November 2024 arXiv papers — page 61

Pyeonghwa Kim, Charis Asante-Agyei, Isabel Munoz, Michael Dunn

What does work and career success mean for those who secure their work using digital labor platforms? Traditional research on success predominantly relies on organizationally-centric benchmarks, such as promotions and income. These measures provide limited insights into the evolving nature of work and careers shaped at the intersection of digital labor platf

Ignacio del Amo, George Datseris, Mark Holland

Two dynamical indicators, the local dimension and the extremal index, used to quantify persistence in phase space have been developed and applied to different data across various disciplines. These are computed using the asymptotic limit of exceedances over a threshold, which turns to be a Generalized Pareto Distribution in many cases. However the derivation

Jiange Yang, Haoyi Zhu, Yating Wang, Gangshan Wu

Learning from multiple domains is a primary factor that influences the generalization of a single unified robot system. In this paper, we aim to learn the trajectory prediction model by using broad out-of-domain data to improve its performance and generalization ability. Trajectory model is designed to predict any-point trajectories in the current frame give

Arjun Sridhar, Chen-Chia Chang, Junyao Zhang, Yiran Chen

Routability optimization in modern EDA tools has benefited greatly from using machine learning (ML) models. Constructing and optimizing the performance of ML models continues to be a challenge. Neural Architecture Search (NAS) serves as a tool to aid in the construction and improvement of these models. Traditional NAS techniques struggle to perform well on r

Jian Shi, Qian Wang, Zhenyu Li, Wenqing Cui

Generating high-quality stereo videos requires consistent depth perception and temporal coherence across frames. Despite advances in image and video synthesis using diffusion models, producing high-quality stereo videos remains a challenging task due to the difficulty of maintaining consistent temporal and spatial coherence between left and right views. We i

Maxwell H. Rosen, Wrick Sengupta, Ian Ochs, Felix Parra Diaz

Collisions are crucial in governing particle and energy transport in plasmas confined in a magnetic mirror trap. Modern gyrokinetic codes model transport in magnetic mirrors, but some utilize approximate model collision operators. This study focuses on a Pastukhov-style method of images calculation of particle and energy confinement times using a Lenard-Bern

Gaurav Kumar, Arezoo M. Ardekani

Lipid nanoparticles (LNPs) are highly effective carriers for gene therapies, including mRNA and siRNA delivery, due to their ability to transport nucleic acids across biological membranes, low cytotoxicity, improved pharmacokinetics, and scalability. A typical approach to formulate LNPs is to establish a quantitative structure-activity relationship (QSAR) be

Yu-Ao Chen, Chenghong Zhu, Keming He, Yingjian Liu

Symmetry plays a crucial role in quantum physics, dictating the behavior and dynamics of physical systems. In this paper, we develop a hypothesis-testing framework for quantum dynamics symmetry using a limited number of queries to the unknown unitary operation and establish the quantum max-relative entropy lower bound for the type-II error. We construct opti

Yuika Ueda, Shinji Deguchi

Cellular adaptation to environmental changes relies on the dynamic remodeling of subcellular structures. Among these, sarcomere structures are fundamental to the organization and function of the cytoskeletal architecture. In muscle-type cells, sarcomeres exhibit ordered structures of consistent lengths, optimized for stable force generation. By contrast, non

Pratik Ingle, Kasper Støy, Andres Faiña

Object manipulation in robotics faces challenges due to diverse object shapes, sizes, and fragility. Gripper-based methods offer precision and low degrees of freedom (DOF) but the gripper limits the kind of objects to grasp. On the other hand, surface-based approaches provide flexibility for handling fragile and heterogeneous objects but require numerous act

Prakriti Kayastha, Erik Fransson, Paul Erhart, Lucy D. Whalley

Chalcogenide perovskites are lead-free materials for potential photovoltaic or thermoelectric applications. BaZrS$_3$ is the most studied member of this family due to its superior thermal and chemical stability, desirable optoelectronic properties, and low thermal conductivity. Phase transitions of BaZrS$_3$ remain underexplored in the literature, as most ex

Arash Behboodi, Gabriele Cesa

Weight sharing, equivariance, and local filters, as in convolutional neural networks, are believed to contribute to the sample efficiency of neural networks. However, it is not clear how each one of these design choices contributes to the generalization error. Through the lens of statistical learning theory, we aim to provide insight into this question by ch

Projesh Nath Choudhury, Shivangi Yadav

The class of strictly sign regular (SSR) matrices has been extensively studied by many authors over the past century, notably by Schoenberg, Motzkin, Gantmacher, and Krein. A classical result of Gantmacher-Krein assures the existence of SSR matrices for any dimension and sign pattern. In this article, we provide an algorithm to explicitly construct an SSR ma

Pietro Carlo Boldini, Benjamin Bugeat, Jurriaan W. R. Peeters, Markus Kloker

We investigate the controlled K-type breakdown of a flat-plate boundary-layer with highly non-ideal supercritical fluid at a reduced pressure of $p_{r,\infty}=1.10$. Direct numerical simulations are performed at a Mach number of $M_\infty=0.2$ for one subcritical (liquid-like regime) temperature profile and one strongly-stratified transcritical (pseudo-boili

Alexander W. Levis, Edward H. Kennedy, Alec McClean, Sivaraman Balakrishnan

Recent methodological research in causal inference has focused on effects of stochastic interventions, which assign treatment randomly, often according to subject-specific covariates. In this work, we demonstrate that the usual notion of stochastic interventions have a surprising property: when there is unmeasured confounding, bounds on their effects do not

Balder ten Cate, Tobias Kappé

Kleene Algebra with Tests (KAT) provides an elegant algebraic framework for describing non-deterministic finite-state computations. Using a small finite set of non-deterministic programming constructs (sequencing, non-deterministic choice, and iteration) it is able to express all non-deterministic finite state control flow over a finite set of primitives. It

Xi Jiang, Aaron Gember-Jacobson, Nick Feamster

Model checkers and consistency checkers detect critical errors in router configurations, but these tools require significant manual effort to develop and maintain. LLM-based Q&A models have emerged as a promising alternative, allowing users to query partitions of configurations through prompts and receive answers based on learned patterns, thanks to transfor

Alexandru G. Ichert, William Barford

A theory of singlet fission in carotenoid dimers is presented which aims to explain the mechanism behind the creation of two uncorrelated triplets. Following the initial photoexcitation of a carotenoid chain to a "bright" $n^1B_u^+$ state, there is ultrafast internal conversion to the intrachain "dark" $1^1B_u^-$ triplet-pair state. This strongly exchanged-c

Kubra Duran, Mehmet Ozdem, Kerem Gursu, Berk Canberk

The dramatic increase in the number of smart services and their diversity poses a significant challenge in Internet of Things (IoT) networks: heterogeneity. This causes significant quality of service (QoS) degradation in IoT networks. In addition, the constraints of IoT devices in terms of computational capability and energy resources add extra complexity to

Yumeng Liu, Xiaoxiao Long, Zemin Yang, Yuan Liu

Our work aims to reconstruct hand-object interactions from a single-view image, which is a fundamental but ill-posed task. Unlike methods that reconstruct from videos, multi-view images, or predefined 3D templates, single-view reconstruction faces significant challenges due to inherent ambiguities and occlusions. These challenges are further amplified by the

Davide Riva, Cristina Rossetti

In this essay we discuss the recent trends in visual analysis and exploration of Knowledge Graphs, particularly in conjunction with Knowledge Graph Embedding techniques. We present an overview of the current state of visualization techniques and frameworks for KGs, in relation to four identified challenges. The challenges in visualizing Knowledge Graphs incl

Pablo Moriano, Steven C. Hespeler, Mingyan Li, Maria Mahbub

Modern cyberattacks in cyber-physical systems (CPS) rapidly evolve and cannot be deterred effectively with most current methods which focused on characterizing past threats. Adaptive anomaly detection (AAD) is among the most promising techniques to detect evolving cyberattacks focused on fast data processing and model adaptation. AAD has been researched in t

P. Baum, C. Ropers

A recent paper by Hui et al. (Ref. [1], Sci. Adv. 10, eadp5805 (2024)) claims the demonstration of 'Attosecond electron microscopy and diffraction' with laser-gated electron pulses. In this comment, we point out a series of physical and technical inconsistencies of the experiment and results. Beyond failing to show any microscopy, the reported concept does n

Maribel Acosta, Chang Qin, Tim Schwabe

This chapter delves into the emerging field of neuro-symbolic query optimization for knowledge graphs (KGs), presenting a comprehensive exploration of how neural and symbolic techniques can be integrated to enhance query processing. Traditional query optimizers in knowledge graphs rely heavily on symbolic methods, utilizing dataset summaries, statistics, and

Oliver Janzer, Peter Manohar

A code $C \colon \{0,1\}^k \to \{0,1\}^n$ is a $q$-query locally decodable code ($q$-LDC) if one can recover any chosen bit $b_i$ of the message $b \in \{0,1\}^k$ with good confidence by querying a corrupted string $\tilde{x}$ of the codeword $x = C(b)$ in at most $q$ coordinates. For $2$ queries, the Hadamard code is a $2$-LDC of length $n = 2^k$, and this

Ahana Ghosh, Liina Malva, Alkis Gotovos, Danial Hooshyar

We explore the role of quizzes in elementary visual programming domains popularly used for K-8 computing education. Prior work has studied various quiz types, such as fill-in-the-gap write-code questions. However, the overall impact of these quizzes is unclear: studies often show utility in the learning phase when enhanced with quizzes, though limited transf

Kimball A. Milton, Nima Pourtolami, Gerard Kennedy

This article summarizes our recent efforts to understand spontaneous quantum vacuum forces and torques, which require that a stationary object be out of thermal equilibrium with the blackbody background radiation. We proceed by a systematic expansion in powers of the electric susceptibility. In first order, no spontaneous force can arise, although a torque c

A. Tavleev, V. F. Suleimanov, K. Werner, A. Santangelo

Supersoft X-ray sources (SSS) are thought to be accreting white dwarfs (WDs) in close binary systems, with thermonuclear burning on their surfaces. The SSS RX J0513.9-6951 in the Large Magellanic Cloud (LMC) exhibits cyclic variations between optical low and high states, which are anti-correlated with its X-ray flux. This behaviour is believed to result from

Iacopo Ghinassi, Leonardo Catalano, Tommaso Colella

The use of Natural Language Processing (NLP) for helping decision-makers with Climate Change action has recently been highlighted as a use case aligning with a broader drive towards NLP technologies for social good. In this context, Aspect-Based Summarization (ABS) systems that extract and summarize relevant information are particularly useful as they provid

Dominic J. Taylor, A. M. Swinbank, Ian Smail, Annagrazia Puglisi

The molecular gas in the interstellar medium (ISM) of star-forming galaxy populations exhibits diverse physical properties. We investigate the $^{12}$CO excitation of twelve dusty, luminous star-forming galaxies at $z \sim 2-4$ by combining observations of the $^{12}$CO from $J_{\rm up} = 1$ to $J_{\rm up} = 8$. The spectral line energy distribution (SLED) h

Meir Yossef Levi, Guy Gilboa

Contrastive Language-Image Pre-Training (CLIP) is highly instrumental in machine learning applications within a large variety of domains. We investigate the geometry of this embedding, which is still not well understood. We examine the raw unnormalized embedding and show that text and image reside on linearly separable ellipsoid shells, not centered at the o

M. A. Guerrero, D. A. Vasquez-Torres, J. B. Rodríguez-González, J. A. Toalá

A considerable number of asymptotic giant branch (AGB) stars exhibit UV excess and/or X-ray emission that indicates a binary companion. AGB stars are so bright that they easily outshine their companions. This almost prevents their identification. Y Gem has been known for some decades to be an AGB star that is bright in the far-UV and X-rays, but it is unclea

Yue Wang, Yuanbiao Yang, Zhuo-xu Cui, Tian Zhou

Magnetic Resonance Imaging (MRI) is an inherently multi-contrast modality, where cross-contrast priors can be exploited to improve image reconstruction from undersampled data. Recently, diffusion models have shown remarkable performance in MRI reconstruction. However, they still struggle to effectively utilize such priors, mainly because existing methods rel

Nishant Mangre, Jiesen Wang

The potential demand in the market and customers' perception of service value are crucial factors in pricing strategies, resource allocation, and other operational decisions. However, this information is typically private and not readily accessible. In this paper, we analyze a service system operating across two stations, each with its own customer flow. Cus

Mika Göös, Gilbert Maystre, Kilian Risse, Dmitry Sokolov

We exhibit a monotone function computable by a monotone circuit of quasipolynomial size such that any monotone circuit of polynomial depth requires exponential size. This is the first size-depth tradeoff result for monotone circuits in the so-called supercritical regime. Our proof is based on an analogous result in proof complexity: We introduce a new family

Susanna F. de Rezende, Noah Fleming, Duri Andrea Janett, Jakob Nordström

We exhibit supercritical trade-off for monotone circuits, showing that there are functions computable by small circuits for which any circuit must have depth super-linear or even super-polynomial in the number of variables, far exceeding the linear worst-case upper bound. We obtain similar trade-offs in proof complexity, where we establish the first size-dep

Xuanrui Feng, Zhenfu Wang

We derive quantitative propagation of chaos in the sense of relative entropy for the 2D viscous vortex model with general circulations, approximating the vorticity formulation of the 2D Navier-Stokes equation on the whole Euclidean space. Our results work on the general setting that the vortices are positioned on the whole space $\R^2$ and that the circulati

Elly Hung, Anastasia Mantziou, Gesine Reinert

In this paper, we propose a new Bayesian Poisson network autoregression mixture model (PNARM). Our model combines ideas from the models of Dahl 2008, Ren et al. 2024 and Armillotta and Fokianos 2024, as it is motivated by the following aims. We consider the problem of modelling multivariate count time series since they arise in many real-world data sets, but

Pedro Enrique Iturria-Rivera, Raimundas Gaigalas, Medhat Elsayed, Majid Bavand

Extended Reality (XR) services are set to transform applications over 5th and 6th generation wireless networks, delivering immersive experiences. Concurrently, Artificial Intelligence (AI) advancements have expanded their role in wireless networks, however, trust and transparency in AI remain to be strengthened. Thus, providing explanations for AI-enabled sy

Alexander Stevens, Jari Peeperkorn, Johannes De Smedt, Jochen De Weerdt

In predictive process monitoring, predictive models are vulnerable to adversarial attacks, where input perturbations can lead to incorrect predictions. Unlike in computer vision, where these perturbations are designed to be imperceptible to the human eye, the generation of adversarial examples in predictive process monitoring poses unique challenges. Minor c

Alexander Saccani, Paolo Tiso

We present a novel technique to significantly reduce the offline cost associated to non-intrusive nonlinear tensors identification in reduced order models (ROMs) of geometrically nonlinear, finite elements (FE)-discretized structural dynamics problems. The ROM is obtained by Galerkin-projection of the governing equations on a reduction basis (RB) of Vibratio

Francesco Toppan

I report the recent advances in applying (graded) Hopf algebras with braided tensor product in two scenarios: i) paraparticles beyond bosons and fermions living in any space dimensions and transforming under the permutation group; ii) physical models of anyons living in two space-dimensions and transforming under the braid group. In the first scenario simple

Loïc Constantin, Jacques Giacomoni, Guillaume Warnault

In this paper, we prove the existence and the uniqueness of a weak and mild solution of the following nonlinear parabolic problem involving the porous $p$-fractional Laplacian: \begin{equation*} \begin{cases} \partial_t u+(-\Delta)^s_p(|u|^{m-1}u)=h(t,x,|u|^{m-1}u) & \text{in} \; (0,T)\times \Omega,\\ u=0 & \text{in} \; (0,T) \times \mathbb{R}^d\backslash \O

Eden Luzon, Guy Amit, Roy Weiss, Torsten Kraub

Neural networks are often trained on proprietary datasets, making them attractive attack targets. We present a novel dataset extraction method leveraging an innovative training time backdoor attack, allowing a malicious federated learning server to systematically and deterministically extract complete client training samples through a simple indexing process

Chelsea A. Williams, Stefano Scali, Antonio A. Gentile, Daniel Berger

Quantum differential equation solvers aim to prepare solutions as $n$-qubit quantum states over a fine grid of $O(2^n)$ points, surpassing the linear scaling of classical solvers. However, unlike classically stored vectors of solutions, the readout of exact quantum states poses a bottleneck due to the complexity of tomography. Here, we show that the readout

Ernests Lavrinovics, Russa Biswas, Johannes Bjerva, Katja Hose

Large Language Models (LLMs) have revolutionized Natural Language Processing (NLP) based applications including automated text generation, question answering, chatbots, and others. However, they face a significant challenge: hallucinations, where models produce plausible-sounding but factually incorrect responses. This undermines trust and limits the applica

Javier Ferrando, Oscar Obeso, Senthooran Rajamanoharan, Neel Nanda

Hallucinations in large language models are a widespread problem, yet the mechanisms behind whether models will hallucinate are poorly understood, limiting our ability to solve this problem. Using sparse autoencoders as an interpretability tool, we discover that a key part of these mechanisms is entity recognition, where the model detects if an entity is one

Zeyu Dong, Yimin Zhu, Yansong Li, Kevin Mahon

Traditional autonomous driving methods adopt a modular design, decomposing tasks into sub-tasks. In contrast, end-to-end autonomous driving directly outputs actions from raw sensor data, avoiding error accumulation. However, training an end-to-end model requires a comprehensive dataset; otherwise, the model exhibits poor generalization capabilities. Recently

An-Ke Lei, Zhi-Lei She, Yu-Liang Yan, Dai-Mei Zhou

Parton And-hadron China Institute of Atomic Energy (PACIAE) is a multipurpose Monte Carlo event generator developed to describe a wide range of high-energy collisions, including lepton-lepton, lepton-hadron, lepton-nucleus, hadron-hadron, hadron-nucleus, and nucleus-nucleus collisions. It is built based on the PYTHIA program, and incorporates parton and hadr

Natenaile Asmamaw Shiferaw, Simpenzwe Honore Leandre, Aman Sinha, Dillip Rout

Course Outcome (CO) and Program Outcome (PO)/Program-Specific Outcome (PSO) alignment is a crucial task for ensuring curriculum coherence and assessing educational effectiveness. The construction of a Course Articulation Matrix (CAM), which quantifies the relationship between COs and POs/PSOs, typically involves assigning numerical values (0, 1, 2, 3) to rep

T. Sperling, J. Eislöffel

An established method measuring the hydrogen ionisation fraction in shock excited gas is the BE99 method, which utilises six bright forbidden emission lines of [SII]6716, 6731, [NII]6548, 6583, and [OI]6300, 6363. We aim to extent the BE99 method by including more emission lines in the blue and near-infrared part of the spectrum ($\lambda$ = 3500-11000A), an

Junhua Liu, Yong Keat Tan, Bin Fu, Kwan Hui Lim

In conversational AI systems, a critical challenge in training effective multi-turn intent classification models lies in the generation of large-scale, domain-specific, multilingual dialogue datasets. In this paper, we introduce Chain-of-Intent, a novel framework that integrates Hidden Markov Models (HMMs) with Large Language Models (LLMs) to generate intent

Xidong Feng, Bo Liu, Yan Song, Haotian Fu

Artificial intelligence progresses towards the "Era of Experience," where agents are expected to learn from continuous, grounded interaction. We argue that traditional Reinforcement Learning (RL), which typically represents value as a scalar, can restrict agent's deep understanding of environments and hinders the active, deliberative learning crucial for nav

Ruiguo Yu, Yiyang Zhang, Yuan Tian, Zhiqiang Liu

Deep learning-based segmentation methods are widely utilized for detecting lesions in ultrasound images. Throughout the imaging procedure, the attenuation and scattering of ultrasound waves cause contour blurring and the formation of artifacts, limiting the clarity of the acquired ultrasound images. To overcome this challenge, we propose a contour-based prob

Nicholas E. Pacheco, Kang Zhang, Ashley S. Reyes, Christopher J. Pacheco

This paper presents a computational model, based on the Finite Element Method (FEM), that simulates the thermal response of laser-irradiated tissue. This model addresses a gap in the current ecosystem of surgical robot simulators, which generally lack support for lasers and other energy-based end effectors. In the proposed model, the thermal dynamics of the

Nahid Javier-Nol, Christian Rubio-Montiel, Ingrid Torres-Ramos

We study an extension to directed graphs of the parameter called the $b$-chromatic number of a graph in terms of acyclic vertex colorings: the dib-chromatic number. We give general bounds for this parameter. We also show some results about tournaments and regular digraphs.

Wei Guo

In this paper, we use the solution phase space approach based on the covariant phase space formalism to compute the conserved charges of the BTZ black hole, namely mass, angular momentum, and entropy. Furthermore, we discuss the first law of the BTZ black hole and the Smarr relation. For completeness, outer horizon and inner horizon cases have been all inclu

Shiming He, Alexander von Rohr, Dominik Baumann, Ji Xiang

How can robots learn and adapt to new tasks and situations with little data? Systematic exploration and simulation are crucial tools for efficient robot learning. We present a novel black-box policy search algorithm focused on data-efficient policy improvements. The algorithm learns directly on the robot and treats simulation as an additional information sou

Samer Afach, Benjamin Marsh, Enrico Rubboli

In this paper, we informally introduce the Pulsar proof of stake consensus paper and discuss the relevant design decisions and considerations. The Pulsar protocol we propose is designed to facilitate the creation of a proof of stake sidechain for a proof of work blockchain. We present an overview of a novel composable density-based chain selection rule for p

Sujinda Chaiyachad, Trung-Phuc Vo, Warakorn Jindata, Sirisak Singsen

Bandgaps in layered materials are critical for enabling functionalities such as tunable photodetection, efficient energy conversion, and nonlinear optical responses, which are essential for next-generation photonic and quantum devices. Gap engineering could form heterostructures with complementary materials like transition metal dichalcogenides or perovskite

Jialin Lu, Junjie Shan, Ziqi Zhao, Ka-Ho Chow

As object detection becomes integral to many safety-critical applications, understanding its vulnerabilities is essential. Backdoor attacks, in particular, pose a serious threat by implanting hidden triggers in victim models, which adversaries can later exploit to induce malicious behaviors during inference. However, current understanding is limited to singl

Alexander Leguizamon-Robayo, Antonio Jiménez-Pastor, Micro Tribastone, Max Tschaikowski

Gaining insights from realistic dynamical models of biochemical systems can be challenging given their large number of state variables. Model reduction techniques can mitigate this by decreasing complexity by mapping the model onto a lower-dimensional state space. Exact constrained lumping identifies reductions as linear combinations of the original state va

C. Bergez-Casalou, Q. Kral

Recent ALMA observations discovered consequent amounts (i.e., up to a few $10^{-1}\; \rm M_\oplus$) of CO gas in debris disks that were expected to be gas-free. This gas is in general estimated to be mostly composed of CO, C, and O (i.e., $\rm H_2$-poor), unlike the gas present in protoplanetary disks ($\rm H_2$-rich). At this stage, the majority of planet f

E. Martínez, J. Vidarte, J. L. Zapata

We investigate the qualitative characteristics of a test particle attracted to an irregular elongated body, modeled as a non-homogeneous straight segment with a variable linear density. By deriving the potential function in closed form, we formulate the Hamiltonian equations of motion for this system. Our analysis reveals a family of periodic circular orbits

Andreas Buchinger, Christian Seifert

We study evolutionary equations in exponentially weighted $\mathrm{L}^{2}$-spaces as introduced by Picard in 2009. First, for a given evolutionary equation, we explicitly describe the $\nu$-adjoint system, which turns out to describe a system backwards in time. We prove well-posedness for the $\nu$-adjoint system. We then apply the thus obtained duality to i

Ravindra B. Bapat, Ranveer Singh, Hitesh Wankhede

Let $G$ be a bipartite graph with adjacency matrix $A(G)$. The characteristic polynomial $\phi(G,x)=\det(xI-A(G))$ and the permanental polynomial $\pi(G,x) = \text{per}(xI-A(G))$ are both graph invariants used to distinguish graphs. For bipartite graphs, we define the modified characteristic polynomial, which is obtained by changing the signs of some of the

Pablo Montenegro, Gabriela P. Ovando

The aim of this work is the study of geodesics on Lorentzian homogeneous spaces of the form $M=G/\Lambda$, where $G$ is a solvable Lie group endowed with a bi-invariant Lorentzian metric and $\Lambda < G$ is a cocompact lattice. Conditions to assert closedness of light, time or spacelike geodesics on the compact quotient spaces are given. This study implicit

Zhenjie Ren, Songbo Wang

We investigate Gibbs measures for diffusive particles interacting through a two-body mean field energy. By identifying a gradient structure for the conditional law, we derive sharp bounds on the size of chaos, providing a quantitative characterization of particle independence. To handle interaction forces that are unbounded at infinity, we study the concentr

T. A. Permyakova, G. Carraro, A. F. Seleznev, A. M. Sobolev

We study the structure, interstellar absorption, color-magnitude diagrams, kinematics, and dynamical state of embedded star clusters in the star-forming region associated with the giant molecular cloud G174+2.5. Our investigation is based on photometric data from the UKIDSS Galactic Plane Survey catalog and astrometric data from the Gaia DR3 catalogs. First,

Lekhashri Konwar, Bhavna Yadav

In this study, we analyze the influence of Non-Standard Interaction (NSI) on steering in three-flavor neutrino oscillations, with a focus on the NO$\nu$A and DUNE experimental setups. DUNE, having a longer baseline, exhibits a more pronounced deviation towards NSI in steering compared to NO$\nu$A. Within the energy range where DUNE's maximum flux appears, th

Zoe Jonassen, Katharine Lawrence, Batia Mishan Wiesenfeld, Stefan Feuerriegel

Remote patient monitoring (RPM) is the use of digital technologies to improve patient care at a distance. However, current RPM solutions are often biased toward tech-savvy patients. To foster health equity, researchers have studied how to address the socio-economic and cognitive needs of diverse patient groups, but their emotional needs have remained largely

Anand Deopurkar, Anand Patel

This paper culminates in the count of the number of 3-Veronese surfaces passing through 13 general points. This follows the case of 2-Veronese surfaces discovered by Coble in the 1920's. One important element of the calculation is a direct construction of a space of "complete triangles." Our construction is different from the classical ordered constructions

Maryam Dehghanian, Nahum Arav, Mayank Sharma, Doyee Byun

Context. Quasar outflows are key players in the feedback processes that influence the evolution of galaxies and the intergalactic medium. The chemical abundance of these outflows provides crucial insights into their origin and impact. Aims. To determine the absolute abundances of nitrogen and sulfur and the physical conditions of the outflow seen in quasar 3

Diletta Abbonato

This paper establishes an empirical baseline of public sentiment toward Fourth Industrial Revolution (4IR) technologies across six European countries during the period 2006--2019, prior to the widespread adoption of generative AI systems. Employing transformer-based natural language processing models on a corpus of approximately 90,000 tweets and news articl

Roberto Fenollosa, Fernando Ramiro-Manzano

Hydrogenated amorphous silicon microspheres feature a pronounced phononic peak around 2000 cm-1 when they are thermally excited by means of a blue laser. This phononic signature corresponds to vibrational modes of silicon-hydrogen bonds and its emitted light can be coupled to Mie modes defined by the spherical cavity. The signal is apparently quite stable at

Yuke Zhu, Chi Xie, Shuang Liang, Bo Zheng

Recent advances on Multi-modal Large Language Models have demonstrated that high-resolution image input is crucial for model capabilities, especially for fine-grained tasks. However, high-resolution images lead to a quadratic increase in the number of visual tokens input into LLMs, resulting in significant computational costs. Current work develop visual tok

Alain Bretto, Mehrdad Nasernejad, Jonathan Toledo

In this paper, we first show that any square-free monomial ideal in $K[x_1, x_2, x_3, x_4, x_5]$ has the strong persistence property. Next we will provide a criterion for a minimal counterexample to the Conforti-Cornuejols conjecture. Finally we give a necessary and sufficient condition to determine the normally torsion-freeness of a linear combination of tw

Johanna Kerler-Back, Timo Reis, Tatjana Stykel

We consider the quasilinear magneto-quasistatic field equations that arise in the simulation of low-frequency electromagnetic devices coupled to electrical circuits. Spatial discretization of these equations on 3D domains using the finite element method results in a singular system of differential-algebraic equations (DAEs). First, we analyze the structural

Colin D. Hamill, Alexandria V. Johnson, Natasha Batalha, Rowan Nag

Examining reflected light from exoplanets aids in our understanding of the scattering properties of their atmospheres and will be a primary task of future flagship space- and ground-based telescopes. We introduce an enhanced capability of Planetary Intensity Code for Atmospheric Scattering Observations (PICASO), an open-source radiative transfer model used f

Patryk-Lipka Bartosik, Kaelan Donatella, Maxwell Aifer, Denis Melanson

Thermodynamic computing has emerged as a promising paradigm for accelerating computation by harnessing the thermalization properties of physical systems. This work introduces a novel approach to solving quadratic programming problems using thermodynamic hardware. By incorporating a thermodynamic subroutine for solving linear systems into the interior-point m

Charalampos Tzerefos, Theodoros Papanikolaou, Spyros Basilakos, Emmanuel N. Saridakis

Within the context of a Chern-Simons running-vacuum-model (RVM) cosmology, one expects an early-matter dominated (eMD) reheating period after RVM inflation driven by the axion field. Treating thus in this work Chern-Simons RVM cosmology as an effective $f(R)$ gravity theory characterized by logarithmic corrections of the spacetime curvature, we study the gra

Kubra Duran, Lal Verda Cakir, Mehmet Ozdem, Kerem Gursu

6G networks are envisioned to enable a wide range of applications, such as autonomous vehicles and smart cities. However, this rapid expansion of network topologies makes the management of 6G wireless networks more complex and leads to performance degradation. Even though state-of-the-art applications on network services are providing promising results, they

Ziying Xiang, Jun-Wei Luo, Shu-Shen Li

The metal-induced gap states (MIGS) are commonly believed to cause the strong Femi level pinning (FLP) in the metal-semiconductors contacts. Here, we unravel unambiguously that the dangling bonds-induced interface states play a crucial role, even comparable with MIGS. The first-principles calculations show that metal-Ge and metal-Si contacts should possess a

Paul Fergus, Carl Chalmers, Naomi Matthews, Stuart Nixon

Camera traps offer enormous new opportunities in ecological studies, but current automated image analysis methods often lack the contextual richness needed to support impactful conservation outcomes. Here we present an integrated approach that combines deep learning-based vision and language models to improve ecological reporting using data from camera traps

Matteo Cerruti, Annika Rudolph, Maria Petropoulou, Markus Böttcher

We perform the first dedicated comparison of five hadronic codes (AM$^3$, ATHE$\nu$A, B13, LeHa-Paris, and LeHaMoC) that have been extensively used in modeling of the spectral energy distribution (SED) of jetted active galactic nuclei. The purpose of this comparison is to identify the sources of systematic errors (e.g., implementation method of proton-photon

Kaushik Bal, Stuti Das

We investigate the following mixed local and nonlocal quasilinear equation with singularity given by \begin{eqnarray*} \begin{split} -\Delta_pu+(-\Delta)_q^s u&=\frac{f(x)}{u^{\delta}}\text { in } \Omega, \\u&>0 \text{ in } \Omega,\\u&=0 \text { in }\mathbb{R}^n \backslash \Omega; \end{split} \end{eqnarray*} where, \begin{equation*} (-\Delta )_q^s u(x):= c_{

Mingqiang Gu, Yuntian Liu, Haiyuan Zhu, Kunihiro Yananose

We propose a novel ferroelectric switchable altermagnetism effect, the reversal of ferroelectric polarization is coupled to the switching of altermagnetic spin splitting. We demonstrate the design principles for the ferroelectric altermagnets and the additional symmetry constraints necessary for switching the altermagnetic spin splitting through flipping the

Martha Lewis, Melanie Mitchell

LLMs have performed well on several reasoning benchmarks, including ones that test analogical reasoning abilities. However, there is debate on the extent to which they are performing general abstract reasoning versus employing non-robust processes, e.g., that overly rely on similarity to pre-training data. Here we investigate the robustness of analogy-making

Junhua Liu, Fanfan Lin, Xinze Li, Kwan Hui Lim

LLM-based autonomous agents have recently shown strong capabilities in solving complex industrial design tasks. However, in domains aiming for carbon neutrality and high-performance renewable energy systems, current AI-assisted design automation methods face critical challenges in explainability, scalability, and practical usability. To address these limitat

Alan Byju, Aman Sudhindra Ladwa, Lorin Sweeney, Alan F. Smeaton

With the expanding use of the short-form video format in advertising, social media, entertainment, education and more, there is a need for such media to both captivate and be remembered. Video memorability indicates to us how likely a video is to be remembered by a viewer who has no emotional or personal connection with its content. This paper presents the r

Alexander Eremko, Larissa Brizhik, Vadim Loktev

For the first time the exact analytical expressions for the three-dimensional bound electron states in the Coulomb field of the chain consisting of positively charged ions, are obtained within the Dirac description, using the new spinor invariant found for this problem. It is demonstrated that within such approach the coupling between electron spin and its o

Simon Boisserée, Evangelos Moulas, Markus Bachmayr

The flow of fluids within porous rocks is an important process with numerous applications in Earth sciences. Modeling the compaction-driven fluid flow requires the solution of coupled nonlinear partial differential equations that account for the fluid flow and the solid deformation within the porous medium. Despite the nonlinear relation of porosity and perm

Janarbek Yuanbek, Yi-Fang Ren, Yusuf Turek

We investigated an orbital angular momentum (OAM) pointer within the framework of von Neumann measurements and discovered its significant impact on optimizing superpositions of Gaussian and Laguerre-Gaussian (LG) states. Calculations of the quadrature squeezing, the second-order cross-correlation function, the Wigner function, and the signal-to-noise ratio (

Jennifer Mead, Kaley Brauer, Greg L. Bryan, Mordecai-Mark Mac Low

We investigate how stellar feedback from the first stars (Population III) distributes metals through the interstellar and intergalactic medium using the star-by-star cosmological hydrodynamics simulation, Aeos. We find that energy injected from the supernovae of the first stars is enough to expel a majority of gas and injected metals beyond the virial radius

Kunhao Liu, Ling Shao, Shijian Lu

The field of novel view synthesis has made significant strides thanks to the development of radiance field methods. However, most radiance field techniques are far better at novel view interpolation than novel view extrapolation where the synthesis novel views are far beyond the observed training views. We design ViewExtrapolator, a novel view synthesis appr

Shivam Saini, Jürgen Peissig

This contribution introduces a dataset of 7th-order Ambisonic Room Impulse Responses (HOA-RIRs), created using the Image Source Method. By employing higher-order Ambisonics, our dataset enables precise spatial audio reproduction, a critical requirement for realistic immersive audio applications. Leveraging the virtual simulation, we present a unique micropho

Pablo Blanco-Mas, Pilar Coloma, Gonzalo Herrera, Patrick Huber

The PANDAX-4T and XENONnT experiments present indications of Coherent Elastic Neutrino Nucleus Scattering (CE$\nu$NS) from ${}^{8}$B solar neutrinos at 2.6$\sigma$ and 2.7$\sigma$, respectively. This constitutes the first observation of the neutrino "floor" or "fog", an irreducible background that future dark matter searches in terrestrial detectors will hav

Zeqing Wang, Qingyang Ma, Wentao Wan, Haojie Li

Recent improvements in visual synthesis have significantly enhanced the depiction of generated human photos, which are pivotal due to their wide applicability and demand. Nonetheless, the existing text-to-image or text-to-video models often generate low-quality human photos that might differ considerably from real-world body structures, referred to as "abnor

Valery Shchesnovich

Quantum models of interacting bosons have a wide range of applications, including the propagation of optical modes in nonlinear media, such as the $k$-photon down-conversion. Many of these models are related to nonlinear deformations of finite group algebras and, in this sense, are exactly solvable. While advanced group-theoretic methods were developed to st

Yusheng Luo, Dimitrios Ntalampekos

We study piecewise quasiconformal covering maps of the unit circle. We provide sufficient conditions so that a conjugacy between two such dynamical systems has a quasiconformal or David extension to the unit disk. Our main result generalizes the main result of arXiv:2010.11256, which deals with piecewise analytic maps. As applications, we provide a classific