Starlink satellite chassis. These findings are applied to the case of an extreme flare that was reported as an Unidentified Aerial Phenomena by th

Alexandre Goossens, Johannes De Smedt, Jan Vanthienen

Process mining aims to comprehend and enhance business processes by analyzing event logs. Recently, object-centric process mining has gained traction by considering multiple objects interacting with each other in a process. This object-centric approach offers advantages over traditional methods by avoiding dimension reduction issues. However, in contrast to

Alejandro Dionis-Ros, Joan Vila-Francés, Rafael Magdalena-Benedicto, Fernando Mateo

In this article, we propose the detection of crowd anomalies through the extraction of information in the form of time series from video format using a multimodal approach. Through pattern recognition algorithms and segmentation, informative measures of the number of people and image occupancy are extracted at regular intervals, which are then analyzed to ob

Xin Li, Shuchen Zhang, Mark J. Bowick, Duanduan Wan

After rainfall, pine needles often float on the surface of small puddles. As the water evaporates, they self-assemble into distinct clusters. Motivated by this natural phenomenon, we experimentally investigate the dynamic evolution of synthetic particles as the liquid surface shrinks in area. Our experiments demonstrate the tendency of particles to aggregate

Zhutian Lin, Junwei Pan, Haibin Yu, Xi Xiao

Multi-domain learning (MDL) has become a prominent topic in enhancing the quality of personalized services. It's critical to learn commonalities between domains and preserve the distinct characteristics of each domain. However, this leads to a challenging dilemma in MDL. On the one hand, a model needs to leverage domain-aware modules such as experts or embed

Omar Hamed, Souhail Bakkali, Marie-Francine Moens, Matthew Blaschko

This work addresses the need for a balanced approach between performance and efficiency in scalable production environments for visually-rich document understanding (VDU) tasks. Currently, there is a reliance on large document foundation models that offer advanced capabilities but come with a heavy computational burden. In this paper, we propose a multimodal

Karthik Upadhya, Akshay Jain, Mikko A. Uusitalo, Harish Viswanathan

5G NR is touted to be an attractive candidate for tactical networks owing to its versatility, scalability, and low cost. However, tactical networks need to be stealthy, where an adversary is not able to detect or intercept the tactical communication. In this paper, we investigate the stealthiness of 5G NR by looking at the probability with which an adversary

Albert Cohen, Ronald DeVore, Eitan Tadmor

We construct uniformly bounded solutions of the equation $div\, {\mathbf u}=f$ for arbitrary data $f$ in the critical spaces $L^d(\Omega)$, where $\Omega$ is a domain of ${\mathbb R}^d$. This question was addressed by Bourgain & Brezis, [On the equation ${\rm div}\, Y=f$ and application to control of phases, JAMS 16(2) (2003) 393-426], who proved that althou

Shahnaz Farhat

The goal of this article is to investigate the dynamics of semi-relativistic or non-relativistic charged particles in interaction with a scalar meson field. Our main contribution is the derivation of the classical dynamics of a particle-field system as an effective equation of the quantum microscopic Nelson model, in the classical limit where the value of th

Minbyul Jeong, Hyeon Hwang, Chanwoong Yoon, Taewhoo Lee

In the medical domain, numerous scenarios necessitate the long-form generation ability of large language models (LLMs). Specifically, when addressing patients' questions, it is essential that the model's response conveys factual claims, highlighting the need for an automated method to evaluate those claims. Thus, we introduce MedLFQA, a benchmark dataset rec

Bart Jacobs

In probabilistic updating one transforms a prior distribution in the light of given evidence into a posterior distribution, via what is called conditioning, updating, belief revision or inference. This is the essence of learning, as Bayesian updating. It will be illustrated via a physical model involving (adapted) water flows through pipes with different dia

Shuai Fu, Tim Dwyer, Peter J. Stuckey

Polymorphic types are an important feature in most strongly typed programming languages. They allow functions to be written in a way that can be used with different data types, while still enforcing the relationship and constraints between the values. However, programmers often find polymorphic types difficult to use and understand and tend to reason using c

Johannes Scherzer, Lukas Lackner, Bo Han, Borislav Polovnikov

We demonstrate evidence of correlated magnetism for exciton-polaritons in a MoSe$_{2}$/WS$_{2}$ moir\'e heterostructure with near-parallel alignment subject to electron doping. In our experiments, interactions between electrons and moir\'e excitons are controlled electrostatically by field-effect doping, and the polaritonic regime of strong light-matter coup

Kaiyuan Li, Yihan Zhang, Huandong Wang, Yan Zhuo

Mobile devices and the Internet of Things (IoT) devices nowadays generate a large amount of heterogeneous spatial-temporal data. It remains a challenging problem to model the spatial-temporal dynamics under privacy concern. Federated learning (FL) has been proposed as a framework to enable model training across distributed devices without sharing original da

Xiaohua Pan, Weifeng Wu, Peiran Liu, Zhen Li

In many practical real-world applications, data missing is a very common phenomenon, making the development of data-driven artificial intelligence theory and technology increasingly difficult. Data completion is an important method for missing data preprocessing. Most existing miss-ing data completion models directly use the known information in the missing

Carla Fabiana Chiasserini, Francesco Malandrino, Nuria Molner, Zhiqiang Zhao

Pruning neural networks, i.e., removing some of their parameters whilst retaining their accuracy, is one of the main ways to reduce the latency of a machine learning pipeline, especially in resource- and/or bandwidth-constrained scenarios. In this context, the pruning technique, i.e., how to choose the parameters to remove, is critical to the system performa

Shuai Fu, Tim Dwyer, Peter J. Stuckey, John Grundy

Statically typed languages offer significant advantages, such as bug prevention, enhanced code quality, and reduced maintenance costs. However, these benefits often come at the expense of a steep learning curve and a slower development pace. Haskell, known for its expressive and strict type system, poses challenges for inexperienced programmers in learning a

Mauro Fava, Emma McCabe, Aldo H. Romero, Eric Bousquet

We demonstrate through first-principles calculations applied to the K$_{3}$NiO$_{2}$ crystal that a structural phase transition from an achiral to a chiral phase can be mediated by a degenerate soft phonon mode and controlled by pressure and epitaxial strain. Breaking such degeneracy with an electric field generates a competition between enantiomorphic, pola

Moises Diaz, Miguel A. Ferrer, Gennaro Vessio

Signature verification is a critical task in many applications, including forensic science, legal judgments, and financial markets. However, current signature verification systems are often difficult to explain, which can limit their acceptance in these applications. In this paper, we propose a novel explainable offline automatic signature verifier (ASV) to

Ian Hamilton, Nick Tawn

Comparative Judgement is an assessment method where item ratings are estimated based on rankings of subsets of the items. These rankings are typically pairwise, with ratings taken to be the estimated parameters from fitting a Bradley-Terry model. Likelihood penalization is often employed. Adaptive scheduling of the comparisons can increase the efficiency of

V. M. Maslov

Variation of fission neutron spectra of 240Pu (sf) and 240Pu (n, F) for E up to 20 MeV predicted.Features of angle-integrated prompt fission neutron spectra of 240Pu (n, F) stem from simultaneous analysis of data for 238U (n, F), 239Pu (n, F) and available data on 240Pu (n, F) prompt fission neutron spectra.The data on average energies of 240Pu (n, F) prompt

S. Bondarenko, Ya. Dydyshka, L. Kalinovskaya, A. Kampf

Complete one-loop electroweak radiative corrections to the charged-current Drell-Yan processes $pp \to \ell^{+}\nu_{\ell}(+X)$ and $pp \to \ell^{-}\bar{\nu}_{\ell}(+X)$ are presented for the case of longitudinal polarization of initial particles. The results can be used to obtain precise predictions for the kinematic distributions of polarized $W^{\pm}$ prod

Nayana T S, Bhaghyesh

In this work, the spectra and decay properties of $B_c$ mesons ($c\bar{b}$) have been investigated using a non-relativistic potential model incorporating corrections from LQCD. The non-relativistic Schrodinger wave equation is solved numerically using the Matrix Numerov Method. Using the obtained masses and wave functions, decay widths, lifetime, branching r

T. Jauk, H. Hampel, J. Walowski, K. Komatsu

Heat and disorder are opponents of magnetism. This fact, expressed in Curie's law established more than a century ago, holds even in the highly non-equilibrium interaction of ultra-intense laser pulses with magnetic matter. In contradiction to this, here we demonstrate that optical excitation of a ferromagnet can abrogate the link between temperature and ord

Yafu Li, Zhilin Wang, Leyang Cui, Wei Bi

AI-generated text detection has attracted increasing attention as powerful language models approach human-level generation. Limited work is devoted to detecting (partially) AI-paraphrased texts. However, AI paraphrasing is commonly employed in various application scenarios for text refinement and diversity. To this end, we propose a novel detection framework

LHCb collaboration, R. Aaij, A. S. W. Abdelmotteleb, C. Abellan Beteta

Decays of $\mathit{\Xi}_{b}^-$ and $\mathit{\Omega}_{b}^-$ baryons to $\mathit{\Lambda}_{c}^+ h^- h^{\prime -}$ final states, with $h^- h^{\prime -}$ being $\pi^-\pi^-$, $K^-\pi^-$ and $K^-K^-$ meson pairs, are searched for using data collected with the LHCb detector. The data sample studied corresponds to an integrated luminosity of $8.7\,\mathrm{fb}^{-1}$

Jianyang Ding, Zhicheng Jiang, Xiuhua Chen, Zicheng Tao

Altermagnetism (AM), a newly discovered magnetic state, ingeniously integrates the properties of ferromagnetism and antiferromagnetism, representing a significant breakthrough in the field of magnetic materials. Despite experimental verification of some typical AM materials, such as MnTe and MnTe$_2$, the pursuit of AM materials that feature larger spin spli

Christian Bonatti, Lorenzo J. Diaz, Katrin Gelfert

We introduce the concept of a heterodimensional cycle of hyperbolic ergodic measures and a special type of them that we call rich. Within a partially hyperbolic context, we prove that if two measures are related by a rich heterodimensional cycle, then the entire segment of probability measures linking them lies within the closure of measures supported on per

Jesse Daas, Cristobal Laporte, Frank Saueressig, Tim van Dijk

General relativity is highly successful in explaining a wide range of gravitational phenomena including the gravitational waves emitted by binary systems and the shadows cast by supermassive black holes. From a modern perspective the theory is not fundamental though, but constitutes the lowest order term in an effective field theory description of the gravit

Yuling Jiao, Lican Kang, Jin Liu, Heng Peng

Deep nonparametric regression, characterized by the utilization of deep neural networks to learn target functions, has emerged as a focus of research attention in recent years. Despite considerable progress in understanding convergence rates, the absence of asymptotic properties hinders rigorous statistical inference. To address this gap, we propose a novel

Liang-Jun He, Bo Liu, Yong-Chang Zhang

Through considering a two-component dipolar Bose-Einstein condensate, we investigate the influence of the angle between the polarization orientations of the two species on the ground states, and show that the miscibility between the two components can be adjusted not only by the inter-component contact interaction but also by the polarization angle. Particul

Adam Białożyt

We demonstrate that every point where X - a closed subset of R^n - is not Lipschitz Normally Embedded is approached by the medial axis of X.

Francisco Neves, Luís Branco, Maria Pereira, Rafael Claro

In the field of autonomous Unmanned Aerial Vehicles (UAVs) landing, conventional approaches fall short in delivering not only the required precision but also the resilience against environmental disturbances. Yet, learning-based algorithms can offer promising solutions by leveraging their ability to learn the intelligent behaviour from data. On one hand, thi

Supriya Pisolkar, Biswanath Samanta

For a prime $p$ and a commutative ring $R$ with unity, let $W(R)$ denote the group of $p$-typical Witt vectors. The group $W(R)$ is endowed with a Verschiebung operator $V: W(R)\to W(R)$ and a Teichm\"{u}ller map $\langle \ \rangle: R\rightarrow W(R)$. One of the properties satisfied by $V, \langle \ \rangle$ is that the map $R \to W(R)$ given by $x\mapsto V

Meng Zeng, Ming-Yuan Zhu, Yu-Peng Zhu, Xiang-Rui Liu

Recently, unconventional antiferromagnets that enable the splitting of electronic spins have been theoretically proposed and experimentally realized, where the magnetic sublattices containing moments pointing at different directions are connected by a novel set of symmetries. Such spin splitting (SS) is substantial, $k$-dependent, and independent of the spin

Ran Gelles, Zvi Lotker, Frederik Mallmann-Trenn

We examine sorting algorithms for $n$ elements whose basic operation is comparing $t$ elements simultaneously (a $t$-comparator). We focus on algorithms that use only a single round or two rounds -- comparisons performed in the second round depend on the outcomes of the first round comparators. We design deterministic and randomized algorithms. In the determ

Ilkka Helenius, Hannu Paukkunen, Sami Yrjänheikki

We present a next-to-leading order perturbative QCD calculation of dimuon production in neutrino-nucleus collisions. This process is typically calculated by assuming it to be proportional to inclusive charm production, which requires an effective acceptance correction to take the experimental cuts on the decay-muon kinematics into account. Here, we instead c

Li Ma, Shoulong Wang, Changchen Liu, Ange Wen

Wrinkle defects were found widely exist in the field of industrial products, i.e. wind turbine blades and filament-wound composite pressure vessels. The magnitude of wrinkle wavelength varies from several millimeters to over one hundred millimeters. Locating the wrinkle defects and measuring their responses are very important to the assessment of the structu

Vikas Rathore, Vyom Desai, Nirav I Jamnapara, Sudhir Kumar Nema

This study presents a novel and ecofriendly method for synthesizing ammonium nitrate using activated prepared through air and ammonia plasma treatments. Initially, PAW containing nitrate ions is produced by treating water with air plasma. This PAW air is then frozen and exposed to low pressure NH$_3$ plasma, introducing ammonium ions to from NH$_4$NO$_3$. We

Boris Bellalta, Katarzyna Kosek-Szott, Szymon Szott, Francesc Wilhelmi

Will AI/ML-defined radios become a reality in the near future? In this paper, we introduce the concept of an AI/ML-defined radio - a radio architecture specifically designed to support AI/ML-based optimization and decision-making in communication functions - and depict its promised benefits and potential challenges. Additionally, we discuss a potential roadm

Arpita Jana, Soham Sen, Sunandan Gangopadhyay

In an earlier analysis \href{https://link.aps.org/doi/10.1103/PhysRevD.105.085007}{Phys. Rev. D 105 (2022) 085007}, we have explored the event of acceleration radiation for an atom freely falling into the event horizon of a quantum-corrected Schwarzschild black hole. We want to explore the acceleration-radiation when the atom is freely falling into the event

David Blanc, Simona Paoli

We describe a comonad on $n$-track categories, for each $n\geq 0$ yielding an explicit cosimplicial abelian group model for the Andr\'{e}-Quillen cohomology of an $(\infty,1)$-category.

Yu Feng, Jijian Song, Bin Xu

Cone spherical metrics, defined on compact Riemann surfaces, are conformal metrics with constant curvature one and finitely many cone singularities. Such a metric is termed \textit{reducible} if a developing map of the metric has monodromy in ${\rm U(1)}$, and \textit{irreducible} otherwise. Utilizing the polystable extensions of two line bundles on a compac

Vedran Krčadinac

We give the first example of a mosaic of three combinatorial designs with distinct parameters $2$-$(13,3,1)$, $2$-$(13,4,2)$, and $2$-$(13,6,5)$. Furthermore, we give examples of mosaics of $2$-$(9,3,2)$ designs that are not resolvable, thereby answering a question posed by M. Wiese and H. Boche. Finally, we give an example of a mosaic of projective planes o

Etera R. Livine, Clara Montagnon, Naritaka Oshita, Hugo Roussille

We compute the Quasi-Normal Mode (QNM) frequencies for scalar perturbations for modified Schwarzschild black holes in Loop Quantum Gravity. We study the singularity-free polymerized metric characterised by two parameters encoding loop quantum effects: the minimal area gap $a_0$ and the polymeric deformation parameter $P$. We perform numerical computations us

M. Kuffmeier, J. E. Pineda, D. Segura-Cox, T. Haugbølle

It has been consensus that star-disk systems accrete most of their mass and angular momentum during the collapse of a prestellar core, such that the rotational direction of a system is equivalent to the net rotation of the core. Recent results, however, indicate that stars experience post-collapse or late infall, during which the star and its disk is refresh

Huangjun Shen, Liangying Shao, Wenbo Li, Zhibin Lan

In recent years, multi-modal machine translation has attracted significant interest in both academia and industry due to its superior performance. It takes both textual and visual modalities as inputs, leveraging visual context to tackle the ambiguities in source texts. In this paper, we begin by offering an exhaustive overview of 99 prior works, comprehensi

Rutger-Jan Lange

Based on Bellman's dynamic-programming principle, Lange (2024) presents an approximate method for filtering, smoothing and parameter estimation for possibly non-linear and/or non-Gaussian state-space models. While the approach applies more generally, this pedagogical note highlights the main results in the case where (i) the state transition remains linear a

Jinzhe Che, Shenjie Huang, Majid Safari

Optical wireless communication (OWC) emerges as a pivotal solution for achieving terabit-level aggregate throughput in next-generation wireless networks. With the mature high-speed transceivers and advanced (de)multiplexing techniques designed for fiber optics, fiber-coupled OWC can be seamlessly integrated into existing ultra-high-speed networks such as dat

Nicolas Jonason, Luca Casini, Bob L. T. Sturm

We present a new approach for fast and controllable generation of symbolic music based on the simplex diffusion, which is essentially a diffusion process operating on probabilities rather than the signal space. This objective has been applied in domains such as natural language processing but here we apply it to generating 4-bar multi-instrument music loops

M. Lopez-Corredoira, F. Melia, J. -J. Wei, C. -Y. Gao

Recent James Webb Space Telescope (JWST) data analyses have shown that massive red galaxies existed at redshifts $z>6$, a discovery that is difficult to understand in the context of standard cosmology ($\Lambda $CDM). Here we analyze these observations more deeply by fitting a stellar population model to the optical and near-infrared photometric data. These

Tao Yu, Pengbo Huang, Shunqing Zhang, Xiaojing Chen

In order to provide design guidelines for energy efficient 6G networks, we propose a novel radial basis function (RBF) based optimization framework to maximize the integrated relative energy efficiency (IREE) metric. Different from the conventional energy efficient optimization schemes, we maximize the transformed utility for any given IREE using spectrum ef

Jia Gong, Shenyu Ji, Lin Geng Foo, Kang Chen

Creating and customizing a 3D clothed avatar from textual descriptions is a critical and challenging task. Traditional methods often treat the human body and clothing as inseparable, limiting users' ability to freely mix and match garments. In response to this limitation, we present LAyered Gaussian Avatar (LAGA), a carefully designed framework enabling the

Olivier Ramaré, Sebastian Zuniga Alterman

Let $\lambda$ the Barban--Vehov weights, defined in $(1)$. Let $X\ge z_1\ge100$ and $z_2=z_1^\tau$ for some $\tau>1$. We prove that \begin{equation*} \sum_{n\le X}\frac{1}{n}\Bigl(\sum_{\substack{d|n}}\lambda_d\Bigr)^2 \le f(\tau)\frac{\log X}{\log (z_2/z_1)}, \end{equation*} for a completely determined function $f:(1,\infty)\to\mathbb{R}_{>0}$. In particula

Jingyuan Yang, Jiawei Feng, Weibin Luo, Dani Lischinski

Affective Image Manipulation (AIM) seeks to modify user-provided images to evoke specific emotional responses. This task is inherently complex due to its twofold objective: significantly evoking the intended emotion, while preserving the original image composition. Existing AIM methods primarily adjust color and style, often failing to elicit precise and pro

Jérémie Chalopin, Victor Chepoi, Kolja Knauer

We prove that any convex geometry $\mathcal{A}=(U,\mathcal{C})$ on $n$ points and any ideal $\mathcal{I}=(U',\mathcal{C}')$ of $\mathcal{A}$ can be realized as the intersection pattern of an open convex polyhedral cone $K\subseteq {\mathbb R}^n$ with the orthants of ${\mathbb R}^n$. Furthermore, we show that $K$ can be chosen to have at most $m$ facets, wher

Ehsan Sadeghi, Karina Skurule, Alessandro Chiumento, Paul Havinga

Recent advancements in non-invasive health monitoring technologies underscore the potential of mm-Wave Frequency-Modulated Continuous Wave (FMCW) radar in real-time vital sign detection. This paper introduces a novel dataset, the first of its kind, derived from mm-Wave FMCW radar, meticulously capturing heart rate and respiratory rate under various condition

Mohammad Azizmalayeri, Ameen Abu-Hanna, Giovanni Cinà

Detecting out-of-distribution (OOD) instances is crucial for the reliable deployment of machine learning models in real-world scenarios. OOD inputs are commonly expected to cause a more uncertain prediction in the primary task; however, there are OOD cases for which the model returns a highly confident prediction. This phenomenon, denoted as "overconfidence"

Yochay Jerby

In his foundational book, Edwards introduced a unique "speculation" regarding the possible theoretical origins of the Riemann Hypothesis, based on the properties of the Riemann-Siegel formula. Essentially Edwards asks whether one can find a method to transition from zeros of $Z_0(t)=cos(\theta(t))$, where $\theta(t)$ is Riemann-Siegel theta function, to zero

Yu-Hsiang Lin, Huang-Ting Shieh, Chih-Yu Liu, Kuang-Ting Lee

Extrapolation in Large language models (LLMs) for open-ended inquiry encounters two pivotal issues: (1) hallucination and (2) expensive training costs. These issues present challenges for LLMs in specialized domains and personalized data, requiring truthful responses and low fine-tuning costs. Existing works attempt to tackle the problem by augmenting the in

Siyu Kong, Adrian S. Lewis

Goldstein's 1977 idealized iteration for minimizing a Lipschitz objective fixes a distance - the step size - and relies on a certain approximate subgradient. That "Goldstein subgradient" is the shortest convex combination of objective gradients at points within that distance of the current iterate. A recent implementable Goldstein-style algorithm allows a re

Dominik Köhler, Stefan Heindorf

Graph Neural Networks (GNNs) are effective for node classification in graph-structured data, but they lack explainability, especially at the global level. Current research mainly utilizes subgraphs of the input as local explanations or generates new graphs as global explanations. However, these graph-based methods are limited in their ability to explain clas

George McArdle, Rose Davies, Igor V. Lerner, Igor V. Yurkevich

We consider how the absence of thermalisation affects the classical Coulomb blockade regime in quantum dots. By solving the quantum kinetic equation in the experimentally accessible regime when the dot has two relevant occupation states, we calculate the current-voltage characteristics for arbitrary coupling to the leads. If the couplings are strongly asymme

Yueshan Lin, Wei Feng, Yunfei Chen, Ning Ge

Quick response to disasters is crucial for saving lives and reducing loss. This requires low-latency uploading of situation information to the remote command center. Since terrestrial infrastructures are often damaged in disaster areas, non-terrestrial networks (NTNs) are preferable to provide network coverage, and mobile edge computing (MEC) could be integr

James S. Pallister, Samuel H. Pickering, Dimitri M. Gangardt, Alexander G. Abanov

We consider directed polymers in 1+1 spatial dimension under action of an external repulsive potential along a line. Using the exact mapping onto imaginary time evolution of free fermions we find that for sufficiently strong potential the system of polymers undergoes a continuous configurational phase transition. The transition corresponds to merging empty r

Lorenzo Gallo, Cesar E. Sobrero, Jorge A. Malarría, Roberto F. Luccas

This work examines the oxygenation process of polycrystalline powder of YBa$_2$Cu$_3$O$_{6+\delta}$ superconductor material through constant temperature thermogravimetric analysis. Starting from completely deoxygenated samples ($\delta$ = 0), both the mass evolution in an oxygen atmosphere and a differential temperature value referenced to an inert sample (a

Alessandro Arsie, Paolo Lorenzoni

We show that a bi-flat F-structure $(\nabla,\circ,e,\nabla^*,*,E)$ on a manifold $M$ defines a differential bicomplex $(d_{\nabla},d_{E\circ\nabla^*})$ on forms with value on the tangent sheaf of the manifold. Moreover, the sequence of vector fields defined recursively by $d_{\nabla}X_{(\alpha+1)}=d_{L\nabla^*}X_{(\alpha)}$ coincide with the coefficients of

Hyeongjin Kim, Sangwon Kim, Dasom Ahn, Jong Taek Lee

Scene graph generation (SGG) is an important task in image understanding because it represents the relationships between objects in an image as a graph structure, making it possible to understand the semantic relationships between objects intuitively. Previous SGG studies used a message-passing neural networks (MPNN) to update features, which can effectively

Sourav Kundu, Siddhartha Lal

We present a theoretical investigation of the electronic specific heat (ESH) at constant volume (Cv) of single-helical proteins modeled within the tight-binding (TB) framework. We study the effects of helical symmetry, long-range hopping, environment and biological defects on thermal properties. We employ a general TB model to incorporate all parameters rele

Yuanhong Tang, Shanshan Jia, Tiejun Huang, Zhaofei Yu

A single neuron receives an extensive array of synaptic inputs through its dendrites, raising the fundamental question of how these inputs undergo integration and summation, culminating in the initiation of spikes in the soma. Experimental and computational investigations have revealed various modes of integration operations that include linear, superlinear,

Hassan Basari V. T.

Previous studies indicate that the expansion law in emergence of space can be derived from the first law f thermodynamics. It has been proposed a unified formulation for the expansion law applicable to a general set of gravity theories in equilibrium description. In that formulation, which is based on the first law of thermodynamics, the non-equilibrium term

Stephen A Church, Francesco Vitale, Aswani Gopakumar, Nikita Gagrani

Active wavelength-scale optoelectronic components are widely used in photonic integrated circuitry, however coherent sources of light -- namely optical lasers -- remain the most challenging component to integrate. Semiconductor nanowire lasers represent a flexible class of light source where each nanowire is both gain material and cavity; however, strong cou

Carlos Arcila Calderón, Bilgeçağ Aydoğdu, Tuba Bircan, Bünyamin Gündüz

Following Turkey's 2020 decision to revoke border controls, many individuals journeyed towards the Greek, Bulgarian, and Turkish borders. However, the lack of verifiable statistics on irregular migration and discrepancies between media reports and actual migration patterns require further exploration. The objective of this study is to bridge this knowledge g

Xiao Yu, Lei Liu, Xing Hu, Jacky Wai Keung

With the increasing utilization of large language models such as ChatGPT during software development, it has become crucial to verify the quality of code content it generates. Recent studies proposed utilizing ChatGPT as both a developer and tester for multi-agent collaborative software development. The multi-agent collaboration empowers ChatGPT to produce t

Han Yan, Xian Chen, Jinhai Zhang, Fan Zhang

Motivated by the old idea of using the moon as a resonant gravitational-wave (GW) detector, as well as the recent updates in modeling the lunar response to GWs, we re-evaluate the feasibility of using a network of lunar seismometers to constrain the stochastic GW background (SGWB). In particular, using the updated model of the lunar response, we derive the p

April Tyack, Elisa D. Mekler

Self-determination theory (SDT), a psychological theory of human motivation, is a prominent paradigm in human-computer interaction (HCI) research on games. However, our prior literature review observed a trend towards shallow applications of the theory. This follow-up work takes a broader view -- examining SDT scholarship on games, a wider corpus of SDT-base

Yihu Tang, Li Huang, Limin Wu, Xianghui Meng

Rough surface lubrication simulation is crucial for designing and optimizing tribological performance. Despite the growing application of Physical Information Neural Networks (PINNs) in hydrodynamic lubrication analysis, their use has been primarily limited to smooth surfaces. This is due to traditional PINN methods suffer from spectral bias, favoring to lea

Y. Hori, A. Fukui, T. Hirano, N. Narita

Sub-Neptunes with $2-3R_\oplus$ are intermediate in size between rocky planets and Neptune-sized planets. The orbital properties and bulk compositions of transiting sub-Neptunes provide clues to the formation and evolution of close-in small planets. In this paper, we present the discovery and follow-up of four sub-Neptunes orbiting M dwarfs (TOI-782, TOI-144

Sujay K. Ashok, Sanhita Parihar, Tanmoy Sengupta, Adarsh Sudhakar

We study two dimensional systems with extended conformal symmetry generated by the ${\mathcal W}_3$ algebra. These are expected to have an infinite number of commuting conserved charges, which we refer to as the quantum Boussinesq charges. We compute the eigenvalues of the quantum Boussinesq charges in both the vacuum and first excited states of the higher s

Linfeng Wen, Minxian Xu, Adel N. Toosi, Kejiang Ye

Cloud native solutions are widely applied in various fields, placing higher demands on the efficient management and utilization of resource platforms. To achieve the efficiency, load forecasting and elastic scaling have become crucial technologies for dynamically adjusting cloud resources to meet user demands and minimizing resource waste. However, existing

Anirvan Dutta, Etienne Burdet, Mohsen Kaboli

Autonomously exploring the unknown physical properties of novel objects such as stiffness, mass, center of mass, friction coefficient, and shape is crucial for autonomous robotic systems operating continuously in unstructured environments. We introduce a novel visuo-tactile based predictive cross-modal perception framework where initial visual observations (

Bao-Thien Nguyen-Tat, Minh-Quoc Bui, Vuong M. Ngo

Haar Cascade is a cost-effective and user-friendly machine learning-based algorithm for detecting objects in images and videos. Unlike Deep Learning algorithms, which typically require significant resources and expensive computing costs, it uses simple image processing techniques like edge detection and Haar features that are easy to comprehend and implement

Kenji Amazaki, Masashi Nashimoto, Makoto Hattori

Cosmic very small dust grains (VSGs) contain 100 to 10,000 atoms, making it a mesoscopic system with specific thermal and optical characteristics due to the finite number of atoms within each grain. This paper focuses on graphite VSGs which contain free electrons. The energy level statistics devised by Kubo (1962, J.Phys.Soc.Jpn., 17, 975-986) were used for

Anna Meyer, Srivatsa Prativadibhayankaram, André Kaup

Learned wavelet image and video coding approaches provide an explainable framework with a latent space corresponding to a wavelet decomposition. The wavelet image coder iWave++ achieves state-of-the-art performance and has been employed for various compression tasks, including lossy as well as lossless image, video, and medical data compression. However, the

Nicolo Micheletti, Samuel Belkadi, Lifeng Han, Goran Nenadic

Large Language Models (LLMs) have revolutionised the field of Natural Language Processing (NLP) and have achieved state-of-the-art performance in practically every task in this field. However, the prevalent approach used in text generation, Causal Language Modelling (CLM), which generates text sequentially from left to right, inherently limits the freedom of

Xiaozhu Fang, Yu Xu, Tianshi Chen

Frequency response function (FRF) estimation is a classical subject in system identification. In the past two decades, there have been remarkable advances in developing local methods for this subject, e.g., the local polynomial method, local rational method, and iterative local rational method. The recent concentrations for local methods are two issues: the

Vincenzo Suriani, Emanuele Musumeci, Daniele Nardi, Domenico Daniele Bloisi

Robots playing soccer often rely on hard-coded behaviors that struggle to generalize when the game environment change. In this paper, we propose a temporal logic based approach that allows robots' behaviors and goals to adapt to the semantics of the environment. In particular, we present a hierarchical representation of soccer in which the robot selects the

Susanna Parenti, Manuel Luna, José Luis Ballester

Partially ionised plasmas (PIP) constitute an essential ingredient of our plasma universe. Historically, the physical effects associated with partial ionisation were considered in astrophysical topics such as the interstellar medium, molecular clouds, accretion disks and, later on, in solar physics. PIP can be found in layers of the Sun's atmosphere as well

Ch. Cobollo, A. Peris

The notion of disjoint $\mathcal{A}$-transitivity for a Furstenberg family $\mathcal{A}$ is introduced with the aim to generalize properties derived from disjoint hypercyclic operators. We begin a systematic study by showing some of the basic properties, including necessary conditions to inherit the property on the whole space from an invariant linearly dens

Mohamed Abdelaal

In this paper, we explore the transformative impact of Artificial Intelligence (AI) in the manufacturing sector, highlighting its potential to revolutionize industry practices and enhance operational efficiency. We delve into various applications of AI in manufacturing, with a particular emphasis on human-machine interfaces (HMI) and AI-powered milling machi

Fan Yang, Furong Wang, Xusheng Xu, Pao Gao

Quantum computing is a promising candidate for accelerating machine learning tasks. Limited by the control accuracy of current quantum hardware, reducing the consumption of quantum resources is the key to achieving quantum advantage. Here, we propose a quantum resonant dimension reduction (QRDR) algorithm based on the quantum resonant transition to reduce th

Fernando Henríquez, Christoph Schwab

We obtain wavenumber-robust error bounds for the deep neural network (DNN) emulation of the solution to the time-harmonic, sound-soft acoustic scattering problem in the exterior of a smooth, convex obstacle in two physical dimensions. The error bounds are based on a boundary reduction of the scattering problem in the unbounded exterior region to its smooth,

Md. Mouzakkir Hossain, Sukhendu Ghosh, Harekrushna Behera, G. P. Raja Sekhar

Linear and weakly nonlinear stability analyses of an externally shear-imposed, gravity-driven falling film over a uniformly heated wavy substrate are studied. The longwave asymptotic expansion technique is utilized to formulate a single nonlinear free surface deflection equation. The linear stability criteria for the onset of instability are derived using th