July 2023 arXiv papers — page 5

Daniel Murnane

The use of graph neural networks has produced significant advances in point cloud problems, such as those found in high energy physics. The question of how to produce a graph structure in these problems is usually treated as a matter of heuristics, employing fully connected graphs or K-nearest neighbors. In this work, we elevate this question to utmost impor

Hongzhe Zhang, Xiaohang Zhao, Xiao Fang, Bintong Chen

Disaster response is critical to save lives and reduce damages in the aftermath of a disaster. Fundamental to disaster response operations is the management of disaster relief resources. To this end, a local agency (e.g., a local emergency resource distribution center) collects demands from local communities affected by a disaster, dispatches available resou

Negin Ghamsarian, Javier Gamazo Tejero, Pablo Márquez Neila, Sebastian Wolf

Models capable of leveraging unlabelled data are crucial in overcoming large distribution gaps between the acquired datasets across different imaging devices and configurations. In this regard, self-training techniques based on pseudo-labeling have been shown to be highly effective for semi-supervised domain adaptation. However, the unreliability of pseudo l

Marco Antonio Stranisci, Eleonora Bernasconi, Viviana Patti, Stefano Ferilli

Digital media have enabled the access to unprecedented literary knowledge. Authors, readers, and scholars are now able to discover and share an increasing amount of information about books and their authors. However, these sources of knowledge are fragmented and do not adequately represent non-Western writers and their works. In this paper we present The Wor

Giovanni Panti

We describe Gauss-type maps as geometric realizations of certain codes in the monoid of nonnegative matrices in the extended modular group. Each such code, together with an appropriate choice of unimodular intervals in P^1R, determines a dual pair of graph-directed iterated function systems, whose attractors contain intervals and constitute the domains of a

Antai Xie, Xinlei Yi, Xiaofan Wang, Ming Cao

This paper studies the privacy-preserving distributed optimization problem under limited communication, where each agent aims to keep its cost function private while minimizing the sum of all agents' cost functions. To this end, we propose two differentially private distributed algorithms under compressed communication. We show that the proposed algorithms a

Etsuko Itou, Akira Matsumoto, Yuya Tanizaki

We consider three distinct methods to compute the mass spectrum of gauge theories in the Hamiltonian formalism: (1) correlation-function scheme, (2) one-point-function scheme, and (3) dispersion-relation scheme. The first one examines spatial correlation functions as we do in the conventional Euclidean Monte Carlo simulations. The second one uses the boundar

Alyson Laskowski, Nirav Mehta

Multichannel quantum defect theory (MQDT) provides a powerful toolkit for describing and understanding collisions of cold alkali atoms. Various MQDT approximations differ primarily in how they characterize the so-called short-ranged $K$-matrix, ${\mathbf K}_{\text{sr}}$, which encapsulates the short-ranged, high-energy physics into a handful of low-energy pa

Rebecca R Andridge

Recently, attention was drawn to the failure of two very large internet-based probability surveys to correctly estimate COVID-19 vaccine uptake in the United States in early 2021. Both the Delphi-Facebook CTIS and Census Household Pulse Survey (HPS) overestimated uptake substantially, by 17 and 14 percentage points in May 2021, respectively. These surveys ha

Aditya Devarakonda, Grey Ballard

In this work, we design, analyze, and optimize sequential and shared-memory parallel algorithms for partitioned local depths (PaLD). Given a set of data points and pairwise distances, PaLD is a method for identifying strength of pairwise relationships based on relative distances, enabling the identification of strong ties within dense and sparse communities

Yu Wu, Dimitris Spathis, Hong Jia, Ignacio Perez-Pozuelo

Deep learning models have shown great promise in various healthcare monitoring applications. However, most healthcare datasets with high-quality (gold-standard) labels are small-scale, as directly collecting ground truth is often costly and time-consuming. As a result, models developed and validated on small-scale datasets often suffer from overfitting and d

Yong Zheng

ChatGPT, an implementation and application of large language models, has gained significant popularity since its initial release. Researchers have been exploring ways to harness the practical benefits of ChatGPT in real-world scenarios. Educational researchers have investigated its potential in various subjects, e.g., programming, mathematics, finance, clini

Zakaria Marah

In this paper we examine the problem of valuing an exotic derivative known as the American passport option where the underlying is driven by a L\'evy process. The passport option is a call option on a trading account. We derive the pricing equation, using the dynamic programming principle, and prove that the option value is a viscosity solution of variationa

Hamed Babaei Giglou, Jennifer D'Souza, Sören Auer

We propose the LLMs4OL approach, which utilizes Large Language Models (LLMs) for Ontology Learning (OL). LLMs have shown significant advancements in natural language processing, demonstrating their ability to capture complex language patterns in different knowledge domains. Our LLMs4OL paradigm investigates the following hypothesis: \textit{Can LLMs effectiv

Eduardo B. Molinero, Bruno Amorim, Mikhail Malakhov, Giovanni Cistaro

Excitons play a key role in the linear optical response of 2D materials. However, their significance in the highly nonlinear optical response to intense mid-infrared light has often been overlooked. Using hBN as a prototypical example, we theoretically demonstrate that excitons play a major role in this process. Specifically, we illustrate their formation an

Clifford M. Will, Smadar Naoz, Aurélien Hees, Alexandria Tucker

We use 23 years of astrometric and radial velocity data on the orbit of the star S0-2 to constrain a hypothetical intermediate-mass black hole orbiting the massive black hole Sgr A* at the Galactic center. The data place upper limits on variations of the orientation of the stellar orbit (inclination, nodal angle, and pericenter) at levels between 0.02 and 0.

Ting Jiang, Shaohan Huang, Zhongzhi Luan, Deqing Wang

Large language models (LLMs) have recently garnered significant interest. With in-context learning, LLMs achieve impressive results in various natural language tasks. However, the application of LLMs to sentence embeddings remains an area of ongoing research. In this work, we propose an in-context learning-based method aimed at improving sentence embeddings

Xiaochong Lan, Chen Gao, Shiqi Wen, Xiuqi Chen

Living needs refer to the various needs in human's daily lives for survival and well-being, including food, housing, entertainment, etc. On life service platforms that connect users to service providers, such as Meituan, the problem of living needs prediction is fundamental as it helps understand users and boost various downstream applications such as person

Manuel Sam Ribeiro, Giulia Comini, Jaime Lorenzo-Trueba

The Grapheme-to-Phoneme (G2P) task aims to convert orthographic input into a discrete phonetic representation. G2P conversion is beneficial to various speech processing applications, such as text-to-speech and speech recognition. However, these tend to rely on manually-annotated pronunciation dictionaries, which are often time-consuming and costly to acquire

Xin-Yu Tian, Jian Shi, Xiaotong Shen, Kai Song

The dynamic ranking, due to its increasing importance in many applications, is becoming crucial, especially with the collection of voluminous time-dependent data. One such application is sports statistics, where dynamic ranking aids in forecasting the performance of competitive teams, drawing on historical and current data. Despite its usefulness, predicting

Jose Mart. n-Roca, Valentino Bianco, Francisco Alarcon, Ajay K. Monnappa

Bacterial biofilms mechanically behave as viscoelastic media consisting of micron-sized bacteria crosslinked to a selfproduced network of extracellular polymeric substances (EPS) embedded in water. Structural principles for numerical modelling aim at describing mesoscopic viscoelasticity without loosing detail on the underlying interactions existing in wide

Michał Sobieraj

In this paper, we investigate the properties of standard and multilevel Monte Carlo methods for weak approximation of solutions of stochastic differential equations (SDEs) driven by the infinite-dimensional Wiener process and Poisson random measure with Lipschitz payoff function. The error of the truncated dimension randomized numerical scheme, which is dete

Seyed Mohammad Reza Safaee, Kaveh, Rahbardar Mojaver, Guowu Zhang

A novel mode-selective thermo-optic phase shifter (MS-TOPS) enabled by subwavelength grating (SWG) structures is proposed and experimentally demonstrated on a 220 nm waveguide thick silicon photonics chip for the first two quasi-transverse electric modes (TE0, TE1). Mode-selective relative phase manipulation of modes unlocks several processing tasks in mode

Maiia Bocharova, Eugene Malakhov, Vitaliy Mezhuyev

The paper focuses on deep learning semantic search algorithms applied in the HR domain. The aim of the article is developing a novel approach to training a Siamese network to link the skills mentioned in the job ad with the title. It has been shown that the title normalization process can be based either on classification or similarity comparison approaches.

Aleksandr Tuxanidy, Daniel Panario

It is proven that, in any given base, there are infinitely many palindromic numbers having at most six prime divisors, each relatively large. The work involves equidistribution estimates for the palindromes in residue classes to large moduli, offering upper bounds for moments and averages of certain products closely related to exponential sums over palindrom

Liping Kevin Ge, Alessandro Tuniz, Martijn de Sterke, James M. Zavislan

The excitation of microresonators using focused intensity modulated light, known as photothermal excitation, is gaining significant attention due to its capacity to accurately excite microresonators without distortions, even in liquid environments, which is driving key advancements in atomic force microscopy and related technologies. Despite progress in the

Daniel Agbaji, Brady Lund, Nishith Reddy Mannuru

The Fourth Industrial Revolution, particularly Artificial Intelligence (AI), has had a profound impact on society, raising concerns about its implications and ethical considerations. The emergence of text generative AI tools like ChatGPT has further intensified concerns regarding ethics, security, privacy, and copyright. This study aims to examine the percep

N. Alam, A. Mannan, A. A. Mamun

Using a Sagdeev pseudopotential approach where the nonlinear structures are stationary in a comoving frame, the arbitrary or large amplitude dust-acoustic solitary waves and double layers have been studied in dusty plasmas containing warm positively charged dust and nonthermal distributed electrons and ions. Depending on the values of the critical Mach numbe

Rabab Abdelfattah, Qing Guo, Xiaoguang Li, Xiaofeng Wang

This paper presents a CLIP-based unsupervised learning method for annotation-free multi-label image classification, including three stages: initialization, training, and inference. At the initialization stage, we take full advantage of the powerful CLIP model and propose a novel approach to extend CLIP for multi-label predictions based on global-local image-

M. D. Adzhymambetov, S. V. Akkelin, Yu. M. Sinyukov

The one- and two-boson momentum spectra are derived in the quantum local-equilibrium canonical ensemble of noninteracting bosons with a fixed particle number constraint. We define the canonical ensemble as a subensemble of events associated with the grand-canonical ensemble. Applying simple hydro-inspired parametrization with parameter values that correspond

Yongxu Fu, Yi Zhang

Surpassing the individual characteristics of the non-Hermitian skin effect (NHSE) and the scale-free (SF) effect observed recently, we systematically exploit the exponential decay behavior of bulk eigenstates via the transfer matrix approach in non-Hermitian systems. We concentrate on one-dimensional (1D) finite-size non-Hermitian systems with 2*2 transfer m

Jayanta Sarkar

We investigate unique continuation inequalities for solutions of the Schr\"odinger equations associated with special Hermite operators. Our main result establishes that if the solution remains small at two distinct time points outside sets of finite measure, then the solution also remains small throughout the entire space. We also explore analogous results f

Xinyu Zhang, Hanbin Hong, Yuan Hong, Peng Huang

The language models, especially the basic text classification models, have been shown to be susceptible to textual adversarial attacks such as synonym substitution and word insertion attacks. To defend against such attacks, a growing body of research has been devoted to improving the model robustness. However, providing provable robustness guarantees instead

Prakash Chandra Chhipa, Johan Rodahl Holmgren, Kanjar De, Rajkumar Saini

Self-supervised learning in computer vision aims to leverage the inherent structure and relationships within data to learn meaningful representations without explicit human annotation, enabling a holistic understanding of visual scenes. Robustness in vision machine learning ensures reliable and consistent performance, enhancing generalization, adaptability,

Qianhui Zhang, Jianfeng Lu, Ziyu Wang, Zhigao Dai

Two-dimensional (2D) transition metal dichalcogenides (TMDs) hold great potential for future low-energy optoelectronics owing to their unique electronic, optical, and mechanical properties. Chemical vapor deposition (CVD) is the technique widely used for the synthesis of large-area TMDs. However, due to high sensitivity to the growth environment, reliable sy

Alejandro Torres-Orjuela, Shun-Jia Huang, Zheng-Cheng Liang, Shuai Liu

TianQin and LISA are space-based laser interferometer gravitational wave (GW) detectors planned to be launched in the mid-2030s. Both detectors will detect low-frequency GWs around $10^{-2}\,{\rm Hz}$, however, TianQin is more sensitive to frequencies above this common sweet-spot while LISA is more sensitive to frequencies below $10^{-2}\,{\rm Hz}$. Therefor

Ke Gao, Lei-Hua Liu

The magnification effect of wormholes and black holes has been extensively researched. It is crucial to provide a finite distance analysis to understand this magnification phenomenon better. In this article, the rotational Simpson-Visser metric (RSV) is chosen as the focus of research. By calculating the deflection of light in RSV metric, we determine the re

Yasuyuki Hatsuda, Masashi Kimura

We often encounter a situation that black hole solutions can be regarded as continuous deformations of simpler ones, or modify general relativity by continuous parameters. We develop a general framework to compute high-order perturbative corrections to quasinormal mode frequencies in such deformed problems. Our method has many applications, and allows to com

Scott Sussex, Pier Giuseppe Sessa, Anastasiia Makarova, Andreas Krause

In Causal Bayesian Optimization (CBO), an agent intervenes on an unknown structural causal model to maximize a downstream reward variable. In this paper, we consider the generalization where other agents or external events also intervene on the system, which is key for enabling adaptiveness to non-stationarities such as weather changes, market forces, or adv

Joseph Smith

We construct theories of free fermions in $(2n-1)$-dimensions with $SU(1,n)$ spacetime symmetry from the null reduction of fermions on a $2n$-dimensional $\Omega$-deformed Minkowski background for $n=2$ and $n=3$. These play a role in the 5d $SU(1,3)$-invariant theories that are conjectured to offer a full description of certain 6d superconformal field theor

Asi Khandelwal, L. S. Sharath Chandra, Archna Sagdeo, Rashmi Singh

The structural and magnetic properties of the as-cast and annealed V$_{0.6-x}$Si$_x$Ti$_{0.4}$ ($x$ = 0, 0.05, 0.10, 0.15) alloy superconductors are reported here. It is found that addition of silicon to the V-Ti alloys results in eutectic precipitation of Ti$_{5}$Si$_3$-phase in the body centred cubic (bcc) $\beta$-V-Ti matrix. In the as-cast V$_{0.6-x}$Si$

Eduard Popescu, Adrian Groza, Ioana Damian

Diabetic retinopathy is an ocular condition that affects individuals with diabetes mellitus. It is a common complication of diabetes that can impact the eyes and lead to vision loss. One method for diagnosing diabetic retinopathy is the examination of the fundus of the eye. An ophthalmologist examines the back part of the eye, including the retina, optic ner

Loreta A. Muscarella, Huygen J. Jöbsis, Bettina Baumgartner, P. Tim Prins

Halide perovskite and elpasolite semiconductors are extensively studied for optoelectronic applications due to their excellent performance together with significant chemical and structural flexibility. However, there is still limited understanding of their basic elastic properties and how they vary with composition and temperature, which is relevant for synt

Chen Liu, Peike Li, Xingqun Qi, Hu Zhang

The audio-visual segmentation (AVS) task aims to segment sounding objects from a given video. Existing works mainly focus on fusing audio and visual features of a given video to achieve sounding object masks. However, we observed that prior arts are prone to segment a certain salient object in a video regardless of the audio information. This is because soun

Thomas Deschatre, Xavier Warin

In this paper, we propose a multidimensional statistical model of intraday electricity prices at the scale of the trading session, which allows all products to be simulated simultaneously. This model, based on Poisson measures and inspired by the Common Shock Poisson Model, reproduces the Samuelson effect (intensity and volatility increases as time to maturi

Zhigao Dai, Yupeng Wang, Lu Liu, Junkai Deng

The intact transfer and assembly of two-dimensional (2D) materials and their heterostructures are critical for their integration into advanced electronic and optical devices. Herein, we report a facile technique called volatile polymer stamping (VPS) to achieve efficient transfer of 2D materials and assembly of large-scale heterojunctions with clean interfac

Zhijian Huang, Sihao Lin, Guiyu Liu, Mukun Luo

Multi-modality fusion and multi-task learning are becoming trendy in 3D autonomous driving scenario, considering robust prediction and computation budget. However, naively extending the existing framework to the domain of multi-modality multi-task learning remains ineffective and even poisonous due to the notorious modality bias and task conflict. Previous w

Juan Hernandez-Toro

The purpose of this article is to introduce the concept of invariance and its properties. These properties can be used to check the primality of a number. Combining these properties with the Euler theorem, it is possible to generalize this theorem for all the values of $a^{\varphi(m)}$ where $0 < a < m {\pmod {m}}$ independently if a is co prime or not with

Marvin Fritz

In this paper, we investigate the well-posedness of weak solutions to the time-fractional Fokker-Planck equation. Its dynamics is governed by anomalous diffusion, and we consider the most general case of space-time dependent forces. Consequently, the fractional derivatives appear on the right-hand side of the equation, and they cannot be brought to the left-

Mingcai Chen, Yuntao Du, Wei Tang, Baoming Zhang

In real-world applications, perfect labels are rarely available, making it challenging to develop robust machine learning algorithms that can handle noisy labels. Recent methods have focused on filtering noise based on the discrepancy between model predictions and given noisy labels, assuming that samples with small classification losses are clean. This work

Marcos Gil de Oliveira, Alfredo Miguel Ozorio de Almeida

The Weyl-Wigner representation of quantum mechanics allows one to map the density operator in a function in phase space - the Wigner function - which acts like a probability distribution. In the context of statistical mechanics, this mapping makes the transition from the classical to the quantum regimes very clear, because the thermal Wigner function tends t

Arnold Filtser, Yuval Gitlitz, Ofer Neiman

A \emph{$\nu$-reliable spanner} of a metric space $(X,d)$, is a (dominating) graph $H$, such that for any possible failure set $B\subseteq X$, there is a set $B^+$ just slightly larger $|B^+|\le(1+\nu)\cdot|B|$, and all distances between pairs in $X\setminus B^+$ are (approximately) preserved in $H\setminus B$. Recently, there have been several works on spar

Eden Kuperwasser, Wojciech Samotij, Yuval Wigderson

Let us say that a graph $G$ is Ramsey for a tuple $(H_1,\dots,H_r)$ of graphs if every $r$-coloring of the edges of $G$ contains a monochromatic copy of $H_i$ in color $i$, for some $i \in [r]$. A famous conjecture of Kohayakawa and Kreuter, extending seminal work of R\"odl and Ruci\'nski, predicts the threshold at which the binomial random graph $G_{n,p}$ b

Gonzalo Morras, Jose Francisco Nuno Siles, Juan Garcia-Bellido

Reduced Order Quadrature (ROQ) methods can greatly reduce the computational cost of Gravitational Wave (GW) likelihood evaluations, and therefore greatly speed up parameter estimation analyses, which is a vital part to maximize the science output of advanced GW detectors. In this paper, we do an in-depth study of ROQ techniques applied to GW data analysis an

João A. Leite, Carolina Scarton, Diego F. Silva

Online social media is rife with offensive and hateful comments, prompting the need for their automatic detection given the sheer amount of posts created every second. Creating high-quality human-labelled datasets for this task is difficult and costly, especially because non-offensive posts are significantly more frequent than offensive ones. However, unlabe

Jonathan Sterling, Daniel Gratzer, Lars Birkedal

We develop a denotational semantics for general reference types in an impredicative version of guarded homotopy type theory, an adaptation of synthetic guarded domain theory to Voevodsky's univalent foundations. We observe for the first time the profound impact of univalence on the denotational semantics of mutable state. Univalence automatically ensures tha

Jonas Primbs, Michael Menth

OpenID Connect (OIDC) is a widely used authentication standard for the Web. In this work, we define a new Identity Certification Token (ICT) for OIDC. An ICT can be thought of as a JSON-based, short-lived user certificate for end-to-end user authentication without the need for cumbersome key management. A user can request an ICT from his OpenID Provider (OP)

Marvin Fritz, Endre Süli, Barbara Wohlmuth

We investigate the well-posedness of a coupled Navier-Stokes-Fokker-Planck system with a time-fractional derivative. Such systems arise in the kinetic theory of dilute solutions of polymeric liquids, where the motion of noninteracting polymer chains in a Newtonian solvent is modelled by a stochastic process exhibiting power-law waiting time, in order to capt

Iwan Feras Fattohi, Christian Prehofer, Frank Slomka

Digital signal theory is an extension of the analysis of continuous signals. This extension is provided by discretization and sampling. The sampling of signals can be mathematically described by a series of Dirac impulses and is well known. Properties of the Dirac impulse, such as sampling, are derived in distribution theory. The theory generalizes different

Álvaro Miguel Moreno, José Ángel Peláez, Elena de la Rosa

We establish new characterizations of the Bloch space $\mathcal{B}$ which include descriptions in terms of classical fractional derivatives. Being precise, for an analytic function $f(z)=\sum_{n=0}^\infty \widehat{f}(n) z^n$ in the unit disc $\mathbb{D}$, we define the fractional derivative $ D^{\mu}(f)(z)=\sum\limits_{n=0}^{\infty} \frac{\widehat{f}(n)}{\mu

Moshe Haim, David Dentelski, Aviad Frydman

We present an experimental study of bilayers of a disordered Ag metal layer close to the metal-insulator transition and an Indium Oxide film which is on the insulating side of the superconductor-insulator-transition. Our results show that superconducting fluctuations within the indium-oxide film, that proximitize the underlying metal layer, induce insulating

Yuzheng Wang, Zhaoyu Chen, Jie Zhang, Dingkang Yang

Data-Free Knowledge Distillation (DFKD) is a novel task that aims to train high-performance student models using only the pre-trained teacher network without original training data. Most of the existing DFKD methods rely heavily on additional generation modules to synthesize the substitution data resulting in high computational costs and ignoring the massive

Sam Adam-Day, Nick Bezhanishvili, David Gabelaia, Vincenzo Marra

We investigate a recent semantics for intermediate (and modal) logics in terms of polyhedra. The main result is a finite axiomatisation of the intermediate logic of the class of all polytopes -- i.e., compact convex polyhedra -- denoted PL. This logic is defined in terms of the Jankov-Fine formulas of two simple frames. Soundness of this axiomatisation requi

Rahul Sharma, Chetana Jain, Biswajit Paul

We present a comprehensive analysis of X-ray pulsar 4U 1626-67 during its current spin-down (2SD) state, following a recent torque reversal. Since its discovery, this ultra-compact binary has experienced multiple torque states, transitioning from spin-up (1SU) during 1977-1990 to spin-down (1SD) during 1990-2008, and again spin-up (2SU) until 2023. From NuST

Kateryna Andrych, Devika Kamath, Jacques Kluska, Hans Van Winckel

Binary post-asymptotic giant branch (post-AGB) stars are products of a poorly understood binary interaction process that occurs during the AGB phase. These systems comprise of a post-AGB primary star, a main-sequence secondary companion and a stable circumbinary disc. Studying the structure and properties of these circumbinary discs is crucial for gaining in

Xinghan Li, Jianqi Chen, Han Zhang, Jieqiang Wei

Errors dynamics captures the evolution of the state errors between two distinct trajectories, that are governed by the same system rule but initiated or perturbed differently. In particular, state observer error dynamics analysis in matrix Lie group is fundamental in practice. In this paper, we focus on the error dynamics analysis for an affine group system

Gabriela Borin Barin, Marco Di Giovannantonio, Thorsten G. Lohr, Shantanu Mishra

Graphene nanoribbons (GNRs) exhibit a broad range of physicochemical properties that critically depend on their width and edge topology. While the chemically stable GNRs with armchair edges (AGNRs) are semiconductors with width-tunable band gap, GNRs with zigzag edges (ZGNRs) host spin-polarized edge states, which renders them interesting for applications in

Steffen Eger, Christoph Leiter, Jonas Belouadi, Ran Zhang

The rapid growth of information in the field of Generative Artificial Intelligence (AI), particularly in the subfields of Natural Language Processing (NLP) and Machine Learning (ML), presents a significant challenge for researchers and practitioners to keep pace with the latest developments. To address the problem of information overload, this report by the

Kai Zhou

Hirotaka Fujimoto proved in [Nagoya Math. J., 1976(64): 117--147] and [Nagoya Math. J., 1978(71): 13--24] a uniqueness theorem for algebraically non-degenerate meromorphic maps into $\mathbb{P}^n(\mathbb{C})$ sharing $(2n+3)$ hyperplanes in general position. The proof of Lemma 3.6 in [Nagoya Math. J., 1976(64): 117--147] is found to contain a mistake. This m

Fabio Massaioli

We discuss the problem of finding non-trivial invariants of non-deterministic, symmetric cut-reduction procedures in the classical sequent calculus. We come to the conclusion that (an enriched version of) the propositional fragment of GS4 -- i.e. the one-sided variant of Kleene's context-sharing style sequent system G4, where independent rule applications pe

Stéphane Devismes, David Ilcinkas, Colette Johnen, Frédéric Mazoit

We present a self-stabilizing algorithm for the (asynchronous) unison problem which achieves an efficient trade-off between time, workload, and space in a weak model. Precisely, our algorithm is defined in the atomic-state model and works in anonymous networks in which even local ports are unlabeled. It makes no assumption on the daemon and thus stabilizes u

Olivia Proust, Frédéric Loulergue

BSML is a pure functional library for the multi-paradigm language OCaml. BSML embodies the principles of the Bulk Synchronous Parallel (BSP) model, a model of scalable parallel computing. We propose a formalization of BSML primitives with WhyML, the specification language of Why3 and specify and prove the correctness of most of the BSML standard library. Fin

Stephen C. Wein

Many applications of quantum optics demand delicate quantum properties of light carefully tailored to accomplish a specific task. To this end, numerical simulations of quantum light sources are vital for designing, characterizing, and optimizing quantum photonic technology. Here, I show that exploiting information hidden in zero-photon measurement outcomes p

Keiichiro Hori, Hideo Suganuma, Hiroki Kanda

We investigate a baryon and its dilatation modes in holographic QCD based on the Sakai-Sugimoto model, which is expressed as a 1+4 dimensional U($N_f$) gauge theory in the flavor space. For spatially rotational symmetric systems, we apply a generalized version of the Witten Ansatz, and reduce 1+4 dimensional holographic QCD into a 1+2 dimensional Abelian Hig

Suepphong Chernbumroong, Pradorn Sureephong, Paweena Suebsombut, Aicha Sekhari

Farmers can now use IoT to improve farm efficiency and productivity by using sensors for farm monitoring to enhance decision-making in areas such as fertilization, irrigation, climate forecast, and harvesting information. Local farmers in Chiang Mai, Thailand, on the other hand, continue to lack knowledge and experience with smart farm technology. As a resul

Egil Bru, Thomas Trautner, Stefan Bruckner

Accessibility in visualization is an important yet challenging topic. Sonification, in particular, is a valuable yet underutilized technique that can enhance accessibility for people with low vision. However, the lower bandwidth of the auditory channel makes it difficult to fully convey dense visualizations. For this reason, interactivity is key in making fu

Paweena Suebsombut, Pradorn Sureephong, Aicha Sekhari, Suepphong Chernbumroong

A chatbot is a software developed to help reply to text or voice conversations automatically and quickly in real time. In the agriculture sector, the existing smart agriculture systems just use data from sensing and internet of things (IoT) technologies that exclude crop cultivation knowledge to support decision-making by farmers. To enhance this, the chatbo

Marcell Tibor Máthé, Kelum Perera, Ágnes Buka, Péter Salamon

Freestanding slender fluid filaments of room temperature ferroelectric nematic liquid crystals are described. They are stabilized either by internal electric fields of bound charges formed due to polarization splay, or by external voltage applied between suspending wires. The phenomenon is similar to those observed in dielectric fluids, such as deionized wat

Toshiyuki Kobayashi

Based on the "generating operator" of the Rankin--Cohen brackets introduced in Kobayashi-Pevzner [arXiv:2306.16800], we present a method to construct various fundamental operators with continuous parameters such as invariant trilinear forms on infinite-dimensional representations, the Fourier and the Poisson transforms on the anti-de Sitter space, and integr

Shili Zhou, Ruian He, Weimin Tan, Bo Yan

Optical Flow Estimation aims to find the 2D dense motion field between two frames. Due to the limitation of model structures and training datasets, existing methods often rely too much on local clues and ignore the integrity of objects, resulting in fragmented motion estimation. Through theoretical analysis, we find the pre-trained large vision models are he

Mandar Datar, Naresh Modina, Rachid El, Eitan Altman

Network slicing (NS) is a key technology in 5G networks that enables the customization and efficient sharing of network resources to support the diverse requirements of nextgeneration services. This paper proposes a resource allocation scheme for NS based on the Fisher-market model and the Trading-post mechanism. The scheme aims to achieve efficient resource

Triantafyllos Kefalas, Yannis Panagakis, Maja Pantic

Video-to-speech synthesis involves reconstructing the speech signal of a speaker from a silent video. The implicit assumption of this task is that the sound signal is either missing or contains a high amount of noise/corruption such that it is not useful for processing. Previous works in the literature either use video inputs only or employ both video and au

Meijie Lu, Xianchang Meng

In this paper, for any integer $k\geq 2$, we study the distribution of the visible lattice points in certain generalized P\'{o}lya's walk on $\mathbb{Z}^k$: perturbed P\'{o}lya's walk and twisted P\'{o}lya's walk. For the first case, we prove that the density of visible lattice points in a perturbed P\'{o}lya's walk is almost surely $1/\zeta(k)$, where $\zet

Nicolas Furnon, Romain Serizel, Slim Essid, Irina Illina

Speech enhancement in ad-hoc microphone arrays is often hindered by the asynchronization of the devices composing the microphone array. Asynchronization comes from sampling time offset and sampling rate offset which inevitably occur when the microphones are embedded in different hardware components. In this paper, we propose a deep neural network (DNN)-based

András Némethi

Let $(X,o)$ be a complex analytic normal surface singularity with rational homology sphere link $M$. The `topological' lattice cohomology ${\mathbb H}^*=\oplus_{q\geq 0} {\mathbb H}^q$ associated with $M$ and with any of its spin$^c$ structures was introduced by the author. Each ${\mathbb H}^q$ is a graded ${\mathbb Z}[U]$--module. Here we consider its homol

Carlos Granero-Belinchon, Manuel Cabeza Gallucci

This article introduces a new Neural Network stochastic model to generate a 1-dimensional stochastic field with turbulent velocity statistics. Both the model architecture and training procedure ground on the Kolmogorov and Obukhov statistical theories of fully developed turbulence, so guaranteeing descriptions of 1) energy distribution, 2) energy cascade and

Yuxin Mao, Jing Zhang, Mochu Xiang, Yunqiu Lv

We propose a contrastive conditional latent diffusion model for audio-visual segmentation (AVS) to thoroughly investigate the impact of audio, where the correlation between audio and the final segmentation map is modeled to guarantee the strong correlation between them. To achieve semantic-correlated representation learning, our framework incorporates a late

Ugo Bruzzo, Armando Capasso, Beatriz Graña Otero

Working in the category of smooth projective varieties over an algebraically closed field of characteristic 0, we review notions of ampleness and numerical nefness for Higgs bundles which &#34;feel&#34; the Higgs field and formulate criteria of the Barton-Kleiman type for these notions. We give an application to minimal surfaces of general type that saturate

Marco Zaffalon, Alessandro Antonucci, Rafael Cabañas, David Huber

We address the problem of integrating data from multiple, possibly biased, observational and interventional studies, to eventually compute counterfactuals in structural causal models. We start from the case of a single observational dataset affected by a selection bias. We show that the likelihood of the available data has no local maxima. This enables us to

Mina Abbaszade, Mariam Zomorodi, Vahid Salari, Philip Kurian

The present study aims to explore the feasibility of language translation using quantum natural language processing algorithms on noisy intermediate-scale quantum (NISQ) devices. Classical methods in natural language processing (NLP) struggle with handling large-scale computations required for complex language tasks, but quantum NLP on NISQ devices holds pro

Euijun Song

Genome-wide association studies (GWAS) involving increasing sample sizes have identified hundreds of genetic variants associated with complex diseases, such as type 2 diabetes (T2D); however, it is unclear how GWAS hits form unique topological structures in protein-protein interaction (PPI) networks. Using persistent homology, this study explores the evoluti

Anuma Garg, Satyabrata Adhikari

Controlled quantum teleportation (CQT) can be considered as a variant of quantum teleportation in which three parties are involved where one party acts as the controller. The usability of the CQT scheme depends on two types of fidelities viz. conditioned fidelity and non-conditioned fidelity. The difference between these fidelities may be termed as power of

Joanna Wojciechowska, Mateusz Sypniewski, Maria Śmigielska, Igor Kamiński

Cultural heritage is an arena of international relations that interests all states worldwide. The inscription process on the UNESCO World Heritage List and the UNESCO Representative List of the Intangible Cultural Heritage of Humanity often leads to tensions and conflicts among states. This research addresses these challenges by developing automatic tools th

Mengqi He, Jing Zhang, Zhaoyuan Yang, Mingyi He

We analysis performance of semantic segmentation models wrt. adversarial attacks, and observe that the adversarial examples generated from a source model fail to attack the target models. i.e The conventional attack methods, such as PGD and FGSM, do not transfer well to target models, making it necessary to study the transferable attacks, especially transfer

Vladimir L. Kalashnikov, Alexander Rudenkov, Irina T. Sorokina

We establish a close analogy between the thermodynamics of the nonlinear systems far from equilibrium and the dissipative solitons. Unlike the solitons in the Hamiltonian systems, their dissipative counterpart looks like an aggregation of bounded quasi-particles interacting on the short range, obeying the Rayleigh-Jeans distribution, and possessing a tempera

Tran Loc Hung

Since the appearance of H. Robbins article (1948), the central limit theorems for random sums have been studied for about 70 years. The central limit theorems for random sums of independent random variables play a very important role in various disciplines such as statistics, financial mathematics, insurance, etc. The purpose of this paper is to randomize so

Feng Gao, Tim Kuhlbusch, Achim Stahl, Jochen Steinmann

The dimensions of liquid scintillator neutrino detectors have grown over the years. Thus, the analog cable length required for the readout increases. In consequence, the signal loss increases as well. With the intelligent Photomultiplier Tube this problem can be solved. The digitiser is moved as close as possible to the Photomultiplier Tube. This concept all

Vivek Kumar Jha, Ravi Joshi, Jayesh Saraswat, Hum Chand

In the innermost regions of Active Galactic Nuclei (AGN), matter is understood to be flowing onto the Supermassive black hole (SMBH), which forms an accretion disk. This disk is responsible for the optical/UV continuum emission observed in the spectra of AGN. Reverberation Mapping of the accretion disk using multiple bands can yield the structure of the disk

A. Marino, T. D. Russell, M. Del Santo, A. Beri

The accretion flow / jet correlation in neutron star (NS) low-mass X-ray binaries (LMXBs) is far less understood when compared to black hole (BH) LMXBs. In this paper we will present the results of a dense multi-wavelength observational campaign on the NS LMXB 4U 1820-30, including X-ray (Nicer, NuSTAR and AstroSAT) and quasi-simultaneous radio (ATCA) observ

B. T. T. Wong

The Dirac equation is a cornerstone of modern particle physics, which integrates special relativity and quantum mechanics into a consistent framework, yielding the prediction of electron and its antiparticle counterpart, positron. The Dirac equation also lays the foundation of quantum electrodynamics, such that QED phenomenon is supported by fundamental Dira