November 2024 arXiv papers — page 98

Mostafa Naseri, Pooya Ashtari, Mohamed Seif, Eli De Poorter

In wireless communications, efficient image transmission must balance reliability, throughput, and latency, especially under dynamic channel conditions. This paper presents an adaptive and progressive pipeline for learned image compression (LIC)-based architectures tailored to such environments. We investigate two state-of-the-art learning-based models: the

Ziming Zhang, Yuping Shao, Yiqing Zhang, Fangzhou Lin

Iterative methods such as iterative closest point (ICP) for point cloud registration often suffer from bad local optimality (e.g. saddle points), due to the nature of nonconvex optimization. To address this fundamental challenge, in this paper we propose learning to form the loss landscape of a deep iterative method w.r.t. predictions at test time into a con

Asmita Roy, Huijuan Zhou, Ni Zhao, Xianyang Zhang

Testing for mediation effect poses a challenge since the null hypothesis (i.e., the absence of mediation effects) is composite, making most existing mediation tests quite conservative and often underpowered. In this work, we propose a subsampling-based procedure to construct a test statistic whose asymptotic null distribution is pivotal and remains the same

Jianliang He, Bowen Gang, Luella Fu

As the volume and complexity of data continue to expand across various scientific disciplines, the need for robust methods to account for the multiplicity of comparisons has grown widespread. A popular measure of type 1 error rate in multiple testing literature is the false discovery rate (FDR). The FDR provides a powerful and practical approach to large-sca

François Bachoc, Alberto González-Sanz, Jean-Michel Loubes, Yisha Yao

Modeling observations as random distributions embedded within Wasserstein spaces is becoming increasingly popular across scientific fields, as it captures the variability and geometric structure of the data more effectively. However, the distinct geometry and unique properties of Wasserstein spaces pose challenges to the application of conventional statistic

Ethan Wu, Caleb Ellington, Ben Lengerich, Eric P. Xing

Tuberculosis (TB) is a major global health challenge, and is compounded by co-morbidities such as HIV, diabetes, and anemia, which complicate treatment outcomes and contribute to heterogeneous patient responses. Traditional models of TB often overlook this heterogeneity by focusing on broad, pre-defined patient groups, thereby missing the nuanced effects of

Yongsong Wang, Haojie Guo, Ane Etxebarria, Sandra Sajan

The layered nature and simple structure of FeSe reveal this iron-based superconductor as a unique building block for the design of artificial heterostructure materials. While superconductivity develops in ultrathin films of FeSe on SrTiO3 substrates, it remains unclear whether it can be developed on more chemically inert, layered materials such as graphene.

Wasim Raja Mondal, Tom Berlijn, N. S. Vidhyadhiraja, Hanna Terletska

The phenomenon of Anderson localization in various disordered media has sustained significant interest over many decades. Specifically, the Anderson localization of phonons has been viewed as a potential mechanism for creating fascinating thermal transport properties in materials. However, despite extensive work, the influence of the vector nature of phonons

Ryan Blair, Alexandra Kjuchukova, Ella Pfaff

Given any link $L\subseteq S^3$, we show that it is possible to embed an unknot $U$ in its complement so that the link $L\cup U$ satisfies the Meridional Rank Conjecture (MRC). The bridge numbers in our construction fit into the equality $\beta(L\cup U)=2\beta(L)-1=\text{rank}(\pi_1(S^3\backslash (L\cup U)))$. In addition, we prove the MRC for new infinite f

Hiroki Aoki, Kyoji Saito

We consider a formal power series in one variable whose coefficients are holomorphic functions in a given multidimensional complex domain. Assume the following two conditions on the series. (C1) The restriction of the series at each point of a dense subset of the domain converges in an open disk of a fixed radius. (C2) The series is algebraic over the ring o

Xudong Lu, Yinghao Chen, Cheng Chen, Hui Tan

The emergence and growing popularity of multimodal large language models (MLLMs) have significant potential to enhance various aspects of daily life, from improving communication to facilitating learning and problem-solving. Mobile phones, as essential daily companions, represent the most effective and accessible deployment platform for MLLMs, enabling seaml

Yunsheng Ma, Burhaneddin Yaman, Xin Ye, Jingru Luo

Bird's eye view (BEV)-based 3D perception plays a crucial role in autonomous driving applications. The rise of large language models has spurred interest in BEV-based captioning to understand object behavior in the surrounding environment. However, existing approaches treat perception and captioning as separate tasks, focusing on the performance of only one

Aymen Alsaadi, Mihael Hategan-Marandiuc, Ketan Maheshwari, Andre Merzky

Exascale computers offer transformative capabilities to combine data-driven and learning-based approaches with traditional simulation applications to accelerate scientific discovery and insight. However, these software combinations and integrations are difficult to achieve due to the challenges of coordinating and deploying heterogeneous software components

Brenden R. Ortiz, William R. Meier, Ganesh Pokharel, Juan Chamorro

The kagome motif is a versatile platform for condensed matter physics, hosting rich interactions between magnetic, electronic, and structural degrees of freedom. In recent years, the discovery of a charge density wave (CDW) in the AV$_3$Sb$_5$ superconductors and structurally-derived bond density waves in FeGe and ScV$_6$Sn$_6$ have stoked the search for new

Pritha Paul, Chris Clarkson, Roy Maartens

Recently the galaxy matter density 4-point correlation function has been looked at to investigate parity violation in large scale structure surveys. The 4-point correlation function is the lowest order statistic which is sensitive to parity violation, since a tetrahedron is the simplest shape that cannot be superimposed on its mirror image by a rotation. If

Kai Helli, David Schnurr, Noah Hollmann, Samuel Müller

While most ML models expect independent and identically distributed data, this assumption is often violated in real-world scenarios due to distribution shifts, resulting in the degradation of machine learning model performance. Until now, no tabular method has consistently outperformed classical supervised learning, which ignores these shifts. To address tem

Afonso S. Bandeira, Sivakanth Gopi, Haotian Jiang, Kevin Lucca

Matrix concentration inequalities, intimately connected to the Non-Commutative Khintchine inequality, have been an important tool in both applied and pure mathematics. We study tensor versions of these inequalities, and establish non-asymptotic inequalities for the $\ell_p$ injective norm of random tensors with correlated entries. In certain regimes of $p$ a

Peijie Zhong, Cheick Ba, Raúl Mondragón, Richard Clegg

When we detect communities in temporal networks it is important to ask questions about how they change in time. Normalised Mutual Information (NMI) has been used to measure the similarity of communities when the nodes on a network do not change. We propose two extensions namely Union-Normalised Mutual Information (UNMI) and Intersection-Normalised Mutual Inf

Mun K. Chan, Katherine A. Schreiber, Oscar E. Ayala-Valenzuela, Eric D. Bauer

The pseudogap state of high-$T_{\rm c}$ cuprates, known for its partial gapping of the Fermi surface above the superconducting transition temperature $T_{\rm c}$, is believed to hold the key to understanding the origin of Planckian relaxation and quantum criticality. However, the nature of the Fermi surface in the pseudogap state has remained a fundamental o

Rômulo Damasclin Chaves dos Santos

This paper presents a rigorous theoretical extension of the Smagorinsky model for turbulence simulations. The author builds on its fundamental framework, addressing known limitations, and making new mathematical advances. Specifically, this work introduces new theorems on the existence and uniqueness of weak solutions and establishes the stability of the mod

Xiaowei Xu, Bi T. Foua, Xingqiao Wang, Vivek Gunasekaran

In this paper, the authors propose TriBERTa, a supervised entity resolution system that utilizes a pre-trained large language model and a triplet loss function to learn representations for entity matching. The system consists of two steps: first, name entity records are fed into a Sentence Bidirectional Encoder Representations from Transformers (SBERT) model

Lidia Cano Pecharroman, Melissa O. Tier, Elke U. Weber

Efforts are needed to identify and measure both communities' exposure to climate hazards and the social vulnerabilities that interact with these hazards, but the science of validating hazard vulnerability indicators is still in its infancy. Progress is needed to improve: 1) the selection of variables that are used as proxies to represent hazard vulnerability

Miriam Asare-Baiden, Kathleen Jordan, Andrew Chung, Sharon Eve Sonenblum

Pressure injury (PI) detection is challenging, especially in dark skin tones, due to the unreliability of visual inspection. Thermography has been suggested as a viable alternative as temperature differences in the skin can indicate impending tissue damage. Although deep learning models have demonstrated considerable promise toward reliably detecting PI, the

Liqiang Hou, Katherine J. Mack

Dark matter annihilation has the potential to leave an imprint on the properties of the first luminous structures at Cosmic Dawn as well as the overall evolution of the intergalactic medium (IGM). In this work, we employ a semi-analytic method to model dark matter annihilation during Cosmic Dawn (approximately redshift $z=20$ to $40$), examining potential mo

Furkan M. Altincicek, Lucian Livadaru, Christopher C. Leon, Taras Chutora

Bare silicon dimers on hydrogen-terminated Si(100) have two dangling bonds. These are atomically localized regions of high state density near to and within the bulk silicon band gap. We studied bare silicon dimers as monomeric units. Silicon dimer wires are much more stable than wires composed of individual dangling bonds. Dimer wires composed of 1 to 5 dime

Guido Governatori

We consider the notion of weak permission as the failure to conclude that the opposite obligation. We investigate the issue from the point of non-monotonic reasoning, specifically logic programming and structured argumentation, and we show that it is not possible to capture weak permission in the presence of deontic conflicts under the well-founded, grounded

Xinran Li

Observational studies provide invaluable opportunities to draw causal inference, but they may suffer from biases due to pretreatment difference between treated and control units. Matching is a popular approach to reduce observed covariate imbalance. To tackle unmeasured confounding, a sensitivity analysis is often conducted to investigate how robust a causal

Divesh Basina, Joseph Raj Vishal, Aarya Choudhary, Bharatesh Chakravarthi

The curse of dimensionality poses a significant challenge to modern multilayer perceptron-based architectures, often causing performance stagnation and scalability issues. Addressing this limitation typically requires vast amounts of data. In contrast, Kolmogorov-Arnold Networks have gained attention in the machine learning community for their bold claim of

Nilberto Bezerra, Van Sérgio Alves, Leandro O. Nascimento, Luis Fernández

We analyze mass renormalization in massive Dirac-like systems in (2+1) dimensions arising from electron-phonon interactions at finite temperatures, employing the large-$N$ expansion. Our model combines the low-energy description of charge carriers in a buckled honeycomb lattice with the low-energy approximation for phonons and electron-phonon interactions in

Jiaxin Yu, Tianchen Qian

Micro-randomized trials (MRTs) are increasingly utilized for optimizing mobile health interventions, with the causal excursion effect (CEE) as a central quantity for evaluating interventions under policies that deviate from the experimental policy. However, MRT often contains missing data due to reasons such as missed self-reports or participants not wearing

Ratun Rahman, Neeraj Kumar, Dinh C. Nguyen

Electric load forecasting is essential for power management and stability in smart grids. This is mainly achieved via advanced metering infrastructure, where smart meters (SMs) are used to record household energy consumption. Traditional machine learning (ML) methods are often employed for load forecasting but require data sharing which raises data privacy c

Fang Wu, Shuting Jin, Xiangru Tang, Junlin Xu

Among these, D-peptides are resistant to proteolysis, exhibit greater in vivo stability, and are easier to synthesize. Despite advances in deep learning for peptide discovery, the scarcity of natural D-protein data limits the transfer of existing generative models to the D-peptide chemical space. We propose D-Flow, a full-atom flow-based framework for de nov

Jingcheng Lu, Jeff Calder

We propose a new method for data visualization based on attraction-repulsion swarming (ARS) dynamics, which we call ARS visualization. ARS is a generalized framework that is based on viewing the t-distributed stochastic neighbor embedding (t-SNE) visualization technique as a swarm of interacting agents driven by attraction and repulsion. Motivated by recent

Owen Burns, Rizwan Qureshi

We address the issue of the exploding computational requirements of recent State-of-the-art (SOTA) open set multimodel 3D mapping (dense 3D mapping) algorithms and present Voxel-Aggregated Feature Synthesis (VAFS), a novel approach to dense 3D mapping in simulation. Dense 3D mapping involves segmenting and embedding sequential RGBD frames which are then fuse

Sourav Roy Chowdhury, Deeptendu Santra

The formation channels of compact object binaries are crucial for interpreting gravitational wave observations and enhancing early multi-messenger alerts. Despite the key role of stellar metallicity in progenitor evolution, many models assume a uniform value for all stars in a cluster. In this study, we investigate the impact of a heterogeneous stellar metal

Samuel Perreault, Yanbo Tang, Ruyi Pan, Nancy Reid

Hierarchical Archimedean copulas (HACs) are multivariate uniform distributions constructed by nesting Archimedean copulas into one another, and provide a flexible approach to modeling non-exchangeable data. However, this flexibility in the model structure may lead to over-fitting when the model estimation procedure is not performed properly. In this paper, w

Meenatchi Sundaram Muthu Selva Annamalai, Borja Balle, Jamie Hayes, Emiliano De Cristofaro

The Differentially Private Stochastic Gradient Descent (DP-SGD) algorithm supports the training of machine learning (ML) models with formal Differential Privacy (DP) guarantees. Traditionally, DP-SGD processes training data in batches using Poisson subsampling to select each batch at every iteration. More recently, shuffling has become a common alternative d

Parand A. Alamdari, Toryn Q. Klassen, Rodrigo Toro Icarte, Sheila A. McIlraith

Pluralistic alignment is concerned with ensuring that an AI system's objectives and behaviors are in harmony with the diversity of human values and perspectives. In this paper we study the notion of pluralistic alignment in the context of agentic AI, and in particular in the context of an agent that is trying to learn a policy in a manner that is mindful of

Marco De Vincenzi, Mert D. Pesé, Chiara Bodei, Ilaria Matteucci

The growing reliance on software in road vehicles has led to the emergence of Software-Defined Vehicles (SDV). This work analyzes SDV security and privacy through a systematic literature review complemented by an industry questionnaire across the automotive supply chain. The analysis is structured as four research questions and results in a security framewor

K. A. Garcia, A. Bader, D. Boeyaert, A. H. Boozer

Resilient divertor features connected to open chaotic edge structures in the Helically Symmetric Experiment (HSX) are investigated. For the first time, an expanded vessel wall was considered that would give space for implementation of a physical divertor target structure. The analysis was done for four different magnetic configurations with very different ch

Alice Guionnet, Karol Kozlowski, Alex Little

In this work we establish under certain hypotheses the $N \to +\infty$ asymptotic expansion of integrals of the form $$\mathcal{Z}_{N,\Gamma}[V] \, = \, \int_{\Gamma^N} \prod_{ a < b}^{N}(z_a - z_b)^\beta \, \prod_{k=1}^{N} \mathrm{e}^{ - N \beta V(z_k) } \, \mathrm{d}\mathbf{z}$$ where $V \in \mathbb{C}[X]$, $\beta \in 2 \mathbb{N}^*$ is an even integer and

Nils Lommen, Éléanore Meyer, Jürgen Giesl

There exist several approaches to infer runtime or resource bounds for integer programs automatically. In this paper, we study the subclass of periodic rational solvable loops (prs-loops), where questions regarding the runtime and the size of variable values are decidable and where we can therefore obtain techniques that are complete for such subclasses. We

Ozgur Can Seckin, Manita Pote, Alexander Nwala, Lake Yin

Social media platforms have become a hub for political activities and discussions, democratizing participation in these endeavors. However, they have also become an incubator for manipulation campaigns, like information operations (IOs). Some social media platforms have released datasets related to such IOs originating from different countries. However, we l

Jack C. Straton

In a prior paper we found that the Fourier-Legendre series of a Bessel function of the first kind J_{N}\left(kx\right) and of a modified Bessel functions of the first kind I_{N}\left(kx\right) lead to an infinite set of series involving \,_{1}F_{2} hypergeometric functions (extracted therefrom) that could be summed, having values that are inverse powers of t

Federico Ettori, Timothy J. Sluckin, Paolo Biscari

We investigate the dynamic behavior of spin reversal events in the dilute Ising model, focusing on the influence of static disorder introduced by pinned spins. Our Monte Carlo simulations reveal that in a homogeneous, defect-free system, the inter-event time (IET) between local spin flips follows an exponential distribution, characteristic of Poissonian proc

Ji Woong Yu, Daeseong Yong, Bae-Yeun Ha, Changbong Hyeon

Inclusions in mobile brushes experience apparent (depletion) attraction, which arises from a tendency to minimize the volume of depletion zones around the inclusions, thereby to maximize the entropy of the surrounding polymers. Here, we study the brush-induced depletion attraction between cylindrical inclusions using molecular dynamics simulations and the As

Yonggan Fu, Zhongzhi Yu, Junwei Li, Jiayi Qian

Motivated by the transformative capabilities of large language models (LLMs) across various natural language tasks, there has been a growing demand to deploy these models effectively across diverse real-world applications and platforms. However, the challenge of efficiently deploying LLMs has become increasingly pronounced due to the varying application-spec

Maryam Shoaeinaeini, Brent Harrison

Human guidance in reinforcement learning (RL) is often impractical for large-scale applications due to high costs and time constraints. Large Language Models (LLMs) offer a promising alternative to mitigate RL sample inefficiency and potentially replace human trainers. However, applying LLMs as RL trainers is challenging due to their overconfidence and less

Hao-Jen You, Yi-Ting Chiang, Arun Bansil, Hsin Lin

We present a machine-learning interatomic potential (MLIP) framework, which substantially accelerates the prediction of lattice thermal conductivity for both particle-like and wave-like thermal transport, including three-phonon and four-phonon scattering processes, and achieves speedups of five orders of magnitude compared to the conventional DFT calculation

Gregory Crane, James Tauber, Alison Babeu, Lisa Cerrato

We report here on the workflow that we needed to develop in order to integrate the growing range of openly licensed, born-digital and, increasingly, machine actionable publications. Our developmental work focused upon textual data for Ancient Greek, Latin, Old English, Classical Arabic and Classical Persian but the challenges that we have had to address are

Sonda Fourati, Wael Jaafar, Noura Baccar

Autonomous driving (AD) technology promises to revolutionize daily transportation by making it safer, more efficient, and more comfortable. Their role in reducing traffic accidents and improving mobility will be vital to the future of intelligent transportation systems. Autonomous driving in harsh environmental conditions presents significant challenges that

D. D. Carvalho, Y. Bertho, A. Seguin, E. M. Franklin

When several intruders move in a granular medium, coupling effects are observed, the motion of one intruder affecting that of others. In this paper, we investigate experimentally how the drag forces acting on a pair of spherical intruders moving amid grains at constant velocity vary with the transverse separation between them and their depth. When intruders

Eric Hsiung, Swarat Chaudhuri, Joydeep Biswas

Quantitative automata are useful representations for numerous applications, including modeling probability distributions over sequences to Markov chains and reward machines. Actively learning such automata typically occurs using explicitly gathered input-output examples under adaptations of the L-star algorithm. However, obtaining explicit input-output pairs

Chad Fiechter, Binayak Kunwar, Guy Tchuente

This study examines the impact of monetary factors on the conversion of farmland to renewable energy generation, specifically solar and wind, in the context of expanding U.S. energy production. We propose a new econometric method that accounts for the diverse circumstances of landowners, including their unordered alternative land use options, non-monetary be

Tom Cappendijk, Pepijn de Reus, Ana Oprescu

The increasing electricity demands of personal computers, communication networks, and data centers contribute to higher atmospheric greenhouse gas emissions, which in turn lead to global warming and climate change. Therefore the energy consumption of code must be minimized. Code can be generated by large language models. We look at the influence of prompt mo

C. V. Mehl, J. N. Orce, C. Ngwetsheni, P. Marević

The spectroscopic quadrupole moment of the first excited state, $Q_{_S}(2^{+}_{1})$, at 1.634 MeV in $^{20}$Ne was determined from sensitive reorientation-effect Coulomb-excitation measurements using a heavy target and safe energies well below the Coulomb barrier. Particle-$\gamma$ coincidence measurements were collected at iThemba LABS with a digital data-a

W. H. J. Hayashi, W. W. Heidbrink, C. M. Muscatello, D. J. Lin

A new sightline geometry for the fast-ion D-alpha (FIDA) diagnostic on the Large Helical Device (LHD) has been confirmed to measure signals for high-energy fast ions produced by negative-ion neutral beam injection. The newly installed sightline uses a 180 keV tangential negative-ion neutral beamline as the active source. Due to the small angle between the be

Minglu Zhao, Dehong Xu, Deqian Kong, Wen-Hao Zhang

We present a minimalistic representation model for the head direction (HD) system, aiming to learn a high-dimensional representation of head direction that captures essential properties of HD cells. Our model is a representation of rotation group $U(1)$, and we study both the fully connected version and convolutional version. We demonstrate the emergence of

Sannara Ek, Kaile Wang, François Portet, Philippe Lalanda

Personalized Federated Learning (PFL) enables distributed training on edge devices, allowing models to collaboratively learn global patterns while tailoring their parameters to better fit each client's local data, all while preserving data privacy. However, PFL faces two key challenges in mobile systems: client drift, where heterogeneous data cause model div

Enya Van den Abeele, Pierre Astier, Anna Niemiec

Since cosmic shear was first observed in 2000, it has become a key cosmological probe and promises to deliver exquisite dark energy constraints. However, shear is inferred from coherent distortions of galaxy shapes, and the relation between galaxy ellipticities and gravitational shear is a serious potential source of bias. To address this, we are developing

Marco Caoduro, Meike Neuwohner, Joseph Paat

The incidence matrix of a graph is totally unimodular if and only if the graph is bipartite, i.e., it contains no odd cycles. We extend the characterization of total unimodularity to hypergraphs whose hyperedges of size at least four are pairwise disjoint, which we call disjoint hypergraphs. Disjoint hypergraphs have been used to model problems with fairness

Pedro Henrique Silva Coutinho, Iury Bessa, Victor Hugo Pereira Rodrigues, Tiago Roux Oliveira

This paper deals with sliding mode control for multivariable polytopic uncertain systems. We provide systematic procedures to design variable structure controllers (VSCs) and unit-vector controllers (UVCs). Based on suitable representations for the closed-loop system, we derive sufficient conditions in the form of linear matrix inequalities (LMIs) to design

Christoph Brosch, Alexander Bouwens, Sebastian Bast, Swen Haab

The enormous progress in the field of artificial intelligence (AI) enables retail companies to automate their processes and thus to save costs. Thereby, many AI-based automation approaches are based on machine learning and computer vision. The realization of such approaches requires high-quality training data. In this paper, we describe the creation process

Harrison E. Cook, Barry McKernan, K. E. Saavik Ford, Vera Delfavero

We use the Monte Carlo For AGN (active galactic nucleus) Channel Testing and Simulation (McFACTS, https://www.github.com/mcfacts/mcfacts) code to study the effect of AGN disk and nuclear star cluster parameters on predicted mass distributions for LIGO-Virgo-KAGRA (LVK) compact binaries forming in AGN disks. The assumptions we vary include the black hole (BH)

Pepijn de Reus, Ana Oprescu, Jelle Zuidema

This study examines quantisation and pruning strategies to reduce energy consumption in code Large Language Models (LLMs) inference. Using StarCoder2, we observe increased energy demands with quantization due to lower throughput and some accuracy losses. Conversely, pruning reduces energy usage but impairs performance. The results highlight challenges and tr

Seyed Mohsen Hosseini Nejad

We analyze the static potentials induced by vacuum domains for various representations in SU($4$) Yang-Mills theory within the framework of the domain structure model. By studying the interactions within the vacuum domains, we can uncover fundamental properties of the static potentials. It appears that attractions within the vacuum domains strongly adhere to

Caspar Oesterheld, Emery Cooper, Miles Kodama, Linh Chi Nguyen

We introduce a dataset of natural-language questions in the decision theory of so-called Newcomb-like problems. Newcomb-like problems include, for instance, decision problems in which an agent interacts with a similar other agent, and thus has to reason about the fact that the other agent will likely reason in similar ways. Evaluating LLM reasoning about New

David Hinojosa-Romero, Renela María Valladares, Alexander Valladares, Isaías Rodríguez

Disordered alloys of silver and gold have been in the interest of the condensed matter community for decades since they are the prototype of the ideal solid solution due to the chemical similarity of their constituents and due to their potential industrial applications. Although they are considered well-known materials, surprises have appeared that have not

Janice Seungyeon Lee, Thomas Detlefsen, Shara Lawande, Saudamini Ghatge

Interactive sensors are an important component of robotic systems but often require manual replacement due to wear and tear. Automating this process can enhance system autonomy and facilitate long-term deployment. We developed an autonomous sensor exchange and calibration system for an agriculture crop monitoring robot that inserts a nitrate sensor into corn

Laura Doval, Federico Echenique Wanying Huang, Yi Xin

We study the allocation of deceased-donor lungs to patients in need of a transplant. Patients make sequential decisions in an order dictated by a priority policy. Using data from a prominent Organ Procurement Organization in the United States, we provide reduced-form evidence of social learning: because patients accept or reject organs in sequence, their dec

Sumika Jinnouchi, Masateru Tsunoda

Computer science unplugged (CS unplugged) is a method of teaching computer science and computational thinking. It does not use a computer but employs physical materials. As CS unplugged, past studies proposed a new method to visualize programming behavior, and evaluated the method based on the understanding test of program. However, the past studied did not

Buntaro Hiraki, Kensei Hamamoto, Ami Kimura, Masateru Tsunoda

Code readability is an important indicator of software maintenance as it can significantly impact maintenance efforts. Recently, LLM (large language models) have been utilized for code readability evaluation. However, readability evaluation differs among developers, so personalization of the evaluation by LLM is needed. This study proposes a method which cal

Jaewoo Heo, Kuan-Chieh Wang, Karen Liu, Serena Yeung-Levy

Motion capture technologies have transformed numerous fields, from the film and gaming industries to sports science and healthcare, by providing a tool to capture and analyze human movement in great detail. The holy grail in the topic of monocular global human mesh and motion reconstruction (GHMR) is to achieve accuracy on par with traditional multi-view cap

Wenxuan Wang, Wenxiang Jiao, Jen-tse Huang, Zhaopeng Tu

In this study, we revisit the commonly-cited off-target issue in multilingual neural machine translation (MNMT). By carefully designing experiments on different MNMT scenarios and models, we attribute the off-target issue to the overfitting of the shortcuts of (non-centric, centric) language mappings. Specifically, the learned shortcuts biases MNMT to mistak

Paulo Cesar Souza Silva, Paulo Cesar Pellanda, Tiago Roux Oliveira

This paper addresses the design and analysis of a multivariable gradient-based stochastic extremum-seeking control method for multi-input systems with arbitrary input delays. The approach accommodates systems with distinct time delays across input channels and achieves local exponential stability of the closed-loop system, guaranteeing convergence to a small

Gu-Feng Zhang, Sheikh Rubaiat Ul Haque, Kelson J. Kaj, Xiang Chen

Antiferromagnets exhibit rapid spin dynamics in a net zero magnetic background which enables novel spintronic applications and interrogation of many-body quantum phenomena. The layered antiferromagnet Sr$_2$IrO$_4$ hosts an exotic spin one-half Mott insulating state with an electronic gap arising from on-site Coulomb repulsion and strong spin-orbit coupling.

Haojie Zheng, Tianyang Xu, Hanchi Sun, Shu Pu

Multimodal large language models (MLLMs) have advanced the integration of visual and linguistic modalities, establishing themselves as the dominant paradigm for visual-language tasks. Current approaches like chain of thought (CoT) reasoning have augmented the cognitive capabilities of large language models (LLMs), yet their adaptation to MLLMs is hindered by

Andrew R. Tawfeek

Given a rational polyhedral space $X$ (a tropical cycle with boundary, in the sense of Mikhalkin--Rau), one can define tropical vector bundles on $X$ having real or tropical fibers. By restricting attention to bounded rational sections of these bundles, one obtains characteristic classes that behave as expected classically. We develop further properties of t

Ana-Catalina Plesa, Julia Maia, Solmaz Adeli, Tina Rückriemen-Bez

Rocky planets in our Solar System, namely Mercury, Venus, Earth, Mars, and the Moon, which is generally added to this group due to its geological complexity, possess a solid surface and share a common structure divided into major layers, namely a silicate crust, a silicate mantle, and an iron-rich core. However, while all terrestrial planets share a common s

José L. Ansorena, Glenier Bello

We prove that for $1\le p,q\le\infty$ the mixed-norm spaces $L_q(L_p)$ are mutually non-isomorphic, with the only exception that $L_q(L_2)$ is isomorphic to $L_q(L_q)$ for all $1<q<\infty$.

Giorgio Tripodi, Xiang Zheng, Yifan Qian, Dakota Murray

Tenure is a cornerstone of the US academic system, yet its relationship to faculty research trajectories remains poorly understood. Conceptually, tenure systems may act as a selection mechanism, screening in high-output researchers; a dynamic incentive mechanism, encouraging high output prior to tenure but low output after tenure; and a creative search mecha

Randall J. Ellis, Audrey Airaud, Chirag J. Patel

Identifying predictive features from high-dimensional datasets is a major task in biomedical research. However, it is difficult to determine the robustness of selected features. Here, we investigate the performance of randomly chosen features, what we term "random feature baselines" (RFBs), in the context of disease risk prediction from blood plasma proteomi

Moshe Kimhi, Idan Kashani, Avi Mendelson, Chaim Baskin

The widely used ReLU is favored for its hardware efficiency, {as the implementation at inference is a one bit sign case,} yet suffers from issues such as the ``dying ReLU'' problem, where during training, neurons fail to activate and constantly remain at zero, as highlighted by Lu et al. Traditional approaches to mitigate this issue often introduce more comp

Lenny Jones

A monic polynomial $f(x)\in {\mathbb Z}[x]$ of degree $n$ that is irreducible over ${\mathbb Q}$ is called cyclic if the Galois group over ${\mathbb Q}$ of $f(x)$ is the cyclic group of order $n$, while $f(x)$ is called monogenic if $\{1,\theta,\theta^2,\ldots, \theta^{n-1}\}$ is a basis for the ring of integers of ${\mathbb Q}(\theta)$, where $f(\theta)=0$.

Jerry W. Xuan, Marshall D. Perrin, Dimitri Mawet, Heather A. Knutson

We present JWST/MIRI low-resolution spectroscopy ($4.75-14~\mu$m) of the first known substellar companion, Gliese 229 Bab, which was recently resolved into a tight binary brown dwarf. Previous atmospheric retrieval studies modeling Gliese 229 B as a single brown dwarf have reported anomalously high carbon-to-oxygen ratios (C/O) of $\approx 1.1$ using $1-5~\m

Songlin Zhao, Rong Zhou, Yu Zhang, Yong Chen

In this paper, we introduce a novel normative modeling approach that incorporates focal loss and adversarial autoencoders (FAAE) for Alzheimer's Disease (AD) diagnosis and biomarker identification. Our method is an end-to-end approach that embeds an adversarial focal loss discriminator within the autoencoder structure, specifically designed to effectively ta

Yuqi Xiao, Leah Edelstein-Keshet, Alain Goriely, Kathryn V Issac

Capsular contracture is a pathological response to implant-based reconstructive breast surgery, where the ``capsule'' (tissue surrounding an implant) painfully thickens, contracts and deforms. It is known to affect breast-cancer survivors at higher rates than healthy women opting for cosmetic cosmetic breast augmentation with implants. We model the early sta

Carole Madengko, Stephane Tchuiaga, Franck Houenou

This paper addresses Banyaga's conjecture asserting that : the group of strong symplectic homeomorphisms is a proper normal subgroup of the symplectic homeomorphism group of a closed symplectic manifold.

Mathilda Campillo, Angélica Osorno, Manuel Rivera

These lecture notes (in Spanish) are based on a mini-course given by A. Osorno and M. Rivera at the First Colombian Geometry and Topology Meeting that took place at the Universidad Nacional de Colombia in July 2024 in Bogota. They are intended to be a guide for a first encounter with homotopy theory and simplicial methods - emphasizing intuition and importan

Yinxuan Zhu, Andrew A. Allerman, Chandan Joishi, Jonathan Pratt

We report on the heterostructure and interfacial engineering of metalorganic chemical vapor deposition (MOCVD) grown reverse-graded contacts to ultra-wide bandgap AlGaN. A record low contact resistivity of 1.4 x 10-6 Ohm.cm2 was reported on an Al0.82Ga0.18N metal semiconductor field effect transistor (MESFET) by compositionally grading the contact layer from

Md. Abdul Awal, Mrigank Rochan, Chanchal K. Roy

Large Language Model (LLM)-generated data is increasingly used in software analytics, but it is unclear how this data compares to human-written data, particularly when models are exposed to adversarial scenarios. Adversarial attacks can compromise the reliability and security of software systems, so understanding how LLM-generated data performs under these c

Jiyeong Kim, Michael L. Chen, Shawheen J. Rezaei, Mariana Ramirez-Posada

Patient-centered research is increasingly important in narrowing the gap between research and patient care, yet incorporating patient perspectives into health research has been inconsistent. We propose an automated framework leveraging innovative natural language processing (NLP) and artificial intelligence (AI) with patient portal messages to generate resea

Mahmudul Hasan

In computer vision tasks, the ability to focus on relevant regions within an image is crucial for improving model performance, particularly when key features are small, subtle, or spatially dispersed. Convolutional neural networks (CNNs) typically treat all regions of an image equally, which can lead to inefficient feature extraction. To address this challen

Tahar Amari, Aurélien Canou, Marco Velli, Zoran Mikic

Models and observations have demonstrated that Twisted Flux Ropes (TFRs) play a significant role in the structure and eruptive dynamics of active regions. Their role in the dynamics of the quiet Sun atmosphere on has remained elusive, their fundamental relevance emerging mainly from theoretical models (Amari et al. 2015), showing that they form and erupt as

Jack H. Y. Lo, Yuan Liu, Tariq Alghamdi, Muhammad F. Afzaal

The rupture of a liquid film, where a thin liquid layer between two other fluids breaks and forms holes, commonly occurs in both natural phenomena and industrial applications. The post-rupture dynamics, from initial hole formation to the complete collapse of the film, are crucial because they govern droplet formation, which plays a significant role in many a

Peter beim Graben

A phenomenological model for aesthetic appraisal is proposed in terms of pragmatic information for a dynamic update semantics over belief states on an aesthetic appreciator. The model qualitatively correlates with aesthetic pleasure ratings in an experimental study on cadential effects in Western tonal music. Finally, related computational and neurodynamical

Basilis Mamalis, Sergios Gerakidis

Wireless Sensor Networks (WSN) and Vehicular Ad-hoc Networks (VANET) have been extensively used in IoT applications for environmental monitoring, especially in rural and agricultural areas. In this paper we present a novel combined approach which uses both WSN and VANET clustered structures for the efficient gathering and processing of environmental paramete

Chris Fallin, Maxwell Bernstein

There is a tension in dynamic language runtime design between speed and correctness: state-of-the-art JIT compilation, the result of enormous industrial investment and significant research, achieves heroic speedups at the cost of complexity that can result in serious correctness bugs. Much of this complexity comes from the existence of multiple tiers and the

Toke Meier Carlsen, Anna Duwenig, Efren Ruiz, Aidan Sims

We consider \'etale Hausdorff groupoids in which the interior of the isotropy is abelian. We prove that the norms of the images under regular representations, of elements of the reduced groupoid $C^*$-algebra whose supports are contained in the interior of the isotropy vary upper semicontinuously. This corrects an error in [T.M. Carlsen, E. Ruiz, A. Sims and

Sheryl Paul, Anand Balakrishnan, Xin Qin, Jyotirmoy V. Deshmukh

Autonomous multi-agent systems such as hospital robots and package delivery drones often operate in highly uncertain environments and are expected to achieve complex temporal task objectives while ensuring safety. While learning-based methods such as reinforcement learning are popular methods to train single and multi-agent autonomous systems under user-spec