October 2022 arXiv papers — page 108

Luccas Campos, Simão Correia, Luiz Gustavo Farah

We consider the initial value problem associated to the inhomogeneous nonlinear Schr\"o\-din\-ger equation, \begin{equation} iu_t + \Delta u +\mu|x|^{-b}|u|^{\alpha}u=0, \quad u_0\in H^s(\mathbb R^N) \text{ or } u_0 \in\dot H ^s(\mathbb R^N), \end{equation} with $\mu=\pm 1$, $b > 0$, $s\geq 0$ and $0 < \alpha \leq \frac{4-2b}{N-2s}$. By means of an adapted v

S. I. Kruglov

Thermodynamics of magnetically charged black holes in Anti-de Sitter space in an extended phase space is studied. The cosmological constant is considered as a pressure and the black hole mass is treated as the chemical entalpy. The black hole thermodynamics is similar to the Van der Waals liquid-gas thermodynamics. Quantities conjugated to the nonlinear elec

Peter B. Kronheimer, Tomasz S. Mrowka

We calculate the singular instanton homology with local coefficients for the simplest n-strand braids in $S^1 \times S^2$ for all odd n, describing these homology groups and their module structures in terms of the coordinate rings of explicit algebraic curves. The calculation is expected to be equivalent to computing the quantum cohomology ring of a certain

Avirup De, Dharmalingam Prabhakaran, Sunil Nair

The nontrivial topology of quasiparticle wavefunctions can manifest themselves in the form of observable surface states. This is now well established in electronic systems, with Dirac and Weyl semimetals bringing to fore the exotic nature of these topologically protected entities. Magnons - which refer to collective excitations of localized spins - offer ano

Daniel Bäumer, Sabine Hittmeir, Rupert Klein

Quasi-geostrophic (QG) theory is of fundamental importance in the study of large-scale atmospheric flows. In recent years, there has been growing interest in extending the classical QG plus Ekman friction layer model (QG-Ekman) to systematically include additional physical processes known to significantly contribute to real-life weather phenomena. This paper

Anna Maria Candela, Caterina Sportelli

In this paper we consider the following coupled gradient-type quasilinear elliptic system \begin{equation*} \left\{ \begin{array}{ll} - {\rm div} ( a(x, u, \nabla u) ) + A_t (x, u, \nabla u) = G_u(x, u, v) &\hbox{ in $\Omega$,}\\[10pt] - {\rm div} ( b(x, v, \nabla v) ) + B_t(x, v, \nabla v) = G_v\left(x, u, v\right) &\hbox{ in $\Omega$,}\\[10pt] u = v = 0 &\

Vladimir Iashin, Weidi Xie, Esa Rahtu, Andrew Zisserman

The objective of this paper is audio-visual synchronisation of general videos 'in the wild'. For such videos, the events that may be harnessed for synchronisation cues may be spatially small and may occur only infrequently during a many seconds-long video clip, i.e. the synchronisation signal is 'sparse in space and time'. This contrasts with the case of syn

Jinhui Ye, Wenxiang Jiao, Xing Wang, Zhaopeng Tu

Sign language gloss translation aims to translate the sign glosses into spoken language texts, which is challenging due to the scarcity of labeled gloss-text parallel data. Back translation (BT), which generates pseudo-parallel data by translating in-domain spoken language texts into sign glosses, has been applied to alleviate the data scarcity problem. Howe

Elaine Crooks, Yini Du

In this paper, we present an approach to characterising fast-reaction limits of systems with nonlinear diffusion, when there are either two reaction-diffusion equations, or one reaction-diffusion equation and one ordinary differential equation, on unbounded domains. Here, we replace the terms of the form uxx in usual reaction-diffusion equation, which repres

Stefano Pozza, Niel Van Buggenhout

The solution of systems of non-autonomous linear ordinary differential equations is crucial in a variety of applications, such us nuclear magnetic resonance spectroscopy. A new method with spectral accuracy has been recently introduced in the scalar case. The method is based on a product that generalizes the convolution. In this work, we show that it is poss

Congzheng Liu

This paper introduces the two-level capacitated vehicle routing problem (2S-CVRP). This problem combines the two-level bin packing problem and the vehicle routing problem into an integrated framework. The problem itself is an NP-hard problem and it can be seen as an extension to the traditional capacitated vehicle routing problem (CVRP). We propose this exte

Misao Sasaki, Valeri Vardanyan, Vicharit Yingcharoenrat

We propose a novel mechanism for significantly enhancing the amplitude of primordial electromagnetic fields during inflation. Similar to existing proposals, our idea is based on parametric resonance effects due to conformal-symmetry-breaking coupling of a gauge field and the inflaton. Our proposed scenario, however, significantly differs from previously stud

Ajay Chawda, Axel Vierling, Karsten Berns

In recent years, convolutional neural networks (CNNs) are used in a large number of tasks in computer vision. One of them is object detection for autonomous driving. Although CNNs are used widely in many areas, what happens inside the network is still unexplained on many levels. Our goal is to determine the effect of Intrinsic dimension (i.e. minimum number

Fernando Casas, Jesús María Sanz-Serna, Luke Shaw

For systems of the form $\dot q = M^{-1} p$, $\dot p = -Aq+f(q)$, common in many applications, we analyze splitting integrators based on the (linear/nonlinear) split systems $\dot q = M^{-1} p$, $\dot p = -Aq$ and $\dot q = 0$, $\dot p = f(q)$. We show that the well-known Strang splitting is optimally stable in the sense that, when applied to a relevant mode

V. Jeganathan, K. Alba, R. Ostilla-Monico

Since Taylor's seminal paper, the existence of large-scale quasi-axisymmetric structures has been a matter of interest when studying Taylor-Couette flow. In this manuscript, we probe their formation in the highly turbulent regime by conducting a series of numerical simulations at a fixed Reynolds number $Re_s=3.6\times 10^4$ while varying the Coriolis parame

A. Urdangarin, T. Goicoa, M. D. Ugarte

The concept of spatial confounding is closely connected to spatial regression, although no general definition has been established. A generally accepted idea of spatial confounding in spatial regression models is the change in fixed effects estimates that may occur when spatially correlated random effects collinear with the covariate are included in the mode

Md Ekramul Hossain, Muhammad Ashad Kabir, Lihong Zheng, Dave L. Swain

Increased biosecurity and food safety requirements may increase demand for efficient traceability and identification systems of livestock in the supply chain. The advanced technologies of machine learning and computer vision have been applied in precision livestock management, including critical disease detection, vaccination, production management, tracking

Peter Ouwehand

In stochastic analysis, the flow of information through time is typically modelled using a filtration. We introduce some of the basic ideas involving enlargements of filtration. Here, we focus mainly on initial enlargements, where a given filtration is enlarged with knowledge of an additional random variable. This has applications to the modelling of insider

Adam Clay, Tyrone Ghaswala

We show that for a surface $S$ with positive genus and one boundary component, the mapping class of a Dehn twist along a curve parallel to the boundary is cofinal in every left ordering of the mapping class group $\operatorname{Mod}(S)$. We apply this result to show that one of the usual definitions of the fractional Dehn twist coefficient -- via translation

Raúl Quintero-Monsebaiz, Enzo Monino, Antoine Marie, Pierre-François Loos

Here, we build on the works of Scuseria (et al.) http://dx.doi.org/10.1063/1.3043729 and Berkelbach https://doi.org/10.1063/1.5032314 to show connections between the Bethe-Salpeter equation (BSE) formalism combined with the $GW$ approximation from many-body perturbation theory and coupled-cluster (CC) theory at the ground- and excited-state levels. In partic

Yixin Guo, Hiroyuki Tajima

We theoretically investigate in-medium two- and three-body correlations in one-dimensional two-component Fermi gases with coexistent even-parity s-wave and odd-parity p-wave interactions. We find the solutions of the stable in-medium three-body cluster states such as Cooper triple by solving the corresponding in-medium variational equations. We further featu

Zhengqi He, Taro Toyoizumi

The ever-growing size of the foundation language model has brought significant performance gains in various types of downstream tasks. With the existence of side-effects brought about by the large size of the foundation language model such as deployment cost, availability issues, and environmental cost, there is some interest in exploring other possible dire

Andre Schidler, Robert Ganian, Manuel Sorge, Stefan Szeider

Treewidth and hypertree width have proven to be highly successful structural parameters in the context of the Constraint Satisfaction Problem (CSP). When either of these parameters is bounded by a constant, then CSP becomes solvable in polynomial time. However, here the order of the polynomial in the running time depends on the width, and this is known to be

Giambattista Albora, Lavinia Rossi-Mori, Andrea Zaccaria

Many bipartite networks describe systems where an edge represents a relation between a user and an item. Measuring the similarity between either users or items is the basis of memory-based collaborative filtering, a widely used method to build a recommender system with the purpose of proposing items to users. When the edges of the network are unweighted, the

Zhu-Bo Wang, Yan-Lei Zhang, Xin-Xin Hu, Guang-Jie Chen

Non-reciprocal optical components are indispensable in optical applications, and their realization without any magnetic field arose increasing research interests in photonics. Exciting experimental progress has been achieved by either introducing spatial-temporal modulation of the optical medium or combining Kerr-type optical nonlinearity with spatial asymme

Thomas Feys, Xavier Mestre, François Rottenberg

Massive multiple input multiple output (MIMO) systems are typically designed under the assumption of linear power amplifiers (PAs). However, PAs are typically most energy-efficient when operating close to their saturation point, where they cause non-linear distortion. Moreover, when using conventional precoders, this distortion coherently combines at the use

M. M. Glazov

We develop a model of the coherent exciton spin-valley dynamics in two-dimensional transition metal dichalcogenides under elastic strain. The strain splits the exciton radiative doublet in linearly polarized states. Consequently, it induces an effective magnetic field acting on the exciton pseudospin and causes its precession. As a result, under circularly p

Andy Jiang, Justin M. Turney, Henry F. Schaefer

We present the working equations for a reduced-scaling method of evaluating the perturbative triples (T) energy in coupled-cluster theory, through the tensor hypercontraction (THC) of the triples amplitudes ($t_{ijk}^{abc}$). Through our method we can reduce the scaling of the (T) energy from the traditional O($N^{7}$) to a more modest O($N^{5}$). We also di

Lorenzo Dall'Amico, Jackie Kleynhans, Laetitia Gauvin, Michele Tizzoni

Contact matrices are a commonly adopted data representation, used to develop compartmental models for epidemic spreading, accounting for the contact heterogeneities across age groups. Their estimation, however, is generally time and effort consuming and model-driven strategies to quantify the contacts are often needed. In this article we focus on household c

Ghaliah Alhamzi, Edwin Beggs

We show that the pure state evaluation map from $ M_{n}(\mathbb{C}) $ to $ C(\mathbb{C} \mathbb{P}^{n-1}) $ (a completely positive map of $ C^{*} $-algebras) extends to a cochain map from the universal calculus on $ M_{n}(\mathbb{C} ) $ to the holomorphic $ \bar{\partial} $ calculus on $ \mathbb{C} \mathbb{P}^{n-1} $. The method uses connections on Hilbert $

Hao Zhou, Man Lan, Yuanbin Wu, Yuefeng Chen

Due to the absence of connectives, implicit discourse relation recognition (IDRR) is still a challenging and crucial task in discourse analysis. Most of the current work adopted multi-task learning to aid IDRR through explicit discourse relation recognition (EDRR) or utilized dependencies between discourse relation labels to constrain model predictions. But

Dieter Coppens, Adnan Shahid, Eli De Poorter

Ultra-wideband technology has become increasingly popular for indoor localization and location-based services. This has led recent advances to be focused on reducing the ranging errors, whilst research focusing on enabling more reliable and energy efficient communication has been largely unexplored. The IEEE 802.15.4 UWB physical layer allows for several set

Rui Yin, Jing Liang, Benrong Mu

In this paper, we have studied the variation of the chaos bound in two regions of the torus-like black hole, i.e., the region close to the black hole horizon and the region at a certain distance from the black hole horizon. The angular momentum of the particle affects the effective potential and influences the magnitude of the chaotic behavior of the particl

Zihan Ye, Guanyu Yang, Xiaobo Jin, Youfa Liu

Zero-shot learning (ZSL) aims to identify unseen classes with zero samples during training. Broadly speaking, present ZSL methods usually adopt class-level semantic labels and compare them with instance-level semantic predictions to infer unseen classes. However, we find that such existing models mostly produce imbalanced semantic predictions, i.e. these mod

Alberto Dennunzio, Enrico Formenti, Luciano Margara

We investigate the computational complexity of deciding whether a given univariate integer polynomial p(x) has a factor q(x) satisfying specific additional constraints. When the only constraint imposed on q(x) is to have a degree smaller than the degree of p(x) and greater than zero, the problem is equivalent to testing the irreducibility of p(x) and then it

Jongmyeong Kim, Minhyun Kim, Ki-Ahm Lee

We present three equivalent definitions of the fractional $p$-Laplacian $(-Δ_{\mathbb{H}^{n}})^{s}_{p}$, $0<s<1$, $p>1$, with normalizing constants, on hyperbolic spaces. The explicit values of the constants enable us to study the convergence of the fractional $p$-Laplacian to the $p$-Laplacian as $s \to 1^{-}$.

Matteo Braglia, Xingang Chen, Dhiraj Kumar Hazra, Lucas Pinol

Future Cosmic Microwave Background (CMB) experiments will deliver extremely accurate measurements of the E-modes pattern of the CMB polarization field. Given the sharpness of the E-modes transfer functions, such surveys make for a powerful detector of high-frequency signals from primordial features that may be lurking in current data sets. With a handful of

Felipe Matus, Jan Střeleček, Pavel Stránský, Pavel Cejnar

Using the adiabatic perturbation theory of driven dynamics [Phys. Rev. A 78, 052508 (2008)] we design a hierarchy of quantum state preparation protocols that systematically increase the fidelity at very long driving times. We test these and other protocols, including those based on the geometric analysis of the parameter space, in a single-qubit system and i

Daniel T. Zhang, Enrico Riccardi, Titus S. van Erp

Path sampling allows the study of rare events like chemical reactions, nucleation and protein folding via a Monte Carlo (MC) exploration in path space. Instead of configuration points, this method samples short molecular dynamics (MD) trajectories with specific start- and end-conditions. As in configuration MC, its efficiency highly depends on the types of M

Rijun Huang, Qingjun Jin, Yi Li

Boundary operators are gauge invariant operators whose form factors correspond to boundary contributions of BCFW shifts. In gauge theory, the boundary operators contain infinite series, which are constrained by gauge symmetry. We compute the boundary operators of all possible BCFW shifts in Yang-Mills theory and QCD, and show that the infinite series can be

Seungeon Lee, Xiting Wang, Sungwon Han, Xiaoyuan Yi

We present SELOR, a framework for integrating self-explaining capabilities into a given deep model to achieve both high prediction performance and human precision. By "human precision", we refer to the degree to which humans agree with the reasons models provide for their predictions. Human precision affects user trust and allows users to collaborate closely

Chong Ye, Yifan Sun, Libin Fu, Xiangdong Zhang

Locally chiral light is an emerging tool for probing and controlling molecular chirality. It can generate large and freely adjustable enantioselectivities in purely electric-dipole effects, offering its major advantages over traditional chiral light. However, the existing types of locally chiral light are phase-mismatched, and thus the global efficiencies ar

Jian Yang, Shaohan Huang, Shuming Ma, Yuwei Yin

Named entity recognition (NER) suffers from the scarcity of annotated training data, especially for low-resource languages without labeled data. Cross-lingual NER has been proposed to alleviate this issue by transferring knowledge from high-resource languages to low-resource languages via aligned cross-lingual representations or machine translation results.

Xingpao Suo, Xi Kang, Chengliang Wei, Guoliang Li

In this paper, we present a spherical Fast Multipole Method (sFMM) for ray tracing simulation of gravitational lensing (GL) on a curved sky. The sFMM is a non-trivial extension of the Fast Multiple Method (FMM) to sphere $\mathbb S^2$, and it can accurately solve the Poisson equation with time complexity of $O(N)\log(N)$, where $N$ is the number of particles

Adrian Hemmi, Ari Paavo Seitsonen, Thomas Greber, Huanyao Cun

The production of high-quality hexagonal boron nitride (h-BN) is essential for the ultimate performance of two-dimensional (2D) materials-based devices, since it is the key 2D encapsulation material. Here, a decisive guideline is reported for fabricating high-quality h-BN on transition metals: It is crucial to exclude carbon from h-BN related process. Otherw

Mathieu Mari, Michał Pawłowski, Runtian Ren, Piotr Sankowski

This paper presents a new research direction for the Min-cost Perfect Matching with Delays (MPMD) - a problem introduced by Emek et al. (STOC'16). In the original version of this problem, we are given an $n$-point metric space, where requests arrive in an online fashion. The goal is to minimise the matching cost for an even number of requests. However, contr

Qianying Liu, Wenyu Guan, Jianhao Shen, Fei Cheng

Previous studies have introduced a weakly-supervised paradigm for solving math word problems requiring only the answer value annotation. While these methods search for correct value equation candidates as pseudo labels, they search among a narrow sub-space of the enormous equation space. To address this problem, we propose a novel search algorithm with combi

Marco Toldo, Umberto Michieli, Pietro Zanuttigh

Deep learning models dealing with image understanding in real-world settings must be able to adapt to a wide variety of tasks across different domains. Domain adaptation and class incremental learning deal with domain and task variability separately, whereas their unified solution is still an open problem. We tackle both facets of the problem together, takin

Xing Li, Manuel Baum, Oliver Brock

We introduce a Learning from Demonstration (LfD) approach for contact-rich manipulation tasks with articulated mechanisms. The extracted policy from a single human demonstration generalizes to different mechanisms of the same type and is robust against environmental variations. The key to achieving such generalization and robustness from a single human demon

Samiha Belmor

We analyze a system of cross-diffusion equations that models the growth of an avascular-tumor spheroid. The model incorporates two nonlinear diffusion effects, degeneracy type and super diffusion. We prove the global existence of weak solutions and justify the convergence towards the free boundary problem of the Hele-Shaw type when the pressure gets stiff. W

Yubao Zhang, Xin Chen, Yuchen Zhang

Due to the increasing popularity of electric vehicles (EVs) and the technological advancement of EV electronics, the vehicle-to-grid (V2G) technique and large-scale scheduling algorithms have been developed to achieve a high level of renewable energy and power grid stability. This paper proposes a deep reinforcement learning (DRL) method for the continuous c

Alphan Sahin

In this study, we propose a digital over-the-air computation (OAC) scheme for achieving continuous-valued (analog) aggregation for federated edge learning (FEEL). We show that the average of a set of real-valued parameters can be calculated approximately by using the average of the corresponding numerals, where the numerals are obtained based on a balanced n

Jianpeng Chen, Yawen Ling, Jie Xu, Yazhou Ren

Multi-view graph clustering (MGC) methods are increasingly being studied due to the explosion of multi-view data with graph structural information. The critical point of MGC is to better utilize view-specific and view-common information in features and graphs of multiple views. However, existing works have an inherent limitation that they are unable to concu

Luca Gennaioli, Nicola Gigli

This note is motivated by recent studies by Eriksson-Bique and Soultanis about the construction of charts in general metric measure spaces. We analyze their construction and provide an alternative and simpler proof of the fact that these charts exist on sets of finite Hausdorff dimension. The observation made here offers also some simplification about the st

Yisu Jia, Robert Lund, Jiajie Kong, Jamie Dyer

This paper develops a mathematical model and statistical methods to quantify trends in presence/absence observations of snow cover (not depths) and applies these in an analysis of Northern Hemispheric observations extracted from satellite flyovers during 1967-2021. A two-state Markov chain model with periodic dynamics is introduced to analyze changes in the

Qingzhai Fan, Jiahui Wang

Let $\Omega$ be a class of unital ${\rm C^*}$-algebras which have the second type tracial nuclear dimensional at moat $n$ (or have tracial nuclear dimensional at most $n$). Let $A$ be an infinite dimensional unital simple ${\rm C^*}$-algebra such that $A$ is asymptotical tracially in $\Omega$. Then ${\rm T^2dim_{nuc}}(A)\leq n$ (or ${\rm Tdim_{nuc}}(A)\leq n

Lois Flower, Marek Schoenherr

In this paper we present an algorithm to add photon-splitting corrections to the Yennie-Frautschi-Suura-style soft-photon resummation available in the Sherpa Monte-Carlo event generator. Photon-splitting corrections enter at NNLO in QED and, as these effects are not incorporated in the standard QED FSR resummations, their size is larger than the pure hard ph

Zhiyu Mou, Yusen Huo, Rongquan Bai, Mingzhou Xie

Recently, auto-bidding technique has become an essential tool to increase the revenue of advertisers. Facing the complex and ever-changing bidding environments in the real-world advertising system (RAS), state-of-the-art auto-bidding policies usually leverage reinforcement learning (RL) algorithms to generate real-time bids on behalf of the advertisers. Due

Marcelo M. Miller Bertolami

In spite of the spectacular progress accomplished by stellar evolution theory some simple questions remain unanswered. One of these questions is ``Why do stars become Red Giants?''. Here we present a relatively simple analytical answer to this question. We validate our analysis by constructing a quantitative toy-model of a red giant and comparing its predict

Sarina Meyer, Pascal Tilli, Pavel Denisov, Florian Lux

In order to protect the privacy of speech data, speaker anonymization aims for hiding the identity of a speaker by changing the voice in speech recordings. This typically comes with a privacy-utility trade-off between protection of individuals and usability of the data for downstream applications. One of the challenges in this context is to create non-existe

Charles Condevaux, Sébastien Harispe

Transformer models achieve state-of-the-art performance on a wide range of NLP tasks. They however suffer from a prohibitive limitation due to the self-attention mechanism, inducing $O(n^2)$ complexity with regard to sequence length. To answer this limitation we introduce the LSG architecture which relies on Local, Sparse and Global attention. We show that L

B. Azah Bei Cho, I. Ndifon Ngek, Alain M. Dikande

The influence of thermo-optic effects on shape profiles of soliton crystals in optical Kerr microresonators is investigated. The study rests on a model that consists of the Lugiato-Lefever equation, coupled to the one-dimensional heat diffusion equation with a source term proportional to the average power of the optical field. Using appropriate variable chan

Xueyong Yuan, Saimon F. Covre da Silva, Diana Csontosova, Huiying Huang

The optical properties of excitons confined in initially-unstrained GaAs/AlGaAs quantum dots are studied as a function of a variable quasi-uniaxial stress. To allow the validation of state-of-the-art computational tools for describing the optical properties of nanostructures, we determine the quantum dot morphology and the in-plane components of externally i

Zeyang Sha, Zheng Li, Ning Yu, Yang Zhang

Text-to-image generation models that generate images based on prompt descriptions have attracted an increasing amount of attention during the past few months. Despite their encouraging performance, these models raise concerns about the misuse of their generated fake images. To tackle this problem, we pioneer a systematic study on the detection and attributio

Isaac Squires, Samuel J. Cooper, Amir Dahari, Steve Kench

Imaging is critical to the characterisation of materials. However, even with careful sample preparation and microscope calibration, imaging techniques are often prone to defects and unwanted artefacts. This is particularly problematic for applications where the micrograph is to be used for simulation or feature analysis, as defects are likely to lead to inac

Ayush Maheshwari, Preethi Jyothi, Ganesh Ramakrishnan

Domain-specific neural machine translation (NMT) systems (e.g., in educational applications) are socially significant with the potential to help make information accessible to a diverse set of users in multilingual societies. It is desirable that such NMT systems be lexically constrained and draw from domain-specific dictionaries. Dictionaries could present

Sebastian Monnet

Given a number field $k$ and a finitely generated subgroup $\mathcal{A} \subseteq k^*$, we study the distribution of $S_4$-quartic extensions of $k$ such that the elements of $\mathcal{A}$ are norms. We show that the density of such extensions is the product of so-called "local masses" at every place of $k$. We give these local masses explicitly in almost al

Christian Käding, Mario Pitschmann

We provide a description of interacting quantum fields in terms of density matrices for any occupation numbers in Fock space in a momentum basis. As a simple example, we focus on a real scalar field interacting with another real scalar field, and present a practicable formalism for directly computing the density matrix elements of the combined scalar-scalar

Richa Upadhyay, Prakash Chandra Chhipa, Ronald Phlypo, Rajkumar Saini

This work proposes Multi-task Meta Learning (MTML), integrating two learning paradigms Multi-Task Learning (MTL) and meta learning, to bring together the best of both worlds. In particular, it focuses simultaneous learning of multiple tasks, an element of MTL and promptly adapting to new tasks, a quality of meta learning. It is important to highlight that we

BESIII Collaboration, M. Ablikim, M. N. Achasov, P. Adlarson

We present a measurement of the dressed cross sections for $e^+ e^- \rightarrow \phi \eta^{\prime}$ at different center-of-mass energies between 3.508 and 4.600 GeV based on 15.1 fb$^{-1}$ of $e^+ e^-$ annihilation data collected with the BESIII detector operating at the BEPCII collider. In addition, a search for the decay $Y(4230) \to \phi \eta^{\prime}$ is

C. Royon

We describe the reaches on quartic $\gamma \gamma \gamma \gamma$, $\gamma \gamma WW$, $\gamma \gamma ZZ$, $\gamma \gamma \gamma Z$, $\gamma \gamma t \bar{t}$ anomalous couplings at the LHC using intact protons in the final state measured in AFP in ATLAS or PPS in CMS-TOTEM.

Ilya Nikitin, Brian O'Connor, Anastasia Safonova

In this paper, we present a seq2seq approach for transliterating missionary Basaa orthographies into the official orthography. Our model uses pre-trained Basaa missionary and official orthography corpora using BERT. Since Basaa is a low-resource language, we have decided to use the mT5 model for our project. Before training our model, we pre-processed our co

Alex Kaltenbach, Michael Růžička

In the present paper, we prove convergence rates for the pressure of the Local Discontinuous Galerkin (LDG) approximation, proposed in Part I of the paper, of systems of $p$-Navier-Stokes type and $p$-Stokes type with $p\in (2,\infty)$. The results are supported by numerical experiments.

Tom van Sonsbeek, Xiantong Zhen, Dwarikanath Mahapatra, Marcel Worring

Medical image datasets and their annotations are not growing as fast as their equivalents in the general domain. This makes translation from the newest, more data-intensive methods that have made a large impact on the vision field increasingly more difficult and less efficient. In this paper, we propose a new probabilistic latent variable model for disease c

Mohamed Farhat, Pai-Yen Chen, Ying Wu

Waveguiding in general and acoustic waveguiding in particular are possible at the condition of having a transverse "discontinuity" or modulation of the refractive index. We propose here a radically different approach that relies on imposing spinning on a column of air, leading to high modified acoustic refractive indices for specific azimuthal modes. Such di

Yuan He, André Pereira, Taras Kucherenko

Embodied Conversational Agents that make use of co-speech gestures can enhance human-machine interactions in many ways. In recent years, data-driven gesture generation approaches for ECAs have attracted considerable research attention, and related methods have continuously improved. Real-time interaction is typically used when researchers evaluate ECA system

HanCong Feng, XinHai Yan, KaiLi Jiang, XinYu Zhao

The automatic classification of radar waveform is a fundamental technique in electronic countermeasures (ECM).Recent supervised deep learning-based methods have achieved great success in a such classification task.However, those methods require enough labeled samples to work properly and in many circumstances, it is not available.To tackle this problem, in t

Roman Engelhardt, Florian Dandl, Klaus Bogenberger

If private vehicle trips can be replaced, ride-pooling services can decrease parking space needed by higher vehicle utilization and increase traffic efficiency by increasing vehicle occupancy. Nevertheless, substantial benefits can only be achieved if a certain market penetration is passed to find enough shareable rides for pooling to take place. Additionall

Abhay Shastry, Abhijith Jayakumar, Apoorva Patel, Chiranjib Bhattacharyya

Quantum kernel methods are a candidate for quantum speed-ups in supervised machine learning. The number of quantum measurements N required for a reasonable kernel estimate is a critical resource, both from complexity considerations and because of the constraints of near-term quantum hardware. We emphasize that for classification tasks, the aim is reliable cl

Alonso Palomino, Martin Potthast, Khalid Al-Khatib, Benno Stein

Most research on natural language processing treats bias as an absolute concept: Based on a (probably complex) algorithmic analysis, a sentence, an article, or a text is classified as biased or not. Given the fact that for humans the question of whether a text is biased can be difficult to answer or is answered contradictory, we ask whether an "absolute bias

Zacharias Viskadourakis, Konstantinos Grammatikakis, Klytaimnistra Katsara, Argyri Drymiskianaki

Energy self sufficiency, as well as optimal management of power in buildings is gaining importance, while obtaining power from traditional fossil energy sources is becoming more and more expensive. In this context, millimeter scale metasurfaces can be employed to harvest energy from microwave sources. They can also be used as sensors in the microwave regime

Hang Yin, Zitao Zhang, Zhurong Wang, Yilmazcan Ozyurt

In e-commerce industry, graph neural network methods are the new trends for transaction risk modeling.The power of graph algorithms lie in the capability to catch transaction linking network information, which is very hard to be captured by other algorithms.However, in most existing approaches, transaction or user connections are defined by hard link strateg

Yan Li, Zhongwei Tang, Heming Wang, Ning Zhou

In this paper we study the problem of prescribing fractional $Q$-curvature of order $2\sigma$ for a conformal metric on the standard sphere $\Sn$ with $\sigma\in (0,n/2)$ and $n\geq2$. Compactness and existence results are obtained in terms of the flatness order $\beta$ of the prescribed curvature function $K$. Making use of integral representations and pert

Alex Degtyarev

We analyze the configurations of conics and lines on a special class of Kummer octic surfaces. In particular, we bound the number of conics by $176$ and show that there is a unique surface with $176$ conics, all irreducible: it admits a faithful action of one of the Mukai groups. Therefore, we also discuss conics and lines on Mukai surfaces: we discover a do

Cristina Vasconcelos, Cengiz Oztireli, Mark Matthews, Milad Hashemi

Neural fields have rapidly been adopted for representing 3D signals, but their application to more classical 2D image-processing has been relatively limited. In this paper, we consider one of the most important operations in image processing: upsampling. In deep learning, learnable upsampling layers have extensively been used for single image super-resolutio

Shaohui Peng, Xing Hu, Rui Zhang, Ke Tang

Hierarchical reinforcement learning (HRL) effectively improves agents' exploration efficiency on tasks with sparse reward, with the guide of high-quality hierarchical structures (e.g., subgoals or options). However, how to automatically discover high-quality hierarchical structures is still a great challenge. Previous HRL methods can hardly discover the hier

Roy Cerqueti, Valerio Ficcadenti, Gurjeet Dhesi, Marcel Ausloos

This paper faces a central theme in applied statistics and information science, which is the assessment of the stochastic structure of rank-size laws in text analysis. We consider the words in a corpus by ranking them on the basis of their frequencies in descending order. The starting point is that the ranked data generated in linguistic contexts can be view

Chris Parker, Jack Saunders

For $p$ a prime, $G$ a finite group and $A$ a normal subset of elements of order $p$, we prove that if $A^2 = \{ab \mid a, b \in A\}$ consists of $p$-elements then $Q = \langle A \rangle$ is soluble. Further, if $O_p(G) = 1$, we show that $p$ is odd, $F(Q)$ is a non-trivial $p'$-group and $Q/F(Q)$ is an elementary abelian $p$-group. We also provide examples

Thomas Lang, Tomas Sauer

Thresholding is the most widely used segmentation method in volumetric image processing, and its pointwise nature makes it attractive for the fast handling of large three-dimensional samples. However, global thresholds often do not properly extract components in the presence of artifacts, measurement noise or grayscale value fluctuations. This paper introduc

Martin Knupfer, Fabian Jerzembeck, Naoki Kikugawa, Friedrich Roth

We report on studies of charge carrier plasmon excitations in Sr2RuO4 by transmission Electron Energy-Loss Spectroscopy. In particular, we present results on the plasmon dispersion and its width as a function of momentum transfer. The dispersion can be qualitatively explained in the framework of RPA calculations, using an unrenormalized tight-binding band st

Zhong Li, Yuxuan Zhu, Matthijs van Leeuwen

In the past two decades, most research on anomaly detection has focused on improving the accuracy of the detection, while largely ignoring the explainability of the corresponding methods and thus leaving the explanation of outcomes to practitioners. As anomaly detection algorithms are increasingly used in safety-critical domains, providing explanations for t

Stephen Church, Nikesh Patel, Ruqaiya Al-Abri, Nawal Al-Amairi

Nanowire lasers are sought for near-field and on-chip photonic applications as they provide integrable, coherent and monochromatic radiation. A wavelength-scale nanowire acts as both the gain medium and the cavity for the lasing action: the functional performance (threshold and wavelength) is therefore dependent on both the opto-electronic and crystallograph

Georg Bergner, Marios Costa, Haralambos Panagopoulos, Ivan Soler

In this work we present perturbative results for the renormalization of the supercurrent operator, $S_\mu$, in ${\cal N} =1$ Supersymmetric Yang-Mills theory. At the quantum level, this operator mixes with both gauge invariant and noninvariant operators, which have the same global transformation properties. In total, there are 13 linearly independent mixing

Nick Malleson, Mark Birkin, Daniel Birks, Jiaqi Ge

Agent-based modelling (ABM) is a facet of wider Multi-Agent Systems (MAS) research that explores the collective behaviour of individual `agents', and the implications that their behaviour and interactions have for wider systemic behaviour. The method has been shown to hold considerable value in exploring and understanding human societies, but is still largel

Binjie Zhang, Shupeng Su, Yixiao Ge, Xuyuan Xu

The traditional model upgrading paradigm for retrieval requires recomputing all gallery embeddings before deploying the new model (dubbed as "backfilling"), which is quite expensive and time-consuming considering billions of instances in industrial applications. BCT presents the first step towards backward-compatible model upgrades to get rid of backfilling.

Dimitris M. Manias, Aliou Sow, Efstathios-Al. Tingas, Francisco E. Hernandez Perez

When designing high-efficiency spark-ignition (SI) engines to operate at high compression ratios, one of the main issues that have to be addressed is detonation development from a pre-ignition front. In order to control this phenomenon, it is necessary to understand the mechanism by which the detonation is initiated. The development of a detonation from a pr

Florian Gut, Thilo Krill, Florian Reich

Call a digraph $H$ \emph{ubiquitous} if every digraph $D$ that contains $k$ vertex-disjoint copies of $H$ for every $k \in \mathbb{N}$ also contains infinitely many vertex-disjoint copies of $H$. We characterise which digraphs whose underlying undirected graph is a ray are ubiquitous.

Robin Forsling, Fredrik Gustafsson, Zoran Sjanic, Gustaf Hendeby

Decentralized state estimation in a communication-constrained sensor network is considered. The exchanged estimates are dimension-reduced to reduce the communication load using a linear mapping to a lower-dimensional space. The mean squared error optimal linear mapping depends on the particular estimation method used. Several dimension-reducing algorithms ar

Sanghyeok Lee, Minkyu Jeon, Injae Kim, Yunyang Xiong

Data augmentation is key to improving the generalization ability of deep learning models. Mixup is a simple and widely-used data augmentation technique that has proven effective in alleviating the problems of overfitting and data scarcity. Also, recent studies of saliency-aware Mixup in the image domain show that preserving discriminative parts is beneficial

LHCb collaboration

We report on a measurement of the $\Lambda_c^+$ to $D^0$ production ratio in PbPb collisions at $\sqrt{s_{\rm NN}}$= 5.02 TeV with the LHCb detector in the forward rapidity region $2 <y< 4.5$. The $\Lambda_c^+$ ($D^0$) hadrons are reconstructed via the decay channel $\Lambda_c^+\rightarrow pK^+\pi^-$ ($D^0 \rightarrow K^-\pi^+$) for $2<p_{\rm T}<8$ GeV$/c$ a