March 2023 arXiv papers — page 120

Eduardo J. C. Dias, I. Madan, S. Gargiulo, F. Barantani

Dense micron-sized electron plasmas, such as those generated upon irradiation of nanostructured metallic surfaces by intense femtosecond laser pulses, constitute a rich playground to study light-matter interactions, many-body phenomena, and out-of-equilibrium charge dynamics. Besides their fundamental interest, laser-induced plasmas hold potential for the ge

Alain Valette

For $n\geq 1$, let $\rho_n$ denote the standard action of $GL_2(\Z)$ on the space $P_n(\Z)\simeq\Z^{n+1}$ of homogeneous polynomials of degree $n$ in two variables, with integer coefficients. For $G$ a non-amenable subgroup of $GL_2(\Z)$, we describe the maximal Haagerup subgroups of the semi-direct product $\Z^{n+1}\rtimes_{\rho_n} G$, extending the classif

Xusheng Du, Tianling Jin, Hui Yang

In this paper, we study existence of solutions to a conformally invariant integral equation involving Poisson-type kernels. Such integral equation has a stronger non-local feature and is not the dual of any PDE. We obtain the existence of solutions in the antipodal symmetry class.

Maya Ben-Yami, Vanessa Skiba, Sebastian Bathiany, Niklas Boers

Observations are increasingly used to detect critical slowing down (CSD) to measure stability changes in key Earth system components. However, most datasets have non-stationary missing-data distributions, biases and uncertainties. Here we show that, together with the pre-processing steps used to deal with them, these can bias the CSD analysis. We present an

Michael Benzke, Tobias Hurth

We report on recent progress in the field of nonlocal (so-called resolved) contributions to the inclusive penguin decays which presently belong to the largest uncertainties in these inclusive decay modes. There is still a very large scale and a large charm mass dependence in the present leading order results which can in the future be decreased by including

Isroil A. Ikromov, Dildora I. Ikromova

In this article, we study the convolution operators $M_k$ with oscillatory kernel, which are related to solutions to the Cauchy problem for the strictly hyperbolic equations. The operator $M_k$ is associated to the characteristic hypersurfaces $\Sigma\subset \mathbb{R}^3$ of a hyperbolic equation and smooth amplitude function, which is homogeneous of order $

Soroush Sadeghnejad, Mojtaba Esfandiari, Farshad Khadivar

Simulated training platforms offer a suitable avenue for surgical students and professionals to build and improve upon their skills, without the hassle of traditional training methods. To enhance the degree of realistic interaction paradigms of training simulators, great work has been done to both model simulated anatomy in more realistic fashion, as well as

Fatima-Ezzahrae Abid, Mohamed Boucetta

A pseudo-Euclidean non-associative algebra $(\mathfrak{g}, \bullet)$ is a real algebra of finite dimension that has a metric, i.e., a bilinear, symmetric, and non-degenerate form $\langle\;\rangle$. The metric is considered $\mathrm{L}$-invariant (resp. $\mathrm{R}$-invariant) if all left multiplications (resp. right multiplications) are skew-symmetric. The

Hans Christianson, Jian Wang, Ruoyu P. T. Wang

We introduce the control conditions for 0th order pseudodifferential operators $\mathbf{P}$ whose real parts satisfy the Morse--Smale dynamical condition. We obtain microlocal control estimates under the control conditions. As a result, we show that there are no singular profiles in the solution to the evolution equation $(i\partial_t-\mathbf{P})u=f$ when $\

Po-Yung Chou, Yu-Yung Kao, Cheng-Hung Lin

Fine-grained visual classification is a challenging task due to the high similarity between categories and distinct differences among data within one single category. To address the challenges, previous strategies have focused on localizing subtle discrepancies between categories and enhencing the discriminative features in them. However, the background also

Nicolás Kuschinski, J. Andrés Christe, Adriana Monroy

A common test for the diagnosis of type 2 diabetes is the Oral Glucose Tolerance Test (OGTT). Recent developments in the study of OGTT tests have framed it as a Bayesian inverse problem. These data analysis advances promise great improvements in the descriptive power of OGTTs. OGTT tests are typically done with invasive, bothersome, and somewhat expensive ve

Jiale Zhang, Yulun Zhang, Jinjin Gu, Jiahua Dong

In this paper, we present a hybrid X-shaped vision Transformer, named Xformer, which performs notably on image denoising tasks. We explore strengthening the global representation of tokens from different scopes. In detail, we adopt two types of Transformer blocks. The spatial-wise Transformer block performs fine-grained local patches interactions across toke

Berker Demirel, Huseyin Ozkan

Group Activity Recognition (GAR) aims to detect the activity performed by multiple actors in a scene. Prior works model the spatio-temporal features based on the RGB, optical flow or keypoint data types. However, using both the temporality and these data types altogether increase the computational complexity significantly. Our hypothesis is that by only usin

Gary C. F. Lee, Amir Weiss, Alejandro Lancho, Yury Polyanskiy

We study the single-channel source separation problem involving orthogonal frequency-division multiplexing (OFDM) signals, which are ubiquitous in many modern-day digital communication systems. Related efforts have been pursued in monaural source separation, where state-of-the-art neural architectures have been adopted to train an end-to-end separator for au

Louis Martini, Sebastian Wolf

We develop the theory of topoi internal to an arbitrary $\infty$-topos $\mathcal B$. We provide several characterisations of these, including an internal analogue of Lurie's characterisation of $\infty$-topoi, but also a description in terms of the underlying sheaves of $\infty$-categories, and we prove a number of structural results about these objects. Fur

Gino Biondini, Alexander J. Bivolcic, Mark A. Hoefer, Antonio Moro

Two-dimensional reductions of the KP-Whitham system, namely the overdetermined Whitham modulation system for five dependent variables that describe the periodic solutions of the Kadomtsev-Petviashvili equation, are studied and characterized. Three different reductions are considered corresponding to modulations that are independent of x , independent of y ,

Mike Thornton, Danilo Mandic, Tobias Reichenbach

During speech perception, a listener's electroencephalogram (EEG) reflects acoustic-level processing as well as higher-level cognitive factors such as speech comprehension and attention. However, decoding speech from EEG recordings is challenging due to the low signal-to-noise ratios of EEG signals. We report on an approach developed for the ICASSP 2023 'Aud

Bohao Tang, Sandipan Pramanik, Yi Zhao, Brian Caffo

In this manuscript, we study the problem of scalar-on-distribution regression; that is, instances where subject-specific distributions or densities, or in practice, repeated measures from those distributions, are the covariates related to a scalar outcome via a regression model. We propose a direct regression for such distribution-valued covariates that circ

Bing He, Mustaque Ahamad, Srijan Kumar

The spread of online misinformation threatens public health, democracy, and the broader society. While professional fact-checkers form the first line of defense by fact-checking popular false claims, they do not engage directly in conversations with misinformation spreaders. On the other hand, non-expert ordinary users act as eyes-on-the-ground who proactive

Devsi Bantva, P L Vihol

For a simple finite connected graph $G$, let $diam(G)$ and $d_{G}(u,v)$ denote the diameter of $G$ and distance between $u$ and $v$ in $G$, respectively. A radio labeling of a graph $G$ is a mapping $f$ : $V(G) \rightarrow \{0, 1, 2,...\}$ such that $|f(u)-f(v)| \geq diam(G) + 1 - d_{G}(u,v)$ holds for every pair of distinct vertices $u,v$ of $G$. The radio

Xijuan Sun, Di Wu, Arnaud Zinflou, Benoit Boulet

Hacking and false data injection from adversaries can threaten power grids' everyday operations and cause significant economic loss. Anomaly detection in power grids aims to detect and discriminate anomalies caused by cyber attacks against the power system, which is essential for keeping power grids working correctly and efficiently. Different methods have b

Zijian Ding, Joel Chan

Large Language Models (LLMs) have demonstrated impressive text generation capabilities, prompting us to reconsider the future of human-AI co-creation and how humans interact with LLMs. In this paper, we present a spectrum of content generation tasks and their corresponding human-AI interaction patterns. These tasks include: 1) fixed-scope content curation ta

Iver Brevik

In cases when it is desirable to transport medication through blood vessels, especially when dealing with brain cancer being confronted with the narrow arteries in the brain, the blood-brain barrier makes the medical treatment difficult. There is a need of expanding the diameters of the arteries in order to facilitate the transport of medicaments. Recent res

Ruicheng Bao, Chaoqun Du, Zhiyu Cao, Zhonghuai Hou

We establish a general lower bound for the entropy production rate (EPR) based on the Kullback-Leibler divergence and the Logarithmic-Sobolev constant that characterizes the time-scale of relaxation. This bound can be considered as an enhanced second law of thermodynamics. When applied to thermal relaxation, it reveals a universal trade-off relation between

S. A. Narawade, Shashank P. Singh, B. Mishra

The dynamical aspect of accelerating cosmological model has been studied in this paper in the context of modified symmetric teleparallel gravity, the $f(Q)$ gravity. Initially, we have derived the dynamical parameters for two well known forms of $f(Q)$ such as: (i) log-square-root form and (ii) exponential form. The equation of state (EoS) parameter for the

Dekui Peng

By a recent result of Juh\'{a}sz and van Mill, a locally compact topological group whose dense subspaces are all separable is metrizable. In this note we investigate the following question: is every locally compact group having all dense subgroups separable also metrizable? We give an example to show the answer is negative for locally compact abelian groups,

Jin Ding, Jie-Chao Zhao, Yong-Zhi Sun, Ping Tan

Deep convolutional neural network (DCNN for short) models are vulnerable to examples with small perturbations. Adversarial training (AT for short) is a widely used approach to enhance the robustness of DCNN models by data augmentation. In AT, the DCNN models are trained with clean examples and adversarial examples (AE for short) which are generated using a s

Jiahui Zhang, Fangneng Zhan, Christian Theobalt, Shijian Lu

Quantizing images into discrete representations has been a fundamental problem in unified generative modeling. Predominant approaches learn the discrete representation either in a deterministic manner by selecting the best-matching token or in a stochastic manner by sampling from a predicted distribution. However, deterministic quantization suffers from seve

Marcel da Câmara Ribeiro-Dantas, Honghao Li, Vincent Cabeli, Louise Dupuis

Discovering causal effects is at the core of scientific investigation but remains challenging when only observational data is available. In practice, causal networks are difficult to learn and interpret, and limited to relatively small datasets. We report a more reliable and scalable causal discovery method (iMIIC), based on a general mutual information supr

Ruijian Han, Boris Kramer, Dongjin Lee, Akil Narayan

Forward simulation-based uncertainty quantification that studies the distribution of quantities of interest (QoI) is a crucial component for computationally robust engineering design and prediction. There is a large body of literature devoted to accurately assessing statistics of QoIs, and in particular, multilevel or multifidelity approaches are known to be

Zheng Wang, Mingyong Jing, Peng Zhang, Shaoxin Yuan

Since its theoretical sensitivity is limited by quantum noise, radio wave sensing based on Rydberg atoms has the potential to replace its traditional counterparts with higher sensitivity and has developed rapidly in recent years. However, as the most sensitive atomic radio wave sensor, the atomic superheterodyne receiver lacks a detailed noise analysis to pa

Sara Fraschini

This thesis aims at investigating the first steps toward an unconditionally stable space-time isogeometric method, based on splines of maximal regularity, for the linear acoustic wave equation. The unconditional stability of space-time discretizations for wave propagation problems is a topic of significant interest, by virtue of the advantages of space-time

Amit Puri, John Jose, Tamarapalli Venkatesh

Memory disaggregation is being considered as a strong alternative to traditional architecture to deal with the memory under-utilization in data centers. Disaggregated memory can adapt to dynamically changing memory requirements for the data center applications like data analytics, big data, etc., that require in-memory processing. However, such systems can f

Juyeon Heo, Vihari Piratla, Matthew Wicker, Adrian Weller

Machine learning from explanations (MLX) is an approach to learning that uses human-provided explanations of relevant or irrelevant features for each input to ensure that model predictions are right for the right reasons. Existing MLX approaches rely on local model interpretation methods and require strong model smoothing to align model and human explanation

Chenjie Cao, Xinlin Ren, Xiangyang Xue, Yanwei Fu

GigaMVS presents several challenges to existing Multi-View Stereo (MVS) algorithms for its large scale, complex occlusions, and gigapixel images. To address these problems, we first apply one of the state-of-the-art learning-based MVS methods, --MVSFormer, to overcome intractable scenarios such as textureless and reflections regions suffered by traditional P

S. Mabrouk, O. Ncib, S. Sendi, S. Silvestrov

The purpose of this paper is to study pseudo-Euclidean and symplectic Hom-alternative superalgebras and discuss some of their proprieties and provide construction procedures. We also introduce the notion of Rota-Baxter operators of pseudo-Euclidean Hom-alternative superalgebras of any weight and Hom-post-alternative superalgebras. A Hom-post-alternative supe

Ananda Hota, Pratik Dabhade, Sravani Vaddi

Minkowski's Object and 'Death Star galaxy' are two of the famous cases of rare instances when a radio jet has been observed to directly hit a neighbouring galaxy. RAD12, the RAD@home citizen science discovery with GMRT being presented here, is not only a new system being added to nearly half a dozen rare cases known so far but also the first case where the n

Andrea Davini, Elena Kosygina, Atilla Yilmaz

We prove homogenization for viscous Hamilton-Jacobi equations with a Hamiltonian of the form $G(p)+V(x,\omega)$ for a wide class of stationary ergodic random media in one space dimension. The momentum part $G(p)$ of the Hamiltonian is a general (nonconvex) continuous function with superlinear growth at infinity, and the potential $V(x,\omega)$ is bounded and

Jules White, Sam Hays, Quchen Fu, Jesse Spencer-Smith

This paper presents prompt design techniques for software engineering, in the form of patterns, to solve common problems when using large language models (LLMs), such as ChatGPT to automate common software engineering activities, such as ensuring code is decoupled from third-party libraries and simulating a web application API before it is implemented. This

Zhongmin Shen, Runzhong Zhao

The flag curvature is a natural Finsler extension of the sectional curvature in Riemannian geometry. However, there are many non-Riemannian quantities which interact with the flag curvature. In this paper, we introduce a notion of weighted flag curvature by modifying the flag curvature using the non-Riemannian quantity, $T$-curvature. We show that a forward

Santiago Price Torrendell, Yang Chen, Hideki Kadone, Modar Hassan

Nonsurgical treatment of Dropped Head Syndrome (DHS) incurs the use of collar-type orthoses that immobilize the neck and cause discomfort and sores under the chin. Articulated orthoses have the potential to support the head posture while allowing partial mobility of the neck and reduced discomfort and sores. This work presents the design, modeling, developme

Céline Bonnet

In this article, we will see a new approach to study the impact of a small microscopic population of cancer cells on a macroscopic population of healthy cells, with an example inspired by pathological hematopoiesis. Hematopoiesis is the biological phenomenon of blood cells production by differentiation of cells called hematopoietic stem cells (HSCs). We will

Hongbiao Zhu, Qiong Wu, Qiang Fan, Pingyi Fan

Multi-input multi-out and non-orthogonal multiple access (MIMO-NOMA) internet-of-things (IoT) systems can improve channel capacity and spectrum efficiency distinctly to support the real-time applications. Age of information (AoI) is an important metric for real-time application, but there is no literature have minimized AoI of the MIMO-NOMA IoT system, which

Xuhang Chen, Baiying Lei, Chi-Man Pun, Shuqiang Wang

Brain network analysis is essential for diagnosing and intervention for Alzheimer's disease (AD). However, previous research relied primarily on specific time-consuming and subjective toolkits. Only few tools can obtain the structural brain networks from brain diffusion tensor images (DTI). In this paper, we propose a diffusion based end-to-end brain network

Manav Raj, Justin Berg, Rob Seamans

The emergence of generative AI technologies, such as OpenAI's ChatGPT chatbot, has expanded the scope of tasks that AI tools can accomplish and enabled AI-generated creative content. In this study, we explore how disclosure regarding the use of AI in the creation of creative content affects human evaluation of such content. In a series of pre-registered expe

Lorenzo Valentini, Marco Chiani

In computer system buses, most of the energy is spent to change the voltage of each line from high to low or vice versa. Bus encoding schemes aim to improve energy efficiency by limiting the number of transitions between successive uses of the bus. We propose an implementation of the optimal code with reduced number of clock cycles.

Peter Ebenfelt, Ming Xiao, Hang Xu

This paper concerns obstruction flatness of hypersurfaces $\Sigma$ that arise as unit sphere bundles $S(E)$ of Griffiths negative Hermitian vector bundles $(E, h)$ over K\"ahler manifolds $(M, g).$ We prove that if the curvature of $(E, h)$ satisfies a splitting condition and $(M,g)$ has constant Ricci eigenvalues, then $S(E)$ is obstruction flat. If, in add

Hitesh Raju, Ankit Sharma, Aoife Smeaton, Alan F. Smeaton

Epilepsy or the occurrence of epileptic seizures, is one of the world's most well-known neurological disorders affecting millions of people. Seizures mostly occur due to non-coordinated electrical discharges in the human brain and may cause damage, including collapse and loss of consciousness. If the onset of a seizure can be forecast then the subject can be

Tamás Csernák

A coloring of a direct product of graphs is said to be {\em trivial} iff it is induced by some coloring of a factor of the product. A graph $G$ is trivially power colorable iff every coloring of a finite power of $G$ with $\chi(G)$-many colors is trivial. Greenwell and Lov\'asz proved that the finite complete graphs $K_n$ for $n\ge 3$ are trivially power col

Massimiliano Sassoli de Bianchi

The phenomenon of quantum tunneling remains a fascinating and enigmatic one, defying classical notions of particle behavior. This paper presents a novel theoretical investigation of the tunneling phenomenon, from the viewpoint of Hartman effect, showing that the classical concept of spatiality is transcended during tunneling, since one cannot describe the pr

Yu. M. Poluektov, A. A. Soroka

In the framework of the theoretical model of the phase transition of binary solutions into spatially inhomogeneous states proposed earlier by the autors [1], which takes into account nonlinear effects, the role of the cubic in concentration term in the expansion of free energy was studied. It is shown that taking into account the cubic term contributions to

Jiayao Sun, Dawei Luo, Zhaoxia Li, Jindong Li

This paper introduces the SWANT team entry to the ICASSP 2023 AEC Challenge. We submit a system that cascades a linear filter with a neural post-filter. Particularly, we adopt sub-band processing to handle full-band signals and shape the network with multi-task learning, where dual signal voice activity detection (DSVAD) and echo estimation are adopted as au

Folkert K. de Vries, Sergey Slizovskiy, Petar Tomić, Roshan Krishna Kumar

Periodic systems feature the Hofstadter butterfly spectrum produced by Brown--Zak minibands of electrons formed when magnetic field flux through the lattice unit cell is commensurate with flux quantum and manifested by magneto-transport oscillations. Quantum oscillations, such as Shubnikov -- de Haas effect and Aharonov--Bohm effect, are also characteristic

A. Boeschoten, V. R. Marshall, T. B. Meijknecht, A. Touwen

We demonstrate a spin-precession method to observe and analyze multi-level coherence between all hyperfine levels in the $X ^2\Sigma^+,N=0$ ground state of barium monofluoride ($^{138}$Ba$^{19}$F). The signal is sensitive to the state-preparation Rabi frequency and external electric and magnetic fields applied in searches for a permanent electric dipole mome

Siyu Lv, Jie Xiong, Wen Xu

This paper is concerned with a partially observed hybrid optimal control problem, where continuous dynamics and discrete events coexist and in particular, the continuous dynamics can be observed while the discrete events, described by a Markov chain, is not directly available. Such kind of problem is first considered in the literature and has wide applicatio

Jerzy Cioslowski, Christian Schilling, Rolf Schilling

The leading terms in the large-$R$ asymptotics of the functional of the one-electron reduced density matrix for the ground-state energy of the H$_2$ molecule with the internuclear separation $R$ is derived thanks to the solution of the phase dilemma at the $R \to \infty$ limit. At this limit, the respective natural orbitals (NOs) are given by symmetric and a

Milind B. Naik, Devendra K. Ojha, Saurabh Sharma, Shailesh B. Bhagat

The TIFR Near Infrared Imaging Camera-II (TIRCAM2) is being used at the Devasthal Optical Telescope (DOT) operated by Aryabhatta Research Institute of Observational Sciences (ARIES), Nainital, Uttarakhand, India. In addition to the normal full frame observations, there has been a requirement for high speed sub-array observations for applications such as luna

Adrien Corenflos, Hany Abdulsamad

We present a novel approach to approximate Gaussian and mixture-of-Gaussians filtering. Our method relies on a variational approximation via a gradient-flow representation. The gradient flow is derived from a Kullback--Leibler discrepancy minimization on the space of probability distributions equipped with the Wasserstein metric. We outline the general metho

Norbert Hauck

A first solution for the eclipsing binary TYC 4481-358-1 has been found by combining the results of BVIc-photometry with known stellar models and stellar spectral energy distributions (SEDs). The binary shows total and annular eclipses in a circular 90-days orbit. Masses, radii and effective temperatures have been derived: about 3.01 Msun, 14.29 Rsun and 495

Abhishek Sinha, Ativ Joshi, Rajarshi Bhattacharjee, Cameron Musco

We consider a fair resource allocation problem in the no-regret setting against an unrestricted adversary. The objective is to allocate resources equitably among several agents in an online fashion so that the difference of the aggregate $\alpha$-fair utilities of the agents between an optimal static clairvoyant allocation and that of the online policy grows

Debdarsan Niyogi

A univariate time series with high variability can pose a challenge even to Deep Neural Network (DNN). To overcome this, a univariate time series is decomposed into simpler constituent series, whose sum equals the original series. As demonstrated in this article, the conventional one-time decomposition technique suffers from a leak of information from the fu

Chengdong Li, Arnaud Siebert, Giacomo Monari, Benoit Famaey

Disc stars from the Gaia DR3 RVS catalogue are selected to explore the phase spiral as a function of position in the Galaxy. The data reveal a two-armed phase spiral pattern in the local $z-v_z$ plane inside the solar radius, which appears clearly when colour-coded by $\langle v_R \rangle (z,v_z)$: this is characteristic of a breathing mode that can in princ

Christian Günther, Bahareh Khazayel, Christiane Tammer

In this paper, we derive some new results for the separation of two not necessarily convex cones by a (convex) cone / conical surface in real (reflexive) normed spaces. In essence, we follow the nonlinear and nonsymmetric separation approach developed by Kasimbeyli (2010, SIAM J. Optim. 20), which is based on augmented dual cones and Bishop-Phelps type (norm

Yuxuan Shi, Shuo Shao, Yongpeng Wu, Jun Chen

A novel distributed source coding model which named semantic-aware multi-terminal (MT) source coding is proposed and investigated in the paper, where multiple agents independently encode an imperceptible semantic source, while both semantic and observations are reconstructed within their respective fidelity criteria. We start from a generalized single-letter

E G Kostadinova, Shannon Greco, Maajida Murdock, Ernesto Barraza-Valdez

This report is a summary of the mini-conference Workforce Development Through Research-Based, Plasma-Focused Science Education and Public Engagement held during the 2022 American Physical Society Division of Plasma Physics (APS DPP) annual meeting. The motivation for organizing this mini-conference originates from recent studies and community-based reports h

Xiaoying Zhang, Junpu Chen, Hongning Wang, Hong Xie

Off-policy learning, referring to the procedure of policy optimization with access only to logged feedback data, has shown importance in various real-world applications, such as search engines, recommender systems, and etc. While the ground-truth logging policy, which generates the logged data, is usually unknown, previous work simply takes its estimated val

Kangcheng Liu, Xinhu Zheng, Chaoqun Wang, Kai Tang

Contrastive learning has recently demonstrated great potential for unsupervised pre-training in 3D scene understanding tasks. However, most existing work randomly selects point features as anchors while building contrast, leading to a clear bias toward background points that often dominate in 3D scenes. Also, object awareness and foreground-to-background dis

Anil Kumar, Vivek Baruah Thapa, Monika Sinha

Compact stars (CS) are stellar remnants of massive stars. Inside CSs the density is so high that matter is in subatomic form composed of nucleons. With increase of density of matter towards the centre of the objects other degrees of freedom like hyperons, heavier non-strange baryons, meson condensates may appear. Not only that at higher densities, the nucleo

Yixuan Zhu, Luke J. W. Canham, David Western

A key task in clinical EEG interpretation is to classify a recording or session as normal or abnormal. In machine learning approaches to this task, recordings are typically divided into shorter windows for practical reasons, and these windows inherit the label of their parent recording. We hypothesised that window labels derived in this manner can be mislead

Alexander Montoya Ocampo, Fernando Szechtman

Given positive integers $p$ and $m$, where $p$ is assumed to be an odd prime, we determine the automorphism groups of $p$-groups $J$, $H$, and $K$ of orders $p^{7m}$, $p^{6m}$, and $p^{5m}$, and nilpotency classes 5, 4, and 3, respectively, all of which arise naturally from the Macdonald group $\langle x,y\,|\, x^{[x,y]}=x^{1+p^m\ell},\, y^{[y,x]}=y^{1+p^m\e

Paolo Victor Redondo, Raphael Huser, Hernando Ombao

Brain connectivity characterizes interactions between different regions of a brain network during resting-state or performance of a cognitive task. In studying brain signals such as electroencephalograms (EEG), one formal approach to investigating connectivity is through an information-theoretic causal measure called transfer entropy (TE). To enhance the fun

N. Belousov, S. Derkachov, S. Kharchev, S. Khoroshkin

We present and prove hypergeometric identities which play a crucial role in the theory of Baxter operators in the Ruijsenaars model.

N. Belousov, S. Derkachov, S. Kharchev, S. Khoroshkin

We introduce Baxter Q-operators for the quantum Ruijsenaars hyperbolic system. We prove that they represent a commuting family of integral operators and also commute with Macdonald difference operators, which are gauge equivalent to the Ruijsenaars Hamiltonians of the quantum system. The proof of commutativity of the Baxter operators uses a hypergeometric id

N. Belousov, S. Derkachov, S. Kharchev, S. Khoroshkin

In the previous paper we introduced a commuting family of Baxter Q-operators for the quantum Ruijsenaars hyperbolic system. In the present work we show that the wave functions of the quantum system found by M. Halln\"as and S. Ruijsenaars also diagonalize Baxter operators. Using this property we prove the conjectured duality relation for the wave function. A

R. S. Prasobh Sankar, Sidharth S. Nair, Siddhant Doshi, Sundeep Prabhakar Chepuri

In this paper, we present an unsupervised learning neural model to design transmit precoders for integrated sensing and communication (ISAC) systems to maximize the worst-case target illumination power while ensuring a minimum signal-to-interference-plus-noise ratio (SINR) for all the users. The problem of learning transmit precoders from uplink pilots and e

Zimeng Zhao, Binghui Zuo, Zhiyu Long, Yangang Wang

Enormous hand images with reliable annotations are collected through marker-based MoCap. Unfortunately, degradations caused by markers limit their application in hand appearance reconstruction. A clear appearance recovery insight is an image-to-image translation trained with unpaired data. However, most frameworks fail because there exists structure inconsis

Weiming Xu, Zhihao Guo

This paper describes aecX team's entry to the ICASSP 2023 acoustic echo cancellation (AEC) challenge. Our system consists of an adaptive filter and a proposed full-band Taylor-style acoustic echo cancellation neural network (TaylorAECNet) as a post-filter. Specifically, we leverage the recent advances in Taylor expansion based decoupling-style interpretable

Teng Wang, Jinrui Zhang, Feng Zheng, Wenhao Jiang

Joint video-language learning has received increasing attention in recent years. However, existing works mainly focus on single or multiple trimmed video clips (events), which makes human-annotated event boundaries necessary during inference. To break away from the ties, we propose a grounded vision-language learning framework for untrimmed videos, which aut

Shanjun Mao, Xiaodan Fan, Jie Hu

The magnitude of Pearson correlation between two scalar random variables can be visually judged from the two-dimensional scatter plot of an independent and identically distributed sample drawn from the joint distribution of the two variables: the closer the points lie to a straight slanting line, the greater the correlation. To the best of our knowledge, sim

Anna Kurbatskaya, Alberto Jaramillo-Jimenez, John Fredy Ochoa-Gomez, Kolbjørn Brønnick

As the number of automatic tools based on machine learning (ML) and resting-state electroencephalography (rs-EEG) for Parkinson's disease (PD) detection keeps growing, the assessment of possible exacerbation of health disparities by means of fairness and bias analysis becomes more relevant. Protected attributes, such as gender, play an important role in PD d

Linda Albanese, Andrea Alessandrelli, Adriano Barra, Alessia Annibale

In this work we present a rigorous and straightforward method to detect the onset of the instability of replica-symmetric theories in information processing systems, which does not require a full replica analysis as in the method originally proposed by de Almeida and Thouless for spin glasses. The method is based on an expansion of the free-energy obtained w

Gaber Faisel, S. Khalil

Direct CP asymmetry in semi-leptonic $\tau$ decays is an intriguing hint for new physics beyond the standard model. We investigate the CP asymmetry in $\tau^- \to K_S^0 \pi^- \nu_\tau$ and $\tau^- \to K^- \pi^0 \nu_\tau$ decays in non-minimal SU(5) model, with 45-dimensional Higgs multiplet. We show that the associate color-triplet scalar is a natural exampl

Zheng Chen, Yulun Zhang, Jinjin Gu, Linghe Kong

Transformer architectures have exhibited remarkable performance in image super-resolution (SR). Since the quadratic computational complexity of the self-attention (SA) in Transformer, existing methods tend to adopt SA in a local region to reduce overheads. However, the local design restricts the global context exploitation, which is crucial for accurate imag

Vu Nguyen Ha, Eva Lagunas, Tedros Salih Abdu, Haythem Chaker

This paper presents a centralized framework for optimizing the joint design of beam placement, power, and bandwidth allocation in an MEO satellite constellation to fulfill the heterogeneous traffic demands of a large number of global users. The problem is formulated as a mixed integer programming problem, which is computationally complex in large-scale syste

Zhuchen Shao, Liuxi Dai, Yifeng Wang, Haoqian Wang

Multiple Instance Learning (MIL), a powerful strategy for weakly supervised learning, is able to perform various prediction tasks on gigapixel Whole Slide Images (WSIs). However, the tens of thousands of patches in WSIs usually incur a vast computational burden for image augmentation, limiting the MIL model's improvement in performance. Currently, the featur

Stevo Racković, Cláudia Soares, Dušan Jakovetić

The problem of rig inversion is central in facial animation as it allows for a realistic and appealing performance of avatars. With the increasing complexity of modern blendshape models, execution times increase beyond practically feasible solutions. A possible approach towards a faster solution is clustering, which exploits the spacial nature of the face, l

Evgeny Reznichenko

Lindel\"of topological groups $G_1$ , $H_1$, $G_2$, $H_2$ are constructed in such a way that the products of $G_1 \times H_1$ and $G_2 \times H_2$ are not $\mathbb R$-factorizable groups and (1) the group $G_1 \times H_1$ is not pseudo-$\aleph_1$-compact; (2) the group $G_2 \times H_2$ is a separable not normal group and contains a discrete closed subset of

Shanjun Mao, Xiaodan Fan

Alzheimer's disease (AD) is a serious neurodegenerative disease consisting of four stages where the illness gets progressively worse. It is of great significance to detect the gene regulatory mechanism as AD progresses and, thus, to help us better understand the causes of AD and find ways to treat or control AD. There are numerous researches to conduct this

Markus Frey, Christian F. Doeller, Caswell Barry

Deep artificial neural networks (DNNs) trained through backpropagation provide effective models of the mammalian visual system, accurately capturing the hierarchy of neural responses through primary visual cortex to inferior temporal cortex (IT). However, the ability of these networks to explain representations in higher cortical areas is relatively lacking

Ina K. B. Kullmann

A long-standing scientific puzzle has been to explain the origin of the heaviest elements in the Universe and, more particularly, the production of the elements heavier than iron up to uranium. The rapid neutron capture process (or r-process) is known to synthesize about 50\% of these heavy elements and the long-lived actinides observed in our solar system a

Johanna Vielhaben, Sebastian Lapuschkin, Grégoire Montavon, Wojciech Samek

The field of eXplainable Artificial Intelligence (XAI) has greatly advanced in recent years, but progress has mainly been made in computer vision and natural language processing. For time series, where the input is often not interpretable, only limited research on XAI is available. In this work, we put forward a virtual inspection layer, that transforms the

Kazuo Ghoroku, Kouji Kashiwa, Yoshimasa Nakano, Motoi Tachibana

We study a holographic model of quantum chromodynamics, which can describe a color superconductor and a dilute nucleon gas phase. The two phases are adjoined in the phase diagram at a critical value of the chemical potential. In other words, a first-order transition from the ordinary nucleon gas to the color superconductor is found by increasing the chemical

Otto Chkhetiani, Michael Kurgansky

An overview is given of the helicity of the velocity field (``kinetic'' helicity to distinguish it from the ``magnetic'' helicity used in magnetohydrodynamics, astrophysics, and solar physics; or simply \emph{helicity} in this Chapter) and of the role, which this concept plays in the modern research in atmospheric physics and atmospheric turbulence. General

Rūta Juozaitienė, Hanno Seebens, Guillaume Latombe, Franz Essl

Aim: Spatio-temporal processes play a key role in ecology, from genes to large-scale macroecological and biogeographical processes. Existing methods studying such spatio-temporally structured data either simplify the dynamic structure or the complex interactions of ecological drivers. This paper aims to present a generic method for ecological research that a

Tiankuo Wei, Sicong Liu

Visible light positioning (VLP) has drawn plenty of attention as a promising indoor positioning technique. However, in nonstationary environments, the performance of VLP is limited because of the highly time-varying channels. To improve the positioning accuracy and generalization capability in nonstationary environments, a cooperative VLP scheme based on fed

Zheqi Zhu, Yuchen Shi, Jiajun Luo, Fei Wang

Federated learning (FL) has prevailed as an efficient and privacy-preserved scheme for distributed learning. In this work, we mainly focus on the optimization of computation and communication in FL from a view of pruning. By adopting layer-wise pruning in local training and federated updating, we formulate an explicit FL pruning framework, FedLP (Federated L

Dal-Ho Moon, Vivek Chavan, Vasant Bhoraskar, Yeong Hoon Jeong

A thin coating of thorium on aluminium substrates with the areal density of 110 to 130 $\mu g/cm^2$ is developed over a circular area of 22 mm diameter by using the electrodeposition method. An electrodeposition system is fabricated to consist of three components; an anode made of a platinum mesh, a cylindrical-shape vessel to contain the thorium solution, a

Li Sun, Xianhui Lu, Peng Liu, Jianjun Wu

The rapid development of advanced computing technologies such as quantum computing imposes new challenges to current wireless security mechanism which is based on cryptographic approaches. To deal with various attacks and realize long-lasting security, we are in urgent need of disruptive security solutions. In this article, novel security transmission paradi

Jun Li, Kexin Li, Yafeng Zhou, S. Kevin Zhou

Targeted diagnosis and treatment plans for patients with coronary artery disease vary according to atherosclerotic plaque component. Coronary CT angiography (CCTA) is widely used for artery imaging and determining the stenosis degree. However, the limited spatial resolution and susceptibility to artifacts fail CCTA in obtaining lumen morphological characteri

Junwen Xiong, Ganglai Wang, Peng Zhang, Wei Huang

Incorporating the audio stream enables Video Saliency Prediction (VSP) to imitate the selective attention mechanism of human brain. By focusing on the benefits of joint auditory and visual information, most VSP methods are capable of exploiting semantic correlation between vision and audio modalities but ignoring the negative effects due to the temporal inco