May 2022 arXiv papers — page 119

M. J. Dunwoody

The first version of this paper gave another proof of the Kropholler Conjecture, which gives a relative version of Stallings Ends Theorem, following an earlier incorrect proof. It has been pointed out by Sam Shepherd that the the second proof was still inadequate. We explain the difficulty and possible ways to obtain a correct proof.

Robin J. Kwik, Jinfei Wang, Pauline Barmby, Benne W. Holwerda

Automating classification of galaxy components is important for understanding the formation and evolution of galaxies. Traditionally, only the larger galaxy structures such as the spiral arms, bulge, and disc are classified. Here we use machine learning (ML) pixel-by-pixel classification to automatically classify all galaxy components within digital imagery

David Geleßus, Michael Leuschel

Even though the core of the Prolog programming language has been standardized by ISO since 1995, it remains difficult to write complex Prolog programs that can run unmodified on multiple Prolog implementations. Indeed, implementations sometimes deviate from the ISO standard and the standard itself fails to cover many features that are essential in practice.

Sheryl A. Singerling, Larry R. Nittler, Jens Barosch, Elena Dobrica

We investigated six presolar grains from very primitive regions of the matrix in the unequilibrated ordinary chondrite Semarkona with TEM. These grains include one SiC, one oxide (Mg-Al spinel), and four silicates. Structural and elemental compositional studies of presolar grains located within their meteorite hosts have the potential to provide information

Daniel J. G. Pearce

In two dimensional nematics, topological defects are point like singularities with both a charge and a phase. We study topological defects within curved nematic textures on the surface of a cylinder. This allows us to isolate the effect of extrinsic curvature on the structure of the topological defect. By minimizing the energy associated with distortions in

Julien Barré, Bastien Fernandez, Grégoire Panel

We investigate the large population dynamics of a family of stochastic particle systems with three-state cyclic individual behaviour and parameter-dependent transition rates. On short time scales, the dynamics turns out to be approximated by an integrable Hamiltonian system whose phase space is foliated by periodic trajectories. This feature suggests to cons

Tung T. Vu, Hien Quoc Ngo, Minh N. Dao, Michail Matthaiou

This letter considers the development of transmission strategies for the downlink of massive multiple-input multiple-output networks, with the objective of minimizing the completion time of the transmission. Specifically, we introduce a session-based scheme that splits time into sessions and allocates different rates in different sessions for the different u

Zeeshan Nisar, Jelica Vasiljević, Pierre Gançarski, Thomas Lampert

Domain shift in digital histopathology can occur when different stains or scanners are used, during stain translation, etc. A deep neural network trained on source data may not generalise well to data that has undergone some domain shift. An important step towards being robust to domain shift is the ability to detect and measure it. This article demonstrates

Daniel N. Levitin

For a metric space $X$ with a compatible measure $\mu$, Genevois and Tessera defined the Scaling Group of $(X,\mu)$ as the subgroup $\Gamma$ of $\mathbb{R}_{>0}$ of positive real numbers $\gamma$ for which there are quasi-isometries of $X$ coarsely scaling $\mu$ by a factor of $\gamma$. We show that for any finitely generated subgroup $\Gamma$ of $\mathbb{R}

Zihan Wang, Gang Wu, Yan Wang

It is not accurate to make recommendations only based one single current session. Therefore, multi-session-based recommendation(MSBR) is a solution for the problem. Compared with the previous MSBR models, we have made three improvements in this paper. First, the previous work choose to use all the history sessions of the user and/or of his similar users. Whe

Thomas Alazard, Martina Magliocca, Nicolas Meunier

We study an incompressible Darcy's free boundary problem, recently introduced in [22]. Our goal is to prove the existence of non-trivial traveling wave solutions and thus validate the interest of this model to describe cell motility. The model equations include a convection diffusion equation for the polarity marker concentration and the incompressible Darcy

Damián Gvirtz-Chen, Zhizhong Huang

A conjecture by Corvaja and Zannier predicts that smooth, projective, simply connected varieties over a number field with Zariski dense set of rational points have the Hilbert Property; this was proved by Demeio for Kummer surfaces which are associated to products of two elliptic curves. In this article, over a finitely generated field of characteristic zero

Chia-Wen Kuo, Zsolt Kira

Significant progress has been made on visual captioning, largely relying on pre-trained features and later fixed object detectors that serve as rich inputs to auto-regressive models. A key limitation of such methods, however, is that the output of the model is conditioned only on the object detector's outputs. The assumption that such outputs can represent a

Jason Harris, Danny Driess, Marc Toussaint

Hierarchical coordination of controllers often uses symbolic state representations that fully abstract their underlying low-level controllers, treating them as "black boxes" to the symbolic action abstraction. This paper proposes a framework to realize robust behavior, which we call Feasibility-based Control Chain Coordination (FC$^3$). Our controllers expos

Sina Sajjadi, Pourya Toranj Simin, Mehrzad Shadmangohar, Basak Taraktas

During the COVID-19 pandemic, we witnessed a disproportionate infection rate among marginalized and low-income groups. Despite empirical evidence suggesting that structural inequalities in society contribute to health disparities, there has been little attempt to offer a computational and theoretical explanation to establish its plausibility and quantitative

Romain Pic, Clément Dombry, Philippe Naveau, Maxime Taillardat

The theoretical advances on the properties of scoring rules over the past decades have broadened the use of scoring rules in probabilistic forecasting. In meteorological forecasting, statistical postprocessing techniques are essential to improve the forecasts made by deterministic physical models. Numerous state-of-the-art statistical postprocessing techniqu

Matthew Ivory

When writing software code, developers typically prioritise functionality over security, either consciously or unconsciously through biases and heuristics. This is often attributed to tangible pressures such as client requirements, but little is understood about the psychological dimensions affecting security behaviours. There is an increasing demand for und

Conrad Sanderson, Qinghua Lu, David Douglas, Xiwei Xu

As the deployment of artificial intelligence (AI) is changing many fields and industries, there are concerns about AI systems making decisions and recommendations without adequately considering various ethical aspects, such as accountability, reliability, transparency, explainability, contestability, privacy, and fairness. While many sets of AI ethics princi

Marco Buzzelli, Simone Bianco, Paolo Napoletano

We present a unified deep learning framework for the recognition of user identity and the recognition of imagined actions, based on electroencephalography (EEG) signals, for application as a brain-computer interface. Our solution exploits a novel shifted subsampling preprocessing step as a form of data augmentation, and a matrix representation to encode the

Sebastian Hube, Roxana Pohlmann, Stefanie Elgeti

A key step during industrial design is the passing of design information from computer aided design (CAD) to analysis tools (CAE) and vice versa. Here, one is faced with a severe incompatibility in geometry representation: While CAD is usually based on surface representations, analysis mostly relies on volumetric representations. The forward pass, i.e., conv

Kirk Baker

Stemming is the process of reducing related words to a standard form by removing affixes from them. Existing algorithms vary with respect to their complexity, configurability, handling of unknown words, and ability to avoid under- and over-stemming. This paper presents a fast, simple, configurable, high-precision, high-recall stemming algorithm that combines

Mathieu Souzy, Alvaro Marin

Forcing dense suspensions of non-cohesive particles through constrictions might either result in a continuous flow, an intermittent one, or indefinite interruption of flow, i.e., a clog. While one of the most important (and obvious) controlling parameters in such a system is the neck-to-particle size ratio, the role of the liquid driving method is not so obv

Jie Fang, Zi-Hao Chen, Yu Su, Zi-Fan Zhu

Excitation energy transfer (EET) and electron transfer (ET) are crucially involved in photosynthetic processes. In reality, the photosynthetic reaction center constitutes an open quantum system of EET and ET, which manifests an interplay of pigments, solar light and phonon baths. So far theoretical studies have been mainly based on master equation approaches

Jia Li, Shiva Nejati, Mehrdad Sabetzadeh

Internet of Things (IoT) is a pivotal technology in application domains that require connectivity and interoperability between large numbers of devices. IoT systems predominantly use a software-defined network (SDN) architecture as their core communication backbone. This architecture offers several advantages, including the flexibility to make IoT networks s

Francesco Lin

We describe a relationship between the monopole Floer homology of three-manifolds and the geometry of Riemann surfaces. Consider an automorphism $\varphi$ of a compact Riemann surface $\Sigma$ with quotient $\mathbb{P}^1$. There is a natural correspondence between theta characteristics $L$ on $\Sigma$ which are invariant under $\varphi$ and self-conjugate sp

Yitian Zhou, Gaétan Lelu, Boris Labbé, Guillaume Pasquier

Purpose. Ability to locate and track ultrasound images in the 3D operating space is of great benefit for multiple clinical applications. This is often accomplished by tracking the probe using a precise but expensive optical or electromagnetic tracking system. Our goal is to develop a simple and low cost augmented reality echography framework using a standard

Michael J Mahoney, Lucas K Johnson, Abigail Z Guinan, Colin M Beier

Novel plant communities reshape landscapes and pose challenges for land cover classification and mapping that can constrain research and stewardship efforts. In the US Northeast, emergence of low-statured woody vegetation, or shrublands, instead of secondary forests in post-agricultural landscapes is well-documented by field studies, but poorly understood fr

Disrael Camargo Neves da Cunha, Christophe Ringeval, François R. Bouchet

We compute the expected strain power spectrum and energy density parameter of the stochastic gravitational wave background (SGWB) created by a network of long cosmic strings evolving during the whole cosmic history. As opposed to other studies, the contribution of cosmic string loops is discarded and our result provides a robust lower bound of the expected s

Harmeet Singh

We present a study on planar equilibria of a terminally loaded elastic rod wrapped around a rigid circular capstan. Both frictionless and frictional contact between the rod and the capstan are considered. We identify three cases of frictionless contact -- namely where the rod touches the capstan at one point, along a continuous arc, and at two points. We sho

Jing Wang, Yousuf El-Jayyousi, Ilker Ozden

How do humans and animals perform trial-and-error learning when the space of possibilities is infinite? In a previous study, we used an interval timing production task and discovered an updating strategy in which the agent adjusted the behavioral and neuronal noise for exploration. In the experiment, human subjects proactively generated a series of timed mot

Maurizio Ferrari Dacrema, Fabio Moroni, Riccardo Nembrini, Nicola Ferro

Feature selection is a common step in many ranking, classification, or prediction tasks and serves many purposes. By removing redundant or noisy features, the accuracy of ranking or classification can be improved and the computational cost of the subsequent learning steps can be reduced. However, feature selection can be itself a computationally expensive pr

Koki Fusejima, Takuya Ishihara, Masayuki Sawada

Diagnostic tests for regression discontinuity design face a size-control problem. We document a massive over-rejection of the diagnostic restriction among empirical studies in the top five economics journals. At least one diagnostic test was rejected for 19 out of 59 studies, whereas less than 5% of the collected 787 tests rejected the null hypotheses. In ot

Sajal Saha, Anwar Haque, Greg Sidebottom

Efficient prediction of internet traffic is an essential part of Self Organizing Network (SON) for ensuring proactive management. There are many existing solutions for internet traffic prediction with higher accuracy using deep learning. But designing individual predictive models for each service provider in the network is challenging due to data heterogenei

Andreas Triantafyllopoulos, Sandra Ottl, Alexander Gebhard, Esther Rituerto-González

Although running is a common leisure activity and a core training regiment for several athletes, between $29\%$ and $79\%$ of runners sustain an overuse injury each year. These injuries are linked to excessive fatigue, which alters how someone runs. In this work, we explore the feasibility of modelling the Borg received perception of exertion (RPE) scale (ra

Yuya Sato, Hideaki Yamamoto, Hideyuki Kato, Takashi Tanii

Neuronal networks in dissociated culture combined with cell engineering technology offer a pivotal platform to constructively explore the relationship between structure and function in living neuronal networks. Here, we fabricated defined neuronal networks possessing a modular architecture on high-density microelectrode arrays (HD-MEAs), a state-of-the-art e

Weichen Wu, Brian W. Junker, Nynke M. D. Niezink

The Bradley-Terry model is widely used for pairwise comparison data analysis. In this paper, we analyze the asymptotic behavior of the maximum likelihood estimator of the Bradley-Terry model in its logistic parameterization, under a general class of linear identifiability constraints. We show that the constraint requiring the Bradley-Terry scores for all com

Yonglun Jiang, Eric R. Weeks, Nicholas P. Bailey

We have studied shear deformation of binary Lennard-Jones glasses to investigate the extent to which the transient part of the stress strain curves is invariant when the thermodynamic state point is varied along an isomorph. Shear deformations were carried out on glass samples of varying stability, determined by cooling rate, and at varying strain rates, at

Loïc Cordone, Benoît Miramond, Philippe Thierion

Automotive embedded algorithms have very high constraints in terms of latency, accuracy and power consumption. In this work, we propose to train spiking neural networks (SNNs) directly on data coming from event cameras to design fast and efficient automotive embedded applications. Indeed, SNNs are more biologically realistic neural networks where neurons com

Charles Pillet, Valerio Bioglio, Pascal Giard

Automorphism Ensemble (AE) decoding has recently drawn attention as a possible alternative to list decoding of polar codes. In this letter, we investigate the distribution of Partially-Symmetric Reed-Muller (PS-RM) codes, a family of polar codes yielding good performances under AE decoding. We prove the existence of these codes for almost all code dimensions

Hamza Zougheib, Toufic El Arwadi, Mohammad El-Hindi

In this work, we analyze porous elastic system with microtemperature from second spectrum viewpoint. Indeed, by using the classical Faedo-Galerkin method combined with the a priori estimates, we prove the existence and uniqueness of a global solution of this problem. Then we prove that this solution is exponentially stable without assuming the condition of e

Anton Freund

We prove that Higman's lemma is strictly stronger for better quasi orders than for well quasi orders, within the framework of reverse mathematics. In fact, we show a stronger result: the infinite Ramsey theorem (for tuples of all lengths) follows from the statement that any array $[\mathbb N]^{n+1}\to\mathbb N^n\times X$ for a well order $X$ and $n\in\mathbb

Lev Vysotsky, Maxim Rakhuba

In this paper, we are concerned with the inversion of circulant matrices and their quantized tensor-train (QTT) structure. In particular, we show that the inverse of a complex circulant matrix $A$, generated by the first column of the form $(a_0,\dots,a_{m-1},0,\dots,0,a_{-n},\dots, a_{-1})^\top$ admits a QTT representation with the QTT ranks bounded by $(m+

Abhijit Kundu, Kyle Genova, Xiaoqi Yin, Alireza Fathi

We present Panoptic Neural Fields (PNF), an object-aware neural scene representation that decomposes a scene into a set of objects (things) and background (stuff). Each object is represented by an oriented 3D bounding box and a multi-layer perceptron (MLP) that takes position, direction, and time and outputs density and radiance. The background stuff is repr

Sajal Saha, Anwar Haque, Greg Sidebottom

Efficient prediction of internet traffic is essential for ensuring proactive management of computer networks. Nowadays, machine learning approaches show promising performance in modeling real-world complex traffic. However, most existing works assumed that model training and evaluation data came from identical distribution. But in practice, there is a high p

A. Samajdar, G. Shaifullah, A. Sesana, J. Antoniadis

Recently, global pulsar timing arrays have released results from searching for a nano-Hertz gravitational wave background signal. Although there has not been any definite evidence of the presence of such a signal in residuals of pulsar timing data yet, with more and improved data in future, a statistically significant detection is expected to be made. Stocha

Roderich Tumulka

We consider ontological models of a quantum system, assuming that not all probability distributions over the space $\Lambda$ of ontic states are preparable, only those belonging to a certain set C. We assume further that every POVM with a finite value space can be measured and that for every density matrix there exists a distribution in C whose outcome stati

Arnaud Grivet Sébert, Renaud Sirdey, Oana Stan, Cédric Gouy-Pailler

This paper tackles the problem of ensuring training data privacy in a federated learning context. Relying on Homomorphic Encryption (HE) and Differential Privacy (DP), we propose a framework addressing threats on the privacy of the training data. Notably, the proposed framework ensures the privacy of the training data from all actors of the learning process,

Weiyi Yu, Zhizhong Huang, Junping Zhang, Hongming Shan

There are considerable interests in automatic stroke lesion segmentation on magnetic resonance (MR) images in the medical imaging field, as stroke is an important cerebrovascular disease. Although deep learning-based models have been proposed for this task, generalizing these models to unseen sites is difficult due to not only the large inter-site discrepanc

Andreas Triantafyllopoulos, Sandra Zänkert, Alice Baird, Julian Konzok

Stress is a major threat to well-being that manifests in a variety of physiological and mental symptoms. Utilising speech samples collected while the subject is undergoing an induced stress episode has recently shown promising results for the automatic characterisation of individual stress responses. In this work, we introduce new findings that shed light on

Sabrina Patsch, Martin Zeppenfeld, Christiane P. Koch

Non-radiative energy transfer between a Rydberg atom and a polar molecule can be controlled by a DC electric field. Here we show how to exploit this control for state-resolved, non-destructive detection and spectroscopy of the molecules where the lineshape reflects the type of molecular transition. Using the example of ammonia, we identify the conditions for

Wei Dai, Rui Liu, Tianyi Wu, Min Wang

Accurate and unbiased examinations of skin lesions are critical for the early diagnosis and treatment of skin diseases. Visual features of skin lesions vary significantly because the images are collected from patients with different lesion colours and morphologies by using dissimilar imaging equipment. Recent studies have reported that ensembled convolutiona

Marta Sewiło, Agata Karska, Lars E. Kristensen, Steven B. Charnley

We report the first detection of deuterated water (HDO) toward an extragalactic hot core. The HDO 2$_{11}$-2$_{12}$ line has been detected toward hot cores N105-2A and 2B in the N105 star-forming region in the low-metallicity Large Magellanic Cloud (LMC) dwarf galaxy with the Atacama Large Millimeter/submillimeter Array (ALMA). We have compared the HDO line

Abhinav Natarajan, Willem van den Boom, Kristoforus Bryant Odang, Maria De Iorio

Gaussian graphical models are useful tools for conditional independence structure inference of multivariate random variables. Unfortunately, Bayesian inference of latent graph structures is challenging due to exponential growth of $\mathcal{G}_n$, the set of all graphs in $n$ vertices. One approach that has been proposed to tackle this problem is to limit se

Aritra Bhowmick

Given a smooth bracket-generating distribution $\mathcal{D}$ of constant growth on a manifold $M$, we prove that maps from an arbitrary manifold $\Sigma$ to $M$, which are transverse to $\mathcal{D}$, satisfy the complete $h$-principle. This partially settles a question posed by M. Gromov.

Rubén González Sendino, Mónica Ortega, Carlos Carrasco

Nowadays, the way in which the people interact with computers has changed. Text- or voice-based interfaces are being widely applied in different industries. Among the most used ways of processing the user input are those based on intents or retrieval algorithms. In these solutions, important information of the user could be lost in the process. For the propo

Blake Bullwinkel, Kristen Grabarz, Lily Ke, Scarlett Gong

Differentially private (DP) synthetic data is a promising approach to maximizing the utility of data containing sensitive information. Due to the suppression of underrepresented classes that is often required to achieve privacy, however, it may be in conflict with fairness. We evaluate four DP synthesizers and present empirical results indicating that three

Luciano Baresi, Davide Yi Xian Hu, Giovanni Quattrocchi, Luca Terracciano

Nowadays a wide range of applications is constrained by low-latency requirements that cloud infrastructures cannot meet. Multi-access Edge Computing (MEC) has been proposed as the reference architecture for executing applications closer to users and reduce latency, but new challenges arise: edge nodes are resource-constrained, the workload can vary significa

Roman Engelhardt, Patrick Malcolm, Florian Dandl, Klaus Bogenberger

Autonomous mobility on demand services have the potential to disrupt the future mobility system landscape. Ridepooling services in particular can decrease land consumption and increase transportation efficiency by increasing the average vehicle occupancy. Nevertheless, because ridepooling services require a sufficient user base for pooling to take effect, th

Morva Saaty, Jaitun V. Patel, Derek Haqq, Timothy L. Stelter

Social media captures examples of people's behaviors, actions, beliefs, and sentiments. As a result, it can be a valuable source of information and inspiration for HCI research and design. Social media technologies can improve, inform, and strengthen insights to better understand and represent user populations. To understand the position of social media rese

Koichi Hattori, Kazunori Itakura

We investigate in-medium polarization effects of the fermion and antifermion pairs at finite temperature and density in strong magnetic fields within the lowest Landau level approximation. Inspecting the integral representation of the polarization tensor by analytic and numerical methods, we provide both the real and imaginary parts of the polarization tenso

Malú Grave, Alex Viguerie, Gabriel F. Barros, Alessandro Reali

The outbreak of COVID-19, beginning in 2019 and continuing through the time of writing, has led to renewed interest in the mathematical modeling of infectious disease. Recent works have focused on partial differential equation (PDE) models, particularly reaction-diffusion models, able to describe the progression of an epidemic in both space and time. These s

Pierre Ohlmann

We study turn-based quantitative games of infinite duration opposing two antagonistic players and played over graphs. This model is widely accepted as providing the adequate framework for formalizing the synthesis question for reactive systems. This important application motivates the question of strategy complexity: which valuations (or payoff functions) ad

Anirban Ghosh, F. N. U. Shariful, David Wisnosky

Introduced by Callahan and Kosaraju back in 1995, the concept of well-separated pair decomposition (WSPD) has occupied a special significance in computational geometry when it comes to solving distance problems in $d$-space. We present an in-browser tool that can be used to visualize WSPDs and several of their applications in $2$-space. Apart from research,

Chengxu Liu, Bin Li, Yongheng Ge, Wen-He Jiao

The quest for quantum materials with diverse symmetry-protected topological states has been the focus of recent research interest, primarily due to their fascinating physical properties and the potential technological utility. In this work, we report on the magnetotransport, de Haas-van Alphen (dHvA) oscillations, and the first-principles calculations of the

Tomoki Sasada, Kento Yasuda, Yuto Hosaka, Shigeyuki Komura

We investigate the mechanical properties of a layered material with interlayer friction. We propose a model that contains lateral elasticity and interlayer friction to obtain the response function both in the Fourier and real spaces. By investigating how the internal deformation is laterally induced due to the applied surface displacement, we find that it is

Federico Laudisa

The history of the debates on the foundational implications of the Bell non-locality theorem displayed very soon a tendency to put the theorem in a perspective that was not entirely motivated by its very assumptions, in particular in term of a 'local-realistic' narrative, according to which a major target of the theorem would be the very possibility to conce

I. Alekseev, K. Balej, V. Belov, S. Evseev

The nuGeN experiment is aimed to investigate neutrino properties using antineutrinos from the reactor of the Kalinin Nuclear Power Plant. The experimental setup is located at about 11 meters from the center of the 3.1 GWth reactor core. Scattering of the antineutrinos from the reactor is detected with low energy threshold high purity germanium detector. Pass

Punyajoy Saha, Kanishk Singh, Adarsh Kumar, Binny Mathew

Recently, many studies have tried to create generation models to assist counter speakers by providing counterspeech suggestions for combating the explosive proliferation of online hate. However, since these suggestions are from a vanilla generation model, they might not include the appropriate properties required to counter a particular hate speech instance.

Alejandra Aguilera, Daniel Seco

We prove the property that a function is cyclic (resp., non-cyclic) is not preserved by norm convergence in Dirichlet-type spaces $D_\alpha$, and show how other significant quantities for cyclicity do remain preserved under the limit of convergent sequences in $D_\alpha$, providing a quantitative view of this convergence issue.

Bruce Kleiner, Stefan Muller, Xiangdong Xie

We consider Rumin's filtration on the de Rham complex of a Carnot group. Although Pansu pullback by a Sobolev map is filtration preserving, it need not be a chain mapping. Nonetheless, we show that Pansu pullback induces a mapping of the associated spectral sequences. This gives an alternate interpretation of the Pullback Theorem from our previous paper.

Abdon Moutinho

We consider the nonlinear wave equation known as the $\phi^{6}$ model in dimension 1+1. We describe the long time behavior of all the solutions of this model close to a sum of two kinks with energy slightly larger than twice the minimum energy of non constant stationary solutions. We prove orbital stability of two moving kinks. We show for low energy excess

Han Wang, Jing Ying Ko, Lihua Xie

Simultaneous Localization and Mapping (SLAM) is one of the most essential techniques in many real-world robotic applications. The assumption of static environments is common in most SLAM algorithms, which however, is not the case for most applications. Recent work on semantic SLAM aims to understand the objects in an environment and distinguish dynamic infor

Shuhao Jiao, Ngai-Hang Chan, Chun-Yip Yau

A new dimension reduction methodology for change-point detection in functional means is developed in this paper. The major advantage and novelty of the proposed method is its efficiency in selecting basis functions that capture the change, or jump, of functional means, leading to higher detection power, especially when the functions cannot be sufficiently ex

Sung-Soo Byun, Christophe Charlier

We study the characteristic polynomial $p_{n}(x)=\prod_{j=1}^{n}(|z_{j}|-x)$ where the $z_{j}$ are drawn from the Mittag-Leffler ensemble, i.e. a two-dimensional determinantal point process which generalizes the Ginibre point process. We obtain precise large $n$ asymptotics for the moment generating function $\mathbb{E}[e^{\frac{u}{\pi} \, \mathrm{Im} \ln p_

Harel Berger, Amit Dvir, Chen Hajaj, Rony Ronen

Android malware is a spreading disease in the virtual world. Anti-virus and detection systems continuously undergo patches and updates to defend against these threats. Most of the latest approaches in malware detection use Machine Learning (ML). Against the robustifying effort of detection systems, raise the \emph{evasion attacks}, where an adversary changes

Suresh Kumar, Rafael C. Nunes, Priya Yadav

Using the latest observational data from Planck-CMB and its combination with the pre-reconstructed full-shape (FS) galaxy power spectrum measurements from the BOSS DR12 sample and eBOSS LRG DR16 sample, we report the observational constraints on the cosmic neutrino properties given by the extended $\Lambda$CDM scenario: $\Lambda$CDM + $N_{\rm eff}$ + $\sum m

Juan Camilo Buitrago-Casas, Lindsay Glesener, Steven Christe, Säm Krucker

Solar nanoflares are small eruptive events releasing magnetic energy in the quiet corona. If nanoflares follow the same physics as their larger counterparts, they should emit hard X-rays (HXRs) but with a rather faint intensity. A copious and continuous presence of nanoflares would deliver enormous amounts of energy into the solar corona, possibly accounting

Huaxin Wang-Lu

The evolution of the pandemic and people's concern over it have an impact on the Bitcoin market, while the extent of individualism could differentiate investor behaviors in the financial market during the pandemic. This paper examines whether public attention to COVID-19 in individualistic countries versus collectivistic countries Granger causes Bitcoin retu

Stevo Racković, Cláudia Soares, Dušan Jakovetić, Zoranka Desnica

Automated methods for facial animation are a necessary tool in the modern industry since the standard blendshape head models consist of hundreds of controllers and a manual approach is painfully slow. Different solutions have been proposed that produce output in real-time or generalize well for different face topologies. However, all these prior works consid

Maryam Zamani, Sander Paekivi, Philipp Meyer, Holger Kantz

We analyze the interaction between stock prices of big companies in the USA and Germany using Granger Causality. We claim that the increase in pair-wise Granger causality interaction between prices in the times of crisis is the consequence of simultaneous response of the markets to the outside events or external stimulus that is considered as a common driver

Christopher Townsend, Maria M. Seron, Nicolas Magdelaine

We characterise the bolus insulin input which minimises the maximum plasma glucose concentration predicted by the Magdelaine and Bergman minimal models in response to any positive bounded disturbance whilst remaining above a fixed lower plasma glucose concentration. This characterisation is in terms of the maxima and minima of the plasma glucose concentratio

Emmanuel Filiot, Ismaël Jecker, Christof Löding, Sarah Winter

The notion of delay between finite transducers is a core element of numerous fundamental results of transducer theory. The goal of this work is to provide a similar notion for more complex abstract machines: we introduce a new notion of delay tailored to measure the similarity between streaming string transducers (SST). We show that our notion is regular: we

Pavel V. Ratnikov

The problem of screening the Coulomb interaction between charge carriers in type II heterostructures based on transition metal dichalcogenides is Analytically solved. At a sufficiently high density of charge carriers, the density dependence of the interlayer exciton energy is obtained. The energy of the interlayer exciton tends to zero in the metal--insulato

Sayan Das, Zoe Himwich, Nitya Mani

Given a graph sequence $\{G_n\}_{n\ge1}$ and a simple connected subgraph $H$, we denote by $T(H,G_n)$ the number of monochromatic copies of $H$ in a uniformly random vertex coloring of $G_n$ with $c \ge 2$ colors. In this article, we prove a central limit theorem for $T(H,G_n)$ with explicit error rates. The error rates arise from graph counts of collections

Eduardo Nuno Almeida, Mohammed Rushad, Sumanth Reddy Kota, Akshat Nambiar

The creation of digital twins of experimental testbeds allows the validation of novel wireless networking solutions and the evaluation of their performance in realistic conditions, without the cost, complexity and limited availability of experimental testbeds. Current trace-based simulation approaches for ns-3 enable the repetition and reproduction of the sa

Ziv Goldfeld, Kengo Kato, Gabriel Rioux, Ritwik Sadhu

Optimal transport (OT) is a versatile framework for comparing probability measures, with many applications to statistics, machine learning, and applied mathematics. However, OT distances suffer from computational and statistical scalability issues to high dimensions, which motivated the study of regularized OT methods like slicing, smoothing, and entropic pe

Junya Sato, Yuki Suzuki, Tomohiro Wataya, Daiki Nishigaki

Large numbers of labeled medical images are essential for the accurate detection of anomalies, but manual annotation is labor-intensive and time-consuming. Self-supervised learning (SSL) is a training method to learn data-specific features without manual annotation. Several SSL-based models have been employed in medical image anomaly detection. These SSL met

Changhong Fu, Kunhan Lu, Guangze Zheng, Junjie Ye

Unmanned aerial vehicle (UAV)-based visual object tracking has enabled a wide range of applications and attracted increasing attention in the field of intelligent transportation systems because of its versatility and effectiveness. As an emerging force in the revolutionary trend of deep learning, Siamese networks shine in UAV-based object tracking with their

Nikhil Kumar Tomar, Debesh Jha, Ulas Bagci, Sharib Ali

Colonoscopy is a gold standard procedure but is highly operator-dependent. Automated polyp segmentation, a precancerous precursor, can minimize missed rates and timely treatment of colon cancer at an early stage. Even though there are deep learning methods developed for this task, variability in polyp size can impact model training, thereby limiting it to th

Anton Korinek, Avital Balwit

As artificial intelligence (AI) becomes more powerful and widespread, the AI alignment problem - how to ensure that AI systems pursue the goals that we want them to pursue - has garnered growing attention. This article distinguishes two types of alignment problems depending on whose goals we consider, and analyzes the different solutions necessitated by each

Pavel V. Ratnikov

The possibility of the formation of an electron-hole liquid in the type II heterostructures based on monolayers (bilayers) of transition metal dichalcogenides is considered. It is indicated that additional valleys in the conduction band, which are present in bilayers, are required for its observation. The binding energy of the interlayer exciton is found by

Amaya Moro-Martín

During the formation of our solar system, a large number of planetesimals were ejected into interstellar space by gravitational encounters with the planets. Debris disks observations and numerical simulations indicate that many other planetary systems, now known to be quite common, would have undergone a similar dynamical clearing process. It is therefore ex

Ernst Seidel, Rasmus Kongsgaard Olsson, Karim Haddad, Zhengyang Li

Although today's speech communication systems support various bandwidths from narrowband to super-wideband and beyond, state-of-the art DNN methods for acoustic echo cancellation (AEC) are lacking modularity and bandwidth scalability. Our proposed DNN model builds upon a fully convolutional recurrent network (FCRN) and introduces scalability over various ban

Luyu Gao, Jamie Callan

Long document re-ranking has been a challenging problem for neural re-rankers based on deep language models like BERT. Early work breaks the documents into short passage-like chunks. These chunks are independently mapped to scalar scores or latent vectors, which are then pooled into a final relevance score. These encode-and-pool methods however inevitably in

Shivam Sharma, Firoj Alam, Md. Shad Akhtar, Dimitar Dimitrov

The automatic identification of harmful content online is of major concern for social media platforms, policymakers, and society. Researchers have studied textual, visual, and audio content, but typically in isolation. Yet, harmful content often combines multiple modalities, as in the case of memes, which are of particular interest due to their viral nature.

Alex Alarcon, Andrew P. Hearin, Matthew R. Becker, Jonás Chaves-Montero

We present Diffstar, a smooth parametric model for the in-situ star formation history (SFH) of galaxies. Diffstar is distinct from conventional SFH models that are used to interpret the spectral energy distribution (SED) of an observed galaxy, because our model is parametrized directly in terms of basic features of galaxy formation physics. The Diffstar mode

Björn de Rijk

We present a nonlinear stability theory for periodic wave trains in reaction-diffusion systems, which relies on pure $L^\infty$-estimates only. Our analysis shows that localization or periodicity requirements on perturbations, as present in the current literature, can be completely lifted. Inspired by previous works considering localized perturbations, we de

P. V. Ratnikov, A. P. Silin

The effect of doping on the parameters of an electron-hole liquid (EHL) in heterostructures based on transition metal dichalcogenides is studied. The phase diagram of the EHL is constructed. It is shown that for the formation of a high-temperature tightly bound EHL, as well as for the transition from the semiconducting (exciton) state to the semimetallic one

D. G. Vlaykov, I. Baraffe, T. Constantino, T. Goffrey

Stellar convection is a non-local process responsible for the transport of heat and chemical species. It can lead to enhanced mixing through convective overshooting and excitation of internal gravity waves (IGWs) at convective boundaries. The relationship between these processes is still not well understood and requires global hydrodynamic simulations to cap

Hervé Déjean, Stéphane Clinchant, Jean-Luc Meunier

This paper investigates the Relation Extraction task in documents by benchmarking two different neural network models: a multi-modal language model (LayoutXLM) and a Graph Neural Network: Edge Convolution Network (ECN). For this benchmark, we use the XFUND dataset, released along with LayoutXLM. While both models reach similar results, they both exhibit very