April 2024 arXiv papers — page 95

Mahta Bakhshizadeh, Christian Jilek, Markus Schröder, Heiko Maus

Over the years, various approaches have been employed to enhance the productivity of knowledge workers, from addressing psychological well-being to the development of personal knowledge assistants. A significant challenge in this research area has been the absence of a comprehensive, publicly accessible dataset that mirrors real-world knowledge work. Althoug

Razvan Gabriel Iagar, Ariel Sánchez

We classify radially symmetric self-similar profiles presenting finite time blow-up to the quasilinear diffusion equation with weighted source $$ u_t=\Delta u^m+|x|^{\sigma}u^p, $$ posed for $(x,t)\in\real^N\times(0,T)$, $T>0$, in dimension $N\geq1$ and in the range of exponents $-2<\sigma<\infty$, $1<m<p<p_s(\sigma)$, where $$ p_s(\sigma)=\left\{\begin{arra

Yinan Chen

The field of natural language processing (NLP) has made significant progress with the rapid development of deep learning technologies. One of the research directions in text sentiment analysis is sentiment analysis of medical texts, which holds great potential for application in clinical diagnosis. However, the medical field currently lacks sufficient text d

Martin Bucher, Daniel Molnar

Much has been written about the representation of noisy linear 2-ports. Here we present a theory of noisy $N$-ports. We show how in the general case there are $(2N)!/(N!)^2$ equivalent representations and give the transformations relating them. We also discuss singular cases in which some of the transformations are not possible as well as how to measure the

Ke Zhu, Zheng Ge, Liang Zhao, Xiangyu Zhang

This paper makes the first attempt towards unsupervised preference alignment in Vision-Language Models (VLMs). We generate chosen and rejected responses with regard to the original and augmented image pairs, and conduct preference alignment with direct preference optimization. It is based on a core idea: properly designed augmentation to the image input will

Martin Nicholson

This is a discussion of miscellaneous summation, integration and transformation formulas obtained using Fourier analysis. The topics covered are: Series of the form $\sum_{n\in\mathbb{Z}} c_ne^{\pi i \gamma n^2}$; Fusion of integrals, and in particular fusion of $q$-beta integrals related to Gauss-Fourier transform, and a related family of eigenfunctions of

Chenggian Ma, Xiangyu Zhao, Chunhui Zhang, Yanzhao Qin

With the development of Large Language Models (LLM), numerous prompts have been proposed, each with a rich set of features and their own merits. This paper summarizes the prompt words for large language models (LLMs), categorizing them into stimulating and framework types, and proposes an Auto-Prompt Graphical Paradigm(APGP) that combines both stimulating an

Sihan Bai, Sanping Zhou, Zheng Qin, Le Wang

Noisy label learning aims to learn robust networks under the supervision of noisy labels, which plays a critical role in deep learning. Existing work either conducts sample selection or label correction to deal with noisy labels during the model training process. In this paper, we design a simple yet effective sample selection framework, termed Two-Stream Sa

Shijing Hu, Zhihui Lu, Xin Xu, Ruijun Deng

Embodied intelligence (EI) enables manufacturing systems to flexibly perceive, reason, adapt, and operate within dynamic shop floor environments. In smart manufacturing, a representative EI scenario is robotic visual inspection, where industrial robots must accurately inspect components on rapidly changing, heterogeneous production lines. This task requires

Florin Manea, Jonas Richardsen, Markus L. Schmid

For two strings u, v over some alphabet A, we investigate the problem of embedding u into w as a subsequence under the presence of generalised gap constraints. A generalised gap constraint is a triple (i, j, C_{i, j}), where 1 <= i < j <= |u| and C_{i, j} is a subset of A^*. Embedding u as a subsequence into v such that (i, j, C_{i, j}) is satisfied means th

Xiaoyang Chen, Ben He, Hongyu Lin, Xianpei Han

The practice of Retrieval-Augmented Generation (RAG), which integrates Large Language Models (LLMs) with retrieval systems, has become increasingly prevalent. However, the repercussions of LLM-derived content infiltrating the web and influencing the retrieval-generation feedback loop are largely uncharted territories. In this study, we construct and iterativ

Georgi Baklicharov, Christophe Ley, Vanessa Gorasso, Brecht Devleesschauwer

Quantile regression is a powerful tool for detecting exposure-outcome associations given covariates across different parts of the outcome's distribution, but has two major limitations when the aim is to infer the effect of an exposure. Firstly, the exposure coefficient estimator may not converge to a meaningful quantity when the model is misspecified, and se

Zhige Chen, Rui Yang, Mengjie Huang, Chengxuan Qin

Because of "the non-repeatability of the experiment settings and conditions" and "the variability of brain patterns among subjects", the data distributions across sessions and electrodes are different in cross-subject motor imagery (MI) studies, eventually reducing the performance of the classification model. Systematically summarised based on the existing s

Krzysztof Szulc, Mateusz Zelent, Maciej Krawczyk

We present a hybrid magnonic crystal composed of a chain of nanodots with strong perpendicular magnetic anisotropy and Dzyaloshinskii-Moriya interaction, positioned above a permalloy waveguide. The micromagnetic study examines two different magnetization states in the nanodots: a single-domain state and an egg-shaped skyrmion state. Due to the dipolar coupli

Muhammad N. Tahir, Honghui Shang, Jia Li, Xinguo Ren

We report an improved implementation for evaluating the analytical gradients of the random phase approximation (RPA) electron-correlation energy based on atomic orbitals and the localized resolution of identity scheme. The more efficient RPA force calculations allow us to relax structures of medium-size water clusters. Particular attention is paid to the str

Mario M. Alvarez, Henry Arneson, Ben Berger, Lee Bousfield

BoLD is a new dispute resolution protocol that is designed to replace the originally deployed Arbitrum dispute resolution protocol. Unlike that protocol, BoLD is resistant to delay attacks. It achieves this resistance without a significant increase in onchain computation costs and with reduced staking costs.

Hongli Wen, Yang Xu, Lin Li, Xudong Ru

Traditional sign language teaching methods face challenges such as limited feedback and diverse learning scenarios. Although 2D resources lack real-time feedback, classroom teaching is constrained by a scarcity of teacher. Methods based on VR and AR have relatively primitive interaction feedback mechanisms. This study proposes an innovative teaching model th

Pavel Bakhvalov

We consider the 2D acoustic system with the Gaussian pulse as the initial data. This case was proposed at the first Workshop on benchmark problems in computational aeroacoustics, and it is commonly used for the verification of numerical methods. We construct an efficient algorithm to evaluate the exact solution for a given time t and distance r. For a precis

Tomoya Kato, Akihiko Miyachi, Naoto Shida, Naohito Tomita

For bilinear Fourier multipliers that contain some oscillatory factors, boundedness of the operators between Lebesgue spaces is given including endpoint cases. Sharpness of the result is also considered.

G. Martí-Devesa, C. C. Cheung, N. Di Lalla, M. Renaud

While SNRs have been considered the most relevant Galactic CR accelerators for decades, CCSNe could accelerate particles during the earliest stages of their evolution and hence contribute to the CR energy budget in the Galaxy. Some SNRs have indeed been associated with TeV gamma-rays, yet proton acceleration efficiency during the early stages of an SN expans

Gaia Collaboration, P. Panuzzo, T. Mazeh, F. Arenou

Gravitational waves from black-hole merging events have revealed a population of extra-galactic BHs residing in short-period binaries with masses that are higher than expected based on most stellar evolution models - and also higher than known stellar-origin black holes in our Galaxy. It has been proposed that those high-mass BHs are the remnants of massive

Carlos Meniño Cotón

In this work we exhibit examples of $5$-manifolds that are not homeomorphic to any leaf of any $C^2$ codimension one foliation of any compact $6$-manifold but are homeomorphic to (proper) leaves of some $C^1$ codimension one foliations and also to (proper) leaves of some $C^\inf$ codimension $2$ foliations. As far as we know, this is the first example of thi

Zongxin Ye, Wenyu Li, Sidun Liu, Peng Qiao

3D Gaussian Splatting (3D-GS) technique couples 3D Gaussian primitives with differentiable rasterization to achieve high-quality novel view synthesis results while providing advanced real-time rendering performance. However, due to the flaw of its adaptive density control strategy in 3D-GS, it frequently suffers from over-reconstruction issue in intricate sc

Ubaid Azam, Imran Razzak, Shelly Vishwakarma, Hakim Hacid

AI-driven medical predictions with trustworthy confidence are essential for ensuring the responsible use of AI in healthcare applications. The growing capabilities of AI raise questions about their trustworthiness in healthcare, particularly due to opaque decision-making and limited data availability. This paper proposes a novel approach to address these cha

Yuki Ishihara

We propose an effective method for primary decomposition of symmetric ideals. Let $K[X]=K[x_1,\ldots,x_n]$ be the $n$-valuables polynomial ring over a field $K$ and $\mathfrak{S}_n$ the symmetric group of order $n$. We consider the canonical action of $\mathfrak{S}_n$ on $K[X]$ i.e. $\sigma(f(x_1,\ldots,x_n))=f(x_{\sigma(1)},\ldots,x_{\sigma(n)})$ for $\sigm

Ubaid Azam, Imran Razzak, Shelly Vishwakarma, Hakim Hacid

Predicting legal judgments with reliable confidence is paramount for responsible legal AI applications. While transformer-based deep neural networks (DNNs) like BERT have demonstrated promise in legal tasks, accurately assessing their prediction confidence remains crucial. We present a novel Bayesian approach called BayesJudge that harnesses the synergy betw

Damien Bloch, Britton Hofer, Sam Roberto Cohen, Maxence Lepers

We report experimental measurements of the dynamical polarizability of dysprosium, at a wavelength of 532 nm. We measure all three components (scalar, vector, tensor) of the anisotropic polarizability for the ground and the excited manifolds of the intercombination transition of Dy at 626 nm. The apparatus on which the measurements are performed is first pre

Xander M. de Wit, Rudie P. J. Kunnen, Herman J. H. Clercx, Federico Toschi

In many natural and industrial applications, turbulent flows encompass some form of dispersed particles. Although this type of multiphase turbulent flow is omnipresent, its numerical modeling has proven to be a remarkably challenging problem. Models that fully resolve the particle phase are computationally very expensive, strongly limiting the number of part

G. Buldgen, A. Noels, R. Scuflaire, A. M. Amarsi

Due to the high quality constraints available for the Sun, we can carry out combined analyses using neutrino, spectroscopic and helioseismic observations. Such studies lay the ground for future improvements of key physical components of solar and stellar models, such as the equation of state, radiative opacities or prescriptions for macroscopic transport pro

Mudasir Raja, Priya Hasan, Md Mahmudunnobe, Md Saifuddin

In this paper, we apply the machine learning clustering algorithm Density Based Spatial Clustering of Applications with Noise (DBSCAN) to study the membership of stars in twelve open clusters (NGC~2264, NGC~2682, NGC~2244, NGC~3293, NGC~6913, NGC~7142, IC~1805, NGC~6231, NGC~2243, NGC 6451, NGC 6005 and NGC 6583) based on Gaia DR3 Data. This sample of cluste

Zeinab Sedaghatjoo, Hossein Hosseinzadeh, Ahmad shirzadi

Haar-like filters are renowned for their simplicity, speed, and accuracy in various computer vision tasks. This paper proposes a novel algorithm to identify optimal fully dispersed Haar-like filters for enhanced facial feature extraction and recognation. Unlike traditional Haar-like filters, these novel filters allow pixels to move freely within images, enab

Donya Rooein, Dirk Hovy

Open conversations are one of the most engaging forms of teaching. However, creating those conversations in educational software is a complex endeavor, especially if we want to address the needs of different audiences. While language models hold great promise for educational applications, there are substantial challenges in training them to engage in meaning

Pietro Recalcati, Fabio Garcea, Luca Piano, Fabrizio Lamberti

Deep neural networks are increasingly used in a wide range of technologies and services, but remain highly susceptible to out-of-distribution (OOD) samples, that is, drawn from a different distribution than the original training set. A common approach to address this issue is to endow deep neural networks with the ability to detect OOD samples. Several bench

Davide Modesti, Sergio Pirozzoli

We establish a theoretical framework for predicting friction and heat transfer coefficients in variable-properties forced air convection. Drawing from concepts in high-speed wall turbulence, which also involves significant temperature, viscosity, and density variations, we utilize the mean momentum balance and mean thermal balance equations to develop integr

Viny Saajan Victor, Manuel Ettmüller, Andre Schmeißer, Heike Leitte

Several numerical differential equation solvers have been employed effectively over the years as an alternative to analytical solvers to quickly and conveniently solve differential equations. One category of these is boundary value solvers, which are used to solve real-world problems formulated as differential equations with boundary conditions. These solver

Alireza HosseiniArania, Manuel Schilling, Quentin Beaufils, Annike Knabe

Recent advances in cold atom interferometry have cleared the path for space applications of quantum inertial sensors, whose level of stability is expected to increase dramatically with the longer interrogation times accessible in space. In this study, a comprehensive in-orbit model is developed for a Mach-Zehnder-type cold-atom accelerometer. Performance tes

Tiantian Zhang, Wenpeng Zhou, Zhixiang Li, Yutao Tang

Nonreciprocal optical devices are essential for laser protection, modern optical communication and quantum information processing by enforcing one-way light propagation. The conventional Faraday magneto-optical nonreciprocal devices rely on a strong magnetic field, which is provided by a permanent magnet. As a result, the isolation direction of such devices

Michael Kiran Huber

We study the Short Path Packing problem which asks, given a graph $G$, integers $k$ and $\ell$, and vertices $s$ and $t$, whether there exist $k$ pairwise internally vertex-disjoint $s$-$t$ paths of length at most $\ell$. The problem has been proven to be NP-hard and fixed-parameter tractable parameterized by $k$ and $\ell$. Most previous research on this pr

Hadiseh Safdari, Caterina De Bacco

Anomaly detection is an essential task in the analysis of dynamic networks, offering early warnings of abnormal behavior. We present a principled approach to detect anomalies in dynamic networks that integrates community structure as a foundational model for regular behavior. Our model identifies anomalies as irregular edges while capturing structural change

Liding Xu, Claudia D'Ambrosio

We study the continuous set covering problem on networks and propose several new MILP formulations and valid inequalities. In contrast to state-of-the-art formulations, the new formulations only use edges to index installed points, and the formulation sizes are smaller. The covering conditions can be represented as multivariate piecewise linear concave const

Giuseppe Alì, Patricio Farrell, Nella Rotundo

In this paper, we present analytical results for the so-called forward lateral photovoltage scanning (LPS) problem. The (inverse) LPS model predicts doping variations in crystal by measuring the current leaving the crystal generated by a laser at various positions. The forward model consists of a set of nonlinear elliptic equations coupled with a measuring d

Robert Laterveer, Charles Vial

The Chow rings of hyper-K\"ahler varieties are conjectured to have a particularly rich structure. In this paper, we formulate a conjecture that combines the Beauville-Voisin conjecture regarding the subring generated by divisors and the Franchetta conjecture regarding generically defined cycles. As motivation, we show that this Beauville-Voisin-Franchetta co

Yu Li, Han Jiang, Chuanyang Gong, Zhihua Wei

Despite the remarkable achievements of language models (LMs) across a broad spectrum of tasks, their propensity for generating toxic outputs remains a prevalent concern. Current solutions involving finetuning or auxiliary models usually require extensive computational resources, hindering their practicality in large language models (LLMs). In this paper, we

Cathal Maguire, Neale P. Gibson, Stevanus K. Nugroho, Mark Fortune

Direct atmospheric retrievals of exoplanets at high-resolution have recently allowed for a more detailed characterisation of their chemistry and dynamics from the ground. By monitoring the longitudinal distribution of species, as well as the varying vertical temperature structure and dynamics between the limbs of WASP-76b, across multiple transits, we aim to

Vikram Vyas

A mathematical model, suitable for smartphone implementation, is presented to simulate the performance of a rainwater harvesting system equipped with a covered storage tank. This model serves to determine the optimal tank size and develop strategies to mitigate drought conditions.

Nicolas Heimann, Lukas Broers, Ludwig Mathey

We present an iterative optimal control method of quantum systems, aimed at an implementation of a desired operation with optimal fidelity. The update step of the method is based on the linear response of the fidelity to the control operators, and its projection onto the mode functions of the corresponding operator. Our method extends methods such as gradien

Henrique Gomes

In general relativity, the strong equivalence principle is underpinned by a geometrical interpretation of fields on spacetime: all fields and bodies probe the same geometry. This geometric interpretation implies that the parallel transport of all spacetime tensors and spinors is dictated by a single affine connection. Can something similar be said about gaug

Jürg Fröhlich, Zhou Gang, Alessandro Pizzo

Using the principles of the ETH - Approach to Quantum Mechanics we study fluorescence and the phenomenon of ``quantum jumps'' in idealized models of atoms coupled to the quantized electromagnetic field. In a limiting regime where the orbital motion of the atoms is neglected and the velocity of light tends to infinity we derive explicit non-linear stochastic

Victor Mukherjee, Uma Divakaran

Can many-body systems be beneficial to designing quantum technologies? We address this question by examining quantum engines, where recent studies indicate potential benefits through the harnessing of many-body effects, such as divergences close to phase transitions. However, open questions remain regarding their real-world applications.

Romal Ramadhan, Khomchan Promneewat, Vorasate Thanasaksukthawee, Teerapat Tosuai

Recognized as a not-an-option approach to mitigate the climate crisis, carbon dioxide capture and storage (CCS) has a potential as much as gigaton of CO2 to sequestrate permanently and securely. Recent attention has been paid to store highly concentrated point-source CO2 into saline formation, of which Thailand considers one onshore case in the north located

Qiuyi Hong, Fanlin Meng, Felipe Maldonado

In the context of increasing demands for long-term multi-energy load forecasting in real-world applications, this paper introduces Patchformer, a novel model that integrates patch embedding with encoder-decoder Transformer-based architectures. To address the limitation in existing Transformer-based models, which struggle with intricate temporal patterns in l

Anton Bushuiev, Roman Bushuiev, Jiri Sedlar, Tomas Pluskal

In recent years, there has been remarkable progress in machine learning for protein-protein interactions. However, prior work has predominantly focused on improving learning algorithms, with less attention paid to evaluation strategies and data preparation. Here, we demonstrate that further development of machine learning methods may be hindered by the quali

Chao Zhang, Tao Zhu

Horndeski theory constitutes the most general model of scalar-tensor theories. It has attracted much attention in recent years in relation with black holes, celestial dynamics, stability analysis, etc. It is important to note that, for certain subclasses of Horndeski models, one can obtain analytic solutions for the background fields. This facilitates the in

Marwan Salam Mohammd

We introduce "$n$-choiceless" supercompact and extendible cardinals in Zermelo-Fraenkel set theory without the Axiom of Choice. We prove relations between these cardinals and Vop\v{e}nka's Principle similar to those of Bagaria's work in his papers "$C^{(n)}$-Cardinals" and "More on the Preservation of Large Cardinals Under Class Forcing." We use these relati

Meriam Zribi, Paolo Pagliuca, Francesca Pitolli

The rapid growth of the Industry 4.0 paradigm is increasing the pressure to develop effective automated monitoring systems. Artificial Intelligence (AI) is a convenient tool to improve the efficiency of industrial processes while reducing errors and waste. In fact, it allows the use of real-time data to increase the effectiveness of monitoring systems, minim

Aaron Malcolm, B. Sharmila, Zhi-Wei Wang, Animesh Datta

Quantum vacuum fluctuations of the electromagnetic field result in two signatures on a harmonically trapped charged particle: a shift from the natural trap frequency and generation of quantum coherences. We assess the role of the long-wavelength and rotating-wave approximations in estimating this frequency shift. We estimate the magnitude of the frequency sh

Maryam Bajalan, Edgar Martinez-Moro

In this paper, we investigate the algebraic structure for polycyclic codes over a specific class of serial rings, defined as $\mathscr R=R[x_1,\ldots, x_s]/\langle t_1(x_1),\ldots, t_s(x_s) \rangle$, where $R$ is a chain ring and each $t_i(x_i)$ in $R[x_i]$ for $i\in\{1,\ldots, s\}$ is a monic square-free polynomial. We define quasi-$s$-dimensional polycycli

Ru He, Junlei Zhao, Jesper Byggmästar, Huan He

Recently reported remarkably high radiation tolerance of $\gamma$/$\beta$-Ga$_2$O$_3$ double-polymorphic structure brings this ultrawide bandgap semiconductor to the frontiers of power electronics applications that are able to operate in challenging environments. Understanding the mechanism of radiation tolerance is crucial for further material modification

Mingda Xu, Peisheng Qian, Ziyuan Zhao, Zeng Zeng

Protein-protein interactions (PPIs) play key roles in a broad range of biological processes. Numerous strategies have been proposed for predicting PPIs, and among them, graph-based methods have demonstrated promising outcomes owing to the inherent graph structure of PPI networks. This paper reviews various graph-based methodologies, and discusses their appli

O. Melchert, A. Demircan

We study solitary wave solutions for the nonlinear Schr\"odinger equation perturbed by the effects of third-, and fourth-order dispersion, maintaining a wavenumber gap between the solitary waves and the propagation constant. We numerically construct members of a family of such solitary waves, including Kruglov and Harvey's exact solution, using the spectral

Eitaro Kawamo, Hiroki Masuda

We study the parameter estimation method for linear regression models with possibly skewed stable distributed errors. Our estimation procedure consists of two stages: first, for the regression coefficients, the Cauchy quasi-maximum likelihood estimator (CQMLE) is considered after taking the differences to remove the skewness of noise, and we prove its asympt

Koen F. A. Jorissen, Lars B. Veldscholte, Mathieu Odijk, Sissi de Beer

We present the study of millisecond-resolved polymer brush swelling dynamics using infrared spectroscopy with a custom-built quantum cascade laser-based infrared spectrometer at a 1 kHz sampling rate after averaging. By cycling the humidity of the environment of the polymer brush, we are able to measure the swelling dynamics sequentially at different wavenum

Matthew Gadd, Daniele De Martini, Luke Pitt, Wayne Tubby

We describe a challenging robotics deployment in a complex ecosystem to monitor a rich plant community. The study site is dominated by dynamic grassland vegetation and is thus visually ambiguous and liable to drastic appearance change over the course of a day and especially through the growing season. This dynamism and complexity in appearance seriously impa

Kafeng Wang, Jianfei Chen, He Li, Zhenpeng Mi

Diffusion models represent a powerful family of generative models widely used for image and video generation. However, the time-consuming deployment, long inference time, and requirements on large memory hinder their applications on resource constrained devices. In this paper, we propose a method based on the improved Straight-Through Estimator to improve th

Rui Qiu, Zhou Yu, Zhenhua Lin

This paper explores the field of semi-supervised Fr\'echet regression, driven by the significant costs associated with obtaining non-Euclidean labels. Methodologically, we propose two novel methods: semi-supervised NW Fr\'echet regression and semi-supervised kNN Fr\'echet regression, both based on graph distance acquired from all feature instances. These met

Jinhui Yuan, Shan Lu, Peibo Duan, Jieyue He

Recently, heterogeneous graph neural networks (HGNNs) have achieved impressive success in representation learning by capturing long-range dependencies and heterogeneity at the node level. However, few existing studies have delved into the utilization of node attributes in heterogeneous information networks (HINs). In this paper, we investigate the impact of

Minas Kouroublakis, Nikolaos L. Tsitsas, George Fikioris

The null-field method (NFM) and the method of auxiliary sources (MAS) have been both used extensively for the numerical solution of boundary-value problems arising in diverse applications involving propagation and scattering of waves. It has been shown that, under certain conditions, the applicability of MAS may be restricted by issues concerning the diverge

Hang Du, Yaping Xue, Weidong Dai, Xuejun Yan

In this report, we present the 1st place solution for ICCV 2023 OmniObject3D Challenge: Sparse-View Reconstruction. The challenge aims to evaluate approaches for novel view synthesis and surface reconstruction using only a few posed images of each object. We utilize Pixel-NeRF as the basic model, and apply depth supervision as well as coarse-to-fine position

Albert Elias-López, Fabio del Sordo, Daniele Viganò

The amplification of astrophysical magnetic fields takes place via dynamo instability in turbulent environments. The presence of vorticity is crucial for the dynamo to happen. However, the role of vorticity is not yet fully understood. This work is an extension of previous research on the effect of an irrotational subsonic forcing on a magnetized medium in t

Zheng Yuan, Štefan Beňuš, Alessandro D'Ausilio

This study explores F0 entrainment in second language (L2) English speech imitation during an Alternating Reading Task (ART). Participants with Italian, French, and Slovak native languages imitated English utterances, and their F0 entrainment was quantified using the Dynamic Time Warping (DTW) distance between the parameterized F0 contours of the imitated ut

Yusuke Hakuta, Yasushi Amano, Tomohiko Jimbo, Shuji Tomura

Battery energy storage systems (BESSs) are essential for stable power supply in renewable energy systems that can operate in all weather. Future BESSs will be massive and pluggable with several heterogeneous batteries. In this paper, a novel decentralized control method for a heterogeneous BESS is proposed, in which each battery autonomously operates based o

Gabriele Trivigno, Carlo Masone, Barbara Caputo, Torsten Sattler

Pose refinement is an interesting and practically relevant research direction. Pose refinement can be used to (1) obtain a more accurate pose estimate from an initial prior (e.g., from retrieval), (2) as pre-processing, i.e., to provide a better starting point to a more expensive pose estimator, (3) as post-processing of a more accurate localizer. Existing a

Feng Zhang

The goal of this note is to provide an alternative proof of Theorem 1.1 (i) in [4], that is, if $n\geq 2$ and $M^{\alpha}$ is bounded on $L^{p}(\mathbb{R}^{n})$ for some $\alpha\in \mathbb{C}$ and $p\geq 2$, then we have \begin{align*} \operatorname{Re} \alpha\geq \max\left\{\frac{1-n}{2}+\frac{1}{p},\frac{1-n}{p}\right\}. \end{align*}

Sean O'Hagan, Jungeum Kim, Veronika Rockova

In generative models with obscured likelihood, Approximate Bayesian Computation (ABC) is often the tool of last resort for inference. However, ABC demands many prior parameter trials to keep only a small fraction that passes an acceptance test. To accelerate ABC rejection sampling, this paper develops a self-aware framework that learns from past trials and e

Terry Amorese, Marialucia Cuciniello, Alessandro Vinciarelli, Gennaro Cordasco

Considered the increasing use of assistive technologies in the shape of virtual agents, it is necessary to investigate those factors which characterize and affect the interaction between the user and the agent, among these emerges the way in which people interpret and decode synthetic emotions, i.e., emotional expressions conveyed by virtual agents. For thes

A. L. Pankratov, A. V. Gordeeva, A. V. Chiginev, L. S. Revin

When measuring electromagnetic radiation of frequency $f$, the most sensitive detector is the one that counts the single quanta of energy $h f$. Single photon detectors (SPDs) were demonstrated from $\gamma$-rays to infrared wavelengths, and extending this range down to the microwaves is the focus of intense research. The energy of $10\,\mathrm{GHz}$ microwa

Christian Tinauer, Anna Damulina, Maximilian Sackl, Martin Soellradl

Motivation. While recent studies show high accuracy in the classification of Alzheimer's disease using deep neural networks, the underlying learned concepts have not been investigated. Goals. To systematically identify changes in brain regions through concepts learned by the deep neural network for model validation. Approach. Using quantitative R2* maps we s

Hong-Chuan Ma, Min Du, Luis C. Ho, Ming-jie Sheng

From the IllustrisTNG-50 simulation, a sample of 836 central disk galaxies with tiny stellar halos is chosen to study the inherent evolution of galaxies driven by nature. These galaxies are classified as compact, normal, or extended by referencing their locations on the mass-size ($M_\star-R_{\rm 1/2}$) diagram. This research demonstrates the distinctive evo

Cecilia Cavaterra, Maurizio Grasselli, Muhammed Ali Mehmood, Riccardo Voso

We consider an evolution system modeling a flow of colloidal particles which are suspended in an incompressible fluid and accounts for colloidal crystallization. The system consists of the Navier-Stokes equations for the volume averaged velocity coupled with the so-called Phase-Field Crystal equation for the density deviation. Considering this system in a pe

Carlos J. Ruestes, Javier Segurado

A stochastic discrete slip approach is proposed to model plastic deformation in submicron domains. The model is applied to the study of submicron pillar ($D~\leq~1\mu m$) compression experiments on tungsten (W), a prototypical metal for applications under extreme conditions. Slip events are geometrically resolved in the specimen and considered as eigenstrain

Antonio Del Donno

In this thesis we study the Durdevic theory of differential calculi on quantum principal bundles within the domain of noncommutative geometry. Throughout the exposition, an algebraic approach based on Hopf algebras is employed. We begin by briefly recalling the foundational concepts of Hopf algebras and comodule algebras. Hopf-Galois extensions are introduce

Zhengwei Tao, Zhi Jin, Junqiang Huang, Xiancai Chen

Multi-modal Event Reasoning (MMER) endeavors to endow machines with the ability to comprehend intricate event relations across diverse data modalities. MMER is fundamental and underlies a wide broad of applications. Despite extensive instruction fine-tuning, current multi-modal large language models still fall short in such ability. The disparity stems from

Mikhail I. Gomoyunov

We consider a game, in which the dynamics is described by a non-linear Volterra integral equation of Hammerstein type with a weakly-singular kernel and the goals of the first and second players are, respectively, to minimize and maximize a given cost functional. We propose a way of how the dynamic programming principle can be formalized and the theory of gen

Xixi Yu, Vinay L. Kashyap, Giulio Del Zanna, David A. van Dyk

We estimate the coronal density of Capella using the O VII and Fe XVII line systems in the soft X-ray regime that have been observed over the course of the Chandra mission. Our analysis combines measures of error due to uncertainty in the underlying atomic data with statistical errors in the Chandra data to derive meaningful overall uncertainties on the plas

Sara Giuliani, Shunsuke Inenaga, Zsuzsanna Lipták, Giuseppe Romana

A bit catastrophe, loosely defined, is when a change in just one character of a string causes a significant change in the size of the compressed string. We study this phenomenon for the Burrows-Wheeler Transform (BWT), a string transform at the heart of several of the most popular compressors and aligners today. The parameter determining the size of the comp

Wadhah Zai El Amri, Nicolás Navarro-Guerrero

Tactile sensing presents a promising opportunity for enhancing the interaction capabilities of today's robots. BioTac is a commonly used tactile sensor that enables robots to perceive and respond to physical tactile stimuli. However, the sensor's non-linearity poses challenges in simulating its behavior. In this paper, we first investigate a BioTac simulatio

Ryo Terada, Daisuke Yamakawa

We introduce reflection functors on quiver schemes in the sense of Hausel--Wong--Wyss, generalizing those on quiver varieties. Also we construct some isomorphisms between quiver schemes whose underlying quivers are different.

Anas Obeidat

We present a discrete filter for subgrid-scale (SGS) model, coupled with the discretization corrected particle strength exchange (DC-PSE) method for the simulation of three-dimensional viscous incompressible flow, at high Reynolds flows. The majority of turbulence modelling techniques, particularly in complex geometries, face significant computational challe

Sergio Venturini

We prove that given a locally integrable function $f$ on an open set of an Euclidean space the distributional derivative $Xf$ with respect to a locally Lipshitzian vector field $X$ is locally integrable if, and only if, the function $f$ admits a locally integrable upper gradient along the vector field $X$; in this case $Xf$ coincides with the Lie derivative

Martina Baiardi, Samuele Burattini, Giovanni Ciatto, Danilo Pianini

We provide a taxonomy of concurrency models for BDI frameworks, elicited by analysing state-of-the-art technologies, and aimed at helping both BDI designers and developers in making informed decisions. Comparison among BDI technologies w.r.t. concurrency models reveals heterogeneous support, and low customisability.

René Heinrich, Lukas Rauch, Bernhard Sick, Christoph Scholz

Deep learning models have significantly advanced acoustic bird monitoring by being able to recognize numerous bird species based on their vocalizations. However, traditional deep learning models are black boxes that provide no insight into their underlying computations, limiting their usefulness to ornithologists and machine learning engineers. Explainable m

Matthieu Futeral, Andrea Agostinelli, Marco Tagliasacchi, Neil Zeghidour

Generative spoken language models produce speech in a wide range of voices, prosody, and recording conditions, seemingly approaching the diversity of natural speech. However, the extent to which generated speech is acoustically diverse remains unclear due to a lack of appropriate metrics. We address this gap by developing lightweight metrics of acoustic dive

Alexandr Valyuzhenich

The spectrum of a complex-valued function $f$ on $\mathbb{Z}_{q}^n$ is the set $\{|u|:u\in \mathbb{Z}_q^n~\mathrm{and}~\widehat{f}(u)\neq 0\}$, where $|u|$ is the Hamming weight of $u$ and $\widehat{f}$ is the Fourier transform of $f$. Let $1\leq d'\leq d\leq n$. In this work, we study Boolean functions on $\mathbb{Z}_{q}^n$, $q\geq 3$, whose spectrum is a s

Guangwen Zhao

We prove a local gradient estimate for positive eigenfunctions of $ \mathcal{L} $-operator on conformal solitons given by a general conformal vector field. As an application, we obtain a Liouville type theorem for $ \mathcal{L} u = 0 $, which improves the one of Li--Sun (Acta Math. Sin. (Engl. Ser.), 37(11): 1768--1782, 2021.). We also consider applications

Pancheng Wang, Shasha Li, Dong Li, Kehan Long

Automatically condensing multiple topic-related scientific papers into a succinct and concise summary is referred to as Multi-Document Scientific Summarization (MDSS). Currently, while commonly used abstractive MDSS methods can generate flexible and coherent summaries, the difficulty in handling global information and the lack of guidance during decoding sti

Bo Deng, Moritz Göb, Max Masuhr, Johannes Roßnagel

We present a tapered Paul trap whose radio frequency electrodes are inclined to the symmetric axis of the endcap electrodes, resulting in a funnel-shaped trapping potential. With this configuration, a charged particle confined in this trap has its radial degrees of freedom coupled to that of the axial direction. The same design was successfully used to exper

Christoph Schneck, Jan Smrek, Christos N. Likos, Andreas Zöttl

We apply monomer-resolved computer simulations of supercoiled ring polymers under shear, taking full account of the hydrodynamic interactions, accompanied, in parallel, by simulations in which these are switched off. The combination of bending and torsional rigidities inherent in these polymers, in conjunction with hydrodynamics, has a profound impact on the

Tiannuo Yang, Wen Hu, Wangqi Peng, Yusen Li

Vector data management systems (VDMSs) have become an indispensable cornerstone in large-scale information retrieval and machine learning systems like large language models. To enhance the efficiency and flexibility of similarity search, VDMS exposes many tunable index parameters and system parameters for users to specify. However, due to the inherent charac

Debabrata Ghorai, Taewon Yuk, Young-Kwon Han, Sang-Jin Sin

The fermion gaps are classified into order gap or Mott gap depending on the presence/absence of the order parameter. We construct the holographic model of the Mott gap using the field that is supported by the density only without introducing any order parameter. We then classify the Mott gap, depending on the shape of the gap in the density of states and whe

Dani Manjah, Davide Cacciarelli, Christophe De Vleeschouwer, Benoit Macq

We present a scalable framework designed to craft efficient lightweight models for video object detection utilizing self-training and knowledge distillation techniques. We scrutinize methodologies for the ideal selection of training images from video streams and the efficacy of model sharing across numerous cameras. By advocating for a camera clustering meth