May 2024 arXiv papers — page 84

Guangbo Xu

We construct an equivariant extension of the quantum Kirwan map and show that it intertwines the classical Steenrod operation on the cohomology of a classifying space with the quantum Steenrod operation of a monotone symplectic reduction. This provides a new method of computing quantum Steenrod operations developed by Seidel-Wilkins. When specialized to the

Arnab Barman Ray, Trevor Ollis, Sethuraj K. R., Anthony Nickolas Vamivakas

The last few years have witnessed a surge in interest and research efforts in the field of twistronics, especially in low-angle twisted bilayers of transition metal dichalocogenides. These novel material platforms have been demonstrated to host periodic arrays of excitonic quantum emitters, interlayer excitons with long lifetimes, and exotic many-body states

San Kim, Gary Geunbae Lee

Recent advancements in open-domain dialogue systems have been propelled by the emergence of high-quality large language models (LLMs) and various effective training methodologies. Nevertheless, the presence of toxicity within these models presents a significant challenge that can potentially diminish the user experience. In this study, we introduce an innova

Simon Halvdansson

Inspired by the success of recent data augmentation methods for signals which act on time-frequency representations, we introduce an operator which convolves the short-time Fourier transform of a signal with a specified kernel. Analytical properties including boundedness, compactness and positivity are investigated from the perspective of time-frequency anal

Manuel de León, Rubén Izquierdo-López

In this paper we study coisotropic reduction in multisymplectic geometry. On the one hand, we give an interpretation of Hamiltonian multivector fields as Lagrangian submanifolds and prove that $k$-coisotropic submanifolds induce a Lie subalgebra in the algebra of Hamiltonian $(k-1)$-forms, similar to how coisotropic submanifolds in symplectic geometry induce

James Holehouse

For the canonical two-state model of transcription, we derive exact analytic expressions for the entropy production rate of transcription at steady state, and assess detailed balance breaking in transcription. Our analytics allow us to easily evaluate the entropy production rate of thousands of genes across seven datasets of two-state model parameters withou

Tariq Adnan, Abdelrahman Abdelkader, Zipei Liu, Ekram Hossain

We present a framework to recognize Parkinson's disease (PD) through an English pangram utterance speech collected using a web application from diverse recording settings and environments, including participants' homes. Our dataset includes a global cohort of 1306 participants, including 392 diagnosed with PD. Leveraging the diversity of the dataset, spannin

A. T. Costa, J. C. G. Henriques, J. Fernández-Rossier

Altermagnets are a new class of magnetic materials with zero net magnetization (like antiferromagnets) but spin-split electronic bands (like ferromagnets) over a fraction of reciprocal space. As in antiferromagnets, magnons in altermagnets come in two flavours, that either add one or remove one unit of spin to the $S=0$ ground state. However, in altermagnets

Daniele Baieri, Filippo Maggioli, Emanuele Rodolà, Simone Melzi

Neural fields have emerged as a powerful representation for 3D geometry, enabling compact and continuous modeling of complex shapes. Despite their expressive power, manipulating neural fields in a controlled and accurate manner -- particularly under spatial constraints -- remains an open challenge, as existing approaches struggle to balance surface quality,

Weicai Li, Tiejun Lv, Wei Ni, Jingbo Zhao

This paper analyzes the impact of imperfect communication channels on decentralized federated learning (D-FL) and subsequently determines the optimal number of local aggregations per training round, adapting to the network topology and imperfect channels. We start by deriving the bias of locally aggregated D-FL models under imperfect channels from the ideal

Bryan Andrews, Erich Kummerfeld

The number of artificial intelligence algorithms for learning causal models from data is growing rapidly. Most ``causal discovery'' or ``causal structure learning'' algorithms are primarily validated through simulation studies. However, no widely accepted simulation standards exist and publications often report conflicting performance statistics -- even when

Leon A. Kerber, Oliver Kreuz, Tom Ring, Hendrike Braun

Quantum chemical calculations of one-photon absorption, electronic circular dichroism and anisotropy factor spectra for the A-band transition of fenchone, camphor and 3-methylcyclopentanone (3MCP) are reported. While the only weakly allowed nature of the transition leads to comparatively large anisotropies, a proper theoretical description of the absorption

Yuang Zhao, Zhaocheng Du, Qinglin Jia, Linxuan Zhang

With the increase in the business scale and number of domains in online advertising, multi-domain ad recommendation has become a mainstream solution in the industry. The core of multi-domain recommendation is effectively modeling the commonalities and distinctions among domains. Existing works are dedicated to designing model architectures for implicit multi

Zhuoheng Li, Yuheng Pan, Houcheng Yu, Zhiheng Zhang

This paper introduces a novel lightweight computational framework for enhancing images under low-light conditions, utilizing advanced machine learning and convolutional neural networks (CNNs). Traditional enhancement techniques often fail to adequately address issues like noise, color distortion, and detail loss in challenging lighting environments. Our appr

Henry Lamm, Ying-Ying Li, Jing Shu, Yi-Lin Wang

We introduce a block encoding method for mapping discrete subgroups to qubits on a quantum computer. This method is applicable to general discrete groups, including crystal-like subgroups such as $\mathbb{BI}$ of $SU(2)$ and $\mathbb{V}$ of $SU(3)$. We detail the construction of primitive gates -- the inversion gate, the group multiplication gate, the trace

N. D. Andriushin, J. Muller, N. S. Pavlovskii, J. Grumbach

Spin-nematic and spin-smectic phases have been reported in magnetic materials, which break rotational symmetry while preserving translational symmetry along certain directions. However, until now the analogy to liquid crystals remained incomplete because no magnetic analog of cholesteric order was known. Here we show that the bilayer perovskite Sr$_3$Fe$_2$O

Sibylle Marcotte, Rémi Gribonval, Gabriel Peyré

Conservation laws are well-established in the context of Euclidean gradient flow dynamics, notably for linear or ReLU neural network training. Yet, their existence and principles for non-Euclidean geometries and momentum-based dynamics remain largely unknown. In this paper, we characterize "all" conservation laws in this general setting. In stark contrast to

V. Ya. Derr

The present book gives a systematic overview of function theory and the theory of Stieltjes integral. In particular, we give a detailed account of the theory of functions of bounded variation and of the theory of regulated functions (= functions having finite one-sided limits at each point of their domain). We also present a detailed discussion of $\sigma$-c

Joseph Donato, Monica Lewis

In the study of Hilbert schemes, the integer partition $\lambda$ helps researchers identify some geometric and combinatorial properties of the scheme in question. To aid researchers in extracting such information from a Hilbert polynomial, we describe an efficient algorithm which can identify if $p(x)\in\mathbb{Q}[x]$ is a Hilbert polynomial and if so, recov

Jin Jiang, Qixuan Gao, Zekang Zhou, Cheng Shen

Moir\'e systems featuring flat electronic bands exhibit a vast landscape of emergent exotic quantum states, making them one of the resourceful platforms in condensed matter physics in recent times. Tuning these systems via twist angle and the electric field greatly enhances our comprehension of their strongly correlated ground states. Here, we report a techn

Abdurahmman Alzahrani, Eyad Babkier, Faisal Yanbaawi, Firas Yanbaawi

In the current era of digital communication and widespread use of social media, it is crucial to develop an understanding of persuasive techniques employed in written text. This knowledge is essential for effectively discerning accurate information and making informed decisions. To address this need, this paper presents a comprehensive empirical study focuse

Cédric Baudet

We consider the Helmholtz equation in an angular sector partially covered by a homogeneous layer of small thickness, denoted $\varepsilon$. We propose in this work an asymptotic expansion of the solution with respect to $\varepsilon$ at any order. This is done using matched asymptotic expansion, which consists here in introducing different asymptotic expansi

Luca Aceto, Antonis Achilleos, Elli Anastasiadi, Adrian Francalanza

This paper focuses on the runtime verification of hyperproperties expressed in Hyper-recHML, an expressive yet simple logic for describing properties of sets of traces. To this end, we consider a simple language of monitors that observe sets of system executions and report verdicts w.r.t. a given Hyper-recHML formula. We first employ a unique omniscient moni

Kiarash Golzadeh, Lukasz Golab, Jaroslaw Szlichta

Expert search and team formation systems operate on collaboration networks, with nodes representing individuals, labeled with their skills, and edges denoting collaboration relationships. Given a keyword query corresponding to the desired skills, these systems identify experts that best match the query. However, state-of-the-art solutions to this problem lac

Giacomo Cacciapaglia, Stefan Hohenegger, Francesco Sannino

Gravitational wave observation has provided numerous insights into the merger of astrophysical black holes. In contrast to other violent events (e.g. supernovae), they are, however, not expected to lead to significant emissions of photons and neutrinos. In this paper we discuss a scenario that would lead to characteristic observable gamma ray bursts, which w

Haomin Fei, Ping Cui, Zhenyu Zhang

Two-dimensional materials are of interest for their exotic properties, for example, superconductivity, and highly tunability. Focusing on phonon-mediating superconductivity, one would propose to promote critical temperature by substituting heavy elements by lighter ones, in order to increase Debye temperature. Following recent experimental progress in transi

Philipp Keßler, Tim Waldsauer, Vedran Jovic, Martin Kamp

We present a systematic growth study of epitaxial RuO$_2$(110) and IrO$_2$(110) on TiO$_2$(110) substrates by pulsed laser deposition. We describe the main challenges encountered in the growth process, such as a deteriorating material flux due to laser induced target metallization or the delicate balance of under- vs over-oxidation of the 'stubborn' Ru and I

Matthias Ruf, Mathias Schäffner

We consider periodic homogenization of hyperelastic models incorporating incompressible behavior via the constraint $\det(\nabla u)=1$. We show that the 'usual' homogenized integral functional $\int W_{\rm hom}(\nabla u)\,dx$, where $W_{\rm hom}$ is the standard multicell-formula of non-convex homogenization restricted to volume preserving deformations, yiel

Martin Böhm, Zachary Friggstad, Tobias Mömke, Joachim Spoerhase

We give improved approximations for two metric Traveling Salesman Problem (TSP) variants. In Ordered TSP (OTSP) we are given a linear ordering on a subset of nodes $o_1, \ldots, o_k$. The TSP solution must have that $o_{i+1}$ is visited at some point after $o_i$ for each $1 \leq i < k$. This is the special case of Precedence-Constrained TSP ($PTSP$) in which

Xiaofei Yu, Yitong Li, Jie Ma

Remote sensing image change captioning (RSICC) aims at generating human-like language to describe the semantic changes between bi-temporal remote sensing image pairs. It provides valuable insights into environmental dynamics and land management. Unlike conventional change captioning task, RSICC involves not only retrieving relevant information across differe

Federica Ferretti, Irene Giardina, Tomas Grigera, Giulia Pisegna

Flocking systems are known to be strongly out of equilibrium. Energy input occurs at the individual level to ensure self-propulsion, and the individual motility in turn contributes to ordering, enhancing information propagation and strengthening collective motion. However, even beyond ordering, a crucial feature of natural aggregations is response. How, then

James Negus, Julia M. Comerford, Francisco Müller Sánchez

Broad H$\alpha$ and H$\beta$ emission lines (FWHM > 1,000 km s$^{-1}$) are incredibly efficient tracers of the high-velocity clouds encircling Active Galactic Nuclei (AGN). As a result, we search for these broad line AGN in the Sloan Digital Sky Survey's Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) catalog. We identify 301 broad-line H$\alpha$

Zerui Zhang, Zhichao Sun, Zelong Liu, Bo Du

Medical anomaly detection is a critical research area aimed at recognizing abnormal images to aid in diagnosis.Most existing methods adopt synthetic anomalies and image restoration on normal samples to detect anomaly. The unlabeled data consisting of both normal and abnormal data is not well explored. We introduce a novel Spatial-aware Attention Generative A

Jinghao Wang, Yanping Wu, Xiaoyang Wang, Ying Zhang

Given a graph G, a budget k and a misinformation seed set S, Influence Minimization (IMIN) via node blocking aims to find a set of k nodes to be blocked such that the expected spread of S is minimized. This problem finds important applications in suppressing the spread of misinformation and has been extensively studied in the literature. However, existing so

L. Maggio, D. Triggiani, P. Facchi, V. Tamma

It is demonstrated a two-photon interfering technique based on polarization-resolved measurements for the simultaneous estimation with the maximum sensitivity achievable in nature of multiple parameters associated with the polarization state of two interfering photonic qubits. This estimation is done by exploiting a novel interferometry technique based on po

Kazuhiro Kikuchi, Yu Mizukoshi, Takumi Fukuda, Paul Fons

We investigate the ultrafast spin dynamics of the prototypical topological insulator $\mathrm{Bi_{2}Se_{3}}$ using time-resolved Kerr-rotation (polarization-change) measurements across near-infrared wavelengths. The Kerr-rotation angle $\Delta \theta_{K}$ of $\mathrm{Bi_{2}Se_{3}}$ was found to significantly depend on photon energy around a resonance transit

Liming Wu, Zhichao Hou, Jirui Yuan, Yu Rong

Learning to represent and simulate the dynamics of physical systems is a crucial yet challenging task. Existing equivariant Graph Neural Network (GNN) based methods have encapsulated the symmetry of physics, \emph{e.g.}, translations, rotations, etc, leading to better generalization ability. Nevertheless, their frame-to-frame formulation of the task overlook

V. P. Utrobin, N. N. Chugai

We present an alternative model of unusual type-IIP SN 2018gj. Despite the short plateau and early gamma-rays escape seeming to favor low-mass ejecta, our hydrodynamic model requires a large ejected mass (about 23 Msun). The high ejecta velocity, we find from hydrogen lines in early spectra, is among crucial constraints on the hydrodynamic model. We recover

Alon Kukliansky, Lukasz Cincio, Ed Younis, Costin Iancu

Existing numerical optimizers deployed in quantum compilers use expensive $\mathcal{O}(4^n)$ matrix-matrix operations. Inspired by recent advances in quantum machine learning (QML), QFactor-Sample replaces matrix-matrix operations with simpler $\mathcal{O}(2^n)$ circuit simulations on a set of sample inputs. The simpler the circuit, the lower the number of r

Yuki Uehara, Naoki Nishimura, Yilin Li, Jie Yang

Currently, many e-commerce websites issue online/electronic coupons as an effective tool for promoting sales of various products and services. We focus on the problem of optimally allocating coupons to customers subject to a budget constraint on an e-commerce website. We apply a robust portfolio optimization model based on customer segmentation to the coupon

Volker Knauthe, Arne Rak, Tristan Wirth, Thomas Pöllabauer

Semantic Image Segmentation facilitates a multitude of real-world applications ranging from autonomous driving over industrial process supervision to vision aids for human beings. These models are usually trained in a supervised fashion using example inputs. Distribution Shifts between these examples and the inputs in operation may cause erroneous segmentati

Cristiano Muzzi, Ronald Santiago Cortes, Devendra Singh Bhakuni, Asja Jelić

We perform a principal component analysis (PCA) of two one-dimensional lattice models belonging to distinct nonequilibrium universality classes - directed bond percolation and branching and annihilating random walks with even number of offspring. We find that the uncentered PCA of datasets storing various system's configurations can be successfully used to d

Steven J. Jones, Robert E. Wray

One part of complying with norms, rules, and preferences is incorporating constraints (such as knowledge of ethics) into one's goal formulation and planning processing. We explore in a simple domain how the encoding of knowledge in different ethical frameworks influences an agent's goal formulation and planning processing and demonstrate ability of an agent

Volker Knauthe, Paul Weitz, Thomas Pöllabauer, Tristan Wirth

Computer vision techniques are on the rise for industrial applications, like process supervision and autonomous agents, e.g., in the healthcare domain and dangerous environments. While the general usability of these techniques is high, there are still challenging real-world use-cases. Especially transparent structures, which can appear in the form of glass d

Jonathan Gagné

Nearby associations of stars which are coeval are important benchmark laboratories because they provide robust measurements of stellar ages. The study of such coeval groups makes it possible to better understand star formation by studying the initial mass function, the binary fraction or the circumstellar disks of stars, to determine how the initially dense

George Zograf, Andrew B. Yankovich, Betül Küçüköz, Abhay V. Agrawal

Transition metal dichalcogenide (TMD) materials have attracted substantial interest due to their remarkable excitonic, optical, electrical, and mechanical properties, which are highly dependent on their crystal structure. Controlling the crystal structure of these materials is essential for fine-tuning their performance, $\textit{e.g.}$, linear and nonlinear

Anirudh Dash

This article explores the intersection of the Coupon Collector's Problem and the Orthogonal Matrix Factorization (OMF) problem. Specifically, we derive bounds on the minimum number of columns $p$ (in $\mathbf{X}$) required for the OMF problem to be tractable, using insights from the Coupon Collector's Problem. Specifically, we establish a theorem outlining t

Mohsen Jozani, Jason A. Williams, Ahmed Aleroud, Sarbottam Bhagat

This study explores the relationship between informational support seeking questions, responses, and helpfulness ratings in online health communities. We created a labeled data set of question-response pairs and developed multimodal machine learning and deep learning models to reliably predict informational support questions and responses. We employed explai

Carlos Munuera-Javaloy, Ander Tobalina, Jorge Casanova

Diamond-based quantum sensors have enabled high-resolution NMR spectroscopy at the microscale in scenarios where fast molecular motion averages out dipolar interactions among target nuclei. However, in samples with low-diffusion, ubiquitous dipolar couplings challenge the extraction of relevant spectroscopic information. In this work we present a protocol th

James Requeima, John Bronskill, Dami Choi, Richard E. Turner

Machine learning practitioners often face significant challenges in formally integrating their prior knowledge and beliefs into predictive models, limiting the potential for nuanced and context-aware analyses. Moreover, the expertise needed to integrate this prior knowledge into probabilistic modeling typically limits the application of these models to speci

Nikita Guseynov, Xiajie Huang, Nana Liu

One of the most promising applications of quantum computers is solving partial differential equations (PDEs). By using the Schrodingerisation technique - which converts non-conservative PDEs into Schrodinger equations - the problem can be reduced to Hamiltonian simulations. The particular class of Hamiltonians we consider is shown to be sufficient for simula

Albrecht von Faber, Christopher Hins, Khalil Zakeri

The propagation of magnons along a symmetry path may depend on the direction of propagation, similar to many other quasiparticles in nature. This phenomenon is commonly referred to as nonreciprocity. In addition to the fact that it is of great interest to understand the fundamental physical mechanism leading to this nonreciprocal propagation, the phenomenon

G Rajasekhar, Jahangir Alam

Leveraging complementary relationships across modalities has recently drawn a lot of attention in multimodal emotion recognition. Most of the existing approaches explored cross-attention to capture the complementary relationships across the modalities. However, the modalities may also exhibit weak complementary relationships, which may deteriorate the cross-

Mario Kahlhofer, Stefan Rass

Cyber deception techniques that are tightly intertwined with applications pose significant technical challenges in production systems. Security measures are usually the responsibility of a system operator, but they are typically limited to accessing built software artifacts, not their source code. This limitation makes it particularly challenging to deploy c

Haoqing Ning, Marios Maimaris, Jiewen Wei, Emilie Gérouville

Femtosecond-fast and nanometre-size pulses of electrons are emerging as unique probes for ultrafast dynamics at the nanoscale. Presently, such pulses are achievable only in highly sophisticated ultrafast electron microscopes or equally complex setups involving few-cycle-pulsed lasers with stable carrier-envelope phase (CEP) and nanotip probes. Here, we show

Jjahao Zhang, Yin Gu, Deyu Sun, Yuhua Gao

Cervical cancer is one of the leading causes of death in women, and brachytherapy is currently the primary treatment method. However, it is important to precisely define the extent of paracervical tissue invasion to improve cancer diagnosis and treatment options. The fusion of the information characteristics of both computed tomography (CT) and magnetic reso

Alejandro Linares-Barranco, Luciano Prono, Robert Lengenstein, Giacomo Indiveri

With the rise of artificial intelligence, neural network simulations of biological neuron models are being explored to reduce the footprint of learning and inference in resource-constrained task scenarios. A mainstream type of such networks are spiking neural networks (SNNs) based on simplified Integrate and Fire models for which several hardware accelerator

Huini Liu, Nianyu Yi, Peimeng Yin

In this paper, we propose a mass- and modified energy-conservative relaxation Crank-Nicolson finite element method for the Schr\"{o}dinger-Poisson equation. Utilizing only a single auxiliary variable, we simultaneously reformulate the distinct nonlinear terms present in both the Schr\"{o}dinger equation and the Poisson equation into their equivalent expressi

Li-Yang Tseng, Tzu-Ling Lin, Hong-Han Shuai, Jen-Wei Huang

Nowadays, humans are constantly exposed to music, whether through voluntary streaming services or incidental encounters during commercial breaks. Despite the abundance of music, certain pieces remain more memorable and often gain greater popularity. Inspired by this phenomenon, we focus on measuring and predicting music memorability. To achieve this, we coll

J. Kurpas, A. D. Schwope, A. M. Pires, F. Haberl

The SRG/eROSITA All-Sky Survey (eRASS) allows for the creation of a complete sample of X-ray dim isolated neutron stars (XDINSs), which will significantly facilitate the study of their population properties, evolution, and connection to other families of isolated neutron stars (INSs). In this work, we conduct a systematic search for XDINSs on the western Gal

Aljaž Krpan, Janez Povh, Dunja Pucher

Given an undirected graph, the stable set problem asks to determine the cardinality of the largest subset of pairwise non-adjacent vertices. This value is called the stability number of the graph, and its computation is an NP-hard problem. In this paper, we solve the stable set problem using the D-Wave quantum annealer. By formulating the problem as a quadra

Adrian Mariano, Jacob Lenz, Dmitro Martynowych, Christopher Miller

Magnetic current imaging (MCI) is useful for non-destructive characterization of microelectronics, including both security analysis and failure analysis, because magnetic fields penetrate the materials that comprise these components to enable through-package imaging of chip activity. Of particular interest are new capabilities offered by emerging magnetic fi

Zhaojian Yu, Yinghao Wu, Zhuotao Deng, Yansong Tang

In recent years, large-scale auto-regressive models have made significant progress in various tasks, such as text or video generation. However, the environmental impact of these models has been largely overlooked, with a lack of assessment and analysis of their carbon footprint. To address this gap, we introduce OpenCarbonEval, a unified framework for integr

Arushi Jain, Shubham Paliwal, Monika Sharma, Lovekesh Vig

Robotic Process Automation (RPA) systems face challenges in handling complex processes and diverse screen layouts that require advanced human-like decision-making capabilities. These systems typically rely on pixel-level encoding through drag-and-drop or automation frameworks such as Selenium to create navigation workflows, rather than visual understanding o

Bowen Zhang, Wei Chen, Hung-Chun Chiu, Charles Zhang

Static analysis techniques enhance the security, performance, and reliability of programs by analyzing and portraiting program behaviors without the need for actual execution. In essence, static analysis takes the Intermediate Representation (IR) of a target program as input to retrieve essential program information and understand the program. However, there

Tong Zeng, Daniel E. Acuna

Obtaining funding is an important part of becoming a successful scientist. Junior faculty spend a great deal of time finding the right agencies and programs that best match their research profile. But what are the factors that influence the best publication--grant matching? Some universities might employ pre-award personnel to understand these factors, but n

Hung Nguyen-Kha, Vu Nguyen Ha, Eva Lagunas, Symeon Chatzinotas

This paper studies the channel model for the integrated satellite-terrestrial networks operating at C-band under deployment in dense urban and rural areas. Particularly, the interference channel from the low-earth-orbit (LEO) satellite to the dense urban area is analyzed carefully under the impact of the environment's characteristics, i.e., the building dens

Max Kerr Winter, Liesbeth M. C. Janssen

Deep Neural Networks (DNNs) share important similarities with structural glasses. Both have many degrees of freedom, and their dynamics are governed by a high-dimensional, non-convex landscape representing either the loss or energy, respectively. Furthermore, both experience gradient descent dynamics subject to noise. In this work we investigate, by performi

Jiachen Hu, Tongyang Li, Xinzhao Wang, Yecheng Xue

We systematically investigate quantum algorithms and lower bounds for mean estimation given query access to non-identically distributed samples. On the one hand, we give quantum mean estimators with quadratic quantum speed-up given samples from different bounded or sub-Gaussian random variables. On the other hand, we prove that, in general, it is impossible

Wei Ji, Li Li, Zheqi Lv, Wenqiao Zhang

In our increasingly interconnected world, where intelligent devices continually amass copious personalized multi-modal data, a pressing need arises to deliver high-quality, personalized device-aware services. However, this endeavor presents a multifaceted challenge to prevailing artificial intelligence (AI) systems primarily rooted in the cloud. As these sys

Vincent Caudrelier, Anup Anand Singh, Benoît Vicedo

We construct a Lagrangian multiform for the class of cyclotomic (rational) Gaudin models by formulating its hierarchy within the Lie dialgebra framework of Semenov-Tian-Shansky and by using the framework of Lagrangian multiforms on coadjoint orbits. This provides the first example of a Lagrangian multiform for an integrable hierarchy whose classical $r$-matr

Mercedes Pelegrin, Martina Cerulli

Aircraft conflict resolution is one of the major tasks of computer-aided air traffic management and represents a challenging optimization problem. Many models and methods have been proposed to assist trajectory regulation to avoid conflicts. However, the question of testing the different mathematical optimization approaches against each other is still open.

Samik Basu, Aloke Kr. Ghosh, Subhankar Sau

In this paper, we analyze the possible homotopy types of the total space of a principal $SU(2)$-bundle over a $3$-connected $8$-dimensional Poincar\'{e} duality complex. Along the way, we also classify the $3$-connected $11$-dimensional complexes $E$ formed from a wedge of $S^4$ and $S^7$ by attaching a $11$-cell.

Wang Jia, Hang Xu

We conduct an active flow control (AFC) study on the mass flow rate of synthetic jets on the upper and lower surfaces of a square cylinder using a deep reinforcement learning (DRL) algorithm, with a focus on investigating the influence of the position and width of the synthetic jets on the flow control performance. At Reynolds numbers ($Re$) of 100 and 500,

Xinyi Wang, Grazziela Figueredo, Ruizhe Li, Wei Emma Zhang

Automatic radiology report generation can alleviate the workload for physicians and minimize regional disparities in medical resources, therefore becoming an important topic in the medical image analysis field. It is a challenging task, as the computational model needs to mimic physicians to obtain information from multi-modal input data (i.e., medical image

Zavareh Bozorgasl, Hao Chen

In this paper, we introduce Wav-KAN, an innovative neural network architecture that leverages the Wavelet Kolmogorov-Arnold Networks (Wav-KAN) framework to enhance interpretability and performance. Traditional multilayer perceptrons (MLPs) and even recent advancements like Spl-KAN face challenges related to interpretability, training speed, robustness, compu

Muhittin Evren Aydin, Rafael López, Adela Mihai

Consider the Euclidean space $\mathbb{R}^3$ endowed with a canonical semi-symmetric non-metric connection determined by a vector field $\mathsf{C}\in\mathfrak{X}(\mathbb{R}^3)$. We study surfaces when the sectional curvature with respect to this connection is constant. In case that the surface is cylindrical, we obtain full classification when the rulings ar

Kaijian Xing, Daniel McEwen, Weiyao Zhao, Abdulhakim Bake

Van der Waals electrode integration is a promising strategy to create near-perfect interfaces between metals and two-dimensional materials, with advantages such as eliminating Fermi-level pinning and reducing contact resistance. However, the lack of a simple, generalizable pick-and-place transfer technology has greatly hampered the wide use of this technique

Gordon Chin, Carrie M. Anderson, Jennifer Bergner, Nicolas Biver

The SALTUS Probe mission will provide a powerful far-infrared (far-IR) pointed space observatory to explore our cosmic origins and the possibility of life elsewhere. The observatory employs an innovative deployable 14-m aperture, with a sunshield that will radiatively cool the off-axis primary to <45K. This cooled primary reflector works in tandem with cryog

Mohammed Larbi Labbi

A $(p,q)$-double form on a Riemannian manifold $(M,g)$ can be considered simultaneously as a vector-valued differential $p$-form over $M$ or alternatively as a vector-valued $q$-form. Accordingly, the usual Hodge-de Rham Laplacian on differential forms can be extended to double forms in two ways. The differential operators obtained in this way are denoted by

Qi Zhou, Zhigui Lin, Carlos Alberto Santos

To understand how impulsive intervention and regional evolution jointly influence the spread of faecal-oral diseases, this paper develops an impulsive faecal-oral model in a periodically evolving environment. The well-posedness of the model is first checked. Then, the existence of the principal eigenvalue dependent on impulse intensity and evolving rate is p

Chang Liu, Yu Tan, Yong Zhang, Zhaoyi Liu

Understanding the nature of brittle failure in ferroelectric materials is essential, but difficult due to the complex interaction between mechanical and electrical concentrated fields near the crack tip. In this work, an extended phase-field model incorporating multiple order parameters is constructed to analyze the coupled evolution of fracture and domain b

Muhittin Evren Aydin, Rafael López, Adela Mihai

In this paper, we study translation surfaces in the Euclidean space endowed with a canonical semi-symmetric non-metric connection. We completely classify the translation surfaces of constant sectional curvature with respect to this connection, proving that they are generalized cylinders. This consequence is the same as in the case of the Levi-Civita connecti

Jialin Lei, Jiming Ma, Qiang Zhang

We study when a group of form $G\times\mathbb{Z}^m (m\geq 1)$ has the finitely generated fixed subgroup property of automorphisms ($\rm{FGFP}_a$), by using the BNS-invariant, and provide some partial answers and non-trivial examples.

Flavia Esposito, Andersen Ang

Nonnegative Matrix Factorization (NMF) is the problem of approximating a given nonnegative matrix M through the product of two nonnegative low-rank matrices W and H. Traditionally NMF is tackled by optimizing a specific objective function evaluating the quality of the approximation. This assessment is often done based on the Frobenius norm (F-norm). In this

Runwei Guan, Ruixiao Zhang, Ningwei Ouyang, Jianan Liu

Embodied perception is essential for intelligent vehicles and robots in interactive environmental understanding. However, these advancements primarily focus on vision, with limited attention given to using 3D modeling sensors, restricting a comprehensive understanding of objects in response to prompts containing qualitative and quantitative queries. Recently

Douglas R. Stinson

We study two types of nestings of balanced incomplete block designs (BIBDs). In both types of nesting, we wish to add a point (the nested point) to every block of a $(v,k,\lambda)$-BIBD in such a way that we end up with a partial $(w,k+1,\lambda+1)$-BIBD for some $w \geq v$. In the case where $w > v$, we are introducing $w-v$ new points. This is called a wea

Hongsheng Wang, Yang Wang, Yalan Liu, Fayuan Hu

In real-world road scenes, diverse material properties lead to complex light reflection phenomena, making accurate color reproduction crucial for enhancing the realism and safety of simulated driving environments. However, existing methods often struggle to capture the full spectrum of lighting effects, particularly in dynamic scenarios where viewpoint chang

Libo Qin, Qiguang Chen, Xiachong Feng, Yang Wu

While large language models (LLMs) like ChatGPT have shown impressive capabilities in Natural Language Processing (NLP) tasks, a systematic investigation of their potential in this field remains largely unexplored. This study aims to address this gap by exploring the following questions: (1) How are LLMs currently applied to NLP tasks in the literature? (2)

Yusheng Lei, Ran Ni

Disordered hyperuniform structures are an exotic state of matter having suppressed density fluctuations at large length-scale similar to perfect crystals and quasicrystals but without any long range orientational order. In the past decade, an increasing number of non-equilibrium systems were found to have dynamic hyperuniform states, which have emerged as a

Janaka Adassuriya, Shashikiran Ganesh, Peter de Cat, Santosh Joshi

We present one high-resolution and a time series of 561 low-resolution follow-up spectroscopic observations of SZ Lyn. It is a high-amplitude Delta Scuti-type pulsating star in a binary system. The photometric observations reveal the existence of radial and non-radial oscillation modes in SZ Lyn. In spectroscopy, the variation of equivalent width of the line

He Zhou, Hui Zou

The mainstream theory of hypothesis testing in high-dimensional regression typically assumes the underlying true model is a low-dimensional linear regression model, yet the Box-Cox transformation is a regression technique commonly used to mitigate anomalies like non-additivity and heteroscedasticity. This paper introduces a more flexible framework, the non-p

Valentin Puente-Varona

This paper presents a highly speculative model encompassing the cortex, thalamus, and hippocampus of the mammalian brain. While the majority of computational neuroscience models are founded upon empirical evidence, this model is predicated upon a hardware proposal for a machine learning accelerator. Such a device was designed to perform a specific task, such

Giuliano Pretti, Robert E. Bird, Nathan D. Gavin, William M. Coombs

The Material Point Method (MPM) is widely used to analyse coupled (solid-water) problems under large deformations/displacements. However, if not addressed carefully, MPM u-p formulations for poro-mechanics can be affected by two major sources of instability. Firstly, inf-sup condition violation can arise when the spaces for the displacement and pressure fiel

Jinyi Deng, Xinru Tang, Zhiheng Yue, Guangyang Lu

Given the increasing complexity of AI applications, traditional spatial architectures frequently fall short. Our analysis identifies a pattern of interconnected, multi-faceted tasks encompassing both AI and general computational processes. In response, we have conceptualized "Orchestrated AI Workflows," an approach that integrates various tasks with logic-dr

Doğa Gürsoy, Dina Sheyfer, Michael Wojcik, Wenjun Liu

Coded apertures, traditionally employed in x-ray astronomy for imaging celestial objects, are now being adapted for micro-scale applications, particularly in studying microscopic specimens with synchrotron light diffraction. In this paper, we focus on micro-coded aperture imaging and its capacity to accomplish depth-resolved micro-diffraction analysis within

Yu-Xin Peng, Si-Qiang Luo, Xiang Liu

In this work, we systematically study the radiative decays of singly heavy baryons, a crucial aspect of their spectroscopic behavior. To enhance the accuracy of our calculations, we utilize numerical spatial wave functions for the singly heavy baryons obtained through the Gaussian expansion method, which also yields their mass spectrum. As hadron spectroscop

Shuai Shao, Yu Guan, Victor Sanchez

Human Activity Recognition (HAR) has become increasingly popular with ubiquitous computing, driven by the popularity of wearable sensors in fields like healthcare and sports. While Convolutional Neural Networks (ConvNets) have significantly contributed to HAR, they often adopt a frame-by-frame analysis, concentrating on individual frames and potentially over

Gouthamaan Manimaran, Sadasivan Puthusserypady, Helena Domínguez, Adrian Atienza

Electrocardiogram (ECG) signals are critical for diagnosing heart conditions and capturing detailed cardiac patterns. As wearable single-lead ECG devices become more common, efficient analysis methods are essential. We present NERULA (Non-contrastive ECG and Reconstruction Unsupervised Learning Algorithm), a self-supervised framework designed for single-lead

Jing Ding, Hanxiao Xiang, Wenqiang Zhou, Naitian Liu

The stacking order and twist angle provide abundant opportunities for engineering band structures of two-dimensional materials, including the formation of moire bands, flat bands, and topologically nontrivial bands. The inversion symmetry breaking in rhombohedral-stacked transitional metal dichalcogenides (TMDCs) endows them with an interfacial ferroelectric