October 2023 arXiv papers — page 136

Zijian Yang, Wei Zhou, Ralf Schlüter, Hermann Ney

In this work, we investigate the effect of language models (LMs) with different context lengths and label units (phoneme vs. word) used in sequence discriminative training for phoneme-based neural transducers. Both lattice-free and N-best-list approaches are examined. For lattice-free methods with phoneme-level LMs, we propose a method to approximate the con

Pedro Carrilho, Chiara Moretti, Maria Tsedrik

The current discrepancy between the CMB and weak lensing measurements of the amplitude of matter fluctuations, the so-called $S_8$ tension, has attracted a great deal of recent attention, as it may show a crack in the $\Lambda$CDM model of cosmology. We review the evidence for this tension and describe potential solutions, focusing on extensions of the stand

Zihan Zhang, Meng Fang, Ling Chen, Mohammad-Reza Namazi-Rad

Although large language models (LLMs) are impressive in solving various tasks, they can quickly be outdated after deployment. Maintaining their up-to-date status is a pressing concern in the current era. This paper provides a comprehensive review of recent advances in aligning LLMs with the ever-changing world knowledge without re-training from scratch. We c

S. Hageboeck, A. Reinsvold Hall, N. Skidmore, G. A. Stewart

In this paper we document the current analysis software training and onboarding activities in several High Energy Physics (HEP) experiments: ATLAS, CMS, LHCb, Belle II and DUNE. Fast and efficient onboarding of new collaboration members is increasingly important for HEP experiments as analyses and the related software become ever more complex with growing da

Sasa Prelovsek

Lattice QCD results on hadrons with heavy quarks are briefly reviewed. The focus is on the spectrum of conventional and exotic hadrons. Structure of certain conventional hadrons is addressed as well.

Cezar Joiţa, Matteo Stockinger, Mihai Tibăr

We give analytic and algebraic conditions under which a deformation of real analytic functions with non-isolated singular locus is a deformation with fibre constancy.

David Cintas

The goal of the ANAIS-112 experiment, which operates at LSC, is to test in a model independent way the DAMA/LIBRA positive signal using the same target (NaI(Tl) crystals) and technique. Several strategies have been followed in this work to improve the sensitivity of the ANAIS-112 experiment. The Quenching Factor (QF) is a key factor in the comparison between

Xumeng Wen, Han Zhang, Shun Zheng, Wei Xu

Tabular data is foundational to predictive modeling in various crucial industries, including healthcare, finance, retail, sustainability, etc. Despite the progress made in specialized models, there is an increasing demand for universal models that can transfer knowledge, generalize from limited data, and follow human instructions. These are challenges that c

Dennis Lehmkuhl, Christian Röken, Juliusz Doboszewski

We present a detailed analysis of Penrose's gravito-optical analogy between the focusing effects of particular families of Ricci- and Weyl-curved spacetime regions on the one hand, and anastigmatic and astigmatic optical lenses on the other. We put the analogy in its historical context, investigate its underlying assumptions, its range of validity, its proof

Shikha Awasthi, Anil Khachi, Lalit Kumar, O. S. K. S. Sastri

In this article, we propose a numerical approach to solve quantum mechanical scattering problems, using phase function method, by considering neutron-proton interaction as an example. The nonlinear phase equation, obtained from the time-independent Schrodinger equation, is solved using the Runge-Kutta method for obtaining S-wave scattering phase shifts for n

Haibo Qiu, Baosheng Yu, Yixin Chen, Dacheng Tao

Significant progress has been made recently in point cloud segmentation utilizing an encoder-decoder framework, which initially encodes point clouds into low-resolution representations and subsequently decodes high-resolution predictions. Inspired by the success of high-resolution architectures in image dense prediction, which always maintains a high-resolut

Junaid Ahmed Ansari, Satyajit Tourani, Gourav Kumar, Brojeshwar Bhowmick

This work proposes a novel approach to social robot navigation by learning to generate robot controls from a social motion latent space. By leveraging this social motion latent space, the proposed method achieves significant improvements in social navigation metrics such as success rate, navigation time, and trajectory length while producing smoother (less j

Ulrich Achatz, Young-Ha Kim, Georg Sebastian Voelker

The interaction between small-scale waves and a larger-scale flow can be described by a multi-scale theory that forms the basis for a new class of parameterizations of subgrid-scale gravity waves (GW) in weather and climate models. The development of this theory is reviewed here. It applies to all interesting regimes of atmospheric stratification, i.e. also

Alexandros Hollender, Chester Lawrence, Erel Segal-Halevi

Given a function f: [a,b] -> R, if f(a) < 0 and f(b)> 0 and f is continuous, the Intermediate Value Theorem implies that f has a root in [a,b]. Moreover, given a value-oracle for f, an approximate root of f can be computed using the bisection method, and the number of required evaluations is polynomial in the number of accuracy digits. The goal of this note

Thomas Pfeil, Til Birnstiel, Hubert Klahr

Protoplanetary disks exhibit a vertical gradient in angular momentum, rendering them susceptible to the Vertical Shear Instability (VSI). The most important condition for the onset of this mechanism is a short timescale of thermal relaxation ($\lesssim 0.1$ orbital timescales). Simulations of fully VSI active disks are characterized by turbulent, vertically

Anjiao Gu, Yajuan Sun

In high-temperature plasma physics, a strong magnetic field is usually used to confine charged particles. Therefore, for studying the classical mathematical models of the physical problems it needs to consider the effect of external magnetic fields. One of the important model equations in plasma is the Vlasov-Poisson equation with an external magnetic field.

Lucas Sort, Laurent Le Brusquet, Arthur Tenenhaus

In this paper, we introduce Functional Generalized Canonical Correlation Analysis (FGCCA), a new framework for exploring associations between multiple random processes observed jointly. The framework is based on the multiblock Regularized Generalized Canonical Correlation Analysis (RGCCA) framework. It is robust to sparsely and irregularly observed data, mak

Tom Barnowsky, Stefano Curtarolo, Arkady V. Krasheninnikov, Thomas Heine

Controlling the magnetic state of two-dimensional (2D) materials is crucial for spintronic applications. By employing data-mining and autonomous density functional theory calculations, we demonstrate the switching of magnetic properties of 2D non-van der Waals materials upon hydrogen passivation. The magnetic configurations are tuned to states with flipped a

Qingyi Si, Tong Wang, Zheng Lin, Xu Zhang

The success of ChatGPT validates the potential of large language models (LLMs) in artificial general intelligence (AGI). Subsequently, the release of LLMs has sparked the open-source community's interest in instruction-tuning, which is deemed to accelerate ChatGPT's replication process. However, research on instruction-tuning LLMs in Chinese, the world's mos

Lionel Morel, Damien Couroussé, Thomas Hiscock

In this paper, we consider that, in practice, attack scenarios involving side-channel analysis combine two successive phases:an analysis phase, targeting the extraction of information about the target and the identification of possible vulnerabilities;and an exploitation phase, applying attack techniques on candidate vulnerabilities. We advocate that protect

Ruimin Song, TIntian Zhao, Chunhui Zhou

This paper takes the development of China's Central bank digital currencies as a perspective, theoretically analyses the impact mechanism of the issuance and circulation of Central bank digital currencies on China's monetary policy and various variables of the money multiplier; at the same time, it selects the quarterly data from 2010 to 2022, and examines t

Jett Janiak, Can Rager, James Dao, Yeu-Tong Lau

Prior work suggests that language models manage the limited bandwidth of the residual stream through a "memory management" mechanism, where certain attention heads and MLP layers clear residual stream directions set by earlier layers. Our study provides concrete evidence for this erasure phenomenon in a 4-layer transformer, identifying heads that consistentl

Karim Radouane, Julien Lagarde, Sylvie Ranwez, Andon Tchechmedjiev

Diverse and extensive work has recently been conducted on text-conditioned human motion generation. However, progress in the reverse direction, motion captioning, has seen less comparable advancement. In this paper, we introduce a novel architecture design that enhances text generation quality by emphasizing interpretability through spatio-temporal and adapt

Wei Zheng, Guogang Zhang, Chenchen Zhao, Qianqian Zhu

Power transformer plays a critical role in grid infrastructure, and its diagnosis is paramount for maintaining stable operation. However, the current methods for transformer diagnosis focus on discrete dissolved gas analysis, neglecting deep feature extraction of multichannel consecutive data. The unutilized sequential data contains the significant temporal

Xiaoye Michael Wang, Derek T. Smith, Qin Zhu

Background. Joint range of motion (ROM) is an important quantitative measure for physical therapy. Commonly relying on a goniometer, accurate and reliable ROM measurement requires extensive training and practice. This, in turn, imposes a significant barrier for those who have limited in-person access to healthcare. Objective. The current study presents and e

Amin Dada, Aokun Chen, Cheng Peng, Kaleb E Smith

Traditionally, large language models have been either trained on general web crawls or domain-specific data. However, recent successes of generative large language models, have shed light on the benefits of cross-domain datasets. To examine the significance of prioritizing data diversity over quality, we present a German dataset comprising texts from five do

Jingxuan Zhu, Alec Koppel, Alvaro Velasquez, Ji Liu

In decentralized cooperative multi-armed bandits (MAB), each agent observes a distinct stream of rewards, and seeks to exchange information with others to select a sequence of arms so as to minimize its regret. Agents in the cooperative setting can outperform a single agent running a MAB method such as Upper-Confidence Bound (UCB) independently. In this work

Bixuan Yang, Jinbiao Wu, Tiexin Guo

In this paper, the theory of mean-field backward doubly stochastic Volterra integral equations (MF-BDSVIEs) is studied. First, we derive the well-posedness of M-solutions to MFBDSVIEs, and prove the comparison theorem for such a type of equations. Furthermore, the regularity result of the M-solution for MF-BDSVIEs is established by virtue of Malliavin calcul

Kyosuke Nishibiro

Kaneko and Tsumura introduced the Arakawa-Kaneko type zeta function $\eta(-k_1,\ldots,-k_r;s_1,\ldots,s_r)$ for non-negative integers $k_1,\ldots,k_r$ and complex variables $s_1,\ldots,s_r$. Recently, Yamamoto showed that, by using the multiple integral expression, $\eta(u_1,\ldots,u_r;s_1,\ldots,s_r)$ can be extended to an analytic function of 2$r$ variable

Francesca Aicardi

For each $p>0$ we define by recurrence a triangle $T^p(n,k)$ whose rows sum to the Fuss-Catalan numbers $ \frac{1}{p n+1}\binom{pn+1}{n}$, generalizing the known Catalan triangle corresponding to the case $p=2$. (In fact, $T^p(n,k)$ has an explicit formula counting simple lattice paths). Moreover, for some small values of $p$, the signed sums turn out to be

Yuewei Zhang, Huanbin Zou, Jie Zhu

In speech enhancement (SE), phase estimation is important for perceptual quality, so many methods take clean speech's complex short-time Fourier transform (STFT) spectrum or the complex ideal ratio mask (cIRM) as the learning target. To predict these complex targets, the common solution is to design a complex neural network, or use a real network to separate

Philip Stange, David Ginsbourger

We tackle the extension to the vector-valued case of consistency results for Stepwise Uncertainty Reduction sequential experimental design strategies established in [Bect et al., A supermartingale approach to Gaussian process based sequential design of experiments, Bernoulli 25, 2019]. This lead us in the first place to clarify, assuming a compact index set,

Tommaso Martorella, Antonio Bucchiarone

The digital age is changing the role of educators and pushing for a paradigm shift in the education system as a whole. Growing demand for general and specialized education inside and outside classrooms is at the heart of this rising trend. In modern, heterogeneous learning environments, the one-size-fits-all approach is proven to be fundamentally flawed. Ind

Mikołaj Sacha, Michał Sadowski, Piotr Kozakowski, Ruard van Workum

Retrosynthesis involves determining a sequence of reactions to synthesize complex molecules from simpler precursors. As this poses a challenge in organic chemistry, machine learning has offered solutions, particularly for predicting possible reaction substrates for a given target molecule. These solutions mainly fall into template-based and template-free cat

Mehdi Letafati, Samad Ali, Matti Latva-aho

A comprehensive study on the applications of denoising diffusion models for wireless systems is provided. The article highlights the capabilities of diffusion models in learning complicated signal distributions, modeling wireless channels, and denoising and reconstructing distorted signals. First, fundamental working mechanism of diffusion models is introduc

Anna Chrysostomou, Alan S. Cornell, Aldo Deandrea, Hajar Noshad

Rich physics can be divined from charged black holes subjected to extremal conditions. When applied in conjunction with principles like Weak Cosmic Censorship, this naturally leads to constraints on the mass and charge of the black hole. However, more nuanced principles such as the Weak Gravity Conjecture (WGC) and the recently proposed Festina-Lente (FL) bo

Andrei C. Aioanei, Regine Hunziker-Rodewald, Konstantin Klein, Dominik L. Michels

Epigraphy increasingly turns to modern artificial intelligence (AI) technologies such as machine learning (ML) for extracting insights from ancient inscriptions. However, scarce labeled data for training ML algorithms severely limits current techniques, especially for ancient scripts like Old Aramaic. Our research pioneers an innovative methodology for gener

Cynthia Vidal, Benjamin Tilmann, Sunny Tiwari, T. V. Raziman

Nanoantennas capable of large fluorescence enhancement with minimal absorption are crucial for future optical technologies from single-photon sources to biosensing. Efficient dielectric nanoantennas have been designed, however, evaluating their performance at the individual emitter level is challenging due to the complexity of combining high-resolution nanof

Dai Shi

A theoretical analysis is carried out to study flow evolution inside the laminar Rayleigh-B\'enard convection system laden with small particles. By describing particle dynamics and particle heat as sources of drag and heat respectively, the physics of particle impact on the flow evolution is studied. It is found that due to the relative velocity of the parti

Georgy Alymov, Dmitry Svintsov

Heterostructures comprised of two two-dimensional electron systems (2DES) separated by a dielectric exhibit resonant tunneling when the band structures of both systems are aligned. It is commonly assumed that the height and width of the resonant peak in the tunneling current is determined by electron scattering and rotational misalignment of crystal structur

Aditi Kanwar, Aditi Seetha, Satyendra Singh Chouhan, Rajdeep Niyogi

This paper presents a Soft Labeling and Noisy Mixup-based open intent classification model (SNOiC). Most of the previous works have used threshold-based methods to identify open intents, which are prone to overfitting and may produce biased predictions. Additionally, the need for more available data for an open intent class presents another limitation for th

Jie Cao, Yanhui Qu

In this paper, we find a full Lebesgue measure set of frequencies $\check \II\subset [0,1]\setminus \Q$ such that for any $(\alpha,\lambda)\in \check \II\times [24,\infty)$, the Hausdorff and box dimensions of the spectrum of the Sturmian Hamiltonian $H_{\alpha,\lambda,\theta}$ coincide and are independent of $\alpha$. Denote the common value by $D(\lambda)$

Zongnan Li, Zhiyuan Li, Ruben Garcia-Benito, Yifei Jin

The origin of the low-ionization nuclear emission-line region (LINER) prevalent in local galaxies and its relationship with supermassive black holes are debated for decades. We preform a comprehensive evaluation of traditional photoionization models against the circumnuclear ionized gas in M81, for which recent CAHA/PPAK integral-field spectroscopic observat

Evdokia K. Oikonomou, Jean-François Berret

Fabric softeners are formulated to enhance textile softness and impart a pleasant scent. One of the most efficient technologies for controlled fragrance delivery onto fabrics involves encapsulating scent molecules in polymer capsules. Here, we investigate the adsorption of anionic fragrance cap-sules on cotton fabrics with the goal of reducing the reliance o

Hangyu Yin

In the context of extriangulated categories, we establish the injective version of Schanuel's lemma in homological algebra.

Yuchong Sun, Che Liu, Kun Zhou, Jinwen Huang

Humans often interact with large language models (LLMs) in multi-turn interaction to obtain desired answers or more information. However, most existing studies overlook the multi-turn instruction following ability of LLMs, in terms of training dataset, training method, and evaluation benchmark. In this paper, we introduce Parrot, a solution aiming to enhance

Andrea Batch, Yipeng Ji, Mingming Fan, Jian Zhao

Analyzing user behavior from usability evaluation can be a challenging and time-consuming task, especially as the number of participants and the scale and complexity of the evaluation grows. We propose uxSense, a visual analytics system using machine learning methods to extract user behavior from audio and video recordings as parallel time-stamped data strea

Yue Zhang, Leyang Cui, Enbo Zhao, Wei Bi

Grammatical Error Correction (GEC) systems play a vital role in assisting people with their daily writing tasks. However, users may sometimes come across a GEC system that initially performs well but fails to correct errors when the inputs are slightly modified. To ensure an ideal user experience, a reliable GEC system should have the ability to provide cons

Robin Staab, Mark Vero, Mislav Balunović, Martin Vechev

Current privacy research on large language models (LLMs) primarily focuses on the issue of extracting memorized training data. At the same time, models' inference capabilities have increased drastically. This raises the key question of whether current LLMs could violate individuals' privacy by inferring personal attributes from text given at inference time.

Huayu Chen, Cheng Lu, Zhengyi Wang, Hang Su

Recent developments in offline reinforcement learning have uncovered the immense potential of diffusion modeling, which excels at representing heterogeneous behavior policies. However, sampling from diffusion policies is considerably slow because it necessitates tens to hundreds of iterative inference steps for one action. To address this issue, we propose t

Florian Mannel, Hari Om Aggrawal, Jan Modersitzki

Many inverse problems are phrased as optimization problems in which the objective function is the sum of a data-fidelity term and a regularization. Often, the Hessian of the fidelity term is computationally unavailable while the Hessian of the regularizer allows for cheap matrix-vector products. In this paper, we study an LBFGS method that takes advantage of

Yuewei Zhang, Huanbin Zou, Jie Zhu

The deep learning-based speech enhancement (SE) methods always take the clean speech's waveform or time-frequency spectrum feature as the learning target, and train the deep neural network (DNN) by reducing the error loss between the DNN's output and the target. This is a conventional single-task learning paradigm, which has been proven to be effective, but

Matthieu Alfaro, Philippe Jouan

We consider the Allen-Cahn equation with the so-called truncated Laplacians, which are fully nonlinear differential operators that depend on some eigenvalues of the Hessian matrix. By monitoring the sign of a quantity that is responsible for switches from a first order ODE regime to a second order ODE regime (and vice versa), we give a nearly complete descri

Kala G. Pradeep, Kulinder Pal Singh, G. C. Dewangan, Elias Aydi

We present multi-wavelength temporal and spectral characteristics of a magnetic cataclysmic variable (MCV) Swift J0503.7-2819, using far ultraviolet (FUV) and X-ray data from AstroSat, supplemented with optical data from the Southern African Large Telescope and X-ray data from the XMM-Newton and Swift observatories. The X-ray modulations at 4897.6657 s and 3

Zhiqing Wei, Chenfei Li, Yanpeng Cui, Xu Chen

Mobile Ad hoc Network (MANET), supporting Machine-Type Communication(MTC), has a strong demand for rapid networking. Neighbor Discovery (ND) is a key initial step in configuring MANETs and faces a serious challenge in decreasing convergence time. Integrated Sensing and Communication (ISAC), as one of the potential key technologies in the 6th Generation (6G)

Marco Maggis

\textit{Il significato soggettivo della probabilit\`a} (1931) by B. de Finetti \cite{deF} is unanimously considered the rise of `subjectivism', a notion which strongly influenced both Probability and Decision Theory. What is less acknowledge is that \cite{deF} posed the foundations of modern arbitrage theory. In this paper we aim at examining how de Finetti'

Marco Alecci, Jordan Samhi, Tegawendé F. Bissyandé, Jacques Klein

Numerous tools rely on automatic categorization of Android apps as part of their methodology. However, incorrect categorization can lead to inaccurate outcomes, such as a malware detector wrongly flagging a benign app as malicious. One such example is the SlideIT Free Keyboard app, which has over 500000 downloads on Google Play. Despite being a "Keyboard" ap

Liang Chen, Yang Deng, Yatao Bian, Zeyu Qin

Large language models (LLMs) outperform information retrieval techniques for downstream knowledge-intensive tasks when being prompted to generate world knowledge. However, community concerns abound regarding the factuality and potential implications of using this uncensored knowledge. In light of this, we introduce CONNER, a COmpreheNsive kNowledge Evaluatio

Masahiro Morikawa, Akika Nakamichi

We first study the solar flare time sequence based on the GOES16 data. We find that the power spectrum density of the low-energy (E\leq E_{mean}) flare shows 1/f fluctuations, but the high-energy (E>E_{mean}) flare shows a flat spectrum. Further, we found that the flare timing time-sequence shows 1/f fluctuations clearer. These facts indicate that the solar

Jan Heuer

With the increase in industrial applications using Answer Set Programming, the need for formal verification tools, particularly for critical applications, has also increased. During the program optimisation process, it would be desirable to have a tool which can automatically verify whether an optimised subprogram can replace the original subprogram. Formall

He Zhang, Ying Sun, Weiyu Guo, Yafei Liu

Personalized interior decoration design often incurs high labor costs. Recent efforts in developing intelligent interior design systems have focused on generating textual requirement-based decoration designs while neglecting the problem of how to mine homeowner's hidden preferences and choose the proper initial design. To fill this gap, we propose an Interac

Yu-Hsueh Chen, Tarun Grover

We study quantum many-body mixed states with a symmetry from the perspective of separability, i.e., whether a mixed state can be expressed as an ensemble of short-range entangled (SRE) symmetric pure states. We provide evidence for 'symmetry-enforced separability transitions' in a variety of states, where in one regime the mixed state is expressible as a con

Weiyang Liu, Linhua Jiang

We present a spectroscopic survey of Ly$\alpha$ emitters (LAEs) at $z\sim3.7$ and $z\sim4.8$. The LAEs are selected using the narrowband technique based on the combination of deep narrowband and broadband imaging data in two deep fields, and then spectroscopically confirmed with the MMT multi-fiber spectrograph Hectospec. The sample consists of 71 LAEs at $z

Xiang Hao, Jibin Wu, Jianwei Yu, Chenglin Xu

Humans can easily isolate a single speaker from a complex acoustic environment, a capability referred to as the "Cocktail Party Effect." However, replicating this ability has been a significant challenge in the field of target speaker extraction (TSE). Traditional TSE approaches predominantly rely on voiceprints, which raise privacy concerns and face issues

Yuchen Liu, Linhua Jiang, Rogier A. Windhorst, Yucheng Guo

We present a study of Lyman continuum (LyC) emission in a sample of $\sim$150 Ly$\alpha$ emitters (LAEs) at $z\approx3.1$ in the Subaru-XMM Deep Survey field. These LAEs were previously selected using the narrowband technique and spectroscopically confirmed with Ly$\alpha$ equivalent widths (EWs) $\ge45$ \r{A}. We obtain deep UV images using a custom interme

Shyni Sharaf, V. S. Anoop

This paper conducts a comprehensive investigation into applying large language models, particularly on BioBERT, in healthcare. It begins with thoroughly examining previous natural language processing (NLP) approaches in healthcare, shedding light on the limitations and challenges these methods face. Following that, this research explores the path that led to

Yu Tokutake, Chihiro Yamasaki, Yongzhi Jin, Ayuka Inoue

In this paper, we propose a solution that won the 10th prize in the KDD Cup 2023 Challenge Task 2 (Next Product Recommendation for Underrepresented Languages/Locales). Our approach involves two steps: (i) Identify candidate item sets based on co-visitation, and (ii) Re-ranking the items using LightGBM with locale-independent features, including session-based

Xiaojun Ji, Ru Wang, Hao Wang, Wenjian Liu

As an optimal one-dimensional reaction coordinate, the committor function not only describes the probability of a trajectory initiated at a phase space point first reaching the product state before reaching the reactant state, but also preserves the kinetics when utilized to run a reduced dynamics model. However, calculating the committor function in high-di

Jarod Duret, Benjamin O'Brien, Yannick Estève, Titouan Parcollet

Textless speech-to-speech translation systems are rapidly advancing, thanks to the integration of self-supervised learning techniques. However, existing state-of-the-art systems fall short when it comes to capturing and transferring expressivity accurately across different languages. Expressivity plays a vital role in conveying emotions, nuances, and cultura

Alexis Kagan

We consider a null recurrent random walk $\mathbb{X}$ on a super-critical Galton Watson marked tree $\mathbb{T}$ in the (sub-)diffusive regime. We are interested in the asymptotic behaviour of the local time of its root at $n$, which is the total amount of time spent by the random walk $\mathbb{X}$ on the root of $\mathbb{T}$ up to the time $n$, and in its $

BESIII Collaboration, M. Ablikim, M. N. Achasov, P. Adlarson

Using a sample of about 10 billion $J/\psi$ events with the BESIII detector, we search for the weak decays of $J/\psi \to \bar{D}^0\pi^0 + c.c.$, $J/\psi \to \bar{D}^0\eta + c.c.$, $J/\psi \to \bar{D}^0\rho^0 + c.c.$, $J/\psi \to D^-\pi^+ + c.c.$, and $J/\psi \to D^-\rho^+ + c.c.$. Since no significant signal is observed, we set the upper limits of the branc

Qizhi Pei, Wei Zhang, Jinhua Zhu, Kehan Wu

Recent advancements in biological research leverage the integration of molecules, proteins, and natural language to enhance drug discovery. However, current models exhibit several limitations, such as the generation of invalid molecular SMILES, underutilization of contextual information, and equal treatment of structured and unstructured knowledge. To addres

Quentin Richard, Marc Choisy, Ramsès Djidjou-Demasse, Thierry Lefèvre

Malaria is one of the most common mosquito-borne diseases widespread in tropical and subtropical regions, causing thousands of deaths every year in the world. In a previous paper, we formulated an age-structured model containing three structural variables: (i) the chronological age of human and mosquito populations, (ii) the time since they are infected, and

Hirokazu Fujiwara, Kensei Terashima, Junya Otsuki, Nayuta Takemori

The spin-dependent band structure of CoS$_2$ which is a candidate for a half-metallic ferromagnet was investigated by both spin- and angle-resolved photoemission spectroscopy and theoretical calculations, in order to reappraise the half-metallicity and electronic correlations. We determined the three-dimensional Fermi surface and the spin-dependent band stru

Yannick Demeusy, Sandrine Gauffinet, Christophe Labbez

Partial substitution of the clinker in the cement by a supplementary cementitious material (SCM) is one of the main solutions to reduce the carbon footprint. Calcined kaolinite is a good candidate due to its availability and relatively high reactivity compared to other SCMs. The main issue with these calcined clay types of cements is the high-water demand at

Alexis Gaget, Tom Joannem, Adelino Gomes, Yves Lussignol

CEA IRFU Saclay is taking part of ESS (European Spallation Source) construction through several packages and, especially in the last three years on the Elliptical Cavity and Cryomodule Test stand Demonstrator (ECCTD). The project consists of RF test, conditioning, cryogenic cool-down and regulations of eight cryomodules with theirs four cavities each. For no

Kiran Jain, Sushanta C. Tripathy

We present analysis of the evolution of subsurface flows in and around active regions with peculiar magnetic configurations and compare their characteristics with the normal active regions. We also study the zonal and meridional components of subsurface flows separately in different polarity regions separately to better understand their role in flux migratio

Razvan Gabriel Iagar, Philippe Laurençot

Existence of specific \emph{eternal solutions} in exponential self-similar form to the following quasilinear diffusion equation with strong absorption$$\partial_t u=\Delta u^m-|x|^{\sigma}u^q,$$posed for $(t,x)\in(0,\infty)\times\mathbb{R}^N$, with $m>1$, $q\in(0,1)$ and $\sigma=\sigma_c:=2(1-q)/(m-1)$ is proved. Looking for radially symmetric solutions of t

Zixiang Chen, Junkai Zhang, Yiwen Kou, Xiangning Chen

The challenge of overfitting, in which the model memorizes the training data and fails to generalize to test data, has become increasingly significant in the training of large neural networks. To tackle this challenge, Sharpness-Aware Minimization (SAM) has emerged as a promising training method, which can improve the generalization of neural networks even i

Changan Yang, Yaxing Chen, Yao Zhang, Helei Cui

Vehicular crowd intelligence (VCI) is an emerging research field. Facilitated by state-of-the-art vehicular ad-hoc networks and artificial intelligence, various VCI applications come to place, e.g., collaborative sensing, positioning, and mapping. The collaborative property of VCI applications generally requires data to be shared among participants, thus for

Giunchi, E, Poggianti, B. M.

We characterize the morphological properties of a statistically relevant sample of H$\alpha$ and UV young star-forming clumps and optical complexes, observed with the \textit{Hubble Space Telescope} in six galaxies of the GASP sample undergoing ram-pressure stripping. The catalogs comprise 2406 (323 in the tails) H$\alpha$ clumps, 3750 (899) UV clumps and 42

Noufel Frikha, Arturo Kohatsu-Higa, Libo Li

In line with the methodology introduced in our recent article for formulating probabilistic representations of integration by parts involving killed diffusion, we establish an integration by parts formula for the first exit time of one-dimensional diffusion processes. However, our approach diverges from the conventional differential calculus applied to the a

Xu Zheng, Yunhao Luo, Pengyuan Zhou, Lin Wang

In this paper, we tackle a new problem: how to transfer knowledge from the pre-trained cumbersome yet well-performed CNN-based model to learn a compact Vision Transformer (ViT)-based model while maintaining its learning capacity? Due to the completely different characteristics of ViT and CNN and the long-existing capacity gap between teacher and student mode

Manuel Delgado, Shalom Eliahou, Jean Fromentin

For a numerical semigroup $S \subseteq \mathbb{N}$, let $m,e,c,g$ denote its multiplicity, embedding dimension, conductor and genus, respectively. Wilf's conjecture (1978) states that $e(c-g) \ge c$. As of 2023, Wilf's conjecture has been verified by computer up to genus $g \le 66$. In this paper, we extend the verification of Wilf's conjecture up to genus $

Afnan Al-Ali, Somaya Al-Maadeed, Moutaz Saleh, Rani Chinnappa Naidu

Dysarthria is a neurological speech disorder that can significantly impact affected individuals' communication abilities and overall quality of life. The accurate and objective classification of dysarthria and the determination of its severity are crucial for effective therapeutic intervention. While traditional assessments by speech-language pathologists (S

Frank Joublin, Antonello Ceravola, Pavel Smirnov, Felix Ocker

In the pursuit of fully autonomous robotic systems capable of taking over tasks traditionally performed by humans, the complexity of open-world environments poses a considerable challenge. Addressing this imperative, this study contributes to the field of Large Language Models (LLMs) applied to task and motion planning for robots. We propose a system archite

Umberto Casti, Giacomo Baggio, Danilo Benozzo, Sandro Zampieri

In this paper, we consider stable stochastic linear systems modeling whole-brain resting-state dynamics. We parametrize the state matrix of the system (effective connectivity) in terms of its steady-state covariance matrix (functional connectivity) and a skew-symmetric matrix $S$. We examine how the matrix $S$ influences some relevant dynamic properties of t

Joost A. A. Opschoor, Christoph Schwab

We show expression rates and stability in Sobolev norms of deep feedforward ReLU neural networks (NNs) in terms of the number of parameters defining the NN for continuous, piecewise polynomial functions, on arbitrary, finite partitions $\mathcal{T}$ of a bounded interval $(a,b)$. Novel constructions of ReLU NN surrogates encoding function approximations in t

Supriya Pan, Weiqiang Yang

The Hubble constant $H_0$ is one of the important cosmological parameters measuring the expansion rate of our universe at present moment. Over the last couple of years, $H_0$ has created an enormous amount of debates interests in the astrophysical and cosmological communities for its different estimations at many standard deviations by different observationa

Haoyu Zhang, Meng Liu, Yisen Feng, Yaowei Wang

In contrast to conventional visual question answering, video-grounded dialog necessitates a profound understanding of both dialog history and video content for accurate response generation. Despite commendable progress made by existing approaches, they still face the challenges of incrementally understanding complex dialog history and assimilating video info

Qing-Hua Shen, Xu Zhang, Xiang Liu, Ju-Jun Xie

The three-body systems $\eta K^* \bar{K}^*$, $\pi K^* \bar{K}^*$, and $K K^* \bar{K}^*$ are further investigated within the framework of fixed-center approximation, where $K^* \bar{K}^*$ is treated as the fixed-center, corresponding to the possible scalar meson $a_0(1780)$ or the tensor meson $f_2'(1525)$. The interactions between $\eta$, $\pi$, $K$, and $K^

W. -J. Kim, J. S. Urquhart, V. S. Veena, G. A. Fuller

The application of silicon monoxide (SiO) as a shock tracer arises from its propensity to occur in the gas phase as a result of shock-induced phenomena, including outflow activity and interactions between molecular clouds and expanding HII regions or supernova remnants. We searched for indications of shocks toward 366 massive star-forming regions by observin

Muhammed O. Sayin

This paper proposes a finite-horizon approximation scheme and introduces episodic equilibrium as a solution concept for stochastic games (SGs), where agents strategize based on the current state and episode stage. The paper also establishes an upper bound on the approximation error that decays with the episode length for both discounted and time-averaged uti

Jinghui Qin, Lihuang Fang, Ruitao Lu, Liang Lin

Deep learning-based hyperspectral image (HSI) super-resolution, which aims to generate high spatial resolution HSI (HR-HSI) by fusing hyperspectral image (HSI) and multispectral image (MSI) with deep neural networks (DNNs), has attracted lots of attention. However, neural networks require large amounts of training data, hindering their application in real-wo

Adam Gindl, Pawan Suthar, František Trojánek, Petr Malý

High harmonic spectra generated in condensed matter carry the fingerprints of sub-cycle electronic motion and the energy structure of the studied system. Here we show that tailoring the waveform of mid-infrared driving light by using a coherent combination with its third harmonic frequency allows to control the time of electron tunneling to the conduction ba

Shuoying Wei, Xinlong Wen, Lida Zhu, Songquan Li

Obtaining accurate and valid information for drug molecules is a crucial and challenging task. However, chemical knowledge and information have been accumulated over the past 100 years from various regions, laboratories, and experimental purposes. Little has been explored in terms of the out-of-distribution (OOD) problem with noise and inconsistency, which m

Rashid Khan, Bingding Huang, Haseeb Hassan, Asim Zaman

Image captioning is a challenging task involving generating a textual description for an image using computer vision and natural language processing techniques. This paper proposes a deep neural framework for image caption generation using a GRU-based attention mechanism. Our approach employs multiple pre-trained convolutional neural networks as the encoder

Abhinav Rao, Aditi Khandelwal, Kumar Tanmay, Utkarsh Agarwal

In this position paper, we argue that instead of morally aligning LLMs to specific set of ethical principles, we should infuse generic ethical reasoning capabilities into them so that they can handle value pluralism at a global scale. When provided with an ethical policy, an LLM should be capable of making decisions that are ethically consistent to the polic

Ibrahim Ethem Hamamci

Glioblastoma is a highly aggressive and lethal form of brain cancer. Magnetic resonance imaging (MRI) plays a significant role in the diagnosis, treatment planning, and follow-up of glioblastoma patients due to its non-invasive and radiation-free nature. The International Brain Tumor Segmentation (BraTS) challenge has contributed to generating numerous AI al

Zachary Jackson, BingKan Xue

Intraspecific trait variation has been increasingly recognized as an important factor in determining species interaction and diversity. Eco-evolutionary models have studied the distribution of trait values within a population that changes over the generations as a result of selection and heritability. Non-heritable traits that can change within the lifetime,