November 2022 arXiv papers — page 6

Victor Brittes

We define a notion of groupoidal 2-quasi-categories and show that they are the fibrant objects of a model structure on the category of $\Theta_2$-sets. We show that this model category is Quillen equivalent to the Kan-Quillen model category of simplicial sets and that 2-truncated groupoidal 2-quasi-categories are models for homotopy 2-types.

Enes Yigitbas, Stefan Sauer, Gregor Engels

In the era of digital transformation, new technological foundations and possibilities for collaboration, production as well as organization open up many opportunities to work differently in the future. The digitization of workflows results in new forms of working which is denoted by the term Work 4.0. In the context of Work 4.0, digital assistance systems pl

Olga Rozanova, Marko Turzinsky

We study the affine solutions of the equations of plane oscillations of cold plasma, which, under the assumption of electrostaticity, correspond to the Euler-Poisson equations in the repulsive case. It is proved that the zero equilibrium state of the cold plasma equations, both with and without the assumption of electrostaticity, is unstable in the class of

Yassir Awwad, Tomislav Prokopec

The large scale geometry of the late Universe can be decomposed as R$\times {\Sigma}_3$, where R stands for cosmic time and ${\Sigma}_3$ is the three dimensional spatial manifold. We conjecture that the spatial geometry of the Universe's spatial section ${\Sigma}_3$ conforms with the Thurston-Perelman theorem, according to which the geometry of $\Sigma_3$ is

Lilian Matthiesen, Mengdi Wang

The aim of this paper is to study distributional properties of integers without large or small prime factors. Define an integer to be $[y',y]$-smooth if all of its prime factors belong to the interval $[y',y]$. We identify suitable weights $g_{[y',y]}(n)$ for the characteristic function of $[y',y]$-smooth numbers that allow us to establish strong asymptotic

Lennart M. Reimann, Sarp Erdönmez, Dominik Sisejkovic, Rainer Leupers

Security still remains an afterthought in modern Electronic Design Automation (EDA) tools, which solely focus on enhancing performance and reducing the chip size. Typically, the security analysis is conducted by hand, leading to vulnerabilities in the design remaining unnoticed. Security-aware EDA tools assist the designer in the identification and removal o

Naohiro Osamura

We report the calculation of the isovector CP-odd $\pi N$ interaction generated by the Weinberg operator, the CP violating three-gluon operator. This enables to restrict models which induce the operator by using experimental data of atomic electric dipole moment. The QCD sum rules are used to determine the matrix element required to assess the CP-odd $\pi N$

Ciro Antonio Mami, Andrea Coser, Eric Medvet, Alexander T. P. Boudewijn

Synthetic data generation has recently gained widespread attention as a more reliable alternative to traditional data anonymization. The involved methods are originally developed for image synthesis. Hence, their application to the typically tabular and relational datasets from healthcare, finance and other industries is non-trivial. While substantial resear

J. J. L. van Rijn, D. Wang, B. Sanyal, T. Banerjee

Multiferroics have found renewed interest in topological magnetism and for logic-in-memory applications. Among them, SrMnO$_{3}$, possessing strong magnetoelectric coupling is gaining attention for the design of coexisting magnetic and polar orders upon straining. Here we demonstrate antiferromagnetic exchange interactions in strained SMO thin films extracte

Jiahuan Yan, Jintai Chen, Yixuan Wu, Danny Z. Chen

Recent development of deep neural networks (DNNs) for tabular learning has largely benefited from the capability of DNNs for automatic feature interaction. However, the heterogeneity nature of tabular features makes such features relatively independent, and developing effective methods to promote tabular feature interaction still remains an open problem. In

Jarosław Błasiok, Parikshit Gopalan, Lunjia Hu, Preetum Nakkiran

We study the fundamental question of how to define and measure the distance from calibration for probabilistic predictors. While the notion of perfect calibration is well-understood, there is no consensus on how to quantify the distance from perfect calibration. Numerous calibration measures have been proposed in the literature, but it is unclear how they co

Claus Michael Ringel

Let $A$ be a finite-dimensional local algebra over an algebraically closed field, let $J$ be the radical of $A.$ The modules we are interested in are the finitely generated left $A$-modules. Projective modules are always reflexive, and an algebra is self-injective iff all modules are reflexive. We discuss the existence of non-projective reflexive module in c

Arda Fazla, Mustafa Enes Aydin, Orhun Tamyigit, Suleyman Serdar Kozat

We investigate ensemble methods for prediction in an online setting. Unlike all the literature in ensembling, for the first time, we introduce a new approach using a meta learner that effectively combines the base model predictions via using a superset of the features that is the union of the base models' feature vectors instead of the predictions themselves

Yaqian Han, Yekun Chai, Shuohuan Wang, Yu Sun

Detecting sarcasm and verbal irony from people's subjective statements is crucial to understanding their intended meanings and real sentiments and positions in social scenarios. This paper describes the X-PuDu system that participated in SemEval-2022 Task 6, iSarcasmEval - Intended Sarcasm Detection in English and Arabic, which aims at detecting intended sar

Pranjali Pathre, Anurag Sahu, Ashwin Rao, Avinash Prabhu

In this paper, we propose and showcase, for the first time, monocular multi-view layout estimation for warehouse racks and shelves. Unlike typical layout estimation methods, MVRackLay estimates multi-layered layouts, wherein each layer corresponds to the layout of a shelf within a rack. Given a sequence of images of a warehouse scene, a dual-headed Convoluti

Guanxiong Luo, Mengmeng Kuang, Peng Cao

The data consistency for the physical forward model is crucial in inverse problems, especially in MR imaging reconstruction. The standard way is to unroll an iterative algorithm into a neural network with a forward model embedded. The forward model always changes in clinical practice, so the learning component's entanglement with the forward model makes the

Carlos Alberto Barrera-Diaz, Amir Nourmohammdi, Henrik Smedberg, Tehseen Aslam

In today's uncertain and competitive market, where enterprises are subjected to increasingly shortened product life-cycles and frequent volume changes, reconfigurable manufacturing systems (RMS) applications play a significant role in the manufacturing industry's success. Despite the advantages offered by RMS, achieving a high-efficiency degree constitutes a

L Ferro, M. Moita, P. Rosati, R. Lolli

Hard X-/soft Gamma-ray astronomy is a key field for the study of important astrophysical phenomena such as the electromagnetic counterparts of gravitational waves, gamma-ray bursts, black holes physics and many more. However, the spatial localization, imaging capabilities and sensitivity of the measurements are strongly limited for the energy range $>$70 keV

Megan E. Farquhar, Qianqian Yang, Viktor Vegh

Diffusional kurtosis imaging (DKI) is a methodology for measuring the extent of non-Gaussian diffusion in biological tissue, which has shown great promise in clinical diagnosis, treatment planning and monitoring of many neurological diseases and disorders. However, robust, fast and accurate estimation of kurtosis from clinically feasible data acquisitions re

Fabian Karl, Ansgar Scherp

Short text classification is a crucial and challenging aspect of Natural Language Processing. For this reason, there are numerous highly specialized short text classifiers. However, in recent short text research, State of the Art (SOTA) methods for traditional text classification, particularly the pure use of Transformers, have been unexploited. In this work

Kazumasa Ohno, Jonathan J. Fortney

Atmospheric nitrogen may provide important constraints on giant planet formation. Following our semi-analytical work (Ohno & Fortney 2022), we further pursue the relation between observable NH3 and an atmosphere's bulk nitrogen abundance by applying the photochemical kinetics model VULCAN across planetary equilibrium temperature, mass, age, eddy diffusion co

Kazumasa Ohno, Jonathan J. Fortney

A major motivation of spectroscopic observations of giant exoplanets is to unveil planet formation processes from atmospheric compositions. Several recent studies suggested that atmospheric nitrogen, like carbon and oxygen, can provide important constrains on planetary formation environments. Since nitrogen chemistry can be far from thermochemical equilibriu

D. Nivedha, S. Devi Yamini

An antimagic labeling of a graph $G$ is a $1-1$ correspondence between the edge set $E(G)$ and $\lbrace 1,2,...,|E(G)|\rbrace$ in which the sum of the labels of edges incident to the distinct vertices are different. The edge corona of any two graphs $G$ and $H$, (denoted by $G$ $\diamond$ $H$) is obtained by joining one copy of $G$ with $|E(G)|$ copies of H

Ye-Won Luke Cho

We present a survey on recent developments of generalizations of Forelli's analyticity theorem and related pluripotential methods.

N. Glazunov

In this paper we prove that the optimal lattice packing of the Minkowski, Davis, and Chebyshev-Cohn balls is realized with respect to the sublattices of index two of the critical lattices of corresponding balls

Eusebio Gardella, Shirly Geffen, Julian Kranz, Petr Naryshkin

We introduce the notion of tracial amenability for actions of discrete groups on unital, tracial C$^*$-algebras, as a weakening of amenability where all the relevant approximations are done in the uniform trace norm. We characterize tracial amenability with various equivalent conditions, including topological amenability of the induced action on the trace sp

Pietro Bongini, Elisa Messori, Niccolò Pancino, Monica Bianchini

Predicting drug side-effects before they occur is a key task in keeping the number of drug-related hospitalizations low and to improve drug discovery processes. Automatic predictors of side-effects generally are not able to process the structure of the drug, resulting in a loss of information. Graph neural networks have seen great success in recent years, th

Fernando Falceto

We carry out the canonical quantization of the electromagnetic field in arbitrary $\xi$-gauge and compute its propagator. In this way we fill a gap in the literature and clarify some existing confusion about Feynman $i\epsilon$ prescription for the propagator of the electromagnetic field. We also discuss the BRST quantization and investigate the apparent sin

Shujuan Li, Junsheng Zhou, Baorui Ma, Yu-Shen Liu

Normal estimation for unstructured point clouds is an important task in 3D computer vision. Current methods achieve encouraging results by mapping local patches to normal vectors or learning local surface fitting using neural networks. However, these methods are not generalized well to unseen scenarios and are sensitive to parameter settings. To resolve thes

Franziska-Luise Paschke-Bruehl, Mohammad Banjafar, Marco Garten, Lingen Huang

We present a computational study of isochoric heating in multi-layered targets at ultra-high intensity laser irradiation (approx. 10**20 W/cm**2). Previous studies have shown enhanced ion heating at interfaces, but at the cost of large temperature gradients. Here, we study multi-layered targets to spread this enhanced interface heating to the entirety of the

Mohsen Rezaee-Hajidehi, Karel Tůma, Stanisław Stupkiewicz

Direct experimental characterization of indentation-induced martensitic microstructures in pseudoelastic shape memory alloys (SMAs) is not possible, and thus there is a lack of evidence and understanding regarding the microstructure pattern and related features. To fill this gap, in this work we employ the phase-field method to provide a detailed and systema

Byoung Jin Choi, Myeonghun Jeong, Joun Yeop Lee, Nam Soo Kim

Zero-shot multi-speaker text-to-speech (ZSM-TTS) models aim to generate a speech sample with the voice characteristic of an unseen speaker. The main challenge of ZSM-TTS is to increase the overall speaker similarity for unseen speakers. One of the most successful speaker conditioning methods for flow-based multi-speaker text-to-speech (TTS) models is to util

Guanglin Niu, Bo Li

A temporal knowledge graph (TKG) stores the events derived from the data involving time. Predicting events is extremely challenging due to the time-sensitive property of events. Besides, the previous TKG completion (TKGC) approaches cannot represent both the timeliness and the causality properties of events, simultaneously. To address these challenges, we pr

Aleksandr N. Grekov, Nikolay A. Grekov, Sergei S. Peliushenko

Acoustic flow velocity and direction meters from the IST series, which can be integrated into various measuring systems, are considered. The simulation of the flow profile in the measuring tube was carried out depending on the free flow velocity. A measurement method has been developed that uses the transit time of repeated acoustic signals reflected from th

Chenze Shao, Jinchao Zhang, Jie Zhou, Yang Feng

Non-autoregressive neural machine translation (NAT) models suffer from the multi-modality problem that there may exist multiple possible translations of a source sentence, so the reference sentence may be inappropriate for the training when the NAT output is closer to other translations. In response to this problem, we introduce a rephraser to provide a bett

Mikhael Sayat, Biveen Shajilal, Sebastian P. Kish, Syed M. Assad

The Gaussian modulated continuous variable quantum key distribution (GM-CVQKD) protocol is known to maximise the mutual information between two parties during quantum key distribution (QKD). An alternative modulation scheme is the discrete modulated CVQKD (DM-CVQKD) protocol. In this paper, we study the Phase Shift Keying (M-PSK) and Quadrature Amplitude Mod

Dan Beilis, Sara Beck, John Lacy

NGC 7538 IRS2 is a compact HII region and recent star formation source, with a shell morphology, lying on the border of the visible HII region NGC 7538. We present a spectral cube of the [NeII] 12.8 micron emission line obtained with the TEXES spectrometer on Gemini North with velocity resolution approximately 4 km/s and angular resolution 0.3". The kinemati

Roman Gaponenko, Mikhail S. Sidorenko, Dmitry Zhirihin, Ilia L. Rasskazov

An experimental demonstration of directivities exceeding the fundamental Kildal limit, a phenomenon called superdirectivity, is provided for spherical high-index dielectric antennas with an electric dipole excitation. A directivity factor of about 10 with a total efficiency of more than 80\% for an antenna having a size of a third of the wavelength was measu

Philip Bille, Inge Li Gørtz, Moshe Lewenstein, Solon P. Pissis

In Gapped String Indexing, the goal is to compactly represent a string $S$ of length $n$ such that for any query consisting of two strings $P_1$ and $P_2$, called patterns, and an integer interval $[\alpha, \beta]$, called gap range, we can quickly find occurrences of $P_1$ and $P_2$ in $S$ with distance in $[\alpha, \beta]$. Gapped String Indexing is a cent

Andrea Cristofaro, Francesco Ferrante

The problem of unknown input observer design is considered for coupled PDE/ODE systems subject to incremental sector bounded nonlinearities and unknown boundary inputs. Assuming available measurements at the boundary of the distributed domain, the synthesis of the unknown input observer is based on Lyapunov methods and convex optimization. Numerical simulati

Katharina Kann, Shiran Dudy, Arya D. McCarthy

The field of natural language processing (NLP) has grown over the last few years: conferences have become larger, we have published an incredible amount of papers, and state-of-the-art research has been implemented in a large variety of customer-facing products. However, this paper argues that we have been less successful than we should have been and reflect

Federico De Lillo, Jishnu Suresh, Antoine Depasse, Magdalena Sieniawska

A stochastic gravitational-wave background (SGWB) is expected to be produced by the superposition of individually undetectable, unresolved gravitational-wave (GW) signals from cosmological and astrophysical sources. Such a signal can be searched with dedicated techniques using the data acquired by a network of ground-based GW detectors. In this work, we cons

Irene Aldridge, Payton Martin

Our main contribution is that we are using AI to discern the key drivers of variation of ESG mentions in the corporate filings. With AI, we are able to separate "dimensions" along which the corporate management presents their ESG policies to the world. These dimensions are 1) diversity, 2) hazardous materials, and 3) greenhouse gasses. We are also able to id

Sergii Favorov

Based on the properties of distributions and measures with discrete support, we investigate temperate almost periodic distributions on the Euclidean space and connection with their Fourier transforms. We also study relations between the Fourier transform of almost periodic distributions and their Fourier coefficients. The main result of the article is the co

Muhan Wang, Zhe Zhang, Xiaolan Qiu, Silin Gao

Tomographic SAR technique has attracted remarkable interest for its ability of three-dimensional resolving along the elevation direction via a stack of SAR images collected from different cross-track angles. The emerged compressed sensing (CS)-based algorithms have been introduced into TomoSAR considering its super-resolution ability with limited samples. Ho

Marc Hellmuth, Guillaume E. Scholz

The modular decomposition of a graph $G$ is a natural construction to capture key features of $G$ in terms of a labeled tree $(T,t)$ whose vertices are labeled as "series" ($1$), "parallel" ($0$) or "prime". However, full information of $G$ is provided by its modular decomposition tree $(T,t)$ only, if $G$ is a cograph, i.e., $G$ does not contain prime modul

John Glover, Federico Fancellu, Vasudevan Jagannathan, Matthew R. Gormley

Scoring the factuality of a generated summary involves measuring the degree to which a target text contains factual information using the input document as support. Given the similarities in the problem formulation, previous work has shown that Natural Language Inference models can be effectively repurposed to perform this task. As these models are trained t

Juraj Országh, Anita Ribar, Marián Danko, Dennis Bodewits

The excitation of nitromethane CH$_3$NO$_2$, which is an important propellant and prototypic molecule for large class of explosives, has been investigated by electron impact and subsequent emission of photons in the UV-VIS spectral region between 300 nm and 670 nm. Emission spectrum of nitromethane was recorded at an electron energy of 50 eV. New dissociativ

Claudio Fernandez-Martín, Umay Kiraz, Julio Silva-Rodríguez, Sandra Morales

Mitotic activity is a crucial proliferation biomarker for the diagnosis and prognosis of different types of cancers. Nevertheless, mitosis counting is a cumbersome process for pathologists, prone to low reproducibility, due to the large size of augmented biopsy slides, the low density of mitotic cells, and pattern heterogeneity. To improve reproducibility, d

Michele Girfoglio, Annalisa Quaini, Gianluigi Rozza

We propose a regularization for Reduced Order Models (ROMs) of the quasi-geostrophic equations (QGE) to increase accuracy when the Proper Orthogonal Decomposition (POD) modes retained to construct the reduced basis are insufficient to describe the system dynamics. Our regularization is based on the so-called BV-alpha model, which modifies the nonlinear term

Tomaž Javornik, Andrej Hrovat, Aleš Švigelj

In this paper, we critically review the potential of today's terrestrial wireless communication systems including wireless cellular technologies (GSM, UMTS, LTE, NR), wireless local area networks (WLANs), and wireless sensor networks (WSNs), for estimating channel state information (CSI), the ratio between training and information symbols and the rate of cha

Juraj Országh, Marián Danko, Peter Čechvala, Štefan Matejčík

The optical emission spectrum of acetylene excited by monoenergetic electrons was studied in the range of 190 nm to 660 nm. The dissociative excitation and dissociative ionization associated with excitation of the ions initiated by electron impact were dominant processes contributing to the spectrum. The spectrum was dominated by the atomic lines H, C and mo

Antoine Henrot, Marco Michetti

In this paper, we obtain optimal upper bounds for all the Neumann eigenvalues in two situations (that are closely related). First we consider a one-dimensional Sturm-Liouville eigenvalue problem where the density is a function $h(x)$ whose some power is concave. We prove existence of a maximizer for $\mu_k(h)$ and we completely characterize it. Then we consi

Raviar S. Karim, Roger J. A. Laeven, Michel R. H. Mandjes

In this paper, we establish a large deviations principle for a multivariate compound process induced by a multivariate Hawkes process with random marks. Our proof hinges on showing essential smoothness of the limiting cumulant of the multivariate compound process, resolving the inherent complication that this cumulant is implicitly characterized through a fi

Yuqian Zhao, Bing Sun, Zhan-Feng Mai, Zhoujian Cao

Quasi-normal modes (QNMs) of a black hole (BH) are the eigen modes describing the dissipative oscillation of various fields in that spacetime, which can be intrinsically produced by the linear perturbation theory. With the discovery of the first gravitational waves (GWs) event, GW150914, a new window into the universe has been opened, allowing for the detect

De Cheng, Haichun Tai, Nannan Wang, Zhen Wang

Unsupervised person re-identification (ReID) aims at learning discriminative identity features for person retrieval without any annotations. Recent advances accomplish this task by leveraging clustering-based pseudo labels, but these pseudo labels are inevitably noisy which deteriorate model performance. In this paper, we propose a Neighbour Consistency guid

Sina Tabakhi, Parham Moradi

The Universal Feature Selection Tool (UniFeat) is an open-source tool developed entirely in Java for performing feature selection processes in various research areas. It provides a set of well-known and advanced feature selection methods within its significant auxiliary tools. This allows users to compare the performance of feature selection methods. Moreove

Verena Brehm, Johannes W. Austefjord, Serban Lepadatu, Alireza Qaiumzadeh

Brain-inspired neuromorphic computing is a promising path towards next generation analogue computers that are fundamentally different compared to the conventional von Neumann architecture. One model for neuromorphic computing that can mimic the human brain behavior are spiking neural networks (SNNs), of which one of the most successful is the leaky integrate

Yanjun Ji

The aim of this work is to model the measurement of flux qubits using Quantum-Flux-Parametron (QFP) and to theoretically investigate and numerically simulate the fidelity of the measurement in different bases.

Tej-Eddine Ghoul, Nader Masmoudi, Eliot Pacherie

In this follow up paper, we focus on the viscous Burgers equation. There, using the Hopf-Cole transformation, we compute the long time behavior of solutions for some classes of infinite mass initial datas. We show that an enhanced dissipation effect occurs generically, that is the decay rate in time is better than if we considered instead the heat equations

Yukang Shen, Wenchuan Wu, Shumin Sun, Bin Wang

To stabilize the frequency of the renewable energy sources (RESs) dominated power system, frequency supports are required by RESs through virtual inertia emulation or droop control in the newly published grid codes. Since the long-term RES prediction involves significant errors, we need online configure the frequency control parameters of RESs in a rolling m

Francesco Battistoni, Giuseppe Molteni

Current methods for the classification of number fields with small regulator depend mainly on an upper bound for the discriminant, which can be improved by looking for the best possible upper bound of a specific polynomial function over an hypercube. In this paper, we provide new and effective upper bounds for the case of fields with one complex embedding an

Sicong Zang, Shikui Tu, Lei Xu

Graphic sketch representations are effective for representing sketches. Existing methods take the patches cropped from sketches as the graph nodes, and construct the edges based on sketch's drawing order or Euclidean distances on the canvas. However, the drawing order of a sketch may not be unique, while the patches from semantically related parts of a sketc

Yining Wang, Xumeng Gong, Shaochuan Li, Bing Yang

In the field of antibody engineering, an essential task is to design a novel antibody whose paratopes bind to a specific antigen with correct epitopes. Understanding antibody structure and its paratope can facilitate a mechanistic understanding of its function. Therefore, antibody structure prediction from its sequence alone has always been a highly valuable

N. Losacco

The holographic approach is applied to study the chaotic behaviour of a strongly coupled $Q \bar Q$ pair in general thermal background. We consider two different backgrounds, one with finite temperature and baryon density, and one with finite temperature and constant magnetic field along a fixed direction. The results allow us to understand the dependence of

Tej-Eddine Ghoul, Nader Masmoudi, Eliot Pacherie

We construct a class of infinite mass functions for which solutions of the viscous Burgers equation decay at a better rate than solution of the heat equation for initial data in this class. In other words, we show an enhanced dissipation coming from a nonlinear transport term. We compute the asymptotic profile in this class for both equations. For the viscou

Alain Andres, Esther Villar-Rodriguez, Javier Del Ser

Reinforcement Learning has emerged as a strong alternative to solve optimization tasks efficiently. The use of these algorithms highly depends on the feedback signals provided by the environment in charge of informing about how good (or bad) the decisions made by the learned agent are. Unfortunately, in a broad range of problems the design of a good reward f

Fabian Meyer, Katharina Glock

In many unmanned aerial vehicle (UAV) applications for surveillance and data collection, it is not possible to reach all requested locations due to the given maximum flight time. Hence, the requested locations must be prioritized and the problem of selecting the most important locations is modeled as an Orienteering Problem (OP). To fully exploit the kinemat

Rafael L. Greenblatt, Markus Lange, Giovanna Marcelli, Marcello Porta

We consider finite-range, many-body fermionic lattice models and we study the evolution of their thermal equilibrium state after introducing a weak and slowly varying time-dependent perturbation. Under suitable assumptions on the external driving, we derive a representation for the average of the evolution of local observables via a convergent expansion in t

Di Huang, Xiaopeng Ji, Xingyi He, Jiaming Sun

This paper presents an approach that reconstructs a hand-held object from a monocular video. In contrast to many recent methods that directly predict object geometry by a trained network, the proposed approach does not require any learned prior about the object and is able to recover more accurate and detailed object geometry. The key idea is that the hand m

Vajira Thambawita, Andrea M. Storås, Steven A. Hicks, Pål Halvorsen

Head and neck cancers are the fifth most common cancer worldwide, and recently, analysis of Positron Emission Tomography (PET) and Computed Tomography (CT) images has been proposed to identify patients with a prognosis. Even though the results look promising, more research is needed to further validate and improve the results. This paper presents the work do

Dafa Li, Yao Liu, Hongchi Wang, Yao Wang

How do dust grains in protoplanetary disks overcome rapid radial drift and grow from micron size particles to planets is not well understood. The key is to search for evidence of dust accumulation and growth as a function of radius in the disk. We investigate the radial profile of grain size in the DS Tau disk by fitting multi-band ALMA observations with sel

Kaixuan Zhou, June Wu, Junheng Shi, Tim Byrnes

In a multi-level energy system with energy transitions, dark states are eigenstates of a Hamiltonian that consist entirely of ground states, with zero amplitude in the excited states. We present several criteria which allows one to deduce the presence of dark states in a general multi-level system based on the submatrices of the Hamiltonian. The dark states

Xiaojun Chang, Ru Wang, Duokui Yan

In this paper, we study the following logarithmic Schr\"{o}dinger equation \[ -\Delta u+a(x)u=u\log u^2\ \ \ \ \mbox{in }V, \] where $\Delta$ is the graph Laplacian, $G=(V,E)$ is a connected locally finite graph, the potential $a: V\to \mathbb{R}$ is bounded from below and may change sign. We first establish two Sobolev compact embedding theorems in the case

Ryan Kellermann, Alessandro Barone, Shoji Hashimoto, Andreas Jüttner

We perform a non-perturbative lattice calculation of the decay rates for inclusive semi-leptonic decays of charmed mesons. In view of the long-standing tension in the determination of the CKM matrix elements $|V_{ub}|$ and $|V_{cb}|$ from exclusive and inclusive processes, recently, the use of lattice QCD has been extended towards the description of inclusiv

Xiaobin Tang, Tong Shen, Manru Dong

The purpose of this study is to propose a new index to measure and reflect China's investment activity in time, and to analyze the changes of China's investment activity in the past five years. This study first uses the NEZHA model for semantic representation, and expand the indicator system based on semantic similarity. Then we calculate China's investment

Sergey V. Gusev

We show that the monoid of all injective and extensive partial transformations of a chain with three elements admits no finite basis of its identities. This completes solving of the finite basis problem for the monoids in the basic frame of partial transformation monoids posed by Volkov.

Gernot Beer, Christian Duenser

The immersed isogeometric Boundary Element Method is presented and applied to the simulation of underground excavations. Nonuniform rational B-splines (NURBS) are used for the accurate definition of complex geometries with few parameters. Immersed technology is applied to automatically generate cell meshes. This allows heterogeneous and anisotropic ground co

Jiaqiang Wen

In this paper, we focus on the solvability of a class of fractional backward stochastic differential equations (BSDEs, for short) with delayed generator. In this class of equations, the generator includes not only the values of the solutions of the present but also the past. Under Lipschitz condition, the existence and uniqueness of such BSDEs are establishe

Jin Qiao, Zhao Li, Tao Zhu, Ran Ji

The examination of parity symmetry in gravitational interactions has drawn increasing attention. Although Einstein's General Relativity is parity-conserved, numerous theories of parity-violating (PV) gravity in different frameworks have recently been proposed for different motivations. In this review, we briefly summarize the recent progress of these theorie

Jiří Pihrt, Rudolf Raevskiy, Petr Šimánek, Matej Choma

The short-term prediction of precipitation is critical in many areas of life. Recently, a large body of work was devoted to forecasting radar reflectivity images. The radar images are available only in areas with ground weather radars. Thus, we aim to predict high-resolution precipitation from lower-resolution satellite radiance images. A neural network call

Shantanu Jaiswal, Liu Yan, Dongkyu Choi, Kenneth Kwok

Commonsense knowledge-graphs (CKGs) are important resources towards building machines that can 'reason' on text or environmental inputs and make inferences beyond perception. While current CKGs encode world knowledge for a large number of concepts and have been effectively utilized for incorporating commonsense in neural models, they primarily encode declara

Shanshan Cao, Guang-You Qin

High-energy heavy-ion collisions at the Relativistic Heavy-Ion Collider and the Large Hadron Collider have evolved from qualitative understanding into precise extraction of the properties of the Quantum Chromodynamics medium at extremely high temperature. Jet quenching has offered unique insights into the transport properties of the Quark-Gluon Plasma (QGP)

Fabian Meyer, Katharina Glock

This paper presents a new method for integrated time-optimal routing and trajectory optimization of multirotor unmanned aerial vehicles (UAVs). Our approach extends the well-known Traveling Salesman Problem by accounting for the limited maneuverability of the UAVs due to their kinematic properties. To this end, we allow each waypoint to be traversed with a d

Wushi Goldring, Jean-Stefan Koskivirta

We establish vanishing results for spaces of automorphic forms in characteristic $0$ and characteristic $p$. We prove that for Hodge-type Shimura varieties, the weight of any nonzero automorphic form in characteristic $0$ satisfies the Griffiths-Schmid conditions, by purely algebraic, characteristic $p$ methods. We state a conjecture for general Hodge-type S

Andrèe Dafne Bolognino, Francesco Giovanni Celiberto, Michael Fucilla, Dmitry Yu. Ivanov

Working in the hybrid high-energy/collinear factorization, where the next-to-leading resummation of energy logarithms is combined with collinear parton densities and fragmentation functions, we study observables sensitive to high-energy dynamics in the context of heavy-flavor physics.

Wushi Goldring, Jean-Stefan Koskivirta

For several Hodge-type Shimura varieties of good reduction in characteristic $p$, we show that the cone of weights of automorphic forms is encoded by the stack of $G$-zips of Pink-Wedhorn-Ziegler. This establishes several instances of a general conjecture formulated in previous papers by the authors. Furthermore, we prove in these cases that any mod $p$ auto

R. S. F. Iskandar, N. Karjanto, Y. S. Kusumah, I. R. Ihsan

This study aims to investigate geometrical concepts related to ethnomathematics in Indonesia. The research design used in this study is to summarize, review, and analyze 24 papers that discussed ethnomathematics. We selected either journal articles or conference proceedings that were published in the last five years, which cover documents from 2016 to 2020,

Dajeong Jang, Woong-Tae Kim

While bars are common in disk galaxies, their formation conditions are not well understood. We use $N$-body simulations to study bar formation and evolution in isolated galaxies consisting of a stellar disk, a classical bulge, and a dark halo. We consider 24 galaxy models that are similar to the Milky Way but differ in the mass and compactness of the classic

Boris Nasedkin, Fedor Kiselev, Ilya Filipov, Darya Tolochko

Vulnerabilities of components used in quantum key distribution (QKD) systems affect its implementation security and must be taken into consideration during system development and security analysis. In this paper, we investigated transmission of fiber optical elements, which are commonly used in QKD systems for designing countermeasures against Trojan-horse a

Hongyi Zhang, Yufeng Zhang, Binlu Feng

In this paper, we investigate the Cauchy problem of the following complex cubic Camassa-Holm (ccCH) equation $$m_{t}=b u_{x}+\frac{1}{2}\left[m\left(|u|^{2}-\left|u_{x}\right|^{2}\right)\right]_{x}-\frac{1}{2} m\left(u \bar{u}_{x}-u_{x} \bar{u}\right), \quad m=u-u_{x x},$$ where $b>0$ is an arbitrary positive real constant. Long-time asymptotics of the equat

Aarjav Jain, Challenger Mishra, Pietro Liò

Neural networks with PDEs embedded in their loss functions (physics-informed neural networks) are employed as a function approximators to find solutions to the Ricci flow (a curvature based evolution) of Riemannian metrics. A general method is developed and applied to the real torus. The validity of the solution is verified by comparing the time evolution of

Charles Graziani, Mathieu Nespoulous, Renaud Denoyel, Stephan Fauve

The temporal and spatial evolution of dispersed media is a fundamental problem in a wide range of physicochemical systems, such as emulsions, suspensions and aerosols. These systems are multiphasic and involve compounds of different densities. They are therefore subject to the influence of gravity which determines the sedimentation rate of their dispersed ph

Raphael Hauer, Georg Haberfehlner, Gerald Kothleitner, Mathieu Kociak

We theoretically investigate the tomographic reconstruction of the three-dimensional photonic environment of nanoparticles. As input for our reconstruction we use electron energy loss spectroscopy (EELS) maps for different rotation angles. We perform the tomographic reconstruction of surface polariton fields for smooth and rough nanorods, and compare the rec

Yanxian Wei, Hailong Zhou, Yunhong Ding, Zihao Cheng

The integration density of photonic integrated circuits has been limited by light coupling between waveguides. Traditional approaches to layout the waveguide with high density are based on refractive index engineering to suppress the light coupling between waveguides. However, these methods mostly require sophisticated and sensitive structure design, thus la

Yuchen Ding, Yu-Chen Sun, Li-Yuan Wang, Yutong Xia

Let $\mathcal{S}=\{1^2,2^2,3^2,...\}$ be the set of squares and $\mathcal{W}=\{w_n\}_{n=1}^{\infty} \subset \mathbb{N}$ be an additive complement of $\mathcal{S}$ so that $\mathcal{S} + \mathcal{W} \supset \{n \in \mathbb{N}: n \geq N_0\}$ for some $N_0$. Let $\mathcal{R}_{\mathcal{S},\mathcal{W}}(n) = \#\{(s,w):n=s+w, s\in \mathcal{S}, w\in \mathcal{W}\} $.

Daniel R. Hawtin, Cheryl E. Praeger, Jin-Xin Zhou

We introduce the notion of an \emph{$n$-dimensional mixed dihedral group}, a general class of groups for which we give a graph theoretic characterisation. In particular, if $H$ is an $n$-dimensional mixed dihedral group then the we construct an edge-transitive Cayley graph $\Gamma$ of $H$ such that the clique graph $\Sigma$ of $\Gamma$ is a $2$-arc-transitiv

Tooba Khan, Kumar Madhukar, Subodh Vishnu Sharma

The generation of adversarial inputs has become a crucial issue in establishing the robustness and trustworthiness of deep neural nets, especially when they are used in safety-critical application domains such as autonomous vehicles and precision medicine. However, the problem poses multiple practical challenges, including scalability issues owing to large-s

Ossama Obeid, Go Inoue, Nizar Habash

We present Camelira, a web-based Arabic multi-dialect morphological disambiguation tool that covers four major variants of Arabic: Modern Standard Arabic, Egyptian, Gulf, and Levantine. Camelira offers a user-friendly web interface that allows researchers and language learners to explore various linguistic information, such as part-of-speech, morphological f

Kun Xiang, Xing Zhang, Jinwen She, Jinpeng Liu

As the COVID-19 pandemic puts pressure on healthcare systems worldwide, the computed tomography image based AI diagnostic system has become a sustainable solution for early diagnosis. However, the model-wise vulnerability under adversarial perturbation hinders its deployment in practical situation. The existing adversarial training strategies are difficult t