October 2022 arXiv papers — page 39

Sławomir Kapka, Jakub Tkaczuk

In this article, we describe Conditioned Localizer and Classifier (CoLoC) which is a novel solution for Sound Event Localization and Detection (SELD). The solution constitutes of two stages: the localization is done first and is followed by classification conditioned by the output of the localizer. In order to resolve the problem of the unknown number of sou

Omer Beg, Muhammad Nasir Zafar, Waleed Anjum

Text generation tasks have gotten the attention of researchers in the last few years because of their applications on a large scale.In the past, many researchers focused on task-based text generations.Our research focuses on text generation based on the ideology and style of a specific author, and text generation on a topic that was not written by the same a

Luo Luo, Yunyan Bai, Lesi Chen, Yuxing Liu

We study the decentralized optimization problem $\min_{{\bf x}\in{\mathbb R}^d} f({\bf x})\triangleq \frac{1}{m}\sum_{i=1}^m f_i({\bf x})$, where the local function on the $i$-th agent has the form of $f_i({\bf x})\triangleq \frac{1}{n}\sum_{j=1}^n f_{i,j}({\bf x})$ and every individual $f_{i,j}$ is smooth but possibly nonconvex. We propose a stochastic algo

A. G. Shamov, O. L. Rezanova

We have reconsidered the results on the masses of the narrow bottomonium states $\Upsilon(1S)$--$\Upsilon(3S)$ obtained in 1982--1986 at CESR, DORIS and VEPP-4 colliders in order to fix shortcomings of the mass determination procedures. For experiments at CESR and DORIS this includes the incorrect accounting of the radiative corrections and usage of the elec

Merab Gogberashvili

Usually, it is supposed that irreversibility of time appears only in macrophysics. Here, we attempt to introduce the microphysical arrow of time assuming that at a fundamental level nature could be non-associative. Obtaining numerical results of a measurement, which requires at least three ingredients: object, device and observer, in the non-associative case

Mehdi Sefidgar Dilmaghani, Waseem Shariff, Cian Ryan, Joe Lemley

Event cameras also known as neuromorphic sensors are relatively a new technology with some privilege over the RGB cameras. The most important one is their difference in capturing the light changes in the environment, each pixel changes independently from the others when it captures a change in the environment light. To increase the users degree of freedom in

M. M. Castro, F. A. Grünbaum

We exhibit three examples showing that the "time-and-band limiting" commutative property found and exploited by D. Slepian, H. Landau and H. Pollak at Bell Labs in the 1960's, and independently by M. Mehta and later by C. Tracy and H. Widom in Random matrix theory, holds for exceptional orthogonal polynomials. The property in question is the existence of loc

Md. Haidar Sharif, Lei Jiao, Christian W. Omlin

Crowd anomaly detection is one of the most popular topics in computer vision in the context of smart cities. A plethora of deep learning methods have been proposed that generally outperform other machine learning solutions. Our review primarily discusses algorithms that were published in mainstream conferences and journals between 2020 and 2022. We present d

Leszek Pysiak, Wiesław Sasin, Michael Heller, Tomasz Miller

According to the basic idea of category theory, any Einstein algebra, essentially an algebraic formulation of general relativity, can be considered from the point of view of any object of the category of smooth algebras; such an object is then called a stage. If we contemplate a given Einstein algebra from the point of view of the stage, which we choose to b

Alexey K. Mazur, Eugene Gladyshev

In many organisms, homologous (or repetitive) chromosomal regions can associate or/and undergo concerted epigenetic changes in the absence of DNA breakage and recombination. The direct specific pairing of DNA duplexes with similar nucleotide sequences represents an attractive mechanism for recognizing such regions. Whereas the pairing of B-DNA duplexes may i

José Figueroa-O'Farrill

We characterise Lie groups with bi-invariant bargmannian, galilean or carrollian structures. Localising at the identity, we show that Lie algebras with ad-invariant bargmannian, carrollian or galilean structures are actually determined by the same data: a metric Lie algebra with a skew-symmetric derivation. This is the same data defining a one-dimensional do

Pierre Le Jeune, Anissa Mokraoui

Few-Shot Object Detection (FSOD) methods are mainly designed and evaluated on natural image datasets such as Pascal VOC and MS COCO. However, it is not clear whether the best methods for natural images are also the best for aerial images. Furthermore, direct comparison of performance between FSOD methods is difficult due to the wide variety of detection fram

Ole Fredrik Brevig, Andrés Chirre, Joaquim Ortega-Cerdà, Kristian Seip

We study the norm of point evaluation at the origin in the Paley--Wiener space $PW^p$ for $0 < p < \infty$, i. e., we search for the smallest positive constant $C$, called $\mathscr{C}_p$, such that the inequality $|f(0)|^p \leq C \|f\|_p^p$ holds for every $f$ in $PW^p$. We present evidence and prove several results supporting the following monotonicity con

Jan Mees, Rok Simič, Thomas C. O'Connor, Nicholas D. Spencer

Self-mated hydrogel contacts show extremely small friction coefficients at low loads but a distinct velocity dependence. Here we combine mesoscopic simulations and experiments to test the polymer-relaxation hypothesis for this velocity dependence, where a velocity-dependent regime emerges when the perturbation of interfacial polymer chains occurs faster than

Thibault Fredon, Julien Zylberman, Pablo Arnault, Fabrice Debbasch

We present various results on the scheme introduced , which is a quantum spatial-search algorithm on a two-dimensional (2D) square spatial grid, realized with a 2D Dirac discrete-time quantum walk (DQW) coupled to a Coulomb electric field centered on the marked node. In such a walk, the electric term acts as the oracle of the algorithm, and the free walk (i.

M. Kioumarsipour, J. Sadeghi

The imaginary potential and entropic force are two important different mechanisms to characterize the dissociation of heavy quarkonia. In this paper, we calculate these two quantities in strongly coupled theories with anisotropic Lifshitz scaling and hyperscaling violation exponent using holographic methods. We study how the results are affected by the hyper

Justus Mattern, Zhijing Jin, Benjamin Weggenmann, Bernhard Schoelkopf

To protect the privacy of individuals whose data is being shared, it is of high importance to develop methods allowing researchers and companies to release textual data while providing formal privacy guarantees to its originators. In the field of NLP, substantial efforts have been directed at building mechanisms following the framework of local differential

Seyyed Morteza Hashemi, Parvaneh Aliniya, Parvin Razzaghi

Detection of out-of-distribution samples is one of the critical tasks for real-world applications of computer vision. The advancement of deep learning has enabled us to analyze real-world data which contain unexplained samples, accentuating the need to detect out-of-distribution instances more than before. GAN-based approaches have been widely used to addres

G. Trinchero, M. B. Amelchakov, A. G. Bogdanov, A. Chiavassa

In this work, we use muon bundles which are formed in extensive air showers and detected at the ground level as a tool for searching anisotropy of high energy cosmic rays. Such choice is explained by the penetrating ability of muons which allows them to retain the direction of primary particles with a good accuracy. In 2012-2022, we performed long-term muon

Christian Strack, Kelsey L. Pomykala, Heinz-Peter Schlemmer, Jan Egger

With the rise in importance of personalized medicine, we trained personalized neural networks to detect tumor progression in longitudinal datasets. The model was evaluated on two datasets with a total of 64 scans from 32 patients diagnosed with glioblastoma multiforme (GBM). Contrast-enhanced T1w sequences of brain magnetic resonance imaging (MRI) images wer

Shahaf Bassan, Guy Katz

With the rapid growth of machine learning, deep neural networks (DNNs) are now being used in numerous domains. Unfortunately, DNNs are "black-boxes", and cannot be interpreted by humans, which is a substantial concern in safety-critical systems. To mitigate this issue, researchers have begun working on explainable AI (XAI) methods, which can identify a subse

Bernet E. Meijer, Richard J. C. Dixey, Franz Demmel, Robin Perry

High-entropy order-disorder phase transitions can be used for efficient and eco-friendly barocaloric solid-state cooling. Here the barocaloric effect is reported in an archetypal plastic crystal, adamantane. Adamantane has a colossal isothermally reversible entropy change of 106 J K-1 kg-1 . Extremely low hysteresis means that this can be accessed at pressur

Hiroaki Tanaka

Based on the first-order perturbation theory, we show that the wave function of a photoelectron is a wave packet with the same width as the incident light pulse. Photoelectron detection measurements revealed that the widths of signal pulses were much shorter than the light pulse and independent of the origin (photoemission or other noises), which is an exper

Feiyang Wang, Chaoying Yin, Ximing Chang, Der-Horng Lee

Bike-sharing has received considerable practice and research attention over the past decade. As a manpower-driven transportation mode, it seems more sensitive to trip length, since one could take a shared bike to a destinated place where is too far to walk, or choose it for simply replacing walking when going to a nearby place. However, little research has p

M. Kioumarsipour, J. Sadeghi

In this paper, we investigate the heavy quark potential and the jet quenching parameter in a system with Lifshitz and hyperscaling violation exponents, by using the AdS/CFT correspondence. It is shown that the heavy quark potential and the jet quenching parameter are dependent upon the nonrelativistic parameters. We show how the heavy quark potential changes

Riccardo Martini, Gian Paolo Vacca, Omar Zanusso

We discuss the birth of the non-perturbative approach to quantum gravity known as quantum Einstein gravity, in which the gravitational interactions are conjectured to be asymptotically safe. The interactions are assumed to be finite and consistent at high energies thanks to a scale-invariant ultraviolet completion. We present the framework on the basis of pe

Anton Vladyka, Christoph J. Sahle, Johannes Niskanen

We report a statistical analysis of Ge K-edge X-ray emission spectra simulated for amorphous GeO$_2$ at elevated pressures. We find that employing machine learning approaches we can reliably predict the statistical moments of the K$\beta''$ and K$\beta_2$ peaks in the spectrum from the Coulomb matrix descriptor with a training set of $\sim 10^4$ samples. Spe

Sotaro Katayama, Tatsunori Taniai, Kazutoshi Tanaka

Contact-rich manipulation is challenging due to dynamically-changing physical constraints by the contact mode changes undergone during manipulation. This paper proposes a versatile local planning and control framework for contact-rich manipulation that determines the continuous control action under variable contact modes online. We model the physical charact

Balázs R. Sziklai, Balázs Lengyel

Social networks play a fundamental role in the diffusion of innovation through peers' influence on adoption. Thus, network position including a wide range of network centrality measures have been used to describe individuals' affinity to adopt an innovation and their ability to propagate diffusion. Yet, social networks are assortative in terms of susceptibil

Zacharaya Shabka, Michael Enrico, Nick Parsons, Georgios Zervas

Proportional-integral-derivative (PID) control underlies more than $97\%$ of automated industrial processes. Controlling these processes effectively with respect to some specified set of performance goals requires finding an optimal set of PID parameters to moderate the PID loop. Tuning these parameters is a long and exhaustive process. A method (patent pend

Min Xu, Ximiao Zhang, Xiuzhuang Zhou

In this paper, we investigate the problem of prediction confidence in face and kinship verification. Most existing face and kinship verification methods focus on accuracy performance while ignoring confidence estimation for their prediction results. However, confidence estimation is essential for modeling reliability and trustworthiness in such high-risk tas

Jean Rabault, Malte Müller, Joey Voermans, Dmitry Brazhnikov

Variability in sea ice conditions, combined with strong couplings to the atmosphere and the ocean, lead to a broad range of complex sea ice dynamics. More in-situ measurements are needed to better identify the phenomena and mechanisms that govern sea ice growth, drift, and breakup. To this end, we have gathered a dataset of in-situ observations of sea ice dr

Alexander Mock, Sebastian Pütz, Thomas Wiemann, Joachim Hertzberg

Triangle mesh maps are a versatile 3D environment representation for robots to navigate in challenging indoor and outdoor environments exhibiting tunnels, hills and varying slopes. To make use of these mesh maps, methods are needed to accurately localize robots in such maps to perform essential tasks like path planning and navigation. We present Mesh ICP Loc

Vikash Sharma, Divya Sharma, Ranu Bhatt, Pankaj Patro

We report on the thermoelectric properties of nickel doped Ag2-xNixTe (x = 0, 0.015, 0.025 & 0.055, 0.115, 0.155) nanostructures in the temperature (T) range of 5 K to 575 K. The electrical resistivity of Ag2Te nanostructure shows metallic behaviour in 5 K to 300 K initially that evolves into two metal to insulator transitions (MITs) at low and mid-temperatu

Wei Wang

The $k$-Cauchy-Fueter complex in quaternionic analysis is the counterpart of the Dolbeault complex in complex analysis. In this paper, we find the explicit transformation formula of these complexes under ${\rm SL}(n+1,\mathbb{H})$, which acts on $\mathbb{H}^{ n}$ as quaternionic fractional linear transformations. These transformation formulae have several in

Asma Elmaizi, Hasna Nhaila, Elkebir Sarhrouni, Ahmed Hammouch

During the last decade, hyperspectral images have attracted increasing interest from researchers worldwide. They provide more detailed information about an observed area and allow an accurate target detection and precise discrimination of objects compared to classical RGB and multispectral images. Despite the great potentialities of hyperspectral technology,

Hamed Saidaoui, Luis Espath, Rául Tempone

In this study, we propose a new numerical scheme for physics-informed neural networks (PINNs) that enables precise and inexpensive solution for partial differential equations (PDEs) in case of arbitrary geometries while strictly enforcing Dirichlet boundary conditions. The proposed approach combines admissible NURBS parametrizations required to define the ph

D. Sugny

This study shows the unexpected and counter-intuitive possibility of simultaneously orienting a molecule while delocalizing its molecular axis in a plane in field-free conditions. The corresponding quantum states are characterized and different control strategies using shaped THz laser pulses are proposed to reach such states at zero and nonzero temperatures

Andreas Stephan, Vasiliki Kougia, Benjamin Roth

In the weakly supervised learning paradigm, labeling functions automatically assign heuristic, often noisy, labels to data samples. In this work, we provide a method for learning from weak labels by separating two types of complementary information associated with the labeling functions: information related to the target label and information specific to one

Régis de la Bretèche, Gérald Tenenbaum

For integer $n\geqslant 1$ and real $u$, let $\Delta(n,u):=|\{d:d\mid n,\,{\rm e}^u<d\leqslant {\rm e}^{u+1}\}|$. The Erd\H{o}s--Hooley Delta-function is then defined by $\Delta(n):=\max_{u\in{\mathbb R}}\Delta(n,u).$ We improve the current upper bounds for the average and normal orders of this arithmetic function.

Shuyang Wang, Qing Wang, Chao An, Yonghui Zhou

The discovery of multiple charge-density-wave (CDW) orders in superconducting cuprates and Kagome CsV3Sb5 has offered a unique milieu for studying the interplay of CDW and superconductivity and altered our perspective on their nature. Here, we report a high-pressure study of quasi-one-dimensional CDW material CuTe through ultralow-temperature (400 mK) electr

Yanheng Ding, Hua-Yang Wang

We study the existence and nonexistence of normalized solutions $(u_a, \lambda_a)\in H^{1}(\mathbb{R}^N)\times \mathbb{R}$ to the nonlinear Schr\"{o}dinger equation with mixed nonlocal nonlinearities. This study can be viewed as a counterpart of the Brezis-Nirenberg problem in the context of normalized solutions to the nonlocal Schr\"{o}diger equation with a

Sven Wedemeyer, Gregory Fleishman, Jaime de la Cruz Rodriguez, Stanislav Gunar

The Atacama Large Millimeter/submillimeter Array (ALMA) offers new diagnostic possibilities that complement other commonly used diagnostics for the study of our Sun. In particular, ALMA's ability to serve as an essentially linear thermometer of the chromospheric gas at unprecedented spatial resolution at millimetre wavelengths and future polarisation measure

Helge Dietert, Frédéric Hérau, Harsha Hutridurga, Clément Mouhot

We present the quantitative method of the recent work arXiv:2209.09340 in a simple setting, together with a compactness argument that was not included in arXiv:2209.09340 and has interest per se. We are concerned with the exponential stabilization (spectral gap) for linear kinetic equations with degenerate thermalization, i.e. when the collision operator van

Jing Gu, DunKun Yang, Qi Bao

Motivated by Liu's recent work in \cite{Liu2022}. We shall reveal the essential feature of Hahn polynomials by presenting two new $q$-exponential operators. These lead us to use a systematic method to study identities involving Hahn polynomials. As applications, we use the method of $q$-exponential operator to prove the bilinear generating function of Hahn p

Jiyun Guo, Miao Fu, Yuqin Zhang, Haiyan Li

The degree sequence of a graph is the sequence of the degrees of its vertices. If $\pi$ is a degree sequence of a graph $G$, then $G$ is a realization of $\pi$ and $G$ realizes $\pi$. Determining when a sequence of positive integers is realizable as a degree sequence of a simple graph has received much attention. One of the early results, by Erd\"{o}s and Ga

Jinus Bordbar, Mohammadreza Mohammadrezaie, Saman Ardalan, Mohammad Ebrahim Shiri

Online social media is integral to human life, facilitating messaging, information sharing, and confidential communication while preserving privacy. Platforms like Twitter, Instagram, and Facebook exemplify this phenomenon. However, users face challenges due to network anomalies, often stemming from malicious activities such as identity theft for financial g

Fateme Nateghi Haredasht, Celine Vens

Many clinical studies require the follow-up of patients over time. This is challenging: apart from frequently observed drop-out, there are often also organizational and financial challenges, which can lead to reduced data collection and, in turn, can complicate subsequent analyses. In contrast, there is often plenty of baseline data available of patients wit

Hadi Amirpour, Vignesh V Menon, Ekrem Çetinkaya, Adithyan Ilangovan

The growth in video Internet traffic and advancements in video attributes such as framerate, resolution, and bit-depth boost the demand to devise a large-scale, highly efficient video encoding environment. This is even more essential for Dynamic Adaptive Streaming over HTTP (DASH)-based content provisioning as it requires encoding numerous representations of

Huy Hoang Nguyen, Matthew B. Blaschko, Simo Saarakkala, Aleksei Tiulpin

Deep neural networks are often applied to medical images to automate the problem of medical diagnosis. However, a more clinically relevant question that practitioners usually face is how to predict the future trajectory of a disease. Current methods for prognosis or disease trajectory forecasting often require domain knowledge and are complicated to apply. I

Martin Ruskov, Lora Taseva

The development of bilingual dictionaries to medieval translations presents diverse difficulties. These result from two types of philological circumstances: a) the asymmetry between the source language and the target language; and b) the varying available sources of both the original and translated texts. In particular, the full critical edition of Tihova of

Michael Heusener, Joan Porti

The aim of this article is to study the SL(2,C)-character scheme of a finitely generated group. Given a presentation of a finitely generated group $\Gamma$, we give equations defining the coordinate ring of the scheme of SL(2,C)-characters of $\Gamma$ (finitely many equations when $\Gamma$ is finitely presented). We also study the scheme of abelian and nonsi

Yuqing Ren, Yifei Shen, Leyu Zhang, Andreas Toftegaard Kristensen

Owing to its high parallelism, belief propagation (BP) decoding is highly amenable to high-throughput implementations and thus represents a promising solution for meeting the ultra-high peak data rate of future communication systems. However, for polar codes, the error-correcting performance of BP decoding is far inferior to that of the widely used CRC-aided

Jean-Simon Pacaud Lemay

Cartesian differential categories come equipped with a differential operator which formalises the total derivative from multivariable calculus. Cofree Cartesian differential categories always exist over a specified base category, where the general construction is based on Fa\`a di Bruno's formula. A natural question to ask is, when given an arbitrary Cartesi

Andreas Ranftl, Fernando Alonso-Fernandez, Stefan Karlsson, Josef Bigun

The authors present a novel face tracking approach where optical flow information is incorporated into a modified version of the Viola Jones detection algorithm. In the original algorithm, detection is static, as information from previous frames is not considered. In addition, candidate windows have to pass all stages of the classification cascade, otherwise

Beatriz Ribeiro Lopes

A search for central exclusive production of top quark pairs ($\mathrm{t}\bar{\mathrm{t}}$) is presented using collision data collected by CMS and the CMS-TOTEM Precision Proton Spectrometer in 2017. A data-driven method to estimate the background from coincidences of inclusive events and pileup protons is described, as well as the development of a Boosted D

Abdullah Abdulaziz, Simon Peter Mekhail, Yoann Altmann, Miles J. Padgett

Conventional endoscopes comprise a bundle of optical fibers, associating one fiber for each pixel in the image. In principle, this can be reduced to a single multimode optical fiber (MMF), the width of a human hair, with one fiber spatial-mode per image pixel. However, images transmitted through a MMF emerge as unrecognizable speckle patterns due to dispersi

Ayse Pelin Dedeler, Canberk Soytekin

An interactive binary star system simulation was developed to be showcased on an educational platform. The main purpose of the project is to provide insight into the orbital mechanics of such star systems with the help of a three-body simulation. The initial simulation script was written in the Python programming language with the help of the VPython additio

Al-Akhir Nayan, Ahamad Nokib Mozumder, Md. Rakibul Haque, Fahim Hossain Sifat

The growth of abnormal cells in the brain's tissue causes brain tumors. Brain tumors are considered one of the most dangerous disorders in children and adults. It develops quickly, and the patient's survival prospects are slim if not appropriately treated. Proper treatment planning and precise diagnoses are essential to improving a patient's life expectancy.

Debasis Das, Xuanyao Fong

Spintronic artificial spiking neurons are promising due to their ability to closely mimic the leaky integrate-and-fire (LIF) dynamics of the biological LIF spiking neuron. However, the neuron needs to be reset after firing. Few of the spintronic neurons that have been proposed in the literature discuss the reset process in detail. In this article, we discuss

Ahmet Ilker Topuz, Madis Kiisk, Andrea Giammanco

The scattering angle due to the target volume can be split into two interior angles in the tomographic setups based on the muon scattering, and we call this property as the triangular correlation where the sum of these two interior angles is equal to the scattering angle. In this study, we apply this triangular correlation for a multi-block material configur

Sayan Bhattacharya, Silvio Lattanzi, Nikos Parotsidis

We consider the classic facility location problem in fully dynamic data streams, where elements can be both inserted and deleted. In this problem, one is interested in maintaining a stable and high quality solution throughout the data stream while using only little time per update (insertion or deletion). We study the problem and provide the first algorithm

Alexis Teter, Iman Nodozi, Abhishek Halder

We propose a custom learning algorithm for shallow over-parameterized neural networks, i.e., networks with single hidden layer having infinite width. The infinite width of the hidden layer serves as an abstraction for the over-parameterization. Building on the recent mean field interpretations of learning dynamics in shallow neural networks, we realize mean

Zhenyu Zhou, Xiaoping Xu

Using the projective oscillator representation of sl(n+1) and Shen's mixed product for Witt algebras, Zhao and the second author (2011) constructed a new functor from sl(n)-Mod to sl(n+1)-Mod. In this paper, we start from n = 2 and use the functor successively to obtain a full projective oscillator realization of any finite-dimensional irreducible representa

Samuele Silveravalle, Alessandro Zuccotti

Thanks to their interpretation as first order correction of General Relativity at high energies, quadratic theories of gravity gained much attention in recent times. Particular attention has been drawn to the Einstein-Weyl theory, where the addition of the squared Weyl tensor to the action opens the possibility of having non-Schwarzschild black holes in the

M. L. Menezes, A. Samara, L. Galway, A. Sant'anna

One of the challenges in virtual environments is the difficulty users have in interacting with these increasingly complex systems. Ultimately, endowing machines with the ability to perceive users emotions will enable a more intuitive and reliable interaction. Consequently, using the electroencephalogram as a bio-signal sensor, the affective state of a user c

Mohammad Asif, Sudhakar Mishra, Majithia Tejas Vinodbhai, Uma Shanker Tiwary

Emotion recognition using EEG signals is an emerging area of research due to its broad applicability in BCI. Emotional feelings are hard to stimulate in the lab. Emotions do not last long, yet they need enough context to be perceived and felt. However, most EEG-related emotion databases either suffer from emotionally irrelevant details (due to prolonged dura

Paolo Nogara, Giuseppe Sottile, Francesco Russo, Giovanni La Rosa

HERMES Pathfinder (High Energy Rapid Modular Ensemble of Satellites Pathfinder) is a space mission based on a constellation of nano-satellites in a low Earth Orbit, hosting new miniaturized detectors to probe the X-ray temporal emission of bright high-energy transients such as Gamma-Ray Bursts and the electromagnetic counterparts of Gravitational Waves. This

Hayato Oshimo, Shiori Hironaka, Mitsuo Yoshida, Kyoji Umemura

Analyzing following behavior is important in many applications. Following behavior may depend on the main intention of the follower. Users may either follow their friends or they may follow celebrities to know more about them. It is difficult to estimate users' intention from their following relationships. In this paper, we propose an approach to analyze fol

Niek Mulleners, Johan Jeuring, Bastiaan Heeren

We present Scrybe, an example-based synthesis tool for a statically-typed functional programming language, which combines top-down deductive reasoning in the style of $\lambda^2$ with Smyth-style live bidirectional evaluation. During synthesis, example constraints are propagated through sketches to prune and guide the search. This enables Scrybe to make more

Nan Yang, Akram Shafie

Terahertz (THz) communications (THzCom) has experienced a meteoric rise of interest, due to its benefits for ultra-high data rate transmission in the sixth generation (6G) and beyond era. Despite so, the research on exploring the potential of THzCom for other performance targets anticipated by 6G, including massive connectivity and security, is still in its

M. Beccaria, G. P. Korchemsky, A. A. Tseytlin

We apply the localization technique to compute the free energy on four-sphere and the circular BPS Wilson loop in the four-dimensional $\cal N$=2 superconformal $Sp(2N)$ gauge theory containing vector multiplet coupled to four hypermultiplets in fundamental representation and one hypermultiplet in rank-2 antisymmetric representation. This theory is unique am

Nadia Olympia Antoniadis, Mark Richard Hogg, Willy Frederik Stehl, Alisa Javadi

Rapid, high-fidelity single-shot readout of quantum states is a ubiquitous requirement in quantum information technologies, playing a crucial role in quantum computation, quantum error correction, and fundamental tests of non-locality. Readout of the spin state of an optically active emitter can be achieved by driving a spin-preserving optical transition and

Fei Ma, Feiyi Liu, Wei Li

Recently methods of graph neural networks (GNNs) have been applied to solving the problems in high energy physics (HEP) and have shown its great potential for quark-gluon tagging with graph representation of jet events. In this paper, we introduce an approach of GNNs combined with a HaarPooling operation to analyze the events, called HaarPooling Message Pass

Paul S. Bourdon, Spiro Pantazatos

We describe several shortcomings of a study by Patone et al, whose findings were recently published in the American Heart Association Journal Circulation, including the following: * The study's principal conclusion, as initially stated, begins "Overall, the risk of myocarditis is greater after SARS-CoV-2 infection than after COVID-19 vaccination ...." Howeve

Emil Engström, Eskil Hansen

Domain decomposition methods are a set of widely used tools for parallelization of partial differential equation solvers. Convergence is well studied for elliptic equations, but in the case of parabolic equations there are hardly any results for general Lipschitz domains in two or more dimensions. The aim of this work is therefore to construct a new framewor

Mohammad Reza Karimi, Ya-Ping Hsieh, Andreas Krause

Non-convex sampling is a key challenge in machine learning, central to non-convex optimization in deep learning as well as to approximate probabilistic inference. Despite its significance, theoretically there remain many important challenges: Existing guarantees (1) typically only hold for the averaged iterates rather than the more desirable last iterates, (

Y. Evangelista, F. Fiore, R. Campana, F. Ceraudo

HERMES (High Energy Rapid Modular Ensemble of Satellites) is a space-borne mission based on a constellation of nano-satellites flying in a low-Earth orbit (LEO). The six 3U CubeSat buses host new miniaturized instruments hosting a hybrid Silicon Drift Detector/GAGG:Ce scintillator photodetector system sensitive to X-rays and gamma-rays. HERMES will probe the

Max Glockner, Yufang Hou, Iryna Gurevych

Misinformation emerges in times of uncertainty when credible information is limited. This is challenging for NLP-based fact-checking as it relies on counter-evidence, which may not yet be available. Despite increasing interest in automatic fact-checking, it is still unclear if automated approaches can realistically refute harmful real-world misinformation. H

Tomoko Morlat

Calculations are presented to describe the dynamic of a growing bubble in a single and simple formulation for R(t). The calculations show clearly that the behavior of the growing bubble is exponentially increasing with the time constant {\tau} showing a universal behavior as a function of the reduced superheat. Experimental data from other researchers are us

Krasymyr Tretiak, Scott Ferson

Data quality is an important consideration in many engineering applications and projects. Data collection procedures do not always involve careful utilization of the most precise instruments and strictest protocols. As a consequence, data are invariably affected by imprecision and sometimes sharply varying levels of quality of the data. Different mathematica

Yuta Nishiyama

Motivated by Sato and Mori's work on the Korteweg-de Vries (KdV) equation and the modified KdV equation, Mizukawa, Nakajima, and Yamada made a conjecture on 2-reduced Schur functions and Schur's Q-functions. The conjecture claims that certain sums of products of a Littlewood-Richardson coefficient and two 2-reduced Schur functions are equal to Schur's Q-func

Ahmed A. A. Osman, Timo Bolkart, Dimitrios Tzionas, Michael J. Black

Statistical 3D shape models of the head, hands, and fullbody are widely used in computer vision and graphics. Despite their wide use, we show that existing models of the head and hands fail to capture the full range of motion for these parts. Moreover, existing work largely ignores the feet, which are crucial for modeling human movement and have applications

R. Campana, G. Baroni, G. Della Casa, G. Dilillo

HERMES (High Energy Rapid Modular Ensemble of Satellites) is a space-borne mission based on a constellation of six 3U CubeSats flying in a low-Earth orbit, hosting new miniaturized instruments based on a hybrid Silicon Drift Detector/GAGG:Ce scintillator photodetector system sensitive to X-rays and gamma-rays. Moreover, the HERMES constellation will operate

Elisa Da Ros, Simon Kanthak, Erhan Sağlamyürek, Mustafa Gündoğan

Bose-Einstein condensates are a promising platform for optical quantum memories, but suffer from several decoherence mechanisms, leading to short memory lifetimes. While some of these decoherence effects can be mitigated by conventional methods, density dependent atom-atom collisions ultimately set the upper limit of quantum memory lifetime to s-timescales i

Sieger Falkena, Hadi Jamali-Rad, Jan van Gemert

Binary Neural Networks (BNNs) are receiving an upsurge of attention for bringing power-hungry deep learning towards edge devices. The traditional wisdom in this space is to employ sign() for binarizing featuremaps. We argue and illustrate that sign() is a uniqueness bottleneck, limiting information propagation throughout the network. To alleviate this, we pr

M. Kioumarsipour, J. Sadeghi

In this paper, we calculate the drag force of a charged particle in systems with hyperscaling violation using the AdS/CFT correspondence. We obtain energy loss, friction coefficient, diffusion and quasi normal modes of a heavy point particle. Here, we consider two cases. In the first, we assume the heavy point particle moves with constant velocity v. In the

Samuel Cahyawijaya, Bryan Wilie, Holy Lovenia, Huan Zhong

Large pre-trained language models (LMs) have been widely adopted in biomedical and clinical domains, introducing many powerful LMs such as bio-lm and BioELECTRA. However, the applicability of these methods to real clinical use cases is hindered, due to the limitation of pre-trained LMs in processing long textual data with thousands of words, which is a commo

Lukas Bernreiter, Shehryar Khattak, Lionel Ott, Roland Siegwart

The exploration of large-scale unknown environments can benefit from the deployment of multiple robots for collaborative mapping. Each robot explores a section of the environment and communicates onboard pose estimates and maps to a central server to build an optimized global multi-robot map. Naturally, inconsistencies can arise between onboard and server es

A. V. Snegirev, V. M. Kovalev, M. V. Entin

Diffusion currents are theoretically examined in two-dimensional Dirac materials, such as those of the transition metal dichalcogenides (TMD) family. The transversal effects are analogues of the valley Hall (VHE) and photogalvanic (PGE) transport phenomena in case when the electron driving force is not an electric field but a gradient of electron density dis

Julia Baligacs, Yann Disser, Nils Mosis, David Weckbecker

We consider the open online dial-a-ride problem, where transportation requests appear online in a metric space and need to be served by a single server. The objective is to minimize the completion time until all requests have been served. We present a new, parameterized algorithm for this problem and prove that it attains a competitive ratio of $1 + \varphi

Ahmed Tawfik Aboukhadra, Jameel Malik, Ahmed Elhayek, Nadia Robertini

Realistic reconstruction of two hands interacting with objects is a new and challenging problem that is essential for building personalized Virtual and Augmented Reality environments. Graph Convolutional networks (GCNs) allow for the preservation of the topologies of hands poses and shapes by modeling them as a graph. In this work, we propose the THOR-Net wh

Weiyi Cong, Zhuoran Zheng, Xiuyi Jia

Label distribution learning (LDL) differs from multi-label learning which aims at representing the polysemy of instances by transforming single-label values into descriptive degrees. Unfortunately, the feature space of the label distribution dataset is affected by human factors and the inductive bias of the feature extractor causing uncertainty in the featur

Juan C. Petit, Matthias Sperl

We study the local structural changes along the jamming transitions in asymmetric bidisperse granu\-lar packings. The local structure of the packing is assessed by the contact orientational order, $\tilde{Q}_{\ell}$, that quantifies the contribution of each contact configuration (Large-Large, Small-Small, Large-Small, Small-Large) in the jammed structure. Th

Julia Baligacs, Yann Disser, Farehe Soheil, David Weckbecker

In the open online dial-a-ride problem, a single server has to deliver transportation requests appearing over time in some metric space, subject to minimizing the completion time. We improve on the best known upper bounds on the competitive ratio on general metric spaces and on the half-line, for both the preemptive and non-preemptive version of the problem.

Ömer Eğecioğlu, Elif Saygı, Zülfükar Saygı

The diameter of a graph is the maximum distance between pairs of vertices in the graph. A pair of vertices whose distance is equal to its diameter are called diametrically opposite vertices. The collection of shortest paths between diametrically opposite vertices are referred as diametral paths. In this work, we enumerate the number of diametral paths for Fi

Weiyi Wang, Jin Chen, Yutao Jiao, Jiawen Kang

Blockchain is considered the critical backbone technology for secure and trusted Internet of Things (IoT) in the future 6G network. However, deploying a blockchain system in a complex wireless IoT network is challenging due to the limited resources, complex wireless environment, and the property of self-interested IoT devices. The existing incentive mechanis

Gudmund Pammer, Benjamin A. Robinson, Walter Schachermayer

We present a multidimensional extension of Kellerer's theorem on the existence of mimicking Markov martingales for peacocks, a term derived from the French for stochastic processes increasing in convex order. For a continuous-time peacock in arbitrary dimension, after Gaussian regularization, we show that there exists a strongly Markovian mimicking martingal

Olivier Bournez, Quentin Guilmant

The class of surreal numbers, denoted by $\textbf{No}$, initially proposed by Conway, is a universal ordered field in the sense that any ordered field can be embedded in it. They include in particular the real numbers and the ordinal numbers. They have strong relations with other fields such as field of transseries. Following Gonshor, surreal numbers can be

Yi Zhao, Rinu Boney, Alexander Ilin, Juho Kannala

Offline reinforcement learning, by learning from a fixed dataset, makes it possible to learn agent behaviors without interacting with the environment. However, depending on the quality of the offline dataset, such pre-trained agents may have limited performance and would further need to be fine-tuned online by interacting with the environment. During online