August 2022 arXiv papers — page 120

I. G. Marchenko, A. Zhiglo, V. Aksenova, V. Tkachenko

We revisit the problem of diffusion in a driven system consisting of an inertial Brownian particle moving in a symmetric periodic potential and subjected to a symmetric time-periodic force. We reveal parameter domains in which diffusion is normal in the long time limit and exhibits intriguing giant damped quasiperiodic oscillations as a function of the exter

Sunny Pradhan, Andrea Maroncelli, Elisa Ercolessi

We study a duality transformation from the gauge-invariant subspace of a $\mathbb{Z}_N$ lattice gauge theory on a two-leg ladder geometry to an $N$-clock model on a single chain. The main feature of this mapping is the emergence of a longitudinal field in the clock model, whose value depends on the superselection sector of the gauge model, implying that the

Jorge L. Arocha, Javier Bracho, Luis Montejano

The purpose of this paper is to study the reflections of a convex body. In particular, we are interested in orthogonal reflections of its sections that can be extended to reflections of the whole body. For this reason, we need to study the case of a non-spherical ellipsoid, where a surprising structure arises (Section 2). These results allow us to give a new

Chengguang Gan, Tatsunori Mori

Information extraction(IE) has always been one of the essential tasks of NLP. Moreover, one of the most critical application scenarios of information extraction is the information extraction of resumes. Constructed text is obtained by classifying each part of the resume. It is convenient to store these texts for later search and analysis. Furthermore, the co

Keegan Quigley, Miriam Cha, Ruizhi Liao, Geeticka Chauhan

Automated analysis of chest radiography using deep learning has tremendous potential to enhance the clinical diagnosis of diseases in patients. However, deep learning models typically require large amounts of annotated data to achieve high performance -- often an obstacle to medical domain adaptation. In this paper, we build a data-efficient learning framewo

Camila Gonzalez, Karol Gotkowski, Moritz Fuchs, Andreas Bucher

Automatic segmentation of ground glass opacities and consolidations in chest computer tomography (CT) scans can potentially ease the burden of radiologists during times of high resource utilisation. However, deep learning models are not trusted in the clinical routine due to failing silently on out-of-distribution (OOD) data. We propose a lightweight OOD det

Neil R. Sheeley

We regard the Sun-as-a-star magnetic field (i.e. the mean field) as a filter for the spherical harmonic components of the photospheric field, and calculate the transmission coefficients of this filter. The coefficients for each harmonic, $Y_{l}^{m}$, are listed in three tables according to their dependence on $B_{0}$, the observer's latitude in the star's po

Simon L. Cotter

There are many issues that can cause problems when attempting to infer model parameters from data. Data and models are both imperfect, and as such there are multiple scenarios in which standard methods of inference will lead to misleading conclusions; corrupted data, models which are only representative of subsets of the data, or multiple regions in which th

Bo Yang, Jianke Yang

We show that new types of rogue wave patterns exist in integrable systems, and these rogue patterns are described by root structures of Okamoto polynomial hierarchies. These rogue patterns arise when the $\tau$ functions of rogue wave solutions are determinants of Schur polynomials with index jumps of three, and an internal free parameter in these rogue wave

A. Gandy, T. J. Matcham

Harrel's concordance index is a commonly used discrimination metric for survival models, particularly for models where the relative ordering of the risk of individuals is time-independent, such as the proportional hazards model. There are several suggestions, but no consensus, on how it could be extended to models where relative risk can vary over time, e.g.

Hemar Godinho, Abílio Lemos, Victor Neumann, Filipe Oliveira

In this paper, we define the constant $D(\varphi, p)$, an analogue for the Davenport constant, for sequences on the finite field $\mathbb{F}_p$, defined via quadratic symmetric polynomials. Next, we state a series of results presenting either the exact value of $D(\varphi, p)$, or lower and upper bounds for this constant.

Qingyang Wang, Michael A. Powell, Ali Geisa, Eric Bridgeford

Why do brains have inhibitory connections? Why do deep networks have negative weights? We propose an answer from the perspective of representation capacity. We believe representing functions is the primary role of both (i) the brain in natural intelligence, and (ii) deep networks in artificial intelligence. Our answer to why there are inhibitory/negative wei

Gaia Comaschi, Marcos Jardim

Generalizing the definitions originally presented by Kuznetsov and Faenzi, we study (possibly non locally free) instanton sheaves of arbitrary rank on Fano threefolds. We classify rank 1 instanton sheaves and describe all curves whose structure sheaves are rank 0 instanton sheaves. In addition, we show that every rank 2 instanton sheaf is an elementary trans

Roberto Merlin

A fully resolvable quantum many-body Hamiltonian is introduced that mimics the behavior of the autocatalytic chemical reaction A+B <-> 2B involving two different molecular species, A and B. The model also describes two nonlinearly-coupled modes of an optical cavity. Consistent with the current understanding of the relaxation dynamics of integrable systems in

Sophie Noiret, Jennifer Lumetzberger, Martin Kampel

Discriminatory practices involving AI-driven police work have been the subject of much controversies in the past few years, with algorithms such as COMPAS, PredPol and ShotSpotter being accused of unfairly impacting minority groups. At the same time, the issues of fairness in machine learning, and in particular in computer vision, have been the subject of a

Andrea Loi, Roberto Mossa

We study the K\"ahler-Einstein manifolds which admits a holomorphic isometry into either the generalized Burns-Simanca manifold $(\tilde {\mathbb C}^n, g_S)$ or the Eguchi-Hanson manifold $(\tilde {\mathbb C}^2, g_{EH})$. Moreover, we prove that $(\tilde {\mathbb C}^n, g_S)$ and $(\tilde {\mathbb C}^2, g_{EH})$ are not relatives to any homogeneous bounded do

Jichang Li, Guanbin Li, Feng Liu, Yizhou Yu

Learning with noisy labels (LNL) aims at designing strategies to improve model performance and generalization by mitigating the effects of model overfitting to noisy labels. The key success of LNL lies in identifying as many clean samples as possible from massive noisy data, while rectifying the wrongly assigned noisy labels. Recent advances employ the predi

Camila Gonzalez, Amin Ranem, Ahmed Othman, Anirban Mukhopadhyay

Most continual learning methods are validated in settings where task boundaries are clearly defined and task identity information is available during training and testing. We explore how such methods perform in a task-agnostic setting that more closely resembles dynamic clinical environments with gradual population shifts. We propose ODEx, a holistic solutio

Matheus Capela, Harshit Verma, Fabio Costa, Lucas Chibebe Céleri

Indefinite causal order is a key feature involved in the study of quantum higher order transformations. Recently, intense research has been focused on possible advantages related to the lack of definite causal order of quantum processes. Quite often the quantum switch is claimed to provide advantages in information-theoretic and thermodynamic tasks. We addre

Victoria Hoskins, Simon Pepin Lehalleur

We prove formulae for the motives of stacks of coherent sheaves of fixed rank and degree over a smooth projective curve in Voevodsky's triangulated category of mixed motives with rational coefficients.

Jiayu Huo, Vejay Vakharia, Chengyuan Wu, Ashwini Sharan

Laser interstitial thermal therapy (LITT) is a novel minimally invasive treatment that is used to ablate intracranial structures to treat mesial temporal lobe epilepsy (MTLE). Region of interest (ROI) segmentation before and after LITT would enable automated lesion quantification to objectively assess treatment efficacy. Deep learning techniques, such as con

Apatsara Sareeto, Jörg Koppitz

The monoid of all partial injections on a finite set (the symmetric inverse semigroup) is of particular interest because of the well-known Wagner-Preston Theorem. In this article, we step forward the study of a submonoid of the symmetric inverse semigroup. We explore the monoid of all order-, fence-, and parity-preserving transformations on an $n$-element ch

Miguel Escudero, Alejandro Ibarra, Victor Maura

Using a new sample of extremely metal poor systems, the EMPRESS survey has recently reported a primordial helium abundance that is $3\sigma$ smaller than the prediction from the standard big bang nucleosynthesis (BBN) scenario. This measurement could be interpreted as a hint for a primordial lepton asymmetry in the electron neutrino flavor. Motivated by the

S. Paron, D. Mast, C. Fariña, M. B. Areal

In addition to the large surveys and catalogs of massive young stellar objects and outflows, dedicated studies of particular sources, in which high-angular observations (mainly at near-IR and mm) are analyzed in depth, are needed to shed light on the processes involved in the formation of massive stars. The galactic source G079.1272+02.2782 (G79), a MYSO at

Francisco Correa, Andreas Fring, Takanobu Taira

We construct and analyse the moduli space (collective coordinates) for a classical field theory in 1 + 1 dimensions that possesses complex stable multi-soliton solutions with real energies when PT-regularized. For the integrable Bullough-Dodd model we show, by comparing with the exact solutions, that a one-dimensional moduli space captures well the main feat

Hebatalla Elnaggar, Abhishek Nag, Maurits W. Haverkort, Ke-jin Zhou

Conventional wisdom suggests that one photon that carries one unit of angular momentum can change the spin angular momentum of a magnetic system with one unit (delta Ms = +-1) at most. This would imply that a two-photon scattering process can manipulate the spin angular momentum of the magnetic system with a maximum of two units. Here we examine the fundamen

Xiaoyu Shen, Svitlana Vakulenko, Marco del Tredici, Gianni Barlacchi

Dense retrieval (DR) approaches based on powerful pre-trained language models (PLMs) achieved significant advances and have become a key component for modern open-domain question-answering systems. However, they require large amounts of manual annotations to perform competitively, which is infeasible to scale. To address this, a growing body of research work

Vinod Kumar Chauhan, Anshul Thakur, Odhran O'Donoghue, David A. Clifton

In electronic health records (EHRs), irregular time-series (ITS) occur naturally due to patient health dynamics, reflected by irregular hospital visits, diseases/conditions and the necessity to measure different vitals signs at each visit etc. ITS present challenges in training machine learning algorithms which mostly are built on assumption of coherent fixe

C. P. Mavroeidis, G. A. Athanassoulis

Hamiltonian variational principles provided, since 60s, the means of developing very successful wave theories for nonlinear free-surface flows, under the assumption of irrotationality. This success, in conjunction with the recognition that almost all flows in the sea are not irrotational, raises the question of extending Hamilton Principle to rotational free

Lucas Dixon

We considers how a particular kind of graph corresponds to multiplicative intuitionistic linear logic formula. The main feature of the graphical notation is that it absorbs certain symmetries between conjunction and implication. We look at the basic definitions and present details of an implementation in the functional programming language Standard ML. This

Eleonora Alfinito, Maura Cesaria, Matteo Beccaria

We propose a model for bacterial Quorum Sensing based on an auxiliary electrostatic-like interac-tion originating from a fictitious electrical charge that represents bacteria activity. A cooperative mechanism for charge/activity exchange is introduced to implement chemotaxis and replication. The bacteria system is thus represented by means of a complex resis

Sebastian Werner, Trever Schirmer

The increasing use of hardware processing accelerators tailored for specific applications, such as the Vision Processing Unit (VPU) for image recognition, further increases developers' configuration, development, and management overhead. Developers have successfully used fully automated elastic cloud services such as serverless computing to counter these add

Ben Lang, Grace F. Morley, Andrew D. Armour

A Josephson junction laser is realised when a microwave cavity is driven by a voltage-biased Josephson junction. Through the ac Josephson effect, a dc voltage generates a periodic drive that acts on the cavity and generates interactions between its modes. A sufficiently strong drive enables processes that down-convert a drive resonant with a high harmonic in

Azzedine Abdedou, Azzeddine Soulaïmani

A non-intrusive reduced order model based on convolutional autoencoders (NIROM-CAEs) is proposed as a data-driven tool to build an efficient nonlinear reduced-order model for stochastic spatio-temporal large-scale physical problems. The method uses two 1d-convolutional autoencoders (CAEs) to reduce the spatial and temporal dimensions from a set of high-fidel

Shunyue Yuan, Yueqing Chang, Lucas K. Wagner

State-of-the-art many-body wave function techniques rely on heuristics to achieve high accuracy at an attainable cost to solve the many-body Schr\"odinger equation. By far the most common property used to assess accuracy has been the total energy; however, total energies do not give a complete picture of electron correlation. In this work, the authors assess

Kurt Shuster, Jing Xu, Mojtaba Komeili, Da Ju

We present BlenderBot 3, a 175B parameter dialogue model capable of open-domain conversation with access to the internet and a long-term memory, and having been trained on a large number of user defined tasks. We release both the model weights and code, and have also deployed the model on a public web page to interact with organic users. This technical repor

Hillel Sanhedrai, Shlomo Havlin

Dynamical processes on complex networks, ranging from biological, technological and social systems, show phase transitions between distinct global states of the system. Often, such transitions rely upon the interplay between the structure and dynamics that takes place on it, such that weak connectivity, either sparse network or frail interactions, might lead

Xiao-Yun Wang, Fancong Zeng, Quanjin Wang

Inspired by the recent near-threshold $J/\psi$ photoproduction measurements, we discuss gluon gravitational form factors (GFFs) and internal properties of the proton. This work presents a complete analysis of the proton gluon GFFs connecting the gluon part of the energy-momentum tensor and the heavy quarkonium photoproduction. In particular, a global fitting

Sujay Bhatt, Guanhua Fang, Ping Li, Gennady Samorodnitsky

In this paper, we provide an extension of confidence sequences for settings where the variance of the data-generating distribution does not exist or is infinite. Confidence sequences furnish confidence intervals that are valid at arbitrary data-dependent stopping times, naturally having a wide range of applications. We first establish a lower bound for the w

G. Grätzer

In a recent paper, G. Cz\'edli and E.\,T. Schmidt present a structure theorem for planar semimodular lattices. In this note, we present an alternative proof.

Raphael Cervantes, Jose Aumentado, Caterina Braggio, Bianca Giaccone

Wavelike, bosonic dark matter candidates like axions and dark photons can be detected using microwave cavities known as haloscopes. Traditionally, haloscopes consist of tunable copper cavities operating in the TM$_{010}$ mode, but ohmic losses have limited their performance. In contrast, superconducting radio frequency (SRF) cavities can achieve quality fact

Penelope K. Jones, Kara D. Fong, Kristin A. Persson, Alpha A. Lee

Ion transport in concentrated electrolytes plays a fundamental role in electrochemical systems such as lithium ion batteries. Nonetheless, the mechanism of transport amid strong ion-ion interactions remains enigmatic. A key question is whether the dynamics of ion transport can be predicted by the local static structure alone, and if so what are the key struc

A. D'Aì, E. Amato, A. Burtovoi, A. A. Compagnino

The ASTRI (Astrofisica con Specchi a Tecnologia Replicante Italiana) Mini-Array will be composed of nine imaging atmospheric Cherenkov telescopes at the Observatorio del Teide site. The array will be best suited for astrophysical observations in the 0.3-200 TeV range with an angular resolution of few arc-minutes and an energy resolution of 10-15\%. A core-sc

Didier Bresch, Rupert Klein, Xin Liu

This work is devoted to investigating a compressible fluid system with low stratification, which is driven by fast acoustic waves and internal waves. The approximation using a soundproof model is justified. More precisely, the soundproof model captures the dynamics of both the non-oscillating mean flows and the oscillating internal waves, while filters out t

Jiahao Huang, Sijie Chen, Min Zhuang, Chaohong Lee

Atomic spectroscopy, an essential tool for frequency estimation, is widely used in quantum sensing. Atom-atom interaction can be used to generate entanglement for achieving quantum enhanced sensing. However, atom-atom interaction always induces collision shift, which brings systematic error in determining the resonance frequency. Contradiction between utiliz

Timothy T. K. Chan, Chong Shen Ng, Dominik Krug

Bubble-particle collisions in turbulence are central to a variety of processes such as froth flotation. Despite their importance, details of the collision process have not received much attention yet. This is compounded by the sometimes counter-intuitive behaviour of bubbles and particles in turbulence, as exemplified by the fact that they segregate in space

S. Vercellone, C. Bigongiari, A. Burtovoi, M. Cardillo

The ASTRI (Astrofisica con Specchi a Tecnologia Replicante Italiana) Project led by the Italian National Institute for Astrophysics (INAF) is developing and will deploy at the Observatorio del Teide a mini-array (ASTRI Mini-Array) composed of nine telescopes similar to the small-size dual-mirror Schwarzschild-Couder telescope (ASTRI-Horn) currently operating

F. G. Saturni, C. H. E. Arcaro, B. Balmaverde, J. Becerra González

The ASTRI Mini-Array is a next-generation system of nine imaging atmospheric Cherenkov telescopes that is going to be built at the Observatorio del Teide site. After a first phase, in which the instrument will be operated as an experiment prioritizing a schedule of primary science cases, an observatory phase is foreseen in which other significant targets wil

Aditeya Pandey, Arjun Srinivasan, Vidya Setlur

Despite the ever-growing popularity of dashboards across a wide range of domains, their authoring still remains a tedious and complex process. Current tools offer considerable support for creating individual visualizations but provide limited support for discovering groups of visualizations that can be collectively useful for composing analytic dashboards. T

Karsten Held

This Chapter of the J\"ulich Summer School 2022 provides for a first reading on diagrammatic extensions of dynamical-mean-field theory and their application to spin fluctuations, pseudogap physics and supercondcutivtiy. The contents is as follows: 1 Introduction 2 Dynamical vertex approximation 3 Ladder dynamical vertex approximation 4 Hubbard model, cuprate

Andrea Richaud, Pietro Massignan, Vittorio Penna, Alexander L. Fetter

We study the motion of a superfluid vortex in condensates having different background density profiles, ranging from parabolic to uniform. The resulting effective point-vortex model for a generic power-law potential $\propto r^k$ can be experimentally realized with recent advances in optical-trapping techniques. Our analysis encompasses both empty-core and f

A. Y. Shaikh

In this study, cosmological models with perfect fluid and a gravitational framework f(Q) will be examined. In this modified theory of gravity, the gravitational force has the form f(Q), where Q stands for the non-metricity scalar. I create two bouncing cosmological models, one in which the Lagrangian f(Q) is assumed to have a linear dependence on Q and the o

M. V. S. Saketh, Justin Vines

We study the process, within classical general relativity, in which an incident gravitational plane wave, of weak amplitude and long wavelength, scatters off a massive spinning compact object, such as a black hole or neutron star. The amplitude of the asymptotic scattered wave, considered here at linear order in Newton's constant $G$ while at higher orders i

Thibault Maho, Teddy Furon, Erwan Le Merrer

Recent advances in the fingerprinting of deep neural networks detect instances of models, placed in a black-box interaction scheme. Inputs used by the fingerprinting protocols are specifically crafted for each precise model to be checked for. While efficient in such a scenario, this nevertheless results in a lack of guarantee after a mere modification (like

Światosław R. Gal, Jarek Kędra

We introduce a refinement of bounded cohomology and prove that the suitable comparison homomorphisms vanish for an amenable group. We investigate in this context Thompson's group F and provide further evidence towards its amenability. We provide a source of nontrivial 1-bounded classes and show that the space of 1-bounded classes in degree 2 is huge.

Xue Hu, Xinghui Li, Benjamin Busam, Yiren Zhou

For visual manipulation tasks, we aim to represent image content with semantically meaningful features. However, learning implicit representations from images often lacks interpretability, especially when attributes are intertwined. We focus on the challenging task of extracting disentangled 3D attributes only from 2D image data. Specifically, we focus on hu

L. E. Pirogov

Using the APEX-12m telescope, continuum maps at 350~$\mu$m of eight gas-dust clouds from the southern hemisphere are obtained. Clouds are associated with the regions of massive star and star cluster formation and have dense cores. Core sizes estimated at the half maximum level are $\sim 0.1-0.2$~pc, core masses and mean gas densities lie in the ranges: $\sim

Zhenyu Zhang, Rui Ma, Jifeng Hu, Qian Wang

Machine learning is a novel and powerful technology and has been widely used in various science topics. We demonstrate a machine-learning based approach built by a set of general metrics and rules inspired by physics. Taking advantages of physical constraints, such as dimension identity, symmetry and generalization, we succeed to rediscover the GellMann Okub

Lucio Fiorin

In this memorie de fin d'etudes, we review some techniques to estimate historical volatility and to price Variance Swaps

Dragi Kocev, Nikola Simidjievski, Ana Kostovska, Ivica Dimitrovski

The volume contains selected contributions from the Machine Learning Challenge "Discover the Mysteries of the Maya", presented at the Discovery Challenge Track of The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2021). Remote sensing has greatly accelerated traditional archaeological lands

A Kishore Kumar, Shefali Waldekar, Md Sahidullah, Goutam Saha

With the rise in multimedia content over the years, more variety is observed in the recording environments of audio. An audio processing system might benefit when it has a module to identify the acoustic domain at its front-end. In this paper, we demonstrate the idea of \emph{acoustic domain identification} (ADI) for \emph{speaker diarization}. For this, we

Jan Nikolas Morshuis, Sergios Gatidis, Matthias Hein, Christian F. Baumgartner

Deep Learning (DL) methods have shown promising results for solving ill-posed inverse problems such as MR image reconstruction from undersampled $k$-space data. However, these approaches currently have no guarantees for reconstruction quality and the reliability of such algorithms is only poorly understood. Adversarial attacks offer a valuable tool to unders

Patrick Reiser, Marlen Neubert, André Eberhard, Luca Torresi

Machine learning plays an increasingly important role in many areas of chemistry and materials science, e.g. to predict materials properties, to accelerate simulations, to design new materials, and to predict synthesis routes of new materials. Graph neural networks (GNNs) are one of the fastest growing classes of machine learning models. They are of particul

Bernd Prach, Christoph H. Lampert

It is a highly desirable property for deep networks to be robust against small input changes. One popular way to achieve this property is by designing networks with a small Lipschitz constant. In this work, we propose a new technique for constructing such Lipschitz networks that has a number of desirable properties: it can be applied to any linear network la

Chiara Fort, Michele Modugno

We present a general discussion of the dipole modes of a heteronuclear bosonic mixture in a harmonic trap by comparing the prediction of the sum-rule approach with full Gross-Pitaevskii (GP) calculations. Yet in the range of interaction in which the mixture is miscible and stable at the mean field level, $g_{12}^2<g_{11}g_{22}$, we find that there are regime

Haim Cohen, Yinon Nachshon, Paz M. Naim, Jürgen Jost

Centrality, in some sense, captures the extent to which a vertex controls the flow of information in a network. Here, we propose Local Detour Centrality as a novel centrality-based betweenness measure that captures the extent to which a vertex shortens paths between neighboring vertices as compared to alternative paths. After presenting our measure, we demon

Parker Trostle, Joseph Guinness, Brian J. Reich

The dynamics that govern disease spread are hard to model because infections are functions of both the underlying pathogen as well as human or animal behavior. This challenge is increased when modeling how diseases spread between different spatial locations. Many proposed spatial epidemiological models require trade-offs to fit, either by abstracting away th

Roman Kossak

In September of 1959, at the conference on Infinitistic Methods in Warsaw, Ernst Specker presented a joint paper with Robert MacDowell in which the authors proved that every model of Peano Arithmetic has an elementary extension such that all new elements are larger than all elements of the model. Until now, the theorem has been a constant source of new resul

Elisa Perrone, Edwin R. van den Heuvel, Zhuozhao Zhan

In this paper, we extend the work of Pimentel et al. (2015) and propose an adjusted estimator of Kendall's $\tau$ for bivariate zero-inflated count data. We provide achievable lower and upper bounds of our proposed estimator and show its relationship with current literature. In addition, we also suggest an estimator of the achievable bounds, thereby helping

Abraham Lozada, S. Tabban

In this work, we derive from first principles the relativistic wave equation of massless particles of arbitrary helicity. We start from unitary projective irreducible representations of the restricted Poincar\'e group. We define a weaker notion of localization and find, in particular, a position operator for any massless particle of arbitrary helicity. There

Arturo de Giorgi, Stefan Vogl

We study the freeze-in of gravitationally interacting dark matter in extra dimensions. Focusing on a minimal dark matter candidate that only interacts with the SM via gravity in a five-dimensional model we find that a large range of dark matter and Kaluza-Klein graviton masses can lead to the observed relic density. The preferred values of the masses and the

Tristan Bompard, Lu Liu, Ludovic Patey

In this article, we give two proofs of Carlson's theorem for located words in~$\mathsf{ACA}^+_0$. The first proof is purely combinatorial, in the style of Towsner's proof of Hindman's theorem. The second uses topological dynamics to show that an iterated version of Hindman's theorem for bounded sums implies Carlson's theorem for located words.

Daniele Manuzzi

This proceeding reports a selection of recent experimental results concerning $C\!P$ violation in the sectors of $B^0$ and $B^\pm$ mesons. They were published within the last two years by the Belle, Belle II and LHCb collaborations. The first set of measurements is related to the determination of the angles of the Unitarity Triangle. The second is connected

S. Dzhenzher, A. Skopenkov

The classical Heawood inequality states that if the complete graph $K_n$ on $n$ vertices is embeddable in the sphere with $g$ handles, then $g \ge\dfrac{(n-3)(n-4)}{12}$. A higher-dimensional analogue of the Heawood inequality is the K\"uhnel conjecture. In a simplified form it states that for every integer $k>0$ there is $c_k>0$ such that if the union of $k

Jorge A. Vila

The Levinthal paradox exposes many critical questions on the protein folding problem, among which we could point out why proteins can reach their native state in a biologically reasonable time. A proper answer to this question is of foremost importance for evolutive biology since it enables us to understand life as we know it. Preliminary results, based on t

Maximilian J. Grill, Wolfgang A. Wall, Christoph Meier

This article proposes a novel computational modeling approach for short-ranged molecular interactions between curved slender fibers undergoing large 3D deformations, and gives a detailed overview how it fits into the framework of existing fiber or beam interaction models, either considering microscale molecular or macroscale contact effects. The direct evalu

Rajesh Tripathi, D. T. Adroja, C. Ritter, Shivani Sharma

We present the results of muon spin relaxation ($\mu$SR) and neutron scattering on the Ce-based quasikagome lattice CeRh$_{1-x}$Pd$_{x}$Sn ($x=0.1$ to 0.75). Our ZF-$\mu$SR results reveal the absence of static long-range magnetic order down to 0.05~K in $x = 0.1$ single crystals. The weak temperature-dependent plateaus of the dynamic spin fluctuations below

Simon Mendez, Willy Garcia, Alexandre Nicolas

Short-range exposure to airborne virus-laden respiratory droplets is now acknowledged as an effective transmission route of respiratory diseases, as exemplified by COVID-19. In order to assess the risks associated with this pathway in daily-life settings involving tens to hundreds of individuals, the chasm needs to be bridged between fluid dynamical simulati

Stefanos Sagkriotis, Dimitrios Pezaros

The programmability of modern network devices has led to innovative research in the area of in-network computing, i.e., offloading certain computations to the programmable data plane. Key-value stores, which offer coordination services for many large-scale data centres, benefited from this technological advancement. Previous research reduced the response lat

Sumit Kumar, Sebastian Spence, Simon Perrett, Zaynab Tahir

We have developed a novel architecture for room temperature microwave cavity optomechanics, which is based on the coupling of a 3D microwave reentrant cavity to a compliant membrane. Devices parameters have enabled resolving the thermomechanical motion of the membrane, and observing optomechanically induced transparency/absorption in the linear regime, for t

Amin Gasmi

The connection between the design and delivery of health care services using information technology is known as health informatics. It involves data usage, validation, and transfer of an integrated medical analysis using neural networks of multi-layer deep learning techniques to analyze complex data. For instance, Google incorporated ''DeepMind'' health mobi

Michael Gröger, Vadim Borisov, Gjergji Kasneci

One of the core challenges facing the medical image computing community is fast and efficient data sample labeling. Obtaining fine-grained labels for segmentation is particularly demanding since it is expensive, time-consuming, and requires sophisticated tools. On the contrary, applying bounding boxes is fast and takes significantly less time than fine-grain

Xingyu Zhang, Xiao-Ming Lu, Jing Liu, Wenkui Ding

In the adiabatic perturbation theory, Berry curvature is related to the generalized force, and the quantum metric tensor is linked with energy fluctuation. While the former is tested with numerous numerical results and experimental realizations, the latter is less considered. Quantum Fisher information, key to quantum precision measurement, is four times qua

Amin Gasmi

Globally, the number of obese patients has doubled due to sedentary lifestyles and improper dieting. The tremendous increase altered human genetics, and health. According to the world health organization, Life expectancy dropped from 80 to 75 years, as obese people struggle with different chronic diseases. This report will address the problems of obesity in

Sai Xu, Yanan Du, Jiliang Zhang, Jie Zhang

This letter proposes to employ intelligent reflecting surface (IRS) as an information media to display a microwave quick response (QR) code for Internet-of-Things applications. To be specific, an IRS is used to form a dynamic bitmap image thanks to its tunable elements. With a QR code shown on the IRS, the transmitting and receiving antenna arrays are jointl

Jürgen Dobaj, Andreas Riel, Georg Macher, Markus Egretzberger

Industrial Product-Service Systems (IPSS) are increasingly dominant in several sectors. Predominant value-adding services provided for industrial assets such as production systems, electric power plants, and car fleets are remote asset maintenance, monitoring, control, and reconfiguration. IPSS designers lack methods and tools supporting them in systematical

Mikhail Evtikhiev, Egor Bogomolov, Yaroslav Sokolov, Timofey Bryksin

In recent years, researchers have created and introduced a significant number of various code generation models. As human evaluation of every new model version is unfeasible, the community adopted automatic evaluation metrics such as BLEU to approximate the results of human judgement. These metrics originate from the machine translation domain and it is uncl

Taewon Yuk, Sang-Jin Sin

We reconsider the fermion spectral function in the presence of the Cooper pair condensation and identified the interaction type of complex scalar and fermion, which gives consistent results with the expected s-wave superconductor for the first time. We derive the matrix Riccati equation, which allows the precise calculation of the fermion spectral function.

Lucas Tonetto, Omar Benhar

A quantitative description of the properties of hot nuclear matter will be needed for the interpretation of the available and forthcoming astrophysical data, providing information on the post merger phase of a neutron star coalescence. We have employed a recently developed theoretical model, based on a phenomenological nuclear Hamiltonian including two- and

Omprakash Atale

Recently, it has been shown by Ighachanea and Akkouchia \cite{0.1} that using binomial coefficients, one can derive some new refinements of Holder's inequalities. This inequalities then can be applied to a wide class of special functions such as the Nielsen's beta function and some extended gamma functions. In this paper, we have derived some generalizations

Richard Marcus, Niklas Knoop, Bernhard Egger, Marc Stamminger

Virtual testing is a crucial task to ensure safety in autonomous driving, and sensor simulation is an important task in this domain. Most current LiDAR simulations are very simplistic and are mainly used to perform initial tests, while the majority of insights are gathered on the road. In this paper, we propose a lightweight approach for more realistic LiDAR

C. Schürmann, N. Langer, X. Xu, C. Wang

In order to predict the spins of stellar remnants we need to understand the evolution of the internal rotation of stars, and to identify at which stage the rotation of the contracting cores of evolved stars decouples from their expanding envelopes. The donor stars of mass transferring binaries lose almost their entire envelope and may thus offer a direct vie

Xinqi Bao, Yujia Xu, Hak-Keung Lam, Mohamed Trabelsi

Time-Frequency Distributions (TFDs) support the heart sound characterisation and classification in early cardiac screening. However, despite the frequent use of TFDs in signal analysis, no study comprehensively compared their performances on deep learning for automatic diagnosis. Furthermore, the combination of signal processing methods as inputs for Convolu

Alexander Armbruster, Lars Rohwedder, Andreas Wiese

An important objective in scheduling literature is to minimize the sum of weighted flow times. We are given a set of jobs where each job is characterized by a release time, a processing time, and a weight. Our goal is to find a preemptive schedule on a single machine that minimizes the sum of the weighted flow times of the jobs, where the flow time of a job

S. D. Bykov, M. R. Gilfanov, S. S. Tsygankov, E. V. Filippova

We report the discovery of the bright reflected emission component in the super-Eddington state of the ULX pulsar Swift J0243.6+6124, based on the NuSTAR observations of the source during its 2017 outburst. The flux of the reflected emission is weakly variable over the pulsar phase while the direct emission shows significantly larger pulsation amplitude. We

Samuel Burer, Kyungchan Park

We study semidefinite programming (SDP) relaxations for the NP-hard problem of globally optimizing a quadratic function over the Stiefel manifold. We introduce a strengthened relaxation based on two recent ideas in the literature: (i) a tailored SDP for objectives with a block-diagonal Hessian; (ii) and the use of the Kronecker matrix product to construct SD

Aman Sangal

We measure the branching fraction for the Singly Cabibbo-suppressed decay $D^0\rightarrow K^0_S\,K^0_S\,\pi^+\pi^-$, and we search for $CP$ violation via a measurement of the $CP$ asymmetry $A^{}_{CP}$ and also the $T$-odd triple-product asymmetry $a_{CP}^{T}$. The later two measurements are complementary. We use 922~fb$^{-1}$ of data recorded by the Belle e

Kalpana Mahalingam, Anuran Maity

In this work, we explore the concept of Watson-Crick conjugates, also known as $\theta$-conjugates (where $\theta$ is an antimorphic involution), of words and languages. This concept extends the classical idea of conjugates by incorporating the Watson-Crick complementarity of DNA sequences. Our investigation initially focuses on the properties of $\theta$-co

ATLAS Collaboration

Searches for the exclusive decays of Higgs and $Z$ bosons into a vector quarkonium state and a photon are performed in the $\mu^+\mu^- \gamma$ final state with a proton$-$proton collision data sample corresponding to an integrated luminosity of $139$ fb$^{-1}$ collected at $\sqrt{s}=13$ TeV with the ATLAS detector at the CERN Large Hadron Collider. The obser

Johan Kwisthout

In decision support systems the motivation and justification of the system's diagnosis or classification is crucial for the acceptance of the system by the human user. In Bayesian networks a diagnosis or classification is typically formalized as the computation of the most probable joint value assignment to the hypothesis variables, given the observed values