May 2023 arXiv papers — page 143

Jintao Huang, Ningyu He, Kai Ma, Jiang Xiao

NFT rug pull is one of the most prominent type of scam that the developers of a project abandon it and then run away with investors' funds. Although they have drawn attention from our community, to the best of our knowledge, the NFT rug pulls have not been systematically explored. To fill the void, this paper presents the first in-depth study of NFT rug pull

Karin Ikeda

In this paper, we present results on the uniqueness of the real zeros of the Hurwitz zeta function in given intervals. The uniqueness in question, if the zeros exist, has already been proved for the intervals $(0,1)$ and $(-N, -N+1)$ for $N \geq 5$ by Endo-Suzuki and Matsusaka respectively. We prove the uniqueness of the real zeros in the remaining intervals

Nawin Ngampoopun, David M. Long, Deborah Baker, Lucie M. Green

We report on the merging between the southern polar coronal hole and an adjacent coronal dimming induced by a coronal mass ejection on 2022 March 18, resulting in the merged region persisting for at least 72 hrs. We use remote sensing data from multiple co-observing spacecraft to understand the physical processes during this merging event. The evolution of t

He Gu, Thomas Plagemann, Maik Benndorf, Vera Goebel

Complex event processing (CEP) is a powerful and increasingly more important tool to analyse data streams for Internet of Things (IoT) applications. These data streams often contain private information that requires proper protection. However, privacy protection in CEP systems is still in its infancy, and most existing privacy-preserving mechanisms (PPMs) ar

Jiyao Wei, Saiping Guan, Xiaolong Jin, Jiafeng Guo

Hyper-relational facts, which consist of a primary triple (head entity, relation, tail entity) and auxiliary attribute-value pairs, are widely present in real-world Knowledge Graphs (KGs). Link Prediction on Hyper-relational Facts (LPHFs) is to predict a missing element in a hyper-relational fact, which helps populate and enrich KGs. However, existing LPHFs

Zhe Liu, Yingjie Zhang, Shenyang Huang, Xue Ming

The pressure-induced color change in the nitrogen-doped lutetium hydride has triggered extensive discussions about the underlying physics. Here, we study the optical response of LuH$_{2 \pm x}$N$_{y}$ in a broad frequency range at ambient pressure and its evolution with pressure in the visible spectral range. The broad-band optical spectra at ambient pressur

Mingqi Yang, Wenjie Feng, Yanming Shen, Bryan Hooi

Proposing an effective and flexible matrix to represent a graph is a fundamental challenge that has been explored from multiple perspectives, e.g., filtering in Graph Fourier Transforms. In this work, we develop a novel and general framework which unifies many existing GNN models from the view of parameterized decomposition and filtering, and show how it hel

Vinayak Ramkumar, Netanel Raviv, Itzhak Tamo

Linear real-valued computations over distributed datasets are common in many applications, most notably as part of machine learning inference. In particular, linear computations that are quantized, i.e., where the coefficients are restricted to a predetermined set of values (such as $\pm 1$), have gained increasing interest lately due to their role in effici

Orkash Amat, Li-Na Hu, Mamat Ali Bake, Melike Mohamedsedik

Effect of spatially oscillating fields on the electron-positron pair production is studied numerically and analytically when the work done by the electric field over its spatial extent is smaller than twice the electron mass. Under large spatial scale, we further explain the characteristics of the position and momentum distribution via tunneling time, tunnel

Long Ma, Kai Lu, Tianbo Che, Hailong Huang

The MultiCoNER II task aims to detect complex, ambiguous, and fine-grained named entities in low-context situations and noisy scenarios like the presence of spelling mistakes and typos for multiple languages. The task poses significant challenges due to the scarcity of contextual information, the high granularity of the entities(up to 33 classes), and the in

Slađan Jelić, Dušan Zorica

Relaxation modulus and creep compliance corresponding to fractional anti-Zener and Zener models are calculated and restrictions on model parameters narrowing thermodynamical constraints are posed in order to ensure relaxation modulus and creep compliance to be completely monotone and Bernstein function respectively, that a priori guarantee the positivity of

Yao-Kun Wang, Rui-Xin Chen, Li-Zhu Ge, Shao-Ming Fei

Originated from the work extraction in quantum systems coupled to a heat bath, quantum deficit is a kind of significant quantum correlations like quantum entanglement. It links quantum thermodynamics with quantum information. We analytically calculate the one-way deficit of the generalized $n$-qubit Werner state. We find that the one-way deficit increases as

Erlend Grong, Irina Markina

We define harmonic maps between sub-Riemannian manifolds by generalizing known definitions for Riemannian manifolds. We establish conditions for when a horizontal map into a Lie group with a left-invariant metric structure is a harmonic map. We show that sub-Riemannian harmonic maps can be abnormal or normal, just as sub-Riemannian geodesics. We illustrate o

Victor Bittencourt, Massimo Blasone, Silvio De Siena, Cristina Matrella

We characterize quantum correlations encoded in a three-flavor oscillating neutrino system by using both plane-wave and wave-packet approach. By means of the Complete Complementarity Relations we study the trade off of predictability, local coherence and non local correlations in terms of the relevant parameters, chosen from recent neutrino experiments. Alth

Iris Berent, Alexzander Sansiveri

A large literature suggests that people are intuitive Dualists--they consider the mind ethereal, distinct from the body. Past research also shows that Dualism emerges, in part, via learning (e.g., Barlev & Shtulman, 2021). But whether learning is sufficient to give rise to Dualism is unknown.The evidence from human learners does address this question because

William Tholke

From the earliest experiments in the 20th century to the utilization of large language models and transformers, dialogue systems research has continued to evolve, playing crucial roles in numerous fields. This paper offers a comprehensive review of these systems, tracing their historical development and examining their fundamental operations. We analyze popu

Bowen Gu, Hao Xie, Dong Li

This letter proposes a new user cooperative offloading protocol called user reciprocity in backscatter communication (BackCom)-aided mobile edge computing systems with efficient computation, whose quintessence is that each user can switch alternately between the active or the BackCom mode in different slots, and one user works in the active mode and the othe

Azimkhon Ostonov, Mikhail Moshkov

In this paper, we consider classes of decision tables with 0-1-decisions closed relative to removal of attributes (columns) and changing decisions assigned to rows. For tables from an arbitrary closed class, we study the dependence of the minimum complexity of deterministic decision trees on various parameters of the tables: the minimum complexity of a test,

Federico Cassano, Charles Bershatsky, Jacob Ginesin, Sasha Bashenko

Memory safety is a cornerstone of secure and robust software systems, as it prevents a wide range of vulnerabilities and exploitation techniques. Among these, we focus on Return-Oriented Programming (ROP). ROP works as such: the attacker takes control of the program's execution flow via a memory corruption attack, then takes advantages of code snippets alrea

M. V. Cheremisin

We investigate the dark axisymmetric plasmon spectrum for partially gated two-dimensional gas of the disk shape. The extension of the central gate spot provides a change in plasmon dispersion from the root to a linear dependence on the wave vector. Intriguingly, the interaction between neighboring modes occurs because of stepwise change in carrier screening

Bingzhao Zhu, Xingjian Shi, Nick Erickson, Mu Li

The success of self-supervised learning in computer vision and natural language processing has motivated pretraining methods on tabular data. However, most existing tabular self-supervised learning models fail to leverage information across multiple data tables and cannot generalize to new tables. In this work, we introduce XTab, a framework for cross-table

José Rodríguez, Abraham Rueda Zoca

We give a sufficient condition for a pair of Banach spaces $(X,Y)$ to have the following property: whenever $W_1 \subseteq X$ and $W_2 \subseteq Y$ are sets such that $\{x\otimes y: \, x\in W_1, \, y\in W_2\}$ is weakly precompact in the projective tensor product $X \widehat{\otimes}_\pi Y$, then either $W_1$ or $W_2$ is relatively norm compact. For instance

Simone Bocca, Alessio Zamboni, Gabor Bella, Yamini Chandrashekar

When building a new application we are increasingly confronted with the need of reusing and integrating pre-existing knowledge. Nevertheless, it is a fact that this prior knowledge is virtually impossible to reuse as-is. This is true also in domains, e.g., eHealth, where a lot of effort has been put into developing high-quality standards and reference ontolo

Frank Joublin, Antonello Ceravola, Joerg Deigmoeller, Michael Gienger

Large language models (LLMs) have recently become a popular topic in the field of Artificial Intelligence (AI) research, with companies such as Google, Amazon, Facebook, Amazon, Tesla, and Apple (GAFA) investing heavily in their development. These models are trained on massive amounts of data and can be used for a wide range of tasks, including language tran

Haozhe Kong, Huasheng Xie, Bing Liu, Muzhi Tan

Non-Maxwellian distributions of particles are commonly observed in fusion studies, especially for magnetic confinement fusion plasmas. The particle distribution has a direct effect on fusion reactivity, which is the focus of this study. We investigate the effects of three types of non-Maxwellian distributions, namely drift-ring-beam, slowing-down, and kappa

Wenyuan Yang, Gongxi Zhu, Yuguo Yin, Hanlin Gu

Federated learning allows multiple parties to collaborate in learning a global model without revealing private data. The high cost of training and the significant value of the global model necessitates the need for ownership verification of federated learning. However, the existing ownership verification schemes in federated learning suffer from several limi

Ching-Chen Yeh, Thi-Hien Do, Pin-Chi Liao, Chia-Hung Hsu

Superconducting properties of thin films can be vastly different from those of bulk materials. Seminal work has shown the critical temperature Tc of elemental superconductors decreases with decreasing film thickness when the normal-state sheet resistance is lower than the quantum resistance h/(4e2). Sporadic examples on disordered films, however, hinted an e

Hua Sun, Hui-Xiang Chen, Yinhuo Zhang

In this paper, we study the representation theory of the small quantum group $\overline{U}_q$ and the small quasi-quantum group $\widetilde{U}_q$, where $q$ is a primitive $n$-th root of unity and $n>2$ is odd. All finite dimensional indecomposable $\widetilde{U}_q$-modules are described and classified. Moreover, the decomposition rules for the tensor produc

Kota Srinivas Reddy, P. N. Karthik, Nikhil Karamchandani, Jayakrishnan Nair

We study best arm identification in a variant of the multi-armed bandit problem where the learner has limited precision in arm selection. The learner can only sample arms via certain exploration bundles, which we refer to as boxes. In particular, at each sampling epoch, the learner selects a box, which in turn causes an arm to get pulled as per a box-specifi

Matti Würthen

Let $\mathcal{X}$ be a smooth $p$-adic formal scheme over a mixed characteristic complete discrete valuation ring $\mathcal{O}_{K}$ with perfect residue field. We introduce a general category $\mathcal{M}\mathcal{F}_{[0, p-2]}^{tor-free}(\mathcal{X})$ of $p$-torsion free crystalline coefficient objects and show that this category is equivalent to the categor

Thanveer Shaik, Xiaohui Tao, Haoran Xie, Lin Li

Machine unlearning (MU) is gaining increasing attention due to the need to remove or modify predictions made by machine learning (ML) models. While training models have become more efficient and accurate, the importance of unlearning previously learned information has become increasingly significant in fields such as privacy, security, and fairness. This pap

Shiyu Xia, Jiaqi Lv, Ning Xu, Gang Niu

Under partial-label learning (PLL) where, for each training instance, only a set of ambiguous candidate labels containing the unknown true label is accessible, contrastive learning has recently boosted the performance of PLL on vision tasks, attributed to representations learned by contrasting the same/different classes of entities. Without access to true la

N. F. Allard, K. Myneni, J. N. Blakely, G. Guillon

Ultracool stellar atmospheres show absorption by alkali resonance lines severely broadened by collisions with neutral perturbers. In the coolest and densest atmospheres, such as those of T dwarfs, Na I and K I broadened by molecular hydrogen and helium can come to dominate the entire optical spectrum. The effects of NaHe collision broadening are also central

Camille Jorge, Amélie Chardac, Alexis Poncet, Denis Bartolo

Viscous flows are laminar and deterministic. Robust linear laws accurately predict their streamlines in structures as complex as blood vessels, porous media and pipe networks. However, biological and synthetic active fluids defy these fundamental laws. Irrespective of their microscopic origin, confined active flows are intrinsically bistable, and therefore n

Foivos Paraperas Papantoniou, Alexandros Lattas, Stylianos Moschoglou, Stefanos Zafeiriou

Following the remarkable success of diffusion models on image generation, recent works have also demonstrated their impressive ability to address a number of inverse problems in an unsupervised way, by properly constraining the sampling process based on a conditioning input. Motivated by this, in this paper, we present the first approach to use diffusion mod

Samantha E. Clark, Ruth Etzioni, Jerry Radich, Zachary Marcum

Objective To assess the price elasticity of branded imatinib in chronic myeloid leukemia (CML) patients on Medicare Part D to determine if high out-of-pocket payments (OOP) are driving the substantial levels of non-adherence observed in this population. Data sources and study setting We use data from the TriNetX Diamond Network (TDN) United States database f

Mario Román, Paweł Sobociński

Premonoidal categories are monoidal categories without the interchange law while effectful categories are premonoidal categories with a chosen monoidal subcategory of interchanging morphisms. In the same sense that string diagrams, pioneered by Joyal and Street, are an internal language for monoidal categories, we show that string diagrams with an added "run

Nikolas Vitsakis, Amit Parekh, Tanvi Dinkar, Gavin Abercrombie

There are two competing approaches for modelling annotator disagreement: distributional soft-labelling approaches (which aim to capture the level of disagreement) or modelling perspectives of individual annotators or groups thereof. We adapt a multi-task architecture -- which has previously shown success in modelling perspectives -- to evaluate its performan

Jean-Pierre Luminet

Alexander Friedmann and Georges Lema\^itre are undoubtedly the real fathers of Big Bang cosmologies. In this article I study the influences their work underwent due to some religious as well as anti-religious ideas. During his career Lema\^itre faced criticisms coming from non-believing scientists, who reproached him (wrongly) to have developed his primeval

Ana Budisa, Xiaozhe Hu, Miroslav Kuchta, Kent-Andre Mardal

We develop multilevel methods for interface-driven multiphysics problems that can be coupled across dimensions and where complexity and strength of the interface coupling deteriorates the performance of standard methods. We focus on solvers based on aggregation-based algebraic multigrid methods with custom smoothers that preserve the coupling information on

Said Zriaa, Mohammed Mouçouf

In this work, the authors provide closed forms and recurrence expressions for computing the $k$th power of the formal power series, some of them in terms of a determinant of some matrices. As a consequence, we obtain the reciprocal of the unit of any formal power series. We apply these results to the generalized Bernoulli numbers and Bernoulli numbers, we de

Ilia V. Zalivako, Alexander S. Borisenko, Ilya A. Semerikov, Andrey Korolkov

The use of multilevel quantum information carriers, also known as qudits, attracts a significant deal of interest as a way for further scalability of quantum computing devices. However, a nontrivial task is to experimentally achieve a gain in the efficiency of realizing quantum algorithms with qudits since higher qudit levels typically have relatively short

Zhihui Liu

We analyze the long-time behavior of numerical schemes for a class of monotone stochastic partial differential equations (SPDEs) driven by multiplicative noise. By deriving several time-independent a priori estimates for the numerical solutions, combined with the ergodic theory of Markov processes, we establish the exponential ergodicity of these schemes wit

E. E. Perepelkin, B. I. Sadovnikov, N. G. Inozemtseva, A. A. Korepanova

This paper presents a comprehensive investigation of the problem of a harmonic oscillator with time-depending frequencies in the framework of the Vlasov theory and the Wigner function apparatus for quantum systems in the phase space. A new method is proposed to find an exact solution of this problem using a relation of the Vlasov equation chain with the Schr

Fernando Galaz-García, Philipp Reiser

We express the total space of a principal circle bundle over a connected sum of two manifolds in terms of the total spaces of circle bundles over each summand, provided certain conditions hold. We then apply this result to provide sufficient conditions for the existence of free circle and torus actions on connected sums of products of spheres and obtain a to

Adri Bhattacharya, Barun Gorain, Partha Sarathi Mandal

We study the problem of treasure hunt in a Euclidean plane by a mobile agent with the guidance of pebbles. The initial position of the agent and position of the treasure are modeled as special points in the Euclidean plane. The treasure is situated at a distance at most $D>0$ from the initial position of the agent. The agent has a perfect compass, but an adv

Juan Zou, Cheng Li, Ruoyou Wu, Tingrui Pei

Federated learning (FL) based magnetic resonance (MR) image reconstruction can facilitate learning valuable priors from multi-site institutions without violating patient's privacy for accelerating MR imaging. However, existing methods rely on fully sampled data for collaborative training of the model. The client that only possesses undersampled data can neit

Yagub N. Aliyev

In the paper we discuss Apollonius Problem on the number of normals of an ellipse passing through a given point. It is known that the number is dependent on the position of the given point with respect to a certain astroida. The intersection points of the astroida and the ellipse are used to study the case when the given point is on the ellipse. The problem

Omri Isac, Yoni Zohar, Clark Barrett, Guy Katz

Deep neural networks (DNNs) are increasingly being deployed to perform safety-critical tasks. The opacity of DNNs, which prevents humans from reasoning about them, presents new safety and security challenges. To address these challenges, the verification community has begun developing techniques for rigorously analyzing DNNs, with numerous verification algor

Nikodem Stolarczyk, Piotr Wcisło, Roman Ciurłyo

The speed-dependent spectral line profiles collapse into a simple Lorentz profile in the regime dominated by the velocity-changing collisions. We derive general formulas for the effective width and shift of the Lorentzian for arbitrary speed-dependent collisional broadening and shift and velocity-changing collision operators. For a quadratic speed dependence

Nouhaila Innan, Muhammad Al-Zafar Khan, Biswaranjan Panda, Mohamed Bennai

Quantum machine learning (QML) has witnessed immense progress recently, with quantum support vector machines (QSVMs) emerging as a promising model. This paper focuses on the two existing QSVM methods: quantum kernel SVM (QK-SVM) and quantum variational SVM (QV-SVM). While both have yielded impressive results, we present a novel approach that synergizes the s

Pahulpreet Singh, Indranil Chakrabarty

In this article, we present a benchmark for resource characterization in the process of controlled quantum state reconstruction and secret sharing for general three-qubit states. This is achieved by providing a closed expression for the reconstruction fidelity, which relies on the genuine tripartite correlation and the bipartite channel between the dealer an

Bruce X. B. Yu, Jianlong Chang, Haixin Wang, Lingbo Liu

Fine-tuning visual models has been widely shown promising performance on many downstream visual tasks. With the surprising development of pre-trained visual foundation models, visual tuning jumped out of the standard modus operandi that fine-tunes the whole pre-trained model or just the fully connected layer. Instead, recent advances can achieve superior per

Takahiro Tsushima

For an additive polynomial and a positive integer, we define an irreducible smooth representation of a Weil group of a non-archimedean local field. We study several invariants of this representation. We deduce a necessary and sufficient condition for it to be primitive.

Zhanqiang Bai, Shaoyi Zhang

Let $\mathfrak{g}$ be a simple complex Lie algebra of classical type with a Cartan subalgebra $\mathfrak{h}$. We fix a standard parabolic subalgebra $\mathfrak{p}\supset \mathfrak{h}$. The socular simple modules are just those highest weight modules with largest possible Gelfand-Kirillov dimension in the corresponding parabolic category $\mathcal{O}^{\mathfr

Yong Qing, Ke Li, Peng-Fei Zhou, Shi-Ju Ran

Neural network (NN) designed for challenging machine learning tasks is in general a highly nonlinear mapping that contains massive variational parameters. High complexity of NN, if unbounded or unconstrained, might unpredictably cause severe issues including \R{overfitting}, loss of generalization power, and unbearable cost of hardware. In this work, we prop

K. Sravan Kumar, João Marto

The presence of CMB Hemispherical Asymmetry (HPA) challenges the current understanding of inflationary cosmology which does not generically predict the parity violation in the primordial correlations. In this paper, we shall review the recently proposed resolution to this based on a new formulation of quantizing inflationary fluctuations by focusing on the d

Sreemayee Aditya, Diptiman Sen

We study if the interplay between dynamical localization and interactions in periodically driven quantum systems can give rise to anomalous thermalization behavior. Specifically, we consider one-dimensional models with interacting spinless fermions with nearest-neighbor hopping and density-density interactions, and a periodically driven on-site potential wit

Nicolò Pagan, Joachim Baumann, Ezzat Elokda, Giulia De Pasquale

Prediction-based decision-making systems are becoming increasingly prevalent in various domains. Previous studies have demonstrated that such systems are vulnerable to runaway feedback loops, e.g., when police are repeatedly sent back to the same neighborhoods regardless of the actual rate of criminal activity, which exacerbate existing biases. In practice,

Olivier Benoist

We prove a comparison theorem between the \'etale cohomology of algebraic varieties over Stein compacta and the singular cohomology of their analytifications. We deduce that the field of meromorphic functions in a neighborhood of a connected Stein compact subset of a normal complex space of dimension $n$ has cohomological dimension $n$. As an application of

Roni Muslim, Rinto Anugraha NQZ, Muhammad Ardhi Khalif

With the success of general conceptual frameworks of statistical physics, many scholars have tried to apply these concepts to other interdisciplinary fields, such as socio-politics, economics, biology, medicine, and many more. In this work, we study the effect of mass media on opinion evolution based on the nonlinear $q$-voter by means with probability $p$ a

Athanasios Masouris, Mansi Sharma, Adrian Boguszewski, Alexander Kozlov

Quantization is a widely adopted technique for deep neural networks to reduce the memory and computational resources required. However, when quantized, most models would need a suitable calibration process to keep their performance intact, which requires data from the target domain, such as a fraction of the dataset used in model training and model validatio

Azhari, Roni Muslim

We investigate the external field effect on opinion formation based on the majority rule and $q$-voter models on a complete graph. The external field can be considered as the mass media in the social system, with the probability $p$ agents following the mass media opinion. Based on our Monte Carlo simulation, the mass media effect is not strong enough to mak

Primoz Potocnik, Alejandra Ramos-Rivera, Micael Toledo, Stephen Wilson

A corner in a map is an edge-vertex-edge triple consisting of two distinct edges incident to the same vertex. A corneration is a set of corners that covers every arc of the map exactly once. Cornerations in a dart-transitive map generalize the notion of a cycle structure in a symmetric graph. In this paper, we study the cornerations (and associated structure

Yubo Ni

Sharp Moser-Trudinger type inequalities and their extremal functions play an important role in studying nonlinear PDEs and geometry. We establish a new sharp Moser-Trudinger type inequality in the upper half space in two dimensions and prove the existence of extremal functions for a sharp Moser-Trudinger type inequality under dynamic changes in the unit ball

Eugenio Moro, Gabriele Gemmi, Michele Polese, Leonardo Maccari

Millimeter wave (mmWave) communications has been recently standardized for use in the fifth generation (5G) of cellular networks, fulfilling the promise of multi-gigabit mobile throughput of current and future mobile radio network generations. In this context, the network densification required to overcome the difficult mmWave propagation will result in incr

Serafeim Chatzopoulos, Kleanthis Vichos, Ilias Kanellos, Thanasis Vergoulis

Various research activities rely on citation-based impact indicators. However these indicators are usually globally computed, hindering their proper interpretation in applications like research assessment and knowledge discovery. In this work, we advocate for the use of topic-aware categorical impact indicators, to alleviate the aforementioned problem. In ad

Albert Roethel, Maria Ganzha, Anna Wróblewska

A considerable number of texts encountered daily are somehow connected with each other. For example, Wikipedia articles refer to other articles via hyperlinks, scientific papers relate to others via citations or (co)authors, while tweets relate via users that follow each other or reshare content. Hence, a graph-like structure can represent existing connectio

K. Sravan Kumar, João Marto

Before we ask what the quantum gravity theory is, it is a legitimate quest to formulate a robust quantum field theory in curved spacetime (QFTCS). Several conceptual problems, especially unitarity loss (pure states evolving into mixed states), have raised concerns over several decades. In this paper, acknowledging the fact that {time} is a parameter in quant

Markus Banagl

Integrally oriented normally nonsingular maps between singular spaces have associated transfer homomorphisms on KO-homology at odd primes. We prove that such transfers preserve Siegel-Sullivan orientations, defined when the singular spaces are compact pseudomanifolds satisfying the Witt condition, for example pure-dimensional compact complex algebraic variet

Nhat-Hao Pham, Khanh-Linh Vo, Mai Anh Vu, Thu Nguyen

Correlation matrix visualization is essential for understanding the relationships between variables in a dataset, but missing data can pose a significant challenge in estimating correlation coefficients. In this paper, we compare the effects of various missing data methods on the correlation plot, focusing on two common missing patterns: random and monotone.

Hongwei Sheng, Xin Yu, Feiyu Wang, MD Wahiduzzaman Khan

Spontaneous retinal Venous Pulsations (SVP) are rhythmic changes in the caliber of the central retinal vein and are observed in the optic disc region (ODR) of the retina. Its absence is a critical indicator of various ocular or neurological abnormalities. Recent advances in imaging technology have enabled the development of portable smartphone-based devices

Tu T. Do, Mai Anh Vu, Tuan L. Vo, Hoang Thien Ly

Monotone missing data is a common problem in data analysis. However, imputation combined with dimensionality reduction can be computationally expensive, especially with the increasing size of datasets. To address this issue, we propose a Blockwise principal component analysis Imputation (BPI) framework for dimensionality reduction and imputation of monotone

Xiao Xu, Jiazheng Zhou, Kang Yin, Jinlin Wang

Flexible Cu2ZnSn(S, Se)4 (CZTSSe) solar cells take the advantages of environmental friendliness, low cost, and multi-scenario applications, and have drawn extensive attention in recent years. Compared with rigid devices, the lack of alkali metal elements in the flexible substrate is the main factor limiting the performance of flexible CZTSSe solar cells. Thi

Andrea Zazzi, Arka Dipta Das, Lukas Hüssen, Renato Negra

We propose a new signaling scheme for on-chip optical-electrical-optical artificial neural networks that utilizes orthogonal delay-division multiplexing and pilot-tone based self-homodyne detection. This scheme offers a more efficient scaling of the optical power budget with increasing network complexity. Our simulations, based on a 220 nm SOI silicon photon

Błażej Wróbel

We prove multiplier theorems on rank one noncompact symmetric spaces which improve aspects of existing results. A common theme of our main results is that we partially drop specific assumptions on the multiplier function such as a Mikhlin-H\"ormander condition. These are replaced by a requirement that parts of the multiplier function on the critical $p$ stri

Hamid Ghourchian, Tobias J. Oechtering, Mikael Skoglund

We extend the results of Ghourchian et al. [IEEE JSAIT-2021], to joint source-channel coding with eavesdropping. Our work characterizes the sequential encoding process using the cumulative rate distribution functions (CRDF) and includes a security constraint using the cumulative leakage distribution functions (CLF). The information leakage is defined based o

Richard Naud, André Longtin

Neuroscience and artificial intelligence are closely intertwined, but so are the physics of dynamical system, philosophy and psychology. Each of these fields try in their own way to relate observations at the level of molecules, synapses, neurons or behavior, to a function. An influential conceptual approach to this end was popularized by David Marr, which f

Zhuofei Huang, Jianlin Liu, Shang Xu, Ying Chen

Multi-view stereo depth estimation based on cost volume usually works better than self-supervised monocular depth estimation except for moving objects and low-textured surfaces. So in this paper, we propose a multi-frame depth estimation framework which monocular depth can be refined continuously by multi-frame sequential constraints, leveraging a Bayesian f

G. H. H. Suen, C. J. Owen, D. Verscharen, T. S. Horbury

Magnetic switchbacks are localised polarity reversals in the radial component of the heliospheric magnetic field. Observations from Parker Solar Probe (PSP) have shown that they are a prevalent feature of the near-Sun solar wind. However, observations of switchbacks at 1 au and beyond are less frequent, suggesting that these structures evolve and potentially

Leonardo Castellani, Pietro Antonio Grassi

The Hodge dual operator, recently introduced for supermanifolds, is used to reformulate super Yang-Mills and supergravity in $D=4$. We first recall the definition of the Hodge dual operator for flat and curved supermanifolds. Then we show how to recover the usual super-Yang-Mills equations of motion for $N=1,2$ supersymmetry, and the obstacles (as seen from

Emanuele Locatelli, Valentino Bianco, Chantal Valeriani, Paolo Malgaretti

Polymers confined in corrugated channels, i.e. channels of varying amplitude, display {multiple local maxima and minima of the diffusion coefficient upon increasing their degree of polymerization $N$}. We propose a theoretical effective free energy for linear polymers based on a Fick-Jacobs approach. We validate the predictions against numerical data, obtain

K. M. Patel, D. J. Goldie, S. Withington, C. N. Thomas

Transition-edge sensors (TESs) have found a wide range of applications in both space- and land-based astronomical photon measurement and are being used in the search for dark matter and neutrino mass measurements. A fundamental aspect of TES physics that has not been investigated is the sensitivity of TESs to strong DC electric fields (10 kV/m and above). Un

Eric J. Hanson

We generalize the "facial weak order" of a finite Coxeter group to a partial order on a set of intervals in a complete lattice. We apply our construction to the lattice of torsion classes of a finite-dimensional algebra and consider its restriction to intervals coming from stability conditions. We give two additional interpretations of the resulting "facial

Antonio Alarcon, Franc Forstneric

Let $X$ be a Stein manifold of complex dimension $n>1$ endowed with a Riemannian metric $\mathfrak{g}$. We show that for every integer $k$ with $\left[\frac{n}{2}\right] \le k \le n-1$ there is a nonsingular holomorphic foliation of dimension $k$ on $X$ all of whose leaves are topologically closed and $\mathfrak{g}$-complete. The same is true if $1\le k<\lef

Meng Liu, Wei-Min Wang, Yu-Tong Li

Quasi-monoenergetic GeV-scale protons are predicted to efficiently generate via radiation pressure acceleration (RPA) when the foil thickness is matched with the laser intensity, e.g., $L_{mat}$ at several nm to 100 nm with $10^{19}-10^{22} \rm ~W cm^{-2}$ available in laboratory. However, non-monoenergetic protons with much lower energies than prediction we

Ludovic Goudenège, Andrea Molent, Antonino Zanette

In this article, we introduce an algorithm called Backward Hedging, designed for hedging European and American options while considering transaction costs. The optimal strategy is determined by minimizing an appropriate loss function, which is based on either a risk measure or the mean squared error of the hedging strategy at maturity. The proposed algorithm

Nicholas Schreck, Alla Slynko, Maral Saadati, Axel Benner

Statistical data simulation is essential in the development of statistical models and methods as well as in their performance evaluation. To capture complex data structures, in particular for high-dimensional data, a variety of simulation approaches have been introduced including parametric and the so-called plasmode simulations. While there are concerns abo

Adrien Petralia, Philippe Charpentier, Paul Boniol, Themis Palpanas

In recent years, smart meters have been widely adopted by electricity suppliers to improve the management of the smart grid system. These meters usually collect energy consumption data at a very low frequency (every 30min), enabling utilities to bill customers more accurately. To provide more personalized recommendations, the next step is to detect the appli

Harshitra Mahalingam, Ben Andrew Olsen, Aleksandr Rodin

Using a nonperturbative classical model for ionic motion through one-dimensional (1D) solids, we explore how thermal lattice vibrations affect ionic transport properties. Based on analytic and numerical calculations, we find that the mean dissipation experienced by the mobile ion is similar to that of the non-thermal case, with thermal motion only contributi

William Leeney, Ryan McConville

Graph Neural Networks (GNNs) have improved unsupervised community detection of clustered nodes due to their ability to encode the dual dimensionality of the connectivity and feature information spaces of graphs. Identifying the latent communities has many practical applications from social networks to genomics. Current benchmarks of real world performance ar

Prateek A. Meshram, Suraj Joshi, Devarshi Mahajan

The first MRI scan was done in the year 1978 by researchers at EML Laboratories. As per an estimate, approximately 251,329 people died due to primary cancerous brain and CNS (Central Nervous System) Tumors in the year 2020. It has been recommended by various medical professionals that brain tumor detection at an early stage would help in saving many lives. W

Shunxin Wang, Raymond Veldhuis, Christoph Brune, Nicola Strisciuglio

The performance of computer vision models are susceptible to unexpected changes in input images caused by sensor errors or extreme imaging environments, known as common corruptions (e.g. noise, blur, illumination changes). These corruptions can significantly hinder the reliability of these models when deployed in real-world scenarios, yet they are often over

Ilaria Colazzo, Eric Jespers, Łukasz Kubat, Arne Van Antwerpen

Quadratic algebras related to some classes of finite left non-degenerate solutions (X,r) of the Yang--Baxter equation have been intensively studied since they are the associative ring-theoretical tool to study solutions. These are the monoid algebras K[M(X,r)] and K[A(X,r)], over a field K, of its structure monoid M(X,r) and left derived structure monoid A(X

Naoki Wake, Atsushi Kanehira, Kazuhiro Sasabuchi, Jun Takamatsu

This technical paper introduces a chatting robot system that utilizes recent advancements in large-scale language models (LLMs) such as GPT-3 and ChatGPT. The system is integrated with a co-speech gesture generation system, which selects appropriate gestures based on the conceptual meaning of speech. Our motivation is to explore ways of utilizing the recent

Sheng Feng

A connection is revealed between the superposition principle and locality. A self consistent interpretation of the superposition principle is put forth, from which it is shown that quantum mechanics may be a local statistical theory. Then it is shown how Bell experiments can be satisfactorily explained by assuming local nature for entangled particles, i.e.,

André F. C. Gomes, Mário A. T. Figueiredo

The partial information decomposition (PID) framework is concerned with decomposing the information that a set of random variables has with respect to a target variable into three types of components: redundant, synergistic, and unique. Classical information theory alone does not provide a unique way to decompose information in this manner and additional ass

D. -Q. To, C. Y. Ameyaw, A. Suresh, S. Bhatt

We analyze theoretically the origin of the spin Nernst and thermal Hall effects in FePS3 as a realization of two-dimensional antiferromagnet (2D AFM). We find that a strong magnetoelastic coupling, hybridizing magnetic excitation (magnon) and elastic excitation (phonon), combined with time-reversal-symmetry-breaking, results in a Berry curvature hotspots in

Valentine Soto

Kauer moves are local moves of an edge in a Brauer graph that yield derived equivalences between Brauer graph algebras [Kau98]. These derived equivalences may be interpreted in terms of silting mutations. In this paper, we generalize the notion of Kauer moves to any finite number of edges. Their construction is based on cutting and pasting actions on the Bra

Yao Deng, Jiaohong Yao, Zhi Tu, Xi Zheng

Recent incidents with autonomous vehicles highlight the need for rigorous testing to ensure safety and robustness. Constructing test scenarios for autonomous driving systems (ADSs), however, is labor-intensive. We propose TARGET, an end-to-end framework that automatically generates test scenarios from traffic rules. To address complexity, we leverage a Large