April 2024 arXiv papers — page 69

Abhishek Banerjee, Subhajit Das, Surjeet Kour

We construct Fredholm modules over an algebra taking values in generalized Hilbert spaces over a rigid $C^*$-tensor category. Using methods of Connes, we obtain Chern characters taking values in cyclic cohomology. These Chern characters are well behaved with respect to the periodicity operator, and depend only on the homotopy class of the Fredholm module.

J. Arturo Esquivel, Yunyi Shen, Vianey Leos-Barajas, Gwendolyn Eadie

We present a hidden Markov model (HMM) for discovering stellar flares in light curve data of stars. HMMs provide a framework to model time series data that are not stationary; they allow for systems to be in different states at different times and consider the probabilities that describe the switching dynamics between states. In the context of stellar flares

Mathias Peirlinck, Juan A. Hurtado, Manuel K. Rausch, Adrian Buganza Tepole

Soft materials play an integral part in many aspects of modern life including autonomy, sustainability, and human health, and their accurate modeling is critical to understand their unique properties and functions. Today's finite element analysis packages come with a set of pre-programmed material models, which may exhibit restricted validity in capturing th

Rafael Gomes Braga, Muhammad Owais Tahir, Ivanka Iordanova, David St-Onge

Deploying mobile robots in construction sites to collaborate with workers or perform automated tasks such as surveillance and inspections carries the potential to greatly increase productivity, reduce human errors, and save costs. However ensuring human safety is a major concern, and the rough and dynamic construction environments pose multiple challenges fo

Daniel May, Matthew Taylor, Petr Musilek

As distributed energy resources (DERs) grow, the electricity grid faces increased net load variability at the grid edge, impacting operability and reliability. Transactive energy, facilitated through local energy markets, offers a decentralized, indirect demand response solution, with model-free control techniques, such as deep reinforcement learning (DRL),

Adam Rycerz, Katarzyna Rycerz, Piotr Witkowski

Highly-doped graphene samples show the conductance reduced and the shot-noise power enhanced compared to standard ballistic systems in two-dimensional electron gas. These features can be understood within a model assuming incoherent scattering of Dirac electrons between two interfaces separating the sample and the leads. Here we find, by adopting the above-m

Christopher Dobrian, Omar Costa Hamido

Correlations between quantum theory and music theory - specifically between principles of quantum computing and musical harmony - can lead to new understandings and new methodologies for music theorists and composers. The quantum principle of superposition is shown to be closely related to different interpretations of musical meaning. Superposition is implem

Chia-Hsuan Chang, Xiaoyang Wang, Christopher C. Yang

Artificial intelligence supports healthcare professionals with predictive modeling, greatly transforming clinical decision-making. This study addresses the crucial need for fairness and explainability in AI applications within healthcare to ensure equitable outcomes across diverse patient demographics. By focusing on the predictive modeling of sepsis-related

Md Nur K. Alam, S. Clima, B. Kaczer, Ph. Roussel

Existence of quasi-static negative capacitance (QSNC) was proposed from an interpretation of the widely accepted Landau model of ferroelectrics. However, many works showed not to support the QSNC theory, making it controversial. In this letter we show the Landau model when used together with transition-state-theory, can connect various models including first

Carlos A. Alfaro, Juan Pablo Serrano, Ralihe R. Villagrán

The Abelian sandpile model was the first example of a self-organized critical system studied by Bak, Tang and Wiesenfeld. The dynamics of the sandpiles occur when the grains topple over a graph. In this study, we allow the graph to evolve over time and change the topology at each stage. This turns out in the occurrence of phenomena impossible in the classica

Hricha Acharya, Zilin Jiang

In 1976, Cameron, Goethals, Seidel, and Shult classified all the graphs whose smallest eigenvalue is at least $-2$ by relating such graphs to root systems that appear in the classification of semisimple Lie algebras. In this paper, extending their beautiful theorem, we give a complete classification of all connected graphs whose smallest eigenvalue lies in $

Mohammed Al-Dubooni, Cuebong Wong, Kaspar Althoefer

Soft growing vine robots show great potential for navigation and decontamination tasks in the nuclear industry. This paper introduces a novel hybrid continuum-eversion robot designed to address certain challenges in relation to navigating and operating within pipe networks and enclosed remote vessels. The hybrid robot combines the flexibility of a soft evers

Bishwa Karki, Chun-Hua Tsai, Pei-Chi Huang, Xin Zhong

In this work, we introduce a novel deep learning-based approach to text-in-image watermarking, a method that embeds and extracts textual information within images to enhance data security and integrity. Leveraging the capabilities of deep learning, specifically through the use of Transformer-based architectures for text processing and Vision Transformers for

John Orlowski-Scherer, Thomas J. Maccarone, Joe Bright, Tomasz Kaminski

The study of transient and variable events, including novae, active galactic nuclei, and black hole binaries, has historically been a fruitful path for elucidating the evolutionary mechanisms of our universe. The study of such events in the millimeter and submillimeter is, however, still in its infancy. Submillimeter observations probe a variety of materials

Katherine A. Suess, John R. Weaver, Sedona H. Price, Richard Pan

In this paper, we describe the "Medium Bands, Mega Science" JWST Cycle 2 survey (JWST-GO-4111) and demonstrate the power of these data to reveal both the spatially-integrated and spatially-resolved properties of galaxies from the local universe to the era of cosmic dawn. Executed in November 2023, MegaScience obtained ~30 arcmin^2 of deep multiband NIRCam im

Nur Aizaan Anwar, Cosmin Badea

As artificially intelligent systems become more anthropomorphic and pervasive, and their potential impact on humanity more urgent, discussions about the possibility of machine consciousness have significantly intensified, and it is sometimes seen as 'the holy grail'. Many concerns have been voiced about the ramifications of creating an artificial conscious e

Tianqi Kou

Two goals - improving replicability and accountability of Machine Learning research respectively, have accrued much attention from the AI ethics and the Machine Learning community. Despite sharing the measures of improving transparency, the two goals are discussed in different registers - replicability registers with scientific reasoning whereas accountabili

Sreeraj Rajan Warrier, D Sri Harshavardhan Reddy, Sriya Bada, Rohith Achampeta

Underwater images taken from autonomous underwater vehicles (AUV's) often suffer from low light, high turbidity, poor contrast, motion-blur and excessive light scattering and hence require image enhancement techniques for object recognition. Machine learning methods are being increasingly used for object recognition under such adverse conditions. These enhan

Zihao Qi, Ilyoun Na, Gil Refael, Yang Peng

When subjected to quasiperiodic driving protocols, superconducting systems have been found to harbor robust time-quasiperiodic Majorana modes, extending the concept beyond static and Floquet systems. However, the presence of incommensurate driving frequencies results in dense energy spectra, rendering conventional methods of defining topological invariants b

Paolo Carniello, Filipe M. Ferreira, Norbert Hanik

We derive novel approximate closed-form expressions for the nonlinear coupling coefficients appearing in the Manakov equations for multimode fibers for space-division multiplexing in the two regimes of strong and weak coupling. The expressions depend only on few fiber design parameters. In particular, the Manakov coefficients are shown to be simple rational

Vedran Sekara, Andrea Martini, Manuel Garcia-Herranz, Do-Hyung Kim

High-resolution human settlement maps provide detailed delineations of where people live and are vital for scientific and practical purposes, such as rapid disaster response, allocation of humanitarian resources, and international development. The increased availability of high-resolution satellite imagery, combined with powerful techniques from machine lear

Swetha Pemma, Rebecca Janisch, Gerhard Dehm, Tobias Brink

The migration of grain boundaries leads to grain growth in polycrystals and is one mechanism of grain-boundary-mediated plasticity, especially in nanocrystalline metals. This migration is due to the movement of dislocation-like defects, called disconnections, which couple to externally applied shear stresses. While this has been studied in detail in recent y

Harshit Kumar, Sudarshan Sharma, Biswadeep Chakraborty, Saibal Mukhopadhyay

This study introduces RT-HMD, a Hardware-based Malware Detector (HMD) for mobile devices, that refines malware representation in segmented time-series through a Multiple Instance Learning (MIL) approach. We address the mislabeling issue in real-time HMDs, where benign segments in malware time-series incorrectly inherit malware labels, leading to increased fa

Luca Amendola, Marco Marinucci, Miguel Quartin

We propose a methodology to measure the cosmological spatial curvature by employing the deviation from statistical isotropy due to the Alcock-Paczy\'nski effect of large scale galaxy clustering. This approach has a higher degree of model independence than most other proposed methods, being independent of calibration of standard candles, rulers, or clocks, of

Ozan Baris Mulayim, Edson Severnini, Mario Bergés

In single-zone multi-node systems (SZMRSs), temperature controls rely on a single probe near the thermostat, resulting in temperature discrepancies that cause thermal discomfort and energy waste. Augmenting smart thermostats (STs) with per-room sensors has gained acceptance by major ST manufacturers. This paper leverages additional sensory information to emp

Ariel Kelman, Umberto Borla, Itay Gomelski, Jonathan Elyovich

Gauge theories form the basis of our understanding of modern physics - ranging from the description of quarks and gluons to effective models in condensed matter physics. In the non-perturbative regime, gauge theories are conventionally treated discretely as lattice gauge theories. The resulting systems are evaluated with path-integral based Monte Carlo metho

Marco Antonio Barroca, Rodrigo Neumann Barros Ferreira, Mathias Steiner

Direct air capture (DAC) of carbon dioxide is a promising method for mitigating climate change. Solid sorbents, such as metal-organic frameworks, are currently being tested for DAC application. However, their potential for deployment at scale has not been fully realized. The computational discovery of solid sorbents is challenging, given the vast chemical se

Satya Prakash Pradhan, Arash Yavari

In this paper, we formulate a continuum theory of solidification within the context of finite-strain coupled thermoelasticity. We aim to fill a gap in the existing literature, as the existing studies on solidification typically decouple the thermal problem (the classical Stefan's problem) from the elasticity problem, and often limit themselves to linear elas

Lami Chan, Hui Tian, Xianyu Liu, Tibor Török

Full-disk spectroscopic observations of the solar corona are highly desired to forecast solar eruptions and their impact on planets and to uncover the origin of solar wind. In this paper, we introduce a new multi-slit design (5 slits) to obtain extreme ultraviolet (EUV) spectra simultaneously. The selected spectrometer wavelength range (184-197 \r{A}) contai

Dušan Popov

In this paper we examine one of the multiple applications of the theta operator xd/dx in quantum mechanics, namely, in the formalism of generalized hypergeometric coherent states (GHG CSs). These states are the most general coherent states, in the sense that from them, through particularization, all coherent states with physical meaning can be obtained. A se

Aidan J. Bradley, Nicole Abaid

Studies on the social behaviors of bats show that they have the ability to eavesdrop on the signals emitted by conspecifics in their vicinity. They can fuse this ``passive" data with actively collected data from their own signals to get more information about their environment, allowing them to fly and hunt more efficiently and to avoid or cause jamming when

Deniz Cennet Dursun, Seval Taşdemir, Seliz Koç, Srishti İyer

In this study, we investigate the fundamental astrophysical parameters of the old open cluster NGC 188 through two complementary methods: isochron-fitting and spectral energy distribution (SED) analysis. Using photometric, astrometric, and spectroscopic data from the Gaia Data Release 3, we identify 868 most likely member stars with membership probabilities

Pedro De La Torre Luque, Martin Wolfgang Winkler, Tim Linden

Tentative observations of cosmic-ray antihelium by the AMS-02 collaboration have re-energized the quest to use antinuclei to search for physics beyond the standard model. However, our transition to a data-driven era requires more accurate models of the expected astrophysical antinuclei fluxes. We use a state-of-the-art cosmic-ray propagation model, fit to hi

Hakan Doga, M. Emre Sahin, Joao Bettencourt-Silva, Anh Pham

Clinical trials are pivotal in the drug discovery process to determine the safety and efficacy of a drug candidate. The high failure rates of these trials are attributed to deficiencies in clinical model development and protocol design. Improvements in the clinical drug design process could therefore yield significant benefits for all stakeholders involved.

Raúl Carballo-Rubio, Stefano Liberati, Vania Vellucci

Singularity theorems demonstrate the inevitable breakdown of the concept of continuous, classical spacetime under highly general conditions. Quantum gravity is expected to intervene to avoid singularities and models so far hint towards several regularized geometries, in which limited spacetime regions requiring full quantum gravitational description can be s

Doron Kushnir, Uri Keshet, Eli Waxman

Observations of diffuse, non-thermal radio emission spanning several megaparsecs have been documented in over 100 galaxy clusters. This emission, classified as giant radio halos (GHs), mini halos, and radio relics based mainly on their location and morphology, is interpreted as synchrotron radiation and implies the presence of relativistic electrons and magn

P. E. Colazo, F. Stasyszyn, N. Padilla

This Letter explores the potential role of primordial black holes (PBHs) to address cosmological tensions as the presence of more massive than expected galaxies at high redshifts, as indicated by recent James Webb Space Telescope observations. Motivated by inflation models that enhance the power at scales beyond the observable range that produce PBHs with Sc

Raffaele Tito D'Agnolo, Paolo Mangini, Gabriele Rigo, Lian-Tao Wang

A Multiverse can arise from landscapes without de Sitter minima. It can be populated during a period of eternal inflation without trans-Planckian field excursions and without flat potentials. This Multiverse can explain the values of the cosmological constant and of the weak scale. In the process of proving these statements we derive a few simple, but counte

Kareem El-Badry

A $33\,M_\odot$ black hole (BH) was recently discovered in an 11.6-year binary only 590 pc from the Sun. The system, Gaia BH3, contains a $0.8\,M_\odot$ low-metallicity giant ($\rm [M/H]=-2.2$) that is a member of the ED-2 stellar stream. This paper investigates whether the system could have formed via isolated binary evolution. I construct evolutionary mode

Zhuofan Zong, Bingqi Ma, Dazhong Shen, Guanglu Song

As the key component in multimodal large language models (MLLMs), the ability of the visual encoder greatly affects MLLM's understanding on diverse image content. Although some large-scale pretrained vision encoders such as vision encoders in CLIP and DINOv2 have brought promising performance, we found that there is still no single vision encoder that can do

Danial Langeroodi, Jens Hjorth

Theoretical models and observational evidence suggest that high-redshift galaxies grow under the bursty mode of star formation, with large temporal star formation rate (SFR) fluctuations around some mean value. From an observational perspective, it has not been clear at which redshift and stellar population characteristics the transition from bursty to smoot

Tao Chu, Pan Zhang, Xiaoyi Dong, Yuhang Zang

Enabling Large Language Models (LLMs) to interact with 3D environments is challenging. Existing approaches extract point clouds either from ground truth (GT) geometry or 3D scenes reconstructed by auxiliary models. Text-image aligned 2D features from CLIP are then lifted to point clouds, which serve as inputs for LLMs. However, this solution lacks the establ

Soham Gadgil, Mahtab Bigverdi

AI in dermatology is evolving at a rapid pace but the major limitation to training trustworthy classifiers is the scarcity of data with ground-truth concept level labels, which are meta-labels semantically meaningful to humans. Foundation models like CLIP providing zero-shot capabilities can help alleviate this challenge by leveraging vast amounts of image-c

Hao Du, Clemens G. Raab

In symbolic integration, the Risch--Norman algorithm aims to find closed forms of elementary integrals over differential fields by an ansatz for the integral, which usually is based on heuristic degree bounds. Norman presented an approach that avoids degree bounds and only relies on the completion of reduction systems. We give a formalization of his approach

Srivani Javvaji, Fengping Li, Jeil Jung

Hexagonal boron nitride ($\it h$-BN) exhibits dominant $\pi$-bands near the Fermi level, similar to graphene. However, unlike graphene, where tight-binding (TB) models accurately reproduce band edges near the $K$ and $K^{\prime}$ points in the Brillouin zone, a wider bandgap in $\it h$-BN necessitates capturing the band edges at both the $K$ and $M$ points f

Xi Wang, Nicolas Dufour, Nefeli Andreou, Marie-Paule Cani

Classifier-Free Guidance (CFG) enhances the quality and condition adherence of text-to-image diffusion models. It operates by combining the conditional and unconditional predictions using a fixed weight. However, recent works vary the weights throughout the diffusion process, reporting superior results but without providing any rationale or analysis. By cond

Tiancheng Gu, Kaicheng Yang, Dongnan Liu, Weidong Cai

Medical visual question answering (Med-VQA) aims to automate the prediction of correct answers for medical images and questions, thereby assisting physicians in reducing repetitive tasks and alleviating their workload. Existing approaches primarily focus on pre-training models using additional and comprehensive datasets, followed by fine-tuning to enhance pe

Jessica Dai, Eve Fleisig

Recent work on the limitations of using reinforcement learning from human feedback (RLHF) to incorporate human preferences into model behavior often raises social choice theory as a reference point. Social choice theory's analysis of settings such as voting mechanisms provides technical infrastructure that can inform how to aggregate human preferences amid d

Mark P. Hertzberg, Abraham Loeb

We analyze consequences of trying to replace dark matter and dark energy with models of stochastic spacetime. In particular, we analyze the model put forth by Ref. [1], in which it is claimed that ``post-quantum classical gravity" (PQCG), a stochastic theory of gravity, leads to modified Newtonian dynamics (MOND) behavior on galactic scales that reproduces g

Daniel Marín Pina, Sara Rastello, Mark Gieles, Kyle Kremer

Context. The star-black hole (S-BH) binary known as Gaia BH3, discovered by the Gaia Collaboration is chemically and kinematically associated with the metal-poor ED-2 stream in the Milky Way halo. Aims. We explore the possibility that Gaia BH3 was assembled dynamically in the progenitor globular cluster (GC) of the ED-2 stream. Methods. We used a public suit

Tobias Schröder, Robert Brandenberger

Embedded walls are domain wall solutions which are unstable in the vacuum but stabilized in a plasma of the early Universe. We show how embedded walls in which the electroweak symmetry is restored can lead to an efficient scenario of electroweak baryogenesis. We construct an extension of the Standard Model of particle physics in which embedded walls exist an

Yifei Li, Jeongwon Park, Guha Manogharan, Feng Ju

Recent technological innovations in the areas of additive manufacturing and collaborative robotics have paved the way toward realizing the concept of on-demand, personalized production on the shop floor. Additive manufacturing process can provide the capability of printing highly customized parts based on various customer requirements. Autonomous, mobile sys

Biyang Guo, He Wang, Wenyilin Xiao, Hong Chen

In the burgeoning field of Large Language Models (LLMs) like ChatGPT and LLaMA, Prompt Engineering (PE) is renowned for boosting zero-shot or in-context learning (ICL) through prompt modifications. Yet, the realm of the sample design for downstream fine-tuning, crucial for task-specific LLM adaptation, is largely unexplored. This paper introduces Sample Desi

Dori Blakely, Doug Johnstone, Gabriele Cugno, Anand Sivaramakrishnan

We observed the planet-hosting system PDS 70 with the James Webb Interferometer, JWST's Aperture Masking Interferometric (AMI) mode within NIRISS. Observing with the F480M filter centered at 4.8 $\mu$m, we simultaneously fit geometrical models to the outer disk and the two known planetary companions. We re-detect the protoplanets PDS 70 b and c at an SNR of

Zhecheng Hu, Wei Zhu, Andrew Gould, Andrzej Udalski

We present the analysis of the microlensing event OGLE-2015-BLG-0845, which was affected by both the microlensing parallax and xallarap effects. The former was detected via the simultaneous observations from the ground and Spitzer, and the latter was caused by the orbital motion of the source star in a relatively close binary. The combination of these two ef

Björn J. R. Davidsson

Cliff collapses on Comet 67P/Churyumov-Gerasimenko expose relatively pristine nucleus matter and offer rare opportunities to characterise ice-rich comet material. Here, Microwave Instrument for \emph{Rosetta} Orbiter (MIRO) observations of two collapsed or crumbling cliffs in the Imhotep and Hathor regions have been assembled. The empirical diurnal antenna t

Albert Much

We introduce a non-commutative product for curved spacetimes, that can be regarded as a generalization of the Rieffel (or Moyal-Weyl) product. This product employs the exponential map and a Poisson tensor, and the deformed product maintains associativity under the condition that the Poisson tensor $\Theta$ satisfies $\Theta^{\mu\nu}\nabla_{\nu}\Theta^{\rho\s

Stephen Choi, William Gazeley

This paper presents the LLM-ADE framework, a novel methodology for continued pre-training of large language models (LLMs) that addresses the challenges of catastrophic forgetting and double descent. LLM-ADE employs dynamic architectural adjustments, including selective block freezing and expansion, tailored to specific datasets. This strategy enhances model

Robin Schwager, Michael Grimm, Xin Liu, Lukas Ewecker

During the use of Advanced Driver Assistance Systems (ADAS), drivers can intervene in the active function and take back control due to various reasons. However, the specific reasons for driver-initiated takeovers in naturalistic driving are still not well understood. In order to get more information on the reasons behind these takeovers, a test group study w

Tianyuan Zhang, Hong-Xing Yu, Rundi Wu, Brandon Y. Feng

Realistic object interactions are crucial for creating immersive virtual experiences, yet synthesizing realistic 3D object dynamics in response to novel interactions remains a significant challenge. Unlike unconditional or text-conditioned dynamics generation, action-conditioned dynamics requires perceiving the physical material properties of objects and gro

Mahnaz Asghari, Alireza Allahyari, David F. Mota

We study the Barrow cosmological model, which proposes that quantum gravity effects create a complex, fractal structure for the universe's apparent horizon. We leverage the thermodynamics - gravity conjecture. By applying the Clausius relation to the apparent horizon of the Friedmann - Lema\^itre - Robertson - Walker universe within this framework, we derive

Ahan Shabanov, Shrisudhan Govindarajan, Cody Reading, Lily Goli

Largely due to their implicit nature, neural fields lack a direct mechanism for filtering, as Fourier analysis from discrete signal processing is not directly applicable to these representations. Effective filtering of neural fields is critical to enable level-of-detail processing in downstream applications, and support operations that involve sampling the f

Tobias Kirschbaum, Thorsten Schumm, Adriana Pálffy

The $^{229}$Th nucleus has a unique transition at only 8 eV which could be used for a novel nuclear clock. We investigate theoretically the prospects of driving this transition with vortex light beams carrying orbital angular momentum. Numerical results are presented for two experimental configurations which are promising for the design of the planned nuclea

Sreenivas Raguraman, Maitreyee Sharma Priyadarshini, Tram Nguyen, Ryan McGovern

Magnesium alloys are emerging as promising alternatives to traditional orthopedic implant materials thanks to their biodegradability, biocompatibility, and impressive mechanical characteristics. However, their rapid in-vivo degradation presents challenges, notably in upholding mechanical integrity over time. This study investigates the impact of high-tempera

Mohammad Mahdi Ahmadi, Erfan Yazdandoost Hamedani

In this paper, we explore a broad class of constrained saddle point problems with a bilevel structure, wherein the upper-level objective function is nonconvex-concave and smooth over compact and convex constraint sets, subject to a strongly convex lower-level objective function. This class of problems finds wide applicability in machine learning, encompassin

Gregory Yauney, David Mimno

Evaluating the in-context learning classification performance of language models poses challenges due to small dataset sizes, extensive prompt-selection using the validation set, and intentionally difficult tasks that lead to near-random performance. The standard random baseline--the expected accuracy of guessing labels uniformly at random--is stable when th

Philippe Angot

We give a simple Tauberian proof of the Prime Number Theorem using only elementary real analysis. Hence, the analytic continuation of Riemann's zeta function $\zeta$ and its non-vanishing value on the whole line $\{z\in {\mathbb C};\,{\mathrm{Re}\,} z=1\}$ are no more required. This is achieved by showing a strong extension for Laplace transforms on the real

Ronglei Ji, A. Murat Tekalp

Despite the fact real-world video deinterlacing and demosaicing are well-suited to supervised learning from synthetically degraded data because the degradation models are known and fixed, learned video deinterlacing and demosaicing have received much less attention compared to denoising and super-resolution tasks. We propose a new multi-picture architecture

Van Tuong Pham, Naveen Sisodia, Ilaria Di Manici, Joseba Urrestarazu-Larrañaga

Magnetic skyrmions are topological magnetic textures that hold great promise as nanoscale bits of information in memory and logic devices. Although room-temperature ferromagnetic skyrmions and their current-induced manipulation have been demonstrated, their velocity has been limited to about 100 meters per second. In addition, their dynamics are perturbed by

Yuchi Liu, Lei Wang, Yuli Zou, James Zou

Model calibration aims to align confidence with prediction correctness. The Cross-Entropy (CE) loss is widely used for calibrator training, which enforces the model to increase confidence on the ground truth class. However, we find the CE loss has intrinsic limitations. For example, for a narrow misclassification (e.g., a test sample is wrongly classified an

Pan Chenxi, Song Sheng, Chen Chungang, Li Xingliang

A high-fidelity finite volume scheme based on the BVD (boundary variation diminishing) concept is proposed in this study to solve the ideal magnetohydrodynamics (MHD) equations. A hybrid spatial reconstruction profile, consisting of a quadratic polynomial and a steepness-adjustable hyperbolic tangent function, is adopted to reproduce the accurate solutions o

Antonio Blanca, Reza Gheissari, Xusheng Zhang

A common obstruction to efficient sampling from high-dimensional distributions with Markov chains is the multimodality of the target distribution because they may get trapped far from stationarity. Still, one hopes that this is only a barrier to the mixing of Markov chains from worst-case initializations and can be overcome by choosing high-entropy initializ

Chuofan Ma, Yi Jiang, Jiannan Wu, Zehuan Yuan

We introduce Groma, a Multimodal Large Language Model (MLLM) with grounded and fine-grained visual perception ability. Beyond holistic image understanding, Groma is adept at region-level tasks such as region captioning and visual grounding. Such capabilities are built upon a localized visual tokenization mechanism, where an image input is decomposed into reg

Igor Petkov, Ruslan Salimov, Mariia Stefanchuk

We investigate the asymptotic behavior at infinity of regular homeomorphic solutions of the nonlinear Beltrami equation with the Jacobian on the right-hand side. The sharpness of the above bounds is illustrated by several examples.

Juris Kalvāns, Aija Kalniņa, Kristaps Veitners

Context. Interstellar surface chemistry is a complex process that occurs in icy layers accumulated onto grains of different sizes. Efficiency of surface processes often depends on the immediate environment of adsorbed molecules. Aims. We investigate how gas-grain chemistry changes when surface molecule desorption is made explicitly dependent to the molecular

Laura Pecorari, Sven Jandura, Gavin K. Brennen, Guido Pupillo

High-rate quantum error correcting (QEC) codes with moderate overheads in qubit number and control complexity are highly desirable for achieving fault-tolerant quantum computing. Recently, quantum error correction has experienced significant progress both in code development and experimental realizations, with neutral atom qubit architecture rapidly establis

Yiheng Lin, James A. Preiss, Fengze Xie, Emile Anand

We study online policy optimization in nonlinear time-varying dynamical systems where the true dynamical models are unknown to the controller. This problem is challenging because, unlike in linear systems, the controller cannot obtain globally accurate estimations of the ground-truth dynamics using local exploration. We propose a meta-framework that combines

Mohammed Yousif, Jonat John Mathew, Huzaifa Pallan, Agamjeet Singh Padda

Generalization in audio deepfake detection presents a significant challenge, with models trained on specific datasets often struggling to detect deepfakes generated under varying conditions and unknown algorithms. While collectively training a model using diverse datasets can enhance its generalization ability, it comes with high computational costs. To addr

Bhabani Prasad Sahu, Poonam Sharma, Santosh Kumar Yadav, Alok Shukla

(111)NiO epitaxial films are grown on c-sapphire substrates at various growth temperatures ranging from room-temperature to 600C using pulsed laser deposition (PLD) technique. Two series of samples, where different laser fluences are used to ablate the target, are studied here. Films grown with higher laser fluence, are found to be embedded with Ni-clusters

Uladzislau Makartsou, Mateusz Gołębiewski, Urszula Guzowska, Alexander Stognij

Extending the scope of the self-imaging phenomenon, traditionally associated with linear optics, to the domain of magnonics, this study presents the experimental demonstration and numerical analysis of spin-wave (SW) self-imaging in an in-plane magnetized yttrium iron garnet film. We explore this phenomenon using a setup in which a plane SW passes through a

Candelario Castaneda, Ross Staffeldt

The join construction produces a third Sasaki manifold from two others, and we investigate the algebraic topology of the joins of circle bundles over surfaces of positive genus with weighted three-spheres. Topologically, such a join has the structure of a lens space bundle over a surface. We calculate invariants determined by the fundamental group, the homol

Yu Lei, Zixuan Wang, Yiqing Feng, Junru Zhang

Recent industrial credit scoring models remain heavily reliant on manually tuned statistical learning methods. Despite their potential, deep learning architectures have struggled to consistently outperform traditional statistical models in industrial credit scoring, largely due to the complexity of heterogeneous financial data and the challenge of modeling e

Wang Jia, Hang Xu

We study the adaptability of deep reinforcement learning (DRL)-based active flow control (AFC) technology for bluff body flows with complex geometries. It is extended from a cylinder with an aspect ratio $Ar = 1$ to a flat elliptical cylinder with $Ar=2$, slender elliptical cylinders with $Ar$ less than 1, and a flat plate with $Ar=0$. We utilize the Proxima

Paulo Henrique dos Santos, Valéria de Carvalho Santos, Eduardo José da Silva Luz

In the steel production domain, recycling ferrous scrap is essential for environmental and economic sustainability, as it reduces both energy consumption and greenhouse gas emissions. However, the classification of scrap materials poses a significant challenge, requiring advancements in automation technology. Additionally, building trust among human operator

Sangita Mondal, Biman Bagchi

The lifetime of a hydrogen bond between water and dimethyl sulfoxide (DMSO) is found to be considerably longer than that between two water molecules in the neat water. This is counter-intuitive because the charge on the oxygen in DMSO is considerably less than that in water. Additionally, the strength of the water-dimethyl sulfoxide (w-D) hydrogen bond is fo

Pouria Rouzrokh, Bardia Khosravi, Shahriar Faghani, Kellen L. Mulford

Transforming two-dimensional (2D) images into three-dimensional (3D) volumes is a well-known yet challenging problem for the computer vision community. In the medical domain, a few previous studies attempted to convert two or more input radiographs into computed tomography (CT) volumes. Following their effort, we introduce a diffusion model-based technology

Lisheng Wu, Ke Chen

Exploration efficiency poses a significant challenge in goal-conditioned reinforcement learning (GCRL) tasks, particularly those with long horizons and sparse rewards. A primary limitation to exploration efficiency is the agent's inability to leverage environmental structural patterns. In this study, we introduce a novel framework, GEASD, designed to capture

Shushma Rani, Niranjan Nehra, Rohit Garg

We investigate the commuting automorphisms of nilpotent Lie algebras $L$ with coclass $\leq 3$. Our examination exposes the conditions under which the set of commuting automorphisms of $L$ forms a subgroup within its automorphism group.

Abdulnasser Hatemi-J

Connectedness measures the degree at which a time-series variable spills over volatility to other variables compared to the rate that it is receiving. The idea is based on the percentage of variance decomposition from one variable to the others, which is estimated by making use of a VAR model. Diebold and Yilmaz (2012, 2014) suggested estimating this simple

Stefan Evans, Ralf Schützhold

We study the interaction between axions and nuclei by combining the Peccei-Quinn mechanism with results from quantum chromo-dynamics (QCD) which imply that the QCD condensates are reduced within nuclear matter. Thus, the effective axion mass is also reduced, yielding a finite axion-nucleon scattering cross section. Even in the absence of real axions, this in

Herman B. Amundsen, Marios Xanthidis, Martin Føre, Sveinung J. Ohrem

Aquaculture is a big marine industry and contributes to securing global food demands. Underwater vehicles such as remotely operated vehicles (ROVs) are commonly used for inspection, maintenance, and intervention (IMR) tasks in fish farms. However, underwater vehicle operations in aquaculture face several unique and demanding challenges, such as navigation in

Clemencia Siro, Mohammad Aliannejadi, Maarten de Rijke

In ad-hoc retrieval, evaluation relies heavily on user actions, including implicit feedback. In a conversational setting such signals are usually unavailable due to the nature of the interactions, and, instead, the evaluation often relies on crowdsourced evaluation labels. The role of user feedback in annotators' assessment of turns in a conversational perce

Reko P. S. Penttilä, Kukka-Emilia Huhtinen, Päivi Törmä

Flat bands may offer a route to high critical temperatures of superconductivity. It has been predicted that the quantum geometry of the bands as well as the ratio of the number of flat bands to the number of orbitals determine flat band superconductivity. However, such results have assumed at least one of the following: an isolated flat band, zero temperatur

Margarida S. Cunha, Yuri C. Damasceno, Juliana Amaral, Anselmo Falorca

Sharp structural variations induce specific signatures on stellar pulsations that can be studied to infer localised information on the stratification of the star. This information is key to improve our understanding of the physical processes that lead to the structural variations and how to model them. Here we revisit and extend the analysis of the signature

Mirco Beltrame, Mauro Conti, Pierpaolo Guglielmin, Francesco Marchiori

The widespread exchange of digital documents in various domains has resulted in abundant private information being shared. This proliferation necessitates redaction techniques to protect sensitive content and user privacy. While numerous redaction methods exist, their effectiveness varies, with some proving more robust than others. As such, the literature pr

István Kovács

Here, the entanglement entropy is calculated at the quantum multicritical point of the random transverse-field Ising model (RTIM). We use an efficient implementation of the strong disorder renormalization group method in two and three dimensions for two types of disorder. For cubic subsystems we find a universal logarithmic corner contribution to the area la

Christos A. Athanasiadis, David G. Wagner

The concept of a fully interlacing matrix of formal power series with real coefficients is introduced. This concept extends and strengthens that of an interlacing sequence of real-rooted polynomials with nonnegative coefficients, in the special case of row and column matrices. The fully interlacing property is shown to be preserved under matrix products, fli

Leslie Gu, Jason Ken Adhinarta, Mikhail Bessmeltsev, Jiancheng Yang

Accurately segmenting 3D curvilinear structures in medical imaging remains challenging due to their complex geometry and the scarcity of diverse, large-scale datasets for algorithm development and evaluation. In this paper, we use dendritic spine segmentation as a case study and address these challenges by introducing a novel Frenet--Serret Frame-based Decom

Christelle Zozoungbo

This paper examines how gender, birth order, and innate ability shape within-household disparities in children's educational attainment in developing countries. Using data from Benin, I find that in households with non-educated parents, gender and birth order drive over two-thirds of the average educational attainment disparities among adult children, while

Renato Spigler

This abstract provides up-to-date insights into fusion (thermonuclear) research, detailing ongoing projects and planned devices. The document also explores alternative sources of energy, offering a comprehensive overview of the current landscape. Additionally, notable comments and observations are provided to illuminate key aspects of the discussed topics. S