April 2024 arXiv papers — page 88

Munkh-Erdene Otgonbold, Ganzorig Batnasan, Munkhjargal Gochoo

Motivated by the need to improve model performance in traffic monitoring tasks with limited labeled samples, we propose a straightforward augmentation technique tailored for object detection datasets, specifically designed for stationary camera-based applications. Our approach focuses on placing objects in the same positions as the originals to ensure its ef

Dongfang Li, Zhenyu Liu, Xinshuo Hu, Zetian Sun

Large Language Models (LLMs) have exhibited an impressive ability to perform In-Context Learning (ICL) from only a few examples. Recent works have indicated that the functions learned by ICL can be represented through compressed vectors derived from the transformer. However, the working mechanisms and optimization of these vectors are yet to be thoroughly ex

Andrew Thompson

Machine learning (ML) models are increasingly being used in metrology applications. However, for ML models to be credible in a metrology context they should be accompanied by principled uncertainty quantification. This paper addresses the challenge of uncertainty propagation through trained/fixed machine learning (ML) regression models. Analytical expression

B. Blankleider, A. N. Kvinikhidze

Recently we formulated covariant equations describing the tetraquark in terms of an admixture of two-body states $D\bar D$ (diquark-antidiquark), $MM$ (meson-meson), and three-body-like states where two of the quarks are spectators while the other two are interacting [Phys. Rev. D 107, 094014 (2023)]. A feature of these equations is that they unify descripti

Jordan Samhi, Andreas Zeller

Dynamic analysis has emerged as a pivotal technique for testing Android apps, enabling the detection of bugs, malicious code, and vulnerabilities. A key metric in evaluating the efficacy of tools employed by both research and practitioner communities for this purpose is code coverage. Obtaining code coverage typically requires planting probes within apps to

Michael Baake, Jeremy Sumner

Markov matrices of equal-input type constitute a widely used model class. The corresponding equal-input generators span an interesting subalgebra of the real matrices with zero row sums. Here, we summarise some of their amazing properties and discuss the corresponding Markov embedding problem, both homogeneous and inhomogeneous in time. In particular, we der

Fakrul Islam Tushar, Liesbeth Vancoillie, Cindy McCabe, Amareswararao Kavuri

Clinical imaging trials play a crucial role in advancing medical innovation but are often costly, inefficient, and ethically constrained. Virtual Imaging Trials (VITs) present a solution by simulating clinical trial components in a controlled, risk-free environment. The Virtual Lung Screening Trial (VLST), an in silico study inspired by the National Lung Scr

Yi Li, Jia-Hui Zhang, Feng Mei, Jie Ma

Ultracold atoms trapped in optical superlattices provide a simple platform for realizing the seminal Aubry-Andr\'{e}-Harper (AAH) model. However, the periodic modulations on the nearest-neighbour hoppings have been ignored in this model. In this paper, we find that optical superlattice system actually can be approximately described by a generalized AAH model

P. J. Steyn, D. Johnson, G. J. J. Botha, S. Régnier

The solar minima between solar cycles 22-23, 23-24 and 24-25 are the best observed minima on record. In situ solar wind and interplanetary magnetic field measurements by the WIND and ACE spacecraft at L1 with one-hour cadence are explored using wavelet analyses for the most quiescent year during each minimum. Times of local peaks in periodicities are identif

Amirhossein Akbar Tabatabai

One of the elegant achievements in the history of proof theory is the characterization of the provably total recursive functions of an arithmetical theory by its proof-theoretic ordinal as a way to measure the time complexity of the functions. Unfortunately, the machinery is not sufficiently fine-grained to be applicable on the weak theories on the one hand

Qin Tan, Yi Zhong, Wen-Di Guo

In this work, we study the gravitational quasinormal modes of the thick brane in Rastall gravity. Using the asymptotic iteration and direct integration methods, we solve the quasinormal frequencies of the Rastall thick brane. We also obtained the waveforms of these quasinormal modes through numerical evolution. The results indicate that although the Rastall

Zhiyuan He, Huiqiang Jiang, Zilong Wang, Yuqing Yang

The performance of large language models (LLMs) is significantly influenced by the quality of the prompts provided. In response, researchers have developed enormous prompt engineering strategies aimed at modifying the prompt text to enhance task performance. In this paper, we introduce a novel technique termed position engineering, which offers a more effici

Zhen-Hua Zhang, Teng Ji, Xiang-Kun Dong, Feng-Kun Guo

Using chiral effective field theory, we predict that there must be isovector charmonium-like $D\bar D^*$ hadronic molecules with $J^{PC}=1^{++}$ denoted as $W_{c1}$. The inputs are the properties of the $X(3872)$, including its mass and the ratio of its branching fractions of decays into $J/\psi\rho^0$ and $J/\psi\omega$. The predicted states are virtual sta

Chuheng Wei, Guoyuan Wu, Matthew J. Barth

A significant challenge in the field of object detection lies in the system's performance under non-ideal imaging conditions, such as rain, fog, low illumination, or raw Bayer images that lack ISP processing. Our study introduces "Feature Corrective Transfer Learning", a novel approach that leverages transfer learning and a bespoke loss function to facilitat

Weiyu Guo, Ziyue Qiao, Ying Sun, Hui Xiong

Gesture recognition based on surface electromyography (sEMG) has been gaining importance in many 3D Interactive Scenes. However, sEMG is easily influenced by various forms of noise in real-world environments, leading to challenges in providing long-term stable interactions through sEMG. Existing methods often struggle to enhance model noise resilience throug

Yuezhou Zhang, Amos A. Folarin, Yatharth Ranjan, Nicholas Cummins

Prior research has shown that changes in seasons and weather can have a significant impact on depression severity. However, findings are inconsistent across populations, and the interplay between weather, behavior, and depression has not been fully quantified. This study analyzed real-world data from 428 participants (a subset; 68.7% of the cohort) in the RA

Rafael Celestre, Laurene Quenot, Christopher Ninham, Emmanuel Brun

X-ray speckles have been used for a wide variety of experiments, ranging from imaging (and tomography), wavefront sensing, spatial coherence measurements all the way to x-ray photon correlation spectroscopy (XPCS) and ptychography. In the near-field regime, x-ray speckle-grains preserve shape and size under free-space propagation for a static random modulati

Alexey Teplinsky

We show the equivalence of two possible definitions of a rotational interval exchange transformation: by the first one, it is a first return map for a circle rotation onto a union of finite number of circle arcs, and by the second one, it is an interval exchange with a scheme (in the sense of interval rearrangement ensembles), whose dual is an interval excha

Chunhui Bao, Jianghui Ji, Dongjie Tan, Guo Chen

The Closeby Habitable Exoplanet Survey (CHES) is dedicated to the astrometric exploration for habitable-zone Earth-like planets orbiting solar-type stars in close proximity, achieving unprecedented micro-arcsecond precision. Given the elevated precision, thorough consideration of photocenter jitters induced by stellar activity becomes imperative. This study

Hongzhao Li, Hongyu Wang, Xia Sun, Hua He

Medical report generation automates radiology descriptions from images, easing the burden on physicians and minimizing errors. However, current methods lack structured outputs and physician interactivity for clear, clinically relevant reports. Our method introduces a prompt-guided approach to generate structured chest X-ray reports using a pre-trained large

Nils Ole Breuer, Andreas Sauter, Majid Mohammadi, Erman Acar

As Artificial Intelligence (AI) is having more influence on our everyday lives, it becomes important that AI-based decisions are transparent and explainable. As a consequence, the field of eXplainable AI (or XAI) has become popular in recent years. One way to explain AI models is to elucidate the predictive importance of the input features for the AI model i

Abel Jansma

Relating macroscopic observables to microscopic interactions is a central challenge in the study of complex systems. While current approaches often focus on pairwise interactions, a complete understanding requires going beyond these to capture the full range of possible interactions. We present a unified mathematical formalism, based on the M\"obius inversio

Yichi Zhang, Yinpeng Dong, Siyuan Zhang, Tianzan Min

Although Multimodal Large Language Models (MLLMs) have demonstrated promising versatile capabilities, their performance is still inferior to specialized models on downstream tasks, which makes adaptation necessary to enhance their utility. However, fine-tuning methods require independent training for every model, leading to huge computation and memory overhe

Haoxiang Deng, Yi Zhu, Ye Wang, Jipeng Qiang

Clickbaits are surprising social posts or deceptive news headlines that attempt to lure users for more clicks, which have posted at unprecedented rates for more profit or commercial revenue. The spread of clickbait has significant negative impacts on the users, which brings users misleading or even click-jacking attacks. Different from fake news, the crucial

Kavitha Raju, Nandini J. Warrier, Manu Madhavan, Selvi C.

The classical dances from India utilize a set of hand gestures known as Mudras, serving as the foundational elements of its posture vocabulary. Identifying these mudras represents a primary task in digitizing the dance performances. With Kathakali, a dance-drama, as the focus, this work addresses mudra recognition by framing it as a 24-class classification p

Linjie Song, Wenming Zou

We develop a new framework to prove the existence of two positive solutions with prescribed mass on star-shaped bounded domains: one is the normalized ground state and another is of M-P type. We merely address the Sobolev critical cases since the Sobolev subcritical ones can be addressed by following similar arguments and are easier. Our framework is based o

R. Iaria, T. Di Salvo, A. Anitra, C. Miceli

XTE J1710-281 is a transient eclipsing binary system with a period close to 3.28 hours, hosting a neutron star. The average eclipse duration is 420 seconds, and eclipse arrival times reported in the literature span from 1999 to 2017. A previous analysis of the eclipse arrival times using the eclipse timing technique revealed a complex pattern of delays, indi

Zhenhua Liu, Zhiwei Hao, Kai Han, Yehui Tang

Compact neural networks are specially designed for applications on edge devices with faster inference speed yet modest performance. However, training strategies of compact models are borrowed from that of conventional models at present, which ignores their difference in model capacity and thus may impede the performance of compact models. In this paper, by s

Shaomu Tan, Di Wu, Christof Monz

Training a unified multilingual model promotes knowledge transfer but inevitably introduces negative interference. Language-specific modeling methods show promise in reducing interference. However, they often rely on heuristics to distribute capacity and struggle to foster cross-lingual transfer via isolated modules. In this paper, we explore intrinsic task

Robert E. Tench, Jean-Marc Delavaux, Wiktor Walasik, Alexandre Amavigan

We report the design and demonstration of novel 2 $\mu$m band Watt-level fiber amplifiers, fiber lasers, and wideband ASE sources that are pumped with broad spectrum Watt-level ASE sources instead of conventional fiber laser pumps. We show good agreement between the simulations and experimental results for the performance of a single-stage Ho-doped fiber amp

Arijit Panda, Debashis Gangopadhyay, Goutam Manna

We show that the Raychaudhuri equation remains form invariant for certain solutions of scalar fields $\phi$ whose Lagrangian is non-canonical and of the form $\mathcal{L}(X,\phi)=-V(\phi)F(X)$, with $X=\frac{1}{2} g_{\mu\nu} \nabla^{\mu}\phi \nabla^{\nu} \phi$ and $V(\phi)$ the potential. Solutions exist for both homogeneous and inhomogeneous fields that are

Han Huang, Ziqian Lin, Dongchen He, Liang Hong

RNA design shows growing applications in synthetic biology and therapeutics, driven by the crucial role of RNA in various biological processes. A fundamental challenge is to find functional RNA sequences that satisfy given structural constraints, known as the inverse folding problem. Computational approaches have emerged to address this problem based on seco

M. Hashem Pesaran, Andreas Pick, Allan Timmermann

We provide a comprehensive examination of the predictive performance of panel forecasting methods based on individual, pooling, fixed effects, and empirical Bayes estimation, and propose optimal weights for forecast combination schemes. We consider linear panel data models, allowing for weakly exogenous regressors and correlated heterogeneity. We quantify th

Yingzhi Du, Tao Luo

For the initial boundary problem of the incompressible MHD equations in a bounded domain with general curved boundary in 3D with the general Navier-slip boundary conditions for the velocity field and the perfect conducting condition for the magnetic field, we establish the uniform regularity of conormal Sobolev norms and Lipschitz norms to addressing the ani

Taro Nagao

It is well-known that two-dimensional Coulomb gases at a special inverse temperature $\beta = 2$ can be analyzed by using the orthogonal polynomial method borrowed from the theory of random matrices. In this paper, such Coulomb gas molecules are studied when they are distributed on an elliptic annulus, and the asymptotic forms of the molecule correlation fun

M. P. K. Frewein, J. K. Mason, B. Maier, H. Cölfen

The crystallographic texture is a key organization feature of many technical and biological materials. In these materials, especially hierarchically structured ones, the preferential alignment of the nano constituents is heavily influencing the macroscopic behaviour of the material. In order to study local crystallographic texture with both high spatial and

Florent Koudohode, Nikolaos Bekiaris-Liberis

We develop a switched predictor-feedback law, which achieves global asymptotic stabilization of linear systems with input delay and with the plant and actuator states available only in (almost) quantized form. The control design relies on a quantized version of the nominal predictor-feedback law for linear systems, in which quantized measurements of the plan

Miao Cai, Mingyuan Chen, Jiangshan Tang, Keyu Xia

Indistinguishability of single photons from independent sources is critically important for scalable quantum technologies. We provide a comprehensive comparison of single-photon indistinguishability of different kinds of cavity quantum electrodynamics (CQED) systems by numerically simulating Hong-Ou-Mandel (HOM) two-photon interference. We find that the CQED

Pascal Wolf, Dennis Sauerland, Reinhard Beck, Jochen Dingfelder

A proton irradiation site for silicon detectors has been developed and commissioned at the Bonn Isochronous Cyclotron. The accelerator provides 14 MeV proton beams of up to 1 $\mu$A at beam widths of a few mm to the setup. Devices Under Test (DUTs) are irradiated inside a cooled, thermally-insulated box at $\le$-20{\deg}C, while being moved through the beam

Dimitri Breda, Davide Liessi

We propose a numerical method for computing the Lyapunov exponents of renewal equations (delay equations of Volterra type), consisting first in applying a discrete QR technique to the associated evolution family suitably posed on a Hilbert state space and second in reducing to finite dimension each evolution operator in the obtained time sequence. The reduct

Luigi Ambrosio, Toni Ikonen, Danka Lučić, Enrico Pasqualetto

This is the first of two works concerning the Sobolev calculus on metric measure spaces and its applications. In this work, we focus on several notions of metric Sobolev space and on their equivalence. More precisely, we give a systematic presentation of first-order $p$-Sobolev spaces, with $p\in[1,\infty)$, defined over a complete and separable metric space

Krzysztof Gogol, Johnnatan Messias, Maria Ines Silva, Benjamin Livshits

Late 2023 witnessed significant user activity on EVM chains, resulting in a surge in transaction activity and putting many rollups into the first live test. While some rollups performed well, some others experienced downtime during this period, affecting transaction finality time and gas fees. To address the lack of empirical research on rollups, we perform

Guy Henniart, Marie-France Vignéras

Let $p$ be a prime number, $F $ a non-archimedean local field with residue characteristic $p$, and $R$ an algebraically closed field of characteristic different from $ p$. We thoroughly investigate the irreducible smooth $R$-representations of $SL_2(F)$. The components of an irreducible smooth $R$-representation $\Pi$ of $GL_2(F)$ restricted to $SL_2(F)$ for

Markus Blothe, Alessandro Alberucci, Namig Alasgarzade, Maxime Chambonneau

In this paper, picosecond laser inscription of segmented waveguides in crystalline silicon based on a deterministic single-pulse modification process is demonstrated.Pulses of 43 ps duration at 1.55 ${\mu}$m wavelength are used to transversely inscribe periodic structures with a pulse-to-pulse pitch of around 2 ${\mu}$m. Infrared shadowgraphy images and Rama

Andrea Lucchini

In a recent paper Cameron, Lakshmanan and Ajith began an exploration of hypergraphs defined on algebraic structures, especially groups, to investigate whether this can add a new perspective. Following their suggestions, we consider suitable hypergraphs encoding the generating properties of a finite group. In particular, answering a question asked in their pa

Adrian Kulmburg, Lukas Schäfer, Matthias Althoff

The zonotope containment problem, i.e., whether one zonotope is contained in another, is a central problem in control theory. Applications include detecting faults and robustifying controllers by computing invariant sets, and obtain fixed points in reachability analysis. Despite the inherent co-NP-hardness of this problem, an approximation algorithm develope

Joonho Yang, Seunghyun Yoon, Byeongjeong Kim, Hwanhee Lee

Through the advent of pre-trained language models, there have been notable advancements in abstractive summarization systems. Simultaneously, a considerable number of novel methods for evaluating factual consistency in abstractive summarization systems has been developed. But these evaluation approaches incorporate substantial limitations, especially on refi

Giorgos Korkidis, Vasiliki Pavlidou

Density profiles are important tools in galaxy cluster research, offering insights into clusters dynamical states and their relationship with the broader Universe. While these profiles provide valuable information about the matter content of the Universe, their utility in understanding its dark energy component has remained limited due a lack of tools allowi

Stefano Gariazzo, William Giarè, Olga Mena, Eleonora Di Valentino

We present model-marginalized limits on the six standard $\Lambda$CDM cosmological parameters ($\Omega_{\rm c} h^2$, $\Omega_{\rm b} h^2$, $\theta_{\rm MC}$, $\tau_{\rm reio}$, $n_s$ and $A_s$), as well as on selected derived quantities ($H_0$, $\Omega_{\rm m}$, $\sigma_8$, $S_8$ and $r_{\rm drag}$), obtained by considering several extensions of the $\Lambda

Chuheng Wei, Guoyuan Wu, Matthew J. Barth, Amr Abdelraouf

Reliable prediction of vehicle trajectories at signalized intersections is crucial to urban traffic management and autonomous driving systems. However, it presents unique challenges, due to the complex roadway layout at intersections, involvement of traffic signal controls, and interactions among different types of road users. To address these issues, we pre

Jiajie Zhu, Yan Wang, Feng Zhu, Zhu Sun

In recent years, dual-target Cross-Domain Recommendation (CDR) has been proposed to capture comprehensive user preferences in order to ultimately enhance the recommendation accuracy in both data-richer and data-sparser domains simultaneously. However, in addition to users' true preferences, the user-item interactions might also be affected by confounders (e.

Jonathan M. Fraser, Ana E. de Orellana

Marstrand's celebrated projection theorem gives the Hausdorff dimension of the orthogonal projection of a Borel set in Euclidean space for almost all orthogonal projections. It is straightforward to see that sets for which the Fourier and Hausdorff dimension coincide have no exceptional projections, that is, \emph{all} orthogonal projections satisfy the conc

C. I. Eze, G. Handler

Asteroseismology coupled with eclipsing binary modelling shows a great potential in improving the efficiency of measurements or calibrations of the interior mixing profile in massive stars. This helps, for instance in treating the challenging and mysterious discrepancies between observations and models of its stellar structure and evolution. This paper discu

Yuxiang Yang

Shallow quantum circuits feature not only computational advantages over their classical counterparts but also cutting-edge applications. Storing quantum information generated by shallow circuits is a fundamental question of both theoretical and practical importance that remained largely unexplored. In this work, we show that $N$ copies of an unknown $n$-qubi

Jakub Löwit

In 1976, Deligne and Lusztig realized the representation theory of finite groups of Lie type inside \'etale cohomology of certain algebraic varieties. Recently, a $p$-adic version of this theory started to emerge: there are $p$-adic Deligne-Lusztig spaces, whose cohomology encodes representation theoretic information for $p$-adic groups - for instance, it pa

Muchun Yang, D. L. Zhou

Quantum distillation is a modern technology to decrease the von Neumann entropy of a subsystem by coherent system dynamics. Here we propose an active quantum distillation protocol, in which a bang-bang theme is applied to actively control the coherent dynamics of our system in order to obtain a subsystem with the von Neumann entropy as low as possible. For a

Thomas Christiansen, Katrin Grunert

We propose a new numerical method for $\alpha$-dissipative solutions of the Hunter-Saxton equation, where $\alpha$ belongs to $W^{1, \infty}(\mathbb{R}, [0, 1))$. The method combines a projection operator with a generalized method of characteristics and an iteration scheme, which is based on enforcing minimal time steps whenever breaking times cluster. Numer

Sebastian Schmutzhard-Höfler

We explore integrals of products of Legendre polynomials with a logarithmic weight function. More precisely, for Legendre polynomials $P_m$ and $P_n$ of orders $m$ and $n$, respectively, we provide simple derivations of the integrals $$\int \limits_0^1 P_n(2x-1) P_m(2x-1)\log (x)dx.$$

Emanuele La Malfa, Gabriele La Malfa, Giuseppe Nicosia, Vito Latora

Deep Neural Networks (DNNs) can be represented as graphs whose links and vertices iteratively process data and solve tasks sub-optimally. Complex Network Theory (CNT), merging statistical physics with graph theory, provides a method for interpreting neural networks by analysing their weights and neuron structures. However, classic works adapt CNT metrics tha

Donald C. Chang

Science is about facts and truth. Yet sometimes the truth and facts are not obvious. For example, in the field of MRI (Magnetic Resonance Imaging), there has been a long-lasting debate about who were the major contributors in its development. Particularly, there was a strong dispute between the followers of two scientists, R. Damadian and P. Lauterbur. In th

Yaojun Hu, Jintai Chen, Lianting Hu, Dantong Li

Heart diseases rank among the leading causes of global mortality, demonstrating a crucial need for early diagnosis and intervention. Most traditional electrocardiogram (ECG) based automated diagnosis methods are trained at population level, neglecting the customization of personalized ECGs to enhance individual healthcare management. A potential solution to

Jichu Jiang

Birthday problem is a well-known classic problem in probability theory widely applied in cryptography, and bubble sort is a popular sorting algorithm leading to some interesting theoretical problems in computer science. However, the relation between bubble sort and birthday problem has not been discovered. By relating bubble sort to birthday problem, based o

Marco Barletta, Marcello Cinque, Catello Di Martino, Zbigniew T. Kalbarczyk

In this paper, we i) analyze and classify real-world failures of Kubernetes (the most popular container orchestration system), ii) develop a framework to perform a fault/error injection campaign targeting the data store preserving the cluster state, and iii) compare results of our fault/error injection experiments with real-world failures, showing that our f

Sunan Zhang, Taixia Shi, Lizhong Jiang, Yang Chen

A microwave photonic short-time Fourier transform (STFT) system based on stabilized period-one (P1) nonlinear laser dynamics and stimulated Brillouin scattering (SBS) is proposed. By using an optoelectronic feedback loop, the frequency-sweep optical signal generated by the P1 nonlinear laser dynamics is stabilized, which is further used in conjunction with a

Xin Guo, Jiacheng Zhang

Motivated by recent development of mean-field systems with common noise, this paper establishes Ito's formula for flows of conditional probability measures under a common filtration associated with general semimartingales. This generalizes existing works on flows of conditional measures on Ito processes and flows of deterministic measure on general semimarti

W. J. Pearson, V. Rodriguez-Gomez, S. Kruk, B. Margalef-Bentabol

Aims. This work aims to reproduce the time before or after a merger event of merging galaxies from the IllustrisTNG cosmological simulation using machine learning. Methods. Images of merging galaxies were created in the u, g, r, and i bands from IllustrisTNG. The merger times were determined using the time difference between the last simulation snapshot wher

Maolin Dai, Bowen Liu, Yifan Ma, Takuma Shirahata

We demonstrate a 783-MHz fundamental repetition rate mode-locked Er-doped all-fiber ring laser with a pulse width of 623 fs. By using carbon nanotubes (CNT) saturable absorber (SA), a relatively low self-starting pump threshold of 108 mW is achieved. The laser has a very compact footprint less than 10 cm * 10 cm, benefiting from the all-active-fiber cavity d

Fabián Aguirre-López

We study the dynamics of the generalized Lotka-Volterra model with a network structure. Performing a high connectivity expansion for graphs, we write down a mean-field dynamical theory that incorporates degree heterogeneity. This allows us to describe the fixed points of the model in terms of a few simple order parameters. We extend the analysis even for div

Zicheng Liu, Li Wang, Siyuan Li, Zedong Wang

Transformer models have been successful in various sequence processing tasks, but the self-attention mechanism's computational cost limits its practicality for long sequences. Although there are existing attention variants that improve computational efficiency, they have a limited ability to abstract global information effectively based on their hand-crafted

Zhuo Diao, Keiichi Ueda, Linfeng Hou, Fengxuan Li

We present an advanced scanning probe microscopy system enhanced with artificial intelligence (AI-SPM) designed for self-driving atomic-scale measurements. This system expertly identifies and manipulates atomic positions with high precision, autonomously performing tasks such as spectroscopic data acquisition and atomic adjustment. An outstanding feature of

Jun Wang, Yu Mao, Yufei Cui, Nan Guan

Pre-processing whole slide images (WSIs) can impact classification performance. Our study shows that using fixed hyper-parameters for pre-processing out-of-domain WSIs can significantly degrade performance. Therefore, it is critical to search domain-specific hyper-parameters during inference. However, searching for an optimal parameter set is time-consuming.

Jessica López Espejel, Mahaman Sanoussi Yahaya Alassan, Merieme Bouhandi, Walid Dahhane

Large Language Models (LLMs) have become a popular choice for many Natural Language Processing (NLP) tasks due to their versatility and ability to produce high-quality results. Specifically, they are increasingly used for automatic code generation to help developers tackle repetitive coding tasks. However, LLMs' substantial computational and memory requireme

Nicolas Chahine, Marcos V. Conde, Daniela Carfora, Gabriel Pacianotto

This paper reviews the NTIRE 2024 Portrait Quality Assessment Challenge, highlighting the proposed solutions and results. This challenge aims to obtain an efficient deep neural network capable of estimating the perceptual quality of real portrait photos. The methods must generalize to diverse scenes and diverse lighting conditions (indoor, outdoor, low-light

Alexey Nefediev

Recent data for the masses of $D$ and $D^*$ mesons determined using methods of lattice QCD for several values of the charm quark mass different from its physical mass are analysed in Heavy Quark Effective Theory. Nonperturbative parameters are extracted that arise at order ${\cal O}(1/m_c)$ in the heavy-quark mass expansion of a heavy-light meson mass. The d

Jingjun You, Su Yi, Yuangang Deng

Ultracold atoms with cavity-mediated long-range interactions offer a promising platform for investing novel quantum phenomena. Exploiting recent experimental advancements, we propose an experimental scheme to create self-ordered supersolid in spin-$1/2$ condensates confined within an optical cavity. The interplay of cavity and pump fields gives rise to super

Chunghyun Park, Seungwook Kim, Jaesik Park, Minsu Cho

Establishing accurate 3D correspondences between shapes stands as a pivotal challenge with profound implications for computer vision and robotics. However, existing self-supervised methods for this problem assume perfect input shape alignment, restricting their real-world applicability. In this work, we introduce a novel self-supervised Rotation-Invariant 3D

Chi Zhang, Qi Song, Feifei Li, Jie Li

The construction of vectorized High-Definition (HD) maps from onboard surround-view cameras has become a significant focus in autonomous driving. However, current map vector estimation pipelines face two key limitations: input-agnostic queries struggle to capture complex map structures, and the view transformation leads to information loss. These issues ofte

Liye Cao, Cuiwei Zhang, Yi Yang, Lei Wang

Utilizing ultrafast time-resolved pump-probe spectroscopy measurements, we investigate the photoinduced quasiparticle dynamics of the topological materials LaSbTe and CeSbTe. In LaSbTe, the relaxation of quasiparticles is dominated by two different mechanisms: electron-phonon coupling, and phonon-assisted electron-hole recombination. Significantly, the ampli

Riccardo Borghi

The description of light diffraction using catastrophe optics is one of the most intriguing theoretical invention in the field of classical optics of the last four decades. Its practical implementation has faced some resistance over the years, mainly due to the difficulty of mathematically decorating the different, topologically speaking, types of optical si

Abdullah F. Al-Battal, Soan T. M. Duong, Van Ha Tang, Quang Duc Tran

Multi-phase computed tomography (CT) scans use contrast agents to highlight different anatomical structures within the body to improve the probability of identifying and detecting anatomical structures of interest and abnormalities such as liver lesions. Yet, detecting these lesions remains a challenging task as these lesions vary significantly in their size

Chaoyue Song, Jiacheng Wei, Chuan-Sheng Foo, Guosheng Lin

In this paper, we address the challenge of reconstructing general articulated 3D objects from a single video. Existing works employing dynamic neural radiance fields have advanced the modeling of articulated objects like humans and animals from videos, but face challenges with piece-wise rigid general articulated objects due to limitations in their deformati

Simon Stock, Davood Babazadeh, Sari Eid, Christian Becker

The vanishing inertia of synchronous generators in transmission systems requires the utilization of renewables for inertial support. These are often connected to the distribution system and their support should be coordinated to avoid violation of grid limits. To this end, this paper presents the Physics-informed Actor-Critic (PI-AC) algorithm for coordinati

Nantika Nguycharoen

As the global population ages, the incidence of Chronic Kidney Disease (CKD) is rising. CKD often remains asymptomatic until advanced stages, which significantly burdens both the healthcare system and patient quality of life. This research developed an explainable machine learning system for predicting CKD in patients with cardiovascular risks, utilizing med

Ciprian A Tudor, Jérémy Zurcher

Let $\left(u(t,x), t\geq 0, x\in \mathbb{R}^d\right)$ be the solution to the stochastic heat or wave equation driven by a Gaussian noise which is white in time and white or correlated with respect to the spatial variable. We consider the spatial average of the solution $F_{R}(t)= \frac{1}{\sigma_R}\int_{\vert x\vert \leq R} \left( u(t,x)-1\right) dx$, where

Deparis Jacques, Gance Julien, Orlando Leite

Electrical Resistivity Tomography (ERT) has become widely used for engineering and environmental applications in the last couple of decades due to (1) the simplification and automating of resistivity meters and (2) the new generation of inversion software. Although the initial domain of application remain relevant today, these techniques are increasingly use

Si-Nuo Li, Liang Tang

Inspired by the recent experimental progress on the $T_{c\bar{s}0}^a(2900)^{0/++}$, the fully open tetraquark spectrum with the configuration of $[8]_{[c\bar{s}]} \otimes [8]_{[q \bar{q^\prime}]}$ is systematically investigated by the QCD sum rules. In this article, we concentrate on the quantum numbers $J^{P}=0^{+}/0^{-}/1^{+}/1^{-}$. Firstly, we construct

Pengdeng Li, Shuxin Li, Chang Yang, Xinrun Wang

Policy-Space Response Oracles (PSRO) as a general algorithmic framework has achieved state-of-the-art performance in learning equilibrium policies of two-player zero-sum games. However, the hand-crafted hyperparameter value selection in most of the existing works requires extensive domain knowledge, forming the main barrier to applying PSRO to different game

Navve Wasserman, Roman Beliy, Roy Urbach, Michal Irani

Combining Functional MRI (fMRI) data across different subjects and datasets is crucial for many neuroscience tasks. Relying solely on shared anatomy for brain-to-brain mapping is inadequate. Existing functional transformation methods thus depend on shared stimuli across subjects and fMRI datasets, which are often unavailable. In this paper, we propose an app

Romain Rouyer, David Bourguignon, Stéphanie Fleck

This research project aims to promote ethical principles among designers engaged in adaptive-XR by providing tools for self-assessment. We introduce a Design-Based Research (DBR) methodology to build bRight-XR, a framework including a heuristic evaluation matrix and based on learning theory.

Barbara Gendron, Gaël Guibon

The advent of deep learning models has made a considerable contribution to the achievement of Emotion Recognition in Conversation (ERC). However, this task still remains an important challenge due to the plurality and subjectivity of human emotions. Previous work on ERC provides predictive models using mostly graph-based conversation representations. In this

Doina Pisla, Paul Tucan, Damien Chablat, Nadim Al Hajjar

The paper presents the methodology used for accuracy and repeatability measurements of the experimental model of a parallel robot developed for surgical applications. The experimental setup uses a motion tracking system (for accuracy) and a high precision measuring arm for position (for repeatability). The accuracy was obtained by comparing the trajectory da

Linfang Zheng, Tze Ho Elden Tse, Chen Wang, Yinghan Sun

Object pose refinement is essential for robust object pose estimation. Previous work has made significant progress towards instance-level object pose refinement. Yet, category-level pose refinement is a more challenging problem due to large shape variations within a category and the discrepancies between the target object and the shape prior. To address thes

M Spite, P Bonifacio, E Caffau, P François

The aim of this work is to measure the abundances of n-capture elements in a sample of six metal-poor N-rich dwarfs that were formed in globular clusters, and subsequently became unbound from the cluster. These N-rich stars, HD 25329, HD 74000, HD 160617, G 24-3, G 53-41, and G 90-3, were previously studied in Paper I. The abundances of the n-capture element

Giulia Pozzi, Davide Ambrosi, Simone Pezzuto

Active solids are a large class of materials, including both living soft tissues and artificial matter, that share the ability to undergo strain even in absence of external loads. While in engineered materials the actuation is typically designed a priori, in natural materials it is an unknown of the problem. In such a framework, the identification of inactiv

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

In this paper, we investigate the application of hexagonal quadrature amplitude modulation (HQAM) in reconfigurable intelligent surface (RIS)-assisted networks, specifically focusing on its efficiency in reducing the number of required reflecting elements. Specifically, we present analytical expressions for the average symbol error probability (ASEP) and pro

Michal Elkind, Noam Popper, Itamar Cohen, Aviv Levinson

We report on an experimental study of proton acceleration by intense laser irradiation of micrometric bar targets, whose dimensions are transversely immersed in the laser focal volume and are longitudinally smaller than half its wavelength. With only 120 mJ of laser energy, we recorded proton energies in excess of 6~MeV, three times higher than those achieve

Juncheng Wei, Zikai Ye, Xiaoyu Zeng, Qidi Zhang

We consider the following five-dimensional heat equation with critical boundary condition \begin{equation*} \partial_t u=\Delta u \mbox{ \ in \ } \mathbb{R}_+^5\times (0,T) , \quad -\partial_{x_5}u =|u|^\frac{2}{3}u \mbox{ \ on \ } \pp \mathbb{R}^5_+ \times (0,T) . \end{equation*} Given $\mathfrak{o}$ distinct boundary points $q^{[i]} \in \partial \mathbb{R}

Jiang Yan, Xing-Gang Wu, Hua Zhou, Hong-Tai Li

In this paper, we analyze the top-quark decay $t\to Wb$ up to next-to-next-to-next-to-leading order (N$^{3}$LO) QCD corrections. For the purpose, we first adopt the principle of maximum conformality (PMC) to deal with the initial pQCD series. Then we adopt the Bayesian analysis approach, which quantifies the unknown higher-order terms' contributions in terms

Bin Zhang, Junli Wang

ICD(International Classification of Diseases) coding involves assigning ICD codes to patients visit based on their medical notes. ICD coding is a challenging multilabel text classification problem due to noisy medical document inputs. Recent advancements in automated ICD coding have enhanced performance by integrating additional data and knowledge bases with

Jinyulin Li, Qing Li, Jinjin Liu, Ying Xiang

There is a common belief that superconductivity and charge density wave (CDW) order accommodate homogenously in real space but compete with each other for the effective density of states in momentum space in CDW superconductors. By measuring resistivity along the $c$-axis in Cs(V$_{1-x}$Ta$_{x}$)$_{3}$Sb$_{5}$, we observe strong superconducting fluctuation b