April 2023 arXiv papers — page 126

Hengkui Dong, Xianzhong Long, Yun Li, Lei Chen

Contrastive learning has emerged as an essential approach for self-supervised learning in visual representation learning. The central objective of contrastive learning is to maximize the similarities between two augmented versions of an image (positive pairs), while minimizing the similarities between different images (negative pairs). Recent studies have de

Yuanhong Chen, Yuyuan Liu, Hu Wang, Fengbei Liu

Audio-visual segmentation (AVS) is a challenging task that involves accurately segmenting sounding objects based on audio-visual cues. The effectiveness of audio-visual learning critically depends on achieving accurate cross-modal alignment between sound and visual objects. Successful audio-visual learning requires two essential components: 1) a challenging

Ulrich Heber

Hyper-velocity stars (HVS) are enigmatic objects because they are travelling so fast that they escape from the Galaxy. Among hot subdwarfs, only one such star is known, the He-sdO US 708. The Hyper-MUCHFUSS collaboration provided additional HVS candidates. Here we revisit the fastest candidates including US 708 by analysing optical spectra and spectral energ

Md Abdullah-Al Kaiser, Gourav Datta, Sreetama Sarkar, Souvik Kundu

The massive amounts of data generated by camera sensors motivate data processing inside pixel arrays, i.e., at the extreme-edge. Several critical developments have fueled recent interest in the processing-in-pixel-in-memory paradigm for a wide range of visual machine intelligence tasks, including (1) advances in 3D integration technology to enable complex pr

Tillmann Buttersack, Henrik Haak, Hendrik Bluhm, Uwe Hergenhahn

We present spatially resolved measurements of the temperature of a flat liquid water microjet for varying pressures, from vacuum to 100% relative humidity. The entire jet surface is probed in a single shot by a high-resolution infrared camera. Obtained 2D images are substantially influenced by the temperature of the apparatus on the opposite side of the IR c

Priyanka Maity, Andreas Bittracher, Péter Koltai, Jörg Schumacher

The dynamics in a confined turbulent convection flow is dominated by multiple long-lived macroscopic circulation states, which are visited subsequently by the system in a Markov-type hopping process. In the present work, we analyze the short transition paths between these subsequent macroscopic system states by a data-driven learning algorithm that extracts

Christian Carisch, Alessandro Romito, Oded Zilberberg

The evolution of a quantum system subject to measurements can be described by stochastic quantum trajectories of pure states. Instead, the ensemble average over trajectories is a mixed state evolving via a master equation. Both descriptions lead to the same expectation values for linear observables. Recently, there is growing interest in the average entangle

Fausto Barbero, Jonni Virtema

Causal multiteam semantics is a framework where probabilistic notions and causal inference can be studied in a unified setting. We study a logic (PCO) that features marginal probabilities and interventionist counterfactuals, and allows expressing conditional probability statements, do expressions and other mixtures of causal and probabilistic reasoning. Our

Mohammadreza Mofayezi, Yasamin Medghalchi

This study investigates the robustness of image classifiers to text-guided corruptions. We utilize diffusion models to edit images to different domains. Unlike other works that use synthetic or hand-picked data for benchmarking, we use diffusion models as they are generative models capable of learning to edit images while preserving their semantic content. T

Rulin Kuan

We employ the enclosure method to reconstruct unknown inclusions within an object that is governed by a semilinear elliptic equation with power-type nonlinearity. Motivated by [16], we tried to solve the problem without using special solutions such as complex geometrical optics solutions to the equation. Instead, we construct approximate solutions obtained f

Lu Zhang, Ning Wu

User-item interaction data in collaborative filtering and graph modeling tasks often exhibit power-law characteristics, which suggest the suitability of hyperbolic space modeling. Hyperbolic Graph Convolution Neural Networks (HGCNs) are a novel technique that leverages the advantages of GCN and hyperbolic space, and then achieves remarkable results. However,

Wojciech Tarnowski, Dariusz Chruściński, Sergey Denisov, Karol Życzkowski

We introduce different ensembles of random Lindblad operators $\cal L$, which satisfy quantum detailed balance condition with respect to the given stationary state $\sigma$ of size $N$, and investigate their spectral properties. Such operators are known as `Davies generators' and their eigenvalues are real; however, their spectral densities depend on $\sigma

Arnaud Grivet Sébert, Martin Zuber, Oana Stan, Renaud Sirdey

While machine learning has become pervasive in as diversified fields as industry, healthcare, social networks, privacy concerns regarding the training data have gained a critical importance. In settings where several parties wish to collaboratively train a common model without jeopardizing their sensitive data, the need for a private training protocol is par

Chun Wang, Haibo Yuan, Maosheng Xiang, Yuan-Sen Ting

We investigate the radial metallicity gradients and azimuthal metallicity distributions on the Galactocentric $X$--$Y$ plane using mono-temperature stellar populations selected from LAMOST MRS young stellar sample. The estimated radial metallicity gradient ranges from $-$0.015\,dex/kpc to $-$0.07\,dex/kpc, which decreases as effective temperature decreases (

Bin Xing, Timothy J. Rupert, Xiaoqing Pan, Penghui Cao

Diffusion involving atom transport from one location to another governs many important processes and behaviors such as precipitation and phase nucleation. Local chemical complexity in compositionally complex alloys poses challenges for modeling atomic diffusion and the resulting formation of chemically ordered structures. Here, we introduce a neural network

Zhanibek Darush, Mikhail Martynov, Aleksey Fedoseev, Aleksei Shcherbak

The continuous monitoring by drone swarms remains a challenging problem due to the lack of power supply and the inability of drones to land on uneven surfaces. Heterogeneous swarms, including ground and aerial vehicles, can support longer inspections and carry a higher number of sensors on board. However, their capabilities are limited by the mobility of whe

Sujoy Karan, Haonan Huang, Alexander Ivanovic, Ciprian Padurariu

The magnetic exchange coupling between magnetic impurities and a superconductor induce so-called Yu-Shiba-Rusinov (YSR) states which undergo a quantum phase transition (QPT) upon increasing the exchange interaction beyond a critical value. While the evolution through the QPT is readily observable, in particular if the YSR state features an electron-hole asym

Yinghui Wei, Malgorzata Wojtys, Lexy Sorrell, Peter Rowe

Time-to-event semi-competing risk endpoints may be correlated when both events are occurring on the same individual. These events and the association between them may also be influenced by individual characteristics. In this paper, we propose copula survival models to estimate hazard ratios of covariates on the non-terminal and terminal events, along with th

Maria Lucia Sambataro, Vincenzo Minissale, Salvatore Plumari, Vincenzo Greco

In the last decade a Quasi-Particle Model (QPM) has been developed to study charm quark dynamics in ultra-relativistic heavy-ion collisions supplying a satisfactory description of the main observables for $D$ meson and providing an estimate of the space-diffusion coefficient $D_s(T)$ from the phenomenology. In this paper, we extend the approach to bottom qua

Ashly Fuller, Martin Lo, Angelica Holmes, Lu Lemanski

Location-based games have come to the forefront of popularity in casual and mobile gaming over the past six years. However, there is no hard data on crimes that these games enable, ranging from assault to cyberstalking to grooming. Given these potential harms, we conduct a risk assessment and quasi-experiment on the game features of location-based games. Usi

Madeleine Sundblad, Tim Fürmann, Anke Weidlich, Mirko Schäfer

Electricity generation and demand time series often are only available on a national scale. In this contribution, we derive regionalization factors to allocate publicly available national generation and demand time series for Germany to the federal-state level. We compare two different types of regionalization approaches: Static factors are based on the regi

Mingjun Xu, Lingyun Qin, Weijie Chen, Shiliang Pu

Domain shift degrades the performance of object detection models in practical applications. To alleviate the influence of domain shift, plenty of previous work try to decouple and learn the domain-invariant (common) features from source domains via domain adversarial learning (DAL). However, inspired by causal mechanisms, we find that previous methods ignore

Hamid Shabani, Avik De, Tee-How Loo

The vanishing affine connections have been used solely while adopting the modified $f(Q)$ gravity theory to the cosmology. Consequently, researchers could not get beyond what is already known in $f(T)$ theory earlier. To alleviate this problem, in the present manuscript we investigate a recently proposed construction of $f(Q)$ theory using non-vanishing affi

Kang Chen, Tao Han, Junchao Gong, Lei Bai

We present FengWu, an advanced data-driven global medium-range weather forecast system based on Artificial Intelligence (AI). Different from existing data-driven weather forecast methods, FengWu solves the medium-range forecast problem from a multi-modal and multi-task perspective. Specifically, a deep learning architecture equipped with model-specific encod

Marek Wadinger, Michal Kvasnica

This paper presents the Real-time Adaptive and Interpretable Detection (RAID) algorithm. The novel approach addresses the limitations of state-of-the-art anomaly detection methods for multivariate dynamic processes, which are restricted to detecting anomalies within the scope of the model training conditions. The RAID algorithm adapts to non-stationary effec

Xiaojian Yang, Wei Shyy, Kun Xu

In this paper, a unified algorithm will be proposed for the study of gas-solid particle multiphase flow. The gas-kinetic scheme (GKS) is used to simulate the continuum gas phase and the multiscale unified gas-kinetic wave-particle (UGKWP) method is developed for the multiple dispersed solid particle phase. At the same time, the momentum and energy exchanges

Wataru Takeda

Bhargava introduced a generalization of the factorial function to extend classical results in integers to Dedekind rings and unify them. We study the Bhargava factorial of the images of polynomial maps from an analytic perspective. We first give the $\mathfrak p$-adic closures of the images of polynomial maps, which is the key to compute $\mathfrak p$-adic p

Matthias Schonlau, Julia Weiß, Jan Marquardt

Open-ended questions in surveys are valuable because they do not constrain the respondent's answer, thereby avoiding biases. However, answers to open-ended questions are text data which are harder to analyze. Traditionally, answers were manually classified as specified in the coding manual. Most of the effort to automate coding has gone into the easier probl

D. Hu, X. Wang, M. Shao, Y. Zhou

The Cooling Storage Ring (CSR) External-target Experiment (CEE) at the Heavy Ion Research Facility in Lanzhou (HIRFL), China, is the first multi-purpose nuclear physics experimental device to operate in the Giga electron-volt (GeV) energy range. The primary goals of the CEE are to study the bulk properties of dense matter and to understand the quantum chromo

Bingkai Lin, Xuandi Ren, Yican Sun, Xiuhan Wang

In this paper, we prove that assuming the exponential time hypothesis (ETH), there is no $f(k)\cdot n^{k^{o(1/\log\log k)}}$-time algorithm that can decide whether an $n$-vertex graph contains a clique of size $k$ or contains no clique of size $k/2$, and no FPT algorithm can decide whether an input graph has a clique of size $k$ or no clique of size $k/f(k)$

You Huang, Hao Yang, Ke Sun, Shengchuan Zhang

Interactive image segmentation enables annotators to efficiently perform pixel-level annotation for segmentation tasks. However, the existing interactive segmentation pipeline suffers from inefficient computations of interactive models because of the following two issues. First, annotators' later click is based on models' feedback of annotators' former click

Dawar Khan, Ciril Bohak, Ivan Viola

Dr. KID is an algorithm that uses isometric decomposition for the physicalization of potato-shaped organic models in a puzzle fashion. The algorithm begins with creating a simple, regular triangular surface mesh of organic shapes, followed by iterative k-means clustering and remeshing. For clustering, we need similarity between triangles (segments) which is

Minoru Eto, Kentaro Nishimura, Muneto Nitta

Low-energy dynamics of QCD can be described by pion degrees of freedom in terms of the chiral perturbation theory(ChPT). A chiral soliton lattice(CSL), an array of solitons, is the ground state due to the chiral anomaly in the presence of a magnetic field larger than a certain critical value at finite density. Here, we show in a model-independent and fully a

Katja Ludwig, Julian Lorenz, Robin Schön, Rainer Lienhart

Performance analyses based on videos are commonly used by coaches of athletes in various sports disciplines. In individual sports, these analyses mainly comprise the body posture. This paper focuses on the disciplines of triple, high, and long jump, which require fine-grained locations of the athlete's body. Typical human pose estimation datasets provide onl

Iasson Karafyllis, Miroslav Krstic, Alexandros Aslanidis

We complete the first step towards the resolution of several decades-old challenges in disturbance-robust adaptive control. For a scalar linear system with an unknown parameter for which no a priori bound is given, with a disturbance that is of unlimited magnitude and possibly persistent (not square integrable), and without a persistency of excitation necess

Haifeng Yang, Manuel Fernandez-Lopez, Zhi-Yun Li, Ian W. Stephens

Crescent-shaped structures in transition disks hold the key to studying the putative companions to the central stars. The dust dynamics, especially that of different grain sizes, is important to understanding the role of pressure bumps in planet formation. In this work, we present deep dust continuum observation with high resolution towards the Oph IRS 48 sy

Xavier Richard, Benoît Richard, Christian Mazza, Jan Roelof van der Meer

Prokaryotic gene expression is dynamic and noisy, and can lead to phenotypic variations. Previous work has shown that the selection of such variation can be modeled through basic reaction networks described by O.D.E. displaying a bistable behavior. While previous mathematical studies have shown that mono- or bistable behavior depends on the rate of the react

Susumu Ito, Nariya Uchida

It has been a long-standing problem how schooling fish optimize their motion by exploiting the vortices shed by the others. A recent experimental study showed that a pair of fish reduce energy consumption by matching the phases of their tailbeat according to their distance. In order to elucidate the dynamical mechanism by which fish control the motion of cau

Mengmeng Xu, Mattia Soldan, Jialin Gao, Shuming Liu

Video activity localization aims at understanding the semantic content in long untrimmed videos and retrieving actions of interest. The retrieved action with its start and end locations can be used for highlight generation, temporal action detection, etc. Unfortunately, learning the exact boundary location of activities is highly challenging because temporal

Hermann Tapamo, Anna Bosman, James Maina, Emile Horak

Flexible road pavements deteriorate primarily due to traffic and adverse environmental conditions. Cracking is the most common deterioration mechanism; the surveying thereof is typically conducted manually using internationally defined classification standards. In South Africa, the use of high-definition video images has been introduced, which allows for saf

Yuke Hu, Wei Liang, Ruofan Wu, Kai Xiao

Knowledge Graph Embedding (KGE) is a fundamental technique that extracts expressive representation from knowledge graph (KG) to facilitate diverse downstream tasks. The emerging federated KGE (FKGE) collaboratively trains from distributed KGs held among clients while avoiding exchanging clients' sensitive raw KGs, which can still suffer from privacy threats

Natalia Kowalczyk, Jacek Rumiński

Face masks are recommended to reduce the transmission of many viruses, especially SARS-CoV-2. Therefore, the automatic detection of whether there is a mask on the face, what type of mask is worn, and how it is worn is an important research topic. In this work, the use of thermal imaging was considered to analyze the possibility of detecting (localizing) a ma

Antonio Fazzi, Alessandro Chiuso

In this paper, we study connections between the classical model-based approach to nonlinear system theory, where systems are represented by equations, and the nonlinear behavioral approach, where systems are defined as sets of trajectories. In particular, we focus on equivalent representations of the systems in the two frameworks for the problem of simulatin

Purnima Pandit, Payal Singh

This article deals with the complexity involved in fuzzy derivatives when both input and output are from nonempty, convex, and compact fuzzy space. Consider a fuzzy valued mapping, and for fuzzy differentiation of fuzzy valued function, we propose Modified Hukuhara derivative. To evaluate this derivative, we need to take the parametric form of, input and the

Luuk Stehouwer, Jan Steinebrunner

Dagger categories are an essential tool for categorical descriptions of quantum physics, for example in categorical quantum mechanics and unitary topological field theory. Their definition however is in tension with the ``principle of equivalence'' that lies at the heart of category theory, thereby inhibiting generalizations to higher categories. In this not

Caroline Braud, Bérengère Podvin, Julien Deparday

We present an experimental study of the aerodynamic forces on a thick and cambered airfoil at a high Reynolds number 3.6 x 10^6, which is of direct relevance for wind turbine design. Unlike thin airfoils at low chord-based Reynolds numbers, no consistent description currently exists for the stall process on such airfoils. We consider two chord-wise rows of i

Tristan van Leeuwen, Andreas Tataris

In this paper, we extend the ROM-based approach for inverse scattering with Neumann boundary conditions, introduced by Druskin at. al. (Inverse Problems 37, 2021), to the 1D Schr{\"o}dinger equation with impedance (Robin) boundary conditions. We also propose a novel data-assimilation (DA) inversion method based on the ROM approach, thereby avoiding the need

Sanya Sinha, Nilay Gupta

According to the World Malaria Report of 2022, 247 million cases of malaria and 619,000 related deaths were reported in 2021. This highlights the predominance of the disease, especially in the tropical and sub-tropical regions of Africa, parts of South-east Asia, Central and Southern America. Malaria is caused due to the Plasmodium parasite which is circulat

Yingbo Li, Anamaria-Beatrice Spulber, Yucong Duan

Physical artificial intelligence can prove to be one of the most important challenges of the artificial intelligence. The governance of physical artificial intelligence would define its responsible intelligent application in the society.

Chenyang Wang, Junjun Jiang, Zhiwei Zhong, Deming Zhai

Face super-resolution is a technology that transforms a low-resolution face image into the corresponding high-resolution one. In this paper, we build a novel parsing map guided face super-resolution network which extracts the face prior (i.e., parsing map) directly from low-resolution face image for the following utilization. To exploit the extracted prior f

Simon Bohlen, Zheng Gong, Michael J. Quin, Matteo Tamburini

Highly polarized, multi-kiloampere-current electron bunches from compact laser-plasma accelerators are desired for numerous applications. Current proposals to produce these beams suffer from intrinsic limitations to the reproducibility, charge, beam shape and final polarization degree. In this Letter, we propose colliding pulse injection as a technique for t

Siyi Wang, Anubhab Baksi, Anupam Chattopadhyay

In this paper, we propose an efficient quantum carry-lookahead adder based on the higher radix structure. For the addition of two $n$-bit numbers, our adder uses $O(n)-O(\frac{n}{r})$ qubits and $O(n)+O(\frac{n}{r})$ T gates to get the correct answer in T-depth $O(r)+O(\log{\frac{n}{r}})$, where $r$ is the radix. Quantum carry-lookahead adder has already att

Shu-Yi Kong, Jun-Tao Zhu, Jun He

In this work, we systematically investigate the charmed-strange dibaryon systems with $csssqq$ quarks and their baryon-antibaryon partners from the interactions $\Xi^{(',*)}_{c}\Xi^{(*)}$, $\Omega^{(*)}_c\Lambda$, $\Omega^{(*)}_c\Sigma^{(*)}$, $\Lambda_c\Omega$ and $\Sigma^{(*)}_c\Omega$ and their baryon-antibaryon partners from interactions $\Xi^{(',*)}_{c}

Euihyoek Lee, Chulhong Min, Jeaseung Lee, Jin Yu

We present GrooveMeter, a novel system that automatically detects vocal and motion reactions to music via earable sensing and supports music engagement-aware applications. To this end, we use smart earbuds as sensing devices, which are already widely used for music listening, and devise reaction detection techniques by leveraging an inertial measurement unit

Steffen M. Recktenwald, Katharina Graessel, Yazdan Rashidi, Jann Niklas Steuer

Constricted blood vessels in the circulatory system can severely impact the spatiotemporal organization of red blood cells (RBCs) causing various physiological complications. In lab-on-a-chip applications, constrictions are commonly used for cell sorting and plasma separation based on the formation of a cell-free layer (CFL) at the channel boundary. However,

Maurice Duits, Diane Holcomb

We study a double scaling limit for a solution of the discrete Painlev\'e II equation with boundary conditions. The location of the right boundary point is in the critical regime where the discrete Painlev\'e equation turns into the continuous Painlev\'e II equation. Our main results it that, instead of the Hastings-McLeod solution (which would occur when th

Jooyeon Geem, Masateru Ishiguro, Mikael Granvik, Hiroyuki Naito

We conducted optical polarimetry and near-infrared spectroscopy of JAXA's Hayabusa2# mission target, (98943) 2001 CC21, in early 2023. Our new observations indicated that this asteroid has a polarimetric inversion angle of ~21 deg, absorption bands around 0.9 and 1.9 um, and a geometric albedo of 0.285 +- 0.083. All these features are consistent with those o

Thodoris Kouzelis, Grigoris Bastas, Athanasios Katsamanis, Alexandros Potamianos

Automated audio captioning is multi-modal translation task that aim to generate textual descriptions for a given audio clip. In this paper we propose a full Transformer architecture that utilizes Patchout as proposed in [1], significantly reducing the computational complexity and avoiding overfitting. The caption generation is partly conditioned on textual A

Liangchen Wang

This work considers the Keller-Segel consumption system \begin{eqnarray*} \left\{ \begin{array}{llll} u_t=\Delta (u\phi(v))+au-bu^\gamma,\quad &x\in \Omega,\quad t>0,\\ v_t=\Delta v-uv,\quad &x\in\Omega,\quad t>0 \end{array} \right. \end{eqnarray*} in a smoothly bounded domain $\Omega\subset \mathbb{R}^n,$ $n\geq1$, under no-flux boundary conditions, where t

Man-Chun Lee

In this work, we extend the existence theory of non-collapsed Ricci flows from point-wise curvature lower bound to Kato-type lower bound. As an application, we prove that compact three dimensional non-collapsed strong Kato limit space is homeomorphic to a smooth manifold. The result also holds in higher dimension under uniform strong Kato lower bound of 1-is

Nikita Jain, Sucheta Dutt, Ranjeet Sehmi

In this paper, necessary and sufficient conditions for a cyclic code of arbitrary length over the non-chain rings $Z_{4}+\nu Z_{4}$ for $\nu^{2} \in \{0,1,\nu,2\nu,3\nu,2+\nu,2+3\nu,3+2\nu\}$ to be a reversible cyclic code have been established. Also, conditions for a cyclic code over these non-chain rings to be a reversible complement cyclic code which are

Urte Adomaityte, Gabriele Sicuro, Pierpaolo Vivo

We characterise the learning of a mixture of two clouds of data points with generic centroids via empirical risk minimisation in the high dimensional regime, under the assumptions of generic convex loss and convex regularisation. Each cloud of data points is obtained via a double-stochastic process, where the sample is obtained from a Gaussian distribution w

Xuanzhe Xiao, Zeng Li, Chuanlong Xie, Fengwei Zhou

Unraveling the reasons behind the remarkable success and exceptional generalization capabilities of deep neural networks presents a formidable challenge. Recent insights from random matrix theory, specifically those concerning the spectral analysis of weight matrices in deep neural networks, offer valuable clues to address this issue. A key finding indicates

Antoine Honet, Luc Henrard, Vincent Meunier

Finite size armchair graphene nanoribbons (GNR) of different families are theoretically studied using the Hubbard model in both mean-field and GW approximations, including spin correlation effects. It is shown that correlation primarily affect the properties of topological end states of the nanoribbons. A representative structure of each of the three GNR fam

Georg Schönweger, Niklas Wolff, Md Redwanul Islam, Maike Gremmel

Analog switching in ferroelectric devices promises neuromorphic computing with highest energy efficiency, if limited device scalability can be overcome. To contribute to a solution, we report on the ferroelectric switching characteristics of sub-5 nm thin Al$_{0.74}$Sc$_{0.26}$N films grown on Pt/Ti/SiO2/Si and epitaxial Pt/GaN/sapphire templates by sputter-

Md Abdullah-Al Kaiser, Edwin Tieu, Ajey P. Jacob, Akhilesh R. Jaiswal

The landscape of emerging applications has been continually widening, encompassing various data-intensive applications like artificial intelligence, machine learning, secure encryption, Internet-of-Things, etc. A sustainable approach toward creating dedicated hardware platforms that can cater to multiple applications often requires the underlying hardware to

Alejo Jose G. Sison, Marco Tulio Daza, Roberto Gozalo-Brizuela, Eduardo C. Garrido-Merchán

This article explores the ethical problems arising from the use of ChatGPT as a kind of generative AI and suggests responses based on the Human-Centered Artificial Intelligence (HCAI) framework. The HCAI framework is appropriate because it understands technology above all as a tool to empower, augment, and enhance human agency while referring to human wellbe

Chunyan Li, Jing Zhong, Songmei Qin, Li Chen

The particularly abundant presence of blue straggler stars (BSS) in Galactic open clusters offers favorable conditions for detailed studies on the statistical properties and the origin of the blue straggler population. With the help of Gaia DR3, the number of identified open clusters continuously increases, and the determination of star cluster members is mo

Christos Koutlis, Manos Schinas, Symeon Papadopoulos

Hate speech is a societal problem that has significantly grown through the Internet. New forms of digital content such as image memes have given rise to spread of hate using multimodal means, being far more difficult to analyse and detect compared to the unimodal case. Accurate automatic processing, analysis and understanding of this kind of content will fac

Najiya V K, Chithra A, Naveen Palanivel

The unitary addition Cayley graph $G_n$, $n\in Z^+$ is the graph whose vertex set is $Z_n$, the ring of integers modulo $n$ and two vertices $u$ and $v$ are adjacent if and only if $u + v \in \cup_n$ where $\cup_n$ is the set of all units of the ring. The $A_\alpha$-matrix of a graph $G$ is defined as $A_\alpha (G) = \alpha D(G) + (1-\alpha)A(G)$, $\alpha \i

Zixuan Xu, Shuai Xu, Ruopeng Zhang, Sibo Zheng

We propose a new freeze-in dark matter candidate which feebly couples to the standard model charged leptons. The feeble interactions allow it (i) to freeze-in from the Standard Model thermal bath with its relic density being either a fraction or the entirety of the observed dark matter density and (ii) to radiatively decay to two photons in the dark matter m

Dimiter Prodanov

The Wright function, which arises in the theory of the space-time fractional diffusion equation, is an interesting mathematical object which has diverse connections with other special and elementary functions. The Wright function provides a unified treatment of several classes of special functions, such as the Gaussian, Airy, Bessel, and Error functions, etc

Jonas Gregor Wiese, Lisa Wimmer, Theodore Papamarkou, Bernd Bischl

Bayesian inference in deep neural networks is challenging due to the high-dimensional, strongly multi-modal parameter posterior density landscape. Markov chain Monte Carlo approaches asymptotically recover the true posterior but are considered prohibitively expensive for large modern architectures. Local methods, which have emerged as a popular alternative,

Hao Zhang

Extracting entities and relations is an essential task of information extraction. Triplets extracted from a sentence might overlap with each other. Previous methods either did not address the overlapping issues or solved overlapping issues partially. To tackle triplet overlapping problems completely, firstly we extract candidate subjects with a standard span

Yuya Otake

Let R be a commutative noetherian ring. In this paper, we find out close relationships between the module M being embedded in a module of projective dimension at most n and the (n+1)-torsionfreeness of the nth syzygy of M. As an application, when R is local with residue field k, we compute the dimensions as k-vector spaces of Ext modules related to syzygies

Lan V. Truong

Subset weighted-Tempered Gibbs Sampler (wTGS) has been recently introduced by Jankowiak to reduce the computation complexity per MCMC iteration in high-dimensional applications where the exact calculation of the posterior inclusion probabilities (PIP) is not essential. However, the Rao-Backwellized estimator associated with this sampler has a high variance a

Marcus Michelen, Oren Yakir

Smale's Seventh Problem asks for an efficient algorithm to generate a configuration of $n$ points on the sphere that nearly minimizes the logarithmic energy. As a candidate starting configuration for this problem, Armentano, Beltr\'an and Shub considered the set of points given by the stereographic projection of the roots of the random elliptic polynomial of

Yiling Zeng, Chunyao Song, Yuhan Li, Tingjian Ge

Graph streams represent data interactions in real applications. The mining of graph streams plays an important role in network security, social network analysis, and traffic control, among others. However, the sheer volume and high dynamics cause great challenges for efficient storage and subsequent query analysis on them. Current studies apply sketches to s

Li Rong Wang, Hsuan Fu, Xiuyi Fan

We study the impacts of business cycles on machine learning (ML) predictions. Using the S&P 500 index, we find that ML models perform worse during most recessions, and the inclusion of recession history or the risk-free rate does not necessarily improve their performance. Investigating recessions where models perform well, we find that they exhibit lower mar

Lingrui Zhang, Shuheng Zhang, Guoyang Xie, Jiaqi Liu

Data augmentation is a promising technique for unsupervised anomaly detection in industrial applications, where the availability of positive samples is often limited due to factors such as commercial competition and sample collection difficulties. In this paper, how to effectively select and apply data augmentation methods for unsupervised anomaly detection

Jacek Miękisz, Javad Mohamadichamgavi, Jakub Łącki

We study stochastic dynamics of the Prisoner's Dilemma game on random Erd\"{o}s-R\'{e}nyi and Barab\'{a}si-Albert networks with a cost of maintaining a link between interacting players. Stochastic simulations show that when the cost increases, the population of players located on Barab\'{a}si-Albert network undergoes a sharp transition from an ordered state,

Daniel Grieser, Jørgen Olsen Lye

We study the behaviour of geodesics on a Riemannian manifold near a generalized conical or cuspidal singularity. We show that geodesics entering a small neighbourhood of the singularity either hit the singularity or approach it to a smallest distance $\delta$ and then move away from it, winding around the singularity a number of times. We study the limiting

Emily Öhman, Riikka Rossi

We propose to use affect as a proxy for mood in literary texts. In this study, we explore the differences in computationally detecting tone versus detecting mood. Methodologically we utilize affective word embeddings to look at the affective distribution in different text segments. We also present a simple yet efficient and effective method of enhancing emot

Zhixuan Xu, Kechun Xu, Yue Wang, Rong Xiong

We focus on the task of language-conditioned object placement, in which a robot should generate placements that satisfy all the spatial relational constraints in language instructions. Previous works based on rule-based language parsing or scene-centric visual representation have restrictions on the form of instructions and reference objects or require large

Chenrui Wu, Zexi Li, Fangxin Wang, Chao Wu

Federated learning (FL) is a distributed framework for collaboratively training with privacy guarantees. In real-world scenarios, clients may have Non-IID data (local class imbalance) with poor annotation quality (label noise). The co-existence of label noise and class imbalance in FL's small local datasets renders conventional FL methods and noisy-label lea

Sarwan Ali, Prakash Chourasia, Zahra Tayebi, Babatunde Bello

The amount of sequencing data for SARS-CoV-2 is several orders of magnitude larger than any virus. This will continue to grow geometrically for SARS-CoV-2, and other viruses, as many countries heavily finance genomic surveillance efforts. Hence, we need methods for processing large amounts of sequence data to allow for effective yet timely decision-making. S

Anupam Ghosh, Partha Konar, Debashis Saha, Satyajit Seth

We explore the pair production of third-generation scalar leptoquark at the Large Hadron Collider to next-to-leading order accuracy in QCD, matched to parton shower for a precise probing of the stemming model. We propose to tag two boosted top-like fatjets produced from the decay of heavy leptoquarks in association with notably large missing transverse momen

C. Fairoos, T. Sharqui

We study the thermodynamic properties of black holes in dRGT massive gravity theory using Duan's topological current $\phi-$ mapping theory. The topological features and the corresponding thermodynamic stability conditions for neutral and charged cases are discussed. The uncharged black hole in four dimensions has a topological number $0$, sharing the same t

A. Olejarz, W. Y. Huo, M. Zielinski, R. Diduszko

High-entropy alloys are extensively studied due to their very promising properties. However manufacturing methods currently used to prepare HEAs are complicated, costly, and likely non-industrially scalable processes. This limits their evolution and poses questions regarding the material's applicability in the future. Considering the abovementioned point, we

Chenzhang Xiao, Mahshid Mansouri, David Lam, Joao Ramos

This paper presents the design and control of a ballbot drivetrain that aims to achieve high agility, minimal footprint, and high payload capacity while maintaining dynamic stability. Two hardware platforms and analytical models were developed to test design and control methodologies. The full-scale ballbot prototype (MiaPURE) was constructed using off-the-s

Yakini Tchouka, Jean-François Couchot, David Laiymani, Philippe Selles

Automatically associating ICD codes with electronic health data is a well-known NLP task in medical research. NLP has evolved significantly in recent years with the emergence of pre-trained language models based on Transformers architecture, mainly in the English language. This paper adapts these models to automatically associate the ICD codes. Several neura

Asad J. Khattak, Austin Harris, Mina Sartipi, Iman Mahdinia

This report aims to support the Tennessee Department of Transportation's decisions about vehicle and infrastructure communication technologies. The transition from Dedicated Short-Range communication (DSRC) V2X to Cellular Vehicle to Everything (C-V2X) is explored using USDOT guidance on relevant issues and presenting the results of experimentation in Tennes

He Wang, Jin Wang

In this paper, we report findings of non-stationary behavior observed in a fully connected qubit network, utilizing a random unitary evolution model in open quantum system theory. The environmental effect is reflected in the partial swap (PSW) interaction between pairs of qubits with a certain probability. Our study begins with a simple Ising-type Hamiltonia

Jiawei Jiang, Yuchao Feng, Honghui Xu, Wanjun Chen

Deep unfolding networks (DUNs) are the foremost methods in the realm of compressed sensing MRI, as they can employ learnable networks to facilitate interpretable forward-inference operators. However, several daunting issues still exist, including the heavy dependency on the first-order optimization algorithms, the insufficient information fusion mechanisms,

Seungpyo Kang, Minseon Kim, Jiwon Sun, Myeonghun Lee

Protein aggregation occurs when misfolded or unfolded proteins physically bind together, and can promote the development of various amyloid diseases. This study aimed to construct surrogate models for predicting protein aggregation via data-driven methods using two types of databases. First, an aggregation propensity score database was constructed by calcula

Benjamin B. Bruce, Malabika Pramanik

Let $\Gamma \subset \mathbb{R}^d$ be a smooth curve containing the origin. Does every Borel subset of $\mathbb R^d$ of sufficiently small codimension enjoy a S\'ark\"ozy-like property with respect to $\Gamma$, namely, contain two elements differing by a member of $\Gamma \setminus \{0\}$? Kuca, Orponen, and Sahlsten have answered this question in the affirma

Imen Benabbas, Belkacem Said-Houari

In this work, we investigate a mathematical model of nonlinear ultrasonic heating based on a coupled system of the Westervelt equation and the hyperbolic Pennes bioheat equation (Westervelt--Pennes--Cattaneo model). Using the energy method together with a fixed point argument, we prove that our model is locally well-posed and does not degenerate under a smal

Sayan Mondal, Saurabh Basu

We have studied the evolution of the topological properties of a band-engineered AB-stacked bilayer honeycomb structure in the presence of a Haldane flux. Without a Haldane flux, band engineering makes the band touching points (the so-called Dirac points) move towards each other and eventually merge into one at an intermediate $\mathbf{M}$ point in the Brill

Mukesh Kumar Singh, Shasvath J. Kapadia, Soummyadip Basak, Parameswaran Ajith

The origin of fast radio bursts (FRBs) is currently an open question with several proposed sources and corresponding mechanisms for their production. Among them are compact binary coalescences (CBCs) that also generate gravitational waves (GWs). Spatial and temporal coincidences between GWs and FRBs have so far been used to search for potential FRB counterpa

Jing Yu, Varun Gupta, Adam Wierman

This paper studies the problem of online stabilization of an unknown discrete-time linear time-varying (LTV) system under bounded non-stochastic (potentially adversarial) disturbances. We propose a novel control algorithm based on convex body chasing (CBC). Under the assumption of infrequently changing or slowly drifting dynamics, the algorithm guarantees bo