November 2024 arXiv papers — page 118

Karim Ezzeddine, Jihad Fahs, Ibrahim Abou-Faycal

We study the rate-distortion problem for both scalar and vector memoryless heavy-tailed $\alpha$-stable sources ($0 < \alpha < 2$). Using a recently defined notion of ``strength" as a power measure, we derive the rate-distortion function for $\alpha$-stable sources subject to a constraint on the strength of the error and show it to be logarithmic in the stre

Nosheen Akbar, Ishrat Asghar, Zaki Ahmad

In this work, radial Schrodinger equation with a non-relativistic quark potential model (NRQPM) is solved numerically by employing the shooting method. Calculated numerical wave functions (or solutions) are used to compute the masses, root mean square (RMS) radii, $E1$ and $M1$ radiative transitions, and branching ratios of $S, P, D$ and $F$ states of toponi

Hanti Lin

There has long been an impression that reliabilism implies externalism and that frequentist statistics, due to its reliabilist nature, is inherently externalist. I argue, however, that frequentist statistics can plausibly be understood as a form of internalist reliabilism -- internalist in the conventional sense, yet reliabilist in certain unconventional and

Yongjiang Wu, Lihua Feng, Yongtao Li

Two families $\mathcal{F}$ and $\mathcal{G}$ are called cross-intersecting if for every $F\in \mathcal{F}$ and $G\in \mathcal{G}$, the intersection $F\cap G$ is non-empty. It is significant to determine the maximum sum of sizes of cross-intersecting families under the additional assumption that one of the two families is intersecting. Such a pair of families

Xin Jin, Qianqian Qiao, Yi Lu, Huaye Wang

Datasets play a pivotal role in training visual models, facilitating the development of abstract understandings of visual features through diverse image samples and multidimensional attributes. However, in the realm of aesthetic evaluation of artistic images, datasets remain relatively scarce. Existing painting datasets are often characterized by limited sco

Xiufeng Yan, Dianhui Wang

Stochastic Configuration Networks (SCNs) are a class of randomized neural networks that integrate randomized algorithms within an incremental learning framework. A defining feature of SCNs is the supervisory mechanism, which adaptively adjusts the distribution to generate effective random basis functions, thereby enabling error-free learning. In this paper,

J. E. Gough

We extend the theory of quantum time loops introduced by Greenberger and Svozil [1] from the scalar situation (where paths have just an associated complex amplitude) to the general situation where the time traveling system has multi-dimensional underlying Hilbert space. The main mathematical tool which emerges is the noncommutative Mobius Transformation and

Larisa A. Thorne

Nearly 70 years since the neutrino was discovered, and 25 years since discovery of neutrino oscillations established its non-zero mass, the absolute neutrino-mass scale remains unknown. Due to its unique characteristics, determining this neutrino property requires new measurement techniques to be developed. Currently, there are four measurement approaches: u

Koichi Murase, Tetsuo Hyodo

Femtoscopy is recently gaining more attention as a new approach complementary to scattering experiments for constraining hadron-hadron interactions. We discuss the effect of higher partial waves on the two-particle correlation function, which has been neglected in traditional formulae used in the femtoscopy analyses. We consider the partial-wave expansion of

Sarthak Duary, Shivam Upadhyay

We revisit the flat limit of AdS/CFT from the point of view of geodesics in AdS. We show that the flat space scattering amplitudes can be constructed from operator insertions where the geodesics of the particles corresponding to the operators hit the conformal boundary of AdS. Further, we compute the Li\'enard-Wiechert solutions in AdS by boosting a static c

Zhe Liu, Jie Li, Mengwu Huo, Bingke Ji

We report on optical studies of the Ruddlesden-Popper nickelates La$_{n+1}$Ni$_{n}$O$_{3n+1}$ with $n = 2$ (La$_{3}$Ni$_{2}$O$_{7}$), $n = 3$ (La$_{4}$Ni$_{3}$O$_{10}$) and $n = \infty$ (LaNiO$_{3}$). As the number of the NiO$_{6}$ octahedra layers $n$ grows, the ratio of the kinetic energy determined from the experimental optical conductivity and that from

Han Qing Yang, Jun Yan Dai, Hui Dong Li, Lijie Wu

The programmable metasurface is regarded as one of the most promising transformative technologies for next-generation wireless system applications. Due to the lack of effective perception ability of the external electromagnetic environment, there are numerous challenges in the intelligent regulation of wireless channels, and it still relies on external senso

Fabian Bongratz, Markus Karmann, Adrian Holz, Moritz Bonhoeffer

Meningeal lymphatic vessels (MLVs) are responsible for the drainage of waste products from the human brain. An impairment in their functionality has been associated with aging as well as brain disorders like multiple sclerosis and Alzheimer's disease. However, MLVs have only recently been described for the first time in magnetic resonance imaging (MRI), and

Li Guo, Wenchuan Hu, Hongyu Xiang, Bin Zhang

The shuffle algebra on positive integers encodes the usual multiple zeta values (MZVs) (with positive arguments) thanks to the representations of MZVs by iterated Chen integrals of Kontsevich. Together with the quasi-shuffle (stuffle) algebra, it provides the algebraic framework to study relations among MZVs. This paper enlarges the shuffle algebra uniquely

Chalisa Veesommai Sillberg, Jose Siqueira De Cerqueira, Pekka Sillberg, Kai-Kristian Kemell

The EU AI Act was created to ensure ethical and safe Artificial Intelligence (AI) development and deployment across the EU. This study aims to identify key challenges and strategies for helping enterprises focus on resources effectively. To achieve this aim, we conducted a Multivocal Literature Review (MLR) to explore the sentiments of both the industry and

Xiaohao Yang, He Zhao, Weijie Xu, Yuanyuan Qi

Topic modeling is a fundamental task in natural language processing, allowing the discovery of latent thematic structures in text corpora. While Large Language Models (LLMs) have demonstrated promising capabilities in topic discovery, their direct application to topic modeling suffers from issues such as incomplete topic coverage, misalignment of topics, and

Wadhah Zai El Amri, Malte Kuhlmann, Nicolás Navarro-Guerrero

Tactile perception is essential for human interaction with the environment and is becoming increasingly crucial in robotics. Tactile sensors like the BioTac mimic human fingertips and provide detailed interaction data. Despite its utility in applications like slip detection and object identification, this sensor is now deprecated, making many valuable datase

Raymond Brummelhuis

Given a normalized state-vector $\psi $, we define the conditional expectation $\mathbb{E }_{\psi } (A | B ) $ of a Hermitian operator $A $ with respect to a strongly commuting family of self-adjoint operators $B $ as the best approximation, in the operator mean square norm associated to $\psi $, of $A $ by a real-valued function of $B . $ A fundamental exam

Ravi Kant Gupta, Mohit Jindal, Garima Jain, Epari Sridhar

We address the challenge of automated classification of diffuse large B-cell lymphoma (DLBCL) into its two primary subtypes: activated B-cell-like (ABC) and germinal center B-cell-like (GCB). Accurate classification between these subtypes is essential for determining the appropriate therapeutic strategy, given their distinct molecular profiles and treatment

Ravi Kant Gupta, Shounak Das, Amit Sethi

Whole Slide Imaging (WSI) is a cornerstone of digital pathology, offering detailed insights critical for diagnosis and research. Yet, the gigapixel size of WSIs imposes significant computational challenges, limiting their practical utility. Our novel approach addresses these challenges by leveraging various encoders for intelligent data reduction and employi

Ravi Kant Gupta, Dadi Dharani, Shambhavi Shanker, Amit Sethi

The advancement of digital pathology, particularly through computational analysis of whole slide images (WSI), is poised to significantly enhance diagnostic precision and efficiency. However, the large size and complexity of WSIs make it difficult to analyze and classify them using computers. This study introduces a novel method for WSI classification by aut

Petteri Kela, Bryan Liu, Alvaro Valcarce

Efficient radio packet scheduling remains one of the most challenging tasks in cellular networks, and while heuristic methods exist, practical deep learning-based schedulers that are 3GPP-compliant and capable of real-time operation in 5G and beyond are still missing. To address this, we first take a critical look at previous deep scheduler efforts. Secondly

Surajit Adhikari, Ayan Chakravorty, Priya Johari

Lead-free perovskite materials have emerged as key players in optoelectronics, showcasing exceptional optical and electronic properties, alongside being environmentally friendly and non-toxic elements. Recently, among studied perovskite materials, vacancy-ordered double perovskites (VODPs) stand out as a promising alternative. In this study, we captured the

Jia-Min Lai, Haonan Chang, Feilong Song, Xiaohong Xu

The correlated Stoke antiStokes (SaS) scattering plays a crucial role in quantum information processing, such as heralded light sources, Fock state dynamics, and write read protocol for quantum memory. However, several reported materials exhibit low degree of SaS correlation and require high-power pulse laser excitation, limiting further applications. Herein

Deborah Gerhardt, Miriam Marcowitz-Bitton, W. Michael Schuster, Avshalom Elmalech

Text is a vehicle to convey information that reflects the writer's linguistic style and communicative patterns. By studying these attributes, we can discover latent insights about the author and their underlying message. This article uses such an approach to better understand patent applications and their inventors. While prior research focuses on patent met

Bastien Batardière, Julien Chiquet, Mahendra Mariadassou

Count data analysis is essential across diverse fields, from ecology and accident analysis to single-cell RNA sequencing (scRNA-seq) and metagenomics. While log transformations are computationally efficient, model-based approaches such as the Poisson-Log-Normal (PLN) model provide robust statistical foundations and are more amenable to extensions. The PLN mo

Jorge Almeida, Manfred Kufleitner, Jan Philipp Wächter

We give a ranker-based description using finite-index congruences for the variety $\boldsymbol{\mathrm{DAb}}$ of finite monoids whose regular $\mathcal{D}$-classes form Abelian groups. This combinatorial description yields a normal form for general pseudowords over $\boldsymbol{\mathrm{DAb}}$. For $(\omega - 1)$-terms, this normal form is computable, which y

Henry Kirveslahti, Xiaohan Wang

The Euler Characteristic Transform (ECT) of Turner et al. provides a way to statistically analyze non-diffeomorphic shapes without relying on landmarks. In applications, this transform is typically approximated by a discrete set of directions and heights, which results in potential loss of information as well as problems in inverting the transform. In this w

Chen-Yang Xu, Han-Guang Wang, Lan Zhang, Yong-Hui Zhang

Recently, researchers have begun to experiment with deep learning-based methods for detecting major depressive disor-der (MDD) using electroencephalogram (EEG) signals in search of a more objective means of diagnosis. However, exist-ing spatiotemporal feature extraction methods only consider the functional correlation between multiple electrodes and temporal

Qu Luo, Pei Xiao, Gaojie Chen, Jing Zhu

Sparse code multiple access (SCMA) is a promising non-orthogonal multiple access scheme for enabling massive connectivity in next generation wireless networks. However, current SCMA codebooks are designed with the same size, leading to inflexibility of user grouping and supporting diverse data rates. To address this issue, we propose a variable modulation SC

S. Riggi, T. Cecconello, U. Becciani, F. Vitello

In this paper we present three different applications, based on deep learning methodologies, that we are developing to support the scientific analysis conducted within the ASKAP-EMU and MeerKAT radio surveys. One employs instance segmentation frameworks to detect compact and extended radio sources and imaging artefacts from radio continuum images. Another ap

Julia Sanders, Paolo Muratore-Ginanneschi

Optimal control theory aims to find an optimal protocol to steer a system between assigned boundary conditions while minimizing a given cost functional in finite time. Equations arising from these types of problems are often non-linear and difficult to solve numerically. In this note, we describe numerical methods of integration for two partial differential

Arak M. Mathai, Hans J. Haubold

The neutrino sector of the seesaw-modified Standard Model is investigated under the anarchy principle. The anarchy principle leading to the seesaw ensemble is studied analytically with tools of random matrix theory. The probability density function is obtained.

Deyi Ji, Lanyun Zhu, Siqi Gao, Peng Xu

The ubiquity and value of tables as semi-structured data across various domains necessitate advanced methods for understanding their complexity and vast amounts of information. Despite the impressive capabilities of large language models (LLMs) in advancing the natural language understanding frontier, their application to large-scale tabular data presents si

Uttama Kumar Saint, Suresh Chandra Baral, Dilip Sasmal, P. Maneesha

Each year, the production of synthetic dye wastewater reaches a trillion tons, posing a significant challenge to addressing water scarcity on a global level. Hence, the treatment of wastewater to prevent water scarcity is of prime importance, and failing to do so will increase ecotoxicological risks and human health. Textile wastewater contains harmful dye.

Maria Miguel Beirão, João Matos, Tiago Gonçalves, Camila Kase

Keratitis is an inflammatory corneal condition responsible for 10% of visual impairment in low- and middle-income countries (LMICs), with bacteria, fungi, or amoeba as the most common infection etiologies. While an accurate and timely diagnosis is crucial for the selected treatment and the patients' sight outcomes, due to the high cost and limited availabili

Michael Erol Schaffer, Lutz Terfloth, Carsten Schulte, Heike M. Buhl

In explanations, explainers have mental representations of explainees' developing knowledge and shifting interests regarding the explanandum. These mental representations are dynamic in nature and develop over time, thereby enabling explainers to react to explainees' needs by adapting and customizing the explanation. XAI should be able to react to explainees

Shatadru Chaudhuri, Shahin Nasrin, Asesh Roy Chowdhury

The effect of electrostatic strong-coupling of dust particles along with their self-gravitational force has been analyzed in a three component dusty plasma. The electrons and ions forming the charge neutral background where the electron distribution is assumed to be Maxwellian while the ion distribution is non-thermal. These days, one of the key topics in pl

Arthur Genthon

Single-cell experiments revealed substantial variability in generation times, growth rates but also in birth and division sizes between genetically identical cells. Understanding how these fluctuations determine the fitness of the population, i.e. its growth rate, is necessary in any quantitative theory of evolution. Here, we develop a biologically-relevant

Amir M. Majd

One propounded theory for the presence of chaos in biological neural networks is that it could be involved in discriminating different olfactory stimuli. Inspired by the idea, in this paper, we define the visual ``chaotic perception'' and spell out the challenges we face when conceptualizing it.

Ruidi Qiu, Grace Li Zhang, Rolf Drechsler, Ulf Schlichtmann

Functional simulation is an essential step in digital hardware design. Recently, there has been a growing interest in leveraging Large Language Models (LLMs) for hardware testbench generation tasks. However, the inherent instability associated with LLMs often leads to functional errors in the generated testbenches. Previous methods do not incorporate automat

Cixiao Zhang, Size Peng, Yin Xu, Qingqing Wu

Rate splitting multiple access (RSMA) is regarded as a crucial and powerful physical layer (PHY) paradigm for next-generation communication systems. Particularly, users employ successive interference cancellation (SIC) to decode part of the interference while treating the remainder as noise. However, conventional RSMA systems rely on fixed-position antenna a

David Svitov, Pietro Morerio, Lourdes Agapito, Alessio Del Bue

We present billboard Splatting (BBSplat) - a novel approach for novel view synthesis based on textured geometric primitives. BBSplat represents the scene as a set of optimizable textured planar primitives with learnable RGB textures and alpha-maps to control their shape. BBSplat primitives can be used in any Gaussian Splatting pipeline as drop-in replacement

Zeeshan Rasheed, Malik Abdul Sami, Jussi Rasku, Kai-Kristian Kemell

Present-day software development faces three major challenges: complexity, time consumption, and high costs. Developing large software systems often requires battalions of teams and considerable time for meetings, which end without any action, resulting in unproductive cycles, delayed progress, and increased cost. What if, instead of large meetings with no i

Abhinav Java, Simra Shahid, Chirag Agarwal

The widespread practice of indiscriminate data scraping to fine-tune language models (LMs) raises significant legal and ethical concerns, particularly regarding compliance with data protection laws such as the General Data Protection Regulation (GDPR). This practice often results in the unauthorized use of personal information, prompting growing debate withi

Alessandro Ballatore, Diego Quan Reyes, Hesheng Bao, Jeroen van Oijen

Tabulated chemistry methods are a well-known strategy to efficiently store the flows thermochemical properties. In particular, the Flamelet-Generated Manifold (FGM) is a widely used technique that generates the database with a small number of control variables. In order to build such a manifold, these coordinates must be monotonic in space and time. However,

Junhua Liu, Kwan Hui Lim, Roy Ka-Wei Lee

How objective and unbiased are we while making decisions? This work investigates cognitive bias identification in high-stake decision making process by human experts, questioning its effectiveness in real-world settings, such as candidates assessments for university admission. We begin with a statistical analysis assessing correlations among different decisi

Jiabao Liu, Hiroki Nagakura, Masamichi Zaizen, Lucas Johns

In astrophysical environments such as core-collapse supernovae (CCSNe) and binary neutron star mergers (BNSMs), neutrinos potentially experience substantial flavor mixing due to the refractive effects of neutrino self-interactions. Determining the survival probability of neutrinos in asymptotic states is paramount to incorporating flavor conversions' effects

Xiao Li, Jia-Yi Hou, Jia-Chao Wang, Guang-Wei Wang

Arrays of single atoms trapped in optical tweezers are increasingly recognized as a promising platform for scalable quantum computing. In both the fault-tolerant and NISQ eras, the ability to individually control qubits is essential for the efficient execution of quantum circuits. Time-division multiplexed control schemes based on atom shuttling or beam scan

Robert Tang

We characterise the (closeness classes of) quasi-isometric embeddings as the regular monomorphisms in the coarsely Lipschitz category, formalising the notion that they are isomorphisms onto their image. Furthermore, we prove that the coarsely Lipschitz category is coregular, and hence admits an (Epi, RegMono)--orthogonal factorisation system. Consequently, q

Yueming Hu, Mengde Li, Songhua Yang, Xuetao Li

Robust grasping represents an essential task in robotics, necessitating tactile feedback and reactive grasping adjustments for robust grasping of objects. Previous research has extensively combined tactile sensing with grasping, primarily relying on rule-based approaches, frequently neglecting post-grasping difficulties such as external disruptions or inhere

Zhennan Li, Pengjie Zhang

Determining the spatial curvature $\Omega_K$ of the Universe has long been crucial in cosmology. In practice, this effort is often entangled with assumptions of dark energy. A combination of distance ($D_{\rm M}$, $D_{\rm L}$) and expansion rate ($H(z)$) measurements can break this degeneracy. However, fitting against discrete data points requires parameteri

Andrea Borio, Francesca Marcon, Maria Strazzullo

In this work, we explore the application of Stabilization-Free Virtual Element Methods for Neumann boundary Optimal Control Problems in saddle point formulation. The method is proposed for arbitrary polynomial order of accuracy and general polygonal meshes. Our contribution includes a rigorous a priori error estimate that holds for general polynomial order.

Ying-Lin Li, Chen-Te Ma, Po-Yao Chang

We have drawn connections between the Sachdev-Ye-Kitaev model and the multi-orbit Hatsugai-Kohmoto model, emphasizing their similarities and differences regarding chaotic behaviors. The features of the spectral form factor, such as the dip-ramp-plateau structure and the adjacent gap ratio, indicate chaos in the disordered orbital Hatsugai-Kohmoto model. One

David S. Robertson, Thomas Burnett, Babak Choodari-Oskooei, Munya Dimairo

Regulatory guidance notes the need for caution in the interpretation of confidence intervals (CIs) constructed during and after an adaptive clinical trial. Conventional CIs of the treatment effects are prone to undercoverage (as well as other undesirable properties) in many adaptive designs, because they do not take into account the potential and realised tr

Chenxi Wang, Lei Wang, Wanling Gao, Fanda Fan

The challenge of CPU evaluation lies in the fact that user-perceived performance metrics can only be measured on an independently running system consisting of the CPU and other indispensable components, and hence it is difficult to accurately attribute the deviations in the evaluation outcomes to the differences between the CPUs. Our experiments reveal that

Qu Luo, Jing Zhu, Gaojie Chen, Pei Xiao

The design of efficient sparse codebooks in sparse code multiple access (SCMA) system have attracted tremendous research attention in the past few years. This paper proposes a novel nonlinear SCMA (NL-SCMA) that can subsume the conventional SCMA system which is referred to as linear SCMA, as special cases for downlink channels. This innovative approach allow

Valentin A. Skoutnev, Andrei M. Beloborodov

The Tayler instability (TI) of toroidal magnetic fields is a candidate mechanism for driving turbulence, angular momentum (AM) transport, and dynamo action in stellar radiative zones. Recently \cite{Skoutnev_2024} revisited the linear stability analysis of a toroidal magnetic field in a rotating and stably stratified fluid. In this paper, we extend the analy

Sihui Zhao, Xinbo Wang, Lin Liu, Xin Zhang

Higher-Order Influence Functions (HOIF), developed in a series of papers over the past twenty years, are a fundamental theoretical device for constructing rate-optimal causal-effect estimators from observational studies. However, the value of HOIF for analyzing well-conducted randomized controlled trials (RCT) has not been explicitly explored. In the recent

Geetanjali Sharma, Abhishek Tandon, Gaurav Jaswal, Aditya Nigam

Iris recognition technology plays a critical role in biometric identification systems, but their performance can be affected by variations in iris pigmentation. In this work, we investigate the impact of iris pigmentation on the efficacy of biometric recognition systems, focusing on a comparative analysis of blue and dark irises. Data sets were collected usi

Johan Carlström

Understanding mechanisms of quantum ordering in strongly correlated systems remains a central challenge in condensed matter physics, with implications for designing novel quantum materials. Here, we investigate kinetic antiferromagnetism on a triangular lattice under an applied magnetic field, where spin-polarons emerge as charge-magnon bound states with mut

Jiaxin Wan, Lin Liu, Haoran Wang, Liangwei Li

Total hip arthroplasty (THA) relies on accurate landmark detection from radiographic images, but unstructured data caused by irregular patient postures or occluded anatomical markers pose significant challenges for existing methods. To address this, we propose UNSCT-HRNet (Unstructured CT - High-Resolution Net), a deep learning-based framework that integrate

M. Carmen Jiménez-López, Ana Carolina Moreno-Maldonado, Natividad Martín-Morales, Francisco OValle

There are several methods to improve cancer patient survival rates by inducing hyperthermia in tumor tissues, which involves raising their temperature above 41{\deg}C. These methods utilize different energy sources to deliver heat to the target region, including light, microwaves or radiofrequency electromagnetic fields. We have developed a new, magnetically

Federico Chiariotti, Andrea Munari, Leonardo Badia, Petar Popovski

Age of Incorrect Information (AoII) is particularly relevant in systems where real time responses to anomalies are required, such as natural disaster alerts, cybersecurity warnings, or medical emergency notifications. Keeping system control with wrong information for too long can lead to inappropriate responses. In this paper, we study the Peak AoII (PAoII)

Kenta Hioki, Umpei Miyamoto

We present a method for determining the physical parameters of a Kerr-Newman black hole through shadow observation. In a system comprising a Kerr-Newman black hole, an observer, and a light source, the relevant parameters are mass $M$, specific angular momentum $a$, electric charge $Q$, inclination angle $i$, and distance $r_o$. We consider the cases where t

Zeyu Chen, Enci Wang, Hu Zou, Siwei Zou

Understanding the circumgalactic medium (CGM) distribution of galaxies is the key to revealing the dynamical exchange of materials between galaxies and their surroundings. In this work, we use DESI EDR dataset to investigate the cool CGM of galaxies ($0.3<z<1.7$) with stacking the spectra of background QSOs to obtain Mg II absorption of foreground galaxies.

Enno Diekema

In the standard work of Bierens de Haan about integrals we look at table 129. This table lists a number of integrals of a certain kind. In this paper the table is expanded with a number of similar integrals. These are determined by a number of different methods. Some of these methods are not treated in the freshman standard works on integral calculus. As a b

Limor Hatsor, Artyom Jelnov

The premise of industrial symbiosis IS is that advancing a circular economy that reuses byproducts as inputs in production is valuable for the environment. We challenge this premise in a simple model. Ceteris paribus, IS is an environmentally friendly approach; however, implementing IS may introduce increased pollution into the market equilibrium. The reason

Anton Kuznietsov, Dirk Schweickard, Steven Peters

In automated driving, object detection is crucial for perceiving the environment. Although deep learning-based detectors offer high performance, their black-box nature complicates safety assurance. We propose a novel methodology to analyze how object- and environment-related factors affect LiDAR- and camera-based 3D object detectors. A statistical univariate

Wenwei Lai, Yulin Shao, Yu Ding, Deniz Gunduz

Variable-length feedback coding has the potential to significantly enhance communication reliability in finite block length scenarios by adapting coding strategies based on real-time receiver feedback. Designing such codes, however, is challenging. While deep learning (DL) has been employed to design sophisticated feedback codes, existing DL-aided feedback c

Luigi Cantini, Ali Zahra

We examine the behavior of a single impurity particle embedded within a Totally Asymmetric Simple Exclusion Process (TASEP). By analyzing the impurity's dynamics, characterized by two arbitrary hopping parameters $ \alpha $ and $\beta$, we investigate both its macroscopic impact on the system and its individual trajectory, providing new insights into the int

Albrecht Pfister, Claus Scheiderer

In 1888, Hilbert proved that every nonnegative quartic form $f=f(x,y,z)$ with real coefficients is a sum of three squares of quadratic forms. His proof was ahead of its time and used advanced methods from topology and algebraic geometry. In a 2012 paper we presented a new approach that used only elementary techniques. In this note we add some further simplif

Frederic Koriche, Jean-Marie Lagniez, Stefan Mengel, Chi Tran

Interpretable Machine Learning faces a recurring challenge of explaining the predictions made by opaque classifiers such as ensemble models, kernel methods, or neural networks in terms that are understandable to humans. When the model is viewed as a black box, the objective is to identify a small set of features that jointly determine the black box response

Kathleen MacWilliam, Thomas Dietzen, Randall Ali, Toon van Waterschoot

The estimation of room impulse responses (RIRs) between static loudspeaker and microphone locations can be done using a number of well-established measurement and inference procedures. While these procedures assume a time-invariant acoustic system, time variations need to be considered for the case of spatially dynamic scenarios where loudspeakers and microp

Markus Strobl, Monica E. Baur, Stavros Samothraktis, Florencia Malamud

Energy efficient, safe and reliable Li-ion batteries (LIBs) are required for a wide range of applications. Charging capabilities of thick electrodes still holding their stored high-energy is a most desirable characteristic in future advanced LIBs. The introduction of ultra-thick graphite anode meets limitations in internal electrode transport properties, lea

Carles Milà, Teodimiro Matsena, Edgar Jamisse, Jovito Nunes

Many studies have predicted SocioEconomic Position (SEP) for aggregated spatial units such as villages using satellite data, but SEP prediction at the household level and other sources of imagery have not been yet explored. We assembled a dataset of 975 households in a semi-rural district in southern Mozambique, consisting of self-reported asset, expenditure

Wenke Liu, Hongliang Lu, Xinyue Luo

An edge-colored graph is called \textit{rainbow graph} if all the colors on its edges are distinct. For a given positive integer $n$ and a family of graphs $\mathcal{G}$, the anti-Ramsey number $ar(n, \mathcal{G})$ is the smallest number of colors $r$ required to ensure that, no matter how the edges of the complete graph $K_n$ are colored using exactly $r$ c

Zarin Anjum Madhiha, Antar Mazumder, Sohani Munteha Hiam

Robotic prostheses and exoskeletons can do wonders compared to their non-robotic counterpart. However, in a cost-soaring world where 1 in every 10 patients has access to normal medical prostheses, access to advanced ones is, unfortunately, extremely limited especially due to their high cost, a significant portion of which is contributed to by the diagnosis a

Yewen Cao, Yulin Shao, Rose Qingyang Hu

High peak-to-average power ratio (PAPR) has long posed a challenge for multi-carrier systems, impacting amplifier efficiency and overall system performance. This paper introduces dynamic angle fractional Fourier division multiplexing (DA-FrFDM), an innovative multi-carrier system that effectively reduces PAPR for both QAM and Gaussian signals with minimal si

Théo Gueuret, Akrem Sellami, Chaabane Djeraba

This comprehensive review delves deeply into the various methodologies applied to facial expression recognition (FER) through the lens of graph representation learning (GRL). Initially, we introduce the task of FER and the concepts of graph representation and GRL. Afterward, we discuss some of the most prevalent and valuable databases for this task. We explo

Tushar Shankar Walunj, Shiksha Singhal, Veeraruna Kavitha, Jayakrishnan Nair

In this paper, we introduce a novel equilibrium concept, called the equilibrium cycle, which seeks to capture the outcome of oscillatory game dynamics. Unlike the (pure) Nash equilibrium, which defines a fixed point of mutual best responses, an equilibrium cycle is a set-valued solution concept that can be demonstrated even in games where best responses do n

Hatef Otroshi Shahreza, Sébastien Marcel

Face recognition datasets are often collected by crawling Internet and without individuals' consents, raising ethical and privacy concerns. Generating synthetic datasets for training face recognition models has emerged as a promising alternative. However, the generation of synthetic datasets remains challenging as it entails adequate inter-class and intra-cl

A. V. Nikulov

Jorge Hirsch, in his Comment on my article published in Entropy, agrees that the conventional BCS theory of superconductivity contradicts the second law of thermodynamics. He tries to prove that this theory cannot be valid because of this contradiction, since the Meissner effect is consistent with the second law of thermodynamics, according to his alternativ

Fadi Al Machot, Martin Thomas Horsch, Habib Ullah

Growing concerns over the lack of transparency in AI, particularly in high-stakes fields like healthcare and finance, drive the need for explainable and trustworthy systems. While Large Language Models (LLMs) perform exceptionally well in generating accurate outputs, their "black box" nature poses significant challenges to transparency and trust. To address

Linyang Wang, Wanquan Liu, Bin Zhu

Factor Analysis is about finding a low-rank plus sparse additive decomposition from a noisy estimate of the signal covariance matrix. In order to get such a decomposition, we formulate an optimization problem using the nuclear norm for the low-rank component, the $\ell_0$ norm for the sparse component, and the Kullback-Leibler divergence to control the resid

Shuntaro Aoki, Hajime Otsuka

We demonstrate that a broad class of modular inflation models predicts the emergence of new physics within an energy range of approximately \( 10^{15} \, \mathrm{GeV} \) to \( 10^{17} \, \mathrm{GeV} \). This prediction arises by comparing the moduli-dependent species scale with observational constraints on inflation. Specifically, we illustrate this within

Quan Zhang, Jinwei Fang, Rui Yuan, Xi Tang

Recent breakthroughs in Multimodal Large Language Models (MLLMs) have gained significant recognition within the deep learning community, where the fusion of the Video Foundation Models (VFMs) and Large Language Models(LLMs) has proven instrumental in constructing robust video understanding systems, effectively surmounting constraints associated with predefin

Noah Cape, Shaul Zemel

The fact that Schubert polynomials are the weighted counting functions for reduced RC-graphs, also known as reduced pipe dreams, was established using their generating functions inside an appropriate Demazure algebra. Here we investigate the generating functions of another family of polynomials, the key polynomials, also known as Demazure characters. Each co

Chao Huang, Jiahui Chen, Chen Chen, Chen Chen

The design of crystal materials plays a critical role in areas such as new energy development, biomedical engineering, and semiconductors. Recent advances in data-driven methods have enabled the generation of diverse crystal structures. However, most existing approaches still rely on random sampling without strict constraints, requiring multiple post-process

Fadi Al Machot, Martin Thomas Horsch, Habib Ullah

This paper presents a hybrid methodology that enhances the training process of deep learning (DL) models by embedding domain expert knowledge using ontologies and answer set programming (ASP). By integrating these symbolic AI methods, we encode domain-specific constraints, rules, and logical reasoning directly into the model's learning process, thereby impro

Yuto Kajikiya, Kosuke Namekata, Yuta Notsu, Hiroyuki Maehara

M-dwarfs show frequent flares and associated coronal mass ejections (CMEs) may significantly impact close-in habitable planets. M-dwarf flares sometimes show red/blue asymmetries in the H$\alpha$ line profile, suggesting prominence eruptions as an early stage of CMEs. However, their high-time-cadence observations are limited. We conducted spectroscopic monit

Xiangyu Jiang, Chunjiang Shi, Ying Chen, Ming Gong

We developed PyQUDA, a Python wrapper for QUDA written in Cython, designed to facilitate lattice QCD calculations using the Python programming language. PyQUDA leverages the optimized linear algebra capabilities of NumPy/CuPy/PyTorch, along with the highly optimized lattice QCD operations provided by QUDA to accelerate research. This integration simplifies t

Zhen-Ting Liu, Shang-Tse Chen

Model Inversion (MI) attacks pose a significant threat to the privacy of Deep Neural Networks by recovering training data distribution from well-trained models. While existing defenses often rely on regularization techniques to reduce information leakage, they remain vulnerable to recent attacks. In this paper, we propose the Trapdoor-based Model Inversion D

Xiaozhi Liu, Jinjiang Wei, Yong Xia

Atomic norm minimization (ANM) is a key approach for line spectral estimation (LSE). Most related algorithms formulate ANM as a semidefinite programming (SDP), which incurs high computational cost. In this letter, we revisit the ANM problem and present a novel limit-based formulation, which dissects the essential components of the semidefinite characterizati

Seongjin Choi, Junyeong Park

We generalize cellular sheaf Laplacians on an ordered finite abstract simplicial complex to the set of simplices of a symmetric simplicial set. We construct a functor from the category of hypergraphs to the category of finite symmetric simplicial sets and define cellular sheaf Laplacians on the set of simplices of finite symmetric simplicial set induced by h

Armand Leclerc, Guillaume Laibe, Nicolas Perez

Inertial waves in convective regions of stars exhibit topological properties linked to a Chern number of 1. The first of these is a unique, unidirectional, prograde oscillation mode within the cavity, which propagates at arbitrarily low frequencies for moderate azimuthal wavenumbers. The second one are phase singularities around which the phase winds in Four

Jean-François Marckert, Ludovic Morin

Pick $n$ independent and uniform random points $U_1,\ldots,U_n$ in a compact convex set $K$ of $\mathbb{R}^d$ with volume 1, and let $P^{(d)}_K(n)$ be the probability that these points are in convex position. The Sylvester conjecture in $\mathbb{R}^d$ is that $\min_K P^{(d)}_K(d+2)$ is achieved by the $d$-dimensional simplices $K$ (only). In this paper, we f

Heejoo Kim, Minho Son

We analyze all individual cosmic strings of various lengths in a large ensemble of the global cosmic string networks in the post-inflationary scenario, obtained from numerical simulations on a discrete lattice with $N^3 = 4096^3$. A strong evidence for a logarithmically growing spectral index of the string power spectrum during the evolution is newly reporte

Ru-Xuan Wang, Mao-Zhi Yang

We revisit $B\to K^*\pi$ and $B\to K\rho$ decay processes using the modified perturbative QCD approach, which is developed based on the perturbative QCD approach with a few improvements. A critical infrared cutoff scale $\mu_c$ is introduced to separate hard and soft contributions in the decay process. Hard contributions with scale $\mu$ larger than $\mu_c$

Yutao Shen, Hongyu Zhou, Xin Yang, Xuqi Lu

Biomass estimation of oilseed rape is crucial for optimizing crop productivity and breeding strategies. While UAV-based imaging has advanced high-throughput phenotyping, current methods often rely on orthophoto images, which struggle with overlapping leaves and incomplete structural information in complex field environments. This study integrates 3D Gaussian