December 2023 arXiv papers — page 2

Alexandra Kakadiaris

This paper uses the MIMIC-IV dataset to examine the fairness and bias in an XGBoost binary classification model predicting the Intensive Care Unit (ICU) length of stay (LOS). Highlighting the critical role of the ICU in managing critically ill patients, the study addresses the growing strain on ICU capacity. It emphasizes the significance of LOS prediction f

Faisal N. Abu-Khzam, Ghinwa Bou Matar, Sergio Thoumi

The Influence Maximization problem under the Independent Cascade model (IC) is considered. The problem asks for a minimal set of vertices to serve as "seed set" from which a maximum influence propagation is expected. New seed-set selection methods are introduced based on the notions of a $d$-packing and vertex centrality. In particular, we focus on selecting

Sayantan Auddy, Sebastian Bergner, Justus Piater

In continual learning from demonstration (CLfD), a robot learns a sequence of real-world motion skills continually from human demonstrations. Recently, hypernetworks have been successful in solving this problem. In this paper, we perform an exploratory study of the effects of different optimizers, initializers, and network architectures on the continual lear

Yuxuan Jiang, Jakub Nawala, Fan Zhang, David Bull

Deep learning techniques have been applied in the context of image super-resolution (SR), achieving remarkable advances in terms of reconstruction performance. Existing techniques typically employ highly complex model structures which result in large model sizes and slow inference speeds. This often leads to high energy consumption and restricts their adopti

Hayat. Laassiri, Ahmed. Daassou, Rachid. Benbrik

This study focuses on precisely calculating analytical critical points for rotating regular AdS black holes, examining scenarios with and without external dark field contributions. Importantly, it represents the first attempt to compute critical points for this specific class of rotating black holes. Our primary focus is on investigating the impact resulting

Yuxiao Hu, Qian Li, Xiaodan Shi, Jinyue Yan

Accurate air quality forecasting is crucial for public health, environmental monitoring and protection, and urban planning. However, existing methods fail to effectively utilize multi-scale information, both spatially and temporally. Spatially, there is a lack of integration between individual monitoring stations and city-wide scales. Temporally, the periodi

Ruwani Herath, Alex Trindade, Fangyuan Zhang

Numerous statistical methods have been developed to explore genomic imprinting and maternal effects, which are causes of parent-of-origin patterns in complex human diseases. Most of the methods, however, either only model one of these two confounded epigenetic effects, or make strong yet unrealistic assumptions about the population to avoid over-parameteriza

Minjie Wang, Haole Jiao, Jiajin Lu, Wenxin Fan

Entanglement swapping (ES) between memory repeater links is critical for establishing quantum networks via quantum repeaters. So far, ES with atomic-ensemble-based memories has not been achieved. Here, we experimentally demonstrated ES between two entangled pairs of spin-wave memories via Duan-Lukin-Cirac-Zoller scheme. With a cloud of cold atoms inserted in

Alexander I. Bufetov

The main result of this note is that the shift of the parameter by 1 in the parameter space of decomposing measures in the problem of harmonic analysis on the infinite-dimensional unitary group corresponds to the taking of the reduced Palm measure at infinity for our decomposing measures. The proof proceeds by finite-dimensional approximation of our measures

Pooya Aavani, Alexandre Trindade, Fangyuan Zhang

Numerous statistical methods have been developed to explore genomic imprinting and maternal effects, which are causes of parent-of-origin patterns in complex human diseases. However, most of them either only model one of these two confounded epigenetic effects, or make strong yet unrealistic assumptions about the population to avoid over-parameterization. A

Hangyu Zhou, Manuel dos Santos Dias, Youguang Zhang, Weisheng Zhao

The kagome lattice is an exciting solid state physics platform for the emergence of nontrivial quantum states driven by electronic correlations: topological effects, unconventional superconductivity, charge and spin density waves, and unusual magnetic states such as quantum spin liquids. While kagome lattices have been realized in complex multi-atomic bulk c

Vahidin Jeleskovic, Anastasia Blokhina

This paper delves into the intricate relationship between the formation of air alliances and the shifts in airport and economic gravity centers across European countries during the period spanning 1990 to 2019. Employing descriptive analysis and the weighted mean center methodology, it explores the interplay between air passenger numbers and economic indicat

Jinchang Hu, Lyuye Zhang, Chengwei Liu, Sen Yang

Open-source software (OSS) greatly facilitates program development for developers. However, the high number of vulnerabilities in open-source software is a major concern, including in Golang, a relatively new programming language. In contrast to other commonly used OSS package managers, Golang presents a distinctive feature whereby commits are prevalently us

Fabian J. Frech, Finn M. Stokes, Kalman K. Szabo, Balint C. Toth

In this study we employ staggered fermions to calculate the two-pion taste singlet states at rest. Leveraging the Clebsch-Gordan coefficients of the symmetry group associated with staggered fermions, we effectively compute the $\pi\pi$ contributions to the resting $\rho$-meson correlator. To discern the distinct energy states involved, we adopt a generalized

Ofer Busani

It is believed that for metric-like models in the KPZ class the following property holds: with probability one, starting from any point, there are at most two semi-infinite geodesics with the same direction that do not coalesce. Until now, such a result was only proved for one model - exponential LPP (Coupier 11') using its inherent connection to the totally

Hugo Herbelin, Ramkumar Ramachandra

Semi-simplicial and semi-cubical sets are commonly defined as presheaves over respectively, the semi-simplex or semi-cube category. Homotopy Type Theory then popularized an alternative definition, where the set of n-simplices or n-cubes are instead regrouped into the families of the fibers over their faces, leading to a characterization we call indexed. More

Evan Deddo, Leopoldo A. Pando Zayas, Christoph F. Uhlemann

We construct Type IIB string theory setups which, via double holography, realize two gravitational systems in separate AdS spaces which interact with each other and with a non-gravitational bath. We employ top-down string theory solutions with concrete field theory duals in the form of 4d $\mathcal N=4$ SYM BCFTs and a first-principles notion of double holog

Moritz Korte-Stapff, Toni Karvonen, Eric Moulines

The family of Mat\'ern kernels are often used in spatial statistics, function approximation and Gaussian process methods in machine learning. One reason for their popularity is the presence of a smoothness parameter that controls, for example, optimal error bounds for kriging and posterior contraction rates in Gaussian process regression. On closed Riemannia

Nadezhda I. Aleksandrova

The aim of this article is to study the attenuation of transient low-frequency waves in 2D lattices of point masses connected by Voigt elements, under an antiplane concentrated loading. The emphasis is on obtaining analytical estimates for solutions using methods of asymptotic inversion of the Laplace and Fourier transforms in the vicinity of the quasi-front

Luis Martínez, Héctor Pinedo

The classical notion of twisted product is studied in the context of partial actions, in particular, we show that the globalization of a partial action is a twisted product. In addition, we establish conditions for the metrizability of twisted products, and some homotopy and categorical properties are proved. Furthermore, sufficient conditions for the envelo

Sergei Kozyrev, Alexander Pechen

Amplification of quantum transfer and ratchet--type processes are important for quantum technologies. We also expect that quantum ratchet works in quantum photosynthesis, where possible role of quantum effects is now widely discussed but the underlying dynamical processes are still not clearly known. In this work, we study a model of amplification of quantum

Mar Grande, Florentino Borondo, Javier Borondo

Currently cryptocurrencies and Decentralized Finance (DeFi), which enable financial services on public blockchains, represents a new growing trend in finance. In contrast to financial markets, ruled by traditional corporations, DeFi is completely transparent as it keeps records of all transactions that occur in the network and makes them publicly available.

Vahidin Jeleskovic, Claudio Latini, Zahid I. Younas, Mamdouh A. S. Al-Faryan

The growing interest in cryptocurrencies has drawn the attention of the financial world to this innovative medium of exchange. This study aims to explore the impact of cryptocurrencies on portfolio performance. We conduct our analysis retrospectively, assessing the performance achieved within a specific time frame by three distinct portfolios: one consisting

Ipsita Mandal

We consider a Josephson junction built with the two-dimensional semi-Dirac semimetal, which features a hybrid of linear and quadratic dispersion around a nodal point. We model the weak link between the two superconducting regions by a Dirac delta potential because it mimics the thin-barrier-limit of a superconductor-barrier-superconductor configuration. Assu

Jie-Yu Zhang, Meng-Yuan Li, Peng Ye

In computer and system sciences, higher-order cellular automata (HOCA) are a type of cellular automata that evolve over multiple time steps and generate complex patterns, which have various applications such as secret sharing schemes, data compression, and image encryption. In this paper, we introduce HOCA to quantum many-body physics and construct a series

Chen Ran, Yao Xueqi, Jiang Xuhui, Han Zhengqi

The field of human settlement construction encompasses a range of spatial designs and management tasks, including urban planning and landscape architecture design. These tasks involve a plethora of instructions and descriptions presented in natural language, which are essential for understanding design requirements and producing effective design solutions. R

Syed Talal Wasim, Muzammal Naseer, Salman Khan, Ming-Hsuan Yang

Video grounding aims to localize a spatio-temporal section in a video corresponding to an input text query. This paper addresses a critical limitation in current video grounding methodologies by introducing an Open-Vocabulary Spatio-Temporal Video Grounding task. Unlike prevalent closed-set approaches that struggle with open-vocabulary scenarios due to limit

Dipankar Sarkar

This paper aims to introduce and analyze the Viz system in a comprehensive way, a novel system architecture that integrates Quantized Low-Rank Adapters (QLoRA) to fine-tune large language models (LLM) within a legally compliant and resource efficient marketplace. Viz represents a significant contribution to the field of artificial intelligence, particularly

D. Kenzhalin, S. Myrzakul, R. Myrzakulov, L. Ravera

We review $F(R,\mathcal{D})$ gravity in the metric-affine framework, where $\mathcal{D}$ is the divergence of the dilation current appearing in the hypermomentum tensor. We assume only linear couplings between the general affine connection and the matter fields (minimal coupling) and break projective invariance to preserve a nonvanishing dilation current. Fo

Reza Ghanbari, Sajjad Pashazadeh, Kesavan Sekar, Kim Nygård

We study the flow stability and spatio-temporal spectral dynamics of cellulose nanocrystal (CNC) suspensions in a custom Taylor-Couette flow cell using the intrinsic shear induced birefringence and liquid crystalline properties of CNC suspensions for flow visualizations for the first time. The analysis is performed at constant ramped speed inputs of the inde

Taika Okuda, Akifumi Sako

We construct a deformation quantization with separation of variables of the Grassmannian $G_{2,4}(\mathbb{C})$. A star product on $G_{2,4}(\mathbb{C})$ can be explicitly determined as the solution of the recurrence relations for $G_{2,4}(\mathbb{C})$ given by Hara and one of the authors (A. Sako). To provide the solution to the recurrence relations, it is ne

Sihao Yuan, Xu Han, Jun Zhang, Zhaoxin Xie

Theoretical studies on chemical reaction mechanisms have been crucial in organic chemistry. Traditionally, calculating the manually constructed molecular conformations of transition states for chemical reactions using quantum chemical calculations is the most commonly used method. However, this way is heavily dependent on individual experience and chemical i

Mohammed M. Al Ezzi, Gayani N. Pallewela, Christophe De Beule, E. J. Mele

By virtue of being atomically thin, the electronic properties of heterostructures built from two-dimensional materials are strongly influenced by atomic relaxation. The atomic layers behave as flexible membranes rather than rigid crystals. Here we develop an analytical theory of lattice relaxation in twisted moir\'e materials. We obtain analytical results fo

Andreas Debrouwere, Lenny Neyt

We characterize the sequences of complex numbers $(z_{n})_{n \in \mathbb{N}}$ and the locally complete $(DF)$-spaces $E$ such that for each $(e_{n})_{n \in \mathbb{N}} \in E^\mathbb{N}$ there exists an $E$-valued function $\mathbf{f}$ on $(0,\infty)$ (satisfying a mild regularity condition) such that $$\int_{0}^{\infty} t^{z_{n}} \mathbf{f}(t) dt = e_{n}, \q

Dimitrios Psychogyios, Emanuele Colleoni, Beatrice Van Amsterdam, Chih-Yang Li

Surgical tool segmentation and action recognition are fundamental building blocks in many computer-assisted intervention applications, ranging from surgical skills assessment to decision support systems. Nowadays, learning-based action recognition and segmentation approaches outperform classical methods, relying, however, on large, annotated datasets. Furthe

Motokazu Abe, Okuto Morikawa, Soma Onoda, Hiroshi Suzuki

In this talk, we give the lattice regularized formulation of the mixed 't Hooft anomaly between the $\mathbb{Z}_N$ $1$-form symmetry and the $\theta$ periodicity for $4$d pure Yang-Mills theory, which was originally discussed by Gaiotto $\textit{et al.}$ in the continuum description. For this purpose, we define the topological charge of the lattice $SU(N)$ g

I. L. Buchbinder, S. A. Fedoruk, A. P. Isaev, M. A. Podoinitsyn

We review the method for constructing local relativistic fields corresponding to the Bargmann-Wigner wave functions that describe the unitary irreducible representations of the $4D$ Poincar\'{e} group. The method is based on the use of the generalized Wigner operator connecting the wave functions of induced representations and local relativistic fields. Appl

Lorenzo Pareschi, Mattia Zanella

Random Batch Methods (RBM) for mean-field interacting particle systems enable the reduction of the quadratic computational cost associated with particle interactions to a near-linear cost. The essence of these algorithms lies in the random partitioning of the particle ensemble into smaller batches at each time step. The interaction of each particle within th

Dang-Zheng Liu, Guangyi Zou

We consider Hermitian and symmetric random band matrices on the $d$-dimensional lattice $(\mathbb{Z}/L\mathbb{Z})^d$ with bandwidth $W$, focusing on local eigenvalue statistics at the spectral edge in the limit $W\to\infty$. Our analysis reveals a critical dimension $d_c=6$ and identifies the critical bandwidth scaling as $W_c=L^{(1-d/6)_+}$. In the Hermitia

Guy Gubnitsky, Roee Diamant

Sperm whales (Physeter macrocephalus) navigate underwater with a series of impulsive, click-like sounds known as echolocation clicks. These clicks are characterized by a multipulse structure (MPS) that serves as a distinctive pattern. In this work, we use the stability of the MPS as a detection metric for recognizing and classifying the presence of clicks in

Tuomas Hytönen

The dyadic representation of any singular integral operator, as an average of dyadic model operators, has found many applications. While for many purposes it is enough to have such a representation for a "suitable class" of test functions, we show that, under quite general assumptions (essentially minimal ones to make sense of the formula), the representatio

Alejandro Moreo, Pablo González, Juan José del Coz

Several disciplines, like the social sciences, epidemiology, sentiment analysis, or market research, are interested in knowing the distribution of the classes in a population rather than the individual labels of the members thereof. Quantification is the supervised machine learning task concerned with obtaining accurate predictors of class prevalence, and to

Eva Elduque, Moisés Herradón Cueto

Motivated by classical Alexander invariants of affine hypersurface complements, we endow certain finite dimensional quotients of the homology of abelian covers of complex algebraic varieties with a canonical and functorial mixed Hodge structure (MHS). More precisely, we focus on covers which arise algebraically in the following way: if $U$ is a smooth connec

Felix Janda, Xin Wang

We establish new universal equations for higher genus Gromov-Witten invariants of target manifolds, by studying both the Chern character and Chern classes of the Hodge bundle on the moduli space of curves. As a consequence, we find new push-forward relations on the moduli space of stable curves.

Daniela Huppenkothen, Juan Pampin, James R. A. Davenport, James Wenlock

Understanding the physical properties of stars, and putting these properties into the context of stellar evolution, is a core challenge in astronomical research. A key visualization in studying stellar evolution is the Hertzsprung-Russell diagram (HRD), organizing data about stellar luminosity and colour into a form that is informative about stellar structur

Swayang Priya Mahanta, Antarjami Sahoo, Sagarika Nayak, T. P. A. Hase

Organic semiconductors (OSCs) are suitable materials for spintronics applications as they form a spinterface when placed next to a ferromagnet, which in turn leads to novel functionalities. The evolution of spinterface can tune the global magnetic anisotropy, magnetization reversal, magnetization dynamics, etc. Planar tris-(8-hydroxyquinoline)aluminum (Alq3)

Haimiao Chen

Let $R$ be a commutative ring with identity and a fixed invertible element $q^{\frac{1}{2}}$, and suppose $q+q^{-1}$ is invertible in $R$. For each planar surface $\Sigma_{0,n+1}$, we present its Kauffman bracket skein algebra over $R$ by explicit generators and relations. The presentation is independent of $R$, and can be considered as a quantization of the

Antarjami Sahoo, Aritra Mukhopadhyaya, Swayang Priya Mahanta, Md. Ehesan Ali

Development of power efficient spintronics devices has been the compelling need in the post-CMOS technology era. The effective tunability of spin-orbit-coupling (SOC) in bulk and at the interfaces of hybrid materials stacking is a prerequisite for scaling down the dimension and power consumption of these devices. In this work, we demonstrate the strong chemi

Martin Mathieu, Francois Schulz

We establish Jafarian's 2009 conjecture that every additive spectrum preserving mapping from a von Neumann algebra onto a semisimple Banach algebra is a Jordan isomorphism.

Ingeborg G. Gjerde, Miroslav Kuchta, Marie E. Rognes, Barbara Wohlmuth

The flow of cerebrospinal fluid through the perivascular spaces of the brain is believed to play a crucial role in eliminating toxic waste proteins. While the driving forces of this flow have been enigmatic, experiments have shown that arterial wall motion is central. In this work, we present a network model for simulating pulsatile fluid flow in perivascula

Paban Kumar Patra, Ranjith R. Kumar, Yixuan Huang, Hridis K. Pal

Moir\'e materials have emerged as a rich platform for exploring strong correlation effects in low dimensions, with twisted bilayer graphene (TBG) as a paradigmatic example. To distill the essential ingredients driving moir\'e-induced phases, a simplified one-dimensional analog -- a two-leg ladder with spatially modulated interleg hopping and a uniform magnet

Esita Pandey, Shaktiranjan Mohanty, Abhisek Mishra, Bhuvneshwari Sharma

The successful commercialization of flexible spintronic devices requires a complete understanding of the impact of external strain on the structural, electronic, and magnetic properties of a system. The impact of bending-induced strain on flexible films is studied quite well. However, little is known about the effect of other modes of flexibility, e.g., wrin

U. Özdem

To improve our understanding of the quark-gluon dynamics underlying multiquark states, we systematically study their electromagnetic properties. In this study, the magnetic and quadrupole moments of the theoretically predicted singly-charmed state with the quantum numbers $\mathrm{J^P = 1^+}$ is investigated within the framework of the QCD light-cone sum rul

Giulia Bertaglia, Lorenzo Pareschi, Giuseppe Toscani

The temporal evolution of a contagious viral disease is modelled as the dynamic progression of different classes of population with individuals interacting pairwise. This interaction follows a binary mechanism typical of kinetic theory, wherein agents aim to improve their condition with respect to a mutual utility target. To this end, we introduce kinetic eq

Davide Addona, Vincenzo Leone, Luca Lorenzi, Abdelaziz Rhandi

In this paper we consider the vector-valued Schr\"{o}dinger operator $-\Delta + V$, where the potential term $V$ is a matrix-valued function whose entries belong to $L^1_{\rm loc}(\mathbb{R}^d)$ and, for every $x\in\mathbb{R}^d$, $V(x)$ is a symmetric and nonnegative definite matrix, with non positive off-diagonal terms and with eigenvalues comparable each o

Satoshi Masaki

In this paper, we study the large-time behavior of small solutions to the standard form of the systems of 1D cubic nonlinear Schr\"odinger equations consisting of two components and possessing a coercive mass-like conserved quantity. The cubic nonlinearity is known to be critical in one space dimension in view of the large-time behavior. By employing the res

Junghoon Kim, Taejoon Kim, Anindya Bijoy Das, Seyyedali Hosseinalipour

Although user cooperation cannot improve the capacity of Gaussian two-way channels (GTWCs) with independent noises, it can improve communication reliability. In this work, we aim to enhance and balance the communication reliability in GTWCs by minimizing the sum of error probabilities via joint design of encoders and decoders at the users. We first formulate

Anyanwu, C. F, Georgewill, O. A.

In developing countries, healthcare challenges and expensive infertility treatments has resulted in resurgent interest in medicinal plants. This study was designed to determine if Curcubita pepo seed can enhance female fertility, by assessing the reproductive outcome in female wistar rats treated with n-hexane (nHE), dichloromethane (DCM) and aqueous ethanol

Hongfei Xue, Yuhao Liang, Bingshen Mu, Shiliang Zhang

This study focuses on emotion-sensitive spoken dialogue in human-machine speech interaction. With the advancement of Large Language Models (LLMs), dialogue systems can handle multimodal data, including audio. Recent models have enhanced the understanding of complex audio signals through the integration of various audio events. However, they are unable to gen

Shuichi Hirahara, Naoto Ohsaka

Motivated by the inapproximability of reconfiguration problems, we present a new PCP-type characterization of PSPACE, which we call a probabilistically checkable reconfiguration proof (PCRP): Any PSPACE computation can be encoded into an exponentially long sequence of polynomially long proofs such that every adjacent pair of the proofs differs in at most one

Silvan David Peter, Shreyan Chowdhury, Carlos Eduardo Cancino-Chacón, Gerhard Widmer

Semantic embeddings play a crucial role in natural language-based information retrieval. Embedding models represent words and contexts as vectors whose spatial configuration is derived from the distribution of words in large text corpora. While such representations are generally very powerful, they might fail to account for fine-grained domain-specific nuanc

Korbinian Schreiber, Timo Wunderlich, Philipp Spilger, Sebastian Billaudelle

Bees display the remarkable ability to return home in a straight line after meandering excursions to their environment. Neurobiological imaging studies have revealed that this capability emerges from a path integration mechanism implemented within the insect's brain. In the present work, we emulate this neural network on the neuromorphic mixed-signal process

Siyuan Li, Luyuan Zhang, Zedong Wang, Di Wu

As the deep learning revolution marches on, self-supervised learning has garnered increasing attention in recent years thanks to its remarkable representation learning ability and the low dependence on labeled data. Among these varied self-supervised techniques, masked modeling has emerged as a distinctive approach that involves predicting parts of the origi

Stefan Haesen, Miroslava Petrović-Torgašev, Leopold Verstraelen

A proposal is made for what may well be the most elementary Riemannian spaces which are homogeneous but not isotropic. In other words: a proposal is made for what may well be the nicest symmetric spaces beyond the real space forms, that is, beyond the Riemannian spaces which are homogeneous and isotropic. The above qualification of `'nicest symmetric spaces'

Silvan David Peter, Carlos Eduardo Cancino-Chacón, Emmanouil Karystinaios, Gerhard Widmer

Generative models of expressive piano performance are usually assessed by comparing their predictions to a reference human performance. A generative algorithm is taken to be better than competing ones if it produces performances that are closer to a human reference performance. However, expert human performers can (and do) interpret music in different ways,

Andreas P. Braun, Hugo Fortin, Daniel Lopez Garcia, Roberto Villaflor Loyola

We study M-Theory solutions with $G$-flux on the Fermat sextic Calabi-Yau fourfold, focussing on the relationship between the number of stabilized complex structure moduli and the tadpole contribution of the flux. We use two alternative approaches to define the fluxes: algebraic cycles and (appropriately quantized) Griffiths residues. In both cases, we colle

Dhruv Ramu, Rishab Jain, Aditya Jain

The growing popularity of generative artificial intelligence (AI) chatbots such as ChatGPT is having transformative effects on social media. As the prevalence of AI-generated content grows, concerns have been raised regarding privacy and misinformation online. Among social media platforms, Discord enables AI integrations -- making their primarily "Generation

Samira Kamali Poorazad, Chafika Benzaıd, Tarik Taleb

The industrial Internet of Things (IIoT) involves the integration of Internet of Things (IoT) technologies into industrial settings. However, given the high sensitivity of the industry to the security of industrial control system networks and IIoT, the use of software-defined networking (SDN) technology can provide improved security and automation of communi

Mikołaj Krakowski, Alicja Kwaśny, Grzegorz Soboń

We report our investigation on ultrashort laser pulse optimization using an AI algorithm in a system consisting of a mode-locked oscillator, a spectral phase shaper, and a highly nonlinear amplifier. We analyzed the performance of the pulse optimization process as a function of two main parameters: the resolution of spectral phase modulation and the number o

Silvan David Peter

Symbolic Music Alignment is the process of matching performed MIDI notes to corresponding score notes. In this paper, we introduce a reinforcement learning (RL)-based online symbolic music alignment technique. The RL agent - an attention-based neural network - iteratively estimates the current score position from local score and performance contexts. For thi

Evangelos Bazinas, Andreas Gregoriades, Marios Raspopoulos, Michael Georgiades

Intelligent transportation systems (ITS) have been developed to improve traffic flow, efficiency, and safety in transportation. Technological advancements in communication such as the Vehicle-to-Everything (V2X), Vehicle-to-Vehicle (V2V) and Vehicle-to Infrastructure (V2I) enable the real-time exchange of information between vehicles and other entities on th

Shengbing Deng, Xingliang Tian

The usual Sobolev inequality in $\mathbb{R}^N$, asserts that $\|\nabla u\|_{L^p(\mathbb{R}^N)} \geq \mathcal{S}\|u\|_{L^{p^*}(\mathbb{R}^N)}$ for $1<p<N$ and $p^*=\frac{pN}{N-p}$, with $\mathcal{S}$ being the sharp constant. Based on a recent work of Figalli and Zhang [Duke Math. J., 2022], a weak norm remainder term of Sobolev inequality in a subdomain $\Om

Ani Vanyan, Alvard Barseghyan, Hakob Tamazyan, Vahan Huroyan

In this paper, we present a comparative analysis of various self-supervised Vision Transformers (ViTs), focusing on their local representative power. Inspired by large language models, we examine the abilities of ViTs to perform various computer vision tasks with little to no fine-tuning. We design evaluation framework to analyze the quality of local, i.e.\

Emiliano Torti

In this article, we prove the existence of rigid analytic families of $G$-stable lattices with locally constant reductions inside families of representations of a topologically compact group $G$, extending a result of Hellman obtained in the semi-simple residual case. Implementing this generalization in the context of Galois representations, we prove a local

Jooyoung Lee, Zhibing He, Charlotte Roscoe, Peter James

In environmental health research, it is of interest to understand the effect of the neighborhood environment on health. Researchers have shown a protective association between green space around a person's residential address and depression outcomes. In measuring exposure to green space, distance buffers are often used. However, buffer distances differ acros

Hyeonjae Jeon, Junghyun Seo, Taesoo Kim, Sungho Son

Autonomous driving technology nowadays targets to level 4 or beyond, but the researchers are faced with some limitations for developing reliable driving algorithms in diverse challenges. To promote the autonomous vehicles to spread widely, it is important to address safety issues on this technology. Among various safety concerns, the sensor blockage problem

Lorène Champougny, Vincent Bertin, Jacco H. Snoeijer, Javier Rodríguez-Rodríguez

We present a surface analog to a dripping faucet, where a viscous liquid slides down an immiscible meniscus. Periodic pinch-off of the dripping filament is observed, generating a succession of monodisperse floating lenses. We show that this interfacial dripping faucet can be described analogously to its single-phase counterpart, replacing surface tension by

L. S. Pilyugin, G. Tautvaisiene

We considered two sequences of spiral galaxies with different shapes of the radial gas-phase oxygen abundance distributions from the galaxies in the MaNGA survey: (1) Galaxies in which the gradient is well approximated by a single linear relation across the whole disc, that is, galaxies with an S (slope) gradients, (2) galaxies in which the metallicity in th

Andrey Kudinov, Ilya Shapirovsky

We study the finite model property of subframe logics with expressible transitive reflexive closure modality. For $m>0$, let $\mathrm{L}_m$ be the logic defined by axiom $\lozenge^{m+1} p\to \lozenge p\vee p$. We construct filtrations for the logics $\mathrm{L}_m$. It follows that these logics and their tense counterparts have the finite model property. Then

Hao Liu, Jun Liu, Raymond H. Chan, Xue-Cheng Tai

In this study, our goal is to integrate classical mathematical models with deep neural networks by introducing two novel deep neural network models for image segmentation known as Double-well Nets. Drawing inspirations from the Potts model, our models leverage neural networks to represent a region force functional. We extend the well-know MBO (Merriman-Bence

Jeremy Miller, Benjamin Leather, Adam Pound, Niels Warburton

Second-order gravitational self-force theory has recently led to the breakthrough calculation of ``first post-adiabatic'' (1PA) compact-binary waveforms [Phys. Rev. Lett. 130, 241402 (2023)]. The computations underlying those waveforms depend on a method of solving the perturbative second-order Einstein equation on a Schwarzschild background in the Fourier d

Ziyi Guan, Yunqi Huang, Penghui Yao, Zekun Ye

This paper gives a nearly tight characterization of the quantum communication complexity of the permutation-invariant Boolean functions. With such a characterization, we show that the quantum and randomized communication complexity of the permutation-invariant Boolean functions are quadratically equivalent (up to a logarithmic factor). Our results extend a r

Satoshi Osawa, Hideo Takaoka

We prove that the Zakharov-Kuznetsov equation on cylindrical spaces is globally well-posed below the energy norm. As is known, local well-posedness below energy space was obtained by the first author. We adapt I-method to extend the solutions globally in time. Using modified energies, we obtain the polynomial bounds on the $H^s$ growth for the global solutio

A. Hammad, S. Moretti, M. Nojiri

We deploy an advanced Machine Learning (ML) environment, leveraging a multi-scale cross-attention encoder for event classification, towards the identification of the $gg\to H\to hh\to b\bar b b\bar b$ process at the High Luminosity Large Hadron Collider (HL-LHC), where $h$ is the discovered Standard Model (SM)-like Higgs boson and $H$ a heavier version of it

Parthasarathy P D, Swaroop Joshi

A UserWay study in 2021 indicates that an annual global e-commerce revenue loss of approximately $16 billion can be attributed to inaccessible websites and applications. According to the 2023 WebAIM study, only 3.7% of the world's top one million website homepages are fully accessible. This shows that many software developers use poor coding practices that d

Parthasarathy PD, Swaroop Joshi

Despite recent initiatives aimed at improving accessibility, the field of digital accessibility remains markedly behind contemporary advancements in the software industry as a large number of real world software and web applications continue to fall short of accessibility requirements. A persisting skills deficit within the existing technology workforce has

Nikhil Sardana, Jacob Portes, Sasha Doubov, Jonathan Frankle

Large language model (LLM) scaling laws are empirical formulas that estimate changes in model quality as a result of increasing parameter count and training data. However, these formulas, including the popular Deepmind Chinchilla scaling laws, neglect to include the cost of inference. We modify the Chinchilla scaling laws to calculate the optimal LLM paramet

Wan-Duo Kurt Ma, J. P. Lewis, W. Bastiaan Kleijn

Within recent approaches to text-to-video (T2V) generation, achieving controllability in the synthesized video is often a challenge. Typically, this issue is addressed by providing low-level per-frame guidance in the form of edge maps, depth maps, or an existing video to be altered. However, the process of obtaining such guidance can be labor-intensive. This

Abdelhamid Salem, Kai-Kit Wong, Chan-Byoung Chae, Yangyang Zhang

In contrast to conventional reconfigurable intelligent surface (RIS), simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) has been proposed recently to enlarge the serving area from 180o to 360o coverage. This work considers the performance of a STAR-RIS aided full-duplex (FD) non-orthogonal multiple access (NOMA) communica

Riju Dutta, Prateek Sharma, Kartick C. Sarkar, James M. Stone

Accreting supermassive black holes (SMBHs) frequently power jets that interact with the interstellar/circumgalactic medium (ISM/CGM), regulating star-formation in the galaxy. Highly supersonic jets launched by active galactic nuclei (AGN) power a cocoon that confines them and shocks the ambient medium. We build upon the models of narrow conical jets interact

Chenxi Zhao, Min Sheng, Junyu Liu, Tianshu Chu

The limited energy and computing resources of unmanned aerial vehicles (UAVs) hinder the application of aerial artificial intelligence. The utilization of split inference in UAVs garners significant attention due to its effectiveness in mitigating computing and energy requirements. However, achieving energy-efficient split inference in UAVs remains complex c

Dexin Wang, Ahmad Bazzi, Marwa Chafii

The following paper proposes a new target localization system design using an architecture based on reconfigurable intelligent surfaces (RISs) and passive radars (PRs) for integrated sensing and communications systems. The preamble of the communication signal is exploited in order to perform target sensing tasks, which involve detection and localization. The

David López-Pérez, Antonio De Domenico, Nicola Piovesan, Merouane Debbah

The energy consumption of mobile networks poses a critical challenge. Mitigating this concern necessitates the deployment and optimization of network energy-saving solutions, such as carrier shutdown, to dynamically manage network resources. Traditional optimization approaches encounter complexity due to factors like the large number of cells, stochastic tra

Jian Xu, De-Wei Han, Kang Li, Jun-Jie Li

The fisheye camera, with its unique wide field of view and other characteristics, has found extensive applications in various fields. However, the fisheye camera suffers from significant distortion compared to pinhole cameras, resulting in distorted images of captured objects. Fish-eye camera distortion is a common issue in digital image processing, requirin

Narcisse G. Bell Bogmis, Calvin Tcheka, Guy R. Biyogmam

In this paper, we define on one hand, the notions of characteristics as well as central characteristics ideals of a given Leibniz algebra g and provide a necessary condition under which for two given subalgebras J and K of g such that, J IS a a non empty subset of K. J is a central characteristics two-sided ideal of K. On the other hand, we introduce the cla

Kévin Le Balc'h, Diego A. Souza

In this article, we study a quantitative form of the Landis conjecture on exponential decay for real-valued solutions to second order elliptic equations with variable coefficients in the plane. In particular, we prove the following qualitative form of Landis conjecture, for $W_1, W_2 \in L^{\infty}(\mathbb R^2;\mathbb R^2)$, $V \in L^{\infty}(\mathbb R^2;\ma

Moien Rangzan, Sara Attarchi, Richard Gloaguen, Seyed Kazem Alavipanah

In contrast to the well-investigated field of SAR-to-Optical translation, this study explores the lesser-investigated domain of Optical-to-SAR translation, a challenging field due to the ill-posed nature of this translation. The complexity arises as a single optical data can have multiple SAR representations based on the SAR viewing geometry. We propose a no

Lucas Chesnel, Sergei A. Nazarov

We are interested in the lower part of the spectrum of the Dirichlet Laplacian $A^\varepsilon$ in a thin waveguide $\Pi^\varepsilon$ obtained by repeating periodically a pattern, itself constructed by scaling an inner field geometry $\Omega$ by a small factor $\varepsilon>0$. The Floquet-Bloch theory ensures that the spectrum of $A^\varepsilon$ has a band-ga

Or Berman, Adam Goldbraikh, Shlomi Laufer

The ability to locate and classify action segments in long untrimmed video is of particular interest to many applications such as autonomous cars, robotics and healthcare applications. Today, the most popular pipeline for action segmentation is composed of encoding the frames into feature vectors, which are then processed by a temporal model for segmentation

Peiwen Yuan, Shaoxiong Feng, Yiwei Li, Xinglin Wang

Significant progress has been made in automatic text evaluation with the introduction of large language models (LLMs) as evaluators. However, current sample-wise evaluation paradigm suffers from the following issues: (1) Sensitive to prompt design; (2) Poor resistance to noise; (3) Inferior ensemble performance with static reference. Inspired by the fact tha