July 2022 arXiv papers — page 15

Francesco Giacosa

In the study of decays, it is quite common that an unstable quantum state/particle has multiple distinct decay channels. In this case, besides the survival probability $p(t)$, also the probability $w_{i}(t)$ that the decay occurs between $(0,t)$ in the $i$-th channel is a relevant object. The general form of the function $w_{i}(t)$ was recently presented in

Nancy Victor, Rajeswari. C, Mamoun Alazab, Sweta Bhattacharya

Internet of Underwater Things (IoUT) have gained rapid momentum over the past decade with applications spanning from environmental monitoring and exploration, defence applications, etc. The traditional IoUT systems use machine learning (ML) approaches which cater the needs of reliability, efficiency and timeliness. However, an extensive review of the various

Tom Burgert, Mahdyar Ravanbakhsh, Begüm Demir

The development of accurate methods for multi-label classification (MLC) of remote sensing (RS) images is one of the most important research topics in RS. To address MLC problems, the use of deep neural networks that require a high number of reliable training images annotated by multiple land-cover class labels (multi-labels) has been found popular in RS. Ho

Mani L. Bhaumik

Credible reasons are presented to reveal that many of the lingering century old enigmas, surrounding the behavior of at least an individual quantum particle, can be comprehended in terms of an objectively real specific wave function. This wave function is gleaned from the single particle energy-momentum eigenstate offered by the theory of space filling unive

Pallabi Saikia, Dhwani Dholaria, Priyanka Yadav, Vaidehi Patel

Deepfakes are the synthesized digital media in order to create ultra-realistic fake videos to trick the spectator. Deep generative algorithms, such as, Generative Adversarial Networks(GAN) are widely used to accomplish such tasks. This approach synthesizes pseudo-realistic contents that are very difficult to distinguish by traditional detection methods. In m

Liang Yan

Using the largest $J/\psi$ and $\psi(3686)$ data samples collected at the BESIII experiment, the hyperon anti-hyperon pairs are generated in their quantum entangle system. The polarization of hyperon has been observed, which makes it possible to measure the decay parameters of hyperon and anti-hyperon precisely. The CP conservation observables have been esti

Matteo Ferraretto, Andrea Richaud, Lorenzo Del Re, Leonardo Fallani

We consider the effect of a local interatomic repulsion on synthetic heterostructures where a discrete synthetic dimension is created by Raman processes on top of $SU(N)$-symmetric two-dimensional lattice systems. At a filling of one fermion per site, increasing the interaction strength, the system is driven towards a Mott state which is adiabatically connec

Donghe Tu, Xingrui Huang, Yang Liu, Zhiguo Yu

In this paper, an on-chip photonic sampled and quantized analog-to-digital converter (ADC) on thin-film lithium niobate platform is experimentally demonstrated. Using two phase modulators as a sampler and a 5$\times$5 multimode interference (MMI) coupler as a quantizer, an 1 GHz sinusoidal analog input signal was successfully converted to a digitized output

Tizian Wenzel, Daniel Winkle, Gabriele Santin, Bernard Haasdonk

We consider meshless approximation for solutions of boundary value problems (BVPs) of elliptic Partial Differential Equations (PDEs) via symmetric kernel collocation. We discuss the importance of the choice of the collocation points, in particular by using greedy kernel methods. We introduce a scale of PDE-greedy selection criteria that generalizes existing

Francesco Zola, Jose Alvaro Fernandez-Carrasco, Jan Lukas Bruse, Mikel Galar

Biometric systems represent valid solutions in tasks like user authentication and verification, since they are able to analyze physical and behavioural features with high precision. However, especially when physical biometrics are used, as is the case of iris recognition, they require specific hardware such as retina scanners, sensors, or HD cameras to achie

John Dougrez-Lewis, Elena Kochkina, M. Arana-Catania, Maria Liakata

Work on social media rumour verification utilises signals from posts, their propagation and users involved. Other lines of work target identifying and fact-checking claims based on information from Wikipedia, or trustworthy news articles without considering social media context. However works combining the information from social media with external evidence

Zhengping Zhu, Ruifeng Hu, Xiaojing Zheng

In this paper, we present a multiple-time-step integration algorithm (MTSA) for particle collisions in particle-resolved simulations. Since the time step required for resolving a collision process is much smaller than that for a fluid flow, the computational cost of the traditional soft-sphere model by reducing the time step is quite high in particle-resolve

H. Duran, J. Cuevas-Maraver, P. G. Kevrekidis, A. Vainchtein

We consider a previously experimentally realized discrete model that describes a mechanical metamaterial consisting of a chain of pairs of rigid units connected by flexible hinges. Upon analyzing the linear band structure of the model, we identify parameter regimes in which this system may possess discrete breather solutions with frequencies inside the gap b

Tatsuro Kawakami

Let $X$ be a normal variety over a perfect field of positive characteristic and $B$ a reduced divisor on $X$. We prove that if the Cartier isomorphism on the log smooth locus of $(X,B)$ extends to the entire $X$, then $(X,B)$ satisfies the logarithmic extension theorem for differential forms. As an application, we show that the logarithmic extension theorem

Yuuka Kanakubo, Yasuki Tachibana, Tetsufumi Hirano

We analyze Pb+Pb collisions at $\sqrt{s_{\mathrm{NN}}}=2.76$ TeV with a novel framework based on the dynamical core--corona picture that describes particle productions from both equilibrium and non-equilibrium components. We remark the possibility of the contribution from non-equilibrium components at very low transverse momentum ($p_{T}$) region and show th

Zvi Kons, Hagai Aronowitz, Edmilson Morais, Matheus Damasceno

Speech transcription, emotion recognition, and language identification are usually considered to be three different tasks. Each one requires a different model with a different architecture and training process. We propose using a recurrent neural network transducer (RNN-T)-based speech-to-text (STT) system as a common component that can be used for emotion r

Caterina Balzotti, Maya Briani

In this paper we propose a multiscale traffic model, based on the family of Generic Second Order Models, which integrates multiple trajectory data into the velocity function. This combination of a second order macroscopic model with microscopic information allows us to reproduce significant variations in speed and acceleration that strongly influence traffic

Bin Xia, Yapeng Tian, Yulun Zhang, Yucheng Hang

The most of CNN based super-resolution (SR) methods assume that the degradation is known (\eg, bicubic). These methods will suffer a severe performance drop when the degradation is different from their assumption. Therefore, some approaches attempt to train SR networks with the complex combination of multiple degradations to cover the real degradation space.

Christoph Schwarzmeier, Ulrich Rüde

The accuracy of the free-surface lattice Boltzmann method (FSLBM) depends significantly on the boundary condition employed at the free interface. Ideally, the chosen boundary condition balances the forces exerted by the liquid and gas pressure. Different variants of the same boundary condition are possible, depending on the number and choice of the particle

Armando Gutierrez Terradillos

In this paper we use the regularized Siegel-Weil formula of Gan-Qiu-Takeda to obtain an expression of the integral of the theta function over the truncated modular curve. We apply this result to express the integral over the truncated modular curve of the logarithm of the Borcherds form and we describe explicitly its asymptotic behaviour, and in particular t

Frank Freimuth, Stefan Blügel, Yuriy Mokrousov

We describe a density-functional method which aims at computing the ground state electron density and the spectral function at the same time. One basic ingredient of our method is the construction of the spectral function from the first four spectral moment matrices. The second basic ingredient is the construction of the spectral moment matrices from density

Charles Lovering, Ellie Pavlick

Many complex problems are naturally understood in terms of symbolic concepts. For example, our concept of "cat" is related to our concepts of "ears" and "whiskers" in a non-arbitrary way. Fodor (1998) proposes one theory of concepts, which emphasizes symbolic representations related via constituency structures. Whether neural networks are consistent with suc

Takehiro Ito, Jun Kawahara, Yu Nakahata, Takehide Soh

This paper proposes an algorithmic framework for various reconfiguration problems using zero-suppressed binary decision diagrams (ZDDs), a data structure for families of sets. In general, a reconfiguration problem checks if there is a step-by-step transformation between two given feasible solutions (e.g., independent sets of an input graph) of a fixed search

Lin-Qing Song, Dan Song, Jun-Tao Zhu, Jun He

In this work, a study of possible molecular states from the $\Lambda_c\bar{\Lambda}_c$ interaction and their productions in nucleon-antinucleon collision is performed in a quasipotential Bethe-Salpeter equation approach. Two bound states with quantum numbers $J^{PC}=0^{-+}$ and $1^{--}$ are produced with almost the same binding energy from the $\Lambda_c\bar

Eng Keat Hng, Domenico Mergoni Cecchelli

We denote by $\text{ex}(n, H, F)$ the maximum number of copies of $H$ in an $n$-vertex graph that does not contain $F$ as a subgraph. Recently, Grzesik, Gy\H{o}ri, Salia, Tompkins considered conditions on $H$ under which $\text{ex}(n, H, K_r)$ is asymptotically attained at a blow-up of $K_{r-1}$, and proposed a conjecture. In this note we disprove their conj

Tommaso Pacini, Alberto Raffero

We prove new variation formulae for the volume of coassociative submanifolds, expressed in terms of $G_2$ data. As a special case, we obtain a second variation formula for variations within the moduli space of coassociative submanifolds; this formula highlights the role of the ambient torsion and Ricci curvature. These results apply, for example, to coassoci

Zexiang Liu, Dong Li, Kaiyue Lu, Zhen Qin

Recently, numerous efficient Transformers have been proposed to reduce the quadratic computational complexity of standard Transformers caused by the Softmax attention. However, most of them simply swap Softmax with an efficient attention mechanism without considering the customized architectures specially for the efficient attention. In this paper, we argue

Antoine Lejay, Sara Mazzonetto

We give an asymptotic development of the maximum likelihood estimator (MLE), or any other estimator defined implicitly, in a way which involves the limiting behavior of the score and its higher-order derivatives. This development, which is explicitly computable, gives some insights about the non-asymptotic behavior of the renormalized MLE and its departure f

Luis Bonah, Oliver Zingsheim, Holger S. P. Müller, Jean-Claude Guillemin

Acetone-13C1 is a complex organic molecule with two internal methyl (-CH3) rotors having relatively low effective barriers to internal rotation of about 249 cm-1. This leads to two low-lying torsional modes and five internal rotation components resulting in a dense and complicated spectrum. In this study, measurements of acetone-13C1 were performed with an i

Freddy Kamdem Simo, Dominique Ernadote, Dominique Lenne

In a Systems Engineering setting, various models are produced using a variety of methods and tools. Focusing on a type of models -- called descriptive models -- which we shall describe, we argue that, while the clarity and precision of models are essential for their exchange and reuse, the way in which the data of these models are defined and the information

Arthur Bik, Alessandro Danelon, Andrew Snowden

A cubic space is a vector space equipped with a symmetric trilinear form. Two cubic spaces are isogeneous if each embeds into the other. A cubic space is non-degenerate if its form cannot be expressed as a finite sum of products of linear and quadratic forms. We classify non-degenerate cubic spaces of countable dimension up to isogeny: the isogeny classes ar

Pan Liu, Sidy Fall, Olivier Baledent

Compared with CINE phase contrast MRI (CINE-PC), echo-planar imaging phase contrast (EPI-PC) can achieve realtime quantification of blood flow, with lower SNR. In this study, the pulsating real model of the simulated cerebral vasculature was used to verify the accuracy of EPI-PC. The imaging time of EPI-PC was 62ms/image at 100*60 spatial resolution. The rec

Olivier Baledent, Pan Liu, Serge Metanbou, Cyrille Capel

It is still debated how breathing interacts with the CSF. New Phase contrast MRI sequence based on Echo Planar imaging (EPI-PC) can now produce continuously during minutes a velocity map, more or less every 100 ms. We did not found in the literature quantitative evaluation of the CSF stroke volume change during breathing. The aim of this work is to quantify

Yaozong Shen, Lijie Wang, Ying Chen, Xinyan Xiao

While pre-trained language models (LMs) have brought great improvements in many NLP tasks, there is increasing attention to explore capabilities of LMs and interpret their predictions. However, existing works usually focus only on a certain capability with some downstream tasks. There is a lack of datasets for directly evaluating the masked word prediction p

Sinem Sav, Abdulrahman Diaa, Apostolos Pyrgelis, Jean-Philippe Bossuat

We present RHODE, a novel system that enables privacy-preserving training of and prediction on Recurrent Neural Networks (RNNs) in a cross-silo federated learning setting by relying on multiparty homomorphic encryption. RHODE preserves the confidentiality of the training data, the model, and the prediction data; and it mitigates federated learning attacks th

Michel Rausch de Traubenberg, M J Slupinski

We continue our study and classification of structures on the Fano plane ${\cal F}$ and its dual ${\cal F}^\ast$ involved in the construction of octonions and the Lie algebra $\mathfrak g_2 (\mathbb F)$ over a field $\mathbb F$. These are a "composition factor": ${\cal F}\times {\cal F} \to\{-1, 1\}$, inducing an octonion multiplication, and a function $\del

Yves Aubry, Fabien Herbaut, Ali Issa

We contribute to the exceptional APN conjecture by showing that no polynomial of degree m = 2 r (2 {\ell} + 1) where gcd(r, {\ell}) 2, r 2, {\ell} 1 with a nonzero second leading coefficient can be APN over infinitely many extensions of the base field. More precisely, we prove that for n sufficiently large, all polynomials of F 2 n [x] of such a degree with

Hai Yang, Yuhang Sheng, Yi Jiang, Xiaoyang Fang

Motivation: Cancer is heterogeneous, affecting the precise approach to personalized treatment. Accurate subtyping can lead to better survival rates for cancer patients. High-throughput technologies provide multiple omics data for cancer subtyping. However, precise cancer subtyping remains challenging due to the large amount and high dimensionality of omics d

Luca Becchetti, Arthur Carvalho Walraven da Cunha, Andrea Clementi, Francesco d'Amore

In the Random Subset Sum Problem, given $n$ i.i.d. random variables $X_1, ..., X_n$, we wish to approximate any point $z \in [-1,1]$ as the sum of a suitable subset $X_{i_1(z)}, ..., X_{i_s(z)}$ of them, up to error $\varepsilon$. Despite its simple statement, this problem is of fundamental interest to both theoretical computer science and statistical mechan

Tsung-Ming Huang, Wei-Hung Liao, Wen-Wei Lin

In this paper, we first extend the finite distortion problem from the bounded domains in $\mathbb{R}^2$ to the closed genus-zero surfaces in $\mathbb{R}^3$ by the stereographic projection. Then we derive a theoretical foundation for spherical equiareal parameterizations between a simply connected closed surface $\mathcal{M}$ and a unit sphere $\mathbb{S}^2$

Zoé Agathe-Nerine

We consider a population of Hawkes processes modeling the activity of $N$ interacting neurons. The neurons are regularly positioned on the segment $[0,1]$, and the connectivity between neurons is given by a random possibly diluted and inhomogeneous graph where the probability of presence of each edge depends on the spatial position of its vertices through a

Léon Zheng, Gilles Puy, Elisa Riccietti, Patrick Pérez

We introduce a regularization loss based on kernel mean embeddings with rotation-invariant kernels on the hypersphere (also known as dot-product kernels) for self-supervised learning of image representations. Besides being fully competitive with the state of the art, our method significantly reduces time and memory complexity for self-supervised training, ma

Agorakis Bompotas, Christos Anagnostopoulos, Athanasios Kalogeras, Georgios Kalogeras

We are currently witnessing an increased occurrence of extreme weather events, causing a great deal of disruption and distress across the globe. In this setting, the importance and utility of Early Warning Systems is becoming increasingly obvious. In this work, we present the design of an early warning system called TransCPEarlyWarning, aimed at seven countr

Catherine Lorenz, Nicola Mimmo, Alena Otto, Daniele Vigo

The Drone Routing Problem with Energy replenishment (DRP-E) belongs to a general class of routing problems with intermediate stops and synchronization constraints. In DRP-E, the drone has to visit a set of nodes and routinely requires battery swaps from a (potentially) mobile replenishment station. Contrary to widespread restrictions in the drone routing lit

Georgy Artemov, Yeon-Koo Che, YingHua He

Motivated by growing evidence of agents' mistakes in strategically simple environments, we propose a solution concept -- robust equilibrium -- that requires only an asymptotically optimal behavior. We use it to study large random matching markets operated by the applicant-proposing Deferred Acceptance (DA). Although truth-telling is a dominant strategy, almo

Guram Bezhanishvili, Luca Carai, Patrick Morandi

We connect Priestley duality for distributive lattices and its generalization to distributive meet-semilattices to Hofmann-Mislove-Stralka duality for semilattices. Among other things, this involves consideration of various morphisms between algebraic frames. We also show how Stone duality for boolean algebras and generalized boolean algebras fits as a parti

Hong Rae Cho, Han-Wool Lee, Soohyun Park

We characterize the Carleson measures for an exponential Bergman space on the unit ball of $\mathbb C^n$ in terms of the ball induced by the complex Hessian of the logarithm of the weight function. The boundedness (or compactness) of integral operators, Ces\`{a}ro operators and Toeplitz operators, is given using the Carleson measure (or vanishing Carleson me

Sobhan Kazempour, Amin Rezaei Akbarieh, Emmanuel N Saridakis

Although quasi-dilaton massive gravity is a well-defined gravitational theory, it exhibits instabilities and suffers from the strong coupling problem. In this work we construct an extension of the theory, through the inclusion of the aether field. Focusing on flat Friedmann-Lemaitre-Robertson-Walker geometry, we show the existence of exact, self-accelerating

Donatella Iacono, Elena Martinengo

We study the functor $\operatorname{Def}_E^k$ of infinitesimal deformations of a locally free sheaf $E$ of $\mathcal{O}_X$-modules on a smooth variety $X$, such that at least $k$ independent sections lift to the deformed sheaf, where $h^0(E) \geq k$. We deduce some information on the $k$-th Brill-Noether locus of $E$, such as the description of the tangent c

Andreas Brendel, Thomas Haubner, Walter Kellermann

In many daily-life scenarios, acoustic sources recorded in an enclosure can only be observed with other interfering sources. Hence, convolutive Blind Source Separation (BSS) is a central problem in audio signal processing. Methods based on Independent Component Analysis (ICA) are especially important in this field as they require only few and weak assumption

Zheng Sun

The Nelson-Seiberg theorem and its extensions relate supersymmetry breaking and R-symmetries in Wess-Zumino models. But their applicability may be limited by previously found non-generic counterexamples. Constructing a dataset of R-symmetric Wess-Zumino models is useful for studying the occurrence of such counterexamples as well as other purposes. This work

Sarira Sahu, Isabel Abigail Valadez Polanco, Subhash Rajpoot

Since its discovery in 1995, the high-energy peaked blazar 1ES 2344+514 has undergone several episodes of GeV-TeV flaring and has been observed in the multiwavelength by several other telescopes. The observed X-ray spectrum of 1996 and the flaring event of 2016 establish that 1ES 2344+514 has a temporary EHBL-like behavior. Such behavior has also been observ

Ioannis Kalogridis

We propose a novel family of multivariate robust smoothers based on the thin-plate (Sobolev) penalty that is particularly suitable for the analysis of spatial data. The proposed family of estimators can be expediently computed even in high dimensions, is invariant with respect to rigid transformations of the coordinate axes and can be shown to possess optima

Zuriñe Yoldi, Antoine Pommerol, Olivier Poch, Nicolas Thomas

The reflectance of water ice and dust mixtures depends, amongst other parameters, on how the components are mixed (e.g. intimate mixture, areal mixture or coating) (Clark et al. 1999). Therefore, when inverting the reflectance spectra measured from planetary surfaces to derive the amount of water ice present at the surface, it is critical to distinguish betw

Hui Li, Xuekang Yang

Incorporating structured knowledge into pre-trained language models has demonstrated signiffcant bene-ffts for domain-speciffc natural language processing tasks, particularly in specialized ffelds like military intelligence analysis. Existing approaches typically integrate external knowledge through masking tech-niques or fusion mechanisms, but often fail to

Rémi Carles, Clotilde Fermanian Kammerer, Caroline Lasser

We prove existence and uniqueness results for the time-dependent Hartree approximation arising in quantum dynamics. The Hartree equations of motion form a coupled system of nonlinear Schr{\"o}dinger equations for the evolution of product state approximations. They are a prominent example for dimension reduction in the context of the the time-dependent Dirac-

Arne J. Klomp, Karsten Albe

Nanoporous metals or nanofoams are a promising material class that is considered for sensing, actuation, and catalysis. To date, they mostly based on simple noble metals such as nanoporous gold, which exhibit peculiar stress-strain response different from the bulk material. At the same time bulk alloys such as NiTi feature a reversible martensitic phase tran

Samy Blusseau, Santiago Velasco-Forero, Jesus Angulo, Isabelle Bloch

In discrete signal and image processing, many dilations and erosions can be written as the max-plus and min-plus product of a matrix on a vector. Previous studies considered operators on symmetrical, unbounded complete lattices, such as Cartesian powers of the completed real line. This paper focuses on adjunctions on closed hypercubes, which are the complete

Eni Kume, Peter Dunne, Nicolas Martin, Patrick Baroni

By reinforcing the interaction energy of the liquid with respect to the surface using total wetting boundary conditions, the response of liquids to mechanical shear stress is stronger and exhibits at sub-millimeter scale elastic properties. This study extends here to liquids with strong electrostatic interactions such as ionic liquids and paramagnetic liquid

Min Meng, Xiuxian Li

In this paper, the generalized Nash equilibrium (GNE) seeking problem for continuous games with coupled affine inequality constraints is investigated in a partial-decision information scenario, where each player can only access its neighbors' information through local communication although its cost function possibly depends on all other players' strategies.

Hans Jurie Zietsman, Jan Harm van Vuuren

The success of any business depends on how well it is able to satisfy customer demand, while remaining financially viable. Globalisation and the growth of e-commerce have resulted in retail businesses having to manage increasing numbers of products. As the number of products sold increases, so does the complexity of the corresponding inventory management pro

Devaraju Vinoda, Pawan Kumar Yadav

In this work we introduce a new transformer architecture called SparseDistilBERT (SDBERT), which is a combination of sparse attention and knowledge distillantion (KD). We implemented sparse attention mechanism to reduce quadratic dependency on input length to linear. In addition to reducing computational complexity of the model, we used knowledge distillatio

Santiago Barbieri, Laurent Niederman

Consider an open, bounded set $\Omega\subset \mathbb{C}$, a positive integer $k$ and a compact $\mathcal{K}\subset \Omega$ of cardinality strictly greater than $k$. We prove that, for any function $f$ which is holomorphic in $\overline \Omega$, and whose graph satisfies $S(z,f(z))=0$ for some polynomial $S\in\mathbb{C}[z,w]$ of degree at most $k$ (hence $f$

Xiaomin Fang, Fan Wang, Lihang Liu, Jingzhou He

AI-based protein structure prediction pipelines, such as AlphaFold2, have achieved near-experimental accuracy. These advanced pipelines mainly rely on Multiple Sequence Alignments (MSAs) as inputs to learn the co-evolution information from the homologous sequences. Nonetheless, searching MSAs from protein databases is time-consuming, usually taking dozens of

L. M. Serrano, D. Gandolfi, S. Hoyer, A. Brandeker

We present the discovery of two small planets transiting HD 93963A (TOI-1797), a G0\,V star (M$_*$=1.109\,$\pm$\,0.043\,M$_\odot$, R$_*$=1.043\,$\pm$\,0.009\,R$_\odot$) in a visual binary system. We combined TESS and CHEOPS space-borne photometry with data from MuSCAT 2, `Alopeke, PHARO, TRES, FIES, and SOPHIE. We validated and spectroscopically confirmed th

Lik Hang Lee, Carlos Bermejo Fernandez, Ahmad Alhilal, Tristan Braud

Human habitation across multiple planets requires communication and social connection between planets. When the infrastructure of a deep space network becomes mature, immersive cyberspace, known as the Metaverse, can exchange diversified user data and host multitudinous virtual worlds. Nevertheless, such immersive cyberspace unavoidably encounters latency in

Min Sik Oh, Min Sang Kim

Persona and Knowledge dual context open-domain chat is a novel dialogue generation task introduced recently. While Persona and Knowledge is each interesting context of open-domain dialogue, the combination of both has not been well studied. We tackle Persona-Knowledge identification and response generation tasks in this paper. We design an informed data augm

Markus Pfeil, Thomas Slawig

The reduction of the computational effort is desirable for the simulation of marine ecosystem models. Using a marine ecosystem model, the assessment and the validation of annual periodic solutions (i.e., steady annual cycles) against observational data are crucial to identify biogeochemical processes, which, for example, influence the global carbon cycle. Fo

Ruben Sanchez, Clément Jailin, Ann-Katherine Carton, Pablo Milioni de Carvalho

Description of purpose: Contrast-enhanced spectral mammography can be used to guide needle biopsies. However, in vertical approach the compressed breast is deformed generating a so-called bump in the paddle aperture, which may interfere with the visibility of contrast-uptakes. Local thickness estimation would provide an enhanced image quality of the recombin

Ramya S. Hebbalaguppe, Soumya Suvra Goshal, Jatin Prakash, Harshad Khadilkar

Modern deep neural network models are known to erroneously classify out-of-distribution (OOD) test data into one of the in-distribution (ID) training classes with high confidence. This can have disastrous consequences for safety-critical applications. A popular mitigation strategy is to train a separate classifier that can detect such OOD samples at the test

G. G. L. Nashed, Shin'ichi Nojiri

Among the modified gravitational theories, the ghost-free Gauss-Bonnet (GFGB) theory of gravity has been considered from the viewpoint of cosmology. The best way to check its applicability could be to elicit observable predicts which give guidelines or limitations on the theory, which could be contrasted with the actual observations. In the present study, we

Antonio Briola, David Vidal-Tomás, Yuanrong Wang, Tomaso Aste

We quantitatively describe the main events that led to the Terra project's failure in May 2022. We first review, in a systematic way, news from heterogeneous social media sources; we discuss the fragility of the Terra project and its vicious dependence on the Anchor protocol. We hence identify the crash's trigger events, analysing hourly and transaction data

Gianluigi Ciocca, Paolo Napoletano, Matteo Romanato, Raimondo Schettini

The management of people with long-term or chronic illness is one of the biggest challenges for national health systems. In fact, these diseases are among the leading causes of hospitalization, especially for the elderly, and huge amount of resources required to monitor them leads to problems with sustainability of the healthcare systems. The increasing diff

Jan-Willem Boiten, Christian Ohmann, Ayodeji Adeniran, Steve Canham

The Horizon 2020 project EOSC-Life brings together the 13 Life Science 'ESFRI' research infrastructures to create an open, digital and collaborative space for biological and medical research. Sharing sensitive data is a specific challenge within EOSC-Life. For that reason, a toolbox is being developed, providing information to researchers who wish to share a

Luigi Santocanale, Cédric de Lacroix

It is known that the quantale of sup-preserving maps from a complete lattice to itself is a Frobenius quantale if and only if the lattice is completely distributive. Since completely distributive lattices are the nuclear objects in the autonomous category of complete lattices and sup-preserving maps, we study the above statement in a categorical setting. We

Georges Gras

The Main Theorem for abelian fields (often called Main Conjecture despite proofs in most cases) has a long history which has found a solution by means of "elementary arithmetic", as detailed in Washington's book from Thaine's method having led to Kolyvagin's Euler systems. Analytic theory of real abelian fields $K$ says (in the semi-simple case) that the ord

Pankaj Kapari, Kashyap Rajeevsarathy, Apeksha Sanghi

For $g\geq 2$, let $\text{Mod}(S_g)$ be the mapping class group of the closed orientable surface $S_g$ of genus $g$. In this paper, we provide necessary and sufficient conditions for a pair of elements in $\text{Mod}(S_g)$ to generate an infinite metacyclic subgroup. In particular, we provide necessary and sufficient conditions under which a pseudo-Anosov ma

Minju Park, Kyogu Lee

Advanced music recommendation systems are being introduced along with the development of machine learning. However, it is essential to design a music recommendation system that can increase user satisfaction by understanding users' music tastes, not by the complexity of models. Although several studies related to music recommendation systems exploiting negat

Ameneh Maghsoodi, Kaushik Bhattacharya

Photomechanical liquid crystal elastomers (LCEs) are responsive polymers that can convert light directly into mechanical deformation. This unique feature makes these materials an attractive candidate for soft actuators capable of remote and multi-mode actuation. In this work, we propose a three-dimensional multi-scale model of the nonlinear and nonlocal dyna

Hiroyuki Tajima, Hajime Moriya, Wataru Horiuchi, Kei Iida

We theoretically investigate the fate of a neutron-alpha $p$-wave resonance in dilute neutron matter, which may be encountered in neutron stars and supernova explosions. While $^5$He is known as a resonant state that decays to a neutron and an alpha particle in vacuum, this unstable state turns into a stable bound state in the neutron Fermi sea because the d

Ba Phi Nguyen, Duy Khuong Phung, Kihong Kim

We investigate numerically the time evolution of wave packets incident on one-dimensional semi-infinite lattices with mosaic modulated random on-site potentials, which are characterized by the integer-valued modulation period $\kappa$ and the disorder strength $W$. For Gaussian wave packets with the central energy $E_0$ and a small spectral width, we perform

Zuriñe Yoldi, Antoine Pommerol, Olivier Poch, Nicolas Thomas

We measure the visible and near-infrared reflectance of icy analogues of the Martian surface made of CO$_2$ ice associated in different ways with H$_2$O ice and the regolith simulant JSC Mars-1. Such experimental results obtained with well-controlled samples in the laboratory are precious to interpret quantitatively the imaging and spectral data collected by

Victor Chu, Andrés Monroy-Hernández

In this paper, we propose CaminAR, an augmented reality (AR) system for remote social walking among dyads. CaminAR enables two people who are physically away from one another to synchronously see and hear each other while going on a walk. The system shows a partner's avatar superimposed onto the physical world using smart glasses while walking and talking. U

Akash Anand, Sameer Chavan, Rajkamal Nailwal

We discuss the problem of classifying polynomials $p : \mathbb R^2_+ \rightarrow (0, \infty)$ for which $\frac{1}{p}=\{\frac{1}{p(m, n)}\}_{m, n \geq 0}$ is joint completely monotone, where $p$ is a linear polynomial in $y.$ We show that if $p(x, y)=a+b x+c y+d xy$ with $a > 0$ and $b, c, d \geq 0,$ then $\frac{1}{p}$ is joint completely monotone if and only

Anwesh Ray

Let $\ell$ be a prime number and $q$ be a power of $\ell$. Given an odd prime number $p$ and an imaginary quadratic extension $F$ of the rational function field $\mathbb{F}_q(T)$, let $\lambda_p(F)$ denote the Iwasawa $\lambda$-invariant of the constant $\mathbb{Z}_p$-extension of $F$. We show that for any number $r>0$ and all large enough values of $q\not\e

Rohan Yadav, Alex Aiken, Fredrik Kjolstad

We introduce SpDISTAL, a compiler for sparse tensor algebra that targets distributed systems. SpDISTAL combines separate descriptions of tensor algebra expressions, sparse data structures, data distribution, and computation distribution. Thus, it enables distributed execution of sparse tensor algebra expressions with a wide variety of sparse data structures

Greeshma R, Rudra Banerjee

The electronic, magnetic, and thermodynamic properties of ordered and chemically disordered FeRh alloy is studied using ab-initio methods. The equiatomic Fe$_{50}$Rh$_{50}$ composition is reported for both ordered and disordered phases. Chemically disordered Fe$_x$Rh$_{100-x}$ is reported and the effect of disorder on electronic and magnetic properties is di

C. Pellet-Mary, M. Perdriat, P. Huillery, G. Hétet

We study relaxation processes of the spins of dipolar-coupled negatively charged nitrogen vacancy (NV$^-$) centers under transverse electric and magnetic fields. Specifically, we uncover regimes where flip-flop, double-flip processes as well as mixing induced by local electric fields play a significant role in NV-NV cross-relaxation. Our results are relevant

Hamid Naderiyan

This paper studies a version of the counting problem in dynamical systems that is of interest, especially in conformal dynamical systems where the functions of the systems are angle preserving. Recently, M. Pollicott and M. Urba\'{n}ski published a result in this context for D-generic systems where the complex transfer operator behaves nicely on the critical

Mubashir Imran, Hongzhi Yin, Tong Chen, Nguyen Quoc Viet Hung

Owing to its nature of scalability and privacy by design, federated learning (FL) has received increasing interest in decentralized deep learning. FL has also facilitated recent research on upscaling and privatizing personalized recommendation services, using on-device data to learn recommender models locally. These models are then aggregated globally to obt

Shoma F. Kamijima, Yutaka Ohira

We investigate the escape process of cosmic rays (CRs) from perpendicular shock regions of a spherical shock propagating to a circumstellar medium with the Parker-spiral magnetic field. The diffusive shock acceleration in perpendicular shocks of supernova remnants (SNRs) is expected to accelerate CRs up to PeV without upstream magnetic field amplification. R

Xue Gong, Desmond J. Higham, Konstantinos Zygalakis

Many complex systems involve interactions between more than two agents. Hypergraphs capture these higher-order interactions through hyperedges that may link more than two nodes. We consider the problem of embedding a hypergraph into low-dimensional Euclidean space so that most interactions are short-range. This embedding is relevant to many follow-on tasks,

Zijue Chen, Keenan Granland, Rhys Newbury, Chao Chen

Orchard automation has attracted the attention of researchers recently due to the shortage of global labor force. To automate tasks in orchards such as pruning, thinning, and harvesting, a detailed understanding of the tree structure is required. However, occlusions from foliage and fruits can make it challenging to predict the position of occluded trunks an

Yotam Wolf, Amit Aharon-Steinberg, Binghai Yan, Tobias Holder

Electron hydrodynamics typically emerges in electron fluids with a high electron-electron collision rate. However, new experiments with thin flakes of WTe$_2$ have revealed that other momentum-conserving scattering processes can replace the role of the electron-electron interaction, thereby leading to a novel, so-called para-hydrodynamic regime. Here, we dev

Zhengqi Zhang, Zhi Zhou

Our aim is to study the backward problem, i.e. recover the initial data from the terminal observation, of the subdiffusion with time dependent coefficients. First of all, by using the smoothing property of solution operators and a perturbation argument of freezing the diffusion coefficients, we show a stability estimate in Sobolev spaces, under some smallnes

Francisco Martinez-Figueroa

Given $0<\alpha\leq\pi$, ${\epsilon}>0$ and $n$, we define random graphs on the $d$-dimensional sphere by drawing $n$ i.i.d. uniform random points for the vertices, and edges $u {\sim} v$ whenever the geodesic distance between $u$ and $v$ is ${\epsilon}$-close to ${\alpha}$. This model generalizes distance graphs on spheres, and also random Borsuk graphs. To

Zhizhen Qin, Tsui-Wei Weng, Sicun Gao

Path-tracking control of self-driving vehicles can benefit from deep learning for tackling longstanding challenges such as nonlinearity and uncertainty. However, deep neural controllers lack safety guarantees, restricting their practical use. We propose a new approach of learning almost-barrier functions, which approximately characterizes the forward invaria

Caleb Tung, Abhinav Goel, Fischer Bordwell, Nick Eliopoulos

Object detectors are vital to many modern computer vision applications. However, even state-of-the-art object detectors are not perfect. On two images that look similar to human eyes, the same detector can make different predictions because of small image distortions like camera sensor noise and lighting changes. This problem is called inconsistency. Existin

Zhongxu Wei, Shengshan Qin, Cui Ding, Jiangping Hu

Determining the pairing symmetry of single-layer FeSe on SrTiO$_3$ is the key to understanding the enhanced pairing mechanism; furthermore, it guides exploring new superconductors with high transition temperatures ($T_\mathrm{c}$). Despite significant efforts, it remains controversial whether the symmetry is the sign-preserving $s$- or the sign-changed $s_{\

Keisuke Kinoshita, Thilo von Neumann, Marc Delcroix, Christoph Boeddeker

Recent speaker diarization studies showed that integration of end-to-end neural diarization (EEND) and clustering-based diarization is a promising approach for achieving state-of-the-art performance on various tasks. Such an approach first divides an observed signal into fixed-length segments, then performs {\it segment-level} local diarization based on an E