May 2024 arXiv papers — page 97

Jaroslaw S. Jaracz

We give an alternate proof of one of the results given in [16] showing that initial data sets with boundary for the Einstein equations $(M, g, k)$ satisfying the dominant energy condition can be conformally deformed to the strict dominant energy condition, while preserving the character of the boundary (minimal, future trapped, or past trapped) while changin

Nadezda Alexandrovna Knorozova, Alessandro Ronca

Recurrent Neural Cascades (RNC) are the class of recurrent neural networks with no cyclic dependencies among recurrent neurons. Their subclass RNC+ with positive recurrent weights has been shown to be closely connected to the star-free regular languages, which are the expressivity of many well-established temporal logics. The existing expressivity results sh

Zoey Chen, Aaron Walsman, Marius Memmel, Kaichun Mo

Constructing simulation scenes that are both visually and physically realistic is a problem of practical interest in domains ranging from robotics to computer vision. This problem has become even more relevant as researchers wielding large data-hungry learning methods seek new sources of training data for physical decision-making systems. However, building s

Tharun V. Puthanveettil, Fnu Obaid ur Rahman

Object tracking is a fundamental task in computer vision with broad practical applications across various domains, including traffic monitoring, robotics, and autonomous vehicle tracking. In this project, we aim to develop a sophisticated aerial vehicle system known as Track Anything Rapter (TAR), designed to detect, segment, and track objects of interest ba

Alessandro Aldini, Davide Fazio, Pierluigi Graziani, Raffaele Mascella

Logical investigations of the notion of secrecy are typically concentrated on tools for deducing whether private information is well hidden from unauthorized, direct, or indirect access attempts. This paper proposes a multi-agent, normal multi-modal logic to capture salient features of secrecy's intentions. Specifically, we focus on the intentions, beliefs,

Daniel B Durham, Manifa Noor, Khandker Akif Aabrar, Yuzi Liu

In hafnia-based thin-film ferroelectric devices, chemical phenomena during growth and processing such as oxygen vacancy formation and interfacial reactions appear to strongly affect device performance. However, the nanoscale structure, chemistry, and electrical potentials in these devices are not fully known, making it difficult to understand their influence

John M. Myers, Hadi Madjid

Although quantum states nicely explain experiments, the outcomes of experiments are not states. Instead, outcomes correspond to probability distributions. Twenty years ago we proved categorically that probability distributions leave open a choice of quantum states to explain experiments that is resolvable only by a move beyond logic, which, inspired or not,

A. F. Vasil'ev, T. I. Vasil'eva

Let $t$ be a fixed natural number. A subgroup $H$ of a group $G$ will be called $\mathrm{K}$-$\mathbb{P}_{t}$-subnormal in $G$ if there exists a chain of subgroups $H = H_{0} \leq H_{1} \leq \cdots \leq H_{m-1} \leq H_{m} = G$ such that either $H_{i-1}$ is normal in $H_{i}$ or $|H_{i} : H_{i-1}|$ is a some prime $p$ and $p-1$ is not divisible by the $(t+1)$t

Vikranth Udandarao, Pratyush Gupta

In the contemporary film industry, accurately predicting a movie's earnings is paramount for maximizing profitability. This project aims to develop a machine learning model for predicting movie earnings based on input features like the movie name, the MPAA rating of the movie, the genre of the movie, the year of release of the movie, the IMDb Rating, the vot

Luyanda Mazwi, Soebur Razzaque, Lutendo Nyadzani

The joint detection of the gravitational wave (GW) event GW170817 and the short-duration gamma-ray burst (SGRB) event GRB 170817A, marked the beginning of GW multi-messenger astronomy and confirmed that binary neutron star mergers are progenitors of at least some SGRBs. An estimated joint detection rate of 0.3 - 1.7 per year between the LIGO-Hanford, LIGO-Li

Swayamtrupta Panda, Francisco Pozo Nuñez, Eduardo Bañados, Jochen Heidt

Reverberation mapping accurately determines virial black hole masses only for redshifts $z <$ 0.2 by utilizing the relationship between the H$\beta$ broad-line region (BLR) size and the 5100 Angstroms continuum luminosity established with $\sim 200$ active galactic nuclei (AGN). For quasars at $z \sim 2-3$ determining the BLR size is time-consuming and limit

Mohamed Jleli, Cristina Maria Pacurar, Bessem Samet

We are concerned with the study of fixed points for mappings $T: X\to X$, where $(X,G)$ is a $G$-metric space in the sense of Mustafa and Sims. After the publication of the paper [Journal of Nonlinear and Convex Analysis. 7(2) (2006) 289--297] by Mustafa and Sims, a great interest was devoted to the study of fixed points in $G$-metric spaces. In 2012, the fi

Li Jiang, Yusen Wu, Junwu Xiong, Jingqing Ruan

Preference datasets are essential for incorporating human preferences into pre-trained language models, playing a key role in the success of Reinforcement Learning from Human Feedback. However, these datasets often demonstrate conflicting alignment objectives, leading to increased vulnerability to jailbreak attacks and challenges in adapting downstream tasks

Ricardo Martin Abraham-Ekeroth, Dani Torrent

Traditional approaches to optical matter often involve complex illumination fields with costly and unstable setups, requiring strong gradient forces, high-intensity laser spots that could harm samples, and substrate support. For binding, attractive inter-particle forces may not be sufficient to assemble systems due to unbalanced components such as centrifuga

Axel Henningsson, Mustafacan Kutsal, Jonathan P. Wright, Wolfgang Ludwig

Strength, ductility, and failure properties of metals are tailored by plastic deformation routes. Predicting these properties requires modeling of the structural dynamics and stress evolution taking place on several length scales. Progress has been hampered by a lack of representative 3D experimental data at industrially relevant degrees of deformation. We p

Andrew H. Song, Richard J. Chen, Tong Ding, Drew F. K. Williamson

Representation learning of pathology whole-slide images (WSIs) has been has primarily relied on weak supervision with Multiple Instance Learning (MIL). However, the slide representations resulting from this approach are highly tailored to specific clinical tasks, which limits their expressivity and generalization, particularly in scenarios with limited data.

Arpan Sinha, Debasish Chaudhuri

Using the Lebwohl-Lasher interaction for reciprocal local alignment, we present a comprehensive phase diagram for a dry, apolar, active nematic system using its stochastic \new{off-lattice} dynamics. \new{The nematic-isotropic transition in this system is first-order and occurs alongside a fluctuation-dominated phase separation.} Our phase diagram identifies

Pedro Mendoza Zélis, Daniel G. Actis, Giuliano A. Basso, Gustavo A. Pasquevich

In application as hyperthermia and nanowarming, power dissipation arises when the time-dependent magnetization $M(t)$ of an out-of-equilibrium system of nanoparticles lags behind the applied field $H(t)$. The key parameter governing this process is the relaxation time $\tau$ of the system, which induces a phase shift $\phi_n$ between $H(t)$ and every nth har

Zishan Gu, Fenglin Liu, Changchang Yin, Ping Zhang

The adoption of large language models (LLMs) in healthcare has attracted significant research interest. However, their performance in healthcare remains under-investigated and potentially limited, due to i) they lack rich domain-specific knowledge and medical reasoning skills; and ii) most state-of-the-art LLMs are unimodal, text-only models that cannot dire

Mohsen Dehghankar, Rahul Raychaudhury, Stavros Sintos, Abolfazl Asudeh

The potential harms of algorithmic decisions have ignited algorithmic fairness as a central topic in computer science. One of the fundamental problems in computer science is Set Cover, which has numerous applications with societal impacts, such as assembling a small team of individuals that collectively satisfy a range of expertise requirements. However, des

Gilberto Bini, Luca Ugaglia

We study cones of pseudoeffective cycles on the blow up of $({\mathbb P}^1)^n$ at points in very general position, proving some results concerning their structure. In particular we show that in some cases they turn out to be generated by exceptional classes and fiber classes relatively to the projections onto a smaller number of copies of projective lines.

Ghazaleh Mahmoudi, Babak Behkamkia, Sauleh Eetemadi

Stance detection, the classification of attitudes expressed in a text towards a specific topic, is vital for applications like fake news detection and opinion mining. However, the scarcity of labeled data remains a challenge for this task. To address this problem, we propose Dynamic Model Adaptation with Contextual Data Generation (DyMoAdapt) that combines F

José-María Martín-Olalla, Antonio Vidal-Crespo, Alejandro F. Manchón-Gordón, Francisco Javier Romero

We study the thermal properties of a bulk Ni55Fe19Ga26 Heusler alloy in a conduction calorimeter. At slow heating and cooling rates (1K/h), we compare as-cast and annealed samples. We report a smaller thermal hysteresis after the thermal treatment due to the stabilization of the 14M modulated structure in the martensite phase. In ultraslow experiments (40mK/

Weisheng Wu

In this paper, we conduct a comprehensive study on ergodic properties of the geodesic flow on a $C^\infty$ uniform visibility manifold $M$ without conjugate points. If $M$ is a closed surface of genus at least two without conjugate points, and with continuous Green bundles and bounded asymptote, we study the geometric properties of singular geodesics and sho

Christian Mehl, Volker Mehrmann, Michał Wojtylak

The spectral theory for operator pencils and operator differential-algebraic equations is studied. Special focus is laid on singular operator pencils and three different concepts of singularity of operator pencils are introduced. The concepts are analyzed in detail and examples are presented that illustrate the subtle differences. It is investigated how thes

Heiner Kremer, Bernhard Schölkopf

Instrumental variable (IV) regression can be approached through its formulation in terms of conditional moment restrictions (CMR). Building on variants of the generalized method of moments, most CMR estimators are implicitly based on approximating the population data distribution via reweightings of the empirical sample. While for large sample sizes, in the

Hyejin Kim, Yiqing Zhou, Yichen Xu, Kaarthik Varma

The imminent era of error-corrected quantum computing urgently demands robust methods to characterize complex quantum states, even from limited and noisy measurements. We introduce the Quantum Attention Network (QuAN), a versatile classical AI framework leveraging the power of attention mechanisms specifically tailored to address the unique challenges of lea

Juan P. G. Villaluenga, David Brunete, Francisco Javier Cao-Garcia

Different types of ligands compete in binding to polymers with different consequences for the physical and chemical properties of the resulting complex. Here, we derive a general kinetic model for the competitive binding kinetics of different types of ligands to a linear polymer, using the McGhee and von Hippel detailed binding site counting procedure. The d

Manuel Mañas, Miguel Rojas

Performing both right and left multiplication operations using general regular matrix polynomials, which need not be monic and may possess leading coefficients of arbitrary rank, on a rectangular matrix of measures associated with mixed multiple orthogonal polynomials, reveals corresponding Christoffel formulas. These formulas express the perturbed mixed mul

Shengxiang Sun, Shenzhe Zhu

Numerous studies on adversarial attacks targeting self-driving policies fail to incorporate realistic-looking adversarial objects, limiting real-world applicability. Building upon prior research that facilitated the transition of adversarial objects from simulations to practical applications, this paper discusses a modified gradient-based texture optimizatio

Raul Wolters, Oksana Iarygina, Ana Achucarro

Rapid-turn slow-roll inflationary trajectories have been shown to be an attractor in two-field models, provided the turn rate is near constant and larger than the slow-roll parameters. These trajectories can produce primordial spectra consistent with current observations on CMB scales. We present the generalized consistency condition for sustained rapid-turn

Num Prasad Acharya, Suresh Basnet, Amar P. Misra, Raju Khanal

We study the oblique propagation of weakly nonlinear dust-ion-acoustic (DIA) solitary waves (SWs) and shocks in collisional magnetized nonthermal dusty plasmas that are relevant in laboratory and space (Saturn's E-ring) environments. We consider plasmas to be composed of $q$-nonextensive hot electrons, thermal positive ions, and immobile negatively charged d

Xiaoyu Chen, Mengfan Fu, Yujing Huang, Xinwei Deng

Regression analysis with probability measures as input predictors and output response has recently drawn great attention. However, it is challenging to handle multiple input probability measures due to the non-flat Riemannian geometry of the Wasserstein space, hindering the definition of arithmetic operations, hence additive linear structure is not well-defi

Kristian Wold, Pedro Ribeiro, Sergey Denisov

Random unitaries are an important resource for quantum information processing. While their universal properties have been thoroughly analyzed, it is not known what happens to these properties when the unitaries are sampled on the present-day noisy intermediate-scale quantum (NISQ) computers. We implement parameterized circuits, which have been proposed as a

Alok Kumar Pandey, Alam Ali, Ashok Kumar Pathak

This article presents a new class of generalized transmuted lifetime distributions which includes a large number of lifetime distributions as sub-family. Several important mathematical quantities such as density function, distribution function, quantile function, moments, moment generating function, stress-strength reliability function, order statistics, R\'

Richard McQueen, Chjan C. Lim

The vortex gas is an approximation used to study 2D flow using statistical mechanics methodologies. We investigate low positive Onsager temperature states for the vortex gas on an annular domain. Using mean field theory, microcanonical sampling of the point gas model, and canonical sampling of a lattice model, we find evidence for edge modes at low energy st

Mireia Hernandez Caralt, Clarence Boon Liang Ng, Marek Rei

Electronic Health Records (EHR) serve as a valuable source of patient information, offering insights into medical histories, treatments, and outcomes. Previous research has developed systems for detecting applicable ICD codes that should be assigned while writing a given EHR document, mainly focusing on discharge summaries written at the end of a hospital st

Shayan Rokhva, Babak Teimourpour, Amir Hossein Soltani

In contemporary society, the application of artificial intelligence for automatic food recognition offers substantial potential for nutrition tracking, reducing food waste, and enhancing productivity in food production and consumption scenarios. Modern technologies such as Computer Vision and Deep Learning are highly beneficial, enabling machines to learn au

Barbara Topolovec, Olivera Jovanovic, Nevena Puac, Nikola Skoro

This study evaluates the effectiveness of non-thermal plasma at atmospheric pressure (NTP APPJ) for treating PFAS - contaminated water in different matrices. Successful removal of several perfluoroalkyl carboxylic acids (PFCAs) (C6 to C4), perfluroalkane sulfonic acids (PFSAs) (C8 to C4) and perfluropolyethers (PFPEs) (GenX and ADONA) PFAS compounds was achi

Guillaume Jaume, Lukas Oldenburg, Anurag Vaidya, Richard J. Chen

Self-supervised learning (SSL) has been successful in building patch embeddings of small histology images (e.g., 224x224 pixels), but scaling these models to learn slide embeddings from the entirety of giga-pixel whole-slide images (WSIs) remains challenging. Here, we leverage complementary information from gene expression profiles to guide slide representat

Mohammad Umar, Mohammad Hasan, Vibhav Narayan Singh, Bhabani Prasad Mandal

To bridge the fractal and non-fractal potentials we introduce the concept of generalized unified Cantor potential (GUCP) with the key parameter $N$ which represents the potential count at the stage $S=1$. This system is characterized by total span $L$, stages $S$, scaling parameter $\rho$ and two real numbers $\mu$ and $\nu$. Notably, the polyadic Cantor pot

Peng Li, Yuan Liu, Xiaoxiao Long, Feihu Zhang

In this paper, we introduce Era3D, a novel multiview diffusion method that generates high-resolution multiview images from a single-view image. Despite significant advancements in multiview generation, existing methods still suffer from camera prior mismatch, inefficacy, and low resolution, resulting in poor-quality multiview images. Specifically, these meth

Stanislav Škorňa, Jitka Machalová, Jana Burkotová, Karel Hron

Reliable estimation and approximation of probability density functions is fundamental for their further processing. However, their specific properties, i.e. scale invariance and relative scale, prevent the use of standard methods of spline approximation and have to be considered when building a suitable spline basis. Bayes Hilbert space methodology allows to

Sangyeop Yeo, Yoojin Jang, Jaejun Yoo

In this paper, we address the challenge of compressing generative adversarial networks (GANs) for deployment in resource-constrained environments by proposing two novel methodologies: Distribution Matching for Efficient compression (DiME) and Network Interactive Compression via Knowledge Exchange and Learning (NICKEL). DiME employs foundation models as embed

Baolong Bi, Shenghua Liu, Lingrui Mei, Yiwei Wang

The knowledge within large language models (LLMs) may become outdated quickly. While in-context editing (ICE) is currently the most effective method for knowledge editing (KE), it is constrained by the black-box modeling of LLMs and thus lacks interpretability. Our work aims to elucidate the superior performance of ICE on the KE by analyzing the impacts of i

Bhaskar Mitra, Henriette Cramer, Olya Gurevich

Robust access to trustworthy information is a critical need for society with implications for knowledge production, public health education, and promoting informed citizenry in democratic societies. Generative AI technologies may enable new ways to access information and improve effectiveness of existing information retrieval systems but we are only starting

Sanjay Raman, Cumrun Vafa

We define the notion of a marked moduli space as the parameter space of a physical theory together with all of its observables. In geometric examples, this coincides with the mathematical notion of Teichm\"uller space. We propose two new Swampland principles about the geometry of marked moduli spaces: We conjecture that a marked moduli space is always contra

Terence Tao

Fix $k \geq 2$. For any $N \geq 1$, let $F_k(N)$ denote the cardinality of the largest subset of $\{1,\dots,N\}$ that does not contain $k$ distinct elements whose product is a square. Erd\H{o}s, S\'ark\H{o}zy, and S\'os showed that $F_2(N) = (\frac{6}{\pi^2}+o(1)) N$, $F_3(N) = (1-o(1))N$, $F_k(N) \asymp N/\log N$ for even $k \geq 4$, and $F_k(N) \asymp N$ f

Partha Pratim Ghosh, Bastien Mallein

We consider a last progeny modified branching random walk, in which the position of each particle at the last generation $n$ is modified by an i.i.d. copy of a random variable $Y$. Depending on the asymptotic properties of the tail of $Y$, we describe the asymptotic behaviour of the extremal process of this model as $n \to \infty$.

Alejandro Mata Ali, Adriano Mauricio Lusso, Edgar Mencia

We present a modular hierarchy of private delegated quantum computation protocols tailored to user-level and industry-level settings and parameterized by the quantum resources available to the client. For each protocol, we specify the client capabilities, delegated gate set, adversarial model, transcript leakage and resulting privacy claims. The hierarchy se

Mengxin Zheng, Cheng Chu, Qian Lou, Nathan Youngblood

This paper presents \textit{OFHE}, an electro-optical accelerator designed to process Discretized TFHE (DTFHE) operations, which encrypt multi-bit messages and support homomorphic multiplications, lookup table operations and full-domain functional bootstrappings. While DTFHE is more efficient and versatile than other fully homomorphic encryption schemes, it

CMS Collaboration

A search is reported for charge-parity $CP$ violation in D$^0$ $\to$ K$^0_\mathrm{S}$K$^0_\mathrm{S}$ decays, using data collected in proton-proton collisions at $\sqrt{s}$ = 13 TeV recorded by the CMS experiment in 2018. The analysis uses a dedicated data set that corresponds to an integrated luminosity of 41.6 fb$^{-1}$, which consists of about 10 billion

Qunxi Zhu, Wei Lin

Continuous-time generative models, such as Flow Matching (FM), construct probability paths to transport between one distribution and another through the simulation-free learning of the neural ordinary differential equations (ODEs). During inference, however, the learned model often requires multiple neural network evaluations to accurately integrate the flow

Cao Huy Linh, Quang Hoa Tran, Thanh Vu

We classify all graphs for which the Rees algebras of their edge ideals are normal and have regularity equal to their matching numbers.

Pascal Fong, Matilde Maccan

We study relatively minimal surfaces equipped with a strongly isotrivial elliptic fibration in positive characteristic by means of the notion of equivariantly normal curves introduced and developed recently by Brion. Such surfaces are isomorphic to a contracted product $E\times^G X$, where $E$ is an elliptic curve, $G$ is a finite subgroup scheme of $E$ and

Upakar Bhatta

The combination of cloud technology, machine learning, and data visualization techniques allows hybrid enterprise networks to hold massive volumes of data and provide employees and customers easy access to these cloud data. These massive collections of complex data sets are facing security challenges. While cloud platforms are more vulnerable to security thr

Csaba Sándor, Maciej Zakarczemny

Denote by $N(n)$ the number of integer solutions $(x_1,\,x_2,\ldots ,x_n)$ of the equation $x_1+x_2+\ldots+x_n=x_1x_2\cdot\ldots\cdot x_n$ such that $x_1\ge x_2\ge\ldots\ge x_n\ge 1$, $n \in \mathbb{Z}^+$. The aim of this paper are is twofold: first we present an asymptotic formula for $\sum\limits_{2\le n\le x}N(n)$, then we verify that the counting functio

Paramvir Ahlawat, Cecilia Clementi, Felix Musil, Maria-Andreea Filip

Metal halide perovskite-based semi-conducting hetero-structures have emerged as promising electronics for solar cells, light-emitting diodes, detectors, and photo-catalysts. Perovskites' efficiency, electronic properties and their long-term stability directly depend on their morphology [1-24]. Therefore, to manufacture stable and higher efficiency perovskite

Carlo Alberto Barbano, Riccardo Renzulli, Marco Grosso, Domenico Basile

In this paper, we present the major results from the Covid Radiographic imaging System based on AI (Co.R.S.A.) project, which took place in Italy. This project aims to develop a state-of-the-art AI-based system for diagnosing Covid-19 pneumonia from Chest X-ray (CXR) images. The contributions of this work are manyfold: the release of the public CORDA dataset

Congchi Yin, Ziyi Ye, Piji Li

Many recent studies have shown that the perception of speech can be decoded from brain signals and subsequently reconstructed as continuous language. However, there is a lack of neurological basis for how the semantic information embedded within brain signals can be used more effectively to guide language reconstruction. Predictive coding theory suggests the

R. Boda, B. Panda, S. Kumar

This study presents innovative nested-isotropic lattices for additive manufacturing, drawing inspiration from bio-architectures found in cortical bone osteons, golden spirals, and fractals. These lattices provide tunable anisotropy by integrating architectural elements like ``nesting orders (NOs)'' and corresponding ``nesting orientations (NORs),'' along wit

Lilia Anguelova

Recent studies, in the context of consistency conditions for rapid-turn and third order slow-roll inflation in two-field models, raised the question whether this regime can be sustained for more than a few e-folds of expansion. We answer this question in the affirmative by showing that the consistency conditions themselves ensure the longevity of the rapid-t

S. Hubrig, S. D. Chojnowski, S. P. Jarvinen, I. Ilyin

Context. In chemically peculiar Ap/Bp stars with large-scale organised magnetic fields with a simple centred dipole configuration, the ratio between the maximum and the minimum of the mean magnetic field modulus is of the order of 1.25. Values of 2 or more are observed only for very few Ap/Bp stars and are indicative of a very unusual magnetic field geometry

Vsevolod I. Ivanov

In this paper, we obtain a new proof of Fritz John necessary optimality conditions for vector problems applying Kakutani fixed point theorem and Hadamard directional derivative. We also derive a similar proof of second-order Fritz John necessary optimality conditions. Sufficient conditions for weak global efficiency with generalized convex functions and loca

Mattes Ohlenbusch, Christian Rollwage, Simon Doclo

Own voice pickup for hearables in noisy environments benefits from using both an outer and an in-ear microphone outside and inside the occluded ear. Due to environmental noise recorded at both microphones, and amplification of the own voice at low frequencies and band-limitation at the in-ear microphone, an own voice reconstruction system is needed to enable

Xinyi Lu, Xu Wang

Evaluating the quality of automatically generated question items has been a long standing challenge. In this paper, we leverage LLMs to simulate student profiles and generate responses to multiple-choice questions (MCQs). The generative students' responses to MCQs can further support question item evaluation. We propose Generative Students, a prompt architec

Youbang Sun, Shixiang Chen, Alfredo Garcia, Shahin Shahrampour

In this paper, we investigate decentralized non-convex optimization with orthogonal constraints. Conventional algorithms for this setting require either manifold retractions or other types of projection to ensure feasibility, both of which involve costly linear algebra operations (e.g., SVD or matrix inversion). On the other hand, infeasible methods are able

Domitilla Tapinassi, Daniele Galli, Marco Padovani, Henrik Beuther

Maps of polarized dust emission of molecular clouds reveal the morphology of the magnetic field associated with star-forming regions. In particular, polarization maps of hub-filament systems show the distortion of magnetic field lines induced by gas flows onto and inside filaments. We aim to understand the relation between the curvature of magnetic field lin

Carlos Muñoz-Moncayo

This work addresses the imposition of outflow boundary conditions for one-dimensional conservation laws. While a highly accurate numerical solution can be obtained in the interior of the domain, boundary discretization can lead to unphysical reflections. We investigate and implement some classes of relaxation methods and far-field operators to deal with this

Petr Slaný

Cosmic repulsion represented by a small positive value of the cosmological constant changes significantly properties of central gravitational fields at large distances, leading to existence of a static (or turnaround) radius where gravitational attraction of a center is just balanced by cosmic repulsion. Analyzing behavior of radial timelike geodesics in the

Qiusong Chen, Wei Hou, Song Lin, GaoFu Liu

The traditional Bragg crystal diffraction experiments use X-rays, harming the participants bodies. Therefore, many universities have not offered this basic experiment. Although microwave simulation Bragg experiments can reduce harm, there are still some potential dangers. To solve this dilemma, this article takes ultrasound as the experimental object and use

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

The processes $h_c\to\gamma P(P = \eta^\prime,~\eta,~\pi^0)$ are studied with a sample of $(27.12\pm0.14)\times10^{8}$ $\psi(3686)$ events collected by the BESIII detector at the BEPCII collider. The decay $h_{c}\rightarrow\gamma\eta$ is observed for the first time with the significance of $9.0\,\sigma$, and the branching fraction is determined to be $(3.77\

Klaus Metsch

The generalized $q$-Kneser graph $K_q(n,k,t)$ for integers $k>t>0$ and $n>2k-t$ is the graph whose vertices are the $k$-dimensional subspaces of an $n$-dimensional $F_q$-vectorspace with two vertices $U_1$ and $U_2$ adjacent if and only if $\dim(U_1\cap U_2)<t$. We determine the treewidth of the generalized $q$-Kneser graphs $K_q(n,k,t)$ when $t\ge 2$ and $n

Mu-Chun Chen, Hao-Yang Liu, Qi-Yan Zhang, Jun Zhang

We investigate the prospect of probing massive fields and testing gravitational theories with multiband observations of gravitational waves emitted from coalescing compact binaries. Focusing on the dipole radiation induced by a massive field, we show that multiband observations can probe the field with mass ranging from $10^{-16} $ to $10^{-15} {\rm eV}$, a

Jialong Guo, Xinghao Chen, Yehui Tang, Yunhe Wang

Transformers have become foundational architectures for both natural language and computer vision tasks. However, the high computational cost makes it quite challenging to deploy on resource-constraint devices. This paper investigates the computational bottleneck modules of efficient transformer, i.e., normalization layers and attention modules. LayerNorm is

Panos Fitsilis, Vyron Damasiotis, Vasileios Kyriatzis, Paraskevi Tsoutsa

The rapid integration of Large Language Models (LLMs) into various industries presents both revolutionary opportunities and unique challenges. This research aims to establish a scalable and efficient framework for LLM customization, exploring how DevOps practices should be adapted to meet the specific demands of LLM customization. By integrating ontologies,

Daniel Commey, Sena Hounsinou, Garth V. Crosby

This study proposes a framework to enhance privacy in Blockchain-based Internet of Things (BIoT) systems used in the healthcare sector. The framework addresses the challenge of leveraging health data for analytics while protecting patient privacy. To achieve this, the study integrates Differential Privacy (DP) with Federated Learning (FL) to protect sensitiv

Subhankar Maity, Aniket Deroy, Sudeshna Sarkar

In the era of generative artificial intelligence (AI), the fusion of large language models (LLMs) offers unprecedented opportunities for innovation in the field of modern education. We embark on an exploration of prompted LLMs within the context of educational and assessment applications to uncover their potential. Through a series of carefully crafted resea

Dazhuo Wei

In this paper, I introduce a random attention span model (RAS) which uses stopping time to identify decision-makers' behavior under limited attention. Unlike many limited attention models, the RAS identifies preferences using time variation without any need for menu variation. In addition, the RAS allows the consideration set to be correlated with the prefer

Bowen Chen, Namgi Han, Yusuke Miyao

Large Language Models (LLMs), trained on massive corpora with billions of parameters, show unprecedented performance in various fields. Though surprised by their excellent performances, researchers also noticed some special behaviors of those LLMs. One of those behaviors is memorization, in which LLMs can generate the same content used to train them. Though

G. Mustafa, Zinnat Hassan, P. K. Sahoo

We explore the possibility of traversable wormhole formation in the dark matter halos in the context of $f(Q)$ gravity. We obtain the exact wormhole solutions with anisotropic matter source based on the Bose-Einstein condensate, Navarro-Frenk-White, and pseudo-isothermal matter density profiles. Notably, we present a novel wormhole solution supported by thes

Xuanli He, Qiongkai Xu, Jun Wang, Benjamin I. P. Rubinstein

Modern NLP models are often trained on public datasets drawn from diverse sources, rendering them vulnerable to data poisoning attacks. These attacks can manipulate the model's behavior in ways engineered by the attacker. One such tactic involves the implantation of backdoors, achieved by poisoning specific training instances with a textual trigger and a tar

Manan Shah, Yash Bhalgat

This report is a reproducibility study of the paper "CDUL: CLIP-Driven Unsupervised Learning for Multi-Label Image Classification" (Abdelfattah et al, ICCV 2023). Our report makes the following contributions: (1) We provide a reproducible, well commented and open-sourced code implementation for the entire method specified in the original paper. (2) We try to

Aditya Challa, Sravan Danda, Laurent Najman, Snehanshu Saha

Standard ML models fail to infer the context distribution and suitably adapt. For instance, the learning fails when the underlying distribution is actually a mixture of distributions with contradictory labels. Learning also fails if there is a shift between train and test distributions. Standard neural network architectures like MLPs or CNNs are not equipped

Holly Pacey

Lepton flavour violation (LFV), and lepton flavour university violation (LFUV), are striking signatures of beyond the Standard Model (BSM) physics. Recent searches for these at the ATLAS and CMS experiments are presented, using proton-proton collisions with a centre of mass energy of 13 TeV. A range of models and signatures are considered, including leptoqua

Zhuowen Li, Chunhua Zhu, Guoliang Lü, Lin Li

Wolf-Rayet stars (WRs) are very important massive stars. However, their origin and the observed binary fraction within the entire WR population are still debated. We investigate some possible merger channels for the formation of WRs, including main sequence (MS)/ Hertzsprung Gap (HG) + MS, He + HG/ Giant Branch (GB). We find that many products produced via b

Ryohei Kageyama

A simplicial analogy of Chen's iterated integral was introduced in another paper. However, its properties were hardly investigated in the paper. In particular, no mention is made of whether it coincides with Chen's iterated integral as a special case. In this paper, we answer this question. This paper consists of two main parts. One of them is the research o

Yue Li, Lei Wang, Junjie Li, Jincheng Wang

Based on the idea of maintaining physical diffuse interface kinetics, enhancing interfacial diffusivity has recently provided a new direction for quantitative phase-field simulation at microstructural length and time scale. Establishing a general relationship between interface diffusivity and width is vital to facilitate the practical application. However, i

Diata Traore, Olivier Adjoua, César Feniou, Ioanna-Maria Lygatsika

Using GPU-accelerated state-vector emulation, we propose to embed a quantum computing ansatz into density-functional theory via density-based basis-set corrections (DBBSC) to obtain quantitative quantum-chemistry results on molecules that would otherwise require brute-force quantum calculations using hundreds of logical qubits. Indeed, accessing a quantitati

Omer Belhasin, Idan Kligvasser, George Leifman, Regev Cohen

Analyzing the cardiovascular system condition via Electrocardiography (ECG) is a common and highly effective approach, and it has been practiced and perfected over many decades. ECG sensing is non-invasive and relatively easy to acquire, and yet it is still cumbersome for holter monitoring tests that may span over hours and even days. A possible alternative

Joeri De Vadder, Jordi De Jonghe, Rony Keppens

To expand on recent work, we introduce collisional terms in the analysis of the warm ion-electron, two-fluid equations for a homogeneous plasma at rest. Consequently, the plasma is now described by six variables: the magnetisation, the ratio of masses over charges, the electron and ion sound speeds, the angle between the wave vector and the magnetic field, a

Zidong Cao, Lin Wang

Monocular 360 depth estimation is challenging due to the inherent distortion of the equirectangular projection (ERP). This distortion causes a problem: spherical adjacent points are separated after being projected to the ERP plane, particularly in the polar regions. To tackle this problem, recent methods calculate the spherical neighbors in the tangent domai

Kwangjae Lee, Jung Hoon Lee, Wan Choi

In this paper, we introduce a novel approach to user-centric association and feedback bit allocation for the downlink of a cell-free massive MIMO (CF-mMIMO) system, operating under limited feedback constraints. In CF-mMIMO systems employing frequency division duplexing, each access point (AP) relies on channel information provided by its associated user equi

Jukka Tuomela

When considering Navier-Stokes equations on Riemannian manifolds one frequently encounters situations where the manifold is embedded in the ambient Euclidean space. In this context it is interesting to investigate what is the precise relationship of the diffusion operator in the ambient space to the diffusion operator on the manifold. The present paper gives

Tanner Nathan Carawan

Waldhausen's $S_\bullet$-construction gives a way to define the algebraic $K$-theory space of a category with cofibrations. Specifically, the $K$-theory space of a category with cofibrations $\mathcal{C}$ can be defined as the loop space of the realization of the simplicial topological space $|iS_\bullet \mathcal{C} |$. Dyckerhoff and Kapranov observed that

Guanyu Zhang, Xiaying Lyu, Yulu Qin, Yaolong Li

The on-chip measurement of polarization states plays an increasingly crucial role in modern sensing and imaging applications. While high-performance monolithic linearly polarized photodetectors have been extensively studied, integrated circularly polarized light (CPL) photodetectors are still hindered by inadequate discrimination capability. In this study, w

Suyash Vardhan Mathur, Akshett Rai Jindal, Manish Shrivastava

While significant work has been done in the field of NLP on vertical thinking, which involves primarily logical thinking, little work has been done towards lateral thinking, which involves looking at problems from an unconventional perspective and defying existing conceptions and notions. Towards this direction, SemEval 2024 introduces the task of BRAINTEASE

Fei Li, Song Zhang, Kai-Jia Sun, Yu-Gang Ma

The production of light nuclei in isobaric $^{96}_{44}$Ru + $^{96}_{44}$Ru and $^{96}_{40}$Zr + $^{96}_{40}$Zr collisions, ranging from $\sqrt{s_{NN}}$ = 7.7 to 200 GeV, are studied using the string melting version of A Multi Phase Transport (AMPT) model in combination with a coalescence approach to light nuclei production. From the calculated yields, transv

Nikolai Meshcheriakov, Victoria Shatalova, Konstantin Stepanyantz

We investigate the structure of renormalization constants within the MS-like renormalization prescriptions for a version of dimensional regularization in which the dimensionful regularization parameter $\Lambda$ differs from the renormalization point $\mu$. Namely, we rewrite the all-loop equations relating coefficients at higher $\varepsilon$-poles and high

Nathaniel Johnston, Shirin Moein, Sarah Plosker

A matrix is said to have factor width at most $k$ if it can be written as a sum of positive semidefinite matrices that are non-zero only in a single $k \times k$ principal submatrix. We explore the ``factor-width-$k$ rank'' of a matrix, which is the minimum number of rank-$1$ matrices that can be used in such a factor-width-at-most-$k$ decomposition. We show