November 2022 arXiv papers — page 156

Niklas Muennighoff, Thomas Wang, Lintang Sutawika, Adam Roberts

Multitask prompted finetuning (MTF) has been shown to help large language models generalize to new tasks in a zero-shot setting, but so far explorations of MTF have focused on English data and models. We apply MTF to the pretrained multilingual BLOOM and mT5 model families to produce finetuned variants called BLOOMZ and mT0. We find finetuning large multilin

Yufei Xu, Jing Zhang, Qiming Zhang, Dacheng Tao

Self-supervised pre-training vision transformer (ViT) via masked image modeling (MIM) has been proven very effective. However, customized algorithms should be carefully designed for the hierarchical ViTs, e.g., GreenMIM, instead of using the vanilla and simple MAE for the plain ViT. More importantly, since these hierarchical ViTs cannot reuse the off-the-she

Jiacheng Ruan, Suncheng Xiang, Mingye Xie, Ting Liu

Recently, some pioneering works have preferred applying more complex modules to improve segmentation performances. However, it is not friendly for actual clinical environments due to limited computing resources. To address this challenge, we propose a light-weight model to achieve competitive performances for skin lesion segmentation at the lowest cost of pa

Matthew Kowal, Mennatullah Siam, Md Amirul Islam, Neil D. B. Bruce

There is limited understanding of the information captured by deep spatiotemporal models in their intermediate representations. For example, while evidence suggests that action recognition algorithms are heavily influenced by visual appearance in single frames, no quantitative methodology exists for evaluating such static bias in the latent representation co

Arij Benkhadra, Isar Stubbe

We prove a fixpoint theorem for contractions on Cauchy-complete quantale-enriched categories. It holds for any quantale whose underlying lattice is continuous, and applies to contractions whose control function is sequentially lower-semicontinuous. Sufficient conditions for the uniqueness of the fixpoint are established. Examples include known and new fixpoi

Guang Yang, Manling Li, Jiajie Zhang, Xudong Lin

Video event extraction aims to detect salient events from a video and identify the arguments for each event as well as their semantic roles. Existing methods focus on capturing the overall visual scene of each frame, ignoring fine-grained argument-level information. Inspired by the definition of events as changes of states, we propose a novel framework to de

Xuan Zhou, Claudio Sbarufatti, Marco Giglio, Leiting Dong

Online damage quantification suffers from insufficient labeled data that weakens its accuracy. In this context, adopting the domain adaptation on historical labeled data from similar structures/damages or simulated digital twin data to assist the current diagnosis task would be beneficial. However, most domain adaptation methods are designed for classificati

W. R. B. Luckin, Y. Li, J. Jiang, S. M. Gunasekera

We report on the interplay between a van Hove singularity and a charge density wave state in 2H-TaSe$_{2}$. We use angle-resolved photoemission spectroscopy to investigate changes in the Fermi surface of this material under surface doping with potassium. At high doping, we observe modifications which imply the disappearance of the $(3\times 3)$ charge densit

Xi-Ci Yang, Z. Y. Xie, Xiao-Tao Yang

We propose to employ the hierarchical coarse-grained structure in the artificial neural networks explicitly to improve the interpretability without degrading performance. The idea has been applied in two situations. One is a neural network called TaylorNet, which aims to approximate the general mapping from input data to output result in terms of Taylor seri

Yi-Ting Shen, Hyungtae Lee, Heesung Kwon, Shuvra Shikhar Bhattacharyya

To effectively interrogate UAV-based images for detecting objects of interest, such as humans, it is essential to acquire large-scale UAV-based datasets that include human instances with various poses captured from widely varying viewing angles. As a viable alternative to laborious and costly data curation, we introduce Progressive Transformation Learning (P

Andreas Stöckl

We generate synthetic images with the "Stable Diffusion" image generation model using the Wordnet taxonomy and the definitions of concepts it contains. This synthetic image database can be used as training data for data augmentation in machine learning applications, and it is used to investigate the capabilities of the Stable Diffusion model. Analyses show t

Hans Zantema

Simon's problem is a standard example of a problem that is exponential in classical sense, while it admits a polynomial solution in quantum computing. It is about a function $f$ for which it is given that a unique non-zero vector $s$ exists for which $f(x) = f(x \oplus s)$ for all $x$, where $\oplus$ is the exclusive or operator. The goal is to find $s$. The

Philip Dittmann

We construct an existentially undecidable complete discretely valued field of mixed characteristic with existentially decidable residue field and decidable algebraic part, answering a question by Anscombe-Fehm in a strong way. Along the way, we construct an existentially decidable field of positive characteristic with an existentially undecidable finite exte

Runyu Ma, Tianxing Ma

The competition between antiferromagnetism and superconductivity is one of the central questions in the research of strong correlated systems. In this work, we utilize a double layer model containing Hubbard interaction and interlayer Heisenberg interaction to reveal their competitions. This model is free of sign problem at certain conditions, and we perform

Harsh Patel, Shivam Sahni

With the growing use of deep learning methods, particularly graph neural networks, which encode intricate interconnectedness information, for a variety of real tasks, there is a necessity for explainability in such settings. In this paper, we demonstrate the applicability of popular explainability approaches on Graph Attention Networks (GAT) for a graph-base

Guangtong Li, L Siddharth, Jianxi Luo

Knowledge proximity refers to the strength of association between any two entities in a structural form that embodies certain aspects of a knowledge base. In this work, we operationalize knowledge proximity within the context of the US Patent Database (knowledge base) using a knowledge graph (structural form) named PatNet built using patent metadata, includi

Daniela D. Doneva, Fethi M. Ramazanoğlu, Hector O. Silva, Thomas P. Sotiriou

Scalarization is a mechanism that endows strongly self-gravitating bodies, such as neutron stars and black holes, with a scalar-field configuration. It resembles a phase transition in that the scalar configuration appears only when a certain quantity that characterizes the compact object, for example, its compactness or spin, is beyond a threshold. A critica

Jia Wang

In this brief review, we report some new development in the functional determinant approach (FDA), an exact numerical method, in the studies of a heavy quantum impurity immersed in Fermi gases and manipulated with radio-frequency pulses. FDA has been successfully applied to investigate the universal dynamical responses of a heavy impurity in an ultracold ide

Yongjun Ahn, Matteo Baggioli, Kyoung-Bum Huh, Hyun-Sik Jeong

Within the framework of holography, the Einstein-Maxwell action with Dirichlet boundary conditions corresponds to a dual conformal field theory in presence of an external gauge field. Nevertheless, in many real-world applications, e.g., magnetohydrodynamics, plasma physics, superconductors, etc. dynamical gauge fields and Coulomb interactions are fundamental

Alexandre d'Aspremont, Cristóbal Guzmán, Clément Lezane

Inspired by regularization techniques in statistics and machine learning, we study complementary composite minimization in the stochastic setting. This problem corresponds to the minimization of the sum of a (weakly) smooth function endowed with a stochastic first-order oracle, and a structured uniformly convex (possibly nonsmooth and non-Lipschitz) regulari

Sofoklis Kakouros, Themos Stafylakis, Ladislav Mosner, Lukas Burget

When recognizing emotions from speech, we encounter two common problems: how to optimally capture emotion-relevant information from the speech signal and how to best quantify or categorize the noisy subjective emotion labels. Self-supervised pre-trained representations can robustly capture information from speech enabling state-of-the-art results in many dow

Christiaan J. F. van de Ven

A continuous bundle of $C^*$-algebras provides a rigorous framework to study the thermodynamic limit of quantum theories. If the bundle admits the additional structure of a strict deformation quantization (in the sense of Rieffel) one is allowed to study the classical limit of the quantum system, i.e. a mathematical formalism that examines the convergence of

Yonghui Liu, Xiao Chen, Yue Liu, Pingfan Kong

Context: Smart TVs have become one of the most popular television types. Many app developers and service providers have designed TV versions for their smartphone applications. Despite the extensive studies on mobile app analysis, its TV equivalents receive far too little attention. The relationship between phone and TV has not been the subject of research wo

Pavel Andreev, Nicholas Babaev, Azat Saginbaev, Ivan Shchekotov

Streaming models are an essential component of real-time speech enhancement tools. The streaming regime constrains speech enhancement models to use only a tiny context of future information. As a result, the low-latency streaming setup is generally considered a challenging task and has a significant negative impact on the model's quality. However, the sequen

Jörg Schöpf, Paul H. M. van Loosdrecht, Ionela Lindfors-Vrejoiu

Magneto-optic Kerr effect can probe the process of magnetization reversal in ferromagnetic thin films and thus be used as an alternative to magnetometry. Kerr effect is wavelength-dependent and the Kerr rotation can reverse sign, vanishing at particular wavelengths. We investigate epitaxial heterostructures of ferromagnetic manganite, La$_{0.7}$Sr$_{0.3}$Mn$

Yang Chen, Leyuan Sun, Mehdi Benallegue, Rafael Cisneros

In immersive humanoid robot teleoperation, there are three main shortcomings that can alter the transparency of the visual feedback: the lag between the motion of the operator's and robot's head due to network communication delays or slow robot joint motion. This latency could cause a noticeable delay in the visual feedback, which jeopardizes the embodiment

A. Grassi, J. Golak, W. N. Polyzou, R. Skibiński

We build a relativistic model to perform calculations of exclusive, semi-exclusive and inclusive unpolarized cross sections and various polarization observables in electron and neutrino scattering experiments with deuteron targets. The strong interaction dynamics is defined by an explicit dynamical unitary representation of the Poincar\'e group, where repres

Filip De Turck

In this paper, we show how different types of distributed mutual algorithms can be compared in terms of performance through simulations. A simulation-based approach is presented, together with an overview of the relevant evaluation metrics and approach for statistical processing of the results. The presented simulations can be used to learn master students o

Tore Selland Kleppe

A metric tensor for Riemann manifold Monte Carlo particularly suited for non-linear Bayesian hierarchical models is proposed. The metric tensor is built from symmetric positive semidefinite log-density gradient covariance (LGC) matrices, which are also proposed and further explored here. The LGCs generalize the Fisher information matrix by measuring the join

Sandeep Bondalapati

Robotics is used to foster creativity. Humans can perform jobs in their unique manner, depending on the circumstances. This situation applies to food cooking. Robotic technology in the kitchen can speed up the process and reduce its workload. However, the potential of robotics in the kitchen is still unrealized. In this essay, the idea of FOON, a structural

Jonas Chaves-Montero, Raul E. Angulo, Sergio Contreras

Recent analyses show that $\Lambda$CDM-based models optimised to reproduce the clustering of massive galaxies overestimate their gravitational lensing by about 30\%, the so-called lensing is low problem. Using a state-of-the-art hydrodynamical simulation, we show that this discrepancy reflects shortcomings in standard galaxy-halo connection models rather tha

Jianjun Jin

In this paper we study a multiplier operator which is induced by the Schwarzian derivative of univalent functions with a quasiconformal extension to the extended complex plane. As applications, we show that the Brennan conjecture is satisfied for a large class of quasidisks. We also establish a new characterization of asymptotically conformal curves and of t

Z. Ovadyahu

Disorder and homogeneity are two concepts that refer to spatial variation of the system potential. In condensed-matter systems disorder is typically divided into two types; those with local parameters varying from site to site (diagonal disorder) and those characterized by random transfer-integral values (off-diagonal disorder). Amorphous systems in particul

Wael Alsobhi, Tarik Alafif, Alaa Abdel-Hakim, Weiwei Zong

Batch Normalization (BN) is an important preprocessing step to many deep learning applications. Since it is a data-dependent process, for some homogeneous datasets it is a redundant or even a performance-degrading process. In this paper, we propose an early-stage feasibility assessment method for estimating the benefits of applying BN on the given data batch

Sargam M. Mulay, Durgesh Tripathi, Helen Mason, Giulio Del Zanna

We have carried out a comprehensive study of the temperature structure of plasmoids, which successively occurred in recurrent active region jets. The multithermal plasmoids were seen to be travelling along the multi-threaded spire as well as at the footpoint region in the EUV/UV images recorded by the Atmospheric Imaging Assembly (AIA). The Differential Emis

Muhsinath. M, Hassan Basari V. T., Titus K. Mathew

The expansion law proposed by Padmanabhan suggests that the evolution of the volume of the horizon is due to the difference between the degrees of freedom on the horizon and the degrees of freedom in the bulk enclosed by the horizon. In formulating this law, Padmanabhan used the temperature, $T=H/2\pi$, for a dynamical expansion. In this work, we modified th

Theresa Bender, Jacqueline Michelle Beinecke, Dagmar Krefting, Carolin Müller

Despite their remarkable performance, deep neural networks remain unadopted in clinical practice, which is considered to be partially due to their lack in explainability. In this work, we apply attribution methods to a pre-trained deep neural network (DNN) for 12-lead electrocardiography classification to open this "black box" and understand the relationship

Teresa Montaruli

Neutrino astronomy saw its birth with the discovery by IceCube of a diffuse flux at energies above 60 TeV with intensity comparable to a predicted upper limit to the flux from extra-galactic sources of ultra-high energy cosmic rays (UHECRs). While such an upper limit corresponds to the case of calorimetric sources, in which cosmic rays lose all their energy

N. Debergh, J. -P. Petit

We consider four subsets of the complexified spacetime algebra, namely the real even part, the real odd part, the imaginary even part and the imaginary odd part. This naturally leads to the four connected components of the Lorentz group, supplemented each time by an additional symmetry. We then examine how these four parts impact the Dirac equation and show

Emre Can Acikgoz, Tilek Chubakov, Müge Kural, Gözde Gül Şahin

This paper describes our winning systems in MRL: The 1st Shared Task on Multilingual Clause-level Morphology (EMNLP 2022 Workshop) designed by KUIS AI NLP team. We present our work for all three parts of the shared task: inflection, reinflection, and analysis. We mainly explore transformers with two approaches: (i) training models from scratch in combination

Paolo Franceschini, Veronica R. Policht, Alessandra Milloch, Andrea Ronchi

Managing light-matter interactions on timescales faster than the loss of electronic coherence is key for achieving full quantum control of the final products in solid-solid transformations. In this work, we demonstrate coherent electronic control of the photoinduced insulator-to-metal transition in the prototypical Mott insulator V$_2$O$_3$. Selective excita

Jing Li, Jing Lu, Z. R. Gong, Lan Zhou

We study the chiral feature in a system composed of one two-level emitter (TLE) and a one dimensional (1D) dimer chain of coupled resonators with the alternate single-photon energies. In the single-excitation subspace, this system not only possesses two energy bands with propagating states, but also possesses chiral bound states. The number of chiral bound s

Ana-Elena Tutueanu, Machteld E. Kamminga, Tim B. Tejsner, Henrik Jacobsen

We present triple-axis neutron scattering studies of low-energy magnetic fluctuations in strongly underdoped La$_{2-x}$Sr$_{x}$CuO$_{4}$ with $x=0.05$, $0.06$ and $0.07$, providing quantitative evidence for a direct competition between these fluctuations and superconductivity. At dopings $x=0.06$ and $x=0.07$, three-dimensional superconductivity is found, wh

R. H Aguilera-del-Toro, M. Arruabarrena, A. Leonardo, A. Ayuela

Iron ilmenene is a new two-dimensional material that has recently been exfoliated from the naturally-occurring iron titanate found in ilmenite ore, a material that is abundant on earth surface. In this work, we theoretically investigate the structural, electronic and magnetic properties of 2D transition-metal-based ilmenene-like titanates. The study of magne

Buddhi Prakash Sharma, Anu Gupta, Chandra Shekhar

Human lives are improving with the widespread use of cutting-edge digital technology like the Internet of Things (IoT). Recently, the pandemic has shown the demand for more digitally advanced IoT-based devices. International Data Corporation (IDC) forecasts that by 2025, there will be approximately 42 billion of these devices in use, capable of producing aro

Emre Ozfatura, Yulin Shao, Amin Ghazanfari, Alberto Perotti

Deep neural network (DNN)-assisted channel coding designs, such as low-complexity neural decoders for existing codes, or end-to-end neural-network-based auto-encoder designs are gaining interest recently due to their improved performance and flexibility; particularly for communication scenarios in which high-performing structured code designs do not exist. C

Miguel Escudero, Thomas Schwetz, Jorge Terol-Calvo

Cosmological constraints on the sum of the neutrino masses can be relaxed if the number density of active neutrinos is reduced compared to the standard scenario, while at the same time keeping the effective number of neutrino species $N_{\rm eff}\approx 3$ by introducing a new component of dark radiation. We discuss a UV complete model to realise this idea,

Giacomo Ferrante, Gabriele Franciolini, Antonio Junior Iovino, Alfredo Urbano

We develop an exact formalism for the computation of the abundance of primordial black holes (PBHs) in the presence of local non-gaussianity (NG) in the curvature perturbation field. For the first time, we include NG going beyond the widely used quadratic and cubic approximations, and consider a completely generic functional form. Adopting threshold statisti

Marek Kwiek, Wojciech Roszka

We examined a large population of Polish science, technology, engineering, mathematics and medicine (STEMM) scientists (N = 16,083) to study rank advancement and productivity. We used two previously neglected time dimensions - promotion age and promotion speed - to construct individual biographical profiles and publication profiles. We used a classificatory

Yiyong Luo, Jim E. Griffin

Vector autoregressions (VARs) are popular model for analyzing multivariate economic time series. However, VARs can be over-parameterized if the numbers of variables and lags are moderately large. Tensor VAR, a recent solution to over-parameterization, treats the coefficient matrix as a third-order tensor and estimates the corresponding tensor decomposition t

Ran Ben-Basat, Gil Einziger, Wenchen Han, Bilal Tayh

Streaming algorithms are fundamental in the analysis of large and online datasets. A key component of many such analytic tasks is $q$-MAX, which finds the largest $q$ values in a number stream. Modern approaches attain a constant runtime by removing small items in bulk and retaining the largest $q$ items at all times. Yet, these approaches are bottlenecked b

Siddharth Gupta, Manish Kumar, Shreyas Pai

In a reconfiguration problem, given a problem and two feasible solutions of the problem, the task is to find a sequence of transformations to reach from one solution to the other such that every intermediate state is also a feasible solution to the problem. In this paper, we study the distributed spanning tree reconfiguration problem and we define a new reco

Mickaël Delcey, Yoann Cheny, Sébastien Kiesgen de Richter

The present work investigates the use of physics-informed neural networks (PINNs) for the 3D reconstruction of unsteady gravity currents from limited data. In the PINN context, the flow fields are reconstructed by training a neural network whose objective function penalizes the mismatch between the network predictions and the observed data and embeds the und

Gal Leibovich, Guy Jacob, Or Avner, Gal Novik

We propose $\textit{iterative inversion}$ -- an algorithm for learning an inverse function without input-output pairs, but only with samples from the desired output distribution and access to the forward function. The key challenge is a $\textit{distribution shift}$ between the desired outputs and the outputs of an initial random guess, and we prove that ite

Petr A. Golovach, Giannos Stamoulis, Dimitrios M. Thilikos

The disjoint paths logic, FOL+DP, is an extension of First-Order Logic (FOL) with the extra atomic predicate $\mathsf{dp}_k(x_1,y_1,\ldots,x_k,y_k),$ expressing the existence of internally vertex-disjoint paths between $x_i$ and $y_i,$ for $i\in\{1,\ldots, k\}$. This logic can express a wide variety of problems that escape the expressibility potential of FOL

Zitha Sasindran, Harsha Yelchuri, T. V. Prabhakar, Supreeth Rao

Many studies have examined the shortcomings of word error rate (WER) as an evaluation metric for automatic speech recognition (ASR) systems. Since WER considers only literal word-level correctness, new evaluation metrics based on semantic similarity such as semantic distance (SD) and BERTScore have been developed. However, we found that these metrics have th

Pavol Gajdoš, Martin Vaňko

Here we present an initial look at the dynamics and stability of 178 multiplanetary systems which are already confirmed and listed in the NASA Exoplanet Archive. To distinguish between the chaotic and regular nature of a system, the value of the MEGNO indicator for each system was determined. Almost three-quarters of them could be labelled as long-term stabl

M. Barbisan, R. Pasqualotto, A. Rizzolo

The ITER Heating Neutral Beam (HNB) injector is required to deliver 16.7 MW power into the plasma from a neutralised beam of H-/D- negative ions, produced by an RF source and accelerated up to 1 MeV. To enhance the H-/D- production, the surface of the acceleration system grid facing the source (the plasma grid) will be coated with Cs because of its low work

R. Gratton, S. Desidera, F. Marzari, M. Bonavita

While a large fraction of the stars are in multiple systems, our understanding of the processes leading to the formation of these systems is still inadequate. Given the large theoretical uncertainties, observation plays a basic role. Here we discuss the contribution of high contrast imaging, and more specifically of the SPHERE instrument at the ESO Very Larg

Bohan Tang, Siheng Chen, Xiaowen Dong

Hypergraph structure learning, which aims to learn the hypergraph structures from the observed signals to capture the intrinsic high-order relationships among the entities, becomes crucial when a hypergraph topology is not readily available in the datasets. There are two challenges that lie at the heart of this problem: 1) how to handle the huge search space

Peter Wissbrock, David Pelkmann, Yvonne Richter

In the end-of-line test of geared motors, the evaluation of product qual-ity is important. Due to time constraints and the high diversity of variants, acous-tic measurements are more economical than vibration measurements. However, the acoustic data is affected by industrial disturbing noise. Therefore, the aim of this study is to investigate the robustness

Samit Dasgupta, Matthew H. L. Honnor, Michael Spieß

We prove the equality of three conjectural formulas for the Brumer--Stark units. The first formula has essentially been proven, so the present paper also verifies the validity of the other two formulas.

Nina del Ser, Vivek Lohani

Chiral magnets can host topological particles known as skyrmions, which carry an exactly quantised topological charge $Q=-1$. In the presence of an oscillating magnetic field ${\bf B}_1(t)$, a single skyrmion embedded in a ferromagnetic background will start to move with constant velocity ${\bf v}_{\text{trans}}$. The mechanism behind this motion is similar

Fei Xu, Jianian Xu, Jiabin Chen, Li Chen

GPUs are essential to accelerating the latency-sensitive deep neural network (DNN) inference workloads in cloud datacenters. To fully utilize GPU resources, spatial sharing of GPUs among co-located DNN inference workloads becomes increasingly compelling. However, GPU sharing inevitably brings severe performance interference among co-located inference workloa

Alyzia Maria Konsta, Alberto Lluch Lafuente, Nicola Dragoni

Internet of Things (IoT) is a network of devices that communicate with each other through the internet and provides intelligence to industry and people. These devices are running in potentially hostile environments, so the need for security is critical. Trust Management aims to ensure the reliability of the network by assigning a trust value in every node in

Feng-Xiao Liu, Ru-Hui Ni, Xian-Hui Zhong, Qiang Zhao

In the framework of a nonrelativistic potential quark model, we investigate the mass spectrum of the $1S$-wave charmed-strange tetraquark states of $cn\bar{s}\bar{n}$ and $cs\bar{n}\bar{n}$ ($n=u$ or $d$) systems. The tetraquark system is solved by a correlated Gaussian method. With the same parameters fixed by the meson spectra, we obtained the mass spectra

Michel Bauer, Denis Bernard, Philippe Biane, Ludwig Hruza

We present a new description of the known large deviation function of the classical symmetric simple exclusion process by exploiting its connection with the quantum symmetric simple exclusion processes and using tools from free probability. This may seem paradoxal as free probability usually deals with non commutative probability while the simple exclusion p

Zeynep Demir Vatansever

We perform extensive Monte Carlo simulations to investigate the dynamic phase transition properties of the two-dimensional kinetic Ising model on the kagome lattice in the presence of square-wave oscillating magnetic field. Through detailed finite-size scaling analysis, we study universality aspects of the non-equilibrium phase transition. Obtained critical

Anthony Whitworth, Felix Priestley, Samuel Geen

We develop a simple analytic model for what happens when an O star (or compact cluster of OB stars) forms in a shock compressed layer and carves out an approximately circular hole in the layer, at the waist of a bipolar HII Region (HIIR). The model is characterised by three parameters: the half-thickness of the undisturbed layer, Zlay, the mean number-densit

Li Chen, Zhan Cao, Ke He, Xin Liu

The realization of chiral Majorana modes is a challenging task. We aim to comprehend the phase diagrams and parameter control capabilities of the actual devices used in the chiral Majorana search. Beyond the well-known minimal models, we develop a numerical simulation scheme using a self-consistent Schrodinger-Poisson approach to study, as an example, the Mn

Timothy L. Molloy, Iman Shames

We investigate the problem of finding paths that enable a robot modeled as a Dubins car (i.e., a constant-speed finite-turn-rate unicycle) to escape from a circular region of space in minimum time. This minimum-time escape problem arises in marine, aerial, and ground robotics in situations where a safety region has been violated and must be exited before a p

Jihyun Mun, Sunhee Kim, Myeong Ju Kim, Jiwon Ryu

In this study, we present a speech corpus of patients with chronic kidney disease (CKD) that will be used for research on pathological voice analysis, automatic illness identification, and severity prediction. This paper introduces the steps involved in creating this corpus, including the choice of speech-related parameters and speech lists as well as the re

Peter Wißbrock, Yvonne Richter, David Pelkmann, Zhao Ren

Acoustic-based fault detection has a high potential to monitor the health condition of mechanical parts. However, the background noise of an industrial environment may negatively influence the performance of fault detection. Limited attention has been paid to improving the robustness of fault detection against industrial environmental noise. Therefore, we pr

Ke Sun, Samir M. Perlaza, Alain Jean-Marie

In this paper, $2\times2$ zero-sum games are studied under the following assumptions: $(1)$ One of the players (the leader) commits to choose its actions by sampling a given probability measure (strategy); $(2)$ The leader announces its action, which is observed by its opponent (the follower) through a binary channel; and $(3)$ the follower chooses its strat

M. Cristina Câmara, Gabriel Lopes Cardoso

Explicit solutions to the non-linear field equations of some gravitational theories can be obtained, by means of a Riemann-Hilbert approach, from a canonical Wiener-Hopf factorisation of certain matrix functions called monodromy matrices. In this paper we describe other types of factorisation from which solutions can be constructed in a similar way. Our appr

Niels Grüttemeier, Philipp Heinrich Keßler, Christian Komusiewicz, Frank Sommer

In the Vertex Triangle 2-Club problem, we are given an undirected graph $G$ and aim to find a maximum-vertex subgraph of $G$ that has diameter at most 2 and in which every vertex is contained in at least $\ell$ triangles in the subgraph. So far, the only algorithm for solving Vertex Triangle 2-Club relies on an ILP formulation [Almeida and Br\'as, Comput. Op

Ajinkya Khoche, Maciej K Wozniak, Daniel Duberg, Patric Jensfelt

Maps play a key role in rapidly developing area of autonomous driving. We survey the literature for different map representations and find that while the world is three-dimensional, it is common to rely on 2D map representations in order to meet real-time constraints. We believe that high levels of situation awareness require a 3D representation as well as t

Danish Kashaev, Guido Schäfer

The vertex cover problem is a fundamental and widely studied combinatorial optimization problem. It is known that its standard linear programming relaxation is integral for bipartite graphs and half-integral for general graphs. As a consequence, the natural rounding algorithm based on this relaxation computes an optimal solution for bipartite graphs and a $2

Natalya Weber, Werner Koch, Tom Froese

The Self-Optimization (SO) model is a useful computational model for investigating self-organization in "soft" Artificial life (ALife) as it has been shown to be general enough to model various complex adaptive systems. So far, existing work has been done on relatively small network sizes, precluding the investigation of novel phenomena that might emerge fro

F. Ursini, A. Marinucci, G. Matt, S. Bianchi

We report on the Imaging X-ray Polarimetry Explorer (IXPE) observation of the closest and X-ray brightest Compton-thick active galactic nucleus (AGN), the Circinus galaxy. We find the source to be significantly polarized in the 2--6 keV band. From previous studies, the X-ray spectrum is known to be dominated by reflection components, both neutral (torus) and

Yue Yao, Daniel Goehring, Joerg Reichardt

Linear trajectory models provide mathematical advantages to autonomous driving applications such as motion prediction. However, linear models' expressive power and bias for real-world trajectories have not been thoroughly analyzed. We present an in-depth empirical analysis of the trade-off between model complexity and fit error in modelling object trajectori

M. Barbisan, R. Agnello, G. Casati, R. Pasqualotto

The Neutral beam Injectors of the ITER experiment will be based on negative ion sources for the generation of beams composed by 1 MeV H/D particles. The prototype of these sources is currently under testing in the SPIDER experiment, part of the Neutral Beam Test Facility of Consorzio RFX, Padua, Italy. Among the targets of the experimentation in SPIDER, it i

M. Fratta, S. Scaringi, M. Monguió, A. F. Pala

State-of-the-art techniques to identify H\alpha emission line sources in narrow-band photometric surveys consist of searching for H\alpha excess with reference to nearby objects in the sky (position-based selection). However, while this approach usually yields very few spurious detections, it may fail to select intrinsically faint and/or rare H\alpha-excess

Thiri Yadanar Htun, Yupeng Yan

We perform the ab initio no-core shell model (NCSM) calculation to investigate the bound state problem of the three-body $\Lambda nn$ system in chiral next-to-next-to-leading-order NN and chiral leading-order YN interactions. The calculations show that no $\Lambda nn$ bound state exists, but predict a low-lying $\Lambda nn$ resonant state near the threshold

Wonseok Hwang, Saehee Eom, Hanuhl Lee, Hai Jin Park

Legal practitioners often face a vast amount of documents. Lawyers, for instance, search for appropriate precedents favorable to their clients, while the number of legal precedents is ever-growing. Although legal search engines can assist finding individual target documents and narrowing down the number of candidates, retrieved information is often presented

Bahram Mashhoon, Sohrab Rahvar

We discuss polarization of gravitational radiation within the standard framework of linearized general relativity. The recent experimental discovery of gravitational waves provides the impetus to revisit the implications of the spin-rotation-gravity coupling for polarized gravitational radiation; therefore, we consider the coupling of helicity of gravitation

Bas Edixhoven, Pierre Parent

We give regular models for modular curves associated with (normalizer of) split and non-split Cartan subgroups of ${\mathrm{GL}}_2 ({\mathbb F}_p )$ (for $p$ any prime, $p\ge 5$). We then compute the group of connected components of the fiber at $p$ of the N\'eron model of their Jacobians.

Viacheslav Borovitskiy, Mohammad Reza Karimi, Vignesh Ram Somnath, Andreas Krause

We propose a principled way to define Gaussian process priors on various sets of unweighted graphs: directed or undirected, with or without loops. We endow each of these sets with a geometric structure, inducing the notions of closeness and symmetries, by turning them into a vertex set of an appropriate metagraph. Building on this, we describe the class of p

Huangjun Zhu, Zihao Li, Masahito Hayashi

We derive simple but nearly tight upper and lower bounds for the binomial lower tail probability (with straightforward generalization to the upper tail probability) that apply to the whole parameter regime. These bounds are easy to compute and are tight within a constant factor of $89/44$. Moreover, they are asymptotically tight in the regimes of large devia

Alastair A. Abbott, Mehdi Mhalla, Pierre Pocreau

We investigate what quantum advantages can be obtained in multipartite non-cooperative games by studying how different types of quantum resources can lead to new Nash equilibria and improve social welfare -- a measure of the quality of an equilibrium. Two different quantum settings are analysed: a first, in which players are given direct access to an entangl

V. Nesrstová, I. Wilms, J. Palarea-Albaladejo, P. Filzmoser

High-dimensional compositional data are commonplace in the modern omics sciences amongst others. Analysis of compositional data requires a proper choice of orthonormal coordinate representation as their relative nature is not compatible with the direct use of standard statistical methods. Principal balances, a specific class of log-ratio coordinates, are wel

Orr Rapoport, Moshe Goldstein

The bulk-edge correspondence (BEC) is the hallmark of topological systems. In continuous (nonlattice) Hermitian systems with an unbounded wave vector, it was recently shown that the BEC of Chern insulators is modified. How would it be further affected in non-Hermitian systems, experiencing loss and/or gain? In this work, we take the first step in this direct

Francois Chapeau-Blondeau

A switched quantum channel with indefinite causal order is studied for the fundamental metrological task of phase estimation on a qubit unitary operator affected by quantum thermal noise. Specific capabilities are reported in the switched channel with indefinite order, not accessible with conventional estimation approaches with definite order. Phase estimati

Pengcheng Lu, Yi Qiao, Junpeng Cao, Wen-Li Yang

We study the exact physical quantities of a competing spin chain which contains many interesting and meaningful couplings including the nearest neighbor, next nearest neighbor, chiral three spins, Dzyloshinsky-Moriya interactions and unparallel boundary magnetic fields in the thermodynamic limit. We obtain the density of zero roots, surface energies and elem

Mauricio Elizalde, Carlos Escudero, Tomoyuki Ichiba

We study the maximization of the logarithmic utility for an insider with different anticipating techniques. Our aim is to compare the utilization of Russo-Vallois forward and Skorokhod integrals in this context. Theoretical analysis and illustrative numerical examples showcase that the Skorokhod insider outperforms the forward insider. This remarkable observ

Saurabh Sharma, Andrea Richichi, Devendra K. Ojha, Brajesh Kumar

TIRCAM2 is the facility near-infrared Imager at the Devasthal 3.6-m telescope in northern India, equipped with an Aladdin III InSb array detector. We have pioneered the use of TIRCAM2 for very fast photometry, with the aim of recording Lunar Occultations (LO). This mode is now operational and publicly offered. In this paper we describe the relevant instrumen

Rahul Jain, Georgios Piliouras, Ryann Sim

Recent advances in quantum computing and in particular, the introduction of quantum GANs, have led to increased interest in quantum zero-sum game theory, extending the scope of learning algorithms for classical games into the quantum realm. In this paper, we focus on learning in quantum zero-sum games under Matrix Multiplicative Weights Update (a generalizat

Petr Blaschke

We are going to study properties of "hypergeometrization" -- an operator which act on analytic functions near the origin by inserting two Pochhammer symbols into their Taylor series. In essence, this operator maps elementary function into hypergeometric. The main goal is to produce number of "change of variable" formulas for this operator which, in turn, can

Xiaokun Zhai, Xuekai Ma, Ying Gao, Chunzi Xing

Manipulating bosonic condensates with electric fields is very challenging as the electric fields do not directly interact with the neutral particles of the condensate. Here we demonstrate a simple electric method to tune the vorticity of exciton polariton condensates in a strong coupling liquid crystal (LC) microcavity with CsPbBr$_3$ microplates as active m

Marco Barbisan, R. Agnello, L. Baldini, G. Casati

The Heating Neutral Beam Injectors (HNBs) for ITER will have to deliver 16.7 MW beams of H/D particles at 1 MeV energy. The beams will be produced from H-/D- ions, generated by a radiofrequency plasma source coupled to an ion acceleration system. A prototype of the ITER HNB ion source is being tested in the SPIDER experiment, part of the ITER Neutral Beam Te