November 2024 arXiv papers — page 70

John Banovetz, Yousuke Utsumi, Joshua Meyers, Maya Beleznay

During electro-optical testing of the camera for the upcoming Vera C. Rubin Observatory Legacy Survey of Space and Time, a unique low-signal pattern was found in differenced pairs of flat images used to create photon transfer curves, with peak-to-peak variations of a factor of 10^-3. A turbulent pattern of this amplitude was apparent in many differenced flat

Gurucharan Mohanta

We propose a class of models based on the parity invariant Left-Right Symmetric Model (LRSM), which incorporates the mechanism of radiative generation of fermion masses while simultaneously possessing the solution to the Strong CP problem. A flavour non-universal gauged abelian symmetry is imposed on top of LRSM, which helps in inducing the masses of second

Limin Wen, Junxue Li, Tong Pu, Yiying Zhang

Conditional risk measures and their associated risk contribution measures are commonly employed in finance and actuarial science for evaluating systemic risk and quantifying the effects of risk interactions. This paper introduces various types of contribution ratio measures based on the MCoVaR, MCoES, and MMME studied in Ortega-Jim\'enez et al. (2021) and Da

Bin Chen, Gehui Li, Rongyuan Wu, Xindong Zhang

Real-world image super-resolution (Real-ISR) aims to reconstruct high-resolution images from low-resolution inputs degraded by complex, unknown processes. While many Stable Diffusion (SD)-based Real-ISR methods have achieved remarkable success, their slow, multi-step inference hinders practical deployment. Recent SD-based one-step networks like OSEDiff and S

Simon Zacharias Lahme, Dominik Dorsel, Heidrun Heinke, Pascal Klein

This exploratory field study investigates the integration of innovative forms of recitation tasks in a first-year introductory mechanics course, focusing on smartphone-based experimental tasks alongside programming and standard recitation tasks. Smartphones, combined with external sensor modules, serve as a gateway enabling students to conduct various low-co

Maxim Khlopov

BSM physics, on which the now standard inflationary cosmology with baryosynthesis and dark matter/energy is based, inevitably leads to cosmological scenarios beyond this standard model, involving specific model dependent choice of models and parameters of BSM physics. Such model dependent cosmological predictions may have already found confirmations in the p

Lars Fluri, A. Ege Yilmaz, Denis Bieri, Thomas Ankenbrand

This research investigates liquidity dynamics in fractional ownership markets, focusing on illiquid alternative investments traded on a FinTech platform. By leveraging empirical data and employing agent-based modeling (ABM), the study simulates trading behaviors in sell offer-driven systems, providing a foundation for generating insights into how different m

Alexey Markin, Sriram Vijendran, Oliver Eulenstein

Phylogenetic networks are directed acyclic graphs that depict the genomic evolution of related taxa. Reticulation nodes in such networks (nodes with more than one parent) represent reticulate evolutionary events, such as recombination, reassortment, hybridization, or horizontal gene transfer. Typically, the complexity of a phylogenetic network is expressed i

Ashadul Halder, Madhurima Pandey, Rupa Basu, Debasish Majumdar

We explore the influence of interactions between dark matter (DM) and dark energy (DE) on the cosmic evolution of the Universe within a viscous dark energy (VDE) framework. Moving beyond traditional interacting dark energy (IDE) models, we propose a generalized IDE model adaptable to diverse IDE scenarios via IDE coupling parameters. In order to investigate

Hoang-Quan Nguyen, Xuan-Bac Nguyen, Hugh Churchill, Arabinda Kumar Choudhary

Vision-brain understanding aims to extract semantic information about brain signals from human perceptions. Existing deep learning methods for vision-brain understanding are usually introduced in a traditional learning paradigm missing the ability to learn the connectivities between brain regions. Meanwhile, the quantum computing theory offers a new paradigm

Duncan Adamson, Will Rosenbaum, Paul G. Spirakis

In this paper, we consider the problem of finding weak independent sets in a distributed network represented by a hypergraph. In this setting, each edge contains a set of r vertices rather than simply a pair, as in a standard graph. A k-weak independent set in a hypergraph is a set where no edge contains more than k vertices in the independent set. We focus

Ricardo Montañana, José A. Gámez, José M. Puerta

We propose ODTE, a new ensemble that uses oblique decision trees as base classifiers. Additionally, we introduce STree, the base algorithm for growing oblique decision trees, which leverages support vector machines to define hyperplanes within the decision nodes. We embed a multiclass strategy -- one-vs-one or one-vs-rest -- at the decision nodes, allowing t

Matthew Ciolino, Willie Maddox

This study investigates the impact of ground sample distance (GSD) on the detection performance of various sized aircraft using the proprietary AllPlanes 120 dataset. The data set comprises 120 civilian, military and museum aircraft from multiple satellite/aerial sources collected over two years. Resolutions ranging from 2.4 to 0.3 meters GSD were simulated.

Eduardo Camps-Moreno, Hiram H. López, Gretchen L. Matthews, Rodrigo San-José

The Generalized Hamming weights and their relative version, which generalize the minimum distance of a linear code, are relevant to numerous applications, including coding on the wire-tap channel of type II, $t$-resilient functions, bounding the cardinality of the output in list decoding algorithms, ramp secret sharing schemes, and quantum error correction.

Tomasz Krawczyk

Circular-arc graphs are the intersection graphs of arcs of a circle. The main result of this work describes the structure of all \emph{normalized intersection models} of circular-arc graphs. Normalized models of a circular-arc graph reflect the neighborhood relation between its vertices and can be seen as its canonical representations; in particular, any int

Marco Barbisan, Marco Boldrin, Luca Cinnirella, Bruno Laterza

Diagnostic Neutral Beam Injectors (DNBI), through the combined use of Charge Exchange Recombination Spectroscopy (CHERS) and Motional Stark effect diagnostics (MSE), are a well-known tool to access important information about magnetically confined plasmas, such as radial profiles of ion temperature, ion flow, impurity content and intensity and direction of t

Ruonan Xu, Luther Yap

We show how clustering standard errors in one or more dimensions can be justified in M-estimation when there is sampling or assignment uncertainty. Since existing procedures for variance estimation are either conservative or invalid, we propose a variance estimator that refines a conservative procedure and remains valid. We then interpret environments where

Susanna Fishel, Jessica Gatica, Luc Lapointe, Maria Elena Pinto

The fundamental quasisymmetric functions in superspace are a generalization of the fundamental quasisymmetric functions involving anticommuting variables. We obtain the action of the product, coproduct, and antipode on the fundamental quasisymmetric functions in superspace. We also extend to superspace the well known expansion of the Schur functions in terms

Alessandra Ragni, Chiara Masci, Anna Maria Paganoni

This paper analyzes the dynamics of higher education dropouts through an innovative approach that integrates recurrent events modeling and point process theory with functional data analysis. We propose a novel methodology that extends existing frameworks to accommodate hierarchical data structures, demonstrating its potential through a simulation study. Usin

Alex Rose, Naman Aggarwal, Christopher Jewison, Jonathan P. How

This paper presents Robust samplE-based coVarIance StEering (REVISE), a multi-query algorithm that generates robust belief roadmaps for dynamic systems navigating through spatially dependent disturbances modeled as a Gaussian random field. Our proposed method develops a novel robust sample-based covariance steering edge controller to safely steer a robot bet

Torben C. Frost

The Kerr spacetime is one of the most widely known solutions to Einstein's vacuum field equations and is commonly used to describe a black hole with mass $m$ and spin $a$. Astrophysical observations in the electromagnetic spectrum as well as detected gravitational wave signals indicate that it can be used to describe the spacetime around candidates for rotat

Hao Xu

We classify all connected and Lagrangian \'etale algebras in the Drinfeld center $\mathscr{Z}_1(\mathbf{2Vect}^\pi_G)$, where $G$ is a finite group and $\pi$ is a 4-cocycle on $G$. By D\'ecoppet's result every bosonic fusion 2-category $\mathfrak{C}$ has its Drinfeld center equivalent to $\mathscr{Z}_1(\mathbf{2Vect}^\pi_G)$ for some $G$ and $\pi$. Combining

Tong Ning, Ke Lu, Xirui Jiang, Jian Xue

Utilizing temporal information to improve the performance of 3D detection has made great progress recently in the field of autonomous driving. Traditional transformer-based temporal fusion methods suffer from quadratic computational cost and information decay as the length of the frame sequence increases. In this paper, we propose a novel method called Mamba

Sasa Ilic, Abdulkerim Karaman, Johannes Pöppelbaum, Jan Niclas Reimann

This study presents a novel approach for predicting wall thickness changes in tubes during the nosing process. Specifically, we first provide a thorough analysis of nosing processes and the influencing parameters. We further set-up a Finite Element Method (FEM) simulation to better analyse the effects of varying process parameters. As however traditional FEM

Muqsit Azeem, Debraj Chakraborty, Sudeep Kanav, Jan Kretinsky

Partially Observable Markov Decision Processes (POMDPs) are a fundamental framework for decision-making under uncertainty and partial observability. Since in general optimal policies may require infinite memory, they are hard to implement and often render most problems undecidable. Consequently, finite-memory policies are mostly considered instead. However,

Wout Merbis, Madelon Geurts, Clélia de Mulatier, Philippe Corboz

The exact treatment of Markovian models of complex systems requires knowledge of probability distributions exponentially large in the number of components $n$. Mean-field approximations provide an effective reduction in complexity of the models, requiring only a number of phase space variables polynomial in system size. However, this comes at the cost of los

Steven Giacalone, Courtney D. Dressing

The Kepler and K2 missions enabled robust calculations of planet occurrence rates around FGKM-type stars. However, these missions observed too few stars with earlier spectral types to tightly constrain the occurrence rates of planets orbiting hotter stars. Using TESS, we calculate the occurrence rate of small ($1 \, R_\oplus < R_{\rm p} < 8 \, R_\oplus$), cl

Yuxuan Jiang, Jakub Nawała, Chen Feng, Fan Zhang

Super-resolution (SR) is a key technique for improving the visual quality of video content by increasing its spatial resolution while reconstructing fine details. SR has been employed in many applications including video streaming, where compressed low-resolution content is typically transmitted to end users and then reconstructed with a higher resolution an

Qinghua Zhang, Navid Valizadeh, Mingpeng Liu, Xiaoying Zhuang

Understanding the fracture mechanisms in composite materials across scales, from nano- to micro-scales, is essential for an in-depth understanding of the reinforcement mechanisms and designing the next generation of lightweight, high-strength composites. However, conventional methods struggle to model the complex fracture behavior of nanocomposites, particul

Leon Riccius, Iuri B. C. M. Rocha, Joris Bierkens, Hanne Kekkonen

Recent advancements in Markov chain Monte Carlo (MCMC) sampling and surrogate modelling have significantly enhanced the feasibility of Bayesian analysis across engineering fields. However, the selection and integration of surrogate models and cutting-edge MCMC algorithms, often depend on ad-hoc decisions. A systematic assessment of their combined influence o

Mahmoud Saad Abouamer, Robin J. Williams, Petar Popovski

We introduce a framework for predicting wireless channel statistics based on digital twin (DT) and ray tracing. The DT is derived from satellite images and is uncalibrated, as it does not assume precise information on the electromagnetic properties of the materials in the environment. The uncalibrated DT is utilized to derive a geometric prior that informs a

C. Miguel Barriuso G., Horacio Serna, Ignacio Pagonabarraga, Chantal Valeriani

The effect of gravity on the collective motion of living microswimmers, such as bacteria and micro-algae, is pivotal to unravel not only bio-convection patterns but also the settling of bacterial biofilms on solid surfaces. In this work, we investigate suspensions of microswimmers under the influence of a gravitational field and hydrodynamics, simulated via

Mai Elkady, Thu Bui, Bruno Ribeiro, David I. Inouye

There has been a growing excitement that implicit graph generative models could be used to design or discover new molecules for medicine or material design. Because these molecules have not been discovered, they naturally lie in unexplored or scarcely supported regions of the distribution of known molecules. However, prior evaluation methods for implicit gra

Chengkai Wang, Weiqing Ji, Mingyang Kou, Zhiyang Chen

Triple patterning lithography (TPL) has been recognized as one of the most promising solutions to print critical features in advanced technology nodes. A critical challenge within TPL is the effective assignment of the layout to masks. Recently, various layout decomposition methods and TPL-aware routing methods have been proposed to consider TPL. However, th

Maurice P. Schmitt, Sarah Wettermann, Kostas Ch. Daoulas, Hendrik Meyer

A central paradigm of polymer physics states that chains in melts behave like random walks as intra- and interchain interactions effectively cancel each other out. Likewise, $\theta$-chains, i.e., chains at the transition from a swollen coil to a globular phase, are also thought to behave like ideal chains, as attractive forces are counterbalanced by repulsi

Linda M. Haines

This short paper is concerned with the use of spherical t-designs as optimal designs for the spherical harmonic regression model in three dimensions over a range of specified criteria. The nature of the designs is explored and their availability and suitability is reviewed.

Magnus R. Lykkegaard, Anders Enevold Dahl, Karsten Flensberg, Tyler Lindemann

In optical diffraction, the phase difference between sources in a grating or multi-slit mask is determined by the angle to the imaging screen, yielding the familiar multi-lobed diffraction image. Here, we realize a similar phenomenon in a superconductor-semiconductor hybrid circuit configured to allow Andreev scattering from multiple parallel scatterers. Pha

Patrick E. Farrell, Umberto Zerbinati

We derive the Helmholtz--Korteweg equation, which models acoustic waves in Korteweg fluids. We further derive a nematic variant of the Helmholtz-Korteweg equation, which incorporates an additional orientational term in the stress tensor. Its dispersion relation coincides with that arising in Virga's analysis of the Euler-Korteweg equations, which we extend t

Xinyi Zhou, Cheng Zhang, Xiaoyu Zhang, Yi Zuo

Miniaturized (mini-) spectrometers are highly desirable tools for chemical, biological, and medical diagnostics because of their potential for portable and in situ spectral detection. In this work, we propose and demonstrate a mini-spectrometer that combines a large-scale radiative cavity array with end-to-end deep learning networks. Specifically, we utilize

Cheng-Yu Fan, Shan Wang, Xu-Zhi Zhou, San Lu

The recently discovered electron-only reconnection has drawn great interests due to abnormal features like lack of ion outflows and high reconnection rates. Using particle-in-cell simulations, we investigate their physical mechanisms. The reconnection rate, when normalized by ion parameters ($R_i$), may appear anomalously high, whereas that normalized by ele

Mingze Yin, Hanjing Zhou, Jialu Wu, Yiheng Zhu

Antibodies safeguard our health through their precise and potent binding to specific antigens, demonstrating promising therapeutic efficacy in the treatment of numerous diseases, including COVID-19. Recent advancements in biomedical language models have shown the great potential to interpret complex biological structures and functions. However, existing anti

Antoine Schneeberger, Olivier Mousis

Deciphering the structure of the circumplanetary disk that surrounded Jupiter at the end of its formation is key to understanding how the Galilean moons formed. Three-dimensional hydrodynamic simulations have shown that this disk was optically thick and significantly heated to very high temperatures due to the intense radiation emitted by the hot, young plan

Hailemicael Lulseged Yimer, Hailegabriel Dereje Degefa, Marco Cristani, Federico Cunico

Ge'ez, an ancient Ethiopic script of cultural and historical significance, has been largely neglected in handwriting recognition research, hindering the digitization of valuable manuscripts. Our study addresses this gap by developing a state-of-the-art Ge'ez handwriting recognition system using Convolutional Neural Networks (CNNs) and Long Short-Term Memory

Tan Hailin, Naeem Akhtar, Gao Xianlong

We investigate the superposition of coherent states, emphasizing quantum states with distinct Wigner phase-space features relevant to quantum information applications. In this study, we introduce generalized versions of the compass state, which display enhanced phase-space characteristics compared with the conventional compass state, typically a superpositio

Sahab Hajebi, Ramin Javadi

A star of length $ \ell $ is defined as the complete bipartite graph $ K_{1,\ell } $. In this paper we deal with the problem of edge decomposition of graphs into stars of varying lengths. Given a graph $ G $ and a list of integers $S=(s_1,\ldots, s_t) $, an $S$-star decomposition of $ G $ is an edge decomposition of $ G $ into graphs $G_1 ,G_2 ,\ldots,G_t $

Julien Dular, Fredrik Magnus, Erik Schnaubelt, Arjan Verweij

The coupled axial and transverse currents (CATI) method was recently introduced to model the AC loss and magnetization in twisted composite superconducting strands with low computational cost and high accuracy. This method involves two-dimensional finite element (FE) models coupled with circuit equations representing the periodicity of the strand. In this pa

Karolina Trajkovska, Matjaž Kljun, Klen Čopič Pucihar

Eye gaze is considered an important indicator for understanding and predicting user behaviour, as well as directing their attention across various domains including advertisement design, human-computer interaction and film viewing. In this paper, we present a novel method to enhance the analysis of user behaviour and attention by (i) augmenting video streams

Cristian Curaba, Denis D'Ambrosi, Alessandro Minisini, Natalia Pérez-Campanero Antolín

Cryptographic protocols play a fundamental role in securing modern digital infrastructure, but they are often deployed without prior formal verification. This could lead to the adoption of distributed systems vulnerable to attack vectors. Formal verification methods, on the other hand, require complex and time-consuming techniques that lack automatization. I

Hailemicael Lulseged Yimer, Hailegabriel Dereje Degefa, Marco Cristani, Federico Cunico

Continuous monitoring of coma patients is essential but challenging, especially in developing countries with limited resources, staff, and infrastructure. This paper presents a low-cost IoT-based system designed for such environments. It uses affordable hardware and robust software to monitor patients without constant internet access or extensive medical per

Luuk Poort, Lars A. L. Janssen, Bart Besselink, Rob H. B. Fey

This paper introduces the concept of abstracted model reduction: a framework to improve the tractability of structure-preserving methods for the complexity reduction of interconnected system models. To effectively reduce high-order, interconnected models, it is usually not sufficient to consider the subsystems separately. Instead, structure-preserving reduct

Yige Yuan, Bingbing Xu, Hexiang Tan, Fei Sun

Confidence calibration in LLMs, i.e., aligning their self-assessed confidence with the actual accuracy of their responses, enabling them to self-evaluate the correctness of their outputs. However, current calibration methods for LLMs typically estimate two scalars to represent overall response confidence and correctness, which is inadequate for long-form gen

Hong-Bin Chen

In [arXiv:2311.08980], it was shown that if the limit of the free energy in a non-convex vector spin glass model exists, it must be a critical value of a certain functional. In this work, we extend this result to multi-species spin glass models with non-convex interactions, where spins from different species may lie in distinct vector spaces. Since the speci

Idan Versano, Eli Turkel

We present a novel architecture for learning geometry-aware preconditioners for linear partial differential equations (PDEs). We show that a deep operator network (Deeponet) can be trained on a simple geometry and remain a robust preconditioner for problems defined by different geometries without further fine-tuning or additional data mining. We demonstrate

Yinsong Wang, Siwei Chen, Ziyi Song, Sheng Zhou

Cooperative perception research is hindered by the limited availability of datasets that capture the complexity of real-world Vehicle-to-Everything (V2X) interactions, particularly under dynamic communication constraints. To address this gap, we introduce WHALES (Wireless enhanced Autonomous vehicles with Large number of Engaged agents), the first large-scal

Sergio Vicenzo, Bing Xu

Direct position estimation (DPE) is an effective solution to the MP issue at the signal processing level. Unlike two-step positioning (2SP) receivers, DPE directly solves for the receiver position, velocity, and time (PVT) in the navigation domain, without the estimation of intermediate measurements, thus allowing it to provide more robust and accurate PVT e

Mario Kapl, Aljaž Kosmač, Vito Vitrih

We present a novel isogeometric collocation method for solving the Poisson's and the biharmonic equation over planar bilinearly parameterized multi-patch geometries. The proposed approach relies on the use of a modified construction of the C^s-smooth mixed degree isogeometric spline space [20] for s=2 and s=4 in case of the Poisson's and the biharmonic equat

Angelo Russotto, Filiberto Ares, Pasquale Calabrese

The entanglement asymmetry measures the extent to which a symmetry is broken within a subsystem of an extended quantum system. Here, we analyse this quantity in Haar random states for arbitrary compact, semi-simple Lie groups, building on and generalising recent results obtained for the $U(1)$ symmetric case. We find that, for any symmetry group, the average

Piotr Oprocha, Jakub Tomaszewski

In the present note we focus on dynamics on the Gehman dendrite $\mathcal{G}$. It is well-known that the set of its endpoints is homeomorphic to a standard Cantor ternary set. For any given surjective Cantor system $\mathcal{C}$ we provide constructions of (i) a mixing but not exact and (ii) an exact map on $\mathcal{G}$, such that in both cases the subsyste

Xinyue Hao, Gen Li, Shreyank N Gowda, Robert B Fisher

Video understanding has made huge strides in recent years, relying largely on the power of transformers. As this architecture is notoriously expensive and video data is highly redundant, research into improving efficiency has become particularly relevant. Some creative solutions include token selection and merging. While most methods succeed in reducing the

Elie Chelly, Andrea Cherubini, Philippe Fraisse, Faiz Ben Amar

Fine dexterous manipulation requires reactive control based on rich sensing of manipulator-object interactions. Tactile sensing arrays provide rich contact information across the manipulator's surface. However their implementation faces two main challenges: accurate force estimation across complex surfaces like robotic hands, and integration of these estimat

Sriram V. Pemmaraju, Sourya Roy, Joshua Z. Sobel

We present the first sublinear-in-$n$ round algorithm for sampling an approximately uniform spanning tree of an $n$-vertex graph in the CongestedClique model of distributed computing. In particular, our algorithm requires $\Tilde{O}(n^{0.657})$ rounds for sampling a spanning tree within total variation distance $1/n^c$, for arbitrary constant $c > 0$, from t

Hai-Tian Wang, Ziming Wang, Yiming Dong, Garvin Yim

The ringdown phase of a gravitational wave (GW) signal from a binary black hole merger provides valuable insights into the properties of the final black hole and serves as a critical test of general relativity in the strong-field regime. A key aspect of this investigation is to determine whether the first overtone mode exists in real GW data, as its presence

Rebecca Maria Kuntz, Heinrich von Campe, Tobias Röspel, Maximilian Philipp Herzog

The significance of statistical physics concepts such as entropy extends far beyond classical thermodynamics. We interpret the similarity between partitions in statistical mechanics and partitions in Bayesian inference as an articulation of a result by Jaynes (1957), who clarified that thermodynamics is in essence a theory of information. In this, every samp

Àlex Pujol Vidal, Anders S. Johansen, Mohammad N. S. Jahromi, Sergio Escalera

We investigate the effectiveness of Explainable AI (XAI) in verifying Machine Unlearning (MU) within the context of harbor front monitoring, focusing on data privacy and regulatory compliance. With the increasing need to adhere to privacy legislation such as the General Data Protection Regulation (GDPR), traditional methods of retraining ML models for data d

Zhao-An Wang, Xiao-Dong Zeng, Yi-Tao Wang, Jia-Ming Ren

Investigating physical models with photonic synthetic dimensions has been generating great interest in vast fields of science. The rapid developing thin-film lithium niobate (TFLN) platform, for its numerous advantages including high electro-optic coefficient and scalability, is well compatible with the realization of synthetic dimensions in the frequency to

Chung Xu, Richard Schier, Caterina Cocchi

Thanks to their favorable electronic and optical properties, sodium-potassium-antimonides are an emerging class of crystals used as photocathodes in particle accelerators. The persisting challenges related to the synthesis and characterization of these materials demand support from theory and make the study of computationally predicted polymorphs particularl

Konstantin Haubner, Federico Lelli, Enrico Di Teodoro, Francis Duey

The Surface Photometry and Accurate Rotation Curves (SPARC) database has provided the community with mass models for 175 nearby galaxies, allowing different research teams to test different dark matter models, galaxy evolution models, and modified gravity theories. Extensive tests, however, are hampered by the somewhat heterogeneous nature of the HI rotation

Francisco J. G. de Oliveira, Zahra Sharif Khodaei, Oliver R. H. Buxton

The impact of several $``\text{flavours}"$ of free-stream turbulence (FST) on the structural response of a cantilevered cylinder, subjected to a turbulent cross-flow is investigated. At high enough Reynolds numbers, the cylinder generates a spectrally rich turbulent wake which significantly contributing to the experienced loads. The presence of FST introduce

Kilian Freitag, Yiannis Karayiannidis, Jan Zbinden, Rita Laezza

Objective: Enhancing the reliability of myoelectric controllers that decode motor intent is a pressing challenge in the field of bionic prosthetics. State-of-the-art research has mostly focused on Supervised Learning (SL) techniques to tackle this problem. However, obtaining high-quality labeled data that accurately represents muscle activity during daily us

Maryam Eshraghi Evari, Md Nasir Sulaiman, Amir Rajabi Behjat

DNA microarray gene-expression data has been widely used to identify cancerous gene signatures. Microarray can increase the accuracy of cancer diagnosis and prognosis. However, analyzing the large amount of gene expression data from microarray chips pose a challenge for current machine learning researches. One of the challenges lie within classification of h

Hiep Nguyen, Haiyang Tang, Matthew Alger, Antoine Marchal

We introduce TPCNet, a neural network predictor that combines Convolutional and Transformer architectures with Positional encodings, for neutral atomic hydrogen (HI) spectral analysis. Trained on synthetic datasets, our models predict cold neutral gas fraction ($f_\text{CNM}$) and HI opacity correction factor ($R_\text{HI}$) from emission spectra based on th

Yuqi Wang, Ralf Deiterding, Jianhan Liang

A second-order-accurate finite volume method, hybridized by blending an extended double-flux algorithm and a traditionally conservative scheme, is developed. In this scheme, hybrid convective fluxes as well as hybrid interpolation techniques are designed to ensure stability and accuracy in the presence of both material interfaces and shocks. Two computationa

Daniel Ramos, Claudia Mamede, Kush Jain, Paulo Canelas

Large Language Models (LLMs) have become integral to various software engineering tasks, including code generation, bug detection, and repair. To evaluate model performance in these domains, numerous bug benchmarks containing real-world bugs from software projects have been developed. However, a growing concern within the software engineering community is th

Yunli Wang, Zhen Zhang, Zixuan Yang, Tianyu Xu

The scaling law is a notable property of neural network models and has significantly propelled the development of large language models. Scaling laws hold great promise in guiding model design and resource allocation. Recent research increasingly shows that scaling laws are not limited to NLP tasks or Transformer architectures; they also apply to domains suc

Nuria Fonseca-Bonilla, Luis Cerdán, Alberto Noriega-Crespo, Amaya Moro-Martín

While WISE is the largest, best quality infrared all-sky survey to date, a smaller coverage mission, Spitzer, was designed to have better sensitivity and spatial resolution at similar wavelengths. Confusion and contamination in WISE data result in discrepancies between them. We present a novel approach to work with WISE measurements with the goal of maintain

Sylvain Crovisier, Mikhail Lyubich, Enrique Pujals, Jonguk Yang

We formulate and prove $\textit{a priori}$ bounds for the renormalization of H\'enon-like maps (under certain regularity assumptions). This provides a certain uniform control on the small-scale geometry of the dynamics, and ensures pre-compactness of the renormalization sequence. In a sequel to this paper, a priori bounds are used in the proof of the main re

Jonathan K. Hofmann, Hoyeon Jeon, Saban M. Hus, Yuqi Zhang

Bi$_4$Br$_4$ is a prototypical quasi one-dimensional (1D) material in which covalently bonded bismuth bromide chains are arranged in parallel, side-by-side and layer-by-layer, with van der Waals (vdW) gaps in between. So far, two different structures have been reported for this compound, $\alpha$-Bi$_4$Br$_4$ and $\beta$-Bi$_4$Br$_4$ , in both of which neigh

Armando Pezo, Dongwook Go, Yuriy Mokrousov, Henri Jaffrès

In this study, we investigate the spin and orbital densities induced by magnetization dynamics in a planar bilayer heterostructure. To do this, we employed a theory of adiabatic pumping using the Keldysh formalism and Wigner expansion. We first conduct simulations on a model system to determine the parameters that control the spin and orbital pumping into an

Georgiana Caltais, Cinzia Di Giusto

This volume contains the proceedings of EXPRESS/SOS 2024: the Combined 31st International Workshop on Expressiveness in Concurrency and the 21st Workshop on Structural Operational Semantics, which was held in Calgary, Canada, as an affiliated workshop of CONFEST 2024. The EXPRESS/SOS workshop series aims at bringing together researchers interested in the for

Sivan Doveh, Nimrod Shabtay, Wei Lin, Eli Schwartz

Vision-Language Models (VLMs) have shown remarkable capabilities across diverse visual tasks, including image recognition, video understanding, and Visual Question Answering (VQA) when explicitly trained for these tasks. Despite these advances, we find that present-day VLMs (including the proprietary GPT-4o) lack a fundamental cognitive ability: learning to

Yongbin Du, Yunlong Liu, Xiangdong Zhang

In this paper, we investigate the motion of spinning particles in the background of covariant loop quantum gravity black holes, focusing on two distinct effective metric solutions. Both metrics incorporate a quantum parameter $\zeta$, which quantifies loop quantum corrections. When $\zeta$ approaches zero, the spacetime reduces to the classical Schwarzschild

Rodyna A. Hosny, Naglaa M. Madbouly, Mostafa K. El-Bably

In the work "Generalized approximation spaces generation from $\mathbb{I}_{j}$-neighborhoods and ideals with application to Chikungunya disease, published in \emph{AIMS Mathematics}, \textbf{9}(4) (2024), 10050$-$10077," Al-Shami and Hosny introduced a novel approach for generating generalized neighborhoods through $\mathbb{I}_{j}$-neighborhoods with ideals,

Shu-Chuan Chen, Jui-Fang Chang, Yintzer Shih

This study investigates air pollution in central Taiwan, focusing on key pollutants, including SO$_2$, NO$_2$, PM$_{10}$, and PM$_{2.5}$. We use non-negative matrix factorization (NMF) to reduce data dimensionality, followed by wind direction analysis and speed to trace pollution sources. Our findings indicate that PM$_{2.5}$ and NO$_2$ levels are primarily

Jiawei Zhang, Tian-Hao Zhang, Jun Wang, Jiaran Gao

Controlling the style and characteristics of speech synthesis is crucial for adapting the output to specific contexts and user requirements. Previous Text-to-speech (TTS) works have focused primarily on the technical aspects of producing natural-sounding speech, such as intonation, rhythm, and clarity. However, they overlook the fact that there is a growing

T. T. Sergeev, A. A. Zyablovsky, E. S. Andrianov

In this work, we consider a composite atom-cavity system interacting with a ring resonator. In such a structure, time crystal regime can be observed. We show that a quadratic observation time dependence of the system's sensitivity to perturbations takes place in the time crystal regime and also in the transition area to the normal state. This dependence is d

Jianjun Liu, Duohui Xiang

We prove an abstract Birkhoff normal form theorem for Hamiltonian partial differential equations on torus. The normal form is complete up to arbitrary finite order. The proof is based on a valid non-resonant condition and a suitable norm of Hamiltonian function. Then as two examples, we apply this theorem to nonlinear wave equation in one dimension and nonli

Kavin Chandrasekaran, Sorin Grigorescu, Gijs Dubbelman, Pavol Jancura

Cameras can be used to perceive the environment around the vehicle, while affordable radar sensors are popular in autonomous driving systems as they can withstand adverse weather conditions unlike cameras. However, radar point clouds are sparser with low azimuth and elevation resolution that lack semantic and structural information of the scenes, resulting i

Jelena Trisovic, Alexandre Didier, Simon Muntwiler, Melanie N. Zeilinger

This paper presents a robust moving horizon estimation (MHE) approach with provable estimation error bounds for solving the simultaneous localization and mapping (SLAM) problem. We derive sufficient conditions to guarantee robust stability in ego-state estimates and bounded errors in landmark position estimates, even under limited landmark visibility which d

T. H. Kim, Jung-Il Kim, Geun-Ju Kim, Kwang-Ho Jang

We theoretically and numerically elucidate the electrical control over spin waves in antiferromagnetic materials (AFM) with biaxial anisotropies and Dzyaloshinskii-Moriya interactions. The spin wave dispersion in an AFM manifests as a bifurcated spectrum with distinct high-frequency and low-frequency bands. Utilizing a heterostructure comprised of platinum a

Caleb Wheeler, Natalie R. Hinkel, Andrea Banzatti

Data access -- or the availability of new and archival data for use by the larger community -- is key for scientific advancement. How data is presented, searched, and formatted determines accessibility and it can be difficult to find a solution that fits the needs of a given subdiscipline. We present a generalized roadmap for developing a specialty astronomy

Sajjad Mohammadi, James L. Kirtley, Alireza Namadmalan

This paper presents analytic study and design considerations of flat wire inductors with distributed gaps for high-power and compact DC-DC Converters. The focus is eddy current loss components within the conductors due to fringing and leakage fluxes. A magnetic equivalent circuit (MEC) is proposed in which eddy currents are modeled by MMFs opposing the prima

Huazhi Dong, Sihao Teng, Xiaopeng Wu, Xu Han

Flexible electrical impedance tomography (EIT) is an emerging technology for tactile sensing in human-machine interfaces (HMI). It offers a unique alternative to traditional array-based tactile sensors with its flexible, scalable, and cost-effective one-piece design. This paper proposes a lattice-patterned flexible EIT tactile sensor with a hydrogel-based co

Shanfeng Xu, Yanshuo Cheng, Siqiang Wang, Xinyi Wang

Existing integrated sensing and communication (ISAC) beamforming design were mostly designed under perfect instantaneous channel state information (CSI), limiting their use in practical dynamic environments. In this paper, we study the beamforming design for multiple-input multiple-output (MIMO) ISAC systems based on statistical CSI, with the weighted mutual

Darragh Buckley, Alex Lonergan, Colm O'Dwyer

Metal oxide thin films are of great interest in scientific advancement, particularly semiconductor thin films in transistors and in a wide range of optoelectronic applications. Many metal oxide thin films attract interest for their electronic bandgap, charge carrier mobility, optical opacity, luminescence, low cost, relative abundance and environmentally-fri

J. T. Chacko, V. Baru, C. Hanhart, S. L. Krug

To improve the theoretical understanding of multiquark states like $Z_b(10610)$ and $Z_b(10650)$, we calculate the heavy-meson heavy-(anti)meson scattering potential up to next-to-leading order, $O(Q^2)$, within chiral effective field theory ($\chi$EFT) employing a power counting scheme that explicitly keeps track with the large momentum scale $Q \sim \sqrt{

Vaishnavi Khindkar, Vineeth Balasubramanian, Chetan Arora, Anbumani Subramanian

With the increased importance of autonomous navigation systems has come an increasing need to protect the safety of Vulnerable Road Users (VRUs) such as pedestrians. Predicting pedestrian intent is one such challenging task, where prior work predicts the binary cross/no-cross intention with a fusion of visual and motion features. However, there has been no e

Xin Du, Hui-Hui He, Xiao-Xiao Man, Zhong-Yi Lu

While the conducting CuO$_2$ planes in cuprate superconductors have been widely recognized as a crucial component in producing high superconducting $T_\text{c}$, recent experimental and theoretical studies on Ba$_{2-x}$Sr$_x$CuO$_{3+}$$_\delta$ have also drawn much attention to the importance of Cu-O chains in one-dimensional (1D) cuprates. To better underst

Tim Lenz, Peter Neidlinger, Marta Ligero, Georg Wölflein

Representation learning of pathology whole-slide images (WSIs) has primarily relied on weak supervision with Multiple Instance Learning (MIL). This approach leads to slide representations highly tailored to a specific clinical task. Self-supervised learning (SSL) has been successfully applied to train histopathology foundation models (FMs) for patch embeddin

Lucas Michel, Jasper Nalbach, Pierre Mathonet, Naïm Zénaïdi

We consider cylindrical algebraic decomposition (CAD) and the key concept of delineability which underpins CAD theory. We introduce the novel concept of projective delineability which is easier to guarantee computationally. We prove results about this which can allow reduced CAD computations.

Akifumi Chitose, Masahiro Ibe, Shunsuke Neda, Satoshi Shirai

Recent observations by pulsar timing arrays (PTAs) indicate a potential detection of a stochastic gravitational wave (GW) background. Metastable cosmic strings have been recognized as a possible source of the observed signals. In this paper, we propose an $R$-invariant supersymmetric new inflation model. It is characterized by a two-step symmetry breaking $\