December 2024 arXiv papers — page 56

Marco Battestini, Marta Missiaggia, Sara Bolzoni, Francesco G. Cordoni

Ultra-high dose-rate (UHDR) radiotherapy, characterized by an extremely high radiation delivery rate, represents one of the most recent and promising frontier in radiotherapy. UHDR radiotherapy, addressed in the field as FLASH radiotherapy, is a disruptive treatment modality with several benefits, including significantly shorter treatment times, unchanged ef

Daniel Killough, Tiger F. Ji, Kexin Zhang, Yaxin Hu

As immersive technologies enable unique, multimodal interaction methods, developers must also use tailored methods to support user accessibility, distinct from traditional software practices. We interviewed 25 industry extended reality (XR) developers, including freelancers, startups, midsize, and big tech companies about their motivations, techniques, barri

Lucas Godoy Garraza, Ilene Speizer, Leontine Alkema

There is interest in learning about the causal effects of modern contraceptive use on empowerment outcomes. Data on this question often come from family planning (FP) programs that increase access to FP and facilitate contraceptive use among some women, rather than directly assigning use. Women whose contraceptive behavior changes because of these programs (

Pranav Gupta

We review the recent literature (January 2022- October 2024) in South Asian languages on text-based language processing, multimodal models, and speech processing, and provide a spotlight analysis focused on 21 low-resource South Asian languages, namely Saraiki, Assamese, Balochi, Bhojpuri, Bodo, Burmese, Chhattisgarhi, Dhivehi, Gujarati, Kannada, Kashmiri, K

Anand Mathew, Yashashree Kulkarni

Interaction of electric fields with biological cells is indispensable for many physiological processes. Thermal electrical noise in the cellular environment has long been considered as the minimum threshold for detection of electrical signals by cells. However, there is compelling experimental evidence that the minimum electric field sensed by certain cells

Junyan Liu, Lillian J. Ratliff

We study the repeated principal-agent bandit game, where the principal indirectly interacts with the unknown environment by proposing incentives for the agent to play arms. Most existing work assumes the agent has full knowledge of the reward means and always behaves greedily, but in many online marketplaces, the agent needs to learn the unknown environment

Erik B. Monson, George G. Pavlov, Gordon P. Garmire

Using a recent Chandra ACIS observation of the eclipsing cataclysmic variable (CV) V1460 Her (2MASS J16211735+4412541) with a fast-rotating ($P_{\rm spin} = 38.9$~s) white dwarf, we estimated a flux $F_{0.5-7 {\rm keV}}^{\rm abs} = (1.9\pm 0.5)\times 10^{-14}$ erg cm$^{-2}$ s$^{-1}$, a factor of $\sim7$ lower than found from previous Swift XRT observations $

Bikash Ghosh, Maria Labendik, Vladimir Umansky, Moty Heiblum

Aharonov-Bohm (AB) interference of fractional quasiparticles in the quantum Hall Effect generally reveals their elementary charge ($e^*$)[1-15]. Recently, our interferometry experiments with several particle states reported flux periods of ${\Delta}{\Phi}=(e/e^*){\Phi}_0$ the flux quantum) at moderate temperatures[16]. Here, we report interference measuremen

R M Potvliege

Newly calculated bounds on the strength of the coupling of an electron to a proton or a neutron by a fifth force are presented. These results are derived from the high precision spectroscopic data currently available for hydrogen, deuterium, helium-3 and helium-4. They do not depend on specific assumptions on how the interaction would couple to a deuteron co

Alexander Kozachinskiy, Alexander Shen, Tomasz Steifer

In perpetual voting, multiple decisions are made at different moments in time. Taking the history of previous decisions into account allows us to satisfy properties such as proportionality over periods of time. In this paper, we consider the following question: is there a perpetual approval voting method that guarantees that no voter is dissatisfied too many

Maryam Contractor, Otto Reed

Given a pair of filling curves $\alpha, \beta$ on a surface of genus $g$ with $n$ punctures, we explicitly compute the mapping classes realizing the minimal dilatation over all the pseudo-Anosov maps given by the Thurston construction on $\alpha,\beta$. We do so by solving for the minimal spectral radius in a congruence subgroup of $\text{PSL}_2(\mathbb{Z})$

Hector Mirallas

The use of Time Projection Chambers (TPCs) in particle physics experiments has been growing since their invention, reaching sizes equivalent to buildings (ALICE or ATLAS at CERN). However, their application in another class of experiments, commonly referred to as rare event experiments, has been more recent. This work focuses on two such experiments aimed at

Yu Jiang, Jing Xu, Zixin Yan, Amin Pishehvar

Cavity magnomechanics is one important hybrid magnonic platform that focuses on the coherent interaction between magnons and phonons. The resulting magnon polarons inherit the intrinsic properties of both magnons and phonons, combining their individual advantages and enabling new physics and functionalities. But in previous demonstrations the magnon-phonon c

Meng-Chieh Lee, Qi Zhu, Costas Mavromatis, Zhen Han

Given a semi-structured knowledge base (SKB), where text documents are interconnected by relations, how can we effectively retrieve relevant information to answer user questions? Retrieval-Augmented Generation (RAG) retrieves documents to assist large language models (LLMs) in question answering; while Graph RAG (GRAG) uses structured knowledge bases as its

Nima Ghafari Cherati, Anton Pershin, Ádám Gali

The negatively charged nitrogen-vacancy (NV) center is one of the most significant and widely studied defects in diamond that plays a prominent role in quantum technologies. The precise engineering of the location and concentration of NV centers is of great importance in quantum technology applications. To this end, irradiation techniques such as nitrogen-mo

Nisha Yadav, Jessica Boulos, Keisha Cook, Angela Alexander-Bryant

Gene silencing via small interfering RNA (siRNA) represents a transformative tool in cancer therapy, offering specificity and reduced off-target effects compared to conventional treatments. A crucial step in siRNA-based therapies is endosomal escape, the release of siRNA from endosomes into the cytoplasm. Quantifying endosomal escape is challenging due to th

Francesca Arceci, Daniela Morale, Stefania Ugolini

We investigate the qualitative behaviour of the solutions of a stochastic boundary value problem on the half-line for a nonlinear system of parabolic reaction-diffusion equations, from a numerical point of view. The model describes the chemical aggression of calcium carbonate stones under the attack of sulphur dioxide. The dynamical boundary condition is giv

Robert J. van der Drift, Paul A. O'Gorman

Precipitation extremes produced by convection have been found to intensify with near-surface temperatures at a Clausius-Clapeyron rate of $6$ to $7\%$ K$^{-1}$ in simulations of radiative-convective equilibrium (RCE). However, these idealized simulations are typically performed over an ocean surface with a high near-surface relative humidity (RH) that stays

Dionysios Anninos, Raúl Arias, Damián A. Galante, Chawakorn Maneerat

We consider four-dimensional general relativity with a negative cosmological constant in the presence of a finite size boundary, $\Gamma$, for both Euclidean and Lorentzian signature. As our boundary condition, we consider the `conformal' boundary condition that fixes the conformal class of the induced metric at $\Gamma$ and the trace of the extrinsic curvat

Luca Maggio, Danilo Triggiani, Paolo Facchi, Vincenzo Tamma

We present a sensing scheme for estimating the frequency difference of two non-entangled photons. The technique consists of time-resolving sampling measurements at the output of a beam splitter. With this protocol, the frequency shift between two photons can be estimated with the ultimate precision achievable in nature, overcoming the limits in precision and

Daniel C. Hackett, Joshua Isaacson, Shirley Weishi Li, Karla Tame-Narvaez

Neutrino-nucleus scattering cross sections are critical theoretical inputs for long-baseline neutrino oscillation experiments. However, robust modeling of these cross sections remains challenging. For a simple but physically motivated toy model of the DUNE experiment, we demonstrate that an accurate neural-network model of the cross section -- leveraging onl

Jinwen Tang, Qiming Guo, Yunxin Zhao, Yi Shang

Recent advancements in NLP have spurred significant interest in analyzing social media text data for identifying linguistic features indicative of mental health issues. However, the domain of Expressive Narrative Stories (ENS)-deeply personal and emotionally charged narratives that offer rich psychological insights-remains underexplored. This study bridges t

Paulo R. B. Gomes, Amarilton L. Magalhães, André L. F. de Almeida

Reconfigurable intelligent surface (RIS) is a recent low-cost and energy-efficient technology with potential applicability for future wireless communications. Performance gains achieved by employing RIS directly depend on accurate channel estimation (CE). It is common in the literature to assume channel reciprocity due to the facilities provided by this assu

Fabian Heitsch, Roark Habegger

We extend the co-scaling formalism of Habegger & Heitsch (2021) implemented in Athena++ to magneto-hydrodynamics. The formalism relies on flow symmetries in astrophysical problems involving expansion, contraction, and center-of-mass motion. The formalism is fully consistent with the upwind constrained transport method implemented in Athena++ and is accurate

Jaelsson S. Lima, Rodrigo von Marttens, Luciano Casarini

Models proposing a non-gravitational interaction between dark energy (DE) and dark matter (CDM) have been extensively studied as alternatives to the standard cosmological model. A common approach to describing the DE-CDM coupling assumes it to be linearly proportional to the dark energy density. In this work, we consider the model with interaction term $Q=3H

Swati Chandna, Benjamin Bagozzi, Snigdhansu Chatterjee

Many real world networks exhibit edge heterogeneity with different pairs of nodes interacting with different intensities. Further, nodes with similar attributes tend to interact more with each other. Thus, in the presence of observed node attributes (covariates), it is of interest to understand the extent to which these covariates explain interactions betwee

Ian MacLaren, Aurys Silinga, Juri Barthel, Josee Kleibeuker

Atomic resolution imaging is key to understanding thin film growth and how a particular set of conditions influences properties. Whilst such imaging in the scanning transmission electron microscope (STEM) has had transformative impact in nanoscience, it forms projection images and provides no direct information about displacements perpendicular to the image

CMS Collaboration

The most precise measurement to date of the W boson hadronic decay branching fraction ratio $R_\mathrm{c}^\mathrm{W}$ = $\mathcal{B}$(W $\to$ cq) / $\mathcal{B}$(W $\to$ $\mathrm{q\bar{q}'}$) is presented. The measurement is based on a sample of proton-proton collision data from the CERN LHC collected by the CMS experiment at a center-of-mass energy of 13 Te

Alberto Cobos Rabano

Given $X$ a smooth projective toric variety, we construct a morphism from a closed substack of the moduli space of stable maps to $X$ to the moduli space of quasimaps to $X$. If $X$ is Fano, we show that this morphism is surjective. The construction relies on the notion of degree of a quasimap at a base-point, which we define. We show that a quasimap is dete

Davide Alimonti, Francesca Baletto

We investigated the complete thermodynamic cycle of aluminium nanoparticles through classical molecular dynamics simulations, spanning a wide size range from 200 atoms to 11000 atoms. The aluminium-aluminium interactions are modelled using a newly developed Bayesian Force Field (BFF) from the FLARE suite, a cutting-edge tool in our field. We discuss the data

Robin Blume-Kohout, Kenneth Rudinger, Timothy Proctor

Quantum process tomography (QPT), used to estimate the linear map that best describes a quantum operation, is usually performed using a priori assumptions about state preparation and measurement (SPAM), which yield a biased and inconsistent estimator. This estimate can be made more accurate and less biased by incorporating SPAM-calibration data. Unobservable

Georgios Doulis, Sebastiano Bernuzzi, Wolfgang Tichy

The construction of high-resolution shock-capturing schemes is vital in producing highly accurate gravitational waveforms from neutron star binaries. The entropy based flux limiting (EFL) scheme is able to perform fast converging binary neutron star merger simulations reaching up to fourth-order convergence in the gravitational waveform phase. In these resul

P. S. Howe, U. Lindström

An exotic linearised theory of superconformal gravity in D = 6, (4,0) superspace, proposed by C. Hull, is discussed in loop space with focus on its bosonic sector. Pursuing an analogy to the loop space version of the system of a two form B and its field strength H, we show that the exotic linearised gravitational potential C and curvature G can be reinterpre

Matteo Marengo, Jarod Lévy, Jean-Emmanuel Bibault

LLMs have transformed the execution of numerous tasks, including those in the medical domain. Among these, summarizing patient-reported outcomes (PROs) into concise natural language reports is of particular interest to clinicians, as it enables them to focus on critical patient concerns and spend more time in meaningful discussions. While existing work with

Brandt A. L. Gaches, Michael Y. Grudić

Constraining the physical and chemical evolution of molecular clouds is essential to our understanding of star formation. These investigations often necessitate knowledge of some local representative number density of the gas along the line of sight. However, constraining the number density is a difficult endeavor. Robust constraints of the number density of

Mengxing Ye, Yuxuan Wang

We develop an effective field theory for a multi-orbital fermionic system using the method of coadjoint orbits for higher-dimensional bosonization. The dynamical bosonic fields are single-particle distribution functions defined on the phase space. We show that when projecting to a single band, Berry curvature effects naturally emerge. In particular, we consi

Eirini C. Telali, T. Rick Perche, Eduardo Martín-Martínez

We analyse the interaction between two quantum systems in spacetime and we compare two possible models to describe it: 1) a fully quantum field theoretical (QFT) description of the coupling of two quantum systems mediated by a quantum field and 2) a quantum-controlled model (qc-model), which is an effectively relativistic direct-coupling in which the interac

Wouter Buijsman, Pieter W. Claeys

Supersymmetry provides a natural playground for the construction of dynamically constrained lattice fermion models. We here illustrate how supersymmetry can be used to construct a fermionic equivalent of the PXP model with an adjustable chemical potential. This model is closely related to the $\mathcal{N} = 2$ supersymmetric $M_1$ model, inheriting its integ

Brandon Kriesten, T. J. Hobbs

The growth in beyond standard model (BSM) models and parametrizations has placed strong emphasis on systematically intercomparing within the range of possible models with controlled uncertainties. In this setting, the language of uncertainty quantification (UQ) provides quantitative metrics of assessing overlaps and discrepancies between models. We leverage

Benjamín Grinstein, Xiaochuan Lu, Carlos Miró, Pablo Quílez

We derive a saturation theorem for general Effective Field Theories (EFTs) constructed using spurion analysis. Let $S$ be a set of spurion fields introduced to organize the breaking of a global symmetry $G_f$, and $H_S$ be the subgroup of $G_f$ that remains unbroken under a generic vacuum expectation value $\langle S\rangle$; we show that the EFT Lagrangian

Sopheak Sorn, Jörg Schmalian, Markus Garst

Magnetic skyrmions are spatially localized whirls of spin moments in two dimension, featuring a nontrivial topological charge and a well-defined topological charge density. We demonstrate that the quantum dynamics of magnetic skyrmions is governed by a dipole conservation law associated with the topological charge, akin to that in fracton theories of excitat

Sinéad M. Griffin, Guy Daniel Hadas, Yonit Hochberg, Katherine Inzani

In a seminal paper now a decade old, it was shown that dark matter detectors geared at probing interactions with nucleons could also be used to probe dark matter interactions with electrons. In this work, we show that new detector concepts designed to probe dark matter-electron interactions at low masses can similarly be used to probe new parameter space for

Simon Holz, Martin Hoferichter, Bai-Long Hoid, Bastian Kubis

The pseudoscalar-pole contributions to hadronic light-by-light scattering are determined by the respective transition form factors (TFFs) into two virtual photons. These TFFs constitute complicated functions of the photon virtualities that, in turn, can be reconstructed in a dispersive approach from their discontinuities. In this work, we present such an ana

Jens F. Mahlmann, Andrei M. Beloborodov

We investigate energy release in the interacting magnetospheres of binary neutron stars (BNSs) with global 3D force-free electrodynamics simulations. The system dynamics depend on the inclinations $\chi_1$ and $\chi_2$ of the stars' magnetic dipole moments relative to their orbital angular momentum. The simplest aligned configuration ($\chi_1=\chi_2=0^\circ$

Laura Baudis, Alexander Bismark, Noah Brugger, Chiara Capelli

We present the first results from the Quantum Resolution-Optimized Cryogenic Observatory for Dark matter Incident at Low Energy (QROCODILE). The QROCODILE experiment uses a microwire-based superconducting nanowire single-photon detector (SNSPD) as a target and sensor for dark matter scattering and absorption, and is sensitive to energy deposits as low as 0.1

Mor Rozner

The efficiency of planet formation is a fundamental question in planetary science, gaining increasing significance as observational data from planet-forming disks accumulates. Here we derive from first principles a correlation between the planet formation rate (PFR) and the gas surface density, i.e. $\rm{PFR}\propto \Sigma_g^n$. This relation serves as an an

Chenxin Tao, Shiqian Su, Xizhou Zhu, Chenyu Zhang

The rapid advance of Large Language Models (LLMs) has catalyzed the development of Vision-Language Models (VLMs). Monolithic VLMs, which avoid modality-specific encoders, offer a promising alternative to the compositional ones but face the challenge of inferior performance. Most existing monolithic VLMs require tuning pre-trained LLMs to acquire vision abili

Shobhita Sundaram, Julia Chae, Yonglong Tian, Sara Beery

Modern vision models excel at general purpose downstream tasks. It is unclear, however, how they may be used for personalized vision tasks, which are both fine-grained and data-scarce. Recent works have successfully applied synthetic data to general-purpose representation learning, while advances in T2I diffusion models have enabled the generation of persona

Ruojin Cai, Jason Y. Zhang, Philipp Henzler, Zhengqi Li

Pairwise pose estimation from images with little or no overlap is an open challenge in computer vision. Existing methods, even those trained on large-scale datasets, struggle in these scenarios due to the lack of identifiable correspondences or visual overlap. Inspired by the human ability to infer spatial relationships from diverse scenes, we propose a nove

Shijie Wang, Samaneh Azadi, Rohit Girdhar, Saketh Rambhatla

Text-Image-to-Video (TI2V) generation aims to generate a video from an image following a text description, which is also referred to as text-guided image animation. Most existing methods struggle to generate videos that align well with the text prompts, particularly when motion is specified. To overcome this limitation, we introduce MotiF, a simple yet effec

Daniel Quigley

This paper proves a homomorphism between extensional formal semantics and distributional vector space semantics, demonstrating structural compatibility. Formal semantics models meaning as reference, using logical structures to map linguistic expressions to truth conditions, while distributional semantics represents meaning through word vectors derived from c

Bharat Vyas, Carol O'Sullivan

The animation of realistic virtual avatars in crowd scenarios is an important element of immersive virtual environments. However, achieving this realism requires attention to multiple factors, such as their visual appearance and motion cues. We investigated how body shape diversity influences the perception of motion clones in virtual crowds. A physics-based

Jean Pierre Mutanguha

A free-by-cyclic group can often be viewed as a mapping torus of a free group automorphism (monodromy) in multiple ways. What dynamical properties must these monodromies share, and to what extent are they invariant under quasi-isometries? We give a new proof using cyclic splittings that the growth type of a monodromy is a geometric invariant of the free-by-c

Sangmin Choi, Alok Laddha, Andrea Puhm

The universality of the logarithmic soft photon theorem in four dimensions can be traced to an infinite-dimensional asymptotic symmetry which acts as a local phase rotation on matter as we have shown in 2403.13053. Here we extend our earlier results for the charges associated to these superphaserotations to all orders in the coupling and prove that their con

Mingliang Liang, Martha Larson

Vision Language Models (VLMs) can be trained more efficiently if training sets can be reduced in size. Recent work has shown the benefits of masking text during VLM training using a variety of strategies (truncation, random masking, block masking and syntax masking) and has reported syntax masking as the top performer. In this paper, we analyze the impact of

Jannik Elsäßer, Laura Weihl, Veronika Cheplygina, Lisbeth Tangaa Nielsen

Seagrass meadows play a crucial role in marine ecosystems, providing benefits such as carbon sequestration, water quality improvement, and habitat provision. Monitoring the distribution and abundance of seagrass is essential for environmental impact assessments and conservation efforts. However, the current manual methods of analyzing underwater video data t

Enis Baty, Alejandro Hernández Díaz, Rebecca Davidson, Chris Bridges

State-Space Models (SSMs) have emerged as an efficient alternative to transformers, yet existing visual SSMs retain deeply ingrained biases from their origins in natural language processing. In this paper, we address these limitations by introducing M2D-SSM, a ground-up re-derivation of selective state-space techniques for multidimensional data. Unlike prior

Huaijie Wang, Shibo Hao, Hanze Dong, Shenao Zhang

Improving the multi-step reasoning ability of large language models (LLMs) with offline reinforcement learning (RL) is essential for quickly adapting them to complex tasks. While Direct Preference Optimization (DPO) has shown promise in aligning LLMs with human preferences, it is less suitable for multi-step reasoning tasks because (1) DPO relies on paired p

Siddharth Ambekar, Yuhang Yao, Ryan Li, Carlee Joe-Wong

Federated training methods have gained popularity for graph learning with applications including friendship graphs of social media sites and customer-merchant interaction graphs of huge online marketplaces. However, privacy regulations often require locally generated data to be stored on local clients. The graph is then naturally partitioned across clients,

Gregory A. L. White, Lloyd C. L. Hollenberg, Charles D. Hill, Kavan Modi

Randomised measurements can efficiently characterise many-body quantum states by learning the expectation values of observables with low Pauli weights. In this paper, we generalise the theoretical tools of classical shadow tomography to the temporal domain to explore multi-time phenomena. This enables us to efficiently learn the features of multi-time proces

Sangmin Choi, Alok Laddha, Andrea Puhm

The universality of gravitational scattering at low energies and large distances encoded in soft theorems and memory effects can be understood from symmetries. In four-dimensional asymptotically flat spacetimes the infinite enhancement of translations, extending the Poincar\'e group to the BMS group, is the symmetry underlying Weinberg's soft graviton theore

Laura Weihl, Bilal Wehbe, Andrzej Wąsowski

Autonomous inspection of infrastructure on land and in water is a quickly growing market, with applications including surveying constructions, monitoring plants, and tracking environmental changes in on- and off-shore wind energy farms. For Autonomous Underwater Vehicles and Unmanned Aerial Vehicles overfitting of controllers to simulation conditions fundame

Simon Douaud, Amir-Kian Kashani-Poor

We study the Borel plane of the topological string free energy on all hypergeometric one-parameter Calabi-Yau models close to singular points in moduli space, focusing on the location of Borel singularities and the value of the associated Stokes constants. We find in particular that in models which exhibit massless D-branes at a singular point, the central c

Dmitry Nesterov, Ksenia Lyamkina

We propose an alternative description of generalized unimodular gravity (GUMG), extending the Henneaux-Teitelboim approach to unimodular gravity (UMG). The central feature of this formulation is the consistent incorporation of time reparameterization, which enhances the gauge structure and reveals a spatial nonlocality hidden in the dynamics of the original

Leon Schindler, Kristin Miriam de Payrebrune

The design of soft robots is still commonly driven by manual trial-and-error approaches, requiring the manufacturing of multiple physical prototypes, which in the end, is time-consuming and requires significant expertise. To reduce the number of manual interventions in this process, topology optimization can be used to assist the design process. The design i

Vishnu Teja Kunde, Jean-Francois Chamberland, Siddharth Agarwal

Robust and fine localization algorithms are crucial for autonomous driving. For the production of such vehicles as a commodity, affordable sensing solutions and reliable localization algorithms must be designed. This work considers scenarios where the sensor data comes from images captured by an inexpensive camera mounted on the vehicle and where the vehicle

Hellina Hailu Nigatu, Zeerak Talat

Global Majority users are exposed to multitudes of harm when interacting with online platforms. This essay illuminates how exploitation in the advances of Artificial Intelligence is tied to historical exploitation and how the use of blanket terminology overshadows the layers of exploitation and harm ``Global Majority'' populations face. It first discusses th

Zeinab Dehghani, Koorosh Aslansefat, Adil Khan, Adín Ramírez Rivera

Despite recent advancements in Instruct-based Image Editing models for generating high-quality images, they are known as black boxes and a significant barrier to transparency and user trust. To solve this issue, we introduce SMILE (Statistical Model-agnostic Interpretability with Local Explanations), a novel model-agnostic for localized interpretability that

Stéphane Detournay, José Figueroa, Alejandro Vilar López

In (super)gravity theories, T-duality relates solutions with an exact isometry which can have wildly different asymptotic behaviors: a well-known example is the duality between BTZ black holes and (non-extremal) three-dimensional black strings. Using this dual pair, we show how the knowledge of a phase space which includes one set of solutions (here, BTZ bla

Seyedreza Mohseni, Seyedali Mohammadi, Deepa Tilwani, Yash Saxena

Malware authors often employ code obfuscations to make their malware harder to detect. Existing tools for generating obfuscated code often require access to the original source code (e.g., C++ or Java), and adding new obfuscations is a non-trivial, labor-intensive process. In this study, we ask the following question: Can Large Language Models (LLMs) potenti

Nafisa Binte Feroz, Chandrima Sarker, Tanzima Ahsan, K M Arefeen Sultan

One of the most urgent problems is the overcrowding in emergency departments (EDs), caused by an aging population and rising healthcare costs. Patient dispositions have become more complex as a result of the strain on hospital infrastructure and the scarcity of medical resources. Individuals with more dangerous health issues should be prioritized in the emer

Alok Tiwari, Sourav Ganguli, Manaswita Bose, V Kumaran

The selection of parameters in the contact law for inter-particle interactions affects the results of simulations of flowing granular materials. The present study aims to understand the effect of the ratio of tangential to normal spring stiffness coefficient ($\kappa$) on inter-particle contact behaviour in terms of the rotational coefficient of restitution

Dirk Bergemann, Marek Bojko, Paul Dütting, Renato Paes Leme

We study mechanism design in environments where agents have private preferences and private information about a common payoff-relevant state. In such settings with multi-dimensional types, standard mechanisms fail to implement efficient allocations. We address this limitation by proposing data-driven mechanisms that condition transfers on additional post-all

Lisa Beck, Ferdinand Eitler, Franz Gmeineder

We establish that locally bounded relaxed minimizers of degenerate elliptic symmetric gradient functionals on $\mathrm{BD}(\Omega)$ have weak gradients in $\mathrm{L}_{\mathrm{loc}}^{1}(\Omega;\mathbb{R}^{n\times n})$. This is achieved for the sharp ellipticity range that is presently known to yield $\mathrm{W}_{\mathrm{loc}}^{1,1}$-regularity in the full gr

Sabrina R. Hatt, Camille Shaw, Emma Zappala, Raju Baral

We present a magnetometry, muon spin relaxation ($\mu$SR), and neutron scattering study of the insulating face-centered-cubic spin glass Zn$_{0.5}$Mn$_{0.5}$Te. The magnetometry and $\mu$SR results confirm a spin freezing transition around $T_f \approx 23$ K, with the spin fluctuation rate decreasing gradually and somewhat inhomogeneously through the sample

Krithika Iyer, Shireen Elhabian, Sarang Joshi

Image registration is a core task in computational anatomy that establishes correspondences between images. Invertible deformable registration, which computes a deformation field and handles complex, non-linear transformations, is essential for tracking anatomical variations, especially in neuroimaging applications where inter-subject differences and longitu

Gunter Malle, J. Miquel Martínez, Carolina Vallejo

We study rationality properties of irreducible characters of finite groups. We show that the continuity of $2$-rationality is a phenomenon that can be detected in the principal $2$-block, thus refining a recent result of N. N. Hung. We also propose a conjectural group theoretical criterion for the continuity gap at level $1$ for all primes

Bipul Verma

Recent research has documented a reversal from divergence to convergence in income levels between rich and poor countries after 2000. This paper employs a growth accounting framework to investigate the proximate sources of convergence over the period 1980-2019. I find that while output levels began to converge only after 2000, capital (physical and human) ha

Mahdi Awawda, Alexander Wimmers

Germany is tasked with ensuring the safe and final storage of high-level radioactive waste in a deep geological repository. Since 2022, the ambitious target year of 2031 to identify a suitable location for such a site has been deferred by most public actors. The target year was pushed back by several decades to 2046 or even 2068, consequently delaying the co

Wenjun Ding, Yogesh K. Vohra, Cheng-Chien Chen

Elemental rare-earth metals provide a playground for studying novel electron correlation effects and complex magnetism. However, ab initio simulations of these systems remain challenging. Here, we employ fully charge self-consistent density functional theory and dynamical mean-field theory (DFT+DMFT) to investigate terbium (Tb) metal under pressure. We show

Shujie Gu, Xu Liu, Lunjin Chen, Maria Usanova

Electromagnetic ion cyclotron (EMIC) waves are discrete electromagnetic emissions separated by multiple ion gyrofrequencies. Harmonic EMIC waves are defined as waves with a strong electric or magnetic field (or both) at the harmonics of the fundamental EMIC mode. In this paper, for the first time, we present a statistical study on harmonic EMIC waves by the

Javier Jiménez-López, Paul R. Newman, Katarzyna Wichmann

We explore the potential for extracting the longitudinal proton structure function $F_{L}$ at the future Electron-Ion Collider (EIC) through a Rosenbluth separation method. The impacts of differing assumptions on sample sizes, systematic uncertainties and beam energy scenarios are investigated. With a sufficiently large number of centre of mass energy config

Leonardo Niccolò Ialongo, Sylvain Bangma, Fabian Jansen, Diego Garlaschelli

The structure of the supply chain network has important implications for modelling economic systems, from growth trajectories to responses to shocks or natural disasters. However, reconstructing firm-to-firm networks from available information poses several practical and theoretical challenges: the lack of publicly available data, the complexity of meso-scal

Lucila G. Alvarez-Zuzek, Laura Ferrarotti, Bruno Lepri, Riccardo Gallotti

As humans perceive and actively engage with the world, we adjust our decisions in response to shifting group dynamics and are influenced by social interactions. This study aims to identify which aspects of interaction affect cooperation-defection choices. Specifically, we investigate human cooperation within the Prisoner's Dilemma game, using the Drift-Diffu

Daniil Larionov, Steffen Eger

Evaluating the quality of machine-generated natural language content is a challenging task in Natural Language Processing (NLP). Recently, large language models (LLMs) like GPT-4 have been employed for this purpose, but they are computationally expensive due to the extensive token usage required by complex evaluation prompts. In this paper, we propose a prom

Muhammad Abdullah Sohail, Salaar Masood, Hamza Iqbal

This study investigates the potential of Large Language Models (LLMs), particularly GPT-4o, for Optical Character Recognition (OCR) in low-resource scripts such as Urdu, Albanian, and Tajik, with English serving as a benchmark. Using a meticulously curated dataset of 2,520 images incorporating controlled variations in text length, font size, background color

Avisha Kumar, Xuzhe Zhi, Zan Ahmad, Minglang Yin

Focused ultrasound (FUS) therapy is a promising tool for optimally targeted treatment of spinal cord injuries (SCI), offering submillimeter precision to enhance blood flow at injury sites while minimizing impact on surrounding tissues. However, its efficacy is highly sensitive to the placement of the ultrasound source, as the spinal cord's complex geometry a

Xiaohu Huang, Hao Zhou, Kai Han

In this paper, we introduce PruneVid, a visual token pruning method designed to enhance the efficiency of multi-modal video understanding. Large Language Models (LLMs) have shown promising performance in video tasks due to their extended capabilities in comprehending visual modalities. However, the substantial redundancy in video data presents significant co

Haoran Lu, Isidora Araya Day, Anton R. Akhmerov, Bernard van Heck

We propose an architecture for bit-flip error correction of Andreev spins that is protected by Kramers' degeneracy. Specifically, we show that a coupling network of linear inductors and Andreev spin qubits results in a static Hamiltonian composed of the stabilizers of a bit-flip code. The electrodynamics of the many-body spin states also respect these stabil

Bhubanjyoti Bhattacharya, Alakabha Datta, Gaber Faisel, Shaaban Khalil

Recent anomalies in $B$-meson decays, such as deviations in $R_{D^{(*)}}$ and $B\to Kν{\barν}$, suggest possible lepton flavor universality violation and new exotic interactions. In this work, we explore these anomalies within a non-minimal SU(5) grand unified theory (GUT) framework, which introduces a 45-dimensional Higgs representation predicting exotic sc

Mahyar Habibi, Dirk Hovy, Carlo Schwarz

There is an ongoing debate about how to moderate toxic speech on social media and the impact of content moderation on online discourse. This paper proposes and validates a methodology for measuring the content-moderation-induced distortions in online discourse using text embeddings from computational linguistics. Applying the method to a representative sampl

Mikhail V. Volkov

We give a combinatorial characterization of the identities holding in the semiring of all upper triangular Boolean $n\times n$-matrices and apply the characterization to computational complexity of identity checking, finite axiomatizability of equational theories, and algebraic descriptions of certain classes of recognizable languages.

Songhua Liu, Zhenxiong Tan, Xinchao Wang

Diffusion Transformers (DiT) have become a leading architecture in image generation. However, the quadratic complexity of attention mechanisms, which are responsible for modeling token-wise relationships, results in significant latency when generating high-resolution images. To address this issue, we aim at a linear attention mechanism in this paper that red

Nils E. Greven, Jonas Ranft, Tilo Schwalger

Mesoscopic models of finite-size neuronal populations are crucial to understand the dynamics of neural networks in the brain, especially their fluctuations and response to stimuli. However, current theories to derive such models are based on homogeneous all-to-all (full) connectivity. This assumption neglects the variance in the connectivity of biologically

Callum Deakin, Xi Chen

We analyse the performance limits of coherent modulation based on lossless unitary transformations, demonstrating that they can achieve high ($>$30~dB) SINAD and outperform conventional IQ modulators at equivalent transmitter laser powers.

Qiang Du, James M. Scott

Motivated by problems in machine learning, we study a class of variational problems characterized by nonlocal operators. These operators are characterized by power-type weights, which are singular at a portion of the boundary. We identify a range of exponents on these weights for which the variational Dirichlet problem is well-posed. This range is determined

Ahmet Bahaddin Ersoz

The integration of Large Vision-Language Models (LVLMs) such as OpenAI's GPT-4 Vision into various sectors has marked a significant evolution in the field of artificial intelligence, particularly in the analysis and interpretation of visual data. This paper explores the practical application of GPT-4 Vision in the construction industry, focusing on its capab

Eugenio Cuniato, Mike Allenspach, Thomas Stastny, Helen Oleynikova

Tilt-rotor aerial robots are more dynamic and versatile than fixed-rotor platforms, since the thrust vector and body orientation are decoupled. However, the coordination of servos and propellers (the allocation problem) is not trivial, especially accounting for overactuation and actuator dynamics. We incrementally build and present three novel allocation met

Luigi Alfonsi, Leron Borsten, Hyungrok Kim, Martin Wolf

The $L_\infty$-algebra approach to scattering amplitudes elegantly describes the nontrivial part of the $S$-matrix but fails to take into account the trivial part. We argue that the trivial contribution to the $S$-matrix should be accounted for by another, complementary $L_\infty$-algebra, such that a perturbative field theory is described by a cyclic relati

Max Langtry, Ruchi Choudhary

Load uncertainty must be accounted for during design to ensure building energy systems can meet energy demands during operation. Reducing building load uncertainty allows for improved designs with less compromise to be identified, reducing the cost of decarbonizing energy usage. However, the building monitoring required to reduce load uncertainty is costly.