January 2022 arXiv papers — page 71

Bibek S. Dhami, Ravi P. N. Tripathi, David J. Hoxie, Kannatassen Appavoo

With hybrid organic-inorganic perovskites increasing its technological reach, from photovoltaics solar cells to light-emitting devices, to nanoscale transistors, it is critical to establish the role of microstructures in dictating how carrier dynamics dictate device efficiency. Here we report on the ultrafast dynamics of charge carriers in hybrid perovskites

D. X. Horvath, K. Hodsagi, G. Takacs

Truncated Conformal Space Approach (TCSA) is a highly efficient method to compute spectra, operator matrix elements and time evolution in quantum field theories defined as relevant perturbations of 1+1-dimensional conformal field theories. However, similarly to other exact diagonalisation methods, TCSA is ridden with the "curse of dimensionality": the dimens

Timothée Goubault de Brugière, Marc Baboulin, Benoît Valiron, Simon Martiel

Linear reversible circuits represent a subclass of reversible circuits with many applications in quantum computing. These circuits can be efficiently simulated by classical computers and their size is polynomially bounded by the number of qubits, making them a good candidate to deploy efficient methods to reduce computational costs. We propose a new algorith

Jean-Michel Begon, Pierre Geurts

Compressing deep networks is essential to expand their range of applications to constrained settings. The need for compression however often arises long after the model was trained, when the original data might no longer be available. On the other hand, unlabeled data, not necessarily related to the target task, is usually plentiful, especially in image clas

Marko J. Rančić

In this theoretical manuscript I propose a scheme for entangling a single electron semiconductor spin qubit with a single electron semiconductor charge qubit in a triangular triple quantum dot configuration. Two out of three quantum dots are used to define a single electron semiconductor charge qubit. Furthermore, the spin qubit is embedded in the Zeeman sub

Yang Nan, Javier Del Ser, Simon Walsh, Carola Schönlieb

Removing the bias and variance of multicentre data has always been a challenge in large scale digital healthcare studies, which requires the ability to integrate clinical features extracted from data acquired by different scanners and protocols to improve stability and robustness. Previous studies have described various computational approaches to fuse singl

Yu Wang, Wujun Xie, Haochang Chen, David Day-Uei Li

This paper presents a low hardware consumption, resolution-configurable, automatically calibrating Gray code oscillator time-to-digital converter (TDC) in Xilinx 16nm UltraScale+, 20nm UltraScale and 28nm Virtex-7 field-programmable gate arrays (FPGAs). The proposed TDC has several innovations: 1) a sampling matrix to improve the resolution. 2) a virtual bin

Villiam Bortolotti, Leonardo Brizi, Germana Landi, Anastasiia Nagmutdinova

Accurate and efficient analysis of materials properties from Nuclear Magnetic Resonance (NMR) relaxation data requires robust and efficient inversion procedures. Despite the great variety of applications requiring to process two-dimensional NMR data (2DNMR), a few software tools are freely available. The aim of this paper is to present MUPen2DTool, an open-s

Fan Bao, Chongxuan Li, Jun Zhu, Bo Zhang

Diffusion probabilistic models (DPMs) represent a class of powerful generative models. Despite their success, the inference of DPMs is expensive since it generally needs to iterate over thousands of timesteps. A key problem in the inference is to estimate the variance in each timestep of the reverse process. In this work, we present a surprising result that

C. C. Espaillat, G. J. Herczeg, T. Thanathibodee, C. Pittman

The Hubble UV Legacy Library of Young Stars as Essential Standards (ULLYSES) Director's Discretionary Program of low-mass pre-main-sequence stars, coupled with forthcoming data from ALMA and JWST, will provide the foundation to revolutionize our understanding of the relationship between young stars and their protoplanetary disks. A comprehensive evaluation o

Zheng Sun, Yuanzhe Wei, Kailiang Wu

This paper presents a systematic theoretical framework to derive the energy identities of general implicit and explicit Runge--Kutta (RK) methods for linear seminegative systems. It generalizes the stability analysis of explicit RK methods in [Z. Sun and C.-W. Shu, SIAM J. Numer. Anal., 57 (2019), pp. 1158-1182]. The established energy identities provide a p

Ruilin Tong

We propose a general method for growing neural network with shared parameter by matching trained network to new input. By leveraging Hoeffding's inequality, we provide a theoretical base for improving performance by adding subnetwork to existing network. With the theoretical base of adding new subnetwork, we implement a matching method to apply trained subne

Pavel Blinov, Arina Reshetnikova, Aleksandr Nesterov, Galina Zubkova

The paper describes the open Russian medical language understanding benchmark covering several task types (classification, question answering, natural language inference, named entity recognition) on a number of novel text sets. Given the sensitive nature of the data in healthcare, such a benchmark partially closes the problem of Russian medical dataset abse

Iwan Morton-Blake, Steven D. Biller

The construction of large-scale liquid scintillator detectors is complicated by the need to separate the scintillation region from photomultiplier tubes (PMTs) due to their intrinsic radioactivity. This is generally done using acrylic or nylon barriers, whose own activity can also lead to substantial reduction of the fiducial detection volume for a number of

V. V. Ryazanov

All real physical processes, including of the first-passage time, occur with a change in entropy. This circumstance is not taken into account when studying the first-passage time, but is illustrated in this article using the example of electron transfer through a metallic double dot. The statistics of the first-passage time of a random process N(t) for elect

Hamdy Mubarak, Sabit Hassan, Shammur Absar Chowdhury, Firoj Alam

The emergence of the COVID-19 pandemic and the first global infodemic have changed our lives in many different ways. We relied on social media to get the latest information about the COVID-19 pandemic and at the same time to disseminate information. The content in social media consisted not only health related advises, plans, and informative news from policy

Igor Strakovsky, Simon Širca, William J. Briscoe, Alexandre Deur

Phenomenological amplitudes obtained in partial-wave analyses (PWA) of single-pion photoproduction are used to evaluate the contribution of this process to the Gerasimov-Drell-Hearn (GDH), Baldin and Gell-Mann-Goldberger-Thirring (GGT) sum rules, by integrating up to 2 GeV in photon energy. Our study confirms that the single-pion contribution to all these su

Zoe Papakipos, Joanna Bitton

We introduce AugLy, a data augmentation library with a focus on adversarial robustness. AugLy provides a wide array of augmentations for multiple modalities (audio, image, text, & video). These augmentations were inspired by those that real users perform on social media platforms, some of which were not already supported by existing data augmentation librari

Zehui Chen, Zhenyu Li, Shiquan Zhang, Liangji Fang

Object detection through either RGB images or the LiDAR point clouds has been extensively explored in autonomous driving. However, it remains challenging to make these two data sources complementary and beneficial to each other. In this paper, we propose \textit{AutoAlign}, an automatic feature fusion strategy for 3D object detection. Instead of establishing

Ivan Letteri, Giuseppe Della Penna, Giovanni De Gasperis, Abeer Dyoub

Stock market forecasting is a lucrative field of interest with promising profits but not without its difficulties and for some people could be even causes of failure. Financial markets by their nature are complex, non-linear and chaotic, which implies that accurately predicting the prices of assets that are part of it becomes very complicated. In this paper

Nicola Rizzo, Veli Mäkinen

Pattern matching on graphs has been widely studied lately due to its importance in genomics applications. Unfortunately, even the simplest problem of deciding if a string appears as a subpath of a graph admits a quadratic lower bound under the Orthogonal Vectors Hypothesis (Equi et al. ICALP 2019, SOFSEM 2021). To avoid this bottleneck, the research has shif

Nathan Chapelier-Laget, Christophe Hohlweg

Given an affine Coxeter group $W$, the corresponding Shi arrangement is a refinement of the corresponding Coxeter hyperplane arrangements that was introduced by Shi to study Kazhdan-Lusztig cells for $W$. In particular, Shi showed that each region of the Shi arrangement contains exactly one element of minimal length in $W$. Low elements in $W$ were introduce

Zhen Lei, Jie Liu, Zhaojie Yang

This paper focuses on a class of nonlinear Klein-Gordon equations in three dimensions, which are Hamiltonian perturbations of the linear Klein-Gordon equation with potential. The unperturbed dynamical system has a bound state with frequency $\omega$, a spatially localized and time periodic solution. In quantum mechanics, metastable states, which last longer

Shashank S. Pandey, Arnab Sarkar, Amna Ali, A. S. Majumdar

We consider the propagation of gravitational waves in the late time Universe with the presence of structure. Before detection, gravitational waves emitted from distant sources have to traverse through regions of spacetime which are far from smooth and homogeneous. We investigate the effect of inhomogeneities on the observables associated with the gravitation

V. Manuilov

It was shown recently by M. Lorentz and R. Willett that all bounded derivations of the uniform Roe algebras of metric spaces of bounded geometry are inner. Here we calculate the space of outer derivations of the uniform Roe algebras with coefficients in uniform Roe bimodules related to various metrics on the two copies of the given space. We also give some r

Santiago Mazuelas, Mauricio Romero, Peter Grünwald

Supervised classification techniques use training samples to learn a classification rule with small expected 0-1 loss (error probability). Conventional methods enable tractable learning and provide out-of-sample generalization by using surrogate losses instead of the 0-1 loss and considering specific families of rules (hypothesis classes). This paper present

Daojing Guo, Khaled Nakhleh, I-Hong Hou, Sastry Kompella

This paper introduces a new theoretical framework for optimizing second-order behaviors of wireless networks. Unlike existing techniques for network utility maximization, which only considers first-order statistics, this framework models every random process by its mean and temporal variance. The inclusion of temporal variance makes this framework well-suite

Edgar Covantes Osuna, Dirk Sudholt

Niching methods have been developed to maintain the population diversity, to investigate many peaks in parallel and to reduce the effect of genetic drift. We present the first rigorous runtime analyses of restricted tournament selection (RTS), embedded in a ($\mu$+1) EA, and analyse its effectiveness at finding both optima of the bimodal function ${\rm T{\sm

Bibek S. Dhami, Vasudevan Iyer, Aniket Pant, Ravi P. N. Tripathi

Coupling between light and matter strongly depends on the polarization of the electromagnetic field and the nature of the excitations in the material. As hybrid perovskites emerge as a promising class of materials for light-based technologies like LEDs, lasers, and photodetectors, understanding the microscopic details of how photons couple to matter is criti

Ana M. Bianco, Graciela Boente, Wenceslao González-Manteiga, Ana Pérez-González

In this paper, we present three estimators of the ROC curve when missing observations arise among the biomarkers. Two of the procedures assume that we have covariates that allow to estimate the propensity and the estimators are obtained using an inverse probability weighting method or a smoothed version of it. The other one assumes that the covariates are re

Christophe Besse, Alexandre Capel, Grégory Faye, Guilhem Fouilhé

In this paper, we study the asymptotic behavior of the solutions of nonlocal bistable reaction-diffusion equations starting from compactly supported initial conditions. Depending on the relationship between the nonlinearity, the interaction kernel and the diffusion coefficient, we show that the solutions can either: propagate, go extinct or remain pinned. We

Irina A. Acharova, Margarita E. Sharina, Egor A. Kazakov

A method is proposed for determining the properties of type Ia supernovae from short-lived precursors -- Prompt SNIa. This method is based on the assumption that this subtype of type Ia supernovae exploded into low-metallicity globular clusters (GCs), and is responsible for the enrichment of the high-metallicity subgroup of GCs and circumgalactic clouds (CGC

Matthew McEneaney

Using the self-analyzing decay of the $\Lambda$, the longitudinal spin transfer $D_{LL'}$ to the hyperon from a polarized electron beam scattering off an unpolarized proton target can be determined. For $\Lambda$s produced in the current fragmentation region, this quantity is proportional to the helicity dependent fragmentation function $G_1^\Lambda$ and can

Philippe Laurençot, Bogdan-Vasile Matioc

Bounded weak solutions are constructed for a degenerate parabolic system with a full diffusion matrix, which is a generalized version of the thin film Muskat system. Boundedness is achieved with the help of a sequence $(\mathcal{E}_n)_{n\ge 2}$ of Liapunov functionals such that $\mathcal{E}_n$ is equivalent to the $L_n$-norm for each $n \ge 2$ and $\mathcal{

Chandrashekar Kuyyamudi, Shakti N. Menon, Sitabhra Sinha

We show that when cells communicate by contact-mediated interactions, heterogeneity in cell shapes and sizes leads to qualitatively distinct collective behavior in the tissue. For inter-cellular coupling that implements lateral inhibition, such disorder-driven transitions can substantially alter the asymptotic pattern of differentiated cells by modulating th

Yong Hu, Xianxin Wu, Brenden R. Ortiz, Xinloong Han

The recently discovered layered kagome metals AV$_3$Sb$_5$(A=K, Rb, Cs) have attracted much attention because of their unique combination of superconductivity, charge density wave (CDW) order, and nontrivial band topology. The CDW order with an in-plane 2x2 reconstruction is found to exhibit exotic properties, such as time-reversal symmetry breaking and rota

Dan Crisan, Prince Romeo Mensah

The Thermal Quasi-Geostrophic (TQG) equation is a coupled system of equations that governs the evolution of the buoyancy and the potential vorticity of a fluid. It has a local in time solution as proved in [4]. In this paper, we give a criterion for the blow-up of solutions to the Thermal Quasi-Geostrophic equation, in the spirit of the classical Beale-Kato-

Joel David Hamkins, Davide Leonessi

We introduce the game of infinite Hex, extending the familiar finite game to natural play on the infinite hexagonal lattice. Whereas the finite game is a win for the first player, we prove in contrast that infinite Hex is a draw -- both players have drawing strategies. Meanwhile, the transfinite game-value phenomenon, now abundantly exhibited in infinite che

Antonio Bueno, Rafael López

In this paper we study the linear Weingarten equation defined by the fully non-linear PDE $$a\, \mbox{div}\frac{Du}{\sqrt{1+|Du|^2}}+b\, \frac{\mbox{det}D^2u}{(1+|Du|^2)^2}=\phi\left(\frac{1}{\sqrt{1+|Du|^2}}\right)$$ in a domain $\Omega\subset\mathbb{R}^2$, where $\phi\in C^1([-1,1])$ and $a,b\in\mathbb{R}$. We approach the existence of radial solutions whe

Snigdha Ghosh, Nilanjan Chaudhuri, Sourav Sarkar, Pradip Roy

The photon self-energy from chirally imbalanced quark matter is evaluated at finite temperature and density using the real time formulation of thermal field theory. The analytic structure is explored in detail exposing the cut structure which corresponds to a variety of physical scattering and decay processes in the medium and their thresholds. The mass of t

Claire L. Davies, Evan A. Rich, Tim J. Harries, John D. Monnier

We present multi-instrument observations of the disc around the Herbig~Ae star, HD~145718, employing geometric and Monte Carlo radiative transfer models to explore the disc orientation, the vertical and radial extent of the near infrared (NIR) scattering surface, and the properties of the dust in the disc surface and sublimation rim. The disc appears incline

K. P. Khemchandani, A. Martínez Torres, Sang-Ho Kim, Seung-il Nam

In this talk I review the findings of our recent works where we have studied the decay of $N^*(1895)$ and the implications of such properties on the photoproduction of light hyperons. I discuss that meson-baryon interactions play an essential role in describing the nature of $N^*(1895)$ and report the details of our investigation of its decays to different m

Eduardo Guendelman, Ramon Herrera, David Benisty

A unified multi scalar field model with three flat regions is discussed. The three flat regions are the inflation, early and late dark energy epochs. The potential is obtained by a spontaneous breaking of scale invariance generated by Non Riemannian Measures of integration (or Two Measures Theories (TMT)).We define the scale invariant couplings of the scalar

Andreas Kabel, Keith Hall, Tom Ouyang, David Rybach

This paper proposes a framework to improve the typing experience of mobile users in morphologically rich languages. Smartphone keyboards typically support features such as input decoding, corrections and predictions that all rely on language models. For latency reasons, these operations happen on device, so the models are of limited size and cannot easily co

Simon Schmitt, John Shawe-Taylor, Hado van Hasselt

To accumulate knowledge and improve its policy of behaviour, a reinforcement learning agent can learn `off-policy' about policies that differ from the policy used to generate its experience. This is important to learn counterfactuals, or because the experience was generated out of its own control. However, off-policy learning is non-trivial, and standard rei

Ioannis Papantonis, Vaishak Belle

Machine learning (ML) applications have automated numerous real-life tasks, improving both private and public life. However, the black-box nature of many state-of-the-art models poses the challenge of model verification; how can one be sure that the algorithm bases its decisions on the proper criteria, or that it does not discriminate against certain minorit

M. Giulietti, M. Massardi, A. Lapi, M. Bonato

We investigate the radio-far infrared (FIR) correlation for a sample of $28$ bright high-redshift ($1 \lesssim z \lesssim 4$) star-forming galaxies selected in the FIR from the Herschel-ATLAS fields as candidates to be strongly gravitationally lensed. The radio information comes either from high sensitivity dedicated ATCA observations at $2.1$ GHz or from cr

Meadhbh O'Neill, Jeff Morgan, Kevin Burke

Process visualizations of data from manufacturing execution systems (MESs) provide the ability to generate valuable insights for improved decision-making. Industry 4.0 is awakening a digital transformation where advanced analytics and visualizations are critical. Exploiting MESs with data-driven strategies can have a major impact on business outcomes. The ad

Angelos Anastopoulos, Marco Benini

The homotopy theory of representations of nets of algebras over a (small) category with values in a closed symmetric monoidal model category is developed. We illustrate how each morphism of nets of algebras determines a change-of-net Quillen adjunction between the model categories of net representations, which is furthermore a Quillen equivalence when the mo

Michail Spitieris, Ingelin Steinsland

We introduce a computational efficient data-driven framework suitable for quantifying the uncertainty in physical parameters and model formulation of computer models, represented by differential equations. We construct physics-informed priors, which are multi-output GP priors that encode the model's structure in the covariance function. This is extended into

Jeong Ho Han, Dalmin Bae, Yong-il Shin

We describe a synthetic three-leg Hall ladder system with a tunable magnetic flux for neutral $^{173}$Yb atoms in a one-dimensional optical lattice. The ladder legs are formed by three hyperfine ground spin states of the atoms, and the complex interleg links are generated through Raman couplings between the spin states using multiple laser beams. The effecti

Tim Whittaker, William E. East, Stephen R. Green, Luis Lehner

There is growing interest in the detection and characterization of gravitational waves from postmerger oscillations of binary neutron stars. These signals contain information about the nature of the remnant and the high-density and out-of-equilibrium physics of the postmerger processes, which would complement any electromagnetic signal. However, the construc

Yi Lei, Shan Yang, Xinsheng Wang, Lei Xie

Expressive synthetic speech is essential for many human-computer interaction and audio broadcast scenarios, and thus synthesizing expressive speech has attracted much attention in recent years. Previous methods performed the expressive speech synthesis either with explicit labels or with a fixed-length style embedding extracted from reference audio, both of

Gencer Sumbul, Jun Xiang, Nimisha Thekke Madam, Begüm Demir

Remote sensing (RS) images are usually stored in compressed format to reduce the storage size of the archives. Thus, existing content-based image retrieval (CBIR) systems in RS require decoding images before applying CBIR (which is computationally demanding in the case of large-scale CBIR problems). To address this problem, in this paper, we present a joint

Garyfallos Konstantinoudis, Virgilio Gómez-Rubio, Michela Cameletti, Monica Pirani

COVID-19 related deaths underestimate the pandemic burden on mortality because they suffer from completeness and accuracy issues. Excess mortality is a popular alternative, as it compares observed with expected deaths based on the assumption that the pandemic did not occur. Expected deaths had the pandemic not occurred depend on population trends, temperatur

Timothée Goubault de Brugière, Marc Baboulin, Benoît Valiron, Simon Martiel

Current proposals for quantum compilers require the synthesis and optimization of linear reversible circuits and among them CNOT circuits. Since these circuits represent a significant part of the cost of running an entire quantum circuit, we aim at reducing their size. In this paper we present a new algorithm for the synthesis of CNOT circuits based on the s

Kalle Ala-Mattinen, Matti Heikinheimo, Kimmo Kainulainen, Kimmo Tuominen

We solve coupled momentum-dependent Boltzmann equations for the phase space distribution of cosmic relic particles, without resorting to approximations of assuming kinetic equilibrium or neglecting backscattering or elastic interactions. Our method is amendable to precision numerical computations. To test it, we consider two benchmark models where the moment

Amaury Trujillo, Stefano Cresci

The subreddit r/The_Donald was repeatedly denounced as a toxic and misbehaving online community, reasons for which it faced a sequence of increasingly constraining moderation interventions by Reddit administrators. It was quarantined in June 2019, restricted in February 2020, and finally banned in June 2020, but despite precursory work on the matter, the eff

Nicolas Wijsen, Angels Aran, Camilla Scolini, David Lario

We model the energetic storm particle (ESP) event of 14 July 2012 using the energetic particle acceleration and transport model named PARADISE, together with the solar wind and coronal mass ejection (CME) model named EUHFORIA. The simulation results illustrate both the capabilities and limitations of the utilised models. We show that the models capture some

Marcio Costa Araújo Filho

We prove some inequalities of Payne-P\'olya-Weinberger-Yang type for eigenvalues of fourth-order elliptic operators in weighted divergence form on complete Riemannian manifolds which generalizes the corresponding result for the clamped plate problem. We also prove estimates for lower order eigenvalues that contain some of the estimates from the literature. A

W. A. Zúñiga-Galindo

In this article we introduce the ultrametric networks which are p-adic continuous analogues of the standard Markov state models constructed using master equations. A p-adic transition network (or an ultrametric network) is a model of a complex system consisting of a hierarchical energy landscape, a Markov process on the energy landscape, and a master equatio

Jaehoon Pyun, Younggeol Cho, Seon Gyeom Kim, Woohun Lee

As In-Vehicle Infotainment Systems (IVIS) grow in complexity, selecting external points of interest (POIs) using traditional touchscreens significantly increases driver cognitive load. Recent evidence indicates that this visual-motor overload induces dangerous "hand-before-eye" behaviors, degrading primary driving tasks. To address this, we propose Point and

Daniel Galvis, David J. Hodson, Kyle C. A. Wedgwood

We studied the effects of spatial configuration on collective dynamics in a nearest-neighbour and diffusively coupled lattice of heterogeneous nodes. The networks contained nodes from two populations, which differed in their intrinsic excitability. Initially, these populations were uniformly and randomly distributed throughout the lattice. We then developed

P. Welter, J. Rhensius, A. Morales, M. S. Wörnle

Scanning magnetometry with nitrogen-vacancy (NV) centers in diamond has emerged as a powerful microscopy for studying weak stray field patterns with nanometer resolution. Due to the internal crystal anisotropy of the spin defect, however, external bias fields -- critical for the study of magnetic materials -- must be applied along specific spatial directions

Shengbing Deng, Xingliang Tian

The goal of this paper is to study the existence of peak solutions for the following fractional Schr\"{o}dinger-Poisson system: \begin{eqnarray*} \left\{ \arraycolsep=1.5pt \begin{array}{ll} \varepsilon^{2s}(-\Delta)^{s}u+u+\phi u=u^p,\ \ \ &\ \mbox{in}\ \Omega,\\[2mm] (-\Delta)^{s}\phi=u^2,\ \ \ &\ \mbox{in}\ \Omega,\\[2mm] u=\phi=0,\ \ \ \ &\ \mbox{in}\ \m

Malte Henkel

The application of quantum Langevin equations for the study of non-equilibrium relaxations is illustrated in the exactly solved quantum spherical model. Tutorial sections on the physical background of non-markovian quantum noise, the spherical model quantum phase transition, the long-time limit of the quantum Langevin equation of the spherical model and phys

Vira Shyta, Flavio S. Nogueira, Jeroen van den Brink

While the phase structure of the $U(1)\times U(1)$-symmetric Higgs theory is still under debate, a version of this theory with an additional Chern-Simons term was recently shown to undergo a second-order phase transition [V. Shyta, J. van den Brink, and F. S. Nogueira, Phys. Rev. Lett. 127, 045701 (2021)]. This theory is dual to a topological field theory of

Malte Breuer, Ulrike Meyer, Susanne Wetzel

To this day, there are still some countries where the exchange of kidneys between multiple incompatible patient-donor pairs is restricted by law. Typically, legal regulations in this context are put in place to prohibit coercion and manipulation in order to prevent a market for organ trade. Yet, in countries where kidney exchange is practiced, existing platf

Volker Betz, Steffen Polzer

We show that the effective mass of the Fr\"ohlich Polaron is bounded below by $c\alpha^{2/5}$ for some constant $c>0$ and for all coupling constants $\alpha$. The proof uses the point process representation of the path measure of the Fr\"ohlich Polaron.

Venktesh V, Mukesh Mohania, Vikram Goyal

Keyphrase extraction from a given document is the task of automatically extracting salient phrases that best describe the document. This paper proposes a novel unsupervised graph-based ranking method to extract high-quality phrases from a given document. We obtain the contextualized embeddings from pre-trained language models enriched with topic vectors from

Piero Fraternali, Federico Milani, Rocio Nahime Torres, Niccolò Zangrando

The application of Deep Neural Networks (DNNs) to a broad variety of tasks demands methods for coping with the complex and opaque nature of these architectures. When a gold standard is available, performance assessment treats the DNN as a black box and computes standard metrics based on the comparison of the predictions with the ground truth. A deeper unders

Guosheng Jiang, Zhehui Wang, Jintian Zhu

Let $ \Omega \subsetneq \mathbf{R}^n\,(n\geq 2)$ be an unbounded convex domain. We study the minimal surface equation in $\Omega$ with boundary value given by the sum of a linear function and a bounded uniformly continuous function in $ \mathbf{R}^n$. If $ \Omega $ is not a half space, we prove that the solution is unique. If $ \Omega $ is a half space, we p

Oussama Bensaid

Introduced by Gromov in the 80's, coarse embeddings are a generalization of quasi-isometric embeddings when the control functions are not necessarily affine. In this paper, we will be particularly interested in coarse embeddings between symmetric spaces and Euclidean buildings. The quasi-isometric case is very well understood thanks to the rigidity results f

Chikh Bouzar, Meryem Slimani

Asymptotic almost automorphy is introduced and studied in the context of some algebras of generalized functions. We also give applications to neutral difference differential systems in the framework of such generalized functions.

Adrian Ruckhofer, Marco Sacchi, Anthony Payne, Andrew P. Jardine

Large-area single-crystal monolayers of two-dimensional (2D) materials such as graphene and hexagonal boron nitride (h-BN) can be grown by chemical vapour deposition (CVD). However, the high temperatures and fast timescales at which the conversion from a gas-phase precursor to the 2D material appear, make it extremely challenging to simultaneously follow the

Hussain Ahmed Khan, Yogesh

Realizing the inflationary epoch driven by a pseudo-Nambu Goldstone boson (pNGB) could ensure the coveted flatness, and the sub-Planckian scales related to the dynamics of the paradigm. In this work, we have taken the most general form of such a scenario: Goldstone inflation proposed in \cite{croon}, and studied the model in Einstein-Gauss-Bonnet gravity. Na

T. Tony Cai, Rong Ma

Motivated by applications in single-cell biology and metagenomics, we investigate the problem of matrix reordering based on a noisy disordered monotone Toeplitz matrix model. We establish the fundamental statistical limit for this problem in a decision-theoretic framework and demonstrate that a constrained least squares estimator achieves the optimal rate. H

Roshni Chakraborty, Ritwika Das, Joydeep Chandra

Signed link prediction in graphs is an important problem that has applications in diverse domains. It is a binary classification problem that predicts whether an edge between a pair of nodes is positive or negative. Existing approaches for link prediction in unsigned networks cannot be directly applied for signed link prediction due to their inherent differe

Noboru Ito

\"Ostlund (2001) showed that all planar isotopy invariants of generic plane curves that are unchanged under cusp moves and triple point moves, and of finite degree (in self-tangency moves) are trivial. Here the term "of finite degree" means Arnold-Vassiliev type. It implies the conjecture, which was often called \"Ostlund conjecture: "Types I and III Reideme

Jianfei Li, Han Feng, Xiaosheng Zhuang

In this paper, we develop a general theoretical framework for constructing Haar-type tight framelets on any compact set with a hierarchical partition. In particular, we construct a novel area-regular hierarchical partition on the 2-sphere and establish its corresponding spherical Haar tight framelets with directionality. We conclude by evaluating and illustr

Selahattin Cansiz, Cem Kesim, Sevval Nur Bektas, Zeynep Kulali

The Henle's fiber layer (HFL) in the retina carries valuable information on the macular condition of an eye. However, in the common practice, this layer is not separately segmented but rather included in the outer nuclear layer since it is difficult to perceive HFL contours on standard optical coherence tomography (OCT) imaging. Due to its variable reflectiv

Weichao Guo, Guoping Zhao

In this paper, we give several characterizations for the boundedness of multilinear Rihaczek distributions acting from Wiener amalgam spaces to modulation and Fourier modulation spaces. Moreover, we establish the crucial self-improvement property which has its independent significance. As applications, sharp exponents are established for the boundedness in s

Shashank Shekhar, Adesh Bansode, Asif Salim

Most of the machine learning models have associated hyper-parameters along with their parameters. While the algorithm gives the solution for parameters, its utility for model performance is highly dependent on the choice of hyperparameters. For a robust performance of a model, it is necessary to find out the right hyper-parameter combination. Hyper-parameter

C. Ramya, Anamay Tengse

Read-once Oblivious Algebraic Branching Programs (ROABPs) compute polynomials as products of univariate polynomials that have matrices as coefficients. In an attempt to understand the landscape of algebraic complexity classes surrounding ROABPs, we study classes of ROABPs based on the algebraic structure of these coefficient matrices. We study connections be

O. A. Kurichin, P. A. Kislitsyn, A. V. Ivanchik

The primordial $^4$He abundance (Y$_p$) is one of the key characteristics of Primordial Nucleosynthesis processes that occurred in the first minutes after the Big Bang. Its value depends on the baryon/photon ratio $\eta\equiv n_b/n_{\gamma}$, and is also sensitive to the relativistic degrees of freedom which affect the expansion rate of the Universe at the r

J. C. G. Henriques, B. Amorim, R. M. Ribeiro, N. M. R. Peres

In this paper we discuss the optical response due to the excitonic effect of two types of hBN bilayers: AB and AA'. Understanding the properties of these bilayers is of great utility to the study of twisted bilayers at arbitrary angles, since these two configurations correspond to the limit cases of 0 and 60 degree rotation. To obtain the excitonic response

Laurent Lamy, Baptiste Cecconi, Stéphane Aicardi, Corentin Louis

In this comment of the article [arXiv:2002.01150] "Locating the source field lines of Jovian decametric radio emissions" by YuMing Wang et al., 2020, we discuss the assumptions used by the authors to compute the beaming angle of Jupiter s decametric emissions induced by the moon Io. Their method, relying on multi-point radio observations, was applied to a si

Zhongkui Kuang, Kamil Serafin, Xingbo Zhao, James P. Vary

We study all-charm tetraquarks in the front form of Hamiltonian dynamics using the many-body basis function approach known as basis light-front quantization. The model Hamiltonian contains transverse and longitudinal confining potentials and a one-gluon-exchange effective potential. We calculate masses of two-charm-two-anticharm states focusing on the lowest

Mahmood Alzubaidi, Marco Agus, Khalid Alyafei, Khaled A Althelaya

Developing innovative informatics approaches aimed to enhance fetal monitoring is a burgeoning field of study in reproductive medicine. Several reviews have been conducted regarding Artificial intelligence (AI) techniques to improve pregnancy outcomes. They are limited by focusing on specific data such as mother's care during pregnancy. This systematic surve

Jiayi Zhu, Qing Guo, Felix Juefei-Xu, Yihao Huang

Modern face recognition systems (FRS) still fall short when the subjects are wearing facial masks, a common theme in the age of respiratory pandemics. An intuitive partial remedy is to add a mask detector to flag any masked faces so that the FRS can act accordingly for those low-confidence masked faces. In this work, we set out to investigate the potential v

Achintya kr. Sarkar, Zheng-Hua Tan

Deep representation learning has gained significant momentum in advancing text-dependent speaker verification (TD-SV) systems. When designing deep neural networks (DNN) for extracting bottleneck features, key considerations include training targets, activation functions, and loss functions. In this paper, we systematically study the impact of these choices o

Hamza Amrani, Daniela Micucci, Marco Mobilio, Paolo Napoletano

Several techniques have been proposed to address the problem of recognizing activities of daily living from signals. Deep learning techniques applied to inertial signals have proven to be effective, achieving significant classification accuracy. Recently, research in human activity recognition (HAR) models has been almost totally model-centric. It has been p

Wayan Wicke, Rebecca C. Felsheim, Lukas Brand, Vahid Jamali

In molecular communication (MC), combining different types of particles at the transmitter is a degree of freedom which can be utilized to improve performance. In this paper, we address the problem of pulse shaping to simplify time synchronization requirements by exploiting and combining the received signal characteristics of particles of different sizes. In

Kestutis Cesnavicius

We overview a web of conjectures about torsors under reductive groups over regular rings and survey some techniques that have been used for making progress on such problems.

Giseop Kim, Seungsang Yun, Jeongyun Kim, Ayoung Kim

Accurate 3D point cloud map generation is a core task for various robot missions or even for data-driven urban analysis. To do so, light detection and ranging (LiDAR) sensor-based simultaneous localization and mapping (SLAM) technology have been elaborated. To compose a full SLAM system, many odometry and place recognition methods have independently been pro

Yann Cado, Mariano Quirós

We study a modification of the Higgs inflation scenario where we introduce an extra scalar $\phi$, with mass $m$, coupled to the Ricci scalar as $g\phi^2 R$, and mixed with the Higgs field $h$ via the Lagrangian term $\mu \phi h^2$. Both fields participate in the inflation process in a unitary theory that predicts values of the cosmological observables in ag

Alexander Dallmann, Johannes Kohlmann, Daniel Zoller, Andreas Hotho

Multiplayer Online Battle Arena (MOBA) games such as Dota 2 attract hundreds of thousands of players every year. Despite the large player base, it is still important to attract new players to prevent the community of a game from becoming inactive. Entering MOBA games is, however, often demanding, requiring the player to learn numerous skills at once. An impo

Nikos Papanikolaou, Giacomo Vaccario, Erik Hormann, Renaud Lambiotte

We study the effect of group interactions on the emergence of consensus in a spin system. Agents with discrete opinions $\{0,1\}$ form groups. They can change their opinion based on their group's influence (voter dynamics), but groups can also split and merge (adaptation). In a hypergraph, these groups are represented by hyperedges of different sizes. The he

Luiz Carlos Ryff

It has been advocated by Bell and Bohm that the Einstein-Podolsky-Rosen (EPR) correlations are mediated through faster-than-light (FTL) interactions. In a previous paper a way to avoid causal paradoxes derived from this FTL hypothesis (via the breakdown of Lorentz symmetry) has been suggested. Lorentz transformations would remain valid, but there would be no

F. Marin, T. Barnouin, E. Lopez-Rodriguez

The Faint Object Camera (FOC) aboard the Hubble Space Telescope (HST) observed 26 individual active galactic nuclei (AGNs) in ultraviolet imaging polarimetry between 1990 and 2002. Tremendous progresses have been made thanks to those high spatial resolution, high signal-to-noise ratio observations, such as the identification of the location of hidden active