October 2022 arXiv papers — page 87

Zetian Zheng, Chen Shen

In recent years, the sub-synchronous oscillation (SSO) accidents caused by wind power have received extensive attention. A method is needed to distinguish if nonlinear behavior exists in the recorded equal-amplitude accident waveforms, so that different methods can be adopted to analyze the mechanism of the oscillation. The theory of higher-order statistics

Tiago P. Peixoto, Alec Kirkley

The task of community detection, which aims to partition a network into clusters of nodes to summarize its large-scale structure, has spawned the development of many competing algorithms with varying objectives. Some community detection methods are inferential, explicitly deriving the clustering objective through a probabilistic generative model, while other

Mikaela M. Larkin, Roman Gerasimov, Adam J. Burgasser

Population III stars were the first stars to form after the Big Bang, and are believed to have made the earliest contribution to the metal content of the universe beyond the products of the Big Bang Nucleosynthesis. These stars are theorized to have had extremely short lifespans, and therefore would only be observable at high redshifts ($z \geq 3-17$) and fa

Olivier Laurent, Adrien Lafage, Enzo Tartaglione, Geoffrey Daniel

Deep Ensembles (DE) are a prominent approach for achieving excellent performance on key metrics such as accuracy, calibration, uncertainty estimation, and out-of-distribution detection. However, hardware limitations of real-world systems constrain to smaller ensembles and lower-capacity networks, significantly deteriorating their performance and properties.

Young-Ju Lee, Jongho Park

We consider additive Schwarz methods for boundary value problems involving the $p$-Laplacian. While existing theoretical estimates suggest a sublinear convergence rate for these methods, empirical evidence from numerical experiments demonstrates a linear convergence rate. In this paper, we narrow the gap between these theoretical and empirical results by pre

Mohamed M. Shaaban, Ajay S. Gill, Jacqueline McCleary, Richard J. Massey

The statistical power of weak lensing measurements is principally driven by the number of high redshift galaxies whose shapes are resolved. Conventional wisdom and physical intuition suggest this is optimised by deep imaging at long (red or near IR) wavelengths, to avoid losing redshifted Balmer break and Lyman break galaxies. We use the synthetic Emission L

Gavin Collins, Devin Francom, Kellin Rumsey

In projection pursuit regression (PPR), an unknown response function is approximated by the sum of M "ridge functions," which are flexible functions of one-dimensional projections of a multivariate input space. Traditionally, optimization routines are used to estimate the projection directions and ridge functions via a sequential algorithm, and M is typicall

John Brennan, Jiří Vala

We present a construction of the Kitaev honeycomb lattice model on an arbitrary higher genus surface. We first generalize the exact solution of the model based on the Jordan-Wigner fermionization to a surface with genus $g = 2$, and then use this as a basic module to extend the solution to lattices of arbitrary genus. We demonstrate our method by calculating

Kiymet Akdemir, Ali Hürriyetoğlu

We approach the classification problem as an entailment problem and apply zero-shot ranking to socio-political texts. Documents that are ranked at the top can be considered positively classified documents and this reduces the close reading time for the information extraction process. We use Transformer Language Models to get the entailment probabilities and

Simon Plätzer

Colour evolution and parton branching at the amplitude level have become important theoretical frameworks to improve parton showers, and are algorithms in their own right: they complement shower development by resummation algorithms capable of including interference effects and subleading colour contributions at an unprecedented level. I summarize recent dev

Johannes Puschnig, Stefan Wallner, Axel Schwope, Magnus Näslund

We present long-term (4-10 years) trends of light pollution observed at 26 locations, covering rural, intermediate and urban sites, including the three major European metropolitan areas of Stockholm, Berlin and Vienna. Our analysis is based on i) night sky brightness (NSB) measurements obtained with Sky Quality Meters (SQMs) and ii) a rich set of atmospheric

Manoj K. Mandal, Pierpaolo Mastrolia, Raj Patil, Jan Steinhoff

We present the result of the quadratic-in-spin interaction Hamiltonian for binary systems of rotating compact objects with generic spins, up to NNNLO corrections within the post-Newtonian expansion. The calculation is performed by employing the effective field theory diagrammatic approach, and it involves Feynman integrals up to three loops, evaluated within

Yuxian Gu, Pei Ke, Xiaoyan Zhu, Minlie Huang

Training language models to learn from human instructions for zero-shot cross-task generalization has attracted much attention in NLP communities. Recently, instruction tuning (IT), which fine-tunes a pre-trained language model on a massive collection of tasks described via human-craft instructions, has been shown effective in instruction learning for unseen

R. A. Dumer, M. Godoy

In this work, we have studied the Ising model with one- and two-spin flip competing dynamics on a two-dimensional additive small-world network (A-SWN). The system model consists of a $L\times L$ square lattice where each site of the lattice is occupied by a spin variable that interacts with the nearest neighbor spins and it has a certain probability $p$ of b

Hien Ohnaka, Shinnosuke Takamichi, Keisuke Imoto, Yuki Okamoto

We propose a method for synthesizing environmental sounds from visually represented onomatopoeias and sound sources. An onomatopoeia is a word that imitates a sound structure, i.e., the text representation of sound. From this perspective, onoma-to-wave has been proposed to synthesize environmental sounds from the desired onomatopoeia texts. Onomatopoeias hav

Fengqiu Adam Dong, Kathryn Crowter, Bradley W. Meyers, Ziggy Pleunis

The Canadian Hydrogen Mapping Experiment (CHIME) is a radio telescope located in British Columbia, Canada. The large FOV allows CHIME/FRB to be an exceptional pulsar and Rotating Radio Transient (RRAT) finding machine, despite saving only the metadata of incoming Galactic events. We have developed a pipeline to search for pulsar/RRAT candidates using DBSCAN,

Ali Cem, Siqi Yan, Yunhong Ding, Darko Zibar

Photonic integrated circuits are facilitating the development of optical neural networks, which have the potential to be both faster and more energy efficient than their electronic counterparts since optical signals are especially well-suited for implementing matrix multiplications. However, accurate programming of photonic chips for optical matrix multiplic

Yinghao Zhu, Kaitong Sun, Si Wu, Pengfei Zhou

Multiferroics represent a class of advanced materials for promising applications and stand at the forefront of modern science for the special feature possessing both charge polar and magnetic order. Previous studies indicate that the family of RECrO3 (RE = rare earth) compounds is likely another rare candidate system holding both ferroelectricity and magneti

Luca Biggio, Georgios Vernardos, Aymeric Galan, Austin Peel

Strong gravitational lensing is a unique observational tool for studying the dark and luminous mass distribution both within and between galaxies. Given the presence of substructures, current strong lensing observations demand more complex mass models than smooth analytical profiles, such as power-law ellipsoids. In this work, we introduce a continuous neura

Frida Marie Viset, Rudy Helmons, Manon Kok

When an agent, person, vehicle or robot is moving through an unknown environment without GNSS signals, online mapping of nonlinear terrains can be used to improve position estimates when the agent returns to a previously mapped area. Mapping algorithms using online Gaussian process (GP) regression are commonly integrated in algorithms for simultaneous locali

Xiaomeng Ma, Lingyu Gao

There is an ongoing debate on whether neural networks can grasp the quasi-regularities in languages like humans. In a typical quasi-regularity task, English past tense inflections, the neural network model has long been criticized that it learns only to generalize the most frequent pattern, but not the regular pattern, thus can not learn the abstract categor

Xavier Rivas

This paper provides a new geometric framework to describe non-conservative field theories with explicit dependence on the space-time coordinates by combining the k-cosymplectic and k-contact formulations. This geometric framework, the k-cocontact geometry, permits to develop a Hamiltonian and Lagrangian formalisms for these field theories. We also compare th

Ran Han, ZhiWei Li, Ruohan Gao, Yao Sun

Geoneutrinos serve as a potent tool for comprehending the radiogenic power and composition of Earth. Although geoneutrinos have been observed in prior experiments, the forthcoming generation of experiments,such as JUNO, will be necessary for fully harnessing their potential. Precise prediction of the crustal contribution is vital for interpreting particlephy

Axel Kleidon

Many aspects of anthropogenic global change, such as land cover change, biodiversity loss and the intensification of agricultural production, threaten the natural biosphere. These aspects seem somewhat disjunct and specific so that it is hard to obtain a bigger picture of what these changes imply and to distinguish beneficial from detrimental human impacts.

Tobias Deußer, Syed Musharraf Ali, Lars Hillebrand, Desiana Nurchalifah

We introduce KPI-EDGAR, a novel dataset for Joint Named Entity Recognition and Relation Extraction building on financial reports uploaded to the Electronic Data Gathering, Analysis, and Retrieval (EDGAR) system, where the main objective is to extract Key Performance Indicators (KPIs) from financial documents and link them to their numerical values and other

Ewa Andrejczuk, Julian Martin Eisenschlos, Francesco Piccinno, Syrine Krichene

Encoder-only transformer models have been successfully applied to different table understanding tasks, as in TAPAS (Herzig et al., 2020). A major limitation of these architectures is that they are constrained to classification-like tasks such as cell selection or entailment detection. We present TABT5, an encoder-decoder model that generates natural language

Minaam Qamar, Matous Mrovec, Yury Lysogorskiy, Anton Bochkarev

We present an atomic cluster expansion (ACE) for carbon that improves over available classical and machine learning potentials. The ACE is parameterized from an exhaustive set of important carbon structures at extended volume and energy range, computed using density functional theory (DFT). Rigorous validation reveals that ACE predicts accurately a broad ran

Sloan Nietert, Ritwik Sadhu, Ziv Goldfeld, Kengo Kato

Sliced Wasserstein distances preserve properties of classic Wasserstein distances while being more scalable for computation and estimation in high dimensions. The goal of this work is to quantify this scalability from three key aspects: (i) empirical convergence rates; (ii) robustness to data contamination; and (iii) efficient computational methods. For empi

Oscar Riaño, Svetlana Roudenko

We study stability of solitary wave solutions for the fractional generalized Korteweg-de Vries equation $$ \partial_t u- \partial_{x_1} D^{\alpha}u+ \tfrac{1}{m}\partial_{x_1}(u^m)=0, ~ (x_1,\dots,x_d)\in \mathbb{R}^d, \, \, t\in \mathbb{R}, \, \, 0<\alpha <2, $$ in any spatial dimension $d\geq 1$ and nonlinearity $m>1$. The arguments developed here are inde

Jaan Kristjan Kaasik, Triinu Veeorg

We construct a Lipschitz-free space that is locally almost square but not weakly almost square; this is the first example of such a Banach space. We also prove a result, which indicates that geodesic metric spaces are a potential metric characterization for weakly almost square Lipschitz-free spaces. Lastly, we prove that a Lipschitz-free space can not have

Josnei Novacoski

In this paper we present a characterization for the defect of a simple algebraic extension of rank one valued fields using the key polynomials that define the valuation. As a particular example, this gives the classification of defect extensions of degree $p$ as dependent or independent presented by Kuhlmann.

Harley Katz, Aayush Saxena, Joki Rosdahl, Taysun Kimm

We use the SPHINX$^{20}$ cosmological radiation hydrodynamics simulation to study how Lyman Continuum (LyC) photons escape from galaxies and the observational signatures of this escape. We define two classes of LyC leaker: Bursty Leakers and Remnant Leakers, based on their star formation rates (SFRs) that are averaged over 10 Myr (SFR$_{10}$) or 100 Myr (SFR

Adam Bene Watts, John Bostanci

We prove the expected disturbance caused to a quantum system by a sequence of randomly ordered two-outcome projective measurements is upper bounded by the square root of the probability that at least one measurement in the sequence accepts. We call this bound the Gentle Random Measurement Lemma. We then consider problems in which we are given sample access t

Lorenzo Iorio

Extrasolar circumbinary planets are so called because they orbit two stars instead of just one; to date, an increasing number of such planets have been discovered with a variety of techniques. If the orbital frequency of the hosting stellar pair is much higher than the planetary one, the tight stellar binary can be considered as a matter ring current generat

Niklas Bunzel, Lukas Graner

Cujo AI and Adversa AI hosted the MLSec face recognition challenge. The goal was to attack a black box face recognition model with targeted attacks. The model returned the confidence of the target class and a stealthiness score. For an attack to be considered successful the target class has to have the highest confidence among all classes and the stealthines

Mark D. McDonnell, Eriita Jones, Megan E. Schwamb, K-Michael Aye

Dark deposits visible from orbit appear in the Martian south polar region during the springtime. These are thought to form from explosive jets of carbon dioxide gas breaking through the thawing seasonal ice cap, carrying dust and dirt which is then deposited onto the ice as dark 'blotches', or blown by the surface winds into streaks or 'fans'. We investigate

Mudit Verma, Katherine Metcalf

Specifying rewards for reinforcement learned (RL) agents is challenging. Preference-based RL (PbRL) mitigates these challenges by inferring a reward from feedback over sets of trajectories. However, the effectiveness of PbRL is limited by the amount of feedback needed to reliably recover the structure of the target reward. We present the PRIor Over Rewards (

Chenglei Si, Zhe Gan, Zhengyuan Yang, Shuohang Wang

Large language models (LLMs) show impressive abilities via few-shot prompting. Commercialized APIs such as OpenAI GPT-3 further increase their use in real-world language applications. However, the crucial problem of how to improve the reliability of GPT-3 is still under-explored. While reliability is a broad and vaguely defined term, we decompose reliability

Qisheng Wang

Lexicographically minimal string rotation is a fundamental problem in string processing that has recently garnered significant attention in quantum computing. Near-optimal quantum algorithms have been proposed for solving this problem, utilizing a divide-and-conquer structure. In this note, we show that its quantum query complexity is $\sqrt{n} \cdot 2^{O(\s

Gaëtan Landreau, Mohamed Tamaazousti

Image-based 3D reconstruction has increasingly stunning results over the past few years with the latest improvements in computer vision and graphics. Geometry and topology are two fundamental concepts when dealing with 3D mesh structures. But the latest often remains a side issue in the 3D mesh-based reconstruction literature. Indeed, performing per-vertex e

Enrico Meloni, Lapo Faggi, Simone Marullo, Alessandro Betti

In this paper, we present PARTIME, a software library written in Python and based on PyTorch, designed specifically to speed up neural networks whenever data is continuously streamed over time, for both learning and inference. Existing libraries are designed to exploit data-level parallelism, assuming that samples are batched, a condition that is not natural

Andrea Antinucci, Francesco Benini, Christian Copetti, Giovanni Galati

We study how non-invertible self-duality defects arise in theories with a holographic dual. We focus on the paradigmatic example of $\mathfrak{su}(N)$ $\mathcal{N} = 4$ SYM. The theory is known to have non-invertible duality and triality defects at $\tau =i$ and $\tau = e^{2 \pi i /3}$, respectively. At these points in the gravitational moduli space, the gau

Niklas V. Lehmann

A simple model is introduced to study the cooperative behavior of nations regarding solar geoengineering. The results of this model are explored through numerical methods. A general finding is that cooperation and coordination between nations on solar geoengineering is very much incentivized. Furthermore, the stability of solar geoengineering agreements betw

Alberto F. Boix, Majid Eghbali

The goal of this paper is twofold; on the one hand, motivated by questions raised by Schenzel, we explore situations where the Hartshorne--Lichtenbaum Vanishing Theorem for local cohomology fails, leading us to simpler expressions of certain local cohomology modules. As application, we give new expressions of the endomorphism ring of these modules. On the ot

Liding Yao

The thesis studies Frobenius-type theorems in non-smooth settings. We extend the definition of involutivity to non-Lipschitz subbundles using generalized functions. We prove the real Frobenius Theorem with sharp regularity on log-Lipschitz subbundles. We also develop a singular version of the Frobenius theorem on log-Lipschitz vector fields: if $X_1,\dots,X_

Carlo Cafaro, Paul M. Alsing

In the geometry of quantum evolutions, a geodesic path is viewed as a path of minimal statistical length connecting two pure quantum states along which the maximal number of statistically distinguishable states is minimum. In this paper, we present an explicit geodesic analysis of the dynamical trajectories that emerge from the quantum evolution of a single-

Eiji Kawasaki, Markus Holzmann, Lawrence Adu-Gyamfi

Markov Chain Monte Carlo (MCMC) algorithms do not scale well for large datasets leading to difficulties in Neural Network posterior sampling. In this paper, we propose Penalty Bayesian Neural Networks - PBNNs, as a new algorithm that allows the evaluation of the likelihood using subsampled batch data (mini-batches) in a Bayesian inference context towards add

Petros Zervoudakis, Maria Plevraki, Eleftheria Plevridi, Alexandros Fragkiadakis

Internet of Things (IoT) technologies have received significant attention in recent years by encompassing a set of technologies that enable a variety of heterogeneous physical objects, called things, to interact and communicate through efficient networking protocols. These technologies have already been used in several domains such as in manufacturing, healt

Wei Zhong, Youjin Deng, Daxing Xiong

We construct the temporal network using the two-dimensional active particle systems which are described by the Vicsek model. The bursts of the interevent times for a specific pair of particles are investigated numerically. We find that for different noise strength, the distribution of the interevent times of a target edge follows by a heavy-tail, revealing a

Rongfan Liao, Siyang Song, Hatice Gunes

Personality determines a wide variety of human daily and working behaviours, and is crucial for understanding human internal and external states. In recent years, a large number of automatic personality computing approaches have been developed to predict either the apparent personality or self-reported personality of the subject based on non-verbal audio-vis

Javier Martín-Goñi

In this paper, we obtain the best possible value of the absolute constant $C$ such that for every isotropic convex body $K \subseteq \mathbb{R}^n$ the following inequality (which was proved by Klartag and reduces the hyperplane conjecture to centrally symmetric convex bodies) is satisfied: $$ L_K\leq CL_{K_{n+2}(g_K)}. $$ Here $L_K$ denotes the isotropic con

Max Taylor, Johnathon Aurand, Feng Qin, Xiaorui Wang

Unit type errors, where values with physical unit types (e.g., meters, hours) are used incorrectly in a computation, are common in today's unmanned aerial system (UAS) firmware. Recent studies show that unit type errors represent over 10% of bugs in UAS firmware. Moreover, the consequences of unit type errors are severe. Over 30% of unit type errors cause UA

Kai Guo, Seungwon Choi, Jongseong Choi

Current video denoising methods perform temporal fusion by designing convolutional neural networks (CNN) or combine spatial denoising with temporal fusion into basic recurrent neural networks (RNNs). However, there have not yet been works which adapt gated recurrent unit (GRU) mechanisms for video denoising. In this letter, we propose a new video denoising m

Jim Beckers, Bart van Erp, Ziyue Zhao, Kirill Kondrashov

Bayesian model reduction provides an efficient approach for comparing the performance of all nested sub-models of a model, without re-evaluating any of these sub-models. Until now, Bayesian model reduction has been applied mainly in the computational neuroscience community on simple models. In this paper, we formulate and apply Bayesian model reduction to pe

Max Nendel

The main result of this paper characterizes the continuity from below of monotone functionals on the space $C_b$ of bounded continuous functions on an arbitrary Polish space as lower semicontinuity in the mixed topology. In this particular situation, the mixed topology coincides with the Mackey topology for the dual pair $(C_b,{\rm ca})$, where ${\rm ca}$ de

Dhanasekar Sundararaman, Nikhil Mehta, Lawrence Carin

While pre-trained large-scale deep models have garnered attention as an important topic for many downstream natural language processing (NLP) tasks, such models often make unreliable predictions on out-of-distribution (OOD) inputs. As such, OOD detection is a key component of a reliable machine-learning model for any industry-scale application. Common approa

Alexei A. Deriglazov

This work contains a brief and elementary exposition of the foundations of Poisson and symplectic geometries, with an emphasis on applications for Hamiltonian systems with second-class constraints. In particular, we clarify the geometric meaning of the Dirac bracket on a symplectic manifold and provide a proof of the Jacobi identity on a Poisson manifold. A

Francisco J. Vielma Leal, Ademir Pastor

The moment method is used to prove the exact controllability of a wide class of bidimensional linear dispersive PDE's posed on the two-dimensional torus $\mathbb{T}^{2}.$ The control function is considered to be acting on a small vertical and horizontal strip of the torus. Our results apply to several well-known models including some bidimesional extensions

Krzysztof Barczynski, Karen A. Meyer, Louise K. Harra, Duncan H. Mackay

The High Resolution Imager (HRI_EUV) telescope of the Extreme Ultraviolet Imager (EUI) instrument onboard Solar Orbiter has observed EUV brightenings, so-called campfires, as fine-scale structures at coronal temperatures. The goal of this paper is to compare the basic geometrical (size, orientation) and physical (intensity, lifetime) properties of the EUV br

Sanyou Wu, Long Feng

This paper aims to present the first Frequentist framework on signal region detection in high-resolution and high-order image regression problems. Image data and scalar-on-image regression are intensively studied in recent years. However, most existing studies on such topics focused on outcome prediction, while the research on image region detection is rathe

Shi-Zhong Du

Bernstein problem for affine maximal type equation \begin{equation}\label{e0.1} u^{ij}D_{ij}w=0, \ \ w\equiv[\det D^2u]^{-\theta},\ \ \forall x\in\Omega\subset{\mathbb{R}}^N \end{equation} has been a core problem in affine geometry. A conjecture proposed firstly by Chern (Proc. Japan-United States Sem., Tokyo, 1977, 17-30) for entire graph and then extended

Thorsten Eisenhofer, Doreen Riepel, Varun Chandrasekaran, Esha Ghosh

Machine unlearning aims to remove points from the training dataset of a machine learning model after training: e.g., when a user requests their data to be deleted. While many unlearning methods have been proposed, none of them enable users to audit the procedure. Furthermore, recent work shows a user is unable to verify whether their data was unlearnt from a

Zhong-Heng Tan, Zhenyue Zhang

Conformal energy minimization is an efficient approach to compute conformal parameterization. In this paper, we develop a stable algorithm to compute conformal parameterization of simply connected open surface, termed Stable Discrete Minimization of Conformal Energy (SDMCE). The stability of SDMCE is reflected in the guarantee of one-to-one and on-to propert

Richard J. Soare, Jean-Pierre Williams, Adam J. Hepburn, Frances E. G. Butcher

The long-term cyclicity and temporal succession of glacial-periglacial (or deglacial) periods or epochs are keynotes of Quaternary geology on Earth. Relatively recent work has begun to explore the histories of the mid- to higher-latitudinal terrain of Mars, especially in the northern hemisphere, for evidence of similar cyclicity and succession in the Mid to

Tal Goldstein, Gal Shmuel

A judicious design of gain and loss leads to counterintuitive wave phenomena that are inaccessible by conservative systems. Notably, such designs can give rise to laser-absorber modes and anisotropic transmission resonances. Here, we analyze the emergence of these phenomena in an optical scatterer with sinusoid gain-loss modulation that is subjected to monoc

M. A. Aksenov, I. V. Zalivako, I. A. Semerikov, A. S. Borisenko

The use of multilevel information carriers, also known as qudits, is a promising path for exploring scalability of quantum computing devices. Here we present a proof-of-principle realization of a quantum processor register that uses optically-addressed $^{171}$Yb$^{+}$ ion qudits in a linear trap. The rich level structure of $^{171}$Yb$^{+}$ ions allows usin

Filip Ficek

From the mathematical side, nonlinear Schr\"odinger equations are usually investigated via variational methods, that cease to work in higher dimensions. This thesis tries to overcome this problem by focusing on spherically symmetric solutions. Then, one can use classical methods coming from the fields of ordinary differential equations and dynamical systems.

Akinari Hoshi, Kazuki Kanai, Aiichi Yamasaki

We give a necessary and sufficient condition for the Hasse norm principle for field extensions $K/k$ when the Galois groups ${\rm Gal}(L/k)$ of the Galois closure $L/k$ of $K/k$ are isomorphic to the Mathieu group $M_{11}$ of degree $11$ of order $7920$ or the Janko group $J_1$ of order $175560$ by determining $H^1(k,{\rm Pic}\, \overline{X})=0$ or $\mathbb{

Iver Brevik, Amedeo M. Favitta, Masud Chaichian

Various aspects of axion electrodynamics in the presence of a homogeneous and isotropic dielectric medium are discussed. 1. We consider first the "antenna-like" property of a planar dielectric surface in axion electrodynamics, elaborating on the treatment given earlier on this topic by Millar {\it et al.} (2017). We calculate the electromagnetic energy trans

Yevgenia Kashina, Yorck Sommerhaeuser

For two families of Yetter-Drinfel'd Hopf algebras considered earlier by the authors, we determine which of them are isomorphic. We also determine which of their Radford biproducts are isomorphic.

G. Rubio, J. Toalá, H. Todt, L. Sabin

Theory predicts that the temperature of the X-ray-emitting gas ($\sim$10$^{6}$ K) detected from planetary nebulae (PNe) is a consequence of mixing or thermal conduction when in contact with the ionized outer rim ($\sim$10$^{4}$ K). Gas at intermediate temperatures ($\sim$10$^{5}$ K) can be used to study the physics of the production of X-ray-emitting gas, vi

Violeta Karyofylli, Marek Behr

This paper highlights how unstructured space-time meshes can be used in production engineering applications with moving domains. Unstructured space-time elements can connect different spatial meshes at the bottom and top level of the space-time domain and deal with complicated domain movements/rotations that the standard arbitrary Lagrangian-Eulerian techniq

Jung-Chao Ban, Wen-Guei Hu, Guan-Yu Lai

In this article, we introduce the concept of the boundary complexity and prove that for a 2-multiplicative integer system (2-MIS) $X^{p}_{\Omega}$ on $\mathbb{N}$ (or $X^{\bf p}_{\Omega}$ on $\mathbb{N}^d,d\geq 2$), every point in $[h(X^p_\Omega), \log r]$ can be realized as a boundary complexity of a 2-MIS with a specific speed, where r stands for the numbe

Stefan Jacob, Shilpi Pandey, Jaime Del Moral, Atefeh Karimzadeh

Migrating active deicing capabilities to transparent materials with low thermal conductivity has a high potential to improve the operations of several seminal industries in the automotive, robotic, energy, and aerospace sectors. However, the development of efficient and environmentally friendly deicing methods is yet in its infancy regarding their compatibil

Loc H. Nguyen, Huong T. Vu

The aim of this paper is to solve an important inverse source problem which arises from the well-known inverse scattering problem. We propose to truncate the Fourier series of the solution to the governing equation with respect to a special basis of L2. By this, we obtain a system of linear elliptic equations. Solutions to this system are the Fourier coeffic

Youssef Aserrar, Elhoucien Elqorachi

We treat two related trigonometric functional equations on semigroups. First we solve the $\mu$-sine subtraction law \[\mu(y) k(x \sigma(y))=k(x) l(y)-k(y) l(x), \quad x, y \in S,\] for $k, l : S\rightarrow \mathbb{C}$, where $S$ is a semigroup and $\sigma$ an involutive automorphism, $\mu :S\rightarrow \mathbb{C}$ is a multiplicative function such that $\mu

Rong Zhang, Vishvesh Kumar, Michael Ruzhansky

We study the Lane-Emden system involving the logarithmic Laplacian: $$ \begin{cases} \ \mathcal{L}_{\Delta}u(x)=v^{p}(x) ,& x\in\mathbb{R}^{n},\\ \ \mathcal{L}_{\Delta}v(x)=u^{q}(x) ,& x\in\mathbb{R}^{n}, \end{cases} $$ where $p,q>1$ and $\mathcal{L}_{\Delta}$ denotes the Logarithmic Laplacian arising as a formal derivative $\partial_s|_{s=0}(-\Delta)^s$ of

Sophie Kadan, Evelyn Thomson

Many Beyond the Standard Model searches at ATLAS employ jets to simplify event reconstruction. These jets cluster particle shower products into calculable objects, which are then used to obtain information about parent particles. Large-R (R = 1.0) jets combine these products into one jet that spans 2 radians, while small-R (R = 0.4) jets are used to further

Emily Hatt, Martin B. Nielsen, William J. Chaplin, Warrick H. Ball

The Transiting Exoplanet Survey Satellite (TESS) mission has provided photometric light curves for stars across nearly the entire sky. This allows for the application of asteroseismology to a pool of potential solar-like oscillators that is unprecedented in size. We aim to produce a catalogue of solar-like oscillators observed by TESS in the 120-second and 2

Priyanka Rushikesh Chaudhary, Rajib Ranjan Maiti

Deployment of IoT cameras in an organization threatens security and privacy policies, and the classification of network traffic without using IP addresses and port numbers has been challenging. In this paper, we have designed, implemented and deployed a system called iCamInspector to classify network traffic arising from IoT camera in a mixed networking envi

Miguel Vasques, Claudia Soares, João Gomes

This paper addresses target localization with an online active learning algorithm defined by distributed, simple and fast computations at each node, with no parameters to tune and where the estimate of the target position at each agent is asymptotically equal in expectation to the centralized maximum-likelihood estimator. ISEE.U takes noisy distances at each

S. Ayik, M. Arik, O. Yilmaz, B. Yilmaz

Production cross-sections of heavy neutron-rich isotopes are calculated by employing quantal transport description in ${}^{250}\text{Cf}+{}^{232}\text{Th}$ collisions. This quantal transport description is based on the stochastic mean-field (SMF) approach, and it provides a microscopic approach beyond time-dependent Hartree-Fock (TDHF) theory to include mean

Rupam Das, Z. E. Musielak

The space of Null Lagrangians is the least investigated territory in dynamics since they are identically sent to zero by their Euler-Lagrange operator and thereby having no effects on equations of motion. A humble effort to discover the relevance of these Null Lagrangians in dynamics is made by introducing a generalized procedure (with respect to the recent

Fei Xu, Lu Cai, Daniele Salvato, Fidelma Dilemma

U-10Zr-based metallic nuclear fuel is a promising fuel candidate for next-generation sodium-cooled fast reactors.The research experience of the Idaho National Laboratory for this type of fuel dates back to the 1960s. Idaho National Laboratory researchers have accumulated a considerable amount of experience and knowledge regarding fuel performance at the engi

Monojit Ghosh, Osamu Yasuda

CP phase determination for the near future long baseline experiments, T2HK and DUNE, will require precise measurements of the oscillation probabilities. However, the uncertainty in the Earth's density must be considered in determining these oscillation probabilities. Therefore, in this study, we update the individual sensitivities of these experiments for de

Adrien Morin

We define a Weil-\'etale complex with compact support for duals (in the sense of the Bloch dualizing cycles complex $\mathbb{Z}^c$) of a large class of $\mathbb{Z}$-constructible sheaves on an integral $1$-dimensional proper arithmetic scheme flat over $\mathrm{Spec}(\mathbb{Z})$. This complex can be thought of as computing Weil-\'etale homology. For those $

Carlos H. F. Poncio, Edivaldo Lopes dos Santos, Leandro Vicente Mauri, Denise de Mattos

In this paper, we present some results related to Barany-Larman colored problem and The Zivaljevic and Vrecica colored Tverberg problem. We give an alternative proof for the Barany-Larman Conjecture for primes -1 and the optimal colored Tverberg theorem. Also, we prove generalizations of the Colored Tverberg theorem of Zivaljevic and Vrecica.

Antonis Sklavos, Pavlos Fafalios, Yannis Tzitzikas

An increasing number of organisations in almost all fields have started adopting semantic web technologies for publishing their data as open, linked and interoperable (RDF) datasets, queryable through the SPARQL language and protocol. Link traversal has emerged as a SPARQL query processing method that exploits the Linked Data principles and the dynamic natur

Lianting Hu, Huiying Liang, Jiajie Tang, Xin Li

Background: Medical images are more difficult to acquire and annotate than natural images, which results in data augmentation technologies often being used in medical image segmentation tasks. Most data augmentation technologies used in medical segmentation were originally developed on natural images and do not take into account the characteristic that the o

Niels Henrik Aase, Asle Sudbø

We study spin-fluctuation mediated divergent superconducting fluctuations in a Luttinger liquid proximity-coupled to a spin chain. Our study provides insight into how spin fluctuations can induce superconductivity in a strongly correlated non-Fermi liquid with repulsive electronic interactions only. The electrons in the system are governed by the Extended Hu

Norbert Ankri, Païkan Marcaggi

Recently, V. Laure van Bambeke used an original approach to solve the famous problem of transformation of values into production prices by considering that capital reallocation to each department (branch) was part of the problem. Here, we confirm the validity of this consideration in relation with the satisfaction of demand (social need which is able to pay

Denis Mourard, Philippe Berio, Cyril Pannetier, Nicolas Nardetto

With a possible angular resolution down to 0.1-0.2 millisecond of arc using the 330 m baselines and the access to the 600-900 nm spectral domain, the CHARA Array is ideally configured for focusing on precise and accurate fundamental parameters of stars. CHARA/SPICA (Stellar Parameters and Images with a Cophased Array) aims at performing a large survey of sta

Marta Bilkova, Sabine Frittella, Daniil Kozhemiachenko, Ondrej Majer

The reasoning with qualitative uncertainty measures involves comparative statements about events in terms of their likeliness without necessarily assigning an exact numerical value to these events. The paper is divided into two parts. In the first part, we formalise reasoning with the qualitative counterparts of capacities, belief functions, and probabilitie

Frauke von Bieberstein, Anna-Corinna Kulle, Stefanie Schumacher

Hand hygiene is one of the key low-cost measures proposed by the World Health Organization (WHO) to contain the spread of COVID-19. In a field study conducted during the pandemic in June and July 2020 in Switzerland, we captured the hand disinfection behavior of customers in five stores of a large retail chain (n = 8,245). The study reveals considerable diff

Michael Greenblatt

We describe an elementary method for bounding a one-dimensional oscillatory integral in terms of an associated non-oscillatory integral. The bounds obtained are efficient in an appropriate sense and behave well under perturbations of the phase. As a consequence, for an $n$-dimensional oscillatory integral with a critical point at the origin, we may apply the

Hengbin Cheng, Jingyu Yang, Zhong Wang, Ling Lu

Among the many far-reaching consequences of the potential existence of a magnetic monopole, it induces topological zero modes in the Dirac equation, which were derived by Jackiw and Rebbi 46 years ago and have been elusive ever since. Here, we show that the monopole and multi-monopole solutions can be constructed in the band theory by coupling the three-dime

Moo K. Chung, Soumya Das, Hernando Ombao

Developing reliable methods to discriminate different transient brain states that change over time is a key neuroscientific challenge in brain imaging studies. Topological data analysis (TDA), a novel framework based on algebraic topology, can handle such a challenge. However, existing TDA has been somewhat limited to capturing the static summary of dynamica

Shai M. Chester, Ning Su

We consider the 3-state Potts model in $d\geq2$ dimensions. For $d$ less than the upper critical dimension $d_\text{crit}$, the model has a critical and a tricritical fixed point. In $d=2$, these fixed points are described by minimal models, and so are exactly solvable. For $d>2$, however, strong coupling makes them difficult to study and there is no consens

Furkan Kınlı, Doğa Yılmaz, Barış Özcan, Furkan Kıraç

Style may refer to different concepts (e.g. painting style, hairstyle, texture, color, filter, etc.) depending on how the feature space is formed. In this work, we propose a novel idea of interpreting the lighting in the single- and multi-illuminant scenes as the concept of style. To verify this idea, we introduce an enhanced auto white-balance (AWB) method

Jürgen Dölz, David Ebert

We consider generalized operator eigenvalue problems in variational form with random perturbations in the bilinear forms. This setting is motivated by variational forms of partial differential equations with random input data. The considered eigenpairs can be of higher but finite multiplicity. We investigate stochastic quantities of interest of the eigenpair