March 2023 arXiv papers — page 97

Kaushiki Mukherjee

Correlations in quantum networks with independent sources exhibit a completely novel form of nonclassicality in the sense that the nonlocality of such correlations can be demonstrated in fixed local input scenarios. Before the pioneering work by M.O.Renou, et al., in [1], the nonlocal feature of such network correlations was directly attributable to standard

Apoorva D. Patel

The quantum density matrix generalises the classical concept of probability distribution to quantum theory. It gives the complete description of a quantum state as well as the observable quantities that can be extracted from it. Its mathematical structure is described, with applications to understanding quantum correlations, illustrating quantum chaos and it

Taras Kucherenko, Pieter Wolfert, Youngwoo Yoon, Carla Viegas

This paper reports on the second GENEA Challenge to benchmark data-driven automatic co-speech gesture generation. Participating teams used the same speech and motion dataset to build gesture-generation systems. Motion generated by all these systems was rendered to video using a standardised visualisation pipeline and evaluated in several large, crowdsourced

Kianusch Vahid Yousefnia, Tobias Bölle, Isabella Zöbisch, Thomas Gerz

Thunderstorms pose a major hazard to society and economy, which calls for reliable thunderstorm forecasts. In this work, we introduce a Signature-based Approach of identifying Lightning Activity using MAchine learning (SALAMA), a feedforward neural network model for identifying thunderstorm occurrence in numerical weather prediction (NWP) data. The model is

Zayd Omar, David A. Stephens, Alexandra M. Schmidt, David L. Buckeridge

We propose a multivariate GARCH model for non-stationary health time series by modifying the variance of the observations of the standard state space model. The proposed model provides an intuitive way of dealing with heteroskedastic data using the conditional nature of state space models. We follow the Bayesian paradigm to perform the inference procedure. I

J. Alfredo Collazos

Neutron stars are one of the most extreme objects in the universe, with densities that can exceed those of atomic nuclei and gravitational fields that are among the strongest known. Theoretical and observational research on neutron stars has revealed a wealth of information about their structural characteristics and physical properties. The structural charac

Beiqi Zhang, Peng Liang, Xiyu Zhou, Aakash Ahmad

With the advances in machine learning, there is a growing interest in AI-enabled tools for autocompleting source code. GitHub Copilot, also referred to as the "AI Pair Programmer", has been trained on billions of lines of open source GitHub code, and is one of such tools that has been increasingly used since its launch on June 2021. However, little effort ha

Anna-Carlotta Zarski, Mathias Harrer, Paula Kuper, Antonia A. Sprenger

Genito-Pelvic Pain/Penetration-Disorder (GPPPD) is a common disorder but rarely treated in routine care. Previous research documents that GPPPD symptoms can be treated effectively using internet-based psychological interventions. However, non-response remains common for all state-of-the-art treatments and it is unclear which patient groups are expected to be

Melissa Chapman, Lily Xu, Marcus Lapeyrolerie, Carl Boettiger

From out-competing grandmasters in chess to informing high-stakes healthcare decisions, emerging methods from artificial intelligence are increasingly capable of making complex and strategic decisions in diverse, high-dimensional, and uncertain situations. But can these methods help us devise robust strategies for managing environmental systems under great u

Hui Zhang, Zheng Wang, Dan Zeng, Zuxuan Wu

Anomaly detection has garnered extensive applications in real industrial manufacturing due to its remarkable effectiveness and efficiency. However, previous generative-based models have been limited by suboptimal reconstruction quality, hampering their overall performance. We introduce DiffusionAD, a novel anomaly detection pipeline comprising a reconstructi

Himesh Nandani, Mootez Saad, Tushar Sharma

Researchers apply machine-learning techniques for code smell detection to counter the subjectivity of many code smells. Such approaches need a large, manually annotated dataset for training and benchmarking. Existing literature offers a few datasets; however, they are small in size and, more importantly, do not focus on the subjective code snippets. In this

Alessia Rondinella, Francesco Guarnera, Oliver Giudice, Alessandro Ortis

This paper presents our solution for the first challenge of the 3rd Covid-19 competition, which is part of the "AI-enabled Medical Image Analysis Workshop" organized by IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP) 2023. Our proposed solution is based on a Resnet as a backbone network with the addition of attention mechanis

Choubo Ding, Guansong Pang

Detecting out-of-distribution (OOD) inputs is a principal task for ensuring the safety of deploying deep-neural-network classifiers in open-set scenarios. OOD samples can be drawn from arbitrary distributions and exhibit deviations from in-distribution (ID) data in various dimensions, such as foreground features (e.g., objects in CIFAR100 images vs. those in

Michael Hoffmann, Meghana M. Reddy

A graph is $2$-planar if it has local crossing number two, that is, it can be drawn in the plane such that every edge has at most two crossings. A graph is maximal $2$-planar if no edge can be added such that the resulting graph remains $2$-planar. A $2$-planar graph on $n$ vertices has at most $5n-10$ edges, and some (maximal) $2$-planar graphs -- referred

Eloi Araujo, Fábio V. Martinez, Carlos H. A. Higa, José Soares

Sequence comparison is a basic task to capture similarities and differences between two or more sequences of symbols, with countless applications such as in computational biology. An alignment is a way to compare sequences, where a giving scoring function determines the degree of similarity between them. Many scoring functions are obtained from scoring matri

J. Lerendegui-Marco, A. Casanovas, V. Alcayne, the n_TOF Collaboration

The n_TOF facility has just undergone in 2021 a major upgrade with the installation of its third generation spallation target that has been designed to optimize the performance of the two n_TOF time-of-flight lines. This contribution describes the key features and limitations for capture measurements in the two beam lines prior to the target upgrade and pres

Arnaud Liehrmann, Guillem Rigaill

Given a time series in $R^n$ with a piecewise constant mean and independent noises, we propose an exact dynamic programming algorithm to minimize a least square criterion with a multiscale penalty promoting well-spread changepoints. Such a penalty has been proposed in Verzelen et al. (2020), and it achieves optimal rates for changepoint detection and changep

Chen Xu, Jun Xu, Xu Chen, Zhenghua Dong

Sequential recommender systems train their models based on a large amount of implicit user feedback data and may be subject to biases when users are systematically under/over-exposed to certain items. Unbiased learning based on inverse propensity scores (IPS), which estimate the probability of observing a user-item pair given the historical information, has

Matthew Burtell, Thomas Woodside

Persuasion is a key aspect of what it means to be human, and is central to business, politics, and other endeavors. Advancements in artificial intelligence (AI) have produced AI systems that are capable of persuading humans to buy products, watch videos, click on search results, and more. Even systems that are not explicitly designed to persuade may do so in

Adam Breitholtz, Fredrik D. Johansson

Understanding generalization is crucial to confidently engineer and deploy machine learning models, especially when deployment implies a shift in the data domain. For such domain adaptation problems, we seek generalization bounds which are tractably computable and tight. If these desiderata can be reached, the bounds can serve as guarantees for adequate perf

Jorge Olmos-Trigo, Manuel Nieto-Vesperinas, Gabriel Molina-Terriza

The search for objects that yield maximum electromagnetic chirality in their emitted wavefield has garnered significant attention in recent years. However, achieving such maximum chirality is challenging, as it typically requires complex chiral metamaterials. Here we demonstrate that chiral spheres can yield maximum chirality in their emitted wavefield. Spec

Sara Rojas, Jesus Zarzar, Juan Camilo Perez, Artsiom Sanakoyeu

This paper proposes a novel approach for rendering a pre-trained Neural Radiance Field (NeRF) in real-time on resource-constrained devices. We introduce Re-ReND, a method enabling Real-time Rendering of NeRFs across Devices. Re-ReND is designed to achieve real-time performance by converting the NeRF into a representation that can be efficiently processed by

Wei Jiang, Hans D. Schotten

Intelligent reflecting surface (IRS) has recently received much attention from the research community due to its potential to achieve high spectral and power efficiency cost-effectively. In addition to traditional cellular networks, the use of IRS in vehicular networks is also considered. Prior works on IRS-aided vehicle-to-everything communications focus on

A. Y. Potekhin, M. E. Gusakov, A. I. Chugunov

Thermal emission of neutron stars in soft X-ray transients (SXTs) in a quiescent state is believed to be powered by the heat deposited in the stellar crust due to nuclear reactions during accretion (deep crustal heating paradigm). Confronting observations of SXTs with simulations helps to verify theoretical models of the dense matter in the neutron stars. Us

Jie Liu, Linchao Ding, Liangcai Xu, Xiaokang Li

Co$_3$Sn$_2$S$_2$ is believed to be a magnetic Weyl semimetal. It displays large anomalous Hall, Nernst and thermal Hall effects with a remarkably large anomalous Hall angle. Here, we present a comprehensive study of how substituting Co by Fe or Ni affects the electrical and thermoelectric transport. We find that doping alters the amplitude of the anomalous

Shuyao Shang, Zhengyang Shan, Guangxing Liu, LunQian Wang

Adapting the Diffusion Probabilistic Model (DPM) for direct image super-resolution is wasteful, given that a simple Convolutional Neural Network (CNN) can recover the main low-frequency content. Therefore, we present ResDiff, a novel Diffusion Probabilistic Model based on Residual structure for Single Image Super-Resolution (SISR). ResDiff utilizes a combina

Louie Hong Yao, Mohamed Swailem, Ulrich Dobramysl, Uwe C. Täuber

We apply a perturbative Doi--Peliti field-theoretical analysis to the stochastic spatially extended symmetric Rock-Paper-Scissors (RPS) and May--Leonard (ML) models, in which three species compete cyclically. Compared to the two-species Lotka--Volterra predator-prey (LV) model, according to numerical simulations, these cyclical models appear to be less affec

Sylwia Cichacz

Let $\overrightarrow{G}$ be a directed graph of order $n$ with no component of order less than $4$, and let $\Gamma$ be a finite Abelian group such that $|\Gamma|\geq n+6$. We show that there exists a mapping $\psi$ from the arc set $E(\overrightarrow{G})$ of $\overrightarrow{G}$ to an Abelian group $\Gamma$ such that if we define a mapping $\varphi_{\psi}$

Anderson Kendi Kohara, Cyrille Marquet, Víctor Vila

At leading-order, the standard dilute-dense Color Glass Condensate formula used for two-particle correlations in proton-nucleus collisions, whose symmetries prevent the generation of odd azimuthal anisotropy harmonics, is the dilute projectile limit of the dense-dense formalism. However, when the projectile is genuinely dilute, the complete formulation conta

Daniel Hübner, Fabian Wein, Michael Stingl

Interest in components with detailed structures increased with the progress in advanced manufacturing techniques in recent years. Parts with graded lattice elements can provide interesting mechanical, thermal, and acoustic properties compared to parts where only coarse features are included. One of these improvements is better global buckling resistance of t

Matteo Cardellini, Paolo De Nardi, Carmine Dodaro, Giuseppe Galatà

A core part of the rehabilitation scheduling process consists of planning rehabilitation physiotherapy sessions for patients, by assigning proper operators to them in a certain time slot of a given day, taking into account several legal, medical and ethical requirements and optimizations, e.g., patient's preferences and operator's work balancing. Being able

Artem Fediai, Patrick Reiser, Jorge Enrique Olivares Peña, Pascal Friederich

The QM9 dataset [Scientific Data, Vol. 1, 140022 (2014)] became a standard dataset to benchmark machine learning methods, especially on molecular graphs. It contains geometries as well as multiple computed molecular properties of 133,885 compounds at B3LYP/6-31G(2df,p) level of theory, including frontier orbitals (HOMO and LUMO) energies. However, the accura

Mohammad Alsalti, Victor G. Lopez, Matthias A. Müller

In the context of data-driven control, persistence of excitation (PE) of an input sequence is defined in terms of a rank condition on the Hankel matrix of the input data. For nonlinear systems, recent results employed rank conditions involving collected input and state/output data, for which no guidelines are available on how to satisfy them a priori. In thi

Michael Rogenmoser, Yvan Tortorella, Davide Rossi, Francesco Conti

Space Cyber-Physical Systems (S-CPS) such as spacecraft and satellites strongly rely on the reliability of onboard computers to guarantee the success of their missions. Relying solely on radiation-hardened technologies is extremely expensive, and developing inflexible architectural and microarchitectural modifications to introduce modular redundancy within a

Adamya P. Goyal, Prachi Sharma, Dmitrii L. Maslov

A Dirac metal is a doped (gated) Dirac material with the Fermi energy ($E_\text{F}$) lying either in the conduction or valence bands. In the non-interacting picture, optical absorption in gapless Dirac metals occurs only if the frequency of incident photons ($\Omega$) exceeds the direct (Pauli) frequency threshold, equal to $2E_\text{F}$. In this work, we st

Rui Zhou, Yan Niu

Fusing a sequence of perfectly aligned images captured at various exposures, has shown great potential to approach High Dynamic Range (HDR) imaging by sensors with limited dynamic range. However, in the presence of large motion of scene objects or the camera, mis-alignment is almost inevitable and leads to the notorious ``ghost'' artifacts. Besides, factors

O. A. Veliev

In this paper we investigate the spectrum of the differential operators generated by the ordinary differential expression of odd order with PT-symmertic periodic matrix coefficients

Mohamed Elminshawi, Srikanth Raj Chetupalli, Emanuël A. P. Habets

We propose a Beamformer-guided Target Speaker Extraction (BG-TSE) method to extract a target speaker's voice from a multi-channel recording informed by the direction of arrival of the target. The proposed method employs a front-end beamformer steered towards the target speaker to provide an auxiliary signal to a single-channel TSE system. By allowing for tim

J. Lerendegui-Marco, V. Babiano-Suárez, J. Balibrea-Correa, C. Domingo-Pardo

Neutron capture cross-section measurements are fundamental in the study of astrophysical phenomena, such as the slow neutron capture (s-) process of nucleosynthesis operating in red-giant and massive stars. However, neutron capture measurements via the time-of-flight (TOF) technique on key $s$-process nuclei are often challenging. Difficulties arise from the

Rafael Wagner, Ernesto F. Galvão

The quantum mechanical weak value $A_w=\left\langle \phi|A|\psi \right \rangle / \left\langle \phi | \psi \right\rangle$ of an observable $A$ is a measurable quantity associated with an observable $A$ and pre- and post-selected states $\vert\psi \rangle, \vert \phi \rangle$. Much has been discussed about the meaning and metrological uses of anomalous weak va

Kaushiki Mukherjee, Soma Mandal, Tapaswini Patro, Nirman Ganguly

We study hidden nonlocality in a linear network with independent sources. In the usual paradigm of Bell nonlocality, there are certain states which exhibit nonlocality only after the application of suitable local filtering operations, which, in turn, are some special stochastic local operations assisted with classical communication (SLOCC). In the present wo

Zhicai Wang, Yanbin Hao, Tingting Mu, Ouxiang Li

It is well-known that zero-shot learning (ZSL) can suffer severely from the problem of domain shift, where the true and learned data distributions for the unseen classes do not match. Although transductive ZSL (TZSL) attempts to improve this by allowing the use of unlabelled examples from the unseen classes, there is still a high level of distribution shift.

Canwen Xu, Julian McAuley, Penghan Wang

We present Mirror, an open-source platform for data exploration and analysis powered by large language models. Mirror offers an intuitive natural language interface for querying databases, and automatically generates executable SQL commands to retrieve relevant data and summarize it in natural language. In addition, users can preview and manually edit the ge

Valeria Banica, Luis Vega

We review some recent results concerning the Initial Value Problem of 1d-cubic non-linear Schr\"odinger equation (NLS) and other related systems as the Schr\"odinger Map. For the latter we prove the existence of a cascade of energy. Finally, some new examples of the Talbot effect at the critical level of regularity are given.

Shuja Khalid, Frank Rudzicz

Novel view synthesis (NVS) is a challenging task in computer vision that involves synthesizing new views of a scene from a limited set of input images. Neural Radiance Fields (NeRF) have emerged as a powerful approach to address this problem, but they require accurate knowledge of camera \textit{intrinsic} and \textit{extrinsic} parameters. Traditionally, st

Cedric Aaron Beschle, Andrea Barth

This paper provides a framework in which multilevel Monte Carlo and continuous level Monte Carlo can be compared. In continuous level Monte Carlo the level of refinement is determined by an exponentially distributed random variable, which therefore heavily influences the computational complexity. We propose in this paper a variant of the algorithm, where the

L. Richard, L. Sorriso-Valvo, E. Yordanova, D. B. Graham

We investigate turbulence in magnetic reconnection jets in the Earth's magnetotail using data from the Magnetospheric Multiscale spacecraft. We show that signatures of a limited inertial range are observed in many reconnection jets. The observed turbulence develops on the time scale of a few ion gyroperiods, resulting in intermittent multifractal energy casc

Siqi Fan, Zhe Wang, Yan Wang, Jingjing Liu

For semantic segmentation in urban scene understanding, RGB cameras alone often fail to capture a clear holistic topology in challenging lighting conditions. Thermal signal is an informative additional channel that can bring to light the contour and fine-grained texture of blurred regions in low-quality RGB image. Aiming at practical RGB-T (thermal) segmenta

Julián Tachella, Laurent Jacques

Recent advances in unsupervised learning have highlighted the possibility of learning to reconstruct signals from noisy and incomplete linear measurements alone. These methods play a key role in medical and scientific imaging and sensing, where ground truth data is often scarce or difficult to obtain. However, in practice, measurements are not only noisy and

Ali Rahimi-Kalahroudi, Janarthanan Rajendran, Ida Momennejad, Harm van Seijen

One of the key behavioral characteristics used in neuroscience to determine whether the subject of study -- be it a rodent or a human -- exhibits model-based learning is effective adaptation to local changes in the environment, a particular form of adaptivity that is the focus of this work. In reinforcement learning, however, recent work has shown that moder

Patrick Zimmer, Michael Halstead, Chris McCool

In weed control, precision agriculture can help to greatly reduce the use of herbicides, resulting in both economical and ecological benefits. A key element is the ability to locate and segment all the plants from image data. Modern instance segmentation techniques can achieve this, however, training such systems requires large amounts of hand-labelled data

Ali Abkar

Using partial derivatives $\partial_zf$ and $\partial_{\ol z}f$, we introduce Besov spaces of polyanalytic functions on the unit disk and on the upper half-plane. We then prove that the dilatations of each function in polyanalytic Besov spaces converge to the same function in norm. This opens the way for the norm approximation of functions in polyanalytic Be

Sabira El Khalfaoui, Mathieu Lhotel, Jade Nardi

In this paper, we introduce a family of codes that can be used in a McEliece cryptosystem, called Goppa--like AG codes. These codes generalize classical Goppa codes and can be constructed from any curve of genus $\mathfrak{g} \geq 0$. Focusing on codes from $C_{a,b}$ curves, we study the behaviour of the dimension of the square of their dual to determine the

Runzhou Tao, Wencheng Han, Zhongying Qiu, Cheng-zhong Xu

Monocular 3D object detection has become a mainstream approach in automatic driving for its easy application. A prominent advantage is that it does not need LiDAR point clouds during the inference. However, most current methods still rely on 3D point cloud data for labeling the ground truths used in the training phase. This inconsistency between the training

Shuning Chang, Pichao Wang, Ming Lin, Fan Wang

The quadratic computational complexity to the number of tokens limits the practical applications of Vision Transformers (ViTs). Several works propose to prune redundant tokens to achieve efficient ViTs. However, these methods generally suffer from (i) dramatic accuracy drops, (ii) application difficulty in the local vision transformer, and (iii) non-general-

Rico Berner, Annie Lu, Igor M. Sokolov

Synchronization is an omnipresent collective phenomenon in nature and technology, whose understanding is in particular for real-world systems still elusive. We study the synchronization transition in a phase oscillator system with two nonvanishing Fourier-modes in the interaction function and hence going beyond the Kuromoto paradigm. We show that the transit

Torsten V. Zache, Daniel González-Cuadra, Peter Zoller

Simulating the real-time dynamics of lattice gauge theories, underlying the Standard Model of particle physics, is a notoriously difficult problem where quantum simulators can provide a practical advantage over classical approaches. In this work, we present a complete Rydberg-based architecture, co-designed to digitally simulate the dynamics of general gauge

Wenqi Ouyang, Yi Dong, Xiaoyang Kang, Peiran Ren

Retouching images is an essential aspect of enhancing the visual appeal of photos. Although users often share common aesthetic preferences, their retouching methods may vary based on their individual preferences. Therefore, there is a need for white-box approaches that produce satisfying results and enable users to conveniently edit their images simultaneous

Md Naseef-Ur-Rahman Chowdhury, Ahshanul Haque, Hamdy Soliman, Mohammad Sahinur Hossen

Malware for Android is becoming increasingly dangerous to the safety of mobile devices and the data they hold. Although machine learning(ML) techniques have been shown to be effective at detecting malware for Android, a comprehensive analysis of the methods used is required. We review the current state of Android malware detection us ing machine learning in

R. Bala, V. S. Prasannaa, D. Chakravarti, D. Mukherjee

In this work, we report results from our extensive spectroscopic study on AlF and AlCl molecules, keeping in mind potential laboratory as well as astrophysical applications. We carry out detailed electronic structure calculations in both the molecules, including obtaining the potential energy surfaces of the $X^1\Sigma$ ground electronic state and some of th

Luan Hoang

We study systems of nonlinear ordinary differential equations where the dominant term, with respect to large spatial variables, causes blow-ups and is positively homogeneous of a degree $1+\alpha$ for some $\alpha>0$. We prove that the asymptotic behavior of a solution $y(t)$ near a finite blow-up time $T_*$ is $(T_*-t)^{-1/\alpha}\xi_*$ for some nonzero vec

Mouhamed Naby Ndiaye, El Houcine Bergou, Hajar El Hammouti

Unmanned aerial vehicles (UAVs) are seen as a promising technology to perform a wide range of tasks in wireless communication networks. In this work, we consider the deployment of a group of UAVs to collect the data generated by IoT devices. Specifically, we focus on the case where the collected data is time-sensitive, and it is critical to maintain its time

Eliott Kacedan, Kohei Soga

This paper proves existence of a global weak solution to the inhomogeneous (i.e., non-constant density) incompressible Navier-Stokes system with mass diffusion. The system is well-known as the Kazhikhov-Smagulov model. The major novelty of the paper is to deal with the Kazhikhov-Smagulov model possessing the non-constant viscosity without any simplification

Guanghao Li, Wansen Wu, Yan Sun, Li Shen

As a popular paradigm of distributed learning, personalized federated learning (PFL) allows personalized models to improve generalization ability and robustness by utilizing knowledge from all distributed clients. Most existing PFL algorithms tackle personalization in a model-centric way, such as personalized layer partition, model regularization, and model

Ahsnaul Haque, Md Naseef-Ur-Rahman Chowdhury, Hamdy Soliman, Mohammad Sahinur Hossen

Wireless Sensor Networks (WSNs) have become increasingly valuable in various civil/military applications like industrial process control, civil engineering applications such as buildings structural strength monitoring, environmental monitoring, border intrusion, IoT (Internet of Things), and healthcare. However, the sensed data generated by WSNs is often noi

Paul Poncet

Relying on the notions of submodular function and partial metric, we introduce normed inverse semigroups as a generalization of normed groups and sup-semilattices equipped with an upper valuation. We define the property of skew-convexity for a metric on an inverse semigroup, and prove that every norm on a Clifford semigroup gives rise to a right-subinvariant

James Bartusek, Dakshita Khurana, Alexander Poremba

We build quantum cryptosystems that support publicly-verifiable deletion from standard cryptographic assumptions. We introduce target-collapsing as a weakening of collapsing for hash functions, analogous to how second preimage resistance weakens collision resistance; that is, target-collapsing requires indistinguishability between superpositions and mixtures

Lyonell Boulton

We examine the linear completeness of trajectories of eigenfunctions associated to non-linear eigenvalue problems, subject to Dirichlet boundary conditions on a segment. We pursue two specific goals. On the one hand, we establish that linear completeness persists for the non-linear Schr\"odinger equation, even when the trajectories lie far from those of the

Julius Richter, Simon Welker, Jean-Marie Lemercier, Bunlong Lay

In this paper, we present a causal speech signal improvement system that is designed to handle different types of distortions. The method is based on a generative diffusion model which has been shown to work well in scenarios with missing data and non-linear corruptions. To guarantee causal processing, we modify the network architecture of our previous work

Patrick Diehl, Gregor Daiß, Kevin Huck, Dominic Marcello

The increasing availability of machines relying on non-GPU architectures, such as ARM A64FX in high-performance computing, provides a set of interesting challenges to application developers. In addition to requiring code portability across different parallelization schemes, programs targeting these architectures have to be highly adaptable in terms of comput

H. Ge, L. Zhang, N. Zhao, J. Yang

In this report, we investigated a new rare earth based one-dimensional Ising spin chain magnet~\DNG~by means of magnetization, specific heat and powder neutron diffraction measurements. Due to the crystalline electrical field splitting, the magnetic Dy ions share an Ising like ground doublet state. Owning to the local point symmetry, these Ising moments form

Kalina Bonofiglio, Lauryn Whiteside, Maya Angeles, Matthew Haahr

Soft underwater robots typically explore bioinspired designs at the expense of power efficiency when compared to traditional underwater robots, which limits their practical use in real-world applications. We leverage a fluidic closed-loop controller to actuate a passive underwater glider. A soft hydrostatic pressure sensor is configured as a bangbang control

Guangyi Liu, Vivek Pandey, Christoforos Somarakis, Nader Motee

We develop a framework to assess the risk of cascading failures when a team of agents aims to rendezvous in time in the presence of exogenous noise and communication time-delay. The notion of value-at-risk (VaR) measure is used to evaluate the risk of cascading failures (i.e., waves of large fluctuations) when agents have failed to rendezvous. Furthermore, a

Atiyeh Bayani, Fahimeh Nazarimehr, Sajad Jafari, Kirill Kovalenko

We study the synchronization properties of a generic networked dynamical system, and show that, under a suitable approximation, the transition to synchronization can be predicted with the only help of eigenvalues and eigenvectors of the graph Laplacian matrix. The transition comes out to be made of a well defined sequence of events, each of which corresponds

Fabio Widmer, Andreas Ritter, Christopher H. Onder

This paper presents the Zurich Transit Bus (ZTBus) dataset, which consists of data recorded during driving missions of electric city buses in Zurich, Switzerland. The data was collected over several years on two trolley buses as part of multiple research projects. It involves more than a thousand missions across all seasons, each mission usually covering a f

NA62 Collaboration

The NA62 experiment at CERN, designed to study the ultra-rare decay $K^+ \to \pi^+\nu\overline{\nu}$, has also collected data in beam-dump mode. In this configuration, dark photons may be produced by protons dumped on an absorber and reach a decay volume beginning 80 m downstream. A search for dark photons decaying in flight to $\mu^+\mu^-$ pairs is reported

Yuhang Lu, Touradj Ebrahimi

Cross-resolution face recognition has become a challenging problem for modern deep face recognition systems. It aims at matching a low-resolution probe image with high-resolution gallery images registered in a database. Existing methods mainly leverage prior information from high-resolution images by either reconstructing facial details with super-resolution

Rafał Gruszczyński, Santiago Jockwich Martinez

One of the main goals of region-based theories of space is to formulate a geometrically appealing definition of points. The paper is devoted to the analysis of two such seminal definitions: Alfred N. Whitehead's (1929) and Andrzej Grzegorczyk's (1960). Relying on the work of Loredana Biacino's and Ginagiacomo Gerla's (1996), we improve their results, solve s

Manon Jarry, Alexis P. Rouillard, Illya Plotnikov, Athanasios Kouloumvakos

Coronal and interplanetary shock waves produced by coronal mass ejections (CMEs) are major drivers of space-weather phenomena, inducing major changes in the heliospheric radiation environment and directly perturbing the near-Earth environment, including its magnetosphere. A better understanding of how these shock waves evolve from the corona to the interplan

Luca Biferale, Fabio Bonaccorso, Michele Buzzicotti, Chiara Calascibetta

We present TURB-Lagr, a new open database of 3d turbulent Lagrangian trajectories, obtained by Direct Numerical Simulations (DNS) of the original Navier-Stokes equations in the presence of a homogeneous and isotropic forcing. The aim is to provide the community interested in data-assimilation and/or Lagrangian-properties of turbulence a new testing-ground ma

Mengru Cong, Han Ge, Lei Zhang, Weijun Ren

Geometrical frustration and the enhancement of strong quantum fluctuations in two-dimensional triangular antiferromagnets can lead to various intriguing phenomena. Here, we studied the spin-1/2 triangular lattice antiferromagnet NdAuAl$_4$Ge$_2$. Thermodynamic and transport properties, such as magnetization and specific heat together with the resistivity mea

Wei Jiang, Hans Dieter Schotten

This paper focuses on studying orthogonal and non-orthogonal multiple access in intelligent reflecting surface (IRS)-aided systems. Unlike most prior works assuming continuous phase shifts, we employ the practical setup where only a finite number of discrete phase shifts are available. To maximize the sum rate, active beamforming and discrete reflection need

Jiaxu Zhang, Junwu Weng, Di Kang, Fang Zhao

A good motion retargeting cannot be reached without reasonable consideration of source-target differences on both the skeleton and shape geometry levels. In this work, we propose a novel Residual RETargeting network (R2ET) structure, which relies on two neural modification modules, to adjust the source motions to fit the target skeletons and shapes progressi

Sriram Radhakrishna, Adithya Balasubramanyam

In this paper, we present a novel algorithm to extract a quaternion from a two dimensional camera frame for estimating a contained human skeletal pose. The problem of pose estimation is usually tackled through the usage of stereo cameras and intertial measurement units for obtaining depth and euclidean distance for measurement of points in 3D space. However,

Moshe Adrian

Let F be a non-archimedean local field of characteristic zero. In this paper we construct examples of supercuspidal representations showing that the bound $[N/2]$ for the local converse theorem of $GL_N(F)$ is sharp, N general, when the residual characteristic of $F$ is bigger than $N$.

Naijia Liu, Minxing Shen, Liang Song, Lixin Yan

Let ${\frak M}^\alpha$ be the spherical maximal operators of complex order $\alpha$ on ${\mathbb R^n}$. In this article we show that when $n\geq 2$, suppose \begin{eqnarray*} \|{\frak M}^{\alpha} f \|_{L^p({\mathbb R^n})} \leq C\|f \|_{L^p({\mathbb R^n})} \end{eqnarray*} holds for some $\alpha$ and $p\geq 2$, then we must have ${\rm Re}\,\alpha \geq \max \{1

Nicolas Meunier, Philippe Souplet

We consider a model of cell motion with boundary signal production which describes some aspects of eukaryotic cell migration. Generic polarity markers located in the cell are transported by actin which they help to polymerize. This leads to a problem whose mathematical novelty is the nonlinear and nonlocal destabilizing term in the boundary condition. We pro

Jiafeng Chen

Consider a normal location model $X \mid \theta \sim N(\theta, \sigma^2)$ with known $\sigma^2$. Suppose $\theta \sim G_0$, where the prior $G_0$ has zero mean and variance bounded by $V$. Let $G_1$ be a possibly misspecified prior with zero mean and variance bounded by $V$. We show that the squared error Bayes risk of the posterior mean under $G_1$ is bound

Nestor Prieto-Chavana, Julie Weeds, David Weir

It is widely accepted that so-called facts can be checked by searching for information on the Internet. This process requires a fact-checker to formulate a search query based on the fact and to present it to a search engine. Then, relevant and believable passages need to be identified in the search results before a decision is made. This process is carried o

Anil Raghav, Kalpesh Ghag, Omkar Dhamane, Zubair Shaikh

Despite centuries of rigorous theoretical and observational research, the origin and acceleration mechanism of Galactic Cosmic Rays (GCRs) remain a mystery. In 1949, Fermi proposed a diffusive shock acceleration model that includes a prominent mechanism for GCR acceleration. However, observational evidence, on the other hand, remains elusive. Here, we provid

Jun Wang, Wan-Ting He, Cong-Wei Lu, Yang-Yang Wang

Due to the long coherence time and efficient manipulation, the surface electron (SE) provides a perfect two-dimensional platform for quantum computation and quantum simulation. In this work, a theoretical scheme to realize the controlled-NOT (CNOT) gate is proposed, where the two-qubit system is encoded on the four-level Rydberg structure of SE. The state tr

Sylvain Deffet, Kevin Souris, Edmond Sterpin

Purpose: A promising approach to enable FLASH conformal proton therapy is to passively degrade a single energy layer using a patient-specific range modulator. We propose an innovative method to directly optimize the geometrical characteristics of the range modulator and the treatment plan with respect to user defined constraints, similarly to state-of-the-ar

Nam Tuan Ly, Atsuhiro Takasu

Image-based table recognition is a challenging task due to the diversity of table styles and the complexity of table structures. Most of the previous methods focus on a non-end-to-end approach which divides the problem into two separate sub-problems: table structure recognition; and cell-content recognition and then attempts to solve each sub-problem indepen

David R. A. Williams, Ranieri D. Baldi, Robert J. Beswick, Ian M. McHardy

The Legacy e-MERLIN Multi-band Imaging of Nearby Galaxies survey (LeMMINGs) is a statistically-complete census of nuclear accretion and star formation processes in the local Universe. The LeMMINGs observations at 1.5 and 5 GHz yield angular resolutions on 10s milliarcsecond-scales, with sensitivities of 10s $\mu$Jy. Awarded 810 hours of observing time, the f

Ye Huang, Di Kang, Shenghua Gao, Wen Li

Existing pyramid-based upsamplers (e.g. SemanticFPN), although efficient, usually produce less accurate results compared to dilation-based models when using the same backbone. This is partially caused by the contaminated high-level features since they are fused and fine-tuned with noisy low-level features on limited data. To address this issue, we propose to

Michael C Denes, Shane R Keating, Gary Froyland

The Southern Ocean plays an integral role in the global climate system, exchanging heat, salt, and carbon throughout the major ocean basins via the deep, fast-flowing Antarctic Circumpolar Current. The Antarctic Circumpolar Current is bounded by spatially and temporally varying fronts that partition distinct water masses. Locating and quantifying cross-front

Oscar Pina, Verónica Vilaplana

Self-supervised learning is gaining considerable attention as a solution to avoid the requirement of extensive annotations in representation learning on graphs. Current algorithms are based on contrastive learning, which is computation an memory expensive, and the assumption of invariance under certain graph augmentations. However, graph transformations such

Matthew M. Dobson, Megan E. Schwamb, Susan D. Benecchi, Anne J. Verbiscer

The Kuiper belt objects, the Centaurs, and the Jupiter-family comets form an evolutionary continuum of small outer Solar System objects, and their study allows us to gain insight into the history and evolution of the Solar System. Broadband photometry can be used to measure their phase curves, allowing a first-order probe into the surface properties of these

Tak Chu Li, Yi-Hsin Liu, Yi Qi, Muni Zhou

Magnetic reconnection and plasma turbulence are ubiquitous processes important for laboratory, space and astrophysical plasmas. Reconnection has been suggested to play an important role in the energetics and dynamics of turbulence by observations, simulations and theory for two decades. The fundamental properties of reconnection at kinetic scales, essential

David González-Álvaro, Masoumeh Zarei

We show that, for any $n\geq 2$, there exists a homogeneous space of dimension $d=8n-4$ with metrics of $\mathrm{Ric}_{\frac{d}{2}-5}>0$ if $n\neq 3$ and $\mathrm{Ric}_6>0$ if $n=3$ which evolve under the Ricci flow to metrics whose Ricci tensor is not $(d-4)$-positive. Consequently, Ricci flow does not preserve a range of curvature conditions that interpola