February 2024 arXiv papers — page 147

Olga Katkova, Anna Vishnyakova

A real sequence $(b_k)_{k=0}^\infty$ is called totally positive if all minors of the infinite matrix $ \left\| b_{j-i} \right\|_{i, j =0}^\infty$ are nonnegative (here $b_k=0$ for $k<0$). In this paper, we investigate the problem of description of the set of sequences $(a_k)_{k=0}^\infty$ such that for every totally positive sequence $(b_k)_{k=0}^\infty$ the

Osho Rawal, Berk Turhan, Irene Font Peradejordi, Shreya Chandrasekar

Protein phosphorylation involves the reversible modification of a protein (substrate) residue by another protein (kinase). Liquid chromatography-mass spectrometry studies are rapidly generating massive protein phosphorylation datasets across multiple conditions. Researchers then must infer kinases responsible for changes in phosphosites of each substrate. Ho

Vincent Holst, Andres Algaba, Floriano Tori, Sylvia Wenmackers

Park et al. [1] reported a decline in the disruptiveness of scientific and technological knowledge over time. Their main finding is based on the computation of CD indices, a measure of disruption in citation networks [2], across almost 45 million papers and 3.9 million patents. Due to a factual plotting mistake, database entries with zero references were omi

Agustinus Kristiadi, Felix Strieth-Kalthoff, Marta Skreta, Pascal Poupart

Automation is one of the cornerstones of contemporary material discovery. Bayesian optimization (BO) is an essential part of such workflows, enabling scientists to leverage prior domain knowledge into efficient exploration of a large molecular space. While such prior knowledge can take many forms, there has been significant fanfare around the ancillary scien

Michael Correll, Laura A. Garrison

With changing attitudes around knowledge, medicine, art, and technology, the human body has become a source of information and, ultimately, shareable and analyzable data. Centuries of illustrations and visualizations of the body occur within particular historical, social, and political contexts. These contexts are enmeshed in different so-called data culture

Kevin Kögler, Alexander Shevchenko, Hamed Hassani, Marco Mondelli

Autoencoders are a prominent model in many empirical branches of machine learning and lossy data compression. However, basic theoretical questions remain unanswered even in a shallow two-layer setting. In particular, to what degree does a shallow autoencoder capture the structure of the underlying data distribution? For the prototypical case of the 1-bit com

Amir K. Khandani

This article presents a novel method for establishing an information theoretically secure encryption key over wireless channels. It exploits the fact that data transmission over wireless links is accompanied by packet error, while noise terms, and thereby the error events observed by two separate receivers are independent of each other. A number of data pack

Yuchen Zhang, Tianle Zhang, Kai Wang, Ziyao Guo

Graph condensation aims to reduce the size of a large-scale graph dataset by synthesizing a compact counterpart without sacrificing the performance of Graph Neural Networks (GNNs) trained on it, which has shed light on reducing the computational cost for training GNNs. Nevertheless, existing methods often fall short of accurately replicating the original gra

Petra Heck

AI systems cannot exist without data. Now that AI models (data science and AI) have matured and are readily available to apply in practice, most organizations struggle with the data infrastructure to do so. There is a growing need for data engineers that know how to prepare data for AI systems or that can setup enterprise-wide data architectures for analytic

Jannis Kreß, Jens Rau, Ingo Behr, Bernd Mohn

This paper investigates the optimization of the exhaust gas composition by applying a velocity-controlled Throttle-by-Wire-System on modern 50 cc scooters (Euro 5). Nowadays combustion-powered scooters are still inefficiently restricted, resulting in an unreasonably high fuel consumption and unfavorable exhaust emissions. The velocity control prevents restri

Hang Zhou, Ke Ma, Xiaopeng Li

This paper presents a comprehensive review of trajectory data of Advanced Driver Assistance System equipped-vehicle, with the aim of precisely model of Autonomous Vehicles (AVs) behavior. This study emphasizes the importance of trajectory data in the development of AV models, especially in car-following scenarios. We introduce and evaluate several datasets:

Zhuoyang Zhang, Han Cai, Song Han

We present EfficientViT-SAM, a new family of accelerated segment anything models. We retain SAM's lightweight prompt encoder and mask decoder while replacing the heavy image encoder with EfficientViT. For the training, we begin with the knowledge distillation from the SAM-ViT-H image encoder to EfficientViT. Subsequently, we conduct end-to-end training on th

Tanmay Surve, Romila Pradhan

Tree-based machine learning models, such as decision trees and random forests, have been hugely successful in classification tasks primarily because of their predictive power in supervised learning tasks and ease of interpretation. Despite their popularity and power, these models have been found to produce unexpected or discriminatory outcomes. Given their o

Jingbang Chen, Qiuyang Mang, Hangrui Zhou, Richard Peng

Signed networks, characterized by edges labeled as either positive or negative, offer nuanced insights into interaction dynamics beyond the capabilities of unsigned graphs. Central to this is the task of identifying the maximum balanced subgraph, crucial for applications like polarized community detection in social networks and portfolio analysis in finance.

M. Dolgushev, T. V. Mendes, B. Gorin, K. Xie

Splitting probabilities quantify the likelihood of a given outcome out of competitive events. This key observable of random walk theory, historically introduced as the gambler's ruin problem, is well understood for memoryless (Markovian) processes. However, in complex systems such as polymer fluids, the motion of a particle should typically be described as a

Peihong Yuan, Ken R. Duffy, Muriel Médard

We present a framework that can exploit the tradeoff between the undetected error rate (UER) and block error rate (BLER) of polar-like codes. It is compatible with all successive cancellation (SC)-based decoding methods and relies on a novel approximation that we call codebook probability. This approximation is based on an auxiliary distribution that mimics

Xinghan Li, Haoying Li, Guangyang Zeng, Qingcheng Zeng

A filter for inertial-based odometry is a recursive method used to estimate the pose from measurements of ego-motion and relative pose. Currently, there is no known filter that guarantees the computation of a globally optimal solution for the non-linear measurement model. In this paper, we demonstrate that an innovative filter, with the state being $SE_2(3)$

Adrien Devolder, Timur V. Tscherbul, Paul Brumer

Interference is widely regarded as a foundational attribute of quantum mechanics. However, for a given experimental arrangement, interference can either contribute or not contribute to the outcome depending upon the basis in which it is measured. This observation is both foundational and particularly relevant to coherent control of molecular processes, an ap

Shashank Sonkar, Kangqi Ni, Sapana Chaudhary, Richard G. Baraniuk

Large Language Models (LLMs), when used in educational settings without pedagogical fine-tuning, often provide immediate answers rather than guiding students through the problem-solving process. This approach falls short of pedagogically best practices and limits their effectiveness as educational tools. We term the objective of training LLMs to emulate effe

Francesco Corso, Giuseppe Russo, Francesco Pierri

Global events like wars and pandemics can intensify online discussions, fostering information sharing and connection among individuals. However, the divisive nature of such events may lead to polarization within online communities, shaping the dynamics of online interactions. Our study delves into the conversations within the largest Italian and French Reddi

D. Santos-Cottin, S. Nasrallah, F. Capitani, P. Simon

We measured the far-infrared reflectivity of a KH2PO4 single crystal up to pressures of 2 GPa in the ferroelectric and paraelectric phases. We find that the nu4 vibrational mode of the PO4 tetrahedron is strongly affected by the applied pressure. At ambient pressure this phonon is destabilized by the presence of the H ions and hence shows a highly damped cha

Andrew Campbell, Jason Yim, Regina Barzilay, Tom Rainforth

Combining discrete and continuous data is an important capability for generative models. We present Discrete Flow Models (DFMs), a new flow-based model of discrete data that provides the missing link in enabling flow-based generative models to be applied to multimodal continuous and discrete data problems. Our key insight is that the discrete equivalent of c

Eighdi Aung, Nicole Abaid, James E. McClure

The flocking of self-propelled particles in heterogeneous environments is relevant to both natural and artificial systems. The Vicsek model is a canonical choice to investigate such systems due to the minimal number of parameters required to define flocking. Prior research on the Vicsek model has investigated the effects of interaction rules, particle speed,

Arnulf Jentzen, Adrian Riekert

Stochastic gradient descent (SGD) optimization methods such as the plain vanilla SGD method and the popular Adam optimizer are nowadays the method of choice in the training of artificial neural networks (ANNs). Despite the remarkable success of SGD methods in the ANN training in numerical simulations, it remains in essentially all practical relevant scenario

Zihan Lin, Dong Chen, Wenlong Lu, Xin Liang

Recently, a novel magnetic phase called altermagnetism has been proposed, ushering in a third distinct magnetic phase beyond ferromagnetism and antiferromagnetism. It is expected that this groundbreaking phase exhibits unique physical properties such as C-paired spin-valley locking, anomalous Hall effect, nontrivial Berry phase, and giant magnetoresistance,

Flavien Gyger, Maximilian Ammenwerth, Renhao Tao, Hendrik Timme

Scaling the size of assembled neutral-atom arrays trapped in optical lattices or optical tweezers is an enabling step for a number of applications ranging from quantum simulations to quantum metrology. However, preparation times increase with system size and constitute a severe bottleneck in the bottom-up assembly of large ordered arrays from stochastically

Tuomas Oikari

The optimal sufficient conditions for the $L^p$-to-$L^q$ compactness of commutators of singular integral operators of both Calder\'on-Zygmund and of rough type are shown in the different exponent ranges $``q>p"$, $``q=p"$ and $``q<p"$ to quickly follow from each other. The approach is through classical compactness interpolation methods. We also present a new

Simone Cantori, Sebastiano Pilati

Recently, deep neural networks have proven capable of predicting some output properties of relevant random quantum circuits, indicating a strategy to emulate quantum computers alternative to direct simulation methods such as, e.g., tensor-network methods. However, the reach of this alternative strategy is not yet clear. Here we investigate if and to what ext

Xiaofu Jin, Wai Tong, Xiaoying Wei, Xian Wang

The global aging trend compels older adults to navigate the evolving digital landscape, presenting a substantial challenge in mastering smartphone applications. While Augmented Reality (AR) holds promise for enhancing learning and user experience, its role in aiding older adults' smartphone app exploration remains insufficiently explored. Therefore, we condu

Mathieu Ouellet, Dani S. Bassett, Lee C. Bassett, Kieran A. Murphy

Prions are misfolded proteins that transmit their structural arrangement to neighboring proteins. In biological systems, prion dynamics can produce a variety of complex functional outcomes. Yet, an understanding of prionic causes has been hampered by the fact that few computational models exist that allow for experimental design, hypothesis testing, and cont

Z. N. Osmanov

By obtaining the assumption that planetary dust particles can escape from the gravitational attraction of a planet, we consider the possibility for the dust grains to leave the star's system by means of the radiation pressure. By taking the typical dust parameters into account, we consider their dynamics and show that they can reach the deep cosmos, taking p

Ciprian Demeter

We introduce two families of inequalities. Large ensemble decoupling is connected to the continuous restriction phenomenon. Tight decoupling is connected to the discrete Restriction conjecture for the sphere. Our investigation opens new grounds and answers some questions.

Javier Pinto, Davide Magri, Paola Valentini, Francisco Palazon

A new and straightforward single-step route to decorate melamine foams with silver nanoparticles (ME/Ag) is proposed.

Adel Javanmard, Matthew Fahrbach, Vahab Mirrokni

This work studies algorithms for learning from aggregate responses. We focus on the construction of aggregation sets (called bags in the literature) for event-level loss functions. We prove for linear regression and generalized linear models (GLMs) that the optimal bagging problem reduces to one-dimensional size-constrained $k$-means clustering. Further, we

T. R. Vishnu, Dibyendu Roy

We investigate heat transport through a one-dimensional open coupled scalar field theory, depicted as a network of harmonic oscillators connected to thermal baths at the boundaries. The non-Hermitian dynamical matrix of the network undergoes a stability-to-instability transition at the exceptional points as the coupling strength between the scalar fields inc

Ahmed A. Elgohary, Sameh A. Eisa

In this paper, we take an initial and novel step toward characterizing the physics of the hovering phenomenon in flapping insects and hummingbirds as a new class of extremum seeking (ES) feedback systems. By characterizing hovering flight in insects and hummingbirds as a natural hovering ES system, we achieve: (1) very simple, (2) stable, (3) model-free, and

Miguel A. Cardona

Let $\mathcal{E}$ be the ideal generated by the $F_\sigma$ measure zero subsets of the reals. The purpose of this survey paper is to study the cardinal characteristics (the additivity, covering number, uniformity, and cofinality) of $\mathcal{E}$.

Ke Di, Shuai Tan, Anyu Cheng, Yinxue Zhao

We present a novel mechanism for generating a wide bandwidth squeezed optical output field in an opto-magnomechanical system. In this system, the magnon (mechanical) mode in the yttrium-iron-garnet crystal is coupled to the microwave field (optical field) through magnetic dipole (radiation pressure) interaction. The magnetostrictive force induced by the yttr

Tobias Clement, Hung Truong Thanh Nguyen, Nils Kemmerzell, Mohamed Abdelaal

This paper presents an approach integrating explainable artificial intelligence (XAI) techniques with adaptive learning to enhance energy consumption prediction models, with a focus on handling data distribution shifts. Leveraging SHAP clustering, our method provides interpretable explanations for model predictions and uses these insights to adaptively refin

Greivin Alfaro Miranda, Leticia F. Cugliandolo, Marco Tarzia

We adapted the SWAP molecular dynamics algorithm for use in lattice Ising spin models. We dressed the spins with a randomly distributed length and we alternated long-range spin exchanges with conventional single spin flip Monte Carlo updates, both accepted with a stochastic rule which respects detailed balance. We show that this algorithm, when applied to th

Hugo Cui, Luca Pesce, Yatin Dandi, Florent Krzakala

In this manuscript, we investigate the problem of how two-layer neural networks learn features from data, and improve over the kernel regime, after being trained with a single gradient descent step. Leveraging the insight from (Ba et al., 2022), we model the trained network by a spiked Random Features (sRF) model. Further building on recent progress on Gauss

Thomas Pöllabauer, Fabian Rücker, Andreas Franek, Felix Gorschlüter

Current state-of-the-art 6d pose estimation is too compute intensive to be deployed on edge devices, such as Microsoft HoloLens (2) or Apple iPad, both used for an increasing number of augmented reality applications. The quality of AR is greatly dependent on its capabilities to detect and overlay geometry within the scene. We propose a synthetically trained

Yihao Li, Ru Zhang, Jianyi Liu

While Large Language Models (LLMs) demonstrate exceptional performance in a multitude of Natural Language Processing (NLP) tasks, they encounter challenges in practical applications, including issues with hallucinations, inadequate knowledge updating, and limited transparency in the reasoning process. To overcome these limitations, this study innovatively pr

Suset Barroso Solares, Javier Pinto, Gabriele Nanni, Despina Fragouli

Fibrous mats with hydrophobic and oleophilic properties have been fabricated and used as absorbents of oil from stable water in oil emulsions.

James C. Osborn

We investigate the effectiveness of tuning HMC parameters using information from the gradients of the HMC acceptance probability with respect to the parameters. In particular, the optimization of the trajectory length and parameters for higher order integrators will be studied in the context of pure gauge and dynamical fermion actions.

Liuqing Chen, Shuhong Xiao, Yunnong Chen, Ruoyu Wu

As Computational Thinking (CT) continues to permeate younger age groups in K-12 education, established CT platforms such as Scratch face challenges in catering to these younger learners, particularly those in the elementary school (ages 6-12). Through formative investigation with Scratch experts, we uncover three key obstacles to children's autonomous Scratc

Daniele Cassani, Minbo Yang, Xinyun Zhang

This paper deals with the following equation $$-\Delta u =K(|x'|, x'')\Big(|x|^{-\alpha}\ast (K(|x'|, x'')|u|^{2^{\ast}_{\alpha}})\Big) |u|^{2^{\ast}_{\alpha}-2}u\quad\mbox{in}\ \mathbb{R}^N,$$ where $N\geq5$, $\alpha>5-\frac{6}{N-2}$, $2^{\ast}_{\alpha}=\frac{2N-\alpha}{N-2}$ is the so-called upper critical exponent in the Hardy-Littlewood-Sobolev inequalit

Serdar Kadıoğlu, Bernard Kleynhans

The goal of this paper is to share our experience in designing and organizing educational competitions with anonymous and (near) real-time leaderboards in both academic and industrial settings. While such competitions serve as a great educational tool and provide participants with hands-on experience, they require significant planning, technical setup, and a

Raphael Saiseau, Henri Truong, Thomas Guérin, Ulysse Delabre

Domain decay is at the heart of the so-called evaporation-condensation Ostwald-ripening regime of phase ordering kinetics, where the growth of large domains occurs at the expense of smaller ones, which are expected to `evaporate'. We experimentally investigate such decay dynamics at the level of a single spherical domain picked from one phase in coexistence

Kaier Liang, Cristian-Ioan Vasile

In this paper, we consider fair assignment of complex requests for Mobility-On-Demand systems. We model the transportation requests as temporal logic formulas that must be satisfied by a fleet of vehicles. We require that the assignment of requests to vehicles is performed in a distributed manner based only on communication between vehicles while ensuring fa

Rosana Montes, Ana M. Sanchez, Pedro Villar, Francisco Herrera

Classic Delphi and Fuzzy Delphi methods are used to test content validity of a data collection tools such as questionnaires. Fuzzy Delphi takes the opinion issued by judges from a linguistic perspective reducing ambiguity in opinions by using fuzzy numbers. We propose an extension named 2-Tuple Fuzzy Linguistic Delphi method to deal with scenarios in which j

Safwan Hossain, Tonghan Wang, Tao Lin, Yiling Chen

We consider the multi-sender persuasion problem: multiple players with informational advantage signal to convince a single self-interested actor to take certain actions. This problem generalizes the seminal Bayesian Persuasion framework and is ubiquitous in computational economics, multi-agent learning, and multi-objective machine learning. The core solution

G. Saxena, P. K. Sharma, Prafulla Saxena

A detailed study of $\alpha$-clusters decay is exhibited by incorporating crucial microscopic nuclear structure information into the estimations of half-life and preformation factor. For the first time, using the k-cross validation approach, two semi-empirical formulas for (i) $\alpha$-decay half-life and (ii) $\alpha$-particle preformation factor, are picke

Andrea Giusti, Andrea Mentrelli, Tommaso Ruggeri

Recently, a non-linear model of viscoelasticity based on Rational Extended Thermodynamics was proposed in [arXiv:2312.05116]. This theory extends the evolution of the viscous stress beyond the linear framework of the Maxwell model to the non-linear realm, provided that the viscous energy function is given. This work aims at establishing a possible constituti

Jacob Siegel, William McGrew, Youssef Hassan, Chun-Chia Chen

We implement coherent delocalization as a tool for improving the two primary metrics of atomic clock performance: systematic uncertainty and instability. By decreasing atomic density with coherent delocalization, we suppress cold-collision shifts and two-body losses. Atom loss attributed to Landau-Zener tunneling in the ground lattice band would compromise c

Piush Aggarwal, Jawar Mehrabanian, Weigang Huang, Özge Alacam

This paper delves into the formidable challenge of cross-domain generalization in multimodal hate meme detection, presenting compelling findings. We provide enough pieces of evidence supporting the hypothesis that only the textual component of hateful memes enables the existing multimodal classifier to generalize across different domains, while the image com

S. Barroso-Solares, M. G. Zahedi, J. Pinto, G. Nanni

Herein we present the fabrication of hydrophobic and oleophilic poly(methyl methacrylate) based nanocomposite fibrous mats with magnetic properties, and their utilization for oil removal from stable water oil emulsions.

Maoyin Lv, Hao Wu

We consider a class of Cahn-Hilliard equation with kinetic rate dependent dynamic boundary conditions that describe possible short-range interactions between the binary mixture and the solid boundary. In the presence of surface diffusion on the boundary, the initial boundary value problem can be viewed as a transmission problem consisting of Cahn-Hilliard ty

Sidra Aleem, Julia Dietlmeier, Eric Arazo, Suzanne Little

Existing domain adaptation (DA) methods often involve pre-training on the source domain and fine-tuning on the target domain. For multi-target domain adaptation, having a dedicated/separate fine-tuned network for each target domain, that retain all the pre-trained model parameters, is prohibitively expensive. To address this limitation, we propose Convolutio

Mostafa Ameli, Jean-Patrick Lebacque, Negin Alisoltani, Ludovic Leclercq

Urban traffic congestion remains a persistent issue for cities worldwide. Recent macroscopic models have adopted a mathematically well-defined relation between network flow and density to characterize traffic states over an urban region. Despite advances in these models, capturing the complex dynamics of urban traffic congestion requires considering the hete

A. Mangu, V. A. Stoica, H. Zheng, T. Yang

A central paradigm of non-equilibrium physics concerns the dynamics of heterogeneity and disorder, impacting processes ranging from the behavior of glasses to the emergent functionality of active matter. Understanding these complex mesoscopic systems requires probing the microscopic trajectories associated with irreversible processes, the role of fluctuation

Sam Patrick

Quantum vortices with more than a single circulation quantum are usually unstable and decay into clusters of smaller vortices. One way to prevent the decay is to place the vortex at the centre of a convergent (draining) fluid flow, which tends to force vortices together. It is found that whilst the primary splitting instability is suppressed in this way (and

Hiroyuki Tajima, Kei Iida, Haozhao Liang

We theoretically investigate a non-relativistic trace anomaly and its impact on the low-temperature equation of state in spatially one-dimensional three-component fermionic systems with a three-body interaction, which exhibit a non-trivial three-body crossover from a bound trimer gas to dense fermionic matter with increasing density. By applying the $G$-matr

Ankita Nandi, Shantanu Chakrabartty, Chetan Singh Thakur

Decoding of Low-Density Parity Check (LDPC) codes can be viewed as a special case of XOR-SAT problems, for which low-computational complexity bit-flipping algorithms have been proposed in the literature. However, a performance gap exists between the bit-flipping LDPC decoding algorithms and the benchmark LDPC decoding algorithms, such as the Sum-Product Algo

Pedro Vianna, Muawiz Chaudhary, Paria Mehrbod, An Tang

Deep neural networks have useful applications in many different tasks, however their performance can be severely affected by changes in the data distribution. For example, in the biomedical field, their performance can be affected by changes in the data (different machines, populations) between training and test datasets. To ensure robustness and generalizat

Lihu Chen, Alexandre Perez-Lebel, Fabian M. Suchanek, Gaël Varoquaux

Large Language Models (LLMs), including ChatGPT and LLaMA, are susceptible to generating hallucinated answers in a confident tone. While efforts to elicit and calibrate confidence scores have proven useful, recent findings show that controlling uncertainty must go beyond calibration: predicted scores may deviate significantly from the actual posterior probab

Filippo Gaia

We obtain a weak formulation of the stationarity condition for the half Dirichlet energy, which can be expressed in terms of a fractional analogous to the Hopf differential. As an application we show that conformal harmonic maps from the disc are precisely the harmonic extensions of stationary points of the half Dirichlet energy on the circle. We also derive

Samuel Kernan Freire, Chaofan Wang, Evangelos Niforatos

Conversational Assistants (CA) are increasingly supporting human workers in knowledge management. Traditionally, CAs respond in specific ways to predefined user intents and conversation patterns. However, this rigidness does not handle the diversity of natural language well. Recent advances in natural language processing, namely Large Language Models (LLMs),

Yongliang Sun, Jinbi Zhang, Yaohua Zhang

Weakly approximable triangulated categories, introduced by Neeman, provide a powerful framework for studying localization phenomena in triangulated categories. In this paper, we establish new localization theorems showing that, under mild assumptions, a recollement of weakly approximable triangulated categories induces short exact sequences on several natura

Ali Amirahmadi, Mattias Ohlsson, Kobra Etminani, Olle Melander

Using electronic health records data and machine learning to guide future decisions needs to address challenges, including 1) long/short-term dependencies and 2) interactions between diseases and interventions. Bidirectional transformers have effectively addressed the first challenge. Here we tackled the latter challenge by masking one source (e.g., ICD10 co

Enrique Martinez-Berti, Antonio-Jose Sanchez-Salmeron, Carlos Ricolfe-Viala

The main goal of this article is to analyze the effect on pose estimation accuracy when using a Kalman filter added to 4-dimensional deformation part model partial solutions. The experiments run with two data sets showing that this method improves pose estimation accuracy compared with state-of-the-art methods and that a Kalman filter helps to increase this

Jonas Wahl, Jakob Runge

Assessing the accuracy of the output of causal discovery algorithms is crucial in developing and comparing novel methods. Common evaluation metrics such as the structural Hamming distance are useful for assessing individual links of causal graphs. However, many state-of-the-art causal discovery methods do not output single causal graphs, but rather their Mar

Shuntaro Tsubouchi

This paper is concerned with the gradient continuity for the parabolic $(1,\,p)$-Laplace equation. In the supercritical case $\frac{2n}{n+2}<p<\infty$, where $n\ge 2$ denotes the space dimension, this gradient regularity result has been proved recently by the author. In this paper, we would like to prove that the same regularity holds even for the subcritica

Wagner A. A. de Moraes

We present necessary and sufficient conditions to have global hypoellipticity for a class of complex-valued coefficient first order evolution equations defined on $\mathbb{T}^1 \times G$, where $G$ is a compact Lie group. First, we show that the global hypoellipticity of the constant coefficient operator related to this operator is a necessary condition, but

O. Galparsoro, R. Pétuya, J. I. Juaristi, C. Crespos

Quasiclassical molecular dynamics simulations are performed to investigate energy dissipation to the (100) and (110) tungsten surfaces upon Eley-Rideal (ER) recombination of H2 and N2. Calculations are carried out within the single adsorbate limit under normal incidence. A generalized Langevin surface oscillator (GLO) scheme is used to simulate the coupling

Tristan Humbert

We combine methods from microlocal analysis and dimension theory to study resonances with largest real part for an Anosov flow with smooth real valued potential. We show that the resonant states are closely related to special systems of measures supported on the stable manifolds introduced by Climenhaga. As a result, we relate the presence of the resonances

Esther Banaian, Raphael Bennett-Tennenhaus, Karin M. Jacobsen, Kayla Wright

We consider certain generalizations of gentle algebras that we call semilinear locally gentle algebras. These rings are examples of semilinear clannish algebras as introduced by the second author and Crawley-Boevey. We generalise the notion of a nodal algebra from work of Burban and Drozd and prove that semilinear gentle algebras are nodal by adapting a theo

Jordan Morris

This paper proposes a machine learning pre-sort stage to traditional supervised learning using Tsetlin Machines. Initially, K data-points are identified from the dataset using an expedited genetic algorithm to solve the maximum dispersion problem. These are then used as the initial placement to run the K-Medoid clustering algorithm. Finally, an expedited gen

Shubham Kanodia, Caleb I. Cañas, Suvrath Mahadevan, Eric B. Ford

Recent discoveries of transiting giant exoplanets around M-dwarf stars (GEMS), aided by the all-sky coverage of TESS, are starting to stretch theories of planet formation through the core-accretion scenario. Recent upper limits on their occurrence suggest that they decrease with lower stellar masses, with fewer GEMS around lower-mass stars compared to solar-

Long Ma, Zhe Liu, Jia Man, Jianyong Li

Short nanopores have various applications in biosensing, desalination, and energy conversion. Here, the modulation of charged exterior surfaces on ionic transport is investigated through simulations with sub-200 nm long nanopores under applied voltages. Detailed analysis of ionic current, electric field strength, and fluid flow inside and outside nanopores r

Esfandiar Nava-Yazdani

The square root velocity transformation provides a convenient and numerically efficient approach to functional and shape data analysis of curves. We study fundamental geometric properties of curves under this transformation. Moreover, utilizing natural geometric constructions, we employ the approach for intrinsic comparison within several classes of surfaces

Vladimir Shpilrain, Bianca Sosnovski

Cayley hash functions are based on a simple idea of using a pair of semigroup elements, A and B, to hash the 0 and 1 bit, respectively, and then to hash an arbitrary bit string in the natural way, by using multiplication of elements in the semigroup. The main advantage of Cayley hash functions compared to, say, hash functions in the SHA family is that when a

Rongwei Xu, Guanfeng Liu, Yan Wang, Xuyun Zhang

Trust plays an essential role in an individual's decision-making. Traditional trust prediction models rely on pairwise correlations to infer potential relationships between users. However, in the real world, interactions between users are usually complicated rather than pairwise only. Hypergraphs offer a flexible approach to modeling these complex high-order

M. Yusuf Şener, Gerhard Kramer, Shlomo Shamai, Ronald Böhnke

A coding scheme with scalar lattices is applied to K-receiver, Gaussian, vector broadcast channels with K independent messages, one for each receiver. The method decomposes each receiver channel into parallel scalar channels with known interference and applies dirty paper coding with a modulo interval, amplitude shift keying (ASK), and probabilistic shaping

Yinghua Qiu, Long Ma

Continuum simulations become an important tool to uncover the mysteries in nanofluidic experiments. However, fluid flow in simulation models is usually unconsidered. Here, systematical simulations are conducted to provide a quantitative understanding of influences from electroosmotic flow (EOF) on ionic transport through nanopores by both types of models wit

R. Kiefe, R. Almeida, J. H. Belo, J. S. Amaral

The adiabatic temperature change ($\Delta T_{ad}$) of a magnetic refrigerant can be indirectly estimated through field ($H$) and temperature ($T$) dependent magnetization ($M$) and specific heat ($C_p$) measurements. A direct integration approach for this estimation is frequently reported, which is an approximation to a rigorous mathematical approach. In thi

Nouf Alghamdi, Mal Horsburgh, Bakhtier Vasiev

The emergence of the phenomenon known as ABR (anti-bacterial resistance), is the result of the gradual decrease in the efficacy of antibiotics and the increase in the cost of producing new antibiotics. Hence, alternative solutions to prevent the spread of the pathogenic species are required. Here we present a combined experimental and mathematical study of t

Jennifer Hernández-Bécares, Luis Costero, Pedro Pablo Gómez-Martín

Videogames developed in the 1970s and 1980s were modest programs created in a couple of months by a single person, who played the roles of designer, artist and programmer. Since then, videogames have evolved to become a multi-million dollar industry. Today, AAA game development involves hundreds of people working together over several years. Management and e

Jessica Pater, Shaan Chopra, Juliette Zaccour, Jeanne Carroll

COVID Long Haul (CLH) is an emerging chronic illness with varied patient experiences. Our understanding of CLH is often limited to data from electronic health records (EHRs), such as diagnoses or problem lists, which do not capture the volatility and severity of symptoms or their impact. To better understand the unique presentation of CLH, we conducted a 3-m

Francesco Petiziol, Florian Mintert, Sandro Wimberger

We review a scheme for the systematic design of quantum control protocols based on shortcuts to adiabaticity in few-level quantum systems. The adiabatic dynamics is accelerated by introducing high-frequency modulations in the control Hamiltonian, which mimic a time-dependent counterdiabatic correction. We present a number of applications for the high-fidelit

Neil Olver, Leon Sering, Laura Vargas Koch

We consider a dynamic model of traffic that has received a lot of attention in the past few years. Infinitesimally small agents aim to travel from a source to a destination as quickly as possible. Flow patterns vary over time, and congestion effects are modeled via queues, which form based on the deterministic queueing model whenever the inflow into a link e

Daniel M. Anderson, Rayanne A. Luke

In this work we develop and investigate mathematical and computational models that describe drug delivery from a contact lens during wear. Our models are designed to predict the dynamics of drug release from the contact lens and subsequent transport into the adjacent pre-lens tear film and post-lens tear film as well as into the ocular tissue (e.g. cornea),

Anthony W. Wickstead

A representational approach to constructing the Fremlin tensor product of two Archimedean Riesz spaces. [Warning: do not view the HTML version!]

Biyonka Liang, Lily Xu, Aparna Taneja, Milind Tambe

Public health programs often provide interventions to encourage program adherence, and effectively allocating interventions is vital for producing the greatest overall health outcomes, especially in underserved communities where resources are limited. Such resource allocation problems are often modeled as restless multi-armed bandits (RMABs) with unknown und

Hannah Alpert

Consider a closed manifold $M$ with two Riemannian metrics: one hyperbolic metric, and one other metric $g$. What hypotheses on $g$ guarantee that for a given radius $r$, there are balls of radius $r$ in the universal cover of $(M, g)$ with greather-than-hyperbolic volumes? We show that this conclusion holds for all $r \geq 1$ if $(\mathrm{Vol} (M, g))^2$ is

Hoang-Oanh Le, Van Bang Le

The well-known Cluster Vertex Deletion problem (CVD) asks for a given graph $G$ and an integer $k$ whether it is possible to delete a set $S$ of at most $k$ vertices of $G$ such that the resulting graph $G-S$ is a cluster graph (a disjoint union of cliques). We give a complete characterization of graphs $H$ for which CVD on $H$-free graphs is polynomially so

Xingchang Huang, Corentin Salaün, Cristina Vasconcelos, Christian Theobalt

Most of the existing diffusion models use Gaussian noise for training and sampling across all time steps, which may not optimally account for the frequency contents reconstructed by the denoising network. Despite the diverse applications of correlated noise in computer graphics, its potential for improving the training process has been underexplored. In this

Shivang Chopra, Suraj Kothawade, Houda Aynaou, Aman Chadha

This paper introduces a novel approach to leverage the generalizability of Diffusion Models for Source-Free Domain Adaptation (DM-SFDA). Our proposed DMSFDA method involves fine-tuning a pre-trained text-to-image diffusion model to generate source domain images using features from the target images to guide the diffusion process. Specifically, the pre-traine

Fenhong Song, Xuan An, Long Ma, Jiakun Zhuang

Besides the dominant NaCl, natural seawater/river water contains trace multivalent ions, which can provide effective screening to surface charges. Here, in both negatively and positively charged nanopores, influences from divalent ions as counterions and coions have been investigated on the performance of osmotic energy conversion (OEC) under natural salt gr

T. Makai, F. Polito, L. Sacerdote

We consider the open problem concerning the possible lack of concentration of the degree distribution in preferential attachment graphs with random initial degree, when its distribution is characterized by extremely heavy tails of power-law type. We show that the addition of such a large number of edges causes a significant upset of the degree distribution,