April 2024 arXiv papers — page 30

Michael T. Hatzon, Eugene N. Ivanov, Jeremy F. Bourhill, Maxim Goryachev

To derive the best oscillator phase noise when implementing a high-Q resonator, the spectral line-shape must have high contrast and symmetry. Ideally, this line-shape is Lorentzian, however, in a high mode density spectral region, low-Q background spurious modes interact and distort the resonance. For a sapphire-loaded cavity resonator operating with whisper

Yinghan Cheng, Qi Zhang, Chongyang Shi, Liang Xiao

Stance detection seeks to identify the viewpoints of individuals either in favor or against a given target or a controversial topic. Current advanced neural models for stance detection typically employ fully parametric softmax classifiers. However, these methods suffer from several limitations, including lack of explainability, insensitivity to the latent da

Quansen Jiu, Lin Ma, Fengchao Wang

In this paper, we consider the initial-boundary value problem of the nonhomogeneous primitive equations with density-dependent viscosity. Local well-posedness of strong solutions is established for this system with a natural compatibility condition. The initial density does not need to be strictly positive and may contain vacuum. Meanwhile, we also give the

Mustafa Sencer Aydın, Igor Kukavica

We consider the vanishing viscosity problem for solutions of the Navier-Stokes equations with Navier boundary conditions in the half-space. We lower the currently known conormal regularity needed to establish that the inviscid limit holds. Our requirement for the Lipschitz initial data is that the first four conormal derivatives are bounded along with two fo

Triet H. M. Le, M. Ali Babar, Tung Hoang Thai

Background: Software Vulnerability (SV) prediction in emerging languages is increasingly important to ensure software security in modern systems. However, these languages usually have limited SV data for developing high-performing prediction models. Aims: We conduct an empirical study to evaluate the impact of SV data scarcity in emerging languages on the st

Boran Wang

Alternating direction multiplication is a powerful technique for solving convex optimisation problems. When challenging subproblems are encountered in the real world, it is useful to solve them by introducing neighbourhood terms. When the neighbourhood matrix is positive definite, the algorithm converges but at the same time makes the iteration step small. R

Alan Gardin, Guillaume Bourcin, Christian Person, Christophe Fumeaux

Coherent and dissipative couplings, respectively characterised by energy level repulsion and attraction, each have different applications for quantum information processing. Thus, a system in which both coherent and dissipative couplings are tunable on-demand and in-situ is tantalising. A first step towards this goal is the two-tone driving of two bosonic mo

Daisuke Niizumi, Daiki Takeuchi, Yasunori Ohishi, Noboru Harada

To reduce the need for skilled clinicians in heart sound interpretation, recent studies on automating cardiac auscultation have explored deep learning approaches. However, despite the demands for large data for deep learning, the size of the heart sound datasets is limited, and no pre-trained model is available. On the contrary, many pre-trained models for g

Shivangi Yadav, Arun Ross

Biometric systems based on iris recognition are currently being used in border control applications and mobile devices. However, research in iris recognition is stymied by various factors such as limited datasets of bonafide irides and presentation attack instruments; restricted intra-class variations; and privacy concerns. Some of these issues can be mitiga

Alice Gao, Samyukta Jayakumar, Marcello Maniglia, Brian Curless

We consider the question of how to best achieve the perception of eye contact when a person is captured by camera and then rendered on a 2D display. For single subjects photographed by a camera, conventional wisdom tells us that looking directly into the camera achieves eye contact. Through empirical user studies, we show that it is instead preferable to {\e

Grey Ercole

Let $\Omega$ be a bounded, smooth domain of $\mathbb{R}^{N},$ $N\geq2.$ For $p>N$ and $1\leq q(p)<\infty$ set \[ \lambda_{p,q(p)}:=\inf\left\{ \int_{\Omega}\left\vert \nabla u\right\vert ^{p}\mathrm{d}x:u\in W_{0}^{1,p}(\Omega)\text{ \ and \ }\int_{\Omega }\left\vert u\right\vert ^{q(p)}\mathrm{d}x=1\right\} \] and let $u_{p,q(p)}$ denote a corresponding pos

Trenton J. Gobel, David M. Williams

In this work, a family of symmetric interpolation points are generated on the four-dimensional simplex (i.e. the pentatope). These points are optimized in order to minimize the Lebesgue constant. The process of generating these points closely follows that outlined by Warburton in "An explicit construction of interpolation nodes on the simplex," Journal of En

Xiaojun Dong, Yan Gu, Yihan Sun, Letong Wang

In this paper, we introduce PASGAL (Parallel And Scalable Graph Algorithm Library), a parallel graph library that scales to a variety of graph types, many processors, and large graph sizes. One special focus of PASGAL is the efficiency on \textit{large-diameter graphs}, which is a common challenge for many existing parallel graph processing systems: many exi

Yuanyuan Liu, Yuxuan Huang, Shuyang Liu, Yibing Zhan

In Video-based Facial Expression Recognition (V-FER), models are typically trained on closed-set datasets with a fixed number of known classes. However, these models struggle with unknown classes common in real-world scenarios. In this paper, we introduce a challenging Open-set Video-based Facial Expression Recognition (OV-FER) task, aiming to identify both

Qiyu Kang, Kai Zhao, Qinxu Ding, Feng Ji

We introduce the FRactional-Order graph Neural Dynamical network (FROND), a new continuous graph neural network (GNN) framework. Unlike traditional continuous GNNs that rely on integer-order differential equations, FROND employs the Caputo fractional derivative to leverage the non-local properties of fractional calculus. This approach enables the capture of

Anubhav Bhatti, Prithila Angkan, Behnam Behinaein, Zunayed Mahmud

We present a novel multimodal dataset for Cognitive Load Assessment in REal-time (CLARE). The dataset contains physiological and gaze data from 24 participants with self-reported cognitive load scores as ground-truth labels. The dataset consists of four modalities, namely, Electrocardiography (ECG), Electrodermal Activity (EDA), Electroencephalogram (EEG), a

Tung Nguyen, Jeffrey Uhlmann

In this paper we argue that conventional unitary-invariant measures of recommender system (RS) performance based on measuring differences between predicted ratings and actual user ratings fail to assess fundamental RS properties. More specifically, posing the optimization problem as one of predicting exact user ratings provides only an indirect suboptimal ap

Ching Hung Lam, Xingjun Lin, Hiroki Shimakura

We complete the program for determining the full automorphism groups of all parafermion vertex operator algebras associated with simple Lie algebras and positive integral levels. We show that the full automorphism group of the parafermion vertex operator algebra is isomorphic to the automorphism group of the associated root system for the remaining cases: (i

Henrique S. Xavier

This paper presents a comprehensive analysis of global web usage patterns based on data from SimilarWeb, a leading source for estimating web traffic. Leveraging a dataset comprising over 250,000 websites, we estimate the total web traffic and investigate its distribution among domains and industry sectors. We detail the characteristics of the top 116 domains

Yufeng Li, Yiwei Ci, Qiusong Yang

Design verification is a complex and costly task, especially for large and intricate processor projects. Formal verification techniques provide advantages by thoroughly examining design behaviors, but they require extensive labor and expertise in property formulation. Recent research focuses on verifying designs using the self-consistency universal property,

Hang-Hyun Jo, Tibebe Birhanu, Naoki Masuda

Long-term temporal correlations in time series in a form of an event sequence have been characterized using an autocorrelation function (ACF) that often shows a power-law decaying behavior. Such scaling behavior has been mainly accounted for by the heavy-tailed distribution of interevent times (IETs), i.e., the time interval between two consecutive events. Y

Weiran Chen, Qi Xu

Spiking Neural Networks (SNNs) aim to bridge the gap between neuroscience and machine learning by emulating the structure of the human nervous system. However, like convolutional neural networks, SNNs are vulnerable to adversarial attacks. To tackle the challenge, we propose a biologically inspired methodology to enhance the robustness of SNNs, drawing insig

Ummay Mowshome Jahan, Brianna Blevins, Sergiy Minko, Vladimir Reukov

Reactive oxygen species (ROS), which are expressed at high levels in many diseases, can be scavenged by cerium oxide nanoparticles (CeO2NPs). CeO2NPs can cause significant cytotoxicity when administered directly to cells, but this cytotoxicity can be reduced if CeO2NPs can be encapsulated in biocompatible polymers. In this study, CeO2NPs were synthesized usi

Eric Cochran

We show that given a compact, connected $m$-quasi Einstein manifold $(M,g,X)$ without boundary, the potential vector field $X$ is Killing if and only if $(M, g)$ has constant scalar curvature. This extends a result of Bahuaud-Gunasekaran-Kunduri-Woolgar, where it is shown that $X$ is Killing if $X$ is incompressible. We also provide a sufficient condition fo

Zavareh Bozorgasl, Hao Chen, Mohammad J. Dehghani

In this paper, we present a novel auto-calibration scheme for the joint estimation of the two-dimensional (2-D) direction-of-arrival (DOA) and the mutual coupling matrix (MCM) for a signal measured using uniform circular arrays. The method employs an integrated wideband dictionary to mitigate the detrimental effects of the discretization of the continuous pa

Aojia Xu, Ruitian Li, Xuan Luo, Hao Sun

We study the production of hyperon resonances in the $p\bar{p}\to\bar{\Lambda}\Sigma\eta$ reaction within an effective Lagrangian approach. The model includes the production of $\Sigma(1750)$ and $\Lambda(1670)$ in the intermediate state excited by the $K$ and $K^*$ meson exchanges between the initial proton and antiproton. Due to the large coupling of $\Sig

Rahul Sahay, Ruben Verresen

Although tensor network states constitute a broad range of exotic quantum states, their realization is challenging and often requires resources whose depth scales with system size. In this work, we explore criteria on the local tensors for enabling deterministic state preparation via a single round of measurements and on-site unitary feedback. We use these c

Jinxiong Jia, Longjun Xiang, Zhenhua Qiao, Jian Wang

It has been known that the semiclassical theory and the response theory can equivalently give the Drude and the intrinsic anomalous Hall conductivities in the linear order of electric field. However, recent theoretical advances implied that the second-order nonlinear conductivities calculated with both approaches are no longer equivalent, which leads to vari

M. Moein Esfahani, Hossein Sadati, Vince D Calhoun

Brain-computer interface systems and the recording of brain activity has garnered significant attention across a diverse spectrum of applications. EEG signals have emerged as a modality for recording neural electrical activity. Among the methodologies designed for feature extraction from EEG data, the method of RCSP has proven to be an approach, particularly

Rohan Acharya, Marcin Jurdziński, Keya Prakash

Our main technical contribution is a polynomial-time determinisation procedure for history-deterministic Büchi automata, which settles an open question of Kuperberg and Skrzypczak, 2015. A key conceptual contribution is the lookahead game, which is a variant of Bagnol and Kuperberg&#39;s token game, in which Adam is given a fixed lookahead. We prove that the

Wei Xie, Yin Yang, Eric Chung, Yunqing Huang

In this paper, we propose a novel multiscale model reduction strategy tailored to address the Poisson equation within heterogeneous perforated domains. The numerical simulation of this intricate problem is impeded by its multiscale characteristics, necessitating an exceptionally fine mesh to adequately capture all relevant details. To overcome the challenges

Vincent Ress, Wei Zhang, David Skuddis, Norbert Haala

Simultaneous localization and mapping (SLAM), i.e., the reconstruction of the environment represented by a (3D) map and the concurrent pose estimation, has made astonishing progress. Meanwhile, large scale applications aiming at the data collection in complex environments like factory halls or construction sites are becoming feasible. However, in contrast to

Suliman Khan

A complex unit gain graph (or a $\mathbb{T}$-gain graph) $\Theta(\Sigma,\varphi)$ is a graph where the unit complex number is assign by a function $\varphi$ to every oriented edge of $\Sigma$ and assign its inverse to the opposite orientation. In this paper, we define the two gain distance Laplacian matrices $DL^{\max}_{<}(\Theta)$ and $DL^{\min}_{<}(\Theta)

Cheryl S. C. Lau, Maya A. Petkova, Ian A. Bonnell

Modelling the interaction between ionizing photons emitted from massive stars and their environment is essential to further our understanding of galactic ecosystems. We present a hybrid Radiation-Hydrodynamics (RHD) scheme that couples an SPH code to a grid-based Monte Carlo Radiative Transfer code. The coupling is achieved by using the particle positions as

Muhammad Abdullah, Anne Querfurth, Deepak Bhatia, Mahdi Mantash

This paper investigates the use of deep learning approaches to estimate the femur caput-collum-diaphyseal (CCD) angle from X-ray images. The CCD angle is an important measurement in the diagnosis of hip problems, and correct prediction can help in the planning of surgical procedures. Manual measurement of this angle, on the other hand, can be time-intensive

Katherine Betz, Feng Fu, Naoki Masuda

Recent developments of eco-evolutionary models have shown that evolving feedbacks between behavioral strategies and the environment of game interactions, leading to changes in the underlying payoff matrix, can impact the underlying population dynamics in various manners. We propose and analyze an eco-evolutionary game dynamics model on a network with two com

Daryl Cooper, Catherine Pfaff

We defined a new set of coordinates with respect to which the Thurston compactification of Teichmuller space is the radial compactification of Euclidean space.

Felipe de Carvalho Pereira, Pedro Jussieu de Rezende, Tallys Yunes, Luiz Fernando Batista Morato

We propose an exact algorithm for the Graph Burning Problem ($\texttt{GBP}$), an NP-hard optimization problem that models the spread of influence on social networks. Given a graph $G$ with vertex set $V$, the objective is to find a sequence of $k$ vertices in $V$, namely, $v_1, v_2, \dots, v_k$, such that $k$ is minimum and $\bigcup_{i = 1}^{k} \{u\! \in\! V

Atul Singh Arora, Jamie Sikora, Thomas Van Himbeeck

Weak coin flipping is the cryptographic task where Alice and Bob remotely flip a coin but want opposite outcomes. This work studies this task in the device-independent regime where Alice and Bob neither trust each other, nor their quantum devices. The best protocol was devised over a decade ago by Silman, Chailloux, Aharon, Kerenidis, Pironio, and Massar wit

Pierre N. Thibodeaux, Alexander P. Ji, William Cerny, Evan N. Kirby

The discovery of a star formed out of pair-instability supernova ejecta would have massive implications for the Population III star initial mass function and the existence of stars over 100 Msun, but none have yet been found. Recently, the star LAMOST J1010+2358 was claimed to be a star that formed out of gas enriched by a pair-instability supernova. We pres

Panagiotis Promponas, Akrit Mudvari, Luca Della Chiesa, Paul Polakos

The practical realization of quantum programs that require large-scale qubit systems is hindered by current technological limitations. Distributed Quantum Computing (DQC) presents a viable path to scalability by interconnecting multiple Quantum Processing Units (QPUs) through quantum links, facilitating the distributed execution of quantum circuits. In DQC,

Adrián Esparza-Amador

We consider the family of entire maps given by $f_{\ell,c}(z)=\ell+c-(\ell-1)\log c-e^z$, where $c\in D(\ell,1)$ and $\ell\in\mathbb N$, $\ell\geq2$. By using the property of $f_{\ell,c}$ to be dynamically projected to an infinite cylinder $\mathbb C/2\pi I\mathbb Z$, where the thermodynamic formalism tools are well-defined, we prove as a main result on this

Philip Broadbridge, Sarah Becirevic, David Hoxley

A quantum field has been coupled to a space-time with accelerating expansion. Dynamical modes are destabilised successively at shorter material wavelengths as they metamorphose from oscillators to repellers. Due to degeneracy of energy levels, the number of unstable modes increases at an accelerating rate, sufficient to account for a significant proportion o

Wei Fu, Mark John, Thathsara D. Maddumapatabandi, Fabio Bussolotti

The manipulation of edge configurations and structures in atomically thin transition metal dichalcogenides (TMDs) for versatile functionalization has attracted intensive interest in recent years. The chemical vapor deposition (CVD) approach has shown promise for TMD edge engineering of atomic edge configurations (1H, 1T or 1T'-zigzag or armchair edges), as w

Gabriel Moreno Cunha, Gillberto Corso, Matheus Phellipe Brasil de Sousa, Gustavo Zampier dos Santos Lima

The inquiry into the origin of brain complexity remains a pivotal question in neuroscience. While synaptic stimuli are acknowledged as significant, their efficacy often falls short in elucidating the extensive interconnections of the brain and nuanced levels of cognitive integration. Recent advances in neuroscience have brought the mechanisms underlying the

Jaglul Hasan, Daniel Shaffer, Maxim Khodas, Alex Levchenko

In this work, we explore the generalities of the supercurrent diode effect. As an illustrative example, we examine a model of a two-dimensional superconductor with Rashba-type spin-orbit coupling under an in-plane magnetic field and in the clean limit, which realizes a helical phase. First, we utilize Ginzburg-Landau phenomenology to derive a general formula

Zhijin Li, Shutong Zhou

We study the $\mathbb{Z}_2$ and $U(1)$ Abelian lattice gauge theories using a bootstrap method, in which the loop equations and positivity conditions are employed for Wilson loops with lengths $L\leqslant L_{\textrm{max}}$ to derive two-sided bounds on the Wilson loop averages. We address a fundamental question that whether the constraints from loop equation

Lingfan Bao, Joseph Humphreys, Tianhu Peng, Chengxu Zhou

Bipedal robots are gaining global recognition due to their potential applications and advancements in artificial intelligence, particularly through Deep Reinforcement Learning (DRL). While DRL has significantly advanced bipedal locomotion, the development of a unified framework capable of handling a wide range of tasks remains an ongoing challenge. This surv

Yaqi Hu, Mingsheng Yin, Marco Mezzavilla, Hao Guo

The upper mid-band (FR3) has been recently attracting interest for new generation of mobile networks, as it provides a promising balance between spectrum availability and coverage, which are inherent limitations of the sub 6GHz and millimeter wave bands, respectively. In order to efficiently design and optimize the network, channel modeling plays a key role

Vaibhav Vyas, Joseph S. Friedman

The increasing advancement of emerging device technologies that provide alternative basis logic sets necessitates the exploration of innovative logic design automation methodologies. Specifically, emerging computing architectures based on the memristor and the bilayer avalanche spin-diode offer non-commutative or `asymmetric' operations, namely the inverted-

Marko Orel, Draženka Višnjić

Let $SGL_n(\mathbb{F}_2)$ be the set of all invertible $n\times n$ symmetric matrices over the binary field $\mathbb{F}_2$. Let $\Gamma_n$ be the graph with the vertex set $SGL_n(\mathbb{F}_2)$ where a pair of matrices $\{A,B\}$ form an edge if and only if $\textrm{rank}(A-B)=1$. In particular, $\Gamma_3$ is the well-known Coxeter graph. The distance functio

Sergiy Mankovsky, Svitlana Polesya, Hubert Ebert

Induced by an ultra-short laser pulse, the electronic structure of a material undergoes strong modifications leading to a fast demagnetization in magnetic materials. Induced spin-flip transitions are one of the reasons for demagnetization, that is discussed in the literature as a Stoner-like mechanism. On the other hand, demagnetization due to transverse spi

Jason Z. S. Hu, Brigitte Pientka

We scale layered modal type theory to dependent types, introducing DeLaM, dependent layered modal type theory. This type theory is novel in that we have one uniform type theory in which we can not only compose and execute code, but also intensionally analyze the code of types and terms. The latter in particular allows us to write tactics as meta-programs and

Ziliang Hong, Debesh Jha, Koushik Biswas, Zheyuan Zhang

Identifying peri-pancreatic edema is a pivotal indicator for identifying disease progression and prognosis, emphasizing the critical need for accurate detection and assessment in pancreatitis diagnosis and management. This study \textit{introduces a novel CT dataset sourced from 255 patients with pancreatic diseases, featuring annotated pancreas segmentation

Hugo Garrido-Lestache Belinchon, Helina Mulugeta, Adam Haile

Generating audio from a video's visual context has multiple practical applications in improving how we interact with audio-visual media - for example, enhancing CCTV footage analysis, restoring historical videos (e.g., silent movies), and improving video generation models. We propose a novel method to generate audio from video using a sequence-to-sequence mo

William Huang, Sam Ghahremani, Siyou Pei, Yang Zhang

Existing pose estimation models perform poorly on wheelchair users due to a lack of representation in training data. We present a data synthesis pipeline to address this disparity in data collection and subsequently improve pose estimation performance for wheelchair users. Our configurable pipeline generates synthetic data of wheelchair users using motion ca

Malcolm Gabbard

In this paper we define the equivariant double-slice genus and equivariant super-slice genus of a strongly invertible knot. We prove lower bounds for both the equivariant double-slice genus and the equivariant super-slice genus. Using these bounds we find a family of knots which are double-slice and equivariantly slice, but have equivariant double-slice genu

Taro Kimura, Go Noshita

We continue the study of generalized gauge theory called gauge origami, based on the quantum algebraic approach initiated in [arXiv:2310.08545]. In this article, we in particular explore the D2 brane system realized by the screened vertex operators of the corresponding W-algebra. The partition function of this system given by the corresponding conformal bloc

E. O. Sevost'yanov, V. A. Targonskii

We have studied the mappings that satisfy the Poletsky-type inverse inequality in the domain of the Euclidean space. It is proved that the uniform boundary of the family of such mappings is a discrete mapping. We separately considered domains that are locally connected at their boundary and regular domains in the quasiconformal sense.

Eliot W. Robson, Dhemath Reddy, Abhishek K. Umrawal

In recent years, there has been increasing interest in network diffusion models and related problems. The most popular of these are the independent cascade and linear threshold models. Much of the recent experimental work done on these models requires a large number of simulations conducted on large graphs, a computationally expensive task suited for low-lev

Seong-Hoon Jang, Yukitoshi Motome

Rare-earth materials hold promise to realize exotic magnetic states owing to synergy between electron correlations and spin-orbit coupling. Recently, quasi-two-dimensional honeycomb magnets $A_2$PrO$_3$ ($A$ = alkali metals) were predicted to be good candidates for Kitaev quantum spin liquids, as the Kitaev-type bond-dependent anisotropic interactions domina

Paolo Joseph Baioni, Tommaso Benacchio, Luigi Capone, Carlo de Falco

The recent evolution of software and hardware technologies is leading to a renewed computational interest in Particle-In-Cell (PIC) methods such as the Material Point Method (MPM). Indeed, provided some critical aspects are properly handled, PIC methods can be cast in formulations suitable for the requirements of data locality and fine-grained parallelism of

Yuhao Zhou, Xiaohong Li, Rony Keppens

Large-scale coronal plasma evolutions can be adequately described by magnetohydrodynamics (MHD) equations. However, full multi-dimensional MHD simulations require substantial computational resources. Given the low plasma $\beta$ in the solar corona, in many coronal studies, it suffices to approximate the magnetic field to remain topologically fixed and effec

Olzhas Mukazhanov, Rittick Roy, Temurbek Mirzaev, Cosimo Bambi

The pursuit of a comprehensive theory of gravity has led to the exploration of various alternative models, necessitating a model-independent framework. The Konoplya-Rezzolla-Zhidenko (KRZ) parameterization offers a robust method for approximating stationary axisymmetric black hole spacetimes, characterized by a rapidly converging continued-fraction expansion

El Hassane Lahrar, Céline Merlet

Ion adsorption and dynamics in porous carbons is crucial for many technologies such as energy storage and desalination. Nuclear Magnetic Resonance (NMR) spectroscopy is a key method to investigate such systems thanks to the possibility to distinguish adsorbed (in-pore) and bulk (ex-pore) species in the spectra. However, the large variety of magnetic environm

Qi Shi

This paper proposes to distinguish four forms of agentive permissions in multiagent settings. The main technical results are the complexity analysis of model checking, the semantic undefinability of modalities that capture these forms of permissions through each other, and a complete logical system capturing the interplay between these modalities.

Shay Snyder, Sumedh R. Risbud, Maryam Parsa

Performing optimization with event-based asynchronous neuromorphic systems presents significant challenges. Intel's neuromorphic computing framework, Lava, offers an abstract application programming interface designed for constructing event-based computational graphs. In this study, we introduce a novel framework tailored for asynchronous Bayesian optimizati

Dennis Brown, Emily Mulder, Samuel Mulder

Binary program comprehension is critical for many use cases but is difficult, suffering from compounded uncertainty and lack of full automation. We seek methods to improve the effectiveness of the human-machine joint cognitive system performing binary PC. We survey three research areas to perform an indirect cognitive task analysis: cognitive models of the P

C. Darren Dowell, Brandon S. Hensley, Marc Sauvage

Interest in the study of magnetic fields and the properties of interstellar dust, explored through increasingly capable far-IR/submillimeter polarimetry, along with maturing detector technology, have set the stage for a transformative leap in polarization mapping capability using a cryogenic space telescope. We describe the approach pursued by the proposed P

Mohammed Perves

Computing cost of equity for private corporations and performing comparable company analysis (comps) for both public and private corporations is an integral but tedious and time-consuming task, with important applications spanning the finance world, from valuations to internal planning. Performing comps traditionally often times include high ambiguity and su

Jinyong Hahn, Guido Kuersteiner, Andres Santos, Wavid Willigrod

This paper studies the testability of identifying restrictions commonly employed to assign a causal interpretation to two stage least squares (TSLS) estimators based on Bartik instruments. For homogeneous effects models applied to short panels, our analysis yields testable implications previously noted in the literature for the two major available identifica

Shay Snyder, Victoria Clerico, Guojing Cong, Shruti Kulkarni

Graph neural networks have emerged as a specialized branch of deep learning, designed to address problems where pairwise relations between objects are crucial. Recent advancements utilize graph convolutional neural networks to extract features within graph structures. Despite promising results, these methods face challenges in real-world applications due to

Francisco Eiras, Aleksandar Petrov, Bertie Vidgen, Christian Schroeder de Witt

In the next few years, applications of Generative AI are expected to revolutionize a number of different areas, ranging from science & medicine to education. The potential for these seismic changes has triggered a lively debate about potential risks and resulted in calls for tighter regulation, in particular from some of the major tech companies who are lead

Maram Assi, Safwat Hassan, Ying Zou

Deep Learning (DL) frameworks play a critical role in advancing artificial intelligence, and their rapid growth underscores the need for a comprehensive understanding of software quality and maintainability. DL frameworks, like other systems, are prone to code clones. Code clones refer to identical or highly similar source code fragments within the same proj

Tommy Zhang, Nicole Werner, Ashis G. Banerjee

Holographic Optical Tweezers (HOT) are powerful tools that can manipulate micro and nano-scale objects with high accuracy and precision. They are most commonly used for biological applications, such as cellular studies, and more recently, micro-structure assemblies. Automation has been of significant interest in the HOT field, since human-run experiments are

Johannes Betz, Melina Lutwitzi, Steven Peters

The aim of this paper is to investigate the relationship between operational design domains (ODD), automated driving SAE Levels, and Technology Readiness Level (TRL). The first highly automated vehicles, like robotaxis, are in commercial use, and the first vehicles with highway pilot systems have been delivered to private customers. It has emerged as a cruci

C. Ashall, P. Hoeflich, E. Baron, M. Shahbandeh

We present a JWST MIRI/MRS spectrum (5-27 $\mathrm{\mu}$m) of the Type Ia supernova (SN Ia), SN 2021aefx at $+415$ days past $B$-band maximum. The spectrum, which was obtained during the iron-dominated nebular phase, has been analyzed in combination with previous JWST observations of SN 2021aefx, to provide the first JWST time series analysis of an SN Ia. We

Manuel Cuerno, Fernando Galaz-García, Sergio Galaz-García, Telmo Pérez-Izquierdo

Empirical research on \textit{construals}--social affinity groups that share similar patterns of meaning--has advanced significantly in recent years. This progress is largely driven by the development of \textit{Construal Clustering Methods} (CCMs), which group survey respondents into construal clusters based on similarities in their response patterns. We id

Adith Jeyasangar, Abdullah Alsalemi, Shan E Ahmed Raza

Whole Slide Images (WSIs) provide exceptional detail for studying tissue architecture at the cell level. To study tumour microenvironment (TME) with the context of various protein biomarkers and cell sub-types, analysis and registration of features using multi-stained WSIs is often required. Multi-stained WSI pairs normally suffer from rigid and non-rigid de

N. T. Howard, P. Rodriguez-Fernandez, C. Holland, J. Candy

Burning plasma performance, transport, and the effect of hydrogen isotope on confinement has been predicted for ITER baseline scenario (IBS) conditions using nonlinear gyrokinetic profile predictions. Accelerated by surrogate modeling [P. Rodriguez-Fernandez NF 2022], high fidelity, nonlinear gyrokinetic simulations performed with the CGYRO code [J. Candy JC

Paul Hovland, Jan Hückelheim

Computer programs containing calls to linear solvers are a known challenge for automatic differentiation. Previous publications advise against differentiating through the low-level solver implementation, and instead advocate for high-level approaches that express the derivative in terms of a modified linear system that can be solved with a separate solver ca

Jordan Beason, Michael Novitzky, John Kliem, Tyler Errico

The objective of this work is to evaluate multi-agent artificial intelligence methods when deployed on teams of unmanned surface vehicles (USV) in an adversarial environment. Autonomous agents were evaluated in real-world scenarios using the Aquaticus test-bed, which is a Capture-the-Flag (CTF) style competition involving teams of USV systems. Cooperative te

M. Asgari-Targhi, D. H. Brooks, M. Hahn, S. Imada

We present a study of spectral line width measurements from the Extreme Ultraviolet Imaging Spectrometer (EIS) on {\it Hinode}. We used spectral line profiles of Fe {\sc xvi} 262.984 {\AA}, Fe {\sc xiv} 264.787 {\AA}, Fe {\sc xiv} 270.519 {\AA}, Fe {\sc xiv} 274.203 {\AA}, and Fe {\sc xv} 284.160 {\AA}, and studied 11 active regions. Previous studies of spec

Yoonha Cha, Victoria Jackson, Isabela Figueira, Stacy M. Branham

Context: Scholars in the software engineering (SE) research community have investigated career advancement in the software industry. Research topics have included how individual and external factors can impact career mobility of software professionals, and how gender affects career advancement. However, the community has yet to look at career mobility from t

Pierre-A. Vuillermot

In this article we introduce a new class of weighted sequence spaces of Sobolev type and prove several compact embedding theorems for them. It is our contention that the chosen class is general enough so as to allow applications in various areas of mathematics and mathematical physics. In particular, our results constitute a generalization of those compact e

Keziah Naggita, Matthew R. Walter, Avrim Blum

Recourse generators provide actionable insights, often through feature-based counterfactual explanations (CFEs), to help negatively classified individuals understand how to adjust their input features to achieve a positive classification. These feature-based CFEs, which we refer to as \emph{low-level} CFEs, are overly specific (e.g., coding experience: \(4 \

Tanvi Deshpande, Eva Prakash, Elsie Gyang Ross, Curtis Langlotz

The high cost of creating pixel-by-pixel gold-standard labels, limited expert availability, and presence of diverse tasks make it challenging to generate segmentation labels to train deep learning models for medical imaging tasks. In this work, we present a new approach to overcome the hurdle of costly medical image labeling by leveraging foundation models l

Peter Deák, Song Li, Adam Gali

Spin-to-photon interfaces from defects in silicon hold great promise towards realizing quantum repeaters with the combination of advanced semiconductor and photonics technologies. Recently, controlled creation and erasure of simple carbon interstitial defects have been successfully realised in silicon. This defect has a stable structure near room temperature

Hao Wang, Jiayou Qin, Xiwen Chen, Ashish Bastola

Assistive visual navigation systems for visually impaired individuals have become increasingly popular thanks to the rise of mobile computing. Most of these devices work by translating visual information into voice commands. In complex scenarios where multiple objects are present, it is imperative to prioritize object detection and provide immediate notifica

Panagiotis Charalambous

In this thesis, we present the emergence of an $SL(2,R)$ ("Love") symmetry in the suitably defined near-zone region, relevant for studying the black hole response problem. This symmetry is globally defined and physical solutions of the black hole linearized field equations are closed under its action. The vanishing of static Love numbers is found to naturall

Vazgen Zohranyan, Vagner Navasardyan, Hayk Navasardyan, Jan Borggrefe

Recent advancements in AI have significantly transformed medical imaging, particularly in angiography, by enhancing diagnostic precision and patient care. However existing works are limited in analyzing the aorta and iliac arteries, above all for vascular anomaly detection and characterization. To close this gap, we propose Dr-SAM, a comprehensive multi-stag

Yunyi Zhu, Faraz Faruqi, Stefanie Mueller

Advances in Generative AI tools have allowed designers to manipulate existing 3D models using text or image-based prompts, enabling creators to explore different design goals. Photochromic color-changing systems, on the other hand, allow for the reprogramming of surface texture of 3D models, enabling easy customization of physical objects and opening up the

Xiangyu Peng, Jessica Quaye, Sudha Rao, Weijia Xu

We explore how interaction with large language models (LLMs) can give rise to emergent behaviors, empowering players to participate in the evolution of game narratives. Our testbed is a text-adventure game in which players attempt to solve a mystery under a fixed narrative premise, but can freely interact with non-player characters generated by GPT-4, a larg

P. L. Krapivsky, S. Redner

We introduce an autocatalytic aggregation model in which the rate at which two clusters merge to form a cluster is controlled by the presence of a third "catalytic" cluster whose mass must equal to the mass of one of the reaction partners. The catalyst is unaffected by the joining event and is available to either participate in or catalyze subsequent reactio

Shih-Hong Huang, Ya-Fang Lin, Zeyu He, Chieh-Yang Huang

Users can discuss a wide range of topics with large language models (LLMs), but they do not always prefer solving problems or getting information through lengthy conversations. This raises an intriguing HCI question: How does instructing LLMs to engage in longer or shorter conversations affect conversation quality? In this paper, we developed two Slack chatb

Pu Gao, Jacob Mausberg, Peter Nelson

We study the evolution of random matroids represented by the sequence of random matrices over ${\mathbb F}_q$ where columns are added one after the other, and each column vector is a uniformly random vector in ${\mathbb F}_q^n$, independent of each other. We study the appearance of matroid minors, the appearance of circuits, the evolution of the connectiviti

Mojtaba Abolfazli, Mohammad Zaeri Amirani, Anders Høst-Madsen, June Zhang

Given a default distribution $P$ and a set of test data $x^M=\{x_1,x_2,\ldots,x_M\}$ this paper seeks to answer the question if it was likely that $x^M$ was generated by $P$. For discrete distributions, the definitive answer is in principle given by Kolmogorov-Martin-L\"{o}f randomness. In this paper we seek to generalize this to continuous distributions. We

Cong Zhang, Kathleen Jepson, Yu-Ying Chuang

Increasingly, phonetic research utilizes data collected from participants who record themselves on readily available devices. Though such recordings are convenient, their suitability for acoustic analysis remains an open question, especially regarding how the individual methods affect acoustic measures over time. We used Quantile Generalized Additive Mixed M

K. Razi Naqvi

A report by Brillouin (from Perrin's laboratory) on the rate of adsorption of `granules' to a glass plate [\textit{Ann. Chim. Phys.} 27 (1912) 412--23] prompted Marian von Smoluchowski (MvS) to interpret the data in terms of his newly developed theory of restricted Brownian motion. Placing an adsorbing wall at $x=0$, he modelled the particle concentration $n

Cristopher McIntyre-Garcia, Adrien Heymans, Beril Borali, Won-Sook Lee

Deep Learning (DL) models excel in computer vision tasks but can be susceptible to adversarial examples. This paper introduces Triple-Metric EvoAttack (TM-EVO), an efficient algorithm for evaluating the robustness of object-detection DL models against adversarial attacks. TM-EVO utilizes a multi-metric fitness function to guide an evolutionary search efficie